Miracle-dz/UniFAR-FTUs huggingface dataset:
Speed Sensorless Model Predictive Current Control Based on Finite Position Set for PMSHM Drives

As an efficient control strategy, model predictive current control (MPCC) has rapid response and simple calculation. This article proposes an improved MPCC scheme for permanent-magnet synchronous hub motor (PMSHM) drives. The mentioned control scheme uses the parameter values at the last moment to obtain the back electromotive force (EMF) and utilizes the obtained back EMF to obtain the predicted current value at the next moment. In the actual application of the motor, to enhance the robustness of the control system, a sliding mode controller is used to replace the conventional proportional-integral (PI) speed loop, and a finite position phase-locked loop based on the dichotomy is added to achieve sensorless speed control and provide an accurate rotor position angle. To improve the steady-state performance, the method of duty cycle is introduced, and the null vector and the actual vector are used together in the same control cycle. The simulation and experimental results both show the effectiveness of the proposed MPCC scheme, and the steady-state performance of MPCC is greatly improved compared with traditional MPCC.
Prediction of Muscle Performance During Dynamic Repetitive Exercise

A method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.
MGMT Immunohistochemical Expression in Colorectal Carcinoma and its Correlation with Tumor Progression

BACKGROUND: There is an urgent need to identify predictive features and markers for progression and treatment of colorectal carcinoma (CRC). AIM: This study aimed to assess O-methylguanine DNA methyltransferase (MGMT) expression in CRC and to correlate with the clinico-pathological aspects of the tumor, also to evaluate the relationship between different histopathologic parameters and tumor progression. MATERIALS AND METHODS: The study was carried on 70 colectomy using formalin fixed paraffin embedded tumor tissue not subjected to chemo-radiotherapy nor with missing data. Specimens were collected from the Department of Pathology of Kasr El-Aini Hospital, Faculty of Medicine, Cairo University, during the period between (March 2017 and May 2018). Immunohistochemistry was used to detect MGMT expression and clinico-pathologic aspects as well as to assess tumor budding, type of desmoplastic reaction (DR), inflammatory lymphocytic milieu, pattern of invasive front and necrosis, and then correlated with MGMT expression and tumor progression, using parametric and non-parametric statistical methods. RESULTS: MGMT loss of expression was detected in 42.9% of CRC cases. MGMT expression status was significantly correlated with tumor stage and metastatic status (p < 0.05), while it was not correlated with other clinicopathologic features, (p > 0.05). DR, tumor budding, stromal tumor infiltrating lymphocytes (TIL-S), and necrosis were correlated with tumor stage (p < 0.05). DR correlated with tumor budding (p < 0.05). Both types of TIL and Crohn’slike lymphoid reaction showed a mutual correlation (p < 0.05). CONCLUSION: MGMT high expression and histopathologic parameters as DR, tumor budding, inflammatory lymphocytic milieu, and necrosis could be correlated with CRC progression. Edited by: Sinisa Stojanoski Citation: Ahmed M, Bayoumi B, Abdallah S, Elserafy M. MGMT Immunohistochemical Expression in Colorectal Carcinoma and its Correlation with Tumor Progression. Open Access Maced J Med Sci. 2021 Feb 05; 9(A):244-251. https://doi.org/10.3889/oamjms.2021. 5879
Optimizing the growth-associated β-galactosidase production by probiotic Lactobacillus reuteri B-14171: experimental design, culture medium volume increase, and cell growth modeling

This study reports an optimized culture medium in submerged cultivation to produce β-galactosidase by Lactobacillus reuteri. Four culture medium parameters were optimized (pH, lactose, casein, and inactive beer yeast), and the effect of different volumes of the optimized culture medium on the bioprocess was evaluated regarding β-galactosidase production. Different kinetic models were applied to predict enzymatic production as a function of biomass and substrate. It is the first time that both the effect of increasing the culture medium volume and mathematical modeling on the β-galactosidase production by L. reuteri have been studied. Besides, different bioprocess parameters were calculated based on the experimental data to verify the feasibility of enzymatic production. The achieved enzymatic activity for the optimized culture medium (12.75 g L-1 lactose; 1.88 g L-1 casein; 1.65 g L-1 inactive beer yeast and pH 5.61) resulted in an increase of 4.74-fold compared to the initial activity. Three culture medium volumes (200, 800, and 3,200 mL) were evaluated, and no significant difference was observed on maximum and total productivities (Pm and Pp), as well as on the product formation yield on biomass (YP/X). The Logistic model resulted in a good fit to the experimental data for all tested volumes, and the modified Luedeking-Piret model provided a satisfactory prediction of the enzymatic activity. The optimized culture medium reported in this work is an outstanding alternative to produce β-galactosidase by L. reuteri, which is microbial growth-associated, and the production was not affected by increasing the culture medium volume.
The Effects of Psychological Capital and Internal Social Capital on Frontline Hotel Employees’ Adaptive Performance

This study examines the relationship between psychological capital, social capital, and adaptive performance in China’s lodging industry. Recent research has revealed that the production attributes of internal social capital can explain adaptive performance, and that psychological capital affects the relationship attributes of social capital. This raises the question of whether social capital might mediate between psychological capital and adaptive performance. Therefore, this study examined data from a sample of 304 hotel employees in China, using internal social capital as a mediating variable. The results confirmed that psychological capital has a significant positive impact on adaptive performance. Social capital also plays a mediating role partially between psychological capital and adaptive performance. The findings of this study contribute to the theoretical framework of psychological capital and adaptive performance and provide a new approach to human resource management in the lodging industry and other dynamically competitive service industries.
Marine Microalgae Contribution to Sustainable Development

The burning of fossil fuels is an unsustainable activity, which is leading to an increase in greenhouse gases (GHGs) emissions and related global warming. Among sustainable energy sources, microalgae represent a promising alternative to fossil fuel and contribute to the achievement of important Sustainable Development Goals (SDGs). In particular, the potential contribution of marine microalgae to sustainable development is large as, among other benefits, they represent a carbon negative energy source and may be applied in many coastal areas around the world. Despite this, significant economic and technological improvements are needed in order to make microalgae biofuels viable on a large scale. This review aims to explore how and to what extent third-generation biofuels (marine microalgae, but also the latest advances in freshwater microalgae) can benefit the realization of these SDGs. From this study we concluded that the production of large-scale marine microalgae biofuels is not yet feasible from the economic perspective at a large scale. However, the cultivation of microalgae in seawater holds great potential for increasing the small to medium viability of this biofuel source. The possibilities for improvement along with the contributions to sustainable development lay the groundwork for continuing to study and apply the potential of sustainable production of microalgae bioenergy.
On the Role of Low-Level Linguistic Tasks for Reading Time Prediction

It has been shown that complexity metrics, computed by a syntactic parser, is a predictor of human reading time, which is an approximation of human sentence comprehension difficulty. Nevertheless, parsers usually take as input sentences that have already been processed or even manually annotated. We propose to study a more realistic scenario, where the various processing levels (tokenization, PoS and morphology tagging, lemmatization, syntactic parsing, and sentence segmentation) are predicted incrementally from raw text. To this end, we propose a versatile modeling framework, we call the Reading Machine, that performs all such linguistic tasks and allows to incorporate cognitive constraints such as incrementally. We illustrate the behavior of this setting through a case study where we test the hypothesis that the complexity metrics computed at different processing levels predict human reading difficulty and that when cognitive constraints are applied to the machine (e.g., incrementality), it yields better predictions.
Study of Material Compatibility for a Thermal Energy Storage System with Phase Change Material

The suitability of stainless steel 316L and Inconel 625 for use in a latent heat thermal energy storage (TES) system was investigated. A NaCl–NaF eutectic mixture with a melting temperature of 680 °C was used as the phase change material (PCM). Containers were filled with the PCM prior to heating to 750 °C, then examined after 100 and 2500 h of high-temperature exposure by analyzing the material surface and cross-section areas. A small amount of corrosion was present in both samples after 100 h. Neither sample suffered significant damage after 2500 h. The undesirable inter-granular grain boundary attack found in SS316L samples was in the order of 1–2 µm in depth. On Inconel 625 sample surface, an oxide complex formed, resisting material dissolution into the PCM. The surface morphology of tested samples remained largely unchanged after 2500 h, but the corrosion pattern changed from an initially localized corrosion penetration to a more uniform type. After 2500 h, the corrosion depth of Inconel 625 remained at roughly 1–2 µm, indicating that the corrosion rate decelerated. Both materials demonstrated good compatibility with the chosen NaF–NaCl eutectic salt, but the low corrosion activity in Inconel 625 samples shows a performance advantage for long term operation.
Computer Vision Syndrome in Medical Students during a Period of Exclusive Online Lecture Classes in Durgapur, West Bengal - A Cross-Sectional Study

BACKGROUND Computer has become an indispensable tool in the modern system of education and training. Health hazard viz. computer vision syndrome (CVS) associated with overuse of computer has been widely studied by different authors. Few studies have underscored the high prevalence of this condition among medical students. Present study has been conducted to find the prevalence of CVS, associated risk factors and to understand the level of awareness about the condition among undergraduate medical students during a period of exclusive online computerbased lecture classes. METHODS A descriptive cross-sectional study was conducted with 310 respondents among undergraduate medical students at IQ City Medical College, Durgapur, West Bengal from June 2020 to September 2020. The students were surveyed with pretested and structured questionnaire for various CVS related symptoms and ergonomic principles adopted by them. Data was collected and analysed. Chisquare test was performed to assess the statistical significance. RESULTS Prevalence of CVS in the study was found to be 58.38 %. Majority of students affected were females (69.5 %). Those using the computer for 2 – 4 hours a day were affected the most (66.5 %). The ergonomic factors that were found to have strong association with CVS were viz. prolonged and continuous use of digital screen, viewing distance, level of the digital screen with respect to eyes and chair support to lower back. The most disturbing symptom following continuous computer use was found to be headache (18.38 %), followed by eye strain (13.87 %). CONCLUSIONS The present study was conducted at a period when computer dependency among the students was high. Though some of the earlier studies have reported much higher prevalence of CVS among students, the present study has revealed a prevalence of 58.38 %. This was possibly due to high level of awareness (78.06 %) among medical students as revealed by the study. The study has also showed statistical significance between various ergonomic factors and development of CVS. KEYWORDS Computer Vision Syndrome, Ergonomics, Undergraduate Medical Students, Awareness
Naive, connected, and counselor tween girl identity groups: Consumption practices and social identity constructions within consumer culture

This research identifies the relationship between consumption practices and the construction of social identity among tweens in a Brazilian context. Using consumer culture theory and social identity theory, we employed 80 h of observation, 9 interviews, and projective techniques with fifteen girls. Three social identity groups were acknowledged: naive, connected, and counselors. These groups revealed different identity projects, such as the integration and maintenance within the social group of current belonging, the access to the social group with the greater distinctions, the generation of differentiable and positive distinctions (both intra- and intergroups), and the expression and consolidation of identity and its respective consumption practices. This research contributes to the consumption literature that relates to consumer identity projects. The findings reveal a current resignification of girlhood and exposes tweens’ consumption practices as a direct mechanism of the expression and construction of their social identities. These are mechanisms of social identity construction as mediated by group relations through the processes of access, maintenance, integration, differentiation, and distinction.
Approximation algorithms for Steiner forest: An experimental study

In the Steiner forest problem, we are given a set of terminal pairs and need to find the minimum cost subgraph that connects each of the terminal pairs together. Motivated by the recent work on greedy approximation algorithms for the Steiner forest, we provide efficient implementations of existing approximation algorithms and conduct a thorough experimental study to characterize their performance. We consider several approximation algorithms: the influential primal‐dual 2‐approximation algorithm due to Agrawal, Klein, and Ravi, the greedy algorithm due to Gupta and Kumar, and a randomized algorithm based on probabilistic approximation by tree metrics. We also consider the simplest heuristic greedy algorithm for the problem, which picks the closest unconnected pair of terminals and connects it using the shortest path between the terminals in the current graph. To characterize the performance of the algorithms, we created a new library with more than one thousand Steiner forest problem instances and conducted an extensive experimental analysis on those instances. Our analysis reveals that for the majority of instances the primal‐dual algorithm is the fastest among all the algorithms considered here, and obtains solutions that are very close to the optimal solutions obtained by solving the integer program formulation of the problem.
Treating Human Hepatocyte-like C 3 A Cells with Estrogen , Thyroid Hormone , and Insulin Reduced the Ability of PCSK 9 to Form Complexes with the LDL Receptor

Hypercholesterolemia is the leading cause of cardiovascular diseases, especially coronary artery disease [1,2]. Hypercholesterolemia is usually caused by mutations in genes encoding the low density lipoprotein (LDL) receptor, apolipoprotein B (Apo B), and proprotein convertase subtilisin/kexin type 9 (PCSK9) [1,3-5]. The LDL receptor is strategically located at the cell surface where it can bind LDL particles and transports it into the cell through receptor-mediated endocytosis [6-8]. In the endosome, LDL is released from the receptor triggered by the low pH; the LDL receptor returns to the cell surface to continue the process [6-8]. PCSK9 regulates plasma LDL levels by binding to and promoting intracellular degradation of LDL receptors [9-11]. The increased degradation of LDL receptor due to PCSK9 leads to reduced clearance of LDL, which accumulates in the plasma [911]. A direct correlation between plasma PCSK9 levels and LDL-cholesterol has been demonstrated [10,12-15].
Stochastic Optimization for Integration of Renewable Energy Technologies in District Energy Systems for Cost-Effective Use

Stochastic optimization of a district energy system (DES) is investigated with renewable energy systems integration and uncertainty analysis to meet all three major types of energy consumption: electricity, heating, and cooling. A district of buildings on the campus of the University of Utah is used as a case study for the analysis. The proposed DES incorporates solar photovoltaics (PV) and wind turbines for power generation along with using the existing electrical grid. A combined heat and power (CHP) system provides the DES with power generation and thermal energy for heating. Natural gas boilers supply the remaining heating demand and electricity is used to run all of the cooling equipment. A Monte Carlo study is used to analyze the stochastic power generation from the renewable energy resources in the DES. The optimization of the DES is performed with the Particle Swarm Optimization (PSO) algorithm based on a day-ahead model. The objective of the optimization is to minimize the operating cost of the DES. The results of the study suggest that the proposed DES can achieve operating cost reductions (approximately 10% reduction with respect to the current system). The uncertainty of energy loads and power generation from renewable energy resources heavily affects the operating cost. The statistical approach shows the potential to identify probable operating costs at different time periods, which can be useful for facility managers to evaluate the operating costs of their DES.
A Bee Colony Algorithm based Solver for Flow Shop Scheduling Problem

Flow Shop Scheduling (FSS) is scheduled to involve n jobs and m machines in the same process sequence, where each machine processes precisely one job in a certain period. In FSS, when a machine is doing work, other machines cannot do the same job simultaneously. The solution to this problem is the job sequence with minimal total processing time. Many algorithms can be used to determine the order in which the job is performed. In this paper, the algorithm used to solve the flow shop scheduling problem is the bee colony algorithm. The bee colony algorithm is an algorithm that applies the metaheuristic method and performs optimization according to the workings of the bee colony. To measure the performance of this algorithm, we conducted some experiments by using Taillard's Benchmark as problem instances. Based on experiments that have been carried out by changing the existing parameter values, the size of the bee population, the number of iterations, and the limit number of bees can affect the candidate solutions obtained. The limit is a control parameter for a bee when looking for new food sources. The more the number of bees, the more iterations, and the limit used, the better the final time of the sequence of work. The bee colony algorithm can reach the upper limit of the Taillard case in some cases in the number of machines 5 and 20 jobs. The more the number of machines and jobs to optimize, the worse the total processing time.
Characterization of Aiphanes aculeata fruit pulp and application in ice cream formulations

The characteristic color of the palm fruits Aiphanes aculeata, also known as Cariota-de-Espinho, suggests the presence of pigments such as carotenoids and anthocyanins, in addition these fruits present other compounds with health benefits such as minerals, vitamins and phenolics. However, there are no studies on the application of these fruits in food formulations since this palm tree is used only for urban landscaping. The present study aimed to characterize the Aiphanes aculeata pulp for proximate composition, physicochemical parameters, mineral contents, bioactive compounds, and antioxidant activity. Three ice cream formulations with the addition of different pulp concentrations were also produced, aimed to contribute to the technological and nutritional use of Aiphanes aculeata fruits. The choice of ice cream as the main investigation occurs due to the importance of functional ice creams to the balance of the physiological functions of the human organism that occurs through the ingestion of active and nutritional ingredients. Ice creams were characterized for overrun, melting behavior, color, and texture profile. The pulp presented representative minerals levels such as iron (49.82 ± 43.85 mg/100g) and zinc (96.07 ± 81.65 mg/100g). The total carotenoids level was significant, corresponding to 92.64 ± 0.83 μg/100g, with an emphasis on the betacarotene levels (56.94 ± 2.11 μg/100g). The different pulp concentrations used in the formulations influenced the characteristics of the ice cream, as it interacted positively with the ingredients until the concentration of 30% pulp. Therefore, the Aiphanes aculeata fruits showed potential for application in the food industry, in the manufacture of ice cream with high nutritional value.
Application of CO2-water-rock reaction transport simulation in NPs-CO2 flooding and storage

As a hot issue in geological engineering, CO2 flooding and sequestration still face many challenges. Injection of nanoparticles into CO2 can improve the injectability and effective reserves of CO2. However, the migration law of the mixed fluid of CO2 and nanoparticles (NPs-CO2) in the reservoir under the condition of chemical reaction is still unclear. Based on chemical reaction kinetics, a mass transfer model of NPs-CO2 nanofluid in reservoir is established by combining the micro-pore structure change of porous media under CO2-water-rock reactions condition and the migration law of NPs-CO2 fluid. The geochemical reaction process between CO2 and reservoir and the influence of heterogeneity caused by rock microstructure on the miscibility and migration of NPs-CO2 brine fluid are simulated. The results show that the CO2-water-rock reaction increases the heterogeneity of reservoir, and the porosity and permeability are rising as a whole; the increase of reservoir heterogeneity caused by chemical reaction can makes the migration of NPs-CO2 selective. The local accumulation of NPs-CO2 in the unconnected pores will weaken the original oil displacement efficiency to some extent; in the process of CO2 sequestration, the density difference between NPs-CO2 and formation water can not only promote the miscibility of NPs-CO2-brine fluid, but also inhibit the acid fluid under buoyancy. The upward diffusion is moved to the cover layer to prevent the chemical reaction of the rocks in the cap layer, so as ensuring the permanent storage of greenhouse gases.