bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidemiology and Risk Mapping of hard ticks (Ixodidae) infecting Small Ruminants in Khyber Pakhtunkhwa Province, Pakistan
Authors: Iqbal Z , Afshan K , Kayani AR , Ahmad H , Irfan M , Qayyum M
Published: April 2024

Ticks and tick-borne diseases (TBDs) cause a negative impact on animal health and production globally. Because of the transhumant production system of sheep and goats in Khyber Pakhtunkhwa (KP), Pakistan, registration and tracking system of animals is not possible, which is a prerequisite for the development of early warning systems for any outbreak of TBDs. Therefore, the present study was aimed to investigate the district-wise surveillance and risk mapping to find the epidemiological profile of tick infestation in small ruminants from KP, Pakistan. Ticks (n=6257) were collected from the six selected districts from May 2017- April 2018. A total of 1500 animals (goats=618 and sheep=881) were screened for the presence of ticks on different host predilection sites. A questionnaire depicting epidemiological information was filled, and a geographic information system (GIS) was used to map the risk areas. The study identified six tick species namely, Rhiphicephalus (R.) microplus, Hyalomma (H.) trancatum, H. anatolicum, H. aegyptium, H. asiaticum, and Haemaphysalis bispinosa. The tick prevalence in study districts was 16% in Peshawar, 15.67% Mardan, 12.8% Bannu, 18% Mansehra, 15.67% Mingora, and 21.87% in Dera Ismail Khan. R. microplus was only prevalent in Peshawar (36.18 %) and in Dera Ismail Khan (63.81 %) districts, while Haemaphysalis bispinosa and H. aegyptium were only recorded in Mardan. The intensity of Hyalomma spp. was recorded at 62.92 % followed by Rhipicephalus spp., 36.55%, and Haemaphysalis spp., 1.15%. Hyalomma spp. showed the highest prevalence on all host predilection sites viz: ears (62.2 %), groin areas (60.8%), under the tail (61.9 %), testicular areas (63.2 %), breast (64.5 %), and in hooves (64.7%) as compared to Rhipicephalus and Haemaphysalis species. Similarly, in sheep and goats, the adult ticks were more prevalent in age group 1-2 years (83.28% and 68.98%) followed by < 1 year of age group (82% and 68.89%), respectively. The results revealed high female (61.9%) tick infestation as compared to male ticks (38.1%), whereas the highest female to male tick ratio was 1.77:1 in Haemaphysalis species. The GIS map demonstrated that the degree of tick infestation varied within districts and villages.  In conclusion, results recorded that economically vital ticks are extensively distributed all over the KP province and cost-effective control studies are needed to minimize the spread of tick-borne diseases.
Assessment anti-granuloma activity of Alpha-lipoic acid in chicks’ models
Authors: Abdul-Ghani MR , Naser AS
Published: April 2024

Background: Alpha-lipoic acid is an anti-inflammatory and antioxidant agent that has free radical scavenging characteristics as well as better effects on the recycling of other cellular antioxidants.Aim: The present study was made to assess the anti-granuloma of Alpha-lipoic acid by the cotton pellet granuloma method.Method: The chicks weighing around 100-150 g were selected, the Alpha-lipoic acid was administered at the following dose of 20, 40 & 80 mg/kg body weight respectively after insertion of cotton pellets into the groin region of chicks.Results: By using the up-and-down technique, it was found that the Median Lethal Dose (LD50) of the Alpha-lipoic acid was 451.8mg/kg, IP.  Alpha-lipoic acid at 20, 40, and 80 mg/kg per body weight daily for consecutive seven days revealed that the ALA shows dose-dependent inhibition of weight of both wet and dry cotton pellets. The inhibition percentage for wet cotton pellets was 5, 11, and 14 respectively whereas the inhibition percentage for dry cotton pellets was 9, 15, and 25 respectively.  Conclusion: We conclude that Alpha-lipoic acid has notable anti-granuloma activity as compared to control in animal models of chronic inflammation. Additional studies must be done to find the molecular role of Alpha-lipoic acid as anti-granuloma remedies
The Effect of Drinking Water Temperature and Stocking Density on Broiler Performance, Meat Quality and Some Behavioral Traits at High Ambient Temperature
Authors: Kaya M , Dereli Fidan E
Published: April 2024

The present study examined the effect of drinking water temperature and stocking density on performance (cumulative body weight gain, feed intake, and feed conversion ratio), meat quality, and behaviour traits (eating, drinking, lying, standing, and dust bathing) in broilers. A total of 360 broiler chicks (Ross 308) were randomly divided into 6 experimental groups, in a 2x3 factorial arrangement of drinking water temperature (10°C or 31°C), with stocking density (12, 15 or 18 birds/m2), each consisting of 4 replicate pens. Meat quality traits (pH15, L*, CL, and WHC), lying and standing behaviours were affected by water temperature. The stocking density significantly affected the cumulative body weight gain, feed intake, feed conversion ratio, color of breast meat [lightness (L*), redness (a*), yellowness (b*)] of broiler chickens. In conclusion, management practices such as stocking density and drinking water temperature in broilers could reduce the detrimental effects of high ambient temperature on growth performance, meat quality traits, and behaviour.
Comparative study on genotypic properties of Pseudomonas aeruginosa isolated from subclinical mastitis in Türkiye
Authors: Turkyilmaz S , Ocak F
Published: April 2024

The results of antibacterial therapy in mastitis may be related to not only the antibiotic sensitivity of the etiological factors, but also to their abilities carrying integron and virulence genes. Integrons are mobile DNA element that can capture and carry genes, particularly those responsible for antibiotic resistance. Pseudomonas aeroginosa has numberless virulence factors which are contributed to bacterial invasion and toxicity. The aim of this study is to investigate antibiotic resistance, integron and virulence gene profiles of P. aeruginosa isolates obtained from cow milk with subclinical mastitis; further, was to evaluate the relationship between the antimicrobial resistance of bacteria with the of integron and virulence gene carrying. Material of the study is consisted with 32 (9.8%) of P. aeruginosa isolates obtained from 326 subclinical mastitic milk samples. After the bacterial identification was done by classical conventional methods, polymerase chain reaction (PCR) was used to verify the genus and species identifications of the isolates and to determine the integron and virulence gene profiles. Using disk diffusion method, antimicrobial resistance was determined to fifteen antibiotics against belonging to eleven antimicrobial families. The relationship the presence of integron and virulence genes associated with antibiotic resistance, further the relationship the presence of virulence genes and antimicrobial resistance was calculated with the Chi-Square (χ2) test. Ten of virulence genes (lasl, lasR, lasB, rhll, rhlR, rhlAB, plcH, plcN, ppyR, exoT) were found in all isolates whilst a virulence gene (aprA) was not present in any isolate. It was found that 34.4% of the isolates carried any integron gene. The results showed that the relationship is important between the presence of int genes and gentamicin, amikacin, tetracycline, cefoperazone, imipenem, aztreonam, ciprofloxacin, enrofloxacin resistance and exoU virulence gene presence. Also; there were also important associations between resistance to certain antibiotics and the presence of P. aeroginosa virulence genes: ciprofloxacin with lasA; netilmicin, cefoperazone and ciprofloxacin with pilB; netilmicin and ciprofloxacin with pelA; amikacin with algD, algU, algL; aztreonam with toxA; enrofloxacin with pvdA. All isolates obtained in this study showed multiple antibiotic resistance (MDR). In these cases, the presence of integron and some virulence genes could play a prominent role in the resistance of P. aeroginosa isolates to antimicrobial drugs. This study could be important in that it is the first study to show the presence of integrons and virulence genes in P. aeroginosa isolates originating from mastitic cow milk in Turkey. The presence of antibiotic-resistant P. aeroginosa strains in cattle farms may also pose a public health risk, as these bacteria can transmit their resistance genes to humans through food consumption.
Antibiotic resistance and enterotoxin gene profiles of Staphylococcus aureus isolated from raw milk in Iran
Authors: Shariatifar M , Salavati-Hamedani M , Rezaeian-Doloei R , Rezaeigolestani M , Mohsenzadeh M
Published: April 2024

Staphylococcus aureus is a food-borne pathogen frequently isolated from raw milk in different parts of the world. The emergence of antibiotic resistant strains of S. aureus has become an important global public health issue. In spite of this problem, the contamination rate of raw milk with enterotoxigenic antibiotic resistant S. aureus strains has been rarely evaluated in Iran. This study aimed to evaluate the prevalence and antibiotic resistance of coagulase positive S. aureus strains isolated from bulk tank milk samples in Mashhad, and to analyze the frequency of genes encoding the staphylococcal enterotoxins (SEs). 250 milk samples were tested for S. aureus by the conventional plating method and PCR. The disc diffusion method was used to assess the antibiotic susceptibility of the isolated S. aureus. Finally, the frequency of the SEs encoding genes was determined by the PCR method. S. aureus was detected in 18.4% of the tested milk samples at mean concentrations of 3.5 × 105 CFU/ml. The results showed that 86.95% of the isolates were resistant to at least one antibiotic and the highest resistance was observed against penicillin, ampicillin and methicillin. In total, 71.74% of the studied bacteria had at least one of the SEs encoding genes, and sec and sea genes were the most prevalent ones. In conclusion, the prevalence of enterotoxigenic antibiotic-resistant S. aureus in the milk samples collected from Mashhad dairy farms proves that additional efforts must be devoted to implementing hygienic processes in dairy farms and controlling antibiotic usage as well.
Kaempferol and Isorhamnetin alleviate Lipopolysaccharide-Induced Anxiety and Depression-Like Behavioral in Balb/C Mice
Authors: Ekici M , Güngör H , Mert DG
Published: April 2024

The etiology of anxiety and depression is linked to inflammation and oxidative stress. Isorhamnetin and Kaempferol are strong antioxidants with antiinflammatory and neuroprotective properties. This study, it was aimed to investigate the effect of Kaempferol and Isorhamnetin in Lipopolysaccharide (LPS)-induced anxiety and depression model in mice. Thirty Balb/C mice were divided into six groups of five mice each weighing 25-35 gr. Kaempferol (50 mg/kg and 100 mg/kg) and Isorhamnetin (30 mg/kg and 60 mg/kg) were given orally to the treatment group, and the vehicle was given to the control and LPS groups for fourteen days, followed by intraperitoneal (0.83 mg/kg) LPS injection (control group excluding) on the fifteenth day. Kaempferol and Isorhamnetin ameliorated LPS-induced anxiety evaluated by open field test, light/dark test, and elevated plus maze test, and LPS-induced depression evaluated by forced swimming test and tail suspension test. Kaempferol and Isorhamnetin alleviated LPS-induced increased oxidative stress in the prefrontal cortex and hippocampus by decreasing MDA and total oxidant status (TOS) levels and increased total antioxidant status (TAS) levels. In addition, it was observed that Kaempferol and Isorhamnetin regulated the increase in prefrontal and hippocampal inflammation caused by LPS by decreasing TNF-α, IL-1β, and IL-6 levels. Most importantly, LPS reduced prefrontal and hippocampal brain-derived neurotrophic factor (BDNF) levels, but the treatment groups reversed it. These results show the possible therapeutic potential of Kaempferol and Isorhamnetin, along with the importance of oxidative stress, inflammation, and BDNF in the etiopathogenesis of anxiety and depression.
Poweromin X Ten, a polyherbal formulation improves male sexual function: In vivo and network pharmacology study
Authors: Bojja Sree Lalitha , Kolathur Kiran Kumar , Chaudhari Bhim Bahadur , Hari Gangadhar , Byregowda Bharath Harohalli , Meka Sai Teja , Selvan Esekia Raja , Moorkoth Sudheer , Kumar Nitesh , Austin Anoop , Rao C. Mallikarjuna
Published: April 2024

Introduction Poweromin X Ten (PXT) is a polyherbal formulation, traditionally used to enhance male sexual function. However, the safety and benefits of PXT have not been scientifically evaluated. Therefore, the present study investigated the toxicity and aphrodisiac potential of PXT in male rats and explored its principal mechanisms of action. Methods Male Wistar rats were orally administered PXT (50 or 100 mg/kg) for 28 days, and sexual activity parameters, including latency and frequency of mounting and intromissions, were studied. The reproductive toxicity and spermatogenic potential were also examined. Furthermore, dopamine and serotonin levels in brain regions associated with sexual activity were assessed. Network analysis was used to identify the key bioactive compounds and their core targets involved in their beneficial actions. Results Treatment with PXT improved sexual activity in male rats, as evidenced by reduced mounting and intromission latency and a significant increase in mount frequency. Moreover, PXT exhibited spermatogenic potential and did not induce reproductive toxicity. Notably, treatment with 50 mg/kg PXT elevated dopamine levels in median preoptic area and hypothalamus. Pathway analysis indicated that PXT primarily modulated the PI3K-Akt, calcium, and MAPK signalling pathways to enhance male sexual function. Network analysis identified macelignan, β-estradiol, testosterone, and paniculatine as key bioactive components of PXT, which likely act through core targets, such as androgen receptor (AR), Mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor (EGFR), estrogen receptor 1 (ESR1), and vascular endothelial growth factor (VEGF) to facilitate the improvement of male sexual function. Conclusion Study results suggest that PXT is a safer alternative with aphrodisiac and spermatogenic potential. These effects are partly attributed to the enhanced dopamine levels in the brain. Furthermore, this study provides insights into the specific signalling pathways and bioactive compounds that underlie the improvements in male sexual function associated with PXT.
Medical students' perspective on the United States Medical Licensing Examination (USMLE) Step 1 transition to Pass/Fail
Authors: Prasad Samiksha , Perez Christine , Carnevale Kate J.F.
Published: April 2024

Background The transition of the United States Medical Licensing Exam: Step 1 to Pass/Fail (P/F), from scored, caused uncertainty about students’ preparedness and wellbeing related to the exam. Comparison of study behavior and results, before and after the P/F transition can provide insights for the medical curriculum and student support. Methods Data from four cohorts of second-year medical students (Class of 2022–25, N = 204) were collected from their dedicated Step 1 self-study block. Student study regiments, aggregate practice test results, Step 1 pass rates and post-block self-reported surveys were analyzed. Results Analysis of practice exam averages across the four student cohorts demonstrates a potentially slower and less rigorous start to Step 1 self-studying during the dedicated preparation block for the cohorts that took the P/F Step 1 exam format as compared to the previous cohorts that prepared for a scored Step 1 exam. Similarly, self-reported study regiments decreased in the median number of hours/day and number of weeks of study for the cohorts with P/F Step 1 exam. There was also a slight shift in the type of study resources used, between the two groups, with the scored group using more traditional board preparation resources. Conclusions The P/F transition of the Step 1 exam may lead to reduced student preparedness and may require adjustments in the resources and support provided by institutions.
High resolution chlorophyll-a in-situ fluorescence sensors versus in-vitro chlorophyll-a measurements in mesocosms with contrasting nutrient and temperature treatments
Authors: Levi Eti Ester , Jeppesen Erik , Nejstgaard Jens C. , Davidson Thomas Alexander
Published: April 2024

Harmful algal blooms (HABs) are a significant threat to freshwater ecosystems, and monitoring for changes in biomass is therefore important. Fluorescence in-situ sensors enable rapid and high frequency real-time data collection and have been widely used to determine chlorophyll-a (Chla) concentrations that are used as an indicator of the total algal biomass. However, conversion of fluorescence to equivalent Chla concentrations is often complicated due to biofouling, phytoplankton composition and the type of equipment used. Here, we validated measurements from 24 Chla and 12 phycocyanin (cyanobacteria indicator) fluorescence in-situ sensors (Cyclops-7F, Turner Designs) against spectrophotometrically (in-vitro) determined Chla and tested a data-cleaning procedure for eliminating data errors and impacts of non-photochemical quenching. The test was done across a range of freshwater plankton communities in 24 mesocosms (i.e. experimental tanks) with a 2x3 (high and low nutrient x ambient, IPCC-A2 and IPCC-A2+50% temperature scenarios) factorial design. For most mesocosms (tanks), we found accurate (r2 ≥ 0.7) calibration of in-situ Chla fluorescence data using simple linear regression. An exception was tanks with high in-situ phycocyanin fluorescence, for which multiple regressions were employed, which increased the explained variance by >16%. Another exception was the low Chla concentration tanks (r2 < 0.3). Our results also show that the high frequency in-situ fluorescence data recorded the timing of sudden Chla variations, while less frequent in-vitro sampling sometimes missed these or, when recorded, the duration of changes was inaccurately determined. Fluorescence in-situ sensors are particularly useful to detect and quantify sudden phytoplankton biomass variations through high frequency measurements, especially when using appropriate data-cleaning methods and accounting for factors that can impact the fluorescence readings.
Enhanced identification of endocrine disruptors through integration of science-based regulatory practices and innovative methodologies: The MERLON Project
Authors: Svingen Terje , Andersson Anna-Maria , Angelova Julianna , Axelstad Marta , Bakker Julie , Baumann Lisa , Beronius Anna , Bouftas Nora , Chalmel Frederic , Christiansen Sofie , Cornil Charlotte , Damdimopoulou Pauliina , Deepika Deepika , Dollé Martijn E. T. , Draskau Monica Kam , Fischer Margit Bistrup , Hagen Casper P. , Hessel Ellen , Holmer Marie Louise , Hughes Samantha , Jensen Genon , Johansson Hanna Katarina Lilith , Juul Anders , Kumar Vikas , Kumar Saurav , Lardenois Aurélie , Main Katharina M. , Mazaud-Guittot Severine , Moe S. Jannicke , Mola Gylli , Parent Anne-Simone , Pineda Rafael , Rolland Antoine , Rosenmai Anna Kjerstine , Song You , Suglia Antonio , Tena-Sempere Manuel , Wehrli Lydia , Zilliacus Johanna , van Duursen Majorie
Published: April 2024

The prevalence of hormone-related health issues caused by exposure to endocrine disrupting chemicals (EDCs) is a significant, and increasing, societal challenge. Declining fertility rates together with rising incidence rates of reproductive disorders and other endocrine-related diseases underscores the urgency in taking more action. Addressing the growing threat of EDCs in our environment demands robust and reliable test methods to assess a broad variety of endpoints relevant for endocrine disruption. EDCs also require effective regulatory frameworks, especially as the current move towards greater reliance on non-animal methods in chemical testing puts to test the current paradigm for EDC identification, which requires that an adverse effect is observed in an intact organism. Although great advances have been made in the field of predictive toxicology, disruption to the endocrine system and subsequent adverse health effects may prove particularly difficult to predict without traditional animal models. The MERLON project seeks to expedite progress by integrating multispecies molecular research, new approach methodologies (NAMs), human clinical epidemiology, and systems biology to furnish mechanistic insights and explore ways forward for NAM-based identification of EDCs. The focus is on sexual development and function, from foetal sex differentiation of the reproductive system through mini-puberty and puberty to sexual maturity. The project aims are geared towards closing existing knowledge gaps in understanding the effects of EDCs on human health to ultimately support effective regulation of EDCs in the European Union and beyond.
The genome sequence of the Sallow Marble, Apotomis capreana (Hübner, 1817)
Authors: Boyes Douglas , Boyes Clare ,   University of Oxford and Wytham Woods Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life Management, Samples and Laboratory team,   Wellcome Sanger Institute Scientific Operations: Sequencing Operations,   Wellcome Sanger Institute Tree of Life Core Informatics team,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: April 2024

We present a genome assembly from an individual male Apotomis capreana (the Sallow Marble; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 743.2 megabases in span. Most of the assembly is scaffolded into 28 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 17.12 kilobases in length.
The genome sequence of an ichneumonid wasp, Oxytorus armatus Thomson, 1883
Authors: Broad Gavin R. , Fletcher Chris , Januszczak Inez ,   Natural History Museum Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life Management, Samples and Laboratory team,   Wellcome Sanger Institute Scientific Operations: Sequencing Operations,   Wellcome Sanger Institute Tree of Life Core Informatics team,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: April 2024

We present a genome assembly from an individual male Oxytorus armatus (an ichneumonid wasp; Arthropoda; Insecta; Hymenoptera; Ichneumonidae). The genome sequence is 367.8 megabases in span. Most of the assembly is scaffolded into 13 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 56.22 kilobases in length.
Minimizing Overhead through Blockchain for Establishing a Secure Smart City with IoT Model
Authors: Xiao Zhixiong
Published: April 2024

Conventional safety measures are inconsistent with inexpensive technologies like the Internet of Things (IoT) due to their significant storage traces, which are prohibitive to their utilization. The blockchain (BC) framework maintains the five essential security primitives: genuineness, credibility, secrecy, accessibility, and non-renunciation. Most IoT gadgets have limited resources, so a traditional blockchain deployment is inappropriate. Traditional deployment of blockchain computing in the Internet of Things leads to significant power consumption, delay, and computational inefficiency. The proposed solution improves the blockchain's conception to serve IoT technologies better. This article proposes a blockchain-based intelligent city design for the IoT that keeps all encryption safety precautions in place. Adding blockchain to an IoT platform does not add much extra labour. After comparing all safety requirements to existing literature, it is clear that the proposed method achieves satisfactory safety effectiveness.
Research on Integrating Blockchain and Machine Learning LPP Algorithm in Online Education Platform under COVID-19 Environment
Authors: Daojun Wang  , Meishu Wang  , Xing Xinli
Published: April 2024

Learners confront the issue of navigating an enormous quantity of resources in the developing field of online education, which has been exacerbated by the COVID-19 pandemic. To solve this, our research proposes a novel Learner Path Planning (LPP) model that integrates blockchain and machine learning technologies to maximize the online learning experience. This model employs the ant colony optimization technique, which has been upgraded with blockchain for enhanced security and machine learning for intelligent path planning, to provide a more personalized and efficient learning experience. Our approach determines the extent of concept realization and interaction by examining the interaction degrees of knowledge points, establishing heuristic information and initial pheromone levels for the optimization process. This technique not only optimizes teaching duration based on instructional efficacy, but it also adapts dynamically to individual learner needs. Our empirical data reveal that goal success rates improve significantly across all learner levels. For example, elementary students in 2021 had the highest goal achievement rate of 0.5896. In 2019, intermediate and advanced learners attained rates of 0.7726 and 0.9058, with a significant association between course similarity and target achievement. Blockchain integration ensures secure and transparent processing of educational data, while machine learning algorithms successfully personalize learning routes to meet the various demands of learners. This study not only assists learners in effectively identifying suitable resources, but it also provides useful insights for instructors in improving online teaching approaches. The model's adaptability and scalability make it particularly applicable in the context of the COVID-19 pandemic's rapid developments and problems in the education sector.
Optimal Feature Selection from High-dimensional Fusion of Blood Smear Images for Leukemia Diagnosis
Authors: Pullaiah G. Chinna , P.M. Ashok Kumar
Published: April 2024

The goal of this study is to improve blood smear image-based blood cancer prediction through medical diagnostic advancements. Blood cancers, particularly leukemia, are challenging to diagnose because of the complexity of biological data and the dimensionality of medical images. There are interpretability and computational problems with each currently in use. We suggest the Random Forest-Recurrent Feature Elimination (RF-RFE) model to increase the precision and dependability of blood cancer diagnosis. This model integrates machine learning and image processing, optimizes feature selection and refinement from high-dimensional data, and applies the XGBoost algorithm to guarantee diagnosis accuracy. Recent model analysis reveals that RF-RFE performs better than them on a wide range of metrics. The RF-RFE offered a sensible, well-rounded strategy. More research on medical diagnostics is made possible by its adaptability in multi-class classification and effectiveness in handling high-dimensional feature values. The optimized feature set and computational efficiency of the model, which may enhance leukemia detection and diagnostics, are highlighted in this study.
A Lightweight Symmetric Cryptography based User Authentication Protocol for IoT based Applications
Authors: A Mahesh Reddy , M Kameswara Rao
Published: April 2024

The utilization of IoT is expanding across various domains, including telecare, intelligent home systems, and transportation networks. In these environments, IoT devices generate data gathered on remote servers, requiring external users to authenticate themselves to access the data. However, existing authentication protocols for IoT must meet the crucial requirements of speed, security against multiple attacks, and ensuring user anonymity and un-traceability. The main objective of this work is to find lightweight symmetric cryptography-based user authentication protocol tailored for IoT-based applications, focusing on MIM (Man-in-the-Middle) attack prevention, enhanced anonymity, and secure communication between IoT nodes and remote servers via IoT gateways. Existing protocols often lack sufficient defenses against MIM attacks and do not adequately address the need for enhanced user anonymity and secure communication channels within the IoT framework. Our research has identified that authentication techniques based on pairing are susceptible to attacks targeting temporary session-specific data, impersonation, privileged insiders, and offline password guessing. Furthermore, using bilinear pairing in these techniques requires significant computational and communication resources to address the security as mentioned above concerns. A new authentication mechanism must be proposed and designed explicitly for IoT scenarios. The proposed approach exclusively utilizes hash and exclusive-or operations to ensure suitability within the IoT context; thoroughly evaluated the recommended protocol against existing authentication protocols, employing both informal and formal analytical routines like BAN logic, ROR model, and AVISPA simulation. Our findings suggest protocol not only enhances performance but also enhances security. The proposed approach is a tried-and-true strategy for improving security rules in practical Internet of Things (IoT) settings addressing the inherent challenges posed by authentication requirements in IoT environments. The accuracy 98.93%, and Node detection rate 46.57% were improved which is a better outcome.
Economic Dispatch of Multi Regional Power Systems Based on CMOPSO Algorithm
Authors: Guo Jinhua
Published: April 2024

With the progress of society and the aggravation of environmental pollution, the economic dispatch of the power system is developing towards multiple environmental and economic goals. To improve energy utilization efficiency, this study innovatively proposes a multi-objective particle swarm optimization algorithm based on competitive learning, and uses this algorithm to solve multi regional environmental and economic scheduling problems. In addition, the study solves static and dynamic economic (S-DE) scheduling problems in multiple regions through improved competitive group optimization algorithms. The research results show that under different testing systems, the average distribution uniformity indicators of the research algorithm built on competitive learning are 0.8058 and 0.8457, and the average anti generation distance is 67.6316 and 1664.0978. The improved competitive group optimization algorithm solves the maximum, minimum, and average fuel costs for static economic scheduling in multiple regions, which are 656.2243 $/h, 655.8592 $/h, and 655.9866 $/h, respectively. Thus, the designed algorithm can effectively solve economic scheduling problems, which is of great significance for resource integration, saving power generation costs, and reducing pollution emissions.
Big Data Analysis and Deep Learning Optimization in Artificial Intelligence Production of Information Enterprises
Authors: Gao Na , Lu Qiuling
Published: April 2024

Intelligent manufacturing technology is required to upgrade existing enterprises' management and production operations. To construct a ground breaking fusion structure, this project unites the theoretical underpinnings, technical breakthroughs, and applications of data analytics, optimisation, and intelligent production engineering. It is driven by China's desire of cutting-edge commodities and efficient growth methods. This research establishes the broad framework for merging optimisation and data analytics. There is a list of data analytics and system optimisation technologies that can address important challenges with intelligent manufacturing. By integrating data analytics and optimisation, businesses may better forecasting and management of new terrain, as well as reveal hidden information to increase decision-making efficacy.
Research and Design of an Automated Security Event Analysis and Handling Framework Based on Threat Intelligence
Authors: Xie Linjiang , Liao Zhouyuan , Li Hanruo
Published: April 2024

In order to deeply explore and utilize the value of threat intelligence, strengthen research on attack organizations, and grasp the correlation between attack organizations, the author proposes the research and design of an automated security event analysis and handling framework based on threat intelligence. The author extracts the behavioral characteristics of the attack organization based on known APT attacks, and uses the machine learning framework Light GBM to establish a multi classification model to complete the analysis of unknown APT attack organizations. Through the study of multi-dimensional analysis of multi-source threat intelligence, attack organization correlation and judgment, an attack organization correlation and judgment system has been designed and implemented. The system includes six modules: threat intelligence collection module, threat intelligence multi-dimensional analysis module, attack organization fingerprint library module, attack organization correlation module, attack organization analysis module, and user module, providing attack organization correlation and judgment services for network security. The test results show that the intelligence reading and search query function can achieve the reading of various information of attack organizations, and achieve visual display of threat intelligence. The intelligence management function can achieve operations such as adding, deleting, and updating intelligence. The user management function of the system can achieve the management of administrator users and ordinary users. After testing, all functions of the system have been implemented and meet expectations.
Application of Intelligent Algorithms and Big Data Analysis in Film and Television Creation
Authors: Wu Weiwei
Published: April 2024

With the rapid development of social media, people can access a large amount of data in a short period of time, and big data technology has emerged. With the vigorous development of cloud computing and big data, the method of mining audience interests through a large amount of data to guide film and television creation has attracted more and more attention from experts and scholars. In order to understand the current situation of film and television drama creation in China and provide suggestions for the shortcomings in the industry, this article mainly analyzes the application of intelligent algorithms for traffic prediction models and big data analysis in film and television creation. This intelligent algorithm can predict the potential audience of movies or TV dramas, helping producers and investors make decisions. This system utilizes artificial intelligence technology to select suitable actors for characters based on their matching degree and past work performance. This article applies intelligent algorithms to big data processing to improve the accuracy of data processing. This article explores the application of intelligent algorithms and big data analysis in film and television creation. Using machine learning algorithms to predict the potential audience of a movie or TV series based on historical data, providing decision-making basis for investors and producers. This system utilizes AI technology to select suitable actors for characters based on their matching degree with characters and past work performance, improving the scientific and accurate selection of roles. The application of these technologies helps to improve production efficiency and quality, reduce costs and risks, and inject new impetus into the sustainable development of the film and television industry.
Concept and Application of Industrial Heritage Planning Decision in Big Data Era
Authors: Han Xiaojuan , Zhu Xuange , Xie Min , Che Hui
Published: April 2024

With the rapid development of big data technology, more and more fields are realizing the importance of big data and applying it to various decision-making processes. Industrial heritage planning decisions are no exception. This article will explore the concept and application of industrial heritage planning and decision-making in the era of big data, aiming to emphasize the importance and application value of big data in industrial heritage planning and decision-making. This article analyzes the development relationship between the construction and transformation of urban industrial utilization and the theory and practice of industrial heritage. Through theoretical and practical technical analysis of specific regions, the value utilization of industrial simulation design has been improved. Through in-depth data mining, the government found that the industrial structure of the region is dominated by traditional manufacturing, lacking support from high-tech industries, and the pollution problem of the surrounding environment is also relatively serious. In response to these issues, corresponding planning plans have been formulated, including measures to introduce high-tech industries, optimize industrial structure, and improve environmental quality. By implementing these measures, the comprehensive strength of the region has been significantly improved and the economic transformation and upgrading have been successfully achieved.
SCHeMoS -- Smart Cow Health Monitoring System: An IoT based Cow Hoof Detection and Healthcare Alert System by Using LSTM Network
Authors: K Durairaj , V Dhilip Kumar , G.R. Kanagachidambaresan
Published: April 2024

Human life and existence are intertwined with a few domestic animals. One of the most important animals of this kind is the cow. Cows play a vital role in daily activities. Most of the people in India consume cow’s milk as one of their major nutrients. Monitoring the health of a cow’s everyday life is quite challenging. After infertility and mastitis, lameness is typically ranked as the third most economically significant health issue in dairy herds.Lameness are caused due to genetics, lack in nutrition i.e. a diet deficient in essential nutrients such as biotin, which can lead to hoof problems. Due to geographical environments like cows kept in wet, muddy conditions are more likely to develop hoof problems. This investigation analyses the typical characteristics of cow behavior, and a Smart Cow Health Monitoring System (ScHeMoS) using IoT is proposed to identify the cow’s health through the data obtained from Internet of Things (IoT) sensors, including position, body temperature, stability, acceleration, and animal feed. IoT is combined with Deep learning (DL) technique to monitor and diagnose animal health. We used the Long Short Term Memory (LSTM) network to predict cow lameness by capturing the body temperature and other parameters, which will aid in predicting their illness. The accelerometer values are stored so that it will further help to determine which cow is lame and which is pregnant or regular and could be intimated to the care takers in the farms. We utilised a self collected dataset to perform the investigation. By implementing this system, we achieved 92.45\% accuracy and 0.92 as F1 score.
Peculiarities of studying the experience of guilt among convicts in a correctional institution
Authors: Malyshev Konstantin , Nasonov Alexey , Lebedeva Maria
Published: April 2024

This article presents the features of studying the experience of guilt in convicts in a correctional institution. The recognition of guilt by convicts is a special criterion for the correction of convicts. The article presents an empirical study conducted on the subject under study. Theoretical and methodological approaches studying guilt as a psychological characteristic are reflected, as well as the complexity of ongoing research on this topic has been noted more than once. Thus, researchers in the field of penitentiary sciences pay attention to the peculiarities of the experience of guilt by convicts in places of deprivation of liberty. The relevance of the study is confirmed by the low level of study of the phenomenon of guilt experience by convicts in a correctional institution. For an empirical study, the goal was defined: to study the characteristics of the experience of guilt in convicts held in places of deprivation of liberty. The object of the study is the feeling of guilt itself. The subject of the study was the peculiarities of the experience of guilt by convicts in a correctional institution. The hypothesis of the study was determined in such a way that the guilt of repeat offenders is less pronounced than that of those who committed a crime for the first time. The study sample consisted of 60 male convicts aged 30 to 60 years, who were divided into 2 experimental groups, taking into account the recurrence of crimes. Diagnostic tools have identified the following methods: the method "Measuring feelings of guilt and shame" (Test of Self-Conscious Affect - TOSCA) (Tangney J.P.) (J. P. Tangney) TOSCA and the test "Measuring maladaptive guilt" (IGQ), developed by American psychologists (O'Connor et al.) in adaptation of E. V. Korotkova. The conducted research allowed us to identify a number of patterns and features. According to the results of the study, some practical recommendations were given to employees of the psychological services of the correctional institution on the organization of preventive, educational and psychocorrective effects on the personality of convicts from their stay in the quarantine department. It is especially important to carry out appropriate work to train convicts of a correctional institution in socially acceptable communication skills, the adoption of an appropriate socially approved lifestyle that will help them adapt to later life after release and cope with the experience of guilt at the present moment.
Features of volitional regulation of behavior in convicted women with drug addiction
Authors: Smirnova Valeria , Butov Vladimir , Sumina Ekaterina
Published: April 2024

The article presents a study of the features of volitional self-regulation of convicted women with drug addiction in conditions of social isolation. The purpose of the study was to study the characteristics of volitional regulation of convicted women with drug addiction. The subject of the study is the peculiarities of volitional regulation of convicted women with drug addiction. The hypothesis of the study is the assumption that the volitional regulation of convicted women with drug addiction differs from the volitional regulation of convicted women who do not have drug addiction. The study was carried out using the following diagnostic tools:

– a methodology for studying stylistic self-regulation of behavior (SSP) aimed at the emotional-volitional sphere;

– the methodology for studying volitional regulation (VVR) is aimed at studying the emotional-volitional and motivational-need spheres of the individual;

– the “Volitional Personality Qualities Questionnaire” (VQL) technique designed to assess the volitional qualities of an individual.

60 respondents took part in the study. The subjects were divided into two groups. 30 convicted women with drug addiction were selected for the experimental group. The control group consisted of 30 convicted women who did not have drug addiction.

The results obtained during the study indicate that convicted women with drug addiction are extremely dependent on the opinions and assessments of others, are unable to independently develop plans and programs of action, and often and uncritically follow other people’s advice. In the absence of outside help, they inevitably experience regulatory failures. The stylistic features of self-regulation of activity reveal uncertainty in a rapidly changing environment; they have great difficulty getting used to changes in life and are extremely dependent on the opinions and assessments of others. They also have a reduced ability to consciously overcome obstacles on the path to their goals and conflict-free behavior; they are characterized by low initiative, independence, suggestibility, and dependence on the opinions of groups.
Life successfulness of the personality of employees of the internal affairs bodies of the Russian Federation: conceptual justification and structural and functional organization
Authors: Semenova Natalya
Published: April 2024

The article is devoted to the theoretical and methodological substantiation of the content and functioning of an individual’s life successfulness as a meta-resource that performs an acceptor function, which consists in anticipating and assessing the results of subjective activity in the process of reflection by the subject of his own goals, values and meanings, taking into account integrative qualities and emotional experiences in the “goal” space. value-meaning." The work substantiates the significance of this meta-resource for the personality of employees of internal affairs bodies and indicates its predictive role in relation to indicators of professional success.

The data from a theoretical analysis of life successfulness as a meta-resource of the individual are summarized, taking into account the philosophical and socio-philosophical contexts, as well as the leading directions of modern psychology. The main structural elements are identified and their functioning is explained from the perspective of integrating the principles of resource, regulatory and subjective approaches and the theory of functional systems. Attention is paid to the relationship between conscious self-regulation and personal resources, and their intersecting functioning is explained. The postulate of the theory of functional systems about understanding the acceptor is extrapolated to the psychological context, in particular when justifying the meaning and functions of life successfulness as a meta-resource of the individual.

Life successfulness as a meta-resource function in the space of goals, values and meanings of the individual, through the interconnection of reflexive-technological, reflexive-axiological, reflexive-ontological mechanisms; instrumental, socio-psychological and dispositional qualities of the individual; practical, moral and existential emotional experiences.

The prospects for further development of the meta-resource concept of life successfulness are outlined.
Der Menschen „Beruf zum freien Denken“. Zum Begriff „Aufklärung“ in der Königsberger Kultur
Authors: Dietzsch Steffen
Published: April 2024

Kant does not understand enlightenment primarily as producing and disseminating knowledge, technology and good morals. Instead, he draws attention to people’s operational powers, which, as subjective abilities, are the reason for the objective improvement of human life and its environment. – The central categories of the Königsberg Enlightenment are “thinking for yourself”, “freedom of thought,” and “criticism of guardianship and immaturity".