bluuebunny/crossref_metadata_2025 huggingface dataset:
Bridge crack segmentation and measurement based on SOLOv2 segmentation model
Authors: Ding Haiping , Wu Songying
Published: May 2024

With the continuous increase of vehicular traffic, the safety caused by bridge crack damage is becoming increasingly prominent. Bridge crack analysis and measurement are of great significance for promoting road traffic safety. However, existing bridge crack image segmentation methods have shortcomings in processing image detail features, resulting in the inability to better measure the actual size of bridge cracks. Therefore, to further optimize the calculation method, a bridge crack image segmentation method based on improved SOLOv2 is designed to achieve more accurate bridge image segmentation. Based on the image segmentation results and combined with the skeleton data extraction method, a bridge crack calculation method is designed. From the results, the segmentation accuracy for crack images was 92.05 % and 93.57 %, respectively. The average mIoU of AM-SOLOv2 method was 0.75, significantly lower than commonly used crack image segmentation methods. In addition, the mIoU value variation amplitude of the AM-SOLOv2 method was relatively smaller. The crack length and width errors were within 0.05 mm and 0.06 mm, significantly lower than the comparison method. It indicates that this method can achieve more accurate crack image segmentation and calculation. This is beneficial for a deeper understanding of the performance degradation and crack damage evolution of bridge structures, thereby improving bridge design and construction technology.
Life prediction method of rolling bearing based on CNN-LSTM-AM
Authors: Huang Wanqing , Chen Yang , Chen Yongqi , Zhang Tao
Published: May 2024

Bearing is the key component to determine the health of machinery, and it is of great significance to monitor its working status in real time and predict its remaining useful life. In recent years, the RUL prediction method based on deep learning has been widely used and achieved good prediction results. Here, a bearing life prediction method based on convolution neural network (CNN), long short term memory (LSTM) and attention mechanism (AM) is proposed. First of all, the time domain and frequency domain features of the original vibration signals of rolling bearings are extracted, and the extracted feature set is normalized as the input of CNN. The main function of CNN is to extract spatial features and reduce the dimension of the data. Then, using LSTM to extract the information that may be ignored by CNN, the feature information extracted by CNN-LSTM is input to the attention mechanism for weighting, and the key information is screened. And then more accurately represent the degradation characteristics of the equipment, and finally get the bearing remaining life. The performance of the model is verified by two sets of public data sets, and the experimental results show that it is compared with the CNN-LSTM method. The root mean square error (RMSE) index based on CNN-LSTM-AM method is reduced by 14.6 % and 13.8 % respectively, and the score index is increased by 2.0 % and 2.4 % respectively. The results show that the proposed method has higher accuracy in bearing RUL prediction.
A combination approach for optimization operation of multi-objective cascade reservoir systems (Case study: Karun reservoirs)
Authors: Khoramipoor Zahra , Farzin Saeed
Published: May 2024

Multi-reservoir systems that have diverse and conflicting objectives are challenging to design due to their uncertainties, non-linearities, dimensions and conflicts. The operation of multi-reservoir systems is crucial to increasing hydropower production. In this study, we have investigated the application and effectiveness of the new optimization algorithm MOAHA in multi-objective cascade reservoirs with conflicting objectives, and it has been investigated on a case-by-case basis on Karun cascade reservoirs (Karun 3, Karun 1, Masjed Soleyman and Gotvand). The suggested method (MOAHA) output with other optimization algorithms, MOALO, MOGWO and NSGA-II, were compared and evaluation criteria were used to select the best performance. Additionally, we employed the powerful TOPSIS method to determine the most suitable algorithm. The considered restrictions have also been observed. The results indicate that MOAHA's proposed method is better than the compared algorithms in solving optimal reservoir utilization problems in multi-reservoir water resource systems. The reduction of evaporation (losses) from the tank surface by 9% is accompanied by a 15% increase in hydropower energy production. MOAHA, scoring 0.90, is deemed the best algorithm in this study, whereas MOGWO, with a score of 0.10, is regarded as the least effective algorithm.
Uncovering sea level patterns in Caspian Sea altimetry data
Authors: A. Ardalan Alireza , Hashemifaraz Asiyeh
Published: May 2024

This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993–2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.
Recent progresses in synthesis and modification of g-C3N4 for improving visible-light-driven photocatalytic degradation of antibiotics
Authors: John Kingsley Igenepo , Ho Goen , Li Dan
Published: May 2024

Graphitic carbon nitride (g-C3N4) is a widely studied visible-light-active photocatalyst for low cost, non-toxicity, and facile synthesis. Nonetheless, its photocatalytic efficiency is below par, due to fast recombination of charge carriers, low surface area, and insufficient visible light absorption. Thus, the research on the modification of g-C3N4 targeting at enhanced photocatalytic performance has attracted extensive interest. A considerable amount of review articles have been published on the modification of g-C3N4 for applications. However, limited effort has been specially contributed to providing an overview and comparison on available modification strategies for improved photocatalytic activity of g-C3N4-based catalysts in antibiotics removal. There has been no attempt on the comparison of photocatalytic performances in antibiotics removal between modified g-C3N4 and other known catalysts. To address these, our study reviewed strategies that have been reported to modify g-C3N4, including metal/non-metal doping, defect tuning, structural engineering, heterostructure formation, etc. as well as compared their performances for antibiotics removal. The heterostructure formation was the most widely studied and promising route to modify g-C3N4 with superior activity. As compared to other known photocatalysts, the heterojunction g-C3N4 showed competitive performances in degradation of selected antibiotics. Related mechanisms were discussed, and finally, we revealed current challenges in practical application.
The Evolution of the Memory of Alexei Gastev as the Founder of the National School of Management – Scientific Organization of Labor in Modern Practices of Commemoration
Authors: Dvoluchansky I. V.
Published: May 2024

The Scientific Organization of Labor (NOT) became the largest school of management in the young Soviet republic, and Alexei Gastev's work as head of the Central Institute of Labor was duly appreciated by both contemporaries and followers. In this connection, during the subsequent period, the ideas of the authors of the NOT were used in management practice to solve urgent problems. In the post-Soviet period, researchers of the national history of management thought considered the developments of the ideologist of the NOT Alexei Gastev as a paradigmatic stage in the development of managerial ideas in our country. This article analyzes not the ideas of the author of the NOT themselves, but the memory of his ideas and how this memory was reflected in the process of their interpretation and application. The research is based on the methodology of Memory studies by such authors as Maurice Halbwachs, Jan and Aleida Assmann, Pierre Nora, as well as on the approaches of representatives of the Cambridge School of Intellectual History Quentin Skinner and John Pocock and the research apparatus of the concept of deterritorialization by Gilles Deleuze. In addition, the author's approach is used in the form of synthesis of the results of a meaningful and contextual analysis of memory practices. The result of the study is a description and justification of changes in the general context of A. K. Gastev's memory practices. Due to the lack of collective and cultural memory of A. K. Gastev in Soviet times, in the early years of the post-Soviet period, the practice of commemoration focuses on the building of memory through the actualization of research on the scientific organization of labor. Further, the context of actualization loses its significance and the process of attaching the memory of A. K. Gastev to nearby cultural objects, such as the culture of the avant-garde era, takes place. At the moment, the transformation of the memory of A. K. Gastev is clearly expressed in the formation of the cultural memory of "Gastevski". This new form of memory does not yet have precise boundaries, but some contours are already emerging.
Research on Pricing on Re Market in Sevastopol
Authors: Bezhan M. V. , Rakitina I. S. , Shevchuk I. A.
Published: May 2024

Affordability of housing is one of the most important and topical trends, that is taken into account in pursuing state economic policy in Russia. Pricing process on RE market acts as a serious factor influencing housing affordability and appeal of certain regions for continuous residence. Construction volumes directly depend on effective demand and conditions of mortgage crediting. The article discusses acute issues of certain factor impact on pricing process on RE market. In order to identify the interconnection of these factors the research conducted econometric assessment of the impact of wage dynamics and mortgage crediting portfolio on changes in market RE cost in the city of federal importance Sevastopol. Methods used in the research: models of vector auto-regression (standard and bias). Data of official statistics were used as an information base, including data of the Bank of Russia, as well as publications by economists. The initial hypothesis of the research said that proposed variables influence seriously the actual figure of housing cost in the region. Econometric analysis of this thesis proved in general the hypothesis. Findings of the research can form a scientific base for forecasting inflation processes on RE market in the city of Sevastopol and can be used in other entities of the Russian Federation.
Forecasting Limits of Feasible Organization Growth by Using Key Predictors of Organizational Transformation
Authors: Bobkov A. L.
Published: May 2024

The article studies methodological approach, advanced by the author, to using key predictors of organizational transformation necessary to forecast limits of feasible organization growth within the frames of the present production structure. The principle distinguishing feature of this methodological approach is the use of indicators defined by the author as key predictors of organizational transformation. This set of indicators was identified by the author through results of earlier statistical research of transformation laws of organization production structure in different sectors of economy. With the help of such indicators it is possible not only to describe the predominant type of organization production structure but also, on the basis of their quantitative values, to identify limits of corresponding level of its development. Methodological approach advanced by the author is based on statistical methods of research and gives an opportunity to forecast limits of feasible organization growth based on the earlier developed method of their production structure. Within the frames of the given methodological approach the method of statistical forecasting limits of feasible organization growth was elaborated. The use of this methodology could allow organization management to forecast in advance the moments of coming organizational transformation, which is connected with changes in production structure type and to make necessary managerial decisions.
Ways of Upgrading Macro-Economic Stimulation of Labour Productivity in View of Neo-Keynesian Economic Theory
Authors: Gerasev I. A.
Published: May 2024

The article analyzed the experience of economic system functioning in view of researching trends acute for resolving problems of labour productivity in Russia.

   The research goal is to find ways of optimizing economic policy of labour productivity stimulation.

   The author conducted theoretical research in raising labour productivity within the frames of neo-Keynesian theory and studied retrospective ideas concerning this problem in the previous classical economic theory. The research showed the emergence of ideas dealing with the role of labour in value creation, macro-economic balance between investment and remuneration in labour productivity. The author identified in theory and proved in practice the importance of raising labour productivity as a factor of economic growth. Based on empiric research results of economic policy were analyzed in certain fields, such as wages, investment macro-economic policy and technological policy of state. By using post-soviet economy of Russia as an example the author proved key economic theses about trends of economic policy necessary for stimulating labour productivity. The importance of macro-economic regulation and innovation was highlighted in view of foreign-economic sanctions and trade restrictions. Findings of the research demonstrate key trends needed to resolve the problem of raising labour productivity and put forward steps necessary to reach positive results.
Sustainable Development of Human Potential as Strategic Priority of Providing National Security
Authors: Gagarina G. Yu. , Gorokhova I. V. , Gretchenko A. I.
Published: May 2024

The article acts as an answer to the request of students of higher education institutions in specialization ‘Economic security’, who face the necessity to estimate the impact of sustainable development of human potential on providing national security of the country. In this context the article studies theoretical aspects of human potential in the system of national security of Russia in the present geopolitical and finance and economic situation in the world. The authors work out the system of key indicators having indentified those, which characterize the level of education and science development as well as public health service and put forward methods to estimate the level of human potential development and its impact on national economic security of the country. Having analyzed threats in the field of education, science and public health service the authors propose ways of their minimization. Special attention is paid to elaboration of forecasts concerning selected indicators, which can help assess the development of human potential in the medium-term perspective and arrange necessary steps aimed at cutting threats and improving economic security in this field.
Depletion of SLC7A11 Sensitizes Nasopharyngeal Carcinoma Cells to
Ionizing Radiation
Authors: Yang Fan , Gong Hongxun , Chen Shiyan , Li Jianzhong , Huang Ning , Wang Maoxin
Published: May 2024

Background:

Radiotherapy is the primary treatment choice for Nasopharyngeal Carcinoma
(NPC). However, its efficacy is compromised due to radioresistance. Ferroptosis, a novel
iron-dependent regulated cell death induced by Ionizing Radiation (IR), plays a role in promoting
cancer cell death. Yet, the relationship between enhanced ferroptosis and increased sensitivity of
NPC cells to IR remains poorly understood.

Objective:

This study aimed to explore the association between IR and ferroptosis in NPC, as well
as the role of the ferroptosis repressor SLC7A11 in IR-treated NPC cells.

Methods:

CNE1 and HNE-2 NPC cells were subjected to IR treatment. We performed qPCR and
western blotting to evaluate the expression of ferroptosis-related genes in both control and IR-treated
NPC cells. Additionally, we used the MTT assay to measure the viability of these NPC cells.
JC-1 and DCFH-DA staining were employed to assess mitochondrial membrane potential and Reactive
Oxygen Species (ROS) levels in both control and IR-treated NPC cells. Furthermore, we examined
the levels of Fe2+, Malondialdehyde (MDA), reduced Glutathione (GSH), and oxidized glutathione
(GSSG) in these cells. Moreover, we depleted SLC7A11 in IR-treated NPC cells to investigate
its impact on the ferroptosis of these cells.

Results:

IR upregulated the expression of ferroptosis-related genes, including SLC7A11, ACSL4,
COX2, FTH1, and GPX4, in CNE1 and HNE-2 cells. IR treatment also resulted in decreased cell
viability, disrupted mitochondrial membrane potential, increased ROS levels, altered glutathione
levels, and elevated Fe2+ levels. Knockdown of SLC7A11 enhanced the sensitivity of NPC cells to
IR.

Conclusion:

IR may induce ferroptosis in NPC cells, and stimulating ferroptosis could potentially
serve as a therapeutic strategy to enhance the efficacy of IR in treating NPC patients.
Smart Polymer Systems: A Futuristic Approach to Enhance Therapeutic Efficacy
Authors: Seth Avinash Kumar , Parmar Ghanshyam , Aundhia Chintan , Shah Nirmal , Gohil Dipti
Published: May 2024

Recently, pharmaceutical industries have placed considerable emphasis on formulating
drug delivery systems that precisely target specific sites, optimize drug utilization,
minimize excipient usage, and mitigate side effects. Smart polymers hold tremendous
promise in the design of innovative formulations tailored to deliver drugs with enhanced
precision, efficacy, and therapeutic benefits while minimizing adverse effects. Within drug
delivery, smart polymers demonstrate exceptional potential in achieving controlled and
targeted release profiles, ensuring drug delivery to specific receptors, and minimizing offtarget
effects. This comprehensive review article focuses on the latest developments in
smart polymers, primarily in the domains of drug delivery. By intelligently responding to
external stimuli, smart polymer-based materials offer various applications, making them
pivotal in modern pharmaceutical research. By utilizing the remarkable attributes of smart polymers, researchers
and industry stakeholders can forge a path toward personalized, efficient, and patient-centric therapies with
reduced side effects, propelling the pharmaceutical field into an era of unprecedented advancements.
Recent Advancements and SAR Studies of Synthetic Coumarins as MAO-B Inhibitors: An Updated Review
Authors: Kaur Prabhjot , Rangra Naresh Kumar
Published: May 2024

Background:

The oxidative deamination of a wide range of endogenous and exogenous
amines is catalyzed by a family of enzymes known as monoamine oxidases (MAOs), which are reliant
on flavin-adenine dinucleotides. Numerous neurological conditions, such as Parkinson's disease
(PD) and Alzheimer's disease (AD), are significantly correlated with changes in the amounts of biogenic
amines in the brain caused by MAO. Hydrogen peroxide, reactive oxygen species, and ammonia,
among other toxic consequences of this oxidative breakdown, can harm brain cells' mitochondria
and cause oxidative damage.

Objective:

The prime objective of this review article was to highlight and conclude the recent advancements
in structure-activity relationships of synthetic derivatives of coumarins for MAO-B inhibition,
published in the last five years' research articles.

Methods:

The literature (between 2019 and 2023) was searched from platforms like Science Direct,
Google Scholar, PubMed, etc. After going through the literature, we have found a number of coumarin
derivatives being synthesized by researchers for the inhibition of MAO-B for the management
of diseases associated with the enzyme such as Alzheimer’s Disease and Parkinson’s Disease. The
effect of these coumarin derivatives on the enzyme depends on the substitutions associated with the
structure. The structure-activity relationships of the synthetic coumarin derivatives that are popular
nowadays have been described and summarized in the current study.

Results:

The results revealed the updated review on SAR studies of synthetic coumarins as MAO-B
inhibitors, specifically for Alzheimer’s Disease and Parkinson’s Disease. The patents reported on
coumarin derivatives as MAO-B inhibitors were also highlighted.

Conclusion:

Recently, coumarins, a large class of chemicals with both natural and synthetic
sources, have drawn a lot of attention because of the vast range of biological actions they have that
are linked to neurological problems. Numerous studies have demonstrated that chemically produced
and naturally occurring coumarin analogs both exhibited strong MAO-B inhibitory action. Coumarins
bind to MAO-B reversibly thereby preventing the breakdown of neurotransmitters like dopamine
leading to the inhibition of the enzyme A number of MAO-B blockers have been proven to be
efficient therapies for treating neurological diseases like Alzheimer’s Disease and Parkinson’s Disease.
To combat these illnesses, there is still an urgent need to find effective treatment compounds.
Lipid-Based Nanocarriers for Targeted Gene Delivery in Lung Cancer Therapy: Exploring a Novel Therapeutic Paradigm
Authors: Beigi Anahita , Naghib Seyed Morteza , Matini Amir , Tajabadi Maryam , Mozafari Mohammad Reza
Published: May 2024

Lung cancer is a significant cause of cancer-related death worldwide. It can be broadly
categorised into small-cell lung cancer (SCLC) and Non-small cell lung cancer (NSCLC). Surgical
intervention, radiation therapy, and the administration of chemotherapeutic medications are
among the current treatment modalities. However, the application of chemotherapy may be limited
in more advanced stages of metastasis due to the potential for adverse effects and a lack of cell
selectivity. Although small-molecule anticancer treatments have demonstrated effectiveness, they
still face several challenges. The challenges at hand in this context comprise insufficient solubility
in water, limited bioavailability at specific sites, adverse effects, and the requirement for epidermal
growth factor receptor inhibitors that are genetically tailored. Bio-macromolecular drugs, including
small interfering RNA (siRNA) and messenger RNA (mRNA), are susceptible to degradation
when exposed to the bodily fluids of humans, which can reduce stability and concentration. In
this context, nanoscale delivery technologies are utilised. These agents offer encouraging
prospects for the preservation and regulation of pharmaceutical substances, in addition to improving
the solubility and stability of medications. Nanocarrier-based systems possess the notable advantage
of facilitating accurate and sustained drug release, as opposed to traditional systemic
methodologies. The primary focus of scientific investigation has been to augment the therapeutic
efficacy of nanoparticles composed of lipids. Numerous nanoscale drug delivery techniques have
been implemented to treat various respiratory ailments, such as lung cancer. These technologies
have exhibited the potential to mitigate the limitations associated with conventional therapy. As
an illustration, applying nanocarriers may enhance the solubility of small-molecule anticancer
drugs and prevent the degradation of bio-macromolecular drugs. Furthermore, these devices can
administer medications in a controlled and extended fashion, thereby augmenting the therapeutic
intervention's effectiveness and reducing adverse reactions. However, despite these promising results,
challenges remain that must be addressed. Multiple factors necessitate consideration when
contemplating the application of nanoparticles in medical interventions. To begin with, the advancement
of more efficient delivery methods is imperative. In addition, a comprehensive investigation
into the potential toxicity of nanoparticles is required. Finally, additional research is needed
to comprehend these treatments' enduring ramifications. Despite these challenges, the field of
nanomedicine demonstrates considerable promise in enhancing the therapy of lung cancer and
other respiratory diseases.
Application of Nanotechnology as a Novel Approach to the Treatment of Skin Cancer
Authors: Singh Sonia , Gupta Aman , Varshney Mahima
Published: May 2024

Skin cancer has become the fifth most frequently reported form of cancer worldwide,
imposing significant economic and public health challenges. Over the course of the last ten years,
there has been a significant increase in the application of Nanoparticles (NPs) as a method of
therapeutic administration to target skin cancer. The information has been gathered from many
online databases, such as Scopus, Pubmed, Science Direct, and Web of Science, among others.
An analysis of research articles that focused on the therapeutic effect of nanoformulations on skin
cancer was included as part of the criteria for selecting the study. Nanoparticles have the potential
to change the pharmacokinetics of the drug, increase the drug’s half-life by lowering immunogenicity,
increase its bioavailability, decrease drug metabolism, and improve the solubility of poorly
water-soluble drugs. The distribution of NP-based treatments to the skin requires special consideration
due to the fact that the skin acts as both a physical and immunologic barrier. In addition,
specialized technologies must take into consideration not only the target but also the channel of
administration in order to be effective. The purpose of this review article was to provide an overview
of many types of NPs, address the current landscape of NPs for skin cancer prevention and
treatment, and provide a description of the application of NP-based technologies for drug delivery
targeting the skin.
An Exploratory Review on Recent Computational Approaches Devised for MiRNA Disease Association Prediction
Authors: Sujamol S. , Vimina E.R. , Krishnakumar U.
Published: May 2024

Recent evidence demonstrated the fundamental role of miRNAs as disease biomarkers
and their role in disease progression and pathology. Identifying disease related miRNAs using computational
approaches has become one of the trending topics in health informatics. Many biological
databases and online tools were developed for uncovering novel disease-related miRNAs. Hence, a
brief overview regarding the disease biomarkers, miRNAs as disease biomarkers and their role in
complex disorders is given here. Various methods for calculating miRNA and disease similarities are
included and the existing machine learning and network based computational approaches for detecting
disease associated miRNAs are reviewed along with the benchmark dataset used. Finally, the
performance matrices, validation measures and online tools used for miRNA Disease Association
(MDA) predictions are also outlined.
State of the Art on Suicide Studies in Morocco: Trends, Risk Factors and Implications for Prevention
Authors: El Ouardi Abdelghani , Hassouny El Hassan El , El Feniche Mohammed , El Habchi Maha , Najat Boucetta , Kiri Said EL , Kisra Hassan
Published: May 2024

Suicide remains a pressing public health concern in Morocco, yet the research landscape surrounding this issue is relatively sparse. To address this gap, we conducted a comprehensive review of 96 articles about suicide in Morocco, sourced from the Scopus database. Focusing on the period from 2014 to 2023, 68 articles were selected for detailed analysis, revealing critical insights into the multifaceted nature of suicidal behavior in the country. Through a thematic categorization of the literature, encompassing domains such as Suicidal Behavior and Mental Health, Epidemiology and Risk Factors, Psychological Disorders, Suicide Prevention, Medical Emergencies, and Methodology and Technology, our review synthesized vital findings and trends in Moroccan suicide research. Notably, the analysis illuminated concerning patterns of suicidal behavior and identified significant risk factors, including mental health disorders, psychosocial stressors, and socio-economic challenges. In light of these findings, urgent attention is warranted to develop and implement targeted prevention strategies tailored to the unique needs of the Moroccan population to mitigate the impact of suicide on individuals, families, and communities alike.
Bioprospecting Antibacterial Properties of Fungi Isolated from Kakinada Sea Coast and Eucalyptus Foliage
Authors: Mancheary John Prathyash Ushus , Kandula Siva Kumar , Valiyaparambil Shilpa , Kotakonda Muddukrishnaiah , Kallungal Sirajudheen Mukriyan , Periyasamy Bharathi , Peddi Koteswari , Metta Venkata Satya Mahesh Kumar , Cheekatla Satyanarayana Swamy
Published: May 2024

Background:

Fungi produce a wide range of secondary metabolites with bactericidal or bacteriostatic properties. In search of novel antibacterial compounds recently, many fungi of marine and plant origin have been studied for their antimicrobial properties.

Aims:

This work aimed to study bio-prospect marine and endophytic fungi for their antibacterial properties.

Methods:

Intensive microbiological methods were followed for isolation, differential growth, and qualitative screening of enzyme production. The isolates were characterised and identified based on morpho-taxonomy, 18S rRNA gene sequencing, and phylogenetic analysis of the tar-get genes. The antimicrobial activity of fungal ethyl acetate extracts against S. aureus, B. sub-tilis, and E. coli was evaluated using a well-diffusion method, and MIC was determined by the microdilution method. Cell lysis was observed through Transmission Electron Microscopy.

Results:

A BLAST search of 18S rRNA gene sequences of the marine isolates GSBT S13 and GSBT S14 showed 99.3 % sequence similarity with A. glaucus for both isolates and that of endophyte GSBT E3 showed 99.7 % sequence similarity with B. pinkertoniae. Cellulase pro-duction was comparatively higher in GSBT E3 and lipase from GSBT S13 and GSBT S14. Ethyl acetate extracts of GSBT S14 and GSBT E3 showed a clear zone of inhibition by the well-diffusion method, further confirmed by electron microscopy. HR-TEM showed that the ethyl acetate extracts of the isolates appeared to damage the cell membrane, leading to cell shrinkage and death in E. coli and S. aureus.

Conclusion:

GSBT S13 and GSBT S14 exhibited extracellular amylase, cellulase, and lipase activities. Ethyl acetate extracts of both GSBT S14 and B. pinkertoniae GSBT E3 showed better antibacterial properties against S. aureus.
Glymphatic System and Psychiatric Disorders: A Rapid Comprehensive
Scoping Review
Authors: Barlattani Tommaso , Grandinetti Paolo , Cintio Alexsander Di , Montemagno Alessio , Testa Roberta , D’Amelio Chiara , Olivieri Luigi , Tomasetti Carmine , Rossi Alessandro , Pacitti Francesca , De Berardis Domenico
Published: May 2024

Background:

Since discovering the glymphatic system, there has been a looming interest in
exploring its relationship with psychiatric disorders. Recently, increasing evidence suggests an involvement
of the glymphatic system in the pathophysiology of psychiatric disorders. However, clear
data are still lacking. In this context, this rapid comprehensive PRISMA-ScR (Preferred Reporting
Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) scoping review
aims to identify and analyze current evidence about the relation between the glymphatic system and
psychiatric disorders.

Methods:

We conducted a comprehensive review of the literature and then proceeded to discuss the
findings narratively. Tables were then constructed and articles were sorted according to authors, year,
title, location of study, sample size, psychiatric disorder, the aim of the study, principal findings,
implications.

Results:

Twenty papers were identified as eligible, among which 2 articles on Schizophrenia, 1 on
Autism Spectrum Disorders, 2 on Depression, 1 on Depression and Trauma-related Disorders, 1 on
Depression and Anxiety, 2 on Anxiety and Sleep Disorders, 8 on Sleep Disorders, 2 on Alcohol use
disorder and 1 on Cocaine Use Disorder.

Conclusion:

This review suggests a correlation between the glymphatic system and several psychiatric
disorders: Schizophrenia, Depression, Anxiety Disorders, Sleep Disorders, Alcohol Use Disorder,
Cocaine Use Disorder, Trauma-Related Disorders, and Autism Spectrum Disorders. Impairment of the
glymphatic system could play a role in Trauma-Related Disorders, Alcohol Use Disorders, Cocaine
Use Disorders, Sleep Disorders, Depression, and Autism Spectrum Disorders. It is important to implement
research on this topic and adopt standardized markers and radio diagnostic tools.
Cost Optimisation Analysis for a Markovian Feedback Queueing System with Discouragement, Breakdown, and Threshold-based Recovery Policy
Authors: Kumar Amit , Bouchentouf Amina Angelika , Boualem Mohamed
Published: May 2024

In this investigation, we deal with a finite capacity Markovian feedback queue with
threshold-based recovery policy, server breakdown, and customers’ impatience. For this
system, the Successive Over-Relaxation (SOR) method is used to obtain the steady-state
probabilities. Besides, the queueing system’s characteristics are also derived. Then, cost
optimization of the system is carried out using the Quasi-Newton method. Further, numerical
studies are performed to support the theoretically obtained results.
Development and Assessment of Data in Solarpowered System for Simultaneous Production of Power, Heating, and Cooling
Authors: Parvez Mohd , Ahamad Taufique , Khan Osama
Published: May 2024

The primary objective of the study is to investigate the trigeneration system for the
simultaneous production of power, heating, and cooling, driven by solar power towers
employing molten salt as the heat transfer fluid. A comparative analysis is provided between
refrigerants (LiNO3-H2O and LiBr-H2O), so as to evaluate the best thermodynamic
performance for the vapor absorption refrigeration system among them. A novel concept of
uncertainty analysis is introduced which is a prime instance in this research area so as to provide
much better results with precision removing all human and machine errors stipulated to be 5.34
% which is to be found in the desired range. Combined energy and exergy analyses are
performed to investigate the variation in efficienices while altering various performance
parameters for the trigeneration system. The highest exergy destruction was found to be 33.6%
by the central receiver, 24.9% by heliostat, and 7.8% by heat recovery steam generators. The
highest energy and exergy efficiencies (62.6% and 20.6%) were obtained by LiBr-H2O,
whereas (60.9% and 19.6%) were obtained from LiNO3-H2O refrigerant.
Labour related migration under conditions of free movement
Authors: Cawley Mary
Published: May 2024

The aim of this chapter is to add to existing knowledge and theory relating international labour migration under conditions of free movement. The chapter focuses on Polish nationals who, with Lithuanians, are the largest immigrant group in Ireland from the eight countries of Central and Eastern Europe that acceded to membership of the European Union (EU) in 2004. The research draws on census of population data at a range of geographical scales. The movement of the immigrants between areas was traced using choropleth mapping and statistical measurement of population density and distribution, compared with the Irish population, using the Hoover Index and the Dissimilarity Index. The greatest concentration of Polish nationals occurs in large centres of population but movement took place to smaller places from the beginning and increased over time.
Marketing territorial como ferramenta para desenvolver o turismo rural no Dombe Grande, Angola
Authors: Santos Rebeca
Published: May 2024

In a context in which Angola has poverty, hunger and the devaluation of rural areas as some of its main characteristics, the implementation of Territorial Marketing in Dombe Grande would be the impetus for the promotion of rural tourism and the sustainable development of the small commune, making it an example of success with an impact at local, regional and national level. The aim of this approach is to give visibility to Dombe Grande's potential and to draw the attention of the authorities responsible for its development to the need for urgent intervention, which can be done through the adoption of Territorial Marketing strategies that boost the publicity of this territory, taking into account the Sustainable Development Goals (SDGs). Territorial Marketing, as an instrument to support Territorial Planning, is used as a central strategy to build and publicise the image of territories, especially those with great potential such as Dombe Grande. In this sense, the rural tourism sector has become the instrument's main ally, complementing it with advantages in terms of economic, social, patrimonial and territorial viability. The means of data collection, based on qualitative and quantitative analysis (interviews and surveys), led to the conclusion that Territorial Marketing strategies must result from appropriate land use policies, based on social inclusion and the creation of services and opportunities that improve the living conditions and well-being of the populations.
Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial (Preprint)
Authors: Tsai Chuan-Ching , Kim Jin Yong , Chen Qiyuan , Rowell Brigid , Yang X Jessie , Kontar Raed , Whitaker Megan , Lester Corey
Published: May 2024

BACKGROUND

Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.

OBJECTIVE

This study aimed to evaluate the cognitive interaction patterns of pharmacists during medication product verification when using an AI prototype. Moreover, we examine the impact of AI’s assistance, both helpful and unhelpful, and the communication of uncertainty of AI-generated results on pharmacists’ cognitive interaction with the prototype.

METHODS

In a randomized controlled trial, 30 pharmacists from professional networks each performed 200 medication verification tasks while their eye movements were recorded using an online eye tracker. Participants completed 100 verifications without AI assistance and 100 with AI assistance (either with black box help without uncertainty information or uncertainty-aware help, which displays AI uncertainty). Fixation patterns (first and last areas fixated, number of fixations, fixation duration, and dwell times) were analyzed in relation to AI help type and helpfulness.

RESULTS

Pharmacists shifted 19%-26% of their total fixations to AI-generated regions when these were available, suggesting the integration of AI advice in decision-making. AI assistance did not reduce the number of fixations on fill images, which remained the primary focus area. Unhelpful AI advice led to longer dwell times on reference and fill images, indicating increased cognitive processing. Displaying AI uncertainty led to longer cognitive processing times as measured by dwell times in original images.

CONCLUSIONS

Unhelpful AI increases cognitive processing time in the original images. Transparency in AI is needed in “black box” systems, but showing more information can add a cognitive burden. Therefore, the communication of uncertainty should be optimized and integrated into clinical workflows using user-centered design to avoid increasing cognitive load or impeding clinicians’ original workflow.
Improving Oral Health in Prisons (PriOH): Protocol for a Randomized Controlled Trial (Preprint)
Authors: Bryne Emilie , Bergum Kathrine Høyvik , Gjedrem William Gilje
Published: May 2024

BACKGROUND

People living in prisons often experience poor oral health, which could be attributed to their limited access to (dental) care, financial constraints, and a general lack of awareness and prioritization toward their oral hygiene. A pilot study involving motivational interviewing (MI) has shown promising results for improving the oral health outcomes of people living in prisons.

OBJECTIVE

The protocol for this study aims to assess the efficacy of integrated MI and oral hygiene packages in improving oral health among people living in prisons, compared to controls without added MI.

METHODS

This oral health in prisons study is a multicenter, randomized, double-blinded controlled trial that recruited inmates from 4 prisons in Rogaland County. The trial aimed to recruit 320 participants before randomly allocating them to either a control or intervention group. The intervention group received MI, consisting of a 30-minute session encouraging inmates to discuss their current and desired oral health behaviors and attitudes, highlighting discrepancies to motivate change. Assessments were conducted at 4 and 12 weeks after initiation. The primary outcome measurement is the mucosal-plaque scores to assess oral health behaviors, attitudes, and oral hygiene. Secondary outcome measurements are oral hygiene routines, sugary food and drink intake, oral health perception, and oral health-related questions.

RESULTS

Data collection started in November 2021 and ended in June 2023. A total of 327 participants were recruited, of which 126 received the intervention.

CONCLUSIONS

Integrating MI in oral health programs at prisons can significantly improve the oral health of incarcerated individuals. Should the results from this study demonstrate efficacy, it could be valuable insight for policy makers, oral health practitioners, and correctional services in addressing the needs of a traditionally underserved group before being scaled up to enhance dental care practices in prisons.

CLINICALTRIAL

ClinicalTrials.gov NCT05695443; https://clinicaltrials.gov/study/NCT05695443

INTERNATIONAL REGISTERED REPORT

DERR1-10.2196/60817
WORKING CAPITAL AND TAX PAYABLE: ANALYSIS OF INTERRELATIONSHIP IN MANUFACTURING COMPANIES
Authors: Adegbite Tajudeen A , Inyada Sunday Joseph
Published: May 2024

Most of the manufacturing firms are blamed for the inability to fulfill their obligations to the government on working capital inadequacy and ineffective plan, control and monitoring which led to business failures, and profitability reduction which invariably reduced tax payable to the government in the past. To this effect, therefore, this study examined working capital effect on tax payable in Nigeria manufacturing companies. Ten manufacturing companies were selected from listed manufacturing companies in the Nigeria stock exchange jurisdiction from 2010 to 2022. The data sourced were: receivable, inventory, payable, profit before tax, and the firm size (the net asset of the companies) from published annual financial statement from 2010 to 2022. After the data arrangement, we employed panel data analysis to gauge working capital effect on tax payable in Nigerian manufacturing companies. We conducted unit root test (Panel) to examine the stationary of the variables. Pearson correlation, panel regression analysis, Feasible Generalized Least Squares (FGLS), and other post estimation tests like autocorrelation, heteroskedasticity test, and Hausman test was also launched to gauge the model suitability between random and fixed effect while Breusch – Pagan LM was further launched to select between random and Pooled OLS. The outcome shows that receivable, inventory, and payable are favourably significant to TAXPAB which ultimately divulges the significance of working capital components on tax payable. Conclusively, working capital significantly, statistically and progressively influences tax payable in Nigeria manufacturing companies.  We further recommended that more efforts should be expended by manufacturing companies to effectively utilize their working capital in their custody because a goodexploitation of working capital enhances company’s profitability and augments the strength for markets competitiveness, firm value, and shareholders’ wealth.
AI Based Mock - Interview Behavioural Recognition Analyst
Authors: Kolpe Prof. Sakharam
Published: May 2024

Abstract: In Present competitive job market hustle, being skilled at interview skills is very vital for current institution graduates looking for further trainings or hiring opportunities. Yet, several Interview Candidates needs suitable preparation for interview situations throughout candidate institute academic years. To discourse this opening, scholars have aims on designing and development of societal skills training classifications to offer candidates with opportunities to boost the interview skills. Job interviews assist as a fundamental means for potential employers to evaluate candidates' appropriateness for their administrations, deeply depended on communal indications displayed by applicants. our paper offers an advanced method to simulate employmentinterviews using a communal simulated character as a recruiter, joined with signal processing techniques to examine employer performance, behaviour and sentiments in real-time. The mock-up aims to support candidates, mainly youths, in improving societal skills necessary for job interviews. The anticipated classification includes a real-time community cue recognition classification, a dialog/scenario manager, a behaviour manager, and a 3D rendering environment. Feedback mechanisms integrated into the classificationinclude facial expressions, head nodding, reaction time, speaking rate, and volume, providing candidates with insights into their performance throughout mock interviews. Additionally, a speech-to-text classification assesses grammar, and graphical representations of results facilitate easy comparison of interview performances to track candidates' progress over multiple sessions. This paper contributes to the interdisciplinary literature on interview assessment and highlights the potential of AI-driven technologies in enhancing candidates' interview preparedness and social competence.
Empirical Sample Complexity of Neural Network Mixed State Reconstruction
Authors: Zhao Haimeng , Carleo Giuseppe , Vicentini Filippo
Published: May 2024

Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments focusing mainly on the noiseless case. In this work, we numerically investigate the performance of different quantum state reconstruction techniques for mixed states: the finite-temperature Ising model. We show how to systematically reduce the quantum resource requirement of the algorithms by applying variance reduction techniques. Then, we compare the two leading neural quantum state encodings of the state, namely, the Neural Density Operator and the positive operator-valued measurement representation, and illustrate their different performance as the mixedness of the target state varies. We find that certain encodings are more efficient in different regimes of mixedness and point out the need for designing more efficient encodings in terms of both classical and quantum resources.