Urban form plays a critical role in enhancing urban climate resilience amidst the challenges of escalating global climate change and recurrent high-temperature heatwaves. Therefore, it is crucial to study the correlation between urban spatial form factors and land surface temperature (LST). This study utilized Landsat 8 remote sensing data to estimate LST. Random forest nonlinear analysis was employed to investigate the interaction between the urban heat island (UHI) and six urban morphological factors: building density (BD), floor area ratio (FAR), building height (BH), fractional vegetation coverage (FVC), sky view factor (SVF), and impervious surface fraction (ISF), within the framework of local climate zones (LCZs). Key findings revealed that Xi’an exhibited a significant urban heat island effect, with over 10% of the study area experiencing temperatures exceeding 40 °C. Notably, the average LST of building-class LCZs (1-6) was 3.5 °C higher than that of land cover-class LCZs (A-C). Specifically, compact LCZs (1-3) had an average LST 3.02 °C higher than open LCZs (4-6). FVC contributed the most to the variation in LST, while FAR contributed the least. ISF and BD were found to have a positive impact on LST, while FVC and BH had a negative influence. Moreover, SVF was observed to positively influence LST in the compact classes (LCZ2-3) and open low-rise class (LCZ6). In the open mid-rise class (LCZ5), SVF and LST showed a U-shaped relationship. There is an inverted U-shaped relationship between FAR and LST, with the inflection point occurring at 1.5. The results of nonlinear analysis were beneficial in illustrating the complex relationships between LST and its driving factors. The study’s results highlight the effectiveness of utilizing LCZ as a detailed approach to explore the relationship between urban morphology and urban heat islands. Recommendations for enhancing urban climate resilience include strategies such as increasing vegetation coverage, regulating building heights, organizing buildings in compact LCZs in an “L” or “I” shape, and adopting an “O” or “C” configuration for buildings in open LCZs to aid planners in developing sustainable urban environments. Full article

Results from the phase III Keynote-024 clinical trial established pembrolizumab monotherapy as the first-line standard of care for patients with metastatic NSCLC who have PD-L1 expression ≥ 50%, EGFR, and ALK wild-type tumors. However, given the differences between patients treated in routine clinical practice and those treated in a clinical trial, real-world data are needed to confirm the treatment benefit in standard practice. Given the lack of data on large cohorts of patients with long follow-ups, we designed an observational retrospective study of patients with metastatic NSCLC who were treated with pembrolizumab, starting from its reimbursement eligibility until December 2020. The primary endpoints were PFS and OS, determined using the Kaplan–Meier method. Response and safety were also evaluated. We followed 880 patients (median follow-up: 35.1 months) until February 2022. Median PFS and OS were 8.6 months (95% CI: 7.6–10.0) and 25.5 months (95% CI: 21.8–31.6), respectively. We also found that ECOG PS, PD-L1 expression, and habitual smoking were prognostic factors for PFS, while age, sex, ECOG PS, habitual smoking and histology had an impact on OS. Multivariable analysis confirms the prognostic role of PD-L1 for PFS and of ECOG for both PFS and OS. 39.9% of patients reported an adverse event, but only 6.3% of patients discontinued therapy due to toxicity. Our results suggest a long-term benefit of pembrolizumab in the first-line setting, as well as a safety profile consistent with the results of Keynote-024. Many collected variables appear to influence clinical outcome, but results from these exploratory unadjusted analyses should be interpreted with caution. Full article

The antimicrobial function of citral, one of the main compounds of the essential oils (EO) of the Citrus genus, and widely used by the food industry toward spoilage yeast, was previously proven. In this study, the possible mode of action of citral against yeast cells was evaluated by using a global deletome approach. Firstly, the suitability of Saccharomyces cerevisiae Σ1278b to serve as model yeast was assessed by determining its sensitivity to citral (MIC = 0.5 μL/mL). Subsequently, the complete library of Σ1278b haploid mutants deleted in 4019 non-essential genes was screened to identify potential molecular targets of citral. Finally, the deleted genes in the 590 mutants showing increased citral resistance was analyzed with an in-silico approach (Gene Ontology). The significantly enriched GO Terms were “cytoplasm”, “vacuole”, and “mitochondrion” (cellular components); “catalytic activity” (molecular function); “pseudohyphal growth” (biological process). For molecular function, resistant mutants were grouped into thiosulfate sulfur transferase activity, transferase activity, and oxidoreductase activity; for cellular components, resistant mutants were grouped as: cytoplasm, intracellular organelle, membrane-bounded organelle, mitochondrion, organelle membrane, and vacuole; and finally, with regard to biological process, deleted genes were grouped as: pseudohyphal growth, mitochondrion organization, lipid metabolic process, DNA recombination and repair, and proteolysis. Interestingly, many identified genes were associated with the cellular response to oxidative stress and ROS scavenging. These findings have important implications for the development of citral-based antimicrobials and the elucidation of its mechanism of action. Full article

The aim of this paper is to examine some American-style financial instruments that lead to two-sided optimal hitting problems. We pay particular attention to derivatives that are similar to strangle options but have a quadratic payoff function. We consider these derivatives in light of much more general payoff structures under certain conditions which guarantee that the optimal strategy is an exit from a strip. Closed-form formulas for the optimal boundaries and the fair price are derived when the contract has no maturity constraints. We obtain the form of the optimal boundaries under the finite maturity horizon and approximate them by maximizing the financial utility of the derivative holder. The Crank–Nicolson finite difference method is applied to the pricing problem. The importance of these novel financial instruments is supported by several features that are very useful for financial practice. They combine the characteristics of the power options and the ordinary American straddles. Quadratic strangles are suitable for investors who need to hedge strongly, far from the strike positions. In contrast, the near-the-money positions offer a relatively lower payoff than the ordinary straddles. Note that the usual options pay exactly the overprice; no more, no less. In addition, the quadratic strangles allow investors to hedge the positions below and above the strike together. This is very useful in periods of high volatility when large market movements are expected but their direction is unknown. Full article

The expansion of forested areas through afforestation and reforestation is widely recognized as a highly effective natural solution for mitigating climate change. Accurately assessing the potential carbon uptake capacity of newly afforested areas requires modelling tools to estimate biomass stocks, including site index curves and biomass models. Given the unique conditions in terms of tree size, uniform spacing, and tree allometries observed in young afforestations compared to natural stands, specific tools are necessary. In Spain, over 800,000 ha has been afforested with native forest species since 1992, but specific modelling tools for these plantations are lacking. Using data from 370 stem analyses collected across an extensive network of plots in young afforestations, we developed dynamic height growth and site index models for the main native species (five pines and five oaks) commonly used in afforestation in Spain. We compared various nonlinear models, such as ADA (algebraic difference approach) and GADA (generalized algebraic difference approach) expansions. The developed site index models were then used to predict the total biomass stored in the afforestation. Our results underscore the necessity for specific site index models tailored to afforestations, as well as the potential of the established site index in predicting biomass and carbon fixation capacity in these young forests. Full article

Remote sensing image change detection (CD) is an important means in remote sensing data analysis tasks, which can help us understand the surface changes in high-resolution (HR) remote sensing images. Traditional pixel-based and object-based methods are only suitable for low- and medium-resolution images, and are still challenging for complex texture features and detailed image detail processing in HR images. At present, the method based on deep learning has problems such as inconsistent fusion and difficult model training in the combination of the difference feature information of the deep and shallow layers and the attention mechanism, which leads to errors in the distinction between the changing region and the invariant region, edge detection and small target detection. In order to solve the above problems of inconsistent fusions of feature information aggregation and attention mechanisms, and indistinguishable change areas, we propose a multi-scale feature fusion Siamese network based on attention mechanism (ABMFNet). To tackle the issues of inconsistent fusion and alignment difficulties when integrating multi-scale fusion and attention mechanisms, we introduce the attention-based multi-scale feature fusion module (AMFFM). This module not only addresses insufficient feature fusion and connection between different-scale feature layers, but also enables the model to automatically learn and prioritize important features or regions in the image. Additionally, we design the cross-scale fusion module (CFM) and the difference feature enhancement pyramid structure (DEFPN) to assist the AMFFM module in integrating differential information effectively. These modules bridge the spatial disparity between low-level and high-level features, ensuring efficient connection and fusion of spatial difference information. Furthermore, we enhance the representation and inference speed of the feature pyramid by incorporating a feature enhancement module (FEM) into DEFPN. Finally, the BICD dataset proposed by the laboratory and public datasets LEVIR-CD and BCDD are compared and tested. We use F1 score and MIoU values as evaluation metrics. For AMBMFNet, the F1 scores on the three datasets are 77.69%, 81.57%, and 77.91%, respectively, while the MIoU values are 84.65%, 85.84%, and 84.54%, respectively. The experimental results show that ABMFNet has better effectiveness and robustness. Full article

In this work, we propose a new technique involving the modification of commercial screen-printed carbon electrodes with electrochemically reduced graphene oxide to serve as the starting point of a future electrochemical biosensor for the detection of two osteogenic biomarkers: alkaline phosphatase (ALP) and Runt-related transcription factor 2 (RUNX2). The electrodes were characterized after each modification by cyclic voltammetry and electrochemical impedance spectroscopy, showing the appropriate electrochemical characteristics for each modification type. The results obtained from scanning electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, and contact angle measurements are well correlated with each other, demonstrating the successful modification of the electrodes with graphene oxide and its subsequent reduction. The bioreceptors were immobilized on the electrodes by physical adsorption, which was confirmed by electrochemical methods, structural characterization, and contact angle measurements. Finally, the functionalized electrodes were incubated with the specific target analytes and the detection relied on monitoring the electrochemical changes occurring after the hybridization process. Our results indicated that the pilot platform has the ability to detect the two biomarkers up to 1 nM, with increased sensitivity observed for RUNX2, suggesting that after further optimizations, it has a high potential to be employed as a future biosensor. Full article

Studying drug-target interactions (DTIs) is the foundational and crucial phase in drug discovery. Biochemical experiments, while being the most reliable method for determining drug-target affinity (DTA), are time-consuming and costly, making it challenging to meet the current demands for swift and efficient drug development. Consequently, computational DTA prediction methods have emerged as indispensable tools for this research. In this article, we propose a novel deep learning algorithm named GRA-DTA, for DTA prediction. Specifically, we introduce Bidirectional Gated Recurrent Unit (BiGRU) combined with a soft attention mechanism to learn target representations. We employ Graph Sample and Aggregate (GraphSAGE) to learn drug representation, especially to distinguish the different features of drug and target representations and their dimensional contributions. We merge drug and target representations by an attention neural network (ANN) to learn drug-target pair representations, which are fed into fully connected layers to yield predictive DTA. The experimental results showed that GRA-DTA achieved mean squared error of 0.142 and 0.225 and concordance index reached 0.897 and 0.890 on the benchmark datasets KIBA and Davis, respectively, surpassing the most state-of-the-art DTA prediction algorithms. Full article

This research presents a novel approach by applying convolutional neural networks (CNNs) to enhance optical camera communication (OCC) signal detection under challenging indoor lighting conditions. The study utilizes a smartphone app to capture images of an LED lamp that emits 25 unique optical codes at distances of up to four meters. The developed CNN model demonstrates superior accuracy and outperforms traditional methodologies, which often struggle under variable illumination. This advancement provides a robust solution for reliable OCC detection where previous methods underperform, particularly in the tourism industry, where it can be used to create a virtual museum on the Unity platform. This innovation showcases the potential of integrating the application with a virtual environment to enhance tourist experiences. It also establishes a comprehensive visible light positioning (VLP) system, marking a significant advance in using CNN for OCC technology in various lighting conditions. The findings underscore the effectiveness of CNNs in overcoming ambient lighting challenges, paving the way for new applications in museums and similar environments and laying the foundation for future OCC system improvements. Full article

Aberrant expression of the heat shock proteins and factors was revealed to be closely associated with male reproduction. Heat shock factor 2 (HSF2) is a transcription factor that is involved in the regulation of diverse developmental pathways. However, the role and the corresponding molecular mechanism of HSF2 in male cattle-yak sterility are still poorly understood. Therefore, the aim of this study was to obtain the sequence and the biological information of the cattle-yak HSF2 gene and to investigate the spatiotemporal expression profiles of the locus during the development of cattle-yak testes. Additionally, the differential expression was analyzed between the cattle-yak and the yak, and the methylation of corresponding promoter regions was compared. Our results showed an additional 54 bp fragment and a missense mutation (lysine to glutamic acid) were presented in the cattle-yak HSF2 gene, which correlated with enriched expression in testicular tissue. In addition, the expression of the HSF2 gene showed dynamic changes during the growth of the testes, reaching a peak in adulthood. The IHC indicated that HSF2 protein was primarily located in spermatocytes (PS), spermatogonia (SP), and Sertoli cells (SC) in cattle-yak testes, compared with the corresponding cells of cattle and the yak. Furthermore, bisulfite-sequencing PCR (BSP) revealed that the methylated CpG sites in the promoter region of the cattle-yak HSF2 were more numerous than in the yak counterpart, which suggests hypermethylation of this region in the cattle-yak. Taken together, the low expression abundance and hypermethylation of HSF2 may underpin the obstruction of spermatogenesis, which leads to male cattle-yak infertility. Our study provided a basic guideline for the HSF2 gene in male reproduction and a new insight into the mechanisms of male cattle-yak sterility. Full article

We studied the impact of major floods occurring in Turkey between 2005 and 2020 on lending and the allocation of loans between sectors that differ in their CO₂ emissions. Our evidence shows that the floods are not significant determinants of lending or the allocation of loans between sectors, even though CO₂ emissions contribute to the reallocation of loans from the more polluting to the less polluting sectors. Indeed, risks and returns of the sector remain the main determinants of lending and of the allocation of loans among sectors. The results are robust to alternative estimation methods and specifications of the econometric models. Since in the period of investigation no environmental regulations were implemented in Turkey, and the Paris Agreement was ratified only at end-2021, the evidence suggests that more stringent regulations and green policies are required to accelerate the green transition in Turkey. Full article

A recent author’s fractal fluid-dynamic dispersion theory in porous media has focused on the derivation of the associated nonergodic (or effective) macrodispersion coefficients by a 3-D stochastic Lagrangian approach. As shown by the present study, the Fickian (i.e., the asymptotic constant) component of a properly normalized version of these coefficients exhibits a clearly detectable minimum in correspondence with the same fractal dimension (d ≅ 1.7) that seems to characterize the diffusion-limited aggregation state of cells in advanced stages of cancerous lesion progression. That circumstance suggests that such a critical fractal dimension, which is also reminiscent of the colloidal state of solutions (and may therefore identify the microscale architecture of both living and non-living two-phase systems in state transition conditions) may actually represent a sort of universal nature imprint. Additionally, it suggests that the closed-form analytical solution that was provided for the effective macrodispersion coefficients in fractal porous media may be a reliable candidate as a physically-based descriptor of blood perfusion dynamics in healthy as well as cancerous tissues. In order to evaluate the biological meaningfulness of this specific fluid-dynamic parameter, a preliminary validation is performed by comparison with the results of imaging-based clinical surveys. Moreover, a multifractal extension of the theory is proposed and discussed in view of a perspective interpretative diagnostic utilization. Full article

Background: Despite the ongoing trend of increasing donor ages in liver transplantation (LT) setting, a notable gap persists in the availability of comprehensive guidelines for the utilization of organs from elderly donors. This study aimed to evaluate the viability of livers grafts from donors aged ≥85 years and report the post-LT outcomes compared with those from “ideal” donors under 40 years old. Methods: Conducted retrospectively at a single center from 2005 to 2023, this study compared outcomes of LTs from donors aged ≥85 y/o and ≤40 y/o, with the propensity score matching to the recipient’s gender, age, BMI, MELD score, redo-LT, LT indication, and cause of donor death. Results: A total of 76 patients received grafts from donors ≥85 y/o and were compared to 349 liver grafts from donors ≤40 y/o. Prior to PSM, the 5-year overall survival was 63% for the elderly group and 77% for the young group (p = 0.002). After PSM, the 5-year overall survival was 63% and 73% (p = 0.1). A nomogram, developed at the time of graft acceptance and including HCC features, predicted 10-year survival after LT using a graft from a donor aged ≥85. Conclusions: In the context of organ scarcity, elderly donors emerge as a partial solution. Nonetheless, without proper selection, LT using very elderly donors yields inferior long-term outcomes compared to transplantation from very young donors ≤40 y/o. The resulting nomogram based on pre-transplant criteria allows for the optimization of elderly donor/recipient matching to achieve satisfactory long-term results, in addition to traditional matching methods. Full article

Congenital vascular malformations (CVMs) are the result of an aberrant development during embryogenesis. Although these lesions are present at birth, they are not always visible yet. Once symptomatic, patients suffer from pain, bleeding, ulcers, infections or lymphatic leakage, depending on the subtype of vessels involved. Treatment includes conservative management, surgery, sclerotherapy, embolization and pharmacological therapy. The clinical presentation varies widely and treatment can be challenging due to the rarity of the disease and potential difficulties of treatment. This review gives an overview of the historical developments in diagnosis and classification and exposes the key elements of innovations in the past decades on the identification of genetic mutations and personalized treatment. These advances in the field and a multidisciplinary approach are highly valuable in the optimization of clinical care aimed at both curing or stabilizing the CVM and pursuing physical and psychosocial wellbeing. Full article

The relevance of assessing the gingival phenotype prior to the initiation of periodontal, orthodontic, or prosthetic therapy has been clearly demonstrated. However, publications on this subject are either old or concerned with the means of assessing the gingival phenotype or the main factors likely to modify it. The main objective of this systematic review of the literature was therefore to investigate the prevalence of different gingival phenotypes in adults in good general health and with a healthy periodontium. A systematic review of the literature was performed following the guidelines of PRISMA recommendations using an electronic search strategy on four databases (PubMed, Scopus, Cochrane Library, and Embase) complemented by a manual search. Three independent authors were involved in study selection, data extraction, and bias assessment. Results: Of 807 articles, 17 of them, published between 2012 and 2023, involving 3277 subjects from 11 countries and 9766 dental sites, fulfilled the inclusion criteria. The prevalence of the gingival phenotype could not be determined at the level of an individual or a dental arch because all the publications assessed this phenotype only at the level of certain dental sectors, and were not chosen at random. The maxillary central incisors and maxillary or mandibular first molar sectors were associated with a high and thick gingival phenotype, independently of the dental morphology, gender, and age of adult subjects. Furthermore, in these regions, this gingival phenotype tended to be associated with a thick vestibular bone table. In contrast, maxillary and mandibular incisors and premolars more often had a thin gingival phenotype. For other teeth, the results were less conclusive. It is important not to rely solely on the overall appearance of the dentition but to independently assess the thickness and height of the gingiva at each dental site requiring intervention. Finally, this study highlights a key point, namely the need for further longitudinal studies to determine the prevalence in healthy adults. For practicality and feasibility reasons, these studies should be designed according to therapeutic needs, dental sector by dental sector, and within homogeneous source populations. PROSPERO registration: CRD 42023392602. Full article

The article describes the results of an investigation to determine the values of radiation intensities emitted by O-, Cl-, Br-, and I-containing liquid spray targets in absolute units in the wavelength range 10–20 nm when excited by pulsed laser radiation. The conversion coefficients of laser radiation into the EUV radiation are given for some wavelengths. The authors’ specially designed pulse extrusion liquid supply system was used to form the liquid spray targets. An Nd:YAG laser with λ = 1064 nm, τ = 8.4 ns, and Е_pulse = 0.8 J was used to excite the targets. Spectral measurements were made using a grazing incidence grating spectrometer–monochromator. The absolute intensities of a number of emission lines were also measured using a Bragg spectrometer based on a Mo/Be multilayer X-ray mirror, calibrated by both sensitivity and wavelength. The high values of absolute intensities of the liquid targets in the extreme ultraviolet wavelength range were demonstrated. Full article

Boron supplementation may improve the musculoskeletal health of pullets before entering the lay phase. This study aimed to evaluate the effects of different boron amounts on the performance, muscle deposition, tibia cross-sectional area (CSA) and mineral density (BMD), ash percent, breaking strength, and bone mineralization (bone-specific alkaline phosphatase [BALP] and pro-collagen type 1 n-terminal propeptide [P1NP]) of a white-feathered strain of pullets. A total of 528 Hy-Line W-36 pullets were distributed across 24 pens and fed basal diets containing varying amounts of boron (C: 0 mg/kg; L: 50 mg/kg; M: 100 mg/kg; H: 150 mg/kg) for 17 weeks. Performance parameters (body weight, average daily weight gain/bird, and average daily feed intake/bird) were measured at weeks 4, 7, 10, 13, and 16, while all other measures were taken at 11 and 17 weeks of age. Performance was not impacted by boron supplementation. Pectoralis major weights were higher in H pullets at 11 weeks of age, and we also observed higher pectoralis major, minor, and leg muscle weights in H pullets at 17 weeks of age. Pullets fed the H diet had larger cortical CSA than the other treatment groups at 11 weeks of age. At 17 weeks of age, both the H and M groups had larger cortical CSA than the L and C groups, but the M group had slightly smaller cortical CSA. Pullets fed the H diet had higher BMD values than the other treatment groups at 11 weeks of age. At 17 weeks of age, pullets fed the H diet had the highest total BMD values compared to the other treatment groups, and cortical BMD increased with increasing boron inclusion. Pullets fed the H diet had the highest tibia ash percentages and concentrations of BALP and P1NP. Pullets fed the M and H diets had greater failure load and maximum bending moment than pullets fed the L or C diet at 11 weeks of age, with H pullets having greater stiffness values than other groups. At 17 weeks of age, pullets fed the H diet had greater failure load and maximum bending moment compared to all other treatment groups. Our results suggest that providing boron within the diet at 150 mg/kg can improve the musculoskeletal characteristics of Hy-Line W-36 pullets up to 17 weeks of age, without impacting performance parameters. Full article

This study analysed the effect of substituting different percentages of natural aggregate with recycled aggregate from concrete crushing, using a coarse fraction as well as a fine fraction. Natural and recycled materials were classified in order to analyse the mechanical performance and impermeability of these eco-concretes in the fresh state as well as in the hardened state. A statistical analysis also determined whether the performance loss was significant from a statistical point of view, finding strength decreases of less than 13% in compressive strength and losses of less than 20% in flexural strength. An increasing trend was found in permeability as the percentage of recycled aggregate in the mix increased. Full article

Various modifications of standard glass fiber filtration media using electrospun PA66 nanofibers are described. PA66 were selected because they were readily available from commercial sources. Other polymers, such as PP, PET and PBT, could also be used. The first set of samples was prepared by mixing the nanofibers at two, three and five weight percent with glass fibers, and the second by laying the same proportion of the nanofibers directly onto the downstream side of the substrate. The aim of these modifications was to improve the three most basic functionalities of filter media, the separation efficiency, the differential pressure (ΔP) and the dirt holding capacity (DHC). The modified media samples were evaluated with the standard textile characterization techniques and filtration performance evaluation procedures. The results showed differences in the several tens of percentage points achieved with the two modification methods. Moreover, additional differences in performance were observed depending on the percentage of nanofibers admixed to the substrate. These differences were most apparent in the filtration efficiency and the DHC, both by several percentage points, with no apparent effect on the ∆P. The results strongly suggest that the preparation of new filter media by incorporating nanofibers directly into the matrix can result in significant improvements in filtration performance characteristics. Full article

This is a cross-sectional serosurveillance study for RSV. Between June and September of 2021, a total of 150 sera were collected from 30 individuals in each age group (<5, 5–18, 19–49, 50–64, and ≥65 years). Seroprevalence was estimated using enzyme-linked immunosorbent assays targeting two stabilized prefusion F (preF; DS-Cav1 and SC-TM) and G proteins. The overall seroprevalence was low in young children and older adults, despite them having a higher risk of severe RSV infection. There was a remarkable difference in age-stratified seroprevalence rates between anti-preF and anti-G protein antibodies. Given the high disease burden and low seroprevalence in both infants and old adults, RSV vaccination would be crucial for pregnant women and people aged over 60 years. Full article

The objective of this study is to develop a remediation technology for composited heavy metal-contaminated soil. Biochars (BC300, BC400, and BC500) derived from corn were combined with potassium dihydrogen phosphate (KH₂PO₄) to immobilize and remove heavy metal ions, including mercury (Hg²⁺), cadmium (Cd²⁺), and lead (Pb²⁺). The adsorption kinetics of metal ions in aqueous solutions with different concentrations was tested, and the fitting effects of the two models were compared. The findings demonstrate that the joint application of biochar and KH₂PO₄ could markedly enhance the immobilization efficacy of Pb²⁺, whereas the utilization of KH₂PO₄ on its own exhibited a more pronounced immobilization impact on Cd²⁺. Furthermore, the present study underscores the shortcomings of various remediation techniques that must be taken into account when addressing heavy metal-contaminated soils. It also emphasizes the value of comprehensive remediation techniques that integrate multiple remediation agents. This study offers a novel approach and methodology for addressing the intricate and evolving challenges posed by heavy metal contamination in soil. Its practical value and potential for application are significant. Full article

Positive and unlabeled learning (PU learning) is a significant binary classification task in machine learning; it focuses on training accurate classifiers using positive data and unlabeled data. Most of the works in this area are based on a two-step strategy: the first step is to identify reliable negative examples from unlabeled examples, and the second step is to construct the classifiers based on the positive examples and the identified reliable negative examples using supervised learning methods. However, these methods always underutilize the remaining unlabeled data, which limits the performance of PU learning. Furthermore, many methods require the iterative solution of the formulated quadratic programming problems to obtain the final classifier, resulting in a large computational cost. In this paper, we propose a new method called the absolute value inequality support vector machine, which applies the concept of eccentricity to select reliable negative examples from unlabeled data and then constructs a classifier based on the positive examples, the selected negative examples, and the remaining unlabeled data. In addition, we apply a hyperparameter optimization technique to automatically search and select the optimal parameter values in the proposed algorithm. Numerical experimental results on ten real-world datasets demonstrate that our method is better than the other three benchmark algorithms. Full article