Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion Tensor Tractography Studies of Central Post-stroke Pain Due to the Spinothalamic Tract Injury: A Mini-Review

Elucidation of the pathophysiological mechanism of central post-stroke pain (CPSP) is essential to the development of effective therapeutic modalities for CPSP. However, the pathophysiological mechanism of CPSP has not yet been clearly elucidated. The recent development of diffusion tensor tractography (DTT), derived from diffusion tensor imaging (DTI), has allowed visualization and estimation of the spinothalamic tract (STT), which has been considered the most plausible neural tract responsible for the pathogenesis of CPSP. In this mini-review, six DTT studies in which CPSP due to STT injury in stroke patients was demonstrated are reviewed. The information provided in the reviewed studies suggests that DTT is useful in the elucidation of the pathophysiological mechanism associated with CPSP. We believe that the reviewed studies will facilitate neurorehabilitation of stroke patients with CPSP. However, DTT studies of CPSP are still in the beginning stage because the total number (six studies) of the reviewed studies is very low and half were case reports. Therefore, further studies involving large numbers of subjects are warranted.
Computational Analysis of Political Texts: Bridging Research Efforts Across Communities

In the last twenty years, political scientists started adopting and developing natural language processing (NLP) methods more actively in order to exploit text as an additional source of data in their analyses. Over the last decade the usage of computational methods for analysis of political texts has drastically expanded in scope, allowing for a sustained growth of the text-as-data community in political science. In political science, NLP methods have been extensively used for a number of analyses types and tasks, including inferring policy position of actors from textual evidence, detecting topics in political texts, and analyzing stylistic aspects of political texts (e.g., assessing the role of language ambiguity in framing the political agenda). Just like in numerous other domains, much of the work on computational analysis of political texts has been enabled and facilitated by the development of resources such as, the topically coded electoral programmes (e.g., the Manifesto Corpus) or topically coded legislative texts (e.g., the Comparative Agenda Project). Political scientists created resources and used available NLP methods to process textual data largely in isolation from the NLP community. At the same time, NLP researchers addressed closely related tasks such as election prediction, ideology classification, and stance detection. In other words, these two communities have been largely agnostic of one another, with NLP researchers mostly unaware of interesting applications in political science and political scientists not applying cutting-edge NLP methodology to their problems. The main goal of this tutorial is to systematize and analyze the body of research work on political texts from both communities. We aim to provide a gentle, all-round introduction to methods and tasks related to computational analysis of political texts. Our vision is to bring the two research communities closer to each other and contribute to faster and more significant developments in this interdisciplinary research area.
Effects of Acute Normobaric Hypoxia on Non-linear Dynamics of Cardiac Autonomic Activity During Constant Workload Cycling Exercise

Aim Measurements of Non-linear dynamics of heart rate variability (HRV) provide new possibilities to monitor cardiac autonomic activity during exercise under different environmental conditions. Using detrended fluctuation analysis (DFA) technique to assess correlation properties of heart rate (HR) dynamics, the present study examines the influence of normobaric hypoxic conditions (HC) in comparison to normoxic conditions (NC) during a constant workload exercise. Materials and Methods Nine well trained cyclists performed a continuous workload exercise on a cycle ergometer with an intensity corresponding to the individual anaerobic threshold until voluntary exhaustion under both NC and HC (15% O2). The individual exercise duration was normalized to 10% sections (10–100%). During exercise HR and RR-intervals were continuously-recorded. Besides HRV time-domain measurements (meanRR, SDNN), fractal correlation properties using short-term scaling exponent alpha1 of DFA were calculated. Additionally, blood lactate (La), oxygen saturation of the blood (SpO2), and rating of perceived exertion (RPE) were recorded in regular time intervals. Results We observed significant changes under NC and HC for all parameters from the beginning to the end of the exercise (10% vs. 100%) except for SpO2 and SDNN during NC: increases for HR, La, and RPE in both conditions; decreases for SpO2 and SDNN during HC, meanRR and DFA-alpha1 during both conditions. Under HC HR (40–70%), La (10–90%), and RPE (50–90%) were significantly-higher, SpO2 (10–100%), meanRR (40–70%), and DFA-alpha1 (20–60%) were significantly-lower than under NC. Conclusion Under both conditions, prolonged exercise until voluntary exhaustion provokes a lower total variability combined with a reduction in the amplitude and correlation properties of RR fluctuations which may be attributed to increased organismic demands. Additionally, HC provoked higher demands and loss of correlation properties at an earlier stage during the exercise regime, implying an accelerated alteration of cardiac autonomic regulation.
Computing Education Theories: What Are They and How Are They Used?

In order to mature as a research field, computing education research (CER) seeks to build a better theoretical understanding of how students learn computing concepts and processes. Progress in this area depends on the development of computing-specific theories of learning to complement the general theoretical understanding of learning processes. In this paper we analyze the CER literature in three central publication venues -- ICER, ACM Transactions of Computing Education, and Computer Science Education -- over the period 2005--2015. Our findings identify new theoretical constructs of learning computing that have been published, and the research approaches that have been used in formulating these constructs. We identify 65 novel theoretical constructs in areas such as learning/understanding, learning behaviour/strategies, study choice/orientation, and performance/progression/retention. The most common research methods used to devise new constructs include grounded theory, phenomenography, and various statistical models. We further analyze how a number of these constructs, which arose in computing education, have been used in subsequent research, and present several examples to illustrate how theoretical constructs can guide and enrich further research. We discuss the implications for the whole field.
CCGweb: a New Annotation Tool and a First Quadrilingual CCG Treebank

We present the first open-source graphical annotation tool for combinatory categorial grammar (CCG), and the first set of detailed guidelines for syntactic annotation with CCG, for four languages: English, German, Italian, and Dutch. We also release a parallel pilot CCG treebank based on these guidelines, with 4x100 adjudicated sentences, 10K single-annotator fully corrected sentences, and 82K single-annotator partially corrected sentences.
DEFT: A corpus for definition extraction in free- and semi-structured text

Definition extraction has been a popular topic in NLP research for well more than a decade, but has been historically limited to well-defined, structured, and narrow conditions. In reality, natural language is messy, and messy data requires both complex solutions and data that reflects that reality. In this paper, we present a robust English corpus and annotation schema that allows us to explore the less straightforward examples of term-definition structures in free and semi-structured text.
Supporting Instruction of Formulaic Sequences Using Videos at Scale

To help language learners achieve fluency, instructors often focus on teaching formulaic sequences (FS)--phrases such as idioms or phrasal verbs that are processed, stored, and retrieved holistically. Teaching FS effectively is challenging as it heavily involves instructors' intuition, prior knowledge, and manual efforts to identify a set of FSs with high utility. In this paper, we present FSIST, a tool that supports instructors for video-based instruction of FS. The core idea of FSIST is to utilize videos at scale to build a list of FSs along with videos that include example usages. To evaluate how FSIST can effectively support instructors, we conducted a user study with three English instructors. Results show that the browsing interactions provided in FSIST support instructors to efficiently find parts of videos that show example usages of FSs. -
Towards Enhanced Accountability in Complying with Healthcare Regulations

The healthcare ecosystem is highly complex. It is composed of multiple stakeholders with intersecting interests. The healthcare regulations such as Health Insurance Portability and Accountability Act, much like the systems they protect, are complex and often difficult to interpret. Regulations contain obligations that must be fulfilled by healthcare systems that form the backbone of modern healthcare. In this paper, we present a model for extracting and deconstructing obligations. The Obligation Model allows for capturing the essence of obligations in terms of their attributes such as Responsible entity, Trigger, Action, Deadline and Reference. We augment the extracted obligations with auxiliary information present in regulation documents and provide an ownership based rendering of the deconstructed obligation in an HTML format. This helps in establishing an explicit ownership of obligations and contributes towards enhancing accountability of stakeholders towards fulfilling the obligations. The rendering will be useful for building compliant healthcare systems by making the legal text more comprehensible for system designers.
Fecal Changes Following Introduction of Milk in Infants With Outgrowing Non-IgE Cow's Milk Protein Allergy Are Influenced by Previous Consumption of the Probiotic LGG

Cow's milk protein allergy (CMPA) is the most common allergy in the first year of life. Non-IgE mediated CMPA is characterized by digestive symptoms and tolerance development before the age of three. Gut microbiota composition in early life has been associated with food allergy. The ingestion of different foods/nutrients may mark different shifts in the microbial colonization of the infant intestine as well as the consumption of probiotics. Aim: To analyze changes in microbiota composition and metabolic and cytokine profiles in fecal samples from infants with non-IgE mediated CMPA after successful milk challenges, tolerance acquisition, and increasing dairy introduction in their diet. Methods: Twelve children with CMPA, aged between 1 and 2 years old, were recruited for the study. Participants were initially consuming hypoallergenic hydrolyzed formulas (four of them supplemented with the probiotic Lactobacillus rhamnosus GG), before being exposed to a standardized oral challenge (SOC) with cow's milk. Fecal samples were collected before, 1 week, and 1 month after performing the SOC. Changes in gut microbiota were determined by high-throughput amplicon sequencing of the 16S rRNA gene. Levels of lactobacilli were also determined by quantitative PCR (qPCR). Microbial metabolites were analyzed by chromatographic methods and fecal cytokines related to the Th1/Th2 balance were determined by immunoassay. Results: Lactic acid bacteria significantly increased in infants who outgrew non-IgE CMPA, after the introduction of milk. Microbial metabolites derived from the fermentation of proteins, such as branched chain fatty acids, and p-cresol, diminished. After the SOC, some cytokines related to inflammation (TNF-α, IFN-γ) increased. Accompanying the introduction of an unrestricted diet, we found significant differences in fecal microbial composition, metabolites, and cytokines between infants who did not consume the probiotic L. rhamnosus GG and those that did. Conclusions: These findings indicate that the introduction of intact milk proteins is followed by modifications in the infant gut environment through changes in immune mediators, microbiota, and its metabolic end-products. Consumption of probiotics during CMPA may contribute to gut homeostasis by fine-tuning these profiles.
Designing for Integrated K-5 Computing and Literacy through Story-making Activities

Proponents of computing education have long stressed the value of computing for learning in other disciplines. Much of the research towards this end has focused on supporting learning in science, engineering, and mathematics (or STEM). However, a trend towards computing in non-STEM disciplines is growing, yet the research base is more limited. We add to this emerging area of research by investigating the potential for integrating computing and literacy education. This paper reports the results of a six-week intervention during an after-school program in a British primary school. We describe the development of a curriculum unit and report on the first iterative cycle in a design-based research project. Our analysis shows that integrating programming and literacy activities supported novice learners in areas of computing such as algorithm design and program execution through a combination of short problem-based tasks and longer project-based activities. Likewise, programming supported learners in creating digital stories by visualizing narrative structure though some caveats were found. We discuss the results of this study and implications for future work in this area.
BDSI: A Validated Concept Inventory for Basic Data Structures

A Concept Inventory (CI) is a validated assessment to measure student conceptual understanding of a particular topic. This work presents a CI for Basic Data Structures (BDSI) and the process by which the CI was designed and validated. We discuss: 1) the collection of faculty opinions from diverse institutions on what belongs on the instrument, 2) a series of interviews with students to identify their conceptions and misconceptions of the content, 3) an iterative design process of developing draft questions, conducting interviews with students to ensure the questions on the instrument are interpreted properly, and collecting faculty feedback on the questions themselves, and 4) a statistical evaluation of final versions of the instrument to ensure its internal validity. We also provide initial results from pilot runs of the CI.
A Systematic Mapping Study on Internet of Things Challenges

The challenge of developing IoT-based systems has been found to be a complex problem. It is influenced by number of factors: heterogeneous devices/resources, various perception-action cycles and widely distributed devices and computing resources. Increasing complexity and immaturity to deal with it have resulted in growing range of problems and challenges in IoT development. This paper identifies essential IoT-related challenges by conducting a systematic mapping study of existing IoT literature. To this end, we distil information with respect to IoT-related: 1) challenges, 2) experimental studies, and 3) recommendations for future research. We then discuss our findings in order to understand better the general state of IoT research, potential gaps in research, and implications for future research.
Scholarly Commons at Boston University School of Law Scholarly Commons at Boston University School of Law

In the face of rising rates of antibacterial resistance, many responses are being pursued in parallel, including ‘ non-traditional ’ antibacterial agents (agents that are not small-molecule drugs and/or do not act by directly targeting bacterial components necessary for bacterial growth). In this Perspective, we argue that the distinction between traditional and non-traditional agents has only limited relevance for regulatory purposes. Rather, most agents in both categories can and should be developed using standard measures of clinical ef ﬁ cacy demonstrated with non-inferiority or superiority trial designs according to existing regulatory frameworks. There may, however, be products with non-traditional goals focused on population-level bene ﬁ ts that would bene ﬁ t from extension of current paradigms. Discussion of such potential paradigms should be undertaken by the development community.
Heart rate variability and incidence of depression during the first six months following first myocardial infarction

Background Post-myocardial depression is a highly prevalent condition worsening the course and prognosis of coronary artery disease. One of the possible pathogenetic factors is dysregulation of the autonomous nervous system, resulting in heart rate variability reduction. Methods Twenty two patients hospitalised due to a first myocardial infarction were included. The Beck Depression Inventory (BDI) was used to rate the severity of their depressive symptoms. Results Depressive symptomatology, defined as BDI ≥10, was present in 36.3% of the patients. Increase in heart rate variability (HRV) was observed in both groups during the first 6 months after the myocardial infarction. The HRV was significantly lower in the depressed group compared to patients without depression. Conclusion Presence of depression after the myocardial infarction (MI) is associated with a significant decrease of the time domain HRV measure SDNN (standard deviation of all normal RR intervals) and with its slower increase during at least a three months period.
Co-delivery of everolimus and vinorelbine via a tumor-targeted liposomal formulation inhibits tumor growth and metastasis in RCC

Background: Renal cell carcinoma (RCC) is notorious for its resistance towards chemotherapy and radiation therapy in general. Combination therapy is often helpful in alleviating the resistance mechanisms by targeting multiple signaling pathways but is usually more toxic than monotherapy. Co-encapsulation of multiple therapeutic agents in a tumor-targeted drug delivery platform is a promising strategy to mitigate these limitations. Methods: A tumor-targeted liposomal formulation was prepared using phospholipids, cholesterol, DSPE-(PEG)2000-OMe and a proprietary tumor-targeting-peptide (TTP)-conjugated lipopeptide. An efficient method was optimized to encapsulate everolimus and vinorelbine in this liposomal formulation. Single drug-loaded liposomes were also prepared for comparison. Finally, the drug-loaded liposomes were tested in vitro and in vivo in two different RCC cell lines. Results: The tumor-targeted liposomal formulation demonstrated excellent tumor-specific uptake. The dual drug-loaded liposomes exhibited significantly higher growth inhibition in vitro compared to the single drug-loaded liposomes in two different RCC cell lines. Similarly, the dual drug-loaded liposomes demonstrated significantly higher suppression of tumor growth compared to the single drug-loaded liposomes in two different subcutaneous RCC xenografts. In addition, the dual drug-loaded liposomes instigated significant reduction in lung metastasis in those experiments. Conclusion: Taken together, this study demonstrates that co-delivery of everolimus and vinorelbine with a tumor-targeted liposomal formulation is an effective approach to achieve improved therapeutic outcome in RCC.
Epidemiological analysis of respiratory and intestinal infectious diseases in three counties of Sichuan: the baseline survey of Disaster Mitigation Demonstration Area in western China

Background Natural disasters can indirectly induce epidemics of infectious diseases through air and water pollution, accelerated pathogen reproduction, and population migration. This study aimed to explore the epidemiological characteristics of the main infectious diseases in Sichuan, a province with a high frequency of natural disasters. Methods Data were collected from the local Centers for Disease Control infectious disease reports from Lu, Shifang and Yuexi counties from 2011 to 2015 and from the baseline survey of the Disaster Mitigation Demonstration Area in Western China in 2016. Principal component regression was used to explore the main influencing factors of respiratory infectious diseases (RIDs). Results The incidence rates of RIDs and intestinal infectious diseases (IIDs) in 2015 were 78.99/100,000, 125.53/100,000, 190.32/100,000 and 51.70/100,000, 206.00/100,000, 69.16/100,000 in Lu, Shifang and Yuexi respectively. The incidence rates of pulmonary tuberculosis (TB) was the highest among RIDs in the three counties. The main IIDs in Lu and Shifang were hand-foot-mouth disease (HFMD) and other infectious diarrhea; however, the main IIDs in Yuexi was bacillary dysentery. The proportions of illiterate and ethnic minorities and per capita disposable income were the top three influencing factors of RIDs. Conclusions TB was the key point of RIDs prevention among the three counties. The key preventable IIDs in Lu and Shifang were HFMD and other infectious diarrhea, and bacillary dysentery was the major IIDs in Yuexi. The incidence rates of RIDs was associated with the population composition, the economy and personal hygiene habits.
Characterization of acquired receptor tyrosine–kinase fusions as mechanisms of resistance to EGFR tyrosine–kinase inhibitors

Purpose: Responses to EGFR-targeted therapy are generally temporary, due to inevitable drug resistance. The prevalence and characteristics of receptor tyrosine–kinase (RTK) fusion as acquired resistance to EGFR tyrosine–kinase inhibitors (TKIs) are rarely investigated. Methods: We retrospectively reviewed genomic profiling data of 3873 EGFR (exons 18–21)-mutant lung cancer patients with more than once next-generation sequencing detection. A total of 16 patients who acquired RTK fusions during EGFR-TKI treatment with paired pre- and post-EGFR-TKI samples were identified. Their treatment history was collected. Results: Newly acquired RTK fusions during EGFR-TKI treatment included RET (n=6, 37.5%), ALK (n=5, 31.3%), NTRK1 (n=4, 25.0%), ROS1 (n=1, 6.3%), and FGFR3 (n=1, 6.3%). All RET and EML4–ALK fusions were uncommon variants of KIF5B-RET and E2:A20 (V5), respectively. Interestingly, RET fusion occurred only after osimertinib treatment, and contributed to drug resistance in 50% (6 of 12) of patients treated with osimertinib, indicating that fusions had different prevalence when functioning as resistance mechanisms to EGFR TKIs. Moreover, we found that in all patients developing drug resistance to EGFR TKIs due to fusion emergence (n=16), those that had a treatment history of third-generation EGFR TKIs accounted for 75% (n=12). Conclusion: We have extended the current knowledge of resistance mechanisms to EGFR TKIs in non-small-cell lung cancer. Detection of RTK fusions should be included in genomic profiling panels to uncover potential resistance mechanisms of EGFR TKIs, which might inform therapeutic strategies, such as combination-therapy approaches, to circumvent tumorigenesis.