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Fintech is an industry that uses technology to enhance and automate financial services. Fintech firms use software, mobile apps, and digital technologies to provide financial services that are faster, more efficient, and more accessible than those provided by traditional banks and financial institutions. Fintech companies take care of processes such as lending, payment processing, personal finance, and insurance, among other financial services. A data breach refers to a security liability when unapproved individuals gain access to or pilfer susceptible data. Data breaches pose a significant financial, reputational, and legal liability for companies. In 2017, Equifax suffered a data breach that revealed the personal information of over 143 million customers. Combining federated learning (FL) and blockchain can provide financial institutions with additional insurance and safeguards. Blockchain technology can provide a transparent and secure platform for FL, allowing financial institutions to collaborate on machine learning (ML) models while maintaining the confidentiality and integrity of their data. Utilizing blockchain technology, FL can provide an immutable and auditable record of all transactions and data exchanges. This can ensure that all parties adhere to the protocols and standards agreed upon for data sharing and collaboration. We propose the implementation of an FL framework that uses multiple ML models to protect consumers against fraudulent transactions through blockchain. The framework is intended to preserve customer privacy because it does not mandate the exchange of private customer data between participating institutions. Each bank trains its local models using data from its consumers, which are then combined on a centralised federated server to produce a unified global model. Data is neither stored nor exchanged between institutions, while models are trained on each institution’s data.

Tick infestation poses an important challenge to livestock in Pakistan. Farm management practices and environmental variables can influence tick infestation prevalence in animals. To this end, a cross-sectional survey of 96 farms in four different geographical districts (24 farms from each district) was conducted in Punjab, Pakistan, between October 2021 and January 2022. An epidemiological questionnaire was designed focusing on farm management practices and their impact on tick infestations at these farms. Data were collected via in-person interviews. Regional and farm-specific variables’ associations were evaluated using Pearson’s chi-square test and Fischer’s exact test, respectively. A multivariable logistic regression model was used to identify significant risk factors. This study identified that using soft bedding materials, e.g., wheat straw, leaf litter or plain soil posed a significant risk of tick infestation. Additionally, the absence of quarantine measures, open sheds and inadequate drainage were found as contributing factors in univariable analysis. Higher tick prevalence in the hotter seasons highlighted the influence of Punjab’s extreme weather on tick infestation. Despite regular veterinary visits and the use of acaricidal drugs, the prevalence of tick infestation at these farms suggested potential drug resistance in the ticks. The study recommended establishing quarantine practices, improving farms’ drainage systems and bedding and using a combination of chemical and traditional remedies to tackle drug resistance in ticks. Education and awareness programs on tick-borne diseases and control measures are advocated to reduce the tick infestation burden on animals. Further research on longitudinal studies to better understand tick population dynamics and develop effective acaricides is encouraged. This called for collaborative control efforts among farmers, veterinarians and research institutions.

Federated learning (FL) is a decentralized machine learning approach whereby each device is allowed to train local models, eliminating the requirement for centralized data collecting and ensuring data privacy. Unlike typical typical centralized machine learning, collaborative model training in FL involves aggregating updates from various devices without sending raw data. This ensures data privacy and security while collecting a collective learning from distributed data sources. These devices in FL models exhibit high efficacy in terms of privacy protection, scalability, and robustness, which is contingent upon the success of communication and collaboration. This paper explore the various topologies of both decentralized or centralized in the context of FL. In this respect, we investigated and explored in detail the evaluation of four widly used end-to-end FL frameworks: FedML, Flower, Flute, and PySyft. We specifically focused on vertical and horizontal FL systems using a logistic regression model that aggregated by the FedAvg algorithm. specifically, we conducted experiments on two images datasets, MNIST and Fashion-MNIST, to evaluate their efficiency and performance. Our paper provides initial findings on how to effectively combine horizontal and vertical solutions to address common difficulties, such as managing model synchronization and communication overhead. Our research indicates the trade-offs that exist in the performance of several simulation frameworks for federated learning.

Abstract Background Brucellosis is a zoonotic disease whose causative agent, Brucella spp., is endemic in many countries of the Mediterranean basin, including Greece. Although the occurrence of brucellosis must be reported to the authorities, it is believed that the disease is under-reported in Greece, and knowledge about the genomic diversity of brucellae is lacking. Methods Thus, 44 Brucella isolates, primarily B. melitensis, collected between 1999 and 2009 from humans and small ruminants in Greece were subjected to whole genome sequencing using short-read technology. The raw reads and assembled genomes were used for in silico genotyping based on single nucleotide substitutions and alleles. Further, specific genomic regions encoding putative virulence genes were screened for characteristic nucleotide changes, which arose in different genotype lineages. Results In silico genotyping revealed that the isolates belonged to three of the known sublineages of the East Mediterranean genotype. In addition, a novel subgenotype was identified that was basal to the other East Mediterranean sublineages, comprising two Greek strains. The majority of the isolates can be assumed to be of endemic origin, as they were clustered with strains from the Western Balkans or Turkey, whereas one strain of human origin could be associated with travel to another endemic region, e.g. Portugal. Further, nucleotide substitutions in the housekeeping gene rpoB and virulence-associated genes were detected, which were characteristic of the different subgenotypes. One of the isolates originating from an aborted bovine foetus was identified as B. abortus vaccine strain RB51. Conclusion The results demonstrate the existence of several distinct persistent Brucella sp. foci in Greece. To detect these and for tracing infection chains, extensive sampling initiatives are required.

Conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) PEDOT:PSS is the most widely used material in stretchable and flexible electronics not only due to its good electrical and mechanical properties but also its use in numerous biomedical sensing applications. This article investigates the electromechanical behavior of PEDOT:PSS and its nanocomposite thin film. The films were rod-coated on a chemically treated, cost-effective single-component polymer that was previously characterized as an alternative available substrate material for stretchable and flexible microelectromechanical systems (MEMS) based devices. The results show that the films exhibit stable resistive behavior in response to various applied mechanical loads such as stretching, twisting, combined stretching, and twisting and forced vibrations. The films also show good thermal stability at relatively high temperatures. The prepared films also reveal their applicability as thermal actuators. It was also found that adding nanophases of silver material in PEDOT:PSS enhances the performance of thin films. These results also suggest that the rod-coated PEDOT:PSS and its composite thin films may have versatile applications like stretchable, twistable, and vibration-tolerant conductors, thermal actuators, and devices for future low-cost MEMS devices.

Brucellosis is a bacterial zoonosis worldwide and a potential health risk in Pakistan due to socio-economic reasons and lack of awareness, veterinary health and modern dairy-processing facilities. The aim of this study was to determine the burden of brucellosis in hospitalized patients of selected districts of Punjab, Pakistan. To this end, a total of 280 serum samples were collected from suspected patients in districts Lahore, Okara and Khushab between 2016 and 2018. Anti-Brucella antibodies were detected in 89 (31.8%) sera by Rose Bengal plate test (RBPT), and Brucella abortus DNA was amplified by polymerase chain reaction (PCR) in 42 (15%) samples. In univariable analysis, the seroprevalence varied significantly (p < 0.05) between districts with Lahore indicating 41/101 (40.6%) Odds ratio (OR) = 53.98 (7.22–403.67; 95% CI), Okara 47/99 (47.5%) OR = 71.4 (9.55–533.65; 95% CI) and Khushab 1/80 (1.3%) as reference. Similarly, exposure to aborted materials and a history of blood transfusion did associate significantly (p < 0.05), posing OR = 2.91 (1.58–5.36; 95% CI) and OR = 4.48 (2.56–7.84; 95% CI) risk. However, consumption of raw milk and history of blood transfusion did associate significantly (p < 0.05) in multivariable analysis indicating OR = 1.91 (1.09–3.34; 95% CI) and OR = 4.92 (2.76–8.75; 95% CI), respectively. The association of history of blood transfusion as a brucellosis risk factor underscores the need to create brucellosis awareness programs both at public and institutional levels in the medical and veterinary fields, as well as facilities and capacity building to delve deeper into the epidemiology of brucellosis in the country. Particular attention should be paid to chronically infected patients. Therefore, laboratory modernization, standardization and validation of the diagnostic tests, and staff trainings are required. Finally, pasteurization of the milk is recommended before consumption.

This study assesses the compressive strength and drying shrinkage behavior of cement and LC3-50-based cementitious composites containing glass powder. A total of four, i.e., 20, 35, 50, and 60 MPa, strengths of cementitious composites were targeted by varying the mix composition and water-to-cement ratios. In all four composite mix types, locally available glass powder was used as 0, 5, 10, and 15% added as a partial replacement of cement and LC3-50. The novelty of this research is the addition of waste glass powder as an alternative to silica fume, especially in a high-strength composite (including 50 and 60 MPa). The aim was to investigate the efficiency of waste glass powder in providing eco-friendly composites. The compressive strength was determined following ASTM C 109 standard and the drying shrinkage test followed ASTM C 157 standard. The results of compressive strength in the enhancement using up to 10% waste glass powder are beneficial in enhancing strength and reducing drying shrinkage. Furthermore, the use of LC3-50 initially reduced compressive strength up to 14 days while increased at 28 days compared to OPC. Contrariwise, the initial drying shrinkage was higher in LC3-50 specimens and lower at later ages compared to OPC. A detailed investigation of existing shrinkage models for mortar/composite is assessed, and limitations are also discussed.

This study focuses on the mechanical behavior of natural fiber-reinforced polymer composites (NFRPs), which are gaining prominence as sustainable materials due to their biodegradability and eco-friendliness. In this study, we aimed to gain a profound understanding of the mechanical behavior of selected NFRPs. Static structural analysis was conducted to simulate tensile effects, while vibrational analysis was performed to predict natural frequencies. The results indicated that all fibers exhibited minimum stress at the 67.5° angle and maximum stress at the 22.5° angle during tensile testing. Additionally, minimum deformation occurred at the 0° angle, whereas maximum deformation was observed at the 67.5° angle. Interestingly, the NFRPs exhibited similar natural frequencies for the lower modes (1st and 2nd), with negligible alterations due to fiber angles. The core aim of this study is to showcase the practicality and viability of the investigated NFRPs by employing sophisticated finite element analysis to anticipate their material behavior beforehand, allowing for a comprehensive comparison of the natural frequencies, stresses, and deformations with traditional Carbon Fiber Reinforced Polymer (CFRP) composites, thereby exploring the potential of NFRPs as feasible alternatives.

Internet of things (IoT) devices are gaining traction around the globe. These devices are sometimes hijacked and turned into zombies or botnets. One risk posed by hijacked devices is a ping flood attack, also known as an internet control message protocol echo request flood. Current literature lacks a ping flood attack dataset generated from an IoT device. This paper contributes by developing an IoT network intrusion detection framework for ping flood attacks. This framework deploys an IoT testbed using embedded devices to emulate two datasets, normal ping traffic and malicious ping flood attack traffic. Features are extracted from the captured traffic using the Zeek tool. Attacks are detected using three machine learning algorithms: logistic regression, K-nearest neighbor, and support vector machine. These models are compared using evaluations such as the confusion matrix, accuracy, precision, recall, F1-score, and misclassification (error rate). The models are validated using split validation and cross-fold validation. The time consumed in training and testing the models across various data levels is also analyzed, along with the time required for feature extraction. The discrepancies between capturing tools are discussed. The use of criteria based on the time difference between requests to detect malicious traffic is considered, as is the impact of machine learning models on memory usage. Our work is compared with similar research. The testbed concluded that the K-nearest neighbor algorithm achieved 99.67% detection accuracy, with an error rate of 0.33% and an F1-score of 99.67%, which is the best amongst the three algorithms.

One of the orthogonal frequency division multiplexing (OFDM) system disadvantages is its sensitivity to frequency offset and phase noise, which lead to losing the orthogonality between the subcarriers and thereby degrade the system performance. In this paper a joint scheme for frequency offset and pilot-based channel estimation is introduced in which the frequency offset is first estimated using an autocorrelation method, and then is fined further by applying an iterative phase correction by means of pilot-based Wiener filtering method. In order to verify the capability of the estimation algorithm, the scheme has been implemented and tested using a real measurement system in a multipath indoor environment. The results show the algorithm capability of compensating for the frequency offset with different transmission and channel conditions.

Brucellosis in cattle herds has caused severe economic losses in many regions worldwide. A cross-sectional study was performed to investigate the presence of Brucella spp. in industrial dairy cattle farms in Iran. For this purpose, 935 blood and 935 milk samples were randomly collected from industrial dairy cattle farms in Iran's Alborz and Tehran provinces. Blood and milk samples were collected on the same day from each cow. Serological, bacteriological, and molecular characterization of Brucella isolates were performed using standard methods. Our results revealed the seroprevalence of brucellosis in dairy cattle farms in the Alborz and Tehran provinces, reaching 19.8%, 6.7%, 5.1%, 14.1%, and 13.1% using the Rose Bengal plate test (RBPT), serum agglutination test (SAT), 2-mercaptoethanol test (2-ME), indirect enzyme-linked immunosorbent assay (i-ELISA) and milk ring test (MRT), respectively. Furthermore, the results of bacterial culture and PCR analyses showed the presence of Brucella abortus among dairy cattle in the Alborz province and Brucella melitensis and B. abortus among dairy cattle in the Tehran province. Moreover, statistical analysis with Cohen's Kappa has highlighted the near-perfect agreement between RBPT and i-ELISA (k = 0.86). In contrast, substantial agreement was shown between RBPT and SAT performance (k = 0.70) and moderate agreement between RBPT and 2-ME (k = 0.67). The findings of this investigation showed shedding of Brucella in the milk of seropositive cows, which is a serious problem involving the maintenance and further spread of Brucella infection on the farm. Therefore, for brucellosis detection or eradication in dairy cattle farms, bacteriological and serological tests of milk samples should be performed along with blood analysis to inhibit the uncontrolled spread of the disease in animals and humans.

Twitter has become a common place to share opinions about various issues. One such issue was the driving of women in the Kingdom of Saudi Arabia (KSA). Many researchers have addressed this issue using methods mostly from social sciences, however, these studies are on a smaller scale. In this paper, we take the approach of understanding the public discussions related to the topic #SaudiWomenCanDrive using methods from network science. Network science allows us to understand the influential people, topics, and communities related to the topic on a large scale. Around two million tweets posted by 630 thousand users are analyzed. Retweet, mention, co-mention, and hash-tag networks are extracted from these tweets. Analysis shows that most influential users include women rights activists like Loujain Hathloul and Manal Alsharif, as well as the political leadership like King Salman bin Abdulaziz and government departments like Ministry of Interior (MoI) and Traffic Department (Moroor). Most important topics identified through hashtags include the support for the movement like (The King Supports Women’s Driving) as well as against it like (Saudis Refuse Women’s Driving). Analyzing such discussions is important for gaining insights into public discussions for understanding public concerns and can be used by the government and non-government organizations to address them.

The cement industry is expanding rapidly around the globe, despite its significant contribution to global carbon dioxide emissions. Likewise, in Pakistan, the cement industry produces million tons of cement and has a history of contributing as high as 10% of the country’s carbon dioxide emissions annually. The most effective technique for reducing carbon dioxide emissions is to use supplementary cementitious materials (SCMs). Limestone Calcined Clay Cement (LC3-50) is a recently developed cement blend comprised of 50% clinker, 30% calcined clay, 15% raw limestone, and 5% gypsum by weight. The focus of this research is to assess the mechanical properties and durability performance of LC3-50 cement composition formulated using raw materials from Pakistan. The comprehensive case study would help advance the research and commercialization activities in the country. In this study, compressive strength, split tensile, flexural, and pull-out tests were performed for evaluating the mechanical properties. For the assessment of durability, water permeability, sorptivity, carbonation, and rapid chloride penetration test (RCPT) tests were performed as per the available standards. It is concluded that the use of LC3-50 instead of ordinary Portland cement (OPC) improved the strength and durability of the end concrete.

Abstract Background Diarrhea is an important ailment limiting the production of the Tibetan pig industry. Dynamic balance of the intestinal microbiota is important for the physiology of the animal. The objective of this work was to study fungal diversity in the feces of early weaning Tibetan piglets in different health conditions. Results In the present study, we performed high-throughput sequencing to characterize the fungal microbial diversity in healthy, diarrheal and treated Tibetan piglets at the Tibet Autonomous Region of the People’s Republic of China. The four alpha diversity indices (Chao1, ACE, Shannon and Simpson) revealed no significant differences in the richness across the different groups (P > 0.05). In all samples, the predominant fungal phyla were Ascomycota, Basidiomycota and Rozellomycota. Moreover, the healthy piglets showed a higher abundance of Ascomycota than the treated ones with a decreased level of Basidiomycota. One phylum (Rozellomycota) showed higher abundance in the diarrheal piglets than in the treated. At genus level, compared with that to the healthy group, the proportion of Derxomyces and Lecanicillium decreased, whereas that of Cortinarius and Kazachstania increased in the diarrheal group. The relative abundances of Derxomyces, Phyllozyma and Hydnum were higher in treated piglets than in the diarrheal ones. Conclusions A decreased relative abundance of beneficial fungi (e.g. Derxomyces and Lecanicillium) may cause diarrhea in the early-weaned Tibetan piglets. Addition of probiotics into the feed may prevent diarrhea at this stage. This study presented the fungal diversity in healthy, diarrheal and treated early-weaned Tibetan piglets.

Coxiellosis is a zoonosis in animals caused by Coxiella burnetii. A cross-sectional study was conducted on 920 (591 female and 329 male) randomly selected camels (Camelus dromedarius) of different age groups from 13 districts representative of the three different ecological zones in the Province Punjab, Pakistan to determine the prevalence and associated risk factors of coxiellosis. The blood samples were collected and tested for anti-C. burnetti antibodies using indirect multispecies ELISA. Real-time PCR was used for the detection of C. burnetii DNA to determine the prevalence in heparinized blood pools. Out of 920 investigated camels, anti-C. burnetii antibodies were detected in 288 samples (31.3%) (95% CI: 28.3–34.4%). The highest (78.6%) and lowest (1.8%) seroprevalence were detected in Rahimyar Khan (southern Punjab) and in Jhang (central Punjab), respectively. Potential risk factors associated with seropositivity of the Q fever in camels included desert area (42.5%; OR = 2.78, 95% CI 1.12–3.21) summer season (35.7%; OR = 2.3, 95% CI: 1.31–3.2), sex (female) (39.1; OR = 2.35, 95% CI: 1.34–2.98), tick infestation (51.3%;OR = 2.81, 95% CI: 1.34–3.02), age (>10 years; 46.4%; OR = 1.56, 95% CI: 0.33–2.05) and herd size (38.5%; OR = 1.21, 95% CI: 0.76–1.54). Coxiella burnetii DNA was amplified in 12 (20%) and 1 (10%) of 60 ELISA-negative and 10 suspected camels, respectively. DNA could not be detected in ELISA positive blood pools. This study emphasizes the seroprevalence and associated risk factors of coxiellosis as well as its potential to spill over to animals and humans in contact with these camel herds.

Rabies virus (RABV) is a cunning neurotropic pathogen and causes top priority neglected tropical diseases in the developing world. The genome of RABV consists of nucleoprotein (N), phosphoprotein (P), matrix protein (M), glycoprotein (G), and RNA polymerase L protein (L), respectively. The virus causes neuronal dysfunction instead of neuronal cell death by deregulating the polymerization of the actin and microtubule cytoskeleton and subverts the associated binding and motor proteins for efficient viral progression. These binding proteins mainly maintain neuronal structure, morphology, synaptic integrity, and complex neurophysiological pathways. However, much of the exact mechanism of the viral-cytoskeleton interaction is yet unclear because several binding proteins of the actin-microtubule cytoskeleton are involved in multifaceted pathways to influence the retrograde and anterograde axonal transport of RABV. In this review, all the available scientific results regarding cytoskeleton elements and their possible interactions with RABV have been collected through systematic methodology, and thereby interpreted to explain sneaky features of RABV. The aim is to envisage the pathogenesis of RABV to understand further steps of RABV progression inside the cells. RABV interacts in a number of ways with the cell cytoskeleton to produce degenerative changes in the biochemical and neuropathological trails of neurons and other cell types. Briefly, RABV changes the gene expression of essential cytoskeleton related proteins, depolymerizes actin and microtubules, coordinates the synthesis of inclusion bodies, manipulates microtubules and associated motors proteins, and uses actin for clathrin-mediated entry in different cells. Most importantly, the P is the most intricate protein of RABV that performs complex functions. It artfully operates the dynein motor protein along the tracks of microtubules to assist the replication, transcription, and transport of RABV until its egress from the cell. New remedial insights at subcellular levels are needed to counteract the destabilization of the cytoskeleton under RABV infection to stop its life cycle.

Brucellosis is an important bacterial zoonosis of domestic and wildlife species. This disease has a significant public health concern and is characterized by reproductive failure resulting in economic losses in the livestock industry. Among thirteen known species, B. abortus, B. melitensis, B. suis, and B. canis are human pathogens. Brucellosis has been extensively investigated in humans and domestic animals. However, the situation in wildlife is still not completely reported and studied. Therefore, a systematic literature search and screening were done to clarify the situation of brucellosis in wildlife in Europe. Sixty-five articles from a total of 13,424 reports published between 1991 and 2021 were selected, applying defined inclusion criteria. Wild boars and brown hares were the most often studied terrestrial wildlife species, whereas seals and porpoises were the most often investigated marine wildlife. Poland, Croatia, and Belgium showed the highest seroprevalences of wild boars caused by B. suis biovar 2. In marine wildlife, brucellosis was mainly caused by B. ceti and B. pinnipedialis. Most samples were from carcasses. Thus, sera could not be collected. It is worrisome that B.abortus and B. melitensis were reported from both terrestrial and marine wild animals, posing a zoonotic threat to people exposed to wild animals. Currently, there is no approved vaccine available for wild animals. The main challenges are the development of specific diagnostics and their validation for use in wildlife.

Brucellosis is a bacterial zoonotic disease that affects many animal species and can be transmitted to humans via direct contact or via contaminated food. Although brucellosis is a serious health hazard, its public health concern has been neglected in many countries. In some developing countries, such as Pakistan, where brucellosis is endemic, this disease continues to be of importance. A literature search for the past 11 years (2011–2021) provided a comprehensive insight into brucellosis in Pakistan. In this review, particular emphasis was placed on occurrence, diagnostic tests used, and prevention, treatment, and control in the context of the “One Health” approach.

Q fever remains a neglected zoonosis in many developing countries including Pakistan. The causing agent Coxiella (C.) burnetii is resistant to environmental factors (such as drying, heat and many disinfectants), resulting in a long-lasting infection risk for both human and animals. As the infection is usually asymptomatic, it mostly remains undiagnosed in animals until and unless adverse pregnancy outcomes occur in a herd. In humans, the infection leads to severe endocarditis and vascular infection in chronic cases. Limited data are available on molecular epidemiology and evolution of this pathogen, especially in ruminants. Genomic studies will help speculating outbreak relationships in this scenario. Likewise, pathogenesis of C. burnetii needs to be explored by molecular studies. Awareness programs and ensuring pasteurization of the dairy milk before human consumption would help preventing Q fever zoonosis.

The present study was planned to evaluate the ameliorative effects of egg yolk antibodies (EYAs) in broiler chicken. For this purpose, 80-day-old broiler chickens were divided into four groups (A–D), where group A was kept as negative control. Experimental infection with C. perfringens (1 × 108 cfu/mL) was induced via oral route on days 17, 18 and 19 of the experiment in groups B, C and D. Groups C and D were passively immunized by anti-clostridial IgYs @ 1 mL per bird via oral and oral and intramuscular (I/M) routes respectively, on days 21 to 24, and on days 22 and 24 of the experiment, respectively. Two necropsies were performed (the first on day 26th and the second on day 35th). Birds in group B showed behavioral signs e.g., laziness, depression and diarrhea, gross post-mortem lesions e.g., increase in the relative weights (RW), due to acute swelling and congestion of liver and kidneys and ballooning and hemorrhages of jejunum and microscopic lesions e.g., congestion and necrosis in liver and kidneys’ parenchyma and disrupted epithelium with fewer goblet cells in jejunum, compared to the group A. Birds in groups C and D, showed significant improvements in clinical and behavioral signs, RW of liver, kidneys and jejunum, swelling, congestion and mononuclear cells’ infiltration in liver and kidneys and damages in the jejunal-wall, compared to group B. The most significant changes were found in birds of group C. Our study revealed ameliorative effects of EYAs on certain biological parameters however, further studies would be needed to justify a safer production and a reliable application of EYAs in NE outbreaks.

Domestic yaks (Bos grunniens) are indigenous to the Tibetan Plateau and display a high diarrhea rate due to poor habitat and husbandry conditions. Lactobacillus has been shown to exert beneficial effects as antimicrobial, growth promotion, and gut microbiota in humans and/or murine models, but the relevant data regarding Lactobacillus isolated from yaks was unavailable. Therefore, this study aimed to investigate the effects of Lactobacillus from yaks on the intestinal microbial community in a mouse model and determine whether Lactobacillus supplementation contributed in alleviating diarrhea by modulating gut microbiota. A total of 12 ileac samples from four groups were collected for 16S rRNA gene amplicon sequencing of V3-V4 region. Results revealed that although Lactobacillus supplementation did not change the diversity of gut microbiota in mice, the proportion of some intestinal microbiota significantly changed. Specifically, the proportion of Lactobacillus and Sphingomonas in the Lactobacillus treated-group (L-group) were increased as compared to control group (C-group), whereas Pantoea, Cutibacterium, Glutamicibacter, Turicibacter, Globicatella, Microbacterium, Facklamia, unidentified_Corynebacteriaceae, Brachybacterium, and Staphylococcus were significantly decreased in the L-group. In contrast, Escherichia coli (E. coli) infection significantly decreased the proportion of beneficial bacteria such as Globicatella, Acinetobacter, Aerococcus, and Comamonas, while loads of pathogenic bacteria significantly increased including Roseburia and Megasphaera. Interestingly, Lactobacillus administration could ameliorate the microbial community structure of E. coli-induced diarrheal mice by reducing the relative abundance of pathogenic bacteria such as Paenibacillus, Aerococcus, Comamonas, Acinetobacter, Corynebacterium, Facklamia, and Globicatella. Results in this study revealed that Lactobacillus supplementation not only improved the gut microbiota but also alleviated diarrhea in mice, which may be mediated by modulating the composition and function of gut microbiota. Moreover, this study is expected to provide a new theoretical basis for the establishment of a preventive and treatment system for diarrhea in yaks.

Hemorrhagic septicemia (HS) and mastitis caused by Pasteurella (P.) multocida, Staphylococcus (S.) aureus and Streptococcus (Str.) agalactiae are important ailments of the dairy industry especially in South Asia. The present study evaluates the efficacy of a locally prepared hemorrhagic septicemia (HS) and mastitis combined vaccine. To this end, a total of 70 HS, S. aureus and Str. agalactiae-free lactating (early stage of lactation) buffaloes (n = 45) and cows (n = 25), and 50 lactating (early stage of lactation) cows (n = 25) and buffaloes (n = 25) positive for S. aureus/Str. agalactiae were subjected to two doses of HS–mastitis combined vaccine with an interval of 21 days. Antibody response was monitored by ELISA up to six months (180 days). Antibody titers against HS and mastitis were significantly (p ˂ 0.05) higher in vaccinated groups as compared to the non-vaccinated groups. Cumulative mean somatic cell counts and mastitis severity scores in vaccinated groups were significantly lower (p < 0.05), and milk yield was significantly higher (p < 0.05) than those in the respective non-vaccinated controls. In conclusion, Montanide®-adjuvanted HS–mastitis combined vaccine showed significant immunogenic effects in dairy cows and buffaloes. However, challenge studies remain overdue.

Brucellosis is reportedly endemic in ruminants in Pakistan. Both Brucella abortus and B. melitensis infections have been decumented in domestic animals and humans in the country. This study aimed to identify the burden of anti-Brucella antibodies in small ruminants as well as associated potential risk factors with its occurrence at nine institutional livestock farms in Punjab, Pakistan. The sera collected from equal number of sheep and goats (500 from each species) were screened by indirect-ELISA for anti-smooth-Brucella antibodies followed by a serial detection by real-time PCR. Overall, 5.1% (51/1000) seropositivity was registered corresponding to 5% (25/500) prevalence in goats and 5.2% (26/500) in sheep. Brucella-DNA could not be detected in any of the tested sera by real-time PCR. Multiple logistic regression model indicated that farm location (OR 34.05), >4 years of age (OR 2.88), with history of reproductive disorders (OR 2.69), and with BCS of ≤ 3 (OR 12.37) were more likely to test positive for brucellosis at these farms. A routine screening, stringent biosecurity, and quarantine measures are warranted for monitoring and eradication of the infection. Similarly, isolation and molecular investigation of the etiologic agent(s) are needed to understand the relationship of epidemiology and out-breaks of brucellosis in the country.

Molecular dynamics models for predicting the behavior of metallic nanostructures typically do not take into account polarization effects in metals. Here, the authors introduce a polarizable Lennard–Jones potential that provides quantitative insight into the role of induced charges at metal surfaces and related complex material interfaces.

Bovine brucellosis is a contagious zoonotic disease that causes economic losses through abortion and infertility. A cross-sectional study was designed to determine the seroprevalence and associated risk factors of bovine brucellosis in district Gujranwala of Punjab, Pakistan. A total of 220 bovine sera (112 from buffaloes, 108 from cattle) from 46 unvaccinated herds were collected. Parallel testing by the Rose Bengal Plate Test (RBPT) and Indirect Enzyme-linked Immunosorbent Assay (I-ELISA) showed a 58.7% (27/46) herd-level and 22.7% (50/220) animal-level seroprevalence. Seroprevalence was higher (p < 0.001, OR = 7.62) in adult animals (37.2%) compared to younger animals (4.9%). A herd size of >10 animals (p = 0.021, OR = 7.83), less housing space (p = 0.037, OR = 6.39) and history of abortion at the farm (p = 0.023, OR = 5.6) were found as risk factors associated with the seropositivity of brucellosis. There was a substantial agreement between the RBPT and I-ELISA results (Cohen’s kappa coefficient (κ) = 64.16, percent agreement = 89.5%). In conclusion, a relatively higher seroprevalence was found compared to the previous reports from the country. Standardization and validation of the advanced diagnostic tests would be needed. Biosecurity, personal protection, quarantine measures and routine screening of animals at the farm level and disease awareness programs and consumption of pasteurized milk in the human population will be helpful in preventing the transmission/zoonosis of the disease.

Tularemia is an endemic zoonotic disease in many parts of the world including Asia. A cross-sectional study was conducted to determine genome-based prevalence of Francisella tularensis (Ft) in soil, assess an association between its occurrence in soil and likely predictors i.e., macro and micro-nutrients and several categorical variables, and determine seroconversion in small and large ruminants. The study included a total of 2,280 soil samples representing 456 villages in eight districts of the Punjab Province of Pakistan followed by an analysis of serum antibodies in 707 ruminants. The genome of Ft was detected in 3.25% (n = 74, 95% CI: 2.60–4.06) of soil samples. Soluble salts (OR: 1.276, 95% CI: 1.043–1.562, p = 0.015), Ni (OR: 2.910, 95%CI: 0.795–10.644, p = 0.106), Mn (OR:0.733, 95% CI:0.565–0.951, p = 0.019), Zn (OR: 4.922, 95% CI:0.929–26.064, p = 0.061) and nutrients clustered together as PC-1 (OR: 4.76, 95% CI: 2.37–9.54, p = 0.000) and PC-3 (OR: 0.357, 95% CI: 0.640, p = 0.001) were found to have a positive association for the presence of Ft in soil. The odds of occurrence of Ft DNA in soil were higher at locations close to a water source, including canals, streams or drains, [χ2 = 6.7, OR = 1.19, 95% CI:1.05–3.09, p = 0.004] as well as places where animals were present [χ2 = 4.09, OR = 2.06, 95% CI: 1.05–4.05, p = 0.02]. The seroconversion was detected in 6.22% (n = 44, 95% CI: 4.67–8.25) of domestic animals. An occurrence of Ft over a wide geographical region indicates its expansion to enzootic range, and demonstrates the need for further investigation among potential disease reservoirs and at-risk populations, such as farmers and veterinarians.

Brucellosis, globally known bacterial zoonosis, is endemic to Pakistan. B. abortus in bovines, B. melitensis in small ruminants and B. canis in dogs mainly cause this disease. A total of 1821 sera (1196 from sheep and 625 from goats) from animal herds near the Pakistan–Afghanistan border were collected. In parallel testing of sera for anti-Brucella antibodies (B. abortus and B. melitensis) was carried out by RBPT and indirect ELISA. The presence of Brucella DNA in sera was tested by real-time PCR. The overall percentage of seropositive samples was 0.99 (18/1821) by both tests. All positive samples originated from Baluchistan territory which translated into 1.76% (18/1021). None of the positive sera had signals for Brucella DNA and none of sera from goats carried detectable antibodies. Both tests showed an almost perfect agreement with Kappa statistics. The flock size was found to be associated with the presence of anti-Brucella antibodies. The samples of Khyber Pakhtunkhwa (KPK) tested negative in both serological tests and hence were not processed for real-time PCR. The present study shows the presence of anti-Brucella antibodies in sheep in the Baluchistan region of Pakistan. Diagnostic services need to be improved and test and slaughter policies might be implemented for eradication of Brucella infection in these areas. Awareness about the infection is needed at the farmer’s level. Isolation and molecular biology of the isolates could help with understanding the prevailing etiology in a better way.

Brucellosis is an important zoonosis worldwide. Equines are susceptible to the infection when in close contact with infected animals. The objective of our study was to update the existing knowledge and detect and differentiate the causative agent of brucellosis in breeding equines in Punjab, Pakistan. A cross-sectional study was designed to evaluate the occurrence and etiology of the infection in the equine population in three districts. A total of 448 equine sera were collected from three prefectures viz. Sahiwal, Khanewal, and Okara of the Punjab Province of Pakistan. Ninety-six (21.4%) samples were found positive by RBPT, 3.56% (16/448) by iELISA, and 4.24% (19/448) by CFT. Real-time PCR demonstrated the presence of Brucella abortus-DNA in sero-positive samples. Age and location were found as risk factors. The study concludes equine brucellosis seroprevalence in the country where Brucella abortus as the main etiology. Fistulous withers and poll evil cases should be treated with care as they could be hazardous and a source of zoonotic transmission. Routine screening at an early age, vaccination in ruminants, and consumption of pasteurized dairy milk in humans is recommended for prevention of the infection. Specific tests need to be standardized and validated.

The advancement in technology has made it possible to create small in size, low cost sensor nodes. However, the small size and low cost of such nodes comesat at price that is, reduced processing power, low memory and significantly small battery energy storage. WSNs (Wireless Sensor Networks) are inherently ad hoc in nature and are assumed to work in the toughest terrain. The network lifetime plays a pivotal role in a wireless sensor network. A long network lifetime, could be achieved by either making significant changes in these low cost devices, which is not a feasible solution or by improving the means of communication throughout the network. The communication in such networks could be improved by employing energy efficient routing protocols, to route the data throughout the network. In this paper the SVR (Spatial Vector Routing) protocol is compared against the most common WSN routing protocols, and from the results it could be inferred that the SVR protocol out performs its counterparts. The protocol provides an energy efficient means of communication in the network

This paper presents the DME (Distance Measurement Error) estimation analysis for the wireless indoor positioning channel. The channel model for indoor positioning is derived and implemented using 8 WLAN (Wireless Local Area Network) antennas system compliant to IEEE 802.11 a/b/g standard. Channel impairments are derived for the TDOA (Time Difference of Arrival) range estimation. DME calculation is performed over distinct experiments in the TDOA channel profiles using 1,2,4 and 8 antennas deployed system. Analysis for the DME for different antennas is presented. The spiral antenna achieves minimum DME in the range of 1m. Data demographics scattering for the error spread in TDOA channel profile is analyzed to show the error behavior. The effect of increase in number of recordings on DME is shown by the results. Transmitter antennas behavior for DME and their standard deviations are depicted through the results, which minimize the error floor to less than 1 m. This reduction is not achieved in the literature to the best of our knowledge.

This paper proposes text independent automatic speaker verification system using IMFCC (Inverse/ Reverse Mel Frequency Coefficients) and IT-EM (Information Theoretic Expectation Maximization). To perform speaker verification, feature extraction using Mel scale has been widely applied and has established better results. The IMFCC is based on inverse Mel-scale. The IMFCC effectively captures information available at the high frequency formants which is ignored by the MFCC. In this paper the fusion of MFCC and IMFCC at input level is proposed. GMMs (Gaussian Mixture Models) based on EM (Expectation Maximization) have been widely used for classification of text independent verification. However EM comes across the convergence issue. In this paper we use our proposed IT-EM which has faster convergence, to train speaker models. IT-EM uses information theory principles such as PDE (Parzen Density Estimation) and KL (Kullback-Leibler) divergence measure. IT-EM acclimatizes the weights, means and covariances, like EM. However, IT-EM process is not performed on feature vector sets but on a set of centroids obtained using IT (Information Theoretic) metric. The IT-EM process at once diminishes divergence measure between PDE estimates of features distribution within a given class and the centroids distribution within the same class. The feature level fusion and IT-EM is tested for the task of speaker verification using NIST2001 and NIST2004. The experimental evaluation validates that MFCC/IMFCC has better results than the conventional delta/MFCC feature set. The MFCC/IMFCC feature vector size is also much smaller than the delta MFCC thus reducing the computational burden as well. IT-EM method also showed faster convergence, than the conventional EM method, and thus it leads to higher speaker recognition scores.

The OFDM (Orthogonal Frequency Division Multiplexing) is well-known, most utilized wideband communication technique of the current era. SCT (Single Carrier Transmission) provides equivalent performance in time domain while decision equalizer is implemented in frequency domain. SCT annihilates the ICT (Inter Carrier Interference) and the PAPR (Peak to Average Power Ratio) which is inherent to OFDM and degrades its performance in time varying channels. An efficient channel model is presented in this contribution, to implement OFDM and SCT in time domain using impulse responses. Both OFDM and SCT models are derived dialectically to model the channel impulse responses. Our model enhances the performance of time domain SCT compared with OFDM and subsides the PAPR and ICI problems of OFDM. SCT is implemented at symbol level contained in blocks. Simulation results implementing Digital Radio Monadiale (DRM) assert the performance gain of SCT over OFDM.

This article highlights the estimation of the results for the algorithms implemented in order to estimate the delays and distances for the indoor positioning system. The data sets for the transmitted and received signals are captured at a typical outdoor and indoor area. The estimation super resolution algorithms are applied. Different state of art and super resolution techniques based algorithms are applied to avail the optimal estimates of the delays and distances between the transmitted and received signals and a novel method for matrix pencil algorithm is devised. The algorithms perform variably at different scenarios of transmitted and received positions. Two scenarios are experienced, for the single antenna scenario the super resolution techniques like ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) and theMatrix Pencil algorithms give optimal performance compared to the conventional techniques. In two antenna scenario RootMUSIC and Matrix Pencil algorithm performed better than other algorithms for the distance estimation, however, the accuracy of all the algorithms is worst than the single antenna scenario. In all cases our devised Matrix Pencil algorithm achieved the best estimation results.

For years complex numbers have been treated as distant relatives of real numbers despite their widespread applications in the fields of electrical and computer engineering. These days computer operations involving complex numbers are most commonly performed by applying divide-and-conquer technique whereby each complex number is separated into its real and imaginary parts, operations are carried out on each group of real and imaginary components, and then the final result of the operation is obtained by accumulating the individual results of the real and imaginary components. This technique forsakes the advantages of using complex numbers in computer arithmetic and there exists a need, at least for some problems, to treat a complex number as one unit and to carry out all operations in this form. In this paper, we have analyzed and proposed a (–1–j)-base binary number system for complex numbers. We have discussed the arithmetic operations of two such binary numbers and outlined work which is currently underway in this area of computer arithmetic.

Federated learning (FL) is a decentralized machine learning approach whereby each device is allowed to train local models, eliminating the requirement for centralized data collecting and ensuring data privacy. Unlike typical typical centralized machine learning, collaborative model training in FL involves aggregating updates from various devices without sending raw data. This ensures data privacy and security while collecting a collective learning from distributed data sources. These devices in FL models exhibit high efficacy in terms of privacy protection, scalability, and robustness, which is contingent upon the success of communication and collaboration. This paper explore the various topologies of both decentralized or centralized in the context of FL. In this respect, we investigated and explored in detail the evaluation of four widly used end-to-end FL frameworks: FedML, Flower, Flute, and PySyft. We specifically focused on vertical and horizontal FL systems using a logistic regression model that aggregated by the FedAvg algorithm. specifically, we conducted experiments on two images datasets, MNIST and Fashion-MNIST, to evaluate their efficiency and performance. Our paper provides initial findings on how to effectively combine horizontal and vertical solutions to address common difficulties, such as managing model synchronization and communication overhead. Our research indicates the trade-offs that exist in the performance of several simulation frameworks for federated learning. [ABSTRACT FROM AUTHOR]