Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing a stochastic approach for optimal scheduling of isolated microgrids

This paper investigates the optimal scheduling problem of available energies in a microgrid during islanding periods. Since in many occasions, the islanded duration of microgrids cannot be determined with certainty, the scheduling problem of these systems has been considered as a challengeable task in viewpoint of microgrids operators. In response to this issue, a stochastic model is developed for scheduling of a typical microgrid comprised of conventional and renewable distributed generators (DGs), energy storage systems (ESSs) as well as critical and flexible loads. The associated optimization model of this problem has been formulated as a linear programming (LP) problem. Objective function of this problem is to minimize the expected value of an isolated microgrid total operation cost, which includes the generation cost of local resources and the cost that should be paid to the curtailed loads. Various aspects of proposed model are studied through application to a test microgrid. The results verify the effectiveness of the proposed scheme in enhancing the robustness of the obtained schedule against uncertainties related to islanding duration of the microgrid. It also demonstrates the benefits it will bring to both customers and distribution system operators when sufficient data are not available.
Both environmental tobacco smoke and personal smoking is related to asthma and wheeze in teenagers

Background Environmental tobacco smoke (ETS) has been reported as a significant risk factor for childhood asthma. Among adults, personal smoking is a major cause of respiratory symptoms and diseases. The effects of these exposures on the prevalence of asthma and wheeze among teenagers are less well known. Objective The aim was to study the independent and combined effects of ETS and personal smoking on the prevalence of asthma and wheeze in teenagers. Methods A longitudinal study of asthma and allergic diseases in schoolchildren has been in progress in Northern Sweden since 1996. All children aged 7–8 years in three municipalities were invited and 3430 (97%) participants have been followed by annual questionnaires. At the age 16–17 years, 82% of the initial participants took part in the 2005 survey. Results Prevalence of physician-diagnosed asthma, ever wheeze and current wheeze was significantly higher among those exposed to maternal ETS and among daily smokers. In multivariate analyses, maternal ETS was a significant risk factor for physician-diagnosed asthma and ever wheeze (OR 1.3–1.5) and personal daily smoking for current wheeze (OR 2.0). ORs for asthma and ever wheeze were highest among daily smokers who were also exposed to maternal ETS with ORs of 1.7 and 2.5, respectively. A significant dose–response association between number of cigarettes/day and the prevalence of wheeze was also found. Conclusions Both ETS and personal smoking were significantly related to asthma and wheeze in teenagers. Maternal ETS exposure was associated with lifetime symptoms, but daily smoking among the teenagers was more strongly related to current symptoms.
Formal Aspects of Computing csp 2 B : A Practical Approach To Combining CSP and B

This paper describes the tool csp2B which provides a means of combining CSP-like descriptions with standard B specifications. The notation of CSP provides a convenient way of describing the order in which the operations of a B machine may occur. The function of the tool is to convert CSP-like specifications into standard machine-readable B specifications which means that they may be animated and appropriate proof obligations may be generated. Use of csp2B means that abstract specifications and refinements may be specified purely using CSP or using a combination of CSP and B. The translation is justified in terms of an operational semantics.
Accelerating Remote Logging by Two Level Asynchronous Checkpointing

For frequently data arriving data environment, this paper tackles the following three problems. (1) Maximizing throughput. (2) Minimizing logging time. (3) Minimizing blocking time. To solve these problems, this paper proposes Two Level Asynchronous Checkpointing technique. Furthermore this paper designs and implements the technique within DBMS and experiments are conducted by using the DBMS to evaluate the technique. The result of experiments show that remote logging provides better performance than disk logging, 10 times for (1), 17 times for (2). Furthermore, average blocking time is shown as 4.38 micro seconds.
The Relationship Between Resiliency and Posttraumatic Growth Following the Death of Someone Close

The study investigates the relations of resiliency and posttraumatic growth among people who experienced a death of someone close. The results of 74 participants, mostly women (63.5%) who completed a series of questionnaires measuring resiliency and posttraumatic growth were analyzed. The age of respondents ranged from 21 to 74 years (M = 38.4; SD = 15.5). The Posttraumatic Growth Inventory developed by Tedeschi and Calhoun and The Resiliency Assessment Scale by Ogińska-Bulik and Juczynski were used in the study. Results revealed positive association between resiliency and posttraumatic growth, particularly with increased self-perception and appreciation of life. However, the results of the study indicate that the relationship between the variables is complex and not all dimensions of resiliency increase the level of changes aftermath trauma.
Approximately Optimal Monitoring of Plan Preconditions

Monitoring plan preconditions can allow for replanning when a precondition fails, generally far in advance of the point in the plan where the precondition is relevant. However, monitoring is generally costly, and some precondition failures have a very small impact on plan quality. We formulate a model for optimal precondition monitoring, using partially-observable Markov decisions processes, and describe methods for solving this model effectively, though approximately. Specifically, we show that the single-precondition monitoring problem is generally tractable, and the multiple-precondition monitoring policies can be effectively approximated using single-precondition solutions.
First-principles simulations of 2-D semiconductor devices: Mobility, I-V characteristics, and contact resistance

We report in this paper ab-initio quantum transport simulations of different types of single-layer 2-D semiconductors: transition metal and group IV dichalcogenides in the 2H or 1T phase as well as black phosphorus. The electron and hole phonon-limited mobilities of eight selected 2-D crystals are first analyzed before using these materials as n- or p-type channels of ultra-scaled single-gate transistors, computing their I-V characteristics in the presence of electron-phonon scattering, and comparing them to each other. Finally, the properties of metal-MoS2 contacts are investigated. It is revealed that the current tends to flow at the edge of the metal layer before entering the semiconductor, thus limiting the injection efficiency.
Context Aware Anomalous Behaviour Detection in Crowded Surveillance

This work addresses the detection of human behavioural anomalies in surveillance. We address in particular the problem of detecting subtle behaviour in a crowded behaviourally heterogeneous surveillance scene. We novel methods of extracting scene context and social context to improve the detection of behavioural anomalies, and in particular permit the detection of subtle behavioural anomalies. Our approach is unsupervised, detecting statistical outliers in a dataset by comparrison of the outlier to the full data. We find that our context aware method performs significantly better than the equivalent method without contextual information. We observe that the use of a contextual information leads to the detection of instances of subtly abnormal behaviour, which otherwise remain indistinguishable from normal behaviour. As a society we have the need to monitor public and pri- vate space in order to prevent criminal behaviour and identify security threats. The scale at which surveillance is undertaken, the density of information in video results in a huge amount of data - the analysis of which using human resources is of- ten prohibitively expensive. The solution is to automate human surveillance (12). Such systems have the potential to monitor a greater amount of data at a lower operating cost and miti- gate the burden on security sta . In order to expose salient behaviour in a video we look for abnormal observations. An abnormal event is one which has a low statistical representa- tion in the training data (9). We motivate our by this defini- tion with emphasis upon contextual information as a method of creating distinct separation between otherwise only subtly dis- tinct behaviours. A good behaviour representation should en- code the dataset in such a way that homogeneous clusters of be- haviour can be segmented from the heterogeneous mass of data. Equally a poor behaviour representation is incapable of measur- ing the distinction between desired subgroups of data. Subtle behaviours provide a greater challenge because the information required to segment them from the greater set is not readily measurable. Subtle behaviours can be handled in the follow- ing two ways; firstly by measuring more relevant information which better segments the data into homogeneous subsets, or secondly by implementing a better suited model which is capa- ble of fitting the nuances of the data domain. In this research we tackle the former point; inspired by work in Scene Mod-
Provided for Non-commercial Research and Educational Use Only. Not for Reproduction, Distribution or Commercial Use. Current Challenges to the Clinical Translation of Brain Machine Interface Technology

commercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who know you, and providing a copy to your institution's administrator. All other uses, reproduction and distribution, including without limitation commercial reprints, selling or licensing copies or access, or posting on open internet sites, your personal or institution's website or repository, are prohibited. For exceptions, permission may be sought for such use through Elsevier's permissions site at: Abstract Development of neural prostheses over the past few decades has produced a number of clinically relevant brain–machine interfaces (BMIs), such as the cochlear prostheses and deep brain stimulators. Current research pursues the restoration of communication or motor function to individuals with neurological disorders. Efforts in the field, such as the BrainGate trials, have already demonstrated that such interfaces can enable humans to effectively control external devices with neural signals. However, a number of significant issues regarding BMI performance, device capabilities, and surgery must be resolved before clinical use of BMI technology can become widespread. This chapter reviews challenges to clinical translation and discusses potential solutions that have been reported in recent literature, with focuses on hardware reliability, state-of-the-art decoding algorithms, and surgical considerations during implantation.
User experience of speech controlled media center for physically disabled users

In this paper, we present results from a long-term user pilot study of speech controlled media center. The pilot users in this case were physically disabled and the system was installed in their apartment for six weeks. We designed a multimodal media center interface based on speech. Full speech control is provided with a hands-free speech recognition input method for people with physical disabilities. In addition, the application includes a zoomable context + focus GUI in tight combination with speech output. The resulting interface was designed following human-centered principles. Finally, the results of user experience studies are presented.
Long-term clinical evaluation of the automatic stance-phase lock-controlled prosthetic knee joint in young adults with unilateral above-knee amputation

Abstract Purpose: The purpose of this study was to clinically evaluate the automatic stance-phase lock (ASPL) knee mechanism against participants’ existing weight-activated braking (WAB) prosthetic knee joint. Method: This prospective crossover study involved 10 young adults with an above-knee amputation. Primary measurements consisted of tests of walking speeds and capacity. Heart rate was measured during the six-minute walk test and the Physiological Cost Index (PCI) which was calculated from heart rate estimated energy expenditure. Activity was measured with a pedometer. User function and quality of life were assessed using the Lower Limb Function Questionnaire (LLFQ) and Prosthetic Evaluation Questionnaire (PEQ). Long-term follow-up over 12 months were completed. Results: Walking speeds were the same for WAB and APSL knees. Energy expenditure (PCI) was lower for the ASPL knees (p = 0.007). Step counts were the same for both knees, and questionnaires indicated ASPL knee preference attributed primarily to knee stability and improved walking, while limitations included terminal impact noise. Nine of 10 participants chose to keep using the ASPL knee as part of the long-term follow-up. Conclusions: Potential benefits of the ASPL knee were identified in this study by functional measures, questionnaires and user feedback, but not changes in activity or the PEQ. Keywords: Amputee; artificial knee joint; energy expenditure; prosthesis; stance-phase control; transfemoral amputation, stance-phase control
A Newly Discovered Verotoxin Variant, VT2g, Produced by Bovine Verocytotoxigenic Escherichia coli

ABSTRACT A new verotoxin (VT) variant, designated vt2g, was identified from a bovine strain of verocytotoxigenic Escherichia coli (VTEC) serotype O2:H25. When vt2g was aligned with published sequences of vt2 and vt variants, it exhibited the highest DNA sequence homology with vt2 and vt2c. However, vt2g was not detected by vt2-specific primers and probes, although it was partially neutralized by an antiserum to the VT2A subunit. VT2g was cytotoxic for Vero and HeLa cells and was not activated by mouse intestinal mucus. The vt2g gene was detected in 3 of 409 (0.7%) bovine VTEC strains, including serotypes O2:H25, O2:H45 and Ont:H−.
Hierarchical loop-flower basis function for low frequency breakdown problem

A novel kind of hierarchical loop-flower basis function is proposed to solve the low frequency scattering problem. The hierarchical loop-flower is defined on a hierarchical mesh. The hierarchical loop basis function is used to expand the solenoidal current and the hierarchical flower basis function is used to expand the nonsolenoidal current and thus the low frequency breakdown problem can be remedied. Compared with the conventional hierarchical loop-tree method, the number of the basis function can be reduced a third.
Constraint-based reachability

Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.
Teaching University Students Kanban with a Collaborative Board Game

Kanban is a workflow management method especially suitable for managing continuous software engineering work. We attempted to teach Kanban and lean thinking in a software project management course in Aalto University with a collaborative Kanban board game. Our goal was to measure if the learning goals of the class were reached and to study the student's perceptions of the game. Data was collected from two subsequent classes in 2014 and 2015. Quantitative data was collected with questionnaires and analysed descriptively and statistically. Qualitative data was collected from 57 learning diaries. The students perceived they had learned substantially from the game. They also evaluated the game very positively. However, the qualitative results and the measured learning indicated that the learning goals were only partially reached. The enjoyable game experience did not fully translate into effective learning.
Special Section on Machine Vision Applications Interactive Object Recognition through Hypothesis Generation and Confirmation

An effective human-robot interaction is essential for wide penetration of service robots into the market. Such robot needs a vision system to recognize objects. It is, however, difficult to realize vision systems that can work in various conditions. More robust techniques of object recognition and image segmentation are essential. Thus, we have proposed to use the human user’s assistance for objects recognition through speech. This paper presents a system that recognizes objects in occlusion and/or multicolor cases using geometric and photometric analysis of images. Based on the analysis results, the system makes a hypothesis of the scene. Then, it asks the user for confirmation by describing the hypothesis. If the hypothesis is not correct, the system generates another hypothesis until it correctly understands the scene. Through experiments on a real mobile robot, we have confirmed the usefulness of the system. key words: segmentation, object recognition, human robot interaction, multimodal interface, interactive object recognition
The graph structure of a deterministic automaton chosen at random

An n‐state deterministic finite automaton over a k‐letter alphabet can be seen as a digraph with n vertices which all have k labeled out‐arcs. Grusho (Publ Math Inst Hungarian Acad Sci 5 (1960), 17–61). proved that whp in a random k‐out digraph there is a strongly connected component of linear size, i.e., a giant, and derived a central limit theorem. We show that whp the part outside the giant contains at most a few short cycles and mostly consists of tree‐like structures, and present a new proof of Grusho's theorem. Among other things, we pinpoint the phase transition for strong connectivity. © 2016 Wiley Periodicals, Inc. Random Struct. Alg. , 51, 428–458, 2017
Anatomy‐Guided Linear Atrial Lesions for Radiofrequency Catheter Ablation of Atrial Fibrillation

The surgical atrial maze procedure has provided proof that atrial fibrillation can be cured by performing atrial incisions based on anatomical and electrophysiological principles. Preliminary reports of attempts at radio frequency catheter ablation of atrial fibrillation utilizing an anatomy‐based “linear incision” method have shown the feasibility of the method. However, postprocedural atrial fibrillation recurrence has been common and in addition new, uniform tachycardias have developed in some patients. Both of these outcomes may be in part due to incomplete or inconsistent lesion deployment. This article details the use of the CARTO system for deploying anatomy guided linear atrial lesions for the purpose of curing atrial fibrillation. The procedure is comprised of three phases, which are discussed in detail: (1) baseline map: (2) lesion deployment and; (3) lesion assessment. Using a single standard ablation electrode, lesions can be deployed safely, and complete lesions can be confirmed. Paradigms for right and left atrial incisions are proposed.
Density Delay in the Evolution of Organizational Populations: A Model and Five Empirical Tests

This research was supported by National Science Foundation grant SES-8809006 and by the Institute of Industrial Relations, University of California, Berkeley. An earlier version was presented at the Wharton Conference on Organizational Evolution, December 1988. We appreciate the research assistance of Anand Swaminathan and the comments of John Freeman, Dan Levinthal, and three ASq referees. This paper claims that density at time of founding has a persisting positive effect on organizational mortality rates, net of the effects of contemporaneous density. High density at time of founding results in a liability of resource scarcity for new entrants that hampers organization building. Niches are tightly packed, and entrants must exploit marginal resources. This claim is tested using data on American labor unions (1836-1985), Argentinean newspapers (1800-1900), Irish newspapers (1800-1970), newspaper publishers in the San Francisco region (18401975), and American brewers (1633-1988). As predicted, density at time of founding has a positive and significant effect on mortality rates in all five populations. This finding has potential implications for explaining the fact that the size of organizational populations commonly declines after reaching a peak. '