bluuebunny/crossref_metadata_2025 huggingface dataset:
Multitask connected U-Net: automatic lung cancer segmentation from CT images using PET knowledge guidance
Authors: Zhou Lu , Wu Chaoyong , Chen Yiheng , Zhang Zhicheng
Published: August 2024

Lung cancer is a predominant cause of cancer-related mortality worldwide, necessitating precise tumor segmentation of medical images for accurate diagnosis and treatment. However, the intrinsic complexity and variability of tumor morphology pose substantial challenges to segmentation tasks. To address this issue, we propose a multitask connected U-Net model with a teacher-student framework to enhance the effectiveness of lung tumor segmentation. The proposed model and framework integrate PET knowledge into the segmentation process, leveraging complementary information from both CT and PET modalities to improve segmentation performance. Additionally, we implemented a tumor area detection method to enhance tumor segmentation performance. In extensive experiments on four datasets, the average Dice coefficient of 0.56, obtained using our model, surpassed those of existing methods such as Segformer (0.51), Transformer (0.50), and UctransNet (0.43). These findings validate the efficacy of the proposed method in lung tumor segmentation tasks.
Methane emissions from municipal landfills: a case study of Chandigarh and economic evaluation for waste-to-energy generation in India
Authors: Mor Suman , Kaur Kamalpreet , Ravindra Khaiwal
Published: August 2024

The present study highlights the dual benefits of landfill gas utilization: mitigating greenhouse gas emissions and generating renewable energy. Municipal waste, containing a large proportion of organic matter, is dumped into Solid Waste Disposal Sites (SWDS), which, after anaerobic decomposition, releases methane (CH4). This study aims to assess the methane emissions from the SWDS of Chandigarh, India, and evaluate the potential for electricity generation from captured landfill gas. Waste samples were obtained using the quartile method and examined for proximate and ultimate analysis. The inventory and estimation of CH4 generation were done using the International Panel on Climate Change (IPCC) methodology, including the potential of electricity generation from the CH4 generated. It has been observed that Chandigarh generates around 350 tons per day (TPD) of waste, with organic material constituting over 50% on average. The estimated amount of municipal waste with observed composition led to the generation of 0.34 Gg/yr of CH4. Depending on the efficiency of the gas energy system, 0.27 MW to 0.77 MW of electric power can be produced in Chandigarh. The study also provides a broader context for solid waste management in India. Analysis of national data revealed that India generates about 160,038.9 TPD of solid waste, with only about half (79,956.3 TPD) being treated. The country has 3,184 existing dumpsites, with significant variations across states. As per the present analysis, when extrapolated to a national scale, India could potentially generate 5,167 MW to 14,355 MW of power from all its SWDS, resulting in annual financial gains of 4.7 to 13 billion USD. These findings underscore the importance of implementing integrated waste management strategies that prioritize waste reduction, efficient treatment, and energy recovery from landfill gas.
Healthcare experiences of LGBTQ+ people: non-binary people remain unaffirmed
Authors: Nowaskie Dustin Z. , Menez Olwen
Published: August 2024

Introduction

Lesbian, gay, bisexual, transgender, queer, and all sexually and gender diverse (LGBTQ+) people experience discrimination across many contexts, including healthcare environments. While some research has shown transgender people and non-binary people often endure higher rates of marginalization than cisgender, sexually diverse people, past data are limited.

Methods

A sample of LGBTQ+ people (N = 173) in the United States completed an anonymous, online, self-reported survey, which included the Consumer Assessment of Healthcare Providers and Systems and healthcare experience questions. Groups, including people who identified as cisgender, sexually diverse (n = 116), transgender (n = 24), and non-binary (n = 33), were compared using chi-square and multivariate analysis of covariance tests.

Results

Compared to cisgender, sexually diverse people, non-binary people were less likely to report feeling comfortable with a physical exam, having good mental health, respected by providers, that providers had adequate medical information, that providers could care for someone going through gender affirmation, and that hospital staff were comfortable interacting with them. Additionally, non-binary people were more likely to report hospital staff misgendering them.

Discussion

These unique LGBTQ+ subgroup differences may be secondary to identity-specific stigma that non-binary people face. More international studies are needed to elucidate these subgroup-specific healthcare experiences across LGBTQ+ identities.
Environmental life cycle assessment of an on-site modular cabinet vertical farm
Authors: Martin Michael , Bustamante Maria J. , Zauli Ilaria , Orsini Francesco
Published: August 2024

The number of vertical farms has been expanding rapidly in recent years to provide more resilient and sustainable global food provisioning closer to consumers. However, there is a lack of empirical evidence on whether vertical farms can provide sustainable sourcing of food. The purpose of this study is to assess the environmental performance of a modular cabinet vertical farm producing lettuce and basil on-site at the end-user. To assess the environmental performance of this system, a life cycle assessment (LCA) was conducted to determine the total impact of producing lettuce and basil on-site, i.e., a kitchen for an office cafeteria, and compare to conventional sourcing. The results from this study suggest that the modular vertical farm can provide crops with environmental impacts comparable to or less than conventionally sourced options. GHG emissions ranged from 0.78–1.18 kg CO2-eq per kg lettuce and from 1.45–2.12 kg CO2-eq per kg basil from on-site production. The ranges suggest that the environmental performance is sensitive to methodological choices and life cycle inventory (LCI) data choices. These include how to treat the infrastructure for the modular cabinet, as it is often rented as a growing-service system, in addition to the LCI data choices related to the source of electricity. In conclusion, under local conditions (i.e., Stockholm, Sweden) the modular vertical farm can produce lettuce with equivalent emissions and quality to imported lettuce, despite its high energy requirement. The findings and knowledge from this study add to the growing body of literature on vertical farming, providing empirical evidence on the sustainability of an on-site commercial cabinet-based vertical farm. Such information can be used for comparisons and validation of claims in the industry, and to provide empirical evidence to this developing field.
A retrospective case series on bisphosphonate related osteonecrosis of the jaw in 20 cats
Authors: Hatunen Suzanna L. , Anderson Jamie G. , Bell Cynthia M. , Campos Hugo C. , Finkelman Matthew D. , Shope Bonnie H.
Published: August 2024

Introduction

This retrospective study highlights the salient aspects of a series of feline patients affected with bisphosphonate related osteonecrosis of the jaw. Though more commonly published in human literature, this presentation is rare in cats. The authors hope that this study will assist in making this a more globally known entity with subsequent improved prognosis.

Methods

Data was retrospectively obtained from the medical records between 2015 and 2021 of 20 cats with Medication Related Osteonecrosis of the Jaw. Data included patient information, clinical history, presenting complaint, systemic diseases, details referable to hypercalcemia and treatment thereof, bisphosphonate specifics (dose and duration), clinical presentation of the lesion, diagnostic testing including radiographic and histopathologic descriptions, treatment, and outcome.

Results

Pertinent results include that all 20 cats who developed Medication Related Osteonecrosis of the Jaw had been treated for idiopathic hypercalcemia with the bisphosphonate medication alendronate. Eighty-five percent of the cases had prior dental extractions at the site of MRONJ lesion. Ninety-five percent of the affected cats required a surgical procedure to control the disease. Thirty-five percent of cases required at least one revision surgery after the initial procedure was performed. Diagnosis of MRONJ was made by a correlation of diagnostic findings and patient history. No single diagnostic, or combination was pathognomonic for lesion diagnosis. As well, there were no statistically significant associations between patient variables assessed and the overall patient outcome.

Discussion

The case series reveals that cats with feline idiopathic hypercalcemia treated with alendronate may be at a risk for development of MRONJ, a serious oral condition with significant morbidity. Prior dental extraction sites in patients concurrently treated with bisphosphonate medications were often associated with MRONJ lesions. Therefore, any needed dental surgery should be performed prior to the use of bisphosphonates where possible. The authors have also included a relevant comparative literature review.
Response of Wheat to Pre-Emergence and Early Post-Emergence Herbicides
Authors: Gitsopoulos Thomas , Georgoulas Ioannis , Botsoglou Despoina , Vazanelli Eirini
Published: August 2024

A two-year field experiment was conducted in two consecutive seasons to evaluate the response of wheat to pre-emergence (PRE) and early post-emergence (EPOST) herbicides. The herbicides prosulfocarb (3200 g ai ha−1) and chlorotoluron plus diflufenican (1380 + 92 g ai ha−1) were applied PRE, whereas the herbicides flufenacet plus diflufenican (240 + 120 g ai ha−1) and flufenacet plus diflufenican plus metribuzin (119.7 + 119.7 + 44.8 g ai ha−1) were applied EPOST at the second leaf growth stage of wheat. Heavy rainfalls that followed the PRE treatments and cold temperatures that occurred during the EPOST applications resulted in crop injuries and reduced yields in prosulfocarb, chlorotoluron plus diflufenican and flufenacet plus diflufenican the first and the second year, respectively. Weather conditions such as heavy rainfalls and low temperatures that may occur during and after herbicide treatments should be considered to avoid crop injuries and increase crop safety.
Deficit Irrigation and High Planting Density Improve Nitrogen Uptake and Use Efficiency of Cotton in Drip Irrigation
Authors: Wu Fengquan , Tang Qiuxiang , Cui Jianping , Tian Liwen , Guo Rensong , Wang Liang , Lin Tao
Published: August 2024

The optimization of plant density plays a crucial role in cotton production, and deficit irrigation, as a water-saving measure, has been widely adopted in arid regions. However, regulatory mechanisms governing nitrogen absorption, transportation, and nitrogen use efficiency (NUE) in cotton under deficit irrigation and high plant density remain unclear. To clarify the mechanisms of N uptake and NUE of cotton, the main plots were subjected to three irrigation amounts based on field capacity (Fc): (315 [W1, 0.5 Fc], 405 [W2, 0.75 Fc, farmers’ irrigation practice], and 495 mm [W3, 1.0 Fc]). Subplots were planted and applied at three densities: (13.5 [M1], 18.0 [M2, farmers’ planting practice], and 22.5 [M3] plants m−2). The results revealed that under low-irrigation conditions, the cotton yield was 5.1% lower than that under the farmer’s irrigation practice. In all plant densities and years, the nitrogen uptake of cotton increased significantly with the increase in irrigation. However, excessive irrigation resulted in nitrogen accumulation and migration, mainly concentrated in the vegetative organs of cotton, which reduced the NUE by 9.2% compared with that under farmers’ irrigation practice. Concerning the interaction between irrigation and plant density, under low irrigation, the nitrogen uptake of high-density planting was higher, and the yield of seed cotton was only 2.9% lower than that of the control (the interaction effect of farmers’ irrigation × plant density), but the NUE was increased by 10.9%. Notably, with the increase in irrigation amount, the soil nitrate nitrogen at the 0–40 cm soil layer decreased, and high irrigation amounts would lead to the transfer of soil nitrate nitrogen to deep soil. With the increase in plant density, the rate of nitrogen uptake and the amount of nitrogen uptake increased, which significantly reduced the soil nitrate nitrogen content. In conclusion, deficit irrigation and high plant density can improve cotton yield and NUE. We anticipate that these findings will facilitate optimized agricultural management in areas with limited water.
Nonlinear Logistic Model for Describing Strawberry Fruit Production
Authors: Diel Maria Inês , Lucio Alessandro Dal Col , Bisognin Dilson Antonio , de Araujo Lopes Gabriel , dos Santos Valdeci Jose
Published: August 2024

Strawberry (Fragaria × ananassa Duch.) production can be evaluated as repeated measurements, since the same plant is harvested multiple times during the production season. The objectives were to evaluate the production of fresh mass and fruit number in successive harvests and compare three strawberry clones in two cultivation conditions. Two experiments were carried out in two environmental cultivations: the rural property and the experimental area of the Plant Science Department, Federal University of Santa Maria, Brazil. The parameters of the nonlinear logistic model and their critical points were estimated via bootstrap for each condition and clone for fresh mass and fruit number with accumulated values, depending on the thermal sum accumulated during the production season. For nonlinear regression analysis, the ordinary least squares method was used with the Gauss–Newton algorithm. Confidence intervals were obtained for each parameter and estimated critical points, and they did not cross; the treatments were considered different. There were significant differences between clones and cultivation conditions for fruit mass and number. The nonlinear logistic models, adjusted for mass and number of strawberry fruits, detailed the production season, highlighting the main differences between cultivation conditions and clones.
Nanoagrochemicals versus Conventional Fertilizers: A Field Case Study with Tailor-Made Nanofertilizers for Sustainable Crop Efficiency of Brassica oleracea L. convar. Capitata var. Sabauda
Authors: González-Feijoo Rocío , Martinez-Castillo Cecilia , Rodríguez-Seijo Andrés , Pérez-Rodríguez Paula , Arenas-Lago Daniel
Published: August 2024

Excessive use of conventional fertilizers in agricultural soils can lead to environmental contamination, particularly affecting aquifers and surface waters. Nanofertilizers, with smaller particles and greater nutrient efficiency, offer a promising alternative. This study evaluates the application of nanofertilizers by reducing NPK-doses compared to conventional fertilizers in the cultivation of Brassica oleracea L. convar. capitata var. sabauda (Savoy cabbage). Field assays were conducted in experimental plots with different NPK doses and treatments using urea-hydroxyapatite and potassium sulfate nanoparticles (optimum dose: 80 N, 100 P2O5, 250 K2O kg ha−1; and half optimum dosage). The assay was monitored throughout the crop cycle, and cabbages were harvested to determine biometric parameters, yield, and nutrient contents. The results indicated that nanofertilizers at half the recommended dosage yielded similar results to conventional fertilization in terms of cabbage growth and yield. Specifically, soil pH and available P increased by the end of the crop cycle, while total N, C, CEC, and soil texture remained unchanged, regardless of the fertilizer dose applied. Cabbage plants treated with nanofertilizers showed no significant differences in nutrient content compared to those treated with conventional fertilizers. This study supports the potential of nanofertilizers as an environmentally sustainable alternative that can reduce nutrient inputs in agriculture without compromising crop yield and quality.
Genome-Wide Analysis of Genetic Diversity and Selection Signatures in Zaobei Beef Cattle
Authors: Shi Liangyu , Zhang Pu , Liu Qing , Liu Chenhui , Cheng Lei , Yu Bo , Chen Hongbo
Published: August 2024

This investigation provides a comprehensive analysis of genomic diversity and selection signatures in Zaobei beef cattle, an indigenous breed known for its adaptation to hot and humid climates and superior meat quality. Whole-genome resequencing was conducted on 23 Zaobei cattle, compared with 46 Simmental cattle to highlight genetic distinctions. Population structure analysis confirmed the genetic uniqueness of Zaobei cattle. Using methods such as DASDC v1.01, XPEHH, and θπ ratio, we identified 230, 232, and 221 genes through DASDC, including hard sweeps, soft sweeps, and linkage sweeps, respectively. Coincidentally, 109 genes were identified when using XPEHH and θπ ratio methods. Together, these analyses revealed eight positive selection genes (ARHGAP15, ZNF618, USH2A, PDZRN4, SPATA6, ROR2, KCNIP3, and VWA3B), which are linked to critical traits such as heat stress adaptation, fertility, and meat quality. Moreover, functional enrichment analyses showed pathways related to autophagy, immune response, energy metabolism, and muscle development. The comprehensive genomic insights gained from this study provide valuable knowledge for breeding programs aimed at enhancing the beneficial traits in Zaobei cattle.
Ningxiang Pig-Derived Microbiota Affects the Growth Performance, Gut Microbiota, and Serum Metabolome of Nursery Pigs
Authors: Li Hongkun , Han Li , Zhou Feng , Wu Zichen , Zhang Longlin , Xie Renjie , Jiang Feng , Tian Qiyu , Huang Xingguo
Published: August 2024

The gut microbiota is crucial for maintaining the host’s intestinal homeostasis and metabolism. This study investigated the effects of fecal microbiota transplantation (FMT) from Ningxiang pigs on the growth performance, fecal microbiota, and serum metabolites of the same-old DLY pigs. The results indicated that the average daily gain of FMT pigs was significantly greater than that of the control (CON) group. Compared to the CON group, the FMT group significantly improved the apparent digestibility of crude fiber, crude ash, gross energy, and calcium of the pigs. The analysis of serum antioxidant status revealed that the activities of total superoxide dismutase and catalase in the serum of pigs in the FMT group were significantly elevated, whereas the level of malondialdehyde was significantly reduced. Furthermore, 16S rRNA sequencing analysis revealed that the Ningxiang pig-derived microbiota altered the fecal microbiota structure and modulated the diversity of the gut microbiota in the DLY pigs. Untargeted LC–MS metabolomics demonstrated that pigs in the FMT group exhibited distinct metabolomic profiles compared to those in the CON group. Significant changes were observed in key metabolites involved in amino acid, lipid, and carbohydrate metabolism. Additionally, a correlation analysis between serum differential metabolites and the gut microbiota revealed that the relative abundance of Lachnospiraceae_NK4A136_group and Corynebacterium was highly correlated with lipid compounds. In conclusion, Ningxiang pig-derived microbiota can alleviate oxidative stress and enhance growth performance in DLY pigs by modulating their gut microbiota and metabolic features.
A Deep Forest Algorithm Based on TropOMI Satellite Data to Estimate Near-Ground Ozone Concentration
Authors: Zong Mao , Song Tianhong , Zhang Yan , Feng Yu , Fan Shurui
Published: August 2024

The accurate estimation of near-ground ozone (O3) concentration is of great significance to human health and the ecological environment. In order to improve the accuracy of estimating ground-level O3 concentration, this study adopted a deep forest algorithm to construct a model for estimating near-ground O3 concentration. It is pointed out whether input data on particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations also affect the estimation accuracy. The model first uses the multi-granularity scanning technique to learn the features of the training set, and then it adopts the cascade forest structure to train the processed data, and at the same time, it adaptively adjusts the number of layers in order to achieve a better performance. Daily near-ground O3 concentrations in Shijiazhuang were estimated using satellite O3 column concentrations, ground-based PM2.5 and NO2 concentration data, meteorological element data, and elevation data. The deep forest model was compared with six models, namely, random forest, CatBoost, XGBoost, LightGBM, Decision Tree, and GBDT. The R-squared (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) of the proposed deep forest model were 0.9560, 13.2542, and 9.0250, respectively, which had significant advantages over other tree-based regression models. Meanwhile, the model performance was improved by adding NO2 and PM2.5 features to the model estimations, indicating the necessity of synergistic observations of NO2, PM2.5, and O3. Finally, the seasonal distribution of O3 concentrations in the Shijiazhuang area was plotted, with the highest O3 concentrations in the summer, the lowest in the winter, and the O3 concentration is in the middle of spring and autumn.
Influence of Field Sampling Methods on Measuring Volatile Organic Compounds in a Swine Facility Using SUMMA Canisters
Authors: Li Xin , Sun Qinqin , Yu Lei , Wang Xiaoshuai , Feng Li , Wang Kaiying
Published: August 2024

Volatile organic compounds (VOCs) play a crucial role in emission control, being one of the most important sources of odor while also serving as significant precursors to secondary organic aerosols and ozone formation. Appropriate sampling methods are essential for accurately assessing the concentration and composition of VOCs within swine barns. In this study, the effects of both passive air sampling and active air sampling on VOCs were evaluated, and the influence of storage time on the VOC stability in sampling canisters for both methods was investigated. SUMMA canisters, which are electropolished and passivated with silanization, offer excellent corrosion protection and resistance to high pressure and temperature and were used in this study. The predominant component categories prevailing within the pig house were found to be oxygenated VOCs (OVOCs) and volatile sulfur compounds (VSCs), with ethanol emerging as the most abundant component of VOCs detected. Notably, the statistical analysis results revealed no significant differences between passive and active sampling regarding the impact of storage time on substance concentration. Changes in canister pressure also did not significantly affect substance stability. The results showed that the C2–C3 compounds remained relatively stable, especially within 3 days, with recoveries above 80% within 20 days. Methyl sulfide, dimethyl disulfide, and ethanol were more stable within the first week, but their recoveries significantly dropped by day 20, with methyl sulfide and dimethyl disulfide at 62.3% and 65.3%, respectively. This study contributes to the development of a foundation for selecting appropriate VOC sampling methods in swine facilities for conducting a rational analysis of VOC samples.
Fabrication of Patterned Magnetic Particles in Microchannels and Their Application in Micromixers
Authors: Li Tianhao , Yang Chen , Shao Zihao , Chen Ya , Zheng Jiahui , Yang Jun , Hu Ning
Published: August 2024

Due to the extremely low Reynolds number, the mixing of substances in laminar flow within microfluidic channels primarily relies on slow intermolecular diffusion, whereas various rapid reaction and detection requirements in lab-on-a-chip applications often necessitate the efficient mixing of fluids within short distances. This paper presents a magnetic pillar-shaped particle fabrication device capable of producing particles with planar shapes, which are then utilized to achieve the rapid mixing of multiple fluids within microchannels. During the particle fabrication process, a degassed PDMS chip provides self-priming capabilities, drawing in a UV-curable adhesive-containing magnetic powder and distributing it into distinct microwell structures. Subsequently, an external magnetic field is applied, and the chip is exposed to UV light, enabling the mass production of particles with specific magnetic properties through photo-curing. Without the need for external pumping, this chip-based device can fabricate hundreds of magnetic particles in less than 10 min. In contrast to most particle fabrication methods, the degassed PDMS approach enables self-priming and precise dispensing, allowing for precise control over particle shape and size. The fabricated dual-layer magnetic particles, featuring fan-shaped blades and disk-like structures, are placed within micromixing channels. By manipulating the magnetic field, the particles are driven into motion, altering the flow patterns to achieve fluid mixing. Under conditions where the Reynolds number in the chip ranges from 0.1 to 0.9, the mixing index for substances in aqueous solutions exceeds 0.9. In addition, experimental analyses of mixing efficiency for fluids with different viscosities, including 25 wt% and 50 wt% glycerol, reveal mixing indices exceeding 0.85, demonstrating the broad applicability of micromixers based on the rapid rotation of magnetic particles.
Synergistic Freeze-Resistant Strategy of Multi-Stage PCM Concrete Incorporated with Rice Husk Ash and Fly Ash
Authors: Hong Zhilong , Wang Sheliang , Ying Honghao , Lu Zhe , Liu Bo , Xu Jin
Published: August 2024

Damage to buildings and infrastructure caused by freeze–thaw cycles is a common problem in cold regions. To counteract this, multi-stage phase change material (PCM) aggregate concrete has gained attention for its potential in structural protection. PCM concrete is a type of intelligent concrete that regulates and controls the temperature by incorporating PCM. PCM aggregate can efficiently absorb and release significant amounts of heat within a defined temperature range. This study explored the feasibility of using agricultural waste rice husk ash (RHA) and industrial waste fly ash (FA) to produce PCM concrete. The combined use of RHA and FA with multi-stage PCM aggregate concrete allowed the two materials, pozzolanic materials and PCM, which have different approaches to improving the freeze resistance of concrete, to be effectively utilized together and synergistically enhance the durability and energy efficiency of buildings in cold regions. An experimental program was conducted to prepare PCM concrete by replacing cement with 5%, 10% and 15% RHA and 10%, 20% and 30% FA in different mixtures. The results show that when the replacement amounts of RHA and FA are both 10%, the compressive strength of the concrete can be effectively improved, while the thermal conductivity and thermal diffusivity are reduced. The incorporation of RHA and FA improved the thermal regulation of PCM concrete. Strength loss, relative dynamic elastic modulus (RDEM) loss and mass loss were all minimal with RHA at 15% and FA at 10% replacement.
Digital Twins in Construction: Architecture, Applications, Trends and Challenges
Authors: Yang Zhou , Tang Chao , Zhang Tongrui , Zhang Zhongjian , Doan Dat Tien
Published: August 2024

The construction field currently suffers from low productivity, a lack of expertise among practitioners, weak innovation, and lack of predictability. The digital twin, an advanced digital technology, empowers the construction sector to advance towards intelligent construction and digital transformation. It ultimately aims for highly accurate digital simulation to achieve comprehensive optimization of all phases of a construction project. Currently, the process of digital twin applications is facing challenges such as poor data quality, the inability to harmonize types that are difficult to integrate, and insufficient data security. Further research on the application of digital twins in the construction domain is still needed to accelerate the development of digital twins and promote their practical application. This paper analyzes the commonly used architectures for digital twins in the construction domain in the literature and summarizes the commonly used technologies to implement the architectures, including artificial intelligence, machine learning, data mining, cyber–physical systems, internet of things, virtual reality, augmented reality applications, and considers their advantages and limitations. The focus of this paper is centered on the application of digital twins in the entire lifecycle of a construction project, which includes the design, construction, operation, maintenance, demolition and restoration phases. Digital twins are mainly moving towards the integration of data and information, model automation, intelligent system control, and data security and privacy. Digital twins present data management and integration challenges, privacy and security protection, technical manpower development, and transformation needs. Future research should address these challenges by improving data quality, developing robust integration methodologies, and strengthening data security measures.
Cost-Effectiveness of Lung Cancer Screening with Low-Dose Computed Tomography: Comparing Hungarian Screening Protocols with the US NLST
Authors: Rajabi Tanya , Szilberhorn László , Győrbíró Dávid , Tatár Manna , Vokó Zoltán , Nagy Balázs
Published: August 2024

We aimed to directly compare the cost-effectiveness of Hungarian (following the NELSON trial) and NLST screening protocols, two trials influencing lung-cancer-screening implementation internationally. A decision-analytic model analyzing the cost-effectiveness of Hungarian protocols was manipulated to reflect the protocols of the NLST, while maintaining features specific to the Hungarian healthcare setting. In the Hungarian protocol, there are three possible outcomes to the initial round of screening, positive, negative, and indeterminate, indicating an uncertain degree of suspicion for lung cancer. This protocol differs from the NLST, in which the only possible screening outcomes are positive or negative, with no indeterminate option. The NLST pathway for smokers aged 55–74 resulted in a EUR 43 increase in the total average lifetime costs compared to the Hungarian screening pathway and resulted in a lifetime gain of 0.006 QALYs. The incremental costs and QALYs yielded an ICER of 7875 EUR/QALY. Our results demonstrate that assigning any suspicious LDCT screen as a positive result (NLST protocol) rather than indeterminate (Hungarian protocol) can reduce patient uncertainty and yield a slight QALY gain that is worth the additional use of resources according to Hungary’s willingness-to-pay threshold. A stratified analysis by age was also conducted, revealing decreasing cost-effectiveness when screening older cohorts. Our study provides insight into the cost-effectiveness, advantages, and disadvantages of various LDCT screening protocols for lung cancer and can assist other countries as they implement their screening programs.
Correlation between Periostin Expression and Pro-Angiogenic Factors in Non-Small-Cell Lung Carcinoma
Authors: Wasik Adrian , Podhorska-Okolow Marzenna , Dziegiel Piotr , Piotrowska Aleksandra , Kulus Michal Jerzy , Kmiecik Alicja , Ratajczak-Wielgomas Katarzyna
Published: August 2024

The role of periostin (POSTN) in remodeling the microenvironment surrounding solid tumors and its effect on the tumor cells in non-small-cell lung carcinoma (NSCLC) have not yet been fully understood. The aim of this study was to determine the relationship between POSTN expression (in tumor cells [NSCLC cells] and the tumor stroma) and pro-angiogenic factors (CD31, CD34, CD105, and VEGF-A) and microvascular density (MVD) in NSCLC. In addition, these associations were analyzed in individual histological subtypes of NSCLC (SCC, AC, and LCC) and their correlations with clinicopathological factors and prognosis were examined. Immunohistochemistry using tissue microarrays (TMAs) was used to assess the expression of POSTN (in tumor cells and cancer-associated fibroblasts [CAFs]) and the pro-angiogenic factors. A significant positive correlation was found between the expression of POSTN (in cancer cells/CAFs) and the expression of the analyzed pro-angiogenic factors (CD31, CD34, CD105, and VEGF-A) and MVD in the entire population of patients with NSCLC and individual histological subtypes (AC, SCC). In addition, this study found that POSTN expression (in tumor cells/CAFs) increased with tumor size (pT), histopathological grade (G), and lymph-node involvement (pN). In addition, a high expression of POSTN (in tumor cells and CAFs) was associated with shorter survival among patients with NSCLC. In conclusion, a high expression of POSTN (in cancer cells and CAFs) may be crucial for angiogenesis and NSCLC progression and can constitute an independent prognostic factor for NSCLC.
Emerging Roles of Circular RNA in Macrophage Activation and Inflammatory Lung Responses
Authors: Son Chang Jun , Carnino Jonathan M. , Lee Heedoo , Jin Yang
Published: August 2024

Circular RNA (circRNA) is a type of single-stranded RNA that forms a covalently closed continuous loop, unlike linear RNA. The expression of circRNAs in mammals is often conserved across species and shows tissue and cell specificity. Some circRNA serve as gene regulators. However, the biological function of most circRNAs is unclear. CircRNA does not have 5′ or 3′ ends. The unique structure of circRNAs provides them with a much longer half-life and more resistance to RNase R than linear RNAs. Inflammatory lung responses occur in the pathogenesis and recovery of many lung diseases. Macrophages form the first line of host defense/innate immune responses and initiate/mediate lung inflammation. For example, in bacterial pneumonia, upon pro-inflammatory activation, they release early response cytokines/chemokines that recruit neutrophils, macrophages, and lymphocytes to sites of infection and clear pathogens. The functional effects and mechanisms by which circRNAs exert physiological or pathological roles in macrophage activation and lung inflammation remain poorly understood. In this article, we will review the current understanding and progress of circRNA biogenesis, regulation, secretion, and degradation. Furthermore, we will review the current reports on the role of circRNAs in macrophage activation and polarization, as well as in the process of inflammatory lung responses.
The Multifunctional Role of KCNE2: From Cardiac Arrhythmia to Multisystem Disorders
Authors: Song Ming , Zhuge Yixin , Tu Yuqi , Liu Jie , Liu Wenjuan
Published: August 2024

The KCNE2 protein is encoded by the kcne2 gene and is a member of the KCNE protein family, also known as the MinK-related protein 1 (MiRP1). It is mostly present in the epicardium of the heart and gastric mucosa, and it is also found in the thyroid, pancreatic islets, liver and lung, among other locations, to a lesser extent. It is involved in numerous physiological processes because of its ubiquitous expression and partnering promiscuity, including the modulation of voltage-dependent potassium and calcium channels involved in cardiac action potential repolarization, and regulation of secretory processes in multiple epithelia, such as gastric acid secretion, thyroid hormone synthesis, generation and secretion of cerebrospinal fluid. Mutations in the KCNE2 gene or aberrant expression of the protein may play a critical role in cardiovascular, neurological, metabolic and multisystem disorders. This article provides an overview of the advancements made in understanding the physiological functions in organismal homeostasis and the pathophysiological consequences of KCNE2 in multisystem diseases.
Electrophoretic Deposition of Bioactive Glass Coatings for Bone Implant Applications: A Review
Authors: Drevet Richard , Fauré Joël , Benhayoune Hicham
Published: August 2024

This literature review deals with the electrophoretic deposition of bioactive glass coatings on metallic substrates to produce bone implants. Biocompatible metallic materials, such as titanium alloys or stainless steels, are commonly used to replace hard tissue functions because their mechanical properties are appropriate for load-bearing applications. However, metallic materials barely react in the body. They need a bioactive surface coating to trigger beneficial biological and chemical reactions in the physiological environment. Bioactive coatings aim to improve bone bonding, shorten the healing process after implantation, and extend the lifespan of the implant. Bioactive glasses, such as 45S5, 58S, S53P4, 13-93, or 70S30C, are amorphous materials made of a mixture of oxides that are accepted by the human body. They are used as coatings to improve the surface reactivity of metallic bone implants. Their high bioactivity in the physiological environment induces the formation of strong chemical bonding at the interface between the metallic implant and the surrounding bone tissue. Electrophoretic deposition is one of the most effective solutions to deposit uniform bioactive glass coatings at low temperatures. This article begins with a review of the different compositions of bioactive glasses described in the scientific literature for their ability to support hard tissue repair. The second part details the different stages of the bioactivity process occurring at the surface of bioactive glasses immersed in a physiological environment. Then, the mechanisms involved in the electrophoretic deposition of bioactive glass coatings on metallic bone implants are described. The last part of the article details the current developments in the process of improving the properties of bioactive glass coatings by adding biocompatible elements to the glassy structure.
Investigation and Comparison of Alternative Oxygen Barrier Coatings for Flexible PP Films as Food Packaging Material
Authors: Sharbafian Farshad , Tosic Katharina , Schmiedt Romana , Novak Martin , Krainz Michael , Rainer Bernhard , Apprich Silvia
Published: August 2024

One of the EU’s ambitious goals is to ensure all plastic packaging is reusable or recyclable by 2030. However, achieving higher recycling rates, particularly in flexible multilayer food packaging, is challenging due to the combination of diverse materials. This highlights the importance of designing for recyclability and exploring alternative barrier solutions. In this study, several types of coatings, such as ORMOCER® (Fraunhofer-ISC, Würzburg, Germany) Michem® Flex B3513 (Michelman International Belgium SRL, Aubange, Belgium), and PVOH (Kuraray Europe GmbH, Frankfurt am Main, Germany), are applied on different polypropylene substrates, including cast PP (CPP70), SiOx, and AlOx-coated PP films. The effect of double coating and optimized curing conditions of ORMOCER® on the oxygen permeability of CPP70 was also investigated. The results showed significant improvements in the barrier properties of PP/SiOx and OPP/AlOx films, and OTR values less than 0.1 cm3/m2·d·bar were achieved. It was also found that ORMOCER® and Michem® Flex B3513 could enhance the oxygen barrier property of CPP70 and the OTR value reduced by a factor of 88 and 551, respectively.
The Population of the Glacial Relict Betula nana Surviving Anthropogenic Pressure (the Case of Šepeta Peatland in Northeastern Lithuania)
Authors: Jukonienė Ilona , Bagušinskaitė Agnė , Kalvaitienė Monika , Ričkienė Aurika , Sinkevičienė Zofija
Published: August 2024

The main objective of the study was to evaluate the population characteristics of Betula nana under different anthropogenic influences. The study was conducted in the vicinity of the exploited Šepeta peatland (northeastern Lithuania). The population status of B. nana was determined by comparing the ramet density and morphology (height, branching, and leaf size), the age structure, the number of generative ramets, and their flowering characteristics in four study areas at different distances from the exploited peatlands and in different habitats. Around 20 environmental factors were included in the analysis, covering water levels, peat, and vegetation characteristics. Shading, drainage and increased amounts of nitrogen in the habitats are the main factors contributing to the differences and structure of B. nana cenopopulations. Although taller ramets with larger leaves are observed under the changed conditions as an adaptation to shading, the negative anthropogenic effects in the most affected habitats are reflected in a reduction in the number of flowering ramets, lower vegetative regeneration, and an increase in the number of dead twigs on mature ramets.
Reviewing the Horizon: The Future of Extended Reality and Artificial Intelligence in Neurorehabilitation for Brain Injury Recovery
Authors: Akbar Khalida , Passaro Anna , Di Gioia Mariacarla , Martini Elvira , Dragone Mirella , Zullo Antonio , Stasolla Fabrizio
Published: August 2024

People with disorders of consciousness, either as a consequence of an acquired brain injury or a traumatic brain injury, may pose serious challenges to medical and/or rehabilitative centers with an increased burden on caregivers and families. The objectives of this study were as follows: to explore the use of extended reality as a critical means of rehabilitative support in people with disorders of consciousness and brain injuries; to evaluate its impact on recovery processes; to assess the improvements in the participants’ quality of life, and to reduce the burden on families and caregivers by using extended reality and artificial-intelligence-based programs. A selective review of the newest empirical studies on the use of extended reality and artificial-intelligence-based interventions in patients with brain injuries and disorders of consciousness was conducted over the last decade. The potential for bias in this selective review is acknowledged. A conceptual framework was detailed. The data showed that extended reality and artificial-intelligence-based programs successfully enhanced the adaptive responding of the participants involved, and improved their quality of life. The burden on caregivers and families was reduced accordingly. Extended reality and artificial intelligence may be viewed as crucial means of recovery in people with disorders of consciousness and brain injuries.
Cost Estimation and Prediction for Residential Projects Based on Grey Relational Analysis–Lasso Regression–Backpropagation Neural Network
Authors: Chen Lijun , Wang Dejiang
Published: August 2024

In the early stages of residential project investment, accurately estimating the engineering costs of residential projects is crucial for cost control and management of the project. However, the current cost estimation of residential engineering in China is primarily carried out by cost personnel based on their own experience. This process is time-consuming and labour-intensive, and it involves subjective judgement, which can lead to significant estimation errors and fail to meet the rapidly developing market demands. Data collection for residential construction projects is challenging, with small sample sizes, numerous attributes, and complexity. This paper adopts a hybrid method combining a grey relational analysis, Lasso regression, and Backpropagation Neural Network (GAR-LASSO-BPNN). This method has significant advantages in handling high-dimensional small samples and multiple correlated variables. The grey relational analysis (GRA) is used to quantitatively identify cost-driving factors, and 14 highly correlated factors are selected as input variables. Then, regularization through Lasso regression (LASSO) is used to filter the final input variables, which are subsequently input into the Backpropagation Neural Network (BPNN) to establish the relationship between the unit cost of residential projects and 12 input variables. Compared to using LASSO and BPNN methods individually, the GAR-LASSO-BPNN hybrid prediction method performs better in terms of error evaluation metrics. The research findings can provide quantitative decision support for cost estimators in the early estimation stages of residential project investment decision-making.
An Approach for Maximizing Computation Bits in UAV-Assisted Wireless Powered Mobile Edge Computing Networks
Authors: Liu Zhenbo , Duan Yunge , Fu Shuang
Published: August 2024

With the development of the Internet of Things (IoT), IoT nodes with limited energy and computing capability are no longer able to address increasingly complex computational tasks. To address this issue, an Unmanned Aerial Vehicle (UAV)-assisted Wireless Power Transfer (WPT) Mobile Edge Computing (MEC) system is proposed in this study. By jointly optimizing variables such as energy harvesting time, user transmission power, user offloading time, CPU frequency, and UAV deployment location, the system aims to maximize the number of computation bits by the users. This optimization yields a challenging non-convex optimization problem. To address these issues, a two-stage alternating method based on the Lagrangian dual method and the Successive Convex Approximation (SCA) method is proposed to decompose the initial problem into two sub-problems. Firstly, the UAV position is fixed to obtain the optimal values of other variables, and then the UAV position is optimized based on the solved variables. Finally, this iterative process continues until the algorithm convergences, and the optimal solution for the given problem is obtained. The simulation results indicate that the proposed algorithm exhibits good convergence. Compared to other benchmark solutions, the proposed approach performs optimally in maximizing computation bits.
The Optimal Choice of the Encoder–Decoder Model Components for Image Captioning
Authors: Bartosiewicz Mateusz , Iwanowski Marcin
Published: August 2024

Image captioning aims at generating meaningful verbal descriptions of a digital image. This domain is rapidly growing due to the enormous increase in available computational resources. The most advanced methods are, however, resource-demanding. In our paper, we return to the encoder–decoder deep-learning model and investigate how replacing its components with newer equivalents improves overall effectiveness. The primary motivation of our study is to obtain the highest possible level of improvement of classic methods, which are applicable in less computational environments where most advanced models are too heavy to be efficiently applied. We investigate image feature extractors, recurrent neural networks, word embedding models, and word generation layers and discuss how each component influences the captioning model’s overall performance. Our experiments are performed on the MS COCO 2014 dataset. As a result of our research, replacing components improves the quality of generating image captions. The results will help design efficient models with optimal combinations of their components.