bluuebunny/crossref_metadata_2025 huggingface dataset:
The light invisible boson in FCNC decays of B and $$B_c$$ mesons
Authors: Li Geng , Wang Tianhong , Zhang Jing-Bo , Wang Guo-Li
Published: June 2021

In this paper, we study the FCNC decay processes of B and $$B_c$$

B
c

meson, in which one invisible particle is emitted. Both the spin-0 and spin-1 cases are considered. The model-independent effective Lagrangian is introduced to describe the coupling between the light invisible boson and quarks. The constraints of the coupling coefficients are extracted by experimental upper limits of the missing energy in B meson decays. The bounds are used to predict the upper limits of branching fractions of corresponding $$B_c$$

B
c

decays, which are of the order of $$10^{-6}$$

10

-
6

or $$10^{-5}$$

10

-
5

when final meson is pseudoscalar or vector, respectively. The maximum branch ratios are achieved when $$m_\chi \approx 3.5$$

m
χ

≈
3.5

–4 GeV, where $$m_\chi $$

m
χ

is the mass of the invisible particle.
Detection of gravitational waves by light perturbation
Authors: Kim Dong-Hoon , Park Chan
Published: June 2021

Light undergoes perturbation as gravitational waves pass by. This is shown by solving Maxwell’s equations in a spacetime with gravitational waves; a solution exhibits a perturbation due to gravitational waves. We determine the perturbation for a general case of both light and gravitational waves propagating in arbitrary directions. It is also shown that a perturbation of light due to gravitational waves leads to a delay of the photon transit time, which implies an equivalence between the perturbation analysis of Maxwell’s equations and the null geodesic analysis for photon propagation. We present an example of application of this principle with regard to the detection of gravitational waves via a pulsar timing array, wherein our perturbation analysis for the general case is employed to show how the detector response varies with the incident angle of a light pulse with respect to the detector.
Cosmological curvature acceleration
Authors: Capozziello S. , Lambiase G.
Published: June 2021

Observed accelerated behavior of the Hubble flow, usually related to the existence of a mysterious unknown fluid dubbed dark energy, can be framed in natural extensions of General Relativity that work at infrared scales. This approach gives rise to a geometric view of the phenomenon that does not require any new particle to be addressed. In this review paper, without claiming for completeness, we will give the main ingredients of such an approach considering models likef(R) gravity, withRthe Ricci curvature scalar, and, in general, higher-order theories of gravity including other curvature invariants. In this context, we will review also Teleparallel Equivalent General Relativity and its extensions likef(T) gravity, whereTis the torsion scalar. We will show that the curvature picture and the torsion picture can be related each other giving an equivalent paradigm where the observed cosmological acceleration can be addressed by extending the gravitational sector.
Survey of Machine Learning Algorithms to Detect Malware in Consumer Internet of Things Devices
Authors: Holbrook Luke , Alamaniotis Miltiadis
Published: June 2021

With the increase of cyber-attacks on millions of Internet of Things (IoT) devices, the poor network security measures on those devices are the main source of the problem. This article aims to study a number of these machine learning algorithms available for their effectiveness in detecting malware in consumer internet of things devices. In particular, the Support Vector Machines (SVM), Random Forest, and Deep Neural Network (DNN) algorithms are utilized for a benchmark with a set of test data and compared as tools in safeguarding the deployment for IoT security. Test results on a set of 4 IoT devices exhibited that all three tested algorithms presented here detect the network anomalies with high accuracy. However, the deep neural network provides the highest coefficient of determination R2, and hence, it is identified as the most precise among the tested algorithms concerning the security of IoT devices based on the data sets we have undertaken.
A complete invariant for closed surfaces in the three-sphere
Authors: Bellettini Giovanni , Paolini Maurizio , Wang Yi-Sheng
Published: June 2021

Associated to an embedded surface in the three-sphere, we construct a diagram of fundamental groups, and prove that it is a complete invariant, whereform we deduce complete invariants of handlebody links, tunnels of handlebody links, and spatial graphs. The main ingredients in the proof of the completeness include a generalization of the Kneser conjecture for three-manifolds with boundary proved here, and extensions of Waldhausen’s theorem by Evans, Tucker and Swarup. Computable invariants of handlebody links derived therefrom are calculated.
A non-local coupling model involving three fractional Laplacians
Authors: Gárriz A. , Ignat L. I.
Published: June 2021

In this paper, we study a non-local diffusion problem that involves three different fractional Laplacian operators acting on two domains. Each domain has an associated operator that governs the diffusion on it, and the third operator serves as a coupling mechanism between the two of them. The model proposed is the gradient flow of a non-local energy functional. In the first part of the paper, we provide results about existence of solutions and the conservation of mass. The second part encompasses results about the [Formula: see text] decay of the solutions. The third part is devoted to study, the asymptotic behavior of the solutions of the problem when the two domains are a ball and its complementary. Exterior fractional Sobolev and Nash inequalities of independent interest are also provided in Appendix A.
Star coloring under some graph operations
Authors: Mahdavi B. Akhavan , Tavakoli M. , Rahbarnia F. , Ashrafi Alireza
Published: June 2021

A star coloring of a graph [Formula: see text] is a proper coloring of [Formula: see text] such that no path of length [Formula: see text] in [Formula: see text] is bicolored. In this paper, the star chromatic number of join of graphs is computed. Some sharp bounds for the star chromatic number of corona, lexicographic, deleted lexicographic and hierarchical product of graphs together with a conjecture on the star chromatic number of lexicographic product of graphs are also presented.
Sequence Alignment with Q-Learning Based on the Actor-Critic Model
Authors: Li Yarong
Published: June 2021

Multiple sequence alignment methods refer to a series of algorithmic solutions for the alignment of evolutionary-related sequences while taking into account evolutionary events such as mutations, insertions, deletions, and rearrangements under certain conditions. In this article, we propose a method with Q-learning based on the Actor-Critic model for sequence alignment. We transform the sequence alignment problem into an agent's autonomous learning process. In this process, the reward of the possible next action taken is calculated, and the cumulative reward of the entire process is calculated. The results show that the method we propose is better than the gene algorithm and the dynamic programming method.
A Comprehensive Survey on Word Representation Models: From Classical to State-of-the-Art Word Representation Language Models
Authors: Naseem Usman , Razzak Imran , Khan Shah Khalid , Prasad Mukesh
Published: June 2021

Word representation has always been an important research area in the history of natural language processing (NLP). Understanding such complex text data is imperative, given that it is rich in information and can be used widely across various applications. In this survey, we explore different word representation models and its power of expression, from the classical to modern-day state-of-the-art word representation language models (LMS). We describe a variety of text representation methods, and model designs have blossomed in the context of NLP, including SOTA LMs. These models can transform large volumes of text into effective vector representations capturing the same semantic information. Further, such representations can be utilized by various machine learning (ML) algorithms for a variety of NLP-related tasks. In the end, this survey briefly discusses the commonly used ML- and DL-based classifiers, evaluation metrics, and the applications of these word embeddings in different NLP tasks.
A Cost-Efficient Digital ESN Architecture on FPGA for OFDM Symbol Detection
Authors: Gan Victor M. , Liang Yibin , Li Lianjun , Liu Lingjia , Yi Yang
Published: June 2021

The echo state network (ESN) is a recently developed machine-learning paradigm whose processing capabilities rely on the dynamical behavior of recurrent neural networks. Its performance outperforms traditional recurrent neural networks in nonlinear system identification and temporal information processing applications. We design and implement a cost-efficient ESN architecture on field-programmable gate array (FPGA) that explores the full capacity of digital signal processor blocks on low-cost and low-power FPGA hardware. Specifically, our scalable ESN architecture on FPGA exploits Xilinx DSP48E1 units to cut down the need of configurable logic blocks. The proposed architecture includes a linear combination processor with negligible deployment of configurable logic blocks and a high-accuracy nonlinear function approximator. Our work is verified with the prediction task on the classical NARMA dataset and a symbol detection task for orthogonal frequency division multiplexing systems using a wireless communication testbed built on a software-defined radio platform. Experiments and performance measurement show that the new ESN architecture is capable of processing real-world data efficiently for low-cost and low-power applications.
A Reconfigurable Multiplier for Signed Multiplications with Asymmetric Bit-Widths
Authors: Guo Chuliang , Zhang Li , Zhou Xian , Zhang Grace Li , Li Bing , Qian Weikang , Yin Xunzhao , Zhuo Cheng
Published: June 2021

Multiplications have been commonly conducted in quantized CNNs, filters, and reconfigurable cores, and so on, which are widely deployed in mobile and embedded applications. Most multipliers are designed to perform multiplications with symmetric bit-widths, i.e.,
n
- by
n
-bit multiplication. Such features would cause extra area overhead and performance loss when
m
- by
n
-bit multiplications (
m
>
n
) are deployed in the same hardware design, resulting in inefficient multiplication operations. It is highly desired and challenging to propose a reconfigurable multiplier design to accommodate operands with both symmetric and asymmetric bit-widths. In this work, we propose a reconfigurable approximate multiplier to support multiplications at various precisions, i.e., bit-widths. Unlike prior works of approximate adders assuming a uniform weight distribution with bit-wise independence, scenarios like a quantized CNN may have a centralized weight distribution and hence follow a Gaussian-like distribution with correlated adjacent bits. Thus, a new block-based approximate adder is also proposed as part of the multiplier to ensure energy-efficient operation with an awareness of the bit-wise correlation. Our experimental results show that the proposed approximate adder significantly reduces the error rate by 76% to 98% over a state-of-the-art approximate adder for Gaussian-like distribution scenarios. Evaluation results show that the proposed multiplier is 19% faster and 22% more power saving than a Xilinx multiplier IP at the same bit precision and achieves a 23.94-dB peak signal-to-noise ratio, which is comparable to the accurate one of 24.10 dB when deployed in a Gaussian filter for image processing tasks.
Toward Integrated CNN-based Sentiment Analysis of Tweets for Scarce-resource Language—Hindi
Authors: Gupta Vedika , Jain Nikita , Shubham Shubham , Madan Agam , Chaudhary Ankit , Xin Qin
Published: June 2021

Linguistic resources for commonly used languages such as English and Mandarin Chinese are available in abundance, hence the existing research in these languages. However, there are languages for which linguistic resources are scarcely available. One of these languages is the Hindi language. Hindi, being the fourth-most popular language, still lacks in richly populated linguistic resources, owing to the challenges involved in dealing with the Hindi language. This article first explores the machine learning-based approaches—Naïve Bayes, Support Vector Machine, Decision Tree, and Logistic Regression—to analyze the sentiment contained in Hindi language text derived from Twitter.

Further, the article presents lexicon-based approaches (Hindi Senti-WordNet, NRC Emotion Lexicon) for sentiment analysis in Hindi while also proposing a Domain-specific Sentiment Dictionary. Finally, an integrated convolutional neural network (CNN)—Recurrent Neural Network and Long Short-term Memory—is proposed to analyze sentiment from Hindi language tweets, a total of 23,767 tweets classified into positive, negative, and neutral. The proposed CNN approach gives an accuracy of 85%.
Quantization of Deep Neural Networks for Accurate Edge Computing
Authors: Chen Wentao , Qiu Hailong , Zhuang Jian , Zhang Chutong , Hu Yu , Lu Qing , Wang Tianchen , Shi Yiyu , Huang Meiping , Xu Xiaowe
Published: June 2021

Deep neural networks have demonstrated their great potential in recent years, exceeding the performance of human experts in a wide range of applications. Due to their large sizes, however, compression techniques such as weight quantization and pruning are usually applied before they can be accommodated on the edge. It is generally believed that quantization leads to performance degradation, and plenty of existing works have explored quantization strategies aiming at minimum accuracy loss. In this paper, we argue that quantization, which essentially imposes regularization on weight representations, can sometimes help to improve accuracy. We conduct comprehensive experiments on three widely used applications: fully connected network for biomedical image segmentation, convolutional neural network for image classification on ImageNet, and recurrent neural network for automatic speech recognition, and experimental results show that quantization can improve the accuracy by 1%, 1.95%, 4.23% on the three applications respectively with 3.5x-6.4x memory reduction.
Improving Deep Learning Networks for Profiled Side-channel Analysis Using Performance Improvement Techniques
Authors: Robissout Damien , Bossuet Lilian , Habrard Amaury , Grosso Vincent
Published: June 2021

The use of deep learning techniques to perform side-channel analysis attracted the attention of many researchers as they obtained good performances with them. Unfortunately, the understanding of the neural networks used to perform side-channel attacks is not very advanced yet. In this article, we propose to contribute to this direction by studying the impact of some particular deep learning techniques for tackling side-channel attack problems. More precisely, we propose to focus on three existing techniques: batch normalization, dropout, and weight decay, not yet used in side-channel context. By combining adequately these techniques for our problem, we show that it is possible to improve the attack performance, i.e., the number of traces needed to recover the secret, by more than 55%. Additionally, they allow us to have a gain of more than 34% in terms of training time. We also show that an architecture trained with such techniques is able to perform attacks efficiently even in the context of desynchronized traces.
A Lightweight Architecture for Hardware-Based Security in the Emerging Era of Systems of Systems
Authors: Mexis Nico , Anagnostopoulos Nikolaos Athanasios , Chen Shuai , Bambach Jan , Arul Tolga , Katzenbeisser Stefan
Published: June 2021

In recent years, a new generation of the Internet of Things (IoT 2.0) is emerging, based on artificial intelligence, the blockchain technology, machine learning, and the constant consolidation of pre-existing systems and subsystems into larger systems. In this work, we construct and examine a proof-of-concept prototype of such a system of systems, which consists of heterogeneous commercial off-the-shelf components, and utilises diverse communication protocols. We recognise the inherent need for lightweight security in this context, and address it by employing a low-cost state-of-the-art security solution. Our solution is based on a novel hardware and software co-engineering paradigm, utilising well-known software-based cryptographic algorithms, in order to maximise the security potential of the hardware security primitive (a Physical Unclonable Function) that is used as a security anchor. The performance of the proposed security solution is evaluated, proving its suitability even for real-time applications. Additionally, the Dolev-Yao attacker model is considered in order to assess the resilience of our solution towards attacks against the confidentiality, integrity, and availability of the examined system of systems. In this way, it is confirmed that the proposed solution is able to address the emerging security challenges of the oncoming era of systems of systems.
Configurational Path to Chinese Reading Stickiness of Digital Library
Authors: Deng Yongliang , Zhang Hua
Published: June 2021

Attracting and retaining readers in an increasingly competitive environment is an urgent problem for digital libraries of original literature. However, few empirical studies address online reading stickiness, particularly the factors affecting the promotion of online reading stickiness, in what combinations or paths these effects exist, and whether there are complementary, alternative, and inhibitory relationships among the factors. To solve the practical problems and fill the theoretical gap, we use a fuzzy-set qualitative comparative analysis to study the interaction effects of the flow experience (feeling of immersion and perceived pleasure), technology acceptance model (perceived usefulness and perceived ease of use), and customer participation (information sharing and interpersonal interaction) to identify the critical configurations leading to a high level of stickiness in online reading and to verify the complementarity, substitution, and inhibition relationships among these variables. The findings provide implications for further research on complexity theory in digital libraries of original literature, and for managers to view and redesign online reading stickiness as configurations of IT and psychological capabilities. This study enriches and develops the existing theories and expands the application of the qualitative comparative analysis method in the field of digital libraries.
Sentiment Analysis Using XLM-R Transformer and Zero-shot Transfer Learning on Resource-poor Indian Language
Authors: Kumar Akshi , Albuquerque Victor Hugo C.
Published: June 2021

Sentiment analysis on social media relies on comprehending the natural language and using a robust machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results. The cultural miscellanies, geographically limited trending topic hash-tags, access to aboriginal language keyboards, and conversational comfort in native language compound the linguistic challenges of sentiment analysis. This research evaluates the performance of cross-lingual contextual word embeddings and zero-shot transfer learning in projecting predictions from resource-rich English to resource-poor Hindi language. The cross-lingual XLM-RoBERTa classification model is trained and fine-tuned using the English language Benchmark SemEval 2017 dataset Task 4 A and subsequently zero-shot transfer learning is used to evaluate the classification model on two Hindi sentence-level sentiment analysis datasets, namely, IITP-Movie and IITP-Product review datasets. The proposed model compares favorably to state-of-the-art approaches and gives an effective solution to sentence-level (tweet-level) analysis of sentiments in a resource-poor scenario. The proposed model compares favorably to state-of-the-art approaches and achieves an average performance accuracy of 60.93 on both the Hindi datasets.
Hardware Trust and Assurance through Reverse Engineering: A Tutorial and Outlook from Image Analysis and Machine Learning Perspectives
Authors: Botero Ulbert J. , Wilson Ronald , Lu Hangwei , Rahman Mir Tanjidur , Mallaiyan Mukhil A. , Ganji Fatemeh , Asadizanjani Navid , Tehranipoor Mark M. , Woodard Damon L. , Forte Domenic
Published: June 2021

In the context of hardware trust and assurance, reverse engineering has been often considered as an illegal action. Generally speaking, reverse engineering aims to retrieve information from a product, i.e., integrated circuits (ICs) and printed circuit boards (PCBs) in hardware security-related scenarios, in the hope of understanding the functionality of the device and determining its constituent components. Hence, it can raise serious issues concerning Intellectual Property (IP) infringement, the (in)effectiveness of security-related measures, and even new opportunities for injecting hardware Trojans. Ironically, reverse engineering can enable IP owners to verify and validate the design. Nevertheless, this cannot be achieved without overcoming numerous obstacles that limit successful outcomes of the reverse engineering process. This article surveys these challenges from two complementary perspectives: image processing and machine learning. These two fields of study form a firm basis for the enhancement of efficiency and accuracy of reverse engineering processes for both PCBs and ICs. In summary, therefore, this article presents a roadmap indicating clearly the actions to be taken to fulfill hardware trust and assurance objectives.
Polysulfide-Permanganate Flow Battery Using Abundant Active Materials
Authors: Yang Zhiwei , Gerhardt Michael R. , Fortin Michael , Shovlin Christopher , Weber Adam Z. , Perry Mike L. , Darling Robert M. , Saraidaridis James D.
Published: June 2021

A new flow battery is presented using the abundant and inexpensive active material pairs permanganate/manganate and disulfide/tetrasulfide. A wetted material set is identified for compatibility with the strongly oxidizing manganese couple at ambient and elevated temperatures. Both solutions allow high active material solubility, with cells tested at theoretical energy densities up to 43 Wh l−1 for the ∼1.2 V cell. Full cells built with nickel foam electrodes and sodium-exchanged Nafion 115 membranes deliver a baseline area-specific resistance of 2.7 Ω-cm2. Incorporation of high-surface-area cobalt-coated carbon paper and high-surface-area stainless steel mesh electrodes, and an expanded Nafion 115 membrane delivers cells with 44% lower resistance at 1.6 Ω-cm2. All cells show performance decay over the course of cycling. The Co-decorated carbon paper electrodes provide significant kinetic improvements, shifting electrode performance from non-linear with Ni-foam to linear with a volume-normalized exchange current density value of 3.2 A cm−3. The expanded membrane provides increased conductivity over the 13 mS cm−1 conductivity observed in as-received, sodium-exchanged Nafion 115. Although boiled membranes provide improved conductivity, it is at the cost of decreased Coulombic efficiency and poorer manufacturability. Full cell models suggest that similar cell resistances (1.7 Ω-cm2) should be feasible with as-received Nafion 115 and advanced electrodes.
Heterogeneity within molecular subtypes of breast cancer
Authors: Turner Kevin M. , Yeo Syn Kok , Holm Tammy M. , Shaughnessy Elizabeth , Guan Jun-Lin
Published: June 2021

Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single-cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells themselves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Interconversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must, therefore, contend with changing phenotypes in an individual patient’s tumor. Identifying targetable drivers of molecular heterogeneity may improve treatment durability and disease progression.
Paradoxical response of pulmonary slowly adapting units during constant pressure lung inflation
Authors: Yu Jerry
Published: June 2021

Typically, unit discharge of slowly adapting receptors (SARs) declines slowly when lung inflation pressure is constant, although in some units it increases instead—a phenomenon hereinafter referred to as creeping. These studies characterize creeping behavior observed in 62 of 137 SAR units examined in anesthetized, open-chest, and mechanically ventilated rabbits. SAR units recorded from the cervical vagus nerve were studied during 4 s of constant lung inflation at 10, 20, and 30 cmH2O. Affected SAR units creep more quickly as inflation pressure increases. SAR units also often deactivate after creeping, i.e., their activity decreases or stops completely. Creeping likely results from encoder switching from a low discharge to a high discharge SAR, because it disappears in SAR units with multiple receptive fields after blocking a high discharge encoder in one field leaves low discharge encoders intact. The results support that encoder switching is a common mechanism operating in lung mechanosensory units.
Event-related synchronization/desynchronization and functional neuroanatomical regions associated with fatigue effects on cognitive flexibility
Authors: Yu Shijing , Mückschel Moritz , Beste Christian
Published: June 2021

We examine the neurophysiological and functional neuroanatomical basis of fatigability in cognitive flexibility. We show that alpha and theta modulations in fronto-parietal and primary sensory areas are central for the understanding of fatigability effects in cognitive flexibility.
Chimera State in the Network of Fractional‐Order FitzHugh–Nagumo Neurons
Authors: Ramadoss Janarthanan , Aghababaei Sajedeh , Parastesh Fatemeh , Rajagopal Karthikeyan , Jafari Sajad , Hussain Iqtadar
Published: June 2021

The fractional calculus in the neuronal models provides the memory properties. In the fractional‐order neuronal model, the dynamics of the neuron depends on the derivative order, which can produce various types of memory‐dependent dynamics. In this paper, the behaviors of the coupled fractional‐order FitzHugh–Nagumo neurons are investigated. The effects of the coupling strength and the derivative order are under consideration. It is revealed that the level of the synchronization is decreased by decreasing the derivative order, and the chimera state emerges for stronger couplings. Furthermore, the patterns of the formed chimeras rely on the order of the derivatives.
Finite-Time Control of Networked Control Systems with Time Delay and Packet Dropout
Authors: Sun Yerong , Sun Yeguo , Yang Chunzhi
Published: June 2021

This paper studies the finite-time stabilization and boundedness problem of a class of network control systems that are simultaneously affected by time delay and packet loss. Based on the Lyapunov function method, the sufficient conditions for the design of the state feedback controller in the form of linear matrix inequality are obtained. The state feedback controller makes the network control system stable for a finite time. Finally, a numerical example is given to illustrate the effectiveness and feasibility of the method. The research results of this paper will develop and enrich the control theory system of the network control system and provide advanced control theory methods and application technology reserves in order to promote the development process of the network control system application and improve the application level.
Fast Synthesis Method for Large Aperture Array Pattern in the Presence of Array Errors
Authors: Huo Lihuan , Bai Rulong , Xue Fei , Chen Jianfeng , Huang Penghui , Liao Guisheng
Published: June 2021

In this paper, an improved array synthesis method with array errors is proposed for large aperture arrays. Because of the array errors such as amplitude-phase errors and positions errors, the performance of the array synthesis is reduced seriously. Firstly, the ideal fast low sidelobe synthesis method is obtained based on the discrete Fourier transform (DFT) method. Then, by using Taylor expansion to remove the coupling relationship between the position of the element and the scanning angle, the compensation matrix for the pattern function and the array weighted vector with amplitude phase and position errors are derived. At last, the conversion relationship between the array with errors and the array weight vector is corrected in the iterative process. The theoretical simulation experiments verify the effectiveness and robustness of the proposed method for the linear array and rectangular array pattern synthesis. Then, the influence of Taylor expansion order on the pattern synthesis results is analysed.
Integrating an Extended Outranking‐TOPSIS Method with Probabilistic Linguistic Term Sets for Multiattribute Group Decision‐Making
Authors: Shen Feng , Yang Zhiyuan , Cai Dongliang
Published: June 2021

Group decision‐making is a common activity in organizational management and economic conditions. In practice, the opinions of experts may be fuzzy. This paper proposes integrating an extended outranking‐TOPSIS method with probabilistic linguistic term sets for multiattribute group decision‐making, which is used to solve the real‐world public‐private partnership (PPP) project selection problem. First, an extended outranking method based on probabilistic linguistic term sets is proposed, and each expert’s ranking of alternatives is obtained according to this method. After the individual ranking is completed, the large‐scale expert group is clustered by the K‐means clustering method, and then the improved consensus mechanism is used to study the degree of consensus of the expert group. If the consensus of the group is not up to the standard, then, for clusters with a lower degree of consensus with the group, the feedback mechanism is used to adjust the weight between different clusters so that the group consensus can be improved. After achieving the target group consensus, an improved technique for order preference by similarity to an ideal solution (TOPSIS) method is used to synthesize expert opinions, and the ranking results are obtained. Finally, there are cases used to demonstrate the feasibility and rationality of the method.
Slope Belts of Paleouplifts Control the Pore Structure of Organic Matter of Marine Shale: A Comparative Study of Lower Cambrian Rocks in the Sichuan Basin
Authors: Wang Pengfei , Zhang Chen , Liu Aoran , Zhang Pengfei , Qiu Yibo , Li Xin , Yu Shanshan , Yao Shuqing , Liu Sanyi , Jiang Zhenxue
Published: June 2021

Extensive exploration of the marine shale of the Niutitang Formation in south China has been conducted. However, exploration and development results have varied considerably in different areas. For example, the Niutitang shale in Jingyan City (Southwestern Sichuan Basin) produces a large amount of gas with a long period of stable production. In contrast, most development wells in the Niutitang shale in Chongqing City do not produce gas. Scanning electron microscopy images showed that the organic matter (OM) pore development in the Niutitang shale in Jingyan is abundant, large in size, and are well connected. In contrast, OM pores in the Niutitang shale in Chongqing are rarely observed. OM pore development of the Jingyan and Chongqing shales is mainly controlled by thermal maturity as shown by equivalent vitrine reflectance determinations. The moderate thermal maturity has resulted in the development of a large number of OM pores in the Niutitang shale in Jingyan, whereas the high thermal maturity of the Niutitang shale in Chongqing has led to the destruction of most of the OM pores. Due to the existence of ancient uplift, the shale was buried shallowly in the process of hydrocarbon generation evolution, and the shale avoided excessive thermal evolution and retained appropriate thermal maturity. In the Jingyan area, due to its location near the central uplift in the Sichuan Basin, the Niutitang shale deposited nearby avoided excessive evolution, and a large number of OM pores were retained in the reservoir.
Scenario of Plant Breeding in Nepal and Its Application in Rice
Authors: K. C. Bigyan , Pandit Rishav , Kandel Bishnu Prasad , K. C. Kanchan Kumar , K. C. Arpana , Poudel Mukti Ram
Published: June 2021

Rice, the number one staple food crop of Nepal, contributes nearly 20% to the agricultural gross domestic product, almost 7% to gross domestic product, and supplies with 40% of the food calorie consumption of Nepalese people. Despite of increasing production, the national demand of rice cannot be fulfilled, and billions of rupees are spent yearly for importing rice from India. This article reviews history, recent scenario, prospects, and importance of rice breeding research in Nepal for self-sufficiency. Though plant breeding inception point in Nepal was 1951, the systematic research in rice was started from 1972 after the establishment of the National Rice Research Program. Introduction and evaluation of high yielding exotic germplasm of rice was the initial rice breeding activities. After analysing several foreign materials, CH-45 variety of rice was first recommended in 1959. Nepal Agriculture Research Council (NARC), the leading organisation for rice varietal improvement to date, has been doing rice research activities such as germplasm conservation, exchange, varietal development, verification of technologies, and knowledge updates in collaboration with various organizations. International Rice Research Institute (IRRI), since 1966, has been playing an important role in Nepal’s rice research. Major plant breeding achievements are introduction of exotic materials and their evaluation, local landraces identification, collection and analysis, crossing of local landraces with exotic genetic materials, heterosis breeding, tissue culture technology, genetic marker technology, and National Genebank. RAPD and SSR, DNA-based markers, are mostly used for diversity appraisal and selecting desirable genotypes. Integration of advanced tools such as genetic engineering, bioinformatics, protoplast fusion, and SNP markers could not be still applied in rice research and development. Hence, emphasis should be given to improve the capacity and abilities of the rice scientists and should release more short duration, drought, and submergence-tolerant rice varieties by optimum utilisation of local landraces combining modern and conventional breeding.
A Panax notoginseng Root Tip Meristem Biosensor and Its Sensing Kinetics for Five Important Nitrogen Nutrients
Authors: Zheng Zi Qing , Niu Bo , Lu Ding Qiang , Pang Guang Chang
Published: June 2021

Plants absorb nitrogen mainly through their roots. Nitrogen sensing is required for the absorption and transport of different nitrogen nutrients. In this study, we constructed biosensors with immobilized Panax notoginseng root tip meristems based on a three‐electrode system and successfully determined the kinetics of the interactions between the P. notoginseng root tip meristems and five important nitrogen nutrients, namely, urea, sodium nitrate, sodium glutamate, disodium inosinate, and disodium guanylate. We discovered that the biosensor’s sensing kinetics was similar to the enzyme–substrate kinetics, and the receptor–ligand interconnected allosteric interaction constant Ka (mol/L), analogous to the Michaelis constant, was calculated. The result showed that the root tip meristems of two‐ to four‐year‐old P. notoginseng plants had a higher capacity to sense inorganic nitrogen nutrients (sodium nitrate and urea) than the three organic nitrogen nutrients. The ability of the plants to sense inorganic nitrogen nutrients decreased with an increase in plant age. The sensing sensitivity of four‐year‐old P. notoginseng plants to disodium inosinate and disodium guanylate was 100‐ to 10,000‐fold lower than that of the two‐ and three‐year‐old plants. Additionally, the capability to sense sodium glutamate decreased initially and then increased with an increase in plant age. The biosensors reached an ultra‐sensitive level (1 × 10−22 mol/L) in sensing the five nitrogen nutrients and exhibited advantages such as good stability and reproducibility, low cost, a simple structure, and a rapid response, providing a new approach for quantitative determination of the capability of plants to sense different nitrogen nutrients.
New Post Quantum Analogues of Hermite–Hadamard Type Inequalities for Interval-Valued Convex Functions
Authors: Kalsoom Humaira , Ali Muhammad Aamir , Idrees Muhammad , Agarwal Praveen , Arif Muhammad
Published: June 2021

The main objective of this paper is to introduce

I

p
,
q

ϱ

-derivative and

I

p
,
q

ϱ

-integral for interval-valued functions and discuss their key properties. Also, we prove the

I

p
,
q

ϱ

-Hermite–Hadamard inequalities for interval-valued functions is the development of

p
,
q

ϱ

-Hermite–Hadamard inequalities by using new defined

I

p
,
q

ϱ

-integral. Moreover, we prove some results for midpoint- and trapezoidal-type inequalities by using the concept of Pompeiu–Hausdorff distance between the intervals. It is also shown that the results presented in this paper are extensions of some of the results already shown in earlier works. The proposed studies produce variants that would be useful for performing in-depth investigations on fractal theory, optimization, and research problems in different applied fields, such as computer science, quantum mechanics, and quantum physics.
Anaemia Associated with Trypanosomes Infections in Cattle of West Gojjam Zone, Northwest Ethiopia
Authors: Lelisa Kumela , Meharenet Behablom
Published: June 2021

Background. African animal trypanosomosis is a major veterinary problem over a large area of the tsetse belt region of Africa. Anaemia is a cardinal sign of trypanosome infections. The mechanism of anaemia due to trypanosomosis is complex and multifactorial in origin. Packed cell volume (PCV) usually gives an indication of the anaemia and disease status of a trypanosome-infected animal. Methods. A cross-sectional study was conducted from December 2017 to January 2018 in West Gojjam zone, Northwest Ethiopia, to determine the trypanosome infections rate and the possible correlation between parasitic infection and anaemia using the dark ground buffy coat technique, Giemsa-stained thin blood smear, and PCV reading on a haematocrit reader. Results. The overall trypanosomosis prevalence was 7.81%, 95% CI = 7.45–8.17. Trypanosoma congolense (4.25%) and T. vivax (3.56%) were the trypanosomes species identified in the studied area. PCV for all sampled cattle was analysed to estimate the degree of anaemia. From the total examined animals (N = 730), 356 (48.77%) were anaemic and 374 (51.23%) were nonanaemic. The mean PCV of parasitemic cattle was significantly lower (21.09%, 95% CI = 20.13–22.05) than that of aparasitemic ones (25.96%, 95% CI = 25.68–26.24). There was a positive association between trypanosome infection and anaemia. Although both trypanosome species are significantly associated with a decreased herd mean PCV (<24), the mean PCV of cattle infected with T. congolense (19.45%) was lower than that of infected with T. vivax (23.04%). The herd mean PCV was not significantly associated to locations, age, and sex of the studied animals. Conclusions. The study confirms that the prevalence of trypanosomes infections and herd mean PCV has a significant association. The mean herd PCV can be a useful cheap tool to screen for possible trypanosome infection. However, there were cattle positive for trypanosomes having mean PCV within the reference interval and negative animals with anaemia. Furthermore, PCV reading should be confirmed by other diagnostic techniques to accurately conclude that trypanosomosis is the only cause of anaemia.
Evaluation of RNA Extraction‐Free Method for Detection of SARS‐CoV‐2 in Salivary Samples for Mass Screening for COVID‐19
Authors: Mahmoud Sally A. , Ganesan Subhashini , Ibrahim Esra , Thakre Bhagyashree , Teddy Juliet G. , Raheja Preety , Abbas Walid Z.
Published: June 2021

In this COVID‐19 pandemic, there is a dire need for cost‐effective and less time‐consuming alternatives for SARS‐CoV‐2 testing. The RNA extraction‐free method for detecting SARS‐CoV‐2 in saliva is a promising option. This study found that it has high sensitivity (85.34%), specificity (95.04%), and was comparable to the gold standard nasopharyngeal swab (NPS) sample tests. The method showed good agreement between salivary and NPS samples, with a kappa coefficient of 0.797. However, there are variations in the sensitivity and specificity based on the RT‐PCR kit used. The Thermo Fisher Applied Biosystems showed high sensitivity, positive predictive value (PPV), and negative predictive value (NPV) but also showed a higher percentage of invalid reports. On the other hand, the BGI kit showed high specificity, better agreement (kappa coefficient) between the results of saliva and NPS samples, and higher correlation between the Ct values of saliva and NPS samples. Thus, the RNA extraction‐free method for salivary sample serves as an effective alternative screening method for COVID‐19.
Effects of the Multidimensional Treatment on Pain, Disability, and Sitting Posture in Patients with Low Back Pain: A Randomized Controlled Trial
Authors: In Tae-Sung , Jung Jin-Hwa , Jung Kyoung-Sim , Cho Hwi-Young
Published: June 2021

The purpose of this study was to investigate the effects of multidimensional approach model on the pain, disability, and sitting posture in patients with nonspecific low back pain (LBP). Sixty LBP patients were recruited and were randomly divided into two groups: multidimensional treatment (MT) group (n = 30) and unimodal treatment (UT) group (n = 30). All participants underwent 48 sessions of treatment (40 min/session, two sessions per day, 2 days per week) for 12 weeks. The MT group conducted a core stability exercise twice a day and additionally provided training on pain principles and management methods. The UT group only performed a core stability exercise twice a day. The visual analog scale (VAS) and Oswestry Disability index (ODI) were used to measure pain intensity and disability. Thoracolumbar kyphosis and lumbar lordosis in the sitting position were measured using a motion capture system. After training, the pain and disability in the MT group improved significantly greater than the UT group (

p
<
0.05

). In the MT group, the pain relief effect persisted 3 months after the end of training. Thoracolumbar kyphosis and lumbar lordosis in the MT group were significantly improved compared to the UT group (

p
<
0.05

). Thus, MT combined with core stability exercise may be used to improve the pain, disability, and sitting posture in patients with LBP.
Study of Electric Field Impact on Crystallization in Tunnel Drainage Pipes in Hard Water Area
Authors: Wei Liangwen , Guo Jingyi , Zhang Xuefu , Li Yunqi , Huang Peng
Published: June 2021

To solve the problem of blockage of crystallization in tunnel drainage pipes in hard water area, electric field devices are designed and applied in the transversal tunnel drainage pipe according to the fundamental law of crystallization. Laboratory tests were carried out to test the crystallizing tunnel drainage pipe under the effect of electric field in order to study the law of electric field impact on crystallization in tunnel drainage pipes in hard water area. The test results indicate that the arranged circumferential and parallel plate electric field devices can form an electrical field within a narrow and small space inside the pipe and influence the ion movement in water and adsorption performance between crystals and the pipe. Under the condition of full flow, the amount of crystals in the ordinary pipe without electric field treatment increases progressively along water flow direction and remains relatively uniform later. The amount of crystals along the water flow direction of the pipe treated with circumferential and parallel plate electric fields presents signs of fluctuation in the early stage and then stableness later. The amount of crystals in the fluctuating section is higher and lower in the uniform section, and its uniform section length is longer than that in ordinary pipes. Under the condition of full current, crystallizing speed declines with elapse of running time. After the electric field is imposed, crystallizing acceleration progressively decreased to a relatively lower level. Comparing three voltages of 5 V, 12 V, and 24 V, the effect of scale inhibition under 5 V is superior. When water amount in the pipe varies, the effects of scale inhibition under different electric field modes are different. The electric field effect causes the changes of the external form of calcium carbonate crystal and its surface abrasion, porous crystal, and structural looseness.
Generalization of Thermal and Mass Fluxes for the Flow of Differential Type Fluid with Caputo–Fabrizio Approach of Fractional Derivative
Authors: Razzaque Asima , Rani Anam , Nazar Mudassar
Published: June 2021

In this research work, generalized thermal and mass transports for the unsteady flow model of an incompressible differential type fluid are considered. The Caputo–Fabrizio fractional derivative is used for the respective generalization of Fourier’s and Fick’s laws. A MHD fluid flow is considered near a flat vertical surface subject to unsteady mechanical, thermal, and mass conditions at boundary. The governing equations of flow model are solved by integral transform, and closed form results for generalized momentum, thermal, and concentration fields are obtained. Generalized thermal and mass fluxes at boundary are quantified in terms of Nusselt and Sherwood numbers, respectively, and presented in tabular form. The significance of the physical parameters over the momentum, thermal, and concentration profiles is characterized by sketching the graphs.
Global Optimal Solutions for Proximal Fuzzy Contractions Involving Control Functions
Authors: Moussaoui Abdelhamid , Hussain Nawab , Melliani Said
Published: June 2021

In this study, we introduce new concepts of

α
−
FZ

-contraction and

α
−
ψ
−
FZ

-contraction and we discuss existence results of the best proximity points of such types of non-self-mappings involving control functions in the structure of complete fuzzy metric spaces. Our results extend, generalize, enrich, and improve diverse existing results in the current literature.