bluuebunny/crossref_metadata_2025 huggingface dataset:
Visual continuous time preferences
Authors: Prissé Benjamin
Published: July 2023

We introduce the Visual Continuous Time Preferences (VCTP) task, a new tool for measuring time preferences that synthesizes the simplicity of Multiple Price List (MPL) and the precision of Convex Time Budget (CTB) tasks thanks to the use of a simple visualization. We evaluate VCTP in a lab experiment by comparing it to MPL using the same experimental design. Results suggest that VCTP effectively measures time preferences and enhances their precision without increasing task time or decreasing subject consistency. We also find that the BRIS payment scheme has an impact on outcomes, compared to hypothetical and real payments. We conclude that visual experiments can effectively measure economic preferences.
A Bioinformatics Analysis of Ovarian Cancer Data Using Machine Learning
Authors: Schilling Vincent , Beyerlein Peter , Chien Jeremy
Published: July 2023

The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1.
Coconut Value Chain Analysis: A Systematic Review
Authors: Zainol Fakhrul Anwar , Arumugam Nalini , Daud Wan Norhayate Wan , Suhaimi Nurul Aisyah Mohd , Ishola Balogun Daud , Ishak Aida Zairina , Afthanorhan Asyraf
Published: July 2023

In the past, Malaysia’s coconut sector faced several difficulties and upheavals related to the economy. However, as a result of the EU’s decision to oppose the cultivation of palm oil due to worries about forest clearing and environmental damage, the business has recently demonstrated enormous potential to be further grown and improved. Thus, this systematic review aimed to synthesize the challenges associated with the level of coconut production and its supply chain. Six electronic databases were searched for publication from 2013 to 2022 (i.e., a cumulative index to give an overview of the coconut value chain and the literature on the coconut supply chain via Scopus, the Web of Science, Google Scholar, Proquest, Science Direct, and Springer Link). Titles/abstracts and then full texts were screened independently. It was discovered that the factors contributing to the low production of coconuts and the difficulties in the coconut supply chain were categorized by some authors as severe or apparent factors, while others categorized these problems as technological, political, or socioeconomic factors, and yet others categorized them as inherent or environmental factors. Therefore, policymakers should introduce some policies such as subsidies, free tax for farmers, farm settlement schemes e.t.c that would encourage more citizens to be willing to go into coconut production. Policymakers also need to encourage scientists to carry out research on how these problems especially environmental factors will be tackled and try to recruit more extensionists.
Developing Plant-Growth-Promoting Rhizobacteria: A Crucial Approach for Achieving Sustainable Agriculture
Authors: Wang Dandan , Wang Chao , Chen Yinglong , Xie Zhihong
Published: July 2023

The rhizosphere is the zone surrounding plant roots where microbial activity attains its maximum potential, playing pivotal roles in maintaining plant health [...]
Appraisal of Soil Taxonomy and the World Reference Base for Soil Resources Applied to Classify Purple Soils from the Eastern Sichuan Basin, China
Authors: Meng Qian , Li Song , Liu Bin , Hu Jin , Liu Junyan , Chen Yangyang , Ci En
Published: July 2023

Purple soil is a type of global soil that is referred to by various names in different countries, which makes it difficult to understand, utilize, and ameliorate purple soil internationally. Soil Taxonomy (ST) and the World Reference Base for Soil Resources (WRB) are the most widely used soil classification systems in the world. The aim of this study was to clarify the classification of purple soil in ST and the WRB and to establish a reference between different classification systems of purple soil. Therefore, based on the current principles and methods of the ST and WRB systems, 18 typical purple soil profiles in the eastern Sichuan Basin were identified, retrieved, and classified. Then, the soil units of the WRB were compared with those of ST and the Chinese Soil Taxonomy (CST). The results revealed that the 18 typical purple soil profiles could be classified into three soil orders, four soil group orders, and seven soil subgroups in ST and four reference soil groups (RSGs) in the WRB; each profile had its own unique principal and supplementary qualifier combinations within the soil units. It was found that when compared with the ST system, the WRB and CST systems had stronger abilities to distinguish purple soil. In addition, the WRB system was able to more comprehensively consider soil characteristics such as soil layer thickness, ferric horizon, soil color, texture mutations, and carbonate through qualifiers. However, the CST system added diagnostic characteristics, such as the lithologic characteristics of purplish sandstones and shales and the ferric properties and alic properties at the soil group and subgroup levels, which enhanced the differentiation ability of the purple soil at the subgroup level.
Method for Segmentation of Banana Crown Based on Improved DeepLabv3+
Authors: He Junyu , Duan Jieli , Yang Zhou , Ou Junchen , Ou Xiangying , Yu Shiwei , Xie Mingkun , Luo Yukang , Wang Haojie , Jiang Qiming
Published: July 2023

As the banana industry develops, the demand for intelligent banana crown cutting is increasing. To achieve efficient crown cutting of bananas, accurate segmentation of the banana crown is crucial for the operation of a banana crown cutting device. In order to address the existing challenges, this paper proposed a method for segmentation of banana crown based on improved DeepLabv3+. This method replaces the backbone network of the classical DeepLabv3+ model with MobilenetV2, reducing the number of parameters and training time, thereby achieving model lightweightness and enhancing model speed. Additionally, the Atrous Spatial Pyramid Pooling (ASPP) module is enhanced by incorporating the Shuffle Attention Mechanism and replacing the activation function with Meta-ACONC. This enhancement results in the creation of a new feature extraction module, called Banana-ASPP, which effectively handles high-level features. Furthermore, Multi-scale Channel Attention Module (MS-CAM) is introduced to the Decoder to improve the integration of features from multiple semantics and scales. According to experimental data, the proposed method has a Mean Intersection over Union (MIoU) of 85.75%, a Mean Pixel Accuracy (MPA) of 91.41%, parameters of 5.881 M and model speed of 61.05 f/s. Compared to the classical DeepLabv3+ network, the proposed model exhibits an improvement of 1.94% in MIoU and 1.21% in MPA, while reducing the number of parameters by 89.25% and increasing the model speed by 47.07 f/s. The proposed method enhanced banana crown segmentation accuracy while maintaining model lightweightness and speed. It also provided robust technical support for relevant parameters calculation of banana crown and control of banana crown cutting equipment.
Transmural Ultrasonography in the Evaluation of Horse Hoof Internal Structures: Comparative Quantitative Findings—Part 2
Authors: Castro-Mesa Andrés Felipe , Resende Faleiros Rafael , Martínez-Aranzales José Ramón
Published: July 2023

The transmural ultrasound allows for the definition of the normal appearance of the hoof tissues and internal structures. Determining such measurements and proportions could contribute to evaluations of the normal spatial distal phalanx–hoof relationship. The objective was to describe the hoof’s dermis and epidermis measurements using the transmural technique, in comparison with DR and anatomical sections. Sixty-two healthy hooves without digital radiographic abnormalities, made up of 30 anatomical pieces (phase 1) and 32 alive horse hooves (phase 2), and 16 sagittal sections of the first ones were used. The proximal and distal planes were compared, defining the following measurements: coronary band-extensor process, distal phalanx apex–hoof wall, sole dermis, middle stratum, parietal dermis, lamellar layer, the sublamellar dermis, and ratios between them. Most of the measurements were consistent among methods. Some showed measurement differences and a minority was impossible to determine. The transmural technique allowed for the observation and replication of measurements of the hoof structures, described with other diagnostic aids. It also allowed for the implementation of new measurements that would help to determine the spatial location of the distal phalanx. Additionally, it contributes to the visualization of normal findings, which will be useful to compare variations in the different phases of laminitis.
PRRSV-1 Stabilization Programs in French Farrow-to-Finish Farms: A Way to Reduce Antibiotic Usage
Authors: Teixeira Costa Charlotte , Berton Pauline , Boulbria Gwenaël , Normand Valérie , Brissonnier Mathieu , Lebret Arnaud
Published: July 2023

Infection with the porcine reproductive and respiratory syndrome virus type 1 (PRRSV-1) has serious economic consequences for the pig industry. Swine practitioners and other agricultural advisors often describe an increase in antibiotic use when PRRSV-1 is circulating. Our objective was to assess the impact of PRRSV-1 stabilization programs on reducing antibiotic use in 19 French farrow-to-finish farms that successfully implemented such a protocol between 2007 and 2019. For each farm, we compared the global antibiotic consumption, including all physiological stages (expressed in mg/PCU and ALEA) one year before (P1) and one year after (P2) the implementation of the protocol, and the change between P1 and P2 was calculated in percentages. The data were also analyzed by level of consumption. We showed that antibiotic use decreased significantly between P1 and P2 if expressed in mg/PCU and showed a decreased tendency in terms of exposure (ALEA) after PRRSV-1 stabilization. Concerning the change from P1 to P2, depending on the level of consumption in P1, our results showed that the higher the consumption levels were in P1, the greater the antibiotic reduction in P2. This study highlights the ability of a stabilization protocol against PRRSV-1 to reduce antibiotic use, especially on farms that have high consumption rates. These hopeful results show that further investigations about the relationship between PRRSV-1 and antibiotic usage could be beneficial.
Building a Teleost Fish Traceability Program Based on Genetic Data from Pacific Panama Fish Markets
Authors: Díaz-Ferguson Edgardo , Chial Magaly , Gonzalez Maribel , Muñoz Edgardo , Chen Olga , Durán Ovidio , Vega Angel Javier , Delgado Carlos Ramos
Published: July 2023

Fish tissue samples from 203 adult individuals were collected in the main ports and markets of the Pacific coast of Panama. Molecular identification based on a cytochrome oxidase I gene segment of all species was verified by GENBANK reference sequences. A total of 34 species from 14 families (Ariidae, Caranjidae, Centropomidae, Gerreidae, Haemulidae, Lobotidae, Lutjanidae, Malacanthidae, Mugilidae, Scianidae, Scombridae, Serranidae, Sphyraenidae, Stromateidae) were identified at the species level from 164 sequences. Additionally, three Caribbean species were molecularly identified among the analyzed samples (Mycteroperca xenarcha, Paralonchurus brasilensis and Lobotes surinamensis). Species diversity was slightly higher in the Gulf of Panama than in the Gulf of Chiriquí. For species with five or more individual sequences, genetic diversity and genetic connectivity parameters such as total number of haplotypes (H), haplotype diversity (Hd), and nucleotide diversity (π) were calculated. Overall, pelagic-migratory species showed higher values of genetic diversity than coastal and estuarine species with some exceptions. Connectivity between Gulf areas was compared using values of genetic distances and genetic differentiation (Fst). The high level of connectivity observed between the Gulf of Chiriqui and the Gulf of Montijo indicates the existence of a single stock in that area for the following species: Scomberomorus sierra, Caranx caninus and Lutjanus guttatus. The demographic history of the most common species was examined using Tajima’s D values, suggesting population expansion for two snapper species, L. peru and L. argentiventris, having significant and higher values. Another important contribution from this research was the production of primers and dual-labeled probes for environmental DNA detection using qPCR for the five most abundant species (spotted rose snapper, yellow snapper, green jack, Pacific crevalle jack and the Pacific sierra fish). These markers represent a new set of tools for environmental DNA (eDNA) detection and molecular traceability of three commercially important fish species along the supply chain including landing sites and markets of the main fishery areas.
Potential Saving of Antibiotics for Respiratory Infections in Several European Countries: Insights from Market Research Data
Authors: Gessner André , Klimek Ludger , Kuchar Ernest , Stelzmueller Ingrid , Fal Andrzej M. , Kardos Peter
Published: July 2023

Antibiotics represent an essential pillar in the treatment of respiratory infections (RI). Overuse of antibiotics in avoidable cases and inappropriate application in bacterial infections facilitate treatment resistance, threatening their effectiveness and causing a significant healthcare challenge. We therefore assessed the savings potential for antibiotics in ambulant care of selected RI (bronchitis and cough, pharyngitis, rhinosinusitis) in several European countries based on market research data for the year 2019. Number of antibiotic packages sold in pharmacies varied, with highest values in Serbia and France, and lowest in Sweden and Switzerland. Selected RI contributed nearly half of overall ambulant antibiotic prescriptions, with around one fifth given for bronchitis and cough; the vast majority was estimated to be of viral origin with potentially avoidable antibiotic use. Antibiotic consumption for selected RI in eight European countries (Austria, Belgium, the Czech Republic, France, Germany, Poland, Slovakia, and Switzerland) amounted to nearly 100 million, with an overall savings potential between 66.2 and 83.7 million packages. The highest estimated volume of avoidable antibiotics was in France (44.7 million, 0.80 per capita), and lowest in Switzerland (1.4 million, 0.18 per capita). Due to substantial savings potential, prudent use of antibiotics and adequate application of alternatives should be promoted in daily practice.
Response Surface Methodology for the Optimization of Flavan-3-ols Extraction from Avocado By-Products via Sonotrode Ultrasound-Assisted Extraction
Authors: Razola-Díaz María del Carmen , Verardo Vito , Guerra-Hernández Eduardo Jesús , García-Villanova Ruiz Belén , Gómez-Caravaca Ana María
Published: July 2023

Avocado peel and seed are the main by-products of avocado processing and are considered as promising sources of phenolic compounds with biological activities. Thus, this research focuses on the establishment, for the first time, of ultrasound-assisted extraction of flavan-3-ols with high antioxidant activity from avocado peel and seed using a sonotrode. Indeed, 2 Box–Behnken designs were performed for 15 experiments, with each design having three independent factors (ratio ethanol/water (v/v), time (min) and amplitude (%)). In both models, the responses included total procyanidins (flavan-3-ols) measured via HPLC-FLD and antioxidant activity measured via DPPH, ABTS and FRAP. The results showed that applying the sonotrode extraction method could increase flavan-3-ols recovery by 54% and antioxidant activity by 62–76% compared to ultrasound bath technology. Therefore, this technology was demonstrated to be a non-thermal, low time-consuming and scalable method that allowed the recovery of flavan-3-ols from avocado by-products that could be used as functional ingredients.
β-Asarone Alleviates High-Glucose-Induced Oxidative Damage via Inhibition of ROS Generation and Inactivation of the NF-κB/NLRP3 Inflammasome Pathway in Human Retinal Pigment Epithelial Cells
Authors: Park Cheol , Cha Hee-Jae , Hwangbo Hyun , Bang EunJin , Hong Su Hyun , Song Kyoung Seob , Noh Jeong Sook , Kim Do-Hyung , Kim Gi-Young , Choi Yung Hyun
Published: July 2023

Diabetic retinopathy (DR) is the leading cause of vision loss and a major complication of diabetes. Hyperglycemia-induced accumulation of reactive oxygen species (ROS) is an important risk factor for DR. β-asarone, a major component of volatile oil extracted from Acori graminei Rhizoma, exerts antioxidant effects; however, its efficacy in DR remains unknown. In this study, we investigated whether β-asarone inhibits high-glucose (HG)-induced oxidative damage in human retinal pigment epithelial (RPE) ARPE-19 cells. We found that β-asarone significantly alleviated cytotoxicity, apoptosis, and DNA damage in HG-treated ARPE-19 cells via scavenging of ROS generation. β-Asarone also significantly attenuated the excessive accumulation of lactate dehydrogenase and mitochondrial ROS by increasing the manganese superoxide dismutase and glutathione activities. HG conditions markedly increased the release of interleukin (IL)-1β and IL-18 and upregulated their protein expression and activation of the nuclear factor-kappa B (NF-κB) signaling pathway, whereas β-asarone reversed these effects. Moreover, expression levels of the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome multiprotein complex molecules, including thioredoxin-interacting protein, NLRP3, apoptosis-associated speck-like protein containing a caspase-recruitment domain, and cysteinyl aspartate-specific proteinase-1, were increased in ARPE-19 cells under HG conditions. However, their expression levels remained similar to those in the control group in the presence of β-asarone. Therefore, β-asarone protects RPE cells from HG-induced injury by blocking ROS generation and NF-κB/NLRP3 inflammasome activation, indicating its potential as a therapeutic agent for DR treatment.
Preparation and Modification of Activated Carbon for the Removal of Pharmaceutical Compounds via Adsorption and Photodegradation Processes: A Comparative Study
Authors: Samir Brahim , Bouazizi Nabil , Nkuigue Fotsing Patrick , Cosme Julie , Marquis Veronique , Dotto Guilherme Luiz , Le Derf Franck , Vieillard Julien
Published: July 2023

In the present research, the removal of pharmaceutical contaminants based on atenolol (AT) and propranolol (PR) using modified activated carbon (AC) in a liquid solution was studied. Two methods, adsorption and photodegradation, were used to eliminate AT and PR. First, AC was prepared from date stems and then modified via hydroxylation (AC-OH) and impregnated into titanium dioxide (AC-TiO2) separately. The removal of AT and PR was investigated in terms of experimental parameters, such as pH, concentration, temperature, and the effectiveness of the processes. The results show that the removal of AT and PR reached 92% for the adsorption method, while 94% was registered for the photodegradation process. Likewise, in optimal experimental conditions, the adsorption of AT and PR over AC-OH showed good stability and recyclability, achieving five cycles without a visible decrease in the removal capacity. The results obtained in this work suggest that the low-cost and environmentally friendly synthesis of AC-OH is suitable to be considered for wastewater treatment at the industrial scale. Interestingly, the above results open a potential pathway to determine whether adsorption or photodegradation is more suitable for eliminating wastewater-related pharmaceutical pollutants. Accordingly, the experimental results recommend adsorption as a promising, durable, eco-friendly wastewater treatment method.
Long-Term Durability of Cement-Treated Soil Used in Offshore Airport Island Construction
Authors: Takahashi Hidenori , Sato Itsuki , Morikawa Yoshiyuki , Ozawa Akira
Published: July 2023

In port and harbour areas, soft soils such as dredged soil can be solidified by mixing them with cement and other solidifiers in a pumping pipe. This method is known as pneumatic flow mixing. In this method, the soil and solidifiers are stirred and mixed using the turbulence effect of the plug flow generated in the pipe. The authors investigate the long-term durability of the treated soil on the artificial island where this method was first fully introduced. This paper summarises the results of five investigations on the island immediately after construction and 4, 10, 15, and 20 years after construction. No reduction in the unconfined compressive strength or needle penetration gradient was observed in the treated soil. Some degradation was observed at the top and bottom exposed surfaces of the treated soil, similar to that of soil subjected to other treatments. In addition to needle penetration and chemical tests, elemental mapping using an electron beam microanalysis was performed to determine the degree of degradation. The depth of degradation 20 years after construction was 18–25 mm. Although the amount of cement added in the pneumatic flow mixing method was relatively small, this value was within the range of degradation depths over time investigated in previous studies and did not represent a significant degradation.
Indicative Effect of Excess Topography on Potential Risk Location of Giant Ancient Landslides—A Case Study in Lengqu River Section
Authors: Wang Xin , Bai Shibiao
Published: July 2023

In order to identify giant ancient landslides more effectively and to quantify the risk of giant ancient landslides, this study takes a Lengqu River section located on the Qinghai–Tibet Plateau as an example and then uses the red relief image map (RRIM) method to enhance the digital elevation model (DEM) for topographic 2D visualization to identify giant ancient landslides. Then, the relationships between giant ancient landslides (GALs), resurgent GALs, the deposition of inactive GALs and the excess topography of hillslopes under 30° threshold are analyzed separately. A total of 54 GALs are identified at last by using the RRIM method; 77.75% of GALs are still located on excess topography, 68.38% of resurgent GALs occurred on excess topography, and 62.21% of the deposition of inactive GALs are on non-excess topography. The RRIM method provides a new way to identify giant ancient landslides. The excess topography provides an indication of the risk of new landslides through the destructive effect of GALs on the threshold hillslope, and the preliminary investigation of the quantitative relationship between the resurrection of GALs and excess topography also shows that there is a certain pattern between the resurrection of GALs and the excess topography under the natural state, so the excess topography has a certain indication of the generation of new landslides and secondary resurrection at the original GAL positions.
Modeling of the Drag Force in Polydisperse Gas–Solid Flow via an Efficient Supervised Machine Learning Approach
Authors: Li Xin , Ouyang Jie , Wang Xiaodong , Dou Jingxi
Published: July 2023

Most granular flow in nature and industrial processing has the property of polydispersity, whereas we are always restricted to using the monodisperse drag force model in simulations since the drag force model with polydispersity is difficult to establish. Ignoring polydispersity often results in obvious deviations between simulation and experimental outcomes. Generally, it is very hard for us to describe the characteristics of polydispersity in drag force by using a function with analytic expression. Recently, the artificial neural network (ANN) model provides us the advantages of estimating these kinds of outcomes with better accuracy. In this work, the ANN is adopted to model the drag force in polydisperse granular flows. In order to construct a reasonable ANN algorithm for modeling the polydisperse drag force, the structures of ANN are elaborately designed. As training for the ANN drag model, a direct numerical simulation method is proposed, based on the lattice Boltzmann method (LBM), to generate the training data, and an adaptive data filtering algorithm, termed as the optimal contribution rate algorithm (OCRA), is introduced to effectively improve the training efficiency and avoid the over-fitting problems. The results support that the polydispersity of the system can be well scaled by the ANN drag model in a relatively wide range of particle concentrations, and the predicted results coincide well with the experimental ones. Moreover, the ANN drag model is not only effective for polydisperse systems, but compatible with monodisperse systems, which is impossible using traditional drag models.
Automatic Fruits Freshness Classification Using CNN and Transfer Learning
Authors: Amin Umer , Shahzad Muhammad Imran , Shahzad Aamir , Shahzad Mohsin , Khan Uzair , Mahmood Zahid
Published: July 2023

Fruit Freshness categorization is crucial in the agriculture industry. A system, which precisely assess the fruits’ freshness, is required to save labor costs related to tossing out rotten fruits during the manufacturing stage. A subset of modern machine learning techniques, which are known as Deep Convolution Neural Networks (DCNN), have been used to classify images with success. There have recently been many changed CNN designs that gradually added more layers to achieve better classification accuracy. This study proposes an efficient and accurate fruit freshness classification method. The proposed method has several interconnected steps. After the fruits data is gathered, data is preprocessed using color uniforming, image resizing, augmentation, and image labelling. Later, the AlexNet model is loaded in which we use eight layers, including five convolutional layers and three fully connected layers. Meanwhile, the transfer learning and fine tuning of the CNN is performed. In the final stage, the softmax classifier is used for final classification. Detailed simulations are performed on three publicly available datasets. Our proposed model achieved highly favorable results on all three datasets in which 98.2%, 99.8%, and 99.3%, accuracy is achieved on aforesaid datasets, respectively. In addition, our developed method is also computationally efficient and consumes 8 ms on average to yield the final classification result.
Road Accident Hotspots on Jordan’s Highway Based on Geometric Designs Using Structural Equation Modeling
Authors: Aldala’in Shatha Aser , Abdul Sukor Nur Sabahiah , Obaidat Mohammed Taleb , Abd Manan Teh Sabariah Binti
Published: July 2023

One of the primary objectives of transportation engineering is to increase the safety of road infrastructure. This study seeks to determine the relationship between geometric design parameters in relation to road accident criteria based on accident hotspots on Jordan’s Desert Highway. The road accident data (from 2016 to 2019) were collected from the Jordan Traffic Department. The spatial pattern of hotspots was identified using a GIS tool named Getis-Ord Gi* based on the severity index of road accidents. A topographic survey was conducted to investigate the road alignment and intersections at hotspot locations. The study utilized the Structural Equation Modeling (SEM) technique via SmartPLS to highlight the correlation between geometric designs in relation to road accidents. The hotspot analysis (Gits-Ord Gi) discovered 80 road accident hotspots along the highway. The study found that horizontal alignment and road intersections significantly impact road accidents in hotspot locations. Furthermore, vertical alignment has no effect on road accidents in hotspot areas. The study enhanced the comprehension of the factors associated with road geometrics and intersections that affect the occurrence of road accidents.
Investigation on Numerical Simulation of VIV of Deep-Sea Flexible Risers
Authors: Jia Liyuan , Sang Song , Shi Xiao , Shen Fukui
Published: July 2023

The vortex-induced vibration (VIV) of flexible risers is a complex fluid–structure interaction (FSI) phenomenon. In this study, we conducted a numerical simulation method based on the slicing method to study the vortex-induced vibration (VIV) of deep-sea flexible risers with different slenderness ratios and uniform flow velocities. The method combines the finite element model of the riser structure with the two-dimensional flow field slices solved by the Fluent solver. The fluid–structure interaction was realized by a self-compiled UDF program and the overset mesh technique. The numerical results were validated by comparing them with experimental data. The VIV characteristics of the riser, such as the vibration track, vibration mode, vibration frequency and wake vortex shedding mode, were analyzed. The article reveals the nonlinear dynamic features of flexible riser vibration, such as multi-frequency vibration, wide-frequency vibration and multi-modal vibration. The article also provides insights into the fluid–structure interaction mechanism of VIV of deep-sea flexible risers.
Revolutionizing Marine Traffic Management: A Comprehensive Review of Machine Learning Applications in Complex Maritime Systems
Authors: Durlik Irmina , Miller Tymoteusz , Dorobczyński Lech , Kozlovska Polina , Kostecki Tomasz
Published: July 2023

This review article explores the applications and impacts of Machine Learning (ML) techniques in marine traffic management and prediction within complex maritime systems. It provides an overview of ML techniques, delves into their practical applications in the maritime sector, and presents an in-depth analysis of their benefits and limitations. Real-world case studies are highlighted to illustrate the transformational impact of ML in this field. The article further provides a comparative analysis of different ML techniques and discusses the future directions and opportunities that lie ahead. Despite the challenges, ML’s potential to revolutionize marine traffic management and prediction, driving safer, more efficient, and more sustainable operations, is substantial. This review article serves as a comprehensive resource for researchers, industry professionals, and policymakers interested in the interplay between ML and maritime systems.
Triangular Silver Nanoparticles Synthesis: Investigating Potential Application in Materials and Biosensing
Authors: Rodriguez Barroso Laura G. , Lanzagorta Garcia Eduardo , Mojicevic Marija , Huerta Miriam , Pogue Robert , Devine Declan M. , Brennan-Fournet Margaret
Published: July 2023

Triangular silver nanoplates (TSNPs) exhibit unique optical and antimicrobial properties due to their shape, sharp edges, and vertices. In this study, TSNPs were incorporated into biopolymer blends (bacterial cellulose (BC) with polylactic acid (PLA), polycaprolactone (PCL), and polyhydroxybutyrate (PHB)). Antimicrobial activity of materials was tested against Escherichia coli ATCC 95922 and Staphylococcus aureus ATCC 25923 (106 CFU/mL). After incubation (24 h at 37 °C, 100 rpm), optical density was measured at 630 nm. In order to assess biosensing applications, specifically fibronectin (Fn) behavior, TSNPs were protected with gold (AuTSNP) and analyzed via sucrose sensitivity test and monitored by localized surface plasmon resonance (LSPR). Additionally, AuTSNPs were coated with polyethylene glycol (PEGAuTSNP). Fibronectin functionalization of PEGAuTSNPs and pH-conformation was monitored (FnPEGAuTSNP). Eventually, adequate Fn and anti-Fn antibody concentrations were determined. BC/PHB/TSNPs showed antimicrobial activity against E. coli and S. aureus with 80 and 95% of growth inhibition, respectively. The sucrose sensitivity test indicated that the LSPRλmax of the spectra is directly proportional to the sucrose concentration. LSPRλmax of Fn-PEGAuTSNPs at pH 7 and pH 4 were measured at 633 and 643 nm, respectively. A total of 5 µg of Fn was determined to be adequate concentration, while 0.212 mg/mL of anti-Fn antibody indicatied system saturation.
Study on Roof Instability Effect and Bearing Characteristics of Hydraulic Support in Longwall Top Coal Caving
Authors: Zeng Qingliang , Li Zhaoji , Wan Lirong , Ma Dejian
Published: July 2023

In longwall top coal caving (LTCC), due to the fracture and migration of top coal, the roof will break and collapse, which causes serious impact damage to hydraulic support. Therefore, we aimed to reveal the relationship between the roof instability effect and the bearing characteristics of hydraulic support in the LTCC face. Based on the occurrence conditions of the 08 mining area in the Shilawusu Coal Mine, the instability model of the upper immediate roof was established, and the working resistance of hydraulic support was derived. Secondly, the dynamic coupling model of roof-top coal-hydraulic support was established in LS-DYNA, and the crushing degree of top coal and the bearing characteristics of the hydraulic support in different roof instability fields were analyzed. The results show that the main factors affecting the working resistance of hydraulic support are the fracture position of the upper immediate roof, the acting force of the lower immediate roof, and the distribution of the gangue in the goaf. The rotary instability of the upper immediate roof at the coal wall brings serious impact effects, resulting in fractures in front of the coal wall and a large amount of crushed coal concentrated at the front end of the canopy. The crushing degree of top coal significantly impacts the canopy, especially the back end of the canopy and the hinged pin shaft, which is prone to bending fracture. The research results can provide references and experience for the stability control of roof strata and the structural optimization of hydraulic support.
Accelerating Pattern Matching Using a Novel Multi-Pattern-Matching Algorithm on GPU
Authors: Çelebi Merve , Yavanoğlu Uraz
Published: July 2023

Nowadays, almost all network traffic is encrypted. Attackers hide themselves using this traffic and attack over encrypted channels. Inspections performed only on packet headers and metadata are insufficient for detecting cyberattacks over encrypted channels. Therefore, it is important to analyze packet contents in applications that require control over payloads, such as content filtering, intrusion detection systems (IDSs), data loss prevention systems (DLPs), and fraud detection. This technology, known as deep packet inspection (DPI), provides full control over the communication between two end stations by keenly analyzing the network traffic. This study proposes a multi-pattern-matching algorithm that reduces the memory space and time required in the DPI pattern matching compared to traditional automaton-based algorithms with its ability to process more than one packet payload character at once. The pattern-matching process in the DPI system created to evaluate the performance of the proposed algorithm (PA) is conducted on the graphics processing unit (GPU), which accelerates the processing of network packets with its parallel computing capability. This study compares the PA with the Aho-Corasick (AC) and Wu–Manber (WM) algorithms, which are widely used in the pattern-matching process, considering the memory space required and throughput obtained. Algorithm tables created with a dataset containing 500 patterns use 425 and 688 times less memory space than those of the AC and WM algorithms, respectively. In the pattern-matching process using these tables, the PA is 3.5 and 1.5 times more efficient than the AC and WM algorithms, respectively.
The Statistical Error Optimization of Dye Sorption Equilibria for the Precise Prediction of Adsorption Isotherms on Activated Graphene
Authors: Deb Hridam , Hasan K. , Islam Md Zahidul , Kai Lv , Yang Shujuan , Zhang Yong , Yao Juming
Published: July 2023

The adsorption equilibrium of methyl blue (MB) at different temperatures was optimized using activated graphene (AG) as an adsorbent. The experimental data were compared using five linear and nonlinear adsorption isotherms, namely, Langmuir, Freundlich, Redlich–Peterson (R-P), Sips, and Toth, to estimate the best fit of the equilibrium data. Five distinct error functions were utilized to conduct nonlinear regression for the adsorption equilibrium: SSE, ARE, HYBRID, MPSD, and EABS. These functions offered a wide range of residuals for comparison. For a more accurate prediction of the isotherm model, two statistical techniques—SNE and CND—were applied. By using these techniques in conjunction, a more objective analysis of the error and deviation between the observed and predicted data was achieved, ultimately leading to improved accuracy in the error analysis. The sorption results demonstrated the highest MB removal of 691.89 mg g−1, which amounted to 98.32% within 120 min. The error analysis findings indicated that the SSE and HYBRID functions produced the smallest error residuals. Based on the “goodness of fit” criterion, the models in this study were ranked as R-P > Toth > Langmuir > Sips > Freundlich. Among these models, the R-P isotherm demonstrated the best fit for the data, exhibiting the lowest variance in residuals. Its CND value ranged between 0.0025 and 0.0048, which further supports its superior fit compared to the other models. The combination of multiple error functions and statistical methods allowed for a comprehensive and objective assessment of the nonlinear regression models. The results highlight the importance of using various techniques to improve the accuracy of error analysis and identify the best-fitting isotherms for adsorption.
Safety Assessment and Uncertainty Quantification of Electromagnetic Radiation from Mobile Phones to the Human Head
Authors: Yi Miao , Wu Boqi , Zhao Yang , Su Tianbo , Chi Yaodan
Published: July 2023

With the rapid development of the mobile communication technology, the design of mobile phones has become more complex, and research on the electromagnetic radiation from mobile phones that reaches the human head has become important. Therefore, first of all, a model of mobile phone daily use was established. Then, based on the established simulation model, the safety of human head exposure to mobile phones was evaluated. The generalized polynomial chaos (gPC) method was used to establish a proxy model of the specific absorption rate (SAR) of the human head at different frequencies to perform a parameter uncertainty quantification (UQ). Finally, the Sobol method was used to quantify the influence of relevant variables on the SAR. The simulation results showed that the gPC method can save time and cost while ensuring accuracy, and the SAR value is greatly influenced by the electromagnetic materials of the mobile phone shell. Combined with the above analysis, this paper can provide reasonable suggestions for the design of mobile phone electromagnetic materials.
A Guide to Data Collection for Computation and Monitoring of Node Energy Consumption
Authors: del Rio Alberto , Conti Giuseppe , Castano-Solis Sandra , Serrano Javier , Jimenez David , Fraile-Ardanuy Jesus
Published: July 2023

The digital transition that drives the new industrial revolution is largely driven by the application of intelligence and data. This boost leads to an increase in energy consumption, much of it associated with computing in data centers. This fact clashes with the growing need to save and improve energy efficiency and requires a more optimized use of resources. The deployment of new services in edge and cloud computing, virtualization, and software-defined networks requires a better understanding of consumption patterns aimed at more efficient and sustainable models and a reduction in carbon footprints. These patterns are suitable to be exploited by machine, deep, and reinforced learning techniques in pursuit of energy consumption optimization, which can ideally improve the energy efficiency of data centers and big computing servers providing these kinds of services. For the application of these techniques, it is essential to investigate data collection processes to create initial information points. Datasets also need to be created to analyze how to diagnose systems and sort out new ways of optimization. This work describes a data collection methodology used to create datasets that collect consumption data from a real-world work environment dedicated to data centers, server farms, or similar architectures. Specifically, it covers the entire process of energy stimuli generation, data extraction, and data preprocessing. The evaluation and reproduction of this method is offered to the scientific community through an online repository created for this work, which hosts all the code available for its download.
Deammonification Potential of Pig Slurries and Vapor Condensates from Sewage Sludge Drying—Substrate Quality and Inhibition
Authors: Reiter Johannes , Beier Maike
Published: July 2023

Deammonification is a well-established process for sludge liquor treatment and promising for wastewaters with high nitrogen loads because of its low energy demand compared to nitrification/denitrification. Two wastewaters with high NH4-N concentrations and a rising significance in Germany—pig slurry (12 samples) and condensates from sewage sludge drying (6 samples)—were studied for their deammonification potential. Furthermore, a comprehensive quality assessment is presented. Both wastewaters show a wide range in terms of CODt, CODs, TN and NH4-N, whereby condensates show a greater variability with no direct relation to dryer type or temperature. In the slurries, CODt shows a relative standard deviation of 106% (mean 21.1 g/L) and NH4-N of 33% (mean 2.29 g/L), while in condensates it reaches 148% for CODt (mean 2.0 g/L) and 122% for NH4-N (mean 0.7 g/L). No inhibition of ammonium-oxidizing-bacteria was detected in the slurries, while two out of five condensates showed an inhibition of >40%, one of >10% and two showed no inhibition at all. Since the inhibition could be avoided by mixing, deammonification can be recommended for condensate treatment. For slurry treatment, the importance of employing some form of solid-liquid-separation as a pretreatment was noted due to the associated COD.
Biosynthesis, Spectrophotometric Follow-Up, Characterization, and Variable Antimicrobial Activities of Ag Nanoparticles Prepared by Edible Macrofungi
Authors: Youssef Mohamed S. , Ahmed Sanaa Ibrahim , Mohamed Ibrahim M. A. , Abdel-Kareem Marwa M.
Published: July 2023

The biosynthesis of silver nanoparticles (Ag NPs) could play a significant role in the development of commercial antimicrobials. Herein, the biosynthesis of Ag NPs was studied using the edible mushroom Pleurotus floridanus, and following its formation, spectrophotometry was used to detect the best mushroom content, pH, temperature, and silver concentration. After that, the morphology was described via transmission electron microscopy (TEM), and nanoscale-size particles were found ranging from 11 to 13 nm. The best conditions of Ag content and pH were found at 1.0 mM and 11.0, respectively. In addition, the best mushroom extract concentration was found at 30 g/L. According to XRD analysis, the crystal structure of the formed amorphous Ag NPs is cubic with a space group of fm-3m and a space group number of 225. After that, the function groups at the surface of the prepared Ag NPs were studied via FTIR analysis, which indicated the presence of C=O, C-H, and O-H groups. These groups could indicate the presence of mushroom traces in the Ag NPs, which was confirmed via the amorphous characteristics of Ag NPs from the XRD analysis. The prepared Ag NPs have a high impact against different microorganisms, which could be attributed to the ability of Ag NPs to penetrate the cell bacterial wall.
Rapid On-Site Detection of SARS-CoV-2 Using RT-LAMP Assay with a Portable Low-Cost Device
Authors: Fu Quanying , Pang Xueyuan , Su Zhenning , Yang Yuxiao , Liu Yiren , Zhang Ziyue , Fu Yuqiu , Wang Jiasi , Zhou Jianhua
Published: July 2023

Emerging infectious diseases pose a serious threat to human health and affect social stability. In recent years, the epidemic situation of emerging infectious diseases is very serious; among these infectious diseases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected many countries and regions in a short time. The prevention and treatment of these diseases require rapid on-site detection methods. However, the common detection method, RT-PCR, requires expensive instruments, complex operations, and professional operators. Here, we developed a portable low-cost assay for rapid on-site detection of viral nucleic acid using reverse transcription-loop-mediated isothermal amplification (RT-LAMP). The SARS-CoV-2 RNA can be successfully amplified within 15 min in a thermos, and the detection result is read rapidly in a portable low-cost device with a sensitivity of 100 copies/µL. The portable low-cost device consists of a black box, a laser or LED and a filter, costing only a few cents. The rapid on-site detection method can provide strong support for the control of biological threats such as infectious diseases. It is also an emergency detection method for low-resource settings, relieving the huge pressure on health care.
A Review of Artificial Intelligence in the Rupture Risk Assessment of Intracranial Aneurysms: Applications and Challenges
Authors: Li Xiaopeng , Zeng Lang , Lu Xuanzhen , Chen Kun , Yu Maling , Wang Baofeng , Zhao Min
Published: July 2023

Intracranial aneurysms (IAs) are highly prevalent in the population, and their rupture poses a significant risk of death or disability. However, the treatment of aneurysms, whether through interventional embolization or craniotomy clipping surgery, is not always safe and carries a certain proportion of morbidity and mortality. Therefore, early detection and prompt intervention of IAs with a high risk of rupture is of notable clinical significance. Moreover, accurately predicting aneurysms that are likely to remain stable can help avoid the risks and costs of over-intervention, which also has considerable social significance. Recent advances in artificial intelligence (AI) technology offer promising strategies to assist clinical trials. This review will discuss the state-of-the-art AI applications for assessing the rupture risk of IAs, with a focus on achievements, challenges, and potential opportunities.