Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Accessibility of Public Transport Systems: the Influence of Double-Decker Bus Acceleration on Passenger Movement

This thesis is exploring the movement of bus passengers in the dynamic environment of a London double-decker bus and aims at defining an acceptable level of acceleration that would provide an accessible bus service to users of all age groups. In addition, it is investigating whether passengers start their journeys with an inherent balance disadvantage due to the interior layout of the vehicle. Twenty-nine healthy, regular bus users, between 20 and 80 years old, undertook three tasks (walking on a flat surface, ascending and descending a staircase) in five environments (static, stationary bus, bus in motion at low, medium and high accelerations) whilst their gait was recorded. During the process they were also asked to assess the experimental tasks and environments, and to report any incidences of balance loss. Innovative experimental methods of gait analysis were employed and statistical analysis revealed that even when the bus is stationary, passengers alter their natural gait whilst moving inside the bus, especially on the bus staircase. Increasing accelerations impel passengers to walk in a less natural way in order to maintain their balance. Moreover, as acceleration is increasing, they adopt additional balancing mechanisms by choosing step types that increase contact with the negotiated surface and provide more stability. Middle-aged participants presented reduced ability to control balance in all examined tasks, whereas older and male participants used the stabilising step types more than the other age groups and gender. To conclude, accelerations of 2.5 m/s² and decelerations of 2.0 m/s² should be avoided, as they are intolerable for most participants. For a truly inclusive and accessible bus system, the acceleration limit should be set to 1.0 m/s², while at accelerations of 1.5 m/s², only the majority of young passengers will sustain their natural gait.
Influence and Establishment of Smart Transport in Smart Cities

In the modern era, the concept of smart cities is becoming more and more popular with each passing day. Smart transportation is the key branch of smart cities. IoT can tackle issues including traffic congestion, automatic fare collection detection, road safety accidents, and limited vehicle parking facilities. In our paper, we will talk about IoT based smart traffic regulating systems. The smart traffic regulating system composed of intelligent sensors deployed at the site is used to monitor the traffic and accordingly regulate the timings of traffic signals. Lanes having lesser traffic may have a green signal for a lesser duration as compared to a lane with higher traffic. How we can handle different traffic problems by implementing smart architecture in smart cities. In this paper, we will also talk about how the implementation of autonomous vehicles will impact our current transportation system and how it will be very useful in the coming times
Three-Dimensional Wheat Modelling Based on Leaf Morphological Features and Mesh Deformation

: The three-dimensional (3D) morphological structure of wheat directly reﬂects the inter-relationship among genetics, environments, and cropping systems. However, the morphological complexity of wheat limits its rapid and accurate 3D modelling. We have developed a 3D wheat modelling method that is based on the progression from skeletons to mesh models. Firstly, we identiﬁed ﬁve morphological parameters that describe the 3D leaf features of wheat from amounts of 3D leaf digitizing data at the grain ﬁlling stage. The template samples were selected based on the similarity between the input leaf skeleton and leaf templates in the constructed wheat leaf database. The leaf modelling was then performed using the as-rigid-as-possible (ARAP) mesh deformation method. We found that 3D wheat modelling at the individual leaf level, leaf group, and individual plant scales can be achieved. Compared with directly acquiring 3D digitizing data for 3D modelling, it saves 79.9% of the time. The minimum correlation R 2 of the extracted morphological leaf parameters between using the measured data and 3D model by this method was 0.91 and the maximum RMSE was 0.03, implying that this method preserves the morphological leaf features. The proposed method provides a strong foundation for further morphological phenotype extraction, functional–structural analysis, and virtual reality applications in wheat plants. Overall, we provide a new 3D modelling method for complex plants.
Recent Progress in Materials Theoretical Modelling of Liquid Crystal Electro-Optical Material Display Elements to Achieve Optimal Low Power Consumption Ship Stealth

Advanced optical stealth techniques are of growing importance in the role of manned and unmanned aircraft or ship platforms. We consider here the concept of using passive reflective display elements rather than high power active light projection to achieve a low observable camouflaged ship platform. This paper presents practical consideration towards minimal radiated power user-driven requirements using adaptive liquid crystal electro-optical methods. Optical reflectivity for a multi-layer liquid crystal cell structure composed of a glass/ ITO/ aligning layer/ liquid crystal/ aligning layer/ ITO/ glass will support optical guided modes. Reflectivity as a function of angle and voltage are compared with theory generated from a Fresnel matrix formalism. Voltage device modulated reflectivities are then simulated across a ship platform to evaluate this method for low power consumption, with minimal radiated optical radiation.
Determination of residual value of construction machinery based on machine age Determination of residual value of construction machinery based machine

The relationship between the residual value and service life of machines is investigated in the paper. The study resulted in establishment of several models based on symbolic regression, where the dependent variable is the residual value, while independent variables are machine models, machine age, cumulative number of machine operating hours, and inflation index. The estimate of residual value is crucial for making investment decisions. The investigation has shown that development of a general prognostic mathematical model of residual value of construction machinery can be made using symbolic analysis of an available set of data formed of 61,153 machines.
Monogenetic Rare Diseases in Biomedical Databases and Text Mining

The testing of pharmacological hypotheses becomes faster and more accurate, but at the same time more difficult than even two decades ago. It takes more time to collect and analyse disease mechanisms and experimental facts in various specialized resources. We discuss a new approach to aggregating individual pieces of information about a single disease using Elsevier's automated text mining technology. The developed algorithm allows for the collection of published facts in a unified format starting only with the name of the disease. A special template, which combines research and clinical descriptions of diseases was developed. The approach was tested, and information was collected for 55 rare monogenic diseases. Clinical, molecular, and pharmacological characteristics of diseases with supporting references from the literature are available in the form of tables and files. Manually curated templates for 10 rare diseases, including top ranked Cystic Fibrosis and Huntington's disease were published to demonstrate the results of the described approach.
Profile of Brazilian inpatients with COVID-19 vaccine breakthrough infection and risk factors for unfavorable outcome

Objective. To characterize the epidemiological and clinical profile of individuals more likely to become infected by SARS-CoV-2 after the fully vaccination schedule in order to profile priority groups to receive a booster dose in situations of vaccine doses shortage as well as for maintenance of personal protective care. Methods. Data from hospitalized COVID-19 patients who had been fully vaccinated and had a SARS-CoV-2 infection positive diagnosis were collected from the SIVEP-Gripe database (Influenza Epidemiological Surveillance Information System) from January 18, 2021 to September 15, 2021. Demographic data, clinical symptoms/signs and preexisting medical conditions (comorbidities) were analyzed. The primary outcome was in-hospital death. Results. The majority of hospitalized patients with vaccine breakthrough infection were elderly [≥]60 years old, male, with critical or severe COVID-19. The fatality rate was extremely high (50.27%) and more pronounced in elderly groups. The most prevalent symptoms were cough, dyspnoea, respiratory distress, and low blood oxygen saturation. The most frequent comorbidities were heart disease and diabetes. High fatality rates were observed among patients admitted to the intensive care units (72.88%) and those who required invasive mechanical ventilation (87.82%). The main risk factors for an unfavorable outcome were older age, respiratory compromise, inactivated virus vaccine immunization, and preexisting medical conditions. Conclusions. We characterize the profile of hospitalized Brazilian patients with COVID-19 vaccine breakthrough infection and the risk factors for an unfavorable outcome. These data have made it possible to identify priority groups to receive a booster dose, in addition to not neglecting personal protection.
Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls

Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalised epilepsy in both ictal and interictal states. Here, we characterise differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy (JME) and assess factors influencing the heterogeneity of these EEG features. We collected EEG data from 147 participants with JME through the Biology of Juvenile Myoclonic Epilepsy (BIOJUME) study. 95 control EEGs were acquired from two independent studies (Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project). We extracted frequency and functional network-based features from 10-20s epochs of resting-state EEG, including relative power spectral density (PSD), peak alpha frequency, network topology measures and Brain Network Ictogenicity (BNI): a computational measure of the propensity of networks to generate seizure dynamics. The influence of covariates such as age, sex, antiseizure medication, EEG time and epoch length were investigated for each EEG feature prior to testing for differences between JME and control EEGs using univariate, multivariable and receiver operating curve (ROC) analysis. Additionally, associations of clinical phenotypes (seizure type, seizure control) with EEG features were investigated in the JME cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in PSD in delta (2-5Hz) (p=0.0007, hedges' g=0.55) and low-alpha (6-9Hz) (p=2.9x10-8, g=0.80) frequency bands, peak alpha frequency (p=0.000007, g=0.66), functional network mean degree (p=0.0006, g=0.48) and BNI (p=0.00006, g=0.56) between JME and controls. Since age (p=0.009) and epoch length (p=1.7x10-8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between JME and controls remained. ROC analysis showed low-alpha PSD was optimal at distinguishing JME from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in JME patients. To conclude, individuals with JME have increased power of neural oscillatory activity at low-alpha frequencies, along with increased BNI compared to controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in IGE particularly for their use as biomarkers.
Attitude towards gender inequitable norms and associated factors among male youths in Arba Minch town, Southern Ethiopia

Background Gender inequitable norms are common cultural traditions across the world, which characterized women as someone who deserves less basic life support and fundamental human rights than men. The unfairness of such practices has demolished womens quality of life. Studies are limited to measuring some factors in Ethiopia. The information obtained from this study will help to take an evidence-based approach to reduce gender inequitable norms. Objective To assess attitude towards gender inequitable norms and associated factors among male youths from August 16 th - 30 th , 2020 at Arba Minch town, Southern Ethiopia. Methods A community-based cross-sectional study was conducted among 423 male youths. Gender-Equitable Men Scale was used to measure the attitudes towards gender inequitable norms. The study participants were selected using a simple random sampling technique by allocating a proportion to each kebeles. Both bivariable and multivariable logistic regression analyses were performed to identify associated factors. The level of statistical significance was set at a p-value of less than 0.05 in multivariable logistic regression. Results The overall prevalence of favorable attitude towards gender inequitable norms among male youths was 47.3% with 95% CI (42%, 52%). No formal education, lower household income, not participating in youth clubs, poor knowledge, and having a prior history of physical violence during childhood were factors significantly associated with a favorable attitude towards gender inequitable norms. Conclusion and recommendation Almost half of the participants had a favorable attitude towards gender inequitable norms. Proactive measures need to be taken to curb the problem by taking integrated interventions for youths like enrolling in school, enhancing participation in a youth club, prevent childhood physical violence, increasing household income, and creating awareness on gender inequitable norms to change traditional beliefs that undermine women.
How useful is a regional SAM in evaluating regional projects in Sri Lanka?: An illustration for post-war regional development policy analysis

Over the last several decades, Social Accounting Matrices (SAMs) have emerged as a widely accepted method for the presentation of macroeconomic data and an analytical technique for impact analyses at national, regional and village levels. Although there is a large body of literature concerning the construction and application of SAMs, there are only a few impact evaluations with regional and village SAMs. This is particularly evident when focusing on the impact of regional investment projects in developing countries. In this paper, we have attempted to demonstrate how a regional SAM can successfully be applied to evaluate the impact of an irrigation project in the Southern Province of Sri Lanka. This example clearly demonstrates the possibility of using regional and village level SAMs in evaluating post-war development projects, such as infrastructure and irrigation projects, in Sri Lanka.
Kinodynamic Planning for Terrain Environments:

Figure 1: (top-left) Experimental environment constructed using the Gravel Pit Lidar-Intensity Imagery Dataset[1], which is generated from LIDAR scans of a 1.1 km of a circuit. (top left) Satellite image of the terrain based on which the dataset is generated [1]. (middle and bottom) Zoomed in images taken at various points along the path. Kinodynamic planning is a branch of motion planning where differential constraints are applied to the motion of the robot. Constraints could include constraints on the direction of motion as well as upper an lower limits on velocity and acceleration. Kinodynamic planning has application in mobile robotics[2], autonomious driving[3], aerial vehicles [4], grasping, manipulation, space exploration, search and rescue and agricultural robots. Kinodynamic planning is characterized by the lack of a solution to the 2-point boundary problem and consequently the lack of a steering function. This makes many common motion planning algorithms, such as the PRM [5] and RRT∗ [6] unsuitable for kinodynamic planning. We must therefore rely on algorithms such as the RRT[7] which only expand through forward propagation. Recent work has focused on the development of asymptotically optimal planners for systems without steering functions, which has lead to the development of methods such as Stable Sparse RRT [8], AO-X [9] and AO-RRT2 [10], and DIRT [11]. The lack of a steering function also makes it infesiable to make use of heurestics such as cost-maps during node expansion which means that most existing methods can only expand nodes by propagating random controls. Physics and Terrain Environments Planning in real-world physical environments is a difficult open problem, due primarily to all of the factors which can influence motion. In addition to dynamics, planning must incorporate factors such as friction, gravity and the complex interactions between physical components of the robot. Terrain environments may also include regions that are impassable and areas with rough or steep terrain that is difficult to traverse.
Ordinary Meaning and Consilience of Evidence 1

: In this chapter I note two recent trends, one in experimental jurisprudence and one in experimental philosophy. First, some work in experimental jurisprudence has pushed for moving beyond textual sources, including the use of linguistic corpora, and toward questionnaire methods in analyzing ordinary meaning. Second, some work in experimental philosophy has urged that we should look to move beyond the use of questionnaire methods and toward the use of linguistic corpora in analyzing ordinary concepts. There is a methodological tension here that suggests further investigation. I do so by considering the legal hypothetical of a prohibition on vehicles in a park that has featured prominently in the back-and-forth over the use of corpus methods in legal interpretation. Taking a closer look at this example, including extending previous corpus analyses, I argue that corpus and questionnaire methods in fact paint a remarkably similar picture of the ordinary use of “vehicle. ” I hold that this highlights how these methods can compliment each other, and conclude that when it comes to difficult empirical questions—such as those that arise in assessing ordinary meaning and ordinary concepts—we should aim to employ multiple sources of information to arrive at a consilience of evidence.
The impact of the Hsp67Bc gene product on Drosophila melanogaster longevity, fecundity, and acute heat stress tolerance

Drosophila melanogaster Hsp67Bc is a heat- and cold-inducible small heat shock protein that participates in the prevention of aggregation of misfolded proteins and in macroautophagy regulation. Overexpression of the Hsp67Bc gene has been shown to enhance macroautophagy in Drosophila S2 cells, and the deletion of this gene leads to the formation of a slightly increased number of autophagic vacuoles in the fruit f ly brain neurons. Recently, we found that Hsp67Bc-null D. melanogaster f lies have poor tolerance to cold stress (0 °C) of various durations. In the present work, we investigated how the Hsp67Bc gene deletion affects the f itness of fruit f lies under normal conditions and their tolerance to elevated temperatures at different developmental stages. Larvae and pupae were not adversely affected by the Hsp67Bc gene deletion, and adult Hsp67Bc-null f lies showed an extended lifespan in comparison with the control at normal (24–25 °C) and elevated temperature (29 °C), and after acute heat stress (37 °C, 2 h). At the same time, the fecundity of the mutant females was lower by 6–13 % in all tested environments, except for permanent maintenance at 29 °C, where the mean numbers of eggs laid by the mutant and control f lies were equal. We explain this phenomenon by a reduced number of ovarioles in Hsp67Bc-null females and enhanced macroautophagy in their germaria, which promotes the death of forming egg chambers. In addition, short heat stress (37 °C, 2 h), which increased the control line’s longevity (an effect common for a wide range of organisms), had a negative impact on the lifespan of Hsp67Bc-null f lies. Therefore, Hsp67Bc-null D. melanogaster have an extended lifespan under normal and elevated temperature conditions, and reduced fecundity and thermal stress tolerance.
Undoped-emitter InP/InGaAs HBTs for high-speed and low-power applications

Scaling down the lateral emitter dimension is an effective way to reduce the power dissipation of HBT ICs. Various authors have demonstrated submicrometer HBTs operating at >100 GHz with submilliampere current. On the other hand, there have been few reports on vertical layer structures optimized for low-current operation. At low current, the dominant delay time of HBTs is the emitter charging time. Thus, it is essential to reduce the emitter junction capacitance by increasing the thickness of the emitter depletion layer. In this paper, we propose an undoped-emitter structure for InP-based HBTs and investigate its impact on low-power applications.
Replication-transcription complex of coronaviruses: functions of individual viral non-structural subunits, properties and architecture of their complexes

Coronaviruses (CoVs) belong to the subfamily Orthocoronavirinae of the family Coronaviridae. CoVs are enveloped (+) RNA viruses with unusually long genomes. Severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and the novel coronavirus (2019-nCoV, SARS-CoV-2) have been identif ied as causing global pandemics. Clinically tested vaccines are widely used to control rapidly spreading, acute, and often severe infections; however, effective drugs are still not available. The genomes of SARS-CoV-2 and SARS-CoV are approximately 80 % identical, while the genomes of SARS-CoV-2 and MERS-CoV are approximately 50 % identical. This indicates that there may be common mechanisms of coronavirus pathogenesis and, therefore, potential therapeutic targets for each virus may be the same. The enzymes and effector proteins that make up the replication-transcription complex (RTC) of coronaviruses are encoded by a large replicase gene. These enzymes and effector proteins represent promising targets for potential therapeutic drugs. The enzyme targets include papain- and 3C-like cysteine proteinases that process two large viral polyproteins, RNA-dependent RNA polymerase, RNA helicase, viral genome-modifying enzymes, and enzymes with 3’–5’ exoribonuclease or uridylate-specif ic endonuclease activity. Currently, there are many studies investigating the complex molecular mechanisms involved in the assembly and function of the RTC. This review will encompass current, modern studies on the properties and complexes of individual non-structural subunits of the RTC, the structures of individual coronavirus RTC subunits, domain organization and functions of subunits, protein-protein interactions, properties and architectures of subunit complexes, the effect of mutations, and the identif ication of mutations affecting the viability of the virus in cell culture. Key words: non-structural proteins CoVs; subunits of replicase CoVs; replication-transcription complex of CoVs; architecture of non-structural protein complexes CoVs.