bluuebunny/crossref_metadata_2025_split huggingface dataset:
Platelet‐rich plasma injections as a treatment for Achilles tendinopathy and plantar fasciitis in athletes
Authors: Sneed Dustin , Wong Carmen 
Published: March 2023

AbstractPlatelet‐rich plasma (PRP) injections represent a growing interest in the use of biologic therapies for treatment of musculoskeletal injuries. One possible application of PRP is in the management of overuse injuries commonly experienced by athletes. The aim of this review is to evaluate and summarize existing evidence regarding the efficacy of PRP in the treatment of Achilles tendinopathy and plantar fasciitis in athletes. Although many lower quality single‐armed studies have demonstrated clinical improvement in athletes treated for Achilles tendinopathy with PRP, higher quality randomized controlled trials (RCTs) have shown no clear benefit in athletes. Existing data suggest PRP significantly improves clinical outcomes for plantar fasciitis in the general population, but very few studies and no RCTs are available that specifically analyze outcomes in athletic populations. More research is needed to evaluate how platelet concentration, leukocyte and erythrocyte presence, and sport type may interact to affect clinical outcomes in athletes.
Decellularized Extracellular Matrix for Remodeling Bioengineering Organoid's Microenvironment
Authors: Zhu Liye , Yuhan Jieyu , Yu Hao , Zhang Boyang , Huang Kunlun , Zhu Longjiao 
Published: March 2023

AbstractOver the past decade, stem cell‐ and tumor‐derived organoids are the most promising models in developmental biology and disease modeling, respectively. The matrix is one of three main elements in the construction of an organoid and the most important module of its extracellular microenvironment. However, the source of the currently available commercial matrix, Matrigel, limits the application of organoids in clinical medicine. It is worth investigating whether the original decellularized extracellular matrix (dECM) can be exploited as the matrix of organoids and improving organoid construction are very important. In this review, tissue decellularization protocols and the characteristics of decellularization methods, the mechanical support and biological cues of extraccellular matrix (ECM), methods for construction of multifunctional dECM and responsive dECM hydrogel, and the potential applications of functional dECM are summarized. In addition, some expectations are provided for dECM as the matrix of organoids in clinical applications.
Coupling of Oxygen Vacancies and Heterostructure on Fe3O4 via an Anion Doping Strategy to Boost Catalytic Activity for Lithium‐Sulfur Batteries
Authors: Xin Shasha , Liu Tao , Li Jing , Cui Hongtao , Liu Yuanyuan , Liu Kaihua , Yang Yanzhao , Wang Meiri 
Published: March 2023

AbstractThe sluggish reaction kinetics and severe shutting behaviors of sulfur cathodes are the major roadblocks to realizing the practical application of lithium−sulfur (Li−S) batteries and need to be solved through designing/constructing rational sulfur hosts. Herein, an effective alternative material of Fe3O4−x/FeP in‐situ embedded in N‐doped carbon‐tube (Fe3O4−x/FeP/NCT) is proposed. In this fabricated heterostructure, NCT skeleton works as a sulfur host provides physical barrier for lithium polysulfides (LiPSs), while Fe3O4−x/FeP heterostructure with abundant oxygen vacancies provides double active centers to simultaneously accelerate e−/Li+ diffusion/transport kinetics and catalysis for LiPSs. Through the respective advantages, Fe3O4−x/FeP/NCT exhibits synergy enhancement effect for restraining sulfur dissolution and enhancing its conversion kinetics. Furthermore, the promoted ion diffusion kinetics, enhanced electrical conductivity, and increased active sites of Fe3O4−x/FeP/NCT are enabled by oxygen vacancies as well as the heterogeneous interfacial contact, which is clearly confirmed by experimental and first‐principles calculations. By virtue of these superiorities, the constructed cathode shows excellent long‐term cycling stability and a high‐rate capability up to 10 C. Specially, a high areal capacity of 7.2 mAh cm−2 is also achieved, holding great promise for utilization in advanced Li−S batteries in the future.
Ultra‐Highly Active Ni‐Doped MOF‐5 Heterogeneous Catalysts for Ethylene Dimerization
Authors: Chen Cailing , Meng Lingkun , Alalouni Mohammed R. , Dong Xinglong , Wu Zhi‐Peng , Zuo Shouwei , Zhang Huabin 
Published: March 2023

AbstractHere, an ultra‐highly active Ni‐MOF‐5 catalyst with high Ni loading for ethylene dimerization is reported. The Ni‐MOF‐5 catalysts are synthesized by a facile one‐pot co‐precipitation method at room temperature, where Ni2+ replaces Zn2+ in MOF‐5. Unlike Zn2+ with tetrahedral coordination in MOF‐5, Ni2+ is coordinated with extra solvent molecules except for four‐oxygen from the framework. After removing coordinated solvent molecules, Ni‐MOF‐5 achieves an ethylene turnover frequency of 352 000 h−1, corresponding to 9040 g of product per gram of catalyst per hour, at 35 °C and 50 bar, far exceeding the activities of all reported heterogeneous catalysts. The high Ni loading and full exposure structure account for the excellent catalytic performance. Isotope labeling experiments reveal that the catalytic process follows the Cossee–Arlman mechanism, rationalizing the high activity and selectivity of the catalyst. These results demonstrate that Ni‐MOF‐5 catalysts are very promising for industrial catalytic ethylene dimerization.
High Mobility IZTO Thin‐Film Transistors Based on Spinel Phase Formation at Low Temperature through a Catalytic Chemical Reaction
Authors: Kim Gwang‐Bok , On Nuri , Kim Taikyu , Choi Cheol Hee , Hur Jae Seok , Lim Jun Hyung , Jeong Jae Kyeong 
Published: March 2023

AbstractIn this paper, In0.22ZnδSn0.78−δO1.89−δ (δ = 0.55) films with a single spinel phase are successfully grown at the low temperature of 300 °C through careful cation composition design and a catalytic chemical reaction. Thin‐film transistors (TFTs) with amorphous In0.22ZnδSn0.78−δO1.89−δ (δ = 0.55) channel layers have a reasonable mobility of 41.0 cm2 V−1 s−1 due to the synergic intercalation of In and Sn ions. In contrast, TFTs with polycrystalline spinel In0.22ZnδSn0.78−δO1.89−δ (δ = 0.55) channel layers, achieved through a metal‐induced crystallization at 300 °C, exhibit a remarkably high field‐effect mobility of ≈83.2 cm2 V−1 s−1 and excellent stability against external gate bias stress, which is attributed to the uniform formation of the highly ordered spinel phase. The relationships between cation composition, microstructure, and performance for the In2O3–ZnO–SnO2 ternary component system are investigated rigorously to attain in‐depth understanding of the roles of various crystalline phases, including spinel Zn2−ySn1−yIn2yO4 (y = 0.45), bixbyite In2−2xZnxInxO4 (x = 0.4), rutile SnO2, and a homologous compound of compound (ZnO)k(In2O3) (k = 5). This work concludes that the cubic spinel phase of Zn2−ySn1−yIn2yO4 (y = 0.45) film is a strong contender as a substitute for semiconducting polysilicon as a backplane channel ingredient for mobile active‐matrix organic light‐emitting diode displays.
Open source variational quantum eigensolver extension of the quantum learning machine for quantum chemistry
Authors: Haidar Mohammad , Rančić Marko J. , Ayral Thomas , Maday Yvon , Piquemal Jean‐Philip 
Published: March 2023

AbstractQuantum chemistry (QC) is one of the most promising applications of quantum computing. However, present quantum processing units (QPUs) are still subject to large errors. Therefore, noisy intermediate‐scale quantum (NISQ) hardware is limited in terms of qubit counts/circuit depths. Variational quantum eigensolver (VQE) algorithms can potentially overcome such issues. Here, we introduce the OpenVQE open‐source QC package. It provides tools for using and developing chemically‐inspired adaptive methods derived from unitary coupled cluster (UCC). It facilitates the development and testing of VQE algorithms and is able to use the Atos Quantum Learning Machine (QLM), a general quantum programming framework enabling to write/optimize/simulate quantum computing programs. We present a specific, freely available QLM open‐source module, myQLM‐fermion. We review its key tools for facilitating QC computations (fermionic second quantization, fermion‐spin transforms, etc.). OpenVQE largely extends the QLM's QC capabilities by providing: (i) the functions to generate the different types of excitations beyond the commonly used UCCSD ansatz; (ii) a new Python implementation of the “adaptive derivative assembled pseudo‐Trotter method” (ADAPT‐VQE). Interoperability with other major quantum programming frameworks is ensured thanks to the myQLM‐interop package, which allows users to build their own code and easily execute it on existing QPUs. The combined OpenVQE/myQLM‐fermion libraries facilitate the implementation, testing and development of variational quantum algorithms, while offering access to large molecules as the noiseless Schrödinger‐style dense simulator can reach up to 41 qubits for any circuit. Extensive benchmarks are provided for molecules associated to qubit counts ranging from 4 to 24. We focus on reaching chemical accuracy, reducing the number of circuit gates and optimizing parameters and operators between “fixed‐length” UCC and ADAPT‐VQE ansätze.This article is categorized under:
Software > Quantum Chemistry
Quantum Computing > Algorithms
Ambivalent Narratives of Motherhood and Mothering: From Normal and Natural to Not-at-all
Authors: Henriksson Helena Wahlström , Williams Anna , Fahlgren Margaretha 
Published: March 2023

AbstractThis chapter introduces the volume by outlining some crucial scholarly histories: the feminist study of motherhood and mothering, and the literary study of mothers in fiction and life writing, across many differences. Since mothers, motherhood, and mothering not only are defined by physical and material experiences but also take shape in narratives—in stories and recorded accounts—these also need to be continuously studied and theorized if we are to understand the culturally specific meanings of motherhood. The chapter then introduces each of the separate studies in the volume. These variously demonstrate that literary representations of mothers and mothering foreground the ways that parenthood and parenting for women are imbricated with dimensions like class, race, age, and nationality, as well as how motherhood is connected to living a heterosexual, lesbian, queer, or trans everyday life. In original analyses of a range of representations, from absent/missing mothers to highly present ones, the studies that comprise this book engage in a dialogue with the previous research, raising questions about how motherhood and mothering are marked by absence and/or presence and by profound ambivalences, about how maternal perspectives and voices gain space or mix with filial voices in the narratives, and about how mothers are constructed in relation to ideals and norms of motherhood.
One Hand Clapping: The Loneliness of Motherhood in Lucia Berlin’s “Tiger Bites”
Authors: Grahn Lisa 
Published: March 2023

AbstractThe issue of safe and legal abortions is and has been highly relevant for generations of women. By describing acts that have previously been carried out in secret, literary fiction makes these experiences visible, meanwhile exposing the circular nature of women’s history. In this chapter, intergenerational experiences of motherhood are examined in Lucia Berlin’s short story “Tiger Bites,” which tells the story of a young mother seeking abortion in Mexico. In Berlin’s representation of the abortion clinic, feelings of isolation and shame are foregrounded, as well as the actual risks to the health of the women and girls involved. The portrayal of the patients and staff at the clinic highlights aspects such as class, the crossings of bodily and national borders, and agency. This chapter argues that family relationships can create feelings of isolation as well as community, and that it is only through her own choice that the protagonist can realize her agency in motherhood. The analysis ultimately argues that Berlin’s story has its own intergenerational relevance, and speaks to the present as well as to its time of initial publication.
Contested Motherhood in Autobiographical Writing: Rachel Cusk and Sheila Heti
Authors: Fahlgren Margaretha , Williams Anna 
Published: March 2023

AbstractThis chapter examines contemporary autobiographical narratives which explore the notion of motherhood as the central issue in women’s lives. These narratives have been important in offering alternative discourses and thereby broadening the concept of motherhood. This chapter discusses them in the light of motherhood studies and theories about matrilineal narratives in contemporary literature. Works by two highly acclaimed Canadian writers are at the center of our study: Rachel Cusk’sA Life’s Work: On Becoming a Mother(first published in 2001; 2008) and Sheila Heti’sMotherhood(2018). Both volumes convey an ambivalence toward motherhood and lean on emotions as well as intellectual argument. Theoretically, the point of departure is Toril Moi’s discussion about contemporary life writing as an “exercise of attention,” and furthermore the feminist examination of the definition of motherhood and mothering in a social context, from Adrienne Rich (1976) to Tina Miller (2005). The texts discussed in this chapter contest different “cultural scripts” (Miller)—discourses that affect societal and subjective views on motherhood and gender.
Professions, Proficiency, and Place: An Introduction
Authors: Glückler Johannes , Punstein Anna Mateja , Winch Christopher 
Published: March 2023

AbstractThe 18th volume of the interdisciplinary series on Knowledge and Space looks at how people learn, create and transfer knowledge within and across social groups, such as professions, scholarly disciplines or communities. On the one hand, creating knowledge across social groups is important for innovation, especially for creating more radical and unconventional novelty. On the other hand, social circles often frame what and how its members think and learn, and so erect structural boundaries to innovation. This introductory chapter emphasizes the collective nature and social process of knowledge creation. Moreover, it suggests combining the study of professions and proficiency with a geographical understanding of the place-specificity of those dynamics that finally enable change, learning and cross-fertilization, especially beyond the boundaries of individual professions and communities.
Spielwiesen: Preparing a Research Agenda on Playgrounds and Serious Work in Academia
Authors: Berthoin Antal Ariane , Hamann Julian 
Published: March 2023

AbstractAcademics generally present the acquisition of academic proficiency as a learning process dedicated to specializing in an area of expertise. During their careers, scholars are expected to develop their academic profile by progressively building on their knowledge and their professional networks in their chosen specialty. However, prompted by reflections on their own experiences and by exploratory conversations with colleagues, the authors find that this portrayal of streamlined professionalization in academia hides playful deviations from the primary path into new intellectual and social spaces. They introduce the notion of a Spielwiese [literally: playing meadow] to describe these spaces, how they emerge, and how academics engage with them. The authors conclude by laying the groundwork for a typology and outline a research agenda for Spielwiesen in academia, whose utilizers should consider national career systems, disciplinary contexts, and different cohorts and career stages.
The Interplay of Knowledge, Strategies, and the Interest in the Development of Expertise within Professions
Authors: Alexander Patricia A. 
Published: March 2023

AbstractWhat role does knowledge play in expertise development in professional domains, and to what extent does that domain-specific knowledge interact with individuals’ strategic abilities and their deep-seated interest in a profession? These are central questions explored in this chapter that positions expertise and its development within the framework of the Model of Domain Learning or MDL. The MDL is a theoretical model used to capture systematic changes in knowledge, strategic abilities, and interest that individuals undergo as they progress from their first exposure to a professional domain to subsequent stages of competence and, perhaps, expertise. After elucidating the concepts of professions, expertise, and knowledge, the author surveys the MDL’s contributions to understanding expertise development. The chapters then culminate with an exploration of societal changes that may have a significant bearing on the nature of expertise and its future development.
The Changing Fortunes of the Architectural Profession in Postwar Britain: Complexity, Technological Change, and the (Re)construction of Knowledge
Authors: Siebert Michael , Windrum Paul 
Published: March 2023

AbstractProfessions are one means of organizing the delivery of goods and services. In this paper, the authors consider how the power and control of professional groups can change within specific fields of work due to a combination of endogenous and exogenous factors. Their case study is the changing role of UK architects within the private residential sector over the post-war period. The architect was once the primary actor who brought together, organized, and integrated the workflow of a myriad of contractors, legal agencies, and planning authorities, but this is no longer the case. To understand how this occurred, and whether the architectural profession could regain a key position in the UK housing industry, the authors conduct a broad historical analysis of the factors at play within the UK architectural profession and the industry as a whole that have resulted in this shift in knowledge, roles and power.
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
Authors: Rymarczyk Dawid , Pardyl Adam , Kraus Jarosław , Kaczyńska Aneta , Skomorowski Marek , Zieliński Bartosz 
Published: March 2023

AbstractThe rapid development of histopathology scanners allowed the digital transformation of pathology. Current devices fastly and accurately digitize histology slides on many magnifications, resulting in whole slide images (WSI). However, direct application of supervised deep learning methods to WSI highest magnification is impossible due to hardware limitations. That is why WSI classification is usually analyzed using standard Multiple Instance Learning (MIL) approaches, that do not explain their predictions, which is crucial for medical applications. In this work, we fill this gap by introducing ProtoMIL, a novel self-explainable MIL method inspired by the case-based reasoning process that operates on visual prototypes. Thanks to incorporating prototypical features into objects description, ProtoMIL unprecedentedly joins the model accuracy and fine-grained interpretability, as confirmed by the experiments conducted on five recognized whole-slide image datasets.
Wasserstein t-SNE
Authors: Bachmann Fynn , Hennig Philipp , Kobak Dmitry 
Published: March 2023

AbstractScientific datasets often have hierarchical structure: for example, in surveys, individual participants (samples) might be grouped at a higher level (units) such as their geographical region. In these settings, the interest is often in exploring the structure on the unit level rather than on the sample level. Units can be compared based on the distance between their means, however this ignores the within-unit distribution of samples. Here we develop an approach for exploratory analysis of hierarchical datasets using the Wasserstein distance metric that takes into account the shapes of within-unit distributions. We use t-SNE to construct 2D embeddings of the units, based on the matrix of pairwise Wasserstein distances between them. The distance matrix can be efficiently computed by approximating each unit with a Gaussian distribution, but we also provide a scalable method to compute exact Wasserstein distances. We use synthetic data to demonstrate the effectiveness of our Wassersteint-SNE, and apply it to data from the 2017 German parliamentary election, considering polling stations as samples and voting districts as units. The resulting embedding uncovers meaningful structure in the data.
A Stopping Criterion for Transductive Active Learning
Authors: Kottke Daniel , Sandrock Christoph , Krempl Georg , Sick Bernhard 
Published: March 2023

AbstractIn transductive active learning, the goal is to determine the correct labels for an unlabeled, known dataset. Therefore, we can either ask an oracle to provide the right label at some cost or use the prediction of a classifier which we train on the labels acquired so far. In contrast, the commonly used (inductive) active learning aims to select instances for labeling out of the unlabeled set to create a generalized classifier, which will be deployed on unknown data. This article formally defines the transductive setting and shows that it requires new solutions. Additionally, we formalize the theoretically cost-optimal stopping point for the transductive scenario. Building upon the probabilistic active learning framework, we propose a new transductive selection strategy that includes a stopping criterion and show its superiority.
Benign and Malignant Renal Disease
Authors: Aganovic Lejla , Nörenberg Dominik 
Published: March 2023

AbstractImaging of renal disease encompasses a wide spectrum of benign, malignant, and non-neoplastic lesions. Focal renal masses (of benign and malignant origin) are the most frequent entities and the number of incidentally detected renal lesions is constantly increasing. Several imaging modalities are available to optimize characterization, staging, and treatment of cystic and solid renal masses. Cystic and solid renal masses can be imaged with ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), with contrast enhancement needed to optimize renal mass detection and characterization. Most very small renal masses of less than 1–1.5 cm cannot be characterized due to their size. Because most of these lesions are benign, follow-up is suggested only when these masses appear heterogeneous on imaging. CT, MRI, and contrast-enhanced US (CEUS) can predict which cystic renal masses are most likely to be malignant. CT and MRI can identify macroscopic fat in the vast majority of benign angiomyolipomas (AMLs), allowing for differentiation from other solid renal masses including renal cell cancer (RCC). Although some solid renal masses without macroscopic fat may contain distinct combinations of imaging features, there is much overlap and renal mass biopsy will often be required for definitive diagnosis as well as for patient risk stratification. Furthermore, CT and MRI are accurate in local staging of renal cancers, predicting whether partial nephrectomy or local ablation can be performed successfully, and for imaging of patients after treatment. Unique patterns of metastatic disease response can be encountered after the treatment of metastatic renal cancer with targeted chemotherapeutic agents. Radiologists must be aware of typical imaging features of cystic and solid renal masses, cancer mimics as well as response patterns and are key stakeholders within interdisciplinary treatment decisions to support the diagnostic workup and management of renal masses with emerging treatment options for RCC.