Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting an old hypothesis of human thermal perception: alliesthesia

Many new technologies and approaches to the provision of comfort inside buildings such as displacement ventilation, mixed-mode strategies, personally controllable (task-ambient) designs, chilled beams as well as some old but recently fashionable ones such as natural ventilation are prompting a rethink of the accepted comfort wisdom. How can a single combination of thermal environmental parameters be deemed unacceptable in a conventional heating ventilation and air-conditioning setting, and yet be regarded as acceptable, or even pleasant, in a naturally ventilated or mixed-mode setting? Why do current comfort standards prescribe static and isothermal conditions for comfort in one building, and dynamic and spatially variable indoor climates for comfort in another? The phenomenon of alliesthesia is used to differentiate thermal pleasure from thermal neutrality and acceptability. Alliesthesia is proposed as the logical framework of a new approach to thermal comfort modelling, building on the solid foundation .
Several Yeast Species Induce Iron Deficiency Responses in Cucumber Plants (Cucumis sativus L.)

Iron (Fe) deficiency is a first-order agronomic problem that causes a significant decrease in crop yield and quality. Paradoxically, Fe is very abundant in most soils, mainly in its oxidized form, but is poorly soluble and with low availability for plants. In order to alleviate this situation, plants develop different morphological and physiological Fe-deficiency responses, mainly in their roots, to facilitate Fe mobilization and acquisition. Even so, Fe fertilizers, mainly Fe chelates, are widely used in modern agriculture, causing environmental problems and increasing the costs of production, due to the high prices of these products. One of the most sustainable and promising alternatives to the use of agrochemicals is the better management of the rhizosphere and the beneficial microbial communities presented there. The main objective of this research has been to evaluate the ability of several yeast species, such as Debaryomyces hansenii, Saccharomyces cerevisiae and Hansenula polymorpha, to induce Fe-deficiency responses in cucumber plants. To date, there are no studies on the roles played by yeasts on the Fe nutrition of plants. Experiments were carried out with cucumber plants grown in a hydroponic growth system. The effects of the three yeast species on some of the most important Fe-deficiency responses developed by dicot (Strategy I) plants, such as enhanced ferric reductase activity and Fe2+ transport, acidification of the rhizosphere, and proliferation of subapical root hairs, were evaluated. The results obtained show the inductive character of the three yeast species, mainly of Debaryomyces hansenii and Hansenula polymorpha, on the Fe-deficiency responses evaluated in this study. This opens a promising line of study on the use of these microorganisms as Fe biofertilizers in a more sustainable and environmentally friendly agriculture.
Development status and infrastructure progress update of aerial imaging measurements on EUV masks

The high volume device manufacturing infrastructure for the 22nm node and below based on EUVL technology requires defect-free EUV mask manufacturing as one of its foundations. The EUV Mask Infrastructure program (EMI) initiated by SEMATECH has identified an actinic measurement system for the printability analysis of EUV mask defects to ensure defect free mask manufacturing and cost-effective high-volume EUV production as an infrastructural prerequisite for the EUVL roadmap ([1], [2]). The Concept and Feasibility study for the AIMSTM EUV resulted in a feasible tool concept for 16nm defect printability review. The main development program for the AIMSTM EUV has been started at Carl Zeiss leading to a commercialized tool available in 2014. In this paper we will present the status of the progress of the design phase of this development and an infrastructure progress update of the EUV Mask defect printability review.
Vulnérabilité et éthique de la présence à l’ère numérique

Digital technologies place their functionality and power at the service of a hypercommunication that is now reaching all strata of the population, especially students. Against this backdrop, the relationship with knowledge is itself reconfigured: cultural, scientific and academic contents, etc., are accessible online and students frequently use them. This communicational and informational efficiency allows social distancing and can reinforce it. Using the lens of the ethics of care, we can understand that the care that everyone needs, as a dependent being, requires a presence. This presence is not simple; it carries multiple parameters, including a certain relationship with others and a form of composure. In order to better understand this hiatus between digital distancing and presence, a survey was carried out among two groups of students, which allowed us to situate the experience and feelings of young people during the different phases of (COVID19) confinements and highlighted the extent of the difficulty induced by distance.
Nonlinear apodization for sidelobe control in SAR imagery

Synthetic aperture radar (SAR) imagery often requires sidelobe control, or apodization, via weighting of the frequency domain aperture. This is of particular importance when imaging scenes containing objects such as ships or buildings having very large radar cross sections. Sidelobe improvement using spectral weighting is invariably at the expense of mainlobe resolution presented here is a class of nonlinear operators which significantly reduce sidelobe levels without degrading mainlobe resolution implementation is via sequential nonlinear operations applied to complex-valued (undetected) SAR imagery. SAR imaging is used to motivate the concepts developed in this work. However, these nonlinear apodization techniques have potentially broad and far-ranging applications in antenna design, sonar, digital filtering etc., i.e., whenever data can be represented as the Fourier transform of a finite-aperture signal. >
Microwaves for breast cancer detection

Microwave imaging for medical applications has been of interest for many years. Microwave images are maps of the electrical property distributions in the body. The electrical properties of various tissues may be related to their physiological state. For example, the properties of tissues change with temperature. One application of microwave imaging that has been proposed is monitoring hyperthermia, which is the application of heat to tissue. In this case, the changing electrical properties indicate the successful deposition of heat in the tissue of interest. Other changes in electrical properties may be caused by disease. There is some evidence of changes in the properties of cancerous tissues when compared to normal tissues. Cancer detection with microwave imaging is based on this contrast in electrical properties. Microwave imaging for breast cancer detection has also interested many researchers.
Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost

Power loss reduction can be considered as one of the main purposes for distribution system operators. Reconfiguration is an operation process used for this optimisation by means of changing the status of switches in a distribution network. Recently, all system operators tried their best in order to obtain well-balanced distribution systems to decrease the operation cost, improve reliability and reduce power loss. This study presents an efficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators. The conventional distribution feeder reconfiguration (DFR) problem cannot meet the reliability requirements, because it only considers loss and voltage deviation as objective functions. The proposed approach considers reliability, operation cost and loss simultaneously. By adding the reliability objective to the DFR problem, this problem becomes more complicated than before and it needs to be solved with an accurate algorithm. Therefore this study utilises an Enhanced Gravitational Search Algorithm called EGSA which profits from a special mutation strategy in order to reduce the processing time and improve the quality of solutions, particularly to avoid being trapped in local optima. The proposed approach has been applied to two distribution test systems including IEEE 33 and 70-node test systems.
Inequality and Dropout in Higher Education in Colombia. A Multilevel Analysis of Regional Differences, Institutions, and Field of Study

In Colombia, the gaps of regional inequalities and social opportunities permeate people’s economic, political, and social participation. Additionally, the initial endowments of individual and socioeconomic background, barriers to financial aid, and academic and personal skills restrict decision-making about studying. In this context, the main objective is to analyze the determinants of dropout rates in Colombia and the differences between the type of institutions, field of study, and regions. We used data from three public administrative agencies for the period 2000–2012. The methodology combines multiple correspondence analysis and a lineal hierarchical model to explain the effect of variables operating at different levels. As a result, we retained four dimensions to represent the individuals’ socioeconomic and financial conditions. The findings obtained from the multilevel model suggest the variation between institutions (11%) and the interaction between institutions and the program cycle (17.8%). It confirms the influence of inequities on desertion. The student chooses between programs with differences in fees and study costs in general, such as quality, social recognition, and employment. In sum, contextual and institutional disparities in the dropout phenomenon’s behavior are explained mainly by the supply conditions in these regions and the individuals’ socioeconomic backgrounds.
Ensuring Microbial Safety in Food Product/ Process Development: Alternative Processing of Meat Products and Pathogen Survival in Low-Salt Cheddar Cheese

Boneless chicken breast portions were thawed by submersion in hot water (60 oC) and compared to refrigerator thawing. Thawing in hot water was significantly quicker (2– 8.5 min) than refrigerator thawing (10–15.5 h). Thawing time in hot water increased with an increase in meat thickness. Sensory panelists could not distinguish a difference between hot water versus refrigerator thawed and subsequently grilled chicken breast portions. A model for Salmonella growth predicts that thawing chicken breast at the slowest rate in this study (0.5 oC/min) would result in a lower increase in the Salmonella concentration than that expected for room temperature storage for 4 h.
Skills and knowledge of senior Taiwanese manufacturing managers

This paper examines how the career development and education of senior manufacturing managers in six electrical/electronics firms equipped them to support the priorities of the Taiwanese national strategy. It reviews the operations management literature, which is subsequently used to evaluate the work experiences and attendance at educational and/or training programmes of the senior managers responsible for manufacturing in the six plants. It shows that these senior managers had limited formal education in manufacturing topics, which was partly compensated for by a number of post‐experience programmes. It also shows that these managers had little prior exposure to manufacturing. This was true in terms of working at more junior levels or in working in related functions such as product development before these senior management appointments. It argues for a cadre of highly skilled manufacturing managers capable of sustaining the ideas built into the national strategy.
Design, synthesis, and structural characterization of helix-forming aliphatic homo-δ-peptides based on conformational restriction due to the structural characteristics of cyclopropane

Considerable effort has been directed toward developing artificial peptide-based oligomers that fold into a specific secondary structure, i.e., peptide foldamers. To date, however, detailed structural analysis of crystals of δ-peptide foldamers consisting of aliphatic δ-amino acids, which have a more extended carbon backbone compared with well-studied β- and γ-amino acids, have not been reported. We rationally designed aliphatic homo-δ-peptide foldamers forming a stable helical structure utilizing a chiral cyclopropane δ-amino acid as a monomer unit whose conformation was tightly restricted by the structural characteristics of cyclopropane depending on its stereochemistry. We stereoselectively synthesized the cyclopropane δ-amino acid monomer and prepared its various homo-oligomers. Structural analysis of the homo-δ-peptides using nuclear magnetic resonance, circular dichroism, and infrared spectroscopy revealed that they form a stable 14-helical structure in solution. Furthermore, the effective conformational regulation of the backbone due to the characteristics of cyclopropane allowed us to achieve X-ray crystallographic analysis of the homo-δ-peptides, showing their common right-handed 14-helical structures. The helical structures were consistent with both those predicted by theoretical calculations and those obtained based on nuclear magnetic resonance spectroscopy in solution. A critical point is that the helical structures of these δ-peptides are theoretically predictable by calculations. To our knowledge, this is the first example of aliphatic homo-δ-peptide foldamers forming a stable helical structure both in solution and in crystal.
Deep Learning Algorithms and Parallel Distributed Computing Techniques for High-Resolution Load Forecasting Applying Hyperparameter Optimization

Electrical load forecasting is one of the critical tasks that helps power utility companies in planning and operation as well as the energy managementsystem (EMS) in controlling and optimizing the power grid’s performance. It guarantees system adequacy and reliability by reducing the gap between supply and demand, and it bolsters cybersecurity by enabling false data detection and system security by predicting system peak load. This article aims to build an accurate long-term load forecasting model based on deep learning (DL) algorithms. Initially, big-data analytics and feature engineering are applied to the power load and weather historical data. Next, three different load forecasting models are developed based on three corresponding deep neural network models (DNN): the simple RNN, the long short term memory (LSTM), and the gated recurrent unit (GRU), respectively. To find an accurate DNN model, a two-step hyperparameter optimization is performed consisting of cross-validation. In the first step, the random search (RS) algorithm is employed to narrow the parameter search space to a smaller local one. In the second step, the grid search (GS) algorithm is used to find the best hyperparameters in the local area located by RS. However, the computational burden of the DNN training process is too high and may lead to out-of-memory (OOM) issues, especially when we are dealing with a big volume of data. To overcome this problem, we developed our Python program based on Tensorflow framework and implemented the framework on a high-performance computer cluster (HPCC). Then, different jobs are defined to employ parallel distributed computing (PDC) capability on the SIU BigDawg HPCC. To this end, all DNN hyperparameters (e.g., number of layers, neurons, dropout, batch size, epoch, learning rate, etc.) can be optimized and result in a comprehensive and accurate load forecasting model. Our proposed method, along with the programming framework, is evaluated on a real-world dataset. Among the three models developed and tested, the GRU, with load and weather as features, has demonstrated excellent performance and outperformed the other two models for long-term forecasting with the best metrics (i.e., MSE, MAPE, $R^2$) and daily error almost less than 1%. Also, our best model (optimized GRU) is compared with the other reported state-of-the-art models such as DBN, SVR, RM-LSTM, DM-GCNN, TCMS-CNN. It is demonstrated that the proposed framework yields a superior performance than the others.
Nonlinear modeling and bifurcations in the boost converter

The occurrence of nonlinear phenomena like subharmonics and chaos in power electronic circuits has been reported recently. In this paper, the authors investigate these phenomena in the current-mode-controlled boost power converter. A nonlinear model in the form of a mapping from one point of observation to the next has been derived. The map has a closed form even when the parasitic elements are included. The bifurcation behavior of the boost power converter has been investigated with the help of this discrete model.
Control System With Safe Obstacle Avoidance Capability

Tele-operated systems allow humans to extend their physical capabiiiti es and enable them to intervene in hazardous operations or where their presence is not poss ible. However, the operation of such systems over long periods has proved to be difficult and stressful. Consequently, means to facilitate their use are the subject of much study and experimental work. In this paper, we propose a collaborative­ shared control strategy that combines the operator abilities with robotic-based tasks to render these systems more flexible and robust. (n our method, the Collaborative Control component is responsible for allowing operator intervention when the robot is facing complex situations, whilst the Shared Control component provid es an automatic control mechanism to assist and to monitor-correct irrational operator actions. The paper will demonstrate how collaborative and shared control strat egies work together to facilitate the telcoperated control of a mobile platform in a cluttered environment. The experimental results include applications to surveillance and to search & rescue operations. In addition, a key component in the form of a hybrid obstacle avoidance module is introduced that allows the robot to be guided on a task basis by the operator at a distance.
Benchmarking, Characterization and Tuning of Shell EcoMarathon Prototype Powertrain

With the automotive industry ever striving to push the limits of fuel efficiency, the Shell EcoMarathon offers a glimpse into this energy conserving mindset by challenging engineering students around the world to design and build ultra-efficient vehicles to compete regionally. This requires synchronization of engineering fields to ensure that the vehicle and powertrain system work in parallel to achieve similar goals. The goal for Cal Poly – San Luis Obispo's EcoMarathon vehicle for the 2015 competition is to analyze the unique operating mode that the powertrain undergoes during competition and improve their current package to increase fuel efficiency. In this study, fuel delivery, ignition timing and engine temperature are experimentally varied to observe trends in steady state fuel consumption. A developmental simulation is then implemented with these trends to analyze potential differences in transient and steady state tuning targets. The engine is then tuned to finalized tuning targets and performance compared with benchmark values. v ACKNOWLEDGMENTS
Active Dual Mode Tilt Control for Narrow Ground Vehicles

SUMMARY Small, narrow commuter vehicles have attracted considerable interest in recent years as a means to increase the utilization of existing freeways and parking facilities. However, conventional narrow track vehicles are likely to have reduced stability against overturning during hard cornering. A possible solution to this problem lies in vehicles which tilt toward the inside of a turn. Two different ways to achieve this tilt will be analyzed. For direct tilt control (DTC) an actuator forces the upper part of the vehicle to tilt. Steering tilt control (STC) uses steering to control the tilt as is done by motorcycle or bicycle riders. At low speeds, only the DTC system is effective while at high speeds the STC offers less lateral acceleration for the passenger during transient cornering and may seem more natural. The two methods of control will be studied separately and it will be shown that even though the same steady state tilt can be achieved with either system, the transient behavior of the systems.
ROCK‐HARD TRIBOLOGY

The author compares the results of a series of tests on BQ wireline and TBW mining bits containing 30/40 US mesh De Beers SDA100 diamond abrasive at 60 concentration when drilling Cornish grey granite at constant penetration rate or constant thrust loads. The results confirmed earlier findings that, by setting the penetration rate of impregnated drill bits, efficient drilling can be maintained throughout the life of the bit.
BOUNDARY LAYER SEPARATION CONTROL WITH DIRECTED SYNTHETIC JETS

A new concept for boundary layer separation control has been developed that is a derivative of the synthetic jet concept (being used primarily for virtual shape control) which converts acoustic oscillations into mean fluid motions. The new concept, the so-called “directed synthetic jet”, has an acoustically excited neck like the synthetic jet, however the neck is curved in the downstream tangential direction. In this manner, the boundary layer flowing over the neck or slot is energized via suction removal of the approaching low momentum fluid on the in-stroke and tangential blowing of high momentum on the out-stroke, thereby making it in the time average more resistant to separation. The concept has been demonstrated to be energy efficient comparing input power to system benefit, yielding a net power gain and also potent enough to completely suppress boundary layer separation. An electroacoustic model is presented which describes the actuator characteristics and enables realistic application analysis.
Improved assessment of maximum streamflow for risk management of hydraulic infrastructures. A case study

ABSTRACT Understanding the risks associated with the likelihood of extreme events and their respective consequences for the stability of hydraulic infrastructures is essential for flood forecasting and engineering design purposes. Accordingly, a hydrological methodology for providing reliable estimates of extreme discharge flows approaching hydraulic infrastructures was developed. It is composed of a preliminary assessment of missing data, quality and reliability for statistically assessing the frequency of flood flows, allied to parametric and non-parametric methods. Model and parameter uncertainties are accounted for by the introduced and proposed modified model averaging (modified MM) approach in the extreme hydrological event's prediction. An assessment of the parametric methods accuracy was performed by using the non-parametric Kernel Density Estimate (KDE) as a benchmark model. For demonstration and validity purposes, this methodology was applied to estimate the design floods approaching the case study ‘new Hintze Ribeiro bridge’, located in the Douro river, one of the three main rivers in Portugal, and having one of Europe's largest river flood flows. Given the obtained results, the modified MM is considered a better estimation method.
Quadratic boost converter with low buffer capacitor stress

A new quadratic boost converter is presented in this study. Compared with the conventional quadratic boost converter, the proposed converter has the feature of lower buffer capacitor voltage stress. This advantage is very valuable for high voltage and high-voltage gain applications. The proposed converter also employed only one active switch and two LC (inductor-capacitor) filters. Detailed analysis for its continuous current mode operation and discontinuous current mode operation both are presented. In addition, modelling for the proposed converter is also developed in this study. A prototype circuit is built and the experimental results confirm the feasibility and performance of the high step-up converter.