Miracle-dz/UniFAR-FTUs huggingface dataset:
Equivalent steady soil moisture profile and the time compression approximation in water balance modeling

The definition of preevent soil moisture profile and time compression analysis are critical components in water balance models that are based on realistic infiltration/exfiltration relations and include profile redistribution of vadose zone moisture. In this paper, detailed analysis of these two fundamental components of water balance modeling is presented. Numerical integration of the governing equations for liquid moisture flow in the unsaturated zone is used in simulations designed to illustrate the role of temporal variability in the system. The simulations consist of forcing the surface of a one-dimensional soil column, bounded at its base by a fixed water table, with the output of a stochastic event-based model of precipitation and potential evaporation. The simulations are run until (and beyond when) an equilibrium condition is reached between the long-term mean values of surface and bottom fluxes. For situations with a deep water table, two distinct zones develop: a near-surface, highly unsteady zone, and a deeper, quasi-steady zone. The equivalent steady moisture profile, i.e., the steady profile corresponding to the mean of the simulated column flow, is found to reasonably approximate the temporal mean, mean prestorm, and mean poststorm moisture profiles, particularly in the deeper zone. In the upper zone the equivalent steady profile forms a biased estimate of the temporal mean. The bias is shown, through perturbation analysis, to lead to overestimation of the wetness of the mean moisture profile. For shallow water tables the distinction between the two zones collapses. In this case both the equivalent steady profile and the mean profile are close to the hydrostatic profile. The simulations are also used to test the utility of the time compression approximation (TCA) in modeling surface fluxes under temporally variable initial conditions. We demonstrate that the use of the mean prestorm and poststorm event moisture profiles as initial conditions for the infiltration and exfiltration flux capacities does not produce major bias in TCA-predicted surface fluxes. In this sense the TCA behaves as a linear operator. Furthermore, we demonstrate that the estimation of these mean initial condition profiles by the equivalent steady state soil moisture profile is an adequate approximation for determining mean land surface response to event-based atmospheric forcing.
Exploring Local Labor Markets and Knowledge Spillover from a Spatial Perspective

Relevance. Cities serve as vital hubs for socioeconomic activities, fostering convergence in local labor markets characterized by high productivity, premium wages, and knowledge spillover. Jakarta Metropolitan, as Indonesia's economic center, embodies these advantages, prompting the need for a spatial investigation of their regional association. Research Objective. This study examines the unique attributes of the labor market in the Jakarta Metropolitan Area. The analysis encompasses anomalies such as the impact of premium wages on local labor productivity and the influence of education levels, as a proxy for knowledge spillover, on urban labor productivity. Data and Methods. Utilizing microdata from Sakernas and macrodata from BPS for 2017-2019, this study offers a comprehensive analysis of the Jakarta Metropolitan Area. By synthesizing cross-level data, the intricate interplay between productivity, wages, and area size becomes evident, particularly the tendency for skilled individuals to gravitate toward larger urban centers. Employing spatial regression, the analysis takes into account local characteristics in regions. Results. Density and education have a positive correlation, while the number of holders of bachelor's degrees has a surprisingly negative impact on productivity. Notably, higher aggregate education levels enhance regional productivity throughout the Jakarta Metropolitan Area, except for highly educated individuals. The level of education influences the minimum wage in a region, driven by spatial disparities in the educational infrastructure and quality. The number of educated people also influences wages in and across regions, prompting migration to regions with higher salaries. Conclusions. By integrating microdata and macrodata and employing spatial regression techniques, this study shows the connection between education, productivity, and regional dynamics, particularly in the Jakarta Metropolitan Area. These findings challenge the assumption that possessing a high level of education guarantees higher productivity and remuneration, demonstrating the need for education reforms that align with labor market demands and bolster the economy.
GEOMORPHOLOGICAL HAZARDS IN SLOVAKIA

The article is focused on an assessment of spatial distribution and mutual relations of the most marked geomorphological hazards in Slovakia. There are defined areas threatened by partial hazards, namely by earthquakes, landslides and related phenomena, karst and mining subsidence and collapsing, snow avalanches, water and wind erosion as well as both regional and local floods. Consequently, the spatial structure of combinations of extreme values of various hazard types from the viewpoint of their possible synergetic operation and multiplication effect is analysed. Finally the authors present synthetic characteristics of hazards and delimit basic hazardous regions. Typifying the Slovak area from the viewpoint of various types of geomorphological hazards represents the result, which is utilisable in the process of landscape planning at a regional level.
Design of Leachate Treatment Project in Chengdu Solid Waste Landfill Site

The leachate treatment project in Chengdu Solid Waste Landfill Site is the first newly constructed large-scale leachate treatment project according to the Standard for Pollution Control on the Landfill Site of Municipal Solid Waste(GB 16889-2008). It adopts MBR/RO/NF process.Since being put into operation on December 31,2008,the leachate treatment project has operated for more than one year,and the effluent quality is excellent.
The Relation between Cognitive and Emotional Processes in Children and Adolescents with Neurodevelopmental Disorders—A Meta-Analysis

Background: Up to 80% of children with autism spectrum disorders (ASDs) have mental health issues—either emotional or behavioral problems. The underlying mechanisms are still unknown, even if emotional regulation (ER) is considered to play a major role in child and adolescent psychopathology. Several studies link the ability to regulate the intensity and quality of emotions with executive functioning. Therefore, we aimed to investigate the association between executive functions (EFs) and ER and affective problems in children with ASD. Methods: This meta-analysis is based on a literature search of peer-reviewed journals from the following databases: Scopus, ProQuest, Ebsco, Science Direct, Springer Link and Clarivate. We analyzed 15 studies that investigated the link between EF, ER or affective problems (APs) in children and adolescents with ASD aged between 2 and 18 y with ASD. To assess the effect size of the relationship between EF and ER, and EF and AP, 15 studies comprising 54 effect sizes were analyzed. Results: Our findings revealed a small effect size regarding the association between EF and ER, r = 0.331, p = 0.034, and a small effect size regarding the association between EF and AP, r = −0.213, p = 0.024. No significant moderators were found. The results are presented in regard to the two analyses developed, as well as a short review of the studies included in the meta-analysis. Conclusion: Even if there are several limitations of this study, especially considering the small number of studies included, the results suggest that it is worth considering EF as an underlying mechanism for the appearance of emotional or behavioral problems in children with ASD. These findings have important implications for the development of ASD intervention plans, as well as for increasing awareness among specialists about the importance of executive functions in school adjustment and social functioning.
Investment Opportunity, Institutional Ownership, and Excess Cash Holdings with Financial Constraint as Moderation

This study examines the effect of investment opportunity and institutional ownership on excess cash holdings with financial constraint as the moderating variable. Holding more cash is often rated as a negative signal for shareholders, because of the probability to use the cash inappropriately and increase the agency cost. Another side, excess cash can give a good impact on the company when is more expensive to access the external financing, or the situation make the firm had financial constraints. This study uses excess cash holdings as a dependent variable with few references and a high chance for further research. Generalized least square (GLS) is employed to analyze the hypothesis with observations during 2015-2020 in listed companies on Indonesia Stock Exchange (IDX). The result of this research shows that investment opportunity has a positive influence on excess cash holdings. If there is a financial constraint, it will decrease the effect of Investment opportunity to the level of excess cash holdings. This study was unable to capture the impact of institutional ownership on excess cash holdings in constraint nor unconstraint firms. The study was robust enough when the proxy of excess cash changed and when using the lag variable to confirm the primary result.
SATISFACTION TOWARD LEARNING MANAGEMENT SYSTEM: EXTENDED SCALE OF EDUCATIONAL SYSTEM QUALITY

Introduction: Consideration against educational system quality in the context of the learning management system has increased during the pandemic period. An inconsistent finding concerning the influence of educational system quality on satisfaction has been identified. To fill this gap in the existing literature, this study aims to extend the educational system quality scale and examine its influence on students’ satisfaction. Methods: Based on an intensive literature review step, device flexibility was proposed as an extended indicator. To validate and examine the proposed hypothesis, this study employed the quantitative method of PLS-SEM. Data were collected from 90 students who actively used learning management systems. Results: Our findings showed that device flexibility is valid and reliable as an educational system quality indicator. Besides, our proposed hypothesis is also confirmed. Through the structural model assessment, the influence of educational system quality on students’ satisfaction is found to be significant. Conclusion and suggestion: Device flexibility has been proven as an educational system quality indicator. In order to maintain students’ satisfaction, system developers are suggested to keep improving learning management system applications, primarily on smartphone devices.
Patient Adherence to Oral Anticancer Agents: A Mapping Review of Supportive Interventions

The development and use of oral anticancer agents (OAAs) continue to grow, and supporting individuals on OAAs is now a priority as they find themselves taking these drugs at home with little professional guidance. This mapping review provides an overview of the current evidence concerning OAA-supportive adherence interventions, identifying potential gaps, and making recommendations to guide future work. Four large databases and the grey literature were searched for publications from 2010 to 2022. Quantitative, qualitative, mixed-method, theses/dissertations, reports, and abstracts were included, whereas protocols and reviews were excluded. Duplicates were removed, and the remaining publications were screened by title and abstract. Full-text publications were assessed and those meeting the inclusion criteria were retained. Data extracted included the year of publication, theoretical underpinnings, study design, targeted patients, sample size, intervention type, and primary outcome(s). 3175 publications were screened, with 435 fully read. Of these, 314 were excluded with 120 retained. Of the 120 publications, 39.2% (n = 47) were observational studies, 38.3% (n = 46) were quasi-experimental, and 16.7% (n = 20) were experimental. Only 17.5% (n = 21) were theory-based. Despite the known efficacy of multi-modal interventions, 63.7% (n = 76) contained one or two modalities, 33.3% (n = 40) included 3, and 3.3% (n = 4) contained four types of modalities. Medication adherence was measured primarily through self-report (n = 31) or chart review/pharmacy refills (n = 28). Given the importance of patient tailored interventions, future work should test whether having four intervention modalities (behavioral, educational, medical, and technological) guided by theory can optimize OAA-related outcomes.
Competing Risks of Coronary Heart Disease Mortality versus Other Causes of Death in 10 Cohorts of Middle-Aged Men of the Seven Countries Study Followed for 60 Years to Extinction

Objectives: To assess whether competing risks help explain why regions with initially high serum cholesterol have higher mortality from coronary heart disease (CHD) and lower mortality from stroke and other major heart diseases, while the reverse is found for those with initially lower serum cholesterol. Material and Methods. Ten cohorts of men (N = 9063) initially aged 40–59 in six countries were examined and followed for fatal outcomes for 60 years. Major cardiovascular disease (CVD) groups were CHD, stroke, and other Heart Diseases of Uncertain Etiology (HDUE), or the combination of stroke and HDUE (STHD), along with all other causes of death. Fine-Gray competing risk analysis was applied with CHD versus all other causes of death or STHD (direct mode) and all other causes of death or STHD versus CHD (inverse mode), and the effects of 19 covariates (of which 3 references) on the cause-specific hazard of the outcomes were assessed, thus investigating potential etiologic roles. A systematic comparison with results obtained by running the Cox model in direct and inverse modes with the same end-point results was also performed and illustrated graphically. Results. CHD mortality is bound to different risk factor relationships when compared with all other causes of death and with STHD. The role of serum cholesterol is crucial since, in both comparisons, by Fine-Gray, its coefficients are positive and significant for CHD and negative and significant for all other causes of death and STHD. Risk factor capabilities in specific outcome types of the CVD domain (CHD versus STHD) are different depending on the outcome types considered. Risk factor coefficients are smaller in Fine-Gray modelling and larger in the Cox model. Fine-Gray detects different risk factors whose coefficients may have opposite algebraic signs. Conclusions. This is the first report whereby a large group of risk factors are investigated in connection with life-long CVD outcomes by Fine-Gray competing risk analysis, and a systematic comparison is performed with results obtained by Cox models in both direct and inverse modes. Subtypes of CVD mortality should be summed with full awareness that some risk factors vary by pathology, and they should at least be disentangled into CHD and STHD.
Neural Radiance Fields-Based 3D Reconstruction of Power Transmission Lines Using Progressive Motion Sequence Images

To address the fuzzy reconstruction effect on distant objects in unbounded scenes and the difficulty in feature matching caused by the thin structure of power lines in images, this paper proposes a novel image-based method for the reconstruction of power transmission lines (PTLs). The dataset used in this paper comprises PTL progressive motion sequence datasets, constructed by a visual acquisition system carried by a developed Flying–walking Power Line Inspection Robot (FPLIR). This system captures close-distance and continuous images of power lines. The study introduces PL-NeRF, that is, an enhanced method based on the Neural Radiance Fields (NeRF) method for reconstructing PTLs. The highlights of PL-NeRF include (1) compressing the unbounded scene of PTLs by exploiting the spatial compression of normal L∞; (2) encoding the direction and position of the sample points through Integrated Position Encoding (IPE) and Hash Encoding (HE), respectively. Compared to existing methods, the proposed method demonstrates good performance in 3D reconstruction, with fidelity indicators of PSNR = 29, SSIM = 0.871, and LPIPS = 0.087. Experimental results highlight that the combination of PL-NeRF with progressive motion sequence images ensures the integrity and continuity of PTLs, improving the efficiency and accuracy of image-based reconstructions. In the future, this method could be widely applied for efficient and accurate 3D reconstruction and inspection of PTLs, providing a strong foundation for automated monitoring of transmission corridors and digital power engineering.
Preliminary Correction of Vaisala Radiosonde Humidity Measurements for Slow Sensor Time-Response at Cold Temperatures

The goal of this study is to improve the accuracy of relative humidity (RH) measurements from Vaisala radiosondes, especially in the upper troposphere (UT), by correcting measurement error that results from slow time-response of the RH sensor at cold temperatures. Accurate water vapor profiles are important for such applications as input to radiative transfer algorithms, calibration, or evaluation of remote-sensor water vapor retrievals, initializing numerical models, and improving parameterizations of cloud processes. Inaccurate measurement of water vapor profiles has been shown by Atmospheric Radiation Measurement (ARM) Program studies to be the primary limitation to improving clear-sky radiative transfer models (e.g., Clough et al. 1999). Although water vapor concentrations are much less in the UT than at lower levels, atmospheric cooling rates in the UT due to water vapor exceed those in the mid troposphere due to the very strong contribution by the wave number range 250 cm to 350 cm (Clough et al. 1992). RH measurements from Vaisala RS80-H radiosondes are heavily relied upon by ARM to characterize the water vapor profile in the UT, because other means such as Raman Lidar or Differential Absorption Lidar have accuracy and/or vertical resolution limitations in the UT (see Turner et al. 2000).
The Report of Access and Engagement With Digital Health Interventions Among Children and Young People: Systematic Review

Background Digital health interventions are increasingly used to deliver health-related interventions for children and young people to change health behaviors and improve health outcomes. Digital health interventions have the potential to enhance access to and engagement with children and young people; however, they may also increase the divide between those who can access technology and are supported to engage and those who are not. This review included studies that reported on the access to or engagement with digital health interventions among children and young people. Objective This review aims to identify and report on access and engagement in studies involving digital health interventions among children and young people. Methods A systematic review following the Joanna Briggs Institute methods for conducting systematic reviews was conducted. An electronic literature search was conducted for all studies published between January 1, 2010, and August 2022, across sources, including MEDLINE, CINAHL, and PsycINFO. Studies were included if they examined any aspect of access or engagement in relation to interventions among children and young people. The quality of the included papers was assessed, and data were extracted. Data were considered for meta-analysis, where possible. Results A total of 3292 references were identified using search terms. Following the exclusion of duplicates and review by inclusion criteria, 40 studies were independently appraised for their methodological quality. A total of 16 studies were excluded owing to their low assessed quality and flawed critical elements in the study design. The studies focused on a variety of health conditions; type 1 diabetes, weight management and obesity, mental health issues, and sexual health were the predominant conditions. Most studies were conducted in developed countries, with most of them being conducted in the United States. Two studies reported data related to access and considered ethnicity and social determinants. No studies used strategies to enhance or increase access. All studies included in the review reported on at least 1 aspect of engagement. Engagement with interventions was measured in relation to frequency of engagement, with no reference to the concept of effective engagement. Conclusions Most digital health interventions do not consider the factors that can affect access and engagement. Of those studies that measured either access or engagement or both, few sought to implement strategies to improve access or engagement to address potential disparities between groups. Although the literature to date provides some insight into access and engagement and how these are addressed in digital health interventions, there are major limitations in understanding how both can be enhanced to promote equity. Consideration of both access and engagement is vital to ensure that children and young people have the ability to participate in studies. Trial Registration PROSPERO CRD42020170874; https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=170874
Prediction Ranifall Using Machine Learning Algorithms: Empirical Evidence from Bogura and Rangpur District of Bangladesh

Around the world, forecasting rainfall has been regarded as one of the most difficult task. Exact and timely rainfall forecasting may be extremely helpful. By uncovering novel links between the readily available elements of historical data, data mining algorithms may accurately anticipate the amount of rainfall. Therefore, it remains intriguing to forecast rainfall data with both the highest degree of accuracy by combining and improving various data mining approaches in case of different weather stations. In this study we compare the forecasting performance of different data mining techniques such as Classification and Regression Trees (CART), Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Random Forest (RF), and Linear Discriminant Analysis (LDA) in case of Bogura and Rangpur district of Bangladesh. For this analysis, the monthly time series data from January 1964 to December 2017 are taken into account. For empirical investigations, the data mining process, including data collection, data pre-processing, modeling, and assessment, is closely adhered to. The empirical study shows that SVM approach is the best option for predicting rainfall in the case of both Bogura and Rangpur district, Bangladesh, for the next time period. The above study will be useful in providing information to support crop, water, and flood control, which will protect people's lives and property and promote economic in its growth. International Journal of Statistical Sciences , Vol. 23(2), November, 2023, pp 47-62
Stability Analysis of Fractional-Order Periodic Piecewise Nonlinear Systems

This paper investigates the stability problem of fractional-order periodic piecewise nonlinear systems. As a preparation, the existence and uniqueness of solutions of the system are derived under the Lipschitz condition and expressed in an equivalent integral expression based on the memorability of fractional derivative. We further propose an upper bound of the system states by using the Laplace transform technique. With the help of piecewise Lyapunov functions and class- $\mathcal {K}$ functions, some sufficient conditions are given to verify the Mittag-Leffler and asymptotic stability of the investigated system mixed with stable and unstable subsystems. Furthermore, asymptotic stability criteria are proposed for a general case, i.e., all subsystems are unstable. Three numerical simulation examples are finally provided to illustrate the effectiveness of the proposed results.