Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptomic reveals the ferroptosis features of host response in a mouse model of Zika virus infection

Zika virus (ZIKV) is a neurotropic flavivirus. The outbreak of ZIKV in 2016 created a global health emergency. However, the underlying pathogenic mechanisms remain elusive. We investigated the host response features of in vivo replication in a mouse model of ZIKV infection, by performing a series of transcriptomic and bioinformatic analyses of ZIKV and mock‐infected brain tissue. Tissue damage, inflammatory cells infiltration and high viral replication were observed in the brain tissue of ZIKV infected mice. RNA‐Seq of the brain indicated the activation of ferroptosis pathways. Enrichment analysis of ferroptosis regulators revealed their involvement in pathways such as mineral absorption, fatty acid biosynthesis, fatty acid degradation, PPAR signaling pathway, peroxidase, and adipokinesine signalling pathway. We then identified 12 interacted hub ferroptosis regulators (CYBB, HMOX1, CP, SAT1, TF, SLC39A14, FTL, LPCAT3, FTH1, SLC3A2, TP53, and SLC40A1) that were related to the differential expression of CD8+ T cells, microglia and monocytes. CYBB, HMOX1, SALT, and SLAC40A1 were selected as potential biomarkers of ZIKV infection. Finally, we validated our results using RT‐qPCR and outside available datasets. For the first time, we proposed a possible mechanism of ferroptosis in brain tissue infected by ZIKV in mice and identified the four key ferroptosis regulators.
Total phenolic compounds and antioxidant activity in plants and application to face mask production

Plant foods are rich sources of antioxidants. The objective of this study was to investigate quantities of tolal phenolic compounds and antioxidants in plants as well as applications to face mask production. There were seven selected plants, namely Indian gooseberries, torch gingers, aloe veras, cashew leaves, passion fruits, gacs, and lemongrasses. Their phenolic compound quantities were 1,028.00, 1,017.20, 1,004.40, 1,021.60, 1,014.40, 996.00, and 944.00 micrograms/liter, respectively. When each plant was boiled at 60°C for 2 minutes, it was found that the phenolic compound quantities in all plants reduced to 960.40, 948.00, 920.00, 913.00, 900.40, 897.60, and 876.80 micrograms/liter, respectively. The torch gingers were selected and used to produce face masks due to the fact that the Indian gooseberries contained too high acid quantity. If the Indian gooseberries had been selected to produce facemasks, their phenolic compounds would necessarily have been diluted, resulting in decreasing antioxidants. In terms of the torch gingers, their extract contained 58.80% of antioxidants, and their antioxidant capacity was 18.146 µmol Trolox equivalents/g. Regarding the application of the torch ginger extract for face mask production and the skin prick test of the face masks made from the extract, it was found that 10 samples did not have pricks on their forearms or they were not allergic to the torch ginger extract in the face masks. The suitable solution formula to make the face masks was 35% of the torch ginger extract and 65% of moisturizer.
Millimeter- and Submillimeter-Wave Rotational Spectra of Rare Hydrogen Sulfide Isotopomers

Pure rotational transitions of the hydrogen sulfide isotopomers H233S, H234S, and H236S have been recorded with high resolution in the frequency range between 165 and 1072 GHz in natural abundance. Together with previously reported FIR pure rotational transitions of H233S and H234S, these data are used to derive an improved set of rotational and centrifugal distortion constants. For the H233S species, electric quadrupole and magnetic spin-rotation hfs constants are also determined. The new data allow accurate frequency predictions throughout the submillimeter-wave region for the two isotopomers H234S and H233S, including hyperfine splittings for H233S. These predictions are of astrophysical relevance.
A Study of the Relationship between New Mainstream Chinese Cinema and the Chinese Cultural Identity of the Youth in Hong Kong

This paper mainly explores the impact of new mainstream Chinese cinema on the Youth in Hong Kong's cultural identity. "Do Hong Kong youth deconstruct the messages conveyed by the new mainstream Chinese cinema when they watch it? Does the film medium strengthen and weaken the Youth in Hong Kong's cultural identity, and thus affect the Youth in Hong Kong's own identity? ". In order to measure and analyze it, this paper constructs a model of the influence of the film medium on identity, in which we use the concept of ethnic identity salience which is highly relevant to cultural identity. Furthermore, we propose four themes (variables) that can measure ethnic identity salience, namely ethnic identity, achieving ethnic identity, ethnic practices, and orientation towards intra-ethnic membership. Under this model, the medium of film affects the four themes of ethnic identity, achievement of ethnic identity, ethnic practices, and orientation towards intra-ethnic membership simultaneously, thus influencing the degree of ethnic identity salience and hence the identity of the Youth in Hong Kong. This paper adopts an experimental method to measure people's ethnic identity salience before and after viewing the film.
Electronic structure of some 3D transition-metal pyrites

Bremsstrahlung Isochromat spectra of FeS2, NiS2 NiS1.2Se0. 8 and NiSe2 are reported. These are the first direct experimental evidence for a sharp antibonding p-like state above the Fermi level. A comparison is made with experimental results in the literature. For FeS2 band structure calculations are also presented; these are in good agreement with experiment. The authors show that it is necessary in this calculation to include 'empty spheres' when using a muffin-tin approximation. This is because the pyrite crystal structure is far from close packed. Furthermore, they briefly discuss the electrical and magnetic properties of the compounds.
Dissipative preparation of three-atom entanglement state via quantum feedback control

Two schemes are presented for generating steady three-atom Greenberger–Horne–Zeilinger and W states in a strongly dissipative cavity via quantum feedback control. The quantum feedback control is only applied to a single atom based on quantum-jump detection to improve the fidelity of the target state. Thus, cavity decay plays a key role in obtaining the target state. The required interaction time need not be accurately controlled.
Fault-Free: A Framework for Analysis and Mitigation of Stuck-at-Fault on Realistic ReRAM-Based DNN Accelerators

Resistive RAM(ReRAM) is gaining attention as a suitable memory platform for accelerating deep neural networks(DNNs) in an energy-efficient way. However, energy-efficient ReRAM-based DNN accelerators suffer from serious Stuck-At-Fault(SAF) issues that significantly degrade the inference accuracy. SAF is a device-level non-ideality, and the problems of SAF worsen in the realistic ReRAM with low cell resolution. To address the problem in the realistic ReRAM, we present a framework for mitigating SAF on ReRAM-based accelerators(Fault-free). We first analyze the impact of SAF on low-resolution cells. Based on the analysis, we present offline compilation, which drastically reduces the impact of SAF on inference accuracy. At the first stage, we extract indices of distorted weights due to SAF. For extracted weights, fault-aware weight decomposition and closest value mapping are applied to minimize the error of weights. In the online phase, the target DNN model is executed on the ReRAM-based accelerator along with lightweight compensation units. The online compensation is selectively performed for a small portion of weights to reduce the hardware overhead. With the proposed framework, the ReRAM-based accelerator successfully ensures the inference accuracy of various DNN models with an average area of 5% and an energy overhead of 0.8% from an ideal ReRAM-based accelerator.
NeuRes: Highly Activated Neurons Responses Transfer via Distilling Sparse Activation Maps

In recent years, Knowledge Distillation has obtained a significant interest in mobile, edge, and IoT devices due to its ability to transfer knowledge from the large and complex teacher to the lightweight student network. Intuitively, Knowledge Distillation refers to forcing the student to mimic the teacher’s neuron responses to improve the generalization of the student by deploying the distillation losses as the regularization terms. However, the non-linearity of the hidden layers and the high dimensionality of the feature maps make the knowledge transfer a rigorous task. Though numerous methods have been proposed to transfer the teacher’s neuron responses in the form of diverse feature characteristics such as attention, contrastive representation, and so on, to the best of our knowledge, no prior works considered feature-level non-linearity during distillation. In this work, we ask, does feature-level non-linearity-based approaches can improve student performance? For investigating those concerns, we propose a novel knowledge distillation technique called the NeuRes (Neuron’s Responses) via distilling the Sparse Activation Maps (SAMs) to transfer the highly activated Neurons Responses to the student to enhance the representation capability. Proposed NeuRes selects the highly activated neuron responses that produce Sparse Activation Maps (SAMs) while transferring the knowledge based on activation normalization. Our proposed NeuRes also transfers the translation invariant features using auxiliary classifiers and augmented data to improve students’ generalization. The detailed ablation studies and extensive experiments on model compression, transferability, adversarial robustness, and few-shot learning verify that NeuRes outperforms state-of-the-art distillation techniques on the standard benchmark datasets.
Mie scattering model for dual-axes confocal architecture

Tissue scattering has a significant effect on the image resolution and light collection efficiency in confocal microscopy. The dual-axes (DA) confocal architecture has many advantages including high axial resolution with low numerical aperture lenses and long working distance for use in vivo as a microendoscope. In addition, less scattered light along the illumination path may be collected and introduced as noise. In this paper, we use Monte Carlo tissue scattering simulations to compare the dual-axes and conventional single-axis (SA) configurations. Simulation results show that the axial response for the dual axes configuration varies with pinhole size and optical thickness of scattering media in a way that differs from the single axis architecture. The DA configuration is able to filter out efficiently multiply-scattered photons and out-of-focus light, thus allowing imaging with greater tissue penetration depths to provide vertical crosssectional images, which has significant implications for in vivo imaging.
Development of Korean Food Image Classification Model Using Public Food Image Dataset and Deep Learning Methods

Food image classification is useful in diet management apps for personal health management. Various methods for classifying food images in a particular country have been proposed in multiple studies. However, knowledge of Korean food image classification is limited. The objective of this study was to train a classification model for Korean food images. To train the classification model, we collected Korean food images from the AI-Hub platform, a public food image dataset. The images were pre-processed and augmented for model training. The proposed model was evaluated in an experiment using a Korean food image dataset and effectively classified Korean food images based on transfer learning. The findings of the study revealed that the model’s performance in classifying food images depended on the type of food. The findings have implications for the classification model training process using CNN and the Korean public food image dataset. Future work is required to improve the performance of a classification model, especially as it pertains to its poor performance for some food image types.
Modeling room-temperature lasing spectra of 1.3-μm self-assembled InAs∕GaAs quantum-dot lasers: Homogeneous broadening of optical gain under current injection

We studied the injection current dependence of room-temperature lasing spectra of a 1.3-μm self-assembled InAs∕GaAs quantum-dot laser both experimentally and theoretically. Starting from the ground-state lasing with a few longitudinal modes, the spectra showed splitting, broadening, excited-state lasing, and quenching of the ground-state lasing as the current increased. We could explain this unique current dependence by numerical simulation based on our quantum-dot laser theory, taking into account the inhomogeneous and homogeneous broadening of the optical gain as well as the carrier relaxation processes in the spatially isolated quantum dots. Through the simulation, we found that the homogeneous broadening of the ground state is kept between 5 and 10 meV under the ground-state lasing, while it increases up to 20 meV under the excited-state lasing.
Role of Ezrin in Asthma-Related Airway Inflammation and Remodeling

Ezrin is an actin binding protein connecting the cell membrane and the cytoskeleton, which is crucial to maintaining cell morphology, intercellular adhesion, and cytoskeleton remodeling. Asthma involves dysfunction of inflammatory cells, cytokines, and airway structural cells. Recent studies have shown that ezrin, whose function is affected by extensive phosphorylation and protein interactions, is closely associated with asthma, may be a therapeutic target for asthma treatment. In this review, we summarize studies on ezrin and discuss its role in asthma-related airway inflammation and remodeling.
Discussion: Fuzzy Logic: Better Science? Or Better Engineering?

Can statisticians afford to ignore fuzzy logic? No! Fuzzy logic appeals to many engineers in places where probabilistic solutions have not penetrated. Judging from the number of papers in recent workshops like "Uncertainty in Artificial Intelligence" and "Artificial Intelligence and Statistics," there are many traditionally "statistical" problems (e.g., control, classification, and decision analysis) for which researchers are using nonstatistical models. We statisticians must look at nonprobabilistic approaches to problem solving, such as fuzzy logic, if only to understand how we can do a better job of marketing statistics to engineers. I would like to thank Laviolette, Seaman, Barrett, and Woodall (hereafter LSBW) for forcing me to go through the effort of evaluating fuzzy logic. I, like many other statisticians, have been all too tempted to say "I don't understand" fuzzy logic (meaning, "I think fuzzy logicians are slightly potty, but I haven't looked into it carefully enough to say that on the record"). Laying out fuzzy and probabilistic models for the same problem side by side, as LSBW do, helps me compare the two approaches and understand the strengths and weaknesses of each.
Energy Shift During Ion Extraction from an ICP Source

In this work, the deviation of energy distribution function of energetic ions from the predetermined value in an inductively coupled plasma (ICP) ion gun source is discussed. An abnormal plasma potential increase at an extraction voltage 400 V caused a beam energy shift of up to 50 eV compared to the preset value. The ion energy peak position was found to be more aected by pressure at higher extraction voltages on the acceleration grid. The energy of primary and secondary ions was measured with an ion energy analyzer. The evolution of the ion energy distribution function during the accelerating voltage change was studied in the pressure range from 3 ◊ 10 3 to 1.1 ◊ 10 2
Platoon Cooperation Across Carriers: From System Architecture to Coordination

Truck platooning is a well-studied technology that has the potential to reduce both the environmental impact and operational costs of trucks. The technology has matured over the last 20 years, and the commercial rollout of platooning is approaching. Cooperation across carriers is essential for the viability of platooning; otherwise, many platooning opportunities are lost. We first present a cross-carrier platooning system architecture in which many carriers cooperate in forming platoons through a platoon-hailing service. Then, we present a cross-carrier platoon coordination approach in which each carrier optimizes its platooning plans according to the predicted plans of other carriers. A profit-sharing mechanism to even out the platooning profit in each platoon is embedded in the platoon coordination approach. Finally, a simulation study over the Swedish road network is performed to evaluate the potential of platooning under realistic conditions. The simulation study shows that the energy consumption of trucks in Sweden can be reduced by 5.4% due to platooning and that cooperation across carriers is essential to achieve significant platooning benefits.
MACHINE LEARNING AS AN ALTERNATIVE TO 3D PHOTOMODELING EMPLOYED IN ARCHITECTURAL SURVEY AND AUTOMATIC DESIGN MODELLING

Abstract. This paper presents some experiments on the use of an alternative technique, Nerf, based on artificial intelligence, which can be used in the survey of architectural structures or parts of them. The Nvidia video cards supported by the new RTX architectures are now able to manage an enormous amount of data both in the calculation of lighting and the rendering of digital shaders, and in the management of the number of polygons that can be displayed in real time in the scene. The support of artificial intelligence has further improved the three-dimensional digitization process in order to support the hardware power of algorithms that use neural networks to optimize and reduce calculation times, improving various aspects of the graphics and also of the digital representation, also influencing the representation on “image based” 3D acquisition methods, currently the most used low-cost systems in the photomodeling of objects or three-dimensional scenes. At the current state of the art, many commercial companies and research organizations, first Nvidia with its Instant Nerf, are betting on algorithms based on the Neural Radiance Field. The paper highlights the criticalities of this new system and shows the discrete results and the expandable research scenarios that can involve the impossible survey with photomodeling methodology related to works of art or architecture, due to the intrinsic nature of the materials that they compose them or because it is impossible or very difficult to photograph them.
The Weissella Genus: Clinically Treatable Bacteria with Antimicrobial/Probiotic Effects on Inflammation and Cancer

Weissella is a genus earlier considered a member of the family Leuconostocaceae, which was reclassified into the family Lactobacillaceae in 1993. Recently, there have been studies emphasizing the probiotic and anti-inflammatory potential of various species of Weissella, of which W. confusa and W. cibaria are the most representative. Other species within this genus include: W. paramesenteroides, W. viridescens, W. halotolerans, W. minor, W. kandleri, W. soli, W. ghanensis, W. hellenica, W. thailandensis, W. fabalis, W. cryptocerci, W. koreensis, W. beninensis, W. fabaria, W. oryzae, W. ceti, W. uvarum, W. bombi, W. sagaensis, W. kimchi, W. muntiaci, W. jogaejeotgali, W. coleopterorum, W. hanii, W. salipiscis, and W. diestrammenae. Weissella confusa, W. paramesenteroides, W. koreensis, and W. cibaria are among the few species that have been isolated from human samples, although the identification of these and other species is possible using metagenomics, as we have shown for inflammatory bowel disease (IBD) and healthy controls. We were able to isolate Weissella in gut-associated bacteria (post 24 h food deprivation and laxatives). Other sources of isolation include fermented food, soil, and skin/gut/saliva of insects/animals. With the potential for hospital and industrial applications, there is a concern about possible infections. Herein, we present the current applications of Weissella on its antimicrobial and anti-inflammatory mechanistic effects, the predisposing factors (e.g., vancomycin) for pathogenicity in humans, and the antimicrobials used in patients. To address the medical concerns, we examined 28 case reports focused on W. confusa and found that 78.5% of infections were bacteremia (of which 7 were fatal; 1 for lack of treatment), 8 were associated with underlying malignancies, and 8 with gastrointestinal procedures/diseases of which 2 were Crohn’s disease patients. In cases of a successful resolution, commonly administered antibiotics included: cephalosporin, ampicillin, piperacillin-tazobactam, and daptomycin. Despite reports of Weissella-related infections, the evolving mechanistic findings suggest that Weissella are clinically treatable bacteria with emerging antimicrobial and probiotic benefits ranging from oral health, skin care, obesity, and inflammatory diseases to cancer.
ZnO nanoparticles as drug delivery agent for photodynamic therapy

Multidrug resistance (MDR) limits the success of many tumoricidal drugs. Non-significant accumulation of the drug into the target site is one major problem in photodynamic therapy. Nanoparticles are extensively used as efficient drug carriers in various local infectious and premalignant biological tissues. Due to their unique physical and chemical properties, PEGylated zinc oxide nanoparticles (ZnO NPs) exhibit high drug loading capacities, sustained drug release profiles and long-term anticancer efficacy. (Polyethylene glycol) PEG-zinc oxide nanoparticles were synthesized using the aquis chemical technique. Morphology/structural analysis of the said nanoparticles was confirmed by applying many techniques, e.g. scanning electron microscopy (SEM) and XRD. Average grain size of the nanoparticles, which was ≈100 nm, was calculated by applying the Scherrer formula. The PEGylated ZnO NPs were loaded with protoporphyrin IX (PpIX) to enhance the capability of drug carrying potency. Current work focused on the comparison of the cell killing effect (apoptosis/necrosis) by functionalizing different nanostructures via PEGylated ZnO NPs and bare ZnO NPs using the free-standing drug delivery procedure. ZnO NPs were used as anticancer drug vehicles because of their biocompatibility and bio-safety profile. The apoptotic effect of PEGylated tumoricidal drugs has been studied in human muscle carcinoma (RD cell line) in the dark as well as under laser exposure. It was concluded that PpIX localization was a significant time greater using encapsulation as compared to a conventional drug delivery system. This new technique may find excellent opportunities in the field of nanomedicine, especially in a multidrug delivery system.
Two-Dimensional Wavelets with Complementary Filter Banks

In this paper, the Two-Dimensional (2D) Complementary Filter (CF) Banks, a signal processing technique which can be used to get scaling and wavelets functions, are presented. The 2D multirate signal processing theory and complementary filters properties are the base of CF Banks, permitting us to consider different types of sampling and filters. Two-dimensional nonseparable quincunx, rectangular and circular complementary filters are designed for an alias free decimation and interpolation. When CF bank is implemented with quincunx sampling and filters, perfect reconstruction is achieved and although it is not reached in others cases, the analysis and synthesis are performed without aliasing. The CF banks are related with wavelet theory and procedures to get 2D scaling and bandpass wavelets functions from the L-level filter bank tree structure iteratively are shown. We illustrate scaling and wavelets functions convergence as the level of decomposition increases.