Miracle-dz/UniFAR-FTUs huggingface dataset:
Integral impact of PVT variation with NBTI degradation on dynamic and static SRAM performance metrics

ABSTRACT Advanced CMOS technology is highly susceptible to ageing effects such as negative bias temperature instability (NBTI) and process variability. This article focuses on investigating the ‘combined impact’ of NBTI degradation along with the process, voltage and temperature (PVT) variations on SRAM metrics. These issues impact the performance of SRAM (Static Random Access Memory) cell in many ways but the two main dynamic metrics are critical read-stability and write-ability. The dynamic metrics can, in turn, be characterised by their static metrics, that determine the static noise margins (SNM) of SRAM. The dynamic metrics were analysed for symmetric and asymmetric NBTI degradation of two inverters of SRAM. NBTI degradations were incorporated on the pull-up transistors of SRAM cell. Furthermore, results of the correlated performance metrics are presented for varied data storage patterns in SRAM cell over its lifetime. This analysis aims to provide an insight into the effects of integrated PVT and NBTI degradation on SRAM cell performance, enabling robust designs and help designers at the early stage of design to mitigate system failure.
AGORA: Automated Generation of Test Oracles for REST APIs

Test case generation tools for REST APIs have grown in number and complexity in recent years. However, their advanced capabilities for automated input generation contrast with the simplicity of their test oracles, which limit the types of failures they can detect to crashes, regressions, and violations of the API specification or design best practices. In this paper, we present AGORA, an approach for the automated generation of test oracles for REST APIs through the detection of invariants—properties of the output that should always hold. In practice, AGORA aims to learn the expected behavior of an API by analyzing previous API requests and their corresponding responses. For this, we extended the Daikon tool for dynamic detection of likely invariants, including the definition of new types of invariants and the implementation of an instrumenter called Beet. Beet converts any OpenAPI specification and a collection of API requests and responses to a format processable by Daikon. As a result, AGORA currently supports the detection of up to 105 different types of invariants in REST APIs. AGORA achieved a total precision of 81.2% when tested on a dataset of 11 operations from 7 industrial APIs. More importantly, the test oracles generated by AGORA detected 6 out of every 10 errors systematically seeded in the outputs of the APIs under test. Additionally, AGORA revealed 11 bugs in APIs with millions of users: Amadeus, GitHub, Marvel, OMDb and YouTube. Our reports have guided developers in improving their APIs, including bug fixes and documentation updates in GitHub. Since it operates in black-box mode, AGORA can be seamlessly integrated into existing API testing tools.
Seasonal discharge response to temperature-driven changes in evaporation and snow processes in the Rhine Basin

Abstract. This study analyses how temperature-driven changes in evaporation and snow processes influence the discharge in the Rhine Basin. Using an efficient distributed hydrological model at high spatio-temporal resolution, we performed two experiments to understand how changes in temperature affect the discharge. In the first experiment, we compared two 10-year periods (1980s and 2010s) to determine how changes in discharge can be related to changes in evaporation, snowfall, melt from snow and ice, and precipitation. By simulating these periods, we can exchange the forcing components (evaporation, temperature for snowfall and melt, and precipitation), to quantify their individual and combined effects on the discharge. Around half of the observed changes could be explained by the changes induced by temperature effects on snowfall and melt (10 %), temperature effects on evaporation (16 %), and precipitation (19 %), showing that temperature-driven changes in evaporation and snow (26 %) are larger than the precipitation-driven changes (19 %). The remaining 55 % was driven by the interaction of these variables: e.g. the type of precipitation (interaction between temperature and precipitation) or the amount of generated runoff (interaction between evaporation and precipitation). In the second experiment we exclude the effect of precipitation and run scenarios with realistically increased temperatures. These simulations show that discharge is generally expected to decrease due to the positive effect of temperature on (potential) evaporation. However, more liquid precipitation and different melt dynamics from snow and ice can slightly offset this reduction in discharge. Earlier snowmelt leaves less snowpack available to melt during spring, when it historically melts, and amplifies the discharge reduction caused by the enhanced evaporation. These results are tested over a range of rooting depths. This study shows how the combined effects of temperature-driven changes affect discharge. With many basins around the world depending on meltwater, a correct understanding of these changes and their interaction is vital.
Machine Learning in Chronic Pain Research: A Scoping Review

Given the high prevalence and associated cost of chronic pain, it has a significant impact on individuals and society. Improvements in the treatment and management of chronic pain may increase patients’ quality of life and reduce societal costs. In this paper, we evaluate state-of-the-art machine learning approaches in chronic pain research. A literature search was conducted using the PubMed, IEEE Xplore, and the Association of Computing Machinery (ACM) Digital Library databases. Relevant studies were identified by screening titles and abstracts for keywords related to chronic pain and machine learning, followed by analysing full texts. Two hundred and eighty-seven publications were identified in the literature search. In total, fifty-three papers on chronic pain research and machine learning were reviewed. The review showed that while many studies have emphasised machine learning-based classification for the diagnosis of chronic pain, far less attention has been paid to the treatment and management of chronic pain. More research is needed on machine learning approaches to the treatment, rehabilitation, and self-management of chronic pain. As with other chronic conditions, patient involvement and self-management are crucial. In order to achieve this, patients with chronic pain need digital tools that can help them make decisions about their own treatment and care.
The Effect of the Soil Properties on Adsorption, Single-Point Desorption, and Degradation of Chlorpyrifos in Two Agricultural Soil Profiles From Colombia

Abstract Structural composition of soil organic matter and the adsorption/desorption characteristics of the insecticide chlorpyrifos were investigated in two soil profiles (Andisol and Entisol) under agriculture production using Fourier transform infrared spectroscopy, nuclear magnetic resonance, and batch analysis methods. Throughout the soil profile, the Andisol had larger values of pH, organic carbon content, cation exchange capacity (CEC), and effective CEC than the Entisol. The Entisol showed larger amounts of kaolinite and ferric and/or aluminum oxides in deeper soil layers. Soil organic matter carbonyl-C, aryl-C, O-alkyl C, and alkyl-C were transported vertically in the vadose zone, with aryl-C being the predominant species in both soils. These results suggest that aryl-C is a reasonable predictor of chlorpyrifos adsorption properties under tropical conditions. Chlorpyrifos adsorption was found to be spontaneous and exothermic, with decreasing adsorption values of the distribution coefficient Kd (37.2–10.1 L kg−1) in the deeper layers of both soil types (although more significant in the Entisol). One-step desorption hysteresis showed a monotonic decrease with increasing soil depth and correlated positively with both organic carbon and CEC. The degradation of chlorpyrifos in Andisol (0–100 cm) was investigated using a laboratory incubation method. Degradation rate k was found to be approximately constant (0.011–0.015 d−1) throughout the soil profile where biotic and abiotic processes are active. Based on the Groundwater Ubiquity Score, chlorpyrifos presented a “transitional” leaching potential with soil depth.
Review of Mechanical Characterization Techniques for Thin Films Used in Flexible Electronics

ABSTRACT Until the past few years, failure of flexible devices has mostly been studied through performance tests or durability tests under cyclic loading but as they rapidly grow into mainstream products it has become mandatory to find the underlying reasons resulting in their failure towards fabrication of reliable and longer lasting devices. Failure of flexible devices can be attributed to either failure of individual layers or interface failure. This article covers characterization techniques for measuring interfacial adhesion and mechanical properties of thin films, specifically those on flexible substrates.
Multiband pass FIR integrator based on prediction and forecasting of coefficients

ABSTRACT In this paper, a novel technique to design Multiband Pass Integrator (MPI) will be presented. This novel technique involves the implementation of the MPI using the approximation of equations abstracted from Z-Transform using sine and cosine function, and . The weights of the integrator are made dependable of the same sine and cosine function. After that, a model is predicted from the integrator weights having minimum error-related ideal integrator. Then, using this model, future values of the weight coefficients of integrator are forecasted for higher frequencies. The relative error for and are found to be in the range of 0.09 0.08 and 0.082 0.078.
Age Group and Gender Classification from Facial Images Based on Deep Neural Network Fusion

Akilli uygulamalar hizla gelismesi sistemlerin yapay zekâya dayali otomatik cikarimlar yapmasinin onunu acmis ve arastirmanin bu alana dogru kaymasina neden olmustur. Insan yuzu bu acidan onemlidir. Cunku duygu, ifade, yas, cinsiyet gibi bircok ozellik bundan elde edilebilir. Bu makalede yuz goruntulerinden yas ve cinsiyet siniflandirmasi uzerine bircok arastirmalar yapilmistir. Evrisimsel sinir agi tabanli bircok algoritma cesitli transfer ogrenme yontemleri ile egitilmis ve sistemin performansinin artmasi icin bircok modifikasyonlar yapilmistir. Ozellikle modellerden elde edilen sonuclar fuzyon yapilarak onerilen yontemin basarisi artirilmistir. Calismada onerilen yontemin basarisini olcmek icin Adience veri seti kullanilmistir. Bu veri seti filtrelenmemis gercek hayat fotograflarindan olusturulmustur ve bu nedenle dusuk goruntu kalitesine sahip goruntuler icermektedir. Elde edilen deneysel sonuclara gore onerilen yontemin dogruluk performansi cinsiyet ve yas siniflandirmasi icin sirasiyla %92,29 ve %60,26 olarak bulunmustur
Principles of Sustainable Agriculture: Defining Standardized Reference Points

No question remains regarding our need to change toward sustainable agriculture. When ranking the industries that have more prevalent environmental impacts, agriculture holds a considerable share of responsibility. However, as sustainability is an ambiguous concept surrounded by controversy and debate, rather than attempt to describe its meaning through a single universal definition, we instead stressed the need to delineate a set of fundamental principles. With the goal of putting the sustainable-agriculture concept into practice, an inductive qualitative content analysis was employed based on multivariate methods on hundreds of different definitions, theories, notions and sustainability indicators gathered through a deep-structured literature review. Through this novel approach, we were able to identify four fundamental principles for sustainable agriculture (integrated management, dynamic balance, regenerative design, and social development), and concluded that in order to shift our current agricultural systems into more efficient and sustainable ones, we need to start making better use of natural and human resources. This work provides guidelines for reference that can be used by anyone whenever they make a decision regarding sustainable agriculture or apply a methodology to assess a particular behavior, process or situation.
Applying Behavioral Science in Combating COVID-19 at the Workplace: A Narrative Review

In the absence of a vaccine, the adoption of responsible behavior is critical to the fight against COVID-19. Practicing preventive etiquettes such as hand washing, hand disinfection, wearing a face mask, practicing physical distancing, disinfection of surfaces and objects can help curb the transmission of the virus at the workplace. This paper focuses on interventions and behaviors required to curb the spread of COVID-19 at workplaces. We undertook a detailed multi-disciplinary literature search on the following topics: hand hygiene, respiratory hygiene, physical distancing, quarantine and isolation, disinfection of objects and surfaces, behavior change, and health crisis communication. We identified interventions that are effective for preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) at workplaces. These findings present very useful non-clinical interventions for preventing COVID-19 in the work environment.
Redox‐Flow‐Batterien: von metallbasierten zu organischen Aktivmaterialien

Die Forschung auf dem Gebiet der Redox-Flow-Batterie (RFB) erlebt momentan einen signifikanten Aufschwung, der durch den wachsenden Bedarf angetrieben wird, immer grosere Elektrizitatsmengen aus erneuerbaren Quellen zwischenzuspeichern. RFBs sind vielversprechende Kandidaten, um in Kombination mit Photovoltaik- und Windkraftanlagen sogenannte “Smart Grids” (d. h. intelligente Stromnetze) aufzubauen. Um das Ziel eines “grunen”, sicheren und kostengunstigen Energiespeichers zu erreichen, wurde in den vergangen Jahren der Fokus von metallbasierten Materialien mehr und mehr auf organische Aktivmaterialien verlagert. In diesem Aufsatz wird eine Ubersicht uber verschiedene Flow-Batterie-Systeme gegeben. Dafur werden relevante Beitrage uber die Geschichte dieser Systeme diskutiert und die Entwicklung innerhalb der letzten Jahre von klassischen, anorganischen uber organisch/anorganische hin zu Redox-Flow-Batterien, welche innerhalb des Katholyten und Anolyten redoxaktive organische Materialien nutzen, aufgezeigt. Wir analysieren die verfugbaren Technologien in Bezug auf deren technische, okonomische und umweltbezogene Aspekte und diskutieren Vorteile und Beschrankungen dieser Systeme. Zum Abschluss werden weitere technologische Herausforderungen und potenzielle Forschungsmoglichkeiten erortert.
Exploring the impact of ethnocentrism on country and brand image: the case of Peugeot

Purpose – It is important to determine the ethnocentric tendencies of Turkish consumers and to reveal the effects of these tendencies on a foreign country and its brand. The aim of this paper is to explore the impact of ethnocentric tendencies of individuals trained in Turkish culture affect the image of a foreign country and its products. For this purpose, research has been carried out on the Peugeot brand of France origin, which is one of the best-selling automobile brands in Turkey. Methodology Data was collected from 400 people by face to face in the city center of Eskisehir. As the research was conducted only in one city, it does not cover all Turkish consumers. In terms of measurement, country image scale, country product image scale and the CETSCALE were used. In this study Structural Equation Modeling (SEM), t test and ANOVA were performed. FindingsThe ethnocentric tendency of Turkish consumers and other relationships were tested with the hypotheses H1, H2, H3a, H3b, H4, H5a, H5b, H6a and H6b. According to the findings, H1, H4, H5b, H6a, H6b were supported but, H2, H3a, H3b and H5a were not supported. ConclusionThe ethnocentric tendency of customers affects only the image of the country of origin, in this case, it negatively affects the image of France. However, it doesn’t affect the general image of French products and brand image statistically. Also, general image of country products and France’s image positively and significantly affects brand image.
Team Psychological Needs and Radical versus Incremental Creativity of Work Teams

ABSTRACT This study distinguishes between radical and incremental creativity at the team level. In addition, group composition in terms of members’ psychological needs is identified as a distinct driver of radical and incremental team creativity. Statistical analysis based on multisource data of 65 work teams shows that (a) team-level need for achievement has a negative main effect on radical team creativity, which disappears in teams with optimistic leaders; (b) team-level need for affiliation has a negative main effect on incremental team creativity, which becomes positive when teams possess high social competence; and (c) team-level need for power is positively related to radical and incremental team creativity. Our analysis demonstrates the multifaceted nature of team creativity and the distinct implications of team-level psychological needs for team creativity.
Investigation on hemolytic effect of poly(lactic co-glycolic) acid nanoparticles synthesized using continuous flow and batch processes

Abstract With the increasing interest in polymeric nanoparticles for biomedical applications, there is a need for continuous flow methodologies that allow for the precise control of nanoparticle synthesis. Poly(lactide-co-glycolic) acid (PLGA) nanoparticles with diameters of 220–250 nm were synthesized using a lab-on-a-chip, exploiting the precise flow control offered by a millifluidic platform. The association and the effect of PLGA nanoparticles on red blood cells (RBCs) were compared for fluorescent PLGA nanoparticles made by this novel continuous flow process using a millifluidic chip and smaller PLGA nanoparticles made by a batch method. Results indicated that all PLGA nanoparticles studied, independent of the synthesis method and size, adhered to the surface of RBCs but had no significant hemolytic effect at concentrations lower than 10 mg/ml.
COVID-19 and Depression from the Nigerian Perspective; A Mini Review

Context: The outbreak of the highly infectious COVID-19 has led to a global public health and economic crisis, especially in developing countries. Due to the global burden and spread and the high mortality rate of the virus, as well as an inadequate mental health care system in Nigeria, inhabitants often experience fear, depression, and anxiety that, if left unaddressed, may lead to long-term consequences. Although depression was a concerning issue in Nigeria before COVID-19, the pandemic has caused a surge in depression cases. This review highlighted the possible causes of depression among Nigerians during the COVID-19 pandemic and identified potential mitigating interventions to prevent depression. Evidence Acquisition: We searched PubMed for the articles published from January 2019 to September 2020 using the terms of “depression”, “COVID-19”, and “Nigeria”. The articles resulting from these searches and the relevant references cited in those articles were reviewed. Results: Nigerians are likely to fall into depression due to the challenges and limitations affecting the economy and development of Nigeria. Conclusions: During the COVID-19 struggle, providing sound mental health services for individuals is imperative to maintain nations’ mental health for a more rapid recovery across various measures of societal well-being post-COVID-19.
Sexual Predators in Contest for Public Office: How the American Electorate Responds to News of Allegations of Candidates Committing Sexual Assault and Harassment

Candidate characteristics have an important impact on voter choice, and scandals are found to negatively impact a political campaign. Yet the literature, with its focus on scandals such as financial and (consensual) affairs, has failed to look into how allegations of sexual assault and harassment may impact electability. This study analyzes the effect that allegations of sexual assault or harassment have on the electoral success of American politicians. Using an original survey experiment, we find that, on average, American citizens are less likely to support a candidate accused of sexual assault or sexual harassment. However, not all voters do so to the same magnitude. We find that Democrats are significantly less likely to support a candidate that faces such allegations. Republicans do not strongly penalize candidates facing allegations of sexual assault or harassment, especially if the candidate is identified as a Republican. We analyze open-ended survey responses to offer an explanation for such variation: a propensity to disbelieve women who speak out about sexual assault and harassment explains variations in why some voters may not change their opinion of a candidate based on an allegation.
Three‐port circularly polarized MIMO antenna for WLAN application with pattern and polarization diversity

In this article, a three‐port circularly polarized (CP) multiple‐input multiple‐output (MIMO) antenna for wireless local area network (WLAN) application with pattern and polarization diversity is proposed. The proposed MIMO antenna system comprises of a broadside CP antenna element with a T‐shaped slot and two endfire CP antenna elements. Good impedance bandwidth of 16.9% and 5.5% are achieved by the broadside CP antenna and endfire CP antenna, respectively, and their corresponding axial ratio (AR) bandwidth is 7% and 10.47%. The isolation between the different antenna elements is better than 20 dB, and the polarization purity for all CP antenna is more than 25 dB along with the maximum radiation.
A DISCRETE-TIME ROBUST ADAPTIVE PI CONTROLLER FOR GRID-CONNECTED VOLTAGE SOURCE CONVERTER WITH LCL FILTER

– In this work, it is presented a new direct discrete-time robust adaptive PI (Proportional Integral) Controller for grid-injected current control loop of a voltage source converter with LCL ﬁlter. The mathematical background is based on Robust Model Reference Adaptive Control theory. However, the proposed controller is straightforward, it does not need a reference model and has capability to track directly currents reference. This approach simpliﬁes signiﬁcantly controller design, resulting in a reformulation of parameters vector used for adaptation of adjustable gains. It turns the controller robust to unmodelled dynamics, while avoid the complexity inherent to the conventional high order adaptive controllers for grid-connected power systems. Besides, it is highlighted that proposed controller does not need resonant controllers for grid disturbance rejection, or require any knowledge of grid parameters, lines impedance or load power demand. Also, due to its simple structure, it is easily implemented and does not require a high processing capacity. Furthermore, the effectiveness of the control strategy in terms of reference tracking, harmonics content and robustness to the grid impedance variation is corroborated through experiments.