Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality of life, health, eating habits and physical development of middle school adolescents in the Świetokrzyskie.

INTRODUCTION AND OBJECTIVE Measurement of the health-related quality of life is currently one of the significant methods of self-evaluation of heath, enabling the detection of disorders in the biopsychosocial functioning of children and adolescents. The aim of the study was to establish significant relationships between the subjective sense of the health-related quality of life, eating habits and objective parameters of physical development among a group of adolescents. MATERIAL AND METHODS The study applied a diagnostic survey methodology with the use of the KIDSCREEN-52 questionnaire, the Health Behaviour in School-aged Children (HBSC) questionnaire, anthropometric measures of choice, and a self-constructed questionnaire. The significance level was set at p<0.05. The collected data was gathered and analyzed using Statistica 10.0 PL. RESULTS Three distinct groups of adolescents with a varying subjective sense of the quality of life were identified. The frequency of basic meal consumption among participants showed some abnormalities. This concerned breakfast in particular, which was consumed before going to school by over half of the participants (63.61%), with boys (70.07%) eating it significantly more frequently than girls (57.83%). Indices based on weight-to-height ratios, such as: BMI, Rohrer's Index and Slender Index were significantly greater in value among boys compared with girls. CONCLUSIONS Adolescents from the Świętokrzyskie region, for the most part exhibited a high subjective sense of the quality of life. The physical development of the participants, as far as basic anthropometric characteristics are concerned, was mostly appropriate and consistent with a high subjective sense of the quality of life and exhibited eating habits.
Carcass characteristics and meat quality of lambs fed high levels of spineless cactus in the diet

The objective was to evaluate the effect of increasing the dietary inclusion of spineless cactus (Nopalea cochenillifera Salm Dyck) on the carcass characteristics and meat quality of confined lambs. Thirty-two male Santa Inês lambs with an average age of 140 days and an initial body weight of 20.4 ± 2.60 kg were used in this study. The lambs were housed in individual stalls for 70 days and individually fed a ration with spineless cactus included at 0, 241, 519, or 753 g/kg of dry matter (DM). The lambs were slaughtered, and characteristics of the carcass and meat were recorded and analysed. Inclusion of spineless cactus had a quadratic effect on the bodyweight at slaughter and on the empty bodyweight of the lambs. The inclusion of 500 g/kg of spineless cactus provided the highest predicted cold carcass weight (16.03 kg). There was a quadratic effect of the inclusion of spineless cactus on the weight of meat cuts and leg composition of lambs. The inclusion of spineless cactus did not influence pH, tenderness, and water-retention capacity of the meat. However, the intramuscular fat content increased 1 mg for every 10 g/kg inclusion of spineless cactus in the diet. Quadratic effects were observed of the inclusion of spineless cactus on the weights of the liver, heart, rumen, blood, skin and internal fat of the lambs. Up to 500 g/kg of spineless cactus could be included in the diet of confined lambs.
Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects

State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend in industrial manufacturing and monitoring is the Digital Twin (DT) which is just now being defined and explored, showing promising results in facilitating the realization of the Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies and would greatly benefit from improved data handling and availability, a lack of combination regarding the two concepts is detected in literature. In addition, the next-generation-Digital-Twin (nexDT) definition is yet ambiguous. Existing DT reviews discuss broader definitions and include citations often irrelevant to PM. This work aims to redefine the nexDT concept by reviewing latest descriptions in broader literature while establishing a specialized denotation for EM manufacturing, PM, and control, encapsulating most of the relevant work in the process, and providing a new definition specifically catered to PM, serving as a foundation for future endeavors. A brief review of both DT research and PM state-of-the-art spanning the last five years is presented, followed by the conjunction of core concepts into a definitive description. Finally, surmised benefits and future work prospects are reported, especially focused on enabling PM state-of-the-art in AI techniques.
Minireview on Self-Healing Polymers: Versatility, Application, and Prospects

Nature is blessed with self-healing properties. Mimicking nature is a traditional practice to innovate new classes of materials for researchers. In this practice, researchers made a revolutionary approach to innovate self-healing polymer (SHP) that can be used to treat damage-related losses. Different SHPs with various properties have been developed for a wide range of applications. SHPs unlocked the key to the taste of real life through their application and versatility in the sectors close to our day-by-day life of this age and the near future. In this study, we reviewed the scopes and prospects of the application of SHPs owing to different properties. Varieties of amazing properties made SHPs fit in different sectors such as construction, paint and coat, electronics, healthcare, textile, and automotive and aerospace. Similarly, due to having suitable functionality, SHPs can also be used in different industries. Therefore, it is high time to generalize the production of SHPs by suitable research and make sure the easy application for the welfare of human civilization and other living creatures.
Differential roles of trithorax protein MLL-1 in regulating neuronal Ion channels

Repressive regulation of potassium channel genes by Polycomb group (PcG) proteins contributes to PcG protein-mediated neuroprotection against neuronal ischemic injury, as seen in an ischemic stroke. Here we asked the question whether Trithorax group (TrxG) proteins, the antagonistic partners of PcG proteins (i.e, epigenetic activators targeting the same genes) may also regulate potassium channels. Results of patch-clamp studies on cultured neuronal cells showed that inhibition of TrxG protein MLL-1 led to an increase in potassium channel activity, an unexpected effect for a presumed gene activator. In contrast, decreased sodium currents were observed with MLL-1 inhibition. Increased or decreased levels of potassium channel protein Kv2.1 or sodium channel protein Nav1.2, respectively, were seen with MLL-1 inhibition, as determined by immunocytochemistry. These results, for the first time, demonstrate an involvement of TrxG protein MLL-1 in regulating neuronal ion channels, potentially repressing potassium channel genes.
RMHP_A_314588 3865..3872

1Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark; 2Data and Development Support, Region Zealand, Sorø, Denmark Purpose: A high number of hospital admissions may indicate poor general health and less than optimal health care across sectors. To prevent hospital admissions, previous studies have focused on predicting readmissions relating to a defined index admission and specific condition, whereas generic models suited for community-dwelling persons are lacking. The aim of this study was to validate a generic model that predicted risk of emergency hospital admission within the following three months and to investigate regional variation. Materials and Methods: This study is an observational register-based validation study of a prediction model. The prediction model was based on a population of frail elderly, persons with non-communicable diseases, and persons with three emergency hospital admissions using information about diagnoses and hospital contacts. The prediction model consisted of two stages. In the first stage, covariate associations to admissions are estimated from observed data in one year. In the second stage, admissions are predicted in the coming three months based on observed estimations from the first stage. The validity of the model was calculated by comparing predicted and observed admissions from August 1st to October 31st, 2016. Results: The study included 112,026 persons. In nationwide data, area under the curve (AUC) was 0.7742 (95% CI 0.7698–0.7786), and the positive predictive value was 52% for the 99th percentile (the top 1%). AUC varied between regions from 0.6914 in Southern Denmark (95% CI 0.6779–0.7049) to 0.8224 (95% CI 0.8064–0.8384) in North Denmark. AUC was higher with nationwide data compared to regional. Conclusion: The model performed satisfactorily in predicting individual risk of emergency hospital admission.
FOUR-ELEMENT CPW-FED UWB MIMO SLOT ANTENNA WITH HIGH ISOLATION AND TRIPLE BAND-NOTCHED CHARACTERISTICS

A novel 4-element UWB MIMO (multiple-input multiple-output) slot antenna with triple band-notched characteristics is designed and fabricated. It is composed of four rectangular slot antennas with two C-slots and a T-slot. To improve the isolation, cross-shaped branches are added. The measured results demonstrate that the antenna can operate ranging 2.51–11.07GHz with the impedance bandwidth (S11 < −10 dB) of 856MHz except three rejected bands, including 3.02–4.07GHz, 4.54– 5.83GHz, and 7.88–9.38GHz, and the inter-element isolation of antenna in the range of UWB band is higher than 21 dB. The presented antenna can filter the interference of WiMAX (3.3–3.7GHz), WLAN (5.15–5.825GHz) and X-band (7.9–8.4GHz). Moreover, the parameters of diversity performance like envelope correlation coefficient (ECC), diversity gain (DG), efficiency, gain, channel capacity loss (CCL), mean effective gain (MEG), and total active reflection coefficient (TARC) have been analyzed. Based on the analysis on simulated and measured results, the proposed MIMO antenna is competent for UWB applications with notched bands for WiMAX, WLAN and X-band.
Shallow soil effects for contrasting peak ground accelerations at nearby strong-motion stations during the 2017, Mj 5.2, southern Akita Prefecture earthquake

On September 8, 2017, an earthquake of Mj 5.2 occurred with the epicenter in southern Akita Prefecture, Japan, at 22:23 local time. According to the Japan Meteorological Agency, the focal depth was 9 km. Many strong-motion stations of K-NET and KiK-net recorded ground motions from the earthquake. The maximum horizontal vector peak ground acceleration (PGA) of approximately 136 cm/s2 was recorded at one of the KiK-net stations at an epicentral distance of about 8 km. However, despite being 37 km and 53 km far from the epicenter, two stations recorded PGAs of approximately 126 and 113 cm/s2, respectively, similar to that near the epicenter. Even though these PGAs are not rare, we found that the PGAs at the two sites strongly deviated from the median values suggested by a ground motion prediction equation (GMPE), while the nearby sites generally followed the GMPE. Available velocity models showed that shallow shear wave velocities, especially in the top 5 m, were lower (i.e., the soils were softer) at the two sites compared to those at their nearest neighboring sites. We compared the ratios of the PGAs and peak ground velocities (PGVs) at the two sites with respect to their neighboring sites for many earthquakes covering a wide range of magnitudes and azimuths. We found that the PGAs and PGVs at the two sites were systematically larger than those at the adjacent sites. Linear theoretical site amplifications using the available soil models gave peak frequencies around 6-8 Hz at the larger PGA sites. Bandpass-filtered records showed significantly larger PGAs around these frequencies at the larger PGA sites. The above results showed that local site condition is one of the major contributing factors to induce large PGAs. Furthermore, softer sites experience more substantial nonlinear site amplification than the stiffer sites when input motions exceed some threshold PGAs. This latter effect means that the softer sites can produce a variety of ground motion spectra. Nevertheless, the degree of damage to built structures depends on several factors, including the design and quality of construction. We expect that this study contributes to developing improved microzonation maps for earthquake disaster mitigation.
Secrecy Energy-Efficient UAV Communication via Trajectory Design and Power Control

This paper investigates the problem of maximizing the secrecy energy efficiency (SEE) for unmanned aerial vehicle- (UAV-) to-ground wireless communication system, in which a fixed-wing UAV tries to transmit covert information to a terrestrial legitimate destination receiver with multiple terrestrial eavesdroppers. In particular, we intend to maximize the worst-case SEE of UAV by jointly optimizing UAV’s flight trajectory and transmit power over a finite flight period. However, the formulated problem is challenging to solve because of its large-scale nonconvexity. For efficiently solving this problem, we first decouple the above optimization problem into two subproblems and then propose an alternating iterative algorithm by adopting block coordinate descent method and Dinkelbach’s algorithm as well as successive convex approximation technique to seek a suboptimal solution. For the sake of performance comparison, two benchmark schemes, the secrecy rate maximization (SRM) scheme and constrained energy minimization (CEM) scheme are considered to obtain more useful insights. Finally, simulation results are executed to verify that our proposed SEE maximization (SEEM) algorithm is superior to two benchmark schemes for the UAV-ground communication system.
Essential oil analysis and biological activities of the aerial parts of Zygophyllum eichwaldii C. A. Mey., a native plant from Iran

is a medicinal plant from Zygophyllaceae family. This of 27 genera and 285 species. Objective: The present study was performed to evaluate the chemical composition of the essential oil of Z. eichwaldii and evaluation of biological activities of its extracts . Methods: Essential oils extraction of Z. eichwaldii aerial parts was performed by three different procedures and its chemical composition were evaluated by GC and GC-MS analyses. Evaluation of the biological activities was carried out by spectrophotometric methods. Results: GC-MS analysis showed menthol, thymol and palmitic acid as major components of the plant essential oils. In biological activity evaluation, while methanol extract showed moderate to week potency in antioxidant assessments, the ethyl acetate fraction was strong in these tests (IC 50 = 178.63 µg/ml in DPPH assay and 70.52 % inhibition in β-carotene/linoleic acid tests). This fraction also showed significant phenol, flavonoid and tannin contents (99.83, 118.29 and 188.05 μg/mg, respectively). Also, plant extracts exhibited considerable antimicrobial activities against most selected bacteria. Conclusion: Significant amount of phenol, flavonoid and tannin compounds in the ethyl acetate fraction and high antimicrobial activity against most bacterial strains, candidates this plant as a good case for further studies in this respect.
Generalization ability of Extreme Learning Machine using different Sample Selection Methods

The recent explosion of data has triggered the need of data reduction for completing the effective data mining task in the process of knowledge discovery in databases (KDD). The process of instance selection (IS) plays a significant role for data reduction by eliminating the redundant, noisy, unreliable and irrelevant instances, which, in-turn reduces the computational resources, and helps to increase the capabilities and generalization abilities of the learning models. This manuscript expounds the concept and functionalities of seven different instance selection techniques (i.e., ENN, AllKNN, MENN, ENNTh, Mul- tiEdit, NCNEdit, and RNG), and also evaluates their effectiveness by using single layer feed-forward neural network (SLFN), which is trained with extreme learning machine (ELM). Unlike traditional neural network, ELM randomly chooses the weights and biases of hidden layer nodes and analytically determines the weights of output layer node. The generalization ability of ELM is analyzed by using both original and reduced datasets. Experiment results depict that ELM provides better generalization with these IS methods.
Design and simulation of cascaded H-bridge multilevel inverter with energy storage

Stand-alone power system provides a solution for the user in rural areas that are disconnected from the utility grid which requires power electronics device for the power conversion. This work proposes a design of 5-level cascaded H-bridge inverter with energy storage to realize DC-AC power conversion for such system. The DC-DC bidirectional converter is designed to control the charging and discharging of current into/from the battery during the buck and boost mode of operation. At the DC side, dual-loop control strategy using PI controllers is designed to control the current and voltage. The inner loop current controller controls the recharging/discharging of current for the battery, while the outer voltage controller controls the DC link voltage at 200 V for each of the H-bridge unit. At the AC side, multiple feedback loop control strategy regulates the inverter output voltage at 240 Vrms under various load change. The modelling and design of the system is implemented under Matlab Simulink environment. From the results, the battery storage unit works well with the DC link voltage to achieve a balance power transfer within the system between the PV source, load and battery storage under variation of PV power and loading condition.
Analysis of Academic Cooperation Network for Returnee Faculty Members to Realize Value from the Perspective of Economics

Drawing on theories of social network and knowledge absorption, this paper examines the direct influence of returnee faculty members (RFMs) over college research performance (CRP) from three aspects, namely, the intensity of cooperative relationship (ICR), research influence (RI), and acquisition capability of heterogeneous knowledge (ACHK). In addition, the authors tested the regulating effect of ICR. The results show that RI of RFMs has a significant positive effect on CRP, ACHK has no significant effect on CRP, and ICR has a significant negative effect and a major regulating effect on CRP.
Maize productivity analysis in response to climate change under different nitrogen management strategies

The evidence of climate change is ubiquitous with an increase in temperature and CO2 concentration, changing precipitation patterns, increased number and severity of climate-related natural disasters, such as heat waves, droughts, severe storms, cyclones, and flooding (Anonymous, 2020). Since agriculture is heavily dependent on weather and climate, the climate extremes may interrupt crop growth, irrigation patterns, water use efficiency, soil health, and its biodiversity, which leads to a reduction in food production and thus, poses threats to food security. The global mean temperature has increased by 0.8°C since 1850s. It is projected to increase by 2 to 7°C at the end of the century (Allison et al., 2009). The atmosphere’s CO2 concentration has risen from 284 to 412 ppm from 1832 to 2020. The CO2 is expected to increase to 798 ppm by the end of the century (Tans and Keeling, 2014). The rising temperature and CO2 concentration could significantly affect crop production in different regions of the world. Globally, the range of yield changes under different climatic scenarios for wheat, rice, maize, and soybean are -6.9 to 22.4 per cent, -3.3 to -10.8 per cent, -8.6 to -27.8 per cent, and -3.6 to -11.6 per cent, respectively. On average, 1.00C increase in global mean temperature would reduce global production of wheat by 6.0, rice by 3.2, and maize by 7.4 and soybean by 3.1 per cent (Zhao et al., 2017).
Sperm subpopulations and quality in fractions obtained after single layer centrifugation in fresh normospermic ram samples

Single layer centrifugation (SLC) technique has been developed to select the best sperm population in the ejaculate in order to increase the fertilization rates by artificial insemination or in vitro fertilization. Normospermic ram semen samples containing 800 and 3,000 × 10 sperms/ml (C800 and C3000, respectively) were processed by SLC. Three sperm fractions were separated in each sample following silica-coloidal sperm centrifugation and sperm yield, quality and subpopulations were analyzed in each one. In C800 group, the sperm recovery rate did not vary in any studied fraction, but when samples were highly concentrated (C3000) the top fraction (F1) contained significantly higher spermatozoa than bottom fraction (F3). Also, it was observed that F1 in C3000 had got a significantly higher percentage of spermatozoa (53.2 %) than in C800, while the quantity of spermatozoa recovered in fraction 2 was lower (25.2 % vs 45.4 %). Based on the sperm motility parameters, three sperm subpopulations were identified: SP1, low velocity spermatozoa showing no progressive movement (19.1 %); SP2, rapid and progressive spermatozoa (43.7 %); and SP3, rapid spermatozoa but non-linear movement Rev Mex Cienc Pecu 2021;12(2):386-401 387 (37.2 %). While SLC has been implemented for sperm separation in suboptimal and/or low concentrated sperm samples, this trial demonstrates that SLC is not efficient to separate different sperm populations in normospermic ram sperm samples containing high concentrations of spermatozoa.