Miracle-dz/UniFAR-FTUs huggingface dataset:
Routability-driven legalization algorithm with minimum total movement for supporting agricultural machinery design

Agricultural mechanization impacts on agricultural productivity and society development far-reaching. The emergence of ASIC (Application Specific Integrated Circuit) provides possibility for full intelligence and automation of agricultural products. Placement is a key step in the physical design of ASIC. Legalization is core task of the detailed placement after global distribution of generous standard cells. It removes cells overlap, aligns them to the sites and places them to their final position. A congestion-length driven legalization algorithm with minimum total movement is presented in this paper. The algorithm takes the total wire-length and congestion as objective and considers the site constraint to legalize cells with minimum movement. It contains series of phases to place cells to their optimal site, like formation, Inter-Row cells distribution and Intra-Row cells overlap elimination. But at the same time, it keeps global placement result and optimizes total wire-length at most. On the ISPD 2011 and DAC 2012 Contest Benchmark Suite, with the official valuation protocol, the routability-driven legalization algorithm outperforms original wirelength-driven algorithm almost every contestant.
Abstract parsing with string updates using LR-parsing technology

parsing with string updates using LR-parsing technology Kyung-Goo Doh, Hyunha Kim, David A. Schmidt 1 Hanyang University, Ansan, South Korea 2 Kansas State University, Manhattan, Kansas, USA Abstract. We combine LR(k)-parsing technology and data-flow analysis to analyze, in advance of execution, the documents generated dynamically by a program. Based on the document language’s context-free reference grammar and the program’s control structure, formatted as a set of flow equations, the analysis predicts how the documents will be generated and simultaneously parses the predicted documents. Recursions in the flow equations cause the analysis to emit a set of residual equations that are solved by least-fixed point calculation in the domain of abstract (folded) LR-parse stacks. Since the technique accommodates LR(k) grammars, it can also handle string-update operations in the programs by translating the updates into finite-state transducers, whose controllers are composed with the LR(k)-parser controller. We combine LR(k)-parsing technology and data-flow analysis to analyze, in advance of execution, the documents generated dynamically by a program. Based on the document language’s context-free reference grammar and the program’s control structure, formatted as a set of flow equations, the analysis predicts how the documents will be generated and simultaneously parses the predicted documents. Recursions in the flow equations cause the analysis to emit a set of residual equations that are solved by least-fixed point calculation in the domain of abstract (folded) LR-parse stacks. Since the technique accommodates LR(k) grammars, it can also handle string-update operations in the programs by translating the updates into finite-state transducers, whose controllers are composed with the LR(k)-parser controller.
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces

In this paper, we propose a novel parameter estimator for probabilistic models on discrete space. The proposed estimator is derived from minimization of homogeneous divergence and can be constructed without calculation of the normalization constant, which is frequently infeasible for models in the discrete space. We investigate statistical properties of the proposed estimator such as consistency and asymptotic normality, and reveal a relationship with the information geometry. Some experiments show that the proposed estimator attains comparable performance to the maximum likelihood estimator with drastically lower computational cost.
Adaptive probabilistic search for peer-to-peer networks

Peer-to-peer networks are gaining increasing attention from both the scientific and the large Internet user community. Popular applications utilizing this new technology offer many attractive features to a growing number of users. At the heart of such networks lies the search algorithm. Proposed methods either depend on the network-disastrous flooding and its variations or utilize various indices too expensive to maintain. We describe an adaptive, bandwidth-efficient algorithm for search in unstructured peer-to-peer networks, the adaptive probabilistic search method (APS). Our scheme utilizes feedback from previous searches to probabilistically guide future ones. It performs efficient object discovery while inducing zero overhead over dynamic network operations. Extensive simulation results show that APS achieves high success rates, increased number of discovered objects, very low bandwidth consumption and adaptation to changing topologies.
Dual Channel Echo Postfiltering for Hands-Free Mobile Terminals

In mobile communications, speech is often degraded by ambient noise and acoustic echo. Both problems have attracted a high level of research interest over the last decades. Recently dual channel solutions for noise reduction have been investigated and can yield better performance than single channel solutions. This paper presents an analysis of the echo problem based on recordings with a handsfree dual channel mock-up phone and proposes a novel residual echo power spectral density (PSD) estimator that uses two microphone signals instead of one. The proposed PSD estimate is compared to an existing single channel residual echo PSD estimator before being assessed within an echo postfilter. Our experiments show that the proposed dual-channel echo PSD outperforms the single channel postfilter, especially at low signal to echo ratios.
A robust linguistic infrastructure for efficient web content analysis: the ALVIS project

This paper focuses on the design and the development of a text processing architecture exploiting specialized NLP tools, to produce linguistically annotated documents. This architecture is instanciated using existing NLP modules and resources which need to be tuned to specific domains. Taking as an example the biological domain, we show how a syntactic analyser can be adapted to this domain. We focus on parsing since it exhibits various kinds of adaptation, ranging from unknown words analysis to specific vocabulary (terms, named entities) and structure identification.
La depresión y ansiedad de las madres se relaciona con el consumo de drogas de sus hijos adolescentes

Title: Was related mothers depression and anxiety with drug consump- tion of your adolescents sons? Abstract: The family can act as a risk or protective factor in the behavior problems that appear during the adolescence, as the consumption of drugs. The objective of the present study is to analyze if there is relation- ship between the presence of depression and trait anxiety problems in mothers, and the consumption of drugs (tobacco, alcohol, cannabis and cocaine) in their sons. The sample is formed by 594 persons, 297 mothers and 297 sons selected at random, stratified by sex and age, of the area of Salnes (Pontevedra). The results indicate that the mothers whose sons have consumed cannabis and/or cocaine at some time, and that they have smoked tobacco in the last 6 months, they have more depressive symp- toms. It is also more probable than they have consumed alcohol (spirits) lifetime and in the last 6 months, and that they have drunkness, the sons of mothers that have a score above the normal population of reference.
Image segmentation using linked mean-shift vectors with region attribution analysis

This paper proposes a novel linked mean-shift algorithm that considers region attribution in a cluster merging process. Mean-shift based image segmentation suffers from its extreme computational complexity, despite of its outstanding segmentation accuracy. To resolve this problem, the linked mean-shift algorithm that removes the iterative process in the mean-shift process was introduced. However, the approximation in the linked-mean-shift algorithm gives rise to unwanted merging of the clusters that should not be merged. To prevent the unwanted merging, the proposed algorithm analyzes region attribution, then, in the merging process, applies strict condition to the clusters that have dissimilar attribution than the clusters that have similar attribution. In experiments, the proposed algorithm improved segmentation accuracy than the linked mean-shift algorithm, while retained twenty times faster speed than the mean-shift algorithm. Furthermore, the experimental results for variation of processing time showed the proposed algorithm can provide much settled throughput than the mean-shift algorithm.
The generic genome browser: a building block for a model organism system database.

The Generic Model Organism System Database Project (GMOD) seeks to develop reusable software components for model organism system databases. In this paper we describe the Generic Genome Browser (GBrowse), a Web-based application for displaying genomic annotations and other features. For the end user, features of the browser include the ability to scroll and zoom through arbitrary regions of a genome, to enter a region of the genome by searching for a landmark or performing a full text search of all features, and the ability to enable and disable tracks and change their relative order and appearance. The user can upload private annotations to view them in the context of the public ones, and publish those annotations to the community. For the data provider, features of the browser software include reliance on readily available open source components, simple installation, flexible configuration, and easy integration with other components of a model organism system Web site. GBrowse is freely available under an open source license. The software, its documentation, and support are available at http://www.gmod. org.
A Voltage Mode Memristor Bridge Synaptic Circuit with Memristor Emulators

A memristor bridge neural circuit which is able to perform signed synaptic weighting was proposed in our previous study, where the synaptic operation was verified via software simulation of the mathematical model of the HP memristor. This study is an extension of the previous work advancing toward the circuit implementation where the architecture of the memristor bridge synapse is built with memristor emulator circuits. In addition, a simple neural network which performs both synaptic weighting and summation is built by combining memristor emulators-based synapses and differential amplifier circuits. The feasibility of the memristor bridge neural circuit is verified via SPICE simulations.
Data-Driven Extraction of a Nested Model of Human Brain Function

Decades of cognitive neuroscience research have revealed two basic facts regarding task-driven brain activation patterns. First, distinct patterns of activation occur in response to different task demands. Second, a superordinate, dichotomous pattern of activation/deactivation, is common across a variety of task demands. We explore the possibility that a hierarchical model incorporates these two observed brain activation phenomena into a unifying framework. We apply a latent variable approach, exploratory bifactor analysis, to a large set of human (both sexes) brain activation maps (n = 108) encompassing cognition, perception, action, and emotion behavioral domains, to determine the potential existence of a nested structure of factors that underlie a variety of commonly observed activation patterns. We find that a general factor, associated with a superordinate brain activation/deactivation pattern, explained the majority of the variance (52.37%) in brain activation patterns. The bifactor analysis also revealed several subfactors that explained an additional 31.02% of variance in brain activation patterns, associated with different manifestations of the superordinate brain activation/deactivation pattern, each emphasizing different contexts in which the task demands occurred. Importantly, this nested factor structure provided better overall fit to the data compared with a non-nested factor structure model. These results point to a domain-general psychological process, representing a “focused awareness” process or “attentional episode” that is variously manifested according to the sensory modality of the stimulus and degree of cognitive processing. This novel model provides the basis for constructing a biologically informed, data-driven taxonomy of psychological processes. SIGNIFICANCE STATEMENT A crucial step in identifying how the brain supports various psychological processes is a well-defined categorization or taxonomy of psychological processes and their interrelationships. We hypothesized that a nested structure of cognitive function, in terms of a canonical domain-general cognitive process, and various subfactors representing different manifestations of the canonical process, is a fundamental organization of human cognition, and we tested this hypothesis using fMRI task-activation patterns. Using a data-driven latent-variable approach, we demonstrate that a nested factor structure underlies a large sample of brain activation patterns across a variety of task domains.
Aza‐scanning of the Potent Melanocortin Receptor Agonist Ac‐His‐d‐Phe‐Arg‐Trp‐NH2

The melanocortin pathway is an important participant in the regulation of skin pigmentation, steroidogenesis, obesity, energy homeostasis, and exocrine gland function. Melanocortin agonists contain the putative sequence ‘His‐Phe‐Arg‐Trp’, which has been designated as the ‘message’ sequence for melanocortin peptides, and this sequence has been hypothesized to adopt a bioactive reverse turn conformation. Exploring the relationship between its structure and biological activity, we report the synthesis and evaluation of seven aza‐analogs of the potent melanocortin receptor agonist Ac‐His‐d‐Phe‐Arg‐Trp‐NH2. Aza‐amino acids, in which the α‐carbon was replaced by nitrogen, were inserted along the peptide sequence to probe the importance of local configuration and turn conformation on the biology of this tetrapeptide. Although systematic substitution of aza‐amino acids for the d‐Phe and Arg residues led to a significant loss of activity relative to the parent peptide for all melanocortin receptor subtypes examined, substitution of aza‐amino acids at the C‐terminal Trp residue gave analogs equipotent to the parent peptide. In summary, the aza‐scan has demonstrated that recognition of this tetrapeptide by the melanocortin receptors is particularly sensitive to modifications of configuration and conformation at the d‐Phe and Arg residues versus the Trp amino acid. In light of aza‐residues imparting resistance from enzymatic degradation, C‐terminal aza‐amino acid analogs may be used to design new peptide mimics with enhanced metabolic stability.
Linear Gadolinium-Based Contrast Agents Are Associated With Brain Gadolinium Retention in Healthy Rats

ObjectivesThe aim of this study was to evaluate Gd retention in the deep cerebellar nuclei (DCN) of linear gadolinium-based contrast agents (GBCAs) compared with a macrocyclic contrast agent. Materials and MethodsThe brain tissue retention of Gd of 3 linear GBCAs (gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide) and a macrocyclic GBCA (gadoterate meglumine) was compared in healthy rats (n = 8 per group) that received 20 intravenous injections of 0.6 mmol Gd/kg (4 injections per week for 5 weeks). An additional control group with saline was included. T1-weighted magnetic resonance imaging was performed before injection and once a week during the 5 weeks of injections and for another 4 additional weeks after contrast period. Total gadolinium concentration was measured with inductively coupled plasma mass spectrometry. Blinded qualitative and quantitative evaluations of the T1 signal intensity in DCN were performed, as well as a statistical analysis on quantitative data. ResultsAt completion of the injection period, all the linear contrast agents (gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide) induced a significant increase in signal intensity in DCN, unlike the macrocyclic GBCA (gadoterate meglumine) or saline. The T1 hypersignal enhancement kinetic was fast for gadodiamide. Total Gd concentrations for the 3 linear GBCAs groups at week 10 were significantly higher in the cerebellum (1.21 ± 0.48, 1.67 ± 0.17, and 3.75 ± 0.18 nmol/g for gadobenate dimeglumine, gadopentetate dimeglumine, and gadodiamide, respectively) than with the gadoterate meglumine (0.27 ± 0.16 nmol/g, P < 0.05) and saline (0.09 ± 0.12 nmol/g, P < 0.05). No significant difference was observed between the macrocyclic agent and saline. ConclusionsRepeated administrations of the linear GBCAs gadodiamide, gadobenate dimeglumine, and gadopentetate dimeglumine to healthy rats were associated with progressive and significant T1 signal hyperintensity in the DCN, along with Gd deposition in the cerebellum. This is in contrast with the macrocyclic GBCA gadoterate meglumine for which no effect was observed.
Innovations in play therapy : issues, process, and special populations

Part I: Special Considerations for the Role of the Play Therapist. Landreth, Facilitative Dimensions of Play in the Therapy Process. Harris, Landreth, Essential Personality Characteristics of Effective Play Therapists. Glover, Cultural Considerations in Play Therapy. Kao, Landreth, Play Therapy with Chinese Children: Needed Modifications. Sweeney, Tatum, What the Play Therapist Needs to Know about Medications. Sweeney, Legal and Ethical Issues in Play Therapy. Crane, The Parent's Part in the Play Therapy Process. Part II: Clinical Innovations in Play as a Diagnostic Tool. White, Draper, Jones, Play Therapy Behaviors of Physically Abused Children. Ater, Play Therapy Behaviors of Sexually Abused Children. Homeyer, Identifying Sexually Abused Children in Play Therapy. Perry, Landreth, Diagnostic Assessment of Children's Play Therapy Behavior. Part III: Innovative Procedures in Play Therapy. Landreth, Sweeney, Child-Centered Group Play Therapy. Tyndall-Lind, Landreth, Intensive Short-Term Group Play Therapy. Johnson, Short-Term Play Therapy. Part IV: Play Therapy with Special Populations. Johnson, Clark, Play Therapy with Aggressive Acting-Out Children. Mittledorf, Hendricks, Landreth, Play Therapy with Autistic Children. Jones, Play Therapy for Children with Chronic Illness. Webb, Play Therapy with Traumatized Children: A Crisis Response. Post, Play Therapy with Selective Mute Children. Klein, Landreth, Play Therapy with Dissociative Identity Disorder Clients with Child Alters. Haynes, Play Therapy with the Elderly. Niel, Landreth, Have Toys-Will Travel: A Traveling Play Therapist in the School Setting.
Optic disk and cup boundary detection using regional information

The shape deformation within the optic disk (OD) is an important indicator for the detection of glaucoma. In this paper, relevant disk parameters are estimated using the OD and cup boundaries. A deformable model guided by regional statistics is used to detect the OD boundary. A cup boundary detection scheme is presented based on the appearance of pallor in Lab colour space and the expected cup symmetry. The proposed scheme is tested on 170 images comprising 40 normal and 130 glaucomatous images. The proposed method gives a mean error 0.030 for normal and 0.121 for glaucomatous images in the estimation of cup-to-disk ratio which compares well with reported figures in literature.
Anterior lumbar fusion improves discogenic pain at levels of prior posterolateral fusion.

STUDY DESIGN A descriptive case review. OBJECTIVES To assess the outcomes of anterior lumbar interbody fusion for painful discs within a solid posterolateral spinal fusion. SUMMARY OF BACKGROUND DATA Some patients continue to have pain after posterolateral spinal fusion despite apparently solid arthrodesis. One potential etiology is pain that arises from a disc within the fused levels. METHOD Retrospective review of 176 patients with anterior interbody fusion, which located 20 who had anterior interbody fusion levels of prior posterolateral spinal fusion. All had low back pain, solid posterolateral spinal fusion, and painful disc(s) at the posterolateral spinal fusion level(s) but not elsewhere. Pain was measured by the Numerical Rating Scale, function by Oswestry Disability Questionnaire, and patient satisfaction by the North American Spine Society Outcome Questionnaire. RESULTS Follow-up data were available for 18 patients (90%). Mean follow-up was 58 months (25 to 102). There were 10 men and 8 women. Mean age was 45 years (26 to 72). Diagnoses were degenerative discs, herniated nucleus pulposus, spondylolisthesis, and spinal stenosis. Eight patients had injuries after the previous posterolateral spinal fusion that precipitated new symptoms. Two patients had one level fusion, 14 had two levels, and 1 each had three and four levels. Four patients had one prior surgery, 5 had two, and 9 had three or more. All patients had solid anterior interbody fusion by radiograph. Mean Numerical Rating Scale improved from 7.9 before surgery to 4.7 after (P< 0.001). Mean Oswestry Disability Questionnaire improved from 56.3 before surgery to 47.9 after (P = 0.04). Of 15 patients unable to work before anterior interbody fusion, 5 returned to work. Sixteen patients (89%) were satisfied with their results. CONCLUSION Low back pain that continues or recurs after apparently solid posterolateral spinal fusion may be caused by painful disc(s) at motion segment(s) within the fusion. A solid posterolateral spinal fusion may not protect the residual disc(s) from injury. Anterior interbody fusion can provide significant improvements in pain and function and a high degree of patient satisfaction in this clinical setting.
MiRNAs and E2F3: a complex network of reciprocal regulations in human cancers

E2F transcription factor 3 (E2F3) is oncogenic in tumorigenesis. Alterations in E2F3 functions correspond with poor prognosis in various cancers, underscoring their status for the clinical cancer phenotype. Latest reports discovered intricate networks between microRNAs (miRNAs) and E2F3 in regulating the balance of these events, including proliferation, apoptosis, metastasis, as well as drug resistance. miRNAs are non-coding small RNAs which negatively regulate gene expressions post-transcriptionally mainly through 3′-UTR binding of target mRNAs. Increasing evidence shows that E2F3 can be activated/inhibited by numerous miRNAs whose dysregulation has been implicated in malignancy. In turn, miRNAs themselves can be transcriptionally regulated by E2F3, thus forming a negative feedback loop. These findings add a new challenging layer of complexity to E2F3 network. Current understanding of the reciprocal link between E2F3 and miRNAs in human cancers were summarized, which could help to develop potential therapeutic strategies.
Learning and Inference in Entity and Relation Identification

In this study, I examine several different approaches to identifying entities and relations in sentences. I compare three different strategies to learn entities and relations. The first uses just local classifiers, the second uses local classifiers with integer linear programming (ILP) inference, and the third uses inference based training (IBT) and evaluates using ILP inference. My experiments indicate that in solving this particular problem, IBT performs the others, followed by local classifiers with (ILP) inference, and lastly the local classifiers by themselves. However these differences are not as large as one might expect.