bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effectiveness of Different Eradication Schemes for Pediatric Helicobacter pylori Infection—A Single-Center Comparative Study from Romania
Authors: Rosu Oana-Maria , Gimiga Nicoleta , Stefanescu Gabriela , Ioniuc Ileana , Tataranu Elena , Balan Gheorghe G. , Ion Laura-Mihaela , Plesca Doina Anca , Schiopu Cristina Gabriela , Diaconescu Smaranda
Published: September 2022

Introduction: In Romania, studies on the pediatric population regarding H. pylori infection or bacterial resistance to antibiotics are limited. Eradication treatment of this infection still raises important problems in medical practice. This study aims to compare the effectiveness of three eradication therapies used against H. pylori infection in the pediatric population. Methods: The prospective study enrolled children aged 6–17 years who were first diagnosed with H. pylori infection. Patients received a randomized treatment either the therapy with clarithromycin (CLR), the therapy with metronidazole (MTZ) or sequential therapy. The effectiveness of the eradication treatment was evaluated after 4–8 weeks from the end of the therapy by testing fecal antigen. Results: 149 patients were enrolled over 18 months. The eradication rates were 49.5% for the treatment scheme with proton pump inhibitor (PPI) + amoxicillin (AMO) + MTZ, 26.7% for PPI + AMO + CLR and 23.8% for sequential therapy. MTZ therapy was superior to CLR therapy, but sequential therapy was not. Side effects were recorded for PPI + AMO + CLR with 39.6%, followed by sequential therapy 37.7%, and only 22.6% for PPI + AMO + MTZ. Conclusions: Therapy with MTZ can achieve a higher eradication rate as a first-line treatment in the case of H. pylori infection. Taking into account that Romania is in an area with increased resistance to CLR, MTZ therapy could be a promising alternative.
From International to Local: Promoting Local Volunteer Tourism to Guarantee the Persistence of Wildlife Conservation Projects in the Post-COVID-19 Era
Authors: Nekaris K. A. I. , Balestri Michela , El Bizri Hani R. , Dewi Tungga , Hedger Katherine , Morcatty Thais Q. , Nijman Vincent , Weldon Ariana V. , Campera Marco
Published: September 2022

Volunteer tourists, often foreigners, collect essential data in wildlife conservation projects worldwide. Due to the COVID-19 pandemic, international tourism activities reduced drastically, forcing many conservation projects to shut down. Using a nine-year (2013–2021) case study in Indonesia, we examine how local and foreign tourists construct the meaning of their volunteer experiences in the light of COVID-19. We aim to highlight the potential benefits of local volunteer tourism to face the travel limitations posed by COVID-19, and to show an example of how conservation projects can overcome the challenges of the current and potential future pandemics. We recruited 117 volunteers (49 Indonesians, 68 foreign; 73 females, 44 males; mean age: 24.2 ± SD 4.7) that collected 50.8% of the total amount of data collected by the project over the same period. Of the 117 volunteers, 81 of them (38 Indonesians, 43 foreigners) filled in a feedback form at the end of their stay. Via logistic regressions, we found that Indonesian volunteers declared more positive feedback on the logistics at the research station (p = 0.047). Via Bayesian structural equation models, we found that Indonesian volunteers reported significantly more frequently than foreign volunteers that they learned new skills (89% Credible Interval = 0.017–0.351) and that they gained personal wisdom, growth and maturity (89% Credible Interval = 0.891–1.003) from the volunteer experience. The volunteer program evolved from being 100% foreign volunteers in 2013 to 100% Indonesian volunteers by 2020 at the peak of the pandemic, which helped maintain the continuity of the research and conservation activities. We presented the positive implications of shifting towards local volunteer tourists in a long-term conservation project. We suggest that promoting local volunteer tourism through training new generations of nationals in conservation projects is key to guarantee the persistence of such initiatives in the post-COVID-19 Era.
Soft Tissue Sarcomas of the Head and Neck Region with Skull Base/Intracranial Invasion: Review of Surgical Outcomes and Multimodal Treatment Strategies: A Retrospective Case Series
Authors: Habib Ahmed , Edem Idara , Bell Diana , Su Shirley Y. , Hanna Ehab Y. , Kupferman Michael E. , DeMonte Franco , Raza Shaan M.
Published: September 2022

Soft tissue sarcomas (STS) invading the skull base are rare with little data to guide surgical management. Here we aimed to determine the factors affecting tumor control rates and survival in patients with T4 stage head and neck STS involving the skull base. A retrospective review of STS patients, surgically treated at our institution between 1994 and 2017 was conducted. Variables were collected and assessed against progression-free survival. Tumors were graded using the Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) system. A total of 51 patients (mean age of 35) were included, of whom 17 (33.3%) patients were FNCLCC grade 1, 8 (15. 7%) were FNCLCC grade 2 and 26 (51%) were FNCLCC grade 3. The median PFS was 236.4 months while the 5- and 10-year PFS rates were 44% and 17%, respectively. Recurrence occurred in 17 (33.3%) patients. Local recurrence occurred in 10 (58.8%). Univariate analysis revealed R0 resection had a near-significant impact on tumor control in radiation-naïve patients. Otherwise, prior radiation (HR 6.221, CI 1.236–31.314) and cavernous sinus involvement (HR 14.464, CI 3.326–62.901) were negative predictors of PFS. The most common cause of treatment failure was local recurrence. In T4 stage head and neck STS with skull-base involvement, FNCLCC grade, radiation status, and anatomic spread should be considered in determining the overall treatment strategy.
Prognostic Impact of Resection Margin Status on Distal Pancreatectomy for Ductal Adenocarcinoma
Authors: Holm Maia Blomhoff , Verbeke Caroline Sophie
Published: September 2022

Pancreatic cancer is associated with a poor prognosis. While surgical resection is the only treatment option with curative intent, most patients die of locoregional and/or distant recurrence. The prognostic impact of the resection margin status has received much attention. However, the evidence is almost exclusively related to pancreatoduodenectomies, while corresponding data for distal pancreatectomy specimens are limited. The key data, such as the rate of microscopic margin involvement (“R1”), the site of margin involvement, and the impact of R1 on patient outcome, are divergent between studies and do not currently allow any general conclusions. The main reasons for the variability in the published data are the small size of the study cohorts and their heterogeneity, as well as the marked divergence in pathology examination practices. The latter is a consequence of the lack of concrete guidance, both for grossing and microscopic examination. The increasing administration of neoadjuvant chemo(radio)therapy introduces a further factor of uncertainty as the conventional definition of a tumour-free margin (“R0”) based on 1 mm clearance is inadequate for these specimens. This review discusses the published data regarding the prognostic impact of margin status in distal pancreatectomy specimens along with the challenges and uncertainties that are related to the assessment of the margins.
Evolution and Biogeographic History of Rubyspot Damselflies (Hetaerininae: Calopterygidae: Odonata)
Authors: Standring Samantha , Sánchez-Herrera Melissa , Guillermo-Ferreira Rhainer , Ware Jessica L. , Vega-Sánchez Yesenia Margarita , Clement Rebecca , Drury Jonathan P. , Grether Gregory F. , González-Rodríguez Antonio , Mendoza-Cuenca Luis , Bota-Sierra Cornelio A. , Bybee Seth
Published: September 2022

The damselflies Hetaerininae, a subfamily of Calopterygidae, comprise four genera distributed from North to South America: Hetaerina, Mnesarete, Ormenophlebia and Bryoplathanon. While several studies have focused on the intriguing behavioral and morphological modifications within Hetaerina, little of the evolutionary history of the group is well understood. Understanding the biogeographical history of Hetaerininae is further complicated by uncertainty in important geological events, such as the closure of the Central American Seaway (CAS). We generated a phylogenetic hypothesis to test the relationships and divergence times within Hetaerininae using IQtree and BEAST2 and found that Mnesarete and Ormenophlebia render Hetaerina paraphyletic. Reclassification of the genera within Hetaerininae is necessary based on our results. We also tested the fit to our dataset of two different hypotheses for the closure of CAS. Our results supported a gradual closure, starting in the Oligocene and ending in the Pliocene. Using Ancestral Character State Reconstruction, we found that the rubyspot, which is associated with higher fecundity in several species, was ancestral for Hetaerininae and subsequently lost four times. Estimates of diversification in association with the rubyspot are needed to understand the plasticity of this important character. Forest habitat was the ancestral state for Hetaerininae, with transitions to generalist species of Hetaerina found primarily in the Mesoamerican region. These results add to our understanding of the relationship between morphology, biogeography and habitat in a charismatic group of damselflies.
Spin Entropy
Authors: Geiger Davi , Kedem Zvi M.
Published: September 2022

Two types of randomness are associated with a mixed quantum state: the uncertainty in the probability coefficients of the constituent pure states and the uncertainty in the value of each observable captured by the Born’s rule probabilities. Entropy is a quantification of randomness, and we propose a spin-entropy for the observables of spin pure states based on the phase space of a spin as described by the geometric quantization method, and we also expand it to mixed quantum states. This proposed entropy overcomes the limitations of previously-proposed entropies such as von Neumann entropy which only quantifies the randomness of specifying the quantum state. As an example of a limitation, previously-proposed entropies are higher for Bell entangled spin states than for disentangled spin states, even though the spin observables are less constrained for a disentangled pair of spins than for an entangled pair. The proposed spin-entropy accurately quantifies the randomness of a quantum state, it never reaches zero value, and it is lower for entangled states than for disentangled states.
A Multigraph-Defined Distribution Function in a Simulation Model of a Communication Network
Authors: Miletic Slobodan , Pokrajac Ivan , Pena-Pena Karelia , Arce Gonzalo R. , Mladenovic Vladimir
Published: September 2022

We presented a method based on multigraphs to mathematically define a distribution function in time for the generation of data exchange in a special-purpose communication network. This is needed for the modeling and design of communication networks (CNs) consisting of integrated telecommunications and computer networks (ITCN). Simulation models require a precise definition of network traffic communication. An additional problem for describing the network traffic in simulation models is the mathematical model of data distribution, according to which the generation and exchange of certain types and quantities of data are realized. The application of multigraphs enabled the time and quantity of the data distribution to be displayed as operational procedures for a special-purpose communication unit. A multigraph was formed for each data-exchange time and allowed its associated adjacency matrix to be defined. Using the matrix estimation method allowed the mathematical definition of the distribution function values. The application of the described method for the use of multigraphs enabled a more accurate mathematical description of real traffic in communication networks.
A Novel Bearing Fault Diagnosis Method Based on Few-Shot Transfer Learning across Different Datasets
Authors: Zhang Yizong , Li Shaobo , Zhang Ansi , Li Chuanjiang , Qiu Ling
Published: September 2022

At present, the success of most intelligent fault diagnosis methods is heavily dependent on large datasets of artificial simulation faults (ASF), which have not been widely used in practice because it is often costly to obtain a large number of samples in reality. Fortunately, various faults can be easily simulated in the laboratory, and these simulated faults contain a lot of fault diagnosis knowledge. In this study, based on a Siamese network framework, we propose a bearing fault diagnosis based on few-shot transfer learning across different datasets (cross-machine), using the knowledge of ASF to diagnose bearings with natural faults (NF). First of all, the model obtains a good feature encoder in the source domain, then defines a fault support set for comparison, and finally adjusts the support set with a very small number of target domain samples to improve the fault diagnosis performance of the model. We carried out experimental verification from many aspects on the ASF and NF datasets provided by Case Western Reserve University (CWRU) and Paderborn University (PU). The results show that the proposed method can fully learn diagnostic knowledge in different ASF datasets and sample numbers, and effectively use this knowledge to accurately identify the health state of the NF bearing, which has strong generalization and robustness. Our method does not need second training, which may be more convenient in some practical applications. Finally, we also discuss the possible limitations of this method.
Consensus-Related Performance of Triplex MASs Based on Partial Complete Graph Structure
Authors: Bian Jicheng , Huang Da , Xu Jiabo , Yu Zhiyong
Published: September 2022

This article mainly studies first-order coherence related to the robustness of the triplex MASs consensus models with partial complete graph structures; the performance index is studied through algebraic graph theory. The topologies of the novel triplex networks are generated by graph operations and the approach of graph spectra is applied to calculate the first-order network coherence. The coherence asymptotic behaviours of the three cases of the partial complete structures are analysed and compared. We find that under the condition that the number of nodes in partial complete substructures n tends to infinity, the coherence asymptotic behaviour of the two sorts of non-isomorphic three-layered networks will be increased by r−12(r+1), which is irrelevant to the peripheral vertices number p; when p tends to infinity, adding star copies to the original triplex topologies will reverse the original size relationship of the coherence under consideration of the triplex networks. Finally, the coherence of the three-layered networks with the same sorts of parameters, but non-isomorphic graphs, are simulated to verify the results.
Detecting Tripartite Steering via Quantum Entanglement
Authors: Chen Zhihua , Fei Shao-Ming
Published: September 2022

Einstein-Podolsky-Rosen steering is a kind of powerful nonlocal quantum resource in quantum information processing such as quantum cryptography and quantum communication. Many criteria have been proposed in the past few years to detect steerability, both analytically and numerically, for bipartite quantum systems. We propose effective criteria for tripartite steerability and genuine tripartite steerability of three-qubit quantum states by establishing connections between the tripartite steerability (resp. genuine tripartite steerability) and the tripartite entanglement (resp. genuine tripartite entanglement) of certain corresponding quantum states. From these connections, tripartite steerability and genuine tripartite steerability can be detected without using any steering inequalities. The “complex cost” of determining tripartite steering and genuine tripartite steering can be reduced by detecting the entanglement of the newly constructed states in the experiment. Detailed examples are given to illustrate the power of our criteria in detecting the (genuine) tripartite steerability of tripartite states.
A New Method for Determining the Embedding Dimension of Financial Time Series Based on Manhattan Distance and Recurrence Quantification Analysis
Authors: Zhu Hanhuai , Huang Jingjing
Published: September 2022

Identification of embedding dimension is helpful to the reconstruction of phase space. However, it is difficult to calculate the proper embedding dimension for the financial time series of dynamics. By this Letter, we suggest a new method based on Manhattan distance and recurrence quantification analysis for determining the embedding dimension. By the advantages of the above two tools, the new method can calculate the proper embedding dimension with the feature of stability, accuracy and rigor. Besides, it also has a good performance on the chaotic time series which has a high-dimensional attractors.
Analysis of Citizen Satisfaction in Municipal Services
Authors: Romero-Subia José Fernando , Jimber-del Rio Juan Antonio , Ochoa-Rico María Salomé , Vergara-Romero Arnaldo
Published: September 2022

Citizen demand for quality public services is increasing, and improvements in the provision of public services affect citizen satisfaction and loyalty. This research is to evaluate citizens’ loyalty to municipal officials on the quality of public services provided by the municipality. The measurement is made through a household-level survey, with a sample of 428 valid questionnaires, in a rural parish of Tengel in Guayaquil, following the American Customer Satisfaction Index (ACSI). This study used the Warp-PLS 7.0 software with a structural equation model to evaluate the seven hypotheses raised. A new component is included in this research: the effect of perceived quality in the provision of municipal services in rural areas on the value ratio perceived by the citizen and overall satisfaction. The results obtained allowed us to observe that the loyalty of the citizen to the elected municipal officials depends on citizen satisfaction with the public services provided by the municipal administration in rural areas. In addition, the quality perceived by the citizen modulates at different levels the relationships between the perceived value and the citizen satisfaction. Areas of improvement in the provision of public services such as municipal police, firefighters, veterinary services, parking services and address information were identified. The findings would allow local public administrators to take action to improve the services provided in rural areas in order to maintain the loyalty of citizens.
The Athletic Identity Measurement Scale: A Systematic Review with Meta-Analysis from 1993 to 2021
Authors: Lochbaum Marc , Cooper Sydney , Limp Sara
Published: September 2022

Sport psychology embraced the study of athletic identity in the 1990s. The Athletic Identity Measurement Scale (AIMS) is at the forefront of athletic identity measurement. This quantitative review examined two hypotheses: individual who are most engaged in sports identify most as athletes and thus score higher on the AIMS, and athletic identity relates to positive (e.g., intrinsic motivation) and negative (negative emotions) factors. In addition to our two hypotheses, we explored whether the AIMS subscales influenced our two hypotheses. After completing a systematic search of SPORTDiscus, APA PsycINFO, ERIC, and Psychology and Behavioral Sciences Collection APA within the EBSCOhost platform along with some hand searching, 101 articles published between 1993 and our end date of August 2021 met the inclusion criteria. The included studies investigated 20,498 athletes competing in a variety of sports from the following continents: Australia, Asia, Europe, and North America. We based all analyses on random- and mixed-effects statistics. Higher-achieving athletes, as expected, self-reported a higher degree of athletic identity. The differences between athlete groups were significant (p < 0.001) and meaningful (g values ranged from 1.55 to 1.93). The AIMS total score correlations with positive and negative factors (correlates) were small in magnitude (r = 0.22 and 0.17). However, the relationships differed across correlate subcategories (e.g., intrinsic motivation/commitment, r = 0.51, and body issues, r = 0.14). Minimal AIMS subscale reporting occurred across the 101 studies; thus, we could not assess their importance with certainty. In conclusion, a higher degree of athletic identity related to valued sport correlates such as intrinsic motivation/commitment and the mastery goal orientation. These correlations were small in relation to negative or less desirable factors in sport such as body disorder issues and negative emotions. We recommend future research of greater complexity and the reporting of athletes’ competitive backgrounds to understand athletic identity. In addition, researchers should report AIMS subscale data.
Systolic Blood Pressure Estimation from PPG Signal Using ANN
Authors: Casadei Benedetta C. , Gumiero Alessandro , Tantillo Giorgio , Della Torre Luigi , Olmo Gabriella
Published: September 2022

High blood pressure is one of the most important precursors for Cardiovascular Diseases (CVDs), the most common cause of death in 2020, as reported by the World Health Organization (WHO). Moreover, many patients affected by neurodegenerative diseases (e.g., Parkinson’s Disease) exhibit impaired autonomic control, with inversion of the normal circadian arterial pressure cycle, and consequent augmented cardiovascular and fall risk. For all these reasons, a continuous pressure monitoring of these patients could represent a significant prognostic factor, and help adjusting their therapy. However, the existing cuff-based methods cannot provide continuous blood pressure readings. Our work is inspired by the newest approaches based on the photoplethysmographic (PPG) signal only, which has been used to continuously estimate systolic blood pressure (SP), using artificial neural networks (ANN), in order to create more compact and wearable devices. Our first database was derived from the PhysioNet resource; we extracted PPG and arterial blood pressure (ABP) signals, collected at a sampling frequency of 125 Hz, in a hospital environment. It consists of 249,672 PPG periods and the relative SP values. The second database was collected at STMicroelectronics s.r.l., in Agrate Brianza, using the MORFEA3 wearable device and a digital cuff-based sphygmomanometer, as reference. The pre-processing phase, in order to remove noise and motion artifacts and to segment the signal into periods, was carried out on Matlab R2019b. The noise removal was one of the challenging parts of the study because of the inaccuracy of the PPG signal during everyday-life activity, and this is the reason why the MORFEA3 dataset was acquired in a controlled environment in a static position. Different solutions were implemented to choose the input features that best represent the period morphology. The first database was used to train the multilayer feed-forward neural network with a back-propagation model, whereas the second one was used to test it. The results obtained in this project are promising and match the Association for the Advancement of Medical Instruments (AAMI) and the British Hypertension Society (BHS) standards. They show a Mean Absolute Error of 3.85 mmHg with a Standard Deviation of 4.29 mmHg, under the AAMI standard, and reach the grade A under the BHS standard.
Genetically Optimized Pitch Angle Controller of a Wind Turbine with Fuzzy Logic Design Approach
Authors: Pehlivan Ahmet Selim , Bahceci Beste , Erbatur Kemalettin
Published: September 2022

An important engineering challenge is the design of a wind turbine’s pitch angle controller. The dependability, safety, and power output maximization of a wind turbine are all impacted by this controller. In this study, a 2 MW doubly fed induction generator wind turbine’s blade angle controller design with a novel fuzzy logic controller is tested in a simulated environment. The evolutionary algorithm technique is used to optimize the fuzzy logic controller with three inputs. A genetic algorithm is used to optimize the specified pitch angle controller for a number of coefficients. After the optimization process, the controller’s performance is assessed in terms of power output, overshoot, and steady-state error characteristics.
Reliability Evaluation of Standalone Microgrid Based on Sequential Monte Carlo Simulation Method
Authors: Weng Zhipeng , Zhou Jinghua , Zhan Zhengdong
Published: September 2022

In order to analyze the influence of uncertainty and an operation strategy on the reliability of a standalone microgrid, a reliability evaluation method based on a sequential Monte Carlo (SMC) simulation was developed. Here, the duty cycles of a microturbine (MT), the stochastic performance of photovoltaics (PV), and wind turbine generators (WTG) were considered. Moreover, the time-varying load with random fluctuation was modeled. In this method, the available capacity of an energy storage system (ESS) was also comprehensively considered by the SMC simulation. Then, the reliability evaluation framework was established from the perspectives of probability, frequency, and duration, and reliability evaluation algorithms under different operation strategies were formulated. Lastly, the influence of WTG and PV penetration and equipment capacity on the reliability was evaluated in the test system. The results showed that the complementary characteristics of wind and solar and the enhancement of the equipment capacity can both improve the reliability; but, with the increase in the penetration rate of WTG and PV, more ESS capacity is needed to cope with the randomness of WTG and PV. In addition, load shedding minimization strategies can minimize the probability and the number of reductions and achieve optimal reliability, which can provide a reference for the formulation of microgrid operation strategies.
Greenhouse Gas Emissions in the Process of Landfill Disposal in China
Authors: Guo Hanwen , Xu Haiyun , Liu Jianguo , Nie Xiaoqin , Li Xu , Shu Tianchu , Bai Binjie , Ma Xingyu , Yao Yuan
Published: September 2022

Quantitative accounting of greenhouse gas (GHG) emissions has become an important global focus. GHG emissions from the waste sector have high potential in GHG emissions reduction. We analyzed the GHG emissions inventory in the waste sector of the European Union, Germany, the United Kingdom, the United States of America, and Canada from 1990 to 2019. Landfill disposal was the main category of GHGs from the waste sector, with a contribution rate between 69% and 95%. Landfill disposal also played a prominent role in emission reduction, with a contribution rate higher than 86%. GHG emissions from landfill sites in China were calculated using the inventory analysis method recommended by the IPCC and combined with actual situations. The results showed that the highest GHG emissions from landfill disposal in China occurred in 2020, with an estimated 165 million tons of carbon dioxide (CO2) equivalent. In 2019, the per capita GHG emissions from landfill sites in China was 117 kg CO2 equivalent/person, which was higher than Germany (87 kg CO2 equivalent/person) but lower than the European Union (189 kg CO2 equivalent/person).
Integrated Optimal Design for Hybrid Electric Powertrain of Future Aircrafts
Authors: Pettes-Duler Matthieu , Roboam Xavier , Sareni Bruno
Published: September 2022

This paper presents the integrated optimal design of the powertrain of a hybrid regional aircraft using multidisciplinary design optimization (MDO). The sizing of the main components of the propulsion chain is performed over the flight mission under various scenarios regarding energy management strategies and technological assessments. For that purpose, a complete set of multidisciplinary surrogate models are integrated into the MDO process, taking account not only of the main electrical, thermal and mechanical aspects but also of environmental constraints such as partial discharges in electric motors regarding flight conditions. Several MDO formulations are investigated comparing local (i.e., motor mass minimization) and global optimizations (i.e., powertrain mass then fuel burn minimization at aircraft level). Results emphasize main systemic couplings showing that despite future technological progress, the series hybrid architecture is heavier than a conventional thermal aircraft. Nevertheless, thanks to the whole aircraft optimization, potential gains related to kerosene consumption can be reached, reducing the environmental footprint. The “energy gains” focused on in this paper may be added with aerodynamic gains potentially involved in more electric powertrain. This work has been carried out in the frame of the HASTECS project under the Clean Sky II program which aims at reducing CO2 emissions and environmental impacts of the aviation sector.
City-Level E-Bike Sharing System Impact on Final Energy Consumption and GHG Emissions
Authors: Raposo Mariana , Silva Carla
Published: September 2022

Bike-sharing systems implemented in cities with good bike lane networks could potentiate a modal shift from short car trips, boosting sustainable mobility. Both passenger and last-mile goods transportation can benefit from such systems and, in fact, bike sharing (dockless or with docking stations) is increasing worldwide, especially in Europe. This research focused on a European city, Lisbon, and the e-bike sharing system GIRA, in its early deployment, in 2018, where it had about 409 bikes of which 30% were non-electric conventional bikes and 70% were e-bikes. The research aims at answering the main research questions: (1) What is the number of trips per day and travel time in conventional bikes and e-bikes?; (2) Do the daily usage peaks follow the trends of other modes of transport in terms of rush hours?; (3) Are there seasonality patterns in its use (weekdays and weekends, workdays and holiday periods)?; (4) How do climate conditions affect its use?; and finally, (5) What would be the impact on final energy consumption and GHG emissions? The dataset for 2018 regarding GIRA trips (distance, time, conventional or e-bike, docking station origin and destination) and weather (temperature, wind speed, relative humidity, precipitation) was available from Lisbon City Hall by means of the program “Lisboa aberta”. Data regarding the profile of the users (which trips GIRA replaces?) and data regarding electricity consumption were not available. The latter was estimated by means of literature e-bike data and electric motor specifications combined with powertrain efficiency. Greenhouse gas (GHG) emissions were estimated by using the latest Intergovernmental Panel on Climate Change (IPCC) CO2 equivalents and a spreadsheet simulator for the Portuguese electricity GHG intensity, which was adaptable to other countries/locations. In a private car fleet dominated by fossil fuels and internal combustion engines, the e-bike sharing system is potentially avoiding 36 Ton GHG/year and reducing the energy consumption by 451 GJ/year. If the modal shift occurs from walking or urban bus to an e-bike sharing system, the impact will be detrimental for the environment.
HVAC System Control Solutions Based on Modern IT Technologies: A Review Article
Authors: Borodinecs Anatolijs , Zemitis Jurgis , Palcikovskis Arturs
Published: September 2022

As energy consumption for building engineering systems is a major part of the total energy spent, it is necessary to reduce it. This leads to the need for the development of new solutions for the control of heating, ventilation, and conditioning (HVAC) systems that are responsive to humans and their demands. In this review article, the existing research and technology advancements of the modern technologies of computer vision and neural networks for application in HVAC control systems are studied. Objectives such as human detection and location, human activity monitoring, skin temperature detection, and clothing level detection systems are important for the operation of precise, high-tech HVAC systems. This article tries to compile the latest achievements and principal solutions on how this information is acquired. Moreover, it how parameters such as indoor air quality (IAQ), variable air volume ventilation, computer vision, metabolic rate, and human clothing isolation can affect final energy consumption is studied. The research studies discussed in this review article have been tested in real application scenarios and prove the benefits of using a particular technology in ventilation systems. As a result, the modernized control systems have shown advantages over the currently applied typical non-automated systems by providing higher IAQ and reducing unnecessary energy consumption.
Blockchain Smart Contract-Enabled Secure Energy Trading for Electric Vehicles
Authors: Xue Feng , Chang Kang , Li Wei , Wang Qin , Zhao Haitao , Zhang Hui , Ni Yiyang , Xia Wenchao
Published: September 2022

In this paper, a blockchain-enabled energy trading method is proposed to deal with the inefficiency and security issues in energy trading for electric vehicles in smart grids. It includes the design of a smart contract and the excitation mechanism of energy sharing. The credit points of each vehicle as a node are considered in the design of the smart contract, which is used to supervise the process of energy trading. A strategy to estimate the credit points of each node and describe the excitation mechanism is illustrated. The connection between the credit points and the probability that a node would be accepted for energy trading has been established. To control the energy trading access, a double auction method is used to choose the part of the nodes participating in energy trading. Only selected nodes with winning bids can supply or request energy from the blockchain-based platform. Then it reaches the conclusion that the higher the credit points they have, the more trading initiative they would have during the energy transaction and transmission. The smart contract design and the excitation mechanism proposed in this paper would reward the vehicles that perform well and punish the beguiling vehicles for regulating the trading process.
Short-Term Wind Power Prediction Based on Data Decomposition and Combined Deep Neural Network
Authors: Wu Xiaomei , Jiang Songjun , Lai Chun Sing , Zhao Zhuoli , Lai Loi Lei
Published: September 2022

A hybrid short-term wind power prediction model based on data decomposition and combined deep neural network is proposed with the inclusion of the characteristics of fluctuation and randomness of nonlinear signals, such as wind speed and wind power. Firstly, the variational mode decomposition (VMD) is used to decompose the wind speed and wind power sequences in the input data to reduce the noise in the original signal. Secondly, the decomposed wind speed and wind power sub-sequences are reconstructed into new data sets with other related features as the input of the combined deep neural network, and the input data are further studied for the implied features by convolutional neural network (CNN), which should be passed into the long and short-term memory neural network (LSTM) as input for prediction. At the same time, the improved particle swarm optimization algorithm (IPSO) is adopted to optimize the parameters of each prediction model. By superimposing each predicted sub-sequence, the predicting wind power could be obtained. Simulations based on a short-term power prediction in different months with huge weather differences is carried out for a wind farm in Guangdong, China. The simulated results validate that the proposed model has a high prediction accuracy and generalization ability.
An OCPP-Based Approach for Electric Vehicle Charging Management
Authors: Hsaini Sara , Ghogho Mounir , Charaf My El Hassan
Published: September 2022

This paper proposes a smart system for managing the operations of grid-connected charging stations for electric vehicles (EV) that use photovoltaic (PV) sources. This system consists of a mobile application for EV drivers to make charging reservations, an algorithm to optimize the charging schedule, and a remote execution module of charging operations based on the open charge point protocol (OCPP). The optimal charging schedule was obtained by solving a binary integer programming problem. The merits of our solution are illustrated by simulating different charging demand scenarios.
Fungal Metabolites in Human Health and Diseases—An Overview
Authors: Esheli Manal , Thissera Bathini , El-Seedi Hesham R. , Rateb Mostafa E.
Published: September 2022

Fungi produce a wide range of secondary metabolites. Some of these metabolites are toxic to humans and cause various health disorders, ranging from acute poisoning to chronic diseases. Contrary to this, some fungal metabolites are valuable sources in therapeutics, such as penicillin. Herein, researchers briefly highlight the role played by different fungal metabolites in human health and diseases and give an overview of the most common fungal genera.
Physiological Effects of Recapture and Transport from Net-Cages in Lumpfish
Authors: Foss Atle , Imsland Albert K. D.
Published: September 2022

Lumpfish are widely used for removing sea lice in salmonid sea-based aquaculture. If these fish are to be harvested and used for human consumption, it is necessary to know how the physical strain associated with removing the lumpfish from the net-cages affects the fish in the short-term, and if live-storage in tanks, well-boats, or nets awaiting slaughter, will result in stress and mortalities. In this study, we investigated the effect of physical stress and mortality in a group of lumpfish recaptured from commercial net-cages, transported to holding tanks, and stored for one week. In addition to cortisol (primary stress response), we analyzed ions directly related to osmoregulation (Na+ and Cl−), osmotic stress (Ca2+), and blood plasma pH as an indicator of a secondary stress response. The aim of the study was to increase the basic physiological understanding of the physiological effects of handling procedures and transport in lumpfish. Only minor, and temporary, effects on primary stress response and secondary stress response were seen in lumpfish recaptured from net-cages and transported to holding facilities, indicating that lumpfish cope well with short transport (here 5 h). These findings are important in a context where lumpfish are harvested for reuse, e.g., human consumption or processing, following their lice-eating stage in net-cages.
Experimental Investigation on the Spray Behaviour of Bluff Body Air-Assisted Atomizer Designs
Authors: Sikka Raghav , Vågsæther Knut , Bjerketvedt Dag , Lundberg Joachim
Published: September 2022

This study investigates the gas dynamic effects and atomization behavior of a novel sonic bluff body-assisted two-fluid atomizer with three different geometric configurations based on airflow orifice diameters (d) of 2.0 mm, 3.0 mm, and 4.0 mm. Along with a 280 µm annular liquid sheet, atomizers that employed a central bluff body (cone) with 6.0 mm cone distance (Lc) are compared based on the range of different air and liquid (water) flow rates. The spray-bluff body-impacted secondary atomization was characterized through volume-normalized droplet size distribution (DSD) and cumulative droplet distribution, excentricity plots, Sauter mean diameter (SMD), and relative span factor (Δ). Droplet number density decreases with the increase in radial location, with lesser droplet density for the 3.0 mm atomizer. DSD and cumulative droplet distribution become less uniform with the increase in the radial locations with wider distribution for larger diameter atomizers (4.0 mm). Droplet excentricity follows an inverse relationship with the droplet diameter such that high diameter droplets have low excentricity (%) and vice versa. SMD and relative span factor (RSF) showed opposite trends when plotted (line plots) against the air-to-liquid ratio (ALR) with larger fluctuation in the SMD than the RSF (Δ) value. The spray pattern spread increases gradually with increasing liquid loading and with decreases in the ALR value for all atomizers.
Preparation and Characterization of Plant Protein Adhesives with Strong Bonding Strength and Water Resistance
Authors: Qu Yang , Guo Qin , Huang Xuegang , Li Tian , Liang Manzhu , Qin Jingjing , Gao Qiang , Liu Hongzhi , Wang Qiang
Published: September 2022

Plant protein adhesive has received considerable attention because of their renewable raw material and no harmful substances such as formaldehyde. However, for the plant protein adhesive used in the field of plywood, low cost, strong water resistance, and high bonding strength were the necessary conditions for practical application. In this work, a double-network structure including hydrogen bonds and covalent bonds was built in hot-pressed peanut meal (HPM) protein (HPMP) adhesive, soybean meal (SBM) protein (SBMP) adhesive and cottonseed meal (CSM) protein (CSMP) adhesives. The ether bonds and ester bonds were the most in CSMP adhesive, followed by SBMP adhesive, while the hydrogen bond was the most in HPMP adhesive. The solubility of the HPMP, SBMP, and CSMP adhesives decreased by 14.3%, 24.2%, and 19.4%, the swelling rate decreased by 56.9%, 48.4%, and 78.5%, respectively. The boiling water strength (BWS) of HPMP (0.82 MPa), SBMP (0.92 MPa), and CSMP adhesives reached the bonding strength requirement of China National Standards class I plywood (type I, 0.7 MPa). The wet shear strength (WSS) of HPMP, SBMP, and CSMP adhesives increased by 334.5% (1.26 MPa), 246.3% (1.42 MPa), and 174.1% (1.59 MPa), respectively. This study provided a new theory and method for the development of eco-friendly plant meal protein adhesive and promotes the development of green adhesive.
Current Sex Distribution of Cooking and Food Shopping Responsibilities in the United States: A Cross-Sectional Study
Authors: Storz Maximilian Andreas , Beckschulte Kai , Brommer Maria , Lombardo Mauro
Published: September 2022

Home cooking is an important obesity prevention strategy and associated with benefits for diet and health. Although cooking may be a joyful act of mindfulness, it also requires planning, preparation and time. Historically, women have been more likely to fulfill the role of food shopping and cooking. More recent studies suggested a transition in traditional household role assignments towards a larger involvement of males. This study examined the current sex distribution of cooking and food shopping responsibilities in the United States of America based on a nationally representative sample of 9078 citizens from the National Health and Nutrition Examination Surveys (2017–2020). More than 80% of women aged 25 years or older indicated that they were the person who did most of the planning/preparing of meals in their families, whereas the percentage of males responding affirmatively was substantially lower, ranging from 38.73% to 43.20% depending on age. Analyses on food shopping duties revealed a comparable distribution. In multivariate regression, female sex was associated with significantly higher odds of being the main food shopper/meal preparer in the family (OR: 4.82 (4.14–5.60) and 5.54 (4.60–6.67), respectively). Our data suggest that the majority of food shopping and cooking duties are still performed by women, which has important implications for public health nutrition initiatives.
A Combined Differential Proteome and Transcriptome Profiling of Fast- and Slow-Twitch Skeletal Muscle in Pigs
Authors: Wei Wei , Zha Chengwan , Jiang Aiwen , Chao Zhe , Hou Liming , Liu Honglin , Huang Ruihua , Wu Wangjun
Published: September 2022

Skeletal muscle fiber types can contribute in part to affecting pork quality parameters. Biceps femoris (Bf) (fast muscle or white muscle) and Soleus (Sol) (slow muscle or red muscle) are two typical skeletal muscles characterized by obvious muscle fiber type differences in pigs. However, the critical proteins and potential regulatory mechanisms regulating porcine skeletal muscle fibers have yet to be clearly defined. In this study, the isobaric Tag for Relative and Absolute Quantification (iTRAQ)-based proteome was used to identify the key proteins affecting the skeletal muscle fiber types with Bf and Sol, by integrating the previous transcriptome data, while function enrichment analysis and a protein–protein interaction (PPI) network were utilized to explore the potential regulatory mechanisms of skeletal muscle fibers. A total of 126 differentially abundant proteins (DAPs) between the Bf and Sol were identified, and 12 genes were found to be overlapping between differentially expressed genes (DEGs) and DAPs, which are the critical proteins regulating the formation of skeletal muscle fibers. Functional enrichment and PPI analysis showed that the DAPs were mainly involved in the skeletal-muscle-associated structural proteins, mitochondria and energy metabolism, tricarboxylic acid cycle, fatty acid metabolism, and kinase activity, suggesting that PPI networks including DAPs are the main regulatory network affecting muscle fiber formation. Overall, these data provide valuable information for understanding the molecular mechanism underlying the formation and conversion of muscle fiber types, and provide potential markers for the evaluation of meat quality.
Chemical Composition and Antioxidant Capacity of the Fruits of European Plum Cultivar “Čačanska Lepotica” Influenced by Different Rootstocks
Authors: Trendafilova Antoaneta , Ivanova Viktoria , Trusheva Boryana , Kamenova-Nacheva Mariana , Tabakov Sava , Simova Svetlana
Published: September 2022

We investigated the influence of different rootstocks on the content of sugars, organic acids, and antioxidant phenolic compounds in the whole fruit and fruit skin of the European plum cultivar “Čačanska Lepotica”. 1H NMR of the fruit extracts allowed for the identification of sucrose, α- and β-glucose, sorbitol, fructose, and malic and quinic acids, while LC–DAD–ESIMS showed the presence of neochlorogenic and chlorogenic acids, cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside, peonidin-3-O-glucoside, peonidin-3-O-rutinoside, hyperoside, isoquercitrin, rutin, and unidentified quercetin-3-diglycoside. The quantitation of the sugars, malic and quinic acids by 1H NMR and phenolic compounds by HPLC–DAD revealed that the rootstock significantly influenced the content of the individual compounds in the fruit skin and fruit. The fruit grafted on “Wavit” rootstock was characterized by significant amounts of neochlorogenic acid, peonidin-3-O-rutinoside, cyanidin-3-O-rutinoside, and sucrose, while the fruit on “GXN-15” was characterized by high levels of sugars, cyanidin-3-O-glucoside, and malic and chlorogenic acids. The fruit skins of plums grafted on “Wavit” were the richest in sugars, organic acids, and phenolic compounds. A good correlation was observed between the content of total phenolics (TPC), flavonoids (TFC), anthocyanins (TAC), and individual phenolic compounds in the extracts of the fruit and the fruit skins and their antioxidant capacity (DPPH, ABTS, and FRAP).