Miracle-dz/UniFAR-FTUs huggingface dataset:
Speeding up anterior-posterior patterning of insects by differential initialization of the gap gene cascade

Recently, it was shown that anterior-posterior patterning genes in the red flour beetle Tribolium castaneum are expressed sequentially in waves. However, in the fruit fly Drosophila melanogaster, an insect with a derived mode of embryogenesis compared to Tribolium, anterior-posterior patterning genes quickly and simultaneously arise as mature gene expression domains that, afterwards, undergo slight posterior-to-anterior shifts. This raises the question of how a fast and simultaneous mode of patterning, like that of Drosophila, could have evolved from a rather slow sequential mode of patterning, like that of Tribolium. In this paper, we elucidate a mechanism for this evolutionary transition based on a switch from a uniform to a gradient-mediated initialization of the gap gene cascade by maternal Hb. The model is supported by computational analyses and experiments.
AN INTERACTIVE GAMES EXPERIENCE MODEL (GXM) FOR THE DESIGN AND EVALUATION OF THE UX OF GAMIFIED APPS OVER TIME

This paper utilized a literature survey method to review prior literature and to provide support for the modeling of a theoretical interactive games experience model (GXM) for the design and evaluation of the games experience of gamified apps players over time. The outcome of the survey indicates that though there are several games experience models, the accessed models are deficient as they lack comprehensive dimensions and criteria required for a holistic design and evaluation of games experience over time. To solve this problem, this paper conceptualized and proposed a more holistic games experience model for a comprehensive design and evaluation of games experience. The model has eight (8) dimensions. These eight dimensions cover a wider spectrum of games design and evaluation qualities. Each dimension has associated criteria. The model supports the temporality and dynamics of games experience.
Set-Based Prediction of Traffic Participants Considering Occlusions and Traffic Rules

Provably safe motion planning for automated road vehicles must ensure that planned motions do not result in a collision with other traffic participants. This is a major challenge in autonomous driving, since the future behavior of other traffic participants is not known and since traffic participants are often hidden due to occlusions. In this work, we propose a formal set-based prediction that contains all acceptable future behaviors of both detected and potentially hidden traffic participants. Based on formalized traffic rules and nondeterministic motion models, we perform reachability analysis to predict the set of possible occupancies and velocities of vehicles, pedestrians, and cyclists. Real-world experiments with a test vehicle in various traffic situations demonstrate the applicability and real-time capability of our over-approximative prediction for both online verification and fail-safe trajectory planning. Even in congested, complex traffic scenarios, our forecasting approach enables self-driving vehicles to never cause accidents.
Power Density Optimization of 700 kHz GaN-Based Auxiliary Power Module for Electric Vehicles

This article proposes a high-power density 1.8 kW auxiliary power module (APM) for electric vehicles (EVs) based on gallium nitride devices. A design procedure for the high-frequency phase-shift full-bridge with current-doubler rectifier using printed circuit board (PCB)-based planar magnetics is proposed. Leakage inductance analysis of the high-frequency pulsewidth-modulation converter is given to achieve both regulation and zero-voltage-switching turn-on. Then, the magnetics optimization procedure for the customized planar core is proposed with a magnetic figure-of-merit concept to meet the high-power density target. Technical considerations are detailed to meet the extreme temperature constraint imposed on the EVs components. Finally, the proposed APM is demonstrated with a switching frequency of 700 kHz and a power density of 8.1 kW/L (132.8 W/in3).
Short-Term Prediction of Level of Service in Highways Based on Bluetooth Identification

A precise knowledge about future traffic will eventually open a new era in traffic management. Research has focused on the still unresolved problem of predicting travel time (TT). However, practitioners favor the level of service (LOS) as a meaningful metric that avoids the continuous fluctuations and link-specificity of TT. Evolving from TT to LOS opens a new research line in the field, moving the underlying mathematical problem from regression to classification. This study proposes a short-term LOS classifier to fulfill this requirement. Given that traffic conditions are mostly free-flow throughout the day, LOS classes are unbalanced. Therefore, we based our predictor on a Random Undersampling Boost algorithm (RUSBoost), especially suited to overcome this issue. We trained and validated this LOS predictor with 12 months of arrival travel time data, captured by a Bluetooth network with 6 links, in real operation on the SE-30 highway (Seville, Spain). This classifier achieved an average recall of 82.8% for prediction horizons up to 15 minutes, reaching 92.5% predicting congestion. We reached this performance by exploiting two facts that we empirically demonstrated: (i) information from every link (even those in the opposite direction) contributes to increase the accuracy of the prediction; and (ii) traffic presents different behavior depending on the day of the week, which we used to segment the data and construct specific classifiers. These promising results show the potential of the proposed LOS predictor, providing a new perspective into traffic forecast and the subsequent traffic management that yields with what practitioners demand.
Measurement of Extinction Angle of Pyrocarbon by One Diagonal Quarter Intensity Principle

In accordance with the extinction characteristics of pyrocarbons deposited around carbon fibers,this paper proposes a method for measurement of the extinction angle based on the one diagonal quarter intensity principle.It develops a dynamic template matching algorithm during image processing for the purpose of amending the bias of the observed patterns.Meanwhile,the problem of gray information extraction is solved for ellipse sections through rectifying the shape of fiber sections in image sequences.The proposed method can achieve the measurement of extinction angles accurately and effectively,which is suitable for both the condition of vertical section and inclined section.The errors between the values measured by the proposed method and observation are within 1°-2°,which increase with the degree of complexity of the polarized light microscopy(PLM) image texture.
Schottky barrier properties of various metals on n-type GaN

Schottky barriers of Ti, Cr, Au, Pd, Ni and Pt on n-type GaN epitaxial layers grown by low-pressure metal-organic chemical vapour deposition on sapphire have been fabricated and characterized. Measurements were carried out using current - voltage (I - V), current - voltage - temperature (I -V - T) and capacitance - voltage (C - V) techniques. A modified Norde plot was used as one of the analysis tools for the I - V - T measurements. The barrier heights, ideality factors and effective Richardson constants are presented. Barrier heights of 0.88, 0.92, 0.99 and 1.08 eV for Au, Pd, Ni and Pt respectively were obtained from the modified Norde plot. Contacts of Ti and Cr exhibited only slightly rectifying characteristics. These results show that the barrier height on n-GaN increases monotonically, but does not scale proportionately, with increasing metal workfunction.
Artifact Removal in Sparse-Angle CT Based on Feature Fusion Residual Network

To reduce the radiation dose from computed tomography (CT) scans and obtain high-quality images, various methods based on deep learning have been proposed for artifact removal in sparse CT. In this article, a new widely applicable method for artifact removal from sparse-angle CT images is proposed. We propose a feature fusion residual network (FFRN), which achieves excellent performance in removing artifacts from different anatomical regions of sparse angle CT images. In the FFRN, the residual skip dense block (RSDB) is introduced in the shallow layer to adequately utilize the feature information from the Conv layer of the residual block (RB). An improved RB is used in the FFRN deep layer to reduce the network complexity and training difficulty. The RSDB implements local feature fusion by skipping connections to enhance feature extraction. The use of a $3\times 3$ convolution kernel in the RSDB and improved RB achieved better performance compared with a $1\times 1$ convolution kernel. Weight normalization (WN) was used instead of batch normalization (BN) to improve the accuracy of the deep network. We use the original Hounsfield (HU) values of CT images for learning. The result obtained is comparable to the label image. In addition, it was verified that artifacts in the sparse-angle CT images can be better predicted without changing the image size.
Synaptic properties and network state-dependent recruitment of VIP-expressing interneuron-specific interneurons in the CA1 hippocampus

In the hippocampus, a highly specialized population of vasoactive intestinal peptide-expressing interneuron-specific (IS) inhibitory cells coordinates the activity of GABAergic interneurons. While disinhibition may play a critical role in hippocampal learning, the synaptic properties and recruitment of IS cells remain unknown. Here, we found that the CA1 type 3 IS cells (IS3) receive excitatory inputs through the Schaffer collateral and the temporoammonic pathways with synapse-specific properties. The computational models predicted that these synaptic inputs could rhythmically drive the IS3 cell firing during theta oscillations and sharp-wave ripples. However, recordings in awake mice revealed a large variability in IS3 cell recruitment, with preferential recruitment of these cells in relation to theta-run epochs and silence during sharp-wave ripples. Taken together, these data indicate that, while synaptic properties of IS3 cells predict a particular output, additional factors may modulate the cell recruitment during different behavioral and network states.
CacheTree: Reducing Integrity Verification Overhead of Secure Nonvolatile Memories

Emerging nonvolatile memories (NVMs), while exhibiting great potential to be DRAM alternatives, are vulnerable to security attacks. Secure NVM designs demand data persistence on top of traditional confidentiality and integrity protection. A simple adaption of existing secure memory designs would incur non-negligible overheads, including performance degradation, NVM lifetime reduction, and energy consumption increase. In this article, we propose CacheTree to address the integrity verification overhead for secure NVMs. By constructing extra Merkle trees (MTs) on top of metadata cache, CacheTree helps to authenticate the volatile cache contents, which enables the adoption of write-back policy and prevents frequent NVM writes in persisting metadata. We then adopt CacheTree to address the integrity verification in secure NVM, in particular, the overheads in persisting message authentication codes (for protecting the integrity of user data at memory line level) and persisting the main MT (for protecting the integrity of the whole memory space). Our experimental results show that CacheTree, with less than 0.5% storage overhead, achieves up to 20.1% performance improvement, 44.3% lifetime increase, and 43.7% energy consumption reduction over the state-of-the-art solutions.
Developing TEI-Aware Ultralow-Power SoC Platforms for IoT End Nodes

Ranging from circuit-level characterization to designing a platform architecture, developing a design automation tool, and fabricating a System on Chip (SoC), this article deals with the entire development process for ultralow-power (ULP) SoCs for Internet-of-Things (IoT) end nodes. More precisely, this article first focuses on the unique characteristics of the ULP circuits, the temperature effect inversion (TEI), i.e., the delay of the ULP circuits decreases with increasing temperature. Existing TEI-aware low-power (TEI-LP) techniques have incredible potential to further reduce the power consumption of conventional ULP SoCs, but there is a critical limitation to be widely adopted in real SoCs. To address this limitation and realize the ULP SoCs that can fully benefit from the TEI-LP techniques, this article proposes a new TEI-inspired SoC platform (TIP) architecture. On top of that, taking into account that the highly complex, time consuming, and labor-intensive development process of these ULP SoCs may hinder their widespread use for IoT end nodes, this article presents a new electronic design automation tool to accelerate ULP SoC development, RISC-V express (RVX). Finally, by using the RVX, this article introduces a TIP prototyping chip fabricated in 28-nm FD-SOI technology. This chip demonstrates that power savings of up to 35% can be achieved by lowering the supply voltage from 0.54 to 0.48 V at 25 °C and 0.44 V at 80 °C while continuing to operate at a target 50-MHz clock frequency.
Dynamics of the Chaplygin Ball with Variable Parameters

This work is devoted to the study of the dynamics of the Chaplygin ball with variable moments of inertia, which occur due to the motion of pairs of internal material points, and internal rotors. The components of the inertia tensor and the gyrostatic momentum are periodic functions. In general, the problem is nonintegrable. In a special case, the relationship of the problem under consideration with the Liouville problem with changing parameters is shown. The case of the Chaplygin ball moving from rest is considered separately. Poincaré maps are constructed, strange attractors are found, and the stages of the origin of strange attractors are shown. Also, the trajectories of contact points are constructed to confirm the chaotic dynamics of the ball. A chart of dynamical regimes is constructed in a separate case for analyzing the nature of strange attractors.
Effects of E. Coli Infection on the Expressions of TGF-β/Smads Signaling Pathway in Broiler Intestine

24/June/2019 Approved: 23/November/2019 ABSTRACT This experiment aimed to investigate whether Escherichia coli ( E. coli ) infection could affect the TGF- β /smads signaling pathway in the jejunal tissue of chickens. One-day-old Cobb 500 broilers were randomly divided into 2 groups and treated with intraperitoneal E. coli or broth injection. Clinical signs of the birds were assessed every day. Spleen and bursa of Fabricius of the birds, post-infection (pi), were collected to evaluate immune organ index. Jejunal tissues were collected to ascertain the expression of TGF- β s, T β Rs, and Smads. The results showed that the infected birds had significantly higher index of the spleen (24hrs and 48hrs pi) compared with birds in the control group ( p< 0.05). The relative gene expression of TGF- β 4 increased ( p< 0.05), while the expression of Smad7 down-regulated in the E. coli group ( p< 0.01). There was no significant difference in TGF- β 2, TGF- β 3, T β R I, T β R II, Smad2, Smad3 expression ( p> 0.05). In conclusion, TGF- β /Smad signaling pathway was associated with the immune response of broilers in E. coli infection and TGF- β 4 was the main subtype interacting with
The Impact of Total Quality Management Multidimensional on Non-Financial Organizational Performance: An Empirical Investigation of Saudi Commission for Tourism and National Heritage Hotels

This examination experimentally explores the most powerful components of all out total quality management (TQM) (top management support, customer focus, employees' participation, training and education, continuous process improvement, strategic planning, effective communication, and decision-making based on data and information ) on the non-financial organizational performance measurements (job satisfaction, organizational commitment, and employee’s creativity). The investigation involved 121 employees from different hotels, which are classified within the Saudi Commission for Tourism and national Heritage (SCTH) in Najran Region. Using multiple regression analysis, findings indicated that Effective communication followed by Top management support, Continuous process improvement, Employee participation, Decision-making based on information, Strategic planning, Training and education and finally by customer focus. Thusly, this current investigation's results can be prescribed to expand acknowledgment of the significance of human resource metrics in organizational performance.
Immunocytochemical Analysis of α-Tubulin Distribution Before and After Rapid Axopodial Contraction in the Centrohelid Raphidocystis contractilis

The centrohelid Raphidocystis contractilis is a heliozoan that has many radiating axopodia, each containing a bundle of microtubules. Although the rapid contraction of the axopodia at nearly a video rate (30 frames/s) is induced by mechanical stimuli, the mechanism underlying this phenomenon in R. contractilis has not yet been elucidated. In the present study, we described for the first time an adequate immunocytochemical fixation procedure for R. contractilis and the cellular distribution of α-tubulin before and after rapid axopodial contraction. We developed a flow-through chamber equipped with a micro-syringe pump that allowed the test solution to be injected at a flow rate below the threshold required to induce rapid axopodial contraction. Next, we used this injection method for evaluating the effects of different combinations of two fixatives (paraformaldehyde or glutaraldehyde) and two buffers (phosphate buffer or PHEM) on the morphological structure of the axopodia. A low concentration of glutaraldehyde in PHEM was identified as an adequate fixative for immunocytochemistry. The distribution of α-tubulin before and after rapid axopodial contraction was examined using immunocytochemistry and confocal laser scanning fluorescence microscopy. Positive signals were initially detected along the extended axopodia from the tips to the bases and were distributed in a non-uniform manner within the axopodia. Conversely, after the induction of a rapid axopodial contraction, these positive signals accumulated in the peripheral region of the cell. These results indicated that axopodial microtubules disassemble into fragments and/ or tubulin subunits during rapid axopodial contraction. Therefore, we hypothesize that the mechanism of extremely rapid axopodial contraction accompanied by cytoskeletal microtubule degradation in R. contractilis involves microtubule-severing at multiple sites.
Nonlinear Equalization Based on Artificial Neural Network in DML-Based OFDM Transmission Systems

This article reports the application of an equalizer based on an artificial neural network (ANN), in the form of nonlinear waveform regression, to mitigate nonlinear impairments in directly modulated laser (DML)-based orthogonal frequency-division multiplexing (OFDM) optical transmission. Experiments involving transmission over 0–200 km demonstrate that using an ANN with one hidden layer can greatly reduce nonlinear distortion. The proposed scheme outperformed a Volterra nonlinear equalizer at transmission distances exceeding 25 km. Using a 10G-class DML, the proposed scheme achieved the following data rates: 39.2 Gbps at 100 km (an improvement of 59%) and 33.5 Gbps at 150 km (an improvement of 57%). We also modified the cost function of the ANN during the training procedure to overcome the poor signal-to-noise ratio of the original ANN at low frequencies. This resulted in $>$30-Gbps transmission over 0–200 km.
Review: Synthetic scaffolds to control the biochemical, mechanical, and geometrical environment of stem cell-derived brain organoids

Stem cell-derived brain organoids provide a powerful platform for systematic studies of tissue functional architecture and the development of personalized therapies. Here, we review key advances at the interface of soft matter and stem cell biology on synthetic alternatives to extracellular matrices. We emphasize recent biomaterial-based strategies that have been proven advantageous towards optimizing organoid growth and controlling the geometrical, biomechanical, and biochemical properties of the organoid's three-dimensional environment. We highlight systems that have the potential to increase the translational value of region-specific brain organoid models suitable for different types of manipulations and high-throughput applications.
Investigation of the anti-cancer properties of natural products and synthetic analogues with NQO2 inhibiting potential

18-19 Declaration . 20 Copyright statement . 21 Acknowledgements . 22 1.0 CHAPTER ONE – INTRODUCTION.23 1.1 Cancer.24-25 1.1.1 Causes of Cancer.25-26 1.1.2 Hallmarks of cancer.26-29 1.1.3 Angiogenesis . 30 1.1.4 Types of cancer.30-33 1.1. 5 Treatment.34-40 1.1. 6 Breast cancer, inflammation and oxidative stress.40-41 1.2 Quinones.42-43 1.3 Quinone Oxidoreductase 1 (NQO1.43-46 1.4 Quinone Oxidoreductase 2 (NQO2) . 46-48 1.4. 1 The ping-pong mechanism of NQO2.48-49 1.4. 2 Role of NQO2 in oxidative stress and cellular growth.50
Remote sensing restores predictability of ectotherm body temperature in the world’s forests

AIM: Rising global temperatures are predicted to increase ectotherms’ body temperatures, benefitting some species but threatening others. Biophysical models predict a key role for shade in buffering these effects, but the difficulty of measuring shade across broad spatial extents limits predictions of ectotherms’ thermal futures at the global scale. Here, we extend biophysical models of ectotherm body temperature to include effects of forest canopy shade, via leaf area index, and test whether considering remotely-sensed canopy density improves predictions of body temperature variation in heavily shaded habitats. LOCATION: Worldwide. TIME PERIOD: 1990–2010. MAJOR TAXA STUDIED: Lizards. METHODS: We test predictions from biophysical ecological theory for how body temperature should vary with microclimate for 269 lizard populations across open, semi-open, and closed habitats worldwide. We extend existing biophysical models to incorporate canopy shade effects via leaf area index, test whether body temperature varies with canopy density as predicted by theory, and evaluate the extent to which incorporating canopy density improves model performance in heavily-shaded areas. RESULTS: We find that body temperatures in open habitats, like deserts, vary with air temperature and incident solar radiation as predicted by biophysical equations, but these relationships break down in forests, where body temperatures become unpredictable. Incorporating leaf area index into our models revealed lower body temperatures in more heavily shaded environments, restoring the predictability of body temperature in forests. CONCLUSIONS: Although biophysical ecological theory can predict ectotherm body temperature in open habitats, like deserts, these relationships decay in closed forests. Models incorporating remotely sensed data on canopy density improved predictability of body temperatures in these habitats, providing an avenue to incorporate canopy shade effects into predictions of animals’ vulnerability to climate change. These results highlight the thermal threat of changes in canopy structure and loss of forest cover for the world’s ectotherms.