Miracle-dz/UniFAR-FTUs huggingface dataset:
PENGARUH SIMULASI PELATIHAN BANTUAN HIDUP DASAR (BHD) TERHADAP MOTIVASI DAN SKILL RESUSITASI JANTUNG PARU (RJP) PADA KARANG TARUNA RW 06 KAMPUNG UTAN KELURAHAN KRUKUT DEPOK

Angka kejadian Out of Hospital Cardiac Arrest (OHCA) terjadi di rumah dan di tempat umum sebanyak 80%. Kejadian OHCA dapat ditangani dengan melakukan tindakan RJP saat awal serangan, namun permasalahannya adalah ketidaktahuan orang awam mengenai cara menolong atau tehnik RJP yang tepat. Untuk itu pelatihan BHD di komunitas Karang Taruna dinilai penting untuk dilakukan agar terbentuk bystander di lingkungan masyarakat. Tujuan penelitian ini untuk menganalisis pengaruh simulasi pelatihan BHD terhadap motivasi dan skill RJP. Desain penelitian menggunakan quasi experiment with one group dengan pretest-posttest. Sampel berjumlah 23 responden yang merupakan anggota Katar RW 06, metode pengumpulan data menggunakan kuesioner dan lembar observasi. Analisa data menggunakan uji T-Independent, T-Dependent, Wilcoxon Sign Test, dan Korelasi Pearson. Hasil penelitian uji T-Dependent didapatkan nilai p value < 0.05. Kesimpulan menunjukan bahwa terdapat pengaruh yang signifikan antara simulasi BHD terhadap motivasi (p=0.000), skill (p=0.000), dan pengetahuan (p=0.000) di RW 06 Krukut. Saran agar pihak Karang Taruna menggunakan pengetahuan dan pengalaman yang didapat dari pelatihan simulasi BHD sehingga dapat meningkatkan motivasi dan skill RJP untuk menolong korban henti jantung, untuk peneliti selanjutnya dapat meneliti faktor lain yang dapat meningkatkan skill dan motivasi.Kata Kunci: BHD, Karang Taruna, Motivasi, Simulasi RJPAngka kejadian Out of Hospital Cardiac Arrest (OHCA) terjadi di rumah dan di tempat umum sebanyak 80%. Kejadian OHCA dapat ditangani dengan melakukan tindakan RJP saat awal serangan, namun permasalahannya adalah ketidaktahuan orang awam mengenai cara menolong atau tehnik RJP yang tepat. Untuk itu pelatihan BHD di komunitas Karang Taruna dinilai penting untuk dilakukan agar terbentuk bystander di lingkungan masyarakat. Tujuan penelitian ini untuk menganalisis pengaruh simulasi pelatihan BHD terhadap motivasi dan skill RJP. Desain penelitian menggunakan quasi experiment with one group dengan pretest-posttest. Sampel berjumlah 23 responden yang merupakan anggota Katar RW 06, metode pengumpulan data menggunakan kuesioner dan lembar observasi. Analisa data menggunakan uji T-Independent, T-Dependent, Wilcoxon Sign Test, dan Korelasi Pearson. Hasil penelitian uji T-Dependent didapatkan nilai p value < 0.05. Kesimpulan menunjukan bahwa terdapat pengaruh yang signifikan antara simulasi BHD terhadap motivasi (p=0.000), skill (p=0.000), dan pengetahuan (p=0.000) di RW 06 Krukut. Saran agar pihak Karang Taruna menggunakan pengetahuan dan pengalaman yang didapat dari pelatihan simulasi BHD sehingga dapat meningkatkan motivasi dan skill RJP untuk menolong korban henti jantung, untuk peneliti selanjutnya dapat meneliti faktor lain yang dapat meningkatkan skill dan motivasi.
Automated system for measuring integral pain index of patients during general anesthesia

For optimal control of the analgesia level during general anesthesia an objective assessment of the realtime patient’s current state is necessary. Such estimates are based on the production and processing of large amounts of data. The authors developed requirements for an automated system for measuring the level of pain experienced by patients during anesthesia, methods and algorithms for implementing such a system. To assess the patient’s condition, a set of indicators is used: flow data on the respiratory cycle of the patient, the spectral characteristics of the electroencephalogram and electrocardiogram; indicators of electrical conductivity of the skin; characteristics of the pulse wave; dynamics of changes in mean blood pressure, heart rate. The article presents a block diagram of the operation of the module for calculating the integral indicator of pain and shows the results of preclinical tests.
Modeling and validation of a new reconfigurable patch antenna through equivalent lumped circuit‐based design for minimum tuning effort

This study presents a modeling of a new reconfigurable patch antenna with equivalent lumped circuit. Instead of intuitive approaches, including structural changes used in the literature, the proposed reconfigurable antenna design is based on minimum tuning effort using only capacitance adjustments. The proposed design resolves impedance mismatch problem, which occurs due to the nature of using several frequencies by only capacitance adjustments rather than physical structure adjustments. Reconfigurable patch antenna for 2.45 GHz (Wi‐Fi), 3.6 GHz (Wi‐max and 5G), 5.4 GHz (WLAN and 5G) was considered for novel design strategy. A complete equivalent circuit model is configured and validated through AWR software. Full wave analysis of the proposed antenna is performed using CST software. A prototype of the proposed antenna is also fabricated on a FR4 substrate with the dimensions of 48.19 x 38.36 x 1.53 mm3 and measured to validate the full wave analysis and circuit theory solution results. It is shown that the equivalent circuit model, full wave analysis, and measurement results are in good agreement.
A Survey on Spark Ecosystem: Big Data Processing Infrastructure, Machine Learning, and Applications

With the explosive increase of big data in industry and academic fields, it is important to apply large-scale data processing systems to analyze Big Data. Arguably, Spark is the state-of-the-art in large-scale data computing systems nowadays, due to its good properties including generality, fault tolerance, high performance of in-memory data processing, and scalability. Spark adopts a flexible Resident Distributed Dataset (RDD) programming model with a set of provided transformation and action operators whose operating functions can be customized by users according to their applications. It is originally positioned as a fast and general data processing system. A large body of research efforts have been made to make it more efficient (faster) and general by considering various circumstances since its introduction. In this survey, we aim to have a thorough review of various kinds of optimization techniques on the generality and performance improvement of Spark. We introduce Spark programming model and computing system, discuss the pros and cons of Spark, and have an investigation and classification of various solving techniques in the literature. Moreover, we also introduce various data management and processing systems, machine learning algorithms and applications supported by Spark. Finally, we make a discussion on the open issues and challenges for large-scale in-memory data processing with Spark.
Characterization of Static and Dynamic Behavior of 1200 V Normally off GaN/SiC Cascode Devices

Systematic characterizations of a cascode device with a low-voltage enhance-mode (E-mode) <italic>p</italic>-GaN gate high-electron mobility transistor as the control device and a high-voltage (HV) depletion-mode (D-mode) silicon carbide junction field effect transistor (JFET) as the voltage blocking device are presented in this article. The demonstrated device with a breakdown voltage rating of 1200 V and a static <sc>on</sc>-resistance (<italic>R</italic><sub>ON</sub>) of 100 mΩ features small device capacitances with fast switching speed, avalanche breakdown capability, thermally stable threshold voltage (<italic>V</italic><sub>TH</sub>), and no dynamic <italic>R</italic><sub>ON</sub> degradation. To identify its safe operation in the <sc>off</sc>-state with a high drain bias, the <sc>off</sc>-state middle point voltage (<italic>V</italic><sub>M</sub>) between the E-mode device drain and D-mode device source is investigated. A relatively low <sc>off</sc>-state <italic>V</italic><sub>M</sub> is achieved under both static and dynamic modes. In addition to the device-level characterization, a custom-designed double-pulse test circuit is built to evaluate the transient switching performance of the cascode device. Optimal gate drive conditions are proposed to 1) overcome the drain bias induced positive dynamic <italic>V</italic><sub>TH</sub> shift; and 2) suppress the increased dynamic <sc>off</sc>-state leakage current (<italic>I</italic><sub>OFF</sub>) induced by <sc>on</sc>-state hole injection. Under 800 V/16 A testing conditions, high switching speed with the drain voltage peak slew rates of 72 V/ns during turn-<sc>on</sc> and 121 V/ns during turn-<sc>off</sc> is achieved.
Prevalence and associated risk factors for bovine brucellosis in the State of Pernambuco, Brazil

This study was conducted to characterize the epidemiology of bovine brucellosis in the state of Pernambuco, Brazil. The state was divided into three regions, and in each region, approximately 300 properties were randomly sampled. From these selected properties, a pre-established number of animals were randomly selected and blood serum samples were obtained. A total of 3,901 animals were selected from 900 properties. For each selected property, an epidemiological questionnaire was administered to assess the type of farming, the animal husbandry practices and the sanitary practices that could be associated with the presence of brucellosis infection. The testing protocol consisted of screening the samples with a buffered acidified plate antigen test and retesting the positive samples with a complement fixation test (CF). One positive animal was enough to define an infected herd. The prevalence rates of infected herds and animals in the state were 4.5% [3.2; 6.4%] and 1.4% [0.7; 2.7%], respectively. By region, the prevalence rates of infected herds and animals, respectively, were as follows: Zona da Mata, 3.3% [1.8; 6.1%] and 1.7% [0.5; 3.0%]; Agreste, 7.4% [4.9; 10.9%] and 1.9% [0.8; 3.0%]; and Sertao, 1.3% [0.5; 3.5%] and 0.7% [0.0; 1.6%]. Flooded pastures (OR = 2.86 [1.37; 6.42]) and the presence of 13 or more females in the herd (3rd quartile) (OR = 2.65 [1.19; 5.89]) were identified as risk factors. The existence of veterinary care emerged as a protective factor against bovine brucellosis in the state of Pernambuco (OR = 0.24 [0.10; 0.58]).
A quadratic reciprocity theorem for arithmetical logic

I have introduced in (Gauthier 2015, see [6]) an interpretation of a logical calculus in terms of congruent arithmetic for a modular polynomial logic. The motive was to develop a purely syntactical approach to the internal consistency of arithmetic. Such an arithmetic was defined as classical Fermat-Kronecker (F-K) arithmetic, that is the general theory of homogeneous polynomials (forms) with infinite descent as a proof procedure. In particular, I treated logical implication (the conditional) as a congruence relation that is interpreted by infinite descent on the binomial expansion. The objective was to endow theorems and proofs in logic with a numerical content. Mathematics Subject Classification: 11A15,11R09, 03F03, 03F35
Doing hair, doing race: the influence of hairstyle on racial perception across the US

ABSTRACT Hair is an easily changeable “racial marker” feature. Although growing interdisciplinary research suggests that hairstyle influences how one is racially perceived, extant methodological practices in racial perception research reduce external validity. This study introduces new experimental and analytical procedures to test the effect of hairstyle on racial perception across racial contexts. Over 1,000 participants from primarily white, black and multiracial test sites racially categorized a diverse group of women from matched pairs of pictures in which the women have different hairstyles. Results from multilevel regression show that altering hairstyle significantly alters how participants perceive mixed-race women, Latinas, most black and some white women and that this varies by racial context with perceptions of race being less swayed by hairstyle in the multiracial context. Our research thus demonstrates that doing hair is a context-dependent part of “doing race” that has theoretical, methodological, and legal implications.
Industrial Internet of Things Common Concepts, Prospects and Software Requirements

The manufacturing and many other critical Infrastructures industries are posed to introduce the initiative popularly known as Industry 4.0 or industrial Internet of things. In developed nations, Industry Internet of thing technologies have already been implemented in varieties of industries like health care, logistics, avionics, waste management, military, smart cities and many other fields. So far, the initiative has provided various benefits that include improved efficiency, productivity and cost reduction. However, the prospective transformation of Internet of things Technology would see some change in the way companies approach manufacturing and other industries in terms of in-house software development, security design and implementation. Considering the fact that Industry 4.0 belong to the family of critical infrastructures, ICT application development, security design and implementation will always be complex, costly, large in scope, involves heterogonous network of things that encompasses dealing with a diverse set of Technological components. This complexity may result in misconfiguration, misappropriation and misconception of facts on part of users, software developer and security architects. For this reason, this paper details information technology component of Industry 4.0 framework with an objective to amplify and clear misunderstanding of key terminologies and the basic composition of industry 4.0 framework. The study also highlights industrial Internet of things prospects and barriers and articulates effective requirement elicitation process for application customization, development, and technological fusion and Security solutions implementation. The methodology of this paper is based on two research techniques namely literature review and a study on application scenarios from research communities and industries. Because of these, simple and effective model for requirement engineering is proposed.
Pressure training for performance domains: A meta-analysis.

Studies have tested pressure training (PT) interventions in which performers practice physical or technical skills under simulated psychological pressure, but research has not yet synthesized the results of these studies. This meta-analysis assessed the magnitude of PT’s effect on performance in sport and other high-pressure domains (e.g., law enforcement). A secondary purpose was to investigate how domain, dose, experience, and the type of task moderated the effectiveness of interventions. A study was included if it was peer-reviewed, conducted a PT intervention for sport or another high-pressure domain, and quantitatively compared a PT group with a control group on posttests under pressure. In all, 14 studies in sport (k = 10) and law enforcement (k = 4) were included. Participants (n = 394) were novices, semiprofessional athletes, elite athletes, and police officers. After removal of an outlier, the mean effect was medium (g = 0.67, 95% confidence interval [0.43, 1.12]) with low heterogeneity (I2 = 17.1%). Subgroup analysis did not indicate clear moderators of performance but did reinforce that PT can benefit both novice and experienced participants on open and closed tasks across different domains. The results suggest coaches and instructors should create pressurized training environments rather than relying on greater amounts of training to help performers adjust to pressure. Future research should develop practical pressure manipulations, conduct retention tests, and measure performance in competitive or real-life scenarios.
Enhanced Job Ranking Backfilling Based on Linear and Logarithmic Ranking Equations

: Grid system is used by many researchers’ and scholars all over the world to solve the complicated and complex problems in different sciences. Job ranking backfilling is the most used model by many researchers in grid system to improve the performance of job scheduling algorithm. The model aims on serving the smallest job in the queue. As a second improvement of job backfilling, researchers proposed job ranking backfilling that serve job based on ranking equation. This paper proposes an enhance job ranking algorithm based on using linear and logarithmic ranking equations. Both proposed ranking equations used curve estimation model to predict on the variables’ coefficients. By simulation and after different tests, the average results of job ranking backfilling with linear ranking equation outperform conventional job ranking backfilling with improvement equal 3.2% and 56.53% in total execution time and average waiting time, respectively. In addition, job ranking backfilling with logarithmic ranking equation shows average improvement equal 1.78% and 46.62% in total execution time and average waiting time, respectively. The results indicate that the proposed ranking equations would improve conventional job ranking backfilling in high and low demand grid system under different conditions.
Quantitative Ultrasound Characterization and Monitoring of Locally Advanced Breast Cancer

Traditional assessment of tumour response to cancer therapy is based on tumour size reduction, which takes several weeks to become clinically sign ificant. In this thesis, novel ultrasound backscatter signal analysis and machine learning te chniques were developed to characterize breast tumours and detect early changes correlated to resp nse. In the first study, tumour cell death was induced i n human breast cancer tumour-bearing mice, using human mimicking chemotherapy drugs. Treatment -r la ed changes in quantitative ultrasound (QUS) parameters, including change in av erage acoustic concentration (AAC) and heterogeneity index, revealed a strong correlation to histologically determined cell death extent (r2=0.64). In the second study, radiofrequency (RF) ul trasound data were acquired from locally advanced breast cancer (LABC) patients prior to tre atm nt. Results suggested that a multiparameter QUS model can sensitively (88%) and specifically (91%) differentiate breast tumours from surrounding normal tissue. Furthermore , a local texture based QUS model was demonstrated as a promising tumour grade predictor (86% accuracy).
Self-regulated learning in blended learning approach

Blended learning allowed students to manage their own pace of learning especially in the online session. This might foster students’ self-regulated learning. This claim, however, need to be investigated with more empirical data. This study, therefore, intended to examine the effect of blended learning on students’ self-regulated learning. A quasi-experiment with the pretest and posttest group design was employed in this study. A total of 115 grade 10 students was cluster randomly selected among senior high schools in the city of Yogyakarta. Two different classes of samples were set, namely experiment class using blended learning android-based-game, and control class using offline class. The students in the two classes learn the same material that is about Function and its graph. Data of students’ self-regulated learning was collected through a questionnaire with five Likert scale. The data was analyzed using Analysis of Variance (ANOVA) technique and it was found that: there is a significant difference of self-regulated learning between students who learn in blended class and those in offline class. This study offers insights on the use of blended learning to foster the students’ self-regulated learning especially in learning mathematics. Nevertheless, the design of blended learning need to considered particularly when and what kind of learning material should be delivered online and offline.
Analysis of Oil Spill and Sea Ice Measurements Using Full-Polarimetric and Hybrid-Polarity Synthetic Aperture Radar data

Paper 2 og Paper 3 er ikke publisert enda, men sendt inn til en journal til review. Paper 2 og Paper 3 (inkludert i selve PhD-avhandlingen) skal dermed ikke publiseres online pa munin-siden hvis oppgaven blir godkjent.
The application potential of self-glazed zirconia crowns confirmed by easy grinding and polishing of the enamel-like surface

The surface profile roughness (Ra), surface area roughness (Sa), and surface topography of newly developed as-prepared, ground, and polished self-glazed zirconia (SGZ) were evaluated using a profilometer, 3D optical surface profiler, and SEM, with conventional dry-milled zirconia (CZ) as a reference. A statistical analysis was conducted using repeated measures analysis of variance (ANOVA) and the Bonferroni test (α = .05). Results revealed that the material (p = .005), clinical adjustment procedure (p < .001), and interaction between factors (p < .001) had statistically significant effects on the Ra values. SGZ showed lower Sa values than CZ during the same period. Ten patient cases involving the restoration of the monolithic anatomic contour SGZ crowns were investigated. All crowns remained functional until the latest clinical follow-up and no further antagonist wear was observed. Thus, SGZ had relatively lower surface roughness, which was also more easily altered than that of CZ.
Confirming Bias Without Knowing? Automatic Pathways Between Media Exposure and Selectivity

This study moves beyond previous research by demonstrating how prior exposure to stereotypical content can reinforce the selection of comparable biased news content and by clarifying its intergroup and interpersonal consequences. With two experiments (N = 236, N = 270), we show that media effects and selectivity of biased media content about Arabic migrant workers are connected by automatic (i.e., implicit) stereotypes. The findings reveal that exposure to moderate doses of stereotypic news primes affects the selection of biased news via implicit stereotypes and subsequently shifts intergroup and interpersonal outcomes in the direction of the activated biased beliefs. These effects did not surface for high doses of stereotypic news primes, suggesting that individuals resist and inhibit activation processes when exposure is perceived to be too extreme. As subtle forms of bias are omnipresent in news environments and implicit stereotypes operate partly under the radar of conscious awareness, they may affect selection without individuals being aware of it. The findings imply that audiences’ biased selectivity should not be seen in isolation from prior media exposure.