Miracle-dz/UniFAR-FTUs huggingface dataset:
Format Readability Enhancing In Basic Mathematical Operations

Individuated font selection, which can increase text reading speed, may be able to increase mathematical expression reading speed and influence reasoning accuracy. To investigate whether the same font that increases a participant’s reading speed enhances mathematical reading, we compared their speed in evaluating mathematical expressions as true or false presented in their fastest reading font as determined by empirical test and with a control font, Times Roman. Participants were faster in completing mathematical problems when using typography selected for individual readability, but no difference occurred in task accuracy, matching patterns previously seen in interlude reading. Future research should assess the impact of elements of time pressure, math complexity, numeric versus text-based questions, and associated math anxiety.
INTER- AND INTRA-FAMILY DIFFERENCES IN GENERATIONAL PROXIMITY IN THE UNITED STATES AND JAPAN

The United States and Japan show a significant difference in their patterns of genera tional proximity. In 1993, half of U.S. non-Hispanic white parents aged 70 or over lived separately but within 10 miles of their nearest children and a majority of them lived far from their non-nearest children. The family geographic network for Japanese elderly parents is more hierarchical. In 1989, 74 percent of Japanese parents aged 70 and over lived with their nearest children but most of them lived far from their nonnearest children. To explain this distinctive pattern of interand intra-family generational proximities in these two societies, I employ a multi-level analysis which compares the net effects of life course conditions of elderly parents and their children, and economic and ecological characteristics of elderly parents’ places of residence on generational proximities. For this multi-level analysis, I use the 1993 Asset and Heath Dynamics among the Oldest Old in the U.S. and the 1989 Second Demographic Survey on Changes in Family Life Course and Household Structures in Japan and the aggregate level data for economic and ecological statistics of U.S. states and Japanese prefectures. This multilevel analysis also accounts for intra-family differences in parent-child proximities employing a within-family variance model.
The association between adverse childhood experiences and self-harm among South Korean children and adolescents: a cross-sectional study

Purpose Adolescent self-harm is a public health problem. Research suggests a link between adverse childhood experiences (ACEs) and self-destructive behaviors. Few studies, however, have examined the effects of ACEs on self-harm among Asian adolescents. This study explored the association between lifetime ACEs and a history of self-harm among Korean children and adolescents in elementary, middle, and high schools. Methods A cross-sectional, retrospective medical record review was conducted on a dataset of a national psychiatrist advisory service for school counselors who participated in the Wee Doctor Service from January 1 to December 31, 2020. The data were analyzed using multiple logistic regression to predict self-harm. Results Student cases (n=171) were referred to psychiatrists by school counselors for remote consultation. Multiple logistic regression analyses revealed that the odds of self-harm were higher among high school students (adjusted odds ratio [aOR]=4.97; 95% confidence interval [CI]=1.94-12.76), those with two or more ACEs (aOR=3.27; 95% CI=1.43-7.47), and those with depression (aOR=3.06; 95% CI=1.32-7.10). Conclusion The study's findings provide compelling evidence that exposure to ACEs can increase vulnerability to self-harm among Korean students. Students with a history of ACEs and depression, as well as high school students, require increased attention during counseling. School counselors can benefit from incorporating screening assessment tools that include questions related to ACEs and depression. Establishing a systematic referral system to connect students with experts can enhance the likelihood of identifying self-harm tendencies and offering the essential support to prevent self-harm.
Three-dimensional adaptive higher order finite element simulation for geo-electromagnetics—a marine CSEM example

SUMMARY We present a new 3-D vector finite element code and demonstrate its strength by modelling a realistic marine CSEM scenario. Unstructured tetrahedral meshes easily allow for the inclusion of arbitrary seafloor bathymetry so that natural environments are mapped into the model in a close-to-reality way. A primary/secondary field approach, an adaptive mesh refinement strategy as well as a higher order polynomial finite element approximation improve the solution accuracy. A convergence study strongly indicates that the use of higher order finite elements is beneficial even if the solution is not globally smooth. The marine CSEM scenario also shows that seafloor topography gives an important response which needs to be reproduced by numerical modelling to avoid the misinterpretation of measurements.
A Cloud Detection Method for Vertically Pointing Millimeter-Wavelength Cloud Radar

A new method using three dimensions of cloud continuity, including range dimension, Doppler dimension, and time dimension, is proposed to discriminate cloud from noise and detect more weak cloud signals in vertically pointing millimeter-wave cloud radar observations by fully utilizing the spatiotemporal continuum of clouds. A modified noise level estimation method based on the Hildebrand and Sekhon algorithm is used for more accurate noise level estimation, which is critical for weak signals. The detection method consists of three steps. The first two steps are performed at the Doppler power spectrum stage, while the third step is performed at the base data stage. In the first step, a new adaptive spatial filter combined with the Kuwaraha filter and the Gaussian filter, using the ratio of mean to standard deviation as the adaptive parameter, is applied to initially mask the potential cloud signals to improve the detection performance at the boundary of cloud and noise. Simulations of boundary cases were performed to compare our adaptive filter and normal Gaussian filters. Box filters are used in steps two and three to remove the remaining noise. We applied our method to cloud radar observations with TJ-II cloud radar at the Nanjing University of Information Science & Technology. The results showed that our method can detect more weak cloud signals than the usual methods, which are performed only at the Doppler power spectrum stage or the base data stage.
Analytical Studies on Approximate Lag and Anticipating Synchronization in Two Unidirectionally Coupled Hyperchaotic Chen Systems without Time Delay

In this paper, approximate lag synchronization (LS) and anticipating synchronization (AS) between two unidirectionally coupled hyperchaotic Chen systems without time-delay coupling are analytically investigated. Firstly, the synchronization condition for exact LS in two unidirectionally coupled hyperchaotic Chen systems with time delay in signal transmission is analytically obtained. Under such conditions, approximate LS and AS are discussed by replacing the true time-delay terms with their Taylor expansions up to the third order.Differently from other research studies, the condition for exact LS is derived by regarding LS as a special type of generalized synchronization (GS), which has nothing to do with the value of the time delay. It is convenient to individually change the value of the lag and anticipation time of approximate LS and AS without considering the synchronization condition. Our study shows the power of a new method for recreating the past signals or predicting the future signals of a hyperchaotic Chen system by using its current signals. The results provide a simple way to eliminate the negative effects of time delay in the signal transmission between two hyperchaotic systems.
Employee Participation, Digital Sophistication and Innovation Performance

The results of the Finnish MEADOW survey of 2021–2022, comprising responses of management from 1,106 companies, show that nearly half of Finnish companies employing ten or more people had produced a new or significantly improved product or service during the last two years. Of these companies, almost half had produced products or services new also to the market. Both the level of digital sophistication and the extent of employee participation in development are positively associated with the company’s innovation performance after all other factors in the multinominal regression analysis are controlled. The odds ratios in the regression models are higher for innovations new to the market than innovations new only for the company. Broad employee participation shows the highest odds ratios of all variables included in the regression models for both types of innovation. As also companies’ cooperation networks and customer involvement can play a role in innovations, we analysed the combined effect of the above four factors on innovation. A clear positive combined effect for both innovations new to the market and new only for the company was detected, suggesting that it is difficult for companies to build innovation superiority based on technological ability alone – or any other single factor – and that broad employee participation in development is an essential part of the portrait of an innovative company also in the digital age.
Analysis and Comparison of Proteomics of Placental Proteins from Cows Using Different Proteases

Simple Summary As an organ of fetal development, the placenta has many biological functions such as anti-oxidation, anti-tumor, anti-apoptosis, immune regulation, and skin care. It was found that the protein content, trace elements, and amino acid types of bovine placenta were similar to those of human placenta—which has been widely studied, developed, and utilized—and at the same time, the waste of resources caused by the random disposal of placenta was avoided. In this study, we explored and compared the proteome of different proteases following their action on cow placenta based on marker-free mass spectrometry and performed a bioinformatics analysis, which provided valuable reference information for the subsequent proteomic analysis of pregnancy-related diseases in cows, the study of the physiological functions of cow placenta, and the development and utilization of its by-products. Abstract Newly found biochemical characteristics of the placenta can provide new insights for further studies on the possible markers of physiological/pathological pregnancy or the function of the placenta. We compared the proteome of the dairy cow placenta after enzymatic hydrolysis by three different proteases using a label-free mass spectrometry approach. In total, 541, 136, and 86 proteins were identified in the trypsin group (TRY), pepsin group (PEP), and papain group (PAP). By comparing the proteome of the PAP and TRY, PEP and TRY, and PEP and PAP groups, 432, 421, and 136 differentially expressed proteins were identified, respectively. We compared the up-regulated DEPs and down-regulated DEPs of each comparison group. The results show that the proteins identified by papain were mostly derived from the extracellular matrix and collagen, and were enriched in the relaxin signaling pathway and AGE-RAGE signaling pathway in diabetic complications; pepsin digestion was able to identify more muscle-related proteins, which were enriched in the lysosome, platelet activation, cardiac muscle contraction, the bacterial invasion of epithelial cells, and small cell lung cancer; trypsin mainly enzymatically degraded the extracellular matrix, blood particles, and cell-surface proteins that were enriched in arginine and proline metabolism, olfactory transduction proteasome, protein processing in the endoplasmic reticulum, pyruvate metabolism, and arrhythmogenic right ventricular cardiomyopathy (ARVC). In summary, these results provide insights into the discovery of the physiological functions of dairy cow placenta and the selection of proteases in dairy cow placenta proteomics.
Optimal Duration of In-Vehicle Data Recorder Monitoring to Assess Bus Driver Behavior

This study examined the optimal sampling durations for in-vehicle data recorder (IVDR) data analysis, focusing on professional bus drivers. Vision-based technology (VBT) from Mobileye Inc. is an emerging technology for monitoring driver behavior and enhancing safety in advanced driver assistance systems (ADASs) and autonomous driving. VBT detects hazardous driving events by assessing distances to vehicles. This naturalistic study of 77 male bus drivers aimed to determine the optimal duration for monitoring professional bus driving patterns and the stabilization point in risky driving events over time using VBT and G-sensor-equipped buses. Of the initial cohort, 61 drivers’ VBT data and 66 drivers’ G-sensor data were suitable for analysis. Findings indicated that achieving a stable driving pattern required approximately 130 h of VBT data and 170 h of G-sensor data with an expected 10% error rate. Deviating downward from these durations led to higher error rates or unreliable data. The study found that VBT and G-sensor data are both valuable tools for driving assessment. Moreover, it underscored the effective application of VBT technology in driving behavior analysis as a way of assessing interventions and refining autonomous vehicle algorithms. These results provide practical recommendations for IVDR researchers, stressing the importance of adequate monitoring durations for reliable and accurate outcomes.
The Second Conference on the Lunar Highlands Crust and New Directions. Spinel-rich lithologies in the lunar highland crust: Linking lunar samples with crystallization experiments and remote sensing

Abstract Mg-Al spinel is rare in lunar rocks (Apollo and meteorite collections), and occurs mostly in troctolites and troctolitic cataclastites. Recently, a new lunar lithology, rich in spinel and plagioclase, and lacking abundant olivine and pyroxene, was recognized in visible to near-infrared (VNIR) reflectance spectra by the Moon Mineralogy Mapper (M3) instrument on the Chandrayaan-1 spacecraft at the Moscoviense basin. These outcrop-scale areas are inferred to contain 20-30% Mg-Al spinel. Possible explanations for the petrogenesis of spinel-bearing and spinel-rich lithology(s) range from low-pressure near-surface crystallization to a deep-seated origin in the lower lunar crust or upper mantle. Here, we describe 1-bar crystallization experiments conducted on rock compositions rich in olivine and plagioclase that crystallize spinel. This would be equivalent to impact-melting, which is moderately common among lunar plutonic rocks and granulites. To explore possible precursor materials and the maximum amount of spinel that could be crystallized, a lunar troctolitic composition similar to Apollo pink spinel troctolite 65785, and a composition similar to ALHA81005 as analog to the source region of this meteorite have been chosen. The crystallization experiments on the composition of AHLA 81005 did not yield any spinel; experiments on the composition similar to Apollo 65785 crystallized a maximum of ~8 wt% spinel, much less than the suggested 20-30% spinel of the new lithology detected by M3. However, our VNIR spectral reflectance analyses of the experimental run products indicate that the spinel composition of the experimental run products not only appears to be similar to the composition of the spinel lithology detected by M3 (characteristics of the spinel absorption), but also that the modal abundances of coexisting phases (e.g., mafic glass) influence the spectral reflectance properties. Thus, the spinel-rich deposits detected by M3 might not be as spinel-rich as previously thought and could contain as little as 4-5 wt% spinel. However, the effect of space weathering on spinel is unknown and could significantly weaken its 2 μm absorptions. If this occurs, weathered lunar rocks could contain more spinel than a comparison with our unweathered experimental charges would suggest.
Climate change impacts on runoff in West Africa: a review

This review summarizes the impacts of climate change on runoff in West Africa, assesses the uncertainty in the projections and describes future research needs for the region. To do so, we constitute a meta-database made of 19 studies and 301 future runoff change values. The future tendency in streamflow developments is overall very uncertain (median of the 301 points is 0% and mean +5.2%), except for (i) the Gambia River, which exhibits a significant negative change (median = −4.5%), and (ii) the Sassandra and the Niger rivers, where the change is positive (+14.4% and +6.1%). A correlation analysis revealed that runoff changes are tightly linked to changes in rainfall ( R = 0.49), and to a smaller extent also to changes in potential evapotranspiration. Other parameters than climate – such as the carbon effect on plant water efficiency, land use dynamics or water withdrawals – could also significantly impact on runoff, but they generally do not offset the effects of climate change. In view of the potential changes, the large uncertainty therein and the high vulnerability of the region to such changes, there is an urgent need for integrated studies that quantify the potential effects of these processes on water resources in West Africa and for more accuracy in climate models rainfall projections. We especially underline the lack of information concerning projections of future floods and droughts, and of interannual fluctuations in streamflow.
Enhancement of state-owned enterprises’ financial reporting through e-governance

State-owned enterprises in Zimbabwe often take long to report their financial statements due to unfunded policy mandates, weak governance, and a lack of capacity of governments to oversee the enterprises/parastatals. Information systems can help improve the operation of state enterprises and expedite financial reporting by interfacing e-governance and corporate governance. This paper aims to present a systematic empirical literature review to examine the role of corporate governance in the timeliness of financial reporting and opportunities of e-Corporate Governance in State-owned enterprises. Specifically, the proposed study’s motivation aroused from vast literature focusing on the role of corporate governance in the timeliness of financial reporting and opportunities of e-Corporate Governance in State-owned enterprises. The study reviewed some of the articles for literature that deliver robust suggestions on the timeliness of financial reporting and opportunities of e-Corporate Governance in State-owned enterprises. Findings suggest that effective corporate governance can improve the performance and accountability of state enterprises. E-corporate governance can help state enterprises report their financial statements promptly. Adoption of e-governance can improve corporate governance in state enterprises by providing best practices and independent oversight mechanisms.
A Prediction of South African Public Twitter Opinion using a Hybrid Sentiment Analysis Approach

—Sentiment analysis, a subfield of Natural Language Processing, has garnered a great deal of attention within the research community. To date, numerous sentiment analysis approaches have been adopted and developed by researchers to suit a variety of application scenarios. This consistent adaptation has allowed for the optimal extraction of the authors emotional intent within text. A contributing factor to the growth in application scenarios is the mass adoption of social media platforms and the bondless topics of discussion they hold. For government, organizations and other miscellaneous parties, these opinions hold vital insight into public mindset, welfare, and intent. Successful utilization of these insights could lead to better methods of addressing said public, and in turn, could improve the overall state of public well-being. In this study, a framework using a hybrid sentiment analysis approach was developed. Various amalgamations were created – consisting of a simplified version of the Valence Aware Dictionary and sEntiment Reasoner (VADER) lexicon and multiple instances of classical machine learning algorithms. In this study, a total of 67,585 public opinion-oriented Tweets created in 2020 applicable to the South African (ZA) domain were analyzed. The developed hybrid sentiment analysis approaches were compared against one another using well known performance metrics. The results concluded that the hybrid approach of the simplified VADER lexicon and the Medium Gaussian Support Vector Machine (MGSVM) algorithm outperformed the other seven hybrid algorithms. The Twitter dataset utilized serves to demonstrate model capability, specifically within the ZA context.
Ribosomal protein L8 regulates the expression and splicing pattern of genes associated with cancer-related pathways

Background/aim Ribosomal proteins have been shown to perform unique extraribosomal functions in cell apoptosis and other biological processes. Ribosomal protein L8 (RPL8) not only has important nonribosomal regulatory functions but also participates in the oncogenesis and development of tumors. However, the specific biological functions and pathways involved in this process are still unknown. Materials and methods RPL8 was overexpressed (RPL8-OE) in HeLa cells. MTT assay and flow cytometry were used to detect cell proliferation and apoptosis, respectively. Transcriptome sequencing was performed to analyze the differentially expressed genes (DEGs) and regulated alternative splicing events (RASEs) by RPL8-OE, both of which were validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay. Results RPL8-OE inhibited cell proliferation and promoted cell apoptosis. RPL8 regulated the differential expression of many oncogenic genes and the occurrence of RASEs. Many DEGs and RASE genes (RASGs) were enriched in tumorigenesis and tumor progression-related pathways, including angiogenesis, inflammation, and regulation of cell proliferation. RPL8 could regulate the RASGs enriched in the negative regulation of apoptosis, consistent with its proapoptosis function. Furthermore, RPL8 may influence cancer-related DEGs by modulating the alternative splicing of transcription factors. Conclusion RPL8 might affect the phenotypes of cancer cells by altering the transcriptome profiles, including gene expression and splicing, which provides novel insights into the biological functions of RPL8 in tumor development.
Prevalence and Phenotypic Diversity of PCOS in Indian Women: An Observational Study

: Aim and objectives: This prospective observational study aimed to investigate the prevalence and phenotypic variations of Polycystic Ovary Syndrome PCOS among Indian women aged 15-35 years, utilizing Rotterdams criteria from 2003 and to study the association between different phenotypes of PCOS and obesity. Methodology: A total of 671 women presenting with irregular menses, clinical hyperandrogenism, or polycystic ovarian morphology were evaluated with help of clinical, biochemical and radiological modality over six months. The study identified four standard PCOS phenotypes A, B, C, D and examined their associations with age, BMI, hirsutism, acne, menstrual irregularities, infertility, and various metabolic and endocrine characteristics. Results: The prevalence of PCOS was highest for phenotype A(HPO;52.57), followed by phenotype D(OP;20.97), phenotype C (HP;15.07), and phenotype B(HO;11.39). PCOS phenotypes exhibited significantly altered endocrine and metabolic profiles compared to controls, with hyperandrogenic phenotypes showing the highest risk for future metabolic disorders. Conclusion: This study underscores the need for vigilant monitoring of women with hyperandrogenic PCOS phenotypes.