Miracle-dz/UniFAR-FTUs huggingface dataset:
Narratives in Crowdsourced Evaluation of Visualizations: A Double-Edged Sword?

We explore the effects of providing task context when evaluating visualization tools using crowdsourcing. We gave crowdsource workers i) abstract information visualization tasks without any context, ii) tasks where we added semantics to the dataset, and iii) tasks with two types of backstory narratives: an analytic narrative and a decision-making narrative. Contrary to our expectations, we did not find evidence that adding data semantics increases accuracy, and further found that our backstory narratives can even decrease accuracy. Adding dataset semantics can however increase attention and provide subjective benefits in terms of confidence, perceived easiness, task enjoyability and perceived usefulness of the visualization. Nevertheless, our backstory narratives did not appear to provide additional subjective benefits. These preliminary findings suggest that narratives may have complex and unanticipated effects, calling for more studies in this area.
Some applications of noncommutative groups and semigroups to information security

Some applications of noncommutative groups and semigroups to information security by Lisa Bromberg Adviser: Professor Vladimir Shpilrain We present evidence why the Burnside groups of exponent 3 could be a good candidate for a platform group for the HKKS semidirect product key exchange protocol. We also explore hashing with matrices over SL2(Fp), and compute bounds on the girth of the Cayley graph of the subgroup of SL2(Fp) for specific generators A,B. We demonstrate that even without optimization, these hashes have comparable performance to hashes in the SHA family.
Dream Content in Complicated Grief: A Window into Loss-Related Cognitive Schemas

Bereavement and its accompanying psychological response (grief) constitute potent experiences that necessitate the reorganization of cognitive-affective representations of lost significant attachment figures during both wakefulness and dreaming. The goals of this preliminary study were to explore whether the dream content of 77 adults with complicated grief (CG) differed from that of a normative sample and whether CG patients who dream of the deceased differ from CG patients who do not dream of the deceased on measures of daytime emotional distress. CG dreams were characterized by more family and familiar characters including the deceased (in women), and fewer social interactions and emotions compared to norms. Increased representations of familiar characters in CG dreams may reflect attempts to reorganize relational cognitive schemas to compensate for the loss.
Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers

The incorporation of increasing core counts in modern processors used to build state-of-the-art supercomputers is driving application development towards exploitation of thread parallelism, in addition to distributed memory parallelism, with the goal of delivering efficient high-performance codes. In this work we describe the exploitation of threading and our experiences with it with respect to a real-world ocean modeling application code, MPAS-Ocean. We present detailed performance analysis and comparisons of various approaches and configurations for threading on the Cray XC series supercomputers.
Determination of Total Protein Content of Bacterial Cells by SYPRO Staining and Flow Cytometry

ABSTRACT An assay has been developed for measuring protein biomass of marine planktonic bacteria by flow cytometry. The method was calibrated by using five species of Bacteria (an Arcobactersp., a Cytophaga sp., an Oceanospirillum sp., aPseudoalteromonas sp., and a Vibrio sp.) recently isolated from seawater samples and grown in culture at different temperatures. The intensity of SYPRO-protein fluorescence of these bacteria strongly correlated with their total protein content, measured by the bicinchoninic acid method to be in the range of 60 to 330 fg of protein cell−1(r2 = 0.93, n = 34). According to the calibration, the mean biomass of planktonic bacteria from the North Sea in August 1998 was 24 fg of protein cell−1.
Summary and Recommendations of the Third International Workshop-Conference on Gestational Diabetes Mellitus

The Third International Workshop-Conference on Gestational Diabetes Mellitus (GDM) was convened in Chicago, Illinois, on 8 November 1990 as an invitational meeting sponsored by the American Diabetes Association with the cooperation of the American College of Obstetricians and Gynecologists, the American Academy of Pediatrics, the National Diabetes Advisory Board, the Centers for Disease Control, and the Diabetic Pregnancy Study Group of the European Association for the Study of Diabetes. The meeting provided a forum for the review of new information concerning GDM in the areas of diagnosis and prevalence, perinatal and long-range implications, and management strategies.
OCCURRENCE OF SYNANTHROPIC FLIES IN TASEK BERA RAMSAR SITE ,

A study of the occurrence and species distribution of synanthropic flies species at Tasek Bera Ramsar Site was carried out during the Biodiversity Inventory Program from 10 to 12 May 2014 and 14 to 16 August 2014. A total of 716 synanthropic flies were collected and grouped according to their morphological characteristics. Molecular identification with partial mitochondrial cytochrome oxidase I (COI) gene sequences confirmed the identity of the flies, namely Chrysomya megacephala, Chrysomya rufifacies, Hemipyrellia ligurriens, Hypopygiopsis infumata, Lucilia cuprina, Atherigona orientalis, and Sarcophaga dux and one unidentified fly. These flies belong to three main families of synanthropic flies (Sarcophagidae, Calliphoridae and Muscidae) and they are important in forensic studies and veterinary entomology. The most abundant family was Calliphoridae (73.2%), followed by Muscidae (21.1%) and Sarcophagidae (5.7%). The highest number of species and individuals captured came from the family Calliphoridae with Chrysomya megacephala as the most prevalent species at 52.7 %.
Crystal structure of neurotoxin Ts1 from Tityus serrulatus provides insights into the specificity and toxicity of scorpion toxins.

The crystal structure of neurotoxin Ts1, a major component of the venom of the Brazilian scorpion Tityus serrulatus, has been determined at 1.7 A resolution. It is the first X-ray structure of a highly toxic anti-mammalian beta-toxin. The folding of the polypeptide chain of Ts1 is similar to that of other scorpion toxins. A cysteine-stabilised alpha-helix/beta-sheet motif forms the core of the flattened molecule. All residues identified as functionally important by chemical modification and site-directed mutagenesis are located on one side of the molecule, which is therefore considered as the Na+channel recognition site. The distribution of charged and non-polar residues over this surface determines the specificity of the toxin-channel interaction. Comparison to other scorpion toxins shows that positively charged groups at positions 1 and 12 as well as a negative charge at position 2 are likely determinants of the specificity of beta-toxins. In contrast, the contribution of the conserved aromatic cluster to the interaction might be relatively small. Comparison of Ts1 to weak beta-toxins from Centruroides sculpturatus Ewing reveals that a number of basic amino acid residues located on the face of the molecule opposite to the binding surface may account for the high toxicity of Ts1.
Fixed Term Contracts as Sorting Mechanisms: Evidence from Job Durations in West Germany

We estimate the effect of initial episodes under fixed term contracts (FTCs) on job duration in the further course of the employment spell, using data from the German Socio-Economic Panel (SOEP) from 1985 to 2002. Using a statistical matching approach, we find that job exit rates are initially much higher if the employment spell began with an FTC. However, exit rates fall below those of comparable spells spent entirely in permanent employment after a few years time. This suggests that FTCs accelerate a sorting process and that they may at least to some part be understood as prolonged probationary periods. Strikingly, the probability of long-term employment of more than five years duration is not lower in spells that are initially concluded as FTCs. Hence, the sorting processes taking place in both forms of contracts seem to be of similar intensity.
Palmprint identification system using shape matching and K-Nearest neighbor algorithm

This paper presents a palmprint identification system based on principle lines. The system is divided into two main subsystems. The first part concerns with palmprint feature extraction using a cascade of consecutive filters to obtain the principle lines. To achieve our proposed system, recognition is provided as the second part to classify principle line image. Firstly, shape histogram is constructed from the extracted image by projections along vertical and horizontal axes. Then, the histogram of query image and the image in database are compared by using cosine similarity measure. Finally, K-Nearest Neighbor is employed to identify a person. The experimental results demonstrate the efficient system yielding high recognition accuracy.
Managing dyspraxia: Pre-school teachers’ perceptions, experiences and strategies

Dyspraxia is a childhood developmental disorder that manifests as a difficulty in thinking, planning, and executing planned movements or tasks. Dyspraxia affects approximately 5–6% of school-aged children. This study aimed to explore pre-school teachers’ awareness and understanding of dyspraxia, and the support they desire for teaching children with dyspraxia. Informants were 15 pre-school teachers from the Cape Peninsula, South Africa (black = 1; coloured/mixed race = 13; white = 1). The teachers completed semi-structured interviews regarding their awareness and knowledge of dyspraxia and the support they require to better facilitate the learners’ development. A thematic analysis of the data suggested that the teachers were aware of the behavioural and cognitive difficulties associated with dyspraxia and that they need to seek professional development to enhance their management of children with dyspraxia. Early intervention strategies, in partnership with the parent carers of the children, appear to hold good prospects for the successful management of dyspraxia among school-aged children.
How slowing senescence changes life expectancy

Mortality decline has historically been a result of reductions in the level of mortality at all ages. The slope of mortality increase with age has been remarkably stable. A number of leading researchers on aging, however, suggest that the next revolution of longevity increase will be the result of slowing down the rate of aging, lessening the rate at which mortality increases as we get older. In this paper, we show mathematically how varying the pace of senescence influences life expectancy. We provide a formula that holds for any baseline hazard function. Our result is analogous to Keyfitz's "entropy" relationship for changing the level of mortality. Interestingly, the influence of the shape of the baseline schedule on the effect of senescence changes is the complement of that found for level changes. We also provide a generalized formulation that mixes level and slope effects.
Two linked genes for outer membrane proteins are absent in four non‐disease strains of Haemophilus somnus

Linked genes encoding two outer membrane proteins (p76 and a family of proteins, p120) of the bovine pathogen, Haemophilus somnus, were investigated. The p120 group was previously shown to have immunoglobulin‐binding activity and to react with polyclonal antiserum specific for a 270 kDa antigen (p270) which also had immunoglobulin Fc‐binding activity. By Western blotting we showed that the p76 antigen also reacted with this antiserum. The p270, p120, and p76 antigens were undetectable in four serum‐sensitive isolates from asymptomatic carriers but were present in the two serum‐resistant virulent strains tested. Genes for p120 and p76 were subcloned on non‐overlapping pUC plasmids from a cosmid (pHS1) originally cloned from a serum‐resistant strain. In Escheriehia coli, plasmid pHS138 expressed p76, while the p120 antigens were produced by pHS140. Southern blots of DNA from the above six strains of H. somnus using probes derived from pHS1 subclones showed that a 13.4kb sequence was missing from the four serum‐sensitive strains, but not the two serum‐resistant strains. This segment included most of the insert in pHS138 and all of the pHS140 insert. The data indicate that p76 and the p120 proteins are absent from serum‐sensitive strains because the coding sequences are missing, raising the possibility of insertion of these genes into the chromosome of both serum‐resistant strains, or deletion from the four serum‐sensitive strains.
Generic Axiomatization of Families of Noncrossing Graphs in Dependency Parsing

We present a simple encoding for unlabeled noncrossing graphs and show how its latent counterpart helps us to represent several families of directed and undirected graphs used in syntactic and semantic parsing of natural language as context-free languages. The families are separated purely on the basis of forbidden patterns in latent encoding, eliminating the need to differentiate the families of non-crossing graphs in inference algorithms: one algorithm works for all when the search space can be controlled in parser input.
Content‐Based Ultrasound Image Retrieval Using a Coarse to Fine Approach

Abstract: One of the current issues for picture archiving and communication systems (PACS) is extending retrieval technologies to deal with multimedia information. This is particularly important for medical applications that assist in diagnostic processes and pathology studies. Accordingly, this paper presents a new approach to content‐based image retrieval (CBIR) for a clinical ultrasound image database (DB). The proposed algorithm consists of two stages so as to maximize the retrieval efficiency. In the first stage, a coarse retrieval is performed using the statistical characteristics of the wavelet coefficients that narrow the search by eliminating up to 70% of the total DB images. In the second stage, a fine retrieval is carried out using the Legendre moment of the global histogram pdf on the reduced image set preretrieved by the coarse retrieval. When tested on an abdominal ultrasound image DB and compared with various other methods, the proposed algorithm gave promising results for applying CBIR to clinical ultrasound images.
Printed Write Once and Read Many Sensor Memories in Smart Packaging Applications

A horizontal printed Write-Once-Read-Many (WORM) resistive memory has been developed for use in wireless sensor tags targeting single-event detection in smart packaging applications. The WORM memory can be programmed using a 1.5-V printed battery. An alternative programming method is to use chemical sintering which allows the development of exposure-time triggered single event tags that can be accessed wirelessly. The new WORM memory has very low losses in the ON-state which allows direct integration into antenna structures. A sensor tag that utilizes the WORM memory functionality and the well established Electronic Article Surveillance (EAS) communication standard has been outlined. Both active and fully passive sensor tag solutions have been proposed. The role of printed electronics in smart packaging applications has been reviewed and discussed. Important enabling factors for the future development have been highlighted, such as the need for hierarchical design and test tools, better printed interconnect technologies as well as better components that allow communication with existing information and communication technology (ICT) standards. This is illustrated and underlined by the presented smart packaging concept demonstrators.
Transfer learning of shared latent spaces between robots with similar kinematic structure

Learning complex manipulation tasks often requires to collect a large training dataset to obtain a model of a specific skill. This process may become laborious when dealing with high-DoF robots, and even more tiresome if the skill needs to be learned by multiple robots. In this paper, we investigate how this learning process can be accelerated by using shared latent variable models for knowledge transfer among similar robots in an imitation setting. For this purpose, we take advantage of a shared Gaussian process latent variable model to learn a common latent representation of robot skills. Such representation is then reused as prior information to train new robots by reducing the learning process to a latent-to-output mapping. We show that our framework exhibits faster training convergence and similar performance when compared to single- and multi-robot models. All experiments were conducted in simulation on three different robotic platforms: WALK-MAN, COMAN and CENTAURO robots.
Rapid and sensitive detection of messenger RNA expression for molecular differential diagnosis of renal cell carcinoma.

PURPOSE The aim of this study was to develop a practical technique to detect mRNA expression and to validate a panel of mRNA markers for molecular differential diagnosis of renal cell carcinoma (RCC). EXPERIMENTAL DESIGN The renal cancer cell line SKRC-52 was used to set up the technique, which consisted of column extraction of RNA and one-step reverse transcription-PCR. We validated a panel of gene markers, including MN/CA9, cadherin-6, vimentin, mucin1, and parvalbumin, and studied 50 renal tumors (30 conventional, 9 papillary, and 5 chromophobe RCCs and 6 oncocytomas), 10 normal tissues, and 10 normal blood samples. We mimicked fine needle aspiration (FNA) biopsy in 10 kidneys with conventional RCC and applied this technique to 10 preoperative FNA samples from imaging-indeterminate renal tumors. RESULTS The technique could detect as few as 10 SKRC-52 cells with MN/CA9 as mRNA marker and was less time consuming and labor intensive. MN/CA9 was a sensitive and rather specific gene marker for conventional RCC. Cadherin-6 gene expression was a sensitive marker for conventional and papillary RCC. Vimentin was highly specific for conventional RCC. Mucin1 mRNA was sensitive for papillary and chromophobe RCC and oncocytoma. Parvalbumin mRNA was a sensitive and highly specific marker for both chromophobe RCC and oncocytoma. Thus, these mRNA markers represent the biomarker genes for the subtypes of renal tumors. Finally, we successfully applied the technique to FNA specimens. Five preoperative FNA samples were MN/CA9 gene positive, suggesting a RCC, whereas the routine cytology was positive in only three cases. CONCLUSIONS A rapid and sensitive assay of mRNA markers was developed for molecular differential diagnosis of RCC. This molecular assay can be used as a powerful ancillary to surgical pathological diagnosis and cytological diagnosis of RCC.
Spectral Subtraction Based on Non-extensive Statistics for Speech Recognition

Spectral subtraction (SS) is an additive noise removal method which is derived in an extensive framework. In spectral subtraction, it is assumed that speech and noise spectra follow Gaussian distributions and are independent with each other. Hence, noisy speech also follows a Gaussian distribution. Spectral subtraction formula is obtained by maximizing the likelihood of noisy speech distribution with respect to its variance. However, it is well known that noisy speech observed in real situations often follows a heavy-tailed distribution, not a Gaussian distribution. In this paper, we introduce a q-Gaussian distribution in the non-extensive statistics to represent the distribution of noisy speech and derive a new spectral subtraction method based on it. We found that the q-Gaussian distribution fits the noisy speech distribution better than the Gaussian distribution does. Our speech recognition experiments using the Aurora-2 database showed that the proposed method, q-spectral subtraction (q-SS), outperformed the conventional SS method. key words: robust speech recognition, spectral subtraction, Gaussian distribution, q-Gaussian, maximum likelihood
Correction to the article “Dynamics and assembly of the cytolethal distending toxin”

The cytolethal distending toxin (CDT) is a widespread bacterial toxin that consists of an active subunit CdtB with nuclease activity and two ricin-like lectin domains, CdtA and CdtC, that are involved in the delivery of CdtB into the host cell. The three subunits form a tripartite complex that is required to achieve the fully active holotoxin. In the present study we investigate the assembly and dynamic properties of the CDT holotoxin using molecular dynamics simulations and binding free energy calculations. The results have revealed that CdtB likely adopts a different conformation in the unbound state with a closed DNA binding site. The two characterized structural elements of the aromatic patch and groove on the CdtA and CdtC protein surfaces exhibit high mobility, and free energy calculations show that the heterodimeric complex CdtA-CdtC, as well as the CdtA-CdtB and CdtB-CdtC sub-complexes are less energetically stable as compared to the binding in the tripartite complex. Analysis of the dynamical cross-correlation map reveals information on the correlated motions and long-range interplay among the CDT subunits associated with complex formation. Finally, the estimated binding free energies of subunit interactions are presented, together with the free energy decomposition to determine the contributions of residues for both binding partners, providing insight into the protein-protein interactions in the CDT holotoxin.
Computer methods for the assessment of toxicity.

The prediction of the biological activity of chemical compounds by means of mathematical models is discussed. Biological activity of chemicals, including their toxicity on man and other biological organisms and systems, involves too complex phenomena to presently be predictable by fundamental models such as ab initio quantum mechanical models or statistical mechanical models. Hence one takes recourse to semi-empirical and empirical models which relate the variation in chemical structure of chemical compounds to the variation in their measured biological activity, e.g. toxicity in one or several test systems. These models are "calibrated" on series of similar compounds with "known" toxicity, the training set. Thereafter the models can--in fortunate cases--be used to predict the toxicity of compounds which are structurally similar to the training set compounds. The formulation and applicability of semi-empirical and empirical models relating chemical structure to biological activity is discussed. Causes and remedies for commonly encountered fallacies are presented.
Robust recovery for radar applications by noise mitigated compressed sensing

Compressed sensing (CS) is an exciting, rapidly growing field that has attracted considerable attention in signal processing, statistics, and computer science. Especially, for radar applications it plays a major role for facilitating the signal processing and information recovery, since the information of interest in radar applications has usually its compressible or even sparse structure. In practice, however, a robust recovery in CS is a difficult task, which is strongly depending on the information of sparsity level and noise energy, something that we cannot know in advance and must be estimated or additionally provided. It would become worse if the related CS problem is ill-conditioned. In this paper, we will present our proposed noise mitigated compressed sensing (NMCS), which gives a promising framework for a robust CS recovery without specifying the signal sparsity or noise level.