Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability analysis of nonlinear circuits driven with modulated signals

Nonlinear microwave circuits are usually simulated with the harmonic-balance method, which is insensitive to the stability properties of the solution obtained. Therefore, this method must be complemented with stability-analysis techniques, in order to check the physical existence of the solution. Existing techniques assume a periodic excitation, usually consisting of a single tone. However, practical circuits such as power amplifiers are generally be driven by modulated signals or multiple input tones. This paper presents a methodology for the stability analysis of nonlinear circuits in the presence of modulation signals. This methodology is based on the determination of the time-varying poles associated to an input-output representation of the system. In the presence of modulated signals, this representation is obtained by linearizing the envelope-transient system that rules the circuit behavior about the modulated steady-state solution. The formulation and methodology have been applied to a practical power-combined amplifier at 3 GHz, with very good results in the comparison with independent simulations and experimental results.
Quantum magnets on the honeycomb and triangular lattices at T=0.

We use series expansions around the ising limit to study several anisotropic quantum spin models on the honeycomb and triangular lattices. These include the antiferromagnetic spin-1/2 and spin-1 Heisenberg model, and the XY antiferromagnet on the honeycomb lattice, and alos the XY ferromagnet on the triangular lattice. Series are calculated for the ground-stae energy energy gap, magnetization, and magnetic susceptibility in each spin direction
Mutations of the Drosophila dDP,dE2F, and cyclin E Genes Reveal Distinct Roles for the E2F-DP Transcription Factor and Cyclin E during the G1-S Transition

ABSTRACT Activation of heterodimeric E2F-DP transcription factors can drive the G1-S transition. Mutation of the Drosophila melanogaster dE2F gene eliminates transcriptional activation of several replication factors at the G1-S transition and compromises DNA replication. Here we describe a mutation in theDrosophila dDP gene. As expected for a defect in the dE2F partner, this mutation blocks G1-S transcription ofDmRNR2 and cyclin E as previously described for mutations of dE2F. Mutation of dDP also causes an incomplete block of DNA replication. When S phase is compromised by reducing the activity of dE2F-dDP by either a dE2F ordDP mutation, the first phenotype detected is a reduction in the intensity of BrdU incorporation and a prolongation of the labeling. Notably, in many cells, there was no detected delay in entry into this compromised S phase. In contrast, when cyclin E function was reduced by a hypomorphic allele combination, BrdU incorporation was robust but the timing of S-phase entry was delayed. We suggest that dE2F-dDP contributes to the expression of two classes of gene products: replication factors, whose abundance has a graded effect on replication, and cyclin E, which triggers an all-or-nothing transition from G1 to S phase.
Primary structure of diphtheria toxin fragment B: structural similarities with lipid-binding domains

Two different lipid-associating domains have been identified in the B fragment of diphtheria toxin using automated Edman degradation of its cyanogen bromide peptides, secondary structure prediction analysis, and comparisons with known phospholipid-interacting proteins. The first domain is located in the highly hydrophilic (polarity index [PI] = 61.0%) 9.00-dalton N-terminal region of fragment B. This region shows primary and predicted secondary structures dramatically similar to those found for the phospholipid headgroup-binding domains of human apolipoprotein A1 (surface lipid-associating domain). The second domain is located in the highly hydrophobic (PI = 32.4%) middle region of fragment B. Its structure resembles that found for the membranous domain of intrinsic membrane proteins (transverse lipid-associating domain). In contrast, the hydrophilic C-terminal 8,000-dalton region of fragment B (PI = 53.8%) does not show structural similarity with lipid- associating domains.
Multistream speaker diarization beyond two acoustic feature streams

Speaker diarization for meetings data are recently converging towards multistream systems. The most common complementary features used in combination with MFCC are Time Delay of Arrival (TDOA). Also other features have been proposed although, there are no reported improvements on top of MFCC+TDOA systems. In this work we investigate the combination of other feature sets along with MFCC+TDOA. We discuss issues and problems related to the weighting of four different streams proposing a solution based on a smoothed version of the speaker error. Experiments are presented on NIST RT06 meeting diarization evaluation. Results reveal that the combination of four acoustic feature streams results in a 30% relative improvement with respect to the MFCC+TDOA feature combination. To the authors' best knowledge, this is the first successful attempt to improve the MFCC+TDOA baseline including other feature streams.
Decreasing the dispatch time of medical reports sent from hospital to primary care with Lean Six Sigma.

RATIONALE, AIMS AND OBJECTIVES Timely communication is important to ensure high-quality health care. To facilitate this, the Gastro Intestinal Oncology Center Amsterdam (GIOCA) stipulated to dispatch medical reports on the day of the patient's visit. However, with the increasing number of patients, administrative processes at GIOCA were under pressure, and this standard was not met for the majority of patients. The aim and objective of this study was to dispatch 90% of medical reports on the day of the patient's visit by improving the logistic process. METHODS To assess the main causes for a prolonged dispatch time and to design improvements actions, the roadmap offered by Lean Six Sigma (LSS) was used, consisting of five phases: Define, Measure, Analyze, Improve and Control (DMAIC roadmap). RESULTS Initially, 12.3% of the reports were dispatched on the day of the patient's visit. Three causes for a prolonged dispatch time were identified: (1) determining which doctors involved with treatment would compose the report; (2) the reports composed by a senior resident had to be reviewed by a medical specialist; and (3) a medical specialist had to authorize the administration to dispatch the reports. To circumvent these causes, a digital form was implemented in the electronic medical record that could be completed during the multidisciplinary team meeting. After implementation, 90.6% of the reports were dispatched on the day of the visit. CONCLUSION The dispatch time of reports sent from hospital to primary care can be significantly reduced using Lean Six Sigma, improving the communication between hospital and primary care.
Improving Neural Networks Prediction Accuracy Using Particle Swarm Optimization Combiner

This paper proposes a technique to improve Artificial Neural Network (ANN) prediction accuracy using Particle Swarm Optimization (PSO) combiner. A hybrid system consists of two stages with the first stage containing two ANNs. The first ANN predictor is a multi-layer feed-forward network trained with error back-propagation and the second predictor is a functional link network. These two predictors are combined in the second stage using PSO combiner in a linear and non-linear fashion. The proposed method is applied to problem of predicting daily natural gas consumption. The performance of ANN predictors and combination methods are tested on real data from four different gas utilities. The experimental results show that the proposed particle swarm optimization combiners results in more accurate prediction compared to using single ANN predictor. Prediction accuracy improvement of the proposed PSO combiners have been shown using hypothesis testing.
Benchmarking the incidence of strategic management accounting in Slovenia

Purpose – To benchmark the degree to which companies in Slovenia, a country that has experienced success in its transition to a market economy, apply strategic management accounting (SMA) techniques.Design/methodology/approach – Survey data collected in Slovenia has been benchmarked to survey data collected in similarly sized Australian companies.Findings – For the Slovenian sample, while none of the techniques investigated are applied extensively, it has been found that competitor focused SMA techniques are the most popular. A group of SMA techniques that have a costing orientation are applied more extensively in Slovenian companies than in the Australian benchmark sample. It has also been found that some techniques that have a relatively high popularity ranking in one country, rank relatively lowly in the other country.Research limitations/implications – In addition to the generally accepted limitations of survey research, it should be noted that there is no definitive listing of SMA techniques and deba.
Identification of Parasite-Host Habitats in Anxiang County, Hunan Province, China Based on Multi-Temporal China-Brazil Earth Resources Satellite (CBERS) Images

Remote sensing is a promising technique for monitoring the distribution and dynamics of various vector-borne diseases. In this study, we used the multi-temporal CBERS images, obtained free of charge, to predict the habitats of the snail Oncomelania hupensis, the sole intermediate host of schistosomiasis japonica, a snail-borne parasitic disease of considerable public health in China. Areas of suitable snail habitats were identified based on the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI), and the predictive model was tested against sites (snails present or absent) that were surveyed directly for O. hupensis. The model performed well (sensitivity and specificity were 63.64% and 78.09%, respectively), and with further development, we may provide an accurate, inexpensive tool for the broad-scale monitoring and control of schistosomiasis, and other similar vector-borne diseases.
DNA barcodes: Genes, genomics, and bioinformatics

It is not a coincidence that DNA barcoding has developed in concert with genomics-based investigations. DNA barcoding (a tool for rapid species identification based on DNA sequences) and genomics (which compares entire genome structure and expression) share an emphasis on large-scale genetic data acquisition that offers new answers to questions previously beyond the reach of traditional disciplines. DNA barcodes consist of a standardized short sequence of DNA (400–800 bp) that in principle should be easily generated and characterized for all species on the planet (1). A massive on-line digital library of barcodes will serve as a standard to which the DNA barcode sequence of an unidentified sample from the forest, garden, or market can be matched. Similar to genomics, which has accelerated the process of recognizing novel genes and comparing gene function, DNA barcoding will allow users to efficiently recognize known species and speed the discovery of species yet to be found in nature. DNA barcoding aims to use the information of one or a few gene regions to identify all species of life, whereas genomics, the inverse of barcoding, describes in one (e.g., humans) or a few selected species the function and interactions across all genes (Fig. 1). The work of Lahaye et al. (2) reported in a recent issue of PNAS brings the application of DNA barcoding one step closer to implementation in plants.
Planetary Rover Control as a Markov Decision Process

Planetary rovers must be effective in gathering scientific data despite uncertainty and limited resources. One step toward achieving this goal is to construct a highlevel mathematical model of the problem faced by the rover and to use the model to develop a rover controller. We use the Markov decision process framework to develop a model of the rover control problem. We use Monte Carlo reinforcement learning techniques to obtain a policy from the model. The learned policy is compared to a class of heuristic policies and is found to perform better in simulation than any of the policies within that class. These preliminary results demonstrate the potential for using the Markov decision process framework along with reinforcement learning techniques to develop rover controllers.
IntAct: an open source molecular interaction database

IntAct provides an open source database and toolkit for the storage, presentation and analysis of protein interactions. The web interface provides both textual and graphical representations of protein interactions, and allows exploring interaction networks in the context of the GO annotations of the interacting proteins. A web service allows direct computational access to retrieve interaction networks in XML format. IntAct currently contains approximately 2200 binary and complex interactions imported from the literature and curated in collaboration with the Swiss-Prot team, making intensive use of controlled vocabularies to ensure data consistency. All IntAct software, data and controlled vocabularies are available at http://www.ebi. ac.uk/intact.
3 D reconstruction is not just a low-level task : retrospect and survey

Although an image is a 2D array, we live in a 3D world. The desire to recover the 3D structure of the world from 2D images is the key that distinguished computer vision from the already existing field of image processing 50 years ago. For the past two decades, the dominant research focus for 3D reconstruction is in obtaining more accurate depth maps or 3D point clouds. However, even when a robot has a depth map, it still cannot manipulate an object, because there is no high-level representation of the 3D world. Essentially, 3D reconstruction is not just a low-level task. Obtaining a depth map to capture a distance at each pixel is analogous to inventing a digital camera to capture the color value at each pixel. The gap between low-level depth measurements and high-level shape understanding is just as large as the gap between pixel colors and high-level semantic perception. Moving forward, we would like to argue that we need a higher-level intelligence for 3D reconstruction. We would like to draw attention of the 3D reconstruction research community to put greater emphasis on mid-level and high-level 3D understanding, instead of exclusively focus on improving of low-level reconstruction accuracy, as is the current situation. In this report, we retrospect the history and analyze some recent efforts in the community, to argue that a new era to study 3D reconstruction at higher level is starting to come.
On Determinism Handling While Learning Reduced State Space Representations

When applying a Reinforcement Learning technique to problems with continuous or very large state spaces, some kind of generalization is required. In the bibliography, two main approaches can be found. On one hand, the generalization problem can be defined as an approximation problem of the continuous value function, typically solved with neural networks. On the other hand, other approaches discretize or cluster the states of the original state space to achieve a reduced one in order to learn a discrete value table. However, both methods have disadvantages, like the introduction of non-determinism in the discretizations, parameters hard to tune by the user, or the use of a high number of resources. In this paper, we use some characteristics of both approaches to achieve state space representations that allow to approximate the value function in deterministic reinforcement learning problems. The method clusters the domain supervised by the value function being learned to avoid the non-determinism introduction. At the same time, the size of the new representation stays small and it is automatically computed. Experiments show improvements over other approaches such as uniform or unsupervised clustering.
A Survey on Various Mechanisms and IP Traceback Schemes To Defend DDoS Attacks

Distributed Denial of Service (DDoS) attacks are the major threat to Internet today that can make the server unavailable for legitimate user and finally take down the service. A number of mechanisms, approaches and various Traceback schemes are developed to defend such attacks. This paper surveys the various defensive techniques and various IP Traceback schemes to prevent various DDoS attacks.
Multi-Sensory Face Biometric Fusion (for Personal Identification)

The objective of this work is to recognize faces using sets of images in visual and thermal spectra. This is challenging because the former is greatly affected by illumination changes, while the latter frequently contains occlusions due to eye-wear and is inherently less discriminative. Our method is based on a fusion of the two modalities. Specifically: we examine (i) the effects of preprocessing of data in each domain, (ii) the fusion of holistic and local facial appearance, and (iii) propose an algorithm for combining the similarity scores in visual and thermal spectra in the presence of prescription glasses and significant pose variations, using a small number of training images (5-7). Our system achieved a high correct identification rate of 97% on a freely available test set of 29 individuals and extreme illumination changes.
Blind Separation of Event-Related Brain Responses into Independent Components

Abstract : Functional imaging of brain activity based on changes in blood flow does not supply information about the relative timing of brief bursts of neural activity in different brain areas. Multichannel electric or magnetic recordings from the scalp provide high temporal resolution, but are not easily decomposed into the separate activities of multiple brain networks. We report here a method for the blind separation of event-related brain responses into spatially stationary and temporally independent subcomponents using an Independent Component Analysis algorithm. Applied to electroencephalographic responses from an auditory detection task, each of the most active identified sources accounted for all or part of a previously identified response component. This spatiotemporal decomposition was robust to changes in sensors and input data length, and was stable within subjects. The method can be used to assess the timing, strength, and stability of event-related activity in brain networks during cognitive tasks, regardless of source location.
An Optimal Swarm Intelligence Approach For Test Sequence Restructuring To Conserve Power Usage In VLSI Testing

: Energy dissipation during testing has been discovered to be more than during regular mode due to increased switching activity. Test Sequence restructuring approach helps mitigate this problem as it allows the decrease of switching action during testing. This research presents a new Test Sequence restructuring approach. A cross model of genetic and pharaonis algorithms devised to restructure the test sequence. The model devised here is empirically verified with ISCAS’85 standard circuits that evident the minimization of switching activity to approximately to 32%.
Asymptotically optimum tests for decentralized change detection

Assuming that sensors have full local memory, we introduce a novel test for the problem of decentralized change detection that is asymptotically optimum. According to our proposed scheme, sensors perform locally repeated SPRTs and communicate, asynchronously, their one-bit decisions to a fusion center. The fusion center in turn uses the sequentially acquired information to perform a CUSUM test in order to decide whether a change took place or not. We prove that the average detection delay of the proposed test differs from the optimum centralized CUSUM test only by a constant. This fact suggests order-2 asymptotic optimality as compared to existing schemes that are optimal of order-1.
A New Precise Measurement of the Coronal Magnetic Field Strength

Magnetism dominates the structure and dynamics of the solar corona. Current theories suggest that it may also be responsible for coronal heating. Despite the importance of the magnetic field in the physics of the corona and despite the tremendous progress made recently in the remote sensing of solar magnetic fields, reliable measurements of the coronal magnetic field strength and orientation do not exist. This is largely due to the weakness of coronal magnetic fields, previously estimated to be on the order of 10 G, and the difficulty associated with observing the extremely faint solar corona emission. Using a very sensitive infrared spectropolarimeter to observe the strong near-infrared coronal emission line Fe XIII λ10747 above active regions, we have succeeded in measuring the weak Stokes V circular polarization profiles resulting from the longitudinal Zeeman effect of the magnetic field of the solar corona. From these measurements, we infer field strengths of 10 and 33 G from two active regions at heights of h = 0.12 R☉ and h = 0.15 R☉, respectively. We expect that this measurement technique will allow, in the near future, the routine precise measurement of the coronal magnetic field strength with application to many critical problems in solar coronal physics.
Keyword-based Text Matching Approach for Design Style Recognition

We present the results of an investigation into the recognition a design style by analysing keywords in the text descriptions of design styles. A simple keyword-based matching technique is used to classify a design style by examining its text description. Domain specific dictionaries of keywords are used to reduce the dimensions of the feature space. The results of the classifier are compared with those of SVM and decision tree based classifiers. The results conclude that design style in the domain that we analysed can be recognised with accuracy of approximately 75% from its descriptions.
High tibial osteotomy in Sweden, 1998–2007

Background and purpose Most studies on high tibial osteotomies (HTOs) have been hospital-based and have included a limited number of patients. We evaluated the use and outcome—expressed as rate of revision to knee arthroplasty—of HTO performed in Sweden with 9 million inhabitants, 1998–2007. Patients and methods 3, 161 HTO procedures on patients 30 years or older (69% men) who were operated on for knee osteoarthritis in Sweden, 1998–2007, were identified through the inpatient and outpatient care registers of the Swedish National Board of Health and Welfare. Pertinent data were verified through surgical records. Conversions of HTO to knee arthroplasty before 2010 were identified through the Swedish Knee Arthroplasty Register (SKAR). The 10-year survival was determined using revision to an arthroplasty as the endpoint. Results The number of HTOs decreased by one third between 1998 and 2007, from 388 operations a year to 257 a year. Most of the HTOs were performed with open wedge osteotomy using external fixation. The cumulative revision rate at 10 years was 30% (95% CI: 28–32). The risk of revision increased with increasing age and was higher in women than in men (RR = 1.3, CI: 1.1–1.5). Interpretation If being without an artificial joint implant is considered to be beneficial, then HTO is an excellent alternative to knee arthroplasty in younger and/or physically active patients suffering from knee osteoarthritis.
Insulin‐like growth factor binding protein 5 is associated with involution of the ventral prostate in castrated and finasteride‐treated rats

Insulin‐like growth factor binding protein (IGFBP)‐5 has been proposed as a signal for apoptosis in the ovary. To determine the relationship between IGFBP‐5 and apoptosis during regression of the androgen‐deprived prostate, rats were castrated or treated with the 5α‐reductase inhibitor finasteride for 4, 9, 14, 21, and 28 days.