Miracle-dz/UniFAR-FTUs huggingface dataset:
Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction

Open Information Extraction systems extract (“subject text”, “relation text”, “object text”) triples from raw text. Some triples are textual versions of facts, i.e., non-canonicalized mentions of entities and relations. In this paper, we investigate whether it is possible to infer new facts directly from the open knowledge graph without any canonicalization or any supervision from curated knowledge. For this purpose, we propose the open link prediction task,i.e., predicting test facts by completing (“subject text”, “relation text”, ? ) questions. An evaluation in such a setup raises the question if a correct prediction is actually a new fact that was induced by reasoning over the open knowledge graph or if it can be trivially explained. For example, facts can appear in different paraphrased textual variants, which can lead to test leakage. To this end, we propose an evaluation protocol and a methodology for creating the open link prediction benchmark OlpBench. We performed experiments with a prototypical knowledge graph embedding model for openlink prediction. While the task is very challenging, our results suggests that it is possible to predict genuinely new facts, which can not be trivially explained.
Cloning of the Mouse Laminin α4 cDNA. Expression in a Subset of Endothelium

Endothelial cells express a 400-kDa or 240-kDa laminin α chain, depending on their tissue of origin or physiological state [1, 2]. Using differential display and subsequent screening of a mouse endothelial cell cDNA library we here identify the gene coding for the 240-kDa laminin chain as the laminin α4 gene. The complete mouse laminin α4 cDNA sequence is reported and compared with other laminin α chains. In situ hybridization of embryonic and new born mouse tissues revealed expression of laminin α4 mRNA in a subset of endothelium, in particular aortic endothelium, endocardium and endothelium of blood vessels in the skin and in the brain. Strong laminin α4 expression by aortic endothelia was confirmed by data obtained from cultured bovine aortic endothelial cells (BAEC). Isolation of laminin from BAEC conditioned medium revealed a Y-shaped molecule in rotary shadowing. Subsequent sequencing of BAEC laminin resulted in laminin α4, β1 and γl amino acid sequences, confirming that laminin α4 is one of the major laminin α chains expressed by aortic endothelium not only in the mouse. In addition, strong laminin α4 mRNA expression occurred in peripheral nerves, cardiac muscle, fat, the dermis of the skin and lung stroma of mouse tissues. The data demonstrate a cytokine and progesterone-regulated differential expression of laminin α4 mRNA in mouse endothelium, suggesting a distinct functional role for this laminin chain in endothelium.
The effects of forage preservation method and proportion of concentrate on digestion of cell wall carbohydrates and rumen digesta pool size in cattle

Six bulls with ruminal and duodenal cannulae were used in a 6 × 6 Latin square design with a 2 × 3 factorial arrangement of treatments. Barn-dried grass (G) and direct-cut silage (S) from the same sward were fed together with 250 (L), 500 (M) and 750 (H) g kg-1 total dry matter (DM) of a barley-based concentrate (barley 875 and rape-seed meal 125 g kg-1) at the level of 80 g DM kg-1 live weight0·75. Rumen and total digestibility of cell wall constituents were measured by a double marker and total collection method. Rumen pool sizes of dietary constituents were estimated by emptying the rumen. Particle-associated enzyme activities were measured from rumen particulate material and feed particles incubated in nylon bags in the rumen. Neutral detergent fibre (NDF) and hemicellulose digestibility were higher (P<0·05) for G diets than for S diets while no differences were observed between the forages in acid detergent fibre (ADF) and cellulose digestibility. Both rumen and total digestibility of cell wall constituents decreased with increasing level of concentrate. The proportion of total cell wall digestion in the rumen was unaffected by the forage preservation method and the proportion of concentrate. NDF, and especially cellulose digestibility, declined quadratically with increasing level of concentrate. Dietary effects on particle-associated carboxymethylcellulase and xylanase activity were consistent with those observed in cell wall digestion. There were no differences between the forages in rumen pool size of total ingesta or any dietary constituent. Rumen pool size of total ingesta decreased with increasing level of concentrate. On the other hand, DM content of ingesta increased with the level of concentrate, while the pool size of DM, NDF and ADF declined quadratically reaching a minimum on M level of concentrate. The differences in rumen NDF pool size were mainly in the digestible fraction. Calculation of digestion kinetic parameters showed that both the rate of passage and especially the rate of digestion were markedly depressed in animals fed on the highest level of concentrate. The results suggest that a reduced fate of digestion of NDF with high concentrate diets can be partially compensated for by an increased NDF retention time in the rumen of animals fed at a restricted level of feeding.
Modeling Decision-Making Process Behavior

As a machine learning (ML) and natural language processing (NLP) researcher, I build probabilistic and statistical models to simulate and analyze human behaviors from their conversations. Unlike other data such as image, video, and sound, natural language is mainly made by humans. So when analyzing texts, we need to think about who creates it, and on the contrary, understand people through texts. Following these principles, I research in NLP by focusing on the relationship between humans and texts. As data, I mainly look at the conversation. The conversation is a typical communication between two people. And its context depends on the speaker. For example, a speaker may have different conversations with different conversational partners. This difference is an important factor in understanding the person, and in contrast, the person makes the conversation more understandable. In my research approach, I aim to 1) develop conversation models that generate human-like responses 2) investigate human behaviors from their conversations by novel ML models.
Incremental potential contact

Contacts weave through every aspect of our physical world, from daily household chores to acts of nature. Modeling and predictive computation of these phenomena for solid mechanics is important to every discipline concerned with the motion of mechanical systems, including engineering and animation. Nevertheless, efficiently time-stepping accurate and consistent simulations of real-world contacting elastica remains an outstanding computational challenge. To model the complex interaction of deforming solids in contact we propose Incremental Potential Contact (IPC) - a new model and algorithm for variationally solving implicitly time-stepped nonlinear elastodynamics. IPC maintains an intersection- and inversion-free trajectory regardless of material parameters, time step sizes, impact velocities, severity of deformation, or boundary conditions enforced. Constructed with a custom nonlinear solver, IPC enables efficient resolution of time-stepping problems with separate, user-exposed accuracy tolerances that allow independent specification of the physical accuracy of the dynamics and the geometric accuracy of surface-to-surface conformation. This enables users to decouple, as needed per application, desired accuracies for a simulation's dynamics and geometry. The resulting time stepper solves contact problems that are intersection-free (and thus robust), inversion-free, efficient (at speeds comparable to or faster than available methods that lack both convergence and feasibility), and accurate (solved to user-specified accuracies). To our knowledge this is the first implicit time-stepping method, across both the engineering and graphics literature that can consistently enforce these guarantees as we vary simulation parameters. In an extensive comparison of available simulation methods, research libraries and commercial codes we confirm that available engineering and computer graphics methods, while each succeeding admirably in custom-tuned regimes, often fail with instabilities, egregious constraint violations and/or inaccurate and implausible solutions, as we vary input materials, contact numbers and time step. We also exercise IPC across a wide range of existing and new benchmark tests and demonstrate its accurate solution over a broad sweep of reasonable time-step sizes and beyond (up to h = 2s) across challenging large-deformation, large-contact stress-test scenarios with meshes composed of up to 2.3M tetrahedra and processing up to 498K contacts per time step. For applications requiring high-accuracy we demonstrate tight convergence on all measures. While, for applications requiring lower accuracies, e.g. animation, we confirm IPC can ensure feasibility and plausibility even when specified tolerances are lowered for efficiency.
Mapping of Quantitative Trait Loci Controlling Physico-chemical Properties of Rice Grains (Oryza sativa L.)

Backcross inbred lines (BILs) derived from a cross of Nipponbare (japonica) / Kasalath (indica) // Nipponbare were used to identify quantitative trait loci (QTLs) controlling physico-chemical properties of rice grains such as amylose content (AC), alkali spreading score (ASS) and gel consistency (GC) by composite interval mapping over a period of two years. A total of 4 QTLs for AC were detected; qAC-5 and qAC-6 showed significant effects (hereafter referred to as “significant”) in both years, and qAC-6 explained more than 80 % of the phenotypic variance and was located in the wx region on the short arm of chromosome 6. The other 2 QTLs for AC with small additive effects were detected and were significant only in one year. Three QTLs for ASS were identified; qASS-6a and qASS-6b were significant in both years, and qASS-6a corresponded to a major gene located in the alk region on chromosome 6, while qASS-3 on chromosome 3 was significant only in one year. Five QTLs for GC were detected and all were significant only in one year. The lock of detection of major gene(s) for GC may be due to the fact that none of the parents were differentiated in terms of GC. These results showed that AC and ASS were mainly controlled by known gene loci, i.e., wx and alk, respectively, with modification by minor genes.
Isolation and characterization of microsatellite loci from Quercus mongolica var. crispula

Microsatellites were isolated and characterized for the Japanese oak species, Quercus mongolica var. crispula, distributed in temperate deciduous forests of Japan. Eleven of the 48 primer pairs designed successfully amplified unambiguous and polymorphic single loci among 67 Q. mongolica var. crispula individuals within a plot in southwestern Japan. The observed and expected heterozygosities of the 11 microsatellite markers ranged from 0.522 to 0.896 and from 0.536 to 0.882, respectively. These polymorphic microsatellite markers are useful for estimating pollen-mediated gene flow in Q. mongolica var. crispula.
Distortions in Production Networks

How does an economy's production structure determine its macroeconomic response to sectoral distortions? We study a static framework in which production is organized in an input-output network and firms' production decisions are distorted. We show how sectoral distortions manifest at the aggregate level via two channels: total factor productivity and the labor wedge. The strength of each channel depends jointly on the input-output structure and the distribution of shocks. Near efficiency, distortions generate zero first-order effects on TFP but non-zero first-order effects on the labor wedge; the latter we show to be determined by the sector's network "centrality. " We apply the model to the 2008-09 Financial Crisis and find that the U.S. input-ouput network may have amplified financial distortions by roughly a factor of two relative to a counterfactual economy devoid of intermediate good trade.
Age-Related Differences in the Association between Plasma High-Sensitivity C-Reactive Protein and Noncalcified or Mixed Coronary Atherosclerotic Plaques

Background Previous studies have demonstrated that plasma high-sensitivity C-reactive protein (hsCRP) was the predictor for unstable coronary plaque. Patients with noncalcified plaque (NCP) or mixed plaque (MP) have a higher risk of poor outcomes. However, the association between hsCRP and the presence of NCP or MP (NCP/MP) in old adults remains unclear, and if present, whether there exist differences between young and old adults remain unknown. Thus, the aim of this study was to investigate the role of hsCRP in predicting the presence of NCP/MP and evaluate whether age has any impact on this association. Methods A total of 951 subjects were included in this study. Complete clinical and laboratory data were collected. According to the characteristics of the most stenotic plaque, we divided them into 2 groups: calcified plaque (CP) and NCP/MP. Subjects with no plaque were classified as the control group (CR). Subjects with age ≥ 60 years were defined as older adults, and those with age < 60 years were classified as nonelderly people. Results Patients with NCP/MP had significantly higher hsCRP level compared with subjects with CR or CP in older adults but not in nonelderly people. The proportion of NCP/MP was significantly increased from 27.0% in the hsCRP < 1.25 mg/L group to 42.7% in the hsCRP > 2.70 mg/L group in older adults. Multiple logistic regression analysis showed that hsCRP was an independent risk factor for the presence of NCP/MP (odds ratio (OR) = 1.093, 95% CI 1.032–1.157, P = 0.001) only in older adults. Conclusions hsCRP is independently associated with the presence of NCP/MP in older adults but not in nonelderly people. These results suggest the potential significance of hsCRP-lowering regimens in older adults with NCP/MP.
Private Sector and Civil Society Partnerships against Corruption in Southeastern Europe

The study seeks to determine whether anti-corruption collaborations between civil society organizations (CSOs) and the private sector (PS) in Southeastern Europe (SEE) exist, as well as to understand the context and nature of such partnerships. As corruption is one of the greatest and most pressing issues in the region, it is of crucial importance that multi-stakeholder groups join forces in the fight against it, as well as to improve transparency and good governance overall. Based on various literature and country desk reviews, followed by qualitative semi-structured interviews with representatives from both CSOs and the PS in the region, the research has found little formal, systemic and effective CSO-PS partnerships in SEE. There are several institutional and sectoral/ individual factors and reasons behind this lack. Nevertheless, all the PS and CSO representatives acknowledged the crucial role of a common direction and collective action in the fight against corruption in the region.
A Deliberate BIAT Logic for Modeling Manipulations

In many applications, selfish, dishonest or malicious agents may find an interest in manipulating others. While many works deal with designing robust systems, few works deal with logical reasoning about manipulation. Based on social science literature, we propose a new logical framework to express and reason about manipulation , defined as a deliberate effect to instrumentalize a victim while making sure to conceal that instrumentalization. Since manipulation relies on deliberate effects of a manipulator, we propose a new BIAT operator to catch deliberate effects. We first prove that this logical framework is sound and complete. Then we formally define manipulation and we show our logical framework also expresses related notions such as coercion, persuasion, or deception.
A Selftuning Approach for Improving Composite Schema Matchers

Most of the schema matching tools are assembled from multiple match algorithms, each employing a particular technique to improve matching accuracy and making matching systems extensible and customizable to a specific domain. Recently, it has been pointed out that the main issue is how to select the most suitable match algorithms to execute for a given domain and how to adjust the multiple parameters. The solutions provided by current schema matching tools consist in aggregating the results obtained by several match algorithms to improve the quality of the discovered matches. In this article, we present a novel method to replace this aggregation function and its drawbacks. Unlike other composite matchers, our matching engine makes use of a decision tree to combine the most appropriate match algorithms. As a first consequence, the performance of the system is improved since only a subset of match algorithms from a large library is used. The second advantage is the improvement of the quality of matches. Indeed, for a given domain, only the most suitable match algorithms are used. Our approach is also able to learn the most appropriate match algorithms for a given domain by relying on the expert feedback. It can also selftune some parameters like thresholds and the performance versus quality ratio.
STUDIES ON OBTAINING OF DRINKING WATER QUALITY IN A DRINKING WATER TREATMENT PLANT

The paper presents studies regarding the water quality from the accumulation lake, characterised by higher turbidity in the studied period, and also the water treatment possibilities with new coagulation reagents (aluminium bases poly chlorines) and alkalisation, comparative with aluminium sulphate and calcium hydroxide, following the efficiency and inefficiency of those in the colloidal systems destabilisation and zeta potential reduction.
The Phantom Menace: Bridging the Regulatory Gap for Sustainable Biogas

Biogas is a key component of the energy system of the future. Once upgraded to biomethane, it has a similar chemical composition to natural gas, thus offering a promising alternative to fossil fuels. For instance, it can be injected into the natural gas grid or power gas-fueled vehicles, thus contributing to the decarbonization of the transport sector. However, biogas production is not always environmentally sustainable. On one hand, biogas production from waste (e.g. manure or agricultural residues) represents an effective way to promote virtuous circles of resource use and re-use. On the other hand, the production of biogas from energy crops poses serious sustainability challenges, due to the negative impacts on biodiversity and the possible competition with food and feed crops. Similar risks are taken into account in the policy framework of the European Union (EU), which, following the adoption of the new Renewable Energy Directive (RED 2018), provides specific sustainability criteria for biogas production. Outside the EU, few other jurisdictions specifically address sustainability challenges related to biogas production. Adopting an interdisciplinary approach, in the first part of this paper we conduct an LCA analysis to assess the regionalized impact of biogas production from different feedstocks. In the second part of the paper, we analyze the essential elements of the EU sustainability criteria and, taking stock of the results of the LCA analysis, we propose a threefold set of policy recommendations to increasingly promote biogas sustainability, with a specific focus on developing countries.
Exploratory study into presence within a social virtual reality environment for use in exposure therapy

This paper presents an explorative study investigating the prospects of using social virtual reality as a tool in exposure therapy for children diagnosed with Autism Spectrum Disorder. A 360° video of a children’s musical concert was used to perform exposure therapy on children diagnosed with Autism Spectrum Disorder (ASD). The prototype allowed the teacher and the student to be present in the same virtual environment. Additionally, the child and their teacher were able to play virtual reality musical instruments along with the musicians of concert experience and communicate with each other through gestures of virtual avatars. An exploratory study was conducted on 12 children diagnosed with ASD and 4 teachers. Both parties were from a school for children with mental disabilities. From data analysis, we can conclude that the prototype provided the children with a fun and playful experience. The potentials and limitations of the social VR application is discussed in the paper
BOPL: Batch Optimized Persistent List

Due to the increase of the number of operations in the databases, and with the improvement of both performance and capacity of the DRAM, the use of In Memory Database (IMDB) has become feasible instead of the current Disk Based Database (DBDB). The emergence of more efﬁcient memories, such as Optane SSD and NVRAM, may lead to replacing the disks in the IMDB and making them more efﬁcient. The use of Non-Volatile Random Access Memory (NVRAM) imposes a modiﬁcation on the structures that are used in DBDB, because in case of a system failure, the data in NVRAM may be incoherent. A number of new structures have been developed with the aim of making the data consistent in NVRAM, but it was found that these structures tend to perform poorly, due to the fact that each modiﬁcation is required to persist. Batch-Optimized Persistent List (BOPL) aims to achieve better performance compared to existing solutions, leaving the structures always consistent in both architectures that have persistent memory such as Intel Optane and/or NVRAM. This type of performance is obtained in BOPL, because persistence is not guaranteed during the critical path of operations, but in the background.
Evolution of pistil length as a choice mechanism for pollen quality

During the fertilisation process in plants, pollen tube growth rate may be selected as a trait important in male to male competition. Since female morphology provides the necessary selective arena for such competition. we investigate if sexual selection theory can be used to explain the evolution of pistil length as a female choice mechanism. This choice is performed by direct interference with male to male competition. Furthermore, the sessile nature of plants limits the number of mates a female can choose between, which could limit the benefit a female can gain from distinguishing between donors. To mirror these circumstances, we model a situation when there are only two competitors at a time. Using a game theoretical approach we show that if pollen tube growth rate can be used as an indication of heritable quality, pistil length can be selected in response to variation of this trait. We further find that length of the pistil affects selection of pollen tube growth rate. Thus female preference and male competitive ability co-evolve, but this does not necessarily lead to a positive relationship between the two. Under certain circumstances we find a negative relation instead. Given realistic differences in male quality, the model indicates that there is a potential for evolution of female morphology as a choice mechanism for pollen quality. (Less)
Modeling Disinformation and the Effort to Counter It: A Cautionary Tale of When the Treatment Can Be Worse Than the Disease

The problem of disinformation in online social networks has recently received a considerable amount of attention from the research community. It has been shown that online social networks are extensively getting exploited to alter public opinion and individuals’ stance on a wide-range of topics. This study proposes an agent-based model that simulates a disinformation campaign by a group of organized users called conspirators , targeting a susceptible population, which are then opposed by a parallel organized group of users referred to as inouclators that try to act as a barrier to the spread of disinformation. The results of this study indicate that the process of inoculating a susceptible population against disinforma-tion is mostly at the price of further polarizing the population.