Miracle-dz/UniFAR-FTUs huggingface dataset:
Tensión/contratensión sobre el músculo pterigoideo interno. Repercusiones en la dinámica mandibular

Objetive: to assess the short-term effects on mandibular dynamics (in terms of jaw opening and bite force) of the application strain/counterstrain (SCS) on latent myofascial trigger points (MTrPs) of the internal pterygoid muscles. Intervention: forty nine subjects, 25 males and 24 females, were randomly allocated to one of two groups: experimental (25 subjects), who received SCS therapy, and control (24 subjects), who received a placebo treatment. As outcome variables, we considered maximum active jaw opening and maximum bite force. Results: the results showed a significant improvement with respect to active jaw opening [controls: (–0,02) mm ± 0,76; experimental subjects: 1,48 mm ± 1,3; p 0,05). Conclussions: our results suggest that muscular inhibition methods through the application of strain/counterstrain (SCS) could be used in the treatment of the MTrPs of the internal pterygoid muscles in order to improve maximum jaw opening and maximum bite force.
Effects of black carbon mitigation on Arctic climate

Abstract. We use the ECHAM-HAMMOZ aerosol-climate model to assess the effects of black carbon (BC) mitigation measures on Arctic climate. To this end we constructed several mitigation scenarios that implement all currently existing legislation and then implement further reductions of BC in a successively increasing global area, starting from the eight member states of the Arctic Council, expanding to its active observer states, then to all observer states, and finally to the entire globe. These scenarios also account for the reduction of the co-emitted organic carbon (OC) and sulfate (SU). We find that, even though the additional BC emission reductions in the member states of the Arctic Council are small, the resulting reductions in Arctic BC mass burdens can be substantial, especially in the lower troposphere close to the surface. This in turn means that reducing BC emissions only in the Arctic Council member states can reduce BC deposition in the Arctic by about 30 % compared to the current legislation, which is about 60 % of what could be achieved if emissions were reduced globally. Emission reductions further south affect Arctic BC concentrations at higher altitudes and thus only have small additional effects on BC deposition in the Arctic. The direct radiative forcing scales fairly well with the total amount of BC emission reduction, independent of the location of the emission source, with a maximum direct radiative forcing in the Arctic of about −0.4 W m−2 for a global BC emission reduction. On the other hand, the Arctic effective radiative forcing due to the BC emission reductions, which accounts for aerosol–cloud interactions, is small compared to the direct aerosol radiative forcing. This happens because BC- and OC-containing particles can act as cloud condensation nuclei, which affects cloud reflectivity and lifetime and counteracts the direct radiative forcing of BC. Additionally, the effective radiative forcing is accompanied by very large uncertainties that originate from the strong natural variability of meteorology, cloud cover, and surface albedo in the Arctic. We further used the TM5-FASST model to assess the benefits of the aerosol emission reductions for human health. We found that a full implementation in all Arctic Council member and observer states could reduce the annual global number of premature deaths by 329 000 by the year 2030, which amounts to 9 % of the total global premature deaths due to particulate matter.
A Recofigurable Tri-Band Interconnect for Future Network-On-Chip

A Reconfigurable Tri-Band Interconnect for Future Network-On-Chip by Alexander Todd Dilello Master of Science in Electrical Engineering West Virginia University Gyungsu Byun, Ph.D., Chair The scaling of CMOS feature sizes has yielded the capability of integrating heterogeneous intellectual properties (IPs) like graphics processing units (GPUs), digital signal processors (DSPs) and central processing units (CPUs) on a single die. The collection of multiple IPs on a single die presents a problem of reliable communication due to congestion. The infrastructure that facilitates and manages communication among IPs is referred to as a network-on-chip (NoC). Its ultimate goal should be low latency with negligible power and area consumption. Unfortunately, as CMOS feature sizes have been scaling smaller, this has exacerbated latency and signal degradation due to increasing on-chip channel resistance. Furthermore, contemporary interfaces use baseband-only signaling and have critical limitations like exponential energy consumption, limited bandwidth and non-reconfigurable data access. In this work, we propose an energy efficient tri-band (baseband + 2 RF bands) signaling interface that is capable of simultaneous bi-directional communication and reconfigurable data access. Additionally, communication is accomplished through a shared transmission line which reduces the overall number of global interconnections. As a result, this reduces area consumption and mitigates interconnection complexity. The primary significance of this interconnect configuration compared to contemporary designs is an increase of bandwidth and energy efficiency. The interconnect design is composed of a baseband transceiver and two RF (10Ghz and 20GHz) transceivers. The RF transceivers utilize amplitude-shift keying (ASK) modulation scheme. ASK modulation allows ease of circuit design, but most importantly it can be used for noncoherent communication, which we implemented in this system. Noncoherent ASK modulation is area conservative and power efficient since there is no longer a need for powerhungry frequency synthesizers. Moreover, noncoherent ASK demodulation accomplishes direct-down conversation through a passive self-mixer for additional power savings. The results from our work show that a multi-band interconnect is a suitable remedy for future NoC communication that has been reaching its bandwidth limitation with basebandonly signaling. In conclusion, this work demonstrates a sustainable balance of energy efficiency and increased bandwidth for future on-chip interconnect designs.
An extended framework for robot learning during child-robot interaction with human engagement as reward signal

Using robots as therapeutic or educational tools for children with autism requires robots to be able to adapt their behavior specifically for each child with whom they interact. In particular, some children may like to be looked into the eyes by the robot while some may not. Some may like a robot with an extroverted behavior while others may prefer a more introverted behavior. Here we present an algorithm to adapt the robot’s expressivity parameters of action (mutual gaze duration, hand movement expressivity) in an online manner during the interaction. The reward signal used for learning is based on an estimation of the child’s mutual engagement with the robot, measured through non-verbal cues such as the child’s gaze and distance from the robot. We first present a pilot joint attention task where children with autism interact with a robot whose level of expressivity is pre-determined to progressively increase, and show results suggesting the need for online adaptation of expressivity. We then present the proposed learning algorithm and some promising simulations in the same task. Altogether, these results suggest a way to enable robot learning based on non-verbal cues and to cope with the high degree of nonstationarities that can occur during interaction with children.
Approximately Optimal Mechanism Design (Preprint)∗

In the Vickrey or second-price single-item auction (Vickrey, 1961), there is a single seller with a single item; assume for simplicity that the seller has no value for the item. There are n bidders, and each bidder i has a valuation vi that is unknown to the seller. The Vickrey auction is designed to maximize the welfare, which in a single-item auction just means awarding the item to the bidder with the highest valuation. This sealed-bid auction collects a bid from each bidder, awards the item to the highest bidder, and charges the second-highest price. The point of the pricing rule is to ensure that truthful bidding is a dominant strategy for every bidder. Provided every bidder follows its dominant strategy, the auction maximizes welfare ex post (that is, for every valuation profile). In addition to being theoretically optimal, the Vickrey auction has a simple and appealing format. Plenty of real-world examples resemble the Vickrey auction. In light of this confluence of theory and practice, what else could we ask for? To foreshadow what lies ahead, we mention that when selling multiple non-identical items, the generalization of the Vickrey auction is much more complex.
Fuzzy Ontology-Driven Method for Ranking Unexpected Rules

Several rule discovery algorithms have the disadvantage to discover too much patterns sometimes obvious, useless or not very interesting to the user. The evaluation of patterns is based more on objective measures and is not based on prior background domain knowledge. Knowledge about the system contains ambiguity and vagueness. Fuzzy ontologies are able to deal with fuzzy knowledge representing knowledge using fuzzy sets and fuzzy relations. In this paper we propose a new approach for patterns ranking according to their unexpectedness and based on a prior background knowledge represented by domain fuzzy ontology organized as DAG (Directed Acyclic Graph) hierarchy.
User Centric Software Quality Model For Sustainability : A Review

Software quality is a tacit and multifaceted concept of desired combination of software attributes. Quality is commonly considered as product property, thus the product view of quality seeks to identify those properties which can be built into a product and assessed to certify quality. The goal of assessment is to satisfy the stakeholders of the software. However there is no single correct quality model may be accepted by researchers and experts in modelling and measuring the software quality. The goal of quality assessment should move towards sustainable software quality. This paper presents part of work done in assessing software quality for sustainability. Among the objectives is making concerns of user’s perspective is crucial among the principles of assessment. Software quality metrics can be employed to asses and quantify the software quality value and helps in reducing the ambiguity of the view towards sustainable software.
Rapid progressive idiopathic pulmonary arterial hypertension (RCD code: II-1A.1)

A 48-year-old woman was admitted to our centre with symptoms of right heart failure. Pulmonary arterial hypertension (PAH) was diagnosed . The patient’s general condition deteriorated despite initiation of sequential PAH specific therapy and hemodynamic support. Coexisting fungal mural endocarditis led to devastating consequences. Infection presented in a deceptive manner. T he patient was afebrile, inflammatory markers were low, b lood cultures were negative for bacteria , echocardiography revealed only an increased trabeculation of the right ventricle. The authors discuss management of decompensated right ventricular failure secondary to chronic pulmonary hypertension. The literature on fungal mural endocarditis is also reviewed . JRCD 2013 ; 1 (2): 33–38 Key words: progressive idiopathic pulmonary arterial hypertension, right ventricular failure, fungal mural endocarditis, sibutramine
Vitamin E og koronar hjartesjukdom – kvifor manglande effekt i store kliniske studiar?

Background. Oxidative modification of lowdensity lipoprotein (LDL) is likely to play a role in the development of atherosclerosis and coronary heart disease. In vitro studies, animal experiments and several observational investigations suggest that vitamin E is an effective preventive agent. Unfortunately, large clinical studies have failed to confirm these findings. Material and methods. On the basis of literature studies, I discuss the lack of effect. Results. The hypothesis that LDL must be oxidised to be really harmful, could be wrong. If oxidised LDL is an important atherogenetic factor, vitamin E (alpha-tocopherol) might not be a powerful enough antioxidant, especially in the later stages of atherosclerosis. Maybe one needs to use a mixture of different kinds of vitamin E and coantioxidants that can regenerate vitamin E to achieve an effect that is powerful enough? The effect of vitamin E might have been masked by n-3 fatty acids in some studies. The most plausible hypothesis is that only people with extraordinarily high oxidative stress will benefit from vitamin E supplementation. Interpretation. Further research is needed to understand how oxidised LDL and vitamin E affect the development of coronary heart disease. In the meantime it is important to point out that a healthy diet with balanced amounts of antioxidants and enough n-3 fatty acids has been proven effective. Oksidativ modifikasjon av low density lipoprotein (LDL) spelar truleg ei rolle i utviklinga av aterosklerose og koronar hjartesjukdom. In vitro-studiar, dyreforsøk og fleire observasjonsundersøkingar tyder på at vitamin E er eit effektivt førebyggande middel. Diverre har ein i store kliniske studiar ikkje lukkast å stadfeste desse funna. På grunnlag av litteraturstudiar diskuterer eg den manglande effekten. Hypotesen om at LDL må bli oksidert for å bli verkeleg skadeleg, kan vere feil. Dersom oksidert LDL er ein viktig aterogen faktor, så er kanskje ikkje vitamin E (alfatokoferol) ein effektiv nok antioksidant, særskilt i dei seinare stadia av aterosklerose. Kanskje lyt ein nytte ei blanding av ulike typar vitamin E og koantioksidantar som kan regenerere vitamin E for å oppnå kraftig nok effekt? Effekten av vitamin E kan ha blitt maskert av n-3feittsyrer i nokre studiar. Den mest plausible hypotesen er at berre menneske med ekstra høgt oksidativt stress vil ha nytte av vitamin E-tilskot. Det trengs meir forsking for å forstå korleis oksidert LDL og vitamin E påverkar utviklinga av koronar hjartesjukdom. I mellomtida er det viktig å understreke at eit sunt kosthald som inneheld ei balansert mengd med antioksidantar og nok n-3-feittsyrer er prova å vere effektivt.
An Intensity-Based Approach for Valuation of Mortgage Contracts Subject to Prepayment Risk

The models in the literature for valuation of mortgage contracts subject to prepayment can generally be classified into one of two categories: the option-based models and the empirical mortgage-to-mortgage-refinancing models. Using risk-neutral martingale methods together with the intensitybased approach borrowed from credit risk modeling, this paper develops a framework that not only generalizes but considerably extends both approaches. In the case of option-based specifications based on non-optimal liability, our prepayment model is the first which is not tied to some particular numerical procedure. In the case where the state process is a diffusion, the mortgage equation is a semi-linear parabolic PDE. To illustrate this point we consider the continuous time limit of Stanton’s model [40] and show that the model is the first order version of splitting-up numerical method applied to our PDE. Throughout the paper we point out various new ways to develop mortgage modeling.
The Study of College English Teaching Pattern Innovation Based on the Blended Learning Mode

This paper analyzes the new challenges of college English teaching environment, and summarizes the characteristics of blended learning mode in modern distance education under the background of “Internet + education”. By employing four dimensions of teaching resources development, knowledge absorption, evaluation of learning activities, and students’ autonomous learning, summary and reflection after class, this paper focuses on the study of college English teaching pattern innovation. Through combining traditional classroom with web-based learning, this paper studies the characteristics of blended teaching mode, learning methods, teaching process and learning assessment under the background of “Internet +education”, and explores the construction of blended college English teaching mode with support service system in the context of modern distance education, so teachers can provide students with precise curriculum learning guidance by using big data technology methods. The research findings show that through the combination of face-to-face tutoring and online-autonomous learning, modern distance education teaching can organically integrate various resources of college English teaching in open universities to maximum advantages of online learning and face-to-face teaching, which can greatly improve the teaching quality and efficiency. Through implementing the reform of talent cultivation model with more flexibility, it can provide educational teaching support for the construction of learning society, and further strengthen human resources development worldwide.
The Diversification Benefits of Universal Banks

We estimate reduced form equilibrium conditions for the markets for outstanding loans, and new issuance of bonds and stocks for the US economy. We find that both the aggregate issuance of bonds, and the volume of loans respond to fluctuations in industrial production and interest rates, but in opposite directions, so that at the aggregate level loans and bonds are substitutes. This result is supported by the finding that the conditional correlation between the two aggregates is negative. We then jointly study different classes of aggregate loans and find that they display a different behavior over the cycle, respond to different macroeconomic determinants, and their conditional correlations are time-varying and all consistently lower than one. These results suggest that universal banks can potentially reduce the cyclical fluctuations of their revenues by providing direct lending to different classes of borrowers, and by jointly providing both lending and security underwriting services.
TOWARDS EGRESS MODELLING IN VOXEL BUILDING MODELS

Abstract. Egress (or Evacuation) modelling has the purpose to simulate how the people inside a building can move outside in a safe manner and as quick as possible in case of an emergency. The goal can be to assess the safety of an existing building or a building design, to establish evacuation routes and install signage, or even to give real-time guidance to the evacuating crowd during an emergency. In all cases, the availability of a three-dimensional building model allows to generate the necessary input for the egress modelling software. The algorithms for such software can be subdivided into two major categories, working with navigation grids or navigation networks, respectively. The purpose of this paper is to illustrate that voxel-based building models are particularly suited to provide input for both categories. We further illustrate how to process might continue using an algorithm based on (electrical) network analysis, which can be applied in both a gridded and a network-based simulation. We provide preliminary results for the gridded case.
Anomaly Detection and Diagnosis in Manufacturing Systems: A Comparative Study of Statistical, Machine Learning and Deep Learning Techniques

Multivariate sensor data collected from manufacturing and process industries represents actual operational behavior and can be used for predictive maintenance of the plants. Anomaly detection and diagnosis, that forms an integral part of predictive maintenance, in industrial systems is however challenging due to their complex behavior, interactions among sensors, corrective actions of control systems and variability in anomalous behavior. Several statistical techniques for anomaly detection have been in use for a long time and are applied for anomaly detection in continuous as well as batch industrial systems. Further, various machine learning and deep learning techniques for anomaly detection gained significant interest in the recent years. However, anomaly diagnosis that involves localization of the faults did not receive much attention. In this work, we compare the anomaly detection and diagnosis capabilities, in semi-supervised mode, of several statistical, machine learning and deep learning techniques on two systems viz. the interacting quadruple tank (IQT) system and the continuous stirred tank reactor (CSTR) system both of which are representative of the complexity of large industrial systems. The techniques studied include principal component analysis (PCA), Mahalanobis distance (MD), one-class support vector machine (OCSVM), isolation forest, elliptic envelope, dense auto-encoder and long short term memory auto-encoder (LSTM AE). The study revealed that MD and LSTM-AE have the highest anomaly detection capability, followed closely by PCA and OCSVM. The above techniques also exhibited good diagnosis capability. The study indicates that statistical techniques in spite of their simplicity could be as powerful as machine learning and deep learning techniques, and may be considered for anomaly detection and diagnosis in manufacturing systems.
Evolution of Growth Processes of Paraphase Nanostructures of Lead Telluride

The classification and the kinematic analysis of parametrical resonant interactions in the transit section of two-stream superheterodyne free electron laser are carried out. It is found out that realization of four types of parametrical resonant interactions is possible. A number of the investigated variants of interactions have plural character – hundreds and more harmonics connected with each other simultaneously participate in a three-wave parametric resonance. A cubically nonlinear multiharmonic theory of plural parametrical resonant interactions is constructed. It is established that such interactions can substantially influence the development of physical processes in the investigated system. It is offered to use the plural parametrical resonant interactions for the formation of a wide multiharmonic spectrum of waves in cluster two-stream superheterodyne free electron lasers.