Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Trends in Hospital System Structures From 2008 to 2015

Background: The Affordable Care Act introduced a major systematic change aimed to promote coordination across the care continuum. Yet, it remains unknown the extent to which hospital system structures have changed following the Affordable Care Act. The structure of hospital systems has important implications for the cost, quality, and accessibility of health services. Objectives: To assess trends in the structures of hospital systems. Research Design: We aggregated data from the American Hospital Association (AHA) Annual Survey to the system level. Using a panel of hospital systems from 2008 to 2015, we assessed trends in the number of hospital systems, their size, ownership characteristics, geospatial arrangements, and integration with outpatient services. Results: In the period 2008–2015, there was an increasing percentage of hospitals that were system affiliated as well as growth in the number of hospital systems. A greater percentage of hospital systems that were organized as moderately centralized systems transitioned to centralized systems than to decentralized systems (19.8% vs. 4.7%; P<0.001). In terms of geospatial arrangement, a greater percentage of hub-and-spoke systems moved to a regional design than to national systems (20.0% vs. 8.2%; P<0.05). An increasing trend over time toward greater integration with outpatient services was found in a measure of total system level integration with outpatient services. Conclusions: Our findings suggest that hospital systems may be moving toward more regional designs. In addition, the trend of increasing integration offered across hospital systems overall, and as portion of total integration, suggests that systems may be increasing their services along the continuum of care.
Appraise Evaluation Framework for Machine Translation

We present Appraise, an open-source framework for crowd-based annotation tasks, notably for evaluation of machine translation output. This is the software used to run the yearly evaluation campaigns for shared tasks at the WMT Conference on Machine Translation. It has also been used at IWSLT 2017 and, recently, to measure human parity for machine translation for Chinese to English news text. The demo will present the full end-to-end lifecycle of an Appraise evaluation campaign, from task creation to annotation and interpretation of results.
NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager

We present bot#1337: a dialog system developed for the 1st NIPS Conversational Intelligence Challenge 2017 (ConvAI). The aim of the competition was to implement a bot capable of conversing with humans based on a given passage of text. To enable conversation, we implemented a set of skills for our bot, including chit-chat, topic detection, text summarization, question answering and question generation. The system has been trained in a supervised setting using a dialogue manager to select an appropriate skill for generating a response. The latter allows a developer to focus on the skill implementation rather than the finite state machine based dialog manager. The proposed system bot#1337 won the competition with an average dialogue quality score of 2.78 out of 5 given by human evaluators. Source code and trained models for the bot#1337 are available on GitHub.
Subgroup‐specific dose finding in phase I clinical trials based on time to toxicity allowing adaptive subgroup combination

A Bayesian design is presented that does precision dose finding based on time to toxicity in a phase I clinical trial with two or more patient subgroups. The design, called Sub‐TITE, makes sequentially adaptive subgroup‐specific decisions while possibly combining subgroups that have similar estimated dose‐toxicity curves. Decisions are based on posterior quantities computed under a logistic regression model for the probability of toxicity within a fixed follow‐up period, as a function of dose and subgroup. Similarly to the time‐to‐event continual reassessment method (TITE‐CRM, Cheung and Chappell), the Sub‐TITE design downweights each patient's likelihood contribution using a function of follow‐up time. Spike‐and‐slab priors are assumed for subgroup parameters, with latent subgroup combination variables included in the logistic model to allow different subgroups to be combined for dose finding if they are homogeneous. This framework can be used in trials where clinicians have identified patient subgroups but are not certain whether they will have different dose‐toxicity curves. A simulation study shows that, when the dose‐toxicity curves differ between all subgroups, Sub‐TITE has superior performance compared with applying the TITE‐CRM while ignoring subgroups and has slightly better performance than applying the TITE‐CRM separately within subgroups or using the two‐group maximum likelihood approach of Salter et al that borrows strength among the two groups. When two or more subgroups are truly homogeneous but differ from other subgroups, the Sub‐TITE design is substantially superior to either ignoring subgroups, running separate trials within all subgroups, or the maximum likelihood approach of Salter et al. Practical guidelines and computer software are provided to facilitate application.
Incorporating Image Matching Into Knowledge Acquisition for Event-Oriented Relation Recognition

Event relation recognition is a challenging language processing task. It is required to determine the relation class of a pair of query events, such as causality, under the condition that there isn’t any reliable clue for use. We follow the traditional statistical approach in this paper, speculating the relation class of the target events based on the relation-class distributions on the similar events. There is minimal supervision used during the speculation process. In particular, we incorporate image processing into the acquisition of similar event instances, including the utilization of images for visually representing event scenes, and the use of the neural network based image matching for approximate calculation between events. We test our method on the ACE-R2 corpus and compared our model with the fully-supervised neural network models. Experimental results show that we achieve a comparable performance to CNN while slightly better than LSTM.
Cognitive Systems: Argument and Cognition

—Developing systems that are aware of, and accommodate for, the cognitive capabilities and limitations of human users is emerging as a key characteristic of a new paradigm of cognitive computing in Artiﬁcial Intelligence. According to this paradigm, the behavior of such cognitive systems is modeled on the behavior of human personal assistants, able to understand the motivations and personal likings / afﬁnities of their interlocutors, while also being able to explain, and ultimately persuade the latter about, their computed solution (e.g., a proposed action) to a problem. This paper examines the link between argument and cognition from the psychological and the computational perspectives, and investigates how the synthesis of work on reasoning and narrative text comprehension from Cognitive Psychology and of work on computational argumentation from AI can offer a scientiﬁcally sound and pragmatic basis for building human-aware cognitive systems for everyday tasks. The paper aims, thus, to reveal how argumentation can form the science of common sense thought on which new forms of cognitive systems can be engineered.
QUALES: Estimación Automática de Calidad de Traducción Mediante Aprendizaje Automático Supervisado y No-Supervisado

La estimacion automatica de calidad (EAC) de la traduccion automatica consiste en medir la calidad de traducciones sin acceso a referencias humanas, habitualmente mediante metodos de aprendizaje automatico. Un buen sistema EAC puede ayudar en tres aspectos del proceso de traduccion asistida por medio de traduccion automatica y posedicion: aumento de la productividad (descartando traducciones automaticas de mala calidad), estimacion de costes (ayudando a prever el coste de posedicion) y seleccion de proveedor (si se dispone de varios sistemas de traduccion automatica). El interes en este campo de investigacion ha crecido significativamente en los ultimos anos, dando lugar a tareas compartidas a nivel mundial (WMT) y a una fuerte actividad cientifica. En este articulo, se hace un repaso del estado del arte en este area y se presenta el proyecto quales que se esta realizando.
Analysis of phthalate esters in two different baby care products available in United Arab Emirates

Abstract Phthalates are used as plasticizers in a wide range of products and are known to affect the human health adversely. Hence, the present study was carried out to identify and quantify the presence of four phthalates namely dimethyl phthalate (DMP), dibutyl phthalate (DBP), and diethyl phthalate (DEP), di (2-ethylhexyl) phthalate (DEHP) in the two baby products i.e. baby oils and baby lotions. The daily exposure levels and hazard index of each phthalate were also calculated. It was an analytical study where two different brands of samples of baby oil and baby lotion each, from the date of manufacturing of 3, 10, and 20 months were collected. The extraction of phthalates from different samples was done and analyzed using HPTLC. Results showed the presence of all four phthalates, although some phthalates were not present in 3 M samples. The maximum concentration of all the phthalates was found in 20 M samples. Their concentration increased with the storage time indicating the possibility of leaching and migration of phthalates from the container into the product. The hazard indices for phthalates estimated for baby oil and baby lotion were found below 1, which denotes that the daily phthalate exposures are within the regulatory limits. It is important to consider that the exposure to phthalates can occur not only by dermal contact of these baby products but also through other routes. Hence, the study signifies the importance of phthalates concentration in such regularly used products.
A Tiered Control Plane Model for Service Function Chaining Isolation

This article presents an architecture for encryption automation in interconnected Network Function Virtualization (NFV) domains. Current NFV implementations are designed for deployment within trusted domains, where overlay networks with static trusted links are utilized for enabling network security. Nevertheless, within a Service Function Chain (SFC), Virtual Network Function (VNF) flows cannot be isolated and end-to-end encrypted because each VNF requires direct access to the overall SFC data-flow. This restricts both end-users and Service Providers from enabling end-to-end security, and in extended VNF isolation within the SFC data traffic. Encrypting data flows on a per-flow basis results in an extensive amount of secure tunnels, which cannot scale efficiently in manual configurations. Additionally, creating secure data plane tunnels between NFV providers requires secure exchange of key parameters, and the establishment of an east–west control plane protocol. In this article, we present an architecture focusing on these two problems, investigating how overlay networks can be created, isolated, and secured dynamically. Accordingly, we propose an architecture for automated establishment of encrypted tunnels in NFV, which introduces a novel, tiered east–west communication channel between network controllers in a multi-domain environment.
A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim

Neutropenia and febrile neutropenia (FN) are serious side effects of cytotoxic chemotherapy which may be alleviated with the administration of recombinant granulocyte colony-stimulating factor (GCSF) derivatives, such as pegfilgrastim (PG) which increases absolute neutrophil count (ANC). In this work, a population pharmacokinetic-pharmacodynamic (PKPD) model was developed based on data obtained from healthy volunteers receiving multiple administrations of PG. The developed model was a bidirectional PKPD model, where PG stimulated the proliferation, maturation, and margination of neutrophils and where circulating neutrophils in turn increased the elimination of PG. Simulations from the developed model show disproportionate changes in response with changes in dose. A dose increase of 10% from the 6 mg therapeutic dose taken as a reference leads to area under the curve (AUC) increases of ~50 and ~5% for PK and PD, respectively. A full random effects covariate model showed that little of the parameter variability could be explained by sex, age, body size, and race. As a consequence, little of the secondary parameter variability (Cmax and AUC of PG and ANC) could be explained by these covariates.
Style Detection for Free Verse Poetry from Text and Speech

Modern and post-modern free verse poems feature a large and complex variety in their poetic prosodies that falls along a continuum from a more fluent to a more disfluent and choppy style. As the poets of modernism overcame rhyme and meter, they oriented themselves in these two opposing directions, creating a free verse spectrum that calls for new analyses of prosodic forms. We present a method, grounded in philological analysis and current research on cognitive (dis)fluency, for automatically analyzing this spectrum. We define and relate six classes of poetic styles (ranging from parlando to lettristic decomposition) by their gradual differentiation. Based on this discussion, we present a model for automatic prosodic classification of spoken free verse poetry that uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We evaluate our model on a large corpus of German author-read post-modern poetry and find that classes can reliably be differentiated, reaching a weighted f-measure of 0.73, when combining textual and phonetic evidence. In our further analyses, we validate the model’s decision-making process, the philologically hypothesized continuum of fluency and investigate the relative importance of various features.
Association of Dietary, Circulating, and Supplement Fatty Acids With Coronary Risk

TO THE EDITOR: We appreciate that Chowdhury and colleagues (1) have corrected some of the gross errors in their original paper. Of note, the inverse association of intake of long-chain -3 polyunsaturated fatty acids (PUFAs) with cardiovascular disease (CVD) risk is now significant. We also appreciate the sensitivity analysis showing that with exclusion of the outlying SDHS (Sydney Diet Heart Study), the included randomized, controlled trials (RCTs) show benefit of replacing saturated fatty acids (SFAs) with PUFAs. The extreme diet used in that study was never recommended or consumed in the United States. It included a trans fatbased margarine and probably very little -3 PUFAs, because sunflower oil was used to replace other fats as much as possible. However, other serious problems with Chowdhury and colleagues analysis remain. They report that the nonsignificant findings for biomarkers of long-chain -3 fatty acid intake are based on total long-chain -3 PUFAs in only 4 studies. However, in the Supplement Tables, long-chain -3 PUFAs were actually examined in 13 studies, and findings for the specific long-chain PUFAs (eicosapentaenoic and docosahexaenoic acids) were robustly and significantly inverse. Thus, the results for both intake and biomarkers for long-chain -3 fatty acids support benefit. Although the findings for RCTs vary, these results would be expected because many of the populations studied had relatively high intake of -3 fatty acids and most individuals would likely experience little benefit. The analysis for -6 PUFAs still includes only 8 studies and omits others included in Jakobsen and coauthors (2) pooled analysis of original data and other published papers. The data on intake of -6 PUFAs from the Kuopio Heart Study (3), the study with the most positive association, are erroneous because the denominator is almost double the number of healthy participants. Contrary to what Chowdhury and colleagues state, they apparently included persons with prevalent CVD at baseline instead of limiting the analysis to healthy persons. The original study reported a relative risk (RR) of 0.38 (95% CI, 0.20 to 0.70) for fatal CVD among those with higher intake of PUFAs. Chowdhury and colleagues still do not acknowledge the earlier pooled analysis of primary data based on a larger number of studies, which allowed direct comparisons among different types of fats. In that analysis, substitution of SFAs with PUFAs was associated with lower risks for coronary heart disease (CHD) (2). The large body of data showing that replacing SFAs with monosaturated fatty acids (MUFAs) or PUFAs reduces low-density lipoprotein (LDL) cholesterol is still not recognized. Although Chowdhury and colleagues say that their conclusions did not change, a more inclusive and correct review of available evidence would support the replacement of SFAs with PUFAs.
The role of NLRP3 inflammasome in stroke and central poststroke pain

Background: NLRP3 inflammasome plays a prominent role in the pathogenesis and progression of many diseases, such as type 2 diabetes mellitus, obesity, atherosclerosis, and Alzheimer's disease. However, little knowledge is known about the role of NLRP3 inflammasome in central post-stroke pain (CPSP). Methods: We selected relevant studies by searching PubMed, Embase, and Medline from inception through February, 2018. We systematically reviewed available publications according to the terms “NLRP3 inflammasome” and “stroke” or “central post-stroke pain” in the title/abstract field. Results: We reviewed the articles and put forward two possible ways for NLRP3 inflammasome in CPSP. One way is that NLRP3 activation causes cerebral cortex injure, decreasing descending projection fiber to thalamus. Such condition may let GABAergic releases reduce, making the ventral basal (VB) neurons excitability increased. Finally, CPSP occur. Another way is that NLRP3 inflammasome leads to thalamic lesion and strengthens inflammatory response of microglia at the same time. Persistent inflammation causes GABAergic alteration in thalamus reticular neurons (TRN) to restrain VB interneurons functions, contributing to CPSP. Conclusions: These possible mechanisms will help become knowledgeable about the occurrence CPSP and provide potential therapy for CPSP.
Latent Agents in Networks: Estimation and Pricing

We focus on a setting where agents in a social network consume a product that exhibits positive local network externalities. A seller has access to data on past consumption decisions/prices for a subset of observable agents, and can target these agents with appropriate discounts to exploit network effects and increase her revenues. A novel feature of the model is that the observable agents potentially interact with additional latent agents. These latent agents can purchase the same product from a different channel, and are not observed by the seller. Observable agents influence each other both directly and indirectly through the influence they exert on the latent agents. The seller knows the connection structure of neither the observable nor the latent part of the network. Due to the presence of network externalities, an agent's consumption decision depends not only on the price offered to her, but also on the consumption decisions of (and in turn the prices offered to) her neighbors in the underlying network. We investigate how the seller can use the available data to estimate the matrix that captures the dependence of observable agents' consumption decisions on the prices offered to them. We provide an algorithm for estimating this matrix under an approximate sparsity condition, and obtain convergence rates for the proposed estimator despite the high dimensionality that allows more agents than observations. Importantly, we then show that this approximate sparsity condition holds under standard conditions present in the literature and hence our algorithms are applicable to a large class of networks. We establish that by using the estimated matrix the seller can construct prices that lead to a small revenue loss relative to revenue-maximizing prices under complete information, and the optimality gap vanishes relative to the size of the network.
Temporal Dynamics of Attentional Bias

Biases of emotional attention are believed to be central to human (mal)adaptation and multiple forms of psychopathology. Yet fundamental questions remain regarding the nature and empirical study of attentional bias (AB). We thus aimed to (a) test a novel conceptualization and related operationalization of AB expression in time and (b) illuminate the nature of AB and specifically its temporal expression. We examined AB expression in time by means of a novel trial-level bias score (TL-BS) analysis of dot probe task data in two experiments—among spider phobics and healthy controls, and among smoking-deprived daily smokers. Findings revealed evidence of the dynamic expression of AB in time; furthermore, TL-BS parameters demonstrated unique associations with psychopathology and addiction beyond traditional bias score. The present research may help to bring the conceptualization and quantification of AB closer to the nature of the phenomenon and thereby advance basic and clinical knowledge.
Blood pressure lowering effect of statin drugs with an application to rosuvastatin

Hyperlipidemia and hypertension are among the major risk factors for cardiovascular disease (CVD) and they often co-exist within a single patient. Recently, many studies published results regarding the potential role of statins in decreasing blood pressure (BP) however there is still a controversy over the efficacy of statin therapy on BP. This study aimed to investigate the potential role of rosuvastatin in BP lowering properties in Korean population. Data were taken from three randomized, multiple-dose cross over studies for rosuvastatin, angiotensin II receptor blocker (ARB) and metformin monotherapies and the combined therapy of rosuvastatin and ARB, in total of 91 healthy male normotensive subjects. Measurements of systolic blood pressure (SBP), diastolic blood pressure (DBP) at the baseline before treatment begins and for 24 hours after the last dose were used in the analysis. The analysis variables used were (i) the mean change in steady-state BP from the baseline, symbolized as ΔBP, and (ii) the difference in ΔBP between the ARB monotherapy and the combined therapy, symbolized as ΔBP,d. The △BP and ΔBP,d for SBP from each study varied in -0.1 ~ -1.3 mmHg and 1.2 ~ 1.6 mmHg, respectively, and were not significantly different from zero. The △BP and ΔBP,d for DBP from each study varied in -2.8 ~ -1.4 mmHg and -2.9 ~ -1.8, respectively, which were statistically significant for △BP (p 0.05). These results indicated that the rosuvastatin monotherapy may produce small blood pressure lowing effect in DBP.
Development of a Power Controller for an Induction Crucible Furnace of Industrial Frequency for Melting Magnesium

Traditionally, the power of induction crucible furnaces of industrial frequency for melting magnesium is carried out by the furnace regulating transformer. During the melting of magnesium ingots in a steel ferromagnetic crucible, the voltage value on the inductor changes dramatically due to a nonlinear change in the parameters of the “inductor-charge” system at a temperature above 723 °C. Smooth power regulation can be achieved by using an uncontrolled power transformer with a thyristor frequency converter that performs the function of voltage regulation and conversion of the number of phases.