Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Phrase Mining with Language Models

A vast amount of vital clinical data is available within unstructured texts such as discharge summaries and procedure notes in Electronic Medical Records (EMRs). Automatically transforming such unstructured data into structured units is crucial for effective data analysis in the field of clinical informatics. Recognizing phrases that reveal important medical information in a concise and thorough manner is a fundamental step in this process. Existing systems that are built for opendomain texts are designed to detect mostly non-medical phrases, while tools designed specifically for extracting concepts from clinical texts are not scalable to large corpora and often leave out essential context surrounding those detected clinical concepts. We address these issues by proposing a framework, CliniPhrase, which adapts domain-specific deep neural network based language models (such as ClinicalBERT) to effectively and efficiently extract high-quality phrases from clinical documents with a limited amount of training data. Experimental results on the MIMIC-III dataset show that our method can outperform the current state-of-the-art techniques by up to 18% in terms of F1 measure while being very efficient (up to 48 times faster). 11Our source code, pre-trained models and documentations are available online at: https://github.com/kaushikmani/PhraseMiningLM
A General Framework for Spatio-Temporal Modeling of Epidemics With Multiple Epicenters: Application to an Aerially Dispersed Plant Pathogen

The spread dynamics of long-distance-dispersed pathogens are influenced by the dispersal characteristics of a pathogen, anisotropy due to multiple factors, and the presence of multiple sources of inoculum. In this research, we developed a flexible class of phenomenological spatio-temporal models that extend a modeling framework used in plant pathology applications to account for the presence of multiple sources and anisotropy of biological species that can govern disease gradients and spatial spread in time. We use the cucurbit downy mildew pathosystem (caused by Pseudoperonospora cubensis) to formulate a data-driven procedure based on the 2008 to 2010 historical occurrence of the disease in the U.S. available from standardized sentinel plots deployed as part of the Cucurbit Downy Mildew ipmPIPE program. This pathosystem is characterized by annual recolonization and extinction cycles, generating annual disease invasions at the continental scale. This data-driven procedure is amenable to fitting models of disease spread from one or multiple sources of primary inoculum and can be specified to provide estimates of the parameters by regression methods conditional on a function that can accommodate anisotropy in disease occurrence data. Applying this modeling framework to the cucurbit downy mildew data sets, we found a small but consistent reduction in temporal prediction errors by incorporating anisotropy in disease spread. Further, we did not find evidence of an annually occurring, alternative source of P. cubensis in northern latitudes. However, we found a signal indicating an alternative inoculum source on the western edge of the Gulf of Mexico. This modeling framework is tractable for estimating the generalized location and velocity of a disease front from sparsely sampled data with minimal data acquisition costs. These attributes make this framework applicable and useful for a broad range of ecological data sets where multiple sources of disease may exist and whose subsequent spread is directional.
Reinforcement Learning in Newcomblike Environments

Newcomblike decision problems have been studied extensively in the decision theory literature, but they have so far been largely absent in the reinforcement learning literature. In this paper we study value-based reinforcement learning algorithms in the Newcomblike setting, and answer some of the fundamental theoretical questions about the behaviour of such algorithms in these environments. We show that a value-based reinforcement learning agent cannot converge to a policy that is not rati ﬁ able , i.e., does not only choose actions that are optimal given that policy. This gives us a powerful tool for reasoning about the limit behaviour of agents – for example, it lets us show that there are Newcomblike environments in which a reinforcement learning agent cannot converge to any optimal policy. We show that a rati ﬁ able policy always exists in our setting, but that there are cases in which a reinforcement learning agent normally cannot converge to it (and hence cannot converge at all). We also prove several results about the possible limit behaviours of agents in cases where they do not converge to any policy.
The impact of acute exercise on factor VIII in young e-cigarette smokers

Background: There is a strong association between factor VIII (FVIII) and presence of cardiovascular disease (CVD). Exercise is a known trigger for myocardial infarction, and the majority of ischemic events from physical stress occur due to an occlusive thrombus. FVIII increases acutely with exercise and remains elevated hours after exercise. Furthermore, FVIII is also higher in cigarette smokers, however, it has not been investigated in e-cigarette smokers. The purpose of this study is to identify potential differences in FVIII before exercise, after exercise, and its magnitude of change in ecigarette users versus non-users. Methods: Eighteen individuals (8 e-cigarette users, 3 women and 5 men, and 10 nonsmokers, 7 women and 3 men; age, 18-32 years old) were recruited to participate in this research study. An incremental test to exhaustion (x̄=12.20 ± 3.20 minutes) was performed on an electronically braked cycle ergometer (Lode Corival cpet; Groningen, Netherlands) to determine the peak rate of oxygen consumption (VO2peak). Ten mL of blood was drawn into a citrate anticoagulant solution from an antecubital vein using clean venipuncture with minimal stasis both prior to and immediately following exercise testing. A commercially available ELISA kit was used to determine plasma concentrations of coagulation FVIII antigen. Results: There was no significant difference between smokers (N = 8, 4.35 ± 2.09 IU/ml) and nonsmokers (N = 9, 5.02 ± 4.87 IU/ml, p=0.72) for resting FVIII antigen. There was a main effect for exercise in that the post-exercise values (N=10, 7.76 ±1.40 IU/ml) were larger than pre-exercise values (N=10, 3.82 ± 0.65, p=0.003). However, there was no main effect for smoking and no smoking x exercise interaction (post-exercise smokers, N=4, 6.67 ± 1.46, post-exercise non-smokers, N= 7, 8.39 ± 5.81, p=0.58).
POTENTIAL OF OZONE TO TREAT INSECTS IN STORED PADDY

The most common insect in stored paddy that is known to cause serious quantitative and qualitative damage to paddy is Rhyzopertha dominica. The larva and adult feeding in and on grain kernels leaves only dust and thin brown shells. The currently available chemical fumigants are not ecofriendly and also recent studies are reporting that insects are developing resistance to these chemicals. Consumers are increasingly demanding good quality grain that is free from live insects and chemical residues caused by controlling pests. This study discusses the use of ozone to kill insects in paddy.
The effect of fermentation temperature on the quality parameters and price evaluation of Central African black teas

Tea was fermented at 15, 25 and 35°C and otherwise manufactured according to commercial practice on several occasions in early May and mid-November 1977. Fermentation at 15°C resulted in teas containing greater amounts of the desirable theaflavin class of pigments. Teas produced at the higher temperatures contained more of the thearubigin pigments, including the polymeric fraction known as the non-dialysable material. Colour development was also more rapid at 25 and 35°C. Teas produced at the low temperature were accorded higher evaluation and a linear relationship between evaluation and theaflavin content was established which explained > 70% of the variation in value data. It is suggested that, since the price premium for quality is high and the market stable, the installation of temperature control equipment to regulate the production of oxidation products would improve the quality of the product and benefit Central African tea industry.
V Discourse Model “ Victoria ” “ she ” corefer refer

Each of the underlined phrases in this passage is used by the writer to refer to a person named Victoria Chen. We call linguistic expressions like her or Victoria Chen mentions or referring expressions, and the discourse entity that is referred mention to (Victoria Chen) the referent. (To distinguish between referring expressions and referent their referents, we italicize the former.)1 Two or more referring expressions that are used to refer to the same discourse entity are said to corefer; thus, Victoria Chen corefer and she corefer in (21.1). Coreference is an important component of natural language understanding. A dialogue system that has just told the user “There is a 2pm flight on United and a 4pm one on Cathay Pacific” must know which flight the user means by “I’ll take the second one”. A question answering system that uses Wikipedia to answer a question about Marie Curie must know who she was in the sentence “She was born in Warsaw”. And a machine translation system translating from a language like Spanish, in which pronouns can be dropped, must use coreference from the previous sentence to decide whether the Spanish sentence ‘“Me encanta el conocimiento”, dice. ’ should be translated as ‘“I love knowledge”, he says’, or ‘“I love knowledge”, she says’. Indeed, this example comes from an actual news article in El Paı́s about a female professor and was mistranslated as “he” in machine translation because of inaccurate coreference resolution (Schiebinger, 2013). Natural language understanding systems (and humans) interpret linguistic expressions with respect to a discourse model (Karttunen, 1969). A discourse model discourse model (Fig. 21.1) is a mental model that the understander builds incrementally when interpreting a text, containing representations of the entities referred to in the text, as well as properties of the entities and relations among them. When a referent is first mentioned in a discourse, we say that a representation for it is evoked into the model. evoked Upon subsequent mention, this representation is accessed from the model. accessed
High Electron Mobility and Ambipolar Transport in Organic Thin‐Film Transistors Based on a π‐Stacking Quinoidal Terthiophene

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Web-based Suicide Prevention using the Concepts of Cognitive Behavioral Therapy

The percentage of Internet users, which was about 10% in 1998, reached about 80% in 2011 (Ministry of Internal Affairs and Communications, 2012), and many people now use the Internet on a daily basis. However, the psychological impact that the use of this media has on our lives remains unclear in many ways, and there are many issues to be examined concerning its use. Websites that encourage suicide can be cited as one of the mental health problems that emerged as Internet use became more prevalent. In Japan, events began occurring around 2000 in which Internet users with suicidal ideation sympathized with each other and committed group suicide (hereinafter referred to as an “Internet suicide pact”), and such phenomena continue to occur intermittently at present. In 2008, cluster suicides occurred when viewers of a website that showed a method for generating hydrogen sulfide committed suicide one after another by using the method. The relationship between Internet use and suicide has become problematic not only in 035 和光大学現代人間学部紀要 第6号(2013年3月)
ENHANCING EXTRACTION YIELD AND PURITY OF MITRAGYNINE FROM MITRAGYNA SPECIOSA THROUGH SEQUENTIAL SOLVENT EXTRACTION AND CHARACTERISATION USING NMR TECHNIQUE

Mitragynine is the main alkaloid in Mitragyna speciosa which are commonly used to treat various illness. In this study, the extraction of mitragynine were performed using successive solvent extraction at different solvents‘ polarities. Purificat ion of the extract produced 0.075 (g/g) of pure mitragynine. The Rf values was identified at 1.60 (hexane extract) and 0.80 (hexane-chloroform and hexane-chloroform-methanol extract). GC-MS analysis confirmed the presence of mitragynine in the extracts. Finally, 98% (w/w) of pure mitragynine was compared based on average intensity ratio of carbon signals to the standard. This study demonstrated high yield of pure mitragynine was successfully extracted from M. speciosa leaves.
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation

We verify our method mainly on the BlendMask [2] framework. Most hyperparameters are kept the same except the resolution of attention map 7 × 7 for the training efficiency. ResNet-50 [3] is used as our backbone network and the weights are pre-trained on ImageNet [4]. We train the model using stochastic gradient descent (SGD) with 4 TITAN RTX GPUs. We set the mini-batch size to 16 images. We adopt 1× schedule (90K iterations) with the initial learning rate of 0.01. It is reduced by a factor of 10 at iteration 60K and 80K, respectively. Input images are resized to have shorter side 800 pixels and a longer side at maximum 1333 pixels.
Structure of Thermally Modified Wood Studied by Liquid State NMR Measurements

Summary Thermal modification is a technique to produce wood with increased dimensional stability and lower equilibrium moisture content. 2H NMR relaxation measurements and pulsed field gradient (PFG-NMR) methods are non-invasive spectroscopic techniques that can be used to measure the response of liquid confined in porous materials and yield information on the size and distribution of the pores. These methods were used to study the structure and changes in structure of thermally modified Scots pine wood. The 2H longitudinal relaxation measurements of wood samples at different moisture contents showed different relaxation times and relaxation time distribution in the thermally treated samples. The effect of the thermal treatments on the cell size in wood samples was studied by PFG-NMR measurements with different dwell times. The PFG-NMR measurements showed no clear change in the cell dimensions of the thermally modified samples compared with control samples taken from the same log.
1,2,3,4,5,6‐Hexa(eq)alkylcyclohexan‐Modellverbindungen für Struktur‐Eigenschafts‐Vergleiche gesättigter discotischer Flüssigkristalle

1,2,3,4,5,6-Hexa(eq)alkylcyclohexane Model Compounds for Structure-Property Comparisons of Saturated Discotic Liquid Crystals The new hydrocarbon (1α, 2β, 3α, 4β, 5α, 6β)-hexahexylcyclohexane (19) and a number of new and differently functionalized scyllo-hexaalkylcyclohexane derivatives (16a, b, 18a – c) with identical stereochemistry were synthesized stereospecifically starting from simple chemical materials. In comparison to the known scyllitol hexaester 1 and the hexaether 2 none of the novel compounds 16, 18, and 19 were thermomesomorphic. This extreme difference in the thermotropic liquid-crystalline behaviour of the hexa(eq)hydroxycyclohexane (scyllitol) derivatives 1 and 2 on the one hand and of our varied hexa(eq)alkylcyclohexans 16, 18, and 19 on the other obviously is a function of the presence and the position of the element oxygen within the side chains of these symmetric star-/disc-shaped compounds. Details concerning this oxygen effect are discussed briefly.
Magnetic Hydrogels and Their Potential Biomedical Applications

Hydrogels find widespread applications in biomedical engineering due to their hydrated environment and tunable properties (e.g., mechanical, chemical, biocompatible) similar to the native extracellular matrix (ECM). However, challenges still exist regarding utilizing hydrogels in applications such as engineering 3D tissue constructs and active targeting in drug delivery, due to the lack of controllability, actuation, and quick‐response properties. Recently, magnetic hydrogels have emerged as a novel biocomposite for their active response properties and extended applications. In this review, the state‐of‐the‐art methods for magnetic hydrogel preparation are presented and their advantages and drawbacks in applications are discussed. The applications of magnetic hydrogels in biomedical engineering are also reviewed, including tissue engineering, drug delivery and release, enzyme immobilization, cancer therapy, and soft actuators. Concluding remarks and perspectives for the future development of magnetic hydrogels are addressed.
The phase diagram of charge-polydisperse colloids: a Monte Carlo study

The effect of charge polydispersity (CPD) on structural ordering of dilute charged aqueous colloidal suspensions is investigated using Monte Carlo simulations as a function of impurity-ion concentration (ni) and CPD. The behaviours of the pair correlation function, mean square displacement and total interaction energy as functions of CPD and ni are investigated to identify different phases. Crystalline order is found to transform into a glass-like order beyond a critical CPD. Both the crystalline and glassy orders are found to melt when ni is increased. The transitions between the crystalline, glassy and liquid-like phases are characterized. The phase diagram as a function of CPD and ni is reported. Colloidal crystals with finite CPD are found to melt at ni lower than that corresponding to the monodisperse (zero-CPD) suspension. The behaviour of the phase boundaries is discussed.
Utilisation of oxygen for enhanced gasification performance

Oxygen-based gasification offers advantages over air-based gasification such as reduced capital costs or similar operating costs combined with the potential to use the higher calorific value syngas in high-efficiency power generation systems, greatly enhancing revenue creation potential. This paper reports on the effects of increasing oxygen purity on the gasification processes and includes a techno-economic assessment that uses both theoretical and experimental observations involving the gasification of a waste fuel. Syngas quality is dramatically affected by the purity of the oxygen used in gasification, with increased purity leading to reduced levels of nitrogen, increased levels of combustible gas components and enhanced calorific values. The calorific value of air-based gasification syngas is 4–5 MJ/Nm3, but increases to 10–12 MJ/Nm3 with oxygen-based gasification. In addition, gasification performance, as measured by cold gas conversion efficiency, is also affected by the purity of the oxygen used i.
α,ωn‐Heterotelechelic Hyperbranched Polyethers Solubilize Carbon Nanotubes

The synthesis of novel linear-hyperbranched (linhb) polyether block copolymers based on poly(ethylene oxide) and branched poly(glycerol), bearing a single pyrene or myristyl moiety at the α-position of the linear chain is described. The polymers exhibit low polydispersity (M w /M n < 1.3) and controlled molecular weights (M n = 5 000 g·mol -1 ). The mainly hydrophilic block copolymers with multiple hydroxyl end groups readily dissolve multiwalled carbon nanotubes (MWCNTs) in water by mixing and subsequent sonification, resulting in noncovalent attachment of the linhb hybrid structure to the carbon nanotubes (CNTs). Transmission electron microscopy (TEM) was employed to visualize the solubilized nanotubes; after sulfation of the multiple hydroxyl groups the polymer layer was detected in the TEM images.
Wavelength‐dispersive x‐ray fluorescence measurements on organic matrices: application to milk‐based products

A simple and fast method for the determination of a series of analytes (sodium, magnesium, phosphorus, sulfur, chlorine, potassium, calcium, iron, zinc) in milk-based products by wavelength-dispersive x-ray fluorescence spectrometry was developed and validated. Reference values were obtained by inductively coupled plasma optical emission spectroscopy and by potentiometry for chloride. The investigated samples were commercial products obtained from various parts of the world. Pellets of 4 g were prepared under 2 t pressure. For each sample, three pellets were prepared and analysed. Limits of quantification and repeatabilities were evaluated for the described analytes. Calibrations were established with 29 samples and validation of the method was made using a second set of 29 samples. An evaluation of this alternative method was done by comparison with data from the reference methods, using robust statistics. Copyright © 2004 John Wiley & Sons, Ltd.
Molecular Dynamics Simulations of Water and Sodium Diffusion in Smectite Interlayer Nanopores as a Function of Pore Size and Temperature

The diffusion coefficients (D) of water and solutes in nanoporous Na-smectite clay barriers have been widely studied because of their importance in high-level radioactive waste (HLRW) management and in the isolation of contaminated sites. However, few measurements have been carried out at the high temperatures that are expected to occur in HLRW repositories. We address this knowledge gap by using molecular dynamics (MD) simulations to predict the temperature dependence of diffusion in clay interlayer nanopores, expressed as a pore scale activation energy of diffusion (Ea). Our sensitivity analysis shows that accurate prediction of pore scale D and Ea values requires careful consideration of the influence of pore size, simulation cell size, and clay structure flexibility on MD simulation results. We find that predicted D values in clay interlayer nanopores are insensitive to the size of the simulation cell (contrary to the behavior observed in simulation of bulk liquid water) but sensitive to the vibration.
Correlations Between Near-Infrared Spectra of Wet-Stored Timber and the Storage Time in Relation to the Water Quality

Near-infrared spectroscopy (NIR) and multivariate calibration using partial least squares regression (PLSR) were used to study the correlation between the storage time of wet-stored timber and NIR spectra of the wood, as well as to distinguish between different wood zones (sapwood and heartwood). The wood zones were well distinguishable by NIR in logs of Scots pine (Pinus sylvestris). When wet-stored using recirculating water, between 70 and 92% of the variance was explained, whereas after wet-storage using tap water, less than 50% of the variance in the storage time was explained.