bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prophylaxis for Pneumocystis jirovecii pneumonia in patients with inflammatory bowel disease: A systematic review
Authors: Sierra Caroline M. , Daiya Krishna C. 
Published: October 2022

AbstractPatients with inflammatory bowel disease (IBD) are at increased risk of developing Pneumocystis jirovecii pneumonia (PJP) than the general population. Many medications utilized for the treatment of IBD affect the immune system, potentially further increasing the risk of PJP. Recommendations for prophylaxis against PJP in this patient population are based upon limited evidence, and risk factors for PJP development are not well‐agreed upon. The purpose of this systematic review was to consolidate and evaluate the evidence for PJP prophylaxis in patients with IBD. An electronic literature search was performed, and 29 studies were included in the review, of which 24 were case reports or case series. Combined data from five cohort studies showed an absolute risk of developing PJP to be 0.07%. The majority of patients who developed PJP were receiving corticosteroids at the time of diagnosis (76%). The number of concomitant immunosuppressants received at time of PJP diagnosis varied from one to four. All studies reporting treatment of PJP utilized sulfamethoxazole‐trimethoprim. Of the 27 studies reporting mortality data, 19% of patients died. Given the lack of conclusive data regarding risk factors for PJP development and the overall low incidence of PJP in patients with IBD, it is recommended to assess the patient's risk on a case‐by‐case basis to determine whether PJP prophylaxis is warranted.
Effect of tetraethylene glycol side chain conformation on chiroptical properties of chirality‐induced benzocoumarin
Authors: Ozturk Perihan , Akdag Akin 
Published: October 2022

AbstractCoumarins are multifaceted molecules with compelling fluorescence features. Along with biocompatible properties, they have recently been used in chiroptical studies. The chirality induction to benzo[f]coumarin moiety at the third position was investigated in this study. The chromophore derivatized with homochiral alanine and phenylalanine resulted in identical spectroscopic properties. When the chiroptical properties are concerned, the distinct CD spectra of both structures are also changed significantly by altering the organic solvent. Inter‐ and intra‐molecular hydrogen bonding affects the CD spectra along with the chiroptical signal. The phenylalanine‐benzo[f]coumarin structures were modified with TEG units to increase water solubility and enhance ordered aggregations. The chiroptical properties of the compounds were analyzed in organic solvents with spectroscopic techniques. It was found that coumarin is not only sensitive to the chiral unit attached but also that any conformational change on the side chain affects the chiroptical signal. Time‐dependent DFT calculations in the gas phase supported these results.
Utility of unmanned aerial systems for measuring plant height and plant vigor among several Georgia runner peanut cultivars
Authors: Brown Nino , Zhang Jing , Maleski Jerome , Schwartz Brian , Branch William D. 
Published: October 2022

AbstractStand establishment, early‐season seedling vigor, and mid‐season canopy closure ensure peanut growers’ timely achievement of a vigorous crop that can resist weeds, take advantage of available moisture and nutrients, and produce optimal yield. Direct measurement of these traits is prohibitively time consuming in large breeding trials and nurseries. Estimations based on visual ratings are rapid but require extensive training and experience for reliable data. Technological improvements in camera and unmanned aerial systems (UAS) has made them a practical and beneficial tool for plant breeders. This study evaluated the use of UAS for measuring plant growth‐related traits in a replicated yield trial of 16 Georgia runner‐type peanut cultivars. Flights were conducted at similar times with ground measurements and visual ratings of seedling and mid‐season plant vigor at the University of Georgia's Gibbs Research Farm in Tifton, GA, from 2019 to 2021. High correlations and similar ranks were seen between UAS‐derived and manual measurements for plant height among cultivars evaluated at mid‐season and late‐season (r2 = 0.95 and 0.75, respectively). For early‐season vigor evaluations, moderate correlations were achieved (r2 = 0.11–0.41), however, high correlations and similar results were evident comparing UAS‐derived mid‐season growth characteristics and visual vigor ratings (r2 = 0.75–0.86). Given the affordability and efficiency of data collection, UAS‐based phenotyping provides a promising and powerful tool for high throughput peanut breeding programs.
Humanistic school science: Research, policy, politics and classrooms
Authors: Aikenhead Glen S. 
Published: October 2022

AbstractThis article establishes a rational, feasible, and necessary conclusion to reform high school science content into an equitable experience for its wide diversity of students' self‐identities. Research indicates that 85% of graduates would not normally have enrolled in any science course unless required. Their values are more aligned with their everyday world and/or the world of the humanities, to varying degrees. The 15% had already fulfilled their science prerequisite for postsecondary science‐related programs, to varying degrees. The article's conclusion rests mainly on historical and economic evidence, respectively: (1) The Sputnik crisis that instilled public fear and anxiety about the perceived technological gap between the United States and Soviet Union. This led to reforming high school science and implementing National Aeronautics and Space Administration. (2) The on‐growing climate‐change crisis for which the smart international money is increasingly investing in sustainable businesses and industries, which catalyze a shift in public values from the current “profit society” to a “sustainable society.” The article's rationale connects the two historical events. Over the past 30 years, the nature of normal science has evolved into post‐normal science. Today the public square also includes: (a) an international assessment project that receives a negative validity audit in this article; (b) a vocal small minority within the 85%, proud of their antiscience self‐identities and their leaders' hostile behavior (a problem to ameliorate by a reformed sustainable science education); and (c) instances of small‐scale, suitable reform examples developed over the last 70 years, often referred to as humanistic school science.
Application of New Magnetic Graphene Oxide‐Porphyrin Nanoparticles for Synthesis of Pyridines and Pyrimidines via Anomeric‐Based Oxidation
Authors: Dashteh Mohammad , Baghery Saeed , Zolfigol Mohammad Ali , Khazaei Ardeshir , Khajevand Masuood 
Published: October 2022

AbstractHerein joining of poly graphene oxide‐porphyrin to magnetic nanoparticles {poly Fe3O4@SiO2@(CH2)3‐GO‐[PTTA‐NH−Ni] MNPs} was occurred. The synthesized catalyst was characterized by several techniques such as FT‐IR, CHN elemental analysis, EDX, WDX elemental maps, TGA, DTG, DTA, XRD, FE‐SEM, TEM, BET, BJH, VSM, and ICP‐AES. The described magnetic nanoparticles were employed as a benign catalyst for the expedient synthesis of 5‐amino‐7‐aryl‐2‐oxo‐2,3‐dihydrothiazolo[4,5‐b] pyridine‐6‐carbonitriles via anomeric‐based oxidation mechanistic pathway. Target molecules were prepared through a four‐component reaction of 2,4‐thiazolidinedione, aldehydes, malononitrile, and ammonium acetate under solvent‐free conditions at 75 °C. Also, the application of the presented catalyst was investigated under the same reaction conditions for the synthesis of 5,7‐diaryl‐4,7‐dihydro‐[1,2,4]triazolo[1,5‐a]pyrimidines through the three‐component reaction of aldehydes, acetophenones, and 3‐amino‐1,2,4‐triazole.
Probing N‐Alkoxy Effects in Domino Reactions of α‐Bromoacetamide Derivatives Towards Functionalized γ‐Lactams
Authors: Champetter Philippe , Alahyen Ismail , Taillier Catherine , Brière Jean‐François , Dalla Vincent , Oudeyer Sylvain , Comesse Sébastien 
Published: October 2022

AbstractThe main objective of the present work is to better delineate the positive impact of N‐alkoxy versus N‐alkyl moieties in domino reactions. The key role of the metallic counterion of the basic reagent via a templating effect has been established, giving an insight over the superiority of N‐alkoxy α‐bromoacetamides compared to their N‐alkyl analogues. The former demonstrated enhanced reactivity and efficiency, thus requiring milder conditions and leading to a wider scope of γ‐lactams in good to excellent yields ranging from 67 to 98%. Overall, this study contributes to the emerging point of view that N‐alkoxy nitrogenated compounds are useful building blocks with powerful but still under‐developed synthetic potential, in particular in domino reactions.
The State of Diversity in Computer Science in 2022
Authors: Bjørn Pernille , Menendez-Blanco Maria , Borsotti Valeria 
Published: October 2022

Abstract‘Datalogy’ (or computer science) is the academic foundation and practice that determines how digital technologies are designed, developed, and introduced into peoples’ lives. Digital technologies shape society, life, and work and influence how people think and act with technology in all aspects of life. In a democracy it is vital that the people who create technology mirror the society’s diversity, to ensure that new digital technologies do not constrain people’s agency but enable people to act and take part in society. Today, in 2022, diversity and inclusion is one of the main challenges for computer science as a field and profession in Western countries such as Denmark and the USA (Frieze and Quesenberry 2019; Borsotti and Bjørn 2022), and studies have shown that computer science will not reach gender parity in this century (Holman et al. 2018) without interventions directed at change.
Equity & Inclusion
Authors: Bjørn Pernille , Menendez-Blanco Maria , Borsotti Valeria 
Published: October 2022

AbstractWhen beginning our research on equity, diversity, and inclusion under the umbrella of FemTech.dk research, we engaged with new literature, theory, and analytical approaches from research on equity and inclusion – research we did not know prior to FemTech.dk but which has been fundamental to our activities. In this chapter, we introduce the theoretical vocabulary we have learned as we entered this research space. Our purpose is to provide a short introduction to the most important concepts we found essential and relevant for our purpose of exploring diversity in computer science and to give readers a quick introduction to the most important concepts, which they then can use to initiate equity work in their institutions.
Online Path Planning in a Multi-agent-Controlled Manufacturing System
Authors: Ramasamy Sudha , Bennulf Mattias , Zhang Xiaoxiao , Hammar Samuel , Danielsson Fredrik 
Published: October 2022

AbstractIn recent years the manufacturing sectors are migrating from mass production to mass customization. To be able to achieve mass customization, manufacturing systems are expected to be more flexible to accommodate the different customizations. The industries which are using the traditional and dedicated manufacturing systems are expensive to realize this transition. One promising approach to achieve flexibility in their production is called Plug & Produce concept which can be realized using multi-agent-based controllers. In multi-agent systems, parts and resources are usually distributed logically, and they communicate with each other and act as autonomous agents to achieve the manufacturing goals. During the manufacturing process, an agent representing a robot can request a path for transportation from one location to another location. To address this transportation facility, this paper presents the result of a futuristic approach for an online path planning algorithm directly implemented as an agent in a multi-agent system. Here, the agent systems can generate collision-free paths automatically and autonomously. The parts and resources can be configured with a multi-agent system in the manufacturing process with minimal human intervention and production downtime, thereby achieving the customization and flexibility in the production process needed.
Detachable, Low-Cost Tool Holder for Grippers in Human-Robot Interaction
Authors: Schmidbauer Christina , Küffner-McCauley Hans , Schlund Sebastian , Ophoven Marcus , Clemenz Christian 
Published: October 2022

AbstractTo hand over more than just pick & place tasks to an industrial collaborative robotic arm with a two-jaw gripper, the gripper must first be removed, and a new tool mounted. This tool change requires either human assistance or an expensive tool changer. The tools applied to the end-effector are often highly expensive and software system interfaces between different tools and robots are seldom available. Therefore, a holder was developed that allows the robot to pick up and operate a tool, such as an electric screwdriver, without having to demount the two-jaw gripper. Instead, the gripper’s functionality is used to activate and deactivate the tool fixed to the holder. This paper presents the state-of-the-art of the underlying problem as well as the development process including simulations, the patented design, and the low-cost production of the tool holder. This detachable, low-cost tool holder enables a flexibilization of human-robot processes in manufacturing.
A Conceptual Framework of a Digital-Twin for a Circular Meat Supply Chain
Authors: Valero M. R. , Hicks B. J. , Nassehi A. 
Published: October 2022

AbstractEvery year more than 900 million tonnes of food is wasted, contributing to almost 10% of total greenhouse gas emissions. Reducing food waste has been identified as essential to tackle the current climate crisis, and links to several UN’s sustainable development goals. This is especially critical for energy and resource-intensive food products like meat, whose consumption is predicted to reach an historical maximum by 2030. Whilst wastage occurs at all stages of the supply chain, tractable data about the journey of food from production to consumer remains largely hidden or unrecorded. Powered by the latest advances in sensing like smart food packaging and digital technologies such as Big Data and IoT, Digital Twins offer a valuable opportunity to monitor and control meat products and processes across the whole supply chain, enabling food waste to be reduced and by-products reintegrated into the supply chain. This paper proposes a new framework for a Digital Twin that integrates key technological enablers across different areas of the meat supply chain towards with the goal of a “zero-waste”, circular meat supply chain.
A Survey of Smart Manufacturing for High-Mix Low-Volume Production in Defense and Aerospace Industries
Authors: Tahmina Tanjida , Garcia Mauro , Geng Zhaohui , Bidanda Bopaya 
Published: October 2022

AbstractDefense and aerospace industries usually possess unique high-mix low-volume production characteristics. This uniqueness generally calls for prohibitive production costs and long production lead-time. One of the major trends in advanced, smart manufacturing is to be more responsive and better readiness while ensuring the same or higher production quality and lower cost. This study reviews the state-of-the-art manufacturing technologies to solve these issues and previews two levels of flexibility, i.e., system and process, that could potentially reduce the costs while increasing the production volume in such a scenario. The main contribution of the work includes an assessment of the current solutions for HMLV scenarios, especially within the defense of aerospace sectors, and a survey of the current and potential future practices focusing on smart production process planning and flexible assembly plan driven by emerging techniques.
Manufacturing Process Optimization via Digital Twins: Definitions and Limitations
Authors: Papacharalampopoulos Alexios , Stavropoulos Panagiotis 
Published: October 2022

AbstractManufacturing process real-time optimization has been one of the main digital twins’ operations. It is of utmost importance to the processes, since it enables the feedback of a digital twin towards the real world. However, it is quite difficult to be implemented, since it requires modelling of the process, adaptivity of both the model and the process, real-time communication and link to other functionalities. Under the framework of formalizing such activities, the current work attempts to categorize the types of manufacturing process real-time optimization and show their limitations. For the sake of simplicity, generic process models are adopted and then the requirements for the process control are given, driving the aforementioned definitions. Specific numerical examples are used to illustrate the definitions, while the latter presented herein span all categories of real-time optimization as well as all manufacturing performance indicators. Finally, both mathematically and physics-wise, the limitations are discussed.
Generation of an Intermediate Workpiece for Planning of Machining Operations
Authors: Šormaz Dušan , Campos Anibal Careaga , Arumugam Jaikumar 
Published: October 2022

AbstractDigital twins in manufacturing plays a key factor for the digital transformation. A necessary component of any digital twin in manufacturing is a geometric model of a workpiece as it is processed through steps. DT requires solid 3d models, machining features, and information regarding machines, tools, and its constraints such as initial setup, machining direction, etc. The objective of this paper is to generate alternate feature interpretations to identify geometric constraints, machine and tool requirements, and stock materials to generate flexible manufacturing plans that fit a defined criterion. In this study we propose using the IMPlanner system to retrieve a 3d model from a CAD software, read its geometric features and convert them into possible machining features. This information along with information from the database of stock materials, tools, machines, and tolerances, the system generates several feature interpretations, thus offering a more flexible manufacturing plan.
High Precision Fabrication of an Innovative Fiber-Optic Displacement Sensor
Authors: Elrawashdeh Zeina , Revel Philippe , Prelle Christine , Lamarque Frédéric 
Published: October 2022

AbstractThis study presents the high precision fabrication technique, employed to manufacture a 3D conical grating, used as the reflector element, for a fiber-optic displacement sensor. To get high performance in terms of the surface quality, as well as a dimensional precision, the surface of the reflector must be a polished-mirror surface. To do so, a high precision turning machine along with aluminum alloy were the technical choices made. Two prototypes with different geometric dimensions, have been fabricated using the same machining strategy. Single crystal diamond tool was chosen, to obtain high surface roughness. The followed machining procedure was divided into two main parts; the first part achieves several cuts, to get the desired dimensions, and the last cut is deduced to get the desired nanometric roughness. Good results have been obtained, which validates the followed machining procedure.
Deep Anomaly Detection for Endoscopic Inspection of Cast Iron Parts
Authors: Schmedemann Ole , Miotke Maximilian , Kähler Falko , Schüppstuhl Thorsten 
Published: October 2022

AbstractDetecting anomalies in image data plays a key role in automated industrial quality control. For this purpose, machine learning methods have proven useful for image processing tasks. However, supervised machine learning methods are highly dependent on the data with which they have been trained. In industrial environments data of defective samples are rare. In addition, the available data are often biased towards specific types, shapes, sizes, and locations of defects. On the contrary, one-class classification (OCC) methods can solely be trained with normal data which are usually easy to obtain in large quantities. In this work we evaluate the applicability of advanced OCC methods for an industrial inspection task. Convolutional Autoencoders and Generative Adversarial Networks are applied and compared with Convolutional Neural Networks. As an industrial use case we investigate the endoscopic inspection of cast iron parts. For the use case a dataset was created. Results show that both GAN and autoencoder-based OCC methods are suitable for detecting defective images in our industrial use case and perform on par with supervised learning methods when few data are available.
Kritische Betrachtung
Authors: Lorenz Sandro 
Published: October 2022

ZusammenfassungMethodisch ist festzuhalten, dass mit der erreichten Fallzahl von 621 eingeschlossenen Patienten die notwendige statistische Power erreicht wurde, um auch geringe Effektstärken detektieren zu können. Bei der ermittelten post-hoc Effektstärke für die Patientenzufriedenheit wäre schon eine Fallzahl von 210 ausreichend gewesen. Der Modus der Datenerhebung mit Hilfe eines anonymen Fragebogens sollte Verzerrungen durch den Einfluss der sozialen Erwünschtheit bestmöglich begrenzen.
Interacting conformal scalar in a wedge
Authors: Bissi Agnese , Dey Parijat , Sisti Jacopo , Söderberg Alexander 
Published: October 2022

Abstract
We study a class of two-point functions in a conformal field theory near a wedge. This is a set-up with two boundaries intersecting at an angle θ. We compute it as a solution to the Dyson-Schwinger equation of motion for a quartic interaction in the d = 4 − ϵ bulk and on one of the boundaries in d = 3 − ϵ, up to order (ϵ). We have extracted the anomalous dimensions from such correlators, which we complemented with Feynman diagrams computations.
Upper bounds of holographic entanglement entropy growth rate for thermofield double states
Authors: Li Ze , Yang Run-Qiu 
Published: October 2022

Abstract
We studied the upper bounds of the holographic entanglement entropy growth rate for thermofield double (TFD) states. By comparing the cases of vacuum AdS and charged AdS black holes, we conjecture: for all static planar or spherically symmetric asymptotically Schwarzschild-AdS black holes of same mass density or entropy density, the vacuum AdS black hole gives the maximum entanglement entropy growth rate. We gave proofs by assuming dominant energy condition. We also considered the AdS black hole spacetime with real scalar fields case, where the scalar fields violate the dominant energy condition and the bulk geometry is not asymptotically Schwarzschild-AdS. Numerical results show that this case vacuum black hole still has maximal growth rate if we fixed entropy. However, in the case of fixed energy, vacuum case has maximal growth rate of entanglement entropy only under standard quantization scheme.
Multi-component dark sectors: symmetries, asymmetries and conversions
Authors: Bas i Beneito Arnau , Herrero-García Juan , Vatsyayan Drona 
Published: October 2022

Abstract
We study the relic abundance of several stable particles from a generic dark sector, including the possible presence of dark asymmetries. After discussing the different possibilities for stabilising multi-component dark matter, we analyse the final relic abundance of the symmetric and asymmetric dark matter components, paying special attention to the role of the unavoidable conversions between dark matter states. We find an exponential dependence of the asymmetries of the heavier components on annihilations and conversions. We conclude that having similar symmetric and asymmetric components is a natural outcome in many scenarios of multi-component dark matter. This has novel phenomenological implications, which we briefly discuss.