bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of IoT devices based on optical topology sensors in simulation of shooting speed for football players
Authors: Bao Juan , Zhou Shengwang , Li Simin 
Published: January 2024

Abstract

Football has always been loved by people, and in recent years, the country has gradually carried out publicity about football, which has gradually made football popular and people's attention to football is also increasing. Football shooting techniques play a very important role in achieving good results. In order to achieve simulation experiments on the shooting speed of football players, this article will conduct simulation experiments on the shooting speed of football players using optical sensor measurement principles combined with topology based IoT devices, and deeply analyze the collected simulation data. Firstly, in order to improve the stability of the system in detection, this article also proposes a sensor based on an array waveguide grating structure that is not affected by factors such as wavelength drift; Secondly, in order to better analyze the advantages and disadvantages of sensors, this article conducts analysis and research on multiple aspects of sensors, and improves the structure and parameters of sensors. The final experimental results indicate that the system designed in this article has the best simulation performance, with good performance in data protection and storage. Therefore, the IoT device based on optical topology sensors proposed in this article is feasible in collecting simulation data on the shooting speed of football players.
Infrared image compensation filtering algorithm based on wearable sensors in sports training simulation
Authors: Jing Xu 
Published: January 2024

Abstract

With the development of sports training simulation technology, wearable sensors have been widely used to monitor the physiological signals of athletes. However, in indoor sports training, sensors are affected by infrared light interference, leading to a decrease in sensor signal quality and thus affecting training effectiveness. A research has proposed an infrared image compensation filtering algorithm based on wearable sensors, which performs a series of preprocessing steps on infrared images to improve image quality. Signal contrast enhancement technology is used to enhance the visual effect of the images. In order to solve the problem of infrared interference, an infrared image compensation model was established, and filtering algorithms were applied to process the compensated images to extract features related to motion posture. Filtering algorithms can improve image noise suppression and contour feature extraction by performing spatial or frequency domain filtering operations on the image. Through experimental verification, this algorithm effectively improves the accuracy and stability of sensor signals while reducing infrared light interference, and can more accurately capture the physiological changes of athletes.
Peer Threat Evaluations Shape One’s Own Threat Perceptions and Feelings of Distress
Authors: Espinosa Lisa , Nook Erik C. , Asperholm Martin , Collins Therese , Davidow Juliet Y. , Olsson Andreas 
Published: January 2024

Abstract
We are continuously exposed to what others think and feel about content online. How do others’ evaluations shared in this medium influence our own beliefs and emotional responses? In two pre-registered studies, we investigated the social transmission of threat and safety evaluations in a paradigm that mimicked online social media platforms. In Study 1 (N=103), participants viewed images and indicated how distressed they made them feel. Participants then categorized these images as threatening or safe for others to see, while seeing how “previous participants” ostensibly categorized these images (these values were actually manipulated across images). We found that participants incorporated both peers’ categorizations of the images and their own distress ratings when categorizing images as threatening or safe. Study 2 (N=115) replicated these findings and further demonstrated that peers’ categorizations shifted how distressed these images made them feel. Taken together, our results indicate that people integrate their own and others’ experiences when exposed to emotional content and that social information can influence both our perceptions of things as threatening or safe, as well as our own emotional responses to them. Our findings provide replicable experimental evidence that social information is a powerful conduit for the transmission of affective evaluations and experiences.
Control System Design for Azimuth Position of Earth Station Antennas
Authors: Al-Mayyahi Auday , Aldair Ammar , Khalaf Zainab A. 
Published: January 2024

Abstract

Smart earth station antennas have been used for several decades in many applications, from satellite communications to space object detection and tracking. The accuracy of the azimuth position for such antennas plays a crucial role in most steerable ground station antennas. Satellite tracking and space object detection demand precise tracking capabilities from the Earth. Several methods and techniques have been developed and used in industry to control the directions of ground station antennas, including the azimuth position. The challenge of azimuth tracking is increasing with the demand for full-sky coverage and with the exponential increase in space objects, including man-made satellites and operational and nonoperational objects; thus, providing accurate tracking is a key technology that demands continuous enhancement and development. This article presents the use of a PID-proportional-integral-derivative controller, a slide mode controller and a fractional order PID controller. It also introduces a new methodology based on model predictive control (MPC). The manuscript provides the core design for each of these controllers and provides insight into the performance of each controller even in the presence of disturbance. The camel optimization algorithm (COA) was used to obtain the optimal design parameters of each controller in the considered scenarios.
Comprehensive Analysis of Ordering in CoCrNi and CrNi2 Alloys
Authors: Coury Francisco , Bacurau Vinícius , Moreira Pedro , Bertoli Gustavo , Andreolli Angelo , Mazzer Eric , Assis Flavio , Gargarella Piter , Figueroa Santiago , Widom Michael , Kaufman Michael , Fantin Andrea , Cao Yifan , Freitas Rodrigo , Miracle Daniel 
Published: January 2024

Abstract

In the intricate realm of high and medium entropy alloys (HEAs/MEAs), the elusive nature of Chemical Short-Range Order (CSRO) has captivated researchers, creating intense debates on its impact on material properties. Rooted in the local arrangement of atoms, CSRO's pivotal role in shaping the structural and mechanical characteristics of HEAs remains a subject of fervent exploration. The challenges lie in confirming and quantifying CSRO, as its detection proves exceptionally demanding, contributing to conflicting data in the literature regarding its true effects on mechanical properties. Our work uses high-precision calorimetric data to unambiguously prove the existence and, coupled with atomistic simulations, quantify the type of CSRO. This methodology allows us to propose a mechanism for its formation and destruction based on the heat evolution during thermal analysis and facilitates a precise identification of local ordering in CoCrNi alloys. Samples of CoCrNi (Co33Cr33Ni33) and CrNi2 (Cr33Ni66) alloys are fabricated in varying ordered states, extensively characterized via synchrotron X-Ray diffraction, X-Ray absorption spectroscopy, and transmission electron microscopy. Samples with considerably different ordered states are submitted to tensile tests with in-situ synchrotron X-Ray diffraction. Despite inducing varied CSRO levels in CoCrNi, no significant alterations in overall mechanical behavior emerge. However, the CrNi2 alloy, which undergoes long-range ordering, experiences profound shifts in yield strength, ultimate tensile stress, dislocation density, and ductility. The novel methodology proposed in this work charts a course toward harnessing the nuanced effects of CSRO on material properties in complex alloys.
The use of ribociclib in real clinical practice: results of a single-center observational retrospective study
Authors: Sultanbaev A. V. , Kolyadina I. V. , Musin Sh. I. , Nasretdinov A. F. , Sultanbaeva N. I. , Menshikov K. V. , Menshikova I. A. , Askarov V. E. , Rakhimov R. R. , Lipatov D. O. , Lipatov O. N. , Sultanbaev M. V. , Zabelin V. M. , Izmailov A. A. , Ayupov R. T. , Izmailov A. A. 
Published: January 2024

Introduction. The standard initial treatment for patients with hormone receptor positive, HER2 negative, metastatic breast cancer (HR+/HER2– mBC) involves the use of CDK4/6 inhibitors (CDK4/6i) in combination with endocrine therapy. The combination therapy has proven effectiveness in numerous Phase II and III randomized controlled trials (RCTs). Nonetheless, RCTs may not fully represent real-world clinical situations due to their stringent inclusion criteria, resulting in a specific patient population.Aim. Analyze of ribociclib using for treating patients with HR+/HER2– advanced breast cancer (mBC) at the Republican Clinical Oncology Dispensary.Materials and methods. Patients diagnosed with HR+/HER2– mBC who were treated in clinical routine with ribociclib in combination with different endocrine agents between 2016 and 2020 were identified and enrolled in this retrospective study. Clinicopathological characteristics and clinical outcomes were recorded with particular emphasis on ribociclib therapy course (progression-free survival (PFS), toxicity, dose reduction).Results. Data from n = 101 patients were evaluated. The mean patient age was 61 years. The study included 67 (66.3%) patients with progression after radical treatment and 34 (33.7%) patients with primary disseminated breast cancer. Dose reduction due to adverse events was performed in n = 14 cases (13.9%). Presence of prior therapy lines and lower ECOG status were associated with shorter PFS, whereas estrogen positivity and the choice of fulvestrant over aromatase inhibitor were positively associated with PFS. Metastatic pattern, progesterone positivity and dose reduction due to toxicity did not significantly impact on PFS.Conclusion. Our real-world data analysis on ribociclib treatment in Russian regional hospital supports data from RCTs regarding both treatment efficacy and safety of CDK4/6i for treatment of patients with HR+/HER2– mBC. Currently, by expanding our experience with CDK4/6 inhibitors in different groups of patients with mBC, we will be able to provide patients with optimal treatment options.
Effects of land use/land cover change on hydrological responses of a watershed in the Central Rift Valley of Ethiopia
Authors: Besha Kokeb Zena , Demissie Tamene Adugna , Feyessa Fekadu Fufa 
Published: January 2024

Abstract

The purpose of this study is to evaluate the impacts of LULC changes on the hydrological components of a watershed using multivariate statistics, and hydrological modeling approaches. The study analyzed the LULC distributions, and changes corresponding to the years 2000, 2010, and 2020. The SWAT model was then applied to assess the hydrological impacts of these changes in the studied watershed. Finally, changes in LULC types were correlated with the water balance components using a Partial Least Squares Regression (PLSR) method. The result showed a continuous expansion of barren, built-up, and cropland areas, while forests, shrubs, and grassland decreased by about 67.12, 41, and 36.88%, respectively. The modeling result showed that surface runoff, water yield, and evapotranspiration decreased by 16.1, 2.9, and 9.3%, respectively. In contrast, base flow, soil water storage, and lateral flow of the watershed increased by up to 19.1%, 55.9%, and 150.4%, respectively, due to LULC changes. The PLSR model identified the cropland, forest, and shrub LULC types as the major factors affecting the water resource components. The study results provide useful information for policymakers and planners in the implementation of sustainable water resource planning and management in the context of environmental change.
The effect of arbuscular mycorrhizal fungi on carbon dioxide (CO2) emission from turfgrass soil under different irrigation intervals
Authors: Boyno Gökhan , Yerli Caner , Çakmakci Talip , Sahin Ustun , Demir Semra 
Published: January 2024

AbstractIncreased nutrient and/or water uptake by arbuscular mycorrhizal (AM) symbiosis can affect soil biochemical properties and emission of the greenhouse gas carbon dioxide (CO2). Therefore, an experiment was designed to investigate the effect of AM fungi (AMF) on CO2 emissions from turfgrass. Three different AMF species (Funneliformis mosseae, Claroideoglomus etunicatum, and Rhizophagus irregularis) were used in this experiment. Turfgrass plants were cultivated in pots containing both mycorrhizal and non-mycorrhizal soils over a 10-week period. To mimic real-world conditions, the plants underwent irrigation cycles at intervals of 1, 2, and 3 days, replicating common irrigation practices in turfgrass fields. The research aimed to comprehensively understand the effects of AMF and varying irrigation intervals on CO2 emissions, soil characteristics, plant growth, and AMF parameters. It was observed that the changing irrigation intervals affected the AM symbiosis and this effect increased as the irrigation interval increased. It was determined that this AM symbiosis created with the plant significantly reduced CO2 emissions. In addition, it was determined that it regulates the soil structure and increases plant growth. In conclusion, it can be said that AMF species reduce CO2 emissions by reducing the need for water in the turfgrass.
Deep learning models for groundwater level prediction based on delay penalty
Authors: Chenjia Zhang , Xu Tianxin , Zhang Yan , Ma Daokun 
Published: January 2024

Abstract
In irrigation agriculture, predicting groundwater level (GWL) using deep learning models can help decision-makers coordinate surface water and groundwater usage, thus aiding in the sustainable development and utilization of groundwater. However, when making a long sequence prediction, prediction sequences often have severe delays affecting the availability of prediction results. In this paper, a new loss function is proposed to minimize the lag and oversmoothing on the prediction of GWLs. GWL, meteorology, and pumping data are collected via an irrigation Internet of Things system in Hutubi County, Xinjiang. Through Pearson's correlation analysis, historical potential evapotranspiration (ET0), groundwater extraction, and GWL were chosen to predict GWLs. Datasets were constructed through the proposed spatiotemporal data fusion method; then, the best model from the six deep learning models was selected by comparing the prediction capability of the datasets. Finally, the mean-squared error (MSE) loss function is replaced by the proposed loss function. Compared to the mean absolute error, MSE, and predicted sequence graphs, the new loss function significantly depresses the time delay with similar prediction accuracy.
IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater
Authors: Arinaitwe Miriam , Okedi John 
Published: January 2024

Abstract

The sustainable management of groundwater resources in developing countries is often challenging due to limited measurement and monitoring infrastructure to collect data necessary for decision support. To make a contribution towards addressing these challenges, this study investigated the use of Internet of Things (IoT) technology and low-cost sensors to collect the required groundwater-level data and develop a model to map the recharge potential with stormwater. The study focused on two stormwater ponds located in a highly urbanised area in Cape Town, South Africa. A combination of Geographic Information System and analytic hierarchy process was integrated to generate a groundwater recharge potential zone map of the study area. The IoT-based data were used to develop and calibrate a numerical groundwater model in MODFLOW. The study determined that retrofitted stormwater ponds are potential groundwater augmentation zones and can provide opportunity for stormwater recharge in urban areas. Overall, this study highlights the potential of IoT to collect hydrogeological data with low-cost sensors. Data can be collected at high temporal resolution, and the spatial scale can be increased due to availability of low-cost sensors.
Molecular Insight into the Apoptotic Mechanism of Cancer Cells: An
Explicative Review
Authors: Karati Dipanjan , Kumar Dileep 
Published: January 2024

Abstract::
Mitosis of somatic cells produces a daughter cell. Apoptosis, a naturally programmed cellular death mechanism, kills abnormal cells produced by
mitosis. Cancer can develop when this equilibrium is disrupted, either by an upsurge in cell propagation or a reduction in tissue demise. Cancer
therapy aims to cause cancer cells to die while inflicting little harm to healthy cells. This review of apoptotic mechanism processes improves our
understanding of how certain malignancies begin and develop. The current cancer treatments can operate either by inducing apoptosis or causing
direct cell damage. An insight into the resistance to apoptosis may explicate why malignancy treatments fail in some situations. New therapies
grounded on our understanding of apoptotic processes are being developed to induce apoptosis of cancer cells while limiting the simultaneous
death of normal cells. Various biological activities require redox equilibrium to function properly.

:
Antineoplastic medications that cause oxidative stress by raising ROS and blocking antioxidant mechanisms have recently attracted much interest.
The rapid accumulation of ROS impairs redox balance and damages cancer cells severely. Here, we discuss ROS-instigating malignancy therapy
and the antineoplastic mechanism used by prooxidative drugs.
Effects of Digitization of Self-Monitoring of Blood Glucose Records Using a Mobile App and the Cloud System on Outpatient Management of Diabetes: Single-Armed Prospective Study
Authors: Handa Tomoko , Onoue Takeshi , Kobayashi Tomoko , Maeda Ryutaro , Mizutani Keigo , Yamagami Ayana , Kinoshita Tamaki , Yasuda Yoshinori , Iwama Shintaro , Miyata Takashi , Sugiyama Mariko , Takagi Hiroshi , Hagiwara Daisuke , Suga Hidetaka , Banno Ryoichi , Azuma Yoshinori , Kasai Takatoshi , Yoshioka Shuko , Kuwatsuka Yachiyo , Arima Hiroshi 
Published: January 2024

Background
In recent years, technologies promoting the digitization of self-monitoring of blood glucose (SMBG) records including app-cloud cooperation systems have emerged. Studies combining these technological interventions with support from remote health care professionals have reported improvements in glycemic control.

Objective
To assess the use of an app-cloud cooperation system linked with SMBG devices in clinical settings, we evaluated its effects on outpatient management of diabetes without remote health care professional support.

Methods
In this multicenter, open-label, and single-armed prospective study, 48 patients with diabetes (including type 1 and type 2) at 3 hospitals in Japan treated with insulin or glucagon-like peptide 1 receptor agonists and performing SMBG used the app-cloud cooperation system for 24 weeks. The SMBG data were automatically uploaded to the cloud via the app. The patients could check their data, and their attending physicians reviewed the data through the cloud prior to the patients’ regular visits. The primary outcome was changes in glycated hemoglobin (HbA1c) levels.

Results
Although HbA1c levels did not significantly change in all patients, the frequency of daily SMBG following applying the system was significantly increased before induction at 12 (0.60 per day, 95% CI 0.19-1.00; P=.002) and 24 weeks (0.43 per day, 95% CI 0.02-0.84; P=.04). In the subset of 21 patients whose antidiabetic medication had not been adjusted during the intervention period, a decrease in HbA1c level was observed at 12 weeks (P=.02); however, this significant change disappeared at 24 weeks (P=.49). The Diabetes Treatment Satisfaction Questionnaire total score and “Q4: convenience” and “Q5: flexibility” scores significantly improved after using the system (all P<.05), and 72% (33/46) patients and 76% (35/46) physicians reported that the app-cloud cooperation system helped them adjust insulin doses.

Conclusions
The digitization of SMBG records and sharing of the data by patients and attending physicians during face-to-face visits improved self-management in patients with diabetes.

Trial Registration
Japan Registry of Clinical Trials (jRCT) jRCTs042190057; https://jrct.niph.go.jp/en-latest-detail/jRCTs042190057
Application of Failure Mode and Effects Analysis to Improve the Quality of the Front Page of Electronic Medical Records in China: Cross-Sectional Data Mapping Analysis
Authors: Zhan Siyi , Ding Liping , Li Hui , Su Aonan 
Published: January 2024

Background
The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences.

Objective
The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes.

Methods
From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People’s Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures.

Results
We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased.

Conclusions
In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China.