LLukas22/scidocs huggingface dataset:
Reinforcement learning-based multi-agent system for network traffic signal control

A challenging application of artificial intelligence systems involves the scheduling of traffic signals in multi-intersection vehicular networks. This paper introduces a novel use of a multi-agent system and reinforcement learning (RL) framework to obtain an efficient traffic signal control policy. The latter is aimed at minimising the average delay, congestion and likelihood of intersection cross-blocking. A five-intersection traffic network has been studied in which each intersection is governed by an autonomous intelligent agent. Two types of agents, a central agent and an outbound agent, were employed. The outbound agents schedule traffic signals by following the longest-queue-first (LQF) algorithm, which has been proved to guarantee stability and fairness, and collaborate with the central agent by providing it local traffic statistics. The central agent learns a value function driven by its local and neighbours’ traffic conditions. The novel methodology proposed here utilises the Q-Learning algorithm with a feedforward neural network for value function approximation. Experimental results clearly demonstrate the advantages of multi-agent RL-based control over LQF governed isolated single-intersection control, thus paving the way for efficient distributed traffic signal control in complex settings.
Gut microbiota dysbiosis contributes to the development of hypertension

BACKGROUND
Recently, the potential role of gut microbiome in metabolic diseases has been revealed, especially in cardiovascular diseases. Hypertension is one of the most prevalent cardiovascular diseases worldwide, yet whether gut microbiota dysbiosis participates in the development of hypertension remains largely unknown. To investigate this issue, we carried out comprehensive metagenomic and metabolomic analyses in a cohort of 41 healthy controls, 56 subjects with pre-hypertension, 99 individuals with primary hypertension, and performed fecal microbiota transplantation from patients to germ-free mice.


RESULTS
Compared to the healthy controls, we found dramatically decreased microbial richness and diversity, Prevotella-dominated gut enterotype, distinct metagenomic composition with reduced bacteria associated with healthy status and overgrowth of bacteria such as Prevotella and Klebsiella, and disease-linked microbial function in both pre-hypertensive and hypertensive populations. Unexpectedly, the microbiome characteristic in pre-hypertension group was quite similar to that in hypertension. The metabolism changes of host with pre-hypertension or hypertension were identified to be closely linked to gut microbiome dysbiosis. And a disease classifier based on microbiota and metabolites was constructed to discriminate pre-hypertensive and hypertensive individuals from controls accurately. Furthermore, by fecal transplantation from hypertensive human donors to germ-free mice, elevated blood pressure was observed to be transferrable through microbiota, and the direct influence of gut microbiota on blood pressure of the host was demonstrated.


CONCLUSIONS
Overall, our results describe a novel causal role of aberrant gut microbiota in contributing to the pathogenesis of hypertension. And the significance of early intervention for pre-hypertension was emphasized.
Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models

In image processing, the Rudin-Osher-Fatemi (ROF) model [L. Rudin, S. Osher, and E. Fatemi, Physica D, 60(1992), pp. 259–268] based on total variation (TV) minimization has proven to be very useful. A lot of efforts have been devoted to obtain fast numerical schemes and overcome the non-differentiability of the model. Methods considered to be particularly efficient for the ROF model include the dual methods of Chan-Golub-Mulet (CGM) [T.F. Chan, G.H. Golub, and P. Mulet, SIAM J. Sci. Comput., 20(1999), pp. 1964–1977] and Chambolle [A. Chambolle, J. Math. Imaging Vis., 20(2004), pp. 89–97], and splitting and penalty based method [Y. Wang, J. Yang, W. Yin, and Y. Zhang, SIAM J. Imaging Sciences, 1(2008), pp. 248–272], as well as split Bregman iteration [T. Goldstein, and S. Osher, SIAM J. Imaging Sciences, 2(2009), pp. 323–343]. In this paper, we propose to use augmented Lagrangian method to solve the model. Convergence analysis will be given for the method. In addition, we observe close connections between the method proposed here and some of the existing methods. We show that the augmented Lagrangian method, dual methods, and split Bregman iteration are different iterative procedures to solve the same system. Moreover, the proposed method is extended to vectorial TV and high order models. Using the approach here, we can easily obtain the CGM dual method and split Bregman iteration for vectorial TV and high order models, which, to our best of knowledge, have not been presented in the literature. Numerical examples demonstrate the efficiency and accuracy of our method.
Legal Translation and Translation Theory : a Receiver-oriented Approach

In this age of globalization, the need for competent legal translators is greater than ever. This perhaps explains the growing interest in legal translation not only by linguists but also by lawyers, the latter especially over the past 10 years (cf. Berteloot, 1999:101). Although Berteloot maintains that lawyers analyze the subject matter from a different perspective, she advises her colleagues also to take account of contributions by linguists (ibid.). I assume this includes translation theory as well. In the past, both linguists and lawyers have attempted to apply theories of general translation to legal texts, such as Catford’s concept of situation equivalence (Kielar, 1977:33), Nida’s theory of formal correspondence (Weisflog, 1987:187, 191); also in Weisflog 1996:35), and, more recently, Vermeer’s skopos theory (see Madsen’s, 1997:17-26). While some legal translators seem content to apply principles of general translation theory (Koutsivitis, 1988:37), others dispute the usefulness of translation theory for legal translation (Weston, 1991:1). The latter view is not surprising since special methods and techniques are required in legal translation, a fact confirmed by Bocquet, who recognizes the importance of establishing a theory or at least a theoretical framework that is practice oriented (1994). By analyzing legal translation as an act of communication in the mechanism of the law, my book New Approach to Legal Translation (1997) attempts to provide a theoretical basis for legal translation within the framework of modern translation theory.
Human-level CMR image analysis with deep fully convolutional networks

Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing a wealth of information for sensitive and specific diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR image analysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images. Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a dataset of unprecedented size, consisting of 4,875 subjects with 93,500 pixelwise annotated images, which is by far the largest annotated CMR dataset. By combining FCN with a large-scale annotated dataset, we show for the first time that an automated method achieves a performance on par with human experts in analysing CMR images and deriving clinical measures. We anticipate this to be a starting point for automated and comprehensive CMR analysis with human-level performance, facilitated by machine learning. It is an important advance on the pathway towards computer-assisted CVD assessment. An estimated 17.7 million people died from cardiovascular diseases (CVDs) in 2015, representing 31% of all global deaths [1]. More people die annually from CVDs than any other cause. Technological advances in medical imaging have led to a number of options for non-invasive investigation of CVDs, including echocardiography, computed tomography (CT), cardiovascular magnetic resonance (CMR) etc., each having its own advantages and disadvantages. Due to its good image quality, excellent soft tissue contrast and absence of ionising radiation, CMR has established itself as the gold standard for assessing cardiac chamber volume and mass for a wide range of CVDs [2–4]. To derive quantitative measures such as volume and mass, clinicians have been relying on manual approaches to trace the cardiac chamber contours. It typically takes a trained
Policy options to support healthy eating in schools.

OBJECTIVES
School nutrition policies offer a promising avenue by which to promote healthy eating and reduce the risk of chronic disease. This article reviews policy components that could support healthy eating, examines their evidence base and suggests directions for future research.


METHOD
Information was drawn from research and other literature written in English between 1994 and 2008. Guided by recommendations from the World Health Organization, evidence pertaining to five potential components of policies was identified and reviewed: foods available, the food environment, health education, health services and counselling, and family and community outreach.


RESULTS
A limited number of evaluations have examined the impact of school nutrition standards and have shown a positive impact on food availability and student nutrient intake. Results have shown that behaviourally focused nutrition education, especially when combined with food services and other initiatives, may affect students' eating habits positively but may not decrease obesity levels. Evidence pertaining to other potential policy subcomponents, such as limiting food marketing in schools, coordinating all food services and providing nutrition-related health services, is limited or lacking.


CONCLUSION
Conceptually, comprehensive school nutrition policies comprising all five policy components offer an integrated and holistic approach to school nutrition. They could provide an umbrella to guide all school actions pertaining to nutrition and serve as a framework for accountability. Does conceptualization match reality? Further research is needed to determine how policy components affect implementation and outcomes.
Ambient Assisted Living: A methodological approach

In this paper, the most important challenges and trends related to the application of Ambient Assisted Living (AAL) methods and techniques to the social/healthcare context are discussed. In order to find out technical solutions to these challenges, the main methodological issues concerning the design of open and distributed architectures are analyzed. The objective is to improve the efficiency/cost ratio in the provision of social and healthcare services to citizens with special needs, through the application of new paradigms in the context of AAL environments. Finally, some results and conclusions regarding the proposed open architecture are illustrated for the case of a distributed biomedical sensor network designed by the authors following this methodology.
Engaging High School and Engineering Students: A Multifaceted Outreach Program Based on a Mechatronics Platform

If we aim to enhance the interest of students in engineering and therefore produce the best engineers, it is essential to strengthen the pipeline to high school education. This paper discusses several outreach activities undertaken by the Faculty of Engineering and Faculty of Education, University of Ottawa (UO), Ottawa, ON, Canada, to help the transition between high school and engineering education and to make students aware of the engineering profession. At the heart of these activities is mechatronics education, which demands an interdisciplinary approach, connects to fundamental math and science concepts, and promotes collaborative project-based learning (PBL). Connected to this focus, a multifaceted program of outreach activities has been initiated. The program includes creation of design-simulate-and-build projects by engineering and high school students, as well as an interactive presentation program whereby engineering students connect with high school students through the sharing of projects that they create in their engineering courses. The survey results indicate that for the high school students, these programs promote students' awareness of engineering and how the mathematics and science they take in school connects to engineering concepts. For the engineering students, they are provided with a meaningful context within which to share their projects and explain their own understanding of engineering principles.
Activity Monitors as Support for Older Persons’ Physical Activity in Daily Life: Qualitative Study of the Users’ Experiences

BACKGROUND
Falls are a major threat to the health and independence of seniors. Regular physical activity (PA) can prevent 40% of all fall injuries. The challenge is to motivate and support seniors to be physically active. Persuasive systems can constitute valuable support for persons aiming at establishing and maintaining healthy habits. However, these systems need to support effective behavior change techniques (BCTs) for increasing older adults' PA and meet the senior users' requirements and preferences. Therefore, involving users as codesigners of new systems can be fruitful. Prestudies of the user's experience with similar solutions can facilitate future user-centered design of novel persuasive systems.


OBJECTIVE
The aim of this study was to investigate how seniors experience using activity monitors (AMs) as support for PA in daily life. The addressed research questions are as follows: (1) What are the overall experiences of senior persons, of different age and balance function, in using wearable AMs in daily life?; (2) Which aspects did the users perceive relevant to make the measurements as meaningful and useful in the long-term perspective?; and (3) What needs and requirements did the users perceive as more relevant for the activity monitors to be useful in a long-term perspective?


METHODS
This qualitative interview study included 8 community-dwelling older adults (median age: 83 years). The participants' experiences in using two commercial AMs together with tablet-based apps for 9 days were investigated. Activity diaries during the usage and interviews after the usage were exploited to gather user experience. Comments in diaries were summarized, and interviews were analyzed by inductive content analysis.


RESULTS
The users (n=8) perceived that, by using the AMs, their awareness of own PA had increased. However, the AMs' impact on the users' motivation for PA and activity behavior varied between participants. The diaries showed that self-estimated physical effort varied between participants and varied for each individual over time. Additionally, participants reported different types of accomplished activities; talking walks was most frequently reported. To be meaningful, measurements need to provide the user with a reliable receipt of whether his or her current activity behavior is sufficient for reaching an activity goal. Moreover, praise when reaching a goal was described as motivating feedback. To be useful, the devices must be easy to handle. In this study, the users perceived wearables as easy to handle, whereas tablets were perceived difficult to maneuver. Users reported in the diaries that the devices had been functional 78% (58/74) of the total test days.


CONCLUSIONS
Activity monitors can be valuable for supporting seniors' PA. However, the potential of the solutions for a broader group of seniors can significantly be increased. Areas of improvement include reliability, usability, and content supporting effective BCTs with respect to increasing older adults' PA.
Physical and chemical characteristics of off vine ripened mango (Mangifera indica L.) fruit (Dodo)

The need to develop the best off vine mango ripening technique for both consumption and processing was investigated. Some physical and chemical measurements were performed on mature Green Dodo mangoes before and during a 3-day and 6-day ripening period by smoked pit ripening (SPR), ethylene (fruit generated) pit ripening (EPR), untreated pit ripening (UPR) and room temperature ripening (RTR) as a control method. The post harvest ripening changes in the quality characteristic of ripe mangoes were correlated among treatments and compared with similar changes in other mango varieties. Changes such as formation of sugars, decreased acidity, and increased carotene reflected the most significant chemical changes in ripeness stage.
A Statically Scheduled Time-Division-Multiplexed Network-on-Chip for Real-Time Systems

This paper explores the design of a circuit-switched network-on-chip (NoC) based on time-division-multiplexing (TDM) for use in hard real-time systems. Previous work has primarily considered application-specific systems. The work presented here targets general-purpose hardware platforms. We consider a system with IP-cores, where the TDM-NoC must provide directed virtual circuits - all with the same bandwidth - between all nodes. This may not be a frequent scenario, but a general platform should provide this capability, and it is an interesting point in the design space to study. The paper presents an FPGA-friendly hardware design, which is simple, fast, and consumes minimal resources. Furthermore, an algorithm to find minimum-period schedules for all-to-all virtual circuits on top of typical physical NoC topologies like 2D-mesh, torus, bidirectional torus, tree, and fat-tree is presented. The static schedule makes the NoC time-predictable and enables worst-case execution time analysis of communicating real-time tasks.
Brute Force Attack on UNIX Passwords with SIMD Computer

As computer technology improves, the security of specific ciphers and one-way hash functions periodically must be reevaluated in light of new technological advances. In this paper we evaluate the security of the UNIX password scheme. We show that the UNIX password scheme is vulnerable to brute-force attack. Using PixelFlow, a SIMD parallel machine, we are able to “crack” a large fraction of passwords used in practice [12] in 2-3 days of computation. We explain how a SIMD machine built in today’s technology could “crack” any UNIX password in two days. We also describe in this paper a simple modification to the UNIX password scheme that makes it harder to break encrypted passwords using dictionary and brute force attack, thus extending the useful life of the UNIX password scheme. The modified password scheme is compatible with the existing password scheme.
Unsupervised Most Frequent Sense Detection using Word Embeddings

An acid test for any new Word Sense Disambiguation (WSD) algorithm is its performance against the Most Frequent Sense (MFS). The field of WSD has found the MFS baseline very hard to beat. Clearly, if WSD researchers had access to MFS values, their striving to better this heuristic will push the WSD frontier. However, getting MFS values requires sense annotated corpus in enormous amounts, which is out of bounds for most languages, even if their WordNets are available. In this paper, we propose an unsupervised method for MFS detection from the untagged corpora, which exploits word embeddings. We compare the word embedding of a word with all its sense embeddings and obtain the predominant sense with the highest similarity. We observe significant performance gain for Hindi WSD over the WordNet First Sense (WFS) baseline. As for English, the SemCor baseline is bettered for those words whose frequency is greater than 2. Our approach is language and domain independent.
A Randomized Trial of Cinacalcet versus Vitamin D Analogs as Monotherapy in Secondary Hyperparathyroidism (PARADIGM).

BACKGROUND AND OBJECTIVES
Direct comparison of cinacalcet and vitamin D analogs as monotherapies to lower parathyroid hormone (PTH) levels has not been undertaken.


DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS
This was a prospective, multicenter, phase 4, randomized, open-label study that enrolled participants from 2010 to 2012. Adult participants (n=312) on hemodialysis with PTH >450 pg/ml were randomized 1:1 to 12 months of treatment with either cinacalcet (n=155) or vitamin D analogs (n=157) to evaluate the mean percentage change in plasma PTH level (primary end point) and the proportion of participants achieving plasma PTH <300 pg/ml or a ≥30% decrease in PTH (secondary end points). A preplanned analysis to determine whether there were important region-by-treatment interactions was also undertaken.


RESULTS
Baseline mean PTH was 846 pg/ml (n=155) for cinacalcet and 816 pg/ml (n=157) for vitamin D analog therapy. The mean (95% confidence interval) percentage change from baseline in PTH was -12.1% (-20.0% to -4.1%) in the cinacalcet arm and -7.0% (-14.9% to 0.8%) in the vitamin D analog arm, a difference of -5.0% (-15.4% to 5.4%) (P=0.35). Similarly, there was no difference in achievement of secondary efficacy end points between arms (19.4% and 15.3% of participants with PTH≤300 pg/ml and 42.6% and 33.8% of participants had a PTH reduction >30% in the cinacalcet and vitamin D analog arms, respectively). A prespecified analysis revealed a large treatment-by-region interaction, with nominally greater response to cinacalcet compared with vitamin D analogs in non-United States participants (US versus non-US participants, P<0.001). Hypocalcemia was more common in the cinacalcet arm, whereas hypercalcemia and hyperphosphatemia occurred more often in the vitamin D analog arm.


CONCLUSIONS
Participants had similar modest reductions in PTH with either cinacalcet or vitamin D analog monotherapy over 52 weeks of treatment, but effects varied by region. Treatments differed with regard to effect on calcium and phosphorus levels.
Considerations for classroom seating arrangements and the role of teacher characteristics and beliefs

As a part of classroom management, teachers face the question of how and where to seat their students. However, it is far from clear what considerations teachers have when making seating arrangements. Therefore, in this study seating arrangement considerations from 50 teachers in grades 4–6 of elementary school were assessed. In Phase 1, teachers were interviewed about their goals and considerations for classroom seating arrangements. Teachers mentioned between 2 and 19 reasons for placing students at specific places in the classroom, with mostly academic considerations. They mainly preferred arrangements in small groups to promote student cooperation. In Phase 2, teachers completed a questionnaire about seating arrangements. This allowed us to examine individual differences between teachers related to gender, years of experience, and beliefs, and the concurrence between the interview and questionnaire data. Teachers reported multiple and various considerations for seating arrangements. Correlations with their general student-oriented or subject-oriented beliefs and personal characteristics were low. The concurrence between measurement methods also was low. The discussion focused on teacher awareness of classroom seating arrangements as an important part of classroom management and a tool for prevention and intervention. & Mariola C. Gremmen m.c.gremmen@rug.nl Yvonne H. M. van den Berg y.vandenberg@psych.ru.nl Eliane Segers e.segers@pwo.ru.nl Antonius H. N. Cillessen a.cillessen@psych.ru.nl 1 Behavioural Science Institute, Radboud University, Montessorilaan 3, 6500 HE Nijmegen, The Netherlands 2 Present Address: Grote Rozenstraat 31, 9712 TG Groningen, The Netherlands 123 Soc Psychol Educ (2016) 19:749–774 DOI 10.1007/s11218-016-9353-y