Miracle-dz/UniFAR-FTUs huggingface dataset:
Incremental Validity of Interactive Multimedia Simulations in Two Organizations

Interactive multimedia simulations are conceptually distinct from other simulations commonly used as selection tools, such as assessment centers and situational judgment tests, and represent a potentially cost-effective and job-related candidate assessment tool. This study investigated the predictive validity of these simulations with a combined sample of call center employees from two organizations. Results indicate that customized interactive multimedia simulations demonstrate substantial criterion-related validity and significant incremental validity over other noncognitive measures such as biodata and personality.
Aggregated search: A new information retrieval paradigm

Traditional search engines return ranked lists of search results. It is up to the user to scroll this list, scan within different documents, and assemble information that fulfill his/her information need. Aggregated search represents a new class of approaches where the information is not only retrieved but also assembled. This is the current evolution in Web search, where diverse content (images, videos, etc.) and relational content (similar entities, features) are included in search results. In this survey, we propose a simple analysis framework for aggregated search and an overview of existing work. We start with related work in related domains such as federated search, natural language generation, and question answering. Then we focus on more recent trends, namely cross vertical aggregated search and relational aggregated search, which are already present in current Web search.
Coherent brain oscillations during processes of human sensorimotor learning

Movements in everyday life are often based on external stimuli. It is therefore essential for the human brain to associate external sensory cues with motor commands. The term 'sensorimotor transformation' refers to the process by which such external stimuli are converted into motor commands. This process is crucial to any organism that possesses the ability to interact with the environment. One particular aspect in the broad field of human motor learning is the investigation of learning processes related to sensorimotor transformation. The investigation of these processes during learning of continuous movements is of particular interest, since they require ongoing online transformation processes and closely resemble the requirements of daily life. The focus of this thesis is therefore placed on the neural control and learning of continuously visually and auditorily-guided tracking movements. The main interest is to investigate changes in the cortical networking between motor and parietal regions during motor leaning. Therefore, coherence / phase locking analysis between electroencephalographic signals of motor and parietal brain regions is applied. Coherence / phase locking is a measures of linear / non-linear co-variance between electroencephalographic signals and is used to represent interactions of brain regions. As a new approach in coherence / phase locking analysis, the computations in the present thesis were based on signals of intracerebral model sources. The first experimental study focuses on the acquisition of movements, which are continuously guided by external visual or auditory stimuli, and aims to delineate the learning-related changes in coherence / phase locking between motor and parietal brain regions. It is concluded from the results of this study that coherent oscillations in the alpha frequency range within the fronto-parietal motor network subserve learning of visually and auditorily-guided tracking movements, which require sensorimotor transformations. The study demonstrates the importance of interregional coupling as a neural correlate for successful acquisition and implementation of externally guided behaviour. As a follow-up, the second study investigates how coherence / phase locking between motor and parietal structures changes from an early learning stage to a skilled level of performance. The results show that increasing practice of continuous tracking movements which are continuously controlled by auditory feedback is not accompanied by a decrease in phase locking in the alpha and beta II frequency range between areas involved. These results suggest that the performance of the present task is in close dependence on the sensory stimuli throughout the learning stages. Additionally, during the task …
PET of EGFR Expression with an 18F-Labeled Affibody Molecule

Epidermal growth factor receptor (EGFR) is often overexpressed in a variety of human cancers, and its expression is associated with poor prognosis for many cancer types. However, an accurate technique to noninvasively image EGFR expression in vivo is not available in the clinical setting. In this research, an Affibody analog, anti-EGFR Ac-Cys-ZEGFR:1907, was successfully site-specifically 18F-labeled for PET of EGFR expression. Methods: The prosthetic group N-[2-(4-18F-fluorobenzamido) ethyl] maleimide (18F-FBEM) was conjugated to Ac-Cys-ZEGFR:1907 under mild conditions (pH 7) to produce the probe 18F-FBEM-Cys-ZEGFR:1907. The binding affinity and specificity tests of 18F-FBEM-Cys-ZEGFR:1907 to EGFR were conducted using A431 cancer cells. Small-animal PET and biodistribution studies were conducted on various mice tumor xenograft models with EGFR overexpression (6 types) after injection of approximately 2.0 MBq of 18F-FBEM-Cys-ZEGFR:1907 with or without coinjection of unlabeled Ac-Cys-ZEGFR:1907 for up to 3 h after injection. A correlation study between 18F-FBEM-Cys-ZEGFR:1907 small- animal PET quantification and ex vivo Western blot analysis of tumor EGFR expression was conducted in those 6 types of tumor models. Results: 18F-FBEM-Cys-ZEGFR:1907 binds to EGFR with low nanomolar affinity (37 nM) in A431 cells. 18F-FBEM-Cys-ZEGFR:1907 rapidly accumulated in the tumor and cleared from most of the normal organs except the liver and kidneys at 3 h after injection, allowing excellent tumor–to–normal tissue contrast to be obtained. In the A431 tumor xenograft model, coinjection of the PET probe with 45 μg of Ac-Cys-ZEGFR:1907 was able to improve the tumor uptake (3.9 vs. 8.1 percentage of the injected radioactive dose per gram of tissue, at 3 h after injection) and tumor imaging contrast, whereas coinjection with 500 μg of Ac-Cys-ZEGFR:1907 successfully blocked the tumor uptake significantly (8.1 vs. 1.0 percentage of the injected radioactive dose per gram of tissue, at 3 h after injection, 88% inhibition, P < 0.05). Moderate correlation was found between the tumor tracer uptake at 3 h after injection quantified by PET and EGFR expression levels measured by Western blot assay (P = 0.007, R = 0.59). Conclusion: 18F-FBEM-Cys-ZEGFR:1907 is a novel protein scaffold–based PET probe for imaging EGFR overexpression of tumors, and its ability to differentiate tumors with high and low EGFR expression in vivo holds promise for future clinical translation.
Google, bing and a new perspective on ranking similarity

In this paper, we propose a framework to characterize and compare two search engine results. Typical user-queries are ambiguous and, consequentially, each search engine will compute ranks in different manners, attempting to answer them in the best possible way. Thus, each search engine will have its own bias. Given the importance of the first page results in Web Search Engines, in this paper we propose a framework to assess the information presented in the first page by measuring the information entropy and the correlations between two ranks. Employing the recently proposed Rank-Biased Overlap measure [2] we compare to which extent do Bing and Google rankings in fact differ. We also extend this measure and propose a measure for comparing the information entropy present in two ranks. The proposed measure is based on the correlation of two ranks and the application of Jensen-Shannon's divergence among two document sets. Our methodology starts with 40,000 user queries and crawls the search results for these queries on both search engines. The results allow us to determine the search engines correlations, crawling coverage, information overlap, and information entropy.
Effect of Heat and Heat Acclimatization on Cycling Time Trial Performance and Pacing

ABSTRACT Purpose This study aimed to determine the effects of heat acclimatization on performance and pacing during outdoor cycling time trials (TT, 43.4 km) in the heat. Methods Nine cyclists performed three TT in hot ambient conditions (TTH, approximately 37°C) on the first (TTH-1), sixth (TTH-2), and 14th (TTH-3) days of training in the heat. Data were compared with the average of two TT in cool condition (approximately 8°C) performed before and after heat acclimatization (TTC). Results TTH-1 (77 ± 6 min) was slower (P = 0.001) than TTH-2 (69 ± 5 min), and both were slower (P < 0.01) than TTC and TTH-3 (66 ± 3 and 66 ± 4 min, respectively), without differences between TTC and TTH-3 (P > 0.05). The cyclists initiated the first 20% of all TT at a similar power output, irrespective of climate and acclimatization status; however, during TTH-1, they subsequently had a marked decrease in power output, which was partly attenuated after 6 d of acclimatization and was further reduced after 14 d. HR was higher during the first 20% of TTH-1 than that in the other TT (P < 0.05), but there were no differences between conditions from 30% onward. Final rectal temperature was similar in all TTH (40.2°C ± 0.4°C, P = 1.000) and higher than that in TTC (38.5°C ± 0.6°C, P < 0.001). Conclusions After 2 wk of acclimatization, trained cyclists are capable of completing a prolonged TT in a similar time in the heat compared with cool conditions, whereas in the unacclimatized state, they experienced a marked decrease in power output during the TTH.
Using parallel isosurface extraction in superficial molecular modeling

Protein-protein interactions are strictly correlated to the surface shape because beside a large number of structural amino acids composing the core there are few superficial amino acids that define the functionality. This study concerns the development of a tool that starting from the 3D atomic coordinates of a protein, as retrieved from the protein data bank (PDB), models the macromolecular surface in an implicit way using an approach that is more suitable for this kind of analysis than the parametric one. The marching cubes algorithm is used to process the volumetric description of the protein obtaining a precise representation of the corresponding surface. Because of the large amount of data to consider in studying whole protein families, this algorithm is implemented in parallel on a computer cluster to improve its performance. The parallel version of marching cubes is developed in ASSIST, a high level structured parallel programming system, obtaining a near optimal performance considering computational activities, and acceptable performance including I/O.
Quantitative Study of Open Source Immigration

Open source software is built by teams of volunteers. Each project has a core team of developers who have the authority to commit changes to the repository; this team is the elite core of the project, selected through a meritocratic process from a larger number of people who participate on the mailing list. Understanding the factors that influence the “who, how and when” of this process is critical for the sustainability of FLOSS projects and for outside stakeholders who want to gain entry and succeed. Prior research indicates that certain types of behaviors, such as the duration and intensity of participation on the developer mailing list, and the submission of patches, play a role in immigration. However, this work has largely been qualitative and/or descriptive. We use quantitative hazard rate modeling, which supports the statistical testing of hypotheses concerning the influence of these factors on the rate of immigration. We develop a theory of open source project joining, and use data from Postgres, Python, and the Apache web server to statistically evaluate it using a piecewise-constant proportional hazard rate model. Quantitative modeling reveals variations across the projects in the effects of a participant’s a) duration in a FLOSS community; b) their volume of patch submission; and c) and their social status. These variations can be attributed to differences across the projects in institutional norms for joining, technical complexity of the projects and governance mechanisms.
Managing OO Projects Better

The author reveals that estimation of effort is key to managing OO development projects, then documents a few rules of thumb for doing this. One lesson he's learned from using these rules is that estimates for a whole project are not reliable if estimates for subcomponents are simply added up. As the project size increases, so does the overhead for communication and general interaction. He goes beyond effort metrics and recommends that one collects metrics throughout the project and uses them for continuous revalidation of assumptions and project performance. If one accepts that "what you can't measure, you can't manage", this is good advice.
High-voltage integrated Class-B amplifier for ultrasound transducers

High-voltage linear amplifiers driving transducers for ultrasound imaging enable apodization profiles with high resolution, beams with low harmonic content and instantaneous changes in transmit energy between pulses. In view of an increased level of integration, the availability of a BCD technology, capable of watts level driving at high frequency, encourages investigation of linear amplifiers, the topic of this work. A feedback amplifier with high voltage - high efficiency Class B output stage is proposed. Device parameters vary significantly with signal amplitude making circuit analysis more involved. We propose the use of describing functions to estimate the large-signal frequency response. Analytical results are in good agreement with simulations and provide useful design insights. From measurements, a test-chip in BCD-6 SOI displays 40.9dB gain, 90Vpk-pk output voltage with a minimum 3dB cut-off frequency of 5.5MHz. Quiescent power dissipation is 37mW only.
Effective usage of vector registers in decoupled vector architectures

The paper presents a study of the impact of reducing the vector register size in a decoupled vector architecture. In traditional in-order vector architectures long vector registers have typically been the norm. The authors present data which shows that, even for highly vectorizable codes, only a small fraction of all elements of a long vector register are actually used. They also show that reducing the register size in a traditional vector architecture in an attempt to reduce hardware cost and maximize register utilization results in a severe performance degradation. However they combine the decoupling technique with the vector register reduction and show that the resulting architecture tolerates very well the register size cuts. They simulate a selection of Perfect Club and Specfp92 programs using a trace driven approach and compare the execution time in a conventional vector architecture with a decoupled vector architecture using different registers sizes. Halving the register size and using decoupling provides speedups between 1.04-1.49 over a traditional in-order vector machines. Even reducing the register length to 1/4 the original size (and in some cases, to 1/8) the performance of the decoupled machine is better than a conventional vector model. Moreover they observe that the resulting decoupled machine with short registers tolerates very well long memory latencies.
Identification of critical primitive path delay faults without any path enumeration

It has been previously shown that in order to guarantee the temporal correctness of a circuit, only the primitive path delay fault set needs to be tested. However, as in the case of the traditional and simpler path delay fault model, the number of possible faults can be exponential to the circuit size and, therefore, it is only practical to consider the set of critical faults. This work defines critical primitive path delay faults and presents an exact algorithm to identify them, using zero-suppressed binary decision diagrams and newly introduced operators necessary for handling multiple path delay faults. We report the number of critical primitive path delay faults for various criticality thresholds under the bounded delay model. The results indicate that only a small, but still necessary, number of multiple (primitive) faults, which escape testing under the singly testable fault criterion, must be considered in order to guarantee the timing correctness of the circuit.1
Effectiveness of Psychoanalytic Psychotherapy and Behavioral Therapy Treatment in Children with Attention Deficit Hyperactivity Disorder and Oppositional Defiant Disorder

The study compares the effectiveness of long-term psychoanalytic psychotherapy without medication with behavioral therapy and/or medication treatment. Seventy-three children with attention-deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) participated in a controlled trial. The primary outcome was symptom reduction 38 months after the pre-treatment assessment. Secondary outcomes were significantly lower scores for Conners Parent and Teacher Rating Scale, Child Behavior Checklist and Teacher Report Form scores. Both treatment groups demonstrated significant symptom reduction, with no significant differences in effectiveness between the two groups. Teacher ratings as well as parent ratings showed a significant decline over time on the ADHD index scores, on oppositional behavior and hyperactivity/impulsivity levels and on internalizing and externalizing problem scores. Both groups demonstrated similar main effects of time. There were no significant interactions between group and time. The findings of this study support psychoanalytic psychotherapy without medication as being as effective as behavioral treatment with methylphenidate in symptom reduction and problem reduction on ADHD/ODD related rating scales.
Label-free detection of biomolecular interaction — DNA — Antimicrobial peptide binding

Interest to biosensors employing surface or localized plamons is rapidly growing both in research and clinical application. Plasmon-based sensors offer extremely high sensitivity, only second to the optical detection techniques involving fluorescent labeling, but without the necessity to label the molecule. In particular, surface plasmon resonance (SPR) sensors have been already demonstrated suitable for food-safety control, label-free screening for various disease markers in bodily fluids, as well as for real-time continuous monitoring of drug levels in intensive care environment. We envisage such sensors to be integrated into wireless communication infrastructure for e-health and environmental monitoring applications. One of the important threats in hospital environment is multi-resistant organisms that are not affected by common antibiotics. The growth of multi-resistant infections spurred an interest in Antimicrobial peptides that are active against broad range of infections including bacteria, fungi and viruses and were shown to be capable of treating multi-resistant infection either alone or in combination with the conventional antibiotics. In this paper, we demonstrate an application of plasmon based biosensors to the study of the interaction of Antimicrobial peptide IL4 and DNA. Our results indicate high affinity binding between IL4 and DNA thereby preventing DNA replication and eventually killing the affected cell. We speculate that this is common for a large class of Antimicrobial peptides and can be a key point explaining their broad range of activity against various pathogens.
A Co-Evolutionary Fuzzy System for Real-Time Signal Pre-Processing

By their nature, Real-Time applications impose the conflicting goals of providing a fast algorithm and reducing the rate of error as much as possible. The Remote Terminal Units (RTU) has a real-time system to convert the data from the field into pulses/counts at the converter stage and transmits them to the main processor. In this paper we take advantage of the fuzzy logic inference system, as a preprocessor which is optimized by an evolutionary algorithm in a cooperative co-evolutionary manner. The novelty of the proposed method is that our system will be optimized by a co-evolutionary algorithm and the output would then be implemented as a lookup table suitable for real-time processing. Simulations demonstrate the most significant improvement to reduce the time complexity down to O (1) and enhance the precision simultaneously.
Sorting a Low-Entropy Sequence

We give the first sorting algorithm with bounds in terms of higher-order entropies: let $S$ be a sequence of length $m$ containing $n$ distinct elements and let (H_\ell (S)) be the $\ell$th-order empirical entropy of $S$, with (n^{\ell + 1} \log n \in O (m)); our algorithm sorts $S$ using ((H_\ell (S) + O (1)) m) comparisons.
Institutional Context, Cognitive Resources and Party Attachments Across Democracies

This paper develops and tests arguments about how national-level social and institutional factors shape the propensity of individuals to form attachments to political parties. Our tests employ a two-step estimation procedure that has attractive properties when there is a binary dependent variable in the first stage and when the number of second-level units is relatively small. We find that voters are most likely to form party attachments when group identities are salient and complimentary. We also find that institutions that assist voters in retrospectively evaluating parties—specifically, strong party discipline and few parties in government—increase partisanship. These institutions matter most for those individuals with the fewest cognitive resources, measured here by education.
On Dynamic Flow-Sensitive Floating-Label Systems

Flow-sensitive analysis for information-flow control (IFC) allows data structures to have mutable security labels, i.e., labels that can change over the course of the computation. This feature is often used to boost the permissiveness of the IFC monitor, by rejecting fewer programs, and to reduce the burden of explicit label annotations. However, when added naively, in a purely dynamic setting, mutable labels can expose a high bandwidth covert channel. In this work, we present an extension for LIO-a language-based floating-label system-that safely handles flow-sensitive references. The key insight to safely manipulating the label of a reference is to not only consider the label on the data stored in the reference, i.e., the reference label, but also the label on the reference label itself. Taking this into consideration, we provide an upgrade primitive that can be used to change the label of a reference in a safe manner. To eliminate the burden of determining when a reference should be upgraded, we additionally provide a mechanism for automatic upgrades. Our approach naturally extends to a concurrent setting, not previously considered by dynamic flow-sensitive systems. For both our sequential and concurrent calculi, we prove non-interference by embedding the flow-sensitive system into the flow-insensitive LIO calculus, a surprising result on its own.
A multivariate generalization of Costa’s entropy power inequality

A simple multivariate version of Costapsilas entropy power inequality is proved. In particular, it is shown that if independent white Gaussian noise is added to an arbitrary multivariate signal, the entropy power of the resulting random variable is a multidimensional concave function of the individual variances of the components of the signal. As a side result, we also give an expression for the Hessian matrix of the entropy and entropy power functions with respect to the variances of the signal components, which is an interesting result in its own right.