bluuebunny/crossref_metadata_2025 huggingface dataset:
Can leisure and entertainment lifestyle promote health among older people living alone in China?—A simultaneous equation approach
Authors: Qin Yinghua , Liu Jingjing , Wang Rizhen , Qi Xinye , Jiang Shengchao , Li Jiacheng , Guo Pengfei , Wu Qunhong
Published: September 2022

Objectives

With the surging number of older people living alone, their lifestyles and health status have aroused increasing concern. This study aims to investigate whether a leisure and entertainment lifestyle (LEL) can improve the multidimensional health among older people living alone and try to identify the latent mechanisms among them.

Method

For this purpose, we extracted data from the Chinese General Social Survey (CGSS) and established a simultaneous equations model, comprising ordinary least square regression (OLS), two-stage least squares (2SLS), and the mediating effect model.

Results

Older people living alone in China reported relatively better mental health status (3.64 ± 1.07), followed by physical health (3.41 ± 1.26) and social health (2.75 ± 1.18). In the OLS model, LEL significantly improved the social health of older people living alone (β = 0.054, P < 0.01), followed by physical health (β = 0.042, P < 0.01) and mental health (β = 0.027, P < 0.01). After endogenous tests from 2SLS model and robustness tests, we found that more active LEL was associated with higher levels of physical health and mental health. However, LEL had no significant effect on the improvement of the social health of the older people living alone. Using the mediation analysis, exercise efficacy partially mediated the relationship of LEL with physical health and mental health, and the ratios were 19.75 and 24.85%, respectively. Similarly, positive life attitudes partially mediated the relationship between LEL and physical health, and LEL and mental health, with ratios of 10.65 and 26.83%, respectively.

Conclusion

Our findings suggested that LEL is significantly associated with better physical and mental health for older people living alone in China, and the association is mediated by exercise efficacy and positive attitudes toward life. Promoting more leisure and recreational activities, upgrading exercise efficacy, and encouraging positive life attitudes are necessary health promotion measures in active aging policies for the wellbeing of older people living alone.
Local socio-structural predictors of COVID-19 incidence in Germany
Authors: Qamar Alisha I. , Gronwald Leonie , Timmesfeld Nina , Diebner Hans H.
Published: September 2022

Socio-economic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socio-economic driving factors of the COVID-19 epidemic is still incomplete. Based on linear random effects regression, an ecological model is derived to estimate COVID-19 incidence in German rural/urban districts from local socio-economic factors and popularity of political parties in terms of their share of vote. Thereby, records provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, are used to construct the dependent variable. Local socio-economic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Socio-economic parameters like per capita income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact on incidence. To the contrary, incidence significantly increases with population density and we observe a strong association with vote shares. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. In order to effectively combat the COVID-19 epidemic, public health policymakers are well-advised to account for social attitudes and behavioral patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive “markers” relevant for public health policy making.
Family functioning and delinquency among Chinese adolescents: Mediating effects of positive behavior recognition according to the humanistic perspective
Authors: Wan Xingli , Ji Shuming , Liu Min , Hong Binxue , Shi Wei , Du Liang , Zhao Li
Published: September 2022

Background

Empirical research on the relationship between family functioning and delinquency has been sparse, although many studies have focused on the influence of family functioning on adolescent development. The current research aimed to fill this gap by exploring the influences of family functioning on adolescent delinquency and the mechanisms connecting the processes.

Methods

We derived the baseline data from a prospective observational school-based cohort Chengdu Positive Child Development (CPCD) project. Students responded to a questionnaire containing validated measures of family functioning, positive behavior recognition, and delinquent behavior. We utilized structural equation modeling and maximum likelihood estimation to test the relationships.

Results

Across 8811 Chinese adolescents, the incidence of delinquency behaviors among Chinese adolescents was relatively low. Family functioning and positive behavior recognition negatively predict delinquency (p < 0.001). Further, positive behavior recognition partially mediated the influence of family functioning on delinquency [p < 0.001, std. error = 0.01, 95% CI = (0.04, 0.07)]. Adolescents with better family functioning had little delinquency behavior, with positive behavior recognition and delinquency behavior negatively reinforcing each other.

Conclusions

This study demonstrated that family functioning was a protective factor against adolescent delinquency and revealed that positive behavior recognition was a critical mediating mechanism linking family functioning to delinquency.
Breakthrough cases of Omicron and Delta variants of SARS-CoV-2 during the fifth wave in Pakistan
Authors: Jamal Zunera , Haider Murtaza , Ikram Aamer , Salman Muhammad , Rana Muhammad Suleman , Rehman Zaira , Haider Syed Adnan , Ammar Muhammad , Nisar Nadia , Umair Massab
Published: September 2022

COVID-19 pandemic has severely affected Pakistan with 1,557,134 cases as of August 4, 2022. However, the data regarding breakthrough infections in Pakistan is scant. Hence, the objective was to analyze SARS-CoV-2 breakthrough infections with respect to vaccines and variants during the fifth wave in Pakistan. Therefore, the Department of Virology (NIH, Pakistan) genotyped 2,467 randomly selected individuals between November 2021 and February 2022 using the SNPsig® SARS-CoV-2 (EscapePLEX) kit (PrimerDesign, UK). P681R and K417N mutations were used to distinguish delta and omicron. Data on the patient's age, gender, date of collection, variant, and vaccination status were analyzed using Statistical Package for Social Sciences (SPSS) software. Among 2,467 genotyped samples, Omicron was detected in 58.6% (n = 1445), Delta in 40.4% (n = 998) and undetermined/wildtype variant in 24 samples. The vaccination status of omicron-positive patients showed (49.7%; n = 718/1445) and Delta-positive patients (39.67%; n = 396/998) to be fully vaccinated. Of note, a high percentage 85% of breakthrough cases (n = 947) were identified among fully vaccinated individuals (n = 1114). Among them, 85.9% (n = 617/718) belonged to omicron and 83.3% (n = 330/396) to delta. Moreover, 76.7% (n = 855) of vaccinated individuals (n = 1114) received Sinopharm (n = 432) and Sinovac (n = 423) vaccines. The majority of breakthrough subjects who contracted Omicron were vaccinated with Sinopharm (93.0%, n = 256) and delta with Cansino (100%, n = 44). Individuals vaccinated with Sinovac showed the most frequent breakthrough cases for both Omicron and Delta variant between the 4th and 6th months (n = 278) after primary vaccination as compared to the 7th to 9th months (n = 24) category. While in case of Sinopharm, maximum breakthrough cases occurred between 7th to 9th months (n = 234) as compared to the 4th to 6th months (n = 120) after primary vaccination. Omicron and Delta breakthrough cases in men (n = 364 and 193) are more frequently seen than women (n = 253 and 138) respectively and breakthrough majority cases (n = 392) occurred in individuals aged 18–33 years. Breakthrough cases limiting monitoring in Pakistan impose a substantial constraint on policymakers' ability to take timely effective decisions. Since the current study consists of only a 2,467-genotyped sample, comprehensive data should be analyzed.
Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: A cross-sectional online survey
Authors: Swed Sarya , Alibrahim Hidar , Elkalagi Nashaat Kamal Hamdy , Nasif Mohamad Nour , Rais Mohammed Amir , Nashwan Abdulqadir J. , Aljabali Ahmed , Elsayed Mohamed , Sawaf Bisher , Albuni Mhd Kutaiba , Battikh Elias , Elsharif Leena Abdelwahab Mohamed , Ahmed Safaa Mohamed Alsharief , Ahmed Eman Mohammed Sharif , Othman Zain Alabdeen , Alsaleh Ahmad , Shoib Sheikh
Published: September 2022

Artificial intelligence has been prevalent recently as its use in the medical field is noticed to be increased. However, middle east countries like Syria are deficient in multiple AI implementation methods in the field of medicine. So, holding these AI implementation methods in the medical field is necessary, which may be incredibly beneficial for making diagnosis more accessible and help in the treatment. This paper intends to determine AI's knowledge, attitude, and practice among doctors and medical students in Syria. A questionnaire conducted an online cross-sectional study on the google form website consisting of demographic data, knowledge, and perception of AI. There were 1,494 responses from both doctors and medical students. We included Syrian medical students and doctors who are currently residing in Syria. Of the 1,494 participants, 255 (16.9%) are doctors, while the other 1,252 (83.1%) are undergraduate medical students. About 1,055 (70%) participants have previous knowledge about AI. However, only 357 (23.7%) participants know about its application in the medical field. Most have shown positive attitudes toward its necessity in the medical field; 689 (45.7%) individuals strongly agree, and 628 (41.7%) agree. The undergraduate students had 3.327 times more adequate knowledge of AI than students in the first year. In contrast, the undergraduate 6th-year students had 2.868 times the attitude toward AI higher than students in the first year. The residents and assistant professors had 2.371 and 4.422 times the practice of AI higher than students, respectively. Although most physicians and medical students do not sufficiently understand AI and its significance in the medical field, they have favorable views regarding using AI in the medical field. Syrian medical authorities and international organizations should suggest including artificial intelligence in the medical field, particularly when training residents and fellowship physicians.
Implementing clinical decision support for reducing women Veterans' cardiovascular risk in VA: A mixed-method, longitudinal study of context, adaptation, and uptake
Authors: Brunner Julian , Farmer Melissa M. , Bean-Mayberry Bevanne , Chanfreau-Coffinier Catherine , Than Claire T. , Hamilton Alison B. , Finley Erin P.
Published: September 2022

Evaluations of clinical decision support (CDS) implementation often struggle to measure and explain heterogeneity in uptake over time and across settings, and to account for the impact of context and adaptation on implementation success. In 2017–2020, the EMPOWER QUERI implemented a cardiovascular toolkit using a computerized template aimed at reducing women Veterans' cardiovascular risk across five Veterans Healthcare Administration (VA) sites, using an enhanced Replicating Effective Programs (REP) implementation approach. In this study, we used longitudinal joint displays of qualitative and quantitative findings to explore (1) how contextual factors emerged across sites, (2) how the template and implementation strategies were adapted in response to contextual factors, and (3) how contextual factors and adaptations coincided with template uptake across sites and over time. We identified site structure, staffing changes, relational authority of champions, and external leadership as important contextual factors. These factors gave rise to adaptations such as splitting the template into multiple parts, pairing the template with a computerized reminder, conducting academic detailing, creating cheat sheets, and using small-scale pilot testing. All five sites exhibited variability in utilization over the months of implementation, though later sites exhibited higher template utilization immediately post-launch, possibly reflecting a “preloading” of adaptations from previous sites. These findings underscore the importance of adaptive approaches to implementation, with intentional shifts in intervention and strategy to meet the needs of individual sites, as well as the value of integrating mixed-method data sources in conducting longitudinal evaluation of implementation efforts.
Role of servitization in transitioning from scarcity to abundance paradigm
Authors: Hora Manpreet
Published: September 2022

Servitization refers to firms that sell an “outcome-as-a-service”, rather than just a physical product. In this study, we first examine how servitization has enabled companies such as Netflix to disrupt industries and transition from offering finite products to delivering relatively abundant services? Second, as firms embark upon servitization, value propositions become much less related to scarcity. This leads to the second research question: what are the value propositions for consumers when the paradigm shifts from ownership to usership? For both these questions, we highlight examples such as Netflix, Amazon Web Services (AWS), and Philips to emphasize on value propositions for the consumer as enhanced customer experience through customization, convenience, and co-creation. Further, we expand on the considerations warranted that include the role of technology, data, and analytics, distribution models for physical versus digital products, and challenges in creating servitization in business models.
Analysis of disease burden in socially disadvantaged areas: Mapping of geographical inequalities in COVID-19 morbidity and mortality using a social disadvantage index in Tennessee
Authors: Antipova Anzhelika
Published: September 2022

Social vulnerability is directly addressed by contemporaneous health research to improve social equity. Existing disadvantage indices capture vulnerability to COVID-19 pandemic less accurately. Health-related studies apply the indices to relate overall vulnerability to health outcomes including severe COVID-related health outcomes leading to hospitalization and death. The multi-variable indices are based on various attributes, some unrelated to COVID-19 severity. Some studies that use multi-attribute indices don't find meaningful association with COVID-19 health outcomes. Additionally, current research is lacking on health impacts of social disadvantage during various COVID-19 stages. Thus, due to variations in inequality in exposure and pandemic susceptibility, community health should be assessed at different time points. To fill this gap, we develop an index using six indicators capturing pandemic vulnerability. We apply it in a retrospective case study of a relationship between social disadvantage and morbidity and mortality due to COVID-19 focusing on disadvantaged communities set in Tennessee with a concentration of vulnerability and rurality. COVID-19-related health outcomes were tested for associations with a social disadvantage index (SDI) for earlier (2021) and later (2022) pandemic stages. First, we describe a methodology to create a social disadvantage index to identify communities at risk for severe COVID-19-related health outcomes based on the CDC guidance. Second, we highlight the differences in COVID-19 health outcomes over time as we examine health disparities associated with social disadvantage during various pandemic stages. To understand how the findings would differ if the same analyses were to be carried out using other vulnerability indices, we apply analyses to areas based on the CDC's-based Social Vulnerability Index and find strong statistical association between the two indices and substantial overlap regarding disadvantaged areas identified and similar health outcome findings. A better understanding of whether residents of socially disadvantaged areas experience worse COVID-related health outcomes can help determine whether policies need to target not only individuals but entire communities to improve outcomes. The developed index based on six indicators is thus especially suitable during the COVID-19 disaster to efficiently identify vulnerable communities and address social equity.
Deep learning based markerless motion tracking as a clinical tool for movement disorders: Utility, feasibility and early experience
Authors: Tien Rex N. , Tekriwal Anand , Calame Dylan J. , Platt Jonathan P. , Baker Sunderland , Seeberger Lauren C. , Kern Drew S. , Person Abigail L. , Ojemann Steven G. , Thompson John A. , Kramer Daniel R.
Published: September 2022

Clinical assessments of movement disorders currently rely on the administration of rating scales, which, while clinimetrically validated and reliable, depend on clinicians’ subjective analyses, resulting in interrater differences. Intraoperative microelectrode recording for deep brain stimulation targeting similarly relies on clinicians’ subjective evaluations of movement-related neural activity. Digital motion tracking can improve the diagnosis, assessment, and treatment of movement disorders by generating objective, standardized measures of patients’ kinematics. Motion tracking with concurrent neural recording also enables motor neuroscience studies to elucidate the neurophysiology underlying movements. Despite these promises, motion tracking has seen limited adoption in clinical settings due to the drawbacks of conventional motion tracking systems and practical limitations associated with clinical settings. However, recent advances in deep learning based computer vision algorithms have made accurate, robust markerless motion tracking viable in any setting where digital video can be captured. Here, we review and discuss the potential clinical applications and technical limitations of deep learning based markerless motion tracking methods with a focus on DeepLabCut (DLC), an open-source software package that has been extensively applied in animal neuroscience research. We first provide a general overview of DLC, discuss its present usage, and describe the advantages that DLC confers over other motion tracking methods for clinical use. We then present our preliminary results from three ongoing studies that demonstrate the use of DLC for 1) movement disorder patient assessment and diagnosis, 2) intraoperative motor mapping for deep brain stimulation targeting and 3) intraoperative neural and kinematic recording for basic human motor neuroscience.
Effects of simulated augmented reality cueing in a virtual navigation task
Authors: Stefanucci Jeanine K. , Brickler David , Finney Hunter C. , Wilson Emi , Drew Trafton , Creem-Regehr Sarah H.
Published: September 2022

Navigational tools are relied on to traverse unfamiliar grounds, but their use may come at a cost to situational awareness and spatial memory due to increased cognitive load. In order to test for a cost-benefit trade off in navigational cues, we implemented a variety of navigation cues known to facilitate target search and spatial knowledge acquisition of an urban virtual environment viewed through an HTC VIVE Pro as a simulation of cues that would be possible using Augmented Reality (AR). We used a Detection Response Task (DRT) during the navigation task to measure cognitive load and situational awareness. Participants searched for targets in the city with access to a map that did or did not have a “you are here” indicator showing the viewer’s location as they moved. In addition, navigational beacons were also present or absent in the environment as well as a compass and street name indicator. Participants searched for three separate target objects and then returned back to their starting location in the virtual world. After returning home, as a measure of spatial knowledge acquisition, they pointed toward each target from the home location and pointed to home and to the other targets from each target location. Results showed that the navigational cues aided spatial knowledge without increasing cognitive load as assessed with the DRT. Pointing error was lowest when all navigational cues were present during navigation and when pointing was done from home to the target objects. Participants who received the “you are here” indicator on their map consulted the map more often, but without detrimental effects for the acquisition of spatial knowledge compared to a map with no indicator. Taken together, the results suggest that navigational cues can help with spatial learning during navigation without additional costs to situational awareness.
Compact extra dimensions as the source of primordial black holes
Authors: Nikulin Valery V. , Krasnov Maxim A. , Rubin Sergey G.
Published: September 2022

This article discusses a model of primordial black hole (PBH) formation at the reheating stage. These small/massive black holes appear due to the specific properties of the compact extra dimensions. The latter gives rise to the low energy model, containing an effective scalar field potential capable of domain wall production. Formed during inflation, these walls are quite dense, meaning they collapse soon after inflation ends. Discussion of the model is framed by the scope of multidimensional f(R)-gravity. We study the possibility of the pure gravitational formation of primordial black holes (PBHs). Interpreting the scalar curvature of compact extra space Rn as an effective scalar field in an Einstein framework and consider effective scalar-field theory that might potentially be capable of producing domain walls with a certain choice of parameters. Hence, we demonstrate that f(R)-gravity contains a mechanism for PBH formation. The study assumed that cosmological inflation is an external process, which satisfied all the cosmological constraints on our mechanism.
Predicting the ideal apex of lumbar lordosis based on individual pelvic incidence and inflection point in asymptomatic adults
Authors: Wang Jingyu , Zhang Qianshi , Liu Fubing , Yuan Hui , Zhang Yi , Wang Xiaobin , Li Jing
Published: September 2022

Objective

The main aim of this study was to comprehensively explore the relationship among pelvic incidence (PI), inflection point (IP), and apex of lumbar lordosis (LLA), and establish a predictive formula for LLA based on individual PI and IP in asymptomatic Chinese adults.

Methods

A total of 385 asymptomatic adults with average age 38.3 ± 11.9 years (range 20–73 years) were recruited between November 2020 and October 2021. Full-spine, standing x-rays were then obtained from each participant. Next, the following sagittal parameters were measured: PI, IP, LLA, the horizontal offset between the plumb line of the lumbar apex and that of the posterosuperior corner of S1 (LASO), the upper lumbar lordosis (ULL) and lower lumbar lordosis (LLL), lumbar lordosis (LL), and thoracic kyphosis (TK). Moreover, the association among PI, IP, and the other sagittal parameters was evaluated, followed by linear regression analyses. A P-value of <0.05 was considered statistically significant.

Results

PI showed statistically significant correlations with LLA (rs = −0.629; P < 0.01), LASO (rs = 0.537; P < 0.01), LLL (rs = 0.788; P < 0.01), and LL (rs = 0.663; P < 0.01). On the other hand, IP also showed statistically significant correlations with LLA (rs = 0.671; P < 0.01), LASO (rs = −0.493; P < 0.01), LLL (rs = −0.402; P < 0.01), and LL (rs = −0.283; P < 0.01). The corresponding predictive formulae were displayed as follows: LLA = −0.03 * PI + 0.23 * IP + 14.45 (R2 = 0.669); LASO = 0.38 * PI−2.09 * IP + 53.62 (R2 = 0.460); and LLL = 0.58 * PI−0.88 * IP + 18.86 (R2 = 0.659).

Conclusion

The specific lumbar shape should be modulated by pelvic morphology and IP level. In addition, we established predictive formulae for ideal sagittal lumbar profile based on individual PI and IP, with the overarching goal of helping surgeons to better comprehend the regulatory mechanisms of the individual sagittal lumbar alignment, and design a precise and personalized corrective plan.
Different treatments for 3- or 4-part proximal humeral fractures in the elderly patients: A Bayesian network meta-analysis of randomized controlled trials
Authors: Guo Jiale , Peng Caiju , Hu Ziyan , Li Yehai
Published: September 2022

Background

Proximal humeral fractures are the third most common fracture in the body, and their incidence is rising year by year as the population ages. However, the treatment of the proximal humerus in parts 3 and 4 is still debatable, necessitating a network meta-analysis to determine the best treatment for each treatment modality.

Methods

We searched PubMed, Embase, Cochrane Library for randomized controlled trials on proximal humeral fractures up to June 21, 2022. We performed data extraction and literature quality assessment by two independent authors and extracted constant score and reoperation rate as indicators for evaluation. Stata software, Revman software, JAGS software and the R-based BlandAltmanLeh package, gemtc package and riags package were used to perform this Bayesian network meta-analysis.

Results

Following screening, 11 papers with a total of 648 participants were included in the analysis. The SUCRA values for the constant score were in the following order: RSA, IMN, Conservative, HA, and LP, and the SUCRA values for the reoperation rate were LP, HA, IMN, Conservative, and RSA.

Conclusion

The elderly with 3- or 4-part proximal humeral fractures should consider RSA because it received the best evaluation ranking in terms of constant score and reoperation rate.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341209, identifier: CRD42022341209.
Pharmacokinetic and Pharmacodynamic integration of tilmicosin against Mycoplasma gallisepticum in the target infection site in chickens
Authors: Zhang Nan , Zhou Minghu , Yan Xiu , Liu Jinxin , Yuan Sheng , Yang Hong , Ding Huanzhong , Zhang Dexian , Bai Yinshan
Published: September 2022

Mycoplasma gallisepticum (M. gallisepticum) is a primary respiratory pathogen of poultry and causes significant economic losses to the poultry industry. There were no reported articles concerning the Pharmacokinetics/Pharmacodynamics (PK/PD) interactions of tilmicosin against M. gallisepticum in vivo. In the current study, we established an in vivo M. gallisepticum infection model and tilmicosin was administered orally to the M. gallisepticum-infected chickens by different dosage regimens. The concentration of tilmicosin in lung tissue was determined by high-pressure liquid chromatography/tandem mass spectrometry (HPLC–MS/MS), besides the counting of the viable colony of M. gallisepticum in lung tissue was also monitored dynamically to appraise the PK/PD interactions of tilmicosin against M. gallisepticum. We found that anti-mycoplasmal activity was concentration-dependent and mycoplasmacidal activity was observed at tilmicosin dosage >7.5 mg/kg. The PK/PD parameter of AUC/MIC (The area under the concentration–time curve divided by the minimal inhibitory concentration) correlated well with anti-mycoplasmal efficacy (R2 = 0.92). The ratios of AUC/MIC for 1 log10 and 3 log10 colony-forming units [CFU]/lung reductions were 300.02 and 6,950.15 h, respectively. These findings indicated that tilmicosin may be therapeutically effective in chickens to treat M. gallisepticum lung infections if administered at a dose of 9.12 mg/kg.
Analysis of the Repricing Practice of Newly Disbursed Housing Loans
Authors: Hajnal Gábor , Lados Csaba
Published: September 2022

In the Hungarian banking system, newly disbursed, fixed-rate housing loans are typically repriced with a lag of several months after a change in the interbank rates, which can be viewed as the cost of funds for institutions. This paper examines the number of months it takes for a change in the interbank rates to pass through to the interest rates of newly disbursed housing loans with an initial interest rate period of over one year. The two-step analysis looks at the repricing practices observed for Certified Consumer-Friendly Housing Loans (CCFHLs) employing a descriptive approach, and then a vector autoregressive model is used to estimate the speed at which interbank rates pass through to aggregate housing loan rates. Based on the authors’ estimate drawing on aggregate interest rate statistics, the changes in interbank rates are incorporated into the mortgage rates applied by Hungarian banks in approximately four months; however, according to the interest rate condition data of institutions’ CCFHL announcements, banks’ repricing practices vary, leading to differences in the speed and extent of the interest rate changes following a shift in the cost of funds.
Model Soups for Various Training and Validation Data
Authors: Suzuki Kaiyu , Matsuzawa Tomofumi
Published: September 2022

Model soups synthesize multiple models after fine-tuning them with different hyperparameters based on the accuracy of the validation data. They train different models on the same training and validation data sets. In this study, we maximized the model fine-tuning accuracy using the inference time and memory cost of a single model. We extended the model soups to create subsets of k training and validation data using a method similar to k-fold cross-validation and trained models on these subsets. First, we showed the correlation between the validation and test data when the models are synthesized, such that their training data contain validation data. Thereafter, we showed that synthesizing k of these models, after synthesizing models based on subsets of the same training and validation data, provides a single model with high test accuracy. This study provides a method for learning models with both high accuracy and reliability for small datasets such as medical images.
Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions
Authors: Thakur Nirmalya
Published: September 2022

The exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and diverse use cases in assisted living, military, healthcare, firefighting, and industry 4.0. The exoskeleton market is projected to increase by multiple times its current value within the next two years. Therefore, it is crucial to study the degree and trends of user interest, views, opinions, perspectives, attitudes, acceptance, feedback, engagement, buying behavior, and satisfaction, towards exoskeletons, for which the availability of Big Data of conversations about exoskeletons is necessary. The Internet of Everything style of today’s living, characterized by people spending more time on the internet than ever before, with a specific focus on social media platforms, holds the potential for the development of such a dataset by the mining of relevant social media conversations. Twitter, one such social media platform, is highly popular amongst all age groups, where the topics found in the conversation paradigms include emerging technologies such as exoskeletons. To address this research challenge, this work makes two scientific contributions to this field. First, it presents an open-access dataset of about 140,000 Tweets about exoskeletons that were posted in a 5-year period from 21 May 2017 to 21 May 2022. Second, based on a comprehensive review of the recent works in the fields of Big Data, Natural Language Processing, Information Retrieval, Data Mining, Pattern Recognition, and Artificial Intelligence that may be applied to relevant Twitter data for advancing research, innovation, and discovery in the field of exoskeleton research, a total of 100 Research Questions are presented for researchers to study, analyze, evaluate, ideate, and investigate based on this dataset.
Nasal Nitric Oxide Levels: Improving the Diagnosis of Primary Ciliary Dyskinesia in Puerto Rico
Authors: De Jesús-Rojas Wilfredo , Alvarado-Huerta Francisco , Meléndez-Montañez Jesús , Muñiz-Hernández José , Santos-López Arnaldo , Mosquera Ricardo
Published: September 2022

Primary Ciliary Dyskinesia (PCD) is a rare genetic disease characterized by motile cilia dysfunction with a prevalence of 1 in 16,309 individuals in Hispanic populations. In Puerto Rico, the prevalence of PCD is unknown. Diagnosis of PCD in Puerto Rico is challenging due to the lack of diagnostic technology. Algorithms for PCD diagnosis include clinical history, genetic testing, ciliary biopsy, and nasal Nitric Oxide (nNO) levels. For the first time, this study successfully implemented and measured the nNO levels in subjects with the RSPH4A (c.921+3_921+6del (intronic)) as a diagnostic tool to complement the current algorithm for PCD diagnosis on the island. The nNO level differentiated homozygous subjects with PCD due to the RSPH4A (c.921+3_921+6del (intronic)) founder mutation compared to healthy gender-age matched controls and subjects with VUS or negative genetic testing for PCD. The acquisition of state-of-the-art diagnostic tools such as nNO positively impacted and expanded our current PCD diagnostic capabilities in Puerto Rico for our founder genetic mutation. The addition of nNO technology promotes earlier disease screening and recognition for patients with PCD on the island. The access to nNO helped us to properly characterize the PCD diagnosis for patients with the RSPH4A (c.921+3_921+6del (intronic)). As a result, our findings will allow us to be part of the national PCD foundation registry and represent Puerto Rican Hispanics in future PCD multicentric clinical trials.
Liquid Smoke Treatment for Natural Fibers: The Effect on Tensile Properties, Surface Morphology, Crystalline Properties, and Functional Groups of Banana Stem Fibers
Authors: Muslimin Mukhlis , Rahim Mustamin , Seng Ahmad , Rais Sandi
Published: September 2022

This study aims to determine the effect of the treatment of banana stem fibers (BSF) with grade three liquid smoke on changes in the micromechanical properties of the BSF, single fiber tensile strength, morphology, crystal properties, and functional groups. This study used four variations of the specimen model, namely, fiber without treatment and immersion in liquid smoke for 1, 2, and 3 h. BSF with treatment was dried in an oven at 40 °C for 30 min. Several tests were carried out, including the tensile test for single fiber capacity of 50N standard ASTM 3379-02, Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD), and Fourier Transform Infra-Red (FTIR) observation. The results showed that the highest increase in fiber strength occurred in P2J, which was 43.78%, with crystal intensity of 34.97%, compared to TP fiber. Treatment of fiber with liquid smoke can form a strong C-C elemental bond caused by the H2O degradation process in BSF so that the carbon atom (C) becomes solid; under conditions of excessive H2O degradation, the fiber strength will become brittle, however, liquid smoke can increase the fiber tensile strength. The morphology of the fiber changed where the untreated fiber was covered in lignin, while the treated fiber had a rectangular pattern of elongated lines, was porous, and the lignin was eroded. The fiber crystallization index increased due to changes in fiber structure, where the highest peak of TP BSF occurred at point two, while the highest peaks in BSF P1J, P2J, and P3J occurred respectively at points two and three. These results prove that the innovation of BSF treatment with liquid smoke can change the morphology, crystalline, and functional aspects of BSF, so that it becomes the choice of composite reinforcement material in the future, an option that is lightweight and environmentally friendly.
Building Trauma-Informed Approaches in Higher Education
Authors: Henshaw Lisa A.
Published: September 2022

Trauma-informed approaches serve as an essential framework for human service organizations and are now being applied in education settings, including higher education institutions (HEIs). The increasing incidence of traumatic events, including the global pandemic of COVID-19 and the systemic violence against persons of color, has prompted HEIs to examine how culture and inclusivity are conceptualized in the curriculum and reflected in institutional policy and programming. Within this context, there is a need to identify how trauma-informed approaches at HEIs can be culturally responsive. This article briefly summarizes evidence supporting the rationale for trauma-informed approaches at HEIs and how culture has historically been addressed through cultural competency and cultural humility. Cultural sensitivity and responsiveness are then conceptualized from a trauma-informed lens as informed by the literature. Finally, key concepts and theory relevant to applying culturally responsive trauma-informed approaches at HEIs are defined, with recommendations for policy, research, and practice.
Disulfiram/Copper Induces Immunogenic Cell Death and Enhances CD47 Blockade in Hepatocellular Carcinoma
Authors: Gao Xingxing , Huang Hechen , Pan Caixu , Mei Zhibin , Yin Shengyong , Zhou Lin , Zheng Shusen
Published: September 2022

Some chemotherapeutic agents have been found to enhance antitumor immunity by inducing immunogenic cell death (ICD). The combination of disulfiram (DSF) and copper (Cu) has demonstrated anti-tumor effects in a range of malignancies including hepatocellular carcinoma (HCC). However, the potential of DSF/Cu as an ICD inducer and whether it can enhance the efficacy of the immune checkpoint blockade in HCC remains unknown. Here, we showed that DSF/Cu-treated HCC cells exhibited characteristics of ICD in vitro, such as calreticulin (CRT) exposure, ATP secretion, and high mobility group box 1 (HMGB1) release. DSF/Cu-treated HCC cells elicited significant immune memory in a vaccination assay. DSF/Cu treatment promoted dendritic cell activation and maturation. The combination of DSF/Cu and CD47 blockade further facilitated DC maturation and subsequently enhanced CD8+ T cell cytotoxicity. Mechanically, DSF/Cu promoted the nuclear accumulation and aggregation of nuclear protein localization protein 4 (NPL4) to inhibit the ubiquitin-proteasome system; thus, inducing endoplasmic reticulum (ER) stress. The inhibition of NPL4 induced ICD-associated damage-associated molecular patterns. Collectively, our findings demonstrated that DSF/Cu-induced ICD-mediated immune activation in HCC enhanced the efficacy of CD47 blockade.
A LETM2-Regulated PI3K-Akt Signaling Axis Reveals a Prognostic and Therapeutic Target in Pancreatic Cancer
Authors: Zhou Shurui , Zhong Ziyi , Lu Yanzong , Li Yunlong , Yao Hanming , Zhao Yue , Guo Tairan , Yang Kege , Li Yaqing , Chen Shaojie , Huang Kaihong , Lian Guoda
Published: September 2022

Pancreatic ductal adenocarcinoma (PDAC) is one of the highest mortalities malignant tumors, which is characterized by difficult diagnosis, rapid progression and high recurrence rate. Nevertheless, PDAC responds poorly to conventional therapies, which highlights the urgency to identify novel prognostic and therapeutic targets. LEMT2 was a newly discovered protein-encoding gene with little cancer research and an unclear mechanism. Thus, this study aimed to illustrate LETM2 as the crucial oncogene for tumor progression in PDAC. In this study, we analyzed the expression level and prognostic value of LETM2 in multiple cancers using pan-cancer analysis. The analyses based on the TCGA-GTEx dataset indicated that the LETM2 expression was obviously elevated in several cancers, and it was the most significantly related to the dismal prognosis of PDAC. Subsequently, we demonstrated the functional role and mechanism of LETM2 by clinical sample evaluation, and in in vitro and in vivo experiments. Immunohistochemical analyses showed that high expression of LETM2 was correlated with poor outcomes of PDAC. Moreover, we demonstrated that LETM2 knockdown significantly inhibited tumor proliferation and metastasis, and promoted cell apoptosis, while LETM2 overexpression exerted the opposite effects. Finally, the impairment caused by LETM2-knockdown could be recovered via excitation of the PI3k-Akt pathway in vitro and in vivo animal models, which suggested that LETM2 could activate the downstream PI3K-Akt pathway to participate in PDAC progression. In conclusion, the study enhanced our understanding of LETM2 as an oncogene hallmark of PDAC. LETM2 may facilitate tumor progression by activating the PI3K-Akt signaling pathway, which provides potential targets for the diagnosis, treatment, and prognosis of pancreatic cancer.
Feasibility, Method and Early Outcome of Image-Guided Volumetric Modulated Arc Radiosurgery Followed by Resection for AJCC Stage IIA–IIIB High-Risk Large Intraocular Melanoma
Authors: Guberina Maja , Sokolenko Ekaterina , Guberina Nika , Dalbah Sami , Pöttgen Christoph , Lübcke Wolfgang , Indenkämpen Frank , Lachmuth Manfred , Flühs Dirk , Chen Ying , Hoffmann Christian , Deuschl Cornelius , Jabbarli Leyla , Fiorentzis Miltiadis , Foerster Andreas , Rating Philipp , Ebenau Melanie , Grunewald Tobias , Bechrakis Nikolaos , Stuschke Martin
Published: September 2022

The main objective of this prospective observational study was the characterization of the feasibility and early outcome of image-guided (IG) volumetric modulated arc (VMAT) radiosurgery (SRS) followed by resection for patients with large intraocular melanoma. Our study included consecutive patients with unfavorable-risk melanoma, enrolled in an ophthalmic oncology center. IG-VMAT-SRS was applied by high-resolution 4D image guidance and monitoring. Current stereotactic technique parameters were evaluated for comparison. Side effects and eye function, based on a 5-point CTC assessment score, were quantified. In patients with tumors located more than 0.7–1 mm apart from the optic nerve, partial to complete volume-sparing of the optic nerve head could be achieved. In 95.5% of this subgroup, the vitality of the optic nerve and vision could be preserved by the multimodality-treatment approach (mean follow-up: 18 months (7.5–36 months)). The advanced technology of stereotactic radiotherapy demonstrated the achievability of steep dose gradients around the high-dose volume, with 4D-IG-VMAT dose application. These results enforce IG-VMAT-SRS followed by resection as one of the major therapeutic options for patients with large intraocular melanoma. The combination of 4D-IG high-precision SRS and resection provides an effective treatment for large intraocular melanoma, with few side effects, and enables an eye bulb and even vision preserving modus operandi.
Ion Channels in Endometrial Cancer
Authors: Costa Bruna Pasqualotto , Nunes Fernanda Bordignon , Noal Francini Corrêa , Branchini Gisele
Published: September 2022

Uterine or endometrial cancer (EC) is the sixth most common neoplasia among women worldwide. Cancer can originate from a myriad of causes, and increasing evidence suggests that ion channels (IC) play an important role in the process of carcinogenesis, taking part in many pathways such as self-sufficiency in growth signals, proliferation, evasion of programmed cell death (apoptosis), angiogenesis, cell differentiation, migration, adhesion, and metastasis. Hormones and growth factors are well-known to be involved in the development and/or progression of many cancers and can also regulate some ion channels and pumps. Since the endometrium is responsive and regulated by these factors, the ICs could make an important contribution to the development and progression of endometrial cancer. In this review, we explore what is beyond (ion) flow regulation by investigating the role of the main families of ICs in EC, including as possible targets for EC treatment.
Enhanced Heart Disease Prediction Based on Machine Learning and χ2 Statistical Optimal Feature Selection Model
Authors: Sarra Raniya R. , Dinar Ahmed M. , Mohammed Mazin Abed , Abdulkareem Karrar Hameed
Published: September 2022

Automatic heart disease prediction is a major global health concern. Effective cardiac treatment requires an accurate heart disease prognosis. Therefore, this paper proposes a new heart disease classification model based on the support vector machine (SVM) algorithm for improved heart disease detection. To increase prediction accuracy, the χ2 statistical optimum feature selection technique was used. The suggested model’s performance was then validated by comparing it to traditional models using several performance measures. The proposed model increased accuracy from 85.29% to 89.7%. Additionally, the componential load was reduced by half. This result indicates that our system outperformed other state-of-the-art methods in predicting heart disease.
ReFuse: Generating Imperviousness Maps from Multi-Spectral Sentinel-2 Satellite Imagery
Authors: Giacco Giovanni , Marrone Stefano , Langella Giuliano , Sansone Carlo
Published: September 2022

Continual mapping and monitoring of impervious surfaces are crucial activities to support sustainable urban management strategies and to plan effective actions for environmental changes. In this context, impervious surface coverage is increasingly becoming an essential indicator for assessing urbanization and environmental quality, with several works relying on satellite imagery to determine it. However, although satellite imagery is typically available with a frequency of 3–10 days worldwide, imperviousness maps are released at most annually as they require a huge human effort to be produced and validated. Attempts have been made to extract imperviousness maps from satellite images using machine learning, but (i) the scarcity of reliable and detailed ground truth (ii) together with the need to manage different spectral bands (iii) while making the resulting system easily accessible to the end users is limiting their diffusion. To tackle these problems, in this work we introduce a deep-learning-based approach to extract imperviousness maps from multi-spectral Sentinel-2 images leveraging a very detailed imperviousness map realised by the Italian department for environment protection as ground truth. We also propose a scalable and portable inference pipeline designed to easily scale the approach, integrating it into a web-based Geographic Information System (GIS) application. As a result, even non-expert GIS users can quickly and easily calculate impervious surfaces for any place on Earth (accuracy >95%), with a frequency limited only by the availability of new satellite images.