Miracle-dz/UniFAR-FTUs huggingface dataset:
CO2-induced ion and fluid transport in human retinal pigment epithelium

In the intact eye, the transition from light to dark alters pH, [Ca2+], and [K] in the subretinal space (SRS) separating the photoreceptor outer segments and the apical membrane of the retinal pigment epithelium (RPE). In addition to these changes, oxygen consumption in the retina increases with a concomitant release of CO2 and H2O into the SRS. The RPE maintains SRS pH and volume homeostasis by transporting these metabolic byproducts to the choroidal blood supply. In vitro, we mimicked the transition from light to dark by increasing apical bath CO2 from 5 to 13%; this maneuver decreased cell pH from 7.37 ± 0.05 to 7.14 ± 0.06 (n = 13). Our analysis of native and cultured fetal human RPE shows that the apical membrane is significantly more permeable (≈10-fold; n = 7) to CO2 than the basolateral membrane, perhaps due to its larger exposed surface area. The limited CO2 diffusion at the basolateral membrane promotes carbonic anhydrase–mediated HCO3 transport by a basolateral membrane Na/nHCO3 cotransporter. The activity of this transporter was increased by elevating apical bath CO2 and was reduced by dorzolamide. Increasing apical bath CO2 also increased intracellular Na from 15.7 ± 3.3 to 24.0 ± 5.3 mM (n = 6; P < 0.05) by increasing apical membrane Na uptake. The CO2-induced acidification also inhibited the basolateral membrane Cl/HCO3 exchanger and increased net steady-state fluid absorption from 2.8 ± 1.6 to 6.7 ± 2.3 µl × cm−2 × hr−1 (n = 5; P < 0.05). The present experiments show how the RPE can accommodate the increased retinal production of CO2 and H2O in the dark, thus preventing acidosis in the SRS. This homeostatic process would preserve the close anatomical relationship between photoreceptor outer segments and RPE in the dark and light, thus protecting the health of the photoreceptors.
A cross-sectional study examining the psychometric properties of the painDETECT measure in neuropathic pain

Background Similarities and differences on the nine-item and seven-item versions of painDETECT, a patient-reported screener to identify neuropathic pain (NeP), have not been psychometrically explored across NeP conditions. Methods Scores on the nine-item painDETECT (seven pain symptom items, one pain course pattern item, one pain radiation item) range from −1 to 38; scores ≥19 indicate NeP is likely (>90% probability). The seven-item version (only pain symptoms) score range is 0 to 35. painDETECT was administered to subjects with confirmed diagnoses of human immunodeficiency virus-related peripheral NeP (HIVP) (n=103), spinal cord injury-related NeP (SCI) (n=103), small fiber neuropathy (n=100), painful diabetic peripheral neuropathy (n=112), posttrauma/postsurgical NeP (n=100), and NeP in chronic low back pain (n=106) identified during office visits to US community-based physicians. Analysis of covariance compared mean scores (adjusted for age, sex, race, ethnicity, time since NeP diagnosis, and number of comorbidities) on the nine-item and seven-item versions of painDETECT. Cronbach’s alpha assessed internal consistency reliability, and corrected item-to-total correlations assessed item-level discrimination. Results The adjusted mean nine-item scores ranged from 21.0 (SCI) to 24.3 (small fiber neuropathy). Differences between conditions were either trivial or small-to-medium in magnitude. Cronbach’s alpha gave overall internal consistency reliability of 0.76, with a range of 0.63 (SCI) to 0.82 (HIVP). Mean scores and Cronbach’s alphas for the seven-item version were generally similar to the nine-item version. Corrected item-to-total correlations adequately discriminated all pain symptom items on both painDETECT versions for each condition (0.3–0.7), but the two nonsensory items on the nine-item version showed lackluster discrimination (<0.3). Conclusion painDETECT scores were within the range indicating high probability of NeP. Differences between conditions were generally modest or not large. Both versions showed evidence of internal consistency reliability and item-level discrimination, suggesting that painDETECT is a useful screening measure for identifying NeP across NeP conditions.
Mechanistic Target of Rapamycin (Mtor) Is Essential for Murine Embryonic Heart Development and Growth

Mechanistic target of rapamycin (Mtor) is required for embryonic inner cell mass proliferation during early development. However, Mtor expression levels are very low in the mouse heart during embryogenesis. To determine if Mtor plays a role during mouse cardiac development, cardiomyocyte specific Mtor deletion was achieved using α myosin heavy chain (α-MHC) driven Cre recombinase. Initial mosaic expression of Cre between embryonic day (E) 10.5 and E11.5 eliminated a subset of cardiomyocytes with high Cre activity by apoptosis and reduced overall cardiac proliferative capacity. The remaining cardiomyocytes proliferated and expanded normally. However loss of 50% of cardiomyocytes defined a threshold that impairs the ability of the embryonic heart to sustain the embryo's circulatory requirements. As a result 92% of embryos with cardiomyocyte Mtor deficiency died by the end of gestation. Thus Mtor is required for survival and proliferation of cardiomyocytes in the developing heart.
3D multi-view system using electro-wetting liquid lenticular lenses

Lenticular multi-view system has great potential of three dimensional image realization. This paper introduces a fabrication of liquid lenticular lens array and an idea of increasing view points with a same resolution. Tunable liquid lens array can produce three dimensional images by using electro-wetting principle that changes surface tensions by applying voltage. The liquid lenticular device consists of a chamber, two different liquids and a sealing plate. To fabricate the chamber, an <100> silicon wafer is wet-etched by KOH solution and a trapezoid shaped chamber can be made after a certain time. The chamber having slanted walls is advantageous for electro-wetting achieving high diopter. Electroplating is done to make a nikel mold and poly methyl methacrylate (PMMA) chamber is fabricated through an embossing process. Indium tin oxide (ITO) is sputtered and parylene C and Teflon AF1600 is deposited for dielectric and hydrophobic layer respectively. Two immiscible liquids are injected and a glass plate as a sealing plate is covered with polycarbonates (PC) gaskets and sealed by UV adhesive. Two immiscible liquids are D.I water and a mixture of 1-chloronaphthalene and dodecane. The completed lenticular lens shows 2D and 3D images by applying certain voltages. Dioptric power and operation speed of the lenticular lens array are measured. A novel idea that an increment of viewpoints by electrode separation process is also proposed. The left and right electrodes of lenticular lens can be induced by different voltages and resulted in tilted optical axis. By switching the optical axis quickly, two times of view-points can be achieved with a same pixel resolution.
Accelerating Multipath Transport Through Balanced Subflow Completion

Simultaneously using multiple network paths (e.g., WiFi and cellular) is an attractive feature on mobile devices. A key component in a multipath system such as MPTCP is the scheduler, which determines how to distribute the traffic over multiple paths. In this paper, we propose DEMS, a new multipath scheduler aiming at reducing the data chunk download time. DEMS consists of three key design decisions: (1) being aware of the chunk boundary and strategically decoupling the paths for chunk delivery, (2) ensuring simultaneous subflow completion at the receiver side, and (3) allowing a path to trade a small amount of redundant data for performance. We have implemented DEMS on smartphones and evaluated it over both emulated and real cellular/WiFi networks. DEMS is robust to diverse network conditions and brings significant performance boost compared to the default MPTCP scheduler (e.g., median download time reduction of 33%--48% for fetching files and median loading time reduction of 6%--43% for fetching web pages), and even more benefits compared to other state-of-the-art schedulers.
Guide Me: Interacting with Deep Networks

Interaction and collaboration between humans and intelligent machines has become increasingly important as machine learning methods move into real-world applications that involve end users. While much prior work lies at the intersection of natural language and vision, such as image captioning or image generation from text descriptions, less focus has been placed on the use of language to guide or improve the performance of a learned visual processing algorithm. In this paper, we explore methods to flexibly guide a trained convolutional neural network through user input to improve its performance during inference. We do so by inserting a layer that acts as a spatio-semantic guide into the network. This guide is trained to modify the network's activations, either directly via an energy minimization scheme or indirectly through a recurrent model that translates human language queries to interaction weights. Learning the verbal interaction is fully automatic and does not require manual text annotations. We evaluate the method on two datasets, showing that guiding a pre-trained network can improve performance, and provide extensive insights into the interaction between the guide and the CNN.
Yield and Relationships among Head Traits in Cabbage as Influenced by Planting Date and Cultivar. II. Processing

This is the second of two related reports dealing with the effects of cultivar × environment interactions on cabbage (Brassica oleracea L., Capitata Group) crop traits. This study examined planting date and cultivar effects on physical head traits of process- ing cabbage and compared these findings to those from a similar study of fresh market cabbage. Six cultivars of processing cabbage were planted in May and June-July of 1999 and 2000 at the OARDC Vegetable Crops Research Branch in Fremont, Ohio. Market- able yield for each crop was determined, and measurements were taken of head weight, diameter, density, and volume, and core length, base width, and volume on more than 450 individual heads. Head and core volume and head density were calculated from these direct measures. Year, planting date, and cultivar significantly affected the majority of head traits. May planting led to higher marketable yield and heavier heads with larger diameters than June-July planting. The most variable trait across cultivars was head volume, which was affected by planting date in all cultivars. Differences between pro- cessing and fresh market cabbage were found. Average head polar/equatorial diameter values were affected by planting date in the fresh market but not the processing study. In contrast, head density and core volume as a percent of head volume were affected by planting date in the processing but not the fresh market study.
Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG

Background and Objective. Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recognize neuropathic changes. This study validates the possibility of extending and refining turns-amplitude analysis using permutation entropy and signal energy. Methods. In this study, we examined needle electromyography in 40 neuropathic individuals and 40 controls. The number of turns, amplitude between turns, signal energy, and “permutation entropy” were used as features for support vector machine classification. Results. The obtained results proved the superior classification performance of the combinations of all of the above-mentioned features compared to the combinations of fewer features. The lowest accuracy from the tested combinations of features had peak-ratio analysis. Conclusion. Using the combination of permutation entropy with signal energy, number of turns and mean amplitude in SVM classification can be used to refine the diagnosis of polyneuropathies examined by needle electromyography.
A cross-sectional investigation of the relationships education , certification , and experience have with knowledge , skills , and abilities among aviation professionals

Daryl Watkins Embry-Riddle Aeronautical University Worldwide, watkind4@erau.edu Jason M. Newcomer Embry-Riddle Aeronautical University Worldwide, jason.newcomer@erau.edu Matthew P. Earnhardt Embry Riddle Aeronautical University, earnharm@erau.edu James W. Marion Embry-Riddle Aeronautical University Worldwide, marionj@erau.edu Rose A. Opengart Embry-Riddle Aeronautical University Worldwide, opengarr@erau.edu Aaron M. Glassman Embry-Riddle Aeronautical University, glassf10@erau.edu
A radiative transfer framework for non-exponential media

We develop a new theory of volumetric light transport for media with non-exponential free-flight distributions. Recent insights from atmospheric sciences and neutron transport demonstrate that such distributions arise in the presence of correlated scatterers, which are naturally produced by processes such as cloud condensation and fractal-pattern formation. Our theory formulates a non-exponential path integral as the result of averaging stochastic classical media, and we introduce practical models to solve the resulting averaging problem efficiently. Our theory results in a generalized path integral which allows us to handle non-exponential media using the full range of Monte Carlo rendering algorithms while enriching the range of achievable appearance. We propose parametric models for controlling the statistical correlations by leveraging work on stochastic processes, and we develop a method to combine such unresolved correlations (and the resulting non-exponential free-flight behavior) with explicitly modeled macroscopic heterogeneity. This provides a powerful authoring approach where artists can freely design the shape of the attenuation profile separately from the macroscopic heterogeneous density, while our theory provides a physically consistent interpretation in terms of a path space integral. We address important considerations for graphics including reciprocity and bidirectional rendering algorithms, all in the presence of surfaces and correlated media.
Thin film technique for preparing nano-Zno gas sensing (O 2 , No 2 ) using Plasma Deposition

Zinc oxide thin films in 40 nm crystalline sizes were deposited on glass plates by using DC- sputtering of Ar/O2 (10%) plasma glow discharges. Home-made DC-glow discharge plasma (reactive ion) source was designed and implemented for this work. Our electrodes assembly configuration is special and less complex for preparing the nanocrystalline thin films in minimum grain size. Investigation concerned the technologies of depositing very thin film (~214-280nm) of zinc oxide and investigated both morphological structure of the produced layers and there optical properties. The structural details and microstructure were obtained from X-ray diffraction, optical microscope and atomic force microscope (AFM). Plasma deposited ZnO films exhibits the uniform prefer rential growth of nano crystalline film and hexagonal type structure with good crystallinity and no indication of amorphous components or other crystalline compounds. The minimum and average crystallite size was obtained using atomic force microscope. The spherical ZnO nanoparticlles form a spatial homogenous film on the substrate without any discontinuities was exhibited from the optical microscope. The energy gap of these plasma deposited ZnO films lies in the range of 3.1-3.3eV. This work also presents investigations on the technology of gas sensing using home-made gas sensing unite and ZnO nanocrystalline films in the O2 and NO2 gases.
Smart-TV Security Analysis: Practical Experiments

Modern home networks are becoming more and more complex with the integration of various types of interconnected smart devices, using heterogeneous networking technologies. Many of these devices are also connected to the Internet, generally through an integrated access device. Those smart devices are potentially vulnerable to several types of attacks. In this practical experience report we investigate the specific case of smart TVs. The main objective is to experimentally explore possible attack vectors and identify practically exploitable vulnerabilities and attack scenarios. In particular, the study covers local and remote attacks using different entry points, including the Digital Video Broadcasting (DVB) transmission channel and the copper-pair local loop. Several methods, allowing to observe and simulate service provider networks, are used to support several experiments considering four types of commercially available smart TVs for a comparative analysis. We also discuss several methods allowing to extract and analyze the embedded firmware, and obtain relevant information concerning target devices.
Ethnic diversity and value sharing: A longitudinal social network perspective on interactive group processes

People often collaborate in groups that are increasingly diverse. As research predominantly investigated effects of diversity, the processes behind these effects remain understudied. We follow recent research that shows creating shared values is important for group functioning but seems hindered in high diversity groups - and use longitudinal social network analyses to study two interpersonal processes behind value sharing: creating relations between members or 'social bonding' (network tie formation and homophily) and sharing values - potentially through these relationships - or 'social norming' (network convergence and influence). We investigate these processes in small interactive groups with low and high ethnic diversity as they collaborate over time. In both low and high diversity groups, members showed social bonding and this creation of relations between members was not organized along ethnic lines. Low diversity groups also showed social norming: Members adjusted their relational values to others they liked and achievement values converged regardless of liking. In high diversity groups, however, there was no evidence for social norming. Thus, ethnic diversity seems to especially affect processes of social norming in groups, suggesting that targeted interventions should focus on facilitating social norming to stimulate value sharing in high diversity groups.
The risk of bleeding with warfarin: A systematic review and performance analysis of clinical prediction rules

Summary It was the objective of this article to qualitatively review and evaluate the clinical prediction rules (CPRs) available for estimating bleeding risk in patients commencing warfarin therapy. A systematic review of PubMed (1949 to December 2006), MEDLINE (1966 to December 2006); EMBASE (1980 to December 2006), Cochrane Database of Systematic Reviews (to December 2006), and International Pharmaceutical Abstracts (1970 to Demember 2006) was conducted. Seven studies were found that detailed CPRs used to assess risk of bleeding prior to commencing warfarin therapy. Four studies described distinct CPRs. The remaining three studies were further validations of one of the CPRs, the Outpatient Bleeding Risk Index. The Outpatient Bleeding Risk Index was classified as being of Level 2 evidence while the remaining three indices were classified as being of Level 4 evidence. In no case did the CPRs exhibit performance characteristics that would indicate“strong” ability to predict the presence of absence of major bleeding among warfarin recipients. The modified Outpatient Bleeding Risk Index exhibited moderate predictive ability for major bleeding in two studies, although pooling of all studies of this CPR did not reveal moderate or better performance. None of the CPRs identified “any bleeding” with moderate or strong predictive ability. None of the available CPRs exhibit sufficient predictive accuracy or have trials evaluating the impact of their use on patient outcomes. Hence, no existing CPR can be recommended for widespread use in practice at present.
Cold Tolerance of Megacopta cribraria (Hemiptera: Plataspidae): An Invasive Pest of Soybeans

Abstract Kudzu bug, Megacopta cribraria Fabricius (Hemiptera: Plataspidae), first discovered in the United States in 2009, is an invasive pest of soybeans. From 2013 to 2016, Maryland has been the northern limit of its distribution in the United States. We sought to determine the physiological cold temperature limits, timing of movement to overwintering locations, and to characterize overwintering microhabitat temperature. We measured supercooling point (SCP) on three populations from distinct USDA plant hardiness zones in Maryland and Virginia between October and December of 2015. The average SCP across all sample months and populations was -12.6°C and no consistent trend of month or population location were observed. Additionally, we assessed the lower lethal temperature to kill 50% of the population (LLT50) at the same population locations in October and November 2015. The average LLT50 over both months and all three population locations was -5.1°C. Again, no consistent trend based on population location was observed but we did find a modest depression in the LLT50 values between October and November. We observed that kudzu bug overwinters in leaf litter and begins to move into the litter in late November to early December. Leaf litter moderates day to night temperature differences and was warmer than ambient temperature by an average of 0.7°C. Evidence suggests that the cold tolerance of the kudzu bug limits its distribution north of Maryland.
Measurement / Simulation Mismatches and Multivariate Data Discretization in the Machine Learning Era

In the era of machine learning and usage of high dimensional data many analyses in astroparticle physics face similar problems. This contribution presents approaches to face two typical challenges in the field: verify agreement between simulated and measured data and binning in multiple dimensions while preserving sufficient statistics. The presented approaches are based on widely used machine learning algorithms making them easy to use and providing good scalability in terms of size and dimensionality of the used data.
Single Stream Parallelization of Recurrent Neural Networks for Low Power and Fast Inference

As neural network algorithms show high performance in many applications, their efficient inference on mobile and embedded systems are of great interests. When a single stream recurrent neural network (RNN) is executed for a personal user in embedded systems, it demands a large amount of DRAM accesses because the network size is usually much bigger than the cache size and the weights of an RNN are used only once at each time step. We overcome this problem by parallelizing the algorithm and executing it multiple time steps at a time. This approach also reduces the power consumption by lowering the number of DRAM accesses. QRNN (Quasi Recurrent Neural Networks) and SRU (Simple Recurrent Unit) based recurrent neural networks are used for implementation. The experiments for SRU showed about 300% and 930% of speed-up when the numbers of multi time steps are 4 and 16, respectively, in an ARM CPU based system.