Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Personality Organization as Assessed by Theory-Driven Profiles of the Dutch Short Form of the MMPI and Self-Reported Features of Personality Organization

In this study, we investigated the relationships between features of personality organization (PO) as assessed by theory driven profiles of the Dutch Short Form of the MMPI (DSFM; Luteijn & Kok, 1985) and 2 self-report measures of personality pathology, that is, the Dutch Inventory of Personality Organization (Berghuis, Kamphuis, Boedijn, & Verheul, 2009) and the Dutch Schizotypy Personality Questionnaire–Revised (Vollema & Hoijtink, 2000), in a sample of 190 outpatient psychiatric patients. Results showed that the single scales of all 3 measures segregated into 2 theoretically expected and meaningful dimensions, that is, a dimension assessing severity of personality pathology and an introversion/extraversion dimension. Theory-driven combinations of single DSFM subscales as a measure of level of PO distinguished characteristics of patients at various levels of PO in theoretically predicted ways. Results also suggest that structural personality pathology may not be fully captured by self-report measures.
Learning to detect and combine the features of an object

To recognize an object, it is widely supposed that we first detect and then combine its features. Familiar objects are recognized effortlessly, but unfamiliar objects—like new faces or foreign-language letters—are hard to distinguish and must be learned through practice. Here, we describe a method that separates detection and combination and reveals how each improves as the observer learns. We dissociate the steps by two independent manipulations: For each step, we do or do not provide a bionic crutch that performs it optimally. Thus, the two steps may be performed solely by the human, solely by the crutches, or cooperatively, when the human takes one step and a crutch takes the other. The crutches reveal a double dissociation between detecting and combining. Relative to the two-step ideal, the human observer’s overall efficiency for unconstrained identification equals the product of the efficiencies with which the human performs the steps separately. The two-step strategy is inefficient: Constraining the ideal to take two steps roughly halves its identification efficiency. In contrast, we find that humans constrained to take two steps perform just as well as when unconstrained, which suggests that they normally take two steps. Measuring threshold contrast (the faintness of a barely identifiable letter) as it improves with practice, we find that detection is inefficient and learned slowly. Combining is learned at a rate that is 4× higher and, after 1,000 trials, 7× more efficient. This difference explains much of the diversity of rates reported in perceptual learning studies, including effects of complexity and familiarity.
A low overhead hardware technique for software integrity and confidentiality

Software integrity and confidentiality play a central role in making embedded computer systems resilient to various malicious actions, such as software attacks; probing and tampering with buses, memory, and I/O devices; and reverse engineering. In this paper we describe an efficient hardware mechanism that protects software integrity and guarantees software confidentiality. To provide software integrity, each instruction block is signed during program installation with a cryptographically secure signature. The signatures embedded in the code are verified during program execution. Software confidentiality is provided by encrypting instruction blocks. To achieve low performance overhead, the proposed mechanism combines several architectural enhancements: a variation of one-time-pad encryption, parallelizable signatures, and conditional execution of unverified instructions. A relatively high memory overhead due to embedded signatures can be reduced by protecting multiple instruction blocks with one signature, with minimal effects on complexity and performance overhead.
The construct validity of session RPE during an intensive camp in young male Karate athletes.

BACKGROUND the aim of this study was to assess the validity of the session rating of perceived exertion (RPE) method and two objective HR-based methods for quantifying karate's training load (TL) in young Karatekas. METHODS eleven athletes (age 12.50±1.84 years) participated in this study. The training period/camp was performed on 5 consecutive days with two training session (s) per-day (d). Construct validity of RPE method in young Karate athletes, was studied by correlation analysis between RPE session's training load and both Edwards and Banister's training impulse score' method. RESULTS significant relationship was found between inter-day (n-11 × d-5 × s-2 = 110) sessions RPE and Edwards (r values from 0.84 to 0.92 p < 0.001) and Banister's (r values from 0.84 to 0.97 p < 0.001), respectively. CONCLUSION this study showed that session-RPE can be considered a valid method for quantifying karate's training load in young karate athletes.
D-term strings

We study the embedding of cosmic strings, related to the Abrikosov-Nielsen-Olesen vortex solution, into d = 4, N = 1 supergravity. We find that the local cosmic string solution which saturates the BPS bound of supergravity with D-term potential for the Higgs field and with constant Fayet–Iliopoulos term, has 1/2 of supersymmetry unbroken. We observe an interesting relation between the gravitino supersymmetry transformation, positive energy condition and the deficit angle of the cosmic string. We argue that the string solutions with magnetic flux with F-term potential cannot be supersymmetric, which leads us to a conjecture that D1-strings (wrapped D1+q-branes) of string theory in the effective 4d supergravity are described by the D-term strings that we study in this paper. We give various consistency checks of this conjecture, and show that it highlights some generic properties of non-BPS string theory backgrounds, such as brane-anti-brane systems. Supersymmetry breaking by such systems can be viewed as FI D-term breaking, which implies, under certain conditions, the presence of gauged R-symmetry on such backgrounds. The D-term nature of the brane-anti-brane energy can also provide information on the superpotential for the tachyon, which Higgses the R-symmetry. In this picture, the inter-brane force can be viewed as a result of the world-volume gauge coupling renormalization by the open string loops.
A Symposium On Matthew B. Crawford's Shop Class as Soul Craft: an Inquiry Into the Value of Work

Matthew Crawford owns a ‘‘speed shop,’’ where he customizes and repairs Honda and other imported motorcycles. He also is a fellow at the Institute for Advanced Studies in Culture at the University of Virginia (he has a PhD in philosophy from Chicago). His book is an extended argument about why being a motorcycle mechanic is more ennobling, meaningful, and ethical than being an academic. I presume that it was written at the University of Virginia and not at the speed shop, but I will bracket that paradox (one of many in this strange little book) and concentrate instead on the larger question it asks: what does a ‘‘good’’ job look like? Good jobs pay well and are invulnerable to outsourcing—characteristics shared by many of the skilled trades. Really good jobs also inspire pride. The motorcycle mechanic develops this pride because the work demands manual competence, practical judgment, and creativity. Objective standards determine the quality of the work. At the end of the day, the motorcycle is fixed or it remains broken, a fact that no amount of abstract theory can alter. This constant vulnerability to public failure refines the worker’s skills and builds moral character. It also promotes social solidarity between the worker and customer, and among workers themselves, who can appreciate the expert craftsmanship in a successful repair. The worker also feels pride when serving higher ideals, in this case, the aesthetics of metal and the spiritual transcendence achieved through high speed racing. In contrast, academics don’t do anything. We engage in abstract theory with no objective standards or physical world to restrain us. We may experience moments of selfesteem, but this is a weak substitute for pride. With no practical know-how, we become dependent, passive, and narcissistic. Our jobs are not inherently meaningful, so we look forward to vacations and other rare occasions when we can reconnect with our humanity and catch glimpses of some higher purpose in life. These are challenging claims to refute since I am an academic and anything I write is likely to sound defensive. (Granted, Crawford doesn’t criticize all academics—Einstein stands out as an exception, as do the members of his own dissertation committee—but I am not in that ‘‘star chamber.’’) So I will simply concede the point. I do not know how to fix anything. I do not teach marketable skills. I am a knowledge worker who is dependent on others to judge my success. I am paid to Shop Class as Soulcraft: An Inquiry into the Value of Work, by Matthew B. Crawford. New York, NY: Penguin Books, 2009. 246pp. $25.95 cloth. ISBN: 9781594202230.
Adaptive Web Accessibility Metrics

1. MOTIVATION Web Accessibility metrics aim at measuring in a precise (often numeric) way the conformance of a given web page with respect to a set of accessibility guidelines. Metrics rely on traditional accessibility guidelines such as WCAG or Section 508, targeting all type of users. Normally, for a more precise assessment that considers specific user groups (blind, deaf, elderly, physically impaired, etc.) only those guidelines that target a determined user group are chosen. This is a first step towards specialization of accessibility metrics; but such a direction can be pursued even more. The following scenarios call for the application of adaptive accessibility metrics:
OASIS : Creating Smart Objects with Dynamic Digital Behaviors

INTRODUCTION Our daily environment is full of physical objects that are unaware of and incapable of engaging with the digital world. These everyday physical objects lack the benefits of being digital, such as access to vast stores of information, complex interactive behaviors, and rich multimedia experiences. Although barcodes, RFID tags, and processors are being built into an increasing percentage of the objects that surround us, there will always be a large class of objects that it is either not possible or not economical to augment or retrofit with direct access to digital information.
The impact of large flows in Content Centric Networks

This paper investigates the impact of large flows in Content Centric Networks (CCN). In CCN, routers have caches, and store all the data after forwarding. If large flows temporarily occupy a content cache, they may evict popular chunks from the cache, and it results in low cache hit ratio. We mathematically analyzed the amount of occupancy of a large flow in a cache, and realized that a few large flows can constitute a significant portion of a cache. Our simulation results showed that small flows experience cache hit ratio degradation as the number of large flows increases. Finally, we present that limiting the occupancy of large flows in a cache can effectively improve the cache hit ratios for small flows.
A noise robust i-vector extractor using vector taylor series for speaker recognition

We propose a novel approach for noise-robust speaker recognition, where the model of distortions caused by additive and convolutive noises is integrated into the i-vector extraction framework. The model is based on a vector taylor series (VTS) approximation widely successful in noise robust speech recognition. The model allows for extracting “cleaned-up” i-vectors which can be used in a standard i-vector back end. We evaluate the proposed framework on the PRISM corpus, a NIST-SRE like corpus, where noisy conditions were created by artificially adding babble noises to clean speech segments. Results show that using VTS i-vectors present significant improvements in all noisy conditions compared to a state-of-the-art baseline speaker recognition. More importantly, the proposed framework is robust to noise, as improvements are maintained when the system is trained on clean data.
An efficient and numerically stable method for computing interval availability distribution bounds

The paper develops a method, called bounding regenerative transformation, for the computation with numerical stability and well-controlled error of bounds for the interval availability distribution of systems modeled by finite (homogeneous) continuous-time Markov chain models with a particular structure. The method requires the selection of a regenerative state and is targeted at a class of models, class C'_1, with a “natural” selection for the regenerative state. For class C'_1 models, bounds tightness can be traded-off with computational cost through a control parameter D_C, with the option D_C = 1 yielding the smallest computational cost. For large class C'_1 models and the selection D_C = 1, the method will often have a small computational cost relative to the model size and, with additional conditions, seems to yield tight bounds for any time interval or not small time intervals, depending on the initial probability distribution of the model. Class C'_1 models with those additional conditions include both exact and bounding failure/repair models of coherent fault-tolerant systems with exponential failure and repair time distributions and repair in every state with failed components with failure rates much smaller than repair rates.
Racial/ethnic disparities in alcohol-related problems: differences by gender and level of heavy drinking.

BACKGROUND While prior studies have reported racial/ethnic disparities in alcohol-related problems at a given level of heavy drinking (HD), particularly lower levels, it is unclear whether these occur in both genders and are an artifact of racial/ethnic differences in drink alcohol content. Such information is important to understanding disparities and developing specific, targeted interventions. This study addresses these questions and examines disparities in specific types of alcohol problems across racial-gender groups. METHODS Using 2005 and 2010 National Alcohol Survey data (N = 7,249 current drinkers), gender-stratified regression analyses were conducted to assess black-white and Hispanic-white disparities in alcohol dependence and negative drinking consequences at equivalent levels of HD. HD was measured using a gender-specific, composite drinking-patterns variable derived through factor analysis. Analyses were replicated using adjusted-alcohol consumption variables that account for group differences in drink alcohol content based on race/ethnicity, gender, age, and alcoholic beverage. RESULTS Compared with white men, black and Hispanic men had higher rates of injuries/accidents/health and social consequences, and marginally greater work/legal consequences (p < 0.10). Hispanic women had marginally higher rates of social consequences. In main effects models controlling for demographics, light drinking and HD, only black women and men had greater odds of alcohol-related problems relative to whites. Interaction models indicated that compared with whites, black women had greater odds of dependence at all levels of HD, while both black and Hispanic men had elevated risk of alcohol problems only at lower levels of HD. Drink alcohol content adjustments did not significantly alter findings for either gender. CONCLUSIONS This study highlights the gender-specific nature of racial/ethnic disparities. Interventions focused on reducing HD might not address disparities in alcohol-related problems that exist at low levels of HD. Future research should consider the potential role of environmental and genetic factors in these disparities.
Gestational Diabetes Mellitus and Macrosomia: A Literature Review

Background: Fetal macrosomia, defined as a birth weight ≥4,000 g, may affect 12% of newborns of normal women and 15-45% of newborns of women with gestational diabetes mellitus (GDM). The increased risk of macrosomia in GDM is mainly due to the increased insulin resistance of the mother. In GDM, a higher amount of blood glucose passes through the placenta into the fetal circulation. As a result, extra glucose in the fetus is stored as body fat causing macrosomia, which is also called ‘large for gestational age'. This paper reviews studies that explored the impact of GDM and fetal macrosomia as well as macrosomia-related complications on birth outcomes and offers an evaluation of maternal and fetal health. Summary: Fetal macrosomia is a common adverse infant outcome of GDM if unrecognized and untreated in time. For the infant, macrosomia increases the risk of shoulder dystocia, clavicle fractures and brachial plexus injury and increases the rate of admissions to the neonatal intensive care unit. For the mother, the risks associated with macrosomia are cesarean delivery, postpartum hemorrhage and vaginal lacerations. Infants of women with GDM are at an increased risk of becoming overweight or obese at a young age (during adolescence) and are more likely to develop type II diabetes later in life. Besides, the findings of several studies that epigenetic alterations of different genes of the fetus of a GDM mother in utero could result in the transgenerational transmission of GDM and type II diabetes are of concern.
A new tool for URDAD to Java EE EJB transformations

Following the Object Management Group's (OMG) Model-Driven Architecture (MDA) approach, the semi-formal, service-orientated "Use Case, Responsibility Driven Analysis and Design" (URDAD) method is used by requirements engineers to specify a software system's functional properties in a Platform Independent Model (PIM). PIMs are represented using the URDAD Domain Specific Language (DSL), and thus conform to the URDAD MOF meta model. As a result, they can be transformed into Platform-Specific Models (PSM) for frameworks such as Java Platform Enterprise Edition (JEE) Enterprise Java Beans (EJB). This paper describes the semi-automatic transformation of a URDAD PIM into a EJB PSM, which is the basis for the further generation of EJB program code. For this purpose, a new prototype CASE tool was implemented to facilitate such transformations. The tool was evaluated using a non-trivial example project, with results indicating that it produces the PSM and template code that constitutes the static Java EE EJB structural representation of the example PIM.
Improving Information Retrieval with Textual Analysis: Bayesian Models and Beyond

Information retrieval (IR) is a difficult problem. While many have attempted to model text documents and improve search results by doing so, the most successful text retrieval to date has been developed in an ad-hoc manner. One possible reason for this is that in developing these models very little focus has been placed on the actual properties of text. In this thesis, we discuss a principled Bayesian approach we take to information retrieval, which we base on the standard IR probabilistic model. Not surprisingly, we find this approach to be less successful than traditional ad-hoc retrieval. Using data analysis to highlight the discrepancies between our model and the actual properties of text documents, we hope to arrive at a better model for our corpus, and thus a better information retrieval strategy. Specifically, we believe we will find it is inaccurate to assume that whether a term occurs in a document is independent of whether it has already occurred, and we will suggest a way to improve upon this without adding complexity to the solution. Thesis Supervisor: David Karger Title: Professor of Computer Science
Evidence that periodontal treatment improves biomarkers and CVD outcomes.

AIM The aim of this review was to critically appraise the evidence on the impact of periodontal treatment of cardiovascular diseases (CVDs) biomarkers and outcomes. METHODS A systematic search was performed in Cinhal, Cochrane, Embase and Medline for relevant articles up to July 2012. Duplicate screening and reference hand searching were performed. Data were then summarized and evidence graded in tables. RESULTS The search resulted in: (a) no evidence on the effects of periodontal therapy on subclinical atherosclerosis, serum levels of CD40 ligand, serum amyloid A and monocyte chemoattractant protein-1, (b) limited evidence on the effects of periodontal therapy on arterial blood pressure, leucocyte counts, fibrinogen, tissue necrosis factor-α, sE-selectin, von Willebrand factors, d-dimers, matrix metalloproteinases, oxidative stress and CVD events, and (c) moderate evidence suggesting a negligible effect of periodontal therapy in reducing interleukin-6 and lipids levels, whilst a positive effect in reducing serum C-reactive protein levels and improving endothelial function. CONCLUSIONS Periodontal therapy triggers a short-term inflammatory response followed by (a) a progressive and consistent reduction of systemic inflammation and (b) an improvement in endothelial function. There is however limited evidence that these acute and chronic changes will either increase or reduce CVD burden of individuals suffering from periodontitis in the long term.
Patients with initially unresectable colorectal liver metastases: is there a possibility of cure?

PURPOSE Although oncosurgical strategies have demonstrated increased survival in patients with unresectable colorectal liver metastases (CLM), their potential for cure is still questioned. The aim of this study was to evaluate long-term outcome after combining downsizing chemotherapy and rescue surgery and to define prognostic factors of cure. PATIENTS AND METHODS All patients with initially unresectable CLM who underwent rescue surgery and had a minimum follow-up of 5 years were included. Cure was defined as a disease-free interval > or = 5 years from last hepatic or extrahepatic resection until last follow-up. RESULTS Mean age of 184 patients who underwent resection (April 1988 through July 2002) was 56.9 years. Patients had a mean number of 5.3 metastases (bilobar in 76%), associated to extrahepatic disease in 27%. Surgery was possible after one (74%) or more (26%) lines of chemotherapy. Five- and 10-year overall survival rates were 33% and 27%, respectively. Of 148 patients with a follow-up > or = 5 years, 24 patients (16%) were considered cured (mean follow-up, 118.6 months), six (25%) of whom were considered cured after repeat resection of recurrence. Twelve "cured" patients (50%) had a disease-free interval more than 10 years. Cured patients more often had three or fewer metastases less than 30 mm (P = .03) responding to first-line chemotherapy (P = .05). Multivariate analysis identified maximum size of metastases less than 30 mm at diagnosis, number of metastases at hepatectomy three or fewer, and complete pathologic response as independent predictors of cure. CONCLUSION Cure can be achieved overall in 16% of patients with initially unresectable CLM resected after downsizing chemotherapy. In addition to increased survival, this oncosurgical approach has real potential for disease eradication.
Complexity transitions in evolutionary algorithms: evaluating the impact of the initial population

This paper proposes an evolutionary approach for the composition of solutions in an incremental way. The approach is based on the metaphor of transitions in complexity discussed in the context of evolutionary biology. Partially defined solutions interact and evolve into aggregations until a full solution for the problem at hand is found. The impact of the initial population on the outcome and the dynamics of the process is evaluated using the domain of binary constraint satisfaction problems.