Miracle-dz/UniFAR-FTUs huggingface dataset:
Jogos Educativos no Ensino de Autômato Finito Determinístico: Um Estudo de Caso com o Jogo A Factory Disaster

O uso de jogos no ensino pode favorecer o aprendizado, uma vez que o caráter lúdico tende a estimular e melhorar a concentração e percepção dos alunos. Na área da Ciência da Computação o uso de jogos é frequente em diferentes tópicos, no entanto, em Linguagens Formais e Autômatos isso não é comum, dada a natureza teórica e abstrata de seus conceitos. Este trabalho apresenta o projeto e desenvolvimento de um jogo voltado ao ensino de conceitos de Autômato Finito Determinístico, ao mesmo tempo em que entretém o usuário. O jogo segue a ideia de um escape room no qual o jogador tem que achar os recursos necessários para escapar das salas. Como forma de avaliar a qualidade do jogo foi utilizado o Instrumento de Avaliação da Qualidade de Jogos Educativos (IAQJEd) com 16 participantes. O resultado obtido foi satisfatório, indicando que o jogo tem boa qualidade para finalidade de ensino.
Effects of Reed Biochar Mass Fraction on the Properties of Polypropylene/Reed Char Composites

Reed charcoal/polypropylene (RC/PP) composites were prepared by melt-blending and molding processes. The effects of RC addition (by mass fraction) on its mechanical properties were investigated and the mechanism characterized. The results showed that RC and PP were physically bonded and formed a mechanical interlocking matrix. The water absorption rate of these composites was <1% at 168 h. As the RC mass fraction increased, the tensile modulus, crystallinity, and energy storage modulus of the composites increased and then decreased, with the tensile modulus reaching a maximum of 679.4 MPa. The thermal decomposition rate peak and starting melt temperature increased by 14.8 and 2.5 °C, respectively, compared to pure PP, and the energy storage modulus reached a maximum of 3752.8 MPa at 40 wt% RC. The addition of RC in appropriate amounts improved the rigidity and thermal stability of these composites.
Is There a Role of Presepsin as a Novel Biomarker in Pediatric Sepsis?

Abstract Background Sepsis in children is a conundrum of diagnostic and therapeutic challenges. There is an exigent need for a novel biomarker that can serve as a clear distinguisher of sepsis from other non-septic inflammatory conditions. The role of presepsin as a biomarker of sepsis in children is still a matter of scientific inquiry. Aim and objectives To evaluate the diagnostic accuracy of presepsin for the prediction of septic shock, in children aged 1 month to 18 years. Materials and methods This prospective cohort study was conducted in the pediatric emergency, ward, and intensive care unit of a tertiary care hospital. We enrolled all consecutive admissions aged 1 month to 18 years with a diagnosis of sepsis and compared the presepsin, procalcitonin, and C-reactive protein (CRP) levels on admission (day 1) and 72 hours later (day 4) with the clinical outcomes. Results The mean (±SD) presepsin values in blood culture-proven sepsis patients at admission and 72 hours later were 609.77 ± 417.30 and 839 ± 748.07, respectively. The procalcitonin and presepsin levels at 72 hours in sepsis patients with shock were significantly elevated (38.2 ± 45.55 and 1129.1 ± 1133.80, respectively) as compared to those without shock (10.7 ± 25.42 and 472.5 ± 507.81, respectively), p <0.05. The receiver operating characteristic (ROC) curve analysis of presepsin at 72 hours had an area under curve (AUC) of 0.730, suggesting a fair diagnostic accuracy. Conclusion Elevated presepsin levels may indicate greater severity of sepsis, particularly in those with shock. However, it lacks diagnostic ability early in the disease and has limited prognostic potential in predicting mortality. How to cite this article Khera D, Toteja N, Singh S, Singh S, Kumar P, Sharma P, et al. Is There a Role of Presepsin as a Novel Biomarker in Pediatric Sepsis? Indian J Crit Care Med 2022;26(6):712–716.
A Comparative Analysis of Quality of Life in Women Diagnosed with Breast and Ovarian Cancer

Background: Previous studies showed that cancer significantly reduces the quality of life of patients. The purpose of this study was to analyze changes in the quality of life of women diagnosed with ovarian and breast cancer after surgical treatment followed by adjuvant cancer therapy. Methods: The study covered 220 women diagnosed with ovarian (n = 89) or breast cancer (n = 131) after surgical treatment followed by adjuvant cancer therapy (chemotherapy, radiotherapy, hormone therapy). The tools used to measure the patients’ quality of life were the standardized EORTC QLQ-C30 questionnaire, the QLQ-BR23 module for breast cancer and the QLQ-OV28 module for ovarian cancer. Results: The subjective assessment of the health and quality of life of the women was carried out using the EORTC QLQ-C30 questionnaire and the QLQ-OV28 and QLQ-BR23 modules. Women with breast cancer rated their health higher than women with ovarian cancer. The health assessment performed by the patients was not related to the type of cancer (p > 0.05). They experienced pain, dyspnea and weakness regardless of the cancer location. Moreover, women’s health status had a clinically significant impact on their family and social life, although no statistically significant differences were found between the two groups (p > 0.05). Whilst the patients with breast cancer rated their quality of life and health higher than the patients with ovarian cancer, the differences were not statistically significant (p > 0.05). Conclusions: Changes in the quality of life of women with breast and ovarian cancer concern the physical sphere, hobbies, fatigue/rest, pain, family and social spheres, and material conditions. It is necessary to support specialists at every stage of treatment of these patients, which may improve the results of the treatment and patients’ perception of health and quality of life.
Molecular Study to Detect Escherichia coli in Diarrheic Children and its Antibiotic Resistance

Diarrheal diseases can lead to infections and cause morbidity and mortality in children. Diarrheagenic Escherichia coli (DEC) is an etiological agent, which is considered the major causative agent of diarrhea in children in some developing countries. The aims of this work were to estimate Escherichia coli (E. coli) causing diarrhea in children less than 5 years old, and to detect some biofilm virulence factors and the effect of some antibiotics. For the methodology, a total of 112 specimens were collected from children from two health centers, Al-Zahraa Teaching Hospital and Public Health Laboratory (located in Al-Kut city/ and the Wasit province in Iraq). All specimens were grown on simple and rich media. A total of 43 (38.4%) E. coli isolates were identified using different traditional methods, such as biochemical tests and 16S rRNA sequencing. Polymerase chain reaction (PCR) testing was used to detect some virulence factor genes that play an important role in the pathogenesis of diarrheic E. coli e.g., 16S rRNA, bfpA, and eaeA. In this study, several antibiotics were used to estimate the sensitivity and resistivity of E. coli isolates. A total of 43 isolates were fully identified as E. coli. These samples were used to detect the virulence factor genes, and 31 (72.1%) and 29 (29.4%) isolates carried bfpA and eaeA, respectively. The preponderance of E. coli isolates were completely resistant to penicillin 43 (100%). Additionally, 33 (76.7%) and 27 (62.8%) isolates were resistant to cephalothin and amoxycillin-clavulanic acid, respectively. Furthermore, the isolates of E. coli isolates showed different levels of sensitivity to antibiotics, including polymyxin B 40 (93%), norfloxacin 38 (88.4%), gentamycin 26 (60.4%), and meropenem 22 (51.2%). In conclusion, diarrheagenic E. coli isolates were the prevalent among diarrheic children. Most isolates showed varying results for the presence of virulence factors. In addition, all isolates were resistant to penicillin and sensitive to polymyxin B.
Analysis of Depth Cameras for Proximal Sensing of Grapes

This work investigates the performance of five depth cameras in relation to their potential for grape yield estimation. The technologies used by these cameras include structured light (Kinect V1), active infrared stereoscopy (RealSense D415), time of flight (Kinect V2 and Kinect Azure), and LiDAR (Intel L515). To evaluate their suitability for grape yield estimation, a range of factors were investigated including their performance in and out of direct sunlight, their ability to accurately measure the shape of the grapes, and their potential to facilitate counting and sizing of individual berries. The depth cameras’ performance was benchmarked using high-resolution photogrammetry scans. All the cameras except the Kinect V1 were able to operate in direct sunlight. Indoors, the RealSense D415 camera provided the most accurate depth scans of grape bunches, with a 2 mm average depth error relative to photogrammetric scans. However, its performance was reduced in direct sunlight. The time of flight and LiDAR cameras provided depth scans of grapes that had about an 8 mm depth bias. Furthermore, the individual berries manifested in the scans as pointed shape distortions. This led to an underestimation of berry sizes when applying the RANSAC sphere fitting but may help with the detection of individual berries with more advanced algorithms. Applying an opaque coating to the surface of the grapes reduced the observed distance bias and shape distortion. This indicated that these are likely caused by the cameras’ transmitted light experiencing diffused scattering within the grapes. More work is needed to investigate if this distortion can be used for enhanced measurement of grape properties such as ripeness and berry size.
International overview on the legal framework for highly automated vehicles

The evolution of Autonomous and automated technologies during the last decades has been constant and maintained. All of us can remember an old film, in which they shown us a driverless car, and we thought it was just an unreal object born of filmmakers imagination. However, nowadays Highly Automated Vehicles are a reality, even not in our daily lives. Hardly a day we don’t have news about Tesla launching a new model or Google showing the new features of their autonomous car. But don’t have to travel far away from our borders. Here in Europe we also can find different companies trying, with more or less success depending on with, not to be lagged behind in this race. But today their biggest problem is not only the liability of their innovative technology, but also the legal framework for Highly Automated Vehicles. As a quick summary, in only a few countries they have testing licenses, which not allow them to freely drive, and to the contrary most nearly ban their use. The next milestone in autonomous driving is to build and homogeneous, safe and global legal framework. With this in mind, this paper presents an international overview on the legal framework for Highly Automated Vehicles. We also present de different issues that such technologies have to face to and which they have to overcome in the next years to be a real and daily technology.
System-Wide Evaluation of Inertia Support Potentials from Wind Farms

In order to limit anthropogenic climate change as well as the dependency on fossil fuels, the wind power generation is rising world wide. Since modern wind turbines are usually variable speed wind turbines, which are connected to the grid via a converter, this causes a decrease in grid coupled inertia. Because decreased inertia causes faster and greater frequency changes for the same disturbances, it is discussed widely how variable speed wind turbines can contribute inertia to the power system. In this project report, inertial response from wind turbines at the system level is investigated with a focus on the swedish power system. An existing database of wind turbines and a metereological model containing wind speeds on defined grid points are used to determine the operating points of all wind turbines included in the database for each hour in the investigated time span 2010 to 2015. Furthermore, the performance of these turbines in three different fixed trajectory inertial response approaches is simulated, aggregated to the system level and analysed accordingly. In this work it is shown that a reliable amount of inertial support in relation to their production can be expected from wind turbines. Although the number of online wind turbines and the total energy production from wind turbines are not strongly correlate, it could been proven that for the fixed power and time inertial response approach a linear relation between the aggregated inertial response capability and total energy production exists. The support power from wind turbines amounts under this conditions to 1:13 times their steady state power. It could further been shown that the assumed inertial response strategies would allow for the compensation of a dimensioning fault.
A Novel Approach for Surface Integrity Monitoring in High-Energy Nanosecond-Pulse Laser Shock Peening: Acoustic Emission and Hybrid-Attention CNN

The high energy, transient, and nanosecond pulse of laser shock peening (LSP) renders real-time monitoring of material surface integrity challenging. Along these lines, this article proposes a novel method for real-time evaluation of the surface quality in the LSP process based on the multiple acoustic emission (AE) technique and hybrid attention-based convolutional neural networks (HACNN). First, a new quality index, surface hardness integrity (SHI) is constructed to fully characterize both the hardening rate and the impact depth of the material surface, while a good linear relationship is demonstrated between SHI and AE. Then, a feature extraction method, called wavelet packet energy cepstrum (WPEC), is proposed that requires minor signal processing expertise while being able to adaptively match the modal distribution of the broadband AE signals. Next, WPEC is fed into HACNN, where HA consists of channel attention and multiscale spatial attention (MSA). MSA combines the information flow at the global time, local time, and local frequency. Moreover, numerous comparisons were conducted with several traditional cepstrum and advanced attention mechanisms. The effectiveness of the proposed method is carefully verified by the LSP experiments for 7075 Al alloy achieving the highest average accuracy of 99.33% for the identification of four types of SHI. In addition, the sensitivity of HA in high-frequency event onset and offset is demonstrated by visualizing the gradient weights.
Inhibition of digestive enzymes (α-amylase, α-glucosidase, lipase, trypsin) by aqueous Hibiscus sabdariffa L. (Malvaceae) extract

A considerable portion of the world population uses medicinal plants to treat chronic diseases. In this context, hibiscus (Hibiscus sabdariffa L. - Malvaceae) stands out for its supposed hypoglycemic and slimming effect. The present work aimed to carry out enzyme inhibition tests for aqueous hibiscus extracts, as a possible mechanism of action related to the supposed slimming and hypoglycemic effects. The inhibition of four digestive enzymes (α-amylase, α-glucosidase, lipase and trypsin) was tested before and after exposure to a simulated gastric fluid. In addition, a molecular anchorage study was carried out, in order to highlight possible molecular interactions between target and ligand. The results showed that the aqueous extract of hibiscus, in the proportion 1:10 (w/v), inhibits only α-glucosidase. It was observed that cyanidin-3-sambubioside, has interaction with the enzyme with properties similar to acarbose, which corroborates the possibility of the presence of an inhibitory effect in the aqueous extract of hibiscus.
Seroprevalence and risk factors of syphilis coinfection in people living with HIV

Objectives: This study aimed to determine syphilis coinfection prevalence in people living with HIV (PLHIV) and risk factors for coinfection. Methods: This single-center retrospective cohort study screened PLHIV who were monitored in our center between March 2000 and February 2020 via the hospital’s database and analyzed them by grouping as TPHA-positive and TPHA-negative. TPHA positivity was considered as indicative of Treponema pallidum exposure. Results: The study included 474 PLHIV of whom median age (IQR) was 37 (30-47), and 429 (90.5%) were male. Of the male participants, 206 (47.9%) were MSM. The syphilis coinfection rate was 30.2% (143/474). Among the participants with syphilis coinfection, 80 (16.9%) were found to be coinfected with syphilis at the time of their HIV diagnosis, while 63 (13.3%) got infected with syphilis at a median (IQR) time of 60 (36-84) months into their HIV follow-up and treatment. Syphilis coinfection was related to being male (p<0.001), MSM (p=0.008) and single (p=0.007). Regular condom use was inversely related to syphilis coinfection (p=0.002). Conclusion: HIV and syphilis have similar transmission routes, and HIV and syphilis coinfection is common among men, MSM and people who do not use condoms. PLHIV should be tested regularly for syphilis and informed about risky sexual behaviors and protection methods. Abstract
234-OR: Noninvasive Hypoglycemia Detection during Real Car Driving Using In-Vehicle Data

Aim: To develop a non-invasive machine learning (ML) approach to detect hypoglycemia during real car driving based on driving (CAN) , and eye and head motion (EHM) data. Methods: We logged CAN and EHM data in 21 subjects with type 1 diabetes (18 male, 41 ± yrs, A1c 6.8 ± 0.7 % [51 ± 7 mmol/mol]) during driving in eu- (EU) and hypoglycemia (< 3.0 mmol/L, HYPO) . Participants drove in a car (Volkswagen Touran) supervised by a driving instructor on a closed test-track. Using CAN and EHM data, we built ML models to predict the probability of the driver being in HYPO. To make our approach applicable to different generations of cars, we present 3 ML models: first, a model combining CAN+EHM, representing the modern car with integrated camera. Second, a CAN model using driving data only, since modern cars are not generally equipped with EHM tracking. Third, anticipating that autonomous driving will limit the role of CAN data in the future, we tested a model solely based on EHM. Results: Mean BG in EU and HYPO was 6.3 ± 0.8 mmol/L and 2.5 ± 0.5 mmol/L (p< 0.001) , respectively. The model CAN+EHM achieved an area under the receiver operating characteristic curve of 0.88 ± 0.05, sensitivity of 0.70 ± 0.30, and specificity of 0.83 ± 0.in detecting HYPO. Further results are in Fig. 1. Conclusion: We propose ML-based approaches to non-invasively detect HYPO from driver behavior, applicable to contemporary cars and anticipating developments in automotive technology. V.Lehmann: None. E.Fleisch: None. T.Kowatsch: Advisory Panel; Pathmate Technologies AG, Research Support; CSS Insurance, Stock/Shareholder; Pathmate Technologies AG. S.N. Lagger: None. M.Laimer: None. F.Wortmann: None. C.Stettler: None. T.Zueger: None. M.Maritsch: None. M.Notter: None. S.Schallmoser: None. C. Bérubé: None. C.Albrecht: None. M.Kraus: None. S.Feuerriegel: None. Swiss National Science Foundation (SNF CRSII5_183569) , Swiss Diabetes Foundation, Diabetes Center Berne, Automobile Club Switzerland (ACS) , Federal Department of Defence, Civil Protection and Sport (DDPS) and Department of Research of the University Hospital Berne
Algorithm for creating a single image of the cutting machine processing field and automated object detection when cutting parts

The article proposes an algorithm for forming a combined image obtained based on scanning the cutting table's working field and detecting contour of object. The creation of a single image, obtained in an automated mode, allows you to analyze objects and perform the initial formation of the shape in a vector or raster form. The process of creating a merged image includes the following operations: preliminary processing, to reduce the influence of noise component associated with lens contamination and interference on the sensitive matrix; simplification of images and selection of areas with a large number of local features; search for stable anchor points; formation of image transformation matrices; combining data.
The Bacterial Composition and Diversity in a Eucalyptus pellita Plantation in South Sumatra, Indonesia

Plantation forests have been strongly established in Indonesia, with Acacias and Eucalyptus as the most common species. Using a single species in a large plantation may affect its sustainability because of the threat from biotic and abiotic factors. The soil microbiome is key to an ecological process strongly associated with both biotic and abiotic factors. However, research aiming to understand soil microbial communities in plantation forests in Indonesia is still limited. We analyzed the soil bacterial communities from six sites of plantation forests and three sites of conservation areas representing natural forest ecosystems. We produced approximately 140,136 reads from nine soil samples and generated 2385 total OTUs from the reads. The ten most abundant phyla were Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi, Firmicutes, Bacteroidetes, Verrucomicrobia, Nitrospirae, Gemmatimonadetes, and Planctomycetes. At the phylum level, the relative abundance of microbes in E. pellita plantation forests and natural forests was similar, except for Bacteroidetes. The richness and diversity of the microbiomes were slightly lower in the plantation forests than in the natural forests. Minor variations in the soil’s chemical properties may be responsible for the variations in the microbiome between natural and plantation forests. According to RDA, the K, total N, and organic C were positively correlated with the bacterial diversity, while the pH was negatively correlated. There was a positive correlation between the abundance of Bacteroidetes and the K content. However, there is not much information regarding this relationship.