Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of a 6-week aerobic exercise programme on the cardiovascular parameters, body composition, and quality of life of people living with human immune virus

This study evaluated the effects of aerobic exercise program on the cardiovascular parameters, body composition, and quality of life (QoL) of people living with human immune virus (HIV). Patients were recruited from the HIV clinic in a tertiary hospital in Nigeria. Fish bowl method was used to randomize the patients to either experimental or control group. Experimental group received nutritional counseling and aerobic exercise program on a treadmill, 3 times a week for a period of 6 weeks, while the control group received only nutritional counseling. Cardiovascular parameters, aerobic fitness, body composition parameters, and QoL were evaluated at baseline and 6 weeks. Descriptive statistics was used to explore demographic data while the hypothesis was tested using inferential statistics of t-test. Alpha level was set at P<0.05. The result showed that there was an improvement in cardiovascular parameters in both groups, attaining significance in the experimental group (P=0.000). Aerobic fitness increased significantly in experimental group (P=0.000). Body composition decreased significantly while there was a significant difference in the muscle mass (%) between groups (P<0.05). All domains of QoL had a significant improvement in both groups (P<0.005). A 6-week aerobic exercise program in addition to nutritional counseling was able to significantly improve cardiovascular fitness, body composition, and QoL in people living with HIV/acquired immune deficiency syndrome. Nutritional counseling alone can bring about an improvement only in QoL parameters.
Research on Passive Assist of Hip Joint Based on Muscle Metabolism

The passive exoskeleton has attracted more and more attention from researchers because of its small weight and portability. However, research on the passive exoskeleton of the hip joint during walking is rarely reported. In order to expand the application of passive exoskeletons in walking assist, this article analyzed human biomechanical characteristics through OpenSim and conducted passive assist research of hip joints based on the characteristics of muscle metabolism. First, starting from the biomechanical properties of the human body, the muscles and their functions related to hip flexion/extension were identified. Further, through the study of muscle metabolism, the support phase was used as the assist phase, and a variable-stiffness hip passive assisted exoskeleton was added to the simplified human musculoskeletal model. Finally, through the OpenSim simulation, the total metabolism of the support phase at different stiffness and the metabolism of the muscles which drive the hip joint were compared. The effect of changes in the stiffness of passive exoskeleton on human metabolism was studied, and a stiffness which is capable of reducing metabolism by 12.84% was obtained. On this basis, the stage of assist was optimized based on the muscle force with/without assist, and the metabolism was further reduced by 21.56%.
Contemplating Urban Operations Involving a UGV Swarm

Recent technological advancements enabled the development of different-size unmanned ground vehicles (UGV) to support a variety of disaster-relief and combat missions. While these systems are to be used in small numbers with no coordination or even awareness of each other in most cases, some applications could benefit from utilizing (smaller-size) UGVs in quantities, featuring a swarming behavior. Among these possible applications are operations in an urban area, which due to its complexity represents a challenging multidimensional environment for ground warfare. This paper presents guidance strategies for a search and destroy mission developed for some generic UGV swarms; and through a series of computer simulations evaluates their feasibility and effectiveness in executing such a mission in indoor as well as outdoor urban environments. The developed simulation allows varying many mission parameters, thus enabling a high degree of authenticity in terms of modeling a variety of real-world situations when different environments, platforms, sensors, and weapons are used. As such, this simulation environment maybe used as a tool, assisting in choosing key mission parameters to maximize the outcome of potential future engagements.
Ability of preschoolers to achieve maximal exercise and its correlation with oxygen uptake efficiency slope ∼ an observational study by direct cardiopulmonary exercise testing

Abstract The oxygen uptake efficiency slope (OUES) is a well-established substitute for maximum oxygen uptake ( O2 max) in submaximal exercise effort among adolescents and adults. Few studies have analyzed the exercise capacity (EC) and OUES of children aged 4 to 6 (preschoolers). Body fat has been proved to negatively affect EC among schoolchildren. The purposes of this study were to assess the capacity of preschoolers in achieving O2 max and evaluate the correlation of peak metabolic equivalent (peak MET) and peak oxygen consumption (peak O2) with OUES. We also evaluated if body fat affected EC among preschoolers. Forty-three preschoolers under the ramped Bruce protocol of treadmill exercise testing had been retrospectively studied. The criteria for achieving O2 max included respiratory exchange ratio (RER) >1.1, heart rate (HR) >85% of age-predicted maximum, and HR >200 bpm. OUES was calculated by the 75% (OUES-75) and the entire (OUES-100) duration of the testing and normalized by body surface area. Body fat was measured using vector bioelectrical impedance analysis. The fat mass (FM) index and fat-free mass index (FFMI) were defined as FM or FFM (kg) divided by height squared (m2), respectively. The mean age of the participants was 5.70 ± 0.56. Seventy-nine percent of preschoolers met at least 1 criterion, 36.84% met 2 criteria, and none met all 3 criteria for O2. OUES-75 was moderately positively correlated with peak MET (P = .034; Spearman's rho = 0.324) and peak O2 (P <.001; Spearman's rho = 0.667). OUES-100 was moderately to highly positively correlated with peak MET (P <.001; Spearman's rho = 0.592) and peak O2 (P <.001; Spearman's rho = 0.825). There were moderate to high positive correlations between FFMI and peak O2 (P <.001; Spearman's rho = 0.668), OUES-75 (P <.001; Spearman's rho = 0.642), and OUES-100 (P < .001; Spearman's rho = 0.670). None of the preschoolers reached all 3 criteria for O2max. OUES-75 and OUES-100 might be indicators of peak O2 at submaximal effort. Preschoolers with higher FFMI had better EC during treadmill exercise testing.
The Model of Time Series as a Piecewise-Stationary Process

This work is devoted to determining the space-time area that contains a time-series trend to address mathematical expectations. A time series trajectory represents the realization of a stochastic process in discrete time; thus, its approximation is random and cannot be considered a trend valuation. We offer to interpret an arbitrary time series as a trajectory of a piecewise-stationary process. This allows for us to describe an algorithm that constructs the area where the trend is located.
Implementation Challenges of Synchronisation of UWB Nodes in TDoA Structures

This paper discusses the synchronization issues of the unilateral TDoA method applied in ultra-wideband (UWB) localization systems. Focus of the paper is on implementation aspects of the synchronization. At first, the structure of unilateral TDoA method is explained and a method for synchronization is proposed. In the next step, typical implementation challenges of synchronization such as rounding effect, outliers, filtering, packet loss detection and thermal dependencies are discussed and for each problem a solution is provided. A set of experiments have been performed on different clock sources to study their effect on the accuracy of synchronization. The results of the experiments confirm that the voltage and temperature compensated oscillator has the highest accuracy, lowest frequency jitter but longest steady state time among the other variants applied. At the end, the performance of the synchronization solution in real experiments are demonstrated. The results prove that the proposed methods can successfully reduce the negative effects of clock inaccuracies. According to the results, localization accuracy of 3cm in average is achieved when a proper oscillator is used.
Re-ranking the search results for users with time-periodic intents

This paper investigates the time of search as a feature to improve the personalization of information retrieval systems. In general, users issue small and ambiguous queries, which can refer to different topics of interest. Although personalized information retrieval systems take care of user's topics of interest, but they do not consider if the topics are time periodic. The same ranked list cannot satisfy user search intents every time. This paper proposes a solution to rerank the search results for time sensitive ambiguous queries. An algorithm "HighTime" is presented here to disambiguate the time sensitive ambiguous queries and re-rank the default Google results by using a time sensitive user profile. The algorithm is evaluated by using two comparative measures, MAP and NDCG. Results from user experiments showed that re-ranking of search results based on HighTime is effective in presenting relevant results to the users.
Using Local Clocks to Reproduce Concurrency Bugs

Multi-threaded programs play an increasingly important role in current multi-core environments. Exposing concurrency bugs and debugging such multi-threaded programs are quite challenging due to their inherent non-determinism. In order to mitigate such non-determinism, many approaches such as record-and-replay have been proposed. However, those approaches often suffer significant performance degradation because they require a large amount of recorded information and/or long analysis and replay time. In this paper, we propose an efficient and effective approach, ReCBuLC (reproducing concurrency bugs using local clocks), to take advantage of the hardware clocks available on modern processors. The key idea is to reduce the recording overhead and the time to analyze events’ global order by recording timestamps in each thread. These timestamps are used to determine the global order of shared accesses. To avoid the large overhead in accessing system-wide global clock, we opt to use local per-core clocks that incur much less access overhead. We then propose techniques to resolve skews among local clocks and obtain an accurate global event order. By using per-core clocks, state-of-the-art bug reproducing systems such as PRES and CLAP can reduce their recording overheads by up to 85 percent, and the analysis time up to 84.66%<inline-formula> <tex-math notation="LaTeX">$\sim$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq1-2752158.gif"/> </alternatives></inline-formula>99.99%, respectively.
Whole body vibration to attenuate reduction of explosive force in chronic kidney disease patients: a randomized controlled trial

To investigate whether whole body vibration (WBV) training increases the explosive force of the knee extensors in chronic kidney disease (CKD) patients. Fourteen CKD patients undergoing hemodialysis were randomly allocated in WBV training or Sham group. Explosive force parameters (contractile impulse [CImp] and relative rate of force development [RFDr]) obtained in early (30 and 50 msec) and late phases (100 and 200 msec) of the knee extensors force/time curve. CImp and RFDr obtained at the early phase of force/time curve reduced after the intervention period, with a smaller decline for WBV (CImp at 50 msec [~−15% and −51%, P=0.038], RFDr at 30 msec [~−22% and −52%, P=0.044] and RFDr at 50 msec [~−11% and −54%; P=0.008]). In the late phase there was a lower decline for WBV group compared to Sham group, respectively: CImp: 100 msec (~−8% and −55%, P=0.025), 200 msec (~−3% and −46%, P= 0.025); RFDr 100 msec (~0.01% and −56%, P=0.033), 200 msec (~−5% and −36%, P=0.004). Three months of WBV training may attenuate the explosive force reduction in CKD patients.
Artificial intelligence and the automatic classification of historical photographs

The amount of historical photographs is a challenge for archives with regard to analyzing, documenting and structuring archival material and make it retrievable and accessible. Established human centric concepts will not be able to handle the instream of un- or semi-structured material or handle analogue documentation. We suggest the use of artificial intelligence to pre-classify and organize historic photographs in collections and archives. With regard to uncertainty the concept of artificial intelligence based classification is discussed based on two questions: (1) What is the uncertainty in current archival documentation, assuming that the quality and completeness of a current classification depends on the partial and restricted knowledge of a person? (2) Can algorithmic concepts help to quantify the level of uncertainty? The aspect of documentation is discussed based on a comparison of algorithms and classical processes. The contribution of artificial intelligence to quantify the uncertainty is tested in a case study. For this an artificial neural network / convolutional neural network was trained and tested on a collection of historical photographs.
Examining consumer purchase intentions of non‐prescription medicines in supermarkets and community pharmacies

As supermarkets continue to expand their healthcare categories, consumers now have more choice and access to non‐prescription medicines. The aim of this current research is to empirically examine the drivers and barriers of consumer purchase intentions, namely trust and perceived risk, of non‐prescription medicines in both supermarkets and community pharmacy settings.
Organizational Trauma-Informed Care: Associations With Individual and Agency Factors

In response to the growing awareness of the high rates of potentially traumatic experiences and their potential adverse impacts, health and human service providers have increasingly focused on implementing trauma-informed care (TIC). However, studies focusing on effective implementation have been limited. In this study, we explored the relationship of individual and agency characteristics to the level of organizational TIC. With data collected from a sample of 345 providers from 67 agencies, we used the TICOMETER, a brief measure of organizational TIC with strong psychometric properties, to determine these associations. We found weak relationships between individual factors and TICOMETER scores and stronger associations for agency-level factors. These included agency type, time since last trauma training, and involvement of service users. These findings highlight the importance of robust cultural changes, service user involvement at all levels of the organization, flattening power differentials, and providing ongoing experiential training. This analysis fills an important gap in our knowledge of how best to ensure agency-wide provision of TIC.
Bottom‐up and top‐down effects of browning and warming on shallow lake food webs

Productivity and trophic structure of aquatic ecosystems result from a complex interplay of bottom‐up and top‐down forces that operate across benthic and pelagic food web compartments. Projected global changes urge the question how this interplay will be affected by browning (increasing input of terrestrial dissolved organic matter), nutrient enrichment and warming. We explored this with a process‐based model of a shallow lake food web consisting of benthic and pelagic components (abiotic resources, primary producers, grazers, carnivores), and compared model expectations with the results of a browning and warming experiment in nutrient‐poor ponds harboring a boreal lake community. Under low nutrient conditions, the model makes three major predictions. (a) Browning reduces light and increases nutrient supply; this decreases benthic and increases pelagic production, gradually shifting productivity from the benthic to the pelagic habitat. (b) Because of active habitat choice, fish exert top‐down control on grazers and benefit primary producers primarily in the more productive of the two habitats. (c) Warming relaxes top‐down control of grazers by fish and decreases primary producer biomass, but effects of warming are generally small compared to effects of browning and nutrient supply. Experimental results were consistent with most model predictions for browning: light penetration, benthic algal production, and zoobenthos biomass decreased, and pelagic nutrients and pelagic algal production increased with browning. Also consistent with expectations, warming had negative effects on benthic and pelagic algal biomass and weak effects on algal production and zoobenthos and zooplankton biomass. Inconsistent with expectations, browning had no effect on zooplankton and warming effects on fish depended on browning. The model is applicable also to nutrient‐rich systems, and we propose that it is a useful tool for the exploration of the consequences of different climate change scenarios for productivity and food web dynamics in shallow lakes, the worldwide most common lake type.
Improved traceability for bidirectional model transformations

Conventional wisdom on bidirectionality in Model-Driven Engineering (MDE) suggests that it represents a crucial component to achieve superior model management, whether it be round-tripping, synchronisation, or consistency restoration. Despite their relevance, bidirectional transformations remain difficult to design and implement due to the complexity they must usually encode and their semantic intricacy. Using a proper traceability support enables transformations to be persistent and permits designers to deal with such cases that would be otherwise largely unfeasible. This also implies dealing with the different types of model relationships that may exist in order to establish (re)usable traceability links. This paper proposes to leverage traceability information between source and target elements of a transformation to a first-class status in order to i) automatise its generation, ii) enable a model-based representation and iii) ease reuse and refinement in a further stage. The approach is realized within the JTL framework.
COSINT: Mining Reasons for Sentiment Variation on Twitter using Cosine Similarity Measurement

An advanced domain has evolved in the field of research over the past decade, called Sentiment Analysis on Social Media. Twitter has made huge impact with more than 500 million Tweets each day. People share their opin- ion in the form of Tweets on many topics. In this paper, we employ Foreground and Background LDA (FB-LDA) and Reason Candidate and Background LDA (RCB-LDA) model to extract the reasons for sentiment variation. Emerging topics or Foreground topics within the sentiment variation period are highly related to the reasons for sentiment variation, whereas Background topics are discussed from long time and does not add to the sentiment variation. FB-LDA model filter out Background topics from the Foreground tweet set and extract the required Foreground topics that contribute for the reason for sentiment variation. RCB-LDA model finds more relevant tweets of the Foreground topic that are extracted in FB- LDA model and rank them to get Reason Candidates. To extract Reason more precisely from Reason Candidates, in this paper we propose COsine SImilarity MesuremeNT (COSINT) using Latent Semantic Analysis methods. This methods mine specific reason for sentiment variation.
The Design of an Augmented Reality System for Urban Search and Rescue

Most robots in urban search and rescue (USAR) fulfill tasks teleoperated by human operators (Such as controlling robot movement to avoid obstacles and explore unknown environments). The operator has to know the location of the robot and find the position of the target (victim). This paper presents an augmented reality system using a Kinect sensor on a customly designed rescue robot. Firstly, Simultaneous Localization and Mapping (SLAM) using RGB-D cameras is running to get the position and posture of the robot. Secondly, a deep learning method is adopted to obtain the location of the target. Finally, we place an AR marker of the target in the global coordinate and display it on the operator's screen to indicate the target even when the target is out of the camera's field of view. The experimental results show that the proposed system can be applied to help humans interact with robots.
Graphene-Based Hyperbolic Metamaterials with Non-Local Quantum Gain

We propose stratified graphene-dielectric structures as a route to active hyperbolic metamaterials. Employing an exact in RPA, non-local quantum conductivity model allows us to describe the graphene plasmons in the photo-inverted graphene carrier system at large wavevectors, which is of key interest for hyperbolic metamaterials. By calculating Bloch modes of these structures, we predict the possibility of mode loss compensation and amplification, as well as show the tunability of these properties.
An Analysis of the New Employee Onboarding Process in Startup

Turnover is one of the factors that can cause the development of a company to be hampered, especially for startup. The high level of employee turnover caused by many things, one of them is employee dissatisfaction. Onboarding process is one of the ways that can be used to introduce the new employee to the culture and work environment so that it can develop job satisfaction and convenience. However, to get an effective result, onboarding process should also be done well and systematically. This paper describes how the onboarding process is done by the startups, especially those that specialize in software engineering. The study used literature review, interview and questionnaire methods. The interview was conducted with the leaders of six startups in Yogyakarta, while questionnaires were distributed to employee in each startup who have worked for about one year. The data of the questionnaire were analyzed using descriptive statistics. Based on the results, it was found that all startups have done the five aspects of onboarding on their new employees. But the average value on these five aspects is below 80%. The lowest average score of 67% is in the documentation aspect. While the lowest sub aspect is a sub aspect of developer-oriented documentation with an average value of 58.22% and this is included in enough criteria.