Miracle-dz/UniFAR-FTUs huggingface dataset:
Including service learning in the undergraduate communication sciences and disorders curriculum: benefits, challenges, and strategies for success.

PURPOSE To describe some of the benefits of service learning (SL), considerations in course development and construction, and implementation and outcomes of an SL course in the undergraduate communication sciences and disorders (CSD) program at a small, public university in northwest Washington. METHOD A review of the literature on SL and a description of the author's experience in course development are provided on the basis of a computerized database search, library search, and discussions with the Western Washington University Center for Service Learning. CONCLUSIONS Teaching an SL course can present challenges to both faculty and students; nonetheless, incorporating SL into the undergraduate CSD curriculum is an excellent way of enriching the academic experience and improving critical-thinking skills of young students. SL provides hands-on opportunities for students to apply what they are learning in their CSD classes to real-world contexts, gain a better understanding of course content through engagement in real situations, and integrate information from a variety of courses in and outside of their major.
Intelligence in Williams Syndrome Is Related to STX1A, Which Encodes a Component of the Presynaptic SNARE Complex

Although genetics is the most significant known determinant of human intelligence, specific gene contributions remain largely unknown. To accelerate understanding in this area, we have taken a new approach by studying the relationship between quantitative gene expression and intelligence in a cohort of 65 patients with Williams Syndrome (WS), a neurodevelopmental disorder caused by a 1.5 Mb deletion on chromosome 7q11.23. We find that variation in the transcript levels of the brain gene STX1A correlates significantly with intelligence in WS patients measured by principal component analysis (PCA) of standardized WAIS-R subtests, r = 0.40 (Pearson correlation, Bonferroni corrected p-value = 0.007), accounting for 15.6% of the cognitive variation. These results suggest that syntaxin 1A, a neuronal regulator of presynaptic vesicle release, may play a role in WS and be a component of the cellular pathway determining human intelligence.
Un cadre expérimental pour les Sciences de la Parole (An experimental framework for speech sciences) [in French]

An experimental framework for speech sciences This article is a position paper in favor of the establishment of a theoretical and practical framework to bring out an empirical science of speech, based on the contribution of all the sciences whose object of study is the speech. Central to this re-convergence is the idea that automatic systems can be used as instruments to explore large amounts of data at our disposal and to derive new linguistic knowledge which, in turn, will allow to improve the models used in the automatic systems. Some crucial points are discussed, such as the definition of the observable, the study of the residual as a diagnostic of the gap between modeling and reality, and the development of instrumental centers for the sharing of development and maintenance of these complex instruments which are automatic speech processing systems.
Spreading the load: Antigen transfer between migratory and lymph node‐resident dendritic cells promotes T‐cell priming

Dendritic cells (DC) are specialized in the processing and presentation of antigen for the activation of lymphocytes. Multiple subsets of DCs exist with distinct functions and roles in the initiation of immune responses. DCs found within tissues acquire antigens or become infected by pathogens and migrate to local draining lymph nodes (LN) where they can directly stimulate T cells. These migratory DCs can also transfer antigens to LN‐resident DCs and may indirectly enhance T cell priming. In this issue of the European Journal of Immunology, Gurevich et al. [Eur. J. Immunol. 2017. 47: 1802–1818] elegantly demonstrate the influence of the transfer of antigen from migratory DCs to resident DCs on the dynamics of CD8 T‐cell priming in mice. Using both in vitro imaging to visualise antigen dissemination and intravital 2‐photon microscopy to track T cell clustering with migratory and resident DCs, antigen‐donor DC were found to efficiently distribute antigen to recipient DC. This process, which involved LFA‐1, enhanced the recruitment of CD8+ T cells into the response and rescued priming when DCs were impaired in presentation capacity. Together, these findings shed light on the dynamics of the transfer of antigens between DCs in vivo for the efficient priming of cytotoxic T cell responses.
Anti-Spoofing Method for Iris Recognition by Combining the Optical and Textural Features of Human Eye

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye’s optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.
Using Active Scanning to Identify Wireless NICs

Computer networks have become increasingly ubiquitous. However, with the increase in networked applications, there has also been an increase in difficulty to manage and secure these networks. The proliferation of 802.11 wireless networks has heightened this problem by extending networks beyond physical boundaries. We propose the use of spectral analysis to identify the type of wireless network interface card (NIC). This mechanism can be applied to support the detection of unauthorized systems that use NICs which are different from that of a legitimate system. We focus on active scanning, a vaguely specified mechanism required by the 802.11 standard that is implemented in the hardware and software of the wireless NIC. We show that the implementation of this function influences the transmission patterns of a wireless stream that are observable through traffic analysis. Our mechanism for NIC identification uses signal processing to analyze the periodicity embedded in the wireless traffic caused by active scanning. A stable spectral profile is created from the periodic components of the traffic and used for the identity of the wireless NIC. We show that we can distinguish between NICs manufactured by different vendors using the spectral profile
Isolation and characterization of phytoconstituents from Chlorophytum borivilianum

Background: The present communication deals with the identification and characterization of bioactive principles from the roots of Chlorophytum borivilianum. Method: Methanolic extract and its fractions were used to isolate different phytoconstituents. The structures of isolated compounds were characterized and elucidated with chemical and spectroscopic techniques such as Infra Red, Nuclear Mass Resonace and Mass spectroscopy experiments. Fatty acids were characterized by GC-MS analysis. Result: Three Fatty acids were isolated and confirmed. One sterol stigmasterol was isolated. One new saponin named as Chlorophytoside-I (3β, 5α, 22R, 25R)-26-(β-D-glucopyranosyloxy)-22-hydroxy-furostan-12-one-3 yl O-β-D-galactopyranosyl (1-4) glucopyranoside was isolated. Conclusion: The roots of Chlorophytum borivilianum contain three important fatty acids, common sterol stigmasterol and one furostanol saponins.
Dealing with Dangerous Data: Part-Whole Validation for Low Incident, High Risk Data

In certain situations, syntactically valid, but incorrect, data entered into a database can result in near-immediate, catastrophic financial losses for an organization. Examples include: omitting zeros in prices of goods on e-commerce sites; and financial fraud where data is directly entered into databases, bypassing application-level financial checks. Such "dangerous data" can, and should, be detected, because it deviates substantially from the statistical properties of existing data. Detection of this kind of problem requires comparing individual data items to a large amount of existing data in the database at run-time. Furthermore, the identification of errors is probabilistic, rather than deterministic, in nature. This research proposes part-whole validation as an approach to addressing the dangerous data situation. Part-whole validation addresses fundamental issues in database management, for example, integrity maintenance. Illustrative and representative examples are first defined, and analyzed. Then, an architecture for part-whole validation is presented and implemented in a prototype to illustrate the feasibility of the research.
A Non-Stochastic Learning Approach to Energy Efficient Mobility Management

Energy efficient mobility management is an important problem in modern wireless networks with heterogeneous cell sizes and increased nodes densities. We show that optimization-based mobility protocols cannot achieve long-term optimal energy consumption, particularly for ultra-dense networks (UDNs). To address the complex dynamics of UDN, we propose a non-stochastic online-learning approach, which does not make any assumption on the statistical behavior of the small base station (SBS) activities. In addition, we introduce handover cost to the overall energy consumption, which forces the resulting solution to explicitly minimize frequent handovers. The proposed batched randomization with exponential weighting (BREW) algorithm relies on batching to explore in bulk, and hence reduces unnecessary handovers. We prove that the regret of BREW is sublinear in time, thus guaranteeing its convergence to the optimal SBS selection. We further study the robustness of the BREW algorithm to delayed or missing feedback. Moreover, we study the setting where SBSs can be dynamically turned ON and OFF. We prove that sublinear regret is impossible with respect to arbitrary SBS ON/OFF, and then develop a novel learning strategy, called ranking expert (RE), that simultaneously takes into account the handover cost and the availability of SBS. To address the high complexity of RE, we propose a contextual ranking expert (CRE) algorithm that only assigns experts in a given context. Rigorous regret bounds are proved for both RE and CRE with respect to the best expert. Simulations show that not only do the proposed mobility algorithms greatly reduce the system energy consumption, but they are also robust to various dynamics which are common in practical ultra-dense wireless networks.
Leukocyte Structural Adaptations in Response to Hemodynamic Forces: Tension Transmitted Through VLA-4 Activates Upstream Rap1, PI3K, and Rac-Dependent Actin Polymerization

During inflammation, leukocytes modulate α4β1(VLA-4) integrin avidity in order to rapidly stabilize nascent adhesive contacts to VCAM-1-expressing endothelial cells and resist detachment forces imparted by the flowing blood. Linkage to the actin cytoskeleton is critical for integrin function, yet the exact role of the actin cytoskeleton in leukocyte adhesion stabilization under conditions of fluid flow remains poorly understood. We modeled leukocyte (U937 cell, mouse lymphocyte and human monocyte) arrest and adhesion stabilization through the use of a parallel plate flow chamber and visualized cells by phase contrast or fluorescent confocal microscopy. Live cell imaging with Lifeact-transfected U937 cells revealed that mechanical forces imparted by fluid flow induced formation of upstream tension-bearing anchors attached to the VCAM-1-coated surface. Scanning electron microscopy confirmed that flow-induced mechanical force culminates in the formation of structures that anchor monocyte adhesion. These structures are critical for adhesion stabilization, since disruption of actin polymerization dramatically inhibited VLA-4-dependent resistance to detachment, but did not affect VLA-4 expression, affinity modulation, and clustering or constitutive linkage to F-actin. Transfection of
Energy-aware resource allocation

This paper deals with the reduction of energy consumption in large scale systems, especially by taking into account the impact of energy consumption for server consolidation. Decreasing the number of physical hosts used while ensuring a certain level of quality of services is the goal of our approach. We introduce a metric called energetic yield which represents the quality of a task placement on a subset of machines, while taking into account quality of service and energy efficiency aspects. It measures the difference between resources required by a job and what the system allocates ultimately, while trying to save energy. Our work aims at minimizing this difference. We propose placement heuristics that are compared to the optimal solution and to a related system. In this paper, we present a set of experiments showing the relevance of this metric in order to reduce significantly energy consumption.
Activation of MAPK overrides the termination of myelin growth and replaces Nrg1/ErbB3 signals during Schwann cell development and myelination

Myelination depends on the synthesis of myelin transcripts and proteins and is controlled by Nrg1/ErbB/Shp2 signaling. Sheean et al. developed a pulse labeling strategy to measure the dynamics of myelin protein production in mice and found that protein synthesis is dampened in the maturing postnatal peripheral nervous system. Sustained activation of MAPK signaling overcomes the signals that end myelination and compensates for the absence of ErbB3 or Shp2 during Schwann cell development and myelination.
Healthy Behavior Change and Cardiovascular Outcomes in Newly Diagnosed Type 2 Diabetic Patients: A Cohort Analysis of the ADDITION-Cambridge Study

OBJECTIVE To examine whether improvements in health behaviors are associated with reduced risk of cardiovascular disease (CVD) in individuals with newly diagnosed type 2 diabetes. RESEARCH DESIGN AND METHODS Population-based prospective cohort study of 867 newly diagnosed diabetic patients aged between 40 and 69 years from the treatment phase of the ADDITION-Cambridge study. Because the results for all analyses were similar by trial arm, data were pooled, and results were presented for the whole cohort. Participants were identified via population-based stepwise screening between 2002 and 2006, and underwent assessment of physical activity (European Prospective Investigation into Cancer-Norfolk Physical Activity Questionnaire), diet (plasma vitamin C and self-report), and alcohol consumption (self-report) at baseline and 1 year. A composite primary CVD outcome was examined, comprised of cardiovascular mortality, nonfatal myocardial infarction, nonfatal stroke, and revascularization. RESULTS After a median (interquartile range) follow-up period of 5.0 years (1.3 years), 6% of the cohort experienced a CVD event (12.2 per 1,000 person-years; 95% CI 9.3–15.9). CVD risk was inversely related to the number of positive health behaviors changed in the year after diabetes diagnosis. The relative risk for primary CVD event in individuals who did not change any health behavior compared with those who adopted three/four healthy behaviors was 4.17 (95% CI 1.02–17.09), adjusting for age, sex, study group, social class, occupation, and prescription of cardioprotective medication (P for trend = 0.005). CONCLUSIONS CVD risk was inversely associated with the number of healthy behavior changes adopted in the year after the diagnosis of diabetes. Interventions that promote early achievement of these goals in patients with newly diagnosed diabetes could help reduce the burden of diabetes-related morbidity and mortality.
Chronic allograft nephropathy

Purpose of reviewDespite dramatic declines in acute rejection and early graft failure, long-term outcomes after kidney transplantation have improved little during the past 25 years. Most late allograft failure is attributed to chronic allograft nephropathy, but this is a clinicopathological description and not a diagnosis, and its pathogenesis and treatment are largely unknown. Recent findingsRecent studies suggest that acute rejection during the first few months, and calcineurin inhibitor toxicity thereafter, may both contribute to chronic allograft nephropathy. There is also accumulating evidence that injury from antibody-mediated rejection may play an important pathogenic role in at least some patients with chronic allograft nephropathy, particularly those with transplant glomerulopathy. Therapeutic measures, including protocols to reduce calcineurin inhibitor exposure, remain largely unproven. SummaryUnderstanding why so many kidney allografts fail, despite effective preventive measures for early acute rejection, is one of the most important areas of research in kidney transplantation today.
Smoking cessation among African American and white smokers in the Veterans Affairs health care system.

OBJECTIVES We examined whether a proactive care smoking cessation intervention designed to overcome barriers to treatment would be especially effective at increasing cessation among African Americans receiving care in the Veterans Health Administration. METHODS We analyzed data from a randomized controlled trial, the Veterans Victory over Tobacco study, involving a population-based electronic registry of current smokers (702 African Americans, 1569 whites) and assessed 6-month prolonged smoking abstinence at 1 year via a follow-up survey of all current smokers. We also examined candidate risk adjustors for the race effect on smoking abstinence. RESULTS The interaction between patient race and intervention condition (proactive care vs. usual care) was not significant. Overall, African Americans had higher quit rates than Whites (13% vs. 9%; P < .006) regardless of condition. CONCLUSIONS African Americans quit at higher rates than Whites. These findings may be a result of the large number of veterans receiving smoking cessation services and the lack of racial differences in receipt of these services as well as racial differences in smoking history, self-efficacy, and motivation to quit that favor African Americans.
Possibilities for Managing Trust in P2P Networks (EPFL Technical Report IC/2004/84)

Reputation systems ofier a viable solution to the old problem of encouraging trustworthy behavior in online communities. Their key presumptions are that the participants of an online community engage in repeated interactions and that the information about their past doings is informative of their future performance and as such will in∞uence it. Thus, collecting, processing, and disseminating the feedback about the participants’pastbehaviorisexpectedtoboosttheirtrustworthiness. We investigate and classify the possibilities appeared so far in the literature todothisinthecontextofP2Pnetworks. Weidentifythreebroadclasses of approaches: social networks formation, probabilistic estimation techniques and game-theoretic reputation models. They difier greatly in the accompanyingtrustsemantics,mainlyre∞ectedinthepossibilitiesofiered tothedecisionmakers,andtheimplementationoverheadtheyincur. The paperbridgesthegapbetweentheexistingworksontrustandreputation management in decentralized networks, driven by the characteristics of thetargetenvironmentandtheformalgame-theoretictreatmentofreputation,aimingataclearandanalyticaldecisionmaking. Thisviewleads ustoidentifytheopenresearchissues,orientedtowardsbothe‐cientand analytical usageofreputation tobuild trustinP2Pnetworks.
Task-Level Dynamic Voltage Scaling for Embedded System Design: Recent Theoretical Results

It is generally accepted that dynamic voltage scaling (DVS) is one of the most effective techniques of energy minimization for real-time applications in embedded system design. The effectiveness comes from the fact that the amount of energy consumption is quadractically proportional to the voltage applied to the processor. The penalty is the execution delay, which is linearly and inversely proportional to the voltage. According to the granularity of tasks to which voltage scaling is applied, the DVS problem is divided into two subproblems: inter-task DVS problem, in which the determination of the voltage is carried out on a task-by-task basis and the voltage assigned to the task is unchanged during the whole execution of the task, and intra-task DVS problem, in which the operating voltage of a task is dynamically adjusted according to the execution behavior to reflect the changes of the required number of cycles to finish the task before the deadline. Frequent voltage transitions may cause an adverse effect on energy minimization due to the increase of the overhead of transition time and energy. In addition, DVS needs to be carefully applied so that the dynamically varying chip temperature should not exceed a certain threshold because a drastic increase of chip temperature is highly likely to cause system function failure. This paper reviews representative works on the theoretical solutions to DVS problems regarding inter-task DVS, intra-task DVS, voltage transition, and thermal-aware DVS.
Evaluation of the Parameters of the Green Supplier Selection Decision in Textile Industry

Green issues are a popular topic in today’s business life, and it is possible to see green products or advertisements in many different places due to the demand for a healthier lifestyle. Companies that are willing to be a part of the green concept should integrate this philosophy in all departments. As a result, the procurement might be seen a crucial part of this integration. However, in the emerging markets, green issues might be pushed into the background due to the competitive environment. In this study, we investigated green and other parameters in the supplier selection decision in textile industry. A decision criteria list was created and evaluated by 28 experts using the fuzzy analytic hierarchy process. The results showed that green issues have an influence on the decision environment; however, classical parameters, such as cost, delivery reliability, quality, service, and strategic alliance still carry more priority compared to green criteria consisting of environmental management, green products, and pollution control.
Modern Tools to Support DoD Software Intensive System of Systems Cost Estimation

Many Department of Defense (DoD) organizations are attempting to provide new system capabilities through the net-centric integration of existing software-intensive systems into a new system often referred to as Software-Intensive System of Systems (SISOS). The goal of this approach is to build on existing capabilities to produce new capabilities not provided by the existing systems in a timely and cost-effective manner. Many of these new SISOS efforts such as the Future Combat Systems are of a size and complexity unlike their predecessor systems and cost estimation tools such as the Constructive Cost Model (COCOMO) suite are undergoing significant enhancements to address these challenges. This article describes the unique challenges of SISOS cost estimation, how current tools are changing to support these challenges, as well as on-going efforts to further support SISOS cost estimation needs. It summarizes key information in DACS Report Number 347336.