bluuebunny/crossref_metadata_2025_split huggingface dataset:
The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example
Authors: La Peyre Megan K. , Sable Shaye , Marshall Danielle A. , Irwin Elise , Hanson Chad 
Published: August 2024

Abstract

Objective
Increasing reliance on numerical simulation models to help inform management and restoration choices benefits from careful consideration of critical early steps in model development. Along the northern coast of the Gulf of Mexico, the eastern oyster Crassostrea virginica fulfills important ecological and economic roles. Using the eastern oyster as an example, we draw on several recent frameworks outlining best practices for model development and application for restoration, conservation, and management.

Methods
We identify priority model questions, outline a conceptual ecological model (CEM) to guide numerical model development, and use this framework to identify uncertainties and research needs.

Result
The CEM uses a nested design, identifying explicit vital rates, processes, attributes, and outcomes for the species (oysters), population, and metapopulation (i.e., network of populations) levels in response to drivers of species, population, and metapopulation changes and changing environmental factors. Most management actions related to oyster restoration and harvest affect population attributes directly, but many coastal management actions and changes (i.e., climate change and coastal and water resource engineering) impact environmental factors that alter vital rates and attributes of oysters, populations, and metapopulations.

Conclusion
Investment in studies targeting individual oyster- and population-level multi-stressor responses (filtration, respiration, growth, and reproduction) and improving hydrodynamic and environmental models targeting drivers that influence metapopulation vital rates and attributes (i.e., connectivity and substrate persistence) would contribute to reducing uncertainties. Development of numerical models covering the entire oyster life cycle and connectivity of populations using hydrodynamic models of current and predicted conditions to provide key abiotic and biotic factors influencing larval movement, recruitment, and on-reef oyster vital rates would assist in balancing the goals of conservation, restoration, and fisheries management of this foundational estuarine species.
Active learning approaches in molecule pKi prediction
Authors: Kashafutdinova I. M. , Poyezzhayeva A. , Gimadiev T. , Madzhidov T. 
Published: August 2024

AbstractDuring the early stages of drug design, identifying compounds with suitable bioactivities is crucial. Given the vast array of potential drug databases, it′s feasible to assay only a limited subset of candidates. The optimal method for selecting the candidates, aiming to minimize the overall number of assays, involves an active learning (AL) approach. In this work, we benchmarked a range of AL strategies with two main objectives: (1) to identify a strategy that ensures high model performance and (2) to select molecules with desired properties using minimal assays. To evaluate the different AL strategies, we employed the simulated AL workflow based on “virtual” experiments. These experiments leveraged ChEMBL datasets, which come with known biological activity values for the molecules. Furthermore, for classification tasks, we proposed the hybrid selection strategy that unified both exploration and exploitation AL strategies into a single acquisition function, defined by parameters n and c. We have also shown that popular minimal margin and maximal variance selection approaches for exploration selection correspond to minimization of the hybrid acquisition function with n=1 and 2 respectively. The balance between the exploration and exploitation strategies can be adjusted using a coefficient (c), making the optimal strategy selection straightforward. The primary strength of the hybrid selection method lies in its adaptability; it offers the flexibility to adjust the criteria for molecule selection based on the specific task by modifying the value of the contribution coefficient. Our analysis revealed that, in regression tasks, AL strategies didn't succeed at ensuring high model performance, however, they were successful in selecting molecules with desired properties using minimal number of tests. In analogous experiments in classification tasks, exploration strategy and the hybrid selection function with a constant c<1 (for n=1) and c≤0.2 (for n=2) were effective in achieving the goal of constructing a high‐performance predictive model using minimal data. When searching for molecules with desired properties, exploitation, and the hybrid function with c≥1 (n=1) and c≥0.7 (n=2) demonstrated efficiency identifying molecules in fewer iterations compared to random selection method. Notably, when the hybrid function was set to an intermediate coefficient value (c=0.7), it successfully addressed both tasks simultaneously.
On the optimality of voronoi‐based column selection
Authors: Emelianenko Maria , Oldaker Guy B. 
Published: August 2024

AbstractWhile there exists a rich array of matrix column subset selection problem (CSSP) algorithms for use with interpolative and CUR‐type decompositions, their use can often become prohibitive as the size of the input matrix increases. In an effort to address these issues, in earlier work we developed a general framework that pairs a column‐partitioning routine with a column‐selection algorithm. Two of the four algorithms presented in that work paired the Centroidal Voronoi Orthogonal Decomposition (CVOD; Centroidal Voronoi Tessellation Based Proper Orthogonal Decomposition Analysis, 2003, 137–150) and an adaptive variant (adaptCVOD) with the Discrete Empirical Interpolation Method (DEIM; SIAM J. Sci. Computer. 38 (2016), no. 3, A1454–A1482). In this work, we extend this framework and pair the CVOD‐type algorithms with any CSSP algorithm that returns linearly independent columns. Our results include detailed error bounds for the solutions provided by these paired algorithms, as well as expressions that explicitly characterize how the quality of the selected column partition affects the resulting CSSP solution. In addition to examples involving matrix approximation, we test several of our partition‐based constructions on tasks commonly encountered in model order reduction (MOR).
An enhanced approach for power quality improvement of unified power quality conditioner connected wind energy conversion system
Authors: Sultana Shaziya , Salma Umme 
Published: August 2024

AbstractThis manuscript proposed a hybrid system for enhancing the control strategy of a unified power quality conditioner connected to a wind energy conversion system. The proposed method is combined with honey badger algorithm (HBA) and reptile search algorithm (RSA). Therefore, it is known as the Enhanced HBA (EnHBA) technique. The key aim of the EnHBA technique is to alleviating the PQ issue exhibited in the WECS. The EnHBA approach is utilized in the non‐linear load condition to find the best solutions from the available searching space in light of the goal function and generates the output. During the load variation conditions the EnHBA technique manages the loss of power, total harmonic distortion (THD), and voltage instability issue respectively. In this way, the PQ system performances improved and moreover, the various qualities decreased with the support of the EnHBA method. The EnHBA techniques' performance is validated through the MATLAB platform and the implementation is calculated with the existing techniques. The method EnHBA technique displays better outcomes in all approaches like, particle swarm optimization, whale optimization algorithm and singular spectrum analysis (SSA). The proposed method's voltage sag and swell are lowered to 14% and 15%, respectively. The THD of the En HBA method is 10%, which is lesser than other existing PSO, WOA, and SSA methods.
Ultrasound‐assisted liquid phase exfoliation of boron nitride nanosheets as fillers for polyacrylate pressure‐sensitive adhesives with enhanced thermal conductivity
Authors: Liu Yuan , Zhang Jimin , Chen Shengli , Liu Yingchun , Xie Yanling , Cao Chaochao , Qu Xiongwei 
Published: August 2024

AbstractHexagonal boron nitride (h‐BN) is widely used as a filler to improve the thermal conductivity of polymers due to the high thermal conductivity, electrical insulation, and chemical stability. However, the small lateral‐size and poor compatibility limit h‐BN's performances and applications in thermal management. Here, boron nitride nanosheets (BNNSs) were prepared by liquid‐phase ultrasonic exfoliation using isopropanol (IPA) as solvent. Specifically, the BNNSs obtained by ultrasonication for 8 h with an initial concentration of h‐BN of 8 mg/mL have the best exfoliation effect and a high yield of 19.8%, showing a large lateral‐size of 1–2 μm and an ultra‐thin thickness. Then, the resulting BNNSs can be modified by grafting silane coupling agent of KH560 (m‐BNNSs), their micromorphology and chemical composition are characterized by various microscopies and spectrometers. Subsequently, polyacrylate pressure‐sensitive adhesives (PSAs) composites are prepared using m‐BNNSs as a thermally conductive filler by UV bulk polymerization, their thermal conductivity can be greatly improved by 250% compared with that of pure PSAs. For comparison, the thermal conductivity of m‐BNNSs/PSAs composites with filler content of 25 wt% is as high as 0.4382 W/(m K), which is 1.6 times higher than that of h‐BN/PSAs composites. In addition, the incorporation of BNNSs will improve the thermal stability, hardness, and 180° peeling force of the PSAs composites, which will stimulate the practical application of PSAs materials.
Comprehensive analysis of chemical and enantiomeric stability of terpenes in Cannabis sativa L. flowers
Authors: Raeber Justine , Bajor Bryan , Poetzsch Michael , Steuer Christian 
Published: August 2024

AbstractObjectiveCannabis sativa L. is renowned for its medicinal and recreational uses. With the increasing global legalization of C. sativa L.‐based products for medicinal purposes, there is a growing need for well‐characterized products. While the stability of cannabinoids such as tetrahydrocannabinol and cannabidiol is well understood, information on the chemical and enantiomeric stability of terpenes remains scarce. This is despite the fact that terpenes are also thought to have pharmacological activity and may contribute to the overall effect of C. sativa L.MethodsTo address these challenges, four analytical methods based on chiral, polar, and apolar gas chromatographic separation combined with either MS or FID detection were developed and validated. These methods successfully separated and quantified a total of 29 terpenes, including 13 enantiomers and 5 diastereomers specific to C. sativa L. Furthermore, terpenes and authentic C. sativa L. flowers and extracts were subjected to UV and heat treatments to observe potential degradation reactions over time.ResultsEach terpene generates a unique pattern of degradation products resulting in a diverse array of oxidation and cyclization products. P‐cymene was identified as a major product of terpene aging. Notably, no enantiomeric conversion was detected, suggesting that the formation of (−)‐α‐pinene in cannabis extracts, for example, originates from other terpenes.ConclusionTerpenes have different degradation rates, even though they are structurally similar. In addition, cultivar‐ and growth‐condition‐specific enantiomeric ratios were observed in C. sativa L., confirming that enantiomer production is species‐specific and has to be considered for therapeutical applications.
Characterization, processing, and modeling of industrial recycled polyolefins
Authors: Kazmer David O. , Nzeh Sixtus O. , Shen Beijun , Elbert David C. , Nagarajan Ramaswamy , Sobkowicz‐Kline Margaret , Nguyen Thao D. 
Published: August 2024

AbstractThis study aims to establish a systematic approach for characterizing recycled polyolefins of unknown composition, with a specific focus on predicting their performance in film extrusion. We explore various characterization techniques, including differential scanning calorimetry (DSC), Fourier‐transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and rheometry to assess their effectiveness in identifying the polyethylene (PE) fractions within polypropylene (PP) recyclates. By integrating experimental data with modeling techniques, we aim to provide insights into the predictive capabilities of these techniques in determining processing behaviors. The research highlights the superior fidelity of DSC in predicting the relative fraction and type of PE in a PP recyclate. FTIR is also identified as a high‐fidelity approach, albeit requiring application‐specific calibration. TGA, capillary, and oscillatory rheometry are recognized for their ability to distinguish between grades of recycled polyolefins but provide aggregate behaviors rather than detailed constituent information. 3D flow simulation of the cast film extrusion investigated the effect of the viscosity characterization method, non‐isothermal assumption, and process settings but could not fully replicate the observed variations in the cast film processing of two industrial polyolefins with similar melt flow rates and viscosity behaviors. This underscores the practical challenge of predicting processing issues prior to actual processing, necessitating reliance on reliable instrumentation suites and human expertise for diagnosing and remedying variations.Highlights
Two industrial recycled polypropylene materials having similar melt flow rates exhibit drastically different cast film processing behaviors.
DSC and FTIR provide reasonable approaches for identifying constituent materials.
Modeling of the melt viscosities characterized by capillary and parallel plate rheology suggests that viscosity variations relative to the power‐law behavior assumed in the coat hanger die design is a predominant driver of cast film instabilities.
Influence of γ‐irradiation dose on the mechanical and tribological properties of fluoroelastomer
Authors: Xiao Yusheng , Zhang Fan , Wei Renbing , Qin Dong , Tang Zhaohua , Bao Yu , Cai Zhenbing 
Published: August 2024

AbstractFluoroelastomer (FKM) undergo various degrees of degradation in a gamma‐irradiated environment, leading to changes in their mechanical and tribological properties. In this paper, changes in the properties of FKM were investigated for six different doses. Fourier transform infrared‐atomic absorption spectroscopy (FTIR‐ATR) results show that FKM samples undergo dehydrofluorination and oxidation reactions during irradiation, resulting in the formation of C=C, C=O, and ‐OH functional groups. The results of the swelling test showed that the degree of cross‐linking of the FKM specimens increased with increasing irradiation dose. Mechanical test results show that the fracture mechanism of FKM specimens gradually evolves from ductile fracture to brittle fracture with the increase of irradiation dose. Its tensile strength reaches its maximum at an irradiation dose of 1000 kGy, and the modulus of elasticity becomes larger with increasing irradiation dose. The results of wear tests show that the average coefficient of friction of FKM specimens first decreases, reaches a minimum at 500 kGy, and then gradually increases. The amount of wear increases with increasing irradiation dose. The wear mechanism of FKM specimens is abrasive wear at 0–500 kGy, adhesive wear at 1000 and 2000 kGy, and fatigue wear at 3000 kGy.Highlights
FKM was irradiated by gamma‐ray with a total dose of 3000 kGy.
Dehydrofluorination and oxidation reactions occur during irradiation.
Increased cross‐linking leads to changes in mechanical properties.
The wear mechanism of FKM with different doses has been investigated.
Ten golden rules for restoration to secure resilient and just seagrass social‐ecological systems
Authors: Unsworth Richard K. F. , Jones Benjamin L. H. , Bertelli Chiara M. , Coals Lucy , Cullen‐Unsworth Leanne C. , Mendzil Anouska F. , Rees Samuel C. , Taylor Flo , Walter Bettina , Evans Ally J. 
Published: August 2024

Societal Impact StatementSeagrass meadows are a globally important habitat subject to significant loss. As efforts to restore these sensitive habitats are hampered by their high cost and low levels of reliability, rigorous guidance is required to improve effectiveness and ensure they are cost‐effective. Here, we define 10 golden rules for how we can undertake seagrass restoration. We do this by considering that for seagrass restoration to be successful, it needs to take place with people and not against people. The framework we present aims to direct efforts for seagrass restoration that are holistic and achieve broad goals for people, biodiversity and the planet.SummaryThe world has lost a significant proportion of its seagrass, and although glimmers of hope for its recovery exist, losses and degradations continue. First and foremost, evidence highlights the need to put the world on a global pathway to seagrass net gain. Achieving this outcome requires that conservation of what remains is a priority, but reaching net gain requires seagrass coverage to increase at rates unlikely to be achieved naturally; large‐scale active restoration is required to fill this gap. Novel finance mechanisms aligned to the climate emergency and biodiversity crises are increasingly leading to larger scale restoration projects. However, no clear framework exists for developing or prioritising approaches. With seagrass restoration expensive and unreliable, rigorous guidance is required to improve effectiveness and ensure it is cost‐effective. Building on evidence from terrestrial and marine sources, here, we apply the ‘10 golden rules’ concept, first outlined for reforestation and later applied to coral reefs, to seagrass restoration. In doing so, we follow international standards for ecological restoration and view seagrass restoration in a broad context, whereby regeneration can be achieved either by planting or by enhancing and facilitating natural recovery. These rules somewhat differ from those on reforestation and coral reef restoration, principally due to the relative immaturity of seagrass restoration science. These 10 golden rules for seagrass restoration are placed within a coupled social‐ecological systems context, and we present a framework for conservation more broadly, to achieve multiple goals pertaining to people, biodiversity and the planet.
Nutritional status in the era of highly effective CFTR modulators
Authors: Bass Rosara , Alvarez Jessica A. 
Published: August 2024

AbstractAdvances in cystic fibrosis (CF) diagnostics and therapeutics have led to improved health and longevity, including increased body weight and decreased malnutrition in people with CF. Highly effective CFTR modulator therapies (HEMT) are associated with increased weight through a variety of mechanisms, accelerating trends of overweight and obesity in the CF population. Higher body mass index (BMI) is associated with improved pulmonary function in CF, yet the incremental improvement at overweight and obese BMIs is not clear. Improvements in pulmonary health with increasing BMI are largely driven by increases in fat‐free mass (FFM), and impact of HEMT on FFM is uncertain. While trends toward higher weight and BMI are generally seen as favorable in CF, the increased prevalence of overweight and obesity has raised concern for potential risk of traditional age‐ and obesity‐related comorbidities. Such comorbidities, including impaired glucose tolerance, hypertension, cardiac disease, hyperlipidemia, fatty liver, colon cancer, and obstructive sleep apnea, may occur on top of pre‐existing CF‐related comorbidities. CF nutrition recommendations are evolving in the post‐modulator era to more individualized approaches, in contrast to prior blanket high‐fat, high‐calorie prescriptions for all. Ultimately, it will be essential to redefine goals for optimal weight and nutritional status to allow for holistic health and aging in people with CF.
Improving growth in infants with CF
Authors: Gabel Megan E. , Gaudio Rachel E. , Shaikhkhalil Ala K. 
Published: August 2024

AbstractCystic fibrosis (CF) results in chronic pulmonary infections, inflammation, pancreatic insufficiency, and multiple gastrointestinal manifestations. Malnutrition and poor growth are hallmarks of CF, and strongly associated with poor outcomes. Through newborn screening, many infants can be diagnosed within a few days of life, which allows for early initiation of nutritional counseling and close clinical follow‐up. Obstacles to growth for infants with CF start in utero, as newborns with CF can have a lower birth weight than the general population. Improving infant growth has been linked to improved clinical outcomes and survival. It remains a top priority and challenge for caregivers and healthcare teams. An interdisciplinary approach, including registered dietitian and social work support, is essential to optimize health for infants with CF. Remaining barriers to normalcy include deficits in linear growth, lack of accurate nutrition biomarkers, persistence of inequities related to social determinant of health, particularly in the global CF community.
Early detection of hepatobiliary involvement in cystic fibrosis: Biomarkers, radiologic methods, and genetic influences
Authors: Sankararaman Senthilkumar , Freeman A. Jay 
Published: August 2024

AbstractCystic fibrosis‐related hepatobiliary involvement (CFHBI) is a term used to describe a spectrum of hepatobiliary involvement ranging from a transient elevation of transaminase levels to advanced cystic fibrosis‐associated liver disease (aCFLD). While CFHBI is common among people with cystic fibrosis (PwCF), aCFLD is rare impacting only approximately 5%–10% of the CF population. After respiratory/cardiorespiratory issues and transplant‐related complications, aCFLD is now the 4th leading cause of mortality among PwCF. Additionally, aCFLD is an independent predictor of all‐cause mortality and is associated with significant morbidity. Despite this recognition, our ability to predict those patients at greatest risk for aCFLD, identify early aCFLD, and monitor the incremental progression of CFHBI is lacking. Here, we review the strengths and weaknesses of the common biomarkers and imaging modalities used in the evaluation and monitoring of CFHBI, as well as the current understanding of genetic modifiers related to aCFLD.
Evolving data on risk and current screening recommendations for colorectal cancer in cystic fibrosis: Pre‐ and posttransplant
Authors: Raza Zain , Islam Bianca N. , Hachem Christine Y. , Cummings Linda C. 
Published: August 2024

AbstractAdvances in treatment for cystic fibrosis (CF), including cystic fibrosis transmembrane conductor regulator (CFTR) modulators, have ushered in an era where patients with CF have much longer life expectancies. This shift in life expectancy demands increased attention to diseases of aging in patients with CF. A notable complication of CF is early‐onset colorectal cancer (CRC), which is especially prevalent in patients with severe mutations and after transplant. CFTR acts as a tumor suppressor gene based on knockout models. Lack of CFTR expression promotes carcinogenic processes such as intestinal inflammation and deleterious gut microbiome changes. The consensus Cystic Fibrosis Foundation recommendations advocate treating this population as a high‐risk group, using a colonoscopy‐only screening strategy starting at age 40 in patients without transplant and at age 30 after transplant. Screening should be considered every 5 years if negative and every 3 years or sooner for patients with adenomatous polyps. Future research will determine the role of noninvasive CRC screening tools in this population, as well as the effects of CFTR modulators on the risk of developing CRC.