bluuebunny/crossref_metadata_2025 huggingface dataset:
Food Powder Flow in Extrusion: Role of Particle Size and Composition
Authors: McGuire Cameron , Siliveru Kaliramesh , Ambrose Kingsly , Alavi Sajid
Published: January 2022

Innovations in food extrusion technology are enabling its rapid expansion and applicability in diverse areas related to bioprocessing and value addition. This study relates raw material particulate rheology to the granular flow in a single screw food extruder. Raw materials based on corn (i.e., meal, flour, and starch), wheat (i.e., farina, flour, and starch), and sucrose (i.e., granulated, superfine, and powdered) were used as model particulate systems for the study. Various particulate-scale characteristics and flow parameters of these nine materials were determined using a powder rheometer, a promising new offline tool. Properties such as basic flow energy, specific energy, cohesion, stability index, flow function, and effective angle of internal friction were good indicators of flowability in an extruder. Corn meal exhibited lower energy requirements and a higher propensity for flow than corn flour (6.7 mJ/g versus 10.7 mJ/g, and “free-flowing” versus “cohesive,” according to Flow Function classifications), with wheat farina showing similar results when compared to wheat flour (5.8 mJ/g versus 7.9 mJ/g, and “highly free-flowing versus “cohesive,” according to Flow Function classifications), although both wheat systems showed comparatively lower energy requirements than their comparable corn systems. Sugar, being of a different base material and particle shape, behaved differently than these starch-based materials—flow energy decreased and propensity to flow increased (51.7 mJ/g versus 8.0 mJ/g, and “free-flowing” versus “highly free-flowing”). This large energy requirement for coarse sugar particles may be attributed more to particle shape than composition, as the sharp edges of sugar can interlock and increase restriction to movement through the sample. The starch-based results were validated in a particulate flow study involving the above model systems (corn meal, corn flour, wheat farina, and wheat flour) in a pilot-scale single screw extruder. Visualization data, obtained using a transparent plexiglass window during extrusion, confirmed that the flours exhibited higher flow energy requirements and a lower flow factor when compared to the coarser-particle size corn meal during extrusion, seen by the increased peak heights and barrel fill.
Mapping Research on Microbial Fuel Cells in Wastewater Treatment: A Co-Citation Analysis
Authors: Chen Tianming , Zou Chao , Pan Jingjing , Wang Mansi , Qiao Liang , Wang Feihong , Zhao Qi , Cheng Haoyi , Ding Cheng , Yuan Ye
Published: January 2022

Microbial fuel cells (MFCs) are promising technologies, aiming at treating different types of industrial and domestic wastewater. In recent years, more and more publications focusing on wastewater treatment have been published. Based on the retrieval of publications from Web of Science Core Collection database, the new emerging trends of microbial fuel cells in wastewater treatment was evaluated with a scientometric analysis method from 1995 to 2020. All publications downloaded from (WOS) were screened by inclusion criteria, and 2233 publications were obtained for further analysis. Document co-citation and burst detection of MFCs in wastewater treatment were analyzed and visualized by software of CiteSpace. Our study indicated that “Environmental Science” is the most popular discipline, while the journal of Bioresource Technology published the greatest quantity of articles in the field of MFCs applied wastewater treatment. China and the Chinese Academy of Science are the most productive country and institution, respectively. “Azo dye” has become the new research topic, which indicates the application area and the development of MFCs. The performance of MFCs for wastewater treatment has been widely discussed. The findings of this study may ameliorate the researcher in seizing the frontier of MFCs in wastewater treatment.
Multimodal Generic Trends of Harvard Business Review Knowledge Communication in and beyond Social Media Context: Exploiting Affordances, Neglecting Opportunities
Authors: Engberg Jan , Maier Carmen Daniela
Published: January 2022

This article is part of an on-going research project dedicated to enhancing our understanding of domain-specific knowledge communication across various multiliterate communities, semiotic modes and media contexts. The focus of the present analytical endeavour is on the dissemination of knowledge of academics from the domain of business and management to professionals and other non-academic communicative partners in the context of the Harvard Business Review journal. The central empirical material is constituted by a cluster of videos selected from the Facebook context of the journal whose intention is to function as a bridge between academia and enterprises. For this bridging effort, a number of video genres which are not traditionally used for scientific knowledge communication in academic contexts (e.g., Quick Study, Explainers, Tips & Ideas, etc.) are employed. Furthermore, in accordance with the Facebook context, the videos are accompanied by users’ commentaries that evaluate the knowledge provided or/and contribute to communicating and co-constructing new knowledge. Finally, we include the articles, books and special issues to which the videos refer in the empirical study. This hybrid knowledge-communication setting is studied from a multimodal perspective in order to address the new ways in which semiotic modes and sub-modes enter into a meaning-making interplay at the level of each video and when users comment on the respective videos. The main analytical tools are the concepts of knowledge expansion and knowledge enhancement that characterize the interaction of modes in the knowledge-building process. Across the video genres that have been investigated, we see a tendency towards engaging users of the videos through diminishing the distance to the viewers. As a consequence, the videos have a high number of views, but at the same time there are few comments and hardly any comments engaging in mutual knowledge building. This paradox is discussed in more detail in the concluding section.
The Potential of Omics in Biological Dosimetry
Authors: Hladik Daniela , Bucher Martin , Endesfelder David , Oestreicher Ursula
Published: January 2022

Biological dosimetry is an internationally recognized method for quantifying and estimating radiation dose following suspected or verified excessive exposure to ionising radiation. In severe radiation accidents where a large number of people are potentially affected, it is possible to distinguish irradiated from non-irradiated people in order to initiate appropriate medical care if necessary. In addition to severe incidents caused by technical failure, environmental disasters, military actions, or criminal abuse, there are also radiation accidents in which only one or a few individuals are affected in the frame of occupational or medical exposure. The requirements for biological dosimetry are fundamentally different for these two scenarios. In particular, for large-scale radiation accidents, pre-screening methods are necessary to increase the throughput of samples for a rough first-dose categorization. The rapid development and increasing use of omics methods in research as well as in individual applications provides new opportunities for biological dosimetry. In addition to the discovery and search for new biomarkers, dosimetry assays based on omics technologies are becoming increasingly interesting and hold great potential, especially for large-scale dosimetry. In the following review, the different areas of biological dosimetry, the problems in finding suitable biomarkers, the current status of biomarker research based on omics, the potential applications of assays using omics technologies, and also the limitations for the different areas of biological dosimetry are discussed.
Editorial for Special Issue “Hydrogen Production and Storage”
Authors: Meille Valérie , Gandía Luis M. , Kawi Sibudjing , Frusteri Francesco
Published: January 2022

Hydrogen appears as an unavoidable energy vector and an almost miracle solution to global warming for many people [...]
Leaf Area Index Estimation of Pergola-Trained Vineyards in Arid Regions Based on UAV RGB and Multispectral Data Using Machine Learning Methods
Authors: Ilniyaz Osman , Kurban Alishir , Du Qingyun
Published: January 2022

The leaf area index (LAI), a valuable variable for assessing vine vigor, reflects nutrient concentrations in vineyards and assists in precise management, including fertilization, improving yield, quality, and vineyard uniformity. Although some vegetation indices (VIs) have been successfully used to assess LAI variations, they are unsuitable for vineyards of different types and structures. By calibrating the light extinction coefficient of a digital photography algorithm for proximal LAI measurements, this study aimed to develop VI-LAI models for pergola-trained vineyards based on high-resolution RGB and multispectral images captured by an unmanned aerial vehicle (UAV). The models were developed by comparing five machine learning (ML) methods, and a robust ensemble model was proposed using the five models as base learners. The results showed that the ensemble model outperformed the base models. The highest R2 and lowest RMSE values that were obtained using the best combination of VIs with multispectral data were 0.899 and 0.434, respectively; those obtained using the RGB data were 0.825 and 0.547, respectively. By improving the results by feature selection, ML methods performed better with multispectral data than with RGB images, and better with higher spatial resolution data than with lower resolution data. LAI variations can be monitored efficiently and accurately for large areas of pergola-trained vineyards using this framework.
Anodically Bonded Photoacoustic Transducer: An Approach towards Wafer-Level Optical Gas Sensors
Authors: Gassner Simon , Schaller Rainer , Eberl Matthias , von Koblinski Carsten , Essing Simon , Ghaderi Mohammadamir , Schmitt Katrin , Wöllenstein Jürgen
Published: January 2022

We present a concept for a wafer-level manufactured photoacoustic transducer, suitable to be used in consumer-grade gas sensors. The transducer consists of an anodically bonded two-layer stack of a blank silicon wafer and an 11 µm membrane, which was wet-etched from a borosilicate wafer. The membrane separates two cavities; one of which was hermetically sealed and filled with CO2 during the anodic bonding and acts as an infrared absorber. The second cavity was designed to be connected to a standard MEMS microphone on PCB-level forming an infrared-sensitive photoacoustic detector. CO2 sensors consisting of the detector and a MEMS infrared emitter were built up and characterized towards their sensitivity and noise levels at six different component distance ranging from 3.0 mm to 15.5 mm. The signal response for the sample with the longest absorption path ranged from a decrease of 8.3% at a CO2 concentration of 9400 ppm to a decrease of 0.8% at a concentration of 560 ppm. A standard deviation of the measured values of 18 ppm was determined when the sensor was exposed to 1000 ppm CO2.
How Does C-V2X Help Autonomous Driving to Avoid Accidents?
Authors: Miao Lili , Chen Shang-Fu , Hsu Yu-Ling , Hua Kai-Lung
Published: January 2022

Accidents are continuously reported for autonomous driving vehicles including those with advanced sensors installed. Some of accidents are usually caused by bad weather, poor lighting conditions and non-line-of-sight obstacles. Cellular Vehicle-to-Everything (C-V2X) radio technology can significantly improve those weak spots for autonomous driving. This paper describes one of the C-V2X system solutions: Vulnerable Road User Collision Warning (VRUCW) for autonomous driving. The paper provides the system architecture, design logic, network topology, message flow, artificial intelligence (AI) and network security feature. As a reference it also includes a commercial project with its test results.
Heart Rate Measurement Based on 3D Central Difference Convolution with Attention Mechanism
Authors: Liu Xinhua , Wei Wenqian , Kuang Hailan , Ma Xiaolin
Published: January 2022

Remote photoplethysmography (rPPG) is a video-based non-contact heart rate measurement technology. It is a fact that most existing rPPG methods fail to deal with the spatiotemporal features of the video, which is significant for the extraction of the rPPG signal. In this paper, we propose a 3D central difference convolutional network (CDCA-rPPGNet) to measure heart rate, with an attention mechanism to combine spatial and temporal features. First, we crop and stitch the region of interest together through facial landmarks. Next, the high-quality regions of interest are fed to CDCA-rPPGNet based on a central difference convolution, which can enhance the spatiotemporal representation and capture rich relevant time contexts by collecting time difference information. In addition, we integrate the attention module into the neural network, aiming to strengthen the ability of the neural network to extract video channels and spatial features, so as to obtain more accurate rPPG signals. In summary, the three main contributions of this paper are as follows: (1) the proposed network base on central difference convolution could better capture the subtle color changes to recover the rPPG signals; (2) the proposed ROI extraction method provides high-quality input to the network; (3) the attention module is used to strengthen the ability of the network to extract features. Extensive experiments are conducted on two public datasets—the PURE dataset and the UBFC-rPPG dataset. In terms of the experiment results, our proposed method achieves 0.46 MAE (bpm), 0.90 RMSE (bpm) and 0.99 R value of Pearson’s correlation coefficient on the PURE dataset, and 0.60 MAE (bpm), 1.38 RMSE (bpm) and 0.99 R value of Pearson’s correlation coefficient on the UBFC dataset, which proves the effectiveness of our proposed approach.
Hybrid-Pattern Recognition Modeling with Arrhythmia Signal Processing for Ubiquitous Health Management
Authors: Hsiao Wei-Ting , Kan Yao-Chiang , Kuo Chin-Chi , Kuo Yu-Chieh , Chai Sin-Kuo , Lin Hsueh-Chun
Published: January 2022

We established a web-based ubiquitous health management (UHM) system, “ECG4UHM”, for processing ECG signals with AI-enabled models to recognize hybrid arrhythmia patterns, including atrial premature atrial complex (APC), atrial fibrillation (AFib), ventricular premature complex (VPC), and ventricular tachycardia (VT), versus normal sinus rhythm (NSR). The analytical model coupled machine learning methods, such as multiple layer perceptron (MLP), random forest (RF), support vector machine (SVM), and naive Bayes (NB), to process the hybrid patterns of four arrhythmia symptoms for AI computation. The data pre-processing used Hilbert–Huang transform (HHT) with empirical mode decomposition to calculate ECGs’ intrinsic mode functions (IMFs). The area centroids of the IMFs’ marginal Hilbert spectrum were suggested as the HHT-based features. We engaged the MATLABTM compiler and runtime server in the ECG4UHM to build the recognition modules for driving AI computation to identify the arrhythmia symptoms. The modeling extracted the crucial data sets from the MIT-BIH arrhythmia open database. The validated models, including the premature pattern (i.e., APC–VPC) and the fibril-rapid pattern (i.e., AFib–VT) against NSR, could reach the best area under the curve (AUC) of the receiver operating characteristic (ROC) of approximately 0.99. The models for all hybrid patterns, without VPC versus AFib and VT, achieved an average accuracy of approximately 90%. With the prediction test, the respective AUCs of the NSR and APC versus the AFib, VPC, and VT were 0.94 and 0.93 for the RF and SVM on average. The average accuracy and the AUC of the MLP, RF, and SVM models for APC–VT reached the value of 0.98. The self-developed system with AI computation modeling can be the backend of the intelligent social-health system that can recognize hybrid arrhythmia patterns in the UHM and home-isolated cares.
Towards LoRaWAN without Data Loss: Studying the Performance of Different Channel Access Approaches
Authors: Loh Frank , Mehling Noah , Hoßfeld Tobias
Published: January 2022

The Long Range Wide Area Network (LoRaWAN) is one of the fastest growing Internet of Things (IoT) access protocols. It operates in the license free 868 MHz band and gives everyone the possibility to create their own small sensor networks. The drawback of this technology is often unscheduled or random channel access, which leads to message collisions and potential data loss. For that reason, recent literature studies alternative approaches for LoRaWAN channel access. In this work, state-of-the-art random channel access is compared with alternative approaches from the literature by means of collision probability. Furthermore, a time scheduled channel access methodology is presented to completely avoid collisions in LoRaWAN. For this approach, an exhaustive simulation study was conducted and the performance was evaluated with random access cross-traffic. In a general theoretical analysis the limits of the time scheduled approach are discussed to comply with duty cycle regulations in LoRaWAN.
Sea-Surface Target Visual Tracking with a Multi-Camera Cooperation Approach
Authors: Rao Jinjun , Xu Kai , Chen Jinbo , Lei Jingtao , Zhang Zhen , Zhang Qiuyu , Giernacki Wojciech , Liu Mei
Published: January 2022

Cameras are widely used in the detection and tracking of moving targets. Compared to target visual tracking using a single camera, cooperative tracking based on multiple cameras has advantages including wider visual field, higher tracking reliability, higher precision of target positioning and higher possibility of multiple-target visual tracking. With vast ocean and sea surfaces, it is a challenge using multiple cameras to work together to achieve specific target tracking and detection, and it will have a wide range of application prospects. According to the characteristics of sea-surface moving targets and visual images, this study proposed and designed a sea-surface moving-target visual detection and tracking system with a multi-camera cooperation approach. In the system, the technologies of moving target detection, tracking, and matching are studied, and the strategy to coordinate multi-camera cooperation is proposed. The comprehensive experiments of cooperative sea-surface moving-target visual tracking show that the method used in this study has improved performance compared with contrapositive methods, and the proposed system can meet the needs of multi-camera cooperative visual tracking of moving targets on the sea surface.
Competition within Cross-Functional Teams: A Structural Equation Model on Knowledge Hiding
Authors: Ton Anh Don , Szabó-Szentgróti Gábor , Hammerl Laszlo
Published: January 2022

The modern challenges of business success make the use of interdisciplinary cross-functional teamwork necessary to tackle social and economic issues alike. The study examines the role of knowledge hiding in within-team coopetition, taking into account its subsequent factors influencing team efficiency. For the investigation, a self-made model was applied that associates the personality of individuals, their role inside the organization and work-environmental aspects with the individual’s behavior as the antecedent of within-team competition. The objective of this study revolves around the question of which factors apply to the efficiency of cross-functional teams. The modern concept of interdisciplinary coopetition faces more difficulties than traditional teams regarding voluntary adoption in new environments. The model was empirically applied to a dataset of 129 participants working in cross-functional teams. Three hypotheses were drafted and statistically evaluated. The factor of knowledge hiding was evaluated as one of the crucial factors blocking the efficiency of team-based work, based on the results from the literature review. This was further fueled by antagonistic behavior and a competitive supervisor. The empirical findings further elaborate that individuals with a competitive supervisor tend to be more antagonistic and competitive themselves. Equally, a highly developed personality trait of antagonism correlates positively with knowledge hiding, thereby resulting in the limiting of team performance. Surprisingly, competitiveness among individuals is negatively correlated with knowledge hiding, indicating that different personality traits and different real-life situations react drastically differently towards competitive environments. The results close the research gap of a strategic necessity for supervisors and managers designing business organizations alike, namely, that an individually adapted and situationally aware leadership is indispensable for a successful cross-functional team approach, even more than in traditional team compositions. As for now, only the effects on personality in educational environments were discussed in previous research.
The Status Quo and Prospect of Sustainable Development of Smart Clothing
Authors: Li Qing , Xue Zhebin , Wu Yuhan , Zeng Xianyi
Published: January 2022

With the booming development of the Internet and AI (Artificial Intelligence), smart clothing has emerged to meet consumers’ personalized needs in healthcare, work, entertainment, etc., and has rapidly become a hotspot in the clothing industry and research field. However, as smart clothing gets popular, sustainability issues are becoming increasingly prominent during its development and circulation. To explore the status quo of the sustainable development of smart clothing, from the perspective of the industry chain, this paper discusses its challenges during raw material supply, design, manufacturing, storage, logistics and recycling. Based on these challenges and the characteristics of smart clothing and the future trend of the apparel industry, some countermeasures are put forward from three aspects: design, raw material and supply chain management. This review aims to arouse the reflection of practitioners and provide feasible suggestions for the healthy and lasting development of the apparel industry, also hoping to offer references for other industries.
The Influence of Small-Sided Football Games with Numerical Variability in External Training Load
Authors: Sousa Honorato , Gouveia Élvio Rúbio , Marques Adilson , Sarmento Hugo , Pestana Marcelo , Quintal Tomás , Lopes Helder , Ihle Andreas
Published: January 2022

Small-sided games (SSGs) are a motivational strategy and effective training method to develop skills and physical fitness at optimal intensity. This study investigates the influence of variability in the number of players on the physiological response using SSGs. The sample was composed of 10 field players with an average age of 15.9 ± 0.50 years old. Three sessions were held on 3 different days to collect information. The 10 min SSG exercise with temporal numerical variability was repeated twice on each day. The numerical ratio of players involved changed every 2 min without disrupting the practice. In a game space with 35 × 25 m, the exercise always started in a situation of 3 vs. 3. External training load metrics (i.e., physical activity counts, activity intensity, and energy expenditure) were assessed using Actigraph WGT3X accelerometers. The 3 vs. 3 format game had higher physical activity counts (i.e., higher vector magnitude) and requested more time spent in very vigorous physical activity intensity. Consequently, the 3 vs. 3 format in young football players had higher energy expenditure (i.e., a higher METs) than that in the other studied game formats. This study confirms the influence of SSGs with numerical variability in external training load.
Transition of Socio-Demographic Characteristics in Urban Areas by Applying a Topic Model to Small Area Units
Authors: Tsukai Makoto , Ohno Satoko , Tsukano Yuta
Published: January 2022

Under the depopulation society in Japan, the hollowing out and suburbanization of urban areas have become very serious problems, but an appropriate analytical tool for land use transition has not yet been proposed. This study analyzes the transitions in socio-demographic characteristics of small area units in the Fukuoka and Kitakyushu metropolitan areas by applying a topic model to geographical data. Plotting the topic shares on a map clarified the spatial distribution of topics, and the transitions between two cross-sections were analyzed along with other geographical characteristics. Our empirical study showed that the topic model could clearly and quantitatively describe the transitions between two cross-sections of these urban areas. The topic model revealed that the urban center of the Fukuoka metropolitan area was expanding, while the urban center of the Kitakyushu metropolitan area was shrinking. In suburban areas, both metropolitan areas had increasing low-density residential and commercial land use. In the Kitakyushu metropolitan area, this transition could seriously threaten the sustainability of land use, since the total population had significantly decreased.
Rice Husk Ash Incorporation in Calcium Aluminate Cement Concrete: Life Cycle Assessment, Hydration and Strength Development
Authors: Abolhasani Amirmohamad , Samali Bijan , Aslani Fatemeh
Published: January 2022

In this research effect of rice husk ash (RHA), as silicate impurities, on the hydration reaction and mechanical strength of calcium aluminate cement (CAC) concrete, as one of the most important non-Portland cements, was investigated. Furthermore, in order to evaluate the environmental performance of mixtures, a lifecycle assessment was performed using the recipe midpoint and endpoint method. Compressive and tensile strength tests were conducted at the ages of 7, 28, and 90 days on specimens containing different contents of RHA (0, 2.5, 5, 7.5, and 10%) substituting for cement at the water-cement ratio of 0.4. Moreover, in order to calculate the hydration reaction of the specimens, thermogravimetric analysis (TGA) was performed at a rate of 10 °C/min to up to 1000 °C. The results revealed that the use of rice husk ash as a partial replacement at a concentration of 5% could reduce CO2 emission and ozone depletion by 18.75% and 31%, respectively. The findings indicate that, at 90 days, the mechanical strength of the mixes containing RHA were higher than those of the control mix, with the maximum improvement occurring at the substitution percentage of 5%. In accordance with TGA analysis the substitution of 5% RHA in CAC concrete led to a higher hydration level, which in turn improved the mechanical properties relative to the specimen without RHA at 90 days.
Grid Connection Studies for Large-Scale Offshore Wind Farms Considering High Penetration of Regional Renewables
Authors: Choi Namki , Kim Beomju , Kim Dohyuk , Park Bohyun , Kim Sangsoo , Lee Byongjun
Published: January 2022

There is a global focus on adding renewable energy sources to the mix of energy supplies. In this study, the grid connections for large-scale offshore wind farms in areas that have high penetration of renewable energy sources were examined. System strength evaluation considering the interaction of wind farms and inverter-based resources (IBRs) was performed; the fault current was then analyzed to determine their contribution to the total fault current at a bus level. These studies revealed that the interaction between offshore wind farms and IBRs may make the power system weaker, and it is possible that fault current contributions from offshore wind farms can violate the capacity limit of existing circuit breakers. The results of steady-state analysis were verified through case studies focused on the southwest area of the Korea Electric Power Corporation (KEPCO) system where large-scale offshore wind farms are planned to be established and connected. Power system planners will benefit from the results of this study with a better understanding of the factors to consider when integrating large-scale wind farms in areas with high penetration of renewables.
Worker Involvement and Performance in Italian Social Enterprises: The Role of Motivations, Gender and Workload
Authors: Tortia Ermanno C. , Gago Mónica , Degavre Florence , Poledrini Simone
Published: January 2022

Over the past two decades, organizational sustainability has been studied from several different perspectives, such as marketing, governance, strategy, and human resource management (HRM). However, sustainability framed in HRM has not yet received enough attention in the literature, especially as it concerns the study of different organizational forms. Building on Enhert and Harry’s (2012) sustainable HRM approach, this article studies worker empowerment and how it affects organizational performance in terms of service quality and service innovation. Specifically, it addresses how relational motivations interact with HR-empowering practices (involvement in decisions and task autonomy) as organizational resources in influencing performance, how workload pressure resulting from HR empowerment can improve performance, and the influence of gender on performance, especially with concerns for human capital (tertiary education) and motivations. To this end, a representative sample of workers employed by Italian social enterprises (ES) in the social service sector is used. We propose multilevel SEMs that are based on two sets of equations specifying worker- and organization-level effects on organizational performance. Our main results show that the combination of worker engagement and an appropriate relational context in the organizational environment is most conducive to delivering better and innovative services. In addition, a higher percentage of well-trained and relationally motivated women employees helps achieve this goal.
Investigation of the Presence Volatile Organic Compounds (BTEX) in the Ambient Air and Biogases Produced by a Shiraz Landfill in Southern Iran
Authors: Khademi Fahimeh , Samaei Mohammad Reza , Shahsavani Abbas , Azizi Kourosh , Mohammadpour Amin , Derakhshan Zahra , Giannakis Stefanos , Rodriguez-Chueca Jorge , Bilal Muhammad
Published: January 2022

The generation and emission of volatile organic compounds (VOCs) affects the environment and air quality, playing an important role in global warming, depletion of atmospheric ozone and emission of unpleasant odors, but also directly affect human health. This study investigated the health risks of benzene, toluene, ethylbenzene, xylene (BTEX) compounds and biogas released in and around the municipal landfill. Sampling of the VOCs was carried out by the 1501NIOSH method from 8 points over 5 months. The samples were analyzed for BTEX in the ambient air of the landfill, resulting in 0.03–18.09 ppm concentrations, while for biogases a 0.08–25.2 ppm range was found. Assessment of definite health and potential risks showed that the lifetime cancer risk (LCR) for benzene and hazard quotient (HQ) for the BTEX components in all studied sampling sites are higher than the acceptable standard. The high concentration of benzene measured in ambient air indicated that petroleum compounds containing benzene and its derivatives have the highest value in the category of BTEX compounds among all emissions. Therefore, high concentrations of volatile compounds derived from VOCs, especially benzene, should be reduced at the site with control engineering measures.
Sustainability of Vertical Farming in Comparison with Conventional Farming: A Case Study in Miyagi Prefecture, Japan, on Nitrogen and Phosphorus Footprint
Authors: Liu Jiarui , Oita Azusa , Hayashi Kentaro , Matsubae Kazuyo
Published: January 2022

The reduced requirement for nutrients in vertical farming (VF) implies that the potential for lower environmental impact is greater in VF than in conventional farming. In this study, the environmental impacts of VF were evaluated based on a case study of VF for vegetables in Miyagi Prefecture in Japan, where VF has been utilized in post-disaster relief operations in the wake of the 2011 Great East Japan Earthquake. The nitrogen (N) and phosphorus (P) footprints of these VFs were determined and analyzed to quantify the potential reduction in N and P emissions. First, the N and P footprints in conventional farming were calculated. Then, those footprints were compared with three different scenarios with different ratios for food imports, which equate to different levels of food self-sufficiency. The results show a decrease in the N and P footprints with increased prefectural self-sufficiency due to the introduction of VF. In addition to reducing the risks to food supply by reducing the dependence on imports and the environmental impacts of agriculture, further analysis reveals that VF is suitable for use in many scenarios around the world to reliably provide food to local communities. Its low vulnerability to natural disasters makes VF well suited to places most at risk from climate change anomalies.
Under-Canopy Regeneration of Scots Pine (Pinus sylvestris L.) as Adaptive Potential in Building a Diverse Stand Structure
Authors: Zawadzka Anna , Słupska Alicja
Published: January 2022

Under-canopy natural regeneration of Scots pine (Pinus sylvestris L.) stand is able to create stands with a complex structure, which are characterised by greater resistance to extreme phenomena related to climate change. The main aim of the work was to analyse the potential of pine undergrowth, its role in the stand, and its usefulness in further breeding plans to create stands of various structure, with greater stability and tolerance to stress factors, including greater resistance to climate change. The study was carried out in north-eastern Poland, in pine stands thinned by strong (hurricane level) wind in 2002. The study area covers 225.2 ha and is located in 29 stands. Naturally regenerated pine saplings with a minimum height of 0.5 m, characterised by a high density, growing under the upper cover of the stand, with varying degrees of thinning, were qualified for the study. On average 7.820 pine saplings were recorded in the area of one hectare. Over 65% of the examined saplings were determined to be of very good or good quality, prognostic for further development and the creation of the main stand in the future. The principle of increasing the structural diversity of stands is the method of increasing the adaptability of forests to environmental changes.
Image Encryption Based on Arnod Transform and Fractional Chaotic
Authors: Chen Chao , Zhang Hongying , Wu Bin
Published: January 2022

An image encryption and decryption algorithm based on Arnod transform and fractional chaos is proposed in this work for solving the problem that the encrypted image is easily cracked and the content of the decrypted image is distorted. To begin with, the Arnold transform is used to encrypt, so that the spatial confidence of the original image has been comprehensively disturbed. Secondly, the XOR involving the fractional order chaotic sequence is used to encrypt. The key sequence is dynamically generated to ensure the randomness and difference of key generation. When decryption is required, the first decryption is performed using the key and XOR. Then, the second decryption is carried out by using the inverse Arnold transform, and finally the decrypted image is obtained. Experimental results show that the improved algorithm has achieved a better performance in encryption and decryption.
Symmetry, Confinement, and the Higgs Phase
Authors: Greensite Jeff , Matsuyama Kazue
Published: January 2022

We show that the Higgs and confinement phases of a gauge Higgs theory, with the Higgs field in the fundamental representation of the gauge group, are distinguished both by a broken or unbroken realization of the global center subgroup of the gauge group, and by the type of confinement in each phase. This is color confinement in the Higgs phase, and a stronger property, which we call “separation-of-charge” confinement, in the confining phase.
Toxin and Immunotoxin Based Therapeutic Approaches
Authors: Bortolotti Massimo , Polito Letizia , Bolognesi Andrea
Published: January 2022

The concept of “magic bullets”, i [...]
TB Hackathon: Development and Comparison of Five Models to Predict Subnational Tuberculosis Prevalence in Pakistan
Authors: Alba Sandra , Rood Ente , Mecatti Fulvia , Ross Jennifer M. , Dodd Peter J. , Chang Stewart , Potgieter Matthys , Bertarelli Gaia , Henry Nathaniel J. , LeGrand Kate E. , Trouleau William , Shaweno Debebe , MacPherson Peter , Qin Zhi Zhen , Mergenthaler Christina , Giardina Federica , Augustijn Ellen-Wien , Baloch Aurangzaib Quadir , Latif Abdullah
Published: January 2022

Pakistan’s national tuberculosis control programme (NTP) is among the many programmes worldwide that value the importance of subnational tuberculosis (TB) burden estimates to support disease control efforts, but do not have reliable estimates. A hackathon was thus organised to solicit the development and comparison of several models for small area estimation of TB. The TB hackathon was launched in April 2019. Participating teams were requested to produce district-level estimates of bacteriologically positive TB prevalence among adults (over 15 years of age) for 2018. The NTP provided case-based data from their 2010–2011 TB prevalence survey, along with data relating to TB screening, testing and treatment for the period between 2010–2011 and 2018. Five teams submitted district-level TB prevalence estimates, methodological details and programming code. Although the geographical distribution of TB prevalence varied considerably across models, we identified several districts with consistently low notification-to-prevalence ratios. The hackathon highlighted the challenges of generating granular spatiotemporal TB prevalence forecasts based on a cross-sectional prevalence survey data and other data sources. Nevertheless, it provided a range of approaches to subnational disease modelling. The NTP’s use and plans for these outputs shows that, limitations notwithstanding, they can be valuable for programme planning.
Reduced Replication of Highly Pathogenic Avian Influenza Virus in Duck Endothelial Cells Compared to Chicken Endothelial Cells Is Associated with Stronger Antiviral Responses
Authors: de Bruin Anja , Spronken Monique , Bestebroer Theo , Fouchier Ron , Richard Mathilde
Published: January 2022

Highly pathogenic avian influenza viruses (HPAIVs) cause fatal systemic infections in chickens, which are associated with endotheliotropism. HPAIV infections in wild birds are generally milder and not endotheliotropic. Here, we aimed to elucidate the species-specific endotheliotropism of HPAIVs using primary chicken and duck aortic endothelial cells (chAEC and dAEC respectively). Viral replication kinetics and host responses were assessed in chAEC and dAEC upon inoculation with HPAIV H5N1 and compared to embryonic fibroblasts. Although dAEC were susceptible to HPAIV upon inoculation at high multiplicity of infection, HPAIV replicated to lower levels in dAEC than chAEC during multi-cycle replication. The susceptibility of duck embryonic endothelial cells to HPAIV was confirmed in embryos. Innate immune responses upon HPAIV inoculation differed between chAEC, dAEC, and embryonic fibroblasts. Expression of the pro-inflammatory cytokine IL8 increased in chicken cells but decreased in dAEC. Contrastingly, the induction of antiviral responses was stronger in dAEC than in chAEC, and chicken and duck fibroblasts. Taken together, these data demonstrate that although duck endothelial cells are permissive to HPAIV infection, they display markedly different innate immune responses than chAEC and embryonic fibroblasts. These differences may contribute to the species-dependent differences in endotheliotropism and consequently HPAIV pathogenesis.
Immune Enhancement by the Tetra-Peptide Hydrogel as a Promising Adjuvant for an H7N9 Vaccine against Highly Pathogenic H7N9 Virus
Authors: Wu Xiaoxin , Tang Songjia , Wang Zhehua , Ma Xiaoyun , Zhang Lingjian , Zhang Fen , Xiao Lanlan , Zhao Shuai , Li Qian , Wang Ying , Wang Qingjing , Chen Keda
Published: January 2022

Background: Short peptide hydrogel was reported as a possible adjuvant for vaccines. In order to evaluate whether the Tetra-Peptide Hydrogel can be a promising adjuvant for an H7N9 vaccine against the highly pathogenic H7N9 virus, we conducted this study. Methods: Tetra-Peptide Hydrogels (D and L conformations) were prepared by a self-assembly system using a Naproxen acid modified tetra peptide of GFFY (Npx-GFFY). Mice received two immunizations with the D-Tetra-Peptide Hydrogel adjuvant vaccine, the L-Tetra-Peptide Hydrogel adjuvant vaccine, or the split vaccine. Fourteen days following the second dose, the mice were challenged with the highly pathogenic A/Guangdong/GZ8H002/2017(H7N9) virus. The mice were observed for signs of illness, weight loss, pathological alterations of the lung tissues and immune responses in the following 2 weeks. Results: The D/L-Tetra-Peptide Hydrogels resembled long bars with hinges on each other, with a diameter of ~10 nm. The H7N9 vaccine was observed to adhere to the hydrogel. All the unvaccinated mice were dead by 8 days post infection with H7N9. The mice immunized by the split H7N9 vaccine were protected against infection with H7N9. Mice immunized by D/L-Tetra-Peptide Hydrogel adjuvant vaccines experienced shorter symptomatic periods and their micro-neutralization titers were higher than in the split H7N9 vaccine at 2 weeks post infection. The hemagglutinating inhibition (HI) titer in the L-Tetra-Peptide Hydrogel adjuvant vaccine group was higher than that in the split H7N9 vaccine 1 week and 2 weeks post infection. The HI titer in the D-Tetra-Peptide Hydrogel adjuvant vaccine group was higher than that in the split H7N9 vaccine at 2 weeks post infection. Conclusion: The D/L Tetra-Peptide Hydrogels increased the protection of the H7N9 vaccine and could be promising adjuvants for H7N9 vaccines against highly pathogenic H7N9 virus.
The Potential of Exosomes in Allergy Immunotherapy
Authors: Engeroff Paul , Vogel Monique
Published: January 2022

Allergic diseases represent a global health and economic burden of increasing significance. The lack of disease-modifying therapies besides specific allergen immunotherapy (AIT) which is not available for all types of allergies, necessitates the study of novel therapeutic approaches. Exosomes are small endosome-derived vesicles delivering cargo between cells and thus allowing inter-cellular communication. Since immune cells make use of exosomes to boost, deviate, or suppress immune responses, exosomes are intriguing candidates for immunotherapy. Here, we review the role of exosomes in allergic sensitization and inflammation, and we discuss the mechanisms by which exosomes could potentially be used in immunotherapeutic approaches for the treatment of allergic diseases. We propose the following approaches: (a) Mast cell-derived exosomes expressing IgE receptor FcεRI could absorb IgE and down-regulate systemic IgE levels. (b) Tolerogenic exosomes could suppress allergic immune responses via induction of regulatory T cells. (c) Exosomes could promote TH1-like responses towards an allergen. (d) Exosomes could modulate IgE-facilitated antigen presentation.
The Suitability of Hybrid Fe0/Aggregate Filtration Systems for Water Treatment
Authors: Tao Ran , Yang Huichen , Cui Xuesong , Xiao Minhui , Gatcha-Bandjun Nadège , Kenmogne-Tchidjo Joseline Flore , Lufingo Mesia , Konadu Amoah Bernard , Tepong-Tsindé Raoul , Ndé-Tchoupé Arnaud Igor , Touomo-Wouafo Marquise , Btatkeu-K Brice Donald , Gwenzi Willis , Hu Rui , Tchatchueng Jean Bosco , Ruppert Hans , Noubactep Chicgoua
Published: January 2022

Metallic iron (Fe0) corrosion under immersed conditions (Fe0/H2O system) has been used for water treatment for the past 170 years. Fe0 generates solid iron corrosion products (FeCPs) which are known to in situ coat the surface of aggregates, including granular activated carbon (GAC), gravel, lapillus, manganese oxide (MnO2), pyrite (FeS2), and sand. While admixing Fe0 and reactive aggregates to build hybrid systems (e.g., Fe0/FeS2, Fe0/MnO2, Fe0/sand) for water treatment, it has been largely overlooked that these materials would experience reactivity loss upon coating. This communication clarifies the relationships between aggregate addition and the sustainability of Fe0/H2O filtration systems. It is shown that any enhanced contaminant removal efficiency in Fe0/aggregate/H2O systems relative to the Fe0/H2O system is related to the avoidance/delay of particle cementation by virtue of the non-expansive nature of the aggregates. The argument that aggregate addition sustains any reductive transformation of contaminants mediated by electrons from Fe0 is disproved by the evidence that Fe0/sand systems are equally more efficient than pure Fe0 systems. This demonstration corroborates the concept that aqueous contaminant removal in iron/water systems is not a process mediated by electrons from Fe0. This communication reiterates that only hybrid Fe0/H2O filtration systems are sustainable.
Enhancing Informed Decisions for Coastal Groundwater Sustainability: A Network Analysis of Water-Related Indicator Results from 122 Cities
Authors: Lee Khawon , Chang Sunwoo , Koop Stef , van Leeuwen Kees , Park Jeryang
Published: January 2022

In many places around the globe, groundwater has been threatened by various pressures, which calls for better management strategies for groundwater sustainability. In this study, we suggest a novel framework for identifying factors critical to coastal groundwater based on results from City Blueprint (CB) assessments. By compiling the 5856 indicator results of the City Blueprint Approach (CBA) from 122 cities and analyzing the correlation between these indicators, we constructed City Blueprint networks (CBN) by using a complex network modeling approach for three groups of cities: all 122 cities, 40 coastal, and 82 non-coastal cities. These networks were then analyzed for their node centralities to identify major factors that influence coastal groundwater management. Interestingly, our analysis revealed that groundwater has various indirect but important links with the factors that are typically unexplored in the literature. We also assessed the CB of the two largest coastal cities in South Korea. By combining the results of network analysis and CB assessment of the two cities, we could identify the indicators that are potentially at risk regarding coastal groundwater. We propose the CBN as a novel approach to unveil underestimated or hidden factors related to the target system (e.g., groundwater), which allows extensive options for sustainable groundwater management.
Study of the Effect of Leucine on Calcium Carbonate Precipitation in a Circular Economy Perspective
Authors: Mazziotti di Celso Giuseppe , Prisciandaro Marina , Karatza Despina , Musmarra Dino , Lancia Amedeo
Published: January 2022

This paper studies the crystallization of calcium carbonate in the presence of leucine—a green additive. The effect of leucine on calcium carbonate precipitation kinetic is particularly interesting since CaCO3 is a valuable product worthy to be recovered from industrial liquid wastes (e.g., desalination brines) in the circular economy approach. Experiments have been performed in a laboratory scale plant with a supersaturation range which spams from 2 to 120 and two different leucine concentration (0.520 × 10−3 and 1.041 × 10−3 mol/L). Results obtained have been compared with previous published ones, carried out without any additives. From the measurements of induction times for calcium carbonate nucleation, it was established that in solution, the leucine favors the precipitation of calcium carbonate, so it can be considered a promoter in calcium carbonate crystallization and this behavior enhances when raising its concentration in solution. Interfacial tension was determined for both leucine concentration levels, and the values obtained are in the range 51–84 mJ/m2.