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DEM calibration insights on the role of particle shape for sub 2 mm particles
Abstract This study introduces a comprehensive calibration technique for discrete element method (DEM) simulations. Its focus is on particles smaller than 2 mm and this showcase shows comparison between spherical and polyhedral particle shape calibration. Very fine powders or particulate materials with small particles are usually calibrated with upscaling. Unfortunately, some applications are dependent heavily on a quite precise particle size range, such as abrasion, crushing, pneumatic conveying, feeding, and dosing. Traditional DEM simulations often rely on spherical or multi-spherical particle models, which lack the precision needed, particularly due to the surface waviness introduced in the latter case. This limitation impacts dynamic industrial applications like mixing, hopper discharge, and abrasion. To address this gap, we present a comparative calibration approach for spherical and polyhedral particles, using silica sand as the test material. The calibration combines static and dynamic parameters such as rolling resistance, particle-to-particle restitution, and wall friction, validated through experiments on a powder flow calibration stand. Results revealed significant differences in flow dynamics, highlighting the enhanced realism of polyhedral models despite increased computational demands. This work provides a comprehensive framework for DEM calibration of fine particulate materials, specifically validated for particle sizes between 400 and 1500 µm, improving simulation accuracy and extending applicability across various industrial processes.
Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation
Oil removal from wastewater with biomass-derived hydrochars laboratory insights
Enhancing urban quality of life evaluation using spatial multi criteria analysis
Natural experiments from Earth Hour reveal urban night sky being drastically lit up by few decorative buildings
The prognostic significance of the geriatric nutritional risk index in postoperative parotid gland carcinoma
Abstract The impact of the Geriatric Nutritional Risk Index (GNRI) on the prognosis of postoperative parotid gland carcinoma (PGC) remains unclear. This study investigates the role of GNRI in predicting disease-free survival (DFS) and overall survival (OS) in postoperative PGC patients and develops a predictive model. We conducted a retrospective analysis of 389 postoperative PGC patients treated from May 2008 to June 2019 at two regional medical centers in China. The independent prognostic factors were identified by univariate and multivariate Cox regression analyses. Then, two nomograms were established based on these independent prognostic factors and verified by a series of methods. The GNRI was identified as an independent prognostic factor in postoperative patients with PGC. A higher GNRI value indicated a worse prognosis for the patient. Based on the recognized independent prognostic factors—such as surgical margin, perineural invasion, extranodal extension (ENE), age-adjusted Charlson comorbidity index (ACCI), American Joint Committee on Cancer (AJCC) stage, and GNRI—two nomograms for overall survival (OS) and disease-free survival (DFS) were developed. The concordance index (C-index) for DFS was 0.712 and 0.730, while for OS it was 0.697 and 0.722 in the training and validation groups, respectively. These results demonstrate a significant improvement over the traditional AJCC staging system. Additionally, the area under the curve (AUC) values in both the training and validation sets were impressive, with all AUC scores exceeding 0.7. Decision curve analysis (DCA) also indicated substantial clinical benefits. The GNRI is an important predictive index in postoperative patients with PGC, which is not limited to the elderly. The newly developed nomograms provide a new tool of prognostic evaluations for postoperative patients with PGC.
Fecal microbiota transplantation improves Sansui duck growth performance by balancing the cecal microbiome
An analysis of sustainability and performance indicators in Eco-Conscious trainers’ brands
Abstract The fashion industry is known for its negative environmental and social impacts globally. Sustainability has become a priority for governmental agendas and concerned consumers. However, achieving sustainability remains a challenge for the industry due to its complex supply chains and systems. Specifically, the footwear industry accounts for 1.4% of global carbon emissions, with trainers being one of the most popular types of footwear among consumers. Recent studies have highlighted their ecological footprint, prompting companies to implement various actions to address this issue. Nevertheless, the environmental impact of this sector continues to pose significant challenges. This paper conducts a content analysis to examine and classify the actions taken by 13 Sustainable Trainers’ Brands according to five categories: Sustainable Materials, Sustainable Manufacturing, Sustainable Distribution, End-of-Life Recovery, and Eco-Design. Results show that Sustainable Materials is the most frequently adopted approach for sustainability, while Eco-Design is the least emphasised area. Additionally, the indicators used to assess sustainability in this sector primarily focus on the Environmental Sphere, with Sustainable Materials being the most prominently coded category. This study identifies Eco-Design as an area that requires further attention in future developments to address sustainability from a broader perspective.
Fusing satellite imagery and ground-based observations for PM2.5 air pollution modeling in Iran using a deep learning approach
Synthesis and characterization of biobased capsules formed from interpenetrating networks of alginate and poly(ethylene glycol) for the encapsulation of blue dye
Osimertinib plus chemotherapy versus osimertinib for patients with advanced NSCLC with concomitant EGFR and TP53 mutations: a prospective cohort study
Variable selection strategies for genomic prediction of growth and carcass related traits in experimental Nellore cattle herds under different selection criteria
Identification and validation of key target genes of penning formula for treating rat chronic endometritis model
Eyes on hold: motion task difficulty jointly delays microsaccade and pupil responses
Citizen science substantiates jellyfish occurrence in the Mediterranean Sea
Abstract In recent decades, gelatinous plankton blooms have attracted media attention due to their damaging effects on fisheries, aquaculture, tourism, human health and power/desalination plants. The scientific community often failed to recognize the rise of jellyfish, due to difficulties in monitoring their appearances and disappearances. In Italian waters, a citizen science approach was employed to monitor the presence and distribution of gelatinous zooplankton over wide spatio-temporal scales. From 2009 to March 2016, citizens identified 27 jellyfish taxa and documented their geographical distribution and seasonal occurrence across the Italian Seas. The main blooming species was Pelagia noctiluca (30% of total sightings), mainly distributed in the western Mediterranean, followed by Rhizostoma pulmo (28% of total sightings), showing a more widespread distribution. Mnemiopsis leidyi, the main Non-Indigenous Species (NIS), initially reported in the western Mediterranean, since 2016 expanded its distribution to the east. Jellyfish blooms were recorded year-round, mainly between late spring and autumn. Jellyfish hotspots were identified in the northern and southern Tyrrhenian, Ligurian Sea, and northern Adriatic regions. Citizen Science enables the detection of phenomena that can be studied more in-depth by professional scientists, leading to the discovery of previously unknown species and a better understanding of the occurrence of bloom events.
High efficiency of laser energy conversion with cavity pressure acceleration
Biased birth sex ratios of mammals and birds in zoos
Abstract Birth sex ratio biases can amplify extinction risks, especially in small, zoo-maintained populations which is of particular concern in species under threat of extinction. Thus, understanding the drivers of such biases is critical for conservation outcomes. We analysed birth records from 129 avian and 324 mammalian species in zoos worldwide between 1980 and 2021. Using Bayesian phylogenetic models, we found a phylogenetic signal in birth sex ratios (BSR), with substantial variation across clades. Penguins, falcons, and parrots showed slightly male-biased BSRs; ungulates showed female-biased BSR, and primates male-biased BSR. Across birds, variation in BSRs was predicted by sexual size dimorphism and clutch size, whereas in mammals, mating system was the main predictor of BSR. We identified 30 conservation flagship species with significantly biased BSRs, raising concern for the demographic sustainability of their captive populations. These results highlight the role of both evolutionary history and life-history traits in shaping sex ratio variation across taxa. Our findings underscore the importance of integrating phylogenetic and biological predictors into conservation planning and breeding program design. They also call for further research into the biological and management processes—that include sexual selection, parental investment, housing, and sexing practices—that may contribute to sex ratio variation in zoo populations.