Miracle-dz/UniFAR-FTUs huggingface dataset:
Structured video content analysis: learning spatio-temporal and multimodal structures

Video data exhibits a variety of structures: pixels exhibit spatial structure, e.g., the same class of objects share certain shapes and/or colors in image; sequences of frames exhibit temporal structure, e.g., dynamic events such as jumping and running have a certain chronological order of frame occurrence; and when combined with audio and text, there is multimodal structure, e.g., human behavioral data shows correlation between audio (speech) and visual information (gesture). Identifying, formulating, and learning these structured patterns is a fundamental task in video content analysis. This thesis tackles two challenging problems in video content analysis human action recognition and behavior understanding and presents novel algorithms to solve each: one algorithm performs sequence classification by learning spatio-temporal structure of human action; another performs data fusion by learning multimodal structure of human behavior. The first algorithm, hierarchical sequence summarization, is a probabilistic graphical model that learns spatio-temporal structure of human action in a fine-to-coarse manner. It constructs a hierarchical representation of video by iteratively summarizing the video sequence, and uses the representation to learn spatio-temporal structure of human action, classifying sequences into action categories. We developed an efficient learning method to train our model, and show that its complexity grows only sublinearly with the depth of the hierarchy. The second algorithm focuses on data fusion the task of combining information from multiple modalities in an effective way. Our approach is motivated by the observation that human behavioral data is modality-wise sparse, i.e., information from just a few modalities contain most information needed at any given time. We perform data fusion using structured sparsity, representing a multimodal signal as a sparse combination of multimodal basis vectors embedded in a hierarchical tree structure, learned directly from the data. The key novelty is in a mixed-norm formulation of regularized matrix factorization via structured sparsity.
Generation of hybrid cell lines with endothelial potential from spontaneous fusion of adult bone marrow cells with embryonic fibroblast feeder

SummaryWe have previously isolated mouse embryonic cell lines with endothelial potential using a simple empirical approach. In an attempt to isolate similar cell lines from adult mouse bone marrow (BM), BM cells were cultured on mitotically inactive mouse embryonic fibroblast (MEF) feeder cells. Several cell lines with putative endothelial potential were generated. They expressed endothelial-specific genes and formed vascular-like structures when plated on matrigel. When transplanted into appropriate mouse models, they incorporated into the endothelium of the vasculature. Similar cell lines were also obtained using human or porcine BM. None of these lines induced tumor formation when transplanted into immunodeficient Rag1−/− mice. However, all the lines were aneuploid with genetic markers from BM samples and the MEF feeder, suggesting that they resulted from a non-species-specific fusion of a BM cell and mitotically inactive MEF. Together, these lines demonstrated for the first time that BM cells can also undergo fusion with commonly used mitotically inactive feeder cells. Although these fusion cell lines were culture artifacts, their derivation would be useful in understanding fusion of BM cells with other cell types, and their endothelial potential will also be useful in characterizing endothelial differentiation.
Multivariate Signed-Rank Tests in Vector Autoregressive Order Identification

The classical theory of rank-based inference is essentially limited to univariate linear models with independent observations. The objective of this paper is to illustrate some recent extensions of this theory to time-series problems (serially dependent observations) in a multivariate setting (multivariate observations) under very mild distributional assumptions (mainly, elliptical symmetry; for some of the testing problems treated below, even second-order moments are not required). After a brief presentation of the invariance principles that underlie the concepts of ranks to be considered, we concentrate on two examples of practical relevance: (1) the multivariate Durbin–Watson problem (testing against autocorrelated noise in a linear model context) and (2) the problem of testing the order of a vector autoregressive model, testing VAR(p0) against VAR(p0 + 1) dependence. These two testing procedures are the building blocks of classical autoregressive order-identification methods. Based either on pseudo-Mahalanobis (Tyler) or on hyperplane-based (Oja and Paindaveine) signs and ranks, three classes of test statistics are considered for each problem: (1) statistics of the sign-test type, (2) Spearman statistics and (3) van der Waerden (normal score) statistics. Simulations confirm theoretical results about the power of the proposed rank-based methods and establish their good robustness properties.
Twitter and the Political Landscape - a Graph Analysis of German Politicians

This paper examines the Twitter social graph of German politicians and political parties during a time period not potentially biased by nearby elections. Based on a data set of 1,719 politicians across the entire political spectrum of this important country in the EU, two graphs are constructed, which also reflect relationships within and between parties: the follower graph, consisting of all followerfollowee relationships between German politicians, and the “mention graph”, which models direct references of politicians to their colleagues. Our main contributions are as follows: First, we analyse these graphs according to several statistics and graph metrics, characterizing political parties according to their collective participation in Twitter. We also investigate the openness for following ideas across political camps, resulting in the discovery of three distinct groups of political parties. We also find that membership in political parties itself explains only little of the variation in the formation of ties. There is also evidence that politicians with less activity exhibit a higher degree of openness than users with active engagement in tweets and discussions. This case study on social media adoption in politics leads to interesting insights into political debate in the information society.
Survey of Visual Question Answering: Datasets and Techniques

Visual question answering (or VQA) is a new and exciting problem that combines natural language processing and computer vision techniques. We present a survey of the various datasets and models that have been used to tackle this task. The first part of the survey details the various datasets for VQA and compares them along some common factors. The second part of this survey details the different approaches for VQA, classified into four types: non-deep learning models, deep learning models without attention, deep learning models with attention, and other models which do not fit into the first three. Finally, we compare the performances of these approaches and provide some directions for future work.
An Approach to Modeling Context Using Semantic Maps

Although a precise definition is hard to pinpoint, context can be seen as the information that meaning is dependent on. For an artificial agent that is expected to interact with humans, the success of its interactions with both the environment and humans depends on context. This report aims to investigate a unified framework for context in robots, inspired from semantic space models and a non-commutative and non-distributive probability framework.
The design of double Gauss systems using digital computers.

A general study of the design of lenses of double Gauss type and derivatives of these has been carried out, with the lenses optimized at an aperture of f/2 and a field angle of +/-20 degrees . The results indicate that the number of optimized designs is small for all of the constructions that were investigated. Numerical examplesfor several designs are given.
An Integrated CP/OR Method for Optimal Control of Modular Hybrid Systems

This paper concerns the optimal control of modular hybrid systems synchronized by shared variables. Instead of synchronizing the discrete dynamics of the system into one global mode before optimization, Constraint Programming (CP) is used to model the discrete dynamics of each modular system separately. Integrated in the CP solver are also classic Operations Research (OR) models in the form of Nonlinear Programs (NLPs) approximating the continuous dynamics of the system. Using CP considerably decreases the number of NLPs which must be solved, compared to that of using a traditional mixed integer nonlinear programming approach.
An anti‐peptide antibody that recognizes a neo‐antigen in the CR1 stump remaining on erythrocytes after proteolysis

Previous studies of erythrocyte CR1 levels in systemic lupus erythematosus (SLE) and other diseases with in vovo complement activation have led lo the conclusion that CR1 levels fall because of loss of CR1 from erythrocytes by proteolysis —predominantly in the liver. In order to measure the existence of proteolysed CR1 remnants on erythrocytes an antibody was raised to a peptide corresponding to the CR1 sequence between the proximal standard consensus repeat (SCR) and the transmembrane segment. This antipeptide antibody recognizes a neo‐antigen found on trypsinized erythrocytes which has been demonstrated to represent the “CRI‐stump”, The anti‐ ‘CR1‐stump’ antiserum detects proteolysed CR1 on the ex vivo erythrocytes of a patient with cold haemolytic antibody disease (CHAD). However, higher affinity antibodies will be needed to make anti‐ CR1 ‐stump a satisfactory diagnostic reagent.
Nb3Sn High Field Magnets for the High Luminosity LHC Upgrade Project

The high luminosity upgrade of the Large Hadron Collider at CERN requires a new generation of high field superconducting magnets. High field large aperture quadrupoles (MQXF) are needed for the low-beta triplets close to the ATLAS and CMS detectors, and high field two-in-one dipoles (11-T dipoles) are needed to make room for additional collimation. The MQXF quadrupoles, with a field gradient of 140 T/m in 150 mm aperture, have a peak coil field of 12.1 T at nominal current. The 11-T dipoles, with an aperture of 60 mm, have a peak coil field of 11.6 T at nominal current. Both magnets require Nb3Sn conductor and are the first applications of this superconductor to actual accelerator magnets. Collaboration between the US LARP (LHC Accelerator Research Program) and CERN is developing the MQXF magnets, whereas the 11-T dipole magnets are being developed by CERN and Fermilab. This paper reviews the status of Nb3Sn technology for accelerator magnets, discusses its main challenges, and discusses how the MQXF and 11-T designs are addressing them.
Classification of prostatic diseases by means of multivariate analysis on in vivo proton MRSI and DCE‐MRI data

Multivariate analysis has been applied on proton magnetic resonance spectroscopic imaging (1H‐MRSI) and dynamic contrast enhanced MRI (DCE‐MRI) data of patients with different prostatic diseases such as chronic inflammation, fibrosis and adenocarcinoma. Multivariate analysis offers a global view of the entire range of information coming from both the imaging and spectroscopic side of NMR technology, leading to an integrated picture of the system relying upon the entire metabolic and dynamic profile of the studied samples. In this study, we show how this approach, applied to 1H‐MRSI/DCE‐MRI results, allows us to differentiate among the various prostatic diseases in a non‐invasive way with a 100% accuracy. These findings suggest that multivariate analysis of 1H‐MRSI/DCE‐MRI can significantly improve the diagnostic accuracy for these pathological entities. From a more theoretical point of view, the complementation of a single biomarker approach with an integrated picture of the entire metabolic and dynamic profile allows for a more realistic appreciation of pathological entities. Copyright © 2009 John Wiley & Sons, Ltd.
Intelligent trajectory control using recurrent averaging learning

In this article, robotic trajectory control using artificial intelligence techniques is developed. The learning strategy is called recurrent averaging learning. It takes the average of initial states and final states after a cycle of training and sets this value as the new initial and final states for next training cycle. A three-layer neural network is used as a controller, it provides the control signals in each stage of a walking gait. A linearized inverse biped model is derived. This model calculates the error signals that will be used to back propagate to the controller in each stage. Through learning, the robot can develop skills to walk along a predefined path with specified step length, walking speed, and crossing clearance. This proposed scheme is tested with simulations of the BLR-G1 walking robot on horizontal and sloping surfaces.
The parietal art of the Late Magdalenian

While lively debate has gone on about the meaning and function of Palaeolithic parietal art, the intractable and essential questions of its dating have been less in the foreground. With Leroi-Gourhan's interpretations goes his identification of styles and their chronology, published in 1965. Now one period, the Late Magdalenian of his Style IV, is looked at closely with chronology in mind
Suppression of Flux Creep in HTS Coil by Applying Low AC Magnetic Field

The suppression of flux creep in the central magnetic field of an high-temperature superconducting (HTS) coil is experimentally validated by applying a low ac magnetic field using additional coils. The HTS coil is fabricated using a Gd-based coated conductor, and a pair of the additional coils wound using copper wires, which are connected in series in the opposite direction, are located coaxially inside and outside the HTS coil. These coils are immersed in liquid nitrogen, and the temporal evolutions of the central fields in the axial direction by applying ac fields for short periods of time using the additional coils after the ramping processes of the HTS coil are observed using a Hall probe. The influences of the amplitude and frequency of ac field on the flux creep in the HTS coil are investigated experimentally.
Fully automated pipeline for quantification and localization of white matter hyperintensity in brain magnetic resonance image

Automated white matter hyperintensity (WMH) segmentation on magnetic resonance imaging is greatly advantageous for various clinical studies using large‐sample data. Accurate localization of WMH can provide more beneficial information for clinical studies, as differences of regional WMH existence may be linked to clinical symptoms. We suggest a fully automated method for WMH quantification and localization without human interaction using T1‐weighted and fluid‐attenuated inversion‐recovery (FLAIR) images. The known sources of false‐positive results in the subarachnoid space and brain‐cerebrospinal fluid (CSF) interface were removed by applying a WMH candidate‐region mask. WMH segmentation was performed based on the Markov random field model. The intensity‐substitution method was developed for the accurate localization of WMH, with proper tissue classification and nonlinear registration. The performance of the method was evaluated via comparison with manual delineation; the similarity index and the overlap ratio were 89.94 and 81.90, respectively. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 193–200, 2011
The humoral immune response to Haemophilus influenzae type b: a mathematical model based on T-zone and germinal center B-cell dynamics.

Through careful mapping of the physiology of the T-zone and GC B-blast dynamics to a mathematical representation of the cell processes including proliferation, migration, differentiation, and cell death, a mathematical model is constructed to capture the dominant nominal primary, late follicular, and secondary humoral response to Haemophilus influenzae Type b. This model explicitly incorporates the dynamics of memory B-cells, T-zone and GC B-dynamics, IgM and IgG antibodies, avidity maturation, and IC presentation by FDCs into a coherent framework. This paper describes the relevant immunology, the pertinent physiological assumptions, the developed model, and the parameter identification procedure. The model parameters were found using a parameter identification procedure that capitalizes on the timing and interactions of certain dominant physiological attributes. Simulation results and validation tests indicate that the model reflects not only a nominal primary and secondary humoral immune response but also the tertiary and T-independent responses. The model shows robustness to variations in infection dosage, bacterial growth rate (virulence of the strain), and onset-timing of the secondary response. The utility of this model in studying the humoral immune response is demonstrated through suggested physiological assumptions, mechanisms, and rates to be eventually clinically evaluated as well as insights into vaccination design. The model and parameter identification techniques are easily adapted to other diseases which primarily evoke a humoral immune response.
The use of ethnographic analyses for researching Late Palaeolithic settlement systems, settlement patterns and land use in the Northwest European Plain

In this paper the results of the analysis of data on residential and non-residential settlements in seventy arctic and sub-arctic North American collector societies are presented. These results are related to the major resource strategies of those societies, and pertain to the ten analytical domains recommended by Binford (1983) for the analysis and interpretation of collector settlements. These results can serve as an effective analogue for the diagnosis and interpretation of Late Palaeolithic Federmesser settlements and land-use practices. Ten fully excavated, representative and mutually comparable Federmesser sites are studied (Houtsma et al. in press). One of these is situated in Great Britain, the others in the Northwest European Plain. By statistical analyses of the ethnographic and the archaeological data, the functions of the ten settlements are diagnosed. Most probably none of these ten sites represents a residential settlement. The hypothesis is proposed that the Federmesser culture constitutes a single language family or perhaps a single tribe/society, with part of its residential settlements in the present North Sea.
The Regulatory Role of Dendritic Cells in the Immune Response

Dendritic cells (DCs) are key regulators of immune reactions. They control early innate responses, regulate long-lasting adaptive immunity and contribute to the maintenance of self-tolerance. DCs continuously monitor the environment through a multifaceted innate antigen receptor repertoire and, in response to perturbations, start a complex genetic reprogramming that leads to a complete activation of innate and, then, adaptive immune responses. This review discusses how DCs become efficient activators of NK and, subsequently, T cells following a microbial encounter.
A Gene Expression Map of the Arabidopsis Root

A global map of gene expression within an organ can identify genes with coordinated expression in localized domains, thereby relating gene activity to cell fate and tissue specialization. Here, we present localization of expression of more than 22,000 genes in the Arabidopsis root. Gene expression was mapped to 15 different zones of the root that correspond to cell types and tissues at progressive developmental stages. Patterns of gene expression traverse traditional anatomical boundaries and show cassettes of hormonal response. Chromosomal clustering defined some coregulated genes. This expression map correlates groups of genes to specific cell fates and should serve to guide reverse genetics.
A 0.8-V 420nW CMOS switched-opamp switched-capacitor pacemaker front-end with a new continuous-time CMFB

A low-voltage low-power pacemaker Front-End for detecting QRS complex is presented in this paper. The circuit includes a switched-opamp switched-capacitor (SO-SC) preamplifier with a gain of 40 db, a fourth-order Butterworth SO-SC filter with a sampling frequency of 1 kHz, and an opamp with a new continuous time common mode feedback (CMFB) circuit which is able to operate with a very low supply voltage. The whole circuit operates with a supply voltage of 0.8 V and consumes a power of 420 nW.
Protective effect of vardenafil on ischemia–reperfusion injury in rat ovary

Several specimens of the tropical schizomid Stenochrus portoricensis Chamberlin, 1922 (family Hubbardiidae) were found in the Poznan Palm House, representing the first record of micro-whip scorpions (Schizomida) from Poland. Stenochrus portoricensis is an alien species in temperate climates, and has been accidentally introduced to greenhouses via potted plants. Its parthenogenetic lifestyle allows for the easy transfer of populations to new locations and the successful founding of new colonies. New DNA sequence data for Stenochrus portoricensis are presented, which comprise a fragment of the cytochrome c oxidase subunit I gene (DNA barcode sequence) from mitochondrial DNA, and a fragment of the 28S rRNA gene (D1-D3 regions) from nuclear DNA.
Social dominance and reproductive differentiation mediated by dopaminergic signaling in a queenless ant

ABSTRACT In social Hymenoptera with no morphological caste, a dominant female becomes an egg layer, whereas subordinates become sterile helpers. The physiological mechanism that links dominance rank and fecundity is an essential part of the emergence of sterile females, which reflects the primitive phase of eusociality. Recent studies suggest that brain biogenic amines are correlated with the ranks in dominance hierarchy. However, the actual causality between aminergic systems and phenotype (i.e. fecundity and aggressiveness) is largely unknown due to the pleiotropic functions of amines (e.g. age-dependent polyethism) and the scarcity of manipulation experiments. To clarify the causality among dominance ranks, amine levels and phenotypes, we examined the dynamics of the aminergic system during the ontogeny of dominance hierarchy in the queenless ant Diacamma sp. , which undergoes rapid physiological differentiation based on dominance interactions. Brain dopamine levels differed between dominants and subordinates at day 7 after eclosion, although they did not differ at day 1, reflecting fecundity but not aggressiveness. Topical applications of dopamine to the subordinate workers induced oocyte growth but did not induce aggressiveness, suggesting the gonadotropic effect of dopamine. Additionally, dopamine receptor transcripts (dopr1 and dopr2) were elevated in the gaster fat body of dominant females, suggesting that the fat body is a potential target of neurohormonal dopamine. Based on this evidence, we suggest that brain dopamine levels are elevated in dominants as a result of hierarchy formation, and differences in dopamine levels cause the reproductive differentiation, probably via stimulation of the fat body. Summary: Dominant Diacamma ants have higher brain dopamine levels than subordinates and the fat body is the potential target of dopamine that mediates reproduction.
Piecing Together a Picture of Trisomy 8 Mosaicism Syndrome

Abstract Relatively few cases of trisomy 8 mosaicism syndrome (T8mS) are documented in the medical literature. It is a rare genetic condition characterized by extreme phenotypic variability—ranging from severe congenital malformations to minute dysmorphic changes. The authors describe a case of T8mS in a man aged 33 years who presented with lumbar spine herniated nucleus propulsus. This case features some of the classic characteristics of T8mS and suggests an association between T8mS and herniated disks.