Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of the Constitutional Court in Reforming the Indonesian State System

: The amendment ofthe 1945 Constitution since the reformation has encouraged the establishment of a more democratic constitutional structure. These changes create state institutional structuresthat are in an equal position to checks and balances. One of the new state institutions established to strengthen the legal and democratic institutions in the Indonesian constitutional structure is the Constitutional Court, as one of the judicial institutions with the judicial power. The changes also confirm that judicial power is an independent power to conduct justice in order to uphold law and justice. This paper will discuss how the Constitutional Court as a state institution performs its constitutional function and role through its decisions which can influence and color the legal and constitutional reforms in Indonesia. The research method used in this study is the normative juridical method. The results showed that the verdict is the Crown of the judiciary; therefore, the achievements and role of the Constitutional Court as a judicial institution in coloring legal and constitutional reforms in the homeland are reflected in its decisions, for example: decisions to recognize simultaneous elections; political rights forthe former members of PKI; recall rights of political parties; the use of KTP for voters unregistered in DPT; cancellation of regional regulations becomes the authority of the supreme court; 20% of the education budget allocation; individual candidates in the elections; religion or indigenous faithcolumn in KTP; women can run for Governor or Vice ofGovernor; DPD members may not come from political party administrators.
The Role of Personality-Tailored Notifications in Mobile-Based Behavior Change Intervention

Mobile phones are ubiquitous, equipped with always-on connectivity and a range of sensors, and are carried by their owners at virtually all times, which renders them an attractive platform for delivering timely and relevant content. One type of such a content is information supporting positive behavior change. Indeed, phones have been proposed as a vessel for motivational messages for more than a decade now. Yet, little is known about the importance of personality-based adaptation of the message content in order to facilitate the behavioral change. In this paper we describe our preliminary investigation of the persuasiveness of mobile notifications delivered within a real-world behavior change intervention mobile app. Unlike the clear cut findings observed in other domains, we discover a rather nuanced relationship between the personalization and persuasiveness that calls for further exploration at the individual participant level.
Research and Development of Evaluation system Based on Neural Network and Expert System

As a single system of evaluation, both neural network (NN) and traditional expert system (ES) have many limitations. Developing evaluation system integrating NN with ES is an available way to offset their weakness. With black-box module, a new frame of evaluation system is developed in relative independent method. Then, a way of programming and realizing evaluation system, which is more close to human thinking, is put forward.
The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase

This paper uncovers the socioeconomic and health/lifestyle factors that can explain the differential impact of the coronavirus pandemic on different parts of the United States during the initial outbreak phase of the pandemic. Using a dynamic panel representation of an epidemiological model of disease spread, the paper develops a Vulnerability Index for US counties from the daily reported number of cases over a 20-day period of rapid disease growth. County-level economic, demographic, and health factors are used to explain the differences in the values of this index and thereby the transmission and concentration of the disease across the country. These factors are also used to examine the number of reported deaths. The paper finds that counties with high median income have a high incidence of cases but reported lower deaths. Income inequality, as measured by the Gini coefficient, is found to be associated with more deaths and more cases. The remarkable similarity in the distribution of cases across the country and the distribution of distance-weighted international passengers served by the top international airports is evidence of the spread of the virus by way of international travel. The distributions of age, race and health risk factors such as obesity and diabetes are found to be particularly significant factors in explaining the differences in mortality across counties. Counties with better access to health care, as measured by the number of primary care physicians per capita, have lower deaths, and so do places with more health awareness as measured by flu vaccination prevalence. Environmental health conditions such as the amount of air pollution are found to be associated with counties with higher deaths from the virus. It is hoped that research such as these will help policymakers to develop risk factors for each region of the country to better contain the spread of infectious diseases in the future.
Bringing light to a hidden genre: the peer review report

ABSTRACT While early career researchers (ECRs) often read and produce articles for peer reviewed journals, they are of ten less familiar with peer review reports (PRRs). Most ECRs learn about the genre of PRRs by reading reports written about their authored manuscripts, and through hands-on experience crafting their own PRRs, albeit often with little guidance or exposure to exemplars. To demystify this ‘hidden’ academic genre, this article reports on a genre analysis of 62 ‘quality’ PRRs, focusing on their communicative purposes, and the structural, content, and linguistic elements that serve to support those purposes. Findings show that the central role of the PRR is to elicit various actions on the part of manuscript authors. Other functions serve to circumvent manuscript authors' potential negative emotional response to PRRs, and this is also seen in limited use of high modality verbs and emotional language. PRRs follow a fairly uniform structure, and focus on all elements of the manuscript, with most attention given to the methods section. The article provides numerous examples that provide a practical guide to support writing pedagogies related to this important academic practice.
COVID-19 Chest X-ray Classification and Severity Assessment Using Convolutional and Transformer Neural Networks

The coronavirus pandemic started in Wuhan, China in December 2019, and put millions of people in a difficult situation. This fatal virus spread to over 227 countries and the number of infected patients increased to over 400 million cases, causing over 6 million deaths worldwide. Due to the serious consequence of this virus, it is necessary to develop a detection method that can respond quickly to prevent the spreading of COVID-19. Using chest X-ray images to detect COVID-19 is one of the promising techniques; however, with a large number of COVID-19 infected cases every day, the number of radiologists available to diagnose the chest X-ray images is not sufficient. We must have a computer aid system that helps doctors instantly and automatically determine COVID-19 cases. Recently, with the emergence of deep learning methods applied for medical and biomedical uses, using convolutional neural net and transformer applications for chest X-ray images can be a supplement for COVID-19 testing. In this paper, we attempt to classify three types of chest X-ray, which are normal, pneumonia, and COVID-19 using deep learning methods on a customized dataset. We also carry out an experiment on the COVID-19 severity assessment task using a tailored dataset. Five deep learning models were obtained to conduct our experiments: DenseNet121, ResNet50, InceptionNet, Swin Transformer, and Hybrid EfficientNet-DOLG neural networks. The results indicated that chest X-ray and deep learning could be reliable methods for supporting doctors in COVID-19 identification and severity assessment tasks.
A novel single‐layer frequency selective surface for gain enhancement of SWB antennas

A novel frequency selective surface (FSS) and its application for gain enhancement of super‐wideband antennas are demonstrated in this article. The FSS is single layer; still it reflects quite in‐phase over the entire operating bandwidth (2–20 GHz) providing fractional bandwidth more than 163%. The proposed FSS is successfully simulated, fabricated and measured. It has excellent radiation characteristics with the antenna. Measured results show a significant gain improvement (4–5dBi) over 2–20GHz frequency range. The compact single‐layer configuration of the designed FSS provides more flexibility for its mounting close to a radiator making it an attractive candidate for modern applications in C‐band, X‐band, Ku‐band, and K‐band. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2030–2035, 2016
Effectiveness of a Brief Lifestyle Intervention in the Prenatal Care Setting to Prevent Excessive Gestational Weight Gain and Improve Maternal and Infant Health Outcomes

Research on perinatal programming shows that excessive gestational weight gain (GWG) increases the risk of overweight and obesity later in a child’s life and contributes to maternal weight retention and elevated risks of obstetrical complications. This study examined the effectiveness of a brief lifestyle intervention in the prenatal care setting, compared to routine prenatal care, in preventing excessive GWG as well as adverse maternal and infant health outcomes. The GeMuKi study was designed as a cluster RCT using a hybrid effectiveness implementation design and was conducted in the prenatal care setting in Germany. A total of 1466 pregnant women were recruited. Pregnant women in intervention regions received up to six brief counseling sessions on lifestyle topics (e.g., physical activity, nutrition, drug use). Data on GWG and maternal and infant outcomes were entered into a digital data platform by the respective healthcare providers. The intervention resulted in a significant reduction in the proportion of women with excessive GWG (OR = 0.76, 95% CI (0.60 to 0.96), p = 0.024). Gestational weight gain in the intervention group was reduced by 1 kg (95% CI (−1.56 to −0.38), p < 0.001). No evidence of intervention effects on pregnancy, birth, or neonatal outcomes was found.
Exploring the feasibility and acceptability of a sleep wearable headband among a community sample of chronic pain individuals: An at-home observational study

Background Chronic pain conditions affect up to one third of the adult population in the United Kingdom. Sleep problems are prevalent and negatively impact quality of life. Lack of standardised tools for routine screening and assessment of sleep changes have been a barrier for sleep management. Novel sleep wearables offer an exciting and accessible way to measure sleep but have not been tested outside of the consumer-led landscape and are not commonly used in research and clinical settings. Aims The study aimed to explore the feasibility and acceptability of a sleep monitoring headband (Dreem 2) utilising EEG technology and accompanying smartphone application among a cohort of adults with chronic pain. Results Twenty-one adults (81% women) completed a one-week home sleep study using a sleep headband and accompanying app. Ninety per cent of participants met the pre-defined requirement of two-night's sleep recording. All participants recorded one night of sleep data via the sleep headband. The majority (76%) of participants were satisfied with the sleep study, and 86% of participants were willing to wear the headband longer than the 2-night minimum requirement. Finally, 76% reported the headband as ‘somewhat’ or ‘extremely’ comfortable whist awake; 57% rated the headband as comfortable during sleep. Conclusion The Dreem 2 headband appears to be a feasible and acceptable means of collecting sleep measurements among individuals with chronic pain, despite common sleep disturbances. These devices may have utility for screening, assessment and monitoring in research and practice. Further research is needed to provide guidelines and training for integration.
A fast right ventricle segmentation in cine-MRI from a dense hough representation

Segmentation of the right ventricle (RV) is essential for the diagnosis of multiple cardiac pathologies and conditions. However, its manual delineation is a tedious task and computational support is complex due to geometric and dynamic variability. This work introduces a dense Hough transform and representation (HT) that allows a nonparametric characterization of the shape, encoding each voxel by its curvature and orientation. This representation is integrated into a bayesian tracking approach, which efficiently segments the RV structure throughout the cardiac cycle. The proposed approach was evaluated on a public dataset, with 16 patients, achieving a Sørensen-Dice coefficient of 0.87 and 0.92, for complete volumes and basal structures, respectively. These results evidence an adequate fit of the proposed model with respect to RV shape throughout the entire cardiac cycle. La segmentación del Ventrículo Derecho (VD) es esencial para el diagnóstico de múltiples patologías y condiciones cardiacas. Sin embargo, su delineación manual es una tarea tediosa y el soporte computacional resulta complejo debido a la variabilidad geométrica y dinámica. Este trabajo introduce una transformación y representación densa de Hough (TH) que permite una caracterización no paramétrica de la forma, codificando cada vóxel por su curvatura y orientación. Esta representación es integrada en un enfoque de seguimiento bayesiano, que logra de forma eficiente segmentar la estructura del VD, a lo largo del ciclo cardíaco. El enfoque propuesto fue evaluado en un conjunto de datos públicos, con 16 pacientes, logrando un coeficiente Sørensen-Dice de 0,87 y 0,92, para volúmenes completos y estructuras basales, respectivamente. Estos resultados evidencian una adecuada adaptación del modelo propuesto respecto a la forma del VD a lo largo de todo el ciclo cardíaco.
Assessing Opportunities for Self-Study and Out-of-Class Activities in a Prescriptive High Contact-Hour Engineering Curriculum

Contribution: This work identifies some attributes of a prescriptive high contact-hour engineering curriculum that could be limiting the development of core skills among engineering students. The findings are put together to develop a guideline for curriculum review that optimizes characteristic student academic hours for in- and out-of-class educational activities. Background: One of the identified factors that contribute to developing core technical and soft skills among engineering students is the amount and nature of the academic workload stipulated by the curriculum. An implication of a curriculum with a high quantity of instruction (QI) (class contact hours) is a deficiency in self-directed learning; an activity believed to support the development of critical thinking and lifelong learning skills among students. Research Question: 1) How does the QI of a prescriptive high contact-hour engineering program affect the time for self-study (TSS)? 2) Are there some features of the curriculum of such programs that can be adapted for controlling QI and TSS? Methodology: A narrative review of a curriculum guideline document was carried out. Using an earlier proposed model that expresses TSS as a function of QI, an analysis of TSS and QI characteristics of six universities awarding the same engineering degree was presented. Findings: Given an average weekly contact hour of 27.75, students in the studied engineering programs are likely to have 60% less TSS in comparison to global counterparts. By addressing some characteristics of the curriculum, these numbers can be improved for more out-of-class activities that foster the development of core technical and soft skills.
Reshaping Local Path Planner

This letter proposes a path planner that reshapes a global path locally in response to sensor-based observations of obstacles in the environment. Two fundamental concepts enable the resultant algorithm (a) a path-following synthetic vehicle whose steering actions are non-myopically optimized to result in a smooth traversible path that meets path curvature constraints, and (b) a path-aware turning moment-field that enables obstacle avoidance while eluding the typical local-minimum-induced stagnation associated with potential field methods. The use of the combination of the two concepts results in a reduced action space over which optimization needs to be performed towards minimizing the path deviation subject to obstacle avoidance, and thus results in an efficient algorithm that can be implemented online. We demonstrate the algorithm in simulations as well as in field experiments, performing real time local path planning and obstacle avoidance on two different vehicle platforms (an ackerman steering vehicle two-axled vehicle, and a differential-steering 4-axled vehicle) in an unstructured off-road terrain.
Evaluation of cattle finishing systems and availability of animal feedstuffs in Magu and Ilemela districts, Mwanza Region

A study was carried out in Magu and Ilemela districts in Mwanza region to characterize cattle finishing systems and identify the factors limiting cattle growth performance. A total of 120 agro pastoralists and 30 cattle finishing entrepreneurs were interviewed using questionnaires. Seven focus group discussions were also performed. In addition, monitoring study on cattle growth performance was done for 56 days on a total of 105 cattle, of which body weight gain of cattle was measured fortnightly. Forages and concentrates used by farmers were collected and subjected into chemical analysis and in vitro dry matter digestibility estimated. The identified cattle finishing systems were grazing alone (GrazAlo), grazing with concentrate supplementation (GrazSup) and feedloting. Cattle under GrazAlo showed lower (P<0.001) body weight gain (0.21kg/day) than those under GrazSup (0.51 kg/day). Natural forages exist in both districts whereas the dominant crop residues in Ilemela and Magu districts were indicated to be maize stover (97.5% and 100% of respondents, respectively) and rice straws (92.5 % and 98.8% of respondents, respectively). Supplements for cattle finishing in both districts were shown to be cotton seed hulls and cotton seed cake with crude protein of 93.91 and 363.9 g/kg DM, respectively. The identified constraints for agro pastoralists in Ilemela and Magu districts were inadequate grazing land (65.9% and 34.5% of respondents, respectively) and inadequate feed resources (31.7% and 60.5% of respondents, respectively). All interviewed cattle finishing entrepreneurs in Ilemela district reported inadequate grazing lands whereas those in Magu district reported high cost of drugs (100% of respondents) and inadequate water (100% of respondents) to be the main challenges. It is concluded that, the growth performance
A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, which is characterized by metabolic reprogramming. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical impacts of cuproptosis-related genes (CRGs) in ccRCC largely remain unclear. In the current study, we systematically evaluated the genetic alterations of cuproptosis-related genes in ccRCC. Our results revealed that CDKN2A, DLAT, DLD, FDX1, GLS, PDHA1 and PDHB exhibited differential expression between ccRCC and normal tissues (|log2(fold change)| > 2/3 and p < 0.05). Utilizing an iterative sure independence screening (SIS) method, we separately constructed the prognostic signature of CRGs for predicting the overall survival (OS) and progression-free survival (PFS) in ccRCC patients. The prognostic score of CRGs yielded an area under the curve (AUC) of 0.658 and 0.682 for the prediction of 5-year OS and PFS, respectively. In the Kaplan−Meier survival analysis of OS, a higher risk score of cuproptosis-related gene signature was significantly correlated with worse overall survival (HR = 2.72 (2.01–3.68), log-rank p = 1.76 × 10−7). Patients with a higher risk had a significantly shorter PFS (HR = 2.83 (2.08–3.85), log-rank p = 3.66 × 10−7). Two independent validation datasets (GSE40435 (N = 101), GSE53757 (N = 72)) were collected for meta-analysis, suggesting that CDKN2A (log2(fold change) = 1.46, 95%CI: 1.75–2.35) showed significantly higher expression in ccRCC tissues while DLAT (log2(fold change) = −0.54, 95%CI: −0.93–−0.15) and FDX1 (log2(fold change) = −1.01, 95%CI: −1.61–−0.42) were lowly expressed. The expression of CDKN2A and FDX1 in ccRCC was also significantly associated with immune infiltration levels and programmed cell death protein 1 (PD-1) expression (CDKN2A: r = 0.24, p = 2.14 × 10−8; FDX1: r = −0.17, p = 1.37 × 10−4). In conclusion, the cuproptosis-related gene signature could serve as a potential prognostic predictor for ccRCC patients and may offer novel insights into the cancer treatment.
Developing data capability with non-profit organisations using participatory methods

In this paper, we explore the methodologies underpinning two participatory research collaborations with Australian non-profit organisations that aimed to build data capability and social benefit in data use. We suggest that studying and intervening in data practices in situ, that is, in organisational data settings expands opportunities for improving the social value of data. These situated and collaborative approaches not only address the ‘expertise lag’ for non-profits but also help to realign the potential social value of organisational data use. We explore the relationship between data literacy, data expertise and data capability to test the idea that collaborative work with non-profit organisations can be a practical step towards addressing data equity and generating data-driven social outcomes. Rather than adopting approaches to data literacy that focus on individuals – or ideal ‘data citizens’ – we target the organisation-wide data settings, goals and practices of the non-profit sector. We conclude that participatory methods can embed social value-generating data capability where it can be sustained at an organisational level, aligning with community needs to promote collaborative data action.
Anti-Disturbance Compensation for Quadrotor Close Crossing Flight Based on Deep Reinforcement Learning

The aim of this article is the design of a feedforward compensator based on deep reinforcement learning (DRL) for cooperative quadrotors in close crossing flight. Quadrotors are described by state-space models that include shearing airflow disturbance from other quadrotors. This disturbance is compensated in a feedforward way using DRL. Both value based compensator and policy based compensator algorithms are proposed for training purposes. Then, Lyapunov stability criteria are used to prove that the reference trajectory can be tracked boundedly even during the training process of the proposed algorithms, and that a smaller bound of tracking error can be achieved when the compensator converges. An indoor experimental system for online training has been developed for validation purposes. Both simulation and experimental results are provided to demonstrate the effectiveness and advantages of the proposed compensator.