Miracle-dz/UniFAR-FTUs huggingface dataset:
SCAMP3 is a component of the Salmonella-induced tubular network and reveals an interaction between bacterial effectors and post-Golgi trafficking

Salmonella enterica are facultative intracellular bacterial pathogens that proliferate within host cells in a membrane‐bounded compartment, the Salmonella‐containing vacuole (SCV). Intracellular replication of Salmonella is mediated by bacterial effectors translocated on to the cytoplasmic face of the SCV membrane by a type III secretion system. Some of these effectors manipulate the host endocytic pathway, resulting in the formation in epithelial cells of tubules enriched in late endosomal markers, known as Salmonella‐induced filaments (SIFs). However, much less is known about possible interference of Salmonella with the secretory pathway. Here, a small‐interference RNA screen revealed that secretory carrier membrane proteins (SCAMPs) 2 and 3 contribute to the maintenance of SCVs in the Golgi region of HeLa cells. This is likely to reflect a function of SCAMPs in vacuolar membrane dynamics. Moreover, SCAMP3, which accumulates on the trans‐Golgi network in uninfected cells, marked tubules induced by Salmonella effectors that overlapped with SIFs but which also comprised distinct tubules lacking late endosomal proteins. We propose that SCAMP3 tubules reflect a manipulation of specific post‐Golgi trafficking that might allow Salmonella to acquire nutrients and membrane, or to control host immune responses.
Trait markers for alcoholism: clinical utility.

Because alcoholism is a multi-factorial psychiatric disorder, with both psychosocial and biochemical/genetic factors leading to its manifestation in any one individual, the presence of biochemical/genetic factors alone may not lead to the manifestation of the disorder. There are numerous difficulties associated with identification of a trait abnormality in a disorder that requires suitable socio-cultural permissiveness with distinct behavioural characteristics to manifest a disorder that may not require that predisposing trait abnormality in order to develop. Numerous studies have been performed in the past to potentially identify a biochemical or genetic trait abnormality in alcoholism, and not all of them have addressed significant methodological flaws in this type of research. This review addresses some of the difficulties inherent in this research, and aims for a comprehensive review of the highlights of the search for a clinically useful trait abnormality. Some series of investigations hold promise that a trait marker for a particular subset of alcoholics may be developed, e.g. severe alcoholism and the dopamine D2 receptor gene; the level of reaction to alcoholism in family history-positive alcoholics; beta-endorphin abnormalities in specific family groups of alcoholics; reduced P3 wave event-related potentials as markers and predictors of development of substance abuse in predisposed youths; reduced growth hormone response to apomorphine as a predictor of relapse to alcoholism in early abstinence; abnormal adenylyl cyclase activity in certain defined subgroups of alcoholics; and abnormal platelet monoamine oxidase levels in subjects with a behavioural predisposition to addictive disorders. The review concludes that while there has not yet been an identification of a comprehensive trait marker for alcoholism, there is hope for identification subgroups of alcoholics with consistent biological markers within that subgroup that may well prove fruitful over time. It will then be up to a future generation of clinicians to take that information and develop prevention programmes that can incorporate this information to help the predisposed individual avoid alcohol problems.
Physics based boiling bubble simulation

Boiling is a daily observed phenomenon. From the physics point of view, boiling is due to the rapid vaporization of liquid like water. In fact, it consists of several complex processes. First, energy transfer, which mainly includes thermal conduction and convection, occurs between the heat source and water, between water molecules and bubbles, and between water molecules and water molecules. Second, there are multiple phases of boiling, each of which has different characteristics, and hence, makes boiling a complicated physical process. In this paper, we propose a new physics based method for simulating bubbles from boiling water with a Smoothed Particle Hydrodynamics (SPH) solver. The proposed work handles "vapor" bubbles rather than "air" bubbles. The most important difference is that the former can condense and merge with the surrounding water while the latter cannot. With our model, 5 interesting phenomena of boiling bubbles are introduced which have not been fully addressed in previous works.
Antiprotozoal Activity against Entamoeba histolytica of Plants Used in Northeast Mexican Traditional Medicine. Bioactive Compounds from Lippia graveolens and Ruta chalepensis

Amoebiasis caused by Entamoeba histolytica is associated with high morbidity and mortality is becoming a major public health problem worldwide, especially in developing countries. Because of the side-effects and the resistance that pathogenic protozoa build against the standard antiparasitic drugs, e.g., metronidazole, much recent attention has been paid to plants used in traditional medicine around the world in order to find new antiprotozoal agents. We collected 32 plants used in Northeast Mexican traditional medicine and the methanolic extracts of these species were screened for antiprotozoal activity against E. histolytica trophozoites using in vitro tests. Only 18 extracts showed a significant inhibiting activity and among them six plant extracts showed more than 80% growth inhibition against E. histolytica at a concentration of 150 µg/mL and the IC50 values of these extracts were determined. Lippia graveolens Kunth and Ruta chalepensis Pers. showed the more significant antiprotozoal activity (91.54% and 90.50% growth inhibition at a concentration of 150 µg/mL with IC50 values of 59.14 and 60.07 µg/mL, respectively). Bioassay-guided fractionation of the methanolic extracts from these two plants afforded carvacrol (1) and chalepensin (2), respectively, as bioactive compounds with antiprotozoal activity.
Data Assimilation Using an Ensemble Kalman Filter Technique

The possibility of performing data assimilation using the flow-dependent statistics calculated from an ensemble of short-range forecasts (a technique referred to as ensemble Kalman filtering) is examined in an idealized environment. Using a three-level, quasigeostrophic, T21 model and simulated observations, experiments are performed in a perfect-model context. By using forward interpolation operators from the model state to the observations, the ensemble Kalman filter is able to utilize nonconventional observations. In order to maintain a representative spread between the ensemble members and avoid a problem of inbreeding, a pair of ensemble Kalman filters is configured so that the assimilation of data using one ensemble of shortrange forecasts as background fields employs the weights calculated from the other ensemble of short-range forecasts. This configuration is found to work well: the spread between the ensemble members resembles the difference between the ensemble mean and the true state, except in the case of the smallest ensembles. A series of 30-day data assimilation cycles is performed using ensembles of different sizes. The results indicate that (i) as the size of the ensembles increases, correlations are estimated more accurately and the root-meansquare analysis error decreases, as expected, and (ii) ensembles having on the order of 100 members are sufficient to accurately describe local anisotropic, baroclinic correlation structures. Due to the difficulty of accurately estimating the small correlations associated with remote observations, a cutoff radius beyond which observations are not used, is implemented. It is found that (a) for a given ensemble size there is an optimal value of this cutoff radius, and (b) the optimal cutoff radius increases as the ensemble size increases.
Integrating Knowledge, Feelings and Action: Using Vee Heuristics and Concept Mapping in Education for Sustainable Development

Integrating Knowledge, Feelings and Action: Using Vee Heuristics and Concept Mapping in Education for Sustainable Development Although children are regularly showered with environmental knowledge, this is rarely transformed into concerned action, probably because it is not meaningful for the learner and/or is highlighted at the expense of a personalized process of learning. Research in Education for Sustainable Development shows that besides knowledge acquisition feelings, psychological factors and active participation while learning are important determinants of commitment. Fostering an attitude of responsible environmental action is not dependent on what knowledge is delivered, but on how it is delivered and experienced. This paper describes the use of Vee Heuristics and Concept Mapping as pedagogical tools within the context of primary school learners' different learning patterns. It provides illustrations of Concept Maps constructed before and after the learning programme and discusses some implications of the findings. This paper suggests that the use of Vee Heuristics and Concept Mapping along with an awareness of how the child prefers to learn may be steps towards tapping-in the child's internal talking so that educators can understand how each learner responds to incoming information. Learning about environmental issues becomes relevant, meaningful and, in the long run, conducive to improved environmental responsible behaviour.
Software modularization operators

There exists a number of large business critical software systems written in newer languages such as C and Java that are fast becoming legacy and increasingly difficult to maintain. Unlike older monolithic systems, where modularization primarily involves splitting the monolithic code base into modules, for such newer systems which already have some basic modular structure, code decomposition is only one of the many possible activities. Even though the area of software modularization has received considerable attention over these past years, there are hardly any case studies documented in literature on modularizing large C and Java systems. We still do not fully comprehend the activities experienced developers perform when they have to modularize such newer systems. The goal of this paper is to learn from past software modularization projects and identify common recurring patterns. This paper formalizes 6 such patterns, which we term as modularization operators, that are likely to be the basic building blocks of any software modularization activity. The operators presented in this paper are validated using modularization case studies of open source software systems and a proprietary software system and several observations and insights are presented.
Optimal Multirobot Path Planning on Graphs: Complete Algorithms and Effective Heuristics

We study optimal multirobot path planning on graphs (MPP) over four minimization objectives: the makespan (last arrival time), the maximum (single-robot traveled) distance, the total arrival time, and the total distance. Having established previously that these objectives are distinct and NP-hard to optimize, in this paper, we focus on efficient algorithmic solutions for solving these optimal MPP problems. Toward this goal, we first establish a one-to-one solution mapping between MPP and a special type of multiflow network. Based on this equivalence and integer linear programming (ILP), we design novel and complete algorithms for optimizing over each of the four objectives. In particular, our exact algorithm for computing optimal makespan solutions is a first that is capable of solving extremely challenging problems with robot-vertex ratios as high as 100%. Then, we further improve the computational performance of these exact algorithms through the introduction of principled heuristics, at the expense of slight optimality loss. The combination of ILP model based algorithms and the heuristics proves to be highly effective, allowing the computation of 1.x-optimal solutions for problems containing hundreds of robots, densely populated in the environment, often in just seconds.
Total Factor Productivity , Foreign Direct Investment and Entry Barriers in the Chinese Automobile Industry

Acknowledgments: We would like to thank Mustafa Caglayan, Jiandong Ju, the two anonymous referees of the journal, and the session participants at the Canadian Economic Association 2011 meeting in Ottawa, the Southern Economic Association 2011 meeting in Washington D.C., and the Eastern Economics Association 2012 meeting in Boston for their comments and suggestions on earlier versions of this paper. For financial support, we thank the Office of the Vice President for Research, the Research Council, and the College of Arts and Sciences at the University of Oklahoma. The usual disclaimer applies.
Better Speed Better Comprehension: Introducing “Integrated Reading Comprehension Strategy

Reading skills are assessed in many standardized English language proficiency tests, such as IELTS, TOEFL, FCE, CAE and CPE. Therefore, test-takers are required to employ effective strategies to perform well in the reading components of these tests. Taking this into account, this study introduces ‘Integrated Reading Comprehension Strategy’ (IRCS) and examines its effectiveness on participants’ reading comprehension, reading speed and reading test-anxiety. The study adopts a non-equivalent quasi-experimental embedded mixed-methods design and uses a sample of 30 teachers selected through convenience sampling from a private Indian school in Ajman, UAE. These participants are divided into two almost equal groups (experimental & control). Both quantitative and qualitative data are collected by means of pre and post-reading comprehension tests, pre and post-reading test-anxiety surveys and semi-structured postproduction interviews. After three weeks of intervention, the quantitative data are analyzed using descriptive (frequency count, percentage & effect size) as well as inferential (independent & paired samples t tests) statistics, whereas content analysis is used for the purpose of analyzing the qualitative data. The findings of the study indicate that IRCS has no statistically significant effects on participants’ reading comprehension and reading speed although all the participants interviewed agree that IRCS enable them to read better and faster. On the other hand, the results of both quantitative and qualitative analyses reveal that IRCS plays a significant role in reducing participants’ reading test-anxiety levels. The study thoroughly discusses these findings, expounds its limitations, and offers suggestions for teachers, course material writers and future researchers.
Observable or Invocable Behaviour - You Have to Choose

Several object-oriented modeling approaches propose to describe the dynamic behaviour of objects by state transition diagrams. None of them provide precise rules or conditions for the interrelation between the behaviour description of classes and those of their sub-classes. In this paper, we discuss this interrelation in detail. It turns out that one has to distinguish between the observable and the invoca-ble behaviour of objects and that diierent compatibility requirements between the diagrams exist depending on the type of behaviour.
Learning-by-Doing Spillovers in the Semiconductor Industry

The semiconductor industry is often cited as a "strategic" industry in part because important learning-by-doing spillovers may justify special industrial policies. Documenting the precise nature of these spillovers is crucial for determining the advisability of such policies and is helpful for understanding the contribution of learning to endogenous growth. Yet existing empirical evidence on learning by doing in semiconductor production is scant and evidence on spillovers is nonexistent. Using quarterly, firm-level data on seven generations of dynamic random access memory (DRAM) semiconductors over 1974-92, we find that (a) learning rates average 20 percent, (b) firms learn three times more from an additional unit of their own cumulative production than from an additional unit of another firm's cumulative production, (c) learning spills over just as much between firms in different countries as between firms within a given country, (d) Japanese firms are indistinguishable from others in learning speed, and (e) intergenerational learning spillovers are weak, being marginally significant in only two of seven DRAM generations.
Arch2030: A Vision of Computer Architecture Research over the Next 15 Years

Application trends, device technologies and the architecture of systems drive progress in information technologies. However, the former engines of such progress - Moore's Law and Dennard Scaling - are rapidly reaching the point of diminishing returns. The time has come for the computing community to boldly confront a new challenge: how to secure a foundational future for information technology's continued progress. The computer architecture community engaged in several visioning exercises over the years. Five years ago, we released a white paper, 21st Century Computer Architecture, which influenced funding programs in both academia and industry. More recently, the IEEE Rebooting Computing Initiative explored the future of computing systems in the architecture, device, and circuit domains. This report stems from an effort to continue this dialogue, reach out to the applications and devices/circuits communities, and understand their trends and vision. We aim to identify opportunities where architecture research can bridge the gap between the application and device domains.
Using Similarity Measures for Context-Aware User Interfaces

Context-aware user interfaces facilitate the user interaction by suggesting or prefilling data derived from the userpsilas current context. This raises the problem of mapping context information to input elements in the user interface. We address this problem for web applications by (i) automatically extracting a textual representation of their input elements, and by (ii) mapping context information to them using these textual representations. In this paper, we present an approach for the representation extraction task that outperforms existing ones, and we explore the potential of similarity measures for the context mapping task.
Scarred by Failure

Are failed entrepreneurs penalized in the labour market? The answer is yes under certain conditions. Using a novel dataset of matched entrepreneurs and employees in Belgium, we show that: (i) on average, entrepreneurs returning to the labour market after a business failure are penalized, but this effect is most pronounced for those coming from the higher echelons of the wage distribution, and absent for those who earned relatively little before entering self-employment. (ii) the penalty is only present for entrepreneurs who fail quickly: entrepreneurs returning to the labour market after 5 or more years do not get penalized. (iii) entrepreneurs who fail fast and move to a new employer limit the wage penalty by changing industry compared to the industry they were venturing in. These results are consistent with theories of adverse selection in the labour market. Scarred by Failure? Jeroen Mahieu∗ KU Leuven Francesca Melillo KU Leuven Toke Reichstein CBS
Subduing High Inflation in Romania. How to Better Monetary and Exchange Rate Mechanisms?

Romania's overall economic performance during the first ten years of transition can be termed so far as disappointing: the country has not been able to deliver steady growth, low unemployment and low inflation. This paper focuses on the effectiveness of monetary mechanisms and policies during this period. Special emphasis is set on the exchange rate mechanism. The first part of the text develops a short introduction to relevant monetary theory in the transition context. In the second part, we analyse the stylised facts pertaining to Romanian economy and put forward some weaknesses of its banking system and monetary policies. The conclusion presents a set of recommendations for a reform of the going monetary policy.
Experimental evidence for chick discrimination without recognition in a brood parasite host

Recognition is considered a critical basis for discriminatory behaviours in animals. Theoretically, recognition and discrimination of parasitic chicks are not predicted to evolve in hosts of brood parasitic birds that evict nest-mates. Yet, an earlier study showed that host reed warblers (Acrocephalus scirpaceus) of an evicting parasite, the common cuckoo (Cuculus canorus), can avoid the costs of prolonged care for unrelated young by deserting the cuckoo chick before it fledges. Desertion was not based on specific recognition of the parasite because hosts accept any chick cross-fostered into their nests. Thus, the mechanism of this adaptive host response remains enigmatic. Here, I show experimentally that the cue triggering this ‘discrimination without recognition’ behaviour is the duration of parental care. Neither the intensity of brood care nor the presence of a single-chick in the nest could explain desertions. Hosts responded similarly to foreign chicks, whether heterospecific or experimental conspecifics. The proposed mechanism of discrimination strikingly differs from those found in other parasite–host systems because hosts do not need an internal recognition template of the parasite's appearance to effectively discriminate. Thus, host defences against parasitic chicks may be based upon mechanisms qualitatively different from those operating against parasitic eggs. I also demonstrate that this discriminatory mechanism is non-costly in terms of recognition errors. Comparative data strongly suggest that parasites cannot counter-evolve any adaptation to mitigate effects of this host defence. These findings have crucial implications for the process and end-result of host–parasite arms races and our understanding of the cognitive basis of discriminatory mechanisms in general.
Diagnosing the Financial System: Financial Conditions and Financial Stress

We approach the task of monitoring financial stability within a framework that balances the costs and benefits of identifying future crisis-like conditions based on past U.S. financial crises. Our results indicate that the National Financial Conditions Index (NFCI) produced by the Federal Reserve Bank of Chicago is a highly predictive and robust indicator of financial stress at leading horizons of up to one year, with measures of leverage playing a crucial role in signaling financial imbalances. At longer forecast horizons, we propose an alternative sub-index of the NFCI that captures the relationship between non-financial leverage, financial stress, and economic activity.