Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Different Types of Motors for the Use in Electric Vehicles

Electric motors are regarded as the future and it is only imperative that we study more about how they can be made consumer-friendly in order to not only improve the adoption rate of electric vehicles but also improve the electrification of countries worldwide. An important aspect that needs to be studied is the type of motor that can provide us with the most value and price to performance ratio while considering its application in the field of electric vehicles. This paper provides a basic study and understanding of all the different motors available for usage in the field of electric vehicles and which kind of motors can prove to be a viable option with regards to usage in the field of electric vehicles.
I See Your Gesture: A VR-Based Study of Bidirectional Communication between Pedestrians and Automated Vehicles

Automated vehicles (AVs) are able to detect pedestrians reliably but still have difficulty in predicting pedestrians’ intentions from their implicit body language. This study examined the effects of using explicit hand gestures and receptive external human-machine interfaces (eHMIs) in the interaction between pedestrians and AVs. Twenty-six participants interacted with AVs in a virtual environment while wearing a head-mounted display. The participants’ movements in the virtual environment were visualized using a motion-tracking suit. The first independent variable was the participants’ opportunity to use a hand gesture to increase the probability that the AV would stop for them. The second independent variable was the AV’s response “I SEE YOU,” displayed on an eHMI when the vehicle yielded. Accordingly, one-way communication (gesture or eHMI) and two-way communication (gesture and eHMI combined) were investigated. The results showed that the participants decided to use hand gestures in 70% of the trials. Furthermore, the eHMI improved the predictability of the AV’s behavior compared to no eHMI, as inferred from self-reports and hand-use behavior. A postexperiment questionnaire indicated that two-way communication was the most preferred condition and that the eHMI alone was more preferred than the gesture alone. The results further indicate limitations of hand gestures regarding false-positive detection and confusion if the AV decides not to yield. It is concluded that bidirectional human-robot communication has considerable potential.
Innovative Therapeutic Approaches to Fight Glioblastoma

3 INTRODUCTION . 5 CLASSIFICATION OF GLIOBLASTOMAS . 5 GLIOMAGENESIS . 6 ANGIOGENESIS . 7 CLINICAL PRESENTATION . 7 DEVELOPMENT OF NOVEL THERAPIES FOR GBM – CHALLENGES . 7 GLIOBLASTOMA CURRENT TREATMENT OPTIONS . 8 SURGERY . 8 RADIOTHERAPY (RADIATION THERAPY) . 8 CHEMOTHERAPY . 8 TUMOUR TREATING FIELDS (TTFS) . 10 NITROSOUREAS . 10 ▪ Gliadel wafers . 10 ▪ Lomustine (CCNU) . 11 BEVACIZUMAB . 11 INNOVATIVE THERAPEUTIC APPROACHES TO FIGHT GLIOBLASTOMA . 12 TARGETED THERAPIES . 12 ▪ RTK/PI3K/MAPK Pathways . 12 • Epidermal Growth Factor Receptor inhibitors (EGFR) . 14 • Platelet-Derived Growth Factor Receptor (PDGFR) . 15 ▪ p53 Pathway . 16 ▪ Retinoblastoma protein (pRb) Pathway . 16 ▪ Others . 17 • Polyamine Biosynthetic Pathway . 17 IMMUNOTHERAPY . 17 ▪ Adoptive cellular therapies (ACT) . 17 • CAR-T Cells Therapy . 17 • TIL Therapy . 18 • TCR Therapy . 18 ▪ Vaccine Therapy . 18 • Dendritic Cell Vaccines . 18 • Peptide Vaccines . 19 • Heat Shock Protein Vaccination . 19 ▪ Checkpoint Inhibition . 20 VIROTHERAPY . 20 GENE THERAPY . 21 OTHER POTENTIAL THERAPIES . 21 ▪ Cholesterol Metabolism . 21 ▪ Hyperthermia . 21 CONCLUSION . 22 REFERENCES . 23
PixelEDL: Unsupervised Skill Discovery and Learning from Pixels

We tackle embodied visual navigation in a task-agnostic set-up by putting the focus on the unsupervised discovery of skills (or options [2]) that provide a good coverage of states. Our approach intersects with empowerment [10]: we address the reward-free skill discovery and learning tasks to discover what can be done in an environment and how. For this reason, we adopt the existing Explore, Discover and Learn (EDL) [1] paradigm, tested only in toy example mazes, and extend it to pixel-based state representations available for embodied AI agents. The information-theoretic paradigm of EDL [1] aims to learn latent-conditioned policies, namely skills π(a|s, z), by maximizing the mutual information (MI) between the inputs s and some latent variables z. Hence, EDL [1] consists of unsupervised skill discovery and training of reinforcement learning (RL) agents without considering the existence of any extrinsic motivation or reward. We present PixelEDL, an implementation of the EDL paradigm for the pixel representations provided by the AI Habitat [11] and MineRL [3] environments. In comparison with EDL, PixelEDL involves self-supervised representation learning of image observations for information-theoretic skill discovery. Still, PixelEDL aims to maximize the MI between inputs and some latent variables and for that it consists of the same three stages of EDL (explore, discover and learn). By breaking down the RL end-to-end training pipeline into the three stages, we also simplify the implicit difficulty in learning both representations and policies from a high dimensional input space all at once [7].
Brooks-Iyengars Real-Time Sensing Algorithm for Future

The article primarily benevolences a two-decade longstanding and most influential Brooks Iyengar’s Hybrid algorithm known as Robust Distributed Computing and Sensing Algorithm. The algorithm has established a foundation mark across various real time operating systems, application areas and fault tolerant schemes. The crucial contribution of the algorithm is majorly found in enhancing the features of MINIX real-time operating system, the hybrid architecture and scalability of the algorithm is proficient enough to encounter the unreliable and distributed sensors data using the Byzantine agreement and distributed decision-making process methods. This article emphasises on inclusion and adoption of most persuasive long running Brooks Iyengar’s algorithm in MINIX real-time operating system and their recent enhancement of incorporating the fault tolerant schemes. Further, the richness of algorithm has acclaimed by millions of vivid category of users around the globe in their research and tasks. Most significantly the algorithm is beneficial to DARPA, Open Source - Linux, IT Industry - Bae Systems and BBN technologies, Academics – Universities of Maryland, Georgia Tech, Purdue, Clemson and Wisconsin etc., and Research Labs like Penn State Applied Research Lab (ARL), USC/ISI. Additionally, the scalability of algorithm proved to be beneficial to other domains like cyber physical systems, robot merging, high-performance computing, reliability of software and hardware appliance and artificial intelligence systems. In this paper, we attempt to showcase the use cases and real-time deployments of Brooks-Iyengar algorithm in various aspects of physical world. Finally, the influence of algorithm across real-time MINIX operating systems. the output produced by the algorithm is real value with appropriate stipulated accuracy. The algorithm is further customised to resemble crusader’s convergence algorithm (CCA) [7], this adoption increases the bandwidth requirement in processing of algorithm. The benefits of algorithm are wide spread across domain like high-performance computing [8], distributed control, software reliability and
BREAKING GROUND IN A TEACHER EDUCATION PROGRAM THROUGH THE IMPLEMENTATION OF FLIPPED LEARNING

This paper describes an ongoing study performed within a teacher education program. This study explores student teachers’ perceptions in relation to self-regulated learning with the purpose of laying the foundations for the implementation of the Flipped Learning approach. Participants are prospective language teachers enrolled in an English Didactics class. The information was collected by means of students and professors’ surveys, a focus group, prospective teachers’ reflections and researchers’ field notes. Data was analyzed using the principles of thematic analysis. The first phase of this research illustrated student teachers’ views concerning self-regulated learning and the role their professors play in their training and their future performance as teachers. Initial findings revealed that it is necessary to train learners on self-regulatory behaviors and transform professors’ roles into facilitators as a necessary condition for Flipped Learning to take place.
Beware: Mobile and Web Application to Prevent Crimes against the Patrimony, Life, Body and Health

—Faced with the difficulty to know all the dangerous areas and find the latest information to avoid becoming the victim of a crime, this article proposes a mobile application for smartphones and smartwatches called Beware , which shows the dangerous zones within a specific geographical area according to the day and time of the week. This application also allows reporting emergencies to the corresponding emergency service entities and communicating events that put at risk the patrimony, life, body and health of other users and yourself. In addition, another Web application is proposed for the emergency service (police station, fire brigade or municipal patrols) responsible for receiving the emergency calls. User tests show that 14 out of 15 citizens consider that the proposed application is useful and very useful for public safety.
Designing a Sustainable Procurement System Model SNI

This research aims to design a model of a sustainable procurement system in SKK Migas in supporting and strengthening the sustainable upstream oil and gas procurement sector. Oil and gas commodity is one of the natural resources that cannot be renewed in a short time and is very important in the world after water resources. However, recently, there have been many challenges faced in managing the national oil and gas industry, one of which is the condition of reserves oil and gas that continues to decline and new reserves that are more difficult to find technically and require larger costs. To survive facing the challenges and volatility in the oil and gas industry, as well as make an optimal contribution to the achievement of production and state revenue from the upstream oil and gas sector, cost control is needed for efficient operations including through the implementation of sustainable principles in the strategy of procurement management of goods and services refer to SNI ISO 20400: 2017. The result showed that the analysis of questionnaire data through SEM LISREL and design concepts using PDCA with the conclusion that the design of a sustainable procurement system model is valid.
S PEEDING U P N EURAL N ETWORK V ERIFICATION VIA A UTOMATED A LGORITHM C ONFIGURATION

Despite their great success in recent years, neural networks have found to be vulnerable to adversarial attacks. These attacks are often based on slight perturbations of given inputs that cause them to be misclassified. Several methods have been proposed to formally prove robustness of a given network against such attacks. However, these methods typically give rise to high computational demands, which severely limit their scalability. Recent state-of-the-art approaches state the verification task as a minimisation problem, which is formulated and solved as a mixed integer linear programming (MIP) problem. We extend this approach by applying automated algorithm configuration techniques to the solver and, more specifically, construct a portfolio of MIP solver configurations optimised for the neural network verification task. Thereby, we achieve a substantial reduction in CPU time by a factor of 4.7 when verifying a neural network classifier on the MNIST dataset and, at the same time, reduce the number of timeouts by a factor of 1.42 compared to the state of the art.
Reprogramming of Automotive Electronic Control Units: A Review on Evolution of Automotive Reprogramming

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Automotive suppliers together with OEMs (Original Equipment Manufacturers) follow some crucial steps to check the security of Electronic Control Units (ECU). Control units are verified to check if it is working in a secure and efficient environment. This process is assisted by updating the software of ECUs to the latest version available through a process called reprogramming. This process also helps the control units to be equipped with the latest security patches and bug fixes. This paper attempts to review the evolution trend to improvise the reprogramming practice.
Analysis of Volatile Compounds in Jingzhi Baigan Liquor by Liquid-liquid Extraction(LLE) and Gas Chromatography-Mass Spectrometry(GC-MS)

Volatile compounds of Jingzhi Baigan liquor were analyzed by liquid-liquid extraction and gas chromatographymass spectrometry and identified by mass spectral library searching and comparison of retention indexes. Different compounds were extracted by using different kinds of organic solvents with various polarities. The results showed that 30 compounds were identified in n-pentane extract compared to 29 compounds in ethyl ether extract and 35 compounds in dichloromethane extract. In total, 65 compounds were extracted with three organic solvents including 9 alcohols, 19 esters, 11 acids, 14 alkanes, 3 aromatics, 3 furans, 3 aldehydes, 1ketones, 1 nitrogenous compound and 1 sulfocompound.
STORM: Refinement Types for Secure Web Applications

We present S TORM , a web framework that allows developers to build MVC applications with compile-time enforcement of centrally speciﬁed data-dependent security policies. S TORM ensures security using a Security Typed ORM that reﬁnes the (type) abstractions of each layer of the MVC API with logical assertions that describe the data produced and consumed by the underlying operation and the users allowed access to that data. To evaluate the security guarantees of S TORM , we build a formally veriﬁed reference implementation using the Labeled IO (LIO) IFC framework. We present case studies and end-to-end applications that show how S TORM lets developers specify diverse policies while centralizing the trusted code to under 1% of the application, and statically enforces security with modest type annotation overhead, and no run-time cost. Abstract Our artifact contains (a snapshot of) the source code for the implementation of S TORM from § 5, the formally veriﬁedrefer-ence implementation λ S TORM described in § 6), the various policies, case-studies and applications used in our evaluation § 7. The artifact provides a we provide show Next, the shows how
The clinical application of preoperative self-anticipated pain score and the correlation with surgical pain after elective surgery - a prospective observational study

Background: Current principles of postoperative pain management are primarily based on the types and extent of surgical intervention. This clinical study measured patient’s self-anticipated pain score before surgery, and correlated the scores with the pain levels and analgesic requirements after surgery.Methods: This prospective observational study recruited consecutive patients who received elective surgery in the E-Da Hospital, Taiwan from June to August 2018. Patients were asked to subjectively rate their highest anticipated pain level (numerical rating scale, 0-10) for the scheduled surgical interventions during their preoperative anesthesia assessment. After the operation, the actual pain intensity (NRS 0-10) experienced by the patient in the post-anesthesia care unit and the total dose of opioids administered during the perioperative period were recorded. Pain scores ³4 on NRS were regarded as being unacceptable levels for anticipated or postoperative pain.Results: A total of 996 patients were included in the study. Most of the patients (86%) received general anesthesia and 73.9% of them had a history of previous operation. Female anticipated significantly higher overall pain intensities than the male patients (adjusted odd ratio 1.532, 95% confidence interval 1.125-2.086; P=0.007). Patients who took regular benzodiazepine at bedtime (P=0.040) and those scheduled to receive more invasive surgical procedures were most likely to anticipate for higher pain intensity at the preoperative period (P<0.001). Although higher anticipated pain scores (NRS³4) were associated with higher postoperative pain levels (P=0.021) and higher total equivalent opioid dose (P=0.001) for acute pain management during the perioperative period, these surgical patients actually experienced less pain than they anticipated at the post-anesthesia care unit.Conclusion: This observational study found that patients who are female, use regular benzodiazepines at bedtime and scheduled for more invasive surgeries anticipate significantly higher surgery-related pain. Therefore, appropriate preoperative counseling for analgesic control and the management of exaggerated pain expectation in these patients is necessary to improve the quality of anesthesia delivered and patient’s satisfaction.
An Extant Review of Literature on Hrd Practices, Knowledge Management and Organizational Performance

Managing business strategically has given rise to the importance of HR as the essential source of competitive advantage. The theory of resource justifies that sustained competitive advantage can only be achieved by valuing the human capital as it is difficult for others to imitate as compared to other resources like raw materials, technology, process, etc. are easy to imitate; hence, HR may be taken as the most important source of sustained competitive advantage. Therefore, the use of strategic management in examining the role of HR as capital has forced to expand the focus of HRM research as a strategic approach (Baird and Meshoulm, 1988). Management of HR in a strategic manner to achieve sustained competitive advantage makes HRM climate and culture apparent for OP, such as increased satisfaction, commitment, employee and customer retention.KM has come out as a critical concept for improving OP through improved use of knowledge and for minimizing the loss of valuable knowledge when employees leave. HRD Climate is frequently observed as a key empowering influence of KM. In acknowledgment of the importance of knowledge in OP, the field of KM developed as an emphasis on improved comprehension of the procedures and their connections to OP in current organizations. At the same time, the field of HRD rose with attention to improved comprehension of the procedures of learning and advancement (L&D) in organizations and their connections to Perf. KM and HRD appear to entwine normally in their ways to deal with OP.HRD practices change the capabilities of employees at all levels in an organization and in this way assume a significant role in driving advancement and development. Individuals' capabilities and how those capabilities are utilized within the organization due to advancements in the systems and processes of HR management involving HRD helps to leverage the many-fold benefits. In that trio of extraordinary capacities, HRD centers focus on learning and improvement at the individual, group, and organizational levels that happens when employees have the knowledge, competencies, skills and attitude for getting the hang of, facing attentive challenges, sharing information, and thinking imaginatively, and when organizations offer help by managing it through effective KM. Ishak et al. (2010) propose KM is fundamental for building up the human asset. It is additionally recommended that HRD is fundamental for developing the knowledge that flows through the KM framework. Hence, the purpose of this study is to investigate the pathways leading from HRD to OP through KM as a mediator and presenting a comprehensive framework for steel companies of India to strategies effective HRD practices for better and effective KM for enhanced Perf organization-wide.
Removal of a Cationic Dye from Aqueous Solution Using Graphene Oxide Nanosheets: Investigation of Adsorption Parameters

In this study, graphene oxide (GO) nanosheets have been used for the adsorption of methyl green, a cationic dye from aqueous solution. GO nanosheets consist of single layered graphite structure decorated with a number of oxygen containing functionalities such as carboxyl, epoxy, ketone, and hydroxyl groups which impart a negative charge density to it in aqueous solution at a wide range of pH. Thus, GO nanosheets can be predicted as a good adsorbent material for the adsorption of cationic species. The adsorption of the methyl green onto the GO nanosheets has been carried out at different experimental conditions such as adsorption kinetics, concentration of adsorbate, pH, and temperature. The kinetics of the adsorption data were analyzed using four kinetic models such as the pseudofirst-order model, pseudosecond-order model, intraparticle diffusion, and the Boyd model to understand the adsorption behavior of methyl green onto the GO nanosheets and the mechanism of adsorption. The kinetics of adsorption resu.
Trust-Free Banking missed the Point - the effect of Distrust in banks on the Adoption of Decentralized Finance

During the global financial crisis in 2008, trust in established financial intermediaries declined sharply. In reaction, blockchain technology was developed as an alternative system to facilitate financial transactions devoid of intermediaries. The application of blockchain in the financial sector brought a new paradigm called Decentralized Finance. Employing a modified technology acceptance model, our study aims at examining the relationship of distrust in financial intermediaries and consumer’s behavioral intention to use Decentralized Finance. Even though this relationship is well-documented regarding the motivation of the development of blockchain technology, as well as in cases of unstable financial systems, empirical data from our survey research does not support this relationship in the context of consumer adoption. Our study contributes to the theory on the foundations of DeFi and the impact of blockchain technology, which must be revised by future research. Further, we propose a trust paradox in the financial sector.
TCAD Simulation of Nano-Scale in AlN/GaN High Electron Mobility Transistor for High Power Millimeter Wave Applications

1-4Student, Dept. of Electronics and Communication Engineering, ANITS College, Visakhapatnam, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract The and microwave characteristics of gate length depletion mode (D-mode) High electron mobility transistor ( ) on substrate with heavily doped source and drain region have investigated using Synopsys TCAD tool. The device having the features of recessed T gate structure, back barrier and passivated device surface. The proposed exhibits a peak drain current density of , transconductance of , current gain cut-off frequency of and power gain cut-off frequency of . At room temperature the measured carrier mobility( ) , sheet charge carrier density ( ) and breakdown voltage are ( ), ( ) and respectively. The superlatives of the proposed are bewitching competitor for future sub-millimeter wave high power circuit applications.