Miracle-dz/UniFAR-FTUs huggingface dataset:
Yet Another Platform? Motivational Factors for Using Online Communities in Business Contexts

As a consequence of ongoing globalization processes and demographic change, many small and medium-sized companies face the problem of knowledge loss. To counteract this, companies are adopting Web 2.0 applications to accumulate and store the knowledge of their employees. However, little is known about the circumstances under which employees are willing to invest time in social media as a part of their work routine. Thus, this paper introduces an exploratory case study focusing the motivational factors that influence the use of an online expert community in business context. The results of the performed focus groups and interviews show that particularly intrinsic motivational factors are considered to be relevant. The attitude towards extrinsic motivational factors and related tangible motivational factors is highly controversial, whereas intangible motivational factors such as social and organizational motivational factors seem to have a positive impact on the motivation to use an intra-organizational online communities (OC). Supplementary motivational factors mentioned by the interviewees refer to the platform itself. Overall, the results indicate that the implementation of Web 2.0 applications in business contexts requires a tailored incentive system that suits to the company-specific requirements and takes into account the employees’ needs.
IoT-based Network Attacks Discovery with Combined Classifiers

In this paper following the recent trends in IoT-based network attacks discovery and advancing further our previous research, in which we optimize and test single neural network, support vector machine and random forest classifiers for both the detection and recognition of multiple DDoS attacks, we propose results from newly developed combined classifiers. The first of them employs only a neural network and a random forest classifier, while the second use additionally a support vector machine. Both are implemented in two modifications – as detectors of malicious vs. normal traffic, and as classifiers of 10 types of attacks vs. non-attack samples. High classification accuracy is being obtained over the popular Bot-IoT dataset and it prove higher than that of the single classifiers. At the same time, it is also higher than other solutions, proposed in the practice.
Sulfate-chloride sodium-magnesium mineral waters modulate neuroendocrine-immune complex and metabolism in healthy female rats

Background. Earlier in an experiment on rats, we showed that newly created sulfate-chloride sodium-magnesium drinking mineral waters of Truskavets’ spa has a significant modulating effect on the parameters of metabolism and the autonomic nervous, endocrine and immune systems. In this study, we combined data obtained on the same animals, in line with the concepts of neuroendocrine-immune complex and functional-metabolic continuum. Materials and Methods. Experiment was performed on 50 healthy female Wistar rats 230-290 g divided into 4 groups. Animals of the first group remained intact, using tap water from drinking ad libitum. Rats of the second (control) group for 6 days administered a single tap water through the tube at a dose of 1,5 mL/100 g of body mass. The rats of the main groups received the water "Myroslava" and "Khrystyna". The object of the study were the metabolic, neuro-endocrine and immune parameters. Results. The method of discriminant analysis revealed 31 parameters, according to which all four groups of animals differ from each other. Classification accuracy is 100%. Conclusion. The newly created sulfate-chloride sodium-magnesium drinking mineral waters of Truskavets’ spa has both similar and specific effects on the neuroendocrine-immune complex and metabolism at healthy old female rats with weekly use. This provides a basis for preclinical studies.
An exploration of the determinants and health impacts of active commuting

Encouraging more walking or cycling amongst commuters in the United Kingdom could help reduce physical inactivity and contribute various health, environmental and other economic benefits. Existing empirical studies of the determinants and impact of active commuting are limited however, since they typically use cross-sectional, observational study designs or focus on small scale behavioural interventions. This thesis explored how the impact of larger scale population-level changes in the design of urban built environments and other transport policies could be assessed using theories and techniques often employed in health economics. There are three main sections. First, a literature review which found few studies of the health impact of changes to the built environment that had used randomisation or advanced econometric techniques (e.g. instrumental variables). This included an assessment of whether the chosen methodological approach critically affected the results obtained and the development of a guide to aid policy makers in distinguishing between, and assessing the quality of, observational studies that used different analytical techniques. Second, an empirical analysis of twenty-one waves of the British Household Panel Survey (BHPS) which included an exploration of the determinants of active commuting including life events (e.g. moving home and changing job) and studies of the impact on body mass index and subjective wellbeing of switching commute mode from car travel to walking, cycling or public transport. Third, an exploration of the potential impact of financial incentives to promote active travel. This included an empirical review of intervention studies as well as a theoretical element, including development of a simple analytical framework and review of behavioural economic concepts. Whilst the identified health improvements could support the case for investment in policies that promote active commuting, the thesis recommended that more robust evaluation of population-level policies is required so that scarce resources can be targeted more effectively.
Changes in Alkaoids Content of Some Selected Nigerian Vegetables during Processing

Alkaloids, natural organic compounds present majorly in plants have been used in all culture as portion, medicine and poison. Vegetables are no exception; they contain varying degree of alkaloids. However, different processing methods are usually applied before consumption which may affect their alkaloids contents. Evaluation and effect of processing (blanching and juicing) were investigated on eight selected vegetables consumed in south western Nigeria. Standard Laboratory procedures were employed. Results showed highest level of alkaloids: in the fresh vegetable; Manihot esculenta 42.09±5.55mg/100d dry weight, in the blanched; Teleferia occidentalis 146.22±96.96 mg/100d dry weight while in the juiced vegetable Manihot esculenta leaf 296.69±61.02mg/100g dry weight. The lowest values were observed in the fresh; Amaranthus spp. (local name "Ebiden") 6.40±. 47 mg/100d dry weight, in the blanched; Ipomoea batatas leaf 14.15±2.22 mg/100d dry weight and in the juiced extract; Amarantus cruentus 93.16±2.22 mg/100d dry weight. The study revealed that the alkaloids content of fresh vegetables varied while blanching and juicing increased its content.
Cultural Values in Water Management and Governance: Where Do We Stand?

Research in water governance and management is a complex subject that involves the appraisal of social, economic, and environmental–biophysical aspects. Cultural and social values are regarded as key drivers in decision-making processes in both domains. Identifying relevant cultural values however is difficult given the interdisciplinary nature of theoretical frameworks and the implementation and operational needs of water governance/management research. In this work, we conduct a systematic literature review and thematic analysis of existing theories of culture (ToC) to identify common cultural values, theoretical frameworks, disciplinary trajectories and implementation trends relevant to water management and governance. Results indicate that the dominant ToC corresponds to Cultural Theory with its four defined categories (Egalitarian–Hierarchist–Individualist–Fatalist). In addition, results show emergent cultural values linked to “local” place-based knowledge perspectives indicating a more pluriversal understanding of cultural values. Cultural values associated with water management revolve around anthropocentrism, whereas values associated with water governance revolve around concepts of provenance/places. Implementation of ToC/cultural values is limited in practical applications, and we provide an example on how to improve on that. We suggest a succinct theory of culture such as Schwartz’s cultural values be considered to be an alternative to capture a greater heterogeneity across the breadth of water governance/management-related and basin-specific contexts.
Effect of autoclaving on the cyclic fatigue resistance of nickel-titanium rotary instruments: An in vitro study

Aim: The aim of the study is to determine the effect of autoclaving on the cyclic fatigue resistance (CFR) in respect to three different rotary nickel-titanium (NiTi) systems. Methods: Three rotary NiTi files with different manufacturing process were selected and arranged into three groups. Group 1: Neolix Neoniti files (n = 15), Group 2: Edge Files (n = 15), Group 3: NeoendoFlex files (n = 15). Each group was then subdivided into three subgroups containing 5 samples each based on the number of cycles of autoclaving (0, 1, 5 cycles). The instruments were subjected to autoclave without usage. The files of size 25, taper 6%, and 25 mm length were taken. After the autoclaving cycles, the files were rotated in cyclic fatigue testing device with simulated canal curvature of 60° until file separation. Time taken for the instrument separation (in minutes) was multiplied by the number of rotations per minute to attain the mean number of cycles to failure for every file. The obtained results were subjected to statistical analysis using two-way ANOVA and Newman–Keuls multiple post hoc procedures. Results: Neolix Neoniti files exhibited the maximum CFR (98.80) than EdgeFiles (80.47) and Neoendo Flex files (41.80) (P = 0.0001). Reduction in CFR was observed with increase in the number of cycles of autoclaving (i.e., 0, 1, 5 cycles). Conclusion: Autoclaving has a negative influence on the CFR of the rotary NiTi files used. Neolix Neoniti files exhibited greater CFR than EdgeFiles and Neoendo Flex files.
Application of the technology acceptance model to food delivery apps

PurposeThis study explores food delivery app users and technology acceptance model as a theoretical underpinning. This study thus investigated the determinants of usefulness, ease of use and intention to use for food delivery app service.Design/methodology/approachThe variables of delivery time, diverse menu, quarantine, review quality and ease of use are employed as determinants of usefulness. The antecedents of ease of use are easy registration and easy payment. This study also examined the association between ease of use, usefulness and intention to use. This study collected data using Amazon Mechanical Turk, and the number of valid observations for statistical analysis was 484. A structural equation model was used to test the hypotheses.FindingsRegarding the results, usefulness was positively affected by delivery time, quarantine, review quality and ease of use. Additionally, ease of use was positively impacted by easy registration and easy payment. Finally, this study showed that ease of use positively affects both usefulness and intention to use, and usefulness is positively associated with intention to use.Originality/valueThis study contributes to the literature by ensuring the explanatory power of technology acceptance model for food delivery app.
Examining physiological roles of adipose derived VEGF: Consequences in substrate availability and endurance exercise capacity in adipocyte specific VEGF deficient mice

Examining physiological roles of adipose derived VEGF: Consequences in substrate availability and endurance exercise capacity in adipocyte specific VEGF deficient mice Nicole J. Zachwieja Reducing vascular endothelial growth factor (VEGF) in adipose tissue alters adipose vascularity and metabolic homeostasis. We hypothesized that this would also affect metabolic responses during exercise-induced stress, and that adipocyte-specific VEGF deficient (adipoVEGF-/-) mice would have impaired endurance capacity. Endurance exercise capacity in adipoVEGF-/(n=10) and littermate control (n=11) mice was evaluated every 4 weeks between 6 & 24 weeks of age using a submaximal endurance run to exhaustion at 20 m/min, 10-degree incline. Maximal running speed, using incremental increases in speed at 30-second intervals, was tested at 25 weeks of age. Beginning at 6 weeks, and continuing with all time points, endurance run time to exhaustion was 30% lower in adipoVEGF-/compared to controls (p<0.001). The age-associated rate of decline in endurance capacity was similar in adipoVEGF-/vs. control mice and there was no difference in maximal running speed between the groups. Following 1 hour of running at 50% maximum running speed, adipoVEGF-/mice displayed decreased circulating insulin, (p<0.001), glycerol (p<0.05), and a tendency for decreased glucose (p=0.06) compared to controls. These data suggest that deficits in adipose tissue vasculature are mediated by adipose VEGF and that deficiency of VEGF blunts the availability of lipid-derived substrates during endurance exercise and affects insulin secretion and glucose metabolism.
A sampling-based probabilistic path planner for multirotor air vehicles in cluttered environments

Successful navigation of small, unmanned aerial vehicles (UAVs) in cluttered environments is a challenging task, especially in the presence of turbulent winds and state estimation uncertainty. This paper proposes a probabilistic path planner for UAVs operating in cluttered environments. Unlike previous sampling-based approaches which select robust paths from a set of trajectory candidates, the proposed algorithm seeks to modify an initial desired path so that it satisfies obstacle avoidance constraints. Given a desired path, Monte Carlo uncertainty propagation is performed and obstacle collision risks are quantified at discrete intervals along the trajectory. A numerical optimization algorithm is used to modify the flight path around obstacles and reduce probability of collision while maintaining as much of the originally desired path as possible. The proposed path planner is specifically designed to leverage embedded massively parallel computers for near real-time uncertainty propagation. Thus the planner can be run in real-time in a feedback manner, modifying the path appropriately as new measurements are obtained. Example results for a standard quadrotor show the ability of the path planning scheme to successfully generate trajectories in cluttered environments. Trade studies characterize algorithm performance as a function of obstacle density and collision risk acceptability.
Fractal nonlocal thermoelasticity of thin elastic nanobeam with apparent negative thermal conductivity

Abstract This study treats a new model of nonlocal fractal thermoelasticity beam theory for nanomaterials characterized by an apparent negative thermal conductivity which occurs in shaped graded materials. The model is based on the new concept of "product-like fractal measure" introduced by Li and Ostoja-Starzewski in their formulation of fractal continuum media with fractal dimension The basic setups of the theory are formulated, yet, we have restricted our analysis for the static case. The effects of fractal dimension on field variables, in particular the lateral deflection and the temperature increment of the resonator were analyzed analytically and graphically. It was observed that the physics of the thin elastic nanobeam is affected by the numerical value of the fractal dimension and the characteristic lengths of the theory. Comparable scenarios observed in complex material structures are obtained and discussed.
An Anatomical Insight into the Morphology of the Brachialis Muscle and its Clinical Implications

Introduction: Being the chief flexor of the elbow joint, brachialis muscle, also known as ‘work horse’ of the elbow or Portal’s muscle is one of the three muscles of the front of arm. Ascertaining the morphology of the muscle is of considerable clinical significance because infrequent mention of the pathologies like tear, rupture, tendinopathies, etc., coupled with the conflicting reports of its morphology may often leads to inaccurate diagnosis of clinical conditions pertaining to it. Aim: To study the origin of the muscle in the form of number of heads and type of fibres at origin, site and manner of insertion, mode of nerve supply and presence of accessory slips. Materials and Methods: The study was carried out in the Department of Anatomy, Parul Institute of Medical Sciences and Research, Parul University, Vadodara on the 82 upper limbs used for routine dissection of first MBBS students. After incising the skin, superficial and deep fascia of the arm and cubital fossa, the biceps was retracted to visualise the origin, insertion and nerve supply of the brachialis muscle. Results: In all 82 (100%) arms, the muscle arose by lateral superficial and medial deep heads. Deep head inserted into the coronoid process and upper part of the ulnar tuberosity by an aponeurosis. In 81 (98.8%) specimens, superficial head was inserted by round tendon on to the ulnar tuberosity distal to the deep head. In one (1.2%) specimen, fibres of the superficial head were merging with biceps tendon and inserted on to the radial tuberosity. In 75 (91.5%) arms, muscle was supplied by musculocutaneous nerve and radial nerves and in four (5%) cases by the musculocutaneous, median and Radial Nerve (RN) whereas in 3 (3.5%) case by median and radial nerves. Accessory slips were present in four (5%) specimens. Conclusion: Considerable difference in the morphology of the brachialis was found with regards to the classical picture and should be kept in mind before undertaking any surgical procedure in the arm and elbow region.
A novel approach on energy‐efficient clustering protocol for wireless sensor networks

Wireless sensor networks are group of nodes capable enough to communicate with other nodes wherever they are deployed. The demanding need for a wireless sensor network in various fields of monitoring and tracking has gained more popularity in recent years. However, as sensor nodes have limited and dissipating battery power, energy conservation is a critical challenge in wireless sensor networks. Clustering is one of the promising methodologies to reduce the consumption of energy. This paper presents a cluster‐based routing algorithm for transferring the data to the base station. The algorithm uses the k‐means approach to select the clusters. Each cluster consists of two cluster heads, one for aggregating the data and the other for data transmission; thereby, they share the load and improve the network lifetime. The data are sent to the base station by a multi‐hop approach. For energy efficiency, a minimum cost path is chosen by considering the energy and distance. Simulations are implemented in NS2. The results obtained show that the proposed protocol is more efficient than the benchmarked algorithms in network lifetime, packet delivery ratio, throughput, total energy consumption, and end to end delay.
Systemic intelligence predictors of cognitive flexibility and cognitive holding power among university students

This study aimed to investigate the role of systemic intelligence factors in explaining cognitive flexibility and cognitive holding power among university students using measures of the aforementioned phenomena. A random sample of (519) students participated in this research, and it was found that factors relating to systemic intelligence could predict cognitive flexibility and cognitive holding power. The elements of systemic intelligence that were most adept at explaining cognitive flexibility were systemic action through positive engagement and active response, while systemic perception was the most explanatory factor in terms of cognitive holding power. The study concluded that systemic intelligence, which has perceptual, cognitive, social and behavioural facets, contributes to student performance in learning settings; consequently, it is recommended that the role of systemic intelligence should be analysed by linking elements of this form of intelligence with the different variables and integrating systemic thinking skills into different learning activities. Keywords: systemic intelligence, cognitive flexibility, cognitive holding power.
Long-term follow-up of a case of choroidal neovascularization secondary to reticular pigmentary retinal dystrophy

Reticular pigmentary retinal dystrophy, also known as Sjögren’s reticular dystrophy, is a rare condition characterized by macular lesions with a reticular pattern, which are best seen on fluorescein angiogram. Choroidal neovascularization secondary to this type of dystrophy is even less common. This report describes a case of reticular pigmentary retinal dystrophy with vision loss due to neovascular membrane, which responded well to treatment with anti-vascular endothelial growth factor.
Deep Convolutional Neural Network-Based Hemiplegic Gait Detection Using an Inertial Sensor Located Freely in a Pocket

In most previous studies, the acceleration sensor is attached to a fixed position for gait analysis. However, if it is aimed at daily use, wearing it in a fixed position may cause discomfort. In addition, since an acceleration sensor can be built into the smartphones that people always carry, it is more efficient to use such a sensor rather than wear a separate acceleration sensor. We aimed to distinguish between hemiplegic and normal walking by using the inertial signal measured by means of an acceleration sensor and a gyroscope. We used a machine learning model based on a convolutional neural network to classify hemiplegic gaits and used the acceleration and angular velocity signals obtained from a system freely located in the pocket as inputs without any pre-processing. The classification model structure and hyperparameters were optimized using Bayesian optimization method. We evaluated the performance of the developed model through a clinical trial, which included a walking test of 42 subjects (57.8 ± 13.8 years old, 165.1 ± 9.3 cm tall, weighing 66.3 ± 12.3 kg) including 21 hemiplegic patients. The optimized convolutional neural network model has a convolutional layer, with number of fully connected nodes of 1033, batch size of 77, learning rate of 0.001, and dropout rate of 0.48. The developed model showed an accuracy of 0.78, a precision of 0.80, a recall of 0.80, an area under the receiver operating characteristic curve of 0.80, and an area under the precision–recall curve of 0.84. We confirmed the possibility of distinguishing a hemiplegic gait by applying the convolutional neural network to the signal measured by a six-axis inertial sensor freely located in the pocket without additional pre-processing or feature extraction.