Miracle-dz/UniFAR-FTUs huggingface dataset:
The Activation of MAPK in Melanoma Cells Resistant to BRAF Inhibition Promotes PD-L1 Expression That Is Reversible by MEK and PI3K Inhibition

Purpose: Selective BRAF inhibition (BRAFi) provides a paradigm shift for melanoma treatment. The duration of benefit is typically limited before resistance develops. Interest remains in combining targeted and immune therapies to overcome resistance and improve durability of clinical benefit. One mechanism of evading immune destruction is programmed death-1-ligand 1 (PD-L1) expression by tumors that results in potent antitumor immune suppression. Experimental Design: BRAFi-resistant melanoma cells were examined for changes in PD-L1 expression by immunoblot and flow cytometry. Signaling pathways involved in altering PD-L1 expression were examined. Strategies to maximize the effect of the BRAFi therapy were studied including MEKi, MEKi combinations, and additional pathways including phosphoinositide-3 kinase (PI3K). Results: Melanoma cells resistant to BRAFi exhibit increased MAPK signaling and promotion of PD-L1 expression. PD-L1 expression is transcriptionally modulated by c-Jun and augmented by STAT3. MEK inhibition (MEKi) regains downregulation of MAPK signaling and suppresses the production of PD-L1. MEKi in melanoma cells shows dual therapeutic effects with simultaneous suppression of PD-L1 expression and induction of apoptosis. By combining MEKi with BRAFi, an additive effect on the inhibition of PD-L1 expression results. Conclusions: We report a novel mechanism that suppresses preexisting immune responses in patients with melanoma receiving BRAFi therapy. BRAFi resistance leads to increased expression of PD-L1 in melanoma cells, mediated by c-Jun and STAT3. MEKi may be feasible to counteract BRAFi resistance of MAPK reactivation and also for the additive effect of PD-L1 suppression. Potential therapeutic benefits of combining targeted inhibitors and immune modulation to improve patient outcomes should be investigated. Clin Cancer Res; 19(3); 598–609. ©2012 AACR.
An Energy-Efficient VCO-Based Matrix Multiplier Block to Support On-Chip Image Analysis

Images typically are represented as uniformly sampled data in the form of matrix of pixels/voxels. Therefore, matrix multiply-and-accumulate (MAC) forms the core of most state-of-the-art image analysis algorithms. While digital implementation of MAC has generally been the preferred approach, high power consumption is an impediment to adopting it for medical image analysis. In this work, we present a time-domain signal processing architecture which performs MAC operations with 7bit accuracy while consuming 400X lower energy than digital implementation. The proposed architecture performs analog computation using mostly digital circuits and is suitable for scaled CMOS technologies. The proposed time-domain MAC architecture is expected to play a central role in empowering the advancement of various on-chip image analysis operations.
Closed form solution for optimal buffer sizing using the Weierstrass elliptic function

This paper presents a fundamental result on buffer sizing. Given an interconnection wire with n buffers evenly spaced along the wire, we would like to size all buffers such that the Elmore delay is minimized. It is well known that the problem can be solved by an iterative algorithm which sizes one buffer at a time. However, no closed form solution has ever been reported. In this paper, we derive a closed form buffer sizing function f(x) where f(x) gives the optimal buffer size for the buffer at position x. We show that f(x) can be expressed in terms of the Weierstrass elliptic function p(x) and its derivative p'(x)
Using neuroevolution for optimal impedance control

This paper describes the use of evolutionary algorithms to find an optimal solution for the parameters of an impedance controller represented as an artificial neural network (ANN). An impedance controller with force tracking capabilities has been evolved using evolutionary strategies which control the forces between a robotic manipulator and the environment. Simulation results show the controllerpsilas performance using a model of a two-link robot arm and a Hunt-Crossley non-linear model of the environment.
Advocacy Coalition Framework: Um Balanço Das Pesquisas Nacionais

The article aims to raise between 2000 and 2013, theses and dissertations that used the Brazilian Advocacy Coalition Framework - ACF as the main theoretical model of analysis and change public policy. The intention is to understand how the ACF has been solidified in Brazil and how academic papers are trying to resolve the criticisms made to the model. Another attempt was to dialogue with Article Weible, Sabatier, and McQueen (2009). Twenty-three theses and dissertations were found, four were discarded, thus passing nineteen for (based on) data systematization criteria. Overall, the results indicated that the model has gained space in Brazil since 2006, applied predominantly in the environmental and energy policy, using qualitative approaches and, in some studies, along with the Model of Multiple Streams. Key-Words : Advocacy Coalitions; National Theses and Dissertations; Summary of searches.
Relationship between liver aminotransferase activity and adrenal cortical hormone metabolism in tumor-bearing rats.

Summary Metabolic regulation was studied in the later stage ( i.e. , in the catabolic stage or in the cachectic stage) of AH-130 ascites tumor-bearing rats. For this purpose, liver l-alanine: 2-oxoglutarate aminotransferase activity, liver l-tyrosine: 2-oxoglutarate aminotransferase activity, and adrenocortical hormone metabolism were investigated sequentially after tumor transplantation. With regard to the adrenocortical hormone metabolism, adrenal weight, and corticosterone content, plasma corticosterone level and liver Δ 4 -3-ketosteroid hydrogenase activity were estimated. The results showed that the rise in the liver aminotransferase activity of the tumor-bearing rats was associated with an elevated plasma corticosterone level, which was ascribed to the increased hormone production, but not to the suppression of the activity of liver Δ 4 -3-ketosteroid hydrogenase, a rate-limiting enzyme in the inactivation processes of the hormone. It was proposed that the increased activity of the liver aminotransferases resulted in the wasting of the host animal through the conversion of body protein to carbohydrate and that cancer cachexia was partly a manifestation of such alterations of the metabolism in the tumor-bearing host. Further, studies were performed with nutritional conditions of high- and low-protein diets and fasting. The results were contrasted to the findings in the tumor-bearing animals to show the specificity of the metabolic regulation in the tumor-bearing animal.
Development and Evaluation of a Career Continuance Model for Company Grade Officers in the United States Army

Abstract : We present a dynamic model of company grade officer career continuance that is designed to inform future interventions intended to retain company grade officers, as well as to inform future research to enhance understanding of the retention process. Both a taxonomic model and a process model are presented, with the taxonomic model defining the constructs included in the process model, and the process model specifying relationships between constructs. A number of moderator variables are hypothesized, which are especially important for suggesting interventions to increase retention. Those moderator variables are consistent with interventions implemented as part of project STAY, and also suggest future interventions beyond the scope of that project. We conducted an initial evaluation of the model using (a) data obtained from existing officer surveys and tracking databases, and (b) evaluations of the interventions implemented as part of this project. We found empirical support for several hypotheses derived from the model, and suggest directions for future research.
Conceptual Modeling Using Conceptual Graphs

The next generation of task support systems aims at providing the relevant knowledge to knowledge-dependent activities, reducing the effort required to find or infer this knowledge from the data. In order to exploit knowledge associated with (or embedded in) databases and to migrate from data to knowledge management environments, conceptual modeling languages must offer more expressiveness than traditional modeling languages. This paper proposes a well established knowledge representation language, the conceptual graph (CG) formalism, as such a conceptual modeling language. It shows through an example, that it is suited for that purpose, allowing great expressiveness and uniformity of representation, though remaining simple to use. Its graphical interface and closeness to well-established modeling formalisms like UML and the ER model should facilitate its understanding and therefore should ease its integration into the market place. Therefore this paper emphasizes this aspect of the formalism.
Neuropsychological evidence for a dissociation in counting and subitizing

There is a long and ongoing debate about whether subitizing and counting are separable processes. In the present paper we report a single case, MH, who presents with a dissociation in subitizing and counting. MH was spared in his ability to enumerate small numbers accurately along with a marked inability to count larger numbers. We show that non-visual counting was intact and visual counting improved when a motor record of counting could be maintained. Moreover, when larger numbers of items were spatially grouped into 2 subitizable units, performance dramatically improved. However, color grouping did not aid MH's performance, despite his being sensitive to color segmentation. In addition, MH made more re-visits of inspected locations than controls, and he was less aware of a re-visitation being made. The data cannot be explained in terms of general working memory problems (verbal working memory was relatively spared), or general number comprehension problems (e.g., simple sums and counting of auditory items was intact); but they can parsimoniously be accounted for in terms of impaired visuo-spatial memory. The findings support the argument that at least some processes are specific to counting and are not required for subitization – in particular spatial coding and memory for previously inspected locations.
Global functional coupling of resting EEG rhythms is abnormal in mild cognitive impairment and Alzheimer's disease: A multicenter EEG study

Alzheimer’s disease (AD) is typically associated with an impairment of brain networks and global cognitive function in aging. In this vein, the present study tested the hypothesis that the functional coupling of resting cortical electroencephalographic (EEG) rhythms is progressively abnormal in amnesic mild cognitive impairment (MCI) and AD subjects. Eyes-closed resting EEG data were recorded (10–20 system) in 33 mild AD, 52 amnesic MCI, and 47 normal elderly subjects (Nold). EEG rhythms of interest were delta (2–4 Hz), theta (4–8 Hz), alpha1 (8–10 Hz), alpha2 (10–13 Hz), beta1 (13–20 Hz), beta2 (20–30 Hz), and gamma (30–40 Hz). The global functional coupling of the EEG rhythms was indexed by means of spectral coherence for all combinations of electrode pairs (i.e., total coherence). The main results showed that the total coherence of delta rhythms was higher in the AD than the MCI group. It was also higher in the MCI than the Nold group. Furthermore, the delta total coherence was negatively correlated wi.
DeTail: reducing the flow completion time tail in datacenter networks

Web applications have now become so sophisticated that rendering a typical page may require hundreds of intra-datacenter flows. At the same time, web sites must meet strict page creation deadlines of 200-300ms to satisfy user demands for interactivity. Long-tailed flow completion times make it challenging for web sites to meet these constraints. They are forced to choose between rendering a subset of the complex page, or delay its rendering, thus missing deadlines and sacrificing either quality or responsiveness. Either option leads to potential financial loss. In this paper, we present a new cross-layer network stack aimed at reducing the long tail of flow completion times. The approach exploits cross-layer information to reduce packet drops, prioritize latency-sensitive flows, and evenly distribute network load, effectively reducing the long tail of flow completion times. We evaluate our approach through NS-3 based simulation and Click-based implementation demonstrating our ability to consistently reduce the tail across a wide range of workloads. We often achieve reductions of over 50% in 99.9th percentile flow completion times.
The effects of instructional method upon the acquisition of inquiry skills

This study investigated the effects of Guided Discovery vs. Didactic methods of instruction upon the acquisition of certain inquiry skills. At the same time, the effects of method on the attainment of factual-conceptual achievement was assessed. Hypotheses of no interaction of the methods variable with the learner variables—sex, measured intelligence, creativity, interest in science, general scholastic achievement, and science achievement—were also tested. The sample consisted of 140 8th-grade students. The duration of the experimental unit was six weeks. The subject matter was the same for each, “Early Man in America. ” The results favored the Didactic group for the factual-conceptual achievement and the Guided Discovery for the acquisition of inquiry skills. However, in the latter there was an interaction of method with levels of measured intelligence and achievement.
Building Retargetable and Efficient Compilers for Multimedia Instruction Sets

Multimedia Instruction Sets have been introduced more than 20 years ago to speedup multimedia processing on General Purpose Processors. However, to take advantage of these instructions, developers have to cope with the low-level assembly or the equivalent C interfaces, which hinders code portability and raises development cost increases. An alternative is to let the compiler automatically generate optimized versions: ICC generates relatively efficient code for its supported platforms but does not target other processors. On the other hand, GCC targets a wide range of devices but generates less efficient code. In this paper, we present a retargetable compiler infrastructure for SIMD architectures based on three key points: a generic Multimedia Instruction Set, the combination of loop vectorization transformations with Super-word Level Parallelism and memory transfer optimizations. Three compilers, for SSE, AVX and NEON have been built using this common infrastructure.
Anthropometric obesity indices and metabolic syndrome in Japanese working men.

BACKGROUND Although the prevalence of obesity in the Japanese adult population is lower than that in the US adult population, there appears to be a trend towards increase in the prevalence of obesity in Japanese men. In this study, the usefulness of waist circumference (WC) and body mass index (BMI) determination as predictors of metabolic syndrome (MetS) was evaluated in Japanese working men. METHODS A cross-sectional study was conducted in the spring of 2007. The sample included 3,486 working men aged 35 to 59 years. The standard criteria of the International Diabetes Federation were used to determine the prevalence of MetS. The results were adjusted for age, smoking, habitual drinking and serum uric acid. To calculate the OR, MetS was tentatively defined as the presence of two or more of the following criteria in the subjects: high blood pressure, glucose intolerance, and dyslipidemia. RESULTS The prevalence of MetS was 17.0%, and it increased with age until the mid-50s. The percentages of subjects with high blood pressure, glucose intolerance, dyslipidemia and hyperuricemia were 57.3, 12.7, 29.4 and 21.3%, respectively. As compared to that in the subjects classified in the lowest WC quintile, the ORs (95% confidence interval (CI)) for MetS of a WC in the range of 76.0 to 81.4, 81.5 to 85.9, 86.0 to 90.9, and >or= 91 cm were 1.66 (1.13-2.45), 1.74 (1.13-2.67), 2.37 (1.50-3.74), and 2.84(1.73-4.64), respectively. In contrast, the OR (95% CI) for MetS of a BMI in the range of 24.5 to 26.5 and >or= 26.6 Kg/m2 were 2.43 (1.58-3.73) and 3.27 (2.04-5.27), which just about reached the significance level. CONCLUSIONS The risk of MetS was correlated with the obesity indices. However, BMI values in the high normal range were not significantly associated with the risk of MetS.
Speaker independent discriminant feature extraction for acoustic pattern-matching

Acoustic pattern-matching algorithms have recently become prominent again for automatically processing speech utterances where no prior knowledge of the spoken language is required. Applications of such technology include, but are not limited to, query-by-example search, spoken term detection and automatic word discovery. Obtaining content-aware acoustic features as independent as possible from speaker and acoustic environment variations is a key step in these algorithms. Currently, GMM posteriorgrams are found to outperform the standard MFCC features even though they were not designed to optimize the discrimination between acoustic classes. In this paper we combine the K-means clustering algorithm with the GMM posteriorgrams front-end to obtain more discriminant features. Results on a query-by-example task show that the proposed approaches outperform standard MFCC features by 7.8% absolute P@N and GMM-based posteriorgram features by 3.7% absolute P@N when using a 64-dimensional feature vector.
Optimizing Spread of Influence in Weighted Social Networks via Partial Incentives

A widely studied process of influence diffusion in social networks posits that the dynamics of influence diffusion evolves as follows: Given a graph $G=(V,E)$, representing the network, initially \emph{only} the members of a given $S\subseteq V$ are influenced; subsequently, at each round, the set of influenced nodes is augmented by all the nodes in the network that have a sufficiently large number of already influenced neighbors. The general problem is to find a small initial set of nodes that influences the whole network. In this paper we extend the previously described basic model in the following ways: firstly, we assume that there are non negative values $c(v)$ associated to each node $v\in V$, measuring how much it costs to initially influence node $v$, and the algorithmic problem is to find a set of nodes of \emph{minimum total cost} that influences the whole network; successively, we study the consequences of giving \emph{incentives} to member of the networks, and we quantify how this affects (i.e., reduces) the total costs of starting process that influences the whole network. For the two above problems we provide both hardness and algorithmic results. We also experimentally validate our algorithms via extensive simulations on real life networks.
Combat Stress Reaction: The Enduring Toll of War

In the Shadow of War. Sisters in Sorrow. Psychological Breakdown on the Battlefield. Naked on Dizengoff. Does the War End When the Shooting Stops? PTSD: The Inner Landscape. From Front Line to Home Front. If At First You Don't Succeed: Military Functioning on the Battlefield. Body and Soul. The Imprint of Trauma. Yet Once More: The Effect of Repeated Wars. Reactivation: Trauma Deepens Trauma. Is Delayed PTSD for Real? Fathers and Sons: The Transgenerational Impact of the Holocaust. Why Don't They Seek Treatment? The Silver Platter. Index.
Automatic tuning of the multiprogramming level in Sybase SQL Anywhere

This paper looks at the problem of automatically tuning the database server multiprogramming level to improve database server performance under varying workloads. We describe two tuning algorithms that were considered and how they performed under different workloads. We then present the hybrid approach that we have successfully implemented in SQL Anywhere 12. We found that the hybrid approach yielded better performance than each of the algorithms separately.
Compression and Sequence Comparison

A novel approach to measure sequences complexity and to objectively quantify two sequences similarity is presented. General genetic sequence complexity can be evaluated using sequence compression, for which we design speciic algorithms. A compression algorithm is an objective criterium to determine wether something is random or structured 5]. Every compression algorithm exploits some precise text regularities, codes them in an economic way, and then outputs a possibly shortened sequence. The fact that the resulting description is shorter than the original text, proves that the algorithm reveals a structure in choosing those regularities. This is the most interesting property of compression. In our work, we do not consider compression as a storage saving process, but as a tool to exhibit the inner structure of a text. Consider the compressor which only deals with direct repeats. It rst looks for inside the input sequence which repeats can be coded, replaces the second occurrence of each repeat by a pointer to the rst and thus performs compression. But also can it compress the input sequence with respect to another sequence, and then measures, by the way of the compression rate, what proportion of the input sequence is signiicantly made of pieces of the reference one. This second use of DNA compression yields to an objective and clearly understandable measurement of sequences similarity (see 6]). In the rst part, we outline the compression basic theoretical concepts enclosed in the Al-gorithmic Information Theory. Part two shows practical attempts of dedicated sequence compression algorithms and their results. The underlying concepts of the Algorithmic Information Theory, worked out in the 60's by A. Kolmogorov and G. Chaitin, warrant the choice of text compression as a general investigation tool for sequence analysis. The core question of this theory is: what is the essential information contained in an object ? Given that any object could be described in a text over f0; 1g, the authors deene the Kolmogorov Complexity of a text, denoted by K, as the length of the smallest program able to generate it 1 5, 3]. This idea strongly tied up the understanding of a text and his representation compression. The more compact representation is its shortest \explanation 2 ". It can be proved that Kol-mogorov Complexity does not depend on the programming language used for the smallest program 3. Hence, K which bounds possible compression, is an absolute measure. A compression algorithm cannot take advantage …
Video Captioning with Semantic Information from the Knowledge Base

Generating video description is a very challenging task due to the complex spatiotemporal information. Recently, many methods have been proposed by utilizing LSTM to generate sentence for video. Inspired by recent work in machine translation and object detection, we propose a new approach for video captioning which aims to incorporate Knowledge Base information with frame features of the video. We compare and analyze our approach with prior work and show that the large volumes information is available to generate video description. We experiment with our ideas on the S2VT model, and we demonstrate that our method outperforms the state-of-the-art on video captioning benchmarks.