bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of a nomogram model for predicting peritoneal metastasis in gastric cancer based on ferroptosis-relate genes and clinicopathological features
Authors: Sun Xiaotong , Duan Kaipeng , Shen Xiaochun , Dong Chao , Zhou Yajing , Chen Tao , Li Weikang , Li Peiyuan , Wang Pengbo , Li Dongbao , Zhou Jin
Published: October 2024

Background
Approximately 60% of gastric cancer deaths are caused by gastric cancer peritoneal metastasis (GCPM). GCPM lacks effective early diagnosis methods. We found that ferroptosis-related genes (FRGs) play a vital role in GCPM, but whether FRGs can predict GCPM is still unknown.
Methods
The RNA-Sequencing and clinical data of gastric cancer (GC) patients were downloaded from GSE62254. They were randomly divided into an experimental group and a validation group in a ratio of 3:2. Cox analyses and least absolute shrinkage and selection operator (LASSO) regression were applied in the experimental group to construct a six FRGs-based nomogram model. We evaluate the predictive value of this nomogram for GCPM in both the experimental and validation groups. 115 clinical samples were collected to verify the accuracy of the prediction model using immunohistochemistry (IHC).
Results
LASSO regression calculated six FRGs along with their coefficients, risk score was calculated for each patient. Univariate and multivariate logistic analyses found that the risk score and pathological stage were significantly associated with GCPM. The ROC curve indicated that the risk score had good predictive ability for GCPM (AUC > 0.7). Combining the risk score and TNM stage significantly enhanced the predictive power (AUC > 0.8). We constructed a nomogram with two features: risk score and TNM stage. The Decision Curve Analysis (DCA) curve showed good clinical application. The IHC results from the 115 clinical samples were consistent with the above results.
Conclusion
A ferroptosis-related gene signature was constructed and has impressive predictive values for the peritoneal metastasis of gastric cancer.
Prediction of surface roughness based on the Multi-Input CNN-MHA in milling
Authors: Guo Miaoxian , Wei Shouheng , Han Chentong , Guo Weicheng , Huang Zhiwen
Published: October 2024

In the realm of manufacturing, the prediction of surface roughness during milling processes is of paramount importance as it directly influences product quality, tool life, and manufacturing efficiency. However, current surface roughness prediction methods exhibit limitations, particularly in terms of feature extraction and prediction accuracy. This study introduces a novel surface roughness prediction method based on a hybrid neural network, which uses time-frequency image and feature vector as multiple inputs, and integrates convolution and multi-head self-attention (MHA) mechanism. Initially, the input signals are subjected to noise reduction using Variational Mode Decomposition (VMD), which effectively extracts cleaner signal features. Subsequently, Continuous Wavelet Transform (CWT) is applied to generate time-frequency maps of the signals, providing a rich source of information for the Convolutional Neural Network (CNN). Furthermore, the Multi-Head Attention mechanism is incorporated to enhance the model's comprehension of global signal characteristics. A multi-input hybrid neural network model is constructed, combining CNN with MHA, and utilizing deep learning techniques to decipher complex relationships between features, thereby achieving high-precision prediction of surface roughness. The results show the proposed method significantly outperforms single-input models in predictive accuracy, with a root mean square error (RMSE) of 0.0349 and a maximum absolute error (MaxAE) of 0.0683.
Targeting Phospholipids: Fingolimod's Antibacterial Mechanism Against Staphylococcus aureus
Authors: Shang Yongpeng , Huang Yu , Meng Qingyin , Yu Zhijian , Wen Zewen , Yu Fangyou
Published: October 2024

It’s urgently needed to find new repurposed antibacterial drugs as the desired novel choices to counter biofilms and persister of gram-positive bacteria. Several reports have supported that Fingolimod, which was approved by FDA as a novel drug for the treatment of relapsing multiple sclerosis, can kill the bacteria by selectively disrupting the cell membrane of bacteria. However, the action mode and mechanism of Fingolimod against gram-positive bacteria remains elusive. Our data indicated that Fingolimod exerted the bactericidal activity against a wide spectrum of gram-positive bacteria, including Staphylococcus aureus, Enterococcus faecalis, Streptococcus agalactiae et al. Moreover, Fingolimod could significantly eliminate the persister, inhibit biofilm formation, eradicate mature biofilm in vitro against S. aureus. Fingolimod rapidly eradicated S. aureus by pH-dependent disruption of the bacterial cell membrane's permeability and integrity, with its minimum inhibitory concentration (MIC) increasing up to 16-fold in response to elevated concentrations of phospholipids CL, PG, and PE. After four months of Fingolimod exposure, the MIC values of S. aureus showed a slight increase, and three genetic mutations related to phospholipid metabolism—PhoP, AcpP, and PhoU2—were identified in Fingolimod-induced clones, suggesting that Fingolimod may disrupt the cell membrane by targeting phospholipids. Overall, Fingolimod kills S. aureus by disrupting the bacteria membrane and targeting the phospholipids within the cell membrane. This study first reveals that Fingolimod kills S. aureus by targeting cell membrane phospholipids, a mechanism similar to cationic bactericides.
The alternative NF-κB RelB subunit is a novel critical sensor of lipid metabolism to promote tumor development
Authors: Becquard* Thomas , Benatar* Clara , Bretot Charles , Eluard Baptiste , Bordereaux Didier , Thirouard Laura , Hammoutene Adel , Montagne Aurelie , Ransy Céline , Alves-Guerra Marie-Clothilde , Caradeuc Cédric , Cagnard Nicolas , Boissan Mathieu , Giraud Nicolas , Bouillaud Frédéric , Bertho Gildas , Paradis Valérie , Chiron David , Dentin Renaud , Prip-Buus Carina , Baud Véronique
Published: October 2024

Cancer cells reprogram their metabolism to fulfill their high energetic demand. Lipid metabolism is most often reprogrammed for cancer cell survival and tumor development. The role of alternative oncogenic NF-κB/RelB subunit in the reprogramming of lipid metabolism in cancer is unknown. Here we report that RelB plays a central role at the crossroads of lipid storage and liberation of fatty acids from the lipid droplets to feed the fatty acid oxidation (FAO) and mitochondrial energetic metabolism. High RelB expression defines a subset of hepatocellular carcinoma (HCC) patients and cell lines with a peculiar gene expression profile enriched in lipid catabolic-related genes, including lipases. Functional studies revealed that high RelB activation controls the expression of major lipolytic lipases including adipose triglyceride lipase (ATGL) and monoglyceride lipase (MAGL), and impacts on HCC cell survival, migration, and tumor development in vivo. Altogether, we uncovered that RelB is a central regulator of the lipid metabolism plasticity and an energy homeostasis sensor in cancer cells.

*Thomas Becquard and Clara Benatar are co-first authors.
Influence of growth temperature on development and yields in a medium late and late Scandinavian cultivar of potato
Authors: Mølmann Jørgen A.B. , Johansen Tor J.
Published: October 2024

With more available meteorological field-sensors for agriculture, there is an increasing need for local-adapted growth models. Especially for cultivation of crop cultivars in areas with marginal temperatures and varying light conditions. The temperature response was therefore studied in climate-controlled growth chambers under constant temperatures from 9 to 21°C under a natural 24 h photoperiod in greenhouse in Tromsø (69.7°N, 18.9°E), Norway, for the potato cultivars Gullauge (medium late) and Mandel (late). There was a strong response in both cultivars to temperature, with reduced developmental time from emergence and leaf formation to visible flower buds at increasing temperature intervals. Developmental rates were higher for Gullauge than for Mandel. Shoot dry matter weight per plant was highest at 12°C and 15°C for both cultivars, though with higher shoot biomass at harvest in Mandel than Gullauge. Tuber yields and tuber dry-matter percentages for both cultivars was higher for Gullauge than for Mandel. Fresh weight yields and dry matter percentage for both cultivars were highest at 15°C. Optimum temperature for above-ground vegetative development-rate was estimated to be 24.0°C and 22.6°C, for Gullauge and Mandel respectively. In contrast, the respective temperature optimums for developing tuber dry matter content were 16.6°C and 15.6°C. Lower temperature optimums for below-ground development makes potato a suitable crop for temperate and boreal climates with cooler autumn temperatures. Different temperature optimums for above- than below-ground development needs to be considered when developing temperature-based growth models for potato cultivars from emergence to tuber yields.
Optimized Intention-adaptive Graph Neural Network for Robust Failure Diagnosis of Microservice System Using Multimodal Data
Authors: Kumar N. Naveen , Suresh S. , Balamurugan S. , Kumar P. Seshu
Published: October 2024

Automatic failure diagnosis is critical for large-scale Microservice systems. Most failure detection methods available today only employ single-modal data (logs, traces, or metrics). It carries out an empirical study using actual failure scenarios to show that the integration of several data sources (multimodal data) leads to a more precise diagnosis. Effectively expressing these data and handling unequal failures remain challenging. The suggested paper, MD-RFD-MS-IGNN, proposes Multimodal Data for Robust Failure Diagnosis of Microservice System using Optimized Intention-adaptive Graph Neural Network. First, GAIA dataset is used to collect the input data. To implement this, the input data is pre-processed using Adaptive Kernel Learning Kalman Filtering (AKLKF) and it removes the N/A (not applicable) values or empty row from the collected data; then the Pre-processed data are feature extracted using Automated Tunable Q Wavelet Transform (ATQWT)is used to extract spatial features like strace, log, and metric. Subsequently, the gathered data is loaded into an Intention-adaptive Graph Neural Network (IGNN) to efficiently classify failure detection into categories such as file missing, system stuck, process crash, and access refused. Generally speaking, optimization algorithms that may be modified to get the optimal parameters for accurate failure classification are not expressed by IGNN. In order to optimize Intention-adaptive Graph Neural Networks, which precisely identify Microservice system failure, Human Evolutionary Optimization (HEO) was used. Next, the suggested MD-RFD-MS-IGNN is put into practice, and performance measures including F1-Score, Precision, and Recall are examined. When analysed through existing techniques such as Automated functional and robustness testing of microservice architectures (AFRT-MA-GCM), MTG_CD: multi-scale learnable transformation graph for fault classification and diagnosis in microservices (MTG-FCDM-GCN), and robust failure diagnosis of microservice system through multimodal data (RFD-MS-MD-GNN), the performance of the MD-RFD-MS-IGNN approach achieves 17.30%, 23.39%, and 32.41% higher F1-Score.
Sentence representation-based text matching algorithm using prompt learning and contrastive learning
Authors: Wu Liang , Li Xiang , Ma Ping , Hu Changhao
Published: October 2024

With the recent global popularity of ChatGPT (Chat Generative Pre-trained Transformer),it signifies that the era of natural language processing (NLP) technology flourishing in human society has arrived. As a fundamental yet indispensable component of NLP technology, text matching techniques have permeated various NLP application scenarios, such as search engines, dialogue systems, large-scale text deduplication, and recommendation systems. In the era of deep learning, particularly after the emergence of the pre-trained language model BERT (Bidirectional Encoder Representations from Transformers), representation-based text matching algorithms built on BERT and its variants have become one of the mainstream text matching algorithms. However, the effectiveness of these algorithms is limited by the low quality of sentence vectors generated by the original BERT. In 2021, the self-supervised contrastive learning algorithm SimCSE was introduced, which significantly improved the quality of sentence vectors encoded by BERT. However, the batch-wise negative sampling method used by SimCSE, due to its strong randomness, may lead to negative samples with low relevance, thereby limiting the amount of information the model can learn. This paper proposes a negative sample construction algorithm based on prompt learning, called PLNSC, which constructs a masked language modeling task. It leverages the powerful language capabilities of pre-trained language models to generate reasonable negative sample representations for each sentence, enabling the model to learn richer information during the contrastive learning process, thereby enhancing the sentence representation capability of the model. This approach improved the average performance of three baseline models across five datasets by 1.93, 0.49, and 0.63, respectively.
Polygenic proxies of age-related plasma protein levels reveal TIMP2 role in cognitive performance
Authors: Anastasi Federica , Genius Patricia , Rodriguez-Fernandez Blanca , Yang Chengran , Gorijala Priyanka , Timsina Jigyasha , Hernández-Villamizar Felipe , Lorenzini Luigi , Campo Marta del , Sanchez-Benavides Gonzalo , Minguillon Carolina , Navarro Arcadi , Cruchaga Carlos , Suárez-Calvet Marc , Vilor-Tejedor Natalia
Published: October 2024

Background While numerous studies have identified blood proteins that modulate brain aging in mice, the direct translation of these findings to human health remains a substantial challenge. Bridging this gap is critical for developing interventions that can effectively target human brain aging and associated diseases.Methods We first identified 12 proteins with aging or rejuvenating properties in murine brains through a systematic review. Using protein quantitative trait loci data for these proteins, we developed polygenic scores to predict plasma protein levels, which we then validated in two independent human cohorts. We employed association models to explore the association between these genetically predicted protein levels and cognitive performance, focusing specifically on their interaction with key genetic markers such as sex, APOE-ε4 and Aβ42 status.Results Predicted plasma levels of Tissue Inhibitor of Metalloproteinases 2 (TIMP2) were significantly associated with improved global cognition and memory performance in humans, also when the models were stratified by sex, APOE-ε4, and Aβ42 status.Conclusions This finding aligns with TIMP2's brain-rejuvenating role in murine models, suggesting it as a promising therapeutic target for brain aging and age-related brain diseases in humans.
Research on multi-section energy-saving operation control methods of urban rail train based on deep reinforcement learning
Authors: Chen Xiaoqiang , Yang Haobo , Meng Jianjun , Li Decang , Xu Ruxun , Guo Youmin
Published: October 2024

In order to improve the operation efficiency of urban rail transit and reduce energy consumption, a multi-objective train energy saving optimization model was established based on the train motion equation, parking accuracy and punctuality. On the basis of making full use of the stability of TD3 (Twin Delayed Deep Deterministic policy gradient) algorithm in processing the high-dimensional continuous action space and better adaptability in the face of complex environment, the maximum speed curve of the train is introduced. A reasonable action range is set to improve the efficiency of the algorithm and reduce the difficulty of solving the model. According to the train schedule, different single interval can be set up to allocate the running time and appropriate reward function within the allowable range of the total running time. The deep reinforcement learning method is used to optimize the train running curve under different running time in each interval by the agent choosing the action freely within a certain range. The simulation experiment is designed on the background of 5 stations and 4 sections of Beijing Metro Line 2, and the improved DDPG algorithm and TD3 algorithm are compared. The efficiency of the improved algorithm is verified by setting up three different energy-saving train running curves under the single interval distributable running time. The results show that the energy consumption of train traction can be reduced to a certain extent by adjusting the allotted time of the interval. However, the energy saving benefits brought by selecting too large allot time are not significant, and will greatly affect the normal operation of trains. Therefore, adjusting the running time of the train in a single interval can effectively save the overall traction energy consumption of the train in multiple intervals, and the maximum energy saving can reach 18.07% compared with the traditional control method. The research results can provide a feasible control method for the energy-saving operation of urban rail trains in multiple sections.
Transovarial transmission of Anaplasma phagocytophilum in Haemaphysalis ticks under field conditions
Authors: Ahn KyuSung , Alkathiri Badriah , Lee Seung-Hun , Lee Haeseung , Kwak Dongmi , Youn SoYoun , Yoo Mi-Sun , Kim Jaemyung , Cho Yun Sang , Shin SungShik
Published: October 2024

Background:
Anaplasmosis, a zoonotic tick-borne pathogen affecting both livestock, companion animals, and humans, exhibits 15 to 18% seropositivity among hunting dogs in Korea. The dominant tick species in Korea, Haemaphysalis longicornis can transmit this pathogen to both humans and animals. Given the limited understanding of transovarial transmission of Anaplasma spp., our study aimed to assess the prevalence of questing larval ticks containing Anaplasma DNA. Additionally, we aimed to gather data for establishing a nationwide forecasting and alert system on seasonal variation of tick developmental stages and tick-borne zoonotic pathogens.
Methods:
From March to October 2021 and again from March to October 2022, we collected a total of 36,912 unfed, questing ticks of Haemaphysalis spp. from 149 sites in Korea. Ticks were collected from herbaceous vegetation using the flagging method using a white flannel cloth. After species identification, one third of collected ticks underwent analysis for Anaplasma gene. Nymph ticks were pooled in groups of one to 10, larvae in groups of one to 50, while adults were examined individually. Nested PCR was performed to detect the genus Anaplasma by amplifying the 16S rRNA gene, followed by sequencing for species identification and phylogenetic analysis.
Results:
Of the 36,912 questing ticks collected, 13,082 (35.4%) were identified as nymphs and adults of H. longicornis and 3,850 (10.4%) as those of H. flava. The morphologically indistinguishable larval stage of Haemaphysalis predominated, with 19,980 (54.1%) collected primarily from July to October. From the 939 tick pools, 24 pools (2.6%) tested positive for Anaplasma, with the larval stage exhibiting the highest number of positive pools (16, 1.7%). Phylogenetic analysis revealed that 21 of the 24 Anaplasma-positive pools contained A. phagocytophilum-specific genes, while the remaining 1 was identified as Anaplasma sp. and 2 as A. bovis.
Conclusions:
Our study provides evidence of transovarial transmission of Anaplasma phagocytophilum in Haemaphysalis spp. larvae under field conditions, as A. phagocytophilum originates from their mother ticks in unengorged questing larval ticks. Additionally, our findings contribute significant data for establishing a nationwide forecasting and alert system on seasonal variation of tick developmental stages and tick-borne zoonotic pathogens.
Investigating Impact of Sound Frequencies and Light Exposure on Pepper Plant Growth
Authors: Abdeldaim Mariam Islam , Hamama Malak , Farha Omar , Gaafar Mostafa
Published: October 2024

Studies have indicated that acoustic waves and light wavelengths may influence plant development by improving enzymat-ic function, and hormonal regulation. This can lead to a decrease in reliance on fertilizers, which cause a significant number of deaths an-nually. Consequently, the primary objective of our experimental study is to examine the effects of red-light wavelength and sound frequen-cy on the growth of pepper plants. to prove the effectiveness of light and sound waves on plants four groups of pepper pots were estab-lished: one reference group with no influences, one with red light at a 660-nm wavelength, one with an auditory frequency of 500 Hz, and one in the presence of both red light and auditory frequency conditions. To attain the most precise outcome, a controlled environment was instituted for all the groups, the quantity of solar radiation that impinges upon the pots, the volume of irrigation, and the homogeneous soil composition. The data was gathered by taking photos of the growing process throughout three consecutive weeks Results obtained showed that the experimental set exposed to the 500 Hz sound frequency had a higher germination rate compared to other groups. The experi-mental group with red light showed a slight increase in growth from the control group. Specimens the combined treatment group demon-strated growth patterns more likely to the only sound-exposed group, indicating that the best result from the only sound group which exam-ines that there is a direct relation between the rate of growth of the plant and the frequency of sound waves depending on the type of plant and the hertz value that stimulate its enzymatic process. These results may serve as a significant determinant in optimizing agricultural methodologies.
Bio-Inspired Graphene Nanomaterials: Synthesis and Characterization for Ambient Microbial Destruction
Authors: Bartaria Vaishnav , Yadav Ishant , Jangid Ashok , Srivas Anupam , Kumar Ranjit
Published: October 2024

This study explores the conversion of carbon-rich coconut waste into bio-inspired graphene oxide (GO) and reduced graphene oxide (rGO) for application as antimicrobial agents, addressing air quality and public health concerns. Both GO and rGO demonstrated significant antimicrobial properties against a variety of airborne microorganisms. GO achieved nearly complete inhibition of bacteria, such as Staphylococcus spp., and fungi, including Aspergillus spp., at low concentrations. Similarly, rGO effectively inhibited Escherichia coli and Brucella spp., highlighting its broad-spectrum antimicrobial activity. The synthesis of GO was performed using an enhanced Hummers' method, producing nanomaterials with distinct surface functionalities, which were characterized by X-ray diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM). XRD analysis revealed a notable shift from the sharp graphite peak at 2θ = 26.4°, indicating the (002) plane, to a broadened peak at 2θ = 11.15° in GO, signifying successful oxidation and exfoliation of graphite. For rGO, the disappearance of the 11.15° peak confirmed the partial restoration of graphitic structure. FESEM imaging displayed the nanosheet morphology of GO and rGO, along with microscopic analysis revealing the physical interaction of GO with bacterial and fungal cells, enabling precise identification of microorganisms. Moreover, the GO-coated surfaces exhibited higher surface roughness, promoting bacterial adhesion, which underscores the critical role of surface properties in antimicrobial efficacy. This research contributes to the Sustainable Development Goals (SDG 3: Good Health and Well-being, and SDG 11: Sustainable Cities and Communities) by providing an eco-friendly solution for mitigating microbial pollution in the ambient environment through the use of bio-based nanomaterials.
How social initiatives affect the value of manufacturing companies in Nigeria
Authors: Inyang William , Effiong Charles , Usoro Abosede , Efiong Eme , Bessong Peter , Oden Essien , Ubi Ije
Published: October 2024

Eighty percent of listed manufacturing firms in Nigeria (4 out of 5 firms) had negative and fluctuating returns on equity eighty-three percent of the time (5 out of 6 years), while inexplicable fluctuations in philanthropic expenditures, labor costs, and creditor days correspondingly occurred during the 6-year period under review (2018–2023). This study looks at how social initiatives affect the value of listed manufacturing firms in Nigeria. Its specific goal was to determine whether a firm’s value (measured as return on equity) is influenced by the cost of corporate giving, the cost of employee well-being, and the time taken to settle creditors. Data were obtained from the financial reports of 5 companies. the sample of which was judgmentally drawn from 16 listed companies using a quantitative method of research. EViews statistical package was used to analyze data. It was found that investments in social initiatives as supported by corporate giving {B1 = 0.010162, P = .2691 or P > .05}, employee well-being {B2 = .012285, P = .3836 or P > .05}, and obligations to creditors {B3 = .012018, P = .8327 or P > .05} are not value-enhancing in Nigeria’s manufacturing sector. In light of the above, it was concluded that listed companies in the manufacturing sector in Nigeria are not legitimately and strategically investing their resources in social initiatives, and corporate value is consequently not enhanced and maximized.
Analysis of the employment structure of ukraine’s population during the war
Authors: Barash Alina
Published: October 2024

Structural shifts in employment in the modern Ukrainian economy are caused by factors such as the military situation, technological progress, demographic changes, and economic instability. These changes affect the sectoral, gender, and regional distribution of workers and require adaptation from labor market participants and social policies to ensure the stability and efficiency of employment. Addressing structural shifts in employment in Ukraine requires a comprehensive approach, which includes stimulating the development of new economic sectors, supporting entrepreneurship, modernizing education and training, and providing social protection for workers during reorientation and retraining processes. Such an approach will help achieve a balanced state of supply and demand in the labor market, thereby ensuring long-term societal protection and well-being.
The problem of constipation in the practice of an outpatient doctor
Authors: Pakhomova I. G. , Lelyakova A. A.
Published: October 2024

Constipation is a disorder that affects a large number of people and has a negative impact on quality of life. Constipation is one of the common reasons for seeking medical help from an outpatient doctor. The problem of constipation can often be multifactorial, with important causes being low fiber in the diet, decreased fluid intake and physical inactivity. For some patients, constipation is not a chronic problem, but may occur at some point in their lives, usually lasts a limited period of time and is not a serious problem, the solution to which may be changes in diet and lifestyle, or a short course of laxatives. In everyday outpatient practice, so-called simple or functional constipation is more common. At the same time, long-term or chronic constipation is often a complex problem for both the doctor and the patient; it is often secondary in nature, affecting not only personal well-being and quality of life, but also causes considerable financial costs, since most patients do not immediately seeks medical help, trying to self-medicate, for a long time and not always successfully, transforming the problem into a chronic one, further complicating the diagnostic search and choice of treatment tactics. Chronic constipation is more often a problem for women and older people. Knowledge and understanding of the causes and possibilities for diagnosing constipation, approaches to therapy, as well as measures for its prevention will allow the outpatient doctor to choose the necessary tactics for managing the patient. The article provides a review of the literature on the etiopathogenetic, diagnostic aspects of constipation, as well as the possibility of an integrated approach in the treatment of patients. Algorithms for diagnostic search and choice of therapy for a patient with constipation are convenient for practical use, which is also presented in the article.
Prevalence and clinical features of gastroesophageal reflux disease in residents of the Makhachkala-Caspian agglomeration
Authors: Akhmedova P. N. , Chamsutdinov N. U.
Published: October 2024

Introduction. Gastroesophageal reflux disease is the most common gastrointestinal disease. In recent decades, various questionnaires have been used to study the prevalence of gastroesophageal reflux disease: GERD-Q, QUEST, FSSG, RDQ, GERD-HRQL, the use of which has allowed us to establish a clear trend towards an increase in the frequency of gastroesophageal reflux disease throughout the world, including in Russia.

Aim. To study the prevalence and features of the clinical course of gastroesophageal reflux disease in residents of the Makhachkala- Caspian agglomeration of the Republic of Dagestan.

Materials and methods. A survey was conducted of 496 residents of the Republic of Dagestan (308 women and 188 men, average age ‒ 40 ± 0.7 years) using the GERD-Q and EFGERD (Epidemiology and Risk Factors for the Development of Gastroesophageal Reflux Disease in Dagestan) questionnaires.

Results. The prevalence of gastroesophageal reflux disease in residents of the Makhachkala-C aspian agglomeration of the Republic of Dagestan according to the GERD-Q questionnaire was 11.8%, according to the EFGERD questionnaire – 26.2%. The most common residents of the Republic of Dagestan who suffer from gastroesophageal reflux disease are Dargins (39.8%), Avars (38.2%) and Kumyks (37.0%). Somewhat less common are Lezgins (30.7%) and mestizos (31.6%). Laks (12%) and Tabasarans (8.9%) suffer from gastroesophageal reflux disease much less frequently. It has been established that in addition to esophageal symptoms of the disease, patients with gastroesophageal reflux disease often have symptoms of gastrointestinal tract diseases, as well as otolaryngological, bronchopulmonary, cardiac and dental symptoms.

Conclusion. The prevalence of gastroesophageal reflux disease in residents of the Makhachkala-C aspian agglomeration of the Republic of Dagestan according to the EFGERD questionnaire was 26.2%. At the same time, the EFGERD questionnaire has shown its high diagnostic value, which makes it possible to recommend it for the purpose of early diagnosis of gastroesophageal reflux disease and its extraesophageal manifestations.
Pain in the epigastral area: current aspects of differential diagnosis
Authors: Trukhan D. I. , Tarasova L. V.
Published: October 2024

Epigastric pain can have a variety of etiologies, including not only diseases of the upper gastrointestinal tract (GIT): gastroesophageal reflux disease, hiatal hernia, gastritis and duodenitis, gastric and/or duodenal ulcers, polyps and stomach cancer, functional dyspepsia, but also other gastrointestinal diseases, somatic diseases of other organs and systems, vascular pathology, infections and invasions, medications and a number of other reasons. More than 10 years have passed since the publication of our previous article on the issues of differential diagnosis of pain in the stomach. In the Elibrary.ru information base, both in the period of time preceding the publication and to this day, we have not found similar publications. This explains its placement in full or in fragments on specialized gastroenterological sites and guidelines for differential diagnosis in gastroenterology. Over the past 10 years, new consensuses and clinical recommendations have been published on diseases and conditions associated with epigastric pain, and the number of publications on other diseases and conditions that were previously considered very rare, but which today must be taken into account when carrying out differential diagnosis, has increased. Several foreign publications on the problem in recent years were found in the PubMed electronic database. In this regard, we consider it appropriate to consider the current aspects of the differential diagnosis of epigastric pain from the perspective of today. The list of diseases and conditions presented in the review, in which epigastric pain occurs in the clinical picture, indicates that the differential diagnosis of this syndrome is an interdisciplinary problem and is of interest not only to the gastroenterologist and therapist, but also to doctors of other specialties.
The interrelation of cardiometabolic risk factors and metabolic dysfunction-associated steatotic liver disease subtypes
Authors: Ishchenko A. Yu. , Galushko M. Yu. , Bakulin I. G.
Published: October 2024

Introduction. Metabolic dysfunction-associated steatotic liver disease is one of the leading causes of cirrhosis, liver cancer and extrahepatic complications. The number and various combinations of cardiometabolic risk factors, as well as the severity of liver steatosis, can affect the aggressiveness and prognosis of the disease. The article presents the results of own studies aimed at determining the prognostic significance of risk factors (individual and in different combinations) and steatometry.

Objective. To determine the influence of individual cardiometabolic factors, their number and various combinations on the aggressiveness and prognosis of metabolic dysfunction-associated steatotic liver disease; to assess the prognostic value of steatometry for the disease.

Material and methods. The examination results (steatometry, blood biochemistry tests, abdominal ultrasound) of patients diagnosed with metabolic dysfunction-associated steatotic liver disease were retrospectively analyzed. Statistical analysis: Student's t-test, Pearson's χ2-test, odds ratio, relative risk, Fisher's φ-test, ROC-analysis.

Results. 146 patients were included. Cohort characteristics: average age 49.3 years, 84 men (57.5%). Aggressive forms (steatohepatitis, advanced steatosis) were associated with arterial hypertension, carbohydrate metabolism disorders (the most significant is insulin resistance), dyslipidemia, hyperuricemia. The severity of liver steatosis was less in patients who received therapy for lipid metabolism disorders comparing with those who didn’t. The presence of three or more cardiometabolic risk factors in a patient increased the risk of steatohepatitis and advanced steatosis. The combination of arterial hypertension and hyperuricemia significantly increased the risk of steatohepatitis. Advanced hepatic steatosis (≥310 dB/m2 by steatometry) was reliably associated with steatohepatitis.

Conclusion. Individual risk factors, their number and combinations, contribute differently to the development of aggressive forms of the disease. Hyperuricemia should be considered as an additional cardiometabolic risk factor. Steatometry is capable of identifying advanced hepatic steatosis, being a risk factor for the development of steatohepatitis, which allows us to recommend it for the early diagnosis of metabolic dysfunction-associated steatotic liver disease.
Lubrication optimization of high-speed train drive gearbox
Authors: Ji Tian , Tao Changwen , Sun Tao
Published: October 2024

The gears in the high-speed heavy-duty gearbox of the high-speed train are typical high-speed heavy-duty gears. Combined with the transmission principle and structural characteristics of the high-speed train drive gearbox, to ensure adequate lubrication of meshing gears and bearings, an optimization of the lubricating oil flow inside the gearbox was conducted. The oil and gas two-phase flow model inside the gearbox adopts the VOF model, and the turbulence model adopts the standard κ-ε model. Fluent is used for simulation calculation. The results show that the exhaust port position of the gearbox has little effect on the flow of lubricating oil inside the gearbox; the overall pressure distribution inside the gearbox is relatively uniform, with higher pressure only at the meshing gears; the distribution of lubricating oil inside the gearbox is related to the rotation of the gears, and the flow velocity of lubricating oil is mainly affected by the rotation of the gears, with the maximum flow velocity appearing around the gears; the flow of lubricating oil inside the gearbox meets the lubrication requirements of the gearbox. These results provide support for the lubrication design, flow channel structure improvement, and effectiveness evaluation of high-speed train transmission gearboxes.
Optimization of reduction gear in anchor winch based on modal analysis
Authors: Liu Xiaoyu , Wu Xiangyao , Calderon Aldrin D.
Published: October 2024

In order to achieve more scientific design of the reduction gear and reduce material waste, pre-stressed modal analysis method was combined with multi-objective optimization algorithm to optimize the structure of the reduction gear basic body. The model was simplified and parameterized and the maximum stress and equivalent stiffness under different parameter size combinations were obtained through finite element analysis. Separately, genetic clustering method, neural network method, and Kriging method were used to construct the response surface function. Through error verification and comparison, it was found that the Kriging method was more suitable for the gear model. In the design of variable extremum search, multi-objective genetic algorithm and sequential quadratic programming were compared and analyzed. The results show that the mass of the gear can be reduced by 39.9 %, while the maximum stress remains unchanged, the equivalent stiffness is not reduced, and a good optimization design effect is achieved.
Modal analysis and seismic optimization of multi-storey gymnasium frame
Authors: Zhao Yue , Wang Chunxiang , Li Wencheng
Published: October 2024

In order to improve the seismic resistance capacity of the multi-storey gymnasium frame, based on the finite element analysis method, the dynamic response characteristics were analyzed, and the natural frequencies and vibration modes were obtained. Based on the results of the modal analysis, different reinforcement methods were proposed for verification. Under the excitation conditions of Borego waves, the vibration responses of different nodes in initial model were obtained. Modal verification was carried out by using two methods of shear strengthening and support rod strengthening respectively. The analysis results show that the bearing capacity of the single-span frame is insufficient, the lateral stiffness is small, and it is prone to cause severe torsional vibration damage. It can also be known that the seismic resistance capacity of the support rods reinforcement is more balanced in different directions. It can not only effectively improve the lateral stiffness and bearing capacity of the structure, but also improve the seismic performance of the main structure through the energy dissipation of component yield, which is more suitable for multi-story buildings.
Substantiation of the methodology for calculating the design of a small-sized hydraulic pulse vibrator
Authors: Obertyukh Roman , Slabkyi Andrii , Petrov Oleksandr , Bakalets Dmytro
Published: October 2024

A methodology for the design calculation of a new design of a hydraulic pulse vibrator with a valve pressure pulse generator of a parametric type has been developed, which allows determining its energy, power and geometric parameters.
Comparison of passive and semi-active piezoelectric transducer damping of cantilever oscillation
Authors: Hussein Mustafa T. , Al-Juboori Ameen M. , Mahdi Sarah Z.
Published: October 2024

The aim of this work is the analysis of passive and semi-active damping methods on the model woven beam with a piezoelectric (PZ) layer. The mathematical model of the PZ layer on cantilever beam is derived. For modeling, real product parameters of PZ layer are used, and through simulation find the optimal values to dampen it. The resistive-inductance passive model, and State-Switch Damping SSD semi-active model are used in this work. The models are processed in the MATLAB Simulink environment and the results of the behavior of the models compared to each other. The program involving passive and semi-active systems, where analyze the behavior of the model for different parameters and the damping capabilities of individual methods are compared. The simulation results show the effectiveness of the semi-active system in comparison with the passive systems, also it shows the passive method is not so effective at low frequency as it in high frequency, and the semi-active method is not optimal for high frequency vibration.
Simulation analysis of force and fatigue life of circular wheel of crawler vehicle
Authors: Wang Chao , Chen Yu , Xue Tao , Ma Tongxin , Zhang Ruipeng
Published: October 2024

During loading and driving, the wheels bear the vertical load from the body mass and the excitation load generated by uneven road surface on the one hand, and bear the driving torque on the other hand. The load-bearing methods of wheels are generally divided into bottom load-bearing and top load-bearing. This paper describes the structural characteristics of the track system of the articulated track vehicle and the interaction relationship between the main components of the track system. Finite element calculation is carried out based on ANSYS software to obtain the stress distribution of each key component under various loading methods. It can be seen from the results that all key components of the track system can meet the strength and rigidity requirements; although there are also areas with large local stress, they are all within the safe range, which is mainly caused by stress concentration. Safe life is obtained through fatigue analysis.
Stabilizing fish oil during storage with Satureja bachtiarica Bunge
Authors: Matbo Atefeh , Ghanbari Mohammad Mehdi , Sekhavatizadeh Seyed Saeed , Nikkhah Mehdi
Published: October 2024

Fish oil is highly susceptible to lipid oxidation, which leads to safety loss during storage. Natural antioxidants can prevent lipid oxidation. Satureja bachtiarica Bunge, also known as savory, is an endemic species plant that contains the necessary bioactive compounds and possesses antioxidant activity suitable for this purpose. This study featured the effects of savory extract and its essential oil as stabilizing agents on kilka fish oil.
We assessed the oxidative stability of fish oil fortified with of savory extract and essential oil in amounts of 0.5 and 1%. Then we compared their oxidative activity with that of samples treated with a synthetic antioxidant during 35 days at 40°C. The fish oil samples were tested for antioxidant activity, acid degree value, thiobarbituric acid-reactive substances, para-anisidine value, conjugated dienoic acids, peroxide value, total oxidation value, and free fatty acids.
Savory essential oil at the concentration of 1% was more effective than other samples in reducing the rate of lipid oxidation in fish oil. On storage day 35, the control sample yielded the following data: peroxide value = 14.79 meq O2/kg, acid degree value = 32.49 mL/g, thiobarbituric acid-reactive substances = 5.82 mg MDA/g, para-anisidine value = 116.03, total oxidation index = 136.27. These results were significantly (p < 0.05) higher than those in the sample with 1 % savory essential oil: peroxide value = 9.52 meq O2/kg, acid degree value = 22.41 mL/g, thiobarbituric acid-reactive substances = 3.46 mg MDA/g, para-anisidine value = 78.3, total oxidation index = 108.09. The fish oil samples contained more unsaturated fatty acids (66.76–68.83%) than saturated fatty acids (31.13–32.6%).
Savory essential oil demonstrated good potential as an effective natural antioxidant that extends the shelf life of fish oil.
Machine learning framework for predicting water quality classification
Authors: Sangwan Vinita , Bhardwaj Rashmi
Published: October 2024

Groundwater serves as the source for nearly half of the world's drinking water, yet understanding of global groundwater resources remains incomplete, and management of aquifers falls short, particularly concerning groundwater quality. This research offers insights into the groundwater quality in 242 stations of Maharashtra and Union Territory of Dadra and Nagar Haveli and nine parameters (pH, TDS, TH, Calcium (Ca2+), Magnesium (Mg2+), Chloride (Cl−), Sulphate (SO42−), Nitrate (NO3−), Fluoride (F−)) were considered for computing the Water Quality Index (WQI) and hence Water Quality Classification (WQC) based on Water Quality Index (WQI). This research introduces the utilisation of Machine Learning (ML) models, specifically, Random Forest, Adaptive Boosting (AdaBoost), Gradient Boosting, XGBoost, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) model for predicting WQC and models are tested. Grid search method as a hyperparameter tuning of parameters is utilized to achieve the best possible performance of ML models. The performance metrics that are used for evaluating and reporting the performance of classification models are Accuracy, Precision, Recall or Sensitivity, F1 Score. SVM achieved the highest performance in predicting WQC. With accurate predictions of WQC, these findings have the potential to enhance NEP concerning water resources by facilitating ongoing improvements in water quality.
A Study on Oxygen Vacancy Resistance Mechanism of V2O5
Authors: He Lijun , Zhang Chaopeng , Wang Liyan , Yu Mi , Mi Cheng , She Liang , Ma Kang , Long Xing
Published: October 2024

Introduction:

Due to its magnetic and semiconductor properties, V2O5 has shown
tremendous potential in resistive switching memory. Method: Therefore, this paper investigates
the resistive mechanism of oxygen vacancies in V2O5. The formation energies of different oxygen
vacancies are calculated. Results: The results indicate that oxygen vacancies tend to form
single-component conductive filaments. In mixed oxygen vacancies clusters, the charge transfer
characteristics and density of states of the V2O5-VO
13 vacancies are the most significant, which is
consistent with the analysis of formation energy data. Conclusions: Additionally, the charge
transfer of cluster oxygen vacancies was calculated, showing that V atoms directly connected to
oxygen vacancies tend to lose electrons, while adjacent oxygen atoms are more likely to gain
electrons. In V2O5-VO
12 and V2O5-VO
13, the number of electrons obtained by O2 and O16 exceeds
the average by 36.4% and 33.2%. Thus, the formation of oxygen vacancies effectively
improves the resistance characteristics of the V2O5.
Relações intertextuais e imagéticas em "Primeiras Estórias": um olhar sobre “As margens da alegria”
Authors: Alessandra Fonseca de Morais
Published: October 2024

Este artigo tem como objetivo realizar uma leitura intersemiótica do conto “As Margens da Alegria” de João Guimarães Rosa e suas respectivas ilustrações, feitas por Luís Jardim para o livro Primeiras Estórias. A análise se concentrará na relação entre palavra e imagem, mostrando como essa interação sugere uma recriação da linguagem. Para alcançar esses resultados, utilizamos teorias gerais da ilustração, integradas com a teoria da semiose hermética de Umberto Eco, apresentada em Os limites da Interpretação (1990), e com a perspectiva de Carl Jung sobre alquimia. O estudo revela como as ilustrações não apenas complementam, mas também expandem e transformam o significado do texto literário, oferecendo uma nova dimensão interpretativa ao conto de Guimarães Rosa.