bluuebunny/crossref_metadata_2025 huggingface dataset:
Immune thrombotic thrombocytopenic purpura: Spotlight on long-term outcomes and survivorship
Authors: Selvakumar Sruthi , Liu Angela , Chaturvedi Shruti
Published: February 2023

Advances in diagnosis and treatment have dramatically improved survival of acute immune thrombotic thrombocytopenic purpura (iTTP) and iTTP has evolved from an acute fatal condition to a chronic relapsing disorder. In addition to the risk of iTTP relapse, iTTP survivors are at risk of multiple adverse health outcomes including higher than expected rates of all-cause mortality, increased rates of stroke and other cardiovascular disease, and higher rates of morbidities such as obesity, hypertension, and autoimmune disorders. iTTP survivors also report neurocognitive impairment, depression, and reduced quality of life. Women with iTTP are at risk for recurrent iTTP, preeclampsia, and other maternal and fetal complications in subsequent pregnancies. ADAMTS13 activity during clinical remission has emerged as an important targetable risk factor for iTTP relapse and other outcomes including stroke and all-cause mortality. This review summarizes current literature regarding the epidemiology and potential mechanisms for adverse long-term sequelae of iTTP, outlines current best practices in iTTP survivorship care, and highlights a research agenda to improve long-term iTTP outcomes.
Research progress on acupuncture treatment in central nervous system diseases based on NLRP3 inflammasome in animal models
Authors: Zhang Hai-Ming , Luo Dan , Chen Rui , Wang Shu-Han , Zhao Ya-Juan , Li Jin-Xiao , Zhou Min-Feng , Yu Zhao-Min , Zhang Jun-Li , Liang Feng-Xia
Published: February 2023

Central nervous system (CNS) disorders exhibit complex neurophysiological and pathological mechanisms, which seriously affect the quality of life in patients. Acupuncture, widely accepted as complementary and alternative medicine, has been proven to exert significant therapeutic effects on CNS diseases. As a part of the innate immune system, NLRP3 inflammasome contributes to the pathogenesis of CNS diseases via regulating neuroinflammation. To further explore the mechanisms of acupuncture regulating NLRP3 inflammasome in CNS diseases, our study focused on the effects of acupuncture on neuroinflammation and the NLRP3 inflammasome in vascular dementia, Alzheimer’s disease, stroke, depression, and spinal cord injury. This study confirmed that the activation of NLRP3 inflammasome promotes the development of CNS diseases, and inhibiting the activation of NLRP3 inflammasome is a potential key target for the treatment of CNS diseases. In addition, it is concluded that acupuncture alleviates neuroinflammation by inhibiting the activation of the NLRP3 inflammasome pathway, thereby improving the progression of CNS diseases, which provides a theoretical basis for acupuncture to attenuate neuroinflammation and improve CNS diseases.
Analysis of factors related to browning of red sour soup during fermentation
Authors: Liu Zhiqi , Zhou Xiaojie , Wen Ming , Gong Zhouliang , Lin Bilian , Zhao Liangzhong , Wang Jianrong
Published: February 2023

As a traditional fermentation food, red sour soup (RSS) is very popular in China. However, browning is always occurred during the process of fermentation, which influences the sensory quality of RSS and limits its further application. Thus, it is meaningful to elucidate the main factors related to browning during the process of fermentation. Herein, the changes in various factors related to browning from group spontaneous (RSS-SF) and inoculant fermentation (RSS-IF) were determined and analyzed. Firstly, the activity changes of enzymes related to browning indicated that browning of group RSS-SF and RSS-IF during fermentation was not related to enzymatic browning. Secondly, path analysis revealed that the main factors related to non-enzymatic browning of group RSS-SF and RSS-IF were oxidation of polyphenol and degradation of ascorbic acid (Vc). The results of this study not only identifies the main factors associate with browning of RSS, but also provides foundation on how to control the browning of RSS in further study.
Automatic quality assurance of radiotherapy treatment plans using Bayesian networks: A multi-institutional study
Authors: Kalendralis Petros , Luk Samuel M. H. , Canters Richard , Eyssen Denis , Vaniqui Ana , Wolfs Cecile , Murrer Lars , Elmpt Wouter van , Kalet Alan M. , Dekker Andre , Soest Johan van , Fijten Rianne , Zegers Catharina M. L. , Bermejo Inigo
Published: February 2023

Purpose

Artificial intelligence applications in radiation oncology have been the focus of study in the last decade. The introduction of automated and intelligent solutions for routine clinical tasks, such as treatment planning and quality assurance, has the potential to increase safety and efficiency of radiotherapy. In this work, we present a multi-institutional study across three different institutions internationally on a Bayesian network (BN)-based initial plan review assistive tool that alerts radiotherapy professionals for potential erroneous or suboptimal treatment plans.

Methods

Clinical data were collected from the oncology information systems in three institutes in Europe (Maastro clinic - 8753 patients treated between 2012 and 2020) and the United States of America (University of Vermont Medical Center [UVMMC] - 2733 patients, University of Washington [UW] - 6180 patients, treated between 2018 and 2021). We trained the BN model to detect potential errors in radiotherapy treatment plans using different combinations of institutional data and performed single-site and cross-site validation with simulated plans with embedded errors. The simulated errors consisted of three different categories: i) patient setup, ii) treatment planning and iii) prescription. We also compared the strategy of using only diagnostic parameters or all variables as evidence for the BN. We evaluated the model performance utilizing the area under the receiver-operating characteristic curve (AUC).

Results

The best network performance was observed when the BN model is trained and validated using the dataset in the same center. In particular, the testing and validation using UVMMC data has achieved an AUC of 0.92 with all parameters used as evidence. In cross-validation studies, we observed that the BN model performed better when it was trained and validated in institutes with similar technology and treatment protocols (for instance, when testing on UVMMC data, the model trained on UW data achieved an AUC of 0.84, compared with an AUC of 0.64 for the model trained on Maastro data). Also, combining training data from larger clinics (UW and Maastro clinic) and using it on smaller clinics (UVMMC) leads to satisfactory performance with an AUC of 0.85. Lastly, we found that in general the BN model performed better when all variables are considered as evidence.

Conclusion

We have developed and validated a Bayesian network model to assist initial treatment plan review using multi-institutional data with different technology and clinical practices. The model has shown good performance even when trained on data from clinics with divergent profiles, suggesting that the model is able to adapt to different data distributions.
Differential regulation of skeletal stem/progenitor cells in distinct skeletal compartments
Authors: Solidum Jea Giezl Niedo , Jeong Youngjae , Heralde Francisco , Park Dongsu
Published: February 2023

Skeletal stem/progenitor cells (SSPCs), characterized by self-renewal and multipotency, are essential for skeletal development, bone remodeling, and bone repair. These cells have traditionally been known to reside within the bone marrow, but recent studies have identified the presence of distinct SSPC populations in other skeletal compartments such as the growth plate, periosteum, and calvarial sutures. Differences in the cellular and matrix environment of distinct SSPC populations are believed to regulate their stemness and to direct their roles at different stages of development, homeostasis, and regeneration; differences in embryonic origin and adjacent tissue structures also affect SSPC regulation. As these SSPC niches are dynamic and highly specialized, changes under stress conditions and with aging can alter the cellular composition and molecular mechanisms in place, contributing to the dysregulation of local SSPCs and their activity in bone regeneration. Therefore, a better understanding of the different regulatory mechanisms for the distinct SSPCs in each skeletal compartment, and in different conditions, could provide answers to the existing knowledge gap and the impetus for realizing their potential in this biological and medical space. Here, we summarize the current scientific advances made in the study of the differential regulation pathways for distinct SSPCs in different bone compartments. We also discuss the physical, biological, and molecular factors that affect each skeletal compartment niche. Lastly, we look into how aging influences the regenerative capacity of SSPCs. Understanding these regulatory differences can open new avenues for the discovery of novel treatment approaches for calvarial or long bone repair.
Decomposing Disability Inequality in Unmet Healthcare Needs and Preventable Hospitalizations: An Analysis of the Korea Health Panel
Authors: Kim Sujin , Jeon Boyoung
Published: February 2023

Objectives: This study examines the inequality between people with and without disabilities regarding unmet healthcare needs and preventable hospitalization.

Methods: We used the Korea Health Panel of 2016–2018; the final analytical observations were 43,512, including 6.95% of persons with disabilities. We examined the differences in contributors to the two dependent variables and decomposed the observed differences into explained and unexplained components using the Oaxaca-Blinder approach.

Results: Unmet healthcare needs and preventable hospitalizations were 5.6% p (15.36% vs. 9.76%) and 0.68% p (1.82% vs. 0.61%), respectively, higher in people with disabilities than in those without, of which 48% and 35% were due to characteristics that the individual variables cannot explain. Decomposition of the distributional effect showed that sex, age, and chronic disease significantly increased disparities for unmet healthcare needs and preventable hospitalization. Socioeconomic factors such as income level and Medical aid significantly increased the disabled–non-disabled disparities for unmet healthcare needs.

Conclusion: Socioeconomic conditions increased the disparities, but around 35%–48% of the disparities in unmet healthcare needs and preventable hospitalization were due to unexplained factors, such as environmental barriers.
Computing the Gromov-Wasserstein Distance between Two Surface Meshes Using Optimal Transport
Authors: Koehl Patrice , Delarue Marc , Orland Henri
Published: February 2023

The Gromov-Wasserstein (GW) formalism can be seen as a generalization of the optimal transport (OT) formalism for comparing two distributions associated with different metric spaces. It is a quadratic optimization problem and solving it usually has computational costs that can rise sharply if the problem size exceeds a few hundred points. Recently fast techniques based on entropy regularization have being developed to solve an approximation of the GW problem quickly. There are issues, however, with the numerical convergence of those regularized approximations to the true GW solution. To circumvent those issues, we introduce a novel strategy to solve the discrete GW problem using methods taken from statistical physics. We build a temperature-dependent free energy function that reflects the GW problem’s constraints. To account for possible differences of scales between the two metric spaces, we introduce a scaling factor s in the definition of the energy. From the extremum of the free energy, we derive a mapping between the two probability measures that are being compared, as well as a distance between those measures. This distance is equal to the GW distance when the temperature goes to zero. The optimal scaling factor itself is obtained by minimizing the free energy with respect to s. We illustrate our approach on the problem of comparing shapes defined by unstructured triangulations of their surfaces. We use several synthetic and “real life” datasets. We demonstrate the accuracy and automaticity of our approach in non-rigid registration of shapes. We provide numerical evidence that there is a strong correlation between the GW distances computed from low-resolution, surface-based representations of proteins and the analogous distances computed from atomistic models of the same proteins.
Survival of Phytophthora cryptogea and Phytophthora cactorum in Commercial Potting Substrates for Eucalyptus globulus Plants
Authors: Benavent-Celma Clara , McLaggan Debbie , van West Pieter , Woodward Steve
Published: February 2023

The international plant trade is considered to be the main pathway causing the spread of oomycetes internationally, especially when live plants are accompanied by soil or potting substrates. Modern, rapid shipping technologies, together with inadequate management practices in nurseries, increase the probability of survival of plant pathogens and the subsequent chances of disease outbreaks in new locations. The survival of two oomycete soil-borne pathogens, Phytophthora cryptogea and Phytophthora cactorum, was studied in two different commercial potting substrates (peat-based and peat-free) in the absence of a plant host under simulated nursery conditions in a glasshouse for 21 months. Colony forming units (CFUs) of both pathogens were recovered 21 months after substrate inoculation, with a decrease in CFUs of between 92 and 99%, depending on the pathogen and substrate. Eucalyptus globulus plants were then planted into these inoculated pots. After 21 months, P. cryptogea and P. cactorum remained capable of producing diseases in E. globulus plants, resulting in up to 30% mortality and an up to 5-fold greater disease severity. These results highlight the ability of these pathogens to survive in the absence of a suitable host plant in potting substrates over time and to then have the capacity to infect a plant. This research adds to the body of essential evidence that is required to develop meaningful management practices and potting substrates at the nursery level to minimize the risk of the spread of oomycetes through the international plant trade.
Comparison of Consumed Power and Safety of Two Types of Semi-Automatic Vegetable Transplanter: Cam and Four-Bar Link
Authors: Markumningsih Sri , Hwang Seok-Joon , Kim Jeong-Hun , Jang Moon-Kyeong , Shin Chang-Seop , Nam Ju-Seok
Published: February 2023

The consumed power and safety of cam and four-bar-link semi-automatic vegetable transplanters were analyzed and compared according to the engine speed and planting distances. A measurement system was constructed to obtain the torque, rotational speed, and strain at the corresponding locations of both transplanters. Field tests were conducted at three engine speeds and three planting distances for each type of transplanter. The torque and rotational speed data of the input shaft of the transplanting devices were used to calculate the power consumed during transplanting. The strain data were converted into stress values to calculate the static safety factor and fatigue life. The results show that the torque and consumed power of the cam transplanter were greater than those of the four-bar-link transplanter under similar operational conditions, owing to its rigid and heavier design. The consumed power increased as the engine speed increased for both types. The static safety factor and fatigue life exhibited different values depending on the measurement location with a sufficient safety margin. Although more skill is required in planting distance control owing to its manual adjustment, the four-bar-link type is more economical under similar operating conditions because of its smaller power requirement.
Wheat Yield Gap Assessment in Using the Comparative Performance Analysis (CPA)
Authors: Laleh Kambiz Mootab , Ghorbani Javid Majid , Alahdadi Iraj , Soltani Elias , Soufizadeh Saeid , González-Andújar José Luis
Published: February 2023

One of the crucial issues in developing nations is diminishing the yield gaps. Therefore, accurate yield gap estimation has many real-world uses for increasing crop production. Utilizing comparative performance analysis (CPA) techniques, the yield gap of wheat fields was evaluated in this study. In Varamin, Tehran Province, Iran, data on 104 wheat fields were collected between 2018 and 2020 and every aspect of wheat field management has been documented. The CPA model determines the yield gap’s contributing factors and potential yield. The results of data analysis revealed that the production ranged from 2600 to 7600 kg ha−1. The CPA method predicted a potential yield of 9316 kg ha−1 and found a yield gap of 3748 kg ha−1; this amount was 40.23% of the potential yield. Leaf chlorophyll (29%), irrigation at stem extension (9%), LAI (7.7%), soil salinity (8.2%), field area (16.3%), phosphorus consumption (6%), nitrogen utilized at the stage of tillering (16%), and HI (7.8%) all contributed to the yield gap in the CPA. It has been said that the computed yield in CPA is a potential yield that can be reached. CPA is a cheap and straightforward tool that could identify yield gaps and their causes in a district without the need for costly experiments. Therefore, developing nations with significant efficiency and yield gaps can use these techniques effectively.
Eco-Physiological Behavior of Five Tunisian Olive Tree Cultivars under Drought Stress
Authors: Boussadia Olfa , Omri Amal , Mzid Nada
Published: February 2023

Tunisia is known to be a country with poor water resources, and water scarcity is evident in certain regions. In the long term, this situation could worsen, given the increased risk of drought. The olive tree (Olea europaea L.) is one of the plants best adapted to this climate, and numerous studies have been carried out to assess the effects of water stress. The aim of this work was to study and compare the ecophysiological behavior of a main Tunisian olive cultivar (Chetoui) and four rare Tunisian olive cultivars (Chemchali, Besbessi, Sayali and Jarboui) under drought stress and to identify the main parameters while comparing the tolerance of the cultivars studied to this abiotic stress. One-year-old olive trees grown in pots in a greenhouse were subjected to four drought treatments (i.e., 15, 30, 45 and 60 days of drought stress) in comparison with control trees. The evaluation of the response of the olives to this induced stress was based on five parameters: relative water content (RWC), stomatal resistance (SR), photosystem PSII, maximal photochemical efficiency (FV/FM), performance index on absorption basis (PI), measured by the handy PEA, and chlorophyll index, measured by SPAD. The relative water content (RWC) of the five cultivars decreased with increasing drought stress. Jarboui showed lower RWC values than Chemchali, especially under severe drought stress. This result was confirmed by changes in fluorescence characteristics. FV/FM, PI and SPAD index decreased during the development of drought stress. These observations are discussed in relation to the strategies developed by the cultivars to grow under drought stress. The Principal Component Analysis allowed the parameter with the strongest loading factor, which is FV/FM, to be highlighted and the cultivars most tolerant to drought stress to be distinguished. These cultivars, Besbessi and Sayali in the north of Tunisia and Chemchali in the south, can present a possible alternative to replace the local or foreign cultivars most cultivated in the country, which are characterized by high water needs.
Climate Change and Citriculture: A Bibliometric Analysis
Authors: Rasera Júlia Boscariol , da Silva Roberto Fray , Mourão Filho Francisco de Assis Alves , Delbem Alexandre Cláudio Botazzo , Saraiva Antonio Mauro , Sentelhas Paulo Cesar , Marques Patricia Angélica Alves
Published: February 2023

Citrus are the most produced fruits worldwide. It is expected that these crops will be severely affected by climate change. However, the literature lacks works that attempt to understand the influence of climate change on citrus. For this reason, a bibliometric analysis was conducted on climate change and citrus to investigate its development and current trends in this research domain. The main trends, keywords, and their relations were identified. The period from 1992 to 2022 was analyzed, resulting in 178 documents in the Scopus database. The most significant publishers’ countries were also the largest citrus producers in the world besides being G7 members. Three main research areas were identified: modeling, socio-political issues, and plant physiology. A tendency to change interest from modeling and risk analysis to physiology and stress studies was observed. Additionally, some of the most cited papers observed the positive impacts of climate change on certain citrus crops. Despite the multidisciplinary publications, two main gaps were identified: (i) the lack of investigations with combined stresses (abiotic and biotic) instead of isolated studies, and (ii) the lack of studies of predictive models for citrus production in different conditions and climate change scenarios. Finally, there was a tendency toward studying water use and irrigation alternatives due to water scarcity and management solutions to improve the production system’s resilience, considering the potential impacts of climate change.
Aquaculture Sludge as Co-Substrate for Sustainable Olive Mill Solid Waste Pre-Treatment by Anthracophyllum discolor
Authors: Araneda Michael , Pinto-Ibieta Fernanda , Xu Xiaofan , Rubilar Olga , Fermoso Fernando G. , Ciudad Gustavo
Published: February 2023

Olive mill solid waste (OMSW) is an agro-industrial waste that has a high content of recalcitrant lignocellulose, which can adversely affect the environment. This study aimed to evaluate the phenol and lignin removal and the enzyme activity involved in the biological pre-treatment of OMSW supplemented with aquaculture sludge (AS) as an external nitrogen source by Anthracophyllum discolor. The highest lignin removal and enzymatic activity performance was obtained in the mixture of OMSW and AS prepared at a C/N ratio 45. In these conditions, the pre-treatment could remove 66% of lignin and 68% of phenols in the solid phase and 56% of phenols in the liquid phase and the maximum activity of laccase, manganese peroxidase and manganese independent peroxidase were of 10, 289 and 75 U L−1 in 25, 30, and 15 days of pre-treatment, respectively. These results propose that the addition of AS as a co-substrate for adjusting the C/N ratio allows a 41 and 141% increase in lignin removal and manganese peroxidase activity respectively, enabling the treatment of both OMSW and AS wastes and the possible recovery of an enzymatic extract of biotechnological interest.
Management of Osteoarthritis and Joint Support Using Feed Supplements: A Scoping Review of Undenatured Type II Collagen and Boswellia serrata
Authors: Zapata Ana , Fernández-Parra Rocio
Published: February 2023

In the multimodal management of osteoarthritis (OA) in recent decades, the use of feed supplements to maintain joint cartilage has been advocated. The aim of this scoping review is to present the results found in the veterinary literature on the use of undenatured type II collagen and Boswellia serrata in dogs, specifically its use in dogs with clinical signs of OA, healthy dogs after intense exercise or dogs with diseases that predispose the individual to OA. For this purpose, a literature review was carried out using the electronic databases PubMed, Web of Science and Google Scholar, from which a total of 26 records were included in this review: fourteen evaluating undenatured type II collagen, ten evaluating Boswellia serrata and two evaluating the combination of undenatured type II collagen and Boswellia serrata. The review of the records showed that undenatured type II collagen decreases the clinical signs associated with OA, improving the general clinical state with a reduction in the degree of lameness and increase in physical activity or mobility. Evaluating the response to supplementation with Boswellia serrata alone is complicated due to the limited publication of studies and variations in the purity and compositions of the products used, but in general terms, its combination with other feed supplements produces benefits by relieving pain and reducing the clinical signs of OA in dogs. The combination of both in the same product provides results similar to those obtained in undenatured type II collagen studies. In conclusion, undenatured type II collagen and Boswellia serrata are considered a valid option for the multimodal approach to the management of OA and for improving activity during intense exercise, but more studies are needed to conclude whether or not it prevents OA in dogs.
Lipoprotein-Associated Phospholipase A2 Activity as Potential Biomarker of Vascular Dementia
Authors: Zuliani Giovanni , Marsillach Judit , Trentini Alessandro , Rosta Valentina , Cervellati Carlo
Published: February 2023

A wealth of evidence suggests that Lipoprotein-associated phospholipase A2 (Lp-PLA2) plays a relevant role in atherogenesis and inflammation, which in turn are associated with the risk of developing dementia. The aim of this study was to evaluate whether serum Lp-PLA2 activity might be an early and/or late biomarker for different forms of dementia. Serum Lp-PLA2 activity was assessed in older patients with mild cognitive impairment (MCI, n = 166; median clinical follow-up = 29 months), Late-Onset Alzheimer’s disease (LOAD, n = 176), vascular dementia (VAD, n = 43), dementia characterized by an overlap between LOAD and VAD (AD-VAD MIXED dementia) (n = 136), other dementia subtypes (n = 45), and cognitively normal controls (n = 151). We found a significant trend towards higher levels of Lp-PLA2 activity in VAD compared with the other groups (ANOVA, p = 0.028). Similarly, Lp-PLA2 activity was greater in MCI converting to VAD compared with those that did not or did convert to the other types of dementia (ANOVA, p = 0.011). After adjusting for potential confounders, high levels of Lp-PLA2 activity were associated with the diagnosis of VAD (O.R. = 2.38, 95% C.I. = 1.06–5.10), but not with other types of dementia. Our data suggest that increased serum Lp-PLA2 activity may represent a potential biomarker for the diagnosis of VAD.
Selecting an Optimal Scenario for Addressing Supplier Selection Problem by Considering Sustainable Scheduling: A Hybrid Approach
Authors: Quan Bingtao , Li Sujian , Wu Kuo-Jui
Published: February 2023

The iron and steel industry is a pillar industry of the national economy in many countries and is also a source of high energy consumption and pollution gas emissions. In addition to the economic aspect, there have been increasing concerns over how to minimise the negative environmental impact and enhance the awareness of social responsibility for iron and steel enterprises. Therefore, this study proposes an intelligent scheduling system for addressing the supplier selection problem by considering sustainable scheduling (SS) (ISS-AFLCSS) to achieve maximised benefits of logistics costs, carbon emission and fatigued driving for the Chengsteel Company. In the ISS-AFLCSS, first, a multiobjective mathematical optimisation model is formulated. Second, this study proposed a hybrid approach using an improved genetic algorithm (GA) to optimise multiple objectives of scenarios and adopting the technique for order preference by similarity to an ideal solution (TOPSIS) method with the analytic hierarchy process (AHP) to precisely optimise and select a best-ideal scenario. The results confirm that the proposed ISS-AFLCSS can provide accurate guidance in practicing SS for managers of enterprises.
A Domain-Driven Framework to Analyze Learning Dynamics in MOOCs through Event Abstraction
Authors: Hidalgo Luciano , Munoz-Gama Jorge
Published: February 2023

Interest in studying Massive Online Open Courses (MOOC) learners’ sessions has grown as a result of the retention and completion issues that these courses present. Applying process mining to study this phenomenon is difficult due to the freedom of navigation that these courses give their students. The goal of this research is to provide a domain-driven top-down method that enables educators who are unfamiliar with data and process analytics to search for a set of preset high-level concepts in their own MOOC data, hence simplifying the use of typical process mining techniques. This is accomplished by defining a three-stage process that generates a low-level event log from a minimum data model and then abstracts it to a high-level event log with seven possible learning dynamics that a student may perform in a session. By examining the actions of students who successfully completed a Coursera introductory programming course, the framework was tested. As a consequence, patterns in the repetition of content and assessments were described; it was discovered that students’ willingness to evaluate themselves increases as they advance through the course; and four distinct session types were characterized via clustering. This study shows the potential of employing event abstraction strategies to gain relevant insights from educational data.
A Numerical Investigation of Induced and Embedded Trench Installations for Large-Diameter Thermoplastic Pipes under High Fill Stresses
Authors: Kılıç Havvanur , Biçer Perihan , Bozkurt Sercan
Published: February 2023

The induced trench installation method is applied by placing material with high compressibility on rigid pipes to reduce the earth pressures acting on them. Although the performance of this method for rigid pipes has been investigated, research on thermoplastic pipes is very limited. In this study, induced trench installation (ITI) and embedded trench installation (ETI) of large-diameter thermoplastic pipes subjected to high fill stresses were investigated by numerical analysis. The numerical model has been verified by considering the field experiments, and a series of analyses were carried out by placing Expanded Polystyrene Foam (EPS Geofoam) in ITI and ETI models. Pipe stresses and deflections were evaluated by considering the pipe diameter, stiffness, and backfill properties. The ITI and ETI models in thermoplastic pipes reduced the stresses acting on the pipes and increased the positive arching regardless of the deflection of the pipe. For pipes with an inner diameter of 0.762 to 1.524 m under 30 m of fill stress, approximately 1.5 to 3.0% deflection occurred. In the ETI model, the horizontal earth pressure in the spring line of the pipe decreased from 65 to 40% depending on the backfill type, and an approximately uniform stress distribution was formed around the pipe.
Role Knowledge Prompting for Document-Level Event Argument Extraction
Authors: Hu Ruijuan , Liu Haiyan , Zhou Huijuan
Published: February 2023

Document-level event argument extraction (DEAE) aims to identify the arguments corresponding to the roles of a given event type in a document. However, arguments scattering and arguments and roles overlapping make DEAE face great challenges. In this paper, we propose a novel DEAE model called Role Knowledge Prompting for Document-Level Event Argument Extraction (RKDE), which enhances the interaction between templates and roles through a role knowledge guidance mechanism to precisely prompt pretrained language models (PLMs) for argument extraction. Specifically, it not only facilitates PLMs to understand deep semantics but also generates all the arguments simultaneously. The experimental results show that our model achieved decent performance on two public DEAE datasets, with 3.2% and 1.4% F1 improvement on Arg-C, and to some extent, it addressed the overlapping arguments and roles.
Toward a Multi-Column Knowledge-Oriented Neural Network for Web Corpus Causality Mining
Authors: Ali Wajid , Zuo Wanli , Wang Ying , Ali Rahman
Published: February 2023

In the digital age, many sources of textual content are devoted to studying and expressing many sorts of relationships, including employer–employee, if–then, part–whole, product–producer, and cause–effect relations/causality. Mining cause–effect relations are a key topic in many NLP (natural language processing) applications, such as future event prediction, information retrieval, healthcare, scenario generation, decision making, commerce risk management, question answering, and adverse drug reaction. Many statistical and non-statistical methods have been developed in the past to address this topic. Most of them frequently used feature-driven supervised approaches and hand-crafted linguistic patterns. However, the implicit and ambiguous statement of causation prevented these methods from achieving great recall and precision. They cover a limited set of implicit causality and are difficult to extend. In this work, a novel MCKN (multi-column knowledge-oriented network) is introduced. This model includes various knowledge-oriented channels/columns (KCs), where each channel integrates prior human knowledge to capture language cues of causation. MCKN uses unique convolutional word filters (wf) generated automatically using WordNet and FrameNet. To reduce MCKN’s dimensionality, we use filter selection and clustering approaches. Our model delivers superior performance on the Alternative Lexicalization (AltLexes) dataset, proving that MCKN is a simpler and distinctive approach for informal datasets.
A Novel Generative Adversarial Network Model Based on GC-MS Analysis for the Classification of Taif Rose
Authors: Abdelmigid Hala M. , Baz Mohammed , AlZain Mohammed A. , Al-Amri Jehad F. , Zaini Hatim G. , Morsi Maissa M. , Abualnaja Matokah , Alhuthal Nawal Abdallah
Published: February 2023

Rose oil production is believed to be dependent on only a few genotypes of the famous rose Rosa damascena. The aim of this study was to develop a novel GC-MS fingerprint based on the need to expand the genetic resources of oil-bearing rose for industrial cultivation in the Taif region (Saudi Arabia). Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for determining the volatile composition of distilled rose oil from flower data. Because biosample availability, prohibitive costs, and ethical concerns limit observations in agricultural research, we aimed to enhance the quality of analysis by combining real observations with samples generated in silico. This study proposes a novel artificial intelligence model based on generative adversarial neural networks (GANs) to classify Taif rose cultivars using raw GC-MS data. We employed a variant of the GAN known as conditional stacked GANs (cSGANs) to predict Taif rose’s oil content and other latent characteristics without the need to conduct laboratory tests. A hierarchical stack of conditional GANs is used in this algorithm to generate images. A cluster model was developed based on the dataset provided, to quantify the diversity that should be implemented in the proposed model. The networks were trained using the cross-entropy and minimax loss functions. The accuracy of the proposed model was assessed by measuring losses as a function of the number of epochs. The results prove the ability of the proposed model to perfectly generate new real samples of different classes based on the GC-MS fingerprint.
A Study on Development of New Type Rubber Boot for Sleeper Floating Track System (STEDEF): Materials and Shapes
Authors: Choi Jung-Youl , Kim Sun-Hee , Park Hee Soo , Chung Jee-Seung
Published: February 2023

Urban railway sleeper floating track (STEDEF) reduces the block vibration transmitted to the subgrade structure by structurally separating the sleeper and the concrete bed, using a rubber boot and a resilient pad. Recently, the replacement of rubber boot material (SBR) after long-term wear and tear has become of utmost importance because of durability problems such as deformation, tearing, and abrasion. This study investigates rubber boots—a component of the urban railway sleeper floating track—to resolve these concerns and proposes the material and shape of a novel rubber boot. The proposed rubber boot reduces the maximum displacement and strain by more than 83% and 90%, respectively, compared with the existing rubber boots. In addition, the results of numerical analysis and indoor tests show that type 3 rubber boots can prevent displacement and stress generation in rubber boots.
Study of Sound Perception Evaluation in Refrigeration Gases
Authors: Rodríguez-Cantalejo Rafael David , Vázquez-Serrano Francisco , Cubero-Atienza Antonio J. , Redel-Macías María Dolores
Published: February 2023

(1) Background: In the past, sound design was focused on the minimization of the emitted sound, understanding that the lower the sound, the better. Nowadays, this concept is outdated; in addition to the sound pressure level, many more aspects of the sound are considered to fulfil the subjective satisfaction of clients. Thus, a new concept called sound quality has emerged to reach more facets of the sound. In refrigeration systems, the recommendations of European Union are aimed at reducing greenhouse emissions by means of the replacement of the hydrochlorofluorocarbons gases with other less pollutant gases. The refrigeration systems are designed to be used with a specific refrigeration gas, and the noise emitted by these systems is certificated using this refrigeration gas. However, the regularizations have changed, and new refrigerant gases should be used. Considering that these new refrigeration gases work at different pressures, it is possible that the noise could be different with these gases. Moreover, the study of sound quality is very important for the manufacture as the perception and therefore the annoyance could change with the use of new gases. (2) Methods: Two different gases, R-449A and R-134A, have been studied. An acoustic camera has been used to measure and identify the sound quality in the refrigeration systems. (3) Results: The results have shown R-134A has better sound quality than R-449A. (4) Conclusions: This study shows that R-449A and R-134A could be a substitute for R-404A in terms of noise level.
The Quality of Scutellaria baicalensis Georgi Is Effectively Affected by Lithology and Soil’s Rare Earth Elements (REEs) Concentration
Authors: Sun Zijian , Shen Wei , Fang Weixuan , Zhang Huiqiong , Chen Ziran , Xiong Lianghui , An Tianhao
Published: February 2023

The top-geoherb “Rehe Scutellaria baicalensis” was naturally distributed on Yanshan Mountain in Chengde city, Hebei Province, China. Exploring the influences of parent materials on the quality of the top-geoherbs in terms of micronutrient elements is of great significance for the protection of origin and for optimizing replanting patterns of Scutellaria baicalensis. In this study, three habitats of Scutellaria baicalensis with contrasting geopedological conditions, i.e., naturally grown habitats (NGHs), artificial planting habitats (APHs), and biomimetic cultivation habitats (BCHs), are taken as objects to probe the influences of parent materials on the quality of Scutellaria baicalensis in terms of rare earth elements (REEs) by testing on REEs concentrations in the weathering profiles, rhizosphere soil and growing Scutellaria baicalensis, as well as their flavonoid compound contents. Hornblende-gneiss was the parent rock in NGHs, whose protolith was femic volcanic rock. Loess was the parent rock in APHs and BCHs. REEs were more abundant in hornblende-gneiss than loess, and therefore, soils developed in NGHs contained higher REE concentrations than those in APHs, which was lower than BCHs after REE-rich micro-fertilizers application. The coefficient of variation (CV) of REEs concentrations in the rhizosphere soils of hornblende-gneiss was higher than that in loess. It possibly was attributed to the complicated minerals compositions and various minerals’ grain sizes of hornblende-gneiss, resulting in the variety of weathering intensity involving eluviation, leaching, adsorption, etc., as well as weathering productions, dominated by clay minerals and Fe-(hydro)oxide, and ultimately the remarkable differences in the migrations, enrichments and fractionations within REEs. The biological absorption coefficients (BACs) of REEs for Scutellaria baicalensis decreased in the order of NGHs > APHs > BCHs. Roots of Scutellaria baicalensis contained similar ΣREE in NGHs (2.02 mg·kg−1) and BCHs (2.04 mg·kg−1), which were higher than that in APHs (1.78 mg·kg−1). Soils developed in hornblende-gneiss were characterized by lower clay fraction content and overall alkalinity with a pH value of 8.06. The absorption and utilization efficiency of REEs for Scutellaria baicalensis in NGHs was higher than in APHs and BCHs. Flavonoid compounds, effective constituents of Scutelleria baicalensis, showed more accumulations in NGHs than APHs and BCHs, implying their optimal quality of Scutellaria baicalensis in NGHs. Flavonoid compounds were remarkably correlated with REEs in the roots, suggesting the influence of REEs concentrations on the quality of Scutellaria baicalensis. It can be concluded that high REEs and micronutrient element concentrations of hornblende-gneiss favored the synthesis and accumulation of flavonoid compounds in Scutellaria baicalensis after the activation of endocytosis induced by REEs.
Real-Time Advanced Computational Intelligence for Deep Fake Video Detection
Authors: Bansal Nency , Aljrees Turki , Yadav Dhirendra Prasad , Singh Kamred Udham , Kumar Ankit , Verma Gyanendra Kumar , Singh Teekam
Published: February 2023

As digitization is increasing, threats to our data are also increasing at a faster pace. Generating fake videos does not require any particular type of knowledge, hardware, memory, or any computational device; however, its detection is challenging. Several methods in the past have solved the issue, but computation costs are still high and a highly efficient model has yet to be developed. Therefore, we proposed a new model architecture known as DFN (Deep Fake Network), which has the basic blocks of mobNet, a linear stack of separable convolution, max-pooling layers with Swish as an activation function, and XGBoost as a classifier to detect deepfake videos. The proposed model is more accurate compared to Xception, Efficient Net, and other state-of-the-art models. The DFN performance was tested on a DFDC (Deep Fake Detection Challenge) dataset. The proposed method achieved an accuracy of 93.28% and a precision of 91.03% with this dataset. In addition, training and validation loss was 0.14 and 0.17, respectively. Furthermore, we have taken care of all types of facial manipulations, making the model more robust, generalized, and lightweight, with the ability to detect all types of facial manipulations in videos.
Polycyclic Aromatic Hydrocarbons in Popcorn Corn Varieties and Popcorns
Authors: Habschied Kristina , Krstanović Vinko , Kartalović Brankica , Galić Vlatko , Ledenčan Tatjana , Mastanjević Krešimir , Zdunić Zvonimir
Published: February 2023

Popping corn is a widespread activity and popcorns are one of the most consumed snacks in the world. As popcorn corn is exposed to environmental conditions and agrotechnical measures in the field, polycyclic aromatic hydrocarbons (PAHs) can end up in corn kernels. Since popcorns are popped at higher temperatures, ca. 180 °C, it is reasonable to assume that PAHs can be found in popcorns. The objective of this paper was to preliminarily determine and quantify the incidence of various PAHs in different popcorn varieties and popcorns popped from them, during two consecutive years. PAHs were determined by using GC-MS. Popcorn corn contained only light PAHs, naphthalene (Nap), acenaphthene (Ane), and fluorene (Fln). However, popped popcorns contained heavier PAHs, such as benz[a]anthracene (BaA), chrysene (Chry), and benzo[a]pyrene (BaP) whose ∑PAH4 was 8.39 µg/kg in sample 1 in 2020. The results indicate that popcorns can be a significant source of PAHs and further studies should be conducted. This is concerning since popcorns are favored snacks in all age groups, including children.
Biochar Extracts Can Modulate the Toxicity of Persistent Free Radicals in the Nematode Caenorhabditis elegans
Authors: Zhang Xuchao , Saul Nadine , Lieke Thora , Chen Yi , Wu Min , Pan Bo , Steinberg Christian E. W.
Published: February 2023

As an effective soil amendment, biochars require a comprehensive ecological evaluation before they can be widely used in agriculture because endogenous contaminants, such as environmentally persistent free radicals (EPFRs), certainly pose an ecological risk to soil invertebrates. In this study, Caenorhabditis elegans (C. elegans) was used as a model organism to investigate the neurotoxicity of two rice straw biochars pyrolyzed at 500 and 700 °C. After 24 h exposure to unwashed biochar, washed biochar, and leaching fluids (supernatants), the neurobehavioral parameters of C. elegans were determined in a liquid toxicity test. The results showed that the washed 700 °C biochar particles significantly impaired locomotion and prolonged the defecation interval at a biochar concentration of 4 g·well−1, while the unwashed biochar and supernatants caused no apparent impairment. Supporting this, electron paramagnetic resonance (EPR) results showed that the intensity of EPFRs in unwashed 700 °C biochar was stronger than that of the corresponding washed particles. This indicates that, in the liquid test, the EPR signal alone is not indicative of particle toxicity. The accessibility and activity of the EPFRs should be considered. Dissolved organic matter (DOM) was observed in the leaching fluids. The neurotoxic activity of the washed biochar was alleviated after the re-addition of leaching fluids to the washed biochar, suggesting that the dissolved organic materials modulate the reactivity of the EPFRs in the liquid phase. This study suggests that the leaching process may increase the risk of biochar when used in the field environment.
Prediction of Effective Elastic and Thermal Properties of Heterogeneous Materials Using Convolutional Neural Networks
Authors: Béji Hamdi , Kanit Toufik , Messager Tanguy
Published: February 2023

The aim of this study is to develop a new method to predict the effective elastic and thermal behavior of heterogeneous materials using Convolutional Neural Networks CNN. This work consists first of all in building a large database containing microstructures of two phases of heterogeneous material with different shapes (circular, elliptical, square, rectangular), volume fractions of the inclusion (20%, 25%, 30%), and different contrasts between the two phases in term of Young modulus and also thermal conductivity. The contrast expresses the degree of heterogeneity in the heterogeneous material, when the value of C is quite important (C >> 1) or quite low (C << 1), it means that the material is extremely heterogeneous, while C= 1, the material becomes totally homogeneous. In the case of elastic properties, the contrast is expressed as the ratio between Young’s modulus of the inclusion and that of the matrix (C = EiEm), while for thermal properties, this ratio is expressed as a function of the thermal conductivity of both phases (C = λiλm). In our work, the model will be tested on two values of contrast (10 and 100). These microstructures will be used to estimate the elastic and thermal behavior by calculating the effective bulk, shear, and thermal conductivity values using a finite element method. The collected databases will be trained and tested on a deep learning model composed of a first convolutional network capable of extracting features and a second fully connected network that allows, through these parameters, the adjustment of the error between the found output and the expected one. The model was verified using a Mean Absolute Percentage Error (MAPE) loss function. The prediction results were excellent, with a prediction score between 92% and 98%, which justifies the good choice of the model parameters.