Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Squat Strength and Muscle Activity Between Female Athletes With Varus Versus Valgus Knee Angles During Jumping

This investigation examined squat strength and muscle activation during jump landings between female athletes who landed with a varus knee position versus a valgus knee position. Twenty-one female athletes were recruited from Appalachian State University. Subjects had at least two years of resistance training experience, and played basketball or volleyball at least 4 hours per week. All subjects performed a one repetition maximum (1RM) in the back squat and performed three of each of the following jumps: countermovement jump, 20 cm, 40 cm, and 60 cm drop jumps. Knee position was calculated using 3D videography at the moment of peak knee flexion. EMG activity was collected on the Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), and Gluteus Maximus (GM) using wireless electrodes. Average muscle activity for 100 ms prior to peak knee flexion was averaged for the left and right leg and EMG activity of the VL and VM were averaged together to represent quadriceps activity. Activation of quadriceps, BF, GM, absolute 1 RM and relative 1RM were not significantly different between the valgus versus varus knee angle groups. Significant differences were observed in knee angles between the valgus and varus groups in all jump conditions (p =0.05).
The CARMENES search for exoplanets around M dwarfs. Benchmarking the impact of activity in high-precision radial velocity measurements

Current exoplanet surveys using the radial velocity (RV) technique are targeting M dwarfs because any habitable zone terrestrial-mass planets will induce a high RV and orbit on shorter periods than for more massive stars. One of the main caveats is that M dwarfs show a wide range of activity levels from inactive to very active, which can induce an asymmetry in the line profiles and, consequently, a spurious RV measurement. We aim to benchmark the impact of stellar activity on high-precision RV measurements using regular-cadence CARMENES visible and near-infrared observations of the active M3.5 dwarf EV Lac. We used the newly developed technique of low-resolution Doppler imaging to determine the centre-of-light, or spot-induced RV component, for eight observational epochs. We confirm a statistically significant and strong correlation between the independently measured centre-of-light and the chromatic index, which is a measure of the amplitude variation with wavelength of the RVs. We also find circular closed-loop relations of several activity indices with RV for a subset of data that covers only several rotation periods. We also investigate the implications of large phase gaps in the periodograms of activity indicators. Finally, by removing the spot-induced RV component we improve the planet-mass sensitivity by a factor of at least three. We conclude that for active M stars, a regular-cadence observing strategy is the most efficient way to identify and eliminate sources of correlated noise.
Agricultural Video as A Learning Medium for Young Farmer

The aim of this study is to identify if learning using video for sharing agricultural activities through YouTube can increase young farmers’ interest and skills. Now the concept of video in social media provides a self-learning environment with the help of information and communication technology tools. This tool is a simulation that allows farmers to experience a real learning experience and be able to interact with other farmers without having face-toface encounters. This facility becomes the best expansion agent that demands farmers to constantly update their knowledge and skills throughout their lives. The studies carried out the survey method using a questionnaire to collect research data. A total of 66 young farmers consisting of farmers in the districts of Jeli, Kuala Krai, and Gua Musang in the Kelantan, Malaysia was selected as respondents. Data for this study analyzed descriptively by using SPSS ver22 software. The findings show the use of learning materials such as videos give the positive impact that can improve the skills and knowledge of farmers in agricultural activities. The finding also showed that video can reduce cognitive load as well as save time, energy and cost to obtain something new information in the field of agriculture. The findings of this study are expected to help individuals who want to venture into the field of agriculture to increase the level of knowledge, understanding, and readiness for self-learning farming methods. It is clear that this video-based learning technology opens up many new opportunities to be explored by change agents in enhancing the learning potential of youth. Therefore, proposed that further research is related to the potential and impact of the latest technologies that can add value from the perspective of Risale-i Nur to existing video technologies. International Journal of Academic Research in Progressive Education and
How to Improve Cumulative Methane and Nitrous Oxide Flux Estimations of the Non‐Steady‐State Chamber Method?

The flux calculation schemes (FCSs) and gas sampling schemes (GSSs) determine the accuracy and representativeness of non‐steady‐state chamber measurements. The study aimed to provide guidelines on FCSs and GSSs to improve cumulative flux estimations of the non‐steady‐state chamber method. Based on a dataset obtained from automated chamber measurements in a permafrost‐affected wetland in northeast China, we evaluated the effects of FCSs and GSSs on cumulative methane and nitrous oxide flux estimates at the field scale. The evolution of chamber headspace gas concentrations was classified into five patterns, presenting the measurement disturbance and variation of non‐steady‐state chamber method. Three FCSs, that is, the sole use of linear model and hybrid use of linear with empirical quadratic and theoretical exponential models, were established on the basis of evolution patterns of chamber headspace gas concentrations. The hybrid FCSs were more robust for cumulative flux estimates than the sole FCS of the linear model. The flux dataset with the high spatiotemporal resolution was subsampled to simulate datasets obtained with different GSSs. The subsampling of flux dataset proved optimization of GSSs by allocating limited measurement resources to preferentially promote the spatial representativeness of measurements (e.g., with more replicate chambers and stratified chamber placement according to microtopographies), characterize the small‐scale spatiotemporal variability of fluxes (e.g., diurnal variation and spatial heterogeneity due to microtopographies), and capture the evolution pattern of chamber headspace gas concentrations, could effectively improve cumulative flux estimates at the field scale. Our guidelines on FCSs and GSSs can serve to the improvement of non‐steady‐state chamber methodology.
Loxl3 Promotes Melanoma Progression and Dissemination Influencing Cell Plasticity and Survival

Simple Summary Malignant melanoma is the most lethal skin cancer due to its aggressive clinical behavior and therapeutic resistance. A comprehensive knowledge of the molecular mechanisms underlying melanoma progression is urgently needed to improve the survival of melanoma patients. Phenotypic plasticity of melanoma cells has emerged as a key process in melanomagenesis and therapy resistance. This phenotypic plasticity is sustained by an epithelial-to-mesenchymal (EMT)-like program that favors multiple intermediate states and allows adaptation to changing microenvironments along melanoma progression. Given the essential role of lysyl oxidase-like 3 (LOXL3) in human melanoma cell survival and its contribution to EMT, we generated mice with conditional melanocyte-specific targeting of Loxl3, concomitant to Braf activation and Pten deletion. Our results supported a key role of Loxl3 for melanoma progression, metastatic dissemination, and genomic stability, and supported its contribution to melanoma phenotypic plasticity by modulating the expression of several EMT transcription factors (EMT-TFs). Abstract Malignant melanoma is a highly aggressive tumor causing most skin cancer-related deaths. Understanding the fundamental mechanisms responsible for melanoma progression and therapeutic evasion is still an unmet need for melanoma patients. Progression of skin melanoma and its dissemination to local or distant organs relies on phenotypic plasticity of melanoma cells, orchestrated by EMT-TFs and microphthalmia-associated TF (MITF). Recently, melanoma phenotypic switching has been proposed to uphold context-dependent intermediate cell states benefitting malignancy. LOXL3 (lysyl oxidase-like 3) promotes EMT and has a key role in human melanoma cell survival and maintenance of genomic integrity. To further understand the role of Loxl3 in melanoma, we generated a conditional Loxl3-knockout (KO) melanoma mouse model in the context of BrafV600E-activating mutation and Pten loss. Melanocyte-Loxl3 deletion increased melanoma latency, decreased tumor growth, and reduced lymph node metastatic dissemination. Complementary in vitro and in vivo studies in mouse melanoma cells confirmed Loxl3’s contribution to melanoma progression and metastasis, in part by modulating phenotypic switching through Snail1 and Prrx1 EMT-TFs. Importantly, a novel LOXL3-SNAIL1-PRRX1 axis was identified in human melanoma, plausibly relevant to melanoma cellular plasticity. These data reinforced the value of LOXL3 as a therapeutic target in melanoma.
The Role of Human Factor in the Transport of Hazardous Materials

This article describes and analyses issues related to modelling of human factor in the transport of hazardous materials. Due to its complexity, a human being constitutes an element parameterization of which encounters numerous difficulties. In the literature various attempts of human actions’ modelling have been presented. Authors of the article have used heuristic techniques – particularly, fuzzy set methods – in order to build a model of human factor for the purposes of their work. This model defines human actions by text description, that is, linguistically. The specificity of fuzzy sets allows the “precision” of human actions’ description to be “naturally” limited. The model has been built upon proprietary expert-based surveys, enabling selection of specific features, influencing driver’s efficiency, with their corresponding fuzzy sets. The model’s initial parameter is λL – intensity of accidents caused by driver’s mistake. The parameter has been created for the purposes of the proprietary risk assessment model in the road transportation of hazardous materials. Driving mistakes can significantly increase the risk of accidents. This heuristic model has been used to prepare a simulation of the influence of selected features on the driving safety.
Effects of Phone-Based Psychological Intervention on Caregivers of Patients with Early-Onset Alzheimer’s Disease: A Six-Months Study during the COVID-19 Emergency in Italy

Caregivers of patients with early-onset Alzheimer’s disease (EOAD) experience higher level of burden, stress, and depression, due to premature role changes and social isolation. Moreover, the SARS-CoV-2 pandemic compelled restrictions regarding social interactions and mobility in Italy from March 2020, prompting telemedicine approaches for supporting patients and their families confined at home. We reported our experience regarding the effects of psychological phone-intervention (phone-I) on EOAD caregivers during pandemic. Twenty caregivers of EOAD patients were randomly assigned to treatment (TG) or control (CG) group. TG weekly underwent a phone-I for one month. All participants were assessed for caregiver burden and needs, anxiety and depression levels, and subjective impact of traumatic events at baseline (T0), at the fifth week (T1) and after 6 months (T2) from phone-I. We observed higher vulnerability to post-traumatic stress in TG compared to CG in all timepoints (p ≤ 0.05). Decreased stress effects and caregiver burden were revealed in TG at T1 compared to T0 (p ≤ 0.05), although showing an increase of these measures at T2 in the treated caregivers. Our findings suggest that although TG showed a peculiar vulnerability to post-traumatic stress, they showed increased wellbeing immediately after phone-I. However, this benefit disappeared six months later, along with the second infection wave, probably due to “exhaustion stage” achievement in “General Adaptation Syndrome”. This trend may suggest a beneficial but not solving role of a prompt phone-I on burden of caregivers of EOAD patients during the SARS-CoV-2 emergency.
Growth and Development of Inhomogeneous Structures

This paper presents a new approach for the design synthesis of continuous inhomogeneous structures with an goal of mimicking the growth of biological structures in nature. The results presented here provide interesting insights into the concept of structural growth in biology, and motivate the combination of evolutionary techniques in future research, such that might provide the ability to explore a wide range of design configurations. In order to model biological growth an artificial model has been created composed of an external environment and a collection of cells. The environment represents the engineering requirements (loads and boundary conditions), while the cells represent small elements of volume of the structure. Each cell contains an artificial DNA sequence which serves as a set of rules that execute during the growth procedure. These rules form a recipe for the structure and are relatively simple. During the growth procedure, cells will be deformed, adhere to other cells, divide, and differentiate. The differentiating rule may cause a cell to change its mechanical properties (σy, ν, E), and by doing so introduce inhomogeneous properties in the structure. The rules form an alphabetic sequence and therefore are well-suited to be used in an evolutionary algorithm, where rules governing the growth and development of individuals are evolved instead of the more traditional evolution of parameters describing the complete individuals.
A Type-2 Fuzzy Controller for Floating Tension-Leg Platforms in Wind Turbines

This paper proposes a type-2 fuzzy controller for floating tension-leg platforms in wind turbines. Its main objective is to stabilize and control offshore floating wind turbines exposed to oscillating motions. The proposed approach assumes that the dynamics of all units are completely unknown. The latter are approximated using the proposed Sugeno-based type-2 fuzzy approach. A nonlinear Kalman-based algorithm is developed for parameter optimization, and linear matrix inequalities are derived to analyze the system’s stability. For the fuzzy system, both rules and membership functions are optimized. Additionally, in the designed approach, the estimation error of the type-2 fuzzy approach is also considered in the stability analysis. The effectiveness and performance of the proposed approach is assessed using a simulation study of a tension leg platform subject to various disturbance modes.
On roof construction and wall strength : non-linear structural integrity analysis of the Early Bronze Age Helike Corridor House

We have demonstrated [1] through Structural Integrity Analysis that the Adobe brick Early Helladic (EH II-III) Helike Corridor House design was sound and it was able to support a second floor. This paper furthers the research focusing on roof loads by performing non-linear and sensitivity analyses addressing two research questions: 1) Was the roof of a light tiled construction or was it heavy as described in [2] about four times heavier than a tiled roof; and 2) What would the behaviour of the structure be when subjected to adverse wet weather under light and heavy roof loads. Previous research has shown that Adobe bricks can absorb large quantities of water from 2 to 10kg/m2 [3, 4]. Furthermore, if it absorbs 4kg/m2 the overall strength of the wall is reduced by 50% [3]. Using mechanical properties of dry and wet Adobe bricks, we have performed non-linear analysis using ANSYS aimed at determining whether or not the structure would collapse under four conditions: LIGHT-DRY (light roof, dry Adobe), LIGHT-WET, HEAVY-DRY and HEAVY-WET. The results show that under a light roof the structure would stand. However, a heavy roof similar to early Minoan structures [2] would lead to total collapse of the house as the Yield Stress on the wall structure is greater than the maximum allowed for wet and for dry Adobe. This points to sophisticated construction techniques with tiled rooves and the possible use of stabilising materials such as lime, ash or organic to protect the tiles [5]. The theory that Helike builders were aware of such techniques could only be supported by planned forthcoming detailed soil analysis to identify possible stabilisers and this would raise further questions on wider interactions such as trade. This research offers new understandings of roof techniques and weight limitations for Adobe building Corridor Houses in a period where only scant evidence is available.
The Impact of Student Characteristics for Working with AR Technologies in Higher Education - Findings from an Exploratory Study with Microsoft HoloLens

Augmented reality (AR) is being used in various fields and increasingly being used in the educational sector. Although there is still little research available on the use of this technology in education, the research literature indicates its potential and effectiveness. However, information about students’ characteristics and individual learning preconditions in relation to learning with AR technologies is still scarce. In this study, 18 student teachers for science and technology for lower secondary schools of a German-speaking university of teacher education were asked about different aspects related to motivation, interest, attitude, and self-efficacy before (questionnaire) and after (interviews) participating in an AR-supported teaching unit with Microsoft HoloLens. The results show that the students have a very positive attitude towards AR technologies and were highly motivated to work with this technology. Attitudes towards AR technologies, as well as towards new technologies in general, were found to be related to motivational factors and aspects of self-efficacy in the context of the AR teaching unit. As these aspects can have an impact on learning outcomes, it is of utmost importance to understand and recognize them. Educators and researchers should therefore pay more attention to these issues in the future.
Probabilistic Selection Approaches in Decomposition-Based Evolutionary Algorithms for Offline Data-Driven Multiobjective Optimization

In offline data-driven multiobjective optimization, no new data are available during the optimization process. Approximation models, also known as surrogates, are built using the provided offline data. A multiobjective evolutionary algorithm can be utilized to find solutions by using these surrogates. The accuracy of the approximated solutions depends on the surrogates and approximations typically involve uncertainties. In this article, we propose probabilistic selection approaches that utilize the uncertainty information of the Kriging models (as surrogates) to improve the solution process in offline data-driven multiobjective optimization. These approaches are designed for decomposition-based multiobjective evolutionary algorithms and can, thus, handle a large number of objectives. The proposed approaches were tested on distance-based visualizable test problems and the DTLZ suite. The proposed approaches produced solutions with a greater hypervolume, and a lower root mean squared error compared to generic approaches and a transfer learning approach that do not use uncertainty information.
Heat/mass transfer distribution in a rotating, two-pass channel with smooth and ribbed walls

Detailed mass transfer measurements have been made in a rotating, two-pass square duct designed to simulate the first two passes of an internal turbine-blade-coolant channel. These measurements have been obtained using the naphthalene sublimation technique. Smooth wall results have been obtained for Reynolds numbers (Re) between 5,000 and 30,000 and rotation numbers (Ro) that satisfy ReRo = 10,000. Ribbed wall results are presented for the parameters above with a rib height to hydraulic diameter ratio fixed at 0.1 and a rib pitch to rib height ratio of 10.5.
Latent heat thermal energy storage systems in lightweight construction: review of PCM applications in Solar Decathlon houses

The use of thermal mass in buildings is an effective way to improve the building’s interior comfort in places with high diurnal temperature variation. Combined with other passive strategies, thermal mass can play an important role in the energy efficiency of the building, minimizing the necessity of the traditional conditioning systems. However contemporary construction tends to industrializing light weight systems with low thermal mass. An innovative way
GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation

Generating recommendations based on user-item interactions and user-user social relations is a common use case in web-based systems. These connections can be naturally represented as graph-structured data and thus utilizing graph neural networks (GNNs) for social recommendation has become a promising research direction. However, existing graph-based methods fails to consider the bias offsets of users (items). For example, a low rating from a fastidious user may not imply a negative attitude toward this item because the user tends to assign low ratings in common cases. Such statistics should be considered into the graph modeling procedure. While some past work considers the biases, we argue that these proposed methods only treat them as scalars and can not capture the complete bias information hidden in data. Besides, social connections between users should also be differentiable so that users with similar item preference would have more influence on each other. To this end, we propose Graph-Based Decentralized Collaborative Filtering for Social Recommendation (GDSRec). GDSRec treats the biases as vectors and fuses them into the process of learning user and item representations. The statistical bias offsets are captured by decentralized neighborhood aggregation while the social connection strength is defined according to the preference similarity and then incorporated into the model design. We conduct extensive experiments on two benchmark datasets to verify the effectiveness of the proposed model. Experimental results show that the proposed GDSRec achieves superior performance compared with state-of-the-art related baselines. Our implementations are available in https://github.com/MEICRS/GDSRec.
Antimycotic Activity of Some Medicinal Plants against Mucor circinelloides

The in vitro antimycotic activity of the leaf extract of Catharanthus roseus, Lantana camara, Nerium indicum, Sida cordifolia, and Ziziphus mauritiana was studied against M. circinelloides. This fungal species causes mucormycosis (black fungus). Presently, mucormycosis is affecting COVID patients due to prolonged use of steroids. So, it is needed to require development of more effective and less toxic antimycotic agents for the treatment of mucormycosis. Plants and their extraction preparations have been used as medicine against infectious disease. In this research, aqueous, ethanol, and DMSO (dimethyl sulfoxide) leaf extracts were used for antimycotic activity. All leaf extracts of selected medicinal plants recorded significant activity against M. circinelloides. Ethanol leaf extract of C. roseus showed the highest antimycotic activity followed by N. indicum and L. camara. Z. mauritiana which showed moderate activity against M. circinelloides.