bluuebunny/crossref_metadata_2025 huggingface dataset:
Increased Likelihood of Dementia with Coexisting Atrophy of Multiple Regions of Interest
Authors: Kim Regina E.Y. , Lee Minho , Kang Dong Woo , Wang Sheng-Min , Kim Donghyeon , Lim Hyun Kook
Published: December 2023

Background: Brain volume is associated with cognitive decline in later life, and cortical brain atrophy exceeding the normal range is related to inferior cognitive and behavioral outcomes in later life. Objective: To investigate the likelihood of cognitive decline, mild cognitive impairment (MCI), or dementia, when regional atrophy is present in participants’ magnetic resonance imaging (MRI). Methods: Multi-center MRI data of 2,545 adults were utilized to measure regional volumes using NEUROPHET AQUA. Four lobes (frontal, parietal, temporal, and occipital), four Alzheimer’s disease-related regions (entorhinal, fusiform, inferior temporal, and middle temporal area), and the hippocampus in the left and right hemispheres were measured and analyzed. The presence of regional atrophy from brain MRI was defined as ≤1.5 standard deviation (SD) compared to the age- and sex-matched cognitively normal population. The risk ratio for cognitive decline was investigated for participants with regional atrophy in contrast to those without regional atrophy. Results: The risk ratio for cognitive decline was significantly higher when hippocampal atrophy was present (MCI, 1.84, p < 0.001; dementia, 4.17, p < 0.001). Additionally, participants with joint atrophy in multiple regions showed a higher risk ratio for dementia, e.g., 9.6 risk ratio (95% confidence interval, 8.0–11.5), with atrophy identified in the frontal, temporal, and hippocampal gray matter, than those without atrophy. Conclusions: Our study showed that individuals with multiple regional atrophy (either lobar or AD-specific regions) have a higher likelihood of developing dementia compared to the age- and sex-matched population without atrophy. Thus, further consideration is needed when assessing MRI findings.
Association Between Urinary Glyphosate Exposure and Cognitive Impairment in Older Adults from NHANES 2013-2014
Authors: Ren Jiawen , Yu Yongquan , Wang Yucheng , Dong Yu , Shen Xiaobing
Published: December 2023

Background: Glyphosate is the most commonly used herbicide with potential neurotoxicity. However, limited epidemical evidence is found in the relationship between glyphosate and cognitive impairment, especially in the cognitive-disrupting sensitive elderly populations. Objective: This study aimed to examine the association of urinary glyphosate exposure with cognitive impairment in the United State (US) older adults. Methods: Cognitive impairment was determined by the following four tests: the Consortium to Establish a Registry for Alzheimer’s disease (CERAD) Immediate Recall test (IR), the CERAD Delayed Recall tests (DR), the Animal Fluency (AF) test and the Digit Substitution test (DSST). Survey weighted logistic regression and restricted cubic splines were applied to evaluate and visualize the association between glyphosate and cognitive impairment. Results: A total of 465 elderly adults were identified in the National Health and Nutrition Examination Survey (NHANES) 2013-2014 cycle, and among them, 83.87% individuals had detectable urinary levels of glyphosate (0.628 ng/mL in average). After adjusting for the potential covariates, glyphosate was significantly linked to increased DR and AF impairment, and the corresponding ORs were 1.52 (1.01 to 2.30, p = 0.049) and 1.69 (1.11 to 2.59, p = 0.019), respectively. No significant association was identified between glyphosate and IR or DSST impairment. The RCS plot further confirmed the linear and positive relationships between glyphosate and DR and AF impairment. Conclusions: These findings suggested that exposure to glyphosate might be associated with declined cognitive function in the elderly, and it might be prudent to evaluate cognitive outcomes for aged individuals with glyphosate exposures.
Empirical analysis of the factors of the green innovation performance of industrial enterprises based on DEMATEL method and factor analysis method
Authors: Li Yafeng , He Yao , Yang Wei , Yu Xintao
Published: December 2023

This study investigated factors of the green innovation performance of industrial enterprises in 30 provinces and autonomous regions across China. This study used literature analysis and DEMATEL method to identify the factors of green innovation performance of industrial enterprises. A green innovation performance evaluation index system was then constructed, and a mathematical model was established using factor analysis method to empirically analyze the factors of green innovation performance of industrial enterprises across 30 provinces and autonomous regions in China from 2012 to 2016. The results show that green innovation strength, technological development level, energy consumption, and environmental protection are the three factors of green innovation performance. Firstly, the influence of innovation strength on comprehensive green innovation performance has the largest weight, meaning that it has the largest impact on comprehensive green innovation performance. Secondly, the influence of the level of scientific and technological development on the comprehensive green innovation performance is weaker. Thirdly, the main influencing factor is the level of energy consumption and environmental protection. Finally, based on the empirical analysis, it is suggested that industrial enterprises should increase investment in green innovation, developing science and technology, and improving ecological environment, so as to enhance the green innovation performance of industrial enterprises.
Cost control problems and countermeasures of e-commerce enterprises under the background of big data and Internet of Things
Authors: Wang Jing
Published: December 2023

The scale of e-commerce in China continues to expand, and it has a relatively good development prospect. However, there are many problems in cost control in the development of e-commerce in our country. E-commerce companies have many problems in terms of promotion costs, warehousing costs, and operating costs. Although predecessors have made great achievements in this field and helped e-commerce companies solve problems related to cost control, there are still many problems in e-commerce companies. Question. This article starts with big data and Internet of Things technology, and focuses on storage costs and transportation costs to solve the problems of cost control in e-commerce companies. The problems existing in the development of e-commerce enterprises are: (1) The cost control system is not mature enough, the business scope is not clear, the cost control lacks innovative awareness, the logistics cost remains high, and the logistics management model is unreasonable. In order to solve these problems, we built a transportation cost optimization model and an operation cost optimization model based on big data and Internet of Things technology. Transportation cost and operation cost are two important components of the cost of e-commerce enterprises in my country. The model has been verified to effectively reduce transportation costs and operating costs, which is of great significance to reducing the cost of e-commerce enterprises in my country, can solve the problems of e-commerce enterprise development, and promote the development of e-commerce in my country. Finally, according to the model constructed by the questionnaire survey and the article, we put forward corresponding suggestions (1) optimize customer relationship, improve the enterprise model (2) promote enterprise innovation, and promote the transformation of marketing costs (3) improve the degree of informatization of e-commerce enterprises.
Diversification of residents’ consumption structure based on ELES model
Authors: Feng Peichun
Published: December 2023

Based on the data of urban residents’ consumption in Jiangsu Province, this paper looks for the Statistical Yearbook of Jiangsu Province from Jiangsu Statistics Bureau, collects the required data of residents’ consumption structure, and defines the components of residents’ consumption structure in Jiangsu Province from eight aspects: clothing, food, housing, transportation and communication, medical care, culture, education, entertainment and other miscellaneous commodities. First, make a systematic theoretical explanation of these eight factors, so as to help us better understand how these eight factors are pieced together into a whole of residents’ consumption structure. Then it analyzes the present situation of consumption structure. Secondly, based on the relevant theories of residents’ consumption structure, in order to know the changes of the components of residents’ consumption structure in Jiangsu Province over the years, this paper analyzes the relevant data of the collected structural factors by using factor analysis and ELES model, based on the data from 2009 to 2018. In the last part, according to the previous analysis results, the characteristics of urban residents’ consumption structure in Jiangsu Province are summarized, and some suggestions and opinions are given. Finally, the future consumption structure is predicted according to the historical data, and some suggestions are given.
A predictive model: A study of employment factors for fresh college graduates
Authors: Li Li
Published: December 2023

The employment situation of fresh college graduates is affected by many factors. In this paper, on the basis of decision tree, the C4.5 method was used to analyze the employment factors of fresh college graduates. An improved C4.5 model was designed by simplifying the calculation formula of the C4.5 method and combining the error tolerance. Experiments were performed on the actual data of fresh college graduates. The results found that the practice level had a great impact on the employment of fresh college graduates, so the training of the practice level should be focused on before graduation. The results of the prediction models showed that the improved C4.5 method had a smaller training error than ID3 and C4.5 methods, a significantly higher prediction accuracy (88.39%), higher precision, recall rate, and F1 value, and a shorter running time (1.642 s); the improved model remained a high accuracy even when the data volume increased. The experimental results verify the reliability of the improved C4.5 model in predicting the employment situation of fresh college graduates. The model can be applied in actual employment guidance.
A comprehensive evaluation method of heat source tower heat pump applicability considering regional climate differences
Authors: Chen Hongyin , Wang Songcen , Zhong Ming , Jin Lu , Jia Xiaoqiang , Guo Yi , Zhang Xinhe , Huang Wei
Published: December 2023

The heat source tower heat pump system is widely used in large and medium-sized air conditioning systems due to its good energy-saving advantages. However, there is no relatively reasonable evaluation system for the applicability of heat source tower heat pumps due to significant regional climate differences. Therefore, in order to better comprehensively evaluate the applicability of the heat source tower heat pump system, a comprehensive evaluation index system for the applicability of the heat source tower heat pump system was first constructed. On the basis of this evaluation index, an applicability evaluation model based on backpropagation neural network is constructed. In response to the slow convergence speed and susceptibility to local values in the application process of this evaluation model, particle swarm optimization algorithm is used to improve it. A comprehensive evaluation model for the applicability of heat source tower heat pumps based on improved backpropagation neural networks has been constructed. For the evaluation model constructed in the study, experimental data from four different regions were selected for validation. The experimental results show that in the training set, the F-Measure value of the evaluation model reaches 0.949, and in the test set, the F-Measure value of the model reaches 0.973. The comprehensive evaluation data from four regions indicate that the heat source tower heat pump system can achieve different heating and cooling effects in different regions. This indicates that the proposed comprehensive evaluation model for the applicability of heat source tower heat pumps based on this improved method has good evaluation results. It can conduct a good analysis of the applicability of the heat source tower heat pump system, providing effective support for developing reasonable and energy-saving refrigeration and heating methods in different regions.
Mathematical formula information retrieval system
Authors: Hou Yong
Published: December 2023

Design and implementation of the system for retrieving information about mathematical formulas – MFIRS. The structure of the system is mainly divided into the modules: input normalization, mathematical formula unification, mathematical formula encoding, text information feature extraction, mathematical formula feature extraction, mathematical formula indexing, retrieval and ranking. A method for extracting mathematical formulas and keywords based on FastText word embedding technology is proposed. This method can be used not only to get the structural features of the formula, but also to facilitate the calculation of the similarity of the formula by the vector result. At the same time, the model introduces the semantic features of context-rich mathematical formulas to improve the domain correlation of search results. The MathRetEval dataset was created based on about 7.9 × 105 arXiv documents and about 1.5 × 108 mathematical formulas. The scalability of the system is verified using this data set. The mathematical formulas can be written in the language TEX or MathML. When queried in the TEX language, it can be converted to a tree representation of the MathML representation and then indexed. This MFIRS is an information retrieval system for mathematical formulas with the features of mathematical perception, which can use the search for the similarity of partial formulas.
Application research of BP neural network PID in control system of heat exchange station
Authors: Liu Chunlei , Zhang Mengru , Zhen Wenshuang , Wang Peng , Ding Yibo , Cai Yang , Sun Yong
Published: December 2023

In the direction of better resolution of time lag, nonlinearity and uncertainty in the heating system, a BPNN-PID (BP neural network PID) controller is proposed in this paper. A complete heating auto-control system is designed with the experimental platform of a university heat exchange station in Zhangjiakou as the research background. The auto-control system takes Programmable Logic Controller (PLC) as the control core, uses BPNN algorithm to optimize the PID control parameters, and finally takes outlet temperature of 1# plate exchanger as the main control parameter to conduct experimental research on BPNN-PID control and single-loop feedback control respectively. The results show that compared with the single-loop feedback controller, the PID control based on BPNN algorithm has superior control quality, with shorter adjustment time, smaller overshoot, finer control accuracy and stability.
A signal processing method for continuous mud pressure wave signals in logging-while-drilling systems
Authors: Liang Yao , Du Guanghong , Li Anzong , Chen Wenhui , Li Xiaojun , Guo Yixiao , Li Zhiguang
Published: December 2023

For signal transmission of mud pressure waves in logging-while-drilling systems, as more measurement parameters are adopted, the conventional signal transmission rate of approximately 1 bps cannot meet the requirements of parameter uploading. Transmission rates greater than 10 bps are widely used by current Chinese and international enterprises in their continuous wave transmission systems. Due to the increasing transmission rates, a conventional single-channel pressure sensor cannot effectively identify the key features of an original signal with a low signal-to-noise ratio at a high transmission rate. This issue results in a low success rate for pressure wave recognition and decoding. This paper addresses a method for the collection of pressure wave signals using multi-channel pressure sensors through the analysis of the signal transmission changes of mud pressure waves with well depths and echo interference caused by drilling rod reflection. In this research, numerical simulation and experimental verification were used to calculate the cross-correlations of the multi-channel signals to effectively remove interference noises such as reflective waves and improve the signal-to-noise ratio of the original signal. The results showed that this method could effectively improve the SNR after the wave filtering of the original pressure wave. The characteristics of the continuous mud pressure wave signals were analysed using a circulation test. A corresponding band-pass filter was designed to remove pump noises to restore the sinusoidal pressure wave signal required by the original transmission rules.
The simulation design of smart home system based on Internet of Things
Authors: Cui Jiantao , Du Zhongzhou , Liu Kejian , Cao Junpeng
Published: December 2023

With the upgrading of the traditional home industry, the deep integration of home design and Internet of Things technology is the development direction of modern smart home design, and it creates a comfortable, energy-saving and safe working and living environment for people. This paper designs an application scenario of the Internet of Things in smart home design, integrates smart home, Internet, Internet of Things and other technologies, designs the overall architecture, topology and IP address allocation scheme of the system, and realizes the intelligent door control and temperature control system of smart home based on the simulation platform. The whole network is connected to ISP Internet through home gateway and mobile data. After testing, the system runs stably as a whole, thus providing a solution for the application of the Internet of Things in smart home.
Optimization path of carbon offsetting in negative urban spaces under dual carbon goals
Authors: Jiao Hong , Bao Lei
Published: December 2023

Using population geographic data to analyze the dynamics of the central urban to explore the negative space and implement green carbon offset retrofits is beneficial for the Dual Carbon goals. We construct a grading system of urban vitality values with ArcGIS to assess the vitality of city blocks and screen out negative spaces. Taking the central urban of Anda as an example, we found that the vitality values along the main road in Anda were high. In contrast, the vitality values of residential sites in the southern and western parts were generally low. By analyzing the distribution of negative space in Anda, we finally recommend that Anda adopt the strategy of “fertile land creation” for the western part, to practice the planning of urban green space projects with joint investment of factories in the southern part, to optimize the low-carbon urban travel space, to implement the green transformation of small negative urban spaces, and to enhance the ecological construction of existing parks and green spaces. We extracted the negative urban spaces and explored the paths and implementability of the carbon offsetting renewal strategies intending to provide some reference for realizing Dual Carbon goals and transforming negative urban spaces in China.
Construction of a dynamic network for retinal vessel segmentation based on computer vision
Authors: Zhang Runze
Published: December 2023

This paper is focused on the field of computer vision in order to investigate the presentation properties of retinal blood vessels. Combining the structure of convolutional neural networks, activation functions, and common metrics in semantic segmentation, a dynamic network model for retinal vessel segmentation based on computer vision is constructed. The purpose of this paper is to discuss the results of retinal vascular segmentation based on computer vision. The image connection and alignment pattern selection process is also established to match retinal vessel images by computer vision. The performance of the dynamic network constructed here and the results of retinal vessel segmentation were then analyzed in three publicly available datasets, DRIVE (digital retinal images for vessel extraction), CHASE_DB1, and STARE (structured snalysis of the retinal. The ROC (retinopathy online challenge) curves on all three datasets exceeded 0.9, showing high performance, and the area under the PR curve exceeded 0.88. The accuracy of the results for retinal vessel segmentation was around 96%. Based on the semantic segmentation direction in the field of computer vision in this study, the dynamic network for retinal vessel segmentation can be well constructed.
Research of immune clone algorithm applying in the LED lamp automatic lock screw workstation
Authors: Ding Dukun , Deng Jianxin , Ye Hui
Published: December 2023

A new automatic lock screw machine for LED lamp has been researched in the paper, which is based on the immune clone algorithm. Firstly, the robot automatic lock screw system has been setup. Vision sensor captured LED lampshade images in real-time. Median filtering operation has been performed to the captured images. On this basis, a new image segmentation method based on the immune clone algorithm has been researched. The antibody and antigen of LED lampshade image have been defined. The immune affinity function has been setup at the same time. Several artificial immune operators have been designed, which can be used to obtain the optimum image segmentation threshold value in real time. The final results showed that the optimum image threshold value can been obtained after less than ten times iterative computation. Compared with the traditional Ostu method, the new method can reduce the disturbance information around the threaded hole, which made basis for threaded hole recognition and location.
RETRACTED: Advancing disease identification in fava bean crops: A novel deep learning solution integrating YOLO-NAS for precise rust
Authors: Slimani Hicham , El Mhamdi Jamal , Jilbab Abdelilah
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
‘A novel TRIP4 Variant Associated with Peripheral Neuropathy: Expanding the Clinical and Genetic Spectrum of ASC1-Related Myopathy’
Authors: Frongia Ivana , Spagnoli Carlotta , Rizzi Susanna , Frattini Daniele , Leon Alberta , Caraffi Stefano Giuseppe , Pollazzon Marzia , Garavelli Livia , Pisani Francesco , Fusco Carlo
Published: December 2023

Activating Signal Cointegrator 1 complex (ASC-1 complex) is a ribonucleoprotein tetramer participating in transcriptional coactivation and RNA processing, consisting of four subunits: ASCC1-ASCC3 and ASC-1. Pathogenic variants in the TRIP4 and ASCC1 genes, encoding the ASC-1 and ASCC1 subunits, were recently described in congenital myopathic conditions without signs of motor neuron involvement, and Spinal Muscular Atrophy-like (SMA-like) phenotype with prenatal bone fractures. We present a novel pathogenic TRIP4 variant in two siblings with severe phenotype and mixed sensory-motor polyneuropathy. The reviewed phenotypic spectrum is broad, but sensory-motor polyneuropathy is so-far unreported. We thus expand ASC-1 related myopathy phenotype.
Prevalence of Concomitant Pathologies in Parkinson’s Disease: Implications for Prognosis, Diagnosis, and Insights into Common Pathogenic Mechanisms
Authors: Walker Lauren , Attems Johannes
Published: December 2023

Pathologies characteristic of Alzheimer’s disease (i.e., hyperphosphorylated tau and amyloid-β (Aβ) plaques), cardiovascular disease, and limbic predominant TDP-43 encephalopathy (LATE) often co-exist in patients with Parkinson’s disease (PD), in addition to Lewy body pathology (α-synuclein). Numerous studies point to a putative synergistic relationship between hyperphosphorylation tau, Aβ, cardiovascular lesions, and TDP-43 with α-synuclein, which may alter the stereotypical pattern of pathological progression and accelerate cognitive decline. Here we discuss the prevalence and relationships between common concomitant pathologies observed in PD. In addition, we highlight shared genetic risk factors and developing biomarkers that may provide better diagnostic accuracy for patients with PD that have co-existing pathologies. The tremendous heterogeneity observed across the PD spectrum is most likely caused by the complex interplay between pathogenic, genetic, and environmental factors, and increasing our understanding of how these relate to idiopathic PD will drive research into finding accurate diagnostic tools and disease modifying therapies.
Understanding the Role of CDH4 in Multiple System Atrophy Brain
Authors: Isik Finula I. , Katzeff Jared S. , Fu YuHong , Kim Woojin Scott
Published: December 2023

Background:

Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disease clinically characterized by parkinsonism, cerebellar ataxia, and autonomic dysfunction. A major pathological feature of MSA is the presence of α-synuclein aggregates in oligodendrocytes, the myelinating cells of the central nervous system. A genome-wide association study revealed that the CDH4 gene is associated with MSA. However, virtually nothing is known about the role of CDH4 in the context of MSA.

Objective:

Our aim was to compare the expression of CDH4 between MSA and control brains, and to investigate its relationship with α-synuclein in oligodendrocytes.

Methods:

RNA and protein were prepared from putamen, motor cortex white matter, cerebellum, and superior occipital cortex tissues collected from MSA ( N = 11) and control ( N = 13) brains. The expression of CDH4 was measured at mRNA and protein levels by qPCR and western blotting. Oligodendrocyte cells were cultured on plates and transfected with CDH4 cDNA and its impact on α-synuclein was analyzed.

Results:

Firstly, we found that CDH4 in MSA brain was significantly elevated in the disease-affected motor cortex white matter in MSA ( N = 11) compared to controls ( N = 13) and unaltered in the disease-unaffected superior occipital cortex. Secondly, we determined that increases in CDH4 expression caused changes in the cellular levels of α-synuclein in oligodendrocytes.

Conclusions:

When put together, these results provide evidence that support the GWAS association of CDH4 with MSA.
Tests for skewness parameter of skew log Laplace distribution
Authors: Khandeparkar Pradnya , Dixit Vaijayanti
Published: December 2023

Laplace probability density function with additional shape parameter that regulates the degree of skewness is a skew Laplace distribution. The various forms of skew Laplace distribution are found in the literature, the distributions defined by Mc Gill (1962), Holla and Bhattacharya (1968), Lingappaiah (1988), Fernandez and Steel (1998). The skew log Laplace distribution is the probability distribution of a random variable whose logarithm follows a skew Laplace distribution. In this paper, the classical optimum tests for skewness parameter of skew log Laplace distribution (SLLD) derived from Lingappaiah (1988) distribution are discussed. Uniformly most powerful test, uniformly most powerful unbiased test and Wald’s sequential probability ratio test for skewness parameter are compared. The exact likelihood ratio test and Neyman structure test for testing skewness parameter when scale parameter is known are derived. Finally, the underreported income of Road Transport Company is analysed on the basis of the tests derived in this paper.
Exact higher-order moments for linear non-homogeneous stochastic differential equation
Authors: Guidoum Arsalane Chouaib , Boukhetala Kamal
Published: December 2023

This paper investigates the moments of a stochastic process that satisfies the one-dimensional linear stochastic differential equation (SDE) with nonlinear time-dependent drift and diffusion coefficients. The goal is to derive formulas for the nth exact moment, that instead of seeking the transition density function by solving the Fokker-Plank equations or moment-generating functions, which can be difficult to solve in closed form. We will appropriately apply Itô’s formula and the properties of the Wiener process with a constant drift and diffusion term, which is a Gaussian process to obtain the exact higher-order moments.
Bayesian inference of financial networks
Authors: Sosa Juan , Betancourt Brenda
Published: December 2023

Network data arises naturally in a wide variety of applications in different fields. In this article we discuss in detail the statistical modeling of financial networks. The structure of such networks red has not been studied thoroughly in the past, mainly due to limited accessible data. We explore the structure of a real trading network corresponding to transactions within the natural gas future market over a four-year period. The detection of meaningful communities of actors within networks is particularly relevant to understand the topology of a complex system like this. We explore the usage of stochastic block models in conjunction with a nonparametric Bayesian approach in order to identify clusters of traders in a flexible modeling framework. Our findings strongly indicate that the proposed models are highly reliable at detecting community structures.
An evolutionary mechanism of social preference for knowledge sharing in crowdsourcing communities
Authors: Meng Jianfeng , Zhang Gongpeng , Li Zihan , Yang Hongji
Published: December 2023

Crowdsourcing community, as an important way for enterprises to obtain external public innovative knowledge in the era of the Internet and the rise of users, has a very broad application prospect and research value. However, the influence of social preference is seldom considered in the promotion of knowledge sharing in crowdsourcing communities. Therefore, on the basis of complex network evolutionary game theory and social preference theory, an evolutionary game model of knowledge sharing among crowdsourcing community users based on the characteristics of small world network structure is constructed. Through Matlab programming, the evolution and dynamic equilibrium of knowledge sharing among crowdsourcing community users on this network structure are simulated, and the experimental results without considering social preference and social preference are compared and analysed, and it is found that social preference can significantly promote the evolution of knowledge sharing in crowdsourcing communities. This research expands the research scope of the combination and application of complex network games and other disciplines, enriches the theoretical perspective of knowledge sharing research in crowdsourcing communities, and has a strong guiding significance for promoting knowledge sharing in crowdsourcing communities.
Hybrid trust-based optimized virtual machine migration for dynamic load balancing and replica management in heterogeneous cloud
Authors: Nebagiri Manjula Hulagappa , Hanumanthappa Latha Pillappa
Published: December 2023

Cloud computing is an upcoming technology that has garnered interest from academic as well as commercial domains. Cloud offers the advantage of providing huge computing capability as well as resources that are positioned at multiple locations irrespective of time or location of the user. Cloud utilizes the concept of virtualization to dispatch the multiple tasks encountered simultaneously to the server. However, allocation of tasks to the heterogeneous servers requires that the load is balanced among the servers. To address this issue, a trust based dynamic load balancing algorithm in distributed file system is proposed. Load balancing is performed by predicting the loads in the physical machine with the help of the Rider optimization algorithm-based Neural Network (RideNN). Further, load balancing is carried out using the proposed Fractional Social Deer Optimization (FSDO) algorithm, where the virtual machine migration is performed based on the load condition in the physical machine. Later, replica management is accomplished for managing the replica in distributed file system with the help of the devised FSDO algorithm. Moreover, the proposed FSDO based dynamic load balancing algorithm is evaluated for its performance based on parameters, like predicted load, prediction error, trust, cost and energy consumption with values 0.051, 0.723, 0.390 and 0.431J correspondingly.
Assessment of Serum Urea and Creatinine Levels in Diabetic Patients
Authors: Ullah Wahid , Nazir Azhar , Israr Hasnain , Hussain Shahid , Farooq Muhammad
Published: December 2023

Diabetic nephropathy is the leading cause of renal morbidity which occurs when chronic diabetes destroys the filtering system of the kidneys. Serum urea and creatinine are widely used as renal function test parameters. This study aims to assess the level of serum urea and creatinine in diabetic patients and their relationship with each other. The study was conducted in Ayub Teaching Hospital from September 15 to December 20, 2019. A total of 176 samples from confirmed diabetic patients were analyzed including 85 female and 91 male patients. Also, 83 control samples were taken for this study. Serum urea and creatinine levels were assessed to evaluate diabetic nephropathy in diabetic patients. SPSS (version 23) was used for statistical analysis. Pearson correlation analysis was used to check the relationship of blood sugar level, creatinine, and urea. Descriptive statistics (mean ± SD) were measured for the continuous variable. Scatter plot diagrams were added for the easy visualization and interpretation of the data. The significant level was set at p < 0.05. Out of the 176 diabetic samples, 32 had abnormally high serum creatinine and 66 had abnormal serum urea. In controls, one individual had high creatinine and three individuals had high serum urea. A significant increase in both urea and creatinine levels was observed in diabetic samples. Both serum urea and creatinine showed a strong positive correlation with the level of glucose and remained statistically significant (p < 0.01). Similarly, blood glucose level showed a strong correlation with the renal function test parameters. Hence, it was concluded that serum urea and creatinine are important parameters to assess kidney function in diabetes mellitus.
A Metaphoric Exploration of Objective Constructivism
Authors: Oldenburg Reinhard
Published: December 2023

The dichotomy between constructive and objective accounts of the epistemic process is a persistent problem. This paper describes the theory of reconstruction in quantum physics that may give a metaphor for the possible compatibility of constructivist and realist accounts. The argument works by analog reasoning and suggests that local subjective and global objective descriptions may converge.
Exploring Historical and Contemporary Academic Disparities: A Comparative Study of Black and Non-Black Nova Scotians
Authors: Fuerst John , Hu Meng
Published: December 2023

In Canada, concerns persist regarding the academic underperformance among historically marginalized racial and ethnic groups. Extensive research has been conducted on the academic achievements of Aboriginal communities, but there’s a noticeable lack of focus on longstanding Afro-descendant populations. Our study aims to address this gap by examining discrepancies in numeracy and overall academic performance, particularly between Black and non-Black residents of Nova Scotia. Utilizing historical census data, we identified a small-to-medium sizes numeracy gap between European and African Nova Scotians, measuring about one-third of a standard deviation, prevalent in the late 19th and early 20th centuries. Furthermore, contemporary data from the 21st century reveals a gap in academic and cognitive test scores between African and other Nova Scotians of approximately half a standard deviation. We analyze these findings in the context of existing research on racial and ethnic academic disparities in the Americas.
The Evolution of Consciousness Theories
Authors: Farhadi Ashkan
Published: December 2023

Consciousness is usually perceived as a state of being aware of one’s environment as well as self. Despite its omnipresence in our life, understanding this concept is challenging. This has given rise to several theories attempting to explain the nature of consciousness, as well as hard and soft problems of consciousness. In fact, the boundaries of consciousness defined by these theories are a topic of continued discussion, particularly in light of the recent advances in artificial intelligence (AI). Some of these theories consider consciousness as a simple integration of information while others purport the need for an agency in the process of integration for an entity to be considered conscious. Some theories consider consciousness as a graded entity and some equate consciousness with content of awareness. In this work, major theories of consciousness are reviewed and compared, focusing on awareness, attention, and sense of self. These findings are interpreted in relation to AI in order to ascertain what makes AI distinct from natural intelligence.
Incidence risk of major reproductive disorders of dairy cows and cow-level risk factors in Wolaita Sodo town, southern Ethiopia
Authors: Hirpassa Lachisa , Mekibib Berhanu , Abebe Rahmeto
Published: December 2023

Reproductive health problems directly affect the reproductive performance of dairy cows and thus reduce the productivity of a dairy herd. A prospective longitudinal study was conducted in Wolaita Sodo town between to estimate the incidence risk of major reproductive disorders in dairy cows and identify potential risk factors. A total of 140 pregnant cows were monitored regularly every two weeks until birth and during the postpartum period. Of these, 74 (52.86%) had at least one of the reproductive problems identified during the study period. The most commonly observed reproductive disorders were retained fetal membrane (RFM) (12.9%), dystocia (12.1%), abortion (10%), stillbirth (6.4%), metritis (5%), uterine prolapse (2.1%), endometritis (1.4%), vaginal prolapse (1.4%), and pyometria (1.4%) in order of decreasing incidence risk. The risk of abortion was significantly higher in Jersey Local Crossbreed (RR = 3.5), in cows kept in the semi-intensive system, in large herds (RR = 4.4) and in cows with a poor body condition score (BCS) (RR = 7.3). The risk of dystocia was significantly higher in cows with poor BCS (RR = 9.1) and in cows that gave birth to a male calf (RR = 2.6). The risk of metritis was significantly higher in cows with poor BCS (RR = 11.9) and multiparous cows (RR = 6.4). The risk of developing RFM was 9.9 times higher in cows with a poor BCS than in cows with a good BCS. In general, the most common reproductive disorders, namely RFM, dystocia and abortion, can significantly affect the subsequent uterine health and thus prolong uterine involution time in affected cows. Therefore, raising awareness among farm owners and attendants on improving dairy farming management practices such as proper feeding, considering the size of sire and dam in artificial insemination and cow health management are recommended as practical measures to minimize the occurrence of these problems and the associated economic losses on the dairy farms.
Beyond Journals and Peer Review: Towards a More Flexible Ecosystem For Scholarly Communication
Authors: Wood Michael
Published: December 2023

This article challenges the assumption that journals and peer review are necessary for developing, evaluating, and disseminating scientific and other academic knowledge. It suggests a more flexible ecosystem and examines some of the possibilities this might facilitate. The market for academic outputs should be opened up by encouraging the separation of the dissemination service from the evaluation service.  Publishing research in subject-specific journals encourages compartmentalising research into rigid categories. The dissemination of knowledge would be better served by an open access, web-based repository encompassing all disciplines, or by a number of such repositories. There would then be a role for organisations to assess the research items to help users find relevant, high-quality work. There could be a variety of such organisations which could enable reviews from peers to be supplemented with evaluation by non-peers from a variety of different perspectives: user reviews, statistical reviews, reviews from the perspective of different disciplines, and so on. This should reduce the inevitably conservative influence of relying on two or three “peers,” and make the evaluation system more critical, multi-dimensional, and responsive to the requirements of different audience groups, changing circumstances, and new ideas. Non-peer review might make it easier to challenge dominant paradigms, and expanding the potential audience beyond a narrow group of peers might encourage the criterion of simplicity to be taken more seriously - which is essential if human knowledge is to continue to progress.
Conflict Resolution Applications to Peace Studies
Authors: Saaida Mohammed
Published: December 2023

This comprehensive study explores the crucial role of mediation and negotiation in conflict resolution, meticulously analyzing their alignment with core peace studies principles. As an inescapable element of human interaction, conflict has long hindered peaceful coexistence and societal progress. This investigation meticulously dissects both the theoretical foundations and practical implications of these conflict resolution approaches, highlighting their vital role as cornerstones of peace studies. By cultivating a deep understanding of these tools, the study champions proactive conflict transcendence, aiming to cultivate sustainable, harmonious environments. To illuminate this crucial nexus, the study utilizes an all-encompassing methodology, incorporating content analysis, case study, and historical analysis. Through this comprehensive analysis, the intricate interplay between conflict resolution and peace studies is illuminated, underscoring their crucial interdependence in improving global affairs and establishing enduring tranquility.
Selection of optimal cultivation conditions to increase the antimicrobial activity of the basidial fungus Lenzites betulina
Authors:   Republican Collection of Microorganisms, Nayekova S.K. , Sarmurzina Z.S. ,   Republican Collection of Microorganisms, Salkhozhayeva G.M. ,   L.N. Gumilyov Eurasian National University, Tekebayeva Zh.B. ,   Republican Collection of Microorganisms, Mamytbekova G.K. ,   Republican Collection of Microorganisms
Published: December 2023

In recent decades, more and more attention has been paid to the study of various compounds isolated from higher basidial fungi. The analysis of the taxonomic species composition of fungi of the genus basidiomycetes causing white rot on birch is carried out. During the study of cultural - morphological and molecular - genetic properties, it was found that the culture of fungi belongs to the species Lenzites betulina. To increase the ability of the isolated fungus to synthesize antimicrobial compounds, the composition of the nutrient medium (the ratio of carbon and peptone) was modified, the optimal temperature (28 ° C) and pH medium (7.5-8.0) were selected. Antagonistic properties between the test cultures of S.marcescens, E. coli, S.aureus, C. albicans and the culture of Lenzites betulina fungi were also studied. The study showed that the greatest antibiotic effect of Lenzites betulina fungi was exerted on the culture of С.albicans yeast and E.coli bacteria. Thus, it was found that fungi of the Lenzites betulina species exhibit high bactericidal and fungicidal activity to opportunistic yeast and bacterial cultures.
Floral composition of the botanical natural monument “Kamenny lake tract” (Kostanay region)
Authors:   A. Baitursynov Kostanay Regional University, Sultangazina G.J. , Kuprijanov А.N. ,   Kuzbass Botanical Garden Federal Research Center of Coal and Coal Chemistry SB RAS
Published: December 2023

There are 15 specially protected natural areas in the Kostanay region. The total area: more than 818 ha. The state natural monument of local importance ‘Kamenny Lake tract’ floristic diversity was studied. Floristic studies were carried out by the route method in 2019–2022. The research task was to study the natural monument floristic composition, identify rare and endangered plants of the Kazakhstani Red Book. During the floristic study, five main ecotopes were identified: shrub thickets on slopes, birch forest on steep slopes, upland meadows with shrub thickets, meadow-marsh communities on coasts, and meadow-steppe communities. Protected natural area flora summary was compiled: for each species the habitat within the protected areas is indicated. In a small area (2.5 ha), 177 species of higher plants belonging to 132 genera and 48 families were found. Higher spore plants are represented by 6 species: Equisetum arvense L., E.Hyemale L., E.pratense Ehrh., Athyrium filix-femina (L.) Roth., Cystopteris fragilis (L.) Bernh., Matteuccia struthiopteris (L.) Tod, gymnosperm - Ephedra Distachia L., angiosperms: 171 species belonging to 44 families. Among them, Asteraceae - 31 species (18%), Rosaceae - 20 species (11.2%), Poaceae - 17 species (10%), Fabaceae - 10 species (6.0%), Lamiaceae - 9 species (5.1%), Caryophyllaceae - 8 species (5.0%). Three species (Adonis wolgensis, Stipa pennata and Tulipa biebersteiniana) are in the Kazakhstan Red Book (2014). The state of rare and endangered species populations is satisfactory.
Zooplankton structure and hydrochemical characteristics of mountain reservoirs of the northern Tien-Shan
Authors:   Institute of Zoology, Krupa Ye.G. , Aubakirova M.O. ,   Research and production center of fish industry, Argynbayeva Ye.M. ,   Institute of Zoology, Romanova S.M. ,   Institute of Zoology
Published: December 2023

The study of hydrochemical parameters and zooplankton structure of three mountain reservoirs of the Northern Tien Shan (Lower Kolsai Lake, Tekes and Bestyubinskoe reservoirs) was carried out in August 2022. Hydrochemical analysis showed that the water in all reservoirs is fresh, soft, carbonate class, calcium group of the second type. The average content of easily oxidizing organic substances reached 5.6–7.6 mg/dm3, nitrite nitrogen – 0.011–0.044 mg/dm3, nitrate nitrogen – 0.274–0.830, ammonium nitrogen –0.045–0.091, phosphates – 0.023–0.031, iron – 0.090–0.166, silicon – 3.0–5.4, manganese - 0.011–0.025 mg/dm3. Zooplankton was represented by 41 species. Zooplankton abundance varied between 11081-69061 ex/m3. Zooplankton biomass reached 11.7–700.2 mg/m3. Cluster analysis based on the calculation of the Bray-Curtis index showed changes in the species composition of planktonic invertebrates over the past fifty years. The growth of species richness in the Lower Kolsai against the background of an increase in the quantitative indicators of planktonic invertebrates is due to the increasing recreational load on the lake and the adjacent land area. The decrease in the species richness and abundance of zooplankton in the Tekes reservoir may be due to sharp fluctuations in the water level in the seasonal and interannual aspect and its periodic filling with river water not enriched with nutrients.