Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Consumer Adverse Drug Reaction Messages on Social Media

The prevalence of social media has resulted in spikes of data on the Internet which can have potential use to assist in many aspects of human life. One prospective use of the data is in the development of an early warning system to monitor consumer Adverse Drug Reactions (ADRs). The direct reporting of ADRs by consumers is playing an increasingly important role in the world of pharmacovigilance. Social media provides patients a platform to exchange their experiences regarding the use of certain drugs. However, the messages posted on those social media networks contain both ADR related messages (positive examples) and non-ADR related messages (negative examples). In this paper, we integrate text mining and partially supervised learning methods to automatically extract and classify messages posted on social media networks into positive and negative examples. Our findings can provide managerial insights into how social media analytics can improve not only postmarketing surveillance, but also other problem domains where large quantity of user-generated content is available.
Minimization of Error Functionals over Perceptron Networks

Supervised learning of perceptron networks is investigated as an optimization problem. It is shown that both the theoretical and the empirical error functionals achieve minima over sets of functions computable by networks with a given number n of perceptrons. Upper bounds on rates of convergence of these minima with n increasing are derived. The bounds depend on a certain regularity of training data expressed in terms of variational norms of functions interpolating the data (in the case of the empirical error) and the regression function (in the case of the expected error). Dependence of this type of regularity on dimensionality and on magnitudes of partial derivatives is investigated. Conditions on the data, which guarantee that a good approximation of global minima of error functionals can be achieved using networks with a limited complexity, are derived. The conditions are in terms of oscillatory behavior of the data measured by the product of a function of the number of variables d, which is decreasing exponentially fast, and the maximum of the magnitudes of the squares of the L1-norms of the iterated partial derivatives of the order d of the regression function or some function, which interpolates the sample of the data. The results are illustrated by examples of data with small and high regularity constructed using Boolean functions and the gaussian function.
Hypothalamic BOLD response to glucose intake and hypothalamic volume are similar in anorexia nervosa and healthy control subjects

Background: Inconsistent findings about the neurobiology of Anorexia Nervosa (AN) hinder the development of effective treatments for this severe mental disorder. Therefore, the need arises for elucidation of neurobiological factors involved in the pathophysiology of AN. The hypothalamus plays a key role in the neurobiological processes that govern food intake and energy homeostasis, processes that are disturbed in anorexia nervosa (AN). The present study will assess the hypothalamic response to energy intake and the hypothalamic structure in patients with AN and healthy controls. Methods: Ten women aged 18–30 years diagnosed with AN and 11 healthy, lean (BMI < 23 kg/m2) women in the same age range were recruited. We used functional magnetic resonance imaging (MRI) to determine function of the hypothalamus in response to glucose. Structural MRI was used to determine differences in hypothalamic volume and local gray matter volume using manual segmentation and voxel-based morphometry. Results: No differences were found in hypothalamic volume and neuronal activity in response to a glucose load between the patients and controls. Whole brain structural analysis showed a significant decrease in gray matter volume in the cingulate cortex in the AN patients, bilaterally. Conclusions: We argue that in spite of various known changes in the hypothalamus the direct hypothalamic response to glucose intake is similar in AN patients and healthy controls.
Parallel SECONDO: Practical and efficient mobility data processing in the cloud

This paper presents a hybrid parallel processing system, named Parallel Secondo. It combines the Hadoop framework and a set of single-computer Secondo databases, in order to introduce the mobility data procedures into the parallel processing community, and vice versa. The system keeps the front-end and the executable language of Secondo to allow the users to state their parallel queries like common sequential queries. Besides, a set of auxiliary scripts is provided so as to make it easier to manage the system no matter how large the underlying cluster is, and keep the Hadoop platform as a transparent level of the system. Further, a parallel data model is also proposed in this paper to encapsulate all available Secondo data types and operators. Thereby, it is able to transform any Secondo sequential query to its corresponding parallel expression. For instance, all example queries in the moving objects database benchmark BerlinMOD are transformed, and two of them are demonstrated in this paper. In the last evaluations, this paper illustrates that Parallel Secondo is not only a practical but also an efficient system. For queries involving large amounts of data, it performs both linear speed-up and scale-up.
Sign Language Recognition by Combining Statistical DTW and Independent Classification

To recognize speech, handwriting, or sign language, many hybrid approaches have been proposed that combine dynamic time warping (DTW) or hidden Markov models (HMMs) with discriminative classifiers. However, all methods rely directly on the likelihood models of DTW/HMM. We hypothesize that time warping and classification should be separated because of conflicting likelihood modeling demands. To overcome these restrictions, we propose using statistical DTW (SDTW) only for time warping, while classifying the warped features with a different method. Two novel statistical classifiers are proposed - combined discriminative feature detectors (CDFDs) and quadratic classification on DF Fisher mapping (Q-DFFM) - both using a selection of discriminative features (DFs), and are shown to outperform HMM and SDTW. However, we have found that combining likelihoods of multiple models in a second classification stage degrades performance of the proposed classifiers, while improving performance with HMM and SDTW. A proof-of-concept experiment, combining DFFM mappings of multiple SDTW models with SDTW likelihoods, shows that, also for model-combining, hybrid classification can provide significant improvement over SDTW. Although recognition is mainly based on 3D hand motion features, these results can be expected to generalize to recognition with more detailed measurements such as hand/body pose and facial expression.
Circulating Coxsackievirus A16 Identified as Recombinant Type A Human Enterovirus, China

To determine the relationship of coxsackievirus A16 (CA16) to prototype CA16-G10, we conducted a phylogenetic analysis of circulating CA16 strains in China. Complex recombinant forms of CA16-related viruses involving multiple human enteroviruses, subgroup A (CA4, CA16, and enterovirus 71), are prevalent among patients with hand, foot, and mouth disease.
FIRST- AND SECOND-ORDER ADAPTIVE DIFFERENTIAL MICROPHONE ARRAYS

Whenever undesired noise sources are spatially nonstationary, conventional directional microphone technology has its limits in terms of interference suppression. Adaptive differential microphone arrays (ADMAs) with their null steering capabilities promise better performance. This contribution introduces and examines firstand second-order ADMAs based on fullband as well as on subband algorithms. A real-time implementation that demonstrates its usability is also presented.
Embedded Security for Network-Attached Storage,

Abstract : As storage interconnects evolve from single host small scale systems, such as traditional SCSI, to the multi-host Internet based systems of Network attached Secure Disks (NASD), protecting the integrity of data transfers between client and storage becomes essential. However, it is also computationally expensive and can impose significant performance penalties on storage systems. This paper explores several techniques that can protect the communications integrity of storage requests and data transfers, imposing very little performance penalty and significantly reducing the amount of required cryptography. Central to this work is an alternative cryptographic approach, called Hash and MAC, that reduces the cost of protecting the integrity of read traffic in storage devices that are unable to generate a message authentication code at full data transfers rates. Hash and MAC does this by precomputing security information, using and reusing the precomputed information on subsequent read requests. We also present a refined Hash and MAC approach that uses incremental hash functions to improve the performance of small read and write operations as well as non-block aligned operations.
Five human genes encoding F-box proteins: chromosome mapping and analysis in human tumors

Members of the f̲-b̲ox p̲rotein (Fbp) family are characterized by an approximately 40 amino acid F-box motif. SCF complexes (formed by s̲kp1, c̲ullin, and one of many f̲bps) act as protein-ubiquitin ligases that control the G1/S transition of the eukaryotic cell cycle. The substrate specificity of SCF complexes is determined by the presence of different Fbp subunits that recruit specific substrates for ubiquitination. Unchecked degradation of cellular regulatory proteins has been observed in certain tumors and it is possible that deregulated ubiquitin ligases play a role in the altered degradation of cell cycle regulators. We have recently identified a family of human Fbps. As a first step aimed at determining if FBP genes could be involved in human neoplasia, we have mapped the chromosome positions of 5 FBP genes by fluorescence in situ hybridization (FISH) to 10q24 (BTRC alias β-TRCP/FBW1a), 9q34 (FBXW2 alias FBW2), 13q22 (FBXL3A alias FBL3a), 5p12 (FBXO4 alias FBX4) and 6q25→q26 (FBXO5 alias FBX5). Since most of these are chromosomal loci frequently altered in tumors, we have screened 42 human tumor cell lines and 48 human tumor samples by Southern hybridization and FISH. While no gross alterations of the genes encoding β-Trcp/Fbw1a, Fbw2, Fbx4 and Fbx5 were found, heterozygous deletion of the FBXL3A gene was found in four of 13 small cell carcinoma cell lines. This is the first evaluation of genes encoding Fbps in human tumors.
The CaaX motif is required for isoprenylation, carboxyl methylation, and nuclear membrane association of lamin B2

Recent evidence suggests that the conserved COOH-terminal CaaX motif of nuclear lamins may play a role in targeting newly synthesized proteins to the nuclear envelope. We have shown previously that in rabbit reticulocyte lysates the cysteine residue of the CaaX motif of chicken lamin B2 is necessary for incorporation of a derivative of mevalonic acid, the precursor of isoprenoids. Here we have analyzed the properties of normal and mutated forms of chicken lamin B2 stably expressed in mouse L cells. Mutation of the cysteine residue of the CaaX motif to alanine or introduction of a stop codon immediately after the cysteine residue was found to abolish both isoprenylation and carboxyl methylation of transfected lamin B2. Concomitantly, although nuclear import of the mutant lamin B2 proteins was preserved, their association with the inner nuclear membrane was severely impaired. From these results we conclude that the COOH-terminal CaaX motif is required for isoprenylation and carboxyl methylation of lamins in vivo, and that these modifications are important for association of B-type lamins with the nucleoplasmic surface of the inner nuclear membrane.
Sit-to-stand task on a humanoid robot from human demonstration

In this work, we perform the challenging task of a humanoid robot standing up from a chair. First we recorded demonstrations of sit-to-stand motions from normal human subjects as well as actors performing stylized standing motions (e.g. imitating an elderly person). Ground contact force information was also collected for these motions, in order to estimate the human's center of mass trajectory. We then mapped the demonstrated motions to the humanoid robot via an inverse kinematics procedure that attempts to track the human's kinematics as well as their center-of-mass trajectory. In order to estimate the robot's center-of-mass position accurately, we additionally used an inertial parameter identification technique that fit mass and center-of-mass link parameters from measured force data. We demonstrate the resulting motions on the Carnegie Mellon/Sarcos hydraulic humanoid robot.
Novel Markers in Zero-Hour Kidney Biopsies Indicate Graft Quality and Clinical Outcome

Background. In renal transplantation, allograft biopsies provide valuable diagnostic information indicating adverse allograft outcome posttransplantation. To uncover novel candidate markers characteristic of subtle inflammation and immune activation present during the intraoperative period, we investigated messenger RNA (mRNA) gene expression profiles in renal zero biopsies. Methods. Transcription profiles from deceased donors (n=63) and living donors (n=26) were investigated for inflammation-associated markers in zero-hour biopsies by real-time reverse-transcriptase polymerase chain reaction. Results. We observed a significant induction of the chemokine receptor 7 ligands [C-C motif] ligand 19/21 in the deceased donor group (P<0.001). Additionally, along with the induction of the activation marker CD69 (P<0.01), we further detected significant elevated mRNA levels of the inducible immunoproteasome subunits PSMB8, PSMB9, and PSMB10 (P<0.001, respectively). Candidate markers were further tested for posttransplantation clinical outcomes showing the potential to predict the development of delayed graft function, acute rejection, and renal function after 6 months. For instance, by combining mRNA gene expression profiles with clinical patient data, the analysis revealed high sensitivity (95%) and specificity (84%, area under the curve=0.93) for the prediction of acute rejection. Conclusions. Zero-hour biopsies of renal allografts may provide useful information on subclinical pathological changes in the grafted kidney. The identification of CCL19/21 or PSMB8/9/10 makes these molecules particularly suitable as potential candidate targets for therapeutic interventions.
Sensitivity of isoprene emissions from the terrestrial biosphere to 20th century changes in atmospheric CO2 concentration, climate, and land use

We describe the development and analysis of a global model based on Model of Emissions of Gases and Aerosols from Nature (MEGAN) (Guenther et al., 2006) for estimating isoprene emissions from terrestrial vegetation. The sensitivity of calculated isoprene emissions to descriptors including leaf age, soil moisture, atmospheric CO2 concentration, and regional variability of emission factors is analyzed. The validity of the results is evaluated by comparison with compilations of published field‐based canopy‐scale observations. Calculated isoprene emissions reproduce above‐canopy flux measurements and the site‐to‐site variability across a wide range of latitudes, with the model explaining 60% of the variance. Although the model underestimates isoprene emissions, especially in northern latitude localities, this disagreement is significantly corrected when regional variability of emission factors for particular plant functional types is considered (r2 = 0.78). At the global scale, we estimate a terrestrial biosphere isoprene flux of 413 TgC yr−1 using the present‐day climate, atmospheric CO2 concentration, and vegetation distribution, and this compares with other published estimates from global modeling studies of 402 to 660 TgC yr−1. The validated model was used to calculate changes in isoprene emissions in response to atmospheric CO2 increase, climate change, and land use change during the 20th century (1901–2002). Changes in all of these factors are found to impact significantly on isoprene emissions over the course of the 20th century. Between 1901 and 2002, we estimate that at the global scale, climate change was responsible for a 7% increase in isoprene emissions, and rising atmospheric CO2 caused a 21% reduction. However, by the end of the 20th century (2002), anthropogenic cropland expansion has the largest impact reducing isoprene emissions by 15%. Overall, these factors combined to cause a 24% decrease in global isoprene emissions during the 20th century. It remains to be determined whether predicted 21st century warming and increased use of isoprene‐emitting crops for biofuels (e.g., oil palm) will more than offset any future CO2 suppression of isoprene emission rates.
Counts of Northern Elephant Seals at Rookeries in the Southern California Bight, 1981-2001

Northern elephant seals (Mirounga angustirostris) at five islands in the Southern California Bight (SCB) were counted during 1981-2001 to monitor status and trends of the population. Counts, stratified by areas within each island, were made during winter breeding season at Santa Barbara Island (1984-2001), San Miguel Island (1985-2001), San Nicolas Island (1988-2001), and Santa Rosa Island (1990-2001) and year-round at San Clemente Island (19812001). At Santa Barbara Island the number of births declined at an average annual rate of -4.8 percent from 1984-2001 (R = 0.20, slope = -0.05, P = 0.08). At San Clemente Island the number of births increased at an average annual rate of 13.4 percent from 1982-2001 (R = 0.506, slope = 0.126, P < 0.001). At San Miguel Island the number of births increased at an average annual rate of 5.1 percent from 1985-1994 (R = 0.981, slope = 0.050, P < 0.001) , but declined at -1.9 percent from 1994-2001 (R = 0.541, slope = -0.019, P = 0.096). At San Nicolas Island the number of births increased at an average annual rate of 7.3 percent from 1988-2001 (R = 0.887, slope = 0.070, P < 0.001). At Santa Rosa Island the number of births increased at an average annual rate of 41.8 percent from 1990-2001 (R = 0.928, slope = 0.349, P < 0.001). Births of northern elephant seals in the SCB increased during 1981-2001. Declines in births which occurred in 1986-87 and 1995-98 were probably due to delayed effects of low pup survival during the 1983 and 1992 El Niño’s which resulted in fewer adult females being recruited into the adult population.
A synchronous rail-to-rail latched comparator based on double-gate organic thin-film-transistors

This paper presents a latched comparator designed in a double-gate p-type-only organic thin film transistors (OTFTs) technology. The circuit is tailored to take the maximum advantage of the features of the double-gate technology, which allows an input capacitance of only ~35fF. The measured single stage-latch reaches rail-to-rail logic levels with less than 100mV differential input signal and about 10V input common mode range for VDD=20V. The DC small-signal gain is larger than 46dB and the static power dissipation is ~30nW. All measurements were taken in air and in daylight.
The complete nucleotide sequence of the Escherichia coli gene appA reveals significant homology between pH 2.5 acid phosphatase and glucose-1-phosphatase

The whole nucleotide sequence of Escherichia coli gene appA, which encodes periplasmic phosphoanhydride phosphohydrolase (optimum pH, 2.5), and its flanking regions was determined. The AppA protein is significantly homologous to the product of the nearby gene agp, acid glucose-1-phosphatase. Because identical amino acids are distributed over the whole lengths of the proteins, it is likely that appA and agp originate from the same ancestor gene.
Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy controls female participants (HC) and decomposed using spatial group independent component analyses (ICA). Using validated templates, we identified components covering the fronto-parietal “control” network, the default mode network (DMN), the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks (RSN). The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self- and body-focused ruminations when AN patients are at rest.
Q2C@UST: our winning solution to query classification in KDDCUP 2005

In this paper, we describe our ensemble-search based approach, Q2C@UST (http://webprojectl.cs.ust.hk/q2c/), for the query classification task for the KDDCUP 2005. There are two aspects to the key difficulties of this problem: one is that the meaning of the queries and the semantics of the predefined categories are hard to determine. The other is that there are no training data for this classification problem. We apply a two-phase framework to tackle the above difficulties. Phase I corresponds to the training phase of machine learning research and phase II corresponds to testing phase. In phase I, two kinds of classifiers are developed as the base classifiers. One is synonym-based and the other is statistics based. Phase II consists of two stages. In the first stage, the queries are enriched such that for each query, its related Web pages together with their category information are collected through the use of search engines. In the second stage, the enriched queries are classified through the base classifiers trained in phase I. Based on the classification results obtained by the base classifiers, two ensemble classifiers based on two different strategies are proposed. The experimental results on the validation dataset help confirm our conjectures on the performance of the Q2C@UST system. In addition, the evaluation results given by the KDDCUP 2005 organizer confirm the effectiveness of our proposed approaches. The best F1 value of our two solutions is 9.6% higher than the best of all other participants' solutions. The average F1 value of our two submitted solutions is 94.4% higher than the average F1 value from all other submitted solutions.