Miracle-dz/UniFAR-FTUs huggingface dataset:
End-Stopping Predicts Curvature Tuning along the Ventral Stream

Neurons in primate inferotemporal cortex (IT) are clustered into patches of shared image preferences. Functional imaging has shown that these patches are activated by natural categories (e.g., faces, body parts, and places), artificial categories (numerals, words) and geometric features (curvature and real-world size). These domains develop in the same cortical locations across monkeys and humans, which raises the possibility of common innate mechanisms. Although these commonalities could be high-level template-based categories, it is alternatively possible that the domain locations are constrained by low-level properties such as end-stopping, eccentricity, and the shape of the preferred images. To explore this, we looked for correlations among curvature preference, receptive field (RF) end-stopping, and RF eccentricity in the ventral stream. We recorded from sites in V1, V4, and posterior IT (PIT) from six monkeys using microelectrode arrays. Across all visual areas, we found a tendency for end-stopped sites to prefer curved over straight contours. Further, we found a progression in population curvature preferences along the visual hierarchy, where, on average, V1 sites preferred straight Gabors, V4 sites preferred curved stimuli, and many PIT sites showed a preference for curvature that was concave relative to fixation. Our results provide evidence that high-level functional domains may be mapped according to early rudimentary properties of the visual system. SIGNIFICANCE STATEMENT The macaque occipitotemporal cortex contains clusters of neurons with preferences for categories such as faces, body parts, and places. One common question is how these clusters (or “domains”) acquire their cortical position along the ventral stream. We and other investigators previously established an fMRI-level correlation among these category domains, retinotopy, and curvature preferences: for example, in inferotemporal cortex, face- and curvature-preferring domains show a central visual field bias whereas place- and rectilinear-preferring domains show a more peripheral visual field bias. Here, we have found an electrophysiological-level explanation for the correlation among domain preference, curvature, and retinotopy based on neuronal preference for short over long contours, also called end-stopping.
Carotid atherosclerosis is associated with inflammation, malnutrition and intercellular adhesion molecule-1 in patients on continuous ambulatory peritoneal dialysis.

BACKGROUND Recent evidence suggests that endothelial cell adhesion molecules may participate in the initiation and progression of atherosclerotic vascular damage. The aim of the present report was to investigate serum intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-selectin concentrations and their probable association with atherosclerotic disease in patients on continuous ambulatory peritoneal dialysis (CAPD). METHODS Sixty-three CAPD patients and 40 age- and sex-matched apparently healthy normotensive controls participated in the study. Atherosclerotic disease in both groups was assessed by measuring the intima-media thickness (IMT) and plaque score of the common carotid arteries using an ultrasound scanner. RESULTS Compared with controls, CAPD patients had significantly increased IMT and plaque score values (P<0.001 and P<0.0001, respectively), as well as serum ICAM-1, VCAM-1 and E-selectin concentrations (P<0.0001, P<0.0001 and P<0.05, respectively). In univariate analyses, IMT values were significantly correlated with age, systolic blood pressure (BP), logCRP, fibrinogen, albumin and ICAM-1 levels (P = 0.001, P = 0.04, P = 0.01, P = 0.04, P = 0.02 and P = 0.002, respectively). Multivariate analysis showed that ICAM-1 levels were a strong independent correlate of IMT (P = 0.005). Serum albumin also remained independently associated with IMT values (P = 0.03). Plaque score values were significantly correlated with age, systolic BP and fibrinogen (P = 0.002, P = 0.04 and P = 0.01, respectively). Multivariate analysis showed that fibrinogen concentrations were a significant independent contributor to plaque score values (P = 0.002). Adhesion molecule concentrations did not show any relation with plaque score either on univariate or multivariate analyses. CONCLUSIONS In CAPD patients, carotid atherosclerosis is associated with markers of inflammation, malnutrition and circulating levels of adhesion molecule ICAM-1. Hypoalbuminaemia and ICAM-1 appear independently related with atherogenesis but the mechanisms supporting these associations remain to be identified.
Assessment of the Damage Tolerance of Postbuckled Hat-Stiffened Panels using Single-Stringer Specimens

A procedure is proposed for the assessment of the damage tolerance and collapse of stiffened composite panels using a single-stringer compression specimen. The dimensions of the specimen are determined such that the specimen’s nonlinear response and collapse are representative of an equivalent multi-stringer panel in compression. Experimental tests are conducted on specimens with and without an embedded delamination. A shell-based finite element model with intralaminar and interlaminar damage capabilities is developed to predict the postbuckling response as well as the damage evolution from initiation to collapse.
Efficiency enhancement in small molecular organic photovoltaic devices employing dual anode interfacial layers

We demonstrated enhanced efficiency in small molecule organic photovoltaic devices using dual organic interfacial layers of PEDOT:PSS followed by tetracene between the ITO anode and the organic donor material. The use of a small molecular templating layer, such as tetracene, proved to increase the molecular stacking of the subsequent phthalocyanine (Pc) based donor materials. Upon application in planar heterojunction devices of ZnPc and C60, an enhancement of over 80 percent in the donor contribution to the external quantum efficiency was observed attributed to the combination of exciton blocking by the higher band gap tetracene layer and enhanced exciton diffusion and charge transport resulting from the increased crystallinity.
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

Convolutional neural networks (CNNs) work well on large datasets. But labelled data is hard to collect, and in some applications larger amounts of data are not available. The problem then is how to use CNNs with small data -- as CNNs overfit quickly. We present an efficient Bayesian CNN, offering better robustness to over-fitting on small data than traditional approaches. This is by placing a probability distribution over the CNN's kernels. We approximate our model's intractable posterior with Bernoulli variational distributions, requiring no additional model parameters. On the theoretical side, we cast dropout network training as approximate inference in Bayesian neural networks. This allows us to implement our model using existing tools in deep learning with no increase in time complexity, while highlighting a negative result in the field. We show a considerable improvement in classification accuracy compared to standard techniques and improve on published state-of-the-art results for CIFAR-10.
Self-Oscillating Switching Technique for Current Source Parallel Resonant Induction Heating Systems

This paper presents resonant inverter tuning for current source parallel resonant induction heating systems based on a new self oscillating switching technique. The phase error is suppressed in a wide range of operating frequencies in comparison with Phase Locked Loop (PLL) techniques. The proposed switching method has the capability of tuning under fast changes in the resonant frequency. According to this switching method, a multi-frequency induction heating (IH) system is proposed by using a single inverter. In comparison with multi-level inverter based IH systems, the advantages of this technique are its simple structure, better transients and wide range of operating frequencies. A laboratory prototype was built with an operating frequency of 35 kHz to 55 kHz and 300 W of output power. The performance of the IH system shows the validity of the new switching technique.
Historical Synthesis-Analysis of Changes in Grain Nitrogen Dynamics in Sorghum

Unraveling the complexity underpinning nitrogen (N) use efficiency (NUE) can be physiologically approached via examining grain N sources and N internal efficiency (NIE) (yield to plant N content ratio). The main objective of this original research paper is to document and understand sorghum NUE and physiological mechanisms related to grain N dynamics. The study of different grain N sources, herein defined as the reproductive-stage shoot N remobilization (Remobilized N), reproductive-stage whole-plant N content (Reproductive N), and vegetative-stage whole-plant N content (Vegetative N), was pursued with the goal of synthesizing scientific literature for sorghum [Sorghum bicolor (L.) Moench] crop. A detailed literature review was performed and summarized on sorghum NUE (13 studies; >250 means) with three Eras, defined by the year of the study, named as Old Era (1965–1980); Transient Era (1981–2000); and New Era (2001–2014). The most remarkable outcomes from this synthesis were: (1) overall historical (1965–2014) cumulative yield gain was >0.5 Mg ha-1 (yields >7 Mg ha-1); (2) NIE did not change across the same time period; (3) grain N concentration (grain %N) accounted for a large proportion (63%) of the variation in NIE; (4) NIE increased as grain %N diminished, regardless of the Eras; (5) Remobilized N was strongly (>R2 0.6) and positively associated with Vegetative N, presenting a unique slope across Eras; and (6) a trade-off was documented for the Remobilized N and Reproductive N (with large variation, <R2) relationship, suggesting complex regulation processes governing N forces. Improvements in NUE are subjected to the interplay between N supply (N from non-reproductive organs) and grain N demand, sink- (driven by grain number) and source-modulated (via restriction of grain N demand).
Genotyping North American Animal Mycobacterium Bovis Isolates Using Multilocus Variable Number Tandem Repeat Analysis

Multilocus variable number tandem repeat analysis (MLVA) has recently emerged as a genotyping method that is both robust and highly discriminatory for the differentiation of Mycobacterium tuberculosis complex (MTBC) strains, including Mycobacterium bovis. However, MLVA assessment of M. bovis isolates recovered from animals in North America has been limited. Using an epidemiologically diverse set of 41 North American M. bovis animal isolates, MLVA, based on 27 published variable number tandem repeat (VNTR) loci, was evaluated. Nineteen loci displayed polymorphism, which resulted in differentiation of 21 unique MLVA genotypes. A subset of 6 loci differentiated the isolates into 14 genetically related groups that displayed remarkable concordance with the epidemiological data gathered via traditional trace-back methods. In most cases, MLVA exhibited greater resolution than spoligotyping, which differentiated the isolates into 11 groups. MLVA genotyping of M. bovis shows great potential as a molecular typing tool for characterizing the epidemiology of M. bovis animal infections in North America. However, the greatest resolution was achieved by using a combination of both MLVA and spoligotyping.
Cancer‐specific survival and predictors of prostate‐specific antigen recurrence and survival in patients with seminal vesicle invasion after radical prostatectomy

The objectives of the current study were to determine the long‐term biochemical recurrence (BCR) and cancer‐specific survival (CSS) rates for men with seminal vesicle invasion (SVI) and to identify risk factors for freedom from BCR and CSS in patients who received treatment in the prostate‐specific antigen era and who had SVI identified at the time of radical prostatectomy (RP).
A Surface-Plasmon-Enhanced Silicon Solar Cell With KOH-Etched Pyramid Structure

A pyramid structure etched with KOH solution was employed on a silicon (Si) surface to increase the absorbing path length of light; subsequently, gold (Au) nanoparticles (NPs) were deposited on the etched surface. Solar cells with and without KOH etching or Au NPs are fabricated to study the effects of KOH etching and Au NPs on the characteristics of solar cells. Due to the larger surface area etched by KOH, more Au NPs adhere to the Si surface, and hence more surface plasmon oscillations are induced by the incident light. For the incident wavelength longer than the oscillation wavelength of Au NPs (550 nm), constructive interference occurs, which enhances the short-circuit current density and conversion efficiency. In contrast, for a wavelength smaller than 550 nm, absorption dominates the extinction spectra. The short-circuit current density and conversion efficiency of the solar cells with KOH etching and Au NPs increase by 26.8% and 28.5%, respectively, compared with that of the solar cells without KOH etching and without Au NPs.
The Snf1-related kinase, Hunk, is essential for mammary tumor metastasis

We previously identified a SNF1/AMPK-related protein kinase, Hunk, from a mammary tumor arising in an MMTV-neu transgenic mouse. The function of this kinase is unknown. Using targeted deletion in mice, we now demonstrate that Hunk is required for the metastasis of c-myc-induced mammary tumors, but is dispensable for normal development. Reconstitution experiments revealed that Hunk is sufficient to restore the metastatic potential of Hunk-deficient tumor cells, as well as defects in migration and invasion, and does so in a manner that requires its kinase activity. Consistent with a role for this kinase in the progression of human cancers, the human homologue of Hunk is overexpressed in aggressive subsets of carcinomas of the ovary, colon, and breast. In addition, a murine gene expression signature that distinguishes Hunk-wild type from Hunk-deficient mammary tumors predicts clinical outcome in women with breast cancer in a manner consistent with the pro-metastatic function of Hunk in mice. These findings identify a direct role for Hunk kinase activity in metastasis and establish an in vivo function for this kinase.
Segmental Recurrent Neural Networks for End-to-End Speech Recognition

We study the segmental recurrent neural network for end-to-end acoustic modelling. This model connects the segmental conditional random field (CRF) with a recurrent neural network (RNN) used for feature extraction. Compared to most previous CRF-based acoustic models, it does not rely on an external system to provide features or segmentation boundaries. Instead, this model marginalises out all the possible segmentations, and features are extracted from the RNN trained together with the segmental CRF. In essence, this model is self-contained and can be trained end-to-end. In this paper, we discuss practical training and decoding issues as well as the method to speed up the training in the context of speech recognition. We performed experiments on the TIMIT dataset. We achieved 17.3 phone error rate (PER) from the first-pass decoding --- the best reported result using CRFs, despite the fact that we only used a zeroth-order CRF and without using any language model.
Effect of processing conditions on shrinkage in injection molding

A systematic study on the effect of processing conditions on mold shrinkage was undertaken for seven common thermoplastic polymers. It turned out that the holding pressure was always the key parameter. The effect of the melt temperature is slightly less important. Injection velocity and mold temperature do not show a general trend for all polymers. It was shown that at least for amorphous polymers a simple thermoelastic model could describe all experimental results. For semi-crystalline materials the model overpredicts shrinkage.
Force decay evaluation of thermoplastic and thermoset elastomeric chains: A mechanical design comparison.

OBJECTIVES To compare the following over a period of 8 weeks: (1) force decay between thermoplastic (TP) and thermoset (TS) elastomeric chains; (2) force decay between light (200-g) and heavy (350-g) initial forces; and (3) force decay between direct chains and chain loops (stretched from one pin around the second pin and back to the first pin). MATERIALS AND METHODS TP and TS chains were obtained from American Orthodontics™ (AOTP, AOTS) and ORMCO™ (OrTP, OrTS). Each of the four chain groups was subdivided into four subgroups with 10 specimens per subgroup: (1) direct chains light force, (2) direct chains heavy force, (3) chain loops light force, and (4) chain loops heavy force. The experiment was performed in artificial saliva (pH of 6.75) at 37°C. RESULTS A significant difference was found between TP and TS chains, with an average mean difference of around 20% more force decay found in the TP chains (P < .001, α = .05). There was no significant difference between direct chains and chain loops except in OrTP, in which direct chains showed more force decay. There was also no significant difference in force decay identified when using light vs heavy forces. CONCLUSIONS TS chains decayed less than TP chains, and chain loop retraction was beneficial only when using OrTP chains. Contrary to the interchangeable use of TP and TS chains in the published literature and in clinical practice, this study demonstrates that they perform differently under stress and that a clear distinction should be made between the two.
Dynamic Knowledge Processing - Practical Approach

There was a new wave of interest to the real-time AI systems as the ideas of knowledge accumulation and knowledge evolution from data got their full recognition. Our paper seeks a solution through the concept of dynamic expert systems. This concept was proposed by the author some time ago, and a quasi-static approach was developed to implement such a system. The latter permits a smooth combination of static and change, when during a certain amount of time the knowledge used is considered to be stable, yet over a larger time intervals some drastic changes of knowledge are allowed. The resulting dynamic expert system never stops, occasionally interrogating the user if it suspects that some of the previously entered data are obsolete. In this aspect the computer system behaves as a "living creature". The proposed approach resolves the classic frame problem of artificial intelligence. Yet some more sophisticated questions of AI related to the interaction of data and knowledge, are considered in the paper as well. The paper also illustrates a close connection of dynamic system approach to the area of empirical bayesian schemes and to the use of dynamic logic in modern neural nets proposed by some researches.
Imaging Voltage in Genetically Defined Neuronal Subpopulations with a Cre Recombinase-Targeted Hybrid Voltage Sensor

Genetically encoded voltage indicators create an opportunity to monitor electrical activity in defined sets of neurons as they participate in the complex patterns of coordinated electrical activity that underlie nervous system function. Taking full advantage of genetically encoded voltage indicators requires a generalized strategy for targeting the probe to genetically defined populations of cells. To this end, we have generated a mouse line with an optimized hybrid voltage sensor (hVOS) probe within a locus designed for efficient Cre recombinase-dependent expression. Crossing this mouse with Cre drivers generated double transgenics expressing hVOS probe in GABAergic, parvalbumin, and calretinin interneurons, as well as hilar mossy cells, new adult-born neurons, and recently active neurons. In each case, imaging in brain slices from male or female animals revealed electrically evoked optical signals from multiple individual neurons in single trials. These imaging experiments revealed action potentials, dynamic aspects of dendritic integration, and trial-to-trial fluctuations in response latency. The rapid time response of hVOS imaging revealed action potentials with high temporal fidelity, and enabled accurate measurements of spike half-widths characteristic of each cell type. Simultaneous recording of rapid voltage changes in multiple neurons with a common genetic signature offers a powerful approach to the study of neural circuit function and the investigation of how neural networks encode, process, and store information. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators hold great promise in the study of neural circuitry, but realizing their full potential depends on targeting the sensor to distinct cell types. Here we present a new mouse line that expresses a hybrid optical voltage sensor under the control of Cre recombinase. Crossing this line with Cre drivers generated double-transgenic mice, which express this sensor in targeted cell types. In brain slices from these animals, single-trial hybrid optical voltage sensor recordings revealed voltage changes with submillisecond resolution in multiple neurons simultaneously. This imaging tool will allow for the study of the emergent properties of neural circuits and permit experimental tests of the roles of specific types of neurons in complex circuit activity.
Node.js Paradigms and Benchmarks

—The current environment of web applications demands performance and scalability. Several previous approaches have implemented threading, events, or both, but increasing trafﬁc requires new solutions for improved concurrent service. Node.js is a new web framework that achieves both through server-side JavaScript and event-driven I/O. Tests will be performed against two comparable frameworks that compare service request times over a number of cores. The results will demonstrate the performance of JavaScript as a server-side language and the efﬁciency of the non-blocking asynchronous model.
Heat and mass transfer in frozen porous media

In this thesis processes and parameters associated with heat and mass transfer in frozen porous media, such as soil, both on a theoretical and empirical basis are studied. First, an improved model was developed for the measurement of thermal conductivity with use of the nonsteady-state probe method. A second improved measuring method was the measurement of bulk electrical conductivity with use of time domain reflectometry (TDR). A third improvement was the use of the dispersion theory in the description of relationships between water content and bulk electrical conductivity or dielectric constant. It is shown that TDR can be used to measure the unfrozen water content and bulk electrical conductivity simultaneously under frozen conditions, and that from the latter parameter solute redistribution can be monitored. From the measured heat flows a time delay in the forming of pore ice can be concluded. From the measured moisture transport, resulting in frost heave, a relationship with some soil properties could be established. For some of the materials studied a minimum temperature gradient was observed at which heave starts. An effort was made to come to a synthesis of the rigid ice concept and the segregation potential concept.