bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying key influences on antibiotic use in China: a systematic scoping review and narrative synthesis
Authors: Coope Caroline , Schneider Annegret , Zhang Tingting , Kadetz Paul , Feng Rui , Lambert Helen , Wang DeBin , Oliver Isabel , Michie Susan , Cabral Christie
Published: March 2022

Introduction

The inappropriate use of antibiotics is a key driver of antimicrobial resistance. In China, antibiotic prescribing and consumption exceed recommended levels and are relatively high internationally. Understanding the influences on antibiotic use is essential to informing effective evidence-based interventions. We conducted a scoping review to obtain an overview of empirical research about key behavioural, cultural, economic and social influences on antibiotic use in China.

Methods

Searches were conducted in Econlit, Medline, PsycINFO, Social Science citation index and the Cochrane Database of Systematic Reviews for the period 2003 to early 2018. All study types were eligible including observational and intervention, qualitative and quantitative designs based in community and clinical settings. Two authors independently screened studies for inclusion. A data extraction form was developed incorporating details on study design, behaviour related to antibiotic use, influences on behaviour and information on effect (intervention studies only).

Results

Intervention studies increased markedly from 2014, and largely focused on the impact of national policy and practice directives on antibiotic use in secondary and tertiary healthcare contexts in China. Most studies used pragmatic designs, such as before and after comparisons. Influences on antibiotic use clustered under four themes: antibiotic prescribing; adherence to antibiotics; self-medicating behaviour and over-the-counter sale of antibiotics. Many studies highlighted the use of antibiotics without a prescription for common infections, which was facilitated by availability of left-over medicines and procurement from local pharmacies.

Conclusions

Interventions aimed at modifying antibiotic prescribing behaviour show evidence of positive impact, but further research using more robust research designs, such as randomised trials, and incorporating process evaluations is required to better assess outcomes. The effect of national policy at the primary healthcare level needs to be evaluated and further exploration of the influences on antibiotic self-medicating is required to develop interventions that tackle this behaviour.
What, how, when and who of trial results summaries for trial participants: stakeholder-informed guidance from the RECAP project
Authors: Bruhn Hanne , Campbell Marion , Entwistle Vikki , Humphreys Rosemary , Jayacodi Sandra , Knapp Peter , Tizzard Juliet , Gillies Katie
Published: March 2022

Objective

To generate stakeholder informed evidence to support recommendations for trialists to implement the dissemination of results summaries to participants.

Design

A multiphase mixed-methods triangulation design involving Q-methodology, content analysis, focus groups and a coproduction workshop (the REporting Clinical trial results Appropriately to Participants project).

Setting

Phase III effectiveness trials.

Participants

A range of participants were included from ongoing and recently completed trials, public contributors, trialists, sponsors, research funders, regulators, ethics committee members.

Results

Fewer than half of the existing trial result summaries contained information on the clinical implications of the study results, an item deemed to be of high importance to participants in the Q-methodology study. Priority of inclusion of a thank you message varied depending on whether considering results for individuals or populations. The need for personally responsive modes of sharing trial result summaries was highlighted as important. Ideally, participants should be the first to know of the results with regard to the timing of sharing results summaries but given this can be challenging it is therefore important to manage expectations. In addition to patients, it was identified that it is important to engage with a range of stakeholders when developing trial results summaries.

Conclusions

Results summaries for trial participants should cover four core questions: (1) What question the trial set out to answer?; (2) What did the trial find?; (3) What effect have the trial results had and how will they change National Health Service/treatment?; and (4) How can I find out more? Trial teams should develop appropriately resourced plans and consult patient partners and trial participants on how ‘best’ to share key messages with regard to content, mode, and timing. The study findings provide trial teams with clear guidance on the core considerations of the ‘what, how, when and who’ with regard to sharing results summaries.
Development of a minimum dataset for subacute rehabilitation: a three-round e-Delphi consensus study
Authors: Young Adrienne M , Chung Hannah , Chaplain Alicia , Lowe Joshua R ,   STARS Rehabilitation Dataset Development Group, Wallace Sarah J
Published: March 2022

Objectives

To develop a minimum dataset to be routinely collected across a heterogenous population within a subacute rehabilitation service to guide best care and outcomes for patients, and value for the health service.

Design

Three-round e-Delphi exercise, followed by consensus meetings.

Setting

Multicentre study in Brisbane, Australia.

Participants

Rehabilitation decision-makers, researchers and clinicians were invited to participate in the e-Delphi exercise. A multidisciplinary project steering committee (rehabilitation decision makers, researchers, clinicians and consumers) participated in consensus meetings.

Methods

In round 1 of the e-Delphi, participants responded to an open-ended question, generating data and outcomes that should be routinely collected in rehabilitation. In rounds 2 and 3, participants rated the importance of collecting each item on a nine-point scale. Consensus was defined a priori, as items rated as ‘essential’ by at least 70%, and of ‘limited importance’ by less than 15%, of respondents. Consensus meetings were held to further refine and define the dataset for implementation.

Results

In total, 38 participants completed round 1 of the e-Delphi. Qualitative content analysis of their responses generated 1072 codes, which were condensed into 39 categories and 209 subcategories. Following two rounds of rating (round 2: n=32 participants; round 3: n=28 participants), consensus was reached for 124 items. Four consensus meetings (n=14 participants) resulted in the final dataset which included 42 items across six domains: (1) patient demographics, (2) premorbid health and psychosocial information, (3) admission information, (4) service delivery and interventions, (5) outcomes and (6) caregiver information and outcomes.

Conclusions

We identified 42 items that reflect the values and experiences of rehabilitation stakeholders. Items unique to this dataset include caregiver information and outcomes, and detailed service delivery and intervention data. Future research will establish the feasibility of collection in practice.
Ethics and ENDS
Authors: Fenton Elizabeth , Robertson Lindsay , Hoek Janet
Published: March 2022

As debate persists over regulating electronic nicotine delivery systems (ENDS), those favouring liberal ENDS policies have advanced rights-based arguments privileging harm reduction to people who smoke over harm prevention to children and never-smokers. Recent ethical arguments advocate regulating ENDS to prioritise their harm reduction potential for people who currently smoke over any future harm to young never-smokers. In this article, we critically assess these arguments, in particular, the assumption that ethical arguments for prioritising the interests of young people do not apply to ENDS. We argue that, when the appropriate comparators are used, it is not clear the weight of ethical argument tips in favour of those who currently smoke and against young never-smokers. We also assert that arguments from a resource prioritisation context are not appropriate for analysing ENDS regulation, because ENDS are not a scarce resource. Further, we reject utilitarian arguments regarding maximising net population health benefits, as these do not adequately consider vulnerable groups’ rights, or address the population distribution of benefits and harms. Lastly, we argue that one-directional considerations of harm reduction do not recognise that ENDS potentially increase harm to those who do not smoke and who would not otherwise have initiated nicotine use.
An Output-Space Based Branch-and-Bound Algorithm for Sum-of-Linear-Ratios Problem
Authors: Zhang Bo , Gao Yuelin
Published: March 2022

Founded on the idea of subdividing the [Formula: see text]-dimensional output space, a branch-and-bound algorithm for solving the sum-of-linear-ratios(SLR) problem is proposed. First, a two-stage equivalent transformation method is adopted to obtain an equivalent problem(EP) for the problem SLR. Second, by dealing with all nonlinear constraints and bilinear terms in EP and its sub-problems, a corresponding convex relaxation subproblem is obtained. Third, all redundant constraints in each convex relaxation subproblem are eliminated, which leads to a linear programming problem with smaller scale and fewer constraints. Finally, the theoretical convergence and computational complexity of the algorithm are demonstrated, and a series of numerical experiments illustrate the effectiveness and feasibility of the proposed algorithm.
EXPERIMENTAL ANALYSIS OF 3D PRINTED PALLET MODEL THROUGH FUSED DEPOSITION MODELING
Authors: BAIRAPUDI ANIL , CHANDRASEKHARA SASTRY C. , VERMA CHETAN
Published: March 2022

Disparate industry bodies across the planet use pallets for storing large and heavy objects. Pallets provide an assurance of safe handling of material (cargo) and storage of material in a damage-free environment. In this work, an attempt has been made to analyze and investigate making pallets out of ULTEM 9805 using the latest additive techniques (FDM). The maximum deflections and von Mises stresses are analyzed for the disparate boundary conditions indicating the possible alternatives or loads to be used. Study of surface (morphology) and characteristics was done in order to establish the relationship between pallet surface and its application. The factors of load, maximum and minimum values, ascertained in each stage are 168.15, 522.22, 215.31 and 316.79 kPa as well as 18.77, 6.7, 1.2 and 35.84 kPa for the floor, rack, forklift and conveyor load supports, respectively. A cross-hatched design causes a rise in capacity of the shear factor owing to the length of the span being in correlation with rectilinear fill. The filament of surface, made of ULTEM 9805, exhibits a level of roughness of 43.14 μm on the pallet surface indicating better holding capacity and grip. A 9∘ peak shift is comprehended with respect to XRD, indicating a compressive residual factor measured at 76.47 MPa.
Running Safety Assessment of a Train Traversing a Long-Span Bridge Under Sudden Changes in Wind Loads Owing to Damaged Wind Barriers
Authors: Han Yan , Zhang Xun , Wang Lidong , Zhu Zhihui , Cai C. S. , He Xuhui
Published: March 2022

In the event of partial damage to the wind barriers installed on a bridge, the wind loads of a train will change abruptly as they enter and exit the damaged area, resulting in the deterioration of the train running safety. This study aimed to assess the running safety of a CRH2 high-speed train traversing a four-tower cable-stayed bridge with damaged wind barriers. Formulas were deduced for the static and dynamic wind loads on the bridge and train and their combined effect. The aerodynamic coefficients of the train and bridge were obtained through wind tunnel tests of a train–bridge sectional model, and a model of the wind–train–track–bridge coupled system was established using multi-body dynamics and the finite element method. The effects of the length of the damaged area and average wind speed on the train running safety were investigated based on the proposed model. The results reveal that the car body lateral displacements and accelerations reach their maximum amplitudes when the vehicles enter and leave the damaged area, respectively. The amplitude of the car body lateral displacement increases as the length of the damaged area increases, until it reaches 72[Formula: see text]m. The wheel load reduction rates (WLRRs) and derailment coefficients (DCs) of the vehicles increase owing to the damage of the wind barriers; however, the percentage increases for each vehicle are considerably different. The train can safely traverse the damaged area of wind barriers at a designed speed of 180[Formula: see text]km/h when the average wind speed is lower than 10[Formula: see text]m/s. When the average wind speed reaches 20[Formula: see text]m/s, the train can still safely cross the damaged area if the length of the damaged area is less than 12[Formula: see text]m.
On integral representations of finite groups and rings generated by character values
Authors: Malinin Dmitry
Published: March 2022

We study realization fields and integrality of characters of finite subgroups of [Formula: see text] and related lattices with a focus on the integrality of characters of finite groups [Formula: see text]. We are interested in the arithmetic aspects of the integral realizability of representations of finite groups, order generated by the character values, the number of minimal realization splitting fields, and in particular, consider the conditions of realizability in the terms of Hilbert symbols and quaternion algebras and some orders generated by character values over the rings of rational and algebraic integers.
Prime ideal sum graph of a commutative ring
Authors: Saha Manideepa , Das Angsuman , Çeli̇kel Ece Yetki̇n , Abdi̇oğlu Ci̇hat
Published: March 2022

Let [Formula: see text] be a commutative ring with identity. The prime ideal sum graph of [Formula: see text], denoted by [Formula: see text], is a graph whose vertices are nonzero proper ideals of [Formula: see text] and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent if and only if [Formula: see text] is a prime ideal of [Formula: see text]. In this paper, we study some connections between the graph-theoretic properties of this graph and some algebraic properties of rings. The clique number, the chromatic number and the domination number of the prime ideal sum graph for some classes of rings are studied. It is observed that under which condition [Formula: see text] is complete. Moreover, the diameter and the girth of [Formula: see text] are studied.
Generation of Black-box Audio Adversarial Examples Based on Gradient Approximation and Autoencoders
Authors: Huang Po-Hao , Yu Honggang , Panoff Max , Wang Ting-Chi
Published: March 2022

Deep Neural Network (DNN) is gaining popularity thanks to its ability to attain high accuracy and performance in various security-crucial scenarios. However, recent research shows that DNN-based Automatic Speech Recognition (ASR) systems are vulnerable to adversarial attacks. Specifically, these attacks mainly focus on formulating a process of adversarial example generation as iterative, optimization-based attacks. Although these attacks make significant progress, they still take large generation time to produce adversarial examples, which makes them difficult to be launched in real-world scenarios. In this article, we propose a real-time attack framework that utilizes the neural network trained by the gradient approximation method to generate adversarial examples on Keyword Spotting (KWS) systems. The experimental results show that these generated adversarial examples can easily fool a black-box KWS system to output incorrect results with only one inference. In comparison to previous works, our attack can achieve a higher success rate with less than 0.004 s. We also extend our work by presenting a novel ensemble audio adversarial attack and testing the attack on KWS systems equipped with existing defense mechanisms. The efficacy of the proposed attack is well supported by promising experimental results.
Algorithm 1022: Efficient Algorithms for Computing a Rank-Revealing UTV Factorization on Parallel Computing Architectures
Authors: Heavner N. , Igual F. D. , Quintana-Ortí G. , Martinsson P. G.
Published: March 2022

Randomized singular value decomposition (RSVD) is by now a well-established technique for efficiently computing an approximate singular value decomposition of a matrix. Building on the ideas that underpin RSVD, the recently proposed algorithm “randUTV” computes a
full
factorization of a given matrix that provides low-rank approximations with near-optimal error. Because the bulk of
randUTV
is cast in terms of communication-efficient operations such as matrix-matrix multiplication and unpivoted QR factorizations, it is faster than competing rank-revealing factorization methods such as column-pivoted QR in most high-performance computational settings. In this article, optimized
randUTV
implementations are presented for both shared-memory and distributed-memory computing environments. For shared memory,
randUTV
is redesigned in terms of an
algorithm-by-blocks
that, together with a runtime task scheduler, eliminates bottlenecks from data synchronization points to achieve acceleration over the standard
blocked algorithm
based on a purely fork-join approach. The distributed-memory implementation is based on the ScaLAPACK library. The performance of our new codes compares favorably with competing factorizations available on both shared-memory and distributed-memory architectures.
Improving Quality of Service in 5G Resilient Communication with the Cellular Structure of Smartphones
Authors: Sangaiah Arun Kumar , Javadpour Amir , Pinto Pedro , Ja'fari Forough , Zhang Weizhe
Published: March 2022

Recent studies in information computation technology (ICT) are focusing on Next-generation networks, SDN (Software-defined networking), 5G, and 6G. Optimal working mode for device-to-device (D2D) communication is aimed at improving the quality of service with the frequency spectrum structure is of research areas in 5G. D2D communication working modes are selected to meet both the predefined system conditions and provide maximum throughput for the network. Due to the complexity of the direct solutions, we formulated the problem as an optimization problem and found the optimal working modes under different parameters of the system through extensive simulations. After determining the links’ optimal modes, we calculated the network throughput; because of selecting the best working modes, we obtained the highest throughput. A major finding from this research is that D2D communication pairs are more inclined to use full-duplex (FD) mode in short distances to meet system requirements, and so most communications take place in FD mode at these distances. According to these results, using FD communication at short distances offers better conditions and Quality of service (QoS) than QoS-D2D method.
All-spin PUF: An Area-efficient and Reliable PUF Design with Signature Improvement for Spin-transfer Torque Magnetic Cell-based All-spin Circuits
Authors: Xu Kangwei , Zhang Dongrong , Ren Qiang , Cheng Yuanqing , Girard Patrick
Published: March 2022

Recently, spin-transfer torque magnetic cell (STT-mCell) has emerged as a promising spintronic device to be used in Computing-in-Memory (CIM) systems. However, it is challenging to guarantee the hardware security of STT-mCell-based all-spin circuits. In this work, we propose a novel Physical Unclonable Function (PUF) design for the STT-mCell-based all-spin circuit (All-Spin PUF) exploiting the unique manufacturing process variation (PV) on STT-mCell write latency. A methodology is used to select appropriate logic gates in the all-spin chip to generate a unique identification key. A linear feedback shift register (LFSR) initiates the All-Spin PUF and simultaneously generates a 64-bit signature at each clock cycle. Signature generation is stabilized using an automatic write-back technique. In addition, a masking scheme is applied for signature improvement. The uniqueness of the improved signature is 49.61%. With ± 20% supply voltage and 5°C to 105°C temperature variations, the All-Spin PUF shows a strong resiliency. In comparison with state-of-the-art PUFs, our approach can reduce hardware overhead effectively. Finally, the robustness of the All-Spin PUF against emerging modeling attacks is verified as well.
Design and Analysis of FPGA-based PUFs with Enhanced Performance for Hardware-oriented Security
Authors: Anandakumar N. Nalla , Hashmi Mohammad S. , Sanadhya Somitra Kumar
Published: March 2022

This article presents a thorough analysis of two distinct Physically Unclonable Functions (PUF), namely RO-PUF (Ring oscillator-based PUF) and RS-LPUF (RS Latch-based PUF), prototyped on FPGA. It is shown that the implemented PUFs possess significantly enhanced performance when compared to the state of the art. It is also identified that the enhancements are achieved through the incorporation of Programmable Delay Lines of FPGA Lookup Tables, the Temporal Majority Voting (TMV) scheme, and placed macro techniques for routing and placements of PUF units. The prototypes developed on Xilinx Artix-7 FPGAs are used for validation over the rated temperature range of 0-85°
C
with ±5% variation in the supply voltage. The proposed schemes when evaluated experimentally also achieve good uniformity, bit-aliasing, uniqueness, and reliability. Finally, it is shown that the proposed designs outperform the existing conventional PUFs in the area and speed tradeoff.
Construction of Arbitrary Order Finite Element Degree-of-Freedom Maps on Polygonal and Polyhedral Cell Meshes
Authors: Scroggs Matthew W. , Dokken Jørgen S. , Richardson Chris N. , Wells Garth N.
Published: March 2022

We develop a method for generating degree-of-freedom maps for arbitrary order Ciarlet-type finite element spaces for any cell shape. The approach is based on the composition of permutations and transformations by cell sub-entity. Current approaches to generating degree-of-freedom maps for arbitrary order problems typically rely on a consistent orientation of cell entities that permits the definition of a common local coordinate system on shared edges and faces. However, while orientation of a mesh is straightforward for simplex cells and is a local operation, it is not a strictly local operation for quadrilateral cells and, in the case of hexahedral cells, not all meshes are orientable. The permutation and transformation approach is developed for a range of element types, including arbitrary degree Lagrange, serendipity, and divergence- and curl-conforming elements, and for a range of cell shapes. The approach is local and can be applied to cells of any shape, including general polytopes and meshes with mixed cell types. A number of examples are presented and the developed approach has been implemented in open-source libraries.
Learning Streamed Attention Network from Descriptor Images for Cross-Resolution 3D Face Recognition
Authors: Neto João Baptista Cardia , Ferrari Claudio , Marana Aparecido Nilceu , Berretti Stefano , Del Bimbo Alberto
Published: March 2022

In this article, we propose a hybrid framework for cross-resolution 3D face recognition which utilizes a Streamed Attention Network (SAN) that combines handcrafted features with Convolutional Neural Networks (CNNs). It consists of two main stages: first, we process the depth images to extract low-level surface descriptors and derive the corresponding Descriptor Images (DIs), represented as four-channel images. To build the DIs, we propose a variation of the 3D Local Binary Pattern (3DLBP) operator that encodes depth differences using a sigmoid function. Then, we design a CNN that learns from these DIs. The peculiarity of our solution consists in processing each channel of the input image separately, and fusing the contribution of each channel by means of both self- and cross-attention mechanisms. This strategy showed two main advantages over the direct application of Deep-CNN to depth images of the face; on the one hand, the DIs can reduce the diversity between high- and low-resolution data by encoding surface properties that are robust to resolution differences. On the other, it allows a better exploitation of the richer information provided by low-level features, resulting in improved recognition. We evaluated the proposed architecture in a challenging cross-dataset, cross-resolution scenario. To this aim, we first train the network on scanner-resolution 3D data. Next, we utilize the pre-trained network as feature extractor on low-resolution data, where the output of the last fully connected layer is used as face descriptor. Other than standard benchmarks, we also perform experiments on a newly collected dataset of paired high- and low-resolution 3D faces. We use the high-resolution data as gallery, while low-resolution faces are used as probe, allowing us to assess the real gap existing between these two types of data. Extensive experiments on low-resolution 3D face benchmarks show promising results with respect to state-of-the-art methods.
Affective Interaction: Attentive Representation Learning for Multi-Modal Sentiment Classification
Authors: Zhang Yazhou , Tiwari Prayag , Rong Lu , Chen Rui , Alnajem Nojoom A. , Hossain M. Shamim
Published: March 2022

The recent booming of artificial intelligence (AI) applications, e.g., affective robots, human-machine interfaces, autonomous vehicles, and so on, has produced a great number of multi-modal records of human communication. Such data often carry latent subjective users’ attitudes and opinions, which provides a practical and feasible path to realize the connection between human emotion and intelligence services. Sentiment and emotion analysis of multi-modal records is of great value to improve the intelligence level of affective services. However, how to find an optimal manner to learn people’s sentiments and emotional representations has been a difficult problem, since both of them involve subtle mind activity. To solve this problem, a lot of approaches have been published, but most of them are insufficient to mine sentiment and emotion, since they have treated sentiment analysis and emotion recognition as two separate tasks. The interaction between them has been neglected, which limits the efficiency of sentiment and emotion representation learning. In this work, emotion is seen as the external expression of sentiment, while sentiment is the essential nature of emotion. We thus argue that they are strongly related to each other where one’s judgment helps the decision of the other. The key challenges are multi-modal fused representation and the interaction between sentiment and emotion. To solve such issues, we design an external knowledge enhanced multi-task representation learning network, termed KAMT. The major elements contain two attention mechanisms, which are inter-modal and inter-task attentions and an external knowledge augmentation layer. The external knowledge augmentation layer is used to extract the vector of the participant’s gender, age, occupation, and of overall color or shape. The main use of inter-modal attention is to capture effective multi-modal fused features. Inter-task attention is designed to model the correlation between sentiment analysis and emotion classification. We perform experiments on three widely used datasets, and the experimental performance proves the effectiveness of the KAMT model.
Simultaneously Achieving Sublinear Regret and Constraint Violations for Online Convex Optimization with Time-varying Constraints
Authors: Liu Qingsong , Wu Wenfei , Huang Longbo , Fang Zhixuan
Published: March 2022

In this paper, we develop a novel virtual-queue-based online algorithm for online convex optimization (OCO) problems with long-term and time-varying constraints and conduct a performance analysis with respect to the dynamic regret and constraint violations.
Optimal Control for Networks with Unobservable MaliciousNodes
Authors: Liu Bai , Modiano Eytan
Published: March 2022

With the rapid development of information technology, modern network systems are becoming increasingly complex and are increasingly vulnerable to attacks such as Distributed Denial-of-Service (DDoS) attack. However, existing network control algorithms either require full observability and/or controllability for all nodes [2, 9, 1, 4, 6], or the network dynamics to be time-invariant and stochastic [7, 3, 8, 5]. In this paper, we aim to develop a new algorithm that can stabilize networks with unobservable and uncontrollable nodes under adversarial dynamics (i.e., external arrivals and actions of malicious nodes).
Fundamental Scaling Laws of Covert DDoS Attacks
Authors: Reza Ramtin Amir , Nain Philippe , Menasche Daniel S. , Towsley Don , de Souza e Silva Edmundo
Published: March 2022

The Internet has become an indispensable commodity in the last several years. This achievement was parallel to the growth of sophistication that home networks have undergone, nowadays hosting a variety of devices such as PCs, tablets, mobile phones and specialized apparatus such as smart thermostats and other Internet of things (IoT) devices. While these devices offer users an array of services and conveniences, they come at the cost of increasing the attack surface of the home network.Because of the vulnerabilities of such devices, they have been increasingly used as the source of Distributed Denial-of-Service (DDoS) attacks.
Improved Scalability of Demand-Aware Datacenter Topologies With Minimal Route Lengths and Congestion
Authors: Pacut Maciej , Dai Wenkai , Labbe Alexandre , Foerster Klaus-Tycho , Schmid Stefan
Published: March 2022

The performance of more and more cloud-based applications critically depends on the performance of the interconnecting datacenter network. Emerging reconfigurable datacenter networks have the potential to provide an unprecedented throughput by dynamically reconfiguring their topology in a demand-aware manner. This paper studies the algorithmic problem of how to design low-degree and hence scalable datacenter networks optimized toward the current traffic they serve. Our main contribution is a novel network design which provides asymptotically minimal route lengths and congestion. In comparison to prior work, we reduce the degree requirements by a factor of four for sparse demand matrices. We further show the problem to be already NP-hard for tree-shaped demands, but permits a 2-approximation on the route lengths and a 6-approximation for congestion. We further report on a small empirical study on Facebook traces.
Current Understanding of Modes of Action of Multicomponent Bioactive Phytochemicals: Potential for Nutraceuticals and Antimicrobials
Authors: Wink Michael
Published: March 2022

Plants produce a diversity of plant secondary metabolites (PSMs), which function as defense chemicals against herbivores and microorganisms but also as signal compounds. An individual plant produces and accumulates mixtures of PSMs with different structural features using different biosynthetic pathways. Almost all PSMs exert one or several biological activities that can be useful for nutrition and health. This review discusses the modes of action of PSMs alone and in combinations. In a mixture, most individual PSMs can modulate different molecular targets; they are thus multitarget drugs. In an extract with many multitarget chemicals, additive and synergistic effects occur. Experiments with the model system Caenorhabditis elegans show that polyphenols and carotenoids can function as powerful antioxidative and longevity-promoting PSMs. PSMs of food plants and spices often exhibit antioxidant, anti-inflammatory, and antimicrobial properties, which can be beneficial for health and the prevention of diseases. Some extracts from food plants and spices with bioactive PSMs have potential for nutraceuticals and antimicrobials.
Review—Revealing the Intercrystalline Cracking Mechanism of NCM and Some Regulating Strategies
Authors: Han Daoyuan , Weng Jingzheng , Zhang Xian , Tong Qingsong , Zhu Mengqi
Published: March 2022

Nickel-rich cathode has received much attention due to its high energy density, high capacity, low cost and environmental friendliness. The existence of intercrystalline microcracks in NCM seriously affects the structural stability and integrity of the battery crystal surface. Irreversible phase transitions result in changes in lattice parameters, the interface side reactions severely corrode the crystal surface, and secondary particle heterogeneity leads to uneven reactions. Common amorphous microcracks include single crystal, gradient doping, etc. This review first introduced the microcrack mechanism of NCM, and then summarized two solutions: single crystal and gradient doping. Finally, we presented new views and insights, and hope to give enlightenment on the subsequent inhibition of intercrystal microcrack, and construct the reasonable structure of NCM cathode.
Effect of Ammonium Salts on the Conductivity and Current Efficiency of Dimethyl Sulfone-Aluminum Chloride Electrolytes
Authors: Matsuda Junichi , Okamoto Atsushi , Akahoshi Haruo , Shironita Sayoko , Umeda Minoru
Published: March 2022

In this study, we investigated the effects of ammonium chloride (NH4Cl) and tetramethylammonium chloride (TMAC) on the conductivity and current efficiency of dimethyl sulfone (DMSO2)-aluminum chloride (AlCl3) electrolyte. When NH4Cl and TMAC were added independently, the conductivity of the electrolyte increased, which was attributed to a decrease in the electrolyte viscosity. 27Al nuclear magnetic resonance (NMR) spectroscopy showed that chloride addition reduced the ratio of solvated Al3+ ions. This occurred because Al3+ and Cl− dissociated from chloride and formed AlCl4
−, which increased the amount of non-solvated DMSO2 species, consequently decreasing the electrolyte viscosity. NH4Cl improved the plating appearance even when added in small amounts; however, when added in relatively high concentrations, the conductivity increased, while the current efficiency decreased significantly. Conversely, TMAC did not induce a significant decrease in the current efficiency up to an addition amount of 0.1 mol. The electrolyte with the co-addition of TMAC and a small amount of NH4Cl showed increased conductivity while minimizing the decrease in current efficiency. Also, good results in the appearance and purity of the plating film were obtained.
Design of a Scavenging Pyrrole Additive for High Voltage Lithium-Ion Batteries
Authors: Yang Jianzhong , Rodrigues Marco-Tulio Fonseca , Yu Zhou , Son Seoung-Bum , Liu Kewei , Dietz Rago Nancy L , Cheng Lei , Zhang Zhengcheng , Abraham Daniel , Liao Chen
Published: March 2022

We report 1-(dimethylamino) pyrrole (PyDMA) as an electrolyte additive for high voltage lithium-ion batteries based on LiNi0.6Mn0.2Co0.2O2 (NMC622)//Graphite with an upper cutoff voltage of 4.4 V. Density Functional Theory (DFT) modeling indicates that the unique structure of PyDMA could be effective in preventing the hydrolysis of LiPF6 in a carbonate electrolyte, mitigating issues related to HF formation. The calculations also indicated that the additive would oxidize at lower potentials than typical electrolyte solvents, which could lead to protective films at the cathode surface. These expectations were tested using Nuclear Magnetic Resonance (NMR) and extensive electrochemical characterization. NMR studies confirmed the superb dehydrating capability of PyDMA, which successfully prevents HF formation even at high water content. Addition of 0.5 wt% PyDMA resulted in improved capacity retention in full-cells, and also in lower levels of transition metal dissolution from the cathode. Incremental capacity (dQ/dV) analysis indicates that benefits of PyDMA at low concentration (0.5–1 wt%) are associated with decreased rates of Li+-trapping reactions, and that higher concentrations of the additive can lead to isolation of cathode domains. Our study indicates that PyDMA could be a promising electrolyte additive for high voltage lithium-ion batteries at a low concentration.
An Emerging Machine Learning Strategy for the Fabrication of Nanozyme Sensor and Voltametric Determination of Benomyl In Agro-Products
Authors: Xu Lulu , Xiong Yao , Wu Ruimei , Geng Xiang , Li Minghui , Yao Hang , Wang Xu , Wen Yangping , Ai Shirong
Published: March 2022

An emerging machine learning (ML) strategy for the fabrication of nanozyme sensor based on multi-walled carbon nanotubes (MWCNTs)/graphene oxide (GO)/dendritic silver nanoparticles (AgNPs) nanohybrid and the voltametric determination of benomyl (BN) residues in tea and cucumber samples is proposed. Nanohybrid is prepared by the electrodeposition of dendritic AgNPs on the surface of MWCNTs/GO obtained by a simple mixed-strategy. The orthogonal experiment design combined with back propagation artificial neural network with genetic algorithm is used to solve multi-factor problems caused by the fabrication of nanohybrid sensor for BN. Both support vector machine (SVM) algorithm and least square support vector machine (LS-SVM) algorithm are used to realize the intelligent sensing of BN compared with the traditional method. The as-fabricated electrochemical sensor displays high electrocatalytic capacity (excellent voltammetric response), unique oxidase-like characteristic (nanozyme), wide working range (0.2–122.2 μM), good practicability (satisfactory recovery). It is feasible and practical that ML guides the fabrication of nanozyme sensor and the intelligent sensing of BN compared with the traditional method. This work will open a new avenue for guiding the synthesis of sensing materials, the fabrication of sensing devices and the intelligent sensing of target analytes in the future.
On the Effect of Thermal Processing on Sn Diffusion and Efficiency Enhancement in Hematite/FTO Photoanodes
Authors: Rodríguez-Gutiérrez Ingrid , Mouriño Beatriz , Freitas André L. M. , Costa Carlos A. R. , Pires Elcio L , Gonçalves Renato V. , Vayssieres Lionel , Souza Flavio L.
Published: March 2022

The frequently underestimated effects of “in air” thermal treatment processing conditions such as temperature, duration, and heating and cooling rates in the design and efficiency of photoelectrodes fabricated for academic studies onto the most common commercial transparent conductive glass substrate i.e. fluorine-doped tin oxide (FTO) were investigated by XRD, XPS, SEM, conductive AFM, electrochemical impedance spectroscopy (EIS) as well as direct current (DC) and photoelectrochemical (PEC) measurements. The PEC response of Hematite photoanode thin films consisting of short nanorods thermally treated at 400 °C and 800 °C upon fast or extended time conditions is inhibited by factors such as crystallinity, Sn diffusion, or substrate integrity. A “fast” thermal treatment in air at 750 °C provided the best synergy between charge transfer resistance, Sn-diffusion from the FTO substrate, nanorod dimensions, reduced recombination, improved charge separation and minimized substrate damage. This study does offer valuable fundamental and practical insights for a better understanding of the benefits and drawbacks of photoelectrode thermal processing, which is critical for the improvement of the PEC performance-reproducibility relationship for FTO-based solar water splitting systems and devices.
Fabrication and Ions Irradiation Study of AlN:Gd Thin Films
Authors: Ullah Asmat , Usman Muhammad , Shah Ahmer , Ahmad Iftikhar , Maqbool Muhammad
Published: March 2022

Thin films of Aluminum Nitride (AlN) doped with Gadolinium (Gd) are deposited on Si (111) substrates, in pure Nitrogen (N) atmosphere using reactive magnetron sputtering technique at room temperature. The as-deposited thin films are irradiated by protons carrying 335 keV energy with a fluence of 1 × 1014 ions cm−2. Rutherford Backscattering Spectroscopy (RBS) is carried out using a 2 MeV He++ beam to understand the stoichiometric and dimensional features of the films. Modifications in the structural, electronic, optical, and electrical properties are investigated prior to and after the irradiation using X-ray diffraction (XRD), Fourier transforms, infrared spectroscopy (FTIR), diffuse reflectance spectroscopy (DRS), and four-probe point method. Stopping power and range of ions in matters (SRIM) is used to study the non-ionizing energy loss (NIEL) and Frenkel defect density/vacancies in AlN, caused by irradiation. Proton irradiation-induced changes in the structure and enhancement in the optical and electrical characteristics of the films make AlN:Gd a good candidate for advanced electronics and optical technology.
Correlating Crystallography, Magnetism, and Electronic Structure Across Anhysteretic First-Order Phase Transition in Pr2In
Authors: Biswas Anis , Chouhan Rajiv K. , Dolotko O. , Thayer A. , Lapidus S. , Mudryk Y. , Pecharsky V. K.
Published: March 2022

Temperature-dependent powder X-ray diffraction and magnetization measurements of Pr2In conclusively prove that the unusual anhysteretic first-order paramagnetic-ferromagnetic phase transition in the compound is related to concurrent changes in both the magnetic and crystallographic lattices. At the same time, the hexagonal Ni2In-type structure is stable at least between 6 and 298 K, including at T
C = ∼57 K. From the density functional theory calculations, the electronic structure of the compound is extraordinarily sensitive to minor changes in lattice parameters that occur across the phase transition, revealing the origin of strong magnetoelastic coupling. In the vicinity of T
C, the maximum entropy change, ΔS
Max = −16 J Kg−1 K−1 induced by a moderate magnetic field change of 20 kOe (ΔS
Max = −20 J Kg−1 K−1 for 50 kOe magnetic field change) is comparable to other known potentially functional materials demonstrating large cryogenic magnetocaloric effect.
Impact of ischemia on left atrial remodeling and dysfunction in swine models of mitral regurgitation
Authors: Sakata Tomoki , Mazurek Renata , Mavropoulos Spyros A. , Romeo Francisco J. , Ravichandran Anjali J. , Watanabe Shin , Kariya Taro , Ishikawa Kiyotake
Published: March 2022

We show different LA structural and functional remodeling patterns between ischemic MR and MR due to leaflet prolapse. Severe ischemic MR was accompanied by extensive LA remodeling, which may be associated with poor clinical outcomes. Our data suggest that detailed structural and functional LA remodeling assessment is important for managing IMR and to determine the presence of LA ischemia.
Microvascular dysfunction and neurovascular uncoupling are exacerbated in peripheral artery disease, increasing the risk of cognitive decline in older adults
Authors: Owens Cameron D. , Mukli Peter , Csipo Tamas , Lipecz Agnes , Silva-Palacios Federico , Dasari Tarun W. , Tarantini Stefano , Gardner Andrew W. , Montgomery Polly S. , Waldstein Shari R. , Kellawan J. Mikhail , Nyul-Toth Adam , Balasubramanian Priya , Sotonyi Peter , Csiszar Anna , Ungvari Zoltan , Yabluchanskiy Andriy
Published: March 2022

Peripheral artery disease (PAD) was associated with significantly decreased cognitive performance, impaired neurovascular coupling (NVC) responses in the prefrontal cortex (PFC), left and right dorsolateral prefrontal cortices (LDLPFC and RDLPFC), and impaired peripheral microvascular endothelial function. A positive correlation between microvascular endothelial function, NVC responses, and cognitive performance may suggest that PAD-related cognitive decrement is mechanistically linked, at least in part, to generalized microvascular endothelial dysfunction and subsequent impairment of NVC responses.
Metabolic transformation of fat in obesity determines the inflammation resolving capacity of splenocardiac and cardiorenal networks in heart failure
Authors: Halade Ganesh V. , Kain Vasundhara , De La Rosa Xavier , Lindsey Merry L.
Published: March 2022

Chronic and surplus dietary intake of safflower oil (SO) increased plasma creatinine dysregulated post-MI splenocardiac inflammation coincides with the dysfunctional cardiorenal network. In contrast, docosahexaenoic acid (DHA) increases post-MI survival in chronic heart failure. DHA transforms into specialized proresolving mediators (SPMs) and limited proinflammatory prostaglandins and thromboxanes following myocardial infarction (MI). DHA promotes Ly6Clow resolving macrophages and T regulatory cells (Foxp3+) in a splenocardiac manner post-MI.
Impaired microcirculatory function, mitochondrial respiration, and oxygen utilization in skeletal muscle of claudicating patients with peripheral artery disease
Authors: Park Song-Young , Pekas Elizabeth J. , Anderson Cody P. , Kambis Tyler N. , Mishra Paras K. , Schieber Molly N. , Wooden TeSean K. , Thompson Jonathan R. , Kim Kyung Soo , Pipinos Iraklis I.
Published: March 2022

Ex vivo skeletal muscle arteriole endothelial function is impaired in claudicating patients with PAD, and this is associated with attenuated skeletal muscle mitochondrial respiration. In vivo skeletal muscle oxygen delivery and utilization capacity are compromised in PAD, and this may be due to microcirculatory and mitochondrial dysfunction. These results suggest that targeting skeletal muscle arteriole function may lead to improvements in skeletal muscle mitochondrial respiration, oxygen delivery, and utilization capacity in claudicating patients with PAD.
A Framework for Assessing the Performance of Adaptively Reused Buildings from Users’ Perspective: A Case Study of School Building
Authors: Chai Qing , Li Huimin , Tian Wei , Zhang Yang , Wang Li
Published: March 2022

The positive relationship between building performance and users’ satisfaction and behavior in new buildings has been widely studied. However, in the context of adaptively reused buildings converted from historic buildings, how each performance aspect affects users’ perception is missing. To explore the design concerns needed to be considered related to the performance of adaptively reused buildings from user’s perspective, this paper proposed a framework to examine the effect of performance of adaptively reused buildings on users’ satisfaction and behavior using structural equation modeling. A total of 608 valid face‐to‐face interview questionnaires were collected at a school building converted from an abandoned industrial building. The empirical conclusions are as follows: (1) Building performance (including indoor environment quality, interior design, building services, and authenticity) all exerted a significant positive correlation with the learning behavior of students, among which indoor environment quality is the most critical factor affecting learning behavior of students. (2) Students’ satisfaction is positively affected by the building performance (including indoor environment quality, interior design, building services, and authenticity), among which authenticity has the greatest effect on students’ satisfaction. (3) The correlation between satisfaction and learning behavior of students is significant and positive. (4) Considering the mediator impact, authenticity indirectly affects learning behavior through satisfaction, while students’ satisfaction has a partially mediating effect between the other three performance aspects and learning behavior. This paper provides a framework for assessing the performance of adaptively reused buildings and gives practical strategies for the improvement of users’ satisfaction and behavior in similar projects.