Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of transforming growth factor beta by human T lymphocytes and its potential role in the regulation of T cell growth

This study examines the potential role of transforming growth factor beta (TGF-beta) in the regulation of human T lymphocyte proliferation, and proposes that TGF-beta is an important autoregulatory lymphokine that limits T lymphocyte clonal expansion, and that TGF-beta production by T lymphocytes is important in T cell interactions with other cell types. TGF-beta was shown to inhibit IL-2-dependent T cell proliferation. The addition of picograms amounts of TGF-beta to cultures of IL-2-stimulated human T lymphocytes suppressed DNA synthesis by 60-80%. A potential mechanism of this inhibition was found. TGF-beta inhibited IL-2-induced upregulation of the IL-2 and transferrin receptors. Specific high-affinity receptors for TGF-beta were found both on resting and activated T cells. Cellular activation was shown to result in a five- to sixfold increase in the number of TGF- beta receptors on a per cell basis, without a change in the affinity of the receptor. Finally, the observations that activated T cells produce TGF-beta mRNA and that TGF-beta biologic activity is present in supernatants conditioned by activated T cells is strong evidence that T cells themselves are a source of TGF-beta. Resting T cells were found to have low to undetectable levels of TGF-beta mRNA, while PHA activation resulted in a rapid increase in TGF-beta mRNA levels (within 2 h). Both T4 and T8 lymphocytes were found to make mRNA for TGF-beta upon activation. Using both a soft agar assay and a competitive binding assay, TGF-beta biologic activity was found in supernatants conditioned by T cells; T cell activation resulted in a 10-50-fold increase in TGF- beta production. Thus, TGF-beta may be an important antigen-nonspecific regulator of human T cell proliferation, and important in T cell interaction with other cell types whose cellular functions are modulated by TGF-beta.
The analysis of 2DPSK signal transmission characteristics of terrestrial mobile satellite channel

According to the defect of satellite mobile communication channel with remote transmission distance, serious signal fading and severe interference, based on in-depth theoretical research and simulation analysis, full shadow channel model which is applicable to the characteristics of satellite mobile communication channel was given. On this basis, Bit error rate (BER) of 2DPSK signal transmission of narrowband and broadband modulation system were compared, simulation shows that using broadband communication system model can effectively ameliorate transmission performance deterioration due to multipath fading and shadowing. When BER is 10-3 and elevation is 60 degree in the broadband single user model, there is 4.6dB SNR gain relative to the narrow band system. In addition, some essential conclusions about the transfer characteristic and its computational formula were presented. And also some important guidance was given for actual mobile communication of non-geostationary orbit satellite.
The Many Roles of Statins in Ischemic Stroke

Stroke is the third leading cause of human death. Endothelial dysfunction, thrombogenesis, inflammatory and oxidative stress damage, and angiogenesis play an important role in cerebral ischemic pathogenesis and represent a target for prevention and treatment. Statins have been found to improve endothelial function, modulate thrombogenesis, attenuate inflammatory and oxidative stress damage, and facilitate angiogenesis far beyond lowering cholesterol levels. Statins have also been proved to significantly decrease cardiovascular risk and to improve clinical outcome. Could statins be the new candidate agent for the prevention and therapy in ischemic stroke? In recent years, a vast expansion in the understanding of the pathophysiology of ischemic stroke and the pleiotropic effects of statins has occurred and clinical trials involving statins for the prevention and treatment of ischemic stroke have begun. These facts force us to revisit ischemic stroke and consider new strategies for prevention and treatment. Here, we survey the important developments in the non-lipid dependent pleiotropic effects and clinical effects of statins in ischemic stroke.
Empirical Estimation of the Term Structure of Implicit Discount Rates in Security Valuation

In this paper we use a reformulation of the residual income (RI) valuation model to generate estimates of the term structure of discount rates (cost of capital) implicit in security prices. We use future realisations of residual income as proxies of their present day expectations and reduce the impact of measurement error in the forecast values by transforming them into a current value plus a series of change variables. Different lengths of the forecast window lead to the coefficients on the current realisations of earnings and book value incorporating different combinations of implicit discount rates. By comparing the coefficients on these two variables for different forecast windows estimates of implicit discount rates can be generated. Terminal values are incorporated within the coefficients on current realisations of earnings and book value. As our estimates of cost of capital are made from comparisons of the earnings and book value coefficients from valuation models of different forecast length we are able to eliminate the impact of terminal value assumptions from our cost of capital estimates. The results indicate no specific pattern to implicit discount rates that would indicate either short termism or excessive optimism about future earnings growth.
Helping Users Protect Themselves from e-Criminals in Click-Based Graphical Passwords

graphical passwords, like other user-selected passwords, suffer from predictability problems. With click-based graphical passwords, user click-points form hotspots, areas of the image that are more likely to be selected, which e-criminals can predict and use to launch dictionary attacks. Our system, Persuasive Cued Click-Points, helps users select more random click-points and reduces the appearance of hotspots while still maintaining usability.
Help, Anyone? A User Study For Modeling Robotic Behavior To Mitigate Malfunctions With The Help Of The User

Service robots for the domestic environment are intended to autonomously provide support for their users. However, state-of-the-art robots still often get stuck in failure situations leading to breakdowns in the interaction flow from which the robot cannot recover alone. We performed a multi-user Wizard-of-Oz experiment in which we manipulated the robot's behavior in such a way that it appeared unexpected and malfunctioning, and asked participants to help the robot in order to restore the interaction flow. We examined how participants reacted to the robot's error, its subsequent request for help and how it changed their perception of the robot with respect to perceived intelligence, likability, and task contribution. As interaction scenario we used a game of building Lego models performed by user dyads. In total 38 participants interacted with the robot and helped in malfunctioning situations. We report two major findings: (1) in user dyads, the user who gave the last command followed by the user who is closer is more likely to help (2) malfunctions that can be actively fixed by the user seem not to negatively impact perceived intelligence and likability ratings. This work offers insights in how far user support can be a strategy for domestic service robots to recover from repeating malfunctions.
Modeling of dielectric charging in RF MEMS capacitive switches

A unified, macroscopic, one‐dimensional model is presented for the quantitative description of the process of dielectric charging in RF MEMS capacitive switches. The model provides for the direct incorporation of various physical factors known to impact dielectric charging, such as surface roughness, material inhomogeneity, and electric field‐dependent conduction in the dielectric. The values of the various parameters used in the model are extracted from experimental data. The proposed model serves as a generalization of various earlier models reported in the literature for the quantitative description of dielectric charging. Its formulation is such that it can be incorporated in a straightforward manner in coupled electro‐mechanical modeling schemes for the computer‐aided analysis of RF MEMS capacitive switches. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 3188–3192, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22903
International Hospitality Management

This study of 51 hotel-school graduates working overseas determined that most felt somewhat ill-prepared for those job assignments. When asked to rate the personal and professional attributes of greatest importance for Skills international management, they gave the highest scores to cultural sensitivity, interpersonal skills, managerial flexibility, adaptive leadership, motivation and interest, intercultural competence (including etiquette), the ability to work with limited resources, and understanding of international business. Yet few had actually received any formal training along those lines. In fact, there was a negative correlation between importance and development of management skills: the more important a skill was perceived by this study's particpants, the less frequently it was developed by prospective overseas managers. The participants indicated that the most-effective training activities preparatory to international assignments were internships abroad, second-language studies, and study overseas.
Optimization of a class of non-convex objectives on the Gaussian MIMO multiple access channel: Algorithm development and convergence analysis

In this paper we develop an algorithm for computing the optimal transmission parameters, which include the transmission covariance, the time-shares and the user-orderings that minimize a particular class of objectives defined over the capacity region of Gaussian multiple antenna multiple access channels. This class includes objectives that are twice-differentiable, non-increasing and convex in the users' rates, but not necessarily convex in the aforementioned transmission parameters. As such, this class includes design objectives that are non-convex and that, without the proposed algorithm, are difficult to solve in general. The proposed algorithm is iterative with polynomial complexity per iteration and with convergence to the global optimal guaranteed. The utility of this algorithm is illustrated via a numerical example for maximizing proportional fairness.
Intelligent Agents as a Modeling Paradigm

Intelligent software agents have been used in many applications because they provide useful integrated features that are not available in “traditional” types of software (e.g., abilities to sense the environment, reason, and interact with other agents). Although the usefulness of agents is in having such capabilities, methods and tools for developing them have focused on practical physical representation rather than accurate conceptualizations of these functions. However, intelligent agents should closely mimic aspects of the environment in which they operate. In the physical sciences, a conceptual model of a problem can lead to better theories and explanations about the area. Therefore, we ask, can an intelligent agent conceptual framework, properly defined, be used to model complex interactions in various social science disciplines? The constructs used in the implementation of intelligent agents may not be appropriate at the conceptual level, as they refer to software concepts rather than to application domain concepts. We propose to use a combination of the systems approach and Bunge’s ontology as adapted to information systems, to guide us in defining intelligent agent concepts. The systems approach will be used to define the components of the intelligent agents and ontology will be used to understand the configurations and interrelationships between the components. We will then provide a graphical representation of these concepts for modeling purposes. As a proof of concept for the proposed conceptual model, we applied it to a marketing problem and implemented it in an agent-based programming environment. Using the conceptual model, the user was able to quickly visualize the complex interactions of the agents. The use of the conceptual representation even sparked an investigation of previously neglected causal factors which led to a better understanding of the problem. Therefore, our intelligent agent framework can graphically model phenomena in the social sciences. This work also provides a theoretically driven concept of intelligent agent components and a definition of the interrelationships between these concepts. Further research avenues are also discussed.
Evolvability in Developmental Systems

The developmental mapping from genotype to phenotype is responsible for much of the evolvability (adaptive variation) exhibited in nature (Raff 1996; Kirschner & Gerhart 1998; Wagner & Altenberg 1996). Random mutations are transformed into structured phenotypic variation and the effects of deleterious mutations are mitigated. This mechanism is powerful precisely because search becomes constrained, generating only highly adaptive phenotypes. In evolutionary computation, acquiring such constraints and bias is akin to learning the underlying structure of a particular fitness function; such structure can be exploited to improve search efficiency. For example, when evolving a design for a coffee table, an evolvable encoding would discover that table height and surface area correspond to fundamental axes of variation, constraining search to solutions that maintain constant height and high surface area (Hornby 2004). Such evolvability is exhibited in indirect encodings, particularly developmental systems. Evolvability helps find good “trajectories” through the search space, not just good fitness peaks. However, selection for evolvability is not always possible with many fitness functions; in general evolution is opportunistic, and will take large immediate fitness gains over smaller fitness gains that may lead to better (e.g. more evolvable) parts of the search space. Thus selecting for evolvability and selecting for good solutions can be viewed as generally antagonistic goals. In other words, even when using developmental encodings, there may be no real selection pressure to optimize the genomic representation for evolvability. This observation may help explain in general why in some cases developmental encodings do not perform well when compared to simpler direct encodings (Reisinger & Miikkulainen 2006). One way in which a consistent selection pressure for evolvability can be generated is by systematically changing the fitness function over time (Kashtan & Alon 2005). However if the representation itself is not adaptable, as in the case of direct encodings, this selection pressure is ignored, leading to highly-optimal, but “brittle” solutions. We believe that this phenomenon may be responsible for much of the cycling and disengagement behavior seen in competitive coevolution; since direct encodings cannot store information about search, populations may be prone to “forgetting” past
WordSleuth Stanton 2 WordSleuth : Deducing Social Connotations from Syntactic Clues

0. Abstract The realm of social and emotional connotation is often thought to be the purview of humans rather than machines. Namely, humans are generally capable of recognizing social connotations including emotions (such as embarrassment), intentions (deception and persuading), attitudes (confidence and disbelief), and tone (formality, politeness, rudeness), and recent work has suggested that machines may also be capable of this feat (Pearl and Steyvers 2010). This study extends the work done by Pearl and Steyvers, improving the data gathering methodology, feature extraction, and machine learning classification. Prior to the WordSleuth project, a major barrier to researching social cues transmitted through text has been a lack of annotated data. WordSleuth, an online Game-With-a-Purpose (von Ahn 2006), solves this problem, creating an effective means of encouraging a wide variety of participants to generate and annotate data. Salient linguistic features can then be extracted from the data gathered and used to train and test machine learning algorithms, effectively teaching machines to identify social connotations in text. In particular, as machines still currently lag behind human capabilities, this study extends Pearl and Steyvers' work by examining more complex linguistic features and exploring more sophisticated machine learning methods, with the aim of substantially improving machine recognition of social connotation.
SPECTRAL GEOMETRY OF THE STEKLOV PROBLEM

The Steklov problem is an eigenvalue problem with the spectral parameter in the boundary conditions, which has various applications. Its spectrum coincides with that of the Dirichlet-to-Neumann operator. Over the past years, there has been a growing interest in the Steklov problem from the viewpoint of spectral geometry. While this problem shares some common properties with its more familiar Dirichlet and Neumann cousins, its eigenval- ues and eigenfunctions have a number of distinctive geometric features, which makes the subject especially appealing. In this survey we discuss some recent advances and open questions, particularly in the study of spectral asymptotics, spectral invariants, eigenvalue estimates, and nodal geometry.
Theft and losses in Turkish electricity sector

Since the 1980s, electricity industries in many countries have been undergoing privatization and liberalization in order to generate improvements in efficiency and quality. Liberalization and privatization can only be successful if privatized utilities can be financially viable on their own and not rely on government subsidies except for those that are designed for social objectives such as universal service. In the case of Turkey, an important impediment to privatization and liberalization are thefts and losses that generate large asymmetries in costs across different regions. In international comparisons these costs are exceptionally high and they threaten the economic and political feasibility of reform. This master thesis undertakes an econometric analysis to identify factors that cause such large variances in electricity theft-losses across different regions of Turkey. Once these factors are identified, empirical results are then used to derive implications for both privatizations as well as principles that should guide tariff design, including possible subsidy mechanisms.
Unsupervised imaging, registration and archiving of tissue microarrays

Tissue microarray (TMA) technology offers several advantages over traditional methods of specimen preparation by maximizing limited tissue resources and providing the means for visualizing molecular targets. Currently, the primary methods used to evaluate arrays involves the interactive review of TMA samples while they are viewed by microscope and are subjectively evaluated and scored. The process is slow, tedious and prone to error. In order to facilitate large-scale, multi-institutional studies a more automated and reliable means for processing tissue microarrays is needed. We have developed a web-based prototype which features automated imaging, registration and intelligent archiving of tissue microarrays in multi-user, network environments.
Congestion Control in Packet Switched Wide Area Networks using a Feedback Model

In a complex world, where networking expands very rapidly, the network stability of flow of bandwidth played a vital role in transmitting packets. Hence, it was imperative to find solution to the problem of congestion especially in the follow of bandwidth stability. Congestion in computer networking is caused by so many factors. Some of the signs are packet loss, queuing delay resulting from overloading the buffer, faulty hardware devices, intermixing of old and new technologies and unstable flow of bandwidth resulting from positive feedback A negative feedback mechanism was added to the network. Feedback was developed using both control and queuing theory. The congested signalling was tested for stability using control theory. Kendall notation was used to determine both arrival and service rates with all the queue disciplines. Matlab was used to simulate the model. Bode plots and impulse responses were used to analyse the performance of the improved model. The results showed that flow of bandwidth was stable with increase in service rate of packets and decrease in the probability of routers not accepting packets. This shows that adopting dynamic explicit feedback model reduced congestion by minimal packet drops, balanced flow of bandwidth, converges to fairness and minimized amplitude of oscillation.
Adaptive Information Passing for Early State Pruning in MapReduce Data Processing Workflows

MapReduce data processing workflows often consist of multiple cycles where each cycle hosts the execution of some data processing operators e.g., join, defined in a program. A common situation is that many data items that are propagated along in a workflow, end up being “fruitless” i.e. they do not contribute to the final output. Given that the dominant costs associated with MapReduce processing (I/O, sorting and network transfer) are very sensitive to the size of intermediate states, such fruitless data items contribute unnecessarily to workflow costs. Consequently, it may be possible to improve the performance of MapReduce data processing workflows by eliminating fruitless data items as early as possible. Achieving this will require maintaining extra information about the state (output) of each operator, and then passing this information to descendant operators in the workflow. The descendant operators can use this state information to prune fruitless data items from their other inputs. However, this process is not without any overhead and in some cases, its costs may outweigh its benefits. Consequently, a technique for adaptively selecting Information Passing as part of an execution plan is needed. This adaptivity will need to be determined by a cost model that accounts for MapReduce’s partitioned execution model as well as its restricted model of communication between operators. These nuances of MapReduce impose limitations on the applicability of information passing techniques developed for traditional database systems. In this paper, we propose an approach for implementing Adaptive Information Passing for MapReduce platforms. Our proposal includes a benefit estimation model, and an approach for collecting data statistics needed for benefit estimation, which piggybacks on operator execution. Our approach has been integrated into Apache Hive and a comprehensive empirical evaluation is presented.