Miracle-dz/UniFAR-FTUs huggingface dataset:
An Exploratory Integrative Review of Restorative Justice and Social Work: Untapped Potential for Pursuing Social Justice

ABSTRACT Restorative justice is an approach that centers the voices of those most impacted by harm through facilitated dialogue, perspective-taking, and storytelling. Restorative justice and social work have mutually beneficial and overlapping values and interests. The aim of this integrative review was to determine how and in what settings these two areas have been integrated over time. Eight academic research databases were searched between 1997-2019, resulting in 27 articles that met our search criteria. We identified three primary themes: conceptual articles, articles related to practice, and articles pertaining to social work education. Our findings indicate the need to implement restorative justice approaches in other social work practice settings beyond the criminal justice system and incorporate restorative justice into social work curricula.
A Vertical stratification of arthropods in the dry ecosystems of Colombian Guyana: morphological patterns and their ecological implications

Introduction: Despite growing interest by the ecosystems derived from the Guyanese formations, the vertical structure of the communities and relationships of the biota with the climatic conditions in these ecosystems are unknown. Objective: Characterize the structure and vertical composition of the arthropod fauna associated with three of the most representative ecosystems of the Northern area of the serranía de La Lindosa in Colombia based on morphological and ecological parameters. Methods: The arthropod fauna was sampled, from the subsurface soil level to the shrub and tree stratum. The fauna was determined up to the level of family or supraspecific group and the values of Alfa and Beta diversity were determined. Body length measurements were made, and the coloration and trophic level of each group were determined. Results: The composition and diversity of the arthropod fauna was different in each ecosystem and vertical stratum and most of the groups in all the ecosystems studied present low abundances. Groups of phytophagous and predatory habits were frequent in all ecosystems and the highest biomass of arthropod fauna comes from groups of polyphagous habits, of medium size and great abundance. Light and dark colorations are the most frequent in landscape-scale. Conclusion: The ecosystems studied are characterized by the low values of diversity and replacement and the large number of non-shared groups that apparently respond to the microclimatic characteristics; however, there are some generalities on a landscape scale such as the greater richness and abundance of groups in the intermediate strata, the greater proportion of groups with phytophagous habits and medium body sizes, and the predominance of dark colorations in the lower strata.
Studies of the weak interaction in atomic systems: towards measurements of atomic parity non-conservation in francium

Tests of the standard model of particle physics should be carried out over the widest possible range of energies. Here we present our plans and progress for an atomic parity non-conservation experiment using the heaviest alkali, francium (Z = 87), which has no stable isotope. Low-energy tests of this kind have sensitivity complementary to higher energy searches, e.g. at the large hadron collider.
Designing a multivariate–multistage quality control system using artificial neural networks

In most real-world manufacturing systems, the production of goods comprises several autocorrelated stages and the quality characteristics of the goods at each stage are correlated random variables. This paper addresses the problem of monitoring a multivariate–multistage manufacturing process and diagnoses the possible causes of out-of-control signals. To achieve this purpose using multivariate time series models, first a model for the autocorrelated data coming from multivariate–multistage processes is developed. Then, a single neural network is designed, trained and employed to control and classify mean shifts in quality characteristics of all stages. In-control and out-of-control average run lengths and correct classification ratio indices have been chosen to investigate the performance of the designed network. The results of a simulation study show that the network is capable of detecting both in-control and out-of-control signals appropriately.
An RNA-binding switch drives ribosome biogenesis and tumorigenesis downstream of RAS oncogene

Oncogenic RAS signaling reprograms gene expression through both transcriptional and post-transcriptional mechanisms. While transcriptional regulation downstream of RAS is relatively well characterized, how RAS post-transcriptionally modulates gene expression to promote malignancy is largely unclear. Using quantitative RNA Interactome Capture analysis, we reveal that oncogenic RAS signaling reshapes the RNA-bound proteomic landscape of cancer cells, with a network of nuclear proteins centered around Nucleolin displaying enhanced RNA-binding activity. We show that Nucleolin is phosphorylated downstream of RAS, which increases its binding to pre-ribosomal-RNA (rRNA), boosts rRNA production, and promotes ribosome biogenesis. This Nucleolin-dependent enhancement of ribosome biogenesis is crucial for RAS-induced cancer cell proliferation, and can be targeted therapeutically to inhibit tumor growth. Our results reveal that oncogenic RAS signaling drives ribosome biogenesis by regulating the RNA-binding activity of Nucleolin, and highlight the crucial role of this process in RAS-mediated tumorigenesis.
Sliding Windows: A Software Method Suitable for Real-Time Inspection of Textile Surfaces

There is a strong interest in expert systems to assist in complex defect identification procedures. To increase accuracy, attempts are made to enhance traditional human inspection by automated visual systems, which employ cameras and image processing routines. It is important that the software core of such a system is based on a robust, fast texture segmentation technique. Many texture segmentation techniques have been pre sented in the literature. Unfortunately, despite the fact that they achieve good results, they are computationally complex and therefore not suitable for real-time applications, since as the complexity of an algorithm grows, it becomes more and more difficult to execute the image examination in real time. This paper presents a detailed description of a fast algorithm for defect detection in textile surfaces and an evaluation of the experimental results for 137 digitized images of representative defects in woven fabrics collected from a larger sample provided by textile companies.
Spread spectrum communications using chirp signals

We report on the use of broadband chirp signals for spread spectrum systems in indoor applications. The presented system concepts make use of chirp transmission and pulse compression. Different modulation schemes for the chirp signals resulting in different system performance and complexity are compared in terms of bit error rate for the AWGN channel and for frequency selective indoor radio channels. We present simulations and measurement results from demonstrator systems which use surface acoustic wave (SAW) devices for the generation and matched altering of the chirp signals. The RF and IF frequency and transmission bandwidth of the presented systems are 2.4 GHz, 348.8 MHz, and 80 MHz, respectively. Due to the processing gain of 16 dB-made possible by the use of SAW devices-and the large transmission bandwidth the system is insensitive against frequency selective fading, CW interference and noise.
Neural control of high performance drives: an application to the PM synchronous motor drive

An increasing role of artificial neural networks (ANNs) in various engineering applications has spurred interest in power electronics and motor drives. In this paper, ANNs are utilized to achieve vector control end parameter compensation for the high performance control of the permanent magnet synchronous motor (PMSM). The overall system is capable of achieving concurrent mutual flux linkages and torque control in the presence of parameter variations and over a wide range of speed. A requirement of this system is an on-line estimation of the respective varying parameters. The proposed method is the most feasible and accurate for PMSM control. This study provides a generalized framework for ANN applications to high performance control of AC machines.
Quantum well resonant tunneling bipolar transistor operating at room temperature

The first resonant tunneling bipolar transistor (RBT) is reported. The AlGaAs/GaAs wide gap emitter device, grown by molecular beam epitaxy, contains a GaAs quantum well and two AlAs barriers between the emitter and the collector. In the common emitter configuration, when the base current exceeds a threshold value, a large drop in the collector current (corresponding to a quenching of the current gain β) is observed at room temperature along with a pronounced negative conductance as a function of the collector-emitter voltage. These striking characteristics are caused by the quenching of resonant tunneling through the double barrier as the conduction band edge in the emitter is raised above the bottom of the first quantized subband of the well. Single frequency oscillations are observed at 300 K. The inherent negative transconductance of these new functional devices is extremely valuable for many logic and signal processing applications.
A New Socially Assistive Robot with Integrated Serious Games for Therapies with Children with Autism Spectrum Disorder and Down Syndrome: A Pilot Study

This work introduces a new socially assistive robot termed MARIA T21 (meaning “Mobile Autonomous Robot for Interaction with Autistics”, with the addition of the acronym T21, meaning “Trisomy 21”, which is used to designate individuals with Down syndrome). This new robot is used in psychomotor therapies for children with Down syndrome (contributing to improve their proprioception, postural balance, and gait) as well as in psychosocial and cognitive therapies for children with autism spectrum disorder. The robot uses, as a novelty, an embedded mini-video projector able to project Serious Games on the floor or tables to make already-established therapies funnier to these children, thus creating a motivating and facilitating effect for both children and therapists. The Serious Games were developed in Python through the library Pygame, considering theoretical bases of behavioral psychology for these children, which are integrated into the robot through the robot operating system (ROS). Encouraging results from the child–robot interaction are shown, according to outcomes obtained from the application of the Goal Attainment Scale. Regarding the Serious Games, they were considered suitable based on both the “Guidelines for Game Design of Serious Games for Children” and the “Evaluation of the Psychological Bases” used during the games’ development. Thus, this pilot study seeks to demonstrate that the use of a robot as a therapeutic tool together with the concept of Serious Games is an innovative and promising tool to help health professionals in conducting therapies with children with autistic spectrum disorder and Down syndrome. Due to health issues imposed by the COVID-19 pandemic, the sample of children was limited to eight children (one child with typical development, one with Trisomy 21, both female, and six children with ASD, one girl and five boys), from 4 to 9 years of age. For the non-typically developing children, the inclusion criterion was the existence of a conclusive diagnosis and fulfillment of at least 1 year of therapy. The protocol was carried out in an infant psychotherapy room with three video cameras, supervised by a group of researchers and a therapist. The experiments were separated into four steps: The first stage was composed of a robot introduction followed by an approximation between robot and child to establish eye contact and assess proxemics and interaction between child/robot. In the second stage, the robot projected Serious Games on the floor, and emitted verbal commands, seeking to evaluate the child’s susceptibility to perform the proposed tasks. In the third stage, the games were performed for a certain time, with the robot sending messages of positive reinforcement to encourage the child to accomplish the game. Finally, in the fourth stage, the robot finished the games and said goodbye to the child, using messages aiming to build a closer relationship with the child.
Water resource prospects for the next 50 years on the water planet: personal perspectives on a shared history from Earth Day, the Fourth Industrial Revolution and One Health to the futures of alternative energy, bioconvergence and quantum computing

ABSTRACT The history and the future of water resource management as well as the endeavours that it influences are inextricably woven into the fabric of the past, current and future states of all life on our watery planet. From the first Earth Day in 1970 and the founding of the International Water Resources Association (IWRA) in 1971 to the development of modern biotechnology applications and alternative energy sources across subsequent decades, this paper reflects on these and other historical underpinnings of how we manage the use of our essential water resources now and might hope to in the future.
Online Verification of Impact-Force-Limiting Control for Physical Human-Robot Interaction

Humans must remain unharmed during their interaction with robots. We present a new method guaranteeing impact force limits when humans and robots share a workspace. Formal guarantees are realized using an online verification method, which plans and verifies fail-safe maneuvers through predicting reachable impact forces by considering all future possible scenarios. We model collisions as a coupled human-robot dynamical system with uncertainties and identify reachset-conforming models based on real-world collision experiments. The effectiveness of our approach for human-robot co-existence is demonstrated for the human hand interacting with the end effector of a six-axis robot manipulator with force sensing. By integrating a human pose detection system, the efficiency of robot movements increases.
Deep Learning Model for Content Aware Caching at MEC Servers

In recent years, mobile data traffic has increased enormously with an increase of mobile and smart devices. The global mobile data traffic is set to increase manifold in the coming years. With the rise in mobile data traffic and heterogeneous mobile devices, substantial improvement has been achieved in wireless media technology in providing a varied range of multimedia services. These multimedia services are often resource-hungry and require high-speed data and low latency transmissions. High-speed networks like the fifth-generation (5G) network helps in faster data delivery resulting in less congestion at the backhaul links and higher transmission capacity. Integrating Mobile Edge Computing (MEC) capabilities into the cellular architecture provides advantages like intelligent and efficient context-aware caching and video adaptations for content delivery. The primary objective of this work is to reduce the overall backhaul congestion and access delay by increasing the cache hit rate at the MEC server. This work proposes a deep learning-based model for caching at the MEC servers based on the content popularity at different time slots of a day. Experimental results reveal that the proposed model outperforms the state-of-the-art standard caching approaches, improves the cache hit probability by almost 21%, and decreases backhaul usage and access delay by approximately 18%.
Microstrip X-band Antenna with Improvement in Performance Using DGS

Simple and new microstrip patch (MSP) antenna for dual operation in X-band using Defective Ground Structure (DGS) is proposed here. DGS structure is used for improving the performance of microstrip patch antenna. By using four rectangular slots in patch we achieved two frequency bands one (9.24-9.68GHz) and other band (11.63-11.87GHz) both are in X-band. And for improving parameter like return loss, bandwidth, gain and directivity of MSP antenna one rectangular slot is cut in ground plane. The proposed antenna is compact in size with dimension 10 x 10 x 1 mm 3 with the ground plane. For designing and fabrication of this structure FR-4 substrate of thickness 1 mm with Dielectric constant 4.9 is used. The parameters of proposed antenna like return loss; Voltage Standing Wave Ratio (VSWR), radiation pattern; gain and directivity are simulated and analyzed using commercial computer simulation technology microwave studio (CST MWS). A good agreement between simulated and measured results is obtained. The designed antenna structure is very simple, compact and occupies less space all these qualities make this antenna suitable for practical applications. The main application of proposed antenna is to make compatible with radiolocation, radio navigation and fixed satellite applications in X-band (8-12GHz).
Prediction of Financial Revenue in Guizhou Province Based on Improved Grey Combination Models

In order to predict accurately the total government revenue in Guizhou, two improved grey models were presented and have higher forecasting accuracy than original grey model, then combined with BP neural network model and higher precision is achieved; besides, the improved grey models integrated with Markov chain were used to forecast public finance budget revenue in Guizhou and provide obviously better accuracy than grey model. Finally, the Grey-Markov models were combined and then further improve the fitting precision. The results show that the methods of grey combination models are feasible and effective in forecasting the revenue.
Cyber security using Machine Learning in Digital Education industry

In modern digital era, as the technological advancements are touching the new heights over internet, so is the crimes related to it. Education industry is no exception. Education sector is facing many cyber threats like application security, patching cadence and point to point security. It is important to understand the need of cyber security and what is at risk. In this paper, we bring light on existing scenario of cyber security in Education including the challenges and how we can make it as a priority, by implementing cyber security through machine learning techniques. Machine learning, subsets of artificial intelligence, for security in cyber world has become an avenger, due to its effectiveness. It provides great help to detect any threats in security, far better than any other software oriented ways, which is a great helps to security analysts.
A study on the directional sensitivity of intracranial responses following head impact

The objective of the present study was to investigate the directional sensitivity of intracranial responses following head impact using a validated mid-sized finite element model of Chinese human head. An impact force was applied to different locations of the model with deformable skull and rigid skull, respectively, under the same boundary conditions. Then a translational acceleration was applied to the rigid skull by keeping the same head position resulting in the same head injury criteria (HIC) as in the cases with impact force. The results showed that directional effect of head impact altered intracranial responses and injury patterns. Brain tissue at impact site was at high risk of contusion during vertical impact and corpus callosum was vulnerable to the impact at forehead when the head was impacted in a 45 degree angle. It was also found that this sensitivity contributed more by a rigid skull than a deformable one.
Neural system for tracking and classification of primary radar echo signals

This work presents a system designed to acquire primary echo radar from aircraft and to operate a classification based upon spectral consideration of the retrieved echo. Fine spectral consideration is carried out exploiting the jet engine modulation (JEM) phenomenon due to the modulation on the primary echo introduced by engine rotating parts. Classification efforts are obtained by the use of a neural network previously trained, put on the system as a classification sub system. Target parameters are investigated analyzing effective signals obtained by two operating radars with an experimental system specifically designed for real time tracking of civilian aircraft using an acquisition sub-system, PC based, interfaced with the radar circuitry.
Uncertainty analysis for flood defence systems in the Netherlands

Reliability and risk assessment becomes more and more important as a background for deci-sion making in the field of flood defence design in The Netherlands. In this development reliability experts have to cooperate with a large group of hydraulic, geotechnical, structural and mechanical engineers. This co-operation leads to many discussions related to the exact meaning of both input and output of the failure prob-ability calculations. Additionally, there are from time to time also discussions with civil servants, politicians and the public in general. In those discussions confusion often seems to be a major key word. This holds in particular for the debates on so called epistemological or knowledge uncertainties. This paper summarises a number of the discussions that have taken place in the past few years and hopefully contributes to a gradual better communication on this difficult but important issue.
OPTIMIZED POST-TENSIONING ANCHORAGE IN PRESTRESSED CONCRETE I-BEAMS

Anchorage zones in prestressed concrete I-beams are designed to accommodate anchorage hardware and to provide adequate space for the reinforcement needed to distribute the highly concentrated post-tensioning force. Based on analytical and full-scale experimental studies, optimized anchorage zone details have been developed. The proposed standardized anchorage zone is suitable for use with a post-tensioning tendon size up to 1-0.6 in. (15 mm) diameter strands. It has a width of 28.5 in. (725 mm), which tapers for a distance of 39.4 in. (1000 mm) to the standard I-beam web width. Standard welded wire reinforcement is proposed for post-tensioning of up to three 15-0.6 in. diameter standard tendons. The use of reduced block size can result in a weight reduction of as much as 80% compared to the commonly used anchorage block. A detailed example is included to demonstrate application of the strut and tie model to the design of the anchorage zone.
INVESTIGATION OF THE EFFECTS OF USING AUGMENTED REALITY APPS ON STUDENTS' LEARNING ACHIEVEMENT AND MOTIVATION IN ENGINEERING DRAWING COURSES

: In engineering education Virtual Reality (VR) and Augmented Reality (AR) technologies have been recently adopted in the teaching of technical subjects showing good potential for visual interaction with the objects. This study aims to investigate the effect of using a specifically developed mobile AR Engineering Drawing (ED) application (Apps) for improving the cognitive learning levels of students and learning achievement. In this study, experimental design with pre-test and post-test control groups and interview were used to measure of participants’ success. For this purpose, a total of 30 participants involved in the experimental group used AR application for training, whereas another 20 participants without AR training were kept as a control group. The increase in performance between pre-test and post-test was 39.7% for the experimental group and 17.2% for the control group. The results indicated a 19.6% higher learning performance in the experimental group through the use of the AR application for training. This result shows the very important effect the mobile AR engineering drawing application had in terms of acquiring new knowledge and skills on the participants. The study also shows that teaching Engineering Drawing subjects using AR Apps significantly increases students' conceptual and cognitive comprehension levels.