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The environmental challenges associated with high-power, high-voltage electrified aircraft require a targeted approach with regard to the development of next-generation aerospace electrical insulation. This study reports findings on polyphenylsulfone (PPSU) as a matrix material based on its unique thermal, mechanical, and dielectric properties, filled with hexagonal boron nitride (h-BN) with micron- and nanoscale particulates. The inorganic ceramic filler was selected for its thermally conductive and electrically insulating performance in extreme environments. The main goal was to investigate the dielectric strength and electrical resistance (endurance) to partial discharges (PDs). Since PDs are a leading accelerated degradation phenomenon causing premature failure in organic electrical insulation, the capability of an insulating material to endure PD-induced degradation for the whole (or part of) its design life is of paramount importance. It was observed that incorporation of h-BN micro fillers can significantly improve the PD resistance, even in comparison with insulating materials typically used for electrified transportation, such as corona-resistant Kapton. It was also observed that a suitable combination of micro and nano fillers can also be used as a viable solution to increase the electrical performance and reliability of the avionics insulation components. [ABSTRACT FROM AUTHOR]

Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse discharge sources, making the evaluation of PD data challenging. The reliability of diagnostics for MV cables hinges on the precise interpretation of PD activity. To streamline the repair and maintenance of cables, it becomes crucial to discern and categorize PD types accurately. This paper presents a comprehensive review encompassing the realms of detection, feature extraction, artificial intelligence, and optimization techniques employed in the classification of PD signals/sources. Its exploration encompasses a variety of sensors utilized for PD detection, data processing methodologies for efficient feature extraction, optimization techniques dedicated to selecting optimal features, and artificial intelligence-based approaches for the classification of PD sources. This synthesized review not only serves as a valuable reference for researchers engaged in the application of methods for PD signal classification but also sheds light on potential avenues for future developments of techniques within the context of MV cables. [ABSTRACT FROM AUTHOR]

Headwater in the Indus River in Pakistan is largely dependent on the glaciers located in the northern part of the country, along with other sources such as direct precipitation. Glaciers are a major source of freshwater that provides agriculture and livelihood to millions of people. The hydro-climatic variations in the Gilgit watershed of the Upper Indus basin are poorly investigated scientifically due to high topographical differences, geography, remoteness of the region, and larger variations in climatic conditions. These glaciers are continuously changing due to melting as a consequence of global warming or accumulation due to snowfall/precipitation at higher altitude regions. The study is carried out using remote sensing data to quantify glacier changes in spatiotemporal variability in the past three decades. Five glaciers in the Gilgit region (near the junction of the Hindukush and Karakoram Mountains) with an area of more than 5 square kilometers were selected, namely Phakor, Karamber, East Gammu, Bhort, and Bad-e-Swat glaciers. These glaciers were monitored for changes in their sizes through a cloud-free continuous series of Landsat satellite imagery. The annual climatic trends were studied through spatially interpolated gridded climate data WοrldClim version-1 climate database for 1970–2000, utilized for assessment of meteorological condition by analyzing the variations of minimum and maximum temperature, solar radiation, and precipitation. The temporal variations in five glaciers in the Gilgit watershed are found to be minimal and, thus, are rather stable and show no sign of rapid melting or diminishing. The little variability of glaciers' extent may be attributed to their geographic condition, altitude, topography, and orientation. The mapped glacier classes have been validated to check the accuracy assessment through an error matrix method. The kappa coefficient from the error matrix has been calculated as 84%, which shows a good agreement. The study makes a critical input towards understanding the dynamics of the glacier in the upper Indus catchment's Gilgit watershed. [ABSTRACT FROM AUTHOR]

Alternanthera yellow vein virus (AlYVV), a monopartite begomovirus, has been identified infecting a diverse range of crops and native plants in Pakistan, India, and China. However, distinctive yellow vein symptoms, characteristic of begomovirus infection, were observed on the Ageratum conyzoides weed in Oman, prompting a thorough genomic characterization in this study. The results unveiled a complete genome sequence of 2745 base pairs and an associated betasatellite spanning 1345 base pairs. In addition, Sequence Demarcation Tool analyses indicated the highest nucleotide identity of 92.8% with a previously reported AlYVV-[IN_abalpur_A_17:LC316182] strain, whereas the betasatellite exhibited a 99.8% nucleotide identity with isolates of tomato leaf curl betasatellite. Thus, our findings propose a novel AlYVV Oman virus (AlYVV-OM) variant, emphasizing the need for additional epidemiological surveillance to understand its prevalence and significance in Oman and the broader region. To effectively manage the spread of AlYVV-OM and minimize its potential harm to (agro)ecosystems, future research should focus on elucidating the genetic diversity of AlYVV-OM and its interactions with other begomoviruses. [ABSTRACT FROM AUTHOR]

Pedilanthus leaf curl virus (PeLCV) is a monopartite begomovirus (family Geminiviridae) discovered just a few decades ago. Since then, it has become a widely encountered virus, with reports from ca. 25 plant species across Pakistan and India, indicative of its notable evolutionary success. Viruses mutate at such a swift rate that their ecological and evolutionary behaviors are inextricably linked, and all of these behaviors are imprinted on their genomes as genetic diversity. So, all these imprints can be mapped by computational methods. This study was designed to map the sequence variation dynamics, genetic heterogeneity, regional diversity, phylogeny, and recombination events imprinted on the PeLCV genome. Phylogenetic and network analysis grouped the full-length genome sequences of 52 PeLCV isolates into 7 major clades, displaying some regional delineation but lacking host-specific demarcation. The progenitor of PeLCV was found to have originated in Multan, Pakistan, in 1977, from where it spread concurrently to India and various regions of Pakistan. A high proportion of recombination events, distributed unevenly throughout the genome and involving both inter- and intraspecies recombinants, were inferred. The findings of this study highlight that the PeLCV population is expanding under a high degree of genetic diversity (π = 0.073%), a high rate of mean nucleotide substitution (1.54 × 10−3), demographic selection, and a high rate of recombination. This sets PeLCV apart as a distinctive begomovirus among other begomoviruses. These factors could further exacerbate the PeLCV divergence and adaptation to new hosts. The insights of this study that pinpoint the emergence of PeLCV are outlined. [ABSTRACT FROM AUTHOR]

Glycolate oxidase (GLO) is an FMN-containing enzyme localized in peroxisomes and performs in various molecular and biochemical mechanisms. It is a key player in plant glycolate and glyoxylate accumulation pathways. The role of GLO in disease and stress resistance is well-documented in various plant species. Although studies have been conducted regarding the role of GLO genes from spinach on a microbial level, the direct response of GLO genes to various stresses in short-season and leafy plants like lettuce has not been published yet. The genome of Lactuca sativa cultivar 'Salinas' (v8) was used to identify GLO gene members in lettuce by performing various computational analysis. Dual synteny, protein–protein interactions, and targeted miRNA analyses were conducted to understand the function of GLO genes. The identified GLO genes showed further clustering into two groups i.e., glycolate oxidase (GOX) and hydroxyacid oxidase (HAOX). Genes were observed to be distributed unevenly on three chromosomes, and syntenic analysis revealed that segmental duplication was prevalent. Thus, it might be the main reason for GLO gene diversity in lettuce. Almost all LsGLO genes showed syntenic blocks in respective plant genomes under study. Protein–protein interactions of LsGLO genes revealed various functional enrichments, mainly photorespiration, and lactate oxidation, and among biological processes oxidative photosynthetic carbon pathway was highly significant. Results of in-depth analyses disclosed the interaction of GLO genes with other members of the glycolate pathway and the activity of GLO genes in various organs and developmental stages in lettuce. The extensive genome evaluation of GLO gene family in garden lettuce is believed to be a reference for cloning and studying functional analyses of GLO genes and characterizing other members of glycolate/glyoxylate biosynthesis pathway in various plant species. [ABSTRACT FROM AUTHOR]

This article comprehensively reviews the applications and algorithms used for monitoring the evolution of clustering solutions in data streams. The clustering technique is an unsupervised learning problem that involves the identification of natural subgroups in a large dataset. In contrast to supervised learning models, clustering is a data mining technique that retrieves the hidden pattern in the input dataset. The clustering solution reflects the mechanism that leads to a high level of similarity between the items. A few applications include pattern recognition, knowledge discovery, and market segmentation. However, many modern-day applications generate streaming or temporal datasets over time, where the pattern is not stationary and may change over time. In the context of this article, change detection is the process of identifying differences in the cluster solutions obtained from streaming datasets at consecutive time points. In this paper, we briefly review the models/algorithms introduced in the literature to monitor clusters' evolution in data streams. Monitoring the changes in clustering solutions in streaming datasets plays a vital role in policy-making and future prediction. Of course, it has a wide range of applications that cannot be covered in a single study, but some of the most common are highlighted in this article. [ABSTRACT FROM AUTHOR]

Retraction: [Muhammad Shafiq, Fatemah H. Alghamedy, Nasir Jamal, Tahir Kamal, Yousef Ibrahim Daradkeh, Mohammad Shabaz, Scientific programming using optimized machine learning techniques for software fault prediction to improve software quality, IET Software 2023 (https://doi.org/10.1049/sfw2.12091)]. The above article from IET Software, published online on 6 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract. [ABSTRACT FROM AUTHOR]

Climate change has challenged large-scale crop production at a global level. Global temperature increases, water scarcity, and a further reduction in cultivable land resources due to anthropogenic impacts have resulted in the need to redesign agricultural systems such as intercropping to maximize the efficient use of natural resources. Arbuscular mycorrhizal fungi (AMF) represent an underexplored area, not only in terms of an alternative to the heavy use of chemical fertilizers, but also as a natural resource used to enhance physiological processes and mitigate the variations in biotic and abiotic factors in plants. On the other hand, the combined use of AMF with suitable but cheaper and environmentally friendly growth substrates is another way to maximize crop production. A study was carried out in a tomato and onion intercropped pattern system to analyze the above- and belowground implications of two AMF commercial products containing Rhizophagus irregularis, propagated in soil and with an in vitro technique addition, with two different mixed growth substrates (river sand and compost) under greenhouse conditions. Overall, both AMF products overall showed significant promoting effects on plant growth (15–30%) and root parameters (50%) in the tomato and onion plants on the sand-mixed substrate. Moreover, the soil-propagated AMF also showed significant positive effects on chlorophyll content (35%), photosynthetic activity, and the accumulation of macro- and micronutrients, especially the Fe and Mn contents (60–80%) in the tomato plants. We present evidence of the benefits to plant performance due to the interactive effects between AMF and the growth substrate, and these positive effects might be due to the intercropping system. Hence, soil-propagated Rhizophagus irregularis is represented here as a promising candidate for enhancing growth, sustainability, and productivity under greenhouse conditions. [ABSTRACT FROM AUTHOR]

Nanoemulgels are considered as potential and ideal drug delivery systems for the transdermal administration of poorly soluble drugs like lornoxicam. Their intrinsic characteristics, such as small globule size as well as excipient type, make transdermal passage of the drug easier. The current study was aimed at developing nanoemulgel based formulation of lornoxicam coloaded with eucalyptol to enhance drug skin permeation and bioavailability in order to promote therapeutic outcome in appropriate time. High shear homogenization technique was utilized to develop optimized lornoxicam encapsulated nanoemulsion followed by its conversion into nanoemulgel formulation by the addition of 1% Carbopol 940 as gelling agent. Different characterization tests were performed on optimized formulation such as surface charge, particle size and size distribution, viscosity, spreadability, pH, drug content determination, drug entrapment efficiency, in vitro drug release, and drug permeation analysis. The optimized formulation had globule size of 143.7 ± 2.18 nm. The results of drug entrapment efficiency, in vitro drug release, and skin penetration experiments were found satisfactory. Based on the formulation type, permeability parameters such as permeability constant (Kp), enhancement ratio (Er), and steady state flux (Jss) revealed greater values and satisfactory outcomes. When compared to other formulations (LRX nanoemulgel and EU nanoemulgel), the LRX-EU nanoemulgel formulation produced improved skin permeation profile (flux, 189.63 ± 7.68 μg/cm2/h; permeability coefficient, 2.09 ± 0.067 cm/h; and ER, 4.274). This work clearly proved that lornoxicam coloaded with eucalyptol nanoemulgel formulations could be developed to generate stable drug delivery systems. Thus, LRX-EU NEG formulation seems promising in terms of physicochemical properties, enhanced bioavailability, and high skin penetration profile as compared to LRX NEG formulation. [ABSTRACT FROM AUTHOR]

Background. Tuberculosis (TB) coinfection in human immunodeficiency virus- (HIV-) infected patients is considered a risk of antiretroviral therapy (ART) failure. Coadministration of antitubercular therapy (ATT) with ART is another challenge for TB management. Objective. The study was aimed at investigating contributing factors affecting treatment outcomes in HIV-/TB-coinfected patients. Design. Cross-sectional. Setting. Samples were collected from the Pakistan Institute of Medical Sciences Hospital Islamabad. Subject and Methods. Clinicodemographic and immunovirological factors between the two groups were compared. The Student t -test and chi-square test were applied to compare outcome variables, and logistic regression was applied to determine the effect of TB on virological failure (VF). Main Outcome Measures. TB coinfection did not increase VF even in univariate (p = 0.974) and multivariate analysis at 6 and 12 months of 2nd-line ART start. ARV switching was significant (p = 0.033) in TB-coinfected patients. VF was significantly high in ATT-coadministered patients along with a viral load of ≥1000 (p = 0.000). Sample Size and Characteristics. We recruited seventy-four HIV patients on 2nd-line ART; 33 coinfected with TB were followed for at least 12 months. Conclusion. In HIV-/TB-coinfected patients, CD4 count, CD4 gain, and VF remained comparable to HIV patients with no TB infection. ATT significantly affects the treatment outcome, suggesting drug-to-drug interactions. These factors are important to revisit the therapeutic guidelines to maximize the benefit of dual therapy in resource-limited settings. [ABSTRACT FROM AUTHOR]

YABBY is among the specific transcription factor (TF) gene family in plants and plays an important role in the development of the leaves and floral organs. Its specific roles include lateral organ development, the establishment of dorsoventral polarity, and response to abiotic stress. Potato is an important crop worldwide and YABBY genes are not still identified and characterized in potato. So, little has been known about YABBY genes in potato until now. This study was carried out to perform genome-wide analysis, which will provide an in-depth analysis about the role of YABBY genes in potato. There have been seven StYAB genes identified, which are found to be located on seven different chromosomes. Through multiple sequence analyses, it has been predicted that the YABBY domain was present in all seven genes while the C2-C2 domain was found to be absent only in StYAB2. With the help of cis-element analysis, the involvement of StYAB genes in light, stress developmental, and hormonal responsiveness has been found. Furthermore, expression analysis from RNA-seq data of different potato organs indicated that all StYAB genes have a role in the vegetative growth of the potato plant. In addition to this, RNA-seq data also identified StYAB3, StYAB5, and StYAB7 genes showing expression during cadmium, and drought stress, while StYAB6 was highly expressed during a viral attack. Moreover, during the attack of Phytophthora infestans on a potato plant StYAB3, StYAB5, StYAB6, and StYAB7 showed high expression. This study provides significant knowledge about the StYAB gene structures and functions, which can later be used for gene cloning, and functional analysis; this information may be utilized by molecular biologists and plant breeders for the development of new potato lines. [ABSTRACT FROM AUTHOR]

The clustering approach is widely accepted as the most prominent unsupervised learning problem in data mining techniques. This procedure deals with the identification of notable structures in unlabeled datasets. In modern days clustering of dynamic data, streams play a vital role in policy-making, and researchers are paying particular attention to monitoring the evolution of clustering solutions over time. The data streams evolve continually, and different sources generate data items over time. The clustering solution over this stream is not stationary and changes with the influx of new data items. This paper presents a comprehensive study of algorithms related to tracing the evolution of clusters over time in cumulative datasets. To demonstrate the applications and significance of the tracing cluster evolution, we implement the MONIC algorithm in R-software. This article illustrates how the data segmentation of dynamic streams is done and shows the applications of monitoring changes in clustering solutions with the help of real-life published datasets. [ABSTRACT FROM AUTHOR]

The partial discharge (PD) measurement is an important method used in determining the condition of medium- and high-voltage cable insulation. Considering the propagation velocity of PD signals in power cables is necessary for determining the location of PD defects. However, the determination of velocity is not straightforward due to propagation-related attenuation and dispersion, which distorts the PD pulse waveform. This introduces a degree of uncertainty into the pulse velocity as well as the PD source locations determined based on that velocity, which is usually considered to be of constant value in PD analysis. This paper investigates the accuracy of the pulse propagation velocity measurement in power cables. Tests were performed on a medium voltage power cable in a laboratory setting using two sets of PD-specific measurement equipment: a high-frequency current transformer (HFCT) and an IEC 60270-compliant conventional measurement system. The propagation velocities and their statistical variability were determined using both devices to assess the uncertainty of the propagation velocity measurement. The results indicate that the measured velocity is slightly higher in the case of the HFCT and that the 50% peak threshold value should be used rather than the peak value of PD sensor response waveforms to increase the precision of velocity measurements. [ABSTRACT FROM AUTHOR]

The wet (rain, snow, fog, sleet, dew) and dry (transport of aerosol, particles and gases) deposition of acidic substance in environment results due to human, automobile, fossil fuel burning and industrial activities. Acid deposition is worldwide environmental degradation problems and in recent years these acidic materials are increasing at alarming scale in the environment both in developed and developing countries, including Pakistan. Some scientific literature survey reports suggest that plant growth and agriculture yield decrease due to consequence of acid rain. In addition, acid rain is found responsible for producing toxic effects on the morphological parameters of agricultural crop. The evidence collected from last more than fifty years showed the common significant effects of acid rain on seed germination percentage, seedling height, root hair and structure, alteration in leaf anatomy, size and area, stomatal structure, size, pollen germination, photosynthetic pigments and physiological changes in herbs, shrubs and trees. Still, little is known on the impact of acid rain on plant growth. This study was aimed to review the effects of acid mist on growth performances of some selected plant species. This review is contributed with the help of literature survey, research work published on the impact of acid rain on the plant growth. [ABSTRACT FROM AUTHOR]

Chilli (Capsicum annuum), which belongs to the family Solanaceae, is an important spice crop cultivated in tropical and subtropical countries. A Protocol for chili plant regeneration with hypocotyl and cotyledon explants was established. The study was conducted to observe the effect of genotypes, culture conditions and growth regulators on plant regeneration of chili pepper genotypes (Seedex Pepper (SP), Loungi, Tatapuri, and Sanam) grown in Pakistan including. For both hypocotyl and cotyledon explants, SP was found to be the most sensitive among the tested genotypes tested. Maximum mean callus induction rate of hypocotyl was 76.6% in SP followed by TP (73.3%); Sanam (57.3%); Loungi (43.3%) respectively. Whereas in case of cotyledon maximum inductions rate was found in Loungi (62.0%) followed by SP (60); Sanam (57.3); TP (46) individually. According to the observations maximum plant regeneration was found in genotype SP (9%), followed by Loungi (1.8%); Sanam (1.5%) but no plant regeneration was found in TP. A. tumefaciens LBA4404 with the 35S GFP/pFGC construct were used to evaluate hypocotyl and cotyledon explants for transformation. The effects of co-cultivation at different temperatures (22 and 25oC), photoperiods (16 hours of light, 8 hours of darkness, and full darkness), and co-cultivation periods were studied. GFP assays revealed that the putative transgenic calli were not transformed and died after 40-60 days. The experiment was repeated ten times to see the success rate of the regeneration system. In this study a protocol for chili plant regeneration was developed for callus induction, plant regeneration, and plant transformation. Because developing a viable chilli tissue culture and plant regeneration system is difficult, this study was designed to help develop one. SP was found to be the most suitable among the four genotypes used for regeneration. [ABSTRACT FROM AUTHOR]

Artificial intelligence plays an essential role in diagnosing lung cancer. Lung cancer is notoriously difficult to diagnose until it has progressed to a late stage, making it a leading cause of cancer-related mortality. Lung cancer is fatal if not treated early, making this a significant issue. Initial diagnosis of malignant nodules is often made using chest radiography (X-ray) and computed tomography (CT) scans; nevertheless, the possibility of benign nodules leads to wrong choices. In their first phases, benign and malignant nodules seem very similar. Additionally, radiologists have a hard time viewing and categorizing lung abnormalities. Lung cancer screenings performed by radiologists are often performed with the use of computer-aided diagnostic technologies. Computer scientists have presented many methods for identifying lung cancer in recent years. Low-quality images compromise the segmentation process, rendering traditional lung cancer prediction algorithms inaccurate. This article suggests a highly effective strategy for identifying and categorizing lung cancer. Noise in the pictures was reduced using a weighted filter, and the improved Gray Wolf Optimization method was performed before segmentation with watershed modification and dilation operations. We used InceptionNet-V3 to classify lung cancer into three groups, and it performed well compared to prior studies: 98.96% accuracy, 94.74% specificity, as well as 100% sensitivity. [ABSTRACT FROM AUTHOR]

Chilli (Capsicum annuum), which belongs to the family Solanaceae, is an important spice crop cultivated in tropical and subtropical countries. A Protocol for chili plant regeneration with hypocotyl and cotyledon explants was established. The study was conducted to observe the effect of genotypes, culture conditions and growth regulators on plant regeneration of chili pepper genotypes (Seedex Pepper (SP), Loungi, Tatapuri, and Sanam) grown in Pakistan including. For both hypocotyl and cotyledon explants, SP was found to be the most sensitive among the tested genotypes tested. Maximum mean callus induction rate of hypocotyl was 76.6% in SP followed by TP (73.3%); Sanam (57.3%); Loungi (43.3%) respectively. Whereas in case of cotyledon maximum inductions rate was found in Loungi (62.0%) followed by SP (60); Sanam (57.3); TP (46) individually. According to the observations maximum plant regeneration was found in genotype SP (9%), followed by Loungi (1.8%); Sanam (1.5%) but no plant regeneration was found in TP. A. tumefaciens LBA4404 with the 35S GFP/pFGC construct were used to evaluate hypocotyl and cotyledon explants for transformation. The effects of co-cultivation at different temperatures (22 and 25 oC), photoperiods (16 hours of light, 8 hours of darkness, and full darkness), and co-cultivation periods were studied. GFP assays revealed that the putative transgenic calli were not transformed and died after 40-60 days. The experiment was repeated ten times to see the success rate of the regeneration system. In this study a protocol for chili plant regeneration was developed for callus induction, plant regeneration, and plant transformation. Because developing a viable chilli tissue culture and plant regeneration system is difficult, this study was designed to help develop one. SP was found to be the most suitable among the four genotypes used for regeneration. [ABSTRACT FROM AUTHOR]

Objective: To determine the Diagnostic accuracy of Kramer's visual assessment of jaundice in term neonates by taking total serum bilirubin levels as a gold standard. Study Design: Cross-sectional study. Place and Duration of Study: Neonatology Department, Pak Emirates Military Hospital, Rawalpindi Pakistan, Mar to Sep 2019. Methodology: The study was based on examining and investigating 300 neonates. Kramer scale was used to examine jaundice in all neonates, and results were compared to total serum bilirubin levels. Results: A total of 300 patients were included in this study. The mean bilirubin level was 229.1±74.5mol/L. The sensitivity and specificity of visual assessment of jaundice using the Kramer visual scale were 83.84% and 73.53%, respectively, for neonates who were not jaundiced below the abdomen and thighs included in Kramer zones 1 to 3. Conclusion: Kramer visual assessment can be used as a noninvasive screening method in neonates jaundiced up to the abdomen and thighs, which is included in Kramer zones 1 to 3 but for markedly jaundiced neonates Kramer scale is not a reliable noninvasive method of bilirubin estimation. [ABSTRACT FROM AUTHOR]

This study enumerates the evolution of basic human values orientations and the dynamic relationship between them, computed from Schwartz's value survey conducted in European nations. For this purpose, eight datasets related to the human value scale were extracted from the European Social Survey; each corresponds to a single round conducted cross-sectionally every two years since 2001. Change detection algorithm was implemented to the cluster solutions of temporal datasets, and the evolution of important clusters was traced. Finding of the study reveals that Universalism and Benevolence values are on the rise in European societies in the last couple of decades. Most of the European inhabitants believe in the smooth group functioning and form the organismic needs of cooperation. The people prefer anxiety-free life, and love for nature, environment, humanity, and kindness to other beings in society are essential constructs for them. They avoid self-centred behaviour and prefer social physiognomies. [ABSTRACT FROM AUTHOR]

Alzheimer is a disease that causes the brain to deteriorate over time. It starts off mild, but over the course of time, it becomes increasingly more severe. Alzheimer's disease causes damage to brain cells as well as the death of those cells. Memory in humans is especially susceptible to this. Memory loss is the first indication of Alzheimer's disease, but as the disease progresses and more brain cells die, additional symptoms arise. Medical image processing entails developing a visual portrayal of the inside of a body using a range of imaging technologies in order to discover and cure problems. This paper presents machine learning-based multimodel computing for medical imaging for classification and detection of Alzheimer disease. Images are acquired first. MRI images contain noise and contrast problem. Images are preprocessed using CLAHE algorithm. It improves image quality. CLAHE is better to other methods in its capacity to enhance the look of mammography in minute places. A white background makes the lesions more obvious to the naked eye. In spite of the fact that this method makes it simpler to differentiate between signal and noise, the images still include a significant amount of graininess. Images are segmented using the k-means algorithm. This results in the segmentation of images and identification of region of interest. Useful features are extracted using PCA algorithm. Finally, images are classified using machine learning algorithms. [ABSTRACT FROM AUTHOR]

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from −8.0 to −9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07–0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25–0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity. [Display omitted] • PPAR-γ modulators enhance insulin sensitivity, crucial in diabetes management. • Machine learning aids in identifying 4 potential PPAR-γ modulators • Compound reveals promising interactions with key PPAR-γ residues. • Stability analysis indicates moderate conformational changes in orthosteric sites. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) seem to be the most efficient way of achieving the intended aerial tasks, according to recent improvements. Various researchers from across the world have studied a variety of UAV formations and path planning methodologies. However, when unexpected obstacles arise during a collective flight, path planning might get complicated. The study needs to employ hybrid algorithms of bio-inspired computations to address path planning issues with more stability and speed. In this article, two hybrid models of Ant Colony Optimization were compared with respect to convergence time, i.e., the Max-Min Ant Colony Optimization approach in conjunction with the Differential Evolution and Cauchy mutation operators. Each algorithm was run on a UAV and traveled a predetermined path to evaluate its approach. In terms of the route taken and convergence time, the simulation results suggest that the MMACO-DE technique outperforms the MMACO-CM approach. [ABSTRACT FROM AUTHOR]

This study aims at optimizing lead time through effective management of resources in an equipment manufacturing industry to ensure timely completion of the projects. The concept of 'project crashing" was implemented to identify potential activities at production line of conventional two-roller machines. The developed model is optimized using modified Genetic Algorithm (GA). The results showed that the proposed model enabled to deliver products as per schedule without increasing planned cost. Sensitivity analyses were also conducted to find out the impact of various process parameters. From the analyses, it was found that the proposed model facilitates the manufacturer in delivering the products at specified time with increasing the planned cost. [ABSTRACT FROM AUTHOR]

Ongoing developments of the measurement sciences say that measurements based on continuous phenomena are no more precise observations but more or less fuzzy. Therefore, it is necessary to utilize this imprecision of observations to obtain such estimators, which are based on all the available information that is given in the form of randomness and fuzziness. Objective of this research was to get such parameter estimation procedure that utilizes all the available information for some well-known two-parameter life time distributions. Therefore, the estimators need to be generalized in such a way to cover both uncertainties. For this purpose, based on δ -cuts of the life time observations, the generalized estimators are developed in such manner to cover stochastic variation in addition to fuzziness. The proposed generalized estimators are much preferred over classical estimators for life time analysis as these are based on all the available information present in the form of fuzziness of single observations and random variation among the observations to make suitable inferences. [ABSTRACT FROM AUTHOR]

Citrus is a valuable crop in Pakistan. It is rich in vitamin C, other nutrients and antioxidants. Huanglongbing (HLB) caused by a bacterium "Candidatus liberibacter asiaticus" (CLas), africanus and americanus has an influence on citrus production around the world. Beside HLB there exist several other bacterial species in citrus groves in Pakistan. The structure and diversity of bacterial species in various ecosystems can be quickly examined using NGS. This approach is considerably quicker and more precise than outdated methods. Healthy or citrus greening infected leaf samples of Grapefruit (Citrus paradisi), C. aurantifolia, and C. reticulata Blanco were used for diversity analysis. In this study high throughput, NGS technique was used to access the population of both cultivable and non-cultivable bacterial endophytes from citrus leaves, by using PCR amplicons of 16S rDNA sequences (V5–V7 regions) with Illumina Hi seq. As a result, a total number of 68,722 sequences were produced from the test samples. According to the NGS-based diversity classification, the most common genera of exploited bacterial endophytes were Proteobacteria, Firmicutes, Bacteroides, Cyanobacteria, and Actinobacteria. C. aurantifolia and C. paradisi showed almost equal diversity, whereas C. reticulata Blanco had a higher proportion of Proteobacteria and Cyanobacteria in their leaves. To determine alpha diversity (AD), additional data was analyzed using statistical indices such as Shannon, Chao1, and Simpson. According to the inverse Simpson diversity index, the abundance of the microbial population in six different citrus samples was 0.48, 0.567, and 0.163, respectively. The metagenomics of microbiota in plant tissues was successfully recorded by NGS technology, which can help us learn more about the interactions between plants and microbes. This research is the first step toward a better understanding of 16SrRNA-based metagenomics from citrus in Pakistan using Illumina (Hi seq) Technology. [ABSTRACT FROM AUTHOR]

Objective: To determine the accurate ability to diagnose the pleural fluid GeneXpert MTB/RIF assessment in the suspected pleural tuberculosis patients considered as gold standard the pleural biopsy. Materials & Methods: This study was a validation cross-sectional survey and it was conducted in the pulmonology department of Pakistan Institute of Medical Sciences, Islamabad from 1st July to 31st December 2018 after approval of IRB. Participants with suspected pathology ≥ 18 years with exudative pleural effusion were included in the study. By implementing the process of the standard technique, closed needle pleural biopsy was executed by means of ABRAM'S needle. The collected samples of patients were sent to the pathology department of the Pakistan Institute of Medical Sciences for histopathology. Pleural fluid was referred to the National Institute of Health Islamabad for GeneXpert MTB/RIF assessment on the alike day and reports were assembled. All findings were entered in a structured Proforma. Data was entered in SPSS version 20 and analyzed. Results: A total of 180 patients were included; 65.6% of patients were male. When the sensitivity of pleural fluid GeneXpert MTB/RIF examination was calculated it was 10.4% whereas, the calculated specificity was 72.8%. While +ve predictive value of GeneXpert was 22.2% and the -ve predictive value was 52.1%. The likelihood ratio was 8.25 and the ROC curve also showed similar values. Conclusion: The sensitivity of pleural fluid GeneXpert MTB/RIF assay is very low and specificity is moderate for diagnosis of pleural tuberculosis when compared with pleural biopsy. [ABSTRACT FROM AUTHOR]

• Experimental study on medium voltage cable insulation under increasing electrical stress. • Development of an effective algorithm for detection of PD pulses in a PRPD pattern. • Analysis of measured PD data and correlation of PD characteristics. • Trending attributes of PD characteristics with increasing electrical stress. • Implementation of regression models to map trending behavior of PD characteristics. Insulation degradation in power components is a looming issue that can have a significant impact on the reliability of power system if not attended timely. Partial discharge (PD) diagnostics is a key technique used for the condition monitoring and health assessment of insulation. Inception of PD is a primary indicator which shows degradation and decreased local dielectric strength of the insulation. PD magnitude can increase with time and level of stress, which may result in failure of insulation. This article investigates the behavior of PD characteristics in a medium voltage (MV) cross-linked polyethylene (XLPE) cable sample, containing a defect at the cable termination, under elevated electrical stresses. PD behavior is studied by investigating the key PD characteristics, such as partial discharge inception voltage (PDIV) , phase of occurrence (ɸ) , mean amplitude (V mean) , pulse repetition rate (PRR) , and phase span (ɸ span). These quantities are extracted from a phase-resolved partial discharge (PRPD) pattern using a pulse detection algorithm. Later, these characteristics are analyzed in correlation with the electrical stress. Various regression models are implemented and compared to find the best fit model that represents trending attributes of major PD characteristics. The presented study can be used as an effective process to analyze the measured PD data for evaluation of the insulation condition in the power components. [ABSTRACT FROM AUTHOR]

The effect of different pH ranges 3-10 was studied on the growth rate of six different bacterial strains, e.g. Escherichia coli, Klebsiella Pneumoniae, Bacillus cereus, Bacillus flexus, Brevibacterium borstelensis, Staphyllococcus scuiri, isolated from different hosts (Kinnow, Gada Dahi, Sweet orange, Musambi, and Bindweed). These bacterial endophytes were distinguished by the use of universal 16s rRNA primers based on morphological characters and biochemical tests as well as molecular approaches. The amplified PCR products were purified and sequenced from Mobix at Mc Master's University, Hamilton, Canada, and submitted to the NCBI database under accession (LT844655, MF966247, LT745986, LT745989, LT745979, and MF977365). The phylogenetic tree of isolated strains was constructed by MEGA 7.0 software. Gen 5 plate reader software was used to measure growth at O.D 600nm in 96 well plate for 24 hours at 30oC in EpochTM microplate spectrophotometer. According to the findings, Escherichia coli grew best in the pH ranges of 6, 7, and 8, but not in the pH range of 9. Similarly, Staphylococcus scuiri grew best in a pH range of 7 to 10, while pH 4 and 5 had no development. The typical growth pattern of Klebsiella pneumoniae was observed at pH 9 and 10, whereas growth was slower or limited in the other pH ranges. Whereas, Bacillus flexus and Bacillus cereus grew best at pH 6-9. Brevibacterium borstelensis, on the other hand, grew best at 4-9.These findings indicate that pH can play an important role in determining bacterial competition in host plants. [ABSTRACT FROM AUTHOR]

Phytoremediation of lead (Pb) contaminated soil is a green technology to reduce Pb exposure and root exudates-derived organic acids play a vital role in this treatment process. In this study, Pb hyperaccumulator Pelargonium hortorum was chosen to investigate root-induced organic acid secretions and their subsequent role in Pb phytoextraction. In the first step, root exudation of P. hortorum was investigated in hydroponic experiments (0.2X Hoagland solution) under control and Pb stress conditions. Possible chemical interactions between Pb and the observed root exudates were then analyzed using Visual MINTEQ modeling. In the next step, the effects of the exogenous application of organic acids on Pb phytoextraction and soil enzymatic activities were studied in a pot experimental setup. Results indicated significant exudation of malic acid > citric acid > oxalic acid > tartaric acid in root exudates of P. hortorum under 50 mg L−1 Pb. Visual MINTEQ modeling results revealed that organic acids directly affect Pb dissolution in the nutrient solution by modulation of solution pH. Experimental results revealed that malic acid and citric acid significantly increased available Pb contents (7.2– and 6.7–folds) in the soil with 1500 mg kg−1 Pb contamination. Whereas, in shoot and root, the highest increase in Pb concentration was observed with citric acid (2.01–fold) and malic (3.75–fold) supplements, respectively. Overall, Pb uptake was notably higher when malic acid was applied (2.8–fold) compared to other organic acids, followed by citric acid (2.7–fold). In the case of soil enzymatic activities, oxalic acid significantly improved dehydrogenase, alkaline phosphatase, and microbial biomass by 1.6–, 1.4– and 1.3–folds, respectively. The organic acids were successful in reviving enzyme activity in Pb-contaminated soil, and might thus be used for long-term soil regeneration. [Display omitted] • Pb exposure resulted in significant induction of root exudates in P. hortorum. • Organic acids significantly improved soil enzymatic activities as: oxalic acid > malic acid > tartaric acid. • In root, the highest Pb concentration was achieved with malic acid supplement. • In shoot, the highest significant increase in Pb concentration was observed with citric acid supplement. • Malic acid significantly improved plant biomass and overall Pb phytoextraction. [ABSTRACT FROM AUTHOR]

[Display omitted] • VEGF-binding peptide "BP" and OEO were loaded into PLGA/Gelatin fibers. • OEO improved anti-inflammatory, anti-oxidative, and anti-bacterial properties. • The BP containing fibers effectively accelerated angiogenesis. • BP and OEO co-loaded fibers showed rapid repair of infected wounds. • Combined delivery of BP and OEO also suppress bacterial growth in vivo. Skin regeneration is hindered by poor vascularization, bacterial infection, prolonged inflammation, and oxidative wound microenvironment, which necessitate the fabrication of alternative wound dressings with anti-adhesion, anti-infection, and angiogenic functions. Prominin-1-derived peptide (PR1P, herein named as BP) may sequester vascular endothelial growth factor (VEGF) by interacting with VEGF receptors and promote wound healing. Oregano essential oil (OEO, herein named as O), is a natural plant extract mainly containing carvacrol and thymol, which manifests low cytotoxicity and cost-effectiveness as well as anti-inflammatory, antibacterial, and anti-oxidative properties. Herein, we fabricated anti-adhesion, anti-infection, and angiogenic wound dressings by simultaneously exploiting BP and O in electrospun poly(L-lactide-co-glycolide)/gelatin (PG)-based fibrous dressings. Different types of in vitro assays manifested anti-inflammatory, anti-oxidative, anti-bacterial, and angiogenic characteristics of dressings. The PG@BPO dressings further enabled good wound healing 14 days post-implantation alongside anti-adhesion, and anti-infection properties. The tensile strength of the repaired skin was almost similar to the normal skin (repaired skin, 1.70 MPa and normal skin, 1.78 MPa). These multifunctional dressings may hold great promise for skin repair and related disciplines. [ABSTRACT FROM AUTHOR]

Heat stress causes irrecoverable damage to plant growth, thus adversely affecting the crop productivity. This study was planned to minimize the heat stress induced-losses to chickpea plants with the exogenous application of growth promoters i.e. moringa leaf extract (MLE), jasmonic acid 100 μM and proline 10uM including distilled water as a control. Two chickpea cultivars (Thal-2006 and Noor-2013) cultivated under optimum sowing time (25th October) and late sowing (25th November) to expose heat stress at the reproductive phase. Results indicated that heat stress severely reduced the chickpea growth and productivity. It was observed that exogenously applied MLE and proline improved productivity even under heat stress conditions as compared to control. However, exogenous application of MLE had a greater influence on the studied parameters than proline, although the insignificant differences were documented in some of the traits. Exogenous application of MLE produced significantly taller plants with improved 100-grains weight, economic yield, biological yield and harvest index. However, foliar spray of proline produced significantly higher enzymatic antioxidants activities than MLE that modulated the adverse impacts of heat stress on yield contributing attributes. Our results suggest that exogenous application of plant growth promoters particularly moringa leaf extract and proline modulated the heat stress induced losses to chickpea plants by improving their antioxidant defense mechanism and enhanced the productivity. [ABSTRACT FROM AUTHOR]

A new class of q-close-to-convex functions associated with Janowski functions is defined. In this regard, we give sufficient conditions and prove famous de Branges theorem for this newly-defined class of q-close-to-convex functions. We also give the application of our results to finding sufficient conditions for the celebrated Mittag-Leffler function to be a Janowski q-close-to-convex function. [ABSTRACT FROM AUTHOR]

A new class of q-close-to-convex functions associated with Janowski functions is defined. In this regard, we give sufficient conditions and prove the famous de Branges theorem for this newly-defined class of q-close-to-convex functions. We also give the application of our results to finding sufficient conditions for the celebrated Mittag-Leffler function to be a Janowski q-close-to-convex function. [ABSTRACT FROM AUTHOR]

Background: Clostridium difficile (C. difficile) is a spore-forming, Gram-positive rod that is known to be associated with antibiotic use. It is one of the leading causes of nosocomial diarrhea in the industrialized world and therefore warrants further study of its nature. It isn't clear if co-infection by other organisms can affect the outcome of C. difficile infection (CDI). Methods: A single center retrospective study was done and it used inclusion criteria of 18 years of age and being tested positive for CDI on FilmArray® multiplex gastro-intestinal (GI) panel. Exclusion criteria were a GI panel performed on an outpatient basis, recurrent CDI, and the presence of end-stage renal disease, cirrhosis, or a non-GI infection. The stool sample for all patients were collected within 48 h of presentation to the hospital. There were 235 of 2576 GI panels selected for a retrospective chart review based on the above criteria. Among these 235 patients, 38 had a co-infection (CDI+ another GI infection = group A or cases) and the rest had only CDI (group B or controls). Group A was compared with group B for CDI severity, its response to treatment, recurrence, and length of the hospital stay, using 0.05 as the alpha criterion. Results: Most patients with CDI were female and above the age of 60 years. Co infection did not increase the severity of CDI based both on the American College of Gastroenterology criteria (p 0.16) as well as Infectious Disease Society of America criteria (p 0.77). Co infection group also didn't have significantly different CDI related treatment failure rate (p 0.23), or CDI recurrence rate (p 0.49). Co-infection was also not associated with lengthier hospital stay (p 0.41). Conclusion: Our study suggests that co-infection doesn't affect the severity of CDI or can cause treatment failures. Additionally, there was no significant increase in hospital stay, or increase in CDI recurrence associated with co-infection. Therefore, if CDI is the leading clinical diagnosis and a patient is tested positive for co-infection in addition to CDI on FilmArray® multiplex GI panel, this co-infection shouldn't change the management for CDI. Limitations of this study (including retrospective nature of the study, small sample size, single site study, not including all microbiome and non-inclusion of race) should also be taken into account, while considering the applicability of the results of this study. [ABSTRACT FROM AUTHOR]

The development of simulation models for improving performances is trendy in manufacturing industries. This paper presents simulation model for evaluating and improving performances of a utensils manufacturing plant. Internal benchmarking is employed for comparison under exactly similar conditions. The data of all input variables is collected and statistical models for each process is developed using Arena input analyzer. The simulation model is then developed using SIMIO to optimize throughput, work-in-process, and cycle time. The experiments have been performed under various scenarios, i.e., at different values of the input parameters. The areas for improvement have been highlighted on the basis of results. Furthermore, best and worst case scenarios have been discussed in detail to provide insights for managerial performance improvements by (1) optimizing inter-arrival time, (2) increasing production rate, and (3) reducing the number of rejected parts without disturbing the existing setup of the manufacturing facility. [ABSTRACT FROM AUTHOR]

A new class of q-close-to-convex functions associated with Janowski functions is defined. In this regard, we give sufficient conditions and prove the famous de Branges theorem for this newly-defined class of q-close-to-convex functions. We also give the application of our results to finding sufficient conditions for the celebrated Mittag-Leffler function to be a Janowski q-close-to-convex function. [ABSTRACT FROM AUTHOR]

Insulated power cables are becoming increasingly popular in today’s developing distribution and transportion networks. However, due to aging, deterioration, and various operational and environmental stresses, insulation defects may appear and so the cable needs to be monitored in a timely manner to avoid unexpected failures. Many of these defects are responsible for partial discharge (PD) activity. The localization of the sources of these discharges is a highly decisive facet in the condition-based monitoring of power cables. The techniques for the localization of single-PD defects in insulated power cables are well presented in the current bibliography. However, when several simultaneous PD sources are active, the localization of the sources becomes quite complex. This paper develops an efficient technique for the separation and localization of multiple PD sources in a medium voltage cable. The experimental results are obtained with single-end-based measurements using a high-frequency current transformer in a laboratory environment. The data processing based on the spectral characteristics of the signals is carried out by using the power ratios technique in order to determine the presence of different types of PD. Once the signals are separated, the PD sources can be localized with an individualized analysis of each source through time-domain reflectometry. The proposed methodology can be very valuable to improve the location diagnostic capability of the condition-based monitoring solutions, especially for underground cables. [ABSTRACT FROM AUTHOR]

Background: In Oman tobacco (Nicotiana tabacum; family Solanaceae) is a minor crop, which is produced only for local consumption. In 2015, tobacco plants exhibiting severe downward leaf curling, leaf thickening, vein swelling, yellowing and stunting were identified in fields of tobacco in Suhar Al-Batina region, Oman. These symptoms are suggestive of begomovirus (genus Begomovirus, family Geminiviridae) infection. Methods: Circular DNA molecules were amplified from total DNA extracted from tobacco plants by rolling circle amplification (RCA). Viral genomes were cloned from RCA products by restriction digestion and betasatellites were cloned by PCR amplification from RCA product, using universal primers. The sequences of full-length clones were obtained by Sanger sequencing and primer walking. Constructs for the infectivity of virus and betasatellite were produced and introduced into plants by Agrobacterium-mediated inoculation. Results: The full-length sequences of 3 begomovirus and 3 betasatellite clones, isolated from 3 plants, were obtained. Analysis of the full-length sequences determined showed the virus to be a variant of Chilli leaf curl virus (ChiLCV) and the betasatellite to be a variant of Tomato leaf curl betasatellite (ToLCB). Both the virus and the betasatellite isolated from tobacco show the greatest levels of sequence identity to isolates of ChiLCV and ToLCB identified in other hosts in Oman. Additionally clones of ChiLCV and ToLCB were shown, by Agrobacterium-mediated inoculation, to be infectious to 3 Nicotiana species, including N. tabacum. In N. benthamiana the betasatellite was shown to change the upward leaf rolling symptoms to a severe downward leaf curl, as is typical for many monopartite begomoviruses with betasatellites. Conclusions: The leaf curl disease of tobacco in Oman was shown to be caused by ChiLCV and ToLCB. This is the first identification of ChiLCV with ToLCB infecting tobacco. The study shows that, despite the low diversity of begomoviruses and betasatellites in Oman, the extant viruses/betasatellites are able to fill the niches that present themselves. [ABSTRACT FROM AUTHOR]

Background: Flexor tendons injuries are common emergency procedures The objectives of this study were to determine the frequency, distribution and results of treatment of acute flexor tendon injuries in zone v of hand in our population. Material and Methods: This descriptive cross-sectional was conducted in the Department of Orthopedic, Gomal Medical College, D.I.Khan, Pakistan from January 2015 to December 2017. Sample size was 30, selected through consecutive technique. Patients having flexor tendon injuries in zone v, admitted through emergency department were included in this study. Demographic variable were sex and age-groups. The research variable were tendon involved, nerves involved, artery involved, mechanism of injury, wound size, duration of injury, season, type of injury, hand involved and results of treatment. All variables, being categorical were analyzed by frequency and percentages using SPSS version 16.0. Results: Out of 30 patients, 22(73.33%) were male. Twenty four (80%) patients were between 21 to 40 years age. Mechanism of injury was glass in 16(53.33%) cases, knife in 10(33.33%) cases. Twenty (66.66%) cases presented in summer. Flexor digitorum sublimus was injured in 21(70.0%), FCR in 11(36.66%), FPL in 8(26.66), FDP in 6(20.0%) and FCU in 4(13.33%) cases. Median nerve was involved in nine (30%) cases. Radial artery was involved in eight (26.66%) cases. Wound size was 2 cm in 24(80%) cases. Sixteen (53.33%) cases came with self-inflicted injuries. Twenty (66.66%) cases came after 12 hours. Twenty five (83.33%) patients achieved good to excellent results. Conclusion: Flexor digitorus sublimus was the most common tendon injured in non-dominant hand, especially in young males. Median nerve and radial artery were commonly injured structures mostly with glass. Majority patients presented more than 12 hours after injury, having wound size of 2cm. Mostly the injuries were self-inflicted and occurred in summer season. [ABSTRACT FROM AUTHOR]

Abstract This study is focused on the investigation of the main sustainability drivers that may improve production performances for Asian firms. The main objective of the paper is to unfold the potential tangible and intangible sustainability resources that can act as strategic assets in improving production performances, with the Resource-Based View as the main framework used in the study. As a further investigation, the research explores how these resources may vary under the contingency perspective by considering two different stages of implementation of Quality Management Systems within the respondents. These issues are examined through a wide survey of textile firms in India and Pakistan, using Structural Equation Modelling as the main tool of investigation. Some of the main outcomes show that Environmental Management and Safety Management result in the strategic use of resources to improve production performances. It emerges from the contingency analysis that increasing importance is given to intangible assets by those firms that are at an advanced stage of implementation of their Quality Management System. Highlights • We realize an extensive survey on the core resources that may impact on production performances for Asian firms. • A contingency analysis is made through Structural Equation Modeling, with Quality Management System as discriminant factor. • Environmental Management, Safety Management and Sustainability Awareness have a key role within a QMS. • Firms at different stages of implementing a QMS do not share the same core resources. • Social Issues and Sustainability Awareness are core resources for firms with an advanced stage of QMS implementation. [ABSTRACT FROM AUTHOR]

Quick recovery of the information signals in secure communications restricts the hacking duration. The short synchronization convergence time is a crucial parameter for faster recovery. This paper develops a novel nonlinear finite-time synchronization control algorithm. This controller accomplishes the global finite-time multi-switching synchronization between two externally perturbed chaotic systems in the drive-response system synchronization scheme. The proposed controller assures the global convergence of the error dynamics in finite-time based on the Lyapunov theory. This implicitly guarantees the global stability of the closed loop. This paper considers Lp(0 < p < 1) norm inequality for the construction of the Lyapunov function. This method provides a means to determine the parameters of the proposed finite-time controller. This paper also studies the significance of structural components of the proposed controller that are responsible for the finite-time synchronization convergence. Computer simulation results of ‘two identical chaotic Lorenz systems’ and ‘chaotic Lorenz and Chen systems’ validate the theoretical findings. The paper discusses the simulation results and compares them with peer works as well. [ABSTRACT FROM AUTHOR]

Salt bodies are important subsurface structures with significant implications for hydrocarbon accumulation and sealing in offshore petroleum reservoirs. This study presents an unsupervised workflow for delineating the surface of salt bodies from 3-D seismic surveying based on a multi-attribute |$k$| -means cluster analysis. The workflow consists of four steps. First, a suite of seismic attributes are selected and computed from the volume of original seismic amplitude, each of which separates the target salt boundaries from the surrounding non-boundary seismic features in its unique way. Second, two sets of representative samples are manually picked in an interpreter-specified vertical section to help initialize the centres of the boundary and non-boundary clusters. Third, the |$k$| -means cluster analysis is performed on the seismic attributes to generate a clustering model for volumetric processing. Finally, applying the built |$k$| -means model to every sample in the seismic volume provides us with a probability volume in which the high values indicate the presence of salt-dome boundaries. The effectiveness of the proposed method is verified for interpreting the multiple salt bodies in the F3 seismic data set over the Netherlands North Sea, and the generated salt-boundary volume can serve as input for more advanced salt interpretation, such as salt surface/body extraction, to assist structural framework modelling in the subsalt zones of high geologic complexities and petroleum potentials. We conclude that the proposed workflow paves the way for computer-aided seismic interpretation in a more comprehensive manner by incorporating more advanced machine learning algorithms (e.g. artificial neural network) and targeting other important seismic structures (e.g. fault). [ABSTRACT FROM AUTHOR]

Class imbalance has become a big problem that leads to inaccurate traffic classification. Accurate traffic classification of traffic flows helps us in security monitoring, IP management, intrusion detection, etc. To address the traffic classification problem, in literature, machine learning (ML) approaches are widely used. Therefore, in this paper, we also proposed an ML-based hybrid feature selection algorithm named WMI_AUC that make use of two metrics: weighted mutual information (WMI) metric and area under ROC curve (AUC). These metrics select effective features from a traffic flow. However, in order to select robust features from the selected features, we proposed robust features selection algorithm. The proposed approach increases the accuracy of ML classifiers and helps in detecting malicious traffic. We evaluate our work using 11 well-known ML classifiers on the different network environment traces datasets. Experimental results showed that our algorithms achieve more than 95% flow accuracy results. [ABSTRACT FROM AUTHOR]

Background: To compare proportion of the patients with attainment of sensory level T4, at 5 and 10 min supine, and after 10 min prone amongst patients receiving 22.5 mg bupivacaine with those receiving 30 mg. Methods: In this randomized clinical trial patients (n=60), undergoing percutaneous nephrolithotomy, were included. It was done to compare the achievement of sensory level T4 during PCNL after spinal anaesthesia with two doses of bupivacaine before and after positioning patients in prone position. Patients were grouped into: Group A (22.5 mg hyperbaric Bupivacaine 0.75%) versus Group B (30 mg hyperbaric Bupivacaine 0.75%) consisting 30 patients each. Spinal anaesthesia was performed while sitting. Sensory level was checked using icecube in mid-axillary line while patients were positioned supine and prone. Results: Number of patients with T4 level at 5 min and 10 min supine in Group B was much higher than in Group A (p<0.001). In comparison of attainment of T4 level in supine and after 10 min of prone position, more number of patients achieved the level after 10 minutes of prone position in contrast to Group A and it was statistically significant (p<0.001). Conclusion: Positioning in prone extends the sensory level of spinal anaesthesia to higher level (T4) when 22.5 mg of hyperbaric bupivacaine is used and hence reduced dose can be given efficiently and safely for the procedure. [ABSTRACT FROM AUTHOR]

Carotenoid cleavage oxygenase (CCO) is an enzyme capable of converting carotenoids into volatile, aromatic compounds and it plays an important role in the production of two significant plant hormones, i.e., abscisic acid (ABA) and strigolactone (SL). The cucumber plant genome has not been mined for genomewide identification of the CCO gene family. In the present study, we conducted a comprehensive genome-wide analysis to identify and thoroughly examine the CCO gene family within the genomic sequence of Cucumis sativus L. A Total of 10 CCO genes were identified and mostly localized in the cytoplasm and chloroplast. The CCO gene is divided into seven subfamilies i.e. 3 NCED, 3 CCD, and 1 CCD-like (CCDL) subfamily according to phylogenetic analysis. Cis-regulatory elements (CREs) analysis revealed the elements associated with growth and development as well as reactions to phytohormonal, biotic, and abiotic stress conditions. CCOs were involved in a variety of physiological and metabolic processes, according to Gene Ontology annotation. Additionally, 10 CCO genes were regulated by 84 miRNA. The CsCCO genes had substantial purifying selection acting upon them, according to the synteny block. In addition, RNAseq analysis indicated that CsCCO genes were expressed in response to phloem transportation and treatment of chitosan oligosaccharides. CsCCD7 and CsNCED2 showed the highest gene expression in response to the exogenous application of chitosan oligosaccharides to improve cold stress in cucumbers. We also found that these genes CsCCD4a and CsCCDL-a showed the highest expression in different plant organs with respect to phloem content. The cucumber CCO gene family was the subject of the first genome-wide report in this study, which may help us better understand cucumber CCO proteins and lay the groundwork for the gene family's future cloning and functional investigations. [ABSTRACT FROM AUTHOR]

The proliferation of Internet-of-Things (IoT) technology and its reliance on the license-free Industrial, Scientific, and Medical (ISM) bands have rendered radio spectrum scarce. The IoT can nevertheless obtain great advantage from Cognitive Radio (CR) technology for efficient use of a spectrum, to be implemented in IEEE 802.11af-based primary networks. However, such networks require a geolocation database and a centralized architecture to communicate white space information on channels. On the other hand, in spectrum sensing, CR presents various challenges such as the Hidden Primary Terminal (HPT) problem. To this end, we focus on the most recently released standard, i.e., IEEE 802.11ah, in which IoT stations can first be classified into multiple groups to reduce collisions and then they can periodically access the channel. Therein, both services are similarly supported by a centralized server that requires signaling overhead to control the groups of stations. In addition, more regroupings are required over time due to the frequent variations in the number of participating stations, which leads to more overhead. In this paper, we propose a new Multiple Access Control (MAC) protocol for CR-based IEEE 802.11ah systems, called Restricted Access with Collision and Interference Resolution (RACIR).We introduce a decentralized group split algorithm that distributes the participating stations into multiple groups based on a probabilistic estimation in order to resolve collisions. Furthermore, we propose a decentralized channel access procedure that avoids the HPT problem and resolves interference with the incumbent receiver. We analyze the performance of our proposed MAC protocol in terms of normalized throughput, packet delay and energy consumption with the Markov model and analytic expressions. The results are quite promising, which makes the RACIR protocol a strong candidate for the CR-based IoT environment. [ABSTRACT FROM AUTHOR]

Background: To compare the hemodynamic changes during induction of anesthesia with propofol and sevoflurane in children undergoing forearm orthopedic surgeries. Methods: In this descriptive study 60 pediatric patients, scheduled for forearm orthopedic surgical procedure under general anesthesia requiring LMA insertion were included. The selected patients were allocated into two groups; A (Propofol) and B (Sevoflurane) of 30 each. Group A was induced with IV Propofol 2mg/kg while Group B was induced by sevoflurane 6-8%. Anesthetic induction was supposedly achieved after loss of eyelash reflex. Results: Compared with base line, both groups showed a statistically significant decline in mean arterial pressure after induction. Propofol group (A) showed a larger transient decrease in MAP compared to sevoflurane group (B) (p<0.001). There was a statistical significant overall greater decline in MAP and heart rate after induction with propofol when compared with sevoflurane. Conclusion: Sevoflurane provides slightly better hemodynamic stability compared to propofol during anesthetic induction. [ABSTRACT FROM AUTHOR]

This paper aims to explore the importance of kinship system in tribal areas (Fazla Kach) of province Punjab, Pakistan. An exploratory research was conducted by using the qualitative research tools for data collection including key informant interviewing and participant observation as the major tools for data collection. It was revealed through data analysis that kinship system plays a central role in tribal life. Kinship system merely serves as the code of tribal life of Buzdar tribe of Fazla Kach, Punjab Pakistan. Extended family system is lead and identified by the grandfather's name who possesses the ultimate decision-making power. Kinship system plays a pivotal role to maintain social order through repressive tribal laws which are executed through Meal-Maraka (indigenous conflict resolution body). Each minimal lineage is represented by Sofaid Rish (white bearded). Furthermore, data revealed that segmentary lineage kinship is decisive in formal electoral process. Ritual and ceremonies, property inheritance, communal land holding and sheep flock herding and conflict resolution are conducted via patriarchal kinship system. Females are very active in daily chores of life yet are invisible in socio-political and economic system of the tribe. [ABSTRACT FROM AUTHOR]