Miracle-dz/UniFAR-FTUs huggingface dataset:
The status of rule reordering

Within the standard theory of generative phonology, the phonological component consists of a set of partially ordered rules; where G1 and G2 are synchronic grammars of a given language L at chronologically earlier and chronologically later stages of L respectively, G1 and G2 may differ in at least the following ways: (a) G2 may contain new (phonological) rules ordered later than all rules in G1; (b) G2 may contain new rules ordered before some rules already present in G1 (c) G2 may contain the same rules as G1, but arranged in some different order; (d) G2 may operate upon a different underlying representation from that for G1 (and hence contain, to a greater or lesser degree, quite different rules); (e) some rules present in G1 may no longer be present in G2 (f) some rules o7f G1 may be present only in a modified form in G2.
Unpacking social capital in Economic Development: How social relations matter

Abstract Social capital is a contested concept, embraced by the mainstream as “the missing link” in economic analysis. This article suggests a way to turn it into a more meaningful understanding of how social relations matter in the economy. It will do so by unpacking the concept into various elements, distinguishing what social relations are from what they do, and by recognizing power in social relationships. We will illustrate our alternative approach with two case studies on the Small and Medium scale Enterprises (SME) footwear sector in Ethiopia and Vietnam. We conclude with suggestions on how this more contextual approach to the understanding of the economic influences of social relations may contribute to social economics.
Exploiting Crowd-Based Labels for Domain Focused Information Retrieval

Information search and retrieval from online sources or social forums is often performed with term based boolean queries. Such queries can produce low relevance documents in situations where the user is interested in retrieving information related to a concept, or belonging to a specific domain. In this work an approach for concept-based information retrieval is presented, which exploits word and document distributions derived from topic modeling performed on data from online sources. Documents acquired from the Reddit and Stack Exchange online social forums are used for extracting concepts, and subsequently training and testing a detector that aids in identifying and retrieving documents associated with the concept of interest. The selection of training sets for our concept based detector is aided by pre-partitioning of documents by online users (or crowd) into concept focused sub-forums, such as sub-reddits. Topics derived from a sample of the overall document set are taken to represent concepts. These topics then form the basis for identifying sub-forums that have a strong correspondence with the concept of interest, and documents within are assigned (noisy) binary labels. The applicability of our approach is demonstrated by creating a domain focused detector for Cyber Security content from Reddit data. The cross utility of this detector is demonstrated by successfully retrieving relevant Cyber Security documents from an alternate test online source: Stack Exchange. Document classification results of the proposed approach are compared favorably with classifications performed by human analysts.
The Military Injury Severity Score (mISS): A better predictor of combat mortality than Injury Severity Score (ISS)

BACKGROUND The Military Injury Severity Score (mISS) was developed to better predict mortality in complex combat injuries but has yet to be validated. METHODS US combat trauma data from Afghanistan and Iraq from January 1, 2003, to December 31, 2014, from the US Department of Defense Trauma Registry (DoDTR) were analyzed. Military ISS, a variation of the ISS, was calculated and compared with standard ISS scores. Receiver operating characteristic curve, area under the curve, and Hosmer-Lemeshow statistics were used to discriminate and calibrate between mISS and ISS. Wilcoxon-Mann-Whitney, t test and &khgr;2 tests were used, and sensitivity and specificity calculated. Logistic regression was used to calculate the likelihood of mortality associated with levels of mISS and ISS overall. RESULTS Thirty thousand three hundred sixty-four patients were analyzed. Most were male (96.8%). Median age was 24 years (interquartile range [IQR], 21–29 years). Battle injuries comprised 65.3%. Penetrating (39.5%) and blunt (54.2%) injury types and explosion (51%) and gunshot wound (15%) mechanisms predominated. Overall mortality was 6.0%. Median mISS and ISS were similar in survivors (5 [IQR, 2–10] vs. 5 [IQR, 2–10]) but different in nonsurvivors, 30 (IQR, 16–75) versus 24 (IQR, 9–23), respectively (p < 0.0001). Military ISS and ISS were discordant in 17.6% (n = 5,352), accounting for 56.2% (n = 1,016) of deaths. Among cases with discordant severity scores, the median difference between mISS and ISS was 9 (IQR, 7–16); range, 1 to 59. Military ISS and ISS shared 78% variability (R2 = 0.78). Area under the curve was higher in mISS than in ISS overall (0.82 vs. 0.79), for battle injury (0.79 vs. 0.76), non–battle injury (0.87 vs. 0.86), penetrating (0.81 vs. 0.77), blunt (0.77 vs. 0.75), explosion (0.81 vs. 0.78), and gunshot (0.79 vs. 0.73), all p < 0.0001. Higher mISS and ISS were associated with higher mortality. Compared with ISS, mISS had higher sensitivity (81.2 vs. 63.9) and slightly lower specificity (80.2 vs. 85.7). CONCLUSION Military ISS predicts combat mortality better than does ISS. LEVEL OF EVIDENCE Prognostic and epidemiologic study, level III.
Online Representation Learning in Recurrent Neural Language Models

We investigate an extension of continuous online learning in recurrent neural network language models. The model keeps a separate vector representation of the current unit of text being processed and adaptively adjusts it after each prediction. The initial experiments give promising results, indicating that the method is able to increase language modelling accuracy, while also decreasing the parameters needed to store the model along with the computation required at each step.
Concepts of Interdisciplinarity: Configurations of Knowledge and Action

Twelve faculty directors of graduate liberal studies programs primarily in the US were interviewed by recorded telephone conversation in an effort to understand how they define interdisciplinarity, the intellectual aims to which they aspire, and their views about the nature of reality in knowledge development. Classification of their comments reinforces other writers’ observations that scholars differ in the degree to which knowledge integration defines interdisciplinarity and they differ in the degree to which they believe interdisciplinary knowledge is endogenous or exogenous to the university. Based on their views of knowledge integration and the social relevance of knowledge, four types of interdisciplinary scholars are hypothesized. Of additional interest are the perceived functions of interdisciplinary work and the way that these scholars by-pass philosophical debates about the nature of reality in favor of their practices of scholarship. Implications for the nature, meaning, and practice of interdisciplinarity are discussed.
Hardware Acceleration of Frequent Itemsets Mining on Data Streams

In recent times, processing of data streams is gaining the attention of the scientific community due to its practical applications. Data stream is an unbounded and infinite flow of data arriving at high rates and, therefore, the classical data mining approaches can not be used straightforward in this scenario. Because of this, finding alternatives to achieve better results in the discovering of frequent itemsets on data streams is an active research topic. One of such alternatives is to develop single-pass parallels methods that can be implemented in hardware to take advantage of the inner parallelism of such devices. In this paper, a new method that can mine high incoming rates data streams is presented. As preliminary results, the proposed methods can mine in exhaustive fashion the incoming data streams when its number of single items is low. When the number of single items is high, the proposed method obtains an approximate solution with no false positives itemset produced.
Propensity Score Analysis With Fallible Covariates

A latent variable modeling approach that permits estimation of propensity scores in observational studies containing fallible independent variables is outlined, with subsequent examination of treatment effect. When at least one covariate is measured with error, it is indicated that the conventional propensity score need not possess the desirable property of bias adjustment with respect to possible prior group differences. For this setting, a modified propensity score is discussed that is based on true scores on fallible covariates and perfectly measured covariates, if available. This modified score can be recommended to use for average treatment effect evaluation in circumstances where selection into groups occurs on corresponding underlying latent dimensions measured with error. The proposed propensity score procedure is illustrated with an example.
Hospital re-admissions in relation to acute stroke unit care versus conventional care in elderly patients the first year after stroke: the Göteborg 70+ Stroke study.

BACKGROUND re-hospitalisation after discharge following index stroke varies over time and with age and comorbidity. There is little knowledge about whether stroke unit care reduces the need of re-admissions. OBJECTIVES to examine whether stroke unit care as compared with care in general medical wards was associated with fewer re-hospitalisations for conditions judged to be secondary to acute stroke and to identify the influence of stroke severity on re-admission rates. DESIGN we conducted a one-year randomised study to compare the outcome of treatment at an acute stroke unit in a care continuum with the outcome of treatment at general medical wards. SETTINGS acute and geriatric hospitals in Göteborg, Sweden. SUBJECTS 216 elderly patients aged >or=70 years discharged to their own homes or to institutionalised living after index stroke. METHODS comparison of comorbidity classified according to Charlson's morbidity index, re-admission rates, length of hospital stay, number of re-admissions and diagnoses between a group treated at a stroke unit and a group treated at general wards. RESULTS the re-admission rates, length of hospital stay and causes of re-admissions did not differ between the two groups. Complications related to the damage to the brain and concomitant heart disease were the most common causes of re-admissions in both groups. Index stroke severity did not influence the re-admission rates. CONCLUSIONS re-admissions for conditions judged to be secondary to acute stroke were equal in the two groups in this prospective study.
Development of a cane with a haptic interface using IC tags for the visually impaired

It is often difficult for visually impaired persons to walk outside to his or her destination. In this paper, we develop a cane with a built-in haptic interface for use by visually impaired persons. The cane is paired with IC tags buried underground (e.g., under street pavement). The haptic interface is controlled with a position and velocity control system that accurately indicates four directions (forward, backwards, right and left). After evaluating the vibration in the haptic interface, we determined the optimal vibration frequencies indicating a specific direction were combinations of 5 (Hz) and 1 (Hz). Furthermore, the optimal repetition of vibrations was determined to be two times. By using these conditions, the four directions were recognized more than 95% of the time. It was also confirmed that the visually impaired person recognized the presented direction even when an IC tag was buried underground. In the future, a mechanism will be developed that will allow visually impaired persons to recognize directions more accurately even if they swing the cane in a controlled manner. In addition, we will integrate a route decision system into the cane equipped with the haptic interface.
A Single Amino Acid Substitution in the Core Protein of West Nile Virus Increases Resistance to Acidotropic Compounds

West Nile virus (WNV) is a worldwide distributed mosquito-borne flavivirus that naturally cycles between birds and mosquitoes, although it can infect multiple vertebrate hosts including horses and humans. This virus is responsible for recurrent epidemics of febrile illness and encephalitis, and has recently become a global concern. WNV requires to transit through intracellular acidic compartments at two different steps to complete its infectious cycle. These include fusion between the viral envelope and the membrane of endosomes during viral entry, and virus maturation in the trans-Golgi network. In this study, we followed a genetic approach to study the connections between viral components and acidic pH. A WNV mutant with increased resistance to the acidotropic compound NH4Cl, which blocks organelle acidification and inhibits WNV infection, was selected. Nucleotide sequencing revealed that this mutant displayed a single amino acid substitution (Lys 3 to Glu) on the highly basic internal capsid or core (C) protein. The functional role of this replacement was confirmed by its introduction into a WNV infectious clone. This single amino acid substitution also increased resistance to other acidification inhibitor (concanamycin A) and induced a reduction of the neurovirulence in mice. Interestingly, a naturally occurring accompanying mutation found on prM protein abolished the resistant phenotype, supporting the idea of a genetic crosstalk between the internal C protein and the external glycoproteins of the virion. The findings here reported unveil a non-previously assessed connection between the C viral protein and the acidic pH necessary for entry and proper exit of flaviviruses.
Factors Affecting the Toxic Effect of Tin on Estuarine Microorganisms

Inorganic tin (SnCl4·H2O) is toxic to microbial populations obtained from estuarine sediments plated on nutrient medium solidified with either agar or purified agar. The use of gelatin as a gelling agent decreased the apparent toxicity of tin, and toxicity was markedly reduced in medium solidified with silica gel. There was no evidence that toxic agar-tin complexes were involved. Cd, Cu, Pb, Ni, and Zn exhibited similar toxicity patterns; therefore, toxicity levels determined in the laboratory should be extrapolated to the environment with caution. The addition of cysteine to the medium had no effect on tin toxicity. Serine or 3-hydroxyflavone enhanced toxicity, while humic acids or gelatin inhibited toxicity. Replacement of SO42− with NO3− did not alter tin toxicity, but replacement of Cl− with NO3− decreased tin toxicity. Thus, the toxic effect(s) of tin depend as much on the chemical speciation of the metal as on the total concentration of the metal in the medium.
Hypomania induced by a Garcinia cambogia supplement

Garcinia cambogia, a tropical fruit traditionally used in India and Southeast Asia for culinary and therapeutic purposes, recently became a popular ingredient in weight-loss over-thecounter supplements. Hydroxycitric acid, considered its main active ingredient, has serotoninergic effects and has been implicated in cases of severe serotoninergic syndrome. Such effects have been proposed to underlie the occurrence of mania associated with consumption of supplements containing Garcinia (Hendrickson et al., 2016; Narasimha et al., 2013). Here, we present the case of a 51-year-old woman with a 12-year history of type 1 bipolar disorder. Written informed consent was obtained from the patient for publication of patient information. After introduction of mood stabilizers, the patient remained stable, with only occasional episodes of hypomania or mild depression. After 2 years of full stability, under treatment with valproic acid 1250 mg/day and paroxetine 20 mg/day, the patient started consumption of a weight-loss dietary supplement containing Garcinia cambogia, calcium, chromium and potassium. After 2 weeks, irritability, agitation, increased energy and decreased need for sleep were noticed, that were sustained until the next routine visit with the psychiatrist, which was 2 weeks later. Given the assessment of a hypomanic episode temporally related to consumption of the dietary supplement, and considering the available literature (Hendrickson et al., 2016; Narasimha et al., 2013), the patient was advised to discontinue the supplement, while maintaining other medication. She returned 2 weeks later and reported that approximately 1 week after ceasing the supplement, while maintaining treatment with valproic acid and paroxetine at the same doses, her mood had stabilized with full remission of all symptoms of hypomania. We believe this case supports and extends prior reports of Garciniaassociated mania. Critically, prior reports either omitted full supplement composition (Hendrickson et al., 2016) or reported on mania after consumption of a supplement containing also other active stimulants, such as caffeine and guarana (Narasimha et al., 2013), rather than only Garcinia and inert ingredients, as reported here. Furthermore, in previous cases, treatment included introduction of mood stabilizers, neuroleptics and/or benzodiazepines, such that improvement could not be attributed specifically to withdrawal of the supplement (Hendrickson et al., 2016; Narasimha et al., 2013). Here, improvement of manic symptoms resulted only from withdrawal of Garcinia, meriting an assessment of a probable/likely causal association between consumption of the Garcinia supplement and occurrence of hypomania (Edwards and Aronson, 2000). This case thus underscores the need to explore and record use of dietary supplements in patients with bipolar disorder, while reinforcing the adequacy of recommending against the use of Garcinia supplement in this patient population.
User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Title of dissertation: USER BEHAVIORAL MODELING OF WEB-BASED SYSTEMS FOR CONTINUOUS USER AUTHENTICATION Leslie C. Milton, Doctor of Philosophy, 2015 Dissertation directed by: Professor Atif M. Memon Department of Computer Science University of Maryland, College Park Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user’s session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to “continuously authenticate users” while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from “normal behavior” can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user’s actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic. USER BEHAVIORAL MODELING OF WEB-BASED SYSTEMS FOR CONTINUOUS USER AUTHENTICATION
Educational change and evaluation in Eastern and Southern Africa

The articles featured in this Special Issue of Compare are revised or reworked versions of papers presented to the 7th Oxford International Conference on Education and Development in 2003, ‘The state of education: quantity, quality and outcomes’. Every two years, the annual BAICE Conference is nested within the larger Oxford Conference framework so, reflecting this relationship, this is the second set of articles to be published in Compare from this event. This particular collection stems largely from a section of the conference on the theme of ‘Culture, context and the quality of education’, and, more specifically, from an integral Southern and Eastern African Symposium that focussed upon the evaluation of policies, programmes and classrooms. The pertinence of these issues is well reflected in the promotional literature produced in advance of the Oxford Conference itself:
A Preliminary Study of Hand Hygiene Compliance Characteristics with Machine Learning Methods

—Increasing hospital re-admission rates due to Hospital Acquired Infections (HAIs) are a concern at many health-care facilities. To prevent the spread of HAIs, caregivers are expected to comply with recommended hand hygiene guidelines, which require reliable and timely hand hygiene compliance measurement systems. The current standard practice of monitoring compliance involves the direct observation of caregivers’ hand cleaning as they enter or exit a patient room by a trained observer, which can be time-consuming, resource-intensive, and subject to bias. To alleviate the heavy manual effort and reduce errors, this paper studies the characteristics of compliance that could be used to assist the direct observation approach by deciding when and where to station manual auditors and to improve compliance by providing just-in-time alerts or potentially recommending training materials to non-compliant staff. The paper analyzes location and handwashing station activation data from a 30-bed intensive care unit (ICU) and uses machine learning to assess if location, time-based factors, or other data can be used to predict handwashing non-compliance events. The results show that a care provider’s entry compliance is highly indicative of the same provider’s exit compliance and that compliance of the most recent patient room visit can also predict entry compliance of a staff member’s current patient room visit