Miracle-dz/UniFAR-FTUs huggingface dataset:
TriPleX: a versatile dielectric photonic platform

Abstract Photonic applications based on planar waveguide technology impose stringent requirements on properties such as optical propagation losses, light coupling to optical fibers, integration density, as well as on reliability and reproducibility. The latter is correlated to a high level of control of the refractive index and waveguide geometry. In this paper, we review a versatile dielectric waveguide platform, called TriPleX, which is based on alternating silicon nitride and silicon dioxide films. Fabrication with CMOS-compatible equipment based on low-pressure chemical vapor deposition enables the realization of stable material compositions being a prerequisite to the control of waveguide properties and modal shape. The transparency window of both materials allows for the realization of low-loss waveguides over a wide wavelength range (400 nm–2.35 μm). Propagation losses as low as 5×10-4 dB/cm are reported. Three basic geometries (box shell, double stripe, and filled box) can be distinguished. A specific tapering technology is developed for on-chip, low-loss (<0.1 dB) spotsize convertors, allowing for combining efficient fiber to chip coupling with high-contrast waveguides required for increased functional complexity as well as for hybrid integration with other photonic platforms such as InP and SOI. The functionality of the TriPleX platform is captured by verified basic building blocks. The corresponding library and associated design kit is available for multi-project wafer (MPW) runs. Several applications of this platform technology in communications, biomedicine, sensing, as well as a few special fields of photonics are treated in more detail.
Absence of PEXEL-Dependent Protein Export in Plasmodium Liver Stages Cannot Be Restored by Gain of the HSP101 Protein Translocon ATPase

Host cell remodeling is critical for successful Plasmodium replication inside erythrocytes and achieved by targeted export of parasite-encoded proteins. In contrast, during liver infection the malarial parasite appears to avoid protein export, perhaps to limit exposure of parasite antigens by infected liver cells. HSP101, the force-generating ATPase of the protein translocon of exported proteins (PTEX) is the only component that is switched off during early liver infection. Here, we generated transgenic Plasmodium berghei parasite lines that restore liver stage expression of HSP101. HSP101 expression in infected hepatocytes was achieved by swapping the endogenous promoter with the ptex150 promoter and by inserting an additional copy under the control of the elongation one alpha (ef1α) promoter. Both promoters drive constitutive and, hence, also pre-erythrocytic expression. Transgenic parasites were able to complete the life cycle, but failed to export PEXEL-proteins in early liver stages. Our results suggest that PTEX-dependent early liver stage export cannot be restored by addition of HSP101, indicative of alternative export complexes or other functions of the PTEX core complex during liver infection.
RTL to GDSII of Harvard Structure RISC Processor

This paper speaks about design of RISC processor and its implementation from RTL to GDSII. Verification of RISC processor Harvard structure is carried using Verilog (RTL file) and test bench for that Verilog file. Cadence NC Launch tool is used for simulation of code. Later verified Verilog file along with. sdc and . lib files, gate level net list was generated from cadence Genus tool. Till this part of gate level net list generations front end part of design will be carried out. Output of Genus tool are verified gate level net list file and. sdc constraints file. Pre-layout simulation results for power, area and timing are carried out. In backend design, cadence Innovus tool was used for floor planning, power planning and routing. Here also post layout simulations carried for power, timing and area. All these processes are carried out using 180nm technology cadence tool. The physical implementation of Harvard Structure RISC Processor is successfully implemented on Cadence Innovus tool. After carrying out pre-clock tree synthesis, post clock tree synthesis and post routing of circuit, one has obtained optimized results for timing 9.236ps, power 0.53155682W and area 17067. 7584µm2.
Playing through Microaggressions on a College Campus with “Blindspot”

Blindspot is a 2D web-based game that tells a story of a Chinese student newly arrived at an American university who experiences microaggressions in her college life. A prologue gives background information of the protagonist, followed by three chapters in different campus settings complete with puzzle games whose mechanics emphasize the microaggression topic of the chapter. Based on player dialogue choices, strategies for dealing with microaggressions may be followed or not, leading to different puzzles, with a hopeful ending presented to all. The narrative and game mechanics foster empathy with the protagonist, providing benefits for players in both marginalized and non-marginalized groups.
Low-Delay Analog Distributed Joint Source-Channel Coding using SIRENs

We consider the design of joint source-channel coding (JSCC) schemes for two multiterminal source-channel coding problems - namely, the transmission of a Gaussian source with side information at the receiver and the transmission of bivariate Gaussian sources over two independent Gaussian channels. Our focus is on low-delay transmission. We formulate the design problem as optimization of an autoencoder (AE) model, and show that sinusoidal representation networks (SIRENs) are a good choice due to their inherent periodicity and the ability of stretched sinusiods to cover the source space. We show that SIRENs outperform parametric ReLU based networks. The complexity of the proposed method scales better with source dimension than the best traditional schemes known in the literature while their performance is comparable to or better than that of the best traditional schemes. We demonstrate that the spontaneously learned encoder mappings share resemblance to the classical Wyner-Ziv mappings for JSCC with side information, and exhibits structured patterns in the case of distributed coding that are interpretable.
The Relationship between Superhydrophobicity, Self-Cleaning Performance and Microstructure of Butterfly Wing

The microstructure and hydrophobicity of butterflywing surfaces were investigated by a scanning electron microscope (SEM), an atomicforce microscope (AFM) and a contact angle meter. The relationship between hydrophobicity,self-cleaning performance and microstructuralcharacteristic was analyzed. The butterfly wing surface is of lowadhesion (water SA 1~3°) and high hydrophobicity (water CA 138~157°). Theaverage rate of CaCO3 pollutionremoval from the wing surface is as high as 86.2%. There is a good positive correlation (R2=0.873)between pollution removal rate and roughness index of the wing surface. The coupling effects of hydrophobic material andrough microstructure contribute to the complex wettability and remarkableself-cleaning property of the wing surface. Butterfly wing can be potentiallyused as a template for design of micro-controllable superhydrophobic surfaceand nano self-cleaning material. This work may offer inspirations forbiomimetic fabrication of novel interfacial material with multi-functions.
Personalizing emotion recognition using incremental random forests

Affective learning analytics is based on video exchanges within students and between students and teachers. Their aim is to manage both cognitive and affective loads. Affective state detection from videos is subject to identity bias, particularly morphological and behavioral. Although machine learning can fairly detect basic expressions (as defined by Paul Ekman), it hardly deals with these biases and perform better after personalization to a given user (or set of users). But this adaptation needs to train incrementally algorithms with new data. We propose here to use incremental random forests that show abilities to deal with covariate shift in data. We initially train our model on CFEE dataset. Then we train incrementally and evaluate on benchmark CK dataset. Experimental results show that, after progressive training, precision increases. These results suggest that the use of incremental training can improve the accuracy of emotion recognition by specializing the model on a given subject.
A Formal Framework for Complex Event Recognition

Complex event recognition (CER) has emerged as the unifying field for technologies that require processing and correlating distributed data sources in real time. CER finds applications in diverse domains, which has resulted in a large number of proposals for expressing and processing complex events. Existing CER languages lack a clear semantics, however, which makes them hard to understand and generalize. Moreover, there are no general techniques for evaluating CER query languages with clear performance guarantees. In this article, we embark on the task of giving a rigorous and efficient framework to CER. We propose a formal language for specifying complex events, called complex event logic (CEL), that contains the main features used in the literature and has a denotational and compositional semantics. We also formalize the so-called selection strategies, which had only been presented as by-design extensions to existing frameworks. We give insight into the language design trade-offs regarding the strict sequencing operators of CEL and selection strategies. With a well-defined semantics at hand, we discuss how to efficiently process complex events by evaluating CEL formulas with unary filters. We start by introducing a formal computational model for CER, called complex event automata (CEA), and study how to compile CEL formulas with unary filters into CEA. Furthermore, we provide efficient algorithms for evaluating CEA over event streams using constant time per event followed by output-linear delay enumeration of the results.
60.1: Distinguished Paper: A Third Generation Timing Controller And Column Driver Architecture Using Point‐to‐Point Differential Signaling

Many assume LCDs will quickly dominate the TV market by simply scaling existing LCD monitor panels to wider formats (e.g. 16:9 HDTV) and larger sizes. However, a number of TV requirements push beyond the state‐of‐the‐art monitors of today; response time, brightness, contrast, color envelope, color temperature, and progressive scan‐and‐hold issues require a re‐engineering of the monitor solution. Building upon the strengths of National's LVDS and RSDS technology solutions in digital video‐data communications, we have created a completely new architecture that fully addresses the needs of TV while supporting existing platforms. The Point‐to‐Point Differential Signaling (PPDS™) architecture is more than a data link between the timing controller and the column driver. It is an architecture that supports very large displays with features like multiple windows each with its own gamma, various gamma optimizations, color balance at every gray level, minimal bezel size, a 30‐bit and beyond color path to the display surface, four‐color mosaics and numerous other benefits.
Low-frequency noise spectroscopy of polycrystalline silicon thin-film transistors

Polycrystalline silicon thin-film transistor (polysilicon TFT's) characteristics are evaluated by using a low-frequency noise technique. The drain current fluctuation caused by trapping and detrapping processes at the grain boundary traps is measured as the current spectral density. Therefore, the properties of the grain boundary traps can be directly evaluated by this technique. The experimental data show a transition from 1/f behavior to a Lorentzian noise. The 1/f noise is explained with an existing model developed for monocrystalline silicon based on fluctuations of the inversion charge near the silicon-oxide interface. The Lorentzian spectrum is explained by fluctuations of the grain boundary interface charge with a model based on a Gaussian distribution of the potential barriers over the grain boundary plane. Quantitative analysis of the 1/f noise and the Lorentzian noise yield the oxide trap density and the energy distribution of the grain boundary traps within the forbidden gap.
Implementations Impact on Iterative Image Processing for Embedded GPU

The emergence of low-power embedded Graphical Processing Units (GPUs) with high computation capabilities has enabled the integration of image processing chains in a wide variety of embedded systems. Various optimisation techniques are however needed in order to get the most out of an embedded GPU. This paper explores several optimisation methods for iterative stencil-like image processing algorithms on embedded NVIDIA GPUs using the Compute Unified Device Architecture (CUDA) API. We chose to focus our architectural optimisations on the TV-L1 algorithm, an optical flow estimation method based on total variation (TV) regularisation and the L1 norm. It is widely used as a model for more complex optical flow estimations and is used in many recent video processing applications. In this work we evaluate the impact of architecture-oriented optimisations on both execution time and energy consumption on several Nvidia Jetson GPU embedded boards. Results show a speedup up to $3\times$ compared to State-of-the-Art versions as well as a $2.6\times$ decrease in energy consumption.
Assessment Of Physico-Chemical Property Of Water Samples From Port Harcourt, Bonny And Opobo Coastal Areas For Sustainable Coastal Tourism Development In Rivers State, Nigeria.

The study evaluated some physico-chemical properties of water samples from Port Harcourt, Bonny and Opobo to determine the safety of water from the areas for sustainable coastal tourism development in Rivers State, Nigeria. Three water samples were collected with three sterilized plastic containers with a capacity of 25cl which were subjected to laboratory tests to know their constituents. The parameters tested were appearance, temperature, colour, turbidity, conductivity, PH, alkalinity, lead (Pb), Chromium (Cr), Cadmium (Cd), Ammonia, BODs and Dissolved Oxygen. The results of the water samples were compared with World Health Organization (WHO) water quality standard and the Nigeria National Water Quality standard to determine the safety of the water for human consumption and tourism development. The study revealed that Port Harcourt site has more prospects for tourism development more than Opobo study site because the Ph, alkalinity and BODs levels were lower than that of Opobo making the water safer except that the amount of dissolved oxygen was a little high in Opobo and turbidity was not detected in Opobo. The study revealed that Bonny water was very dense in appearance, dark brown in colour, highly turbid, basic and with mean concentration of the heavy metals – Lead, chromium and cadmium higher than the recommended World Health Organization (WHO) water quality standard and the Nigeria National Water Quality standard and therefore not safe for drinking and swimming. Treated portable water should be provided for the people of Port Harcourt, Opobo and Bonny especially people from Bonny area and development of tourism in the state to save the people and tourists from imminent danger of fecal contaminants and toxic substances.
Planar reconfigurable pattern antenna by reactive‐load switching

Reactive‐load switching is proposed to achieve a reconfigurable unidirectional pattern for a planar center‐loaded linear Yagi dipole array. Two crossed arrays of dipoles are printed on both sides of a substrate in order to implement a scanning pattern in the whole horizontal plane, and each group consists of one active dipole and a couple of reactive‐load parasitic dipoles. Due to the capacity of loaded value optimization, this antenna has good front‐to‐back ratio in its gain pattern; moreover, it has a compact structure and is suitable for integration with mobile terminals. Simulation and measurement are carried out to verify this design. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 47: 506–507, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.21212
Classification of Pulmonary Viruses X-ray and Detection of COVID-19 Based on Invariant of Inception-V 3 Deep Learning Model

Coronavirus (COVID-19) is a catastrophic illness that has already infected several million individuals and caused thousands of fatalities globally. Any technical technique that enables quick testing of the COVID-19 with high accuracy might be essential for healthcare providers. X-ray imaging is an easily available technique that might be a great option for its quick detection. This research was conducted to examine the usefulness of artificial intelligence (AI) to detect COVID-19 quickly and accurately from chest X-ray scans. The objective of this study is to provide a solid technical method for the automatic identification of COVID-19, Pneumonia, Lung opacity, and Normal digital X-ray scans using pretrained, deep learning algorithms while optimizing detection accuracy. Inception v3 with an additional added dense layer is used with image augmentation to train and validate the selected dataset. The obtained accuracy of 99.72% promises speedy detection of COVID-19.
System configuration of Human-in-the-loop Simulation for Level 3 Autonomous Vehicle using IPG CarMaker

The increasingly automated vehicles (AV) have increased the complexity of the testing methods and number of driven miles required to demonstrate the vehicle system’s reliability. Most modern autonomous driving systems also used deep neural networks which requires a large amount of data to develop. Physical driving alone to collect driving data and test system’s safety is no longer suitable for development of AV as this is costly, time consuming and could harm the road users if the safety system failed. This paper proposed human-in-the-loop simulation testing for evaluation of an autonomous vehicle using a 3D virtual vehicle driving platform that can be used for safety assessment of autonomous vehicle. The aim of this study is to establish human-computer interaction platform that can be used as safety testing for Level 3 autonomous vehicle whereby an emergency takeover is required during critical driving conditions. The proposed platform make use of IPG CarMaker to provide 3D virtual environment with accurate vehicle dynamics model, sensor model and environment model. We are able to interface the IPG CarMaker with Simulink and successfully developed a Simulink model that can interface a steering and pedal driving hardware with the virtual vehicle in the simulation. We can also collect driving data and simulation data from the IPG CarMaker as well as accessing the variable in the IPG CarMaker in real-time using Python. The recorded data can be used to train and fine-tune autonomous system based on machine learning.
Design and testing of a piezostack-actuated leading-edge flap

This paper presents the design and preliminary test results of a piezoelectric stack (piezostack) driven leading-edge flap actuator. The actuator uses six commercially available piezostacks with a curved contact tip for force and stroke profile tailoring. Force requirements were calculated using a quasi-steady aerodynamic model. Stroke amplification is achieved through a single lever. Initial results show that the current prototype is not ready to achieve the desired stroke output, but potential problems are identified and action is being take to rectify these problems.
Channel drop filter using a single defect in a 2-D photonic crystal slab waveguide

This paper describes a theoretical and experimental analysis of the channel drop filter using a single defect formed near the two-dimensional (2-D) photonic crystal slab waveguide. First, we calculate the transmission spectrum of a 2-D photonic crystal waveguide and show that high transmittance for a wide wavelength range (/spl sim/60 nm) is obtained in the 1.55-/spl mu/m region. We also show that a defect state having a wavelength within the high transmission wavelength range can be formed in the photonic bandgap by introducing a single defect of appropriate radius. Next, we fabricate several devices and show that the emission wavelength from each defect can be tuned by changing the defect radius. The measured tuning characteristics coincide well with the calculated results. From the near-field pattern of the device, we estimate the emission efficiency of the present device at almost a few tens percent. We clarify the structural condition in order to obtain the maximum output efficiency and show that tuning of emission wavelength while maintaining high output efficiency is possible by selecting appropriate defect radius and position. Based on these results, we propose an ultrasmall channel drop filter for a wavelength-division-multiplex optical communication system.
Delineation of the Direct Contribution of Candida auris ERG11 Mutations to Clinical Triazole Resistance

Candida auris is an emerging multidrug-resistant and health care-associated pathogen of urgent clinical concern. The triazoles are the most widely prescribed antifungal agents worldwide and are commonly utilized for the treatment of invasive Candida infections. ABSTRACT Resistance to fluconazole is one of clinical characteristics most frequently challenging the treatment of invasive Candida auris infections, and is observed among >90% of all characterized clinical isolates. In this work, the native C. auris ERG11 allele in a previously characterized fluconazole-susceptible clinical isolate was replaced with the ERG11 alleles from three highly fluconazole-resistant clinical isolates (MIC ≥256 mg/L), encoding the amino acid substitutions VF125AL, Y132F, and K143R, using Cas9-ribonucleoprotein (RNP) mediated transformation system. Reciprocally, the ERG11WT allele from the same fluconazole-susceptible clinical isolate, lacking any resistance-associated mutation, was introduced into a previously characterized fluconazole-resistant clinical isolate, replacing the native ERG11K143R allele, using the same methods. The resulting collection of strains was subjected to comprehensive triazole susceptibility testing, and the direct impact each of these clinically-derived ERG11 mutations on triazole MIC was determined. Introduction of each of the three mutant ERG11 alleles was observed to increase fluconazole and voriconazole MIC by 8- to 16-fold. The MIC for the other clinically available triazoles were not significantly impacted by any ERG11 mutation. In the fluconazole-resistant clinical isolate background, correction of the K143R encoding mutation led to a similar 16-fold decrease in fluconazole MIC, and 8-fold decrease in voriconazole MIC, while the MIC of other triazoles were minimally changed. Taken together, these findings demonstrate that mutations in C. auris ERG11 significantly contribute to fluconazole and voriconazole resistance, but alone cannot explain the substantially elevated MIC observed among clinical isolates of C. auris. IMPORTANCE Candida auris is an emerging multidrug-resistant and health care-associated pathogen of urgent clinical concern. The triazoles are the most widely prescribed antifungal agents worldwide and are commonly utilized for the treatment of invasive Candida infections. Greater than 90% of all C. auris clinical isolates are observed to be resistant to fluconazole, and nearly all fluconazole-resistant isolates of C. auris are found to have one of three mutations (encoding VF125AL, Y132F, or K143R) in the gene encoding the target of the triazoles, ERG11. However, the direct contribution of these mutations in ERG11 to fluconazole resistance and the impact these mutations may have the susceptibility of the other triazoles remains unknown. The present study seeks to address this knowledge gap and potentially inform the future application the triazole antifungals for the treatment of infections caused by C. auris.