Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel life history evolution in mouthbrooding cichlids from the African Great Lakes

The existence of ancient deep-water lakes provides an opportunity to study the independent adaptation of aquatic organisms to pelagic, benthic, and rocky shore habitats. With improving resolution of their phylogenetic relationships, the many cichlid fish species endemic to the African Great Lakes Malawi, Tanganyika, and Victoria provide a significant resource for the comparative study of such evolutionary processes. Here, we show that cichlid lineages colonizing rocky shores and pelagic habitats in the different lakes have independently evolved larger eggs and lower fecundities than benthic lineages, suggesting parallel adaptive life-history evolution. By contrast, other pelagic teleost fishes in both marine and freshwater habitats, including African lakes, typically produce large numbers of very small eggs. Our results also suggest that decreased fecundity and increased egg size not only occurred independently in each lake but occurred independently in the colonization of rocky and pelagic habitats.
A 0.18-$\mu$ m CMOS SoC for a 100-m-Range 10-Frame/s 200 $\,\times\,$96-Pixel Time-of-Flight Depth Sensor

With the emerging need for high-resolution light detection and ranging (LIDAR) technologies in advanced driver assistance systems (ADAS), we introduce a system-on-a-chip (SoC) that performs time-correlated single-photon counting and complete digital signal processing for a time-of-flight (TOF) sensor. At the core of the 0.18-μm CMOS SoC, we utilize linear arrays of 16 TOF and 32 intensity-only macro-pixels based on single-photon avalanche diodes in an original look-ahead concept, thus acquiring active TOF and passive intensity images simultaneously. The SoC also comprises an array of circuits capable of generating precise triggers upon spatiotemporal correlation events, an array of 64 12-b time-to-digital converters, and 768 kb of SRAM memory. The SoC provides the system-level electronics with a serial and low-bit-rate digital interface for: 1) multi-echo distance; 2) distance reliability; 3) intensity; and 4) passive-only intensity, thus mitigating system-level complexity and cost. A proof-of-concept prototype that achieves depth imaging up to 100 m with a resolution of 202 × 96 pixels at 10 frames/s has been implemented. Quantitative evaluation of the TOF sensor under strong solar background illuminance, i.e., 70 klux, revealed a repeatability error of 14.2 cm throughout the distance range of 100 m, thus leading to a relative precision of 0.14%. Under the same conditions, the relative nonlinearity error was 0.11%. In order to show the suitability of our approach for ADAS-related applications, experimental results in which the depth sensor was operated in typical traffic situations have also been reported.
Analysis of repeated measures data with clumping at zero

Longitudinal or repeated measures data with clumping at zero occur in many applications in biometrics, including health policy research, epidemiology, nutrition, and meteorology. These data exhibit correlation because they are measured on the same subject over time or because subjects may be considered repeated measures within a larger unit such as a family. They present special challenges because of the extreme non-normality of the distributions involved. A model for repeated measures data with clumping at zero, using a mixed-effects mixed-distribution model with correlated random effects, is presented. The model contains components to model the probability of a nonzero value and the mean of nonzero values, allowing for repeated measurements using random effects and allowing for correlation between the two components. Methods for describing the effect of predictor variables on the probability of nonzero values, on the mean of nonzero values, and on the overall mean amount are given. This interpretation also applies to the mixed-distribution model for cross-sectional data. The proposed methods are illustrated with analyses of effects of several covariates on medical expenditures in 1996 for subjects clustered within households using data from the Medical Expenditure Panel Survey.
Off-line (and on-line) text analysis for computational lexicography

Acknowledgements The research reported on in this thesis was based on work in two projects: the DFG-project Deutsches Referenzkorpus, a joint project of the Institut für Maschinelle Sprachverarbeitung (IMS) in Stuttgart, the Seminar für Sprach-wissenschaft (SfS) in Tübingen, and the Institut für deutsche Sprache (IDS) in Mannheim, and the DFG-Transferbereich project Automatische Exzerption which is intended to support the transfer of know-how from universities to companies (project partners are the Institut für Maschinelle Sprachverarbeitung (IMS) in Stuttgart, the Dudenredaktion in Mannheim and the Langenscheidt KG in München). I would like to thank all the members of the IMS for providing an excellent and friendly working environment. In particular I wish to thank my supervisors Christian Rohrer and Ulrich Heid for fruitful discussions, for their feedback and motivation, and for the fact that they were always willing to lend me an ear. I am grateful to Esther König, who was responsible for the DEREKO-project, for her permanent unofficial supervision. She encouraged me to go my own way without losing sight of the main issues. She was of great help discussing conceptual as well as technical issues, thus putting my research on a solid foundation. Special thanks go to Stefan Evert, my office-mate, who not only discussed work matters with me, but is also responsible for implementing, and modifying tools I used for my research. I could not have realized many of the ideas I had, had he not implemented new features, and thus opened up new possibilities. In addition, I want to thank Wolfgang Lezius for providing an import filter for TIGERSearch for my chunker. I also want to thank Stefanie Dipper, Sabine Schulte im Walde, Heike Zinsmeister, and Arne Fitschen for giving me insights into their work, Kristina Spranger for writing a Dutch version of the chunker and for giving remarks on the grammar, and Piklu Gupta for revising my English. Finally, I wish to thank my family and friends for the support, encouragement and distraction they provided me. And, last but not least, I want to thank Thomas for his support and for letting me forget about work.
Studies on the estimation of the hygienic condition of frozen broiler chickens

SUMMARY Various sampling techniques to determine the aerobic, E. coli and Entero-bacteriaceae counts and to detect the presence of salmonellas were compared. As a simple method for the detection of salmonellas a modified Surkeiwicz procedure using both drip and rinse water is advocated. To evaluate hygiene during processing, determination of the number of Enterobacteriaceae in pieces of skin from the ventral, lateral and breast region is preferred.
3-Sweep

We introduce an interactive technique for manipulating simple 3D shapes based on extracting them from a single photograph. Such extraction requires understanding of the components of the shape, their projections, and relations. These simple cognitive tasks for humans are particularly difficult for automatic algorithms. Thus, our approach combines the cognitive abilities of humans with the computational accuracy of the machine to solve this problem. Our technique provides the user the means to quickly create editable 3D parts---human assistance implicitly segments a complex object into its components, and positions them in space. In our interface, three strokes are used to generate a 3D component that snaps to the shape's outline in the photograph, where each stroke defines one dimension of the component. The computer reshapes the component to fit the image of the object in the photograph as well as to satisfy various inferred geometric constraints imposed by its global 3D structure. We show that with this intelligent interactive modeling tool, the daunting task of object extraction is made simple. Once the 3D object has been extracted, it can be quickly edited and placed back into photos or 3D scenes, permitting object-driven photo editing tasks which are impossible to perform in image-space. We show several examples and present a user study illustrating the usefulness of our technique.
Role of Linkers between Zinc Fingers in Spacing Recognition by Plant TFIIIA-Type Zinc-Finger Proteins

The EPF family of plant TFIIIA-type zinc-finger (ZF) proteins (ZPTs) is characterized by long linkers separating ZF motifs. We previously reported that two-fingered ZPTs bind to two tandem core sites that are separated by several base pairs, each ZF making contact with one core site. Here we report further characterization of DNA-binding activities of ZPTs using four family members, ZPT2-14, ZPT2-7, ZPT2-8, and ZPT2-2, having inter-ZF linkers of different lengths and sequences, to investigate the correlation of the length and/or sequence of the linker with preference for the spacing between core sites in target DNAs. Selected and amplified binding site (SAAB)-imprinting assays and gel mobility shift assays prompted three conclusions. (1) The four ZPTs have common specificity for core binding sites—two AGT(G)/(C)ACTs separated by several nucleotides. (2) The four ZPTs prefer a spacing of 10 bases between the core sites, but each ZPT has its own preference for suboptimal spacing. (3) At a particular spacing, two zinc fingers may bind to the core sites on both strands. The results provide new information about how the diversity in linker length/sequence affects DNA-sequence recognition in this protein family.
Transcriptomic Responses of the Heart and Brain to Anoxia in the Western Painted Turtle

Painted turtles are the most anoxia-tolerant tetrapods known, capable of surviving without oxygen for more than four months at 3°C and 30 hours at 20°C. To investigate the transcriptomic basis of this ability, we used RNA-seq to quantify mRNA expression in the painted turtle ventricle and telencephalon after 24 hours of anoxia at 19°C. Reads were obtained from 22,174 different genes, 13,236 of which were compared statistically between treatments for each tissue. Total tissue RNA contents decreased by 16% in telencephalon and 53% in ventricle. The telencephalon and ventricle showed ≥ 2x expression (increased expression) in 19 and 23 genes, respectively, while only four genes in ventricle showed ≤ 0.5x changes (decreased expression). When treatment effects were compared between anoxic and normoxic conditions in the two tissue types, 31 genes were increased (≥ 2x change) and 2 were decreased (≤ 0.5x change). Most of the effected genes were immediate early genes and transcription factors that regulate cellular growth and development; changes that would seem to promote transcriptional, translational, and metabolic arrest. No genes related to ion channels, synaptic transmission, cardiac contractility or excitation-contraction coupling changed. The generalized expression pattern in telencephalon and across tissues, but not in ventricle, correlated with the predicted metabolic cost of transcription, with the shortest genes and those with the fewest exons showing the largest increases in expression.
Face Recognition Based on Principle Component Analysis and Support Vector Machine

Face recognition is an important research field of pattern recognition.Up to now,it caused researchers great concern from these fields,such as pattern recognition,computer vision,and physiology,and so on.Various recognition algorithms have been proposed. Generally,we can make sure that the performance of face recognition system is determined by how to extract feature vector exactly and to classify them into a class accurately.Therefore,it is necessary for us to pay close attention to feature extractor and classifier.In this paper, in order to raise recognition rate,Principle Component Analysis (PCA) is used to extract image feature,and Support Vector Machine (SVM) is used to deal with face recognition problem. SVM has been recently proposed as a new classifier for pattern recognition.We take Principle Component Analysis & Support Vector Machine (PCA&SVM) to do experiments on the Cambridge ORL Face database,and compare this method with Principle Component Analysis & Nearest Neighbor (PCA&NN) and Support Vector Machine (SVM) on recognition rate and recognition time respectively.Finally,this experimental results show that recognition rate of this method,under small samples circumstance,is better than other two methods. It shows that,for face recognition,sending PCA features to SVM classifiers is feasible and correct.
Local Gaussian Processes for Efficient Fine-Grained Traffic Speed Prediction

Traffic speed is a key indicator for the efficiency of an urban transportation system. Accurate modeling of the spatiotemporally varying traffic speed thus plays a crucial role in urban planning and development. This paper addresses the problem of efficient fine-grained traffic speed prediction using big traffic data obtained from static sensors. Gaussian processes (GPs) have been previously used to model various traffic phenomena, including flow and speed. However, GPs do not scale with big traffic data due to their cubic time complexity. In this work, we address their efficiency issues by proposing local GPs to learn from and make predictions for correlated subsets of data. The main idea is to quickly group speed variables in both spatial and temporal dimensions into a finite number of clusters, so that future and unobserved traffic speed queries can be heuristically mapped to one of such clusters. A local GP corresponding to that cluster can then be trained on the fly to make predictions in real-time. We call this method localization. We use non-negative matrix factorization for localization and propose simple heuristics for cluster mapping. We additionally leverage on the expressiveness of GP kernel functions to model road network topology and incorporate side information. Extensive experiments using real-world traffic data collected in the two U.S. cities of Pittsburgh and Washington, D.C., show that our proposed local GPs significantly improve both runtime performances and prediction accuracies compared to the baseline global and local GPs.
Cardiac autonomic testing and diagnosing heart disease. “A clinical perspective”

Background Coronary heart disease (CHD) is a major health concern, affecting nearly half the middle-age population and responsible for nearly one-third of all deaths. Clinicians have responsibilities beyond diagnosing CHD, including risk stratification of patients for major adverse cardiac events (MACE), modifying the risks and treating the patient. In this first of a two-part review, identifying risk factors is reviewed, including more potential benefit from autonomic testing. Methods Traditional and non-traditional, and modifiable and non-modifiable risk factors for MACE where compared, including newer risk factors, such as inflammation, carotid intimal thickening, ankle-brachial index, CT calcium scoring, and autonomic function testing, specifically independent measurement of parasympathetic and sympathetic (P&S) activity. Results The Framingham Heart Study, and others, have identified traditional risk factors for the development of CHD. These factors effectively target high-risk patients, but a large number of individuals who will develop CHD and MACE are not identified. Many patients with CHD who appear to be well-managed by traditional therapies still experience MACE. In order to identify these patients, other possible risk factors have been explored. Advanced autonomic dysfunction, and its more severe form, cardiac autonomic neuropathy, have been strongly associated with an elevated risk of cardiac mortality and are diagnosable through P&S testing. Conclusions Independent measures of P&S activity, provides additional information and has the potential to incrementally add to risk assessment. This additional information enables physicians to (1) specifically target more high-risk patients and (2) titrate therapies, with autonomic testing guidance, in order to minimize risk of cardiac mortality and morbidity.
Crossover from high to low Reynolds number turbulence.

The Taylor-Reynolds and Reynolds number (Re lambda and Re) dependence of the dimensionless energy dissipation rate c epsilon = epsilon L / u31,rms is derived for statistically stationary isotropic turbulence, employing the results of a variable range mean field theory. Here epsilon is the energy dissipation rate, L the (fixed) outer length scale, and u1,rms a rms velocity component. Results for c epsilon (Re lambda ) and also for Re lambda (Re) are in good agreement with experiment. Using the Re dependence of c epsilon we account for the time dependence of the mean vorticity omega (t) for decaying isotropic turbulence. The lifetime of decaying turbulence, depending on the initial Re lambda ,0 is predicted to saturate at 0.18L2 / nu [is proportional to] Re2 lambda ,0 ( nu the viscosity) for large Re lambda ,0.
Phenomenological Model for Predicting the Catabolic Potential of an Arbitrary Nutrient

The ability of microbial species to consume compounds found in the environment to generate commercially-valuable products has long been exploited by humanity. The untapped, staggering diversity of microbial organisms offers a wealth of potential resources for tackling medical, environmental, and energy challenges. Understanding microbial metabolism will be crucial to many of these potential applications. Thermodynamically-feasible metabolic reconstructions can be used, under some conditions, to predict the growth rate of certain microbes using constraint-based methods. While these reconstructions are powerful, they are still cumbersome to build and, because of the complexity of metabolic networks, it is hard for researchers to gain from these reconstructions an understanding of why a certain nutrient yields a given growth rate for a given microbe. Here, we present a simple model of biomass production that accurately reproduces the predictions of thermodynamically-feasible metabolic reconstructions. Our model makes use of only: i) a nutrient's structure and function, ii) the presence of a small number of enzymes in the organism, and iii) the carbon flow in pathways that catabolize nutrients. When applied to test organisms, our model allows us to predict whether a nutrient can be a carbon source with an accuracy of about 90% with respect to in silico experiments. In addition, our model provides excellent predictions of whether a medium will produce more or less growth than another () and good predictions of the actual value of the in silico biomass production.
Applying Knowledge Discovery to Predict Water-Supply Consumption

Optimizing the control of operations in a municipal water distribution system can reduce electricity costs and realize other economic benefits. However, optimal control requires the ability to precisely predict short-term water demand so that minimum-cost pumping schedules can be prepared. One of the objectives of our project to develop an intelligent system for monitoring and controlling municipal water-supply systems is to ensure optimal control and reduce energy costs. Hence, prediction of water demand is essential. We present an application of a rough-set approach for the automated discovery of rules from a set of data samples for daily water-demand predictions. The database contains 306 training samples, covering information on seven environmental and sociological factors and their corresponding daily volume of distribution flow. The rough-set method generates prediction rules from the observed data, using statistical information that is inherent in the data to handle incomplete and ambiguous training samples. Experimental results indicate that this method provides more precise information than is available through knowledge acquisition from human experts.
Product Types and Supplier Roles in Product Development: An Exploratory Analysis

Manufacturers today often strive toward early supplier involvement in product development. Yet the research literature offers limited guidance on this issue to manufacturing companies and suppliers, and often assumes a "one-size-fits-all" approach. In this paper, we empirically examine whether suppliers for different sourced products play distinctly different roles in product development, by analyzing survey data on a wide range of sourced automotive products. We use cluster analysis to identify four different groupings of sourced products, based on differences along three dimensions: the nature of the sourced products, their cost structures, and the nature of the original equipment manufacturer (OEM)-supplier interaction in product development. We further test the usefulness of our scheme via a set of validating variables that include both key decisions and output performance measures in the OEM-supplier interaction process. We identify critical systems as highly differentiating, high cost, highly complex systems, for which OEMs provide information to their suppliers largely through performance specifications, and involve suppliers early in product development. In contrast, hidden components are less differentiating low-cost simple components that are defined primarily via physical specifications, whose suppliers are involved later in product development. Invisible subassemblies are nondifferentiating, moderately costly, moderately complex systems whose suppliers are provided information via a mix of performance specifications and detailed physical dimensions. Finally, simple differentiators are highly differentiating, moderately costly, simple assemblies or components. We discuss the implications of our study for managing differential supplier roles in product development.
Oxidative Stress by Tartrazine in the Testis of Wistar Rats

The aim is to study the effect of Tartrazine (E102) - synthetic food colour - on the antioxidant status of testis of Wistar rats. Twelve male Wistar rats were grouped into 2 groups of six each - Control and Tartrazine-treated groups. Control group was orally administered with water alone while the experimental group was orally administered with tartrazine dissolved in water. The treatment was carried out for 60 days and the activities of antioxidant enzymes - superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and glutathione reductase (GR) and the levels of their cofactors were subsequently determined in the testis, along with histological studies. Activities of the 4 enzymes showed a common decrease with corresponding alterations in their cofactor levels. The colour orally administered to the experimental animals probably would have generated reactive oxygen species (ROS) and H2O2, thereby disrupting the enzymatic antioxidant defense of their testes. Tartrazine is capable of producing free radicals, which in turn cause damage to the cellular compartment system of rat testis.