bluuebunny/crossref_metadata_2025 huggingface dataset:
A Wearable, Multi-Frequency Device to Measure Muscle Activity Combining Simultaneous Electromyography and Electrical Impedance Myography
Authors: Ngo Chuong , Munoz Carlos , Lueken Markus , Hülkenberg Alfred , Bollheimer Cornelius , Briko Andrey , Kobelev Alexander , Shchukin Sergey , Leonhardt Steffen
Published: March 2022

The detection of muscle contraction and the estimation of muscle force are essential tasks in robot-assisted rehabilitation systems. The most commonly used method to investigate muscle contraction is surface electromyography (EMG), which, however, shows considerable disadvantages in predicting the muscle force, since unpredictable factors may influence the detected force but not necessarily the EMG data. Electrical impedance myography (EIM) investigates the change in electrical impedance during muscle activities and is another promising technique to investigate muscle functions. This paper introduces the design, development, and evaluation of a device that performs EMG and EIM simultaneously for more robust measurement of muscle conditions subject to artifacts. The device is light, wearable, and wireless and has a modular design, in which the EMG, EIM, micro-controller, and communication modules are stacked and interconnected through connectors. As a result, the EIM module measures the bioimpedance between 20 and 200 Ω with an error of less than 5% at 140 SPS. The settling time during the calibration phase of this module is less than 1000 ms. The EMG module captures the spectrum of the EMG signal between 20–150 Hz at 1 kSPS with an SNR of 67 dB. The micro-controller and communication module builds an ARM-Cortex M3 micro-controller which reads and transfers the captured data every 1 ms over RF (868 Mhz) with a baud rate of 500 kbps to a receptor connected to a PC. Preliminary measurements on a volunteer during leg extension, walking, and sit-to-stand showed the potential of the system to investigate muscle function by combining simultaneous EMG and EIM.
Research on Classification of Open-Pit Mineral Exploiting Information Based on OOB RFE Feature Optimization
Authors: Zhou Yi , Tian Shufang , Chen Jianping , Liu Yao , Li Chaozhu
Published: March 2022

Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this information is essential to mineral management and environmental protection. In recent years, there are an increasingly large number of pieces of research on land surface information classification by conducting multi-source remote sensing data. However, in order to achieve the best classification result, how to select the optimal feature combination is the key issue. This study creatively combines Out of Bag data with Recursive Feature Elimination (OOB RFE) to optimize the feature combination of the mineral exploiting information of non-metallic building materials in Fujian province, China. We acquired and integrated Ziyuan-1-02D (ZY-1-02D) hyperspectral imagery, landsat-8 multispectral imagery, and Sentinel-1 Synthetic Aperture Radar (SAR) imagery to gain spectrum, heat, polarization, and texture features; also, two machine learning methods were adopted to classify the mineral exploiting information in our study area. After assessment and comparison on accuracy, it proves that the classification generated from our new OOB RFE method, which combine with random forest (RF), can achieve the highest overall accuracy 93.64% (with a kappa coefficient of 0.926). Comparing with Recursive Feature Elimination (RFE) alone, OOB REF can precisely filter the feature combination and lead to optimal result. Under the same feature scheme, RF is effective on classifying the mineral exploiting information of the research field. The feature optimization method and optimal feature combination proposed in our study can provide technical support and theoretical reference for extraction and classification of mineral exploiting information applied in other regions.
A Correlation-Based Anomaly Detection Model for Wireless Body Area Networks Using Convolutional Long Short-Term Memory Neural Network
Authors: Albattah Albatul , Rassam Murad A.
Published: March 2022

As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare services. WBANs are made up of tiny devices that can effectively enhance patient quality of life by collecting and monitoring physiological data and sending it to healthcare givers to assess the criticality of a patient and act accordingly. The collected data must be reliable and correct, and represent the real context to facilitate right and prompt decisions by healthcare personnel. Anomaly detection becomes a field of interest to ensure the reliability of collected data by detecting malicious data patterns that result due to various reasons such as sensor faults, error readings and possible malicious activities. Various anomaly detection solutions have been proposed for WBAN. However, existing detection approaches, which are mostly based on statistical and machine learning techniques, become ineffective in dealing with big data streams and novel context anomalous patterns in WBAN. Therefore, this paper proposed a model that employs the correlations that exist in the different physiological data attributes with the ability of the hybrid Convolutional Long Short-Term Memory (ConvLSTM) techniques to detect both simple point anomalies as well as contextual anomalies in the big data stream of WBAN. Experimental evaluations revealed that an average of 98% of F1-measure and 99% accuracy were reported by the proposed model on different subjects of the datasets compared to 64% achieved by both CNN and LSTM separately.
A Dual-Mode 303-Megaframes-per-Second Charge-Domain Time-Compressive Computational CMOS Image Sensor
Authors: Kagawa Keiichiro , Horio Masaya , Pham Anh Ngoc , Ibrahim Thoriq , Okihara Shin-ichiro , Furuhashi Tatsuki , Takasawa Taishi , Yasutomi Keita , Kawahito Shoji , Nagahara Hajime
Published: March 2022

An ultra-high-speed computational CMOS image sensor with a burst frame rate of 303 megaframes per second, which is the fastest among the solid-state image sensors, to our knowledge, is demonstrated. This image sensor is compatible with ordinary single-aperture lenses and can operate in dual modes, such as single-event filming mode or multi-exposure imaging mode, by reconfiguring the number of exposure cycles. To realize this frame rate, the charge modulator drivers were adequately designed to suppress the peak driving current taking advantage of the operational constraint of the multi-tap charge modulator. The pixel array is composed of macropixels with 2 × 2 4-tap subpixels. Because temporal compressive sensing is performed in the charge domain without any analog circuit, ultrafast frame rates, small pixel size, low noise, and low power consumption are achieved. In the experiments, single-event imaging of plasma emission in laser processing and multi-exposure transient imaging of light reflections to extend the depth range and to decompose multiple reflections for time-of-flight (TOF) depth imaging with a compression ratio of 8× were demonstrated. Time-resolved images similar to those obtained by the direct-type TOF were reproduced in a single shot, while the charge modulator for the indirect TOF was utilized.
An Image Augmentation Method Based on Limited Samples for Object Tracking Based on Mobile Platform
Authors: Wang Zihao , Yang Sen , Shi Mengji , Qin Kaiyu
Published: March 2022

This paper proposes an image augmentation model of limited samples on the mobile platform for object tracking. The augmentation method mainly aims at the detection failure caused by the small number of effective samples, jitter of tracking platform, and relative rotation between camera and object in the tracking process. Aiming at the object tracking problem, we first propose to use geometric projection transformation, multi-directional overlay blurring, and random background filling to improve the generalization ability of samples. Then, selecting suitable traditional augmentation methods as the supplements, an image augmentation model with an adjustable probability factor is provided to simulate various kinds of samples to help the detection model carry out more reliable training. Finally, combined with a spatial localization algorithm based on geometric constraints proposed by the author’s previous work, a framework for object tracking with an image augmentation method is proposed. SSD, YOLOv3, YOLOv4, and YOLOx are adopted in the experiment of this paper as the detection models. And a large number of object recognition and object tracking experiments are carried out by combining with common data sets OTB50 and OTB100 as well as the OTMP data set proposed by us for mobile platform. The augmented module proposed in this paper is conducive for the detection model to improve the detection accuracy by at least 10%. Especially for objects with planar characteristics, the affine and projection transformation used in this paper can greatly improve the detection accuracy of the model. Based on the object tracking framework of our augmented model, the RMSE is estimated to be less than 4.21 cm in terms of the actual tracking of indoor objects.
Spatially Resolved Temperature Distribution in a Rare-Earth-Doped Transparent Glass-Ceramic
Authors: Sedmak Ivan , Podlipec Rok , Urbančič Iztok , Štrancar Janez , Mortier Michel , Golobič Iztok
Published: March 2022

Knowing the temperature distribution within the conducting walls of various multilayer-type materials is crucial for a better understanding of heat-transfer processes. This applies to many engineering fields, good examples being photovoltaics and microelectronics. In this work we present a novel fluorescence technique that makes possible the non-invasive imaging of local temperature distributions within a transparent, temperature-sensitive, co-doped Er:GPF1Yb0.5Er glass-ceramic with micrometer spatial resolution. The thermal imaging was performed with a high-resolution fluorescence microscopy system, measuring different focal planes along the z-axis. This ultimately enabled a precise axial reconstruction of the temperature distribution across a 500-µm-thick glass-ceramic sample. The experimental measurements showed good agreement with computer-modeled heat simulations and suggest that the technique could be adopted for the spatial analyses of local thermal processes within optically transparent materials. For instance, the technique could be used to measure the temperature distribution of intermediate, transparent layers of novel ultra-high-efficiency solar cells at the micron and sub-micron levels.
Individual Diet Optimization in French Adults Shows That Plant-Based “Dairy-like” Products May Complement Dairy in Sustainable Diets
Authors: Gazan Rozenn , Vieux Florent , Lluch Anne , de Vriese Stephanie , Trotin Beatrice , Darmon Nicole
Published: March 2022

This study aimed to explore the potential role of plant-based “dairy-like” products (PBDL) in sustainable diets. For each individual from a representative sample of French adults (INCA2 survey 2006–2007; n = 1816), a diet optimized to be more sustainable (nutritionally adequate while having a 30% reduced carbon impact with minimal change from the actual diet and isocaloric content) was modelled. The food content of the optimized diets was compared to actual diets, with a focus on PBDL and dairy products. The presented quantitative results focused on women. Optimized diets contained more plant-based products and less meats than actual diets. PBDL products were present in 7.3% and 55.7% of the subjects’ actual and optimized diets, respectively, increasing significantly from 7 to 48 g/day. Regarding dairy products, cheese decreased (−14 g/day), milk increased (+14 g/day), and yogurt remained constant (87 g/day) between the actual and optimized diets, such that the intake of this food group remained constant (214 g/day). Women for whom PBDL products were introduced as new foods in their optimized diets were found to be those with actual low energy intake (1755 kcal/d on average). As a complement to dairy products, fortified PBDL products may help to achieve more sustainable diets, especially for individuals with low energy intakes.
What Causes the M&A Performance of High-Tech Firms?
Authors: Cho Sung-woo , Jung Jin-young , Kim Byoung-Jin , Song Hyunjoo
Published: March 2022

We perform an event study on 2824 cases of domestic mergers and acquisitions (M&A) that were disclosed in the Korean domestic stock exchange and took effect between 2002 and 2015. We focus on Korean capital markets to define the factor variables affecting the disclosure effect of M&A in high-tech industries and the effect of disclosure on long-term performance. We find the following. First, the disclosure effect of M&A benefits acquirers’ shareholder wealth; this effect is more pronounced for high-tech firms than for non-high-tech firms. Second, M&A of high- and non-high-tech firms harm acquirers’ shareholder wealth via the disclosure effect. Finally, M&A between high- and non-high-tech firms negatively affect long-term firm performance. However, acquirers that are mature high-tech firms have a positive effect on long-term performance. This result affirms that organizationally mature firms adapt better to highly specialized technologies and knowledge that are not yet internalized as corporate routines owing to their learned capabilities and breadth of experience. This study provides a significant novel perspective on high-tech M&A by emphasizing the financial performance of firms involved in them.
Computer Architectures for Incremental Learning in Water Management
Authors: Kenda Klemen , Mellios Nikolaos , Senožetnik Matej , Pergar Petra
Published: March 2022

This paper presents an architecture and a platform for processing of water management data in real time. Stakeholders in the domain are faced with the challenge of handling large amounts of incoming sensor data from heterogeneous sources after the digitalization efforts within the sector. Our water management analytical platform (WMAP) is built upon the needs of domain experts (it provides capabilities for offline analysis) and is designed to solve real-world problems (it provides real-time data flow solutions and data-driven predictive analytics) for smart water management. WMAP is expected to contribute significantly to the water management domain, which has not yet acquired the competences to implement extensive data analysis and modeling capabilities in real-world scenarios. The proposed architecture extends existing big data architectures and presents an efficient way of dealing with data-driven modeling in the water management domain. The main improvement is in the speed (online analytics) layer of the architecture, where we introduce heterogeneous data fusion in a set of data streams that provide real-time data-driven modeling and prediction services. Using the proposed architecture, the results illustrate that models built with datasets with richer contextual information and multiple data sources are more accurate and thus more useful.
Low-Voltage Plasma Generator Based on Standing Wave Voltage Magnification
Authors: Covaci Mihnea Antoniu , Szolga Lorant Andras
Published: March 2022

The applied electronics domain has great importance due to many applications, such as energy conversion, directly influencing specific processes involving renewable energy. The development of newer manufacturing processes for many integrated components allows for better overall efficiency in certain switching DC/DC converters used for implementing such low-voltage electric field or X-ray generators. Hence, the work presented in this paper involves the development of a helical resonator using a complex DC/DC low-voltage power supply and other required high-voltage conversion circuits. It also follows that there is a possibility of improving this design using only renewable energy supplies. Following two different approach methods, using a circuit model compared to transmission line mathematics, the standing wave propagation mathematics yields multiple scenarios for building a model that predicts the secondary side natural frequency. Moreover, standing wave occurrence conditions in various-dimensioned conductors were further investigated.
The Effects of Pilgrimage on the Meaning in Life and Life Satisfaction as Moderated by the Tourist’s Faith Maturity
Authors: Baek Kyuri , Choe Yunseon , Lee Seungjae , Lee Gyehee , Pae Tae-Il
Published: March 2022

Searching and finding meaning and happiness in life is the ultimate quest for humans. Pilgrimages embody special meanings and values. This research delves into the effects of pilgrimage experiences on meaning and life satisfaction via structure equation modeling (SEM) based on a bottom-up approach to life satisfaction. Moreover, the moderating role that faith maturity plays between experience and meaning life is noteworthy, which was assessed based on Ping’s two-step procedure. For data collection, an on-line survey was conducted for those who had visited overseas Christian pilgrimage sites. A total of 257 responses were analyzed via SEM for hypothesis tests. The results of this study identified (1) the effect of the pilgrimage experience on meaning in life and life satisfaction, (2) the effect of the search for meaning on the construction of meaning in life, and (3) the effect of meaning in life on perceived life satisfaction, suggesting that the bottom-up approach holds true in the context of religious trips. It was also found that faith maturity had a significant moderating effect on the relationship between the experience of the pilgrimage and the presence of meaning in one’s life. This study contributes to the existing literature by incorporating travel experience into QOL domains and also taps on the possibility to expand the research topic into more contemporary modes of travel, including meditation travel and various forms of new travel linked to spirituality. Practical and theoretical implications of the findings to the tourism research are discussed.
The Cost Benefit Analysis of Commercial 100 MW Solar PV: The Plant Quaid-e-Azam Solar Power Pvt Ltd.
Authors: Asad Muhammad , Mahmood Farrukh Ibne , Baffo Ilaria , Mauro Alessandro , Petrillo Antonella
Published: March 2022

The energy crisis in Pakistan has crippled the country’s economy with an energy shortfall reaching up to 6000 MW. Fortunately, Pakistan lies close to the Sun Belt and therefore receives very high irradiation. To this end, in the beginning of 2014 the Pakistani government sanctioned a solar photovoltaic project namely Quaid-e-Azam Solar Park which was rated at 1000 MW. In this study, a cost benefit analysis for the Quaid-e-Azam Solar Park has been developed. The model uses RETScreen software. In fact, a literature review pointed out that most of the previous research work with reference to cost benefit analysis for solar projects has been mainly carried out on smaller power plants. The outcome of the study shows promising results with the simple payback period coming out at 5.6 years. Furthermore, this analysis can serve as guideline for future solar photovoltaic projects in Pakistan and can help in the development and utilization of the huge solar potential of the country, thus aiding in the reduction of energy shortage. In its proposal, our research is unique and innovative in the Pakistani context. The results aim to serve as a guideline for decision makers and researchers interested in this topic.
Evaluation of Urban Spatial Resilience and Its Influencing Factors: Case Study of the Harbin–Changchun Urban Agglomeration in China
Authors: Ma Xuefei , Chen Xiaohong , Du Yue , Zhu Xuan , Dai Yue , Li Xin , Zhang Rui , Wang Ying
Published: March 2022

This study constructs a framework for evaluating urban spatial resilience based on five dimensions: scale, intensity, morphology, function, and benefit. Likewise, it empirically analyzes the spatial differences and influencing factors of urban spatial resilience in the Harbin–Changchun urban agglomeration from 2000 to 2020. Overall, the spatial resilience of the Harbin–Changchun urban agglomeration declined from 2000 to 2019. In addition, its ability to resist external disturbances weakened. The five dimensions of spatial resilience declined. However, urban spatial morphological resilience slightly increased. The spatial diversity of the Harbin–Changchun urban agglomeration is obvious, implying that the spatial resilience of cities in the central region, mainly in Suihua and Songyuan, is higher than in peripheral areas of the urban agglomeration, mostly in the Yanbian Korean Autonomous Prefecture, Siping, and Qiqihar. The period between 2000 and 2019 was dominated by cities with fluctuating spatial resilience. Furthermore, urban spatial resilience is influenced by a combination of factors, with economic support being the primary one. The selection of the urban spatial resilience research index system in this study is more spatially oriented and more accurately reflects the urban spatial resilience situation, which, in turn, provides a new planning perspective for urban planning in China.
A Deep Learning Framework for Multimodal Course Recommendation Based on LSTM+Attention
Authors: Ren Xinwei , Yang Wei , Jiang Xianliang , Jin Guang , Yu Yan
Published: March 2022

With the impact of COVID-19 on education, online education is booming, enabling learners to access various courses. However, due to the overload of courses and redundant information, it is challenging for users to quickly locate courses they are interested in when faced with a massive number of courses. To solve this problem, we propose a deep course recommendation model with multimodal feature extraction based on the Long- and Short-Term Memory network (LSTM) and Attention mechanism. The model uses course video, audio, and title and introduction for multimodal fusion. To build a complete learner portrait, user demographic information, explicit and implicit feedback data were added. We conducted extensive and exhaustive experiments based on real datasets, and the results show that the AUC obtained a score of 79.89%, which is significantly higher than similar algorithms and can provide users with more accurate recommendation results in course recommendation scenarios.
Changes in the Innovation- and Marketing-Habits of Family SMEs in the Foodstuffs Industry, Caused by the Coronavirus Pandemic in Hungary
Authors: Bajkó Norbert , Fülöp Zsolt , Pércsi Kinga Nagyné
Published: March 2022

The economic specialties caused by the global coronavirus pandemic completely changed everyday life regarding certain sectors. For the small and medium enterprises, processing during the pandemic held several significant challenges, such as: cost-efficient operations, hardship of keeping employees, efficient management of innovation and various corporate activities, keeping the customers, etc. Many enterprises saw severe damages indirectly from the coronavirus pandemic, as society itself had its habits significantly changed, thereby necessitating changes in strategy for small and medium enterprises, most notably for local service providers and producers that have no delivery service. In order to solve the issue at hand, several governments tried applying a variety of solutions—mostly by financing the enterprises in question. The goal of the authors is to understand the current operation of innovation initiatives that small and medium enterprises have post-COVID-19, and to obtain a clear view on changes in marketing habits. Furthermore, the analysis concentrates on the following: the state of family SMEs dealing in foodstuffs, and how to create a future view for such members of the sector by identifying best practices. Using data collected during 2020 and 2021, and employing descriptive statistics and a conjoint analysis, the authors wished to see how the coronavirus pandemic affected SMEs, detect the changes in their marketing and innovation policy due to the pandemic, and help them create core business strategy via consumer feedback. Authors found that SMEs had to innovate by 2021 beyond their 2019 expectations, and that customers had partially validated their endeavors through their answers.
Implementation and Early Adoption of an Ethereum-Based Electronic Voting System for the Prevention of Fraudulent Voting
Authors: Ahn Byeongtae
Published: March 2022

Today’s online voting systems pose security concerns and cannot be used for public elections, while offline voting costs significantly more. As a result, a decentralized electronic voting system is emerging, backed by blockchain technology. With blockchain technology applied to online voting, the system can guarantee transparency and confidentiality because individual voter information and aggregate information are stored in a distributed fashion. Due to its decentralized nature, a blockchain-based voting system is more secure than the existing central server-based online voting system. In this study, an Ethereum-based electronic voting system was developed. This system resolves the issue of fraudulent voting by enhancing the safety and reliability of the electronic voting system.
Cemeteries as a Part of Green Infrastructure and Tourism
Authors: Sallay Ágnes , Mikházi Zsuzsanna , Gecséné Tar Imola , Takács Katalin
Published: March 2022

The world’s population and the proportion of it living in cities and urban areas has exploded in recent decades. In the European Union, 62% of the population lives in urban areas and 80% in suburban areas, and these proportions are projected to increase further in the coming decades. It has long been researched and proven that ‘urban greenery’ can play a major role in mitigating the so-called urban heat island effect, and during the COVID-19 pandemic the role of daily recreation has come to the forefront. The combined memorial, recreational, and touristic use of cemeteries can help to ensure their economic management, and thus the long-term preservation of their value. In international tourism the model of managing cemeteries as tourist attractions already exists; however, this is not yet part of conventional practice. In addition to traditional cemetery tourism (e.g., visiting the graves of celebrities or enjoying artistic treasures and values), cemeteries are used as venues for events and sports activities. In Western Europe forest and park cemeteries have been established since the 19th century, and their large green areas and open spaces are a prerequisite for their use as public parks. Thus, the use of cemeteries as public parks is a common if quite specific practice. Our aim with this article is to identify the green space values of Budapest’s cemeteries, in addition to their well-known cultural and architectural significance, as well as to define the potential and means of their involvement in tourism-related activities. Another aim of our study is to raise awareness of green cemeteries within the tourism profession as potentially wider tourist attractions. We consider it important to draw the attention of decision-makers to the significance of the greenspace values when preserving or reusing closed cemeteries. Based on our work, other major cities in Hungary can identify and exploit the touristic and green space potential of their cemeteries.
Bootstrapped DEA and Clustering Analysis of Eco-Efficiency in China’s Hotel Industry
Authors: Li Yang , Liu An-Chi , Yu Yi-Ying , Zhang Yueru , Zhan Yiting , Lin Wen-Cheng
Published: March 2022

As one of the world’s largest and fastest growing industries, tourism is facing the challenge of balancing growth and eco-environmental protection. Taking tourism CO2 emissions as undesirable outputs, this research employs the bootstrapping data envelopment analysis (DEA) approach to measure the eco-efficiency of China’s hotel industry. Using a dataset consisting of 31 provinces in the period 2016–2019, the bootstrapping-based test validates that the technology exhibits variable returns to scale. The partitioning around medoids (PAM) algorithm, based on the bootstrap samples of eco-efficiency, clusters China’s hotel industry into two groups: Cluster 1 with Shandong as the representative medoid consists of half of the superior coastal provinces and half of the competitive inland provinces, while Cluster 2 is less efficient with Jiangsu as the representative medoid. Therefore, it is suggested that the China government conduct a survey of only Shandong and Jiangsu to approximately capture the key characteristics of the domestic hotel industry’s eco-efficiency in order to formulate appropriate sustainable development policies. Lastly, biased upward eco-efficiencies may provide incorrect information and misguide managerial and/or policy implications.
The Roles of Orbital and Meltwater Climate Forcings on the Southern Ocean Dynamics during the Last Deglaciation
Authors: Mandal Gagan , Yu Jia-Yuh , Lee Shih-Yu
Published: March 2022

The last deglacial climate evolution, from 19 to 9 thousand years before the present, represents the vital role of feedback in the Earth’s climate system. The Southern Ocean played a fundamental role by exchanging nutrients and carbon-rich deep ocean water with the surface during the last deglaciation. This study employs a fully coupled Earth system model to investigate the evolution of Southern Ocean dynamics and the roles of changes in orbital and meltwater forcings during the last deglaciation. The simulation supports that the Southern Ocean upwelling was primarily driven by windstress. The results show that the melting and formation of Antarctic sea ice feedback influenced Southern Ocean surface buoyancy flux. The increase in Antarctic sea ice melt-induced freshwater flux resulted in a steepened north-south surface salinity gradient in the Southern Ocean, which enhanced the upwelling. The single-forcing experiments indicate that the deglacial changes in orbital insolation influenced the Southern Ocean upwelling. The experiments also highlight the dominant role of Northern Hemisphere meltwater discharge in the upper and lower branch of the Meridional Overturning Circulation. Furthermore, orbital forcing shows lesser deglacial Antarctic sea ice retreat than the Northern Hemisphere meltwater forcing, which follows the bipolar seesaw mechanism.
Influence Mechanism and Evolutionary Game of Environmental Regulation on Green Port Construction
Authors: Deng Gaodan , Chen Jingxiao , Liu Quanlong
Published: March 2022

Ports are not only an important driving force for the growth of the world economy but also the main energy-consuming unit and pollution source in the world. Under the new global energy crisis and environmental deterioration situation, the international port community has put forward the concept of green port development. As a guide, the government’s environmental regulation strategy can directly affect green port construction through market incentive or command control means and can also indirectly affect green port construction through the intermediary role of green innovation, industrial agglomeration and green logistics. Considering the strategic choices of the government, port enterprises and transportation enterprises, this paper constructs a tripartite evolutionary game model and considers whether the government carrying out environmental regulation is affected by the fine income and management cost, whether the willingness of port enterprises to carry out green port construction is determined by the extra construction cost and income and whether transportation enterprises choose green port logistics transportation depending on the extra income they receive. In the process of tripartite cooperation, the government’s environmental regulation, port enterprises’ green port construction and transportation enterprises’ choice of the green port logistics transportation mode constitute the most ideal strategy combination. Finally, the paper puts forward some suggestions for the strategy selection of the three parties in order to promote the realization of the ideal strategy combination and provide a theoretical reference for the construction of green ports.
Comparative Study of Optimal PV Array Configurations and MPPT under Partial Shading with Fast Dynamical Change of Hybrid Load
Authors: Boghdady Tarek A. , Kotb Yasmin E. , Aljumah Abdullah , Sayed Mahmoud M.
Published: March 2022

The characteristics of photovoltaic (PV) are directly affected by partial shading (PS) conditions due to the non-uniform irradiance. The PV system can be compromised based on the shading pattern as well as the shading area. Thus, the need for a solution that can deal with non-uniform irradiance has increased significantly. Consequently, this paper proposes a thorough analysis of the impact of PS patterns on different PV array configurations such as SP, TCT, and BL. The five optimization algorithms PSO, DA, MLS-SPA, IGWO, and BWO, were used to tune the variable step of the conventional P&O technique to extract the maximum power point. The proposed PV array is 4×4 with a fixed location, yet changing electrical connections. The main objective and novelty of this paper is to locate the Global Maximum Power Point (GMPP) of a PV array while the occurrence of different PSC with fast change of hybrid load e.g., (resistive and pump load). The results showed the superior performance of the IGWO algorithm regarding the maximum power tracking and disturbance rejection.
Position-Aware Guided Hiding Data Scheme with Reversibility and Adaptivity for Dual Images
Authors: Chang Chin-Chen , Su Guo-Dong , Lin Chia-Chen , Li Yung-Hui
Published: March 2022

Reversible data hiding (RDH) in dual images is a technique that shares secret messages into two similar shadow images, while the secret messages and the cover image can be restored only when those two shadows are gathered simultaneously. In this paper, a novel turtle shell-based RDH hiding scheme based on the symmetric property is presented in order to increase the embedding capacity and maintain good visual quality in dual images under the guidance of position-aware. First, we classify each pixel pair into one of four types according to their locations and then determine a sunflower area centered around it in order to construct the combination of positions and the embedding table. Using the embedding table, the secret messages are concealed into a cover image by generating two shadow images. At the decoder’s side, the complete restoration of the secret messages and the cover image can be accomplished by identifying the position relationship between the two stego-pixel pairs. The experimental results confirmed that the proposed position-aware guided RDH scheme is superior to some of the relevant works on the aspects of embedding capacity or image quality. In addition, the proposed scheme provides a secure communication that can effectively resist attacks on the pixel value difference histogram, relative entropy, and regular singular analysis.
Least-Squares Finite Element Method for Solving Stokes Flow under Point Source Magnetic Field
Authors: Ayob Alia Rafiza Che , Ismail Zuhaila , Kasiman Erwan Hafizi
Published: March 2022

The least-squares finite element method (LSFEM) is successfully employed for the discretization of the Stokes equations and the numerical computation of the behaviour of two-dimensional Stokes flow in a straight rectangular channel under the effect of a point-source magnetic field. LSFEM has several advantages in terms of theory and computing, where it can always create a symmetric, positive-definite algebraic system of equations. It also allows for using an equal order shape function for both velocity and pressure, and it is not required to satisfy the Ladyzhenskaya–Babuška–Brezzi (LBB) condition. Despite this, LSFEM has an issue where low-order nodal expansions tend to lock. Thus, the present study proposes the discretization of the problem domain using higher-order nodes elements with full numerical integration. Results concerning velocity contour and streamlines pattern are shown. On the basis of current findings, it can be concluded that the LSFEM can be used to solve Stokes flow problem under the point source magnetic field.
Saporin as a Commercial Reagent: Its Uses and Unexpected Impacts in the Biological Sciences—Tools from the Plant Kingdom
Authors: Ancheta Leonardo R. , Shramm Patrick A. , Bouajram Raschel , Higgins Denise , Lappi Douglas A.
Published: March 2022

Saporin is a ribosome-inactivating protein that can cause inhibition of protein synthesis and causes cell death when delivered inside a cell. Development of commercial Saporin results in a technology termed ‘molecular surgery’, with Saporin as the scalpel. Its low toxicity (it has no efficient method of cell entry) and sturdy structure make Saporin a safe and simple molecule for many purposes. The most popular applications use experimental molecules that deliver Saporin via an add-on targeting molecule. These add-ons come in several forms: peptides, protein ligands, antibodies, even DNA fragments that mimic cell-binding ligands. Cells that do not express the targeted cell surface marker will not be affected. This review will highlight some newer efforts and discuss significant and unexpected impacts on science that molecular surgery has yielded over the last almost four decades. There are remarkable changes in fields such as the Neurosciences with models for Alzheimer’s Disease and epilepsy, and game-changing effects in the study of pain and itch. Many other uses are also discussed to record the wide-reaching impact of Saporin in research and drug development.
Alternative Hapten Design for Zearalenone Immunoreagent Generation
Authors: Abad-Fuentes Antonio , Agulló Consuelo , López-Puertollano Daniel , Navarro-Fuertes Ismael , Abad-Somovilla Antonio , Mercader Josep Vicent
Published: March 2022

Appropriate hapten design and synthesis have been identified as critical steps to generate high-performance immunoreagents and to develop sensitive and selective immunoanalytical methods. Antibodies and immunoassays for the major mycotoxin zearalenone have been reported and marketed. However, zearalenone haptens have mostly been prepared by the oxime active ester technique, and hapten characterization has generally been poor or non-existent. In the present study, novel haptens of zearalenone with longer linkers and with alternative tethering sites have been designed for immunizing and assay conjugate preparation. All of these molecules were purified and spectroscopically verified, and a structure-activity relationship evaluation was carried out. This approach revealed that the hapten with the linker at the carbonyl group generated antibodies with a higher affinity than the hapten functionalized at the phenyl moiety. Antibodies produced with the latter hapten, on the other hand, showed lower cross-reactivity values to the major zearalenone metabolites. Finally, similar immunoassay sensitivity was achieved with all of the antibodies when heterologous haptens were employed. Furthermore, by altering the structure of the competing antigen, the immunoassay selectivity was modified. These results demonstrate that immunochemical methods for zearalenone rapid analysis can still be improved in terms of sensitivity and selectivity.
Previous Infection with SARS-CoV-2 Correlates with Increased Protective Humoral Responses after a Single Dose of an Inactivated COVID-19 Vaccine
Authors: Bagno Flávia F. , Andrade Luis A. F. , Sérgio Sarah A. R. , Parise Pierina L. , Toledo-Teixeira Daniel A. , Gazzinelli Ricardo T. , Fernandes Ana P. S. M. , Teixeira Santuza M. R. , Granja Fabiana , Proença-Módena José L. , da Fonseca Flavio G.
Published: March 2022

Previous studies have indicated that antibody responses can be robustly induced after the vaccination in individuals previously infected by SARS-CoV-2. To evaluate anti-SARS-CoV-2 humoral responses in vaccinated individuals with or without a previous history of COVID-19, we compared levels of anti-SARS-CoV-2 antibodies in the sera from 21 vaccinees, including COVID-19-recovered or -naïve individuals in different times, before and after immunization with an inactivated COVID-19 vaccine. Anti-SARS-CoV-2-specific antibodies elicited after COVID-19 and/or immunization with an inactivated vaccine were measured by ELISA and Plaque Reduction Neutralizing assays. Antibody kinetics were consistently different between the two vaccine doses for naïve individuals, contrasting with the SARS-CoV-2-recovered subjects in which we observed no additional increase in antibody levels following the second dose. Sera from SARS-CoV2-naïve individuals had no detectable neutralizing activity against lineage B.1 SARS-CoV-2 or Gamma variant five months after the second vaccine dose. Contrarily, SARS-CoV-2-recovered subjects retained considerable neutralizing activity against both viruses. We conclude that a single inactivated SARS-CoV-2 vaccine dose may be sufficient to induce protective antibody responses in individuals with previous history of SARS-CoV-2 infection.
Acute Vascular Response of Hand to Force and Vibration
Authors: Gao Shuxiang , Ye Ying
Published: March 2022

This study aimed to investigate the acute effect of grip and feed exertions on the vascular system at the fingers during exposure to hand-arm vibration (HAV), and to identify which active hand force situation would have the most effect on finger vascular function. A total of 12 individuals attended the test, and each of them were subjected to eight sets of force-and-vibration situations: four with combinations of forces and vibration, and four control ones with only hand forces applied. The vibration stimulus was applied on the right hand at 2.75 m/s2 with a frequency of 125 Hz for three minutes, during which the application of grip and feed forces were set at either 10 N or 50 N. The weakening of the finger vascular function was reflected by a reduction in the finger blood flow (FBF) and finger skin temperature (FST). They were tested on both hands at fixed intervals before, during and after the exposure for in-time measurement. Hand forces resulted in clear reductions in FBF and FST in exposed right fingers whether the force was exerted solely or combined with vibration. The greater the hand force (especially grip force), the stronger the vascular response, while the additional reductions in FBF and FST from vibration were not significant. In the non-exposed left fingers, no significant changes in finger circulation occurred in response to force or vibration. Generally, vibration-induced acute finger vasoconstriction was affected by the hand forces, in which hand force seemed to play a more important part than vibration. A larger grip force would lead to a greater loss in the digital circulation than feed force. Thus, the level of hand force exerted on the tool handle should be limited to reduce the risk of harm from HAV.
Risk-Based Evaluation of Improvements in Drinking Water Treatment Using Cost-Benefit Analysis
Authors: Sköld Nils-Petter , Bergion Viktor , Lindhe Andreas , Keucken Alexander , Rosén Lars
Published: March 2022

Reliable and safe drinking water supply requires adequate risk management. Decision support models can aid decisionmakers to effectively evaluate risk mitigation measures and allocate societal resources. Here, a Swedish case study illustrates how the installation of ultrafiltration membranes can be evaluated by combining risk assessment and cost-benefit analysis. Quantitative microbial risk assessment was used to assess several contamination sources and estimate the achieved risk reduction from waterborne pathogens using Campylobacter, Norovirus, and Cryptosporidium as reference pathogens. The societal value of the improved water quality was estimated in the cost-benefit analysis by monetising the gained quality adjusted life years and aesthetic water quality improvements. The calculated net present value (mean of 7 MEUR) indicated that the installation of the ultrafiltration membranes was a sound investment from a societal economic perspective. The ultrafiltration membranes reduced the annual probability of infection from 3 × 10−2 to 10−7, well below the U.S. EPA’s acceptable level, as well as improving the aesthetic quality of the drinking water. The results provide a novel example of the importance for water distributors to consider not only health-related metrics when evaluating treatment options or monitoring the drinking water quality, but to also consider the aesthetic quality of the drinking water.
Impact of Large Wood on River Ecosystems
Authors: Schalko Isabella , Weitbrecht Volker
Published: March 2022

Large wood (LW) can be defined as logs with a length of ≥1 m and a diameter of ≥0 [...]
The Partitioning of Catchment Evapotranspiration Fluxes as Revealed by Stable Isotope Signals in the Alpine Inland River Basin
Authors: Wang Zhigang , Cao Shengkui , Cao Guangchao , Hou Yaofang , Wang Youcai , Kang Ligang
Published: March 2022

Evapotranspiration is an important process in the water budget of an ecosystem. Quantifying the components of evapotranspiration is of great significance in revealing the ecohydrological process of alpine inland river basins. In this study, the evapotranspiration fluxes in the Shaliu River basin were classified by hydrogen and oxygen stable isotope technology and remote sensing technology. The results showed the following: (1) The average value of soil fractional evaporation (E1) in the summer of 2018 and 2019 was 7.59 mm and 2.10 mm, respectively. (2) The average ratio of soil evaporation (Esoil) in the summer of 2018 was 48.82%, 68.11%, 54.99%, respectively. The average ratio of Esoil in the summer of 2019 was 66.86%, 57.50%, 55.53%, respectively. The average value of Esoil in the summer of 2018 and 2019 was 42.84 mm and 35.36 mm, respectively. (3) The average ratio of vegetation transpiration (T) in the summer of 2018 was 51.18%, 31.89%, and 45.01%, respectively. The average ratio of T in the summer of 2019 was 33.14%, 42.50%, and 44.47%, respectively. The average value of T in the summer of 2018 and 2019 was 32.59 mm and 26.23 mm, respectively. Obviously, the soil fractionation was stronger in the summer of 2018 than that in the summer of 2019. At the same time, both soil evaporation and plant transpiration in summer 2018 were higher than those in summer 2019, and soil evaporation in the Shaliu River basin was greater than plant transpiration in summer during the study period. The results of this study can provide data reference for mastering the eco-hydrological process of the Shaliu River basin.
The Impact of Wastewater Quality and Flow Characteristics on H2S Emissions Generation: Statistical Correlations and an Artificial Neural Network Model
Authors: Sherief Mohsina , Aly Hassan Ashraf
Published: March 2022

Hydrogen sulfide (H2S) is a naturally occurring, highly toxic gas that is formed from the decomposition of sulfur compounds. H2S is a common source of concrete and metal corrosion that results in huge economic losses in wastewater collection and treatment plants. Hence, it is necessary to analyze H2S generation and emission. H2S concentrations were measured at the Al-Saad wastewater treatment plant in the United Arab Emirates. Wastewater samples were collected, and water quality parameters were characterized in the laboratory. Simultaneously, flow characteristics, humidity, headspace airflow, and temperature were measured onsite. A neural network model to predict H2S emissions was formulated using significant parameters. It was observed that flowrate, velocity, sulfate, and total sulfur had a similar cyclic pattern throughout the sampling events. The temperature, humidity, total sulfur, and depth of wastewater were identified as the most important parameters influencing H2S emissions through correlation analysis. The neural model validation and testing had an R value of 0.9. The training had an R value of 0.8. The model provided an accuracy of 80% for the prediction of H2S concentration in wastewater treatment plants. The accuracy can be improved by increasing the data. The model is limited to its applicability in the prediction of H2S emissions under conditions similar to the inlet of a wastewater treatment plant.