Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a data acquisition program to measure the exhaust time of a pneumatic valve

This paper deals with development of a data acquisition program to measure the exhaust time of a mechanical actuated pneumatic valve. The volume, which will be exhausted is determined by a so-called end of line testing procedure. The data acquisition unit is an Advantech ADAM 4117 8 channel analogue input module. The measuring and logging program is developed in LabVIEW software. The program provides the data in comma separated value file format for postprocessing opportunities.
Harmonic phase angles for a domestic customer with different types of lighting

Summary This paper presents measurements of the changes in phase angle of the harmonic current for a domestic costumer due to the introduction of energy-efficient lamps (compact fluorescent lamps and light-emitting diodes lamps). Those results are then compared with the aggregation rules according to standard IEC 61000-3-6 and with a mathematical model, in order to highlight the importance of using phase angles in the harmonic estimations. The paper presents both the emission from individual household devices and the variations in the complex harmonic current from a group of devices. Cancellation because of phase-angle difference plays an important role in the emission from a group of different devices. This explains why the increase in emission after changing to energy-efficient lamps is much smaller than expected. Some other power-quality parameters are also considered such as total harmonic distortion, total power factor, and displacement power factor. It is concluded that the complex plane presentation is a useful tool to estimate the harmonic emission from a group of domestic appliances. Copyright © 2014 John Wiley & Sons, Ltd.
A Comparative Perspective on the Paradox of Choice

The paradox of choice leads one to desire more options over fewer options even when there are negative consequences when choosing from larger arrays (choice overload). The paradox of choice may be shared among mammals or it could result from cultural influences relevant to humans. Research with monkeys and young children sheds light on the developmental precursors of the paradox and may highlight the human-uniqueness of this effect. I tested young children (41.5–66.0 months) and monkeys (tufted capuchins, rhesus macaques) to examine choice overload effects. Limited evidence was found that children exhibited choice overload when choosing among six and twelve toys but not when choosing among three toys. No evidence of choice overload was found for monkeys, although this may be due to methodological limitations. Consistent with previous literature on choice and control, monkeys also demonstrated a preference for more options over fewer. INDEX WORDS: Paradox of choice, Choice overload, Comparative cognition, Nonhuman primates, Developmental psychology Copyright by Maisy D. Bowden 2021 A Comparative Perspective on the Paradox of Choice
Extracting Drug-Protein Interaction using an Ensemble of Biomedical Pre-trained Language Models through Sequence Labeling and Text Classification Techniques

— Automatic text mining the interactions between drugs and proteins is significantly beneficial to drug discovery, drug repurposing, drug design, and bioinformatics knowledge graph mining. The DrugProt track of BioCreative VII aims to promote the development and evaluation of systems that are able to automatically detect in relations between chemical compounds/drugs and genes/proteins. This paper describes our method used to create our submissions to the task. We formulated the task of extracting the relation pairs of drugs and proteins using two separate frameworks: text classification and sequence labeling. The cutting-edge biomedical pre-trained language models are used for both frameworks. Then different ensemble methods are further used to improve the final performance. Our best submission achieves the F1-scores of 0.795 and 0.789 on the main test set and the additional large-scale test set, respectively.
Design of a 5-GHz two-stage cascode CMOS

CHAPTER 1: INTRODUCTION Background Motivation for Using Cascade CMOS Low Noise Amplifier Structure Recent LNA Researches CHAPTER 2: LOW NOISE AMPLIFIER DESIGN Circuit Topology Design and Analysis Spiral Inductor Modeling Electrostatic Discharge (ESD) Design CHAPTER 3: SIMULATION AND LAYOUT Scattering Parameters Two-Port Network Simulation Schematic Simulation LNA Layout and Verification Post Layout Simulation Test Inductors v
Enhancement and Analysis of TARS Few-shot Learning Model for Product Attribute Extraction from Unstructured Text

Few-shot learning techniques rely on generalizations of a base model trained on a large training set in order to transfer learn to more specialized tasks. Such techniques extend unsupervised learning models by allowing for fine-tuning a general model to a domain of interest using a relatively low number of training samples. This is especially important for applications where data may be non-homogeneous and difficult to label, such as product catalog data that vary drastically from category to category and require domain expertise for labeling. In this paper, we explore the application of a few-shot learning model to infer structured product attribute values from unstructured descriptive text. We experiment with Task-Aware Representation of Sentences (TARS) model [3] applied to catalog data, and further extend the model to support training on negative examples. We demonstrate that with a few labeled examples, we can train a specialized model for each attribute of a product category, and provide results of comparable quality to current state-of-the art techniques. Results show that with only 40 training examples per product attribute, the model, when cross trained over attributes, produces improved recall and comparable precision over an existing baseline model that relies on tens of thousands of examples per product attribute. To further exemplify the generalization power, experiments are conducted using synthetic training data, extracted automatically from search queries. This completely eliminates the need for manually labeled examples and further leverages customer behavioral signals to help prioritize model training by what customers deem important.
Mansoura Veterinary Medical Journal THE EFFECT OF DIETARY SUPPLEMENTATION WITH SACCHAROMYCES CEREVISIAE ON GROWTH PERFORMANCE, SOME SELECTIVE HEMATOLOGICAL, BIOCHEMICAL AND ANTIOXIDANT PARAMETERS IN NEW ZEALAND WHITE RABBITS

The present study was conducted to evaluate the effect of Saccharomyces cerevisiae dietary supplementation on growth performance, some selective hematological, biochemical, oxidative stress marker and antioxidant parameters in New Zealand White (NZW) rabbits. Thirty weaned rabbits were divided into three groups (n=10), C: control fed basal diet, S1: fed basal diet supplied with Saccharomyces cerevisiae (Sc) 4g/kg diet and S2: supplied with Sc 10g/kg diet for 6 weeks. The weight gain, feed intake and feed conversion rate (FCR) were calculated at the end of 3 and 6 week. The blood samples were collected; one with anticoagulant for hematological examination, and other coagulated one for obtain clear serum sample to estimate some selective serum biochemical parameters and serum total antioxidant capacity. One gram of hepatic tissue was collected from each rabbit for preparation of hepatic homogenate which used for analyzing oxidative stress marker and antioxidant parameters (MDA, SOD, Catalase and GSH). At the end of the study, the growth performances were significantly improved in S1and S2 groups than control one. Serum AST, creatinine, glucose and lipid profile were significantly decreased in S1and S2 groups than control group. S1 and S2 groups showed a marked increase in hepatic GSH compared with control group. Other parameters were insignificantly differed between all experimental groups. Saccharomyces cerevisiae supplementation as a feed additive in rabbits’ diet had a desirable effect on weight gain, FCR and antioxidant enzymes activities as well as improved the lipid profile, glucose level, liver and kidney functions.
Effect of Isothermal Ageing on Damping Capacity of Cu-20.4Al-8.7Mn

The effect of ageing temperature on damping capacity of the Cu-20.4Al-8.7Mn alloy at room temperature was investigated by internal friction measurements. The results indicated that damping capacity of the alloy exhibits a non-monotonous changing trend with ageing temperature. Ageing at lower temperature of less than 150oC, damping capacity rapidly increses even up to maximum of 0.01 with the increasing ageing temperature, the reason of which should relate with the increased amount of twin boundaries and phase interfaces between martensites due to the thinning and splitting of martensitic plates, whereas when the ageing temperature exceeds 150oC, the damping capacity trends to steeply decrease as the ageing temperature increases until close to a constant in last corresponding to the ageing at higher temperature due to the occurrence and complete finish of transformation of martensites to austenites.
Basic Graphic Shape Decoding for EEG-based Brain-Computer Interfaces

Image decoding using electroencephalogram (EEG) has became a new topic for brain-computer interface (BCI) studies in recent years. Previous studies often tried to decode EEG signals modulated by a picture of complex object. However, it’s still unclear how a simple image with different positions and orientations influence the EEG signals. To this end, this study used a same white bar with eight different spatial patterns as visual stimuli. Convolutional neural network (CNN) combined with long short-term memory (LSTM) was employed to decode the corresponding EEG signals. Four subjects were recruited in this study. As a result, the highest binary classification accuracy could reach 97.2%, 95.7%, 90.2%, and 88.3% for the four subjects, respectively. Almost all subjects could achieve more than 70% for 4-class classification. The results demonstrate basic graphic shapes are decodable from EEG signals, which hold promise for image decoding of EEG-based BCIs.
Reflecting on the organization: introducing engineers to corporate identity, image, brand, and culture

Engineers are expected to understand the structure, goals, and values of the organizations for which they work. Only then can they contribute effectively to these organizations through the production of appropriate goods and services as well as routine communications. Based on the work of Hatch and Schultz (2000), the author offers four concepts (identity, image, brand, and culture) for conducting organizational analysis from varied internal and external perspectives and presents composing practices that follow from this analysis. An advertisement for Ford Motor Company is the primary artifact through which the concepts are examined. As students of engineering enter their respective fields, they must be well equipped to provide not only technical knowledge and skills but also effective communication to the organizations they join. Part of this preparation involves teaching students how to analyze (and critique, if necessary) the goals, values, and priorities of the environments in which they will work, since the context of an organization influences document concerns ranging from audience assumptions to visual layout to language use. This paper addresses some of the ways in which students of engineering might be better prepared to enter the profession through increased knowledge of the workplace, as we as how seasoned engineers might be re-introduced to the purposes behind their work for a particular organization.
Exploring supply chain issues affecting food access and security among urban poor in South Africa

Access to food through retail supply chain distribution can vary significantly among the urban poor and leads to household food insecurity. The paper explores this sustainable supply chain phenomenon through a field study among South Africa's urban poor. ,Urban metabolic flows is the theoretical basis in the context of supply chain management (SCM). The field study comprised 59 semi-structured interviews in one South African township. Data were recorded, transcribed and translated, and coded using NVivo 12 to provide an inventory of eight themes categorized and patterned from the analysis. ,Findings indicate societal factors play a significant role affecting food distribution, access and security from a spatial perspective of retail outlet locations and a nutritional standpoint regarding quality and quantity of food. ,The study is exploratory in one township, and while rigorously conducted, the generalizability of findings is limited to this context. ,The study practically contributes by providing guidance for food retailers and policymakers to include nutritional guidelines in their distribution planning, as well as the dynamics of diverse neighbourhoods that exist in modern urban contexts. ,New forms of retail food distribution can provide better security and access to food for the urban poor, contributing to Sustainable Development Goals (SDGs) 2 Zero Hunger and 11 Liveable Cities. ,The study is interdisciplinary and contributes by linking UN SDGs and SCM through urban metabolic flows from development studies as an overarching framework to enable analysis of relationships between physical, social and economic factors in the urban environment.
AN EFFICIENT HYBRID NUMERICAL METHOD FOR THE TWO-ASSET BLACK-SCHOLES PDE

In this paper, an efficient hybrid numerical method for solving two-asset option pricing problem is presented based on the Crank-Nicolson and the radial basis function methods. For this purpose, the two-asset Black-Scholes partial differential equation is considered. Also, the convergence of the proposed method are proved and implementation of the proposed hybrid method is specifically studied on Exchange and Call on maximum Rainbow options. In addition, this method is compared to the explicit finite difference method as the benchmark and the results show that the proposed method can achieve a noticeably higher accuracy than the benchmark method at a similar computational time. Furthermore, the stability of the proposed hybrid method is numerically proved by considering the effect of the time step size to the computational accuracy in solving these problems.
Pre-orders for Reasoning about Input-to-State Stability Properties of Hybrid Systems

In this paper, we investigate pre-orders for reasoning about input-to-state stability properties of hybrid systems. We deﬁne the notions of uniformly continuous input simulations and bisimulations , which extend the notions in previous work to include inputs. We show that uniformly continuous input bisimulations preserve incremental input-to-state stability of hybrid systems, and thus provide a basis for constructing abstractions for veriﬁcation. We show that Lyapunov function based input-to-state stability analysis can be cast in our framework as constructing a simpler one-dimensional system, using a uniformly continuous input simulation, which is input-to-state stable, and thus, inferring the input-to-state stability of the original system.
MODELING BICYCLE DEMAND AS A MAINSTREAM TRANSPORTATION PLANNING FUNCTION

This article examines the need for quantitative modeling of bicycle demand and reviews the techniques available for incorporating bicycles into existing transportation planning models. It is argued that there is insufficient attention paid to quantitative modeling of bicycle demand and that this results in the case for bicycle provision being poorly based. Transportation modeling, as in many other areas of research, has a traditional method of approach. Improvements in models have tended to be incremental rather than revolutionary. In improving the models of bicycle demand, it is appropriate to review the elements of the traditional approach to determine whether it is possible to tailor those models to the needs of bicycle planning. The location-specific models of traditional transportation models are characterized by considerable spatial detail and very few variables that relate to travel behavior. Although these models are unsatisfactory, particularly insofar as they have treated bicycle transportation, their results continue to be required by practitioners responsible for transportation provision. In the future, however, these models will have a different focus than the predict-and-provide approach taken in years past. This can be expected to result in improved treatment of minority modes such as bicycles. The challenge for incorporating bicycles into future models is to develop a behavioral understanding of bicycle demand that can be incorporated into the spatially defined network models. Some new tools of transportation planning and network management can also be exploited to ensure that bicycle transportation is not forgotten by mainstream transportation researchers.
Small signal models of a zero-voltage-switched SEPIC dual converter with a coupled inductor

Several small signal models are developed for the coupled-inductor zero-voltage-switched SEPIC dual power converter via the extended circuit averaging method and compared to the measured response. Although the ideal model shows only a two-pole response because of the coupled inductor action, the final model must include the parasitic resistances and the leakage inductances of the coupled inductor to match the actual measured four-pole power converter response. The parasitic resistances are found to affect the location of the transfer function zeros. The turns ratio and the leakage inductances of the coupled inductor, which determine the large signal zero current ripple condition, are found to influence the transfer function response. Therefore, the DC and AC design of the power converter are forced to be interdependent because of the coupled inductor operation. <<ETX>>
Exploiting convergent evolution to derive a pan-cancer cisplatin sensitivity gene expression signature

Precision medicine offers remarkable potential for the treatment of cancer, but is largely focused on tumors that harbor actionable mutations. Gene expression signatures can expand the scope of precision medicine by predicting response to traditional(cytotoxic) chemotherapy agents without relying on changes in mutational status. We present a novel signature extraction method, inspired by the principle of convergent evolution, which states that tumors with disparate genetic backgrounds may evolve similar phenotypes independently. This evolutionary-informed method can be utilized to produce signatures predictive of response to over 200 chemotherapeutic drugs found in the Genomics of Drug Sensitivity in Cancer Database. Here, we demonstrate its use by extracting the Cisplatin Response Signature, CisSig, for use in predicting a common trait (sensitivity to cisplatin) across disparate tumor subtypes (epithelial-origin tumors). CisSig is predictive of cisplatin response within the cell lines and clinical trends in independent datasets of tumor samples. This novel methodology can be used to produce robust signatures for the prediction of traditional chemotherapeutic response, dramatically increasing the reach of personalized medicine in cancer.
Robustness Testing Framework For Neural Network Image Classifier

Neural network has made remarkable achievements in the field of image classification, but they are threatened by adversarial examples in the process of application, making the robustness of neural network classifiers face danger. Programs or software based on neural network image classifiers need to undergo rigorous robustness testing before use and promotion, in order to effectively reduce losses and security risks. To comprehensively test the robustness of neural network image classifiers and standardize the test process, starting from the two aspects of generated content and interference intensity, a variety of robustness test sets are constructed, and a robustness testing framework suitable for neural network classifiers is proposed. And the feasibility and effectiveness of the test framework and method are verified by testing LENET-5 and the model reinforced by the adversavial training.
Information Security Problems and Solutions in Cloud Era

Era of cloud computing, data and personal information into gold on the “cloud” has great value, at present for the cloud of the era of corporate and personal data leakage, network attacks and other security events are occurring, this article mainly discusses the cloud age how to ensure the security of enterprise and personal data, the information security how from passive defense to conduct surveillance and response, etc are analyzed and explored.
Monitoring and Early Warning of Transmission Line External Breakage Based on Satellite-Ground Coordination

This article first proposes a high-precision spatio-temporal registration method between satellite remote sensing images and ground sensors. Then, using satellite remote sensing images, an intelligent identification model for typical external damage hidden dangers of transmission lines based on satellite remote sensing is established to realize intelligent identification of transmission line construction work areas and mining affected areas. Aiming at the results of intelligent identification of construction work areas and mining-affected areas, the proposed YOLOv4-based external damage identification algorithm for transmission lines is used to detect external damage hidden dangers. Through the method in this paper, it is possible to realize a regular general survey of hidden dangers of external damage (construction work area, mining affected area) with full coverage of transmission channels, and carry out targeted 24-hour monitoring on the ground. The test results show that the satellite-ground coordinated transmission line external damage monitoring and early warning in this paper. The method timely and accurately realizes the monitoring and early warning of the external breakage of the transmission line.
Long-Term Environmental Monitoring

Monitoring (from the Latin monere = to warn) is the act of following or controlling a process through a monitor and being warned if the process deviates from expectation. Environmental monitoring is the controlling of an environmental process, or ‘the intermittent surveillance to ascertain the extent of compliance with a predetermined standard or degree of deviation from an expected norm’. This means in practice a series of carefully planned, repeated observations of parameters indicating changes in a process we do not want to change. Monitoring ‘provides the essential data on how systems are changing and how fast’.