Miracle-dz/UniFAR-FTUs huggingface dataset:
Occupational therapists' assessment of the caregivers of their elderly patients

OF THE THESIS OCCUPATIONAL THERAPISTS’ ASSESSMENT OF THE CAREGIVERS OF THEIR ELDERLY PATIENTS by Ernest Vincent Corradetti Florida International University, 1998 Miami, Florida Professor Gail Ann Hills, Major Professor The purpose of this study was to determine the methods and extent to which occupational therapists who are practicing in aging are assessing the caregivers of their elderly patients. A random sample of 500 therapists who subscribe to a special interest group publication of a professional organization were surveyed by mail and 204 responses were received. Respondents were asked to indicate all of the activities related to caregiver assessments in which they engage. Methods of assessment included: (a) professional caregiving activities, (b) informal assessment methods, and (c) formal assessment methods. There were more than 90% of respondents who indicated that they engaged in at least two professional activities related to caregiving, such as patient and/or caregiver education and discharge planning. Approximately one-third of subjects indicated that formal assessment is performed with a facility created assessment cited as the most frequently used formal instrument. Informal assessment methods were used by all but one subject in the sample. Direct questioning/discussion with caregiver and observation of the caregiver were the most frequently used informal assessment methods at 90% and 93.6%, respectively. The findings indicate that virtually all occupational therapists are highly engaged in assessing the caregivers of their elderly patients. Most of the assessment being performed relies on their clinical expertise and observation and/or facility created assessments. Furthermore, clinicians are highly engaged in patient and/or caregiver education. It is recommended that more of the body of research related to formal multidimensional caregiver assessment be disseminated into the occupational therapy
THE SEIE-SCUT SYSTEMS FOR IEEE AASP CHALLENGE ON DCASE 2017 : DEEP LEARNING TECHNIQUES FOR AUDIO REPRESENTATION AND CLASSIFICATION

In this report, we present our works about three tasks of IEEE AASP challenge on DCASE 2017, i.e. task 1: Acoustic Scene Classification (ASC), task 2: detection of rare sound events in artificially created mixtures and task 3: sound event detection in real life recordings. Tasks 2 and 3 belong to the same problem, i.e. Sound Event Detection (SED). We adopt deep learning techniques to extract Deep Audio Feature (DAF) and classify various acoustic scenes or sound events. Specifically, a Deep Neural Network (DNN) is first built for generating the DAF from MelFrequency Cepstral Coefficients (MFCCs), and then a Recurrent Neural Network (RNN) of Bi-directional Long Short Term Memory (Bi-LSTM) fed by the DAF is built for ASC and SED. Evaluated on the development datasets of DCASE 2017, our systems are superior to the corresponding baselines for tasks 1 and 2, and our system for task 3 performs as good as the baseline in terms of the predominant metrics.
Emotional Barriers to Peace: Emotions and Public Opinion of Jewish Israelis About the Peace Process in the Middle East

It is well-established today that the psychological barrier is one of the most prominent factors operating against efforts to promote peace. However, most studies along these lines have concentrated on the cognitive barriers and neglected the emotional ones. Hence, the main goal of this study is to create a deeper understanding of how emotions (e.g., fear, anger, and hatred) directed toward an adversary serve as a barrier to potential public support for peaceful resolution of a conflict. To that end, an experimental survey was conducted among a representative nationwide sample of Jewish Israelis (N = 501) in the week prior to the Annapolis Peace Summit. Negative emotions were stimulated, and different variables reflecting support for peace or violence were measured. Results obtained via paths analysis using structural equation modeling have drawn a comprehensive map of the distinct impact of each emotion on specific aspects of public opinion toward the peace process.
COPING AND WORKAHOLISM. RESULTS FROM A LARGE CROSS-OCCUPATIONAL SAMPLE

Objective: the aim of this study was to examine coping correlates of workaholism components (Work Involvement, Drive, Enjoyment of Work). Method: a sample of 661 Norwegian crossoccupational employees from six different companies completed a web-based survey measuring workaholism and coping styles (Active Problem Solving, Passive Avoidance, Depressive Reaction Pattern). Results: the Workaholism Battery (WorkBAT) components showed significant relationships with reports of coping styles. Work Involvement was positively related to Active Problem Solving and Depressive Reaction Pattern, and negatively to Passive Avoidance. Drive was positively related to Depressive Reaction Pattern. Enjoyment of Work was positively related to Active Problem Solving, and negatively to Depressive Reaction Pattern. Conclusion: the findings suggest that some workaholism components are related to healthy coping, whereas other workaholism components are related to unhealthy coping, which is in line with contemporary and central theories on the relationship between workaholism, stress, and health.
Software Defined Networks in Industrial Automation

Trends such as the Industrial Internet of Things and Industry 4.0 have increased the need to use new and innovative network technologies in industrial automation. The growth of industrial automation communications is an outcome of the shift to harness the productivity and efficiency of manufacturing and process automation with a minimum of human intervention. Due to the ongoing evolution of industrial networks from Fieldbus technologies to Ethernet, a new opportunity has emerged to harness the benefits of Software Defined Networking (SDN). In this paper, we provide a brief overview of SDN in the industrial automation domain and propose a network architecture called the Software Defined Industrial Automation Network (SDIAN), with the objective of improving network scalability and efficiency. To match the specific considerations and requirements of having a deterministic system in an industrial network, we propose two solutions for flow creation: the Pro-active Flow Installation Scheme and the Hybrid Flow Installation Scheme. We analytically quantify the proposed solutions that alleviate the overhead incurred from the flow setup. The analytical model is verified using Monte Carlo simulations. We also evaluate the SDIAN architecture and analyze the network performance of the modified topology using the Mininet emulator. We further list and motivate SDIAN features and report on an experimental food processing plant demonstration featuring Raspberry Pi as a software-defined controller instead of traditional proprietary Programmable Logic Controllers. Our demonstration exemplifies the characteristics of SDIAN.
Comparative Study of Frequent Item Set in Data Mining

In this paper, we are an overview of already presents frequent item set mining algorithms. In these days frequent item set mining algorithm is very popular but in the frequent item set mining computationally expensive task. Here we described different process which use for item set mining, We also compare different concept and algorithm which used for generation of frequent item set mining From the all the types of frequent item set mining algorithms that have been developed we will compare important ones. We will compare the algorithms and analyze their run time performance.
The prognostic significance of serum glucose levels after the onset of ventricular arrhythmia on in-hospital mortality of patients with acute coronary syndrome.

BACKGROUND Several studies have illustrated the role played by serum glucose levels in cardiovascular morbidity and mortality in general and, more particularly, after an acute coronary event. AIM The aim of this study was to evaluate the impact of serum potassium and glucose levels on in-hospital mortality in patients with ischemic heart disease, who exhibited severe ventricular arrhythmia. METHODS We enrolled 162 consecutive patients who were referred to our institution for an acute coronary event and presented with sustained ventricular tachycardia or ventricular fibrillation during the first 24 hours of hospitalization. Serum potassium and glucose levels were measured in all patients at the onset of tachycardia and after 2, 4, 6, 12, 36, 48 hours. RESULTS During hospitalization, 23 out of 162 patients died (61% males). Serum glucose levels at the onset of the arrhythmia, as well as after 2, 12, 36 and 48 hours, were higher in the deceased (onset: 228.8 +/- 108 vs. 158 +/- 68 mg/dl, p = 0.0001, 2 h: 182 +/- 109 vs. 149 +/- 59 mg/dl, p = 0.03, 12 h: 155.5 +/- 72 vs. 128 +/- 48 mg/dl, p = 0.025, 36 h: 163.8 +/- 63 vs.116 +/- 42 mg/dl, p = 0.002, and 48 h: 138 +/- 64 vs. 122 +/- 42 mg/dl, p = 0.05, respectively), even after adjustment for age, sex, diabetes, left ventricular ejection fraction, type of acute coronary syndrome and site of infarction and medication intake. There was no difference in serum potassium levels between the deceased and survivors. CONCLUSION Serum glucose levels at the onset of arrhythmia and 2, 36 and 48 hours later seem to have prognostic significance for in-hospital mortality in patients hospitalized for an acute coronary event, who exhibit severe ventricular arrhythmia.
Development of a bio-mathematical model in rats to describe clearance, retention and translocation of inhaled nano particles throughout the body

Studies of the translocation of inhaled nanoparticles from rodent lungs to different target organs provide data to model the inhalation and translocation of nanoparticles. A compartmental model was developed based on biological information about the major organs and how they interrelate. This model, which is quantified by a set of differential equations 'describing' the passage of nanoparticles through the body, gives estimates of the particle mass present in each organ. Optimal parameter estimates were found by minimising the model mean squared error. Data from two different studies in rats (one endotracheal instillation and one inhalation exposure) were used to calibrate the model. Most of the nanoparticle mass remained in the lungs. The overall fit of the model to the total measured particle mass in the body was very good for both studies (R2=0.98-0.99), although different parameter estimates were sometimes required to fit the study-specific data. The model fit to the measured particle mass by organ was very good for the lungs, brain, and spleen (R2=0.81-0.98) in both studies, but not as good for the liver and kidney (R2=0.32-0.53). While this model describes the retention and translocation of nanoparticles from the lungs reasonably well, further model evaluation and validation is needed using additional data.
DDT as anti-malaria tool: the bull in the China shop or the elephant in the room?

Malaria is a parasitic disease confined mostly to the tropical areas, caused by Plasmodium parasites and transmitted by Anopheles mosquitoes. In 2010, nearly 655.000 human deaths, mainly of children ≤5 years of age, were registered among more than 200 million cases worldwide of clinical malaria; the vast majority of cases occurred in the African Region (81%) and South-East Asia (13%), and 91% of them were due to P. falciparum, the most viru‐ lent among Plasmodia strains (WHO, 2011a).
APPLICATION OF THE METHOD OF FUNDAMENTAL SOLUTIONS WITH THE LAPLACE TRANSFORMATION FOR THE INVERSE TRANSIENT HEAT SOURCE PROBLEM

The paper deals with the inverse determination of heat source in an unsteady heat conduction problem. The governing equation for the unsteady Fourier heat conduction in 2D region with unknown internal heat source is known as the inverse boundary-initial-value problem. The identification of strength of the heat source is achieved by using the boundary condition, initial condition and a known value of temperature in chosen points placed inside the domain. For the solution of the inverse problem of determination of the heat source, the Laplace transformation with the method of fundamental solution and radial basis functions is proposed. Due to ill conditioning of the inverse transient heat conduction problem, the Tikhonov regularization method based on SVD and L-curve criterion was used. As the test problems, the 2D inverse boundary-initial-value problems (2D_IBIVP) in region $ \Omega$ with known analytical solutions are considered.
Rehabilitating criminal justice policy and practice.

For over 30 years, criminal justice policy has been dominated by a “get tough” approach to offenders. Increasing punitive measures have failed to reduce criminal recidivism and instead have led to a rapidly growing correctional system that has strained government budgets. The inability of reliance on official punishment to deter crime is understandable within the context of the psychology of human conduct. However, this knowledge was largely ignored in the quest for harsher punishment. A better option for dealing with crime is to place greater effort on the rehabilitation of offenders. In particular, programs that adhere to the Risk-NeedResponsivity (RNR) model have been shown to reduce offender recidivism by up to 35%. The model describes: a) who should receive services (moderate and higher risk cases), b) the appropriate targets for rehabilitation services (criminogenic needs), and c) the powerful influence strategies for reducing criminal behavior (cognitive social learning). Although the RNR model is well known in the correctional field it is less well known, but equally relevant, for forensic, clinical, and counseling psychology. The paper summarizes the empirical base to RNR along with implications for research, policy, and practice.
Graph-based Centrality Algorithms for Unsupervised Word Sense Disambiguation

This thesis introduces an innovative methodology of combining some traditional dictionary based approaches to word sense disambiguation (semantic similarity measures and overlap of word glosses, both based on WordNet) with some graph-based centrality methods, namely the degree of the vertices, Pagerank, closeness, and betweenness. The approach is completely unsupervised, and is based on creating graphs for the words to be disambiguated. We experiment with several possible combinations of the semantic similarity measures as the first stage in our experiments. The next stage attempts to score individual vertices in the graphs previously created based on several graph connectivity measures. During the final stage, several voting schemes are applied on the results obtained from the different centrality algorithms. The most important contributions of this work are not only that it is a novel approach and it works well, but also that it has great potential in overcoming the new-knowledge-acquisition bottleneck which has apparently brought research in supervised WSD as an explicit application to a plateau. The type of research reported in this thesis, which does not require manually annotated data, holds promise of a lot of new and interesting things, and our work is one of the first steps, despite being a small one, in this direction. The complete system is built and tested on standard benchmarks, and is comparable with work done on graph-based word sense disambiguation as well as lexical chains. The evaluation indicates that the right combination of the above mentioned metrics can be used to develop an unsupervised disambiguation engine as powerful as the state-of-the-art in WSD.
A Study of Deep Learning Techniques for Cultural Events Recognition

Indian Culture exceeds beyond the mere definition of ‘simply how people live’ as it scientifically operates according to specific, detailed knowledge of the eventual aim of life and the means to attain it. Over the years, a lot of work has been done on object recognition and scene recognition but Event Recognition is still one of the fields wherein lies a huge potential for lots of research work and so with this paper, we put forward our best step to preserve the culture of India. More than 150 images of near about 20 cultural events are collected. Results are derived from support vector machine classifier using features extracted by a pre-trained convolutional neural networkAlex Net. In most visual recognition tasks, it strongly suggested that features obtained from deep learning with convolutional nets should be the chief candidate. Our proposed framework has classified images with a comparable accuracy of 77.72 %.
Experimental Study on Local Subcooled Flow Boiling Heat Transfer in a Vertical Mini-Gap Channel

An experimental study of subcooled flow boiling in a highaspect-ratio, one-sided heating rectangular mini-gap channel was conducted using deionized water. The local heat transfer coefficient, onset of nucleate boiling, and flow pattern of subcooled boiling were investigated. The influence of heat flux and mass flux were studied with the aid of a high-speed camera. The results show that the flow pattern was mainly isolated bubbly flow when the narrow microchannel was placed vertically. The bubbles generated at lower mass fluxes were larger and did not easily depart, forming elongated bubbly flow and flowing upstream. The thin film evaporation mechanism dominated the entire test section due to the elongated bubbles and transient local dryout as well as rewet. The local heat transfer coefficient near the exit of the test section was larger. INTRODUCTION Highly efficient heat-dissipation system is of great importance to the operation, duration, and performance of high power components such as IGBT chips. The conventional air cooled and water cooled heat exchangers are unable to meet the need of high heat-flux dissipation density due to the increased power consumption and decreased size of these devices. Tuckerman and Pease found that the microchannel heat sink was a very promising solution for highly efficient heat dissipation in 1981. Higher heat transfer coefficient, better uniformity of temperature distribution, and lower mass flux as well as lower pump power needed can be realized by utilizing phase change in the evaporators. Meanwhile, there is a variety of complicated problems in the microchannel, such as the instability of flow boiling, which imposes limitations on the application of two phase heat transfer in microchannels. A comprehensive review about the research progress of the Proceedings of the ASME 2016 14th International Conference on Nanochannels, Microchannels, and Minichannels ICNMM2016 July 10-14, 2016, Washington, DC, USA
CD4 T Lymphopenia, Thymic Function, Homeostatic Proliferation and Late Complications Associated with Kidney Transplantation

Chronic kidney disease represents a public health problem worldwide. The prevalence of chronic kidney disease lies between 3 to 16% according to different epidemiological studies [1-5]. This high prevalence is observed in both developed and developing countries [1-5]. Chronic kidney disease is responsible for increased risk of cardiovascular diseases and endstage renal failure. In the United States, for instance, the number of patients exhibiting endstage renal failure was around 150 000 in 1995, 360 000 in 2003, and is estimated to reach 650 000 in 2015 [6]. This exponential growth of the end-stage renal disease population has relevant implications for health care systems. The treatment option for these patients is dialysis or kidney transplantation. The number of end-stage renal failure patients treated by either dialysis or transplantation was around 209 000 in 1991 and 472 000 in 2004 (data from the US Renal Data System 2006, reported in [3]). The costs of Medicare for end-stage renal failure treatment represents 5% of total budget, while it serves only 0.7% of patients [6]. The same observation is true for Europe with the proportion of the total health care budget dedicated to the end-stage renal disease population varying from 0.7% in the United Kingdom to 1.8% in Belgium in 1994, while this population is only 0.022% to 0.04% of the general population, respectively [6]. In France, the REIN (for Réseau Epidémiologie et Information en Néphrologie) program, hosted by the Agence de BioMédecine, is dedicated to assess the number of French patients suffering from end-stage renal failure and how these patients are treated (i.e., dialysis
EFFECTIVE BANDWIDTH ANALYSIS OF MIMO BASED MOBILE CLOUD COMPUTING

Digital Disruption is all around us. Mobile is overtaking desktop, Social Media is beating search, Messaging Application are challenging e-mails and everything around us is becoming connected. Mobile devices especially the smart phones are fueling the culture of “Anytime, Anywhere, And Anything’’. Smartphone is not only ubiquitous but also the primary computing device for many . These paradigm shifts are fueled by the explosive growth of smart phones which has touched a volume of 1.6 billion units globally. Smartphone growth has also triggered the explosive growth of mobile applications and cloud computing . Together, Mobile cloud computing is now a potential technology for mobile services . MCC overcomes obstacles related to battery life, storage capacity and low bandwidth. Current smart phones uses 2x2 MIMO which gives a speed 300Mbps, by using massive MIMO technology speed can be enhanced up to 1Gbps. This paper gives a BER (Bit Error Ratio) analysis to prove that by increasing number of transmitting and receiving antennas the performance can be enhanced.
A review of early intervention in youth psychosis

Australian Medical Student Journal 17 Introduction Psychotic disorders are characterised by the presence of symptoms that reflect an excess or distortion of normal functions. For example, hallucinations, delusions, thought disorder and disorganised behaviour are symptoms characteristic of psychosis. Patients diagnosed with schizophrenia must demonstrate positive symptoms or severe negative symptoms (e.g. flattened affect, social withdrawal) in addition to deterioration in their social and vocational functioning. [1] Hence, the diagnosis is typically made after the onset of significant symptomology.