bluuebunny/crossref_metadata_2025_split huggingface dataset:
Why mow?: A review of the resulting ecosystem services and disservices from mowing turfgrass
Authors: Patton Aaron J. 
Published: October 2024

AbstractTurfgrasses are those grasses that tolerate frequent mowing. The act of mowing turfgrasses, primarily lawn mowing, has received much negative attention primarily due to its labor requirement and the resulting mower emissions. This paper provides a comprehensive review of the benefits and drawbacks of mowing grasses, specifically turfgrasses used on lawns, parks, golf courses, and sports fields, using an ecosystem services and disservices framework. Discussed is the challenge of creating a “one‐size‐fits‐all” approach to selecting the best mowing management practices and sociocultural tensions that exist related to lawn mowing. Discussion also includes the benefits and value gained from mowing turfgrass and strategies to mitigate ecosystem disservices that result from mowing.
A deep learning‐based channel estimation and joint adaptive hybrid beamforming approach for mm‐wave massive MIMO with group‐of‐subarrays
Authors: Srinivas Ch V V S , Borugadda Somasekhar 
Published: October 2024

SummaryMillimeter‐wave massive multiple‐input‐multiple‐output (MIMO) is a wireless communication that enables communication at extremely high data rates. It is widely used to expand communication bandwidth to improve spectral and energy efficiency. The mm‐wave system is usually based on the radio frequency (RF) chain. Beamforming is used to minimize the interface signal and maximize each user's received signal power. The hybrid beamforming method uses channel estimation and beam generation techniques that improve overall performance and save energy. There are various limitations and disadvantages arising from different techniques of the MIMO system. Hence, the proposed model is introduced to enhance the performance and maximize the spectral and energy efficiency. Initially, the optimal RF chain selection and channel optimization are done by the differential evolution firefly‐assisted optimized channel compression‐reconstruction (DEF_OCCR) network. In this research, the RF chain selection process is done using hybrid differential evolution firefly optimization. A robust autoencoder‐driven deep learning model is proposed for channel estimation after RF chain selection. Finally, the deep learning convolutional joint adaptive hybrid beamforming network (DConvHB) is used for beamforming to maximize spectral efficiency. The overall performance of this work is analyzed using several existing models to describe its superiority. The average system throughput is 12.85 bits, and the spectral efficiency of the proposed model is 5 bits for 10 dB and 32.18 bits for 13 dB. The proposed energy efficiency model is 1.73 bits and 4.96 bits for 10 dB.
Habitat area more consistently affects seagrass faunal communities than fragmentation per se
Authors: Yarnall Amy H. , Yeager Lauren A. , Lopazanski Cori , Poray Abigail K. , Morley James W. , Hurlbert Allen H. , Fodrie F. Joel 
Published: October 2024

AbstractSeminal ecological theories, island biogeography and the single large or several small (SLOSS) reserve debate, examine whether large contiguous habitats conserve biodiversity better than multiple smaller patches. Today, delineating the ecological effects of habitat area versus configuration in a fragmentation context remains difficult, and often confounds efforts to understand proximate and ultimate drivers of community change in response to habitat alteration. We examined how the major components of fragmentation, habitat division versus area loss, independently influence faunal communities using landscapes constructed from artificial seagrass at scales relevant for juvenile estuarine nekton. We deployed 25 unique, 234‐m2 landscapes designed along orthogonal axes: habitat percent cover (i.e., area) and fragmentation per se (i.e., patchiness) to examine their effects on faunal density, community composition, and probability of bait‐assay consumption. Faunal sampling occurred in both artificial seagrass and interspaced sandflat matrix. We also examined whether larval‐settler density drove faunal density patterns across landscapes. Further, we assessed the relative importance of landscape‐scale parameters versus fine‐scale complexity–canopy height and epiphyte biomass–in determining faunal densities. We most consistently observed increasing epibenthic fish and macroinvertebrate density with increasing seagrass percent cover. Fragmentation per se only negatively affected epibenthic faunal density within the matrix at low seagrass coverage. Bait consumption increased with seagrass cover, suggesting larger habitats are relative foraging hotspots. Alternatively, benthopelagic fish density was unaffected by habitat parameters, reflecting lower seagrass reliance, or increased matrix tolerance. Community compositions did not vary across landscapes, suggesting that abundant species used landscapes indiscriminately. Finally, the relative importance of habitat parameters shifted across faunal guilds and life stages. Landscape percent cover most affected epibenthic faunal density, but not benthopelagic fish density, and neither pattern was related to settler density. Further, only fine‐scale complexity influenced settler densities. Collectively, our results indicate habitat area is a primary, positive driver of faunal densities and generalist consumption, and therefore should be prioritized in seagrass conservation. However, sampling across spatial scales and habitat types revealed nuances in habitat use patterns among faunal guilds and life stages that were not solely area‐dependent, illustrating that a variety of landscape configurations support essential nursery functions.
Harvest sustainability assessments need rethinking under climate change: A ringed seal case study from Svalbard, Norway
Authors: Nater Chloé R. , Lydersen Christian , Andersen Magnus , Kovacs Kit M. 
Published: October 2024

AbstractThroughout the Arctic, ice‐affiliated marine mammals constitute local subsistence resources but detrimental effects of declines in their sea ice habitats create a need for harvest sustainability assessments in light of climate change. At the same time, empirical data required for thorough population analysis of these species are often sparse at best, as illustrated by the focal species in this study, ringed seals in Svalbard: the last population survey took place two decades ago (2002–2003), demographic data are limited to age, sex, and reproductive status of a small subset of shot individuals, and harvest reporting is patchy and incomplete. Data sparsity is one of the main reasons why potential biological removal (PBR) became a commonly used tool for assessing sustainability of marine mammal harvests. Herein, we calculated PBR for Svalbard ringed seals using both recommended default parameters and population‐specific parameters obtained from an integrated population model (IPM). PBR estimates were highly uncertain, suggesting the number of sustainably harvestable individuals could lie anywhere between 0 and 91, with a substantial chance of any harvest being unsustainable under current environmental conditions and trends. Subsequent population viability analyses (PVAs) further confirmed that the current harvest was likely unsustainable, even in a scenario in which sea ice conditions would not deteriorate (and therefore lower pup survival) further. However, uncertainty in population projections was high, and forecasts thus not ideal for formulating management advice. Better forecasts will require more frequent population surveys and obtaining more knowledge regarding the links between vital rates and environmental conditions, both of which may be facilitated by the adoption of novel technology (e.g., drone monitoring, genetic studies). The modeling framework created in this study can be readily updated with new data as they become available, and can serve as a tool for adaptive management of this and other marine mammal populations.
The roles and unexplored potential of policy experimentation in climate adaptation governance: A systematic literature review
Authors: Cosoveanu Flavia Simona , Hegger Dries , Mees Heleen , Buijs Jean‐Marie , Terpstra Teun , Driessen Peter P. J. 
Published: October 2024

AbstractPolicy experimentation has emerged globally as a novel governance approach to address complex socio‐environmental problems. In the climate adaptation literature, policy experiments that test technical and governance innovations on a small scale in real‐world conditions are increasingly utilized to explore new pathways for climate adaptation. However, there is a lack of empirical evidence on how policy experiments lead to transformative change in climate adaptation governance, particularly regarding their role as a change strategy. This systematic literature review aims to thoroughly investigate the topic by mapping the empirical characteristics of policy experiments, their role and their outcomes. An existing analytical framework was adapted to fulfill this objective by qualitatively and quantitatively analyzing 27 empirical papers. The findings reveal that policy experiments in climate adaptation often address multiple climate hazards, sectors and actors, yet they are spatially and temporally limited, being predominantly located in Europe. Moreover, the study highlights the transformative potential of policy experiments in climate adaptation governance, emphasizing their effectiveness in testing technical and governing innovations, as well as implementing adaptation policies. Policy experiments predominantly contribute to social learning rather than direct policy changes, requiring specific strategies to upscale the knowledge generated. We conclude the paper with a research agenda that stresses the need for more cumulative and comparative (post)assessments of climate adaptation experiments. This is important given the potential of policy experiments as governing approaches in the advancement of climate adaptation.
Rapid and General Access to α‐Halogenated Carbonyl Compounds Using Amidine Halide Salts as Halogen Sources under Mild Conditions
Authors: Li Lewan , Luo Mengxiang , Liu Shuntian , Lv Jian , Zeng Jie , Yan Qiongjiao , Liao Jie , Wang Haifeng , Gu Shuangxi 
Published: October 2024

AbstractRapid and efficient construction of α‐haloketones with diazo compounds and amidine ⋅ HX (X=Cl, Br, I) salts as halogen sources has been recognized as a simple and practical strategy. The reaction exhibits a broad scope and scalability, thereby enabling synthesis of a broad spectrum of functionally orchestrated α‐haloketones under mild and metal‐free conditions in a short time. Control experiments established the involvement of triffate 10 in the mechanism.
Feasibility and design of nonlinear negative‐stiffness isolating approach for solid‐rocket‐motor‐type structures
Authors: Wang Yanchao , Gao Jie , Wang Xueren , Zhao Zhipeng , Zhang Yanshen 
Published: October 2024

AbstractSolid rocket motor (SRM)‐type structures are popular due to their reliability, considering that service safety during transportation can be improved by applying advanced vibration control technologies. In this study, a negative‐stiffness‐enhanced isolation system (NSeIS) with appropriately designed linear and nonlinear properties was developed to vertically isolate SRMs subjected to transportation‐ and deployment‐induced vibrations. The NSeIS design, based on the combination of a negative‐stiffness device and vertical isolator, involved a clear mechanical model, physical realization, and mechanical properties. Parametric analyses were performed on a typical SRM controlled with a linear and nonlinear NSeIS and a conventional isolation system. Subsequently, a feasible parameter domain and design recommendations were deduced. Finally, design cases for the SRM for time‐domain verification were considered. The results revealed that the NSeIS offers a flexible and enhanced isolating effect through the parallel arrangement of the negative‐stiffness device and conventional isolators. For the motor‐type structure, NSeIS ensures marked enhancements in performance and multiple levels of mitigation effects. Thus, compared with a conventional isolator with the same damping, NSeIS achieves a more substantial negative‐stiffness effect for a large displacement response range owing to its nonlinear property. NSeIS can isolate more vibration‐induced energy, thereby suppressing the interface Mises stress, which is essential for SRM‐type structures.
Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform
Authors: Joga S Ramana Kumar , SaiPrakash Chidurala , Velpula Srikanth , Mohapatra Alivarani , Kambo Theophilus A. T. 
Published: October 2024

ABSTRACTPhotovoltaic (PV) arrays have gained significant attention in recent years due to their potential for sustainable energy generation. However, the reliable operation of PV arrays is crucial for optimal performance and long‐term durability. The early detection of faults in PV arrays is vital to prevent further damage, improve maintenance strategies, and ensure uninterrupted energy production. In this study, we propose a novel fault detection method based on Time Frequency Analysis (TFA) using the Scaling Basis Chirplet Transform (SBCT). In this proposed fault detection method, PV array signal is decomposed into a set of chirplets using the SBCT. The chirplets represent localized time‐frequency components that can capture the dynamic behavior of the PV array signal. To evaluate the effectiveness of the proposed method, extensive simulations and experiments are conducted using real‐world PV array data. The SBCT with combination of various machine learning algorithms is proposed to detect faults in PV array. SBCT in combination with Support Vector Machine, Decision Tree, Random Forest, and ANN classifiers are able to detect faults in PV array with 99%, 98.5%, 99.2%, and 99.5% accuracies in no shading condition and 88%, 85%, 89%, and 89.5% accuracies in severe shading condition. The proposed method achieves high accuracy and robustness in detecting various types of faults in PV arrays, even in the presence of noise and uncertainties. The proposed fault detection method using TFA based on the SBCT offers a promising solution for efficient and reliable fault detection in PV arrays. It enables early fault detection, facilitating timely maintenance and minimizing energy losses. The proposed approach can contribute to enhancing the overall performance, reliability, and lifespan of PV arrays, thereby advancing the adoption of renewable energy sources and promoting sustainable development.
Novel lattice Boltzmann method for simulation of strongly shear thinning viscoelastic fluids
Authors: Kellnberger Richard , Jüngst Tomasz , Gekle Stephan 
Published: October 2024

AbstractThe simulation of viscoelastic liquids using the Lattice–Boltzmann method (LBM) in full three dimensions remains a formidable numerical challenge. In particular the simulation of strongly shear‐thinning fluids, where the ratio between the high‐shear and low‐shear viscosities is large, is often prevented by stability problems. Here we present a novel approach to overcome this issue. The central idea is to artificially increase the solvent viscosity which allows the method to benefit from the very good stability properties of the LBM. To compensate for this additional viscous stress, the polymer stress is reduced by the same amount. We apply this novel method to simulate two realistic cell carrier fluids, methyl cellulose and alginate solutions, of which the latter exhibits a viscosity ratio exceeding 10,000.
Progress in essential oil extraction and their applications in food packaging and preservation
Authors: Borah Ridhi , Purkayastha Manashi Das , Malakar Madhusmita , Mukherjee Avik , Roy Arnab , Kumar Santosh 
Published: October 2024

AbstractEssential oils (EOs) are secondary metabolites synthesised by many aromatic plants, which have good antimicrobial and antioxidant activities making them popular functional agents for food preservation and packaging applications. In recent years, novel extraction techniques, such as super critical fluid extraction, pulsed electric field assisted extraction and ultrasound assisted extraction have been explored as alternatives to the conventional solvent‐based extraction methods. This review mainly discusses on recent progresses in sustainable extraction of essential oil (EO) from aromatic plants and food processing wastes and their functional properties, and applications in food preservation have also been summarised. Sustainable extraction techniques yield better‐quality EO due to low temperature and short time process compared to the conventional extraction. Despite efficacy of EOs as good active agents, their low water solubility, volatile nature, strong flavour, and susceptibility to food processing parameters are major challenges against their applications in food. These challenges can be mitigated by advanced techniques such as encapsulation and nanoemulsification of EO, which provide dual functions of enhanced applicability and improved functional properties. Incorporation of EO in the biopolymer‐based films and coatings can open avenues for sustainable food packaging and preservation.
Influence of Aloe Vera Gel and Safe Salts on Storage Quality of Minimally Processed Carrot
Authors: Dey Swagata , Ali Mohammad , Hasan Md. Fakhrul , Labib Litun Ahmed 
Published: October 2024

ABSTRACTThis experiment investigated the impact of aloe vera gel and safe salts on the physical quality and physicochemical properties of minimally processed carrots during storage, aiming to determine the most effective edible coating postharvest treatment. The experiment employed a Completely Randomized Design (CRD) with three replications. Results indicated significant (p ≤ 0.01) effects of various treatments on the physical quality and physicochemical properties of carrots compared to untreated ones. Freshly harvested carrots were subjected to different treatments, including a control (T1), 30% aloe vera gel (T2), 1% NaCl (T3), and 1.5% NaHCO3 (T4), combinations thereof, such as 30% aloe vera gel with 1% NaCl (T5) or 1.5% NaHCO3 (T6), and 1% NaCl with 1.5% NaHCO3 (T7), and a combination of 30% aloe vera gel with 1% NaCl and 1.5% NaHCO3 (T8). Among the treatments, the combination of 30% aloe vera gel and 1% NaCl (T5) exhibited the most promising results after nine days of storage, with the lowest weight loss (1.19%), highest firmness (3.80 N), total soluble solids (TSS) content (8.40%), titratable acidity (0.477%), ascorbic acid content (9.02 mg/100 g FW), anthocyanin content (28.84 μg/g FW), phenol content (4.278 mg/100 g FW), and total sugar content (13.32%). This treatment effectively protected carrots from undesirable color, texture, and flavor changes during storage. The utilization of natural‐source‐based edible coatings containing health‐promoting additives presents a viable strategy to enhance both the internal and external qualities of minimally processed carrots. Overall, the edible coating comprising 30% aloe vera gel and 1% NaCl emerges as a promising approach for preserving the quality of minimally processed carrots.
Effect of anesthetic technique on antitumor immunity in patients undergoing surgery for gall bladder cancer: A prospective randomized comparative study
Authors: Sharma Ankit , Kumari Lata , Ratre Brajesh Kumar , Khan Maroof Ahmad , Kumar Sunil , Deepak Rakesh Kumar , Kumar Vinod , Gupta Nishkarsh , Garg Rakesh , Mishra Seema , Bhatnagar Sushma , Bharati Sachidanand Jee 
Published: October 2024

AbstractThere is a paucity of literature regarding the effect of anesthetic techniques on antitumor immunity, especially in gall bladder malignancies. We designed a study to compare the effect of propofol‐based total intravenous anesthesia and sevoflurane‐based general anesthesia—on antitumor immunity, including tumor growth factor‐β (TGF‐β), T‐helper cell profile, and inflammatory markers. A pilot prospective randomized trial was conducted in 64 patients undergoing surgery for gall bladder malignancy under general anesthesia in a tertiary specialty cancer hospital. Adult cancer patients of ASA physical status I‐III fulfilling the inclusion criteria were randomized to either group S (sevoflurane‐based general anesthesia) or group T (propofol‐based total intravenous anesthesia). Preoperative (morning of surgery) and postoperative (24 h and 1 month after surgery) blood samples were obtained. Demographic profile and preoperative parameters were comparable between both groups. There was a statistically significant difference in the postoperative value of TGF‐β (higher in group T). There was a statistically significant difference in postoperative interleukin‐17A value (indicative of TH17 cells), and it was found to be higher in group S. Propofol‐based TIVA increases serum TGF‐β levels. At the same time, Sevoflurane modulates T‐helper cells‐based immunity to increase TH17 cells in patients with gall bladder cancer. Multiple larger studies will be required to validate the results and provide useful recommendations.
Engaging Indigenous communities in research to inform practice: The multisite implementation evaluation of Tribal home visiting
Authors: Salvador Melina , Abrahamson‐Richards Tess , Lyon Kate , Whitesell Nancy Rumbaugh 
Published: October 2024

AbstractCommunity engagement (CE) is widely acknowledged as a way to enhance the ethics, rigor, and impact of research. Additionally, CE is a demonstrated way to integrate Indigenous and colonial (western) research systems. For these reasons and others, designers of the Multi‐site Implementation Evaluation of Tribal Home Visiting (MUSE) used a community‐engaged approach to study the implementation of federally funded home‐visiting programs across 17 Indigenous communities throughout the United States. This paper describes MUSE's community‐engaged approach and its practical applications from the perspective of the MUSE study team. The paper highlights key outcomes attributable to CE, addresses barriers to CE, and details responses to these barriers and their impacts. Adding to the rich evidence base demonstrating the value of community‐engaged approaches, MUSE demonstrates that in‐depth CE is feasible and valuable in multisite studies done in partnership with Indigenous communities.