bluuebunny/crossref_metadata_2025 huggingface dataset:
Cell Type-Specific Pherophorins of Volvox carteri Reveal Interplay of Both Cell Types in ECM Biosynthesis
Authors: von der Heyde Benjamin , Hallmann Armin
Published: December 2022

The spheroidal green algae Volvox carteri serves as a model system to investigate the formation of a complex, multifunctional extracellular matrix (ECM) in a relatively simple, multicellular organism with cell differentiation. The V. carteri ECM is mainly composed of hydroxyproline-rich glycoproteins (HRGPs) and there are diverse region-specific, anatomically distinct structures in the ECM. One large protein family with importance for ECM biosynthesis stands out: the pherophorins. The few pherophorins previously extracted from the ECM and characterized, were specifically expressed by somatic cells. However, the localization and function of most pherophorins is unknown. Here, we provide a phylogenetic analysis of 153 pherophorins of V. carteri and its unicellular relative Chlamydomonas reinhardtii. Our analysis of cell type-specific mRNA expression of pherophorins in V. carteri revealed that, contrary to previous assumptions, only about half (52%) of the 102 investigated pherophorin-related genes show stronger expression in somatic cells, whereas about one-third (34%) of the genes show significant higher expression in reproductive cells (gonidia). We fused two pherophorin genes that are expressed by different cell types to yfp, stably expressed them in Volvox and studied the tagged proteins by live-cell imaging. In contrast to earlier biochemical approaches, this genetic approach also allows the in vivo analysis of non-extractable, covalently cross-linked ECM proteins. We demonstrate that the soma-specific pherophorin SSG185 is localized in the outermost ECM structures of the spheroid, the boundary zone and at the flagellar hillocks. SSG185:YFP is detectable as early as 1.5 h after completion of embryogenesis. It is then present for the rest of the life cycle. The gonidia-specific pherophorin PhG is localized in the gonidial cellular zone 1 (“gonidial vesicle”) suggesting its involvement in the protection of gonidia and developing embryos until hatching. Even if somatic cells produce the main portion of the ECM of the spheroids, ECM components produced by gonidia are also required to cooperatively assemble the total ECM. Our results provide insights into the evolution of the pherophorin protein family and convey a more detailed picture of Volvox ECM synthesis.
Identification of a Novel N7-Methylguanosine-Related LncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma and Experiment Verification
Authors: Yang Chou , Zhang Lingyan , Hao Xin , Tang Mengdie , Zhou Bin , Hou Jinlin
Published: December 2022

(1) Background: It is well-known that long non-coding RNAs (lncRNAs) and N7-methylguanosine (m7G) contribute to hepatocellular carcinoma (HCC) progression. However, it remains unclear whether lncRNAs regulating m7G modification could predict HCC prognosis. Thus, we sought to explore the prognostic implications of m7G-related lncRNAs in HCC patients. (2) Methods: Prognostic M7G-related lncRNAs obtained from The Cancer Genome Atlas (TCGA) database were screened by co-expression analysis and univariate Cox regression analysis. Next, the m7G-related lncRNA signature (m7GRLSig) was conducted by Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analysis. Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC) assessed the prognostic abilities of our signature. Univariate and multivariate Cox regression, nomogram, and principal component analysis (PCA) were conducted to evaluate our signature. Subsequently, we investigated the role of m7GRLSig on the immune landscape and sensitivity to drugs in HCC patients. The potential function of lncRNAs obtained from the prognostic signature was explored by in vitro experiments. (3) Results: A novel m7GRLSig was identified using seven meaningful lncRNA (ZFPM2-AS1, AC092171.2, PIK3CD-AS2, NRAV, CASC19, HPN-AS1, AC022613.1). The m7GLPSig exhibited worse survival in the high-risk group and served as an independent prognostic factor. The m7GRLSig stratification was sensitive in assessing the immune landscape and sensitivity to drugs between the high-risk and low-risk groups. Finally, in vitro experiments confirmed that the knockdown of NRAV was accompanied by the downregulation of METTL1 during HCC progression. (4) Conclusions: The m7G-related signature is a potential predictor of HCC prognosis and contributes to individualize the effective drug treatment of HCC.
Community Structure in an Isolated Tropical Forest Biome: One Year of Fruit-Feeding Butterfly Trapping in Four Habitats in the Western Ghats, India
Authors: Das Karumampoyil Sakthidas Anoop , Radhamany Dhanya , Molleman Freerk
Published: December 2022

Insect communities in tropical forests tend to be structured vertically and with respect to tree fall gaps and edges. Furthermore, insect communities vary over time. Insight into such habitat specificity and temporal variation is needed to design and interpret biodiversity surveys and to compare conservation value among habitats. Some aspects of tropical insect community structure, such as the proportion of canopy specialists and temporal variation, vary among biogeographical regions and climatic zones. To date, few regions have been sampled systematically, so generalization remains difficult. We compared fruit-feeding butterfly communities among understory, canopy, natural treefalls, and forest edge, in a tropical forest of the Western Ghats, a strip of rainforest that is isolated from Sundaland, the large rainforest block of South-East Asia. During a yearlong study, we captured 3018 individuals belonging to 32 species and representing 14 genera. While some butterflies were captured in the canopy, no species was significantly more abundant in the canopy than in the understory. This observation was contrary to studies elsewhere in the tropics where 14–55% of the species could be classified as canopy specialists. Even though the largest number of species was captured at forest edges, species diversity was highest in the gaps. The communities at the forest edge differed importantly from those in treefall gaps: at the forest edge, we caught grassland species in addition to the forest species. Larger treefall gaps had higher butterfly abundance than smaller gaps. Both abundance and diversity peaked during the late monsoon season, and all common species in our sample also peaked during this period. The spatiotemporal community structure appears to depend on biogeography (less vertical stratification further from large forest blocks) and climate (more synchrony among species in seasonal abundance when there is a more severe dry season).
Mediterranean Matters: Revision of the Family Onchidorididae (Mollusca, Nudibranchia) with the Description of a New Genus and a New Species
Authors: Furfaro Giulia , Trainito Egidio , Fantin Marco , D’Elia Marcella , Madrenas Enric , Mariottini Paolo
Published: December 2022

The Mediterranean Sea hosts a great Nudibranchia diversity and has proved to be particularly intriguing in the case of the family Onchidorididae, a group of dorid nudibranchs that lately increased its diversity with the addition of one recently described Mediterranean species. The Onchidorididae family has a troubled systematic history to date, characterized by uncertainties and genera that are considered valid or not, according to the different authors. This confused taxonomy reflects the lack of a broad and comprehensive view on the phylogenetic relationships occurring between Onchidorididae members, an incorrect interpretation of the diagnostic morphological characters, and a poor knowledge of important biological aspects characterizing the different genera included in the family. To shed some light on the systematics of Onchidorididae, an integrative taxonomic revision was carried out involving morphological, ecological, and molecular analyses on an updated dataset. Mediterranean specimens and species were added to the dataset of the already known Onchidorididae and a new species from the Adriatic Sea (Central Mediterranean Sea) is described here. Furthermore, historical controversies are clarified due to the discovery of new important synapomorphies useful to define genera belonging to the Onchidorididae family and to describe a new genus. Finally, the taxonomic status of all the known Onchidorididae species is investigated and discussed, filling the gap of knowledge on neglected species.
Antimicrobial Susceptibility Data for Six Lactic Acid Bacteria Tested against Fifteen Antimicrobials
Authors: Nikodinoska Ivana , Heikkinen Jouni , Moran Colm A.
Published: December 2022

Antimicrobial resistance is a rising threat in the agrifood sector. The misuse of antibiotics exerts selective pressure, driving resistance mechanisms in bacteria, which could ultimately spread through many routes and render treatments for infectious diseases inefficient in humans and animals. Herein, we report antimicrobial susceptibility data obtained for six lactic acid bacteria, the members of which are commonly used in the food and feed chain. Fifteen antimicrobials were considered for the phenotypic testing: ampicillin, gentamicin, kanamycin, tetracycline, erythromycin, clindamycin, chloramphenicol, streptomycin, vancomycin, quinupristin-dalfopristin, bacitracin, sulfamethoxazole, ciprofloxacin, linezolid, and rifampicin. The reported dataset could be used for the comparison, generation, and reconsideration of new and/or existing cut-off values when considering lactic acid bacteria, particularly lactobacilli and pediococci.
Natural Language Processing to Extract Information from Portuguese-Language Medical Records
Authors: da Rocha Naila , Barbosa Abner , Schnr Yaron , Machado-Rugolo Juliana , de Andrade Luis , Corrente José , de Arruda Silveira Liciana
Published: December 2022

Studies that use medical records are often impeded due to the information presented in narrative fields. However, recent studies have used artificial intelligence to extract and process secondary health data from electronic medical records. The aim of this study was to develop a neural network that uses data from unstructured medical records to capture information regarding symptoms, diagnoses, medications, conditions, exams, and treatment. Data from 30,000 medical records of patients hospitalized in the Clinical Hospital of the Botucatu Medical School (HCFMB), São Paulo, Brazil, were obtained, creating a corpus with 1200 clinical texts. A natural language algorithm for text extraction and convolutional neural networks for pattern recognition were used to evaluate the model with goodness-of-fit indices. The results showed good accuracy, considering the complexity of the model, with an F-score of 63.9% and a precision of 72.7%. The patient condition class reached a precision of 90.3% and the medication class reached 87.5%. The proposed neural network will facilitate the detection of relationships between diseases and symptoms and prevalence and incidence, in addition to detecting the identification of clinical conditions, disease evolution, and the effects of prescribed medications.
Screening for Liver Fibrosis in the General Population: Where Do We Stand in 2022?
Authors: Canivet Clémence M. , Boursier Jérôme
Published: December 2022

Approximately 30% of the worldwide population has at least one risk factor for liver disease. Identifying advanced liver disease before the occurrence of complications remains a difficult challenge in clinical practice, where diagnosis comes too late for many patients, at the time of liver decompensation or palliative hepatocellular carcinoma, with poor short-term prognosis. Noninvasive, blood- or elastography-based tests of liver fibrosis (NITs) have been developed for the early diagnosis of advanced liver fibrosis. Recent population-based studies evaluating the screening of liver fibrosis with these NITs have provided important information on at-risk groups that should be targeted. New measures based on the sequential use of NITs help to better organize the referral of at-risk patients to the liver specialist. However, energizing these measures will require increased awareness of both chronic liver diseases and the use of NITs among non-specialists.
Design and Construct Validity of a Postural Control Test for Pre-Term Infants
Authors: Kniaziew-Gomoluch Katarzyna , Szopa Andrzej , Kidoń Zenon , Siwiec Andrzej , Domagalska-Szopa Małgorzata
Published: December 2022

A review of the literature indicated that the greatest prognostic value for predicting motor impairment in high-risk infants is the absence of fidgety movements (FMs) at 3 months of post-term age. The purpose of the present study was to characterize a new posturometric test (PT) based on a center-of-pressure (CoP) movement analysis, in terms of design and construct validity, for the detection of postural control disturbances in pre-term infants. The comparative studies were carried out between pre-term infants who presented normal FMs (18 participants) and infants with absent FMs (19 participants), which consisted of the analysis of the CoP trajectory and CoP area in supine and prone positions using the force platform. New PT was performed simultaneously with GMs recorded using a force platform. Statistical analyses revealed significant differences between the groups of infants who presented absent FMs and normal FMs for almost all CoP parameters describing spontaneous sway in the supine position. Based on these preliminary results, it can be concluded, that the application of PT based on the analysis of CoP trajectory, area, and velocity in the supine position has been demonstrated to be valid for the detection of postural control disturbances in pre-term infants.
Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers
Authors: Moramarco Graziano
Published: December 2022

We propose an approach for jointly measuring global macroeconomic uncertainty and bilateral spillovers of uncertainty between countries using a global vector autoregressive (GVAR) model. Over the period 2000Q1–2020Q4, our global index is able to summarize a variety of uncertainty measures, such as financial-market volatility, economic-policy uncertainty, survey-forecast-based measures and econometric measures of macroeconomic uncertainty, showing major peaks during both the global financial crisis and the COVID-19 pandemic. Global spillover effects are quantified through a novel GVAR-based decomposition of country-level uncertainty into the contributions from all countries in the global model. We show that this approach produces estimates of uncertainty spillovers which are strongly related to the structure of the global economy.
A Novel Approach for Classifying Brain Tumours Combining a SqueezeNet Model with SVM and Fine-Tuning
Authors: Rasool Mohammed , Ismail Nor Azman , Al-Dhaqm Arafat , Yafooz Wael M. S. , Alsaeedi Abdullah
Published: December 2022

Cancer of the brain is most common in the elderly and young and can be fatal in both. Brain tumours can heal better if they are diagnosed and treated quickly. When it comes to processing medical images, the deep learning method is essential in aiding humans in diagnosing various diseases. Classifying brain tumours is an essential step that relies heavily on the doctor’s experience and training. A smart system for detecting and classifying these tumours is essential to aid in the non-invasive diagnosis of brain tumours using MRI (magnetic resonance imaging) images. This work presents a novel hybrid deep learning CNN-based structure to distinguish between three distinct types of human brain tumours through MRI scans. This paper proposes a method that employs a dual approach to classification using deep learning and CNN. The first approach combines the unsupervised classification of an SVM for pattern classification with a pre-trained CNN (i.e., SqueezeNet) for feature extraction. The second approach combines the supervised soft-max classifier with a finely tuned SqueezeNet. To evaluate the efficacy of the suggested method, MRI scans of the brain were used to analyse a total of 1937 images of glioma tumours, 926 images of meningioma tumours, 926 images of pituitary tumours, and 396 images of a normal brain. According to the experiment results, the finely tuned SqueezeNet model obtained an accuracy of 96.5%. However, when SqueezeNet was used as a feature extractor and an SVM classifier was applied, recognition accuracy increased to 98.7%.
Beyond Benchmarks: Spotting Key Topical Sentences While Improving Automated Essay Scoring Performance with Topic-Aware BERT
Authors: Wu Yongchao , Henriksson Aron , Nouri Jalal , Duneld Martin , Li Xiu
Published: December 2022

Automated Essay Scoring (AES) automatically allocates scores to essays at scale and may help teachers reduce the heavy burden during grading activities. Recently, researchers have deployed neural-based AES approaches to improve upon the state-of-the-art AES performance. These neural-based AES methods mainly take student essays as the sole input and focus on learning the relationship between student essays and essay scores through deep neural networks. However, their only product, the predicted holistic score, is far from providing adequate pedagogical information, such as automated writing evaluation (AWE). In this work, we propose Topic-aware BERT, a new method of learning relations among scores, student essays, as well as topical information in essay instructions. Beyond improving the AES benchmark performance, Topic-aware BERT can automatically retrieve key topical sentences in student essays by probing self-attention maps in intermediate layers. We evaluate the performance of Topic-aware BERT of different variants to (i) perform AES and (ii) retrieve key topical sentences using the open dataset Automated Student Assessment Prize and a manually annotated dataset. Our experiments show that Topic-aware BERT achieves a strong AES performance compared with the previous best neural-based AES methods and demonstrates effectiveness in identifying key topical sentences in argumentative essays.
Dielectric Performance of Natural- and Synthetic-Ester-Based Nanofluids with Fullerene Nanoparticles
Authors: Šárpataky Miloš , Kurimský Juraj , Rajňák Michal , Krbal Michal , Adamčák Marek
Published: December 2022

According to the latest research, nanofluids as a possible future substitution for high-voltage equipment insulation have the potential to enhance the heat transfer and insulation properties of their base fluids. Dielectric properties are represented by breakdown strength (AC, DC, lightning) and dielectric performance as a set of quantities including dissipation factor, permittivity, and volume resistivity. In this study, natural and synthetic esters were mixed with C60 nanoparticles. Samples were examined for dissipation factor, relative permittivity, and volume resistivity at temperatures between 25 °C and 140 °C to monitor changes in dielectric performance with rising temperature, in accordance with IEC 60247. In addition, the samples were tested for AC breakdown voltage (using mushroom-like electrodes with a gap distance of 1 mm) and evaluated using the Weibull distribution statistical method. These measurements allowed complex evaluation of the examined mixtures and the determination of optimal concentration for each ester-based nanofluid.
Study on the Effect of the Water Injection Rate on the Cavern Leaching Strings of Salt Cavern Gas Storages
Authors: Dong Shengwei , Fang Taian , Wan Jifang , Hu Xuhui , Li Jingcui , Liu Hangming , Li Dongyang , Qiao Shaofeng
Published: December 2022

In the early construction of cavern leaching in salt cavern gas storages, the inner leaching tubing is often blocked, frequently leading to the bending deformation phenomenon of the leaching strings, which can result in out-of-control cavity shapes. It is difficult to monitor the stress, vibration, and morphological changes of the inner tube during the construction of a cavity. There are few research results in this field at home and abroad, and they are limited only to preliminary explorations of the mechanism or summaries and speculation of the field operation. In this paper, an experimental device for testing the dynamic characteristics of salt cavern leaching strings is developed based on the similarity principle. The device is used to simulate two types of operation processes, i.e., the direct and reverse circulation leaching processes. The experimental data are processed using the modal analysis method to obtain the vibration characteristic parameters of the inner leaching tubing in the circulation process with identical flow rates inside the tubing and the annular region. The following main conclusions can be drawn: The circulation mode has no significant effect on the vibration frequency of cavern leaching strings. The deformation characteristics of cavern leaching strings during direct and reverse circulation are identical, featuring maximum deformation at the bottom and minimum deformation in the middle. The maximum deformation of cavern leaching strings during reverse circulation is about 1.5 times that during direct circulation. Through an experimental investigation and analysis, the effects of the water injection rate and the cavern leaching method on the vibration frequency and bending deformation of cavern leaching strings was determined, providing a reference for further solving the bending problem of cavern leaching strings in combination with engineering practice.
Renewable Energies in the Agricultural Sector: A Perspective Analysis of the Last Three Years
Authors: Hernandez-Escobedo Quetzalcoatl , Muñoz-Rodríguez David , Vargas-Casillas Alejandro , Juárez Lopez José Manuel , Aparicio-Martínez Pilar , Martínez-Jiménez María Pilar , Perea-Moreno Alberto-Jesus
Published: December 2022

Renewable energy arises as a tool for the supply of energy to the agriculture sector. Currently, there is a growing concern for the environment. This circumstance has led to technological progress in energy use in relation to natural resources and their availability for all productive sectors, including agriculture. The main objective of this work is to perform analysis from a bibliometric point of view and to analyze scientific advances in renewable energy and agriculture worldwide that have occurred in the last three years (2019–2021). The purpose of this study is to provide an overview of the last three years on the topic in order to contribute to the international scientific community, specifically towards collaboration between authors, institutions, and countries. A keyword analysis using community detection was applied to detect the five main clusters of this research and was largely dedicated to the following topics: renewable energy technologies in agriculture, bioenergy, sustainable agriculture, biomass energy, and the environmental impact of agriculture. The main countries found to be conducting research on renewable energy and agriculture include India, China, the United States, Italy, the United Kingdom, Poland, Indonesia, Germany, the Russian Federation, and Spain; the most important institutions conducting research in this area include the Ministry of Agriculture of the People’s Republic of China, the Tashkent Institute of Irrigation and Agricultural Mechanization Engineers at the National Research University in Uzbekistan, the Chinese Academy of Agricultural Sciences, and the Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento in Portugal. These results may contribute to the identification of new research needs and therefore to the development of future directions of research on renewable energies in the agricultural sector.
Applications of Artificial Intelligence Algorithms in the Energy Sector
Authors: Szczepaniuk Hubert , Szczepaniuk Edyta Karolina
Published: December 2022

The digital transformation of the energy sector toward the Smart Grid paradigm, intelligent energy management, and distributed energy integration poses new requirements for computer science. Issues related to the automation of power grid management, multidimensional analysis of data generated in Smart Grids, and optimization of decision-making processes require urgent solutions. The article aims to analyze the use of selected artificial intelligence (AI) algorithms to support the abovementioned issues. In particular, machine learning methods, metaheuristic algorithms, and intelligent fuzzy inference systems were analyzed. Examples of the analyzed algorithms were tested in crucial domains of the energy sector. The study analyzed cybersecurity, Smart Grid management, energy saving, power loss minimization, fault diagnosis, and renewable energy sources. For each domain of the energy sector, specific engineering problems were defined, for which the use of artificial intelligence algorithms was analyzed. Research results indicate that AI algorithms can improve the processes of energy generation, distribution, storage, consumption, and trading. Based on conducted analyses, we defined open research challenges for the practical application of AI algorithms in critical domains of the energy sector.
Towards the Integration of Flexible Green Hydrogen Demand and Production in Ireland: Opportunities, Barriers, and Recommendations
Authors: De Tommasi Luciano , Lyons Pádraig
Published: December 2022

Ireland’s Climate Action Plan 2021 has set out ambitious targets for decarbonization across the energy, transport, heating and agriculture sectors. The Climate Action Plan followed the Climate Act 2021, which committed Ireland to a legally binding target of net-zero greenhouse gas emissions no later than 2050, and a reduction of 51% by 2030. Green hydrogen is recognized as one of the most promising technologies for enabling the decarbonization targets of economies across the globe, but significant challenges remain to its large-scale adoption. This research systematically investigates the barriers and opportunities to establishing a green hydrogen economy by 2050 in Ireland, by means of an analysis of the policies supporting the optimal development of an overall green hydrogen eco-system, in the context of other decarbonizing technologies, including green hydrogen production using renewable generation, distribution and delivery, and final consumption. The outcome of this analysis is a set of clear recommendations for the policymaker that will appropriately support the development of a green hydrogen market and eco-system in parallel with the development of other more mature low-carbon technologies. The analysis has been supplemented by an open “call for evidence,” which gathered relevant information about the future policy and roles of hydrogen involving the most prominent stakeholders of hydrogen in Ireland. Furthermore, the recommendations and conclusions from the research have been validated by this mechanism.
IEDA-HGEO: Improved Energy Efficient with Clustering-Based Data Aggregation and Transmission Protocol for Underwater Wireless Sensor Networks
Authors: Joshi Shubham , Anithaashri T.P , Rastogi Ravi , Choudhary Gaurav , Dragoni Nicola
Published: December 2022

With the emerging technology in underwater wireless sensor networks (UWSN), many researchers are undergoing this field since it cannot maintain the batteries and recharge them manually. Network duration should be taken into account because they can easily be recharged by a non-conventional resource like solar energy. When coming to the data collection process, clustering is an effective method to construct vitality effective UWSNs. The clustering properties of UWSNs differ from those of terrestrial wireless sensor networks (TWSNs) due to the sparse deployment of nodes as well as the dynamic nature of the channel. This paper proposes improved efficient data aggregation in a Hexagonal grid with energy optimization (IEDA-HGEO) protocol for effective data transmission with an optimal clustering process. It is further compared with ERP2R n energy-efficient routing protocol and EGRC (Energy-efficiency Grid Routing based on 3D Cubes). The three techniques mentioned above are specifically examined for their applicability to underwater communication, and their performance is compared in terms of energy consumption, efficiency, throughput, packet delivery ratio, and delay. The proposed method achieved the following metrics: delay 41%, energy consumption 48%, efficiency 95%, throughput 95%, and PDR 92%.
Promising Hydrate Formation Promoters Based on Sodium Sulfosuccinates of Polyols
Authors: Chirkova Yulia F. , Mirzakimov Ulukbek Zh. , Semenov Matvei E. , Pavelyev Roman S. , Varfolomeev Mikhail A.
Published: December 2022

The use of natural gas as an energy source is increasing significantly due to its low greenhouse gas emissions. However, the common methods of natural gas storage and transportation, such as liquefied or compressed natural gas, are limited in their applications because they require extreme conditions. Gas hydrate technology can be a promising alternative to conventional approaches, as artificially synthesized hydrates provide an economical, environmentally friendly, and safe medium to store energy. Nevertheless, the low rate of hydrate formation is a critical problem that hinders the industrial application of this technology. Therefore, chemical promoters are being developed to accelerate the kinetics of gas hydrate formation. In this paper, the effect of new sodium sulfosuccinate compounds, synthesized based on glycerol and pentaerythritol, on methane hydrate formation was studied. Experiments under dynamic conditions using high-pressure autoclaves demonstrated that the conversion of water-to-hydrate forms increased from 62 ± 5% in pure water to 86 ± 4% for the best promoter at concentration 500 ppm. In addition, the rate of hydrate formation increases 2–4 times for different concentrations. Moreover, none of the synthesized reagents formed foam, compared to sodium dodecyl sulfate, in which the foam rate was 3.7 ± 0.2. The obtained reagents showed good promotional properties and did not form foam, which makes them promising promoters for gas hydrate technology.
Assessing the Role of Energy Storage in Multiple Energy Carriers toward Providing Ancillary Services: A Review
Authors: Alpízar-Castillo Joel , Ramirez-Elizondo Laura , Bauer Pavol
Published: December 2022

Renewable energy power plants and transport and heating electrification projects are being deployed to enable the replacement of fossil fuels as the primary energy source. This transition encourages distributed generation but makes the grid more weather-dependent, thus reducing its inertia. Simultaneously, electrical network operators face voltage, frequency, and stability challenges at the distribution level. Networks were not designed to manage the stochasticity of renewable energy sources or the congestion caused by the new transport and heating demands. Such challenges are commonly addressed through infrastructure reinforcements. This review studies how energy storage systems with different carriers can provide a collaborative solution involving prosumers as ancillary services providers at the distribution level. We focused on the European urban context; thus, we analyzed renewable energy sources, batteries, supercapacitors, hydrogen fuel cells, thermal energy storage, and electric vehicles. A thorough review of successful implementations proved that including storage in one or more carriers benefits the distribution system operators and the prosumers, from both technical and economic perspectives. We propose a correlation between individual energy storage technologies and the ancillary services they can provide based on their responses to specific grid requirements. Therefore, distribution system operators can address network issues together with the prosumers. Nevertheless, attractive regulatory frameworks and business models are required to motivate prosumers to use their assets to support the grid. Further work is recommended to describe the joint operation of multiple storage technologies as multicarrier systems, focusing on the coupling of electrical and thermal energy storage. Additionally, how ancillary services affect the energy storage system’s aging should be studied.
Management of Birch Spruce Mixed Stands with Consideration of Carbon Stock in Biomass and Harvested Wood Products
Authors: Vuguls Jānis , Dubra Stefānija , Garanča Anete , Zute Daiga , Jansons Āris
Published: December 2022

Forests play an important role in climate change mitigation. Usage of harvested wood products (HWP) can extend the carbon cycle by retaining carbon as well as preventing new fossil emission via substitution. We compared carbon balance of different management strategies of birch spruce mixed stands over an eight-year period: unmanaged, representing a decision of prolonged rotation, and managed, representing a decision of final harvest of birch and retention of spruce for continuous forest cover and regeneration harvest. Management resulted in a higher contribution of mixed stands to climate change mitigation, if the carbon stock (CS) in biomass as well carbon balance (CB) of wood product is jointly considered in comparison to no management (prolonged rotation). Assortment structure plays an important role in CB of HWP, therefore a practice ensuring higher outcome of longer-lasting wood products are beneficial to climate change mitigation.
Superposition Risk Assessment and Calculation Model of the Working Position of Coal-Seam Fire Accidents in China
Authors: Li Feng , Zhang Chenyu , He Xiaoxuan , Duan Baoyan , Wang Chenchen , Yan Zhengxu
Published: December 2022

The coal-seam fire is one of the most significant disasters in the coal mining industry in China, affecting the safety of coal production in China. The working-position risk in coal mining has an important impact on the risk of fire occurrence, and thus it would be worthwhile to analyze working-position risks so as to effectively prevent and control coal-seam fires. Based on the kernel density estimation (KDE), this research puts forward an innovative calculation-model and assessment method of the superposition risk of the working position on coal-seam fire accidents. This research aims to evaluate the priority of risk management of working positions in coal-seam fire accidents. In order to achieve this research aim and objectives, this research carried out a statistical analysis of 100 classic cases of coal-seam fire accidents from 2000 to 2022, using the accident-tree-structure importance analysis method. This research contributed to the evaluation of the frequency and severity of various risk factors leading to fire accidents, and the development of the value at risk (VaR) of various risk factors in the coal-seam fire accidents. Integrating all the risk factors involved in each position and their risk values, and building a position-risk calculation model was carried out. In addition, in accordance with the kernel density estimation (KDE), a post-superposition risk model was established. Moreover, ArcGIS software was used to obtain the superimposed risk of posts and build a risk-distribution map. Based on the possibility of post-risk occurrence and the severity of the consequences, a risk-assessment matrix was developed, a post-risk grading standard was established, and risk levels of the working position were divided up in this research. Results indicated that (1) before risk superposition, working-position risks and risk levels are densely distributed, and nearly 80% of risk levels of the working position are focused on Level II and III, without Level I. (2) After risk superposition, the post-risk is affected by the surrounding post-risk, and the risk- and level-distribution is more hierarchical; the number of Level I risks in working positions increased to 12, which were mainly distributed among the comprehensive mining team, comprehensive excavation team and ventilation team, which accords more with the objective and actual production-conditions. The risk-distribution map directly showed that the post-fire risk at the mining face and shaft is higher, a result which will take on a significant guiding role in the effective control and prevention of risk in coal-seam fires in the future.
From Fractal Behavior of Iteration Methods to an Efficient Solver for the Sign of a Matrix
Authors: Liu Tao , Ullah Malik Zaka , Alshahrani Khalid Mohammed Ali , Shateyi Stanford
Published: December 2022

Investigating the fractal behavior of iteration methods on special polynomials can help to find iterative methods with global convergence for finding special matrix functions. By employing such a methodology, we propose a new solver for the sign of an invertible square matrix. The presented method achieves the fourth rate of convergence by using as few matrix products as possible. Its attraction basin shows larger convergence radii, in contrast to its Padé-type methods of the same order. Computational tests are performed to check the efficacy of the proposed solver.
An RNA Interference (RNAi) Toolkit and Its Utility for Functional Genetic Analysis of Leishmania (Viannia)
Authors: Lye Lon-Fye , Owens Katherine L. , Jang Soojin , Marcus Joseph E. , Brettmann Erin A. , Beverley Stephen M.
Published: December 2022

RNA interference (RNAi) is a powerful tool whose efficacy against a broad range of targets enables functional genetic tests individually or systematically. However, the RNAi pathway has been lost in evolution by a variety of eukaryotes including most Leishmania sp. RNAi was retained in species of the Leishmania subgenus Viannia, and here we describe the development, optimization, and application of RNAi tools to the study of L. (Viannia) braziliensis (Lbr). We developed vectors facilitating generation of long-hairpin or “stem-loop” (StL) RNAi knockdown constructs, using GatewayTM site-specific recombinase technology. A survey of applications of RNAi in L. braziliensis included genes interspersed within multigene tandem arrays such as quinonoid dihydropteridine reductase (QDPR), a potential target or modulator of antifolate sensitivity. Other tests include genes involved in cell differentiation and amastigote proliferation (A600), and essential genes of the intraflagellar transport (IFT) pathway. We tested a range of stem lengths targeting the L. braziliensis hypoxanthine-guanine phosphoribosyl transferase (HGPRT) and reporter firefly luciferase (LUC) genes and found that the efficacy of RNAi increased with stem length, and fell off greatly below about 128 nt. We used the StL length dependency to establish a useful ‘hypomorphic’ approach not possible with other gene ablation strategies, with shorter IFT140 stems yielding viable cells with compromised flagellar morphology. We showed that co-selection for RNAi against adenine phosphoryl transferase (APRT1) using 4-aminopyrazolpyrimidine (APP) could increase the efficacy of RNAi against reporter constructs, a finding that may facilitate improvements in future work. Thus, for many genes, RNAi provides a useful tool for studying Leishmania gene function with some unique advantages.
Ensuring Population Health in the Era of Aging in Vietnam: Policy Review and Factors Associated with Intentions of Childbearing before the Age of 30 among Youths
Authors: Doan Linh Phuong , Nguyen Long Hoang , Do Ha Ngoc , Nguyen Tham Thi , Vu Giang Thu , Do Hoa Thi , Latkin Carl A. , Ho Roger C. M. , Ho Cyrus S. H.
Published: December 2022

Background: Delayed childbearing has become a concern among policymakers across the world. In Vietnam, population policies have been adjusted to cope with this issue. In 2020, Decision 588/QD-TTg was ratified to encourage people to marry and give birth before the age of 30. This study reviewed recent changes in Vietnam’s population policies and assessed the intention of giving birth before 30 in young Vietnamese to provide insights into the potential effectiveness of the policy changes among young people. Methods: This study combined two approaches: a desk review and a survey of a group of youths. An online cross-sectional study was conducted on 116 respondents aged 16 to 30 in Vietnam from June to July 2020. The intention of childbearing before 30 and the importance and responsiveness of different social-environmental factors were asked using a structured questionnaire. We used multivariate logistic regression to identify associated factors of such intention. Results: The incentives set out by the Vietnamese government shared similarities with those of other countries. The plan of childbearing before the age of 30 among young adults in Vietnam was demonstrated to correlate with age, socioeconomic and biological characteristics, resources of the local health systems, as well as a clean and safe living environment. Conclusion: This study highlighted the recent crucial shift in Vietnam’s population policy. However, the quantitative analysis suggested that measures relating to environmental factors should be incorporated under this policy, implying that further interventions need to be taken into account to cope with delayed childbearing.
Effects of Urban Forest Therapy Program on Depression Patients
Authors: Yeon Poung-Sik , Kim In-Ok , Kang Si-Nae , Lee Nee-Eun , Kim Ga-Yeon , Min Gyeong-Min , Chung Chung-Yeub , Lee Jung-Sok , Kim Jin-Gun , Shin Won-Sop
Published: December 2022

Depression is a common serious mental health condition that can have negative personal and social consequences, and managing it is critical for treating depression patients. Forest therapy is emerging as a promising non-pharmacological intervention to improve mental health. However, although the effectiveness of forest therapy programs using forests far from the city has been proven, it is not well known that urban forests can be easily accessed in daily life. Therefore, this study aimed to examine the effects of an urban forest therapy program on depression symptoms, sleep quality, and somatization symptoms of depression patients. To evaluate this, a randomized controlled trial (RCT) design was employed. A total of 47 depression patients participated in this study (22 in the urban forest therapy program group and 25 in the control group). The Beck Depression Inventory (BDI), the Hamilton Rating Scale for Depression (HRSD), the Pittsburgh Sleep Quality Index (PSQI), and the Patient Health Questionnaire-15 (PHQ-15) were administered to each participant to assess the effects of the urban forest therapy program. The results of this study revealed that depression patients in the urban forest therapy program had significantly alleviated depression symptoms and improved sleep quality and somatization symptoms compared to the control group. In conclusion, this study demonstrates the possibility that the urban forest therapy program could be used as an effective non-pharmacological treatment to alleviate depression disorder.
Relationship between Changes in Foot Arch and Sex Differences during the Menstrual Cycle
Authors: Edama Mutsuaki , Ohya Tae , Maruyama Sae , Shagawa Mayuu , Sekine Chie , Hirabayashi Ryo , Yokota Hirotake , Ishigaki Tomonobu , Akuzawa Hiroshi , Togashi Ryoya , Yamada Yuki , Takabayashi Tomoya
Published: December 2022

This study investigated the relationship between changes in foot characteristics and sex differences during the menstrual cycle in healthy male and female university students. We examined 10 female subjects and 14 male subjects. The menstrual cycle was divided into the three phases: the early follicular phase, ovulatory phase, and luteal phase via basal body temperature, an ovulation kit, and salivary estradiol and progesterone concentration measurements. Foot characteristics required for the calculation of the arch height index (AHI) were measured using a three-dimensional foot scanner under conditions of 10% and 50% weight-bearing loads. Arch height at 50% of foot length and truncated foot length were measured, and AHI was calculated by dividing arch height by truncated foot length. Arch height flexibility (AHF) was defined as the change in arch height from 10% weight-bearing load to 50% weight-bearing load. AHI was significantly lower in females than in males in the early follicular and ovulatory phases but did not differ significantly between males and females in each phase. AHF did not differ significantly between males and females in each phase. AHI and AHF showed no periodic fluctuation, suggesting that sex differences in AHF may be absent.
Knowledge, Attitudes, and Practices of Communal Livestock Farmers regarding Animal Health and Zoonoses in Far Northern KwaZulu-Natal, South Africa
Authors: Ngoshe Yusuf Bitrus , Etter Eric , Gomez-Vazquez Jose Pablo , Thompson Peter N.
Published: December 2022

The presence of zoonotic diseases adversely affects livestock production and farmers’ livelihood in communal areas. A lack of awareness about zoonotic diseases among rural farmers results in economic losses and health risks. The far north-eastern corner of KwaZulu-Natal (KZN) province, South Africa, is home to large numbers of communal livestock farmers who live adjacent to wildlife reserves and international borders. There have been reports of zoonotic and trade-sensitive diseases in the area, but farmers’ knowledge, attitudes, and practices (KAP) in this regard are poorly understood. This study investigated the KAPs of communal livestock farmers in far northern KZN regarding livestock and zoonotic diseases found in the livestock–wildlife interface and determined the constraints and challenges faced by communal livestock farmers. A cross-sectional questionnaire survey was conducted among 504 livestock farmers at 45 dip tanks between August and November 2020, using a closed-ended questionnaire. Although the overall level of knowledge regarding animal disease transmission was fairly good (score: 53.2%), 25.4% and 21.4% of farmers had moderate and poor knowledge, respectively, about zoonotic disease transmission and prevention. Over 40% of the farmers were not aware of the zoonotic nature of wildlife and livestock diseases. Older farmers, despite their lower level of education, were more knowledgeable on animal diseases and had better practices in regard to zoonotic disease prevention and management compared to younger ones. The majority of farmers cited the lack of water, insufficient grazing land, stock theft, the restriction of animal movement, and animal diseases as the most significant challenges they faced regarding animal production. The results indicate the need for extension programs that target educating livestock farmers to improve their knowledge of these diseases.
Influence of Psychological Factors on Participation and Life Satisfaction in the Context of Travel and Tourism after Spinal Cord Injury
Authors: Hua Chenggang , Cole Shu
Published: December 2022

Spinal cord injury (SCI) can significantly compromise people’s participation in travel and tourism activities, which is considered an important and meaningful way to engage in one’s chosen lifestyle and wellness pursuits. Yet, travel often presents challenges for people with spinal cord injury (PwSCI), as it requires overcoming a wide range of potential psycho-physical challenges or barriers during trips. There is a lack of theory-based research that can help us understand and address the psychological factors and processes influencing participation and life satisfaction following SCI. Drawing on self-determination theory (SDT), this study examines the effects of psychological needs satisfaction on participation in the travel setting, and their subsequent impact on perceived life satisfaction. This study uses a mixed-methods approach with 39 in-depth telephone interviews conducted that focus on developing needs satisfaction measures for PwSCI in the travel setting, and an online survey among 258 PwSCI examining the relations between needs satisfaction and outcome variables. This study finds that the psychological needs satisfaction of autonomy and relatedness significantly contribute to self-determined participation in travel and tourism activities for PwSCI. This self-determined participation outcome thus represents an individual’s improved ability to exert choice and control, which exhibits their level of regained mobility and further improves their life satisfaction.