An Optimized Approach to Deep Learning for Botnet Detection and Classification for Cybersecurity in Internet of Things Environment

The recent development of the Internet of Things(IoTs)resulted in the growth of IoT-based DDoS attacks.The detection of Botnet in IoT systems implements advanced cybersecurity measures to detect and reduce malevolent botnets in interconnected devices.Anomaly detection models evaluate transmission patterns,network traffic,and device behaviour to detect deviations from usual activities.Machine learning(ML)techniques detect patterns signalling botnet activity,namely sudden traffic increase,unusual command and control patterns,or irregular device behaviour.In addition,intrusion detection systems(IDSs)and signature-based techniques are applied to recognize known malware signatures related to botnets.Various ML and deep learning(DL)techniques have been developed to detect botnet attacks in IoT systems.To overcome security issues in an IoT environment,this article designs a gorilla troops optimizer with DL-enabled botnet attack detection and classification(GTODL-BADC)technique.The GTODL-BADC technique follows feature selection(FS)with optimal DL-based classification for accomplishing security in an IoT environment.For data preprocessing,the min-max data normalization approach is primarily used.The GTODL-BADC technique uses the GTO algorithm to select features and elect optimal feature subsets.Moreover,the multi-head attention-based long short-term memory(MHA-LSTM)technique was applied for botnet detection.Finally,the tree seed algorithm(TSA)was used to select the optimum hyperparameter for the MHA-LSTM method.The experimental validation of the GTODL-BADC technique can be tested on a benchmark dataset.The simulation results highlighted that the GTODL-BADC technique demonstrates promising performance in the botnet detection process.

Blockchain-Based Message Authentication Scheme for Internet of Vehicles in an Edge Computing Environment

As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for users.Users can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel efficiency.However,in the IoV system,there are always malicious vehicle nodes publishing false information.Therefore,it is essential to ensure the legitimacy of the source.In addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance bottlenecks.Most existing authentication schemes have the problem of low authentication efficiency in the scenario.To address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour Traffic.Here,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message authentication.In addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network attacks.In the simulation experiment,we compare our scheme with other existing works.Our scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.

Effects of thinning on the understory light environment of different stands and the photosynthetic performance and growth of the reforestation species Phoebe bournei

Light levels determine regeneration in stands and a key concern is how to regulate the light environment of different stand types to the requirements of the understory.In this study,we selected three stands typical in south China(a Cryptomeria japonica plantation,a Quercus acutissima plantation,and a mixed stand of both)and three thinning intensities to determine the best understory light environ-ment for 3-year-old Phoebe bournei seedlings.The canopy structure,understory light environment,and photosynthe-sis and growth indicators were assessed following thin-ning.Thinning improved canopy structure and understory light availability of each stand;species composition was the reason for differences in the understory light environ-ment.Under the same thinning intensity,the mixed stand had the greatest light radiation and most balanced spectral composition.P.bournei photosynthesis and growth were closely related to the light environment;all three stands required heavy thinning to create an effective and sustained understory light environment.In a suitable understory light environment,the efficiency of light interception,absorption,and use by seedlings was enhanced,resulting in a higher carbon assimilation the main limiting factor was stomatal conductance.As a shade-avoidance signal,red/far-red radia-tion is a critical factor driving changes in photosynthesis and growth of P.bournei seedlings,and a reduction increased light absorption and use capacity and height:diameter ratios.The growth advantage transformed from diameter to height,enabling seedlings to access more light.Our findings suggest that the regeneration of shade-tolerant species such as P.bournei could be enhanced if a targeted approach to thinning based on stand type was adopted.

Corrosion behavior of HVOF Inconel 625 coating in the simulated marine environment

High velocity oxygen fuel(HVOF)spraying process is commonly used to produce superalloy coatings.Inconel 625 coating was prepared on Q235B low carbon steel by HVOF.A series of experiments were conducted to examine the surface and corrosion resistance properties of Inconel 625 HVOF coating.In this paper,potentiodynamic polarization tests and electrochemical impedance spectroscopy(EIS)tests were carried out to evaluate the corrosion resistance of Inconel 625 coating under simulated marine environment.The experiment-al results showed that Inconel 625 coating revealed low porosity and desired coating thickness.Shift in the corrosion potential(E_(corr))to-wards the noble direction combined with much low corrosion current density(i_(corr))indicating a significant improvement of HVOF Inconel 625 coating compared with the substrate.

Design and Sizing of an Ecological Wastewater Treatment System in a School Environment: A Case Study of Ndiebene Gandiol 1 School

The primary objective of this study was to design and size a sustainable sanitation solution for the Ndiebene Gandiol 1 school located in the eponymous commune in northern Senegal. Field investigations led to the collection of wastewater samples. Their analysis revealed specific pollutant loads, including loads of BOD5 3.6966 kgO2/day and COD of 12.8775 kgO2/day, which were central to the design phase. Following a rigorous assessment of the existing sanitation infrastructure, constructed wetland (CWs) emerged as the most appropriate ecological solution. This system, valued for its ability to effectively remove contaminants, was tailored to the specific needs of the site. Consequently, the final design of the filter extends over 217.16 m2, divided into two cells of 108.58 m2 each, with dimensions of 12.77 m in length and 8.5 m in width. The depth of the filtering medium is approximately 0.60 m, meeting the standards while ensuring maximized purification. Typha, an indigenous and prolific plant known for its purification abilities, was selected as the filtering agent. Concurrently, non-crushed gravel was chosen for its proven filtration capacity. This study is the result of a combination of scientific rigor and design expertise. It provides a holistic view of sanitation for Ndiebene Gandiol. The technical specifications and dimensions of the constructed wetland filter embody an approach that marries indepth analysis and practical application, all aimed at delivering an effective and long-lasting solution to the local sanitation challenges. By integrating precise scientific data with sanitation design expertise, this study delivers a holistic solution for Ndiebene Gandiol. The detailed dimensions and specifications of the constructed wetland filter reflect a methodology that combines meticulous analysis with practical adaptation, aiming to provide an effective and sustainable response to the challenges of rural and school sanitation in the northern region of Senegal.

Synthesis and nitrogen content regulation of diamond in a high-pressure hydrogen-rich environment

The regulating nitrogen content of diamond in a hydrogen-rich high-temperature and high-pressure(HPHT) growth environment was systematically investigated in this work by developing three growth systems,namely, "FeNi+Ti", "FeNi+G_(3)N_(6)H_(6)",and "FeNi+Ti+C_(3)N_(6)H_(6)".Optical microscopy,infrared spectroscopy,and photoluminescence(PL)spectroscopy measurements were conducted to analyze the spectroscopic characteristics of diamonds grown in these three systems.From our analysis,it was demonstrated that the presence of hydrogen in the sp^(3) hybrid C-H does not directly affect the color of the diamond and facilitates the increase of the nitrogen-vacancy(NV) center concentration in a highnitrogen-content diamond.In addition,titanium plays an important role in nitrogen removal,while its impact on hydrogen doping within the diamond lattice is insignificant.Most importantly,by regulating the ratio of nitrogen impurities that coexist in the nitrogen and hydrogen HPHT environment,the production of hydrogenous Ⅱa-type diamond,hydrogenous Ib-type diamond,and hydrogenous high-nitrogen-type diamonds was achieved with a nitrogen content of less than 1 ppm to 1600 ppm.

Predict the evolution of mechanical property of Al-Li alloys in a marine environment

The ocean is one of the essential fields of national defense in the future,and more and more attention is paid to the lightweight research of Marine equipment and materials.This study it is to develop a Machine learning(ML)-based prediction method to study the evolution of the mechanical properties of Al-Li alloys in the marine environment.We obtained the mechanical properties of Al-Li alloy samples under uniaxial tensile deformation at different exposure times through Marine exposure experiments.We obtained the strain evolution by digital image correlation(DIC).The strain field images are voxelized using 2D-Convolutional Neural Networks(CNN)autoencoders as input data for Long Short-Term Memory(LSTM)neural networks.Then,the output data of LSTM neural networks combined with corrosion features were input into the Back Propagation(BP)neural network to predict the mechanical properties of Al-Li alloys.The main conclusions are as follows:1.The variation law of mechanical properties of2297-T8 in the Marine atmosphere is revealed.With the increase in outdoor exposure test time,the tensile elastic model of 2297-T8 changes slowly,within 10%,and the tensile yield stress changes significantly,with a maximum attenuation of 23.6%.2.The prediction model can predict the strain evolution and mechanical response simultaneously with an error of less than 5%.3.This study shows that a CNN/LSTM system based on machine learning can be built to capture the corrosion characteristics of Marine exposure experiments.The results show that the relationship between corrosion characteristics and mechanical response can be predicted without considering the microstructure evolution of metal materials.

Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Heterogeneous population distribution enhances resistance to wheat lodging by optimizing the light environment

Lodging is still the key factor that limits continuous increases in wheat yields today,because the mechanical strength of culms is reduced due to low-light stress in populations under high-yield cultivation.The mechanical properties of the culm are mainly determined by lignin,which is affected by the light environment.However,little is known about whether the light environment can be sufficiently improved by changing the population distribution to inhibit culm lodging.Therefore,in this study,we used the wheat cultivar“Xinong 979”to establish a low-density homogeneous distribution treatment(LD),high-density homogeneous distribution treatment(HD),and high-density heterogeneous distribution treatment(HD-h)to study the regulatory effects and mechanism responsible for differences in the lodging resistance of wheat culms under different population distributions.Compared with LD,HD significantly reduced the light transmittance in the middle and basal layers of the canopy,the net photosynthetic rate in the middle and lower leaves of plants,the accumulation of lignin in the culm,and the breaking resistance of the culm,and thus the lodging index values increased significantly,with lodging rates of 67.5%in 2020–2021 and 59.3%in 2021–2022.Under HD-h,the light transmittance and other indicators in the middle and basal canopy layers were significantly higher than those under HD,and the lodging index decreased to the point that no lodging occurred.Compared with LD,the activities of phenylalanine ammonia-Lyase(PAL),4-coumarate:coenzyme A ligase(4CL),catechol-O-methyltransferase(COMT),and cinnamyl-alcohol dehydrogenase(CAD)in the lignin synthesis pathway were significantly reduced in the culms under HD during the critical period for culm formation,and the relative expression levels of TaPAL,Ta4CL,TaCOMT,and TaCAD were significantly downregulated.However,the activities of lignin synthesis-related enzymes and their gene expression levels were significantly increased under HD-h compared with HD.A partial least squares path modeling analysis found significant positive effects between the canopy light environment,the photosynthetic capacity of the middle and lower leaves of plants,lignin synthesis and accumulation,and lodging resistance in the culms.Thus,under conventional high-density planting,the risk of wheat lodging was significantly higher.Accordingly,the canopy light environment can be optimized by changing the heterogeneity of the population distribution to improve the photosynthetic capacity of the middle and lower leaves of plants,promote lignin accumulation in the culm,and enhance lodging resistance in wheat.These findings provide a basis for understanding the mechanism responsible for the lower mechanical strength of the culm under high-yield wheat cultivation,and a theoretical basis and for developing technical measures to enhance lodging resistance.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

Depositional Environment and Origin of Inertinite-rich Coal in the Ordos Basin

Inertinite-rich coal is widely distributed in the Ordos Basin,represented by the No.2 coal seam of the Middle Jurassic Yan'an Formation.This paper combined coal petrology and geochemistry to analyze the origin of inertinite,changes in the coal-forming environment and control characteristics of wildfire.Research has shown that there are two forms of inertinite sources in the study area.Alongside typical fusinization,wildfire events also play a substantial role in inertinite formation.There are significant fluctuations in the coal-forming environment of samples at different depths.Coal samples were formed in dry forest swamp with low water levels and strong oxidation,which have a high inertinite content,and the samples formed in wet forest swamp and limnic showed low inertinite content.Conversely,the inertinite content of different origins does not fully correspond to the depositional environment characterized by dryness and oxidation.Nonpyrogenic inertinites were significantly influenced by climatic conditions,while pyrofusinite was not entirely controlled by climatic conditions but rather directly impacted by wildfire events.The high oxygen level was the main factor causing widespread wildfire events.Overall,the combination of wildfire activity and oxidation generates a high content of inertinite in the Middle Jurassic coal of the Ordos Basin.

Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

Sedimentary Environment and Mineralization of the Black Shale Polymetallic Layer in the Early Cambrian,SW China:Constraints from in situ LA-ICP-MS Analysis of Pyrite

A polymetallic layer is usually developed at the bottom of the early Cambrian black shale in Guizhou Province.The mineral that makes up the polymetallic layer is related to the sedimentary facies.To analyze the differentiation mechanism between polymetallic deposits(Ni-Mo and V),the Zhijin Gezhongwu profile located in the outer shelf and the Sansui Haishan V deposit located in the lower slope are selected to study the in situ sulfur isotopes and trace elements of pyrite.The results show that δ^(34)S values of pyrite vary widely from−7.8‰to 28‰in the Gezhongwu profile,while the δ^(34)S values are relatively uniform(from 27.8‰to 38.4‰)in the Haishan profile.The isotopic S composition is consistent with the transition that occurs in the sedimentary phase from the shelf to the deep sea on the transgressive Yangtze platform;this indicates that the δ^(34)SO_(4)^(2−)values in seawater must be differently distributed in depositional environments.The sulfur in the Ni-Mo layer is produced after the mixing of seawater and hydrothermal fluid,while the V layer mainly originates from seawater.Overall,the Ni-Mo and V deposits have been differentiated primarily on the basis of the combined effect of continental weathering and hydrothermal fluid.

The chemical environment and structural ordering in liquid Mg-Y-Zn system:An ab-initio molecular dynamics investigation of melt for the formation mechanism of LPSO structure

In an effort to clarify the formation mechanism of LPSO structure in Mg-Y-Zn alloy,the chemical environment and structural ordering in liquid Mg-rich Mg-Y-Zn system are investigated with the aid of ab-initio molecular dynamics simulation.In liquid Mg-rich Mg-Y alloys,the strong Mg-Y interaction is determined,which promotes the formation of fivefold symmetric local structure.For Mg-Zn alloys,the weak Mg-Zn interaction results in the fivefold symmetry weakening in the liquid structure.Due to the coexistence of Y and Zn,the strong attractive interaction is introduced in liquid Mg-Y-Zn ternary alloy,and contributes to the clustering of Mg,Y,Zn launched from Zn.What is more,the distribution of local structures becomes closer to that in pure Mg compared with that in binary Mg-Y and Mg-Zn alloys.These results should relate to the origins of the Y/Zn segregation zone and close-packed stacking mode in LPSO structure,which provides a new insight into the formation mechanism of LPSO structure at atomic level.

Grain size and surface micro-texture characteristics and their paleoenvironmental significance of Holocene sediment in southern margin of the Gurbantunggut Desert,China

The southern margin of the Gurbantunggut Desert,China,is characterized by alternating layers of aeolian and alluvial deposits.Investigating the characteristics of arenaceous sediment in this area is of significant importance for understanding the interactive processes of wind and water forces,as well as the provenance of sediment.However,there are relatively few investigations on the characteristics of such sediment at present.In this study,we researched three aeolian-alluvial interactive stratigraphic profiles and different types of surface sediment on the desert-oasis transitional zone of southern margin of the Gurbantunggut Desert.Based on the optically stimulated luminescence(OSL)dating of aeolian sand and analyses of quartz sand grain size and surface micro-texture,we explored the aeolian-alluvial environmental change at southern margin of the desert in Holocene,as well as the provenance of sediment.The results indicated that the grain size characteristics of different types of sediment in the stratigraphic profiles were similar to those of modern dune sand,interdune sand,muddy desert surface soil,and riverbed sand.Their frequency curves were unimodal or bimodal,and cumulative probability curves were two-segment or three-segment,mainly composed of suspension load and saltation load.The quartz sand in the sediment at southern margin of the desert had undergone alternating transformation of various exogenic forces,with short transportation distance and time,and sedimentary environment was relatively humid.In Holocene,southern margin of the desert primarily featured braided river deposits,and during intermittent period of river activity,there were also aeolian deposits such as sand sheet deposits,stabilized dune deposits,and mobile dune deposits.The provenance for Holocene alluvial deposits at southern margin of the desert remains relatively constant,with the debris of the Tianshan Mountains being the primary provenance.Aeolian sand is mainly near-source recharge,which is formed by in situ deposition of fluvial or lacustrine materials in southern margin of the desert transported by wind erosion,and its provenance was still the weathered debris of the Tianshan Mountains.In addition,the sand in interior of the desert may be transported by northwest wind in desert-scale,thus affecting the development of dunes in southern margin of the desert.The results of this study provide a reference for understanding the composition and provenance changes of desert sand in the context of global climate change.

Paleogene transgression process and environmental evolution in the deepwater area of the Baiyun Depression in the northern South China Sea

Multiple borehole samples are collected from the Baiyun Depression in deep-water area of the northern South China Sea(SCS)in an effort to reconstruct transgression processes during the Paleogene based on palynalgal analysis.This study indicates that the Baiyun Depression generated a large group of palynopore assemblages and fluvial/lacustrine-related algae during the early and middle Eocene when the Wenchang Formation was deposited.The entire depression was dominated by fluvial and lacustrine facies before transgression.Its eastern and southeastern sags transitioned to shallow marine environment by generating a large abundance of marine dinoflagellates during the Enping deposition of the late Eocene.Meanwhile,the southern uplift zone simply yielded fluvial/lacustrine-related palynopores and algae,and was dominated by the fluvial and lacustrine environment during the early stage of the Enping Formation,prior to shifting into transitional setting in the later period.Northwestern sags remained extensive fluvial and delta facies without existence of marine dinoflagellates.It was until the depositional stage of the Zhuhai Formation(Oligocene)that the overall depression was strongly impacted from transgression process.Both eastern and southeastern sags were mainly under deep marine setting on a continental slope while northwestern and southern areas developed transitional facies.Although distribution and accumulation patterns varied greatly among sub-sags,the overall Baiyun Depression was characterized by widespread development of marine dinoflagellates.It should be noted that the northwestern sag also partly generated large-scale river delta deposits.Due to the eustatic rise and change of SCS spreading axis,the overall Baiyun Depression was mostly influenced by the deep marine environment on a continental slope during the early Miocene.Both northwestern sag and southern uplift zone were found plentiful marine dinoflagellates.In summary,transgression initiated from the eastern and southeastern Baiyun Depression before subsequently progressing into the farther west.Evolution of transgression process is also greatly consistent with the gradual westward expansion of the SCS.

Environment Development and Health Safety System in Rural Areas of Bangladesh (Noakhali and Lakshmipur Districts)

At present time, Bangladesh is developing its position in all sectors of world prosperity. Economic development of Bangladesh depends on working ability of whole population of this country, although Bangladesh is not developed in health status of its whole population. A large percentage of people live in rural areas without any proper shelter. This study revealed the environmental development and health safety system in rural areas of Bangladesh, which is located in Noakhali and Lakshmipur districts of Bangladesh. Many sections were studied, which are the main structure of environmental development and health safety system of southeastern region of Bangladesh. The study found that there were three types of handicraft enterprises in the surveyed area such as handicraft input, like palm leaf, factories, Betel nut businesses, and Coconut businesses were headed and owned by the women and they were unaware of their health, environment and waste management or reduction of pollution. This study also reveals that microentrepreneurs did not ensure purified water supply and hygienic toilets within enterprises in the study area. The study also found that a significant portion of the microentrepreneurs are workers, and their family members were always fewer users of protective equipment during the COVID-19 pandemic. This study identified that most MEs faced transport or carrying facilities or big costing problems, including problems in available services for raw materials in the high category. In contrast, the high cost of transport facilities was very intensive in the study area. Moreover, it found that Microentrepreneurs (MEs) faced high product marketing costs for transport facilities, and a lack of proper pricing of the products in the study area. In addition, it explored that most of the microentrepreneurs did not receive sufficient credit support, and they faced negative attitudes and delayed responses from the credit services providers in the study area. It also found that the majority of the microentrepreneurs argued that capital support, loan, aid, technological assistance, infrastructural assistance, availability of skilled labor forces, availability of raw materials, and getting the government assistance and services were the major reasons for the highest growth of the enterprises in the study area. In addition, entire MEs had no knowledge and understanding of climate change in the study area. It is worth mentioning that MEs were not aware of climate change and its impacts on nature in the handicrafts sector and in their daily lives. A significant portion of the MEs took safety measures against risk and protected themselves and workers within the enterprises in the study area. MEs had various demands such as infrastructural development, economic assistance (/aid/loan/grants/financial), training and development, assistance for environment development, and machinery assistance for promoting their business. MEs argued that the implementation of their suggestion is the key to improve the current situation of the enterprises. The MEs suggested appointing expert workers, ensuring quality inputs, training workers and reserving products carefully.

A CombustionModel for Explosive Charge Affected by a Bottom Gap in the Launch Environment

Launch safety of explosive charges has become an urgent problem to be solved by all countries in the world aslaunch situation of ammunition becomes consistentlyworse.However, the existing numericalmodels have differentdefects. This paper formulates an efficient computational model of the combustion of an explosive charge affectedby a bottom gap in the launch environment in the context of the material point method. The current temperatureis computed accurately from the heat balance equation, and different physical states of the explosive charges areconsidered through various equations of state. Microcracks in the explosive charges are described with respectto the viscoelastic statistical crackmechanics (Visco–SCRAM) model. Themethod for calculating the temperatureat the bottomof the explosive charge with respect to the bottomgap is described. Based on this combustionmodel,the temperature history of a Composition B (COMB) explosive charge in the presence of a bottom gap is obtainedduring the launch process of a 155-mm artillery. The simulation results show that the bottom gap thickness shouldbe no greater than 0.039 cm to ensure the safety of the COM B explosive charge in the launch environment. Thisconclusion is consistent with previous results and verifies the correctness of the proposed model. Ultimately, thispaper derives amathematical expression for themaximumtemperature of the COMB explosive chargewith respectto the bottomgap thickness (over the range of 0.00–0.039 cm), and establishes a quantitative evaluationmethod forthe launch safety of explosive charges.The research results provide some guidance for the assessment and detectionof explosive charge safety in complex launch environments.

Study on Distribution of Four Pseudomonas Species in Living Environment Using Multiplex PCR

Purpose: The genus Pseudomonas is a ubiquitous microorganism frequently detected from immunocompromised patients. The inherent resistance to numerous antimicrobial agents contributes to the opportunistic character of this pathogen exhaustive monitoring of this pathogen is considered of critical importance to public health organizations. The reliable identification method able to distinguish genetic close Pseudomonas species is needed, because these organisms are difficult to differentiate by phenotypic or biochemical methods. The purpose of the present study was to design species-specific primers in order to identify and detect four Pseudomonas species which are frequently detected from the human oral cavities, and to investigate the distribution of these organisms in the living environment using a multiplex PCR. Methods: Polymerase chain reaction (PCR) primers were designed based on partial sequences of the rpoD gene of four Pseudomonas species. Swab samples were collected from fifty washstands, and the distribution of Pseudomonas species was investigated using a conventional PCR at genus level and a multiplex PCR at species level. Results: Multiplex PCR method developed in this study was able to distinguish four Pseudomonas species clearly. The genus Pseudomonas was detected from all samples (100%), whereas P. putida, P, aeruginosa, P. stutzeri and P. fluorescens were detected at 44%, 8%, 4% and 2% in fifty swab samples, respectively. Conclusion: Our developed one-step multiplex PCR method is accurate, specific, cost-effective, time-saving, and works without requiring DNA extraction. It was indicated that washstands were the uninhabitable environment for P. putida, P, aeruginosa, P. stutzeri and P. fluorescens.

Integrating linear and nonlinear models to assess the built environment’s impact on older adults’behaviors in China

China is experiencing rapid population aging.The one contributing factor affecting senior citizens’lives is the disconnect between the built environment in urban and rural areas and the behavioral preferences of older adults.However,research on the relation between the built environment and the behavior of older individuals has been limited.Thus,this paper uses the most recent health tracking data on factors influencing aging in China released in 2020(China Senior Health Survey Tracking Survey).Applying traditional regression,least absolute shrinkage and selection operator regression,and two decision tree optimization models from machine learning,a comprehensive comparative study is carried out to investigate the correlation between the built environment and the physical activity,dietary habits,and social interactions of older age groups.The findings reveal that built environment variables most significantly impact physical activity,accounting for 52.525%,followed by social interaction behaviors at 50.202%and dietary intake at 47.991%.Furthermore,the authors identify population density and greenness rate as the built environment factors having considerable effects on the behavior of older adults.Thus,this study establishes a theoretical foundation for developing age-friendly community environments for older adults.