Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time 3D Tracking of Simple Objects with an RGB Camera

Nowadays, algorithms that obtain 3D information of objects, have a high importance in applications in different areas, such as in sports, robotics, medicine, among others. This work, intends to improve a monocular region-based tracking algorithm using an RGB camera. The algorithm to be improved, derives from a particle ﬁlter where each particle represents a hypothesis of the state of the object in 3D, which allows the use of realistic 3D motion models. However, the literature mentions that the particle ﬁlter (PF) uses a very limited importance distribution to propagate the particles, which easily leads to the ﬁlter degenerating and losing track of the object. Given the limitation of the PF, an unscented particle ﬁlter (UPF) is proposed, this one obtains an approximation to the optimal importance distribution, by adding a current observation of the state. Since, only the importance distribution is different, the observation model remains identical, where a method based on the color distributions of the interior and exterior regions of the object’s silhouette, is used to calculate the likelihood of each particle. In order to compare the proposed algorithm with the previous one, both are implemented in this work and several real and simulated experiments with a simple object are performed. From the results obtained, is shown that the ﬁlters are successful, with the UPF being more robust against degeneration, different numbers of particles and different adjustments in the interior and exterior regions of the object’s silhouette.
Sistem Prediksi Kualitas Kopra Putih Menggunakan k-Nearest Neighbor ( k -NN)

Area dan Perimeter). R, G, dan B masing-masing merupakan besaran yang menyatakan nilai intensitas warna merah, hijau, dan biru. Area suatu objek adalah jumlah piksel penyusun objek tersebut dan unit umum digunakan adalah piksel, karena sejumlah piksel tadi membentuk suatu luasan. Area dapat mencerminkan ukuran atau berat objek sesunggunhnya. Hal ini berlaku untuk benda pejal dengan bentuk yang hampir seragam, tetapi tidak demikian untuk benda yang berongga. Perimeter, adalah bagian terluar dari suatu objek yang bersebelahan dengan piksel latar. Metode klasifikasi yang digunakan untuk melakukan prediksi adalah k-Nearest Neighbor . Metode k-Nearest Neighbor memiliki prinsip kerja mencari kemiripan antara data yang akan dievaluasi dengan data sampelnya. Nilai k yang digunakan pada penelitian ini adalah k= 1, k=3 dan k=5. Pengukuran kemiripan menggunakan Euclidean Distance , yang merupakan selisih nilai piksel 2 vektor ciri yang dievaluasi. Pengujian hasil prediksi menggunakan metode Holdout . Akurasi yang diperoleh pada saat menggunakan k=1 sebesar 93,33%, pada k = 3 sebesar 83,33%, dan pada k=5 sebesar 81,67%. Akurasi terbaik untuk prediksi kopra putih menggunakan metode k-nearest neighbor didapat pada k=1, yakni sebesar 93,33%. Kata kunci: Prediksi, Klasifikasi
Ser/Thr Kinase-Dependent Phosphorylation of the Peptidoglycan Hydrolase CwlA Controls Its Export and Modulates Cell Division in <named-content content-type='genus-species'>Clostridioides difficile</named-content>

Cell growth and division require a balance between synthesis and hydrolysis of the peptidoglycan (PG). Inhibition of PG synthesis or uncontrolled PG hydrolysis can be lethal for the cells, making it imperative to control peptidoglycan hydrolase (PGH) activity. The synthesis or activity of several key enzymes along the PG biosynthetic pathway is controlled by the Hanks-type serine/threonine kinases (STKs). In Gram-positive bacteria, inactivation of genes encoding STKs is associated with a range of phenotypes, including cell division defects and changes in cell wall metabolism, but only a few kinase substrates and associated mechanisms have been identified. We previously demonstrated that STK-PrkC plays an important role in cell division, cell wall metabolism, and resistance to antimicrobial compounds in the human enteropathogen Clostridioides difficile. In this work, we characterized a PG hydrolase, CwlA, which belongs to the NlpC/P60 family of endopeptidases and hydrolyses cross-linked PG between daughter cells to allow cell separation. We identified CwlA as the first PrkC substrate in C. difficile. We demonstrated that PrkC-dependent phosphorylation inhibits CwlA export, thereby controlling hydrolytic activity in the cell wall. High levels of CwlA at the cell surface led to cell elongation, whereas low levels caused cell separation defects. Thus, we provided evidence that the STK signaling pathway regulates PGH homeostasis to precisely control PG hydrolysis during cell division. IMPORTANCE Bacterial cells are encased in a PG exoskeleton that helps to maintain cell shape and confers physical protection. To allow bacterial growth and cell separation, PG needs to be continuously remodeled by hydrolytic enzymes that cleave PG at critical sites. How these enzymes are regulated remains poorly understood. We identify a new PG hydrolase involved in cell division, CwlA, in the enteropathogen C. difficile. Lack or accumulation of CwlA at the bacterial surface is responsible for a division defect, while its accumulation in the absence of PrkC also increases susceptibility to antimicrobial compounds targeting the cell wall. CwlA is a substrate of the kinase PrkC in C. difficile. PrkC-dependent phosphorylation controls the export of CwlA, modulating its levels and, consequently, its activity in the cell wall. This work provides a novel regulatory mechanism by STK in tightly controlling protein export.
X-ray Diffraction and Photoluminescence Studies on ZnO Nanoparticles Synthesized by Sol Gel Auto Combustion Method Glycine Assisted Chelating Agent

Zinc oxide (ZnO) nanoparticles were synthesized via a sol gel auto combustion method Glycine assisted chelating agent/fuel. The obtained ZnO nanoparticles were characterized by X-ray powder Diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and photoluminescence spectroscopy technique. The XRD patterns indicate that ZnO nanoparticles was of good crystallinity and having hexagonal wurtzite structure with single phase. The lattice parameter and other structural parameters were calculated from XRD data. The average crystallite size was found 24 nm. FTIR spectra showed the characteristic vibrations frequency band of Zn–O at 453 cm. Photo luminescence spectrum showed that two emission peaks at 380 nm and 393 nm, which are ascribed to near band edge transitions. The peak observed at 410 nm is attributed to a violet emission of ZnO nanoparticles. The violet emission at 410 nm is probably due to the defects of zinc interstitial and zinc vacancies related to the interface traps existing at the grain boundaries of ZnO.
A Case for Natural Language in Robot Learning

: This note outlines a case for robot learning researchers to introduce 1 natural language into their research agenda. The importance of language in robot 2 learning goes beyond the potential of natural language interfaces. Language 3 touches on core aspects of the robot learning problem, including modularity, sam-4 ple complexity, simulation, and the gap between short-and long-term behaviors. 5
ReDoSHunter: A Combined Static and Dynamic Approach for Regular Expression DoS Detection

Regular expression Denial of Service (ReDoS) is a class of algorithmic complexity attacks using the regular expressions (regexes) that cause the typical backtracking-based matching algorithms to run super-linear time. Due to the wide adoption of regexes in computation, ReDoS poses a pervasive and serious security threat. Early detection of ReDoS-vulnerable regexes in software is thus vital. Existing detection approaches mainly fall into two categories: static and dynamic analysis. However, they all suffer from either poor precision or poor recall in the detection of vulnerable regexes. The problem of accurately detecting vulnerable regexes at high precision and high recall remains unsolved. Furthermore, we observed that many ReDoS-vulnerable regex contain more than one vulnerability in reality. Another problem with existing approaches is that they are incapable of detecting multiple vulnerabilities in one regex. To address these two problems, we propose ReDoSHunter, a ReDoS-vulnerable regex detection framework that can effectively pinpoint the multiple vulnerabilities in a vulnerable regex, and generate examples of attack-triggering strings. Re-DoSHunter is driven by ﬁve vulnerability patterns derived from massive vulnerable regexes. Besides pinpointing vulnerabilities, ReDoSHunter can assess the degree (i.e., exponential or polynomial) of the vulnerabilities detected. Our experiment results show that ReDoSHunter achieves 100% precision and 100% recall in the detection of ReDoS-vulnerable regexes in three large-scale datasets with 37,651 regexes. It signiﬁcantly outperforms seven state-of-the-art techniques.
MMVText: A Large-Scale, Multidimensional Multilingual Dataset for Video Text Spotting

Video text spotting is crucial for numerous real application scenarios, but most 1 existing video text reading benchmarks are challenging to evaluate the performance 2 of advanced deep learning algorithms due to the limited amount of training data 3 and tedious scenarios. To address this issue, we introduce a new large-scale bench-4 mark dataset named M ultidimensional M ultilingual V ideo Text (MMVText), the 5 ﬁrst large-scale and multilingual benchmark for video text spotting in a variety of 6 scenarios. There are mainly three features for MMVText. Firstly, we provide 510 7 videos with more than 1,000,000 frame images, four times larger than the existing 8 largest dataset for text in videos. Secondly, our dataset covers 30 open categories 9 with a wide selection of various scenarios, e.g., life vlog, sports news, automatic 10 drive, cartoon, etc . Besides, caption text and scene text are separately tagged for the 11 two different representational meanings in the video. The former represents more 12 theme information, and the latter is the scene information. Thirdly, the MMVText 13 provides multilingual text annotation to promote multiple cultures live and commu-14 nication. In the end, a comprehensive experimental result and analysis concerning 15 text detection, recognition, tracking, and end-to-end spotting on MMVText are pro-16 vided. We also discuss the potentials of using MMVText for other video-and-text 17 research. The dataset and code can be found at github . com / weijiawu / MMVText . 18
Wine price determinants. Is there a homogeneous international standard?

Th is article presents an international comparison of the main determinants of wine prices in specialist online wine shops. Hedonic price functions were estimated for 9624 wines spread among four datasets from France, Italy, Germany and Australia. To explain price variation data was collected on wine classifi cation, closure type, wine origin, medals or awards, vintage, alcohol content, color, and grape variety. Results from quantile regression models show that the wine vintage is a common price driver in all markets and quantiles. A quite similar eff ect was found for alcohol content. In terms of color, the implicit prices for red and white wines are also structurally diff erent between countries, particularly in origin, blend, closure, awards and age. Th us, the markets should be assumed as heterogeneous, and the extrapolation of the results from one market to another may lead to erroneous management decisions.
H-Bridge 7 Switches Transformerless MOSFET Inverter to Improve Efficiency of Grid-Tied Photovoltaic System

Abstract: This paper proposes a new type of high-efficiency transformerless single phase photovoltaic inverter that uses superjunction MOSFET as the main power switches. The main power switch does not require any reverse recovery problems, and the voltage on the switch is half of the DC input voltage. For this reason, super-junction MOSFET have been used to improve efficiency. The two additional switches in the traditional full H-bridge topology ensure that the PV module is disconnected from the grid in freewheeling voltage that causes leakage current minimized. The proposed topology does not require PWM dead time, which reduces AC output current distortion. KeywordsCommon Mode Voltage (CM), Photovoltaic PV, High efficient and reliable inverter concept topology (HERIC), total harmonic distortion (THD), H-bridge zero voltage rectifier (HB-ZVR)
EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation

We introduce EventNarrative, a knowledge graph-to-text dataset from publicly available open-world knowledge graphs. Given the recent advances in event-driven Information Extraction (IE), and that prior research on graph-to-text only focused on entity-driven KGs, this paper focuses on event-centric data. However, our data generation system can still be adapted to other other types of KG data. Existing large-scale datasets in the graph-to-text area are non-parallel, meaning there is a large disconnect between the KGs and text. The datasets that have a paired KG and text, are small scale and manually generated or generated without a rich ontology, making the corresponding graphs sparse. Furthermore, these datasets contain many unlinked entities between their KG and text pairs. EventNarrative consists of approximately 230,000 graphs and their corresponding natural language text, 6 times larger than the current largest parallel dataset. It makes use of a rich ontology, all of the KGs entities are linked to the text, and our manual annotations confirm a high data quality. Our aim is two-fold: help break new ground in event-centric research where data is lacking, and to give researchers a well-defined, large-scale dataset in order to better evaluate existing and future knowledge graph-to-text models. We also evaluate two types of baseline on EventNarrative: a graph-to-text specific model and two state-of-the-art language models, which previous work has shown to be adaptable to the knowledge graph-to-text domain.
Optimal Portfolio Liquidation

Optimal Portfolio Liquidation is one of the common challenges in stock trading whose aim is to minimize a combination of risks and transactions cost arising from permanent and temporary market impact when selling a large number of stocks within a given time frame. Our attempt in this project is to turn this challenge into a reinforcement learning problem and compare the research result with a known baseline method achieved with Almgren and Chriss model[1]. A quick introduction video is here https://youtu.be/dBjzqcKjlBQ
Teleworking During the COVID-19 Pandemic: Determining Factors of Perceived Work Productivity, Job Performance, and Satisfaction

Due to the COVID-19 pandemic, telework has been adopted extensively as a way to ensure business continuity. However, its effects on important employee outcomes such as work productivity, job performance, and satisfaction are unclear. The purpose of this study was to investigate whether the factors previously identified as important determinants of telework effectiveness are also relevant in the context of the pandemic. Drawing on Baruch and Nicholson’s Model of Teleworking, the relationship between individual, home/family, job, and organizational factors and adjustment to telework during COVID-19 was examined. Survey data was collected from 482 employees who worked from home on a full-time basis during the pandemic. Results indicated that individual factors (i.e., self-management tactics) and home/family factors (i.e., the need for adequate telework conditions) are important predictors for employee productivity, performance and satisfaction while teleworking during COVID-19. Furthermore, workload (i.e., job factor) was a significant predictor for work productivity and satisfaction with telework. Surprisingly, organizational support for teleworking was not related to any of these outcomes. Implications for research and practice concerning telework during the pandemic are discussed. © 2021, Amfiteatru Economic. All Rights Reserved.
Effect of the inclusion of Musa sp. on the conservation of silages of Trichanthera gigantea (Humb. & Bonpl.) Nees

Objective: To evaluate the effect of the inclusion of different levels of Musa sp. on the nutritional and fermentative quality of Trichanthera gigantea (Humb. & Bonpl.) Nees. Materials and Methods: A complete unrestricted design was used, with four treatments: T1) 100 % T. gigantea, T2) 85 % T. gigantea: 25 % Musa sp. , T3) 70 % T. gigantea: 30 % Musa sp. and T4) 55 % T. gigantea: 45 % Musa sp. The silages were made in 5-kg plastic bags during 40 days. At the moment of opening their bromatological characteristics, as well as the fermentation indicators, were measured. A variance analysis was applied and the possible correlations among all the bromatological variables, as well as fermentation indicators, were measured. A variance analysis was applied and the possible correlations among all the bromatological variables and fermentative indicators, were analyzed. Results: Improvement was found in the fermentative indicators of the silages due to increase in the concentration of lactic acid and pH decrease, proportional to the quantity of Musa sp. used. The dry matter concentration increased, at a rate of a 0,9 percentage points for each increase of Musa sp. in the silages. Likewise, increase was generated in the content of non-fibrous carbohydrates and starch, which improved the energy contribution of the silages. There was decrease in the quantity of crude protein and fiber, at a rate of 1,8 and 5,7 percentage points for each increase in the quantity of Musa sp. , respectively, without negative effect on the digestibility of the silages. Conclusions: The mixtures with 30 % Musa sp. showed adequate fermentative and nutritional characteristics for their conservation and use as supplement for ruminants; nevertheless, levels 0 and 5 % showed the highest protein and fiber values, but low in energy. In turn, the mixtures of 0 and 45 % achieved the best fermentative indicators.
Exploring Variational Meta-RL for Social Robotics

: The use of reinforcement learning for social robotics is underdeveloped 1 because of the difﬁculties in designing reward functions, and the need of large 2 amounts of human-robot interaction data. We propose to explore the use of meta-3 RL in social tasks so as to better generalize to new tasks, and reduce the amount of 4 adaptation needed. In this paper we demonstrate the interest in variational meta-5 RL for social robotics, report our ﬁndings on posterior collapse, and propose a 6 simple strategy to mitigate its effects, hoping to foster research on the topic. 7
Virtual Laboratory Based on Discovery Learning to Train an Analyzing-Interpreting Data: A Systematic Review

Virtual laboratories based on discovery learning are an alternative source to support the distance learning process during the current pandemic. The study aims to provide an overview of how virtual laboratories based on discovery learning can be applied to the ability to analyze and interpret student data. The method used is a systematic review. The articles used are from Google Scholar and ERIC, then the search findings are directed to national and international journals published in 2010-2020. The number of articles used was 26 articles based on relevant research sources. The results of the analysis show that a virtual laboratory based on discovery learning can improve students' data analyzing-interpreting abilities through practicum simulations with scientific methods. Experimental simulations are carried out independently so that learning is more than meaningful. Students display data as proof to support their conclusion.
TheEffect ofBaru (DypterixalataVog.)AlmondOil onMarkersof Bowel Habits in Hemodialysis Patients

Gastrointestinal symptoms are common in patients in hemodialysis treatment and were frequently associated with low intake of dietary fibers and liquids, oral iron supplementation, phosphate binders, and low level of physical activity. -us, the aim of this study was to evaluate the effect of baru almond oil in comparison with mineral oil supplementation on bowel habits of hemodialysis patients. -irty-five patients on hemodialysis (57% men, 49.9± 12.4 years) were enrolled in a 12-week single-blind clinical trial. Patients were allocated (1 : 2) by sex and age into (1) the mineral group: 10 capsules per day of mineral oil (500mg each) or (2) the baru almond oil group: 10 capsules per day of baru almond oil (500mg each). Bowel habits were assessed by the Rome IV criteria, Bristol scale, and self-perception of constipation. Food consumption, physical activity level, and time spent sitting were also evaluated at the baseline and at the end of the study. After 12 weeks of supplementation, the baru almond oil group showed reduced Rome IV score (6.1± 5.5 vs 2.8± 4.3, p � 0.04) and the straining on the evacuation score (1.2± 1.4 vs 0.4± 0.7; p � 0.04), while the mineral group did not show any change in the parameters. -e frequency of self-perception of constipation was lower in the baru almond oil group after intervention (45.0% vs 15.0%, p � 0.04). Baru almond oil improved bowel habit and the straining on evacuation in hemodialysis patients.
Comparison of Effects between Combined Lumbar-Sacral Plexus Block plusGeneral Anesthesia andUnilateral Spinal Anesthesia in Elderly Patients Undergoing Hip Fracture Surgery: A Pilot Randomized Controlled Trial

Purpose. Hip fracture is a common injury in geriatric populations, which is associated with poor quality of life. However, the ideal anesthesia technique for this disease is yet to be identified. 'is study aimed to compare the combined lumbar-sacral plexus block (CLSB) plus general anesthesia (bispectral index (BIS) 60–80) with the unilateral spinal anesthesia (SA) on activity of daily living in elderly patients undergoing hip fracture surgery.Methods. A total of 124 elderly patients undergoing hip fracture surgery were randomly assigned to two groups. Patients in the SA group received light-specific gravity spinal anesthesia, and patients in the CLSB group received lumbar and sacral plexus block with general anesthesia (BIS 60–80). 'e primary outcomes were 30-day activity of daily living (ADL). 'e secondary outcomes were postoperative pain scores, postoperative delirium, in-hospital cost, andmajor complications. Results. 'e ADL scores of postoperative day 30 (POD30) in the CLSB group are higher than those in the SA group (27.34± 7.01 versus 24.70± 6.40, P � 0.045). Compared to preoperative ADL scores, there were higher increased scores in the CLSB group than in POD30 (CLSB group 8.09± 3.39 versus SA group 4.87± 3.90, P< 0.001). Mild-to-moderate pain did not have differences between the two groups (rest pain: 3 versus 2, P � 0.344; motion pain: 5 versus 4, P � 0.073). 'ere were no significant differences in incidence of postoperative delirium, PONV, and other complications. Conclusion. 'e unilateral SA can reduce the deterioration of ADL after hip fracture surgery and provide a better postoperative recovery.