Agri-waste derived electroactive carbon-iron oxide nanocomposite for oxygen reduction reaction: an experimental and theoretical study

Herein, we have utilized agri-waste and amalgamating low Fe3+, to develop an economic iron oxide-carbon hybrid-based electrocatalyst for oxygen reduction reaction (ORR) with water as a main product following close to 4e- transfer process. The electrocatalytic activity is justified by electrochemical active surface area, synergetic effect, and density functional theory calculations.

Perrault syndrome: The Way Forward After Genetic Counselling?

A female, term neonate, born via vaginal delivery to a G5P1D1A3 hypothyroid mother with a history of an elder sibling being homozygous for HSD17B4 mutation, diagnosed while working up his progressive neurological disorder and succumbing to the same. The family screening revealed that both parents were heterozygous carriers of the same mutation in the gene HSD17B4 After genetic counselling, amniocentesis revealed the fetus to be having homozygosity for the same mutation. In view of precious pregnancy, normal antenatal scans and investigations, the pregnancy was continued, and baby was born with a birth weight of 2.65 kg and had a smooth perinatal transition. Parents were counselled regarding the course of the illness, possible complications and the need for regular follow-up. Ultrasound of the abdomen, pelvis and head was normal in the neonatal period. She was vaccinated as per the national schedule and gaining weight normally.

Single-atom catalysts supported on a hybrid structure of boron nitride/graphene for efficient nitrogen fixation via synergistic interfacial interactions

Hexagonal boron nitride (BN) shows significant chemical stability and promising thermal nitrogen reduction reaction (NRR) activity but suffers from low conductivity in electrolysis with a wide band gap. To overcome this problem, two-dimensional (2D) BN and graphene (G) are designed as a heterostructure, namely BN/G. According to density functional theory (DFT), the higher conductivity of G narrows the band gap of BN by inducing some electronic states near the Fermi energy level (Ef). Once transition metals (TMs) are anchored in the BN/G structure as single atom catalysts (SACs), the NRR activity improves as the inert BN basal layer activates with moderate *NH2 binding energy and further the band gap is reduced to zero. V (vanadium) and W (tungsten) SACs exhibit the best performance with limiting potentials of -0.22 and -0.41 V, respectively. This study helps in understanding the improvement of the NRR activity of BN, providing physical insights into the adsorbate-TM interaction.

Phenomenology, quality of life, and predictors of reversibility in patients with drug-induced movement disorders: a prospective study

BACKGROUND

Drug-induced movement disorders (DIMDs) form an important subgroup of secondary movement disorders, which despite conferring a significant iatrogenic burden, tend to be under-recognized and inappropriately managed.

OBJECTIVE

We aimed to look into phenomenology, predictors of reversibility, and its impact on the quality of life of DIMD patients.

METHODS

We conducted the study in the Department of Neurology at a tertiary-care centre in India. The institutional ethics-committee approved the study. We assessed 55-consecutive DIMD patients at presentation to our movement disorder clinic. Subsequently, they followed up to evaluate improvement in severity-scales (UPDRS, UDRS, BARS, AIMS) and quality of life (EuroQol-5D-5L). Wilcoxan-signed-rank test compared the scales at presentation and follow-up. Binary-logistic-regrerssion revealed the independent predictors of reversibility.

RESULTS

Fourteen patients (25.45%) had acute-subacute DIMD and 41 (74.55%) had tardive DIMD. Tardive-DIMD occurred more commonly in the elderly (age 50.73±16.92 years, p<0.001). Drug-induced-Parkinsonism (DIP) was the most common MD, followed by tardivedyskinesia. Risperidone and levosulpiride were the commonest culprit drugs. Patients in both the groups showed a statistically significant response to drug-dose reduction /withdrawal based on follow-up assessment on clinical-rating-scales and quality of life scores (EQ-5D-5L). DIMD was reversible in 71.42% of acute-subacute DIMD and 24.40% of patients with chronic DIMD (p=0.001). Binary-logistic-regression analysis showed acute-subacute DIMDs and DIP as independent predictors of reversibility.

CONCLUSION

DIP is the commonest and often reversible drug-induced movement disorder. Levosulpiride is notorious for causing DIMD in the elderly, requiring strict pharmacovigilance.

Improved indirect instantaneous torque control based torque sharing function approach of SRM drives in EVs using hybrid technique

This manuscript proposes an improved indirect instantaneous torque control (IITC) based torque sharing function (TSF) method of switched reluctance motor (SRM) drives in electric vehicles (EVs) using a hybrid system. The proposed hybrid techniques are joint performance of both Reptile Search Algorithm (RSA) and Honey Badger Algorithm (HBA), hence it is named as Enhanced RSA (ERSA) method. Here, an IITC method of SRMs for EVs is utilized. It achieves the requirements of the vehicle, like minimum torque ripple, improved speed range, high effectiveness, and maximal torque per ampere (MTPA). To precisely specify the switched reluctance motor and its magnetic features are measured by the proposed method. The modified Torque sharing function compensates the torque error along with incoming phase, which contains the minimal rate of change of flux linkage. Finally, the ERSA method is implemented to define the best control parameters. Then, the proposed ERSA system is performed on the MATLAB platform and the performance is compared to different existing systems. The MSE for case 1 and case 2 using proposed system attains 0.01093 and 0.01095. The voltage deviation for case 1 and case 2 using proposed system reaches 5 and 5. The power factor for case 1 and case 2 reaches a value of 50 and 40 using the proposed system.

Mucormycosis infection associated with global COVID-19 pandemic - an institutional histopathological study

BACKGROUND

Coronavirus disease 2019 (COVID-19) in the recent times have instilled signs of immunosuppression globally which has further precipitated increasing range of opportunistic infections. Mucormycosis is a distressing opportunistic fungal infection with a high incidence and is the third commonest acute invasive infection following candidiasis and aspergillosis. The aim of the present observational study is to delineate the enigmatic histopathological profile between mucormycosis cases seen prior to pandemic (PPM) and pandemic associated mucormycosis (PAM).

MATERIAL AND METHODS

Tissue archives of 105 histopathologically diagnosed cases of mucormycosis were included and analysed for demographical details and histopathological parameters like fungal load and localization, granuloma formation, necrosis, inflammatory infiltrate and tissue invasion.

RESULTS

0ut of 105 included cases, 11/105 (10.48%) were reported PPM and 94/105 (89.52%) PAM. Among 94 cases of PAM, 51/94 (54%) cases also showed COVID-19 positivity, while 43/94 (46%) did not. Of all the histological variables, increased fungal load and necrosis were observed in PAM relative to PPM cases.

CONCLUSIONS

The histopathological variables like fungal load, necrosis, granuloma formation and tissue invasion, could help the clinician in assessing the clinical status at the time of tissue diagnosis and improve the treatment accordingly.

A wideband hybrid combiner design for ITER ion cyclotron radio frequency source

The high-power radio frequency source for ion cyclotron heating and current drive of ITER tokamak consists of two identical 1.5 MW amplifier chains. These two chains will be combined using a wideband hybrid combiner with adequate coupling flatness, phase balance, return loss, and isolation response to generate 2.5 MW radio frequency (RF) power in the frequency range of 36 to 60 MHz. As part of the in-house development program at ITER-India, a wideband hybrid combiner with coupling flatness and return loss/isolation better than 0.4 and -25 dB, respectively, has been simulated. A detailed analysis for matched load performance of the hybrid combiner for the output power level of 3 MW as well as mismatched load performance for load power of 2.5 MW with voltage standing wave ratio 2.0 and 3.0 MW with voltage standing wave ratio 1.5 has been performed. Based on the simulation, a prototype model was in-house fabricated, and the simulated results have been validated experimentally in splitter and combiner mode. To evaluate performance as a combiner, two solid-state power amplifiers were combined through the prototype combiner for input power levels up to 2.5 kW on matched and mismatched load conditions. In the power splitter experiment, the RF power level up to 1.5 MW from a single amplifier chain was split through the prototype combiner to be dumped in the high power loads in the frequency range of 36 to 60 MHz.

Intelligent cloud agent based action recognition detection using machine learning

On the lap of this present-day epoch, Human Activity Recognition (HAR) has been of considerable assistance in case of health monitoring and recovery. The utilization of machine learning approach integration with intelligent agent in the area of health informatics collected via Human Activity Recognition enhances the decision making quality and significance. Its specific homogenization into the Smart Healthcare Monitoring permits gathering, examining and learning from Internet of Things (IoT) wearable devices, undoubtedly achieving knowledge and making analysis on the patient’s state. Despite several research works conducted on Smart Healthcare Monitoring, there remains certain amount of pitfalls, like, time, overhead involved in analysis and also the falsification of analysis. To focus on these issues, a Statistical Partial Regression and Support Vector Intelligent Agent Learning (SPR-SVIAL) for Smart Healthcare Monitoring is proposed. The SPR-SVIAL method is split into two stages. First, data pre-processing along with the dimensionality reduced features are extracted by employing Statistical Partial Regression Feature Extraction model. Here, with the ceaseless thump to-pulsate heart information, triaxial accelerometer information, rest quality, actual work and mental attributes obtained from the input dataset acquired from IoT wearable devices, Partial Least Square is applied to extract the dimensionality reduced features, therefore contributing to Smart Healthcare Monitoring time and accuracy. Next, with these resultant features, Support Vector Intelligent Agent Learning is proposed for Smart Healthcare Monitoring that with the aid of Machine Learning and Intelligent Agent not only reduces the falsification of analysis but also reduces the overhead incurred. The SPR-SVIAL method is tested on simulators and the obtained results indicated better performance upon comparison with the other methods. The results show that we can reduce the time, overhead, false positive rate for healthcare monitoring and achieve a high accuracy rate by performing feature extraction for each of the data recording.

Less invasive surfactant administration via infant feeding tube versus InSurE method in preterm infants: a randomized control trial

There is growing evidence that less invasive surfactant administration (LISA) is a better alternative to the standard Intubate-surfactant-extubate (InSurE) procedure in spontaneously breathing preterm infants with RDS. The infant feeding tube is easily available and cost-effective in comparison to special catheters used for surfactant administration in various studies on LISA and cost-effective health care is the need of the hour for countries like ours which are Low and middle-income countries(LMICs).The present study was planned to compare the total duration of respiratory support in preterm babies between 26 to 34 weeks of gestation with RDS requiring surfactant therapy administered by LISA technique using an infant feeding tube or InSurE method. In this unblinded randomised controlled trial, 150 infants were allocated to LISA (n = 74) or InSurE group (n = 76). An 8F feeding tube was used for surfactant delivery in the LISA group. The primary outcome was the total duration of respiratory support required and secondary outcomes included the proportion of babies developing BPD, IVH, PDA, NEC, ROP, air leaks, CPAP failure, and those requiring a repeat dose of surfactant along with the duration of hospitalization, time to regain birth weight and Death. The baseline variables including birth weight and gestation age were similar in the two groups. Nearly 27% of the mothers did not receive any dose of antenatal steroids (ANS) while around 37% of the mothers received complete course of ANS. A high proportion of babies (57%) were delivered by cesarean section. Intrapharyngeal reflux was significantly more in babies who received surfactant with the LISA method in comparison to InSurE technique (32% v/s 3%, p < 0.001). There was no statistically significant difference in the primary outcome of the total duration of respiratory support in both groups with a median duration of 120 h, 95% CI (69-235), and p = 0.618. The need for invasive mechanical ventilation was significantly lower in the LISA group (p = 0.017) with RR (95% CI) 0.498 (0.259-0.958). The rate of CPAP failure was significantly lower in the LISA group (p = 0.005) with RR (95% CI) 0.55 (0.34-0.89). In this study, the total duration of hospital stay was reduced in the LISA group (19 days) compared to InSurE group (26 days), although the same was not statistically significant. LISA with an 8F feeding tube is feasible and an effective strategy for surfactant administration which resulted in a significant reduction in CPAP failure and the need for invasive mechanical ventilation.Trial registration: www.ctri.nic.in id CTRI/2020/05/025360. Trial was registered at CTRI on 26/05/2020. First case of trial was enrolled on 28/05/2020.

Trust based COVID-19 vaccine distribution using blockchain technology

The COVID-19 outbreak has impacted huge number of individuals all around the world and has caused a great economic loss all over the world. Vaccination is most effective solution to prevent this disease. It helps in protecting the whole community. It improves the human immune system and fights against corona virus reducing the death rate. This paper deals with the different types of COVID-19 vaccine and their related distribution, it includes measures to ensure safe and secured distribution of the vaccine through block chain technology with the help of supply chain. Any malfunction in the chain is identified by the trust value of the function point method and the value of the Markov Chain.

Blockchain security in virtual environment

This paper is to improve the privacy and security in the distributed virtual environment using blockchain technology. One of the feature it provides is greater security in the decentralized virtual environment. A key aspect of this technology is used for various fields like healthcare, finance, business and cloud environment. Key issue of the virtual environment is to protect the data privacy and security which is difficult to handle. To overcome this issue, a new security model to protect the virtual environment is created and will focus on different types of attacks in blockchain technology.

Sclerotic lumbar chordoma: A case report

Chordoma is a rare tumor, often occurring in the cervical spine and sacrococcygeal spine with a lytic appearance, but rarely in the thoracolumbar spine. Chordomas can occasionally be sclerotic and are included in the differential diagnosis for an ivory vertebra. We present a case of a sclerotic chordoma in an upper lumbar vertebral body with corresponding multimodality imaging. This case demonstrates that chordoma should be a concern for an older adult with a sclerotic vertebral lesion, particularly if it is a solitary lesion. Knowledge of the variable location and appearance of chordomas is critical so it is not mistaken for a metastasis.

Fast atomic structure optimization with on-the-fly sparse Gaussian process potentials. J Phys Condens Matter 2022;34:344007. [PMID: 35675808 DOI: 10.1088/1361-648x/ac76ff]

We apply on-the-fly machine learning potentials (MLPs) using the sparse Gaussian process regression (SGPR) algorithm for fast optimization of atomic structures. Great acceleration is achieved even in the context of a single local optimization. Although for finding the exact local minimum, due to limited accuracy of MLPs, switching to another algorithm may be needed. For random gold clusters, the forces are reduced to ∼0.1 eV Å^-1within less than ten first-principles (FP) calculations. Because of highly transferable MLPs, this algorithm is specially suitable for global optimization methods such as random or evolutionary structure searching or basin hopping. This is demonstrated by sequential optimization of random gold clusters for which, after only a few optimizations, FP calculations were rarely needed.

Unveiling the Role of Charge Transfer in Enhanced Electrochemical Nitrogen Fixation at Single-Atom Catalysts on BX Sheets (X = As, P, Sb)

To tune single-atom catalysts (SACs) for effective nitrogen reduction reaction (NRR), we investigate various transition metals implanted on boron-arsenide (BAs), boron-phosphide (BP), and boron-antimony (BSb) using density functional theory (DFT). Interestingly, W-BAs shows high catalytic activity and excellent selectivity with an insignificant barrier of only 0.05 eV along the distal pathway and a surmountable kinetic barrier of 0.34 eV. The W-BSb and Mo-BSb exhibit high performances with limiting potentials of -0.19 and -0.34 V. The Bader-charge descriptor reveals that the charge transfers from substrate to *NNH in the first protonation step and from *NH₃ to substrate in the last protonation step, circumventing a big hurdle in NRR by achieving negative free energy change of *NH₂ to *NH₃. Furthermore, machine learning (ML) descriptors are introduced to reduce computational cost. Our rational design meets the three critical prerequisites of chemisorbing N₂ molecules, stabilizing *NNH, and destabilizing *NH₂ adsorbates for high-efficiency NRR.

Assessing the clinical utility of volumetric HRCT in pediatric enlarged vestibular aqueduct related hearing loss

OBJECTIVES

|The aim of this study was to evaluate the use of volumetric HRCT measurements in the diagnosis of enlarged vestibular aqueduct syndrome (EVAS) and describe the association of this novel radiographic approach with clinical hearing outcomes. We hypothesized that volumetric measurements may have stronger correlation to hearing loss given the anatomic variability of the vestibular aqueduct in linear measurements.

METHODS

A retrospective study design was used, including 51 patients that fit the inclusion criteria for the study for a total of 81 ears. 3D volumes were calculated using the MIM Software platform (MIM Software Inc.) from semiautomatic segmentation of the VA across individual slices on CT scan. Air and bone conduction data was collected from medical records with the air-bone gap being calculated from these data. Univariate and multivariate analyses were conducted to determine if volumetric VA size correlated with hearing loss outcomes.

RESULTS

Out of the study population, 30 subjects (58.8%) demonstrated bilateral EVA. Average VA size estimated by volumetric CT methodology was 0.035 mm³; sd = 0.025 mm³. Volumetric measurements significantly correlated to both midpoint length and operculum size. Multivariate analysis adjusting for age, race, and gender demonstrated significant correlation between volumetric VA size and both low and high frequencies for PTA Air (p = 0.009; 0.010) and PTA Bone (p = 0.027; 0.002), respectively. Of note, the coefficient values for volumetric data were higher than linear measurements showing a potentially stronger correlation, albeit with high variability. Volumetric size was not significantly correlated to air-bone gap at either low or high frequency (p = 0.335; 0.062).

CONCLUSION

Our results indicate that volumetric CT measurements of the VA may be a valid and viable new method for assessing EVAS patients. In our study, volumetric VA measurements demonstrated a strong correlation across both air and bone conduction at both frequency ranges measured, with potentially greater correlative strength than linear measurements.

Mask Detection and Social Distance Identification Using Internet of Things and Faster R-CNN Algorithm

The drones can be used to detect a group of people who are unmasked and do not maintain social distance. In this paper, a deep learning-enabled drone is designed for mask detection and social distance monitoring. A drone is one of the unmanned systems that can be automated. This system mainly focuses on Industrial Internet of Things (IIoT) monitoring using Raspberry Pi 4. This drone automation system sends alerts to the people via speaker for maintaining the social distance. This system captures images and detects unmasked persons using faster regions with convolutional neural network (faster R-CNN) model. When the system detects unmasked persons, it sends their details to respective authorities and the nearest police station. The built model covers the majority of face detection using different benchmark datasets. OpenCV camera utilizes 24/7 service reports on a daily basis using Raspberry Pi 4 and a faster R-CNN algorithm.

Urban Classification, Not COVID-19 Community Rates, Was Associated With Modes of Learning in US K-12 Schools?

OBJECTIVES

To identify factors associated with the decision to provide in-person, hybrid, and remote learning in kindergarten through 12th grade school districts during the 2020-2021 school year.

METHODS

We performed a retrospective study evaluating school district mode of learning and community coronavirus 2019 (COVID-19) incidence and percentage positivity rates at 3 time points during the pandemic: (1) September 15, 2020 (the beginning of the school year, before Centers for Disease Control and Prevention guidance); (2) November 15, 2020 (midsemester after the release of Centers for Disease Control and Prevention guidance and an increase of COVID-19 cases); and (3) January 15, 2021 (start of the second semester and peak COVID-19 rates). Five states were included in the analysis: Michigan, Missouri, North Carolina, Ohio, and Wisconsin. The primary outcome was mode of learning in elementary, middle, and high schools during 3 time points. The measures included community COVID-19 incidence and percentage positivity rates, school and student demographics, and county size classification of school location.

RESULTS

No relationship between mode of learning and community COVID-19 rates was observed. County urban classification of school location was associated with mode of learning with school districts in nonmetropolitan and small metropolitan counties more likely to be in-person.

CONCLUSIONS

Community COVID-19 rates did not appear to influence the decision of when to provide in-person learning. Further understanding of factors driving the decisions to bring children back into the classroom are needed. Standardizing policies on how schools apply national guidance to local decision-making may decrease disparities in emergent crises.

Evaluation of Effect of Aluminum Oxide on Flexural Strength and Surface Roughness of Conventional Heat-Cure Denture Base Resin

PURPOSE

Acrylic denture base tends to fracture frequently during their service due to poor strength. The surface roughness of denture base is a critical property because denture base with rough surface will cause accumulation of food particles ,thereby leading plaque retention . Microbes such as candida albicans are seen inhabitating the surface.

MATERIALS AND METHODS

Conventional heat cure denture base reins(DPI) and heat cure denture base resin with incorporation of 15wt% aluminium oxide was studied in two groups with 20 samples each. A mold of size 65 mm × 10 mm × 3 mm (ISO Standard) was obtained by investing brass rectangles. About forty specimens were prepared. Specimens were divided into two groups (n = 20) coded A and B. Group A was the control group (n = 20) without addition of aluminum oxide. Group B was the experimental group (n = 20) with addition of 15 wt % aluminum oxide. All the specimens were stored in distilled water for 14 days. The flexural strength was measured using a three-point bending test in a universal testing machine, and the surface roughness was measured using contact-type profilometer.

RESULTS

Incorporation of 15wt% aluminum oxide leads to a significant increase in flexural strength and surface roughness of conventional heat-cure denture base resin.

The Effect of Joint Surface Preparations and Chemical Surface Treatment on the Transverse Strength of Repaired Denture Base Resin

AIM

The aim of the study is to investigate the effect of joint surface preparations and chemical surface treatment given to prepared surface on the transverse strength of repaired denture base resin.

METHODOLOGY

Two hundred and twenty specimens (DPI India) were randomly allocated into eight groups (n = 10), according to the combination of joint surface preparation (Butt joint, 45° bevel, and rounded joint) and chemical surface treatment (methylene chloride, ethyl acetate, and methyl methacrylate) for 30 and 60 s each. Specimens, after surface treatment, were repaired with self-cured resin (DPI India) and then subjected to 3-point bending test to measure transverse strength. Fractured surfaces were viewed under stereomicroscope and subjected to AutoCAD analysis to determine type of failure (adhesive or cohesive) and measure their area. Measurement data were analyzed by one-way analysis of variance, paired t-test, Dunnett's D test, and multiple comparison Bonferroni t-test, with a 5% significance level.

RESULTS

Most of the comparisons between the test specimens were statistically significant. Specimens (methylene chloride for 60 s and rounded joint) show 60%-70% gain of strength.

CONCLUSIONS

For providing better bond strength to a repaired specimen, the segment of fractured specimens to be provided "Rounded joint" preparation with etching by methylene chloride for 60 s.

Prediction of Breast Cancer Using Extremely Randomized Clustering Forests (ERCF) Technique

cancer in breast indeed a significant public health concern in both developed and developing countries female population. It is almost one in three cancers diagnosed in all women. Data mining and pattern recognition applications in conjunction have been proven to be quite useful and relevant to extract the information useful for the medical purpose. This research work reflects the work based on Extremely Randomized Clustering Forests (ERCF) technique which is nothing but a type of pattern recognition technique that may be implemented as the prediction model for Breast Cancer (BC). The accuracy achieved through ERCF has also been compared with that of k-NN(Correlation) and k-NN(Euclidean) in this research work (where k-NN refers to k-Nearest Neighbours technique) and thereafter, final conclusions have been drawn depending upon the testing attributes. The results show that the accuracy of ERCF in the forecasting of breast cancer is so much larger than that of the exactness of k-NN(Correlation) and k-NN(Euclidean). Hence, ERCF, a randomized technique for pattern classification, is best

Clinical usefulness of eosinopenia in differentiating COVID-19 versus other flu-like illness in outpatient set-up

Introduction and Aim:Corona virus disease 2019 (Covid-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 has affected over 200 countries and territories. The aim of the present study is to evaluate the role of eosinopenia in differentiating COVID-19 suspect from other    flu-like illnesses in an outpatient setting.   Materials and Methods:It was a retrospective case control study in which data of 1252 suspected COVID 19 patients who visited the fever clinic were enrolled. Among this, 701 patients were found to have COVID-19 pneumonia and 551 had other flu-like illnesses. CBC (complete blood count) and CRP(C- reactive protein) were taken in all patients along with chest x-ray as routine protocol.   Results:Among the 701 positive patients, eosinopenia was seen in 527 patients and had a sensitivity of 75.2 % and specificity of 68.6 %. When combined with other lab parameters such as the increased CRP and lymphopenia, the specificity rises up to 78.6 %.   Conclusion:Our study shows that eosinopenia as an independent variable, is a reliable marker to differentiate COVID-19 suspect patients from other flu-like illnesses on outpatient basis, however when combined with other parameters like lymphopenia and CRP the specificity increases further.

Health-related quality of life in patients with chronic obstructive pulmonary disease: A hospital-based study

Background & objectives:

Chronic obstructive pulmonary disease (COPD) adversely affects various functional and structural domains of the lungs, in addition to having an array of extra-pulmonary effects which affect overall well-being of a patient. This study was aimed at measuring the health-related quality of life (HRQOL) in COPD patients and relating the severity of disease and other factors with the degree of impairment of HRQOL.

Methods:

This cross-sectional study was conducted on 100 individuals with established COPD aged 45 yr or above. COPD severity was graded based on the Global Initiative for Obstructive Lung Disease (GOLD) staging system. Pulmonary function test was carried out as per the American Thoracic Society and European Respiratory Society task force standardised lung function testing guidelines. The quality of life was measured using the COPD-specific version of the St. George's Respiratory Questionnaire (SGRQ). The three component scores (activity, impact and symptoms) and the total score were compared across the various categories of age, gender and COPD grades. Using multivariable linear regression analysis, the relationship between COPD grades and various component scores, adjusting for age and gender, was determined.

Results:

The mean total SGRQ Classification score was found to be 48.5±17.1. There was a significant increase in the symptom, activity and impact component scores and the total scores of the participants with worsening of COPD grade. The activity, impact component scores and total score showed an increasing trend with age. However, the values of these three scores were lower in participants in the age group of 56-65 yr in comparison to those in the 45-55 yr age group. There was a significant increase in the symptom component score with increasing age across the study population. The difference in the various scores between males and females was not significant.

Interpretation & conclusions:

HRQOL is impaired in patients with COPD, and it deteriorates with increasing severity of the disease. The onset of COPD at a younger age has a much more significant deterioration of HRQOL, due to the early onset of symptoms and complications. These findings call for better early care and integration of pulmonary rehabilitation programmes into current health policies.

Design of Double Barrier Ceramic Radio Frequency Vacuum Window

Vacuum windows are an essential part of any radio frequency (RF) system which launches/couples RF power from an atmospheric to a vacuum environment. This paper describes the RF design of a double barrier ceramic coaxial vacuum window. Alumina 99.5% pure is considered as ceramic barrier material while inner and outer conductors are oxygen-free copper. As the initial design approach the thickness, slope, depth of ceramic in the conductor is varied and the performance of the window is studied. The design is optimised to achieve the best insertion loss, return loss response for operating frequency range up to 65MHz.

Towards practical implementation of the compressed sensing framework for multi-element synthetic transmit aperture imaging

Compressed sensing (CS) has been adapted to synthetic aperture (SA) ultrasound imaging to improve the frame-rate of the system. Recently, we proposed a novel CS framework using Gaussian under-sampling to reduce the number of receive elements in multi-element synthetic transmit aperture (MSTA) imaging. However, that framework requires different receive elements to be chosen randomly for each transmission, which may add to practical implementation challenges. Modifying the scheme to employ the same set of receive elements for all transmissions of MSTA leads to degradation of the recovered image quality. Therefore, this work proposes a novel sampling scheme based on a genetic algorithm (GA), which optimally chooses the receive element positions once and uses it for all the transmission of MSTA. The CS performance using GA sampling schemes is evaluated against the previously proposed CS framework on in-vitro and in-vivo datasets. The obtained results suggest that not only does the GA-based approach allows the use of the same set of sparse receive elements for each transmit, but also leads to the lowest CS recovery error (NRMSE) and 14% overall improvement in image contrast, in comparison to the previously-proposed Gaussian sampling scheme. Thus, using the CS framework along with GA, can potentially reduce the complexity in implementation of CS-framework to MSTA based systems.

Comparative Analysis of Intelligent Driving and Safety Assistance Systems Using YOLO and SSD Model of Deep Learning

Bad road conditions are one of the main causes of road accidents around the world. These kinds of accidents prove to be fatal as many lives are lost in these accidents that are mainly caused by potholes or distress on surface of roads. This paper suggests a system that will not only help in reducing the chances of these accidents by making the driver aware of the upcoming distress/potholes on the road but also saving the location of these potholes which can be sent to respective authorities so that they can be repaired. The authors have used technologies like image processing, computer vision, deep learning, and internet of things (IoT) to make this happen. It uses a camera mounted in front near windshield that will capture the images which will be further be processed to get the location of the potholes and distress on road. These detected potholes can be projected on a heads-up display (HUD) placed near windshield which will notify the driver of the potholes.

Limbic Encephalitis as a Heralding Manifestation of Primary Sjogren's Syndrome

Sjogren's syndrome (SS) is an autoimmune disorder characterized by lymphocytic and plasma cell infiltration of exocrine glands, resulting in dry mouth and keratoconjunctivitis sicca. The clinical symptoms may range from mucosal dryness to more systemic complaints. We report a 42-year-old man presenting with rapid cognitive decline and memory impairment for 2 months. Magnetic resonance imaging of the cranium revealed abnormal signals at the bilateral medial temporal lobe and hippocampal region. The autoimmune panel and paraneoplastic antibodies were negative. The patient was labeled as a case of primary SS based on the vasculitis profile and pathological examination of lip biopsy. This case illustrates a rare, heralding manifestation of SS as limbic encephalitis.

Cardiorenal Amyloidosis

Amyloidosis is a conglomeration of diseases due to production and deposition of amyloid, a proteinaceous substance, into organs, tissues, nerves and other places in the body affecting their normal function. This case report is of a 65 year old gentleman, resident of Bihar admitted with a short history of two months. He came with chief complaints of swelling in both lower limbs associated with heaviness in legs, shortness of breath, dizziness, fatigue and passage of frothy urine for two months. He was investigated and found to have proteinuria, low voltage ECG, Echocardiography showed left ventricular hypertrophy, diastolic dysfunction, mitral regurgitation. Cardiac MRI showed dilated cardiomyopathy due to amyloidosis.

Performance optimization of test facility for coaxial transmission line components based on traveling wave resonator

As part of development program for a high power co-axial transmission line component test facility, an existing traveling wave resonator based test stand is modified to improve power gain and ring return loss. The 10 dB directional coupler in the earlier test stand is replaced with a 14 dB directional coupler to couple radio frequency power with the ring. To achieve an improved isolation and return loss, the 14 dB directional coupler design is equipped with two broadside strip-lines with a tunable gap between them. Detailed design and optimization of the 14 dB directional coupler with and without the traveling wave resonator setup is performed using a high frequency simulator Computer Simulation Technology Microwave Studio. The low power test of the fabricated directional coupler is performed at several tuning positions to achieve an optimum operating frequency for the traveling wave resonator. Furthermore, after optimization, the maximum power gain of around 18 dB and minimum return loss of about -22 dB inside the ring are obtained. Finally, a preliminary study of the future 3 MW test facility is discussed.

Detection and identification of COVID -19 based on chest medical image by using convolutional neural networks

Covid-19 pandemic has caused major out-break all around the world. This pandemic out-break requires lot of testing, which is a tedious process. Deep learning is a successful method that has evolved in image category in the past few years. In this work to detects the presence of coronavirus by using deep learning approach. Here, convolutional neural networks with specific focus on to classify Covid-19 chest radiography images. The database comprises Covid-19, normal and viral pneumonia chest X-ray images with 800 different samples under each class. We evaluated the model on 500 images and the networks has achieved a sensitivity rate of 95% and specificity rate of 97%. The DenseNet121 Architecture performed slightly better, compared to other state of art networks. The performance achieved by the method proposed is very encouraging and the accuracy rates can be improved further with larger datasets. Apart from sensitivity and specificity rates, the proposed model is also compared on receiver operating characteristic (ROC), and area under the curve (AUC) of each model. The model is implemented on the TensorFlow framework with the datasets that are publicly available for research community.

Duodenal variceal bleeding with large SPSS treated with transjugular intrahepatic portosystemic shunt and embolization: A case report

BACKGROUND

Duodenal variceal bleeding is a rare cause of gastrointestinal bleeding. The most common site is the duodenal bulb. It is usually detected endoscopically but it can be very challenging to diagnose if it is located distal to the second part of duodenum. The pre- transjugular intrahepatic portosystemic shunt (TIPS) presence of SPSS was found to be associated with an increased risk of early morbidity and mortality after TIPS placement.

CASE SUMMARY

A 43-year-old cirrhotic male presented with melena for three days. Upper endoscopy was performed and showed active blood oozing from the distal duodenum concerning for ectopic duodenal varix. A computed tomography (CT) angiogram was performed and showed an enlarged cluster of venous collaterals around the distal duodenum. He underwent TIPS placement. He had another episode of melena three days later. Push enteroscopy with injection sclerotherapy into the duodenal varices was performed with no success. A repeat CT angiogram showed occluded TIPS shunt. Therefore, a TIPS revision was performed and there was an extensive portal venous thrombosis with a large shunt between the inferior mesenteric vein and left renal vein via the left gonadal vein. Thrombectomy and TIPS shunt balloon angioplasty was performed, followed by embolization of the portosystemic. The melena was resolved, and patient was discharged with arranged hepatology follow up.

CONCLUSION

It important to look and embolize the SPSS shunts in patients with early TIPS dysfunction and recurrent duodenal variceal bleeding.

Lateral Resolution Improvement in Ultrasound Imaging System using Compressed Sensing: Initial Results

Compressed-Sensing (CS) has been applied to ultrasound imaging to reduce data or to reduce the data acquisition time. There appears to be no report that uses CS framework to reduce the number of active receive elements in Conventional Focused Beamforming (CFB). Thus, in our previous work, a novel undersampling scheme based on Gaussian distribution was investigated and reported for reducing the number of active receive elements and data in CFB. In this paper, we exploit the Gaussian sampling based CS framework to improve the lateral resolution (LR) of the ultrasound system without increasing the system's complexity and cost. A notable difference from our previous work being the use of waveatom as the sparsifying basis, instead of 2D-Fourier basis, and analysis of the proposed framework for different receive aperture sizes. Simulation data for this study were generated using Field II, and experimental data were acquired from an in-vitro cyst phantom using Verasonics V-64 ultrasound scanner. The results indicate that the proposed framework of choosing a limited number of receive elements from a receive aperture length that is three or four times the corresponding active aperture size obtained from the same number of consecutive receive elements yields nearly twice an improvement in LR and about 27% increase in contrast to that of CFB reference image. Thus, the findings suggest a possibility to improve the LR of the current ultrasound system without increasing the system complexity, which will be significant for affordable point-of-care ultrasound systems.

Disorganization of Retinal Inner Layers (DRIL) and Neuroretinal Dysfunction in Early Diabetic Retinopathy

Purpose

To elucidate the relationship between disorganization of retinal inner layers (DRILs) and retinal function in diabetic patients without diabetic retinopathy (DR) and with nonproliferative DR, but without diabetic macular edema (DME).

Methods

Fifty-seven participants with diabetes mellitus (DM) and 18 healthy controls underwent comprehensive ophthalmic examination, fundus photography, and spectral-domain optical coherence tomography. Scans of the fovea were evaluated for the presence of DRIL. Retinal function was evaluated using Early Treatment Diabetic Retinopathy Study (ETDRS) visual acuity, the quick contrast sensitivity function (qCSF) on the AST Sentio Platform, short-wavelength automated perimetry (SWAP), standard automated perimetry (SAP), and frequency doubling perimetry (FDP). ANOVA and Kruskal-Wallis were used to compare retinal function in subjects with and without DRIL. Tukey-Kramer test and Wilcoxon were used for post hoc analysis.

Results

DRIL was identified in 9 of 57 diabetic subjects. DRIL subjects had higher body mass index and longer diabetes duration compared to diabetic subjects without DRIL (P = 0.03 and P = 0.009, respectively). Subjects with DRIL had reduced ETDRS visual acuity (P = 0.003), contrast sensitivity function (P = 0.0003), and SAP performance (PSD, P < 0.0001) compared to controls and diabetic subjects without DRIL. Structural analysis revealed inner retinal thinning, and some outer retinal thinning, associated with DRIL.

Conclusions

Diabetic subjects with DRIL have reduced retinal function compared to those without DRIL, and defective retinal lamination may be an early cellular consequence of diabetes responsible for this in some patients. Following further longitudinal studies, DRIL may be a readily available and reliable structural biomarker for reduced retinal function in early diabetic neuroretinal disease.

Intra-arterial ampicillin and gentamicin and the incidence of splenic abscesses following splenic artery embolization: A 20-year case control study

PURPOSE

Splenic abscesses represent a major complication following splenic artery embolization. The purpose of this study was to assess the effectiveness of intra-arterial antibiotics administered during splenic artery embolization in reducing splenic abscess formation.

MATERIALS AND METHODS

406 patients were screened. 313 (77.1%) patients who underwent splenic artery embolization and were >18 years old were included. Mean age of the cohort was 58 ± 15 years (range: 18-88 years). There were 205 (65.5%) male patients and 108 (34.5%) female patients. 197 (62.9%) patients underwent embolization without intra-arterial antibiotics and 116 (37.1%) patients underwent embolization with 1 g ampicillin and 80 mg gentamicin administered in an intra-arterial fashion. Primary outcome was splenic abscess formation. Secondary outcomes included type of splenic artery embolization, embolic agent, and technical success.

RESULTS

Partial splenic embolization was performed in 229 (73.1%) patients. Total splenic embolization was performed in 84 (26.8%) patients. Platinum coils were the most commonly used embolic agent overall (n = 178; 56.9%) followed by particulates (n = 114; 36.4%). Embolization technical success was achieved in 312 (99.7%) patients. 7 (3.6%) splenic abscesses were detected in the non-intra-arterial antibiotic group and 1 (0.9%) in the intra-arterial antibiotic cohort (P = 0.27). Coils were found to be statistically more likely to result in splenic abscesses than any other embolic agent (P = 0.03). Mean time to abscess identification was 74 days ±120 days (range: 9-1353 days).

CONCLUSION

Splenic abscesses occurred more frequently in patients who did not receive intra-arterial antibiotics during splenic embolization; however, this did not reach statistical significance.

Reinforcing mitochondrial functions in aging brain: An insight into Parkinson's disease therapeutics

Mitochondria, the powerhouse of the neural cells in the brain, are also the seat of certain essential gene signaling pathways that control neuronal functions. Deterioration of mitochondrial functions has been widely reported in normal aging as well as in a spectrum of age-associated neurological diseases, including Parkinson's disease (PD). Evidences accumulated in the recent past provide not only advanced information on the causes of mitochondrial bioenergetics defects and redox imbalance in PD brains, but also much insight into mitochondrial biogenesis, quality control of mitochondrial proteins, and genes, which regulate intra- and extra-mitochondrial signaling that control the general health of neural cells. The mitochondrial quality control machinery is affected in aging and especially in PD, thus affecting intraneuronal protein transport and degradation, which are primarily responsible for accumulation of misfolded proteins and mitochondrial damage in sporadic as well as familial PD. Essentially we considered in the first half of this review, mitochondria-based targets such as mitochondrial oxidative stress and mitochondrial quality control pathways in PD, relevance of mitochondrial DNA mutations, mitophagy, mitochondrial proteases, mitochondrial flux, and finally mitochondria-based therapies possible for PD. Therapeutic aspects are considered in the later half and mitochondria-targeted antioxidant therapy, mitophagy enhancers, mitochondrial biogenesis boasters, mitochondrial dynamics modulators, and gene-based therapeutic approaches are discussed. The present review is a critical assessment of this information to distinguish some exemplary mitochondrial therapeutic targets, and provides a utilitarian perception of some avenues for therapeutic designs on identified mitochondrial targets for PD, a very incapacitating disorder of the geriatric population, world over.