bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wearable-based Physical Activity as a Digital Biomarker of Inflammation, Biological Age, and Mortality: A Hierarchical Clustering Analysis of NHANES 2011-2014
Authors: Shim Jinjoo , Fleisch Elgar , Barata Filipe 
Published: February 2023

Abstract
Current measures of health and longevity are based on factors such as inflammation, biological age, and mortality. The potential of using continuously collected data from digital devices to explain these measures remains largely unstudied. In this work, we investigate a data-driven segmentation of the 24-hour physical activity profiles from wearables as a novel digital biomarker for longevity in 7,297 U.S. adults from the 2011–2014 National Health and Nutrition Examination Survey. Using hierarchical clustering, we identified five clusters and described them as follows: “High physical activity (PA)”, “Low PA”, “Mild circadian rhythm (CR) disruption”, “Extreme CR disruption”, and “Very low PA”. Young adults with extreme CR disturbance are seemingly healthy with few comorbid conditions, but in fact associated with higher white blood cell, neutrophils, and lymphocyte counts (0.05–0.07 log-unit, all p < 0.05) and accelerated biological aging (1.45 years, p < 0.001). Older adults with CR disruption are significantly associated with increased systemic inflammation indexes (0.09–0.13 log-unit, all p < 0.001), biological aging advance (1.31 years, p = 0.008), and all-cause mortality risk (HR = 1.67, p = 0.019). Our findings highlight the importance of circadian alignment on longevity across all ages and suggest that digitally measured physical activity data can help in identifying at-risk populations and personalize treatments for healthier aging.
Professionals' Quality of Life of dentist who works in public and private health care facilities
Authors: Noormohammadi Robab , Ghoflgari Tooba , Faghfouri Mehran , Maleki Azam 
Published: February 2023

Abstract
Background
Dentistry is a fascinating occupation but entails its own set of challenges. Long-term work and job stress can negatively impact dentists' physical and mental health, as well as their quality of life. The current study aimed to examine the professional quality of life of dentists who work in public and private healthcare facilities.
Methods
A cross-sectional study was conducted on 68 dentists. Data was collected using standard professional quality of life questionnaires and analyzed using descriptive statistics, independent t-tests, ANOVA, and a linear regression model.
Results
Participants' mean total professional quality of life score was 63.53, with a standard deviation of 18.29. As indicated by their scores, 27.9% (19 people) had a low level of professional quality of life, 20.6% (14 people) had an average level, and 51.5% (35 people) had a high level of professional quality of life. There was a significant relationship between income and type of organizational activity (P >0.05).
Discussion
Our result showed that more than half of dentists had a high level of professional quality of life. Considering the relationship between activity and income and the quality of life of public-sector dentists, it seems necessary to develop plans to improve the quality of their lives.
Data Monitoring in Student Psychological Automatic Evaluation System by using Dynamic Acquisition Algorithm
Authors: Li Peng 
Published: February 2023

Abstract
The purpose of Designing Embedded Internet of things and studying the ad hoc technology of gateway is to meet the monitoring requirements brought by the continuous expansion of data center. Among them, in the aspect of dynamic data monitoring, this paper designs a dynamic acquisition algorithm, that is, by analyzing the characteristics of data center resources and the number of information acquisition methods, so as to adjust the data acquisition cycle, so as to reduce the monitoring workload and improve the monitoring flexibility. At the same time, this paper also studies the automatic psychological evaluation system of students. It is found that with the intensification and efficient operation of social competition, some special groups of college students are facing increasing pressure, and events caused by psychological problems emerge one after another. Even though there are many psychological evaluation systems on the network. However, a large number of psychological knowledge and mental health management on the Internet can not effectively manage and improve the psychological status of college students. Therefore, the university needs to build a psychological evaluation system for college students in time, and combine the automatic psychological evaluation system for college students with embedded Internet of Things and cloud service technology to improve the accuracy of psychological evaluation. The application of the system, college students can independently evaluate their own mental state, if there are psychological problems can be timely counseling, not only can improve the level of mental health education in colleges and universities, but also can promote the development of physical and mental health.
App interaction design in the pop music singing teaching system based on Differential Evolution Algorithm
Authors: Wu Qinke 
Published: February 2023

Abstract
The dynamic spectrum management of cognitive technology can greatly increase the utilization of network spectrum, but while bringing convenience to our daily lives, this new technology will also greatly increase the consumption of nodes. At present, the short video industry is growing rapidly with the development of smart phones. Among them, the emergence of online pop music singing teaching platforms (software that mainly uses music as the background to shoot short videos) Significant changes have taken place in people's lifestyles. We can learn from the three-stage theory of flow experience to design and explore the method of plan implementation, and propose a targeted interaction design strategy for each flow characteristic, so that the overall design strategy becomes more practical and practical. In the design of this paper, the principle of cognitive wireless sensor network is applied in the technical aspect, and the principle of interactive design is applied in the product design.When a user reaches a state of flow while using the online popular music singing teaching platform, it can be evaluated that the user experience of the App is the best. The research on the interaction design of the online pop music singing teaching platform under the flow experience is intended to propose an interactive design strategy that can guide the online pop music singing teaching platform to better create a flow experience for users.
Online task scheduling and English online cooperative learning based on 5G mobile communication network
Authors: Guo Shanshan 
Published: February 2023

Abstract
The task density of the data processing platform is increasing, and effective online task scheduling directly determines the business flexibility of the data processing platform. This article starts with the remarkable dynamic characteristics of 5G cellular networks, creates an adaptive environment to optimize online task scheduling, and designs the workload characteristics of data processing and computing tasks. On this basis, based on the 5G mobile communication network programming model and the operating and functional principles of its supporting system, the actual structure and field of online task scheduling work templates have been developed and designed. In addition, this article is developing a technology-based, non-intrusive online task scheduling program that can perform detailed real-time detection of the actual implementation of online task scheduling. In this paper, 5G cellular network is used to further reduce the service cache location of online content, and collaborative English learning and deployment at the edge of the network closer to the end user can further reduce network delay, which is important for improving mobile network communication and improving the efficiency of network content distribution. This article creates a model for online collaborative learning of college English on a 5G cellular network, and analyzes the data based on experiments with comparative models to improve their self-confidence and interpersonal skills, these skills can help improve students' language skills.
Improvement of geoid accuracy using convolution neural networks and empirical rules
Authors: Nasser Mohammed , Sami Kamal , Abdalla Ahmed 
Published: February 2023

Abstract
We improve the accuracy of global geoid models (GGMs) by utilizing deep convolutional neural networks (CNNs) and empirical rules. The geoid heights obtained from the global geopotential models (GGM), EGM2008, and XG2019, are validated using geometrical geoid heights obtained from GNSS/leveling data. We used AlexNet, LeNet, and VGG16 CNN models to investigate the improvement of geoid accuracy and found that VGG16 model shows the most significant improvement among all the models. The VGG16 model improves the geoid accuracy of EGM2008 and XGM2019e by about 39 cm. Additionally, we apply empirical rules for outliers detection to eliminate unreliable GNSS/leveling data and found that this further improves the geoid accuracy by 13 cm for EGM2008 and 12 cm for XGM2019e. We also used a 7-parameter stochastic model to remove existing systematic errors, impacting 9 mm on AlexNet and VGG16.
Network learning path of university political education based on simulation data and sparse neural network
Authors: Shao Kaixuan 
Published: February 2023

Abstract
In the face of the impact of the New Coronary Pneumonia epidemic, Schools need to actively engage in online teaching in response to the Ministry of Education's call for "uninterrupted teaching". Ideological and political education is an important way to train socialist successors, and is the basis for establishing students' correct outlook on life, values and the world outlook. Therefore, in this paper, sparse neural network algorithm is introduced to complete the construction of ideological and political online education platform for colleges and universities. Through the design of simulation experiments, we can know that the sparse model can still maintain the stability and accuracy of the network under the condition of black box attacks, and even after a certain amount of tailoring, it can still exceed the accuracy of the original network. The experimental results show the superiority of this platform. In this paper, the platform system is roughly divided into three layers: user layer, data storage layer and functional logic layer. The evaluation is carried out from four dimensions: teaching resources, teaching activities, teacher-student interaction and teacher-student evaluation. According to the results, students have higher systematic evaluation than teachers. Among them, the recognition of teaching resources and activities is high, which proves that the platform in this paper is effective. The online teaching platform designed in this paper can make full use of the characteristics of network technology, realizes the reform and innovation development path of the ideological course in schools, and enhances the attraction of the political course and the enthusiasm of students to learn. This paper designs a kind of network education system by introducing sparse neural network into ideological online education.
Maize//soybean intercropping promotes activation of soil phosphorus fractions by secreting more phosphatase in red soil under different phosphorus application rates
Authors: Zhou Long , Su Lizheng , Zhao Hongmin , Wang Sirui , Zheng Yi , Tang Li 
Published: February 2023

Abstract
Aims
Rational intercropping plays an important role on improving Phosphorus(P) uptake and utilization. This study aimed to investigate the effects of intercropping on the activation of soil P fractions and available P in acid soil.
Methods
The field experiments were conducted for two consecutive years to investigate the effects of maize intercropping with soybean at different P application rates (0, 60, 90, and 120 kg P2O5 ha− 1) on soil P fractions and P turnover.
Results
Compared with the monoculture maize, intercropping significantly increased maize P uptake by 43.6%~74.3% and 45.5%~76.8% in two years, while the intercropping advantage gradually weakened with the increasing of P levels. Intercropping maize promoted the activation of soil P pools, which increased labile P pools by 32.5%~38.4% and 14.4%~82.1%, while reducing non-labile P pools by 7.4%~10.9% and 6.6%~11.6% compared with monoculture maize. Meanwhile, intercropping could deplete NaOH-Po, conc. HCl-Pi, conc. HCl-Po and Residual-P fractions, and increase Resin-P, NaHCO3-Pi, NaHCO3-Po by 4.3%~41.2%, 21.1%~84.6% and 9.7%~98.8%, respectively. In addition, intercropping significantly increased alkaline phosphatase activity (ALP) by 21.2%~42.6% and 19.9%~28.6%, and significantly increased acid phosphatase activity (ACP) by 13.8%~27.1% and 9.5%~13.4% under different P rate. Structural equation model (SEM) showed that both ACP and ALP plays curtail role increased available P directly or indirectly through their effects on organic P turnover.
Conclusions
These result highlight the importance that intercropping maize with soybean increases soil P bioavailability by transforming organic P pools (NaOH-Po and conc. HCl-Po) into soluble phosphate (Resin-P, NaHCO3-Pi and NaOH-Pi) by facilitating the secretion of phosphatase.
Lung Cell Cancer Identification Mechanism Using Deep Learning Approach
Authors: wankhade shalini , S Vigneshwari 
Published: February 2023

Abstract
Nowadays, healthcare solutions have accomplished radical advancements in developing diagnostic mechanisms using machine and deep learning (DL) based techniques. The symptoms of lung cell cancer are common to many other ailments; hence the healthcare practitioners may make mistakes in identification of lung cancer in early stages. Cancer enters into human body silently and the symptoms such as weakness, weight loss and fever are common to many other ailments which may confuse the physicians to distinguish between cancer symptoms and other ailment symptoms. Cancer is usually detected in lateral stages when it is difficult to control the further spread of cancer in the other parts of the body. Cancer is one of the major causes of the deaths in the youngsters these days. There are many existing techniques which can help in diagnosis of cancer but still there is a need to explore more intelligent mechanisms which not only identify the presence of cancer in the cells but also determine the stages of the cancer for timely treatment. Hence the proposed DL based diagnostic mechanism not only identifies the presence of cancer in lung cells but also determines the respective stage. A DL-based Lung Cell Cancer Detection (DL-LCCD) is suggested in this paper to detect lung cell cancer. The proposed DL-LCCD method determines the cancerous cells with the aid of digital image processing techniques with high accuracy and precision. A Hybrid CNN model is devised to determine the cancer from the CT scanned images. The evaluation metrics are used to test the viability of the proposed DL-LCCD method. The classification accuracy of 95.30% is achieved with 10-fold cross-validation and 96.10% accuracy with 15-fold cross-validation.
Role of microRNA-dependent PTEN downregulation in the resistance to PI3K inhibitor alpelisib in head &amp; neck squamous cell carcinoma
Authors: Pulito Claudio , Ganci Federica , Frascolla Carlotta , Sacconi Andrea , Benedetti Anna , Manciocco Valentina , Covello Renato , Morrone Aldo , Pellini Raul , Muti Paola , Meens Jalna , Karamboulas Christina , Nichols Anthony , Ailles Laurie , FAZI FRANCESCO , Strano Sabrina , Fontemaggi Giulia , Blandino Giovanni 
Published: February 2023

Abstract
Head and neck squamous cell carcinomas (HNSCCs) frequently harbor alterations in the PI3K signaling axis and, particularly, in the PIK3CA gene. The promising rationale of using PI3K inhibitors for the treatment of HNSCC has, however, clashed with a spontaneous development of resistance over time, observed both in PDX models and cell lines.
Aimed at identifying valuable targets to circumvent acquired resistance to the PI3Kα inhibitor alpelisib in HNSCC herein we performed microRNA profiling in a cohort of HNSCC PDXs, treated or not with alpelisib, including both responding and resistant tumors. We highlighted that microRNAs specifically altered in resistant PDXs include members of miR-17-92 cluster, encoded by MIR17HG. Mechanistically, we observed that hyperactive c-Myc protein is recruited on MIR17HG regulatory regions in alpelisib-resistant cells, causing the sustained expression of miR-17-5p, miR-19b-3p and miR-20a-5p which, in turn, downregulate the expression of tumor suppressor PTEN. Of note, either knocking out (KO) or silencing PTEN confers resistance to treatment with alpelisib in HNSCC cells. By phosphoproteomic profiling we identified a panel of PTEN-dependent phosphorylation events involved in alpelisib resistance, such as p-Plk1-T210. Interestingly, targeting of Plk1 through rigosertib treatment strongly reduced the viability of alpelisib-resistant cells.
In aggregate, this study reveals that post-transcriptional non-genetic events contribute to the downregulation of PTEN in HNSCC during treatment with PI3K inhibitors thus favoring the onset of resistance. We propose the blocking of PTEN-dependent targets as a powerful strategy for the treatment of alpelisib-resistant HNSCCs.
Using natural language from a smartphone pregnancy app to identify maternal depression
Authors: Krishnamurti Tamar , Allen Kristen , Hayani Laila , Rodriguez Samantha , Rothenberger Scott , Moses-Kolko Eydie , Simhan Hyagriv 
Published: February 2023

Abstract

Depression is highly prevalent in pregnancy, yet it often goes undiagnosed and untreated. Language can be an indicator of psychological well-being. This longitudinal, observational cohort study of 1,274 pregnancies examined written language shared in a prenatal smartphone app. Natural language feature of text entered in the app (e.g. in a journaling feature) throughout the course of participants’ pregnancies were used to model subsequent depression symptoms. Language features were predictive of incident depression symptoms in a 30-day window (AUROC = 0.72) and offer insights into topics most salient in the writing of individuals experiencing those symptoms. When natural language inputs were combined with self-reported current mood, a stronger predictive model was produced (AUROC = 0.84). Pregnancy apps are a promising way to illuminate experiences contributing to depression symptoms. Even sparse language and simple patient-reports collected directly from these tools may support earlier, more nuanced depression symptom identification.
Reference intervals and sources of variation of pressure pain threshold for quantitative sensory testing in a Japanese population
Authors: Suzuki Hidenori , Tahara Shu , Mitsuda Mao , Funaba Masahiro , Fujimoto Kazuhiro , Ikeda Hironori , Izumi Hironori , Yukata Kiminori , Seki Kazushige , Uranami Kota , Nishida Norihiro , Sakai Takashi 
Published: February 2023

Abstract

Quantitative sensory testing (QST) is useful when analysing musculoskeletal pain disorders. A handheld algometer is most commonly used for pressure pain threshold (PPT) tests. However, reference intervals for PPTs are not elucidated. We assessed reference intervals of PPTs for QST in 158 healthy adult Japanese (73 females, 85 males) with no history of musculoskeletal or neurological problems. A handheld algometer was used to record PPT at five different assessment sites on the body: lumbar paravertebral muscle (PVM), musculus gluteus maximus (MGM), quadriceps (QC), tibialis anterior muscle (TA), and anterior talofibular ligament (TL). Multiple regression analysis (MRA) was performed to explore sources of variation of PPT according to sex, age, body mass index (BMI), UCLA Activity Level Rating (ALR), and Tegner Activity Score. Reference intervals were determined parametrically by Gaussian transformation of PPT values using the two-parameter Box-Cox formula. MRA results revealed that age was significantly associated with PPT-PVM in males and with PPT-PVM and PPT-MGM in females. In females, BMI showed significant positive correlation with PPT-TL, and ALR reflecting daily activities also showed significant positive association with PPT-TA and PPT-TL. Site-specific reference intervals of PPTs for Japanese are of practical relevance in fields of pain research using a handheld algometer.
Maturation of Nucleus Accumbens Synaptic Transmission Signals a Critical Period for the Rescue of Social Deficits in a Mouse Model of Autism Spectrum Disorder
Authors: Matthiesen Melina , Khlaifia Abdessattar , Steininger Carl Frank David , Dadabhoy Maryam , Mumtaz Unza , Arruda-Carvalho Maithe 
Published: February 2023

Abstract
Social behavior emerges early in development, a time marked by the onset of neurodevelopmental disorders featuring social deficits, including autism spectrum disorder (ASD). Although social deficits are at the core of the clinical diagnosis of ASD, very little is known about their neural correlates at the time of clinical onset. The nucleus accumbens (NAc), a brain region extensively implicated in social behavior, undergoes synaptic, cellular and molecular alterations in early life, and is particularly affected in ASD mouse models. To explore a link between the maturation of the NAc and neurodevelopmental deficits in social behavior, we compared spontaneous synaptic transmission in NAc shell medium spiny neurons (MSNs) between the highly social C57BL/6J and the idiopathic ASD mouse model BTBR T+Itpr3tf/J at postnatal day (P) 4, P6, P8, P12, P15, P21 and P30. BTBR NAc MSNs display increased spontaneous excitatory transmission during the first postnatal week, and increased inhibition across the first, second and fourth postnatal weeks, suggesting accelerated maturation of excitatory and inhibitory synaptic inputs compared to C57BL/6J mice. BTBR mice also show decreased optically evoked medial prefrontal cortex-NAc synaptic transmission at P15 and P30. These early changes in synaptic transmission are consistent with a potential critical period, which could maximize the efficacy of rescue interventions. To test this, we treated BTBR mice in either early life (P4-P8) or adulthood (P60-P64) with the mTORC1 antagonist rapamycin, a well-established intervention for ASD-like behavior. Rapamycin treatment rescued social interaction deficits in BTBR mice when injected in infancy, but not in adulthood.