Miracle-dz/UniFAR-FTUs huggingface dataset:
Interferon- (IFN-) does not mimic the catabolic effects of tumor necrosis factor- (TNF-)

Cachexia is common in chronic inflammatory diseases and is attributed, in part, to elevation of circulating pro-inflammatory cytokines. TNF-α is the prototype in this category. IFN-γ is also thought to play a role, but the evidence supporting this model is primarily indirect. To determine the direct effects of IFN-γ stimulation on muscle cells, we selected key components of the pro-catabolic signaling pathways by which TNF-α stimulates protein loss. We tested two hypotheses: a. ) IFN-γ mimics TNF-α signaling by increasing intracellular oxidant activity and activating mitogen activated protein kinases (MAPKs) and NF-κB, and; b. ) IFN-γ increases expression of the ubiquitin ligases atrogin1/MAFbx and MuRF1. Results showed that treatment with IFN-γ 60 ng/ml increased Stat1 phosphorylation after 15 min, indicating receptor activation. IFN-γ had no effect on cytosolic oxidant activity as measured by 2’,7’-dichlorofluorescein oxidation. Nor did IFN-γ activate jun N-terminal kinase (JNK), extracellular-regulated kinases 1 and 2 (ERK1/2) or p38 MAPK as assessed by Western blot. Treatment for up to 60 min did not decrease IκBα protein levels as measured by Western blot or DNA binding activity of NF-κB activity as measured by electrophoresis mobility shift assay. After 6 hr, IFN-γ decreased Akt phosphorylation and increased atrogin1/MAFbx and MuRF1 mRNA. Daily treatment for up to 72 hr did not alter adult fast-type myosin heavy chain (MHCf) content or total protein:DNA ratio. These data show that responses of myotubes to IFN-γ and TNF-α differ markedly and provide little evidence for a direct catabolic effect of IFN-γ on muscle.
Making use of business goals in usability evaluation: an experiment with novice evaluators

The utility and impact of a usability evaluation depend on how well its results align with the business goals of the system under evaluation. However, how to achieve such alignment is not well understood. We propose a simple technique that requires active consideration of a system's business goals in planning and reporting evaluations. The technique is tested in an experiment with 44 novice evaluators using think aloud testing. The evaluators considering business goals report fewer usability problems compared to evaluators that did not use the technique. The company commissioning the evaluation, however, assesses those problems 30-42% higher on four dimensions of utility. We discuss how the findings may generalize to usability professionals, and how the technique may be used in realistic usability evaluations. More generally, we discuss how our results illustrate one of a variety of ways in which business goals and other facets of a system's context may enter into usability evaluations.
The Road to Watergate and Beyond: The Growth and Abuse of Executive Authority Since 1940

The investigation of Watergate, as well as other inquiries, revealed a host of presidential illegalities: break-ins, buggings, violations of privacy, cover-ups, abuse of the national security machinery (Justice Department, FBI, CIA, NSA) and related agencies (especially the Internal Revenue Service). In the aftermath of Watergate, many Americans have asked, "How could President Nixon have been so wrong as to believe that he could get away with it-the break-in, bugging, and cover-up? " This question overlooks two fundamental points: first, that he did almost get away with "it"; and second, that he had reason to believe that he would succeed because his actions were, in important ways, similar to earlier executive misuse of power, especially in the area of internal security, often involving the FBI.3 According to this thesis, Watergate was a culmination of the growth4 and
Speech enhancement with zero replacement signal at low SNR

In this paper, we propose a speech enhancement method with zero replacement signal of noisy speech signal. The proposed method utilizes the Fourier transform of the cross-correlation function between the noisy speech signal and zero replacement signal. Minimum values of the absolute value of the resulting spectrum become the power spectrum of original clean speech signal. For the proposed method, noise estimation is not required to emphasize the speech signal. By subjective evaluation in the presence of both stationary and non-stationary noises, it is shown that the proposed method provides better performance than the conventional method at lower signal-to-noise ratio.
BSR winter school Big Software on the Run : Where Software meets Data

Software-related problems have an incredible impact on society, organizations, and users that increasingly rely on information technology. Since software is evolving and operates in a changing environment, one cannot anticipate all problems at design-time. We propose to use process mining to analyze software in its natural habitat. Process mining aims to bridge the gap between model-based process analysis methods such as simulation and other business process management techniques on the one hand and data-centric analysis methods such as machine learning and data mining on the other. It provides tools and techniques for automated process model discovery, conformance checking, data-driven model repair and extension, bottleneck analysis, and prediction based on event log data. Process discovery techniques can be used to capture the real behavior of software. Conformance checking techniques can be used to spot deviations. The alignment of models and real software behavior can be used to predict problems related to performance or conformance. Recent developments in process mining and the instrumentation of software make this possible. This lecture provides pointers to the state-of-the-art in process mining and its application to software.
Hierarchical spherical distance fields for collision detection

The problem of collision detection between objects is fundamental in many different communities including CAD, robotics, computer graphics, and computational geometry. This article presents a fast collision detection technique for all types of rigid bodies, demonstrated using polygon soups. We present two algorithms for computing a discrete spherical distance field of models. For compactly storing the distance field, we use a subsampling filter bank.
Human Resource Management in the Multi-Divisional Company

Using research-based case examples, this book is the first systematic attempt to analyze the way human resources are managed within multi-divisional structures. John Purcell and Bruce Ahlstrand discuss the role of the corporate personnel department, the managers of unions and collective bargaining, and differing management styles. The book will be a useful aid in understanding the complexity for human resources management in the multi-divisional company, and providing a basis for action.
Gender and Terrorism

It is well documented that the world's active combat forces have been almost all male. With the exception of the legends of Amazons, there have been no known formal female fighting forces. History does record women such as Joan of Arc (France), Jhansi ki Rani, Razia Sultana (Indian subcontinent), and more recently Phoolan Devi (India) who led fighting forces comprised of men, but these are a rare occurrence. Similarly, in the last few decades, more men than women have been involved and are visible in acts of terrorism, including suicide attacks across Afghanistan, Kashmir, Sri Lanka, Bosnia, Palestine, Turkey, Chechnya, and elsewhere (barring Russia, where women have been active and quite visible). Keywords: gender; terrorism; equity; alienation; revenge; identification; modernization; women terrorists; role modeling; gender role differentiation; territoriality
Optimizing Transmitter-Receiver Collaborative-Relay Beamforming with Perfect CSI

This letter studies a three-hop channel constructed by collaborative relaying terminals at both the transmitter and receiver ends. Our objective is to optimize the complex amplify-and-forward (AF) weights of the relaying terminals if the channel state information (CSI) is exploited. A near-optimal numerical solution for the collaborative-relay beamforming (CRBF) weights is first found from solving an unconstrained multi-variant minimization problem. Using the concept of subspace averaging, a near-optimal closed-form CRBF solution is then proposed.
Optimal and topologically safe simplification of building footprints

We present an optimization approach to simplify sets of building footprints represented as polygons. We simplify each polygonal ring by selecting a subsequence of its original edges; the vertices of the simplified ring are defined by intersections of consecutive (and possibly extended) edges in the selected sequence. Our aim is to minimize the number of all output edges subject to a user-defined error tolerance. Since we earlier showed that the problem is NP-hard when requiring non-intersecting simple polygons as output, we cannot hope for an efficient, exact algorithm. Therefore, we present an efficient algorithm for a relaxed problem and an integer program (IP) that allows us to solve the original problem with existing software. Our IP is large, since it has O(m6) constraints, where m is the number of input edges. In order to keep the running time small, we first consider a subset of only O(m) constraints. The choice of the constraints ensures some basic properties of the solution. Constraints that were neglected are added during optimization whenever they become violated by a new solution encountered. Using this approach we simplified a set of 144 buildings with a total of 2056 edges in 4.1 seconds on a standard desktop PC; the simplified building set contained 762 edges. During optimization, the number of constraints increased by a mere 13%. We also show how to apply cartographic quality measures in our method and discuss their effects on examples.
ADAPTIVE VIDEO DELIVERY USING SEMANTICS

The diffusion of network appliances such as cellular phones, personal digital assistants and hand-held computers has created the need to personalize the way media content is delivered to the end user. Moreover, recent devices, such as digital radio receivers with graphics displays, and new applications, such as intelligent visual surveillance, require novel forms of video analysis for content adaptation and summarization. To cope with these challenges, we propose an automatic method for the extraction of semantics from video, and we present a framework that exploits these semantics in order to provide adaptive video delivery. First, an algorithm that relies on motion information to extract multiple semantic video objects is proposed. The algorithm operates in two stages. In the first stage, a statistical change detector produces the segmentation of moving objects from the background. This process is robust with regard to camera noise and does not need manual tuning along a sequence or for different sequences. In the second stage, feedbacks between an object partition and a region partition are used to track individual objects along the frames. These interactions allow us to cope with multiple, deformable objects, occlusions, splitting, appearance and disappearance of objects, and complex motion. Subsequently, semantics are used to prioritize visual data in order to improve the performance of adaptive video delivery. The idea behind this approach is to organize the content so that a particular network or device does not inhibit the main content message. Specifically, we propose two new video adaptation strategies. The first strategy combines semantic analysis with a traditional frame-based video encoder. Background simplifications resulting from this approach do not penalize overall quality at low bitrates. The second strategy uses metadata to efficiently encode the main content message. The metadata-based representation of object's shape and motion suffices to convey the meaning and action of a scene when the objects are familiar. The impact of different video adaptation strategies is then quantified with subjective experiments. We ask a panel of human observers to rate the quality of adapted video sequences on a normalized scale. From these results, we further derive an objective quality metric, the semantic peak signal-to-noise ratio (SPSNR), that accounts for different image areas and for their relevance to the observer in order to reflect the focus of attention of the human visual system. At last, we determine the adaptation strategy that provides maximum value for the end user by maximizing the SPSNR for given client resources at the time of delivery. By combining semantic video analysis and adaptive delivery, the solution presented in this dissertation permits the distribution of video in complex media environments and supports a large variety of content-based applications.
An efficient and robust rotation invariant descriptor

A novel scheme to calculate feature descriptors with rotation invariance was proposed in this paper. Unlike traditional methods of computing feature orientations and descriptors using a single sampling pattern, we calculate the orientation of a feature point with one sampling pattern and generate its descriptor with another one. Based on this idea, we present a method to generate a rotation invariant descriptor using the sampling patterns of FREAK and BRIEF. The experimental results on image matching show that our method is not only invariant to image rotation but also robust to many other situations such as image blur, viewpoint change, illumination change and JEPG compression. At the same time, the proposed method performs competitively with BRISK and FREAK in computational time.
Multivariate Logistic Regression for Predicting Total Culturable Virus Presence at the Intake of a Potable-Water Treatment Plant: Novel Application of the Atypical Coliform/Total Coliform Ratio

ABSTRACT Predicting the presence of enteric viruses in surface waters is a complex modeling problem. Multiple water quality parameters that indicate the presence of human fecal material, the load of fecal material, and the amount of time fecal material has been in the environment are needed. This paper presents the results of a multiyear study of raw-water quality at the inlet of a potable-water plant that related 17 physical, chemical, and biological indices to the presence of enteric viruses as indicated by cytopathic changes in cell cultures. It was found that several simple, multivariate logistic regression models that could reliably identify observations of the presence or absence of total culturable virus could be fitted. The best models developed combined a fecal age indicator (the atypical coliform [AC]/total coliform [TC] ratio), the detectable presence of a human-associated sterol (epicoprostanol) to indicate the fecal source, and one of several fecal load indicators (the levels of Giardia species cysts, coliform bacteria, and coprostanol). The best fit to the data was found when the AC/TC ratio, the presence of epicoprostanol, and the density of fecal coliform bacteria were input into a simple, multivariate logistic regression equation, resulting in 84.5% and 78.6% accuracies for the identification of the presence and absence of total culturable virus, respectively. The AC/TC ratio was the most influential input variable in all of the models generated, but producing the best prediction required additional input related to the fecal source and the fecal load. The potential for replacing microbial indicators of fecal load with levels of coprostanol was proposed and evaluated by multivariate logistic regression modeling for the presence and absence of virus.
Finger Usage and Arithmetic in Adults with Math Difficulties: Evidence From a Case Report

The role of finger usage upon learning arith-metic has received increasing interest from various disciplines. In this opinion paper, we would like to emphasize that finger usage in calculation is not a unitary phenomenon. Rather, we propose two different types of finger usage: First, in many countries and independent of the number system in use, typically developing children use fingers as important transitory (and intuitive) tools to represent small quantities ( Butterworth, 1999; Bender and Beller, 2011). According to Di Luca and Pesenti (2011) , finger count-ing habits are needed to build, acquire, and access mental number representations, the building blocks for semantic number knowledge. Second, developmentally inap-propriate finger usage of children with math difficulties (MD) reflects their persistent need to apply back-up strategies to compen-sate for deficient or lacking number repre-sentations (e.g., Brissaud, 1992; Kaufmann, 2002; Wright et al., 2002). Here, we will focus on the second type of finger usage (i.e., persistent finger usage in individuals with MD) and we argue that (a) finger usage in arithmetic is not restricted to children; and (b) finger-based calculation strategies utilized by adults with MD reflect immature calculation strategies that are comparable to those displayed by affected children.
Weighted and Constrained Consensus for Distributed Power Dispatch of Scalable Microgrids

Microgrids with distributed energy generators, controllable appliances, electric vehicle charging infrastructures, and energy storage systems introduce new technical challenges in the management of distribution networks. This paper introduces a new framework for power flow control based on the emerging consensus control for networked systems. Due to unique features of power systems, the consensus control problem becomes weighted and constrained, beyond the typical consensus formulation. Using only neighborhood communication for each bus on the microgrid, the consensus control achieves global weighted load balancing. Algorithms are introduced and their convergence properties are established. It is shown that the algorithms have the fastest convergence rates in terms of consensus error variances, by achieving asymptotically the Cramér‐Rao lower bound, and hence is optimal among all algorithms. Examples and case studies demonstrate convergence, robustness, and scalability of the methodology and feasibility in distribution networks. Practical issues are further discussed.
1999 Nationwide French Hospitals Database Intervention in Acute Myocardial Infarction : Microsimulation Analysis of the Gender Differences in Hospital Mortality and Use of Percutaneous Coronary

Copyright © 2007 American Heart Association. All rights reserved. Print ISSN: 0009-7322. Online 72514 Circulation is published by the American Heart Association. 7272 Greenville Avenue, Dallas, TX DOI: 10.1161/CIRCULATIONAHA.106. 664979 2007;115;833-839 Circulation Carine Milcent, Brigitte Dormont, Isabelle Durand-Zaleski and Philippe Gabriel Steg 1999 Nationwide French Hospitals Database Intervention in Acute Myocardial Infarction: Microsimulation Analysis of the Gender Differences in Hospital Mortality and Use of Percutaneous Coronary http://circ.ahajournals. org/cgi/content/full/115/7/833 located on the World Wide Web at: The online version of this article, along with updated information and services, is
Investor attention , overconfidence and category learning

Motivated by psychological evidence that attention is a scarce cognitive resource, we model investors’ attention allocation in learning and study the effects of this on asset-price dynamics. We show that limited investor attention leads to category-learning behavior, i.e., investors tend to process more market and sector-wide information than firm-specific information. This endogenous structure of information, when combined with investor overconfidence, generates important features observed in return comovement that are otherwise difficult to explain with standard rational expectations models. Our model also demonstrates new cross-sectional implications for return predictability. r 2005 Elsevier B.V. All rights reserved. JEL classification: G12; G14
Decrease in spectral entropy by low tidal volume ventilation-associated severe hypercapnia: a case report

Severe hypercapnia can be predicted by a decrease in cerebral electrical activity. The authors describe a sudden decrease in spectral entropy due to severe hypercapnia-induced respiratory acidosis in a patient with chronic pulmonary obstructive disease during lung resection. After two and a half hours of low tidal volume ventilation in the lateral position, the state entropy suddenly dropped from 45 to 7, without any changes in the effect-site concentration of propofol, end-tidal carbon dioxide (CO2) tension, oxygen saturation, or arterial pressure. However, arterial blood gas analysis showed severe respiratory acidosis (pH 7.01, PaCO2 115 mmHg and PaO2 246 mmHg with FIO2 of 0.5). Immediate hyperventilation improved the state entropy and acid-base balance. Electroencephalography-based spectral entropy can detect severe hypercapnia in chronic pulmonary obstructive disease patients with a large arterial to end-tidal CO2 difference due to prolonged hypoventilation during thoracic surgery.
Recurrent concussion and risk of depression in retired professional football players.

PURPOSE The purpose of our study was to investigate the association between prior head injury and the likelihood of being diagnosed with clinical depression among retired professional football players with prior head injury exposure. METHODS A general health questionnaire, including information about prior injuries, the SF-36 (Short Form 36), and other markers for depression, was completed by 2552 retired professional football players with an average age of 53.8 (+/-13.4) yr and an average professional football-playing career of 6.6 (+/-3.6) yr. A second questionnaire focusing on mild cognitive impairment (MCI)-related issues was completed by a subset of 758 retired professional football players (50 yr and older). RESULTS Two hundred sixty-nine (11.1%) of all respondents reported having prior or current diagnosis of clinical depression. There was an association between recurrent concussion and diagnosis of lifetime depression (chi2=71.21, df=2, P<0.005), suggesting that the prevalence increases with increasing concussion history. Compared with retired players with no history of concussion, retired players reporting three or more previous concussions (24.4%) were three times more likely to be diagnosed with depression; those with a history of one or two previous concussions (36.3%) were 1.5 times more likely to be diagnosed with depression. The analyses controlled for age, number of years since retirement, number of years played, physical component score on the SF-36, and diagnosed comorbidities such as osteoarthritis, coronary heart disease, stroke, cancer, and diabetes. CONCLUSION Our findings suggest a possible link between recurrent sport-related concussion and increased risk of clinical depression. The findings emphasize the importance of understanding potential neurological consequences of recurrent concussion.
A $Q$ -Band Four-Element Phased-Array Front-End Receiver With Integrated Wilkinson Power Combiners in 0.18-$\mu{{\hbox{m}}}$  SiGe BiCMOS Technology

A four-element phased-array front-end receiver based on 4-bit RF phase shifters is demonstrated in a standard 0.18-mum SiGe BiCMOS technology for Q-band (30-50 GHz) satellite communications and radar applications. The phased-array receiver uses a corporate-feed approach with on-chip Wilkinson power combiners, and shows a power gain of 10.4 dB with an IIP3 of -13.8 dBm per element at 38.5 GHz and a 3-dB gain bandwidth of 32.8-44 GHz. The rms gain and phase errors are les1.2 dB and les8.7deg for all 4-bit phase states at 30-50 GHz. The beamformer also results in les0.4 dB of rms gain mismatch and les2deg of rms phase mismatch between the four channels. The channel-to-channel isolation is better than -35 dB at 30-50 GHz. The chip consumes 118 mA from a 5-V supply voltage and overall chip size is 1.4times1. 7 mm2 including all pads and CMOS control electronics.