Miracle-dz/UniFAR-FTUs huggingface dataset:
Kernel partial least squares regression for relating functional brain network topology to clinical measures of behavior

In this paper we present a novel method for analyzing the relationship between functional brain networks and behavioral phenotypes. Drawing from topological data analysis, we first extract topological features using persistent homology from functional brain networks that are derived from correlations in resting-state fMRI. Rather than fixing a discrete network topology by thresholding the connectivity matrix, these topological features capture the network organization across all continuous threshold values. We then propose to use a kernel partial least squares (kPLS) regression to statistically quantify the relationship between these topological features and behavior measures. The kPLS also provides an elegant way to combine multiple image features by using linear combinations of multiple kernels. In our experiments we test the ability of our proposed brain network analysis to predict autism severity from rs-fMRI. We show that combining correlations with topological features gives better prediction of autism severity than using correlations alone.
Construction of an instrument to measure effectiveness of placement settings and experiences

Evidence-based evaluation instruments for course units offer academics quality data, useful for continual improvement. Placement units are not traditional course units and may require a specific evaluation instrument, of which none seem available. This study commenced the development of a placement evaluation instrument supported by a relevant learning framework. The qualitative study was conducted (n=56) and examined the views of placement stakeholders regarding what attributes of the placement experience should be evaluated. Data were thematically analyzed, leading to a 25 item evaluation instrument. This instrument can be completed by students to evaluate and improve placement experiences and outcomes.
Identifying Potential Adverse Drug Events in Tweets Using Bootstrapped Lexicons

Adverse drug events (ADEs) are medical complications co-occurring with a period of drug usage. Identiﬁcation of ADEs is a primary way of evaluating available quality of care. As more social media users begin discussing their drug experiences online, public data becomes available for researchers to expand existing electronic ADE reporting systems, though non-standard language inhibits ease of analysis. In this study, portions of a new corpus of approximately 160,000 tweets were used to create a lexicon-driven ADE detection system using semi-supervised, pattern-based bootstrapping. This method was able to identify misspellings, slang terms, and other non-standard language features of social media data to drive a competitive ADE detection system.
Chapter 11 Forecasting breaks and forecasting during breaks

Success in accurately forecasting breaks requires that the y are predictable from relevant information available at the forecast origin using an appropriat e model form, which can be selected and estimated before the break. To clarify the roles of these six necessary conditions, we distinguish between the information set for ‘normal forces’ and the one f or ‘break drivers’, then outline sources of potential information. Relevant non-linear, dynamic mo dels facing multiple breaks can have more candidate variables than observations, so we discuss autom tic odel selection. As a failure to accurately forecast breaks remains likely, we augment our str ategy by modelling breaks during their progress, and consider robust forecasting devices. JEL classifications : C1, C53.
Image subtraction for real time moving object extraction

This paper studies the task of extracting moving object from static irrelevant background. The implementation is prepared for the purpose of real time application. Some image processing concepts related to this study are first presented and improvement is proposed. We have obtained motion mask by applying background subtraction and consecutive frame differencing. We also propose a reliable background update and noise reduction operator to facilitate the result of moving object extraction. The analysis and result are obtained by using Matlab Image Processing Toolbox Version 6.01.
Effect of solvents on the degree of ionization of polystyrene balls and their liquid crystallization in the suspension using static light scattering method

The effect of solvents viz. water, benzene and toluene on the ionization of polystyrene balls has been studied using static light scattering method. The degree of ionization of polystyrene balls are different in different solvents that results dissociable charges on polystyrene balls to vary appreciably in magnitude, which have been determined by fitting the observed data with that of rescaled mean spherical approximation results. The ordering has been found to depend on particles concentration in the suspension. At a given concentration, the dielectric constant of the medium is a deciding factor regarding the nature of the binding and hence transition between FCC and BCC type of the ordering. Liquid-like ordering of FCC type amongst the polystyrene macroions suspended into water and BCC type of orderings in macroions suspended into benzene and toluene solvents have been reported.
Context-free Process Algebras Extended with Deadlocks

Recently it has been shown that the class of BPA (or context-free) processes can be widely used to describe sequential processes and to deﬁne their semantics. This class has been intensively studied. Bisimilarity and regularity appeared to be decidable within the BPA processes (see [CHS95], [BCS96]). We extend these processes with a deadlocking state into BPA (cid:14) systems. We show that the BPA (cid:14) class is more expressive w.r. t. bisimulation equivalence but it remains language equivalent to BPA . We prove that bisimilarity and regularity remain decidable in the BPA (cid:14) class. Finally we give a characterisation of those BPA (cid:14) processes which can be equivalently (up to bisimilarity) described within the ‘pure’ BPA syntax.
Integrated Computational and Experimental Analysis of the Neuroendocrine Transcriptome in Genetic Hypertension Identifies Novel Control Points for the Cardiometabolic Syndrome

Background—Essential hypertension, a common complex disease, displays substantial genetic influence. Contemporary methods to dissect the genetic basis of complex diseases such as the genomewide association study are powerful, yet a large gap exists betweens the fraction of population trait variance explained by such associations and total disease heritability. Methods and Results—We developed a novel, integrative method (combining animal models, transcriptomics, bioinformatics, molecular biology, and trait-extreme phenotypes) to identify candidate genes for essential hypertension and the metabolic syndrome. We first undertook transcriptome profiling on adrenal glands from blood pressure extreme mouse strains: the hypertensive BPH (blood pressure high) and hypotensive BPL (blood pressure low). Microarray data clustering revealed a striking pattern of global underexpression of intermediary metabolism transcripts in BPH. The MITRA algorithm identified a conserved motif in the transcriptional regulatory regions of the underexpressed metabolic genes, and we then hypothesized that regulation through this motif contributed to the global underexpression. Luciferase reporter assays demonstrated transcriptional activity of the motif through transcription factors HOXA3, SRY, and YY1. We finally hypothesized that genetic variation at HOXA3, SRY, and YY1 might predict blood pressure and other metabolic syndrome traits in humans. Tagging variants for each locus were associated with blood pressure in a human population blood pressure extreme sample with the most extensive associations for YY1 tagging single nucleotide polymorphism rs11625658 on systolic blood pressure, diastolic blood pressure, body mass index, and fasting glucose. Meta-analysis extended the YY1 results into 2 additional large population samples with significant effects preserved on diastolic blood pressure, body mass index, and fasting glucose. Conclusions—The results outline an innovative, systematic approach to the genetic pathogenesis of complex cardiovascular disease traits and point to transcription factor YY1 as a potential candidate gene involved in essential hypertension and the cardiometabolic syndrome.
CD8+ T-Cell Responses to Trypanosoma cruzi Are Highly Focused on Strain-Variant trans-Sialidase Epitopes

CD8+ T cells are crucial for control of a number of medically important protozoan parasites, including Trypanosoma cruzi, the agent of human Chagas disease. Yet, in contrast to the wealth of information from viral and bacterial infections, little is known about the antigen specificity or the general development of effector and memory T-cell responses in hosts infected with protozoans. In this study we report on a wide-scale screen for the dominant parasite peptides recognized by CD8+ T cells in T. cruzi–infected mice and humans. This analysis demonstrates that in both hosts the CD8+ T-cell response is highly focused on epitopes encoded by members of the large trans-sialidase family of genes. Responses to a restricted set of immunodominant peptides were especially pronounced in T. cruzi–infected mice, with more than 30% of the CD8+ T-cell response at the peak of infection specific for two major groups of trans-sialidase peptides. Experimental models also demonstrated that the dominance patterns vary depending on the infective strain of T. cruzi, suggesting that immune evasion may be occurring at a population rather than single-parasite level.
Functional classification of CATH superfamilies: a domain-based approach for protein function annotation

Motivation: Computational approaches that can predict protein functions are essential to bridge the widening function annotation gap especially since <1.0% of all proteins in UniProtKB have been experimentally characterized. We present a domain-based method for protein function classification and prediction of functional sites that exploits functional sub-classification of CATH superfamilies. The superfamilies are sub-classified into functional families (FunFams) using a hierarchical clustering algorithm supervised by a new classification method, FunFHMMer. Results: FunFHMMer generates more functionally coherent groupings of protein sequences than other domain-based protein classifications. This has been validated using known functional information. The conserved positions predicted by the FunFams are also found to be enriched in known functional residues. Moreover, the functional annotations provided by the FunFams are found to be more precise than other domain-based resources. FunFHMMer currently identifies 110 439 FunFams in 2735 superfamilies which can be used to functionally annotate > 16 million domain sequences. Availability and implementation: All FunFam annotation data are made available through the CATH webpages (http://www.cathdb.info). The FunFHMMer webserver (http://www.cathdb.info/ search/by_funfhmmer) allows users to submit query sequences for assignment to a CATH FunFam. Contact: sayoni.das. 12@ucl.ac. uk Supplementary information: Supplementary data are available at Bioinformatics online.
Social Networks for Knowledge Management

—Online social networks have changed the way many people communicate and interact as private individuals and employees. Sharing and communication through this medium has become, for many, a daily habit. Many of these networks provide a simple way to seek and find knowledge and expertise from both friends and strangers. Information technology has been used in many ways to support knowledge management initiatives. However the use of social networking technology has been little explored. It is thus argued that combining knowledge management systems with social networking technology would bridge this gap. Social software is becoming part of a standard arsenal of tools deployed within companies, tools that may help knowledge management. Evidence is presented from a review of relevant literature and through a survey, conducted via online social networks, asking respondents’ usage of social networking for knowledge management purposes in both their private lives and also work-related practices. It shows that personal networks are often used as a medium to seek knowledge for personal and for organisational motives. The results confirm that online social networks, and their enterprise counterparts, are aiding knowledge management initiatives. Knowledge appears to be flowing through online social networks. Findings also include the confirmation of Dunbar’s number, and reaffirming the strength of “weak ties” as originally proposed by Granovetter. The paper proposes the new concept of temporary ties that are aided through social networks. It also describes the work in progress and findings so far on the use of social networking technology and habits for aiding knowledge management initiatives.
Mixed-Membership Stochastic Block-Models for Transactional Data

Transactional network data arise in many fields. Although social network models have been applied to transactional data, these models typically assume binary relations between pairs of nodes. We develop a latent mixed membership model capable of modelling richer forms of transactional data. Estimation and inference are accomplished via a variational EM algorithm. Simulations indicate that the learning algorithm can recover the correct generative model. We further present results on a subset of the Enron email dataset.
Effect of Gate Dielectrics on the Performance of P-Type Cu2O TFTs Processed at Room Temperature

Single-phase Cu2O films with p-type semiconducting properties were successfully deposited by reactive DC magnetron sputtering at room temperature followed by post annealing process at 200°C. Subsequently, such films were used to fabricate bottom gate p-channel Cu2O thin film transistors (TFTs). The effect of using high-κ SrTiO3 (STO) as a gate dielectric on the Cu2O TFT performance was investigated. The results were then compared to our baseline process which uses a 220 nm aluminum titanium oxide (ATO) dielectric deposited on a glass substrate coated with a 200 nm indium tin oxide (ITO) gate electrode. We found that with a 150 nm thick STO, the Cu2O TFTs exhibited a p-type behavior with a field-effect mobility of 0.54 cm2.V-1.s-1, an on/off ratio of around 44, threshold voltage equaling-0.62 V and a sub threshold swing of 1.64 V/dec. These values were obtained at a low operating voltage of-2V. The advantages of using STO as a gate dielectric relative to ATO are discussed.
Atlas: Baidu's key-value storage system for cloud data

Users store rapidly increasing amount of data into the cloud. Cloud storage service is often characterized as having a large data set and few deletes. Hosting the service on a conventional system consisting of servers of powerful CPUs and managed by either a key-value (KV) system or a file system is not efficient. First, as demand on storage capacity grows much faster than that on CPU power, existing server configurations can lead to CPU under-utilization and inadequate storage. Second, as data durability is of paramount importance and storage capacity can be limited, a data protection scheme relying on data replication is not space efficient. Third, because of the unique distribution of data object size (mostly a few KBytes), hard disks may suffer from unnecessarily high request rate (when data is stored as KV pairs and need constant re-organization) or too many random writes (when data is stored as relatively small files). In Baidu this inefficiency has become an urgent issue as data is uploaded into the storage at an increasingly high rate and both the user population and the system are rapidly expanding. To address this issue, we adopt a customized compact server design based on the ARM processors and replace three-copy replication for data protection with erasure coding to enable low-power and high-density storage. Furthermore, there is a huge number of objects stored in the system, such as those for photos, MP3 music, and documents, but their sizes do not allow efficient operations in the conventional KV systems. To this end we propose an innovative architecture separating metadata and data managements to enable efficient data coding and storage. The resulting production system, called Atlas, is a highly scalable, reliable, and cost-effective KV store supporting Baidu's cloud storage service.
Prediction of Fracture and Detection of Fatigue in Ceramic Composites from Electrical Resistivity Measurements

Fracture prediction and fatigue detection techniques in ceramic composites were examined. Composites with an electric conduction path were fabricated with ceramics having different electrical resistivity, using calcium fluoride powder as the insulating matrix and silicon carbide whiskers as the conducting additive. When a bending load was applied to the test piece, the electrical resistivity of the composites increased up to fracture. When the test pieces were repeatedly loaded below the fracture limit, there was a gradual increase of electrical resistivity before fracture. These phenomena suggested the possibility of predicting fracture and detecting fatigue in ceramic composites. The movement of whiskers disconnecting the conduction path and leading to an increase in electrical resistivity was confirmed by scanning electron microscopy observation.
Mineralocorticoid receptor overexpression in embryonic stem cell-derived cardiomyocytes increases their beating frequency.

AIMS Cardiac mineralocorticoid receptor (MR) activation triggers adverse cardiovascular events that could be efficiently prevented by mineralocorticoid antagonists. To gain insights into the pathophysiological role of MR function, we established embryonic stem (ES) cell lines from blastocysts of transgenic mice overexpressing the human MR driven by its proximal P1 or distal P2 promoter and presenting with cardiomyopathy, tachycardia, and arrhythmia. Cardiomyocyte differentiation allowed us to investigate the molecular mechanisms contributing to MR-mediated cardiac dysfunction. METHODS AND RESULTS During cardiac differentiation, wild-type (WT) and recombinant ES cell cultures and excised beating patches expressed endogenous MR along with cardiac gene markers. The two-fold increase in MR protein detected in P1.hMR and P2.hMR cardiomyocytes led to a parallel increase in the spontaneous beating frequency of hMR-overexpressing cardiomyocytes compared with WT. The MR-mediated chronotropic effect was ligand-independent, could be partially repressed by spironolactone, and was accompanied by a significant two- to four-fold increase in mRNA and protein levels of the pacemaker channel HCN1, generating depolarizing If currents, thus revealing a potential new MR target. This was associated with modification in the expression of HCN4, the inward-rectifier potassium channel Kir2.1, and the L-type voltage-dependent calcium channel Cav1.2. CONCLUSION We demonstrate that the amplification of MR signalling in ES-derived cardiomyocytes has a major impact on cardiomyocyte contractile properties through an important remodelling of ion channel expression, contributing to arrhythmias. Our results highlight the prominent role of MR function in cardiac physiology and support the benefit of MR antagonists in the management of cardiac dysfunctions.
Enabling accurate analysis of private network data

This dissertation addresses the challenge of enabling accurate analysis of network data while ensuring the protection of network participants' privacy. This is an important problem: massive amounts of data are being collected (facebook activity, email correspondence, cell phone records), there is huge interest in analyzing the data, but the data is not being shared due to concerns about privacy. Despite much research in privacy-preserving data analysis, existing technologies fail to provide a solution because they were designed for tables, not networks, and cannot be easily adapted to handle the complexities of network data. We develop several technologies that advance us toward our goal. First, we develop a framework for assessing the risk of publishing a network that has been “anonymized. ” Using this framework, we show that only a small amount of background knowledge about local network structure is needed to re-identify an “anonymous” individual. This motivates our second contribution: an algorithm that transforms the structure of the network to provably lower re-identification risk. In comparison with other algorithms, we show that our approach more accurately preserves important features of the network topology. Finally, we consider an alternative paradigm, in which the analyst can analyze private data through a carefully controlled query interface. We show that the degree sequence of a network can be accurately estimated under strong guarantees of privacy.
Functional morphology of the pectoral fins in bamboo sharks, Chiloscyllium plagiosum: Benthic vs. Pelagic station‐holding

Bamboo sharks (Chiloscyllium plagiosum) are primarily benthic and use their relatively flexible pectoral and pelvic fins to rest on and move about the substrate. We examined the morphology of the pectoral fins and investigated their locomotory function to determine if pectoral fin function during both benthic station‐holding and pelagic swimming differs from fin function described previously in leopard sharks, Triakis semifasciata. We used three‐dimensional kinematics and digital particle image velocimetry (DPIV) to quantify pectoral fin function in five white‐spotted bamboo sharks, C. plagiosum, during four behaviors: holding station on the substrate, steady horizontal swimming, and rising and sinking during swimming. During benthic station‐holding in current flow, bamboo sharks decrease body angle and adjust pectoral fin angle to shed a clockwise fluid vortex. This vortex generates negative lift more than eight times that produced during open water vertical maneuvering and also results in an upstream flow that pushes against the posterior surface of the pectoral fin to oppose drag. In contrast, there is no evidence of significant lift force in the wake of the pectoral fin during steady horizontal swimming. The pectoral fin is held concave downward and at a negative dihedral angle during steady horizontal swimming, promoting maneuverability rather than stability, although this negative dihedral angle is much less than that observed previously in sturgeon and leopard sharks. During sinking, the pectoral fins are held concave upward and shed a clockwise vortex with a negative lift force, while in rising the pectoral fin is held concave downward and sheds a counterclockwise vortex with a positive lift force. Bamboo sharks appear to sacrifice maneuverability for stability when locomoting in the water column and use their relatively flexible fins to generate strong negative lift forces when holding position on the substrate and to enhance stability when swimming in the water column. J. Morphol. 249:195–209, 2001. © 2001 Wiley‐Liss, Inc.