海南省奶源和养殖环境主要肠杆菌科细菌的分布及基因分型

本研究从2021年海南省两个奶牛场采集的52份样本中分离肠杆菌科细菌,并对分离菌株进行了毒力基因、质粒型和生物被膜形成能力检测及肠杆菌科细菌基因间重复序列分子分型(ERIC-PCR)研究,以期明确牛奶及奶牛场环境中肠杆菌科细菌分布流行状况及其生物学特性。首先,采用16S rDNA PCR和ERIC-PCR对分离的肠杆菌科细菌进行鉴定和去重,结果显示52份样本中分离到肠杆菌科细菌49株,其中大肠埃希菌(Escherichia coli)32株,肺炎克雷伯菌(Klebsiella pneumoniae)13株,阴沟肠杆菌(Enterobacter cloacae)3株,产气肠杆菌(Enterobacter aerogenes)1株;其次,采用PCR方法进行了分离菌株的毒力基因检测,结果显示,ompA的检出率最高;之后,采用CARATTOLI创建的基于PCR的质粒复制子分型,结果显示K质粒的检出率最高;采用刚果红琼脂法对分离菌株进行了生物被膜形成能力定性检测,发现49株肠杆菌科细菌中有37株指示有生物被膜形成能力;最后,通过ERIC-PCR分型进行了肠杆菌科细菌的亲缘关系和遗传多样性分析,发现49株肠杆菌科菌株可划分为17型(Ⅰ~ⅩⅦ),Ⅵ型为优势型(均为Escherichia coli),共20株。整体研究表明肠杆菌科细菌在奶源环境中广泛存在、生物特性多样,推测具有一定的致病力和耐药性,引起人类和动物疾病风险较高,提示养殖、运输中的卫生和规范操作至关重要。

Investigating ischemia and reperfusion-induced organ damage in severe cardiac arrest:A comprehensive proteomics perspective

Cardiac arrest(CA)is a life-threatening condition with complex pathophysiology and limited treatment options.To gain deeper insights into the pathological state of vital organs,we employed a proteomics analysis in rodents to assess proteome alterations in the brain,heart,kidney,and liver using a rat model of CA.The brain displayed severe protein alterations in essential cellular pathways,including three major energy-generating pathways after CA,which worsened after resuscitation,resulting in the most significant overall protein changes among the organs.Conversely,the liver,experiencing the most substantial protein alterations post-CA,demonstrated significant recovery,presenting the least protein changes post-resuscitation.

PCR Based Detection and Phylogenetic Analysis of Fowl Adenovirus Strains Isolated from 2019 Epidemic from Punjab and Sindh, Pakistan

Hydro-Pericardium Hepatitis (HPH) is an emerging infectious disease of commercial poultry, caused by different serotypes of Fowl Adeno Virus. The vertical transmission of the virus into the progeny may results in devastating damage, causing huge economic losses to its farmers. In present study, molecular typing is performed on basis of partially conserved hexon gene sequences, using a unique set of primers having common reverse oligo for simultaneous detection of FAdV1, FAdV-4 and FAdV-11. A total of 14 fowl adeno virus strains were isolated from 100 suspected adeno virus liver samples, collected from different districts in Pakistan, between 2018 and 2019. FASTA’s sequence alignment and phylogenetic analysis revealed that out of the 14, one isolate which belonged to group A showed 27% similarity with FAdV-1, while three isolates showed 99%, 95% & 45% similarity to FAdV-4 (Group C). Whereas, ten isolates showed more than 99% similarity to FAdV-11 (Group D). The serotypes FAdV1, FAdV-4 and FAdV-11 are prevailing in the breeder and broilers. These results hold great importance in rapid, reliable and simultaneous detection of the three FAdV serotypes. Therefore, fowl adeno virus vaccine production for commercial poultry shall be according to the prevalent field serotypes.

Aggregate Suitability Assessment of Wargal Limestone for Pavement Construction in Pakistan

This paper presents the evaluation of the potential aggregate source for pavement construction in Pakistan. Recently the demand for construction materials has been increased significantly due to the establishment of the China-Pakistan Economic Corridor (CPEC) Projects. Therefore, it is essential to look for new resources of construction materials along with the CPEC routes in consideration of this increasing demand. In this context, a Physical and Mechanical characterization investigation is carried out on the Permian Wargal Limestone from Zaluch Nala, Salt Range to explore their potential to utilize as construction materials. The studied samples have tolerable values for all standard engineering parameters, proposed by various national and international agencies such as AASHTO, ASTM, BS, and NHA. Furthermore, as a performance indicator of aggregate overall quality, the evaluated mechanical qualities were integrated into a single characteristic, Toughness Index (TI). The TI values also suggested that the Permian Wargal limestone aggregates meet international quality standards for pavement construction. On the basis of geotechnical testing and Toughness Index (TI), the late Permian Wargal limestone, Zaluch Nala, Salt Range, is strongly recommended as a potential aggregate resource for mega projects such as the China-Pakistan Economic Corridor (CPEC) and other construction projects.

Measurement of Acceleration Due to Gravity Using Arduino and Ultrasonic Sensor

In this study, a simple Arduino-based experiment was designed to examine the acceleration of the object during free fall and to calculate the value of “g” (acceleration due to gravity). Experimental data on the free fall of a plastic box through the air was gathered with the help of an ultrasonic distance sensor (HC-SR04). Readings were taken at different intervals during the fall to obtain distance time curves. Acceleration during the free fall was then determined by applying the standard kinematic equations. The shape of the distance-time graphs obtained from the experimental setup was in good agreement with the predicted graphs and the calculated values of g lie within the expected range. After repeated experiments, value of gravitational acceleration was found to be 9.805 m/s2. Hardware and software prepared for the experiment are sufficient to examine movement of ordinary objects during free fall, therefore the experiment can be easily settled in a laboratory for the purpose of learning and teaching.

Crop photosynthetic response to light quality and light intensity

Under natural conditions, plants constantly encounter various biotic and abiotic factors, which can potentially restrict plant growth and development and even limit crop productivity. Among various abiotic factors affecting plant photosynthesis, light serves as an important factor that drives carbon metabolism in plants and supports life on earth. The two components of light(light quality and light intensity) greatly affect plant photosynthesis and other plant's morphological, physiological and biochemical parameters. The response of plants to different spectral radiations and intensities differs in various species and also depends on growing conditions. To date, much research has been conducted regarding how different spectral radiations of varying intensity can affect plant growth and development. This review is an effort to briefly summarize the available information on the effects of light components on various plant parameters such as stem and leaf morphology and anatomy, stomatal development, photosynthetic apparatus, pigment composition, reactive oxygen species(ROS) production, antioxidants, and hormone production.

Controllable Vapor Growth of Large-Area Aligned CdS_xSe_(1-x) Nanowires for Visible Range Integratable Photodetectors

The controllable growth of large area band gap engineered-semiconductor nanowires(NWs) with precise orientation and position is of immense significance in the development of integrated optoelectronic devices. In this study, we have achieved large area in-plane-aligned CdS_xSe_(1-x) nanowires via chemical vapor deposition method. The orientation and position of the alloyed CdS_xSe_(1-x)NWs could be controlled well by the graphoepitaxial effect and the patterns of Au catalyst. Microstructure characterizations of these as-grown samples reveal that the aligned CdS_xSe_(1-x)NWs possess smooth surface and uniform diameter. The aligned CdS_xSe_(1-x)NWs have strong photoluminescence and high-quality optical waveguide emission covering almost the entire visible wavelength range. Furthermore, photodetectors were constructed based on individual alloyed CdS_xSe_(1-x)NWs. These devices exhibit high performance and fast response speed with photoresponsivity ～670 A W^(-1) and photoresponse time ～76 ms. Present work provides a straightforward way to realize in-plane aligned bandgap engineering in semiconductor NWs for the development of large area NW arrays,which exhibit promising applications in future optoelectronic integrated circuits.

Synthesis and characterization of caprolactone based polyurethane with degradable and antifouling performance

In this work,a degradable polyurethane composed of caprolactone(CL)and L-Lactide(LLA)as soft segments,and 4,40-methylenebis(cyclohexyl isocyanate)(H12 MDI)and polytetramethylene ether glycol(PTMEG)as hard segments,was prepared.Hydrolytic degradation experiment revealed that the degradable polyurethane(PU)could be degraded in artificial seawater.It also showed that caprolactone-copolyurethane(CL-PU)copolymer with higher crystallinity degraded much slower in artificial seawater.However,the introduction of LLA resulted in an increase in the hydrophilicity and reduction in the crystallinity of degradable PU,as demonstrated by the contact angle analysis.The result of the scanning electron microscope showed that the surface of degradable PU renewed under static condition.Moreover,degradable PU was able to be used as a carrier,and it controlled the release rate of 4,5-dichloro-2-octyl-isothiazolone(DCOIT).The anti-diatom(Navicula incerta)test demonstrated that the(caprolactone-co-L-lactide)-co-polyurethane 4(CL/LAx-PU4)with DCOIT contents prevented the adhesion of diatom Navicula incerta(88.37%reduction)due to their self-polishing and the release of antifoulants.Therefore,the degradable PU consisted of CL,LLA,and DCOIT could be a durable resin with good antifouling activity for the application in the marine anti-biofouling field.

Identification of Anomalous Behavioral Patterns in Crowd Scenes

Real time crowd anomaly detection and analyses has become an active and challenging area of research in computer vision since the last decade.The emerging need of crowd management and crowd monitoring for public safety has widen the countless paths of deep learning methodologies and architectures.Although,researchers have developed many sophisticated algorithms but still it is a challenging and tedious task to manage and monitor crowd in real time.The proposed research work focuses on detection of local and global anomaly detection of crowd.Fusion of spatial-temporal features assist in differentiation of feature trained using Mask R-CNN with Resnet101 as a backbone architecture for feature extraction.The data from,BIWI Walking Pedestrian dataset and the Crowds-By-Examples(CBE)dataset and Self-Generated dataset has been used for experimentation.The data deals with different situations like one set of data deals with normal situations like people walking and acting individually,in a group or in a dense crowd.The other set of data contains images four unique anomalies like fight,accident,explosion and people behaving normally.The simulated results show that in terms of precision and recall,our system performs well with Self-Generated dataset.Moreover,our system uses an early stopping mechanism,which allows our system to outperform to make our model efficient.That is why,on 89th epoch our system starts generating finest results.

Economical Requirements Elicitation Techniques During COVID-19: A Systematic Literature Review

Requirements elicitation is a fundamental phase of software development in which an analyst discovers the needs of different stakeholders and transforms them into requirements.This phase is cost-and time-intensive,and a project may fail if there are excessive costs and schedule overruns.COVID-19 has affected the software industry by reducing interactions between developers and customers.Such a lack of interaction is a key reason for the failure of software projects.Projects can also fail when customers do not know precisely what they want.Furthermore,selecting the unsuitable elicitation technique can also cause project failure.The present study,therefore,aimed to identify which requirements elicitation technique is the most cost-effective for large-scale projects when time to market is a critical issue or when the customer is not available.To that end,we conducted a systematic literature review on requirements elicitation techniques.Most primary studies identified introspection as the best technique,followed by survey and brainstorming.This finding suggests that introspection should be the first choice of elicitation technique,especially when the customer is not available or the project has strict time and cost constraints.Moreover,introspection should also be used as the starting point in the elicitation process of a large-scale project,and all known requirements should be elicited using this technique.

Attitude dynamics and control of spacecraft using geomagnetic Lorentz force

Attitude stabilization of a charged rigid spacecraft in Low Earth Orbit using torques due to Lorentz force in pitch and roll directions is considered. A spacecraft that generates an electrostatic charge on its surface in the Earth’s magnetic field will be subject to perturbations from the Lorentz force. The Lorentz force acting on an electrostatically charged spacecraft may provide a useful thrust for controlling a spacecraft’s orientation. We assume that the spacecraft is moving in the Earth’s magnetic field in an elliptical orbit under the effects of gravitational, geomagnetic and Lorentz torques. The magnetic field of the Earth is modeled as a non-tilted dipole.A model incorporating all Lorentz torques as a function of orbital elements has been developed on the basis of electric and magnetic fields. The stability of the spacecraft orientation is investigated both analytically and numerically. The existence and stability of equilibrium positions is investigated for different values of the charge to mass ratio（α＊）. Stable orbits are identified for various values of α＊. The main parameters for stabilization of the spacecraft are α＊and the difference between the components of the moment of inertia for the spacecraft.

Augmenting IoT Intrusion Detection System Performance Using Deep Neural Network

Due to their low power consumption and limited computing power,Internet of Things(IoT)devices are difficult to secure.Moreover,the rapid growth of IoT devices in homes increases the risk of cyber-attacks.Intrusion detection systems(IDS)are commonly employed to prevent cyberattacks.These systems detect incoming attacks and instantly notify users to allow for the implementation of appropriate countermeasures.Attempts have been made in the past to detect new attacks using machine learning and deep learning techniques,however,these efforts have been unsuccessful.In this paper,we propose two deep learning models to automatically detect various types of intrusion attacks in IoT networks.Specifically,we experimentally evaluate the use of two Convolutional Neural Networks(CNN)to detect nine distinct types of attacks listed in the NF-UNSW-NB15-v2 dataset.To accomplish this goal,the network stream data were initially converted to twodimensional images,which were then used to train the neural network models.We also propose two baseline models to demonstrate the performance of the proposed models.Generally,both models achieve high accuracy in detecting the majority of these nine attacks.

A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI

Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to death.Magnetic resonance imaging methods capture skull images that contain healthy and affected tissue.Radiologists checked the affected tissue in the slice-by-slice manner,which was timeconsuming and hectic task.Therefore,auto segmentation of the affected part is needed to facilitate radiologists.Therefore,we have considered a hybrid model that inherits the convolutional neural network(CNN)properties to the support vector machine(SVM)for the auto-segmented brain tumor region.The CNN model is initially used to detect brain tumors,while SVM is integrated to segment the tumor region correctly.The proposed method was evaluated on a publicly available BraTS2020 dataset.The statistical parameters used in this work for the mathematical measures are precision,accuracy,specificity,sensitivity,and dice coefficient.Overall,our method achieved an accuracy value of 0.98,which is most prominent than existing techniques.Moreover,the proposed approach is more suitable for medical experts to diagnose the early stages of the brain tumor.

Smart Dynamic Trafc Monitoring and Enforcement Syste

Enforcement of trafc rules and regulations involves a wide range of complex tasks,many of which demand the use of modern technologies.variable speed limits(VSL)control is to change the current speed limit according to the current trafc situation based on the observed trafc conditions.The aim of this study is to provide a simulation-based methodological framework to evaluate(VSL)as an effective Intelligent Transportation System(ITS)enforcement system.The focus of the study is on measuring the effectiveness of the dynamic trafc control strategy on trafc performance and safety considering various performance indicators such as total travel time,average delay,and average number of stops.United Arab Emirates(UAE)was selected as a case study to evaluate the effectiveness of this strategy.A micro simulation software package VISSIM with add-on module VisVAP is used to evaluate the impacts of VSL.It has been observed that VSL control strategy reduced the average delay time per vehicle to around 7%,travel time by 3.2%,and number of stops by 48.5%.Dynamic trafc control strategies also alleviated congestion by increasing the capacity of the bottleneck section and improving safety.Results of this study would act as a guidance for engineers and decision makers to new trafc control system implementation.

Framework for Effective Utilization of Distributed Scrum in Software Projects

There is an emerging interest in using agile methodologies in Global Software Development(GSD)to get the mutual benefits of both methods.Scrum is currently admired by many development teams as an agile most known meth-odology and considered adequate for collocated teams.At the same time,stake-holders in GSD are dispersed by geographical,temporal,and socio-cultural distances.Due to the controversial nature of Scrum and GSD,many significant challenges arise that might restrict the use of Scrum in GSD.We conducted a Sys-tematic Literature Review(SLR)by following Kitchenham guidelines to identify the challenges that limit the use of Scrum in GSD and to explore the mitigation strategies adopted by practitioners to resolve the challenges.To validate our reviewfindings,we conducted an industrial survey of 305 practitioners.The results of our study are consolidated into a research framework.The framework represents current best practices and recommendations to mitigate the identified distributed scrum challenges and is validated byfive experts of distributed Scrum.Results of the expert review were found supportive,reflecting that the framework will help the stakeholders deliver sustainable products by effectively mitigating the identified challenges.

Equilibria of a charged artificial satellite subject to gravitational and Lorentz torques

The attitude dynamics of a rigid artificial satellite subject to a gravity gradient and Lorentz torques in a circular orbit are considered. Lorentz torque is developed on the basis of the electrodynamic effects of the Lorentz force acting on the charged satellite＇s surface. We assume that the satellite is moving in a Low Earth Orbit in the geomagnetic field, which is considered to be a dipole. Our model of torque due to the Lorentz force is developed for an artificial satellite with a general shape, and the nonlinear differential equations of Euler are used to describe its attitude orientation. All equilibrium positions are determined and conditions for their existence are obtained.The numerical results show that the charge q and radius ρ0of the center of charge for the satellite provide a certain type of semi-passive control for the attitude of the satellite. The technique for this kind of control would be to increase or decrease the electrostatic screening on the satellite. The results obtained confirm that the change in charge can affect the magnitude of the Lorentz torque, which can also affect control of the satellite. Moreover, the relationship between magnitude of the Lorentz torque and inclination of the orbit is investigated.

Epidemiology and Antibiotic Susceptibility Profile of Methicillin Sensitive Staphylococcus aureus among Livestock and Pet Animals

Staphylococcus aureus is an important zoonotic pathogen that is responsible for a variety of infectious diseases in humans and animals.The present study was designed to check the prevalence and antimicrobial resistance of MSSA from three different animal origins(bovine,caprine and pet).A total of n=450 samples(150 each source)were collected from bovine,caprine and pets.Collected samples were subjected to S.aureus identification by microbiological examination and confirmed S.aureus isolates were put to oxacillin disk diffusion test to declare them MSSA.The MSSA confirmed isolates were subjected to various antibiotics for susceptibility profiling using Kirby Bauer Disk Diffusion test.The present study found higher prevalence of MSSA from caprine origin(goat 83.33%)as compared to pet(cat 69.33%;dog 65.33%)and bovine origin(buffalo 26.66%;cattle 31.66%).The in-vitro findings of current study revealed oxytetracycline and gentamicin presented 100%efficacy against MSSA of all origins while the vancomycin presented>35%,>40%and>65%resistance against MSSA isolated from bovine,caprine and pet origin respectively.However,ciprofloxacin was equally effective(50%)against MSSA from buffalo and cattle while>80%efficacy was noted against MSSA from cat and dogs.Linezolid and amoxicillin+clavulanic acid were 77.78%and 66.67%sensitive to MSSA isolates from caprine milk.The present study found higher prevalence of MSSA from bovine,caprine and pet isolates with diversified pattern of susceptibility of different antibiotics from all sources.

Exploring the diversity of microbes and natural products from fungus-growing termite tripartite symbiosis

The fungus-growing termite is considered a distinct ecological niche because it involves a tripartite symbiosis between the termite host,gut microflora,and the in vitro fungus Termitomyces,which has led to the expansion of highly organized and complex societies among termite colonies.Tripartite symbiosis in fungus-growing termites may promote unique microbes with distinctive metabolic pathways that may serve as valuable resources for developing novel antimicrobial therapeutic options.Recent research on complex tripartite symbioses has revealed a plethora of previously unknown natural products that may have ecological roles in signaling,communication,or defense responses.Natural products produced by symbionts may act as crucial intermediaries between termites and their pathogens by providing direct protection through their biological activities.Herein,we review the state-of-the-art research on both microbes and natural products originated from fungus-growing termite tripartite symbiosis,highlighting the diversity of microbes and the uniqueness of natural product classes and their bioactivities.Additionally,we emphasize future research prospects on fungus-growing termite related microorganisms,with a particular focus on their potential roles in bioactive product discovery。

Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl-Eyring fluid flow with diffusive magnetic layers effect over an elongated surface

In recent years,the integration of stochastic techniques,especially those based on artificial neural networks,has emerged as a pivotal advancement in the field of computational fluid dynamics.These techniques offer a powerful framework for the analysis of complex fluid flow phenomena and address the uncertainties inherent in fluid dynamics systems.Following this trend,the current investigation portrays the design and construction of an important technique named swarming optimized neuroheuristic intelligence with the competency of artificial neural networks to analyze nonlinear viscoelastic magneto-hydrodynamic Prandtl-Eyring fluid flow model,with diffusive magnetic layers effect along an extended sheet.The currently designed computational technique is established using inverse multiquadric radial basis activation function through the hybridization of a well-known global searching technique of particle swarm optimization and sequential quadratic programming,a technique capable of rapid convergence locally.The most appropriate scaling group involved transformations that are implemented on governing equations of the suggested fluidic model to convert it from a system of nonlinear partial differential equations into a dimensionless form of a third-order nonlinear ordinary differential equation.The transformed/reduced fluid flow model is solved for sundry variations of physical quantities using the designed scheme and outcomes are matched consistently with Adam's numerical technique with negligible magnitude of absolute errors and mean square errors.Moreover,it is revealed that the velocity of the fluid depreciates in the presence of a strong magnetic field effect.The efficacy of the designed solver is depicted evidently through rigorous statistical observations via exhaustive numerical experimentation of the fluidic problem.

Diversity of fungal isolates from fungus-growing termite Macrotermes barneyi and characterization of bioactive compound from Xylaria escharoidea

Owing to their potential applications,as well as their structural diversity,the discovery of novel secondary metabolites from insect-associated fungi has been of interest to researchers in recent years.The aim of this study was therefore to estimate the diversity of fungi associated with fungus-growing termites and bioprospecting these for potential secondary metabolites.In total,18 fungal species were isolated and described from the gut and comb of Macrotermes barneyi based on 18S ribosomal DNA gene sequence analysis.Antimicrobial activity assays were carried out on all the known fungi,and nine isolates were recorded as active against pathogenic fungi.Xylaria escharoidea,the best performing isolate,was grown at laboratory scale and 4,8-dihydroxy-3,4-dihydronaphthalen-l(2H)was isolated and characterized.The minimum inhibitory concentration of this isolated compound against tested pathogenic organisms was found to be 6.25 fig.In addition,molecular docking studies have revealed that 4,8-dihydroxy-3,4-dihydronaphthalen-l(2H)is a prominent antibacterial agent with a marked interaction with key residues on protein A(agrAc)that regulates the accessory gene.The findings of this study support the drug discovery of antimicrobial properties in insect-associated fungi,which may lead to novel secondary metabolites.