Miracle-dz/UniFAR-FTUs huggingface dataset:
Alopecia Areata and Dry Eye

Background: There is paucity of studies reporting tear film changes and ocular surface pathologies in AA patients. Aim and Objectives: This study aims to evaluate anterior segment changes in alopecia areata patients and compare them with healthy individuals. Materials and methods: Total of 34 patients were enrolled for study with a mean age of 24.56±7.82 years. Schirmer’stest, Tear film Break Up Time (TBUT), Tear meniscus height and Optical surface disease Index (OSDI) Questionnaire were performed to assess tear film changes. Pachymetry, keratometry and slit examination to detect any corneal involvement was also done. Results: Asymptomatic punctate lenticular opacities were found in 12 (35.3%) cases and 2 (5.8%) controls. Mean values of schirmer test (in mm) was 18.59±10.15 in cases and 22.76±9.73 in controls with p=0.23 while mean values of TBUT( in seconds) was 9.59±5.49 in cases and 17.76±5.98 in controls with p=0.002. Dry eye was found in 15 (44.11%) cases and 6 (17.6%) controls with a p value 0.03, thus statistically significant. Conclusion: Alopecia areata strikes hair and Meibomian gland and spares out lacrimal gland.
Estimates of variance components for feedlot traits of the Simmentaler breed in South Africa

Breeding of beef cattle is changing, with more emphasis on efficiency of production. Feed cost is the highest expense, and reducing it has the potential to increase profitability. Common measures of efficiency are ratio traits such as feed conversion (feed consumed/weight gain) and feed efficiency (weight gain / feed consumed). Feed conversion ratio is commonly used in South Africa in an attempt to improve feed efficiency. These ratio traits are associated with growth rate. Selection for them would result in higher growth as a correlated response and might also increase the mature size of the cows and their maintenance cost. Thus, alternative efficiency traits such as residual feed intake and residual daily gain have been proposed. In this study, variance components, and genetic parameters for feedlot traits for the South African Simmentaler breed were estimated, with emphasis on the efficiency traits. The focus was to evaluate the use of residual feed intake as an alternative trait. The results indicate non-significant correlations between residual feed intake and body weight and growth traits, implying that residual feed intake should have little effect on the other traits. This is in contrast to the moderate to strong correlations of feed conversion ratio with the same traits. The study demonstrates that considerable genetic variation exists for residual feed intake, which can be exploited. Selection for residual feed intake can reduce the carbon footprint of beef due to the associated lower methane emissions.
Supply Chain of Pomelo Orange

The limitation number production of Pomelo Orange in Pangkep District is uncertainty in supply chain arragement. This research aims to analyze supply chain of Pomelo Orange in Padang Lampe and Punranga village, Ma’rang Sub-district, Pangkep District. Recearch design on farmer, merchant collector, retailer are chosen purpopsive sampling and home industry selected in total sampling. The analysis is qualitative analysis that descriptive identification from questionnaire, describe flow of the supply chain. The result of research show that there is the main perpetrators and perpetrators on supply chain Pomelo Orange. The flow of principal cultivators starts from the farmer until wholesalers and consumers there is also a flow of goods from the supporting actors to the main perpetrators. The flow of information is obtained from the main actors as well as the supporting actors. The flow of money starts from the consumer with the farmers and the main actors to the supporting actors. It was concluded that the supply chain of pomelo orange had the main perpetrators and supporters. The three flow of supply chain of pomelo orange is the flow of products, money, and information in research location looks good eventough the demand flow of products as much 17,86% unfulfilled.
EHES Working Paper | No. 219 | November 2021 Ireland in a Danish mirror: A microlevel comparison of the productivity of Danish and Irish creameries before the First World War

The relative success of the Danish and failure of the Irish dairy industries before the First World War is often contrasted given their competition for the lucrative British butter market. The traditional narrative implicitly assumes that Ireland failed because it was unsuccessful at adopting the cooperative institution, and that Irish cooperatives were not as efficient as their Danish counterparts, despite having been explicitly modelled on them. This assumption is, however, untested at the ‘firm’ level. We seek to rectify this through the analysis of a large microlevel database of creameries in both countries over the period 1898-1903. Using Stochastic Frontier Analysis (SFA), a standard methodology in modern productivity studies, we find no evidence for significant productivity differences on average, although there was a much larger variance in Ireland. This nuances the idea that the Irish were unable to cooperate successfully, although some creameries were certainly productivity laggards.
A statistical analysis of energy and power demand for the tractive purposes of an electric vehicle in urban traffic - an analysis of a short and long observation period

The article presents the results of a statistical dispersion analysis of an energy and power demand for tractive purposes of a battery electric vehicle. The authors compare data distribution for different values of an average speed in two approaches, namely a short and long period of observation. The short period of observation (generally around several hundred meters) results from a previously proposed macroscopic energy consumption model based on an average speed per road section. This approach yielded high values of standard deviation and coefficient of variation (the ratio between standard deviation and the mean) around 0.7-1.2. The long period of observation (about several kilometers long) is similar in length to standardized speed cycles used in testing a vehicle energy consumption and available range. The data were analysed to determine the impact of observation length on the energy and power demand variation. The analysis was based on a simulation of electric power and energy consumption performed with speed profiles data recorded in Poznan agglomeration.
Experiment on leader propagation characteristics of air gaps in UHVDC transmission towers under positive switching impulse voltages

Rapid developments in EHV/UHV transmission systems require a deeper understanding of the mechanism of long air gap discharge. Leader propagation is one of the main processes in long gap breakdown. In this paper, the leader propagation characteristics of real size ±800 kV UHVDC transmission tower gaps under positive switching impulse voltages (185/ 2290 μs) are investigated. An integrated observation platform consisting of an impulse voltage divider, a coaxial shunt, a high-speed video camera, and a set of integrated optical electric field sensors (IOES), is established. The waveforms of impulse voltage, discharge current, electric field variation at specific positions, and time-resolved photographs of discharge morphology are recorded. Axial leader velocity and the relationship between leader advancements and injected charge are obtained. The typical value of leader stable propagation velocity is 1.7-2.2 cm/μs, which varies slightly with the gap length and applied voltage amplitude. The leader velocity in the re-illumination process is much higher, and is seen as varying from 5 cm/μs to 30 cm/μs, with an average value around 10 cm/μs. The charge in leader channel per unit length is 20- 40 μC/m, which illustrates a near-direct proportion relationship between discharge current and leader velocity. The observed parameters are important for further simulation of the tower gap breakdown processes.
Offshore pipelines and ice gouge geohazards: Comparative performance assessment of decoupled structural and coupled continuum models

Offshore pipelines in ice environments may be subjected to unique geohazards such as seabed ice gouging. These events involve nonlinear processes including large deformations and strains, contact mechanics, and failure mechanisms. Current pipeline engineering design practice employs decoupled, structural finite element modelling procedures to assess system demand and capacity. The inherent error and uncertainty within this approach drives conservative engineered solutions. Physical modelling and continuum numerical simulation tools complement this engineering framework to improve confidence in predicted outcomes. The relative performance of engineering models, used in current practice, and numerical simulation tools, including structural and continuum finite element modelling procedures, to predict the deformation and strain response of a buried pipeline subjected to an ice gouge event is examined. Refinements to the numerical modeling procedures and establishment of a consistent and compatible reference .
High-Frequency Transformer Design for Solid-State Transformers in Electric Power Distribution Systems

The objective of this thesis is to present a highor medium-frequency transformer design methodology for Solid-State Transformer (SST) applications. SSTs have been proposed as a replacement of the traditional 50/60 Hz transformer in applications demanding high-power density. Moreover, due to the high penetration of distributed generation, DC grids, energy storage systems, and sensitive loads, SSTs have been considered as an enabling technology for envisioned future energy systems. These applications demand additional functionalities that may not be achieved with traditional transformers. For example, active power flow control, harmonic suppression, voltage regulation, voltage sag compensation, and reduced size and volume. In this thesis, SST topologies are evaluated in order to determine their impact upon the transformer design. In addition, design considerations for core and wire selections, isolation requirements, and different transformer structures are investigated. As a result, the proposed transformer design methodology accounts for leakage inductance requirements for optimal power transfer, high-frequency effects in the transformer core and windings, and a flux density optimization to maximize transformer’s efficiency. The design procedure has been implemented in MATLAB as an interactive tool for designing high-frequency transformers.
Data-driven decision-making in creating class rosters

PurposeThis article informs school leaders and staffs about existing research findings on the use of data-driven decision-making in creating class rosters. Given that teachers are the most important school-based educational resource, decisions regarding the assignment of students to particular classes and teachers are highly impactful for student learning. Classroom compositions of peers can also influence student learning.Design/methodology/approachA literature review was conducted on the use of data-driven decision-making in the rostering process. The review addressed the merits of using various quantitative metrics in the rostering process.FindingsFindings revealed that, despite often being purposeful about rostering, school leaders and staffs have generally not engaged in data-driven decision-making in creating class rosters. Using data-driven rostering may have benefits, such as limiting the questionable practice of assigning the least effective teachers in the school to the youngest or lowest performing students. School leaders and staffs may also work to minimize negative peer effects due to concentrating low-achieving, low-income, or disruptive students in any one class. Any data-driven system used in rostering, however, would need to be adequately complex to account for multiple influences on student learning. Based on the research reviewed, quantitative data alone may not be sufficient for effective rostering decisions.Practical implicationsGiven the rich data available to school leaders and staffs, data-driven decision-making could inform rostering and contribute to more efficacious and equitable classroom assignments.Originality/valueThis article is the first to summarize relevant research across multiple bodies of literature on the opportunities for and challenges of using data-driven decision-making in creating class rosters.
Multi-Institutional Evaluation of Engineering Discipline Selection

During the fall of 2014, a quantitative study of first-year engineering student discipline selection was conducted at four dissimilar institutions in the Midwest: (1) an Urban Public, (2) a Private, (3) a Large Land Grant, and (4) a Large Urban. At all four institutions, an on-line survey was conducted at the start and at the end of the semester. The questions related to how interested students are in engineering (as compared to other academic majors), how certain they are that engineering is the best field of study for them, which discipline of engineering they are most interested in studying, and how certain they are of that engineering discipline choice. Collectively, there were over 3,300 student responses from across the four institutions studied. The data illuminated some differences between the institutions. However, a common result across all 4 institutions was a decrease in interest in engineering over the fall semester which may be accounted for by a “polarizing” effect in which the students that were more neutral in terms of certainty of engineering and their engineering discipline at the start of the semester shift over the course of the fall semester to the extremes, both high certainty and low certainty.
masticatory motor system functional disorders Ćwiczenia mięśni w rehabilitacji zaburzeń czynnościowych układu ruchowego narządu żucia

Summary On the basis of selected cases, evaluation of the usefulness of muscular exercises in rehabilitation of patients stricken by a dysfunction of the motor system of the chewing organ was accomplished. The assessment of the electric function of chewing muscles together with the registration of mandibular movements with the axiographic Zebris JMA apparatus was made, both before and after muscular therapy. The examination has shown that regardless of microor macro-traumatic cause, the set of muscular exercises appropriately selected and dutifully carried out is able to restore full condition of the motor system of the bone-dental structure effectively. dysfunction of the temporomandibular joints (TMJ) • muscle activity
Active Learning in Engineering Education: a (re)introduction

ABSTRACT The informal network ‘Active Learning in Engineering Education’ (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners construct their knowledge based on meaningful activities and knowledge. In 2014, the steering committee of the ALE network reinforced the need to discuss the meaning of Active Learning and that was the base for this proposal for a special issue. More than 40 submissions were reviewed by the European Journal of Engineering Education community and this theme issue ended up with eight contributions, which are different both in their research and Active Learning approaches. These different Active Learning approaches are aligned with the different approaches that can be increasingly found in indexed journals.
Two-stage class-AB OTA with enhanced DC gain and slew rate

ABSTRACT This article proposes a new two-stage class-AB operational trans-conductance amplifier (OTA). In this OTA, the characteristics of class-AB are applied in both of the stages. By increasing the effective trans-conductance of the first stage, DC gain is improved. Non-linear current mirror boosts the current of the second stage; therefore, slew rate (SR) is increased. In order to verify the performance of the proposed OTA, some simulations are carried out in a 0.18-μm CMOS process in which the supply voltage is 1.8 V. The simulation results indicate 21-dB enhancement in DC gain and 2.7 times improvement in SR compared to its conventional counterpart. The post-layout and Monte Carlo simulations show the proposed OTA has better performance than the state-of-the art designs.
Sub-Bases Layers of Residual Granite Soil Stabilised with Lime

This paper describes the results of research carried out for evaluating the effects of hydrated lime, with and without chemical activators, for the modification (up to 2% lime) and stabilisation (more than 2% lime) of residual granite soils. The effects of the modification of granitic soils with the addition of 2% calcitic lime were studied; and the results of these modifications on particle size distribution, plasticity and strength gain of two soils with different clay fractions are reported. Furthermore, the effects on compressive strength when 6 and 10% lime were added for curing times up to 10 weeks were monitored. The effects of saturation of the stabilised soils were also studied, as well as the effects of a small percentage of NaCl on stabilised soils with and without saturation. This addition of NaCl proved to be highly beneficial and a better alternative than the addition of larger amounts of lime. Estimated loss of strength due to saturation of cured specimens appeared to be constant with curing time, indicating that this effect is due to loss of suction potential.
Machine Learning Enabled Non-invasive Diagnosis of Nonalcoholic Fatty Liver Disease and Assessment of Abdominal Fat from MRI Data

Nonalcoholic fatty liver disease (NAFLD) is the most rapidly growing contributor to chronic liver disease worldwide with high disease burden and suffers from limitations in diagnosis. Inspired by recent advances in machine learning digital diagnostics, we explored the efficacy of training a neural network to classify high risk NAFLD vs. non-NAFLD patients in the UK Biobank dataset based on proton density fat fraction (PDFF). We compared the performance of several ResNet-derived architectures in the context of whole abdomen MRI, segmented liver and abdomen excluding liver (sans-liver). Non-local ResNet trained on whole abdomen MRI images yielded the highest precision (0.88 for NAFLD) and F1 (0.89 for NAFLD). Furthermore, our work on a second, larger cohort explored multi-task learning and the relationship among PDFF, visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT). Interestingly, multi-task learning experiments found a decline in performance for PDFF when combined with VAT and ASAT. We address this deterioration using Multi-gate Mixture-of-Experts (MMoE) approaches. Our work opens the possibility for using a non-invasive deep learning-based diagnostic for NAFLD, and directly enables clinical and genomic research using a larger cohort of potential NAFLD patients in the UK Biobank study.
Validation of AI-based software for objectification of conjunctival provocation test results in routine examinations and clinical studies

1. Background: Provocation tests are widely used in allergology to objectively reveal patients sensitivity to specific allergens. The objective quantification of an allergic reaction is a crucial characteristic of the tests. Due to the absence of objective quantitative measurements the conjunctival provocation test (CPT) is a less frequently used method despite its sensitivity and simplicity. We developed a new method AllergoEye based on AI for quantitative evaluation of conjunctival allergic reactions and validated it in a clinical study. 2. Methods: AllergoEye was implemented as a two component system. The first component is based on an Android smartphone camera for imaging the patients eye and the second one is PC based for image analysis and quantification. For AllergoEye validation an open-label, prospective, monocentric study was carried out on 41 patients. Standardized CPT was performed with sequential titration of grass allergen in 4 dilutions with the reaction evaluated by subjective/qualitative symptom scores and by quantitative AllergoEye scores. 3. Results: AllergoEye demonstrated high sensitivity (98%) and specificity (90%) as compared with human-estimated allergic reaction. Tuning cut-off threshold allowed to increase the specificity of AllergoEye to 97%, where correlation between detected sensitivity to allergen and sIgE CAP-class becomes obvious. Strikingly, such correlation was not found with sensitivity to allergen detected by subjective and qualitative symptom scores. 4. Conclusion: Clinical validation demonstrated that AllergoEye is a sensitive and efficient instrument for objective measurement of allergic reactions in CPT for clinical studies as well as for routine therapy control.
Analysis of humoral immunity against emerging SARS-CoV-2 variants: a population-based prevalence study in Yokohama, Japan

Background Little is known about the population prevalence of antibodies against emerging immune escape variants of SARS-CoV-2. Methods A population-based prevalence study was conducted in Yokohama City, the most populous municipality of Japan. Quantitative measurements of immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG) and qualitative measurements of neutralization antibodies against the Omicron BA.1 and BA.2 variants were performed. Results Of 6,000 randomly selected residents aged 20-74, 1,277 participated in the study during a period from January 30 to February 28, 2022. Of them, 3% had prior diagnosis of COVID-19, 96% received at least two-doses of SARS-CoV-2 vaccines, and 94% were positive for SP-IgG. The positive rates of neutralizing antibodies were 28% to Omicron BA.1 and BA.2 variants in a random sample of 10% of participants (n=123) and 100% to BA.1 and BA.2 among participants who received the third vaccination at least 7 days before (n=66). Conclusions In this population-based prevalence study in Japan, most had SP-IgG antibodies but the overall neutralizing antibody positive rate was 28% against the Omicron BA.1 and BA.2 variants. The population-level insufficient humoral immunity against the Omicron variants may explain the outbreak of COVID-19 during this period in Japan.