Miracle-dz/UniFAR-FTUs huggingface dataset:
Incrementality and effect simulation in the simply typed lambda calculus

Certified programming is a framework in which any program is correct by construction. Proof assistants and dependently typed programming languages are the representatives of this paradigm where the proof and implementation of a program are done at the same time. However, it has some limitations: a program in Type Theory is built only with pure and total functions. Our objective is to write efficient and certified programs. The contributions of this work are the formalization, in the Simply Typed Lambda Calculus, of two mechanisms to achieve efficiency: to validate impure computations and to optimize computations by incrementality. An impure computation, that is a program with effects, and its validation in a functional and total language is done through a posteriori simulation. The simulation is performed afterwards on a monadic procedure and is guided by a prophecy. An efficient oracle is responsible for producing prophecies which is actually, the monadic procedure itself translated into an effectful programming language. The second contribution is an optimization to perform incremental computations. Incrementality as a way to propagate an input change into a corresponding output change is guided by formal change descriptions over terms and dynamic differentiation of functions. Displaceable types represent data-changes while an extension of the simply typed lambda calculus with differentials and partial derivatives offers a language to reason about incrementality.
Pump laser-induced space-charge effects in HHG-driven time- and angle-resolved photoelectron spectroscopy

With the advent of ultrashort-pulsed extreme ultraviolet sources, such as free-electron lasers or high-harmonic-generation (HHG) sources, a new research field for photoelectron spectroscopy has opened up in terms of femtosecond time-resolved pump-probe experiments. The impact of the high peak brilliance of these novel sources on photoemission spectra, so-called vacuum space-charge effects caused by the Coulomb interaction among the photoemitted probe electrons, has been studied extensively. However, possible distortions of the energy and momentum distributions of the probe photoelectrons caused by the low photon energy pump pulse due to the nonlinear emission of electrons have not been studied in detail yet. Here, we systematically investigate these pump laser-induced space-charge effects in a HHG-based experiment for the test case of highly oriented pyrolytic graphite. Specifically, we determine how the key parameters of the pump pulse—the excitation density, wavelength, spot size, and emitted electron e.
The Elastic-Viscoelastic Correspondence Principle and Parameter Identification

This paper presents an identification method for viscoelastic materials employing the wavelet analysis. The proposed inverse analysis is based on elastic-viscoelastic correspondence principle for linear viscoelastic materials, and two-dimensional discrete wavelet analysis is applied to the system matrix of the iteration equation for identifying viscoelastic materials. The elastic-viscoelastic correspondence principle [1] is that the Laplace time-transformed viscoelastic field equations and boundary conditions are formally identical with the equations for an elastic body of the same geometry. Therefore, identification analysis of viscoelastic materials can be converted to an ’associated’ elastic problem in the Laplace domain [2]. By applying the discrete wavelet transform to the system matrix, we estimate unknown material parameters for not only overdetermined systems and determined systems, but also underdetermined systems. Numerical example is calculated to investigate the validity of the method.
GAPDH Released from Lactobacillus johnsonii MG Enhances Barrier Function by Upregulating Genes Associated with Tight Junctions

Extracellular glyceraldehyde-3-phosphate dehydrogenase (GAPDH) has multiple interactions with various gut epithelial components. For instance, GAPDH in Lactobacillus johnsonii MG cells interacts with junctional adhesion molecule-2 (JAM-2) in Caco-2 cells and enhances tight junctions. However, the specificity of GAPDH toward JAM-2 and its role in the tight junctions in Caco-2 cells remain unclear. In the present study, we assessed the effect of GAPDH on tight junction regeneration and explored the GAPDH peptide fragments required for interaction with JAM-2. GAPDH was specifically bound to JAM-2 and rescued H2O2-damaged tight junctions in Caco-2 cells, with various genes being upregulated in the tight junctions. To understand the specific amino acid sequence of GAPDH that interacts with JAM-2, peptides interacting with JAM-2 and L. johnsonii MG cells were purified using HPLC and predicted using TOF–MS analysis. Two peptides, namely 11GRIGRLAF18 at the N-terminus and 323SFTCQMVRTLLKFATL338 at the C-terminus, displayed good interactions and docking with JAM-2. In contrast, the long peptide 52DSTHGTFNHEVSATDDSIVVDGKKYRVYAEPQAQNIPW89 was predicted to bind to the bacterial cell surface. Overall, we revealed a novel role of GAPDH purified from L. johnsonii MG in promoting the regeneration of damaged tight junctions and identified the specific sequences of GAPDH involved in JAM-2 binding and MG cell interaction.
Genetic and Epigenetic Host–Virus Network to Investigate Pathogenesis and Identify Biomarkers for Drug Repurposing of Human Respiratory Syncytial Virus via Real-World Two-Side RNA-Seq Data: Systems Biology and Deep-Learning Approach

Human respiratory syncytial virus (hRSV) affects more than 33 million people each year, but there are currently no effective drugs or vaccines approved. In this study, we first constructed a candidate host–pathogen interspecies genome-wide genetic and epigenetic network (HPI-GWGEN) via big-data mining. Then, we employed reversed dynamic methods via two-side host–pathogen RNA-seq time-profile data to prune false positives in candidate HPI-GWGEN to obtain the real HPI-GWGEN. With the aid of principal-network projection and the annotation of KEGG pathways, we can extract core signaling pathways during hRSV infection to investigate the pathogenic mechanism of hRSV infection and select the corresponding significant biomarkers as drug targets, i.e., TRAF6, STAT3, IRF3, TYK2, and MAVS. Finally, in order to discover potential molecular drugs, we trained a DNN-based DTI model by drug–target interaction databases to predict candidate molecular drugs for these drug targets. After screening these candidate molecular drugs by three drug design specifications simultaneously, i.e., regulation ability, sensitivity, and toxicity. We finally selected acitretin, RS-67333, and phenformin to combine as a potential multimolecule drug for the therapeutic treatment of hRSV infection.
Nonlinear interacting particle filter algorithm

In state estimation problem of nonlinear non-Gaussian systems,the analytical form of the posterior density function is hard to gain,so the common particle filter employs state transition density function as importance proposal distribution without considering the latest observation.For the above problem,a nonlinear interacting multiple model method is developed.The method is used to generate the importance density function(importance proposal distribution),based on which a modified particle filter,nonlinear interacting particle filter,is proposed.The new importance proposal distribution takes the latest observation into considerations,which makes it much more close to the posterior density function.Experiments show the effectiveness of the proposed algorithm.
Corection of the Jicamarca electron‐ion temperature ratio problem: Verifying the effect of electron Coulomb collisions on the incoherent scatter spectrum

Ever since the first attempts to fit Jicamarca autocorrelation function (ACF) measurements in the 1970s using a full nonlinear least squares analysis, an apparent electron-ion temperature ratio below unity has been deduced for a large portion of the F region data. The cause of this unexpected and geophysically unreasonable result has been a mystery until recently, when Sulzer and Gonzalez [1999] (herein SG) explained how electron Coulomb collisions can distort, or narrow, the incoherent backscatter spectrum, and that for this narrowing to be observable two conditions must be met. First, the radar k vector must lie in a small range near perpendicular to the magnetic field, and second, the radar wavelength must be sufficiently long. Both of these conditions are true at Jicamarca. The accurate calculations from the SG theory are now available in a compact library, which we have incorporated into an incoherent scatter least squares fitting code. Using this code, we have reduced Jicamarca ACF data taken with the Faraday double-pulse mode, and find that the SG theory correctly interprets the ACF data from Jicamarca, thereby solving the longstanding Te/Ti ratio problem and thus allowing accurate electron and ion temperature measurements.
An Method and Corresponding Arithmetic of Initial Orbit Determination based on Sparse Space-based Angle Measurements

Model and algorithm for initial orbit determination based on sparse space-based angle measurements are discussed in this article.Above all,the double ρ iteration,a new model of space-based initial orbit determination,is put forward to remedy invalidations of the traditional ground Laplace and Gauss methods.Then,adjustable-scale algorithm and genetic algorithm are focused to solve the problem.The numerical simulations in the end show that the double ρ iteration model can overcome the drawbacks of the traditional ground methods and the adjustable-scale algorithm is able to solve more than 90% cases and the modified genetic algorithm is a potent supplement.The combination of two algorithms would be perfect.
Tools of the Trade: Image Analysis Programs for Confocal Laser-Scanning Microscopy Studies of Biofilms and Considerations for Their Use by Experimental Researchers

Confocal laser-scanning microscopy (CLSM) is the bedrock of the microscopic visualization of biofilms. Previous applications of CLSM in biofilm studies have largely focused on observations of bacterial or fungal elements of biofilms, often seen as aggregates or mats of cells. However, the field of biofilm research is moving beyond qualitative observations alone, toward the quantitative analysis of the structural and functional features of biofilms, across clinical, environmental, and laboratory conditions. In recent times, several image analysis programs have been developed to extract and quantify biofilm properties from confocal micrographs. These tools not only vary in their scope and relevance to the specific biofilm features under study but also with respect to the user interface, compatibility with operating systems, and raw image requirements. Understanding these considerations is important when selecting tools for quantitative biofilm analysis, including at the initial experimental stages of image acquisition. In this review, we provide an overview of image analysis programs for confocal micrographs of biofilms, with a focus on tool selection and image acquisition parameters that are relevant for experimental researchers to ensure reliability and compatibility with downstream image processing.
Optimization of Caviar-Like Hydrogel Beads Containing Melanin-Free Cuttlefish Ink: Physicochemical Characterization

ABSTRACT MFI was extracted from cuttlefish (Sepia officinalis) and used as a colorant, flavoring, and bioactive compound in caviar-like hydrogel beads. The production parameters, including alginate, salt (NaCl), MFI concentration, and pH, were optimized using response surface methodology. The physicochemical properties of beads produced at optimum conditions (NaCl: 2%, alginate: 1.25%, pH: 8.12, and MFI: 1.39%) were compared with commercial lumpfish (Cyclopterus lumpus) caviar. The analyses showed no significant difference between caviar-like beads and commercial lumpfish caviar. These results suggest that caviar-like beads produced under optimum conditions can be commercialized at low cost to provide an opportunity for sustainable aquaculture.
Precooling and cold storage effects on antioxidant system in calla lily postharvest

ABSTRACT Low-temperature storage is one of the most effective techniques to maintain the quality and durability of cut flowers. Both quality maintenance and durability are dependent on plant metabolism factors such as antioxidant system. The objective was to evaluate the effect of low-temperature on precooling and storage after harvest, on the metabolism of calla lily [Zantedeschia aethiopica (L.) K. Spreng] concerning the antioxidant system, levels of hydrogen peroxide (H2O2), and malondialdehyde (MDA). Therefore, different storage temperatures (4 ºC and 21 ºC) were tested as well as the effect of precooling in different periods (0 to 24 hours). It was observed that the activity of catalase (CAT) and superoxide dismutase (SOD) was increased at 4 °C, as well as inflorescence durability in the commercial standard (around 12 days). At 21 °C, the content of H2O2 and MDA was higher and the visual quality reduction in the inflorescence was accelerated. Low-temperature leads to a higher activity of the enzymes of the antioxidant system (CAT and SOD) and increases postharvest longevity for calla lily. Precooling did not influence the visual quality and longevity of calla lily. Long-term exposure periods at low temperatures, with 12 and 24 hours of precooling caused stress, evidenced higher MDA levels and higher CAT activity. SOD activity was related to low temperature and shorter precooling periods resulted in better antioxidant system activity and lower MDA levels.
Influence of UI, UX and E-Service Quality on Tokopedia Purchase Via Perceived Risk

The development of technology and information have led to increase shopping activity on many e-commerce, especially in Indonesia. Tokopedia, one of the largest e-commerce in Indonesia, experienced a surge in transactions with high purchasing decisions. A high purchase decision indicates that the product or service has succeeded in attracting the attention of consumers and is related to engagement in choosing and making decisions to buy goods or use services. UI Design, UX Design and e-ServQual are the first aspects consumers feel when opening an application before making a purchase. Therefore, this research was conducted to determine the relationship between UI, UX, e-ServQual, Perceived Risk and Purchase Decision which are used as latent variables of this research. This study adopted a correlational research design and analysis was carried out using PLS-SEM method with SmartPLS 4.0 software. There are 114 respondents with various backgrounds and ages from all over Indonesia who use the Tokopedia mobile application. The results revealed that the factor that most influenced the purchasing decisions was e-ServQual with the indicator "The entire process of using the application is efficient". Furthermore, the factor that most influences perceived risk is UX Design, even though perceived risk does not have a mediating effect on purchasing decisions and become a gap in this study. The study suggested further studies to be conducted to relate the variables.
Alternating direction methods for non convex optimization with applications to second-order least-squares and risk parity portfolio selection

In this paper we mainly focus on optimization of sums of squares of quadratic functions, which we refer to as second-order least-squares problems, subject to convex constraints. Our motivation arises from applications in risk parity portfolio selection. We generalize the setting further by considering a class of nonlinear, non convex functions which admit a (non separable) two-block representation with special structure. We then develop alternating direction and alternating linearization schemes for such functions and analyze their convergence and complexity. Due to the special structure of our functions, the steps of our methods reduce to solving convex optimization subproblems. We provide convergence rate results for the proposed methods. Furthermore, some global relaxation techniques are presented to find lower bounds and strengthen our local algorithms. We show the e↵ectiveness of our techniques in application to risk parity optimization in portfolio management.
A Unified Framework for Contextual and Factoid Question Generation

Question generation (QG) aims to automatically generate fluent and relevant questions, where the two most mainstream directions are generating questions from unstructured contextual texts (CQG), such as news articles, and generating questions from structured factoid texts (FQG), such as knowledge graphs or tables. Existing methods for these two tasks mainly face challenges of limited internal structural information as well as scarce background information, while these two tasks can benefit each other for alleviating these issues. For example, when meeting the entity mention “United Kingdom” in CQG, it can be inferred that it is a country in European continent based on the structural knowledge “(Europe, countries_within, United Kingdom)” in FQG. And when meeting the entity “Houston Rockets” in FQG, more background information, such as “an American professional basketball team based in Houston since 1971”, can be found in the related passages of CQG. To this end, we propose a unified framework for the tasks of CQG and FQG, where: (i) two types of task-sharing modules are developed to learn shared contextual and structural knowledge, where the task format is unified with a pseudo passage reformulation strategy; (ii) for the CQG task, a task-specific knowledge module with a knowledge selection and aggregation mechanism is introduced, so as to incorporate more factoid knowledge from external knowledge graphs and alleviate the word ambiguity problem; and (iii) for the FQG task, a task-specific passage module with a multi-level passage fusion mechanism is designed to extract fine-grained word-level knowledge. Experimental results in both automatic and human evaluation show the effectiveness of our proposed method.
Relative effect sizes for measures of risk

ABSTRACT Effect sizes are an important component of experimental design, data analysis, and interpretation of statistical results. In some situations, an effect size of clinical or practical importance may be unknown to the researcher. In other situations, the researcher may be interested in comparing observed effect sizes to known standards to quantify clinical importance. In these cases, the notion of relative effect sizes (small, medium, large) can be useful as benchmarks. Although there is generally an extensive literature on relative effect sizes for continuous data, little of this research has focused on relative effect sizes for measures of risk that are common in epidemiological or biomedical studies. The aim of this paper, therefore, is to extend existing relative effect sizes to the relative risk, odds ratio, hazard ratio, rate ratio, and Mantel–Haenszel odds ratio for related samples. In most scenarios with equal group allocation, effect sizes of 1.22, 1.86, and 3.00 can be taken as small, medium, and large, respectively. The odds ratio for a non rare event is a notable exception and modified relative effect sizes are 1.32, 2.38, and 4.70 in that situation.
On the shooting algorithm for optimal control problems with state constraints

This thesis deals with (deterministic) optimal control problems of an ordinary differential equation subject to one or several state constraints, of arbitrary orders, in the case when the strengthened Legendre-Clebsch condition is satisfied. Pontryagin's minimum principle provides us with a well-known first-order optimality condition. In this thesis we first obtain a second-order sufficient optimality condition which is the weakest possible, i.e. which is as close as possible to the second-order necessary condition and characterizes quadratic growth. This condition allows us to obtain a characterization of the well-posedness of the shooting algorithm in presence of state constraints. Then stability and sensitivity analysis of solutions under perturbation of the data is investigated. We obtain for the first time stability results for state constraints of order greater than or equal to two that make no assumption on the structure of the trajectory. Moreover, results on structural stability of Pontryagin's extremals are given. Finally, the above results on the well-posedness of the shooting algorithm and on stability analysis allow us to design a new continuation method, for state constraints of first and second-order, whose novelty is to automatically detect the structure of the trajectory and initialize the associated shooting parameters.
Testing for Generational Difference Impacts on Employee New Job Seeking Intent in Response to COVID-19 and the Black Lives Matter Movement

Using a sample of 122 employed U.S. survey respondents, this study investigated if there were generational difference impacts on employees seeking jobs in response to COVID-19 and the Black Lives Matter (BLM) movement. Four generations were sampled – Generation Z (Gen Z), Generation Y (Millennials), Generation X (Gen X), and Baby Boomer (Boomers). Results showed that generation had a significant effect on employees search for new jobs in response to COVID-19 and BLM after controlling for demographics, i.e., gender, race, and education level and organization variables, i.e., annual salary, COVID-19 employee experience and BLM employee experience. Further analysis showed that Gen Z employees were more likely to actively seek new employment in response to the BLM movement than Gen X and Boomers, whereas Millennials were more to actively search than Gen X due to COVID-19. These results suggest insights into the role of societal crises in shaping workplace behavior across generations.
The Nature of the (Oligo/Hetero)Arene Linker Connecting Two Triarylborane Cations Controls Fluorimetric and Circular Dichroism Sensing of Various ds-DNAs and ds-RNAs

A series of tetracationic bis-triarylborane dyes, differing in the aromatic linker connecting two dicationic triarylborane moieties, showed very high submicromolar affinities toward ds-DNA and ds-RNA. The linker strongly influenced the emissive properties of triarylborane cations and controlled the fluorimetric response of dyes. The fluorene-analog shows the most selective fluorescence response between AT-DNA, GC-DNA, and AU-RNA, the pyrene-analog’s emission is non-selectively enhanced by all DNA/RNA, and the dithienyl-diketopyrrolopyrrole analog’s emission is strongly quenched upon DNA/RNA binding. The emission properties of the biphenyl-analog were not applicable, but the compound showed specific induced circular dichroism (ICD) signals only for AT-sequence-containing ds-DNAs, whereas the pyrene-analog ICD signals were specific for AT-DNA with respect to GC-DNA, and also recognized AU-RNA by giving a different ICD pattern from that observed upon interaction with AT-DNA. The fluorene- and dithienyl-diketopyrrolopyrrole analogs were ICD-signal silent. Thus, fine-tuning of the aromatic linker properties connecting two triarylborane dications can be used for the dual sensing (fluorimetric and CD) of various ds-DNA/RNA secondary structures, depending on the steric properties of the DNA/RNA grooves.