bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences in blood pressure control based on hypertension subtype in patients with a de novo diagnosis: a retrospective cohort study
Authors: Gallo-Villegas Jaime , Rivera-Martínez Wilfredo , Casanova-Valderrama María , Figueroa-Torregroza Lunevar , Ocampo-Chaparro José , Salazar-Solarte Aura , Zambrano José , Aristizabal Dagnovar 
Published: July 2023

Abstract
The burden of disease due to arterial hypertension (AH) is huge and studies have shown that AH prevalence continues to increase and that control rates are still low, despite public health efforts, lifestyle and pharmacological interventions recommended by guidelines. Therefore, improved therapeutic schemes based on patient´s characteristics are required to achieve blood pressure (BP) goals and thus avoid the impact AH on cardiovascular outcomes. In this real-world study, a cohort of 1397 Latin American subjects with a de novo diagnosis of AH received antihypertensive therapy following current guidelines. Thereafter, they were retrospectively classified by hypertension subtype and BP response was assessed based on whether patients initially received an appropriate treatment according to arterial hemodynamics. The initiation of a proper antihypertensive regimen was statistically significant associated with greater BP control at the follow-up clinical visit, even when the statistical model was adjusted for multiple variables (OR 2.17 CI 1.49–3.15, p value < 0.001). Among patients who were not well controlled, the divergent systolic-diastolic hypertension (SDH-D) subtype was the most frequent (46.7%), and those patients initially had higher BP, cardiac output, total systemic vascular resistance (SVR), and lower arterial compliance. Our findings indicate that the appropriate selection of an antihypertensive treatment guided by the AH subtype is associated with better BP control in patients with newly diagnosed AH.
Routing Optimization for Energy Efficiency in Software-Defined IoT and RPL Networks
Authors: Gasouma Amir , Yusof Kamaludin M. , Bouallegue Belgacem , Ahmed Abdelmoty M. , Matter Safaa S. 
Published: July 2023

Abstract
The Internet of Things (IoT) is a rapidly expanding network of interconnected smart devices and an active area of study in the field of information technology. These smart devices may be monitored, managed, and shared information via the internet. Some of them may be tiny gadgets or sensors with restricted power and battery life. These devices short lifespans have consequences for the IoT network due to their high energy consumption. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is defined in RFC6550 by the Internet Engineering Task Force (IETF), which is one of the most important protocols for routing for the IoT and the sole widely used protocol that aids in routing in Low Power and Lossy Networks (LLNs). Adapting objective functions (OFs) for routing and regulating control messages for RPL operations, which improves energy efficiency, is a major need in a method that handles IoT network difficulties and exploits new flexible network designs, such as Software-Defined RPL networks. This paper describes a software defined RPL system optimized for heterogeneous IoT environments. The proposed research made use of TriOF, an acronym for the three objective functions (OF1, OF2, and OF3) used for adaptive OF selection and routing. Use the Killer Whale Optimization (KWO) algorithm to select the best OF based on current network conditions. The energy efficiency of networks and OF selection adaptation both improved. The outcomes of simulations performed in Network Simulator 3 (NS3) are examined. The experiments' outcomes demonstrate the feasibility of our suggestion with reduced control overhead and control messages, as well as 40% and 60% less energy consumption when compared to previous works.
Machine Learning Uncovers CCM Isoforms as Transcription Factors
Authors: Zhang Jun , Croft Jacob , Gao Liyuan , Sheng Victor 
Published: July 2023

Abstract
This study investigates the TF potential of CCM gene isoforms that undergo alternative splicing and nucleocytoplasmic shuttling. Experiments showed that CCMs shuttle with progesterone receptors, which act as both cell signaling components and TFs, raises the possibility of CCMs as TFs. The study challenges existing knowledge with a Biased-SVM model to indicate that numerous CCM isoforms function as TFs.
Revealing the Potential of Necroptosis-Related Genes in Prognosis, Immune Characteristics, and Treatment Strategies for Head and Neck Squamous Cell Carcinoma
Authors: Cao Junhua , Wu Congxiao , Han Zhaofeng , Yang Zheng , Ren Minge , Wang Ximei , Liu Zheng 
Published: July 2023

Abstract
Necroptosis is a recently discovered apoptotic mechanism that has been linked to tumor formation, prognosis, and treatment response. However, the relationship between the TME and NRGs remains unclear. In this study, we analyzed the expression patterns of NRGs in 769 HNSCC cases from two distinct data sets. Our findings revealed distinct genetic groups and a correlation between patient clinical features, prognosis, TME cell infiltration characteristics, and NRG alterations. We then developed an NRG model to predict OS and confirmed its accuracy in predicting OS in HNSCC patients. Moreover, we have devised a precise nomogram that enhances the clinical utility of the NRG model substantially. The low-risk group had a better OS, and they were associated with immune suppression, more mutated genes, and higher TIDE scores. The risk score also had a significant correlation with the CSC index and susceptibility to anti-tumor agents. Our study provides insights into how NRGs affect prognosis, clinically significant features, TME, and immunotherapy response in HNSCC. With a better knowledge of NRGs in HNSCC, we could assess the prognosis and develop immunotherapy regimens that are more successful at opening up new doors.
The Construction and Optimization of Finished Vehicle Logistics Multimodal Transportation Routing Problem Model based on Ant Colony Algorithm under the Background of Belt and Road Initiative
Authors: Wang Yaoyan 
Published: July 2023

Abstract
Vehicle logistics is a very important mode of freight car combination logistics. In China, more than 80% of the total logistics operation through highway transportation is based on the completion of vehicle logistics. Because of the lack of transportation mode in the whole vehicle logistics process, the problems of the relatively small batch of transportation but large duplicate batches are very common. Therefore, in the aspect of cost control, the whole vehicle logistics system of our country has much room for improvement compared with western countries. Multimodal transportation can be adopted to reduce costs, and multimodal transport mode of vehicle logistics can also be carried out to avoid the logistics defects caused by single highway transportation, so as to facilitate management and reduce costs. The case analysis to the B Company in the entire vehicle logistics aspect work was carried out in this paper. Combined with the idea of route optimization, a model of vehicle logistics cost budget based on multimodal transportation was established. The ant colony algorithm was adopted, and the validity of the model and calculation method was verified.
Reduction in EEG Theta Power as a Potential Marker for Spatial Disorientation during Flight
Authors: Geva Gil , Getter Nir , Nakdimon Idan , Blecher Boris , Ben-Ari Oded , Gordon Barak , Shriki Oren 
Published: July 2023

Abstract

Spatial disorientation (SD) during flight is a common occurrence, manifesting when an aircrew's perception conflicts with the aircraft's actual motion, attitude, or position. A prevalent form of SD is the somatogyral illusion, which is elicited by constant speed rotation, causing a false perception of motion in the opposite direction once rotation ceases. This research aimed to investigate brain activity changes during exposure to this illusion. We designed a unique experimental setup where twenty-three volunteers were exposed to the somatogyral illusion while seated on a Barany (rotating) chair. The study employed EEG and eye-tracking glasses to monitor brain activity and eye movements, respectively. Subjects were isolated from external stimuli, promoting effective illusion induction. Participants reported their perceived motion direction using a joystick, allowing us to compare a reference condition to one with the illusion present. Results indicated a significant decrease (52%) in theta power (4–8 Hz) over left frontal channels during the illusion, complemented by the occurrence of nystagmus in 72% of trials. These findings align with previous studies linking SD and theta band changes, suggesting implications for EEG-based identification of SD in flight.
Crack The Crux Of "Psychological Contract" Between Sports And Students Under Big Data Technology
Authors: Chen Wenfeng 
Published: July 2023

Abstract
Studies on the elements that impact students' learning in sports education are important because they reflect the shift in focus from teachers to students brought about by educational reform and growth. This research investigates how the actions of college and university sports instructors affect their students' drive to learn and study. This paper develops a behavioral model of the psychological contract between Chinese undergraduate students and their physical education instructors. We first collect the student data from numerous firms to begin this inquiry. Before processing a raw dataset, min-max normalization must be carried out. The psychological contract scale served as the basis for the survey instrument created for use with college faculty and students. "Statistical analysis is done using the Student t-test, Chi-square test, and Analysis of Variance (ANOVA)." According to the findings, the psychological agreement between a teacher and their pupils has a major influence on the latter's actions in the classroom. Students’ learning motivation acts as mediator between instructors' teaching practices and students’ achievement. Improved communication between faculty and undergraduates in physical education classes, more teacher motivation to effectively administer the physical education curriculum, and higher standards for physical education instruction are all tangible outcomes of this research.
Study on Ensemble Calibration of Flood Forecasting Based on Response curve of rainfall dynamic system and LSTM.
Authors: Tian Lu , Li Zhichao , Liu Chengshuai , Yu Qiying , Li Wenzhong , Hu Caihong 
Published: July 2023

Abstract

A dynamic system response curve correction method is used to establish the error of the rainfall time series, modify the surface precipitation of the basin, and use the surface precipitation of the revised as input to improve flood forecast accuracy using the Shouxi watershed in Sichuan Province and the Qingyangcha domain in Shanxi Province as the research object. Flood forecasting is carried out using the excess storage and excess infiltration simultaneously model. Combined with the hierarchical optimization method and the LSTM (Long Short-Term Memory neural network) error output correction method, the three-process error set correction is carried out. The results show that the accuracy of the flood forecast discharge with area-rainfall correction was improved compared with that without area-rainfall correction. Specifically, The absolute value of flood peak error for 12 of 15 floods in the Shouxi Basin validation set decreased by 0.566.3% compared to before the areal rainfall correction, the NSE of 13 flood forecast discharge increased by 0.0020.015, and the current difference of 2 peaks shortened by 1 hour. The peak error of five floods was reduced by 0.23-5.49% in the Qingyangcha watershed validation set compared to before the areal rainfall correction, the NSE (Nash Social Welfare Efficiency) of five flood forecast flows was increased by 0.01-0.071, and the current difference of two peaks was shortened by one hour. The comprehensive results show that this method is applicable to reduce the prediction error and improve the accuracy of flood forecasting in the watershed.
Benthic daily oxygen variability and stress as drivers for animal diversification in the Cambrian
Authors: Hammarlund Emma , Bukkuri Anuraag , Norling Magnus , Posth Nicole , Carroll Christopher , Baratchart Etienne , Amend Sarah , Gatenby Robert , Pienta Kenneth , Brown Joel , Peters Shanan , Hancke Kasper 
Published: July 2023

Abstract
The delay between the origin of animals in the Neoproterozoic and their Cambrian diversification remains perplexing. Animal diversification mirrors an expansion in marine shelf area, but the mechanisms linking this environmental change to early organismal ecology are unclear. In this study, we used a biogeochemical model to consider oxygen dynamics at the sunlit sediment–water interface over night-day (diel) cycles in the early Cambrian under a greenhouse climate. We found that temperatures dictated the diurnal benthic oxic-anoxic shifts that were physiologically stressful to early animals and this dynamic expanded over nutrient-rich shelf areas as continents were flooded in the Cambrian. We suggest that the combination of a greenhouse climate and continental flooding combined to amplify diurnal benthic redox variability, which promoted the adaptive radiation of animals tolerant to oxygen fluctuations and stress, the Metazoa.
Enhancing Mechanical Properties of PLA and PP Composites through Ionic Zeolite with copper nanoparticles Reinforcement: Microstructural and Micromechanical Characterization
Authors: Onate Angelo , Sáez-Llanos Thyare , Jaramillo Andrés , Vargas-Silva Gustavo , Melendrez Manuel , Medina Carlos 
Published: July 2023

Abstract
The objective of this research is the micromechanical characterization of new materials for 3D printing, comprised of commercial polymer matrices of PLA and PP, reinforced with zeolite and copper nanoparticles. To characterize the microstructure of the composite materials, digital tools such as ImageJ software were used to determine the number and size of inclusions present in the samples through image analysis. Besides, the morphology of the reinforcing phase was determined through analysis with the SEM microscope. To determine the mechanical properties of the composite materials, nanoindentation was used to obtain the elastic modulus and Poissons ratio of constituents. With both, microstructure characterization and mechanical properties of the constituents, the composite materials obtained were simulated using Digimat FE software, and mentioned engineering constants were obtained. Finally, simulations results were compared with experimental tensile testing of studied composite materials, and it was determined that the simulation using Digimat delivered reliable mechanical results.
Exploring research trend and hotspots on oxidative stress in ischemic stroke (2001-2022): insights from bibliometric
Authors: Jiang Nan , Yang Ting , Han Hongxia , Shui Jing , Hou Miaomiao , Wei Wenyue , Kumar Gajendra , Song Lijuan , Ma Cungen , Li Xinyi , Ding Zhibin 
Published: July 2023

Abstract
Oxidative stress is widely involved in the pathological process of ischemic stroke and ischemia-reperfusion. Several research have demonstrated that eliminating or reducing oxidative stress can alleviate the pathological changes of ischemic stroke. However, current clinical antioxidant treatment did not always perform as expected. This bibliometric research aims to identify research trends, topics, hotspots and evolution on oxidative stress in the field of ischemic stroke, and to find potentially antioxidant strategies in future clinical treatment. Relevant publications were searched from the Web of Science (WOS) Core Collection databases (2001–2022). VOSviewer was used to visualize and analyze the development trends and hotspots. In the field of oxidative stress and ischemic stroke, the number of publications increased significantly from 2001 to 2022. China and the USA were the leading countries for publication output. The most prolific institutions were Stanford University. Journal of Cerebral Blood Flow and Metabolism and Stroke were the most cited journals. The research topics in this field include inflammation with oxidative stress, mitochondrial damage with oxidative stress, oxidative stress in reperfusion injury, oxidative stress in cognitive impairment and basic research and clinical translation of oxidative stress. Moreover, "NLRP3 inflammasome", "autophagy", "mitophagy", "miRNA", "ferroptosis" and "signaling pathway" are the emerging research hotspots in recent years. At present, multi-target regulation focusing on multi-mechanism crosstalk has progressed across this period, while challenges come from the transformation of basic research to clinical application. New detection technology and new nanomaterials are expected to integrate oxidative stress into the clinical treatment of ischemic stroke better.
Investigating the antimicrobial activity of cell-free supernatant of lactic acid bacteria against spoilage bacteria of vacuum-packed sliced emulsion-type sausages
Authors: Tajbakhsh Samaneh , Eskandari Mohammad Hadi , Shekarforoush Seyed Shahram 
Published: July 2023

Abstract
Spoilage is very common in vacuum-packed sliced emulsion-type sausages during refrigerated storage. Bacteria causing spoilage of this products were identified. Four lactic acid bacteria (LAB) were the predominant spoilage bacteria. A total of 43 LABs were screened for inhibitory activity against the four spoilage bacteria. Six strains of Lactobacillus acidophilus ATCC 4356, Lactobacillus helveticus PTCC 1332, Lactiplantibacillus plantarum CEC 17484, Lactiplantibacillus plantarum LL441, Lacticaseibacillus rhamnosus GG ATCC 53103, and Pediococcus acidilactici DSM 20284 that produced antimicrobial metabolites effective against these spoilage agents, including compounds with a proteinaceous nature, in addition to acids and H2O2, were selected as protective bacteria. The cell-free supernatant (CFS) of the protective bacteria successfully inhibited four spoilage bacteria (more than 88%). The MIC90 of all protective bacteria was less than 10 mg/ml against E. mandetii and L. sakei. The CFS of L. rhamnosus had an effect on three spoilage bacteria, including L. sakei, E. mandetii, and L. curvatus, at the lowest concentration (3.0, 3.1, and 10.5 mg/ml, respectively). The effective metabolites were resistant to the pasteurization temperature of sausage, so these supernatants can be used even in the pre-pasteurization stage of the production of sliced sausage as biopreservatives.
Properties of -1 and 1 being Roots of Polynomials over Real/Complex Field
Authors: Bhosale Mandar 
Published: July 2023

Abstract
The given article is about elaborating the alternate proofs for 1 and -1 being roots of polynomials having some specific properties. The proof explains equivalent conditions with more explanation. The first proposition states that for any polynomial of single variable 𝑥 say 𝑝(𝑥), the sum of all coefficients is zero if and only if (𝑥 − 1) is factor of 𝑝(𝑥) equivalently 1 is root of 𝑝(𝑥).
The second Proposition states for any polynomial of single variable 𝑥 say 𝑝(𝑥), alternate sums of coefficients i.e. sum of coefficients of odd degree terms (𝑥, 𝑥3, 𝑥5, .., 𝑥2𝑛−1, ..) and sum of coefficients of even degree terms (constant, 𝑥2, 𝑥4, .., 𝑥2𝑛 , ..) are same if and only if (𝑥 + 1) is a factor of 𝑝(𝑥) equivalently -1 is the root of 𝑝(𝑥).
As mentioned above, the arguments are equivalent conditions hence we are proving by proving two parts i.e. prove if 𝑝 is true then 𝑞 is true. After this,we will prove the converse part i.e. if 𝑞 is true then 𝑝 is true. Both parts will be done using the direct proof method.
Improved Corrosion Resistance and Cytotoxicity of Nickel-based alloy using Novel Plasma processing technique
Authors: Yousaf Muhammad , Iqbal Tahir , Mansha Muhammad Salim , Saeed Adnan , Abrar Muhammad , Afsheen Sumera , Ahmed Irfan , AlObaid Abeer A. , Al-Maswari Basheer M. 
Published: July 2023

Abstract

Nickel-based (NiCr) alloys are mostly utilized in the dental industry because of their good corrosion resistance, ease of casting, and adequate thermal coefficient of friction with ceramic porcelain. However, leakage of toxic metal ions (Ni and Cr) due to breakage or damage of protective metal oxide layers in aggressive body fluids affects corrosion resistance, tribological properties, and cytotoxicity. These drawbacks ultimately affect the biocompatibility of NiCr alloys for medical applications. This study employs magnetron sputtering in conjunction with cathodic cage plasma nitriding (CCPN) to perform a novel duplex plasma treatment on Ni-Cr alloy. Moreover, the cathodic cage plasma-treated TiN (CCPN-TiN) samples showed further enhanced corrosion resistance and low metal ion leakage. These findings made duplex plasma treatment an efficient method for the surface modification of metallic alloys against the leaching of toxic ions in chloride-aggressive electrolytes, thus proving an excellent strategy for various biomedical applications.
Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems
Authors: Chen Hao-Yuan , Chang Yen-Jui , Chang Ching-Ray 
Published: July 2023

Abstract
Quantum computing holds great potential for advancing the limitations of machine learning algorithms to handle higher data dimensions and reduce overall training parameters in deep neural network (DNN) models. This study uses a parameterized quantum circuit (PQC) on a gate-based quantum computer to investigate the potential for quantum advantage in a model-free reinforcement learning problem. Through a comprehensive investigation and evaluation of the current model and capabilities of quantum computers, we designed and trained a novel hybrid quantum neural network based on the latest Qiskit and PyTorch framework. We compared its performance with a full-classical DNN with and without an integrated PQC. Our research provides insights into the potential of deep quantum learning to solve a maze problem and, potentially, other reinforcement learning problems. We conclude that various reinforcement learning problems can be effective with reasonable training epochs. Moreover, a comparative discussion of the various quantum reinforcement learning model on maze problems is discussed to evaluate our research's overall potential and advantages.