A novel skin cancer detection model using modified finch deep CNN classifier model

Skin cancer is one of the most life-threatening diseases caused by the abnormal growth of the skin cells, when exposed to ultraviolet radiation. Early detection seems to be more crucial for reducing aberrant cell proliferation because the mortality rate is rapidly rising. Although multiple researches are available based on the skin cancer detection, there still exists challenges in improving the accuracy, reducing the computational time and so on. In this research, a novel skin cancer detection is performed using a modified falcon finch deep Convolutional neural network classifier (Modified Falcon finch deep CNN) that efficiently detects the disease with higher efficiency. The usage of modified falcon finch deep CNN classifier effectively analyzed the information relevant to the skin cancer and the errors are also minimized. The inclusion of the falcon finch optimization in the deep CNN classifier is necessary for efficient parameter tuning. This tuning enhanced the robustness and boosted the convergence of the classifier that detects the skin cancer in less stipulated time. The modified falcon finch deep CNN classifier achieved accuracy, sensitivity, and specificity values of 93.59%, 92.14%, and 95.22% regarding k-fold and 96.52%, 96.69%, and 96.54% regarding training percentage, proving more effective than literary works.

Exploring the ecological meanings of temperature sensitivity of ecosystem respiration from different methods

Temperature sensitivity (Q10) of ecosystem respiration (Re) is a critical parameter for predicting global terrestrial carbon dynamics and its response to climate warming. However, the determination of Q10 has been controversial. In this study, we scrutinized the underpinnings of three mainstream methods to reveal their relationships in estimating Q10 for Re in the Heihe River Basin, northwest China. Specifically, these methods are Q10 estimated from the long-term method (Q10_long), short-term method (Q10_short), and the low-frequency (Q10_lf) and high-frequency (Q10_hf) signals decomposed by the singular spectrum analysis (SSA) method. We found that: 1) Q10_lf and Q10_long are affected by the confounding effects caused by non-temperature factors, and are 1.8 ± 0.3 and 1.7 ± 0.3, respectively. 2) The high-frequency signals of the SSA method and short-term method have consistent roles in removing the confounding effects. Both Q10_short and Q10_hf reflect the actual response of respiration to temperature. 3) Overall, Q10_long has a larger variability (1.7 ± 0.3) across different biomes, whereas Q10_short and Q10_hf show convergence (1.4 ± 0.2 and 1.3 ± 0.1, respectively). These results highlight the fact that Q10 can be overestimated by the long-term method, whereas the short-term method and high-frequency signals decomposed by the SSA method can obtain closer and convergent values after removing the confounding effects driven by non-temperature factors. Therefore, it is recommended to use the Q10 value estimated by the short-term method or high-frequency signals decomposed by the SSA method to predict carbon dynamics and its response to global warming in Earth system models.

DCDLN: A densely connected convolutional dynamic learning network for malaria disease diagnosis

Malaria is a significant health concern worldwide, particularly in Africa where its prevalence is still alarmingly high. Using artificial intelligence algorithms to diagnose cells with malaria provides great convenience for clinicians. In this paper, a densely connected convolutional dynamic learning network (DCDLN) is proposed for the diagnosis of malaria disease. Specifically, after data processing and partitioning of the dataset, the densely connected block is trained as a feature extractor. To classify the features extracted by the feature extractor, a classifier based on a dynamic learning network is proposed in this paper. Based on experimental results, the proposed DCDLN method demonstrates a diagnostic accuracy rate of 97.23%, surpassing the diagnostic performance than existing advanced methods on an open malaria cell dataset. This accurate diagnostic effect provides convincing evidence for clinicians to make a correct diagnosis. In addition, to validate the superiority and generalization capability of the DCDLN algorithm, we also applied the algorithm to the skin cancer and garbage classification datasets. DCDLN achieved good results on these datasets as well, demonstrating that the DCDLN algorithm possesses superiority and strong generalization performance.

Investigations into the anatomical location, physiological function, clinical implications, and significance of the nucleus of Perlia

BACKGROUND

The article discusses the investigations into the nucleus of Perlia (NP), a spindle-shaped nucleus located in the dorsal aspect of the oculomotor complex. However, there is still debate over its exact location and function, with conflicting findings in nonhuman primates. Therefore, the current study aimed the describe the location, function, clinical and surgical implications of NP.

METHODS

A systematic review was conducted to identify studies related to the following MeSH terms: "perlia nucleus" OR "nucleus of "perlia" OR "convergence nucleus" OR "nucleus of convergence" OR "Perlia's nucleus". The search was conducted until September 2022.

RESULTS

The location of the NP has been consistently reported in various studies, with most describing it as situated ventral to the Edinger-Westphal nucleus (EW) and dorsomedial to the oculomotor complex. The incidence of the NP in humans has been reported to range from 9 to 40%. In primates, it was observed to be absent in 77% of midbrains, while well developed in 9%. It is also noted that the NP is not a single nucleus, but rather a group of nuclei that are interconnected and involved in the coordination of eye movements that contain parasympathetic neurons.

CONCLUSIONS

The study of the NP holds clinical implications for understanding the neural mechanisms underlying the irregularities in the pupillary light reflex, such as anisocoria or abnormal responses to light, diagnosis, and treatment of neurological disorders like Horner's syndrome, and management of eye movement disorders including one-and-a-half syndrome, vertical gaze palsy, skew deviation and ptosis. The current study also highlighted the limitations of previous studies, including variations in the reported prevalence of the NP, limitations of the histological techniques, and inconsistent findings across human and animal studies.

On random conformity bias in cultural transmission of polychotomous traits

Mathematical models of conformity and anti-conformity have commonly included a set of simplifying assumptions. For example, (1) there are m=2 cultural variants in the population, (2) naive individuals observe the cultural variants of n=3 adult "role models," and (3) individuals' levels of conformity or anti-conformity do not change over time. Three recent theoretical papers have shown that departures from each of these assumptions can produce new population dynamics. Here, we explore cases in which multiple, or all, of these assumptions are violated simultaneously: namely, in a population with m variants of a trait where conformity (or anti-conformity) occurs with respect to n role models, we study a model in which the conformity rates at each generation are random variables that are independent of the variant frequencies at that generation. For this model a class of symmetric constant equilibria exist, and it is possible that all of these equilibria are simultaneously stochastically locally stable. In such cases, the effect of initial conditions on subsequent evolutionary trajectories becomes very complicated.

Abnormal occipital and frontal activity during voluntary convergence in intermittent exotropia: A task-fMRI study

Intermittent exotropia (IXT) is characterized by intermittently outward deviation of the eye and involved with vergence dysfunction. This study aimed to investigate the brain areas related to voluntary convergence and cortical activation changes between IXT patients and normal subjects. A total of 21 subjects, including 11 IXT patients and 10 age- and sex-matched normal subjects, were recruited for this study. A voluntary convergence task was employed, with changes in brain function measured by functional magnetic resonance imaging (fMRI). Correlations between cortical activation and clinical measurements were conducted by Pearson's correlation analysis. fMRI results showed that during voluntary convergence, the medial frontal gyrus (MFG) and bilateral occipital cortex were activated in the normal group, whereas only activation of the occipital cortex in IXT patients. Compared with the normal, IXT patients showed hypo-activation of both the MFG and cuneus during the task. The activation of MFG was negatively correlated to the duration of IXT. This study demonstrates that both MFG and occipital cortex may participate in voluntary convergence in normal subjects, while IXT patients have an aberrant cortical function of the MFG and cuneus, and the duration of IXT likely influences the severity of MFG. These findings may provide valuable insights for understanding the relationship between convergence and IXT.

Carbapenem-resistant hypervirulent ST23 Klebsiella pneumoniae with a highly transmissible dual-carbapenemase plasmid in Chile

BACKGROUND

The convergence of hypervirulence and carbapenem resistance in the bacterial pathogen Klebsiella pneumoniae represents a critical global health concern. Hypervirulent K. pneumoniae (hvKp) strains, frequently from sequence type 23 (ST23) and having a K1 capsule, have been associated with severe community-acquired invasive infections. Although hvKp were initially restricted to Southeast Asia and primarily antibiotic-sensitive, carbapenem-resistant hvKp infections are reported worldwide. Here, within the carbapenemase production Enterobacterales surveillance system headed by the Chilean Public Health Institute, we describe the isolation in Chile of a high-risk ST23 dual-carbapenemase-producing hvKp strain, which carbapenemase genes are encoded in a single conjugative plasmid.

RESULTS

Phenotypic and molecular tests of this strain revealed an extensive resistance to at least 15 antibiotic classes and the production of KPC-2 and VIM-1 carbapenemases. Unexpectedly, this isolate lacked hypermucoviscosity, challenging this commonly used hvKp identification criteria. Complete genome sequencing and analysis confirmed the K1 capsular type, the KpVP-1 virulence plasmid, and the GIE492 and ICEKp10 genomic islands carrying virulence factors strongly associated with hvKp. Although this isolate belonged to the globally disseminated hvKp clonal group CG23-I, it is unique, as it formed a clade apart from a previously reported Chilean ST23 hvKp isolate and acquired an IncN KPC-2 plasmid highly disseminated in South America (absent in other hvKp genomes), but now including a class-I integron carrying blaVIM-1 and other resistance genes. Notably, this isolate was able to conjugate the double carbapenemase plasmid to an E. coli recipient, conferring resistance to 1st -5th generation cephalosporins (including combinations with beta-lactamase inhibitors), penicillins, monobactams, and carbapenems.

CONCLUSIONS

We reported the isolation in Chile of high-risk carbapenem-resistant hvKp carrying a highly transmissible conjugative plasmid encoding KPC-2 and VIM-1 carbapenemases, conferring resistance to most beta-lactams. Furthermore, the lack of hypermucoviscosity argues against this trait as a reliable hvKp marker. These findings highlight the rapid evolution towards multi-drug resistance of hvKp in Chile and globally, as well as the importance of conjugative plasmids and other mobile genetic elements in this convergence. In this regard, genomic approaches provide valuable support to monitor and obtain essential information on these priority pathogens and mobile elements.

Switching and non-switching dead-beat sliding mode control with monotonic convergence

Performance requirements necessitate control designs that assure not only transient response specifications but also steady-state accuracy. Monotonic convergence of the tracking error is crucial for an efficient control design to prevent the performance degradation caused by overshooting. This needs a balanced consideration of both reaching conditions and the monotonic convergence, in the context of sliding mode control. In this paper, the dynamic behaviour of the dead-beat sliding mode control is characterized and the signum function is replaced by employing a non-switching one, in order to reduce chattering. The paper conducts a thorough analysis of monotonic convergence of both the switching and the non-switching error dynamics. By deriving the conditions for monotonic convergence, the control parameters can be strategically chosen to ensure monotonic convergence of the tracking error. Numerical and experimental results are presented to validate effectiveness of the proposed control scheme, which evaluate the tracking performance achieved by both the switching and the non-switching control methods.

Asia Core Dossier: Standardizing CMC Requirement to Facilitate Best Case Submissions in Asia

When the regulatory requirements are converged or harmonized, the country-specific variance of countries is often reduced or omitted, and this facilitates the possibility of preparing a core dossier that caters to multiple countries. When such options of a core dossier are acceptable to multiple countries, the resource required to prepare the dossier and the time taken to prepare it is also reduced, thus eliminating resource constraints in supporting dossier planning and preparation and indirectly facilitating earlier submission in countries. In this paper, the authors have illustrated a process applied to standardize the dossier requirements amongst selected countries in Asia, producing an output of a core dossier that applies to four submission types amongst these countries. The core dossier adopts the International Council for Harmonization-Common Technical Dossier format as a reference. Main focus is the standardization of format and requirements within the Module 3 or Chemistry Manufacturing Controls sections of the dossier, which from the authors' organizational experience usually notes a higher variances and country-specific elements. Development of the dossier standardization process is due to an internal hurdle within the authors' organization, where global resource constraints and prioritizations of dossier preparation and compliance review process needed to be improved to facilitate earlier or near-simultaneously submissions in the majority of the Asia countries. The paper demonstrates an assessment of the dossier components and standardization to assemble a fit-for-purpose core dossier termed 'Asia Core Dossier' (ACD). ACD has been successfully implemented within the authors' organization to reduce country-specific requirements and facilitate earlier (fit for strategy) submissions in the selected Asia countries. The paper also discusses the tangible benefits of the authors' experiences from utilizing the ACD. Regulatory professionals in different organizations could reference the ACD as a template for preparing a simplified and efficient dossier and as a relevant component of Good Submission Practice (GSubP).

A multi-detector comparison to determine convergence of measured relative output factors for small field dosimetry

The TRS-483 Code of Practice (CoP) provides generic relative output correction factors, [Formula: see text], for a range of detectors and beam energies as used in small field dosimetry. In this work, the convergence of the relative output factors (ROFs) for 6 MV X-ray beams with and without flattening filters was investigated under different combinations of beam collimation and published detector correction factors. The SFD, PFD and CC04 (IBA) were used to measure ROFs of a TrueBeam STx linear accelerator with small fields collimated by the high-definition MLC, which has 2.5 and 5.0 mm projected leaves. Two configurations were used for the collimators: (1) fixed jaws at 10 × 10 cm2 and (2) with a 2 mm offset from the MLC edge, in line with the recommended geometry from IROC-H as part of their auditing program and published dataset. The [Formula: see text] factors for the three detectors were taken from the TRS483 CoP and other published works. The average differences of ROFs measured by detectors under MLC fields with fixed jaws and with 2 mm jaws offset for the 6 MV-WFF beam are 1.4% and 1.9%, respectively. Similarly, they are 2.3% and 2.4% for the 6MV-FFF beam. The relative differences between the detector-average ROFs and the corresponding IROC-H dataset are 2.0% and 3.1% for the 6 MV-WFF beam, while they are 2.4% and 3.2% for the 6MV-FFF beam at the smallest available field size of 2 × 2 cm2. For smaller field sizes, the average ROFs of the three detectors and corresponding results from Akino and Dufreneix showed the largest difference to be 6.6% and 6.2% under the 6 MV-WFF beam, while they are 3.4% and 3.6% under the 6 MV-WFF beam at the smallest field size of 0.5 × 0.5 cm2. Some well-published specific output correction factors for different small field detector types give better convergence in the calculation of the relative output factor in comparison with the generic data provided by the TRS-483 CoP. Relative output factor measurements should be performed as close as possible to the clinical settings including a combination of collimation systems, beam types and using at least three different types of small field detector for more accurate computation of the treatment planning system. The IROC-H dataset is not available for field size smaller than 2 × 2 cm2 for double checks and so that user should carefully check with other publications with the same setting.

Brief Report: Convergence and Discrepancy Between Self- and Informant-Reported Depressive Symptoms in Young Autistic Adults

PURPOSE

Autistic individuals exhibit elevated rates of depression; however, assessment is complicated by clinical presentations and limited validation in this population. Recent work has demonstrated the utility of the Beck Depression Inventory (BDI-II) in screening for depression in ASD. The current study extends this work by examining the convergence and divergence of self- and informant-reported depression in autistic (n = 258) and non-autistic (n = 255) young adults.

METHODS

Participants completed the BDI-II as a self-report measure of depression; informants completed the Achenbach Adult Behavior Checklist. Analyses probed for between-group differences in rates of depression symptoms, convergence between self- and informant-reported depression, and discrepancy between self- and informant-reported depression.

RESULTS

Results indicated significantly higher rates of depressive symptoms in the autistic group. Convergence was significant in both groups, with significantly greater agreement in the autistic group. There was differential divergence, with the autistic group reporting significantly lower scores relative to informants, and the non-autistic group reporting significantly higher scores relative to informants.

CONCLUSIONS

Consistent with prior reports, results suggest that depression rates are elevated in autism. Additionally, while the BDI-II may be adequate for screening depressive symptoms in speaking autistic young adults, eliciting information from a close adult informant provides valuable diagnostic information, due to clinically critical concerns about underreporting in this population. Although controlled in analyses, between-group differences in gender, age, race, and informant identity, and a predominantly White and non-Latinx sample, limit the generalizability of these results.

Dynamic distribution, regional differences and convergence of health workforce allocation in township health centers in China

This study evaluated the dynamic distribution, regional differences, and convergence of health workforce allocation in Township Health Centers in China during 2011-2020 using data obtained from the China Health Statistics Yearbook (2012-2021). The Gini coefficient and kernel density estimation were chosen to examine the dynamic distribution and regional differences in health workforce allocation in Township Health Centers in China and their components. σ convergence and β convergence were used to investigate the change trend of health workforce allocation in Township Health Centers. The results show that between 2011 and 2020, the number of licensed doctors and registered nurses per thousand population in Township Health Centers both increased largely and regional disparities still exist. In 2020, the largest differences in the density of licensed doctors and registered nurses were found in the eastern and central regions, respectively, and the intensity of trans-variation contributed the most to the overall disparities. The allocation of licensed doctors and registered nurses both exhibited σ convergence, absolute and conditional β convergence, indicating that the regional differences in health workforce in THCs among provinces will decrease. The growth of healthcare workforce was positively impacted by the urbanization rate, growth rate of government health expenditures and growth domestic product per capita, but negatively impacted by population density in rural areas and fiscal self-sufficiency.

Relationship between floating marine debris accumulation and coastal fronts in the Northeast coast of the USA

Floating marine debris (FMD) is one of the world's most concerning issues due to its potential impact on biodiversity, communities, and ecosystem services. FMD transport and concentrations are driven by fronts, generated by oceanographic processes, and the accumulation of FMD has been reported in gyres, eddies, tidal fronts, salinity fronts, and coastal fronts. This study explores the relationship between fronts and FMD accumulation in the Gulf of Maine (GoM) and the surrounding coastal areas (USA). Frontal edge detection algorithms were applied to sea surface temperature (SST) imagery from the Moderate-resolution Imaging Spectroradiometer (MODIS) between 2002 and 2012. Frontal location is spatially correlated with FMD concentrations collected by the Sea Education Association. Higher concentrations of FMD are associated with frontal frequencies (FF) of 5-10 %. FMD is trapped between fronts and the coastline in accumulation zones. These results highlight the need to consider coastal FMD hotspots, given these are areas of high biodiversity value.

The Effect of Cycloplegia on Ocular Alignment and AC/A Ratio

Purpose

The present study sets out to investigate the effect of cyclopentolate-induced cycloplegia on distance and near deviation and the accommodative convergence/accommodation (AC/A) ratio.

Methods

This prospective study was performed on 30 subjects. The inclusion criteria included a lack of any active ocular pathology and systemic diseases, no history of ocular surgery, and nonuse of various medications. Refraction, near and distance deviation were measured for all subjects, and the same examinations were repeated after the administration of two drops of cyclopentolate 1% to both eyes.

Results

The obtained data from 30 subjects, including 19 males, with a mean age of 22.53 ± 1.74 years were analyzed. The mean ± SD of near deviation in dry and cycloplegic conditions were -6.9 ± 8.1 and +6.4 ± 9.1 prism diopters, respectively, which were statistically significant (P < 0.001). Distance deviation in cycloplegic conditions demonstrated an average difference of 0.8 prism diopters, compared to dry conditions (P < 0.001). AC/A ratios were 4.7 ± 2.5 and 9.7 ± 3.9 (Δ/D) in non-cycloplegic and cycloplegic conditions, respectively, which was a statistically significant difference (P < 0.001). The multiple regression indicated that among all under study variables, refraction (B coefficient: -2.4; P < 0.001) and near pre-cycloplegic deviation (B coefficient: 0.56; P < 0.001) were significantly associated with post-cycloplegic near deviation.

Conclusion

The results of this study indicated that cycloplegia causes a considerable esophoric shift in near deviation and a negligible esophoric shift in distance deviation. As a result, the AC/A ratio demonstrated a significant increase due to unequal changes in near and distance deviation.

The green productivity of broiler production in China: Considering the resource utilization of manure

Resource constraints and environmental challenges have emerged as serious impediments to the sustainable development of China's broiler industry, with potentially adverse consequences. The pursuit of sustainable development in China's broiler industry is predicated on significant reductions in manure and pollutant emissions from broiler farming. This study utilizes the slacks-based model and the global Malmquist-Luenberger index to calculate the green total factor productivity of broiler breeding across various provinces and scales from 2005 to 2020 within a joint production framework of considering undesirable outputs and desirable outputs. Fluctuations in economic distribution of broiler breeding are characterized using the kernel density estimation, and a convergence analysis is performed via absolute and conditional β convergence methods. The results revealed an overall upward trend in China's broiler farming green total factor productivity from 2005 to 2020, corresponding to green total factor productivity in small-, medium-, and large-scale broiler breeding were 1.015, 1.017, and 1.009, respectively. The kernel density curve implies a narrowing trend in the discrepancy of green total factor productivity levels among provinces in broiler breeding of varying scales. For all scales, broiler breeding's green total factor productivity demonstrates considerable conditional and absolute β convergence. Therefore, improving the efficiency of broiler breeding while addressing externalities requires the cultivation of broilers at different scales across diverse regions, coupled with an increased focus on improving the utility efficiency of broiler waste fertilization.

A survey of methods for handling initial state shifts in iterative learning control

This paper introduces three types of controllers: a PID-type iterative learning controller, an adaptive iterative learning controller, and an optimal iterative learning controller, and reviews the history and research status of initial shifts rectifying algorithms. Initial state shifts have attracted research attention because they affect both the tracking performance and system stability. This study focuses on the current common initial shifts rectifying methods and analyzes the underlying mechanism in detail. To verify the effectiveness of the presented initial shifts rectifying algorithms, we simulated those using ideal first- and second-order systems. Finally, directions for the future development of iterative learning control (ILC) and some challenging topics related to initial shifts rectifying for ILC are presented. This article aims to introduce recent developments and advances in initial shifts rectifying algorithms and discuss the directions for their further exploration.

BERTs of a feather: Studying inter- and intra-group communication via information theory and language models

When communicating, individuals alter their language to fulfill a myriad of social functions. In particular, linguistic convergence and divergence are fundamental in establishing and maintaining group identity. Quantitatively characterizing linguistic convergence is important when testing hypotheses surrounding language, including interpersonal and group communication. We provide a quantitative interpretation of linguistic convergence grounded in information theory. We then construct a computational model, built on top of a neural network model of language, that can be deployed to measure and test hypotheses about linguistic convergence in "big data." We demonstrate the utility of our convergence measurement in two case studies: (1) showing that our measurement is indeed sensitive to linguistic convergence across turns in dyadic conversation, and (2) showing that our convergence measurement is sensitive to social factors that mediate convergence in Internet-based communities (specifically, r/MensRights and r/MensLib). Our measurement also captures differences in which social factors influence web-based communities. We conclude by discussing methodological and theoretical implications of this semantic convergence analysis.

Does reflective equilibrium help us converge?

I address the worry that reflective equilibrium is too weak as an account of justification because it fails to let differing views converge. I take up informal aspects of convergence and operationalise them in a formal model of reflective equilibrium. This allows for exploration by the means of computer simulation. Findings show that the formal model does not yield unique outputs, but still boosts agreement. I conclude from this that reflective equilibrium is best seen as a pluralist account of justification that cannot be accused of resulting in an "anything goes" relativism.

Green total-factor energy efficiency and its convergence of industrial sub-sectors in China

Existing literature ignores to consider multiple types of pollutants when analyzing energy efficiency and its convergence. Under this background, using SuperSBM-GML model, the improved entropy method, and convergence model, this paper calculates the green total-factor energy efficiency and its evolution trend of 35 China's industrial sub-sectors considering multiple pollutants, and analyzes its convergence. The results indicate that the average score of industrial green total-factor energy efficiency is low, and there are significant differences among sub-sectors: "Utilization of waste resources" is the highest, while "Manufacture of paper and paper products" is the lowest. The green total-factor energy efficiency shows an overall upward trend from 2006 to 2021, the main driving force comes from technological progress, but numerous sub-sectors have not sufficiently caught up with existing cutting-edge technologies. Specifically, the growth rate of green total-factor energy efficiency in high-energy-consumption sub-sectors is higher than low-to-medium-energy-consumption sub-sectors. There are both σ-convergence and β-convergence in low-to-medium-energy-consumption group, indicating that development of sub-sectors is stable and outstanding. Nevertheless, the high-energy-consumption group only exhibits conditional β-convergence, revealing an imbalance in energy efficiency development. Consequently, formulating the benchmark level of energy efficiency and developing energy efficiency "leader" system are suggested for low-to-medium and high-energy-consumption sub-sectors, respectively.

Dying together: A convergence analysis of fatalities during COVID-19

Governments implemented countermeasures to mitigate the spread of the COVID-19 virus. This had a severe effect on the economy. We examine convergence patterns in the evolution of COVID-19 deaths across countries. We aim to investigate whether countries that implemented different measures managed to limit the number of COVID-19 deaths. We extend the most recent macro-growth convergence methodology to examine convergence of COVID-19 deaths. We combine a long memory stationarity framework with the maximal clique algorithm. This provides a rich and flexible club formation strategy that goes beyond the stationary/non stationary approach adopted in the previous literature. Our results suggest that strict measures (even belated) or an aggressive vaccination scheme can confine the spread of the disease while maintaining the strictness of the measures steady can lead to a burst of the virus. Finally, we observe that fiscal measures did not have an effect on the containment of the virus.

Club convergence analysis of fossil fuels material footprint at the global level

Material footprint is vital for playing a role in increasing the pace of climate change and the sustainability of development efforts. Fossil fuels material footprint (FFMF) remains a critical indicator of environment-friendly economic development. Fossil fuels have also retained their dominance as prominent drivers of global growth since the Industrial Revolution. FFMF levels show considerable variations in economic growth worldwide as awareness of sustainability and climate change propagates. Although biomass/carbon emission convergence have been discussed extensively in the existing literature, FFMF convergence is still scanty despite its vital role in climate change. Hence, this study adds to the existing literature by examining the convergence of FFMF for 154 countries for the period from 1970 to 2019 using club convergence analysis. The results show that FFMF converges to a single steady state, stating a symmetric decline in FFMF growth. Further, the findings from sigma and beta tests are consistent with the main results. Thus, the demonstrated convergence of FFMF directs that global efforts regarding FFMF control should be continued. Moreover, future climate change policies should also be formulated to enhance the awareness of FFMF and long-term sustainability.

Convergence analysis on a tracking differentiator used in active disturbance rejection control

This paper presents convergence analysis for a tracking differentiator of an active disturbance rejection control method which is widely applied but lacks theoretical analysis. Since a nonlinear piecewise function is used in the tracking differentiator, the convergence analysis is difficult for tracking errors. Convergence proof processes of the tracking differentiator are divided into three situations based on the nonlinear piecewise function. Tracking errors of the tracking differentiator are proved to be uniformly ultimately bounded considering three situations, and relationships between upper bounds of tracking errors and adjustment parameters are founded by a Lyapunov approach, which provides a basis for parameters adjustment. Finally, simulation and experiment results verify the effectiveness of the proposed convergence analysis.

Research on the dynamic evolution and convergence of collaborative capacity of pollution control and carbon reduction: from the perspective of whole-process governance

Under the strategic goals of achieving peak carbon neutrality, deepening the battle against pollution, and building a beautiful China, improving the collaborative capacity of pollution control and carbon reduction is an important means to achieve comprehensive green and low-carbon transformation of the social economy. Starting from the essential requirements of improving the collaborative capacity of pollution control and carbon reduction, based on the whole-process governance perspective of "source-process-end-of-pipe," build an evaluation index system, measure the collaborative capacity, quantify the spatial differences, analyze the evolution characteristics, and explore the improvement path. The study found that China's collaborative capacity of pollution control and carbon reduction is characterized by homogeneous agglomeration and unbalanced regional development. Intra-regional differences are the main source of the differences, sorting by contribution is "Eastern > Western > Central > Northeast." After taking into account the factors of green transformation of industry, the input of scientific and technological elements, and opening to the outside world, the differences have gradually narrowed. Among them, the green transformation of industry is instrumentally in bridging the gap in eastern, central, and northeastern, the input of scientific and technological elements is instrumentally in bridging the gap between regions and the eastern and northeast, and opening to the outside world is instrumentally in bridging the gap between regions and the western. The scientific measurement and improvement of this capacity will provide the factual basis and path choice for achieving the task goal of "significantly improving China's collaborative capacity of pollution control and carbon reduction by 2030," which is of great practical significance for building a higher-quality, more sustainable, and greener pattern of the collaborative capacity of pollution control and carbon reduction.

Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations

Physics Informed Neural Networks (PINNs) are shown to be a promising method for the approximation of partial differential equations (PDEs). PINNs approximate the PDE solution by minimizing physics-based loss functions over a given domain. Despite substantial progress in the application of PINNs to a range of problem classes, investigation of error estimation and convergence properties of PINNs, which is important for establishing the rationale behind their good empirical performance, has been lacking. This paper presents convergence analysis and error estimates of PINNs for a multi-physics problem of thermally coupled incompressible Navier-Stokes equations. Through a model problem of Beltrami flow it is shown that a small training error implies a small generalization error. Posteriori convergence rates of total error with respect to the training residual and collocation points are presented. This is of practical significance in determining appropriate number of training parameters and training residual thresholds to get good PINNs prediction of thermally coupled steady state laminar flows. These convergence rates are then generalized to different spatial geometries as well as to different flow parameters that lie in the laminar regime. A pressure stabilization term in the form of pressure Poisson equation is added to the PDE residuals for PINNs. This physics informed augmentation is shown to improve accuracy of the pressure field by an order of magnitude as compared to the case without augmentation. Results from PINNs are compared to the ones obtained from stabilized finite element method and good properties of PINNs are highlighted.

Spatiotemporal divergence and convergence test of green total factor productivity of grain in China: based on the dual perspective of carbon emissions and surface source pollution

The topic of grain production and quality has always been a fundamental issue for the country's livelihood. With the purpose of contributing to high-quality grain development and ensuring national food security, this paper explores the spatial and temporal evolution, regional differences and convergence of grain green total factor productivity (GTFP) in the main grain-producing regions of China from the dual perspectives of carbon emissions and surface pollution with the help of EBM-GML model, kernel density function estimation and convergence methods. The results show that (1) Grain GTFP has generally shown a positive growth trend, although there exists obvious spatial differences. (2) In terms of decomposition indices, technological progress is the source of the increase in grain GTFP. (3) There are σ convergence, absolute β convergence and conditional β convergence in the main producing region as well as in the Yellow River basin and the Yangtze River basin; there are only absolute β convergence and conditional β convergence in the Songhua River basin. Grain GTFP has a single high-efficiency convergence point, and the grain GTFP is enhancing year by year in each province, and the inter-provincial gap is shrinking.

Speed of convergence in global value chains: Forward or backward linkage

The COVID-19 pandemic is creating uncertainty that potentially causes a decline in global trade. It hampers the catching-up processes of developing countries because they are already connected through global value chains (GVCs). This study investigates the speed of convergence in GVC participation. Furthermore, we propose a forward and backward GVC participation approach to trace domestic and foreign value-added contributions and to overcome overvaluation in gross exports. We compare forward and backward linkages and determine countries' convergence speeds. We scrutinize stochastic, σ, and β-convergence using the system generalized method of moments; additionally, we use this method to address potential endogeneity issues. Using a dynamic panel approach, we investigate global convergence countries in GVCs and possible foreign direct investment (FDI) factors that may influence convergence. In addition, we analyze the early effect of the COVID-19 pandemic on the convergence rate using the recent Asian Development Bank multi-regional input-output database that covers the period 2010-2019. The results illustrate convergence in both forward and backward GVC participation; however, the convergence speed varies among group countries. A group comprising countries in the Association of Southeast Asian Nations and other countries experiences faster convergence than advanced countries in forward GVC participation. In contrast, advanced countries experience faster convergence in backward GVC participation. Furthermore, the results reveal that FDI plays a significant role in GVC participation. Overall, The COVID-19 pandemic has decreased GVC participation on average.

The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union?

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

Analysis of regional differences and spatial spillover effects of agricultural carbon emissions in China

In order to realize "double carbon" target in agriculture and high-quality development of the rural economy in China, it is crucial to study the regional differences and spatial spillover effects of agricultural carbon emissions (ACE). This paper measures ACE using panel data of 31 Chinese provinces from 2005 to 2020, examines the spatio-temporal evolution characteristics，the convergence of agricultural carbon emissions, compares and analyzes regional differences, and investigates the spatial correlation and spatial spillover effects. The study found that: (1) Total agricultural carbon emissions over the research period exhibit a rising and then reducing trend, the spatial distribution of total agricultural carbon emissions is described as high in east-central and low in west. The gap of agricultural carbon emissions is gradually declining in the east, and will eventually reach their respective steady-state levels in the west and northeast. (2) There is a strong spatial interprovincial link of ACE, which has a beneficial knock-on effect on the convergence of adjacent provinces. (3) Agricultural industrial structure, urbanization level, the size of the agricultural labor force, and the intensity of the agricultural machinery input all directly affect ACE in this province and indirectly affect ACE in adjacent provinces, with the exception of the negligible coefficient of economic development level on ACE. Hence, pertinent policy suggestions are put out to serve as a guide for reducing ACE.

Identification of evolutionary trajectories shared across human betacoronaviruses

Comparing the evolution of distantly related viruses can provide insights into common adaptive processes related to shared ecological niches. Phylogenetic approaches, coupled with other molecular evolution tools, can help identify mutations informative on adaptation, whilst the structural contextualization of these to functional sites of proteins may help gain insight into their biological properties. Two zoonotic betacoronaviruses capable of sustained human-to-human transmission have caused pandemics in recent times (SARS-CoV-1 and SARS-CoV-2), whilst a third virus (MERS-CoV) is responsible for sporadic outbreaks linked to animal infections. Moreover, two other betacoronaviruses have circulated endemically in humans for decades (HKU1 and OC43). To search for evidence of adaptive convergence between established and emerging betacoronaviruses capable of sustained human-to-human transmission (HKU1, OC43, SARS-CoV-1 and SARS-CoV-2), we developed a methodological pipeline to classify shared non-synonymous mutations as putatively denoting homoplasy (repeated mutations that do not share direct common ancestry) or stepwise evolution (sequential mutations leading towards a novel genotype). In parallel, we look for evidence of positive selection, and draw upon protein structure data to identify potential biological implications. We find 30 candidate mutations, from which four [codon sites 18121 (nsp14/residue 28), 21623 (spike/21), 21635 (spike/25) and 23948 (spike/796); SARS-CoV-2 genome numbering] further display evolution under positive selection and proximity to functional protein regions. Our findings shed light on potential mechanisms underlying betacoronavirus adaptation to the human host and pinpoint common mutational pathways that may occur during establishment of human endemicity.

Phase field modeling and computation of vesicle growth or shrinkage

We present a phase field model for vesicle growth or shrinkage induced by an osmotic pressure due to a chemical potential gradient. The model consists of an Allen-Cahn equation describing the evolution of the phase field parameter that describes the shape of the vesicle and a Cahn-Hilliard-type equation describing the evolution of the ionic fluid. We establish conditions for vesicle growth or shrinkage via a common tangent construction using free energy curves. During the membrane deformation, the model ensures total mass conservation of the ionic fluid, and we weakly enforce a surface area constraint of the vesicle. We develop a stable numerical scheme and an efficient nonlinear multigrid solver to evolve the phase and concentration fields, and we use this to evolve the fields to near equilibrium for 2D vesicles. Convergence tests confirm an [Formula: see text] accuracy for our scheme and near-optimal convergence for our multigrid solver. Numerical results reveal that the diffuse interface model captures the main features of cell shape dynamics: for a growing vesicle, there exist circle-like equilibrium shapes if the concentration difference across the membrane and the initial osmotic pressure are large enough; while for a shrinking vesicle, there exists a rich collection of finger-like equilibrium morphologies.

Physician density: will we ever close the gap?

OBJECTIVE

Physician density is a crucial element of a well-functioning health system. Previous research has investigated factors affecting country-level physician supply. To date, however, no evidence has been provided about the patterns of convergence in physician density among countries. This paper thus tested club convergence in physician density in 204 countries worldwide from 1990 to 2019. A nonlinear time-varying factor model was adopted to identify potential clubs, wherein groups of countries tend to converge towards the same level of physician density. Our primary purpose was to document the potential long-lasting disparity in future global physician distribution.

RESULTS

Despite physician density increasing in all regions globally from 1990 to 2019, we found no evidence in favor of the hypothesis of global convergence. Conversely, the clustering algorithm successfully identified three main patterns (i.e., three final clubs). With few exceptions, the results indicated an uneven physician distribution between the majority of North and Sub-Saharan African countries (where physician density would remain well below the estimated threshold of at least 70% of the Universal Health Coverage Services Index) and the rest of the world. These findings support the WHO's global strategy to reverse the chronic under-investment in human resources for health.

Spatio-temporal efficiency of fiscal environmental expenditure in reducing CO2 emissions in China's cities

Although market-based CO₂ emission control measures (e.g., carbon tax and carbon trading market) have been deeply discussed, government-based measures have received limited attention. This has led to increased uncertainty regarding the formulation of targeted emission reduction policies. Using a unique dataset, the non-radial directional distance function, a proposed spatial meta-frontier analysis method, and the log t convergence model, this study comprehensively investigates the spatio-temporal trends in fiscal environmental expenditure efficiency (FE) and corresponding causes for in a case study for 106 Chinese cities over 2007-2019. The results show that city-level FE presented a slow upward trend at a relatively low level, with a clearly skewed distribution. The technology gap effect between city groups and the overall best production technology, and the efficiency gap effect within city groups were the main drivers widening the overall FE gap. Convergence analysis indicated that three convergence clubs of FE were found, which were distributed across the country. This study highlights that, when constructing fiscal environmental expenditure policies, the government should focus on balancing the regional gap of FE while comprehensively improving FE.

Health outcome convergence in Africa: the roles of immunization and public health spending

BACKGROUND

Reducing health outcomes disparities in Africa is a major concern for policymakers. Inter-country disparities in Africa is well documented. However, little is known about the accurate trajectory of these disparities over time. Thus, this paper investigates the convergence hypothesis in health outcomes in 40 African countries using data from the World Development Indicators. The study used panel data from 2000 to 2019.

METHOD

The study employs a nonlinear time-varying factor model to test the convergence hypothesis on infant mortality rate, under-five mortality, and life expectancy at birth. Then, we use the marginal effects of the ordered logit regression model to investigate the factors that explain club memberships.

RESULTS

The findings showed the absence of overall convergence for the three variables of interest. However, we identified the presence of convergence clubs. Moreover, we observed substantial gaps between the estimated clubs. The marginal effect results reveal that real GDP per capita, population structure, urbanization, trade, access to basic sanitation, and external health expenditure are essential to club formation. In addition, DTP immunization and the general government health expenditure as a percentage of the general government expenditure (our Abuja Declaration instrument) also play a significant role in explaining the club membership.

CONCLUSION

The findings suggest that policymakers should develop and implement targeted club-specific health policies. Furthermore, interventions to promote increased immunization, particularly among children, should be encouraged. Governments should also make substantial efforts to increase the share of their national budget allocated to the health sector by at least 15 percent.

Energy poverty and the convergence hypothesis across EU member states

Energy poverty is an emerging issue towards global affairs. Currently, the development of energy-related policies is becoming essential, with regard to new societies, social inclusion and social rights. In this paper, we examine the dynamic patterns of energy poverty among 27 EU member states between 2005 and 2020. We use the log-t regression test to investigate the convergence hypothesis, and the P&S data-driven algorithm to detect potential convergence clubs. The empirical results of energy poverty indicators are mixed, and the convergence hypothesis of the states is rejected. Instead, convergence clubs are exhibited, implying that groups of countries converge to different steady states in the long run. In view of the convergence clubs, we suggest that the affordability of heating services is potentially explained by structural conditions of housing, climate conditions and energy costs. Besides, the adverse financial and social conditions for the European households have significantly triggered the arrears on utility bills. Moreover, a significant proportion of households do not have basic sanitation services.

The approximate functional equation of some Diophantine series

We prove that a family of Diophantine series satisfies an approximate functional equation. It generalizes a result by Rivoal and Roques and proves an extended version of a conjecture posed in their paper. We also characterize the convergence points.

MOCOVIDOA: a novel multi-objective coronavirus disease optimization algorithm for solving multi-objective optimization problems

A novel multi-objective Coronavirus disease optimization algorithm (MOCOVIDOA) is presented to solve global optimization problems with up to three objective functions. This algorithm used an archive to store non-dominated POSs during the optimization process. Then, a roulette wheel selection mechanism selects the effective archived solutions by simulating the frameshifting technique Coronavirus particles use for replication. We evaluated the efficiency by solving twenty-seven multi-objective (21 benchmarks & 6 real-world engineering design) problems, where the results are compared against five common multi-objective metaheuristics. The comparison uses six evaluation metrics, including IGD, GD, MS, SP, HV, and delta p (Δ P ). The obtained results and the Wilcoxon rank-sum test show the superiority of this novel algorithm over the existing algorithms and reveal its applicability in solving multi-objective problems.

Convergence of per capita ecological footprint among BRICS-T countries: evidence from Fourier unit root test

In recent years there has been a great deal of research into environmental pollution using a variety of techniques in response to growing environmental concerns. Convergence analysis, one of these techniques, helps determine whether the developing countries will catch up with the rich countries in pollution using unit root tests. However, the vast majority of the research in the field has generally used conventional unit root tests. Since many economic series contain structural breaks, using unit root tests that account for structural breaks is essential for accurate prediction. More specifically, if the series has a fractional process, conventional unit root tests may erroneously conclude that the departure from linearity is permanent. Moreover, the existing literature mainly uses gas emissions, such as carbon dioxide, which represent pollution weakly. Therefore, we use per capita ecological footprint (EF hereafter) as a more comprehensive pollution indicator of environmental degradation. In this direction, the study aims to determine whether BRICS-T countries' EF converges to the average of the BRICS-T for the 1992-2017 period. Besides the ADF unit root test, we employed the Fourier ADF unit root test, which considers the structural breaks, and the Fractional Frequency Fourier ADF unit root test, which accounts for structural breaks by considering fractional values. Our results showed that EF converges in Russia and Turkey according to the conventional ADF test, in China and Russia according to the Fourier ADF test, and in Brazil and China according to the Fractional Fourier Frequency test.

Health expenditure convergence and the roles of trade and governance in Africa

This study investigates the convergence hypothesis in health expenditures in 40 African countries over the 2000-2019 period. The new non-linear dynamic factor model is used on panel data extracted from the World Development Indicator and the World Governance Indicator. We consider two categories of health expenditures: the domestic general government health expenditure as a percentage of government expenditure and the domestic general government health expenditure per capita. The results show the absence of full panel convergence for the two indicators used. However, there is evidence of convergence clubs. The overall marginal effect of the control variables is consistent with the existing literature. The results further show a strong influence of trade in attaining convergence among the clubs for both models. However, governance quality only affects the probability of converging in a club for the general government health expenditure as a percentage of government expenditure model. The findings suggest that policies on promoting health expenditure convergence should pursue initiatives that encourage trade. Efforts should also be targeted to improve the quality of governance.

A direct discretization recurrent neurodynamics method for time-variant nonlinear optimization with redundant robot manipulators

Discrete time-variant nonlinear optimization (DTVNO) problems are commonly encountered in various scientific researches and engineering application fields. Nowadays, many discrete-time recurrent neurodynamics (DTRN) methods have been proposed for solving the DTVNO problems. However, these traditional DTRN methods currently employ an indirect technical route in which the discrete-time derivation process requires to interconvert with continuous-time derivation process. In order to break through this traditional research method, we develop a novel DTRN method based on the inspiring direct discrete technique for solving the DTVNO problem more concisely and efficiently. To be specific, firstly, considering that the DTVNO problem emerging in the discrete-time tracing control of robot manipulator, we further abstract and summarize the mathematical definition of DTVNO problem, and then we define the corresponding error function. Secondly, based on the second-order Taylor expansion, we can directly obtain the DTRN method for solving the DTVNO problem, which no longer requires the derivation process in the continuous-time environment. Whereafter, such a DTRN method is theoretically analyzed and its convergence is demonstrated. Furthermore, numerical experiments confirm the effectiveness and superiority of the DTRN method. In addition, the application experiments of the robot manipulators are presented to further demonstrate the superior performance of the DTRN method.

Earth Systems to Anthropocene Systems: An Evolutionary, System-of-Systems, Convergence Paradigm for Interdependent Societal Challenges

Humans have made profound changes to the Earth. The resulting societal challenges of the Anthropocene (e.g., climate change and impacts, renewable energy, adaptive infrastructure, disasters, pandemics, food insecurity, and biodiversity loss) are complex and systemic, with causes, interactions, and consequences that cascade across a globally connected system of systems. In this Critical Review, we turn to our "origin story" for insight, briefly tracing the formation of the Universe and the Earth, the emergence of life, the evolution of multicellular organisms, mammals, primates, and humans, as well as the more recent societal transitions involving agriculture, urbanization, industrialization, and computerization. Focusing on the evolution of the Earth, genetic evolution, the evolution of the brain, and cultural evolution, which includes technological evolution, we identify a nested evolutionary sequence of geophysical, biophysical, sociocultural, and sociotechnical systems, emphasizing the causal mechanisms that first formed, and then transformed, Earth systems into Anthropocene systems. Describing how the Anthropocene systems coevolved, and briefly illustrating how the ensuing societal challenges became tightly integrated across multiple spatial, temporal, and organizational scales, we conclude by proposing an evolutionary, system-of-systems, convergence paradigm for the entire family of interdependent societal challenges of the Anthropocene.

Self-Generated Motives of Social Casino Gamers

Social casino games have achieved widespread popularity, and are accessed by more than 85 million people each day. Yet, why people play social casino games is largely unknown. To address this gap, an inductive approach was taken to better understand the motives for playing social casino games, as well as the motives for transitioning from social casino gaming to gambling and vice versa. To this end, 269 social casino gamers were asked to provide a ranked list of their motives for playing social casino games. Additionally, we asked participants their motivations for transitioning from gambling to social casino gaming (n = 202) or vice versa (n = 67). A total of 795, 605, and 201 unique responses describing motives for playing social casino games, transitioning from social casino gaming to gambling, and transitioning from gambling to social casino gaming, respectively, were analyzed using a thematic content analysis. The most frequently endorsed motive for playing social casino games was for enhancement (e.g., fun, challenge). Participants also noted playing to earn rewards, including money, and for social reasons. Several motives linked social casino game play to gambling. These included: to hone gambling-related 'skills', a desire to transition to gambling to win real money, and as a gambling harm-reduction strategy. Motives for playing social casino games did not differ significantly between those who first gambled and then transitioned to social casino gaming and vice versa, suggesting that once people begin playing social casino games, they have similar motives for continued engagement. The present study contributes to understanding the immense popularity of social casino games and their links to gambling.

Does ecological footprint in ECCAS and ECOWAS converge? Empirical evidence from a panel unit root test with sharp and smooth breaks

The costs due to climate change have been increasing day by day. In addition to the risk of losing our planet's natural assets due to the increasing destructiveness of climate-related natural disasters and extreme climate events, we are also faced with grave economic risks. For this reason, researchers have recently focused on environmental issues. Nevertheless, they generally have investigated developed countries and ignored developing and least developed countries such as African countries. The United Nations (2015) report highlights that African countries should be specially investigated. Hence, the paper analyzes whether the ecological footprint in the Economic Community of Central African States (ECCAS) and Economic Community of West African States (ECOWAS) converges for the period from 1961 to 2017. We employ Bahmani-Oskooee et al.'s (2014) panel unit root test with sharp and smooth breaks. The empirical findings demonstrate that the ecological footprint is stationary in ECCAS and ECOWAS. Stated in other words, the ecological footprint in these countries converges. Therefore, policymakers could implement similar policies to reduce the ecological footprint in these countries. This policy framework paves the way for an effective sustainable development.

Food provisioning results in functional, but not compositional, convergence of the gut microbiomes of two wild Rhinopithecus species: Evidence of functional redundancy in the gut microbiome

The consumption of similar diets has led to the convergence of gut microbial compositions and functions across phylogenetically distinct animals. However, given the functional redundancy in gut microbiomes, it remains unclear whether synchrony occurs in their functions only and not in their composition, even within phylogenetically close animals consuming a similar diet. In this study, we collected fresh fecal samples from a Rhinopithecus roxellana population in April 2021 (before food provisioning) and June and December 2021 (after food provisioning) and used high-throughput sequencing methods (full-length 16S rRNA gene sequencing and metagenomes) to investigate changes in the gut microbiome due to food provisioning. Combining the results from our previous studies on a wild Rhinopithecus bieti population, we found that the artificial food provisions (e.g., apples, carrots, and peanuts) affected the gut microbiome, and synchrony occurred only in its functions and antibiotic resistance gene community in both Rhinopithecus species, reflecting its ecological functional redundancy. Given the current findings (e.g., depletion in probiotic microbes, dysbiosis in the gut microbial community, and changes in the antibiotic resistance gene profile), anthropogenic disturbances (e.g., food provisioning) would have potential negative effects on host health. Therefore, human activity in animal conservation should be rethought from the standpoint of gut microbial diversity.

On numerical solution of boundary layer flow of viscous incompressible fluid past an inclined stretching sheet in porous medium and heat transfer using spline technique

In this paper, the boundary layer flow of viscous incompressible fluid over an inclined stretching plate in porous media with body force and heat transfer has been studied. To solve this problem, we develop a suitable spline method which is used to calculate the velocity function of the flow problem. We proceed as follows:•With a suitable stream function, the concerned boundary layer equation is converted into non-linear third order ordinary differential equation together with appropriate boundary conditions in an infinite domain which has been further linearized by using quasi-linearization method.•Then, we develop a non polynomial quintic spline technique which has been used to find the numerical values of the velocity function of the flow problem. The convergence analysis of the developed spline technique has been discussed.•Later, the method developed so far has been applied to solve nonlinear boundary value problem for different angles of inclination and Froude number. The values obtained so far have been used to study heat flow problem. Finally, skin friction has been discussed.

Human Capital, Trade Competitiveness and Environmental Efficiency Convergence Across Asia Pacific Countries

This study mainly investigates 14 Asia Pacific economies' environmental efficiency. Departing from previous studies ignoring environmental technology heterogeneity, we evaluate environmental efficiency through metafrontier super epsilon based model (EBM). We compare environmental efficiency convergence across different regions via unit root test and truncated regressions. We analyze how trade competitiveness impact environmental efficiency. We also explore effect of green technology and human capital on environmental efficiency from the perspective of endogenous growth. Our findings indicate that stochastic and absolute β-convergence tendencies were confirmed. Human capital can enhance environmental efficiency convergence. Trade competitiveness showed a mixed impact on environmental efficiency convergence, confirming scale, composition and technical effects. It is better to enhance human capital, strengthening environmental regulations under international competition as well as relentlessly pursuing green industrialization across Asia Pacific countries.

Gene expressions between obligate bamboo-eating pandas and non-herbivorous mammals reveal converged specialized bamboo diet adaptation

BACKGROUND

It is inevitable to change the function or expression of genes during the environmental adaption of species. Both the giant panda (Ailuropoda melanoleuca) and red panda (Ailurus fulgens) belong to Carnivora and have developed similar adaptations to the same dietary switch to bamboos at the morphological and genomic levels. However, the genetic adaptation at the gene expression level is unclear. Therefore, we aimed to examine the gene expression patterns of giant and red panda convergent specialized bamboo-diets. We examined differences in liver and pancreas transcriptomes between the two panda species and other non-herbivorous species.

RESULTS

The clustering and PCA plots suggested that the specialized bamboo diet may drive similar expression shifts in these two species of pandas. Therefore, we focused on shared liver and pancreas DEGs (differentially expressed genes) in the giant and red panda relative to other non-herbivorous species. Genetic convergence occurred at multiple levels spanning carbohydrate metabolism, lipid metabolism, and lysine degradation. The shared adaptive convergence DEGs in both organs probably be an evolutionary response to the high carbohydrate, low lipid and lysine bamboo diet. Convergent expression of those nutrient metabolism-related genes in both pandas was an intricate process and subjected to multi-level regulation, including DNA methylation and transcription factor. A large number of lysine degradation and lipid metabolism related genes were hypermethylated in promoter regions in the red panda. Most genes related to carbohydrate metabolism had reduced DNA methylation with increased mRNA expression in giant pandas. Unlike the red panda, the core gene of the lysine degradation pathway (AASS) doesn't exhibit hypermethylation modification in the giant panda, and dual-luciferase reporter assay showed that transcription factor, NR3C1, functions as a transcriptional activator in AASS transcription through the binding to AASS promoter region.

CONCLUSIONS

Our results revealed the adaptive expressions and regulations of the metabolism-related genes responding to the unique nutrients in bamboo food and provided data accumulation and research hints for the future revelation of complex mechanism of two pandas underlying convergent adaptation to a specialized bamboo diet.

A new spline technique for the time fractional diffusion-wave equation

The current research article proposes an approximate solution of the fractional diffusion wave equation (FDWE) by using a new collocation method based on the cubic B-splines. The fractional derivative in the time direction is considered in Caputo form. The theoretical research of the proposed algorithm is discussed with L _∞ and H ¹ norms. The method presented in this article is found to be of order (∆t ^{3- α} + h ⁴). The highlights of the current technique proposed in this article are as under:•The method is high-order collocation and uses a compact stencil. The error analysis is discussed to authenticate the order of convergence of the proposed numerical approximation.•The comparisons of errors with the already existing methods are done and observed that our method produces more accurate results than the methods presented in the literature.

Orthogonal cubic splines for the numerical solution of nonlinear parabolic partial differential equations

In this paper, a new orthogonal basis for the space of cubic splines has been introduced. A linear combination of cubic orthogonal splines is considered to approximate the functions in which the coefficients are calculated with numerically stable formulae. Applications to the numerical solutions of some parabolic partial differential equations are given, in which the approximations are obtained using the first and second integral of orthogonal splines which leads to an efficient solution procedure. The convergence analysis in the approximate scheme is investigated. A comparison of the obtained numerical solutions with some other papers indicates that the presented method is reliable and yields result with good accuracy. The main parts of our study are as follows:•We propose a robust approach based on the orthogonal cubic splines procedure in conjunction with the operational matrix.•The convergence in the approximate scheme is analyzed.•Numerical examples show that the proposed method is very accurate.

The convergence of 2,6-dichloro-1,4-benzoquinone in the whole process of lignin phenol precursor chlorination

The formation and decomposition of 2,6-dichloro-1,4-benzoquinone, an emerging disinfection byproduct (DBP), was studied in the chlorination of lignin phenol precursors. The results show that DCBQ and the related hydroxyl DCBQ (DCBQ-OH) acts as the intermediate products of the chlorination process of the three typical lignin phenol precursors (p-hydroxybenzoic acid, protocatechuic acid, and gallic acid). The contributions of lignin phenol precursors to the overall formation of the targeted DBPs were determined based on the observed abundances of individual lignin phenols and their DBP yields. DCBQ and DCBQ-OH were generated within 2-6 h, the relative abundance of the yields of mol carbon atoms in DCBQ corresponding to the mol carbon atoms in the three model precursors (DCBQ-C) was about 0.01%-14.37% under different pH conditions. With the chlorination reaction time increased (after two or four h), the concentrations of DCBQ and DCBQ-OH entirely decreased, and the decomposition of DCBQ do not follow a pseudo-first-order kinetics during chlorination. Conversely, the decomposition of DCBQ generated from p-hydroxybenzoic acid followed a pseudo-second-order kinetics. Moreover, the formation of trichloromethane (TCM), dichloroacetic acid (DCAA), and trichloroacetic acid (TCAA) was also detected during the chlorination. The contribution of the decomposed DCBQ was mainly to TCAA and the unknown DBPs within 2-12 h, and DCBQ decomposition pathway was affected by pH. Moreover, except for DCBQ/DCBQ-OH and TCM/HAAs, there were still 73.6%-92.41% unknown products (including non-halogenated aromatic DBPs and chlorine-substituted DBPs) needing to identify during the chlorination process for lignin phenols. Overall, revealing the formation and decomposition of DCBQ during the chlorination of lignin phenol precursors would contribute to the effective development of drinking water treatment processes for the removal of highly toxic intermediates generated during disinfection.

A fractional gradient descent algorithm robust to the initial weights of multilayer perceptron

For multilayer perceptron (MLP), the initial weights will significantly influence its performance. Based on the enhanced fractional derivative extend from convex optimization, this paper proposes a fractional gradient descent (RFGD) algorithm robust to the initial weights of MLP. We analyze the effectiveness of the RFGD algorithm. The convergence of the RFGD algorithm is also analyzed. The computational complexity of the RFGD algorithm is generally larger than that of the gradient descent (GD) algorithm but smaller than that of the Adam, Padam, AdaBelief, and AdaDiff algorithms. Numerical experiments show that the RFGD algorithm has strong robustness to the order of fractional calculus which is the only added parameter compared to the GD algorithm. More importantly, compared to the GD, Adam, Padam, AdaBelief, and AdaDiff algorithms, the experimental results show that the RFGD algorithm has the best robust performance for the initial weights of MLP. Meanwhile, the correctness of the theoretical analysis is verified.