Miracle-dz/UniFAR-FTUs huggingface dataset:
NTUplace4dr: A Detailed-Routing-Driven Placer for Mixed-Size Circuit Designs With Technology and Region Constraints

A placer without considering modern technology and region constraints could generate solutions with irresolvable detailed-routing (DR) violations or even illegal solutions. This paper presents a high-quality placement algorithm to satisfy technology and region constraints and optimize DR routability with five major techniques: 1) a clustering algorithm followed by two-round quadratic placement to obtain an initial placement satisfying region constraints; 2) a novel density control technique to handle prefixed architectures and minimize global routing congestions; 3) an analytical placement algorithm with new wirelength and density models to consider region constraints; 4) a dynamic penalty increment strategy that reduces wirelength increments during global placement; and 5) a legalization algorithm that preserves the solution quality of global placement while satisfying technology and region constraints. Compared with the winning teams of the ISPD 2015 Blockage-Aware Detailed Routing-Driven Placement Contest and recent works, our placer achieves the best overall score and DR results.
Models of Social Influence: Towards the Next Frontiers

In 1997, Robert Axelrod wondered in a highly influential paper "If people tend to become more alike in their beliefs, attitudes, and behavior when they interact, why do not all such differences eventually disappear? " Axelrodâ€™s question highlighted an ongoing quest for formal theoretical answers joined by researchers from a wide range of disciplines. Numerous models have been developed to understand why and under what conditions diversity in beliefs, attitudes and behavior can co-exist with the fact that very often in interactions, social influence reduces differences between people. Reviewing three prominent approaches, we discuss the theoretical ingredients that researchers added to classic models of social influence as well as their implications. Then, we propose two main frontiers for future research. First, there is urgent need for more theoretical work comparing, relating and integrating alternative models. Second, the field suffers from a strong imbalance between a proliferation of theoretical studies and a dearth of empirical work. More empirical work is needed testing and underpinning micro-level assumptions about social influence as well as macro-level predictions. In conclusion, we discuss major roadblocks that need to be overcome to achieve progress on each frontier. We also propose that a new generation of empirically-based computational social influence models can make unique contributions for understanding key societal challenges, like the possible effects of social media on societal polarization.
Resorbable composite scaffolds for bone tissue engineering

Bone loss associated with trauma osteo-degenerative diseases and tumors has tremendous socioeconomic impact related to personal and occupation disability and health care costs. Bone grafting is often critical to surgical therapies. Autogenous bone is presently the preferred grafting material; however, this holds several disadvantages such as donor site morbidity. In the present climate of increasing life expectancy with an ensuing increase in bone-related injuries, orthopaedic surgery is undergoing a paradigm shift from bone-grafting to bone engineering, where a scaffold is implanted to provide adequate load bearing and enhance tissue regeneration. Our group at Queensland University of Technology (QUT) have developed, characterised and tested polycaprolactone/ tricalcium phosphate (PCL/TCP) composite scaffolds for low load-bearing bone defects. These scaffolds are being further developed for application in higher load bearing sites. Our approach emphasizes the importance of the biomaterials’ structural design, the scaffold architecture and structural and nutritional requirements for cell culture. These first-generation scaffolds made from medical grade PCL (mPCL) have been studied for more than 5 years within a clinical setting 1. This paper describes the application of second-generation scaffolds in small and large animal bone defect models and the ensuing bone regeneration as shown by histology and µCT.
SERGE: Successive Event Recommendation Based on Graph Entropy for Event-Based Social Networks

With the fast development of many event-based social networks (EBSNs), event recommendation, which is to recommend a list of upcoming events to a user according to his preference, has attracted a lot of attentions in both academia and industry. In this paper, we propose a successive event recommendation based on graph entropy (SERGE) to deal with the new event cold start problem by exploiting diverse relations as well as asynchronous feedbacks in EBSNs. The SERGE creates recommendation lists at discrete times during each publication period. At the beginning, it constructs a primary graph (PG) based on the entities and their relations in an EBSN and computes the user-event similarity scores by applying a random walk with restart (RWR) algorithm on PG. At each recommendation time, it then constructs a feedback graph (FG) based on the up-to-date user feedbacks on event reservations and applies the RWR again on FG to compute new user-event similarity scores. We then propose to weight the two sets of similarity scores with the graph entropies of both PG and FG and create the final recommendation lists accordingly. We have crawled two datasets from a real EBSN for two cities, Beijing and Shanghai in China. Experimental results validate the effectiveness and superiority of the proposed SERGE scheme over the peer schemes.
WAFL Iron: Repairing Live Enterprise File Systems

Consistent and timely access to an arbitrarily damaged file system is an important requirement of enterpriseclass systems. Repairing file system inconsistencies is accomplished most simply when file system access is limited to the repair tool. Checking and repairing a file system while it is open for general access present unique challenges. In this paper, we explore these challenges, present our online repair tool for the NetApp® WAFL® file system, and show how it achieves the same results as offline repair even while client access is enabled. We present some implementation details and evaluate its performance. To the best of our knowledge, this publication is the first to describe a fully functional online repair tool.
ICT-enabled social innovation

Social innovation paves the way to resilient society. After financial crisis, in the middle of changing global economy, migrant, climate crisis, the traditional welfare society cannot cope in the traditional bureaucratic way with the challenges, such demography, unemployment, robots and automatization, gender issues. Social innovation is based on the widest inclusion of every stakeholder, citizens, communities, third sector. Ultimate solution does not exist, but there is a rich toolset for specific problems. The paper outlines the architecture of a collaborative framework, which enables the users harmoniously applying different technologies to enhance the ICT-enabled social innovation.
Comparison of immunomagnetic separation beads for detection of six non‐O157 Shiga toxin‐producing Escherichia coli serogroups in different matrices

Immunomagnetic separation used with culture based methods has been a useful technique in the detection of pathogens. However, previous studies have not answered many of the necessary questions for real world applications. The objective of this study was to assess the efficacy of different immunomagnetic separation (IMS) bead types in recovery of the correct serogroup from a mixture of big six non‐O157 Shiga toxin‐producing Escherichia coli strains. To determine the impact of different matrices on recovery, samples of sterile phosphate buffered saline (PBS), sterile and non‐sterile cattle faeces, ground beef and lettuce were inoculated with 10 CFU per ml mixture of isolates representing the six serogroups. After a 6 h incubation at 37°C, samples were mixed with IMS beads from three different commercial sources and plated on eosin methylene blue agar (EMB). Three suspect E. coli colonies were selected from each EMB plate and multiplex polymerase chain reaction was used to determine the serogroup. The rate of correct identification varied with the serogroup, IMS bead manufacturer and matrix. Overall, recovery of the correct serogroup became less likely with increase in matrix complexity, with enrichments containing lettuce having the greatest number of bead types with significantly lower likelihood of correct recovery compared to recovery in PBS.
Evaluating Computational Creativity

This article is a tutorial for researchers who are designing software to perform a creative task and want to evaluate their system using interdisciplinary theories of creativity. Researchers who study human creativity have a great deal to offer computational creativity. We summarize perspectives from psychology, philosophy, cognitive science, and computer science as to how creativity can be measured both in humans and in computers. We survey how these perspectives have been used in computational creativity research and make recommendations for how they should be used.
Virtual environment applications in clinical neuropsychology

Virtual environment (VE) technology is increasingly being recognized as a useful medium for the study, assessment, and rehabilitation of cognitive processes and functional abilities. The capacity of VE technology to create dynamic three-dimensional (3D) stimulus environments, within which all behavioral responding can be recorded, offers clinical assessment and rehabilitation options that are not available using traditional neuropsychological methods. This work has the potential to advance the scientific study of normal cognitive and behavioral processes and to improve our capacity to understand, measure, and treat the impairments typically found in clinical populations with central nervous system (CNS) dysfunction. The paper provides a rationale for the application of VE technology in the areas of neuropsychological assessment and cognitive rehabilitation, presents a tabled summary of the VE literature targeting cognitive/functional processes in clinical CNS populations and briefly describes two of our VE applications targeting attention and visuospatial processing.
Rebuilding Life: Investigating the Long-Term Homecare Needs of Clients With Spinal Cord Injuries

Background: Clients with a spinal cord injury (SCI) must learn to manage their disabilities and may never be able to resume their previous lifestyle. Therefore, receiving relevant information and support from care practitioners and institutions is essential for clients with long-term SCI. Purpose: This study investigated the long-term homecare needs of clients with SCIs. Methods: A qualitative approach was used in this study. Data were collected from March to May 2013. Four SCI associations were selected using purposive sampling, and four focus group interviews were conducted in Northern, Central, Southern, and Eastern Taiwan. Each focus group was composed of 7–12 participants. In-depth interviews (1.5–2.5 hours) were conducted. A content analysis method was adopted for data analysis. Results: Thirty-eight participants took part in the study. The long-term care needs of clients with SCI require the following dynamic processes for rebuilding their lives: physical care and complication prevention, life planning, social support, discovery of the value of existence, and sexual satisfaction. Conclusions/Implications for Practice: The results reveal the long-term care needs of clients with SCI. Nurses are expected to provide client-centered care, emphasize prevention rather than treatment of complications, initiate life planning at the early stages of a client’s rehabilitation, enhance a client’s social support, encourage a client’s search for companionship and search for the value of existence and a life purpose, and be attentive to the sexual concerns of people with physical disabilities.
Finding Key Integer Values in Many Features for Learners' Academic Performance Prediction

In recent years, along with the proliferation of the learning management system (LMS), a large amount of data regarding the interaction between the system and the learners has been accumulated. Correspondingly, various data mining methods have been applied to these data. In order to employ a suitable computational model that is at the core of the data mining method and is not automatically acquired by the mining method itself, it is important to make or find various reasonable hypotheses for target variables. In this paper, we propose a method for analyzing closely the degree to which the explanatory variables represented in integer value contributes to predicting categorical objective variables, such as a learner's academic performance. Specifically, we describe that a decision tree combining support vector machines (SVM) achieves accuracy consistent with existing research, and it contributes further extraction of particular explanatory values from the integer features. Before making a model with SVM, our proposal method expands original features represented by integer value to corresponding binary features. With this expansion of original features, we can identify the key values that closely relate to a learner's academic performance from behavioral features gathered from LMS. Identifying such key values in specific features plays an important role in developing a hypothesis that explains the objective variables, using them as explanatory variables. We believe that closer analysis of these key explanatory values will find latent knowledge that can improve learners' academic abilities
Impact of incident myocardial infarction on the risk of venous thromboembolism: the Tromsø Study

Essentials Registry‐based studies indicate a link between arterial‐ and venous thromboembolism (VTE). We studied this association in a cohort with confounder information and validated outcomes. Myocardial infarction (MI) was associated with a 4.8‐fold increased short‐term risk of VTE. MI was associated with a transient increased risk of VTE, and pulmonary embolism in particular.
Using gated recurrence units neural network for prediction of melt spinning properties

In this paper, a prediction method of the melt spinning properties based on the Gated Recurrence Units (GRU) neural network model is proposed considering the time series property of the data. Spinning process plays a key role in the melt spinning production process, the product of this process is called primary fiber. Primary fiber has three major property indicators: breaking strength, elongation at break and 1.5 times of elongation, its quality directly affects the subsequent processing of the fiber. The algorithm is experimentally based on the data of elongation at break. This experiment result demonstrates that GRU neural network performs better than Long Short Term Memory (LSTM) neural network and other exciting models such as traditional linear regression model and radical basis function neural network. To the best of our knowledge, this is the first time that GRU is applied to melt spinning process prediction.
Wideband Fabry-Perot Cavity Antenna With a Shaped Ground Plane

This paper proposes a novel approach to broaden the 3-dB gain bandwidth of Fabry–Perot cavity (FPC) antennas by utilizing a shaped ground plane. The shaped ground plane is flat in the middle to accommodate the source antenna, and then angled up in the shape of trapezoids. Compared with an FPC antenna with a traditional flat ground plane, the 3-dB gain bandwidth of the one with a shaped ground plane is improved from 11% to 20.2% with the maximum realized gain and the 10-dB impedance bandwidth almost unchanged. To validate the feasibility of the proposed approach, an FPC antenna prototype has been designed, fabricated, and measured. It consists of a U-slot rectangular microstrip patch antenna as the source, a Rogers RT6006 superstrate as the partially reflective surface, and the proposed shaped ground plane. Measured results on input reflection coefficients and radiation patterns agree well with simulated ones. Therefore, this new approach can be an effective way to enhance the gain bandwidth without increasing the cavity profile or using multi-layer superstrate structures.
Robust-adaptive-observer design based on /spl gamma/-positive real problem for sensorless induction-motor drives

This paper proposes a design of a robust-adaptive full-order observer based on the /spl gamma/-positive real problem for sensorless induction-motor drives. The adaptive full-order observer is known to become unstable in a major part of the regenerating-mode low-speed operation, and this prevents the sensorless vector controller from operating an induction motor successfully. In this paper, a design of the observer gain for both stable speed identification and robust flux phase estimation and an adaptive scheme for stator resistance identification are proposed. First, the error system of the adaptive full-order observer is reconsidered-requirements of this observer with a speed identifier are described, in which a simple robust observer gain design in the sense of H/sub /spl infin// optimization is not useful in reality. Next, in order to satisfy all the requirements of the robust adaptive observer, the design of the observer gain based on the /spl gamma/-positive real problem and the adaptive scheme for stator resistance are described. Finally, several experimental results show the feasibility and effectiveness of the proposed design.
Efficient Parametric Identification for STL

We describe a new algorithm for the parametric identification problem for signal temporal logic (STL), stated as follows. Given a dense-time real-valued signal w and a parameterized temporal logic formula φ, compute the subset of the parameter space that renders the formula satisfied by the signal. Unlike previous solutions, which were based on search in the parameter space or quantifier elimination, our procedure works recursively on φ and computes the evolution over time of the set of valid parameter assignments. This procedure is similar to that of monitoring or computing the robustness of φ relative to w. Our implementation and experiments demonstrate that this approach can work well in practice.
Biological Evaluation of a Novel Tissue Engineering Scaffold of Layered Double Hydroxides (LDHs)

Bone Tissue Engineering (BTE) composed of three main parts: scaffold, cells and signaling factors. Several materials and composites are suggested as a scaffold for BTE. Biocompatibility is one of the most important property of a BTE scaffold. In this work synthesis of a novel nanocomposite including layered double hydroxides (LDH) and gelatin is carried out and its biological properties were studied. The co-precipitation (pH=11) method was used to prepare the LDH powder, using calcium nitrate, Magesium nitrate and aluminum nitrate salts as starting materials. The resulted precipitates were dried. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) analyses were used to characterize the synthesized powders. The results demonstrated the presence of nanocrystals of Ca-LDH and Mg-LDH as Hexagonal and Layered Morphology. The obtained powders were composed to gelatin via solvent casting method then freez dried. The scaffold was prepared via membrane lamination method from the resulted layers that linked together with gelatin as binder. In order to investigate the scaffold cytotoxicity MTT assay was done with a osteosarcoma cell line. No toxic response was observed in specimens. As a major result, it was demonstrated that the specimen showed a significant cellular response. Then osteosarcoma cells were cultured for 7-day and 14-day extract of powders. The composites osteoconductivity was investigate with cells alkaline phosphatase extraction. The results demonstrated that the Ca-LDH/gelatin composite scaffold has a good potential for bone tissue engineering applications and Mg-LDH specimen has a better osteconductivity.
Models of Closest Marginal States of Power Systems in p-Norms

In order to maintain power system security at the appropriate level and low cost, it is essential to accurately assess steady-state stability limits and power flow feasibility boundaries, i.e., power system marginal states (MS). This paper is devoted to researching the closest MS models in the p-norms. The theoretical studies have revealed that the model of the closest MS in the weighted max-norm, which considers errors of the power change forecast by means of the weighted Euclidean norm, corresponds most closely to requirements of the system operator (SO) for an assessment of the steady-state stability reserve and for the preventive control. At the same time the model of the closest MS in the one-norm best satisfies SO requirements for the corrective and emergency control, and for moving a system state into the power flow feasibility region. This model gives a control action to a critical bus, adding others only in the case of a dosage lack. As a result minimum number of buses will be affected, and minimum loads will be shed.
The adjective in Germanic and Romance

In this introductory chapter the similarities and differences in the development and the current behavior of the adjective in Germanic and Romance, both within and between the language families, are discussed. A deeper analysis suggests that what seem to be differences may in fact be similarities and vice versa. Topics that are discussed are the emergence of the adjective as a category, the distinction between attributive and predicative adjectives, the position of adjectives within the noun phrase, and adjectival inflection. This introduction forms the basis for the chapters that follow and in which current visions on variation and change with respect to the adjective in Germanic and Romance are presented in more detail.
Design of Compact but Fabrication-Tolerant Vertical Coupler for Active–Passive Integration

We propose a novel scheme of compact but fabric-ation-tolerant vertical coupler based on resonant coupling for active–passive integration. The transfer matrix method is used to carry out the design and optimization of various vertical coupler structures efficiently. Simulations show that transfer efficiency higher than 96% can be achieved for the proposed coupler with a length as short as 55 μm which is about half of a classic adiabatic coupler design. By employing a mode beating section with a length twice the beating length and a relatively steep linear taper, the proposed resonant coupler breaks the strongly periodic behavior of mode beating in conventional resonant couplers, thus dramatically improving the fabrication tolerance. The proposed resonant coupler is predicted with a fabrication tolerance of 380 nm which is about 2.5 times of the conventional resonant coupler, under the condition that the transfer efficiency is higher than 90%. The scheme of this paper can be widely used to design compact and fabrication-tolerant couplers.