Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Mental Fatigue Scale and its relation to Cognitive and Emotional Functioning after Traumatic Brain Injury or Stroke

Objective: After traumatic brain injury (TBI) or stroke, long-term mental fatigue may occur with significant impact on work and social interactions. With the intention to measure mental fatigue irrespective of neurological illness, we developed the Mental Fatigue Scale (MFS). The scale incorporates affective, cognitive and sensory symptoms, duration of sleep and daytime variation in symptom severity. In this study, we evaluated the MFS and its relationship to cognitive and emotional functions. Participants: Healthy controls and well-rehabilitated subjects suffering from mental fatigue after mild TBI, TBI or stroke (age 19-69) were included in the study. Results: The results showed MFS to be invariant to age, gender and education. A cutoff score at 10.5 is suggested. Of the cognitive functions measured, information processing speed was found to be a significant predictor for the rating on MFS. We found that a significant effect on depression between controls and brain injured subjects can be a misleading conclusion if the effect of mental fatigue is not considered. Conclusions: We suggest MFS to be linked to mental impairment after brain injury. This study also demonstrated that mental fatigue must be treated as a separate construct and should not be mixed up with depression or anxiety.
Knowledge Sharing and Organizational Learning in the Context of Hospital Infection Prevention

Recently, hospitals that have been successful in preventing infections have labeled their improvement approaches as either the Toyota Production System (TPS) approach or the Positive Deviance (PD) approach. PD has been distinguished from TPS as being a bottom-up approach to improvement, as against top-down. Facilities that have employed both approaches have suggested that PD may be more effective than TPS for infection prevention. This article integrates organizational learning, institutional, and knowledge network theories to develop a theoretical framework for understanding the structure and evolution of effective knowledge-sharing networks in health care organizations, that is, networks most conducive to learning and improvement. Contrary to arguments put forth by hospital success stories, the framework suggests that networks rich in brokerage and hierarchy (ie, top-down, “TPS-like” structures) may be more effective for learning and improvement in health care organizations, compared with a networks rich in density (ie, bottom-up, “PD-like” structures). The theoretical framework and ensuing analysis help identify several gaps in the literature related to organization learning and improvement in the infection prevention context. This, in turn, helps put forth recommendations for health management research and practice.
Alignment of galaxy spins in the vicinity of voids

We provide limits on the alignment of galaxy orientations with the direction to the void center for galaxies lying near the edges of voids. We locate spherical voids in volume limited samples of galaxies from the Sloan Digital Sky Survey using the HB inspired void finder and investigate the orientation of (color selected) spiral galaxies that are nearly edge-on or face-on. In contrast with previous literature, we find no statistical evidence for departure from random orientations. Expressed in terms of the parameter c, introduced by Lee & Pen to describe the strength of such an alignment, we find that c0.11(0.13) at 95% (99.7%) confidence limit within a context of a toy model that assumes a perfectly spherical voids with sharp boundaries.
A Sequence of Outbursts from the Transient X-Ray Pulsar GS 0834–430

GS 0834-430, a 12.3 s accretion-powered pulsar, has been observed in seven outbursts with the BATSE large-area detectors on the Compton Gamma Ray Observatory. The first five outbursts observed by BATSE occurred at intervals of about 107 days, while the final two outbursts were separated by about 140 days. The photon energy spectrum, measured by Earth occultation in the 20-100 keV band, can be fitted by a power law with photon index α ≈ -3.7 or by an exponential spectrum with temperature kT ≈ 15 keV, with some variations within outbursts. The source has a low pulse fraction, ≲0.15 in the 20-50 keV band. We have observed significant temporal and energy-dependent variations in epoch folded pulse profiles. Because the intrinsic torque effects for this system are at least comparable to orbital effects, pulse timing analysis did not produce a unique orbital solution. However, confidence regions for the orbital elements yielded the following 1 σ limits: orbital period Porb = 105.8 ± 0.4 days and eccentricity 0.10 ≲ e ≲ 0.17. GS 0834-430 is most likely a Be/X-ray binary.
Low-complexity Subspace Tracking Based Channel Estimation Method for OFDM Systems In Time-Varying Channels

In this paper, a group of low-complexity subspace tracking based pilot-aided channel estimation methods for orthogonal frequency-division multiplexing (OFDM) systems is studied. These methods are based on a parametric channel model where the channel response is characterized as a collection of sparse propagation paths. Considering the slow variations of the channel correlation matrix's signal subspace, we first translate the estimation of channel parameters into an unconstrained minimization problem. Then, to solve this minimization problem, a novel Kalman-filter based subspace tracking method is proposed, which employs the constant signal subspace to construct state equation and measurement equation. In contrast, other two adaptive filters, LMS and RLS, are applied and evaluated. These three methods constitute a group of low-complexity subsapce tracking schemes. It is shown that the proposed Kalman filter method is able to effectively track the time-varying channels, and outperforms LMS and RLS methods with large Doppler frequency spread.
Small bowel tumor detection for wireless capsule endoscopy images using textural features and support vector machine

Wireless capsule endoscopy (WCE) has been gradually applied in hospitals due to its great advantage that it can directly view the entire small bowel in human body compared with traditional endoscopies and other imaging techniques for gastrointestinal diseases. However, a challenging problem with this new technology is that too many images produced by WCE causes a tough task to doctors, so it is very significant to help and relief the clinicians if we can develop computer based automatic detection system to prescreen the collected large amount of images and identify the images with potential problems. In this paper, we propose a new scheme aimed for small bowel tumor detection of WCE images. This new scheme utilizes texture feature, also a powerful clue used by physicians, to detect tumor images with support vector machine. We put forward a new idea of wavelet based local binary pattern as the textural features to discriminate tumor regions from normal regions, which take advantage of wavelet transform and uniform local binary pattern. With support vector machine as the classifier, three-fold cross validation experiments on our present image data verify that it is promising to employ the proposed texture features to recognize the small bowel tumor regions.
Application of the Multigrid Data Assimilation Scheme to the China Seas ’ Temperature Forecast

Correlation scales have been used in the traditional scheme of three-dimensional variational data assimilation (3DVAR) to estimate the background (or first guess) error covariance matrix (the B matrix in brief) for the numerical forecast and reanalysis of ocean for decades. However, it is challenging to implement this scheme. On the one hand, determining the correlation scales accurately can be difficult. On the other hand, the positive definite of the B matrix cannot be guaranteed unless the correlation scales are sufficiently small. Xie et al. indicated that a traditional 3DVAR only corrects certain wavelength errors, and its accuracy depends on the accuracy of the B matrix. Generally speaking, the shortwave error cannot be sufficiently corrected until the longwave error is corrected. An inaccurate B matrix may mistake longwave errors as shortwave ones, resulting in erroneous analyses. A new 3DVAR data assimilation scheme, called a multigrid data assimilation scheme, is proposed in this paper for quickly minimizing longwave and shortwave errors successively. By assimilating the sea surface temperature and temperature profile observations into a numerical model of the China Seas, this scheme is applied to a retroactive real-time forecast experiment and favorable results are obtained. Compared to the traditional scheme of 3DVAR, this new scheme has higher forecast accuracy and lower root-meansquare errors. Note that the new scheme demonstrates greatly improved numerical efficiency in the analysis procedure.
Towards experimental evaluation of code obfuscation techniques

While many obfuscation schemes proposed, none of them satisfy any strong definition of obfuscation. Furthermore secure general-purpose obfuscation algorithms have been proven to be impossible. Nevertheless, obfuscation schemes which in practice slow down malicious reverse-engineering by obstructing code comprehension for even short periods of time are considered a useful protection against malicious reverse engineering. In previous works, the difficulty of reverse engineering has been mainly estimated by means of code metrics, by the computational complexity of static analysis or by comparing the output of de-obfuscating tools. In this paper we take a different approach and assess the difficulty attackers have in understanding and modifying obfuscated code through controlled experiments involving human subjects.
Comparison of the Young’s moduli of polymers measured from nanoindentation and bending experiments

Spherical and conical nanoindentation experiments were performed for the same polymer specimens to compare Young’s moduli measured from the elastic loading and unloading curves, and bending experiments. Finite-element simulation was employed to ensure pure elastic deformation during spherical nanoindentation. The moduli measured from the elastic loading curves using Hertz’s contact law are very close to the bending moduli, because both measurements were conducted under the same elastic deformation. However, the moduli measured from the elastic unloading curves are up to 60% higher than the bending moduli owing to plastic deformation close to the sharp conical indenter tip.
Modeling of physical and electrical characteristics of organic thin film transistors

The most studied and widely employed material for electronics is undoubtedly silicon. Its semiconductor properties and its associated costs make it an ideal candidate for most of the needs of today electronics. However, several different materials have been studied in the last years. In 1977, Alan J. Heeger, Alan G. MacDiarmid, and Hideki Shirakawa discovered a new, carbon based, highly-conductive polymer: the oxidized, iodine-doped polyacetylene. For their discovery, which was one of the most important milestones for organic electronics, they were jointly awarded the chemistry Nobel Prize in 2000. In this doctoral thesis, a theoretical framework for the electronics of organic transistors is developed. In chapter 2 an overview of the topic is presented: starting from the fundamental properties of the organic semiconductors, the chapter develops to provide a thorough analysis of the underlying physics and the electrical models which describe the behavior of organic thin film transistors. The next chapters describe models for organic thin film transistors with a cylindrical geometry, with short channel, and as a function of time. Chapter 6 concludes the doctoral thesis. The most important achievements and considerations are here summarized, and possible future activities on the topic are exposed.
Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning

Obtaining labels can be costly and time-consuming. Active learning allows a learning algorithm to intelligently query samples to be labeled for efficient learning. Fisher information ratio (FIR) has been used as an objective for selecting queries in active learning. However, little is known about the theory behind the use of FIR for active learning. There is a gap between the underlying theory and the motivation of its usage in practice. In this paper, we attempt to fill this gap and provide a rigorous framework for analyzing existing FIR-based active learning methods. In particular, we show that FIR can be asymptotically viewed as an upper bound of the expected variance of the log-likelihood ratio. Additionally, our analysis suggests a unifying framework that not only enables us to make theoretical comparisons among the existing querying methods based on FIR, but also allows us to give insight into the development of new active learning approaches based on this objective.
Intrusion-Resilient Authentication in the Limited Communication Model

We describe a general technique for building authentication systems that resist compromises at the client side. We derive this resistance by storing key information on hardware fast enough for valid use but too slow for an intruder (e.g., a virus) to capture much of the key before being detected and removed. We give formal models for two types of protocols: user authentication and authenticated session-key generation. The first can be used for physical authentication tokens, e.g., used for gaining access to a building. The second can be used for conducting secure remote sessions on laptops that are occasionally infected by viruses. We present and analyze protocols for each of these tasks and describe how they can be implemented. With one example setting of parameters, in the case of user authentication, we are able to guarantee security for 6 months using a device storing 384MB, and in the key generation protocol, a 128GB drive guarantees that an adversary would need 700 days to compromise the key information. The model for intrusion resilience considered in this paper was first introduced by Dagon et al. [DLL05] and motivated by the bounded storage model for cryptography [Mau92]. Recently Dziembowski [Dzi05] independently developed this model, and studied the same problems as the ones addressed in this paper. Our user authentication protocol is essentially the same as that of [Dzi05], while our authenticated session-key generation protocol builds on that of [Dzi05].
WCMP: weighted cost multipathing for improved fairness in data centers

Data Center topologies employ multiple paths among servers to deliver scalable, cost-effective network capacity. The simplest and the most widely deployed approach for load balancing among these paths, Equal Cost Multipath (ECMP), hashes flows among the shortest paths toward a destination. ECMP leverages uniform hashing of balanced flow sizes to achieve fairness and good load balancing in data centers. However, we show that ECMP further assumes a balanced, regular, and fault-free topology, which are invalid assumptions in practice that can lead to substantial performance degradation and, worse, variation in flow bandwidths even for same size flows. We present a set of simple algorithms that achieve Weighted Cost Multipath (WCMP) to balance traffic in the data center based on the changing network topology. The state required for WCMP is already disseminated as part of standard routing protocols and it can be readily implemented in the current switch silicon without any hardware modifications. We show how to deploy WCMP in a production OpenFlow network environment and present experimental and simulation results to show that variation in flow bandwidths can be reduced by as much as 25X by employing WCMP relative to ECMP.
A source model mitigation technique for distributed speech recognition over lossy packet channels

In this paper, we develop a new mitigation technique for a distributed speech recognition system over IP. We have designed and tested several methods to improve the interpolation used in the Aurora DSR ETSI standard without any significant increase of computational cost at the decoder. These methods make use of the information contained in the data-source, because, in IP networks, unlike in cellular networks, no information is received during packet losses. When a packet loss occurs, the lost information can be reconstructed through estimations from the N nearest received packets. Due to the enormous amount of combinations from previous and next received speech vector sequences, we have developed a methodology that drastically reduces the amount of required estimations.
Thermoinducible transcription system for Bacillus subtilis that utilizes control elements from temperate phage phi 105

We describe a thermoinducible-expression system for Bacillus subtilis which utilized an early promoter-operator sequence from temperate phage phi 105 and the thermolabile prophage repressor from the phage variant phi 105 cts23. The system operated at the transcriptional level to control expression in B. subtilis of the cat-86 gene derived from Bacillus pumilis. Details of the strategies used to isolate the early phage promoter are described. This promoter lay in close proximity to the prophage repressor gene on the phi 105 genome. The sequence of the early promoter differed from that of the vegetative B. subtilis consensus promoter by 1 base pair in both the -10 and -35 regions. We also present evidence that our phage-derived expression system could function in Escherichia coli to effect thermoinducible expression of the galK gene.
A continuum model for alignment of self-propelled particles with anisotropy and density-dependent parameters

We consider the macroscopic model derived by Degond and Motsch from a time-continuous version of the Vicsek model, describing the interaction orientation in a large number of self-propelled particles. In this paper, we study the influence of a slight modification at the individual level, letting the relaxation parameter depend on the local density and taking in account some anisotropy in the observation kernel (which can model an angle of vision). The main result is a certain robustness of this macroscopic limit and of the methodology used to derive it. With some adaptations to the concept of generalized collisional invariants, we are able to derive the same system of partial differential equations, the only difference being in the definition of the coefficients, which depend on the density. This new feature may lead to the loss of hyperbolicity in some regimes. We then provide a general method which enables us to get asymptotic expansions of these coefficients. These expansions shows, in some effective situations, that the system is not hyperbolic. This asymptotic study is also useful to measure the influence of the angle of vision in the final macroscopic model, when the noise is small.
Scalable Locomotion for Large Self-Reconfiguring Robots

For large self-reconfiguring robots, any algorithm that requires linear amounts of memory per module (with respect to the number of modules) or linear time for computation or communication per actuation is undesirable. While shape-forming may require linear amounts of memory, locomotion can be performed with simpler shape specifications, and therefore sublinear algorithms are possible. In this paper, we present a locomotion technique that performs both planning and actuation control in sublinear time and memory. The algorithm is inspired by reinforcement learning and uses dynamic programming to plan module paths in parallel. To ensure the physical integrity of the overall robot during motion, we have developed a novel localized cooperation scheme which may also be used with other self-reconfiguration algorithms. Our overall algorithm is able to direct locomotion over arbitrary obstacles, and the formulation of the goal used in the planning encourages dynamic stability
Similar Structures to the E-to-H Helix Unit in the Globin-Like Fold are Found in Other Helical Folds

A protein in the globin-like fold contains six alpha-helices, A, B, E, F, G and H. Among them, the E-to-H helix unit (E, F, G and H helices) forms a compact structure. In this study, we searched similar structures to the E-to-H helix of leghomoglobin in the whole protein structure space using the Dali program. Several similar structures were found in other helical folds, such as KaiA/RbsU domain and Type III secretion system domain. These observations suggest that the E-to-H helix unit may be a common subunit in the whole protein 3D structure space. In addition, the common conserved hydrophobic residues were found among the similar structures to the E-to-H helix unit. Hydrophobic interactions between the conserved residues may stabilize the 3D structures of the unit. We also predicted the possible compact regions of the units using the average distance method.
Risk assessment of released cellulose nanocrystals – mimicking inhalatory exposure

Cellulose nanocrystals (CNCs) exhibit advantageous chemical and mechanical properties that render them attractive for a wide range of applications. During the life-cycle of CNC containing materials the nanocrystals could be released and become airborne, posing a potential inhalatory exposure risk towards humans. Absent reliable and dose-controlled models that mimic this exposure in situ is a central issue in gaining an insight into the CNC-lung interaction. Here, an Air Liquid Interface Cell Exposure system (ALICE), previously designed for studies of spherical nanoparticles, was used for the first time to establish a realistic physiological exposure test method for inhaled fiber shaped nano-objects; in this case, CNCs isolated from cotton. Applying a microscopy based approach the spatially homogenous deposition of CNCs was demonstrated as a prerequisite of the functioning of the ALICE. Furthermore, reliability and controllability of the system to nebulise high aspect ratio nanomaterials (HARN, e.g. CNCs) was shown. This opens the potential to thoroughly investigate the inhalatory risk of CNCs in vitro using a realistic exposure system.
New objective functions for social collaborative filtering

This paper examines the problem of social collaborative filtering (CF) to recommend items of interest to users in a social network setting. Unlike standard CF algorithms using relatively simple user and item features, recommendation in social networks poses the more complex problem of learning user preferences from a rich and complex set of user profile and interaction information. Many existing social CF methods have extended traditional CF matrix factorization, but have overlooked important aspects germane to the social setting. We propose a unified framework for social CF matrix factorization by introducing novel objective functions for training. Our new objective functions have three key features that address main drawbacks of existing approaches: (a) we fully exploit feature-based user similarity, (b) we permit direct learning of user-to-user information diffusion, and (c) we leverage co-preference (dis)agreement between two users to learn restricted areas of common interest. We evaluate these new social CF objectives, comparing them to each other and to a variety of (social) CF baselines, and analyze user behavior on live user trials in a custom-developed Facebook App involving data collected over five months from over 100 App users and their 37,000+ friends.