Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantification of Adequacy of Peritoneal Dialysis

Nineteen patients treated by continuous ambulatory peritoneal dialysis (CAPD) were studied according to clinical outcome parameters: insomnia, asthenia, pruritus, arterial hypertension, anorexia, nausea and/or vomiting, anemia, and rate of hospitalization. Using clinical scores, three groups were defined: poor clinical outcome (P), intermediate (I), and good (G). The quantity of treatment by PD was evaluated monthly with urea kinetic tests (weekly Kt/V, weekly urea clearance/1.73 m2 of body surface area (BSA), index of dialysis by Teehan), and with the weekly creatinine clearance/1.73 m2 of BSA. The metabolic index was analyzed: normalized protein catabolic rate (NPCR), serum albumin (Alb) and prealbumin, and reabsorption of glucose. There was good correlation between clinical scores and quantity of dialysis. The Alb was lower in group P. Group G was differentiated from group I and from group P by quantification tests and NPCR, with lower levels as follows: weekly Kt/V=2.06, urea clearance 70 L/week/1.73 m2, index of dialysis = 0.87, and creatinine clearance = 60 L/week/1.73 m2. We conclude that the qualitative clinical approach is not sufficient to predict deleterious signs, and the quantitative approach is predictive of the good clinical outcome and good nutritional status. We think that levels proposed to now are insufficient, and we suggest the following: weekly urea clearance >70 L, weekly Kt/V >2, weekly creatinine clearance >60 L, and index of dialysis >0.85.
Offenders' Perceptions of the Sentencing Process: A Study of Deterrence and Stigmatisation in the New South Wales Children's Court

Abstract The criminal court system remains society's pre-eminent response to criminal activity, despite recent innovations such as youth justice conferences. Little is known, however, about the impact of an appearance before court and, in particular, whether subjective reactions to the court process have any impact on recidivism. The current article reports the results of a longitudinal study conducted in the New South Wales (NSW) Children's Court. Two hundred and six young offenders were interviewed immediately after the conclusion of their sentencing hearing using a questionnaire designed to measure the extent to which they perceived the court hearing to be a deterrent, and the extent to which they felt either stigmatised or reintegrated by the experience of being sentenced. Other factors measured included the developmental background of the young person, their academic record, peer influence, and licit and illicit drug use. Participants with previous convictions and who felt stigmatised by the hearing were more likely to reoffend, while participants rating their likelihood of arrest in the event of future offending as high, and who reported that the sentence they received would prevent future offending, were less likely to reoffend. Some evidence was obtained, therefore, to support both deterrence and labelling theory.
Regularized Kernel Algorithms for Support Estimation

In the framework of non-parametric support estimation, we study the statistical properties of an estimator defined by means of Kernel Principal Component Analysis (KPCA). In the context of anomaly/novelty detection the algorithm was first introduced by Hoffmann in 2007. We also extend to above analysis to a larger class of set estimators defined in terms of a filter function.
Second-stage music teachers' perceptions of career development and trajectory

The purpose of this study was to investigate the career development of three music teachers who are in the second stage of their teaching careers. Using research on both the teacher career cycle and the second stage of teaching, the participants were identified as second-stage teachers. The study employed a qualitative methodology that used a descriptive case study design (Merriam, 1998). The primary research questions were (a) how do participants perceive their career development from the first into the second stage, and (b) how do they anticipate their career trajectory through and beyond the second stage? Findings indicated that the participants perceived a transition from a first to a second stage, had different degrees and areas of self-confidence, were uncertain about their futures in music education, and were concerned about experiencing withdrawal from teaching. This study has implications for professional development, induction, and the retention and attrition of music teachers. Suggestions for further research are also included.
Reporting Pupil Progress without Report Cards

Report cards have long furnished the most direct line of communication between the home and the school. Frequently they provide the chief basis for the interpretation of the school and its program. A majority of parents, and too many teachers, conclude that the school's most important contribution to the child's education is recorded on the card. Yet the confusion of parents and the scarcely less obvious uncertainty of teachers have long suggested the inadequacy of school marks as a reliable interpreter of pupil progress or adjustment. The vicious by-products of lesson-learning, the "getby" attitude, the "passing" complex, and unwholesome competition are readily admitted. Many administrators have been experimenting with new media for reporting pupil progress. In the main, these efforts have taken the direction of reducing the range of the point scale from six or seven symbols to two or three. Frequently "satisfactory" or "unsatisfactory" are the only marks to appear on a report card. A common accompaniment to this abbreviated report of scholastic achievement is the more or less analytical check list of personality traits. Nearly everyone is ready to concede that the school must concern itself with character development and personality adjustments, but few maintain that a check list is the ideal method by which parents may be informed of pupil progress. It is too brief, too stereotyped, and too impersonal. For example, a check mark indicating that a pupil's co-operation is "showing improvement" or "needs attention" provides the parent with an inadequate picture of personality development. Frequently, too, such reports reflect no serious analyses of the growing but complex personalities intrusted to the teacher's charge. Many superintendents admit the inade-
High prevalence of cytotoxin positive Helicobacter pylori in patients unrelated to the presence of peptic ulcers in Japan

Background—It has been reported that infection with vacuolating cytotoxin positive Helicobacter pyloristrains is associated with gastroduodenal disease in Western countries. Aims—To evaluate the prevalence of cytotoxin producing strains among patients with H pyloriinfection in relation to gastrointestinal diseases in Japan. Patients—Ninety seven patients undergoing endoscopy. Methods—A Western blot assay was conducted to detect serum antibodies against the cytotoxin using recombinant cytotoxin (VacA protein) as an antigen. To obtain a purified recombinant cytotoxin, the vacA gene (2233 nucleotides) was cloned into an expression vector to produce the protein (744 amino acids), which was expressed in Escherichia coli. Results—Serum IgG antibodies to the cytotoxin were present in 85%, 95%, 95%, and 100% of infected patients with gastric ulcer (n=26), duodenal ulcer (n=21), chronic gastritis (n=19), and endoscopically normal mucosa (n=14), respectively. Conclusion—The western blot method using recombinant VacA protein is simple and useful for detecting antibody to vacuolating cytotoxin. This method showed antibodies against cytotoxin were highly prevalent, even in subjects with endoscopically normal mucosa in Japan, indicating that the cytotoxin may not be an independent cause of gastrointestinal diseases induced by H pylori infection.
On the calibration of active binocular and RGBD vision systems for dual-arm robots

This paper describes a camera and hand-eye calibration methodology for integrating an active binocular robot head within a dual-arm robot. For this purpose, we derive the forward kinematic model of our active robot head and describe our methodology for calibrating and integrating our robot head. This rigid calibration provides a closed-form hand-to-eye solution. We then present an approach for updating dynamically camera external parameters for optimal 3D reconstruction that are the foundation for robotic tasks such as grasping and manipulating rigid and deformable objects. We show from experimental results that our robot head achieves an overall sub millimetre accuracy of less than 0.3 millimetres while recovering the 3D structure of a scene. In addition, we report a comparative study between current RGBD cameras and our active stereo head within two dual-arm robotic testbeds that demonstrates the accuracy and portability of our proposed methodology.
Generating Actionable Knowledge from Big Data

The last few years have seen a rapid increase of sheer amount of data produced and communicated over the Internet and the Web. While it is widely believed that the availability of such ``Big Data'' holds the potential to revolutionize many aspects of our modern society (e.g., intelligent transportation, environmental monitoring, and energy saving), many challenges need to be addressed before this potential can be realized. This PhD project focuses on one critical challenge, namely extracting actionable knowledge from Big Data. Tremendous efforts have been contributed on mining large-scale data on the Web and constructing comprehensive knowledge bases (KBs). However, existing knowledge extraction systems retrieve data from limited types of Web sources. In addition, data fusion approaches consider very little of the noises produced by those knowledge extraction systems. Consequently, the constructed KBs are far from being comprehensive and accurate. In this paper, we present our initial design of a framework for extracting machine-readable data with high precision and recall from four types of data sources, namely Web texts, Document Object Model (DOM) trees, existing KBs, and query stream. Confidence scores are attached to the resulting knowledge, which can be used to further improve the knowledge fusion results.
For sale : your data: by : you

Monetizing personal information is a key economic driver of online industry. End-users are becoming more concerned about their privacy, as evidenced by increased media attention. This paper proposes a mechanism called 'transactional' privacy that can be applied to personal information of users. Users decide what personal information about themselves is released and put on sale while receiving compensation for it. Aggregators purchase access to exploit this information when serving ads to a user. Truthfulness and efficiency, attained through an unlimited supply auction, ensure that the interests of all parties in this transaction are aligned. We demonstrate the effectiveness of transactional privacy for web-browsing using a large mobile trace from a major European capital. We integrate transactional privacy in a privacy-preserving system that curbs leakage of information. These mechanisms combine to form a market of personal information that can be managed by a trusted third party.
Revisiting Warfarin Dosing Using Machine Learning Techniques

Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographic variables or pharmacogenetic models which additionally contain the genetic variables. In this paper, a new methodology for warfarin dosing is proposed. The patients are initially classified into two classes. The first class contains patients who require doses of >30 mg/wk and the second class contains patients who require doses of ≤30 mg/wk. This phase is performed using relevance vector machines. In the second phase, the optimal dose for each patient is predicted by two clinical regression models that are customized for each class of patients. The prediction accuracy of the model was 11.6 in terms of root mean squared error (RMSE) and 8.4 in terms of mean absolute error (MAE). This was 15% and 5% lower than IWPC and Gage models (which are the most widely used models in practice), respectively, in terms of RMSE. In addition, the proposed model was compared with fixed-dose approach of 35 mg/wk, and the model proposed by Sharabiani et al. and its outperformance were proved in terms of both MAE and RMSE.
Protein complex scaffolding predicted as a prevalent function of long non-coding RNAs

Abstract The human transcriptome contains thousands of long non-coding RNAs (lncRNAs). Characterizing their function is a current challenge. An emerging concept is that lncRNAs serve as protein scaffolds, forming ribonucleoproteins and bringing proteins in proximity. However, only few scaffolding lncRNAs have been characterized and the prevalence of this function is unknown. Here, we propose the first computational approach aimed at predicting scaffolding lncRNAs at large scale. We predicted the largest human lncRNA–protein interaction network to date using the catRAPID omics algorithm. In combination with tissue expression and statistical approaches, we identified 847 lncRNAs (∼5% of the long non-coding transcriptome) predicted to scaffold half of the known protein complexes and network modules. Lastly, we show that the association of certain lncRNAs to disease may involve their scaffolding ability. Overall, our results suggest for the first time that RNA-mediated scaffolding of protein complexes and modules may be a common mechanism in human cells.
Oblivious interference scheduling

In the interference scheduling problem, one is given a set of n communication requests described by pairs of points from a metric space. The points correspond to devices in a wireless network. In the directed version of the problem, each pair of points consists of a dedicated sending and a dedicated receiving device. In the bidirectional version the devices within a pair shall be able to exchange signals in both directions. In both versions, each pair must be assigned a power level and a color such that the pairs in each color class (representing pairs communicating in the same time slot) can communicate simultaneously at the specified power levels. The feasibility of simultaneous communication within a color class is defined in terms of the Signal to Interference Plus Noise Ratio (SINR) that compares the strength of a signal at a receiver to the sum of the strengths of other signals. This is commonly referred to as the "physical model" and is the established way of modelling interference in the engineering community. The objective is to minimize the number of colors as this corresponds to the time needed to schedule all requests. We study oblivious power assignments in which the power value of a pair only depends on the distance between the points of this pair. We prove that oblivious power assignments cannot yield approximation ratios better than Ω(n) for the directed version of the problem, which is the worst possible performance guarantee as there is a straightforward algorithm that achieves an O(n)-approximation. For the bidirectional version, however, we can show the existence of a universally good oblivious power assignment: For any set of n bidirectional communication requests, the so-called "square root assignment" admits a coloring with at most polylog(n) times the minimal number of colors. The proof for the existence of this coloring is non-constructive. We complement it by an approximation algorithm for the coloring problem under the square root assignment. This way, we obtain the first polynomial time algorithm with approximation ratio polylog(n) for interference scheduling in the physical model.
“I Would Want You to Understand It:” Students’ Perspectives on Addressing Race in the Classroom

This article reports on qualitative research addressing pedagogical issues related to race in the classroom. In 5 focus groups and 14 one-on-one interviews, researchers asked students to share their expertise regarding the challenges to and possibilities for talking about race in college and university classrooms. Results are reported related to instructor practices and student practices. Data point to the importance of instructor support for diversity and of self-reflexivity on the part of instructors related to race.
Household Surveys as a Source of Data for Event History Analysis

The authors introduce a method that allows the use of data from rotating panel surveys, a design used in many household or labour force surveys, to realize statistical analyses similar to event history analysis. The method is illustrated with two examples, one on the dynamics of poverty — the effect of demographic and socioeconomic factors on the hazard of becoming poor in Argentina — and the other on family dynamics — the conversion of consensual unions into marriages. Both examples use data from the Argentinean Encuesta Permanente de Hogares, a national survey that is not designed to collect prospective or biographical data. The method allows for the use of time-varying independent variables and thus allows one to estimate the effect of an event on the hazard of another event, as in conventional event history analysis; several examples are provided.
Th17 Cells Induce a Distinct Graft Rejection Response That Does Not Require IL‐17A

IL‐17A‐producing helper T (Th17) cells have been implicated in the pathogenesis of autoimmune disease, inflammatory bowel disease and graft rejection, however the mechanisms by which they cause tissue damage remain ill‐defined. We examined what damage Th17 cell lines could inflict on allogeneic skin grafts in the absence of other adaptive lymphocytes. CD4+ Th17 cell lines were generated from two TCR transgenic mouse strains, A1(M). RAG1−/− and Marilyn, each monospecific for the male antigen Dby. After prolonged in vitro culture in polarizing conditions, Th17 lines produced high levels of IL‐17A with inherently variable levels of interferon gamma (IFNγ) and these cells were able to maintain IL‐17A expression following adoptive transfer into lymphopenic mice. When transferred into lymphopenic recipients of male skin grafts, Th17 lines elicited a damaging reaction within the graft associated with pathological findings of epidermal hyperplasia and neutrophil infiltration. Th17 cells could be found in the grafted skins and spleens of recipients and maintained their polarized phenotype both in vivo and after ex vivo restimulation. Antibody‐mediated neutralization of IL‐17A or IFNγ did not interfere with Th17‐induced pathology, nor did it prevent neutrophil infiltration. In conclusion, tissue damage by Th17 cells does not require IL‐17A.
Compliance Checking of Organizational Interactions

In business environments, different sorts of regulations are imposed to restrict the behavior of both public and private organizations, ranging from legal regulations to internal policies. Regulatory compliance is important for the safety of individual actors as well as the overall business environment. However, complexity derives from not only the contents of the regulations but also their interdependencies. As such, the verification of whether actors are able to comply with the combined regulations cannot be done by checking each regulation separately. To these ends, we introduce a normative structure Norm Nets (NNs) for modeling sets of interrelated regulations and setting a basis for compliance checking of organizational interactions against interrelated regulations. NNs support a modular design by providing the constructs to represent regulations and the relationships between them. Additionally, we propose a computational mechanism to reason about regulatory compliance by mapping NNs to Colored Petri Nets (CPNs). We show that compliance checking of both individual actors’ behavior and the collective behavior of the business environment can be achieved automatically using state space analysis techniques of CPNs. The approach is illustrated with a case study from the domain of international trade.
Visual field differences and the recognition of alpha-numeric material

Abstract Ss were required to identify and localize letters and digits from displays presented, at brief exposures, (a) to the left of a central fixation point, (b) to the right of fixation, (c) to the left and right of fixation. No differences were obsereved with respect to visual fields in identification scores, but a significant interaction between visual field and presentation condition was found in localization scores. The implications of these findings are discussed.
Environmental Belief Systems in Western Europe

For most parts of the 20th century, class and religious predispositions guided individuals' perceptions of the political space in Western Europe. Recently, however, analysts have noted the weakening of class and religious cleavages. Moreover, new social movements emerged in Western Europe, despite the inapplicability of traditional class and partisan cues to ecological issues. In light of the presumed lack of sophistication of mass publics, these developments raise the following question. What mental structures, if any, do individuals employ in evaluating competing Old and New Politics issues? In an attempt to answer the question, we analyze citizens' environmental belief systems in four West European countries. We find that environmental belief systems are substantially constrained by general political predispositions in Germany and the Netherlands. In contrast, environmental attitudes are significantly less constrained in France and Great Britain. These crossnational variations in belief systems constraint are attributed to varying activity levels of environmental elites. The implications of these findings for the sources of belief systems constraint and for the sophistication of mass beliefs are assessed.
Effect of Cadence Regulation on Muscle Activation Patterns During Robot-Assisted Gait: A Dynamic Simulation Study

Cadence or stride frequency is an important parameter being controlled in gait training of neurologically impaired subjects. The aim of this study was to examine the effects of cadence variation on muscle activation patterns during robot-assisted unimpaired gait using dynamic simulations. A 2-D musculoskeletal model of human gait was developed considering eight major muscle groups along with an existing ground contact force model. A 2-D model of a robotic orthosis was also developed that provides actuation to the hip, knee, and ankle joints in the sagittal plane to guide subject's limbs on reference trajectories. A custom inverse dynamics algorithm was used along with a quadratic minimization algorithm to obtain a feasible set of muscle activation patterns. Predicted patterns of muscle activations during slow, natural, and fast cadence were compared and the mean muscle activations were found to be increasing with an increase in cadence. The proposed dynamic simulation provides important insight into the muscle activation variations with change in cadence during robot-assisted gait and provides the basis for investigating the influence of cadence regulation on neuromuscular parameters of interest during robot-assisted gait.