Search Results (86)

Soil co-contamination with cadmium (Cd) and zinc (Zn) poses serious threats to environmental safety and public health. This study investigates the enhancement effect and underlying mechanism of the biodegradable chelator Ethylenediamine-N,N′-disuccinic acid (EDDS) on phytoremediation of Cd-Zn contaminated soil using Sedum lineare. The results demonstrate that EDDS application (3.65 g·L⁻¹) effectively alleviated metal-induced phytotoxicity by enhancing chlorophyll synthesis, activating antioxidant enzymes (catalase and dismutase), regulating S-nitrosoglutathione reductase activity, and promoting leaf protein synthesis, thereby improving photosynthetic performance and cellular integrity. The combined treatment significantly increased the bioavailability of Cd and Zn in soil, promoted their transformation into exchangeable fraction, and resulted in removal rates of 30.8% and 28.9%, respectively. EDDS also modified the interaction patterns between heavy metals and essential nutrients, particularly the competitive relationships through selective chelation between Cd/Zn and Fe/Mn during plant uptake. Soil health was substantially improved, as evidenced by reduced electrical conductivity, enhanced cation exchange capacity, and enriched beneficial microbial communities including Sphingomonadaceae. Based on the observed ion antagonism during metal uptake and translocation, this study proposes a novel “Nutrient Regulation Assisted Remediation” strategy to optimize heavy metal accumulation and improve remediation efficiency through rhizosphere nutrient management. These findings confirm the EDDS–S. lineare system as an efficient and sustainable solution for remediation of Cd–Zn co-contaminated soils. Full article

For a no-wait flow shop with continuous-flow characteristics, this study simultaneously considers machine setup times and rated processing speed constraints, aiming to minimize the sum of the maximum completion time and the maximum tardiness. First, lower bounds for the maximum completion time, the maximum tardiness, and the total objective function are developed. Second, a mixed-integer programming (MIP) model is formulated for the problem, and nonlinear elements are subsequently linearized via time discretization. Due to the computational complexity of the problem, two algorithms are proposed: a heuristic algorithm with fixed machine links and greedy rules (HAFG) and a genetic algorithm based on altering machine combinations (GAAM) for solving large-scale instances. The Earliest Due Date (EDD) rule is used as baselines for algorithmic comparison. To better understand the behaviors of the two algorithms, we observe the two components of the objective function separately. The results show that, compared with the EDD rule and GAAM, the HAFG algorithm tends to focus more on optimizing the maximum completion time. The performance of both algorithms is evaluated using their relative deviations from the developed lower bounds and is compared against the EDD rule. Numerical experiments demonstrate that both HAFG and GAAM significantly outperform the EDD rule. In large-scale instances, the HAFG algorithm achieves a gap of about 4%, while GAAM reaches a gap of about 3%, which is very close to the lower bound. In contrast, the EDD rule shows a deviation of about 10%. Combined with a sensitivity analysis on the number of machines, the proposed framework provides meaningful managerial insights for continuous-flow production environments. Full article

The use of biodegradable chelating agents and fertilizer to improve phytoremediation is a cost-effective and environmental-friendly method for remediation of copper (Cu)- and cadmium (Cd)-polluted agricultural soil. A pot experiment was conducted to investigate the effects of phosphorus (P) fertilizer and the chelator ethylenediamine disuccinic acid (EDDS), both individually and in combination, on the phytoremediation efficiency of castor plants. The experiment included six treatments with three replicates, which were as follows: control (no P or EDDS), EDDS alone, P at 100 mg kg⁻¹, P at 300 mg kg⁻¹, P at 100 mg kg⁻¹ + EDDS, and P at 300 mg kg⁻¹ + EDDS. The results demonstrated that phosphorus significantly promoted the growth of castor plants. In the treatment in which 300 mg kg⁻¹ P₂O₅ and 5.0 mmol kg⁻¹ EDDS were added, the shoot dry weight and root dry weight increased by 42.0% and 67.6%, respectively, when compared to the treatment only applying EDDS, and this treatment significantly promoted the absorption of Cd by shoots of castor. In the absence of phosphorus application, EDDS significantly diminished the dry weight of castor roots by 27.3%. Nevertheless, it improved the concentrations of Cu in the shoots and roots of castor plants, which were 3.43 times and 3.27 times higher than those of the control, respectively. Furthermore, when combined with phosphorus fertilizers, EDDS further promoted the absorption of Cu and Cd in the shoots of castor, which significantly increased by 13.34 times and 0.47 times, respectively, with addition of 100 mg kg⁻¹ phosphorus and 5.0 mmol kg⁻¹ of EDDS compared with the control. Phosphorus and EDDS synergistically decreased the activity of POD enzymes in leaves and roots compared with those treated with only EDDS and alleviated the toxicity of EDDS and heavy metals to castor plants. These findings provide scientific evidence for the use of agronomic measures and chelators to optimize phytoremediation efficiency in Cu and Cd co-contaminated soils. Full article

The pressure arch effect limits the influence range of excavation on the surrounding rock, reduces the geological pressure on underground structures, and serves as an important indicator for evaluating the stability of underground engineering. By accounting for the energy transfer process in surrounding rock during the tunnel-induced pressure arch formation, this paper proposes a novel approach for determining the range of the pressure arch around tunnels—the energy density difference (EDD) method. Numerical analysis is conducted to evaluate the effects of tunnel span, internal friction angle, and lateral pressure coefficient on post-excavation energy density fields and pressure arch zones in tunnels. Comparative studies with three existing approaches confirm the EDD method’s efficacy in identifying the arch zones of tunnel-surrounding rock. Critically, the proposed approach addresses the controversy regarding the determination of the deviation degree of principal stress vectors and provides a physically meaningful interpretation of the formation and evolution mechanisms of pressure arches. Full article

Background: Previous studies have demonstrated the beneficial effects of Ligilactobacillus salivarius A3iob on honeybee (Apis mellifera) colonies’ health and honey production. The present work aimed to assess the genomic characteristics of the A3iob strain to understand its ability to improve bees’ health. Methods: The comparative genomic analysis was performed with the A3iob genome and the genomes of probiotic L. salivarius strains of human, porcine, and chicken origin, as well as bacteria isolated from the bees’ gut. The analysis included the examination of metabolic genes and functional genes related to adhesion, the production of bioactive compounds, the modulation of the host’s immune system, and antimicrobial substances. Genes associated with antimicrobial resistance and virulence were also analyzed. Results: In silico studies revealed that L. salivarius A3iob possesses genes for glycosyltransferases (GTs) from the families GT2 and GT4, like Bombella apis and Bombella intestinalis, and glycosylhydrolases (GH) from the families GH1, GH2, GH13, GH36, GH65, and GH177, similar to Apilactobacillus kunkeei, Enterococcus durans, and bifidobacteria isolated from the bee intestine. The A3iob strain also has a unique genetic profile with a high number of secretion system genes and adhesion genes, including the ones coding for the SecA2/Y2 system, the mucus-binding proteins MucBP1, MucBP2, and MucBP3, and a pilus cluster (pilA, SpaA, SpaB, and sorteaseA) that has only been described in five strains of the L. salivarius species and in the intestinal bee-derived strain E. durans EDD2, which could be involved in the successful colonization of the A3iob strain in the bee gastrointestinal tract. Additionally, L. salivarius A3iob showed the presence of exopolysaccharide biosynthesis clusters described in the probiotic L. salivarius UCC118. Genes related to oxidative stress response (thioredoxin and NrdH-redoxin systems) and the bacteriocin genes abp118A and abp118B were found in the A3iob genome. L. salivarius A3iob does not harbor virulence or antibiotic resistance genes. Conclusions: The genomic characterization of L. salivarius A3iob performed in this work provides some clues about the genetic mechanisms underlying its probiotic properties, paving the way for future research aimed at improving bees’ health and productivity in the face of environmental challenges. Full article

Congenital ichthyoses, now grouped under the acronym EDD (Epidermal Differentiation Disorders), include nonsyndromic forms (nEDD) that may be caused by loss-of-function mutations in the CDSN gene encoding corneodesmosin (CDSN-nEDD, formerly Peeling skin syndrome type 1). It is characterized by skin peeling, inflammation, itching and food allergies, while no specific therapy is currently available. High levels of KLK5, the serine protease that initiates the desquamation cascade, are found in the epidermis of CDSN-nEDD patients. Thus, we hypothesized that KLK5 inhibition would alleviate the symptoms of CDSN-nEDD and could serve as a new pharmacological target. A human epidermal equivalent (HEE) model for CDSN-nEDD was developed using shRNA-mediated CDSN knockdown. This model was characterized and used to assess the role of KLK5 knockdown on CDSN-nEDD. Also, Klk5^−/− mice were crossed with Cdsn^epi−/− mice, the murine model of CDSN-nEDD, to examine in vivo the effect(s) of Klk5 deletion in CDSN-nEDD. Both models recapitulated the CDSN-nEDD desquamating phenotype. Elimination of KLK5 aggravated the CDSN-nEDD phenotype. Epidermal proteolysis was surprisingly elevated, while severe ultrastructural (corneo)desmosomal alterations increased epidermal barrier permeability and stratum corneum detachment was manifested. Based on these results, we concluded that targeting epidermal proteolysis with KLK5 ablation cannot compensate for the loss of corneodesmosin and rescue over-desquamation of the CDSN-nEDD. Possibly, in the absence of KLK5, other proteases take over which increases the severity of over-desquamation in CDSN-nEDD. The translational outcome is that over-desquamation may not always be rescued by eliminating epidermal proteolysis, but fine protease modulation is more likely required. Full article

Generating realistic and contextually appropriate gestures is crucial for creating engaging embodied conversational agents. Although speech is the primary input for gesture generation, adding controls like gesture velocity, hand height, and emotion is essential for generating more natural, human-like gestures. However, current approaches to controllable gesture generation often utilize a limited number of control parameters and lack the ability to activate/deactivate them selectively. Therefore, in this work, we propose the Cont-Gest model, a Transformer-based gesture generation model that enables selective control activation through masked training and a control fusion strategy. Furthermore, to better support the development of such models, we propose a novel evaluation-driven development (EDD) workflow, which combines several iterative tasks: automatic control signal extraction, control specification, visual (subjective) feedback, and objective evaluation. This workflow enables continuous monitoring of model performance and facilitates iterative refinement through feedback-driven development cycles. For objective evaluation, we are using the validated Kinetic–Hellinger distance, an objective metric that correlates strongly with the human perception of gesture quality. We evaluated multiple model configurations and control dynamics strategies within the proposed workflow. Experimental results show that Feature-wise Linear Modulation (FiLM) conditioning, combined with single-mask training and voice activity scaling, achieves the best balance between gesture quality and adherence to control inputs. Full article

Quantifying future changes in extreme events and associated flooding is challenging yet fundamental for stormwater managers. Along the U.S. Atlantic Coast, Eastern North Carolina (ENC) is frequently exposed to catastrophic floods from extreme rainfall that is typically associated with tropical cyclones. This study presents a novel approach that uses rainfall data from five dynamically and statistically downscaled (DD and SD) global climate models under two scenarios to visualize a potential future extent of flooding in ENC. Here, we use DD data (at 36-km grid spacing) to compute future changes in precipitation intensity–duration–frequency (PIDF) curves at the end of the 21st century. These PIDF curves are further applied to observed rainfall from Hurricane Matthew—a landfalling storm that created widespread flooding across ENC in 2016—to project versions of “Matthew 2100” that reflect changes in extreme precipitation under those scenarios. Each Matthew-2100 rainfall distribution was then used in hydrologic models (HEC-HMS and HEC-RAS) to simulate “2100” discharges and flooding extents in the Neuse River Basin (4686 km²) in ENC. The results show that DD datasets better represented historical changes in extreme rainfall than SD datasets. The projected changes in ENC rainfall (up to 112%) exceed values published for the U.S. but do not exceed historical values. The peak discharges for Matthew-2100 could increase by 23–69%, with 0.4–3 m increases in water surface elevation and 8–57% increases in flooded area. The projected increases in flooding would threaten people, ecosystems, agriculture, infrastructure, and the economy throughout ENC. Full article

Background/Objectives: In rhegmatogenous retinal detachment (RRD), vitreous cortex remnants (VCRs) may contribute to the development and progression of proliferative vitreoretinopathy (PVR). This study aimed to evaluate potential toxicity and trauma secondary to VCRs visualization and removal during pars plana vitrectomy (PPV) for RRD. Methods: Prospective study on patients with primary RRD who underwent PPV. Imaging assessment included widefield OCT (WF-OCT), ultra-WF retinography and fundus autofluorescence (FAF). During PPV, a filtered and diluted triamcinolone acetonide (TA) solution (20 mg/mL) was used to evaluate the presence and extension of VCRs, removed using an extendible diamond-dusted sweeper (EDDS). After six months, retinal and retinal pigment epithelium toxicity and retinal trauma due to VCRs removal were investigated. Results: Retinal reattachment was achieved in 21/21 cases included in the study. No signs of retinal or RPE toxicity were detected and WF-OCT performed in the areas of VCRs removal revealed an intact inner retinal architecture in the majority of eyes, with minor and localized inner retinal indentations in 4 cases. Conclusions: VCRs visualization and removal using TA and EDDS appears to be safe, with no retinal toxicity and very limited and circumscribed mechanical trauma. This approach may contribute to reducing the risk of postoperative PVR. Full article

This paper explores how redesigned Education Doctorate (EdD) programs in educational leadership can serve as a lever for strengthening the use of research evidence (URE) in schools and districts. Drawing on the COM-B framework, we conceptualize a theory of action that links EdD program design to leaders’ capabilities, motivations, and behaviors in applying research to educational improvement. We identify key dimensions of leadership preparation that align with well-documented URE practices. Finally, we discuss how these insights can inform doctoral programs as well as in-service professional learning and suggest the need for additional empirical work on these relationships and a deeper understanding of how local contexts shape the effectiveness of leadership preparation in supporting research-informed decision-making. Full article

The population of the southeastern USA is exposed to frequent extreme summertime high heat and humidity and is thus vulnerable to the resulting human thermal stress. Regional dew point variability in the USA is relatively underexplored in the literature compared to extreme heat. Here, we analyze hourly summer dew point data from 34 cities in the region during the period 1973–2022 (n = 50) to identify annual values of extreme dew point hours (EDH) and extreme dew point days (EDD). Regionally, significant (p ≤ 0.05) positive trends for both EDH (r_s = 0.28, R² = 0.078, +1.53 EDH/year) and EDD (r_s = 0.30, R² = 0.086, +0.05 EDD/year) occurred, although not all stations had increased dew point temperatures. Rather, positive changes are most concentrated among stations located along the upper Piedmont of the southern Appalachian Mountains. Conversely, no significant (i.e., p < 0.05) differences in either aggregate mean values of EDH or EDD occurred when splitting the data into early (1973–1997) and late (1998–2022) periods. High summer values of EDH and EDD are associated with variability in the 500 hPa geopotential height flow over North America. In particular, anomalous high pressure over the Gulf of Alaska is associated with the highest frequencies of summer extreme dew points in the study area, and vice versa. This connection to slow-changing ocean–atmosphere variability could lead to enhanced predictability of periods of extreme high dew point conditions in the Southeast, with implications for human well-being. Full article

This paper considers the single-machine scheduling problem of total tardiness minimization. Due to its computational intractability, exact approaches such as dynamic programming algorithms and branch-and-bound algorithms struggle to produce optimal solutions for large-scale instances in a reasonable time. The advent of Deep Q-Networks (DQNs) within the reinforcement learning paradigm could be a viable approach to transcending these limitations, offering a robust and adaptive approach. This study introduces a novel approach utilizing DQNs to model the complexities of job scheduling for minimizing tardiness through an informed selection utilizing look-ahead mechanisms of actions within a defined state space. The framework incorporates seven distinct reward-shaping strategies, among which the Minimum Estimated Future Tardiness strategy notably enhances the DQN model’s performance. Specifically, it achieves an average improvement of 14.33% over Earliest Due Date (EDD), 11.90% over Shortest Processing Time (SPT), 17.65% over Least Slack First (LSF), and 8.86% over Apparent Tardiness Cost (ATC). Conversely, the Number of Delayed Jobs strategy secures an average improvement of 11.56% over EDD, 9.10% over SPT, 15.01% over LSF, and 5.99% over ATC, all while requiring minimal computational resources. The results of a computational study demonstrate DQN’s impressive performance compared to traditional heuristics. This underscores the capacity of advanced machine learning techniques to improve industrial scheduling processes, potentially leading to decent operational efficiency. Full article

Background: Early-phase clinical trials offer a unique opportunity for patients with cancer. These trials often mandate biopsies to collect tumor tissue for research purposes, requiring patients to undergo invasive procedures. Some trials mandate molecular prescreening, but the success of these analyses relies on the quality and quantity of the tested materials. Additionally, bioptic procedures may result in complications. Methods: We retrospectively examined the records of patients referred to the Early Drug Development (EDD) Unit of the European Institute of Oncology who underwent biopsies for research purposes between January 2014 and December 2022. Our objective was to assess the safety of biopsy procedures and adequacy of the samples for NGS testing. Results: In total, 355 out of 731 patients (48.6%) underwent protocol-mandated biopsies. The most frequent sites of biopsy were the liver, lymph nodes, skin, and breast. Histological diagnosis was achieved in 349 (98%) patients, and NGS testing was successfully conducted in 111/127 (88.4%) cases. Of the 16 unsuccessful NGS attempts, 9 were performed on liver tissue. Unsuccessful NGS testing was attributed to poor sample quality and/or quantity, and the success rate varied significantly based on the specific tests attempted. Complications occurred in a small proportion of patients (4.8%), and none were serious. Conclusions: The non-negligible failure rate of NGS testing highlights the crucial need for implementing specific guidelines and Standard Operating Procedures for samples intended for NGS. With the use of a risk-based biopsy framework to guide clinical decisions, procedure-related complications may be minimized. Full article

This study proposes a robust precast concrete (PC) production scheduling model for PC construction projects with schedule uncertainty by adopting a proactive scheduling approach. The proposed model consists of a PC production simulation module that simulates and evaluates the total tardiness of the schedule at a certain confidence level with contractor schedule uncertainty and a GA-based production schedule optimization module that finds an optimal schedule through iterative schedule generation and evaluation using a PC production simulation module. The experimental study shows that the proposed model can find the best schedule with 303.8 h of tardiness at a 100% confidence level, followed by NEHedd 324.7 h, basic GA 328.5 h, and EDD 335.8 h. The results of this study will help PC production schedulers to perform robustly despite contractors’ schedule changes and will thus contribute to the successful completion of PC construction projects. Full article

Corrosion of metallic equipment is a critical issue across various industries, necessitating the development of advanced protective strategies. This study utilized dispersion-corrected density functional theory (DFT) with Becke–Johnson D3(BJ) to examine the atomic-level adsorption of quinoxalinones on Fe(110) surfaces, focusing on optimizing substitution strategies to enhance corrosion inhibition. Three quinoxalinones, quinoxalin-2(1H)-one (QNO), 3-methylquinoxalin-2(1H)-one (QNOM), and 3,7-dimethylquinoxalin-2(1H)-one (QNO2M), were investigated in various configurations and protonation states. Protonated quinoxalinones demonstrated a stronger surface affinity, primarily interacting through oxygen atoms and conjugated systems, with greater energetic stability compared to neutral molecules, driven by enhanced electrostatic interactions and charge transfer mechanisms. The parallel adsorption configuration was more stable than the perpendicular mode, which in some adsorption systems did not form bonds with the iron surface. Notably, the presence of methyl substitutions did not significantly enhance adsorption strength; QNO exhibited higher energetic stability due to reduced steric interference, which maintained its planarity. Projected density of states (PDOS), electron density difference (EDD), and electron localization function (ELF) analyses confirmed the importance of charge transfer between quinoxalinone active sites and the 3d orbitals of iron in stabilizing the adsorption of molecules. These findings underscore the importance of judicious quinoxalinone functionalization to preserve their efficacy as corrosion inhibitors. Full article