Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Measures for Diffusion of Linguistic Innovation: As Seen in the Usage of Verbal “Nok” in Thai Twitter

The existence of several SNS (social networking service) such as Twitter accelerates the diffusion process of language change. In this paper, we examine the diffusion of the innovative verbal usage of n´ok in Thai Twitter. We collected more than 25 millions tweets and adopted not only word frequency but also three probabilistic measures of analysis: conditional probability, PMI and cosine similarity of word embeddings. The result of these three probabilistic measures show the stability of the innovation regardless of decrease of word frequency. These facts support the idea that the innovation n´ok is lexically established in Thai language. Most importantly, it shows that the three probabilistic measures can be used to quantify diffusion of linguistic innovation regardless of its polysemy.
Mixed-conducting particulate composites for soft electronics

Mixed-conducting particulate composite can form functional electronic components by varying particle size and density. Bioelectronic devices should optimally merge a soft, biocompatible tissue interface with capacity for local, advanced signal processing. Here, we introduce an organic mixed-conducting particulate composite material (MCP) that can form functional electronic components by varying particle size and density. We created MCP-based high-performance anisotropic films, independently addressable transistors, resistors, and diodes that are pattern free, scalable, and biocompatible. MCP enabled facile and effective electronic bonding between soft and rigid electronics, permitting recording of neurophysiological data at the resolution of individual neurons from freely moving rodents and from the surface of the human brain through a small opening in the skull. We also noninvasively acquired high–spatiotemporal resolution electrophysiological signals by directly interfacing MCP with human skin. MCP provides a single-material solution to facilitate development of bioelectronic devices that can safely acquire, transmit, and process complex biological signals.
Structural investigation of single biomolecules

NMR spectroscopy and X-ray crystallography are currently the most common techniques capable of determining the structures of biological macromolecules like proteins and nucleic acids at an atomic level of resolution. The atomic force microscope (AFM) is mostly known for its imaging capabilities, but it is also a very sensitive tool for quantitatively measuring forces on a single molecule level. This capability allows the use of AFM as an alternative technique for the investigation of the structural configuration of macromolecules under native conditions. Measuring forces within and between single molecules provides another approach to the understanding of molecular energy landscapes and chemical reaction kinetics. The AFM can measure individual bonds forming and breaking, rather than being limited to statistical averages over a population.
Making Metaphors: A Quantitative Analysis of Metaphor Production and Interpretation in Japanese Using a Multimodal Task

Two key features of Conceptual Metaphor Theory are that metaphors appear in multiple modes of communication from language to gestures to pictures and that metaphors scaffold our understanding of abstract concepts by grounding them in embodied, physically experienced concepts. In an exploratory study, we investigated metaphor production and interpretation using cross modal stimuli (verbal and pictorial). Native Japanese participants viewed an abstract word in the textual mode, in the form of an incomplete copula metaphor (Friendship is .), and then saw six images of concrete entities (castle, heater, colored pencils, etc.). They chose one of these image concepts to complete the copula metaphor and then provided an interpretation of it. In this paper, we first analyze these choice selections using descriptive statistics. Results indicate that there is a wide amount of variability among these selected responses. Secondly, we analyze the interpretations, which use (1) external or systemic properties of the pictorial entity; (2) situational functions or actions performed on the entity; or (3) some form of introspection related to the entity.
Opleiding Informatica Visalization of Patterns in Scrum Software Development

ICTU is a Dutch governmental agency that creates software products for various branches of the government. To manage their development process they use the Scrum methodoloy. Over the years they have gathered a lot of data related to the software development process. To make this data more accessible and to provide insights for different stakeholders three visualizations were created. First, a heatmap which shows a comparison between external data such as temperature, and internal data such as the number of commits per day. Secondly, a network graph which shows the relations between people and the projects they work on, making it visible who works on multiple projects. Lastly, an existing timeline visualization was enhanced with a burndown chart to better show velocity. We find that these visualizations can help with identifying patterns in large datasets, but the data and measure needs to be chosen carefully. Usability is very important to help the user understand the purpose of the visualization and find value in it.
A UTOMATIC UNDERSTANDING OF LYRICS FROM SINGING

When listening to a song, we automatically recognize the words and interpret the linguistic information. We can identify an artist by its voice and a song by its lyrics. Performing some of these tasks in an automated manner has a significant potential in music classification, because the increased amount of available storage and music players have led to large music collections that need to be organized.
Modeling the Idiomaticity of Chinese Quadra-syllabic Idiomatic Expressions

This paper proposes a computational model of idiomaticity for Chinese Quadra-syllabic id-iomatic expressions based on variations, com-poundness and compositeness measure. Two classification experiments are conducted to test the model, together with linguistic analysis of the connection to wordnet. The result is promising and we believe that it will shed more light on our understanding of cognitive dynamics that underlies multiword expressions processing.
Diagnosis of Patients with Hypothyroidism Using Spectrochemical Analysis of Blood Sera

Biochemical tests are critical in the management of patients with hypothyroidism (HT). Fourier Transfer Infrared (FTIR) which allows for global bio-fluid metabolic profiling may give more appropriate information by measuring a broad range of metabolic parameters in bio-fluid. Here we present the application of FTIR with chemo metric analysis for the diagnosis of patients with hypothyroidism (HT). Twenty-six patients and twenty-six healthy sex-matched individuals were prospectively recruited in this study. FTIR spectra were measured in serum samples. The most informative variables obtained by FTIR were selected by variable importance in the projection (VIP) value after creating an OPLS-DA model at three specific regions: 900-1200 cm-1, 1500-1700 cm-1, and 2800-3100 cm-1. The significance of each created model was validated by P-value (P<0.05) of CV-ANOVA. Multivariate analysis (OPLS-DA) of the FTIR data revealed the differences in the serum metabolic components of patients with hypothyroidism. OPLS-DA models revealed validation for 900-1200 cm-1 region (R2Y(cum)=0.934; Q2(cum)=0.514), 1500-1700 cm-1 region (R2Y(cum)=0.726; Q2(cum)=0.555), and 2800-3100 cm-1 region (R2Y(cum)= 0.959; Q2(cum)= 0.618) with P-value <0.05 of CV-ANOVA. The results indicated that FTIR spectral biomarkers distinguish the serum of patients with hypothyroidism, for example, carbohydrates and nucleic acids, proteins (Amide I/ Amide II), and lipids biomolecules. In summary, this work demonstrates that FTIR spectroscopy supported by Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) has the potential to become a fast and reagent-free method for biochemical characterization of serum that consequently could have a diagnostic significance in patients with hypothyroidism (HT).
Building Cendana: a Treebank for Informal Indonesian

This paper introduces Cendana, a treebank for informal Indonesian. The corpus is from a subset of online chat data between customer service staff and customers at Traveloka ( traveloka.com ), an online travel agency (OTA) from Indonesia that provides airline ticketing and hotel booking services. Lines of conversation text are parsed using the Indonesian Resource Grammar (INDRA) (Moeljadi et al., 2015), a computational grammar for Indonesian in the Head-Driven Phrase Structure Grammar (HPSG) framework (Pollard and Sag, 1994; Sag et al., 2003) and Minimal Recursion Semantics (MRS) (Copestake et al., 2005). The annotation was done using Full Forest TreeBanker (FFTB) (Packard, 2015). Our purpose is to create a treebank, as well as to develop INDRA for informal Indonesian. Testing on 2,000 lexically dense sentences, the coverage is 64.1% and 715 items or 35.8% was treebanked, with correct syntactic parses and semantics. INDRA has been developed by adding 6,741 new lexical items and 22 new rules, especially the ones for informal Indonesian. The treebank data was employed to build a Feature Forest-based Maximum Entropy Model Trainer. Testing against the annotated data, the precision was around 90%. Moreover, we leveraged the treebank data to develop a POS tagger and present benchmark results evaluating the same.
Diagnosis and Identification of Gastric Helicobacter Species by Polymerase Chain Reaction in Dogs

Helicobacter spp. are almost ubiquitously present in the stomach of dogs. Various Helicobacter species have been isolated, however, their identification by routine diagnostic methods is impossible, culture is cumbersome and not sensitive. We developed and validated a PCR assay based on amplification of the urease B gene for the detection of Helicobacter species in gastric biopsy specimens of dogs against a set of established invasive and non-invasive detection methods. Altogether, urease B gene PCR had a sensitivity of 98% identifying 59 of 60 infected dogs in a series of 65 dogs. Direct identification of helicobacters present in gastric biopsies was obtained by species-specific PCR based on the urease gene with a newly developed PCR for H. bizzozeronii/H. salomonis and in established PCR assays for H. felis and ' H. heilmannii '. In the 59 dogs positive by the urease B gene PCR the colonizing Helicobacter was identified by species specific PCR and/or culture as H. bizzozeronii/H. salomonis in nineteen, ' H. heilmannii ' in twelve, H. felis in seven and a Helicobacter sp. in two; no identification was obtained in 31 dogs and a double infection was found in six dogs. Results of species-specific PCR were concordant with conventional and molecular identification of Helicobacter strains isolated in six culture positive dogs. These findings indicate that urease B gene PCR is accurate in diagnosing a helicobacteriosis in dogs, and that various Helicobacter species can reliably be identified by species specific urease PCR. Keywords: canine, spiral organisms, urease gene, histology.
Simulating Segmentation by Simultaneous Interpreters for Simultaneous Machine Translation

One of the major issues in simultaneous machine translation setting is when to start translation. Inspired by the segmentation technique of human interpreters, we aim to simulate this technique for simultaneous machine translation. Using interpreters’ output, we identify segment boundaries in source texts and use them to train a predictor of segment boundaries. Our experiment reveals that translation based on our approach achieves a better RIBES score than conventional sentence-level translation.
Analytical Chemistry of Tungsten : Method of Trace Determination of Tungsten (VI) Using 6-Chloro-3-hydroxy-7-methyl-2-(2’-thienyl)-4-oxo-4H-1-benzopyran as an Analytical Reagent

A binary complex of tungsten (VI) with 6-chloro-3-hydroxy-7-methyl-2-(2’thienyl)-4-oxo-4H-1-benzopyran (CHMTB) is produced from hydrochloric acid medium and studied spectrophotometrically. The 1:3 (M: L) complex is quantitatively extracted into dichloromethane and absorbs light intensity in the range 410-418 nm. Beer’s law as shown by the calibration curve holds good in the W(VI) concentration range of 0-1.6 μg ml-1 in the measured solution (r = 0.9998). The molar annihilation coefficient and Sandell’s sensitivity are calculated to be 9.93 × 104l mol-1 cm-1 and 0.00185 μg cm-2, respectively at 415 nm. The proposed method offers advantage of a quick, cheap, reproducible, sensitive and selective technique and has been successfully used in the determination of tungsten in spiked samples like flue dust and water with satisfactory results.
Combining Epidemiological and Genetic Networks Signifies the Importance of Early Treatment in HIV-1 Transmission

Inferring disease transmission networks is important in epidemiology in order to understand and prevent the spread of infectious diseases. Reconstruction of the infection transmission networks requires insight into viral genome data as well as social interactions. For the HIV-1 epidemic, current research either uses genetic information of patients' virus to infer the past infection events or uses statistics of sexual interactions to model the network structure of viral spreading. Methods for a reliable reconstruction of HIV-1 transmission dynamics, taking into account both molecular and societal data are still lacking. The aim of this study is to combine information from both genetic and epidemiological scales to characterize and analyse a transmission network of the HIV-1 epidemic in central Italy. We introduce a novel filter-reduction method to build a network of HIV infected patients based on their social and treatment information. The network is then combined with a genetic network, to infer a hypothetical infection transmission network. We apply this method to a cohort study of HIV-1 infected patients in central Italy and find that patients who are highly connected in the network have longer untreated infection periods. We also find that the network structures for homosexual males and heterosexual populations are heterogeneous, consisting of a majority of ‘peripheral nodes’ that have only a few sexual interactions and a minority of ‘hub nodes’ that have many sexual interactions. Inferring HIV-1 transmission networks using this novel combined approach reveals remarkable correlations between high out-degree individuals and longer untreated infection periods. These findings signify the importance of early treatment and support the potential benefit of wide population screening, management of early diagnoses and anticipated antiretroviral treatment to prevent viral transmission and spread. The approach presented here for reconstructing HIV-1 transmission networks can have important repercussions in the design of intervention strategies for disease control.
Learning about Good Healthcare Practices through Interactive Storytelling with Virtual Peers

Storytelling can be used to raise awareness on healthcare practices among young children. Combined with interactive environments, children can be given a virtual simulated world to learn about the effects of practicing good healthcare habits with the guidance of virtual peers. In this paper, we present Sarah, a virtual peer that shares interactive healthcare stories centering on events that may lead to symptoms and recovery from common childhood ailments. Armed with a collection of domain knowledge about healthcare facts, the virtual peer utilizes story planning and dialogue generation strategies to facilitate a text-based storytelling session with children age 7 to 10 years old. Children participate in the storytelling by using free-form input text to respond to questions posed by Sarah. Results from end-user validation showed that children prefer to interact with virtual peers that exude a more friendly persona, and that can generate relevant responses aligned to their story text.
Sequential Zeroing: Online Heavy-Hitter Detection on Programmable Hardware

F1ows that have exceeded a given percentage of the last sliding window of N packets, denoted as heavy-hitter flows, require special handling, since they may disrupt the service of other flows or may be indicative of malicious traffic. However, even when equipped with a programmable switch, it is unclear how to detect heavy hitters on a per-packet basis, while obeying the stringent switch memory access rates. For instance, existing solutions, such as HashPipe, cannot detect heavy hitters without halving the line rate and do not support sliding windows. To the best of our knowledge, this paper is the first to present heavy-hitter detection solutions that provide per-packet granularity at line-rate performance. We realize this by introducing (1) Modulo sketching, a novel counting algorithm that reuses counters and limits the impact of smaller flows beyond early processing stages; and (2) Sequential Zeroing, a new approach to extending interval-based schemes to sliding window measurements. Our solutions are extensively evaluated, both via simulations and experiments on a Netronome SmartNIC, and demonstrate significant performance gains over the state-of-theart.
On the “Easy” Task of Evaluating Chinese Irony Detection

In this paper, we present a discussion on the problem in the evaluation of irony detection in Mandarin Chinese, especially due to the difficulties of finding an exhaustive definition and to the current lack of a gold standard for computational models. We describe some preliminary results of our experiments on an irony detection system for Chinese, and analyze examples of irony or other related phenomena that turned out to be challenging for NLP classifiers
Limits of preprocessing

It is a classical result that the inner product function cannot be computed by an AC0 circuit [17, 1, 22]. It is conjectured that this holds even if we allow arbitrary preprocessing of each of the two inputs separately. We prove this conjecture when the preprocessing of one of the inputs is limited to output n + n/(logω(1) n) bits. Our methods extend to many other functions, including pseudorandom functions, and imply a (weak but nontrivial) limitation on the power of encoding inputs in low-complexity cryptography. Finally, under cryptographic assumptions, we relate the question of proving variants of the main conjecture with the question of learning AC0 under simple input distributions.
Perfect Order and Its Components: Application for Deliveries of Fast Moving Consumer Goods to Retail Stores

The perfect order concept is traditionally used to measure logistics performance, but the conventional assessment of the perfect order from the perspective of the “in-time, in-full and error-free” trinity is no longer viable today. This paper aims to make a modest contribution to creating a novel understanding of the perfect order concept. Based on the primary survey in 132 Czech retail stores, the authors identify the key components that constitute a perfect order fulfilment of fast moving consumer goods to retail stores, namely reliability, collaboration, extra adaptation, ordering, and promotion. Subsequently, it was discovered that there are the differences in the influence of the identified components depending on the retail store type. Retail stores in the sense of drugstores regard extra adaptation and promotion as being the more important components compared to retail stores specialising in food products. Independent retail stores regard collaboration and promotion as being much less important components compared to retail stores that form part of a retail chain. Ordering is a more important component for small retail stores compared to large retail stores. Retail stores located in a capital city and in towns representing the centres of individual regions regard collaboration and extra adaptation to be the more important components compared to retail stores located in small towns. Research results support perfection in measuring logistics performance and make it possible to improve retail store operation.
Temperate eucalypt woodlands: A review of their status, processes threatening their persistence and techniques for restoration

Temperate eucalypt woodlands were once widespread throughout southern Australia and Tasmania. Following European settlement, woodlands were cleared for agriculture, or grazed and converted to pasture. In the wheatbelts of south-western and south-eastern Australia, woodlands have been almost completely eliminated from the landscape with as little as 3% of some woodland types remaining. As a consequence, some temperate eucalypt woodland communities are amongst the most poorly conserved ecosystems in Australia. The main effect of widespread clearing and grazing has been the loss of habitat. This has had a devastating impact on the woodland flora and fauna. A number of species have become extinct and many are threatened; many others have undergone regional and local population declines. Woodlands now occur throughout much of their former range as remnants of varying size, quality and isolation. Many of these are under threat from further clearing, rising saline water tables and increased inundation, livestock grazing, nutrient enrichment, soil structural decline, altered fire regimes and the invasion of exotic weeds. The degradation and loss of biodiversity in temperate eucalypt woodlands will continue unless clearing stops and the management of remnants changes; this will invariably involve ecological restoration both at the patch and landscape level. The review discusses approaches to restoration and reveals that there are few data in the published literature describing techniques for reversing degrading processes and restoring diversity structure and function in remnant woodlands. This information is urgently needed. Past research on temperate eucalypt woodlands has focused on identifying the processes of degradation and these are now relatively well documented. There is a need to shift the focus of research to developing solutions for these problems.
Biodiversity and composition of the herpetofauna from the Tien Hai Wetland Nature Reserve, North Vietnam

Based on the novel data collected during the field surveys in 2019, we here in provided a checklist of eight species of amphibians belonging to seven genera (five families, one order) and nine species of reptiles belonging to eight genera (seven families, two orders) from Tien Hai Wetland Nature Reserve in Thai Binh Province. The species Hemidactylus stejnegeri is reported for the first time from Thai Binh Province. In terms of distribution pattern most of recorded species were found in the canal and aquaculture pond habitat (nine species of amphibians and reptiles, 52.94% of the total number of species). The diversity of amphibian and reptile species recorded from Tien Hai Wetland Nature Reserve is lower than the other wetland areas in North Vietnam. In this nature reserve, the number of species change according to salinity of amphibians is higher than of reptiles.