Miracle-dz/UniFAR-FTUs huggingface dataset:
An Applied Statistician's Creed

SUMMARY Hypothesis testing, as performed in the applied sciences, is criticized. Then assumptions that the author believes should be axiomatic in all statistical analyses are listed. These assumptions render many hypothesis tests superfluous. The author argues that the image of statisticians will not improve until the nexus between hypothesis testing and statistics is broken.
Overlapping Reactions During Tag Questions

This article examines the form and the functions of what we label overlapping reactions. These are premature responses which overlap utterances containing a variable interrogative tag, e.g., It’s nice, isn’t it. They are orientated towards the proposition contained in the tag question. Our research is grounded in a corpus of spoken British English and, employs methods and insights from corpus linguistics, conversation analysis and phonetics. Based on the clustering of observed grammatical, discoursal and prosodic features we propose a typology of the interactional functions of overlapping responses, i.e., acknowledgements, continuers, disagreements, non-committals and turn-competitive early responses. We show that such responses are not errors but rather function as part of the well-oiled machinery of spontaneous dialogue. We show that the typology of overlaps proposed by Jefferson ([1983]. “Two Explorations of the Organization of Overlapping Talk in Conversation.” Language and Literature 28: 1–33) is unable to fully distinguish between the functional categories identified in our data. Hence we suggest that a taxonomy of overlaps must be based on the patterning of formal and functional features. Our data provide evidence that tag questions are responded to a syntagmatic wholes rather than as a sequence of two parts: anchor and tag.
MCDM methods: Practical difficulties and future directions for improvement

This paper critically reviews practical difficulties inherent in some of the existing multi-criteria decision-making methods. The paper also emphasizes why a benchmark decision situation is essential in assessing the capabilities of any multi-criteria decision-making method. The capability is in terms of accuracy in modeling the human decision-making process. Most multi-criteria decision-making methods consist of two important steps. The first step involves elicitation of preferences from the decision-maker on various criteria and alternatives of the problem. In the second step, the preferences defined by the decision-maker are aggregated. The overall score generated after aggregation is used in rank order calculation and final selection. However, if the prescriptions of multi-criteria decision-making method do not resemble actual or real decision of the very same decision-maker, then multi-criteria decision-making method failed in either capturing the true preferences of the decision-maker or in aggregating these preferences as per the expectations of the decision-maker. This paper discusses some of the latest theories of decision-making and provides three important directions to improve the descriptive aspects of multi-criteria decision analysis.
SLR: From Saltzer & Schroeder to 2021. . . 47 years of research on the development and validation of Security API recommendations

Producing secure software is challenging. The poor usability of security Application Programming Interfaces (APIs) makes this even harder. Many recommendations have been proposed to support developers by improving the usability of cryptography libraries; rooted in wider best practice guidance in software engineering and API design. In this SLR, we systematize knowledge regarding these recommendations. We identify and analyze 65 papers, offering 883 recommendations. Through thematic analysis, we identify 7 core ways to improve usability of APIs. Most of the recommendations focus on helping API developers to construct and structure their code and make it more usable and easier for programmers to understand . There is less focus, however, on documentation , writing requirements , code quality assessment and the impact of organizational software development practices . By tracing and analyzing paper ancestry, we map how this knowledge becomes validated and translated over time. We ﬁnd that very few API usability recommendations are empirically validated, and that recommendations speciﬁc to usable security APIs lag even further behind.
An Exploration of Openness in Hardware and Software Through Implementation of a RISC-V Based Desktop Computer

Open hardware and open source software platforms bring benefits to both implementers and users in the form of system adaptability and maintainability, and through the avoidance of lock-in, for example. Development of the RISC-V Instruction Set Architecture and processors during the last ten years has made the implementation of a desktop computer using open hardware, including open processors, and open source software an approaching possibility. We use the SiFive Unmatched development board and Ubuntu Linux, and the recorded experiences of system builders using the Unmatched board to explore the extent to which it is possible to create an open desktop computer. The work identifies current limitations to implementing an open computer system, which lie mainly at the interface between the operating system and hardware components. Potential solutions to the challenges uncovered are proposed, including greater consideration of openness during the early stages of product design. A further contribution is made by an account of the synergies arising from open collaboration in a private-collective innovation process.
DeltaDroid: Dynamic Delivery Testing in Android

Android is a highly fragmented platform with a diverse set of devices and users. To support the deployment of apps in such a heterogeneous setting, Android has introduced dynamic delivery—a new model of software deployment in which optional, device- or user-specific functionalities of an app, called Dynamic Feature Modules (DFMs), can be installed, as needed, after the app’s initial installation. This model of app deployment, however, has exacerbated the challenges of properly testing Android apps. In this article, we first describe the results of an extensive study in which we formalized a defect model representing the various conditions under which DFM installations may fail. We then present DeltaDroid—a tool aimed at assisting the developers with validating dynamic delivery behavior in their apps by augmenting their existing test suite. Our experimental evaluation using real-world apps corroborates DeltaDroid’s ability to detect many crashes and unexpected behaviors that the existing automated testing tools cannot reveal.
A Survey on FPGA Cybersecurity Design Strategies

This article presents a critical literature review on the security aspects of field-programmable gate array (FPGA) devices. FPGA devices present unique challenges to cybersecurity through their reconfigurable nature. The article also pays special attention to emerging system-on-chip (SoC) FPGA devices that incorporate a hard processing system (HPS) on the same die as the FPGA logic. While this incorporation reduces the need for vulnerable external signals, the HPS in SoC FPGA devices adds a level of complexity that is not present for stand-alone FPGA devices. This added complexity necessarily hands over the task of securing the device to developers. Even with standard security features in place, the HPS might still have unhindered access to the FPGA logic. A single software flaw could open up a breach that might allow an attacker to extract the FPGA’s configuration data. A robust cybersecurity strategy is thus required for developers. As such, this work aims to provide the groundwork to build a solid threat-based cybersecurity design strategy that is specially adapted to SoC FPGA devices.
The survey of the factors influencing the use of open government data in Taiwan: The preliminary findings

Recent research in open government data has indicated that data providers and data users both play important roles to form a sound open data ecosystem. Nevertheless, researchers find that the use of open government data has not kept with the expectation. Accordingly, this study adopts the constructs of UTAUT and IS Success model to investigate how open data users perceive the impacts of the influential factors, and whether open data users intend to continue their use of open government data. A survey approach through online questionnaire is employed to collect quantitative empirical data from open data users in Taiwan. The preliminary descriptive data analysis is briefly presented and discussed in this paper.
Enhancing Firms’ Financial Support Decision-Making with Predictions of Technological Resilience to Economic Crises

Economic crises of different durations, intensities and geographic scopes are often appearing in market-based economies, while at the same time the economic stability periods become shorter. They have several negative impacts on firms, which include a decrease of their technological investments in various technological resources (e.g., production equipment, ICT, etc.). This can result in firms’ technological backwardness and obsolescence, and finally lower competitiveness and growth, or even threaten the survival of many firms. At the same time, economic crises can have some positive impacts on firms as well, as they put pressure on them to exploit more efficiently their resources by rationalizing and improving the relevant processes and practices they follow for using and exploiting their resources, including the technological ones, which can have positive impacts on their competitiveness and growth. Therefore, institutions that provide financial support to firms, such as government agencies (through various government firms’ financial support programs), banks (through the provision of various kinds of loans), and institutional investors, in their relevant decision-making should take into account not only criteria concerning firms’ economic performance during normal economically stable periods but also criteria concerning their ‘technological resilience’ (with respect to their main production technologies, ICT, etc.) during economic crises periods as well. This is important because low technological resilience in economic crisis periods can result in severe technological backwardness and obsolescence, and finally lower future competitiveness and growth, and even threaten their survival. This paper proposes a methodology for enhancing government agencies’, banks’ and, institutional investors’ decision-making concerning the financial support of firms by adding to pre-existing relevant criteria predictions of firms’ technological resilience to economic crises. Having as theoretical foundation the resources and capabilities theory from the strategic management domain, we view technological resilience as a two-dimensional concept, which consists of a) the extent of reduction of technological investments during economic crises, and b) the extent of rationalization and improvement of their technological resources’ exploitation processes and practices during economic crises. These predictions are based on existing data from government agencies (Statistical Authorities), which are used to construct relevant prediction models through artificial intelligence techniques from the area of machine learning. Also, an application of this methodology is described, which gives satisfactory results.
A Systems View of Enterprise Data Governance for Artificial Intelligence Applications in Government

The government “enterprise” involves a complex set of organizations with a multitude of goals and values, serving an equally diverse group of constituents. Because of this complexity, governing Artificial Intelligence (AI) applications as well as the necessary data infrastructure to support them has proven to be a difficult task that –according to experts– requires a systems perspective in its design and implementation. In this management paper, we take a conceptual approach to respond to this call from experts by providing working definitions of both enterprise data governance and a systems approach to management. Using these working definitions and the use case of AI-driven statistical profiling, we propose a pluralistic view of systems approaches for the design and governance of AI applications in government.
The Evolution of HCI and Human Factors: Integrating Human and Artificial Intelligence

We review HCI history from both the perspective of its 1980s split with human factors and its nature as a discipline. We then revisit human augmentation as an alternative to user friendliness that seems particularly relevant in the areas of inclusive design and artificial intelligence. Viewing human-AI interaction as a kind of human augmentation raises issues such as how to promote trust and situation awareness. We also pose the question: Can HCI and human factors engineering work together to solve the increasingly urgent challenges of human-AI technology? In an initial look at this question, we contrast the different approaches of HCI and human factors on emerging AI research. This article concludes by considering other potentially promising paths for HCI. We propose more collaboration between HCI and human factors, or related disciplines, in the future to address the massive challenges posed by the rapid growth in data science and artificial intelligence.
Conceptual challenges of researching Artificial Intelligence in public administrations

Research has been advancing on the development and deployment of Artificial Intelligence (AI) in public administrations. However, there is limited consensus and agreement on what is considered Artificial Intelligence, as different understandings and approaches in research and practice exist. This paper explores and compares the varying ways AI has been described and understood in previous Information Systems and eGovernment research. Following, a survey amongst Belgium civil servants is analysed to assess what they associate with the term Artificial Intelligence. The findings show that many civil servants tend to associate AI with being able to conduct intelligent tasks, have certain capabilities or are specific applications they are familiar with. Specific algorithms or learning methods, often included in research papers, are not associated with the term AI. These results show that researchers and policymakers may have opposite or even paradoxical views on what is or is not AI, which could have significant consequences for researching the adoption of AI in government, as well as comparing different research findings. In this respect, the paper proposes to use an integrative lens to study AI in government, by including different dimensions and understandings.
Alinhamento múltiplo progressivo de sequências de proteínas

O alinhamento multiplo dc sequencias e uma tarefa de grande relevância cm Bioin-formatica. Atraves dele e possivel estudar eventos evolucionarios c restricoes estruturais ou funcionais, sejam de sequencias de proteina, DNA ou RNA, tornando possivel entender a estrutura, funcao c evolucao dos genes que compoem um organismo. O objetivo do alinhamento multiplo e a melhor representacao do cenario dc evolucao das sequencias ao longo do tempo, considerando a possibilidade dc ocorrerem diferentes eventos de mutacao. Encontrar um alinhamento multiplo dc sequencias otimo e um problema NP-Dificil. Desta forma, diversas abordagens tem sido desenvolvidas no intuito de encontrar uma solucao heuristica que represente da melhor maneira possivel o cenario dc evolucao real, dentre elas esta a abordagem progressiva. O alinhamento progressivo c uma das maneiras mais simples dc se realizar o alinhamento multiplo, pois utiliza pouco tempo c memoria computacional. Ele c realizado cm tres etapas principais: determinar a distância entre as sequencias que serao alinhadas, construir uma arvore guia a partir das distâncias c finalmente construir o alinhamento multiplo. Este trabalho foi desenvolvido a partir do estudo de diferentes metodos para realizar cada etapa dc um alinhamento progressivo. Foram construidos 342 alinhadores resultantes da combinacao dos metodos estudados. Os parâmetros dc entrada adequados para a maioria dos alinhadores foram determinados por estudos empiricos. Apos a definicao dos parâmetros adequados para cada tipo dc ahnhador, foram realizados testes com dois subconjuntos de referencia do BAliBASE. Com esses testes observamos que os melhores alinhadores foram aqueles que utilizam o agrupamento dc perfil para gerar o alinhamento multiplo, com destaque paTa os que utilizam pontuacao afim para penalizar buracos. Observamos tambem, que dentre os alinhadores dc agrupamento por consenso, os que utilizam funcao logaritmica, para penalizar buracos demonstraram melhores desempenhos Abstract
Structural and electrical study of nanocomposite Fe0.2Ni00.3Cu0.5 anode with effect of graphene oxide (GO) for low‐temperature SOFCs

Solid oxide fuel cell (SOFC) found to be promising alternative energy conversion technology due to its higher efficiency, flexibility of fuel uses and environment friendly. However, conventional SOFC requires high operational temperature, increasing the cost and degradation of the cell components. The current work demonstrates the synthesis of nanocomposite Fe0.2Ni00. 3Cu0.5 by solid state method to be studied as anode for low‐temperature SOFC. Due to the earnest effect of graphene and its derivatives, graphene oxide (GO) has been incorporated in order to enhance the properties of the prepared Fe0.2Ni00. 3Cu0.5 anode to lower the operating temperature, at reduced cost for market acceptability. The crystal structure and surface morphology of prepare material was investigated by X‐ray diffraction (XRD) and scanning electron microscopy (SEM). Thermal gravitational analysis TGA and Fourier transform infrared FTIR were further employed to observe the thermal and functional behavior of prepared materials. The crystalline size was found to be 17‐41 nm and results were validated by SEM analysis. Conductivity measurements were carried out by DC four‐probe method in temperature range 300°C to 600°C and maximum conductivity was calculated as 43 S/cm. The peak power density of fuel cell has been achieved as 529 mW/cm2 for Fe0.2Ni00. 3Cu0.5 incorporated with 1.5 wt. % GO using H2 fuel which is enhanced value comparable to the base composite. The graphene‐incorporated FNC materials can be suggested as the cost‐effective potential candidate as anode for low‐temperature SOFC.
Discovery of a novel monoclonal PD-L1 antibody H1A that promotes T-cell mediated tumor killing activity in renal cell carcinoma

In the last decade, the therapeutic landscape of renal cell carcinoma has rapidly evolved with the addition of PD-1/PD-L1 immune checkpoint inhibitors in the armamentarium of oncologists. Despite clinical evidence of improved oncological outcomes, only a minority of patients experience long-lasting antitumor immune response and complete response. The intrinsic and acquired resistance to PD-1/PD-L1 immune checkpoint blockade is an important challenge for patients and clinicians as no reliable tool has been developed to predict individualized response to immunotherapy. In this study, we demonstrate the translational relevance of an ex-vivo functional assay that measure the tumor cell killing ability of patient-derived CD8 T cells isolated from peripheral blood. Cytotoxic activity of CD8 T cells was improved at 3-month post-radical nephrectomy compared to baseline and it was associated with higher circulating levels of tumor-reactive effector CD8 T cells (CD11ahighCX3CR1+GZMB+). Pretreatment of peripheral immune cells with FDA-approved PD-1/PD-L1 inhibitors enhanced tumor cell killing activity of CD8 T cells but differential response was observed at the individual patient level. Finally, we found a newly developed monoclonal antibody (H1A), which induces PD-L1 degradation, demonstrated superior efficacy in promoting T-cell mediated tumor killing activity compared to FDA-approved PD-1/PD-L1 inhibitors. PBMC immunophenotyping by mass cytometry revealed enrichment of effector CD8 T cells in H1A-treated PBMC. To conclude, our study lays the ground for future investigation of the therapeutic value of H1A as a next-generation immune checkpoint inhibitor. Furthermore, further work is needed to evaluate the potential of measuring T-cell cytotoxicity activity as a tool to predict individual response to immune checkpoint inhibitors in patients with advanced renal cell carcinoma.
Perceptual learning improves discrimination while distorting appearance

Perceptual sensitivity often improves with training, a phenomenon known as ‘perceptual learning’. Another important perceptual dimension is appearance, the subjective sense of stimulus magnitude. Are training-induced improvements in sensitivity accompanied by more accurate appearance? Here, we examine this question by measuring both discrimination and estimation capabilities for nearhorizontal motion perception, before and after training. Observers trained on either discrimination or estimation exhibited improved sensitivity, along with increases in already-large estimation biases away from horizontal. To explain this counterintuitive finding, we developed a computational observer model in which perceptual learning arises from changes in the precision of underlying neural representations. For each observer, the fitted model accounted for both discrimination performance and the distribution of estimates, and their changes after training. Our empirical findings and modeling suggest that learning enhances distinctions between categories, a potentially important aspect of real-world perception and perceptual learning.
Alternatively Spliced Landscape of PPARγ mRNA in Podocytes Is Distinct from Adipose Tissue

Podocytes are highly differentiated epithelial cells, and their structural and functional integrity is compromised in a majority of glomerular and renal diseases, leading to proteinuria, chronic kidney disease, and kidney failure. Traditional agonists (e.g., pioglitazone) and selective modulators (e.g., GQ-16) of peroxisome-proliferator-activated-receptor-γ (PPARγ) reduce proteinuria in animal models of glomerular disease and protect podocytes from injury via PPARγ activation. This indicates a pivotal role for PPARγ in maintaining glomerular function through preservation of podocytes distinct from its well-understood role in driving insulin sensitivity and adipogenesis. While its transcriptional role in activating adipokines and adipogenic genes is well-established in adipose tissue, liver and muscle, understanding of podocyte PPARγ signaling remains limited. We performed a comprehensive analysis of PPARγ mRNA variants due to alternative splicing, in human podocytes and compared with adipose tissue. We found that podocytes express the ubiquitous PPARγ Var 1 (encoding γ1) and not Var2 (encoding γ2), which is mostly restricted to adipose tissue and liver. Additionally, we detected expression at very low level of Var4, and barely detectable levels of other variants, Var3, Var11, VartORF4 and Var9, in podocytes. Furthermore, a distinct podocyte vs adipocyte PPAR-promoter-response-element containing gene expression, enrichment and pathway signature was observed, suggesting differential regulation by podocyte specific PPARγ1 variant, distinct from the adipocyte-specific γ2 variant. In summary, podocytes and glomeruli express several PPARγ variants, including Var1 (γ1) and excluding adipocyte-specific Var2 (γ2), which may have implications in podocyte specific signaling and pathophysiology. This suggests that new selective PPARγ modulators can be potentially developed that will be able to distinguish between the two forms, γ1 and γ2, thus forming a basis of novel targeted therapeutic avenues.