bluuebunny/crossref_metadata_2025 huggingface dataset:
INFLUENCE OF THE ASSORTMENT POLICY ON THE FORMATION OF THE FINANCIAL RESULTS OF THE ENTERPRISE
Authors: Piatak Tetianaail
Published: December 2023

In the course of the conducted research, an integral model was proposed that can be used to form an optimal assortment policy aimed at achieving the planned financial results of the enterprise. The integrated model allows for dynamic analysis of the relationship between the range of products, the volume of production, operating leverage and the financial results of the enterprise obtained from the sale of each type of manufactured product. Stimulating measures for the sale of products and management of receivables are proposed, which are developed on the basis of individual flexible pricing for the company's products. Price discounts to stimulate product sales have been determined and measures have been proposed to shorten the repayment terms of receivables, the expediency of attracting loan funds to expand the financing of operational activities based on the use of financial leverage has been analyzed. The use of financial leverage as a management tool provides an opportunity to form an effective capital structure for a certain range of products. A mechanism for forming the optimal assortment of products is proposed, which allows taking into account the influence of internal and external factors on the financial results of the enterprise. Such a mechanism involves conducting research using the method of successive approximations, by choosing the optimal combination of selected factors to obtain the planned financial result in the future. The created mechanism involves the use of an integral model that allows establishing the necessary relationships between the structural divisions of the enterprise. The integrated model includes the modules necessary for the implementation and functioning of the mechanism by which the optimal assortment of the company's products is formed. Thus, the defined set of external and internal factors in combination with organizational production planning provides an opportunity to form the most acceptable range of products for the enterprise and allows to forecast the financial results of the enterprise and control their dynamics under the influence of these factors in the planning period.
SMART SPECIALIZATION STRATEGY AS AN INNOVATIVE BASIS OF GLOBAL ECONOMIC DEVELOPMENT: EUROPEAN EXPERIENCE
Authors: Maslak Olga , Gryshko Natalia , Yakovenko Yaroslava , Hladenkyi Bohdan , Marchenko Vitaliy
Published: December 2023

The strategy of smart specialization rightly serves as a key reference point for the economic development of individual industries and regions. This study is aimed at analyzing the European experience in applying the strategy of smart specialization as an innovative basis of global economic development. It is becoming increasingly clear that the strategy of smart specialization can fundamentally change the rules for many industries. The research focuses on the fact that by focusing on specific areas of knowledge and developing targeted capabilities, businesses and organizations can find unique niches and gain a competitive advantage. The smart specialization strategy also has drawbacks, as it requires a deep understanding of the industry and a willingness to invest in specialized skills and resources, or may need to move away from broader, more general strategies to achieve smart specialization. However, it is emphasized that the benefits of smart specialization are clear when it comes to standing out in a crowded marketplace, building deeper relationships with customers, and ultimately driving growth. As industries continue to develop and become more complex, the strategy of smart specialization does not lose its relevance, and the European experience of its implementation will be useful for Ukraine.
Posterior Tibiotalar Impingement After Pediatric Ankle Fracture Surgical Fixation
Authors: Liu David S. , Watkins Ian T. , Adams Taylor , Kramer Dennis E. , Watkins Colyn J.
Published: December 2023

Case:

A 13-year-old healthy, nearly skeletally mature, female patient presented to an outpatient clinic after sustaining a bimalleolar ankle fracture-dislocation, which was subsequently treated with open reduction and internal fixation and casting. Postoperatively, the patient had significant limitations to ankle range of motion. Imaging revealed posterior tibiotalar impingement. The patient underwent arthroscopic debridement and osteoplasty, and she was able to return to previous levels of activity.

Conclusions:

Complications from pediatric ankle fractures are rare, so further diagnostic workup is warranted for patients with persistent pain and limitations.
Exploration and Development of Shale Oil in China: State, Challenges, and Prospects
Authors: Jin Z. , Liang X.
Published: December 2023

—This article presents the latest state of exploration and development of shale oil of continental lacustrine formations in the main basins of China, summarizes the main theoretical considerations and key technologies for exploration and development, and suggests prospects for exploration and development of shale oil in China. It is believed that the exploration and development of oil in shale formations rich in organic matter of types I and II of medium and high maturity are key to the breakthrough of production of 10 million tons in China. This will play an important role in China’s stable oil production at the level of 200 million tons per year in the future. The efficient development of medium- and low- maturity shale oil resources can be significantly improved and lead to serious changes in oil production only after new breakthroughs in the theory and technology of shale deposits.
Distributed Multi-Agent Learning is More Effectively than Single-Agent
Authors: Ke Shuya , Liu Wenqi
Published: December 2023

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. Interpretable distributed group intelligence techniques have emerged as an essential topic in artificial intelligence. The mathematical interpretability of prediction outcomes is critical for improving the reliability of machine learning, especially in random scenes. Although some experimental results published so far show that the prediction of group intelligence is better than individual intelligence, establishing a mathematical foundation for the superiority of distributed group intelligence is still a challenging problem for enhancing the interpretability of learning systems. Through the Radermacher complexity principle, we proved mathematically that the learning quality of group machine intelligence is better than its subset machine intelligence with a high probability, significantly better than any individual among them if the number of individuals in the group is large enough. We proposed a multi-agent distributed learning method for time series forecasting by incorporating multi-agent cooperation in cognitive processes into machine learning. In addition, since the way of cooperative interaction between multi-agent affects the training effect of the model, we provide a generalized interaction approach and prove its convergence. We conduct sufficient experiments on predicting time series for classically chaotic systems, and the results indicate that distributed group intelligence significantly improves the prediction accuracy of individual intelligence. The experiments result shows that the prediction error reduces substantially as the number of agents increases, confirming the theoretical accuracy and the model's validity. This work provides new ideas for theoretically exploring how group intelligence emerges.
Challenges to Diagnosis of SARS-CoV-2 Infection in the Nervous System
Authors: Silva Samya Jezine da , Cabral–Castro Mauro Jorge , Gonçalves Cássia A , Mariani Diana , Ferreira Orlando , Tanuri Amílcar , Puccioni-Sohler Marzia
Published: December 2023

The SARS-CoV-2 may invade the nervous system but it is rarely found in the cerebrospinal fluid (CSF). We evaluated the accuracy of real-time reverse transcription-polymerase chain reaction (real-time RT-PCR) for SARS-CoV-2 combined with specifics IgG and IgM, neopterin and CXCL-10 in 70 CSF from patients with neurological disorders associated or not with COVID-19. We found 57.1% sensitivity for IgG, 28.57% for IgM, 100% specificity for both tests, and higher protein and CXCL-10 in COVID-19 groups. No samples were positive for RT-PCR in CSF. Although the limited sensitivity, the reactive tests may still contribute to confirm the diagnosis of neurological complications associated with COVID-19.
HIF-1α participates in the regulation of S100A16-HRD1-GSK3β/CK1α pathway in renal hypoxia injury
Authors: Liang Xiubin , Han Shuying , Jin Runbing , Huo Lei , Zhao Lihua , Zhang Kaini , Li Rongfeng , Su Dongming
Published: December 2023

S100 calcium-binding protein 16 (S100A16) is implicated in both chronic kidney disease (CKD) and acute kidney injury (AKI). Previous research has shown that S100A16 contributes to AKI by facilitating the ubiquitylation and degradation of glycogen synthase kinase 3β (GSK3β) and casein kinase 1α (CK1α) through the activation of HMG-CoA reductase degradation protein 1 (HRD1). However, the mechanisms governing S100A16-induced HRD1 activation and the upregulation of S100A16 expression in renal injury are not fully understood. In this study, we observed elevated expression of Hypoxia-inducible Factor 1-alpha (HIF-1α) in the kidneys of mice subjected to ischemia-reperfusion injury (IRI). S100A16 deletion attenuated the increased HIF-1α expression induced by IRI. Using a S100A16 knockout rat renal tubular epithelial cell line (NRK-52E cells), we found that S100A16 knockout effectively mitigated apoptosis during hypoxic reoxygenation (H/R) and cell injury induced by TGF-β1. Our results revealed that H/R injuries increased both protein and mRNA levels of HIF-1α and HRD1 in renal tubular cells. S100A16 knockout reversed the expressions of HIF-1α and HRD1 under H/R conditions. Conversely, S100A16 overexpression in NRK-52E cells elevated HIF-1α and HRD1 levels. HIF-1α overexpression increased HRD1 and β-catenin while decreasing GSK-3β. HIF-1α inhibition restored HRD1 and β-catenin upregulation and GSK-3β downregulation by cellular H/R injury. Notably, Chromatin immunoprecipitation (ChIP) and luciferase reporter assays demonstrated HIF-1α binding signals on the HRD1 promoter, and luciferase reporter gene assays confirmed HIF-1α's transcriptional regulation of HRD1. Additionally, we identified Transcription Factor AP-2 Beta (TFAP2B) as the upregulator of S100A16. ChIP and luciferase reporter assays confirmed TFAP2B as a transcription factor for S100A16. In summary, this study identifies TFAP2B as the transcription factor for S100A16 and demonstrates HIF-1α regulation of HRD1 transcription within the S100A16-HRD1-GSK3β/CK1α pathway during renal hypoxia injury. These findings provide crucial insights into the molecular mechanisms of kidney injury, offering potential avenues for therapeutic intervention.
Assessing well-being of university students and evaluation of its determinants
Authors: Szepe Orsolya , Meszaros Agnes
Published: December 2023

Background:Well-being as well as stress and anxiety get more attention today especially in case of university students; the beginning of university life is an important period of transition from adolescence to young adulthood, which brings many challenges and difficulties for the student due to the general stressors. The aim of our study was to examine the well-being of students studying at the three (non-medical) faculties of Semmelweis University Budapest and to analyse the relationships between well-being, stress, emotional support, sleep patterns, sport and further variables like smoking, consumption of sleeping pills, sedatives, energy drinks and exam anxiety.
Methods: Our survey was a non-interventional, cross-sectional study. In our questionnaire we asked questions about academic performance in the form of average grade of the previous term, physical activity/ sports, sleep patterns, medication use, alcohol and energy drink consumption habits. Our questionnaire asked students also about the level of anxiety they experience during exams, two internationally recognised instruments were applied, the WHO-5 Well-Being Index and the Perceived Stress Scale.
Results:the mean WHO-5 well-being index was 42.62+20.51 on a scale ranging from 0 to 100. We saw an inverse correlation between student well-being, years of study. The average anxiety level regarding oral exam, assessments was 7.63+SD=2.04, while the mean level was lower concerning written exams and assessments 5.74+SD=2.09. The result of a linear regression model indicates that the best level of explaining power by the regression model was with following variables combination: grade average + anxiety before written exam + academic year + stress.
Conclusion: Our data indicate that some students have poor or very poor well-being, which fluctuates over the study period. The worst state was found in the first and final academic year. The students’ well-being level is positively correlated with emotional support, physical activity and quality of sleep and correlates negatively with anxiety before exams. Our results suggest that the well-being could be improved when universities play an active role, supporting influential activities and offering help regarding coping with stress, like stress management, as well as by providing information on learning methods and techniques.
Analysis of the diagnostic flow of cutaneous leishmaniasis in the state of Minas Gerais-Brazil
Authors: Medeiros Fernanda Alvarenga Cardoso , Filho Job Alves Souza , Reis Ilka Afonso , Menezes-Souza Daniel , Silva Aline Fagundes da , Marcelino Andreza Pain
Published: December 2023

Objective
To assess the performance of the proposed new diagnostic pathway in patients with suggestive clinical symptoms of CL within MG's public laboratory network.
Methods
This is a descriptive study where the results of CL tests were analyzed in patients with clinical suspicion of the disease who had their tests conducted within MG's public laboratory network and the results were registered in the Laboratory Management System of the Ezequiel Dias Foundation, during the period from 2017 to 2020.
Results
Out of a total of 1,369 individuals analyzed, the diagnosis of CL was confirmed in 704 (51.4%), with 610 (86.7%) through DPE and 94 (13.4%) through PCR. Additionally, 53 (25.3%) patients with negative DPE results showed positive PCR results.
Conclusion
The proposed CL diagnostic pathway in MG proved to be effective as it ensures that the initial test is conducted on-site, allowing for greater access and efficiency in the treatment of confirmed cases. PCR demonstrated to be an effective confirmatory test.
Guiding antibiotics towards their target using bacteriophage proteins
Authors: Zhao Xinghong , Zhong Xinyi , Yang Shinong , Deng Jiarong , Deng Kai , Huang Zhengqun , Li Yuanfeng , Yin Zhongqiong , Liu Yong , Viel Jakob , Wan Hongping
Published: December 2023

Novel therapeutic strategies against difficult-to-treat bacterial infections are desperately needed, and the faster and cheaper way to get them might be by repurposing existing antibiotics. Nanodelivery systems enhance the efficacy of antibiotics by guiding them to their targets, increasing the local concentration at the site of infection. While recently described nanodelivery systems are promising, they are generally not easy to adapt to different targets, and lack biocompatibility or specificity. Here, nanodelivery systems are created that source their targeting proteins from bacteriophages. Bacteriophage receptor-binding proteins and cell-wall binding domains were conjugated to nanoparticles, for the targeted delivery of rifampicin against bacterial pathogens. They showed excellent specificity against their targets, and accumulated at the site of infection to deliver their antibiotic payload. Moreover, the nanodelivery systems suppressed pathogen infections more effectively than higher doses of free antibiotic. This study demonstrates that bacteriophage sourced targeting proteins are promising candidates to guide nanodelivery systems. Their specificity, availability, and biocompatibility make them great options to guide the antibiotic nanodelivery systems that are desperately needed to combat difficult-to-treat infections.
Real-time monitoring of mitochondrial oxygenation during machine perfusion using resonance Raman spectroscopy predicts organ function
Authors: Jain Rohil , Ajenu Emmanuella O. , Hafiz Ehab O.A. , Romfh Padraic , Tessier Shannon N.
Published: December 2023

Organ transplantation is a life-saving procedure affecting over 100,000 people on the transplant waitlist. Ischemia reperfusion injury is a major challenge in the field as it can cause post-transplantation complications and limits the use of organs from extended criteria donors. Machine perfusion technology is used to repair organs before transplant, however, currently fails to achieve its full potential due to a lack of highly sensitive and specific assays to predict organ quality during perfusion. We developed a real-time and non-invasive method of assessing organ function and injury based on mitochondrial oxygenation using resonance Raman spectroscopy. It uses a 441 nm laser and a high-resolution spectrometer to predict the oxidation state of mitochondrial cytochromes during perfusion, which vary due to differences in storage compositions and perfusate compositions. This index of mitochondrial oxidation, or 3RMR, was found to predict organ health based on clinically utilized markers of perfusion quality, tissue metabolism, and organ injury. It also revealed differences in oxygenation with perfusates that may or may not be supplemented with packed red blood cells as oxygen carriers. This study emphasizes the need for further refinement of a reoxygenation strategy during machine perfusion that is based on a gradual recovery from storage. Thus, we present a novel platform that provides a real-time and quantitative assessment of mitochondrial health during machine perfusion of livers, which is easy to translate to the clinic.
Identification of Biomarker Genes in the Early Immune State of Bladder Epithelial Cancer
Authors: Wang Shuai , Zhang Lingyun , Qiu Zeliang
Published: December 2023

Background:This study aims to comprehensively understand the complex immune response imbalance in bladder epithelial cancer through the identification of highly immune-correlated hub genes and the development of a clinical diagnostic model.
Methods: The bladder epithelial cancer-related dataset was retrieved from the TCGA database. The Xiantao tool was utilized to obtain immune infiltration data for constructing the WGCNA module. Data processing involved the application of the RAA and SVA algorithms. The MCODE plug-in was utilized for target screening, immune data collection, and unsupervised clustering analysis. Multiple models were constructed to identify hub genes, and gene expression consistency was validated through animal experiments, data analysis with the assistance of Xiantao tools.
Results: Our integrated computational biology and experimental approach revealed six key genes closely related to bladder epithelial cancer and immunity: MMP8, MMP15, MMP2, MMP11, CXCL2, CXCL5,MMP15, and IL-7 .These genes facilitated the classification of patients into three subtypes, with the C2 subtype exhibiting significantly distinct levels of immune infiltration, indicating partial activation of the immune system.This finding presents a novel approach for early identification of bladder epithelial cancer.We identified CXCL2, and MMP15 as hub genes using four algorithms and developed a clinical prediction model that incorporates these features.The model demonstrated strong bladder epithelial cancer identification capabilities and exhibited a correlation with immune cell infiltration in bladder epithelial cancer patients.These genes are believed to play crucial roles in early bladder epithelial cancer detection and the regulation of the immune process.
Conclusion: Expression levels of CXCL2, and MMP15 serve as crucial indicators for identification of immune suppression in bladder epithelial cancer patients.
A stochastic encoder using point defect in two-dimensional materials
Authors: Das Saptarshi , Ravichandran Harikrishnan , Knobloch Theresia , Radhakrishnan Shiva Subbulakshmi , Stepanoff Sergei , Stampfer Bernhard , Ghosh Subir , Oberoi Aaryan , Waldhoer Dominic , Chen Chen , Redwing Joan , Wolfe Douglas , Grasser Tibor
Published: December 2023

Defects pose a significant challenge to the reliability of electronic devices, particularly when dealing with scaled dimensions in the silicon microelectronic industry. Consequently, extensive efforts have been made to eliminate these defects from devices through the optimization of growth and fabrication processes. However, in the realm of emerging nanomaterials, such as two-dimensional semiconductors, a different scenario unfolds, where defects are prevalent. It is crucial to comprehend how these defects can impact device reliability. In this study, we employ a multifaceted approach, encompassing atomistic imaging, density functional theory calculations, device modeling, and low-temperature transport experiments, to unveil the implications of defects on device reliability. Specifically, we investigate their influence on random telegraph signals. On a parallel track, it is worth noting that defects have proven to be beneficial in numerous quantum and energy-harvesting applications. Surprisingly, their potential for computational purposes remains largely untapped. In our study, we harness defects in aggressively scaled 2D transistors to accelerate an inference engine based on a stochastic spiking neural network, offering remarkable noise resilience. In conclusion, our investigation underscores the critical importance of comprehending and leveraging intrinsic point defects in 2D materials, both as challenges to reliability and as opportunities for neuromorphic computing.
Evaluation of naturally acquired immune responses against novel pre-erythrocytic P. vivax proteins in a low endemic malaria population located in the Peruvian Amazon Basin
Authors: Ventocilla Julio A. , Tapia L. Lorena , Ponce Reynaldo , Franco Adriano , Leelawong Mindy , Aguiar Joao C. , Baldeviano G. Christian , Wilder Brandon K.
Published: December 2023

Background
Plasmodium vivax (Pv) represents the most geographically widespread human malaria parasite affecting civilian and military populations in endemic areas. Targeting the pre-erythrocytic (PE) stage of the parasite life cycle is especially appealing for developing Pv vaccines as it would prevent disease and transmission. Here, we explore naturally acquired immunity to a panel of Pv PE antigens which may facilitate vaccine development and lead to a better understanding of naturally acquired PE immunity.
Methods
Twelve Pv PE antigens orthologous to a panel of P. falciparum antigens previously identified as highly immunogenic in protected subjects after immunization with radiation attenuated sporozoites (RAS) were used for evaluation of humoral and cellular immunity by ELISA and ELISpot. We used samples from Pv infected individuals (n = 76) from a low endemic malaria region in the Peruvian Amazon Basin.
Results
In our clinical samples, all PE antigens evaluated showed positive IgG antibody reactivity with a variable prevalence of 58–99% in recently P. vivax diagnosed patients. The magnitude of the IgG antibody response against PE antigens was lower compared with blood stage antigens MSP1 and DBP-II, although titers persisted better for PE antigens (average decrease of 6% for PE antigens and 43% for MSP1, p < 0.05). A significant correlation between IgG antibodies and the number of previous malaria episodes was observed only for blood stage antigens (p < 0.001). High IgG responders across PE and blood stage antigens showed significantly lower parasitemia compared to low IgG responders (median 1,921 vs 4,663 par/µl, p < 0.05). We observed a positive T cell response in 35% vs 9–35% of total volunteers against blood stage MSP1 and PE antigens, respectively, but no correlation with IgG responses.
Conclusions
Our results demonstrate clear humoral and T cell responses against Pv PE antigens in individuals naturally infected with P. vivax. These data identify novel attractive PE antigens suitable for use in the potential development and selection of new malaria vaccine candidates which can be used as a part of malaria prevention strategies in civilian and military populations living in Pv endemic areas.
Palynotaxonomy of Wissadula Medik. (Malvaceae: Malvoideae) in Brazil
Authors: Alves Gabriela Conde de Mello , Bovini Massimo G. , Mendonça Cláudia Barbieri Ferreira , Gonçalves-Esteves Vânia
Published: December 2023

Malvaceae is divided into nine subfamilies, one of which is Malvoideae. WissadulaMedik., a genus within the Malvoideae, is divided into two sections according to mericarp morphology and the number of ovules per locule. Species belonging to the section Euwissadula have 3 or rarely 2 ovules, whereas species belonging to the section Wissada have a single ovule. In Brazil, 19 species are recorded under the two sections, including a single species (Wissadula stipulata Bovini) in section Euwissadula and 18 species in section Wissada. This study analyzed pollen grains from both sections of Wissadula with the aim of confirming or not the existence of these sections based on pollen morphology. All 19 taxa occurring in Brazil were analyzed. The botanical material was collected from exsiccatae deposited in national herbaria and subjected to the acetolysis method. Subsequently, slides were prepared, examined under light microscopy, and photomicrographed. Pollen grains are shed as monads, isopolar, large, suboblate, and triporate. The polar area is small in most species and large in a few others. The exine is thick, with echinate ornamentation, granules, and perforations. It was possible to distinguish the analyzed species on the basis of pollen diameters and spine characteristics (dimensions and distance). The findings showed that the pollen grains of species belonging to the two sections of Wissadulaare very similar in size, shape, aperture type, aperture number, and sexine ornamentation.
The alteration of interspecific interaction responsed to various relative sowing time in wheat/maize intercropping
Authors: Sun Jun-Wei , Zhu Ying-An , Pang Yu , Liu Chen-Xi , Sun Jian-Hao , Zhang Wei-Ping , Li Long , Liu Yixiang
Published: December 2023

Purpose An interspecific interaction is an important reason for the yield advantage of interspecific cropping compared with sole cropping, and the relative sowing time of species is an important factor affecting interspecific competitiveness. Our purpose was to explore the effects of different relativesowing timeson the interspecific competition-recovery phenomenon in wheat and maize intercroppingsystems.
Methods Three planting methods (wheat/maize intercropping, wheat and maize sole cropping) and different relative sowing timesof wheat were used to carry out field experiments over two years. Sequential harvest of subplots was performed between 3 and 6 times, and the biomass data werefitted to logistic growth model.
Results Delaying the sowing time of wheat reduced the wheat yield, biomass and nutrient acquisition and increased those of maize, but wheat still had an intercropping advantage during the cogrowthperiod. At the same time, the nutrient acquisition of maize was still inhibited, but its recovery growth advanced.
Changing the relative sowing time of wheat significantly changed the maximum instantaneous growth rates of wheat and maize. Delaying the relative sowing time of wheat significantly decreased the maximum instantaneous growth rate of wheat and promoted that of maize to achieve a symmetric mutual benefit.
Conclusions Delaying the sowing time of wheat to the same sowing time as maize will change wheat/maize intercropping from asymmetrical interspecific facilitation to symmetrical interspecific facilitation. However, in this case, intercropped wheat still had an interspecific competitive advantage in the cogrowth stage, and intercropped maize still underwent a competition-recovery process.
Regularization by Deep Learning in Signal Processing
Authors: Villamarin Carlos Ramirez , Suazo Erwin , Oraby Tamer
Published: December 2023

In this paper, we explore a new idea of using deep learning representations as a principle for regularization in Inverse Problems for Digital Signal Processing. Specifically, we consider the standard variational formulation, where a composite function encodes a fidelity term that quantifies the proximity of the candidate solution to the observations (under a physical process), and a second regularization term that constrains the space of solutions according to some prior knowledge. In this work, we investigate deep learning representations as a means of fulfilling the role of this second (regularization) term. Several numerical examples are presented for signal restoration under different degradation processes, showing successful recovery under the proposed methodology. Moreover, one of these examples uses real data on energy usage by households in London from 2012 to 2014.
Solitary Fibrous Tumor of the Parapharyngeal Space: Report of 2 cases and a Literature Review
Authors: Laxague Francisco , Duncan Nicholas S. Murdoch , Jurado María Gracia Álvarez , Bilbao Érica Rojas , Mezzadri Norberto A. , Vila Juan M. Fernández
Published: December 2023

Purpose The solitary fibrous tumor (SFT) is usually described as a lesion arising from the pleura. Rarely, it has been described in the parapharyngeal space (PS). This study aims to report two cases of SFT in the PS and to perform a literature review on this topic.Methods Two patients undergoing surgical resection of a SFT in the PS were reported. A literature review on SFT of the PS was performed in order to develop a diagnostic and therapeutic algorithm.Results Two patients were analyzed. Both patients underwent surgical resection, followed by adjuvant radiotherapy, for SFT arising from the PS. The surgeries were uneventful and both patients recovered well after the procedure. No recurrences were diagnosed during the follow-up.Conclusion SFT of the PS is an infrequent entity. Surgical resection is the gold standard treatment, and adjuvant radiation should be considered in patients with risk factors for recurrence or distant metastases.
Seasonality but Not Tree Age Determines Secondary Plant Metabolite Composition in Scots Pine Needles
Authors: Gąsecka Monika , Ilek Anna , Magdziak Zuzanna , Saitanis Costas , Siegert Courtney
Published: December 2023

Background and Aims:
Secondary plant metabolites, including organic acids and phenolic compounds, play key roles in plant physiology and response to environmental stressors. How the production of these compounds varies across tree age and seasonality are of considerable interest to understanding plant stress response.
Methods
Monthly, we collected fallen needles of Scots pine (Pinus sylvestris L.) across stands of five different age classes (20, 40, 60, 80, 100 years) for one year and measured organic acids and phenolic compounds.
Results
Seven low molecular weight organic acids and thirteen phenolic compounds were detected. No differences were observed across stand age. Significant seasonal differences were detected. Most compounds peaked during the growing season. Succinic acid was the most prevalent organic acid, comprising 78% of total organic acids (351.27 ± 34.27 ug g− 1), and was 1.5 to 11.0 times greater in the summer than all other seasons. Sinapic acid was the most prevalent phenolic compound (42.15 µg g− 1) representing 11% of total phenolic compounds and was 39.8 times greater in spring and summer compared to autumn and winter. Growing season peaks in needle concentrations were observed for all thirteen phenolic compounds and two organic acids (lactic, succinic). Citric acid exhibited a definitive peak in late winter into early spring.
Conclusion
Our results highlight the change in secondary metabolite production in response to seasonality, likely in response to UV-B radiation and the onset of the growing season. These compounds protect against environmental stressors through metabolic reactions within needles as trees acclimate to seasonal conditions.
ARTS: Augmented Reality Tactical Sandbox for improved situational awareness in a multi-user scenario
Authors: Korkiakoski Mikko , Chakal Khalil , Fernando Roshan , Kostakos Panos
Published: December 2023

The Augmented Reality Tactical Sandbox (ARTS) is an augmented reality (AR)application that provides real-time immersive analytics of mission-critical information over a virtual map using a head-mounted display (HMD). Prior studies into AR concentrate on single-user experiences rather than having multiple users interacting with each other in the same AR realm. The research is especially lacking when considering situational awareness (SA) and in the case of more users: distributed SA (DSA). Unlike these previous studies, we focus on both the single-user experience and the multi-user experience and the differences between the two. Our application implements a service to enhance teamwork, remote collaboration, and SA. The multi-user environment is created using a client-server protocol over a RESTful HTTP service, allowing local and remote users to collaborate in real-time to accomplish objectives involving metaverse assets displayed on the map. We conducted a user experiment with 28 participants divided into two groups comparing the performance and SA of a single user and a team in a drone (co)piloting task using an AR map. We observed a carryover effect when going from a single user to a team and vice versa. There was no significant difference in SA between the tasks but overall single-user SA was better than multi-user. We also found that men performed significantly faster than women in the single-user task. The application illustrates how the concept of SA can be extended to the command and control domain.
A Four Years Longitudinal Study of Childhood Vaccination Trends and Supply Chain Resilience in Tanzania amid COVID-19 Pandemic
Authors: Sangeda Raphael Zozimus , James Daniel , Mariki Harrison , Mbwambo Mbonea Erick , Mwenesi Mwendwa E. , Nyaki Honesti , Tinuga Florian , Manyanga Daudi Peter
Published: December 2023

Background
The COVID-19 pandemic has significantly disrupted healthcare systems at all levels globally, notably affecting routine healthcare services such as childhood immunisations. This study delves into the impact of these disruptions on routine childhood vaccination programs in Tanzania.
Methodology
We conducted a longitudinal study over four years in five Tanzanian regions: Mwanza, Dar es Salaam, Mtwara, Arusha, and Dodoma. The study analysed trends in the usage of six key vaccines: Bacille Calmette-Guérin (BCG), Bivalent Oral Polio Vaccine (bOPV), Diphtheria Tetanus Pertussis, Hepatitis-B and Hib vaccine (DTP-HepB-Hib), measles-rubella (MR), Pneumococcal Conjugate Vaccine (PCV), and Rota vaccines. We evaluated annual and monthly vaccination trends using time series and regression analyses. Predictive modelling was performed using an Autoregressive Integrated Moving Average (ARIMA) model.
Results
The study recorded a total of 32,602,734 vaccination events across the regions from 2019 to 2022. Despite declining vaccination rates in 2020, there was a notable rebound in 2021, indicating the resilience of Tanzania's immunisation program. The analysis also highlighted regional differences in varying vaccination rates when standardised per 1000 population. Seasonal fluctuations were observed in the monthly vaccination rates, with BCG showing the most stable trend. Predictive modelling of BCG indicated stable and increasing vaccination coverage through 2023.
Conclusion
The findings underscore the robustness of Tanzania's childhood immunisation infrastructure in overcoming the challenges posed by the COVID-19 pandemic, marked by a strong recovery in vaccination rates post-2020. We provide valuable insights into the dynamics of vaccinations during a global health crisis and highlight the importance of sustained immunisation efforts in maintaining public health.
Electromagnetic Compatibility Issues in 400-MHz-Band Wireless Medical Telemetry Systems and Their Management Using Simplified Methods for Safe Operation
Authors: Ishida Kai , Fujii Kiyotaka , Hanada Eisuke
Published: December 2023

Wireless medical telemetry systems (WMTSs) are typical radio communication–based medical devices that monitor various biological parameters, such as electrocardiograms and respiration rates. In Japan, the assigned frequency band for WMTSs is 400 MHz. However, the issues accounting for poor reception in WMTS constitute major concerns. For example, the 400 MHz frequency band is also shared by other radio communication systems. Further, the intermodulation (IM) effect significantly reduces reception in WMTS. Additionally, the electromagnetic noises generated from electrical devices, such as light-emitting diode lamps and security cameras, can exceed the 400 MHz frequency band as these devices employ the switched-mode power supply and/or central processing unit and radiate wideband emissions. In this study, we analyzed the effects of the electromagnetic interferences caused by other radio communication systems, the IM effect, and the noises generated from electrical devices on WMTS and discussed their management. Moreover, we proposed and evaluated simplified and facile methods for evaluating the electromagnetic environment.
Reversing the directionality of reactions between non-oxidative pentose phosphate pathway and glycolytic pathway boosts mycosporine-like amino acid production in Saccharomyces cerevisiae
Authors: Hengardi Miselle Tiana , Cui Liang , Madivannan Keshiniy , Yang Lay Kien , Koduru Lokanand , Kanagasundaram Yoganathan , Arumugam Prakash
Published: December 2023

Background
Mycosporine-like amino acids (MAAs) are a class of strongly UV-absorbing compounds produced by cyanobacteria, algae and corals and are promising candidates for natural sunscreen components. Low MAA yields from natural sources, coupled with difficulties in culturing its native producers, have catalysed synthetic biology-guided approaches to produce MAAs in tractable microbial hosts like Escherichia coli, Saccharomyces cerevisiae and Corynebacterium glutamicum. However, the MAA titres obtained in these hosts are still low, necessitating a thorough understanding of cellular factors regulating MAA production.
Results
To delineate factors that regulate MAA production, we constructed a shinorine (mycosporine-glycine-serine) producing yeast strain by expressing the four MAA biosynthetic enzymes from Nostoc punctiforme in Saccharomyces cerevisiae. We show that shinorine is produced from the pentose phosphate pathway intermediate sedoheptulose 7-phosphate (S7P), and not from the shikimate pathway intermediate 3-dehydroquinate (3DHQ) as previously suggested. Deletions of transaldolase (TAL1) and phosphofructokinase (PFK1/PFK2) genes boosted S7P/shinorine production via independent mechanisms. Unexpectedly, the enhanced S7P/shinorine production in the PFK mutants was not entirely due to increased flux towards the pentose phosphate pathway. We provide multiple lines of evidence in support of a reversed pathway between glycolysis and the non-oxidative pentose phosphate pathway (NOPPP) that boosts S7P/shinorine production in the phosphofructokinase mutant cells.
Conclusion
Reversing the direction of flux between glycolysis and the NOPPP offers a novel metabolic engineering strategy in Saccharomyces cerevisiae.
The causal role of immune cells in asthma: a Mendelian randomization study
Authors: PAN Yu-shuo , QIN Yi-bing , Qu Ni-ni
Published: December 2023

Background
Immune cells may play a crucial role in the pathogenesis and progression of asthma. We conducted a Mendelian random analysis to evaluate the causal relationship between immune cells and asthma.
Objective
Immune cells play an important role in the development of asthma, but the specific relationship between them is not clear. This study aims to infer the causal relationship between them from the perspective of genetics.
Methods
The statistical data were collected from the published genome-wide association studies(GWAS)study of immune cells, and the genetic variation points were selected as instrumental variables(IVS).Inverse variance weighted (IVW), Weighted median, MR-Egger regression, Simple mode and Weighted mode were used for two sample Mendelian randomization (MR) analysis. Sensitivity analysis was used to test the heterogeneity, horizontal pleiotropy and stability of the results.
Results
IVW results showed that BAFF − R on B cell, BAFF − R on IgD− CD27−,BAFF − R on IgD+ CD24−,BAFF − R on IgD+ CD38dim,CD14 on CD33br HLA DR+ CD14dim,CD25 on B cell,CD25 on IgD+ CD24−,CD25 on IgD+ CD38− naive,CD25 on naive − mature B cell,CD25 on transitional,CD33 on basophil,CD33 on CD14+ monocyte,CD33 on CD33dim HLA DR+ CD11b−,CD33 on CD66b++ myeloid cell,CD38 on IgD− CD38dim,CD86 on myeloid DC,HLA DR on CD14− CD16+ monocyte, IgD+ CD38br %lymphocyte, Transitional %lymphocyte may be the risk factors of asthma,CD11b on CD14+ monocyte,CD24 on IgD+ CD38br,CD28 on CD45RA+ CD4+,CD45 on NK,CD28 on CD45RA+ CD4+,HLA DR+ NK %CD3− lymphocyte, HLA DR+ NK AC, IgD− CD38− %B cell, PDL − 1 on CD14+ CD16− monocyte, Plasmacytoid DC %DC may be a protective factor for asthma.
Conclusion
This study explored the causal relationship between immune cells and asthma, and screened out immune cells related to asthma. These immune cells may become new biomarkers or therapeutic targets, provide new treatment ideas for the prevention and treatment of asthma, and promote the understanding of asthma.
The Behavior of Seeking Professional Psychological Help Among Pregnant Women: A Qualitative Study in China
Authors: Xu Hongbin , Li Yingqi , Ma Xuemei , Yang Qin , Qiu Lei
Published: December 2023

This study aimed to understand the mental health status of pregnant women, clarify their needs for psychological help, and identify obstacles in seeking psychological help. Semi-structured interviews were conducted with 20 pregnant women, focusing on sources of psychological stress, expectations for psychological help, and difficulties in seeking psychological help. We distilled five themes: (1) Psychological conditions during pregnancy, which includes stress and emotional fluctuations and anticipations of postpartum challenges; (2) Barriers to seeking help, underscored by societal misconceptions, limited professional access, and varied familial support; (3) Sources of psychological stress, highlighting physical changes, familial and work pressures, and societal expectations; (4) Expectations for psychological assistance, emphasizing the need for professional understanding and societal awareness; (5) Impact of psychological issues on daily life, such as decreased work efficiency and affected social activities. Our conclusion points to a stark reality: Pregnant women in China confront significant psychological stress and face multiple barriers in accessing help. There is an urgent need for enhanced societal understanding and improved access to psychological services for this demographic.
Enhanced TSN Configuration Detection Using Optimized BPNN with Feature Selection for Industry 4.0
Authors: Wang Cheng , Chen Lin , Tang Chengjie , Wang Yongsong , Xian Yaqiao , Zhao Yuhao , Xue Hai , Huan Zhan
Published: December 2023

With the advancement of Industry 4.0, Time-Sensitive Networking (TSN) has become essential for ensuring prompt and reliable data transmission. As an augmentation of Ethernet, TSN aims to supply services capable of low latency, minimal jitter, and low packet loss for urgent data in decentralized, user-oriented networks. Efficient detection techniques are integral to TSN for swiftly determining the practicability of network configurations, as existing schedulability analysis proves insufficient. This paper delves into the potential of backpropagation neural networks (BPNN) in schedulability analysis efficiency. We optimize BPNN using spearman correlation feature selection combined with a voting ensemble method and Particle Swarm Optimization, forming two models: Spearman-Vote-BPNN and Spearman-PSO-BPNN. Testing on 5,000 network configurations in computer simulations, both models demonstrated high generalization accuracy, around 97.4%. Spearman-Vote-BPNN achieved the fastest training speed at 0.63 seconds and an accuracy of 98.2%. Meanwhile, Spearman-PSO-BPNN showed the highest accuracy (98.5%) with the quickest detection speed (5.6ms). The outcomes of this research significantly advance the efficacy and precision of TSN network configuration detection and establish a formidable groundwork for future scholarly pursuits in this area.
International Journal of Machine Learning and Cybernetics A Study of Repetitive Demand Prediction Based on Integrated Learning and Time Series
Authors: zhu Zhirong , Liu Yiwen , Tang Yan , Wen Wenkan
Published: December 2023

In this paper, we propose a time-series-based method to analyze the process of ‘‘repetition‘‘. The method is able to obtain the repetition reliability of the detectee from the attribute information of the detection target and the detection index at different time points, and to predict the probability of the possible outcome of the next detection. We address the local optimum phenomenon that may be brought about by traditional time series due to the low relevance of data dimensions and optimize and improve on the classical time series analysis model. We also combine an integrated learning model for prediction after comprehensive processing of the data. In this paper, we take the problem of the repetition testing of AIDS patients in medical analysis as the background environment, and rely on the experimental results obtained from simulation experiments to outperform the experimental prediction results of the proposed model. An accuracy rate of about 91.8% was achieved. Thus, the feasibility of the method is verified. It can reduce the repetition detection rate and improve the detection efficiency to a certain extent. It also saves unnecessary testing costs.
Revisiting Class Imbalance: A Generalized Notion for Oversampling
Authors: Velayuthan Purushoth , Karunasingha Navodika , Nagahawaththa Hasalanka , Jayasekara Buddhi G. , Hevapathige Asela
Published: December 2023

Class imbalance is a salient problem in both machine learning and data mining realms. Sampling techniques have become a cornerstone in solving this challenge, as they enable the creation of class-balanced datasets that is essential for robust model training. Addressing class imbalance not only enhances the predictive accuracy of machine learning algorithms but also ensures fair and unbiased decision-making across various applications, making it a critical aspect of research and development in various sectors. Through this work, we introduce the concept of a generalized oversampling function, unifying existing synthetic oversampling approaches. We explore diverse design decisions for such a function, presenting six functions categorized as linear and non-linear variants. We provide extensive experiments with these functions to gain an in-depth understanding of their behavior. Through our experiments, we observe that the best-performing function is primarily data-driven. Also, it is perceived that non-linear functions like minimum and maximum often depict higher learning capacity and steady performance in comparison to their linear counterparts mainly due to their ability in modelling non-trivial patterns. While moderate input counts would yield desirable performance in these functions, we can see varying robustness from these functions for distorted input data.