Miracle-dz/UniFAR-FTUs huggingface dataset:
ResMatch: Residual Attention Learning for Local Feature Matching

Attention-based graph neural networks have made great progress in feature matching learning. However, insight of how attention mechanism works for feature matching is lacked in the literature. In this paper, we rethink cross- and self-attention from the viewpoint of traditional feature matching and filtering. In order to facilitate the learning of matching and filtering, we inject the similarity of descriptors and relative positions into cross- and self-attention score, respectively. In this way, the attention can focus on learning residual matching and filtering functions with reference to the basic functions of measuring visual and spatial correlation. Moreover, we mine intra- and inter-neighbors according to the similarity of descriptors and relative positions. Then sparse attention for each point can be performed only within its neighborhoods to acquire higher computation efficiency. Feature matching networks equipped with our full and sparse residual attention learning strategies are termed ResMatch and sResMatch respectively. Extensive experiments, including feature matching, pose estimation and visual localization, confirm the superiority of our networks.
Entity Identifier: A Natural Text Parsing-based Framework For Entity Relation Extraction

The field of programming has a diversity of paradigms that are used according to the working framework. While current neural code generation methods are able to learn and generate code directly from text, we believe that this approach is not optimal for certain code tasks, particularly the generation of classes in an object-oriented project. Specifically, we use natural language processing techniques to extract structured information from requirements descriptions, in order to automate the generation of CRUD (Create, Read, Update, Delete) class code. To facilitate this process, we introduce a pipeline for extracting entity and relation information, as well as a representation called an"Entity Tree"to model this information. We also create a dataset to evaluate the effectiveness of our approach.
Computer-assisted proofs for radially symmetric solutions of PDEs

We obtain radially symmetric solutions of some nonlinear (geometric) partial differential equations via a rigorous computer-assisted method. We introduce all main ideas through examples, accessible to non-experts. The proofs are obtained by solving for the coefficients of the Taylor series of the solutions in a Banach space of geometrically decaying sequences. The tool that allows us to advance from numerical simulations to mathematical proofs is the Banach contraction theorem.
EFFECT OF JASMONIC ACID ON THE HERBIVORY AND OVIPOSITION OF Neoleucinodes elegantalis (Guenée) IN Solanum quitoense (Lam) PLANTS.

Sebastián Yánez 1 , Bernardo Navarrete 2 and Enrique Vallejos 3 . 1. Profesor and Research of the Faculty of Agricultural Sciences. Central University of Ecuador. Quito – Ecuador. 2. Research. National Institute of Agricultural Research. Portoviejo – Ecuador. 3. Student of Master in Plant Sciences (Plant Health). Austral University of Chile. Valdivia – Chile. Manuscript Info Abstract . Manuscript History
An optimal control model of carbon reduction and trading

In this study, a stochastic control model is established for a country to formulate a carbon abatement policy to minimize the total carbon reduction costs. Under Merton's consumption framework, by considering carbon trading, carbon abatement and penalties in a synthetic manner, the model is converted into a two-dimensional Hamilton--Jacobi--Bellman equation. We rigorously prove the existence and uniqueness of its viscosity solution. We also present the numerical results and discuss the properties of the optimal carbon reduction policy and the minimum total costs.
Introduction to Nonparametric Bayesian Models

This paper introduces nonparametric Bayesian models, in particular, Dirichlet process mixture (DPM) models and the infinite relational model (IRM) as an extension of DPM for multi-way data clustering. The nonparametric Bayesian modelling is a more flexible approach than a standard parametric Bayesian modelling in that a nonparametric prior distribution over model parameters is incorporated into the data gereration process. More specifically, DPM enables us to define distributions over the countably infinite sets by exploring their clustering structures. In this paper, we explain the basic idea of DPM modelling and its learning algorithms. We also illustrate practical usefulness of DPM modelling though experimental results using IRM.
Jurnal Litbang Industri

Sejarah artikel: Bananas commonly grow in tropical areas and have many health benefits derived from both the inner and outer parts of the fruit. The proximate composition and functional properties of banana flour with varying ripening stages of plantain banana fruit (green, green-yellow, yellow-green) were studied in this research. Banana was peeled prior to drying and milling into flour followed by starch extraction. Besides proximate analysis, the yields of the obtaining banana flour and starch, as well as the functional properties of starch such as solubility, swelling power, and pasting properties, were also determined. The total carbohydrate, crude fiber, and ash content tended to decrease with the ripening process, in contrast, fat, protein, and moisture content tended to increase over ripening. The amylose/amylopectin content of banana starch influenced the functional properties such as solubility, swelling, and pasting profiles. However, there were no significant differences in the chemical compositions and functional characteristics of banana flour compared with its ripening stage ( P >0.05) based on Kruskal-Wallis non-parametric statistical tests. Indeed, the information about chemical characteristics and functional properties of banana flour and starch during fruit ripening is important for the banana fruit processing and their product quality assurance.
Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education

This report documents the program and the outcomes of Dagstuhl Seminar 23031 "Frontiers of Information Access Experimentation for Research and Education", which brought together 38 participants from 12 countries. The seminar addressed technology-enhanced information access (information retrieval, recommender systems, natural language processing) and specifically focused on developing more responsible experimental practices leading to more valid results, both for research as well as for scientific education. The seminar featured a series of long and short talks delivered by participants, who helped in setting a common ground and in letting emerge topics of interest to be explored as the main output of the seminar. This led to the definition of five groups which investigated challenges, opportunities, and next steps in the following areas: reality check, i.e. conducting real-world studies, human-machine-collaborative relevance judgment frameworks, overcoming methodological challenges in information retrieval and recommender systems through awareness and education, results-blind reviewing, and guidance for authors. Date: 15--20 January 2023. Website: https://www.dagstuhl. de/23031.
An algorithm for multi-task learning based on combinatorial optimization of U-curves

Here we report the development of an algorithm that explores properties of U-shaped curves (“U-curves”) in cost functions of multi-task transfer learning (MTL) models. The proposed algorithm works even with the insertion of different tasks that may or may not be related to the original task of learning. To find a global minimum of the described curve, a Boolean lattice is organized based on the enumeration of the search space with the weights of the group of different tasks used in training. This traversal of that lattice is carried out through a branch-and-bound procedure, in which the pruning criterion is the increase of the cost in a chain of that lattice. To benchmark the proposed algorithm against established MTL methods, we carried out computational experiments with both synthetic and real datasets. We expect that this proposed algorithm will represent a relevant alternative for multi-task learning models.
Coresets For Monotonic Functions with Applications to Deep Learning

Coreset (or core-set) in this paper is a small weighted \emph{subset} $Q$ of the input set $P$ with respect to a given \emph{monotonic} function $f:\mathbb{R}\to\mathbb{R}$ that \emph{provably} approximates its fitting loss $\sum_{p\in P}f(p\cdot x)$ to \emph{any} given $x\in\mathbb{R}^d$. Using $Q$ we can obtain approximation to $x^*$ that minimizes this loss, by running \emph{existing} optimization algorithms on $Q$. We provide: (i) a lower bound that proves that there are sets with no coresets smaller than $n=|P|$ , (ii) a proof that a small coreset of size near-logarithmic in $n$ exists for \emph{any} input $P$, under natural assumption that holds e.g. for logistic regression and the sigmoid activation function. (iii) a generic algorithm that computes $Q$ in $O(nd+n\log n)$ expected time, (iv) novel technique for improving existing deep networks using such coresets, (v) extensive experimental results with open code.oving existing deep networks using such coresets, (v) extensive experimental results with open code.
FORMATION OF ADOLESCENTS’ SOCIAL COMPETENCE IN EDUCATIONAL INSTITUTION ENVIRONMENT

The study is devoted to the actual problem of the formation of social competence of adolescents. The aim of the research is to present the theoretical essence of the social competence and try the method of forming the social competence of teenagers out in practice. It is stated that t he formation of the personal social competence is one of the key tasks of the present-day school due to the main school documents and the guidelines for the schoolchildren education in educational institutions. It is justified that social competence is an acquired skill that can be formed and developed throughout the person’s life. The developed social competence determines the status of an individual in society and affects personal success in further professional activities
Asymptotics of diffusion-limited fast reactions

We are concerned with the fast-reaction asymptotics λ → ∞ for a semi-linear coupled diﬀusion-limited reaction system in contact with inﬁnite reservoirs of reactants. We derive the system of limit equations and prove the uniqueness of its solutions for equal diﬀusion coeﬃcients. Additionally, we emphasize the struc-ture of the limit free boundary problem. The key tools of our analysis include (uniform with respect to λ ) L 1 -estimates for both ﬂuxes and products of reaction and a balanced formulation , where combinations of the original components which balance the fast reaction are used.
Emotional Intelligence Positively Affects Student's Social Skills in Physical Education

The social skills of teenagers, especially those of high school age, are very concerning. Numerous pieces of evidence point to the existence of social issues that manifest themselves not only in the context of the educational institution but also in the wider society. Lack or low emotional intelligence is considered the presence of disturbances in emotional and social functioning. Social skills and managing emotions are essential to blocking problematic behaviors. But empirical evidence of emotional intelligence and its influence on social skills is minimal. This study aims to prove the influence of emotional intelligence on students' social skills at the High School level. This research uses a descriptive method with a correlational type of research. The population used in this study was all high school students in the Tasikmalaya area, and as many as 173 students were sampled in this study by random cluster sampling. The data analysis was a simple linear regression test using IBM SPSS 26. The result of this study is the relationship between variables of 0.503 in a positive direction, with a coefficient of determination (R Square) of 0.253, which means that free variables have an influence of 25.3% on bound variables. Referring to the calculated F value = 57.967 with a Sig. rate of 0.000 < 0.05 means that the null hypothesis is rejected, and the research hypothesis is accepted. In conclusion, emotional intelligence positively affects students' social skills in Physical Education.
Supplementation of goats with mesquite pod meal in deferred ( Urochloa mosambicenses) grass pasture in the semiarid region

: Supplementation emerges as a simple strategy to improve animal productivity in systems that adopt deferred grass pasture as the basic diet. This study aimed to evaluate the effect of levels of supplementation of mesquite pod meal on intake, digestibility of nutrients, and body weight (BW) gain of goats in grazing deferred. Thirty-five (35) goat males (24.0 ± 2.9 kg BW) were distributed in a completely randomized design, with five treatments and seven replications. Treatments constituted a supplement control (0.05% BW of
Perceptions of journalism and trust in news among traditionalist and digitalist media users: A comparative analysis of Denmark, Spain and USA

This study analyses trust in news and the relevance granted to journalism by different user profiles in three countries (Denmark, Spain and the United States), each from a different media system as identified by Hallin and Mancini (2004). For this research we used two online surveys (2019, 2020) carried out by the Reuters Institute with more than 2000 people in each country. Our results show that users who consume news through newspapers, radios and television trust news more than those whose main source of information are digital devices. Traditionalist users also have a higher degree of satisfaction with the classic functions of journalism: making the powerful accountable (adversarial function), disseminating current information (disseminating function) and explaining current events to the public (interpretative function). There are differences between countries, especially in the evaluation of the adversarial function. Spaniards, who belong to the polarized pluralist system, are the ones who worst value its fulfilment among their country’s media.
An evaluation of the convection‐permitting ensemble COSMO‐E for three contrasting precipitation events in Switzerland

Specific aspects of the performance of COSMO‐E, a newly operational convection‐permitting ensemble prediction system run by the Swiss national weather service, are evaluated for three contrasting precipitation events and compared with its driving model, the ECMWF ensemble (EC ENS). The events include locally triggered air‐mass convection on four consecutive days (CONV), a complex flood‐producing rainfall episode (LSF1), and a summertime cold‐frontal precipitation event (LSF2). Investigating the precipitation forecasts reveals that COSMO‐E outperforms EC ENS in all cases in terms of precipitation pattern, whereas both ensembles fail in predicting the correct domain‐averaged precipitation for LSF1 and struggle with the correct timing of the daily precipitation onset for CONV. For LSF2, EC ENS produces an almost perfect time series of domain‐averaged precipitation, but this seemingly excellent forecast fails in predicting the spatial distribution. Spread–error relationships also yield a rather complex picture. The higher resolution of COSMO‐E leads to increased spread and reduced underdispersion for near‐surface variables. However, in the free troposphere the two ensembles perform similarly, and the agreement of spread and error varies between cases, variables and levels. For both events with large‐scale advection, underdispersion occurs for mid‐tropospheric relative humidity near fronts, whose propagation is overconfident in EC ENS, while for the convective event COSMO‐E clearly shows larger spread than EC ENS. Because frontal propagation is largely determined by lateral boundary conditions, this underdispersion also occurs for COSMO‐E. In summary, this study confirms the benefit of a convection‐permitting model for many aspects of ensemble forecasting, and illustrates the challenge of robustly assessing the quality of an ensemble forecast for hydrometeorologically relevant events.
ANALYSIS OF THE RELATIONSHIP BETWEEN CRUDE OIL PRICES AND ECONOMIC PERFORMANCE INDICATORS IN IRAQ FOR THE PERIOD (2004-2021)

: Global economies are significantly affected by the volatility of crude oil prices. The economies of oil-producing countries may thrive when crude oil prices are high or stable within a range that achieves their desired goals, driving development and accelerating economic growth. This is achieved through targeted expansionary policies that promote local and foreign investments in infrastructure development. Conversely, the opposite occurs when prices decline. The study found that sharp fluctuations in oil prices lead to varying economic and social impacts, affecting economic growth, unemployment rates, and inflation. It also recommended the possibility of achieving sustainable economic growth by the government exerting more efforts in diversifying income sources, reducing heavy dependence on oil, and enhancing adaptability to price fluctuations.
Multivariate subordination of stable processes

This article is devoted to some time-changed stochastic models based on multivariate stable processes. The considered models have several advantages in comparison with classical time-changed Brownian motions - for instance, it turns out that they are more appropriate for describing stock prices if the amount of transactions is used for a stochastic time change. In this paper, we provide a detailed discussion of the model, which is based on two popular concepts - multivariate subordination and L{\'e}vy copulas.
Mathematical simulation of brightness fields in broken clouds for observations from Earth’s surface and from space in plane and spherical atmospheric models

We present original statistical algorithms for calculating brightness fields of upward and downward solar radiation in deterministic inhomogeneous clouds in the plane-parallel and spherical atmospheric models. Poisson model on the basis of point fluxes in space is used to simulate the cloud fields. We implemented a few modifications of the algorithms, differing in the methods for simulating free path length and accounting for the molecular absorption. Results of crosschecks of the developed modifications and estimations of their efficiency are presented.
The Effect of Lumbricus Rubellus as a Substitution for Antibiotic Growth Promotor (AGP) on the Performance of Ayam Kampung Super : Infection by Salmonella Sp

Currently the demand for Ayam Kampung Super chickens is increasing, both meat and eggs. This is because it tastes delicious. This study aims to investigate the use of worm flour of Lumbricus rubella as an additive in feed in order to replace the use of Antibiotic growth promoter (AGP). The study parameters were consumption feed, body weight, and conversion feed of Ayam Kampung chicken. This study was conducted from January to April 2022. A random complete design (CRD) was used for study research design with 5 (five) treatments and 6 ( six ) replications, where every treatment had 5 (five) of chicken. Treatments includes P0 Control ( No infection ); P 1: Without Antibiotics + Infection ; P 2: Antibiotics Trimizyn -s + Infection ; P 3: 50 mg/kg Earthworms flour + Infection ; P 4: 100 mg/kg Earthworm flour + Infection. The results show that the average consumption ratio (g/head/week) P0, P1, P2, P3, and P4 was 322.18; 303.97; 310.57; 313.80, and 315.09 respectively, increments body weight (g/ head ) was 821.92; 712.71; 777.08; 773.49 and 780.87 respectively. Conversion rations is 3.50; 3.52; 3.85; 3.57 and 3.74. It can be concluded that worm flour of Lumbricus rubella is capable replace Antibiotic growth promoter (AGP) in rations of Ayam Kampung Super.
Review Article Effects of intravenous sodium thiosulfate on vascular calcification in dialysis patients with end-stage renal disease: a systematic review and meta-analysis

Background: In dialysis patients, vascular calcification is a common complication and is closely related to the morbidity and mortality of cardiovascular disease. We performed a systematic review to determine the efficacy and safety of sodium thiosulfate (STS) in the progression of vascular calcification in dialysis patients with end-stage renal disease. Methods: The PubMed, Web of Science, Embase, Cochrane Library, Wanfang, CNKI, China Biology Medicine disc and Weipu databases were searched up to 9 March 2022 for clinical trials to synthesise findings on the efficacy and safety of STS in the progression of vascular calcification in dialysis patients. The primary outcome was coronary artery calcifica-tion scores (CACS) or abdominal aortic calcification scores (AACS) or Kauppila index. The secondary outcome was pulse-wave velocity (PWV). Laboratory data were shown in safety data. A random-effect model was used to provide the summary measures of effect [standardised mean difference (SMD) and 95% confidence interval (CI)]. Results: Seven randomised, controlled trials and one non-randomised, controlled trial involving 370 patients were included. Six studies reported that the progression of CACS or AACS was slower in the intravenous STS group compared with the control group (SMD –3.24, 95% CI: –5.29, –1.18, p = 0.002). Two studies showed the increase in PWV was less in the STS group compared with the control group (SMD –0.52, 95% CI: –0.92, –0.13, p = 0.009). During the trial period, a lower high-sensitivity C-reactive protein level (SMD 1.61, 95% CI: 0.19, 3.04, p = 0.03), a decrease in serum bicarbonate level (SMD 0.67, 95% CI: 0.22, 1.11, p = 0.003) and an increase in serum phosphate level (SMD –0.32, 95% CI: –0.62, –0.03, p = 0.03) were noted in the intravenous STS group compared with the control group. However, serum calcium and parathyroid hormone levels showed no difference between the two groups after the trials. The most common adverse events were temporary nausea and vomiting, which occurred in 12.5 to 75% of patients. Conclusions: Intravenous STS may slow down the progression of vascular calcification and ameliorate arterial stiffness in dialysis patients. Reliably defining the efficacy and safety of intravenous STS in attenuating the progression of vascular calcification requires a high-quality trial with a large sample size.
In-Network Probabilistic Monitoring Primitives under the Influence of Adversarial Network Inputs

Network management tasks heavily rely on network telemetry data. Programmable data planes provide novel ways to collect this telemetry data efficiently using probabilistic data structures like bloom filters and their variants. Despite the benefits of the data structures (and associated data plane primitives), their exposure increases the attack surface. That is, they are at risk of adversarial network inputs. In this work, we examine the effects of adversarial network inputs to bloom filters that are integral to data plane primitives. Bloom filters are probabilistic and inherently susceptible to pollution attacks which increase their false positive rates. To quantify the impact, we demonstrate the feasibility of pollution attacks on FlowRadar, a network monitoring and debugging system that employs a data plane primitive to collect traffic statistics. We observe that the adversary can corrupt traffic statistics with a few well-crafted malicious flows (tens of flows), leading to a 99% drop in the accuracy of the core functionality of the FlowRadar system.