Search Results (21,583)

This study investigated the impacts of land-use history and an episodic flood event on the soil quality of a riverine floodplain ecosystem, providing long-term and short-term disturbance perspectives. The study took place in the Saint Michael’s College Natural Area, which has over a hundred-year history of land-use change. Based on aerial orthoimagery, three zones (a recently abandoned farm field, a new-growth forest, and an old-growth forest) were selected that reflected different land-use histories. Two plots were selected per zone and pooled soil samples were collected from each before and after a major flooding event. Surface soil quality before flooding was often similar among the new- and old-growth forested areas (1.4 mg-P/g-soil, 6.8% soil organic matter (SOM), 0.79 humification index (HIX), and 13% Peak T) but differed from that found in the recently abandoned farm field, which had higher phosphorus levels (1.6 mg-P/g-soil), lower SOM content (3.9%), more microbial-like SOM (0.65 HIX and 17% Peak T), and drier soils. Flooding caused SOM to better resemble that of a forest rather than an agricultural field, and it lowered phosphorus levels. The results of our study suggest that episodic flooding events could help accelerate the restoration of soil organic matter conditions. Full article

The construction industry is a cornerstone of New Zealand (NZ)’s economic growth, yet strategic infrastructure planning is constrained by fragmented and inconsistent pipeline data. Despite the increasing availability of construction pipeline datasets in NZ, their limited clarity, interoperability, and standardisation impede effective forecasting, policy development, and investment alignment. These challenges are compounded by disparate data structures, inconsistent reporting formats, and semantic discrepancies across sources, undermining cross-agency coordination and long-term infrastructure governance. To address this issue, the study begins by assessing the quality of four prominent pipeline datasets using Wang and Strong’s multidimensional data quality framework. This evaluation provides a necessary foundation for identifying the structural and semantic barriers that limit data integration and informed decision-making. The analysis examines four dimensions of data quality: accessibility, intrinsic quality, contextual relevance, and representational clarity. The findings reveal considerable inconsistencies in data fields, classification systems, and levels of detail across the datasets. Building on these insights, this study also develops a conceptual minimum dataset (MDS) framework comprising three core thematic categories: project identification, project characteristics, and project budget and timing. The proposed conceptual MDS includes unified data definitions, standardised reporting formats, and semantic alignment to enhance cross-platform usability and data confidence. This framework applies to the New Zealand context and is designed for replication in other jurisdictions, supporting the global push toward open, high-quality infrastructure data. The study contributes to the construction informatics and infrastructure planning by offering a practical solution to a critical data governance issue and introducing a transferable methodology for developing minimum data standards in the built environment to enable more informed, coordinated, and evidence-based decision-making. Full article

Interest in the wine sector focusing on no- or low-alcohol wines is growing. De-alcoholation, typically a post-fermentation process, faces restrictions in some countries and is often quite costly. Using raw materials like low-sugar grapes suitable for this purpose seems logical, yet the literature currently lacks contributions in this area. In this review paper, we outline an ideal ripening process where the goal of producing “low-sugar grapes” can be achieved through various methodologies applied at (i) the whole-canopy level (minimal pruning, hedge mechanical pruning with or without hand finishing, cane pruning combined with high bud load and no cluster thinning, applications of exogenous hormones, late irrigation, and double cropping); (ii) the canopy microclimate level, involving changes in the leaf area-to-fruit ratios (netting, apical or basal leaf removal, late shoot trimming, use of antitranspirants); and (iii) through new technologies (high-yield plots from vigor maps and the adoption of agrivoltaics). However, the efforts in this survey extend beyond merely achieving the production of low-sugar grapes in the vineyard, which is indeed primary but not exhaustive. Therefore, we also explore solutions for obtaining low-sugar grapes while simultaneously enhancing features such as lower acidity, increased phenolics, and aroma potential, which might boost consumer appreciation. The review emphasizes that (i) grapes intended for low-alcohol wine production should not be viewed as a low-quality sector but rather as an alternative endeavour, where the concept of grape quality remains firmly intact and (ii) viticulture for low sugar concentration is a primary strategy, rather than merely a support to dealcoholization techniques. Full article

Batch processing machines (BPMs) are extensively present in high energy-consuming manufacturing processes such as casting, and they show some symmetries on adjacent batches and jobs within each batch. Preventive maintenance (PM) is very important for the stable running and energy saving of BPMs; however, PM in a parallel BPM shop is seldom studied. In this study, the energy-efficient parallel BPM scheduling problem with PM is considered and an imperialist competitive algorithm with three empires (TEICA) is presented to minimize makespan and total energy consumption. To obtain high-quality solutions, the number of empires is not used as a parameter and fixed at 3, a new way is applied to construct three initial empires, each of which has a new structure like two imperialists, a new assimilation is given, and an adaptive imperialist competition is implemented based on historical competition data. A number of computational experiments are conducted on 108 instances. The computational results show that the new strategies of TEICA are effective; TEICA can provide better results than all comparative methods on more than 90% instances of the considered BPM scheduling problem, and TEICA may be an effective way to solve other BPM scheduling problem. Full article

Advanced therapy medicinal products (ATMPs), especially effective against cancer, remain costly due to their reliance on genetically modified T cells. Contamination during production is a major concern, as traditional quality control methods involve samplings, which can themselves introduce contaminants. It is therefore necessary to develop methods for detecting contamination without sampling and, if possible, in real time. In this article, we present a white light spectroscopy method that makes this possible. It is based on shape analysis of the absorption spectrum, which evolves from an approximately Gaussian shape to a shape modified by the 1/λ component of bacterial absorption spectra when contamination develops. A warning value based on this shape descriptor is proposed. It is demonstrated that a few hours are sufficient to detect contamination and trigger an alarm to quickly stop the production. This time-saving should reduce the cost of these new drugs, making them accessible to as many people as possible. This method can be used regardless of the type of contaminants, provided that the shape of their absorption spectrum is sufficiently different from that of pure T cells so that the shape descriptor is efficient. Full article

Concrete is an essential material in the construction industry due to its strength and versatility. However, its quality can be compromised by environmental factors during its fresh and early-age states. To address this vulnerability, various sensors have been implemented to monitor critical parameters. While high-precision sensors (e.g., piezoelectric and fiber optic) offer accurate measurements, their cost and fragility limit their widespread use in construction environments. In response, this study proposes a cost-effective, Arduino-based wireless monitoring system to track temperature and humidity in fresh and early-age concrete elements. The system was validated through laboratory tests on cylindrical specimens and industrial applications on self-compacting concrete New Jersey barriers. The sensors recorded temperature variations between 15 °C and 35 °C and relative humidity from 100% down to 45%, depending on environmental exposure. In situ monitoring confirmed the system’s ability to detect thermal gradients and evaporation dynamics during curing. Additionally, the presence of embedded sensors caused a tensile strength reduction of up to 37.5% in small specimens, highlighting the importance of sensor placement. The proposed solution demonstrates potential for improving quality control and curing management in precast concrete production with low-cost devices. Full article

For the precise description of gas physical processes in high-voltage direct current (HVDC) transmission, an advanced and robust numerical framework for the simulation of transient particle densities in the course of corona discharges is developed in this work. The aim is the scalable and consistent modeling of the space charge density under realistic conditions. The core component of the framework is a discontinuous Galerkin method that ensures the conservative properties of the underlying hyperbolic problem. The space charge density at the electrode surface is imposed as a dynamic boundary condition via Lagrange multipliers. To increase the numerical stability and convergence rate, a homotopy approach is also integrated. For the experimental validation, a measurement concept was realised that uses a subtraction method to specifically remove the displacement current component in the signal and thus enables an isolated recording of the transient ion current with superimposed voltage stresses. The experimental results on a small scale agree with the numerical predictions and prove the quality of the model. On this basis, the framework is transferred to hybrid HVDC overhead line systems with a bipolar design. In the event of a fault, significant transient space charge densities can be seen there, especially when superimposed with new types of voltage waveforms. The framework thus provides a reliable contribution to insulation coordination in complex HVDC systems and enables the realistic analysis of electrohydrodynamic coupling effects on an industrial scale. Full article

Skeletal muscle atrophy is a critical health issue affecting the quality of life of elderly individuals and patients with chronic diseases. These conditions induce dysregulation of glucocorticoid (GC) secretion. GCs play a critical role in maintaining homeostasis in the stress response and glucose metabolism. However, prolonged exposure to GC is directly linked to muscle atrophy, which is characterized by a reduction in muscle size and weight, particularly affecting fast-twitch muscle fibers. The GC-activated glucocorticoid receptor (GR) decreases protein synthesis and facilitates protein breakdown. Numerous antagonists have been developed to mitigate GC-induced muscle atrophy, including 11β-HSD1 inhibitors and myostatin and activin receptor blockers. However, the clinical trial results have fallen short of the expected efficacy. Recently, several emerging pathways and targets have been identified. For instance, GC-induced sirtuin 6 isoform (SIRT6) expression suppresses AKT/mTORC1 signaling. Lysine-specific demethylase 1 (LSD1) cooperates with the GR for the transcription of atrogenes. The kynurenine pathway and indoleamine 2,3-dioxygenase 1 (IDO-1) also play crucial roles in protein synthesis and energy production in skeletal muscle. Therefore, a deeper understanding of the complexities of GR transactivation and transrepression will provide new strategies for the discovery of novel drugs to overcome the detrimental effects of GCs on muscle tissues. Full article

Optical coordinate measurement is a universal technique that aligns with the rapid development of industrial technologies and new materials. Nevertheless, can this technique be consistently effective when applied to the precise measurement of all types of materials? As shown in this article, an analysis of optical measurement systems reveals that some materials cause difficulties during the scanning process. This article details the matting process, resulting, as demonstrated, in lower measurement uncertainty values compared to the pre-matting state, and identifies materials for which applying a matting spray significantly improves the measurement quality. The authors propose a classification of materials into easy-to-scan and hard-to-scan groups, along with specific procedures to improve measurements, especially for the latter. Tests were conducted in an accredited Laboratory of Coordinate Metrology using an articulated arm with a laser probe. Measured objects included spheres made of ceramic, tungsten carbide (including a matte finish), aluminum oxide, titanium nitride-coated steel, and photopolymer resin, with reference diameters established by a high-precision Leitz PMM 12106 coordinate measuring machine. Diameters were determined from point clouds obtained via optical measurements using the best-fit method, both before and after matting. Color measurements using a spectrocolorimeter supplemented this study to assess the effect of matting on surface color. The results revealed correlations between the material type and measurement accuracy. Full article

Kiwifruit (Actinidia spp.) is a globally important economic fruit with high nutritional value. Fruit peelability, defined as the mechanical ease of separating the peel from the fruit flesh, is a critical quality trait influencing consumer experience and market competitiveness and has emerged as a critical breeding target in fruit crop improvement programs. The present review systematically synthesized existing studies on kiwifruit peelability, and focused on its evolutionary trajectory, genotypic divergence, quantitative evaluation, possible underlying mechanisms, and artificial manipulation strategies. Kiwifruit peelability research has advanced from early exploratory studies in New Zealand (2010s) to systematic investigations in China (2020s), with milestones including the development of evaluation metrics and the identification of genetic resources. Genotypic variation exists among kiwifruit genera. Several Actinidia eriantha accessions and the novel Actinidia longicarpa cultivar ‘Guifei’ exhibit superior peelability, whereas most commercial Actinidia chinensis and Actinidia deliciosa cultivars exhibit poor peelability. Quantitative evaluation highlights the need for standardized metrics, with “skin-flesh adhesion force” and “peel toughness” proposed as robust, instrument-quantifiable indicators to minimize operational variability. Mechanistically, peelability is speculated to be governed by cell wall polysaccharide metabolism and phytohormone signaling networks. Pectin degradation and differential distribution during fruit development form critical “peeling zones”, whereas ethylene, abscisic acid, and indoleacetic acid may regulate cell wall remodeling and softening, collectively influencing skin-flesh adhesion. Owing to the scarcity of easy-to-peel kiwifruit cultivars, artificial manipulation methods, including manual peeling benchmarking, lye treatment, and thermal peeling, can be employed to further optimize kiwifruit peelability. Currently, shortcomings include incomplete genotype-phenotype characterization, limited availability of easy-peeling germplasms, and a fragmented understanding of the underlying mechanisms. Future research should focus on methodological innovation, germplasm development, and the elucidation of relevant mechanisms. Full article

Saproxylic beetles are key bioindicators of forest ecosystem quality and play essential roles in deadwood decomposition and nutrient cycling. However, their populations are increasingly threatened by habitat fragmentation, deadwood removal, and climate-driven environmental changes. For this reason, an integrated sampling method can increase the detection of species with varying ecological traits. We evaluated the effectiveness of integrative sampling methodologies to assess saproxylic beetle diversity within Sila National Park, a Mediterranean forest ecosystem of high conservation value, specifically in two beech forests and four pine forests. The sampling methods tested included Pan Traps (PaTs), Malaise Traps (MTs), Pitfall Traps (PTs), Bait Bottle Traps (BBTs), and Visual Census (VC). All specimens were identified to the species level whenever possible, using specialized dichotomous keys and preserved in the Entomological Collection TB, Unical. Various trap types captured a different number of species: the PaT collected 32 species, followed by the PT with 24, the MT with 16, the VC with 7, and the BBT with 5 species. Interestingly, biodiversity analyses conducted using PAST software version 4.17 revealed that PaTs and MTs recorded the highest biodiversity indices. The GLMM analysis, performed using SPSS software 29.0.1.0, demonstrated that various traps attracted different species with different abundances. By combining multiple trapping techniques, we documented a more comprehensive community composition compared to single-method approaches. Moreover, PaTs, MTs, and PTs recorded 20%, 40%, and 33% of the Near Threatened species, respectively. We report new records for Sila National Park, including the LC species Pteryngium crenulatum (Curculionidae) and the NT species Grynocharis oblonga (Trogossitidae). For the first time in Calabria, the LC species Triplax rufipes (Erotylidae) and the NT species Oxypleurus nodieri (Cerambycidae) and Glischrochilus quadrisignatus (Nitidulidae) were collected. Our results emphasize the importance of method diversity in capturing species with distinct ecological requirements and highlight the relevance of saproxylic beetles as indicators of forest health. These findings support the adoption of multi-method sampling protocols in forest biodiversity monitoring and management programs, especially in biodiversity-rich and structurally heterogeneous landscapes. Full article

Generative Adversarial Networks (GANs) using Long Short-Term Memory (LSTM) provide a computationally cheaper approach for text generation compared to large language models (LLMs). The low hardware barrier of training GANs poses a threat because it means more bad actors may use them to mass-produce prompt attack messages against LLM systems. Thus, to better understand the threat of GANs being used for prompt attack generation, we train two well-known GAN architectures, SeqGAN and RelGAN, on prompt attack messages. For each architecture, we evaluate generated prompt attack messages, comparing results with each other, with generated attacks from another computationally cheap approach, a 1-billion-parameter Llama 3.2 small language model (SLM), and with messages from the original dataset. This evaluation suggests that GAN architectures like SeqGAN and RelGAN have the potential to be used in conjunction with SLMs to readily generate malicious prompts that impose new threats against LLM-based systems such as chatbots. Analyzing the effectiveness of state-of-the-art defenses against prompt attacks, we also find that GAN-generated attacks can deceive most of these defenses with varying levels of success with the exception of Meta’s PromptGuard. Further, we suggest an improvement of prompt attack defenses based on the analysis of the language quality of the prompts, which we found to be the weakest point of GAN-generated messages. Full article

Achieving a win-win situation for both economy and ecology is crucial for promoting sustainable social development and shaping new advantages in high-quality developments. This article constructs an ecological economic resilience (EER) analysis framework by integrating both ecological and economic dimensions from a resilience perspective. Based on panel data from 290 cities in China, it explores the dynamic evolution characteristics, regional differences, and convergence trends of EER. The findings indicate that the EER has weakened nationwide and in the four major economic regions, overall tending towards stability. Significant disparities exist in EER, particularly pronounced in the northeast. There is $\sigma$ convergence in the nation as well as in the northeast and east regions. Additionally, both absolute and conditional $\beta$ convergence is evident nationwide and in all regions, with conditional convergence occurring at a faster pace. The research findings in this paper provide solid theoretical support for promoting regional coordinated development and constructing a new development paradigm. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a worldwide challenge. There are an estimated 17–24 million patients worldwide, with an estimated 60 percent or more who have not been diagnosed. Without a known cure, no specific curative medication, disability lasting years to being life-long, and disagreement among healthcare providers as to how to most appropriately treat these patients, ME/CFS patients are in need of assistance. Appropriate healthcare provider education would increase the percentage of patients diagnosed and treated; however, in-school healthcare provider education is limited. To address the latter issue, the New Jersey Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Association (NJME/CFSA) has developed an independent, incentive-driven, learning program for students of the health professions. NJME/CFSA offers a yearly scholarship program in which applicants write a scholarly paper on an ME/CFS-related topic. The efficacy of the program is demonstrated by the 2024–2025 first place scholarship winner’s essay, which addresses the biological basis of ME/CFS and how the healthcare provider can improve the quality of life of ME/CFS patients. For the reader, the essay provides an update on what is known regarding the biological underpinnings of ME/CFS, as well as a medical student’s perspective as to how the clinician can provide care and support for ME/CFS patients. The original essay has been slightly modified to demonstrate that ME/CFS is a worldwide problem and for publication. Full article

Pitaya (Selenicereus undatus) is a long-day climbing cactus that blooms in waves mostly on 1-year old, succulent leafless shoots called cladodes. Nonetheless, pitaya can also bloom on new-year growth if the buds of the cladodes are mature enough and competent for flower induction. Here, we tested, during two consecutive years, whether early pruning could have a positive effect on promoting more flowering waves, better fruiting, and heavier yield of ‘Korean White’ pitaya cultivated in unheated greenhouses of Southeastern Spain. The results show that pruning in January instead of March did not consistently modify the reproductive behavior of ‘Korean White’ pitaya in our conditions. Therefore, no significant effects on the number of blooming waves, flowering intensity, fruit set, quality or yield were observed. The only positive effect, not always significant, was an increase in fruit size that led to better fruit distribution into commercial categories in one out of the two experimental seasons. The lack of effect of early pruning was attributed to the prevalent low temperatures during winter in Spain. The results, however, suggest it is worthwhile exploring whether greenhouse heating with temperatures above pitaya’s base temperature may have the desired effects on increasing blooming waves. The profitability of this practice have to be carefully assessed. Full article