bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hibridaciones y desbordamientos entre disciplinas y sectores en arte y comunicación. Trazando el potencial creativo transdisciplinar para la docencia
Authors: Obradors Matilde 
Published: July 2021

Con el convencimiento de que la facultad creativa mejora con la práctica y con la inmersión en modelos innovativos, y puesto que una de las operaciones fundamentales de la creatividad es la asociación de ideas, la analogía, la mezcla y la combinación de referentes que lleva a cosas nuevas, una asignatura dedicada a la hibridación y la transdisciplinariedad entre comunicación, arte y cultura, es imprescindible para comprender e incentivar la creatividad, mejorar su práctica y obtener resultados, diferenciados e innovadores. El presente estudio propone trazar un mapa de hibridaciones como contenido lectivo para incentivar la creatividad. Las hibridaciones entre diversas disciplinas culturales y artísticas se vienen produciendo desde los años 20 a lo largo de todo el siglo pasado, a pesar de que las diferentes industrias han preservado sus dominios por cuestiones comerciales y de élite de pertenencia a un ámbito. En el siglo veintiuno se dan múltiples expresiones de sensibilidad a las problemáticas sociales, en las que las hibridaciones configuran nuevas prácticas dentro de lo que se ha dado en llamar la Innovación Social; encontramos diseñadores gráficos, artistas, cineastas, publicitarios… implicados en temas sociales y prácticas artísticas, comprometidos con la sociedad. La denominada Revolución Tecnológica ha cambiado las prácticas y las formas de relación. Con Internet y las Redes Sociales, ha aumentado considerablemente la hibridación, puesto que todos podemos acceder a los artilugios tecnológicos que la hacen posible, pero es fundamental, considerar las manifestaciones anteriores a la era digital, conocer el origen de las prácticas de cruce entre disciplinas.
MPLA Case 3: Don’t criticize me in public!
Authors: Hendrickson Kristi , Kim Sara , Stambaugh Cassandra , Gronberg Mary , Kim Leonard , Wang Dongxu ,   MPLA Cases Subcommittee
Published: July 2021

AbstractThis work of fiction re‐enacts a scenario in which a medical physics resident was not able to address a physics call during patient simulation and was criticized by the supervising faculty physicist in front of the team and the patient. The resident and the faculty agreed to meet afterwards to debrief the situation, in the hope of establishing a better working relationship. The intended use of this case, through group discussion, self‐study, or role‐play, is to encourage readers to discuss the situation at hand, inspire professionalism and leadership thinking, and allow the practice of conflict management. Facilitator's notes are available upon request to the MPLA Cases Subcommittee. This case study falls under the scope of and is supported by the Medical Physics Leadership Academy (MPLA), a committee in the American Association of Physicists in Medicine (AAPM).
The association between the belief in coronavirus conspiracy theories, miracles, and the susceptibility to conjunction fallacy
Authors: Wabnegger Albert , Gremsl Andreas , Schienle Anne 
Published: June 2021

SummaryPrevious research has shown that people who endorse conspiracy theories are more prone to the conjunction fallacy: the tendency to perceive conjunct events as more probable than constituent events. The present study examined the relationship between specific beliefs (belief in conspiracy theories, religiosity) and the susceptibility to conjunction errors (CEs) in specific domains. A total of 500 participants was presented with brief scenarios from the domains “coronavirus conspiracy,” “miraculous healing,” and a control condition. Each scenario included one statement about a separate event and a second statement about two joint events co‐occurring. The participants estimated the probability of each statement. Results showed that the number of CEs made in the coronavirus domain was only associated with the belief in conspiracy theories, while general religiosity was only associated with CEs for scenarios describing miraculous healings. The assessed beliefs were not associated with CEs made in the control condition. Results suggest that distinct beliefs are uniquely associated with the susceptibility to conjunction errors in particular domains.
Recent Advances in the Direct Functionalization of Isoindolinones for the Synthesis of 3,3‐Disubstituted Isoindolinones
Authors: Chen Long , Zou Yun‐Xiang 
Published: June 2021

AbstractThe construction of tetrasubstituted carbon centers (especially chiral ones) represents one of the most challenging and demanding topics in the synthesis of natural products and related drugs. The development of isoindolinones with this feature appears to be of great importance, because 3,3‐disubstituted isoindolinones, which feature all kinds of tetrasubstituted carbon centers, also including spirocyclic and all‐carbon or heteroatom‐containing centers, show a wide spectrum of biological and pharmaceutical activities. Therefore, the synthetic methodologies for preparing these skeletons have received significant attention during the past decade. In general, these strategies can be classified into two major categories, namely the direct functionalization of parent isoindolinones and lactam‐ring‐formation‐involved reactions, depending on whether there is a lactam‐ring‐formation process or not during the production of the final 3,3‐disubstituted isoindolinone. Since the second strategy has been well reviewed, this review mainly summarizes the recent progress in the direct functionalization of parent isoindolinones to construct 3,3‐disubstituted isoindolinones via three subdivided strategies.magnified image
Structure‐Based Programming of Supramolecular Assemblies in Living Cells for Selective Cancer Cell Inhibition
Authors: Hu Liangbo , Li Ying , Lin Xinhui , Huo Yucheng , Zhang Hongyue , Wang Huaimin 
Published: June 2021

AbstractHere we report on the design, synthesis, and assembly of an enzymatic programmable peptide system inspired by endocytic processes to induce molecular assemblies formation spatiotemporally in living cancer cells, resulting in glioblastoma cell death mainly in necroptosis. Our results indicate the stability and glycosylation of molecules play an essential role in determining the final bioactivity. Detailed mechanistic studies by CLSM, Flow cytometry, western blot, and Bio‐EM suggest the site‐specific formation of assemblies, which could induce the LMP and activate the downstream cell death pathway. Moreover, we also demonstrate that our strategy can boost the activity of commercial chemotherapy drug by escaping lysosome sequestration. We expected this work would be expanded towards artificial intelligent biomaterials for cancer therapy and imaging precisely.
Controlling Polymer Molecular Weight Distribution through a Latent Mediator Strategy with Temporal Programming
Authors: Chen Miao , Li Jiajia , Ma Kaiqi , Jin Guoqin , Pan Xiangqiang , Zhang Zhengbiao , Zhu Jian 
Published: June 2021

AbstractPolymer molecular weight distribution (MWD) is a key parameter of polymers. Here we present a robust method for controlling polymer MWD in controlled cationic polymerizations. A latent mediator strategy was designed and combined with temporal programming to regenerate mediators at different times during polymerization. Both the breadths and shapes of MWD curves were tuned easily by adjusting an external light source. Bimodal, trimodal, and tetramodal distributions were obtained, and the breadths could be varied from 1.06 to 2.09. Polymers with different MWDs prepared by this method had good chain end fidelity, which was demonstrated with successful chain‐extension experiments. In addition, the introduction of temporal programming with a computer‐controlled single chip for the light source opened an avenue for the use of artificial intelligence in polymer synthesis.
Characterization of response to atezolizumab + bevacizumab versus sorafenib for hepatocellular carcinoma: Results from the IMbrave150 trial
Authors: Salem Riad , Li Daneng , Sommer Nicolas , Hernandez Sairy , Verret Wendy , Ding Beiying , Lencioni Riccardo 
Published: June 2021

AbstractBackgroundIMbrave150 is a phase III trial that assessed atezolizumab + bevacizumab (ATEZO/BEV) versus sorafenib (SOR) in patients with unresectable hepatocellular carcinoma (HCC) and demonstrated a significant improvement in clinical outcomes. Exploratory analyses characterized objective response rate (ORR), depth (DpR), and duration of response (DoR), and patients with a complete response (CR).MethodsPatients were randomized 2:1 to intravenous ATEZO (1200 mg) + BEV (15 mg/kg) every 3 weeks or oral SOR (400 mg) twice daily. Tumors were evaluated using Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) and HCC‐modified RECIST (mRECIST). ORR by prior treatment and largest baseline liver lesion size, DoR, time to response (TTR), and complete response (TTCR) were analyzed.ResultsFor both criteria, responses favored ATEZO/BEV versus SOR regardless of prior treatment and in patients with lesions ≥3 cm. Median TTR was 2.8 months per RECIST 1.1 (range: 1.2–12.3 months) and 2.8 months per mRECIST (range: 1.1–12.3 months) with ATEZO/BEV. Patients receiving ATEZO/BEV had a greater DpR, per both criteria, across baseline liver lesion sizes. Characteristics of complete responders were similar to those of the intent‐to‐treat population. In complete responders receiving ATEZO/BEV per mRECIST versus RECIST 1.1, respectively, median TTCR was shorter (5.5 vs. 7.0 months), mean baseline sum of lesion diameter was longer (5.0 [SD, 5.1] vs. 2.6 [SD, 1.4] cm), and mean largest liver lesion size was larger (4.8 [SD, 4.2] vs. 2.3 [SD, 1.0] cm).ConclusionsThese data highlight the improved ORR, DpR, and CR rates with ATEZO/BEV in unresectable HCC.
Cascaded multilevel inverter based on ladder bridges: Analysis, optimization, and implementation
Authors: Aalami Mohammadamin , Hadiizadeh Hassan , Babaei Ebrahim 
Published: June 2021

AbstractThis paper proposes a new ladder‐switch based cascaded multilevel inverter that requires a lower number of insulated gate bipolar transistors (IGBTs) and direct current (DC) voltage sources to generate a specified range of voltage levels. Regarding this topology, it consists of λ stages, where each stage comprises k legs, besides each leg composed of n cells. So, the proposed topology can be optimized to obtain the lower requirement for IGBTs and DC voltage sources. It is required to mention that this topology generates both negative and positive voltage levels inherently. Two different algorithms are presented to synthesize all odd and even voltage levels. After, regarding each of the algorithms, the proposed topology is optimized from different aspects of the lowest number of IGBTs or the lowest number of DC voltage sources, and results are depicted. A comparison assessment is performed to find the advantages and possible disadvantages of the proposed topology. In the end, a 23‐level prototype of the proposed topology is used to validate the correct performance of the proposed topology using the experimental results.
Increase in leaf organic acids to enhance adaptability of dominant plant species in karst habitats
Authors: Tang Songbo , Liu Jianfeng , Lambers Hans , Zhang Lingling , Liu Zhanfeng , Lin Yutong , Kuang Yuanwen 
Published: June 2021

AbstractEstimation of leaf nutrient composition of dominant plant species from contrasting habitats (i.e., karst and nonkarst forests) provides an opportunity to understand how plants are adapted to karst habitats from the perspective of leaf traits. Here, we measured leaf traits—specific leaf area (SLA), concentrations of total carbon ([TC]), nitrogen ([TN]), phosphorus ([TP]), calcium ([Ca]), magnesium ([Mg]), manganese ([Mn]), minerals ([Min]), soluble sugars, soluble phenolics, lipids, and organic acids ([OA])—and calculated water‐use efficiency (WUE), construction costs (CC), and N/P ratios, and searched for correlations between these traits of 18 abundant plant species in karst and nonkarst forests in southwestern China. Variation in leaf traits within and across the abundant species was both divergent and convergent. Leaf [TC], [Ca], [Min], [OA], and CC were habitat‐dependent, while the others were not habitat‐ but species‐specific. The correlations among [TN], [TP], SLA, [TC], CC, [Min], WUE, [OA], and CC were habitat‐independent, and inherently associated with plant growth and carbon allocation; those between [CC] and [Lip], between [Ca] and [Mg], and between [Mg] and [WUE] were habitat‐dependent. Habitat significantly affected leaf [Ca] and thus indirectly affected leaf [OA], [Min], and CC. Our results indicate that plants may regulate leaf [Ca] to moderate levels via adjusting leaf [OA] under both high and low soil Ca availability, and offer new insights into the abundance of common plant species in contrasting habitats.
Automated quantification of live articular chondrocyte fluorescent staining using a custom image analysis framework
Authors: Yang Linjun , Brouillette Marc J. , Coleman Mitchell C. , Kluz Paige N. , Goetz Jessica E. 
Published: July 2021

AbstractThe goal of this study was to develop, validate, and implement an image analysis framework to automatically analyze chondrocytes in 3D image stacks of cartilage acquired using a fluorescent confocal microscope. Source specimens consist of viable osteochondral tissue co‐stained with multiple live‐cell dyes. Our framework utilizes a seeded watershed‐based algorithm to automatically segment individual chondrocytes in each 2D slice of the confocal image stack. The resulting cell segmentations are colocalized in 3D to eliminate duplicate segmentation of the same cell resulting from the visibility of fluorescence signal in multiple imaging planes, and the 3D cell distribution is used to automatically define the cartilage tissue volume. The algorithm then provides chondrocyte density data, and the associated segmentation can be used as a mask to extract and quantify per cell intensity of a secondary, functional dye co‐staining the chondrocytes. The accuracy of the automated chondrocyte segmentation was validated against manual segmentations (average IOU = 0.79). When applied to a cartilage surrogate, this analysis framework estimated chondrocyte density within 10% of the true density and demonstrated a good agreement between framework's counts and manual counts (R2 = 0.99). In a real application, the framework was able to detect the increased dye signal of monochlorobimane (MCB) in chondrocytes treated with N‐acetylcysteine (NAC) after mechanical injury, quantifying intracellular biochemical changes in living cells. This new framework allows for fast and accurate quantification of intracellular activities of chondrocytes, and it can be adapted for broader application in many imaging and treatment modalities, including therapeutic OA research.
The relations between wear behavior and basic material properties of graphene‐based materials reinforced ultrahigh molecular weight polyethylene
Authors: Shahemi Nur Hidayah , Liza Shahira , Sawae Yoshinori , Morita Takehiro , Fukuda Kanao , Yaakob Yazid 
Published: June 2021

AbstractThis article aims to investigate the influence of reinforcing graphene oxide (GO) and graphite flakes (GF) fillers into ultrahigh molecular weight polyethylene (UHMWPE) for orthopedic application. These fillers were expected to physically bond to UHMWPE, thus can enhance the subsurface strength, improving the wear behavior of the composites. UHMWPE/GO and UHMWPE/GF composites were prepared at 0.1 and 1.0 wt% by melt‐blending, followed by a compression molding technique. A multidirectional pin‐on‐disc wear test was performed to simulate the kinematic of hip application. Whilst getting exposed in the artificial in‐vivo lubricant bath (30 v/v% diluted bovine serum). Following this, the wear mechanism fostered by each filler (GO and GF) was determined by wear features obtained from the optical microscope and scanning electron microscope (SEM). The crystallinity degree and crystal defect were assessed using x‐ray diffraction (XRD). The mechanical properties of fabricated composites were evaluated by using a universal testing machine and Vickers microhardness. We found that UHMWPE/GO has the lowest specific wear rate due to the improved subsurface strength, as the reduction of a weak adhesive point was observed on the worn surface. Meanwhile, higher GF content (1 wt%) in UHMWPE displayed a lower specific wear rate than neat UHMWPE after completing the 10 km sliding distance attributed to the filler resurfaced, responsible for providing a strong resistance of the shear stress applied upon sliding with the metal counterface. Interestingly, the hardness and tensile strength for both UHMWPE/GO and UHMWPE/GF increased, although the crystallinity percentage was declining compared to neat UHMWPE.
Big Data Value Creation by Example
Authors: Pazzaglia Jean-Christophe , Alonso Daniel 
Published: June 2021

AbstractThe Big Data Value contractual Public-Private Partnership between the European Commission and the Big Data Value Association (BDVA) was signed in October 2014. Since then, more than 50 projects and numerous BDVA members have explored how data can drive innovation across the data stack and how industries can transform business practices. Meanwhile, start-ups have been working at the confluence of new sources of data (e.g. IoT, DNA, HD pictures, satellite data) and new or revisited processing paradigms (e.g. Edge computing, blockchain, machine learning) to tackle new use cases and to provide disruptive solutions for known problems. This chapter details a collection of stories showing concrete examples of the value created thanks to a renewed usage of data.
Business Models and Ecosystem for Big Data
Authors: Zillner Sonja 
Published: June 2021

AbstractWith the recent technical advances in digitalisation and big data, the real and the virtual worlds are continuously merging, which, again, leads to entire value-added chains being digitalised and integrated. The increase in industrial data combined with big data technologies triggers a wide range of new technical applications with new forms of value propositions that shift the logic of how business is done. To capture these new types of value, data-driven solutions for the industry will require new business models. The design of data-driven AI-based business models needs to incorporate various perspectives ranging from customer and user needs and their willingness to pay for new data-driven solutions to data access and the optimal use of technologies, while taking into account the currently established relationships with customers and partners. Successful data-driven business models are often based on strategic partnerships, with two or more players establishing the basis for sustainable win-win situations through transparent resource-, investment-, risk-, data- and value-sharing. This chapter will explore the different data-driven business approaches and highlight in this context the importance of functioning ecosystems on the various levels. The chapter will conclude with an introduction to the data-driven innovation framework, a proven methodology to guide the systematic investigation of data-driven business opportunities while incorporating the dynamics of the underlying ecosystems.
Innovation in Times of Big Data and AI: Introducing the Data-Driven Innovation (DDI) Framework
Authors: Zillner Sonja 
Published: June 2021

AbstractTo support the process of identifying and scoping data-driven innovation, we are introducing the data-driven innovation (DDI) framework, which provides guidance in the continuous analysis of factors influencing the demand and supply sides of a data-driven innovation. The DDI framework describes all relevant aspects of any generic data-driven innovation and is backed by empirical data and scientific research encompassing a state-of-the-art analysis, an ontology describing the central dimensions of data-driven innovation, as well as a quantitative and representative research study covering more than 90 data-driven innovations. This chapter builds upon a short analysis of the nature of data-driven innovation and provides insights into how to best screen it. It details the four phases of the empirical DDI research study and discusses central findings related to trends, frequencies and distributions along the main dimensions of the DDI framework that could be derived by percentage-frequency analysis.
The Road to Big Data Standardisation
Authors: Walshe Ray 
Published: June 2021

AbstractThis chapter covers the critical topic of standards within the area of big data. Starting with an overview of standardisation as a means for achieving interoperability, the chapter moves on to identify the European Standards Development Organizations that contribute to the European Commission’s plan for the Digital Single Market. The author goes on to describe, through use cases, exemplar big data challenges, demonstrates the need for standardisation and finally identifies the critical big data use cases where standards can add value. The chapter provides an overview of the key standardisation activities within the EU and the current status of international standardisation efforts. Finally, the chapter closes with future trends for big data standardisation.
Technical Research Priorities for Big Data
Authors: Curry Edward , Zillner Sonja , Metzger Andreas , Berre Arne J. , Auer Sören , Walshe Ray , Despenic Marija , Petkovic Milan , Roman Dumitru , Waterfeld Walter , Seidl Robert , Hasan Souleiman , ul Hassan Umair , Ojo Adegboyega 
Published: June 2021

AbstractTo drive innovation and competitiveness, organisations need to foster the development and broad adoption of data technologies, value-adding use cases and sustainable business models. Enabling an effective data ecosystem requires overcoming several technical challenges associated with the cost and complexity of management, processing, analysis and utilisation of data. This chapter details a community-driven initiative to identify and characterise the key technical research priorities for research and development in data technologies. The chapter examines the systemic and structured methodology used to gather inputs from over 200 stakeholder organisations. The result of the process identified five key technical research priorities in the areas of data management, data processing, data analytics, data visualisation and user interactions, and data protection, together with 28 sub-level challenges. The process also highlighted the important role of data standardisation, data engineering and DevOps for Big Data.
Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving Technologies
Authors: Timan Tjerk , Mann Zoltan 
Published: June 2021

AbstractThis chapter addresses privacy challenges that stem particularly from working with big data. Several classification schemes of such challenges are discussed. The chapter continues by classifying the technological solutions as proposed by current state-of-the-art research projects. Three trends are distinguished: (1) putting the end user of data services back as the central focal point of Privacy-Preserving Technologies, (2) the digitisation and automation of privacy policies in and for big data services and (3) developing secure methods of multi-party computation and analytics, allowing both trusted and non-trusted partners to work together with big data while simultaneously preserving privacy. The chapter ends with three main recommendations: (1) the development of regulatory sandboxes; (2) continued support for research, innovation and deployment of Privacy-Preserving Technologies; and (3) support and contribution to the formation of technical standards for preserving privacy. The findings and recommendations of this chapter in particular demonstrate the role of Privacy-Preserving Technologies as an especially important case of data technologies towards data-driven AI. Privacy-Preserving Technologies constitute an essential element of the AI Innovation Ecosystem Enablers (Data for AI).