Miracle-dz/UniFAR-FTUs huggingface dataset:
Interocular masking and summation indicate two stages of divisive contrast gain control

Our understanding of early spatial vision owes much to contrast masking and summation paradigms. In particular, the deep region of facilitation at low mask contrasts is thought to indicate a rapidly accelerating contrast transducer (eg a square-law or greater). In experiment 1, we tapped an early stage of this process by measuring monocular and binocular thresholds for patches of 1 cycle deg-1 sine-wave grating. Threshold ratios were around 1.7, implying a nearly linear transducer with an exponent around 1.3. With this form of transducer, two previous models (Legge, 1984 Vision Research 24 385 - 394; Meese et al, 2004 Perception 33 Supplement, 41) failed to fit the monocular, binocular, and dichoptic masking functions measured in experiment 2. However, a new model with two-stages of divisive gain control fits the data very well. Stage 1 incorporates nearly linear monocular transducers (to account for the high level of binocular summation and slight dichoptic facilitation), and monocular and interocular suppression (to fit the profound 42 Oral presentations: Spatial vision Thursday dichoptic masking). Stage 2 incorporates steeply accelerating transduction (to fit the deep regions of monocular and binocular facilitation), and binocular summation and suppression (to fit the monocular and binocular masking). With all model parameters fixed from the discrimination thresholds, we examined the slopes of the psychometric functions. The monocular and binocular slopes were steep (Weibull s˜3-4) at very low mask contrasts and shallow (s˜1.2) at all higher contrasts, as predicted by all three models. The dichoptic slopes were steep (s˜3-4) at very low contrasts, and very steep (s>5.5) at high contrasts (confirming Meese et al, loco cit.). A crucial new result was that intermediate dichoptic mask contrasts produced shallow slopes (s˜2). Only the two-stage model predicted the observed pattern of slope variation, so providing good empirical support for a two-stage process of binocular contrast transduction. [Supported by EPSRC GR/S74515/01]
Adenovirus-associated virus vector-mediated gene transfer in hemophilia B.

BACKGROUND Hemophilia B, an X-linked disorder, is ideally suited for gene therapy. We investigated the use of a new gene therapy in patients with the disorder. METHODS We infused a single dose of a serotype-8-pseudotyped, self-complementary adenovirus-associated virus (AAV) vector expressing a codon-optimized human factor IX (FIX) transgene (scAAV2/8-LP1-hFIXco) in a peripheral vein in six patients with severe hemophilia B (FIX activity, <1% of normal values). Study participants were enrolled sequentially in one of three cohorts (given a high, intermediate, or low dose of vector), with two participants in each group. Vector was administered without immunosuppressive therapy, and participants were followed for 6 to 16 months. RESULTS AAV-mediated expression of FIX at 2 to 11% of normal levels was observed in all participants. Four of the six discontinued FIX prophylaxis and remained free of spontaneous hemorrhage; in the other two, the interval between prophylactic injections was increased. Of the two participants who received the high dose of vector, one had a transient, asymptomatic elevation of serum aminotransferase levels, which was associated with the detection of AAV8-capsid-specific T cells in the peripheral blood; the other had a slight increase in liver-enzyme levels, the cause of which was less clear. Each of these two participants received a short course of glucocorticoid therapy, which rapidly normalized aminotransferase levels and maintained FIX levels in the range of 3 to 11% of normal values. CONCLUSIONS Peripheral-vein infusion of scAAV2/8-LP1-hFIXco resulted in FIX transgene expression at levels sufficient to improve the bleeding phenotype, with few side effects. Although immune-mediated clearance of AAV-transduced hepatocytes remains a concern, this process may be controlled with a short course of glucocorticoids without loss of transgene expression. (Funded by the Medical Research Council and others; ClinicalTrials.gov number, NCT00979238.).
High-Throughput Logic Timing Simulation on GPGPUs

Many EDA tasks such as test set characterization or the precise estimation of power consumption, power droop and temperature development, require a very large number of time-aware gate-level logic simulations. Until now, such characterizations have been feasible only for rather small designs or with reduced precision due to the high computational demands. The new simulation system presented here is able to accelerate such tasks by more than two orders of magnitude and provides for the first time fast and comprehensive timing simulations for industrial-sized designs. Hazards, pulse-filtering, and pin-to-pin delay are supported for the first time in a GPGPU accelerated simulator, and the system can easily be extended to even more realistic delay models and further applications. A sophisticated mapping with efficient memory utilization and access patterns as well as minimal synchronizations and control flow divergence is able to use the full potential of GPGPU architectures. To provide such a mapping, we combine for the first time the versatility of event-based timing simulation and multi-dimensional parallelism used in GPU-based gate-level simulators. The result is a throughput-optimized timing simulation algorithm, which runs many simulation instances in parallel and at the same time fully exploits gate-parallelism within the circuit.
Minimal Enclosing Hyperbolas of Line Sets

We prove the following theorem: If H is a slim hyperbola that contains a closed set S of lines in the Euclidean plane, there exists exactly one hyperbola Hmin of minimal volume that contains S and is contained in H. The precise concepts of “slim”, the “volume of a hyperbola” and “straight lines or hyperbolas being contained in a hyperbola” are defined in the text.
Addressing Relationships among Moral Judgment Development, Narcissism, and Electronic Media and Communication Devices

Introduction Lawrence Kohlberg's Approach The Neo-Kohlbergian Approach of James Rest Assessing Moral Judgment Development Higher Education and Moral Judgment Development as Inferred via Scores on the DIT The Rise of Narcissism and Technology Use and their Behavioral Implications Moral Judgment Development in Relation to Narcissism and Technology Use Purpose of the Study Hypotheses
Automatic generation of model traversals from metamodel definitions

Developing software from models is a growing practice and there exist many model-based tools (e.g., model editors, model interpreters) for supporting model-driven engineering. Even though these tools facilitate the automation of software engineering tasks and activities, such tools are typically engineered manually. In this paper, a simple technique is described that enables automatic generation of model traversals. Semantic rules can be inserted into a traversal algorithm to provide meaning to the modeling language. The combination of automated traversal generation with attached semantic rules can generate a model interpreter that can translate a model into some other representation.
Form in darkness: Linking visual cortex structure with spontaneous neural function

Spontaneous neural activity within visual cortex is synchronized at varying spatial scales, from the cytoarchitecural level of individual neurons to the coarse scale of whole regions. The neural basis of this synchronicity remains ambiguous. In this thesis, we focus on the role visual experience plays in organizing the spontaneous activity within the visual system. We start in Chapter 2 by creating a means by which to analyze homologous patches of cortex between sighted and blind individuals, as lack of vision precludes the use of traditional stimulus-driven mapping techniques. We find that anatomy alone could indeed predict the retinotopic organization of an individual's striate cortex with an accuracy equivalent to the length of a typical mapping experiment. Chapter 3 applies this approach to analyze the organization of spontaneous signals within the striate cortex of blind and sighted subjects. We find that lack of visual experience produces a subtle change in the pattern of corticocortico correlations only between the hemispheres, and that these correlations are best modeled as function of cortical distance, not retinotopy. Chapter 4 expands our analysis to include areas V2 and V3. Here, we find that persistent visual experience supports network-level neural synchrony between spatially distributed cortical visual areas at both a coarse (regional) and fine (topographic) scale. Together, these results allow us model the organization of spontaneous activity in visual cortex as a combination of network signals linked to visual function and intrinsic signals coupled to structural connections. In the final chapter, we examine possible top-down mediators that may further modulate this network-level correlation. Minimal change in synchronicity is observed in a subject with a corpus callosotomy, suggesting the preeminence of bottom-up inputs. Taken together, this work advances our understanding of the origins of coherent spontaneous neural activity within visual cortex. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Neuroscience First Advisor Geoffrey K. Aguirre
The effect of shifting on wires and split ring resonators

Based on finite integration technique, the effect of shifting introduced in wires and split ring resonators on the pass band and resonant frequency of wires and split ring resonators is investigated. We similar pass bands and resonant frequency for two shifting structures of negative refractive index materials.The results show that there exists a shifting for resonant frequency and a narrowing in pass band deduced by the introduction of shifting wires and SRRs into materials.
Decision tree-based detection of denial of service and command injection attacks on robotic vehicles

Mobile cyber-physical systems, such as automobiles, drones and robotic vehicles, are gradually becoming attractive targets for cyber attacks. This is a challenge because intrusion detection systems built for conventional computer systems tend to be unsuitable. They can be too demanding for resource-restricted cyber-physical systems or too inaccurate due to the lack of real-world data on actual attack behaviours. Here, we focus on the security of a small remote-controlled robotic vehicle. Having observed that certain types of cyber attacks against it exhibit physical impact, we have developed an intrusion detection system that takes into account not only cyber input features, such as network traffic and disk data, but also physical input features, such as speed, physical jittering and power consumption. As the system is resource-restricted, we have opted for a decision tree-based approach for generating simple detection rules, which we evaluate against denial of service and command injection attacks. We observe that the addition of physical input features can markedly reduce the false positive rate and increase the overall accuracy of the detection.
PolyaPeak: Detecting Transcription Factor Binding Sites from ChIP-seq Using Peak Shape Information

ChIP-seq is a powerful technology for detecting genomic regions where a protein of interest interacts with DNA. ChIP-seq data for mapping transcription factor binding sites (TFBSs) have a characteristic pattern: around each binding site, sequence reads aligned to the forward and reverse strands of the reference genome form two separate peaks shifted away from each other, and the true binding site is located in between these two peaks. While it has been shown previously that the accuracy and resolution of binding site detection can be improved by modeling the pattern, efficient methods are unavailable to fully utilize that information in TFBS detection procedure. We present PolyaPeak, a new method to improve TFBS detection by incorporating the peak shape information. PolyaPeak describes peak shapes using a flexible Pólya model. The shapes are automatically learnt from the data using Minorization-Maximization (MM) algorithm, then integrated with the read count information via a hierarchical model to distinguish true binding sites from background noises. Extensive real data analyses show that PolyaPeak is capable of robustly improving TFBS detection compared with existing methods. An R package is freely available.
Pneumoencephalographic findings suggesting aneurysm of the vertebral-basilar junction. Differentiation of cases simulating mass lesions.

EURYSMS of t h e v e r t e b r a l b a s i l a r s y s t e m f r e q u e n t l y a p p e a r as mass lesions in t h e p o s t e r i o r fossa wi th no h i s t o ry of b l eed ing . 1,a-1~ P n e u m o e n c e p h a l o g r a p h y is g e n e r a l l y r e g a r d e d as t he d iagnos t i c p roced u r e of choice in pos t e r i o r fossa t u m o r suspec t s . I f a mass les ion of t he b r a i n s t em is f o u n d a n d inte133reted as a g l ioma, o p e r a t i o n o r r a d i a t i o n t h e r a p y m a y be u n d e r t a k e n w i t h o u t f u r t h e r r ad io log ic s tudies . T h e p u r p o s e of t h i s p a p e r is to p r e sen t t h e p n e u m o e n c e p h a l o g r a p h i c f indings in aneu r y s m s a b o u t t h e v e r t e b r a l b a s i l a r j u n c t i o n w h i c h c l in i ca l ly r e s e m b l e d mass lesions w i th o u t a h i s t o r y of s u b a r a c h n o i d hemor rhage . T h e s e f ind ings a p p e a r to be a l m o s t specific a n d , w h e n seen, i n d i c a t e the need for ve r t e b r a l a n g i o g r a p h y . Successful t r e a t m e n t of a p o s t e r i o r fossa a n e u r y s m was desc r ibed b y S c h w a r t z in 1948, s a n d there h a v e been nu m e r o u s s u b s e q u e n t repor t s . 2,~ T h e s e cases a n d s u b s e q u e n t t e c h n i c a l a d v a n c e s e m p h a s ize t h e need for m o r e def in i t ive d iagnosis .
Analyzing Dyadic Sequence Data—Research Questions and Implied Statistical Models

The analysis of observational data is often seen as a key approach to understanding dynamics in romantic relationships but also in dyadic systems in general. Statistical models for the analysis of dyadic observational data are not commonly known or applied. In this contribution, selected approaches to dyadic sequence data will be presented with a focus on models that can be applied when sample sizes are of medium size (N = 100 couples or less). Each of the statistical models is motivated by an underlying potential research question, the most important model results are presented and linked to the research question. The following research questions and models are compared with respect to their applicability using a hands on approach: (I) Is there an association between a particular behavior by one and the reaction by the other partner? (Pearson Correlation); (II) Does the behavior of one member trigger an immediate reaction by the other? (aggregated logit models; multi-level approach; basic Markov model); (III) Is there an underlying dyadic process, which might account for the observed behavior? (hidden Markov model); and (IV) Are there latent groups of dyads, which might account for observing different reaction patterns? (mixture Markov; optimal matching). Finally, recommendations for researchers to choose among the different models, issues of data handling, and advises to apply the statistical models in empirical research properly are given (e.g., in a new r-package “DySeq”).
Weakly Supervised Metric Learning towards Signer Adaptation for Sign Language Recognition

In this paper, we introduce metric learning into Sign Language Recognition(SLR) for the first time and propose a signer adaption framework to address signer-independent SLR. For adapting the general model to the new signer, both clustering and manifold constraints are considered in the adaptive distance metric optimization. The contribution of our work mainly lies in three-folds. Firstly, a Weakly Supervised Metric Learning(WSML) framework is proposed, which combines the clustering and manifold constraints simultaneously. Secondly, the general framework is applied to signer adaptation and achieves good performance. Thirdly, a fragment based feature is designed for sign language representation and the effectiveness is verified in large vocabulary datasets. Our proposed WSML framework can be decomposed into two key steps. The first one is to learn a generic metric from the given labeled data. Then the second step is to realize the distance metric adaptation by considering the clustering and manifold constraints with the unlabeled data. To learn a generic distance metric, the labeled data are used under clustering assumption with classical large margin hinge loss. Specifically, the distances between data points within the same cluster(with same label) should be minimized and the distances between data points from different clusters(with different labels) should be maximized. Here we define the index set with same labels as Sg = {(i, j)|yi = y j,xi,x j ∈ Xl} and the index triplet Bg = {(i, j,k)|yi = y j,yi 6= yk,xi,x j,xk ∈ Xl}. The objective function is
Map Assisted Pedestrian Orientation Detection by Smart Phone

Accurate indoor navigation system based on smart phones has been extensively studied and considered to be of good prospect for the reducing cost and increasing popular rate of smart phones. Dead reckoning method which measures steps and direction of each step is one of the most popular pedestrian positioning methods on the smart-phone platform, and its accuracy is mainly limited by the error of orientation detection. This paper presents a lightweight algorithm(MAPOD) that can measure pedestrian’s orientation in an accurate and real-time way by the following procedures: indentify certain locations such as corridor-corner in an indoor environment by signatures on multiple sensors to establish pedestrian’s initial orientation or correct orientation error, establish pedestrian’s temporary orientation when a change in smart phone’s mounting method is detected, calculate orientation by initial orientation and orientation sensor’s reading when no mounting change is detected. Results from three different mounting scenarios demonstrate 90% direction error of 5 °. MAPOD gains more accuracy with no significant increase in system energy consumption, is effective to improve the indoor positioning accuracy and availability in smart phones.
Sensory specificity and speciation: a potential neuronal pathway for host fruit odour discrimination in Rhagoletis pomonella

Behavioural changes in habitat or mate choice can trigger population divergence, leading to speciation. However, little is known about the neurological bases for such changes. Rhagoletis pomonella (Diptera: Tephritidae) is a model for ecological speciation via host plant shifts. Within the past 180 years, Rhagoletis flies infesting hawthorn (Crataegus spp.) shifted to attack domesticated apple (Malus pumila). The two populations differ in their olfactory preferences for apple versus hawthorn fruit. Here, we looked for patterns of sensory organization that may have contributed to this shift by characterizing the morphology, specificity and distribution of olfactory sensory neurons (OSNs) on the antennae of Rhagoletis responding to host fruit and non-host volatiles. Of 28 OSN classes identified, two colocalized OSN pairs were found that specifically responded to the major behavioural attractant and antagonist volatiles for each fly population. A reversal in the response of these OSNs to fruit volatiles, either through a switch in receptor expression between these paired neurons or changes in neuronal projections in the brain, could therefore account for the behavioural difference between apple and hawthorn flies. The finding supports the hypothesis that relatively minor changes in olfactory sensory pathways may contribute to rapid host shifting and divergence in Rhagoletis.
Influence of Different Light Intensities on the Content of Diosgenin, Lipids, Carotenoids and Fatty Acids in Leaves of Dioscorea zingiberensis

Cultivation of the climbing plant Dioscorea zingiberensis at a light intensity of 100 μE · m-2 · sec-1 yields three different phenotypes. Most of the plants grow as green phenotype (DzW). Two further forms differ in their leaf shape and leaf color. Whereas one type exhibits a more pointed leaf shape in the upper part of the plant with leaves appearing yellow-green with white stripes or hatchings (DzY), the other type shows a more round leaf shape with an intensive yellow-green color (DzT). These three plant types differ in their diosgenin content not only in their rhizomes but also in the chloroplasts. In the rhizomes the diosgenin content in the green form is 0.4%, in the DzY-form 0.6% and in the DzT-form even 1.3% of the dry weight. Furthermore, even in chloroplasts of the green DzW-form and of the DzY-form the presence of diosgenin was demonstrated. It occurs there as the epimeric form yamogenin. The DzT-form contains no yamogenin in its chloroplasts. Besides this, these plant forms differ in their chlorophyll and carotenoid content and in their fatty acid composition. Carotenoids increase from 1.3% of total lipids in the green phenotype to 3.3% in the DzYand to 4.2% in the DzT-form. This increase refers to _-carotene as well as to lutein and neoxanthin. The chlorophyll content in the green type is 8.1% and lower in the DzY-form with 7%. The highest chlorophyll content is found in the DzT-form with 12%. Fatty acids in the DzY-form and in the DzT-form have a more unsaturated character than in the green phenotype. The content of the monoenoic acid trans-hexadecenoic acid is considerably lower in both phenotypes when compared to the green phenotype. In both phenotypes the quantity of fatty acids with 16 carbon atoms is reduced, whereas fatty acids with 18 carbon atoms occur in higher concentration. Cultivation of the green phenotype (DzW) at the three light intensities of 10, 100 and 270 μE · m-2 · sec-1 leads to changes of the diosgenin content in rhizomes, to an increase of leaf dry weight, to a reduction of the grana structure in chloroplasts and therewith to a decrease of the chlorophyll content. The total lipid content is highest under the cultivation at 100 μE · m-2 · sec-1 and reduced by 30% at 10 and 270 μE · m-2 · sec-1. Carotenoids, however, are highest in shaded plants (10 μE · m-2 · sec-1) and plants grown under high light conditions of 270 μE · m-2 · sec-1. At 100 μE · m-2 · sec-1 a decrease of saturated fatty acids is observed in comparison to plants grown under shaded conditions.
Outage-Optimal Power Allocation for Space-Time Cooperative Network Coding with Amplify-and-Forward

To improve the resource utilization of traditional two-way wireless relay system, an optimal power allocation (OPA) algorithm for a space-time cooperative network coding scheme employing amplify-and-forward protocol (AF-ST-CNC) is proposed. The system performance in terms of outage probability and its approximation in high signal-to-noise (SNR) regimes are first derived, and by minimizing the larger outage probability of the two sources with respect to the characteristic of network coding, optimal power factors are obtained for some special cases are presented. The proposed algorithm only needs the average channel gain information and has low computation complexity, which facilitates the practical implementation. Simulation results show that the proposed AF-ST-CNC with OPA algorithm outperforms the AF-ST-CNC with equal power allocation (EPA) algorithm and the space-time cooperative network coding scheme employing amplify-and-forward protocol (DF-ST-CNC) with OPA algorithm in terms of outage performance.