bluuebunny/crossref_metadata_2025 huggingface dataset:
Finger Pain as an Uncommon Primary Manifestation of Lung Carcinoma
Authors: Holzgreve Adrien , Dürr Hans Roland , Stäbler Axel , Kaemmerer Mathias , Unterrainer Lena M. , Tufman Amanda , Manapov Farkhad , Kunz Wolfgang G. , Unterrainer Marcus
Published: February 2023

A 54-year-old patient presented with progressive pain for one month in the second finger of the right hand with an emphasis on the proximal interphalangeal (PIP) joint. Subsequent magnetic resonance imaging (MRI) showed a diffuse intraosseous lesion at the base of the middle phalanx with destruction of the cortical bone and extraosseous soft tissue. An expansively growing chondromatous bone tumor, e.g., a chondrosarcoma, was suspected. After incisional biopsy, the pathologic findings finally revealed, surprisingly, a metastasis of a poorly differentiated non-small cell adenocarcinoma of the lung. This case illustrates a rare but important differential diagnosis for painful finger lesions.
A Novel Strategy to Fit and Validate Physiological Models: A Case Study of a Cardiorespiratory Model for Simulation of Incremental Aerobic Exercise
Authors: Sarmiento Carlos A. , Serna Leidy Y. , Hernández Alher M. , Mañanas Miguel Á.
Published: February 2023

Applying complex mathematical models of physiological systems is challenging due to the large number of parameters. Identifying these parameters through experimentation is difficult, and although procedures for fitting and validating models are reported, no integrated strategy exists. Additionally, the complexity of optimization is generally neglected when the number of experimental observations is restricted, obtaining multiple solutions or results without physiological justification. This work proposes a fitting and validation strategy for physiological models with many parameters under various populations, stimuli, and experimental conditions. A cardiorespiratory system model is used as a case study, and the strategy, model, computational implementation, and data analysis are described. Using optimized parameter values, model simulations are compared to those obtained using nominal values, with experimental data as a reference. Overall, a reduction in prediction error is achieved compared to that reported for model building. Furthermore, the behavior and accuracy of all the predictions in the steady state were improved. The results validate the fitted model and provide evidence of the proposed strategy’s usefulness.
Theoretical Study on the Collective Scattering Properties of Charged Particles to Electromagnetic Waves
Authors: Hu Xiaofeng , Zhou Shuai , Wang Lei , Wang Yingying
Published: February 2023

The rapid development of electromagnetic technology has been widely used in many fields. For example, the transmission of electromagnetic waves in extreme environments (such as sandstorms and haze) and the monitoring of particle composition in the atmosphere by using electromagnetic wave technology. The properties of particles, such as particle electrification, will affect electromagnetic wave scattering and directly affect the signal transmission quality and monitoring results. Based on the scattering characteristics of electromagnetic waves of charged particles, the effects of different particle composition, different electric quantity, different humidity and different particle numbers on electromagnetic wave propagation are studied in this paper. The multiple scattering of electromagnetic waves by the random distribution of multiple particles is studied, and the Maxwell equation is converted into the Foldy–Lax multiple scattering equation, and the numerical solution is carried out. The influence of charged particle clusters on the electromagnetic scattering is analyzed. The simulation and experiment show that the charge of particles has a great influence on the electromagnetic scattering near some frequencies.
Electrical Load Forecasting Using LSTM, GRU, and RNN Algorithms
Authors: Abumohsen Mobarak , Owda Amani Yousef , Owda Majdi
Published: February 2023

Forecasting the electrical load is essential in power system design and growth. It is critical from both a technical and a financial standpoint as it improves the power system performance, reliability, safety, and stability as well as lowers operating costs. The main aim of this paper is to make forecasting models to accurately estimate the electrical load based on the measurements of current electrical loads of the electricity company. The importance of having forecasting models is in predicting the future electrical loads, which will lead to reducing costs and resources, as well as better electric load distribution for electric companies. In this paper, deep learning algorithms are used to forecast the electrical loads; namely: (1) Long Short-Term Memory (LSTM), (2) Gated Recurrent Units (GRU), and (3) Recurrent Neural Networks (RNN). The models were tested, and the GRU model achieved the best performance in terms of accuracy and the lowest error. Results show that the GRU model achieved an R-squared of 90.228%, Mean Square Error (MSE) of 0.00215, and Mean Absolute Error (MAE) of 0.03266.
A Wind Turbine Vibration Monitoring System for Predictive Maintenance Based on Machine Learning Methods Developed under Safely Controlled Laboratory Conditions
Authors: Granados David Pérez , Ruiz Mauricio Alberto Ortega , Acosta Joel Moreira , Lara Sergio Arturo Gama , Domínguez Roberto Adrián González , Kañetas Pedro Jacinto Páramo
Published: February 2023

Wind energy is one of the most relevant clean energies today, so wind turbines must have good health and be reliable in operation. Current wind turbines have slender and elastic structures that can be easily damaged through vibrations and compromise their health; therefore, vibration monitoring is essential to ensure safe operation. Here, we present a method for simple wind turbine vibration monitoring in the laboratory by means of an accelerometer placed on a weathervane under different scenarios, with recording of different amplitudes of vibrations caused at a constant speed of 10 km/h. The variables, trends, and data captured during vibration monitoring were then used to implement a prediction system of synthetic failure using machine learning methods such as: Medium Trees, Cubic SVN, Logistic Regression Kernel, Optimized Neural Network, and Bagged Trees, with the last demonstrating an accuracy of up to 0.87%.
Maximizing Energy Performance of University Campus Buildings through BIM Software and Multicriteria Optimization Methods
Authors: Tsantili Angeliki , Koronaki Irene , Polydoros Vasilis
Published: February 2023

University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s energy behavior can be simulated using software to identify the optimal strategies that result in energy savings. In this research, Autodesk Revit, Autodesk Insight, and Green Building Studio are among the programs utilized to examine the energy efficiency of the university building in four European cities. Following the development of several energy-saving scenarios for the building, the offered solutions are evaluated based on their annual energy consumption, energy costs, and CO2  emissions. Finally, multicriteria analysis techniques such as the AHP and PROMETHEE are applied to choose the best scenario for each instance. The study’s findings indicate that the ASHRAE Terminal Package Heat Pump scenario performed well in all of the cities examined, reducing yearly energy usage by 43.75% in Wien and annual energy costs by 47.31% in Mallorca. In comparison, the scenario utilizing a high-efficiency VAV system with a gas boiler and chiller came in last in all situations, resulting in a decrease of 12.67% in Mallorca’s annual energy usage and a reduction of 17.57% in Palermo’s annual energy expenses.
Perennial Grass Species for Bioenergy Production: The State of the Art in Mechanical Harvesting
Authors: Stefanoni Walter , Latterini Francesco , Pari Luigi
Published: February 2023

Future European strategies to reduce dependence on foreign markets for energy supply and energy production will rely on the further exploitation of the primary sector. Lignocellulosic feedstock for bioenergy production is a valuable candidate, and dedicated crops such as giant reed (Arundo donax L.), miscanthus (Miscanthus × giganteus), reed canary grass (Phalaris arundinacea L.), and switchgrass (Panicum virgatum L.) have been proven to be suitable for extensive cultivation on marginal lands. The present review aimed at providing a comprehensive picture of the mechanical strategies available for harvesting giant reed, miscanthus, reed canary grass, and switchgrass that are suitable for the possible upscaling of their supply chain. Since harvesting is the most impactful phase of a lignocellulosic supply chain in dedicated crops, the associated performance and costs were taken into account in order to provide concrete observations and suggestions for future implementation. The findings of the present review highlighted that the investigated species have a sufficient technology readiness level concerning mechanical harvesting for the upscaling of their cultivation. All the species could indeed be harvested with existing machinery, mostly derived from the context of haymaking, without compromising the work productivity.
Enhanced Control Designs to Abate Frequency Oscillations in Compensated Power System
Authors: Yousuf Saqib , Yousuf Viqar , Gupta Neeraj , Alharbi Talal , Alrumayh Omar
Published: February 2023

The interconnection of transmission, distribution, and generation lines has established a structure for the power system that is intricate. Uncertainties in the active power flow are caused by changes in load and a growing dependence on renewable energy sources. The study presented in this paper employs several controlling strategies to reduce frequency variations in series-compensated two-area power systems. Future power systems will require the incorporation of flexible AC transmission system (FACTS) devices, since the necessity for compensation in the power system is unavoidable. Therefore, a static synchronous series compensator (SSSC) is installed in both areas of our study to make it realistic and futuristic. This makes it easier to comprehend how series compensation works in a load–frequency model. With the integration of electrical vehicles (EVs) and solar photovoltaic (PV) systems, several control strategies are presented to reduce the frequency oscillations in this power system. Particle swarm optimization (PSO) is used to obtain the best PI control. To improve results, this work also covers the design of fuzzy logic control. In addition, the adoption of neural network control architecture is proposed for even better outcomes. The outcomes clearly show how well the proposed control techniques succeeded.
Advanced Technologies for Energy Storage and Electric Vehicles
Authors: Salkuti Surender Reddy
Published: February 2023

The demand for energy in the world has been growing rapidly [...]
A Novel Model for Spot Price Forecast of Natural Gas Based on Temporal Convolutional Network
Authors: Pei Yadong , Huang Chiou-Jye , Shen Yamin , Wang Mingyue
Published: February 2023

Natural gas is often said to be the most environmentally friendly fossil fuel. Its usage has increased significantly in recent years. Meanwhile, accurate forecasting of natural gas spot prices has become critical to energy management, economic growth, and environmental protection. This work offers a novel model based on the temporal convolutional network (TCN) and dynamic learning rate for predicting natural gas spot prices over the following two weekdays. The residual block structure of TCN provides good prediction accuracy, and the dilated causal convolutions minimize the amount of computation. The dynamic learning rate setting was adopted to enhance the model’s prediction accuracy and robustness. Compared with three existing models, i.e., the one-dimensional convolutional neural network (1D-CNN), gate recurrent unit (GRU), and long short-term memory (LSTM), the proposed model can achieve better performance over other models with mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean squared error (RMSE) scores of 4.965%, 0.216, and 0.687, respectively. These attractive advantages make the proposed model a promising candidate for long-term stability in natural gas spot price forecasting.
Efficient Virus-Induced Gene Silencing in Ilex dabieshanensis Using Tobacco Rattle Virus
Authors: Chong Xinran , Wang Yue , Xu Xiaoyang , Zhang Fan , Wang Chuanyong , Zhou Yanwei , Zhou Ting , Li Yunlong , Lu Xiaoqing , Chen Hong
Published: February 2023

Ilex dabieshanensis is not only an important ornamental plant, but can also be used to produce Kuding tea, owing to its lipid-lowering and anti-inflammatory medicinal properties. The genetic transformation of I. dabieshanensis is currently difficult, which restricts functional gene studies and molecular breeding research on this species. Virus-induced gene silencing (VIGS) is a powerful tool for determining gene functions in plants. The present study reports the first application of VIGS mediated by a tobacco rattle virus (TRV) vector in I. dabieshanensis. We tested the efficiency of the VIGS system to silence Mg-chelatase H subunit (ChlH) gene through agroinfiltration. The agroinfiltrated leaves of I. dabieshanensis exhibited a typical yellow-leaf phenotype of ChlH gene silencing at 21 days post infiltration. Endogenous ChlH expression levels in the leaves of yellow-leaf phenotype plants were all significantly lower than that in the leaves of mock-infected and control plants. Overall, our results indicated that the TRV-based VIGS system can efficiently silence genes in I. dabieshanensis, and this system will contribute to efficient functional genomics research in I. dabieshanensis.
In Vitro Studies on Rumen Fermentation and Methanogenesis of Different Microalgae and Their Effects on Acidosis in Dairy Cows
Authors: Sucu Ekin
Published: February 2023

Two in vitro studies were carried out on nonlactating dairy cows. Experiment 1 compared the methanogenesis and rumen fermentation parameters of various microalgae (Spirulina platensis, Chlorella vulgaris, and Schizochytrium spp.) and protein feeds (sunflower meal, soybean meal, and alfalfa hay) with monensin (MON). Rumen fermentation parameters were determined by an in vitro gas production system. Experiment 2 compared the ability of three microalgae to prevent acidosis. They were tested for 6 h against oat straw (100 mg) and MON (12 g/mL) to ameliorate ruminal acidosis caused by the addition of glucose (0.1 g/mL) as a fermentable carbohydrate with rumen fluid. In experiment 1, there were variations in the nutrient content of microalgae and protein sources. The dry matter content of the substrates ranged from 90 to 94%, and the organic matter content ranged from 82 to 88%, with Schizochytrium spp. having the highest. Protein content in algae and protein feeds ranged from 18–62% of dry matter (DM) to 16–48% DM, with S. platensis and C. vulgaris having the highest. The ether extract of Schizochytrium spp. (45.5% DM) was the highest of any substrate. In vitro rumen fermentation revealed that protein feeds increased the cumulative gas production at the highest level while MON caused a decrease. Ruminal pH was found to be higher in MON (6.95) and protein feeds (6.77–6.81) than in algae (6.37–6.50). In addition, in terms of metabolizable energy and digestible organic matter, protein feeds outperformed algae. The MON produced the least amount of methane (CH4) of any substrate, but Schizochytrium spp. demonstrated potential for CH4 reduction. In these groups, the decrease in CH4 production was accompanied by a decrease in total volatile fatty acids, acetate, and the acetate-to-propionate ratio, but an increase in propionate. Experiment 2 revealed MON as the most effective cure for controlling acidosis. However, C. vulgaris and Schizochytrium spp. had an effect on medium culture pH and demonstrated potential for acidosis prevention. This study found that algae can influence ruminal fermentation, have the potential to reduce CH4 production, and may reduce acidosis incidence rates. These assumptions, however, must be validated through in vivo studies.
Effects of Capsicum oleoresin Inclusion on Rumen Fermentation and Lactation Performance in Buffaloes (Bubalus bubalis) during Summer: In Vitro and In Vivo Studies
Authors: An Zhigao , Zhao Junwei , Zhang Xinxin , Gao Shanshan , Chen Chao , Niu Kaifeng , Nie Pei , Yao Zhiqiu , Wei Ke , Riaz Umair , Yang Liguo
Published: February 2023

This research aimed to evaluate the effects of Capsicum oleoresin (CAP) supplementation on rumen fermentation in vivo and In vitro, and lactation performance in buffaloes. In the experiment in vitro, 2 × 5 factorial design was carried out according to two temperatures (normal temperature: 39 °C; hyperthermal temperature: 42 °C) and five CAP concentrations (0 mg/L; 2 mg/L; 20 mg/L; 200 mg/L; 2000 mg/L). In the experiment in vivo, four multiparous mid-lactating Mediterranean buffaloes (body weight: 640.08 ± 17.90 kg) were randomly allocated to four treatments according to 4 × 4 Latin square design for CAP supplementation in four dosages (0 mg/kg, 10 mg/kg, 20 mg/kg, or 40 mg/kg of dry matter). The experiment’s results In vitro showed that hyperthermal temperature affected all fermentation characteristics measured in this research. CAP decreased the pH, short-chain fatty acids concentration, and percentages of propionate, butyrate, isobutyrate, valerate, and caproate, while increasing the percentage of acetate and the ratio of acetate to propionate at normal temperature (p ≤ 0.05). In the experiment in vivo, CAP decreased the percentage of propionate and quadratically affected acetate percentage in rumen fluid (p ≤ 0.05). CAP reduced rectal temperature and respiratory rates (p ≤ 0.05) and tended to increase dry matter intake quadratically (p ≤ 0.10). For lactation performance, CAP increased milk yield and milk lactose yield (p ≤ 0.05), and tended to increase milk protein yield (p ≤ 0.10). In conclusion, CAP modified rumen fermentation characteristics in vivo and In vitro and had beneficial effects on lactation performance in buffaloes during summer.
Bioconversion of Glycerol to 1,3-Propanediol Using Klebsiella pneumoniae L17 with the Microbially Influenced Corrosion of Zero-Valent Iron
Authors: Kong Da Seul , Kim Minsoo , Li Shuewi , Mutyala Sakuntala , Jang Min , Kim Changman , Kim Jung Rae
Published: February 2023

The bacterial redox state is essential for controlling the titer and yield of the final metabolites in most bioconversion processes. Glycerol conversion to 1,3-propanediol (PDO) requires a large amount of reducing equivalent and the expression of reductive pathways. Zero-valent iron (ZVI) was used in the glycerol bioconversion of Klebsiella pneumoniae L17. The level of 1,3-PDO production increased with the oxidation of ZVI (31.8 ± 1.2 vs. 25.7 ± 0.5, ZVI vs. no ZVI) while the cellular NADH/NAD+ level increased (0.6 vs. 0.3, ZVI vs. no ZVI). X-ray diffraction showed that the iron oxide (Fe2O3) was formed during glycerol fermentation. L17 obtained electrons from ZVI and dissolved the iron continuously to form cracks on the surface, suggesting microbially influenced corrosion (MIC) was involved on the surface of ZVI. The ZVI-implemented fermentation shifted bioconversion to a more glycerol-reductive pathway. The qPCR-presented glycerol dehydratase (DhaB) with ZVI implementation was strongly expressed compared to the control. These results suggest that ZVI can contribute to the biotransformation of PDO by inducing intracellular metabolic shifts. This study could also suggest a novel microbial fermentation strategy with the application of MIC.
Data Protection and Multi-Database Data-Driven Models
Authors: Jiang Lili , Torra Vicenç
Published: February 2023

Anonymization and data masking have effects on data-driven models. Different anonymization methods have been developed to provide a good trade-off between privacy guarantees and data utility. Nevertheless, the effects of data protection (e.g., data microaggregation and noise addition) on data integration and on data-driven models (e.g., machine learning models) built from these data are not known. In this paper, we study how data protection affects data integration, and the corresponding effects on the results of machine learning models built from the outcome of the data integration process. The experimental results show that the levels of protection that prevent proper database integration do not affect machine learning models that learn from the integrated database to the same degree. Concretely, our preliminary analysis and experiments show that data protection techniques have a lower level of impact on data integration than on machine learning models.
Blockchain-Enabled Chebyshev Polynomial-Based Group Authentication for Secure Communication in an Internet of Things Network
Authors: Singh Raman , Sturley Sean , Tewari Hitesh
Published: February 2023

The utilization of Internet of Things (IoT) devices in various smart city and industrial applications is growing rapidly. Within a trusted authority (TA), such as an industry or smart city, all IoT devices are closely monitored in a controlled infrastructure. However, in cases where an IoT device from one TA needs to communicate with another IoT device from a different TA, the trust establishment between these devices becomes extremely important. Obtaining a digital certificate from a certificate authority for each IoT device can be expensive. To solve this issue, a group authentication framework is proposed that can establish trust between group IoT devices owned by different entities. The Chebyshev polynomial has many important properties, semigroup is one of the most important. These properties make the Chebyshev polynomial a good candidate for the proposed group authentication mechanism. The secure exchange of information between trusted authorities is supported by Blockchain technology. The proposed framework was implemented and tested using Python and deployed on Blockchain using Ethereum’s Goerli’s testnet. The results show that the proposed framework can reasonably use Chebyshev polynomials with degrees up to four digits in length. The values of various parameters related to Blockchain are also discussed to understand the usability of the proposed framework.
Biogeography and Genetic Diversity of Terrestrial Mites in the Ross Sea Region, Antarctica
Authors: Collins Gemma E. , Young Monica R. , Convey Peter , Chown Steven L. , Cary S. Craig , Adams Byron J. , Wall Diana H. , Hogg Ian D.
Published: February 2023

Free-living terrestrial mites (Acari) have persisted through numerous glacial cycles in Antarctica. Very little is known, however, of their genetic diversity and distribution, particularly within the Ross Sea region. To redress this gap, we sampled mites throughout the Ross Sea region, East Antarctica, including Victoria Land and the Queen Maud Mountains (QMM), covering a latitudinal range of 72–85 °S, as well as Lauft Island near Mt. Siple (73 °S) in West Antarctica and Macquarie Island (54oS) in the sub-Antarctic. We assessed genetic diversity using mitochondrial cytochrome c oxidase subunit I gene sequences (COI-5P DNA barcode region), and also morphologically identified voucher specimens. We obtained 130 sequences representing four genera: Nanorchestes (n = 30 sequences), Stereotydeus (n = 46), Coccorhagidia (n = 18) and Eupodes (n = 36). Tree-based analyses (maximum likelihood) revealed 13 genetic clusters, representing as many as 23 putative species indicated by barcode index numbers (BINs) from the Barcode of Life Datasystems (BOLD) database. We found evidence for geographically-isolated cryptic species, e.g., within Stereotydeus belli and S. punctatus, as well as unique genetic groups occurring in sympatry (e.g., Nanorchestes spp. in QMM). Collectively, these data confirm high genetic divergence as a consequence of geographic isolation over evolutionary timescales. From a conservation perspective, additional targeted sampling of understudied areas in the Ross Sea region should be prioritised, as further diversity is likely to be found in these short-range endemic mites.
Evaluation of Genetic Testing in a Cohort of Diverse Pediatric Patients in the United States with Congenital Cataracts
Authors: Rossen Jennifer L. , Bohnsack Brenda L. , Zhang Kevin X. , Ing Alexander , Drackley Andy , Castelluccio Valerie , Ralay-Ranaivo Hanta
Published: February 2023

The aim of this study was to evaluate the diagnostic yield from prior genetic testing in a 20-year cohort of pediatric patients with congenital cataracts. A retrospective review of patients with congenital cataracts who underwent genetic testing was completed from 2003–2022. The diagnostic yield of the test was determined by variant classification and inheritance pattern. Variants from initial testing underwent reclassification in accordance with ACMG-AMP (American College of Medical Genetics and Genomics—American Association of Molecular Pathology) 2015 or 2020 ACMG CNV guidelines. A total of 95 variants were identified in 52 patients with congenital cataracts (42 bilateral, 10 unilateral); 42 % were White, 37% were Hispanic, 8% were Black, and 6% were Asian. The majority of patients (92%) did not have a family history of congenital cataracts but did have systemic illnesses (77%). Whole exome sequencing and targeted congenital cataract panels showed diagnostic yields of 46.2% and 37.5%, respectively. Microarray had the lowest yield at 11%. Compared to the initial classification, 16% (15 of 92 variants) had discrepant reclassifications. More testing is needed, and an increased focus is warranted in the field of ocular genetics on congenital cataracts, particularly in those with systemic illnesses and no family history, to advance our knowledge of this potentially blinding condition.
Relationship of Psychological Flexibility and Mindfulness to Caregiver Burden, and Depressive and Anxiety Symptoms in Caregivers of People with Dementia
Authors: Tan Khai Pin , Ang Jin Kiat , Koh Eugene Boon Yau , Pang Nicholas Tze Ping , Mat Saher Zanariah
Published: February 2023

Caregivers of People with dementia (PwD) commonly experience burdens and other mental health issues, e.g., depression and anxiety. At present, there are limited studies that examine the relationships between caregiver psychological factors and caregiver burden, and depressive and anxiety symptoms. Therefore, this study’s objectives were to examine the relationships between psychological flexibility and mindfulness in caregivers of PwD, and to determine the predictors of these three outcomes. This was a cross-sectional study conducted in the geriatric psychiatry clinic of Kuala Lumpur Hospital, Malaysia, and the sample (n = 82) was recruited via a universal sampling method over three months. The participants completed a questionnaire that consisted of the sociodemographics of the PwD and caregivers, illness characteristics of the PwD, Acceptance and Action Questionnaire-II (AAQ-II), Mindful Attention Awareness Scale (MAAS), Zarit Burden Interview Scale (ZBI), Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). The results show that despite significant relationships between psychological flexibility and mindfulness and lower levels of caregiver burden, and depressive and anxiety symptoms (p < 0.01), only psychological inflexibility (p < 0.01) remained as a significant predictor of the three outcomes. Therefore, in conclusion, intervention programs that target the awareness of the caregiver’s psychological inflexibility should be implemented to alleviate these adverse outcomes in dementia caregivers.
Trauma Characteristics Associated with E-Scooter Accidents in Switzerland—A Case Series Study
Authors: Bracher Ava Insa , Klingler Samuel , Koba Sabine , Jakob Dominik Andreas , Exadaktylos Aristomenis , Klukowska-Rötzler Jolanta , Burkhard John-Patrik
Published: February 2023

E-scooters have gained popularity worldwide in the last few years. Due to the increase in users, more accidents related to e-scooters can be observed. The present study aimed to analyse epidemiological data, characteristics, and severity of injuries in patients admitted to a Level I trauma centre in Switzerland (Inselspital Bern, University Hospital Bern) after accidents associated with e-scooters. This retrospective case series evaluated 23 patients who presented to the University Hospital of Bern between 1 of May 2019 and 31 of October 2021 after an e-scooter accident. Data were collected on patient demographics, time and cause of the accident, speed, alcohol consumption, helmet use, type and localisation of injury, number of injuries per patient, and outcome. Men were most frequently affected (61.9%). The mean age was 35.8 (STD 14.8) years. Slightly more than half (52.2%) of all accidents were self-inflicted. Most accidents were reported during the night (7 p.m. to 7 a.m., 60.9%) and in summer (43.5%). Alcohol consumption was reported in 43.5% of cases, with a mean blood alcohol level of 1.4 g/l. Most injuries were observed in the face (25.3%) and head/neck area (20.25%). Skin abrasions (56.5%) and traumatic brain injury (43.5%) were the most common types of traumata in terms of total number of patients. Only in one case it was reported that a protective helmet had been worn. Five patients required hospitalisation and four patients underwent surgery. Three patients underwent emergency orthopaedic surgery, and one patient underwent emergency neurosurgery. E-scooter accidents result in a significant number of facial and head/neck injuries. E-scooter riders would potentially benefit from a helmet to protect them in the event of an accident. Additionally, the results of this study indicate that a significant number of e-scooter accidents in Switzerland occurred under the influence of alcohol. Prevention campaigns to raise awareness of the risks of driving e-scooters under the influence of alcohol could help prevent future accidents.
Technological, Ecological, and Energy-Economic Aspects of Using Solidified Carbon Dioxide for Aerobic Granular Sludge Pre-Treatment Prior to Anaerobic Digestion
Authors: Kazimierowicz Joanna , Dębowski Marcin , Zieliński Marcin
Published: February 2023

The technology of aerobic granular sludge (AGS) seems prospective in wastewater bio-treatment. The characteristics as well as compactness and structure of AGS have been proved to significantly affect the effectiveness of thus far deployed methods for sewage sludge processing, including anaerobic digestion (AD). Therefore, it is deemed necessary to extend knowledge on the possibilities of efficient AGS management and to seek viable technological solutions for methane fermentation of sludge of this type, including by means of using the pre-treatment step. Little is known about the pre-treatment method with solidified carbon dioxide (SCO2), which can be recovered in processes of biogas upgrading and enrichment, leading to biomethane production. This study aimed to determine the impact of AGS pre-treatment with SCO2 on the efficiency of its AD. An energy balance and a simplified economic analysis of the process were also carried out. It was found that an increasing dose of SCO2 applied in the pre-treatment increased the concentrations of COD, N-NH4+, and P-PO43− in the supernatant in the range of the SCO2/AGS volume ratios from 0.0 to 0.3. No statistically significant differences were noted above the latter value. The highest unit yields of biogas and methane production, reaching 476 ± 20 cm3/gVS and 341 ± 13 cm3/gVS, respectively, were obtained in the variant with the SCO2/AGS ratio of 0.3. This experimental variant also produced the highest positive net energy gain, reaching 1047.85 ± 20 kWh/ton total solids (TS). The use of the higher than 0.3 SCO2 doses was proved to significantly reduce the pH of AGS (below 6.5), thereby directly diminishing the percentage of methanogenic bacteria in the anaerobic bacterial community, which in turn contributed to a reduced CH4 fraction in the biogas.
Cross-Sectional Analysis of Family Factors Associated with Lifestyle Habits in a Sample of Italian Primary School Children: The I-MOVE Project
Authors: Sanmarchi Francesco , Masini Alice , Poli Carolina , Kawalec Anna , Esposito Francesco , Scrimaglia Susan , Scheier Lawrence M. , Dallolio Laura , Sacchetti Rossella
Published: February 2023

The acquisition of healthy dietary and exercise habits during childhood is essential for maintaining these behaviors during adulthood. In early childhood, parents have a profound influence on a child’s lifestyle pursuits, serving as both role models and decision-makers. The present study examines family factors as potential contributors to healthy lifestyle habits and their child’s overall diet quality among a sample of primary school children. A secondary aim is to evaluate several aspects of diet quality using the Mediterranean adaptation of the Diet Quality Index-International (DQI-I). This cross-sectional study involved 106 children enrolled in a primary school located in Imola, Italy. Data were collected from October to December 2019 using an interactive tool used to assess parent characteristics, children’s lifestyle, food frequency (ZOOM-8 questionnaire), and actigraph accelerometers to capture children’s physical activity and sedentary behavior. Adherence to the Mediterranean Diet (expressed by KIDMED Index) was positively associated with fathers’ educational level, parental sport participation, and the parent’s overall nutritional knowledge. Higher mothers’ educational level was inversely associated with children’s leisure screen time. Parents’ nutritional knowledge was positively related to children’s average daily minutes of organized sport activities. The better score for DQI-I was for consumption adequacy, followed by variety and moderation. The lowest score was for overall balance. The present study reinforces the importance of family factors in young children’s lifestyle choices, particularly their dietary, leisure time, and exercise habits.
A Scoping Review of the Factor Associated with Older Adults’ Mobility Barriers
Authors: Che Had Nur Hasna , Alavi Khadijah , Md Akhir Noremy , Muhammad Nur Irina Riyanti , Shuhaimi Muhammad Shakir Zufayri , Foong Hui Foh
Published: February 2023

The phenomenon of ageing may contribute to the rise of the dependent population. Due to the obstacles and difficulties they confront, the elderly’s mobility decreases significantly. The aim of this article is to identify factors associated with mobility barriers in older adults. The method employed is an examination of articles published between 2011 and 2022 to identify common themes in previous studies. Four search engines were being used, and 32 articles have been included. This study demonstrated that health is a major factor associated with decreased mobility. This review identified four types of barriers which are health, built environment, socio-economic background and social relation change. This review could help policy makers and gerontologist in identifying solutions to resolve the mobility issues in older people.
A Systematic Review on Food Recommender Systems for Diabetic Patients
Authors: Yera Raciel , Alzahrani Ahmad A. , Martínez Luis , Rodríguez Rosa M.
Published: February 2023

Recommender systems are currently a relevant tool for facilitating access for online users, to information items in search spaces overloaded with possible options. With this goal in mind, they have been used in diverse domains such as e-commerce, e-learning, e-tourism, e-health, etc. Specifically, in the case of the e-health scenario, the computer science community has been focused on building recommender systems tools for supporting personalized nutrition by delivering user-tailored foods and menu recommendations, incorporating the health-aware dimension to a larger or lesser extent. However, it has been also identified the lack of a comprehensive analysis of the recent advances specifically focused on food recommendations for the domain of diabetic patients. This topic is particularly relevant, considering that in 2021 it was estimated that 537 million adults were living with diabetes, being unhealthy diets a major risk factor that leads to such an issue. This paper is centered on presenting a survey of food recommender systems for diabetic patients, supported by the PRISMA 2020 framework, and focused on characterizing the strengths and weaknesses of the research developed in this direction. The paper also introduces future directions that can be followed in the next future, for guaranteeing progress in this necessary research area.
Analysis of Carbon Emission Projections and Reduction Potential of Resource-Dependent Urban Agglomerations from the Perspective of Multiple Scenarios—A Case Study of Hu-Bao-O-Yu Urban Agglomeration
Authors: Ning Xuanwei , He Yushuang , Zhang Jiayi , Wu Chengliang , Zhang Yang
Published: February 2023

The Hu-Bao-O-Yu urban agglomeration is an important energy exporting and high-end chemical base in China, and is an important source of carbon emissions in China. The early achievement of peak carbon emissions in this region is particularly crucial to achieving the national carbon emission reduction targets. However, there is a lack of multi-factor system dynamics analysis of resource-dependent urban agglomerations in Northwest China, as most studies have focused on single or static aspects of developed urban agglomerations. This paper analyses the relationship between carbon emissions and their influencing factors, constructs a carbon emission system dynamics model for the Hu-Bao-O-Yu urban agglomeration, and sets up different single regulation and comprehensive regulation scenarios to simulate and predict the carbon peak time, peak value, and emission reduction potential of each city and urban agglomeration under different scenarios. The results show that: (1) Hohhot and Baotou are expected to reach peak carbon by 2033 and 2031 respectively, under the baseline scenario, while other regions and the urban agglomeration will not be able to reach peak carbon by 2035. (2) Under single regulation scenarios, the effect of factors other than the energy consumption varies across cities, but the energy consumption and environmental protection input are the main factors affecting carbon emissions in the urban agglomeration. (3) A combination of the economic growth, industrial structure, energy policy, environmental protection, and technology investment is the best measure to achieve carbon peaking and enhance the carbon emission reduction in each region as soon as possible. In the future, we need to coordinate the economic development, energy structure optimisation and transformation, low-carbon transformation of industry, strengthen research on carbon sequestration technology, and further increase the investment in environmental protection to make the Hu-Bao-O-Yu urban agglomeration a resource-saving urban agglomeration with an optimal emission reduction.
Variation in Global Policy Responses to COVID-19: A Bidirectional Analysis
Authors: Wang Caixia , Li Huijie
Published: February 2023

Against the unprecedented outbreaks of the COVID-19 variants, countries have introduced restrictive measures with discretion, ranging from lifting the closure thoroughly to implementing stringent policies, but all together guarding the global public health. Under the changing circumstances, we firstly apply the panel data vector autoregression (PVAR) model, using a sample of 176 countries/territories from 15 June 2021 to 15 April 2022, to estimate the potential associations among the policy responses, the progression of COVID-19 in deaths and vaccination, and medical resources possessed. Furthermore, we use the random effect method and the fixed effect speculation, to examine the determinants of policy variances across regions and over time. Our work has four main findings. Firstly, it showed the existence of a bidirectional relationship between the policy stringency and variables of interest including new daily deaths, the fully vaccinated percentage and health capacity. Secondly, conditional on the availability of vaccines, the sensitivity of policy responses to the death numbers tends to decline. Thirdly, the role of health capacity matters in coexisting with the virus mutation. Fourthly, regarding the variance in policy responses over time, the impact of new deaths tends to be seasonal. As to geographical differences in policy responses, we present the analysis for Asia, Europe, and Africa, and they show different levels of dependencies on the determinants. These findings suggest that bidirectional correlations exist in the complex context of wrestling with the COVID-19, as government interventions exert influence on the virus spread, the policy responses also progress alongside multiple factors evolving in the pandemic. This study will help policymakers, practitioners, and academia to formulate a comprehensive understanding of the interactions between policy responses and the contextualized implementation factors.
Perinatal Depression and Anxiety Symptoms, Parental Bonding and Dyadic Sensitivity in Mother–Baby Interactions at Three Months Post-Partum
Authors: Della Vedova Anna Maria , Santoniccolo Fabrizio , Sechi Cristina , Trombetta Tommaso
Published: February 2023

The quality of the early parent–infant relationship is crucial for the child’s optimal development, and parental sensitivity plays a key role in early interactions. The purpose of the study was to evaluate the influence of maternal perinatal depression and anxiety symptoms on dyadic sensitivity at three months post-partum, also considering a large set of maternal and infant variables. At the third trimester of pregnancy (T1) and at three months postpartum (T2), 43 primiparous women filled in a set of questionnaires evaluating symptoms of depression (CES-D) or anxiety (STAI), the woman’s parental bonding experiences (PBI), alexithymia (TAS-20), maternal attachment to the baby (PAI, MPAS) and the perceived social support (MSPSS). At T2 mothers also completed a questionnaire on infant temperament and took part in the CARE-Index videotaped procedure. Dyadic sensitivity was predicted by higher maternal trait anxiety scores in pregnancy. In addition, the mother’s experience of being cared for by her father in childhood was predictive of her infant’s lower compulsivity, while paternal overprotection predicted higher unresponsiveness. The results highlight the influence of perinatal maternal psychological well-being and maternal childhood experiences on the quality of the dyadic relationship. The results may be useful to foster mother–child adjustment during the perinatal period.
Evolutionary Game Analysis of Behavior Strategies of Multiple Stakeholders in an Elderly Care Service System
Authors: Zhang Zhiyong , Song Xiaodie , Shi Yongqiang
Published: February 2023

As the aging of Chinese society continues to deepen, it is particularly important for the development of the national elderly care service industry to further strengthen the government’s supervision of private pension institutions and improve their management awareness of standardized operations. The strategic behaviors among the participants of senior care service regulation have not been well studied yet. In the process of senior care service regulation, there is a certain game association among three stakeholders, namely, government departments, private pension institutions, and the elderly. This paper firstly constructs an evolutionary game model including the above three subjects and analyzes the evolutionary path of strategic behaviors of each subject and the evolutionary stabilization strategy of the system. On this basis, the feasibility of the evolutionary stabilization strategy of the system is further verified through simulation experiments, and the effects of different initial conditions and key parameters on the evolutionary process and results are discussed. The research results show that (1) There are four ESSs in the pension service supervision system, and revenue is the decisive factor that affects the evolution of the stakeholders’ strategy. (2) The final evolution result of the system is not necessarily related to the initial strategy value of each agent, but the size of the initial strategy value will affect the rate of each agent’s evolution to a stable state. (3) The increase in the success rate of government regulation, subsidy coefficient and punishment coefficient, or the reduction in the cost of regulation and the fixed subsidy for the elderly can effectively promote the standardized operation of private pension institutions, but the large additional benefits will lead to their tendency to operate in violation of regulations. The research results can provide reference and a basis for government departments to formulate the regulation policy for elderly care institutions.
Association between Health-Related Quality of Life and Access to Chronic Disease Management by Primary Care Facilities in Mainland China: A Cross-Sectional Study
Authors: Wang Yang , Wu Yibo , Chu Hongling , Xu Zhijie , Sun Xinying , Fang Hai
Published: February 2023

The integration of chronic disease management (CDM) services into the essential public health services offered by primary care facilities has been a major strategy in China’s healthcare reform since 2009. We aimed to measure the percentage of patients with chronic diseases in China who believed that they could easily obtain CDM services at a nearby primary care facility in mainland China and determine its association with the EQ visual analog scale (EQ-VAS) score and the utility index of the 5-level EQ-5D version (EQ-5D-5L). A cross-sectional survey was conducted nationwide between 20 June 2022 and 31 August 2022, involving 5525 patients with chronic diseases from 32 provincial-level administrative divisions, of which 48.1% (n = 2659) were female with a median age of 55.0 years. The median EQ-VAS score was 73.0 and the utility index of the EQ-5D-5L was 0.942. A majority of patients reported definite (24.3%) or mostly (45.9%) easy access to CDM services from nearby primary care facilities. Multivariable logistic regression analysis revealed that easy access to CDM services in primary care facilities was positively associated with higher HRQoL. Our findings indicate that, as of 2022, approximately 70% of patients with chronic diseases in mainland China had easy access to CDM services provided by primary care facilities, which was significantly and positively associated with their health status.