Miracle-dz/UniFAR-FTUs huggingface dataset:
The Functional Roles and Regulation of Circular RNAs during Cellular Stresses

Circular RNAs (circRNAs) are a novel class of regulatory RNA involved in many biological, physiological and pathological processes by functioning as a molecular sponge, transcriptional/epigenetic/splicing regulator, modulator of protein–protein interactions, and a template for encoding proteins. Cells are constantly dealing with stimuli from the microenvironment, and proper responses rely on both the precise control of gene expression networks and protein–protein interactions at the molecular level. The critical roles of circRNAs in the regulation of these processes have been heavily studied in the past decades. However, how the microenvironmental stimulation controls the circRNA biogenesis, cellular shuttling, translation efficiency and degradation globally and/or individually remains largely uncharacterized. In this review, how the impact of major microenvironmental stresses on the known transcription factors, splicing modulators and epitranscriptomic regulators, and thereby how they may contribute to the regulation of circRNAs, is discussed. These lines of evidence will provide new insight into how the biogenesis and functions of circRNA can be precisely controlled and targeted for treating human diseases.
HIVE: Route Optimization Problem of Automatic Delivery System with Mobile Depot and Multiple Drones

An automatic delivery system with mobile depot and multiple drones, HIVE, is proposed. Through this system and a series of embedded devices such as drone automatic launch and recovery device etc., two delivery modes, manual delivery and unmanned delivery, are executed in parallel. To solve the delivery route of this system, Two-Echelon Routing Problem with Mobile Depot and Multiple Drones (2E-RP-MD&mD) is investigated. A heuristic algorithm based on the regression is designed according to the route characteristics of the HIVE delivery system. Parameters of mobile depot and drones are standardized referred to the performance of delivery vehicles. Experiments on random instances as well as actual case based on Changsha are carried out to test the performance of the proposed algorithm and prove the delivery efficiency of HIVE automatic delivery system.
PENGARUH MEDIA e-LEARNING BERBASIS WEBLOG PADA PEMBELAJARAN MODEL KOOPERATIF TIPE TPS (THINK PAIR SHARE) TERHADAP HASIL BELAJAR KIMIA SISWA PADA POKOK BAHASAN STRUKTUR ATOM DAN SISTEM PERIODIK UNSUR

Abstract This research was purposed to look at the influence of e-learning based weblog implementation toward the increasing of student’s achievement on subject of atom structure and periodict unsure system. The population of research was all students of XI IPA SMAN 3 Medan which consisted of 9 classes with total of 414 students. By using random sample, 2 classes with total of 80 students was used as sample such that gotten class of 1 st experiment was e-learning based weblog with instructional model of TPS cooperative type and class of 2 nd experiment was not e-learning based weblog with instructional model of TPS cooperative type. The percentage of student’s achievement was increasing by using e-learning based weblog toward the teaching and learning with instructional model of TPS cooperative type was 77.920% and without it was 66.200%. By using data analysis, t-statistics was 6.267 than t-table was 1.994 where α = 0.05 and dk = 78 such that t-statistics > t-table. So, Ha was accepted and could be concluded that student’s achievement by using e-learning based weblog implementation using instructional model of TPS cooperative type was higher than the student’s achievement without it. Kata Kunci : e-Learning, Weblog, Think Pair Share (TPS)
The role of remote ischemic preconditioning in preventing contrast-induced nephropathy following invasive coronary angiography; a randomized controlled trial

Introduction: Remote ischemic preconditioning (RIPC) is now proposed as an effective approach for preventing contrast-induced nephropathy (CIN); however, the results on its efficacy have already remained uncertain. Objectives: We aimed to assess the beneficial effects of RIPC in preventing CIN in patients undergoing coronary angiography (CA) followed by angioplasty. Patients and Methods: One hundred patients candidate for elective CA and coronary angioplasty, moderate to high risk for CIN were randomized into two groups including the group which planned for RIPC, and the control group. The overall prevalence rate of CIN was assessed and compared across the two groups. Results: The two groups were matched for demographics, cardiovascular risk profiles and laboratory parameters. The prevalence of CIN in RIPC group was 14.0% and in the control group was 26.0% indicating no statistical difference between the two groups (P = 0.105). Requiring dialysis was also planned for 0.0% and 2.0% respectively with no difference (P = 0.500). Conclusion: RIPC may not prevent CIN in patients who are candidate for invasive CA. Trial Registration: The study was approved in the Iranian Registry of Clinical Trials (identifier: IRCT20171230038144N1; https://www.irct.ir/trial/28715, ethical code: IR.IUMS. FMD.REC 1396.9311171014).
Analysis of the Twitter discourse on sustainability using natural language processing

This publication aims to map the environmental sustainability discourse on Twitter. This will be achieved through two commonly used methods of natural language processing; topic modelling, which is used to uncover hidden themes in the document collection, and sentiment analysis, which is used to detect the attitudes of the authors of the text towards a particular attitude. The exploration of communication can provide an opportunity to find a solution to a multifaceted problem in order to protect our common future.
High-Frequency Transformer Isolated Power Conditioning System for Fuel Cells to Utility Interface

Supervisory Committee: Dr. Ashoka K. S. Bhat, (Department of Electrical and Computer Engineering) Supervisor Dr. H. L. Kwok, (Department of Electrical and Computer Engineering) Department member Dr. Subhasis Nandi, (Department of Electrical and Computer Engineering) Department member Dr. Ned Djilali, (Department of Mechanical Engineering) Outside Member This thesis presents interfacing of fuel cells to a single-phase utility line using a highfrequency transformer isolated power converter. This research contributes towards selecting a suitable utility interfacing scheme and then designing a power conditioning system along with its control for connecting fuel cells to a single-phase utility line that can achieve high efficiency and compact size. The power conditioning system, designed and built in the research laboratory is connected with the utility line and the experimental results are presented. Based on the literature available on photovoltaic (PV) array and fuel cell based utility interactive inverters with high-frequency transformer isolation, the interfacing schemes for connecting a DC source, in particular fuel cells, to a single-phase utility line are classified. Based on the fuel cell characteristics and properties, performance and the comparison of these utility interfacing schemes, a suitable scheme for the present application is selected. Because of low voltage fuel cells, the system takes higher current from the fuel cell and results in lower efficiency of the system. The inverter stage of the selected scheme deals with the higher voltage (lower current) and therefore, its efficiency is higher. In this sense, the efficiency of the whole system depends mainly on the efficiency of the frontend DC-DC converter. To realize a low cost, small size and light weight system, soft-
Design and Joint Position Control of Bionic Jumping Leg Driven by Pneumatic Artificial Muscles

Using the skeletal structure and muscle distribution of the hind limbs of a jumping kangaroo as inspiration, a bionic jumping leg was designed with pneumatic artificial muscles (PAMs) as actuators. Referring to the position of biarticular muscles in kangaroos, we constructed a bionic joint using biarticular and monoarticular muscle arrangements. At the same time, the problem of the joint rotation angle limitations caused by PAM shrinkage was solved, and the range of motion of the bionic joint was improved. Based on the output force model of the PAM, we established a dynamic model of the bionic leg using the Lagrange method. In view of the coupling problem caused by the arrangement of the biarticular muscle, an extended state observer was used for decoupling. The system was decoupled into two single-input and single-output systems, and angle tracking control was carried out using active disturbance rejection control (ADRC). The simulation and experimental results showed that the ADRC algorithm had a better decoupling effect and shorter adjustment time than PID control. The jumping experiments showed that the bionic leg could jump with a horizontal displacement of 320 mm and a vertical displacement of 150 mm.
Network Interconnection Security Buffer Technology for Power Monitoring System

In recent years, the risk of malicious attacks on power monitoring systems has increased, and there have been many attacks on power systems in the world. Aiming at the network interconnection security problem of the core control system, the concept of “security buffer” is introduced, and a network security buffer method forpower monitoring system is proposed, which is composed of three parts: paradigm check, behavior analysis, and dynamic conversion and jointly realizes the multilevel security inspection of interconnection requests. Experimental verification results show that the proposed method has a protective effect on malicious attacks of power monitoring system.
THE ROLE OF KNOWLEDGE STRUCTURES IN RECONFIGURING RURAL TOURISM IN RESPONSE TO THE COVID-19 PANDEMIC: AN EXPLORATORY STUDY OF RURAL TOURISM IN ITALY AND KAZAKHSTAN

The aim of this paper is to analyze changes in the notion and role of rural tourism provoked by the COVID-19 pandemic. The paper examines how rural tourism in the pandemic year 2020 has accommodated human needs for well-being: which touristic resources have been mobilized and what knowledge structures have contributed to mobilization of touristic resources. The authors use a qualitative multimethod approach to develop insights about the impact of the COVID-19 pandemic on changing roles played by rural tourism in Italy and Kazakhstan. The theoretical novelty of the research is that it conceptualizes tourism resource mobilization strategies as a result of the historical and emerging knowledge structures. It was found that while both geographical and ethno-cultural resources form the basis for rural tourism development, knowledge structures play a critical role in setting both the interpretative and institutional frames defining rural tourism forms and directions of development.
A Wideband and High Gain Dual-Polarized Filtering Antenna Based on Multiple Patches

This communication investigated a wideband filtering patch antenna with high gain and high selectivity. The antenna is mainly composed of an aperture-coupled driven patch, a stacked patch and four center-shorted trapezoidal thin patches. The stacked patch can introduce a higher-frequency resonant mode and a radiation null due to the magnetic coupling. Four trapezoidal thin patches loaded with shorting vias are located around the driven patch, acting as a vertical split-ring resonator (SRR) and introducing a lower-frequency resonant mode and a radiation null due to the electric coupling. With two radiation nulls at the edges of the passband, the filtering gain response with high selectivity is achieved. As no filtering circuits are utilized, the antenna can obtain high gain and high efficiency. Due to the symmetrical structure, a dual-polarized filtering antenna is also presented for base-station application, demonstrating good radiation performances and an isolation of 20 dB. A fabricated dual-polarized antenna is measured and showing a wide bandwidth up to 18.8% (from 3.19 GHz to 3.85 GHz), a peak gain of 9.5 dBi and two near-band radiation nulls located at 3.13 GHz and 4 GHz.
Bio-Herbicidal Potential of Nanoemulsions with Peppermint Oil on Barnyard Grass and Maize

Bio-based nanoemulsions are part of green pest management for sustainable agriculture. This study assessed the physicochemical properties and the herbicidal activities of the peppermint essential oil nanoemulsions (PNs) in concentrations 1.0–10% stabilized by Eco-Polysorbate 80 on germinating seeds and young plants of maize and barnyard grass. Based on the design of experiment (DOE) results, the final nanoemulsion formulations were obtained with 1, 1.5, 2, and 5% of essential oil concentration. Biological analyses were conducted to select the most promising sample for selective control of barnyard grass in maize. Seedlings growing in the presence of PNs displayed an overall inhibition of metabolism, as expressed by the calorimetric analyses, which could result from significant differences in both content and composition of carbohydrates. Concentration–response sub estimation showed that leaf-sprayed concentration of PN causing 10% of maize damage is equal to 2.2%, whereas doses causing 50% and 90% of barnyard grass damage are 1.1% and 1.7%, respectively. Plants sprayed with PN at 5% or 10% concentration caused significant drops in relative water content in leaves and Chlorophyll a fluorescence 72 h after spraying. In summary, peppermint nanoemulsion with Eco-Polysorbate 80 at 2% concentration is a perspective preparation for selective control of barnyard grass in maize. It should be analyzed further in controlled and field conditions.
1.3 Optimising Trajectories in Simulations with Deep Reinforcement Learning for Industrial Robots in Automotive Manufacturing

This paper outlines the concept of optimising trajectories for industrial robots by applying deep reinforcement learning in simulations. An application of high technical relevance is considered in a production line of an autmotive manufacturer (AUDI AG), where industrial manipulators apply sealant on a car body to prevent water intrusion and hence corrosion. A methodology is proposed that supports the human expert in the tedious task of programming the robot trajectories. A deep reinforcement learning agent generates trajectories in virtual instances where the use case is simulated. By making use of the automatically generated trajectories, the expert’s task is reduced to minor changes instead of developing the trajectory from scratch. This paper describes an appropriate way to model the agent in the context of Markov decision processes and gives an overview of the employed technologies. The use case outlined in this paper is a proof of concept to demonstrate the applicability of reinforcement learning for industrial robotics.
Comparison of Proclarix, PSA Density and MRI-ERSPC Risk Calculator to Select Patients for Prostate Biopsy after mpMRI

Simple Summary The selection of proper candidates for prostate biopsy after magnetic resonance imaging (MRI) has usually been studied in the overall population with suspected prostate cancer (PCa). However, the performance of these tools can change regarding the Prostate Imaging-Reporting and Data System (PI-RADS) categories. We compared three different tools: PSA density, MRI-ERSPC risk calculator and Proclarix in 567 men with suspected PCa (PSA > 3 ng/mL and/or abnormal rectal examination) in one academic institution. All patients underwent multiple transrectal ultrasound guided biopsies after a multiparametric MRI was performed. We concluded that in the overall population, MRI-ERSPC RC outperformed PSA density and Proclarix, whereas in patients with lesions PI-RADS < 3 Proclarix was better than the other tools. However, no tool guaranteed 100% detection of clinically significant PCa in PI-RADS 4 and 5. Abstract Tools to properly select candidates for prostate biopsy after magnetic resonance imaging (MRI) have usually been analyzed in overall populations with suspected prostate cancer (PCa). However, the performance of these tools can change regarding the Prostate Imaging-Reporting and Data System (PI-RADS) categories due to the different incidence of clinically significant PCa (csPCa). The objective of the study was to analyze PSA density (PSAD), MRI-ERSPC risk calculator (RC), and Proclarix to properly select candidates for prostate biopsy regarding PI-RADS categories. We performed a head-to-head analysis of 567 men with suspected PCa, PSA > 3 ng/mL and/or abnormal rectal examination, in whom two to four core transrectal ultrasound (TRUS) guided biopsies to PI-RADS ≥ three lesions and/or 12-core TRUS systematic biopsies were performed after 3-tesla mpMRI between January 2018 and March 2020 in one academic institution. The overall detection of csPCa was 40.9% (6% in PI-RADS < 3, 14.8% in PI-RADS 3, 55.3% in PI-RADS 4, and 88.9% in PI-RADS 5). MRI-ERSPC model exhibited a net benefit over PSAD and Proclarix in the overall population. Proclarix outperformed PSAD and MRI-ERSPC RC in PI-RADS ≤ 3. PSAD outperformed MRI-ESRPC RC and Proclarix in PI-RADS > 3, although none of them exhibited 100% sensitivity for csPCa in this setting. Therefore, tools to properly select candidates for prostate biopsy after MRI must be analyzed regarding the PI-RADS categories. While MRI-ERSPC RC outperformed PSAD and Proclarix in the overall population, Proclarix outperformed in PI-RADS ≤ 3, and no tool guaranteed 100% detection of csPCa in PI-RADS 4 and 5.
Heterologous Production of Acrylic Acid: Current Challenges and Perspectives

Acrylic acid (AA) is a chemical with high market value used in industry to produce diapers, paints, adhesives and coatings, among others. AA available worldwide is chemically produced mostly from petroleum derivatives. Due to its economic relevance, there is presently a need for innovative and sustainable ways to synthesize AA. In the past decade, several semi-biological methods have been developed and consist in the bio-based synthesis of 3-hydroxypropionic acid (3-HP) and its chemical conversion to AA. However, more recently, engineered Escherichia coli was demonstrated to be able to convert glucose or glycerol to AA. Several pathways have been developed that use as precursors glycerol, malonyl-CoA or β-alanine. Some of these pathways produce 3-HP as an intermediate. Nevertheless, the heterologous production of AA is still in its early stages compared, for example, to 3-HP production. So far, only up to 237 mg/L of AA have been produced from glucose using β-alanine as a precursor in fed-batch fermentation. In this review, the advances in the production of AA by engineered microbes, as well as the hurdles hindering high-level production, are discussed. In addition, synthetic biology and metabolic engineering approaches to improving the production of AA in industrial settings are presented.
Cumulative Endogenous Estrogen Exposure Is Associated With Postmenopausal Fracture Risk: The Women's Health Initiative Study

We aimed to evaluate the relationship between cumulative endogenous estrogen exposure and fracture risk in 150,682 postmenopausal women (aged 50 to 79 years at baseline) who participated in the Women's Health Initiative. We hypothesized that characteristics indicating lower cumulative endogenous estrogen exposure would be associated with increased fracture risk. We determined ages at menarche and menopause as well as history of irregular menses from baseline questionnaires and calculated years of endogenous estrogen exposure from ages at menarche and menopause. Incident clinical fractures were self‐reported over an average 16.7 years of follow‐up. We used multivariable proportional hazards models to assess the associations between the estrogen‐related variables and incidence of any clinical fracture. In fully adjusted models, those with the fewest years of endogenous estrogen exposure (<30) had an 11% higher risk of developing central body fractures and a 9% higher risk of lower extremity fractures than women with 36 to 40 years of endogenous estrogen exposure (the reference category). In contrast, women with the most years of endogenous estrogen exposure (more than 45 years) had a 9% lower risk of lower extremity fractures than the reference category. Women with irregular (not monthly) menstrual cycles were 7% to 8% more likely to experience lower extremity fractures than women with regular monthly cycles. Our findings support the hypothesis that characteristics signifying lower cumulative endogenous estrogen exposure are associated with higher fracture risk. © 2022 American Society for Bone and Mineral Research (ASBMR).
The Influence of Learning Mathematics in Online Learning on the Results of Mid-Semester Assessment

This research is a quantitative analytical survey research with an explanatory method in which the researcher attempts to explain to what extent the effect of learning mathematics on the results of mid-semester assessments for class VIII students in one of the junior high schools in Tangerang Regency. The sample of this research is students in class VIII. The sample selection was done randomly by taking 31 students from a total of 70 students. In collecting data related to student learning, we distributed a simple questionnaire by google form and to obtain data on the results of the mid-semester assessment of our students, we collaborated with the mathematics teacher in charge of the school. The results of this study stated that the way students learn in learning mathematics, especially in online learning, is said to have an effect of 11.45% on the results of the students' midterm assessment. the way to learn in online learning is divided into four sub categories of learning methods, including: how to take math lessons online, how to learn math independently at home, how to study math textbooks, and how to face math exams. Of these four sub-categories, three of them are in the good category in their implementation, while the sub-category of how to learn in online learning is in the sufficient category which indirectly means that there is still a need for re-evaluation related to the mechanism for implementing mathematics online learning.
Specific OWL-based RPG Ontology

This paper deals with a problem of describing role-playing games in a computer readable format, such as an ontology. Ontology as a model represents a union of gaming, knowledge and artificial intelligence aproaches, and is therefore interesting to research as a description of a domain included in the modern market of role-playing games (and especially massive multiplayer online role-playing games) that have a rich turnover and numerous players available, which makes them a suitable domain to be researched. In this paper an onotology used for describing MMORPGs is presented and discussed along with suggested possible future research.