bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of the Techniques of the Data Analytics and Islanding Detection of Distribution Systems Using Phasor Measurement Unit Data
Authors: Arefin Ahmed Amirul , Baba Maveeya , Singh Narinderjit Singh Sawaran , Nor Nursyarizal Bin Mohd , Sheikh Muhammad Aman , Kannan Ramani , Abro Ghulam E. Mustafa , Mathur Nirbhay
Published: September 2022

The application of the Phasor Measurement Unit (PMU) in the power system is expanding day by day since it provides a higher reliability through fast symmetrically monitoring and protection and assists in controlling power systems. For power systems, islanding is a significant event due to its hazardous consequences. To detect islanding events, several schemes have been previously proposed but inappropriate threshold setting, higher computational time, and false tripping are the main limitations. In addition, differentiating between real island events and transient faults is another limitation. However, appropriate threshold setting plays a considerable part in detecting the island event, which is also important to differentiate between real and non-island events. Phasor Measurement Unit can assist in islanding detection, but it can generate 30 samples/s, so there is always the possibility of making particular period data disappear. The principal contribution of this review article is its detailed discussion of real-time symmetrical PMU data and it further presents different PMU data analytic techniques and the proposed schemes for the islanding detection system. An appropriate methodology tried to understand how to incorporate missing PMU data techniques along with the islanding detection system to ensure the higher reliability of the network.
Improving Efficiency of Large RFID Networks Using a Clustered Method: A Comparative Analysis
Authors: Pandian M. Thurai , Chouhan Kuldeep , Kumar B. Muthu , Dash Jatindra Kumar , Jhanjhi N. Z. , Ibrahim Ashraf Osman , Abulfaraj Anas W.
Published: September 2022

Radio Frequency Identification (RFID) is primarily used to resolve the problems of taking care of the majority of nodes perceived and tracking tags related to the items. Utilizing contactless radio frequency identification data can be communicated distantly using electromagnetic fields. In this paper, the comparison and analysis made between the Clustered RFID with existing protocols Ad hoc On-demand Multicast Distance Vector Secure Adjacent Position Trust Verification (AOMDV_SAPTV) and Optimal Distance-Based Clustering (ODBC) protocols based on the network attributes of accuracy, vulnerability and success rate, delay and throughput while handling the huge nodes of communication. In the RFID Network, the clustering mechanism was implemented to enhance the performance of the network when scaling nodes. Multicast routing was used to handle the large number of nodes involved in the transmission of particular network communication. While scaling up the network, existing methods may be compromised with their efficiency. However, the Clustered RFID method will give better performance without compromising efficiency. Here, Clustered RFID gives 93% performance, AOMDV_SAPTV can achieve 79%, and ODBC can reach 85% of performance. Clustered RFID gives 14% better performance than AOMDV_SAPTV and 8% better performance than ODBC for handling a huge range of nodes.
IoT-Based Access Management Supported by AI and Blockchains
Authors: Schiller Eryk , Esati Elfat , Stiller Burkhard
Published: September 2022

Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and recognition by incorporating the most recent state-of-the-art techniques. The system developed uses IoT devices for video surveillance, AI for face recognition, and BCs for immutable permanent storage to provide excellent properties in terms of image quality, end-to-end delay, and energy efficiency.
Study on the Dormancy Characteristics of Chinese Pistache (Pistacia chinensis Bunge) Seeds
Authors: Guo Huanhuan , Liu Yong , Wang Haijiao , Li Shiqin
Published: September 2022

Chinese pistache tree (Pistacia chinensis Bunge, Anacardiaceae) is an important oil, ornamental and afforestation tree species. Seeds of this species are known due to their erratic germination, so it is urgent to determine the causes of such dormancy. To do so, we tested water permeability, respiration rate, mechanical constraint and germination inhibitors. The results indicated that the testa was water-permeable, the raphe and hilum as the areas that contributed most to imbibition. Removal of the testa increased the imbibition rate and improved the oxygen availability to the embryo. Furthermore, the analysis of the extracts showed that the endotesta and embryo may contain inhibitors that negatively affect germination and seedling growth. The widely targeted metabolomics revealed that phenolic acids and organic acids may be the potential inhibitors. Seed scarification, exogenous gibberellin (GA3) and cold stratification greatly increased the germination, but seed scarification (removal of the exotesta and 1/2 cotyledon) was the most effective strategy, since it increased the germination up to 89% after 5 days of incubation, a rate significantly higher regarding the other strategies, which barely reached 60% in 20 days. In conclusion, there seems to exist both a mechanical dormancy due to the testa and a physiological inhibition due to the embryo.
Functional and Healthy Yogurts Fortified with Probiotics and Fruit Peel Powders
Authors: Zahid Hafza Fasiha , Ranadheera Chaminda Senaka , Fang Zhongxiang , Ajlouni Said
Published: September 2022

The application of processing waste by-products along with probiotics is an interesting choice to confer potential functional aspects to food products. This study was designed to investigate the nutritional capacity of freeze-dried mango peel powder (MPP) and banana peel powder (BPP) in the presence of a mixture of three probiotic species (1% of each of three probiotics (Lacticaseibacillus casei (431®), Lacticaseibacillus rhamnosus (LGG®) and Bifidobacterium subsp. Lactis (Bb-12®)) as sources of additional nutrients and prebiotics in fresh and rehydrated freeze-dried (RFD) yogurts for 28 days of refrigerated storage. The net count of probiotics in yogurt fortified with MPP and BPP increased by at least 1 log CFU/g after 4 weeks of refrigerated storage. Adding fruit peel powder (FPP) significantly (p < 0.05) increased fat, ash, and protein contents in both fresh and RFD yogurts in comparison with the control yogurt. Similarly, the total phenolic contents (TPC) and antioxidant activity (AOA) was enhanced significantly (p < 0.05). The TPC reached 2.27 ± 0.18 and 2.73 ± 0.11 mg GAE/g in RFD enriched with BPP and MPP compared to a TPC of 0.31 ± 0.07 mg GAE/g in the control. Additionally, yogurt samples enriched with BPP (Y-5) and MPP (Y-6) demonstrated 12% more sugar contents than non-fortified yogurts (Y-1). Higher titratable acidity and lower pH values were also recorded in the RFD yogurt. Significant differences (p < 0.05) in the color parameters were detected in both fresh and RFD yogurts with reduced brightness (L*) and increased redness (a*) of the product. These findings demonstrated the suitability of MPP and BPP in yogurt formulations to optimize the advantages of such synbiotic products with higher availability of phenolic compounds.
INFOGEST Digestion Assay of Raw and Roasted Hazelnuts and Its Impact on Allergens and Their IgE Binding Activity
Authors: Prodić Ivana , Smiljanić Katarina , Nagl Christoph , Ballmer-Weber Barbara , Hoffmann-Sommergruber Karin , Veličković Tanja Ćirković
Published: September 2022

Most of the food allergens sensitized via the gastrointestinal tract resist thermal treatments and digestion, particularly digestion by pepsin. Roasted hazelnuts are more commonly consumed than raw ones. Since no studies have characterized gastric digestion protein fragments of raw and roasted hazelnuts nor their IgE binding properties, we compared these aspects of raw and roasted hazelnuts’ gastric digesta obtained by INFOGEST protocol. Their electrophoretically resolved profiles were probed with hazelnut allergic patients’ sera in 1D and 2D immunoblots. Electrophoretic profiles demonstrated pepsin digestion of all hazelnut allergens to varying extents. While 2D immunoblots indicated that roasting slightly reduced allergenicity, IgE ELISA with the pool of sera showed a slight significant (10%) increase in IgE binding in both gastric digesta. Cor a 9 isolated from the raw and roasted hazelnuts, characterized by far and near CD, remained stable after roasting, with preserved IgE reactivity. Its immunoreactivity contribution by inhibitory ELISA was noticeable in raw and roasted hazelnut digesta; its activity was slightly stronger in the roasted preparations. Roasting has a visible impact on proteins; however, it did not affect overall IgE reactivity. Gastric digestion slightly increases the overall IgE reactivity in raw and roasted hazelnuts, and may therefore impact the profiles of allergens and their fragments available to interact with the immune system in the small intestine.
Irrigation of Young Olives Grown on Reclaimed Karst Soil Increases Fruit Size, Weight and Oil Yield and Balances the Sensory Oil Profile
Authors: Jukić Špika Maja , Romić Davor , Žanetić Mirella , Zovko Monika , Klepo Tatjana , Strikić Frane , Perica Slavko
Published: September 2022

The influence of different irrigation regimes on olive fruit morphological parameters and on the quantity and quality (marketable indices, phenolic content, fatty acid composition, and sensory profile) of virgin olive oil (VOO) obtained from the Croatian cultivar Oblica, grown on an extremely rocky and dry reclaimed karst soil, was studied over three years. Four treatments were applied: rain-fed and three treatments calculated as 50%, 75%, and 100% of the crop’s irrigation requirement (Irr). Principal component analysis separated growing seasons (GS) that differed in precipitation. In the 2016 season, which had a low number of fruits per kilogram and provided a higher amount of balanced VOO with medium to intense bitterness and pungency (rain-fed treatment), the oil yield increased by irrigation (Irr 75 and Irr 100) up to 18%, while unchanged phenolics, bitterness, and pungency were observed for the VOOs obtained. In the drier GS (2017), which under rain-fed conditions had high fruit per kg, smallest fruit sizes, and lowest oil yield, and in which the VOOs had high phenolic content and intense sensory taste attributes, fruit weight, fruit sizes, and oil yield increased by 35% in all irrigation treatments, while phenols, bitterness, and pungency decreased, balancing the sensory profile of the VOOs. The results obtained here led us to conclude that the irrigation of young olives resulted in a positive effect, with the indication that an abundant water supply is more effective in drought conditions.
Radiation Dosimetry by Use of Radiosensitive Hydrogels and Polymers: Mechanisms, State-of-the-Art and Perspective from 3D to 4D
Authors: De Deene Yves
Published: September 2022

Gel dosimetry was developed in the 1990s in response to a growing need for methods to validate the radiation dose distribution delivered to cancer patients receiving high-precision radiotherapy. Three different classes of gel dosimeters were developed and extensively studied. The first class of gel dosimeters is the Fricke gel dosimeters, which consist of a hydrogel with dissolved ferrous ions that oxidize upon exposure to ionizing radiation. The oxidation results in a change in the nuclear magnetic resonance (NMR) relaxation, which makes it possible to read out Fricke gel dosimeters by use of quantitative magnetic resonance imaging (MRI). The radiation-induced oxidation in Fricke gel dosimeters can also be visualized by adding an indicator such as xylenol orange. The second class of gel dosimeters is the radiochromic gel dosimeters, which also exhibit a color change upon irradiation but do not use a metal ion. These radiochromic gel dosimeters do not demonstrate a significant radiation-induced change in NMR properties. The third class is the polymer gel dosimeters, which contain vinyl monomers that polymerize upon irradiation. Polymer gel dosimeters are predominantly read out by quantitative MRI or X-ray CT. The accuracy of the dosimeters depends on both the physico-chemical properties of the gel dosimeters and on the readout technique. Many different gel formulations have been proposed and discussed in the scientific literature in the last three decades, and scanning methods have been optimized to achieve an acceptable accuracy for clinical dosimetry. More recently, with the introduction of the MR-Linac, which combines an MRI-scanner and a clinical linear accelerator in one, it was shown possible to acquire dose maps during radiation, but new challenges arise.
A 20-Year Journey of Forecasting with the “Every Earthquake a Precursor According to Scale” Model
Authors: Rhoades David A. , Rastin Sepideh J. , Christophersen Annemarie
Published: September 2022

Nearly 20 years ago, the observation that major earthquakes are generally preceded by an increase in the seismicity rate on a timescale from months to decades was embedded in the “Every Earthquake a Precursor According to Scale” (EEPAS) model. EEPAS has since been successfully applied to regional real-world and synthetic earthquake catalogues to forecast future earthquake occurrence rates with time horizons up to a few decades. When combined with aftershock models, its forecasting performance is improved for short time horizons. As a result, EEPAS has been included as the medium-term component in public earthquake forecasts in New Zealand. EEPAS has been modified to advance its forecasting performance despite data limitations. One modification is to compensate for missing precursory earthquakes. Precursory earthquakes can be missing because of the time-lag between the end of a catalogue and the time at which a forecast applies or the limited lead time from the start of the catalogue to a target earthquake. An observed space-time trade-off in precursory seismicity, which affects the EEPAS scaling parameters for area and time, also can be used to improve forecasting performance. Systematic analysis of EEPAS performance on synthetic catalogues suggests that regional variations in EEPAS parameters can be explained by regional variations in the long-term earthquake rate. Integration of all these developments is needed to meet the challenge of producing a global EEPAS model.
Aquifer and Land Subsidence Interaction Assessment Using Sentinel-1 Data and DInSAR Technique
Authors: Rafiei Fatemeh , Gharechelou Saeid , Golian Saeed , Johnson Brian Alan
Published: September 2022

Climate change and overpopulation have led to an increase in water demands worldwide. As a result, land subsidence due to groundwater extraction and water level decline is causing damage to communities in arid and semiarid regions. The agricultural plain of Samalghan in Iran has recently experienced wide areas of land subsidence, which is hypothesized to be caused by groundwater overexploitation. This hypothesis was assessed by estimating the amount of subsidence that occurred in the Samalghan plain using DInSAR based on an analysis of 25 Sentinel-1 descending SAR images over 6 years. To assess the influence of water level changes on this phenomenon, groundwater level maps were produced, and their relationship with land subsidence was evaluated. Results showed that one major cause of the subsidence in the Samalghan plain was groundwater overexploitation, with the highest average land subsidence occurring in 2019 (34 cm) and the lowest in 2015 and 2018 (18 cm). Twelve Sentinel-1 ascending images were used for relative validation of the DInSAR processing. The correlation value varied from 0.69 to 0.89 (an acceptable range). Finally, the aquifer behavior was studied, and changes in cultivation patterns and optimal utilization of groundwater resources were suggested as practical strategies to control the current situation.
Identification and Spread of the Ghost Silverfish (Ctenolepisma calvum) among Museums and Homes in Europe
Authors: Querner Pascal , Szucsich Nikolaus , Landsberger Bill , Erlacher Sven , Trebicki Lukasz , Grabowski Michał , Brimblecombe Peter
Published: September 2022

Ctenolepisma calvum was first described in Sri Lanka (Ceylon) in 1910, and this island is probably the origin of this species. Later, it was also found in the Caribbean (Cuba and Trinidad and Tobago). Up until the present, it has only been identified within buildings (a synanthropic species), and its natural habitat is unknown. In 2007, it was discovered in Germany and was considered a neobiotic species of Lepismatidae in Europe. It has rapidly spread throughout Europe and beyond in recent years. This led us to analyze the available data of the first occurrences in Germany, Austria, and other European countries. Furthermore, we compared the spread inside of museums in Vienna (Austria) and Berlin (Germany). These museums have been monitored for a long period with sticky traps, representing the best source of information on the dispersion dynamics of Ctenolepisma calvum. We found a scattered occurrence of this species in 18 countries in Europe (including Russia and Ukraine). The first record for Poland has not previously been published; however, this species has been present there since 2014. Surprisingly, it was found in Hungary in 2003, but a record was only published online in 2021. Additionally, in Germany and Austria, where most data are available, the spread of the species does not follow any clear pattern. In museums in Berlin, the species has only been found in one location. In contrast, the species rapidly spread in museums in Vienna between 2014 and 2021, from four to 30 locations, and it is now a well-established species with occasional high abundance. We examined the spread of the species at three spatial scales: (i) Europe, (ii) national, and (iii) regional. Our observations indicate that it is possibly distributed with materials (packaging material, hygiene articles, paper, cardboard, and collection items). Little is yet known about the biology of this introduced pest. We describe its preferred habitat within buildings, its climate requirements, and its potential to act as a new museum pest in Central Europe. This species seems to thrive at room temperature in buildings. Further impact on the species due to climate change in the future is also discussed. We offer a simple morphological key and a detailed identification table to help correct species identification.
Performance Evaluation of Federated Learning for Residential Energy Forecasting
Authors: Petrangeli Eugenia , Tonellotto Nicola , Vallati Carlo
Published: September 2022

Short-term energy-consumption forecasting plays an important role in the planning of energy production, transportation and distribution. With the widespread adoption of decentralised self-generating energy systems in residential communities, short-term load forecasting is expected to be performed in a distributed manner to preserve privacy and ensure timely feedback to perform reconfiguration of the distribution network. In this context, edge computing is expected to be an enabling technology to ensure decentralized data collection, management, processing and delivery. At the same time, federated learning is an emerging paradigm that fits naturally in such an edge-computing environment, providing an AI-powered and privacy-preserving solution for time-series forecasting. In this paper, we present a performance evaluation of different federated-learning configurations resulting in different privacy levels to the forecast residential energy consumption with data collected by real smart meters. To this aim, different experiments are run using Flower (a popular federated learning framework) and real energy consumption data. Our results allow us to demonstrate the feasibility of such an approach and to study the trade-off between data privacy and the accuracy of the prediction, which characterizes the quality of service of the system for the final users.
Different Machine Learning Approaches for Implementing Telehealth-Based Cancer Pain Management Strategies
Authors: Cascella Marco , Coluccia Sergio , Monaco Federica , Schiavo Daniela , Nocerino Davide , Grizzuti Mariacinzia , Romano Maria Cristina , Cuomo Arturo
Published: September 2022

Background: The most effective strategy for managing cancer pain remotely should be better defined. There is a need to identify those patients who require increased attention and calibrated follow-up programs. Methods: Machine learning (ML) models were developed using the data prospectively obtained from a single-center program of telemedicine-based cancer pain management. These models included random forest (RF), gradient boosting machine (GBM), artificial neural network (ANN), and the LASSO–RIDGE algorithm. Thirteen demographic, social, clinical, and therapeutic variables were adopted to define the conditions that can affect the number of teleconsultations. After ML validation, the risk analysis for more than one remote consultation was assessed in target individuals. Results: The data from 158 patients were collected. In the training set, the accuracy was about 95% and 98% for ANN and RF, respectively. Nevertheless, the best accuracy on the test set was obtained with RF (70%). The ML-based simulations showed that young age (<55 years), lung cancer, and occurrence of breakthrough cancer pain help to predict the number of remote consultations. Elderly patients (>75 years) with bone metastases may require more telemedicine-based clinical evaluations. Conclusion: ML-based analyses may enable clinicians to identify the best model for predicting the need for more remote consultations. It could be useful for calibrating care interventions and resource allocation.
Taking a Closer Look: The Relationship between Pre-School Domain General Cognition and School Mathematics Achievement When Controlling for Intelligence
Authors: Ehlert Antje , Poltz Nadine , Quandte Sabine , Kohn Juliane , Kucian Karin , Von Aster Michael , Esser Günter
Published: September 2022

Intelligence, as well as working memory and attention, affect the acquisition of mathematical competencies. This paper aimed to examine the influence of working memory and attention when taking different mathematical skills into account as a function of children’s intellectual ability. Overall, intelligence, working memory, attention and numerical skills were assessed twice in 1868 German pre-school children (t1, t2) and again at 2nd grade (t3). We defined three intellectual ability groups based on the results of intellectual assessment at t1 and t2. Group comparisons revealed significant differences between the three intellectual ability groups. Over time, children with low intellectual ability showed the lowest achievement in domain-general and numerical and mathematical skills compared to children of average intellectual ability. The highest achievement on the aforementioned variables was found for children of high intellectual ability. Additionally, path modelling revealed that, depending on the intellectual ability, different models of varying complexity could be generated. These models differed with regard to the relevance of the predictors (t2) and the future mathematical skills (t3). Causes and conclusions of these findings are discussed.
Reproductive Characteristics of the Flat Oyster Ostrea denselamellosa (Bivalvia, Ostreidae) Found on the Southern Coast of South Korea
Authors: Han Jeonghoon , Kim Han-Jun , Oh Sung-Yong , Choi Young-Ung
Published: September 2022

In this study, we investigated the reproductive pattern of the commercially and ecologically important species, Ostrea denelamellosa, to inform stock management strategies in South Korea. Prior to the reproduction experiment, the complete mitochondrial (mt) genome of the flat oyster, Ostrea denselamellosa, was analyzed using next-generation sequencing technology. Then, to determine the reproductive pattern of Ostrea denselamellosa, we investigated monthly changes in the gametogenesis, reproductive cycle, and sex ratio from January to October 2021 in females. The total length of the mt genome sequence of O. denselamellosa was 16,225 bp and contained 37 genes (13 protein-coding genes, 22 tRNA genes, and 2 rRNA genes). Molecular phylogenetic comparison with 20 known species of Pteriomorphia showed that O. denselamellosa belongs to the family Ostreidae. In addition, O. denselamellosa clustered together with the O. denselamellosa Chinese strain, with a bootstrap value of 100%. Histological analysis indicated a discrepancy in gamete development of O. denselamellosa with synchronous maturation of oocytes and asynchronous development of spermatozoa in gonads. The spawning activity occurred between May and September with a temperature range gap of 6.5 °C. The spawning activity occurred from May when the temperature reached 16.7 °C until September when the temperature dropped below 23.2 °C. Furthermore, sex ratio bias was observed. This is the first study to report the complete mt genome sequence and examine the reproductive pattern in native O. denselamellosa in South Korea. Overall, these findings will help enhance the knowledge for the management and sustainable fishery of endangered oyster species including O. denselamellosa in the South Sea of Korea.
Biodiversity and Bioprospecting of Fungal Endophytes from the Antarctic Plant Colobanthus quitensis
Authors: Bertini Laura , Perazzolli Michele , Proietti Silvia , Capaldi Gloria , Savatin Daniel V. , Bigini Valentina , Longa Claudia Maria Oliveira , Basaglia Marina , Favaro Lorenzo , Casella Sergio , Fongaro Benedetta , Polverino de Laureto Patrizia , Caruso Carla
Published: September 2022

Microorganisms from extreme environments are considered as a new and valuable reservoir of bioactive molecules of biotechnological interest and are also utilized as tools for enhancing tolerance to (a)biotic stresses in crops. In this study, the fungal endophytic community associated with the leaves of the Antarctic angiosperm Colobanthus quitensis was investigated as a new source of bioactive molecules. We isolated 132 fungal strains and taxonomically annotated 26 representative isolates, which mainly belonged to the Basidiomycota division. Selected isolates of Trametes sp., Lenzites sp., Sistotrema sp., and Peniophora sp. displayed broad extracellular enzymatic profiles; fungal extracts from some of them showed dose-dependent antitumor activity and inhibited the formation of amyloid fibrils of α-synuclein and its pathological mutant E46K. Selected fungal isolates were also able to promote secondary root development and fresh weight increase in Arabidopsis and tomato and antagonize the growth of pathogenic fungi harmful to crops. This study emphasizes the ecological and biotechnological relevance of fungi from the Antarctic ecosystem and provides clues to the bioprospecting of Antarctic Basidiomycetes fungi for industrial, agricultural, and medical applications.
Fractile Graphical Analysis in Finance: A New Perspective with Applications
Authors: Bera Anil K. , Ghosh Aurobindo
Published: September 2022

Fractile Graphical Analysis (FGA) was proposed by Prasanta Chandra Mahalanobis in 1961 as a method for comparing two distributions at two different points (of time or space) controlling for the rank of a covariate through fractile groups. We use bootstrap techniques to formalize the heuristic method used by Mahalanobis for approximating the standard error of the dependent variable using fractile graphs from two independently selected “interpenetrating network of subsamples.” We highlight the potential and revisit this underutilized technique of FGA with a historical perspective. We explore a new non-parametric regression method called Fractile Regression where we condition on the ranks of the covariate and compare it with existing regression techniques. We apply this method to compare mutual fund inflow distributions after conditioning on ranks or fractiles of pre-tax and post-tax returns and compare distributions of private and public equity returns after controlling for fractiles of assets under management size using the two sample smooth test.
Effects of Sex and Whole Life Cycle UVB Irradiation on Performance and Mineral and Vitamin D3 Contents in Feeder Crickets (Gryllus bimaculatus)
Authors: Michaels Christopher J. , Ferguson Amanda , Newton-Youens Jade , Harland Robert , Hickles Ross
Published: September 2022

Captive insectivore nutrition is challenging due to the differing nutritional profiles of wild and captive diets and an incomplete understanding of both. Ultraviolet B (UVB)-irradiation has recently been explored as a means of improving prey-insect vitamin D3 and Ca content. Although short-term irradiation has been successful in some species, it has been unsuccessful in black field crickets (Gryllus bimaculatus)—a commonly cultured feeder insect. We exposed crickets to UVB irradiation from hatchling to adult stages and measured the vitamin D3 and mineral contents of crickets by sex. We did not detect vitamin D3 (detection limit 0.5 iU/g) or an effect of UVB irradiation on mineral content under either UV+ or UV− conditions. We identified large differences between sexes in Ca, K, Mg and P (females higher) and Cu, Fe, S and Zn (males higher), likely linked to reproductive investment. The differences do not straddle the minimum recommended concentrations of minerals for vertebrate growth and thus may be most relevant to animal nutrition in contexts of particular sensitivity or need. We demonstrate a UV-linked trade-off in cricket performance between individual cricket size and the numbers of crickets produced and characterise the energy costs associated with UVB provision. Our results do not support the use of UVB lighting for G. bimaculatus to improve nutrition but demonstrate previously unreported differences in the nutritional profiles between sexes in this species.
Genomic Analysis of LEA Genes in Carica papaya and Insight into Lineage-Specific Family Evolution in Brassicales
Authors: Zou Zhi , Guo Jingyuan , Zheng Yujiao , Xiao Yanhua , Guo Anping
Published: September 2022

Late embryogenesis abundant (LEA) proteins comprise a diverse superfamily involved in plant development and stress responses. This study presents a first genome-wide analysis of LEA genes in papaya (Carica papaya L., Caricaceae), an economically important tree fruit crop widely cultivated in the tropics and subtropics. A total of 28 members were identified from the papaya genome, which belong to eight families with defined Pfam domains, i.e., LEA_1 (3), LEA_2 (4), LEA_3 (5), LEA_4 (5), LEA_5 (2), LEA_6 (2), DHN (4), and SMP (3). The family numbers are comparable to those present in Ricinus communis (Euphorbiaceae, 28) and Moringa oleifera (Moringaceae, 29), but relatively less than that found in Moringa oleifera (Cleomaceae, 39) and Arabidopsis thaliana (Brassicaceae, 51), implying lineage-specific evolution in Brassicales. Indeed, best-reciprocal-hit-based sequence comparison and synteny analysis revealed the presence of 29 orthogroups, and significant gene expansion in Tarenaya and Arabidopsis was mainly contributed by whole-genome duplications that occurred sometime after their split with the papaya. Though a role of transposed duplication was also observed, tandem duplication was shown to be a key contributor in gene expansion of most species examined. Further comparative analyses of exon-intron structures and protein motifs supported fast evolution of this special superfamily, especially in Arabidopsis. Transcriptional profiling revealed diverse expression patterns of CpLEA genes over various tissues and different stages of developmental fruit. Moreover, the transcript level of most genes appeared to be significantly regulated by drought, cold, and salt stresses, corresponding to the presence of cis-acting elements associated with stress response in their promoter regions. These findings not only improve our knowledge on lineage-specific family evolution in Brassicales, but also provide valuable information for further functional analysis of LEA genes in papaya.
Correction: Mothe, J. Analytics Methods to Understand Information Retrieval Effectiveness—A Survey. Mathematics 2022, 10, 2135
Authors: Mothe Josiane
Published: September 2022

The author wishes to make the following corrections to this paper [1]:In Abstract, (1) “It depicts how data analytics has been used in IR for a better understanding system effectiveness” should be “It depicts how data analytics has been used in IR to gain a better understanding of system effectiveness”; (2) “This review concludes lack of full understanding of system effectiveness according to the context although it has been possible to adapt the query processing to some contexts successfully” should be changed to “This review concludes that we lack a full understanding of system effectiveness related to the context which the system is in, though it has been possible to adapt the query processing to some contexts successfully”; (3) “This review also concludes that, even if it is possible to distinguish effective from non effective system on average on a query set” should be changed to “This review also concludes that, even if it is possible to distinguish effective from non-effective systems for a query set” [...]
Entropy Analysis in MHD CNTS Flow Due to a Stretching Surface with Thermal Radiation and Heat Source/Sink
Authors: Sneha K. N. , Mahabaleshwar U. S. , Sharifpur Mohsen , Ahmadi Mohammad Hossein , Al-Bahrani Mohammed
Published: September 2022

The consequence of magnetohydrodynamics (MHD) flow on entropy generation analysis and thermal radiation for carbon nanotubes via a stretched surface through a magnetic field has been discovered. The governing partial differential equations are altered into ordinary differential equations with the aid of the similarity variable. Here, water is considered the base fluid with two types of carbon nanotubes, such as single-wall carbon nanotubes (SWCNTs) and multi-wall carbon nanotubes (MWCNTs). This domain is used in the energy equation, and then it is solved analytically and transferred in terms of hypergeometric function. The existence and nonexistence of solutions for stretching are investigated. Some of the primary findings discussed in this article show that the presence of carbon nanotubes, magnetic field, and Eckert number develop heat transfer in nanofluids and heat sources and that Eckert number reduces entropy formation. Different regulating parameters, such as Casson fluid, mass transpiration, thermal radiation, solid volume fractions, magnetic constraint, and heat source/sink constraint, can be used to analyze the results of velocity and temperature profiles. The novelty of the current study on the influence of magnetic field entropy analysis on CNTs flow with radiation, is that elastic deformation is the subject of this research, and this has not previously been examined. Higher values of heat sources and thermal radiation enhance the heat transfer rate. The study reveals that thermal radiation, Casson fluid; mass transpiration, Darcy number, and Prandtl number increase, and that decrease in the buoyancy ratio, magnetic parameter, and volume fraction decrease the values of the buoyancy ratio, and also control the transfer of heat.
CLTSA: A Novel Tunicate Swarm Algorithm Based on Chaotic-Lévy Flight Strategy for Solving Optimization Problems
Authors: Cui Yi , Shi Ronghua , Dong Jian
Published: September 2022

In this paper, we proposed a tunicate swarm algorithm based on Tent-Lévy flight (TLTSA) to avoid converging prematurely or failing to escape from a local optimal solution. First, we combined nine chaotic maps with the Lévy flight strategy to obtain nine different TSAs based on a Chaotic-Lévy flight strategy (CLTSA). Experimental results demonstrated that a TSA based on Tent-Lévy flight (TLTSA) performed the best among nine CLTSAs. Afterwards, the TLTSA was selected for comparative research with other well-known meta-heuristic algorithms. The 16 unimodal benchmark functions, 14 multimodal benchmark functions, 6 fixed-dimension functions, and 3 constrained practical problems in engineering were selected to verify the performance of TLTSA. The results of the test functions suggested that the TLTSA was better than the TSA and other algorithms in searching for global optimal solutions because of its excellent exploration and exploitation capabilities. Finally, the engineering experiments also demonstrated that a TLTSA solved constrained practical engineering problems more effectively.
POI Recommendation Method of Neural Matrix Factorization Integrating Auxiliary Attribute Information
Authors: Li Xiaoyan , Xu Shenghua , Jiang Tao , Wang Yong , Ma Yu , Liu Yiming
Published: September 2022

Point-of-interest (POI) recommendation is the prevalent personalized service in location-based social networks (LBSNs). A single use of matrix factorization (MF) or deep neural networks cannot effectively capture the complex structure of user–POI interactions. In addition, to alleviate the data-sparsity problem, current methods primarily introduce the auxiliary information of users and POIs. Auxiliary information is often judged to be equally valued, which will dissipate some of the valuable information. Hence, we propose a novel POI recommendation method fusing auxiliary attribute information based on the neural matrix factorization, integrating the convolutional neural network and attention mechanism (NueMF-CAA). First, the k-means and term frequency–inverse document frequency (TF-IDF) algorithms are used to mine the auxiliary attribute information of users and POIs from user check-in data to alleviate the data-sparsity problem. A convolutional neural network and an attention mechanism are applied to learn the expression of auxiliary attribute information and distinguish the importance of auxiliary attribute information, respectively. Then, the auxiliary attribute information feature vectors of users and POIs are concatenated with their respective latent feature vectors to obtain the complete latent feature vectors of users and POIs. Meanwhile, generalized matrix factorization (GMF) and multilayer perceptron (MLP) are used to learn the linear and nonlinear interactions between users and POIs, respectively, and the last hidden layer is connected to integrate the two parts to alleviate the implicit feedback problem and make the recommendation results more interpretable. Experiments on two real-world datasets, the Foursquare dataset and the Weibo dataset, demonstrate that the proposed method significantly improves the evaluation metrics—hit ratio (HR) and normalized discounted cumulative gain (NDCG).
Synergistic Sequential Emission of Fractional 10.600 and 1540 nm Lasers for Skin Resurfacing: An Ex Vivo Histological Evaluation
Authors: Nisticò Steven , Bennardo Luigi , Zingoni Tiziano , Pieri Laura , Fusco Irene , Rossi Francesca , Magni Giada , Cannarozzo Giovanni
Published: September 2022

Background: Fractional ablative and non-ablative lasers are useful treatments for skin rejuvenation. A procedure that provides the sequential application of fractional ablative followed by non-ablative laser treatment may reduce patients’ downtime and deliver better cosmetic results than with either laser alone. Objective: The purpose of the current study was to demonstrate the ameliorative and therapeutic effects in skin remodeling of the synergistic use of the two laser wavelengths (fractional ablative CO2 and non-ablative 1540 nm) with three different types of pulse shapes, S-Pulse (SP), D-Pulse (DP) and H-Pulse (HP), through which the CO2 laser can emit, performing an ex vivo histological evaluation. Methods: In this prospective study, ex vivo sheep inner thigh skin was chosen due to its similarity to human skin tissue, and a histological evaluation was performed. Three irradiation conditions, using all of the three CO2 pulse shapes (alone or averaged), were investigated: (1) 10.600 nm alone, the sequential irradiation of the two wavelengths in the same perfectly controlled energy pulses (DOT) for the entire scan area; ((2) 10.600 nm followed immediately by 1540 nm; and (3) 1540 nm followed immediately by 10.600 nm). Results: When comparing ablative to sequential irradiations, the synergy of the two wavelengths did not alter the typical ablative pulse shape of the 10.600 nm laser alone. With the same CO2 pulse shape, the lesion depth did not vary with the synergy of the two wavelengths, while thermal lesion width increased compared to CO2 alone. The ablation rate was achieved, while the total thermal lesion coverage in the scanning area of CO2 − 1540 lasers was greater than when using CO2 alone and then the other sequential irradiation. Conclusions: This study provides important preclinical data for new and early uses of the novel 10.600/1540 nm dual-wavelength non-ablative fractional laser. The synergy of the two wavelengths enhanced all the benefits already available when using CO2 laser systems both in terms of tone strengthening, thanks to a greater shrinking effect, and in terms of stimulation and collagen remodeling thanks to a greater volumetric thermal effect.
Therapeutic Efficacy of Weissella cibaria CMU and CMS1 on Allergic Inflammation Exacerbated by Diesel Exhaust Particulate Matter in a Murine Asthma Model
Authors: Do Kyung-Hyo , Seo Kwangwon , Kim Sanggu , Kim Soochong , Park Geun-Yeong , Kang Mi-Sun , Lee Wan-Kyu
Published: September 2022

Background and Objectives: Diesel exhaust particulate matter (DEPM) is an air pollutant that is associated with asthma. In this study, the therapeutic efficacy of Weissella cibaria strains CMU (Chonnam Medical University) and CMS (Chonnam Medical School) 1, together with the drug Synatura, an anti-tussive expectorant, was investigated in a murine asthma model exacerbated by DEPM. Materials and Methods: BALB/c mice were sensitized with ovalbumin (OVA) before intranasal challenge with OVA and DEPM. W. cibaria CMU, CMS1, and Synatura were administered orally for 21 days. Results: Neither Synatura nor W. cibaria strains affected spleen, liver, or lung weights. W. cibaria strains CMU and CMS1 significantly reduced the levels of interleukin (IL)-4, OVA-specific immunoglobulin E (IgE), and total lung collagen in bronchoalveolar lavage fluid (BALF), similar to those with Synatura, regardless of the oral dose concentration (p < 0.05). In addition, the W. cibaria CMU strain significantly alleviated IL-1β, IL-6, IL-12, monocyte chemotactic protein-1, and tumor necrosis factor-α in BALF, whereas the CMS1 strain significantly alleviated IL-10 and IL-12 in BALF (p < 0.05); however, Synatura did not show any statistical efficacy against them (p > 0.05). All concentrations of W. cibaria CMU and low concentrations of W. cibaria CMS1 significantly reduced lung bronchiolar changes and inflammatory cell infiltration. Conclusions: In conclusion, W. cibaria CMU in asthmatic mice showed better efficacy than W. cibaria CMS1 in improving asthma exacerbated by DEPM exposure, as well as better results than pharmaceuticals.
Bio-Based Ceramic Membranes for Bacteria Removal from Water
Authors: Kamgang-Syapnjeu Pelagie , Njoya Dayirou , Kamseu Elie , Balme Sebastien , Bechelany Mikhael , Soussan Laurence
Published: September 2022

Bio-based ceramic membranes were elaborated from kaolinite clays, coconut husks and eggshells to retain E. coli bacteria present in water intended for human consumption. Their characterization and removal performances are investigated in this work. These bio-ceramic membranes were obtained by heating the formulation containing 75% clay, 15% coconut husk and 10% eggshell at 900 °C or 1000 °C, at different temperature rates, to give S1, S2 and S3 materials. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), mercury porosimetry and scanning electron microscopy (SEM) were used to characterize these membranes. Water flux density, bacterial removal and biofouling were also assessed. Water flux density was shown to depend on material porosity. Bacteria retention was 90% (with 1 log-removal) for S1, 80% (with 0.7 log-removal) for S2 and 100% (with 3.3 log-removal) for S3. Membranes S1 and S2 presented reversible biofouling, while no fouling was evidenced for S3 in the tested conditions. This work shows that the best bio-ceramic membrane in terms of bacterial removal and flux density was S3. Its water flux density was 2123 ± 72 L/h/m2 at an initial pressure of 0.2 bar. This material is particularly interesting because its production protocol is quite simple, fast and without the addition of chemical additives. Moreover, it can be used to efficiently remove bacteria from drinking water.
Insight into the Relationship between Oral Microbiota and the Inflammatory Bowel Disease
Authors: Han Yimin , Wang Boya , Gao Han , He Chengwei , Hua Rongxuan , Liang Chen , Xin Shuzi , Wang Ying , Xu Jingdong
Published: September 2022

Inflammatory bowel disease has been a growing concern of lots of people globally, including both adults and children. As a chronic inflammatory disease of the intestine, even though the etiology of inflammatory bowel disease is still unclear, the available evidence from clinic observations has suggested a close association with microorganisms. The oral microbiota possesses the characteristics of a large number and abundant species, second only to the intestinal microbiota in the human body; as a result, it successfully attracts the attention of researchers. The highly diverse commensal oral microbiota is not only a normal part of the oral cavity but also has a pronounced impact on the pathophysiology of general health. Numerous studies have shown the potential associations between the oral microbiota and inflammatory bowel disease. Inflammatory bowel disease can affect the composition of the oral microbiota and lead to a range of oral pathologies. In turn, there are a variety of oral microorganisms involved in the development and progression of inflammatory bowel disease, including Streptococcus spp., Fusobacterium nucleatum, Porphyromonas gingivalis, Campylobacter concisus, Klebsiella pneumoniae, Saccharibacteria (TM7), and Candida albicans. Based on the above analysis, the purpose of this review is to summarize this relationship of mutual influence and give further insight into the detection of flora as a target for the diagnosis and treatment of inflammatory bowel disease to open up a novel approach in future clinical practice.
Opportunities and Limitations of Molecular Methods for Studying Bat-Associated Pathogens
Authors: Zemanová Silvia , Korytár Ľuboš , Tomčová Jana , Prokeš Marián , Drážovská Monika , Myczko Łukasz , Tryjanowski Piotr , Nusová Gréta , Matysiak Alicja , Ondrejková Anna
Published: September 2022

Bats have been identified as reservoirs of zoonotic and potentially zoonotic pathogens. Significant progress was made in the field of molecular biology with regard to infectious diseases, especially those that infect more than one species. Molecular methods, sequencing and bioinformatics have recently become irreplaceable tools in emerging infectious diseases research and even outbreak prediction. Modern methods in the molecular biology field have shed more light on the unique relationship between bats and viruses. Here we provide readers with a concise summary of the potential and limitations of molecular methods for studying the ecology of bats and bat-related pathogens and microorganisms.