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Background: Typhoid fever caused by Salmonella enterica serovar Typhi (S. typhi) continues to pose a significant risk to public health in developing countries, including Pakistan. This study investigated the epidemiological factors linked to suspected and confirmed S. typhi infections in Peshawar's hospital population. Methodology: A total of 5735 blood samples of patients with suspected enteric fever were collected from September 2022 to November 2023. S. typhi infection was confirmed using microbiological culture of blood samples, biochemical-based tests, and DNA-sequencing methods. Drug sensitivity testing on cultures was conducted as per the CLSI guidelines. Chi-square tests were used to analyze the clinical and epidemiologic characteristics of 5735 samples stratified by S. typhi infection status, and risk factors were assessed by applying logistic regression models to estimate odds ratios (ORs). Results: The number of confirmed typhoid fever cases in this hospital-based study population was 691 (/5735, 12.0%), more prevalent in males (447/3235 13.8%) and children (0–11 years) (429/2747, 15.6%). Compared to children, the risk of S. typhi infection was lower in adolescence (adjusted OR = 0.52; 95% CI: 0.42–0.66), adulthood (19–59 years; aOR = 0.30; 95% CI: 0.25–0.38), and older adulthood (aOR = 0.08; 95% CI: 0.04–0.18) (p < 0.001). Compared to males, the risk of S. typhi infection was lower in females (aOR = 0.67; 95% CI = 0.56–0.80; p = 0.002). Living in a rural residence (compared to urban) was associated with a higher risk of infection (aOR = 1.38; 95% CI: 1.16–1.63; p = 0.001), while access to a groundwater source (compared to municipal water supply) led to a lower risk (aOR = 0.56; 95% CI: 0.43–0.73; p = 0.002). Vaccination demonstrated a robust protective effect (aOR = 0.069; 95% CI = 0.04–0.11, p = 0.002). For those with typhoid infections, clinical biomarker analysis revealed the presence of leucopenia (65/691, 9.4%), thrombocytopenia (130/691, 18.8%), and elevated alanine aminotransferase (ALT) (402/691, 58.2%) and C-reactive protein (CRP) (690/691, 99.9%) levels. Worryingly, among the positive S. typhi isolates, there was a high prevalence of drug resistance (653/691), including multidrug-resistant (MDR 82/691, 11.9%) and extensively drug-resistant types (XDR, 571/691, 82.6%). Conclusions: This study highlights the importance of age, sex, locality, water source, and vaccination status in shaping the epidemiological landscape of S. typhi in the Peshawar district. It implies that expanding vaccination coverage to the broader population of Khyber Pakhtunkhwa province, particularly in the district of Peshawar, would be beneficial. [ABSTRACT FROM AUTHOR]

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of −8.9, −8.7 and −8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials. [ABSTRACT FROM AUTHOR]

High concentrations of toxic cadmium (Cd) in soils are problematic as the element accumulates in food crops such as rice and cacao. A mitigation strategy to minimise Cd accumulation is to enhance the competitive uptake of plant-essential metals. Theobroma cacao seedlings were grown hydroponically with added Cd. Eight different treatments were used, which included/excluded hydroponic or foliar zinc (Zn) and/or iron (Fe) for the final growth period. Analyses of Cd concentrations and natural stable isotope compositions by multiple collector ICP-MS were conducted. Cadmium uptake and translocation decreased when Fe was removed from the hydroponic solutions, while the application of foliar Zn-EDTA may enhance Cd translocation. No significant differences in isotope fractionation during uptake were found between treatments. Data from all treatments fit a single Cd isotope fractionation model associated with sequestration (seq) of isotopically light Cd in roots and unidirectional mobilisation (mob) of isotopically heavier Cd to the leaves (ε114Cdseq-mob = −0.13‰). This result is in excellent agreement with data from an investigation of 19 genetically diverse cacao clones. The different Cd dynamics exhibited by the clones and seen in response to different Fe availability may be linked to similar physiological processes, such as the regulation of specific transporter proteins. [ABSTRACT FROM AUTHOR]

Land use land cover (LULC) changes have emerged as a pivotal driver of environmental challenges in the Northwestern mountainous belts of Pakistan. These changes are increasingly recognized for their pervasive impacts on biodiversity and ecosystem services. The conversion of pastures and rangelands into other land uses is a key facet of LULC change, posing a substantial threat to the availability of animal feed sources. This study aims to evaluate LULC changes and investigate their consequences on animal feed sources in the Upper Kurram Valley, located in the Koh-e-Safid mountain of Northwestern Pakistan. The study employs a multidisciplinary methodological approach that incorporates remotely sensed data, focus group discussions, interviews, and field observations. The study findings uncover a notable decline in rangeland (26.6%) and forest cover (28.7%) over a span of more than three decades (1987–2019). The shrinkage of rangeland has spurred an increased reliance on crop residues and fodder crops. The free grazing practices have been replaced by stall-feeding and controlled grazing methods. This declining rangeland resources has negatively affected animal husbandry, and the average number of livestock per household decreased from 32 in 1980 to 3.7 in 2019. In essence, this transition has not only impacted animal feed sources but also reshaped the livelihoods of local communities closely connected to animal husbandry. [ABSTRACT FROM AUTHOR]

Streptococcus mutans, the primary cause of dental caries, relies on its ability to create and sustain a biofilm (dental plaque) for survival and pathogenicity in the oral cavity. This study was focused on the antimicrobial biofilm formation control and biofilm dispersal potential of Coumaric acid (CA) against Streptococcus mutans on the dentin surface. The biofilm was analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) viability assay, microtiter plate assay, production of extracellular polymeric substances (EPSs), florescence microscopy (surface coverage and biomass μm2) and three-dimensional (3D) surface plots. It was observed that CA at 0.01 mg/mL reduced bacterial growth by 5.51%, whereases at 1 mg/mL, a significant (p < 0.05) reduction (98.37%) was observed. However, at 1 mg/mL of CA, a 95.48% biofilm formation reduction was achieved, while a 73.45% biofilm dispersal (after 24 h. treatment) was achieved against the preformed biofilm. The MTT assay showed that at 1 mg/mL of CA, the viability of bacteria in the biofilm was markedly (p < 0.05) reduced to 73.44%. Moreover, polysaccharide (EPS) was reduced to 24.80 μg/mL and protein (EPS) to 41.47 μg/mL. ImageJ software (version 1.54 g) was used to process florescence images, and it was observed that the biofilm mass was reduced to 213 (μm2); the surface coverage was reduced to 0.079%. Furthermore, the 3D surface plots showed that the untreated biofilm was highly dense, with more fibril-like projections. Additionally, molecular docking predicted a possible interaction pattern of CA (ligand) with the receptor Competence Stimulating Peptide (UA159sp, PDB ID: 2I2J). Our findings suggest that CA has antibacterial and biofilm control efficacy against S. mutans associated with dental plaque under tested conditions. [ABSTRACT FROM AUTHOR]

Potentilla nepalensis belongs to the Rosaceae family and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in earlier studies. However, the PCs affecting human genes and their roles in the body have not previously been disclosed. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDSs), and MMGBSA methodologies. The SMILES format of PCs from the PubChem was used as input to DIGEP-Pred, with 764 identified as the inducing genes. Their enrichment studies have shown inducing genes' gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analyzing parameters performed in Cytoscape v3.10 revealed three therapeutic targets: TP53 from MS-, NR-, and NS-induced genes; HSPCB and Nf-kB1 from MR-induced genes. From 40 PCs, two PCs, 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of −8.6 and −8.0, and three PCs, 3a, (NR) 4a, and 4c (NS), with HSP protein of −9.6, −8.7, and −8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Therapeutic targets identified in this study have a prominent role in numerous cancers. Thus, further investigations such as in vivo and in vitro studies should be carried out to find the molecular functions and interlaying mechanism of the identified therapeutic targets on numerous cancer cell lines in considering the PCs of P. nepalensis. [ABSTRACT FROM AUTHOR]

The cocoa crop (Theobroma cacao L.) is known to be a host for several badnaviruses, some of which cause severe disease, while others are asymptomatic. Recently, the first preliminary evidence has been published concerning the occurrence of a polerovirus in cacao. We report here the first near-complete genome sequence of cacao polerovirus (CaPV) by combining bioinformatic searches of cacao transcript databases, with cloning from the infected germplasm. The reported novel genome has all the genome features known for poleroviruses from other species. Pairwise identity analyses of RNA-dependent RNA polymerase and coat protein indicates < 60% similarity of CaPV with any reported poleroviruses; hence, we propose that the polerovirus isolate reported in this study is a novel polerovirus. The genome sequence information was also used to develop a multiplex RT-PCR assay, which was applied to screen a selected range of germplasms and to identify several infected clones. Although there is no evidence that this virus causes any severe disease, this new information, together with a robust diagnostic assay, are of strategic importance in developing protocols for the safe international transfer of cacao germplasms. [ABSTRACT FROM AUTHOR]

Fossil fuel and electricity-powered irrigation techniques boost the water availability expense and increase greenhouse gas emissions. Especially in developing countries, solar-powered irrigation is becoming more popular as a response to the growing energy and environmental issues associated with agriculture systems. The existing study used data from 1080 wheat farmers in Balochistan, Pakistan, to investigate the impact of solar-powered irrigation system (SPIS) usage on the technical efficiency (TE) of wheat production. The TE of wheat production is estimated using a stochastic frontier production function, and the potential self-selectivity bias is addressed using an endogenous switching regression model. The findings indicated that 13.7% of the wheat cultivators assessed used SPISs to produce their crops. Using an endogenous switching regression model shows that SPIS usage increases the TE of wheat growers by 6.657%, after controlling for self-selection bias. While using SPISs, wheat farmers with large farms and farming familiarity had stronger positive effects on TE. The results highlight the need for more investigation and research into evidence-based good practice for SPIS solutions at the site level to ensure that the rollout of modern equipment not only drives the energy sector forward but also contributes significantly to our level playing field and sustainable environment. [ABSTRACT FROM AUTHOR]

Background: A substantial portion of the world's population owns and utilizes computers and mobile devices, contributing to the rapid expansion of digital advertising. Marketers swiftly recognized the communicative benefits of social media platforms like Facebook, YouTube, Twitter, Instagram, Snapchat, Pinterest, and LinkedIn. Considering the importance of social media platforms and digital modes of marketing, it is considered especially significant for small firms to integrate these platforms into their business strategies in order to improve performance. Methods: Based on this aim, this study collected data from 363 owners/managers of SMEs in Pakistan. Structural equation modeling is used to check the hypothesized model of the study. Results: The results show that compatibility, owner/manager support, employee IT skills, financial cost, government policies, and social influence significantly affect adoption of digital marketing by SMEs in Pakistan. Conclusions: Furthermore, digital marketing also positively affects SME performance. This paper discusses the study's findings as well as managerial and academic implications, including its limitations and future research avenues. [ABSTRACT FROM AUTHOR]

The growth and productivity of wheat crops depend on the availability of essential nutrients such as zinc (Zn) and potassium (K2O), which play critical roles in the plant's physiological and biochemical processes. This study aimed to investigate the synergizing effect of zinc and potassium fertilizers on uptake of both the nutrients, growth, yield, and quality of the Hashim-08 cultivar and local landrace, during the 2019–2020 growing season in Dera Ismail Khan, Pakistan. The experiment was designed using a split plot pattern in a randomized complete pattern, with main plots for the wheat cultivars and subplots for the fertilizer treatments. Results indicated that both cultivars responded positively to the fertilizer treatments, with the local landrace exhibiting maximum plant height and biological yield, and improved Hashim-08, showing increased agronomic parameters, including the number of tillers and grains and spike length. Application of Zn and K2O fertilizers significantly enhanced agronomic parameters, such as the number of grains per plant, spike length, thousand-grain weight, grain yield, harvest index, Zn uptake of grain, dry gluten content, and grain moisture content, while crude protein and grain potassium remained relatively unchanged. The soil's Zn and K content dynamics were found to vary among treatments. In conclusion, the combined application of Zn and K2O fertilizers proved beneficial in improving the growth, yield, and quality of wheat crops, with the local landrace exhibiting lower grain yield but greater Zn uptake through fertilizer application. The study's findings highlight that the local landrace showed good response to the growth and qualitative parameter when compared with the Hashim-08 cultivar. Additionally, the combined application of Zn and K showed a positive relation in terms of nutrient uptake and soil Zn and K content. [ABSTRACT FROM AUTHOR]

In this article, a new deterministic disease system is constructed to study the influence of treatment adherence as well as awareness on the spread of tuberculosis (TB). The suggested model is composed of six various classes, whose dynamics are discussed in the sense of the Caputo fractional operator. Firstly the model existence of a solution along with a unique solution is checked to determine whether the system has a solution or not. The stability of a solution is also important, so we use the Ulam–Hyers concept of stability. The approximate solution analysis is checked by the technique of Laplace transformation using the Adomian decomposition concept. Such a solution is in series form which is decomposed into smaller terms and the next term is obtained from the previous one. The numerical simulation is established for the obtained schemes using different fractional orders along with a comparison of classical derivatives. Such an analysis will be helpful for testing more dynamics instead of only one type of integer order discussion. [ABSTRACT FROM AUTHOR]

In fuzzy artificial intelligent decision support systems, three-way intelligent-decision making (TWIDM) has played a very important role in ranking objects under the double hierarchy linguistic variable (DHLV). The 8 × 8 S-boxes are very important for image encryption in secure communication. Therefore, the aim of the present study is to develop a new approach to artificial intelligent three-way decision making via DHLV and apply it to S-box image encryption. Artificial intelligent based three-way decision-making problems with double hierarchy hesitant linguistic terms are developed. The first and second hierarchy hesitant linguistic term sets make up the double hierarchy hesitant linguistic term set, which allows for more flexible expressions of doubt and fuzziness. First, we define the Einstein operational laws, score function, and Einstein aggregation operators; i.e., double hierarchy hesitant linguistic Einstein weighted averaging and weighted geometric operators. First, the unknown weight vector for decision experts is determined by using aggregation operators and entropy measures for DHLV. Then, we find the weight vector for our criteria by using the distance measure. In TWIDM, conditional probability is determined by using the extended TOPSIS method for evaluating the S-boxes for image encryption. The expected losses are then computed by aggregating the loss functions with the help of Einstein-weighted averaging aggregation operators. Finally, we apply the minimum-loss decision rules for the selection of S-box to image encryption. The proposed decision technique has been compared with existing three-way decisions and the result of proposed three-way decision making for analyzing and ranking the S-box is very good and reliable for decision making. [ABSTRACT FROM AUTHOR]

Silybum marianum has been used for a variety of purposes all over the world. This plant is used to treat cancer, liver disease, and inflammation. Eleven endophytic bacteria were isolated from S. marianum collected from heavy metal polluted sites and identified using 16s rRNA sequencing in the current investigation. Three isolates stood out for having many features, including heavy metal resistance, plant growth stimulation, plant hormones, heavy metal toxicity remediation, and antibacterial action. SJLC (6.06 µg/L) and SJRB (5.98 µg/L) were the greatest producers of IAA among the isolates and were identified as Bacillus sp. and Lysinibacillus sp., respectively. Root and shoot length have improved as a result of IAA production. The SJLC was found to be effective against four of the pathogens tested. The strain SJLC showed the most activity against Bacillus cereus with a 20 mm zone of inhibition, followed by the isolate SJRB, which showed a 16 mm zone of inhibition against B. cereus. The same isolates also show inhibition against X. campestris. Almost majority of the Brassica napus plants inoculated with bacterial isolates were able to translocate and degrade heavy metals like Cr. Therefore, it was concluded that these isolates are capable to grow in highly polluted environments. [ABSTRACT FROM AUTHOR]

Cystic echinococcosis (CE), or hydatid cyst disease (HCD), is a zoonosis of significant importance caused by the cestode of Echinococcus granulosus sensu lato (s. l.) that affects mainly nomadic populations and has substantial economic consequences. Due to the 76% rural and nomadic population, Baluchistan is a highly endemic region in Pakistan for CE; however, it has not yet been investigated for CE. For this purpose, this study was carried out to investigate the molecular epidemiology of CE in this region. In total, 23 human hydatid cyst samples were collected from tertiary health care units in Baluchistan and processed for DNA extraction, which was then followed by sequencing of the cox1 mitochondrial gene of all 23 collected samples, genotyping, and phylogenetic and haplotype analysis. Most subjects were livestock owners (39.13%) in rural settings (73.91%). Most patients (73.19%) were pet owners (dogs) and used water from open sources for drinking. The liver was the most affected organ (52.17%), followed by the lungs (17.39%). Sequence analysis based on the cox1 gene revealed that EG genotype 1 (G1) was the most prevalent (56.52%), followed by G3 (34.78%), while some samples (8.7%) were identified as the Echinococcus canadensis (G6/7) genotype. A total of five haplotypes were detected with high haplotype diversity (0.80) and low nucleotide diversity (0.033). Phylogenetic analysis revealed two diverse sub-clades, each of G1 and G3 isolates from Baluchistan, that were evolutionarily related to previously reported G1 and G3 isolates from Pakistan and China. On the other hand, the G6/7 isolates of this study were evolutionarily identical to the already reported G6/7 isolates from Pakistan, Turkey, and Kazakhstan. This study concludes that diverse G1 and G3 EG isolates are present in this part of Pakistan, while the G6/G7 genotype was reported for the first time from Baluchistan. [ABSTRACT FROM AUTHOR]

The cost-effective adsorbents of carbonized pistachio shell magnetic nanoparticles (CPSMNPs) were synthesized. SEM, EDX, and BET characterized the prepared CPSMNPs. The CPSMNPs were used as adsorbents to remove Metanil Yellow (MY) dye. The adsorption of MY was investigated with the effect of pH, contact time, initial dye concentration, adsorbent dose, and temperature. The SEM image of CPSMNPs reveals fine particles with an average size of 400–700 nm and a substantial surface area increase (112.58 m2/g). The EDX analysis confirms the carbonization of PS to CPS and the successful impregnation of Fe3O4 nanoparticles. CPSMNPs showed excellent adsorption efficiency, i.e., 94% for adsorption of MY of 10 mL of 100 ppm MY at optimum conditions. Kinetics data fit pseudo-second-order kinetics. The Langmuir isotherm better represents the equilibrium data with the spontaneous sorption process. This study investigates that the synthesized nanoparticles have an excellent texture and can be used as a special adsorbent for the adsorption of wastewater pollutants like MY. [ABSTRACT FROM AUTHOR]

Probiotics are delivered orally for treating gastrointestinal tract (GIT) infections; thus, they should be protected from the harsh environment of the GIT, such as through microencapsulation. Here, we microencapsulated cells of the probiotic Lacticaseibacillus rhamnosus GG via the liquid-droplet-forming method and evaluated them for oral delivery of bovine lactoferrin (bLf). Briefly, sodium alginate capsules (G-capsules) were first prepared, crosslinked with calcium chloride (C-capsules), and then modified with disodium hydrogen phosphate (M-capsules). All capsules showed good swelling behavior in the order of G-capsules > C-capsules > M-capsules in simulated gastric fluid (SGF, pH 2) and simulated intestinal fluid (SIF, pH 7.2). FE-SEM observations showed the formation of porous surfaces and successful microencapsulation of L. rhamnosus GG cells. The microencapsulated probiotics showed 85% and 77% viability in SGF and SIF, respectively, after 300 min. Compared to the 65% and 70% viability of gelation-encapsulated and crosslinking-encapsulated L. rhamnosus GG cells, respectively, the mineralization-encapsulated cells showed up to 85% viability after 300 min in SIF. The entrapment of bLf in the mineralization-encapsulated L. rhamnosus GG cells did not show any toxicity to the cells. FTIR spectroscopy confirmed the successful surface modification of L. rhamnosus GG cells via gelation, crosslinking, and mineralization, along with the entrapment of bLf on the surface of microencapsulated cells. The findings of these studies show that the microencapsulated L. rhamnosus GG cells with natural polyelectrolytes could be used as stable carriers for the oral and sustainable delivery of beneficial biotherapeutics without compromising their viability and the activity of probiotics. [ABSTRACT FROM AUTHOR]

Simple Summary: Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Due to the absence of specific early symptoms, most of CRC patients are often diagnosed at late stages. Different screening and diagnostic biomarkers are currently used for risk stratification and early detection of CRC, which might prolong the overall survival. High-throughput technologies have witnessed rapid advancements in the last decade. Consequently, the development of multiple omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, microbiomics, and lipidomics, has been widely applied to develop novel biomarkers that could contribute to the clinical management of CRC. In this paper, we aim to summarize the recent advances and future perspectives in using multi-omics technologies in CRC research, and reveal the potential implications of multi-omics for discovering novel biomarkers and enhancing clinical evaluations. Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments. [ABSTRACT FROM AUTHOR]

With the economic crisis going around the world, a new approach, "build back better", has been adopted as a recovery package for various systems. The tsunami detection and warning system is one such system, crucial for saving human lives and infrastructure. While designing a tsunami detection system, the social, economic, and geographical circumstances are considered to be vital. This research is focused on designing a low-cost early warning system mainly for underdeveloped countries, which are more prone to tsunami damage due to a lack of any reliable early warning and detection systems. Such countries require proper cost-effective solutions to address these issues. Previous research has shown that the existing systems are either very costly or hard to implement and manage. In this study, we present a wireless sensor networking model, which is an optimized model in terms of cost, delay, and energy consumption. This research contemplates the techniques and advantages of the intelligence of marine animals. We propose a fuzzy logic-based approach for early tsunami detection, using electromagnetic and pressure sensors, based on the behavioral attributes of turtles and real-time values of earthquakes and water levels. [ABSTRACT FROM AUTHOR]

A new COVID-19 variant, Omicron, has emerged from South Africa, indicating that the pandemic will not be over anytime soon. An unimaginable amount of economic damage has resulted from the pandemic. Omicron and its economic implications are discussed in detail in this review article. It also includes statistics on occurrence, mortality, and recuperation in Pakistan and data on the country's immunization coverage. Developing countries with unstable economies, such as Pakistan, have experienced increased economic difficulties. As a result, all developed and underdeveloped countries should strictly adhere to preventive measures and improvements in diagnostic tests and vaccine development to bring the pandemic under control. [ABSTRACT FROM AUTHOR]

The current studies were focused on the phytochemical profiling of two local wild Artemisia species, Artemisia scoparia and Artemisia absinthium leaves' essential oils, extracted via the hydro distillation method along with evaluation of their antioxidant as well as antimicrobial effects. The constituents of EOs were identified using a combined gas chromatography-mass spectrometric (GC-MS) technique. A total of 25 compounds in A. scoparia essential oil (EOAS) were identified, and 14 compounds with percentage abundance of >1% were tabulated, the major being tocopherol derivatives (47.55%). A total of nine compounds in Artemisia absinthium essential oil (EOAA) were enlisted (% age > 1%), the majority being oleic acid derivatives (41.45%). Strong antioxidant effects were pronounced by the EOAS in DPPH (IC50 = 285 ± 0.82 µg/mL) and in ABTS (IC50 = 295 ± 0.32 µg/mL) free radical scavenging assays. Both the EOs remained potent in inhibiting the growth of bacterial species; Escherichia coli (55–70%) and Shigella flexneri (60–75%) however remained moderately effective against Bacillus subtilis as well as Staphylococcus aureus. Both EOAS and EOAA strongly inhibited the growth of the tested fungal species, especially Aspergillus species (up to 70%). The oils showed anti-cholinesterase potential by inhibiting both Acetylcholinesterase (AChE; IC50 = 30 ± 0.04 µg/mL (EOAS), 32 ± 0.05 µg/mL (EOAA) and Butyrylcholinesterase (BChE; IC50 = 34 ± 0.07 µg/mL (EOAS), 36 ± 0.03 µg/mL (EOAA). In conclusion, the essential oils of A. scoparia and A. absinthium are promising antioxidant, antimicrobial and anticholinergic agents with a different phytochemical composition herein reported for the first time. [ABSTRACT FROM AUTHOR]

A one-dimensional (1D) coordination polymer [Cu2(bpba)(CH3COO)4] (1) and a two-dimensional (2D) coordination polymer [Cu(bpba)2(H2O)(NO3)](NO3)∙2H2O∙MeOH (2) were synthesized by the reaction between Cu(CH3COO)2∙H2O/Cu(NO3)2∙3H2O and bis(4-pyridyl)benzylamine (bpba). The Cu(II) ions of 1 and 2 have distorted-square pyramidal coordination with a paddle-wheel structure and an octahedral geometry, respectively. By coordinating the Cu(II) ions and bpba ligands, 1 and 2 formed zigzag 1D and puckered 2D coordination polymers, respectively. Polymer 1 exhibits strong emissions at 355 and 466 nm, whereas polymer 2 exhibits strong emissions only at 464 nm. The emissions are strongly dependent on the geometry of the Cu(II) ions linked by the bpba and anionic ligands. Polymer 1 exhibits a very strong antiferromagnetic interaction within the paddle-wheel dimer, whereas polymer 2 exhibits a very weak antiferromagnetic interaction through the bpba linkers and/or space. [ABSTRACT FROM AUTHOR]

Deforestation in remote mountainous regions is considered to be one of the fundamental elements for triggering changes in the biophysical environment driven by various socioeconomic parameters, particularly population growth and road construction in a previously inaccessible environment. A sudden increase in population exerts adverse impacts on the local natural resources, specifically forests. The present study is conducted in Tribal District Kurram, located in the northwestern mountainous belt of Pakistan. This study is aimed to analyze the temporal pattern of deforestation and to explore the impacts of population growth and accessibility on forest cover. It is based on remotely sensed data, focused group discussions, interviews and field observations. The satellite images were processed and classified using ArcGIS and ERDAS IMAGINE. The time span of this study is 1972 to 2019, which is further divided into three periods. The results revealed that almost half (48%) of the forest cover was reduced in ca. five decades. However, considerable variation has been observed in the deforestation rate during the study period. The results of this study revealed that both population change and accessibility have played a vital role in the deforestation process. [ABSTRACT FROM AUTHOR]

Background: Mismanagement in disaster relief operations (DROs) has created a requirement for fast, fair, and safe humanitarian logistics (HL). The deployment of digital solutions in DROs is supported by humanitarian organizations (HOs) as well as recent research; therefore, the key purpose of this article is to investigate the impact of digitalization for fast, fair, and safe HL in DROs. Methods: Primary empirical data were acquired from 449 disaster relief workers (DRWs) via questionnaires and by employing the snowball sampling methodology and partial least squares structural equation modeling (PLS-SEM) in SmartPLS 3. Results: The result of this study indicates that fast, fair, and safe HL is crucial because it can save people's lives and reduce suffering, and it achieves long-term sustainable development. The findings of the study could be beneficial to all catastrophe risk-management stakeholders as they look for ways to help victims. In addition, the ultimate beneficiaries of digitalized and effective HL will be all of society, notably disaster victims. Conclusions: By implementing proper technologies in DROs, the afflicted may receive needed resources on time, which can save many lives. The utility of the proposed variables is promoting awareness about HL in a fast, fair, and safe manner, and we discuss implications, limitations, and future research. The research adds to the literature by presenting the first quantitative evidence assessing the independent role of digitalization in generating fast, fair, and safe HL from one of the world's most disaster-prone countries. [ABSTRACT FROM AUTHOR]

Background: Type-2 diabetes mellitus (T2DM) is a non-communicable, life-threatening syndrome that is present all over the world. The use of eco-friendly, cost-effective and green synthesised nanoparticles (NPs) as a medicinal therapy in the treatment of T2DM is an attractive option. Aim: The present study aimed to evaluate the anti-diabetic potential of the phyto-synthesised silver nanoparticles (AgNPs) obtained from Phagnalon niveum plant methanolic extract. Methods: The green synthesised AgNPs made from Phagnalon niveum plant methanolic extract were analysed by Ultraviolet-Visible (UV-Vis) spectroscopy, and the functional groups involved in the reduction of the silver ions (Ag+) were characterised by Fourier Transform Infrared (FTIR) spectroscopy. The size and crystallinity were assessed via X-ray Diffraction (XRD). The morphology of AgNPs was confirmed using Scanning Electron Microscopy (SEM). The amount of silver (Ag) was estimated via energy dispersive X-ray (EDX) analysis. An intraperitoneal injection of 200 mg alloxan per kg albino Wistar rats' body weight, at eight weeks old and weighing 140–150 g, was used to induce diabetes mellitus (N = 25; n = 5/group). Group C: untreated normal control rats that only received distilled water, group DAC: diabetic control rats that received alloxan 200 mg/Kg body weight, DG: diabetic rats treated with glibenclamide at 0.5 mg/kg body weight, DE: diabetic rats that received methanolic P. niveum extract at 10 mg/Kg body weight, and DAgNPs: diabetic rates that received AgNPs synthesised from P. niveum at 10 mg/kg body weight. The blood glucose levels were monitored on days 0, 7, and 14, while lipid, liver, and kidney profiles were checked after dissection at the end of treatment (day 21). On the final day of the period study (day 21), an oral glucose tolerance test was carried out by administering orally 2 g/kg body weight of glucose to the respective groups, and the blood glucose level was checked. A fasting glucose level was measured using a glucometer. Urine samples were collected from each animal and analysed using lab-made assay kits for glucose, bilirubin, pH, leukocytes, and nitrite, among other factors. For statistical analyses, a one-way ANOVA and Dunnett's test were applied. Results: The green-mediated synthesis of AgNPs using P. niveum methanolic extract produced spherical and mono-dispersed NPs with a size ranging from 12 to 28 nm (average: 21 nm). Importantly, a significant reduction of blood glucose levels and an increase in body weight, as well as a remarkable improvement in lipid, liver, and kidney profiles, were noticed. Conclusions: The biosynthesised AgNPs significantly improved the abnormalities in body weight, urine, and serum levels, indicating that it is a promising anti-diabetic agent. [ABSTRACT FROM AUTHOR]

The multi-sonar distributed fusion system has been pervasively deployed to jointly detect and track marine targets. In the realistic scenario, the origin of locally transmitted tracks is uncertain due to clutter disturbance and the presence of multi-target. Moreover, attributed to the different sonar internal processing times and diverse communication delays between sonar and the fusion center, tracks unavoidably arrive in the fusion center with temporal out-of-sequence (OOS), both problems pose significant challenges to the fusion system. Under the distributed fusion framework with memory, this paper proposes a novel multiple forward prediction-integrated equivalent measurement fusion (MFP-IEMF) method, it fuses the multi-lag OOST with track origin uncertainty in an optimal manner and is capable to be implemented in both the synchronous and asynchronous multi-sonar tracks fusion system. Furthermore, a random central track initialization technique is also proposed to detect the randomly born marine target in time via quickly initiating and confirming true tracks. The numerical results show that the proposed algorithm achieves the same optimality as the existing OOS reprocessing method, and delivers substantially improved detection and tracking performance in terms of both ANCTT and estimation accuracy compared to the existing OOST discarding fusion method and the ANF-IFPFD method. [ABSTRACT FROM AUTHOR]

The objective of smart cities is to improve the quality of life for citizens by using Information and Communication Technology (ICT). The smart IoT environment consists of multiple sensor devices that continuously produce a large amount of data. In the IoT system, accurate inference from multi-sensor data is imperative to make a correct decision. Sensor data are often imprecise, resulting in low-quality inference results and wrong decisions. Correspondingly, single-context data are insufficient for making an accurate decision. In this paper, a novel compound context-aware scheme is proposed based on Bayesian inference to achieve accurate fusion and inference from the sensory data. In the proposed scheme, multi-sensor data are fused based on the relation and contexts of sensor data whether they are dependent or not on each other. Extensive computer simulations show that the proposed technique significantly improves the inference accuracy when it is compared to the other two representative Bayesian inference techniques. [ABSTRACT FROM AUTHOR]

Rockfall is a natural mountain hazard posing a severe threat to people, infrastructure, and vehicles along the transportation corridors. In this research, the standard Rockfall Hazard Rating System (RHRS) is slightly modified for the mountainous terrains of Pakistan through the quantification of animal activity along the highways. In the modified Rockfall Hazard and Rating System for Pakistan (RHRSP), animal activity is scored based on permanent and random animal tracks, shallow and higher altitudes, and shoulder width. The model is applied along the Karakoram Highway (KKH), which traverses a suture between Besham and Dasu (≈78 km), for Rockfall hazard and risk assessment mapping. An inventory of rockfalls, topples, and debris slides is compiled at 30 stations. Results show that rockfalls are mostly of the wedge and topple type failures. Fifty-seven percent of the area falls under the very-high to high hazard zone, 18% under moderate hazard, and 25% covers the low to very low hazard zone. Sixty-seven percent of the stretch is at very-high to high risk, distributed from Dubair to Dasu. The main reason for this risk is associated with narrow road width and limited shoulder width for vehicles. The RHRSP model is also applicable for other highways with the same geological and morphological settings. [ABSTRACT FROM AUTHOR]

The objective of this paper is to ascertain the impact of Chinese FDI on economic growth in Pakistan. This study documents the exploration of the determinants of economic growth in Pakistan by emphasizing the significant role played by Chinese FDI and investments in renewable energy in particular. This paper employs time series data analysis to examine the relationship between GDP and Chinese FDI, inflation, trade openness, exchange rates, interest rates, remittances, and renewable energy consumption from 1990 to 2019. The study involved performing the ARDL bounds test, and it was determined that the dependent and independent variables are linked in the long term. Furthermore, the error correction model is negative and noteworthy, which checks the long-run relationship between variables. According to the findings of the autoregressive distributed lag (ARDL) model, Chinese FDI has a substantial favorable effect on Pakistan's economic growth. Furthermore, renewable energy usage has a long-term favorable and significant association with Pakistan's economic growth. This study established that FDI, and particularly renewable energy, will stimulate the economic growth of Pakistan. Our research has substantial policy implications, especially when it comes to the relationship between FDI and renewable energy. [ABSTRACT FROM AUTHOR]

Trust and credibility in machine learning models are bolstered by the ability of a model to explain its decisions. While explainability of deep learning models is a well-known challenge, a further challenge is clarity of the explanation itself for relevant stakeholders of the model. Layer-wise Relevance Propagation (LRP), an established explainability technique developed for deep models in computer vision, provides intuitive human-readable heat maps of input images. We present the novel application of LRP with tabular datasets containing mixed data (categorical and numerical) using a deep neural network (1D-CNN), for Credit Card Fraud detection and Telecom Customer Churn prediction use cases. We show how LRP is more effective than traditional explainability concepts of Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP) for explainability. This effectiveness is both local to a sample level and holistic over the whole testing set. We also discuss the significant computational time advantage of LRP (1–2 s) over LIME (22 s) and SHAP (108 s) on the same laptop, and thus its potential for real time application scenarios. In addition, our validation of LRP has highlighted features for enhancing model performance, thus opening up a new area of research of using XAI as an approach for feature subset selection. [ABSTRACT FROM AUTHOR]

Automatic catheter and guidewire segmentation plays an important role in robot-assisted interventions that are guided by fluoroscopy. Existing learning based methods addressing the task of segmentation or tracking are often limited by the scarcity of annotated samples and difficulty in data collection. In the case of deep learning based methods, the demand for large amounts of labeled data further impedes successful application. We propose a synthesize and segment approach with plug in possibilities for segmentation to address this. We show that an adversarially learned image-to-image translation network can synthesize catheters in X-ray fluoroscopy enabling data augmentation in order to alleviate a low data regime. To make realistic synthesized images, we train the translation network via a perceptual loss coupled with similarity constraints. Then existing segmentation networks are used to learn accurate localization of catheters in a semi-supervised setting with the generated images. The empirical results on collected medical datasets show the value of our approach with significant improvements over existing translation baseline methods. [ABSTRACT FROM AUTHOR]

Biomimetic scaffolds have been investigated in vascular tissue engineering for many years. Excellent biodegradable materials are desired as temporary scaffolds to support cell growth and disappear gradually with the progress of guided tissue regeneration. In the present paper, a series of biodegradable copolymers were synthesized and used to prepared micro/nanofibrous scaffolds for vascular tissue engineering. Poly(lactide-co-glycolide-co-3(S)-methyl-morpholine-2,5-dione) [P(LA-co-GA-co-MMD)] copolymers with different L-lactide (LA), glycolide (GA), and 3(S)-methyl-2,5-morpholinedione (MMD) contents were synthesized using stannous octoate as a catalyst. Moreover, the P(LA-co-GA-co-MMD) nanofibrous scaffolds were prepared by electrospinning technology. The morphology of scaffolds was analyzed by scanning electron microscopy (SEM), and the results showed that the fibers are smooth, regular, and randomly oriented with diameters of 700 ‡ 100 nm. The weight loss of scaffolds increased significantly with the increasing content of MMD, indicating good biodegradable property of the scaffolds. In addition, the cytocompatibility of electrospun nanofibrous scaffolds was tested by human umbilical vein endothelial cells. It is demonstrated that the cells could attach and proliferate well on P(LA-co-GA-co-MMD) scaffolds and, consequently, form a cell monolayer fully covering on the scaffold surface. Furthermore, the P(LA-co-GA-co-MMD) scaffolds benefit to excellent cell infiltration after subcutaneous implantation. These results indicated that the P(LA-co-GA-co-MMD) nanofibrous scaffolds could be potential candidates for vascular tissue engineering. [ABSTRACT FROM AUTHOR]

A bioassay-guided column chromatographic strategy was adopted in the present study to fractionate the culture extract of Photorhabdus temperata M1021 to identify potential insecticidal and antimicrobial compounds. An ethyl acetate (EtOAc) culture extract of P. temperata was assayed against Galleria mellonella larvae through intra-hemocoel injection and exhibited 100% insect mortality within 60 h. The EtOAc fraction and an isolated compound exhibited phenoloxidase (PO) inhibition of up to 60% and 63%, respectively. The compound was identified as 1,2-benzenedicarboxylic acid (phthalic acid, PA) by gas chromatography-mass spectrometry and nuclear magnetic resonance. PA exhibited insecticidal activity against G. mellonella in a dose-dependent manner, and 100% insect mortality was observed at 108 h after injection of 1 M PA. In a PO inhibition assay, 0.5 and 1 M concentrations of PA were found to inhibit PO activity by 74% and 82%, respectively; and in a melanotic nodule formation assay, nodule formation was significantly inhibited (27 and 10 nodules) by PA (0.5 and 1 M, respectively). PA was furthermore found to have substantial antioxidant activity and maximum antioxidant activity was 64.7% for 0.5 M PA as compare to control. Antibacterial activity was assessed by The MIC values ranged from 0.1 M to 0.5 M of PA. This study reports a multifunctional PA, a potential insecticidal agent, could a factor of insect mortality along with other toxins produced by P. temperata M1021. [ABSTRACT FROM AUTHOR]

Photorhabdus temperata is an entomopathogenic enterobacterium; it is a nematode symbiont that possesses pathogenicity islands involved in insect virulence. Herein, we constructed a P. temperata M1021 cosmid library in Escherichia coli XL1-Blue MRF' and obtained 7.14 × 105 clones. However, only 1020 physiologically active clones were screened for insect virulence factors by injection of each E. coli cosmid clone into Galleria mellonella and Tenebrio molitor larvae. A single cosmid clone, PtC1015, was consequently selected due to its characteristic virulent properties, e.g., loss of body turgor followed by death of larvae when the clone was injected into the hemocoel. The sequence alignment against the available sequences in Swiss-Prot and NCBI databases, confirmed the presence of the mcf gene homolog in the genome of P. temperata M1021 showing 85% homology and 98% query coverage with the P. luminescens counterpart. Furthermore, a 2932 amino acid long Mcf protein revealed limited similarity with three protein domains. The N-terminus of the Mcf encompassed consensus sequence for a BH3 domain, the central region revealed similarity to toxin B, and the C-terminus of Mcf revealed similarity to the bacterial export domain of ApxIVA, an RTX-like toxin. In short, the Mcf toxin is likely to play a role in the elimination of insect pests, making it a promising model for use in the agricultural field. [ABSTRACT FROM AUTHOR]

Multi-target tracking (MTT) is a challenging issue due to an unknown number of real targets, motion uncertainties, and coalescence behavior of sensor (such as radar) measurements. The conventional MTT systems deal with intractable computational complexities because they enumerate all feasible joint measurement-to-track association hypotheses and recursively calculate the a posteriori probabilities of each of these joint hypotheses. Therefore, the state-of-art MTT system demands bypassing the entire joint data association procedure. This research work utilizes linear multi-target (LM) tracking to treat feasible target detections followed by neighbored tracks as clutters. The LM integrated track splitting (LMITS) algorithm was developed without a smoothing application that produces substantial estimation errors. Smoothing refines the state estimation in order to reduce estimation errors for an efficient MTT. Therefore, we propose a novel Fixed Interval Smoothing LMITS (FIsLMITS) algorithm in the existing LMITS algorithm framework to improve MTT performance. This algorithm initializes forward and backward tracks employing LMITS separately using measurements collected from the sensor in each scan. The forward track recursion starts after the smoothing. Therefore, each forward track acquires backward multi-tracks that arrived from upcoming scans (future scans) while simultaneously associating them in a forward track for fusion and smoothing. Thus, forward tracks become more reliable for multi-target state estimation in difficult cluttered environments. Monte Carlo simulations are carried out to demonstrate FIsLMITS with improved state estimation accuracy and false track discrimination (FTD) in comparison to the existing MTT algorithms. [ABSTRACT FROM AUTHOR]

Confocal microscopy image analysis is a useful method for neoplasm diagnosis. Many ambiguous cases are difficult to distinguish with the naked eye, thus leading to high inter-observer variability and significant time investments for learning this method. We aimed to develop a deep learning-based neoplasm classification model that classifies confocal microscopy images of 10× magnified colon tissues into three classes: neoplasm, inflammation, and normal tissue. ResNet50 with data augmentation and transfer learning approaches was used to efficiently train the model with limited training data. A class activation map was generated by using global average pooling to confirm which areas had a major effect on the classification. The proposed method achieved an accuracy of 81%, which was 14.05% more accurate than three machine learning-based methods and 22.6% better than the predictions made by four endoscopists. ResNet50 with data augmentation and transfer learning can be utilized to effectively identify neoplasm, inflammation, and normal tissue in confocal microscopy images. The proposed method outperformed three machine learning-based methods and identified the area that had a major influence on the results. Inter-observer variability and the time required for learning can be reduced if the proposed model is used with confocal microscopy image analysis for diagnosis. [ABSTRACT FROM AUTHOR]

Exploring biological agents to control biofilm is a vital alternative in combating pathogenic bacteria that cause dental plaque. This study was focused on antimicrobial, biofilm formation and biofilm dispersal efficacy of Gallic acid (GA) against bacteria, including Proteus spp., Escherichia coli, Pseudomonas spp., Salmonella spp., Streptococcus mutans, and Staphylococcus aureus and multispecies bacteria. Biofilm was qualitatively and quantitatively assessed by crystal violet assay, florescence microscopy (bacterial biomass (µm2), surface coverage (%)) and extracellular polymeric substances (EPS). It was exhibited that GA (1–200 mg/L) can reduce bacterial growth. However, higher concentrations (100–200 mg/L) markedly reduced (86%) bacterial growth and biofilm formation (85.5%), while GA did not exhibit any substantial dispersal effects on pre-formed biofilm. Further, GA (20–200 mg/L) exhibited 93.43% biomass reduction and 88.6% (p < 0.05) EPS (polysaccharide) reduction. Microscopic images were processed with BioImageL software. It was revealed that biomass surface coverage was reduced to 2% at 200 mg/L of GA and that 13,612 (µm2) biomass was present for control, while it was reduced to 894 (µm2) at 200 mg/L of GA. Thus, this data suggest that GA have antimicrobial and biofilm control potential against single and multispecies bacteria causing dental plaque. [ABSTRACT FROM AUTHOR]

In this study, Ailanthus altissima sawdust was chemically activated and characterized by Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR), Energy Dispersive X rays (EDX), and surface area analyzer. The sawdust was used as an adsorbent for the removal of azo dye; Acid Yellow 29 (AY 29) from wastewater. Different kinetic and equilibrium models were used to calculate the adsorption parameters. Among the applied models, the more suitable model was Freundlich with maximum adsorption capacities of 9.464, 12.798, and 11.46 mg/g at 20 °C, 30 °C, and 40 °C respectively while R2 values close to 1. Moreover, the kinetic data was best fitted in pseudo second order kinetic model with high R2 values approaching to 1. Furthermore, adsorption thermodynamics parameters such as free energy, enthalpy, and entropy were calculated and the adsorption process was found to be exothermic with a value of ∆H° = −9.981 KJ mol−1, spontaneous that was concluded from ΔG° values which were negative (−0.275, −3.422, and −6.171 KJ mol−1 at 20, 30, and 40 °C respectively). A positive entropy change ∆S° with a value of 0.0363 KJ mol−1 indicated the increase disorder during adsorption process. It was concluded that the activated sawdust could be used as a suitable adsorbent for the removal of waste material, especially dyes from polluted waters. [ABSTRACT FROM AUTHOR]

Pakistan possesses the fourth largest irrigation network in the world, serving 20.2 million hectares of cultivated land. With an increasing irrigated area, Pakistan is short of freshwater resources and faces severe water scarcity and food security challenges. This is the first comprehensive study on the water footprint (WF) of crop production in Peshawar Basin. WF is defined as the volume of freshwater required to produce goods and services. In this study, we assessed the blue and green water footprints (WFs) and annual blue and green water consumption of major crops (maize, rice, tobacco, wheat, barley, sugarcane, and sugar beet) in Peshawar Basin, Pakistan. The Global Water Footprint Assessment Standard (GWFAS) and AquaCrop model were used to model the daily WF of each crop from 1986 to 2015. In addition, the blue water scarcity, in the context of available surface water, and economic water productivity (EWP) of these crops were assessed. The 30 year average blue and green WFs of major crops revealed that maize had the highest blue and green WFs (7077 and 2744 m3/ton, respectively) and sugarcane had the lowest blue and green WFs (174 and 45 m3/ton, respectively). The average annual consumption of blue water by major crops in the basin was 1.9 billion m3, where 67% was used for sugarcane and maize, covering 48% of the cropland. The average annual consumption of green water was 1.0 billion m3, where 68% was used for wheat and sugarcane, covering 67% of the cropland. The WFs of all crops exceeded the global average. The results showed that annually the basin is supplied with 30 billion m3 of freshwater. Annually, 3 billion m3 of freshwater leaves the basin unutilized. The average annual blue water consumption by major crops is 31% of the total available surface water (6 billion m3) in the basin. Tobacco and sugar beet had the highest blue and green EWP while wheat and maize had the lowest. The findings of this study can help the water management authorities in formulating a comprehensive policy for efficient utilization of available water resources in Peshawar Basin. [ABSTRACT FROM AUTHOR]

This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate. [ABSTRACT FROM AUTHOR]

Target detection and tracking is important in military as well as in civilian applications. In order to detect and track high-speed incoming threats, modern surveillance systems are equipped with multiple sensors to overcome the limitations of single-sensor based tracking systems. This research proposes the use of information from RADAR and Infrared sensors (IR) for tracking and estimating target state dynamics. A new technique is developed for information fusion of the two sensors in a way that enhances performance of the data association algorithm. The measurement acquisition and processing time of these sensors is not the same; consequently the fusion center measurements arrive out of sequence. To ensure the practicality of system, proposed algorithm compensates the Out of Sequence Measurements (OOSMs) in cluttered environment. This is achieved by a novel algorithm which incorporates a retrodiction based approach to compensate the effects of OOSMs in a modified Bayesian technique. The proposed modification includes a new gating strategy to fuse and select measurements from two sensors which originate from the same target. The state estimation performance is evaluated in terms of Root Mean Squared Error (RMSE) for both position and velocity, whereas, track retention statistics are evaluated to gauge the performance of the proposed tracking algorithm. The results clearly show that the proposed technique improves track retention and and false track discrimination (FTD). [ABSTRACT FROM AUTHOR]

In the multiple asynchronous bearing-only (BO) sensors tracking system, there usually exist two main challenges: (1) the presence of clutter measurements and the target misdetection due to imperfect sensing; (2) the out-of-sequence (OOS) arrival of locally transmitted information due to diverse sensor sampling interval or internal processing time or uncertain communication delay. This paper simultaneously addresses the two problems by proposing a novel distributed tracking architecture consisting of the local tracking and central fusion. To get rid of the kinematic state unobservability problem in local tracking for a single BO sensor scenario, we propose a novel local integrated probabilistic data association (LIPDA) method for target measurement state tracking. The proposed approach enables eliminating most of the clutter measurement disturbance with increased target measurement accuracy. In the central tracking, the fusion center uses the proposed distributed IPDA-forward prediction fusion and decorrelation (DIPDA-FPFD) approach to sequentially fuse the OOS information transmitted by each BO sensor. The track management is carried out at local sensor level and also at the fusion center by using the recursively calculated probability of target existence as a track quality measure. The efficiency of the proposed methodology was validated by intensive numerical experiments. [ABSTRACT FROM AUTHOR]

The smart grid (SG) has emerged as a key enabling technology facilitating the integration of variable energy resources with the objective of load management and reduced carbon-dioxide (CO 2 ) emissions. However, dynamic load consumption trends and inherent intermittent nature of renewable generations may cause uncertainty in active resource management. Eventually, these uncertainties pose serious challenges to the energy management system. To address these challenges, this work establishes an efficient load scheduling scheme by jointly considering an on-site photo-voltaic (PV) system and an energy storage system (ESS). An optimum PV-site matching technique was used to optimally select the highest capacity and lowest cost PV module. Furthermore, the best-fit of PV array in regard with load is anticipated using least square method (LSM). Initially, the mathematical models of PV energy generation, consumption and ESS are presented along with load categorization through Zero and Finite shift methods. Then, the final problem is formulated as a multiobjective optimization problem which is solved by using the proposed Dijkstra algorithm (DA). The proposed algorithm quantifies day-ahead electricity market consumption cost, used energy mixes, curtailed load, and grid imbalances. However, to further analyse and compare the performance of proposed model, the results of the proposed algorithm are compared with the genetic algorithm (GA), binary particle swarm optimization (BPSO), and optimal pattern recognition algorithm (OPRA), respectively. Simulation results show that DA achieved 51.72% cost reduction when grid and renewable sources are used. Similarly, DA outperforms other algorithms in terms of maximum peak to average ratio (PAR) reduction, which is 10.22%. [ABSTRACT FROM AUTHOR]

Fusion of the Global Positioning System (GPS) and Inertial Navigation System (INS) for navigation of ground vehicles is an extensively researched topic for military and civilian applications. Micro-electro-mechanical-systems-based inertial measurement units (MEMS-IMU) are being widely used in numerous commercial applications due to their low cost; however, they are characterized by relatively poor accuracy when compared with more expensive counterparts. With a sudden boom in research and development of autonomous navigation technology for consumer vehicles, the need to enhance estimation accuracy and reliability has become critical, while aiming to deliver a cost-effective solution. Optimal fusion of commercially available, low-cost MEMS-IMU and the GPS may provide one such solution. Different variants of the Kalman filter have been proposed and implemented for integration of the GPS and the INS. This paper proposes a framework for the fusion of adaptive Kalman filters, based on Sage-Husa and strong tracking filtering algorithms, implemented on MEMS-IMU and the GPS for the case of a ground vehicle. The error models of the inertial sensors have also been implemented to achieve reliable and accurate estimations. Simulations have been carried out on actual navigation data from a test vehicle. Measurements were obtained using commercially available GPS receiver and MEMS-IMU. The solution was shown to enhance navigation accuracy when compared to conventional Kalman filter. [ABSTRACT FROM AUTHOR]

Make and model recognition (MMR) of vehicles plays an important role in automatic vision-based systems. This paper proposes a novel deep learning approach for MMR using the SqueezeNet architecture. The frontal views of vehicle images are first extracted and fed into a deep network for training and testing. The SqueezeNet architecture with bypass connections between the Fire modules, a variant of the vanilla SqueezeNet, is employed for this study, which makes our MMR system more efficient. The experimental results on our collected large-scale vehicle datasets indicate that the proposed model achieves 96.3% recognition rate at the rank-1 level with an economical time slice of 108.8 ms. For inference tasks, the deployed deep model requires less than 5 MB of space and thus has a great viability in real-time applications. [ABSTRACT FROM AUTHOR]

A localization and tracking algorithm for an early-warning tracking system based on the information fusion of Infrared (IR) sensor and Laser Detection and Ranging (LADAR) is proposed. The proposed Kalman filter scheme incorporates Out-of-Sequence Measurements (OOSMs) to address long-range, high-speed incoming targets to be tracked by networked Remote Observation Sites (ROS) in cluttered environments. The Rauch–Tung–Striebel (RTS) fixed lag smoothing algorithm is employed in the proposed technique to further improve tracking accuracy, which, in turn, is used for target profiling and efficient filter initialization at the targeted platform. This efficient initialization increases the probability of target engagement by increasing the distance at which it can be effectively engaged. The increased target engagement range also reduces risk of any damage from debris of the engaged target. Performance of the proposed target localization algorithm with OOSM and RTS smoothing is evaluated in terms of root mean square error (RMSE) for both position and velocity, which accurately depicts the improved performance of the proposed algorithm in comparison with existing retrodiction-based OOSM filtering algorithms. The effects of assisted target state initialization at the targeted platform are also evaluated in terms of Time to Impact (TTI) and true track retention, which also depict the advantage of the proposed strategy. [ABSTRACT FROM AUTHOR]

Cocoa, Theobroma cacao , is an important tropical perennial crop grown widely in the humid tropics. The exchange of cocoa germplasm between germplasm collections and breeding centres is vital for varietal development. Intermediate quarantine facilities, such as the International Cocoa Quarantine Centre, Reading UK (ICQC-R) play a vital role in ensuring the transfer of germplasm whilst minimising the risk of spreading pests and diseases. Current screening procedures combine visual inspection and molecular techniques, which are effective in detecting Cocoa swollen shoot virus (CSSV), a badnavirus, which causes severe losses but are restricted to West Africa. However, the detection of latent or mild virus infections that produce no visual symptoms has been a challenge. Recently two badnavirus species of cocoa producing mild symptoms, cacao mild mosaic virus (CaMMV) and cacao yellow vein-banding virus (CYVBV), have been sequenced. Here, we report new assays for the detection of these two species, for the first time in non-symptomatic accessions. Evolutionary and bioinformatic analyses of the viruses suggest their most recent source was from Trinidad, though there is historic evidence that these viruses may have their origin in South America and then become widespread globally over the last century. We also report a novel colorimetric Loop-mediated isothermal amplification (LAMP) assay for the detection of CYVBV. This simple and accurate method could be employed in field virus testing.

Biomimetic scaffolds have been investigated in vascular tissue engineering for many years. Excellent biodegradable materials are desired as temporary scaffolds to support cell growth and disappear gradually with the progress of guided tissue regeneration. In the present paper, a series of biodegradable copolymers were synthesized and used to prepared micro/nanofibrous scaffolds for vascular tissue engineering. Poly(lactide- co -glycolide- co -3( S )-methyl-morpholine-2,5-dione) [P(LA- co -GA- co -MMD)] copolymers with different l-lactide (LA), glycolide (GA), and 3( S )-methyl-2,5-morpholinedione (MMD) contents were synthesized using stannous octoate as a catalyst. Moreover, the P(LA- co -GA- co -MMD) nanofibrous scaffolds were prepared by electrospinning technology. The morphology of scaffolds was analyzed by scanning electron microscopy (SEM), and the results showed that the fibers are smooth, regular, and randomly oriented with diameters of 700 ± 100 nm. The weight loss of scaffolds increased significantly with the increasing content of MMD, indicating good biodegradable property of the scaffolds. In addition, the cytocompatibility of electrospun nanofibrous scaffolds was tested by human umbilical vein endothelial cells. It is demonstrated that the cells could attach and proliferate well on P(LA- co -GA- co -MMD) scaffolds and, consequently, form a cell monolayer fully covering on the scaffold surface. Furthermore, the P(LA- co -GA- co -MMD) scaffolds benefit to excellent cell infiltration after subcutaneous implantation. These results indicated that the P(LA- co -GA- co -MMD) nanofibrous scaffolds could be potential candidates for vascular tissue engineering.