Miracle-dz/UniFAR-FTUs huggingface dataset:
Straight on through to Universal Grammar: Spatial modifiers in second language acquisition

There has been considerable progress in second language (L2) research at the syntax—semantics interface addressing how syntax can inform phrasal semantics, in terms of interpretive correlates of word order (Slabakova, 2008). This article provides evidence of a flow of information ostensibly in the opposite direction, from meaning to grammar, at the interface between lexical semantics and syntax. It is argued that there is a functional hierarchy of modifiers in the domain of adpositions, which enables the linguistic elaboration of trajectories, but that not all languages lexicalize all types. This study examines whether L2 learners of English are able to overcome the poverty of the stimulus and recruit the relevant functional categories despite their absence in the first language (L1). Modifiers were taught to learners individually, but never in combination. A computer-animated narrative was designed in order to create felicitous contexts for combinations of modifiers, and preference and grammaticality judgment tasks were administered to 121 students from various L1 backgrounds, as well as 20 native speakers. Accuracy scores were remarkably targetlike on binary combinations of modifiers (1) across proficiency levels, (2) across L1s, and (3) across the two tasks, revealing that with the semantics of modifiers in place, the syntactic hierarchy is naturally manifested.
SilkDB v2.0: a platform for silkworm (Bombyx mori ) genome biology

The SilkDB is an open-access database for genome biology of the silkworm (Bombyx mori). Since the draft sequence was completed and the SilkDB was first released 5 years ago, we have collaborated with other groups to make much remarkable progress on silkworm genome research, such as the completion of a new high-quality assembly of the silkworm genome sequence as well as the construction of a genome-wide microarray to survey gene expression profiles. To accommodate these new genomic data and house more comprehensive genomic information, we have reconstructed SilkDB database with new web interfaces. In the new version (v2.0) of SilkDB, we updated the genomic data, including genome assembly, gene annotation, chromosomal mapping, orthologous relationship and experiment data, such as microarray expression data, Expressed Sequence Tags (ESTs) and corresponding references. Several new tools, including SilkMap, Silkworm Chromosome Browser (SCB) and BmArray, are developed to access silkworm genomic data conveniently. SilkDB is publicly available at the new URL of http://www.silkdb. org.
In Silico Description of the Direct Inhibition Mechanism of Endothelial Lipase by ANGPTL3

Angiopoietin-like protein 3 (ANGPTL3) is a plasmatic protein that plays a crucial role in lipoprotein metabolism by inhibiting the lipoprotein lipase (LPL) and the endothelial lipase (EL) responsible for the hydrolysis of phospholipids on high-density lipoprotein (HDL). Interest in developing new pharmacological therapies aimed at inhibiting ANGPTL3 has been growing due to the hypolipidemic and antiatherogenic profile observed in its absence. The goal of this study was the in silico characterization of the interaction between ANGPTL3 and EL. Because of the lack of any structural information on both the trimeric coiled-coil N-terminal domain of ANGPTL3 and the EL homodimer as well as data regarding their interactions, the first step was to obtain the three-dimensional model of these two proteins. The models were then refined via molecular dynamics (MD) simulations and used to investigate the interaction mechanism. The analysis of interactions in different docking poses and their refinement via MD allowed the identification of three specific glutamates of ANGPTL3 that recognize a positively charged patch on the surface of EL. These ANGPTL3 key residues, i.e., Glu154, Glu157, and Glu160, could form a putative molecular recognition site for EL. This study paves the way for future investigations aimed at confirming the recognition site and at designing novel inhibitors of ANGPTL3.
SPATIAL REASONING AND UNDERSTANDING THE PARTICULATE NATURE OF MATTER: A MIDDLE SCHOOL PERSPECTIVE

OF DISSERTATION SPATIAL REASONING AND UNDERSTANDING THE PARTICULATE NATURE OF MATTER: A MIDDLE SCHOOL PERSPECTIVE This dissertation employed a mixed-methods approach to examine the relationship between spatial reasoning ability and understanding of chemistry content for both middle school students and their science teachers. Spatial reasoning has been linked to success in learning STEM subjects (Wai, Lubinski, & Benbow, 2009). Previous studies have shown a correlation between understanding of chemistry content and spatial reasoning ability (e.g., Pribyl & Bodner, 1987; Wu & Shah, 2003: Stieff, 2013), raising the importance of developing the spatial reasoning ability of both teachers and students. Few studies examine middle school students’ or in-service middle school teachers’ understanding of chemistry concepts or its relation to spatial reasoning ability. The first paper in this dissertation addresses the quantitative relationship between mental rotation, a type of spatial reasoning ability, and understanding a fundamental concept in chemistry, the particulate nature of matter. The data showed a significant, positive correlation between scores on the Purdue Spatial Visualization Test of Rotations (PSVT; Bodner & Guay, 1997) and the Particulate Nature of Matter Assessment (ParNoMA; Yezierski, 2003) for middle school students prior to and after chemistry instruction. A significant difference in spatial ability among students choosing different answer choices on ParNoMA questions was also found. The second paper examined the ways in which students of different spatial abilities talked about matter and chemicals differently. Students with higher spatial ability tended to provide more of an explanation, though not necessarily in an articulate matter. In contrast, lower spatial ability students tended to use any keywords that seemed relevant, but provided little or no explanation. The third paper examined the relationship between mental reasoning and understanding chemistry for middle school science teachers. Similar to their students, a significant, positive correlation between scores on the PSVT and the ParNoMA was observed. Teachers who used consistent reasoning in providing definitions and examples for matter and chemistry tended to have higher spatial abilities than those teachers who used inconsistent reasoning on the same questions. This is the first study to explore the relationship between spatial reasoning and understanding of chemistry concepts at the middle school level. Though we are unable to infer cause and effect relationship from correlational data, these results illustrate a need to further investigate this relationship as well as identify the relationship between different spatial abilities (not just mental rotation) and other chemistry concepts.
Network Pharmacology and Experimental Verification Reveal the Regulatory Mechanism of Chuanbeimu in Treating Chronic Obstructive Pulmonary Disease

Background Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder in pulmonology. Chuanbeimu (CBM) is a traditional Chinese medicinal herb for treating COPD and has been widely utilized in clinical practice. However, the mechanism of CBM in the treatment of COPD remains incompletely understood. This study aims to investigate the underlying therapeutic mechanism of CBM for COPD using network pharmacology and experimental approaches. Methods Active ingredients and their targets were obtained from the Traditional Chinese Medicine Systems Pharmacology database. COPD-associated targets were retrieved from the GeneCards database. The common targets for CBM and COPD were identified through Venn diagram analysis. Protein-protein interaction (PPI) networks and disease-herb-ingredient-target networks were constructed. Subsequently, the results of the network pharmacology were validated by molecular docking and in vitro experiments. Results Seven active ingredients and 32 potential targets for CBM were identified as closely associated with COPD. The results of the disease-herb-ingredient-target network and PPI network showed that peimisine emerged as the core ingredient, and SRC, ADRB2, MMP2, and NOS3 were the potential targets for CBM in treating COPD. Molecular docking analysis confirmed that peimisine exhibited high binding affinity with SRC, ADRB2, MMP2, and NOS3. In vitro experiments demonstrated that peimisine significantly upregulated the expression of ADRB2 and NOS3 and downregulated the expression of SRC and MMP2. Conclusion These findings indicate that CBM may modulate the expression of SRC, ADRB2, MMP2, and NOS3, thereby exerting a protective effect against COPD.
The Emotional Side of Software Developers in JIRA

ABSTRACTIssue tracking systems store valuable data for testing hy-potheses concerning maintenance, building statistical pre-diction models and (recently) investigating developer affec-tiveness. For the latter, issue tracking systems can be minedto explore developers emotions, sentiments and politeness, affects for short. However, research on affect detection insoftware artefacts is still in its early stage due to the lack ofmanually validated data and tools.In this paper, we contribute to the research of affectson software artefacts by providing a labeling of emotionspresent on issue comments.We manually labeled 2,000 issue comments and 4,000 sen-tences written by developers with emotions such as love,joy, surprise, anger, sadness and fear. Labeled commentsand sentences are linked to software artefacts reported inour previously published dataset (containing more than 1Kprojects, more than 700K issue reports and more than 2million issue comments). The enriched dataset presented inthis paper allows the investigation of the role of affects insoftware development.
Object-Oriented and Visual-Based Localization in Urban Environments

In visual-based localization, prior research falls short in addressing challenges for the Internet of Things with limited computational resources. The dominant state-of-the-art models are based on separate feature extractors and descriptors without consideration of the constraints of small hardware, the issue of inconsistent image scale, or the presence of multi-objects. We introduce “OOPose”, a real-time object-oriented pose estimation framework that leverages dense features from off-the-shelf object detection neural networks. It balances between pixel-matching accuracy and processing speed, enhancing overall performance. When input images share a comparable set of features, their matching accuracy is substantially heightened, while the reduction in image size facilitates faster processing but may compromise accuracy. OOPose resizes both the original library and cropped query object images to a width of 416 pixels. This adjustment results in a 2.4-fold improvement in pose accuracy and an 8.6-fold increase in processing speed. Moreover, OOPose eliminates the need for traditional sparse point extraction and description processes by capitalizing on dense network backbone features and selecting the detected query objects and sources of object library images, ensuring not only 1.3 times more accurate results but also three times greater stability compared to real-time sparse ORB matching algorithms. Beyond enhancements, we demonstrated the feasibility of OOPose in an autonomous mobile robot, enabling self-localization with a single camera at 10 FPS on a single CPU. It proves the cost-effectiveness and real-world applicability of OOPose for small embedded devices, setting the stage for potential markets and providing end-users with distinct advantages.
The January 15, 1466 and November 23, 1980 Irpinia (Italy) earthquakes

On the night between 14 and 15 January of 1466, an earthquake damaged towns close to those more recently destroyed by the 1980 Irpinia earthquake. It was felt in Naples, about 80 km from the epicentre, resulting in panic and slight damage. To obtain source parameters related to January 15, 1466, the observed macroseismic field of the November 23, 1980 earthquake was reproduced by synthetic peak strong acceleration. The results suggest that the whole of the 1466 faulting was again activated by the 1980 event and that the northern part remained non-activated. Quite possibly, the near southernmost source of the large earthquake of 1456 affected the occurrence of the nearby event ten years later. Furthermore, the value of Mo=7.5 10 18 Nm obtained makes the medieval event of 1466 one of the most severe recorded in southern Italy.
SpeechBot: a Speech Recognition based Audio Indexing System for the Web

We have developed an audio search engine incorporating speech recognition technology. This allows indexing of spoken documents from the World Wide Web when no transcription is available. This site indexes several talk and news radio shows covering a wide range of topics and speaking styles from a selection of public Web sites with multimedia archives. Our Web site is similar in spirit to normal Web search sites; it contains an index, not the actual multimedia content. The audio from these shows suffers in acoustic quality due to bandwidth limitations, coding, compression, and poor acoustic conditions. The shows are typically sampled at 8 kHz and transmitted, RealAudio compressed, at 6.5 kbps. Our word-error rate results using appropriately trained acoustic models show remarkable resilience to the high compression, though many factors combine to increase the average word-error rates over standard broadcast news benchmarks. We show that, even if the transcription is inaccurate, we can still achieve good retrieval performance for typical user queries (69%). Because the archive is large - over 5000 hours of content (and growing at a rate of 100 hours per week), totaling 47 million words and growing rapidly - we measure performance in terms of the precision of the top-ranked matches returned to the user.
Categorizing Unknown Text Patterns for Information Extraction Using a Search Result Mining Approach

An advanced information extraction system requires an effective text categorization technique to categorize extracted facts (text patterns) into a hierarchy of domain-specific topic categories. Text patterns are often short and their categorization is quite different from conventional document categorization. This paper proposes a Web mining approach that exploits Web resources to categorize unknown text patterns with limited manual intervention. The feasibility and wide adaptability of the proposed approach has been shown with extensive experiments on categorizing different kinds of text patterns including domain-specific terms, named entities, and even paper titles into Yahoo! ’s taxonomy trees.
Verification of a coastal wave transfer function for the New South Wales coastline

A detailed understanding of spatial and temporal variability in oceanic and nearshore wave climates is essential to better assess the present and future risks of coastal hazards such as erosion and inundation. Previously, the Office of Environment and Heritage (OEH) have developed a NSW Coastal Ocean Wave Model System, comprising coupled WAVEWATCH-III and SWAN spectral wave models. That model system has been applied to develop long-term wave hindcast data sets, see [1] and [2], at offshore locations along the NSW coastline. However, due to the computational effort required to transfer the deep-water wave data sets to the shoreline, the process of dynamically simulating nearshore wave climates can only be carried out on a project-specific basis for selected locations at present. This paper presents three different methods for a Wave Transfer Function to transfer measured and hindcast (modelled) wave data from deep water across the continental shelf offshore of NSW to the nearshore. The WTF's have been calibrated with hindcast wave data from the WW-III nearshore model used to develop WTF's, and also measured WaveRider buoy data from two nearshore sites. Two spectral WTF methods were demonstrated to have excellent validation with the physics based WW-III hindcast model, and also good agreement with the measured nearshore WRB data. The computational requirement for all of the WTF's to develop a long-term wave hindcast along the NSW coastline is less than 2% of that required for the state-wide numerical WW-III model, demonstrating that the WTF approach provides an accurate and computationally efficient method to develop long term nearshore hindcast wave data along the whole NSW coastline.
Bakery Product Enrichment with Phenolic Compounds as an Unexplored Strategy for the Control of the Maillard Reaction

The Maillard reaction (MR) is one of the main reactions that occurs during the thermal processing of food. It contributes positively to the flavor, aroma, and color of food but also produces harmful by-products, including acrylamide and advanced glycation end products (AGEs). Bakery products are major staples consumed daily by people from all walks of life and of all ages; the identification of strategies to hamper acrylamide formation in bread and bread-like products is thus crucial for public health. Several strategies have been proposed to inhibit the MR in food processing, including biochemical approaches such as the use of enzymes; innovative technologies such as ohmic heating, pulsed electric field, high pressure processing, or encapsulation of metal ions; and the chemical modification of reactants, intermediates, or products of MR. Recently, phenolic compounds have been reported to have an inhibitory effect on the formation of harmful by-products resulting from the MR. The aim of this paper is, therefore, to provide a state-of-the-art overview of the use of phenolic compounds in the formulation of bakery products to inhibit the MR. A systematic review of the most up-to-date scientific literature was thus performed. It emerged that the inhibitory action was mainly investigated in bread. Phenolic extracts and powders obtained from plant-based foods have been included in the formulation of bakery products. The effect of pure phenolic standards was also considered.
Renormalization , Ward Identities , Symmetries , and Quantum Anomalies : Logical Aspect

Logical aspects associated with renormalization methods, Ward identities, symmetries, and quantum anomalies are investigated for ultraviolet divergent VV, AA, AV, and VA massanisotropic spinor amplitudes characterizing the most important polarization properties of many-fermion vacuum in any space-time dimension n = 2r+δn, δn = 0, 1. It is shown clearly that genuine algorithmic cause of perturbation theory anomalies is a logical descrepancy arising in the course of evaluating finite values of UV-divergent Feynman amplitudes (FAs) by means of commonly used renormalization techniques. Some important lessons, which teach us the manner how to construct a logically consistent renormalization technique, i.e. self-consistent renormalization (SCR), are revealed as part of this study.
Synchronization of Interconnected Systems With Applications to Biochemical Networks: An Input-Output Approach

This paper provides synchronization conditions for networks of nonlinear systems. The components of the network (referred to as “compartments” in this paper) are made up of an identical interconnection of subsystems, each represented as an operator in an extended L2 space and referred to as a “species. ” The compartments are, in turn, coupled through a diffusion-like term among the respective species. The synchronization conditions are provided by combining the input-output properties of the subsystems with information about the structure of the network. The paper also explores results for state-space models, as well as biochemical applications. The work is motivated by cellular networks where signaling occurs both internally, through interactions of species, and externally, through intercellular signaling. The theory is illustrated by providing synchronization conditions for networks of Goodwin oscillators.
Application of Rough Set Theory on scene image classification

This paper utilizes the rough set theory to classify the scene image. The system learns knowledge for classification automatically and therefore breaks the limitation of the traditional template method. For a scene image, its color relates with object and semantic closely. Therefore, we extracted two major colors and the quantity, spatial relations and textures of the regions formed by them to describe the scene image. Experimental results show that the rules are effective to classify the four types of scene images and obtain 85% of average retrieval performance.
A Picea abies Linkage Map Based on SNP Markers Identifies QTLs for Four Aspects of Resistance to Heterobasidion parviporum Infection

A consensus linkage map of Picea abies, an economically important conifer, was constructed based on the segregation of 686 SNP markers in a F1 progeny population consisting of 247 individuals. The total length of 1889.2 cM covered 96.5% of the estimated genome length and comprised 12 large linkage groups, corresponding to the number of haploid P. abies chromosomes. The sizes of the groups (from 5.9 to 9.9% of the total map length) correlated well with previous estimates of chromosome sizes (from 5.8 to 10.8% of total genome size). Any locus in the genome has a 97% probability to be within 10 cM from a mapped marker, which makes the map suited for QTL mapping. Infecting the progeny trees with the root rot pathogen Heterobasidion parviporum allowed for mapping of four different resistance traits: lesion length at the inoculation site, fungal spread within the sapwood, exclusion of the pathogen from the host after initial infection, and ability to prevent the infection from establishing at all. These four traits were associated with two, four, four and three QTL regions respectively of which none overlapped between the traits. Each QTL explained between 4.6 and 10.1% of the respective traits phenotypic variation. Although the QTL regions contain many more genes than the ones represented by the SNP markers, at least four markers within the confidence intervals originated from genes with known function in conifer defence; a leucoanthocyanidine reductase, which has previously been shown to upregulate during H. parviporum infection, and three intermediates of the lignification process; a hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyltransferase, a 4-coumarate CoA ligase, and a R2R3-MYB transcription factor.