Miracle-dz/UniFAR-FTUs huggingface dataset:
Customized shape optimization of switched reluctance motor using B-Splines

Purpose This study aims to design the rotor geometry of switched reluctance motor (SRM) in a completely flexible way. In the proposed method, there is no default geometry for the rotor. The initial geometry of the rotor can start from a circle or any other shape and depending on the required performance takes the final shape during the optimal design. In this way, the best performance, possible with geometric design, can be achieved. Design/methodology/approach The rotor boundary of a 4/2 SRM is defined by a few B-splines. Some control points are located around the rotor and changing their locations causes customized changes in the rotor boundary. Locations of these points are defined as design variables. A 2-D finite element analysis using MATLAB/PDE is applied to the SRM model and sensitivity analysis is used to optimization design by means of minimizing of objective function. Findings The proposed method has many more capabilities for matching different objective functions. For the suggested objective function, while the conventional rotor torque profile difference with the desired torque profile reaches 40%, this difference for B-spline rotor is about 17%. Experimental results from a prototype motor have a close agreement with analysis results. Originality/value The B-splines have been used to design machines and electromagnetic devices. However, this method is used for the first time in design of the whole rotor of a SRM.
Evaluating the robustness of self‐consolidating concrete: An approach to the mix design procedure

This paper aimed to develop a method to analyze and rank self‐consolidating concrete (SCC) according to its robustness, considering isolated and simultaneous variations in its main components, like water (±6%) and cement content (ΔC±), in three matrices with binder to aggregate ratio (rich, intermediate and poor). In the experimental campaign, only water variations (±6%) were considered, and the cement content variations were considered in the analytical method. The method regarded the behavior of SCC in fresh and hardened states and turned out to be potentially useful to the academic community and the industry. The simple additive weighting method was used for that reason, which is probably the most adopted among methods for decisions with multiple variables due to its simplicity. Among the families studied, the poor mixture presented the lowest robustness with variation in water content due to the higher initial w/c ratio. However, for the condition ΔC±, the poor mixture achieved the second‐best robustness index. The rich mixture behaved differently as it was ranked second for ±6% of water and the worst for ΔC± due to slump‐flow and segregation results. The intermediate matrix presented the highest robustness in both conditions analyzed, water (±6%), and cement content (ΔC±).
Ten-year estimation of Oriental beech (Fagus orientalis Lipsky) volume increment in natural forests: a comparison of an artificial neural networks model, multiple linear regression and actual increment

Determining forest volume increment, the potential of wood production in natural forests, is a complex issue but is of fundamental importance to sustainable forest management. Determining potential volume increment through growth and yield models is necessary for proper management and future prediction of forest characteristics (diameter, height, volume, etc.). Various methods have been used to determine the productive capacity and amount of acceptable harvest in a forest, and each has advantages and disadvantages. One of these methods involves the artificial neural network techniques, which can be effective in natural resource management due to its flexibility and potentially high accuracy in prediction. This research was conducted in the Ramsar forests of the Mazandaran Province of Iran. Volume increment was estimated using both an artificial neural network and regression methods, and these were directly compared with the actual increment of 20 one-hectare permanent sample plots. A sensitivity analysis for inputs was employed to determine which had the most effect in predicting increment. The actual average annual volume increment of beech was 4.52 m3ha−1 yr−1, the increment was predicted to be 4.35 and 4.02 m3ha−1 yr−1 through the best models developed using an artificial neural network and using regression, respectively. The results showed that an estimate of increment can be predicted relatively well using the artificial neural network method, and that the artificial neural network method is able to estimate the increment with higher accuracy than traditional regression models. The sensitivity analysis showed that the standing volume at the beginning of the measurement period and the diameter of trees had the greatest impact on the variation of volume increment.
Validation of pure rotational Raman temperature data from the Raman Lidar for Meteorological Observations (RALMO) at Payerne

Abstract. The Raman Lidar for Meteorological Observations (RALMO) is operated at the MeteoSwiss station of Payerne (Switzerland) and provides, amongst other products, continuous measurements of temperature since 2010. The temperature profiles are retrieved from the pure rotational Raman (PRR) signals detected around the 355 nm Cabannes line. The transmitter and receiver systems of RALMO are described in detail, and the reception and acquisition units of the PRR channels are thoroughly characterized. The FastCom P7888 card used to acquire the PRR signal, the calculation of the dead time and the desaturation procedure are also presented. The temperature profiles retrieved from RALMO PRR data during the period going from July 2017 to the end of December 2018 have been validated against two reference operational radiosounding systems (ORSs) co-located with RALMO, i.e. the Meteolabor SRS-C50 and the Vaisala RS41. The ORSs have also served to perform the calibration of the RALMO temperature during the validation period. The maximum bias ( ΔTmax ), mean bias ( μ ) and mean standard deviation ( σ ) of RALMO temperature Tral with respect to the reference ORS, Tors , are used to characterize the accuracy and precision of Tral along the troposphere. The daytime statistics provide information essentially about the lower troposphere due to lower signal-to-noise ratio. The ΔTmax , μ and σ of the differences Δ T = T ral - T ors are, respectively, 0.28, 0.02±0.1 and 0.62±0.03 K. The nighttime statistics provide information for the entire troposphere and yield ΔTmax=0.29 K, μ = 0.05 ± 0.34 K and σ = 0.66 ± 0.06 K. The small ΔTmax , μ and σ values obtained for both daytime and nighttime comparisons indicate the high stability of RALMO that has been calibrated only seven times over 18 months. The retrieval method can correct for the largest sources of correlated and uncorrelated errors, e.g. signal noise, dead time of the acquisition system and solar background. Especially the solar radiation (scattered into the field of view from the zenith angle Φ ) affects the quality of PRR signals and represents a source of systematic error for the retrieved temperature. An imperfect subtraction of the background from the daytime PRR profiles induces a bias of up to 2 K at all heights. An empirical correction f(Φ) ranging from 0.99 to 1 has therefore been applied to the mean background of the PRR signals to remove the bias. The correction function f(Φ) has been validated against the numerical weather prediction model COSMO (Consortium for Small-scale Modelling), suggesting that f(Φ) does not introduce any additional source of systematic or random error to Tral . A seasonality study has been performed to help with understanding if the overall daytime and nighttime zero bias hides seasonal non-zero biases that cancel out when combined in the full dataset.
Genetic diversity and SSR markers development of ancient Camellia sinensis in Sandu County of Guizhou Province

Background: The genetic abundance of ancient tea germplasm has been preserved in the long evolution process, which provides valuable resources for the protection and breed selection of ancient tea germplasm. However, the limited studies related to the genetic diversity of ancient tea germplasm restrict protection and breed selection. Therefore, the genetic diversity of ancient tea germplasm in Sandu county of Guizhou Province was explored in this study. II.Methods and Results: The genetic diversity was analyzed using phenotypes and SSR markers. The ranges for the variation coefficients of the six quantitative and seven qualitative characters were 17.76%-60.37% and 18.58%-50.64%, respectively. The ranges of diversity indices of the six quantitative and seven qualitative characters were 1.72-2.74 and 0.55-0.84, respectively. Ninety-six bands were amplified using 15 pairs of SSR primers from the 145 samples, and the average polymorphism information index was 0.66. The analysis revealed that the average values of Nei’s genetic diversity index (H) and the Shannon information index (I) are 0.26 and 0.41, respectively. Further, a genetic similarity coefficient of 0.734 shown by UPGMA dendrogram classified the 145 samples decreased into four groups. III.Conclusions: This study revealed the rich phenotypic variation and high molecular genetic diversity and the genetic diversity of the arbor is higher than that of the shrub of the ancient tea germplasm in Sandu of Guizhou province. Thus, this study not only provides a theoretical basis for the protection and breed selection but also promotes further research of ancient tea germplasm.
Safety and feasibility of a factory-calibrated continuous glucose monitoring system in term and near-term infants at risk of hypoglycemia

Objective Hypoglycemia increases the risk of adverse neurological outcomes in neonates. Adequate glucose monitoring requires repetitive and painful blood sampling. We aimed to evaluate the feasibility and accuracy of a continuous glucose monitoring system (CGMS) using factory-calibrated sensors to improve glucose monitoring and decrease the frequency of blood samples in neonates. Material and Methods A methodological study was conducted to investigate a correlation of CGMS values with blood glucose measurements. Results Factory-calibrated CGMS sensors were placed on 21 infants at risk of hypoglycemia after delivery. CGMS values were compared with blood glucose concentrations. Thirty-seven pairs of CGMS and blood glucose values were obtained. There was a good correlation between CGMS and blood glucose values (R=0.67, p<0.01) with a mean difference (2 standard deviations) of 9.78 (−24.68 to 44.25) mg/dL. The mean differences at <3 hours and ≥3 hours after sensor placement were 17.35 (−4.54 to 39.21) mg/dL and 0.88 (−37.62 to 39.38) mg/dL, respectively. CGMS values were significantly higher than blood glucose concentration at <3 hours after sensor placement (p<0.01), whereas no significant differences in glucose values were observed between the CGMS and blood glucose values at ≥3 hours after sensor placement (p=0.852). Conclusion The factory-calibrated CGMS was a safe and feasible modality for glucose monitoring. However, it has a tendency to overestimate the blood glucose concentrations. Therefore, this system should be used cautiously for neonates at risk of hypoglycemia, especially within 3 hours after sensor placement.
In Vitro Characterization of Cell Surface Properties of 14 Vaginal Lactobacillus Strains as Potential Probiotics

Probiotics are live microorganisms which when administered in adequate amounts confer a health benefit on the host. Human-origin Lactobacillus is a preferable source of probiotic bacteria. This study screened 14 vaginal Lactobacillus strains as probiotic candidates by investigating probiotic-related cell surface characteristics including cell surface hydrophobicity (CSH), Lewis acidity/basicity, autoaggregation, and biofilm formation. Moderate to high CSH and autoaggregation, high basicity and low acidity were prevalent in the 14 tested strains. Biofilm formation varied in a large range among the 14 tested strains. CSH showed a high correlation with Lewis acidity and autoaggregation, while Lewis acidity was highly correlated with autoaggregation and biofilm formation. Four strains were selected as promising probiotic strains. This study was the first one to compare antibiotic sensitivity between biofilm-forming cells and planktonic cells of Lactobacillus species, and found that biofilm-forming cells of a L. fermentum strain had a significantly higher survival rate than planktonic cells in cefotaxime, cefmetazole and tetracycline, but were as sensitive to oxacillin and ampicillin as planktonic cells were.
Toward high‐resolution agronomic soil information and management zones delineated by ground‐based electromagnetic induction and aerial drone data

Detailed knowledge of the intra‐field variability of soil properties and crop characteristics is indispensable for the establishment of sustainable precision agriculture. We present an approach that combines ground‐based agrogeophysical soil and aerial crop data to delineate field‐specific management zones that we interpret with soil attribute measurements of texture, bulk density, and soil moisture, as well as yield and nitrate residue in the soil after potato (Solanum tuberosum L.) cultivation. To delineate the management zones, we use aerial drone‐based normalized difference vegetation index (NDVI), spatial electromagnetic induction (EMI) soil scanning, and the EMI–NDVI data combination as input in a machine learning clustering technique. We tested this approach in three successive years on six agricultural fields (two per year). The field‐scale EMI data included spatial soil information of the upper 0–50 cm, to approximately match the soil depth sampled for attribute measurements. The NDVI measurements over the growing season provide information on crop development. The management zones delineated from EMI data outperformed the management zones derived from NDVI in terms of spatial coherence and showed differences in properties relevant for agricultural management: texture, soil moisture deficit, yield, and nitrate residue. The combined EMI–NDVI analysis provided no extra benefit. This underpins the importance of including spatially distributed soil information in crop data interpretation, while emphasizing that high‐resolution soil information is essential for variable rate applications and agronomic modeling.
Determinants of digital technology adoption in supply chain. An exploratory analysis

ABSTRACT This paper is aimed at identifying the main patterns related to the application of new Digital Supply Chain Technologies that through the Industry 4.0 paradigm, are redefining supply chain organisations. To this end, a set of DSC initiatives has been analysed via an Analysis of Variance (ANOVA) to understand the influence of several social and economical factors on the implementation of DSC solutions. Results show that the time factor, the Gross Domestic Product per capita, the amount of foreign investment, and the expenditure in Research and Development are significant drivers of DSC technologies. In particular, Big Data are associated with a higher economic effort than Blockchain, although these two technologies, together with Augmented Reality and Artificial Intelligence, usually characterise most recent implementations. The present work might foster research about the contextual factors affecting the DSC diffusion it could assist both practitioners and policymakers in defining appropriate DSC strategies.
“This New Chapter of Life”: Content Analysis of Facebook Posts After Traumatic Brachial Plexus Injury

Background: After traumatic brachial plexus injuries (BPI), the sudden loss of physical function is often accompanied by psychological distress. Given the complex nature and relative infrequency of the injury, BPI patients will often use online resources for information about their injury as well as emotional support. Questions/Purpose: Recognizing the influence of social media, we sought to search a popular social media platform to identify challenges faced by BPI patients and strategies used to overcome these challenges. Methods: We searched “traumatic brachial plexus injury” on Facebook and selected the 2 most popular BPI support groups. We collected posts regarding traumatic BPI from November 1, 2018 through November 1, 2019. We performed inductive and deductive thematic analysis of the posts to identify recurring topics, knowledge gaps, and peer interaction dynamics. Results: We analyzed 7694 posts from the 2 Facebook support groups. The following themes emerged: (1) BPI patients express discontent regarding the inability to use their arm and the slow or stagnant pace of recovery; (2) BPI patients are frustrated over their inability to retain their preinjury livelihood; and (3) BPI patients emphasize that acceptance and moving on are key components of adjustment to their condition. Some patients described the role of limb amputation in achieving these goals. Conclusions: Our analysis demonstrates the areas in which BPI patients are in need of emotional support. Adjustment to BPI might be facilitated through multidisciplinary care that addresses emotional aspects of recovery and emphasizes self-management skills, in addition to the traditional focus on physical function.
Correlation between disability measure and Black Hole (T1 hypointense lesion) lesion load in brain magnetic resonance imaging of patients with multiple sclerosis: Protocol for a systematic review and meta-analysis

Rationale: As the role of neurodegeneration in the pathophysiology of multiple sclerosis (MS) has become more prominent, the formation and evolution of chronic or persistent T1-hypointense lesions (Black Holes) have been used as markers of axonal loss and neuronal destruction to measure disease activity. However, findings regarding this subject are controversial. In this study we aim to clarify the level of importance of T1 hypointense lesions for estimating the prognosis of patients.Objectives: To evaluate the correlation between T1 hypointensities (Black holes) lesion load (lesion mean volume) on brain MRI with disability level of patients with Relapsing-Remitting Multiple Sclerosis (RRMS) or Secondary-Progressive Multiple Sclerosis (SPMS). Data sources: We will search MEDLINE (through PubMed), Embase, CENTRAL, Science Citation Index – Expanded (Web of Science), and Conference Proceedings Citation Index – Science (Web of Science). We won’t consider any timeframe, language, or geographical restrictions.Methods: Standard systematic review protocol methodology is employed. Eligibility criteria is reported in line with PICOTS system. Population is limited to adult patients diagnosed with RRMS or SPMS, based on the McDonald criteria. Index (prognostic factor) of interest will be T1 hypointense (black hole) lesion mean volume (lesion load) on brain Magnetic Resonance Imaging (MRI). There will be no comparators. Outcome of interest will be the disability measure using Expanded Disability Status Scale (EDSS). For the timing domain, we will include studies only if the outcome was measured at the same time MRI was performed (or with a very close time interval between). Inpatient and outpatient settings will both be included. All included studies will be assessed for the risk of bias using a tailored version of the Quality In Prognosis Studies (QUIPS) tool. Extracted correlation coefficients will be converted to the Fisher’s z scale and a meta-analysis will be performed on the results. We will then convert back the results to correlation coefficients again for the sake of presentation. For the purpose of assessing heterogeneity we will use prediction intervals. If feasible, we will also try to perform subgroup and sensitivity analyses. We will also evaluate the publication bias using Funnel plots and assess the confidence in cumulative evidence using an adapted version of the GRADE for prognostic factor research.
بررسی پارامترهای هیدرودینامیکی در داخل یک روتور سانتریفیوژ گازی در حضور گازهای سبک هیدروژن فلوراید و هوا با روش‌های DSMC و تابع توزیع بولتزمن

معادله بولتزمن معادله‌ای بسیار مهم در علم فیزیک و دینامیک سیالات می‌باشدکه برخورد‌های دوتایی بین مولکول‌ها را توصیف می‌نماید. به دلیل غیر خطی بودن و پیچیدگی عبارت‌های انتگرال برخورد، استفاده مستقیم از معادله بولتزمن برای گاز‌های رقیق دشوار و پیچیده می‌باشد. یکی از روش های حل معادله بولتزمن روش شبیه سازی مستقیم مونت کارلو می‌باشد. از آنجائیکه فشار اغلب تجهیزات واحد‌های فرآیند غنی سازی کمتر از فشار اتمسفر می‌باشد، ممکن است در طی عملیات غنی سازی رطوبت هوا به دفعات و در مکان‌های مختلف زنجیره‌ها به لوله سیال نشت کند و طی واکنش با گاز هگزافلوراید اورانیوم سبب تولید رسوب بر روی سطوح داخلی روتور سانتریفیوژ و گاز هیدروژن فلوراید ‌گردد. در این تحقیق تاثیر غلظت و فشار کل داخل روتور سانتریفیوژ فرضی برای شرایط دو جزئی (97/0=ZUF6 و 03/0=ZHF)، (93/0=ZUF6 و 07/0=ZHF)، (9/0=ZUF6 و 1/0=ZHF)، (85/0=ZUF6 و 15/0=ZHF) و سه جزئی (9/0=ZUF6، 05/0=ZHF و 05/0=ZAir) و (8/0=ZUF6، 1/0=ZHF و 1/0=ZAir) مورد بررسی قرار گرفته است. نتایج با روش تحلیلی مورد مقایسه قرار گرفته است. نتایج نشان داد که افزایش میزان گاز سبک به همراه گاز UF6باعث کاهش فلاکس جرمی محوری می‌گردد.
Generation Y’s Perception of Servant Leadership and Job Satisfaction

Generation Y wants to know the reason for everything in their lives, they are curious and most importantly, their characteristic of questioning everything makes them stand out. At the same time, it is hard to influence their characteristic features such as their lack of social skills, little respect for authority, and low level of commitment to their employers when Generation X management tactics are used. The purpose of this study is to better understand Generation Y, to examine their relations with servant leadership practices, and to determine what effects they have on businesses. The field study was made at an established organized industrial zone (OIZ) dating back to 1963. This OIZ is built on an area bigger than 10 million m2 and is divided into 5 subzones. It is currently home to 53,500 employees, has a gross foreign trade volume of $7,200,000,000 and is located in the western Aegean Region of Turkey. The data for the study was collected from 248 participants and scales tested for validity and reliability in Turkish. A model was developed using the data and then it was tested using the confirmatory factor analysis method. The study used Structural Equation Model (SEM) to define the causal relationships between latent variables with a model in the analysis of the data and test its compliance. The result of the analysis reveals that dimensions of accountability and forgiveness from servant leadership practices have a statistically significant effect on personal success, whereas empowerment, accountability, and personal success dimensions have statistically significant effects on job satisfaction. Modesty dimension does not have a significant effect on the personal success and job satisfaction and the dimensions of accountability and forgiveness do not have a significant effect on job satisfaction. In addition, empowerment dimension does not have a meaningful effect on personal success. There is need for more studies to support the accuracy of the result for modesty dimension, since it seems like there is no effect on personal success and job satisfaction. This is a pioneer study since it is an empirical one looking at the application of the servant leadership theory on Generation Y employees.