Miracle-dz/UniFAR-FTUs huggingface dataset:
Preoperative High C-Reactive Protein to Albumin Ratio Predicts Short- and Long-Term Postoperative Outcomes in Elderly Gastric Cancer Patients

Simple Summary Individual differences exist in the tolerability of surgical intervention among elderly patients, and it is necessary for appropriate treatment planning. The aim of our retrospective study was to investigate the efficacy of markers of preoperative inflammatory and nutritional status and identified perioperative high-risk elderly patients with gastric cancer. We analyzed whether preoperative inflammatory nutritional markers of 571 gastric cancer patients (<65 years old; n = 192, ≥65 years old; n = 379) can predict postoperative short-term and long-term outcomes. Preoperative high C-reactive albumin ratio (CAR) was not only associated with the occurrence of postoperative complications but also with poor prognosis in elderly gastric cancer patients. However, these trends were not observed among younger patients. The importance of these findings is that CAR has the potential to be used as a simple tool to predict short- and long-term postoperative outcomes that reflect the nutritional inflammatory status of the elde. Abstract Individualized preoperative assessment of the general condition of elderly patients with gastric cancer is necessary for appropriate surgical treatment planning. This study investigated the efficacy of preoperative markers that could be easily calculated from preoperative peripheral blood to predict the short- and long-term postoperative outcomes of gastrectomy. In total, 571 patients who underwent R0 surgical resection for gastric cancer were enrolled. In the elderly patient group (≥65 years old), univariate analyses revealed that the incidence of postoperative complications was associated with poor performance status (p = 0.012), more comorbidities (p = 0.020), high C-reactive protein to albumin ratio (CAR, p = 0.003), total gastrectomy (p = 0.003), open approach (p = 0.034), blood transfusion (p = 0.002), and advanced cancer (p = 0.003). Multivariate analysis showed that a high CAR was associated with a high incidence of postoperative complications (p = 0.046). High CAR was also associated with poor OS (p = 0.015) and RFS (p = 0.035). However, these trends were not observed among younger patients (<65 years old). Preoperative CAR may play a significant role in predicting short- and long-term surgical outcomes, particularly in elderly patients with gastric cancer.
The mediating role of the left ventricular mass index on the relationship between the fluid balance and left ventricular diastolic function in patients with chronic kidney disease

Background The pathophysiological mechanism of cardiovascular disease in patients with chronic kidney disease (CKD) is complicated. Mediation analysis is an important statistical tool for gaining insight into the complex mechanisms of exposure-outcome effects. We investigated the potential mediating role of the left ventricular mass index (LVMI) on the association between fluid balance (overhydration/extracellular water, OH/ECW) and left ventricular diastolic function (E/e´ ratio) in patients with CKD not yet on dialysis. Methods Bioimpedance spectroscopy, echocardiography, and laboratory evaluations were performed on 425 consecutive patients on the same day. The patients were classified into two groups according to the estimated glomerular filtration rate corresponding to CKD stages 3 and 5. Mediation analysis was performed using the PROCESS macro and bootstrapping methods. Results OH/ECW and LVMI were positively correlated with the E/e´ ratio in both the CKD stages 3 and five groups. In CKD stage 5, there was a statistically significant association between OH/ECW and LVMI, whereas no correlation was observed in CKD stage 3. In the mediation analysis, LVMI positively mediated the relationship between OH/ECW and E/e´ ratio when controlling for confounders in patients with CKD stage 5 (B = 2.602; Boot 95% confidence interval, 1.313–4.076). Conclusion In our analysis, the indirect effect of mediators was significant in patients with advanced CKD. Therefore, our study suggests that further research on several other risk factors may be needed to determine the underlying mechanisms of association between the associated factors in all CKD stages.
Old world and new world wine concepts of terroir and wine: perspectives of three renowned non-French wine makers

ABSTRACT The concept of ‘terroir’ has roots steeped in French history of wine and evocative stories of the land. Today terroir is important as a quality marker in brand management for upmarket wines. French wines have benefited from their historical connotation with terroir but other wine growing countries have also adopted the term to mean characteristics in wine attributable to place of origin. However there is no universally accepted definition of terroir except to say it refers to a particular place. This paper addresses this ambiguity by seeking the practice-based views of three experienced non-French winemakers. This reveals a social dimension to terroir that in various degrees supports and extends both the technical/scientific progress and brand value for premium wines in both Old and New World regions. This article contributes to the growing body of research that seeks to understand the practicality of terroir as a marketing and brand value indicator.
Deep Reinforcement Learning Robots for Algorithmic Trading: Considering Stock Market Conditions and U.S. Interest Rates

With the development of artificial intelligence, there have been many attempts to incorporate artificial intelligence into algorithmic trading. In particular, reinforcement learning, which aims to solve dynamic decision-making problems, is attracting attention because of its high utilization in algorithmic trading. In this paper, we will implement a simple Deep Reinforcement Learning (DRL) trading robot to check the performance of DRL. In addition, we tried to find out how much performance improvement can be achieved by comparing a robot that learned a single stock data with a robot that learned stock data, market index, and interest rate data. This paper aims to develop a stock investment robot using a Proximal Policy Optimization (PPO) reinforcement learning algorithm and analyze the performance of the robot. The first robot used only the stock data of APPL INC, a single stock, as input, and the second robot used stock data of APPL INC and the S&P 500 index together with US interest rate data as input data. Afterward, the stock investment performance of the two robots for APPL INC was comparatively analyzed using the test data.
Human metapneumovirus respiratory infection affects both innate and adaptive intestinal immunity

Introduction Respiratory infections are one of the leading causes of morbidity and mortality worldwide, mainly in children, immunocompromised people, and the elderly. Several respiratory viruses can induce intestinal inflammation and alterations in intestinal microbiota composition. Human metapneumovirus (HMPV) is one of the major respiratory viruses contributing to infant mortality in children under 5 years of age worldwide, and the effect of this infection at the gut level has not been studied. Methods Here, we evaluated the distal effects of HMPV infection on intestinal microbiota and inflammation in a murine model, analyzing several post-infection times (days 1, 3, and 5). Six to eight-week-old C57BL/6 mice were infected intranasally with HMPV, and mice inoculated with a non-infectious supernatant (Mock) were used as a control group. Results We did not detect HMPV viral load in the intestine, but we observed significant changes in the transcription of IFN-γ in the colon, analyzed by qPCR, at day 1 post-infection as compared to the control group. Furthermore, we analyzed the frequencies of different innate and adaptive immune cells in the colonic lamina propria, using flow cytometry. The frequency of monocyte populations was altered in the colon of HMPV -infected mice at days 1 and 3, with no significant difference from control mice at day 5 post-infection. Moreover, colonic CD8+ T cells and memory precursor effector CD8+ T cells were significantly increased in HMPV-infected mice at day 5, suggesting that HMPV may also alter intestinal adaptive immunity. Additionally, we did not find alterations in antimicrobial peptide expression, the frequency of colonic IgA+ plasma cells, and levels of fecal IgA. Some minor alterations in the fecal microbiota composition of HMPV -infected mice were detected using 16s rRNA sequencing. However, no significant differences were found in β-diversity and relative abundance at the genus level. Discussion To our knowledge, this is the first report describing the alterations in intestinal immunity following respiratory infection with HMPV infection. These effects do not seem to be mediated by direct viral infection in the intestinal tract. Our results indicate that HMPV can affect colonic innate and adaptive immunity but does not significantly alter the microbiota composition, and further research is required to understand the mechanisms inducing these distal effects in the intestine.
The Russian Strategy of using Crystalline Rock as a Repository for Nuclear Waste

The first Russian underground repository for high- and intermediate-level radioactive waste (HLW and ILW, respectively) will be built in the crystalline Archean granite–gneisses at Yeniseisky (Krasnoyarsk region, Siberia). The geological and hydrogeological characteristics of this site are similar to those found in Forsmark (Sweden) and Olkiluoto (Finland). However, the Russian disposal strategy is different. HLW will be disposed in the form of an aluminophos phate glass and ILW (with long-lived radionuclides) will be cemented. Preliminary research on all aspects of repository design (stability of waste forms, waste packages, and bentonite buffer; evaluation of the geologic barrier; and simulation of radionuclide transport by groundwater) will be performed at an on-site underground research laboratory.
On Multilayer Problems in Radio Frequency Identification : A System Approach

Radio Frequency Identification systems make possible the identification of the objects in the environment with neither physical nor visual contact. Retail, rental, surveillance etc. are the domains with RFID tags have very real and promising applications. In real life applications in an environment these tags have serious implications on the privacy of the people. Sometimes the technology concept yields serious opposition and create problems. The problem occurs beyond the application layer. RFID system have three layers viz. Application layer, Communication layer and physical layer. By observing each layer we can solve privacy problems of the whole system. The generalized policy has been used in the aspect of privacy as multilayer system.
Analisis Faktor-Faktor Yang Memengaruhi Angka Prevalensi Penyakit Kusta Di Jawa Timur Dengan Pendekatan Spatial Durbin Model

Persebaran penyakit kusta di Provinsi Jawa Timur harus mendapat perhatian lebih karena pada tahun 2012, Jawa Timur merupakan penyumbang penderita kusta tertinggi di antara provinsi lainnya dengan angka prevalensi kusta per 10.000 penduduk sebesar 1,46. Kejadian penyakit menular seperti kusta, perlu mempertimbangkan pengaruh kedekatan kewilayahan (spasial) sehingga penelitian ini juga mempertimbangkan kabupaten/kota di Jawa Tengah yang berbatasan langsung dengan kabupaten/kota di Jawa Timur. Penelitian ini menganalisis faktor-faktor yang memengaruhi angka prevalensi penyakit kusta di Jawa Timur dengan menggunakan pendekatan Spatial Durbin Model (SDM) yang merupakan bentuk khusus dari metode Spatial Autoregressive Model (SAR). Matriks pembobot yang digunakan adalah Queen Continguity (persinggungan sisi sudut). Hasil penelitian ini menunjukkan bahwa model SDM memberikan hasil yang lebih baik daripada metode OLS dan metode SAR dengan nilai R 2 sebesar 83,05% dan nilai AIC sebesar 89,083. Variabel yang signifikan berpengaruh terhadap angka prevalensi kusta adalah persentase rumah tangga ber-PHBS, kepadatan penduduk, persentase penduduk miskin dan persentase puskesmas per 100.000 penduduk.
Case report: Diagnosis and autogenous vaccine treatment of herpesvirus in a green turtle (Chelonia mydas) in Santa Marta, Colombia

This study reports the first case of fibropapillomatosis (FP) in the green turtle Chelonia mydas that has been successfully diagnosed and treated in Colombia. Worldwide, FP has reached epizootic proportions as it has been reported in marine turtles of tropical and subtropical waters, and in severe cases, it reduces the probability of survival. Treatment has been elusive as multiple surgical excisions are needed due to tumor recurrence. In this case, one green turtle with multiple tumors was diagnosed by histopathology and molecular detection of the chelonid herpesvirus 5 (ChHV5) by means of amplification and sequencing of the DNA polymerase (DNApol) gene. Two separate treatments that consisted of autogenous vaccines and surgical excisions were applied; the first one had a partial success as one out of the tumors treated reappeared after 3 months post-treatment. Treatment 2 consisted of an autogenous vaccine enriched with adjuvants and applied at increasing doses, after which, the tumor significatively decreased in size and was surgically removed. At the end of the 6 months follow-up period, no tumor recurrence was observed, and the turtle was in apparent optimal health conditions. These findings, although limited, suggest a possible treatment that might help to contain this epizootic problem.
Determination of the Influence of Thermal Comfort in Care and Concentration of Media Education Students: Case Colombia

Objectives: This research was conducted in order to determine the influence of thermal comfort, as measured by the index of temperature Wet bulb globe temperature (WBGT), the Global Attention and Perception Index (GIFS) of high school students from a school in Barranquilla, Colombia. Methods/Statistical Analysis: For this, an experimental design was performed, in which the variable peck response was the GIFS, the potential factor was the WBGT, whose levels were the records under different environmental conditions, and the disturbing factor controllable was “student”, this last it was blocked to minimize variability that this could introduce in response, thus obtaining a completely random model blocks. Subsequently, a group of tenth and eleventh grade other selected, subjected to different environmental conditions for 6 days, in which we applied the Toulouse-Pieron test, to measure attention and concentration; and a survey based on the McIntyre scale to evaluate thermal satisfaction, while thermal comfort was measured using a heat stress monitor. Findings: The collected data were processed statistically using analysis of variance, to see if there were differences between levels, and if the data came from a normal distribution, correlation analysis to determine the influence of WBGT factor in the response variable GIFS and descriptive techniques as bar charts, box and whisker plot, among others, which allowed characterizing the information and identify trends. Application/Improvements: The results showed values of WBGT index mostly within the TLV’s; an inverse strong correlation of 90% between the two variables for the sample taken from tenth grade and a moderately strong relationship of 64.9% for eleventh grade, showing greater influence of environmental conditions on the rate of attention and concentration and thermal student satisfaction in the first group compared to the second, who apparently are less sensitive to these.
Presenilin: A Multi-Functional Molecule in the Pathogenesis of Alzheimer’s Disease and Other Neurodegenerative Diseases

Presenilin, a transmembrane protein primarily known for its role in Alzheimer’s disease (AD) as part of the γ-secretase complex, has garnered increased attention due to its multifaceted functions in various cellular processes. Recent investigations have unveiled a plethora of functions beyond its amyloidogenic role. This review aims to provide a comprehensive overview of presenilin’s diverse roles in AD and other neurodegenerative disorders. It includes a summary of well-known substrates of presenilin, such as its involvement in amyloid precursor protein (APP) processing and Notch signaling, along with other functions. Additionally, it highlights newly discovered functions, such as trafficking function, regulation of ferritin expression, apolipoprotein E (ApoE) secretion, the interaction of ApoE and presenilin, and the Aβ42-to-Aβ40-converting activity of ACE. This updated perspective underscores the evolving landscape of presenilin research, emphasizing its broader impact beyond established pathways. The incorporation of these novel findings accentuates the dynamic nature of presenilin’s involvement in cellular processes, further advancing our comprehension of its multifaceted roles in neurodegenerative disorders. By synthesizing evidence from a range of studies, this review sheds light on the intricate web of presenilin functions and their implications in health and disease.
Investigation of Dry Horizontal Stirred Milling Applications for Cement Grinding Circuits

Bu tez calismasi kapsaminda, kuru yatay karistirmali degirmen teknolojisinin ince ogutmenin onem arz ettigi cimento endustrisinde kullanim olanaklari arastirilmistir. Calismanin temel amaclari, degirmende olusabilecek ogutme sorunlarini tespit etmek, tasarim ve isletme degiskenlerinin ogutme performansina olan etkilerini incelemek, degirmen icin en uygun isletme kosullarini belirlemek, modelleme calismalarini yurutmek ve sonrasinda bu modelleri farkli cimento ogutme devresi alternatiflerinin simulasyonu sirasinda kullanmak olarak siralanabilir.
Pre-Implant Immune Status is Associated with Infection Risk After Left Ventricular Assist Device Implantation

Purpose Infection is the most common complication after left ventricular assist device (LVAD) implantation. The immune status of LVAD patients is relevant for the incidence and severity of infection, but it is unknown if there is a predisposing immune status prior to LVAD implantation that contributes to an increased risk for infection in the post-implant period. We analyzed the pre-LVAD immune status in patients with infection within 3 months after LVAD implantation in comparison to infection-free patients. Patients and Methods Fifty-four consecutive LVAD patients were included in this study. According to their infectious history in the first 3 months after LVAD implantation, these patients were grouped into an infection (n=23) and an infection-free group (n=31). Pre-LVAD blood samples were obtained for flow cytometric analysis of immunological parameters including B cells, subsets of T, dendritic and natural killer cells. Patient-specific, clinical and laboratory data were recorded. Results Blood count analysis prior to LVAD implantation showed comparable counts of erythrocytes (p=0.19), platelets (p=0.33) and leukocytes (p=0.50) between patients with infection and infection-free patients in the post-implant period. Patients with infection in the first 3 months after LVAD implantation had lower concentrations of lymphocytes (p=0.02). Forty percent of the patients with infection showed more often pre-LVAD neutrophil-to-lymphocyte ratios (NLR) >7 than patients without infection in the first 3 months after LVAD implantation (14%, p=0.05). Patients with infection already had lower percentages of CD3+ T cells (p=0.03), CD19+ B cells (p<0.01), BDCA2+ pDCs (p=0.03) and BDCA4+ plasmacytoid DCs (pDCs) (p=0.05) prior to LVAD implantation than infection-free patients. Conclusion Our results demonstrated that patients with infection in the early post-implant period showed lower concentrations of lymphocytes, especially of CD3+ T cells and CD19+ B cells, decreased percentages of BDCA2+ and BDCA4+ pDCs, and had more often NLRs >7 indicating moderate-to-severe inflammation. Thus, we identified specific immunological changes pre-LVAD that could help to identify patients at risk for infection in the early post-implant period.
Advancements in Machine Learning and Data Mining Techniques for Collision Prediction and Hazard Detection in Internet of Vehicles

The Internet of Vehicles (IoV) has transfigured transportation with connected vehicles, smart infrastructure, and self-driving cars. Road collisions and accidents are still a problem for road safety. This review of the literature discusses the prediction of IoV accidents and collisions as well as the detection of hazards using data mining, deep learning, and machine learning techniques. It describes the most recent developments to these methods and how they enhanced IoV safety. The article starts off by going over data collection, data quality, and the ever-changing nature of IoV traffic scenarios. What follows is a detailed breakdown of the ML, DL, and DM methods used in IoV safety applications. Convolutional neural networks, artificial neural networks, recurrent neural networks, support vector machines, and decision trees. As examples of real-world applications and case studies, intelligent accident prediction models, driver attention forecasting, traffic congestion forecasting, spatiotemporal analysis in autonomous vehicles, scene-graph embedding, and V2P collision risk alerts are discussed. The goal of this review is to give readers a comprehensive overview of the cutting-edge methods enhancing IoV accident prediction, collision avoidance, and hazard detection.
Automatic Blood Cell Detection Based on Advanced YOLOv5s Network

There is a great demand for automatic detection and classification of blood cells (BCs) in clinical medical diagnoses. Traditional methods, such as hematology analyzer and manual counting were laborious, time intensive, and limited by analysts’ professional experience and knowledge. In this paper, the one-stage network based upon improved YOLOv5s is provided to detect BCs. First, the Transformer and bidirectional feature pyramid network (BiFPN) are introduced into the backbone network and neck network for refining the adaptive features, respectively. Second, Convolutional Block Attention Module (CBAM) is added to neck network outputs to strengthen the key features in space and channel. In addition, an Efficient Intersection over Union (EIoU) was introduced to improve model accuracy regarding localization and performance. The improvements are embedded into the YOLOv5s model and termed YOLOv5s-TRBC. The experiments on the blood cell dataset (BCCD) show that in the three types of BCs detections, the mean average precision (mAP) of the method proposed reached 93.5%. Furthermore, comparative experiments demonstrate that the model could perform favorably against the counterparts with respect to mAP rate, and the model’s Giga Floating-point Operations Per Second (GFLOPs) is reduced to 1/6 of YOLOv5, which provides a potential solution for future computer-aid diagnostic systems.