J, Volume 2, Issue 2 (June 2019) – 10 articles

This paper presents the findings from a study of an equine assisted intervention (EAI), which is currently referred over 150 predominantly young people with mental health and behavioural problems each year. The young people are referred to this intervention when other services such as Child & Adolescent Mental Health Services (CAMHS) are not effective. Performing an exploratory study of implementation may be indicated when, there are few previously published studies or existing data using a specific intervention technique. This study showed some positive changes for participants across eight dimensions including; assertiveness, engagement with learning, calmness, planning, taking responsibility, empathy, communication and focus and perseverance. The equine intervention literature has shown mixed results across a variety of study designs and target groups, in terms of the gold standard of evidence, randomised controlled studies however the evidence currently is very limited. This study used a non-randomised sample, no control group and an unstandardised measurement filled out by those who refer young people to the intervention (social workers and teachers). The outcomes however from this exploratory study would suggest that a randomised control trial may be warranted and achievable. Full article

Among many clustering algorithms, the K-means clustering algorithm is widely used because of its simple algorithm and fast convergence. However, the K-value of clustering needs to be given in advance and the choice of K-value directly affect the convergence result. To solve this problem, we mainly analyze four K-value selection algorithms, namely Elbow Method, Gap Statistic, Silhouette Coefficient, and Canopy; give the pseudo code of the algorithm; and use the standard data set Iris for experimental verification. Finally, the verification results are evaluated, the advantages and disadvantages of the above four algorithms in a K-value selection are given, and the clustering range of the data set is pointed out. Full article

Study of emotions has gained interest in the field of sensory and consumer research. Accurate information can be obtained by studying physiological behavior along with self-reported-responses. The aim was to identify physiological and self-reported-responses towards visual stimuli and predict self-reported-responses using biometrics. Panelists (N = 63) were exposed to 12 images (ten from Geneva Affective PicturE Database (GAPED), two based on common fears) and a questionnaire (Face scale and EsSense). Emotions from facial expressions (FaceReader^TM), heart rate (HR), systolic pressure (SP), diastolic pressure (DP), and skin temperature (ST) were analyzed. Multiple regression analysis was used to predict self-reported-responses based on biometrics. Results showed that physiological along with self-reported responses were able to separate images based on cluster analysis as positive, neutral, or negative according to GAPED classification. Emotional terms with high or low valence were predicted by a general linear regression model using biometrics, while calm, which is in the center of emotion dimensional model, was not predicted. After separating images, positive and neutral categories could predict all emotional terms, while negative predicted Happy, Sad, and Scared. Heart Rate predicted emotions in positive (R² = 0.52 for Scared) and neutral (R² = 0.55 for Sad) categories while ST in positive images (R² = 0.55 for Sad, R² = 0.45 for Calm). Full article

The inconsistency between the time-reversible Liouville equation and time-irreversible Boltzmann equation has been pointed out by Loschmidt. To avoid Loschmidt’s objection, here we propose a new dynamical system to model the motion of atoms of gas, with their interactions triggered by a random point process. Despite being random, this model can approximate the collision dynamics of rigid spheres via adjustable parameters. We compute the exact statistical steady state of the system, and determine the form of its marginal distributions for a large number of spheres. We find that the Kullback–Leibler entropy (a generalization of the conventional Boltzmann entropy) of the full system of random gas spheres is a non-increasing function of time. Unlike the conventional hard sphere model, the proposed random gas system results in a variant of the Enskog equation, which is known to be a more accurate model of dense gas than the Boltzmann equation. We examine the hydrodynamic limit of the derived Enskog equation for spheres of constant mass density, and find that the corresponding Enskog–Euler and Enskog–Navier–Stokes equations acquire additional effects in both the advective and viscous terms. Full article

Maintaining records of artisanal and small-scale mining sites in developing countries requires considerable effort, so it would be beneficial if Earth observation data from space could assist in the identifying and monitoring of such sites. Artificial light emissions are common at industrial-scale mining sites and have been associated with small-scale illegal mining in some contexts. Here, we examine whether known artisanal and small-scale mining sites in the Democratic Republic of the Congo (DRC) are associated with observations of night light emissions by the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB). Light emissions from the mining sites were not observed: the radiance observed from the sites was near zero and nearly identical to that observed for a set of randomly-chosen locations in the same region. While it is the case that DNB night lights’ products provide useful data in other resource extraction contexts, they do not appear to be useful for identifying artisanal mining sites in the DRC. Full article

Peripheral arterial disease (PAD) is an atherosclerotic disease closely associated with high morbidity and mortality in cardiac events. Inflammation is crucial in atherosclerosis both at triggering and in progression. Numerous inflammatory biomarkers (cytokines, matrix metalloproteinases (MMPs), selectin, intracellular adhesion molecule (ICAM), vascular cell adhesion molecule (VCAM) C-reactive protein (CRP), fibrinogen) have been measured in atherosclerotic diseases including PAD. This paper summarizes the data on the inflammatory biomarkers for PAD pathophysiology and highlights the most useful markers in monitoring PAD outcomes. Full article

It is likely that tardive dyskinsesia is caused by the oxidation of dopamine in dopaminergic neurons. This oxidation produces oxygen radicals that damage neurons. Damage accumulates until tardive dyskinesia occurs. The use of dopamine D2 receptor inhibitors should be limited to the lowest doses for the shortest duration possible. Full article

In this short communication, we review seven applications of NFL that we have explored in a number of papers: (1) Background: the purpose of this study is to review how neutrosophic logic can be found useful in a number of diverse areas of interest; (2) Methods: we use logical analysis based on NL; (3) Results: some fields of study may be found elevated after analyzed by NL theory; and (4) Conclusions: we can expect NL theory to be applied in many areas of research too, in applied mathematics, economics, and physics. Hopefully the readers will find a continuing line of thoughts in our research from the last few years. Full article

Red ginseng, as an effective herbal medicine, has been traditionally and empirically used for the treatment of neuronal diseases. Many studies suggest that red ginseng and its ingredients protect the brain and spinal cord from neural injuries such as ischemia, trauma, and neurodegeneration. This review focuses on the molecular mechanisms underlying the neuroprotective effects of red ginseng and its ingredients. Ginsenoside Rb1 and other ginsenosides are regarded as the active ingredients of red ginseng; the anti-apoptotic, anti-inflammatory, and anti-oxidative actions of ginsenosides, together with a series of bioactive molecules relevant to the above actions, appear to account for the neuroprotective effects in vivo and/or in vitro. Moreover, in this review, the possibility is raised that more effective or stable neuroprotective derivatives based on the chemical structures of ginsenosides could be developed. Although further studies, including clinical trials, are necessary to confirm the pharmacological properties of red ginseng and its ingredients, red ginseng and its ingredients could be promising candidate drugs for the treatment of neural injuries. Full article

With the advent of the World Wide Web, the smartphone and the Internet of Things, not only society but also the sciences are rapidly changing. In particular, the social sciences can profit from these digital developments, because now scientists have the power to study real-life human behavior via smartphones and other devices connected to the Internet of Things on a large-scale level. Although this sounds easy, scientists often face the problem that no practicable solution exists to participate in such a new scientific movement, due to a lack of an interdisciplinary network. If so, the development time of a new product, such as a smartphone application to get insights into human behavior takes an enormous amount of time and resources. Given this problem, the present work presents an easy way to use a smartphone application, which can be applied by social scientists to study a large range of scientific questions. The application provides measurements of variables via tracking smartphone–use patterns, such as call behavior, application use (e.g., social media), GPS and many others. In addition, the presented Android-based smartphone application, called Insights, can also be used to administer self-report questionnaires for conducting experience sampling and to search for co-variations between smartphone usage/smartphone data and self-report data. Of importance, the present work gives a detailed overview on how to conduct a study using an application such as Insights, starting from designing the study, installing the application to analyzing the data. In the present work, server requirements and privacy issues are also discussed. Furthermore, first validation data from personality psychology are presented. Such validation data are important in establishing trust in the applied technology to track behavior. In sum, the aim of the present work is (i) to provide interested scientists a short overview on how to conduct a study with smartphone app tracking technology, (ii) to present the features of the designed smartphone application and (iii) to demonstrate its validity with a proof of concept study, hence correlating smartphone usage with personality measures. Full article