Miracle-dz/UniFAR-FTUs huggingface dataset:
A temporally oriented data model

The research into time and data models has so far focused on the identification of extensions to the classical relational model that would provide it with “adequate” semantic capacity to deal with time. The temporally oriented data model (TODM) presented in this paper is a result of a different approach, namely, it directly operationalizes the pervasive three-dimensional metaphor for time. One of the main results is thus the development of the notion of the data cube: a three-dimensional and inherently temporal data construct where time, objects, and attributes are the primary dimensions of stored data. TODM's cube adds historical depth to the tabular notions of data and provides a framework for storing and retrieving data within their temporal context. The basic operations in the model allow the formation of new cubic views from existing ones, or viewing data as one moves up and down in time within cubes. This paper introduces TODM, a consistent set of temporally oriented data constructs, operations, and constraints, and then presents TOSQL, a corresponding end-user's SQL-like query syntax. The model is a restricted but consistent superset of the relational model, and the query syntax incorporates temporal notions in a manner that likewise avoids penalizing users who are interested solely in the current view of data (rather than in a temporal perspective). The naturalness of the spatial reference to time and the added semantic capacity of TODM come with a price—the definitions of the cubic constructs and basic operations are relatively cumbersome. As rudimentary as it is, TODM nonetheless provides a comprehensive basis for formulating an external data model for a temporally oriented database.
Relevance Segmentation of Laparoscopic Videos

In recent years, it became common to record video footage of laparoscopic surgeries. This leads to large video archives that are very hard to manage. They often contain a considerable portion of completely irrelevant scenes which waste storage capacity and hamper an efficient retrieval of relevant scenes. In this paper we (1) define three classes of irrelevant segments, (2) propose visual feature extraction methods to obtain irrelevance indicators for each class and (3) present an extensible framework to detect irrelevant segments in laparoscopic videos. The framework includes a training component that learns a prediction model using nonlinear regression with a generalized logistic function and a segment composition algorithm that derives segment boundaries from the fuzzy frame classifications. The experimental results show that our method performs very good both for the classification of individual frames and the detection of segment boundaries in videos and enables considerable storage space savings.
Effects of seasonal olive mill wastewater application on soil: field experiment in Bait Reema village, Palestine

The global problematic issue of the olive oil industry is in its generation of large amounts of olive mill wastewater (OMW). The direct discharge of OMW to the soil is very common which presents environmental problems for olive oil producing countries. Both, positive as well as negative effects on soil have been found in earlier studies. Therefore, the current study hypothesized that whether beneficial effects or negative effects dominate depends on the prevailing conditions before and after OMW discharge to soil. As such, a better understanding of the OMW-soil interaction mechanisms becomes essential for sustainable safe disposal of OMW on soil and sustainable soil quality. A field experiment was carried out in an olive orchard in Palestine, over a period of 24 months, in which the OMW was applied to the soil as a single application of 14 L m-2 under four different environmental conditions: in winter (WI), spring (SP), and summer with and without irrigation (SUmoist and SUdry). The current study investigated the effects of seasonal conditions on the olive mill wastewater (OMW) soil interaction in the short-term and the long-term. The degree and persistence of soil salinization, acidification, accumulation of phenolic compounds and soil water repellency were investigated as a function of soil depth and time elapsed after the OMW application. Moreover, the OMW impacts on soil organic matter SOM quality and quantity, total organic carbon (SOC), water-extractable soil organic carbon (DOC), as well as specific ultraviolet absorbance analysis (SUVA254) were also investigated for each seasonal application in order to assess the degree of OMW-OM decomposition or accumulation in soil, and therefore, the persisting effects of OMW disposal to soil. The results of the current study demonstrate that the degree and persistence of relevant effects due to OMW application on soil varied significantly between the different seasonal OMW applications both in the short-term and the long-term. The negative effects of the potentially hazardous OMW residuals in the soil were highly dependent on the dominant transport mechanisms and transformation mechanisms, triggered by the ambient soil moisture and temperature which either intensified or diminished negative effects of OMW in the soil during and after the application season. The negative effects of OMW disposal to the soil decreased by increasing the retention time of OMW in soil under conditions favoring biological activity. The moderate conditions of soil moisture and temperature allowed for a considerable amount of applied OMW to be biologically degraded, while the prolonged application time under dry conditions and high temperature resulted in a less degradable organic fraction of the OMW, causing the OMW constituents to accumulate and polymerize without being degraded. Further, the rainfall during winter season diminished negative effects of OMW in the soil; therefore, the risk of groundwater contamination by non-degraded constituents of OMW can be highly probable during the winter season.
Attention to Local Health Burden and the Global Disparity of Health Research

Most studies on global health inequality consider unequal health care and socio-economic conditions but neglect inequality in the production of health knowledge relevant to addressing disease burden. We demonstrate this inequality and identify likely causes. Using disability-adjusted life years (DALYs) for 111 prominent medical conditions, assessed globally and nationally by the World Health Organization, we linked DALYs with MEDLINE articles for each condition to assess the influence of DALY-based global disease burden, compared to the global market for treatment, on the production of relevant MEDLINE articles, systematic reviews, clinical trials and research using animal models vs. humans. We then explored how DALYs, wealth, and the production of research within countries correlate with this global pattern. We show that global DALYs for each condition had a small, significant negative relationship with the production of each type of MEDLINE articles for that condition. Local processes of health research appear to be behind this. Clinical trials and animal studies but not systematic reviews produced within countries were strongly guided by local DALYs. More and less developed countries had very different disease profiles and rich countries publish much more than poor countries. Accordingly, conditions common to developed countries garnered more clinical research than those common to less developed countries. Many of the health needs in less developed countries do not attract attention among developed country researchers who produce the vast majority of global health knowledge—including clinical trials—in response to their own local needs. This raises concern about the amount of knowledge relevant to poor populations deficient in their own research infrastructure. We recommend measures to address this critical dimension of global health inequality.
Subinhibitory Concentrations of Perilla Oil Affect the Expression of Secreted Virulence Factor Genes in Staphylococcus aureus

Background The pathogenicity of staphylococcus aureus is dependent largely upon its ability to secrete a number of virulence factors, therefore, anti-virulence strategy to combat S. aureus-mediated infections is now gaining great interest. It is widely recognized that some plant essential oils could affect the production of staphylococcal exotoxins when used at subinhibitory concentrations. Perilla [Perilla frutescens (L.) Britton], a natural medicine found in eastern Asia, is primarily used as both a medicinal and culinary herb. Its essential oil (perilla oil) has been previously demonstrated to be active against S. aureus. However, there are no data on the influence of perilla oil on the production of S. aureus exotoxins. Methodology/Principal Findings A broth microdilution method was used to determine the minimum inhibitory concentrations (MICs) of perilla oil against S. aureus strains. Hemolysis, tumour necrosis factor (TNF) release, Western blot, and real-time RT-PCR assays were performed to evaluate the effects of subinhibitory concentrations of perilla oil on exotoxins production in S. aureus. The data presented here show that perilla oil dose-dependently decreased the production of α-toxin, enterotoxins A and B (the major staphylococcal enterotoxins), and toxic shock syndrome toxin 1 (TSST-1) in both methicillin-sensitive S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA). Conclusions/Significance The production of α-toxin, SEA, SEB, and TSST-1 in S. aureus was decreased by perilla oil. These data suggest that perilla oil may be useful for the treatment of S. aureus infections when used in combination with β-lactam antibiotics, which can increase exotoxins production by S. aureus at subinhibitory concentrations. Furthermore, perilla oil could be rationally applied in food systems as a novel food preservative both to inhibit the growth of S. aureus and to repress the production of exotoxins, particularly staphylococcal enterotoxins.
Sentiment Analysis of Breast Cancer Screening in the United States using Twitter

Whether or not U.S. women follow the recommended breast cancer screening guidelines is related to the perceived benefits and harms of the procedure. Twitter is a rich source of subjective information containing individualsâ sentiment towards public health interventions/technologies. Using our modified version of Hutto and Gilbert (2014) sentiment classifier, we described the temporal, geospatial, and thematic patterns of public sentiment towards breast cancer screening with 8 months of tweets (n=64,524) in the U.S. To examine how sentiment was related to screening uptake behaviour, we investigated and identified significant associations between breast cancer screening sentiment (via Twitter) and breast cancer screening uptake (via BRFSS) at the state level.
Risks of Death and Graft Failure After Surgical Versus Percutaneous Coronary Revascularization in Renal Transplant Patients

Background Reliable data regarding absolute and relative risks of death and graft failure after coronary artery bypass graft surgery (CABG) and percutaneous coronary intervention (PCI) in renal transplant patients are unavailable. Methods and Results Renal transplant patients undergoing inpatient CABG (n=1400) or PCI (n=4097) were identified from United States Renal Data System data. Cumulative incidence of nonfatal graft failure and death was reported for observed events. A Cox model with the Fine–Gray method was used to account for competing risks in assessing relative hazards. Age and race were similarly distributed; patients who underwent CABG were more likely to have acute arrhythmia and congestive heart failure but less likely to have acute myocardial infarction on index admission. In‐hospital death was more frequent after CABG (5.6% versus 3.0%, P<0.001). Cumulative incidence of death, graft failure, and the combined outcome at 3 years were 23.1%, 15.4%, and 38.5% after CABG and 22.9%, 13.3%, and 36.1% after PCI, respectively. In adjusted analyses, CABG was not associated with increased risk of graft failure versus PCI during the first 6 months (hazard ratio 1.06, 95% CI 0.79 to 1.43) or from 6 to 36 months (0.98, 0.78 to 1.22). Risk of death increased after CABG during the first 3 months (1.37, 1.08 to 1.73), but decreased from 6 months on (0.76, 0.63 to 0.93). Conclusions CABG does not appear to be associated with a difference in risk of graft failure compared with PCI in renal transplant patients. Compared with PCI, adjusted risk of early death is higher after CABG; however, mortality from 6 months on is lower.
Sparsely encrusted hardground in the Darriwilian calcareous sandstone of Cape Pakri, NW Estonia (Baltica)

The occurrence of echinoderm and ptilodictyid bryozoan holdfasts on the surface of Darriwilian calcareous sandstone in northwestern Estonia indicates that it was lithified before encrustation. Pelmatozoans outnumber the bryozoans and cover a larger area of the hardground although both are very sparse. The hardground is very sparsely encrusted (0.37% of the total area studied) and lacks signs of bioerosion.
Introduction to Temporal Database Research

A wide range of database applications manage time-varying data. In contrast, existing database technology provides little support for managing such data. The research area of temporal databases aims to change this state of affairs by characterizing the semantics of temporal data and providing expressive and efficient ways to model, store, and query temporal data. This chapter offers a brief introduction to temporal database research. It concisely introduces fundamental temporal database concepts, surveys state-of-the-art solutions to challenging aspects of temporal data management, and also offers a look into the future of temporal database research.
Erd\H{o}s-P\'osa property of chordless cycles and its applications

A chordless cycle in a graph $G$ is an induced subgraph of $G$ which is a cycle of length at least four. We prove that the Erd\H{o}s-P\'osa property holds for chordless cycles, which resolves the major open question concerning the Erd\H{o}s-P\'osa property. Our proof for chordless cycles is constructive: in polynomial time, one can find either $k+1$ vertex-disjoint chordless cycles, or $ck^2 \log k$ vertices hitting every chordless cycle for some constant $c$. It immediately implies an approximation algorithm of factor $\mathcal{O}(\sf{opt}\log {\sf opt})$ for Chordal Vertex Deletion. We complement our main result by showing that chordless cycles of length at least $\ell$ for any fixed $\ell\ge 5$ do not have the Erd\H{o}s-P\'osa property. As a corollary, for a non-negative integral function $w$ defined on the vertex set of a graph $G$, the minimum value $\sum_{x\in S}w(x)$ over all vertex sets $S$ hitting all cycles of $G$ is at most $\mathcal{O}(k^2 \log k)$ where $k$ is the maximum number of cycles (not necessarily vertex-disjoint) in $G$ such that each vertex $v$ is used at most $w(v)$ times.
Novel Algorithms CIPFP for Mining Frequent Patterns using Counting Inference from Probabilistic Databases and Future Possibilities

We consider the problem of discovering frequent item sets and association rules between items in a large database of transactional databases acquired under uncertainty. A probabilistic database considered here is one in which with each transaction associated is a probability, represents the confidence that the transaction will occur with given associated certainty. In this paper, we address the problem of the efficiency of the main phase of most data mining applications: The frequent pattern extraction. This problem is mainly related to the number of operations required for counting pattern supports in the database and we propose a new method, called counting inference probabilistic frequent pattern miner in probabilistic databases, this algorithm allows to perform as few support counts as possible. It is optimized to reduce the number of database scan as well as the number of patterns for which explicit support count is required. Using this method, the support of a pattern is determined without accessing the database whenever possible, using the supports of some of its sub-patterns called key patterns. This method was implemented in the CIPFP, counting inference based probabilistic frequent pattern mining algorithm that is an optimization of the simple and efficient Apriori algorithm. The goal is to transform all key patterns into non-key patterns as early as possible as for non-key-patterns database scan is not required at all. General Terms Data Mining, Big Data, Data Science, Association Rule Mining,
Radial basis Boltzmann machines and learnng with missing values

A Radial Basis Boltzmann Machine (RBBM) is a specialized Boltzmann Machine archi tecture that combines feed-forward mapping with probability estimation in the input space, and for which very fast learning rules exist. The hidden representation of the network displays symmetry breaking as a function of the noise in the Glauber dynamics. Thus generalization can be studied as a function of the noise in the neuron dynamics instead of as a function of the number of hidden units. For the special case of unsupervised learning, we show that this method is an elegant alternative of k nearest neighbor, leading to comparable performance without the need to store all data. We show that the RBBM has good classification performance compared to the MLP. The main advantage of the RBBM is that simultaneously with the input-output mapping, a model of the input space is obtained which can be used for learning with missing values. We show that the RBBM compares favorably to the MLP for large percentages of missing values.
Establishing the Relationship Between Discourse Models and User Models

Many current research efforts have focused on building cooperat ive systems that interact with the{r users in a natural language such as English. To be effective, these systems must be robust, their dialog must be coherent, and their responses must be helpful to the user. A user m o d e l (UM), which can be modified during the interaction to represent updated beliefs about the current user, is one mechanism that can contribute to a robust, coherent, and cooperat ive dialog. In general, when we as speakers describe certain situations, we try to communicate these situations to our listeners. As proposed by some researchers (Webber 1978, Kamp 1984), speakers do so by attempting to get their listeners to construct an appropriate model: a d i scourse mode l . A discourse model (DM) is viewed as containing representations of entities, along with their properties and relations they participate in. The key, then, in successful communication is for the speaker to transmit as much information about those entities, their properties and relations to the listener so as to achieve the goals of the current interaction. From the point of view of a system, a computational discourse model is used by the system to generate and/or interpret a discourse. This paper focuses on the relationship between DMs and UMs. It starts by describing what a DM is, and the role it plays in a coherent di~dog. It then describes what a UM is, and the role it plays in a cooperat ive dialog. I argue that the DM should be viewed as one part of the UM-tha t is, as one part of the system's model of the user. The examples of the natural language interactions are presented in the context of a natural language interface to an expert system that provides advice on cooking with chilies. (Part of the data was taken from the section "Cooking with Chilies" that appeared in Bon A p p e t i t magazine, December 1986. The expert system can provide information about the different varieties of chili peppers as well as descriptions of how to " tu rn down the hea t " of the chilies (make them less spicy), and how to cook with them without getting any kind of skin or eye irritations. ) I justify this by showing how DMs can be viewed as part of UMs and how both models can affect each other. In other words, part of the UMs that systems have correspond to the DM, that is, a representat ion of what is talked about in a specific interaction. This piece, which changes with each discourse, affects the UM and varies from interaction to interaction.
Tropical forest recovery from logging: a 24 year silvicultural experiment from Central Africa

Large areas of African moist forests are being logged in the context of supposedly sustainable management plans. It remains however controversial whether harvesting a few trees per hectare can be maintained in the long term while preserving other forest services as well. We used a unique 24 year silvicultural experiment, encompassing 10 4 ha plots established in the Central African Republic, to assess the effect of disturbance linked to logging (two to nine trees ha−1 greater than or equal to 80 cm DBH) and thinning (11–41 trees ha−1 greater than or equal to 50 cm DBH) on the structure and dynamics of the forest. Before silvicultural treatments, above-ground biomass (AGB) and timber stock (i.e. the volume of commercial trees greater than or equal to 80 cm DBH) in the plots amounted 374.5 ± 58.2 Mg ha−1 and 79.7 ± 45.9 m3 ha−1, respectively. We found that (i) natural control forest was increasing in AGB (2.58 ± 1.73 Mg dry mass ha−1 yr−1) and decreasing in timber stock (−0.33 ± 1.57 m3 ha−1 yr−1); (ii) the AGB recovered very quickly after logging and thinning, at a rate proportional to the disturbance intensity (mean recovery after 24 years: 144%). Compared with controls, the gain almost doubled in the logged plots (4.82 ± 1.22 Mg ha−1 yr−1) and tripled in the logged + thinned plots (8.03 ± 1.41 Mg ha−1 yr−1); (iii) the timber stock recovered slowly (mean recovery after 24 years: 41%), at a rate of 0.75 ± 0.51 m3 ha−1 yr−1 in the logged plots, and 0.81 ± 0.74 m3 ha−1 yr−1 in the logged + thinned plots. Although thinning significantly increased the gain in biomass, it had no effect on the gain in timber stock. However, thinning did foster the growth and survival of small- and medium-sized timber trees and should have a positive effect over the next felling cycle.
An experimental test of whether cheating is context dependent

Microbial cells rely on cooperative behaviours that can breakdown as a result of exploitation by cheats. Recent work on cheating in microbes, however, has produced examples of populations benefiting from the presence of cheats and/or cooperative behaviours being maintained despite the presence of cheats. These observations have been presented as evidence for selection favouring cheating at the population level. This apparent contradiction arises when cheating is defined simply by the reduced expression of a cooperative trait and not in terms of the social costs and benefits of the trait under investigation. Here, we use two social traits, quorum sensing and iron‐scavenging siderophore production in Pseudomonas aeruginosa, to illustrate the importance of defining cheating by the social costs and benefits. We show that whether a strain is a cheat depends on the costs and benefits associated with the social and abiotic environment and not the absolute expression of a cooperative trait.