Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Account for Idiomatic German Support Verb Constructions in Statistical Machine Translation

Support-verb constructions (i.e., multiword expressions combining a semantically light verb with a predicative noun) are problematic for standard statistical machine translation systems, because SMT systems cannot distinguish between literal and idiomatic uses of the verb. We work on the German to English translation direction, for which the identification of support-verb constructions is challenging due to the relatively free word order of German. We show that we achieve improved translation quality for verb-object supportverb constructions by marking the verbs when occuring in such constructions. Additional evaluations revealed that our systems produce more correct verb translations than a contrastive baseline system without verb markup.
Markov Decision Processes with Unobserved Confounders : A Causal Approach

Markov decision processes (MDPs) constitute one of the most general frameworks for modeling decision-making under uncertainty, being used in multiple fields, including economics, medicine, and engineering. The goal of the agent in an MDP setting is to learn more about the environment so as to optimize a certain criterion. This task is pursued through the exploration of the environment by actively performing interventions (i.e., through the randomization of its actions), which contrasts with the agent passively observing the environment and not exerting any control over it (i.e., through random sampling). The existence of unobserved confounders, namely, unmeasured variables affecting both the action and the outcome or both the action and the state variables, implies that these two datacollection modes (passive and active) will in general not coincide. It is clear that by performing interventions, any potential inclination (intuition) of the agent will be ignored, which will imply a loss of information and failure to achieve an optimal behavior. In this paper, we formalize this observation and study its conceptual and algorithmic implications. We first demonstrate that standard algorithms may act sub-optimally when unobserved confounders are present. We then propose a systematic method to enhance these algorithms using causal inference theory and leveraging observational data. We formally and empirically show that this new approach produces superior results than current state-of-the-art MDP algorithms.
Framing Dependencies Introduced by Underground Commoditization

Internet crime has become increasingly dependent on the underground economy: a loose federation of specialists selling capabilities, services, and resources explicitly tailored to the abuse ecosystem. Through these emerging markets, modern criminal entrepreneurs piece together dozens of a la carte components into entirely new criminal endeavors. From an abuse fighting perspective, criminal reliance on this black market introduces fragile dependencies that, if disrupted, undermine entire operations that as a composite appear intractable to protect against. However, without a clear framework for examining the costs and infrastructure behind Internet crime, it becomes impossible to evaluate the effectiveness of novel intervention strategies. In this paper, we survey a wealth of existing research in order to systematize the community’s understanding of the underground economy. In the process, we develop a taxonomy of profit centers and support centers for reasoning about the flow of capital (and thus dependencies) within the black market. Profit centers represent activities that transfer money from victims and institutions into the underground. These activities range from selling products to unwitting customers (in the case of spamvertised products) to outright theft from victims (in case of financial fraud). Support centers provide critical resources that other miscreants request to streamline abuse. These include exploit kits, compromised credentials, and even human services (e.g., manual CAPTCHA solvers) that have no credible non-criminal applications. We use this framework to contextualize the latest intervention strategies and their effectiveness. In the end, we champion a drastic departure from solely focusing on protecting users and systems (tantamount to a fire fight) and argue security practitioners must also strategically focus on disrupting frail underground relationships that underpin the entire for-profit abuse ecosystem—including actors, infrastructure, and access to capital.
Study on the critical loosening condition toward a new design guideline for bolted joints

An understanding of conditions that trigger the loosening of bolted joints is essential to ensure joint reliability. In this study, a three-dimensional finite element model of a typical bolted joint is developed, and a new simulation method is proposed to quantitatively identify the critical transverse force for initiating loosening. This force is used to evaluate the anti-loosening capacity of bolted joints. Using the proposed simulation method, the effects of factors affecting critical loosening are systematically studied. It is found that the preload, frictional coefficients at the thread and the bearing surfaces, clamped length, and fit tolerance mainly affected loosening. When the preload and friction coefficients are increased, and the clamped length and fit tolerance are reduced, loosening is inhibited. Experiments are performed to demonstrate the reliability of the results. Finally, a suggestion is proposed to improve the design guideline VDI 2230 for bolted joints, which considers the requirement of avoiding loosening under vibrational loading.
AppSec: A Safe Execution Environment for Security Sensitive Applications

Malicious OS kernel can easily access user's private data in main memory and pries human-machine interaction data, even one that employs privacy enforcement based on application level or OS level. This paper introduces AppSec, a hypervisor-based safe execution environment, to protect both the memory data and human-machine interaction data of security sensitive applications from the untrusted OS transparently. AppSec provides several security mechanisms on an untrusted OS. AppSec introduces a safe loader to check the code integrity of application and dynamic shared objects. During runtime, AppSec protects application and dynamic shared objects from being modified and verifies kernel memory accesses according to application's intention. AppSec provides a devices isolation mechanism to prevent the human-machine interaction devices being accessed by compromised kernel. On top of that, AppSec further provides a privileged-based window system to protect application's X resources. The major advantages of AppSec are threefold. First, AppSec verifies and protects all dynamic shared objects during runtime. Second, AppSec mediates kernel memory access according to application's intention but not encrypts all application's data roughly. Third, AppSec provides a trusted I/O path from end-user to application. A prototype of AppSec is implemented and shows that AppSec is efficient and practical.
Esophageal motility disorder achalasia

Purpose of reviewAlthough not a common disease, the last several years have had exciting breakthroughs in better defining the pathophysiology of achalasia, classifying the disease with high-resolution manometry and potentially exciting new treatments. Recent findingsThe introduction of high-resolution manometry with detailed assessment of lower esophageal sphincter function and peristalsis has made it possible to classify achalasia into three subtypes. This becomes clinically important as patients with type II achalasia do best with both pneumatic dilation and surgical myotomy, whereas type III achalasia may respond better to surgery. The first multicenter randomized controlled trial published by the European Achalasia Trial group reported similar excellent outcomes over a 2-year follow-up with both pneumatic dilation and laparoscopic myotomy in a study involving nearly 200 achalasia patients. Although longer follow-up is required, this supports the continued use of pneumatic dilation for treating achalasia. Finally, the novel endoscopic technique of peroral endoscopic myotomy is a promising new treatment option for achalasia, but it requires increased experiences and careful evaluation before widespread application. SummaryThese are exciting times in the diagnosis and treatment of achalasia, which will definitely improve patient treatment outcomes. However, we still await breakthroughs in the basic science arena to identify the actual cause of achalasia.
Interfacing Conducting Polymer Nanotubes with the Central Nervous System: Chronic Neural Recording using Poly(3,4‐ethylenedioxythiophene) Nanotubes

Development of advanced chronic, high-fidelity neural interfaces is accelerating research into brain function[1] and more effective treatments for neurological conditions. [2–5] The primary functional requirements of these interfaces include recording and/or stimulating from a number of discretely sampled volumes of the brain at requisite spatial resolutions for specific time periods that may extend from hours to years. [6–9] This translates to a push towards smaller electrodes that are more biologically transparent and biocompatible[10–12] with a high density of electrode sites that remain functional for long period of time. [13–15] As electrode size goes to the microscale (higher spatial selectivity), the impedance of electrode site increases, and consequently, the quality of signal recordings decreases (lower sensitivity). Thus, there is a trade off between the size (spatial selectivity) and quality of signal recordings (sensitivity) in neural microelectrodes. [16–18] Studies have also shown that the response of brain tissue to implanted microelectrodes includes an acute injury and a chronic reactive tissue response. The chronic response is characterized by the presence of both activated microglia and reactive astrocytes, which eventually encapsulate the electrode to some degree. [10,12,19–21] Consequently, in addition to the initial high impedance of microelectrodes, these reactive tissue responses have been associated with a progressive increase in the impedance of the electrode/tissue interface. [10,12] Therefore, achieving a very low impedance electrode/tissue interface is important for maintaining and improving signal quality.
Digital polarization-holographic 3D reconstruction of the polycrystalline structure of blood films in the diagnosis of breast cancer

An optical model of the polycrystalline structure of the human blood film is proposed as a superposition of completely polarized and depolarized components. Analytical algorithms for describing the polarization manifestations of such components are found. A new technique for laser sounding of blood films and detection of polarization-inhomogeneous fields by means of variations in the states of polarization of the reference wave is developed. The algorithm of digital holographic reconstruction of distributions of complex amplitudes of the polarization-inhomogeneous object field of polycrystalline films of blood is used. Layered maps of the distribution of azimuth and ellipticity of polarization of the object field of polycrystalline films of blood were obtained and analyzed. 3D distributions of the linear and circular birefringence and dichroism of such films are determined. Sensitivity, specificity and balanced accuracy of the method of digital polarization-holographic 3D reconstruction of the polycrystalline structure of blood films are determined. Statistical analysis of polarization maps of the polycrystalline structure of blood films revealed objective criteria for the diagnosis of breast cancer.
Painting multiple views of complex objects

This paper reviews and illustrates a direct manipulation approach to visualization of complex objects called painting multiple views. We describe a programming model for direct manipulation in general and for painting in particular, based on simple constraints between entities in an the underlying scientific database and the components of displays used to examine the data. With this model, the original notion of “brushing scatterplots” is easily extended.
Autobiographical Narratives Can Be Used With Confidence to Collect Information About Ex-smokers’ Reasons For Quitting Smoking

Although autobiographical narratives (ABNs) provide rich descriptions of how people change addictive behaviors, psychometric evaluations of such reports are rare. 27 ex-smokers who had quit for 1 to 5 years were interviewed twice about why they quit. Participants’ ABN reasons for why they quit smoking were compared with their answers on the Reasons For Quitting (RFQ) scale and found to be similar. Ex-smokers’ ABNs are reliably reported for number and types of reasons given for quitting. Reasons ex-smokers gave in their ABNs were similar to their RFQ subscale answers. ABNs, a qualitative measure of quitting smoking, captured more information about how people quit smoking than quantitative scales.
Reminiscence and adaptation to critical life events in older adults with mild to moderate depressive symptoms

Objectives: The role of reminiscence as a way of adapting to critical life events and chronic medical conditions was investigated in older adults with mild to moderate depressive symptoms. Reminiscence is the (non)volitional act or process of recollecting memories of one's self in the past. Method: 171 Dutch older adults with a mean age of 64 years (SD = 7.4) participated in this study. All of them had mild to moderate depressive symptoms. Participants completed measures on critical life events, chronic medical conditions, depressive symptoms, symptoms of anxiety and satisfaction with life. The reminiscence functions included were: identity, problem solving, bitterness revival and boredom reduction. Results: Critical life events were positively correlated with identity and problem solving. Bitterness revival and boredom reduction were both positively correlated with depressive and anxiety symptoms, and negatively to satisfaction with life. Problem solving had a negative relation with anxiety symptoms. When all the reminiscence functions were included, problem solving was uniquely associated with symptoms of anxiety, and bitterness revival was uniquely associated with depressive symptoms and satisfaction with life. Interestingly, problem solving mediated the relation of critical life events with anxiety. Discussion: This study corroborates the theory that reminiscence plays a role in coping with critical life events, and thereby maintaining mental health. Furthermore, it is recommended that therapists focus on techniques which reduce bitterness revival in people with depressive symptoms, and focus on problem-solving reminiscences among people with anxiety symptoms.
Some results on systems described by convolutional equations

In this paper, convolutional systems in the behavioral approach are considered. Convolutional equations generalize both differential and delay-differential systems. Three fundamental problems are treated and solved. The first consists of characterizing two kernel representations when they are equivalent, i.e., to determine when two different convolutional equations provide the same set of solutions. The second problem deals with the characterization of the spectral controllability for this class of systems. The third problem provides a partial solution of the so called latent variable elimination problem, which is one of the basic steps of the modeling procedure in the behavioral approach.
Megakaryocytic Maturation in Response to Shear Flow Is Mediated by the Activator Protein 1 (AP-1) Transcription Factor via Mitogen-activated Protein Kinase (MAPK) Mechanotransduction*

Megakaryocytes (MKs) are exposed to shear flow as they migrate from the bone marrow hematopoietic compartment into circulation to release pro/preplatelets into circulating blood. Shear forces promote DNA synthesis, polyploidization, and maturation in MKs, and platelet biogenesis. To investigate mechanisms underlying these MK responses to shear, we carried out transcriptional analysis on immature and mature stem cell-derived MKs exposed to physiological shear. In immature (day (d)9) MKs, shear exposure up-regulated genes related to growth and MK maturation, whereas in mature (d12) MKs, it up-regulated genes involved in apoptosis and intracellular transport. Following shear-flow exposure, six activator protein 1 (AP-1) transcripts (ATF4, JUNB, JUN, FOSB, FOS, and JUND) were up-regulated at d9 and two AP-1 proteins (JunD and c-Fos) were up-regulated both at d9 and d12. We show that mitogen-activated protein kinase (MAPK) signaling is linked to both the shear stress response and AP-1 up-regulation. c-Jun N-terminal kinase (JNK) phosphorylation increased significantly following shear stimulation, whereas JNK inhibition reduced shear-induced JunD expression. Although p38 phosphorylation did not increase following shear flow, its inhibition reduced shear-induced JunD and c-Fos expression. JNK inhibition reduced fibrinogen binding and P-selectin expression of d12 platelet-like particles (PLPs), whereas p38 inhibition reduced fibrinogen binding of d12 PLPs. AP-1 expression correlated with increased MK DNA synthesis and polyploidization, which might explain the observed impact of shear on MKs. To summarize, we show that MK exposure to shear forces results in JNK activation, AP-1 up-regulation, and downstream transcriptional changes that promote maturation of immature MKs and platelet biogenesis in mature MKs.
SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHIC ANALYSIS OF HEALTHY RETINA IN BRANCH RETINAL VEIN OCCLUSION AND ITS RESPONSE TO ANTIANGIOGENIC THERAPY

Purpose: To propose a model that measures the effect of intravitreal bevacizumab (IVB) on relatively healthy retina. The purpose is to analyze the remote effect of a branch retinal vein occlusion in the healthy retina, to determine the response it may have to IVB, and to determine if IVB has an atrophic effect on the healthy retina. Methods: Retrospective, longitudinal comparative analysis of patients with branch retinal vein occlusion treated with IVB. Eyes were divided into experimental (branch retinal vein occlusion eye) and control (contralateral eye) groups. Each eye was analyzed for thickness and area. Thickness measurements were performed for total retinal thickness, inner retina thickness, and outer retina thickness. Area was measured for photoreceptors, choroid, and total retina. Results: Eighteen eyes of 9 patients. For thickness analysis, 1,050 scans were studied, and 126 measurements were performed on 42 scans for area analysis. No difference was observed for thickness, except for inner retina thickness. No difference was observed for area. No difference was observed when analyzing a cumulative exposure to IVB. Conclusion: There is no evidence to suggest an atrophic effect caused by IVB when analyzing thickness or area in this experiment. This model could be used to analyze the long-term safety of IVB in larger studies.
Draft DG SANCO document: Addressing the new challenges for risk assessment—an industry perspective

The draft European Commission's Directorate General for Health and Consumer Policy (DG SANCO) document represents the state of the art in environmental risk assessment (ERA) including new trends and combining high level environmental protection and realism. Using the ecosystem services concept, it offers a promising approach to determine which impact may be tolerable, where, and when. Established ERA uses a stepwise approach starting with standardized internationally accepted studies combined with appropriate assessment factors (AFs) and where needed followed by higher tier assessments and respective adjusted AFs. The draft SANCO document follows this approach and presents additional refinements to improve the realism of risk assessment, which is desirable; however, that such additional data becomes a standard requirement without a clear need must be avoided. The idea of additional AFs presented in parts of this article should accordingly first consider risks and benefits in line with this approach and only be requested if data indicates their necessity. In addition, the suggested focus on uncertainty analysis without any obvious according benefits in terms of reduced assessment factors where uncertainty is reduced, is still a challenge. The requirement for science‐ and/or data‐based relevant concerns before requesting more data, and the list of requirements for new innovative approaches that should be met before such approaches can be used in regulatory ecological risk assessments, is well‐founded and strongly supported. Modeling has been included in ERA to allow extrapolation of risk assessments without the need of excessive (animal) testing; it will also address uncertainties more quantitatively. However, this should be done in an overall realistic ecological assessment; simply adding up various individual uncertainties and worst‐case assumptions must be avoided, as this is counterproductive for the use of this valuable tool. The need for expert judgment should be low at the lower tiers of ERA; however, more complex and less standard ERA will still require significant expertise. Integr Environ Assess Manag 2013;9:e81–e84. © 2013 SETAC
Distinguishing between stochasticity and determinism: Examples from cell cycle duration variability

We describe a recent approach for distinguishing between stochastic and deterministic sources of variability, focusing on the mammalian cell cycle. Variability between cells is often attributed to stochastic noise, although it may be generated by deterministic components. Interestingly, lineage information can be used to distinguish between variability and determinism. Analysis of correlations within a lineage of the mammalian cell cycle duration revealed its deterministic nature. Here, we discuss the sources of such variability and the possibility that the underlying deterministic process is due to the circadian clock. Finally, we discuss the “kicked cell cycle” model and its implication on the study of the cell cycle in healthy and cancerous tissues.
ComSoc: adaptive transfer of user behaviors over composite social network

Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization and recommendation, etc. A major challenge lies in that, the available behavior data or interactions between users and items in a given social network are usually very limited and sparse (e.g., >= 99.9% empty). Many previous works model user behavior from only historical user logs. We observe that many people are members of several social networks in the same time, such as Facebook, Twitter and Tencent's QQ. Importantly, their behaviors and interests in different networks influence one another. This gives us an opportunity to leverage the knowledge of user behaviors in different networks, in order to alleviate the data sparsity problem, and enhance the predictive performance of user modeling. Combining different networks "simply and naively" does not work well. Instead, we formulate the problem to model multiple networks as "composite network knowledge transfer". We first select the most suitable networks inside a composite social network via a hierarchical Bayesian model, parameterized for individual users, and then build topic models for user behavior prediction using both the relationships in the selected networks and related behavior data. To handle big data, we have implemented the algorithm using Map/Reduce. We demonstrate that the proposed composite network-based user behavior model significantly improve the predictive accuracy over a number of existing approaches on several real world applications, such as a very large social-networking dataset from Tencent Inc.