Miracle-dz/UniFAR-FTUs huggingface dataset:
Update in the management of penile cancer.

PURPOSE The management of penile cancer has evolved as less invasive techniques are applied in the treatment of the primary tumor and inguinal lymph nodes. MATERIALS AND METHODS Herein we review the literature focusing on advances in the preservation of the phallus as well as less morbid procedures to evaluate and treat the groins. RESULTS Promising imaging modalities for staging are discussed. New techniques are described and tables provided for penile preservation. We also review the contemporary morbidity of modified surgical forms for evaluation of the inguinal nodes. CONCLUSIONS Advances in surgical technique have made phallic preservation possible in a greater number of primary penile cancers. The groins can be evaluated for metastasis with greater accuracy through new radiologic means as well as with less morbid modified surgical techniques.
Predicting Computer System Failures Using Support Vector Machines

Mitigating the impact of computer failure is possible if accurate failure predictions are provided. Resources, applications, and services can be scheduled around predicted failure and limit the impact. Such strategies are especially important for multi-computer systems, such as compute clusters, that experience a higher rate failure due to the large number of components. However providing accurate predictions with sufficient lead time remains a challenging problem. This paper describes a new spectrum-kernel Support Vector Machine (SVM) approach to predict failure events based on system log files. These files containmessages that represent a change of system state. While a single message in the file may not be sufficient for predicting failure, a sequence or pattern of messages may be. The approach described in this paper will use a sliding window (sub-sequence) of messages to predict the likelihood of failure. The a frequency representation of the message sub-sequences observed are then used as input to the SVM. The SVM then associates the messages to a class of failed or non-failed system. Experimental results using actual system log files from a Linux-based compute cluster indicate the proposed spectrum-kernel SVM approach has promise and can predict hard disk failure with an accuracy of 73% two days in advance.
Perceived teacher affective support in relation to emotional and motivational variables in elementary school science classrooms in Turkey

Abstract Background: In recent research, affective learning environments and affective support have been receiving increasing attention for their roles in stimulating students’ learning outcomes. Despite its raising importance, little is known about affective support in educational contexts in developing countries. Moreover, international student assessment programmes (e.g. PISA and TIMSS) reveal poor science proficiency of students in most of those countries, which provokes the question of how to make positive changes in students’ perspectives and attitudes in science. Purpose: In the current study, the purpose was to investigate the relations among perceived teacher affective support (PTAS), academic emotions (academic enjoyment, academic anxiety, and academic hopelessness), academic self-efficacy and behavioural engagement in elementary school science classrooms in Turkey. Sample: A total of 633 fourth- and fifth-grade students in eight elementary schools in Istanbul, Turkey were participated in the study. Design and methods: A self-report questionnaire was administered to participating students. The data were analysed using structural equation modelling. Results: Findings showed that PTAS was both directly and indirectly related to the given variables. PTAS was found to be significantly positively associated with students’ academic enjoyment, academic self-efficacy and behavioural engagement and significantly negatively related to their academic anxiety and academic hopelessness in science classrooms. An important finding is that the total effect of PTAS on behavioural engagement, a factor strongly associated with academic success in all disciplines, was as strong as the effect of students’ perceived academic self-efficacy beliefs in science. Conclusions: Findings suggest that PTAS may help promoting positive emotions and motivation among students in science classrooms, eventually leading to more desirable attitudes and achievement outcomes in science. Teacher affective support deserves greater recognition from researchers, educational policy-makers, administrators and teachers to build better learning conditions for all students.
An energy and power consumption analysis of FPGA routing architectures

In this work, we evaluate bi-directional and unidirectional FPGA routing architectures in terms of energy and power consumption using an updated power estimation framework compatible with VPR 5.0. The goal of this research is to help FPGA vendors find the best FPGA architectures. Initially, we make some general observations on how two types of routing architectures affect speed, area consumption, and power consumption. We observe how routing buffer sizing affects both the critical path delay and power and energy consumption of FPGAs with certain routing architectures. Our results show that uni-directional routing architecture, in all but one case, is the most energy efficient choice both in the traditional FPGA domain and the mobile domain where clock frequencies are fixed.
Sphingosine 1-Phosphate Induces Neutrophil Chemoattractant IL-8: Repression by Steroids

The bioactive sphingolipid sphingosine 1-phosphate (S1P) is found in increased amounts in the airways of asthmatics. S1P can regulate airway smooth muscle functions associated with asthmatic inflammation and remodeling, including cytokine secretion. To date however, whether S1P induces secretion of an important chemokine responsible for neutrophilia in airway inflammation – IL-8 – was unexplored. The aim of this study was to investigate whether S1P induces IL-8 gene expression and secretion to enhance neutrophil chemotaxis in vitro, as well as examine the molecular mechanisms responsible for repression by the corticosteroid dexamethasone. We show that S1P upregulates IL-8 secretion from ASM cells and enhance neutrophil chemotaxis in vitro. The corticosteroid dexamethasone significantly represses IL-8 mRNA expression and protein secretion in a concentration- and time-dependent manner. Additionally, we reveal that S1P-induced IL-8 secretion is p38 MAPK and ERK-dependent and that these key phosphoproteins act on the downstream effector mitogen- and stress-activated kinase 1 (MSK1) to control secretion of the neutrophil chemoattractant cytokine IL-8. The functional relevance of this in vitro data was demonstrated by neutrophil chemotaxis assays where S1P-induced effects can be significantly attenuated by pretreatment with dexamethasone, pharmacological inhibition of p38 MAPK- or ERK-mediated pathways, or by knocking down MSK-1 with siRNA. Taken together, our study reveals the molecular pathways responsible for IL-8 secretion from ASM cells in response to S1P and indicates ways in which the impact on IL-8-driven neutrophilia may be lessened.
Practice Concepts

Purpose: This article (a) describes a 10-week, behavioral, activities-based intervention for depression that can be implemented in nursing homes collaboratively with nursing home activities staff and (b) presents data related to its development, feasibility, and preliminary outcomes. Design and Methods: We developed BE-ACTIV, which stands for Behavioral Activities Intervention, in two pilot study phases: a treatment development phase and a feasibility–outcome phase with a small, randomized trial. We first piloted the intervention with five depressed residents in a single nursing home in collaboration with the social services and activities staff. The second phase randomized 20 residents from six nursing homes to receive either the intervention or treatment as usual. Results: The intervention was well received by residents, family, and staff members. Experience with the intervention and input from staff members resulted in modifications to streamline the intervention and improve implementation. Results suggest that BEACTIV reduced institutional barriers to participation in pleasant activities, increased resident control over activity participation, increased overall activity participation, and improved depressive symptoms. Despite low power, statistical and graphical comparisons suggest superiority of the intervention over treatment as usual. Implications: Because depression among nursing home residents is prevalent, heterogeneous, and often treatment resistant, there is a need for effective, low-cost interventions that are ecologically acceptable and efficient. BE-ACTIV is a promising intervention; it is brief, addresses institutional barriers, involves facility staff in treatment, and is acceptable to residents. As such, BE-ACTIV merits further evaluation to establish efficacy and effectiveness.
Spectrophotometric and computerized evaluation of tooth bleaching employing 10 different home-bleaching procedures: In-vitro study

Objective: The aim of this in-vitro study was to evaluate the efficacy of bleaching products, determine the applicability and validation of the measurement methods. Materials and Methods: Freshly extracted 110 human incisor teeth were stained with whole blood and hemolysate solution prior to the application of 10 different home-bleaching products. Spectrophotometric measurements of the tooth shades were performed for each specimen before and after bleaching at the 1 st , 3 rd , 7 th , and 14 days. Differences in lightness (Δl ), chroma (Δc ), hue (Δh ) values and shade changes were measured to evaluate process. Computerized digital imaging analyses to determine the color changes were performed with Photoshop CS4 software (Adobe, San Jose, CA, USA). Statistical analyses were performed with analysis of variance, Scheffe and Tukey tests. Results: In all of the test groups regardless of the material used, a significant increase in lightness and hue, and decrease of chroma were observed, as compared to the control group. After recommended bleaching applications, Δl and Δh values respectively increased in group Zaris White and Brite (ZWB) and group Pola Night and Δc values showed significant decrease in groups ZWB and Rembrandt REM3 (P < 0.05). At the end of the procedure both spectrophotometric and digital imaging analysis showed ZWB was the most effective product among the others while Yotuel and Happy Smile were the least (P < 0.05). Conclusions: Home-bleaching systems showed slower but almost permanent bleaching effect likewise office-based methods. Both software and spectrophotometric analyses have advantages such as evaluating the results objectively and numerically, also treatment outcomes could be preserved.
Using One-Sided RDMA Reads to Build a Fast, CPU-Efficient Key-Value Store

Recent technological trends indicate that future datacenter networks will incorporate High Performance Computing network features, such as ultra-low latency and CPU bypassing. How can these features be exploited in datacenter-scale systems infrastructure? In this paper, we explore the design of a distributed in-memory key-value store called Pilaf that takes advantage of Remote Direct Memory Access to achieve high performance with low CPU overhead. In Pilaf, clients directly read from the server's memory via RDMA to perform gets, which commonly dominate key-value store workloads. By contrast, put operations are serviced by the server to simplify the task of synchronizing memory accesses. To detect inconsistent RDMA reads with concurrent CPU memory modifications, we introduce the notion of self-verifying data structures that can detect read-write races without client-server coordination. Our experiments show that Pilaf achieves low latency and high throughput while consuming few CPU resources. Specifically, Pilaf can surpass 1.3 million ops/sec (90% gets) using a single CPU core compared with 55K for Memcached and 59K for Redis.
Downregulation of HIPK2 Increases Resistance of Bladder Cancer Cell to Cisplatin by Regulating Wip1

Cisplatin-based combination chemotherapy regimen is a reasonable alternative to cystectomy in advanced/metastatic bladder cancer, but acquisition of cisplatin resistance is common in patients with bladder cancer. Previous studies showed that loss of homeodomain-interacting protein kinase-2 (HIPK2) contributes to cell proliferation and tumorigenesis. However, the role of HIPK2 in regulating chemoresistance of cancer cell is not fully understood. In the present study, we found that HIPK2 mRNA and protein levels are significantly decreased in cisplatin-resistant bladder cancer cell in vivo and in vitro. Downregulation of HIPK2 increases the cell viability in a dose- and time-dependent manner during cisplatin treatment, whereas overexpression of HIPK2 reduces the cell viability. HIPK2 overexpression partially overcomes cisplatin resistance in RT4-CisR cell. Furthermore, we showed that Wip1 (wild-type p53-induced phosphatase 1) expression is upregulated in RT4-CisR cell compared with RT4 cell, and HIPK2 negatively regulates Wip1 expression in bladder cancer cell. HIPK2 and Wip1 expression is also negatively correlated after cisplatin-based combination chemotherapy in vivo. Finally, we demonstrated that overexpression of HIPK2 sensitizes chemoresistant bladder cancer cell to cisplatin by regulating Wip1 expression. Conclusions These data suggest that HIPK2/Wip1 signaling represents a novel pathway regulating chemoresistance, thus offering a new target for chemotherapy of bladder cancer.
Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection

This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11],[12].
TAMENESS FROM LARGE CARDINAL AXIOMS

Abstract We show that Shelah’s Eventual Categoricity Conjecture for successors follows from the existence of class many strongly compact cardinals. This is the first time the consistency of this conjecture has been proven. We do so by showing that every AEC with LS(K) below a strongly compact cardinal κ is < κ-tame and applying the categoricity transfer of Grossberg and VanDieren [11]. These techniques also apply to measurable and weakly compact cardinals and we prove similar tameness results under those hypotheses. We isolate a dual property to tameness, called type shortness, and show that it follows similarly from large cardinals.
Personalizing PageRank Based on Domain Profiles

Personalized versions of PageRank have been proposed to rank the results of a search engine based on a user’s topic or query of interest. This paper introduces a methodology for personalizing PageRank vectors based on URL features such as Internet domains. Users specify interest profiles as binary feature vectors where a feature corresponds to a DNS tree node. Given a profile vector, a weighted PageRank can be computed assigning a weight to each URL based on the match between the URL and the profile features. We present promising preliminary results from a small experiment in which users were allowed to select among nine URL features combining the top two levels of the DNS tree, leading to 2 pre-computed PageRank vectors from a Yahoo crawl. Personalized PageRank performed favorably compared to pure similarity based ranking and traditional PageRank.
Linear Epitopes of Paracoccidioides brasiliensis and Other Fungal Agents of Human Systemic Mycoses As Vaccine Candidates

Dimorphic fungi are agents of systemic mycoses associated with significant morbidity and frequent lethality in the Americas. Among the pathogenic species are Paracoccidioides brasiliensis and Paracoccidioides lutzii, which predominate in South America; Histoplasma capsulatum, Coccidioides posadasii, and Coccidioides immitis, and the Sporothrix spp. complex are other important pathogens. Associated with dimorphic fungi other important infections are caused by yeast such as Candida spp. and Cryptococcus spp. or mold such as Aspergillus spp. , which are also fungal agents of deadly infections. Nowadays, the actual tendency of therapy is the development of a pan-fungal vaccine. This is, however, not easy because of the complexity of eukaryotic cells and the particularities of different species and isolates. Albeit there are several experimental vaccines being studied, we will focus mainly on peptide vaccines or epitopes of T-cell receptors inducing protective fungal responses. These peptides can be carried by antibody inducing β-(1,3)-glucan oligo or polysaccharides, or be mixed with them for administration. The present review discusses the efficacy of linear peptide epitopes in the context of antifungal immunization and vaccine proposition.
Seeing the world through non rose-colored glasses: anxiety and the amygdala response to blended expressions

Anxious individuals have a greater tendency to categorize faces with ambiguous emotional expressions as fearful (Richards et al., 2002). These behavioral findings might reflect anxiety-related biases in stimulus representation within the human amygdala. Here, we used functional magnetic resonance imaging (fMRI) together with a continuous adaptation design to investigate the representation of faces from three expression continua (surprise-fear, sadness-fear, and surprise-sadness) within the amygdala and other brain regions implicated in face processing. Fifty-four healthy adult participants completed a face expression categorization task. Nineteen of these participants also viewed the same expressions presented using type 1 index 1 sequences while fMRI data were acquired. Behavioral analyses revealed an anxiety-related categorization bias in the surprise-fear continuum alone. Here, elevated anxiety was associated with a more rapid transition from surprise to fear responses as a function of percentage fear in the face presented, leading to increased fear categorizations for faces with a mid-way blend of surprise and fear. fMRI analyses revealed that high trait anxious participants also showed greater representational similarity, as indexed by greater adaptation of the Blood Oxygenation Level Dependent (BOLD) signal, between 50/50 surprise/fear expression blends and faces from the fear end of the surprise-fear continuum in both the right amygdala and right fusiform face area (FFA). No equivalent biases were observed for the other expression continua. These findings suggest that anxiety-related biases in the processing of expressions intermediate between surprise and fear may be linked to differential representation of these stimuli in the amygdala and FFA. The absence of anxiety-related biases for the sad-fear continuum might reflect intermediate expressions from the surprise-fear continuum being most ambiguous in threat-relevance.
An Approach for Mining Similarity Profiled Temporal Association Patterns Using Gaussian Based Dissimilarity Measure

The problem of mining frequent patterns in non-temporal databases is studied extensively. Conventional frequent pattern algorithms are not applicable to find temporal frequent items from the temporal databases. Given a reference support time sequence, the problem of mining similar temporal association patterns has been the current interest among the researchers working in the area of temporal databases. The main objective of this research is to propose and validate the suitability of Gaussian distribution based dissimilarity measure to find similar and dissimilar temporal association patterns of interest. The measure designed serves as similarity measure for finding the similar temporal association patterns. Finally, in this research, we consider the problem of mining similarity profiled temporal patterns from the set of time stamped transaction of temporal database using proposed measure. We show using a case study how the proposed dissimilarity measure may be used to find the temporal frequent patterns and compare the same with the work carried in the literature. The proposed measure has the fixed lower bound and upper bound values as 0 and 1 respectively which is its advantage as compared to Euclidean distance measure which has no fixed upper bound.
Artificial Neural Networks for developing localization framework in Wireless Sensor Networks

Intelligent sensing, communication, and computing is leading the development of Wireless Sensor Networks (WSNs) and its applications. Artificial Neural Network (ANNs) is being extensively used to develop localization framework in WSN. In this paper, we present a comparative analysis of some conjugate gradient based Feedforward Artificial Neural Network (FFANNs) for developing localization framework in wireless sensor networks (WSNs). Localization is the process by which the sensor nodes in the network can identify their own location in the overall network. Localisation in WSN plays a crucial role in implementing myriad of applications such as healthcare management, disaster management, environment management, and agriculture management. Artificial neural network based localization framework are gaining importance due to faster speed of convergence and low cost of computation. We present analysis of conjugate gradient backpropagation with Powell-Beale restarts, conjugate gradient backpropagation with Fletcher-Reeves update, conjugate gradient backpropagation with Polak-Ribiere updates, one-step secant, and scaled conjugate gradient backpropagation training algorithms in this paper. Comprehensive evaluation of these training algorithms is done in perfect simulation scenario. The proposed method effectively demonstrates that conjugate gradient FFANNs based sensor motes can be designed for developing cost-effective localization framework.
EVOLUTION OF GASEOUS DISK VISCOSITY DRIVEN BY SUPERNOVA EXPLOSIONS IN STAR-FORMING GALAXIES AT HIGH REDSHIFT

Motivated by Genzel et al.'s observations of high-redshift star-forming galaxies, containing clumpy and turbulent rings or disks, we build a set of equations describing the dynamical evolution of gaseous disks with inclusion of star formation and its feedback. Transport of angular momentum is due to “turbulent” viscosity induced by supernova explosions in the star formation region. Analytical solutions of the equations are found for the initial cases of a gaseous ring and the integrated form for a gaseous disk, respectively. For a ring with enough low viscosity, it evolves in a slow process of gaseous diffusion and star formation near the initial radius. For a high viscosity, the ring rapidly diffuses in the early phase. The diffusion drives the ring into a region with a low viscosity and starts the second phase undergoing pile-up of gas at a radius following the decreased viscosity torque. The third is a sharply decreasing phase because of star formation consumption of gas and efficient transportation of gas inward forming a stellar disk. We apply the model to two z ∼ 2 galaxies BX 482 and BzK 6004, and find that they are undergoing a decline in their star formation activity.