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In present-day dialogues pertaining to the stewardship of the environment, the essential interconnectedness between the management of resources sustainably and the conservation of biodiversity has surfaced as an issue of considerable significance. The efficacious overseeing of natural resources, which includes both ecosystems found on land and in water, is fundamentally necessary for the preservation of the fragile equilibrium that supports the resilience of ecosystems. The intensifying pressures stemming from climate change, urban expansion, and the exploitation of resources compel the adoption of novel strategies which must not only safeguard the resource availability for forthcoming generations but also actively advance the well-being of ecological systems. This discourse will delving into the complex interrelation between practices of sustainable resource management and their repercussions on biodiversity, positing that an all-encompassing approach is crucial. By amalgamating principles of ecology with considerations rooted in socio-economics, it is plausible to bolster the resilience of ecosystems that are progressively susceptible to human-induced influences. In conclusion, the discussion will elucidate potential routes toward a future characterised by sustainability, emphasising the recognition that the health and vitality of our natural resources are fundamentally intertwined with biodiversity and the stability of ecosystems. A crucial component of the safeguarding of ecological integrity pertains to the sustainable administration of natural resources, which is characterised as the action of utilising these resources in a way that addresses current demands without endangering the capacity of subsequent generations to satisfy their own. This necessitates the equilibrium of ecological, economic, and social imperatives, thereby enhancing biodiversity and the resilience of ecosystems. [ABSTRACT FROM AUTHOR]

The role of farmers in the modern era is both pivotal and complex, as they stand at the nexus of food production, environmental stewardship, and economic sustainability. This abstract delves into the multifaceted challenges and pressing issues that confront farmers in this dynamic landscape. In an era defined by rapid technological advancements, shifting consumer demands, environmental concerns, and global market dynamics, the modern farmer faces a unique set of challenges. In the intricate web of our contemporary world, the role of farmers emerges as nothing short of pivotal, and yet their journey is one that traverses a landscape as intricate as the crops they cultivate. The modern farmer, often obscured beneath the broad brim of a sun-worn hat, is a figure who carries the aspirations of a global society—a society demanding sustenance, stewardship, and stability. Modern farmers find themselves at the confluence of diverse challenges that shape the dynamics of contemporary agriculture. This abstract provides a concise overview of the critical issues that weigh on the minds and shoulders of those who till the soil and tend to livestock. In an era marked by technological innovation, shifting consumer preferences, environmental concerns, and global market fluctuations, the challenges facing modern farmers are both intricate and pressing. In conclusion, modern farmers confront a complex web of challenges, including technological disparities, environmental sustainability, consumercentric farming, economic uncertainties, rural depopulation, and policy advocacy. Their journey is one of adaptation and resilience as they navigate the evolving landscape of agriculture and its multifaceted challenges. [ABSTRACT FROM AUTHOR]

Volumetric modulated arc therapy (VMAT) is widely used in radiotherapy (RT) treatment planning, yet manual treatment planning (MP) remains labor-intensive and skill-dependent. To address this, we propose a fully automated treatment planning (AP) approach for prostate cancer treatments, aiming to streamline planning while maintaining quality. Our pipeline takes as input a contoured planning CT, the targeted Linac machine and the prescription dose. It uses a deep learning model trained on 123 clinical cases for dose prediction and direct aperture VMAT plan optimization. A clinical evaluation study was performed on another 25 cases. The RT plans generated were calculated using a Collapsed Cone Convolution engine and the obtained RTdoses were compared with the reference doses from MP. First, a quantitative evaluation was performed based on dose-volume histogram (DVH) points and plan parameters metrics (monitor units (MU) and modulation complexity score (MCS)). Paired Wilcoxon signed-rank test was used to assess significant differences between the MP and AP plans (with p<0.05 considered statistically significant). Secondly, a double blinded plan comparison study was organized, showing side-by-side the RTdoses from AP and MP plans. Three experts (from major European and US cancer centers) evaluated plan acceptability and preference. The results of the quantitative evaluation showed that the AP doses to PTV_80Gy were similar to those of MP (<0.5Gy absolute dose difference) and without statistically significant differences in the median (D50%) and maximum (D2%) doses (Table1). AP reduced toxicity to organs-at-risk (OARs), notably a 6Gy decrease in D5% to the right femoral head. Significant differences between MP vs AP were also observed in the number of MU (589.67 ± 57.39 vs 658.48 ± 72.52) and MCS (0.19 ± 0.03 vs 0.17 ± 0.03). Qualitative evaluation found both AP and MP plans clinically acceptable (87% and 85%, respectively). AP was preferred in 18/25, 13/25, and 22/25 cases by three experts, revealing varying clinical priorities. Table1. Dosimetric study results. With * are highlighted the statistically significant differences between MP and AP (p<0.05) Our automated pipeline produces plans comparable to manual ones, deemed clinically acceptable and sometimes superior. Differences in expert preferences highlight variations in clinical practice across centers and countries. [ABSTRACT FROM AUTHOR]

Background/Objectives : To evaluate an end-to-end pipeline for normo-fractionated prostate-only and whole-pelvic cancer treatments that requires minimal human input and generates a machine-deliverable plan as an output. Methods : In collaboration with TheraPanacea, a treatment planning pipeline was developed that takes as its input a planning CT with organs-at-risk (OARs) and planning target volume (PTV) contours, the targeted linac machine, and the prescription dose. The primary components are (i) dose prediction by a single deep learning model for both localizations and (ii) a direct aperture VMAT plan optimization that seeks to mimic the predicted dose. The deep learning model was trained on 238 cases, and a held-out set of 86 cases was used for model validation. An end-to-end clinical evaluation study was performed on another 40 cases (20 prostate-only, 20 whole-pelvic). First, a quantitative evaluation was performed based on dose-volume histogram (DVH) points and plan parameter metrics. Then, the plan deliverability was assessed via portal dosimetry using the global gamma index. Additionally, the reference clinical manual plans were compared with the automated plans in terms of monitor unit (MU) numbers and modulation complexity scores (MCSv). Results : The automated plans provided adequate treatment plans (or minor deviations) with respect to the dose constraints, and the quality of the plans was similar to the manual plans for both localizations. Moreover, the automated plans showed successful deliverability and passed the portal dose verification. Despite higher median total MUs, no statistically significant correlation was observed between any of the gamma criteria tested and the number of MUs or MCSv. Conclusions : This study shows the feasibility of a deep learning-based fully automated treatment planning pipeline that generates high-quality plans that are competitive with manually made plans and are clinically approved in terms of dosimetry and machine deliverability.

This paper presents a continuation of the Chambadal model optimization of the irreversible Carnot engine. We retrieved the results presented in the Special Issue "Carnot Cycle and Heat Engine Fundamentals and Applications II" and enriched them with new contributions that allowed comparing two points of view: (1) the now classical one, centered on entropy production in the four processes of the cycle, which introduces the action of entropy production, with several sequential optimizations; (2) the new one that is relative to an energy degradation approach. The same démarche of sequential optimization was used, but the results were slightly different. We estimate that the second approach is more representative of physics by emphasizing the energy conservation and the existence on an upper and a lower bound in the mechanical energy and power output of the engine.

The objective of this study was to analyse the influence of materials and their position within the upper assembly on the behaviour of casual footwear using finite element simulation tools. The study was carried out on three models of casual footwear, which are identical in terms of design lines, varying only in the materials of the upper assembly, namely calfskin leather (M1), knitted fabric (M2), and combination of knitted fabric and calfskin leather (M3). The footwear models were designed according to the design constraints specific to casual footwear. The foot was reconstructed based on the shoe last obtained based on anthropometric data. Material definition, 3D models editing, setting up analysis conditions, and constraints were performed using the Ansys 17.2 software. Gait biomechanics were taken into account to define the loading model, force distribution, force values, and constraints. The study evaluates footwear behaviour in terms of directional deformation (Z axis), equivalent von Mises stress, and equivalent elastic strain distribution. This paper explores a methodology that has the potential to enhance the footwear design and manufacturing process, providing designers with information about the deformations and stress distribution on upper parts of the footwear product.

Purpose: To investigate the performance of 4 atlas-based (multi-ABAS) and 2 deep learning (DL) solutions for head-and-neck (HN) elective nodes (CTVn) automatic segmentation (AS) on CT images., Material and Methods: Bilateral CTVn levels of 69 HN cancer patients were delineated on contrast-enhanced planning CT. Ten and 49 patients were used for atlas library and for training a mono-centric DL model, respectively. The remaining 20 patients were used for testing. Additionally, three commercial multi-ABAS methods and one commercial multi-centric DL solution were investigated. Quantitative evaluation was assessed using volumetric Dice Similarity Coefficient (DSC) and 95-percentile Hausdorff distance (HD 95% ). Blind evaluation was performed for 3 solutions by 4 physicians. One recorded the time needed for manual corrections. A dosimetric study was finally conducted using automated planning., Results: Overall DL solutions had better DSC and HD 95% results than multi-ABAS methods. No statistically significant difference was found between the 2 DL solutions. However, the contours provided by multi-centric DL solution were preferred by all physicians and were also faster to correct (1.1 min vs 4.17 min, on average). Manual corrections for multi-ABAS contours took on average 6.52 min Overall, decreased contour accuracy was observed from CTVn2 to CTVn3 and to CTVn4. Using the AS contours in treatment planning resulted in underdosage of the elective target volume., Conclusion: Among all methods, the multi-centric DL method showed the highest delineation accuracy and was better rated by experts. Manual corrections remain necessary to avoid elective target underdosage. Finally, AS contours help reducing the workload of manual delineation task., Competing Interests: Declaration of Competing Interest This work was performed in the framework of a research cooperation agreement with Elekta AB., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Cuscuta (dodder) includes ca. 200 species of plant obligate stem parasites with enormous ecological and economical significance. Inflorescences have been historically used in Cuscuta for species descriptions and identification keys, but no comprehensive study exists to date. The main objectives of this study were to survey the diversity and evolution of inflorescences and to uncover their possible form-function relationships. The inflorescence architecture of 132 Cuscuta taxa was analysed using herbarium specimens and eight species were grown to study their inflorescence development. Inflorescence traits were mapped into a genus phylogeny obtained from a combined analysis of nuclear ITS and plastid trnL-F sequences. To test the hypothesis that inflorescence architecture is connected to sexual reproduction, correlations between inflorescence traits (using Principal Components), sexual reproductive traits (pollen/ovule ratios, corolla length and diameter), fruit charaters (fruit length and width), and the modes of dehiscence were analyzed. Based on their development, three major types of inflorescences were observed: "Cuscuta type", a simple, monochasial scorpioid cyme; "Monogynella type", a compound monochasial scorpioid cymes with the longest primary axes having prolonged vegetative growth and giving the appearance of thyrses; and "Grammica type", a compound monochasial scorpiod cymes with up to five orders of axes. Maximum likelihood analyses suggested Monogynella as the ancestral type, while Cuscuta and Grammica were derived. Overall, the total length of axes exhibited a reduction trend throughout the genus evolution, but it was not correlated with the pedicels length. Inflorescences with similar architectures may exhibit contrasting pollen-ovule ratios. Positive significant correlations were noted between the size of the flower traits and pollen-ovule ratios. Several modes of dehiscence had statistically significant different total axes lengths, suggesting that the infructescence architecture is connected to the modes of dehiscence in Cuscuta and therefore seed dispersal., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Glofcheskie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Poor air quality inside museums can have a double effect; on the one hand, influencing the integrity of the exhibits and on the other hand, endangering the health of employees and visitors. Both components can be very sensitive to the influence of the internal microclimate, therefore careful monitoring of the physical parameters and pollutants is required in order to maintain them within strict limits and thus to reduce the hazards that can be induced. The current study considers the determination and analysis of 15 indicators of the internal microclimate in an Art Nouveau museum built at the beginning of the 20th century in the Municipality of Oradea, Romania. The monitoring spanned a period of seven months, between September 2021 and March 2022, targeting three rooms of the museum with different characteristics and containing exhibits with a high degree of fragility. The results show that, although there are numerous indicators that have exceeded the thresholds induced by international standards, the possible negative impact on the exhibits and/or on human health remains moderate. This is due to the fact that, most of the time, exceeding the permitted limits are small or only sporadic, the values quickly returning to the permitted limits. Thus, only 22 of the 212 days of monitoring recorded marginal conditions regarding the quality of the indoor air, the rest having acceptable and good conditions. To improve the indoor conditions, a more careful management is needed, especially regarding the values of temperature, humidity, particulate matters, natural and artificial light, volatile organic compounds (VOC) and formaldehyde (HCHO), which during the measurements recorded high values that fluctuated in a wide spectrum. The obtained results can represent the basis for the development and implementation of long-term strategies for stabilizing the microclimatic conditions in the museum in order to preserve the exhibits preventively and to ensure a clean and safe environment for people.

Background and Purpose: To investigate the performance of head-and-neck (HN) organs-at-risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep learning (DL) solutions., Material and Methods: All patients underwent iodine contrast-enhanced planning CT. Fourteen OAR were manually delineated. DL.1 and DL.2 solutions were trained with 63 mono-centric patients and > 1000 multi-centric patients, respectively. Ten and 15 patients with varied anatomies were selected for the atlas library and for testing, respectively. The evaluation was based on geometric indices (DICE coefficient and 95th percentile-Hausdorff Distance (HD 95% )), time needed for manual corrections and clinical dosimetric endpoints obtained using automated treatment planning., Results: Both DICE and HD 95% results indicated that DL algorithms generally performed better compared with ABAS algorithms for automatic segmentation of HN OAR. However, the hybrid-ABAS (ABAS.3) algorithm sometimes provided the highest agreement to the reference contours compared with the 2 DL. Compared with DL.2 and ABAS.3, DL.1 contours were the fastest to correct. For the 3 solutions, the differences in dose distributions obtained using AS contours and AS + manually corrected contours were not statistically significant. High dose differences could be observed when OAR contours were at short distances to the targets. However, this was not always interrelated., Conclusion: DL methods generally showed higher delineation accuracy compared with ABAS methods for AS segmentation of HN OAR. Most ABAS contours had high conformity to the reference but were more time consuming than DL algorithms, especially when considering the computing time and the time spent on manual corrections., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: This work was performed in the framework of a research cooperation agreement with Elekta AB., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This study presents the production, characterization, and application of celandine ( Chelidonium majus L.) extracts (aqueous, acidic, alcoholic, and ultrasound) on wool fibers and their characterization. The study aims to obtain an ecologically dyed wool support that possesses biocompatible and antimicrobial activities. The plant extracts were characterized based on pH, total polyphenol content, and berberine content. Ecologically dyed wool supports were characterized based on scanning electron microscopy, levelness index, color measurements, contact angle indirect biocompatibility, and antibacterial analysis. According to the obtained results, celandine extract can be considered a potential candidate for the sustainable dyeing and functionalization of wool fibers.

This paper aimed to define two critical mechanical properties of leather-Young's modulus and Poisson ratio-essential to the virtual simulation of the behaviour of the footwear uppers against the manufacturing operations of stitching and perforating. The following technological aspects were considered to analyse the materials from manufacturing conditions point of view: the number of layers (one layer and two layers), the nature of the materials used for uppers subgroups (calfskin-outer upper, sheep leather-lining, polyester knitted fabric-lining), the overlapping width in the stitching area, the number of parallel stitches (single stitch and double stitch), the punching interval and the type of perforations (simple and with eyelets), resulting in nine kinds of samples. Furthermore, the elasticity (Young's modulus) and lateral contraction (Poisson's ratio) were calculated during the tensile strength analysis performed on the SATRA STM 466 equipment. Both mechanical parameters are essential to simulate the behaviour of the virtual footwear prototypes in various conditions., Competing Interests: The authors declare no conflict of interest.

The old fibers that make up heritage textiles displayed in museums are degraded by the aging process, environmental conditions (microclimates, particulate matter, pollutants, sunlight) and the action of microorganisms. In order to counteract these processes and keep the textile exhibits in good condition for as long as possible, both reactive and preventive interventions on them are necessary. Based on these ideas, the present study aims to test a natural and non-invasive method of cleaning historic textiles, which includes the use of a natural substance with a known antifungal effect (being traditionally used in various rural communities)-lye. The design of the study was aimed at examining a traditional women's shirt that is aged between 80-100 years, using artificial intelligence techniques for Scanning Electron Microscopy (SEM) imagery analysis and X-ray powder diffraction technique in order to achieve a complex and accurate investigation and monitoring of the object's realities. The determinations were performed both before and after washing the material with lye. SEM microscopy investigations of the ecologically washed textile specimens showed that the number of microorganism colonies, as well as the amount of dust, decreased. It was also observed that the surface cellulose fibers lost their integrity, eventually being loosened on cellulose fibers of cotton threads. This could better visualize the presence of microfibrils that connect the cellulose fibers in cotton textiles. The results obtained could be of real value both for the restorers, the textile collections of the different museums, and for the researchers in the field of cultural heritage. By applying such a methodology, cotton tests can be effectively cleaned without compromising the integrity of the material.

Karyotypes are characterized by traits such as chromosome number, which can change through whole-genome duplication and dysploidy. In the parasitic plant genus Cuscuta (Convolvulaceae), chromosome numbers vary more than 18-fold. In addition, species of this group show the highest diversity in terms of genome size among angiosperms, as well as a wide variation in the number and distribution of 5S and 35S ribosomal DNA (rDNA) sites. To understand its karyotypic evolution, ancestral character state reconstructions were performed for chromosome number, genome size, and position of 5S and 35S rDNA sites. Previous cytogenetic data were reviewed and complemented with original chromosome counts, genome size estimates, and rDNA distribution assessed via fluorescence in situ hybridization (FISH), for two, seven, and 10 species, respectively. Starting from an ancestral chromosome number of x  = 15, duplications were inferred as the prevalent evolutionary process. However, in holocentric clade (subgenus Cuscuta ), dysploidy was identified as the main evolutionary mechanism, typical of holocentric karyotypes. The ancestral genome size of Cuscuta was inferred as approximately 1C = 12 Gbp, with an average genome size of 1C = 2.8 Gbp. This indicates an expansion of the genome size relative to other Convolvulaceae, which may be linked to the parasitic lifestyle of Cuscuta . Finally, the position of rDNA sites varied mostly in species with multiple sites in the same karyotype. This feature may be related to the amplification of rDNA sites in association to other repeats present in the heterochromatin. The data suggest that different mechanisms acted in different subgenera, generating the exceptional diversity of karyotypes in Cuscuta ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ibiapino, García, Amorim, Baez, Costea, Stefanović and Pedrosa-Harand.)

Cuscuta is a cytogenetically diverse genus, with karyotypes varying 18-fold in chromosome number and 127-fold in genome size. Each of its four subgenera also presents particular chromosomal features, such as bimodal karyotypes in Pachystigma. We used low coverage sequencing of the Cuscuta nitida genome (subgenus Pachystigma), as well as chromosome banding and molecular cytogenetics of three subgenus representatives, to understand the origin of bimodal karyotypes. All three species, C. nitida, C. africana (2n = 28) and C. angulata (2n = 30), showed heterochromatic bands mainly in the largest chromosome pairs. Eighteen satellite DNAs were identified in C. nitida genome, two showing similarity to mobile elements. The most abundant were present at the largest pairs, as well as the highly abundant ribosomal DNAs. The most abundant Ty1/Copia and Ty3/Gypsy elements were also highly enriched in the largest pairs, except for the Ty3/Gypsy CRM, which also labelled the pericentromeric regions of the smallest chromosomes. This accumulation of repetitive DNA in the larger pairs indicates that these sequences are largely responsible for the formation of bimodal karyotypes in the subgenus Pachystigma. The repetitive DNA fraction is directly linked to karyotype evolution in Cuscuta., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)