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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]

Memristors have several chaotic dynamic models and have been used successfully in various fields, including secure communication systems, information storage, and artificial neural networks. The memristor-based four-dimensional chaotic (FDMC) systems generate unpredictable and intricate time domain signals. Parameter fluctuations in the FDMC system may give birth to chaos, making it difficult to suppress. Stabilizing chaos in the FDMC system improves the circuit's performance. This paper synthesizes a novel time-efficient chatter-free nonlinear robust adaptive control (NLRAC) technique that stabilizes chaos in the FDMC system affected by time-varying unknown bounded exogenous disturbances and model uncertainties. The proposed NLRAC strategy decimates the time-varying unknown bounded exogenous disturbances and model uncertainties effects; it establishes a faster, smoother state-variable trajectories convergence to the zero vicinity. The theoretical analysis and mathematical proofs are based on the Lyapunov stability technique. Computer simulation results show that the proposed NLRAC technique effectively brings the FDMC system's state-variable trajectories to zero with reduced fluctuations for control input signals and state-variable trajectories. This feedback controller's attribute enhances closed-loop stability performance, improves precision, and reduces risk overshoot. The paper includes comparative computer simulation results to endorse the proposed controller performance. [ABSTRACT FROM AUTHOR]

Multiplexing techniques will be employed based on duration, polarization, and frequency to achieve the expanding demand for broadcast bandwidth. Adding time as an additional aspect to transmission networks has been put out as a flexible way to handle potential bandwidth problems. For interaction programs such as space imaging, optical fiber setup, submerged portable visual hyperlinks, onboard interconnects, information centers indoor relations, radio signals, and auditory interactions, we examine the possibilities of utilizing time as a further level of independence. Beginning in 2010, space-divisional multiplexer (SDM) studies gained popularity, partly because they had been suggested to increase the data-carrying ability of fiber optics while also boosting effectiveness through collaboration on assets. The proposed SDM transfer technologies spectrum includes identical single-mode fibers using shared amplifiers pumping laser light and the complete spatial arrangement of transceiver equipment, signal analysis, and amplifiers near a fiber with more than 100 geographical networks composed of several threads, all executing various forms. In this study, we discuss SDM study's advancements. The major categories and characteristics of innovative SDM fibers, like multiple-core fibers (MCFs), multiple-mode fibers, fewer-mode MCFs, and coupled-core MCFs, are initially described. While examining present tendencies and speculating on potential advances and uses outside optical data transfer, we provide analyses between various fiber kinds. [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]

Presently, different types of eye diseases, such as glaucoma, myopia, infection, and dry eyes are treated with topical eye drops. However, due to ocular surface barriers, eye drops require multiple administrations, which may cause several risks, thereby necessitating additional strategies. Some of the key characteristics of an ideal ocular drug delivery system are as follows: (a) good penetration into cornea, (b) high drug retention in the ocular tissues, (c) targetability to the desired regions of the eye, and (d) good bioavailability. It is worthy to note that the corneal epithelial tight junctions hinder the permeation of therapeutics through the cornea. Therefore, it is necessary to design nanocarriers that can overcome these barriers and enhance drug penetration into the inner parts of the eye. Moreover, intelligent multifunctional nanocarriers can be designed to include cavities, which may help encapsulate sufficient amount of the drug. In addition, nanocarriers can be modified with the targeting moieties. Different types of nanocarriers have been developed for ocular drug delivery applications, including emulsions, liposomes, micelles, and nanoparticles. However, these formulations may be rapidly cleared from the eye. The therapeutic use of the nanoparticles (NPs) is also hindered by the non-specific adsorption of proteins on NPs, which may limit their interaction with the cellular moieties or other targeted biological factors. Functional drug delivery systems (DDS), which can offer targeted ocular drug delivery while avoiding the non-specific protein adsorption could exhibit great potential. This could be further realized by the on-demand DDS, which can respond to the stimuli in a spatio-temporal fashion. The cell-mediated DDS offer another valuable platform for ophthalmological drug delivery. [Display omitted] • Nanocarriers-based ocular drug delivery systems (DDS) hold great promise. • Ocular DDS (ODDS) may help overcome limitations associated with traditional carriers. • DDS can be comprised of polymers, ceramics, and medical devices. • ODDS may be functionalized to enhance targetability, penetration, and retention. • Nanocarriers may be tailored to co-load hydrophilic and hydrophobic drugs. [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]

Aim This study aimed to investigate the high-resolution phenotypic and genotypic characterization of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli strains isolated from hospitalized patients to explore the resistance genes and mobile genetic elements (MGEs) involved in horizontal dissemination. Methods Between May and September 2021, a total of 216 ESBL-producing E. coli isolates were recovered from multiple departments. The identification of strains was performed using MALDI-TOF mass spectrometry and PCR, while antibiotic susceptibility testing was carried out using the Vitek 2 COMPACT system to determine resistance patterns, while PCR was used to detect different resistance genes and MGEs. In addition, a conjugation assay was performed to investigate the horizontal gene transfer of resistance genes. Selected isolates underwent whole-genome sequencing (WGS) using the Illumina MiSeq platform. Results A total of 216 out of 409 E. coli isolates recovered from a tertiary hospital were observed to be ESBL-producing, giving a carriage rate of 52.8%, as determined by phenotypic screening. The most frequent sources of ESBL-producing E. coli isolates were urine (129/216, 59.72%) and blood (50/216, 23.14%). The most prevalent ESBL genes identified were bla CTX-M (60.18%), bla TEM (40.27%), and bla SHV (18.05%). Three E. coli isolates were found to carry the genes bla NDM, mcr-1 , and fosA3 genes. The most prevalent MGEs were IS 26 (95.37%), Int (87.03%), and IncFIB (76.85%). WGS analysis of eight MDR E. coli strains revealed that these isolates belonged to eight different sequence types (STs) and serotypes and were found to harbor multiple plasmid replicons and virulence factors. Conclusion This study highlights a high incidence of antibiotic resistance genes and MGEs associated with the dissemination of ESBLs and other resistance genes. [ABSTRACT FROM AUTHOR]

Citrus tristeza virus (CTV) produces the most damaging disease of citrus worldwide and is a continuous threat to the citrus industry. It is primarily spread through infected root-stock and brown citrus aphid in a semi-persistent manner. Infected trees produce small sized and poor quality fruit, and in severe cases tree dies. Sour orange rootstock is highly susceptible to CTV. Several mild and severe strains have been identified which produce from invisible-to-visible symptoms in diseased plants. Existence of multiple CTV strains in nature is a challenge for CTV management. Symptomless infection in certain citrus species results in the inoculum build up and further spread of the disease. Breeding for CTV resistance genes is a long and time-consuming process that takes 8-10 years before a CTV resistant variety is developed. Genomic manipulation of CTV genome is challenging due to its larger genome size. Modern biotechnological tools can be used to control this disease and to prevent its spread in the future. However, CTV offers a valuable research tool for its role as a stable marker in genetic transformation of plants. This review highlights the challenges in developing resistant citrus cultivars against CTV and future prospects of CTV and is an update to the research status of CTV. [ABSTRACT FROM AUTHOR]

Parthenium hysterophorus is an invasive weed, produces a lot of non edible biomass that is hazardous to humans. This study provides an insight to its beneficial use by converting the biomass into value-added materials like compost and biochar and subsequent amendment in soil as fertilizer. The biochar was prepared in a locally fabricated charcolator while the compost was prepared in a rolling tumbler. Two-year field experiment was set up using different combinations of biochar (BC), compost (C) and commercial fertilizer (CF) in the rice-wheat cultivation system in Lahore, Pakistan to assess soil health and crops performance after characterizing the products using advanced analyses. GCMS analysis has revealed the presence of stigmasterol and campesterol (plant growth promoters) in prepared compost. Field data showed that the combined application of compost and biochar in rice and wheat fields significantly improved the characteristics of soil like SOM and CEC. Agronomic characteristics such as the number of grains per tiller, grain weight and biological yield were significantly higher in C + CF (half dose of each) and almost equal to CF in the first year. In the second year, both crops agronomic performance was considerably more evident and pronounced following the same pattern. All other agronomic features also followed the same pattern. Thus, mixed application of organic and inorganic fertilizer on recurrent basis is recommended to improve yield of wheat and rice along with soil amelioration in the rice wheat cultivation system. [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]

Hysteresis and other nonlinearities exhibited by piezoelectric materials significantly limit the tracking capability of piezoelectric actuators (PAs). To eliminate these effects, several model-based controllers adopted the inverse model-based approach. However, these controllers are overly sensitive to the uncertainties in the model parameters and can lead to poor tracking performance. This paper proposes a novel model-free learning-based controller to achieve high position tracking performance. The new combined feedforward-feedback controller synthesizes the control signal using the input and output data. The paper uses the passivity theory and the Lyapunov method to prove the system closed-loop stability and the boundedness of the tracking errors and the control signals. It further develops "intelligent" rules to ensure the system's robustness to transient disturbances. The proposed controller was tested using a commercial long-stroke piezoelectric actuator to assess its tracking performance. [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]

Pedilanthus leaf curl virus (PeLCV) is a widely encountered monopartite begomovirus with a wide host range that usually associates with a betasatellite. The cloned PeLCV used was highly infectious to Nicotiana benthamiana plants by agroinoculation and symptoms were enhanced by co-inoculation with tobacco leaf curl betasatellite (TbLCB). The study investigated the effects of the mutation of the coat protein (CP), V2, C2 and C4 genes of PeLCV on infectivity, symptoms and maintenance of TbLCB in N. benthamiana. Mutation of the CP abolished infectivity of PeLCV, which was not rescued by co-inoculation with TbLCB. Mutation of the V2 gene severely reduced infectivity that, in a small number of plants, was rescued by TbLCB, resulting in plants with very mild symptoms. Mutation of the C2 or V4 genes led to a significant reduction in virus infectivity, but also to non-symptomatic infections. Co-inoculation of either mutant with TbLCB led to a greater number of plants infected but fewer plants ultimately maintained the betasatellite, compared with inoculation of the betasatellite with the wild-type virus, indicating that the C2 and C4 proteins play a role in the maintenance of the betasatellite. For the C2 mutation, but not the C4 mutation, the presence of the betasatellite also resulted in mild symptoms. The results here, in conjunction with earlier studies, highlight commonalities as well as differences for the effects of gene mutations and interactions with betasatellites of different begomoviruses, indicating that begomovirus--betasatellite interaction is highly nuanced. [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]

Objectives: To investigate the occurrence and molecular features of ESBL‐producing and colistin‐resistant Escherichia coli isolates recovered from healthy food‐producing animals in Pakistan. Methods: A total of 153 E. coli isolates were recovered from 250 faecal samples collected from livestock and poultry. The antibiotic susceptibility, resistant determinants and mobile genetic elements were determined for all the isolates. The clonal relatedness was analysed by MLST. Plasmids harbouring, localization and transferability of mcr‐1 gene were carried out by Southern hybridization, S1‐PFGE and transconjugation. Results: Out of 153 E. coli strains, 49.01% isolates were ESBLs producers, whereas 18.95% were resistant to colistin and 84.31% of the isolates. Multidrug resistance was found in 84% of the isolates. The ESBL‐producing E. coli in buffaloes, cattle, sheep, goat and broilers faecal samples were 60%, 74%, 54%, 50% and 68%, respectively. Among the ESBLs genes, blaCTX‐M was the most prevalent group detected in 98.66%, while only mcr‐1 of the colistin‐resistant genes could be PCR amplified in 29 isolates. The common MGEs found were ISECP1 (35.13%), ISCR1 (33.78%), ISApl1 (20.27%) and Inti1 (58.10%). The most predominant Inc. types found were IncFIB 46.66%, followed by IncFIA 30.66%, IncFIC 26.66%, IncFrepB 26.66%, IncHI2 26.66%, IncP 22.66% and IncX4 21.33%. The most frequent sequence type detected was ST58. Southern blot and S1‐PFGE confirmed the plasmid harbouring of mcr‐1 gene. Conclusion: The co‐occurrence of mcr‐1 and ESBLs‐encoding genes, along with MGEs in E. coli from healthy food animals in Pakistan, is a major concern. Significance and Impact of Study: Antimicrobial resistance can be transferred from animals to humans by direct contact or via the food chain and environment. The prevalence and co‐occurrence of ESBL and colistin resistance genes from food‐producing animals is rare in Pakistan. To our knowledge, this is the first report to find ESBLs and mcr‐1‐harbouring E. coli from the faecal samples of the healthy food‐producing animals in Pakistan. The presence of ARGs in association with MGEs, co‐harbouring the virulence factors, as determined in the current study, is a severe threat to livestock and the human community as it has horizontally and food web transferability. [ABSTRACT FROM AUTHOR]

This study describes the results of investigations into the effects of the makeup of aliphatic polyester polyol synthesized by mixing adipic acid with the variable quantities of glycerin (GLY) is a cross-linker upon the mechanical parameters of polyurethane (PU) polymer. Polyurethane (PU) polymer is a thermoplastic polymer that is used to make foams for seats etc. Aliphatic polyester polyols are produced through the esterification of acids, an appropriate catalyst, and glycerin (GLY); whereas a polyurethane polyol is made through the pre-polymerization of (aliphatic polyester) polyol with pure prepolymer, i.e., methylene diphenyl diisocyanate (MDI), and subsequent polymerization of the polyol with prepolymer Shore A hardness and other mechanical attributes of polyurethane are investigated via shore A testing for hardness. Along with this, apparent density was determined using the (American Society for Testing and Materials) ASTM D1622-08 method, as well as resistance against abrasion was determined using a DIN abrasion wear resistance tester. Fourier-transform infrared spectroscopy (FTIR) examination is employed to analyze the structural features of the sample. The findings suggest that the shoreline increased hardness of the PU is associated with an increase in GLY concentrations, which ranges from 4 to 12 g. In spite of this, the PU density shows a decrease with an increase in crosslinker content. The abrasion wears resistance of polyurethane, on the other hand, increases as the concentration of GLY in the polyurethane increases. The presence of specific peaks in the FTIR spectrum supports the creation of polyurethane, according to the results of a structural investigation. [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]

Pollution from dye-containing industrial wastewater is a major health hazard in many nations, necessitating modern remediation approaches. Herein, zinc oxide (ZnO) was employed to degrade methyl orange (MO) as an organic dye pollutant under UV light irradiation. The performance was observed experimentally and theoretically under optimized conditions including the pH (11), the concentration of the nanoparticle solution (900 ppm), and time (3 h), resulting in a degradation efficiency of 89.6%. Furthermore, the influence of various parameters on MO degradation was evaluated by response surface methodology (RSM). X-ray diffraction (XRD) and transmission electron microscopy (TEM) was performed to investigate the crystallinity and morphological behavior of ZnO-NPs. In addition, the surface chemical composition was evaluated by the XPS analysis. This study evaluates the degradation efficiency of ~ 90% using single metal oxide to degrade MO, opening new opportunities for environmental applications. [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]

This paper proposes a novel continuous-time robust direct adaptive controller for the attitude control of the three-dimensional unknown chaotic spacecraft system. It considers that the plant's nonlinear terms, exogenous disturbances, and model uncertainties are unknown and bounded; the controller design is independent of the system's nonlinear terms. These controller attributes flourish the robust performance of the closed-loop and establish smooth state vector convergence to zero. The proposed controller consists of three parts: (1) a linear controller establishes the stability of the closed-loop at the origin, (2) a nonlinear controller component that autonomously adjusts the feedback gain, and (3) a nonlinear adaptive controller compensates for the model uncertainties and external disturbances using the online estimates of bounds and model uncertainties. The output of this part remains within a given upper and lower bound. The feedback controller gain is large when the state variables are away from the origin and become small in the origin's vicinity. This feature is novel and contributes to the synthesis of smooth control effort that establishes robust fast and oscillation-free convergence of the state variables to zero. The Lyapunov direct stability analysis assures the global asymptotic robust stability of the closed-loop. Computer simulations and comparative analysis are included to verify the theoretical findings. [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]

Two of the multiple limitations of phytoextraction efficiency (PE %) of TSW polluted soils are: (i) low growth of plant performance, (ii) poor bioavailability of excessive essential and heavy metals (ascribed as Category-I and II metals respectively) The current study reports biostimulant role of allochthonous Trichoderma harzianum (F1) and autochthonous Trichoderma pseudokoningii (F2) in growth of Tagetes patula L. and uptake of Category-I & II metals from TSW-soil (0, 5 & 10%). Significantly higher growth (27.5–47.8% dry wt. than Control) and highly significantly higher uptake of Category-I & II metals (72–80% Ca, 32–69% K, 72–76% Na & 73–86% Cd, 63–100% Cr, 72–77% Cu, 73–78% Fe, 43–77% Mg, 22–33% Ni, 70–73% Zn) was observed in T. patula applied with F1 + F2 treatment. The PE (%) parameters viz.specific extraction yield, tolerance and translocation index of Category-I & II metals were higher in plants cultivated on fungal inoculated TSW:soil. The Trichoderma spp. acted as strong biostimulants for enhancing plant growth and conc. of catalase (CAT, 44-52% than control), superoxide dismutase (SOD, 37–43%), soluble proteins (37-68%) and total chlorophyll (10–26%) in T. patula during metal phytoextraction of TSW:soil. Novelty statement Due to multiple socio-economic constraints for effective management of tannery solid waste (TSW), the heavy metal phytoextraction seems to be one of the promising approaches. However, due to complex composition of TSW, that is, with more than 37 components, high pH, multiple types and high conc. of metals; there lies huge challenge of enhancing phytoextraction efficiency (PE %). This can be done by enhancing growth of hyperaccumulator plants and increasing bioavailable fraction of metals. The current study suggests application of selected fungal biostimulants for increasing growth of T. patula while improving bioavailable fraction of the total metal contents of the TSW: soil. [ABSTRACT FROM AUTHOR]

This paper is focused on facilitating the manufacturer in making quantity allocation decisions. A revenue-sharing model with prior commitment from the retailers, two-way penalties, and reallocation of pre-allocated quantities is proposed to coordinate a supply chain comprising one manufacturer and two retailers facing stochastic demand. Over and under-purchase penalties are introduced to motivate the retailers to commit close to expected demand. In contrast, the under-supply penalty is presented for the manufacturer to compensate the stock-out loss of the retailers. Reallocation of pre-allocated quantities is also allowed to reduce the allocation risk of the manufacturer. The analysis reveals that the proposed model helps motivate stakeholders to share accurate demand information through a reward-penalty mechanism. Moreover, coordination improves the performance of the supply chain with a "win-win" solution for the stakeholders. The case study results reveal that the proposed model through the reward-penalty mechanism ensures true information sharing. Furthermore, reallocation reduces the possibility of waste. This is the first revenue-sharing model, including prior commitments, two-way penalties, and reallocation of pre-allocated quantities. [ABSTRACT FROM AUTHOR]

This paper proposes a novel nonlinear adaptive controller for the synchronization of two identical unknown chaotic systems. The proposed controller accomplishes fast convergence of the steady-state error to the origin and reduces the amplitude of the oscillations in the error signals during the transient. The rapid convergence increases the disturbance rejection attributes of the controller. The reduction in the oscillations' magnitude decreases energy consumption and lowers the actuators' degradation, reducing the probability of failure. This controller consists of linear adaptive and nonlinear control components, and they jointly synthesize control signals to penalize the synchronization error. The direct linear adaptive term keeps the closed-loop system stable; it ensures that the synchronization error converges to zero. The nonlinear terms heavily penalize the large state error vector in the transient, and its effect becomes minimal in the steady-state. The linear adaptive control is active in the steady-state, which synthesizes a smooth control signal in the vicinity of zero; this behavior causes oscillation free convergence of the error. Analysis based on the Lyapunov direct theorem proves the global asymptotic stabilization of the closed-loop at the origin. The paper also introduces parameters update laws that estimate the controller and unknown parameters of the master system and assure the convergence. This work also presents a comparative study of a numerical example of two identical Lorenz-Like unknown chaotic systems. [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]

Purpose: The purpose of this paper is to develop some interesting results in the field of chaotic synchronization with a new finite-time controller to reduce the time of convergence. Design/methodology/approach: This article proposes a finite-time controller for the synchronization of hyper(chaotic) systems in a given time. The chaotic systems are perturbed by the model uncertainties and external disturbances. The designed controller achieves finite-time synchronization convergence to the steady-state error without oscillation and elimination of the nonlinear terms from the closed-loop system. The finite-time synchronization convergence reduces the hacking duration and recovers the embedded message in chaotic signals within a given preassigned limited time. The free oscillation convergence keeps the energy consumption low and alleviates failure chances of the actuator. The proposed finite-time controller is a combination of linear and nonlinear parts. The linear part keeps the stability of the closed-loop, the nonlinear part increases the rate of convergence to the origin. A generalized form of analytical stability proof is derived for the synchronization of chaotic and hyper-chaotic systems. The simulation results provide the validation of the accomplish synchronization for the Lu chaotic and hyper-chaotic systems. Findings: The designed controller not only reduces the time of convergence without oscillation of the trajectories which can run the system for a given time domain. Originality/value: This work is originally written by the author. [ABSTRACT FROM AUTHOR]

AbstractFrom tannery effluent (TE) severely polluted with heavy metals (HMs viz., Cr, Cu, Cd, and Pb), hydrophytic phytoextraction remains a challenge as transplanted plants succumb to death on facing acclimatization shock. Current study was aimed at diluting TE with harvested rainwater (HR) for improving HM phytoextraction potential of Phragmites australis (a hydrophyte) assisted with phycoremediation of coupled algae (viz., Oedogonium sp. and Pithophora sp.). The TE:HR dilutions (TEDs) 0, 25, 50, 75, and 100% (v/v) included three sets: set-1 included algae only, set-2 included P. australis only and set-3 included P. australis coupled with combined algal inoculum. Results showed that P. australis assisted with HR dilution and combined algal inoculum showed significantly greater uptake of HMs from each of the TEDs than respective control treatments. Combined algal application in the TEDs proved phycoremediation assistants based on their bioaccumulation factor (BF). The dry biomass of P. australis in TEDs applied with phycoremediation assistants remained greater than uninoculated ones. Overall, HM translocation factor (TF) of P. australis for Cr, Cu, Cd, and Pb remained ≥ 1. The study concludes that HM phytoextraction is substantially increased when concentrated TE is diluted with HR and assisted with phycoremediation of HM tolerant algae. [ABSTRACT FROM AUTHOR]

Premature ventricular contractions (PVCs) are one of the most common cardiovascular diseases with high risk to a large population of patients. It has been shown that supervised learning algorithms can detect PVCs from beat-level ECG data. However, a huge human effort is needed in order to achieve an accurate detection rate. A convolutional autoencoder was trained in this work in an unsupervised fashion to extract features automatically with zero prior specialized knowledge. Random forest was adopted as a supervised algorithm trained on the features generated by the autoencoder. Various active learning selection strategies, uncertainty-based and diversity-based, were studied on top of the random forest. In each iteration of active learning, the training data are updated with newly selected samples and fed into the classifier. The performance on an independent validation set is recorded in each iteration. As a result, among the different uncertainty sampling strategies, the least confidence score shows a better F1 score of 0.85 than other methods. In between the two diversity-based strategies, the representative clustering sample had the best F1 score than the k-center-greedy algorithm. By comparing the performance of different active learning methods trained on half of the original data size with the same classifier trained on the full set, the F1 score of least confidence is still better than the full set. This study demonstrates that active learning could help reduce human annotation effort by achieving the same level of performance as the classifier trained on the fully annotated training data. [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]