bluuebunny/crossref_metadata_2025 huggingface dataset:
Precision Leak Detection in Supermarket Refrigeration Systems Integrating Categorical Gradient Boosting with Advanced Thresholding
Authors: Wijethunga Rashinda , Nouraei Hooman , Zych Craig , Samarabandu Jagath , Sadhu Ayan
Published: February 2024

Supermarket refrigeration systems are integral to food security and the global economy. Their massive scale, characterized by numerous evaporators, remote condensers, miles of intricate piping, and high working pressure, frequently leads to problematic leaks. Such leaks can have severe consequences, impacting not only the profits of the supermarkets, but also the environment. With the advent of Industry 4.0 and machine learning techniques, data-driven automatic fault detection and diagnosis methods are becoming increasingly popular in managing supermarket refrigeration systems. This paper presents a novel leak-detection framework, explicitly designed for supermarket refrigeration systems. This framework is capable of identifying both slow and catastrophic leaks, each exhibiting unique behaviours. A noteworthy feature of the proposed solution is its independence from the refrigerant level in the receiver, which is a common dependency in many existing solutions for leak detection. Instead, it focuses on parameters that are universally present in supermarket refrigeration systems. The approach utilizes the categorical gradient boosting regression model and a thresholding algorithm, focusing on features that are sensitive to leaks as target features. These include the coefficient of performance, subcooling temperature, superheat temperature, mass flow rate, compression ratio, and energy consumption. In the case of slow leaks, only the coefficient of performance shows a response. However, for catastrophic leaks, all parameters except energy consumption demonstrate responses. This method detects slow leaks with an average F1 score of 0.92 within five days of occurrence. The catastrophic leak detection yields F1 scores of 0.7200 for the coefficient of performance, 1.0000 for the subcooling temperature, 0.4118 for the superheat temperature, 0.6957 for the mass flow rate, and 0.8824 for the compression ratio, respectively.
Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control
Authors: Wang Yang , Chakraborty Sajib , Geury Thomas , Hegazy Omar
Published: February 2024

Modular multilevel converters (MMCs) with integrated battery energy storage systems (BESSs) are becoming crucial for modern power grids. This paper investigates the modeling and control of a grid-connected MMC-BESS, with a specific emphasis on state-of-charge (SoC) balancing. Compared to conventional hard arm SoC balancing control (HASBC), this paper proposes an alternative soft arm SoC balancing control (SASBC). The simulation results and analysis indicate the following: 1. SASBC provides superior performance in achieving SoC balance both between and within the arms, as compared to HASBC. 2. The MMC-BESS power fluctuates between phases, arms, and individual submodules to balance the SoC of batteries. After the accomplishment of SoC equalization, the power is equally distributed, and the circulating current is well eliminated. 3. MMC-BESS can operate in both the charging and discharging modes, and the total harmonic distortion (THD) of the output current is reduced from 6.80% to 1.13% after SoC balancing is achieved. 4. A robustness test shows the control system’s effective performance in handling component variations.
Are Design Strategies for High-Performance Buildings Really Effective? Results from One Year of Monitoring of Indoor Microclimate and Envelope Performance of a Newly Built nZEB House in Central Italy
Authors: Carletti Cristina , Piselli Cristina , Sciurpi Fabio
Published: February 2024

As buildings are one of the major contributors to greenhouse gas emissions and energy consumption, they have a key potential for energy efficiency and indoor environmental quality improvement. Therefore, the development of nearly Zero-Energy Buildings (nZEBs) is strategic to respond to these challenges and to design and retrofit sustainable highly performing buildings. Actually, the nZEB target can also be reached with highly insulated wooden technologies. However, they must be critically revised and adapted when taking into account the warm climate peculiarities. The paper contributes to this attempt by dealing with the implementation of a methodology specifically focused on the long-term assessment of the real building envelope performance. The methodology is applied to a recently built wooden nZEB detached single-story dwelling constructed in 2017 in central Italy. One year monitoring data were collected about the envelope in-field dynamic performance and the indoor microclimate and well-being conditions. The theoretical design-stage data and the monitored data were compared. The positive aspects as well as the critical issues of nZEB target in the Mediterranean climate context and the performance gap were underlined. Accordingly, the main aspects to be considered in the design of nZEBs envelope were highlighted.
Gas Temperature Distribution in the Combustion Chamber of a GTM400 MOD Turbojet Engine Powered by JET A-1 Fuel and Hydrogen
Authors: Brodzik Łukasz
Published: February 2024

Research on engine operation using hydrogen may enable appropriate optimization of thrust, and therefore performance, related to its potential use in aircraft. It is particularly important as the share of hydrogen in combustion affects the reduction of combustion products such as carbon dioxide, carbon monoxide, nitrogen oxide, hydrocarbons, and solid matter. This is in line with the new requirements regarding the increased supply of sustainable aviation fuels (SAFs) and the related changes in emissions, i.e., reducing the harmful impact of exhaust gases on the environment. This paper presents the results of measurements carried out in the GTM400 MOD turbojet engine. Based on the research performed, the impact of hydrogen and aviation kerosene combustion on selected engine parameters is presented. The paper shows changes in the rotational speed and volume flow of JET A-1 fuel as a function of engine operation time. Changes in temperature measured at the edge of the flame tube were also examined. The tests confirmed that the combustion chamber worked correctly in the selected area in the range of the tested fuel mixtures. After incorporating hydrogen into the combustion process, the consumption of traditional JET A-1 fuel was significantly reduced.
Effect of Ancient Salinity on the Distribution and Composition of Tricyclic Terpane in Hydrocarbon Source Rocks in the Mahu Depression
Authors: Chen Haojie , Zhang Min , He Taohua
Published: February 2024

Ma2 and Ma3 hydrocarbon source rock samples from the Fengcheng Formation in well Maye 1, Mahu Depression, Junggar Basin, were studied using conventional geochemical analysis methods and saturated hydrocarbon gas chromatography–mass spectrometry. The distribution patterns, abundance, relative content, and ratios of different carbon compounds of tricyclic terpane in hydrocarbon source rocks from fresh-to-mildly-saline (type I), moderately saline (type II), and saline (type III) water environments significantly differed. The C28–C29TT/C30H and C19–C29TT/C30H ratios were the lowest in the type I hydrocarbon source rock. The relative ratios of C23TT/C21TT, C25TT/C24TT, C28TT/C26TT, (C23–C26TT)/(C19–C22TT), and (C28–C29TT)/(C19–C22TT) gradually increased with the increase in the salinity of the hydrocarbon source rock. The percentage of low-carbon tricyclic terpanes gradually decreased to 28%, whereas those of the medium- and high-carbon tricyclic terpanes increased to 52% and 20%, respectively. The differences in triterpane types of different hydrocarbon source rocks were mainly controlled by the depositional environment. The primary factor that controlled the distribution pattern; relative abundance, especially the high carbon tricyclic terpane content; and differences in the relative ratio of different carbon compounds in different hydrocarbon source rocks was the salinity of the ancient waterbody during deposition.
Energetic Performance of Natural Building Materials: Numerical Simulation and Experimental Evaluation
Authors: Mastino Costantino , Concu Giovanna , Frattolillo Andrea
Published: February 2024

The current goal of the European Commission, which aims to reduce CO2 by 90% compared to values estimated in 1980, and the ever-increasing sensitivity to environmental sustainability, fully involve the construction sector, which, according to the OECD (Organization for Economic Co-Operation and Development) is responsible for over one-third of the world’s energy requirement. In this frame, numerous researchers and companies are focusing on ecologically sustainable building materials, to be used in new and existing buildings, that are able to simultaneously fulfill the constructive function and improve the energy behavior of the building envelope. The goal of the present paper is the analysis of the energy performance of some innovative locally produced natural building materials (timber, sheep wool, rammed earth, lime-based plaster, natural fibers) used in multilayer vertical closures, compared to that of more common building materials (bricks, concrete, synthetic insulation). First, the physical-mechanical characterization of the local natural materials was carried out, then the model of a building was implemented, whose energetic performance was simulated by varying the type of stratigraphy of the walls, including the use of both innovative and common materials. The building chosen for the simulation consists of one of the BESTEST ANSI/ASHRAE reported in the 140-2017 standard using the climatic data of the Mediterranean area. The results of the simulation have been presented and discussed.
Temperature Reduction as Operando Performance Recovery Procedure for Polymer Electrolyte Membrane Fuel Cells
Authors: Zhang Qian , Schulze Mathias , Gazdzicki Pawel , Friedrich Kaspar Andreas
Published: February 2024

To efficiently mitigate the reversible performance degradation of polymer electrolyte membrane fuel cells, it is crucial to thoroughly understand recovery effects. In this work, the effect of operando performance recovery by temperature reduction is evaluated. The results reveal that operando reduction in cell temperature from 80 °C to 45 °C yields a performance recovery of 60–70% in the current density range below 1 A cm−2 in a shorter time (1.5 h versus 10.5 h), as opposed to a known and more complex non-operando recovery procedure. Notably, the absolute recovered voltage is directly proportional to the total amount of liquid water produced during the temperature reduction. Thus, the recovery effect is likely attributed to a reorganization/rearrangement of the ionomer due to water condensation. Reduction in the charge transfer and mass transfer resistance is observed after the temperature reduction by electrochemical impedance spectroscopy (EIS) measurement. During non-operando temperature reduction (i.e., open circuit voltage (OCV) hold during recovery instead of load cycling) an even higher recovery efficiency of >80% was achieved.
Dynamic Knowledge Management in an Agent-Based Extended Green Cloud Simulator
Authors: Wrona Zofia , Ganzha Maria , Paprzycki Marcin , Krzyżanowski Stanisław
Published: February 2024

Cloud infrastructures operate in highly dynamic environments, and today, energy-focused optimization become crucial. Moreover, the concept of extended cloud infrastructure, which, among others, uses green energy, started to gain traction. This introduces a new level of dynamicity to the ecosystem, as “processing components” may “disappear” and “come back”, specifically in scenarios where the lack/return of green energy leads to shutting down/booting back servers at a given location. Considered use cases may involve introducing new types of resources (e.g., adding containers with server racks with “next-generation processors”). All such situations require the dynamic adaptation of “system knowledge”, i.e., runtime system adaptation. In this context, an agent-based digital twin of the extended green cloud infrastructure is proposed. Here, knowledge management is facilitated with an explainable Rule-Based Expert System, combined with Expression Languages. The tests were run using Extended Green Cloud Simulator, which allows the modelling of cloud infrastructures powered (partially) by renewable energy sources. Specifically, the work describes scenarios in which: (1) a new hardware resource is introduced in the system; (2) the system component changes its resource; and (3) system user changes energy-related preferences. The case study demonstrates how rules can facilitate control of energy efficiency with an example of an adaptable compromise between pricing and energy consumption.
A Novel Data-Driven Approach for Predicting the Performance Degradation of a Gas Turbine
Authors: Dai Shun , Zhang Xiaoyi , Luo Mingyu
Published: February 2024

Gas turbines operate under harsh conditions of high temperature and pressure for extended periods, inevitably experiencing performance degradation. Predicting the performance degradation trend of gas turbines and optimizing planned maintenance cycles are crucial for the economic and safety aspects of gas turbine operation. In this study, a novel data-driven approach for predicting gas turbine performance degradation is proposed. Initially, gas turbine operating data are augmented using a mechanism model. Subsequently, a data-driven performance model is constructed based on support vector regression (SVR) and gas turbine operational characteristics, enabling real-time calculation of performance degradation indicators. Building on this, an Autoregressive Neural Network (AR-Net) is employed to construct a model for predicting the trend of performance degradation. The proposed method is applied to predict performance degradation caused by fouling in the compressor of a gas turbine. Comparative analysis with three other performance degradation prediction methods indicates that the proposed approach accurately identifies the performance degradation trend of gas turbines, determining the optimal maintenance timing. This holds significant importance for the condition-based maintenance of gas turbines.
Assessing the Wind Power Potential in Naama, Algeria to Complement Solar Energy through Integrated Modeling of the Wind Resource and Turbine Wind Performance
Authors: Sekkal Mohammed Chakib , Ziani Zakarya , Mahdad Moustafa Yassine , Meliani Sidi Mohammed , Baghli Mohammed Haris , Bessenouci Mohammed Zakaria
Published: February 2024

In the context of the escalating global climate crisis and the urgent need for sustainable energy solutions, this study explores the integration of wind energy as a supplementary source to solar photovoltaic energy in Naama, Algeria. The research utilizes a decade-long anemometric dataset, along with concurrent solar radiation data, to investigate the potential of harnessing wind energy, particularly during periods of low solar irradiance. Employing advanced statistical methods, including the Weibull distribution, the study assesses the wind power generation potential of a 2 kW/day turbine. The research highlights an average evening increase in wind speeds, which inversely correlates with the diminished solar energy production after sunset. This seasonal pattern is further substantiated by a significant negative correlation between wind speed and solar radiation for most of the year (January to May and September to December), with Pearson coefficients ranging from −0.713 to −0.524 (p < 0.05). However, the study also notes an absence of a notable correlation during the summer months (June to August) attributed to seasonal wind variations and the peak of solar irradiance. These findings confirm Naama as an ideal location for integrated renewable energy systems, thereby demonstrating the natural synergy between solar and wind energy. This synergy is particularly effective in mitigating the intermittency of solar power, thus highlighting the potential of wind energy during periods of low solar activity.
Rapid Design Method of Heavy-Loaded Propeller for Distributed Electric Propulsion Aircraft
Authors: Shi Shijie , Huo Jiabo , Liu Zhongbao , Zou Aicheng
Published: February 2024

On Distributed Electric Propulsion (DEP) aircraft, the deployment of numerous high-lift propellers with small diameters on the wing’s leading edge significantly enhances lift during low-speed flight. The increase in the number of propellers leads to a decrease in diameter, which increases the disc loading. In this paper, a rapid design method applicable to heavy-loaded propellers is developed and does not require iterative calculations compared to traditional heavy-loaded propeller design methods, enabling rapid completion of the propeller design. The results of CFD computation show that the relative thrust error of the method proposed in this paper is within 5% for disc loading ranging from 600 Pa to 1400 Pa, features a high-accuracy design of propellers with required thrust, and high thrust coefficients are achieved within large advance ratio range.
Labor Market Institutions and Employment
Authors: Giotis Georgios
Published: February 2024

The role of labor market institutions and policies has received great attention throughout the history of labor economics. Labor market institutions are responsible for a wide range of policies, regulations, and organizations that affect the labor market, though their impact on employment can vary depending on the specific institutions and the economic context across countries. This entry attempts to provide an overview of five main labor market institutions and policies, i.e., the minimum wage, employment protection, the power of unions, active labor market policies, and unemployment insurance/unemployment benefits. It also presents theoretical expectations of their effects on employment outcomes and collates relevant results from the related literature, focusing mainly on the most recent empirical evidence. Finally, this entry provides insights regarding labor market institutions and offers proposals for shaping the labor market landscape.
Screening, Diagnosis, and Treatment of Patients with Binge Eating Disorder and Obesity: What the Endocrinologist Needs to Know
Authors: Marucci Simonetta , Busetto Luca , Chianelli Marco , Fusco Alessandra , Carpentieri Maria , Armellini Marina , Tassone Francesco , Sciaraffia Marcello , Ponziani Maria Chantal , Nelva Anna , Cuttica Carla Micaela
Published: February 2024

Binge eating disorder (BED) is the most common eating disorder categorized in the DSM-V, but it is often not diagnosed in patients with obesity because it can be difficult to detect in these patients who often have altered eating patterns. In this narrative review, we have highlighted the most recent findings in the screening, diagnosis, and treatment of patients with BED and obesity. The results of our search showed that many BED patients are not obese, and most people with obesity do not have binge behavior. In the diagnostic assessment of these patients, it is important to evaluate not only the clinical and nutritional status and the presence of medical comorbidities, but also the psychological signs and symptoms related to psychiatric comorbidities to define the appropriate diagnosis and the consequent level of treatment. Well-tolerated drugs with action on both body weight and binges can be useful as a second-line complement to cognitive behavioral therapy (CBT). Specific guidelines are needed to obtain consensus on appropriate recommendations in patients with obesity and BED approaching bariatric surgery, taking into account not only weight reduction and clinical data, but also eating behaviors. Identification of BED is important for targeting individuals at high risk of obesity, adverse metabolic patterns, and cardiovascular disease. The challenge is to also achieve lasting weight loss in patients with BED and concomitant obesity.
Pigment Production Using Submerged Fermentation
Authors: Venkatachalam Mekala
Published: February 2024

There has been a continuous increase in consumer awareness regarding the availability of natural, sustainable, biodegradable options in all sectors, including food, cosmetics, pharmaceuticals, textiles, painting, printing inks, etc [...]
Investigating a Fractal–Fractional Mathematical Model of the Third Wave of COVID-19 with Vaccination in Saudi Arabia
Authors: Alalhareth Fawaz K. , Alharbi Mohammed H. , Laksaci Noura , Boudaoui Ahmed , Medjoudja Meroua
Published: February 2024

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease-19 (COVID-19). This virus has caused a global pandemic, marked by several mutations leading to multiple waves of infection. This paper proposes a comprehensive and integrative mathematical approach to the third wave of COVID-19 (Omicron) in the Kingdom of Saudi Arabia (KSA) for the period between 16 December 2022 and 8 February 2023. It may help to implement a better response in the next waves. For this purpose, in this article, we generate a new mathematical transmission model for coronavirus, particularly during the third wave in the KSA caused by the Omicron variant, factoring in the impact of vaccination. We developed this model using a fractal-fractional derivative approach. It categorizes the total population into six segments: susceptible, vaccinated, exposed, asymptomatic infected, symptomatic infected, and recovered individuals. The conventional least-squares method is used for estimating the model parameters. The Perov fixed point theorem is utilized to demonstrate the solution’s uniqueness and existence. Moreover, we investigate the Ulam–Hyers stability of this fractal–fractional model. Our numerical approach involves a two-step Newton polynomial approximation. We present simulation results that vary according to the fractional orders (γ) and fractal dimensions (θ), providing detailed analysis and discussion. Our graphical analysis shows that the fractal-fractional derivative model offers more biologically realistic results than traditional integer-order and other fractional models.
Integrated Petrophysical Evaluation and Rock Physics Modeling of Broom Creek Deep Saline Aquifer for Geological CO2 Storage
Authors: Pothana Prasad , Ifrene Ghoulem , Ling Kegang
Published: February 2024

Fossil fuels, such as coal and hydrocarbons, are major drivers of global warming and are primarily responsible for worldwide greenhouse gas emissions, including carbon dioxide CO2. The storage of CO2 in deep saline reservoirs is acknowledged as one of the top practical and promising methods to reduce CO2 emissions and meet climate goals. The North Dakota Industrial Commission (NDIC) recently approved the fourth Class VI permit for a carbon capture and storage project in the Williston basin of North Dakota for the geological CO2 storage in the Broom Creek formation. The current research aimed to conduct a comprehensive petrophysical characterization and rock physics modeling of the Broom Creek deep saline reservoir to unravel the mineralogical distribution and to understand the variations in petrophysical and elastic properties across the formation. This study utilized geophysical well logs, routine core analysis, and advanced core analysis to evaluate the Broom Creek formation. Multimineral petrophysical analysis calibrated with X-ray diffraction results reveals that this formation primarily comprises highly porous clean sandstone intervals with low-porosity interspersed with dolomite, anhydrite, and silt/clay layers. The formation exhibits varying porosities up to 0.3 and Klinkenberg air permeabilities up to ∼2600 mD. The formation water resistivity using Archie’s equation is approximately 0.055 ohm-m at 150 °F, corresponding to around 63,000 ppm NaCl salinity, which is consistent with prior data. The pore throat distribution in the samples from clean sandstone intervals is primarily situated in the macro-mega scales. However, the presence of anhydrite and dolomite impedes both porosity and pore throat sizes. The accurate prediction of effective elastic properties was achieved by developing a rock physics template. Dry rock moduli were modeled using Hill’s average, while Berryman’s self-consistent scheme was employed for modeling saturated moduli.
Clinical Simulation in Palliative Care for Undergraduate Nursing Students: A Randomized Clinical Trial and Complementary Qualitative Study
Authors: Esteban-Burgos Ana Alejandra , Moya-Carramolino Jesús , Vinuesa-Box Miriam , Puente-Fernández Daniel , García-Caro María Paz , Montoya-Juárez Rafael , López-Morales Manuel
Published: February 2024

Background: a lack of adequate training in palliative care leads to a greater emotional burden on nurses. Purpose: to assess the effect of a simulation using standardized patients on self-efficacy in palliative care, ability to cope with death, and emotional intelligence among nursing students. Methods: a randomized clinical trial and qualitative study. A total of 264 nursing students in a palliative care module completed the Bugen, trait meta-mood, and self-efficacy in palliative care scales after active participation in the simulation (n = 51), watching the simulation (n = 113), and the control group (n = 100). An ANOVA with a multi-comparative analysis and McNemar’s tests for paired samples were calculated. Active participants were interviewed, and a thematic analysis was conducted. Results: there was an improvement after the assessment in all three groups assessed for coping with death (p < 0.01), emotional intelligence (p < 0.01), and self-efficacy (p < 0.01). In addition, the active group improved more than the observer group and the control group in coping with death, attention, and repair. The students in the interviews identified sadness and an emotional lack of control. Conclusions: the simulation improved nursing students’ self-efficacy in palliative care. This effect was partially stronger in the active group.
New Frontiers in the Digital Restoration of Hidden Texts in Manuscripts: A Review of the Technical Approaches
Authors: Perino Michela , Pronti Lucilla , Moffa Candida , Rosellini Michela , Felici Anna Candida
Published: February 2024

The digital restoration of historical manuscripts centers on deciphering hidden writings, made imperceptible to the naked eye due to factors such as erasure, fading, carbonization, and aging effects. Recent advancements in modern technologies have significantly improved our ability to unveil and interpret such written cultural heritage that, for centuries, had remained inaccessible to contemporary understanding. This paper aims to present a critical overview of state-of-the-art technologies, engaging in discussions about perspectives and limitations, and anticipating future applications. Serving as a practical guide, this work seeks to assist in the selection of techniques for digitally restoring ancient writings. Additionally, potential and challenges associated with integrating these techniques with advanced machine-learning approaches are also outlined.
Sustainable Stewardship of Egypt’s Iconic Heritage Sites: Balancing Heritage Preservation, Visitors’ Well-Being, and Environmental Responsibility
Authors: Hassan Thowayeb H. , Almakhayitah Muhanna Yousef , Saleh Mahmoud I.
Published: February 2024

While sustainability is widely recognized as necessary for managing heritage sites, balancing preservation demands with tourism development pressures presents significant challenges. A critical gap in the existing research relates to understanding the recurring issues that undermine the long-term sustainability of prominent archaeological destinations in Egypt and visitor well-being. Specifically, more research is needed to identify the specific sustainability and visitor experience problems that persist across Egypt’s major archaeological sites despite ongoing management efforts. Addressing this knowledge gap could help inform strategies for these destinations to balance conservation priorities with tourism in a more sustainable manner that enhances visitors’ cultural exploration. This study contributes a novel multisite content analysis of over 4423 online reviews from TripAdvisor pertaining to three of Egypt’s premier archaeological destinations—Giza Pyramids, Al Mu’izz Street, and Saqqara. Using established text mining methodologies and algorithms within Voyant Tools, critical challenges were identified through word frequency, concept network, and trend analyses. Recurring issues documented included uncontrolled commercialization undermining the ambiance of historic locales, environmental degradation from inadequate waste management and tourism overflows, and overcrowding compromising visitor comfort, health and safety. Deficiencies in signage, transportation, and other tourist services were also prominent themes. The holistic evaluation of cross-cutting concerns faced at the diverse yet interrelated sites advanced the theoretical knowledge on cooperative governance models and competencies necessary for integrative heritage management. The recommendations center on collaborative stakeholder partnerships to reform commercial practices through licensing and enforcement, upgrading aging infrastructure to support sustainable tourism volumes, and implementing zoning and carrying capacity policies tailored to local community contexts. The proposed solutions aim to safeguard Egypt’s irreplaceable cultural treasures by addressing recurrent problems that undermine environmental, economic and socio-cultural sustainability if left unresolved, positioning its archaeological wonders for appreciation and study by present and future generations.
Optimized Fertilizer–Water Management Improves Carrot Quality and Soil Nutrition and Reduces Greenhouse Gas Emissions on the North China Plain
Authors: Tang Wenhui , Zhang Cuiyue , Zhang Peiqiang , Zhao Ying , Guo Mengyao , Li Yun , Chi Ruiping , Chen Yanling
Published: February 2024

In order to improve carrot quality and soil nutrition and reduce the environmental pollution caused by intensive carrot production, more comprehensive combined water–fertilizer management strategies are necessary. This study hypothesizes that optimal management of water and fertilizer can improve carrot yield and quality and reduce greenhouse gas emissions and soil nutrient residues. Thus, coordinated water–fertilizer management strategies were tested for carrot production on the North China Plain over two consecutive growing seasons. Four treatments were tested: local standard fertilization and irrigation practices (FNP); optimized irrigation and chemical nitrogen, phosphorus, and potassium fertilizer (OPT); OPT treatment with partial replacement of chemical fertilizer with peanut shell (PS); and OPT treatment with partial replacement of chemical fertilizer with mushroom residue (M). Compared to the FNP treatment, there were statistically significant increases in soluble sugars (12–27%) and free amino acids (14–26%), and decreases in the nitrate content (7–17%) of fleshy root in the OPT, PS, and M treatments. In autumn carrots, the OPT and M treatments decreased yield, whereas PS increased yield; spring carrot yield was significantly decreased in the OPT, PS, and M groups compared to the FNP group. There were no significant effects of the treatment group on carrot growth rates, nutrient accumulation, or nutrient distribution. However, the OPT, PS, and M treatments were associated with significantly increased partial productivity of phosphate fertilizer (233–363%), reduced residual levels of nitrate and available phosphorus in the top 80 cm of soil, and decreased greenhouse gas emissions by 8–18% compared to the FNP treatment. These results highlight the effectiveness of partial organic fertilizer substitution and integrated water–fertilizer management to produce high-quality carrots with minimal environmental damage.
Past as Prologue: Predicting Potential Psychosocial–Ethical Burdens of Positive Newborn Screens as Conditions Propagate
Authors: Bush Lynn W. , Levy Harvey L.
Published: February 2024

We look to the past as prologue for guidance in predicting and circumventing potential psychosocial–ethical challenges, including those that may influence the attachment process for some parents. We consider the evolution of bioethics and developmental psychology as they intersect with newborn screening while exploring potential implications of positive findings, be they false positives, true positives, or secondary as well as incidental findings. We reflect on navigating the complex landscape that may be significantly impacted by variable phenotypes, the age of onset, and uncertain prognoses, mindful of the diagnostic odyssey continuum. We explore select facets of ethical and psychological challenges encountered with positive newborn screening findings by highlighting enduring debates to improve the policy process in public health and medicine. We believe substantive empirical research is needed, including long-term follow-up, routine prenatal assessment of tolerance for uncertainties, and especially innovative methodologies to better evaluate potential psychological distress that may be present in some at-risk individuals during the perinatal period preceding and following reports of positive findings. Mitigation strategies building on lessons learned from NBS and clinical follow-up should be implemented and studied. We conclude by pondering why we remain far afield from providing these services. Research directed towards understanding the implications of positive NBS findings will further reduce the burdens on families and care providers alike and should lead to improved communication.
Overlapping Receptor-Based Pathogenic Cascades in Degenerative Disease: Implications Ranging from Tumor Targeting to Aging and Dementia Therapeutics
Authors: D’Arrigo Joseph S.
Published: February 2024

Previous research has already shown that apolipoprotein (apo)A-I is adsorbed from the bloodstream onto the surface of certain colloidal lipid particles after the intravenous injection of such colloidal nanocarriers. As a result, various blood–brain barrier (BBB) scavenger receptors are targeted by these (apoA-I-coated) colloidal nanocarriers. This targeted molecular interaction is mediated/facilitated by the adsorbed apoA-I, which is then followed by receptor-mediated endocytosis and subsequent transcytosis of the nanocarrier particles across the BBB. A multifunctional combination therapy is obtained by adding the appropriate drug(s) to these biomimetic (lipid cubic phase) nanocarriers. This therapeutic targets specific cell-surface scavenger receptors, primarily class B type I (SR-BI), and crosses the blood–brain barrier. The lipid contents of artificial biomimetic (nanoemulsion) nanocarrier particles and of naturally occurring high-density lipoproteins (HDL) have been shown to be similar, which enables these nanocarrier particles to partially imitate or simulate the known heterogeneity (i.e., subpopulations or subspecies) of HDL particles. Hence, colloidal drug nanocarriers have the potential to be used in the biomedical treatment of complicated medical conditions including dementia, as well as certain elements of aging. Widespread inflammation and oxidative stress—two processes that include several pathophysiological cascades—are brought on by dementia risk factors. More recent studies suggest that proinflammatory cytokines may be released in response to a prolonged inflammatory stimulus in the gut, for example through serum amyloid A (SAA). Therefore, pharmacologically targeting a major SAA receptor implicated in the SAA-mediated cell signaling processes that cause aging and/or cognitive decline, and ultimately Alzheimer’s disease or (late-onset) dementia, could be an effective preventive and therapeutic approach.
Combining Wave and Particle Effects in the Simulation of X-ray Phase Contrast—A Review
Authors: Pietersoone Emilie , Létang Jean Michel , Rit Simon , Brun Emmanuel , Langer Max
Published: February 2024

X-ray phase-contrast imaging (XPCI) is a family of imaging techniques that makes contrast visible due to phase shifts in the sample. Phase-sensitive techniques can potentially be several orders of magnitude more sensitive than attenuation-based techniques, finding applications in a wide range of fields, from biomedicine to materials science. The accurate simulation of XPCI allows for the planning of imaging experiments, potentially reducing the need for costly synchrotron beam access to find suitable imaging parameters. It can also provide training data for recently proposed machine learning-based phase retrieval algorithms. The simulation of XPCI has classically been carried out using wave optics or ray optics approaches. However, these approaches have not been capable of simulating all the artifacts present in experimental images. The increased interest in dark-field imaging has also prompted the inclusion of scattering in XPCI simulation codes. Scattering is classically simulated using Monte Carlo particle transport codes. The combination of the two perspectives has proven not to be straightforward, and several methods have been proposed. We review the available literature on the simulation of XPCI with attention given to particular methods, including the scattering component, and discuss the possible future directions for the simulation of both wave and particle effects in XPCI.
A Reference Design Model to Manage Consent in Data Subjects-Centered Internet of Things Devices
Authors: Khatiwada Pankaj , Yang Bian , Lin Jia-Chun , Mugurusi Godfrey , Underbekken Stian
Published: February 2024

Internet of Things (IoT) devices have changed how billions of people in the world connect and interact with each other. But, as more people use IoT devices, many questions arise about how these devices handle private data and whether they properly ask for permission when using it. Due to information privacy regulations such as the EU’s General Data Protection Regulation (GDPR), which requires companies to seek permission from data subjects (DS) before using their data, it is crucial for IoT companies to obtain this permission correctly. However, this can be really challenging in the IoT world because people often find it difficult to interact with and manage multiple IoT devices under their control. Also, the rules about privacy are not always clear. As such, this paper proposes a new model to improve how consent is managed in the world of IoT. The model seeks to minimize “consent fatigue” (when people get tired of always being asked for permission) and give DS more control over how their data are shared. This includes having default permission settings, being able to compare similar devices, and, in the future, using AI to give personalized advice. The model allows users to easily review and change their IoT device permissions if previous conditions are not met. It also emphasizes the need for easily understandable privacy rules, clear communication with users, and robust tracking of consent for data usage. By using this model, companies that provide IoT services can do a better job of protecting user privacy and managing DS consent. In addition, companies can more easily comply with data protection laws and build stronger relationships with their customers.
Water Uptake Behavior of Injection-Molded Wood–Plastic Composites
Authors: Burgstaller Christoph , Renner Károly
Published: February 2024

Wood–plastic composites (WPC) are partially biobased composite materials that exhibit appealing properties, but also some drawbacks. One is the inherent propensity to take up water, which influences different composite properties. In this work, we investigated the general water uptake behavior of injection-molded WPC and applied a simple model to evaluate different formulations. We found that the major influence is the wood content, but also, wood particle size showed a distinct influence on the water uptake speed, while the saturation concentration correlated with the equilibrium moisture content of the wood. The mechanical properties, such as elastic modulus and tensile strength, were reduced with increasing water uptake, and the reduction correlated with wood content and the moisture content of the wood, while the particle size did not show an influence in the investigated region.
Numerical Model of Simultaneous Multi-Regime Boiling Quenching of Metals
Authors: González-Melo Marco Antonio , Rodríguez-Rodríguez Omar Alonso , Hernández-Morales Bernardo , Acosta-González Francisco Andrés
Published: February 2024

This work presents a heat transfer and boiling model that computes the evolution of the temperature field in a representative steel workpiece quenched from 850 or 930 °C by immersion in water flowing at average velocities of 0.2 or 0.6 m/s, respectively. Under these conditions, all three boiling regimes were present during cooling: stable vapor film, nucleate boiling, and single-phase convection. The model was based on the numerical solution of the heat conduction equation coupled to the solution of the energy and momentum equations for water. The mixture phase approach was adopted using the Lee model to compute the rates of water evaporation–condensation. Heat flux at the wall was calculated for all regimes using a single semi-mechanistic model. Therefore, the evolution of boiling regimes at every position on the wall surface was automatically determined. Predictions were validated using laboratory results, namely: (a) videorecording the upward motion of the wetting front along the workpiece wall surface; and (b) cooling curves obtained with embedded thermocouples in the steel probe. Wall heat flux calculations were used to determine the importance of the simultaneous presence of all three boiling regimes on the heat flux distribution. It was found that this simultaneous presence leads to high heat flux variations that should be avoided in production lines. In addition, it was determined that the corresponding inverse heat conduction problem to estimate the active heat transfer boundary condition must be set-up for 2D heat flow.
A Data-Driven Method for Ship Motion Forecast
Authors: Jiang Zhiqiang , Ma Yongyan , Li Weijia
Published: February 2024

Accurate forecasting of ship motion is of great significance for ensuring maritime operational safety and working efficiency. A data-driven ship motion forecast method is proposed in this paper, aiming at the problems of low generalization of a single forecast model and insufficient forecast accuracy under unknown conditions. First, the fluid dynamics simulations of the ship are carried out under multiple node conditions based on overset mesh technology, and the obtained motion data is used for training the Bidirectional Long Short-term Memory network models. One or more pre-trained forecast models would be selected based on the correlation of condition nodes when forecasting ship motion under non-node conditions. The Golden Jackal Optimization Algorithm is used to compute the regression coefficient of each node model in real time, and finally, the dynamic model average is calculated. The results show that the method proposed in this study can accurately forecast the pitch and heave of the KCS ship in 5 s, 10 s, and 15 s of forecast duration. The accuracy of the multi-order forecast model improves more in longer forecast duration tasks compared with the first-order model. When forecasting ship motion under non-node conditions, the method shows stronger model generalization capabilities.
A Rigid-Flexible Coupling Dynamic Model for Robotic Manta with Flexible Pectoral Fins
Authors: Qu Yilin , Xie Xiao , Zhang Shucheng , Xing Cheng , Cao Yong , Cao Yonghui , Pan Guang , Song Baowei
Published: February 2024

The manta ray, exemplifying an agile swimming mode identified as the median and paired fin (MPF) mode, inspired the development of underwater robots. Robotic manta typically comprises a central rigid body and flexible pectoral fins. Flexible fins provide excellent maneuverability. However, due to the complexity of material mechanics and hydrodynamics, its dynamics are rarely studied, which is crucial for the advanced control of robotic manta (such as trajectory tracking, obstacle avoidance, etc.). In this paper, we develop a multibody dynamic model for our novel manta robot by introducing a pseudo-rigid body (PRB) model to consider passive deformation in the spanwise direction of the pectoral fins while avoiding intricate modeling. In addressing the rigid-flexible coupling dynamics between flexible fins and the actuation mechanism, we employ a sequential coupling technique commonly used in fluid-structure interaction (FSI) problems. Numerical examples are provided to validate the MPF mode and demonstrate the effectiveness of the dynamic model. We show that our model performs well in the rigid-flexible coupling analysis of the manta robot. In addition to the straight-swimming scenario, we elucidate the viability of tailoring turning gaits through systematic variations in input parameters. Moreover, compared with finite element and CFD methods, the PRB method has high computational efficiency in rigid-flexible coupling problems. Its potential for real-time computation opens up possibilities for future model-based control.
Meiotic Cytokinesis in Saccharomyces cerevisiae: Spores That Just Need Closure
Authors: Durant Matthew , Mucelli Xheni , Huang Linda S.
Published: February 2024

In the budding yeast Saccharomyces cerevisiae, sporulation occurs during starvation of a diploid cell and results in the formation of four haploid spores forming within the mother cell ascus. Meiosis divides the genetic material that is encapsulated by the prospore membrane that grows to surround the haploid nuclei; this membrane will eventually become the plasma membrane of the haploid spore. Cellularization of the spores occurs when the prospore membrane closes to capture the haploid nucleus along with some cytoplasmic material from the mother cell, and thus, closure of the prospore membrane is the meiotic cytokinetic event. This cytokinetic event involves the removal of the leading-edge protein complex, a complex of proteins that localizes to the leading edge of the growing prospore membrane. The development and closure of the prospore membrane must be coordinated with other meiotic exit events such as spindle disassembly. Timing of the closure of the prospore membrane depends on the meiotic exit pathway, which utilizes Cdc15, a Hippo-like kinase, and Sps1, an STE20 family GCKIII kinase, acting in parallel to the E3 ligase Ama1-APC/C. This review describes the sporulation process and focuses on the development of the prospore membrane and the regulation of prospore membrane closure.