bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping sustainable practices and concepts in the transportation ecosystem for the EU-27 countries, based on LinkedIn company profiles
Authors: Tsironis Georgios , Karagkouni Aristi , Dimitriou Dimitrios , Tsagarakis Konstantinos P.
Published: October 2023

Sustainability has been a topic of growing interest over the past years with many governments, organizations, and companies trying to achieve the Sustainable Development Goals. The major challenge of implementing more sustainable practices within the corporate environments is still in the foreground, probably even in higher demand, due to the intense environmental degradation and the strict deadlines related to the decarbonization and shift towards greener production systems. Indicatively, the European Commission suggests that transport currently accounts for a quarter of the European Union’s (EU) greenhouse gas emissions and this figure continues to rise as demand grows. In this work, we investigate the transportation sector, distribution systems, and supply chain through the prism of sustainability by mining and analyzing open-access data on the LinkedIn social media platform, which is widely used for professional networking, especially, in the European market. Thus, we extract valuable insights into the current trends around sustainability within the transportation sector. More precisely, 1,638 LinkedIn profiles registered as “companies” related to transportation have been data mined providing valuable outputs regarding their sustainability-oriented activities. Our dataset contains companies with a staff range of over 200 employees, aiming to gain insights from medium SMEs and large organizations. Key findings of our analysis include the differentiation of application areas regarding sustainable concepts and the rise of the percentage of sustainability-related companies with the company staff size combined with a rather strong connection between the United Kingdom’s and United States’s transportation sectors.
Development of millet-acid whey formulations with nutritional, microbiological, and sensory characterization
Authors: Malik Sargun , Mustapha Azlin , Krishnaswamy Kiruba
Published: October 2023

Introduction

Disposal of the acid whey waste stream is one of the major challenges faced by the Greek yogurt industry. However, based on its physicochemical characteristics and composition analysis, it has huge potential in the health industry. Likewise, millets are highly nutritive and health benefitting ancient grains. Combining acid whey and millet matrix can help in solving the problem of both food losses and food security. Hence, the objective of the study is to analyze the enhancement or degradation of the nutrition profile when acid whey is combined with millet matrix using spray-drying technology.

Method

The methodology of the study includes composition analysis and functional characterization based on antioxidant properties, microbial analysis, and sensory evaluation.

Results and discussion

The results showed that there was enhancement of functional properties of the millet-acid whey formulation matrix specifically in terms of polyphenolic compounds, lactose content, and mineral content. Overall, the study aims to provide an alternative method for the utilization and consumption of acid whey that is currently being mishandled and considered as waste by the Greek yogurt manufacturing companies.
A Hybrid Approach for Soil Total Nitrogen Anomaly Detection Integrating Machine Learning and Spatial Statistics
Authors: Zheng Wengang , Lan Renping , Zhangzhong Lili , Yang Linnan , Gao Lutao , Yu Jingxin
Published: October 2023

Soil total nitrogen is one of the most important basic indicators for fertiliser decision making, but tens of millions of soil total nitrogen sampling data have been accumulated, forming a huge database. In this large database, there is a large amount of anomalous data, which can interfere with data analysis, affect the construction of spatial interpolation and prediction models, and then affect the accuracy of nutrient management decisions. The traditional method of identifying soil total nitrogen anomalies based on boxplots suffers from the problems of not being able to identify local anomalies, which can easily lead to misclassification of soil total nitrogen data anomalies, and the detection efficiency is not high. We propose a method to identify soil total nitrogen outliers by combining the Isolation Forest algorithm and local spatial autocorrelation analysis, which can simultaneously detect global and local outliers from large amounts of data and combine organic matter as an auxiliary indicator in the spatial analysis to help judge local outliers. Finally, the results of global and local anomalies were combined to provide a comprehensive assessment of the soil nitrogen data, avoiding the misjudgement or omission of judgement that can occur when using a single method. Using 25,930 soil test data from Yunnan Province in 2009 as an example, we compared and analysed the typical boxplot method and the unsupervised OneClassSVM method and evaluated the performance of each method in terms of correct detection rate, false positive rate and false negative rate. The results show that the proposed method has a correct detection rate (TR) of 99.97%, a false positive rate (FPR) of 8.06% and a false negative rate (FNR) of 0.01% on the data, which shows high validity and accuracy; it is also comparable to the independent isolated forests (FNR = 4.76%), boxplot (FNR = 3.90%) and OneClassSVM (FNR = 4.77%), and the false negative rate is reduced by 4.75%, 3.89% and 4.76%, respectively.
Calibration of Small-Grain Seed Parameters Based on a BP Neural Network: A Case Study with Red Clover Seeds
Authors: Ma Xuejie , Guo Mengjun , Tong Xin , Hou Zhanfeng , Liu Haiyang , Ren Haiyan
Published: October 2023

In order to enhance the accuracy of discrete element numerical simulations in the processing of small-seed particles, it is essential to calibrate the parameters of seeds within the discrete element software. This study employs a series of physical tests to obtain the physical and contact parameters of red clover seeds. A discrete element model of red clover seeds is established. Plackett–Burman Design, steepest ascent, and Central Composite Design experiments are sequentially conducted. The simulation deviation of the resting angle of red clover seeds is employed as the evaluation criterion for parameter optimization. The results indicate that the coefficients of static friction between red clover seeds, the coefficients of rolling friction between red clover seeds, and the coefficients of static friction between red clover seeds and the steel plates significantly influence the resting angle. Modeling was performed using a backpropagation neural network, a genetic algorithm–optimized BP network, particle swarm optimization, and simulated annealing. It was found that GA-BP ensured both accuracy and stability. Compared to the traditional response surface methodology, GA-BP showed better fitting performance. For the optimized red clover seed simulation, the error between the angle of repose and the physical experiment was 0.98%. This research provides new insights into the calibration of small-grain seed parameters, demonstrating the value of GA-BP for precision modeling.
Root Causes of Flowering: Two Sides of Bolting in Sugar Beet
Authors: Kroupin Pavel Yu. , Kroupina Aleksandra Yu. , Karlov Gennady I. , Divashuk Mikhail G.
Published: October 2023

Sugar beet is an important root crop with a biennial life cycle. In the first year of its life cycle, it produces huge amounts of leaf and root mass used for the production of sugar and bioethanol, livestock feed, confectionery and pharmaceuticals, fertilizers, and soil restoration. Normally, after exposure to cold temperatures during winter storage, in the second year of its life cycle, it enters its reproductive phase. However, during the first year of growth, sugar beet plants may be susceptible to producing flowering shoots, or “bolting”, due to vernalization and long-day conditions. Bolting reduces both the yield and the sugar content of roots. Here, we review the published research works that study the environmental factors influencing bolting, the genetic (including epigenetic) and physiological mechanisms that regulate the transition to the reproductive phase, and the agrotechnical and breeding practices used to prevent bolting. Models of gene networks that regulate the transition to flowering are presented. Methods for selecting non-bolting plants using conventional, marker-assisted, and genomic breeding are demonstrated. Attention is also paid to the speed breeding technology that stimulates bolting and flowering sugar beet plants in an artificial climate. Growing sugar beet plants “from seed to seed” can potentially accelerate the breeding and seed production of sugar beet. This review compares different conditions for inducing bolting in sugar beet in climatic chambers and greenhouses. It examines parameters such as temperature, duration of light exposure, and light intensity during the pre-vernalization, post-vernalization, and vernalization periods. The present review may be useful for specialists in sugar beet cultivation, breeders working on developing cultivars and hybrids that are resistant to bolting, and molecular biologists studying the genetic and physiological mechanisms underlying the transition of plants into the flowering stage.
Chatbots Put to the Test in Math and Logic Problems: A Comparison and Assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard
Authors: Plevris Vagelis , Papazafeiropoulos George , Jiménez Rios Alejandro
Published: October 2023

In an age where artificial intelligence is reshaping the landscape of education and problem solving, our study unveils the secrets behind three digital wizards, ChatGPT-3.5, ChatGPT-4, and Google Bard, as they engage in a thrilling showdown of mathematical and logical prowess. We assess the ability of the chatbots to understand the given problem, employ appropriate algorithms or methods to solve it, and generate coherent responses with correct answers. We conducted our study using a set of 30 questions. These questions were carefully crafted to be clear, unambiguous, and fully described using plain text only. Each question has a unique and well-defined correct answer. The questions were divided into two sets of 15: Set A consists of “Original” problems that cannot be found online, while Set B includes “Published” problems that are readily available online, often with their solutions. Each question was presented to each chatbot three times in May 2023. We recorded and analyzed their responses, highlighting their strengths and weaknesses. Our findings indicate that chatbots can provide accurate solutions for straightforward arithmetic, algebraic expressions, and basic logic puzzles, although they may not be consistently accurate in every attempt. However, for more complex mathematical problems or advanced logic tasks, the chatbots’ answers, although they appear convincing, may not be reliable. Furthermore, consistency is a concern as chatbots often provide conflicting answers when presented with the same question multiple times. To evaluate and compare the performance of the three chatbots, we conducted a quantitative analysis by scoring their final answers based on correctness. Our results show that ChatGPT-4 performs better than ChatGPT-3.5 in both sets of questions. Bard ranks third in the original questions of Set A, trailing behind the other two chatbots. However, Bard achieves the best performance, taking first place in the published questions of Set B. This is likely due to Bard’s direct access to the internet, unlike the ChatGPT chatbots, which, due to their designs, do not have external communication capabilities.
Increased Milk Yield and Reduced Enteric Methane Concentration on a Commercial Dairy Farm Associated with Dietary Inclusion of Sugarcane Extract (Saccharum officinarum)
Authors: Ahmed Awais , Flavel Matthew , Mitchell Shane , Macnab Gregor , Dunuarachchige Manisha Dunuarachchi , Desai Aniruddha , Jois Markandeya
Published: October 2023

(1) Background: The purpose of this study was to assess the influence of a natural sugarcane extract (Polygain™) on milk production, milk composition and methane emissions on a commercial dairy farm. (2) Methods: A three-week baseline was established for lactating Holstein × Friesian animals. Following this baseline period, these animals were fed Polygain™ at 0.25% of their estimated dry matter intake for 3 weeks. Methane concentration in the feed bin was determined at each milking using the Gascard NG Infrared Sensor (Edinburgh Sensors LTD). (3) Results: During the intervention phase milk yield increased significantly from 26.43 kg to 28.54 kg per cow per day, whilst methane emissions and bulk tank somatic cell counts decreased significantly in the intervention phase. For methane concentration, an average of 246 ppm during the baseline periods reduced to an average of 161.09 ppm during the intervention phase. For the bulk tank somatic cell counts, the average was observed at 283,200 during the baseline and reduced to an average value of 151,100 during the intervention phase. (4) Conclusions: The natural sugarcane extract was shown to have the potential to mitigate enteric methane emissions while also increasing production and animal wellbeing outcomes in a commercial dairy setting.
Carbon Dioxide Fluxes and Influencing Factors in the Momoge Salt Marsh Ecosystem, Jilin Province, China
Authors: Ma Qiongfang , Zhang Chaofan , Chen Ling , Yao Mingyuan , Yang Fan , Yan Hong , Li Wei
Published: October 2023

This study observed the characteristics and influencing factors of the carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations in CO2 fluxes in the Momoge salt marshes were observed using the eddy covariance method and were compared with various environmental factors. An overall daily “U”-shaped distribution was observed, with uptake during the day (negative values) and release at night (positive values). Annually, the carbon fluxes in the study area roughly exhibited a “V” shape. The carbon fluxes during the non-growing season predominantly showed positive values, indicating the release of CO2 into the atmosphere. Photosynthetically active radiation was the primary influencing factor affecting the hourly and daytime variations in net ecosystem exchange (NEE) during the growing season, while temperature was the main factor influencing nighttime NEE dynamics. The air temperature, soil temperature, photosynthetically active radiation, precipitation, and water level all had significant impacts on the daily net CO2 exchange. At the monthly scale, larger values of soil temperature, air temperature, photosynthetically active radiation, and aboveground biomass corresponded to a stronger carbon absorption capacity of the ecosystem. Overall, temperature remains the primary factor for carbon fluxes in the Momoge wetlands.
The Dose-Dependent Role of Sage, Clove, and Pine Essential Oils in Modulating Ruminal Fermentation and Biohydrogenation of Polyunsaturated Fatty Acids: A Promising Strategy to Reduce Methane Emissions and Enhance the Nutritional Profile of Ruminant Products
Authors: Bokharaeian Mostafa , Ghoorchi Taghi , Toghdory Abdolhakim , Esfahani Iman Janghorban
Published: October 2023

The livestock industry significantly contributes to greenhouse gas emissions, with ruminant animals, including cows, sheep, and goats, being responsible for a substantial share of these emissions due to methane production. Reducing methane emissions from ruminants is crucial for mitigating the environmental impact of livestock production. Additionally, there has been a growing interest in improving the nutritional quality of ruminant products through modifying their profile of fatty acids. The current study aimed to investigate the potential of sage (SAG), pine (PIN), and clove (CLO) essential oils as natural additives for modulating in vitro ruminal fermentation characteristics and biohydrogenation of polyunsaturated fatty acids (PUFA). Within the current experiment, three dose levels (300, 600, and 900 mg/L) of essential oils were evaluated using rumen inoculum from three mature Dalagh ewes (58 ± 2.84 kg body weight). The results revealed that the essential oils had a significant impact on gas production, methane and carbon dioxide production, ruminal fermentation parameters, and ruminal biohydrogenation of dietary PUFAs. The essential oil treatments resulted in reduced gas production compared with the control group. Methane production was significantly reduced by all doses of the essential oils, with the highest dose of CLO resulting in the lowest methane production. In addition, the essential oils affected ruminal fermentation parameters, including pH, ammonia concentration, and production of total volatile fatty acids. Promising modifications in ruminal biohydrogenation of PUFAs and the profile of fatty acids were also observed in the current study. These findings suggest that SAG, Pin, and CLO hold promise in mitigating methane emissions and improve the nutritional value of ruminant products. Further investigation is required to evaluate their effectiveness in practical feeding strategies for livestock.
The Impact of Vegetation Roots on Shallow Stability of Expansive Soil Slope under Rainfall Conditions
Authors: Wang Yangming , Xu Weisheng , Wang Zhe , Zhu Yingna
Published: October 2023

The impact of reinforcing vegetation roots on the stability of expansive soil slopes with moisture absorption and expansion was investigated. Then, poinsettia is selected as the slope protection plant, and ABAQUS software (version 2022) with secondary development is used to simulate the moisture absorption and expansion of the expansive soil slope. After that, the strength reduction method is employed to study the effects on the displacement and plastic zone, and on the shallow layer of the expansive soil slope at different rainfall conditions. The following points are revealed: (1) The roots of the poinsettia can reduce the displacement of the slope. But, when the rainfall intensity exceeds the soil permeability coefficient, the soil reinforcement effect decreases. (2) The poinsettia root system can alleviate the concentration of plastic strain, disperse the plastic zone, and increase slope stability along the distribution of the roots. (3) The poinsettia roots can improve the shallow stability of the slope. But when the rainfall intensity exceeds the surface permeability coefficient, the magnitude of the reinforcement decreases. The results demonstrate that the poinsettia roots can enhance shallow slope stability. However, with increasing rainfall intensity, the ability of the poinsettia roots to enhance shallow slope stability gradually weakens.
Federated Learning for Computer-Aided Diagnosis of Glaucoma Using Retinal Fundus Images
Authors: Baptista Telmo , Soares Carlos , Oliveira Tiago , Soares Filipe
Published: October 2023

Deep learning approaches require a large amount of data to be transferred to centralized entities. However, this is often not a feasible option in healthcare, as it raises privacy concerns over sharing sensitive information. Federated Learning (FL) aims to address this issue by allowing machine learning without transferring the data to a centralized entity. FL has shown great potential to ensure privacy in digital healthcare while maintaining performance. Despite this, there is a lack of research on the impact of different types of data heterogeneity on the results. In this study, we research the robustness of various FL strategies on different data distributions and data quality for glaucoma diagnosis using retinal fundus images. We use RetinaQualEvaluator to generate quality labels for the datasets and then a data distributor to achieve our desired distributions. Finally, we evaluate the performance of the different strategies on local data and an independent test dataset. We observe that federated learning shows the potential to enable high-performance models without compromising sensitive data. Furthermore, we infer that FedProx is more suitable to scenarios where the distributions and quality of the data of the participating clients is diverse with less communication cost.
Reinforcement Learning as a Path to Autonomous Intelligent Cyber-Defense Agents in Vehicle Platforms
Authors: Raio Stephen , Corder Kevin , Parker Travis W. , Shearer Gregory G. , Edwards Joshua S. , Thogaripally Manik R. , Park Song J. , Nelson Frederica F.
Published: October 2023

Technological advancement of vehicle platforms exposes opportunities for new attack paths and vulnerabilities. Static cyber defenses can help mitigate certain attacks, but those attacks must generally be known ahead of time, and the cyber defenses must be hand-crafted by experts. This research explores reinforcement learning (RL) as a path to achieve autonomous, intelligent cyber defense of vehicle control networks—namely, the controller area network (CAN) bus. We train an RL agent for the CAN bus using Toyota’s Portable Automotive Security Testbed with Adaptability (PASTA). We then apply the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory’s methodology for quantitative measurement of cyber resilience to assess the agent’s effect on the vehicle testbed in a contested cyberspace environment. Despite all defenses having similar traditional performance measures, our RL agent averaged a 90% cyber resilience measurement during drive cycles executed on hardware versus 41% for a naïve static timing defense and 98% for the bespoke timing-based defense. Our results also show that an RL-based agent can detect and block injection attacks on a vehicle CAN bus in a laboratory environment with greater cyber resilience than prior learning approaches (1% for convolutional networks and 0% for recurrent networks). With further research, we believe there is potential for using RL in the autonomous intelligent cyber defense agent concept.
Nonlinear Static Analysis for Seismic Evaluation of Existing RC Hospital Building
Authors: Kuria Kevin Karanja , Kegyes-Brassai Orsolya Katalin
Published: October 2023

Nonlinear Static Analysis otherwise known as pushover analysis will be used in this study to evaluate the seismic performance of an existing reinforced concrete (RC) hospital structure. This method aids in determining the structure’s ability to withstand lateral loads and calculating its local and global deformation requirements. The study begins with a thorough analysis of the geometry, materials, and structural elements of the structure, followed by a review of pertinent building regulations and codes. A finite element model in three dimensions of the hospital building is created, encapsulating the main features of the structure’s behavior under seismic loading. The lateral force method of analysis and static pushover analysis is then carried out and compared, and the findings are used to pinpoint crucial weak places, potential failure mechanisms, and regions needing additional research or fortification. Recommendations are given to improve the seismic performance of the current RC hospital building based on the pushover analysis’s findings. These adjustments can be made to the structural system via retrofitting techniques or to non-structural elements. For engineers, architects, and legislators concerned with the seismic assessment and renovation of hospital buildings and other crucial infrastructure, the findings from this study are valuable.
A Review of Sodium-Metal Chloride Batteries: Materials and Cell Design
Authors: Leonardi Salvatore Gianluca , Samperi Mario , Frusteri Leone , Antonucci Vincenzo , D’Urso Claudia
Published: October 2023

The widespread electrification of various sectors is triggering a strong demand for new energy storage systems with low environmental impact and using abundant raw materials. Batteries employing elemental sodium could offer significant advantages, as the use of a naturally abundant element such as sodium is strategic to satisfy the increasing demand. Currently, lithium-ion batteries represent the most popular energy storage technology, owing to their tunable performance for various applications. However, where large energy storage systems are required, the use of expensive lithium-ion batteries could result disadvantageous. On the other hand, high-temperature sodium batteries represent a promising technology due to their theoretical high specific energies, high energy efficiency, long life and safety. Therefore, driven by the current market demand and the awareness of the potential that still needs to be exploited, research interest in high-temperature sodium batteries has regained great attention. This review aims to highlight the most recent developments on this topic, focusing on actual and prospective active materials used in sodium-metal chloride batteries. In particular, alternative formulations to conventional nickel cathodes and advanced ceramic electrolytes are discussed, referring to the current research challenges centered on cost reduction, lowering of the operating temperature and performance improvement. Moreover, a comprehensive overview on commercial tubular cell design and prototypal planar design is presented, highlighting advantages and limitations based on the analysis of research papers, patents and technical documents.
Usefulness and Clinical Impact of Whole-Body MRI in Detecting Autoimmune Neuromuscular Disorders
Authors: Pace Mario , Cannella Roberto , Di Stefano Vincenzo , Lupica Antonino , Alonge Paolo , Morici Giulio , Brighina Filippo , Brancato Federica , Midiri Federico , Galia Massimo
Published: October 2023

Autoimmune neuromuscular diseases are a group of heterogenous pathologies secondary to the activation of the immune system that damage the structures of the peripheric nerve, the neuromuscular junction, or the skeleton muscle. The diagnosis of autoimmune neuromuscular disorders comprises a combination of data from clinical, laboratory, electromyography, imaging exam, and biopsy. Particularly, the whole-body MRI examination in the last two decades has been of great use in the assessment of neuromuscular disorders. MRI provides information about the structures involved and the status of activity of the disease. It can also be used as a biomarker, detect the pattern of specific muscle involvement, and is a useful tool for targeting the optimal muscle site for biopsy. In this work, we summarized the most used technical protocol of whole-body MRI and the role of this imaging technique in autoimmune neuromuscular disorders.
An Integrated Workflow for Designing and Fabricating Multi-Functional Building Components through Additive Manufacturing with Clay
Authors: Taher Ammar , Aşut Serdar , van der Spoel Willem
Published: October 2023

This article presents a project that explores the potential of Additive Manufacturing (AM) for designing and fabricating multi-functional building components for improved climate performance. In this project, an innovative façade wall design was developed by using a computational method in an attempt to integrate a displacement ventilation system into the wall. A robotic AM solution is integrated into the workflow as a potentially feasible fabrication method for the resulting wall design with an intricate geometry. Clay is proposed as the AM material, being a potential low-carbon building material. To this end, a material exploration of clay was conducted to develop an appropriate composite for AM. A displacement ventilation system was developed to achieve better indoor air quality by using a Computational Fluid Dynamics (CFD) model. Subsequently, an AM solution was integrated into the workflow to automate the fabrication phase. Finally, a partial prototype of the design was made through AM with clay to demonstrate the feasibility and observe the material qualities of the final product. The proposed workflow proves applicable, highlighting directions for future research.
Alternative Approaches to HVAC Control of Chat Generative Pre-Trained Transformer (ChatGPT) for Autonomous Building System Operations
Authors: Ahn Ki Uhn , Kim Deuk-Woo , Cho Hyun Mi , Chae Chang-U
Published: October 2023

Artificial intelligence (AI) technology has rapidly advanced and transformed the nature of scientific inquiry. The recent release of the large language model Chat Generative Pre-Trained Transformer (ChatGPT) has attracted significant attention from the public and various industries. This study applied ChatGPT to autonomous building system operations, specifically coupling it with an EnergyPlus reference office building simulation model. The operational objective was to minimize the energy use of the building systems, including four air-handling units, two chillers, a cooling tower, and two pumps, while ensuring that indoor CO2 concentrations remain below 1000 ppm. The performance of ChatGPT in an autonomous operation was compared with control results based on a deep Q-network (DQN), which is a reinforcement learning method. The ChatGPT and DQN lowered the total energy use by 16.8% and 24.1%, respectively, compared with the baseline operation, while maintaining an indoor CO2 concentration below 1000 ppm. Notably, compared with the DQN, ChatGPT-based control does not require a learning process to develop intelligence for building control. In real-world applications, the high generalization capabilities of the ChatGPT-based control, resulting from its extensive training on vast and diverse data, could potentially make it more effective.
Endotoxin Tolerance Creates Favourable Conditions for Cancer Development
Authors: Roy Konkonika , Kozłowski Henryk Mikołaj , Jędrzejewski Tomasz , Sobocińska Justyna , Maciejewski Bartosz , Dzialuk Artur , Wrotek Sylwia
Published: October 2023

Endotoxin tolerance (ET) is an adaptive phenomenon of the immune system that protects the host from clinical complications due to repeated exposure of the body to endotoxins such as lipopolysaccharide (LPS). Since ET is an immunosuppressive mechanism in which a significant reprogramming of macrophages is observed, we hypothesized that it could influence cancer development by modifying the tumour environment. This study aimed to explore whether ET influences cancer progression by altering the tumour microenvironment. Endotoxin-tolerant macrophages (MoET) were examined for their impact on breast and colon cancer cells via direct interaction and conditioned media exposure. We characterized cancer cell behaviour by viability, clonogenic potential, motility, scratch assays, and 3D spheroidal assays. MoET-derived factors increased cancer cell viability, motility, and clonogenicity, suggesting a conducive environment for cancer development. Remarkably, despite reduced TNFα and IL-6 levels, MoET exhibited M1 polarization. These findings uncover an ET-associated macrophage reprogramming that fosters a favourable context for cancer progression across diverse tumours. Targeting ET could emerge as a promising avenue for cancer therapy and prevention.
Review of RM-1929 Near-Infrared Photoimmunotherapy Clinical Efficacy for Unresectable and/or Recurrent Head and Neck Squamous Cell Carcinoma
Authors: Miyazaki Nanami L. , Furusawa Aki , Choyke Peter L. , Kobayashi Hisataka
Published: October 2023

Head and neck squamous cell carcinoma (HNSCC) contribute to a significant global cancer burden. Developments in current therapeutic approaches have improved patient outcomes but have limited efficacy in patients with unresectable and/or recurrent HNSCC. RM-1929 near-infrared photoimmunotherapy (NIR-PIT) is an emerging treatment that is currently being investigated in a Phase III clinical trial and has been conditionally approved for the treatment of unresectable and/or recurrent HNSCC in Japan. Here, we collect a series of case reports and clinical trial data to assess the efficacy of RM-1929 NIR-PIT. Disease control rates ranged from 66.7 to 100% across these studies, and overall response rates ranged from 43.3 to 100%, suggesting positive clinical outcomes. Low-grade postoperative localized pain and edema were the most frequently reported side effects, and preliminary reports on quality of life and pain levels suggest that RM-1929 NIR-PIT does not significantly decrease quality of life and is manageable with existing pain management strategies, including opioids. These preliminary data in real-world use of RM-1929 NIR-PIT show that it is a well-tolerated therapy that has clinically meaningful outcomes for patients with unresectable and/or recurrent HNSCC.
Optimal Management for Stage IVB Endometrial Cancer: A Systematic Review
Authors: Capozzi Vito Andrea , Scarpelli Elisa , De Finis Alessandra , Rotondella Isabella , Scebba Davide , Gallinelli Asya , Montrucchio Carlotta , Martignon Giulia , Leotta Martina , Ghi Tullio , Berretta Roberto
Published: October 2023

(1) Background: Endometrial cancer (EC) is a common gynecological malignancy, often diagnosed at an early stage with a high overall survival rate. Surgical treatment is the primary approach, guided by pathological and molecular characteristics. Stage IVB EC, characterized by intra and/or extra-abdominal metastasis, presents a significant challenge with no clear consensus on optimal management. (2) Methods: A systematic literature review was conducted from January to May 2023, covering studies from 2000 to 2023. Eligible studies included retrospective case series, prospective trials, and randomized clinical trials. (3) Results: Of 116 studies identified, 21 were deemed relevant: 7 on primary surgery, 10 on neoadjuvant chemotherapy (NACT), and 4 on adjuvant treatment. Notably, the impact of residual tumor after primary surgery was a critical factor affecting survival. The use of NACT followed by interval debulking surgery showed promise, particularly in cases deemed unresectable. Adjuvant treatment, combining radiotherapy and chemotherapy, demonstrated improved survival but lacked consensus regarding its role. (4) Conclusions: Stage IVB EC poses a complex challenge with limited evidence to guide management. Optimal cytoreduction remains crucial, and NACT should be considered for unresectable cases. Multimodality adjuvant therapy may benefit patients, even with disease spread beyond the pelvis. Future advances in molecular classification and targeted therapies are expected to enhance treatment strategies.
Generation of Fibrotic Liver Organoids Using Hepatocytes, Primary Liver Sinusoidal Endothelial Cells, Hepatic Stellate Cells, and Macrophages
Authors: Yoon Yongdae , Gong Seong Chan , Kim Moon Young , Baik Soon Koo , Hong Ju-Eun , Rhee Ki-Jong , Ryu Hoon , Eom Young Woo
Published: October 2023

Liver organoids generated with single or multiple cell types have been used to investigate liver fibrosis development, toxicity, pathogenesis, and drug screening. However, organoid generation is limited by the availability of cells isolated from primary tissues or differentiated from various stem cells. To ensure cell availability for organoid formation, we investigated whether liver organoids could be generated with cell-line-based Huh-7 hepatocellular carcinoma cells, macrophages differentiated from THP-1 monocytes, and LX-2 hepatic stellate cells (HSCs) and primary liver sinusoidal endothelial cells (LSECs). In liver organoids, hepatocyte-, LSEC-, macrophage-, and HSC-related gene expression increased relative to that in two-dimensional (2D)-cultured Huh-7/LSEC/THP-1/LX-2 cells without Matrigel. Thioacetamide (TAA) increased α-smooth muscle actin expression in liver organoids but not in 2D-cultured cells, whereas in TAA-treated organoids, the expression of hepatic and LSEC markers decreased and that of macrophage and HSC markers increased. TAA-induced fibrosis was suppressed by treatment with N-acetyl-L-cysteine or tumor-necrosis-factor-stimulated gene 6 protein. The results showed that liver toxicants could induce fibrotic and inflammatory responses in liver organoids comprising Huh-7/LSEC/macrophages/LX-2 cells, resulting in fibrotic liver organoids. We propose that cell-line-based organoids can be used for disease modeling and drug screening to improve liver fibrosis treatment.
Ranking of Variation Orders Caused by the Owners of Construction Projects in Saudi Arabia Using Statistical and Fuzzy-Based Methods
Authors: Alsohiman Nawaf K. , Alattyih Wael , Haider Husnain
Published: October 2023

One common theme in the international construction sector is project variation, which influences project outcomes. This study argued that variation could occur during the lifecycle of a construction project that might affect the contracted project success criteria (PSC), including cost, time, quality, or scope parameters. These variations can originate from the owner, consultant, contractor, or external factors. The construction industry is a critical partner in operationalizing and implementing the long-term sustainability objectives of Vision 2030 in the Kingdom of Saudi Arabia (KSA). The present study identified 18 factors that can cause variation orders by the owners of construction projects and evaluated them using statistical and fuzzy-based methods. To estimate the influence of variation orders on PSC in Saudi Arabia, over 70 experienced professionals, including project managers (58%), engineers (26%), and strategic management officers (16%) working in the construction industry evaluated the identified factors through a questionnaire survey. A 1–4 Likert scale, no impact (1) to high impact (4) on PSC, was used to rank identified factors. Analysis of variance and Tukey tests found no statistically significant difference between the respondents’ opinions. Out of the four PSC, cost and time with 14 out of 18 factors obtaining scores higher than “3” superseded quality with seven and scope with six factors. The Fuzzy Synthetic Evaluation identified inadequate planning, managerial corruption, the method of lowest bidding procurement, the inadequate experience of owner’s staff, additional work added by the owners, delayed starts, mode of financing and payments, and public works contract rigidity as the most critical factors affecting PSC of the construction projects in the view of participated stakeholders. Conversely, shortening the project period, long intervals between design and project initiation, and restrictions against foreign companies were identified as the least important factors. The study helps stakeholders achieve long-term sustainability by focusing on the top-ranked factors in KSA’s construction industry and the Gulf Region with similar working environments, rules, and regulations.
Comparison of Fe30Co20Cr20Ni20Mo3.5 High Entropy Alloy Coatings Prepared Using Plasma Cladding, High-Speed Laser Cladding, and Deep Laser Cladding
Authors: Li Mengzhao , Li Chao , Li Bingyuan , Zhou Yicheng , Huang Long , Cai Ang , Cui Chang , Gao Senao , Zhang Guodong , Yang Bing
Published: October 2023

Three kinds of Fe30Ni20Co20Cr20Mo3.5 high entropy alloy (HEA) coatings were prepared on the surface of a Q235 steel plate using plasma cladding and laser cladding. The microstructure, crystal structure, element distribution, microhardness, wear resistance, and corrosion resistance of the coatings were studied. The grain size of the high-speed laser cladding coating (HLC) was the smallest. The crystal structures of the plasma cladding coating (PC) and HLC were single face-centered cubic (FCC), while that of the deep laser cladding coating (DLC) was body-centered cubic (BCC). DLC had the best microhardness and wear resistance. The microhardness of PC, HLC, and DLC increased by 70%, 108%, and 109%, respectively, and the average friction coefficient decreased by 33%, 44%, and 51%, respectively, compared to Q235. HLC had the best corrosion resistance, with an annual corrosion rate of 0.66925 mm/a. The annual corrosion rate of PC and HLC was only 40% of Q235. The polarization curves of PC and HLC had obvious passivation regions with a width of up to 2 V. The corrosion types of PC were pitting corrosion and intergranular corrosion, that of HLC was general corrosion, and that of DLC was severe pitting corrosion.
Electrofrictional Hardening of the 40Kh and 65G Steels
Authors: Sagdoldina Zhuldyz , Tyurin Yuri , Berdimuratov Nurbol , Stepanova Olga , Magazov Nurtoleu , Baizhan Daryn
Published: October 2023

This study investigated the influence of electrofrictional treatment on the structure and hardness of the surface layers of the 40Kh and 65G steels. Based on the results of scanning electron microscopy, it was determined that during the electrofrictional hardening (EFH) of 40Kh steel, a hardened surface layer, with a microhardness of 873 ± 37 HV0.1, was formed. This layer consisted of two zones: a surface-quenched zone, with a structure of fine needle-like martensite and austenite; and a heat-affected zone (transition layer), with a structure of martensite and high-dispersion pearlite (troostite), smoothly transitioning into the original ferrite–pearlite structure. After EFH, a layer with a thickness of ~150 μm containing carbides in the martensite was formed on the surface of the 65G steel, which smoothly transitions into the heat-affected zone with a structure of needle-like martensite. The microhardness of the 65G steel in its initial state was 277 ± 20 HV0.1, and after EFH, it reached 811 ± 23 HV0.1. The results of the microstructure analysis of the 40Kh and 65G steels after EFH were consistent with the results of X-ray phase analysis. It was established that the phase composition of the 40Kh and 65G steels in their initial states consisted of an α-Fe phase with a body-centered cubic (BCC) lattice, and after EFH, both steels formed strengthening phases: residual austenite (γ-Fe) and martensite (α′-Fe). During EFH, under high temperature and pressure conditions, carbon from the cast iron electrode was alloyed with iron, contributing to the formation of cementite on the surface of the 65G steel. These obtained data allowed us to conclude that electrofrictional treatment is an effective method for the surface hardening of 40Kh and 65G steels.
The Denticle Multiverse: Morphological Diversity of Placoid Scales across Ontogeny in the Portuguese Dogfish, Centroscymnus coelolepis, and Its Systematic Implications
Authors: Vaz Diego F. B. , Avery Tess M. , Gabler-Smith Molly K. , Lauder George V.
Published: October 2023

Centroscymnus coelolepis is a deep-water sleeper shark and, like most sharks, it is covered in placoid scales, or dermal denticles. The morphological diversity of the dermal denticles in this species, however, has not been described in detail, and ontogenetic changes in denticle morphology are poorly understood in sharks. Combining scanning-electron microscopy and micro-CT imaging, we demonstrate the presence of eleven dermal-denticle morphotypes across the ontogeny and different regions of the body of Centroscymnus coelolepis. The snout, interspiracular, and trunk/tail regions have similar changes in denticle morphotype during development. For example, on the trunks and tails of juveniles (~350 mm TL), denticle crowns have two to three longitudinal ridges and three posterior cusps that are gradually replaced by ridgeless and cuspless crowns in adults (>800 mm TL). Sixteen measurements were obtained from the 3D models generated. A principal component analysis demonstrated that the eleven distinct dermal-denticle morphotypes observed were located in different regions of the morphospace. The denticle volume and surface area showed negative allometry with respect to body length throughout the ontogeny. The results reflect the considerable diversity within the denticle multiverse (ontogenetic and intraspecific variations), and much of this diversity remains to be explored to fully understand the role of dermal denticles in shark taxonomy, ecology, and biomechanics.
Evaluation of an Isothermal Amplification HPV Assay on Self-Collected Vaginal Samples as Compared to Clinician-Collected Cervical Samples
Authors: Chan Aaron H. Y. , Ngu Siew-Fei , Lau Lesley S. K. , Tsun Obe K. L. , Ngan Hextan Y. S. , Cheung Annie N. Y. , Chan Karen K. L.
Published: October 2023

This study aimed to evaluate the concordance of HPV results between the SentisTM HPV assay (Sentis) (BGI Group, Shenzhen, China), an isothermal amplification-based HPV assay, on self-collected and clinician-collected samples and the agreement of Sentis on self-collected samples with the BD OnclarityTM HPV assay (Onclarity) (Becton, Dickinson, and Company, Franklin Lakes, New Jersey, USA), a PCR-based HPV assay, on clinician-collected samples. This was a prospective study of 104 women attending the colposcopy clinic for abnormal smears. After informed consent, participants self-collected vaginal samples before having clinician-collected cervical samples. Self-collected samples underwent HPV testing with Sentis (Self-Sentis HPV) and clinician-collected samples were tested with Sentis (Clinician-Sentis HPV) and Onclarity (Clinician-Onclarity), which was used as a reference standard. The concordance was assessed using Cohen’s kappa. The prevalence of HPV and the acceptability of self-sampling were also evaluated. The concordance rate between Self-Sentis HPV and Clinician-Sentis HPV was 89.8% with a kappa of 0.769. The concordance rate between Self-Sentis HPV and Clinician-Onclarity was 84.4% with a kappa of 0.643. The prevalence of HPV was 26.0% on Clinician-Onclarity, 29.3% on Clinician-Sentis HPV, and 35.6% on Self-Sentis HPV. Overall, 65% of participants would undergo self-sampling again. This was attributed to mainly not feeling embarrassed (68%) and being convenient (58%). Our study showed a substantial agreement between Self-Sentis HPV with Clinician-Sentis HPV and Clinician-Onclarity. Self-sampling was also shown to be a generally well-accepted method of screening.
Development of a Taxon-Specific Real-Time Polymerase Chain Reaction Method to Detect Trichoderma reesei Contaminations in Fermentation Products
Authors: Fraiture Marie-Alice , Gobbo Andrea , Papazova Nina , Roosens Nancy H. C.
Published: October 2023

Recently, a genetically modified microorganism (GMM) detection strategy using real-time PCR technology was developed to control fermentation products commercialized in the food and feed chain, allowing several unexpected GMM contaminations to be highlighted. Currently, only bacterial strains are targeted by this strategy. Given that fungal strains, like Trichoderma reesei, are also frequently used by the food industry to produce fermentation products, a novel real-time PCR method specific to this fungal species was developed and validated in this study to reinforce the GMM detection strategy. Designed to cover a sequence of 130 bp from the translation elongation factor alpha 1 (Tef1) gene of T. reesei, this real-time PCR method, namely TR, allows for the screening of commercial fermentation products contaminated with T. reesei, genetically modified or not, which is one of the major fungal species used as an industrial platform for the manufacturing of fermentation products. The developed real-time PCR TR method was assessed as specific and sensitive (LOD95% = eight copies). In addition, the developed real-time PCR TR method performance was confirmed to be in line with the “Minimum Performance Requirements for Analytical Methods of GMO Testing” of the European Network of GMO Laboratories. The validated real-time PCR TR method was also demonstrated to be applicable to commercial microbial fermentation products. Based on all these results, the novel real-time PCR TR method was assessed as valuable for strengthening the current GMM detection strategy regarding major fungal species used by the food industry to produce microbial fermentation products.