Search results for: predictive validity

Authors: Kingkan Chumjamras

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There are permanent and temporary tracheostomies, and in a permanent tracheostomy, care giver are important persons to know and be able to care for the tracheostomy patient. The objective of this quasi-experimental study was to evaluate outcomes of educating care giver in tracheostomy wound care for discharge planning of tracheostomy patients. The subjects of the study were relatives who directly cared for tracheostomy patients. Thirty subjects were selected according to specified criteria. The research instruments consisted of practice guidelines, manual for relatives in caring for the tracheostomy wound, an assisted model with a tracheostomy wound, a test, an observation form, and a patient’s relative satisfaction questionnaire. The instrument validity was tested by three experts, and the questionnaire reliability was tested with Cronbach’s alpha, and the reliability coefficient was 0.83; the data were analyzed using descriptive statistics, and paired t-test. The results of the study on educating relatives in tracheostomy wound care for discharge planning of tracheostomy patients revealed that the score for knowledge and ability in caring for the tracheostomy wound before receiving the education was at a low level (M= 19.23, SD= 1.57) compared with the very high score (M= 36.40, SD= 19.23) after receiving the education. The difference was statistically significant (p < .05), and relatives’ satisfaction was at a high level (80 percent). Knowledge and ability in caring for tracheostomy patients among patients’ relatives could cause tracheostomy wound complications for tracheostomy patients. One way to control such complications and returns to hospital from infection, in addition to care by the health care team, is educating relatives in tracheostomy wound care for discharge planning of tracheostomy patients.

Keywords: outcomes, educating, care giver, Tracheostomy Wound Care, discharge planning

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Authors: Penina Orenstein

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In today’s world, particularly with COVID-19 a constant worldwide threat, organizations need greater visibility over their supply chains more than ever before, in order to find areas for improvement and greater efficiency, reduce the chances of disruption and stay competitive. The concept of supply chain mapping is one where every process and route is mapped in detail between each vendor and supplier. The simplest method of mapping involves sourcing publicly available data including news and financial information concerning relationships between suppliers. An additional layer of information would be disclosed by large, direct suppliers about their production and logistics sites. While this method has the advantage of not requiring any input from suppliers, it also doesn’t allow for much transparency beyond the first supplier tier and may generate irrelevant data—noise—that must be filtered out to find the actionable data. The primary goal of this research is to build data maps of supply chains by focusing on a layered approach. Using these maps, the secondary goal is to address the question as to whether the supply chain is re-engineered to make improvements, for example, to lower the carbon footprint. Using a drill-down approach, the end result is a comprehensive map detailing the linkages between tier-one, tier-two, and tier-three suppliers super-imposed on a geographical map. The driving force behind this idea is to be able to trace individual parts to the exact site where they’re manufactured. In this way, companies can ensure sustainability practices from the production of raw materials through the finished goods. The approach allows companies to identify and anticipate vulnerabilities in their supply chain. It unlocks predictive analytics capabilities and enables them to act proactively. The research is particularly compelling because it unites network science theory with empirical data and presents the results in a visual, intuitive manner.

Keywords: data mining, supply chain, empirical research, data mapping

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Authors: R. Santos Alimi

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Using time-series techniques, this study empirically tested the validity of existing theory which stipulates there is a nonlinear relationship between government size and economic growth; such that government spending is growth-enhancing at low levels but growth-retarding at high levels, with the optimal size occurring somewhere in between. This study employed three estimation equations. First, for the size of government, two measures are considered as follows: (i) share of total expenditures to gross domestic product, (ii) share of recurrent expenditures to gross domestic product. Second, the study adopted real GDP (without government expenditure component), as a variant measure of economic growth other than the real total GDP, in estimating the optimal level of government expenditure. The study is based on annual Nigeria country-level data for the period 1970 to 2012. Estimation results show that the inverted U-shaped curve exists for the two measures of government size and the estimated optimum shares are 19.81% and 10.98%, respectively. Finally, with the adoption of real GDP (without government expenditure component), the optimum government size was found to be 12.58% of GDP. Our analysis shows that the actual share of government spending on average (2000 - 2012) is about 13.4%.This study adds to the literature confirming that the optimal government size exists not only for developed economies but also for developing economy like Nigeria. Thus, a public intervention threshold level that fosters economic growth is a reality; beyond this point economic growth should be left in the hands of the private sector. This finding has a significant implication for the appraisal of government spending and budgetary policy design.

Keywords: public expenditure, economic growth, optimum level, fully modified OLS

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Authors: R. Harihara Prakash, Shweta R. Parikh, Sangna S. Sheth

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The purpose of this study was to explore the usefulness of the Mini-BESTest compared to the Berg Balance Scale in evaluating balance in people with Parkinson's Disease (PD) of varying severity. Evaluation were done to obtain (1) the distribution of patients scores to look for ceiling effects, (2) concurrent validity with severity of disease, and (3) the sensitivity & specificity of separating people with or without postural response deficits. Methods and Material: Seventy-seven(77) people with Parkinson's Disease were tested for balance deficits using the Berg Balance Scale, Mini-BESTest. Unified Parkinson’s Disease Rating Scale (UPDRS) III and the Hoehn & Yahr (H&Y) disease severity scales were used for classification. Materials used in this study were case record sheet, chair without arm rests or wheels, Incline ramp, stopwatch, a box, 3 meter distance measured out and marked on the floor with tape [from chair]. Statistical analysis used: Multiple Linear regression was carried out of UPDRS jointly on the two scores for the Berg and Mini-BESTest. Receiver operating characteristic curves for classifying people into two groups based on a threshold for the H&Y score, to discriminate between mild PD versus more severe PD.Correlation co-efficient to find relativeness between the two variables. Results: The Mini-BESTest is highly correlated with the Berg (r = 0.732,P < 0.001), but avoids the ceiling compression effect of the Berg for mild PD (skewness −0.714 Berg, −0.512 Mini-BESTest). Consequently, the Mini-BESTest is more effective than the Berg for predicting UPDRS Motor score (P < 0.001 Mini-BESTest versus P = 0.72 Berg), and for discriminating between those with and without postural response deficits as measured by the H&Y (ROC).

Keywords: balance, berg balance scale, MINI BESTest, parkinson's disease

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Authors: Nor Erlissa Abd Aziz, R. M. U. S. Udagedara, S. Sharifi

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Managing and sharing knowledge has been a broadly satisfactory strategy to most of the organisations. Harnessing the power of knowledge supported the organisations to gain a competitive advantage over their competitors. Along with the invention of social media, knowledge sharing process has been more efficient and comfortable. Numerous researches have been conducted to investigate the effect of social media platforms for public and academic use. Furthermore, knowledge sharing, in general, have been subject to considerable n research, but research on sharing knowledge in Higher Education Institutions (HEIs) is rare. Also, it is noted that still there is a gap related to the organisational elements that contribute to the successful knowledge sharing through social media platforms. Thus, this research aims to investigate organisational elements that influence the social media platform based knowledge sharing within the context of Malaysian Higher Education Institutions (HEIs). The research used qualitative research methods to get an in-depth understanding of the subject matter. The conclusions of this study are based on interpreting the results of semi-structured interviews with academic staff from various Malaysian HEIs from the public and private sectors. Documents review will supplement the data from the interviews, and this ensures triangulation of the responses and thus increase the validity of the research. This research contributes to the literature by investigating an in-depth understanding the role of organisational elements about the social media platform based knowledge sharing in nourishing knowledge and spreading it to become better HEIs in utilising their knowledge. The proposed framework which identifies the organisational elements influences of social media platform based knowledge sharing will present as the main contribution of this research.

Keywords: knowledge sharing, social media, knowledge and knowledge management

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Authors: Hussaini Bala

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There are different opinions in the literature on the relationship between Audit Committee characteristics and earnings management. The mix of opinions makes the direction of their relationship ambiguous. This study investigated the relationship between Audit Committee characteristics and earnings management of listed food and beverages Firms in Nigeria. The study covered the period of six years from 2007 to 2012. Data for the study were extracted from the Firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences. The dependent variable was generated using two steps regression in order to determine the discretionary accrual of the sample Firms. Multiple regression was employed to run the data of the study using Random Model. The results from the analysis revealed a significant association between audit committee characteristics and earnings management of the Firms. While audit committee size and committees’ financial expertise showed an inverse relationship with earnings management, committee’s independence, and frequency of meetings are positively and significantly related to earnings management. In line with the findings, the study recommended among others that listed food and beverages Firms in Nigeria should strictly comply with the provision of Companies and Allied Matters Act (CAMA) and SEC Code of Corporate Governance on the issues regarding Audit Committees. Regulators such as SEC should increase the minimum number of Audit Committee members with financial expertise and also have a statutory position on the maximum number of Audit Committees meetings, which should not be greater than four meetings in a year as SEC code of corporate governance is silent on this.

Keywords: audit committee, earnings management, listed Food and beverages size, leverage, Nigeria

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Ahmad Abdulkadir Ibrahim

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The Islamic law of transactions laid down the methods and instruments of accounting and analyzed its basic assumptions in the modern world. There is a need to examine the implications of accounting initiatives in the Muslim world and attempt to outline the important characteristics of Islamic accounting and how Islamic accounting resolves the problem of measuring the cost of Murabaha goods in case of exchange rate variation. The research tends to discuss an analytical approach to the Islamic accounting concept as well as elaborating the jurisprudential matter and practical aspects of accounting in Islamic financial transactions. It also aims to alert the practitioners of accounting in the Islamic world to be aware of the concept of accounting in Islamic jurisprudence and its historical development. The methodology adopted in this research is the qualitative method through the consultation of relevant literature, which focuses on the thematic study of the subject matter. This is followed by an analysis and discussion of the contents of the materials used. It is concluded that Islamic accounting is unique in its norms as it has been characterized by fairness, accuracy in measuring tools, truthfulness, mutual trust, moderation in making a profit, and tolerance. It was also qualified by capacity and flexibility in terms of the tools and terminology used and invented by Islamic jurisprudence in the accounting system, which indicates its validity and consistency anytime and anywhere. An important conclusion of the research also lies in the refutation of the popular idea that an Italian writer known as Luca Pacilio was the first writer who developed the basis of double-entry due to the presented proofs by Muslim scholars of critical accounting developments, which cannot be ignored. It concludes further that Islamic jurisprudence draws the accounting system codified in the foundations of a market that is far from usury, fraud, cheating, and unfair competition in all areas.

Keywords: accounting, Islamic accounting, Islamic transactions, Islamic jurisprudence, double entry, murabaha, characteristics

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Authors: Prathyusha Samvedam, Hiranmaya Nanda

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Doping refers to the practice of using drugs or practices that enhance an athlete's performance. This is a problem that occurs on a worldwide scale and compromises the fairness of athletic tournaments. There are rules that have been created on both the national and international levels in order to prevent doping. However, these rules sometimes contradict one another, and it is possible that they don't do a very good job of prohibiting people from using PEDs. This study will contend that India's inability to comply with specific Code criteria, as well as its failure to satisfy "best practice" standards established by other countries, demonstrates a lack of uniformity in the implementation of anti-doping regulations and processes among nations. Such challenges have the potential to undermine the validity of the anti-doping system, particularly in developing nations like India. This article on the legislative framework in India governing doping in sports is very important. To begin, doping in sports is a significant problem that affects the spirit of fair play and sportsmanship. Moreover, it has the potential to jeopardize the integrity of the sport itself. In addition, the research has the potential to educate policymakers, sports organizations, and other stakeholders about the current legal framework and how well it discourages doping in athletic competitions. This article is divided into four distinct sections. The first section offers an explanation of what doping is and provides some context about its development throughout time. Followed the role of anti-doping authorities and the responsibilities they perform are investigated. Case studies and the research technique that will be employed for the study are in the third section; finally, the results are presented in the last section. In conclusion, doping is a severe problem that endangers the honest competition that exists within sports.

Keywords: sports law, doping, NADA, WADA, performance enhancing drugs, anti-doping bill 2022

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Authors: Hutomo Abdurrohman, Muhammad Latief, Waridatun Nida, Ranta Dwi Irawati

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Yogyakarta Kembali Monument (Monjali) is one of the most popular tourist attraction in Yogyakarta. Yogyakarta is known as ‘Student City’, and Monjali is a right place to learn and explore more about Yogyakarta, especially for students in elementary and junior high school to do the study tour. Monjali is located in North Ringroad, Jongkang, Sariharjo village, Ngaglik Subdistrict, Sleman Regency, Yogyakarta. Monjali offers many historical replicas, and also the story behind them. That is about the war between Indonesia's fighter, called TNI (Indonesian national army) and the colonizer of Netherlands in Yogyakarta, on March, 1st 1949. That event could open the eyes of the whole of Indonesia, because at that time the TNI was placed by the invaders. This research is an effort to evaluate the visitor's interest in Monjali as a special tourist attraction. The substance that we use in this research is the Monjali's visitors whom up to 17 years old by taking a respondent in every 15 persons who visit Monjali, and we need 200 respondents to know the condition and facilities of Monjali. This research has been collected since January 2017 until October 2017. We do the interview and spread the questionnaire which has been tested all of its validity and reliability. This data analysis is descriptive statistic analysis by using the qualitative data, which is converted into the quantitative data, use the Linkert Scale. The result of this research shows that the interest of Monjali's visitors is higher 75,6%. Based on the result, we know that Monjali is being an attractiveness for people which always experience its improvements and the development. Monjali is the success to be a place which combines the entertainment with its education as a vision of Yogyakarta as a Student City.

Keywords: descriptive statistical analysis, Jogja Kembali monument, Linkert scale, sensation

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Authors: M. B. Peter

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The Sacrament of Penance and Reconciliation has long been upheld, by the Catholic Church, as one of the Sacraments of healing, mainly due to the sense of peace, tranquility and psychological quiescence it accords the penitent upon receiving Sacramental absolution of sin through the action of the priest. This paper explores the Sacramental character of this practice and the psychological benefits of the celebration of the Sacrament. This is achieved in two parts: firstly, by the intellectual engagement of Sacred Scripture and the consolidated Sacred Tradition that the Catholic magisterium protects and, secondly, via a broad survey of the works of Carl Gustav Jung and Orval Hobart Mowrer regarding confession and forgiveness. The former will serve to demonstrate the Catholic belief of the divine institution of the Sacrament whilst the latter will demonstrate how this belief, coupled with the existing benefit of confessing guilt, collectively bolsters the Sacrament’s overall psychological efficacy. Fundamentally, the analysis of Jung and Mowrer’s works demonstrate that man, as a naturally religious being, has an inherent need for the confession of his wrong that he might be alleviated of psychological guilt in obtaining forgiveness of a (divinely ordained) minister who is sanctioned to absolve, i.e. the priest. The paper also presents the curative effect of the celebration of this Sacrament, illustrating how, without the act of confession, man remains in moral isolation from God and man; and, that with it, man is relieved of the mysterious feeling of guilt which lies at the root of his disquiet of mind and disturbance of will. Thus, the paper penultimately establishes how the Sacrament of Reconciliation is positioned in that place where psychology and theology meet: man’s sense of guilt. It is Jung’s views on confession and forgiveness that ultimately bridge the chasm between psychology and Christianity.

Keywords: Catholic, confession, Jung, Mowrer, penance, psychology, Sacrament of Reconciliation

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Authors: Zsanett Bahor, Cristina Nunes-Fonseca, Gillian L. Currie, Emily S. Sena, Lindsay D.G. Thomson, Malcolm R. Macleod

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Psychosis is ranked as the third most disabling medical condition in the world by the World Health Organization. Despite a substantial amount of research in recent years, available treatments are not universally effective and have a wide range of adverse side effects. Since many clinical drug candidates are identified through in vivo modelling, a deeper understanding of these models, and their strengths and limitations, might help us understand reasons for difficulties in psychosis drug development. To provide an unbiased summary of the preclinical psychosis literature we performed a systematic electronic search of PubMed for publications modelling a psychotic disorder in vivo, identifying 14,721 relevant studies. Double screening of 11,000 publications from this dataset so far established 2403 animal studies of psychosis, with the most common model being schizophrenia (95%). 61% of these models are induced using pharmacological agents. For all the models only 56% of publications test a therapeutic treatment. We propose a systematic review of these studies to assess the prevalence of reporting of measures to reduce risk of bias, and a meta-analysis to assess the internal and external validity of these animal models. Our findings are likely to be relevant to future preclinical studies of psychosis as this generation of strong empirical evidence has the potential to identify weaknesses, areas for improvement and make suggestions on refinement of experimental design. Such a detailed understanding of the data which inform what we think we know will help improve the current attrition rate between bench and bedside in psychosis research.

Keywords: animal models, psychosis, systematic review, schizophrenia

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Authors: Linda Boussaid, Farid Brahim Belaribi

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The physico-chemical properties of liquid materials in the industrial field, in general, and in that of the chemical industries, in particular, constitutes a prerequisite for the design of equipment, for the resolution of specific problems (related to the techniques of purification and separation, at risk in the transport of certain materials, etc.) and, therefore, at the production stage. Chloroalkanes, ethers constitute three chemical families having an industrial, theoretical and environmental interest. For example, these compounds are used in various applications in the chemical and pharmaceutical industries. In addition, they contribute to the particular thermodynamic behavior (deviation from ideality, association, etc.) of certain mixtures which constitute a severe test for predictive theoretical models. Finally, due to the degradation of the environment in the world, a renewed interest is observed for ethers, because some of their physicochemical properties could contribute to lower pollution (ethers would be used as additives in aqueous fuels.). This work is a thermodynamic, experimental and theoretical study of the volumetric properties of liquid binary systems formed from compounds belonging to the chemical families of chloroalkanes, ethers, having an industrial, theoretical and environmental interest. Experimental determination of the densities and excess volumes of the systems studied, at different temperatures in the interval [278.15-333.15] K and at atmospheric pressure, using an AntonPaar vibrating tube densitometer of the DMA5000 type. This contribution of experimental data, on the volumetric properties of the binary liquid mixtures of 1,2-dichloroethane with an ether, supplemented by an application of the theoretical model of Prigogine-Flory-Patterson PFP, will probably contribute to the enrichment of the thermodynamic database and the further development of the theory of Flory in its Prigogine-Flory-Patterson (PFP) version, for a better understanding of the thermodynamic behavior of these liquid binary mixtures

Keywords: prigogine-flory-patterson (pfp), propriétés volumétrique , volume d’excés, ethers

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Authors: Kritin K. Verma, Brian L. Ransdell

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White patches are a symptom of vitiligo, a chronic autoimmune dermatological condition that causes a loss of pigmentation in the skin. Vitiligo can cause issues of self-esteem and quality of life while also progressing the development of other autoimmune diseases. Current treatments in allopathy and homeopathy exist; some treatments have been found to be toxic, whereas others have been helpful. Allopathy has seemed to offer several treatment plans, such as phototherapy, skin lightening preparations, immunosuppressive drugs, combined modality therapy, and steroid medications to improve vitiligo. This presentation will review the FDA-approved topical cream, Opzelura, a JAK inhibitor, and its effects on limiting vitiligo progression. Meanwhile, other non-conventional methods, such as Arsenic Sulphuratum Flavum used in homeopathy, will be debunked based on current literature. Most treatments still serve to arrest progression and induce skin repigmentation. Treatment plans may differ between patients due to depigmentation location on the skin. Since there is no gold standard plan for treating patients with vitiligo, the oral presentation will review all topical and systemic pharmacological therapies that fight the depigmentation of the skin and categorize their validity from a systematic review of the literature. Since treatment plans are limited in nature, all treatment methods will be mentioned and an attempt will be made to make a golden standard treatment process for these patients.

Keywords: vitiligo, phototherapy, immunosuppressive drugs, skin lightening preparations, combined modality therapy, arsenic sulphuratum flavum, homeopathy, allopathy, golden standard, Opzelura

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Authors: Khaled M. Hama, Mohammed Al Magableh, Zaid Al Kuri, Ahmad Qayam

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The study aimed to identify the role of academic leaders at Jerash University in crisis management from the faculty members' point of view, ‘the emerging Corona pandemic as a model’, as well as to identify the differences in the role of academic leaders at Jerash University in crisis management at the significance level (0.05 ≤ α) according to the study variables Gender Academic rank, years of experience, and identifying proposals that contribute to developing the performance of academic leaders at Jerash University in crisis management, ‘the Corona pandemic as a model’. The study was applied to a randomly selected sample of (72) faculty members at Jerash University, The researcher designed a tool for the study, which is the questionnaire, and it included two parts: the first part related to the personal data of the study sample members, and the second part was divided into five areas and (34) paragraphs to reveal the role of academic leaders at Jerash University in crisis management - the Corona pandemic as a model, it was confirmed From the validity and reliability of the tool, the study used the descriptive analytical method The study reached the following results: that the role of academic leaders at Jerash University in crisis management from the point of view of faculty members, ‘the emerging corona pandemic as a model’, came to a high degree, and there were no statistically significant differences at the level of statistical significance (α = 0.05) between the computational circles for the estimates of individuals The study sample for the role of academic leaders at Jerash University in crisis management is attributed to the study variables (gender, academic rank, and years of experience)

Keywords: academic leaders, crisis management, corona pandemic, Jerash University

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Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar

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It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.

Keywords: accuracy, exponential smoothing, forecasting, initial value

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Authors: Yeimis Milton, Palomino Pichihua

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The city, like living organisms, originates from codes, structured information in the form of rules that condition the physical form and performance of urban space. Usually, the so-called urban codes clash with the spontaneous nature of the city, with the urban Kháos that contextualizes the free creation (poiesis) of human collectives. This contradiction is especially evident in Latin America, which, like other developing regions, lacks adequate instruments to guide urban growth. Thus constructing a hybrid between the formal and informal city, categories that are difficult to separate one from the other. This is a comparative study focusing on the urban codes created to address the pandemic. The objective is to build an overview of these innovations in the region. The sample is made up of official norms published in pandemic, directly linked to urban planning and building control (urban form). The countries analyzed are Brazil, Mexico, Argentina, Peru, Colombia, and Chile. The study uncovers a shared interest in facing future urban problems, in contrast to the inconsistency of proposed legal instruments. Factors such as the lack of articulation, validity time, and ambiguity, among others, accentuate this problem. Likewise, it evidences that the political situation of each country has a significant influence on the development of these norms and the possibility of their long-term impact. In summary, the global emergency has produced opportunities to transform urban systems from their internal rules; however, there are very few successful examples in this field. Therefore, Latin American cities have the task of learning from this defeat in order to lay the foundations for a more resilient and sustainable urban future.

Keywords: pandemic, regulation, urban planning, latin America

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Authors: Darren Edwards, Thomas Pinna

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Background: Interoception and heart rate variability have been found to predict outcomes of mental health and well-being. However, these have usually been investigated independently of one another. Objectives: This review aimed to explore the associations between interoception and heart rate variability (HRV) with emotion regulation (ER) and ER strategies within the existing literature and utilizing systematic review methodology. Methods: The process of article retrieval and selection followed the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines. Databases PsychINFO, Web of Science, PubMed, CINAHL, and MEDLINE were scanned for papers published. Preliminary inclusion and exclusion criteria were specified following the patient, intervention, comparison, and outcome (PICO) framework, whilst the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) framework was used to help formulate the research question, and to critically assess for bias in the identified full-length articles. Results: 237 studies were identified after initial database searches. Of these, eight studies were included in the final selection. Six studies explored the associations between HRV and ER, whilst three investigated the associations between interoception and ER (one of which was included in the HRV selection too). Overall, the results seem to show that greater HRV and interoception are associated with better ER. Specifically, high parasympathetic activity largely predicted the use of adaptive ER strategies such as reappraisal, and better acceptance of emotions. High interoception, instead, was predictive of effective down-regulation of negative emotions and handling of social uncertainty, there was no association with any specific ER strategy. Conclusions: Awareness of one’s own bodily feelings and vagal activation seem to be of central importance for the effective regulation of emotional responses.

Keywords: emotional regulation, vagal tone, interoception, chronic conditions, health and well-being, psychological flexibility

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Authors: Pius Babuna, Xiaohua Yang, Roberto Xavier Supe Tulcan, Bian Dehui, Mohammed Takase, Bismarck Yelfogle Guba, Chuanliang Han, Doris Abra Awudi, Meishui Lia

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Water inequality, water security, and water governance are fundamental parameters that affect the sustainable use of water resources. Through policy formulation and decision-making, water governance determines both water security and water inequality. Largely, where water inequality exists, water security is undermined through unsustainable water use practices that lead to pollution of water resources, conflicts, hoarding of water, and poor sanitation. Incidentally, the interconnectedness of water governance, water inequality, and water security has not been investigated previously. This study modified the Gini coefficient and used a Logistics Growth of Water Resources (LGWR) Model to access water inequality and water security mathematically, and discussed the connected role of water governance. We tested the validity of both models by calculating the actual water inequality and water security of Ghana. We also discussed the implications of water inequality on water security and the overarching role of water governance. The results show that regional water inequality is widespread in some parts. The Volta region showed the highest water inequality (Gini index of 0.58), while the central region showed the lowest (Gini index of 0.15). Water security is moderately sustainable. The use of water resources is currently stress-free. It was estimated to maintain such status until 2132 ± 18, when Ghana will consume half of the current total water resources of 53.2 billion cubic meters. Effectively, water inequality is a threat to water security, results in poverty, under-development heightens tensions in water use, and causes instability. With proper water governance, water inequality can be eliminated through formulating and implementing approaches that engender equal allocation and sustainable use of water resources.

Keywords: water inequality, water security, water governance, Gini coefficient, moran index, water resources management

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Yong Hwang, Kang Yeol Suh, Yundeok Jang, Tae Hoon Kim

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Introduction: Rhabdomyolysis is a syndrome characterized by muscle necrosis and the release of intracellular muscle constituents into the circulation. Acute kidney injury is a potential complication of severe rhabdomyolysis and the prognosis is substantially worse if renal failure develops. We try to identify the factors that were predictive of AKI in severe trauma patients with rhabdomyolysis. Methods: This retrospective study was conducted at the emergency department of a level Ⅰ trauma center. Patients enrolled that initial creatine phosphokinase (CPK) levels were higher than 1000 IU with acute multiple trauma, and more than 18 years older from Oct. 2012 to June 2016. We collected demographic data (age, gender, length of hospital day, and patients’ outcome), laboratory data (ABGA, lactate, hemoglobin. hematocrit, platelet, LDH, myoglobin, liver enzyme, and BUN/Cr), and clinical data (Injury Mechanism, RTS, ISS, AIS, and TRISS). The data were compared and analyzed between AKI and Non-AKI group. Statistical analyses were performed using IMB SPSS 20.0 statistics for Window. Results: Three hundred sixty-four patients were enrolled that AKI group were ninety-six and non-AKI group were two hundred sixty-eight. The base excess (HCO3), AST/ALT, LDH, and myoglobin in AKI group were significantly higher than non-AKI group from laboratory data (p ≤ 0.05). The injury severity score (ISS), revised Trauma Score (RTS), Abbreviated Injury Scale 3 and 4 (AIS 3 and 4) were showed significant results in clinical data. The patterns of CPK level were increased from first and second day, but slightly decreased from third day in both group. Seven patients had received hemodialysis treatment despite the bleeding risk and were survived in AKI group. Conclusion: We recommend that HCO3, CPK, LDH, and myoglobin should be checked and be concerned about ISS, RTS, AIS with injury mechanism at the early stage of treatment in the emergency department.

Keywords: acute kidney injury, emergencies, multiple trauma, rhabdomyolysis

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Dafna Knani, Sarit S. Sivan

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Aggrecan, one of the main components of the intervertebral disc (IVD), belongs to the family of proteoglycans (PGs) that are composed of glycosaminoglycan (GAG) chains covalently attached to a core protein. Its primary function is to maintain tissue hydration and hence disc height under the high loads imposed by muscle activity and body weight. Significant PG loss is one of the first indications of disc degeneration. A possible solution to recover disc functions is by injecting a synthetic hydrogel into the joint cavity, hence mimicking the role of PGs. One of the hydrogels proposed is GAG-analogues, based on sulfate-containing polymers, which are responsible for hydration in disc tissue. In the present work, we used molecular dynamics (MD) to study the effect of the hydrogel crosslinking (type and degree) on the swelling behavior of the suggested GAG-analogue biomimetics by calculation of cohesive energy density (CED), solubility parameter, enthalpy of mixing (ΔEmix) and the interactions between the molecules at the pure form and as a mixture with water. The simulation results showed that hydrophobicity plays an important role in the swelling of the hydrogel, as indicated by the linear correlation observed between solubility parameter values of the copolymers and crosslinker weight ratio (w/w); this correlation was found useful in predicting the amount of PEGDA needed for the desirable hydration behavior of (CS)₄-peptide. Enthalpy of mixing calculations showed that all the GAG analogs, (CS)₄ and (CS)₄-peptide are water-soluble; radial distribution function analysis revealed that they form interactions with water molecules, which is important for the hydration process. To conclude, our simulation results, beyond supporting the experimental data, can be used as a useful predictive tool in the future development of biomaterials, such as disc replacement.

Keywords: molecular dynamics, proteoglycans, enthalpy of mixing, swelling

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Authors: Atefeh Abedini, Fatemeh Razavi, Mihan Pourabdollah Toutkaboni, Hossein Mehravaran, Arda Kiani

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In countries with the highest prevalence of tuberculosis, such as Iran, the differentiation of malignant tumors from non-malignant is very important. In this study, which was conducted for the first time among the Iranian population, the utility of the ultrasonographic morphological characteristics in patients undergoing EBUS was used to distinguish the non-malignant versus malignant lymph nodes. The morphological characteristics of lymph nodes, which consist of size, shape, vascular pattern, echogenicity, margin, coagulation necrosis sign, calcification, and central hilar structure, were obtained during Endobronchial Ultrasound-Guided Trans-Bronchial Needle Aspiration and were compared with the final pathology results. During this study period, a total of 253 lymph nodes were evaluated in 93 cases. Round shape, non-hilar vascular pattern, heterogeneous echogenicity, hyperechogenicity, distinct margin, and the presence of necrosis sign were significantly higher in malignant nodes. On the other hand, the presence of calcification and also central hilar structure were significantly higher in the benign nodes (p-value ˂ 0.05). Multivariate logistic regression showed that size>1 cm, heterogeneous echogenicity, hyperechogenicity, the presence of necrosis signs and, the absence of central hilar structure are independent predictive factors for malignancy. The accuracy of each of the aforementioned factors is 42.29 %, 71.54 %, 71.90 %, 73.51 %, and 65.61 %, respectively. Of 74 malignant lymph nodes, 100% had at least one of these independent factors. According to our results, the morphological characteristics of lymph nodes based on Endobronchial Ultrasound-Guided Trans-Bronchial Needle Aspiration can play a role in the prediction of malignancy.

Keywords: EBUS-TBNA, malignancy, nodal characteristics, pathology

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Authors: Siliang Luan, Zhongtai Jiang

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The risk of highway incidents is commonly recognized as a major concern for transportation authorities due to the hazardous consequences and negative influence. It is crucial to respond to these unpredictable events as soon as possible faced by emergency management decision makers. In this paper, we focus on path planning for emergency vehicles, one of the most significant processes to avoid congestion and reduce rescue time. A Mixed-Integer Linear Programming with Semi-Soft Time Windows Model (MIPSSTWM) is conducted to plan an optimal routing respectively considering the time consumption of arcs and nodes of the urban road network and the highway network, especially in developing countries with an enormous population. Here, the arcs indicate the road segments and the nodes include the intersections of the urban road network and the on-ramp and off-ramp of the highway networks. An attempt in this research has been made to develop a comprehensive and executive strategy for emergency vehicle routing in heavy traffic conditions. The proposed Cuckoo Search (CS) algorithm is designed by imitating obligate brood parasitic behaviors of cuckoos and Lévy Flights (LF) to solve this hard and combinatorial problem. Using a Chinese city as our case study, the numerical results demonstrate the approach we applied in this paper outperforms the previous method without considering the nodes of the road network for a real-world situation. Meanwhile, the accuracy and validity of the CS algorithm also show better performances than the traditional algorithm.

Keywords: emergency vehicle, path planning, cs algorithm, urban traffic management and urban planning

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: R. Posia, J. Mistry, K. Kamani

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The health screening of laboratory rodents is essential for ensuring animal health and the validity of biomedical research data. Routine health monitoring is necessary to verify the effectiveness of biosecurity and the specific pathogen free (SPF) status of the colony. The present screening was performed in barrier maintained rat (Rattus norvegicus) colony. Rats were maintained under a controlled environment and strict biosecurity in the facility. The screening was performed on quarterly bases from randomly selected animals from breeding and or maintenance colonies. Selected animals were subject to blood collection under isoflurane anaesthesia. Serum was separated from the collected blood and stored samples at -60 ± 10 °C until further use. A total of 88 samples were collected quarterly bases from animals in a year. In the serological test, enzyme-linked immunosorbent assay (ELISA) was used for screening of serum samples against sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV). ELISA kits were procured from XpressBio, USA. Test serum samples were run along with positive control, negative control serum in 96 well ELISA plates as per the procedure recommended by the vendor. Test ELISA plate reading was taken in the microplate reader. This screening observed that none of the samples was observed positive for the sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV), indicating that effectiveness of biosecurity practices followed in the rodent colony. The result of serological screening helps us to declare that our rodent colony is specifically pathogen free for these pathogens.

Keywords: biosecurity, ELISA, specific pathogen free, serological screening, serum

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Authors: Musaab Mohammed Ahmed Ali, Vladimir Vodichev

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work deals with an universal control technique or single controller for linear and nonlinear stabilization and tracing control systems. These systems may be structured as SISO and MIMO. Parameters of controlled plants can vary over a wide range. Introduced a novel control systems design method, construction of stable platform orbits using derivative balance, solved transfer function stability preservation problem of linear system under partial substitution of a rational function. Universal controller is proposed as a polar system with the multiple orbits to simplify design procedure, where each orbit represent single order of controller transfer function. Designed controller consist of proportional, integral, derivative terms and multiple feedback and feedforward loops. The controller parameters synthesis method is presented. In generally, controller parameters depend on new polynomial equation where all parameters have a relationship with each other and have fixed values without requirements of retuning. The simulation results show that the proposed universal controller can stabilize infinity number of linear and nonlinear plants and shaping desired previously ordered performance. It has been proven that sensor errors and poor performance will be completely compensated and cannot affect system performance. Disturbances and noises effect on the controller loop will be fully rejected. Technical and economic effect of using proposed controller has been investigated and compared to adaptive, predictive, and robust controllers. The economic analysis shows the advantage of single controller with fixed parameters to drive infinity numbers of plants compared to above mentioned control techniques.

Keywords: derivative balance, fixed parameters, stable platform, universal control

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Authors: Susanne Fridsten, Kristina Hellman, Anders Sundin, Lennart Blomqvist

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Background: Patients diagnosed with locally advanced cervical carcinoma are treated with definitive concomitant chemo-radiotherapy. Treatment failure occurs in 30-50% of patients with very poor prognoses. The treatment is standardized with risk for both over-and undertreatment. Consequently, there is a great need for biomarkers able to predict therapy outcomes to allow for individualized treatment. Aim: To explore the role of T2- and diffusion-weighted magnetic resonance imaging (MRI) for early prediction of therapy outcome and the optimal time point for assessment. Methods: A pilot study including 15 patients with cervical carcinoma stage IIB-IIIB (FIGO 2009) undergoing definitive chemoradiotherapy. All patients underwent MRI four times, at baseline, 3 weeks, 5 weeks, and 12 weeks after treatment started. Tumour size, size change (∆size), visibility on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and change of ADC (∆ADC) at the different time points were recorded. Results: 7/15 patients relapsed during the study period, referred to as "poor prognosis", PP, and the remaining eight patients are referred to "good prognosis", GP. The tumor size was larger at all time points for PP than for GP. The ∆size between any of the four-time points was the same for PP and GP patients. The sensitivity and specificity to predict prognostic group depending on a remaining tumor on DWI were highest at 5 weeks and 83% (5/6) and 63% (5/8), respectively. The combination of tumor size at baseline and remaining tumor on DWI at 5 weeks in ROC analysis reached an area under the curve (AUC) of 0.83. After 12 weeks, no remaining tumor was seen on DWI among patients with GP, as opposed to 2/7 PP patients. Adding ADC to the tumor size measurements did not improve the predictive value at any time point. Conclusion: A large tumor at baseline MRI combined with a remaining tumor on DWI at 5 weeks predicted a poor prognosis.

Keywords: chemoradiotherapy, diffusion-weighted imaging, magnetic resonance imaging, uterine cervical carcinoma

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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