Miracle-dz/UniFAR-FTUs huggingface dataset:
Tumor-Associated Macrophages in Glioblastoma Multiforme—A Suitable Target for Somatostatin Receptor-Based Imaging and Therapy?

Background Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. Tumor-associated macrophages (TAM) have been shown to promote malignant growth and to correlate with poor prognosis. [1,4,7,10-tetraazacyclododecane-NN′,N″,N′″-tetraacetic acid]-d-Phe1,Tyr3-octreotate (DOTATATE) labeled with Gallium-68 selectively binds to somatostatin receptor 2A (SSTR2A) which is specifically expressed and up-regulated in activated macrophages. On the other hand, the role of SSTR2A expression on the cell surface of glioma cells has not been fully elucidated yet. The aim of this study was to non-invasively assess SSTR2A expression of both glioma cells as well as macrophages in GBM. Methods 15 samples of patient-derived GBM were stained immunohistochemically for macrophage infiltration (CD68), proliferative activity (Ki67) as well as expression of SSTR2A. Anti-CD45 staining was performed to distinguish between resident microglia and tumor-infiltrating macrophages. In a subcohort, positron emission tomography (PET) imaging using 68Ga-DOTATATE was performed and the semiquantitatively evaluated tracer uptake was compared to the results of immunohistochemistry. Results The amount of microglia/macrophages ranged from <10% to >50% in the tumor samples with the vast majority being resident microglial cells. A strong SSTR2A immunostaining was observed in endothelial cells of proliferating vessels, in neurons and neuropile. Only faint immunostaining was identified on isolated microglial and tumor cells. Somatostatin receptor imaging revealed areas of increased tracer accumulation in every patient. However, retention of the tracer did not correlate with immunohistochemical staining patterns. Conclusion SSTR2A seems not to be overexpressed in GBM samples tested, neither on the cell surface of resident microglia or infiltrating macrophages, nor on the surface of tumor cells. These data suggest that somatostatin receptor directed imaging and treatment strategies are less promising in GBM.
High-performance VLSI architecture for the Viterbi algorithm

The Viterbi (1967) algorithm (VA) is known to be an efficient method for the realization of maximum-likelihood (ML) decoding of convolutional codes. The VA is characterized by a graph, called a trellis, which defines the transitions between states. To define an area efficient architecture for the VA is equivalent to obtaining an efficient mapping of the trellis. We present a methodology that permits the efficient hardware mapping of the VA onto a processor network of arbitrary size. This formal model is employed for the partitioning of the computations among an arbitrary number of processors in such a way that the data are recirculated, optimizing the use of the PEs and the communications. Therefore, the algorithm is mapped onto a column of processing elements and an optimal design solution is obtained for a particular set of area and/or speed constraints. Furthermore, the management of the surviving path memory for its mapping and distribution among the processors was studied. As a result, we obtain a regular and modular design appropriate for its VLSI implementation in which the only necessary communications between processors are the data recirculations between stages.
Section Editor: New Research in the Field of Stroke: Therapeutic Hypothermia after Cardiac Arrest Emerging Therapies

T herapeutic hypothermia as a potential treatment for stroke, cerebral ischemia, and other neurological diseases has gained momentum since the initial discovery that relatively small differences in intraischemic brain temperature critically determine ischemic neuronal vulnerability. 1 Since that time, laboratories throughout the world have investigated the potential use of mild-to-moderate hypother-mia in many ischemia models. 2,3 Various studies have also investigated potential mechanisms contributing to hypother-mic protection. Pathomechanisms sensitive to intra-and postischemic temperature reductions and elevations include glutamate release, stabilization of the blood-brain barrier, oxygen radical production, intracellular signal conduction, protein synthesis, ischemic depolarization, reduced cerebral metabolism, membrane stabilization, inflammation, activation of protein kinases, cytoskeletal breakdown, and early gene expression. 2,4 Because the pathophysiology of ischemic brain injury is complex, the fact that many injury mechanisms have been reported to be temperature sensitive may account for the dramatic effects of temperature on ischemic outcome. Thus, therapeutic hypothermia has the necessary support from preclinical data to initiate well-designed clinical studies targeting various patient populations. In a recent issue of The New England Journal of Medicine, the results of 2 randomized clinical trials showed clearly that mild hypothermia improves neurologic outcome and reduces overall mortality in survivors of out-of-hospital–witnessed cardiac arrest. 5,6 In the study from Australia, a total of 77 patients who remained comatose after the return of spontaneous circulation (ROSC) were randomized to receive 12 hours of hypothermia or standard normothermic temperature management. 5 In that study, surface cooling was begun in the field and the target temperature of 32°C to 34°C was reached within 2 hours of ROSC. Forty-nine percent of those treated with hypothermia were discharged home or to a rehabilitation facility, as compared with 26% of those not treated with hypothermia (Pϭ0.046). In the second study from Europe, 9 centers in 5 countries participated, with a total enrollment of 136 patients. 6 Cooling was initiated at a median of 105 minutes after ROSC, and the target temperature of 32°C to 34°C was not reached until 8 hours after ROSC. After 24 hours of hypothermia, passive rewarming was allowed to occur over the next 8 hours. These investigators found that a favorable neurologic outcome occurred in 55% of hypother-mic patients compared with 39% of normothermic patients (Pϭ0.009). Hypothermic patients also had a lower 6-month mortality rate (41% versus 55%, Pϭ0.02). Importantly, in neither study was hypothermia associated with deleterious side effects such as sepsis, bleeding, severe electrolyte disturbances, …
Cultural Variables and Factor Analysis of BASIS-A Using a Jordanian Sample

The purpose of this study was to evaluate the psychometric properties of an Arabic version of the Basic Adlerian Scales for Interpersonal Success–Adult Form using a Jordanian sample. The sample included 330 Jordanian citizens for whom Arabic is the native language. The results revealed three factors instead of the original five. The first factor included all items from the Belonging and Social Interest scale and nine items from the Wanting Recognition scale. All eight items of the Taking Charge scale, as well as one item from the Going Along scale, constituted the second factor. Finally, the third factor included seven items from the Being Cautious scale, two of the Going Along items, and one item from the Wanting Recognition scale.
Improving Urban Vehicle Localization with Traffic Sign Recognition

Accurate and reliable vehicle localization is an important requirement for many vehicular applications. In challenging environments like urban areas, the GNSS accuracy often degrades due to blocked or reflected satellite signals. To improve the standalone positioning accuracy, we propose a landmark based localization method using traffic signs. The traffic sign detections from a camera are associated with the landmarks in a pre-generated traffic sign database and correct the GNSS position of the vehicle within a Bayes Filter. This approach was evaluated with real-world data collected during a test drive in difficult urban scenarios and the results were compared with low-cost GNSS positioning.
Interrelation of self-report, behavioural and electrophysiological measures assessing pain-related information processing.

INTRODUCTION A number of variables reflecting attentional and emotional mechanisms of processing pain-related information have recently attracted interest, ie, fear of pain, pain catastrophizing, hypervigilance and attentional bias to pain. These variables can be assessed by explicit measures based on conscious self-report, or by implicit measures assessing mainly preconscious stages of information processing such as behavioural or electrophysiological tests. Convergent validity within implicit measures was assumed to be high, as was the discriminant validity between implicit and explicit measures. METHOD In the present study, two implicit measures (the dot-probe task for pain words and a word-processing task for pain words allowing event-related brain potential recordings) and three self-report measures (Pain Catastrophizing Scale, Pain Anxiety Symptoms Scale, and Pain Hypervigilance and Awareness Questionnaire) were administered to 27 healthy participants. RESULTS No significant associations were found between the implicit measures, or between the event-related brain potentials of pain words and the explicit measures. A single significant positive correlation was found between the dot-probe pain bias and the Pain Anxiety Symptoms Scale. CONCLUSION All variables appeared to be only weakly associated. The attempt to organize the field of variables targeting attentional and emotional mechanisms of processing pain-related information using concepts such as implicit and explicit measures failed as far as the present test on convergent⁄discriminant validity proved.
Adaptive Algorithms for Feedback-Based Flow Control in High Speed, Wide-Area ATM Networks

This paper gives a class of flow control algorithms for the adaptive allocation of bandwidths to virtual connections (VC) in high-speed, wide-area ATM networks. The feedback rate to the source from the network is parsimonious, with each feedback bit indicating whether the buffer at a distant switch is above or below a threshold. The service discipline at the switch is first-come-first-served. The important goal of adaptability aims to make all of the network bandwidth available to the active VCs, even though the number of such VCs is variable over a given range. Each VC has two parameters, one giving its minimum guaranteed bandwidth and the other is the weight for determining its share of the uncommitted bandwidth. Judicious selection of these parameters defines distinctive services, such as best effort and best effort with minimum bandwidth. We derive design rules for selecting the parameters of the algorithms such that the appropriate guarantees and fairness properties are exhibited in the dynamical behavior. The systematic use of "damping" in right proportion with "gain" is shown to be a powerful device for stabilizing behavior and achieving fairness. Our analyses are based on a simple analytic fluid model composed of a system of first-order delay-differential equations, which reflect the propagation delay across the network. Extensive simulations examine the following: (1) fairness, especially to start-up VCs; (2) oscillations; (3) transient behavior, such as the rate of equalization from different initial conditions; (4) disparate bandwidth allocations; (5) multiple paths with diverse propagation delays; (6) adaptability and robustness with respect to parameters; and (7) interoperability of different algorithms. >
Generalizable Features From Unsupervised Learning

Humans learn a predictive model of the world and use this model to reason about future events and the consequences of actions. In contrast to most machine predictors, we exhibit an impressive ability to generalize to unseen scenarios and reason intelligently in these settings. One important aspect of this ability is physical intuition(Lake et al., 2016). In this work, we explore the potential of unsupervised learning to find features that promote better generalization to settings outside the supervised training distribution. Our task is predicting the stability of towers of square blocks. We demonstrate that an unsupervised model, trained to predict future frames of a video sequence of stable and unstable block configurations, can yield features that support extrapolating stability prediction to blocks configurations outside the training set distribution
Ad hoc matching of vectorial road networks

In integration of road maps modeled as road vector data, the main task is matching pairs of objects that represent, in different maps, the same segment of a real-world road. In an ad hoc integration, the matching is done for a specific need and, thus, is performed in real time, where only a limited preprocessing is possible. Usually, ad hoc integration is performed as part of some interaction with a user and, hence, the matching algorithm is required to complete its task in time that is short enough for human users to provide feedback to the application, that is, in no more than a few seconds. Such interaction is typical of services on the World Wide Web and to applications in car-navigation systems or in handheld devices. Several algorithms were proposed in the past for matching road vector data; however, these algorithms are not efficient enough for ad hoc integration. This article presents algorithms for ad hoc integration of maps in which roads are represented as polylines. The main novelty of these algorithms is in using only the locations of the endpoints of the polylines rather than trying to match whole lines. The efficiency of the algorithms is shown both analytically and experimentally. In particular, these algorithms do not require the existence of a spatial index, and they are more efficient than an alternative approach based on using a grid index. Extensive experiments using various maps of three different cities show that our approach to matching road networks is efficient and accurate (i.e., it provides high recall and precision). General Terms:Algorithms, Experimentation
The application of the Chinese version of K6 and K10 screening scales for psychological distress on the psychological investigation of college students

OBJECTIVE The objective of the study was to compare the application values of the K6 and K10 versions of the Kessler Psychological Distress Scales on the investigation of psychological conditions of college students and to analyze the mental health statuses of college students. METHODS 1 380 college students at an university in Sichuan Province were selected by stratified random sampling, and psychological conditions of the students were investigated by using the Kessler Psychological Distress Scale. The resulting data were analyzed by statistical methods, including t test, variance analysis, ranksum test, correlation analysis, and multiple linear regression analysis. RESULTS Average scores on K6 and K10 of the 1380college students were 4.62 ± 3.72 and 7.82 ± 5.91, respectively. 3.8% of the students had a K6 score of over 12, and 4.3%scored higher than 19(Level 4) on K10. Significant differences in scores on K6 and K10 were observed between students in different years of study and in different age groups; and the correlation coefficient between K6 and K10 scores was 0.973(P﹤0.05). CONCLUSION Mental health conditions of the college students vary in different years of study and in different age groups, and the K6 scale is suitable for psychological investigations of college students.
Effective IS Security

Security has not been one of the top issues facing IS managers. Many managers permit their installations to be either lightly protected or wholly unprotected, apparently willing to risk major losses from computer abuse. This study, based on the criminological theory of General Deterrence, investigates whether a management decision to invest in IS security results in more effective control of computer abuse. Data gathered through a survey of 1211 randomly-selected organizations indicates that security countermeasures that include deterrent administrative procedures and preventive security software will result in lower computer abuse. Knowledge about these relationships is useful for making important decisions about the security function. ______________________________________________________________________________
Formal Verification of OAuth 2.0 Using Alloy Framework

Over the past few years, the paradigm of social networking has grown to such a degree that social networking websites have evolved into full-fledged platforms, catering to a wide range of consumer interests. The near-ubiquity of Internet access has facilitated the proliferation of users that indulge in social networking. However, this wide spread usage of the Internet and social networking in particular brings with it the need to design and implement a plethora of security enhancing and privacy preserving protocols and standards. Several protocols and security mechanisms have been proposed to ensure primary security features such as confidentiality, integrity, authenticity and non repudiation. However, ensuring the correctness of these protocols is crucial in ensuring user confidence in system security. Therefore, these protocols need to be verified in some formal sense that involves an exhaustive examination of the protocol flow and its state transitions. In this paper, we formalize OAuth, an authentication standard which has found wide acceptance in the Internet community. We formalize the protocol using a method called knowledge flow analysis, using the Alloy modeling language for specification and the Alloy Analyzer for verification. We show how the Alloy Analyzer successfully discovers the known security vulnerability in OAuth.
Effect of Rotation on the Stability of a Stalled Cylindrical Shock and Its Consequences for Core-Collapse Supernovae

A perturbative analysis is used to investigate the effect of rotation on the instability of a steady accretion shock (SASI) in a simple toy model, in view of better understanding supernova explosions in which the collapsing core contains angular momentum. A cylindrical geometry is chosen for the sake of simplicity. Even when the centrifugal force is very small, rotation can have a strong effect on the nonaxisymmetric modes of SASI by increasing the growth rate of the spiral modes rotating in the same direction as the steady flow. Counterrotating spiral modes are significantly damped, while axisymmetric modes are hardly affected by rotation. The growth rates of spiral modes have a nearly linear dependence on the specific angular momentum of the flow. The fundamental one-armed spiral mode (m = 1) is favored for small rotation rates, whereas stronger rotation rates favor the mode m = 2. A WKB analysis of higher harmonics indicates that the efficiency of the advective-acoustic cycles associated with spiral modes is strongly affected by rotation in the same manner as low-frequency modes, whereas the purely acoustic cycles are stable. These results suggest that the linear phase of SASI in rotating core-collapse supernovae naturally selects a spiral mode rotating in the same direction as the flow, as observed in the three-dimensional numerical simulations of Blondin and Mezzacappa. This emphasizes the need for a three-dimensional approach to rotating core collapse, before conclusions on the explosion mechanisms and pulsar kicks can be drawn.
The noise clinic: A universal blind denoising algorithm

Most papers on denoising methods assume a white Gaussian noise model. Yet in most images handled by the public or by scientific users, the noise model is unknown and is not white, because of the various processes applied to the image before it reaches the user: scanning, demosaicing, compression, de-convolution, etc. To cope with this wide ranging problem, we propose a blind multiscale denoising algorithm working for noise which is simultaneously signal and frequency dependent. On noisy images coming from diverse sources (JPEG, scans of old photographs, .) we show perceptually convincing results. This algorithm is compared to the state-of-the-art and it is also validated on images with white noise.
Empirical Distribution of Equilibrium Play and Its Testing Application

We show that in any n -player, m -action normal-form game, we can obtain an approximate equilibrium by sampling any mixed-action equilibrium a small number of times. We study three types of equilibria: Nash, correlated, and coarse-correlated. For each one we obtain upper and lower bounds on the number of samples required for the empirical distribution over the sampled action profiles to form an approximate equilibrium with probability close to 1. These bounds imply that using a small number of samples we can test whether or not players are playing according to an approximate equilibrium, even in games where n and m are large. In addition, our results substantially improve previously known upper bounds on the support size of approximate equilibria in games with many players. In particular, for the three types of equilibria we show the existence of approximate equilibrium with support-size polylogarithmic in n and m , whereas the previously best-known upper bounds were polynomial in n (Hemon et al. [Hemon S, de Rougemont M, Santha M (2008) Approximate nash equilibria for multi-player games. Algorithmic Game Theory (Springer), 267–278], Germano and Lugosi [Germano F, Lugosi G (2007) Existence of sparsely supported correlated equilibria. Econom. Theory 32(3):575–578], Hart et al. [Hart S, Mas-Colell A, Babichenko Y (2013) Simple Adaptive Strategies: From Regret-Matching to Uncoupled Dynamics , Vol. 4 (World Scientific Publishing Company)]).
Learning Shape Hierarchies for Shape Detection

One approach to detecting objects in greyscale scenes is to design the computational process itself rather than probability distributions (generative modeling) or decision boundaries (predictive learning). The general idea is to construct a tree-structured representation of the space of object instantiations as well as a binary classifier for each cell in this hierarchical scaffold. This is highly efficient due to pruning groups of hypotheses simultaneously at all stages of processing. The emphasis in existing work has been on design and modeling. Our approach is more data-driven and focused on learning. In particular, we induce the hierarchy of shapes directly from training data, employ boosting to build the classifiers utilizing cell-dependent “negative” examples, and extend and adapt the hierarchy as new samples are encountered. The resulting generality is illustrated by applying the very same learning and parsing algorithms to detecting both rigid and deformable shapes.
Conformance and mirroring for timed asynchronous circuits

Conformance has been used as a correctness criterion for asynchronous circuits. In the case of untimed systems, conformance of an implementation to a specification is equivalent to the failure-freeness between the implementation and the mirror of the specification. For bounded-delay systems, in general this property does not hold. In this paper, we define various notions of failures and examine whether the above property holds or not. We then discuss an alternative and effective algorithm for conformance checking of bounded-delay asynchronous circuits.
PCR-based detection of genetically modified soybean and maize in raw and highly processed foodstuffs.

The PCR method has proved to be an invaluable tool for the specific and sensitive detection of genetically modified material (e.g., Roundup Ready Soybean and Bt-176 "Maximizer" Maize) in foodstuffs. The first step in the procedure, namely the purification of nucleic acids from the sample, is often the deciding factor in the production of meaningful results. In this study, we present two procedures that enable an efficient isolation of trace amounts of genetic material from both raw and highly processed foodstuffs. We show that for optimal, PCR-ready DNA purification from highly processed foodstuffs and PCR inhibitor-rich substances--such as cocoa-containing products--adapted protocols for the QIAGEN QIAamp DNA Stool Mini Kit can be utilized. For complete DNA isolation from raw foodstuffs, a protocol using the DNeasy Plant Mini Kit is presented.