bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of disease-modifying drug trials in amyotrophic lateral sclerosis
Authors: Tornese Paolo , Lalli Stefania , Cocco Antoniangela , Albanese Alberto
Published: February 2022

We analysed clinical trials of pharmacological interventions on patients with amyotrophic lateral sclerosis (ALS), and compared study quality and design features. The systematic review included articles published in PubMed and trials registered in ClinicalTrials.gov. Included studies were randomised double-blind placebo-controlled clinical trials assessing a disease-modifying pharmacological intervention. Studies were excluded if primary end points were safety or dose finding. A total of 28 735 articles and 721 current trials were identified. 76 published articles and 23 ongoing trials met inclusion criteria; they referred to distinct populations comprising 22 817 participants with ALS. Most articles and all current trials had parallel group design; few articles had cross-over design. A run-in observation period was included in about 20% of published studies and ongoing trials. Primary end points included functional assessment, survival, muscle strength, respiratory function, biomarkers and composite measures. Most recent trials had only functional assessment and survival. Risk of bias was high in 23 articles, moderate in 35, low in 18. A disease modification effect was observed for 10 interventions in phase II studies, two of which were confirmed in phase III. Three confirmatory phase III studies are currently underway. The present review provides cues for the design of future trials. Functional decline and survival, as single or composite measures, stand as the reference end points. Post hoc analyses should not be performed, particularly in studies using composite end points. There is a general agreement on diagnostic criteria; but eligibility criteria must be improved. Run-in observations may be used for censoring patients but are discouraged for refining participants’ eligibility. The ALS Functional Rating Scale-Revised needs improvement for use as an ordinal measure of functional decline.
Narratives of prevention and redemption in opioid overdose obituaries
Authors: Adams Elizabeth Troutman , Buchbinder Mara
Published: February 2022

Obituaries of people who died from an opioid overdose represent a new territory for understanding cultural narratives of the US opioid epidemic. Drawing on textual analysis of 30 opioid overdose obituaries published on Legacy.com between 2015 and 2020, we describe a prototypical narrative conveyed through opioid overdose obituaries, which renders symbolic meaning through the voices of the bereaved. Obituary authors reimagine their subjects as tragic heroes and reconstitute opioid addiction as a curse, plight or affliction that befalls its victims. Many of these obituaries invoke the language of public health, calling for reform, action or general awareness so other families might avoid the havoc and heartbreak of opioid addiction. We argue that obituaries contribute to broader cultural narratives of opioid addiction by reproducing tragic storylines, vindicating and humanising the deceased, framing opioid addiction as a societal, rather than individual, problem, and medicalising addiction as a brain disease beyond a person’s control. Obituary texts thus intertwine a personal story with a broader societal health crisis, transforming stories of the deceased into cautionary tales and public health warnings.
Combination of magnesium supplementation with treadmill exercise improves memory deficit in aged rats by enhancing hippocampal neurogenesis and plasticity: a functional and histological study
Authors: El-Domiaty Heba Fathy , El-Roghy Eman S. , Salem Heba Rady
Published: February 2022

This study aimed to investigate the possible ameliorative effects of co-supplementation with Mg2+ and treadmill exercise on memory deficit in aged rats. Fifty male albino rats (10 young and 40 aged rats) were divided into 5 groups (10 rats/group): young, aged sedentary, aged exercised, aged Mg2+-supplemented, and aged exercised and Mg2+-supplemented. Memory was assessed using the Y-maze and novel object recognition tests. Plasma samples were collected for measurement of C-reactive protein (CRP). Subsequently, brain malondialdehyde and catalase levels were measured. Histological and immunohistochemical analyses of the hippocampi were performed. Our results showed impaired memory in aged sedentary rats, with significantly elevated plasma CRP and brain malondialdehyde levels and decreased brain catalase. The hippocampus of aged sedentary rats showed cellular degeneration, downregulation of synaptophysin (SYP) and proliferating cell nuclear antigen (PCNA), and upregulation of glial fibrillary acidic protein (GFAP) and caspase-3. Mg2+ supplementation and/or treadmill exercise significantly improved memory tests in aged rats, which could be explained by the upregulation of hippocampal SYP and PCNA expression and downregulation of GFAP and caspase-3 expression with antioxidant and anti-inflammatory mechanisms. The combined therapy had a better effect than both treatments alone, confirming the role of Mg2+ supplementation with physical exercise in enhancing age-related memory deficit.

Novelty: Magnesium supplementation with treadmill exercise improves memory deficit in aged rats. The possible mechanisms are upregulation of the hippocampal synaptophysin and PCNA, downregulation of GFAP and caspase-3, the antioxidant and anti-inflammatory mechanisms.
Deep long-period earthquakes near Mount Meager, British Columbia
Authors: Lu Luhong , Bostock Michael G.
Published: February 2022

Deep long-period earthquakes (DLPs) are a class of seismicity that has been documented in volcanic fields worldwide and are thought to be related to the motion of fluids (magmas and volatiles) associated with volcanic processes. We applied an automatic event detection algorithm to stations of the Canadian National Seismograph Network in southwestern British Columbia and documented the first DLPs observed within the Garibaldi Volcanic Belt. A total of 42 events satisfying the spectral criteria of DLPs were detected at station PMB between 1993 and 1998, of which 26 events were located using three-component polarization analysis and 1-D ray tracing. An additional six events were identified and located from station MGMB between 2016 and 2019. The events are small ( ML ∼ 0) and the majority of the epicenters are clustered at ∼45 km ENE of Mount Meager, the site of Canada’s most recent large eruption at 2.4 ka. They lie in closer proximity and may be related to Quaternary volcanism associated with the Bridge River Cones.
The structural and electronic properties of Stone–Wales defective zigzag/armchair antimonene nanotubes: first-principles calculations
Authors: Yang Lei , Huang Bin , Chen Changpeng , Lan Qingwen , Qin Tian
Published: February 2022

Geometric optimization and electronic properties of Stone–Wales defective antimonene nanotubes were calculated using the method of first-principles calculations based on density functional theory. The possible orientations of zigzag/armchair nanostructures when Stone–Wales defects were formed were investigated, respectively. The band structures, partial density of states, and electron density isosurfaces were calculated to reveal the influence of Stone–Wales defects on antimonene nanotubes. When the structure of antimonene changed from monolayer to tube, the indirect gap semiconductor antimonene transformed to a direct gap semiconductor. Moreover, the character of the direct bandgap for the antimonene nanotube was preserved, while the energy of the conduction band bottom changed due to the intervention of the defect energy level in the bandgaps. These findings may provide valuable references for the development and design of novel nanodevices based on antimonene nanotubes.
On some new analytical solutions to the (2+1)-dimensional nonlinear electrical transmission line model
Authors: Ali Khalid K. , Mehanna M. S.
Published: February 2022

In the present paper, from the field of communications in physics and engineering, we select the $$(2+1)$$

(
2
+
1
)

-dimensional nonlinear electrical transmission line equation to be studied. The model under study is one of the models that has important applications in the field of physics and telecommunications engineering. We acquire the soliton solutions by using two simple methods. We present some figures in two and three dimensions to show that these solutions actually have the properties of soliton waves.
Stochastic consensus dynamics for nonconvex optimization on the Stiefel manifold: Mean-field limit and convergence
Authors: Ha Seung-Yeal , Kang Myeongju , Kim Dohyun , Kim Jeongho , Yang Insoon
Published: February 2022

We study a consensus-based method for minimizing a nonconvex function over the Stiefel manifold. The consensus dynamics consists of stochastic differential equations for interacting particle system, whose trajectory is guaranteed to stay on the Stiefel manifold. For the proposed model, we prove the mean-field limit of the stochastic system toward a nonlinear Fokker–Planck equation on the Stiefel manifold. Moreover, we provide a sufficient condition on the parameter and the initial data, so that the solution to the Fokker–Planck equation is asymptotically concentrated on the point near a global optimizer. To implement our consensus-based optimization (CBO) algorithm, we provide two algorithms; one is improved from the algorithm suggested in our previous work, and the other is based on an entirely different approach, namely the Cayley transformation. We validate the CBO algorithms on the various test problems on the Stiefel manifold.
FRACTAL SOLITARY WAVE SOLUTIONS FOR FRACTAL NONLINEAR DISPERSIVE BOUSSINESQ-LIKE MODELS
Authors: WANG KANGLE
Published: February 2022

In this study, the fractal nonlinear dispersive Boussineq-like equation is investigated by variational perspective for the first time. The fractal variational principle of the fractal Boussineq-like equation is established via fractal semi-inverse method (FSM). Based on the fractal variational principle, variational transform method (VTM) is proposed to find the exact fractal solitary wave solution for the fractal nonlinear dispersive Boussineq-like equation. The numerical examples illustrate the novel scheme is very simple and efficient. Moreover, some physical properties of fractal solitary wave solutions are illustrated by some simulation graphics.
Perfect codes and universal adjacency spectra of commuting graphs of finite groups
Authors: Banerjee Subarsha
Published: February 2022

The commuting graph [Formula: see text] of a finite group [Formula: see text] has vertex set as [Formula: see text], and any two distinct vertices [Formula: see text] are adjacent if [Formula: see text] and [Formula: see text] commute with each other. In this paper, we first study the perfect codes of [Formula: see text]. We then find the universal adjacency spectra of the join of two regular graphs, join of two regular graphs in which one graph is a union of two regular graphs, and generalized join of regular graphs in terms of adjacency spectra of the constituent graphs and an auxiliary matrix. As a consequence, we obtain the adjacency, Laplacian, signless Laplacian, and Seidel spectra of the above graph operations. As an application of the results obtained, we calculate the adjacency, Laplacian, signless Laplacian, and Seidel spectra of [Formula: see text] for [Formula: see text], where [Formula: see text] is the dihedral group, [Formula: see text] is the dicyclic group and [Formula: see text] is the semidihedral group. Moreover, we provide the exact value of the spectral radius of the adjacency, Laplacian, signless Laplacian, and Seidel matrix of [Formula: see text] for [Formula: see text]. Some of the theorems published in [F. Ali and Y. Li, The connectivity and the spectral radius of commuting graphs on certain finite groups, Linear Multilinear Algebra 69 (2019) 1–14; T. Cheng, M. Dehmer, F. Emmert-Streib, Y. Li and W. Liu, Properties of commuting graphs over semidihedral groups, Symmetry 13(1) (2021) 103] can be deduced as corollaries from the theorems obtained in this paper.
Partial actions of a Hopf algebra on its base field and the corresponding partial smash product algebra
Authors: Martini Grasiela , Paques Antonio , Silva Leonardo Duarte
Published: February 2022

In this paper, we introduce the concept of a [Formula: see text]-Hopf algebra as a Hopf algebra obtained as the partial smash product algebra of a Hopf algebra and its base field, and show that every Hopf algebra is a [Formula: see text]-Hopf algebra. Moreover, a method to compute partial actions of a given Hopf algebra on its base field is developed and, as an application, we exhibit all partial actions of such type for some families of Hopf algebras.
Gate-based circuit designs for quantum adder-inspired quantum random walks on superconducting qubits
Authors: Koch Daniel , Samodurov Michael , Projansky Andrew , Alsing Paul M.
Published: February 2022

Quantum random walks, which drew much attention over the past few decades for their distinctly nonclassical behavior, are a promising subfield within quantum computing. Theoretical framework and applications for these walks have seen many great mathematical advances, with experimental demonstrations now catching up. In this study, we examine the viability of implementing coin quantum random walks using a Quantum Adder-based Shift Operator, with quantum circuit designs specifically for superconducting qubits. We focus on the strengths and weaknesses of these walks, particularly circuit depth, gate count, connectivity requirements and scalability. We propose and analyze a novel approach to implementing boundary conditions for these walks, demonstrating the technique explicitly in one and two dimensions. Finally, we present several fidelity results from running our circuits on IBM’s quantum volume 32 ‘Toronto’ chip, showcasing the extent to which these noisy intermediate-scale quantum devices can currently handle quantum walks.
Four-qubit states generated by Clifford gates
Authors: Latour Frédéric , Perdomo Oscar
Published: February 2022

The Clifford group is the set of gates generated by controlled not (CNOT) gates and the two local gates [Formula: see text] and [Formula: see text]. We will say that an [Formula: see text]-qubit state is a Clifford state if it can be prepared using Clifford gates, this is, [Formula: see text] is Clifford if [Formula: see text] where [Formula: see text] is a Clifford gate. In this paper, we study the set of all 4-qubit Clifford states. We prove that there are 293760 states, each of which has entanglement entropy equal to 0, [Formula: see text], 1, [Formula: see text], or [Formula: see text]. We also show that any pair of these states can be connected using local gates and at most 3 CNOT gates. We also study the Clifford states with real entries under the action of the subgroup [Formula: see text] of Clifford gates with real entries. This time we show that every pair of Clifford states with real entries can be connected with at most 5 CNOT gates and local gates in [Formula: see text]. To understand the action of the 12 different CNOT gates, we partition the Clifford states into orbits using the equivalence relation: two states are equivalent if they differ by a local Clifford gate. We label each orbit in such a way that it is easy to see the effect of the CNOT gates. Diagrams and tables explaining the action of the CNOT gates on all the orbits are presented in the paper. The link https://youtu.be/42MI6ks2_eU leads to a YouTube video that explains the most important results in this paper.
Investigation of Intelligent Substation Inspection Robot by Using Mobile Data
Authors: Qin Zhixian , Xu Zhao Dan , Sun Quan Cai , Poovendran Parthasarathy , Balamurugan P.
Published: February 2022

Substation equipment inspection is essential for the power industry. The expansion of the smart grid scale improves the transmission capacity and enhances the likelihood of power plant facilities failure. To ensure the safety of the electric power supply, it is essential to inspect substation equipment. Metal commercial equipment can be traversed by remote inspection robots equipped with magnetic wheels. It is possible to use robots like this to examine equipment and pipelines remotely. In many cases, these gadgets are able to scale vertical surfaces and even traverse obstacles with a variety of shapes. Finally, researchers in the field of robotics have indicated that challenges such as restricted onboard battery capacity, undependable line fault detection, electrical insulation, power mechanism, and advanced control techniques for outer wind disruption are highly promising research areas. To build an unmanned, intelligent, and succeeded substation, the substation progressively implements inspection robots instead of physical exertion. Hence, in this paper, the mobile-based Intelligent Tracking Framework (MITF) has been proposed using inspection robots. This inspection robot is autonomous and can be used for various tracking tools: visual, infrared, and partial charge–discharge camera. The robot is integrated with a camera and thermal infrared imager sensors that have been collectively designated as workload. These inspection sensors are used to detect environmental parameters such as reading meters, evaluation thermoelectric temperature. The accurate localization of working loads and the inspection robot electromagnetic interference within substations have been resolved. This mobile robot delivers innovative monitoring and precise detection for the unmanned substation and smart substation. The suggested approach’s effectiveness is verified through experiment results based on the electrical equipment of the substation. The experimental outcome of the proposed method boosts the Meter Reading Analysis (94.19%), Transmission Capacity Analysis (98.5%), Workload Analysis (98.9%), Temperature Analysis (97.6%), and Safety Analysis (95.41%).
Design and Research of Computer-Aided English Teaching Methods
Authors: Li Bing
Published: February 2022

Design of intelligent research systems is considered as one of the most prominent developments in multi-modal information domains in our day-to-day life. While significant growth in computer-aided English teaching methods (CAETMs) has made a progression over the past few years using techniques such as computational intelligence, biological computing aspects within the artificial intelligence domain. All the research in English teaching structures has been automated through online cloud-based applications and progressing at a rapid rate. But there are still a number of subjects that need to be explored in terms of its design, implementation, deployment of intelligent methods, and multi-agent systems in a real-world environment. However establishing teaching research subjects with novel techniques and methodologies utilized in computer vision in support of deep learning, semantic models in healthcare, organizations, and education sector are in need of further research with innovative and creative ideas. This paper will provide the emerging CAETM that solved the global needs of people in the educational domain. We will also discuss the improvements that need to be done in English teaching methods with digital computing solutions.
Individual Cryptocurrency Investors: Evidence From A Population Survey
Authors: Ante Lennart , Fiedler Ingo , Meduna Marc von , Steinmetz Fred
Published: February 2022

Cryptocurrencies, such as Bitcoin, are a highly volatile asset class where very high returns are offset by large losses. This study examines the financial success of individual investments in cryptocurrencies and analyzes whether it relates to similar explanatory factors as for investments in other asset classes. For this purpose, a nationally representative survey data set of 3,864 German citizens is used, of which 354 (9.2%) reported owning cryptocurrencies in March 2019. We analyze the subpopulation of 225 cryptocurrency owners who classify as investors. 56% of them experienced positive returns, while 29% had negative results. The remaining respondents broke even. The average investment was €1,773 in a portfolio of two cryptocurrencies. At the time of the survey, the average portfolio value had risen to €7094 — an average gain of 300%. While nearly half of the investors (44%) outperformed Bitcoin market returns, not a single one of the early investors (2009–2012) did. We find that net income, the degree of cryptocurrency knowledge and the degree of ideological motivation for owning cryptocurrency have positive effects on returns. This first scientific analysis of individual investment in cryptocurrencies provides a basis for future research and for regulatory decision-making.
Photo-activated thin films of porphyrins for reactive oxygen species generation
Authors: Gibbons Dáire J. , Boh Alexandre , Habermeyer Benoit , Villandier Nicolas , Leroy-Lhez Stéphanie , Williams René M.
Published: February 2022

The use of a single component porphyrin thin-film for photodynamic antimicrobial chemotherapy is unexplored. Herein, a porphyrin with good film formation properties is used to make thin layers, by physical vapor phase deposition, that are stable in aqueous media and can generate singlet oxygen upon 650 nm excitation. The synthesis and photophysical studies, in solution and as thin film, of free base 5,10,15,20-tetra-(4-hexyloxyphenyl)porphyrin are described. The porphyrin was synthesized via modified Adler-Longo conditions. Thin films of this porphyrin were made on quartz glass via spin coating and via vapour-phase deposition. The porphyrin was studied, in solution and as thin film (without a polymer component or matrix), with UV-Vis spectroscopy and with steady-state and time-resolved photoluminescence spectroscopy. The spin coated films display sharp J-band emission at 741 nm, indicating J-aggregate formation, but are not stable in aqueous media. The thin films obtained via vapour-phase deposition do not show the J-band emission, but are stable. The detection of singlet oxygen generated by the porphyrin thin film using a chemiluminescent water-soluble singlet oxygen probe is reported.
A Novel Learning Approach for Different Profile Shapes of Convecting–Radiating Fins Based on Shifted Gegenbauer LSSVM
Authors: Shivanian Elyas , Hajimohammadi Zeinab , Baharifard Fatemeh , Parand Kourosh , Kazemi Ramin
Published: February 2022

The purpose of this paper is to introduce a novel learning approach to solve the heat transfer problem from convecting-radiating fin model. This model is a nonlinear differential equation in which different boundary conditions cause different profile shapes including rectangular, triangular, trapezoidal and concave parabolic. We consider one-dimensional, steady conduction in the fin and neglect radiative exchange between adjacent fins and between the fin and its primary surface. Our method is based on using the quasilinearization method to linearize the nonlinear models and applying shifted Gegenbauer polynomials as new kernel in least squares support vector machines method. The results of fin efficiency and heat transfer rate of the problems which compared with available previous results indicate better efficiency and accuracy of the proposed approach.
Construction of Hyperbolic Fuzzy Set and its Applications in Diverse COVID-19 Associated Problems
Authors: Dutta Palash , Borah Gourangajit
Published: February 2022

This paper’s core objective is to introduce a novel notion called hyperbolic fuzzy set (HFS) where, the grades follow the stipulation that the product of optimistic and pessimistic degree must be less than or equal to one (1), rather than their sum not exceeding one (1) as in case of IFSs. The concept of HFS originates from a hyperbola, which provides extreme flexibility to the decision makers in the representation of vague and imprecise information. It is observed that IFSs, Pythagorean fuzzy sets (PFSs), and q-rung orthopair fuzzy sets (Q-ROFSs) often failed to express the uncertain information properly under some specific situations, while HFS tends to overcome such limitations by being applicable under those perplexed situations too. In this paper, we first define some basic operational laws and few desirable properties of HFSs. Second, we define a novel score function, accuracy function, and also establish some of their properties. Third, a novel similarity and distance measure is proposed for HFSs that are capable of distinguishing between different physical objects or alternatives based on the grounds of “similitude degree” and “farness coefficient”, respectively. Later, the advantages of all of these newly defined measures have been showcased by performing a meticulous comparative analysis. Finally, these measures have been successfully applied in various COVID-19 associated problems such as medical decision-making, antivirus face-mask selection, efficient sanitizer selections, and effective medicine selection for COVID-19. The final results obtained with our newly defined measures comply with several other existing methods that we considered and the decision strategy adopted is simple, logical, and efficient. The significant findings of this study are certain to aid the healthcare department and other frontline workers to take necessary measures to reduce the intensity of the coronavirus transmission, so that we can hopefully progress toward the end of this ruthless pandemic.
Expansion and Reduction of Soft Sets and their Applications in Decision Making
Authors: Çağman Naim , Eraslan Selim
Published: February 2022

In this study, we first define expansion and reduction of the soft sets that are based on the linguistic modifiers. By using these new notions, we then construct a decision-making method called soft reduction method, which selects a set of optimum alternatives. We finally present an example which shows that the methods can be successfully applied to many problems containing uncertainties.
Investigating the role of differential biotic production on carbonate geometries through stratigraphic forward modelling and sensitivity analysis: the Llucmajor example
Authors: Tella Timothy O. , Winterleitner Gerd , Mutti Maria
Published: February 2022

The geometry of carbonate platforms reflects the interaction of several factors. However, the impact of carbonate-producing organisms has been poorly investigated so far. This study applies stratigraphic forward modelling (SFM) and sensitivity analysis to examine, referenced to the Miocene Llucmajor Platform, the effect of changes of dominant biotic production in the oligophotic and euphotic zones on platform geometry. Our results show that the complex interplay of carbonate production rates, bathymetry and variations in accommodation space control the platform geometry. The main driver of progradation is the oligophotic production of rhodalgal sediments during the lowstands. This study demonstrates that platform geometry and internal architecture varies significantly according to the interaction of the predominant carbonate-producing biotas. The input parameters for this study are based on well-understood Miocene carbonate biotas with characteristic euphotic, oligophotic and photo-independent carbonate production in which it is crucial that each carbonate-producing class is modelled explicitly within the simulation run and not averaged with a single carbonate production–depth profile. This is important in subsurface exploration studies based on stratigraphic forward models where the overall platform geometry may be approximated through calibration runs, and constrained by seismic surveys and wellbores. However, the internal architecture is likely to be oversimplified without an in-depth understanding of the target carbonate system and a transfer to forward modelling parameters.
POMACS V6, N1, March 2022 Editorial
Authors: Carlsson Niklas , Cohen Edith , Robert Philippe
Published: February 2022

The ACM Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) focuses on the measurement and performance evaluation of computer systems and operates in close collaboration with the ACM Special Interest Group SIGMETRICS. All papers in this issue of POMACS will be presented during the ACM SIGMETRICS/Performance 2022 conference. The issue contains papers selected by the editorial board via a rigorous review process that follows a hybrid conference and journal model, with reviews conducted by the 97 members of our POMACS editorial board. Each paper was either conditionally accepted (and shepherded), allowed a "one-shot" revision (to be resubmitted to one of the subsequent two deadlines), or rejected (with resubmission allowed after a year). For this issue, which represents the fall deadline, we accepted 25 papers out of 106 submissions (including 4 papers that had been given a "one-shot" revision opportunity). All submitted papers received at least 3 reviews and we held an online TPC meeting. Based on the indicated primary track, roughly 30% of the submissions were in the Measurement & Applied Modeling track, 28% were in the Systems track, 26% were in the Theory track, and 15% were in the Learning track. Many people contributed to the success of this issue of POMACS. First, we would like to thank the authors, who submitted their best work to SIGMETRICS/POMACS. Second, we would like to thank the TPC members who provided constructive feedback in their reviews to authors and participated in the online discussions and TPC meetings. We also thank several external reviewers who provided their expert opinion on specific submissions that required additional input. We are also grateful to the SIGMETRICS Board Chair, Giuliano Casale, and to past TPC Chairs. Finally, we are grateful to the Organization Committee and to the SIGMETRICS Board for their ongoing efforts and initiatives for creating an exciting program for ACM SIGMETRICS/Performance 2022.
Argus
Authors: Regmi Hem , Sur Sanjib
Published: February 2022

We propose Argus, a system to enable millimeter-wave (mmWave) deployers to quickly complete site-surveys without sacrificing the accuracy and effectiveness of thorough network deployment surveys. Argus first models the mmWave reflection profile of an environment, considering dominant reflectors, and then use this model to find locations that maximize the usability of the reflectors. The key component in Argus is an efficient machine learning model that can map the visual data to the mmWave signal reflections of an environment and can accurately predict mmWave signal profile at any unobserved locations. It allows Argus to find the best picocell locations to provide maximum coverage and also lets users self-localize accurately anywhere in the environment. Furthermore, Argus allows mmWave picocells to predict device's orientation accurately and enables object tagging and retrieval for VR/AR applications. Currently, we implement and test Argus on two different buildings consisting of multiple different indoor environments. However, the generalization capability of Argus can easily update the model for unseen environments, and thus, Argus can be deployed to any indoor environment with little or no model fine-tuning.
NG-Scope
Authors: Xie Yaxiong , Jamieson Kyle
Published: February 2022

Accurate and highly-granular channel capacity telemetry of the cellular last hop is crucial for the effective operation of transport layer protocols and cutting edge applications, such as video on demand and video telephony. This paper presents the design, implementation, and experimental performance evaluation of NG-Scope, the first such telemetry tool able to fuse physical-layer channel occupancy readings from the cellular control channel with higher-layer packet arrival statistics and make accurate capacity estimates. NG-Scope handles the latest cellular innovations, such as when multiple base stations aggregate their signals together to serve mobile users. End-to-end experiments in a commercial cellular network demonstrate that wireless capacity varies significantly with channel quality, mobility, competing traffic within each cell, and the number of aggregated cells. Our experiments demonstrate significantly improved cell load estimation accuracy, missing the detection of less than 1% of data capacity overall, a reduction of 82% compared to OWL, the state-of-the-art in cellular monitoring. Further experiments show that MobileInsight-based CLAW has a root-mean-squared capacity error of 30.5 Mbit/s, which is 3.3× larger than NG-Scope (9.2 Mbit/s).
Metamorphic Testing of Deep Learning Compilers
Authors: Xiao Dongwei , LIU Zhibo , Yuan Yuanyuan , Pang Qi , Wang Shuai
Published: February 2022

The prosperous trend of deploying deep neural network (DNN) models to diverse hardware platforms has boosted the development of deep learning (DL) compilers. DL compilers take the high-level DNN model specifications as input and generate optimized DNN executables for diverse hardware architectures like CPUs, GPUs, and various hardware accelerators. Compiling DNN models into high-efficiency executables is not easy: the compilation procedure often involves converting high-level model specifications into several different intermediate representations (IR), e.g., graph IR and operator IR, and performing rule-based or learning-based optimizations from both platform-independent and platform-dependent perspectives. Despite the prosperous adoption of DL compilers in real-world scenarios, principled and systematic understanding toward the correctness of DL compilers does not yet exist. To fill this critical gap, this paper introduces MT-DLComp, a metamorphic testing framework specifically designed for DL compilers to effectively uncover erroneous compilations. Our approach leverages deliberately-designed metamorphic relations (MRs) to launch semantics-preserving mutations toward DNN models to generate their variants. This way, DL compilers can be automatically examined for compilation correctness utilizing DNN models and their variants without requiring manual intervention. We also develop a set of practical techniques to realize an effective workflow and localize identified error-revealing inputs. Real-world DL compilers exhibit a high level of engineering quality. Nevertheless, we detected over 435 inputs that can result in erroneous compilations in four popular DL compilers, all of which are industry-strength products maintained by Amazon, Facebook, Microsoft, and Google. While the discovered error-triggering inputs do not cause the DL compilers to crash directly, they can lead to the generation of incorrect DNN executables. With substantial manual effort and help from the DL compiler developers, we uncovered four bugs in these DL compilers by debugging them using the error-triggering inputs. Our proposed testing frameworks and findings can be used to guide developers in their efforts to improve DL compilers.
Evolution and Functions of Plant U-Box Proteins: From Protein Quality Control to Signaling
Authors: Trenner Jana , Monaghan Jacqueline , Saeed Bushra , Quint Marcel , Shabek Nitzan , Trujillo Marco
Published: February 2022

Posttranslational modifications add complexity and diversity to cellular proteomes. One of the most prevalent modifications across eukaryotes is ubiquitination, which is orchestrated by E3 ubiquitin ligases. U-box-containing E3 ligases have massively expanded in the plant kingdom and have diversified into plant U-box proteins (PUBs). PUBs likely originated from two or three ancestral forms, fusing with diverse functional subdomains that resulted in neofunctionalization. Their emergence and diversification may reflect adaptations to stress during plant evolution, reflecting changes in the needs of plant proteomes to maintain cellular homeostasis. Through their close association with protein kinases, they are physically linked to cell signaling hubs and activate feedback loops by dynamically pairing with E2-ubiquitin-conjugating enzymes to generate distinct ubiquitin polymers that themselves act as signals. Here, we complement current knowledgewith comparative genomics to gain a deeper understanding of PUB function, focusing on their evolution and structural adaptations of key U-box residues, as well as their various roles in plant cells.
A Loss of Charge at Reduction of Hydrogen Ion by Fast Scan Voltammetry
Authors: Liu Yuanyuan , Aoki Koichi Jeremiah , Chen Jingyuan
Published: February 2022

The voltammetry of hydrogen ion is revisited quantitatively at a thin wire platinum electrode at scan rates less than 8 V s−1 in the context of the amount of adsorption and the negative capacitance. The first reduction wave was attributed to the reduction of adsorbed hydrogen ion, which is inconsistent with the Volmer step. The second one was composed of the partially-diffusion control current and the negatively capacitive current associated with the redox reaction. The capacitance causes the potential shift at high scan rates owing to the relaxation of the electric field for the faradaic reactions.
The Effects of Testing Conditions on Corrosion Behaviours of SS316L for Bipolar Plate of PEMFC
Authors: Leng Yu , Yang Daijun , Ming Pingwen , Li Bing , Zhang Cunman
Published: February 2022

Corrosion of stainless steel bipolar plate (BPP) remains a big challenge while it has been considered to be one of the most appropriate candidates for proton exchange membrane fuel cell (PEMFC) in automotive application. This work aims to study comprehensively the effects of temperature, pH, bubbled gas and potential on corrosion behaviours of SS316L. Moreover, SEM and EDX are performed to reveal the evolutions of surface morphology, microstructure and chemical composition of SS316L under different testing conditions. The results indicate that temperature, pH and potential have significant influences on corrosion potential (Ecorr.), corrosion current density (Icorr.) and passive current density (Ip) of SS316L. In addition, interactions between different testing conditions on corrosion resistance are strong. The main corrosion mechanism of SS316L would be shifted from pitting to intergranular or uniform corrosion as pH decreases from 3 ∼ 5 to 0.3 ∼ 1. Accelerated testing solutions with pH in the range of 0.3 ∼ 1 may be suitable to evaluate corrosion resistance of materials for BPP at lower potential. However, simulated testing conditions with pH in the range of 3 ∼ 5 is more appropriate when higher potentials of 1.0 ∼ 1.4 V (vs Ag/AgCl) need to be considered.
High-fidelity porcine models of metabolic syndrome: a contemporary synthesis
Authors: Cluzel Gaston L. , Ryan Paul M. , Herisson Florence M. , Caplice Noel M.
Published: February 2022

This review aims to describe and compare porcine models of metabolic syndrome. This syndrome and its associated secondary comorbidities are set to become the greatest challenge to healthcare providers and policy makers in the coming century. However, an incomplete understanding of the pathogenesis has left significant knowledge gaps in terms of efficacious therapeutics. To further our comprehension and, in turn, management of metabolic syndrome, appropriate high-fidelity models of the disease complex are of great importance. In this context, our review aims to assess the most promising porcine models of metabolic syndrome currently available for their similarity to the human phenotype. In addition, we aim to highlight the strengths and shortcomings of each model in an attempt to identify the most appropriate application of each. Although no porcine model perfectly recapitulates the human metabolic syndrome, several pose satisfactory approximations. The Ossabaw miniature swine in particular represents a highly translatable model that develops each of the core parameters of the syndrome with many of the associated secondary comorbidities. Future high-fidelity porcine models of metabolic syndrome need to focus on secondary sequelae replication, which may require extended induction period to reveal.
Divergent roles of angiotensin II upon the immediate and sustained increases of renal blood flow following unilateral nephrectomy
Authors: Shimada Satoshi , Yang Chun , Kurth Theresa , Cowley Allen W.
Published: February 2022

This study found that the immediate increases of renal blood flow (RBF) following unilateral nephrectomy (UNX) are a consequence of reduced ANG II type 1 (AT1) receptor stimulation. The continuous monitoring of RBF and intermittent measurement of glomerular filtration rate (GFR) in conscious rats during the 1-wk period of rapid hypertrophy following UNX provided unique insights into the regulation of RBF and GFR when faced with increased metabolic loads. It was found that neither kidney hypertrophy nor the associated increase of capillaries was an AT1-dependent phenomenon.
Fasting-induced HMGCS2 expression in the kidney does not contribute to circulating ketones
Authors: Venable Andrea H. , Lee Lauren E. , Feola Kyle , Santoyo John , Broomfield Tatyana , Huen Sarah C.
Published: February 2022

The mitochondrial enzyme hydroxymethylglutaryl-CoA synthase 2 (HMGCS2) catalyzes the rate-limiting step of ketogenesis. Although the liver constitutively expresses HMGCS2 and is considered the main ketogenic organ, HMGCS2 is induced in the kidney during fasting, leading to the proposal that the kidney contributes to fasting ketosis. We showed kidney HMGCS2 does not contribute to circulating ketones during fasting and cannot compensate for hepatic ketogenic insufficiency.
Performance Analysis and Node Selection of Intelligent Reflecting Surface-Aided Visible Light Communication for Parallel Vehicles
Authors: Zhan Ling , Zhao Hong , Zhang Wenhui , Lin Jiming , Zhao Xiang
Published: February 2022

In the visible light communication (VLC) for parallel vehicles, the light emitted by the headlamps cannot reach the photodiode (PD), which is the receiver installed on another vehicle. To solve this problem, the mirror array-based intelligent reflecting surface- (IRS-) aided VLC system is designed for parallel vehicles, and the system performance with different number of mirrors and transmission distance is analyzed. The maximum distance between adjacent IRSs is calculated via the exhaustive method, and the nearest neighbor iterative search (NNIS) algorithm is proposed for IRS node selection. Numerical results show that the SNR increases with the number of mirrors increasing. If the number of mirrors is

6
×
6

in the IRS, the maximum distance between adjacent IRSs is 37 meters. When the interval between adjacent IRSs is 32 meters, the required BER can be satisfied with merely three IRSs working together according to the NNIS algorithm.
Path Analysis of Agricultural Economy Information Construction under the Perspective of Urban-Rural Integration Strategy in the “Internet Plus” Era
Authors: Xurui Zhang
Published: February 2022

China Internet plus rural industrial integration is applied in the era of agricultural informatization in the era of Internet plus urban integration strategy. For many years, the themes of urban-rural integration, agricultural economy, and rural revitalization have been the core topics of China’s economic research. This study fully integrates the above elements and analyzes the development path of rural economic informatization in China’s special environment. Supported by the national strategic direction and related policies such as the integration of urban and rural areas, Internet plus agriculture, agricultural informatization, and rural revitalization, we hope to achieve faster agricultural economic development through the rational optimization of agricultural economic integration and supervision and promotion programs and the use of the existing information platform. The problems of China’s agricultural economic development caused by historical reasons are thoroughly solved. China’s regional agricultural economy should not only be not limited to the large-scale and intensive development of planting, animal husbandry, forestry, and fishery in the primary industry but also should realize the integration of urban and rural areas under the background of economic informatization, develop the secondary and tertiary industries related to agriculture in the agricultural economic zone, let the agricultural economy get rid of the constraints of the development ideas of the primary industry, and let the high value-added characteristics of the secondary industry and the tertiary industry fully contribute to the development of agricultural economy.
The Role of PKC and HIF-1 and the Effect of Traditional Chinese Medicinal Compounds on Cerebral Ischemia-Reperfusion Injury
Authors: Fang Zheyu , Zhang Yangyang , Zhao Xixi , Jin Weifeng , Yu Li
Published: February 2022

Neuronal death occurs during cerebral ischemia. However, when hemoperfusion and oxygen supply are resumed to the ischemic focus of the brain tissue, the brain tissue damage is further aggravated, resulting in cerebral ischemia-reperfusion injury (CIRI) to the patients. Protein kinase C (PKC) plays an important role in CIRI. Through the IP3/DAG/Ca2+ signaling pathway, it promotes the influx of calcium ions in neurons and causes calcium overload, which aggravates the damage. At the same time, when brain cells are hypoxic, hypoxia-inducible factor-1 (HIF-1) is expressed, which regulates the expression of Bcl-2 and Bax through the PI3K/Akt signaling pathway and reduces nerve cell injury. It also fights hypoxic-ischemic injury by increasing the production of vascular endothelial growth factor (VEGF) to promote blood vessel formation. The PKC and HIF-1 signaling pathways are also linked to CIRI. HIF-1 activates the PKC and ERK pathways via the upregulation of VEGF, leading to increased Cx43 phosphorylation and dysfunction and aggravating CIRI. Existing studies have shown that certain traditional Chinese medicine (TCM) compounds regulate the PKC and HIF-1 signaling pathways and alleviate CIRI. These compounds downregulate the PKC and the activity of the PKC-related signaling pathways to alleviate CIRI. They can also promote the expression of HIF-1, increase the content of VEGF in ischemic tissues to promote the generation of blood vessels, and improve microcirculation. TCM compounds can inhibit the cascade of reactions underlying disease occurrence and development by targeting multiple components using different herbal formulations to improve the structural and material changes in the brain cells, which alleviate CIRI and protect the brain tissue. This study briefly describes the role of PKC and HIF-1, their relationship in CIRI, and the effect of TCM on them.
A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning
Authors: Hao Ruqian , Liu Lin , Zhang Jing , Wang Xiangzhou , Liu Juanxiu , Du Xiaohui , He Wen , Liao Jicheng , Liu Lu , Mao Yuanying
Published: February 2022

Vaginitis is a gynecological disease affecting the health of millions of women all over the world. The traditional diagnosis of vaginitis is based on manual microscopy, which is time-consuming and tedious. The deep learning method offers a fast and reliable solution for an automatic early diagnosis of vaginitis. However, deep neural networks require massive well-annotated data. Manual annotation of microscopic images is highly cost extensive because it not only is a time-consuming process but also needs highly trained people (doctors, pathologists, or technicians). Most existing active learning approaches are not applicable in microscopic images due to the nature of complex backgrounds and numerous formed elements. To address the problem of high cost of labeling microscopic images, we present a data-efficient framework for the identification of vaginitis based on transfer learning and active learning strategies. The proposed informative sample selection strategy selected the minimal training subset, and then the pretrained convolutional neural network (CNN) was fine-tuned on the selected subset. The experiment results show that the proposed pipeline can save 37.5% annotation cost while maintaining competitive performance. The proposed promising novel framework can significantly save the annotation cost and has the potential of extending widely to other microscopic imaging applications, such as blood microscopic image analysis.