Miracle-dz/UniFAR-FTUs huggingface dataset:
Availability and Accessibility of Primary Care for the Remote, Rural, and Poor Population of Indonesia

Background: Adopting Universal Health Coverage for implementation of a national health insurance system [Jaminan Kesehatan Nasional (JKN)/Badan Penyelenggara Jaminan Sosial or the Indonesian National Social Health Insurance Scheme (BPJS)] targets the 255 million population of Indonesia. The availability, accessibility, and acceptance of healthcare services are the most important challenges during implementation. Referral behavior and the utilization of primary care structures for underserved (rural/remote regions) populations are key guiding elements. In this study, we provided the first assessment of BPJS implementation and its resulting implications for healthcare delivery based on the entire insurance dataset for the initial period of implementation, specifically focusing on poor and remote populations. Methods: Demographic, economic, and healthcare infrastructure information was obtained from public resources. Data about the JKN membership structure, performance information, and reimbursement were provided by the BPJS national head office. For analysis, an ANOVA was used to compare reimbursement indexes for primary healthcare (PHC) and advanced healthcare (AHC). The usage of primary care resources was analyzed by comparing clustered provinces and utilization indices differentiating poor [Penerima Bantuan Iur (PBI) membership] and non-poor populations (non-PBI). Factorial and canonical discrimination analyses were applied to identify the determinants of PHC structures. Results: Remote regions cover 27.8% of districts/municipalities. The distribution of the poor population and PBI members were highly correlated (r2 > 0.8; p < 0.001). Three clusters of provinces [remote high-poor (N = 13), remote low-poor (N = 15), non-remote (N = 5)] were identified. A discrimination analysis enabled the >82% correct cluster classification of infrastructure and human resources of health (HRH)-related factors. Standardized HRH (nurses and general practitioners [GP]) availability showed significant differences between clusters (p < 0.01), whereas the availability of hospital beds was weakly correlated. The usage of PHC was ~2-fold of AHC, while non-PBI members utilized AHC 4- to 5-fold more frequently than PBI members. Referral indices (r2 = 0.94; p < 0.001) for PBI, non-PBI, and AHC utilization rates (r2 = 0.53; p < 0.001) were highly correlated. Conclusion: Human resources of health availability were intensively related to the extent of the remote population but not the numbers of the poor population. The access points of PHC were mainly used by the poor population and in remote regions, whereas other population groups (non-PBI and non-Remote) preferred direct access to AHC. Guiding referral and the utilization of primary care will be key success factors for the effective and efficient usage of available healthcare infrastructures and the achievement of universal health coverage in Indonesia. The short-term development of JKN was recommended, with a focus on guiding referral behavior, especially in remote regions and for non-PBI members.
Application of training data affects success in broad-scale local climate zone mapping

are likely spatially autocorrelated and lead to overly optimistic estimates of model accuracy. Although both effects – inconsistent labeling and spatial autocorrelation – are theoretically possible, it is unknown whether they substantially affect accuracy. We investigated both issues, specifically asking: (i) how do the discrepancies of LCZ labeling by different experts impact broad-scale LCZ mapping? (ii) to what extent does spatial correlation affect model prediction power? We used two classifiers (Random Forests and ResNets) to map eight metropolitan areas in the US into LCZs, comparing training areas drawn by different or consistent interpreters, and data splitting strategy using rules that allow or reduce spatial autocorrelation. We found large discrepancies among results built from crowdsourced training areas digitized by different experts; improving the consistency of labels can lead to substantial improvements in LCZ classification accuracy. Second, we found that spatial autocorrelation can boost the apparent accuracy of the classifier by 16% to 21%, leading to erroneous interpretation of mapping results. The two effects interplay as well: spatial auto-correlation in the raw data can lead to an underestimation of the model ’ s predictive error when modeling with crowdsourced training areas of high inconsistency. Due to the uncertainty in the labeling process and spatial autocorrelation in derived training data, broad-scale LCZ mapping results should be interpreted with caution.
Intelligent Network Intrusion Prevention Feature Collection and Classification Algorithms

Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies offer protection in interactions in dispersed locations such as, e-commerce, mobile networking, telecommunications and management of network. Furthermore, this article proposed on intelligent feature selection methods and intrusion detection (ISTID) organization in webs based on neuron-genetic algorithms, intelligent software agents, genetic algorithms, particulate swarm intelligence and neural networks, rough-set. These techniques were useful to identify and prevent network intrusion to provide Internet safety and improve service value and accuracy, performance and efficiency. Furthermore, new algorithms of intelligent rules-based attributes collection algorithm for efficient function and rules-based improved vector support computer, were proposed in this article, along with a survey into the current smart techniques for intrusion detection systems.
Influence of lead-free glass frit in the front contact paste on the conversion efficiency of polycrystalline silicon solar cells

Due to the demand for a new environmentally friendly silver front conductive paste, it is imperative for silicon solar cells to use nontoxic lead-free glass frits. In the present paper, three kinds of Bi–Te–B–Si–P–O lead-free glass frits with different mass fraction ratios of B2O3/SiO2 (10/4, 6/8, and 2/12) were prepared by a melt cooling route. First, we investigated that the effect of those B2O3/SiO2 ratios on the transition temperature (Tg) of glass frits, and their Tg were 311 °C, 347 °C, and 366 °C, respectively. Then, the influence of Tg on cross-sectional microstructures of the front-silver electrodes, the Ag crystallites distribution on Si substrate, and electrical performance were studied. The fabricated solar cell showed the lowest series resistance (0.0017 Ω) and the highest photoelectric conversion efficiency (18.260%) based on the glass frit Tg of 347 °C. This is because the dense thick-film Ag grid can reduce the bulk resistance of the grid line. Besides, the glass frit with the Tg of 347 °C could control the growth and homogeneous distribution of silver crystallites in the glass layer and silicon substrate, which contributed to forming good ohmic contacts and tunneling effect with enough energy photoelectrons. The result was compared with the solar cell fabricated with a classical Pb-based glass frit with the conversion efficiency (18.230%) using the same device configuration, which indicated the designed lead-free glass frit could be a suitable substitute for a Pb-based glass frit for preparing environmentally friendly front-side silver paste for crystalline silicon solar cells.
Risk Factors Associated with Post-therapeutic Outcome for Medulloblastoma: An Experience from Indonesia

Context: The prognosis of medulloblastoma is better in patients who underwent complete treatment consisting of surgery, radiotherapy, and chemotherapy. However, the realization of such multidiscipline management is quite challenging in developing countries, including Indonesia. Until now, no study on the management of medulloblastoma has ever been conducted in Indonesia. Aims: The authors aimed to study the characteristics, management, and mortality outcome of medulloblastoma patients in Dr. Cipto Mangunkusumo National Referral Hospital, Jakarta, Indonesia. Subjects and Methods: This study was based on medical record and registry of 44 medulloblastoma patients who underwent tumor removal in Dr. Cipto Mangunkusumo National Referral Hospital, Jakarta, Indonesia, between 2011 and 2018. Statistical Analysis Used: Cox regression analysis was utilized to determine the relationship between patients' demography, tumor characteristics, and treatment, with mortality. Results: The incidence of mortality was 84.1% and median months' survival time (95% confidence interval [CI]) was 13 (8.67–17.32). Gross total removal (GTR) was performed in 43.2% of all tumor removal surgery. Only 50% of all patients completed radiotherapy, and 6.8% concluded multimodalities treatment (surgery, radiotherapy, and chemotherapy). Significant statistical association between age, gender, and extent of resection with mortality was identified (HR [95% CI] for age: 0.44 [0.22–0.88], gender: 0.001 [0.000–0.27; REF: female], and biopsy: 31.52 [1.09–910.56; REF: GTR]). Conclusions: The survival rate of medulloblastoma in Indonesia is inferior to that previously reported in other studies. There is no unusual characteristic contributing to neoteric risk factor. The authors surmise that insufficient multidisciplinary management for the disease, consisting of suboptimal tumor resection, the absence of risk stratification, and incomplete postsurgical treatment (radiotherapy and chemotherapy) resulted in such outcome.
Transvenous Embolization of Cavernous Sinus Dural Arteriovenous Fistula through the Angiographically Occlusive Superior Ophthalmic Vein

Transvenous embolization (TVE) through the superior ophthalmic vein (SOV) is a useful approach for the treatment of cavernous sinus (CS) dural arteriovenous fistulae (DAVFs). This venous route is usually confirmed by angiography. Herein, we present a case of favorable embolization of the CS DAVF through the angiographically occlusive SOV. A 61-year-old man presented with progressive exophthalmos and hypertonia. The patient was diagnosed with a CS DAVF, and TVE was planned. The first approach through the inferior petrosal sinus was infeasible; therefore, we attempted to approach the fistula through the left facial vein. The microcatheter was easily advanced to the shunt point through the angiographically occlusive SOV. We performed coil embolization, and the CS DAVF was completely obstructed.
Inhibitory Roles of Nigella sativa seed extracts on in vitro glycation and aggregation

Background: Glycation is the multi-step process wherein the carbonyl group of glucose reacts with the amino group of other nitrogen-containing compounds like proteins and DNA. This interaction leads to the generation of harmful metabolites commonly known as advanced glycation end products (AGEs). These AGEs have been implicated in various diseases such as cataracts, diabetes, and Alzheimer's. Objectives: The aim of the present study was to check the effect of Nigella sativa seed extracts on glycation and aggregation and for this purpose, two proteins (bovine serum albumin [BSA] and hemoglobin) and two sugars (glucose, and ribose) were selected. Materials and Methods: The amount of glycation mediated products was measured by established methods such as browning, nitroblue tetrazolium (NBT) assay, carbonyl content, and aggregation assays in the presence or absence of extracts (1 mg/ml). The effect of extracts was also checked on glycated DNA by agarose gel electrophoresis. Results: Analysis of results indicates that extracts (1 mg/ml) significantly prevented the generation of early products up to 30.57% (BSA-Rib) and 64.90% (Hb-Glu). The AGEs formation was also suppressed in different glycation systems up to 60.76% (BSA-Glu), 30.79% (BSA-Rib) and 10.74% (Hb-Glu) in the presence of extracts. There was also a decrease in the level of glycation-mediated protein aggregation. Seed extracts were able to prevent the glycoxidative damage of DNA. Conclusion: It can be concluded that black cumin seeds have antiglycating and antiaggregation potential as well as antioxidant properties. Further characterization will help in the identification of active compounds which can be used for the prevention of secondary complications of diabetes and aggregation.
Long-Term Electrocardiographic and Echocardiographic Progression of Arrhythmogenic Right Ventricular Cardiomyopathy and Their Correlation With Ventricular Tachyarrhythmias

Supplemental Digital Content is available in the text. Background: Prior studies of structural and electrocardiographic changes in arrhythmogenic right ventricular (RV) cardiomyopathy and their role in predicting ventricular arrhythmias (ventricular tachycardia) have shown conflicting results. Methods: We reviewed 405 ECGs, 315 transthoracic echocardiographies, and 441 implantable cardioverter defibrillator interrogations in 64 arrhythmogenic RV cardiomyopathy patients (56% men, mean age [SD], 44.2 [14.6] years) over a mean follow-up of 10 (range, 2.3–19) years. Generalized estimating equations were used to identify the association between ECG abnormalities, clinical variables, and transthoracic echocardiographic measurements (>mild degree of tricuspid regurgitation, RV outflow tract diameter in parasternal long axis and short axis, RV end-diastolic area, fractional area change). Results: There was a 4.65 (95% CI, 0.51%–8.8%) increase in RV end-diastolic area, a 3.75 (95% CI, 1.17%–6.34%) decrease in fractional area change, and 1.9 (95% CI, 1.3–2.8) higher odds (odds ratio) of RV wall motion abnormality with every 5-year increase in age after patients’ first transthoracic echocardiography. >Mild tricuspid regurgitation was an independent predictor of RV enlargement and dysfunction (hazard ratio of >10% drop in fractional area change from baseline [95% CI], 3.51 [1.77–6.95] and hazard ratio of >10% increase in RV end-diastolic area from baseline [95% CI], 4.90 [2.52–9.52]). Patients with implantable cardioverter defibrillator were more likely to develop >mild tricuspid regurgitation and larger structural and functional disease progression. More pronounced increase in RV end-diastolic area was translated into higher rates of any ventricular tachycardia. Inferior T-wave inversions and sum of R waves (mm) in V1 to V3 were predictors of RV enlargement and dysfunction with the former also predicting risk of any ventricular tachycardia. Conclusions: Arrhythmogenic RV cardiomyopathy is a progressive disease. Tricuspid regurgitation is an independent predictor of structural disease progression, which may be exacerbated by use of a transvenous implantable cardioverter defibrillator lead.
Supplementary material to "Quantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratio"

Abstract. We present a method for estimating fossil fuel methane emissions using observations of methane and ethane, accounting for uncertainty in their emission ratio. The ethane:methane emission ratio is incorporated as a variable parameter in a Bayesian model, with its own prior distribution and uncertainty. We find that using an emission ratio distribution mitigates bias from using a fixed, potentially incorrect emission ratio and that uncertainty in this ratio is propagated into posterior estimates of emissions. A synthetic data test is used to show the impact of assuming an incorrect ethane:methane emission ratio and demonstrate how our variable parameter model can better quantify overall uncertainty. We also use this method to estimate UK methane emissions from high-frequency observations of methane and ethane from the UK Deriving Emissions linked to Climate Change (DECC) network. Using the joint methane-ethane inverse model, we estimate annual mean UK methane emissions of approximately 0.27 (95 % uncertainty interval 0.26–0.29) Tg per year from fossil fuel sources and 2.06 (1.99–2.15) Tg per year from non-fossil fuel sources, during the period 2015–2019. Uncertainties in UK fossil fuel emissions estimates are reduced on average by 15 %, and up to 35 %, when incorporating ethane into the inverse model, in comparison to results from the methane-only inversion.
Automated Framework for the Augmentation of Missing Anatomical Structures and Generation of Personalized Atrial Models from Clinical Data

Personalized computational models are often generated from electroanatomical maps, which might lack important anatomical structures like the appendages, or from imaging data which are potentially affected by segmentation uncertainty. A bi-atrial statistical shape model (SSM) was shown to cover atrial shape variability. We hypothesized that it could, therefore, also be used to infer the shape of missing structures and deliver ready-to-use models to assess atrial fibrillation vulnerability in silico. We implemented a highly automatized pipeline to generate a personalized computational model by fitting the SSM to the clinically acquired geometries. We applied our framework to a geometry coming from an electroanatomical map and one derived from magnetic resonance images (MRI). Only landmarks belonging to the left atrium and no information from the right atrium were used in the fitting process. The left atrium surface-to-surface distance between electroanatomical map and a fitted instance of the SSM was 2.26±1.95mm. The distance between MRI segmentation and SSM was 2.07±1.56 mm and 3.59±2.84mm in the left and right atrium, respectively. Our semi-automatic pipeline provides personalized computational models representing the original anatomy well by fitting a SSM. We were able to infer the shape ofthe right atrium even in the case ofusing information only from the left atrium.
TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation

Recent progress in generative language models has enabled machines to generate astonishingly realistic texts. While there are many legitimate applications of such models, there is also a rising need to distinguish machine-generated texts from human-written ones (e.g., fake news detection). However, to our best knowledge, there is currently no benchmark environment with datasets and tasks to systematically study the so-called"Turing Test"problem for neural text generation methods. In this work, we present the TuringBench benchmark environment, which is comprised of (1) a dataset with 200K human- or machine-generated samples across 20 labels {Human, GPT-1, GPT-2_small, GPT-2_medium, GPT-2_large, GPT-2_xl, GPT-2_PyTorch, GPT-3, GROVER_base, GROVER_large, GROVER_mega, CTRL, XLM, XLNET_base, XLNET_large, FAIR_wmt19, FAIR_wmt20, TRANSFORMER_XL, PPLM_distil, PPLM_gpt2}, (2) two benchmark tasks -- i.e., Turing Test (TT) and Authorship Attribution (AA), and (3) a website with leaderboards. Our preliminary experimental results using TuringBench show that FAIR_wmt20 and GPT-3 are the current winners, among all language models tested, in generating the most human-like indistinguishable texts with the lowest F1 score by five state-of-the-art TT detection models. The TuringBench is available at: https://turingbench.ist. psu.edu/
A Test for Product Design Features Perceived as Sustainable to Drive Online Purchasing Decisions

Designers are challenged to create sustainable products that succeed in the marketplace, often relying on life cycle analyses to identify engineered sustainable features while neglecting perceived-as-sustainable (PAS) features. PAS features may not contribute to engineered sustainability but are identified by customers as sustainable. In previous papers we proposed methods for extracting PAS features from online reviews using machine learning techniques and validating them using collage placement techniques. We demonstrated our methods using French presses (and other products). In this paper, we combined design and marketing approaches to test previously extracted PAS features in terms of valuing and purchasing products that include PAS features, as compared to others that do not. We built a simulated Amazon shopping experience using incentive alignment and constructed a within-subject, fractional- factorial design with a variety of product features and physical appearances. We collected data on purchase intent, willingness to pay, and sustainability rating. We found that participants opted to purchase products with PAS features more often than products with dummy features. Participants also indicated they were willing to pay more for products with PAS features and rated those products as more sustainable, despite the features not contributing to engineered sustainability. Our findings demonstrate the potential value of identifying and including PAS features in sustainable products and a new application for shopping simulation experiments in design research. We recommend that sustainable designers include both engineered and PAS features in sustainable products to align with customer needs, drive purchasing decisions, and potentially increase profitability.
IODA: A Host/Device Co-Design for Strong Predictability Contract on Modern Flash Storage

Predictable latency on flash storage is a long-pursuit goal, yet, unpredictability stays due to the unavoidable disturbance from many well-known SSD internal activities. To combat this issue, the recent NVMe IO Determinism (IOD) interface advocates host-level controls to SSD internal management tasks. While promising, challenges remain on how to exploit it for truly predictable performance. We present IODA, an I/O deterministic flash array design built on top of small but powerful extensions to the IOD interface for easy deployment. IODA exploits data redundancy in the context of IOD for a strong latency predictability contract. In IODA, SSDs are expected to quickly fail an I/O on purpose to allow predictable I/Os through proactive data reconstruction. In the case of concurrent internal operations, IODA introduces busy remaining time exposure and predictable-latency-window formulation to guarantee predictable data reconstructions. Overall, IODA only adds 5 new fields to the NVMe interface and a small modification in the flash firmware, while keeping most of the complexity in the host OS. Our evaluation shows that IODA improves the 95-99.99th latencies by up to 75x. IODA is also the nearest to the ideal, no disturbance case compared to 7 state-of-the-art preemption, suspension, GC coordination, partitioning, tiny-tail flash controller, prediction, and proactive approaches.