Miracle-dz/UniFAR-FTUs huggingface dataset:
Sistem informasi publik e-lapor pengaduan masyarakat di kelurahan sriwidari menggunakan CRM berbasis android

Kelurahan Sriwidari adalah salah satu kelurahan yang ada di Kecamatan Gunungpuyuh, Kota Sukabumi, Provinsi Jawa Barat. Kelurahan Sriwidari saat ini menerima pengaduan masyarakat dengan metode manual, yaitu dengan cara masyarakat datang langsung ke kantor Kelurahan Sriwidari untuk menyampaikan pengaduan. Namun, metode ini seringkali kurang efektif karena butuh proses untuk menyampaikan pada setiap petugas sesuai kategori pengaduan, berkas pengaduan dapat hilang dan juga rusak selain itu rekap data yang dilakukan juga sulit karena harus melakukan pengecekan berkas satu persatu. Oleh karena itu penulis tertarik untuk memberikan sebuah solusi dari persoalan tersebut maka dibuatlah aplikasi E-Lapor pengaduan masyarakat berbasis android dengan bahasa pemograman Java dan Firebase Realtime sebagai database. Aplikasi E-Lapor pengaduan masyarakat berbasis android ini dapat mempermudah masyarakat untuk melakukan pengaduan tanpa harus datang ke kantor Kelurahan. Peneliti menggunakan metode Customer Relationship Management (CRM) untuk merancang Aplikasi e-lapor pengaduan masyarakat berbasis android ini. Hasilnya, sistem ini dapat dipergunakan sebagai media publikasi dan komunikasi antara masyarakat yang ada di Kelurahan Sriwidari.
Assembling Spheroids of Rat Primary Neurons Using a Stress-Free 3D Culture System

Neural injuries disrupt the normal functions of the nervous system, whose complexities limit current treatment options. Because of their enhanced therapeutic effects, neurospheres have the potential to advance the field of regenerative medicine and neural tissue engineering. Methodological steps can pose challenges for implementing neurosphere assemblies; for example, conventional static cultures hinder yield and throughput, while the presence of the necrotic core, time-consuming methodology, and high variability can slow their progression to clinical application. Here we demonstrate the optimization of primary neural cell-derived neurospheres, developed using a high-throughput, stress-free, 3D bioreactor. This process provides a necessary baseline for future studies that could develop co-cultured assemblies of stem cells combined with endothelial cells, and/or biomaterials and nanomaterials for clinical therapeutic use. Neurosphere size and neurite spreading were evaluated under various conditions using Image J software. Primary neural cells obtained from the hippocampi of three-day-old rat pups, when incubated for 24 h in a reactor coated with 2% Pluronic and seeded on Poly-D-Lysine-coated plates establish neurospheres suitable for therapeutic use within five days. Most notably, neurospheres maintained high cell viability of ≥84% and expressed the neural marker MAP2, neural marker β-Tubulin III, and glial marker GFAP at all time points when evaluated over seven days. Establishing these factors reduces the variability in developing neurospheres, while increasing the ease and output of the culture process and maintaining viable cellular constructs.
Community pharmacists’ skills and practice regarding dispensing fiscalized substances: a cross-sectional survey

Background: The use of drugs containing fiscalized substances is essential in different medical areas, including pain management, obstetric emergencies, and the treatment of mental disorders. However, due to their potential for abuse and negative health effects, the dispensing of these substances demands pharmacists with the requisite skills and practice. Objective: This study assesses the skills and practices of pharmacy personnel in the United Arab Emirates (UAE) regarding the dispensing of tramadol, a medication containing fiscalized substances, in community pharmacies. Methodology: A cross-sectional study was conducted. Community Pharmacies were chosen via random sampling, and seven well-trained final year pharmacy students visited them and conducted face-to-face interviews. The survey tool covered items highlighting the demographic data of the subjects, and items on the practice and skills regarding dispensing the fiscalized substances. The content validity ratio values of all tool questions were more than 0.78, suggesting acceptable validity and the Cronbach’s α of 0.75 showed as acceptable internal reliability. The primary outcome measures of interest were the skills and practice regarding dispensing Fiscalized substances. Results: A total of 612 pharmacists were recruited in the study. The average practice score was 80%. There was a statistically significant association (p < 0.05) between practices about dispensing fiscalized substances and gender, age group, pharmacy type, work experience, university of graduation, and receiving training on epilepsy and antiepileptic drugs. Conclusion: The results implied that competency and experience are vital factors for the dispensing of tramadol. Contextually, the majority of the pharmacists evidently have the requisite competencies to provide high-quality and proper medical care, with regards to dispensing tramadol, which will minimize drug abuse and medication errors, and assist outpatients to manage their drugs containing fiscalized substances.
Cost effectiveness of nonpharmacological prevention programs for diabetes: A systematic review of trial‐based studies

Abstract Trial‐based economic value of prevention programs for diabetes is inexplicit. We aimed to review the cost‐effectiveness of nonpharmacological interventions to prevent type‐2 diabetes mellitus (T2DM) for high‐risk people. Six electronic databases were searched up to March 2022. Studies assessing both the cost and health outcomes of nonpharmacological interventions for people at high‐risk of T2DM were included. The quality of the study was assessed by the Consolidated Health Economic Evaluation Reporting Standards 2022 checklist. The primary outcome for synthesis was incremental cost‐effectiveness ratios (ICER) for quality‐adjusted life years (QALYs), and costs were standardized in 2022 US dollars. Narrative synthesis was performed, considering different types and delivery methods of interventions. Sixteen studies included five based on the US diabetes prevention program (DPP), six on non‐DPP‐based lifestyle interventions, four on health education, and one on screening plus lifestyle intervention. Compared with usual care, lifestyle interventions showed higher potential of cost‐effectiveness than educational interventions. Among lifestyle interventions, DPP‐based programs were less cost‐effective (median of ICERs: $27,077/QALY) than non‐DPP‐based programs (median of ICERs: $1395/QALY) from healthcare perspectives, but with larger decreases in diabetes incidence. Besides, the cost‐effectiveness of interventions was more possibly realized through the combination of different delivery methods. Different interventions to prevent T2DM in high‐risk populations are both cost‐effective and feasible in various settings. Nevertheless, economic evidence from low‐ and middle‐income countries is still lacking, and interventions delivered by trained laypersons and combined with peer support sessions or mobile technologies could be potentially a cost‐effective solution in such settings with limited resources.
Potential Release Areas and Return Period of Avalanches: Is There a Relation?

Avalanche hazard zones are usually defined in terms of impact pressures and run-out distances for avalanches with a specific return period (T). Calculating these parameters through avalanche dynamics models requires a range of input parameters including the extent of the release area, which gives, together with the fracture depth, the total avalanche volume. Today, in Switzerland and Italy release areas for a 30, 100 and 300 year avalanches are assumed to have the same size while fracture depths are varied with T. This paper focuses on the question of whether it is possible to find a reliable relationship between the extent of a release area and the return period. Following the same approach that is used in Switzerland to determine the fracture depth of avalanches, we analyzed with Gumbel extreme-value statistics the relationship between T and the extent of the release area of previously observed events in specific avalanche paths. This study is based on avalanche databases of the regions of Davos, Switzerland and the Aosta Valley, Italy. The results show that for 300yr-avalanches the total extent of the potential release area has to be considered. However, for more frequent avalanches, it is often appropriate to specify only a subarea of the total potential release area. This result suggests that avalanche hazard mapping experts could use the proposed procedure as a help to determine the extent of the release area with a given return period. However, such an approach also emphasizes the need to extend avalanche release area databases by adding new regions and by improving the quality of the release area information collected.
The Role of P-Glycoprotein (P-gp) in Cancer Multidrug Resistance (MDR): Challenges for Inhibiting P-gp in the Context of Overcoming MDR

Multidrug resistance (MDR), as is well known, is regarded as the primary factor in cancer therapy failure. A common mechanism of MDR in anticancer drugs is the expression of P-glycoprotein (P-gp), a class of ATP-dependent membrane transport efflux pumps called adenosine triphosphate (ATP)-binding cassette (ABC) transporters. It pumps xenobiotics outside the cell and plays part in typical physiological detoxification and host defense activities. This transporter is distributed in gastrointestinal mucosa epithelial cell surfaces, blood-tissue barriers, hepatic biliary epithelium, proximal tubules of the kidney, and the adrenal cortex. P-gp is known to be responsible for MDR because of its over-expression in malignant cells. It functions as an efflux pump lowering the concentration of drugs intracellularly, thus decreasing the effectiveness of cancer chemotherapy. Although using multiple anticancer medications is a good strategy, Cancerous cells are able to develop MDR. A number of chemically synthesized P-gp inhibitors were investigated to overcome MDR in clinical studies. Additionally, certain natural compounds have been observed to modulate P-gp. Numerous investigations on strategies to modulate MDR have been conducted as a result of the significant impact of chemotherapeutic drug resistance. This review discusses the role of P-gp in cancer MDR and challenges for inhibiting P-gp in the context of overcoming MDR mediated by P-gp. It is concluded that the discovery of selective, safe, and potent inhibitors of P-gp remains necessary.
Non-Linear Migrations and Urban Resilience

This paper looks at migrations as an inherent component of urban resilience and critically examines the linear understanding of rural-to-urban migration in urban studies. Based on an eight-month-long qualitative empirical study in Dhaka, Bangladesh, this paper reports how migrants from different rural parts of the country, with their complex experiences around migrations, enter various spatial systems in urban Dhakaranging from shared living to institutional involvements to temporal displacements due to external factors(such as pandemic). This paper also documents how their nonlinear migratory journeys contribute to building a sense of urban resilience toward the uncertainties that various spatial systems offer to them. Drawing from a rich body of literature on urbanization, rural-urban migration, and actor-based resilience, we explain how alternative narratives of non-linear migration studies from our fieldwork can redefine urban resilience from a migrant’s perspective.
Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification

The use of remotely sensed data as input into geographical information systems has promoted new interest in issues related to the accuracy of multispectral classification. This paper investigates the impact of classification uncertainty on the estimation of area from satellite derived land-cover data. Applying four variants of the maximum-likelihood classifier, it is shown that the estimated area for different land-cover classes is highly influenced by the methods which are used for classifier training. To evaluate the uncertainty of area estimates, a new error modeling strategy is proposed. Assuming that attribute uncertainty in image classification is field-based rather than pixel-based, the image is segmented in fields according to similarities in the probability vectors of adjacent pixels. In simulating uncertainty, this field structure is explicitly taken into account. Using different strategies for image segmentation, it is shown that the spatial correlation of classification uncertainty has a major impact on the assessment of the uncertainty of area estimates. Centre for Cartography and GIS, Department of Geography, Vrije Universiteit Brussel, Pleinlaan 2, B 1050 Brussel, Belgium.
Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy

Objective The aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population. Methods A population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration. Results A total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased. Conclusion CReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs.
Progressive drought alters the root exudate metabolome and differentially activates metabolic pathways in cotton (Gossypium hirsutum)

Root exudates comprise various primary and secondary metabolites that are responsive to plant stressors, including drought. As increasing drought episodes are predicted with climate change, identifying shifts in the metabolome profile of drought-induced root exudation is necessary to understand the molecular interactions that govern the relationships between plants, microbiomes, and the environment, which will ultimately aid in developing strategies for sustainable agriculture management. This study utilized an aeroponic system to simulate progressive drought and recovery while non-destructively collecting cotton (Gossypium hirsutum) root exudates. The molecular composition of the collected root exudates was characterized by untargeted metabolomics using Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) and mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Over 700 unique drought-induced metabolites were identified throughout the water-deficit phase. Potential KEGG pathways and KEGG modules associated with the biosynthesis of flavonoid compounds, plant hormones (abscisic acid and jasmonic acid), and other secondary metabolites were highly induced under severe drought, but not at the wilting point. Additionally, the associated precursors of these metabolites, such as amino acids (phenylalanine and tyrosine), phenylpropanoids, and carotenoids, were also mapped. The potential biochemical transformations were further calculated using the data generated by FT-ICR MS. Under severe drought stress, the highest number of potential biochemical transformations, including methylation, ethyl addition, and oxidation/hydroxylation, were identified, many of which are known reactions in some of the mapped pathways. With the application of FT-ICR MS, we revealed the dynamics of drought-induced secondary metabolites in root exudates in response to drought, providing valuable information for drought-tolerance strategies in cotton.
Active Reinforcement Learning from Demonstration in Continuous Action Spaces

Learning from Demonstration (LfD) is a human-in-the-loop paradigm that aims to overcome the limitations of safety considerations and weak data efficiency in Reinforcement Learning (RL). Active Reinforcement Learning from Demonstration (ARLD) takes LfD a step further by actively involving the human expert only during critical moments, reducing the costs associated with demonstrations. While successful ARLD strategies have been developed for RL environments with discrete actions, their potential in continuous action environments has not been thoroughly explored. In this work, we propose a novel ARLD strategy specifically designed for continuous environments. Our strategy involves estimating the uncertainty of the current RL agent directly from the variance of the stochastic policy within the state-of-the-art Soft Actor-Critic RL model. We demonstrate that our strategy outperforms both a naive attempt to adapt existing ARLD strategies to continuous environments and the passive LfD strategy. These results validate the potential of ARLD in continuous environments and lay the foundation for future research in this direction.
The application of logotherapy to improve the meaning of life in emerging adults with self-injury

Self-injury occurs commonly in young people, especially during the development phase of emerging adults. It is seen as a manifestation of existential problems, such as obstacles in fulfilling or pursuing meaning in life which is the most basic human motivation. This study aims to determine the effect of logotherapy as an intervention to increase purpose in life in emerging adults who engage in self-injury. The research utilized a single case experiment A-B design involving two subjects, measuring their level of meaning in life with the Meaning in Life Questionnaire (MLQ). The analysis technique of visual analysis, baseline-corrected tau, and Reliable Change Index (RCI) yielded outcomes indicating logotherapy as an effective intervention option for increasing meaning in life in emerging adults with self-injury.
In-situ monitoring of the melt pool dynamics in ultrasound-assisted metal 3D printing using machine learning

ABSTRACT Ultrasound-assisted directed energy deposition (UADED) is a promising technology for improving the properties of printed parts. However, process monitoring during UADED remains a challenge as ultrasound obscures the physical characteristics of DED. Here, the physical phenomena during UADED are captured using in-situ imaging and an unsupervised learning with auto-encoding is proposed to reconstruct images of the melt pool and analyse the features of spatter and plume to achieve the forming quality monitoring. This method enables effectively identifying the dynamic relationship in melt pool-spatter-plume, and the average recognition accuracy for reconstructed images reaches 94.52% during fully connected auto-encoders. Based on recognition results, the spatters during UADED are more intense, but the plume phenomenon is weakened compared to DED. The reason is that the flow mode was changed into reciprocal flow due to ultrasound. Subsequently, experiments indicated the method possessed high accuracy and robustness. The paper aims to provide a reference source for research studies on intelligent monitoring metal 3D printing. GRAPHICAL ABSTRACT
Evo Morales: The Extraordinary Rise of the First Indigenous President of Bolivia

The fascinating Bolivian president Evo Morales is vying with the brash and provocative leader of Venezuela, Hugo Chavez, as the most influential figure in South American politics today. His rule has already had direct repercussions for the United States, and as one of our top oil exporters, Bolivia will become increasingly significant to our economy. Since coming into office four years ago, Morales has been intensely critical of the United States, speaking out agaisnt the drug war at the United Nations and implementing socialist programs at home, including the nationalization of British Petroleum holdings and other foreign investments. And he has reached out to our political enemies, including Cuba and Iran. In this first biography of this fascinating figure - ranked as one of the top books of last year by the Spanish press - Argentinean journalist Martin Sivak provides a fast-paced and in-depth look at the man behind the president. Based on personal interviews and unprecedented access Sivak traces his rise from its humble origins in a family of migrant workers to his youth as union organizer and explosion on the natioanl stage. Sivak offers a close up portrait that reveals a consequential world leader whose international platform is growing.
3D temporal evolution of displacements through the SISTEM method

Differential interferometric SAR (DInSAR) is widely used for many ground deformation monitoring applications. However it is affected by two main limitations: temporal decorrelation and atmospheric heterogeneities. In order to overcome these drawbacks several techniques to study the temporal evolution of ground deformation have been developed [1-3]. These techniques provide mono dimensional time evolution of displacement measured along the Line Of Sight (LOS) of the satellite. The aim of this paper is to propose a strategy able to provide 3D temporal evolution of displacements. To this end, for a given multi-temporal dataset of SAR and GPS measurements, the SISTEM (Simultaneous and Integrated Strain Tensor Estimation from geodetic and satellite deformation Measurements) method [4] is used both to filter atmospheric effects (by a new iterative procedure) and to produce 3D ground deformation maps. Then a SBAS-like algorithm is used to “link” these maps and to provide 3D temporal evolution of deformations. The proposed methodology was tested on both synthetic and experimental data.
Landmark-Based Navigation of an Unmanned Ground Vehicle (UGV)

Abstract : We present a method for estimating the position and orientation of a ground vehicle in an environment with landmarks. From the geometric relationships, we derive a set of linear equations with a quadratic constraint, which forms the basis for our optimisation problem. We also extend the problem to associating two sets of measurements taken at two successive locations to improve the navigation accuracy. This method is efficient and the performance is robust against large measurement errors.