Miracle-dz/UniFAR-FTUs huggingface dataset:
Proceedings of the Military Operational Medicine Research Program Return-to-Duty Toolkit Working Group Symposium, 1-2 September 2015

Abstract : A Return-to-Duty (RTD) Toolkit Working Group Symposium was held at Fort Detrick, MD, on the 1st and 2nd of September, 2015. Sponsored by the U.S. Army Medical Research and Materiel Command (USAMRMC) Military Operational Medicine Research Program (MOMRP), a working group of experts came together to evaluate new and innovative assessment instruments and batteries for determining operational readiness to RTD following neurosensory injury. The clinical and psychometric properties of each assessment tool were presented by U.S. Army Aeromedical Research Laboratory (USAARL) or collaborating institutional researchers, under the direction of the USAARL Task Area Manager, Dr. Arthur Estrada, and Program Area Manager, Dr. John Crowley. Leading scientists, policy-makers, and clinicians with domain knowledge and expertise in traumatic brain injury in the context of operational RTD evaluated the various instruments and engaged in lively, active, informative, and fruitful discussions during the Symposium. These recordings were transcribed and are included herewith. Bringing together experts from across the scientific spectrum reduces the likelihood of needless duplication of efforts, reducing waste, and encouraging collaboration among scientists.
Introductory Chapter

Conventional hemodialysis (HD) treatment, which is the most prevalent dialysis modality and can be performed in hospital and at home, has been associated over the past 40 years with reduction in mortality rate [1], and in recent years, it has been associated with slight incremental improvement in survival rate [2]. However, its prescription remains far from being optimal in replacing the function of normal kidneys, and its unphysiologic clearance pattern and inability to remove all types and sizes of uremic toxins resulted in interand intradialytic complications, higher hospitalization rate, poor quality of life and an unacceptably high rate of cardiovascular and all-cause mortality [3–5]. The major HD-contributing factors to high mortality and morbidity rates are excess fluids (hypervolemia) and retention of middle and larger size uremic toxins.
Low Power, Scalable Platforms for Implantable Neural Interfaces

Author(s): Muller, Rikky | Advisor(s): Rabaey, Jan M. | Abstract: Clinically viable and minimally invasive neural interfaces stand to revolutionize disease care for patients with neurological conditions. For example, recent research in Brain-Machine Interfaces has shown success in using electronic signals from the motor cortex of the brain to control artificial limbs, providing hope for patients with spinal cord injuries. Currently, neural interfaces are large, wired and require open-skull operation. Future, less invasive interfaces with increased numbers of electrodes, signal processing and wireless capability will enable prosthetics, disease control and completely new user-computer interfaces.The first part of this thesis presents a signal-acquisition front end for neural recording that uses a digitally intensive architecture to reduce system area and enable operation from a 0.5V supply. The entire front-end occupies only 0.013mm2 while including "per-pixel" digitization, and enables simultaneous recording of LFP and action potentials for the first time. The second part presents the development of a minimally invasive yet scalable wireless platform for electrocorticography (ECoG), an electrophysiological technique where electrical potentials are recorded from the surface of the cerebral cortex, greatly reducing cortical scarring and improving implant longevity. A high-density flexible MEMS electrode array is tightly integrated with active circuits and a power-receiving antenna to realize a fully implantable system in a very small footprint. Building on the previously developed digitally intensive architecture, an order of magnitude in circuit area reduction is realized with 3x improvement in power efficiency over state-of-the-art enabling a scalable platform for 64-channel recording and beyond.
Psychosis , victimisation and childhood disadvantage Evidence from the second British National Survey of Psychiatric Morbidity

Declaration of interest None. Evidence of candidate causes from genetic, physical environmental and social environmental domains has encouraged the application of a biopsychosocial model to schizophrenia and other psychoses. Garety et al (2001) have suggested that early events may predispose to adult styles of thinking that foster the emergence of psychotic symptoms, particularly if some later event recapitulates aspects of the early events. This led us, in the current study, to use data from the second British National Survey of Psychiatric Morbidity (Singleton et al, 2001) to test the association of psychotic disorder with selected types of events. Most can be described as ‘victimisation experiences’ (see Table 1). They seem likely to involve the quality of intrusiveness, which Harris (1987) has postulated as having a particular relevance for psychotic disorders. Our hypothesis was that such events contribute to vulnerability to psychosis, and we therefore predicted that people with psychosis would report victimisation experiences over their lifetime more frequently than a normal control group. We also predicted that there would be no evidence of specificity, that is the same would be true of other types of psychiatric disorder.
JUVENILE DELINQUENCY AND COPING STRATEGIES: PSYCHOLOGICAL EXPLORATION OF THE RESOCIALIZATION PROCESS IN COLOMBIA

The objective was to identify coping strategies, risk and protective factors in adolescents who are finishing their sanction at the Valle del Lili Youth Training Center. The study with a qualitative and descriptive-cross-sectional approach used the semi-structured interview as an instrument, having as a selection criterion a minimum compliance of 80% of the sanction and an age range between 14 and 17 years. It was found that both adolescents came from single-parent families by separation, raised by the mother from a permissive authority with a lack of norms and rules, allowing freedom in activities and social ties.
FPGA-based ARX-Laguerre PIO fault diagnosis in robot manipulator

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARXLaguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.
Development of a novel tumor-targeted vascular disrupting agent activated by MT-MMPs

Vascular disrupting agents (VDA) offer a strategy to starve solid tumors of nutrients and oxygen concomitant with tumor shrinkage. Several VDAs have progressed into early clinical trials but their therapeutic value seems to be compromised by systemic toxicity. In this report, we describe the design and characterization of a novel VDA, ICT2588, that is non-toxic until activated specifically in the tumor by membrane-type-1 matrix metalloproteinase (MT1-MMP). HT1080 cancer cells expressing MT1-MMP were selectively chemosensitive to ICT2588, whereas MCF7 cells that did not express MT1-MMP were non-responsive. Preferential hydrolysis of ICT2588 to its active metabolite (ICT2552) was observed in tumor homogenates of HT1080 relative to MCF7 homogenates, mouse plasma and liver homogenate. ICT2588 activation was inhibited by the MMP inhibitor Ilomastat. In HT1080 tumor-bearing mice, ICT2588 administration resulted in formation of the active metabolite, diminution of tumor vasculature and hemorrhagic necrosis of the tumor. The antitumor activity of ICT2588 was superior to its active metabolite, exhibiting reduced toxicity, improved therapeutic index, enhanced pharmacodynamic effect and greater efficacy. Co-administration of ICT2588 with doxorubicin resulted in a significant antitumor response (22.6 day growth delay), which was superior to administration of ICT2588 or doxorubicin as a single agent, including complete tumor regressions. Our findings support the clinical development of ICT2588 which achieves selective VDA targeting based on MT-MMP activation in the tumor microenvironment.
Image classification and comparision of different Convolutional neural network srtuctures based On Keras

— Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Deep learning technologies are becoming the major approaches for natural signal and information processing, like image classification, speech recognition. Deep learning is a technology inspired by the functioning of human brain. Convolutional neural networks (CNN) become very popular for image classification in deep learning. In this paper, discussed about a deep learning convolutional network structures based on keras. Four different structures of CNN are compared on CPU system, with four different combinations of classifiers and activation functions.
In reply to the letter to the editor 'in Reply to Gandaglia et al.' by De Bari et al.

comparing IMRT against observation or older radiotherapy techniques are available. The absence of randomised data does not imply the absence of evidence: indeed other forms of comparative effectiveness research such as the proposed propensitymatched population-based analysis using SEER-Medicare database can inform clinical practice as well, provided that this methodology adhere to strict criteria. Despite that, comparisons presented and discussed in this article present, in our opinion, some important limitations which might have affected the proposed title and conclusions. First, the prescribed radiation dose was not reported, and it was not included as covariate in statistical analysis. This information has always a crucial role in the interpretation of the results of studies concerning radiotherapy, in particular for high-risk PCa, where higher doses are needed and recommended [3]. IMRT is a sophisticated technique allowing dose escalation, while maintaining equal (or reducing) toxicity, when compared with standard 3D conformal technique [4, 5]. The absence of any information about dose prescription, when IMRT is the key point of the data interpretation, makes impossible to discern whether improved outcomes are related to IMRT by itself, rather than its inherently associated capability of allowing dose escalation. Secondly, 52.6% of the IMRT population also received androgen deprivation therapy (ADT, versus 26.4% in the observation group), but no further data as the duration time, the type of drug and the category risk of patients receiving it are reported. Moreover, ADT was not considered as covariate in statistical evaluation. ADT has already showed a major impact on the overall survival of intermediate and high-risk PCa [3], and then it could potentially influence the results, in particular for the population that seem to benefit from IMRT. This is a crucial factor able to clearly affect the conclusions of the study. Last but not least, it is difficult to share the decision of grouping lowand intermediate-risk patients, also looking at the recent data by Bill-Axelson et al., showing no impact of surgery on low-risk PCa. Indeed, a potential impact of radiotherapy could not be excluded also in this population of patients and, in the era of the active surveillance, it is important to state which patients would really benefit of radical treatments.
Hybrid algorithm based on Genetic Algorithm and Tabu Search for Reconfiguration Problem in Smart Grid Networks Using " R "

Reconﬁguration of distribution networks aims to support the decision support, planning and/or real-time control of the operation of the electricity network. It is accomplished modifying the network structure of distribution feeders by changing the sectionalizing switches. Ensure higher levels of continuity and reliability to the electricity supply service are some of the requirements of consumers and electric power providers in the Smart Grid (SG) context. The goal of this paper is to propose a hybrid algorithm (Genetic and Tabu) for the reconﬁguration problem based on “R” in order to better support the decision making process. Beyond that, “R” modeling of electricity networks improves the response time when handling issues of network reconﬁguration using graph theory. The status of switches is decided according to graph theory subject to the radiality constraint of the distribution networks. The algorithm is presented and simulation results of IEEE 16-bus system, showing good results and computational eﬃciency.
Experience window influences development and retention of memory to recognize predators in the larval skipper frogs

Learning and memory are critical for predator recognition as they allow prey species to develop an adaptive response to a novel situation, thus increasing their chances of survival. In prey species that lack innate predator recognition, alarm cues play a crucial role in learning by their association with novel predator odour. Perception of novel predator odours along with alarm cues allows the prey to learn to detect predatory odours alone in their future encounters. A single event of exposure is considered to be sufficient for the prey to associate predatory cues with alarm cues. However, the minimum time required for learning and memorizing information about predator identity is unknown. Hence we used the tadpoles of Euphlyctis cyanophlyctis to determine the association between the experience window and memory development and its retention. We conditioned tadpoles with a mixture of dragonfly nymph odours and alarm cues for 1, 3, 6, 12 and 24 h, and subsequently assessed their antipredator behaviour at different intervals. Our results show that the minimum duration required for associative learning is ∼6 h. Interestingly, the intensity of antipredator response was proportional to the duration of conditioning. Moreover, retention of memory increased with an increase in the duration of conditioning. Hence, we show the significance of conditioning duration in learning. We also show an association between the duration of conditioning and retention of memory. In aquatic ecosystems, where the prey encounters a wide array of predatory cues, our findings open a new avenue for understanding the complexities associated with learning and the development of memory.
Exploring the Behavioral Sprouts of Smart Home Farming

In times of climate change and growing urbanization, the way food is produced and consumed also changes. Meanwhile, digitization is transforming farming practices, which also applies to the domestic growing of crops. More and more so-called smart home farms (SHF) are finding their way into private households. This paper conceptualizes the unique nature of enabled smart services and their underlying technology. Following an inductive interpretive approach, this study explores the antecedents of smart home farming practices. Our sample consists of eleven actual smart home farmers. We found six constructs to be of salient importance: expected outcomes related to harvesting, positive feelings, and sustainability; a combination of one's affinity for green and novel technologies; and the smartness and visibility of the enabled services. In the outlook, we present some preliminary thoughts for testing our qualitative findings.
Endovascular Revascularization for the Obstruction after Patch Angioplasty in Buerger’s Disease

− 174 − Department of Thoracic and Cardiovascular Surgery, Inje University Haeundae Paik Hospital, Inje University College of Medicine Received: December 5, 2013, Revised: January 5, 2014, Accepted: January 16, 2014 Corresponding author: Hee Jae Jun, Department of Thoracic and Cardiovascular Surgery, Inje University Haeundae Paik Hospital, Inje University College of Medicine, 875 Haeun-daero, Haeundae-gu, Busan 612-862, Korea (Tel) 82-51-797-3131 (Fax) 82-51-797-3101 (E-mail) cs523@dreamwiz.com C The Korean Society for Thoracic and Cardiovascular Surgery. 2014. All right reserved. CC This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Endovascular Revascularization for the Obstruction after Patch Angioplasty in Buerger’s Disease
On the Performance Analysis of Yagi-Uda at Wide Range Operational Frequencies

This paper evaluated the performance of Yagi-Uda antenna at High Frequency (HF), Very High Frequency (VHF) and Ultra High Frequency (UHF) communications. By employing popular method of moments algorithm for transforming electric field integral equation into a matrix equation, the current amplitude on the antenna emerged after matrix inversion of impedance matrix and multiplication by the voltage. The far zone field expression was developed by taking an integral of known current amplitude and green’s function. Using radiation far zone pattern as the performance metric, it was found that, the antenna was characterized by significant main lobe radiation along the axis of the antenna with small minor lobe radiation. This characteristic remained unchanged over all frequencies utilized as candidates for investigation. It was revealed through the study that varying operational frequency has negligible effect on the radiation characteristics exhibited by Yagi-Uda antenna and this lends credence to its usage for a number of applications over a wide frequency range.
Spectrum Allocation of Secondary Users Using Optimization Problem of Linear Cooperative Spectrum Sensing Techniques

— Resource allocation is used for complete utilization of frequency spectrum in cognitive radio networks. To maximize capacity is current research problem because of the many practical limitations such as transmission power, interference threshold of primary users and traffic demands of secondary users. In this paper consider spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cognitive Radio Networks (CRNs). Genetic algorithm (GA) is an efficient technique used for achieving power allocation in proposed systems. Cognitive radio has attracted a lot of attention recently due to its superior spectral efficiency and could play a vital role in improving the capacity of future networks. This paper presents resource allocation in terms of number of user, power. Simulation is done in MATLAB software and results shows that resource allocation gives complete utilization of spectrum bandwidth with minimum power along with maximum data rate.
A System-Level Aging and Mitigation Assessment Simulation Framework

As technology scaling enters the nanometer regime, device aging effects cause quality and reliability issues in CMOS Integrated Circuits (ICs), which in turn shorten its lifetime. Evaluating system aging through circuit simulations is very complex and time consuming. In this thesis, a framework is proposed, which allows for the evaluation of long-term aging effects of ICs and the corresponding measures to counteract premature failure. The focus of this work lies in the abstraction of low-level aging models to system-level models, in order to facilitate swift high-level simulation, without any knowledge of underlying circuit dynamics. Two major aging mechanisms, namely Negative Bias Temperature Instability (NBTI) and Channel Hot Carrier (CHC) degradation are considered for analysis. System-level aging management is performed with the prototype of a System-on-Chip (SoC) including a Management Unit (MU), which counteracts aging by employing Dynamic Voltage Scaling (DVS), Dynamic Frequency Scaling (DFS), and Adaptive Body Biasing (ABB). The simulation platform prototype is based on System-C AMS and a 65-nm technology library. This SoC simulation computes path delay using characterized models, which represent the aged behaviour of individual circuit elements. Results show that the obtained values are within 2% of circuit-level simulation values at the cost of a simulation time which is 15× lesser than conventional circuit simulators (e.g. Cadence NCSim). A System-Level Aging and Mitigation Assessment Simulation Framework
Emotional correspondence between preschoolers and teachers

The effects of the emotion regulation skills of the children attending preschool education on their interactions with their teachers are emphasized in recent studies. Therefore, in this study, we examined the effects of emotion regulation skills on the quality of the relationship between the teacher and the child. In total 39 preschool teachers and 119 preschool children (55 girls and 64) boys from five public preschools were participated in the study. Teachers were asked to fill Student-Teacher Relationship Scale-Short Form regarding three children in their classrooms and Emotion Regulation Questionnaire for themselves. We conducted four observations bu using MPAC-R/S in order to assess child’s abilities to express and regulate emotions. The results showed that children's emotional states were effective on teacher's relationship perception, and that teacher's emotion regulation skills were also effective on his/her relationship perception. In addition, the cognitive reappraisal strategy used by the teacher in emotion regulation has also been found to have an impact on the negative emotional state of children.
University of Birmingham The Birmingham MC 40 Cyclotron Facility

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Towards an Ontology of Crucial Knowledge Identification to Improve the K-DSS

— In this paper, we propose a characterization of the main classes contained in the database of the system K-DSS and related to the domain of identification of the crucial knowledge for which a capitalizing operation is required. We exploit ontological categories existing in the literature to define the notions of Knowledge, Actor, Support and Criteria of knowledge vulnerability. The objective is to improve the process of the crucial knowledge evaluation providing to different decision makers a unified semantic of these entities. Such approach brings us a preliminary analysis for the construction of an application ontology that we aim to integrate as a new component of the decision support system K-DSS.