bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling the Properties of Phage Display Fab Libraries and Their Use in the Selection of Gliadin-Specific Probes by Applying High-Throughput Nanopore Sequencing
Authors: Garcia-Calvo Eduardo , García-García Aina , Rodríguez Santiago , Martín Rosario , García Teresa
Published: April 2024

Directed evolution is a pivotal strategy for new antibody discovery, which allowed the generation of high-affinity Fabs against gliadin from two antibody libraries in our previous studies. One of the libraries was exclusively derived from celiac patients’ mRNA (immune library) while the other was obtained through a protein engineering approach (semi-immune library). Recent advances in high-throughput DNA sequencing techniques are revolutionizing research across genomics, epigenomics, and transcriptomics. In the present work, an Oxford Nanopore in-lab sequencing device was used to comprehensively characterize the composition of the constructed libraries, both at the beginning and throughout the phage-mediated selection processes against gliadin. A customized analysis pipeline was used to select high-quality reads, annotate chain distribution, perform sequence analysis, and conduct statistical comparisons between the different selection rounds. Some immunological attributes of the most representative phage variants after the selection process were also determined. Sequencing results revealed the successful transfer of the celiac immune response features to the immune library and the antibodies derived from it, suggesting the crucial role of these features in guiding the selection of high-affinity recombinant Fabs against gliadin. In summary, high-throughput DNA sequencing has improved our understanding of the selection processes aimed at generating molecular binders against gliadin.
Long-Term Impairment of Working Ability in Subjects under 60 Years of Age Hospitalised for COVID-19 at 2 Years of Follow-Up: A Cross-Sectional Study
Authors: Frallonardo Luisa , Ritacco Annunziata Ilenia , Amendolara Angela , Cassano Domenica , Manco Cesari Giorgia , Lugli Alessia , Cormio Mariangela , De Filippis Michele , Romita Greta , Guido Giacomo , Piccolomo Luigi , Giliberti Vincenzo , Cavallin Francesco , Segala Francesco Vladimiro , Di Gennaro Francesco , Saracino Annalisa
Published: April 2024

Background: Coronavirus disease 2019 (COVID-19) can lead to persistent and debilitating symptoms referred to as Post-Acute sequelae of SARS-CoV-2 infection (PASC) This broad symptomatology lasts for months after the acute infection and impacts physical and mental health and everyday functioning. In the present study, we aimed to evaluate the prevalence and predictors of long-term impairment of working ability in non-elderly people hospitalised for COVID-19. Methods: This cross-sectional study involved 322 subjects hospitalised for COVID-19 from 1 March 2020 to 31 December 2022 in the University Hospital of Bari, Apulia, Italy, enrolled at the time of their hospital discharge and followed-up at a median of 731 days since hospitalization (IQR 466–884). Subjects reporting comparable working ability and those reporting impaired working ability were compared using the Mann-Whitney test (continuous data) and Fisher’s test or Chi-Square test (categorical data). Multivariable analysis of impaired working ability was performed using a logistic regression model. Results: Among the 322 subjects who were interviewed, 184 reported comparable working ability (57.1%) and 134 reported impaired working ability (41.6%) compared to the pre-COVID-19 period. Multivariable analysis identified age at hospital admission (OR 1.02, 95% CI 0.99 to 1.04), female sex (OR 1.90, 95% CI 1.18 to 3.08), diabetes (OR 3.73, 95% CI 1.57 to 9.65), receiving oxygen during hospital stay (OR 1.76, 95% CI 1.01 to 3.06), and severe disease (OR 0.51, 95% CI 0.26 to 1.01) as independent predictors of long-term impaired working ability after being hospitalised for COVID-19. Conclusions: Our findings suggest that PASC promotes conditions that could result in decreased working ability and unemployment. These results highlight the significant impact of this syndrome on public health and the global economy, and the need to develop clinical pathways and guidelines for long-term care with specific focus on working impairment.
Challenges in Treating Pediatric Cancer Patients during the COVID-19 Pandemic: Balancing Risks and Care
Authors: Chávez-Pacheco Juan Luis , Castillejos-López Manuel , Hernández-Regino Laura M. , Velasco-Hidalgo Liliana , Zapata-Tarres Marta , Correa-Carranza Valeria , Rosario-Méndez Guillermo , Barrientos-Ríos Rehotbevely , Aquino-Gálvez Arnoldo , Torres-Espíndola Luz María
Published: April 2024

The COVID-19 pandemic has resulted in millions of fatalities worldwide. The case of pediatric cancer patients stands out since, despite being considered a population at risk, few studies have been carried out concerning symptom detection or the description of the mechanisms capable of modifying the course of the COVID-19 disease, such as the interaction and response between the virus and the treatment given to cancer patients. By synthesizing existing studies, this paper aims to expose the treatment challenges for pediatric patients with COVID-19 in an oncology context. Additionally, this updated review includes studies that utilized the antiviral agents Remdesivir and PaxlovidTM in pediatric cancer patients. There is no specific treatment designed exclusively for pediatric cancer patients dealing with COVID-19, and it is advisable to avoid self-medication to prevent potential side effects. Managing COVID-19 in pediatric cancer patients is indeed a substantial challenge. New strategies, such as chemotherapy application rooms, have been implemented for children with cancer who were positive for COVID-19 but asymptomatic since the risk of disease progression is greater than the risk of complications from SARS-CoV-2.
Longitudinal Analysis of Humoral and Cellular Immune Response up to 6 Months after SARS-CoV-2 BA.5/BF.7/XBB Breakthrough Infection and BA.5/BF.7-XBB Reinfection
Authors: Wang Xun , Zhang Meng , Wei Kaifeng , Li Chen , Yang Jinghui , Jiang Shujun , Zhao Chaoyue , Zhao Xiaoyu , Qiao Rui , Cui Yuchen , Chen Yanjia , Li Jiayan , Cai Guonan , Liu Changyi , Yu Jizhen , Zhang Wenhong , Xie Faren , Wang Pengfei , Zhang Yanliang
Published: April 2024

The rapid mutation of SARS-CoV-2 has led to multiple rounds of large-scale breakthrough infection and reinfection worldwide. However, the dynamic changes of humoral and cellular immunity responses to several subvariants after infection remain unclear. In our study, a 6-month longitudinal immune response evaluation was conducted on 118 sera and 50 PBMC samples from 49 healthy individuals who experienced BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection. By studying antibody response, memory B cell, and IFN-γ secreting CD4+/CD8+ T cell response to several SARS-CoV-2 variants, we observed that each component of immune response exhibited distinct kinetics. Either BA.5/BF.7/XBB breakthrough infection or BA.5/BF.7-XBB reinfection induces relatively high level of binding and neutralizing antibody titers against Omicron subvariants at an early time point, which rapidly decreases over time. Most of the individuals at 6 months post-breakthrough infection completely lost their neutralizing activities against BQ.1.1, CH.1.1, BA.2.86, JN.1 and XBB subvariants. Individuals with BA.5/BF.7-XBB reinfection exhibit immune imprinting shifting and recall pre-existing BA.5/BF.7 neutralization antibodies. In the BA.5 breakthrough infection group, the frequency of BA.5 and XBB.1.16-RBD specific memory B cells, resting memory B cells, and intermediate memory B cells gradually increased over time. On the other hand, the frequency of IFN-γ secreting CD4+/CD8+ T cells induced by WT/BA.5/XBB.1.16 spike trimer remains stable over time. Overall, our research indicates that individuals with breakthrough infection have rapidly declining antibody levels but have a relatively stable cellular immunity that can provide some degree of protection from future exposure to new antigens.
Parameter Optimization of Frazil Ice Evolution Model Based on NSGA-II Genetic Algorithm
Authors: Chen Yunfei , Lian Jijian , Zhao Xin , Yang Deming
Published: April 2024

This study is based on the research results of frazil ice evolution in recent years and proposes an improved frazil ice evolution mathematical model. Based on the NSGA-II genetic algorithm, seven key parameters were used as optimization design variables, the minimum average difference between the number of frazil ice, the mean and the standard deviation of particle diameter of the simulation results, and the observed data were used as the optimization objective, the Pareto optimal solution set was optimized, and the importance of each objective function was analyzed and discussed. The results show that compared to previous models, the improved model has better agreement between simulation results and experimental results. The optimal parameters obtained by the optimization model reduces the difference rate of water temperature process by 5.75%, the difference rate of quantity process by 39.13%, the difference rate of mean particle size process by 47.64%, and the difference rate of standard deviation process by 56.84% during the period of intense evolution corresponding to the initial parameter group. The results prove the validity of the optimization model of frazil ice evolution parameters.
Greedy Weighted Stacking of Machine Learning Models for Optimizing Dam Deformation Prediction
Authors: Alocén Patricia , Fernández-Centeno Miguel Á. , Toledo Miguel Á.
Published: April 2024

Dam safety monitoring is critical due to its social, environmental, and economic implications. Although conventional statistical approaches have been used for surveillance, advancements in technology, particularly in Artificial Intelligence (AI) and Machine Learning (ML), offer promising avenues for enhancing predictive capabilities. We investigate the application of ML algorithms, including Boosted Regression Trees (BRT), Random Forest (RF), and Neural Networks (NN), focussing on their combination by Stacking to improve prediction accuracy on concrete dam deformation using radial displacement data from three dams. The methodology involves training first-level models (experts) using those algorithms, and a second-level meta-learner that combines their predictions using BRT, a Linear Model (LM) and the Greedy Weighted Algorithm (GWA). A comparative analysis demonstrates the superiority of Stacking over traditional methods. The GWA emerged as the most suitable meta-learner, enhancing the optimal expert in all cases, with improvement rates reaching up to 16.12% over the optimal expert. Our study addresses critical questions regarding the GWA’s expert weighting and its impact on prediction precision. The results indicate that the combination of accurate experts using the GWA improves model reliability by reducing error dispersion. However, variations in optimal weights over time necessitate robust error estimation using cross-validation by blocks. Furthermore, the assignment of weights to experts closely correlates with their precision: the more accurate a model is, the more weight that is assigned to it. The GWA improves on the optimal expert in most cases, including at extreme values of error, with improvement rates up to 41.74%. Our findings suggest that the proposed methodology significantly advances AI applications in infrastructure monitoring, with implications for dam safety.
Identification of Trends in Dam Monitoring Data Series Based on Machine Learning and Individual Conditional Expectation Curves
Authors: Fernández-Centeno Miguel Á. , Alocén Patricia , Toledo Miguel Á.
Published: April 2024

Dams are complex systems that involve both the structure itself and its foundation. Rheological phenomena, expansive reactions, or alterations in the geotechnical parameters of the foundation, among others, result in non-reversible and cumulative modifications in the dam response, leading to trends in the monitoring data series. The accurate identification and definition of these trends to study their evolution are key aspects of dam safety. This manuscript proposes a methodology to identify trends in dam behavioural data series by identifying the influence of the time variable on the predictions provided by the ML models. Initially, ICE curves and SHAP values are employed to extract temporal dependence, and the ICE curves are found to be more precise and efficient in terms of computational cost. The temporal dependencies found are adjusted using a GWO algorithm to different function characteristics of irreversible processes in dams. The function that provides the best fit is selected as the most plausible. The results obtained allow us to conclude that the proposed methodology is capable of obtaining estimates of the most common trends that affect movements in concrete dams with greater precision than the statistical models most commonly used to predict the behaviour of these types of variables. These results are promising for its general application to other types of dam monitoring data series, given the versatility demonstrated for the unsupervised identification of temporal dependencies.
Harnessing the Potential of Extracellular Polymeric Substances in Enhancing ANAMMOX Processes: Mechanisms, Strategies, and Perspectives
Authors: Fan Lijing , Jiang Cancan , Wang Xu , Yang Yang , Xie Yawen , Su Jiaqi , Sun Hong , Xu Shengjun , Zhuang Xuliang
Published: April 2024

Anaerobic ammonium oxidation (ANAMMOX) has emerged as a promising sustainable nitrogen removal technology that offers significant advantages over conventional nitrification–denitrification processes, such as reduced energy consumption, a 60% reduction in oxygen demand, and a 90% reduction in sludge production. However, the practical application of ANAMMOX is hindered by several challenges, including the slow growth of ANAMMOX bacteria, long start-up periods, and high sensitivity to environmental disturbances. Recent studies have highlighted the crucial role of extracellular polymeric substances (EPSs) in the formation, activity, and stability of ANAMMOX biofilms and granules. An EPS is a complex mixture of high-molecular-weight polymers secreted by microorganisms, mainly composed of polysaccharides, proteins, nucleic acids, and lipids. The diverse physicochemical properties and functional groups of EPSs enable them to serve as a structural scaffold, protective barrier, sorption site, electron shuttle, and nutrient source for ANAMMOX bacteria. This review aims to provide an overview of the latest research progress on harnessing the potential of EPSs to enhance the ANAMMOX process. The characteristics, compositions, and extraction methods of ANAMMOX-derived EPSs are summarized. The mechanisms of how EPSs facilitate the enrichment, immobilization, aggregation, and adaptation of ANAMMOX bacteria are elucidated. The strategies and effects of EPS supplementation on improving the performance and robustness of ANAMMOX reactors under various stresses are critically reviewed. The challenges and future perspectives of the EPS-mediated optimization of the ANAMMOX process are also discussed. This review sheds new light on exploiting EPSs as a renewable bioresource to develop more efficient and stable ANAMMOX applications for sustainable wastewater treatment.
Simultaneous Synthesis of Single- and Multiple-Contaminant Water Networks Using LINGO and Excel Software
Authors: Shoaib Abeer M. , Atawia Amr A. , Hassanean Mohamed H. , Gadallah Abdelrahman G. , Bhran Ahmed A.
Published: April 2024

Controlling the distribution of water and wastewater between industrial processes is vital to rationalize water usage and preserve the environment. In this paper, a mathematical technique is proposed to optimize water–wastewater networks, and a nonlinear program is introduced to minimize the consumption of freshwater and, consequently, the flowrate of wastewater discharge. A general mathematical model, able to handle industrial plants containing up to eight sources and eight sinks, is developed using LINGO optimization software to facilitate dealing with complex case studies. The introduced model can handle single-contaminant networks as well as multiple-contaminant ones. The optimal water network is synthesized through two steps; the first step involves the introduction of the case study data into the developed mathematical model. The second step considers using the optimal solution produced after running the developed LINGO model as feed data for a pre-designed Excel sheet able to deal with these results and simultaneously draw the optimal water–wastewater network. The proposed mathematical model is applied to two case studies. The first case study includes actual data from four fertilizer plants located in Egypt; the water resources and requirements are simultaneously integrated to obtain a sensible cutting in both freshwater consumption (lowered by 52.2%) and wastewater discharge (zero wastewater discharge). The second case study regards a Brazilian petrochemical plant; the obtained results show noticeable reductions in freshwater consumption by 12.3%, while the reduction percentage of wastewater discharge is 4.5%.
Precipitation Modeling Based on Spatio-Temporal Variation in Lake Urmia Basin Using Machine Learning Methods
Authors: Arbabi Sajjad , Sattari Mohammad Taghi , Attar Nasrin Fathollahzadeh , Milewski Adam , Sakizadeh Mohamad
Published: April 2024

The amount of rainfall in different regions is influenced by various factors, including time, place, climate, and geography. In the Lake Urmia basin, Mediterranean air masses significantly impact precipitation. This study aimed to model precipitation in the Lake Urmia basin using monthly rainfall data from 16 meteorological stations and five machine learning methods (RF, M5, SVR, GPR, and KNN). Eight input scenarios were considered, including the monthly index, longitude, latitude, altitude, distance from stations to Lake Urmia, and distance from the Mediterranean Sea. The results revealed that the random forest model consistently outperformed the other models, with a correlation rate of 0.968 and the lowest errors (RMSE = 5.66 mm and MAE = 4.03 mm). This indicates its high accuracy in modeling precipitation in this basin. This study’s significant contribution is its ability to accurately model monthly precipitation using spatial variables and monthly indexes without measuring precipitation. Based on the findings, the random forest model can model monthly rainfall and create rainfall maps by interpolating the GIS environment for areas without rainfall measurements.
Trends of modern Ukrainian jazz music in Germany in the XXI century (on the example of Tamara Lukasheva’s creativity)
Authors: Voropaieva Olena
Published: April 2024

Statement of the problem. European jazz art of the 21st century continues to develop the trends that were formed in world jazz in the last third of the 20th century. Among them is the interaction with musical ideas of folklore of various peoples of the world, as well as rock music. As a result of this process, such phenomena as ethno-jazz, fusion, and funk and there experimental types were formed, which is found a wide distribution in the territory of Ukraine and provided many opportunities for the disclosure and popularization of the national musical culture. Scientific interest is seen in the study of trends in its development not only within the country, but also abroad, in particular in Germany, where Ukrainian jazz musicians come to. In modern jazzology, the topic of the Jazz and Ukrainian folklore interaction has been studied to some extent, as well as the theme of interaction between jazz and academic music. Some features of the activities of Ukrainian jazzmen in Ukraine and abroad, including T. Lukasheva, are revealed in interviews with musicians, popular science articles, as well as reviews of albums or concerts. Objectives, methods, and novelty of the research. The purpose of the article is to reveal the genre-stylistic specificity of T. Lukasheva’s work in the context of Ukrainian jazz music making in Germany in the 21st century. A set of scientific methods, such as historical-genetic, comparative, interpretive and analytical, contributed to the disclosing the theme of the article. The novelty of the research topic is connected with almost complete lack of its researching in the national jazz studies. Research results and conclusion. T. Lukasheva’s work is in line with the trends that emerged in Ukrainian jazz at the turn of the twentieth and twenty-first centuries: ethno-jazz, funk, fusion in there experimental forms. The individualization of her author’s style took place in Germany, where she revealed herself not only as a virtuoso vocalist and pianist, but also as a talented composer and arranger. This was manifested in the compositions that were performed in the concerts at the Stadtgarten and were considered in the study. They confirm the opinion that the artist masterfully owns her voice, demonstrates a variety of vocal techniques, embodies a wide variety of artistic images. The musician has a wide vocal range of three octaves, non-standard harmonic thinking and a sense of musical time, which allows her to freely feel herself in improvisational solos and in other sections of the form where complex meter and rhythm meet. It is indisputable that one of the leading driving forces in jazz is a creative personality, who must have leadership qualities, bright charisma, musical intelligence, and attract like-minded musicians. All these qualities are fully characteristic of Tamara Lukasheva.
ENVIRONMENTAL AND ENERGY JUSTIFICATION OF THE NEED FOR AGRICULTURAL AREAS TO ENSURE FOOD SECURITY OF UKRAINE
Authors: Andreev V. , Sluchak O. , Sluchak O.
Published: April 2024

The article examines the energy equivalent of the needs in cultivated areas to ensure food security of Ukraine. It was determined that integration into WFE-strategies of food policy requires a comprehensive assessment of the energy component of agricultural production relative to the area of arable land, which will include the productivity of the main crops in the aspect of converting solar energy into food calories. A methodology was created and the efficiency of converting solar energy into the commodity energy value of the products of the grocery basket was calculated: 0.15-0.8% for cereals and vegetables, 0.042-0.054% for meat, 0.015-0.035% for drinks and spices, 0.12 % for dairy products, 0.37-0.93% for eggs. The overall efficiency of human consumption of solar energy through the food chain is 0.22%. To meet these needs, 1,831.3 m2 is needed, which receives 545.8 MW of solar energy during the growing season. It was determined that the yield fluctuations of the main crops are sinusoidal and their use in modeling the need for sowing areas will in the future allow to develop a dynamic model of management of benefits and quotas to stimulate the coverage of a possible shortage of certain main products. Also estimated is the amount of energy that can be used without affecting the yield by renewable energy when using a mobile configuration of its placement (or, on the contrary, directed to artificial lighting of the crop under stationary systems). As a result, basic indicators were obtained, which can be relied upon when developing a food security strategy for cities, and it was also determined that a standard household plot of 0.25 hectares fully covers the needs of one person with a surplus.
ENVIRONMENTAL POLLUTANTS OF THE RAINWATER DRAINAGE SYSTEM OF MYKOLAIV
Authors: Ostapenko V. , Grygorieva L.
Published: April 2024

The article is devoted to the study of the chemical composition and quantitative volume of pollutants entering the Bug Estuary with the rainwater sewage of Mykolaiv. It is known that sewage from industrial and municipal enterprises poses a threat of a significant additional burden on limited regional water resources. First and foremost, uncontrolled stormwater runoff is a major concern. In Mykolaiv, there are 49 registered stormwater drains, of which 19 are directly discharged into open water bodies.
The purpose of the study was to investigate the chemical composition and volume of urban stormwater runoff into the Bug Estuary. The study was based on the results of chemical analyses of water samples from four storm sewers in Mykolaiv, performed in 2022. The materials of chemical analyses of water samples from five storm sewers of Mykolaiv in 1997 were also included.
It was proved that phosphates, oil products, and nitrite nitrogen are present in the stormwater runoff from Mykolaiv to the Bug Estuary. The multiplicity of exceedances of the maximum permissible concentrations is: for biological oxygen consumption - 14-37 times; nitrite - 10-39 times; chemical oxygen consumption - 7-18 times. It has been shown that lead, nickel, iron, copper, chromium, and zinc are released into the Bug estuary with rainwater runoff. Excessive pollution of rainwater with suspended solids is associated with contamination of territories with dust, soil, clay, etc. Excessive pollution with oil products and heavy metals is associated with the operation of motor vehicles and industrial enterprises. It has been shown that unauthorized connections of domestic and industrial sewage systems are mostly responsible for some of the substances that pollute stormwater (phosphates, nitrates). Prospects for further research are the study of the sorption capacity of bottom sediments for the retention of pollutants and the assessment of the ecological capacity of the bottom sediments of the Bug estuary..
The Impact of Device Type Number on IoT Device Classification
Authors: Ergün Ahmet Emre , Can Özgü
Published: April 2024

Today, connected systems are widely used with the recent developments in technology. The internet-connected devices create data traffic when communicating with each other. These data may contain extremely confidential information. Observers can obtain confidential information from the traffic when the security of this traffic cannot be adequately ensured. This confidential information can be personal information as well as information about the type of device used by the person. Attackers could use machine learning to analyze encrypted data traffic patterns from IoT devices to infer sensitive information, even without decrypting the actual content. For example, if someone uses IoT devices for health monitoring or smoke detection, attackers could leverage machine learning to discern victims' habits or identify health conditions. An increase in the number of IoT devices may decrease the accuracy of classification when using machine learning. This paper presents the importance of the effect of device type number on the classification of IoT devices. Therefore, inference attacks on privacy with machine learning algorithms, attacks on machine learning models, and the padding method that is commonly used against such attacks are presented. Moreover, experiments are carried out by using the dataset of the traffic generated by the Internet of Things (IoT) devices. For this purpose, Random Forest, Decision Tree, and k-Nearest Neighbors (k-NN) classification algorithms are compared, and the accuracy rate changes according to the number of devices are presented. According to the results, the Random Forest and Decision Tree algorithms are found to be more effective than the k-NN algorithm. When considering a scenario with two device types, the Random Forest and Decision Tree algorithms achieved an accuracy rate of 98%, outperforming the k-NN algorithm, which had an accuracy rate of 95%.
Multidisciplinary approach to the treatment of children with congenital cleft lip and palate in Ukraine
Authors: Filonenko V. , Kaniura O. , Bidenko N. , Iefymenko V. , Iakovenko A.
Published: April 2024

Children with congenital cleft lip and palate (CLP) develop a composite complex of anatomical, functional and aesthetic disorders that increase with growth and require comprehensive and multi-stage treatment. Treatment and diagnostic measures require a multidisciplinary approach to overcome the identified problems. The main task of orthodontic support for children with CLP at the stages of primary surgical interventions is aimed at preventing orthognathic surgical correction in the future, by optimizing the choice and tactics of orthodontic treatment within the framework of multidisciplinary comprehensive rehabilitation measures. The purpose of the work is the substantiation, approval and introduction into clinical practice of a complex of medical and diagnostic measures aimed at the rehabilitation of children with CLP. It confirmed that providing the necessary conditions for sucking creates optimal conditions for surgical intervention on the lip and palate. The tactics of orthodontic treatment depended on the period of development of the dentognathic apparatus, age, type of cleft, staging, timing and volume of surgical interventions, quality and methods of surgery, severity of deformations in the transversal and sagittal planes and components of the symptom complex of anomalies and deformations complicating the pathology, psychological and emotional child state, factors of parents and patients communication with the doctor, social and economic components. Removable and fixed orthodontic appliances are used in most cases at the initial stage of treatment for the treatment of dentognathic deformities, obtaining satisfactory sagittal and vertical overlap and normalization of transversal ratios. A separate area of rehabilitation was prevention and treatment of diseases of hard tissues of teeth and periodontal tissues. Speech therapy and psychological support started from 2–3 months. The proposed complex of treatment and diagnostic measures, determined in time, terms, sequence and volume, aimed at the rehabilitation of children with CLP, made it possible to obtain positive anatomical, functional and aesthetic results in 87.6% of children.

Keywords: therapeutic and diagnostic measures, orthodontic treatment, speech therapy and psychological support, rehabilitation algorithm.
Kızamık Hastalığı ve Bağışıklamasında Göz Ardı Edilen Grup: Genç Erişkinler
Authors: Beyazgül Burcu , Gündüzalp Ahmet
Published: April 2024

Kızamık, Rubeola virüsünün sebep olduğu, sıklıkla çocukluk çağında görülen ve oldukça bulaşıcı akut bir enfeksiyondur. Hastalık ateş ve makülo-papüler döküntü ile karakterizedir. Virüsün insan dışında rezervuarı olmayıp, tek doğal konağı insandır (1). Kızamık, aşı ile önlenebilir hastalıklar içinde en bulaşıcı olanıdır. Hava yolu ile bulaşması bulaştırıcılığını arttıran önemli faktörlerden birisidir. Hastalar döküntünün başlamasından dört gün öncesine ve dört gün sonrasına kadar bulaştırıcı kabul edilmektedir. Bir hasta 16-18 kişiyi enfekte edebilir. Genel olarak iyi seyirli bir çocukluk çağı hastalığı olarak bilinse de, ciddi komplikasyonlarla ölüme neden olabilmektedir. Beş yaş altındaki çocuklarda çok önemli olmakla birlikte, 20 yaş üzerindeki erişkinlerde de görülmektedir. Kızamık virüsü için kaynak sadece insan olduğu için eliminasyonu mümkün olan bir hastalıktır. Kızamık virüsü ılıman bölgelerde genellikle kış ayları sonunda ve bahar aylarında yayılım göstermektedir (2). Aşılama, kızamık hastalığından korunma ve hastalığın kontrolünde bilinen etkili bir yöntemdir (3). Yaş arttıkça kızamık seroprevalans düzeyinin arttığı ve bu artışın 30 yaş ve üzerinde daha belirgin olduğu literatürdeki birçok çalışma ile açıkça gösterilmiştir. 18-30 yaş aralığındaki genç erişkin bireylerin kızamık seroprevalans düzeylerinin diğer yaş gruplarına kıyasla belirgin düşük olduğu görülmektedir. Ancak, yetişkinlerdeki bu seroprevalans düşüklüğü bir yetişkin sağlığı sorunu olarak algılanmamalıdır. Bu yürütülmekte olan GBP sorunu ya da çocukluk dönemi aşılama sorunlarının bir uzantısı olarak görülmeli ve buna göre uygulamalar gözden geçirilmelidir.
Salgını önleme konusunda birinci basamak sağlık hizmetlerine önemli görev düşmektedir. 18-30 yaş aralığındaki bireylere catch-up (yakalama) aşılama yöntemi ile ekstra doz kızamık aşısı uygulanmasının yeniden değerlendirilmesinin gerekli olabileceğini düşündürmektedir. Catch-up aşılaması sonrası %95’in altında aşılama oranında kalmış yerler var ise Mop-up aşılama yöntemine geçilip, kapı kapı dolaşarak catch-up kampanyasında aşılanmamış bireylerin aşılanması sağlanmalıdır.
Salgının bir diğer nedeni de son yıllarda hem dünyada hem de ülkemizde artış gösteren aşı redleridir. Aşı redlerinin ülkemizde en çok Güneydoğu Anadolu bölgesinde olduğu bilinmektedir (26). Aşı redlerine karşı önlem amacıyla aşılamanın önemi mutlaka ailelere kavratılmalı ve aşı takviminin 2 yaşında bitmediği, okul döneminde de devam ettiği söylenmelidir. Kızamığın eliminasyonu hedeflenen ülkemizde tüm toplumun kızamık ve kızamık aşısı hakkında yeterli düzeyde bilgilendirilmesi gerekmektedir. Bu durum salgınların önüne geçilmesi ve kızamık eliminasyonu açısından da son derece önemlidir.
The emergence and clinical significance of artificial intelligence–enhanced electrocardiography
Authors: Baek Yong-Soo
Published: April 2024

The integration of artificial intelligence (AI) with electrocardiography (ECG), a technology known as AI-ECG, represents a transformative leap in the field of cardiovascular medicine. This innovative approach has significantly advanced the capabilities of ECG, traditionally used for diagnosing heart diseases. AI-ECG excels in detecting subtle changes and interconnected patterns in cardiac waveforms, offering a level of precision and sensitivity that was previously unattainable with conventional methods. The scope of AI-ECG extends beyond the realm of heart diseases. It has shown remarkable potential in predicting and identifying the impacts of noncardiac conditions on heart health, thereby broadening the diagnostic capabilities of ECG. This is especially valuable given the complex nature of cardiovascular diseases and their interactions with other health conditions. Despite its groundbreaking potential, AI-ECG faces several challenges. One of the primary concerns is the "black box" nature of AI algorithms, which can make the decision-making process opaque and difficult to interpret. This poses a challenge in medical settings where understanding the rationale behind a diagnosis is crucial. Additionally, the effectiveness of AI-ECG is dependent on the quality and diversity of the datasets used to train the algorithms. Limited or biased datasets can lead to inaccuracies and diminish the reliability of the technology. However, the benefits of AI-ECG are significant. It enables faster, more accurate diagnoses and has the potential to greatly enhance the efficiency of cardiovascular care. As research and technology continue to evolve, AI-ECG is poised to become an indispensable tool in the diagnosis and management of heart diseases.
KLASIFIKASI TEKS ULASAN APLIKASI NETFLIX PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN SVM
Authors: Khoirunnisaa Nabiilah , Nabila Nastiti Kesuma Kaylista , Setiawan Septhiyanthi , Yunizar Pratama Yusuf Ajif
Published: April 2024

Netflix ialah platform streaming berlangganan yang menyajikan beragam acara seperti tv series, dokumenter, serta film yang terhubung pada sebuah perangkat yang terkoneksi dengan internet. Netflix salah satu platform aplikasi streaming video yang digunakan paling banyak di seluruh dunia dan kini mulai menerapkan teknologi analisis data dan machine learning untuk meningkatkan layanan penggunanya. Melalui Google Play Store, pengguna dapat menyampaikan berbagai macam ulasan mengenai aplikasi Netflix. Dari banyaknya data ulasan tersebut, dapat dimanfaatkan untuk mengekstrak informasi penting yang tersembunyi dan bermanfaat untuk mengevaluasi kualitas suatu aplikasi. Oleh karena itu, penelitian ini bertujuan guna mengklasifikasikan ulasan teks aplikasi Netflix dengan membandingkan dua algoritma yang diterapkan yakni, Support Vector Machine (SVM) serta Naive Bayes. Dengan maksud untuk mendapati manakah algoritma yang lebih efektif dari segi akurasinya. Dataset diperoleh melalui Google Play Store dan menerapkan metode scraping, sebanyak 1000 ulasan dan diolah menggunakan bahasa pemrograman Python. Kemudian data ulasan aplikasi Netflix yang telah didapatkan dipecah menjadi train data 70% dan test data 30%. Penerapan algoritma Naive Bayes mendapatkan hasil accuracy senilai 82%, lalu Support Vector Machine (SVM) memperoleh hasil accuracy senilai 85%. Sehingga, menunjukkan hasil penerapan algoritma Naive Bayes tidak lebih efektif dibandingkan Support Vector Machine (SVM).
Relating tradition to innovation within the Chinese arts: the application of digital technique to visual art
Authors:   , Ke Lijia
Published: April 2024

Along with the rapid development of technology and worldwide cultural exchange, there has been a conflict between the traditional and modern within China. In the visual art area currently, the biggest impact would be that of digital technique on traditional art, especially painting. After many decades of chasing the 'global standard', and the concern that the so called national culture might be abandoned by the next generation, finding the link between the traditional and the modern becomes imperative for the Chinese. In order to make a contributuon to this process, this study focuses on the potential of digital media in the context of traditional visual art, in particualr on Chinese literati painting.
APPLICATION OF COMPLEX METHODS OF FORMING A PERSONNEL RESERVE ON THE EXAMPLE OF AN ENTERPRISE WORKING IN THE FIELD OF INFORMATION TECHNOLOGY
Authors:   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Vilken Victoria V. , Fedorova Ekaterina S. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Skryabina Sofia M. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Published: April 2024

The application of scientific approaches in the management of the personnel reserve of enterprises in the information technology field is an urgent topic due to the importance of this area in the country's economy and its active development. Information technologies represent the sphere of highly intelligent work, which determines the complexity in personnel management and the investment nature of personnel reserve programs. The article presents the results of a study devoted to the analysis of methodology and the search for commonality in the application of current scientific approaches to personnel reserve management in organizations in the information technology field. Examples of their application in the organization in which the authors of the article were trained are presented.
ORGANIZATION OF PROJECT ACTIVITIES OF STUDENTS AT THE REQUEST OF EMPLOYERS: METHODOLOGICAL FOUNDATIONS FOR FORMING STUDENT TEAMS
Authors:   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Ivanova Marina V. , Livintsova Maria G. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Published: April 2024

The development of real projects commissioned by employers as part of the implementation of student project activities makes it possible to achieve maximum interactive and practice-oriented educational programs. A relevant and promising tool for implementing student project activities can be the formation of multipotential student teams, formed from students of various fields and specialties of training to work on projects proposed by employers. The article discusses methodological issues of forming multipotential student teams as a form of project work for students in higher educational institutions in order to bridge the gaps between the requirements of employers and the qualifications of graduates. The tools proposed by the authors for organizing competitive selection into project teams are focused on the formation of a student team representing various areas of training and meeting the requirements for effective project work. The proposed selection methodology also makes it possible to take into account the interests of the university and employers when developing the project task.
INTANGIBLE MOTIVATION SYSTEM AS A STRATEGIC FOCUS TO DEVELOP HUMAN POTENTIAL IN RUSSIAN UNIVERSITIES
Authors:   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Vrublevskaya Maria V.
Published: April 2024

The article deals with the qualitative research with special reference to leading Russian universities participating in the strategic academic leadership program ‘Priority 2030’. The paper presents key findings based on document study of the research universities development programs. The basic principles and solutions of how to execute transition from human resources to human capital management model have been examined using the sample of the bespoke universities. The article considers consistence patterns and discrepancies of human capital management models comparatively to the size and location of the universities.
MODELS OF EMPLOYMENT OF UNIVERSITY GRADUATES IN MODERN CONDITIONS OF THE FORMATION OF AN INTERLEVEL NETWORK MODEL OF SEAMLESS EDUCATION
Authors:   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Shchepinin Vladimir E. , Rodionov Dmitry G. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Eremina Irina A. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Published: April 2024

The study examined the main characteristics of the interlevel network model of seamless education, which is an important component of modern educational practice and is aimed at training qualified specialists who are able to work effectively in a rapidly changing world. The inter-level network model of seamless education is a concept of education that seeks to combine different educational levels, contexts and forms of learning into one continuous learning environment. During the analysis, the main reasons hindering the effective employment of graduates are scientifically substantiated, mechanisms and methods for job search are systematized in the context of the formation of an inter-level network model of seamless education. A detailed study of the application of employment models for graduates who studied in modern conditions of formation, development and functioning of an inter-level network model of seamless education made it possible to identify their key features and develop recommendations for improving mechanisms for solving problems that arise for young professionals trying to find their first job after graduation. Further study of the graduate employment process will help ensure that educational programs meet the needs of the labor market and eliminate the identified contradictions, which, on the one hand, will make it easier for young people to find work, and on the other hand, will open up new opportunities for employers in solving personnel issues. To achieve this compliance, the principles of interaction between the educational services market and the labor market were developed in the context of the formation of an inter-level network model of seamless education. The employment models of university graduates are directly related to the growth of the country's development rate. The high level of graduate employment contributes to the economic and social development of Russia and its regions, contributes to the growth of labor productivity and income of the population, poverty reduction, and a better future for graduates and society as a whole. In order to develop the considered models of graduate employment, it is proposed to introduce an additional educational program for the development of an inter-level network model of seamless education not only in a separate university, but also in a single subject of the Russian Federation, and the main criteria for evaluating the effectiveness of this program have been developed. Seamless education is an essential component of improving the efficiency of the entire higher education system of the Russian Federation.
METHODS FOR STUDYING SOCIAL REPRESENTATIONS STUDENTS ABOUT TRADITIONAL AND MULTIVARIATE CAREERS IN THE CONTEXT OF THE DEVELOPMENT OF MODERN HIGHER EDUCATION
Authors:   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia, Shchepinin Vladimir E. , Rodionov Dmitry G. ,   Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Published: April 2024

The analysis of theoretical sources on the research problem showed that the concept of a multivariate career is still quite young and has not been fully explored, which opens up a fairly large range of promising areas of study. Traditional and multivariate careers can be studied using social ideas, which will help to more accurately and better understand these phenomena. And it is the social ideas of students, as a special socio-psychological and age category, that will be able to provide a clear vision and understanding of the chosen issue. Theoretical approaches to the study of social ideas in domestic and foreign literature were considered, the phenomenon of «career» in modern research was characterized, a program and methods of empirical research were developed, and the results of the study were analyzed and interpreted. It has been scientifically proven that students' multivariate careers mean that they strive to develop not only in one area, but also in several different directions. Among the students of the «Economics » direction, the following areas were identified: «active and active career», «free career», «career associated with starting one’s own business», «career involving continuous development», «integration of lifestyles», «career, associated with risks», «hard career». In the course of conducting an empirical study of students’ social ideas about traditional and multivariate careers, it was possible to develop a program and methods of empirical research; for this purpose, the method of subjective scaling and the «Career Anchors» technique of E. Schein were taken, and the Kruskal-Wallis H-criterion, U-Mann-Whitney test and factor analysis. It was found that, in general, students view modern careers as more multivariate, and also that the social ideas of students in various fields of study about a promising career actually have a certain content specificity. The students studied have the idea that real careers have changed and are still constantly changing due to the demands of the modern world.
VETERINARY AND SANITARY REQUIREMENTS AT INSIDE AND HOUSEHOLD ANIMAL SLAUGHTERING
Authors:   Russian Biotechnological University, (BIOTECH University), Moscow 125080, Russian Federation, Seryoguin Ivan G. , Kozaк Yulia A. ,   Russian State Agricultural University – MSHA named after K.A.Timiryazev, Moscow 127434, Russian Federation
Published: April 2024

Animal slaughtering proper organization and meat raw material control are of great importance for population providing with meat. Animal slaughtering for meat and carcasses cutting up are the complex of difficult manufacturing operations that must be made in accordance with technologic instructions, standards and veterinary and sanitary expertise regulations.
DETERMINATION OF THE RESIDUAL CONTENT OF PESTICIDES IN EXOTIC FRUITS BY GAS CHROMATOGRAPHY
Authors:   Russian Biotechnological University (ROSBIOTECH), Moscow 125080, Russian Federation, Kulach Polina V. , Nityaga Inga M. ,   Russian Biotechnological University (ROSBIOTECH), Moscow 125080, Russian Federation, Satyukova Ludmila P. ,   Russian Biotechnological University (ROSBIOTECH), Moscow 125080, Russian Federation, Shikhov Sergey S. ,   Russian Biotechnological University (ROSBIOTECH), Moscow 125080, Russian Federation, Krylova Polina A. ,   Russian Biotechnological University (ROSBIOTECH), Moscow 125080, Russian Federation
Published: April 2024

This article will describe an improved method for determining the residual amount of pesticides in 40 sample of exotic fruits purchased on the food market.