bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Two Field Deployable PCR Platforms for SARS-CoV-2 and Influenza A and B Viruses’ Detection
Authors: Bouamar Hakim , Reed Grace M. , Lyon Wanda , Lopez Hector , Ochoa Anna , Asin Susana N.
Published: January 2025

Background: Respiratory viral infections are a major public health challenge and the most diagnosed medical condition, particularly for individuals living in close proximity, like military personnel. We compared the sensitivity and specificity of the Biomeme FranklinTM and Truelab® RT-PCR thermocyclers to determine which platform is more sensitive and specific at detecting SARS-CoV-2 and influenza A and B viruses. Methodology: RNA extracted from nasopharyngeal swabs of infected and uninfected individuals was tested on the Biomeme FranklinTM at Lackland and the Truelab® at Wright Patterson Air Force bases. Results: We found an 88% and 71% positivity rate in SARS-CoV-2-infected samples tested on Biomeme and Truelab®, respectively. Likewise, we found a 49% and 80% positivity rate in influenza-positive samples tested on Biomeme and Truelab®, respectively. One hundred percent of uninfected swab samples tested negative for SARS-CoV-2 on both platforms. Conversely, 91% and 100% of uninfected swabs tested negative for flu on Biomeme and Truelab®, respectively. Significance: Differences in specificity and sensitivity in detection of SARS-CoV-2 and influenza between Biomeme and Truelab® suggest that Truelab® is a more promising and potentially deployable diagnostic platform for SARS-CoV-2 and influenza viruses’ detection in an austere environment.
Comparative Performance of Ante-Mortem Diagnostic Assays for the Identification of Mycobacterium bovis-Infected Domestic Dogs (Canis lupus familiaris)
Authors: O’Halloran Conor , Burr Paul , Gunn-Moore Danielle A. , Hope Jayne C.
Published: January 2025

The domestic dog (Canis lupus familiaris) is a competent host for Mycobacterium (M.) bovis infection but no ante mortem diagnostic tests have been fully validated for this species. The aim of this study was to compare the performance of ante mortem diagnostic tests across samples collected from dogs considered to be at a high or low risk of sub-clinical M. bovis infection. We previously tested a total of 164 dogs at a high risk of infection and here test 42 dogs at a low risk of infection and 77 presumed uninfected dogs with a combination of cell-based and/or serological diagnostic assays previously described for use in non-canid species. The interferon-gamma release assay (IGRA) using peripheral blood mononuclear cells (PBMCs) identified the highest number of test-positive animals (85, 52%), with a suggested specificity of 97.3%, whilst a whole-blood IGRA was found to be unreliable. The production of antigen-specific tumour necrosis factor-alpha (TNF-α) by PBMC in response to a cocktail of ESAT-6 and CFP-10 peptides correlated very strongly with the overall IGRA results, suggesting future diagnostic potential. All three serological assays employed in this study (Idexx M. bovis Ab ELISA, [Idexx Laboratories, Westbrook, ME, USA], DPP VetTB lateral flow assay [Chembio, Medford, NY, USA], and comparative PPD ELISA [in-house]) identified seropositive dogs but, overall, the test-positive rate for the serological assays was only one third that of the cellular-based assays. Circulating serum cytokine concentrations of interferon gamma and TNF-α were not statistically different between the high- and low-risk groups of dogs. While many dogs in the high-risk group had serum biochemical abnormalities, these did not correlate with the findings from the diagnostic TB tests. This study demonstrates, for the first time, the utility of two cellular and three serological assays for detecting sub-clinical M. bovis infections of dogs. Whilst the data suggest a high test specificity for all assays evaluated, further work is needed to validate the sensitivity and specificity of individual or combinations of tests using sufficient numbers of dogs of a known infection status.
A Novel Strain of Orientia tsutsugamushi Detected from Chiggers (Acari: Trombiculidae) on Wild Rodents
Authors: Lee Hak Seon , Kim Seong Yoon , Lee Hee Il
Published: January 2025

Scrub typhus is caused by intracellular bacteria belonging to the genus Orientia. Until 2010, the endemic region was thought to be restricted to the Asia–Pacific region. Orientia species have recently been discovered in South America, Africa, Europe, and North America. In accordance with these circumstances, we tried to find new or novel bacterial strains in the Republic of Korea (ROK). We found that a new strain of O. tsutsugamushi formed a unique clade based on a 56-kDa type-specific antigen gene and showed 63.2–77.8% similarity to other strains of the same species. Additionally, we identified another sequence with 99.8% similarity to the O3 strain, which has not been recorded in the ROK and whose pathogenicity remains unknown. These findings confirm the diversity of O. tsutsugamushi strains in the ROK, and highlight the need for continued surveillance and further studies to characterize the pathogenicity of this novel bacterial strain.
Seroprevalence of Toxoplasma gondii in White-Tailed Deer (Odocoileus virginianus) in New York State
Authors: Ledgerwood Emily D. , Luscier Jason D.
Published: January 2025

The parasitic protozoa, Toxoplasma gondii (T. gondii), is a model organism for one health because of its wide-ranging impacts on humans, wildlife, and domestic animals. Intermediate hosts, including white-tailed deer (Odocoileus virginianus), have been implicated in its maintenance. Prior analysis of Toxoplasma gondii seroprevalence in New York State deer focused on rural areas; however, the high density of domestic cats (Felis catus) in urban areas has been implicated in its spread amongst deer. To address this, the seroprevalence of Toxoplasma gondii was assessed across two suburban and urban areas with known deer overabundance in Onondaga and Suffolk County. Here, domestic cats are the only likely definitive host. Between 2019 and 2023, serum from culled deer was collected, and Toxoplasma gondii seropositivity was determined using the modified agglutination test. Overall seroprevalence was 49.31% (n = 144) but was significantly higher in Onondaga (64%) compared to Suffolk County (36%), despite similarities between these two regions. Deer from Onondaga also had higher antibody titers. These data suggest that although urbanization may be a predictor of Toxoplasma gondii seropositivity in deer, there are additional contributing factors. Overall, this study emphasizes the need for continued surveillance in intermediate hosts and informs public health and wildlife management decisions aimed at limiting the impact of Toxoplasma gondii.
Harnessing the AI/ML in Drug and Biological Products Discovery and Development: The Regulatory Perspective
Authors: Mirakhori Fahimeh , Niazi Sarfaraz K.
Published: January 2025

Artificial Intelligence (AI) has the disruptive potential to transform patients’ lives via innovations in pharmaceutical sciences, drug development, clinical trials, and manufacturing. However, it presents significant challenges, ethical concerns, and risks across sectors and societies. AI’s rapid advancement has revealed regulatory gaps as existing public policies struggle to keep pace with the challenges posed by these emerging technologies. The term AI itself has become commonplace to argue that greater “human oversight” for “machine intelligence” is needed to harness the power of this revolutionary technology for both potential and risk management, and hence to call for more practical regulatory guidelines, harmonized frameworks, and effective policies to ensure safety, scalability, data privacy, and governance, transparency, and equitable treatment. In this review paper, we employ a holistic multidisciplinary lens to survey the current regulatory landscape with a synopsis of the FDA workshop perspectives on the use of AI in drug and biological product development. We discuss the promises of responsible data-driven AI, challenges and related practices adopted to overcome limitations, and our practical reflections on regulatory oversight. Finally, the paper outlines a path forward and future opportunities for lawful ethical AI. This review highlights the importance of risk-based regulatory oversight, including diverging regulatory views in the field, in reaching a consensus.
Innovative Strategies in Oncology: Bacterial Membrane Vesicle-Based Drug Delivery Systems for Cancer Diagnosis and Therapy
Authors: Li Guodong , Pu Shuangpeng , You Lisiyao , Gao Yuan , Zhong Yuexia , Zhao Huadong , Fan Dong , Lu Xiyan
Published: January 2025

Outer membrane vesicles (OMVs) are double-layered structures of nanoscale lipids released by gram-negative bacteria. They have the same membrane composition and characteristics as primitive cells, which enables them to penetrate cells and tissues efficiently. These OMVs exhibit excellent membrane stability, immunogenicity, safety, and permeability (which makes it easier for them to penetrate into tumour tissue), making them suitable for developing cancer vaccines and drug delivery systems. Recent studies have focused on engineering OMVs to enhance tumour-targeting capabilities, reduce toxicity, and extend circulation time in vivo. This article reviews the latest progress in OMV engineering for tumour treatment and discusses the challenges associated with the use of OMV-based antitumour therapy in clinical practice.
Demonstration of Eight-Sensor Sagnac Fiber-Optic Hydrophone Array with Alternative Quadrature Phase Bias and Response Equalization Demodulation Algorithm
Authors: Zhao Delong , Wang Ke , Yang Shuolin , Xie Wenjie , Chen Yuzhong , Yang Jie , Song Zhangqi , Sun Zhaohua
Published: January 2025

The Sagnac interferometer-based fiber-optic hydrophone (S-FOH) exhibits a frequency-dependent response, causing the output signal to deviate from the original acoustic signal, with severe cases leading to signal distortion. A response equalization demodulation algorithm is demonstrated to recover high-fidelity acoustic signals from interference phase signals. An eight-sensor S-FOH array featuring an alternative quadrature phase bias scheme is demonstrated, and experimental verification of the response equalization demodulation algorithm is performed. The temporal relationship of phase modulation pulses and sampling light pulses is analyzed, and a demodulation algorithm is introduced to obtain the phase difference of the Sagnac interferometer. The acoustic pressure sensitivity is equalized to be flat with an average of −135.0 ± 0.4 dB from 10 to 2032 Hz. The pulse response of the S-FOHA after the equalization algorithm is highly similar to the PZT hydrophone output signal, with a correlation coefficient of 0.987.
Experimental Study on Fracture Propagation in Carbonate Rocks by Acid Fracturing Using the Image-Based 3D Object Reconstruction Technique
Authors: Jin Chenhao , Mao Haijun , Zhou Jun , Liu Yiming , Duan Motao , Guo Zechen , Wang Kaijie
Published: January 2025

Acid fracturing is an effective method of reservoir stimulation and has been widely used for carbonate reservoir development. However, knowledge on the propagation characteristics of acid-etched fracture is still poor due to the complexities of acidization and stress conditions, as well as the limitations of the fracture network reconstruction method, especially when dealing with large specimens. In this paper, a new method based on image-based 3D object reconstruction is proposed to study the fracture networks of specimens after acid fracturing by cutting rock specimens into thin slices, scanning them, and reconstructing 3D fracture networks. This method is more precise than the method of separating specimens into pieces and scanning, and it has advantages over the method of CT X-ray scanning when dealing with large specimens. Using this approach, the effects of natural fractures, stress conditions, and acid systems on the fracture propagation of specimens after true triaxial acid-fracturing tests were investigated. The fracture initiation and propagation patterns of specimens under different conditions were summarized. The results of the study show that the presence of a natural fracture will induce the propagation of fractures, in addition to demonstrating the positive effect of high horizontal stress difference on fracture initiation and provide an acid system conducive to the formation of a fracture network.
A Review of Safety Valves: Standards, Design, and Technological Advances in Industry
Authors: Cană Petrică , Ripeanu Razvan George , Diniță Alin , Tănase Maria , Portoacă Alexandra Ileana , Pătîrnac Iulian
Published: January 2025

This review synthesizes insights from the literature and incorporates computational and experimental analyses to explore various types of safety valves and their applications across industries such as oil and gas, chemical manufacturing, and power generation. Key areas of focus include global regulatory standards from organizations like the American Society of Mechanical Engineers (ASME), International Organization for Standardization (ISO), Deutsches Institut für Normung (DIN), and American Petroleum Institute (API), which ensure stringent design and testing requirements. This paper examines the historical development of safety valves, recent technological advancements such as smart valves with integrated sensors, and predictive maintenance capabilities, along with ongoing challenges in high-pressure and corrosive environments. Additionally, it highlights the role of computational tools like CFD and FEA in optimizing valve designs and ensuring reliability under demanding conditions. By presenting a streamlined analysis of standards, innovations, and future directions, this review underscores the indispensable importance of safety valve technology in ensuring operational safety across various industrial applications.
Numerical Study to Optimize the Operating Parameters of a Real-Sized Industrial-Scale Micron Air Classifier Used for Manufacturing Fine Quartz Powder and a Comparison with the Prototype Model
Authors: Ho Nang Xuan , Dinh Hoi Thi , Dau Nhu The
Published: January 2025

In this study, we successfully captured and compared the gas−particle flow field in a real-sized industrial-scale micron air classifier and in a prototype. All simulation calculations were performed using high-performance computing (HPC) systems and 3D transient simulations with the TWC-RSM–DPM (Two-Way Coupling–Reynolds Stress Model–Discrete Phase Model) in ANSYS Fluent (version 2022 R2). The following objectives were achieved: (i) a comparison of the simulation results was made between a real-size industrial-scale micron air classifier and a prototype model (scaled-down model) to show the differences between them and highlight the necessity of a simulation study on a real-size industrial-scale model for optimization purposes; (ii) a detailed analysis of the effects of the multiple vortices inside both the main and secondary classification zones provided a deeper understanding of the classification mechanism of the real-sized industrial-scale micron air classifier; and (iii) on the basis of the classifier’s key performance indicators (KPIs: d50, K, η) and the constrained condition (i.e., the know-how particle size distribution curve (KHC) of quartz fine powder material of 0–45 µm) applied in manufacturing engineering stone, the relationship between the operating parameters and classification performance was addressed, and the optimal set of operating parameters for the production of quartz fine powder material (0–45 µm) was selected. The simulation results will be validated using experimental results at the Vicostone Plant, Phenikaa Group.
Synergistic Pd-La Catalysts on ATO for Clean Conversion of Methane into Methanol and Electricity
Authors: Gomes Paulo Victor. R. , Lazar Dolores R. R. , Silvestrin Gabriel , Maia Victoria Amatheus , de Souza Rodrigo Fernando B. , Neto Almir Oliveira
Published: January 2025

This study investigates the electrochemical conversion of methane to methanol using fuel-cell-type reactors with palladium- and lanthanum-based catalysts supported on antimony-doped tin oxide (ATO). The combination of these elements demonstrated promising characteristics for selective methanol production. Transmission electron microscopy (TEM) analysis revealed the impact of lanthanum addition on palladium nanoparticles, influencing size distribution and clusters. Polarization curves and power density plots highlighted the Pd50La50/ATO catalyst, indicating an optimal palladium/lanthanum ratio for methanol optimization. FTIR analysis confirmed the presence of methanol in the reaction products, while the methanol production rate showcased the superior performance of the Pd50La50/ATO catalyst compared to other compositions. The synergistic effects between lanthanum’s water activation capability and the carbophilic nature of PdO emerged as crucial factors for the catalyst’s success.
Time to Diagnosis and Treatment of Postpartum Hypertensive Disorders in the Emergency Department—A Single Retrospective Cohort Study
Authors: Ezell Gabrielle J. , Smith Nicolina , Condon Mary , Joyce Katherine , Joseph John , Springer Kylie , Pitts D’Angela S.
Published: January 2025

Background/Objectives: In the postpartum period, approximately 12% of patients seek care in the emergency department (ED), with a higher representation of Black patients. Hypertension is a common reason for ED visits during this period, often leading to dangerously delayed diagnosis and treatment. Objective: This study aims to assess the time to diagnosis and treatment of hypertensive disorders in the postpartum period in the ED, focusing on potential disparities in care, to identify areas for quality improvement. Design: Retrospective cohort study. Setting: A multi-centered large medical institution in the metro Detroit area. Methods: Postpartum patients (day 2 through day 28) presenting to the ED from November 2015 to December 2022. Exposures: none. Main Outcome Measures: Primary analysis assessed the time elapsed between severe-range blood pressure readings (greater than/equal to 160 systolic and/or 110 diastolic) and the administration of antihypertensives. Secondary analyses assessed the presence of essential laboratory workups such as complete blood counts, complete metabolic panels, and urine protein and creatinine. Results: Among the 430 women who presented to the ED during the postpartum period with hypertension, 372 (86.5%) exhibited severe-range blood pressure (greater than/equal to 160 systolic and/or 110 diastolic). Patients presented on average on postpartum day 6. Of the patients with severe hypertension, only 72% received a complete blood count, 66% underwent evaluation of creatinine and liver profile, and 4% had a urine protein and creatinine test ordered. The average time from severe-range blood pressure reading to antihypertensive administration was 189 min for Black patients and 370 min for White patients. There were no statistically significant differences in the time of the first blood pressure reading, laboratory evaluation, or treatment of severe-range blood pressure between racial groups. Conclusions: This study identifies the most significant area for improvement in the timely administration of antihypertensive medication following severe-range blood pressure readings. Additional areas for improvement were observed in ordering essential laboratory tests to assess the severity of preeclampsia. The institution demonstrated delayed yet equitable care for White and Black patients, contrary to the existing literature indicating potential racial disparities. A targeted quality improvement plan has been implemented to improve the identified areas of concern to adhere to the ACOG’s treatment recommendations for hypertensive disorders of pregnancy. The impact on patient care will be reassessed at the 1-year mark.
Research on the Simulation Model of Dynamic Shape for Forest Fire Burned Area Based on Grid Paths from Satellite Remote Sensing Images
Authors: Ling Xintao , Zhang Gui , Zheng Ying , Xiao Huashun , Yang Yongke , Zhou Fang , Wu Xin
Published: January 2025

The formation of forest fire burned area, influenced by a variety of factors such as meteorology, topography, vegetation, and human intervention, is a dynamic process of fire line burning that develops from the point of ignition to the boundary of the burned area. Accurately simulating and predicting this dynamic process can provide a scientific basis for forest fire control and suppression decisions. In this study, five typical forest fires located in different regions of China were used as the study object. The straight path distances from the ignition point grid to each grid on fire line in Sentinel-2 imageries for each forest fire were used as the target variables. We obtained the values of 11 independent variables for each pathway, including wind speed component, Temperature, Relative Humidity, Elevation, Slope, Aspect, Degree of Relief, Normalized Difference Vegetation Index, Vegetation Type, Fire Duration, and Gross Domestic Product reflecting human intervention capacity for fires. The value of each target variable and that of its corresponding independent variable constituted a sample. Four machine learning models, such as Random Forest (RF), Gradient Boosting Decision Trees (GBDT), Support Vector Machine (SVM), and Multilayer Perceptron (MLP), were trained using 80% effective samples from four forest fires, and 20% used to verify the above models. The hyper-parameters of each model were optimized using grid search method. After analyzing the validation results of models which showed temperature as a non-significant variable, the training and validation process of models above was repeated after excluding temperature. The results show that RF is the optimal model with 49.55 m for root mean square error (RMSE), 29.19 m for mean absolute error (MAE) and 0.9823 for coefficient of determination (R2). This study used the RF model to construct the shape of burned areas by predicting lengths of all straight path distances from the ignition point to the fire line. The study can dynamically capture the development of forest fire scenes.
An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction
Authors: Hadded Ahmed , Ben Ayed Mossaad , Alshaya Shaya A.
Published: January 2025

Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FET) biosensor with a high-gain amplification circuit and a 1D Convolutional Neural Network (CNN) implemented on FPGA hardware. This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency. The integration of a 1D CNN model on FPGA hardware for adaptive, non-linear noise filtering sets this design apart from conventional filtering approaches by achieving high accuracy and low power consumption in a portable format. This integration of SiNW-FET with FPGA-based CNN noise reduction offers a unique approach, as prior noise reduction techniques for biosensors typically rely on linear filtering or digital smoothing, which lack adaptive capabilities for complex, non-linear noise patterns. By introducing the 1D CNN on FPGA, this architecture enables real-time, high-fidelity noise reduction, preserving critical signal characteristics without compromising processing speed. Notably, the findings presented in this work are based exclusively on comprehensive simulations using COMSOL and MATLAB, as no physical prototypes or biomarker detection experiments were conducted. The SiNW-FET biosensor, functionalized with antibodies specific to viral antigens, detects impedance shifts caused by antibody–antigen interactions, providing a highly sensitive platform for viral detection. A high-gain folded-cascade amplifier enhances the Signal-to-Noise Ratio (SNR) to approximately 70 dB, verified through COMSOL and MATLAB simulations. Additionally, a 1D CNN model is employed for adaptive noise reduction, filtering out non-linear noise patterns and achieving an approximate 75% noise reduction across a broad frequency range. The CNN model, implemented on an Altera DE2 FPGA, enables high-throughput, low-latency signal processing, making the system viable for real-time applications. Performance evaluations confirmed the proposed system’s capability to enhance the SNR significantly while maintaining a compact and energy-efficient design suitable for portable diagnostics. This integrated architecture thus provides a powerful solution for high-precision, real-time viral detection, and continuous health monitoring, advancing the role of biosensors in accessible point-of-care diagnostics.
A Framework of State Estimation on Laminar Grinding Based on the CT Image–Force Model
Authors: Liu Jihao , Zheng Guoyan , Yan Weixin
Published: January 2025

It is a great challenge for a safe surgery to localize the cutting tip during laminar grinding. To address this problem, we develop a framework of state estimation based on the CT image–force model. For the proposed framework, the pre-operative CT image and intra-operative milling force signal work as source inputs. In the framework, a bone milling force prediction model is built, and the surgical planned paths can be transformed into the prediction sequences of milling force. The intra-operative milling force signal is segmented by the tumbling window algorithm. Then, the similarity between the prediction sequences and the segmented milling signal is derived by the dynamic time warping (DTW) algorithm. The derived similarity indicates the position of the cutting tip. Finally, to overcome influences of some factors, we used the random sample consensus (RANSAC). The code of the functional simulations has be opened.
Robust Multi-Subtype Identification of Breast Cancer Pathological Images Based on a Dual-Branch Frequency Domain Fusion Network
Authors: Li Jianjun , Wang Kaiyue , Jiang Xiaozhe
Published: January 2025

Breast cancer (BC) is one of the most lethal cancers worldwide, and its early diagnosis is critical for improving patient survival rates. However, the extraction of key information from complex medical images and the attainment of high-precision classification present a significant challenge. In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain. Given the above considerations, this study is designed to explore the application of frequency domain analysis in BC histopathological classification. This study proposes the dual-branch adaptive frequency domain fusion network (AFFNet), designed to enable each branch to specialize in distinct frequency domain features of pathological images. Additionally, two different frequency domain approaches, namely Multi-Spectral Channel Attention (MSCA) and Fourier Filtering Enhancement Operator (FFEO), are employed to enhance the texture features of pathological images and minimize information loss. Moreover, the contributions of the two branches at different stages are dynamically adjusted by a frequency-domain-adaptive fusion strategy to accommodate the complexity and multi-scale features of pathological images. The experimental results, based on two public BC histopathological image datasets, corroborate the idea that AFFNet outperforms 10 state-of-the-art image classification methods, underscoring its effectiveness and superiority in this domain.
Experimental Study of the Interaction of Silica Nanoparticles with a Phospholipid Membrane
Authors: Milkova Viktoria
Published: January 2025

This study aims to contribute to the physical understanding of the behavior of nanoparticles in lipid–nanoparticle composite systems. Therefore, composite films were formed on hydrophilic or hydrophobic surfaces through the sequential adsorption of liposomes and silica nanoparticles. The process was performed using dispersions with different pHs by using optical fixed-angle reflectometry. In the first step, liposomes were deposited on the surface, resulting in a lipid monolayer or bilayer depending on the surface’s properties. The kinetic experiments indicated that the adsorption of liposomes is a diffusion-limited process that depends on the pH and the properties of the substrate. In the second step, negatively charged nanoparticles were adsorbed on the membrane as a result of the electrostatic interactions with the positively charged domains on the membrane. The amounts of liposomes and particles adsorbed depend on the charge density of the particles and net charge density of the membrane: an increase in the pH and hydrophobicity of the surface leads to a decrease in the amounts adsorbed because of the increase in the electrostatic repulsion between particles and lipids. The procedure was supplemented with the formation of two liposomes/nanoparticles bilayers.
Intersectionality and Birth in Latin America: A Research Protocol on Maternal Health of Indigenous and Afro-Descendant Women in La Guajira, Colombia
Authors: Évora Mariana Anginho
Published: January 2025

This article presents a research protocol focusing on the maternal health of Indigenous wayuu and Afro-descendant women in the region of La Guajira, Colombia. Following a decolonial approach and expecting the project to contribute to the field of sociology of birth, in this paper I propose to discuss the mobilized literature, methodologies, and ethical concerns critically and reflectively. This research aims to understand how the various paradigms of birth interact in contemporary times and how these interactions affect women’s experiences and expectations; to contribute to knowledge about birth and maternity among the Indigenous and Afro-descendant people of Colombia; and to evaluate existing maternal health indicators while proposing new ones that respond to the criteria and needs of the population under study. An ethnography and narrative interviews will be conducted with Indigenous wayuu and Afro-descendant women and health professionals in La Guajira, a department of Northern Colombia. Additionally, statistical birth analysis using data available from the National Statistical System of Colombia will be implemented. The results will be combined, co-created with study participants, and disseminated to a variety of audiences.
‘Why Are the White Kids Clean and the Brown Kids Still Dirty?’: Parental Encounters with Racial Discrimination in Early Childhood Services
Authors: Lamb Cherie Suzanne
Published: January 2025

In Australia, the Early Years Learning Framework sets out a vision for all children to experience belonging, wellbeing, confidence, and a sense of identity. This article forefronts the voices of parents with refugee experience, through focus groups and interviews, to explore why they removed their children from early childhood education and care (ECEC) services. Supplemented by interviews with early childhood practitioners and researcher experience, constructivist grounded theory overlaid with critical race theory provided a lens through which to scrutinize the way racism implicitly impacts structural practices within ECEC environments. The overarching message was that everything is framed within the parameters of the dominant culture, which was taken for granted by educators, who are predominantly White and middle class. Parents withdrew their children because they perceived care to be culturally unsafe and unsuitable and because cultural and linguistic support was rarely available. Of concern were the smothering effects of assimilation and the imposition of a foreign culture which unsettled family life. Compromised identity and the nullification of cultural and linguistic heritage left children with little or no sense of belonging.
Effects of Intermittent Drought During Tillering and Stalk Elongation Stages on the Physiological Attributes of Diverse Sugarcane Genotypes
Authors: Tippa-art Mintra , Klomsa-ard Peeraya , Songsri Patcharin , Jongrungklang Nakorn
Published: January 2025

The growth and yield of sugarcane have been negatively impacted by drought stress, particularly during two stages of development, namely, tillering and elongation. This research aimed to determine the responses of diverse sugarcane cultivars under water-withholding conditions during the tillering and stalk elongation stages. A factorial experiment in CRD with four replications was used. Two water regimes were allocated to factor A, namely, providing water and controlling soil moisture at the field capacity (FC), and providing water-withholding (WW) conditions continuously at the tillering and elongation stages. Five different sugarcane cultivars were assigned to factor B. Drought significantly impacts the physiological characteristics of sugarcane during both the tillering and stalk elongation stages, with the tillering stage being more severely affected. KK3 and PK4 demonstrated superior drought tolerance in terms of relative water content and stomatal conductance, maintaining higher levels compared to the others. Increased proline content in the roots of K88-92 and MPT14-618 under drought conditions facilitated osmotic adjustment. Biomass production varied significantly across genotypes, with MPT14-618, KK3, and K88-92 maintaining better biomass compared to UT12 and PK4. The findings suggest that drought stress differentially impacts sugarcane genotypes, with KK3, K88-92, and MPT14-618 exhibiting superior physiological and growth resistance. These genotypes show promising potential for cultivation in arid regions.
Elevated Soil Temperatures Impact Nematode Reproduction Biology
Authors: GC Sagar , Banakar Prakash , Harshman David , Khanal Churamani
Published: January 2025

Plant-parasitic nematodes are one of the economically most important pathogens, and how rising soil temperatures due to climate change impact their ability to damage crops is poorly understood. The current study was conducted to evaluate the reproduction biology (reproduction and virulence) of Rotylenchulus reniformis and Meloidogyne floridensis on tomato at soil temperatures of 26 °C (control), 32 °C, 34 °C, and 36 °C. The reproduction and virulence of both nematode species were differentially impacted by soil temperature. Relative to the control, the increase in reproduction of R. reniformis ranged from 20% to 116% while that of M. floridensis ranged from 22% to 133%. The greatest reproduction of R. reniformis was observed at 34 °C while that of M. floridensis was observed at 32 °C. Across all temperatures, reproduction of M. floridensis was 2.9 to 7.8 times greater than the reproduction of R. reniformis, suggesting that the former nematode species has a greater fecundity. The rates of change in reproduction relative to the controls were greater in M. floridensis than in R. reniformis, indicating that the latter nematode species is more resilient to changes in soil temperature. The virulence of both nematode species increased numerically or significantly at 32 °C and 36 °C, but not at 34 °C. The greatest virulence of both nematode species was observed at 36 °C at which 57% and 60% root biomass was lost to R. reniformis and M. floridensis, respectively, compared to the root biomass of uninoculated plants at that temperature. The results of the current study suggested that crop damage by nematodes will likely increase as global soil temperature continues to increase.
One-Pot Combined Hydrodistillation of Industrial Orange Peel Waste for Essential Oils and Pectin Recovery: A Multi-Objective Optimization Study
Authors: Paini Jacopo , Midolo Giusi , Valenti Francesca , Ottolina Gianluca
Published: January 2025

Sustainable waste management for orange peel waste is a global concern that presents a concomitant opportunity. In this study, a combined process was developed to optimize the simultaneous recovery of pectin, essential oils, and sugars from industrial orange peel waste. The sequential recovery process was used as a benchmark, while a one-pot combined process was optimized through the design of the experiments. A multi-objective desirability function was computed to maximize process performance while balancing opposing optimal conditions. The aim was to find a model able to confidently predict yields while reducing the process environmental footprint, potentially giving the necessary multi-product flexibility in modern biorefining. As a result, the combined process under optimal conditions, liquid-to-solid ratio of 2.5, pH value of 3.7, and residence time of 130 min, yielded 0.52% of essential oils and 11% of pectin on a dry basis. The environmental factor 18 is relevant to the fine chemicals industry, which is the target sector of this study. Finally, the process mass balance was calculated, demonstrating the opportunity to further enhance process environmental sustainability and efficiency by upgrading the resulting solid fraction.
An Assessment of Relation Between Sustainability and Architectural Representativeness of Passenger Airport Terminals in Poland
Authors: Duliński Wojciech
Published: January 2025

As the civil aviation market is in a state of continuous growth, the architecture of passenger airport terminals needs to follow the industry’s constant development. The objective of this research is to investigate the current state of terminals in Poland in relation to the aspects of representativeness and low-tech sustainability solutions incorporated into design strategies. The conducted study is a critical review of existing literature followed by a case study of relevant examples of airport terminals, from an architectural perspective. The main findings show that seemingly contradicting principles can co-exist in particular spectra of design. The broadly used big shed design method, which provides terminal buildings with an adequate level of prominence, can also facilitate sustainable solutions, especially in the areas of user comfort, energy efficiency and life cycle assessment, i.e., buildings are easily adaptable, what is demanded by constantly evolving operational models and increasing airport terminal capacities. As further improvements are definitely needed to answer the increasing demand for a reduction in the carbon footprint of buildings, changes are desirable and should focus on establishing an adequate balance between a sustainable approach and the urge to create representative, state-of-the art terminal buildings.
Ergonomic Optimization of University Dormitory Furniture: A Digital Human Modeling Approach Using Jack Software
Authors: Wei Yihan , Chen Yushu
Published: January 2025

University dormitories are vital spaces for students’ daily lives and informal learning, and require desks and chairs of utmost comfort. This study evaluates the desks and chairs at F University using Jack 8.01 software to optimize ergonomic design. By simulating three common sitting postures, this research identifies key issues, such as posture-related strain and limited reachability, particularly for female users. The optimized design introduces adjustable desk height (440~840 mm), chair height (250~520 mm), and tilt angle (0~60°), resulting in a 14.3% and 51.9% improvement in hip and knee joint comfort for the 5th percentile of female users, respectively, and effectively avoids the health risks caused by poor sitting posture. At the same time, based on the universal design concept, the design considerations for non-normative people are introduced. From the perspective of environmental sustainability, fewer wood-based panels used in the improved desk can reduce the greenhouse gas (GHG) footprint by approximately 135 kg CO2 e. These enhancements highlight the critical role of digital human modeling (DHM) in developing ergonomic, “people-centered” furniture that promotes healthier and more effective learning environments, as well as the sustainable development of educational facilities. Future work will validate these findings in real-world settings and explore their applications across educational and professional spaces.
Factors Determining Employee Loyalty During the COVID-19 Pandemic
Authors: Maksim Monika , Śliwicki Dominik
Published: January 2025

Building employee loyalty is a prerequisite for a company to achieve a competitive advantage, high organizational performance, and sustainability. The lack of voluntary leaves does not result in recruitment costs or reduced efficiency during the adaptation period of a new employee. It helps retain knowledge and experience within the organization. The article aims to explore employees’ loyalty in terms of voluntary employment continuity during the pandemic slowdown of COVID-19, when employee loyalty was put to an exceptional test, and identify the factors that have had the most significant impact. This empirical study was carried out for Germany, mainly due to the strength and position of the German economy in Europe and the availability of a large, detailed micro dataset necessary for in-depth econometric analyses. The dataset used in the survey is the fifth wave of the German Linked Personnel Panel—LPP in 2020/21 (N = 7397). A multinomial logit model was used as a research tool. Loyalty appears as an explained variable in four ordered logit models that differ in the set of explanatory variables. The explanatory variables include demographics, job title, working conditions, compensation and rewards, job content, training and career development, teamwork, and relationships with colleagues and superiors. The results confirm the influence of extra-organizational factors, such as age and living in a four- or five-person household, on employee loyalty. However, age seems to be a factor of decreasing importance. Too much complexity of work, manifested by great task variety, working in multiple teams, and the requirement to perform work remotely, harmed employee loyalty during the pandemic. Findings justify building loyalty based on sustainable human resource policies to increase income satisfaction, reasonable workload, competence development, and greater autonomy at work. It is also clear that leadership issues (fairness in contact with superiors and recognition for work) mattered during this challenging time and have a high potential to improve employee loyalty in the future.
Assessment of Vegetation Dynamics in Xinjiang Using NDVI Data and Machine Learning Models from 2000 to 2023
Authors: Ma Nan , Cao Shanshan , Bai Tao , Yang Zhihao , Cai Zhaozhao , Sun Wei
Published: January 2025

This study utilizes NASA’s Normalized Difference Vegetation Index (NDVI) data from the Google Earth Engine (GEE) platform and employs methods such as mean analysis, trend analysis, and the Hurst index to assess NDVI dynamics in Xinjiang, with a particular focus on desert, meadow, and grassland vegetation. Furthermore, multiple linear regression, random forest, support vector machines, and XGBoost models are applied to construct and evaluate the NDVI prediction models. The key driving forces are identified and ranked based on the results of the optimal model. Changes in the vegetation cover in response to these driving forces are analyzed using the Mann–Kendall test and partial correlation analysis. The results indicate the following: (1) From 2000 to 2023, the annual variation in NDVI in Xinjian fluctuates at a rate of 0.0012 per year. The intra-annual trend follows an inverted U shape, with meadow vegetation exhibiting the highest monthly NDVI fluctuations. (2) During this period, the annual average NDVI in Xinjiang ranges from 0 to 0.3, covering 74.74% of the region. Spatially, higher NDVI values are observed in the north and northwest, while lower values are concentrated in the south and southeast. (3) The overall slope of the variation in NDVI in Xinjiang between 2000 and 2023 ranges between −0.034 and 0.047, indicating no significant upward trend. According to the Hurst index, future projections suggest a shift from vegetation improvement to potential degradation. (4) Machine learning models are developed to predict NDVI, with random forest and XGBoost showing the highest precision. Soil moisture, runoff, and potential evaporation are identified as key drivers. In the last 24 years, the temperatures in Xinjiang have generally increased, while precipitation, soil moisture, and runoff have declined. There is a significant negative correlation between NDVI and both temperature and potential evaporation, while the correlation between NDVI and precipitation, soil moisture, and runoff is positive and significant, with distinct spatial variations throughout the region. The overall trend of vegetation cover in Xinjiang has been increasing, but the future outlook is less promising. Enhanced environmental monitoring and protective measures are essential moving forward.
Degradation and Stabilization Degree of Municipal Solid Waste: The Case of Two Landfills in China
Authors: Wang Chenghao , Zhang Zhenying , Ma Zheheng , Zhang Youwen , Zhu Hui , Lu Bingke , Chen Wenjie
Published: January 2025

The relationship between the cellulose/lignin (C/L) ratio and degradation rate of municipal solid waste (MSW) in landfills remains unclear. In this study, the USA National Renewable Energy Laboratory (NREL) method was employed to determine the cellulose and lignin contents of MSW at different stages of aging. A normalized degradation-stabilization index (β) that represents the ratio of C/L change to the initial C/L value was introduced to characterize the degradation and stabilization degree of solid waste, aiming to provide a scientific basis for the sustainable management of landfills. We made the following observations: (1) Over time, the degradation rate of organic matter in MSW slows down and stabilizes. This process is crucial for predicting the long-term environmental impact of landfills and formulating resource recovery strategies, contributing to the sustainable management of landfills. (2) The degradation rates of lignin and cellulose change from fast to slow over time, and the relationship between the C/L ratio and landfill age can be described effectively by the exp-decay formula. Understanding this relationship helps to optimize the waste decomposition process, reduce the negative environmental impact of landfills, and promote the sustainable development of landfills. (3) During the aging process of the landfill, the degree of waste degradation and stabilization initially increases rapidly and then shows a gradually decreasing trend. The relationship between the landfill stabilization degree, landfill age, and degradation rate can be represented adequately by a logistic formula. We also obtained expressions showing the correlations among landfill degradation–stabilization degree, age, and organic matter content. The findings provide valuable insights into landfill capacity, operational lifespan, and the redevelopment of landfills for MSW disposal, all of which are essential aspects for the sustainable management of landfills.