Evaluation of soil texture classification from orthodox interpolation and machine learning techniques

The current investigation examines the effectiveness of various approaches in predicting the soil texture class (clay, silt, and sand contents) of the Rawalpindi district, Punjab province, Pakistan. The employed techniques included artificial neural networks (ANNs), kriging, co-kriging, and inverse distance weighting (IDW). A total of 44 soil specimens from depths of 10-15 cm were gathered, and then the hydrometer method was adopted to measure their texture. The map of soil grain sets was formulated in the ArcGIS environment, utilizing distinct interpolation approaches. The MATLAB software was used to evaluate soil texture. The gradient fraction, latitude and longitude, elevation, and soil texture fragments of points were proposed to an ANN. Several statistical values, such as correlation coefficient (R), geometric mean error ratios (GMER), and root mean square error (RMSE), were utilized to evaluate the precision of the intended techniques. In assessing grain size and spatial dissemination of clay, silt, and sand, the effectiveness and precision of ANN were superior compared to kriging, co-kriging, and inverse distance weighting. Still, less than a 50% correlation was observed using the ANN. In this examination, the IDW had inferior precision compared to the other approaches. The results demonstrated that the practices produced acceptable results and can be used for future research. Soil texture is among the most central variables that can manipulate agriculture plans. The prepared maps exhibiting the soil texture groups are imperative for crop yield and pastoral scheduling.

Effects of hydraulic retention time and cultivation on nutrients removal and biomass production in wastewater by membrane photobioreactor: Modeling and optimization by machine learning and response surface methodology

Discharge of excess nutrients in wastewater can potentially cause eutrophication and poor water quality in the aquatic environment. A new approach of nutrients removal in wastewater is by utilizing microalgae which grow by absorbing CO2 from air. Furthermore, the use of membrane photo-bioreactor (MPBR) that combines membranes and photo-bioreactor has emerged as a novel wastewater treatment method. This research sought to model, forecast, and optimize the behavior of dry biomass, dissolved inorganic nitrogen (DIN), and dissolved inorganic phosphorus (DIP) in MPBR by response surface methodology (RSM) and artificial neural network (ANN) algorithms, which saved time and resources of experimental work. The independent variables that have been used for modeling were hydraulic retention time (HRT) and cultivation. For this purpose, the dry biomass of algal production, DIN and DIP behavior were modeled by RSM and ANN algorithms, to identify the optimum mode of processing. RSM modeling has shown good agreement with experimental data. According to RSM optimization, the optimum mode for DIN and DIP occurred at 1.15 days of HRT and 1.92 days of cultivation. The ANN showed better performance than the RSM model, with the margin of deviation being less than 10%. Furthermore, the ANN algorithm showed higher accuracy than RSM method in predicting the dry biomass, DIN and DIP behavior in MPBR.

Societal knowledge, attitude, and practices towards dengue and associated factors in epidemic-hit areas: Geoinformation assisted empirical evidence

Dengue is one of Pakistan's major health concerns. In this study, we aimed to advance our understanding of the levels of knowledge, attitudes, and practices (KAPs) in Pakistan's Dengue Fever (DF) hotspots. Initially, at-risk communities were systematically identified via a well-known spatial modeling technique, named, Kernel Density Estimation, which was later targeted for a household-based cross-sectional survey of KAPs. To collect data on sociodemographic and KAPs, random sampling was utilized (n = 385, 5 % margin of error). Later, the association of different demographics (characteristics), knowledge, and attitude factors-potentially related to poor preventive practices was assessed using bivariate (individual) and multivariable (model) logistic regression analyses. Most respondents (>90 %) identified fever as a sign of DF; headache (73.8 %), joint pain (64.4 %), muscular pain (50.9 %), pain behind the eyes (41.8 %), bleeding (34.3 %), and skin rash (36.1 %) were identified relatively less. Regression results showed significant associations of poor knowledge/attitude with poor preventive practices; dengue vector (odds ratio [OR] = 3.733, 95 % confidence interval [CI ] = 2.377-5.861; P < 0.001), DF symptoms (OR = 3.088, 95 % CI = 1.949-4.894; P < 0.001), dengue transmission (OR = 1.933, 95 % CI = 1.265-2.956; P = 0.002), and attitude (OR = 3.813, 95 % CI = 1.548-9.395; P = 0.004). Moreover, education level was stronger in bivariate analysis and the strongest independent factor of poor preventive practices in multivariable analysis (illiterate: adjusted OR = 6.833, 95 % CI = 2.979-15.672; P < 0.001) and primary education (adjusted OR = 4.046, 95 % CI = 1.997-8.199; P < 0.001). This situation highlights knowledge gaps within urban communities, particularly in understanding dengue transmission and signs/symptoms. The level of education in urban communities also plays a substantial role in dengue control, as observed in this study, where poor preventive practices were more prevalent among illiterate and less educated respondents.

Rainwater harvesting for agriculture development using multi-influence factor and fuzzy overlay techniques

Rainwater harvesting (RWH) is an essential technique for enhancing agricultural development, particularly in regions facing water scarcity or unreliable rainfall patterns. Water shortage, however, is one of the key causes of low crop production especially in mountainous regions like the Khyber Pakhtunkhwa province where most rainwater is lost by runoff. Therefore, rainwater harvesting could be a suitable to make better use of runoff and increase crop production. The study focuses on selecting suitable rainwater harvesting sites in District Karak to enhance agriculture by utilizing multi-influence factor (MIF) and fuzzy overlay techniques. We considered seven factors, i.e., land use land cover (LULC), slope, geology, soil, rainfall, lineament, drainage density, to create a ranking system to understand its application in site selection analysis. The results were combined into one overlay process to produce a rainwater harvesting suitability map. The weighted overlay analysis of the MIF model results reveals that 167.96 km2 area has a very high potential for rainwater harvesting, 874.17 km2 has a high potential, 1182.92 km2 has a moderate and 354.50 km2 has a poor potential for rainwater harvesting. The fuzzy overlay analysis revealed that 257.53 km2 has a very high potential for rainwater harvesting, 896.56 km2 area is classified as high, 1018.30 km2 moderate, and 407.7 km2 has poor potential for rainwater harvesting. The findings of this research work will help the policymakers and decision-makers construct various rainwater harvesting structures in the study area to overcome the water shortage problems.

The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models

Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increase in population and climate change. Various crop genotypes can survive in harsh climatic conditions and give more production with less disease infection. Remote sensing can play an essential role in crop genotype identification using computer vision. In many studies, different objects, crops, and land cover classification is done successfully, while crop genotypes classification is still a gray area. Despite the importance of genotype identification for production planning, a significant method has yet to be developed to detect the genotypes varieties of crop yield using multispectral radiometer data. In this study, three genotypes of wheat crop (Aas-'2011', 'Miraj-'08', and 'Punjnad-1) fields are prepared for the investigation of multispectral radio meter band properties. Temporal data (every 15 days from the height of 10 feet covering 5 feet in the circle in one scan) is collected using an efficient multispectral Radio Meter (MSR5 five bands). Two hundred yield samples of each wheat genotype are acquired and manually labeled accordingly for the training of supervised machine learning models. To find the strength of features (five bands), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Nonlinear Discernment Analysis (NDA) are performed besides the machine learning models of the Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) and Artificial Neural Network (ANN) with detailed of configuration settings. ANN and random forest algorithm have achieved approximately maximum accuracy of 97% and 96% on the test dataset. It is recommended that digital policymakers from the agriculture department can use ANN and RF to identify the different genotypes at farmer's fields and research centers. These findings can be used for precision identification and management of the crop specific genotypes for optimized resource use efficiency.

Using Sentinel-2 data to estimate the concentration of heavy metals caused by industrial activities in Ust-Kamenogorsk, Northeastern Kazakhstan

This study aims to investigate the change in heavy metal concentration and evaluate pollution intensity using Sentinel-2 data. Sixty samples collected from the surface soil in the area were used to determine the concentration of lead, copper, and zinc using atomic absorption spectroscopy. Then, the step-by-step regression method was used in ArcGIS software to determine the relationship between the concentration of heavy metals and the ranking of the influential spectral bands of Sentinel-2 to monitor heavy metals in the relevant sampling points. According to the results, lead monitoring was effective through the blue channel, the ratio of green to near infrared-IV channels, and the ratio of short-wave infrared-III to near infrared-II channels. At the same time, copper was monitored through reflectance values in the red channel, the ratios of green to near infrared-IV channels, and the ratio of short-wave infrared-III to near infrared-II channels. The blue channel and the ratio of green to near infrared-IV channels the ratio of near infrared-II to near infrared-IV channels were efficient for zinc monitoring. Pollution Load Indices (PLI) and Geographical Accumulation Index (Igeo) were calculated to classify the contaminated soils of the region. The efficiency of each relationship obtained was evaluated using the root mean square error (RMSE) and Pearson's correlation coefficient (R). In summary, the copper, lead, and zinc equations had RMSE values of 1.8, 2.5, and 1.60 mg/kg, respectively. The Pearson correlation coefficients (R) for copper, lead, and zinc were 0.80, 0.76, and 0.72, respectively, which indicated good agreement between measured and estimated values.

Comprehensive genomic analysis of Bacillus paralicheniformis strain BP9, pan-genomic and genetic basis of biocontrol mechanism

Many Bacillus species are essential antibacterial agents, but their antibiosis potential still needs to be elucidated to its full extent. Here, we isolated a soil bacterium, BP9, which has significant antibiosis activity against fungal and bacterial pathogens. BP9 improved the growth of wheat seedlings via active colonization and demonstrated effective biofilm and swarming activity. BP9 sequenced genome contains 4282 genes with a mean G-C content of 45.94% of the whole genome. A single copy concatenated 802 core genes of 28 genomes, and their calculated average nucleotide identity (ANI) discriminated the strain BP9 from Bacillus licheniformis and classified it as Bacillus paralicheniformis. Furthermore, a comparative pan-genome analysis of 40 B. paralicheniformis strains suggested that the genetic repertoire of BP9 belongs to open-type genome species. A comparative analysis of a pan-genome dataset using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of Orthologous Gene groups (COG) revealed the diversity of secondary metabolic pathways, where BP9 distinguishes itself by exhibiting a greater prevalence of loci associated with the metabolism and transportation of organic and inorganic substances, carbohydrate and amino acid for effective inhabitation in diverse environments. The primary secondary metabolites and their genes involved in synthesizing bacillibactin, fencing, bacitracin, and lantibiotics were identified as acquired through a recent Horizontal gene transfer (HGT) event, which contributes to a significant part of the strain`s antimicrobial potential. Finally, we report some genes essential for plant-host interaction identified in BP9, which reduce spore germination and virulence of multiple fungal and bacterial species. The effective colonization, diverse predicted metabolic pathways and secondary metabolites (antibiotics) suggest testing the suitability of strain BP9 as a potential bio-preparation in agricultural fields.

A series of spatio-temporal analyses and predicting modeling of land use and land cover changes using an integrated Markov chain and cellular automata models

For sustainable land cover planning, spatial land cover models are essential. Deforestation, loss of agriculture, and conversion of pasture land to urban and industrial uses are only some of the negative consequences of human kind's insatiable need for more land. Using remote sensing multi-temporal data, spatial criteria, and prediction models can effectively monitor these changes and plan for sustainable land use. This research aims to predict the land use and land cover (LULC) with cellular automata (CA) and Markov chain models. Landsat TM, ETM + , and OLI/TIRS data were used for mapping LULC distributions for the years 1990, 2006, and 2022. A CA-Markov chain was developed for simulating long-term landscape changes at 16-year time steps from 2022 to 2054. Analysis of urban sprawl was carried out by using the support vector machine (SVM). Through the CA-Markov chain analysis, we expect that built-up area will grow from 285.68 km² (22.59%) to 383.54 km² (30.34%) in 2022 and 2054, as inferred from the changes that occurred from 1990 to 2022. Therefore, substantial deforestation area reduction will result if existing tendencies in change continue despite sustainable development efforts. The findings of this research can inform land cover management strategies and assist local authorities in preparing for the present and the future. They can balance expanding the city and preserving its natural resources.

Land subsidence analysis using synthetic aperture radar data

Land subsidence is considered a threat to developing cities and is triggered by several natural (geological and seismic) and human (mining, groundwater withdrawal, oil and gas extraction, constructions) factors. This research has gathered datasets consisting of 80 Sentinel-1A ascending and descending SLC images from July 2017 to July 2019. This dataset, concerning InSAR and PS-InSAR, is processed with SARPROZ software to determine the land subsidence in Gwadar City, Balochistan, Pakistan. Later, the maps were created with ArcGIS 10.8. Due to InSAR’s limitations in measuring millimeter-scale surface deformation, Multi-Temporal InSAR techniques, like PS-InSAR, are introduced to provide better accuracy, consistency, and fewer errors of deformation analysis. This remote-based SAR technique is helpful in the Gwadar area; for researchers, city mobility is constrained and has become more restricted post-Covid-19. This technique requires multiple images acquired of the same place at different times for estimating surface deformation per year, along with surface uplifting and subsidence. The InSAR results showed maximum deformation in the Koh-i-Mehdi Mountain from 2017 to 2019. The PS-InSAR results showed subsidence up to −92 mm/year in ascending track and −66 mm/year in descending track in the area of Koh-i-Mehdi Mountain, and up to −48 mm/year in ascending track and −32 mm/year in descending track in the area of the deep seaport. From our experimental results, a high subsidence rate has been found in the newly evolving Gwadar City. This city is very beneficial to the country’s economic development because of its deep-sea port, developed by the China-Pakistan Economic Corridor (CPEC). The research is associated with a detailed analysis of Gwadar City, identifying the areas with significant subsidence, and enlisting the possible causes that are needed to be resolved before further developments. Our findings are helpful to urban development and disaster monitoring as the city is being promoted as the next significant deep seaport with the start of CPEC.

Modeling spatio-temporal assessment of land use land cover of Lahore and its impact on land surface temperature using multi-spectral remote sensing data

Urban sprawl, also widely known as urbanization, is one of the significant problems in the world. This research aims to assess and predict the urban growth and impact on land surface temperature (LST) of Lahore as well as land use and land cover (LULC) with a cellular automata Markov chain (CA-Markov chain). LULC and LST distributions were mapped using Landsat (5, 7, and 8) data from 1990, 2004, and 2018. Long-term changes to the landscape were simulated using a CA-Markov model at 14-year intervals from 2018 to 2046. Results indicate that the built-up area was increased from 342.54 (18.41%) to 720.31 (38.71%) km². Meanwhile, barren land, water, and vegetation area was decreased from 728.63 (39.16%) to 544.83 (29.28%) km², from 64.85 (3.49%) to 34.78 (1.87%) km², and from 724.53 (38.94%) to 560.63 (30.13%) km², respectively. In addition, urban index, a non-vegetation index, accurately predicted LST, showing the maximum correlation R² = 0.87 with respect to retrieved LST. According to CA-Markov chain analysis, we can predict the growth of built-up area from 830.22 to 955.53 km² between 2032 and 2046, based on the development from 1990 to 2018. As urban index as the predictor anticipated that the LST 20-23 °C and 24-27 °C, regions would all decline in coverage from 5.30 to 4.79% and 15.79 to 13.77% in 2032 and 2046, while the temperature 36-39 °C regions would all grow in coverage from 15.60 to 17.21% of the city. Our results indicate severe conditions, and the authorities should consider some strategies to mitigate this problem. These findings are significant for the planning and development division to ensure the long-term usage of land resources for urbanization expansion projects in the future.

Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data

The present study is designed to monitor the spatio-temporal changes in forest cover using Remote Sensing (RS) and Geographic Information system (GIS) techniques from 1990 to 2017. Landsat data from 1990 (Thematic mapper [TM]), 2000 and 2010 (Enhanced Thematic Mapper [ETM+]), and 2013 to 2017 (Operational Land Imager/Thermal Infrared Sensor [OLI/TIRS]) were classified into the classes termed snow, water, barren land, built-up area, forest, and vegetation. The method was built using multitemporal Landsat images and the machine learning techniques Support Vector Machine (SVM), Naive Bayes Tree (NBT) and Kernel Logistic Regression (KLR). According to the results, forest area was decreased from 19,360 km² (26.0%) to 18,784 km² (25.2%) from 1990 to 2010, while forest area was increased from 18,640 km² (25.0%) to 26,765 km² (35.9%) area from 2013 to 2017 due to "One billion tree Project". According to our findings, SVM performed better than KLR and NBT on all three accuracy metrics (recall, precision, and accuracy) and the F1 score was >0.89. The study demonstrated that concurrent reforestation in barren land areas improved methods of sustaining the forest and RS and GIS into everyday forestry organization practices in Khyber Pakhtun Khwa (KPK), Pakistan. The study results were beneficial, especially at the decision-making level for the local or provincial government of KPK and for understanding the global scenario for regional planning.

Efficacy of pentamidine-loaded chitosan nanoparticles as a novel drug delivery system for Leishmania tropica

The present study compares the in vitro effects of nanoparticles loaded pentamidine drug and conventional pentamidine on Leishmania tropica. Herein, pentamidine-loaded chitosan nanoparticles (PTN-CNPs) have been synthesized through an ionic gelation method with sodium tripolyphosphate (TPP). Next, the physical characteristics of PTN-CNPs were determined through the surface texture, zeta potential, in vitro drug release, drug loading content (DLC), and encapsulation efficacy (EE) and compared its efficacy with free pentamidine (PTN) drug against promastigotes and axenic amastigotes forms of L. tropica in vitro. The PTN-CNPs displayed a spherical shape having a size of 88 nm, an almost negative surface charge (-3.09 mV), EE for PTN entrapment of 86%, and in vitro drug release of 92% after 36 h. In vitro antileishmanial activity of PTN-CNPs and free PTN was performed against Leishmania tropica KWH23 promastigote and axenic amastigote using 3-(4, 5- dimethylthiazol-2-yl)-2, 5-diphenyletetrazolium bromide (MTT) assay. It was observed that the effect of PTN-CNPs and free PTN on both forms of the parasite was dose and time dependent. Free PTN presented low efficacy even at higher dose (40 µg/ml) with 25.6 ± 1.3 and 26.5 ±1.4 mean viability rate of the promastigotes and axenic amastigotes, respectively after 72 hrs incubation. While PTN-CNPs showed strong antileishmanial effects on both forms of parasite with 16 ± 0.4 and 19 ± 0.7 mean viability rate at the same higher concentration (40 µg/ml) after 72 hrs incubation. Half maximal inhibitory concentration (IC50) values of PTN-CNPs toward promastigotes and amastigotes were obtained as 0.1375 µg/ml and 0.1910 µg/ml, respectively. In conclusion, PTN-CNPs effectively inhibited both forms of the L. tropica; however, its effect was more salient on promastigotes. This data indicates that the PTN-CNPs act as a target drug delivery system. However, further research is needed to support its efficacy in animal and human CL.

Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan

This research aims to assess the urban growth and impact on land surface temperature (LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical information system (GIS) and remote sensing (RS) techniques (maximum likelihood classification (MLC)) LST, and different normalized satellite indices have been implemented to analyse the spatio-temporal trends of Lahore city; by using Landsat for 1990, 2004, and 2018. The development of integrated use of RS and GIS and combined cellular automata-Markov models has provided new means of assessing changes in land use and land cover and has enabled the projection of trajectories into the future. Results indicate that the built-up area and bare area increased from 15,541 (27%) to 23,024 km² (40%) and 5756 km² (10%) to 13,814 km² (24%). Meanwhile, water area and vegetation were decreased from 2302 km² (4%) to 1151 km² (2%) and 33,961 km² (59%) to 19,571 km² (34%) respectively. Under this urbanization, the LST of the city was also got affected. In 1990, the mean LST of most of the area was between 14 and 28 ℃, which rose to 22-28 ℃ in 2004 and 34 to 36 ℃ in 2018. Because of the shift of vegetation and built-up land, the surface reflectance and roughness of each land use land cover (LULC) class are different. The analysis established a direct correlation between Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI) with LST and an indirect correlation among Soil Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI), and Built-up Index (BI) with LST. The results are important for the planning and development department since they may be used to guarantee the sustainable utilization of land resources for future urbanization expansion projects.

An Investigation of Vascular Endothelial Growth Factor (VEGFR-1 and VEGFR-2) in Burn Wound Healing

Burn damage is a complicated trauma that causes local and general tissue edema as a result of cell breakage and capillary leak syndrome. Angiogenesis plays a key part in the mechanisms that are initiated by tissue damage (e.g., burns) since it works directly and precisely on endothelial cells. The primary mediators of angiogenesis are vascular endothelial growth factor (VEGF) and its receptors (VEGFR-1 and VEGFR-2). This study aimed to figure out what functions VEGF and its receptors play in wound healing after burn, and the systemic release of VEGF in people following severe burn damage. This study included 23 burnt adult serum and 20 healthy controls. The enzyme-linked immunosorbent test was used to assess circulating VEGF serum levels and its receptors (VEGFR-1 and VEGFR-2). VEGF serum levels were considerably higher in this study, compared to VEGF levels in healthy controls. The levels of VEGFR-1 and VEGFR-2 have significantly risen; moreover, VEGF and its receptors have a significant impact on edema-related problems in severely burned individuals. Burn is a frequent disease that damages the skin and induces the production of mediators that cause neovasculature in the majority of patients. VEGF, which causes vasculogenesis and angiogenesis, is one of the most important factors in the skin.

Adaptive Machine Learning Based Distributed Denial-of-Services Attacks Detection and Mitigation System for SDN-Enabled IoT

The development of smart network infrastructure of the Internet of Things (IoT) faces the immense threat of sophisticated Distributed Denial-of-Services (DDoS) security attacks. The existing network security solutions of enterprise networks are significantly expensive and unscalable for IoT. The integration of recently developed Software Defined Networking (SDN) reduces a significant amount of computational overhead for IoT network devices and enables additional security measurements. At the prelude stage of SDN-enabled IoT network infrastructure, the sampling based security approach currently results in low accuracy and low DDoS attack detection. In this paper, we propose an Adaptive Machine Learning based SDN-enabled Distributed Denial-of-Services attacks Detection and Mitigation (AMLSDM) framework. The proposed AMLSDM framework develops an SDN-enabled security mechanism for IoT devices with the support of an adaptive machine learning classification model to achieve the successful detection and mitigation of DDoS attacks. The proposed framework utilizes machine learning algorithms in an adaptive multilayered feed-forwarding scheme to successfully detect the DDoS attacks by examining the static features of the inspected network traffic. In the proposed adaptive multilayered feed-forwarding framework, the first layer utilizes Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), k-Nearest Neighbor (kNN), and Logistic Regression (LR) classifiers to build a model for detecting DDoS attacks from the training and testing environment-specific datasets. The output of the first layer passes to an Ensemble Voting (EV) algorithm, which accumulates the performance of the first layer classifiers. In the third layer, the adaptive frameworks measures the real-time live network traffic to detect the DDoS attacks in the network traffic. The proposed framework utilizes a remote SDN controller to mitigate the detected DDoS attacks over Open Flow (OF) switches and reconfigures the network resources for legitimate network hosts. The experimental results show the better performance of the proposed framework as compared to existing state-of-the art solutions in terms of higher accuracy of DDoS detection and low false alarm rate.

Strawberry Fungal Leaf Scorch Disease Identification in Real-Time Strawberry Field Using Deep Learning Architectures

Plant health is the basis of agricultural development. Plant diseases are a major factor for crop losses in agriculture. Plant diseases are difficult to diagnose correctly, and the manual disease diagnosis process is time consuming. For this reason, it is highly desirable to automatically identify the diseases in strawberry plants to prevent loss of crop quality. Deep learning (DL) has recently gained popularity in image classification and identification due to its high accuracy and fast learning. In this research, deep learning models were used to identify the leaf scorch disease in strawberry plants. Four convolutional neural networks (SqueezeNet, EfficientNet-B3, VGG-16 and AlexNet) CNN models were trained and tested for the classification of healthy and leaf scorch disease infected plants. The performance accuracy of EfficientNet-B3 and VGG-16 was higher for the initial and severe stage of leaf scorch disease identification as compared to AlexNet and SqueezeNet. It was also observed that the severe disease (leaf scorch) stage was correctly classified more often than the initial stage of the disease. All the trained CNN models were integrated with a machine vision system for real-time image acquisition under two different lighting situations (natural and controlled) and identification of leaf scorch disease in strawberry plants. The field experiment results with controlled lightening arrangements, showed that the model EfficientNet-B3 achieved the highest classification accuracy, with 0.80 and 0.86 for initial and severe disease stages, respectively, in real-time. AlexNet achieved slightly lower validation accuracy (0.72, 0.79) in comparison with VGGNet and EfficientNet-B3. Experimental results stated that trained CNN models could be used in conjunction with variable rate agrochemical spraying systems, which will help farmers to reduce agrochemical use, crop input costs and environmental contamination.

Involvement of soluble proteins in growth and metabolic adjustments of drought-stressed Calligonum mongolicum seedlings under nitrogen addition

The planting of seedlings is the most effective measure for vegetation restoration. However, this practice is challenging in desert ecosystems where water and nutrients are scarce. Calligonum mongolicum is a sand-fixing pioneer shrub species, and its adaptive strategy for nitrogen (N) deposition and drought is poorly understood. Thus, in a pot experiment, we studied the impacts of four N levels (0, 3, 6, 9 gN·m^-2 ·year^-1 ) under drought or a well-watered regime on multiple eco-physiological responses of 1-year-old C. mongolicum seedlings. Compared to well-watered conditions, drought considerably influenced seedling growth by impairing photosynthesis, osmolyte accumulation and activity of superoxide dismutase and enzymes related to N metabolism. Nitrogen addition improved the productivity of drought-stressed seedlings, as revealed by increased water use efficiency, enhanced superoxide dismutase and nitrite reductase activity and elevated N and phosphorus (P) levels in seedlings. Nevertheless, the addition of moderate to high levels of N (6-9 gN·m^-2 ·year^-1 ) impaired net photosynthesis, osmolyte accumulation and nitrate reductase activity. N addition and water regimes did not markedly change the N:P ratios of aboveground parts; while more biomass and nutrients were allocated to fine roots to assimilate the insufficient resources. Soluble protein in assimilating shoots might play a vital role in adaptation to the desert environment. The response of C. mongolicum seedlings to N addtion and drought involved an interdependency between soluble protein and morphological, physiological and biochemical processes. These findings provide an important reference for vegetation restoration in arid lands under global change.

Role of endophytic Penicillium species and Pseudomonas monteilii in inducing the systemic resistance in okra against root rotting fungi and their effect on some physiochemical properties of okra fruit

AIMS

The efficacy of three isolates of endophytic Penicillium species that have shown significant suppressive effect on root rotting fungi in our previous study were further evaluated in pots and field plot experiments for their effect on root diseases of okra, induction of systemic resistance and physiochemical properties of okra fruit.

METHODS AND RESULTS

Aqueous suspensions of endophytic Penicillium and Pseudomonas monteilii were applied in pots and field plots using okra as test plant. Data on the fungal infection of roots, plant growth, plant resistance markers like polyphenol, salicylic acid and antioxidant status of plant were determined. These isolates significantly suppressed root diseases and induced systemic resistance via increasing level of resistance markers, polyphenol and salicylic acid besides improving antioxidant activity of Penicillium and P. monteilii-treated plants as compared to control plants. GC-MS analysis of n-hexane extract of mycelium of P. nigricans revealed the presence of 15 different volatile compounds.

CONCLUSIONS

Endophytic Penicillium and P. monteilii have potential against root-infecting fungi of okra and can improve plant growth and yield.

SIGNIFICANCE AND IMPACT OF THE STUDY

Endophytic Penicillium species and P. monteilii can suppress root rotting fungi by direct mechanism or induction of systemic resistance in plants.

Perioperative intravenous contrast administration and the incidence of acute kidney injury after major gastrointestinal surgery: prospective, multicentre cohort study

BACKGROUND

This study aimed to determine the impact of preoperative exposure to intravenous contrast for CT and the risk of developing postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery.

METHODS

This prospective, multicentre cohort study included adults undergoing gastrointestinal resection, stoma reversal or liver resection. Both elective and emergency procedures were included. Preoperative exposure to intravenous contrast was defined as exposure to contrast administered for the purposes of CT up to 7 days before surgery. The primary endpoint was the rate of AKI within 7 days. Propensity score-matched models were adjusted for patient, disease and operative variables. In a sensitivity analysis, a propensity score-matched model explored the association between preoperative exposure to contrast and AKI in the first 48 h after surgery.

RESULTS

A total of 5378 patients were included across 173 centres. Overall, 1249 patients (23·2 per cent) received intravenous contrast. The overall rate of AKI within 7 days of surgery was 13·4 per cent (718 of 5378). In the propensity score-matched model, preoperative exposure to contrast was not associated with AKI within 7 days (odds ratio (OR) 0·95, 95 per cent c.i. 0·73 to 1·21; P = 0·669). The sensitivity analysis showed no association between preoperative contrast administration and AKI within 48 h after operation (OR 1·09, 0·84 to 1·41; P = 0·498).

CONCLUSION

There was no association between preoperative intravenous contrast administered for CT up to 7 days before surgery and postoperative AKI. Risk of contrast-induced nephropathy should not be used as a reason to avoid contrast-enhanced CT.

A Modified Technique in Submandubular Salivary Gland Excision: Preservation of Facial Artery

Cutting and ligation of facial artery is the conventional practice for excision of submandibular gland. Facial artery is the main arterial supply to the lower face. Its preservation results in preservation of large proportion of vascularity to the lower face, preserves vascularity of platysma myocutaneous flap, allows repair of lower lip using Bernard's technique; facial artery is one of the most important recipient artery for microvascular free flap in modern reconstructive surgery in head and neck oncology. This prospective study was carried out in Department of Otolaryngology, Bangabandhu Sheikh Mujib Medical University Hospital (BSMMU), Dhaka, Bangladesh from October 2005 to October 2012 on 31 cases. Chronic submandibular sialoadenitis, benign submandibular gland tumours and cases of neck dissection where level I cervical lymph nodes were not involved by metastasis were included in this study. The facial artery was identified proximal to the gland and was dissected free from the gland by ligating or cauterizing its glandular branches to mobilize the gland. Appropriate anatomical aspects were noted and the time required for separation of the artery from the gland was recorded. Thirty-one consecutive cases were studied. The indications were chronic sialoadenitis (67.7%), pleomorphic adenoma (12.9%) and as a part of neck dissection for oncologic clearance of neck (19.4%). The mean duration of time for separation of the artery from the gland was 10.26 minutes. In two cases the facial artery could not be safely separated due to excessive adhesion from chronic inflammation. No significant complications were noted. Preservation of facial artery in submandibular gland excision is a simple procedure. So it should not be routinely sacrificed during this surgery.

Real-time forecasting of epidemic trajectories using computational dynamic ensembles

Forecasting the trajectory of social dynamic processes, such as the spread of infectious diseases, poses significant challenges that call for methods that account for data and model uncertainty. Here we introduce an ensemble model for sequential forecasting that weights a set of plausible models and use a frequentist computational bootstrap approach to evaluate its uncertainty. We demonstrate the feasibility of our approach using simple dynamic differential-equation models and the trajectory of outbreak scenarios of the Ebola Forecasting Challenge. Specifically, we generate sequential short-term forecasts of epidemic outbreaks by combining phenomenological models that incorporate flexible epidemic growth scaling, namely the Generalized-Growth Model (GGM) and the Generalized Logistic Model (GLM). We rely on the root-mean-square error (RMSE) to quantify the quality of the models' fits during the calibration periods for weighting their contribution to the ensemble model while forecasting performance was evaluated using the RMSE of the forecasts. For a given forecasting horizon (1-4 weeks), we report the performance for each model as the percentage of the number of times each model outperforms the other models. The overall mean RMSE performance of the GLM and the GGM-GLM ensemble models outcompeted that of participant models of the Ebola Forecasting Challenge. We also found that the ensemble model provided more accurate forecasts with higher frequency than the GGM and GLM models, but its performance varied across forecasting horizons. For instance, across all of the Ebola Challenge Scenarios, the ensemble model outperformed the other models at horizons of 2 and 3 weeks while the GLM outperformed other models at horizons of 1 and 4 weeks.

Restraining the multidrug efflux transporter STY4874 of Salmonella Typhi by reserpine and plant extracts

Efflux-mediated multidrug resistance is a well-known phenomenon facilitated by multidrug resistant (MDR) transporters. One of the approaches to counteract efflux-mediated resistance is the use of MDR pump inhibitors, and thus be used in combination with the conventional antibiotics to treat deadly diseases like typhoid fever. We have previously reported that STY4874, an efflux transporter of Salmonella serotype Typhi, exhibited promising characteristics as MDR pump. In this study, we aimed to get an insight into possible STY4874 inhibitors of plant origin. STY4874 was overexpressed in Escherichia coli and extracts from pomegranate peel, milk thistle seeds and reserpine, a synthetic plant alkaloid, were screened for inhibition of ciprofloxacin efflux. The extracts of milk thistle seeds and reserpine when incubated with ciprofloxacin showed statistically significant STY4874-mediated inhibitory activity, rendering the efflux pump inactive and hence early growth inhibition of host cells compared with cells expressing efflux pump and incubated only with ciprofloxacin. This efflux pump inhibitory activity was further confirmed by time-kill experiments. This study is the first to report on efflux pump inhibition of S. Typhi STY4874 and results can be extended towards its close homologues such as MdfA and MdtM from E. coli. SIGNIFICANCE AND IMPACT OF THE STUDY: Understanding and combating resistance governed by multidrug efflux transporters is an ongoing research intensive area, affecting treatment of various nosocomial and endemic/epidemic infections. Confronting drug resistance requires that inhibitors debilitating the underlying mechanisms should be included in combination therapy. One such example is the prescription of clavulanic acid as combination therapy with amoxicillin, collectively called as co-amoxiclav to combat β-lactamase-mediated resistance. However, research related to finding the inhibitors of efflux transporters, the resistance mechanism distinct from β-lactamase mediated resistance is at an early stage. The current study finds that plant-derived inhibitors can be an option towards restraining efflux-mediated resistance.

Design challenges for electronic medication administration record systems in residential aged care facilities: a formative evaluation

INTRODUCTION

Electronic medication administration record (eMAR) systems are promoted as a potential intervention to enhance medication safety in residential aged care facilities (RACFs). The purpose of this study was to conduct an in-practice evaluation of an eMAR being piloted in one Australian RACF before its roll out, and to provide recommendations for system improvements.

METHODS

A multidisciplinary team conducted direct observations of workflow (n=34 hours) in the RACF site and the community pharmacy. Semi-structured interviews (n=5) with RACF staff and the community pharmacist were conducted to investigate their views of the eMAR system. Data were analysed using a grounded theory approach to identify challenges associated with the design of the eMAR system.

RESULTS

The current eMAR system does not offer an end-to-end solution for medication management. Many steps, including prescribing by doctors and communication with the community pharmacist, are still performed manually using paper charts and fax machines. Five major challenges associated with the design of eMAR system were identified: limited interactivity; inadequate flexibility; problems related to information layout and semantics; the lack of relevant decision support; and system maintenance issues. We suggest recommendations to improve the design of the eMAR system and to optimize existing workflows.

DISCUSSION

Immediate value can be achieved by improving the system interactivity, reducing inconsistencies in data entry design and offering dedicated organisational support to minimise connectivity issues. Longer-term benefits can be achieved by adding decision support features and establishing system interoperability requirements with stakeholder groups (e.g. community pharmacies) prior to system roll out. In-practice evaluations of technologies like eMAR system have great value in identifying design weaknesses which inhibit optimal system use.

Are soft tissue measurements on lateral cervical spine X-rays reliable in the assessment of traumatic injuries?

INTRODUCTION

Traumatic neck pain is a common presentation to the emergency department. Lateral plain radiographs remain the primary investigation in the assessment of these injuries. Soft tissue assessment forms an integral component of these radiographs. They can provide information on subtle injuries that may not be obvious. Many methods are used to assess the prevertebral soft tissue shadows. The two more commonly used techniques include the 'seven at two and two at seven' rule (method 1) and the ratio of the soft tissues with respect to the vertebral width (method 2).

AIM

To assess which of the above two methods in assessing cervical spine soft tissue shadows on lateral radiographs is more sensitive in the presence of cervical spine injuries.

METHODS

A retrospective analysis of consecutive traumatic cervical spine films performed within a busy trauma tertiary centre over a period of 7 months. Patients were divided into two groups: group 1-fractures; group 2-no fractures. The prevertebral soft tissue shadows were measured at referenced points on the lateral cervical spine films with respect to the above two methods and comparisons between the groups were made.

RESULTS

Thirty-nine patients in group 1 were compared to a control group of 60 patients in group 2. Both methods failed to identify any significant differences between the two groups. The sensitivity and specificity for method 1 was 7.6 and 93 %, and for method 2, they were 7.6 and 98 %, respectively.

CONCLUSION

There is no significant difference between the soft tissue shadows when comparing patients with and without cervical spine fractures on lateral radiographs. Both commonly used measures of soft tissue shadows in clinical practice are insensitive in identifying patients with significant osseous injuries. They, therefore, do not offer any further value in interpreting traumatic cervical spine radiographs. The management of patients with cervical spine trauma in the absence of obvious osseous injury on standard radiographs should warrant a computed tomography (CT) scan if clinically indicated.

Endoscopic dacryocystorhinostomy

Dacryocystorhinostomy (DCR) is the treatment of distal nasolacrimal duct blockage. It has got many advantages of over external DCR with higher patient's acceptance. Twenty one consecutive cases of endoscopic DCR were studied during the period of two and a half years with a mean follow up period of 13.12 months (SD=7.05). The mean age of cases was 42.95 years (SD=14.49). In most of the cases the cause was either idiopathic (71.43%) or inflammatory (23.81%). The techniques used for making bony window were chisel-hammer (19.50%), powered drill (23.81%), Kerrison punch forceps (14.29%) or combination of powered drill and Kerrison punch forceps (42.86%). Silicon stent was used in 71.43% cases. There was no significant peroperative complication; premature extrusion of stent (4.76%), synaechia (9.52%), excessive granulation tissue formation (9.52%) and stomal stenosis with recurrence of symptoms (9.52%) were the complications noticed here. Anatomical success with patent stoma was observed in 90.48% cases but symptomatic improvement with dry comfortable eyes were seen in 86% cases. There was no statistically significant difference of outcome between this study and that of recently published studies (p>0.05). Some comparative studies showed both higher and lower success rates of endoscopic DCR than external procedure but there was no significant difference (p>0.05).

Audit on the success of partner notification for sexually transmitted infections in the West Midlands

The aim of this study is to investigate the success of partner notification (PN) among 13 genitourinary medicine centres in West Midlands. The West Midlands Audit Group conducted a regional audit between June and August 2007. Information on screening and management of patients with chlamydia, gonorrhoea, early syphilis and HIV were collected separately. Participating centres were asked to provide PN details for 10 index patients with each of chlamydia, gonorrhoea, early syphilis and HIV infections. For each index patient with chlamydia or gonorrhoea, 0.54 and 0.44 partners were screened, respectively. Among partners of patients with syphilis and HIV, 24% and 35% were screened, respectively. Only 9% of 311 screened partners were involved in casual partnerships with index patients. Acquisition of more robust targets for PN, better documentation, improved communication between genitourinary (GU) medicine centres, and provider referral may improve the performance of PN for Sexually transmitted infections.

An audit on the management of pelvic inflammatory disease in the West Midlands, UK

The potential complications of pelvic inflammatory disease (PID) make optimizing its management a high priority. A clinical audit of PID against current national management guidelines was conducted in 14 departments of genitourinary medicine in the West Midlands for women presenting with PID between January and December 2005. There were a total of 810 diagnoses of PID made from a total of 49,390 female attendees for that year, giving an incidence of 164 cases per 10,000 attendees. Of these 810 cases, data collection and analysis for this audit were performed on 139. An ofloxacin 400 mg twice daily (b.i.d.) based regimen was prescribed in 91 (65%, 95% confidence interval [CI] 57-73%) cases. Doxycycline 100 mg b. i. d. for 14 days plus metronidazole 400 mg b. i. d. for 5-14 days was prescribed in 44 (32%, 95% CI 25-40%) cases, but a third-generation cephalosporin was only given with this regimen in three cases. Partner notification was performed in 101 (73%, 95% CI 65-79%) cases. A total of 130 male contacts were recorded on the data collection forms, and of these 58 (45%) were traced and 51 (39%), treated. A follow-up appointment was given to 133 (96%, 95% CI 91-98%) women, although in most cases this was for seven days or more, and 104 (78%, 95% CI 67-81%) women attended for follow-up. Adherence to the national guidelines in this cohort of patients did not reach the national standard for choice of treatment regimen nor did it attain the target for proportion of male partners traced. Barriers preventing adherence to the national guidelines need to be explored and appropriate assistance given to physicians to help meet national standards of care.

Epilepsy: public knowledge and attitude in a slum area of Karachi, Pakistan

BACKGROUND

Epilepsy is a common but widely misunderstood illness. Consequently, epileptics suffer from considerable stigmatization in society. Since no studies have detailed the misperceptions about epilepsy in our community, it is not possible to provide focused intervention aimed at eliminating this prejudice.

PURPOSE

To assess the knowledge and attitude regarding epilepsy in an adult population of a Karachi slum area.

METHODS

A face-to-face interview was conducted on 487 consenting adult non-epileptics (305 males; 182 females) who were conveniently sampled. Chi-square test was employed to calculate the variability in knowledge and attitude with demographic and other variables.

RESULTS

In all, 12.5% had never heard about epilepsy. Among the rest, 66.7% identified epilepsy as being non-infectious, while 28.2% were unaware of any treatment available for it. Among the other 71.8%, 62.7% were aware of the existence of anti-epileptic drugs. Religious/spiritual treatment was chosen as the most effective treatment by 33.1%. Males were more likely to identify epilepsy as being non-infectious (p=0.02). Nearly 18% of the respondents would not object to their child marrying an epileptic, 69.5% did not want to socially isolate the epileptics, 83.1% said epileptics could receive academic education, 85.6% said they could perform activities of daily life and 62.4% said they could become useful members of the society. Those who considered epilepsy to be infectious were more likely to carry negative attitudes towards epilepsy (p<0.01 with four attitudes).

CONCLUSIONS

Considerable gaps exist in the community's knowledge about epilepsy. Some of these may explain the prevalence of negative attitudes towards this ailment.

Reducing the risk of gonorrhoea in black Caribbean men: can we identify risk factors?

OBJECTIVES

Grouping patients by self assigned ethnicity may hide intraethnic differences in disease associations and sexual behaviour patterns. The aim of the study was to detect associations between gonorrhoea with differences in ancestry, degree of acculturation, and religious belief in young black Caribbean men, which could subsequently be used to target health promotion interventions.

METHODS

A questionnaire based case-control study of black Caribbean men with gonorrhoea and a community control group without gonorrhoea.

RESULTS

A lesser degree of acculturation, attending a single sex school, increasing numbers of partners, lack of condom use, not being married, and a belief that sex before marriage was not wrong were associated with an increased risk of gonorrhoea. Country of birth and religious belief were not associated with gonorrhoea.

CONCLUSIONS

A number of factors were identified which may be useful in designing healthcare interventions in young black Caribbean men and these differed little from those in other ethnic groups. The healthcare intervention should include advice on reducing the number of partners and increasing the use of condoms.

Audit of official STD returns from genitourinary medicine

We audited the accuracy of KC 60 coding in our department over a two-week period in 1999. Case notes of 400 consecutive new and rebook patients who attended during each of the audit periods were reviewed, and their clinical diagnosis was compared with KC 60 returns entered into the computer and sent to the Department of Health. We concentrated on four KC 60 diagnoses of positive sexually transmitted infections: uncomplicated gonorrhoea (B1) and chlamydia (c4a), first episodes of anogenital warts (C 11 a) and herpes (C 10 a). At the end of the audit, specific recommendations were introduced, aiming at improving accuracy of KC 60 coding, and a re-audit was carried out in 2000, using identical methodology. In the first audit period there were 106 positive diagnoses, of which 41 (38.7%) were not recorded in the KC 60 returns. In the second audit period there were 149 positive diagnoses, of which 20 (13%) were not recorded, showing a significant improvement (Chi square P = 0.0005).

Seroprevalence of hepatitis A immunity in male genitourinary medicine clinic attenders: a case control study of heterosexual and homosexual men

OBJECTIVES

To compare the seroprevalence of hepatitis A in homosexual and heterosexual men to determine their susceptibility to infection and provide guidance for a policy on vaccination.

METHODS

A case-control study design was utilised to compare the risk factors associated with hepatitis A in homosexual and heterosexual men attending a city centre genitourinary medicine clinic. Demographic and sexual behavioural characteristics were included in univariate and multivariate models.

RESULTS

The overall seropositivity rate was 29% with no significant difference between homosexual and heterosexual men. Ethnicity and age were strongly associated with hepatitis A seropositivity in both homosexuals and heterosexuals. A history of sex in a sauna in homosexual men, and being born outside the United Kingdom for heterosexual men, was associated with hepatitis A seropositivity.

CONCLUSIONS

Targeted hepatitis A screening and vaccination of homosexual men attending UK genitourinary medicine clinics is not supported by the results of this study.

Viral sexually transmitted infections: current management strategies

Viral sexually transmitted infections are a major health problem associated with considerable morbidity. This article reviews the current strategies used in the management of infections such as genital warts, genital herpes and molluscum contagiosum. Pros and cons of different treatment regimens have been discussed with an emphasis on a selective approach to therapy. The importance of education, counselling and follow-up is highlighted and issues relating to the associated psychosexual morbidity have been addressed. Treatment of these infections in pregnancy and HIV has also been described.