bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical mixing of a catalyst and a hydrophobic polymer promotes CO hydrogenation through dehydration
Authors: Fang Wei , Wang Chengtao , Liu Zhiqiang , Wang Liang , Liu Lu , Li Hangjie , Xu Shaodan , Zheng Anmin , Qin Xuedi , Liu Lujie , Xiao Feng-Shou
Published: July 2022

In many reactions restricted by water, selective removal of water from the reaction system is critical and usually requires a membrane reactor. We found that a simple physical mixture of hydrophobic poly(divinylbenzene) with cobalt-manganese carbide could modulate a local environment of catalysts for rapidly shipping water product in syngas conversion. We were able to shift the water-sorption equilibrium on the catalyst surface, leading to a greater proportion of free surface that in turn raised the rate of syngas conversion by nearly a factor of 2. The carbon monoxide conversion reached 63.5%, and 71.4% of the hydrocarbon products were light olefins at 250°C, outperforming poly(divinylbenzene)-free catalyst under equivalent reaction conditions. The physically mixed CoMn carbide/poly(divinylbenzene) catalyst was durable in the continuous test for 120 hours.
Quantum effects in thermal reaction rates at metal surfaces
Authors: Borodin Dmitriy , Hertl Nils , Park G. Barratt , Schwarzer Michael , Fingerhut Jan , Wang Yingqi , Zuo Junxiang , Nitz Florian , Skoulatakis Georgios , Kandratsenka Alexander , Auerbach Daniel J. , Schwarzer Dirk , Guo Hua , Kitsopoulos Theofanis N. , Wodtke Alec M.
Published: July 2022

There is wide interest in developing accurate theories for predicting rates of chemical reactions that occur at metal surfaces, especially for applications in industrial catalysis. Conventional methods contain many approximations that lack experimental validation. In practice, there are few reactions where sufficiently accurate experimental data exist to even allow meaningful comparisons to theory. Here, we present experimentally derived thermal rate constants for hydrogen atom recombination on platinum single-crystal surfaces, which are accurate enough to test established theoretical approximations. A quantum rate model is also presented, making possible a direct evaluation of the accuracy of commonly used approximations to adsorbate entropy. We find that neglecting the wave nature of adsorbed hydrogen atoms and their electronic spin degeneracy leads to a 10× to 1000× overestimation of the rate constant for temperatures relevant to heterogeneous catalysis. These quantum effects are also found to be important for nanoparticle catalysts.
Improving catalysis by moving water
Authors: Ding Mingyue , Xu Yanfei
Published: July 2022

The conversion of gases into building blocks for synthesizing plastics is enhanced
Disruption of sncRNA Improves the Protective Efficacy of Outer Membrane Vesicles against Helicobacter pylori Infection in a Mouse Model
Authors: Li Biaoxian , Xu Yilian , Xu Tian , Guo Zhicheng , Xu Qianwen , Li Yi , Zeng Lingbin , Huang Xiaotian , Liu Qiong
Published: July 2022

The outer membrane vesicles (OMVs) secreted by
Helicobacter pylori
contain various bacterial components, such as proteins, phospholipids, toxins, and nucleic acids, including small noncoding RNA (sncRNA), which have regulatory functions in cell envelope structure, metabolism, bacterial communication, biofilm formation, and virulence. We previously showed that knocking out sncRNAs sR-989262 and sR-2509025 at the cellular level increased interleukin 8 (IL-8) levels in mice exposed to OMVs.
Synechococcus
sp. PCC7002 Uses Peroxiredoxin to Cope with Reactive Sulfur Species Stress
Authors: Liu Daixi , Chen Jinyu , Wang Yafei , Meng Yue , Li Yuanning , Huang Ranran , Xia Yongzhen , Liu Huaiwei , Jiao Nianzhi , Xun Luying , Liu Jihua
Published: July 2022

Cyanobacteria are the earliest microorganisms that perform oxygenic photosynthesis, which has played a key role in the evolution of life on Earth, and they are the most important primary producers in the modern oceans. The cyanobacterium
Synechococcus
sp.
Demographic disparities in unimproved drinking water and sanitation in Ghana: a nationally representative cross-sectional study
Authors: Oppong Felix Boakye , Boateng Dennis , Senkyire Ephraim Kumi , Logo Divine Darlington
Published: July 2022

Objective

The government of Ghana has targeted universal access to safe drinking water by 2025 and elimination of open defecation by year 2030. This study explored the use of unimproved drinking water and unimproved sanitation and assessed their association with demographic factors.

Design

This was a secondary data analysis of the 2017 Ghana Maternal Health Survey, a nationally representative cross-sectional survey. Open defecation households were mapped to show regional differences. Weighted logistic regression was used to assess the association of demographic variables with use of unimproved drinking water and unimproved toilet facilities.

Setting

Ghana.

Participants

A total of 26 324 households were included in the analysis.

Primary and secondary outcome measures

Use of unimproved drinking water and unimproved toilet facilities.

Results

Out of the 26 324 households, 8.9% used unimproved drinking water while 81.6% used unimproved sanitation. Open defecation was practised by 15.2% of Ghanaian households, with a prevalence of 58.8%, 6.7% and 12.5% in the Northern, Middle and Coastal zones, respectively. In the multivariate analysis, rural households (p<0.001), households with more than five members (p<0.001), households with heads less than 25 years (p=0.018), male-headed households (p<0.001) and household heads with no/low level of education (p<0.001) were significantly associated with drinking unimproved water. Also, rural households (p=0.002), households in the Northern zone (p<0.001), single-member households (p<0.001), households with heads less than 25 years (p<0.001) and household heads with no/low level of education (p<0.001) were significantly associated with using unimproved toilet facilities.

Conclusion

The target of universal access to safe drinking water by 2025 and elimination of open defecation by 2030 seems impossible to be achieved if appropriate measures are not implemented. We recommend that state authorities, health partners and non-governmental organisations support local-level sanitation plans and strategies.
Effects of cardiovascular health, musculoskeletal health and physical fitness on occupational performance of firefighters: protocol for a systematic review and meta-analysis
Authors: Ras Jaron , Kengne Andre Pascal , Smith Denise , Soteriades Elpidoforos Soterakis , Leach Lloyd
Published: July 2022

Introduction

Firefighting is a hazardous occupation, where firefighters are involved in life-threatening situations, being placed under tremendous physical strain, while wearing heavy and insulated equipment to protect them from chemicals, fumes and high temperatures. This necessitates that firefighter stay in good physical condition and maintain adequate cardiovascular fitness to cope with these stressors and perform their duties with minimal health risks. The aim of this systematic review and meta-analysis is to determine the effect of cardiovascular health, musculoskeletal health and physical fitness on the occupational performance of firefighters.

Methods and analysis

All study types and designs will be included and appraised. The following electronic databases will be searched: PubMed/Medline, Scopus, Web of Science, Embase, EBSCOHost and CINAHL, with no restrictions on publication date. The literature search will be conducted comprehensively to enable the capturing of as many relevant articles as possible but will be limited to English-language papers only. A combination of the appropriate terms (search string) will be used to ensure the inclusion of the relevant components of the participants, exposure, comparison and outcome. A researcher-generated form with the key characteristics of each study will be used to retrieve all relevant details from the selected studies for initial eligibility screening. The Rayyan Intelligent Systematic Review tool will be used to screen and select studies for inclusion, and information from the included studies will be captured on the researcher-generated data extraction form. The The appraisal tool for cross-sectional studies (AXIS) checklist and the Critical Appraisal Skills Programme toolkit will be used to conduct the methodological assessment of each study. Data will be analysed using Review Manager V.5.3. Generated results will be presented using a combination of figures, graphs and tables. The synthesis of quantitative data (using a meta-analysis methodology) will involve the integration of quantitative findings from multiple studies to achieve coherence.

Ethics and dissemination

This study obtained ethical clearance from the University of the Western Cape Biomedical Research Ethics Committee (BM21/10/9). We will disseminate the findings of in peer-reviewed journals and at national and international conferences. The protocol will form part of a chapter for a doctoral thesis.

PROSPERO registration number

CRD42021258898.
Optimising the secondary use of primary care prescribing data to improve quality of care: a qualitative analysis
Authors: Barbazza Erica , Verheij Robert A , Ramerman Lotte , Klazinga Niek , Kringos Dionne
Published: July 2022

Objectives

To explore available data sources, secondary uses and key considerations for optimising the actionability of primary care prescribing data to improve quality of care in the Dutch context.

Design

An exploratory qualitative study was undertaken based on semi-structured interviews. We anchored our investigation around three tracer prescription types: antibiotics; benzodiazepines and opioids. Descriptive and explanatory themes were derived from interview data using thematic analysis.

Setting

Stakeholders were sampled from across the micro (clinical), meso (organisational) and macro (policy) contexts of the Dutch primary care system.

Participants

The study involved 28 informants representing general practitioners (GPs), community pharmacists, regional chronic care networks (care groups), academia and research institutes, insurers, professional associations, electronic health record (EHR) vendors and national authorities.

Results

In the Netherlands, three main sources of data for improving prescribing in primary care are in use: clinical data in the EHRs of GP practices; pharmacy data in community pharmacy databases and claims data of insurers. While the secondary use of pharmacy and claims data is well-established across levels, the use of these data together with EHR data is limited. Important differences in the types of prescribing information needed by micro-meso-macro context are found, though the extent to which current indicators address these varies by prescription type. Five main themes were identified as areas for optimising data use: (1) measuring what matters, (2) increasing data linkages, (3) improving data quality, (4) facilitating data sharing and (5) optimising fit for use analysis.

Conclusions

To make primary care prescribing data useful for improving quality, consolidated patient-specific data on the indication for a prescription and dispensed medicine, over time, is needed. In the Netherlands, the selection of indicators requires further prioritisation to better signal the appropriateness and long-term use of prescription drugs. Prioritising data linkages is critical towards more actionable use.
Clinical outcome following checkpoint therapy in renal cell carcinoma is associated with a burst of activated CD8 T cells in blood
Authors: Carlisle Jennifer Wilkinson , Jansen Caroline S , Cardenas Maria Andrea , Sobierajska Ewelina , Reyes Adriana Moon , Greenwald Rachel , Del Balzo Luke , Prokhnevska Nataliya , Kucuk Omer , Carthon Bradley C , Mullane Patrick Connor , Osunkoya Adeboye , Baumgarten Deborah , Hosseinzadeh Fares , Wilkinson Scott , Lake Ross , Sowalsky Adam G , Liu Yuan , Master Viraj A , Bilen Mehmet A , Kissick Haydn
Published: July 2022

Purpose

Checkpoint therapy is now the cornerstone of treatment for patients with renal cell carcinoma (RCC) with advanced disease, but biomarkers are lacking to predict which patients will benefit. This study proposes potential immunological biomarkers that could developed for predicting therapeutic response in patients with RCC.

Methods

Using flow cytometry, RNA sequencing, and T-cell receptor (TCR) sequencing, we investigated changes in T cells in the peripheral blood of patients with advanced RCC after receiving immunotherapy. We used immunofluorescence (IF) imaging and flow cytometry to investigate how intratumoral T cells in patients’ tumors (resected months/years prior to receiving checkpoint therapy) predicted patient outcomes after immunotherapy.

Results

We found that a small proportion of CD4 and CD8 T cells in the blood activate following checkpoint therapy, expressing the proliferation marker Ki67 and activation markers HLA-DR and CD38. Patients who had the highest increase in these HLA-DR +CD38+CD8 T cells after treatment had the best antitumor immune response and experienced clinical benefit. Using RNA sequencing, we found that while these cells expanded in most patients, their phenotype did not drastically change during treatment. However, when we analyzed the TCR repertoire of these HLA-DR +CD38+CD8+T cells, we found that only patients who clinically benefitted had a burst of new clonotypes enter this pool of activated cells. Finally, we found that abundant T cells in the untreated tumors predicted clinical benefit to checkpoint therapy on disease progression.

Conclusions

Together, these data suggest that having a strong pre-existing immune response and immediate peripheral T-cell activation after checkpoint therapy is a predictor of clinical benefit in patients with RCC.
Development of a small and transportable de-icing/anti-icing drone-mounted system. Part 2: Prototype testing and proof of concept
Authors: Villeneuve Eric , Karmouch Eric , Boulerice Xavier
Published: July 2022

During winter, aircraft de-icing and anti-icing is a significant part of the operations at large airports. These mandatory operations ensure that the aircraft is clean of any contaminations during take-off. However, these operations are complex due to the heavy equipment required. They cannot be performed at most small airports and remote northern locations. As part of Canada’s Department of National Defense Innovation for Defense Excellence and Security research program, a study to design a de/anti-icing system mounted onto a drone has been initiated. This system should greatly increase the flexibility of these operations, allowing them to be easily performed when no other infrastructure is available. The developed system can even be transported inside the aerial vehicle itself for operations at its initial location and at its destinations. This paper presents the second part of this study in which the system is first tested under laboratory controlled conditions to demonstrate its ability to perform de/anti-icing operations with a real fluid. Then, a flight test is performed for a proof-of-concept in which the system successfully cleans a commercial box truck from contaminants.
Transformational changes for achieving the Post-2020 Global Biodiversity Framework ecological connectivity goals
Authors: Lemieux Christopher J. , Beazley Karen F. , MacKinnon David , Wright Pamela , Kraus Daniel , Pither Richard , Crawford Lindsay , Jacob Aerin L. , Hilty Jodi
Published: July 2022

The first draft of the United Nations Convention on Biological Diversity (CBD) Post-2020 Global Biodiversity Framework (GBF) includes an unprecedented call for states that have ratified the treaty (Parties) to implement measures to maintain and enhance ecological connectivity as urgent actions to abate further biodiversity loss and ecosystem decline. Considering the challenges that lie ahead for Parties to the CBD, we highlight the ways in which effective and equitable connectivity conservation can be achieved through four transformative changes, including: (1) mainstreaming connectivity retention and restoration within biodiversity conservation sector and influencing sectors (e.g., transportation, energy, agriculture, forestry); (2) mainstreaming financial resources and incentives to support effective implementation; (3) fostering collaboration with a focus on cross-sector collective action; and (4) investing in diverse forms of knowledge (co-)production and management in support of adaptive governance. We detail 15 key actions that can be used to support the implementation of these transformative changes. While ambitious, the transformative changes and associated key actions recommended in this perspective will need to be put in place with unprecedented urgency, coherency, and coordination if Parties to the CBD truly aspire to achieve the goals and targets of the forthcoming Post-2020 GBF in this new decade of biodiversity.
The pion in the graviton soft-wall model: phenomenological applications
Authors: Rinaldi Matteo , Ceccopieri Federico Alberto , Vento Vicente
Published: July 2022

The holographic graviton soft-wall model, introduced to describe the spectrum of scalar and tensor glueballs, is improved to incorporate the realization of chiral-symmetry as in QCD. Such a goal is achieved by including the longitudinal dynamics of QCD into the scheme. Using the relation between AdS/QCD and light-front dynamics, we construct the appropriate wave function for the pion which is used to calculate several pion observables. The comparison of our results with phenomenology is remarkably successful.
An Intelligent Face Recognition Technology for IoT-Based Smart City Application Using Condition-CNN with Foraging Learning PSO Model
Authors: Rajendran Surendran , Sundarapandi Arun Mozhi Selvi , Krishnamurthy Anbazhagan , Thanarajan Tamilvizhi
Published: July 2022

The internet of things (IoT) is a rapidly expanding network of smart digital devices that can communicate with one another and be controlled remotely over the internet. Moreover, IoT devices are cheap and can be used to control and monitor activities remotely. Due to this reason, IoT is widely used in the applications of a smart city. Moreover, the smart devices that are used in IoT-based smart city applications are used to gather information from devices, humans, and other sources for analyzing purposes. Hence, it is crucial to conduct the face recognition process to ensure the safety of the city. Several works were conducted by the researchers to recognize the face accurately. Typically, the effectiveness of achieving face recognition is still an intricate one. To tackle those issues, we have proposed a novel condition convolutional neural network (condition-CNN)-based bee foraging learning (BFL)-based particle swarm optimization (PSO) algorithm (CCNNBFLPSO). To recognize the facial images from the face image datasets, the proposed CCNNBFLPSO model is used. To ensure the prediction accuracy condition, CNN uses the conditional probability weight matrix (CPWM) to estimate the higher and lower class level of image features. Meanwhile, the learning of CPWM can be performed by utilizing the adopted BPL-PSO approach. For experimental purposes, we have taken three datasets namely the CVL face database, the MUCT database, and the CMU multi-PIE face database. The training time and the training accuracy are analyzed for all the three datasets, and comparative studies are performed with state-of-art works such as LBPH, FoL TDL, and TPS approaches. The training and validation loss functions are analyzed with baseline CNNs, B-CNN, and condition-CNN. The proposed approach accomplishes better face recognition accuracy and F1-score of about 99.9% and 99.9%, respectively.
Fault Diagnosis of Industrial Robots Based on Phase Difference Correction Method
Authors: Xie Changgui , Xu Hao
Published: July 2022

Aiming at the characteristics of the fault spectrum of industrial robots, a new phase difference correction method is proposed on the basis of Fourier transform, which combines autocorrelation technology and windowing technology to convert the original signal into a discrete spectrum with fault characteristics, which effectively improves the accuracy of fault spectrum correction and provides important help for robot fault diagnosis. Simulation analysis and example verification show that the new algorithm is quite effective in the extraction of industrial robot fault features, and the algorithm still has a smaller relative error than the traditional algorithm under noise conditions, with high estimation accuracy and strong compatibility and robustness. The algorithm not only has high theoretical value in pattern recognition, but also has great practical significance in engineering fields such as robot diagnosis.
The role of closed timelike curves in particle motion within van Stockum spacetime: A generalization
Authors: Dutta Ayanendu , Roy Dhritimalya , Chakraborty Subenoy
Published: July 2022

This work analyzes the particle motion in the van Stockum spacetime considering the existence of closed timelike curves (CTCs). Test particles with or without angular momentum are studied in the present geometry. It is found that only nonzero angular momentum test particles exist in the neighborhood of CTCs. The minimum particle energy and the range of backward time jump in closed timelike geodesics (CTGs) are studied within a Cauchy horizon. Finally, a general prescription for CTC and CTG has been presented with appropriate examples.
EFFECT OF FRICTIONAL HEATING ON MECHANICALLY MIXED LAYERS DURING DRY SLIDING CONTACT OF Ti-6Al-4V ALLOYS AT HIGH TEMPERATURE IN VACUUM CONDITION
Authors: LAL BASANT , DEY ABHIJIT , WANI M. F.
Published: July 2022

Ti-6Al-4V (an [Formula: see text] titanium alloy) pins were slid against the SS316L disc in a pin-on-disc apparatus at different temperatures under vacuum and ambient conditions. Tribological characterization was performed using a field emission scanning electron microscope (FESEM) equipped with energy dispersive X-ray (EDAX) analysis and X-ray diffraction. The worn pin surfaces of Ti-6Al-4V were investigated in order to identify the effect of frictional heating at the interface of tribo-pair. To investigate the effects of frictional heating on mechanically mixed layer (MML), experiments were performed under vacuum conditions ([Formula: see text] Torr) by varying the temperature from 25°C to 400°C at a constant sliding speed of 0.01[Formula: see text]ms[Formula: see text] and at constant normal load of 137[Formula: see text]N. The material was found to transfer from the counter-face to the worn pin surface of alloy where an MML and tribo-oxide (TO) layer were observed to developed on the worn pin surfaces under both the experimental environments. Moreover, a new mechanism, called the “debris burial mechanism” during the formation of the MML at different temperatures was obtained at the interface. The rate of wear was observed to decreased with the increase in frictional heating at the interface resulting to the progressive formation of thicker MML over the worn pin surface. The wear resistances in Ti–6Al–4V alloy decrease rapidly due to loosening the generated MML on the sliding surface.
A Deep Energy Method for the Analysis of Thermoporoelastic Functionally Graded Beams
Authors: Mojahedin Arvin , Hashemitaheri Maryam , Salavati Mohammad , Fu Xiaolong , Rabczuk Timon
Published: July 2022

In this paper, we present a deep energy method for functionally graded beams based on both Euler–Bernoulli and Timoshenko beam theory to study their mechanical and thermal properties. We consider the effect of temperature as well as porosity under saturated and unsaturated conditions. The objective function is related to the total potential energy (and boundary conditions) and minimized through neural network training. The results are validated by comparison with benchmark problems available in the literature.
Engineered Interphase Mechanics in Single Lap Joints: Analytical and PINN Formulations
Authors: Budarapu P. R. , Kumar S. , Khan M. A. , Rammohan B. , Anitescu C.
Published: July 2022

Adhesively bonded joints showcase non-uniform stress distribution, along their length as the load is transferred through layers of dissimilar stiffness. For efficient transfer of loads, the peak interfacial shear stress is required to be engineered. In this study, inspired by electric pulses, the interphase modulus is modified according to square, sinusoidal and triangular pulses. The variation in peak stresses with increased number of pulses up to four is also investigated. The developed analytical model is solved for the interfacial shear stresses as well as the peel stresses, using energy functional approach, through MAPLE software. The abrupt changes in modulus in square pulse graded interphase are observed to create highest interfacial shear stresses among the considered grading profiles. Furthermore, the peak interfacial stresses are observed to increase with increased number of pulses. An effective elastic modulus parameter is defined to indicate the area under the modulus profile curve. The effective modulus is found to be gradually increasing with increase number of pulses in square graded interphase. Whereas, it is constant for sinusoidal- and triangular-graded interphases. A deep machine learning-based physics informed neural network model is developed to quickly solve the developed governing differential equations. Therefore, results from the machine leaning model are compared to the analytical results.
Element Differential Method for Computational Acoustics in Time Domain
Authors: Zhu Yu-Mo , Gao Xiao-Wei
Published: July 2022

In this paper, a new robust numerical method, named element differential method (EDM), is developed to solve computational acoustic problems in time domain. The key aspect of the method is the direct differentiation of shape functions of the isoparametric elements used to characterize the geometry and physical variables, which can be utilized to evaluate the spatial partial derivatives of the physical variables appearing in the governing equations and boundary conditions. Moreover, a unique collocation technique is proposed to form the system of equations, in which the governing equation is collocated at internal nodes of elements and the acceleration equilibrium equation is collocated at interface nodes between elements and outer surface nodes. EDM is a strong-form numerical method that doesn’t require a variational principle or a control volume to set up the computational scheme, and no integration is performed. Based on the Newmark difference technique, a time marching solution scheme is developed for solving the time-dependent system of equations. For the point sound source expressed in terms of the Dirac function, a sound source density function is proposed to approximate the point sound source to make it handleable in EDM. Three numerical examples are given to demonstrate the correctness and application potential of the developed method.
Energy in the relativistic theory of gravity
Authors: Koivisto Tomi
Published: July 2022

The more precise definition and the more fundamental understanding of the concepts of time, energy, entropy and information are building upon the new, relativistic foundation of gravity. This lecture is an attempt to explain the basic principles that underpin this progress, by focusing on the simple but subtle universal definition of energy. The principles are unearthed from Einstein’s theory and Noether’s theorems, beneath a century of misconceptions.
Agegraphic model based on the generalized uncertainty principle
Authors: Sadatian S. Davood , Sabouri A.
Published: July 2022

Many models of dark energy have been proposed to describe the universe since the beginning of the Big Bang. In this study, we present a new model of agegraphic dark energy based on the three generalized uncertainty principles KMM (Kempf, Mangan, Mann), Nouicer and [Formula: see text] (higher orders generalized uncertainty principle). Using the obtained relations from three types of Generalized Uncertainty Principle (GU P), in the form of three scenarios (Emergent, Intermediate, Logamediate), we consider three different eras of the universe evolution. Also, we describe the evolution and expansion of the universe in each subsection. We will plot the obtained relations in these models for better comparatione.
Lie symmetry analysis, exact solutions and power series solutions of the logarithmic Monge–Ampère flow evolution equation
Authors: Ma Yanzhi , Song Yunjia , Yang Ben , Wang Zenggui
Published: July 2022

In this paper, the logarithmic Monge–Ampère flow evolution equation is studied by the classical Lie symmetry analysis method. First, the optimal system was obtained by the adjoint representation table. Second, by performing symmetric transformation on the optimal system, the corresponding ordinary differential equations are obtained, and the Jacobian elliptic function solution, the periodic solution and the power series solution are constructed. Finally, the dynamical behaviors of the solutions are described by choosing arbitrary parameters.
Marder space-time with Tsallis holographic dark energy
Authors: Santhi M. Vijaya , Chinnappalanaidu T.
Published: July 2022

This present communication is an outcome of the investigation on newly proposed holographic dark energy model such as the Tsallis holographic dark energy (THDE) with Hubble horizon cutoff regarded as IR cutoff (infrared cutoff) for a spatially homogeneous and anisotropic Marder space-time in the framework of general relativity theory (GRT). Here, we have constructed the THDE models with Hubble horizon cutoff in three different ways, based on the following possibilities: (i) a varying deceleration parameter proposed by Mishra et al., (ii) hybrid expansion law (HEL) proposed by Akarsu et al. and (iii) a linearly varying deceleration parameter (LVDP) given by Akarsu and Dereli. The rapid expansion of the cosmos is thus justified for obtained models through the deceleration parameter (DP). In this way, the equation of state (EoS) parameter ([Formula: see text]) of the models describe the phantom and quintessence phases of the cosmos. Also, we compare the cosmological parameters of the obtained models with the parameters of [Formula: see text]CDM model, which indicates that the models-I and II are nearly identical to the [Formula: see text]CDM model.
LesionTalk: Core Data Extraction and Multi-class Lesion Detection in IoT-based Intelligent Healthcare
Authors: Guo Kehua , Zhu Feihong , Zhou Xiaokang , Zhang Lingyan , Wang Yifei , Kang Jian
Published: July 2022

With the development of intelligent medicine, lesion detection supported by Internet of Things (IoT), big data, and deep learning has become a hotspot. However, lesion detection technology based on deep learning requires huge amounts of high-quality medical image data, and the data from social IoT has the problems of uneven quality and lack of lesion labeling. Current studies usually ignore the unstable quality of IoT data and the interpretability of diagnostic results, resulting in deeper model layers, larger models, poor real-time performance, and lack of persuasion. To address the problems, this article first proposes a core data extraction method for multi-class lesion detection based on unlabeled medical image from social IoT. Then, we propose an ensemble algorithm based on lightweight models to improve the detection accuracy. Finally, we visualize pathological features to enhance the interpretability of core data and detection results. The experimental results show that our method can effectively extract the core data of multiple lesions from low-quality medical images and improve the accuracy of the lightweight lesion detection model as well as the interpretation of detection results.
Exploiting Rateless Codes and Cross-layer Optimization for Low-power Wide-area Networks
Authors: Lv Jiamei , Chen Gonglong , Dong Wei
Published: July 2022

Long communication range and low energy consumption are the two most important design goals of Low-power Wide-area Networks (LPWANs); however, many prior works have revealed that the performance of LPWAN in practical scenarios is not satisfactory. Although there are PHY-layer and link-layer approaches proposed to improve the performance of LPWAN, they either rely heavily on the hardware modifications or suffer from low data recovery capability, especially with bursty packet loss patterns. In this article, we propose a practical system, eLoRa, for COTS devices. eLoRa utilizes rateless codes and joint decoding with multiple gateways to extend the communication range and lifetime of LoRaWAN. To further improve the performance of LoRaWAN, eLoRa optimizes parameters of the PHY-layer (e.g., spreading factor) and the link layer (e.g, block length). We implement eLoRa on COTS LoRa devices and conduct extensive experiments on an outdoor testbed to evaluate the effectiveness of eLoRa. Results show that eLoRa can effectively improve the communication range of DaRe and LoRaWAN by 43.2% and 55.7% with a packet reception ratio higher than 60%, and increase the expected lifetime of DaRe and LoRaWAN by 18.3% and 46.6%.
Computational thinking in the era of data science
Authors: Mike Koby , Ragonis Noa , Rosenberg-Kima Rinat B. , Hazzan Orit
Published: July 2022

Incorporating data thinking into computer science education.
Deep Q Network–Driven Task Offloading for Efficient Multimedia Data Analysis in Edge Computing–Assisted IoV
Authors: Yang Chenyi , Xu Xiaolong , Zhou Xiaokang , Qi Lianyong
Published: July 2022

With the prosperity of Industry 4.0, numerous emerging industries continue to gain popularity and their market scales are expanding ceaselessly. The Internet of Vehicles (IoV), one of the thriving intelligent industries, enjoys bright development prospects. However, at the same time, the reliability and availability of IoV applications are confronted with two major bottlenecks of time delay and energy consumption. To make matters worse, massive heterogeneous and multi-dimensional multimedia data generated on the IoV present a huge obstacle to effective data analysis. Fortunately, the advent of edge computing technology enables tasks to be offloaded to edge servers, which significantly reduces total overhead of IoV systems. Deep reinforcement learning (DRL), equipped with its excellent perception and decision-making capability, is undoubtedly a dominant technology to solve task offloading problems. In this article, we first employ an optimized Fuzzy C-means algorithm to cluster vehicles and other edge devices according to their respective service quality requirements. Then, we employ an election algorithm to assist in maintaining the stability of the IoV. Last, we propose a task-offloading algorithm based on the Deep Q Network (DQN) to acquire an optimal task offloading scheme. Massive simulation experiments demonstrate the superiority of our method in minimizing time delay and energy consumption.
A Novel Time-Interval Based Modulation for Large-Scale, Low-Power, Wide-Area-Networks
Authors: Sangar Yaman , Biradavolu Yoganand , Krishnaswamy Bhuvana
Published: July 2022

Wireless communication over long distances has become the bottleneck for battery-powered, large-scale deployments. Low-power protocols like Zigbee and Bluetooth Low Energy have limited communication range, whereas long-range communication strategies like cellular and satellite networks are power-hungry. Technologies that use narrow-band communication like LoRa, SigFox, and NB-IoT have low spectral efficiency, leading to scalability issues. The goal of this work is to develop a communication framework that is energy efficient, long-range, and scalable. We propose, design, and prototype WiChronos, a communication paradigm that encodes information in the time interval between two narrowband symbols to drastically reduce the energy consumption in a wide area network with large number of senders. We leverage the low data-rate and relaxed latency requirements of such applications to achieve the desired features identified above. We design and implement chirp spread spectrum transmitter and receiver using off-the-shelf components to send the narrowband symbols. Based on our prototype, WiChronos achieves an impressive 60% improvement in battery life compared to state-of-the-art LPWAN technologies in transmission of payloads less than 10 bytes at experimentally verified distances of over 4 km. We also show that more than 1,000 WiChronos senders can co-exist with less than 5% collision probability under low traffic conditions.
A Deep Neural Network Accelerator using Residue Arithmetic in a Hybrid Optoelectronic System
Authors: Peng Jiaxin , Alkabani Yousra , Puri Krunal , Ma Xiaoxuan , Sorger Volker , El-Ghazawi Tarek
Published: July 2022

The acceleration of
Deep Neural Networks (DNNs)
has attracted much attention in research. Many critical real-time applications benefit from DNN accelerators but are limited by their compute-intensive nature. This work introduces an accelerator for
Convolutional Neural Network (CNN)
, based on a hybrid optoelectronic computing architecture and
residue number system (RNS)
. The RNS reduces the optical critical path and lowers the power requirements. In addition, the
wavelength division multiplexing (WDM)
allows high-speed operation at the system level by enabling high-level parallelism. The proposed RNS compute modules use one-hot encoding, and thus enable fast switching between the electrical and optical domains. We propose a new architecture that combines residue electrical adders and optical multipliers as the matrix-vector multiplication unit. Moreover, we enhance the implementation of different CNN computational kernels using WDM-enabled RNS based integrated photonics. The area and power efficiency of the proposed accelerator are 0.39 TOPS/s/mm
2
and 3.22 TOPS/s/W, respectively. In terms of computation capability, the proposed chip is 12.7× and 4.02× better than other optical implementation and memristor implementation, respectively. Our experimental evaluation using DNN benchmarks illustrates that our architecture can perform on average more than 72 times faster than GPU under the same power budget.
Polymerization-Pyrolysis Assisted Construction of Multiscale Porous Carbon for High-Performance Supercapacitors
Authors: Feng Liping , Chang Yunzhen , Song Hua , Hou Wenjing , Zhang Ying , Zhao Yun , Xiao Yaoming , Zhu Sheng , Han Gaoyi
Published: July 2022

High energy density combined with rapid mass transport is highly desired for carbon-based electrical double-layer capacitors. Here, multiscale porous carbon has been constructed by an efficient polymerization-pyrolysis strategy. The resorcinol-formaldehyde polymer anchored with Fe3+ is firstly prepared, and the in situ formed Fe3O4 nanoparticles act as mesoporous template during the pyrolysis process. The resultant hierarchically porous carbon achieves an extended surface area of 2260.3 m2 g−1 and wide pore size distributions including micro-, meso-, and macropores. The synergism of large surface area, high conductivity, and interconnected ion transport channels leads to superior energy storage performances of prepared multiscale porous carbon electrode. It delivers a high specific capacitance of 271.7 F g−1 at 0.5 A g−1 in KOH electrolyte, accompanied with a prominent capacitance retention of 88.5% when the current density is 10.0 A g−1. Besides, the assembled symmetric supercapacitor using organic electrolyte exhibits a maximum energy density of 54.0 Wh kg−1 at the power density of 750.0 W kg−1, as well as the superior cyclic stability with a capacitance retention of 88.2% after 10000 cycles.
Satellite cell depletion does not affect diaphragm adaptations to hypoxia
Authors: Thomas Nicholas T. , Confides Amy L. , Fry Christopher S. , Dupont-Versteegden Esther E.
Published: July 2022

Satellite cells show consistent fusion into diaphragm muscle fibers throughout life, suggesting a critical role in maintaining homeostasis. Here, we report identical diaphragm adaptations to hypoxia with and without satellite cells in adult and aged mice. In addition, we propose that the higher number of Pax3-positive cells in satellite cell-depleted diaphragm muscle acts as a compensatory mechanism.
Perceptions of Risk and Responses to Tanning Bed Warning Labels: A Pilot Study
Authors: McGrath John M. , Wallace Harry
Published: July 2022

Tanning bed use has been linked to increases in skin cancer among young women. Although a causal relationship between ultraviolet radiation emitted by tanning beds and melanoma is well established, it is unclear if tanning bed users are aware of the risk and how they would respond to a warning message. Two hundred and ten women aged 16–29 who had used a tanning bed at least once in the last year were asked about their perceptions of risk and their responses to a warning label. Participants were already aware that tanning beds could cause cancer, but after viewing a warning label, most people said they would stop or reduce their tanning bed use. Reactions to a prototype warning label were encouraging and future research should pursue the possibility that current guidelines for tanning bed warning labels may need to be revised.
ERCP-Related Adverse Events in Primary Sclerosing Cholangitis: A Systematic Review and Meta-Analysis
Authors: Natt Navneet , Michael Faith , Michael Hope , Dubois Sacha , Al Mazrou’i Ahmed
Published: July 2022

Background and Aims. While endoscopic retrograde cholangiopancreatography (ERCP) is a valuable diagnostic and therapeutic tool in primary sclerosing cholangitis (PSC), there is conflicting data on associated adverse events. The aims of this systematic review and meta-analysis are to (1) compare ERCP-related adverse events in patients with and without PSC and (2) determine risk factors for ERCP-related adverse events in PSC. Methods. Embase, PubMed, and CENTRAL were searched between January 1, 2000, and May 12, 2021. Eligible studies included adults with PSC undergoing ERCP and reported at least one ERCP-related adverse event (cholangitis, pancreatitis, bleeding, and perforation) or an associated risk factor. The risk of bias was assessed with the Newcastle-Ottawa scale and Cochrane Risk of Bias 2. Raw event rates were used to calculate odds ratios (ORs) and then pooled using random-effects models. Results. Twenty studies met eligibility criteria, of which four were included in a meta-analysis comparing post-ERCP adverse events in patients with PSC (n = 715) to those without PSC (n = 9979). We found a significant threefold increase in the 30-day odds of cholangitis in PSC compared to those without (OR 3.263, 95% CI 1.076–9.896;

p
=
0.037

). However, there were no significant differences in post-ERCP pancreatitis (PEP), bleeding, or perforation. Due to limitations in primary data, only risk factors contributing to PEP could be analyzed. Accidental passage of the guidewire into the pancreatic duct (OR 7.444, 95% CI 3.328–16.651;

p
<
0.001

; I2 = 65.0%) and biliary sphincterotomy (OR 4.802, 95% CI 1.916–12.033;

p
=
0.001

; I2 = 73.1%) were associated with higher odds of PEP in a second meta-analysis including five studies. Conclusions. In the context of limited comparative data and heterogeneity, PSC patients undergoing ERCP have higher odds of cholangitis despite the majority receiving antibiotics. Additionally, accidental wire passage and biliary sphincterotomy increased the odds of PEP. Future studies on ERCP-related risks and preventive strategies are needed.
Laparoscopic Surgery for Pheochromocytoma in Hemodialysis Patients
Authors: Tatarano Shuichi , Mitsuke Akihiko , Sakaguchi Takashi , Matsushita Ryosuke , Inoguchi Satoru , Yoshino Hirofumi , Nishimura Hiroaki , Yamada Yasutoshi , Enokida Hideki
Published: July 2022

Objectives. We analyzed the clinical outcomes of laparoscopic adrenalectomy for pheochromocytomas in hemodialysis compared with nonhemodialysis patients. Methods. Fifty-seven patients (7 hemodialysis and 50 nonhemodialysis) were included in the study. We analyzed the differences in clinical parameters and outcomes between the hemodialysis patient groups and nonhemodialysis patient groups as well as identified predictors for an intraoperative hypertensive spike. Results. The increasing intravascular volume before surgery in hemodialysis patients made perioperative hemodynamic management safer. No significant difference in clinical parameters between the two groups was observed except for the length of hospitalization that was significantly longer in the hemodialysis patients (9 vs. 6 days,

P
=
0.005

). An increase in systolic blood pressure at CO2 insufflation was an independent predictor of a hypertensive spike with a cutoff value of 22.5 mmHg (odds ratio 1.038, 95% confidence interval 1.012–1.078). Conclusion. Laparoscopic adrenalectomy for pheochromocytomas in hemodialysis was safe and feasible. An increase in systolic blood pressure at CO2 insufflation was a predictor of the intraoperative hypertensive spike. The research in this manuscript is not registered. This is a retrospective study.
Construction and Evaluation of College Students’ Psychological Quality Evaluation Model Based on Analytic Hierarchy Process
Authors: Shi Wei
Published: July 2022

College students are a special group of society, having received university education and being at the forefront of new ideas and technologies in society. The basic psychological characteristics common to modern college students and the unique role psychological characteristics of ordinary students are the two major group factors. The basic psychological factors include cognition, personality, and social adaptive behavior. Hierarchical analysis (AHP) is a scientific method for assessing and identifying problems, correlating quantitative treatment of problems with qualitative analysis, and is well suited for semistructured or unstructured decision-making problems. This paper preliminarily studies the structure of College Students’ psychological quality under the background of localization and the construction method of College Students’ psychological quality evaluation model based on analytic hierarchy process. It is proposed to introduce the hierarchical analysis method into the behavioral assessment model of college students’ psychological disorders as the entry point. A model was built to help college ideological and political educators determine whether college students have psychological disorders and disorders provide important insights. The results showed that the split-half reliability of this constructed method was 0.782, and the retest reliability was 0. The standard deviation of the coefficients among all the test subjects was 0.842, indicating that there is a positive correlation between the coefficients. The standard deviation of the coefficients between all test subjects was 0.842, indicating good confidence. Therefore, the model can objectively assess the psychological state of college students and realize the quantitative safety psychological assessment of college students, which is useful for reference in the implementation of teaching decisions.