Psychiatric Diagnosis and Inmate Profiles in a Metropolitan County Jail

In recent years, there has been an increase in public and professional concern regarding the mentally ill offender in the criminal justice system. Several researchers have identified the need for further investigation of the mentally ill in correctional environments. This research was pai1 of a program evaluation in a large metropolitan county jail. Four main question were investigated: 1. Do inmates identified as mentally ill differ from the general jail population? 2. How consistent are the diagnoses of those identified as mentally in the correctional computer database (SWIS) compared to the diagnoses recorded in the medical records? 3. Is there a discrepancy between those identified as mentally ill from their medical records and the SWIS database? 4. What percentage of those diagnosed as mentally ill received treatment? The typical inmate identified as mentally ill in this study is male and Caucasian. However, of the inmates identified as mentally ill, Caucasians and females were overrepresented compared to the general jail population. They were also less likely to be African American. Sixty-six percent of the individuals identified as mentally ill were not given a diagnosis in the SWIS database while only 15.9% of those identified as mentally ill in their medical charts were not diagnosed. In the general jail population, 17% of inmates were diagnosed as mentally ill from medical chart reviews, while only 4.1 % were so diagnosed in the SWIS database. Nineteen percent of inmates identified as mentally ill from their medical charts did not receive treatment after being so identified. This information can be utilized to increase effectiveness in the identification and diagnosis of the mentally ill in correctional facilities. It can also be used to improve appropriate treatment once appropriate diagnoses have been made

Forecasting exports and imports through artificial neural network and autoregressive integrated moving average

Nowadays, Saudi government has established several strategic tactics such as Saudi Vision 2030 to predict the future of the country. In order to accomplish a superior growth in the economy of the country, mathematical model and forecasting techniques are important tools. In this study, total annual exports and imports of the Kingdom of Saudi Arabia are forecasted using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models. This paper tries to predict a time series data using ANN and ARIMA models on total annual exports and imports of Kingdom of Saudi Arabia from the year 1968 to the year 2017 with the help of statistical software XLSTAT. The applied models are used to predict some future values of total annual exports and imports of the Kingdom of Saudi Arabia. It is found that the ANN and ARIMA (1, 1, 2) and ARIMA (0, 1, 1) models are suitable for predicting the total annual exports and imports of the Kingdom of Saudi Arabia

Trend analysis of cost efficiency for the pharmaceutical industry: A DEA approach

This paper evaluates the efficiency of five Indian pharmaceutical Industries using Data Envelopment Analysis (DEA) approach. The paper uses Net Block, Cash and Bank Balance, Share Capital, Reserve and Surplus, Secure Loan and Unsecured Loan as input variables and Investments and ‘Loans and Advances’ as output variables. In this study, the Basic Radial Models input oriented with Constant Returns to scale (CRS) are used to estimate the efficiency of pharmaceutical Industries. The DEA tool assists the administrators to identify the inefficient measures and take necessary actions for improvement. The results are indicative of the scenario that changed patent laws in India are not detrimental to the financial and overall health of Indian pharmaceutical companies in general. The Indian pharmaceutical companies have suitably modified their business model to cope up with the changed legal environment. It is a positive sign for all Indian pharmaceutical companies that they are dynamic in management and operational policies to face any new situation and shall flourish more in the coming days

Sustainability Model for the Internet of Health Things (IoHT) Using Reinforcement Learning with Mobile Edge Secured Services

[EN] In wireless multimedia networks, the Internet of Things (IoT) and visual sensors are used to interpret and exchange vast data in the form of images. The digital images are subsequently delivered to cloud systems via a sink node, where they are interacted with by smart communication systems using physical devices. Visual sensors are becoming a more significant part of digital systems and can help us live in a more intelligent world. However, for IoT-based data analytics, optimizing communications overhead by balancing the usage of energy and bandwidth resources is a new research challenge. Furthermore, protecting the IoT network's data from anonymous attackers is critical. As a result, utilizing machine learning, this study proposes a mobile edge computing model with a secured cloud (MEC-Seccloud) for a sustainable Internet of Health Things (IoHT), providing real-time quality of service (QoS) for big data analytics while maintaining the integrity of green technologies. We investigate a reinforcement learning optimization technique to enable sensor interaction by examining metaheuristic methods and optimally transferring health-related information with the interaction of mobile edges. Furthermore, two-phase encryptions are used to guarantee data concealment and to provide secured wireless connectivity with cloud networks. The proposed model has shown considerable performance for various network metrics compared with earlier studies.This work has been partially funded by the "La Fundacion para el Fomento de la Investigacion Sanitaria y Biomedica de la Comunitat Valenciana (Fisabio)" through the project PULSIDATA (A43). This research is supported by the Artificial Intelligence & Data Analytics Lab (AIDA), CCIS Prince Sultan University, Riyadh, Saudi Arabia. The authors are thankful for technical support.Rehman, A.; Saba, T.; Haseeb, K.; Alam, T.; Lloret, J. (2022). Sustainability Model for the Internet of Health Things (IoHT) Using Reinforcement Learning with Mobile Edge Secured Services. Sustainability. 14(19):1-14. https://doi.org/10.3390/su141912185114141

Acceptability and feasibility of introducing strengthened school-based sexual and reproductive health information and services in Accra, Ghana

An initial study conducted by Population Council under the Strengthening Evidence for Programming on Unintended Pregnancies (STEP UP) project in 2012 assessed the knowledge and reproductive health needs of adolescents living in selected slums in Brong Ahafo and Greater Accra regions with the view of informing an improvement in adolescent sexual health (ASRH) programming in Ghana. The study concludes that stakeholders generally believed there was the need for enhanced adolescent sexual and reproductive health services in school as the present system of delivering these services were not sufficiently addressing ASRH needs. The use of trained psychologists and health workers was perceived as feasible and acceptable in the Ghanaian context, provided mechanisms are institutionalized to address the financial and other logistical considerations in its implementation. Stakeholders furthermore believed it was important to consider a dedicated curriculum to specifically address the population and family life education needs of adolescents; however, comprehensive stakeholder engagement would be required to determine content and implementation strategies

Improving well-being and equality outcomes: Aligning processes, supporting implementation and creating new opportunities

This report for Welsh Government considers the existing statutory duties in Wales, and how imoroved outcomes for equality and well-being might be improved by integrating engagement, setting objectives, delivery and reporting. The report also sets recommendations for reviewing Wales' specific duties, reflexive learning and practices and joint working opportunities between Wales' staturtory Commission

Energy Efficient and Resilient Infrastructure for Fog Computing Health Monitoring Applications

In this paper, we propose an energy efficient and resilient fog computing infrastructure for health monitoring applications. We design the infrastructure to be resilient against server failures under two scenarios, without geographical constraint and with geographical constraint. We consider a heart monitoring application where patients send their 30-seconds recording of Electrocardiogram (ECG) signal for processing, analysis and decision making at both primary and backup servers. A Mixed Integer Linear Programming (MILP) is used to optimize the number and locations of the primary and backup processing servers so that the energy consumption of both the processing and networking equipment are minimized. The results show that considering geographical constraint yields a network energy consumption increase by up to 9.36% compared to without geographical constraint. The results also show that, the increasing number of processing servers that can be served at each candidate node can reduce the energy consumption of networking equipment besides reducing the energy increment rate of networking equipment due to increasing level of demand

Understanding the gap between access and use: a qualitative study on barriers and facilitators to insecticide-treated net use in Ghana

Mass and continuous distribution channels have significantly increased access to insecticide-treated nets (ITNs) in Ghana since 2000. Despite these gains, a large gap remains between ITN access and use.; A qualitative research study was carried out to explore the individual and contextual factors influencing ITN use among those with access in three sites in Ghana. Eighteen focus group discussions, and free listing and ranking activities were carried out with 174 participants; seven of those participants were selected for in-depth case study. Focus group discussions and case study interviews were audio-recorded, transcribed verbatim, and analysed thematically.; ITN use, as described by study participants, was not binary; it varied throughout the night, across seasons, and over time. Heat was the most commonly cited barrier to consistent ITN use and contributed to low reported ITN use during the dry season. Barriers to ITN use throughout the year included skin irritation; lack of airflow in the sleeping space; and, in some cases, a lack of information on the connection between the use of ITNs and malaria prevention. Falling ill or losing a loved one to malaria was the most powerful motivator for consistent ITN use. Participants also discussed developing a habit of ITN use and the economic benefit of prevention over treatment as facilitating factors. Participants reported gender differences in ITN use, noting that men were more likely than women and children to stay outdoors late at night and more likely to sleep outdoors without an ITN.; The study results suggest the greatest gains in ITN use among those with access could be made by promoting consistent use throughout the year among occasional and seasonal users. Opportunities for improving communication messages, such as increasing the time ITNs are aired before first use, as well as structural approaches to enhance the usability of ITNs in challenging contexts, such as promoting solutions for outdoor ITN use, were identified from this work. The information from this study can be used to inform social and behaviour change messaging and innovative approaches to closing the ITN use gap in Ghana

Cardioprotection by systemic dosing of thymosin beta four following ischemic myocardial injury

Thymosin beta 4 (Tβ4) was previously shown to reduce infarct size and improve contractile performance in chronic myocardial ischemic injury via two phases of action: an acute phase, just after injury, when Tβ4 preserves ischemic myocardium via antiapoptotic or anti-inflammatory mechanisms; and a chronic phase, when Tβ4 activates the growth of vascular or cardiac progenitor cells. In order to differentiate between the effects of Tβ4 during the acute and during the chronic phases, and also in order to obtain detailed hemodynamic and biomarker data on the effects of Tβ4 treatment suitable for use in clinical studies, we tested Tβ4 in a rat model of chronic myocardial ischemia using two dosing regimens: short term dosing (Tβ4 administered only during the first 3 days following injury), and long term dosing (Tβ4 administered during the first 3 days following injury and also every third day until the end of the study). Tβ4 administered throughout the study reduced infarct size and resulted in significant improvements in hemodynamic performance; however, chamber volumes and ejection fractions were not significantly improved. Tβ4 administered only during the first 3 days following injury tended to reduce infarct size, chamber volumes and improve hemodynamic performance. Plasma biomarkers of myocyte injury were significantly reduced by Tβ4 treatment during the acute injury period, and plasma ANP levels were significantly reduced in both dosing groups. Surprisingly, neither acute nor chronic Tβ4 treatment significantly increased blood vessel density in peri-infarct regions. These results suggest the following: repeated dosing may be required to achieve clinically measureable improvements in cardiac function post-myocardial infarction (MI); improvement in cardiac function may be observed in the absence of a high degree of angiogenesis; and that plasma biomarkers of cardiac function and myocardial injury are sensitive pharmacodynamic biomarkers of the effects of Tβ4

IVOA Recommendation: IVOA Astronomical Data Query Language Version 2.00

This document describes the Astronomical Data Query Language (ADQL). ADQL has been developed based on SQL92. This document describes the subset of the SQL grammar supported by ADQL. Special restrictions and extensions to SQL92 have been defined in order to support generic and astronomy specific operations