Miracle-dz/UniFAR-FTUs huggingface dataset:
Expected Performance Centering for Analog/RF Designs

We unite the conventional analog/RF design objectives such as design centering and performance targeting and propose a generalized analog/RF design objective. We propose expected performance centering, i.e., to maximize the expected performance margin of a circuit under process and environmental variations for topology selection with performance specification in a hierarchical design. We develop three methods to compute expected performance margin. Our experimental results show improved expected performance margin achieved by the proposed expected performance centering technique
Multiple human tracking in RGB-depth data: a survey

Multiple human tracking (MHT) is a fundamental task in many computer vision applications. Appearance-based approaches, primarily formulated on RGB data, are constrained and affected by problems arising from occlusions and/or illumination variations. In recent years, the arrival of cheap RGB-depth devices has led to many new approaches to MHT, and many of these integrate colour and depth cues to improve each and every stage of the process. In this survey, the authors present the common processing pipeline of these methods and review their methodology based (a) on how they implement this pipeline and (b) on what role depth plays within each stage of it. They identify and introduce existing, publicly available, benchmark datasets and software resources that fuse colour and depth data for MHT. Finally, they present a brief comparative evaluation of the performance of those works that have applied their methods to these datasets.
Moderating Focus Groups

Preface About This Book Guiding Principles of Moderating What You Need to Do Before the Focus Group What You Need to Do During the Focus Group Selecting the Moderator Personal Qualities of Moderators Roles of Moderators Problems Encountered by Moderators People Problems Assistant Moderator Responsibilities Taking Notes and Recording the Discussion The Rapid Focus Group Rate Yourself - Check Sheets for Moderating Improving Your Moderating Skills Teaching Others to Moderate
The Three P's of Total Risk Management

Current risk-management practices are based on probabilities of extreme dollar losses (e.g., measures like Value at Risk), but these measures capture only part of the story. Any complete risk-management system must address two other important factors—prices and preferences. Together with probabilities, these compose the three P's of “Total Risk Management. ” This article describes how the three P's interact to determine sensible risk profiles for corporations and for individuals—guidelines for how much risk to bear and how much to hedge. By synthesizing existing research in economics, psychology, and decision sciences and through an ambitious research agenda to extend this synthesis into other disciplines, a complete and systematic approach to rational decision making in an uncertain world is within reach.
Particle filter parallelisation using random network based resampling

The particle filter approximation to the posterior density converges to the true posterior as the number of particles used increases. The greater the number of particles, the higher the computational load, which can be implemented by operating the particle filter in parallel architectures. However, the resampling stage in the particle filter requires synchronisation, extensive interchange and routing of particle information, and thus impedes the use of parallel hardware systems. This paper presents a novel resampling technique using a fixed random network. This idea relaxes the synchronisation constraints and minimises the particle interaction to a significant level. Using simulations we demonstrate the validity of our technique to track targets in linear and non-linear sensing scenarios.
Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.
Nambu system associated with n-dimensional maps

We studied that arbitrary 2-dimensional maps are Hamilton system if a initial value of map is a "time" variable. In this paper, we generalize this correspondence, and show that an n-dimensional map is a Nambu system in which one of initial values of the map play a role of "time" variable.
Global Gene Expression Responses to Low- or High-Dose Radiation in a Human Three-Dimensional Tissue Model

Abstract Accumulating data suggest that the biological responses to high and low doses of radiation are qualitatively different, necessitating the direct study of low-dose responses to better understand potential risks. Most such studies have used two-dimensional culture systems, which may not fully represent responses in three-dimensional tissues. To gain insight into low-dose responses in tissue, we have profiled global gene expression in EPI-200, a three-dimensional tissue model that imitates the structure and function of human epidermis, at 4, 16 and 24 h after exposure to high (2.5 Gy) and low (0.1 Gy) doses of low-LET protons. The most significant gene ontology groups among genes altered in expression were consistent with effects observed at the tissue level, where the low dose was associated with recovery and tissue repair, while the high dose resulted in loss of structural integrity and terminal differentiation. Network analysis of the significantly responding genes suggested that TP53 dominated the response to 2.5 Gy, while HNF4A, a novel transcription factor not previously associated with radiation response, was most prominent in the low-dose response. HNF4A protein levels and phosphorylation were found to increase in tissues and cells after low- but not high-dose irradiation.
Experimental Conditions That Enhance Potency of an Antibacterial Oligo-Acyl-Lysyl

ABSTRACT Oligo-acyl-lysyls (OAKs) are synthetic mimics of host defense peptides known to exert antibacterial activity both in cultures and in animal models of disease. Here, we investigated how environmental conditions (temperature, pH, and ionic strength) affect the antibacterial properties of an octamer derivative, C12K-7α8. Data obtained with representative bacteria, including the Gram-negative bacterium Escherichia coli and the Gram-positive bacteria Listeria monocytogenes and Staphylococcus aureus, showed that OAK's potency was proportionally affected by pH changes and subsided essentially throughout a wide range of salt concentrations and temperature values, whereas antistaphyloccocal activity was relatively more vulnerable. It was rather the mode of action that was most susceptible to the environmental changes. Thus, OAK's bactericidal effect was limited to a growth-inhibitory effect under acidic pH, low temperatures, or high salt concentrations, whereas basic pH or high temperatures have enhanced the bactericidal kinetics. Properties of binding to model phospholipid membranes provided evidence that correlated the differential modes of action with variable binding affinities. Interestingly, combination of the optimal incubation conditions resulted in a remarkable increase in potency, as expressed by a 16- to 32-fold reduction in the MIC value and by much faster bactericidal rates (>99% death induced within minutes versus hours) compared with the standard incubation conditions. Collectively, the data suggest that OAKs might be useful in developing design strategies for robust antimicrobial peptides that are able to affect a pathogen's viability under a large spectrum of incubation conditions.
IMp: The customizable LEGO® Pinned Insect Manipulator

Abstract We present a pinned insect manipulator (IMp) constructed of LEGO® building bricks with two axes of movement and two axes of rotation. In addition we present three variants of the IMp to emphasise the modular design, which facilitates resizing to meet the full range of pinned insect specimens, is fully customizable, collapsible, affordable and does not require specialist tools or knowledge to assemble.
Multi-level Modeling of Quotation Families Morphogenesis

This paper investigates cultural dynamics in social media by examining the proliferation and diversification of clearly-cut pieces of content: quoted texts. In line with the pioneering work of Leskovec et al. and Simmons et al. on memes dynamics we investigate in deep the transformations that quotations published online undergo during their diffusion. We deliberately put aside the structure of the social network as well as the dynamical patterns pertaining to the diffusion process to focus on the way quotations are changed, how often they are modified and how these changes shape more or less diverse families and sub-families of quotations. Following a biological metaphor, we try to understand in which way mutations can transform quotations at different scales and how mutation rates depend on various properties of the quotations.
A Review of Geometric Transformations for Nonrigid Body Registration

This paper provides a comprehensive and quantitative review of spatial transformations models for nonrigid image registration. It explains the theoretical foundation of the models and classifies them according to this basis. This results in two categories, physically based models described by partial differential equations of continuum mechanics (e.g., linear elasticity and fluid flow) and basis function expansions derived from interpolation and approximation theory (e.g., radial basis functions, B-splines and wavelets). Recent work on constraining the transformation so that it preserves the topology or is diffeomorphic is also described. The final section reviews some recent evaluation studies. The paper concludes by explaining under what conditions a particular transformation model is appropriate.
A C-SVM Based Anomaly Detection Method for Multi-Dimensional Sequence over Data Stream

Anomaly detection over multi-dimensional data stream has attracted considerable attention recently in various fields, such as network, finance and aerospace. In many cases, anomalies are composed of a sequence of multi-dimensional data, and it's necessary to detect this type of anomalies accurately and efficiently over data stream. Existing online methods of anomaly detection merely focus on the single-dimensional sequence. What's more, current studies about multi-dimensional sequence are mainly concentrated on static database. However, the anomaly detection for multi-dimensional sequence over data stream is much more difficult, due to the complexity of multidimensional sequence processing, the dynamic nature of data stream and the unbalance between normal and abnormal data. Facing these challenges, we propose an anomaly detection method for multi-dimensional sequence over data stream based on cost sensitive support vector machine (C-SVM) called ADMS. First, to improve the accuracy and efficiency, the ADMS transforms multi-dimensional sequences into feature vectors in a lossless way and prunes worthless features of these vectors. And then, the ADMS can detect abnormal sequences over dynamically imbalanced data stream by lively testing these vectors based on C-SVM. Experiments show that the false negative rate (FNR) of the ADMS is lower than 5%, the false positive rate (FPR) is lower than 7%, and the throughput is improved 42% by pruning worthless features. In addition, the AMDS performs well when there are concept drifts over the data stream.
Discrete quantum theories

We explore finite-field frameworks for quantum theory and quantum computation. The simplest theory, defined over unrestricted finite fields, is unnaturally strong. A second framework employs only finite fields with no solution to x2 + 1 = 0, and thus permits an elegant complex representation of the extended field by adjoining i=−1? >. Quantum theories over these fields recover much of the structure of conventional quantum theory except for the condition that vanishing inner products arise only from null states; unnaturally strong computational power may still occur. Finally, we are led to consider one more framework, with further restrictions on the finite fields, that recovers a local transitive order and a locally-consistent notion of inner product with a new notion of cardinal probability. In this framework, conventional quantum mechanics and quantum computation emerge locally (though not globally) as the size of the underlying field increases. Interestingly, the framework allows one to choose separate finite fields for system description and for measurement: the size of the first field quantifies the resources needed to describe the system and the size of the second quantifies the resources used by the observer. This resource-based perspective potentially provides insights into quantitative measures for actual computational power, the complexity of quantum system definition and evolution, and the independent question of the cost of the measurement process.
Support‐seeking, support‐provision and support‐perception in distressed married couples: a multi‐method analysis

An emerging consensus argues for the importance of spousal support in our understanding of how relationships succeed or fail. This report covers two studies that examined support seeking, support provision and support perception in distressed married couples. In Study 1 a total of seventy distressed and seventy non-distressed couples participated in a survey study; in Study 2 twenty distressed and twenty non-distressed couples participated in an observational study. Global self-reports were used in both studies to assess spouses’ support behaviour and perceived support. These measures were supplemented in Study 2 with measures of observed support behaviour and interaction-based perceived support as assessed during specific support interactions. Our self-report and observational measures consistently indicated that distressed marital couples display lower levels of positive support-seeking and emotional or instrumental support provision than non-distressed couples. We also found evidence for higher levels of negative support-seeking and provision behaviour in distressed couples, as compared to non-distressed couples. Distressed spouses also reported lower levels of global and interaction-based perceived support than non-distressed spouses. Practitioner points Assess and evaluate the different support behaviour in couples Explain the interactional support behaviour cycle Increase support skills within the couple Detect and block negative support behaviour
Low power 1 GHz charge pump phase-locked loop in 0.18 µm CMOS process

Demand of modern measurement systems in submicron CMOS process introduced new challenges in design of low power high frequency clock generation systems. Technical possibilities for clock generation using classical oscillator based on a quartz filter is limited to tens of megahertz. Thus, 1 GHz clock generation is not possible without a frequency multiplier system. It is difficult to achieve, because in submicron process, where the integration of analog and digital blocks poses serious challenges. The proposed solution is a low power charge pump phase-locked loop (CPPLL) with the center frequency of 1 GHz. It combines various modern circuit techniques, whose main aim is to lower power consumption, which is below 800 µW for the whole PLL, while maintaining good noise properties, where the jitter rms is 8.87 ps. The proposed phase-locked loop is designed in 0.18 µm CMOS process.
Can haemophilic arthropathy be prevented?

Can haemophilic arthropathy be prevented? The simple answer is that, nowadays, it can. An abundance of published evidence unequivocally attests that haemophilic arthropathy can be prevented in boys with severe haemophilia A or B by the early initiation of regular prophylactic treatment with the respective factor concentrate (FVIII or FIX) (Nilsson et al, 1970, 1976, 1992; Petrini et al, 1991; Aledort et al, 1994; Liesner et al, 1996). As outlined in joint recommendations by the WHO (World Health Organization) and the WFH (World Federation of Hemophilia), agreed on at Geneva in 1994. ‘Since the main goal is to prevent joint bleeding and its sequelae, prophylaxis should be considered optimal management for persons with severe haemophilia A or B (i.e. with basal factor VIII/IX levels <1% of normal). Treatment should be started at the age of 1–2 years and be continued indefinitely. Where prophylaxis is not feasible or appropriate, on-demand therapy should be given’ (Berntorp et al, 1995). This type of prophylaxis is sometimes referred to as primary (long-term or permanent) prophylaxis, as distinct from secondary prophylaxis, i.e. short-term prophylactic treatment given after the onset of recurrent bleeds when arthropathy is usually already manifest. In too many parts of the world, however, fulfilment of these recommendations must be viewed as a long-range goal in haemophilia care, as national economic resources are insufficient for regular prophylactic treatment to be achievable. In many countries the health authorities do not consider the provision of prophylactic treatment to be a necessary criterion of a medically acceptable standard of haemophilia care. Moreover, medical opinion differs not only regarding the relative merits of on-demand treatment, and primary and secondary prophylaxis, but also, even among adherents of primary prophylaxis, regarding the optimal regimen.
Using multi-criteria decision making for personalized point-of-interest recommendations

Location-based business review (LBBR) sites (e.g., Yelp) provide us a possibility to recommend new points of interest (POIs) for users. The geographical position and category of POIs have been considered as two major factors in modeling users' preferences. However, it is argued that the user's visiting behaviors are also affected by the attributes of POIs, which reflect the basic features of the POIs. Besides, a user may have different preference levels on the same POI with regard to different criteria. To this end, we propose a new personalized POI recommendation framework using Multi-Criteria Decision Making (MCDM). Firstly, preference models are built for the user's geographical, category, and attribute preferences. Then, an MCDM-based recommendation framework is designed to iteratively combine the user's preferences on the three criteria and select the top-N POIs as a recommendation list. Experimental results show that our framework not only outperforms the state-of-the-art POI recommendation techniques, but also provides a better trade-off mechanism for MCDM than the weighted sum approach.
Joint Recognition of Multiple Concurrent Activities using Factorial Conditional Random Fields

Recognizing patterns of human activities is an important enabling technology for building intelligent home environments. Existing approaches to activity recognition often focus on mutually exclusive activities only. In reality, people routinely carry out multiple concurrent activities. It is therefore necessary to model the co-temporal relationships among activities. In this paper, we propose using Factorial Conditional Random Fields (FCRFs) for recognition of multiple concurrent activities. We designed experiments to compare our FCRFs model with Linear Chain Condition Random Fields (LCRFs) in learning and performing inference with the MIT House n data set, which contains annotated data collected from multiple sensors in a real living environment. The experimental results show that FCRFs can effectively improve the recognition accuracy up to 10% in the presence of multiple concurrent activities.
Maggots and wound healing: an investigation of the effects of secretions from Lucilia sericata larvae upon the migration of human dermal fibroblasts over a fibronectin‐coated surface

Lucilia sericata larvae, or greenbottle fly maggots, placed within chronic wounds have been observed to remove necrotic tissue and infection. They are also believed to actively promote granulation tissue formation. Interactions between fibroblasts and the surrounding extracellular matrix play a crucial role in tissue formation, influencing fibroblast proliferation, migration, and tissue remodeling. For example, the strength of cell adhesion to surfaces coated with extracellular matrix influences cell motility. L. sericata larval excretory/secretory products having previously been shown to modify fibroblast adhesion to collagen and particularly fibronectin, it was hypothesized that these products would alter fibroblast migration. This was investigated using a two‐dimensional in vitro wound assay, time‐lapse digital photography, enzyme class‐specific substrates and inhibitors, and gel electrophoresis. Results showed that L. sericata excretory/secretory products promoted fibroblast migration upon a fibronectin‐coated surface. This was related to the degradation of fibronectin by serine proteinases within maggot excretion/secretions. The presence of a metalloproteinase activity may also have played a role. Thus, a possible mechanism by which maggots enhance tissue formation within wounds may be via the promotion of fibroblast motility, providing for a wider distribution of viable fibroblasts.
Cost-based variable-length-gram selection for string collections to support approximate queries efficiently

Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in data as well as queries. Several existing algorithms use the concept of "grams," which are substrings of strings used as signatures for the strings to build index structures. A recently proposed technique, called VGRAM, improves the performance of these algorithms by using a carefully chosen dictionary of variable-length grams based on their requencies in the string collection. Since an index structure using fixed-length grams can be viewed as a special case of VGRAM, a fundamental problem arises naturally: what is the relationship between the gram dictionary and the performance of queries? We study this problem in this paper. We propose a dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance. We analyze how a gram dictionary affects the index structure of the string collection and ultimately the performance of queries. We also propose an algorithm for automatically computing a dictionary of high-quality grams for a workload of queries. Our experiments on real data sets show the improvement on query performance achieved by these techniques. To our best knowledge, this study is the first cost-based quantitative approach to deciding good grams for approximate string queries.