bluuebunny/crossref_metadata_2025 huggingface dataset:
Fronto-parietal and cerebellar circuits characterise individuals with high trait anxiety: a parallel ICA and Random Forest approach
Authors: Baggio Teresa , Grecucci Alessandro , Crivello Fabrice , Joliot Marc , Tzourio Christophe
Published: October 2023

Anxiety is a diffuse condition that can range from mild to more severe manifestations, including proper anxiety disorders. Specific sensitive periods such as adolescence and young adulthood are particularly vulnerable to anxious states and may favour the onset of future anxiety disorders. Until now, neuroanatomical research on anxiety has focused mainly on adults, employed univariate inference-based approaches, and considered one single neuroimaging modality, thus leading to an incomplete picture. The aim of the present study is to characterize the joint GM-WM contribution in high versus low trait anxiety, in a large sample of young individuals, exploiting a data fusion machine learning technique known as Parallel ICA, and to build a predictive model of trait anxiety based on a Random Forest classifier. Additionally, we aimed to characterize high anxiety individuals for their usage of maladaptive coping strategies, and other affective dimensions such as anger, impulsivity, and stress, and to test their relevance in predicting new cases of high trait anxiety.
At the neural level we found a fronto-parieto-cerebellar network to have a decrease gray matter concentration in high anxious individuals, and a parieto-temporal network to have an increase white matter concentration in high anxious individuals.
Additionally, at the psychological level, individuals with high anxiety are characterized by higher stress, cognitive and motor impulsivity, and avoidance/emotional coping.
Lastly, the Random Forest classifier robustly confirmed the goodness of the morphometric and psychological factors in predicting new cases of trait anxiety. As such, these findings may pave the road for the creation of an early biomarker of trait anxiety in young individuals, contributing to an early intervention to prevent the future development of anxiety disorders.
EpiVECS: Exploring spatiotemporal epidemiological data using cluster embedding and interactive visualization.
Authors: Mason Lee , Hicks Blánaid , Almeida Jonas
Published: October 2023

The analysis of data over space and time is a core part of descriptive epidemiology, but the complexity of spatiotemporal data makes this challenging. There is a need for methods which simplify the exploration of such data for tasks such as surveillance and hypothesis generation. In this paper, we use combined clustering and dimensionality reduction methods (hereafter referred to as ‘cluster embedding’ methods) to spatially visualize patterns in epidemiological time-series data. We compare several cluster embedding techniques to see which performs best along a variety of internal cluster validation metrics. We find that methods based on k-means clustering generally perform better than self-organizing maps on real world epidemiological data, with some minor exceptions. We also introduce EpiVECS, a tool which allows the user to perform cluster embedding and explore the results using interactive visualization. EpiVECS is available as a privacy preserving, in-browser open source web application at https://episphere.github.io/epivecs.
Study of Simultaneous Wireless Information and Power Transfer (SWIPT) in 5G - IoT
Authors: Bavethra M , Palani U
Published: October 2023

The SWIPT technology, recognized as a wireless energy harvesting technique to steer the advancement of subsequent generations of wireless systems, namely 5G and its successors. The Internet of Things is anticipated to enhance the life of human quality, though IoT devices are confronted with energy limitations stemming from available resource constraints. In recent years, SWIPT-based radio frequency will be regarded as a promising energy harvesting technique likely there will be an increase in number of devices connected to networks and applications in near future, which will increase the demand for next-generation wireless communications, causes an increase in energy consumption. As a consequence, energy harvesting and data transmission are necessary for the energy-efficient communication, therefore, green communications based on SWIPT are expected to become an essential component of both 5G and 5G+. SWIPT systems conventionally utilize ambient signals for both information transfer and energy supply. As such, the present dissertation endeavors to scrutinize SWIPT communication with the aim of engendering enhanced comprehension of the system's operation and performance. This paper reviews two levels of literature on multiuser SWIPT communications for 5G. First, SWIPT enabled the selective OFDM model. Second, SWIPT-enabled mm-wave propagation was reviewed for system characterized to 5G IoT devices.
Antiplatelet therapy prior to COVID-19 infection impacts on patients mortality: A propensity score-matched cohort study.
Authors: Sokolski Mateusz , Reszka Konrad , Adamik Barbara , Kilis-Pstrusinska Katarzyna , Lis Weronika , Pomorski Michał , Sokolowski Janusz , Doroszko Adrian , Madziarska Katarzyna , Jankowska Ewa Anita , Protasiewicz Marcin
Published: October 2023

Hyperinflammation and coagulopathy with interaction with platelets are the pathomechanisms responsible for the unfavorable outcome of COVID-19. Therefore, the role of antiplatelet therapy (AP) therapy in patients with COVID-19 is uncertain. The aim of this study was to investigate if AP has an impact on the in-hospital course and medium-term outcomes in hospitalized COVID-19 patients. The study population (2170 COVID-19 patients: 60 (19) years old, 50% male) was divided into a group of 274 patients receiving any AP prior to COVID-19 infection (AP group), and after propensity score matching, a group of 274 patients without previous AP (non-AP group). Patients from the AP group were less frequently hospitalized in the intensive care unit (9% vs. 15%, P=0.027), developed less often shock (9% vs. 15%, P=0.033), and required less aggressive forms of therapy. The AP group had more coronary revascularizations (5% vs. 1%, P=0.008) and strokes/TIA (5% vs. 1%, P=0.017). The bleeding rate was comparable (6% vs. 9%, P=0.370). The patients from the AP group had lower 3-month mortality: 31% vs. 39%, P=0.032; HR(95%CI): 0.69(0.51–0.93). The groups did not differ significantly in terms of 6-month mortality. The AP may have a beneficial impact on hospital course and mortality in COVID-19.
Impact of Donor Variant Anatomy on Graft Reconstruction in Living Donor Liver Transplantation
Authors: Saleem M. Asad , Khalid Abdullah , Haq Ihsan , Rashid Sohail , Khan M. Yasir , Dar Faisal Saud
Published: October 2023

Background
Living donor liver transplantation (LDLT) is a definitive treatment option in Asian countries where deceased donation is scarce. Various anatomical variations may occur, posing a significant challenge to liver transplant surgeons. This study aimedto evaluate the impact of a donor’s variant anatomy on graft reconstruction in liver transplantation.
Methods
Aretrospective analysis of 400 LDLTfrom March 2019 to March 2023 was conducted. Clinical data and operative details were collected. Kaplan Meier curve was used for biliary complications and survival.
Results
This study included 400 patients with a mean age of 43. There were 48 mortalities after a median follow-up of 18 months. The study found a significant relationship between cold ischemia time and portal vein anatomy type (p-value < 0.001). The most common graft arterial reconstruction was with RHA of the recipient (82.6%) and five (1.5%) anastomosed directly to the aorta via autologous saphenous vein graft. For most grafts with dual orifice, autologous Portal Vein Y-graft was used. There was no significant association between biliary reconstructive technique and biliary complications (p=0.50). Ductoplasty and anastomosis with higher biliary radicals were associated with a higher rate of biliary complications; 28% and 23%, respectively. The survival rates were 91% for biliary complications, 80% for HAT, and 92% for PVT. The overall survival rate was 88%.
Conclusions
A good outcome can be achieved with appropriate preoperative planning and modification of surgical technique. There was no association between biliary reconstructive technique and biliary and vascular complications.
Autoregression and Under-Sampled Autoregression Processes in Image and Texture Synthesis
Authors: Holton Matthew
Published: October 2023

While autoregression models have been identified as a tool for image synthesis and image processing for many years there has been limited progress in expanding the basic AR framework much beyond the initial concepts presented work published in the 1970s and 80s. In this paper I present some new developments in the use of AR models in texture synthesis. These come in two categories. Firstly the use of functional and conditional structures applied to the traditional AR regime use in scan-line texture synthesis. Secondly the use of under-sampling to both eliminate orthographic bias and support targeted texture design in the use of AR models as a general texture synthesis methodology. This is enhanced through the use of functional, conditional and image-based extensions to the under-sampled autoregression framework to expand to scope of this image and texture synthesis approach.
Predictors of parental acceptability of COVID-19 vaccination for children, especially trust in primary health care: a cross-sectional online survey from Iran
Authors: Sarbazi Ehsan , Masoudi Nazanin , Mehri Ahmad , Mehdizadeh Robab , Azizi Hosein , Pouraghaei Mahboub , Soleimanpour Hassan
Published: October 2023

BACKGROUND
Children are the most susceptible to vaccination within the people, thus it's critical to evaluate parents' and guardians' willingness to vaccinate their children. This study aims to investigate the acceptance prevalence of COVID-19 vaccination among children under 18 in Iran and its relationship with trust in the Priamry Health Care (PHC) system.
METHOD
A cross-sectional online survey of 549 Iranian parents was conducted between January and March of 2023. After adjusting for background factors, multivariate logistic regression model was applied to investigate the relationships between COVID-19 vaccination related factors and trust in PHC with parental acceptability.
RESULTS
Of 549 parents with the age range was between 19 to 67 years (median = 38 years), 358 (65.2%) were female. The prevalence of vaccine acceptance and vaccine hesitancy among parents was 257 (46.8%), and 53.2%, respectively. After adjusting for background features, child’s age (adjusted odds ratio [AOR] 0.81, 95% CI 0.71–0.91), child vaccination doses (1-dose: AOR 14.72, 95% CI 6.44–33.65, 2-dose: AOR 32.54, 95% CI 15.22–69.57), child’s disease (AOR 5.31, 95% CI 2.19–12.85), and trust in PHC (AOR 1.01, 95% CI 1.00-1.02) were associated with greater parental acceptability of COVID-19 vaccination.
CONCLUSIONS
The findings of this study suggest that the child’s age, vaccine doses received by the child, child’s diseases, and trust in PHC are significant in parental acceptability of COVID-19 vaccination for children in Iran. The results of this can be used in service planning regarding children COVID-19 vaccination.
Health risks related to metallic trace element contamination of Quaternary groundwater on the west coast of Lomé, Togo (West Africa)
Authors: ADJE K. , AHOUDI H. , OURO-SAMA K. , Dheoulaba S. Hodabalo , Gnon T. , Sadikou A. , Esso-Essinam B. Tchaa , Kissao G.
Published: October 2023

This study focuses on the physico-chemical analysis of 24 well water samples (collected in March 2023) from the Kodjoviakopé district (Lomé) and the quality assessment by comparison with the WHO standard. The analysis focused on physico-chemical parameters such as turbidity, pH and conductivity and on some metallic trace elements (cadmium, lead, iron, arsenic, chromium). It emerges from the analysis of the results that the well waters of the Kodjoviakopé district are highly mineralized, contaminated with cadmium, lead and arsenic; with strong contamination factors. In descending order of content, we note 220 times the WHO standard for arsenic; 33.92 times for the lead and 1.76 times for cadmium. The other elements analyzed showed values ​​that remain low compared to the different concentrations set by the WHO for drinking water. Overall, the well waters of the Kodjoviakopé district are contaminated with regard to the results, therefore posing a public health problem for the population of this locality. Sensitizing and educating the population on the effects of water contaminants and the policy of drinking water supply and sanitation in the area must be a priority for the country's authority.
Machine learning's model-agnostic interpretability on The Prediction of Students' Academic Performance in Video-Conference-Assisted Online Learning During the Covid-19 Pandemic
Authors: Miranda Eka , Aryuni Mediana , Rahmawati Mia Ika , Hiererra Siti Elda , Sano Dian
Published: October 2023

The Covid-19 pandemic had an immediate impact on higher education. Although online technology has made contributions to higher education, its adoption has had a significant impact on learning activities during the Covid-19 pandemic. This paper proposed a predictive model for predicting students’ academic performance in video-conference-assisted online learning (VCAOL) during Covid-19 pandemic based on machine learning approach. We investigated: Random Forest (RF), Support Vector Machine (SVM) and Gaussian Naive Bayes (GNB). There were 361 data gathered as a dataset from September 2022 to January 2023. The overall result revealed RF outperformed SVM and GNB with accuracy score of 60.27%, precision 59.46%, recall 60.27%, F1-score 59.51% and ROC AUC 87%. Understanding a machine learning model's black-box output was crucial for providing predictions that explain why and how they were developed. SHAP value of global interpretability to visualize global feature importance revealed that students' performance while using VCAOL (Performance) was the most critical attribute for predicting students' academic performance. The SHAP local interpretability bar plot revealed that ‘student academic performance was still well achieved during the learning process, despite using video conferencing during the Covid-19 pandemic’ (Performance), when Performance decreased it contributed negative impact on students’ academic performance in VCAOL during Covid-19.
Continuous Stimulation of Subcutaneously Implanted Xenogeneic Protein Thread Recruited Treg Cells and M2 Macrophages to Induce Inguinal White Adipose Tissue Browning
Authors: Jiang Shenglu , Zhu Lili , Xu Yukun , Liu Zhao , Cai Jialin , Zhu Tao , Fan Qing , Zhao Zhenxiong
Published: October 2023

Brown adipose tissue and beige adipose tissue have emerged as potential targets for obesity intervention, but the present strategies targeting at inducing the browning of white adipose tissue are not satisfactory. Xenogeneic protein thread implantation is an attempt of complementary and alternative medicine in the field of obesity treatment, but the specific effect or mechanism has not been well validated. This study examined the corrective effect of subcutaneous catgut or absorbable polymer thread embedding on obesity and metabolic syndrome, and aimed to explore the mechanism of subcutaneous white adipose tissue browning after catgut embedding. Embedding of catgut reduced weight gain and improved metabolic status in ob/ob mice. Browning of bilateral inguinal WAT was induced after catgut embedding, with massive infiltration of Treg cells and M2 macrophages in the tissue slices of fat pads. IL-10 and TGF-β released by Treg cells targeted the macrophages and the induced M2 macrophages promoted the secretion of norepinephrine in sympathetic nervous system, leading to the activation of β3-AR related pathways in adipocytes. This study demonstrates abdominal subcutaneous catgut embedding has the potential to combat obesity through inducing the browning of WAT mediated by the infiltrated Treg cells and macrophages.
An Analytical Methodology of Rock Burst with Fully Mechanized Top- coal Caving Mining in Steeply Inclined Thick Coal Seam
Authors: Shan Pengfei , Yan Zhongming , Lai Xingping , Xu Huicong , Hu Qinxin , Guo Zhongan
Published: October 2023

Rock burst disaster is still one of the most serious dynamic disasters in coal mining, seriously restricting the safety of coal mining. The b value is the main parameter for monitoring rockburst, and by analyzing its changing characteristics, it can effectively predict the dangerous period of rockburst. This article proposes a method based on deep learning that can predict rock burst using data generated from microseismic monitoring in underground mining. The method first calculates the b value from microseismic monitoring data and constructs a time series dataset, and uses the dynamic time warping algorithm (DTW) to reconstruct the established b value time series. A bidirectional short-term and short-term memory network (BiLSTM) loaded with differential evolution algorithm and attention mechanism was used for training, and a prediction model for the dangerous period of rock burst based on differential algorithm optimization was constructed. The study used microseismic monitoring data from B1 + 2 fully mechanized mining face and B3 + 6 working face in the southern mining area of Wudong Coal Mine for engineering case analysis. The commonly used residual sum of squares, mean square error, root mean square error, and correlation coefficient R2 for time series prediction were introduced, which have significant advantages compared to basic LSTM algorithms. This verifies that the prediction method proposed in this article has good prediction results and certain feasibility, and can provide technical support for the prediction and prevention of rock burst in steeply inclined thick coal seams in strong earthquake areas.
Household economic losses and community knowledge determine control strategies: A case of cerebral coenurosis in small ruminants in Northern Tanzania
Authors: Nzalawahe Jahashi Saidi , Mlanzi Dunia Saidi , Lupindu Athumani Msalale , Ngowi Helena , Eisler Mark Charles
Published: October 2023

Background
Cerebral coenurosis is caused by Taenia multiceps and affects sheep and goats worldwide and has zoonotic implications. Information on the financial burden, understanding of the disease and control practices by farmers may inform control strategies.
Methods
A cross-sectional study was conducted in Babati and Ngorongoro Districts, Tanzania, to determine the economic losses, farmers’ knowledge, attitude and practices on control of Taenia multiceps coenurosis in small ruminants. A structured questionnaire was administered to 558 households to collect data in the study area.
Results
The study showed that the estimated total annual direct and indirect economic loss encountered for the past one year were TZS 121.4M (USD52.3K), and TZS 1.4M (USD 609.49) for Babati and TZS 642.4M (USD 276.8K) and TZS 14.2M (USD 6.1 K) for Ngorongoro respectively. The total annual loss was TZS 122.8M (USD 52.9K) for Babati and TZS 656.5M (USD 282.9K) for Ngorongoro District. The average annual household financial loss for 2019 was TZS 356.8K (USD 153.83) for Babati and TZS 3.1M (USD1.3K) for Ngorongoro District. The questionnaire revealed that coenurosis was the most common disease of small ruminants to 50.9 - 78% of respondents followed by helminthosis and CCPP. About 85.4 – 96.7% of respondents were aware of coenurosis from their own experience while 0 - 0.6% of the respondents had no knowledge of it at all. Based on a summated index scale, the average knowledge score was 5.85 out of 16 (36.6%) which implies a low level of knowledge on coenurosis. A total of 94.5% of respondents showed willingness to own, coordinate, participate in the control plans and pay the control costs. The average attitude score on 8-point Likert scale was 32.5 out of 40. Respondents sold coenurosis suspected animals (41.4%), slaughtered them for home consumption (25.3%) or opted for treatment (33.3%).
Conclusion
Given the economic loss, favourable attitude on coenurosis control participation, delivery of an educational package on epidemiology and control of coenurosis to livestock keepers may be expected to trigger a collaborative and sustainable intervention.
Does faeces excreted by moxidectin-treated sheep impact coprophagous insects and the activity of soil microbiota in subtropical pastures?
Authors: Hentz Susana Gilaverte , Reyes Felix Guillermo Reyes , Kaschuk Glaciela , de Oliveira Leandro Bittencourt , Fernandes Maria Angela Machado , Monteiro Alda Lúcia Gomes
Published: October 2023

Moxidectin (MOX) is used to control helminth parasites in ruminant livestock being released through faeces into the environment. We aimed at evaluating the impact of MOX-contaminated sheep feces on soil coprophagous insects, microbial biomass, and activity. In a field experiment, faeces from MOX-treated rams (subcutaneous dose of 0.2 mg kg-1 body weight) and faeces from non-treated rams were placed on an animal-free pasture, protected or not from rain, for 88 days. Coprophagous insects were captured, identified, and counted, while N mineralization, and C e N contents were monitored. In a controlled experiment, faeces from non-treated animals were amended with MOX concentrations ranging from 75 to 3,000 ng MOX kg-1 faeces, mixed with soil from an animal-free pasture, and incubated for 28 days. Soil microbial biomass, respiration, and culture-microbe counting were determined. Diptera, Hymenoptera, Isoptera, and Coleoptera were equally found in faeces from both MOX-treated and non-treated animals. Faeces from MOX-treated animals had more N and degraded faster than those from non-treated animals. Even the lowest MOX concentration decreased soil microbial biomass, respiration, and N mineralization. Despite not harming coprophagous insects, the addition of MOX to feces from drug-free sheep has a negative impact on soil microbial biomass and activity.
Transcriptome analysis of the mechanism to ginsenoside inhibiting on Botrytis cinerea
Authors: Yang He , Xie Lu , Jin Hongyan , Di Peng , Lu Baohui , Chen Xiaolin , Wang Yingping , Xu Yonghua
Published: October 2023

Background: The control of tomato gray mold mainly relies on chemical fungicides, which can easily cause pesticide residues and environmental pollution. Therefore, a new fungicide for the control of tomato gray mold is urgently needed. Ginsenosides can inhibit the growth of diseases and are safe and non-toxic. To reveal the antibacterial mechanism of ginsenoside against Botrytis cinerea, and to provide theoretical basis for the development of ginsenoside plant pesticide.
Results: Ginsenoside showed significant inhibitory activity against B. cinerea, and the inhibition rate reached 95.45% at 1 mg·mL-1. Transcriptome results showed that there were 21 DEGs in the 3 stages, among which 17 genes were upregulated in the treatment group. Bioinformatics analysis showed that the DEGs are mainly related to metabolic pathways such as Metabolism, Cenetic Information Processing, Environmental information Processing and Cellular Processes. Quantitative real-time PCR results demonstrated the accuracy of transcriptome data. Ginsenosides seriously damaged the ultramicrostructure of B. cinerea, resulting in the exosmosis of contents, the formation of a large number of cytoplasm cavities, and the change and degradation of mitochondrial structure.
Conclusion: Transcriptomic analysis indicated that ginsenoside may inhibit the growth of B. Cinerea by decreasing the stability of cell membrane or cell wall, and B. Cinerea may respond to the stress caused by ginsenoside by increasing ergosterol synthesis and ABC transporter expression.
Optimizing a Interpretable Diagnostic Model for Colorectal Cancer Based on Yin Deficiency Pattern Characteristic Genes Using 21 Machine Learning Algorithms and Bayesian Opitimization
Authors: Li Yuqing , Huang Zhongquan , Liu Xiang , Xu Shun , Chen Zhuoni , Zhang Ning , Lin Rongrong , Cheng Hongyan , Li Geng , Liang Zhiwei
Published: October 2023

In this study, we aimed to identify a core set of Yin Deficiency Pattern (YDP) genes for predicting colorectal
cancer (CRC) and to construct reliable machine learning models optimized by Optuna. Comprehensive analysis was performed
on nine datasets, totaling 1,680 samples. A CRC diagnostic prediction model was developed by comparing 21 machine
learning classification models with Optuna hyperparameter optimization and validated across six independent external
cohorts. Additionally, the expression patterns of the core diagnostic genes were experimentally validated.
Linear Discriminant Analysis (LDA), along with four other machine learning models (please specify these models), ranked as the top five performing models
across six cohorts, demonstrating superior performance with AUC values exceeding 0.99 and all other performance metrics surpassing 0.899. This study marks
the first utilization of four specific novel machine learning models (again, please specify these models) in CRC diagnosis.
The robust performance of the top models across multiple external validation sets underscores the reliability and generalizability
of our diagnostic model. These results hold potential implications for the development of personalized medicine approaches
in CRC treatment, offering a new avenue for early detection and prognosis improvement.
Evidence of P. vivax in Northern Kenya, an emerging malaria control threat; An incidence report from the outcome of the mid-2023 epidemic response survey
Authors: Kimani Francis T. , Thiong’o Kelvin , Karani Lewis , Otinga Maureen A. , Ombati Mary , Gesusu Nemrod , Onchieku Noah M. , Kamau Luna , Matoke Damaris
Published: October 2023

Background: Malaria mortality and morbidity in Kenya has all along been largely due to Plasmodium falciparum infections with no cases attributed to P.vivax. The epidemiology in northern Kenya counties is traditionally classified as zero to low-risk transmission zones. A recent upsurge in febrile illnesses was reported in the counties of Marsabit, Mandera and Turkana, in mid-2023 which required an emergency pandemic response by the county and national health teams. In addition to possible viral infection that had featured in these areas previously, malaria disease was also investigated as part of the response. An analysis determining the presence of Plasmodium infection and the species present in this rapid response are hereby reported.
Methods: A total of 89 blood samples were collected from patients suspected of malaria in the Northern Kenya counties, after which they were analyzed. Positivity and speciation was performed using 18S rRNA and qPCR TaqMan probes with species specific primers
Results: From 3 health facilities in Marsabit, Mandera and Turkana counties a total of 24, 50 and 15 dried blood spot samples were received respectively. There were 11, 40 and 15 Plasmodium positive samples in the three county health facilities respectively. This translated to a total positivity of 74.2%. Speciation analysis was done for the four common plasmodium species. This analysis recorded a total of 60 P. falciparum positive samples, 2 samples with a mixed infection of P. malariae and P. falciparum, 2 P.vivaxmono infection samples, and 2 P. vivax P. falciparum co-infected samples. No P.ovale was observed in any of the facilities. Three of the P.vivax infections were in Marsabit county while the remaining case was from Mandera County translating to an incidence rate of 12.5% (3/24)and 2%(1/50) respectively. No P.vivax infection was identified in Turkana county.
Conclusion: The findings of this analysis show that the incidence of malaria from the response sites was quite high, at 74.2%. Although the burden of P. vivax in these counties is undetermined, the presence of the observed proportions in such a small sample size is an indicator of an underlying problem of cases that are rarely diagnosed in a clinical setting and may often be asymptomatic. The presence of Anopheles stephensi that was recently identified for the first time in Kenya in the same study region, implies the potential expansion of a highly competent vector here, which could dramatically enhance the transmission of P. vivax and reverse all the malaria control gains made over the years.
Computer Model of Pump-Well-Reservoir System Based on the New Concept of Imitational Modeling of Dynamic Systems
Authors: ALIEV F. A. , MOVAHEEDI ZABIHULLAH , JAMALBAYOV M. A. , VALIYEV N. A. , HAJIYEVA N. S. , SHOKRI ALI
Published: October 2023

The concept of imitational modeling of dynamical systems is being developed. The fundamentals, terms of the concept and principles of creating a simulation of a physical process are outlined. The proposed concept is applied to the integrated modeling of the process of developing a volatile oil reservoir operated by a rod-pump well in the "pump-well-reservoir" system. The "pump-well-reservoir" model developed on the principles of the concept, taking into account the presence of the annulus and the fluid flow between the annulus and the lifting pipe, was used for a numerical study of the operation of the system. The dependence of the flow rate of a rod pump well and the degree of filling of the pump cylinder on the swing number was studied. It has been established that with an increase in the swing number, the pump flow and the filling degree of the cylinder increase up to a certain point, after which the pump flow almost does not change, and the degree of filling decreases sharply. Full filling of the rod pump cylinder does not always coincide with the maximum flow rate of the well. In such cases, the optimal mode can only be achieved by switching to a periodic regime of the pumping.
WITHDRAWN: A new perspective on the SDGs nexus: ethnobiology’s contribution
Authors: Arrivabene Alexandre , Lasic Lou , Blanco Julien , Carrière Stéphanie M. , Ladio Ana , Caillon Sophie , Porcher Vincent , Teixidor-Toneu Irene
Published: October 2023

Progress achieving the Sustainable Development Goals (SDGs) is insufficient at global scale. A thorough understanding of SDG synergies and trade-offs is needed to enhance their achievement, but such understanding is still limited. Ethnobiology has been proposed as a discipline able to contribute to sustainability and finely-tuned to study these interlinkages. In this study, we conducted a systematic review of all articles published by the Journal of Ethnobiology since 2015 (SDGs’ adoption year) and evaluated if and how they address one or more SDGs. We asked the following questions: 1) Do articles mention explicitly or implicitly the SDGs? 2) What connections does ethnobiology establish between them? 3) How do articles define sustainability? And, (4) whether articles dealing with sustainability are more inclusive to non-academics. Our study shows that ethnobiology implicitly addresses almost all SDGs and focuses particularly on the connectedness of SDGs 1–3 and 15. Biodiversity’s understanding (SDG 15) provides the basis for culture and Indigenous and local knowledge and ensures communities’ food security (SDG 2), health and well-being (SDG 3), and prosperity (SDG 1). We observe that ethnobiology studies sustainability in paradigm ethics of Indigenous peoples and local communities rather than that of the global sustainability agenda, but that local actors are still not commonly engaged in knowledge co-construction processes. While ethnobiology can provide an analysis of the SDGs complimentary to that of sustainability science and be a motor of transformative change, this potential is not fully realized because of a persisting decoupling between place-based research and global sustainability frameworks.
Properties and structural features of native and modified proteins of concentrates from white and brown rice
Authors: Kolpakova V. V. , Fan Q. Ch. , Gaivoronskaya I. S. , Chumikina L. V.
Published: October 2023

The physicochemical properties and structural features of proteins of concentrates (PC) from white and brown rice are described. Differences in a degree of proteolysis and the relationship between the functional and technological properties of proteins and their structure were established. Proteins from white rice had lower molecular weights (MW) than proteins from brown rice: 1.3–199.5 kDa versus 1.5–251.1 kDa. Most proteins were grouped in three low-molecular-weight fractions (МW 11.7–27.5 kDa) in PC from white rice and in one fraction with the high molecular weight (182–251.1 kDa) in PC from brown rice. In the process of hydrolysis, the MW of proteins (high-molecular-weight) of PC from white rice decreased from 199.5 to 120.2 kDa with generation of peptides with a molecular weight of <1.3 kDa, while the MW remained unchanged upon hydrolysis of proteins of PC from brown rice. In the composition of PC from white rice, flavonoids interacted with protein fractions with molecular weights of 131, 10, and 4.0 kDa; while in PC from brown rice, they interacted with only one fraction with a molecular weight of 216 kDa. The quantity of flavonoids in PC from white rice was 2.3 times less than that in PC from brown rice. Elements of protein secondary structure were established for PC: α–helix, 310 — helix, β-structure, β-bends, and irregular shape. Proteolysis of proteins was accompanied by a decrease in the number of α-helices, increase in the proportion of β-structures and irregular regions, weakening of the hydrophobic properties of proteins and an increase in the number of S–S bonds; PC from brown rice was characterized by a higher content of –СН2  groups from the flavonoid family, as well as by a higher degree of unsaturation of groups of benzene nuclei, ketone and ester groups. A negative correlation was found between the foaming ability of PC and the upper boundaries of molecular weights (r = — 0.95), quantity of high-molecular weight proteins (r = — 0.80) and aggregation constants, and a positive correlation (r = + 0.8) with the number of S–S bonds. The high foaming ability is interrelated with proteins with a molecular weight of no more than 120 kDa. The results are intended to regulate the functional properties of protein products based on the characteristics of the physicochemical properties of native and modified proteins.
Regional specificity of Algerian olive oil
Authors: Ghernoug H. , Chernukha I. M. , Utyanov D. A.
Published: October 2023

Algeria is the ninth biggest producer of olive oil in the world and the fourth biggest producer of table olives. In 2023, 868,754 tons of this product were produced there. The paper examines the regional and climatic special features of olive oil (OO) production with detalization by this product grown in Algeria. The fatty acid composition of OO produced in various regions of the country was studied in comparison with oil from Spain and Italy. The positive effect of diets and medicines based on OO is described. The prospects of the development of target products based on protein-fat modules with the use of OO from certain Algerian regions are indicated.
Justifying the use of structure-forming agents to increase storability of confectionery products with the foamy structure
Authors: Kondratev N. B. , Rudenko O. S. , Kazantsev E. V. , Belova I. A. , Petrova N. A.
Published: October 2023

Confectionery products with the foamy structure such as pastila and zefir (Russian marshmallow-like confectioneries) are in demand among various consumer groups. The expansion of the range and sales markets requires ensuring quality of such products during their transportation, storage, as well as increasing their shelf life. The patterns of change in quality indicators allow establishing additional requirements for them to improve storability of such products. Moisture transfer processes are predominant during storage of confectionery products with the foamy structure and define their hardening or moistening. Therefore, it is necessary to evaluate the influence of various factors on quality indicators during storage of zefir. Studies have been carried out to determine the influence of various structure-forming agents, such as agar, pectin, gelatin, on the direction and rate of moisture transfer processes during storage of zefir samples. The possibility of using the method of infrared spectroscopy for assessing quality of structure-forming agents during incoming inspection is shown. The mass fraction of moisture in zefir made using agar decreased by 3.5% after 10 weeks of storage at a temperature of 18°C. During this period, the mass fraction of moisture in zefir made using pectin as a structure-forming agent decreased by 2.5%, while in zefir prepared on the basis of gelatin, the mass fraction of moisture decreased only by 1.2%. Thus, the addition of gelatin makes it possible to reduce the rate of moisture transfer by approximately 2–3 times. The low moisture transfer rate of zefir is due to the water-holding properties of the protein structure of gelatin. Diffusion coefficients were calculated to predict the rate of moisture transfer processes in zefir samples made using various structure-forming agents and stored at different temperatures. The lowest diffusion coefficient was determined in zefir made with the addition of pectin, while the highest diffusion coefficient was in the sample based on gelatin. However, zefir made from gelatin had the lowest actual moisture transfer rate, since the gradient of the water activity was minimal (7.6%). With an increase in the storage temperature of zefir made with the addition of various structure-forming agents from 18°C to 28°C, the rate of moisture transfer increased. In zefir produced on the basis of agar, this indicator increased by 2.7 times, in the sample from pectin by 3.0 times; in zefir based on gelatin by only 1.5 times. The results obtained make it possible to predict the risks of changes in zefir quality during storage.
Methodology for the development of identification criteria of stone fruit brandy
Authors: Krikunova L. N. , Tomgorova S. M. , Zaharova V. A.
Published: October 2023

The need to develop identification criteria for fruit brandy is connected with the prevention of the sale of counterfeit products on the Russian alcohol market. Due to the variety of factors affecting the final product, the solution to this problem requires the use of a methodology based on an integrated approach. The work is devoted to its first stage — the assessment of the influence of the biochemical composition of fruit stone raw materials, as well as various technological factors on the formation of essential (identification) characteristics of products. Fresh fruits of apricots, cherry plums, cherries, dogwood and plums, as well as samples of fermented raw materials were used as objects of research. The biochemical composition of fresh fruits was assessed by the content of sugars, free organic acids, amino acids and pectin substances. It has been found that the values of all main indicators of the biochemical composition varied widely in the samples of initial raw materials. At the same time, significant differences were noted between the types of fruit raw materials in the content of free amino acids (dogwood, cherry plum up to 0.08% and 0.12%, respectively; cherry, plum and apricot up to 0.19–0.30%) and pectin substances (cherry, apricot up to 0.6–0.8%; cherry plum, dogwood, plum up to 1.2–1.3%). The following factors were studied in the work as technological factors: a method of primary processing of raw materials (obtaining pulp or juice extraction); a maceration method — without enzyme preparations and with treatment with enzyme preparations; a fermentation method — without fermentation activators and using fermentation activators. It has been established that the method for primary processing of raw materials affects the concentration of methanol, esters and higher alcohols in fermented raw materials. The use of fermentation activators contributes to an increase in the concentration of higher alcohols and esters in them by almost 2 times, and the use of individual complex enzyme preparations — by 16% and 80%, respectively. It has been shown that the methodology for developing identification criteria for fruit vodkas at the first stage should include an assessment of the physico-chemical composition of initial raw materials and individual technological factors at the stage of preparing them for distillation.
Phases of cold holographic QCD: Baryons, pions and rho mesons
Authors: Kovensky Nicolas , Poole Aaron , Schmitt Andreas
Published: October 2023

We improve the holographic description of isospin-asymmetric baryonic matter within the Witten-Sakai-Sugimoto model by accounting for a realistic pion mass, computing the pion condensate dynamically, and including rho meson condensation by allowing the gauge field in the bulk to be anisotropic. This description takes into account the coexistence of baryonic matter with pion and rho meson condensates. Our main result is the zero-temperature phase diagram in the plane of baryon and isospin chemical potentials. We find that the effective pion mass in the baryonic medium increases with baryon density and that, as a consequence, there is no pion condensation in neutron-star matter. Our improved description also predicts that baryons are disfavored at low baryon chemical potentials even for arbitrarily large isospin chemical potential. Instead, rho meson condensation sets in on top of the pion condensate at an isospin chemical potential of about 9.4\, m_\pi9.4mπ. We further observe a highly non-monotonic phase boundary regarding the disappearance of pion condensation.
Optimizing the utilization of government-owned tangible assets through managing institutional factors in Indonesia
Authors: Faridah  , Rahman Lubis Abdul , Diantimala Yossi , Ridwan
Published: October 2023

This study aims to examine whether the institutional factors – governance, asset knowledge, internal control system, and competencies – optimize the utilization of provincial, regency, and municipal governments’ tangible assets in supporting public services. In contrast to previous research, which employed Sharia ethics as exogenous variables, this study includes Sharia ethics as a moderating variable in the model. Sharia ethics is one specific factor in implementing Sharia principles by the government that applies Islamic law in Indonesia. The province of Aceh, with all its regencies and municipals, is the only province that applies Islamic principles in running its government. Primary data were collected using a questionnaire sent to 285 provincial and district government asset managers using a Google form; 229 questionnaires were returned. Structural equation modelling (SEM) was employed to analyze the complex relationships and the hypotheses. The results reveal that institutional factors are not strong enough to optimize the utilization of tangible assets without having deep Sharia ethics. It meant that Sharia ethics is necessary for strengthening the relationship between the institutional factors and the optimization of government asset management in provincial, regency, and municipal governments. The results provide recommendations for provincial, regency, and municipal governments to develop appropriate and reasonable regulations and standards for optimizing asset management within the Aceh government.
Climate Legislation and Legal Relations: Current State and Development Prospects Within the National Security Framework
Authors: Getman Anatolii , Anisimova Hanna
Published: October 2023

The article is devoted to the scientific and theoretical analysis of the current paradigm of development of national climate legislation and legal relations within the Europeanization framework. The subject of the study is the analysis of international legal norms, national legislation and judicial practice in the aspect of adaptation to climate change. The purpose of the article is to provide a comprehensive, integrated study and analysis of the provisions of legal acts from the standpoint of the formation of climate legal relations in the context of ensuring national security. The chosen goal has led to the setting and solution of such tasks as: a) consideration of the theoretical and methodological foundations of the emergence and formation of climate legal relations; b) study of the current provisions of environmental and legal doctrine with regard to the need for adaptation to climate change; c) outlining the ways to improve and further systematize national climate legislation in the context of European integration and sustainable development. The methodological basis of the study is formed by general scientific and special methods of cognition of legal phenomena: dialectical, historical and legal, formal and logical, systemic and structural, theoretical and prognostic, comparative legal, formal and legal, interpretation of legal provisions, legal modeling, etc. The author examines the peculiarities of the formation of climate legal relations which are closely related to environmental and security legal relations, along with energy, agricultural, etc. It is proved that they are gradually being formed and distinguished into an independent interdisciplinary institution of environmental, energy, agrarian, environmental security law, as well as international and EU law, which is likely to become an independent branch of public law in the future. The article emphasizes that the development and implementation of national climate policy (especially in the context of regulatory and legal support) should be fully based on the fundamental provisions of the EU climate policy. The author considers the issues of judicial protection of climate human rights and humanity in case of non-fulfillment of policy and program documents and non-compliance with international obligations by the State. The problems of compensation for climate damage and the impact of climate change on migration processes (climate migration) are outlined. It is argued that modern climate policy should be built on a cross-sectoral level to ensure the preservation of ecosystems, landscape and biological diversity, accelerate the transition to low-carbon energy saving systems, reduce dependence on fossil fuels, expand the use of renewable energy sources, improve energy efficiency, and increase the adaptive potential of natural resources to climate change.
Application of machine learning in river water quality management: a review
Authors: Cojbasic Sanja , Dmitrasinovic Sonja , Kostic Marija , Turk Sekulic Maja , Radonic Jelena , Dodig Ana , Stojkovic Milan
Published: October 2023

Machine learning (ML), a branch of artificial intelligence (AI), has been increasingly used in environmental engineering due to the ability to analyze complex nonlinear problems (such as ones connected with water quality management) through a data-driven approach. This study provides an overview of different ML algorithms applied for monitoring and predicting river water quality. Different parameters could be monitored or predicted, such as dissolved oxygen (DO), biological and chemical oxygen demand (BOD and COD), turbidity levels, the concentration of different ions (such as Mg2+ and Ca2+), heavy metal or other pollutant's concentration, pH, temperature, and many more. Although many algorithms have been investigated for the prediction of river water quality, there are several which are most commonly used in engineering practice. These models mostly include so-called supervised learning algorithms, such as artificial neural network (ANN), support vector machine (SVM), random forest (RF), decision tree (DT), and deep learning (DL). To further enhance prediction power, novel hybrid algorithms, could be used. However, the quality of prediction is not only dependent on the applied algorithm but also on the availability of previously mentioned water quality parameters, their selection, and the combination of input data used to train the ML model.