Miracle-dz/UniFAR-FTUs huggingface dataset:
Tensor Multi-Task Learning for Multi-View Representation of 3D Shape

Research on 3D representation has sprung up recently. However, most existing view-based methods lack interpretability and few researchers explore to mine high-order correlation for multi-view features aggregate in 3D shape representation. This paper presents a tensor multi-task model learning, T-MTL, which transforms the original multi-view classification problem into constructing a common space in which the multi-view representation can be compared. The proposed method can construct a tensor structure in the classifier weight subspace with multiple viewpoints and use a tensor low-rank constraint and Bregman discrepancy to capture high-order correlations between multi-view images and 3D models. In the classifier weight subspace, our method makes the inter-class divergence larger and the intra-class divergence smaller. Moreover, the proposed model can improve recognition performance further by unifying multiple visual features in a flexible manner. Abundant experiments on these challenging benchmark datasets show that our method achieves comparable results to the deep learning models approach.
A Convolutional Neural Network to Reconstruct Ocean Surface PAR from Physical Predictors

A deep learning Convolutional Neural Network (CNN) architecture is proposed to reconstruct time series of photosynthetically available radiation (PAR) at the ocean surface. The CNN is informed by the main physical drivers of PAR variability, i.e., cloud fractional coverage and optical thickness, which are obtained from satellite and/or reanalysis data. This is crucial to properly account for cloud effects in gap regions because they cannot be predicted confidently from the spatiotemporal structure of the data in gap-free regions. Setting randomly blocks of missing pixels in each training epoch and using the remaining observations as input proved to be effective. Missing data in satellite-derived daily mean PAR products (MODIS-Aqua) are filled accurately using the CNN, with a R2 of 0.97, a RMSE of 3.22 E/m2/day (9.9%), and a small bias of 0.17 E/m2/day (0.5%). Comparisons between reconstructed PAR from MODIS and estimates with no gaps from EPIC show agreement in gap regions. The CNN also allows reconstruction of global PAR fields for the period prior to Earth observing satellites, enabling low-frequency variability studies. The study will yield long-term gapless PAR products that are critical for some data assimilating physical/biogeochemical models which need homogenized forcing fields and will help to assess the impact of the light field on aquatic ecosystems.
Data-centric Misbehavior Detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is very important problem with wide range of implications including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. Because of this (\emph{rational behavior}), it is more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can independently decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alert with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. Instead of revoking all the secret credentials of misbehaving nodes, as done in most schemes, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes.
Robust generalized predictive control of the Orthoglide robot

The purpose of this paper is to address the synthesis and experimental application of a generalized predictive control (GPC) technique on an Orthoglide robot.Design/methodology/approach– The control strategy is composed of two control loops. The inner loop aims at linearizing the nonlinear robot dynamics using feedback linearization. The outer loop tracks the desired trajectory based on GPC strategy, which is robustified against measurement noise and neglected dynamics using Youla parameterization.Findings– The experimental results show the benefits of the robustified predictive control strategy on the dynamical performance of the Orthoglide robot in terms of tracking accuracy, disturbance rejection, attenuation of noise acting on the control signal and parameter variation without increasing the computational complexity.Originality/value– The paper shows the implementation of the robustified predictive control strategy in real time with low computational complexity on the Orthoglide robot.
Screening for hotspot mutations in PI3K, JAK2, FLT3 and NPM1 in patients with myelodysplastic syndromes

INTRODUCTION: Myelodysplastic syndromes encompass a heterogeneous group of clonal hematopoietic stem cell disorders characterized by ineffective hematopoiesis, refractory cytopenia and a tendency to progress toward acute myeloid leukemia. The accumulation of genetic alterations is closely associated with the progression of myelodysplastic syndromes toward acute myeloid leukemia. OBJECTIVE: To investigate the presence of mutations in the points most frequent for mutations (hotspot mutations) in phosphatidylinositol-3-kinase (PI3K), Janus kinase 2 (JAK2), FMS-like tyrosine kinase 3 (FLT3) and nucleophosmin (NPM1), which are involved in leukemia and other cancers, in a population of Brazilian MDS patients. METHODS: Fifty-one myelodysplastic syndromes patients were included in the study. According to French-American-British classification, the patients were distributed as follows: 31 with refractory anemia, 8 with refractory anemia with ringed sideroblasts, 7 with refractory anemia with excess blasts, 3 with refractory anemia with excess blasts in transformation and 2 with chronic myelomonocytic leukemia. Bone marrow samples were obtained and screened for the presence of hotspot mutations using analysis based on amplification with the polymerase chain reaction, sequencing, fragment size polymorphisms or restriction enzyme digestion. All patients were screened for mutations at the time of diagnosis, and 5 patients were also screened at the time of disease progression. RESULTS: In the genes studied, no mutations were detected in the patients at the time of diagnosis. One patient with chronic myelomonocytic leukemia was heterozygous for a Janus kinase 2 mutation after disease progression. CONCLUSIONS: These results show that hotspot mutations in the PI3K, JAK2, FLT3 and NPM1 genes are not common in MDS patients; nevertheless, JAK2 mutations may be present in myelodysplasia during disease progression.
Deep Submicron Switching Current Modeling for CMOS Logic Output Transition Time Determination

Non zero signal rise and fall times contribute significantly to CMOS gate performances such as propagation delay or short circuit power dissipation. We present a closed form expression to model output rise and fall times in deep submicron CMOS structures. The model is first developed for inverters considering fast and slow input ramp conditions. It is then extended to gates through a reduction procedure considering the maximum current available in the serial transistor array. Validation of this modeling is obtained by comparing calculated gate output transition time to simulated ones (HSPICE level and foundry card model on 0.18µm process)
Sexual Dysfunction as a Marker of Cardiovascular Disease in Males With 50 or More Years of Type 1 Diabetes

OBJECTIVE Vascular dysfunction is a major contributor to diabetes complications. It is also the primary physiologic cause of erectile dysfunction and considered an independent predictor of cardiovascular disease (CVD) in males over age 40 years. A cohort of individuals with 50 or more years of type 1 diabetes, Joslin Medalists, have low rates of small but not large vessel complications. This study aims to identify the prevalence and longitudinal association of sexual dysfunction (SD) with CVD in Joslin Medalists. RESEARCH DESIGN AND METHODS Description and association of self-assessment of SD in males of the Medalist cohort by self-reported sexual problems with CVD. SD is validated through the use of the abbreviated International Index of Erectile Dysfunction (IIEF). RESULTS Of 301 males in the Medalist Study, 69.8% reported a history of SD. Unadjusted risk factors included elevated glycated hemoglobin (HbA1c) (P = 0.02), elevated BMI (P = 0.03), higher total cholesterol (P = 0.02), lower HDL (P < 0.01), and increased levels of interleukin-6 (P = 0.03). SD was independently associated with CVD (age-, HbA1c-, and BMI-adjusted OR 1.9 [95% CI 1.0–3.5]). In adjusted analyses, retinal, neural, and renal complications were not associated (P > 0.05) with SD. Current report of SD (IIEF score ≤17) in a subset of Medalists was significantly correlated with self-reported longitudinal SD. CONCLUSIONS SD in those with extreme-duration type 1 diabetes is independently associated with CVD, representing a large-vessel pattern. The findings suggest that SD may predict CVD in those with type 1 diabetes of long duration. These individuals have also been found to be relatively free of microvascular complications.
Exposure of the Superior Gluteal Neurovascular Bundle for the Safe Application of Acetabular Reinforcement Cages in Complex Revisions

The posterior approach to the hip is the most common extensile approach used, however exposure is limited superiorly by the superior gluteal neurovascular bundle (SGNB). The extra-pelvic course of the SGNB demonstrates variability between individuals, occasionally located only 1 cm from the acetabular rim. In complex acetabular reconstructions where the application of a reinforcement cage maybe required protecting the SGNB is challenging. The flanges of these cages are designed to sit on the ilium superior to the acetabular rim and to receive screws for fixation. The application of such cages may result in iatrogenic injury to the SGNB by way of forceful retraction or entrapment. We describe a technique that involves exposure and release of the SGNB such that the flanges of cage constructs may be safely applied.
Is it design or is it inquiry? Exploring technology research in a Filipino school setting

M y case study explored Filipino secondary students' and teachers' experiences with technology research, project-based pedagogy. The study was conducted to examine the nature of a Technology Research (TR) Curriculum, and how it mediates non-Western students' learning, and interest in technology-based careers. The context for my study is Philippine Science High School's (PSHS) TR program wherein students outline a proposal, design an experiment or a device, and implement their design to address a real world problem. My data sources included semi-structured interviews of 27 students and 2 teachers; participant observations of classroom and group activities, teacherstudent consultations, and Science-Technology Fair presentations; TR curriculum documents; and researcher journal logs. M y examination of curriculum documents revealed that since the 1960s, the Philippine government has implemented specialized educational programs, such as the PSHS Science/Technology Streaming and TR programs, to support Filipino youth interested in science and technology courses and careers. Data analyses showed that the TR program provided a rich, practical learning environment where 'doing technology design' blended with 'doing science inquiry'. The TR activities enhanced student understanding of science and technology; helped them integrate and apply knowledge and skills learned from other school subjects; encouraged them to be creative, problem-solvers; and helped develop their lifelong learning skills. Students recognized that TR teachers adopted alternative instructional strategies that prompted students to adopt more active roles in their learning. Research findings revealed that student interest in pursuing technology-related careers was supported by their participation in the streaming and the TR programs. Data also showed that Filipino cultural practices
Design Patterns for Visualization-Based Tools in Sustainable Product Design

Most design activities involve exploring and comparing existing designs. Thus, adopting an eco-conscious approach in the design exploration process can aid environmentally sustainable product design (SPD). One approach for supporting exploration in SPD is through tools based on information visualization (InfoVis). The use of InfoVis for SPD allows data-driven exploration of solutions that is rapid, direct, and supports investigation of questions that the designer may not have identified. Previous work has demonstrated the utility of InfoVis tools for different facets of the lifecycle, e.g. redesign, supply chain exploration, and life cycle assessment. These tools focus on projecting sustainability-related implications back to design. However, to fully realize their potential, future tools must synthesize data in a manner that helps designers view the effects of a design change on all downstream stages. Such tools will have to work across multiple data types, visual representations, and stakeholders. In this paper, we take the first steps towards addressing this challenge by formulating design patterns for visualization and interaction of product lifecycle data. These design patterns were synthesized by reviewing previous works that have successfully created visualization-based tools for SPD. The suggested ∗Address all correspondence devr@mit.edu design patterns can, (1) serve as a guide for creating integrated visualization-based tools for SPD, and (2) help create reusable visual components that aid in quick interface wireframing.
A Markovian Model for HSDPA TNL Congestion Control Performance Analysis

High speed downlink packet access (HSDPA) is an extension of the universal mobile telecommunication system (UMTS) technology of 3GPP Rel-99, with the objective of increasing the data rate and also reduce the latency in the downlink. The focus of this study is to develop an analytical model for HSDPA congestion control (CC) performance analysis. Often the transport network layer (TNL) is congested in HSDPA networks which degrades the overall HSDPA performance. The congestion control and detection algorithms are implemented in the Node B and RNC in order to minimize system congestions. There are several simulation based investigations carried out so far for the performance analysis of such algorithms. An analytical model which is based on the Embedded Markov chain with multiple departures (EMC-MD) is developed to analyse the effect of CC for the HSDPA performance. This analytical model includes all the important functionalities of the congestion control at TNL level. This paper also shows that the results from the analytical model are in agreement with the simulation results and that the analytical model can be effectively used to analyse the effect of parameters on performance of the HSDPA network and can be used dimensioning of the parameters.
Comparison of Metabolic Pathways using Constraint Graph Drawing

Databases contain a large amount of data about metabolic pathways, in particular about similar pathways in different species. Biologists are familiar with visual representations of metabolic pathways. Visualizations help them to understand the complex relationships between the components of the pathways, to extract information from the data, and to compare pathways between different species. However, visual interfaces to metabolic pathway databases cannot cope well with the visual comparison of similar pathways in different species.This paper presents a new approach for the visual comparison of metabolic pathways using a constraint graph drawing algorithm. Using layout constraints the same parts of similar pathways in different species are placed side by side, thereby highlighting similarities and differences between these pathways. This visualization method can be used as a visual interface to databases and has been tested with data obtained from the BioPath system and from the KEGG database.
Array-based analysis of genomic DNA methylation patterns of the tumour suppressor gene p16INK4A promoter in colon carcinoma cell lines

Aberrant DNA methylation at CpG dinucleotides can result in epigenetic silencing of tumour suppressor genes and represents one of the earliest events in tumourigenesis. To date, however, high-throughput tools that are capable of surveying the methylation status of multiple gene promoters have been restricted to a limited number of cytosines. Here, we present an oligonucleotide microarray that permits the parallel analysis of the methylation status of individual cytosines, thus combining high throughput and high resolution. The approach was used to study the CpG island in the promoter region of the tumour suppressor gene p16INK4A. In total, 876 oligonucleotide probes of 21 nt in length were used to inspect the methylation status of 53 CpG dinucleotides, producing correct signals in colorectal cancer cell lines as well as control samples with a defined methylation status. The information was validated by established alternative methods. The overall methylation pattern was consistent for each cell line, while different between them. At the level of individual cytosines, however, significant variations between individual cells of the same type were found, but also consistencies across the panel of cancer cell lines were observed.
Nested mappings: schema mapping reloaded

Many problems in information integration rely on specifications, called schema mappings, that model the relationships between schemas. Schema mappings for both relational and nested data are well-known. In this work, we present a new formalism for schema mapping that extends these existing formalisms in two significant ways. First, our nested mappings allow for nesting and correlation of mappings. This results in a natural programming paradigm that often yields more accurate specifications. In particular, we show that nested mappings can naturally preserve correlations among data that existing mapping formalisms cannot. We also show that using nested mappings for purposes of exchanging data from a source to a target will result in less redundancy in the target data. The second extension to the mapping formalism is the ability to express, in a declarative way, grouping and data merging semantics. This semantics can be easily changed and customized to the integration task at hand. We present a new algorithm for the automatic generation of nested mappings from schema matchings (that is, simple element-to-element correspondences between schemas). We have implemented this algorithm, along with algorithms for the generation of transformation queries (e.g., XQuery) based on the nested mapping specification. We show that the generation algorithms scale well to large, highly nested schemas. We also show that using nested mappings in data exchange can drastically reduce the execution cost of producing a target instance, particularly over large data sources, and can also dramatically improve the quality of the generated data.
Robust Generalized Empirical Likelihood for Heavy Tailed Autoregressions with Conditionally Heteroscedastic Errors

We present a robust Generalized Empirical Likelihood estimator and confidence region for the parameters of an autoregression that may have a heavy tailed heteroscedastic error. The estimator exploits two transformations for heavy tail robustness: a redescending transformation of the error that robustifies against innovation outliers, and weighted least squares instruments that ensure robustness against heavy tailed regressors. Our estimator is consistent for the true parameter and asymptotically normally distributed irrespective of heavy tails.
On the analysis of phylogenetically paired designs

As phylogenetically controlled experimental designs become increasingly common in ecology, the need arises for a standardized statistical treatment of these datasets. Phylogenetically paired designs circumvent the need for resolved phylogenies and have been used to compare species groups, particularly in the areas of invasion biology and adaptation. Despite the widespread use of this approach, the statistical analysis of paired designs has not been critically evaluated. We propose a mixed model approach that includes random effects for pair and species. These random effects introduce a “two-layer” compound symmetry variance structure that captures both the correlations between observations on related species within a pair as well as the correlations between the repeated measurements within species. We conducted a simulation study to assess the effect of model misspecification on Type I and II error rates. We also provide an illustrative example with data containing taxonomically similar species and several outcome variables of interest. We found that a mixed model with species and pair as random effects performed better in these phylogenetically explicit simulations than two commonly used reference models (no or single random effect) by optimizing Type I error rates and power. The proposed mixed model produces acceptable Type I and II error rates despite the absence of a phylogenetic tree. This design can be generalized to a variety of datasets to analyze repeated measurements in clusters of related subjects/species.
Streptococcus mitis Strains Causing Severe Clinical Disease in Cancer Patients

The genetically diverse viridans group streptococci (VGS) are increasingly recognized as the cause of a variety of human diseases. We used a recently developed multilocus sequence analysis scheme to define the species of 118 unique VGS strains causing bacteremia in patients with cancer; Streptococcus mitis (68 patients) and S. oralis (22 patients) were the most frequently identified strains. Compared with patients infected with non–S. mitis strains, patients infected with S. mitis strains were more likely to have moderate or severe clinical disease (e.g., VGS shock syndrome). Combined with the sequence data, whole-genome analyses showed that S. mitis strains may more precisely be considered as >2 species. Furthermore, we found that multiple S. mitis strains induced disease in neutropenic mice in a dose-dependent fashion. Our data define the prominent clinical effect of the group of organisms currently classified as S. mitis and lay the groundwork for increased understanding of this understudied pathogen.
World City Network Research at a Theoretical Impasse: On the Need to Re-Establish Qualitative Approaches to Understanding Agency in World City Networks

From the late 1990s, the establishment of a new relational ‘turn’ in the study of world city connectedness in globalisation has run parallel to the wider relational turn occurring in economic geography. Early work, built firmly upon a qualitative approach to the collection and analyses of new intercity datasets, considered cities as being constituted by their relations with other cities. Subsequent research, however, would take a strong quantitative turn, best demonstrated through the articulation of the inter-locking world city network (ILWCN) ‘model’ for measuring relations between cities. In this paper, we develop a critique of research based around the ILWCN model, arguing that this ‘top down’ quantitative approach has now reached a theoretical impasse. To address this impasse, we argue for a move away from structural approaches in which the firm is the main unit of analysis, towards qualitative approaches in which individual agency and practice are afforded greater importance.