Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges of Differentially Private Release of Data Under an Open-world Assumption

Since its introduction a decade ago, differential privacy has been deployed and adapted in different application scenarios due to its rigorous protection of individuals' privacy regardless of the adversary's background knowledge. An urgent open research issue is how to query/release time evolving datasets in a differentially private manner. Most of the proposed solutions in this area focus on releasing private counters or histograms, which involve low sensitivity, and the main focus of these solutions is minimizing the amount of noise and the utility loss throughout the process. In this paper we consider the case of releasing private numerical values with unbounded sensitivity in a dataset that grows over time. While providing utility bounds for such case is of particular interest, we show that straightforward application of current mechanisms cannot guarantee (differential) privacy for individuals under an open-world assumption where data is continuously being updated, especially if the dataset is updated by an outlier.
Force and Contact Location Shading Methods for Use Within Two- and Three-Dimensional Polygonal Environments

Current state-of-the-art haptic interfaces only provide kinesthetic (force) feedback, yet studies have shown that providing tactile feedback in concert with kinesthetic information can dramatically improve a person's ability to dexterously interact with and explore virtual environments. In this research, tactile feedback was provided by a device, called a contact location display (CLD), which is capable of rendering the center of contact to a user. The chief goal of the present work was to develop algorithms that allow the CLD to be used with polygonal geometric models, and to do this without the resulting contact location feedback being overwhelmed by the perception of polygonal edges and vertices. Two haptic shading algorithms were developed to address this issue and successfully extend the use of the CLD to 2D and 3D polygonal environments. Two experiments were run to evaluate these haptic shading algorithms. The first measured perception thresholds for rendering faceted objects as smooth objects. It was found that the addition of contact location feedback significantly increased user sensitivity to edges and that the use of shading algorithms was able to significantly reduce the number of polygons needed for objects to feel smooth. The second experiment explored the CLD device's ability to facilitate exploration and shape recognition within a 3D environment. While this study provided a validation of our 3D algorithm, as people were able to identify the rendered objects with reasonable accuracy, this study underscored the need for improvements in the CLD device design in order to be effectively used in general 3D environments.
Three Biomarkers Identified from Serum Proteomic Analysis for the Detection of Early Stage Ovarian Cancer

Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center case-control study, serum proteomic expressions were analyzed on 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. Data from patients with early stage ovarian cancer and healthy women at two centers were analyzed independently and the results cross-validated to discover potential biomarkers. The results were validated using the samples from two of the remaining centers. After protein identification, biomarkers for which an immunoassay was available were tested on samples from the fifth center, which included 41 healthy women, 41 patients with ovarian cancer, and 20 each with breast, colon, and prostate cancers. Three biomarkers were identified as follows: (a) apolipoprotein A1 (down-regulated in cancer); (b) a truncated form of transthyretin (down-regulated); and (c) a cleavage fragment of inter-α-trypsin inhibitor heavy chain H4 (up-regulated). In independent validation to detect early stage invasive epithelial ovarian cancer from healthy controls, the sensitivity of a multivariate model combining the three biomarkers and CA125 [74% (95% CI, 52–90%)] was higher than that of CA125 alone [65% (95% CI, 43–84%)] at a matched specificity of 97% (95% CI, 89–100%). When compared at a fixed sensitivity of 83% (95% CI, 61–95%), the specificity of the model [94% (95% CI, 85–98%)] was significantly better than that of CA125 alone [52% (95% CI, 39–65%)]. These biomarkers demonstrated the potential to improve the detection of early stage ovarian cancer.
Information Cascades and Observational Learning

An information cascade occurs when it is optimal for an individual, having observed the actions and possibly payoffs of those ahead of him, to take the same action regardless of his own information. When there are informational cascades, society may reap only a modest fraction of the potential gains from aggregating the diverse information of many individuals. As a result, information cascades can help explain some otherwise puzzling aspects of human and animal behavior. For example, why do individuals tend to converge on similar behavior? Why is mass behavior prone to error and fads? We suggest that the theory of observational learning, and particularly of information cascades, has much to offer economics and other social sciences.
A novel approach to assess diagnostic test and observer agreement for ordinal data

Statistical evaluation of medical diagnostic tests traditionally focuses on the cases when the disease classification is of two states (healthy vs. diseased). The two-state disease classification results from a binary gold standard. However, when the gold standard tests are ordinal, we have a multi-state disease classification system. There is a lack of suitable statistical methods to evaluate diagnostic test performance when the disease classification is more than two states, especially when the investigational test is also ordinal. This manuscript develops a novel method to assess the performance of ordinal tests when the gold standard is also ordinal. We propose two conditional probability-based indices to evaluate test performance which are averages of sensitivities and specificities at different cut-off points. Furthermore, the ratio and average of the two new indices are used to measure observer agreement when the data are ordinal. An estimating procedure is presented and simulation studies are used to investigate the small sample behavior of these indices. We illustrate our method via two real data examples.
Power quality of smart grids with Plug-in Electric Vehicles considering battery charging profile

The impact of different battery charging rates of Plug-in Electric Vehicles (PEVs) on the power quality of smart grid distribution systems is studied in this paper. PEV battery chargers are high power nonlinear devices that can generate significant amount of current harmonics. PEVs will be an integral component to the operation of smart grids and therefore their power quality impacts must be thoroughly analyzed. Based on decoupled harmonic load flow analysis, different PEV charging scenarios (e.g., time zone scheduling, charging rate and penetration level) are tested for a typical large distribution network topology. The impacts of PEV charge rate on voltage profile, fundamental and harmonic losses, transformer loading and total harmonic distortions are demonstrated.
Toward a Theory of Situation Awareness in Dynamic Systems

This paper presents a theoretical model of situation awareness based on its role in dynamic human decision making in a variety of domains. Situation awareness is presented as a predominant concern in system operation, based on a descriptive view of decision making. The relationship between situation awareness and numerous individual and environmental factors is explored. Among these factors, attention and working memory are presented as critical factors limiting operators from acquiring and interpreting information from the environment to form situation awareness, and mental models and goal-directed behavior are hypothesized as important mechanisms for overcoming these limits. The impact of design features, workload, stress, system complexity, and automation on operator situation awareness is addressed, and a taxonomy of errors in situation awareness is introduced, based on the model presented. The model is used to generate design implications for enhancing operator situation awareness and future directions for situation awareness research.
Image guided orthopaedic surgery design and analysis

Within the next few years it is envisaged that a number of computer assisted surgery products will become available. For many surgical procedures, outcome of surgery,, will rely on the accuracy and repeatability with which a computer assisted surgical toolperforms its task. This paper presents a Computer Assisted Orthopaedic System (CAOS) which takes an image guided approach to planning and implementing a trajectory, to assist an orthopaedic surgeon. Accurate delivery of this trajectory is achieved via an intelligent guide. This paper details the design issues and identifies the registration and calibration techniques used by the CAOS intelligent guide. The paper also enumerates, and where possible quantifies, thefactors that influence the accuracy performance of the system. Accuracy trees are used to show the root source of inaccuracies and how they propagate and combine in a system.
A new theory of MHC evolution: beyond selection on the immune genes

The major histocompatibility complex (MHC) is a dense region of immune genes with high levels of polymorphism, which are arranged in haplotype blocks. Traditional models of balancing selection (i.e. overdominance and negative frequency dependence) were developed to study the population genetics of single genes. However, the MHC is a multigene family surrounded by linked (non-neutral) polymorphisms, and not all of its features are well explained by these models. For example, (i) the high levels of polymorphism in small populations, (ii) the unexpectedly large genetic differentiation between populations, (iii) the shape of the allelic genealogy associated with trans-species evolution, and (iv) the close associations between particular MHC (human leucocyte antigen, HLA) haplotypes and the approximately 100 pathologies in humans. Here, I propose a new model of MHC evolution named Associative Balancing Complex evolution that can explain these phenomena. The model proposes that recessive deleterious mutations accumulate as a ‘sheltered load’ nearby MHC genes. These mutations can accumulate because (i) they are rarely expressed as homozygotes given the high MHC gene diversity and (ii) purifying selection is inefficient with low recombination rates (cf. Muller's ratchet). Once fixed, these mutations add to balancing selection and further reinforce linkage through epistatic selection against recombinants.
A semi-Markov decision process based dynamic power management for mobile devices

Power management for mobile devices, such as smartphone and tablet, are more important than ever because the growth of battery density doesn't satisfy the increasing demand for user experience with various applications. However, existing approaches have more or less drawbacks: (1) focusing on certain sub-system and neglecting global optimization, (2) having a great burden on computation or data collection, (3) the risk of exposing user's privacy information. In this paper, we present a semi-Markov decision process (SMDP) based power management solution that balances user experience and power consumption. We choose GPS sampling rate and LCD brightness as control variables. This approach has less state number and needs less computation time. The simulation results show that the proposed solution can prolong usage time for about 53% and increase total experience by about 51% in comparison with the general fixed policy.
Nutrition and health status of school children in urban area of Ahmedabad, India: Comparison with Indian Council of Medical Research and body mass index standards

Background: Identifying the commonly prevailing health and nutritional disorders in school going children is essential to initiate appropriate public health measures. Materials and Methods: A cross-sectional prospective study was designed to conduct a detail physical health assessment of children studying in class 1-8 (age- 5-13 years) of 31 schools of Ahmedabad city, India between December 2011 and February 2012. Under the school health program of state government, medical history, height, weight and general physical examination findings, including dental and ophthalmic examination were recorded by qualified medical practitioners. Children with abnormal results were further investigated and treated by the subject experts. Result: Total 28,256 children were screened (boys-15,087 and girls-13,169). Mean weight and height of the children were 27.04 kg and 128.81 cm, respectively. Analysis of nutritional status of the cohort population as compared to body mass index standards revealed that 8319 (29.44%) children were underweight while only 221 (0.78%) children were either overweight or obese. The subgroup analysis of basic nutrition indices in children revealed prevalence of significant malnutrition (based on Indian Council of Medical Research standards) in children below 10 years of age. Commonly prevailing health disorders included worm infestation (42%), upper respiratory tract infection (36.39%), anemia (30.99%) dental caries (25.19%) and refractory errors (10.2%). Conclusions: Malnutrition and related health disorders are commonly prevailing childhood diseases in the urban community and can effectively be addressed by appropriate public health program.
Personality Differences Associated with Smoking Experimentation Among Adolescents with and without Comorbid Symptoms of ADHD

This study evaluated differences in adolescent personality (novelty seeking, harm avoidance, and reward dependence), lifetime cigarette smoking, and symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD) among 1051 youths enrolled in several public high schools in middle Atlantic towns in the United States in 2000 and 2001. Psychological and behavioral data were obtained via self-report on the Temperament and Character Inventory (personality), standard epidemiological survey items (smoking), and the Current Symptoms Scale (ADHD). The results indicated that adolescent “ever smokers” with high-normal symptoms of ADHD had the highest novelty seeking scores compared to all other study groups. These data highlight the greater “vulnerability” to smoking that is associated with novelty seeking and symptoms of inattention and hyperactivity. To the extent that novelty seeking and ADHD share cognitive and/or behavioral elements that may negatively impact upon youths’ ability to attend to tobacco control communications, additional research on ways to adjust the delivery and content of smoking prevention and intervention program messages to meet the needs of these adolescents is warranted.
Early Childhood Caries Is Associated with Genetic Variants in Enamel Formation and Immune Response Genes

Early childhood caries (ECC) is a chronic, infectious disease that affects the primary dentition of young children. It is the result of an imbalance of risk factors and protective factors that influence the disease. The aim of this study was to assess genetic and environmental factors that may contribute to ECC. Two hundred and fifty-nine unrelated children were evaluated using a cross-sectional design. Data on oral habits were obtained through a questionnaire, and caries experience data were collected by clinical examination. Twenty-three markers in 10 genes were studied. Genotyping of the selected polymorphisms was carried out by real-time PCR. Regression analyses were performed comparing individuals with and without caries experience. Of 259 subjects, 123 were caries free. The genotype TT in ALOX15 (rs7217186) was a risk factor for ECC, whereas the genotypes GG in ENAM (rs1264848), AG and GG in KLK4 (rs198968), CT in LTF (rs4547741), and GG in TUFT1 (rs3790506) were protective for EEC. In conclusion, environmental factors and gene interactions can act as protective or risk factors for ECC. These factors together contribute to the presence and severity of the disease.
World Englishes and Culture Wars

Part I. World Englishes Today: 1. The agony and ecstasy 2. The second diaspora 3. Culture wars 4. Standards and codification 5. The power and politics Part II. Context and Creativity: 6. The speaking tree 7. Creativity and literary canons Part III. Past and Prejudice: 8. Liberation linguistics 9. Sacred linguistic cows 10. The paradigms of marginalization Part IV. Ethical Issues and the ELT Empire: 11. Applying linguistics 12. Leaking paradigms Part V. World Englishes and the Classroom: 13. Mythology in teaching Part VI. Research Areas and Resources: 14. Research resources.
Redefining Retention: Recovery from the Patient's Perspective

Abstract This study examines the process of discharge and treatment reentry for six participants who entered treatment voluntarily but were administratively discharged from methadone treatment programs. The participants completed semistructured interviews at treatment entry and at four, eight and 12 months post-treatment entry. Grounded theory methodology was used to examine the phenomenon of treatment reentry from the perspective of the patients, who often viewed their recovery as an accumulation of positive changes. Differences in terms of the patients' goals and motivations for seeking treatment from those of the treatment programs, combined with difficulties encountered during the treatment process eventually led to discharge. However, these patients were then able to navigate their way through the treatment system in different ways in order to remain in treatment. The authors conclude that failure to abide by treatment clinic rules do not necessary constitute “treatment failure” from the perspective of patients, who often wish to remain in treatment even if it is not progressing optimally from the program's perspective. As a result, the recovery process can be more fragmented and is often characterized by a series of cyclical treatment episodes rather than continuous time in treatment, thereby impeding their progress towards recovery.
X-LiSA: Cross-lingual Semantic Annotation

The ever-increasing quantities of structured knowledge on the Web and the impending need of multilinguality and cross-linguality for information access pose new challenges but at the same time open up new opportunities for knowledge extraction research. In this regard, cross-lingual semantic annotation has emerged as a topic of major interest and it is essential to build tools that can link words and phrases in unstructured text in one language to resources in structured knowledge bases in any other language. In this paper, we demonstrate X-LiSA, an infrastructure for cross-lingual semantic annotation, which supports both service-oriented and user-oriented interfaces for annotating text documents and web pages in different languages using resources from Wikipedia and Linked Open Data (LOD).
Dialogical mindfulness in supervision role-play

Aims: This exploratory pilot study investigated Mindfulness-based Role-play (MBRP) supervision to find out how therapists would experience the approach, and to what extent they would find it useful, particularly in relation to empathy toward clients. Method: Thirteen therapists participated in a workshop, introducing mindfulness and MBRP supervision, and subsequently had one individual MBRP supervision session. Data collection and analysis: Qualitative data were collected by means of semi-structured interviews and analysed with regard to participants' supervision experiences by means of a modified version of the Consensual Qualitative Research method. Findings: Participants predominantly had positive emotional and cognitive responses to their supervision experiences. The main supervision outcomes were empathy with the client's emotional experience, enhanced awareness of functioning as a therapist, and thoughts about how to proceed in therapy. A subset of participants also reported observed effects in therapy with clients. Conclusions: Even taking into account the methodological limitations of the study, these findings are promising and suggest that further research into the MBRP supervision approach is warranted.
Predicting protein structural class with Ensemble of Flexible Neural Tree

The protein structural class plays an important role in protein science. In this paper, a new method for predicting protein structural class based Flexible Neural Tree Ensemble (FNTE) is introduced. The structure of Flexible Neural Tree (FNT) is developed by Probabilistic Incremental Program Evolution (PIPE) and the parameters are optimized by Particle Swarm Optimization (PSO) algorithm. The one thousand six hundred and seventy three protein sequence (25PDB) is used as the dataset. The experiment data is validated by tenfold cross validation. The experiment result shows our method can improve the predictive accuracy rate.
A cellular coevolutionary algorithm for image segmentation

Clustering is inherently a difficult problem, both with respect to the definition of adequate models as well as to the optimization of the models. We present a model for the cluster problem that does not need knowledge about the number of clusters a priori. This property is among others useful in the image segmentation domain, which we especially address. Further, we propose a cellular coevolutionary algorithm for the optimization of the model. Within this scheme multiple agents are placed in a regular two-dimensional (2-D) grid representing the image, which imposes neighboring relations on them. The agents cooperatively consider pixel migration from one agent to the other in order to improve the homogeneity of the ensemble of the image regions they represent. If the union of the regions of neighboring agents is homogeneous then the agents form alliances. On the other hand, if an agent discovers a deviant subject, it isolates the subject. In the experiments we show the effectiveness of the proposed method and compare it to other segmentation algorithms. The efficiency can easily be improved by exploiting the intrinsic parallelism of the proposed method.
High Density Lipoprotein Cholesterol, Total Cholesterol Screening, and Myocardial Infarction: The Framingham Study

The relation between high density lipoprotein cholesterol (HDL-C) and the development of myocardlal Infarction was examined In 2425 subjects, aged 50 to 79 years, who were enrolled In the Framingham Study from 1969 to 1971. After 12 years of follow-up, men in the bottom three quartiles of HDL-C (<52 mg/dl) experienced a 60% to 70% excess of myocardlal Infarction as compared to men whose HDL-C levels were higher (p<0.05). The effect of HDL-C was especially strong In women. In separate comparisons to the 4th quartlle of HDL-C (> 67 mg/dl), the risk of myocardial Infarction Increased from a fourfold excess In the adjacent 3rd quartlle (56 to 66 mg/dl, p<0.01) to a nearly sixfold excess In the 1st quartile (<46 mg/dl, p < 0.001). These results persisted after adjusting for age and other risk factors. In addition, a significant effect of HDL-C remained In subjects who had the lowest concentrations of total cholesterol (=s 192 mg/dl In men and 211 mg/dl In women) In which 29% had levels of HDL-C (s 36 mg/dl In men and 46 mg/dl In women) that were associated with a marked elevation In the Incidence of myocardlal Infarction. We conclude that screening for total cholesterol alone In men and women aged 50 and older may not adequately Identify the coronary candidate. In addition, selective screening of HDL-C only for Individuals with high concentrations of total cholesterol can leave the false Impression that low total cholesterol Is uniformly associated with a healthy risk profile.