bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatiotemporal evolution of growing‐season vegetation coverage and its natural‐human drivers in the Yellow River Basin, China
Authors: Zang Yongge , Yu Bowei , Wu Chunsheng , Zhao Zhonghe 
Published: August 2023

AbstractThe Yellow River Basin (YRB) is an important ecological security barrier in northern China, where vegetation has undergone rapid changes under the high‐intensity anthropological activities and ongoing climate change in recent decades. This study focused on the spatiotemporal evolution of fractional vegetation cover (FVC) and the driving factors during the growing season in different sub‐basins of the YRB between 2000 and 2020. The trend analysis was employed to examine the FVC spatiotemporal changes, and the geographical detector model (GDM) and the geographically weighted regression (GWR) model were utilized to explore spatial heterogeneity of natural‐human drivers on FVC. The 21‐year average FVC was 0.5780 in the growing season in the YRB, and the southeast region was greater than the northwest region. The FVC exhibited a fluctuating and rising trend of 0.44% yr−1 in the whole YRB from 2000 to 2020, and areas with improved FVC were 36.40% more than those with degraded FVC. The dominant factors influencing the growing‐season FVC were precipitation and temperature, followed by elevation and human activity intensity. The influence of natural factors on FVC showed a decreasing trend, whereas human factors exhibited an increasing trend. Natural factors promoted vegetation growth in most area of the YRB, especially in the northwest, whereas human factors had more negative effects, except for the middle parts of the basin. The spatial differentiation analyses of FVC and driving factors provide scientific guidance for ecological restoration and sustainable development in the YRB.
OPENING DOORS: FRANCES HESSELBEIN’S LEADERSHIP, COURAGE, IMAGINATION, AND VISION
Authors: Haas Elizabeth 
Published: August 2023

AbstractThe author had a long history with Frances Hesselbein, going back to Frances’s years as CEO Girl Scouts of the USA. She knew her through good times and exceedingly challenging ones. She writes, “Frances often said, ‘leadership is who you are, not what you do;’ but what she did at the vanguard of key social movements in the second half of the last century and the first two decades of this century made a real difference to our society. She helped make us who we are.” The author also includes comments made two decades ago during her interview with the late Tom Moran, when he was Chairman of Mutual of America, an organization Frances worked with closely, with offices in its headquarters building. Moran recounted “… the outstanding example Frances set. There is no way to measure the inspiration she provides others to give that extra effort to make the world a better place to live in and share.”
Functional Microneedle Patch for Wound Healing and Biological Diagnosis and Treatment
Authors: Wang Ye , Zong Qida , Wu Huiying , Ding Yan , Pan Xi , Fu Bo , Sun Wei , Zhai Yinglei 
Published: August 2023

AbstractWound healing, especially chronic wounds, has been one of the major challenges in the field of biomedicine. Drug therapy alone is not effective, so a variety of functional wound healing dressings have been developed. Microneedles have attracted more and more attentions in the field of wound healing dressings due to their penetration and high drug delivery efficiency. In this review, all the studies on the application of microneedles in wound healing in recent years are summarized, classify different microneedles according to their functions in the process of wound healing, discuss the current challenges in the transformation of microneedle technology toward clinical applications, and finally look forward to the future design and development directions of microneedles in this field.
Combining Step‐Growth and Chain‐Growth Polymerizations in One Pot: Light‐Induced Fabrication of Conductive Nanoporous PEDOT‐PCL Scaffold
Authors: Tabak Tugberk , Kaya Kerem , Isci Recep , Ozturk Turan , Yagci Yusuf , Kiskan Baris 
Published: August 2023

AbstractA novel method based on light‐induced fabrication of a poly (3,4‐ethylenedioxythiophene)‐polycaprolactone (PEDOT‐PCL) scaffold using phenacyl bromide (PAB) as a single‐component photoinitiator is presented. HBr released from the step‐growth polymerization of EDOT is utilized as an in situ catalyst for the chain‐growth polymerization of ε‐caprolactone. Detailed investigations disclose the formation of a self‐assembled nanoporous electroconductive scaffold (1.2 mS cm−1). Fluorescence emission spectra of the fabricated scaffold exhibit a mixed solvatochromic behavior, indicating specific interactions between the self‐assembled scaffold and solvents with varying polarities, as evidenced by transmission electron microscopy (TEM). Moreover, the same light‐induced technique can also be applied for bulk photopolymerization showcasing the versatility and wide‐ranging scope of the originated method. In brief, this study introduces a novel approach for light‐induced polymerization reactions that is merging step‐growth and chain‐growth mechanisms. This innovative approach is promising to facilitate in situ polymerization of monomers possessing diverse functionalities.
Effectiveness of DPD Simulations to Predict the Dynamics of Polymer Chains in Solutions at Equilibrium and Steady Shear Flows
Authors: Kumar Praphul , Jana Sanjay , Shyam Hari , Saha Dalal Indranil 
Published: August 2023

AbstractThe suitability of dissipative particle dynamics simulations is investigated to predict the dynamics of polymer chains in dilute polymer solutions. The authors find that the predictions depend on the value of the repulsive parameter for bead‐bead pairwise interactions used in the DPD simulations (aij). For all systems, the chain sizes and the relaxation time spectrum are analyzed. For aij = 0, theta solvent behaviour is obtained, whereas the dynamics at equilibrium agrees well with the predictions of the Zimm model. For higher values of aij, the static properties of the chain show good solvent behaviour. However, the scaling laws for the chain dynamics at equilibrium show wide variations, with consistent results obtained only at an intermediate value of aij = 25. At higher values of the repulsive parameter (aij ⩾ 25), the simulations are also able to predict the abrupt cut‐off in the relaxation spectrum, which has been observed earlier in experiments of dilute solutions. To verify further, the chain dynamics in shear flow using DPD simulations is studied. Specifically, the variation of the chain is analysed stretch and end‐over‐end tumbling with shear rates. Overall, the trends obtained from DPD simulations agree well with those observed in earlier BD simulations.
Bandwidth‐improved self‐diplexing planar cavity‐backed slot antenna
Authors: Syed Avez , Almalki Mansour H. , Alzahrani Ahmed S. , Alsalami Omar M. 
Published: August 2023

AbstractThe authors present a novel self‐diplexing antenna (SDA) designed using substrate‐integrated waveguide (SIW) technology. The antenna features a planar‐backed cavity with a radiating slot and two input ports tuned to produce two resonances in the operating band for enhanced bandwidth. The design is simple and easy to implement, with similar radiation characteristics across the bandwidth. Experimental validation of the antenna shows good agreement with simulated matching, with two operating frequency channels in the X‐band (8.21−8.47 GHz and 9.42−9.764 GHz). The SDA's stable wideband performance makes it suitable for various wireless access points and applications. Overall, the study contributes a new SDA design with improved bandwidth and radiation features.
Dual output feature fusion networks for femoral segmentation and quantitative analysis of the knee joint
Authors: He Dongdong , Guo Yuan , Zhang Xushu , Wang Changjiang , Zhao Zihui , Chen Weiyi , Zhang Kai , Ji Binping 
Published: August 2023

AbstractBackgroundMagnetic resonance imaging (MRI) is the preferred imaging modality for diagnosing knee disease. Segmentation of the knee MRI images is essential for subsequent quantification of clinical parameters and treatment planning for knee prosthesis replacement. However, the segmentation remains difficult due to individual differences in anatomy, the difficulty of obtaining accurate edges at lower resolutions, and the presence of speckle noise and artifacts in the images. In addition, radiologists must manually measure the knee's parameters which is a laborious and time‐consuming process.PurposeAutomatic quantification of femoral morphological parameters can be of fundamental help in the design of prosthetic implants for the repair of the knee and the femur. Knowledge of knee femoral parameters can provide a basis for femoral repair of the knee, the design of fixation materials for femoral prostheses, and the replacement of prostheses.MethodsThis paper proposes a new deep network architecture to comprehensively address these challenges. A dual output model structure is proposed, with a high and low layer fusion extraction feature module designed to extract rich features through the cross‐fusion mechanism. A multi‐scale edge information extraction spatial feature module is also developed to address the boundary‐blurring problem.ResultsBased on the precise automated segmentation results, 10 key clinical parameters were automatically measured for a knee femoral prosthesis replacement program. The correlation coefficients of the quantitative results of these parameters compared to manual results all achieved at least 0.92. The proposed method was extensively evaluated with MRIs of 78 patients’ knees, and it consistently outperformed other methods used for segmentation.ConclusionsThe automated quantization process produced comparable measurements to those manually obtained by radiologists. This paper demonstrates the viability of automatic knee MRI image segmentation and quantitative analysis with the proposed method. This provides data to support the accuracy of assessing the progression and biomechanical changes of osteoarthritis of the knee using an automated process, thus saving valuable time for the radiologists and surgeons.
Metabolomic evolution of the postpartum dairy cow uterus
Authors: Aranciaga Nicolas , Ross Alastair B. , Morton James D. , McDonald Robin , Gathercole Jessica L. , Berg Debra K. 
Published: August 2023

AbstractHigh rates of early pregnancy loss are a critical issue in dairy herds, particularly in seasonal, grazing systems. Components of the uterine luminal fluid (ULF), on which the early embryo depends for sustenance and growth, partly determine early pregnancy losses. Here, changes in ULF from early to mid‐postpartum in crossbred dairy cows were explored, linking them with divergent embryo development. For this, the uteri of 87 cows at Day 7 of pregnancy at first and third estrus postpartum were flushed to collect ULF. Eighteen metabolites (chiefly organic acids and sugars) significantly varied in abundance across postpartum, indicating a molecular signature of physiological recovery consistent of the upregulation of pyrimidine metabolism and glycerophospholipid metabolism, and downregulation of pentose phosphate and taurine metabolism pathways. Joint pathway analysis of metabolomics data and a previously generated proteomics data set on the same ULF samples suggests key links between postpartum recovery and subsequent successful embryo development. These include upregulation of VEGFA and downregulation of metabolism, NRF2, T‐cell receptor, which appear to improve the ULF's capacity of sustaining normal embryo development, and a putative osmo‐protectant role of beta‐alanine. These relationships should be further investigated to develop tools to detect and reduce early pregnancy loss in dairy cows.
Nurses' knowledge on assessment and management of cancer therapy‐associated oral mucositis
Authors: Raymond Barnabas Manlokiya , Agyeman‐Yeboah Joana 
Published: August 2023

AbstractAimThis study aimed to explore baseline nursing knowledge on assessment and management of patients at risk for developing cancer therapy‐associated oral mucositis (OM) at a tertiary hospital in Ghana.DesignA descriptive generic qualitative study design was conducted. The study population were nurses who cared for patients diagnosed with cancer.MethodsParticipants were recruited using a purposive non‐probability sampling technique. Data were obtained through face‐to‐face interviews using semi‐structured interview guide. Data collection and analysis were done concurrently.ResultsThe study found that nurses had knowledge on the pre‐treatment assessment of clients undergoing cancer treatment; however, they had insufficient knowledge on the standardized tool for the assessment of OM. They also lack a definitive approach to prevent and treat OM. Nurses provided general education on cancer treatment but paid little attention to the education on the possible side effect that includes OM. Additionally, insufficient knowledge level of nurses on cancer treatment‐associated mucositis and lack of structured protocol for OM coupled with unavailable tools for assessing the oral mucosa were also identified as militating against the management of OM. Findings from this study will guide policy that will improve the care that clients who are at risk of oral mucositis receive.
Simulating and reporting frequentist operating characteristics of clinical trials that borrow external information: Towards a fair comparison in case of one‐arm and hybrid control two‐arm trials
Authors: Kopp‐Schneider Annette , Wiesenfarth Manuel , Held Leonhard , Calderazzo Silvia 
Published: August 2023

AbstractBorrowing information from historical or external data to inform inference in a current trial is an expanding field in the era of precision medicine, where trials are often performed in small patient cohorts for practical or ethical reasons. Even though methods proposed for borrowing from external data are mainly based on Bayesian approaches that incorporate external information into the prior for the current analysis, frequentist operating characteristics of the analysis strategy are often of interest. In particular, type I error rate and power at a prespecified point alternative are the focus. We propose a procedure to investigate and report the frequentist operating characteristics in this context. The approach evaluates type I error rate of the test with borrowing from external data and calibrates the test without borrowing to this type I error rate. On this basis, a fair comparison of power between the test with and without borrowing is achieved. We show that no power gains are possible in one‐sided one‐arm and two‐arm hybrid control trials with normal endpoint, a finding proven in general before. We prove that in one‐arm fixed‐borrowing situations, unconditional power (i.e., when external data is random) is reduced. The Empirical Bayes power prior approach that dynamically borrows information according to the similarity of current and external data avoids the exorbitant type I error inflation occurring with fixed borrowing. In the hybrid control two‐arm trial we observe power reductions as compared to the test calibrated to borrowing that increase when considering unconditional power.
Angelica sinensis polysaccharide improves mitochondrial metabolism of osteoarthritis chondrocytes through PPARγ/SOD2/ROS pathways
Authors: Ni Su , Yi Ning , Yuan Hang , Li Dong , Chen Xu , Zhuang Chao 
Published: August 2023

AbstractOsteoarthritis (OA) is a common degenerative joint disease, which is characterized by wear of articular cartilage and narrow joint space, resulting in joint movement disorder. At present, accurate molecular mechanisms and effective interventions are still being explored. Here, we propose that angelica sinensis polysaccharide (ASP) alleviates OA progression by activating peroxisome proliferator‐activated receptor gamma (PPARγ). Therapeutic effect of ASP improving mitochondrial metabolism of OA chondrocytes was evaluated in vitro and in vivo, respectively. During cell experiments, the concentration and time response of tert butyl hydroperoxide (TBHP) and ASP were determined by cell viability. Apoptosis was detected by flow cytometry. Mitochondrial metabolism was detected by reactive oxygen species (ROS), mitochondrial membrane potential (MMP), release of cytochrome C, adenosine triphosphate (ATP) production, and superoxide dismutase 2 (SOD2) activity. Expressions of Aggrecan, collagen type II (Col2a1), PPARγ, and SOD2 were detected by qRT‐PCR and western blot. In animal experiments, we detected cell apoptosis and target protein expression separately through terminal deoxynucleotidyl transferase dUTP nick end‐labeling (TUNEL) staining and immunohistochemistry. Pretreatment of ASP significantly activated PPARγ and SOD2 in rat chondrocytes incubated with TBHP, cleared ROS, improved mitochondrial metabolism, increased chondrocytes viability, and alleviated chondrocytes apoptosis. In vivo, the administration of ASP could effectively ameliorate cartilage degeneration in OA rats, promote extracellular matrix synthesis, and decelerate the progress of OA. Our research identifies the role of ASP in mitochondrial metabolism of OA chondrocytes through PPARγ/SOD2/ROS pathways, which provides a new idea for the treatment of OA.
Pre‐treatment methods for stable oxygen and carbon isotope analyses of structural carbonates of bones in marine teleost fishes
Authors: Chung Ming‐Tsung , Kitagawa Takashi , Murakami‐Sugihara Naoko , Tanaka Kentaro , Miki Shiono , Shirai Kotaro 
Published: August 2023

RationaleAlthough the proportion of structural carbonates in vertebrate bones is low, the values of isotopes, namely stable oxygen (δ18O) and carbon (δ13C), in structural carbonates provide environmental and physiological information, which can be beneficial for estimating the palaeontological and ecological parameters of vertebrates. However, a few studies have analysed the isotopes of structural carbonates in modern teleost fishes, and a well‐developed protocol for sample preparation is lacking.MethodsWe examined different pre‐treatment methods of preparing bone samples of three marine teleost fishes (Japanese flounder, Pacific bluefin tuna and yellowtail) and investigated the effects of the cleaning methods on the stable isotope values of structural carbonates among vertebrae in the same individual. Isotope values were analysed using isotope ratio mass spectrometry.ResultsPhysical cleaning was the most promising pre‐treatment method and resulted in δ18O values that were comparable to those of otoliths. Chemical treatments with NaOH and H2O2 changed the percentage of structural carbonates in the bone and affected δ18O and δ13C values. High‐temperature treatments, such as boiling and roasting, altered δ18O values due to the exchange of oxygen with environmental water or vapour.ConclusionsOur results suggest that chemical cleaning methods used to prepare bone phosphate or collagen samples for isotope analyses are not suitable for structural carbonates. Physical cleaning is the appropriate pre‐treatment method for analysing the isotopes of structural carbonates. Also, we emphasise that standardising the vertebral number is necessary to make δ13C values comparable between specimens in the same species.
Automatic detection and segmentation of chorda tympani under microscopic vision in otosclerosis patients via convolutional neural networks
Authors: Huang Yu , Ding Xin , Zhao Yang , Tian Xu , Feng Guodong , Gao Zhiqiang 
Published: August 2023

AbstractBackgroundArtificial intelligence (AI) techniques, especially deep learning (DL) techniques, have shown promising results for various computer vision tasks in the field of surgery. However, AI‐guided navigation during microscopic surgery for real‐time surgical guidance and decision support is much more complex, and its efficacy has yet to be demonstrated. We propose a model dedicated to the evaluation of DL‐based semantic segmentation of chorda tympani (CT) during microscopic surgery.MethodsVarious convolutional neural networks were constructed, trained, and validated for semantic segmentation of CT. Our dataset has 5817 images annotated from 36 patients, which were further randomly split into the training set (90%, 5236 images) and validation set (10%, 581 images). In addition, 1500 raw images from 3 patients (500 images randomly selected per patient) were used to evaluate the network performance.ResultsWhen evaluated on a validation set (581 images), our proposed CT detection networks achieved great performance, and the modified U‐net performed best (mIOU = 0.892, mPA = 0.9427). Moreover, when applying U‐net to predict the test set (1500 raw images from 3 patients), our methods also showed great overall performance (Accuracy = 0.976, Precision = 0.996, Sensitivity = 0.979, Specificity = 0.902).ConclusionsThis study suggests that DL can be used for the automated detection and segmentation of CT in patients with otosclerosis during microscopic surgery with a high degree of performance. Our research validated the potential feasibility for future vision‐based navigation surgical assistance and autonomous surgery using AI.
Superelastic Cobalt Silicate@Resorcinol Formaldehyde Resin Core‐Shell Nanobelt Aerogel Monoliths with Outstanding Fire Retardant and Thermal Insulating Capability
Authors: Li Fuzhong , Song Jiabei , Niu Yutong , Zhang Hewei , Niederberger Markus , Cheng Wei 
Published: August 2023

AbstractThe practical applications of resorcinol formaldehyde resin (RFR) aerogels are prevented by their poor mechanical properties. Herein, a facile template‐directed method is reported to produce macroscopic free‐standing cobalt silicate (CS)@RFR core‐shell nanobelt aerogels that display superelastic behavior and outstanding thermal insulating and fire‐resistant capability. The synthesis relies on the polymerization of RFR on pre‐formed CS nanobelts which leads to in situ formation of hydrogel monoliths that can be transformed to corresponding aerogels by a freeze‐drying method. The composite nanobelt aerogel can withstand a compressive load of more than 4000 times of its own weight and fully recover after the removal of the weight. It can also sustain 1000 compressive cycles with 6.9% plastic deformation and 91.8% of the maximum stress remaining, with a constant energy loss coefficient as low as 0.16, at the set strain of 30%. The extraordinary mechanical properties are believed to be associated with the structural flexibility of the nanobelts and the RFR‐reinforced joints between the crosslinked nanobelts. These inorganic‐organic composite aerogels also show good thermal insulation and excellent fire‐proof capability. This work provides an effective strategy for fabricating superelastic RFR‐based aerogels which show promising applications in fields such as thermal insulation, energy storage, and catalyst support.