bluuebunny/crossref_metadata_2025 huggingface dataset:
Injectable Thermosensitive Iodine‐Loaded Starch‐g‐poly(N‐isopropylacrylamide) Hydrogel for Cancer Photothermal Therapy and Anti‐Infection
Authors: Fan Man , Li Mengyao , Wang Xiao , Liao Yonggui , Wang Hong , Rao Jingyi , Yang Yajiang , Wang Qin
Published: April 2022

Although photothermal therapy (PTT) can effectively eliminate tumors, the normal tissues near tumors are inevitably damaged by heat and infected by bacteria, which greatly limits the therapeutic effect. In this work, an injectable thermosensitive hydrogel based on iodine‐loaded starch‐g‐poly(N‐isopropylacrylamide) (PNSI) is developed to overcome this problem. FTIR, 1H NMR, and UV–vis spectra confirm the graft copolymerization of poly(N‐isopropylacrylamide) with starch and the formation of “iodine−starch” complex. Transmission electron microscope images show PNSI polymer self‐assembles into regular spherical nanogel with a size of ≈50 nm. The concentrated nanogel dispersion is a sol at room temperature and transforms to hydrogel at body temperature. Under NIR laser irradiation for 10 min, the ΔT of the nanogel dispersion approachs about 20 °C with excellent thermal stability and high cytotoxicity due to the photothermal effect of the “iodine−starch” complex. After intratumor injection, this injectable hydrogel efficiently inhibites the tumor growth under 808 nm laser irradiation. Furthermore, it can also suppress Staphylococcus aureus infection in the wound post‐PTT due to the release of iodine, which promotes wound healing. Therefore, this injectable thermosensitive “iodine−starch” composite hydrogel with advantages of good biocompatible and easy preparation possesses potential application for tumor photothermal therapy and antibacterial infection.
Nomenclature of Genetic Movement Disorders: Recommendations of the International Parkinson and Movement Disorder Society Task Force – An Update
Authors: Lange Lara M. , Gonzalez‐Latapi Paulina , Rajalingam Rajasumi , Tijssen Marina A.J. , Ebrahimi‐Fakhari Darius , Gabbert Carolin , Ganos Christos , Ghosh Rhia , Kumar Kishore R. , Lang Anthony E. , Rossi Malco , van der Veen Sterre , van de Warrenburg Bart , Warner Tom , Lohmann Katja , Klein Christine , Marras Connie ,   on behalf of the Task Force on Genetic Nomenclature in Movement Disorders
Published: April 2022

In 2016, the Movement Disorder Society Task Force for the Nomenclature of Genetic Movement Disorders presented a new system for naming genetically determined movement disorders and provided a criterion‐based list of confirmed monogenic movement disorders. Since then, a substantial number of novel disease‐causing genes have been described, which warrant classification using this system. In addition, with this update, we further refined the system and propose dissolving the imaging‐based categories of Primary Familial Brain Calcification and Neurodegeneration with Brain Iron Accumulation and reclassifying these genetic conditions according to their predominant phenotype. We also introduce the novel category of Mixed Movement Disorders (MxMD), which includes conditions linked to multiple equally prominent movement disorder phenotypes. In this article, we present updated lists of newly confirmed monogenic causes of movement disorders. We found a total of 89 different newly identified genes that warrant a prefix based on our criteria; 6 genes for parkinsonism, 21 for dystonia, 38 for dominant and recessive ataxia, 5 for chorea, 7 for myoclonus, 13 for spastic paraplegia, 3 for paroxysmal movement disorders, and 6 for mixed movement disorder phenotypes; 10 genes were linked to combined phenotypes and have been assigned two new prefixes. The updated lists represent a resource for clinicians and researchers alike and they have also been published on the website of the Task Force for the Nomenclature of Genetic Movement Disorders on the homepage of the International Parkinson and Movement Disorder Society (https://www.movementdisorders.org/MDS/About/Committees--Other-Groups/MDS-Task-Forces/Task-Force-on-Nomenclature-in-Movement-Disorders.htm). © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.
Qualitative geometric analysis of traveling wave solutions of the modified equal width Burgers equation
Authors: Liu Yongjian , Chen Biyu , Huang Xiezhen , Ye Li , Wei Zhouchao
Published: April 2022

This paper devotes to the qualitative geometric analysis of the traveling wave solutions of MEW‐Burgers wave equation. Firstly, MEW‐Burgers equation is transformed into an equivalent planar dynamical system by using traveling wave transformation. Then the global structure of the planar system is presented, and solitary waves, kink waves (anti‐kink waves), and periodic waves are found. Secondly, Jacobi stability for the planar system is studied based on KCC theory, and Jacobi stability of any point on the trajectory of system is dicussed. The dynamical behavior of the deviation vector near the equilibrium points is analyzed, and the numerical simulation is consistent with the theoretical analysis. Lyapunov stability and Jacobi stability of the equilibrium points are also compared and analyzed. The obtaining results show that Lyapunov stability of the equilibrium points of the system is not exactly consistent with Jacobi stability. Finally, the planar system with periodic disturbance is transformed into a six dimensional nonlinear system, and the periodic, quasi‐periodic, and chaotic dynamical behaviors of the system are numerically simulated.
Anti‐Diabetic Intestinal Mechanisms: Foods, Herbs, and Western Medicines
Authors: Feng Yuwei , Cao Hong , Hua Jiao , Zhang Feng
Published: April 2022

The role of intestinal factors in the pathogenesis of diabetes, such as a decrease in the incretin effect, has recently attracted considerable attention. An imbalance in the gut microbiota inhibits the secretion of incretins, which are metabolic hormones can reduce blood glucose levels, and promotes the occurrence and development of diabetes. Numerous studies have demonstrated that foods are environmental factors that are important in the modulation of gut microbial‐mediated glucose metabolism. In general, functional foods trigger the gut microbiota to produce beneficial metabolites or reduce harmful products through metabolic pathways and then regulate glucose and lipid metabolism. Recent studies have shown that similar to functional foods, the regulatory effects of some herbs and Western medicines are closely related to alterations in the gut microbiota. In this review, the intestinal mechanism of foods, herbs, and Western medicine in affecting the process of glucose metabolism is summarized.
Does response to percutaneous tibial nerve stimulation predict similar outcome to sacral nerve stimulation?
Authors: Kapriniotis Konstantinos , Jenks Julie , Toia Bogdan , Pakzad Mahreen , Gresty Helena , Stephens Ross , Malde Sachin , Sahai Arun , Greenwell Tamsin , Ockrim Jeremy
Published: April 2022

Aims

Percutaneous tibial nerve stimulation (PTNS) is a simple neuromodulation technique to treat an overactive bladder. It is unclear whether the response to PTNS would suggest a similar response to sacral nerve stimulation (SNS), and whether PTNS could be utilized as an alternative test phase for an SNS implant. This study assessed whether PTNS response was a reliable indicator for subsequent SNS trials.

Methods

We performed a retrospective review of the hospital databases to collect all patients who had PTNS and who subsequently had an SNS trial in two tertiary hospitals from 2014 to 2020. Response to both interventions was assessed. A 50% reduction in overactive symptoms (frequency−volume charts) was considered a positive response. McNemar's tests using exact binomial probability calculations were used. The statistical significance level was set to 0.05.

Results

Twenty‐three patients who had PTNS subsequently went on to a trial of SNS. All patients except one had previously poor response to PTNS treatment. Eight of them also failed the SNS trial. However, 15 patients (including the PTNS responder) had a successful SNS trial and proceeded with the second‐stage battery implantation. The difference in response rates between the PTNS and SNS trial was statistically significant (p < 0.001).

Conclusions

Poor response to PTNS does not seem to predict the likelihood of patients responding to SNS. A negative PTNS trial should not preclude a trial of a sacral nerve implant. The predictive factors for good and poor responses will be the subject of a larger study.
Patients’ body image after open abdominal surgery of abdominal aortic aneurysm – Perceptions and experiences
Authors: Pettersson Monica , Mattsson Erney , Bergbom Ingegerd
Published: April 2022

Aims

To explore and gain an understanding of patients’ perceptions and experiences of their body and bodily function in connection with open surgery of abdominal aortic aneurysm.

Background

After the operation of an abdominal aortic aneurysm (AAA) it may be difficult for the patients to understand what the procedure means.

Design

The design was descriptive and based on an analysis of 13 audio‐taped consultations with patients undergoing open surgery for AAA at a Swedish university hospital. The patients’ age varied from 57–79 and the mean age was 71 (70.5 female).

Methods

A hermeneutic approach was used whereby patients were interviewed and draw a picture of their thoughts and experiences of the surgery and what had been done in their bodies. Once patients had finished their drawings, the interviewer asked what thoughts and experiences they had of the AAA.

Results

Patients described experiences as a process of “going from broken to whole again.”
Effect of different nanostructured SiC on thermal, ablation and char layer mechanical properties of ethylene propylene diene monomer composites
Authors: Kun Hui , Li Jiang , Yan Ning , Bian Cheng , Guan Yiwen , Yang Yanjing , Li Hongyan
Published: April 2022

SiC nanowire (SiC‐NW) and SiC nanopowder (SiC‐NP) were used to reinforce ethylene propylene diene monomer (EPDM) composites to improve their ablation and erosion resistance. The mechanical and thermal properties of the composites were investigated. The ablation resistance and thermal insulation performance of the composites were evaluated based on the oxyacetylene ablation and ablation motor experiments. In addition, the particle erosion resistance of the char layer was characterized. The test and experimental results show that, compared with the basic formulation, the ablation resistance of the formulations containing SiC‐NW and SiC‐NP increased by 85.54% and 71.08%, respectively. The particle erosion resistance of the char layer increased by 80.61% and 63.39%, respectively. Meanwhile, the SiC nanofiller reduced the thermal insulation performance of the EPDM composites. Compared with the basic formulation, the maximum back temperature of the SiC‐NW and SiC‐NP formulations increased by 39.23% and 13.08%, respectively. It inferred that during the ablation process, the SiC nanofiller can not only promote the deposition reaction of pyrolysis gas, but also react with oxidizing components and the char layer at different temperatures, thus improving the ablation resistance of the EPDM composites and the strength of the char layer. However, the high thermal conductivity of SiC nanofiller reduces the thermal insulation performance of the composites.
Hydrophilic modification of polypropylene membrane via tannic and titanium complexation for high‐efficiency oil/water emulsion separation driven by self‐gravity
Authors: Wang Huanmin , Guo Xiaoming , Pei Cunbao , Dong Wei , Yao Yongyi
Published: April 2022

Membrane separation technology has played an enormous role in water treatment. However, the surface of the separation membrane has low wettability, and it is easy to cohere with oil droplets during the oil–water separation process, which affects the efficiency of water treatment. To improve its separation property, this article reports the continuous deposition of tannic acid (TA)‐titanium (TiIV) complex interconnected networks with high adhesion and long‐term stability on the surface of polypropylene (PP) membranes to achieve oil–water separation. The hydrophilic TA‐Ti nanostructured coating shows high adhesion and long‐term stability on non‐polar surfaces of the PP membrane. Notably, after modification, the membrane can be used to separate hexadecane‐in‐water emulsions under gravity force, with a separation efficiency of over 99% and a water flux of 227 Lm−2 h−1. Compared with some membranes modified with polyphenols, this easy‐to‐prepare TA‐Ti@PP membrane can achieve better separation performance with only gravity actuation. Furthermore, the modified membrane has superior reusability and excellent chemical stability (salt/acid/alkali resistance), and it has great potential in the field of oil‐in‐water and wastewater treatment.
Spraying of dsRNA molecules derived from Phytophthora infestans, along with nanoclay carriers as a proof of concept for developing novel protection strategy for potato late blight
Authors: S Sundaresha , Sharma Sanjeev , Bairwa Aarti , Tomar Maharishi , Kumar Ravinder , Bhardwaj Vinay , Jeevalatha A. , Bakade Rahul , Salaria Neha , Thakur Kajal , Singh Bir Pal , Chakrabarti S. K.
Published: April 2022

BACKGROUND

Phytophthora infestans is a late blight‐causing oomycetes pathogen. It rapidly evolves and adapts to the host background and new fungicide molecules within a few years of their release, most likely because of the predominance of transposable elements in its genome. Frequent applications of fungicides cause environmental concerns. Here, we developed target‐specific RNA interference (RNAi)‐based molecules, along with nanoclay carriers, that when sprayed on plants are capable of effectively reducing late blight infection.

RESULTS

Targeted the genes unique to sporulation, early satge infection and the metabolism pathway stages based on in an our own microarray data. We used nanoclay as a carrier for sorbitol dehydrogenase, heat shock protein 90, translation elongation factor 1‐α, phospholipase‐D like 3 and glycosylphosphatidylinositol‐anchored acidic serine–threonine‐rich HAM34‐like protein double‐stranded (ds)RNAs, which were assessed by culture bioassay, detached leaf assay and spray methods, and revealed a reduction in growth, sporulation and symptom expression. Plants sprayed with multigene targeted dsRNA–nanoclay showed enhanced disease resistance (4% disease severity) and less sporulation (<1 × 103) compared with plants sprayed with dsRNA alone.

CONCLUSION

The use of nanoclay with multigene targeted dsRNA was assumed to be involved in effective delivery, protection and boosting the action of RNAi as a spray‐induced gene silencing approach (SIGS). A significant reduction in growth, sporulation, disease severity and decreased gene expression authenticates the effects of SIGS on late blight progression. This study demonstrated as a proof of concept the dsRNA–nanoclay SIGS approach, which could be used as an alternative to chemical fungicides and transgenic approaches to develop an environmentally friendly novel plant protection strategy for late blight. © 2022 Society of Chemical Industry.
Metallurgical Data Science for Steel Industry: A Case Study on Basic Oxygen Furnace
Authors: Nenchev Bogdan , Panwisawas Chinnapat , Yang Xiaoan , Fu Jun , Dong Zihui , Tao Qing , Gebelin Jean-Christophe , Dunsmore Andrew , Dong Hongbiao , Li Ming , Tao Biao , Li Fucun , Ru Jintong , Wang Fang
Published: April 2022

The steel industry has developed sensorization to generate data, monitoring systems, and steelmaking process control. The remaining challenges are data storage issues, lack of cross‐production data links, and erroneous datasets, which significantly increase the quality control complexity. The development of a data‐driven approach through artificial intelligence (AI) techniques enables machine learning techniques to big datasets aiming to provide process–property optimization and identify challenges and gaps in the data. Recently, computational capabilities and algorithmic developments have significantly grown in power and complexity, accelerating process optimization. Addressing large‐scale industrial data process–property optimization strategies involve numerous influencing possessing factors but limited data. As one of the largest production chains in the world, the steel industry faces an ever‐increasing demand for larger components, high levels of functionality, and quality of the final product. Herein, an integrated data‐driven steelmaking case study is built with the aim of predicting and optimizing the final product composition and quality. Machine learning is used collaboratively with fundamental knowledge, first‐principal calculation, and feedback into a backpropagation neural network (NN) model. Integrating data mining and machine learning generates reasonable predictions and addresses process efficiencies within the steelmaking furnaces. The ultimate goal is to enhance the digitalization of the steel industry.
Evolution and Deformability of Inclusions in Steel Containing Rare‐Earth Element Under Different Deoxidation Conditions
Authors: Wang Yeguang , Liu Chengjun
Published: April 2022

The experiments under different deoxidation conditions are carried out on the basis of thermodynamic calculation in the Ce–Si–Al–O–S system. The control conditions of various inclusions and the evolution of inclusions are investigated. The results show that Al2O3 is modified to CeAlO3 by adding Ce, which is further transformed to Ce2O2S with the increase of Ce addition in Al‐killed melts. By adding Ce to the melts with Si and Si/Al deoxidation, SiO2 and SiO2–Al2O3 are gradually replaced by Ce2SiO5 and SiO2–Al2O3–Ce2O3 liquid inclusions, respectively. Subsequently, the change of inclusions deformability at low temperature characterized by Young's modulus is calculated in Ce2O3–SiO2–Al2O3 oxide systems. The decrease of Al2O3 content and the increase of Ce2O3 and SiO2 contents improved inclusions deformability by reducing their Young's modulus. The inclusions deformability is improved by modifying SiO2–Al2O3 to SiO2–Al2O3–Ce2O3 inclusion. The Ce2SiO5 with Young's modulus less than 160 Gpa shows good deformability among the RE‐inclusions in this study.
Computational Study of Gas‐Flow and Temperature Dynamics at Blast Furnace Charging
Authors: Mondal Debanga Nandan , Wei Han , Yu Yaowei , Saxén Henrik
Published: April 2022

The burden in the blast furnace is charged to form separate layers of ore and coke, which makes it possible to control the conditions in the shaft because the materials have different gas permeabilities and therefore affect the gas distribution in the shaft. Since ore and coke are of fundamentally different densities, the burden mass flux at different radial locations will vary, which influences the heating of the burden upon its descent. To gain an understanding of the effect of charging on the thermal and flow conditions in the upper shaft, the system is analyzed by computational fluid dynamics combined with the discrete element method. A model of the counter‐current flow of gas and solids and the temperature of the two phases in a simplified setup is developed. It simulates the intermittent charging and continuous descent of burden and the simultaneous ascent of gas through the particle bed. The model captures the complex interaction between the solid and gas flows, which affects the radial temperature distribution due to heat transfer and gas redistribution. The dynamics of the system are illustrated and analyzed using a simple charging cycle, and some implications of the findings are discussed.
COVID‐19 mortality in cirrhosis is determined by cirrhosis‐associated comorbidities and extrahepatic organ failure: Results from the multinational LEOSS registry
Authors: Brozat Jonathan F. , Hanses Frank , Haelberger Martina , Stecher Melanie , Dreher Michael , Tometten Lukas , Ruethrich Maria M. , Vehreschild Janne J. , Trautwein Christian , Borgmann Stefan , Vehreschild Maria J. G. T. , Jakob Carolin E. M. , Stallmach Andreas , Wille Kai , Hellwig Kerstin , Isberner Nora , Reuken Philipp A. , Geisler Fabian , Nattermann Jacob , Bruns Tony ,   the LEOSS study group
Published: April 2022

Background and Objective

International registries have reported high mortality rates in patients with liver disease and COVID‐19. However, the extent to which comorbidities contribute to excess COVID‐19 mortality in cirrhosis is controversial.

Methods

We used the multinational Lean European Open Survey on SARS‐CoV‐2‐infected patients (LEOSS) to identify patients with cirrhosis documented between March 2020 and March 2021, when the wild‐type and alpha variant were predominant. We compared symptoms, disease progression and mortality after propensity score matching (PSM) for age, sex, obesity, smoking status, and concomitant diseases. Mortality was also compared with that of patients with spontaneous bacterial peritonitis (SBP) without SARS‐CoV‐2 infection, a common bacterial infection and well‐described precipitator of acute‐on‐chronic liver failure.

Results

Among 7096 patients with SARS‐CoV‐2 infection eligible for analysis, 70 (0.99%) had cirrhosis, and all were hospitalized. Risk factors for severe COVID‐19, such as diabetes, renal disease, and cardiovascular disease were more frequent in patients with cirrhosis. Case fatality rate in patients with cirrhosis was 31.4% with the highest odds of death in patients older than 65 years (43.6% mortality; odds ratio [OR] 4.02; p = 0.018), Child‐Pugh class C (57.1%; OR 4.00; p = 0.026), and failure of two or more organs (81.8%; OR 19.93; p = 0.001). After PSM for demographics and comorbidity, the COVID‐19 case fatality of patients with cirrhosis did not significantly differ from that of matched patients without cirrhosis (28.8% vs. 26.1%; p = 0.644) and was similar to the 28‐day mortality in a comparison group of patients with cirrhosis and SBP (33.3% vs. 31.5%; p = 1.000).

Conclusions

In immunologically naïve patients with cirrhosis, mortality from wild‐type SARS‐CoV‐2 and the alpha variant is high and is largely determined by cirrhosis‐associated comorbidities and extrahepatic organ failure.
A reinforcement‐learning approach for individual pitch control
Authors: Coquelet Marion , Bricteux Laurent , Moens Maud , Chatelain Philippe
Published: April 2022

Individual pitch control has shown great capability of alleviating the oscillating loads experienced by wind turbine blades due to wind shear, atmospheric turbulence, yaw misalignment, or wake impingement. This work presents a novel controller structure that relies on the separation of low‐level control tasks and high‐level ones. It is based on a neural network that modulates basic periodic pitch angle signals. This neural network is trained with reinforcement learning, a trial and error way of acquiring skills, in a low‐fidelity environment exempt from turbulence. The trained controller is further deployed in large eddy simulations to assess its performances in turbulent and waked flows. Results show that the method enables the neural network to learn how to reduce fatigue loads and to exploit that knowledge to complex turbulent flows. When compared to a state‐of‐the‐art individual pitch controller, the one introduced here presents similar load alleviation capacities at reasonable turbulence intensity levels, while displaying very smooth pitching commands by nature.
Pedagogical approaches for facilitating engineering leadership development
Authors: Didiano Teresa J. , Simpson Annie E. , Bayless David
Published: April 2022

This article describes transformative, impactful pedagogical practices that engage students in the process of leadership development. We share practical examples of instructional strategies and facilitation techniques from curricular and co‐curricular initiatives.
Case Study #7: University of Toronto
Authors: Moore Emily
Published: April 2022

The University of Toronto's Troost ILead helps all engineering students blend research and experiential education to find the leader within.
Big Data Analytics in the Manufacturing Sector: Guidelines and Lessons Learned Through the Centro Ricerche FIAT (CRF) Case
Authors: Alexopoulos Andreas , Becerra Yolanda , Boehm Omer , Bravos George , Chatzigiannakis Vassilis , Cugnasco Cesare , Demetriou Giorgos , Eleftheriou Iliada , Fotis Spiros , Genchi Gianmarco , Ioannidis Sotiris , Jakovetic Dusan , Kallipolitis Leonidas , Katusic Vlatka , Kavakli Evangelia , Kopanaki Despina , Leventis Christoforos , Martínez Miquel , Mascolo Julien , Milosevic Nemanja , Montanera Enric Pere Pages , Ristow Gerald , Ruiz-Ocampo Hernan , Sakellariou Rizos , Sirvent Raül , Skrbic Srdjan , Spais Ilias , Spennacchio Giuseppe Danilo , Stamenkovic Dusan , Vasiliadis Giorgos , Vinov Michael
Published: April 2022

Manufacturing processes are highly complex. Production lines have several robots and digital tools, generating massive amounts of data. Unstructured, noisy and incomplete data have to be collected, aggregated, pre-processed and transformed into structured messages of a common, unified format in order to be analysed not only for the monitoring of the processes but also for increasing their robustness and efficiency. This chapter describes the solution, best practices, lessons learned and guidelines for Big Data analytics in two manufacturing scenarios defined by CRF, within the I-BiDaaS project, namely ‘Production process of aluminium die-casting’, and ‘Maintenance and monitoring of production assets’. First, it reports on the retrieval of useful data from real processes taking into consideration the privacy policies of industrial data and on the definition of the corresponding technical and business KPIs. It then describes the solution in terms of architecture, data analytics and visualizations and assesses its impact with respect to the quality of the processes and products.
Next-Generation Big Data-Driven Factory 4.0 Operations and Optimization: The Boost 4.0 Experience
Authors: Lázaro Oscar , Alonso Jesús , Ohlsson Philip , Tijsma Bas , Lekse Dominika , Volckaert Bruno , Kerkhove Sarah , Nielandt Joachim , Masera Davide , Patrimia Gaetano , Pittaro Pietro , Mulè Giuseppe , Pellegrini Edoardo , Köchling Daniel , Naskos Thanasis , Metaxa Ifigeneia , Leßmann Salome , von Enzberg Sebastian
Published: April 2022

This chapter presents the advanced manufacturing processes and big data-driven algorithms and platforms leveraged by the Boost 4.0 big data lighthouse project that allows improved digital operations within increasingly automated and intelligent shopfloors. The chapter illustrates how three different companies have been able to implement three distinct, open, yet sovereign cross-factory data spaces under a unified framework: the Boost 4.0 big data reference architecture and Digital Factory Alliance (DFA) service development framework.
Leveraging Data-Driven Infrastructure Management to Facilitate AIOps for Big Data Applications and Operations
Authors: McCreadie Richard , Soldatos John , Fuerst Jonathan , Argerich Mauricio Fadel , Kousiouris George , Totow Jean-Didier , Nieto Antonio Castillo , Navidad Bernat Quesada , Kyriazis Dimosthenis , Macdonald Craig , Ounis Iadh
Published: April 2022

As institutions increasingly shift to distributed and containerized application deployments on remote heterogeneous cloud/cluster infrastructures, the cost and difficulty of efficiently managing and maintaining data-intensive applications have risen. A new emerging solution to this issue is Data-Driven Infrastructure Management (DDIM), where the decisions regarding the management of resources are taken based on data aspects and operations (both on the infrastructure and on the application levels). This chapter will introduce readers to the core concepts underpinning DDIM, based on experience gained from development of the Kubernetes-based BigDataStack DDIM platform (https://bigdatastack.eu/). This chapter involves multiple important BDV topics, including development, deployment, and operations for cluster/cloud-based big data applications, as well as data-driven analytics and artificial intelligence for smart automated infrastructure self-management. Readers will gain important insights into how next-generation DDIM platforms function, as well as how they can be used in practical deployments to improve quality of service for Big Data Applications.

This chapter relates to the technical priority Data Processing Architectures of the European Big Data Value Strategic Research & Innovation Agenda [33], as well as the Data Processing Architectures horizontal and Engineering and DevOps for building Big Data Value vertical concerns. The chapter relates to the Reasoning and Decision Making cross-sectorial technology enablers of the AI, Data and Robotics Strategic Research, Innovation & Deployment Agenda [34].
The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures
Authors: Aldinucci Marco , Atienza David , Bolelli Federico , Caballero Mónica , Colonnelli Iacopo , Flich José , Gómez Jon A. , González David , Grana Costantino , Grangetto Marco , Leo Simone , López Pedro , Oniga Dana , Paredes Roberto , Pireddu Luca , Quiñones Eduardo , Silva Tatiana , Tartaglione Enzo , Zapater Marina
Published: April 2022

At the present time, we are immersed in the convergence between Big Data, High-Performance Computing and Artificial Intelligence. Technological progress in these three areas has accelerated in recent years, forcing different players like software companies and stakeholders to move quickly. The European Union is dedicating a lot of resources to maintain its relevant position in this scenario, funding projects to implement large-scale pilot testbeds that combine the latest advances in Artificial Intelligence, High-Performance Computing, Cloud and Big Data technologies. The DeepHealth project is an example focused on the health sector whose main outcome is the DeepHealth toolkit, a European unified framework that offers deep learning and computer vision capabilities, completely adapted to exploit underlying heterogeneous High-Performance Computing, Big Data and cloud architectures, and ready to be integrated into any software platform to facilitate the development and deployment of new applications for specific problems in any sector. This toolkit is intended to be one of the European contributions to the field of AI. This chapter introduces the toolkit with its main components and complementary tools, providing a clear view to facilitate and encourage its adoption and wide use by the European community of developers of AI-based solutions and data scientists working in the healthcare sector and others.
Forschungsdesign und Methoden
Authors: Kumkar Nils C. , Holubek-Schaum Stefan , Gottschall Karin , Hollstein Betina , Schimank Uwe
Published: April 2022

In diesem Kapitel stellen wir die zentralen Aspekte des Forschungsdesigns unserer empirischen Untersuchung vor und erläutern, wie wir methodisch vorgegangen sind: die Auswahl der untersuchten Fälle, den Einsatz biographisch-narrativer Interviews mit leitfadengestützten Nachfrageteilen und die Auswertung der Interviews mit der dokumentarischen Methode.
New dressing factors for AdS3/CFT2
Authors: Frolov Sergey , Sfondrini Alessandro
Published: April 2022

Abstract

The worldsheet S matrix of strings on the AdS3× S3× T4 background is almost entirely fixed by symmetries, up to five functions — the dressing factors. These must satisfy several consistency conditions, in particular a set of crossing equations. We find that the existing proposal for the dressing factors, while crossing invariant, violates some of these consistency conditions. We put forward a new set of dressing factors and discuss in detail their analytic properties in the string and mirror region, as well as under bound-state fusion.
Frugal U(1)X models with non-minimal flavor violation for b → sℓℓ anomalies and neutrino mixing
Authors: Bhatia Disha , Desai Nishita , Dighe Amol
Published: April 2022

Abstract

We analyze the class of models with an extra U(1)X gauge symmetry that can account for the b → sℓℓ anomalies by modifying the Wilson coefficients C9e and C9μ of the operators $$ {O}_{9\mathrm{\ell}}\equiv \left(\overline{b}{\gamma}_{\mu }{P}_Ls\right)\left(\overline{\mathrm{\ell}}{\gamma}^{\mu}\mathrm{\ell}\right) $$

O

9
ℓ

≡

b
¯

γ
μ

P
L

s

ℓ
¯

γ
μ

ℓ

from their standard model values. At the same time, these models generate appropriate quark mixing, and give rise to neutrino mixing via the Type-I seesaw mechanism. Apart from the gauge boson Z′, these frugal models only have three right-handed neutrinos for the seesaw mechanism, an additional SU(2)L scalar doublet for quark mixing, and a SM-singlet scalar that breaks the U(1)X symmetry. This set-up identifies a class of leptonic symmetries, and necessitates non-zero but equal charges for the first two quark generations. If the quark mixing beyond the standard model were CKM-like, all these symmetries would be ruled out by the latest flavor constraints on Wilson coefficients and collider constraints on Z′ parameters. However, we identify a single-parameter source of non-minimal flavor violation that allows a wider class of U(1)X symmetries to be compatible with all data. We show that the viable leptonic symmetries have to be of the form Le± 3Lμ− Lτ or Le− 3Lμ + Lτ, and determine the (MZ′, gZ′) parameter space that may be probed by the high-luminosity data at the LHC.
Teleparallelism in the algebraic approach to extended geometry
Authors: Cederwall Martin , Palmkvist Jakob
Published: April 2022

Abstract

Extended geometry is based on an underlying tensor hierarchy algebra. We extend the previously considered L∞ structure of the local symmetries (the diffeomorphisms and their reducibility) to incorporate physical fields, field strengths and Bianchi identities, and identify these as elements of the tensor hierarchy algebra. The field strengths arise as generalised torsion, so the naturally occurring complex in the L∞ algebra is$$ \dots \leftarrow \mathrm{torsion}\ \mathrm{BI}'\mathrm{s}\leftarrow \mathrm{torsion}\leftarrow \mathrm{vielbein}\leftarrow \mathrm{diffeomorphism}\ \mathrm{parameters}\leftarrow \dots $$
…
←
torsion

BI
’
s
←
torsion
←
vielbein
←
diffeomorphism parameters
←
…

In order to obtain equations of motion, which are not in this complex, (pseudo-)actions, quadratic in torsion, are given for a large class of models. This requires considering the dual complex. We show how local invariance under the compact subgroup locally defined by a generalised metric arises as a “dual gauge symmetry” associated with a certain torsion Bianchi identity, generalising Lorentz invariance in the teleparallel formulation of gravity. The analysis is performed for a large class of finite-dimensional structure groups, with E5 as a detailed example. The continuation to infinite-dimensional cases is discussed.
Algorithmic fairness through group parities? The case of COMPAS-SAPMOC
Authors: Lagioia Francesca , Rovatti Riccardo , Sartor Giovanni
Published: April 2022

Machine learning classifiers are increasingly used to inform, or even make, decisions significantly affecting human lives. Fairness concerns have spawned a number of contributions aimed at both identifying and addressing unfairness in algorithmic decision-making. This paper critically discusses the adoption of group-parity criteria (e.g., demographic parity, equality of opportunity, treatment equality) as fairness standards. To this end, we evaluate the use of machine learning methods relative to different steps of the decision-making process: assigning a predictive score, linking a classification to the score, and adopting decisions based on the classification. Throughout our inquiry we use the COMPAS system, complemented by a radical simplification of it (our SAPMOC I and SAPMOC II models), as our running examples. Through these examples, we show how a system that is equally accurate for different groups may fail to comply with group-parity standards, owing to different base rates in the population. We discuss the general properties of the statistics determining the satisfaction of group-parity criteria and levels of accuracy. Using the distinction between scoring, classifying, and deciding, we argue that equalisation of classifications/decisions between groups can be achieved thorough group-dependent thresholding. We discuss contexts in which this approach may be meaningful and useful in pursuing policy objectives. We claim that the implementation of group-parity standards should be left to competent human decision-makers, under appropriate scrutiny, since it involves discretionary value-based political choices. Accordingly, predictive systems should be designed in such a way that relevant policy goals can be transparently implemented. Our paper presents three main contributions: (1) it addresses a complex predictive system through the lens of simplified toy models; (2) it argues for selective policy interventions on the different steps of automated decision-making; (3) it points to the limited significance of statistical notions of fairness to achieve social goals.
Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer
Authors: Tollens Fabian , Baltzer Pascal A. T. , Dietzel Matthias , Schnitzer Moritz L. , Schwarze Vincent , Kunz Wolfgang G. , Rink Johann , Rübenthaler Johannes , Froelich Matthias F. , Schönberg Stefan O. , Kaiser Clemens G.
Published: April 2022

Objectives

Abbreviated breast MRI (AB-MRI) was introduced to reduce both examination and image reading times and to improve cost-effectiveness of breast cancer screening. The aim of this model-based economic study was to analyze the cost-effectiveness of full protocol breast MRI (FB-MRI) vs. AB-MRI in screening women with dense breast tissue for breast cancer.

Methods

Decision analysis and a Markov model were designed to model the cumulative costs and effects of biennial screening in terms of quality-adjusted life years (QALYs) from a US healthcare system perspective. Model input parameters for a cohort of women with dense breast tissue were adopted from recent literature. The impact of varying AB-MRI costs per examination as well as specificity on the resulting cost-effectiveness was modeled within deterministic sensitivity analyses.

Results

At an assumed cost per examination of $ 263 for AB-MRI (84% of the cost of a FB-MRI examination), the discounted cumulative costs of both MR-based strategies accounted comparably. Reducing the costs of AB-MRI below $ 259 (82% of the cost of a FB-MRI examination, respectively), the incremental cost-effectiveness ratio of FB-MRI exceeded the willingness to pay threshold and the AB-MRI-strategy should be considered preferable in terms of cost-effectiveness.

Conclusions

Our preliminary findings indicate that AB-MRI may be considered cost-effective compared to FB-MRI for screening women with dense breast tissue for breast cancer, as long as the costs per examination do not exceed 82% of the cost of a FB-MRI examination.

Key Points

• Cost-effectiveness of abbreviated breast MRI is affected by reductions in specificity and resulting false positive findings and increased recall rates.

• Abbreviated breast MRI may be cost-effective up to a cost per examination of 82% of the cost of a full protocol examination.

• Abbreviated breast MRI could be an economically preferable alternative to full protocol breast MRI in screening women with dense breast tissue.
Serum albumin at resection predicts in-hospital death, while serum lactate and aPTT on the first postoperative day anticipate anastomotic leakage after Ivor-Lewis-esophagectomy
Authors: Scheufele Florian , Vogel Thomas , Gasiorek Melanie , Novotny Alexander , Friess Helmut , Demir Ihsan Ekin , Schorn Stephan
Published: April 2022

Background

Anastomotic leakage (AL) is a major complication after esophagectomy, potentiating morbidity and mortality. There are several patient risk factors associated with AL, but high-fidelity postoperative predictors are still under debate. The aim was to identify novel reliable predictors for AL after esophagectomy.

Methods

A high-volume single-center database study, including 138 patients receiving Ivor-Lewis-esophagectomy between 2017 and 2019, was performed. Serum levels of albumin, aPTT, and lactate before and after surgery were extracted to assess their impact on AL and in-hospital mortality.

Results

High serum lactate on postoperative day 1 (POD1) could be shown to predict AL after esophagectomy [AL vs. no AL: 1.2 (0.38) vs. 1.0 (0.37); p < 0.001]. Accordingly, also differences of serum lactate level between end (POD0-2) and start of surgery (POD0-1) (p < 0.001) as well as between POD1 and POD0-1 (p < 0.001) were associated with AL. Accordingly, logistic regression identified serum lactate on POD 1 as an independent predictor of AL [HR: 4.37 (95% CI: 1.28–14.86); p = 0.018]. Further, low serum albumin on POD0 [2.6 (0.53) vs. 3.1 (0.56); p = 0.001] and high serum lactate on POD 0–1 [1.1 (0.29) vs. 0.9 (0.30); p = 0.043] were associated with in-hospital death. Strikingly, logistic-regression (HR: 0.111; p = 0.008) and cox-regression analysis (HR: 0.118; p = 0.003) showed low serum albumin as an independently predictor for in-hospital death after esophagectomy.

Conclusions

This study identified high serum lactate as an independent predictor of AL and low serum albumin as a high-fidelity predictor of in-hospital death after esophagectomy. These parameters can facilitate improved postoperative treatment leading to better short-term as well as long-term outcomes.
Multisensory synchrony of contextual boundaries affects temporal order memory, but not encoding or recognition
Authors: van de Ven Vincent , Kleuters Guyon , Stuiver Joey
Published: April 2022

We memorize our daily life experiences, which are often multisensory in nature, by segmenting them into distinct event models, in accordance with perceived contextual or situational changes. However, very little is known about how multisensory boundaries affect segmentation, as most studies have focused on unisensory (visual or audio) segmentation. In three experiments, we investigated the effect of multisensory boundaries on segmentation in memory and perception. In Experiment 1, participants encoded lists of pictures while audio and visual contexts changed synchronously or asynchronously. After each list, we tested recognition and temporal associative memory for pictures that were encoded in the same audio-visual context or that crossed a synchronous or an asynchronous multisensory change. We found no effect of multisensory synchrony for recognition memory: synchronous and asynchronous changes similarly impaired recognition for pictures encoded at those changes, compared to pictures encoded further away from those changes. Multisensory synchrony did affect temporal associative memory, which was worse for pictures encoded at synchronous than at asynchronous changes. Follow up experiments showed that this effect was not due to the higher dimensionality of multisensory over unisensory contexts (Experiment 2), nor that it was due to the temporal unpredictability of contextual changes inherent to Experiment 1 (Experiment 3). We argue that participants formed situational expectations through multisensory synchronicity, such that synchronous multisensory changes deviated more strongly from those expectations than asynchronous changes. We discuss our findings in light of supportive and conflicting findings of uni- and multi-sensory segmentation.
Heterogenous NECTIN4 expression in urothelial high-risk non-muscle-invasive bladder cancer
Authors: Garczyk Stefan , Degener Stephan , Bischoff Felix , Schnitzler Tician , Salz Anne , Golz Reinhard , Buchner Alexander , Schulz Gerald B. , Schneider Ursula , Gaisa Nadine T. , Knüchel Ruth
Published: April 2022

High-grade non-muscle-invasive bladder cancer (HG NMIBC) patients are at high risk (HR) of progression to muscle-invasion. Bladder-preserving therapies for this patient subgroup are limited, and additional treatments are desirable. Recently, enfortumab vedotin, targeting cancer-associated NECTIN4, has been approved for the treatment of advanced urothelial carcinoma. However, data on the expression of NECTIN4 and its therapeutic potential for HR NMIBC are scarce. Here, NECTIN4 was immunohistochemically analyzed in urothelial HG NMIBC by studying cohorts of carcinoma in situ (CIS)/T1HG (N = 182 samples), HG papillary tumors from mixed-grade lesions (mixed TaHG) (N = 87) and papillary HG tumors without a history of low-grade disease (pure TaHG/T1HG) (N = 98) from overall 225 patients. Moreover, inter-lesional NECTIN4 heterogeneity in multifocal HG NMIBC tumors was determined. A high prevalence of NECTIN4 positivity was noted across HG NMIBC subgroups (91%, N = 367 samples), with 77% of samples showing moderate/strong expression. Heterogenous NECTIN4 levels were observed between HG NMIBC subgroups: non-invasive areas of CIS/T1HG and pure TaHG/T1HG samples showed NECTIN4 positivity in 96% and 99%, with 88% and 83% moderate/strong expressing specimens, respectively, whereas significantly lower NECTIN4 levels were detected in mixed TaHG lesions (72% positivity, 48% of samples with moderate/strong NECTIN4 expression). Moreover, higher NECTIN4 heterogeneity was observed in patients with multifocal mixed TaHG tumors (22% of patients) compared to patients with multifocal CIS/T1HG and pure TaHG/T1HG tumors (9% and 5%). Taken together, NECTIN4-directed antibody–drug conjugates might be promising for the treatment of HR NMIBC patients, especially for those exhibiting CIS/T1HG and pure TaHG/T1HG tumors without a history of low-grade disease.
Paediatric intestinal pseudo-obstruction: a scoping review
Authors: Nham Susan , Nguyen Alexander T. M. , Holland Andrew J. A.
Published: April 2022

Paediatric intestinal pseudo-obstruction (PIPO) encompasses a group of rare disorders in which patients present with the clinical features of bowel obstruction in the absence of mechanical occlusion. The management of PIPO presents a challenge as evidence remains limited on available medical and surgical therapy. Parenteral nutrition is often the mainstay of therapy. Long-term therapy may culminate in life-threatening complications including intestinal failure-related liver disease, central line thrombosis and sepsis. Intestinal transplantation remains the only definitive cure in PIPO but is a complex and resource-limited solution associated with its own morbidity and mortality. We conducted a scoping review to present a contemporary summary of the epidemiology, aetiology, pathophysiology, diagnosis, management and complications of PIPO.

Conclusion: PIPO represents a rare disorder that is difficult to diagnose and challenging to treat, with significant morbitity and mortality. The only known cure is intestinal transplantation.

What is Known:• Paediatric intestinal pseudo-obstruction is a rare, heterogeneous disorder that confers a high rate of morbidity and mortality• Complications of paediatric intestinal pseudo-obstruction include chronic pain, small intestine bacterial overgrowth and malrotation. Other complications can occur related to its management, such as line infections with parenteral nutrition or cardiac side effects of prokinetic medications

What is New:• Progress in medical and surgical therapy in recent years has led to improved patient outcomes• Enteral autonomy has been reported in most patients at as early as 1 month post-transplantation