Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Simulation of Temperature Evolution of Overhead Transmission Lines Based on Analytical Solution and NWP

Transmission lines are vital components in power systems. Outages of transmission lines caused by overtemperature are a major threat to system reliability, so it is necessary to efficiently simulate line temperature under both normal operation conditions and foreseen fault conditions. Existing methods based on thermal-steady-state analyses cannot support the simulation of transient temperature evolution, and, thus, cannot provide timing information needed for taking remedial actions. Moreover, the conventional numerical method requires huge computational efforts and barricades system-wide analysis. In this regard, this paper derives an approximate analytical solution of transmission-line temperature evolution enabling efficient analysis on multiple operation states. Considering the uncertainties in environmental parameters, the region of overtemperature is constructed in the environmental parameter space to realize the overtemperature risk assessment in both the planning stage and real-time operations. A test on a typical conductor model verifies the accuracy of the approximate analytical solution. Based on the analytical solution and numerical weather prediction data, an efficient simulation method for temperature evolution of transmission systems under multiple operation states is proposed. As demonstrated on a Northeast Power Coordinating Council 140-bus system, it achieves over 1000 times of efficiency enhancement, verifying its potential in online risk assessment and decision support.
First-order dynamical phase transition in models of glasses: an approach based on ensembles of histories

We investigate the dynamics of kinetically constrained models of glass formers by analysing the statistics of trajectories of the dynamics, or histories, using large deviation function methods. We show that, in general, these models exhibit a first-order dynamical transition between active and inactive dynamical phases. We argue that the dynamical heterogeneities displayed by these systems are a manifestation of dynamical first-order phase coexistence. In particular, we calculate dynamical large deviation functions, both analytically and numerically, for the Fredrickson–Andersen model, the East model, and constrained lattice gas models. We also show how large deviation functions can be obtained from a Landau-like theory for dynamical fluctuations. We discuss possibilities for similar dynamical phase-coexistence behaviour in other systems with heterogeneous dynamics.
Assessing the potential of calcium‐based artificial ocean alkalinization to mitigate rising atmospheric CO2 and ocean acidification

Enhancement of ocean alkalinity using calcium compounds, e.g., lime has been proposed to mitigate further increase of atmospheric CO2 and ocean acidification due to anthropogenic CO2 emissions. Using a global model, we show that such alkalinization has the potential to preserve pH and the saturation state of carbonate minerals at close to today's values. Effects of alkalinization persist after termination: Atmospheric CO2 and pH do not return to unmitigated levels. Only scenarios in which large amounts of alkalinity (i.e., in a ratio of 2:1 with respect to emitted CO2) are added over large ocean areas can boost oceanic CO2 uptake sufficiently to avoid further ocean acidification on the global scale, thereby elevating some key biogeochemical parameters, e.g., pH significantly above preindustrial levels. Smaller‐scale alkalinization could counteract ocean acidification on a subregional or even local scale, e.g., in upwelling systems. The decrease of atmospheric CO2 would then be a small side effect.
Sequence-to-point learning with neural networks for nonintrusive load monitoring

Energy disaggregation (a.k.a nonintrusive load monitoring, NILM), a single-channel blind source separation problem, aims to decompose the mains which records the whole house electricity consumption into appliance-wise readings. This problem is difficult because it is inherently unidentifiable. Recent approaches have shown that the identifiability problem could be reduced by introducing domain knowledge into the model. Deep neural networks have been shown to be a promising approach for these problems, but sliding windows are necessary to handle the long sequences which arise in signal processing problems, which raises issues about how to combine predictions from different sliding windows. In this paper, we propose sequence-to-point learning, where the input is a window of the mains and the output is a single point of the target appliance. We use convolutional neural networks to train the model. Interestingly, we systematically show that the convolutional neural networks can inherently learn the signatures of the target appliances, which are automatically added into the model to reduce the identifiability problem. We applied the proposed neural network approaches to real-world household energy data, and show that the methods achieve state-of-the-art performance, improving two standard error measures by 84% and 92%.
Does Empathy Predict Instructional Assignment-Related Stress? A Study in Special and General Education Teachers

Abstract The role of empathy in the teaching profession has been vastly investigated in relation to its effect on students, but research on how teachers’ empathy affects their own well-being at work is limited. This study investigated empathy and instructional assignment-related stress factors of primary school teachers serving in general or special education; moreover, it investigated if empathy predicted instructional assignment-related stress. Data were collected from 190 primary school teachers using the Interpersonal Reactivity Index and the Inventory of Job-related Stress Factors. Teachers reported moderately high levels of perspective-taking and empathic concern and lower levels of fantasising and personal distress. Also, they reported moderate to low levels of stress regarding instructional assignment-related factors. General and special education teachers did not differ in their reported scores on empathy or stress-related factors. Finally, it was found that instructional assignment-related stress factors can be predicted by personal distress and fantasising; however, the core empathy skills (empathic concern and perspective taking) were not found to be strong predictors of the stress factors tested.
SocialMood: A visualization tool to measure the mood of students in social networks

Based on the arena of social networks (SN), this study, through of a visualization tool aims to identify trends mood among undergraduate students. Combining the methodology Self-Assessment Manikin (SAM), which originated in the field of Psychology, the system filters the content provided on the Web and isolates certain words, establishing a range of values as perceived positive, negative or neutral. A data base summarizing the results, assisting in the construction and visualization of behavioral profiles generic, so we have a guideline for the visualization of information about SN through information visualization (IV) tool.
Implicit and Explicit Evaluation of Visual Symmetry as a Function of Art Expertise

In perception, humans typically prefer symmetrical over asymmetrical patterns. Yet, little is known about differences in symmetry preferences depending on individuals’ different past histories of actively reflecting upon pictures and patterns. To address this question, we tested the generality of the symmetry preference for different levels of individual art expertise. The preference for symmetrical versus asymmetrical abstract patterns was measured implicitly, by an Implicit Association Test (IAT), and explicitly, by a rating scale asking participants to evaluate pattern beauty. Participants were art history and psychology students. Art expertise was measured using a questionnaire. In the IAT, art expertise did not alter the preference for symmetrical over asymmetrical patterns. In contrast, the explicit rating scale showed that with higher art expertise, the ratings for the beauty of asymmetrical patterns significantly increased, but, again, participants preferred symmetrical over asymmetrical patterns. The results are discussed in light of different theories on the origins of symmetry preference. Evolutionary adaptation might play a role in symmetry preferences for art experts similarly to nonexperts, but experts tend to emphasize the beauty of asymmetrical depictions, eventually considering different criteria, when asked explicitly to indicate their preferences.
Dual-Quality 4:2 Compressors for Utilizing in Dynamic Accuracy Configurable Multipliers

In this paper, we propose four 4:2 compressors, which have the flexibility of switching between the exact and approximate operating modes. In the approximate mode, these dual-quality compressors provide higher speeds and lower power consumptions at the cost of lower accuracy. Each of these compressors has its own level of accuracy in the approximate mode as well as different delays and power dissipations in the approximate and exact modes. Using these compressors in the structures of parallel multipliers provides configurable multipliers whose accuracies (as well as their powers and speeds) may change dynamically during the runtime. The efficiencies of these compressors in a 32-bit Dadda multiplier are evaluated in a 45-nm standard CMOS technology by comparing their parameters with those of the state-of-the-art approximate multipliers. The results of comparison indicate, on average, 46% and 68% lower delay and power consumption in the approximate mode. Also, the effectiveness of these compressors is assessed in some image processing applications.
Efficacy of mediastinal lymph node dissection during thoracoscopic lobectomy.

While the first description of thoracoscopy occurred as early as 1910 (1), the first successful attempts of video-assisted thoracoscopic (VATS) lobectomy for non-small cell lung cancer (NSCLC) did not take place until the early 1990s (2). As VATS lobectomy continues to gain acceptance as the less invasive alternative to open thoracotomy, extensive research has been conducted to compare its efficacy, postoperative outcomes and oncologic effectiveness to thoracotomy. Despite its many proven advantages, concerns regarding the oncologic effectiveness of VATS lobectomy remain as one of the major obstacles to its wider adoption (3). As an important assessment for accurate staging of NSCLC, adequate evaluation of lymph nodes, especially mediastinal lymph nodes, has been the center of the controversy.
Expression of the SART‐1 Antigens in Uterine Cancers

We recently reported that the SART‐1 gene, encoding the SART‐1259 tumor antigen which is recognized by HLA‐A26‐restricted cytotoxic T lymphocytes (CTLs), is expressed in the cytosol of squamous cell carcinomas and adenocarcinomas. The present study deals with the expression of SART‐1259 and SART‐1800 antigens in uterine cancers. The SART‐1259 antigen was detected in the cytosol fraction of 4 of 8 uterine cancer cell lines, 24 of 74 (32%) uterine cancer tissues, 0 of 7 uterine myomas, and 0 of 5 non‐tumorous uterine tissues. The SART‐1800 antigen was expressed in the nuclear fraction of all the uterine cancer cell lines, 41 of 74 (55%) uterine cancer tissues, 0 of 7 myomas, and 3 of 5 non‐tumorous uterine tissues. The SART‐1259+ uterine cancer cells were recognized by HLA‐A24 restricted and SART‐1 specific CTLs. Therefore, SART‐1259 antigen could be an appropriate vaccine candidate for a relatively large number of uterine cancer patients.
Year : 2009 Versican V 2 assembles the extracellular matrix surrounding the nodes of ranvier in the CNS

The CNS-restricted versican splice-variant V2 is a large chondroitin sulfate proteoglycan incorporated in the extracellular matrix surrounding myelinated fibers and particularly accumulating at nodes of Ranvier. In vitro, it is a potent inhibitor of axonal growth and therefore considered to participate in the reduction of structural plasticity connected to myelination. To study the role of versican V2 during postnatal development, we designed a novel isoform-specific gene inactivation approach circumventing early embryonic lethality of the complete knock-out and preventing compensation by the remaining versican splice variants. These mice are viable and fertile; however, they display major molecular alterations at the nodes of Ranvier. While the clustering of nodal sodium channels and paranodal structures appear in versican V2-deficient mice unaffected, the formation of the extracellular matrix surrounding the nodes is largely impaired. The conjoint loss of tenascin-R and phosphacan from the perinodal matrix provide strong evidence that versican V2, possibly controlled by a nodal receptor, organizes the extracellular matrix assembly in vivo.
Emotion in Conflict and Negotiation: Introducing the Emotions as Social Information (EASI) Model

This paper reviews the current state of research on the interpersonal effects of emotions in conflict and negotiation. The review shows that a great variety of emotions, such as anger, happiness, guilt, regret, disappointment, and worry, have pervasive effects on negotiation behavior and conflict development. However, the review also reveals some inconsistent findings, especially with regard to the impact of anger and happiness on cooperation and competition. To understand these apparent inconsistencies, I introduce a new model of the interpersonal effects of emotions in conflict and negotiation - the Emotions as Social Information (EASI) model. The EASI model posits that emotions may exert interpersonal influence via two distinct paths - an informational-strategic path and an affective - relational path. Behavior is proposed to depend on the relative strength of these two routes, which is in turn determined by individuals' information processing tendencies and a number of situational characteristics, which are also discussed. I conclude by identifying some avenues for future inquiry.
High Affinity Promotes Internalization of Engineered Antibodies Targeting FGFR1

Fibroblast growth factor receptor 1 (FGFR1) is a plasma membrane protein that transmits signals from the extracellular environment, regulating cell homeostasis and function. Dysregulation of FGFR1 leads to the development of human cancers and noncancerous diseases. Numerous tumors overproduce FGFR1, making this receptor a perspective target for cancer therapies. Antibody-drug conjugates (ADCs) are highly potent and selective anticancer agents. ADCs are composed of antibodies (targeting factors) fused to highly cytotoxic drugs (warheads). The efficiency of ADC strategy largely depends on the internalization of cytotoxic conjugate into cancer cells. Here, we have studied an interplay between affinity of anti-FGFR1 antibodies and efficiency of their cellular uptake. We have developed a unique set of engineered anti-FGFR1 antibodies that bind the same epitope in the extracellular part of FGFR1, but with different affinities. We have demonstrated that these antibodies are effectively taken up by cancer cells in the FGFR1-dependent manner. Interestingly, we have found that efficiency, defined as rate and level of antibody internalization, largely depends on the affinity of engineered antibodies towards FGFR1, as high affinity antibody displays fastest internalization kinetics. Our data may facilitate design of therapeutically relevant targeting molecules for selective treatment of FGFR1 overproducing cancers.
Noise reduction by vector median filtering

ABSTRACTThe scalar median filter (SMF) is often used to reduce noise in scalar geophysical data. We present an extension of the SMF to a vector median filter (VMF) for suppressing noise contained in geophysical data represented by multidimensional, multicomponent vector fields. Although the SMF can be applied to each component of a vector field individually, the VMF is applied to all components simultaneously. Like the SMF, the VMF intends to suppress random noise while preserving discontinuities in the vector fields. Preserving such discontinuities is essential for exploration geophysics because discontinuities often manifest important geologic features such as faults and stratigraphic channels. The VMF is applied to synthetic and field data sets. The results are compared to those generated by using SMF, f-x deconvolution, and mean filters. Our results indicate that the VMF can reduce noise while preserving discontinuities more effectively than the alternatives. In addition, a fast VMF algorithm is descr.
Holistic Virtual Machine Scheduling in Cloud Datacenters towards Minimizing Total Energy

Energy consumed by Cloud datacenters has dramatically increased, driven by rapid uptake of applications and services globally provisioned through virtualization. By applying energy-aware virtual machine scheduling, Cloud providers are able to achieve enhanced energy efficiency and reduced operation cost. Energy consumption of datacenters consists of computing energy and cooling energy. However, due to the complexity of energy and thermal modeling of realistic Cloud datacenter operation, traditional approaches are unable to provide a comprehensive in-depth solution for virtual machine scheduling which encompasses both computing and cooling energy. This paper addresses this challenge by presenting an elaborate thermal model that analyzes the temperature distribution of airflow and server CPU. We propose GRANITE – a holistic virtual machine scheduling algorithm capable of minimizing total datacenter energy consumption. The algorithm is evaluated against other existing workload scheduling algorithms MaxUtil, TASA, IQR and Random using real Cloud workload characteristics extracted from Google datacenter tracelog. Results demonstrate that GRANITE consumes 4.3—43.6 percent less total energy in comparison to the state-of-the-art, and reduces the probability of critical temperature violation by 99.2 with 0.17 percent SLA violation rate as the performance penalty.
Sonographic Evaluation of Pleural Effusion

Background: Although at times small amounts of pleural fluid is detected on the lateral decubitus chest radiograph, this may be impossible to obtain in severely ill patients. Because of its ready availability and ability for bedside imaging, ultrasonography has become a crucial imaging modality not only in detecting the presence of pleural fluid but also as a guide to aspiration. Aims: To sonographically determine the nature of pleural effusions. To analyze predictability of both benign and malignant pleural effusions and to study statistical value of various ultrasound characteristics in differentiating exudative and transudative as well as benign and malignant effusions in correlation with thoracocentesis. Material and Methods: Sonographic feature as well as fluid cytology was evaluated. Following categorization into exudates or transudate as well as benign or malignant the diagnosis was then correlated biochemically. Results: Transudates were anechoic, while an anechoic effusion may be either a transudate or an exudate. Complex septation, internal echoes, thickened pleura or homogeneously echogenic patterns were always exudates. Sonographic findings of pleural nodules and associated parenchymal lesions in the lung and liver were indicative of malignancy. Conclusions: Ultrasound in addition to being highly sensitive for pleural effusion also aided in characterizing the nature and minimizing the complications during thoracocentesis. Pleural effusions were categorized into exudates and transudate as well as benign and malignant with a certain degree of confidence based on sonographic findings.
POIsam: a System for Efficient Selection of Large-scale Geospatial Data on Maps

In this demonstration we present POIsam, a visualization system supporting the following desirable features: representativeness, visibility constraint, zooming consistency, and panning consistency. The first two constraints aim to efficiently select a small set of representative objects from the current region of user's interest, and any two selected objects should not be too close to each other for users to distinguish in the limited space of a screen. One unique feature of POISam is that any similarity metrics can be plugged into POISam to meet the user's specific needs in different scenarios. The latter two consistencies are fundamental challenges to efficiently update the selection result w.r. t. user's zoom in, zoom out and panning operations when they interact with the map. POISam drops a common assumption from all previous work, i.e. the zoom levels and region cells are pre-defined and indexed, and objects are selected from such region cells at a particular zoom level rather than from user's current region of interest (which in most cases do not correspond to the pre-defined cells). It results in extra challenge as we need to do object selection via online computation. To our best knowledge, this is the first system that is able to meet all the four features to achieve an interactive visualization map exploration system.
A simulation study of xcp-b performance in wireless multi-hop networks

XCP-b proposes a modification to the XCP router algorithm that computes the spare bandwidth. The modification removes the need for an XCP router to know the exact capacity of the channel, making it possible to use the XCP-b variant in transmission media where the capacity is hard to measure. An example of this kind of medium is the IEEE 802.11. Previous work shows that XCP-b behaves well in single-hop wireless networks and that it outperforms TCP in terms of fairness, queuing delay, stability and efficiency when the bandwidth delay product of the network grows. In this paper we extend the validation and evaluation of XCP-b to the case of multi-hop wireless networks, both stand-alone and as access networks to other wired networks. The results show that XCP-b maintains its fundamental characteristics in wireless multi-hop scenarios, such as stable throughput and low standing queues, while distributing the bandwidth fairly and using the available capacity efficiently. The simulations also show that XCP-b produces congestion window values that are closer than TCP to the theoretical upper-bound which maximizes spatial reuse.
Best of two worlds: Secure cloud federations meet eIDAS

The federation of information technology (IT) systems is a common approach to bundle capabilities and get the best results for all participants. Cloud computing and electronic identity (eID) are only two out of many domains, for which federated solutions have been a topic of scientific and corporate interest during the past years. Recently, the H2020 project SUNFISH has introduced a new cloud-federation approach called ‘Federation as a Service’ (FaaS). FaaS enables secure cloud federations, where data owners remain in full control of their data and workflows. In this paper, we identify shortcomings of the FaaS approach in terms of secure and reliable user authentication. In this sense, data security and protection mechanisms are only as good as the applied authentication measures. We solve this issue by proposing the integration of an existing pan-European federation of national eID systems into FaaS. This increases security guarantees of FaaS by using a trustworthy and liable eID solution that has a strong legal basis in the form of the EU eIDAS Regulation. A first successful implementation and deployment of the proposed solution demonstrates its feasibility and shows the great potential of combining federation solutions from the cloud domain and the eID domain.