bluuebunny/crossref_metadata_2025 huggingface dataset:
FABRICATION OF HYDROPHOBIC COATINGS ON BETULA ALNOIDES WOOD WITH DIFFERENT ALKYLTRICHLOROSILANES
Authors: JIAN YULAN , WAN HUI , XU KAIMENG , ZHANG YARU , XIE LINKUN
Published: November 2022

To study the hydrophobic properties of Betula alnoides wood modified by alkyltrichlorosilanes, four alkyltrichlorosilanes with different chain lengths were used to prepare hydrolytic solutions by adding 0.25% (v/v) of alkyltrichlorosilane to anhydrous toluene, and the wood samples were immersed in the hydrolytic solutions for 4 h. The surface chemical compositions of the samples were analyzed by X-ray photoelectron spectroscopy (XPS) and Varian 640-IR Fourier Infrared Spectrometer (ATR-FTIR), the surface morphology of the samples was observed by scanning electron microscopy (SEM), and the wettability of the modified wood was investigated using an optical contact angle goniometer. The results demonstrated that treatment with alkyltrichlorosilanes introduced Si and low surface energies of –CH2 and –CH3 on the surface of Betula alnoides wood. The –CH2 and –CH3 content increased with the increase in chain length. Alkyltrichlorosilanes formed a different micro or nanoscale roughness on the surfaces of the wood samples. The water contact angles of all coatings of alkyltrichlorosilanes are greater than [Formula: see text], and greater than [Formula: see text] after 180 s. The water absorption decreases with the increase in chain length. The water absorption of the uncoated sample is [Formula: see text] wt.%, while those of samples modified by MTCS and OTCS are [Formula: see text] wt.% and [Formula: see text] wt.%, respectively.
Casimir traversable wormholes for GUP corrected energy densities in f (T) gravity
Authors: Rani Shamaila , Sulehri Muhammad Bilal Amin , Jawad Abdul , Zafar Usman
Published: November 2022

Traversable wormholes are always supported by negative energy and therefore an exotic matter source is required for their principle existence. In this work, we consider Casimir energy density as an exotic matter source in the framework of f (T) gravity. In this way, we examine the behavior of shape function, equation of state parameters, energy conditions and stability conditions for wormhole geometry in teleparallel and f (T) gravity. We also assume three different generalized uncertainty principle corrected Casimir wormhole models. We analyze the effect of the generalized uncertainty principle minimal parameter on the constructed wormhole properties in f (T) gravity.
Dark energy density and Israel–Stewart (IS) bulk viscosity model
Authors: Sadatian S. Davood , Saburi A.
Published: November 2022

In this paper, we investigate the thermodynamics of a dark energy bulk viscosity model as a cosmic fluid. In this regard, the two theories of Eckart and Israel–Stewart (IS) are the bases of our work. Therefore, we first investigate the thermodynamics of cosmic fluids in the dark energy bulk viscosity model and the general relationships. Then, we express the thermodynamic relationships of Eckart’s theory. Due to the basic equations of Eckart’s theory and Friedmann’s equations, we consider two states, one is [Formula: see text] (standard) and the other is [Formula: see text] (non-standard). In the standard state, we define the pressure [Formula: see text], energy density [Formula: see text] and bulk viscosity coefficient [Formula: see text] of the cosmic fluid in terms of cosmic time and we obtain its relations. We also mention that in this standard state, because of [Formula: see text], the value of [Formula: see text] is zero, so [Formula: see text] is not defined in this state. But in the non-standard case [Formula: see text], the bulk viscosity coefficient [Formula: see text] is zero and only the scale factor, pressure and energy density of the cosmic fluid are defined. We also consider two states of constant and variable bulk viscosity coefficients and obtain three Hubble constant parameters and scale factor in terms of cosmic time, and energy density in terms of scale factor. In the state of variable bulk viscosity coefficient, we consider the viscosity coefficient as the power law from energy density [Formula: see text], which is [Formula: see text] and a constant. Following this, we discuss about the dissipative effects of cosmic fluids and examine the effects of energy density for dark energy in the IS theory. The results are comprehensively presented in Tables 1 and 2. Also, according to observational constraints, the results of the likelihood analysis for the IS viscous model are summarized in Table 3.
Do Green Technology Innovation, Renewable Energy Consumption and Renewable Energy Investment Improve Environmental Quality?
Authors: Tan Wenting , Cao Teng
Published: November 2022

This paper discusses the effects of green technology innovation, renewable energy consumption and renewable energy investment on environmental quality. Panel data covering 81 countries from 2001 to 2020 are used to estimate the effects. The results indicate the following: First, at the total sample level, the effect of green technology innovation, renewable energy consumption and renewable energy investment on Carbon dioxide (CO[Formula: see text] emissions is significantly negative at the level of 10–1%; Second, at the subsample level, the green technology innovation and renewable energy consumption of non-Belt and Road (B&R) and high-income countries significantly affect CO2 emissions; while the green technology innovation and renewable energy consumption of middle- and low-income and B&R countries have no significant effect on CO2 emissions; Third, the endogeneity and robustness tests of the model verified that this empirical process is credible. Based on the above results, this paper proposes a series of policy implications needed to achieve carbon emission reduction and environmental quality improvement.
Consecutive quadratic residues in Beatty sequences
Authors: Jing Mengyao , Liu Huaning
Published: November 2022

Let [Formula: see text] be an odd prime. We study the distribution of consecutive quadratic residues modulo [Formula: see text] in non-homogeneous Beatty sequences [Formula: see text], where [Formula: see text] and [Formula: see text] is irrational. Furthermore, we study the pseudorandom properties of sequences formed by the Legendre symbol and Beatty sequences. In addition, we give upper bounds for certain character sums over [Formula: see text].
Orthogonal Eisenstein series and theta lifts
Authors: Kiefer Paul
Published: November 2022

We show that the additive Borcherds lifts of vector-valued non-holomorphic Eisenstein series are orthogonal non-holomorphic Eisenstein series for [Formula: see text]. Using this we give another proof that they have a meromorphic continuation, calculate their Fourier expansion and show that they have a functional equation analogous to the classical case. Moreover, we will investigate the image of Borcherds lift and give a sufficient condition for surjectivity.
An effective adaptive algorithm for linear fractional dynamical systems
Authors: Bu Weiping , Qu Min
Published: November 2022

This study proposes a time-stepping [Formula: see text] scheme to approximate the linear fractional dynamical systems based on nonuniform mesh. The developed numerical scheme is unconditionally stable, and exhibits second-order accuracy when the suitable graded mesh is used. A posteriori error estimation is derived for the obtained numerical scheme and the corresponding adaptive algorithm is devised. Finally, two numerical examples are provided to demonstrate the effectiveness of our approach and verify the theoretical results.
Parameters to Assess the Operation of Thrust Vector Control Systems in Jet Engines
Authors: Boryaev A. A.
Published: November 2022

This paper discusses the parameters for evaluating the effectiveness of various methods of controlling the thrust vector of jet engines. An approach to the multi-parametric optimization of the nozzle structure and the parameters of jet injection into the supersonic flow is developed. The approach is based on a numerical model for a turbulent flow of a viscous compressible gas. A classification of parameters is proposed for evaluating methods for controlling the thrust vector of jet engines.
MeshTaichi
Authors: Yu Chang , Xu Yi , Kuang Ye , Hu Yuanming , Liu Tiantian
Published: November 2022

Meshes are an indispensable representation in many graphics applications because they provide conformal spatial discretizations. However, mesh-based operations are often slow due to unstructured memory access patterns. We propose MeshTaichi, a novel mesh compiler that provides an intuitive programming model for efficient mesh-based operations. Our programming model hides the complex indexing system from users and allows users to write mesh-based operations using reference-style neighborhood queries. Our compiler achieves its high performance by exploiting data locality. We partition input meshes and prepare the wanted relations by inspecting users' code during compile time. During run time, we further utilize on-chip memory (shared memory on GPU and L1 cache on CPU) to access the wanted attributes of mesh elements efficiently. Our compiler decouples low-level optimization options with computations, so that users can explore different localized data attributes and different memory orderings without changing their computation code. As a result, users can write concise code using our programming model to generate efficient mesh-based computations on both CPU and GPU backends. We test MeshTaichi on a variety of physically-based simulation and geometry processing applications with both triangle and tetrahedron meshes. MeshTaichi achieves a consistent speedup ranging from 1.4× to 6×, compared to state-of-the-art mesh data structures and compilers.
Interactive Exploration of Tension-Compression Mixed Shells
Authors: Miki Masaaki , Mitchell Toby
Published: November 2022

Achieving a pure-compression stress state is considered central to the form-finding of shell structures. However, the pure-compression assumption restricts the geometry of the structure's plan in that any free boundary edges cannot bulge outward. Allowing both tension and compression is essential so that overhanging leaves can stretch out toward the sky. When performing tension-compression mixed form-finding, a problem with boundary condition (BC) compatibility arises. Since the form-finding equation is hyperbolic, boundary information propagates along the asymptotic lines of the stress function. If conflicting BC data is prescribed at either end of an asymptotic line, the problem becomes ill-posed. This requires a user of a form-finding method to know the solution in advance. By contrast, pure-tension or pure-compression problems are elliptic and always give solutions under any BCs sufficient to restrain rigid motion. To solve the form-finding problem for tension-compression mixed shells, we focus on the Airy's stress function, which describes the stress field in a shell. Rather than taking the stress function as given, we instead treat both the stress function and the shell as unknowns. This doubles the solution variables, turning the problem to one that has an infinity of different solutions. By enforcing equilibrium in the shell interior and prescribing the correct
matching pairs
of BCs to both the stress function and the shell, a stress function and shell can be simultaneously found such that equilibrium is satisfied everywhere in the shell interior and thus automatically has compatible BCs by construction. The problem of a potentially over-constrained form-finding is thus avoided by expanding the solution space and creating an under-determined problem. By varying inputs and repeatedly searching for stress function-shell pairs that fall within the solution space, a user is allowed to interactively explore the possible forms of tension-compression mixed shells under the given plan of the shell.
Video-Driven Neural Physically-Based Facial Asset for Production
Authors: Zhang Longwen , Zeng Chuxiao , Zhang Qixuan , Lin Hongyang , Cao Ruixiang , Yang Wei , Xu Lan , Yu Jingyi
Published: November 2022

Production-level workflows for producing convincing 3D dynamic human faces have long relied on an assortment of labor-intensive tools for geometry and texture generation, motion capture and rigging, and expression synthesis. Recent neural approaches automate individual components but the corresponding latent representations cannot provide artists with explicit controls as in conventional tools. In this paper, we present a new learning-based, video-driven approach for generating dynamic facial geometries with high-quality physically-based assets. For data collection, we construct a hybrid multiview-photometric capture stage, coupling with ultra-fast video cameras to obtain raw 3D facial assets. We then set out to model the facial expression, geometry and physically-based textures using separate VAEs where we impose a global MLP based expression mapping across the latent spaces of respective networks, to preserve characteristics across respective attributes. We also model the delta information as wrinkle maps for the physically-based textures, achieving high-quality 4K dynamic textures. We demonstrate our approach in high-fidelity performer-specific facial capture and cross-identity facial motion retargeting. In addition, our multi-VAE-based neural asset, along with the fast adaptation schemes, can also be deployed to handle in-the-wild videos. Besides, we motivate the utility of our explicit facial disentangling strategy by providing various promising physically-based editing results with high realism. Comprehensive experiments show that our technique provides higher accuracy and visual fidelity than previous video-driven facial reconstruction and animation methods.
Motion In-Betweening via Two-Stage Transformers
Authors: Qin Jia , Zheng Youyi , Zhou Kun
Published: November 2022

We present a deep learning-based framework to synthesize motion in-betweening in a two-stage manner. Given some context frames and a target frame, the system can generate plausible transitions with variable lengths in a non-autoregressive fashion. The framework consists of two Transformer Encoder-based networks operating in two stages: in the first stage a Context Transformer is designed to generate rough transitions based on the context and in the second stage a Detail Transformer is employed to refine motion details. Compared to existing Transformer-based methods which either use a complete Transformer Encoder-Decoder architecture or additional 1D convolutions to generate motion transitions, our framework achieves superior performance with less trainable parameters by only leveraging the Transformer Encoder and masked self-attention mechanism. To enhance the generalization of our transformer-based framework, we further introduce Keyframe Positional Encoding and Learned Relative Positional Encoding to make our method robust in synthesizing longer transitions exceeding the maximum transition length during training. Our framework is also artist-friendly by supporting full and partial pose constraints within the transition, giving artists fine control over the synthesized results. We benchmark our framework on the LAFAN1 dataset, and experiments show that our method outperforms the current state-of-the-art methods at a large margin (an average of 16% for normal-length sequences and 55% for excessive-length sequences). Our method trains faster than the RNN-based method and achieves a four-time speedup during inference. We implement our framework into a production-ready tool inside an animation authoring software and conduct a pilot study to validate the practical value of our method.
High-Order Directional Fields
Authors: Boksebeld Iwan , Vaxman Amir
Published: November 2022

We introduce a framework for representing face-based directional fields of an arbitrary piecewise-polynomial order. Our framework is based on a primal-dual decomposition of fields, where the exact component of a field is the gradient of piecewise-polynomial conforming function, and the coexact component is defined as the adjoint of a dimensionally-consistent discrete curl operator. Our novel formulation sidesteps the difficult problem of constructing high-order non-conforming function spaces, and makes it simple to harness the flexibility of higher-order finite elements for directional-field processing. Our representation is structure-preserving, and draws on principles from finite-element exterior calculus. We demonstrate its benefits for applications such as Helmholtz-Hodge decomposition, smooth PolyVector fields, the vector heat method, and seamless parameterization.
Position-Based Surface Tension Flow
Authors: Xing Jingrui , Ruan Liangwang , Wang Bin , Zhu Bo , Chen Baoquan
Published: November 2022

This paper presents a novel approach to simulating surface tension flow within a position-based dynamics (PBD) framework. We enhance the conventional PBD fluid method in terms of its surface representation and constraint enforcement to furnish support for the simulation of interfacial phenomena driven by strong surface tension and contact dynamics. The key component of our framework is an on-the-fly local meshing algorithm to build the local geometry around each surface particle. Based on this local mesh structure, we devise novel surface constraints that can be integrated seamlessly into a PBD framework to model strong surface tension effects. We demonstrate the efficacy of our approach by simulating a multitude of surface tension flow examples exhibiting intricate interfacial dynamics of films and drops, which were all infeasible for a traditional PBD method.
MIPNet
Authors: Gauthier Alban , Faury Robin , Levallois Jérémy , Thonat Théo , Thiery Jean-Marc , Boubekeur Tamy
Published: November 2022

We present MIPNet, a novel approach for SVBRDF mipmapping which preserves material appearance under varying view distances and lighting conditions. As in classical mipmapping, our method explicitly encodes the multiscale appearance of materials in a SVBRDF mipmap pyramid. To do so, we use a tensor-based representation, coping with gradient-based optimization, for encoding anisotropy which is compatible with existing real-time rendering engines. Instead of relying on a simple texture patch average for each channel independently, we propose a cascaded architecture of multilayer perceptrons to approximate the material appearance using only the fixed material channels. Our neural model learns simple mipmapping filters using a differentiable rendering pipeline based on a rendering loss and is able to transfer signal from normal to anisotropic roughness. As a result, we obtain a drop-in replacement for standard material mipmapping, offering a significant improvement in appearance preservation while still boiling down to a single per-pixel mipmap texture fetch. We report extensive experiments on two distinct BRDF models.
ICARUS
Authors: Rao Chaolin , Yu Huangjie , Wan Haochuan , Zhou Jindong , Zheng Yueyang , Wu Minye , Ma Yu , Chen Anpei , Yuan Binzhe , Zhou Pingqiang , Lou Xin , Yu Jingyi
Published: November 2022

The practical deployment of Neural Radiance Fields (NeRF) in rendering applications faces several challenges, with the most critical one being low rendering speed on even high-end graphic processing units (GPUs). In this paper, we present ICARUS, a specialized accelerator architecture tailored for NeRF rendering. Unlike GPUs using general purpose computing and memory architectures for NeRF, ICARUS executes the complete NeRF pipeline using dedicated plenoptic cores (PLCore) consisting of a positional encoding unit (PEU), a multi-layer perceptron (MLP) engine, and a volume rendering unit (VRU). A PLCore takes in positions & directions and renders the corresponding pixel colors without any intermediate data going off-chip for temporary storage and exchange, which can be time and power consuming. To implement the most expensive component of NeRF, i.e., the MLP, we transform the fully connected operations to approximated reconfigurable multiple constant multiplications (MCMs), where common subexpressions are shared across different multiplications to improve the computation efficiency. We build a prototype ICARUS using Synopsys HAPS-80 S104, a field programmable gate array (FPGA)-based prototyping system for large-scale integrated circuits and systems design. We evaluate the power-performancearea (PPA) of a PLCore using 40nm LP CMOS technology. Working at 400 MHz, a single PLCore occupies 16.5
mm
2
and consumes 282.8 mW, translating to 0.105 uJ/sample. The results are compared with those of GPU and tensor processing unit (TPU) implementations.
Pupil-Aware Holography
Authors: Chakravarthula Praneeth , Baek Seung-Hwan , Schiffers Florian , Tseng Ethan , Kuo Grace , Maimone Andrew , Matsuda Nathan , Cossairt Oliver , Lanman Douglas , Heide Felix
Published: November 2022

Holographic displays promise to deliver unprecedented display capabilities in augmented reality applications, featuring a wide field of view, wide color gamut, spatial resolution, and depth cues all in a compact form factor. While emerging holographic display approaches have been successful in achieving large étendue and high image quality as seen by a camera, the large étendue also reveals a problem that makes existing displays impractical: the sampling of the holographic field by the eye pupil. Existing methods have not investigated this issue due to the lack of displays with large enough étendue, and, as such, they suffer from severe artifacts with varying eye pupil size and location.

We show that the holographic field as sampled by the eye pupil is highly varying for existing display setups, and we propose pupil-aware holography that maximizes the perceptual image quality irrespective of the size, location, and orientation of the eye pupil in a near-eye holographic display. We validate the proposed approach both in simulations and on a prototype holographic display and show that our method eliminates severe artifacts and significantly outperforms existing approaches.
Deep Adaptive Sampling and Reconstruction Using Analytic Distributions
Authors: Salehi Farnood , Manzi Marco , Roethlin Gerhard , Weber Romann , Schroers Christopher , Papas Marios
Published: November 2022

We propose an adaptive sampling and reconstruction method for offline Monte Carlo rendering. Our method produces sampling maps constrained by a user-defined budget that minimize the expected future denoising error. Compared to other state-of-the-art methods, which produce the necessary training data on the fly by composing pre-rendered images, our method samples from analytic noise distributions instead. These distributions are compact and closely approximate the pixel value distributions stemming from Monte Carlo rendering. Our method can efficiently sample training data by leveraging only a few per-pixel statistics of the target distribution, which provides several benefits over the current state of the art. Most notably, our analytic distributions' modeling accuracy and sampling efficiency increase with sample count, essential for high-quality offline rendering. Although our distributions are approximate, our method supports joint end-to-end training of the sampling and denoising networks. Finally, we propose the addition of a global summary module to our architecture that accumulates valuable information from image regions outside of the network's receptive field. This information discourages sub-optimal decisions based on local information. Our evaluation against other state-of-the-art neural sampling methods demonstrates denoising quality and data efficiency improvements.
Shape from Release
Authors: Panetta Julian , Mohammadian Haleh , Luci Emiliano , Babaei Vahid
Published: November 2022

Objects with different shapes can dissolve in significantly different ways inside a solution. Predicting different shapes' dissolution dynamics is an important problem especially in pharmaceutics. More important and challenging, however, is controlling the dissolution via shape,
i.e.
, designing shapes that lead to a desired release behavior of materials in a solvent over a specific time. Here, we tackle this challenge by introducing a computational inverse design pipeline. We begin by introducing a simple, physically-inspired differentiable forward model of dissolution. We then formulate our inverse design as a PDE-constrained topology optimization that has access to analytical derivatives obtained via sensitivity analysis. Furthermore, we incorporate fabricability terms in the optimization objective that enable physically realizing our designs. We thoroughly analyze our approach on a diverse set of examples via both simulation and fabrication.
Could Tierless Languages Reduce IoT Development Grief?
Authors: Lubbers Mart , Koopman Pieter , Ramsingh Adrian , Singer Jeremy , Trinder Phil
Published: November 2022

Internet of Things (IoT) software is notoriously complex, conventionally comprising multiple tiers. Traditionally an IoT developer must use multiple programming languages and ensure that the components interoperate correctly. A novel alternative is to use a single
tierless
language with a compiler that generates the code for each component and ensures their correct interoperation.

We report a systematic comparative evaluation of two tierless language technologies for IoT stacks: one for resource-rich sensor nodes (Clean with iTask) and one for resource-constrained sensor nodes (Clean with iTask and mTask). The evaluation is based on four implementations of a typical smart campus application: two tierless and two Python-based tiered.

(1) We show that tierless languages have the potential to significantly reduce the development effort for IoT systems, requiring 70% less code than the tiered implementations. Careful analysis attributes this code reduction to reduced interoperation (e.g., two embedded domain-specific languages and one paradigm versus seven languages and two paradigms), automatically generated distributed communication, and powerful IoT programming abstractions. (2) We show that tierless languages have the potential to significantly improve the reliability of IoT systems, describing how Clean iTask/mTask maintains type safety, provides higher-order failure management, and simplifies maintainability. (3) We report the first comparison of a tierless IoT codebase for resource-rich sensor nodes with one for resource-constrained sensor nodes. The comparison shows that they have similar code size (within 7%), and functional structure. (4) We present the first comparison of two tierless IoT languages, one for resource-rich sensor nodes and the other for resource-constrained sensor nodes.
BAHD Company: The Ever-Expanding Roles of the BAHD Acyltransferase Gene Family in Plants
Authors: Moghe Gaurav , Kruse Lars H. , Petersen Maike , Scossa Federico , Fernie Alisdair R. , Gaquerel Emmanuel , D'Auria John C.
Published: November 2022

Plants’ ability to chemically modify core structures of specialized metabolites is the main reason why the plant kingdom contains such a wide and rich array of diverse compounds. One of the most important types of chemical modifications of small molecules is the addition of an acyl moiety to produce esters and amides. Large-scale phylogenomics analyses have shown that the enzymes that perform acyl transfer reactions on the myriad small molecules synthesized by plants belong to only a few gene families. This review is focused on describing the biochemistry, evolutionary origins, and chemical ecology implications of one of these families—the BAHD acyltransferases. The growth of advanced metabolomic studies coupled with next-generation sequencing of diverse plant species has confirmed that the BAHD family plays critical roles in modifying nearly all known classes of specialized metabolites. The current and future outlook for research on BAHDs includes expanding their roles in synthetic biology and metabolic engineering.
Exploiting Liquid Surface Tension in Microrobotics
Authors: Barbot Antoine , Ortiz Francisco , Bolopion Aude , Gauthier Michaël , Lambert Pierre
Published: November 2022

Surface tension effects are known to be dominant at the submillimeter scale. Within this context, the literature has extensively described the underlying physics (e.g., surface tension, wetting, surface texturation, and coatings), and capillary forces have been exploited in a variety of applications (e.g., capillary picking, self-alignment, capillary sealing, and capillary bearings). As several stimuli can be used to control liquid menisci, these forces have been used mainly in microrobotics in open loop (i.e., without real-time feedback). However, at least two major sources of uncertainty hinder these forces from working properly in open loop: the variability due to contact-angle hysteresis (the difference between wetting and unwetting) and the variability in the involved volume of liquid. To be able to reject these disturbances, successful sensor integration and associated advanced control schemes need to be embedded in capillary microrobotic microsystems. This article analyzes research contributions in this field from three different perspectives: the stimulus action of the surface tension effect (light, B-field, etc.), the application field (actuation, picking, sealing, etc.), and the sensing and control schemes. Technologically complex developments coexist with elegant and straightforward engineering solutions. Biological aspects of surface tension are not included in this review.
Quiescence in Saccharomyces cerevisiae
Authors: Breeden Linda L. , Tsukiyama Toshio
Published: November 2022

Most cells live in environments that are permissive for proliferation only a small fraction of the time. Entering quiescence enables cells to survive long periods of nondivision and reenter the cell cycle when signaled to do so. Here, we describe what is known about the molecular basis for quiescence in Saccharomyces cerevisiae, with emphasis on the progress made in the last decade. Quiescence is triggered by depletion of an essential nutrient. It begins well before nutrient exhaustion, and there is extensive crosstalk between signaling pathways to ensure that all proliferation-specific activities are stopped when any one essential nutrient is limiting. Every aspect of gene expression is modified to redirect and conserve resources. Chromatin structure and composition change on a global scale, from histone modifications to three-dimensional chromatin structure. Thousands of proteins and RNAs aggregate, forming unique structures with unique fates, and the cytoplasm transitions to a glass-like state.
Chemical Preparation of Metallic Cu Layer on Glass Substrate Using Intermediate Cu(OH)2/Cu(O, S) Bilayer
Authors: Shimizu Haruka , Sasano Junji , Khoo Pei Loon , Izaki Masanobu
Published: November 2022

A metallic Cu layer with a sheet resistance of 0.19 Ω was chemically prepared on a glass substrate by chemical reduction of the intermediate Cu(OH)2/Cu(O,S) bilayers using dimethylamine-borane (DMAB), while Cu(OH)2, and Cu(O,S) layers were fabricated by a sequential chemical bath deposition (CBD) in aqueous solutions containing copper (II) nitrate hydrate and ammonium nitrate with urea and thiourea. The thickness of the Cu(OH)2 and resultant Cu layers were strongly affected by the structure under the Cu(O, S) layer, and a metallic Cu layer was formed mainly from the Cu(OH)2 layer. The reduction reactions of Cu(OH)2 and Cu(O, S) were discussed based on thermodynamics.
Accuracy and effort costs together lead to temporal asynchrony of multiple motor commands
Authors: Tanis Daniel , Calalo Jan A. , Cashaback Joshua G. A. , Kurtzer Isaac L.
Published: November 2022

An important goal in the fields of sensorimotor neuroscience and biomechanics is to explain the timing of different muscles during behavior. Here, we propose that energy and accuracy considerations underlie the asynchronous onset of postural and arm muscles during rapid movement. Our novel model-based framework replicates a broad range of observations across varying task demands and plant dynamics and offers a new perspective to study motor timing.
Moxibustion with Walnut Shell Spectacles Could Improve the Objective Symptoms and Tear Film Stability of Patients with Dry Eye Disease: A Randomized Controlled Trial
Authors: Zhang Guoliang , Fu Weiwei , Xu Jing , Hu Pei , Zhang Yi , Sang Zijin , Wu Wenting , Zheng Kun , Wu Lie , Liu Zhishun
Published: November 2022

Objectives. This study aims to evaluate the efficacy and acceptability of moxibustion with walnut shell spectacles in treating dry eye disease (DED) patients and to provide treatment options. Methods. 126 DED patients were randomly allocated into the moxibustion group (treated by moxibustion with walnut shell spectacles, 64 cases) and the artificial tears group (treated with sodium hyaluronate eye drops, 62 cases). Evaluate the changes in the ocular surface disease index (OSDI), the visual analogue scale (VAS) of ocular discomfort, the tear film break-up time (TBUT), corneal fluorescein staining (CFS), and the Schirmer I test during the trial at baseline and after 1-week, 2-week, 3-week, and 4-week treatment. Evaluate the OSDI scale and the ocular symptom VAS scale one month after the end of treatment. Results. There were no significant differences in baseline characteristics between the two groups. For OSDI scores, the results showed that the efficacy of the moxibustion group was no less than that of the artificial tear group. For VAS of ocular discomfort, both groups significantly reduced their score compared with baseline, and for the moxibustion group, the decrease was more significant. For TBUT, FAS, and PPS, results showed that the efficacy of the moxibustion group was significant in both eyes after 4 weeks of treatment, but the right eye was in the artificial tear group. For CFS and Schirmer I test scores, there was no significant effect for both groups. Conclusion. Moxibustion with walnut shell spectacles could improve the clinical symptoms and tear film stability of DED patients; however, it has no significant efficacy on improving corneal injury and tear secretion, just the same as sodium hyaluronate eye drops. Nevertheless, moxibustion with walnut shell spectacles may have better effects on the self-assessment of ocular discomfort than sodium hyaluronate eye drops.
IL1RN and PRRX1 as a Prognostic Biomarker Correlated with Immune Infiltrates in Colorectal Cancer: Evidence from Bioinformatic Analysis
Authors: Wang Qi , Huang Xufeng , Zhou Shujing , Ding Yuntao , Wang Huizhi , Jiang Weiye , Xu Min
Published: November 2022

The extensive morbidity of colorectal cancer (CRC) and the inferior prognosis of terminal CRC urgently call for reliable prognostic biomarkers. For this, we identified 704 differentially expressed genes (DEGs) by intersecting three datasets, GSE41328, GSE37364, and GSE15960 from Gene Expression Omnibus database, to maximize the accuracy of the results. Preliminary analysis of the DEGs was then performed using online gene analysis datasets, such as DAVID, UCSC Cancer Genome Browser, CBioPortal, STRING, and UCSC Cancer Genome Browser. Cytoscape was utilized to visualize the protein perception interaction network of DEGs, and the bubble map of GO and KEGG enrichment function was demonstrated using the R package. The Molecular Complex Detection (MCODE), Biological Network Gene Oncology (BiNGO) plug-in in Cytoscape, was applied to further screen the DEGs to obtain 15 seed genes, which were IL1RN, GALNT12, ADH6, SCN7A, CXCL1, FGF18, SOX9, ACACB, PRRX1, MZB1, SLC22A3, CNNM4, LY6E, IFITM2, and GDPD3. Among them, IL1RN, ADH6, SCN7A, ACACB, MZB1, and GDPD3 exhibited statistically significant survival differences, whereas limited studies were conducted in CRC. Based on the enrichment results of the “Gene Ontology“(GO) and “Kyoto Encyclopedia of Genes and genomes “(KEGG) as well as documented findings of key genes, we further emphasized the potential of IL1RN and PRRX1 as markers of immune infiltrates in CRC and confirmed our hypothesis by compiling data from the UALCAN, Tumor Immune Estimation Resource, and TISIDB databases for these two genes. The above-mentioned genes might offer a valuable insight into the diagnosis, immunotherapeutic targets, and prognosis of CRC.
Pterostilbene Attenuates Subarachnoid Hemorrhage-Induced Brain Injury through the SIRT1-Dependent Nrf2 Signaling Pathway
Authors: Zhang Zihuan , Fang Jincheng , Zhou Jiawang , Ding Fei , Zhou Gang , Zhao Xintong , Zhuang Zong , Lu Yue
Published: November 2022

Neuroinflammatory injury, oxidative insults, and neuronal apoptosis are major causes of poor outcomes after subarachnoid hemorrhage (SAH). Pterostilbene (PTE), an analog of resveratrol, has been verified as a potent sirtuin 1 (SIRT1) activator. However, the beneficial actions of PTE on SAH-induced brain injury and whether PTE regulates SIRT1 signaling after SAH remain unknown. We first evaluated the dose-response influence of PTE on early brain impairment after SAH. In addition, EX527 was administered to suppress SIRT1 signaling. The results revealed that PTE significantly attenuated microglia activation, oxidative insults, neuronal damage, and early neurological deterioration. Mechanistically, PTE effectively enhanced SIRT1 expression and promoted nuclear factor-erythroid 2-related factor 2 (Nrf2) accumulation in nuclei. Furthermore, EX527 pretreatment distinctly repressed PTE-induced SIRT1 and Nrf2 activation and deteriorated these beneficial outcomes. In all, our study provides the evidence that PTE protects against SAH insults by activating SIRT1-dependent Nrf2 signaling pathway. PTE might be a therapeutic alternative for SAH.
Isolation, Identification, and Genetic Characterization of Antibiotic Resistance of Salmonella Species Isolated from Chicken Farms
Authors: Shalaby Ahmed , Ismail Mahmoud M. , El-Sharkawy Hanem
Published: November 2022

Salmonella is a major cause of foodborne outbreaks. It causes gastroenteritis in humans and animals. This micro-organism causes severe illness in chickens and has a major impact on chicken productivity and the poultry industry. This study aimed to address the prevalence of Salmonella infection in broiler chicken farms in Kafrelsheikh, Gharbia, and Menofeya provinces in Egypt during 2020–2022. This work also aimed to evaluate the genetic characterization and antibiotic resistance of the isolated Salmonella strains. Clinical signs and mortalities were observed and recorded. In total, 832 samples were collected from 52 broiler flocks, including 26 from both one-week-old and 6-week-old chicken farms from different organs (liver, intestinal content, spleen, and gallbladder). The prevalence of Salmonella infections was reported in the study region to be 36.54%. Of the 26 one-week-old farms surveyed, 11 (42.31%) and 8/26 (30.77%) of the six-week-old broiler chicken farms had Salmonella infections. Recovered isolates were serotyped as 9 (47.37%) S. enteritidis O 1,9,12, ad monophasic H: g, m: -, 6 (31.58.%) S. shangani 2, (10.53%) S. gueuletapee 1, (5.26%) S. II (salamae), and 1 (5.26%) untypable. The results showed that Salmonella infection was predominant in one-week-old chicks compared to infection in six-week-old and uninfected flocks. All Salmonella isolates were resistant to ampicillin and erythromycin, while all isolates were sensitive to ciprofloxacin, chloramphenicol, and levofloxacin. The isolates also contained 10.53% (2/19) streptomycin, 10.53% (2/21) gentamicin, 15.79% (3/19) doxycycline, and 26.32% (5/19) lincomycin and colistin. The phenotypically resistant Salmonella samples against ampicillin, erythromycin, and macrolide harbored blaTEM, blaSHV, ermB, ereA, mphA, and ermB, respectively. This baseline data on Salmonella spp. prevalence, serotyping, and antibiotic profiles are combined to define the antimicrobial resistance to this endemic disease. Elucidation of the mechanisms underlying this drug resistance should be of general importance in understanding both the treatment and prevention of Salmonella infection in this part of Egypt.
Robust Sequential Fusion Estimation Based on Adaptive Innovation Event-Triggered Mechanism for Uncertain Networked Systems
Authors: Xu Ke , Li Xinye , Wang Jie , Gao Yuan
Published: November 2022

In order to reduce the transmission pressure of the networked system and improve its robust performance, an adaptive innovation event-triggered mechanism is designed for the first time, and based on this mechanism, the robust local filtering algorithm for the multi-sensor networked system with uncertain noise variances and correlated noises is presented. To avoid calculating the complex error cross-covariance matrices, applying the sequential fusion idea, the robust sequential covariance intersection (SCI) and sequential inverse covariance intersection (SICI) fusion estimation algorithms are proposed, and their robustness is analyzed. Finally, it is verified in the simulation example that the proposed adaptive innovation event-triggered mechanism can reduce the communication burden, the robust local filtering algorithm is effective for the uncertainty generated by the unknown noise variances, and two robust sequential fusion estimators show good robustness, respectively.
Suppression of Selective Voltage-Gated Calcium Channels Alleviates Neuronal Degeneration and Dysfunction through Glutathione S-Transferase-Mediated Oxidative Stress Resistance in a Caenorhabditis elegans Model of Alzheimer’s Disease
Authors: Zheng Zihui , Wu Kanglu , Ruan Qinli , Li Dongfang , Liu Weizhen , Wang Min , Li Yaoyao , Xia Jintao , Yang Dongqing , Guo Jun
Published: November 2022

Calcium homeostasis plays a vital role in protecting against Alzheimer’s disease (AD). In this study, amyloid-β (Aβ)-induced C. elegans models of AD were used to elucidate the mechanisms underlying calcium homeostasis in AD. Calcium acetate increased the intracellular calcium content, exacerbated Aβ1–42 aggregation, which is closely associated with oxidative stress, aggravated neuronal degeneration and dysfunction, and shortened the lifespan of the C. elegans models. Ethylene glycol tetraacetic acid (EGTA) and nimodipine were used to decrease the intracellular calcium content. Both EGTA and nimodipine showed remarkable inhibitory effects on Aβ1–42 aggregations by increasing oxidative stress resistance. Moreover, both compounds significantly delayed the onset of Aβ-induced paralysis, rescued memory deficits, ameliorated behavioral dysfunction, decreased the vulnerability of two major (GABAergic and dopaminergic) neurons and synapses, and extended the lifespan of the C. elegans AD models. Furthermore, RNA sequencing of nimodipine-treated worms revealed numerous downstream differentially expressed genes related to calcium signaling. Nimodipine-induced inhibition of selective voltage-gated calcium channels was shown to activate other calcium channels of the plasma membrane (clhm-1) and endoplasmic reticulum (unc-68), in addition to sodium-calcium exchanger channels (ncx-1). These channels collaborated to activate downstream events to resist oxidative stress through glutathione S-transferase activity mediated by HPGD and skn-1, as verified by RNA interference. These results may be applied for the treatment of Alzheimer’s disease.
Antimicrobial Susceptibility of Salmonella Isolated from Chickens and Humans in Wau, South Sudan
Authors: Saad Shereen , Jubara Ambros , Wani Charles , Munyeme Musso , Taha Alfateh , Mudenda Steward , Zulu Mildred , Mwasinga Wizaso , Samutela Mulemba , Tembo Rabecca , Muleya Walter , Kwenda Geoffrey , Hang’ombe Bernard Mudenda
Published: November 2022

Background. Salmonella infections are a public health problem across the globe. In South Sudan, there is little information regarding the prevalence and antibiotic resistance patterns of Salmonella. Therefore, this study assessed the prevalence and antimicrobial susceptibility of Salmonella isolates from chickens and humans in South Sudan. Fecal samples were collected and cultured on Xylose Lysine Deoxycholate Agar for the isolation of Salmonella and confirmed using biochemical tests and PCR through the amplification of the invA gene. A total of 417 fecal samples were examined, of which 270 (64.7%) were chicken cloacal swabs while 147 (35.3%) were humans’ stool specimens. Results. Eleven (11) Salmonella isolates were isolated from humans while nine were from chickens. All 11 isolates from humans were susceptible to sulfamethoxazole-trimethoprim, chloramphenicol, streptomycin, cefotaxime, nalidixic acid, and gentamicin. However, 4 (36.7%) isolates showed resistance to ciprofloxacin, 2 (18.9%) to ampicillin, and 1 (9.1%) to tetracycline. All chicken isolates were susceptible to chloramphenicol, streptomycin, sulfamethoxazole-trimethoprim, ciprofloxacin, cefotaxime, nalidixic acid, and gentamicin but showed resistance to tetracycline 2 (22.2%) and ampicillin 1 (11.1%). Conclusion. Antimicrobial resistant isolates were isolated in both chickens and humans. Further, MDR isolates were found in both chicken and human samples, and this is a public health concern. This, therefore, calls for concerted efforts to educate producers and consumers on public health, food safety, food hygiene in food production, and enhancement of surveillance programmes on zoonotic bacteria and antimicrobial susceptibility.
Theories and Models of Technology Adoption in Agricultural Sector
Authors: Dissanayake C. A. K. , Jayathilake W. , Wickramasuriya H. V. A. , Dissanayake U. , Kopiyawattage K. P. P. , Wasala W. M. C. B.
Published: November 2022

Agriculture is crucial in catering to the increasing demand for food and employment. Thus, adoption of novel technologies is important. Many scientists have developed different theories and models explaining the process of behavioral change relevant to adoption. They are either completely different, similar, or improvements of previously developed models. Therefore, compilation and summarization of these theories and models will support future studies and researchers. Thus, an analysis of literature on technology adoption was conducted. The review was prepared based on literature from various sources spanning around 50 years. The theories and models identified by different studies were compiled and analyzed in this review paper. Many theories and models in agricultural technology adoption such as transtheoretical model, theory of reasoned action, theory of interpersonal behavior, model for innovation-decision process, different versions of technology acceptance model, theory of planned behavior, theory of diffusion of innovation, task-technology fit, technology readiness, unified theory of acceptance and use of technology, expectancy livelihood model, social cognitive theory, and perceived characteristics of innovating theory were compiled. Each theory and model has its own uniqueness, which had explained different aspects of technology adoption process and factors determining the behavioral change. These theories and models included affecting factors such as technological, personal, social, and economical factors. In conclusion, it can be stated that, rather than having a single theory or a model, an integrated and amalgamated form will be more explanatory for technology adoption.