Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Verb Inference Rules from Linguistically-motivated Evidence

Many natural language processing (NLP) applications need to perform semantic inference in order to complete their task. Such inference relies on knowledge that can be represented by inference rules between atomic units of language such as words or phrases. In this work, we focus on automatically learning one of the most important rule types, namely, entailment rules between verbs. Most prior work on learning such rules focused on a rather narrow set of information sources: mainly distributional similarity, and to a lesser extent manually constructed verb co-occurrence patterns. In this work, we claim that it is imperative to utilize information from various textual scopes: verb co-occurrence within a sentence, within a document, as well as overall corpus statistics. To this end, we propose an integrative model that improves rule learning by exploiting entailment cues: linguistically motivated indicators that are specific to verbs. These cues operate at different levels of verb co-occurrence and signal the existence (or non-existence) of the entailment relation between any verb pair. These novel cues are encoded as features together with other useful features adapted from prior work. Two experiments performed in different settings show that our proposed model outperforms, with a statistically significant improvement, state-of-the-art algorithms. Further feature analysis indicates that our novel linguistic features substantially improve performance and that features at all co-occurrence levels, and especially at the sentence level, contain valuable information for verb entailment learning.
Resource savings in gridless coherent submarine networks with filterless architectures

Flexible and scalable networking solutions are req uir d to offer more efficient bandwidth allocation and increased connectivity in submarine networks. In this regard, filterless optical networks based on agile edge nod es equipped with coherent transceivers and passive broadcast-and-select nodes are promising co st-effective options which allow for more flexible capacity allocation and resource optimizat ion in the optical layer. In this paper, we evaluate possible resource and cost savings in a fi lterless submarine network architecture.
Extension of Water Flowing Fractured Zone during Coal Seams Mining in No.1 Mine of Tashendian Area

In coal seams mining in No. 1 mine of Tashendian area, three methods of theoretical analysis, UDEC numerical simulation, and physical simulation test were used in this research to analyze the extension height of water flowing fractured zone and the height of waterproof coal (rock) pillar. By calculation, it was obtained that, after each coal seam mined out, the height of water flowing fractured zone is about 33.7 m above 8-1 # coal seam, and the size of waterproof coal (rock) pillar greater than 44.06 m was reasonable; after upper and lower groups coal seam mined out, the height of water flowing fractured zone is about 81 m above 8-1# coal seam, and the size of waterproof coal (rock) pillar greater than 91.36 m was reasonable; after all coal seams mined out simultaneously, the height of water flowing fractured zone is about 95.1 m above 8-1 # coal seam, and the size of waterproof coal (rock) pillar greater than 105.46 m was reasonable. By numerical simulation, it was obtained that, after upper and lower groups coal seam mined out, the height of water flowing fractured zone is about 46.0 m above 8-1 # coal seam, and the size of waterproof coal (rock) pillar greater than 56.36 m was reasonable; after all coal seams mined out simultaneously, the height of water flowing fractured zone is about 76.0 m above 8-1# coal seam, and the size of waterproof coal (rock) pillar greater than 86.36 m was reasonable; By physical simulation, it was obtained that, after upper and lower groups coal seam mined out, the height of water flowing fractured zone is about 40.0 m above 8-1 # coal seam. And the waterproof coal (rock) pillar was about 70.0 m between and the aquifer. In situ production, each coal seam was mined out orderly. Keywords—coal seams, water flowing fractured zone, waterproof coal (rock) pillar, theoretical analysis, numerical simulation, physical simulation
Bioaccessibility of potentially harmful elements (PHEs) from environmental matrices and implications for human health

Internationally publicized impacts upon human health associated with exposure to potentially harmful elements (PHE) have been reported globally. Particular concern has surrounded the exposure to Pb indicated by the presence of highly elevated concentrations of Pb in blood and hair samples amongst internally displaced populations (IDPs) in Mitrovica, Kosovo, following the Kosovan War (Runow, 2005). The exposure risk to humans depends in part on the potential of the PHE to mobilise from its matrices in the human digestive and respiratory systems (bioaccessibility) and enter the blood stream (bioavailability). This study utilizes physiologically based in-vitro extraction methods to assess the bioaccessibility of PHEs in surface soils and metallurgical waste in Mitrovica and assesses the potential daily ingestion of soil-bound PHEs (As, Cd, Cu, Mn, Pb, and Zn) and inhalation (Pb) of particulate matter < 10 μm (PM10). A total of 63 samples (52 surface soils and 11 mine/smelter waste) were selected based on PHE loadings and their spatial distribution. For the in-vitro oral bioaccessibility 0.3 g subsamples were analysed using the UBM method (adopted by BARGE, Wragg et al., 2009). The mean bioaccessibility of Cd, Pb and Zn in the gastric phase is 51 %, 57 % and 41 %, respectively, compared to 18 %, 16% and 14%, respectively, in the gastric-intestinal phase. The trend with As and Cu data is less consistent across the sample locations, with a mean of 20 % and 22 % in the gastric phase and 22 % and 26 % bioaccessibility in the gastric-intestinal phase, respectively. To investigate the role of mineralogy in understanding the bioaccessibility data subsamples (< 250 μm) were submitted to the British Geological Survey, Nottingham, for X-ray diffraction (XRD) analyses. Samples associated with lower bioaccessibilities typically contain a number of XRD-identifiable primary and secondary mineral phases, particularly As- and Pb-bearing arseninian pyrite, beudantite, galena and cerrusite. For the inhalation bioaccessibility, PM10 subsamples were extracted from 33 samples using a locally developed laboratory based wet method. The 0.3 g PM10 subsamples were analysed using a new tracheobronchial fluid and protocol developed as part of this study. The bioaccessibility of Pb for all the 33 samples tested ranged from 0.02 to 11 % and it is consistent with a range (0.17 to 11 %) previously reported by Harris and Silberman (1988) for Pb bioaccessibility in inhalable particulates (< 22 μm) using canine serum. Quantification of the potential human exposure risk associated with the inhalation and ingestion of soil-associated PHEs indicates the likely possibility of local populations exceeding the recommended tolerable daily intake of Pb. IEUBK model (USEPA, 2007) predicted mean blood Pb concentrations for children based on bioaccessible (ingestion) data are above the CDC level of concern (10 μg/dL).
Beijing City Lab

In the past decade, rapid urbanization and industrialization has taken place in China, and is still making a big difference in cities. Mobile Internet has been widely spread, benefiting the dramatic growth of Web 2.0 applications. Nearly everyone is social media user. And cities are evolving into “Wired Cities” with digital devices installed everywhere, intended to monitor, manage and regulate urban flows. As a result, data explosion has taken place in cities. With advanced techniques on data storage and high-performance computing, big/open urban data has opened up important development opportunities for urban studies, planning practice and commercial consultancy. Urban researchers and planners are eager to make use of these abundant, sophisticated, dynamic, and more-spatially-temporally-detailed data to deepen our understanding of urban form and functions. However, lack of proper data for urban analytics is an often-met dilemma. Open urban data in China is still at an early stage. Very few urban data is freely accessible, due to constraints on data distribution and data holders’ concerns of losing their own advantages. Besides, cities are complex systems, efficient and effective interoperation of multi-source urban datasets is a must to draw reliable conclusions on urban behaviors, but dealing with the heterogeneity between datasets is also another critical challenge, especially for urban planners or government officers, who care about and understand cities, need the support from data analysis, but has little data processing experience. In such context, we initiated SinoGrids (Plan Xu Xiake), a crowdsourcing platform for encouraging the standardization (downscaling), sharing and interoperation of micro-scale urban data in China. On one hand, the downscaling preserves the advantage of original data holder and can thus, provide more sharable urban datasets. On the other hand, the downscaling works as a standardization process, making the datasets more manageable, and also, providing a way for effective and efficient interoperation of multi-source urban data. Technical guidelines and tools of the standardization process are provided and freely accessible to make SinoGrids more easily accepted and applicable. Last but not least, a human participated test was proposed for user performance evaluation of SinoGrids.
Necessary and Sufﬁcient Conditions for High-Dimensional Salient Feature Subset Recovery

—We consider recovering the salient feature subset for distinguishing between two probability models from i.i. d. samples. Identifying the salient set improves discrimination performance and reduces complexity. The focus in this work is on the high-dimensional regime where the number of variables d , the number of salient variables k and the number of samples n all grow. The deﬁnition of saliency is motivated by error exponents in a binary hypothesis test and is stated in terms of relative entropies. It is shown that if n grows faster than max { ck log(( d − k ) /k ) , exp( c (cid:2) k ) } for constants c,c (cid:2) , then the error probability in selecting the salient set can be made arbitrarily small. Thus, n can be much smaller than d . The exponential rate of decay and converse theorems are also provided. An efﬁcient and consistent algorithm is proposed when the distributions are graphical models which are Markov on trees.
On Gapping Grammars

A Gapping Grammar (GG) has rewriting rules of the form: \[\alpha_{1}, {\em gap}(x_{1}), \alpha_{2}, {\em gap}(x_{2}), \ldots, \alpha_{n-1}, {\em gap}(x_{n-1}), \alpha_{n} \rightarrow \beta\] \[\alpha_{i} \epsilon V_{N} \bigcup V_{T}\] \{ {\em gap}(x_{1}),{\em gap}(x_{2}), \ldots,{\em gap}(x_{n-1}) \}\] \[x_{i} \epsilon V_{T}^{*}\] \[\beta \epsilon V_{N}^{*} \bigcup V_{T}^{*} \bigcup G^{*}\] where $V_{T}$ and $V_{N}$ are the terminal and non-terminal vocabularies of the Gapping Grammar. Intuitively, a GG rule allows one to deal with unspecified strings of terminal symbols called {\em gaps}, represented by $x_{1}, x_{2}, \ldots, x_{n-1}$, in a given context of specified terminals and non-terminals, represented by $\alpha_{1}, \alpha_{2}, \ldots, \alpha_{n}$ and then to distribute them in the right hand side $\beta$ in any order. GG''s are a generalization of Fernando Pereira''s {\em Extrapontion Grammars} where rules have the form (using our notation ): \begin{eqnarray*} \alpha_{1},{\em gap}(x_{1}), \alpha_{2}, {\em gap}(x_{2}), \ldots, {\em gap}(x_{n-1}), \alpha_{n} \rightarrow \\ \beta, {\em gap}(x_{1}), {\em gap}(x_{2}), \ldots, {\em gap}(x_{n-1}) \end{eqnarray*} i.e., gaps are rewritten in their sequential order in the rightmost positions of the rewriting rule. In this paper we motivate GG''s by presenting grammatical examples where XGs are not adequate and we describe and discuss alternative implementations of GGs in logic.
Scholarship@Western Scholarship@Western

Knowledge of common events is central to many aspects of cognition. Intuitively, it seems as though events are linear chains of the activities of which they are comprised. In line with this intuition, a number of theories of the temporal structure of event knowledge have posited mental representations (data structures) consisting of linear chains of activities. Competing theories focus on the hierarchical nature of event knowledge, with representations comprising ordered scenes, and chains of activities within those scenes. We present evidence that the temporal structure of events typically is not well-deﬁned, but it is much richer and more variable both within and across events than has usually been assumed. We also present evidence that prediction-based neural network models can learn these rich and variable event structures and produce behaviors that reﬂect human performance. We conclude that knowledge of the temporal structure of events in the human mind emerges as a consequence of prediction-based learning.
Advanced Simulation Methods

Sequential Monte Carlo (SMC) methods, aka “particle methods”, constitute a broad and popular class of Monte Carlo algorithms that have been developed over the past twenty years to provide approximate solutions to intractable inference problems. For a detailed treatment of SMC, see [1], [2] and [3]. In these notes, we build upon Sequential Importance Sampling (SIS), which was introduced in the previous notes, in order to describe a generic SMC algorithm. The notation is essentially the same as in Chapter 8.
TweetVista : An AI-Powered Interactive Tool for Exploring Conversations

Citation Vijayaraghavan, Prashanth, Soroush Vosoughi, Ann Yuan, and Deb Roy. “TweetVista: An AI-Powered Interactive Tool for Exploring Conversations on Twitter. ” In Proceedings of the 22nd International Conference on Intelligent User Interfaces Companion (IUI '17 Companion), Limassol, Cyprus, March 1316, 2017, ACM, New York, NY, USA, pp.145-148. As Published http://dx.doi. org/10.1145/3030024.3040979 Publisher Association for Computing Machinery (ACM)
Edinburgh Research Explorer Understanding Learning Dynamics Of Language Models with SVCCA

Research has shown that neural models implicitly encode linguistic features, but there has been no research showing how these en-codings arise as the models are trained. We present the ﬁrst study on the learning dynamics of neural language models, using a simple and ﬂexible analysis method called Singular Vector Canonical Correlation Analysis (SVCCA), which enables us to compare learned representations across time and across models, without the need to evaluate directly on annotated data. We probe the evolution of syntactic, semantic, and topic representations and ﬁnd that part-of-speech is learned earlier than topic; that recurrent layers become more similar to those of a tagger during training; and embedding layers less similar. Our results and methods could inform better learning al-gorithms for NLP models, possibly to incor-porate linguistic information more effectively.
Impact of Climate Change on Smallholder Dairy Production and Coping Mechanism in Sub-Saharan Africa - Review

The current problems in the world are variation/declining of rainfall, shortage of feed and water, incidence of disease and rising of temperature, these are come about because of climate change. So, the objective of this review is to appraisal the impact of climate change on smallholder dairy production and coping mechanism in sub-Saharan Africa. Climate change is a long-term and significant change in the expected patterns of a specific region’s average weather for an appropriately significant period of time caused by the accumulation of greenhouse gases (gases facilitate for climate change are CO 2, CH 4 and N 2 O) in the atmosphere which leads to global warming. Africa has been identified as one of the parts of the world most vulnerable to the impacts of climate change. Though climate change affect livestock production directly and indirectly, can be mitigate through adaptation measures involve production and management system modifications, breeding strategies, institutional and policy changes, science and technology advances, and changing farmers’ perception, manure management, shifting dietary and reducing enteric methane production. Keywords: Climate Change, Smallholder dairy production, Mitigation, Sub Saharan Africa
Rural primary school principals’ leadership strategies for ICT integration

This paper explored the factors influencing the leadership strategies of school principals in rural primary schools regarding the integration of information and communication technologies (ICTs) in the process of teaching and learning in their schools. School principals are responsible for ensuring that there is ICTs integration in their schools’ teaching and learning processes. Embedded within the theory of learning-centred leadership (LCL), school principals have a responsibility to lead, foster, manage, and support the learning process for teachers and learners in their schools. Thus, school principals need to be well acquainted with innovative technologies for teaching and learning amidst the Fourth Industrial Revolution (4IR), which is global, complex, and fast-paced, to lead learning through ICT integration. Underpinned by the interpretive qualitative approach and using a multiple case study as a research design, this study generated data from three selected South African rural primary schools through face-to-face interviews with the three school principals. Data were analysed thematically. Findings revealed that school principals’ leadership strategies are influenced by their attitudes towards ICT integration into teaching and learning, their exposure to ICT workshops, and their own judgements of their abilities in using ICT. The paper recommends customised in-service training for school principals and teachers to alter and improve their exposure to, attitudes, perceptions toward ICT integration in teaching and learning.
Omnivorous summer feeding by juvenile Antarctic krill in coastal waters

The Antarctic krill Euphausia superba is often considered an herbivore but is notable for its trophic flexibility, which includes feeding on protistan and metazoan zooplankton. Characterizing krill trophic position (TP) is important for understanding carbon and energy flow from phytoplankton to vertebrate predators and to the deep ocean, especially as plankton composition is sensitive to changing climate. We used repeated field sampling and experiments to study feeding by juvenile krill during three austral summers in waters near Palmer Station, Antarctica. Our approach was to combine seasonal carbon budgets, gut fluorescence measurements, imaging flow cytometry, and compound‐specific isotope analysis of amino acids. Field measurements coupled to experimentally derived grazing functional response curves suggest that phytoplankton grazing alone was insufficient to support the growth and basal metabolism of juvenile krill. Phytoplankton consumption by juvenile krill was limited due to inefficient feeding on nanoplankton (2–20 μm), which constituted the majority of autotrophic prey. Mean krill TP and the metazoan dietary fraction increased in years with higher mesozooplankton biomass, which was not coupled to phytoplankton biomass. Comparing TP estimates using δ15N of different amino acids indicated a substantial and consistent food‐web contribution from heterotrophic protists. Phytoplankton, metazoans, and heterotrophic protists all were important contributors to a diverse krill diet that changed substantially among years. Juvenile krill fed mostly on heterotrophic prey during summer near Palmer Station, and this food web complexity should be considered more broadly throughout the changing Southern Ocean.
Estudo técnico em cerâmica pré-histórica do Brasil

This paper presents data resulting from the experimental part of the PhD thesis Analise cerâmica: estudo tecnotipologico, (Department of Anthropology, University of Sao Paulo, August 1988). Its subject matters are the study of ceramic paste, the burning temperature indices inference and the detection of coloring minerals present in the four ceramic sets originating from the two archaeological sites situated in the State of Sao Paulo ("Franco de Godoy" and "de Lagoa Sao Paulo") and two located in the State of Minas Gerais ("Prado" and "Silva Serrote"). The petrographic microscopy analysis of transmitted light, X Ray diffractometry analysis and scanning electronic microscopy and microanalysis techniques were employed in this Study.
Antioxidant and Neuroproliferative Effects of THL-3-PTD5 Peptide Derived from Hydramacin-1 Antimicrobial Peptide

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by reduced dopamine levels in the brain, affecting over 6 million people worldwide. While current treatments for patients primarily focus on symptom relief, there is a necessity for the development of novel therapeutic agents due to the presence of side effects and declining effectiveness. Functional peptides, known for their high selectivity, specificity, and diverse bioactivities, have shown the potential to develop therapeutic candidates for neurodegenerative diseases. Notably, the macin family of proteins exhibits potent antimicrobial activity and nerve repair effects. In this study, we investigated the antioxidant activity and neuroproliferative effects of a series of truncated peptides (THL, THL-1, THL-2, and THL-3) derived from the C-terminal sequence of hydramacin-1. Results showed that THL-3 exhibited the strongest antioxidant activity (EC50 of 22.5 μM) in ABTS-radical scavenging assays, with amino acid residues Cys5, Pro6, Leu7, Lys9, and Lys10 playing critical roles in its activity. Upon conjugation with the cell-penetrating PTD5 peptide to form THL-3-PTD5, it exhibited a significant dose-dependent neuroproliferative effect, increasing the viability of SH-SY5Y cells by 118% at 100 μM. However, it did not exhibit neuroprotective effects under in vitro conditions of oxidative stress induced by an exogenous oxidizing agent. This study suggests that THL-3-PTD5 may serve as a potential candidate for developing therapeutic agents against neurodegenerative diseases.
SecureSense: Enhancing Person Verification through Multimodal Biometrics for Robust Authentication

Biometrics provide enhanced security and convenience compared to conventional methods of individual authentication. A more robust and effective method of individual authentication has emerged due to recent advancements in multimodal biometrics. Unimodal systems offer lower security and lack the robustness found in multimodal biometric systems. The research paper introduces a novel approach, employing multiple biometric modalities, including face, fingerprint, and iris, to authenticate users in a multimodal biometric system. The paper proposes the ”Secure Sense” framework, which combines multiple biometric modalities to improve person verification accuracy. The proposed system utilizes both web-based and real-time datasets. For the web-based dataset, we employed the Chicago Face dataset for facial data, the MMU1 dataset for iris data, and the SOCOfing dataset for fingerprint data. In real-time data collection, facial data is captured using a Zebronics Zeb-Gem webcam, fingerprint data is obtained using the Mantra MFS scanner, and iris data is collected using the Mantra MIS scanner. In the envisioned system, we introduce an innovative approach that employs a decision-level fusion technique across three unique biometric modalities, resulting in an impressive accuracy rate of approximately 93% across all modalities.