Miracle-dz/UniFAR-FTUs huggingface dataset:
Pertumbuhan Padi Gogo pada Medium Ultisol dengan Aplikasi Biochar dan Asap Cair

Penelitian ini telah dilakukan di rumah kaca fakultas pertanian univeristas riau, dalam bentuk RAL Faktorial. Faktor Pertama yaitu biochar dosis 10 ton/ha yang terdiri dari 4 taraf yaitu tanpa biochar, biochar sekam padi, biochar tempurung kelapa, dan campuran biocha sekam padi dan tempurung kelapa. Faktor kedua yaitu asap cair yang terdiri dari 3 taraf yaitu tanpa asap cair, asap cair sekam padi, asap cair tempurung kelapa. Hasil penelitian menunjukkan bahwa biochar berpengaruh terhadap tinggi tanaman, jumlah anakan maximum dan produktif bobot kering jeramai dan mempercepat umur keluar malai. asap cair dapat meningkatkan tinggi tanaman, bobot kering jerami dan mempercepat umur keluar malai. Interaksi keduanya berpengaruh terhadap tiinggi tanaman, anakan produktif bobot kering jerami dan mempercepat umur keluar malai dibandingkan tanpa perlakuan (kontrol)
Computational Characterization of Nylon 4, a Biobased and Biodegradable Polyamide Superior to Nylon 6

This study is an attempt to develop a theoretical methodology to elucidate or predict the structural characteristics and the physical properties of an isolated polymeric chain and its crystalline state precisely and quantitatively. To be more specific, conformational characteristics of a biobased and biodegradable polyamide, nylon 4, in the free state have been revealed by not only ab initio molecular orbital calculations on its model compound but also nuclear magnetic resonance experiments for the model and nylon 4. Furthermore, the crystal structure and solid-state properties of nylon 4 have been elucidated by density functional theory calculations with a dispersion force correction under periodic boundary conditions. In the free state, the nylon 4 chain forms intramolecular N–H···O=C hydrogen bonds, which force the polymeric chain into distorted conformations including a number of gauche bonds, whereas nylon 4 crystallizes in the fully extended all-trans structure (α form) that is stabilized by intermolecular N–H···O=C hydrogen bonds. The intermolecular interaction energy (ΔECP) in the crystal was accurately calculated via a counterpoise (CP) method contrived here to correct the basis set superposition error, and the ultimate crystalline modulus (Eb) in the chain axis (b axis) direction at 0 K was also evaluated theoretically. The results were compared with those obtained from the α and γ crystalline forms of nylon 6, and, consequently, the superiority of nylon 4 to nylon 6 in thermal stability and mechanical properties was indicated: the ΔECP and Eb values are, respectively, −214 cal g–1 and 334 GPa (nylon 4), −191 cal g–1 and 316 GPa (α form of nylon 6), and −184 cal g–1 and 120 GPa (γ form of nylon 6). In conclusion, nylon 4 is expected to be put to practical use as a tough environmentally friendly polyamide.
Emotional intelligence Vs normative behavior of juvenile male convicts

In recent years, the level of crime among young people has increased, so there is a need to improve the methods of education and correction of such persons, which is why the in-depth study of the emotional intelligence of the convict is relevant. Based on empirical data, the components of emotional intelligence of male juveniles with normative behavior and convicts were compared. The following research methods were used: semantic, sociological (observation, interviewing, psychodiagnostic testing), comparative analysis, and correlation analysis. The study found that the level of emotional intelligence of juvenile convicts is lower than the emotional intelligence of normative behavior. Convicts have a lower level of understanding and control of their emotions, reduced empathy, which is expressed in the inability to consciously interpret the emotional state of another person, and reduced control over their expression. The above directly proportionally affects the ability of juveniles to commit criminal offenses, so it is necessary to purposefully influence and develop emotional intelligence and emotional competence in juvenile male convicts. Based on the constant analysis of the emotional intelligence of convicts, it is possible to more effectively identify and eliminate the causes and conditions that contribute to the commission of offenses and anti-social actions.
High Bleeding Risk (HBR) patients Percutaneous Coronary Intervention-a Challenge to Deal with

Coronary artery disease (CAD) is one of the leading causes of death in our patient population. In the era of cardiovascular intervention, Percutaneous coronary intervention (PCI) is one of the most important modalities in treating these group of patients. Several CAD risks factors and co-morbid conditions are key responsible factor of procedural success. High bleeding risk (HBR) patients undergoing PCI is not an uncommon phenomenon. Incidences and prevalence of HBR patients with CAD and their management by PCI is not well addressed in our literature. PCI in HBR patients carries potential risk of intracranial hemorrhage (ICH) and lifethreatening bleeding. Therefore, careful pre-PCI assessment of possible risk or threats of post-PCI complications in patients with HBR are deem necessitate to understand. We recommend forming multicenter common consensus and to form a guideline in treating HBR patient by PCI. Thus, to reduce post procedural complication and subsequent improvement of mortality and morbidity in HBR patients undergoing PCI in both ST segment elevated myocardial infarction (STEMI) and as well as non-STEMI. Bangladesh Heart Journal 2021; 36(2): 133-138
Um Modelo Estocástico de Liquidez para Otimização de Portfólios com uso do Conditional Value at Risk

Além da rentabilidade e do risco, uma variável importante na gestão de portfólios de investimentos é a liquidez, pois todo portfólio formado precisará um dia ser vendido. Este trabalho teve como propósito analisar os resultados referentes à otimização de portfólio por meio de um modelo de programação linear que faz uso do conditional value at risk (CVaR) associado a uma condição estocástica de liquidez dos ativos. Os testes foram feitos sobre dados originados de ações negociadas na bolsa brasileira (B3). Os resultados mostraram que o modelo proposto formou portfólios mais vantajosos que aqueles obtidos pelo modelo tradicional de média-variância.
The Impact of COVID-19 on Outpatient Antibiotic Prescriptions in Ontario, Canada; An Interrupted Time Series Analysis

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has potentially impacted outpatient antibiotic prescribing. Investigating this impact may identify stewardship opportunities in the ongoing COVID-19 period and beyond. Methods We conducted an interrupted time series analysis on outpatient antibiotic prescriptions and antibiotic prescriptions/patient visits in Ontario, Canada, between January 2017 and December 2020 to evaluate the impact of the COVID-19 pandemic on population-level antibiotic prescribing by prescriber specialty, patient demographics, and conditions. Results In the evaluated COVID-19 period (March–December 2020), there was a 31.2% (95% CI, 27.0% to 35.1%) relative reduction in total antibiotic prescriptions. Total outpatient antibiotic prescriptions decreased during the COVID-19 period by 37.1% (95% CI, 32.5% to 41.3%) among family physicians, 30.7% (95% CI, 25.8% to 35.2%) among subspecialist physicians, 12.1% (95% CI, 4.4% to 19.2%) among dentists, and 25.7% (95% CI, 21.4% to 29.8%) among other prescribers. Antibiotics indicated for respiratory infections decreased by 43.7% (95% CI, 38.4% to 48.6%). Total patient visits and visits for respiratory infections decreased by 10.7% (95% CI, 5.4% to 15.6%) and 49.9% (95% CI, 43.1% to 55.9%). Total antibiotic prescriptions/1000 visits decreased by 27.5% (95% CI, 21.5% to 33.0%), while antibiotics indicated for respiratory infections/1000 visits with respiratory infections only decreased by 6.8% (95% CI, 2.7% to 10.8%). Conclusions The reduction in outpatient antibiotic prescribing during the COVID-19 pandemic was driven by less antibiotic prescribing for respiratory indications and largely explained by decreased visits for respiratory infections.
Automatic Noise Analysis on Still Life Chart

In this paper, we tackle the issue of estimating the noise level of a camera, on its processed still images and as perceived by the user. Commonly, the characterization of the noise level of a camera is done using objective metrics determined on charts containing uniform patches at a given condition. These methods can lead to inadequate characterizations of the noise of a camera because cameras often incorporate denoising algorithms that are more efficient on uniform areas than on areas containing details. Therefore, in this paper, we propose a method to estimate the perceived noise level on natural areas of a still-life chart. Our method is based on a deep convolutional network trained with ground truth quality scores provided by expert annotators. Our experimental evaluation shows that our approach strongly matches human evaluations.
A Broadband Dual-polarized Antenna for 2G/3G/4G/5G Base Station Applications

─ This paper presents a novel broadband base station antenna element covering 2G/3G/4G/5G bands. The proposed antenna consists of a dual-dipole radiator and an open-box shaped reflector. The main radiating portion of each dipole arm is designed with a dualhexagon shape to improve bandwidth. Four small hexagonal-shaped parasitic patches are adopted to further decrease the reflection coefficient. Dual polarization is excited by placing two dipoles orthogonally. The openbox shaped reflector derives from a planar metal plate with four inverted L-shaped edges which are arranged below the radiator to enhance the antenna gain and reduce the half power bandwidth (HPBW) in 3.3-3.8 GHz. The prototype has been fabricated and measured with bandwidth of 1.68-3.8 GHz, coupling below -20 dB, stable HPBW with 65°± 5° and average gain of 8.5 dBi. The values of the cross-polarization discrimination (XPD) are better than 20 dB at the boresight and 10 dB within ±60° directions. The proposed antenna has a small overall size of 145×145×35.6 mm. Index Terms ─ 5G antenna, base station antenna, broadband antenna, dual-polarized antenna.
Lower-layer performance is not indicative of upper-layer success

End users don't interact with the Internet for the sake of it. Most human use is direct and goal driven (e.g. sending email, receiving a video call, browsing the Web), and supported by applications. The relationship between application and Internet is an indirect and asymmetric dependency from the user perspective. Humans will have various levels of technical understanding of what role the Internet plays in achieving their goals. The lowest common denominator being that "any Internet connection" is required. This is, in a sense, similar to utilities like water and electricity.
THE DETECT DOS ATTACK FROM NETWORK TRAFFIC USING GRAY WOLF OPTIMIZATION ALGORITHM

A DoS attack can temporarily suspend the service or damage the system itself by consuming all system platforms such as memory, network bandwidth, CPU, etc., as seen in the incidents of commercial web servers. The damage can be extended to all network-related systems. Since this type of attack is dangerous to systems and networks, many researches are continuing to detect this type of attack and how to avoid the DoS attack. In this research a model for detecting DoS attack is presented. Intelligent techniques are used to minimize its damage. Specially swarm techniques, and more specially the gray wolf algorithm is used in detecting the attack. By taking the data from the packet of network and after analysing it, it is entered into the wolf algorithm, the results of the wolf algorithm were analysed and tested to obtain the attack detection rate with the false alarm and the negative alarm. The results were satisfactory and good. We used Matlab language version 10 on the Windows 10 operating system with the TCP/IP protocol.
Measures of noncompactness and infinite systems of integral equations of Urysohn type in L∞(G)

In this article, applying the concept of measure of noncompactness, some fixed point theorems in the Fréchet space L∞(G) (where G ⊆ Rω) have been proved. We handle our obtained consequences to inquiry the existence of solutions for infinite systems of Urysohn type integral equations. Our results extend some famous related results in the literature. Finally, to indicate the effectiveness of our results we present a genuine example.
Oddities of Active Systems

Textbook (for instance, [1]) says that mobility of a particle in a fluid and diffusion coefficient are related to one another by Einstein relation Dij = μijkBT , and each is a symmetric tensor: Dij = Dji and μij = μji. Following Onsager, textbooks explain that the latter symmetry, although can be derived from hydrodynamics, is more fundamental and is due to the time reversal symmetry of the underlying molecular mechanics. All of this is of course well familiar. Furthermore, symmetry of the diffusivity tensor seems to survive quite drastic generalizations. For instance, active Brownian particles, on the length and time scales above their persistence length/time, perform the usual random walks (which is why they are called Brownian), and, therefore, obey the usual Fick’s law. As a reminder, active Brownian particles (see, e.g., [2]) are the ones which are propelled forward by some internal source of energy with a fixed speed v0, but in the direction that slowly reorients due to angular diffusion. To keep things simple, in 2D these particles obey overdamped Langevin dynamics of the form
THE EFFECT OF CINNAMALDEHYDE ON STRESS-INDUCED DEFICITS IN ACQUISITION BEHAVIOR WITH BARNES MAZE IN RAT

Stress can disrupt the physiological homeostasis of biological organisms which follow by behavioral impairment; especially it can induce deficits in learning and memory process. Studies showed that Cinnamaldehyde (CA) have many pharmacological activities such as anti-diabetic, antioxidant, cognitive enhancer, anti-inflammatory and anti-cancer activity. To examine the effects of Cinnamaldehyde on stress-induced cognitive deficits, we assessed and compared the Electric foot Shock Stress (EShS) and Immobility stress (ImmS) on Barnes maze acquisition. In this experiment 60 Male Wistar rats were randomly divided into 5 groups (n=12): vehicle, two groups with stress and two groups with stress plus CA treatment. The learning and memory process were measured by Barnes maze. One week stress induction was begun two days before starting acquisition protocol and during it. Cinnamaldehyde was administered orally via gavage (20mg/kg/day) during experiment. This study demonstrated that both EShS and ImmS could disrupt the acquisition and memory with Barnes maze. The time of latency and distance pursuit to find goal box and number of errors increased in stress induced groups. Treatment with Cinnamaldehyde improves learning and memory process both in control and stress induced groups. Furthermore, the improvement effect of Cinnamaldehyde was better in electric foot shock stressed group than restraint group. The present study suggest that Cinnamaldehyde can improve learning and memory process both in control and stress-induced groups.The improvement against electric foot shock stress is better than immobilization.
Challenges of Applying Knowledge Graph and their Embeddings to a Real-world Use-case

Different Knowledge Graph Embedding (KGE) models have been proposed so far which are trained on some specific KG completion tasks such as link prediction and evaluated on datasets which are mainly created for such purpose. Mostly, the embeddings learnt on link prediction tasks are not applied for downstream tasks in real-world use-cases such as data available in different companies/organizations. In this paper, the challenges with enriching a KG which is generated from a real-world relational database (RDB) about companies, with information from external sources such as Wikidata and learning representations for the KG are presented. Moreover, a comparative analysis is presented between the KGEs and various text embeddings on some downstream clustering tasks. The results of experiments indicate that in use-cases like the one used in this paper, where the KG is highly skewed, it is beneficial to use text embeddings or language models instead of KGEs.
Using Multimodal Video and Language Representation for Video Question Answering

Video Question Answering is the task of answering questions given videos and natural language (subtitles or audio) as the context. In this task, the challenge is to incorporate information from both videos and language in a way that makes it easier for spatio-temporal reasoning which is important for video question answering. In this work, we explore a technique of multimodal representation learning to jointly learn representations using various video and language based features such as action recognition and BERT in the realm of video question answering.
Tracking long track ice skaters in the bend Name :

In long track speed skating, there are many different paths to take and techniques to use when skating through the bend of a long track ice skating rink. In order to find out which path and technique yields the fastest time, it is very useful to be able to examine the trajectories for both the left and right skate of a skater that is skating through the bend. In order to do this, a camera is installed in the ceiling of the Thialf ice skating stadium, providing top-view video footage of skaters that skate through the bend. This research contributes to the end goal of determining the best path and technique by attempting to automatically track the skates of skaters in the video footage. The video footage is annotated manually in order to create the ground truth, being the real positions of the skates throughout each video. This research gives an overview of the existing state-of-the-art methods for tracking objects and for tracking ice skaters in general, after which it presents two novel CNN-based methods for tracking both separate skates for each skater. The first method analyzes an image of a skater and then predicts the coordinates for the two skates, while the other analyzes a combination of a skater image and a potential skate and predicts whether the potential skate is actually one of the correct skates of the skater. Finally, this research presents a way of getting from the predicted skates to skate trajectories that can be analyzed. Although the experiments that are conducted during this research show that the models are not as accurate as they need to be in order to use them to analyze the skate trajectories, this research does provide a solid start for this skate tracking task as well as an analysis of which approach is likely to produce a model that is accurate enough.
CHoRaL: Collecting Humor Reaction Labels from Millions of Social Media Users

Humor detection has gained attention in recent years due to the desire to understand user-generated content with figurative language. However, substantial individual and cultural differences in humor perception make it very difficult to collect a large-scale humor dataset with reliable humor labels. We propose CHoRaL, a framework to generate perceived humor labels on Facebook posts, using the naturally available user reactions to these posts with no manual annotation needed. CHoRaL provides both binary labels and continuous scores of humor and non-humor. We present the largest dataset to date with labeled humor on 785K posts related to COVID-19. Additionally, we analyze the expression of COVID-related humor in social media by extracting lexico-semantic and affective features from the posts, and build humor detection models with performance similar to humans. CHoRaL enables the development of large-scale humor detection models on any topic and opens a new path to the study of humor on social media.
A Study of the Cultivation of College Students' Learner Autonomy in the Multimedia Environment

The study first covered the literature review on multimedia assisted teaching, the theory of constructivism, and research on learner autonomy. Then, a 14-week experiment was conducted on 160 fresh students. Three findings were concluded from the research. First, a new learning environment for foreign language learning and teaching has been created with the assistance of multimedia technologies. Second, combined with those multimedia technologies, the constructivist theory, can greatly promote the students’ learner autonomy. Third, strengthening the learner autonomy will contribute to the improvement of students’ English proficiency. The study ended with some measures on how to cultivate college students' learner autonomy in the multimedia environment: First, teachers should firmly take "students" as the center of teaching and "teachers" as the auxiliary. Second, teachers should change the traditional role as from the authority to the friends of the students. Third, teachers create a good environment for students’ autonomous learning and promote their cooperative learning. Fourth, teachers should leave the students more free time for them to speak English, and evaluate their performance. Finally, teachers should teach students in accordance with their aptitude.
Heart rate reactivity, aggression, anger, and antisocial behavior in dating males

Heart Rate Reactivity, Aggression, Anger, and Antisocial Behavior in Dating Males Jennifer L. Guriel This study assessed heart rate reactivity and antisocial characteristics, subjective report of anger, and family history variables in 18 aggressive and 18 nonaggressive undergraduate males in an attempt to test the generalizability of Gottman et al.’s (1995) investigation of cardiovascular reactivity as a typological variable for male batterers. Participants were categorized according to their scores on the Conflict Tactics Scale, Revised. Heart rate reactivity, personality variables (using the Minnesota Multiphasic Personality Inventory, Second Edition), and anger (using the State Trait Anger Expression Inventory) were subsequently measured during standardized interpersonal discussion tasks with a female confederate during the laboratory phase. Aggressive males reported having angrier temperaments and reactions to provocative situations than did their non-aggressive peers. Aggressive and non-aggressive males did not differ in terms of heart rate reactivity, personality variables, control or expression of anger, or witnessing violence between parents.
Semantic Analysis of Action with Spatio-Temporal Features Based on Object Detection

—Vast studies on action analysis with spatio-temporal features and deep learning algorithms have proposed countless improvements over the years. This paper presents a domain model with continuous and spatio-temporal features based on object detection for the industrial pipeline scenario. In this way, we can conduct a comprehensive evaluation: action pose accuracy in the spatial dimension and action efﬁciency in the temporal dimension. The method is applicable to scenarios that require semantic recognition of action in a short time, without any dedicated action capture devices. Firstly, the discretized images are combined into spatio-temporal, structured and continuous action sequences. Then we apply the model to the sequences to get the spatial action information through video streams with only two-dimensional information, and then complete the analysis of the action speciﬁcation based on these action streams with temporal features. Furthermore, this paper performs several ablation experiments on training strategies and hyperparameters to improve accuracy. Experimental performances show that it achieves an average recognition accuracy of about 96.45%.