Miracle-dz/UniFAR-FTUs huggingface dataset:
Innovation as an accelerating effect on Gross Domestic Product (GDP) per capita

Most economists agree that innovation is a key driver of economic growth, prosperity and human well-being. Patents are an important indicator of innovation output. This study aims to investigate the relationship between patents as an innovation output and Gross Domestic Product (GDP) per capita as an economic welfare. In the study 166 countries were analyzed and a high positive correlation between patent grants per million population and GDP per capita as 0.804. The inequality in income distribution in the world is also clearly seen in the distribution of patent grants. High-income countries have 61 percent of global income whereas they have 66.9 percent of total patent grants in the world. Low-income countries have 0.5 percent of global income whereas they have 0.3 percent of total patent grants in the world. Global average patent grants per million population is 221.3 in 2020. Patent grants per million population is 943.6 in high-income countries and 8.6 in low-income countries. Test results show that, the natural logarithm of patent grants per million population increase 10 percent, it causes approximately 4.1 percent increase in natural logarithm of GDP per capita. In other words, if patent grants per million population in the world increase 23.3, it causes approximately 523.1 USD increase in global GDP per capita in average.
Ontological Support for Harmonization and Integration of Ukrzaliznytsia Information Systems Data

Purpose. The development strategy of Ukrzaliznytsia includes the following areas: integration and standardization of information systems, increasing the truthfulness of data and automating business processes. The integration of railway information systems is possible by ontological means without changing their structure. In this work, the main aim is the analysis of existing transportation ontological developments and determination of approaches to the application of related domains developments to the objectives of Ukrzaliznytsia’s development. Methodology. Ontological developments are systematized according to the type and format of their resources, the level of data integration, and the goals of ontology-based software. Methods of system analysis are used. Findings. The analysis showed that European Union railway transport ontologies are used to integrate infrastructure description data, train timetables, and others. At the same time, insufficient attention is paid to the regulatory support of the transportation process. There are software tools for annotating texts, extracting knowledge from tables and developing ontologies, but they are not used to support the Ukrainian railway transportation process. It has been determined that the actual problem is normative documentation annotation to establish a link between the ontology and the regulation texts. Originality. The basis for achieving the development goals of Ukrzaliznytsia by ontological means was laid, using the analysis and systematization of existing ontological developments of transport and related domains. The possibilities of using ontological means in railway transport are scientifically substantiated for: formalization of regulatory support; data transformations; data integration; checking the consistency of information systems data and regulations. Practical value. The work made it possible to identify the most significant ontological projects in transport. The foundations for the implementation of the conceptualization of the tabular representation of knowledge and the development of an ontology for the integration of models of railway subsystems have been laid.
Underachievement at school relative to potential: links between reasoning, phonological decoding, short-term memory, and complex grammar

Abstract Around 6% of U.K. children are underachieving at school relative to their potential (URP). We explored whether difficulties with phonological decoding, short-term memory (STM), and complex grammar may be responsible. We compared school-based reading test data or formal SATs, and verbal reasoning in 2462 children (150 URP and 2312 non-URP children) and administered a 7-min follow-up test to a matched subgroup of 106 URP and 106 non-URP children. Thirty-three of our original 150 URP children (22%) scored in the top 10% nationally for verbal reasoning, compared with 46 of our 2312 non-URP children (2%). Phonological decoding, STM, and complex grammar acquisition made independent URP contributions in children aged 7–9; in ages 10–12, only phonological decoding contributed. URP children were more likely to show multiple difficulties. The 7-min test enables school staff to quickly identify areas for targeted support. Some URP children not previously detected as capable may be encouraged to take up and succeed in further education.
Cloning of Toll-like Receptor 3 Gene from Schizothorax prenanti (SpTLR3), and Expressions of Seven SpTLRs and SpMyD88 after Lipopolysaccharide Induction

Toll-like receptor 3 (SpTLR3) from Schizothorax prenanti (S. prenanti) was cloned and identified, and the tissue distribution of the SpTLR3 gene was examined in this study. Moreover, the relative mRNA expression levels of myeloid differentiation factor 88 gene (SpMyD88) and seven TLR genes (SpTLR2, SpTLR3, SpTLR4, SpTLR18, SpTLR22-1, SpTLR22-2 and SpTLR22-3) from S. prenanti after lipopolysaccharide (LPS) challenge were analyzed through quantitative real-time polymerase chain reaction (qRT-PCR). The full length of SpTLR3 gene is 3097 bp, and complete coding sequence (CDS) is 2715 bp, which encodes 904 amino acids. The SpTLR3 amino acid sequence shared 43.94–100% identity with TLR3 sequences from other vertebrates; SpTLR3 was expressed in all eight tissues examined; and the highest level appeared in the liver, which was significantly higher than in all other tissues (p < 0.05), followed by the levels in the heart and muscles. LPS significantly up-regulated all eight genes in the S. prenanti tissues at 12 or 24 h (p < 0.05). Compared with the PBS control group, no significant transcripts changes were found in SpTLR2 or SpTLR3 at 12 h after LPS induction, but they were significantly up-regulated at 24 h (p < 0.001). The most abundant transcripts were found in the head kidney SpTLR22 genes after 24 h LPS induction, with high to low levels, which were SpTLR22-1 (564-fold), SpTLR22-3 (508-fold) and SpTLR22-2 (351-fold). Among these eight genes, the expression level of SpTLR4 was the least up-regulated. Overall, SpTLR4 in the head kidney was involved in the antibacterial immune response earlier, and the level was increased at 12 h with extreme significance after LPS stimulation (p < 0.001), while the other seven genes were the most significantly up-regulated at 24 h post injection. Taken together, the results suggest that SpMyD88, SpTLR2, SpTLR3, SpTLR4, SpTLR18, SpTLR22-1, SpTLR22-2 and SpTLR22-3 participate in an innate immune response stimulated by LPS, and the response intensity of the genes was organ-specific, with differing kinetics. Our findings will contribute to a more complete understanding of the roles of these TLR genes in antibacterial immunity.
How to backdoor LWE-like cryptosystems

We present a rather generic backdoor mechanism that can be applied to many LWE-like public-key cryptosystems. Our construction manipulates the key generation algorithm of such schemes in a way that allows a malicious adversary in possession of secret backdoor information to recover generated secret keys from corresponding public keys. To any user of the cryptosystem however, the output of our backdoored key generation is indistinguishable from output of the legitimate key generation algorithm. Our construction relies on elliptic-curve cryptography and draws on existing work on encoding of elliptic curve points as bit strings. Ourbackdoor mechanism can be applied to public-key cryptosystems where the secret key is generated from a secret seed and the public key includes a public seed of the same length. This holds - though not exclusively - for many cryptosystems based on LWE. In particular, we point out that our construction can be applied to backdoor HQC, FrodoKEM, Kyber and Dilithium. We also suggest a countermeasure that makes our backdoor detectable by users of the cryptosystem. To this end, we modify the key generation such that the public and secret key are pseudorandomly generated from a single seed which is included in the generated secret key. This allows any user of the key generation algorithm to regenerate keys us-ing an independent implementation, making our backdooring attempt detectable.
On The Applications of Lifting Techniques

Lifting techniques are some of the main tools in solving a variety of different computational problems related to the field of computer algebra. In this thesis, we will consider two fundamental problems in the fields of computational algebraic geometry and number theory, trying to find more efficient algorithms to solve such problems. The first problem, solving systems of polynomial equations, is one of the most fundamental problems in the field of computational algebraic geometry. In this thesis, we discuss how to solve bivariate polynomial systems over either k(T ) or Q using a combination of lifting and modular composition techniques. We will show that one can find an equiprojectable decomposition of a bivariate polynomial system in a better time complexity than the best known algorithms in the field, both in theory and practice. The second problem, polynomial factorization over number fields, is one of the oldest problems in number theory. It has lots of applications in many other related problems and there have been lots of attempts to solve the problem efficiently, at least, in practice. Finding p-adic factors of a univariate polynomial over a number field uses lifting techniques. Improving this step can reduce the total running time of the factorization in practice. We first introduce a multivariate version of the Belabas factorization algorithm over number fields. Then we will compare the running time complexity of the factorization problem using two different representations of a number field, univariate vs multivariate, and at the end as an application, we will show the improvement gained in computing the splitting fields of a univariate polynomial over a rational field.
Interactive Effects of Increasing Temperature and Decreasing Oxygen on Coastal Copepods

The copepods of coastal seas are experiencing warming water temperatures, which increase their oxygen demand. In addition, many coastal seas are also losing oxygen because of deoxygenation due to cultural eutrophication. Warming coastal seas have changed copepod species’ composition and biogeographic boundaries and, in many cases, resulted in copepod communities that have shifted in size distribution to smaller species. While increases in ambient water temperatures can explain some of these changes, deoxygenation has also been shown to result in reduced copepod growth rates, reduced size at adulthood, and altered species composition. In this review we focus on the interactive effects of temperature and dissolved oxygen on pelagic copepods, which dominate coastal zooplankton communities. The uniformity in ellipsoidal shape, the lack of external oxygen uptake organs, and the pathway of oxygen uptake through the copepod’s integument make calanoid copepods ideal candidates for testing the use of an allometric approach to predict copepod size with increasing water temperatures and decreasing oxygen in coastal seas. Considering oxygen and temperature as a combined and interactive driver in coastal ecosystems will provide a unifying approach for future predictions of coastal copepod communities and their impact on fisheries and biogeochemical cycles. Given the prospect of increased oxygen limitation of copepods in warming seas, increased knowledge of the physiological ecology of present-day copepods in coastal deoxygenated zones can provide insights into the copepod communities that will inhabit a future warmer ocean.
Exact and approximate algorithms for partially observable markov decision processes

Automated sequential decision making is crucial in many contexts. In the face of uncertainty, this task becomes even more important, though at the same time, computing optimal decision policies becomes more complex. The more sources of uncertainty there are, the harder the problem becomes to solve. In this work, we look at sequential decision making in environments where the actions have probabilistic outcomes and in which the system state is only partially observable. We focus on using a model called a partially observable Markov decision process (POMDP) and explore algorithms which address computing both optimal and approximate policies for use in controlling processes that are modeled using POMDPs. Although solving for the optimal policy is PSPACE-complete (or worse), the study and improvements of exact algorithms lends insight into the optimal solution structure as well as providing a basis for approximate solutions. We present some improvements, analysis and empirical comparisons for some existing and some novel approaches for computing the optimal POMDP policy exactly. Since it is also hard (NP-complete or worse) to derive close approximations to the optimal solution for POMDPs, we consider a number of approaches for deriving policies that yield sub-optimal control and empirically explore their performance on a range of problems. These approaches borrow and extend ideas from a number of areas; from the more mathematically motivated techniques in reinforcement learning and control theory to entirely heuristic control rules.
Reflected BSDEs when the obstacle is not right-continuous and optimal stopping

In the first part of the paper, we study reflected backward stochastic differential equations (RBSDEs) with lower obstacle which is assumed to be right upper-semicontinuous but not necessarily right-continuous. We prove existence and uniqueness of the solutions to such RBSDEs in appropriate Banach spaces. The result is established by using some tools from the general theory of processes such as Mertens decomposition of optional strong (but not necessarily right-continuous) supermartingales, some tools from optimal stopping theory, as well as an appropriate generalization of It{o}'s formula due to Gal'chouk and Lenglart. In the second part of the paper, we provide some links between the RBSDE studied in the first part and an optimal stopping problem in which the risk of a financial position $\xi$ is assessed by an $f$-conditional expectation $\mathcal{E}^f(\cdot)$ (where $f$ is a Lipschitz driver). We characterize the "value function" of the problem in terms of the solution to our RBSDE. Under an additional assumption of left upper-semicontinuity on $\xi$, we show the existence of an optimal stopping time. We also provide a generalization of Mertens decomposition to the case of strong $\mathcal{E}^f$-supermartingales.
A Wavelet-Packet Census Algo-rithm for Calculating Vortex Statistics

A generalized wavelet-packet based technique for decomposing signals into coherent and noncoherent parts is presented. The method is tested on the vorticity field of numerical simulations of weakly decaying two-dimensional turbulence. The easily recognizable coherent vortex structures that emerge are systematically filtered from the solution. Once extracted, various properties of the vortices, such as their number, size, circulation, and peak value are computed. The results compare well with a similar study [J. Fluid Mech. 219, 361 (1990); Phys. Fluids 5, 608 (1993)], which employs a complex pattern recognition technique based exclusively on a priori knowledge of the properties of the solution—that is, the features typical of the resulting vortex structures. The similarity of the results is encouraging, suggesting that the wavelet packet technique, by absorbing much of the complexity into the mathematical features of the transform itself, can provide an efficient, standardized tool that is readily extendi.
An Intelligent World Model for Autonomous Off-Road Driving

This paper describes a world model designed to act as a bridge between multiple sensory inputs and a behavior generation (path planning) subsystem for off−road autonomous driving. It describes how the world model map is built and how the objects and features of the world are represented. The functions used to maintain the model are explained and the sensors and sensory processing used to provide data for this application are discussed. The paper includes examples of integrating and fusing sensory data from multiple sources into the world model map. The representation is being developed for the Army's Demo III autonomous driving experiment, which is an on−going research project. The paper concludes with a discussion of future research directions.
Expression and Variations in EPAS1 Associated with Oxygen Metabolism in Sheep

Endothelial PAS domain protein 1 gene (EPAS1) is a member of the HIF gene family. This gene encodes a transcription factor subunit that is involved in the induction of oxygen-regulated genes. Several studies have demonstrated that a mutation in EPAS1 could affect oxygen sensing, polycythemia, and hemoglobin level. However, whether EPAS1 mutation affects sheep oxygen metabolism is still unknown. Therefore, we explored the relationship between the variation of EPAS1 and oxygen metabolism in sheep. In this study, variations in ovine EPAS1 exon 15 were investigated in 332 Tibetan sheep and 339 Hu sheep by polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) analysis. In addition, we studied the effect of these variations on blood gas in 176 Tibetan sheep and 231 Hu sheep. Finally, the mRNA expression of EPAS1 in six tissues of Hu sheep and Tibetan sheep living at different altitudes (2500 m, 3500 m, and 4500 m) was analyzed by real-time quantitative PCR (RT-qPCR). Four alleles (A, B, C, and D) were detected, and their distributions highly differed between Tibetan sheep and Hu sheep. In Tibetan sheep, B was the dominant allele, and C and D alleles were rare, whereas all four alleles were common in Hu sheep. Six single nucleotide polymorphisms (SNPs) were identified between the four alleles and one of them was non-synonymous (p.F606L). While studying the blood gas levels in Tibetan sheep and Hu sheep, one variant region was found to be associated with an elevated pO2 and sO2, which suggested that variations in EPAS1 are associated with oxygen metabolism in sheep. RT-qPCR results showed that EPAS1 was expressed in the six tissues of Hu sheep and Tibetan sheep at different altitudes. In addition, the expression of EPAS1 in four tissues (heart, liver, spleen, and longissimus dorsi muscle) of Hu sheep was lower than that in Tibetan sheep from three different altitudes, and the expression of EPAS1 was positively correlated with the altitude. These results indicate that the variations and expression of EPAS1 is closely related to oxygen metabolism.
M-theory Calabi-Yau Quantum Mechanics

This thesis explores an exotic class of M-theory compactifications in which the compact manifold is taken to be a Calabi-Yau five-fold. The resulting effective theory is a one-dimensional N=2 super-mechanics model that exhibits peculiar features of one-dimensional supersymmetry, such as the appearance of fermion-only super-multiplets. The latter necessitates reducing also the fermionic sector of M-theory, which is not normally included in the compactification literature and is thus presented, together with the required technology, in detail. The one-dimensional effective theory is most elegantly described in superspace and therefore, a detailed account of one-dimensional flat and curved N=2 superspace is provided. This includes developing the theory of fermionic multiplets and the study of cross-couplings between 2a and 2b multiplets. Another important aspect is the inclusion of flux. We study its consistency conditions, its relation to supersymmetry and the way it gives rise to a potential in the one-dimensional effective action. It is also explained how the supersymmetry-preserving part of the potential can be obtained from a Gukov-type superpotential. The main motivation of this compactification scenario is rooted in the realm of cosmology. Its virtue is a democratic treatment of spatial dimensions. As opposed to the artificial 3+7 split in most string compactifications, the early universe starts out with all spatial dimensions compact and small in our approach. One then seeks for dynamical ways in which three dimensions grow large at late times. Possible realisations of this idea are discussed both at the classical and at the quantum level. Finally, preliminary work on Calabi-Yau five-fold compactifications of F-theory and the resulting two-dimensional string-like actions is presented.
A systematic approach to quantify the influence of indoor environmental parameters on students' perceptions, responses, and short‐term academic performance

Abstract Several studies found that classrooms' indoor environmental quality (IEQ) can positively influence in‐class activities. Understanding and quantifying the combined effect of four indoor environmental parameters, namely indoor air quality and thermal, acoustic, and lighting conditions on people is essential to create an optimal IEQ. Accordingly, a systematic approach was developed to study the effect of multiple IEQ parameters simultaneously. Methods for measuring the IEQ and students' perceived IEQ, internal responses, and academic performance were derived from literature. Next, this systematic approach was tested in a pilot study during a regular academic course. The perceptions, internal responses, and short‐term academic performance of participating students (n = 163) were measured. During the pilot study, the IEQ of the classrooms varied slightly. Significant associations (p < 0.05) were observed between these natural variations and students' perceptions of the thermal environment and indoor air quality. These perceptions were significantly associated with their physiological and cognitive responses (p < 0.05). Furthermore, students' perceived cognitive responses were associated with their short‐term academic performance (p < 0.01). The observed associations confirm the construct validity of the systematic approach. However, its validity for investigating the influence of lighting remains to be determined.
Reconstructed Genome-Scale Metabolic Model Characterizes Adaptive Metabolic Flux Changes in Peripheral Blood Mononuclear Cells in Severe COVID-19 Patients

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a mortal threat to human health. The elucidation of the relationship between peripheral immune cells and the development of inflammation is essential for revealing the pathogenic mechanism of COVID-19 and developing related antiviral drugs. The immune cell metabolism-targeting therapies exhibit a desirable anti-inflammatory effect in some treatment cases. In this study, based on differentially expressed gene (DEG) analysis, a genome-scale metabolic model (GSMM) was reconstructed by integrating transcriptome data to characterize the adaptive metabolic changes in peripheral blood mononuclear cells (PBMCs) in severe COVID-19 patients. Differential flux analysis revealed that metabolic changes such as enhanced aerobic glycolysis, impaired oxidative phosphorylation, fluctuating biogenesis of lipids, vitamins (folate and retinol), and nucleotides played important roles in the inflammation adaptation of PBMCs. Moreover, the main metabolic enzymes such as the solute carrier (SLC) family 2 member 3 (SLC2A3) and fatty acid synthase (FASN), responsible for the reactions with large differential fluxes, were identified as potential therapeutic targets. Our results revealed the inflammation regulation potentials of partial metabolic reactions with differential fluxes and their metabolites. This study provides a reference for developing potential PBMC metabolism-targeting therapy strategies against COVID-19.