Miracle-dz/UniFAR-FTUs huggingface dataset:
Patterns, outcomes, and risk factors of mild head injuries in children: do we know enough?

Background: Mild head injuries in children are associated with morbidity and family distress. Though they are common causes of emergency department visits, they have been studied less than other more severe types of head trauma. This study aims to contribute to the reduction of this gap. Method and Materials: The medical records of 381 children with mild head injuries were reviewed and analyzed. Identification of any associated risk factors has been attempted with regression analysis. Results: The age group of 6-8 years was the most affected (44.6%). There was male predominance. Incidence presented seasonal variation. Concussion diagnosis was set in one tenth of patients. Half of children were under adult supervision during the traumatic incident. Cranial radiography was routinely performed in almost all patients, and computed tomography in 1.8%. Neurosurgical consultation was requested in 8.1%. Pedestrians, bicycle-riders, and car-passengers were at most risk of suffering mild head injury. Occurrence at street and playgrounds were risk factors for coexisting abdominal injuries. Absence of adult supervision was a risk factor for bicycle-riders, and occurrence at school for neurosurgical consultation. Conclusions: Mild head injuries occur more often at the streets of urban areas. Clinical observation for 24 hours is considered satisfactory for a safe outcome. Identification of risk factors of mild head injuries may improve both prevention and outcome. Improvement of training of physicians in pediatric trauma is also required. Quality of adult supervision is important to improve prevention.
Transient Vibration by Vector Methods

Summary In control theory, stability is investigated by established techniques such as the root-locus method. The same techniques may be applied to the control equivalent of a mechanical system and will show the transient state of the system. Vector methods such as are used to solve vibration problems may also be extended to give transients. This note gives a vector representation of the transient vibration of a one degree of freedom system possessing inertia, elasticity and viscous damping. For the transient which is set up by a change in the steady vibration of the system, the initial amplitude and phase angle are readily found by vector methods. This information is sufficient to define the transient.
Wireless state feedback and control of a pipe inspection robot

Inspection of gas distribution mains in urban areas is a time consuming and expensive task. This is why a first robot prototype has been built at the Control Engineering Group of the University of Twente. Goal of this robot, called PIRATE, is to inspect the low pressure gas distribution network in theNetherlands from inside the pipe autonomously on leaks or other damages. The goal of this project is to use mostly the internal state data to perform this complex task of autonomous navigation. The development is done partially on the robot itself and partially outside the robot in the 20sim environment. A bidirectional wireless communication channel operating in the 2,4GHz range is set up to perform wireless state feedback to the outside world. Furthermore, the link is used for sending parameters to the robot. The state data is transmitted to a prototype of a docking station which will in turn transmit this data to a PC. In this way the pirate robot can be monitored and controlled wirelessly which enables the user to getmore insight in the complex tasks of tackling environmental features like T-joints or 90 degree bends. On the PC side world modeling is done using the 20simenvironment. The 3D animation editor is used to construct a graphical representation of the pirate robot and can perform a realtime animation. In the world model a pipe diameter and environmental feature estimation is made which can be used for further development of an autonomous inspection robot.
FROM THE OCTOPUS TO SOFT ROBOTS CONTROL: AN OCTOPUS INSPIRED BEHAVIOR CONTROL ARCHITECTURE FOR SOFT ROBOTS

In recent years, breakthroughs have been made in both biology and robotics by the close cooperation between biologists and roboticists. Researchers in the fields of octopus biological study and soft robotics can also benefit from working together and inspiring each other. However, this collaboration is not easy because of the different research motivations and terminologies used. This paper starts from challenges for controlling soft robots, through biological inspirations from the octopus, to their engineering interpretation for creating a behavior control architecture for soft robots. Hypotheses related to the octopus biology from the engineering perspective are also proposed. This work serves as a case study in biologist-roboticist collaboration. It wishes to promote mutual understanding and cooperation between these two disciplines.
Repetitive transcranial magnetic stimulation (r-TMS) and selective serotonin reuptake inhibitor-resistance in obsessive-compulsive disorder: A meta-analysis and clinical implications.

INTRODUCTION Despite promising results from several randomized controlled trials (RCTs) and meta-analyses, the efficacy of r-TMS as a treatment for OCD remains controversial, at least in part owing to inconsistency in the trial methodologies and heterogeneity in the trial outcomes. This meta-analysis attempts to explain some of this heterogeneity by comparing the efficacy of r-TMS in patients with or without resistance to treatment with selective serotonin reuptake inhibitors (SSRI), defined using standardized criteria. METHODS We conducted a pre-registered (PROSPERO ID: 241381) systematic review and meta-analysis. English language articles reporting blinded RCTs were retrieved from searches using MEDLINE, PsycINFO, and Cochrane Library databases. Studies were subjected to subgroup analysis based on four stages of treatment resistance, defined using an adaptation of published criteria (1 = not treatment resistant, 2 = one SSRI trial failed, 3 = two SSRI trials failed, 4 = two SSRI trials failed plus one or more CBT trial failed). Meta-regression analyses investigated patient and methodological factors (age, duration of OCD, illness severity, stage of treatment-resistance, or researcher allegiance) as possible moderators of effect size. RESULTS Twenty-five independent comparisons (23 studies) were included. Overall, r-TMS showed a medium-sized reduction of Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) scores (Hedge's g: -0.47; 95%CI: - 0.67 to -0.27) with moderate heterogeneity (I2 = 39.8%). Assessment of publication bias using Trim and Fill analysis suggested a reduced effect size that remained significant (g: -0.29; 95%CI: -0.51 to -0.07). Subgroup analysis found that those studies including patients non-resistant to SSRI (stage 1) (g: -0.65; 95%CI: -1.05 to -0.25, k = 7) or with low SSRI-resistance (stage 2) (g:-0.47; 95%CI: -0.86 to -0.09, k = 6) produced statistically significant results with low heterogeneity, while studies including more highly resistant patients at stage 3 (g: -0.39; 95%CI: -0.90 to 0.11, k = 4) and stage 4 (g: -0.36; 95%CI: -0.75 to 0.03, k = 8) did not. Intriguingly, the only significant moderator of the effect size found by meta-regression was the severity of baseline depressive symptoms. All trials showed evidence of researcher allegiance in favour of the intervention and therefore caution is required in interpreting the reported effect sizes. CONCLUSION This meta-analysis shows that r-TMS is an effective treatment for OCD, but largely for those not resistant to SSRI or failing to respond to only one SSRI trial. As a consequence, r-TMS may be best implemented earlier in the care pathway. These findings would have major implications for clinical service development, but further well-powered RCTs, which eliminate bias from researcher allegiance, are needed before definitive conclusions can be drawn.
The intention of consumers to use augmented reality apps in gastronomy – case of Málaga

ABSTRACT The intention of consumers to use mobile applications with augmented reality is analyzed in order to assess which variables have the greatest influence on their use by consumers. The UTAUT-2 model has been used, analyzing: performance expectancy, effort expectancy, social influence, hedonic motivation, price value, facilitating conditions, habit and behavioural intention. The results show that predictors of a more social nature, such as aspects associated with perceived enjoyment: habits and social influence are not supported. Also, the hypothesis on the value of price could not be supported; since most augmented reality applications are free, although it is a variable that exerts a positive influence on the intention to use because of the perceived benefits. The demographic profiles of consumers can also become important predictors when using augmented reality apps, being the millennial generation and generation Z the most likely to use mobile devices with augmented reality.
Edge-Assisted Spectrum Sharing for Freshness-Aware Industrial Wireless Networks: A Learning-Based Approach

Information freshness is essential to industrial wireless networks (IWNs) and can be quantified by the age-of-information (AoI) metric. This paper addresses an AoI-aware spectrum sharing (AgeS) problem in IWNs, where multiple device-to-device (D2D) links opportunistically access the spectrum to satisfy their AoI constraints while maximizing primal links’ throughput. Particularly, we orchestrate the access of D2D links in a distributed manner. Since distributed scheduling results in incomplete observation, D2D links share the spectrum with uncertainty on the transmission environment. Therefore, we propose a distributed scheduling scheme, called D-age, to deal with the transmission uncertainty in the AgeS problem, where an adaptation of actor-critic method is adopted with AoI constraints tackled in the dual domain. To address the non-stationary environment and multi-agent credit assignment issue, cooperative multi-agent reinforcement learning (MARL) approach is developed, where multiple local actors are designed to guide D2D links to make real-time decisions via distributed scheduling policies, which are evaluated by an edge-assisted global critic with action-aware advantage functions. Integrated with graph attention networks (GATs), the critic selectively learns contextual information by assigning different importances to neighboring links, which enables the evaluation of scheduling policies in a scalable and computation-efficient manner. Theoretical guarantee of the time-averaged AoI constraints is provided and the effectiveness of D-age in terms of both AoI violation ratio and the capacity of primal links is demonstrated by simulation.
Applying Acoustic Scattering Layer Descriptors to Depict Mid-Trophic Pelagic Organisation: The Case of Atlantic African Large Marine Ecosystems Continental Shelf

To identify key nonspecific organisational characteristics of the mid-trophic pelagic communities, which remain a challenge, we work with sound scattering layers (SSLs). Application was tested in the three African Atlantic Large Marine Ecosystems (AALMEs) to assess the utility of adapting and developing new acoustic variables. Our methodology allowed comparison between Large Marine Ecosystems (LMEs) based on 14 morphological, spatial and acoustic variables to characterize SSLs over time. These original variables were effective in monitoring and comparing the LMEs, and even allowed us to discriminate different organisations inside the Canary Current LME. Common traits identified for all AALMEs included the importance of the shallowest SSL. However, we identified an unexpected night-time pattern in SSL distributions in the Benguela Current LME which reflect a major difference in diel vertical migration mechanisms relative to other AALMEs. We also highlighted the predominance of elementary sampling unit (ESUs) with a single SSL and an unoccupied tiny layer close to the bottom, even if some ESUs presented up to six SSLs. Inter-annual changes in SSL organisation are highlighted by adaptation of original variables as the proportion of the water column occupied by SSLs and the relative importance of the shallowest SSL. SSL variables have been used mostly in deep water; here, we applied them on the continental shelf. SSL variables can be used to standardize the monitoring of marine ecosystems and capture change in spatial structure and function of mid-trophic pelagic marine ecosystems worldwide, even in data-poor areas where species identification of lower-trophic pelagic organism remains a challenge.
Predictive potential of genotypes within the prolactin, growth hormone and insulin -like growth factor-I pathways in genetic evaluation of 305 days milk yield in Holstein cows in Sonora, Mexico

ii ACKNOWLEDGEMENTS . iv DEDICATION . v LIST OF TABLES . x LIST OF FIGURES . xii CHAPTER 1: INTRODUCTION . 1 CHAPTER 2: LITERATURE REVIEW . 3 Genetic evaluation of dairy cattle . 3 Mixed model and Best Linear Unbiased Prediction (BLUP) . 4 Marker assisted selection (MAS) . 5 Genomic selection (GS) . 6 Principles of genomic selection in dairy cattle . 7 Genome-wide association studies (GWAS). 8 Genomic best linear unbiased prediction (gBLUP) . 11 Genomic relationship matrix (G-matrix) . 13 Accuracy of Genomic breeding values from dairy cattle breeding programs . 15 Implications of GS and genotyping . 16 Genomic prediction validation . 17
Changing Perspectives and Attitudes on Early Childhood Research and Education

He is the founder and leader of the unique early childhood neuropedagogical research group and laboratory in Hungary. Together with prominent professionals, he has established an international research and counselling network. He is the member of international advisory groups of American and European educational scientific journals. In the frame of research and teaching scholarships he has represented Hungarian higher education and educational science all over the world. His main research fields are childhood’s effect on personal life paths, children’s worldview and children’s culture, childhood progress and development, constructivist pedagogy, early childhood neuropedagogy and competence-based education. He was awarded with Apáczai Csere János Prize for his outstanding academic performance in promoting educational practice. Her the socio-linguistic effects misleading recommendations from neuroscience research are made for classrooms. This article provides an overview of neuroeducational research studies in early childhood education to demonstrate how this field of study impacts teachers’ and parents’ understanding of best practices and optimal development. Also, to address the concern of the valid and reliable research in neuroeducation, we outline the principles of neuroeducational research based on Nouri (2016), and propose directions
Boamente: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation

People at risk of suicide tend to be isolated and cannot share their thoughts. For this reason, suicidal ideation monitoring becomes a hard task. Therefore, people at risk of suicide need to be monitored in a manner capable of identifying if and when they have a suicidal ideation, enabling professionals to perform timely interventions. This study aimed to develop the Boamente tool, a solution that collects textual data from users’ smartphones and identifies the existence of suicidal ideation. The solution has a virtual keyboard mobile application that passively collects user texts and sends them to a web platform to be processed. The platform classifies texts using natural language processing and a deep learning model to recognize suicidal ideation, and the results are presented to mental health professionals in dashboards. Text classification for sentiment analysis was implemented with different machine/deep learning algorithms. A validation study was conducted to identify the model with the best performance results. The BERTimbau Large model performed better, reaching a recall of 0.953 (accuracy: 0.955; precision: 0.961; F-score: 0.954; AUC: 0.954). The proposed tool demonstrated an ability to identify suicidal ideation from user texts, which enabled it to be experimented with in studies with professionals and their patients.
NEW CONFIGURATIONS FOR HYBRID FILTERS TO IMPROVE POWER QUALITY

Reforms in Power Sector have given an opportunity to the consumer to demand Quality Power. Unbalance, Distortion and poor regulation in the supply voltage have detrimental effect on the life of equipment and leads to poor efficiency in operation. Variable speed drives, Electric Traction and Furnace Loads inject harmonic currents into the supply system creating Bus voltage distortion. Even linear loads connected to this Bus will experience distorted load currents. These high frequency currents do not generate any useful output but produce over heating of motors, increased reactive power demand and ripples in the generated torque causing vibrations, leading to failure and poor performance efficiency. So there is a need for bypassing the load current harmonics generated by nonlinear loads from entering the system Bus Conventionally passive tuned filters connected to the Bus are used for bypassing the harmonics, but these filters have many limitations and become less effective under some operating conditions. Advent of high frequency, high power switching devices has given rise to new tools to mitigate the harmonic distortion in the Bus Voltage by freewheeling the harmonic currents, these are generally called as Active Filters. There are many configurations of these filters. Many of the limitations faced by tuned passive filters are overcome by the use of Active filters, but by combining the tuned and active filter the reliability and affectivity in improving power quality is enhanced, these are called Hybrid Filters. This paper briefly deals with two new configurations of Hybrid filter, one based on Pulse Width Modulation (PWM) operated Voltage Source Converter and the other on Current Controlled Converter. Results of performance of these two filters applied to a simple distribution system with a nonlinear load are given.
Programmed Assembly of Quantum-Dot Arrays on DNA Templates: Hardware for Quantum Computing?

This paper reports progress in the fabrication and characterization of an array of 1nm-scale colloidal particles (i.e., quantum-dot array) that can be operated to execute nontrivial and innovative computations, possibly including quantum logic. We discuss the actual fabrication of 2-nm metal clusters as an example of possible quantum dot implementation. Innovative and unconventional paradigms underlie the different stages of this work. For example, regular array geometry is achieved by directing appropriately derivatized metal clusters to preselected locations along a stretched strand of an engineered DNA sequence.
Dimensiones objetivas y subjetivas de las trayectorias laborales de los ingenieros egresados de una universidad tecnológica en México

Se discuten los resultados obtenidos en una investigación exploratoria que se llevó a cabo en el periodo 2017-2018 sobre trayectorias laborales de técnicos superiores universitarios (TSU) ingenieros egresados de la Universidad Tecnológica del Sur de Sonora (México). Se utilizó una metodología cualitativa y se aplicaron entrevistas en profundidad a una muestra de 33 graduados de la carrera de ingeniería con el fin de identificar las dimensiones subjetivas y objetivas de sus itinerarios ocupacionales en el mercado de trabajo de Ciudad Obregón, Sonora. Se distingue entre ingenieros graduados con experiencia laboral como TSU respecto de los que se insertaron al empleo por primera vez sin haber trabajado antes como técnicos. Los resultados destacan los efectos de la formación práctica que brindan las UT en la rápida inserción al primer empleo que experimentan tanto egresados TSU como ingenieros, aunque no parece haber muchas diferencias en los puestos laborales en que se ocupan.
Infrared thermography as diagnostic tool for bovine subclinical mastitis detection

Forty-eight Holstein cows were assessed using infrared thermography as non-invasive diagnostic tool for subclinical mastitis detection. The temperature analysis of animals negative in the California Mastitis Test has evidenced a difference between the mean temperatures in the front and rear quarters (p=0.001). The infrared thermography comparison between the rear quarters of animals positive and negative in the California Mastitis Test has not shown any difference (p=0.236), but the comparison of results of the front quarters has shown difference between the mean temperature of the infrared thermography of positive (32.35oC ±2.35) and negative CMTs (31.00oC ± 2.20 (p=0.025). The use of infrared thermography as diagnostic tool seems to be promising; however, it is necessary determining a protocol to guide its use.
A smart home security system based on ZigBee

The purpose of this project is to design and develop a security system for monitoring any intruders and others emergency situation around the house and display to the user in the form of computer monitor display. The chosen sensor is PIR motion sensor and the semiconductor sensor. The PIR can be used to detect movements, normally used to detect human movement when passing in or out of range sensor The gas sensor used in this project is MQ2, the semiconductor gas sensor which detects the presence of combustible gas and smoke at concentrations from 300 to 10,000 ppm. These sensors will detect the concentration of the gas according the voltage output of the sensor. To make the sensors operate in the alarm system and data monitoring system, Arduino Uno was used as the microcontroller for the whole system. The circuit also includes LEDs, buzzer, exhaust fan and Xbee. Xbee will send the data reading from gas sensor to data monitoring system that display on computer monitor display.
User Grouping in Multiuser Satellite MIMO Downlink With Fairness Consideration

In this letter, a multi-user satellite MIMO downlink including a multi-beam GEO satellite and multiple user terminals (UTs) is considered. In order to make every UT get the service fairly, all UTs need to be divided into multiple groups so that UTs in the same group can be served simultaneously, and different groups can be served sequentially in different time slots. The user grouping problem is investigated in this letter with the objective of maximizing the average channel capacity per time slot, and a genetic based user grouping (GBUG) algorithm is proposed. Simulations show that the average channel capacity obtained by GBUG is larger than that of the existing algorithms in the ZF and MMSE precoding system.