Miracle-dz/UniFAR-FTUs huggingface dataset:
Soluble fms-Like Tyrosine Kinase 1 as a Link Between Angiogenesis and Endothelial Dysfunction in Pediatric Patients With β-Thalassemia Intermedia

Endothelial damage has been implicated in the pathogenesis of vascular complications in β-thalassemia intermedia (β-TI). Soluble fms-like tyrosine kinase 1 (sFLT-1) is a member of the vascular endothelial growth factor receptor (VEGFR) family. Soluble fms-like tyrosine kinase 1 is an antiangiogenic protein that induces endothelial dysfunction by adhering to and inhibiting VEGF and placenta growth factor. The aim of this study was to assess the level of sFLT-1 in 35 children and adolescents with β-TI, correlating it with markers of hemolysis and iron overload as well as cardiopulmonary complications. Patients were studied focusing on the history of cardiac disease, splenectomy, transfusion, chelation/hydroxyurea therapy, serum ferritin, and sFLT-1 levels. Echocardiography and measurement of carotid intima–media thickness (CIMT) were done for all participants. Soluble fms-like tyrosine kinase 1 was significantly higher in TI patients compared to the control group (median [interquartile range], 110 [80-155] pg/mL versus 70 [60-90] pg/mL; P < .001). Splenectomized patients and those who had pulmonary hypertension risk or heart disease had higher sFLT-1 levels than those without (P < .001). The sFLT-1 cutoff value that differentiates patients with and without pulmonary hypertension risk or heart disease was determined. Soluble fms-like tyrosine kinase 1 was lower among patients who received chelation therapy and/or hydroxyurea. Significant positive relations were observed between sFLT-1 and lactate dehydrogenase, serum ferritin, liver iron concentration, tricuspid regurgitant jet velocity, and CIMT. We suggest that sFLT-1 represents a link between angiogenesis, endothelial dysfunction, and subclinical atherosclerosis. Measurement of sFLT-1 as a marker of vascular dysfunction in β-TI may provide utility for early identification of patients at increased risk of cardiopulmonary complications.
Metal and ceramic parts fabricated by microminiature powder injection molding

Microminiature powder injection molding (μPIM) is a promising variant of powder injection molding (PIM) with development profiting by the demand for highly resistive micro products made of metal or ceramic materials. μPIM involves low-pressure or high pressure injection molding; the former is com- monly used for prototypes and small runs while the latter reflects medium and large-scale production. In relation to feedstock improvement, current research focuses on the exploitation of additives and the application of ultrafine powders. In terms of the μPIM shaping process, primary challenges are further miniaturization and the production of micro components with increased complexity. Presently, variants of multi-component μPIM are under development and the process parameters have to be adjusted for metals and ceramics to address issues of disconnection in micro areas. Examples are shaft―wheel combinations consisting of different couples of ceramics or metals. Depending on the powders and process parameters, mobile or immobile joints can be fabricated.
An unsuspected danger in display

Materials used to construct a display case may produce chemical damage to museum objects. A recent investigation of the cause of rapid tarnishing of some ancient silver coins was traced to sulfur in a rubberized adhesive employed to secure a cork lining into a show case. The author cites other instances where various woods had destructive effects on metals. Tests were carried out in glass-stoppered conical flasks with samples of wood, textiles and adhesives in the presence of metal test pieces. Poly(vinyl acetate) adhesives were found to have harmful action on lead foil. Some textiles such as velvet and felt used to line displays contain residual amounts of sulfur compounds in the dyes. These dyes accelerate tarnishing of silver. Two illustrations accompany the text.
Tears and fears: modeling emotions and emotional behaviors in synthetic agents

Emotions play a critical role in creating engaging and believable characters to populate virtual worlds. Our goal is to create general computational models to support characters that act in virtual environments, make decisions, but whose behavior also suggests an underlying emotional current. In service of this goal, we integrate two complementary approaches to emotional modeling into a single unified system. Gratch's Émile system focuses on the problem of emotional appraisal: how emotions arise from an evaluation of how environmental events relate to an agent's plans and goals. Marsella et al. 's IPD system focuses more on the impact of emotions on behavior, including the impact on the physical expressions of emotional state through suitable choice of gestures and body language. This integrated model is layered atop Steve, a pedagogical agent architecture, and exercised within the context of the Mission Rehearsal Exercise, a prototype system designed to teach decision- making skills in highly evocative situations.
Towards a definition of robustness for market-style open multi-agent systems

Multi-agent systems (MAS) are an integral part of current(D)AI research. Their success and the success of agenttechnology is in the majority of the literature ascribed to threemajor advantages, one of which is that multi-agent systems arerobust systems (cf. [1, 9]). Although the literature treatsrobustness like an inherent feature of MAS (which it is not),there is hardly any discussion on what robustness actuallymeans (a rare exception is the work of Kaminka and Tambe [7]and Klein and Dellarocas [3]). Just like any other artificialcomplex system, multi-agent systems need to be specificallydesigned to be robust. Compared to conventional computerscience, the issue of robustness in MAS is different. Mostcomputer science systems are transformational systems, whichmeans they compute a function on some input. Here, techniquesfor ensuring robustness exist (e.g. cf. [6]). However, the mostinteresting multi-agent systems are open systems, which donot explicitly compute a function (e.g. looking at the mostpredominant example of an open system, namely the Internet, ascomputing a function certainly misses the point).
Effect of wind changes during the Last Glacial Maximum on the circulation in the Southern Ocean

Present-day surface wind stress climatology is manipulated to simulate wind conditions during the last glacial maximum. These estimated wind fields force a one-layer, wind-driven numerical model of the southern ocean to determine if a change in the strength of the surface wind stress can shift the location of the Antarctic Polar Front, which is part of the Antarctic Circumpolar Current. A change in the forcing by a factor of 0.5–2.0 results in a change in the speed of the flow by an identical factor with no change in position. However, if the present-day wind climatology is shifted meridionally, there is a change in both strength of the circulation and spatial pattern. A shift of the wind stress of more than 5° of latitude is required to produce a shift in the location of the polar front.
Keynote I: "Designing heterogeneous systems in the AI era: Challenges and opportunities"

Artificial Intelligence has recently become a major trend, driving the rapid development of new compute capabilities. As AI functionality has improved, the demand for even greater capabilities has grown, requiring significantly higher levels of performance and energy-efficiency in the IT infrastructure. The maturation of classical semiconductor scaling has made delivering these higher levels much more challenging; reliance on scaling alone is insufficient. As a result, innovations in design, design automation, and architecture are crucial to improving power-performance. Accelerators in heterogeneous systems will increasingly be needed to improve overall system capabilities and power/performance. To enable practical accelerator integration, system architectures must be designed to easily incorporate heterogeneous components such as today's GPUs, as well as future accelerators for cognitive applications. Design processes must increase in efficiency to enable the cost-effective design of application-specific accelerators. In this presentation, I will describe these trends, some exemplary innovations that address them, and areas of future research towards heterogeneous systems for the AI era.
NETs: organ-related epigenetic derangements and potential clinical applications

High-throughput next-generation sequencing methods have recently provided a detailed picture of the genetic landscape of neuroendocrine tumors (NETs), revealing recurrent mutations of chromatin-remodeling genes and little-to-no pathogenetic role for oncogenes commonly mutated in cancer. Concurrently, multiple epigenetic modifications have been described across the whole spectrum of NETs, and their putative function as tumorigenic drivers has been envisaged. As result, it is still unclear whether or not NETs are epigenetically-driven, rather than genetically-induced malignancies. Although the NET epigenome profiling has led to the identification of molecularly-distinct tumor subsets, validation studies in larger cohorts of patients are needed to translate the use of NET epitypes in clinical practice. In the precision medicine era, recognition of subpopulations of patients more likely to respond to therapeutic agents is critical, and future studies testing epigenetic biomarkers are therefore awaited. Restoration of the aberrant chromatin remodeling machinery is an attractive approach for future treatment of cancer and in several hematological malignancies a few epigenetic agents have been already approved. Although clinical outcomes of epigenetic therapies in NETs have been disappointing so far, further clinical trials are required to investigate the efficacy of these drugs. In this context, given the immune-stimulating effects of epidrugs, combination therapies with immune checkpoint inhibitors should be tested. In this review, we provide an overview of the epigenetic changes in both hereditary and sporadic NETs of the gastroenteropancreatic and bronchial tract, focusing on their diagnostic, prognostic and therapeutic implications.
What is mood? A computational perspective

Abstract The neurobiological understanding of mood, and by extension mood disorders, remains elusive despite decades of research implicating several neuromodulator systems. This review considers a new approach based on existing theories of functional brain organisation. The free energy principle (a.k.a. active inference), and its instantiation in the Bayesian brain, offers a complete and simple formulation of mood. It has been proposed that emotions reflect the precision of – or certainty about – the predicted sensorimotor/interoceptive consequences of action. By extending this reasoning, in a hierarchical setting, we suggest mood states act as (hyper) priors over uncertainty (i.e. emotions). Here, we consider the same computational pathology in the proprioceptive and interoceptive (behavioural and autonomic) domain in order to furnish an explanation for mood disorders. This formulation reconciles several strands of research at multiple levels of enquiry.
Source Properties of a Hollow Cathode Arc Plasma

Experiments have been carried out on the properties of a hollow cathode as an ion-source. The measured electron density, ion and neutral temperatures and drift velocities have been compared with predictions from the conservation laws for matter, momentum and energy. Very large exit drift velocities of ions and neutrals are observed. The magnitude and direction, against the electric field, can be explained on the basis of the momentum balance. At weak magnetic field strengths even supersonic drift velocities are found. The charge flux carried by the ions is about five percent of the net arc current. For small flows, the ionized fraction of the gas supply approaches 100%. The neutral particle density outside the cathode consist of a fraction drifting with a large velocity out of the cathode and a fraction of cool background atoms. The change of the ratio of these fractions with increasing distance to the cathode causes the average neutral particle drift to decrease very rapidly. Finally, an analysis of the overall cathode power balance is given.
Well-Posedness and Smoothing Effect for Nonlinear Dispersive Equations

where α is a real constant with 2α/3 ̸∈ Z and T > 0. In (1), all the parameters are normalized except for α. Equation (1) appears as a mathematical model for nonlinear pulse propagation phenomena in various fields of physics, especially in nonlinear optics (see [54], [27] and [1]). So far, equation (1) without the third order derivative, that is, the cubic NLS equation has attracted much mathematical and physical interest. Recently, as the ultra-short pulse has become important in the photonic crystal fiber, an increasing attention among theoretical and experimental physicists in nonlinear optics has been paid to the role of the third order dispersion in equation (1). From a viewpoint of the PDE theory, the well-posedness issue of the Cauchy problem for nonlinear evolution equations such as (1)-(2) is one of the most fundamental problems. The Cauchy problem is said to be locally (resp. globally) well-posed if the following three properties hold: (i) local (resp. global) existence of solutions, (ii) uniqueness of solutions, (iii) continuous dependence of solutions on initial data. We refer to the local and the global well-posedness as (LWP) and (GWP), respectively. The Caucy problem is said to be ill-posed if it is not well-posed. Many mathematicians have been studying what is the largest space where the Cauchy problem of a nonlinear evolution equation at hand is well-posed. Especially, there has been a great progress in nonlinear dispersive equations for the last two decades. In this note, we take equation (1) as an example to explain recent results obtained by the author in collaboration with Nobu Kishimoto (RIMS, Kyoto University), Tomoyuki Miyaji (Meiji Inst. Adv. Stud. Math. Sci., Meiji University), Tadahiro Oh (The University of Edinburgh) and Nikolay Tzvetkov (University of Cergy-Pontoise). First, in Section 2, we consider solving the Cauchy problem (1)-(2) in H for s < 0, elements of which may not be functions but distributions. When we work with the space consisting of distributions, the problem we immediately meet with is how the nonlinear term can make sense, because the product of distributions is not necessarily well-defined. In 1993, Bourgain [4] presented the so-called Forier restriction method with the Fourier restriction norm. The Fourier restriction norm and its variants succeeded in capturing specific features of nonlinear oscillations and have been applied to many nonlinear evolution equations describing nonlinear wave phenomena (see, e.g., [4], [13], [18], [22]-[26], [32], [34]-[36], [40], [42], [44]-[49], [57]-[60]). The Fourier restriction method also led a new mathematical insight into the nonlinear interaction
Temporal variation in synchrony among chinook salmon (Oncorhynchus tshawytscha) redd counts from a wilderness area in central Idaho

Metapopulation dynamics have emerged as a key consideration in conservation planning for salmonid fishes. Implicit to many models of spatially structured populations is a degree of synchrony, or correlation, among populations. We used a spatially and temporally extensive database of chinook salmon (Oncorhynchus tshawytscha ) redd counts from a wilderness area in central Idaho to examine patterns in synchrony as these fish underwent a sixfold decrease in abundance. Our results suggested that populations became strongly synchronous as abundances decreased and that the range, or diversity of correlations, exhibited among populations also decreased. These changes indicate that the likeli - hood of simultaneous extirpations has increased, which could have long-term detrimental consequences for metapopulation persistence. Implications for management are that the resilience of many metapopulations to large-scale disturbance and anthropogenic suppression may not depend solely on attempts to maintain large and productive compo- nent populations, but also on efforts to desynchronize populations that have become strongly correlated. Such efforts could entail promoting the existence of a broad distribution and diversity of habitats that support a wide array of life- history forms and ensuring that some habitats are sufficiently spatially disjunct so that risks from catastrophic stochas - tic events are minimized.
See it on a radio story: sound effects and shots to evoked imagery and attention on audio fiction

Radio’s capacity to stimulate the creation of mental images in the mind of its listeners has long been acknowledged. Nevertheless, research into mental imagery has focused principally on the study of visual stimuli, although studies into radio itself have mostly concerned the field of advertising. In this study, we examine the influence of two stimuli associated with auditory processing on radio: sound effects and sound shots. The chosen context for the study is that of a fictional story, or audio drama, through which to measure the role of these stimuli both in creating mental images in the listener’s mind and in maintaining his or her attention. Our findings demonstrate that the inclusion of descriptive sound effects and especially of sound shots in a fictional radio drama increases mental imagery and that a relationship exists between this increase and the degree of listener attention.
Fermentation in the large intestine of single-stomached animals and its relationship to animal health

The phasing out of antibiotic compounds as growth promoters from the animal industry means that alternative practices will need to be investigated and the promising ones implemented in the very near future. Fermentation in the gastrointestinal tract (GIT) is being recognized as having important implications for health of the gut and thus of the host animal. Fermentation in single-stomached animals occurs to the largest extent in the large intestine, mainly because of the longer transit time there. The present review examines the micro-ecology of the GIT, with most emphasis on the large intestine as the most important site of fermentative activity, and an attempt is made to clarify the importance of the microfloral activity (i.e. fermentation) in relation to the health of the host. The differences between carbohydrate and protein fermentation are described, particularly in relation to their endproducts. The roles of volatile fatty acids (VFA) and NH3 in terms of their relationship to gut health are then examined. The large intestine has an important function in relation to the development of diarrhoea, particularly in terms of VFA production by fermentation and its role in water absorption. Suggestions are made as to feeds and additives (particularly those which are carbohydrate-based) which could be, or are, added to diets and which could steer the natural microbial population of the GIT. Various methods are described which are used to investigate changes in microbial populations and reasons are given for the importance of measuring the kinetics of fermentation activity as an indicator of microbial activity.
How Should Alcohol Problems Be Conceptualized? Causal Indicators Within the Rutgers Alcohol Problem Index

Alcohol-related problems have traditionally been conceptualized and measured by an effect indicator model. That is, it is generally assumed that observed indicators of alcohol problems are caused by a latent variable. However, there are reasons to think that this construct is more accurately conceptualized as including at least some causal indicators, in which observed indicators cause the latent variable. The present study examined the measurement model of a well-known alcohol consequences questionnaire, the Rutgers Alcohol Problem Index. Participants were 703 students from a large public university in the Northeast mandated to an alcohol intervention. We conducted a zero tetrad test to examine a measurement model consisting solely of effect indicators and a model with both causal and effect indicators. Overall, the results suggested the hybrid model fit the data better than a model with only effect indicators. These findings have implications regarding the theoretical underpinnings of alcohol-related consequences.
User Interaction Modeling and Profile Extraction in Interactive Systems: A Groupware Application Case Study †

A relevant goal in human–computer interaction is to produce applications that are easy to use and well-adjusted to their users’ needs. To address this problem it is important to know how users interact with the system. This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides, using machine learning techniques, generative models of how users behave. Additionally, these models are transformed into a text that describes in natural language the main characteristics of the interaction of the users with the system.
The Impact of Data Quality on Value Based Management of Financial Institutions

Data quality plays a crucial role for financial institutions. Some would even say that data quality is one of the principal reasons for the current financial crisis. Anyway, sufficient data quality is needed to make well-informed business decisions. The dependence on good data quality is especially high if value based management is applied, since then the control of an institution only depends on a few selected key indicators. Bad data quality will lead to inaccurate indicators. To achieve a higher level of data quality, financial institutions need to invest in data quality projects. Although they are generally willing to do this, data quality projects need to be justified through business cases. In this research-in-progress paper, we present the results of a survey in which we asked German financial institutions to give their perspective on the influence of data quality on value based management. The findings of this study provide the basis for our future research as we finally aim at developing a business case model that financial institutions can apply to prepare business cases for data quality projects.
DLNE: A hybridization of deep learning and neuroevolution for visual control

This paper investigates the potential of combining deep learning and neuroevolution to create a bot for a simple first person shooter (FPS) game capable of aiming and shooting based on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature representations, while the evolving network takes those features as inputs to infer actions. Two types of feature representations are evaluated in terms of (1) how precise they allow the deep network to recognize the position of the enemy, (2) their effect on evolution, and (3) how well they allow the deep network and evolved network to interface with each other. Overall, the results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution.