Miracle-dz/UniFAR-FTUs huggingface dataset:
Tumult in Higher Education: An Open Systems Perspective of Faculty Reactions to Organizational Change at Christian Universities

Abstract Christian higher education has been experiencing frequent transformational organizational change (e.g., downsizing, elimination of departments, technological innovations, addition of majors, etc.). These changes are significantly impacting faculty members. In other contexts, researchers have asserted that organizational change correlates with interpersonal conflict for employees and that such conflict is associated with counterproductive work behaviors (CWBs). If these associations are occurring for faculty members in Christian higher education, the result of CWBs as well as the consequences of conflict could result in lowered faculty engagement levels, turnover intentions, and other typical negative behaviors reflective of these variables in other contexts. Because faculty members in Christian higher education institutions are a vital link to student learning and faith integration within the curriculum, it is important for leaders to understand how change efforts might have unintended consequences that ultimately could undermine change efforts and impact the student experience. We utilized a multivariate analysis of theoretically identified variables related to CWBs, while examining faculty alignment with university values. A cross-sectional survey design assessed faculty (N = 267) perceptions of organizational change, interpersonal conflict, CWBs, and organizational identification at five Christian universities. The results indicated that organizational change was significantly correlated with interpersonal conflict and conflict was significantly correlated with CWBs. Organizational identification revealed an intervening effect on conflict and CWBs. A model applying open systems theory suggested that leaders in Christian higher education must consider the systemic effects of organizational change as they implement change initiatives.
Application of Algorithm of Hidden Markov Model and High-Order Spectrum in Fault Diagnosis of Power Electronic Circuit

This paper presents a method of applying the discrete hidden markov model and high-order spectrum to fault diagnosis of power electronic circuit.With bispectrum analysis, an ARMA model parametric bispectrum estimation is presented for Fault feature extraction firstly,and then fault modes were trained and recognized by Discrete Hidden Markov Model. Finally, electric locomotive main converter of SS8 type is used as an example to illustrate the new approach of fault diagnosis. The experimental results show that the proposed method has a high correct rate.The correct rate of the proposed method is 100%in the case of no noise or 5% noise whicn is 16.11% and 23.79% higher respectively than that of DHMM and BP neural network methods. So the method has practical value.
Computer‐Integrated Design Drawings and Construction Project Plans

Computer technology has provided the construction industry with valuable tools for managing and integrating the large volume of information generated during the design and construction phases of a project. This paper focuses on computer-integrated systems using affordable technology that can help generate construction project plans from information embedded in the design drawings. The discussion traces the evolution of microcomputer-based integration technology including a historical perspective of computer-integration restraints. Implementation of a computer-aided design (CAD) based integration system using current levels of technology is reviewed. A description of the implementation process is offered to provide direction to professionals interested in developing similar applications. Along these lines, the paper presents the basic sets of information required for an integrated system including a review of the resulting data flow between the CAD engine and the various applications. Future trends related to multiapplication systems are introduced as a basis for exploring more advanced integrated applications. Lessons learned from the integration process are conveyed along with a series of implementation recommendations.
Structural and Functional Deficits in Patients with Poststroke Dementia: A Multimodal MRI Study

Although many neuroimaging studies have reported structural and functional abnormalities in the brains of patients with cognitive impairments following stroke, little is known about the pattern of such brain reorganization in poststroke dementia (PSD). The present study was aimed at investigating alterations in spontaneous brain activity and gray matter volume (GMV) in PSD patients. We collected T1-weighted and resting-state functional magnetic resonance imaging data from 20 PSD patients, 24 poststroke nondementia (PSND) patients, and 21 well-matched normal controls (NCs). We compared the differences among the groups in GMV and the fractional amplitude of low-frequency fluctuations (fALFF). Then, we evaluated the relationship between these brain measures and cognitive assessments and explored the possible distinguisher for PSD by receiver operating characteristic (ROC) curve analysis. PSD patients showed smaller GMV in the right superior temporal gyrus and lower fALFF values in the right inferior frontal gyrus than both PSND patients and NCs, but such differences were not observed between PSND patients and NCs. Moreover, GMV in the left medial prefrontal cortex showed a significant positive correlation with the Mini-Cog assessment in PSD patients, and GMV in the left CPL displayed the highest area under the ROC curve among all the features for classifying PSD versus PSND patients. Our findings suggest that PSD patients show dementia-specific structural and functional alteration patterns, which may help elucidate the pathophysiological mechanisms underlying PSD.
Predictors of Population Awareness of Cancer Genetic Tests: Implications for Enhancing Equity in Engaging in Cancer Prevention and Precision Medicine.

Racial and ethnic disparities in genetic awareness (GA) can diminish the impact of personalized cancer treatment and risk assessment. We assessed factors predictive of GA in a diverse population-based sample to inform awareness strategies and reduce disparities in genetic testing. METHODS A cross-sectional study was conducted from July 2019 to August 2019, with the survey e-mailed to 7,575 adult residents in southeastern Pennsylvania and New Jersey. Constructs from National Cancer Institute Health Information and National Trends Survey assessed cancer attitudes or beliefs, health literacy, and numeracy. Characteristics were summarized with mean ± standard deviation for numeric variables and frequency counts and percentages for categorical variables. Comparison of factors by race or ethnicity (non-Hispanic White and non-Hispanic Black) and sex was conducted by t-tests, chi-square, or Fisher's exact tests. Multivariate logistic regression models were conducted to identify factors independently predictive of GA. RESULTS Of 1,557 respondents, data from 940 respondents (the mean age was 45 ± 16.2 years, 35.5% males, and 23% non-Hispanic Blacks) were analyzed. Factors associated with higher GA included female gender (P < .001), non-Hispanic White (P < .001), college education (P < .001), middle-higher income (P < .001), stronger belief in genetic basis of cancer (P < .001), lower cancer fatalism (P = .004), motivation for cancer information (P < .001), and higher numeracy (P = .002). On multivariate analysis, college education (odds ratio [OR] 1.79; 95% CI, 1.22 to 2.63), higher motivation for cancer information (OR 1.56; 95% CI, 1.17 to 2.09), stronger belief in genetics of cancer (OR 2.21; 95% CI, 1.48 to 3.30), and higher medical literacy (OR 2.21; 95% CI, 1.34 to 3.65) predicted greater GA. CONCLUSION This population-based study conducted in the precision medicine era identified novel modifiable factors, importantly perceptions of cancer genetics and medical literacy, as predictive of GA, which informs strategies to promote equitable engagement in genetically based cancer care.
Analysis of Pedestrian Walking Speeds at Crosswalks in Taiwan

This paper conducts a field survey with cameras at intersections to collect and analyze pedestrian walking speeds with one factor and multiple factors. Following regression analysis and factor identification, this paper also develops a prediction model for pedestrian walking speed. Results show that the mean speed of male adults is significantly higher than that of female adults in most cases. The mean walking speed of individual crossers is higher than the mean speeds of a group of two people or a group of three or more people. People walk faster on cold days, but slower on rainy days. People tend to increase their walking speed when walking across a wider street or an intersection without pedestrian control devices. In addition, regression analysis shows that the walking speed for pedestrians is significantly affected by the factors of sex, temperature, weather, number of lanes, signal type, and pedestrian phase length.
A Simple Graphene Functionalized Electrochemical Aptasensor for the Sensitive and Selective Detection of Glycated Albumin

Glycated albumin (GA) has been previously introduced as a promising biomarker for glycemic monitoring in diabetes patients with thalassemia. In this study, a label-free graphene oxide (GO)-modified aptasensor was developed for the rapid detection of GA. The fabrication of the aptasensor was dependent on the covalent interaction of the amine-functionalized GA-specific aptamer with the carboxylic groups of GO. Square wave voltammetry (SWV) analysis was carried out for the measurement of GA-aptamer binding to their specific proteins. The peak current changes before and after incubation with GA protein were directly proportional to the concentration. The developed aptasensor exhibited a broad linearity (1–10,000 µg mL−1), a low detection limit (LOD) of 0.031 µg mL−1, and high selectivity for GA detection. In addition, the aptasensor was successfully applied to detect GA in both spiked and clinical serum samples. The comparison of the developed method with a commercial assay validated the reliability of the aptasensor for clinical application. Therefore, the newly developed aptasensor is a promising tool for GA measurements in diabetic patients with underlying thalassemia.
Household dietary diversity in rural households of Oromia Regional state, Ethiopia: A cross-sectional study

Household dietary diversity (HDD) is an important nutrition outcome measuring the economic ability of a household to access a variety of foods during a determined period. This paper examines the determinants of HDD among wheat dominated rural households of Sinana District, Oromia Regional State. Multi stage sampling procedure was used to select 384 sample households. Data were collected using structured survey questionnaire, focus group discussions, and key informant interviews. Zerotruncated Poisson regression model was used to measure the determinants of HDD. The results show that almost all the respondents consumed food made from cereal and only 20.05, 10.16 and 7.29% of the household consumed egg, meat and fruits in previous seven days, respectively. On average household consumed 5.73 food groups. Further, the finding indicates that about 13.54, 50.52 and 35.94% of the participants were consumed low, medium and high dietary diversity level, respectively. Marital status, education level, participating in irrigation farming, membership of farmers cooperatives, farm size and Total Livestock Unit (TLU) positively affected HDD while distance to nearest market and remittances negatively influenced HDD. Therefore, stakeholders in the agricultural sector should promote and encourage crop diversification strategies, expand access to irrigation, introduce agricultural technologies to boost income of rural households and thus diversify their diet.
Characterization of Prestressed Concrete Cylinder Pipe by Resonance Acoustic Spectroscopy

AbstractPrestressed concrete cylinder pipe (PCCP) is a composite pipe structure commonly used for high-pressure water transmission. If these pipes deteriorate, they can cause a water main break, which can cause extensive property damage and compromise the potable water system. Accordingly, there has been considerable interest in developing reliable nondestructive evaluation (NDE) techniques capable of identifying damaged pipes prior to rupture. In the current study, a series of finite-element and experimental studies are undertaken to establish the groundwork for an acoustic resonance–based NDE method capable of characterizing the earliest stage of deterioration in PCCP associated with damage to its outermost layer.
Death-Associated Protein Kinase 1 Inhibits Progression of Thyroid Cancer by Regulating Stem Cell Markers

The activation of metastatic reprogramming is vital for cancer metastasis, but little is known about its mechanism. This study investigated the potential role of death-associated protein kinase 1 (DAPK1) in thyroid cancer progression. We generated knockdown (KD) DAPK1 using siRNA or shRNA in 8505C and KTC-1 cell lines, which we transiently or stably overexpressed in MDA-T32 and BCPAP cell lines. DAPK1 KD in 8505C and KTC-1 cells significantly increased cell proliferation and colony formation compared with controls. We observed significant inhibition of cancer cell invasion in cells overexpressing DAPK1, but the opposite effect in KD cells. Tumorsphere formation significantly increased after inhibition of DAPK1 expression in 8505C cells and was significantly suppressed in DAPK1-overexpressing MDA-T32 and BCPAP cells. DAPK1 overexpression inhibited mRNA and protein levels of stem markers (OCT4, Sox2, KLF4, and Nanog). Furthermore, the expression of these markers increased after KD of DAPK1 in 8505C cells. Mechanistic studies suggest that DAPK1 may modulate the expression of stem cell markers through the inhibition of β-catenin pathways. These findings were consistent with the public data and our thyroid tissue analysis, which showed higher DAPK1 expression was associated with advanced-stage papillary thyroid cancer with a higher stemness index and lower disease-free survival.
A control system for HVDC transmission by voltage sourced converters

A national technical project is under way in Japan to develop a high-power voltage sourced converter and its control system for the future DC interconnection between AC systems. Three developed prototype 53 MVA GTO-based converters were manufactured and went into operation. As for the control system, the voltage margin method for two terminal, and the 2-stage DC voltage control method for multi-terminal DC link were developed. Field testing is being carried out at Shin-Shinano Substation of Tokyo Electric Power Company. Satisfactory results verify the superiority of the DC link with voltage sourced converters.
Role of Photobiomodulation Therapy in Neurological Primary Burning Mouth Syndrome. A Systematic Review and Meta-Analysis of Human Randomised Controlled Clinical Trials

Mitochondrial homeostasis is crucial for energy production and neuronal survival in neurological primary burning mouth syndrome (npBMS). Photobiomodulation therapy (PBMT) has been utilised in npBMS management, however, its role of intervention remains controversial. The aim of this systematic review and meta-analysis of CRD 42020198921 PROSPERO registration reference was to oversee and determine the efficacy of PBMT in patients with npBMS, identifying the gaps and bridge them by proposing recommendations for future studies purposes. PRISMA guidelines and Cochrane Collaboration recommendations followed. Various search engines employed to analyse a total of 351 studies of which 12 were included. A wide range of utilised PBM wavelengths was between 635–980 nm and the power output ranged between 30 mW and 4000 mW. A high risk of bias (RoB) was noted in 7 out of 12 included studies (58.3%), as results of qualitative analysis. Meta-analysis findings of 4 out of 12 studies showed statistically significant intergroup differences (SSID) for visual analogue scale (VAS) values (MD = −1.47; 95% CI = −2.40 to −0.53; Z = 3.07 (p = 0.002) whereas meta-analysis on 5 out of 12 studies revealed SSID for anxiety/depression and quality of life (MD = −1.47; 95% CI = −2.40 to −0.53; Z = 3.07 (p = 0.002), favouring PBMT group to the control treatment strategies. Despite the inconsistency and diversity in PBM parameters (wavelength, power, light source, spot size, emission mode, energy per point, total energy) and treatment protocols (exposure time, number of sessions, time interval between sessions, treatment duration)—majority of the included studies showed positive PBM results. The high RoB and meta-analytical heterogeneity in the eligible studies warrant the necessity to perform well-designed and robust RCTs after acknowledging the drawbacks of the available scientific literature and addressing our suggested recommendations highlighted in our review.
Finite-Elements Simulation of Etch Front Propagation in Silicon Electropolishing Process

Electrochemical etching of silicon (anodization) in hydrofluoric acid (HF) is a flexible process that can be applied for etching 3D structures in silicon with controlled anisotropy [1]. At low applied current densities and high concentration of HF in electrolyte, porous silicon (PS) is formed. At higher current densities and low HF concentrations the etch process runs in diffusion controlled mode through oxide formation, and silicon wafer surface is electropolished. In the presented work electrochemical axisymmetrical 2D FEM model for simulation of etch front movement during the electropolishing process for the first time has been developed and verified experimentally.
Effects of Clay Mineral Composition on the Dynamic Properties and Fabric of Artificial Marine Clay

Marine clays are easily affected by different mineral composition in cyclic load-based geological hazards. Therefore, based on analyzing the mineral composition of natural marine clay, it is the key to predict the dynamic properties of natural materials under cyclic loading by using quantitated artificial marine clay. In this study, the marine clay found in the South China Sea deltas was investigated. Based on the results of geological conditions and mineral composition analyses, raw non-clay minerals (such as quartz, albite) and clay minerals (such as Na-montmorillonite and kaolinite) were used to produce artificial marine clay, the dynamic properties of which were studied from the impact of mineral composition. Dynamic triaxial laboratory testing for artificial marine clay comprising various clay minerals was performed under identical test conditions. The artificial marine clay with high montmorillonite content exhibited slower development of strain, more sluggish growth in pore water pressure, more rounded hysteresis curves, greater stiffness, and more prolonged viscous energy growth than the clay with low montmorillonite content. In addition, the flocculated fabric of the artificial marine clay with high montmorillonite content demonstrated sufficient pore space changes, more uniform pore distribution, and larger specific surface area than the dispersed fabric of the clay with low montmorillonite content. The factors arising from the influence of montmorillonite may lead to microstructural and fabric changes, hinder the development of pore water, and increase intergranular contact stiffness as well as delay the cyclic strain amplitude at the breakpoint of viscous energy dissipation. In general, the results presented in this study confirm that clay minerals, especially montmorillonite, have significant influence on the dynamic properties of large strain.
Development of Biologically Interpretable Multimodal Deep Learning Model for Cancer Prognosis Prediction

Robust cancer prognostication can enable more effective patient care and management, which may potentially improve health outcomes. Deep learning has proven to be a powerful tool to extract meaningful information from cancer patient data. In recent years it has displayed promise in quantifying prognostication by predicting patient risk. However, most current deep learning-based cancer prognosis prediction methods use only a single data source and miss out on learning from potentially rich relationships across modalities. Existing multimodal approaches are challenging to interpret in a biological or medical context, limiting real-world clinical integration as a trustworthy prognostic decision aid. Here, we developed a multimodal modeling approach that can integrate information from the central modalities of gene expression, DNA methylation, and histopathological imaging with clinical information for cancer prognosis prediction. Our multimodal modeling approach combines pathway and gene-based sparsely coded layers with patch-based graph convolutional networks to facilitate biological interpretation of the model results. We present a preliminary analysis that compares the potential applicability of combining all modalities to uni- or bi-modal approaches. Leveraging data from four cancer subtypes from the Cancer Genome Atlas, results demonstrate the encouraging performance of our multimodal approach (C-index=0.660 without clinical features; C-index=0.665 with clinical features) across four cancer subtypes versus unimodal approaches and existing state-of-the-art approaches. This work brings insight to the development of interpretable multimodal methods of applying AI to biomedical data and can potentially serve as a foundation for clinical implementations of such software. We plan to follow up this preliminary analysis with an in-depth exploration of factors to improve multimodal modeling approaches on an in-house dataset.
Investigating the Effectiveness and Acceptability of Oral Health and Related Health Behaviour Interventions in Adults with Severe and Multiple Disadvantage: Protocol for a Mixed-Methods Systematic Review

Increasing numbers of people in England experience homelessness, substance use, and repeated offending (known as ‘severe and multiple disadvantage’; SMD). Populations experiencing SMD often have extremely poor oral health, which is closely inter-linked with high levels of substance use, smoking, and poor diet. This study aims to undertake an evidence synthesis to identify the effectiveness, resource requirements, and factors influencing the implementation and acceptability of oral health and related health behaviour interventions in adults experiencing SMD. Two systematic reviews will be conducted using mixed-methods. Review 1 will investigate the effectiveness and resource implications of oral health and related health behaviours (substance use, smoking, diet) interventions; Review 2 will investigate factors influencing the implementation of such interventions. The population includes adults (≥18 years) experiencing SMD. Standard review methods in terms of searches, screening, data extraction, and quality appraisal will be conducted. Narrative syntheses will be conducted. If feasible, a meta-analysis will be conducted for Review 1 and a thematic synthesis for Review 2. Evidence from the two reviews will then be synthesised together. Input from people with experience of SMD will be sought throughout to inform the reviews. An initial logic model will be iteratively refined during the review.