Miracle-dz/UniFAR-FTUs huggingface dataset:
Title: Pilot testing of a personalised digital intervention to improve sedentary behaviour and wellbeing in the workplace

: Welbot is a cross-platform, personalised, digital intervention that delivers regular nudges to reduce sedentary behaviour and improve mental wellbeing at work. Objective: To explore the effect of the Welbot intervention on sedentary behaviour and mental wellbeing. Methods: A single arm repeated measures trial was conducted over three weeks of intervention delivery. The primary outcome was sedentary behaviour measured using subjective (Occupational Sitting and Physical Activity Questionnaire) and objective (Activpal measurement on a subset of participants (n=6)). Mental wellbeing variables collected were: depression, anxiety, stress, procrastination, wellbeing and work engagement. A subset of participants (n=6) were interviewed with a view to gaining a contextualised understanding of participants’ experiences of using the Welbot intervention. Results: Forty-one (6M/35F) university staff members with mean age of 43 years (range 22-63 years) participated. Following the intervention, participants self-reported significantly less time sitting and more time standing, and objectively recorded more steps at week-1 follow-up (p<.05). The change in all mental wellbeing outcomes were in the expected direction. However, only scores on the Depression Anxiety Stress Scale (DASS) showed significant changes (p<.05) with a decrease in the total DASS score and depression, anxiety and stress subscale scores between baseline and follow up. After using the Welbot intervention participants perceived they had a positive behaviour change, increased awareness of unhealthy behaviours at work, and provided suggestions for intervention improvement. Conclusions: Findings support the use of the Welbot digital intervention as an acceptable and practical way to improve employees’ physical and mental wellbeing at work.
MALAYSIAN JOURNAL OF CONSUMER AND FAMILY ECONOMICS 1 CONSUMERS’ INTENTION TO PURCHASE DATES: APPLICATION OF THEORY OF REASONED ACTION (TRA)

For years, dates are known for its numerous health advantages in both modern and traditional medicinal articles. Apart from its benefits, hypothetically, the consumption of dates is increasing due to the rising income level caused by economic growth. On that note, this paper investigates the role of attitude and subjective norms in determining consumers’ intention to purchase dates. Also, this study examines the role of demographic variables as moderating factors. Using purposive sampling method, a total number of 1,354 completed survey questionnaires were collected from eight (8) selected states in Malaysia. Descriptive analysis, Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM) were performed. The results indicate that attitude and subjective norms influence consumers’ intention in purchasing while consumers’ marital status and income moderate the relationship between attitude, subjective norms and consumers’ intention. Findings from this study is useful for policymakers in encouraging and promoting daily consumption of dates as a food commodity in Malaysia.
Generating news tips for local journalism with topic modeling

Natural language processing and text-mining are rarely used in the ﬁeld of jour-nalism, where reviewing voluminous corpora by hand is the norm. We test the power of topic modeling algorithms to discover newsworthy themes in a corpus of more than 3,000 meeting agendas and meeting minutes collected from government agencies in the Bay Area. We ﬁnd these methods successfully detect certain emergent news events and suggest additional steps to reduce the number of illegible or irrelevant topics surfaced by the models.
Online assessment for the final year medical students during covid-19 pandemics;the exam quality and students' performance

Background: Saudi Arabia responded to corona virus (COVID 19) pandemic earlier, the decision of lockdown taken in March 2020, and education and assessment were continued through E-learning since that time. Objectives: We aimed to assess the quality of online MCQs test taken by final medical students after COVID 19 pandemic and to review student’s performance in online assessment. Methods: This study was carried out in the college of medicine, King Khalid University, Saudi Arabia, participants were undergraduate final year medical students who completed their four major clinical courses. Item analysis parameters of the online MCQs test were compared with the item analysis parameters of the paper-based tests. Paper-based tests assessed the cohort of students in semester one before COVID 19 pandemic lockdown. The overall student’s performance on classical, face to face assessment was compared with the performance on an online assessment. Chisquare test was used P values<0:05 considered as statistically significant. Results: In two courses out of four, the test reliability of online MCQs tests improved significantly compared with paper-based tests. Three courses out of four showed significantly increased average discrimination indices among the online MCQs items. The average difficulty indices of all courses increased significantly in online MCQs tests. We observed that out of a maximum raw score of 100, the mean student’s score for online assessment in three courses was significantly higher than that for traditional assessment. Conclusion: we studied the impact of the COVID-19 pandemic on assessment of final year medical students. Online MCQs approved to be more reliable, better discrimination ability, but easier than paper-based examination. The overall student’s performance in theoretical and practical assessment was significantly improved in online assessment.
The Effect of Endurance Training and Coenzyme Q10 Supplementation on Sleep Quality in Children With Autism Spectrum Disorders

Background: Autism is a developmental disorder that impairs social relationships. Sleep disorders are one of the major problems of patients with autism spectrum disorders (ASD). Objectives: Concerning the need to investigate problems and impairments caused by this disease, the present study aimed at determining the effect of an eight-week endurance training program plus Q10 supplementation on sleep quality in children with ASD in 2017. Methods: The present double-blind study was performed on three experimental groups. Group 1 performed eight-week endurance training on a one-mile distance as brisk walking. Group 2 received 100 mg Q10 supplements daily and Group 3 underwent a combination of both interventions. Preand post-tests were performed to determine the sleep habits of the study subjects using the children's sleep habits questionnaire (CSHQ) by parents. Finally, the preand post-tests data were compared using the paired samples t-test. Results: A significant difference was observed between the preand post-test results in the mean total and eight subscales scores in the endurance training plus Q10 supplementation group (P <0.05). There was no significant difference between the preand post-test results in the sleep anxiety and sleep-disordered breathing subscales in the endurance training group and the sleep-disordered breathing subscale in the supplementation group. Conclusion: According to the study results, it seems that the sleep of children with autism was improved by increased physical activity and Q10 supplementation.
Evaluation and management of suspected sepsis and septic shock in adults

In this topic review, the management of sepsis and septic shock is discussed. Our approach is consistent with 2016 guidelines issued by the Surviving Sepsis Campaign [3,4]. While we use the Society of Critical Care Medicine (SCCM)/European Society of Intensive Care Medicine (ESICM) definitions, such definitions are not unanimously accepted. For example, the Center for Medicare and Medicaid Services (CMS) still continues to support the previous definition of systemic inflammatory response syndrome, sepsis, and severe sepsis. In addition, the Infectious Diseases Society of America (IDSA) does not endorse the SCCM/ESICM 2016 guidelines for many reasons as outlined in several sections in this topic [5]. In particular the IDSA does not agree with “one size fits all” recommendations based upon varying definitions of sepsis that do not clearly differentiate between sepsis and septic shock stating that following the SCCM recommendations, while life-saving for those with shock, may lead to overtreatment with broad spectrum antibiotics for those with milder variants of sepsis. Definitions, diagnosis, pathophysiology, and investigational therapies for sepsis, as well as management of sepsis in the asplenic patient are reviewed separately. (See "Sepsis syndromes in adults: Epidemiology, definitions, clinical presentation, diagnosis, and prognosis" and "Pathophysiology of sepsis" and "Investigational and ineffective therapies for sepsis" and "Clinical features, evaluation, and management of fever in patients with impaired splenic function".)
Procedural Generation via Machine Learning

The automatic generation of content can be useful for video game developers creating a game. It can provide developers with the capabilities to automatically generate interesting content for gamers to play through. The ﬁeld that allows developers to do this is called Procedural Content Generation (PCG). While this ﬁeld has been around for a very long time, progress in technology has allowed developers to think up of new algorithms that allow them to generate content better and more suited to their target demographic. In this paper, we will talk about two Procedural Content Generation methods, both of which employ Machine Learning.
A nod and shake compatibility effect

Studies from the embodiment perspective on language processing have shown facilitation or interference effects depending on the compatibility between verbal contents, concrete or abstract, and the motion of various parts of the body. The aim of the present study was to test whether such compatibility effects can be found when a higher cognitive process like truth evaluation is accomplished with head movements. Since nodding is a vertical head gesture typically performed with positive and affirmative responses, and shaking is a horizontal head gesture associated with negative and dissenting contents, faster response times can be expected when true information is evaluated by making a vertical head movement and false information by making a horizontal head movement. Three experiments were designed in order to test this motor compatibility effect. In the first experiment a series of very simple sentences were asked to be evaluated as true or false by dragging them vertically and horizontally with the head. It resulted that truth-value was assessed faster when it was compatible with the direction of the head movement, compared to when it was incompatible. In the second experiment participants were asked to evaluate the same sentences as the first experiment but by moving them with the mouse. In the third experiment, a non-evaluative classification task was given, where sentences concerning animals or objects were to be dragged by vertical and horizontal head movements. In the second and third experiment no compatibility effect was observed. Overall results support the hypothesis of an embodiment effect between the abstract processing of truth evaluation and the direction of the two head movements of nodding and shaking. Cultural aspects, cognitive implications, and the limits of these findings are discussed.
Mälardalen University School of Innovation Design and Engineering Väster̊as, Sweden Thesis for the Degree of Master of Science (60 credits) in Computer Science with Specialization in Software Engineering TOOL ORCHESTRATION FOR MODELING, VERIFICATION AND ANALYSIS OF COLLABORATING AUTONOMOUS MACHINE

System of systems (SoS) is a collective of multiple system units that have a common purpose. In this thesis, the Volvo Electric Site is investigated as an example case study in which safety and performance properties of collaborating autonomous machines are evaluated and analyzed. Formal methods in software engineering aim to prove the correctness of the system by evaluating its mathematical model. We use an actor-based framework, AdaptiveFlow, for modeling system functionalities and timing features. The aim is to link an abstract model evaluation and a simulation of real-world cases that are deployed in the VCE Simulator. In addition, it is necessary to make sure that AdaptiveFlow provides correct-by-design scenarios. The verification is conducted by developing an orchestration method between the AdaptiveFlow framework and the VCE Simulator. A tool named VMap is developed throughout this thesis for automated mapping of the input models of AdaptiveFlow and the VCE Simulator to make the orchestration possible. Furthermore, AdaptiveFlow is perceived in two different ways, as a design tool, and as an analysis tool. The models created in AdaptiveFlow are directly mapped to the VCE Simulator by using the VMap tool where the VCE Simulator is used as a testbed for checking these models. The outcome of this thesis is reflected in the establishment of a mapping pattern between AdaptiveFlow inputs and VCE simulator by developing the VMap tool for automatic mapping. It was shown that there is a natural mapping between the AdaptiveFlow models and VCE simulator inputs. By using VMap, we can quickly get to the desired scenarios. Through the development of three different cases, the results show that it is possible to design safe and optimal scenarios by orchestrating the AdaptiveFlow and the VCE Simulator using the VMap tool as well as the correlation between results from AdaptiveFlow and VCE Simulator.
Using Weakly Aligned Score-Audio Pairs to Train Deep Chroma Models for Cross-Modal Music Retrieval

Many music information retrieval tasks involve the comparison of a symbolic score representation with an audio recording. A typical strategy is to compare score–audio pairs based on a common mid-level representation, such as chroma features. Several recent studies demonstrated the effectiveness of deep learning models that learn task-speciﬁc mid-level representations from temporally aligned training pairs. However, in practice, there is often a lack of strongly aligned training data, in particular for real-world scenarios. In our study, we use weakly aligned score–audio pairs for training, where only the beginning and end of a score excerpt is annotated in an audio recording, without aligned correspondences in between. To exploit such weakly aligned data, we employ the Connectionist Temporal Classiﬁcation (CTC) loss to train a deep learning model for computing an enhanced chroma representation. We then apply this model to a cross-modal retrieval task, where we aim at ﬁnding relevant audio recordings of Western classical music, given a short monophonic musical theme in symbolic notation as a query. We present systematic experiments that show the effectiveness of the CTC-based model for this theme-based retrieval task.
X-ray powder diffraction data of AII(ZnXVO4)2 compounds (A=Sr, Ba; X=P, As)

Two new arsenates with general formula AII(ZnAsO4)2 (A=Sr, Ba) were synthetized by solid state reaction. Furthermore, a high pressure form of Ba(ZnPO4)2 was obtained under hydrothermal conditions. Indexing of their X-ray diffractograms was carried out with a monoclinic unit-cell and space group P21/c. These compounds are isostructural with Sr(ZnPO4)2 and the paracelsian form of Ba(AlSiO4)2.
Use of nanoparticles to improve thermochemical resistance of synthetic polymer to enhanced oil recovery applications: a review

Partially Hydrolyzed Polyacrylamide (HPAM) is the polymer most used in chemical enhanced oil recovery (cEOR) processes and it has been implemented in several field projects worldwide. Polymer injection has shown to be an effective EOR process. However, it has not been implemented massively due to HPAM polymer's limitations, mostly related to thermal and chemical degradation caused by exposure at high temperatures and salinities (HTHS). As an alternative, a new generation of chemically stable monomers to improve the properties of HPAM has been assessed at laboratory and field conditions. However, the use of enhanced polymers is limited due to its larger molecular size, large-scale production, and higher costs. One of the alternatives proposed in the last decade to improve polymer properties is the use of nanoparticles, which due to their ultra-small size, large surface area, and highly reactive capacity, can contribute to reduce or avoid the degrading processes of HPAM polymers. Nanoparticles (NPs) can be integrated with the polymer in several ways, it being worth to highlight mixing with the polymer in aqueous solution or inclusion by grafting or chemical functionalization on the nanoparticle surface. This review focuses on hybrid nanomaterials based on SiO2 NPs and synthetic polymers with great EOR potential. The synthesis process, characterization, and the main properties for application in EOR processes, were reviewed and analyzed. Nanohybrids based on polymers and silica nanoparticles show promising results in improving viscosity and thermal stability compared to the HPAM polymer precursor. Furthermore, based on recent findings, there are great opportunities to implement polymer nanofluids in cEOR projects. This approach could be of value to optimize the technical-economic feasibility of projects by reducing the polymer concentration of using reasonable amounts of nanoparticles. However, more significant efforts are required to understand the impact of nanoparticle concentrations and injection rates to support the upscaling of this cEOR technology.
DESIGN AND MODELING OF INSET FEED MICROSTRIP PATCH ANTENNA FOR GSM 1.5GHZ IMT SERVICES

Ever growing global support as International Mobile Telecommunication) IMT service band two candidate bands are 1.35-1.4GHz and 1.421.51GHz. The band 1.42-1.51GHz has been already used in Japan and Europe for commercial IMT services. The band provides considerable amount of bandwidth, better coverage in outdoor and building areas and cost efficient. For radiating at this frequency the antenna should be efficient, low cost and compact. Microstrip Patch Antenna (MPA) is having advantage of compact design, light weight, easy fabrication method and low profile over the conventional antennas. Due to their planar structure Microstrip Patch Antenna are widely used in wireless communication, satellite communication and in many areas where electromagnetic waves are used. Mobile communication requires compact, inexpensive and low profile antennas. Microstrip Patch Antenna satisfies all these requirements. This paper presents the design and analysis of inset feed Microstrip Patch Antenna. The design is simulated and analyzed for 1.5GHz band for GSM (900/1500) IMT Services. The electric field norm plot, radiation pattern are analyzed. Directivity is approx. 7dB and return loss   11 S calculated is –20.5dB and front to back ratio is calculated as 15dB. M. SHARMA, S. GOYAL, R. KAKKAR and B. SHARMA Advances and Applications in Mathematical Sciences, Volume 19, Issue 5, March 2020 302
Extraction of geometrical information used in photovoltaic and rainwater harvesting potential estimation from UAV optical images

Photovoltaic and rainwater harvesting assessment on rooftop has been studied extensively. Detailed methodologies are available over large study areas and designed to use data that are usually difficult and expensive to acquire. However, much less attention has been paid to the use of low-cost data for the estimation of photovoltaic parameters and rainwater collection in individual buildings. In this study, a workflow for extraction of geometrical information used in Photovoltaic and rainwater harvesting potential estimation from UAV optical images used to estimate photovoltaic and rainwater harvesting potential is presented. The optical images captured by the DJI Phantom 4 Unmanned Aerial Vehicle (UAV) were used to compute a point cloud, using state of the art Structure from Motion (SfM) algorithms. The modeling of the roof planes was made based on the spatial relationships between points using a Delaunay triangulation. From the generated model, roof geometrical parameters such as area, slope, and orientation were extracted and compared with reference measurements of Light Detection And Ranging (LiDAR) of the same scene. Statistical results from the experiments show that the SfM and LiDAR extracted parameters are very similar. The geometric parameters derived from UAV optical images can be used to support the analysis of the photovoltaic and rainwater harvesting potential in individual buildings. This method has the advantage to achieve results through the combination of low-cost technologies for data acquisition and processing, resulting in an easily reproducible methodology.
Knowledge, attitude and practice of small bowel obstruction among Saudi population

Background: Small bowel obstruction (SBO) is defined as a complete or partial mechanical blockage to the passage of intraluminal contents. In the United States, 15% of admissions for abdominal pain are secondary to SBO, with 300,000 hospital admissions annually. The most common causes of SBO by order are adhesions followed by hernias, Crohn’s disease, malignancy, and volvulus. ANALYSIS 24(106), November December, 2020 Medical Science ISSN 2321–7359 EISSN 2321–7367
Effect of positive and negative dimensions of mental imagery and self-talk on learning of soccer kicking skill

Purpose: Mental imagery and self-talk are two important mental skills that are used for improvement of performance and learning of motor and sport skills. This study aimed to investigate the effect of positive/negative mental imagery and positive/negative self-talk on learning of soccer kicking skill. Material: Participants included 48 young soccer player students. Participants were soccer player students with mean age 18.44 and SD=. 88 years. After selecting the sample and filling out the personal detail form, the imagery and self-talk instructions, the method of completing mental imagery questionnaire, Moore-Christine kickskill test instructions, and principles of free kick at soccer were explained to participants. Then, the mental imagery test and kick-skill test were run in 4 blocks of 4 attempts and the results were recorded. Based on their pre-test scores, the participants were divided into 4 groups. The acquisition sessions were held for 3 weeks and 2 sessions per week, with 8 blocks of 4 trials (32 trials) per session. The data was analyzed using one-way ANOVA, mixed ANOVA, and two-way ANOVA tests at different learning stages (significance level=
Toward Effective Multimodal Interaction in Augmented Reality

Immersive analytics (IA) applications commonly visualize data in AR or VR using stereo rendering and embodied perspective providing new opportunities for data visualization. Efficient IA systems need to be complimented with effective user interfaces. With this position paper, we discuss the importance of effective mapping of interaction modalities to analytics tasks and to prior approaches in previous AR interaction literature. We use this synthesis to identify often overlooked aspects of AR multimodal interfaces. These include transitions between interactions, the importance of field of view, issues with traditional text entry, and employing complementary display types. In identifying these challenges, we hope to facilitate and guide future work toward interaction best practices for IA.