bluuebunny/crossref_metadata_2025_split huggingface dataset:
(Almost) matrix‐free solver for piecewise linear functions in abs‐normal form
Authors: Bosse Torsten 
Published: July 2019

SummaryThe abs‐normal form (ANF) is a compact algebraic representation for piecewise linear functions. These functions can be used to approximate piecewise smooth functions and contain valuable information about the nonsmoothness of the investigated function. The information helps to define step directions within general Newton methods that obey the structure of the original function and typically yield better convergence. However, the computation of the generalized Newton directions requires the solution of a piecewise linear equation in ANF. It was observed that the ANF can become very large, even for simple functions. Hence, if a solver is based on the ANF and uses the (Schur‐complement) matrices of the explicit ANF representation, it has to be considered computationally expensive. In this paper, we will address this question and present the first (almost) matrix‐free versions of some solver for ANFs. The theoretical discussion is supported by some numerical run‐time experiments.
Influence of comonomer distribution on crystallization kinetics and performance of polyethylene of raised temperature resistance
Authors: Zhang Chao , Zhao Bing , Ding Lei , Zhang Daoxin , Yang Feng , Xiang Ming 
Published: July 2019

AbstractThree polyethylene of raised temperature resistance (PE‐RT) materials have been used to explore the factors that cause the differences in crystallization kinetics and mechanical performance between different classes and between the same classes. 1‐PE‐RT and 3‐PE‐RT belong to the same class (type II) but with different comonomer, while 2‐PE‐RT (type I) and 3‐PE‐RT use the same comonomer. The results of tensile and bending tests and isothermal crystallization indicate that different classes or even the same classes of PE‐RT have differences in high‐temperature resistance and long‐term performance. Characterization of the molecular chain structure shows that the comonomer content within the high molecular weight chains is significantly higher than that within the low molecular weight chains, and the comonomer is not uniformly distributed over the short‐chain molecules, which makes 1‐PE‐RT have higher modulus and better long‐term performance. Because the difference of comonomer content in long‐chain molecules and short‐chain molecules is small and the comonomer is relatively uniformly distributed over the short‐chain molecules, 3‐PE‐RT cannot balance the stiffness and the long‐term performance very well. For 2‐PE‐RT, the comonomer content in the long‐chain molecules and the short‐chain molecules is approximately the same and there is no intramolecular comonomer distribution, and thus it has the best long‐term performance but the lowest modulus. 2‐PE‐RT cannot have rigidity and good long‐term performance at the same time. © 2019 Society of Chemical Industry
Barriers and facilitators to community‐based psycho‐oncology services: A qualitative study of health professionals’ attitudes to the feasibility and acceptability of a shared care model
Authors: Vaccaro Lisa , Shaw Joanne , Sethi Suvena , Kirsten Laura , Beatty Lisa , Mitchell Geoffrey , Kissane David , Kelly Brian , Turner Jane 
Published: July 2019

AbstractObjectivePsychological therapies combined with medication are effective treatments for depression and anxiety in patients with cancer. However, the psycho‐oncology workforce is insufficient to meet patient need and is hard to access outside of the major cities. To bridge this gap, innovative models of care are required. Implementation of a new model of care requires attention to the facilitators and barriers. The aim of this study was to explore stakeholders’ attitudes to the feasibility and acceptability of a community‐based, shared care model for the treatment of depression and anxiety.MethodsSemi‐structured interviews were conducted with community‐based clinical psychologists (n = 10), general practitioners (n = 6), and hospital‐based psychologists working in psycho‐oncology (n = 9). Framework analysis was conducted to identify key themes.ResultsAll stakeholders perceived the model as feasible and acceptable. Potential barriers/facilitators to implementation were summarised under six key themes: (a) initiative, ownership, and autonomy; (b) resources; (c) pathway establishment; (d) support; (e) skill acquisition; and (f) patient engagement. Facilitators included quality communication between health professionals across primary and tertiary care and appropriate education and support for community‐based clinicians.ConclusionsThis in‐depth exploration of Australian health professionals’ perceptions of the feasibility and acceptability of a community‐based model of psycho‐oncology care revealed that most clinicians were willing to adopt the proposed changes into practice. An RCT of a shared care intervention for depressed patients with cancer is needed.
Band Gap Prediction for Large Organic Crystal Structures with Machine Learning
Authors: Olsthoorn Bart , Geilhufe R. Matthias , Borysov Stanislav S. , Balatsky Alexander V. 
Published: July 2019

AbstractMachine‐learning models are capable of capturing the structure–property relationship from a dataset of computationally demanding ab initio calculations. Over the past two years, the Organic Materials Database (OMDB) has hosted a growing number of calculated electronic properties of previously synthesized organic crystal structures. The complexity of the organic crystals contained within the OMDB, which have on average 82 atoms per unit cell, makes this database a challenging platform for machine learning applications. In this paper, the focus is on predicting the band gap which represents one of the basic properties of a crystalline material. With this aim, a consistent dataset of 12 500 crystal structures and their corresponding DFT band gap are released, freely available for download at https://omdb.mathub.io/dataset. An ensemble of two state‐of‐the‐art models reach a mean absolute error (MAE) of 0.388 eV, which corresponds to a percentage error of 13% for an average band gap of 3.05 eV. Finally, the trained models are employed to predict the band gap for 260 092 materials contained within the Crystallography Open Database (COD) and made available online so that the predictions can be obtained for any arbitrary crystal structure uploaded by a user.
Sulfonic Acid Functionalized MIL‐101(Cr) Metal‐Organic Framework for Catalytic Production of Acetals
Authors: Mortazavi Saeideh‐Sadat , Abbasi Alireza , Masteri‐Farahani Majid , Farzaneh Faezeh 
Published: July 2019

AbstractA simple and green process for acetalization of benzaldehyde derivatives in the presence of a new solid acid nanocatalyst is reported. For this purpose, MIL‐101(Cr) was synthesized in the absence of HF and then sulfonic acid functionalized MOF was prepared under mild conditions without using hazardous chemicals. First, the MIL‐101(Cr) was functionalized with cysteamine as a non‐toxic material to afford MIL‐101(Cr)‐SH. Then, reaction of the MIL‐101(Cr)‐SH with hydrogen peroxide as a clean oxidant followed by acidification with diluted sulfuric acid produced MIL‐101(Cr)‐SO3H solid acid nanocatalyst. Characterization of the prepared nanocatalyst was carried out with various physicochemical methods. The results of elemental analysis and FT‐IR spectroscopy confirmed the stepwise functionalization of MIL‐101(Cr) with sulfonic acid groups. Nitrogen adsorption‐desorption analysis indicated the reduction of surface area after functionalization of pristine MIL‐101(Cr). X‐ray diffraction (XRD) analysis showed that the MIL‐101(Cr) kept its crystal structure during the modification steps. Finally, the activity of prepared catalyst was evaluated in the clean acetalization of benzaldehyde derivatives with ethylene glycol which exhibited excellent efficiencies and produced water as the only byproduct. The nanocatalyst was consecutively recovered and applied 5‐times without notable loss of its activity.
Mono and Dinuclear Cu(II) Carboxylate Complexes with Pyridine and 1‐methylimidazole as Co–Ligands: Synthesis, Structure, Antibacterial Activity and Catalytic Nitroaldol Reactions
Authors: Premkumar Muniyappan , Kaleeswaran Dhananjayan , Kaviyarasan Govindaraj , Prasanth Dorairaj Arvind , Venkatachalam Galmari 
Published: July 2019

AbstractA new series of Cu(II) carboxylate complexes [Cu2(RCOO)4(Py)2] (1 & 2) and [Cu(RCOO)2(MIm)2] (3 & 4) {RCOO=p–FBA (p‐fluorobenzoic acid), BA (benzoic acid), Py (Pyridine), MIm (1–methylimidazole)} have been synthesized. The composition of complexes (1–4) has been established by spectral (FTIR, UV/Vis & EPR) methods and elemental analysis. Molecular structures of copper(II) carboxylate complexes [Cu2(p–FBA)4(Py)2] (1) and [Cu(p–FBA)2(MIm)2] (3) were established by X–ray diffraction. These copper(II) carboxylate complexes 1–4 exhibit a very good catalytic activity towards nitroaldol (Henry) reaction of various aldehydes with nitromethane. The ligands and copper(II) complexes were also screened for their antibacterial activity against microorganisms Staphylococcus aureus and Escherichia coli.
Mild and Rapid Aniline/HBF4•DEE‐Catalysed Formation of Sulfinyl Imines
Authors: Blomkvist Björn , Dinér Peter 
Published: July 2019

AbstractThe combination of anline and tetrafluoroboric acid diethyl etherate (2.5 mol% and 5 mol%, respectively) significantly accelerates the formation of sulfinyl imines in dichloromethane and isopropylacetate at room temperature compared to previous procedures. A DFT and NMR spectroscopic study shows that the anilinium tetrafluoroborate complex is solvated by sulfinamide molecules in the initial state and that the rate‐limiting step of the reaction is the addition of the sulfinamide molecule to the protonated aniline‐based imine. In addition, the catalytic system was also utilised in a one‐pot, two step reaction, where the in situ formed sulfinyl imine was arylated in a rhodium catalysed reaction with high diastereoselectivity.
A Highly Efficient Synthesis of Pyrrolo[1,2‐a]pyrimidine Derivatives Containing 1,3‐Indandione Skeleton
Authors: Alizadeh Abdolali , Ghasemzadeh Hossein , Xiao Hong‐Ping 
Published: July 2019

AbstractThe pyrimidines fused with pyrrole ring, pyrrolopyrimidines, showed broad applicability in medicinal chemistry. Herein, we synthesized the new derivatives (8 examples) of pyrrolo[1,2‐a]pyrimidine containing 1,3‐indandione skeleton by the use of triethylammonium thiolates, methyl iodide, and ketene aminals via a one‐pot three‐component reaction.
Comparative Desorption Studies on Remediation of Remazol Dyes Using Biochar (Sorbent) Derived from Green Marine Seaweeds
Authors: Ravindiran Gokulan , Jeyaraju Raja Murugadoss , Josephraj Jegan , Alagumalai Avinash 
Published: July 2019

AbstractIn this work, regeneration of Remazol dye loaded biochar produced from three different green marine seaweeds namely U.lactuca, U.reticulata and C.scalpelliformis was studied using different elutants as a regenerant. Before the regeneration, remediation of remazol dyes were studied in batch trails and U. Lactuca derived biochar is found to best ‐suited biochar for the remediation all four remazol dyes with a removal efficiency in the order of Remazol brilliant orange 3R (91%), followed by Remazol brilliant blue R (89.6%), Remazol brilliant violet 5R (84.2%) and Remazol Black B (77.8%). Further Remazol brilliant orange 3R is studied for the remediation of real wastewater and also continuous remediation of dyes is performed. The present work aspires to find the best regenerant for dye loaded biochars. From the investigation NaOH(0.01 M) is found to be the best elutant for all the three different biochars. Desorption efficiency for U. lactuca biochar loaded remazol dyes were between 99.3 to 99.7%, U. reticulate biochar loaded remazol dyes were between 99.4 to 99.8% and for C. scalpelliformis biochar loaded remazol dyes were between 99.2 to 99.6%. The impacts of S/L ratio on the elution efficiency of NaOH towards dye‐bounded biochar were examined. The results indicated that elution efficiency of NaOH remain unaltered until S/L ratio=5 and additional enhancement of S/L ratio caused significant decrease in elution efficiency for all systems.
Alkynyl‐ or Azido‐Functionalized 1,2,3‐Triazoles: Selective MonoCuAAC Promoted by Physical Factors
Authors: Topchiy Maxim A. , Ageshina Alexandra A. , Chesnokov Gleb A. , Sterligov Grigorii K. , Rzhevskiy Sergey A. , Gribanov Pavel S. , Osipov Sergey N. , Nechaev Mikhail S. , Asachenko Andrey F. 
Published: July 2019

AbstractThe chemical factors are tending to be the usual way to control the reaction selectivity. However, this approach is inapplicable in cases of compounds with two or more functional groups of almost the same or equal reactivity. On these occasions considering the reaction bulk physical properties can be much more beneficial. In the present work we studied one of these complicated cases, namely, the CuAAC reaction of symmetrical diazides or diynes in equimolar amounts, and developed two approaches to solve the selectivity problem between mono‐ and diaddition. Single cycloaddition in the CuAAC reaction of symmetric diazides or diynes can be achieved by: 1) precipitation of the monoaddition product, 1,2,3‐triazole, from nonpolar solvent – heptane; 2) the reaction halt after formation of monoaddition product due to increase of the viscosity in solvent‐free procedure. Thus, two new “green” one‐step methods of alkynyl‐ or azido‐functionalized 1,2,3‐triazoles synthesis were devised. Their utility was shown on 17 examples of good to excellent yields.
Metabolism and Gut Microbiota in Cancer Immunoediting, CD8/Treg Ratios, Immune Cell Homeostasis, and Cancer (Immuno)Therapy: Concise Review
Authors: Kareva Irina 
Published: July 2019

Abstract
The concept of immunoediting, a process whereby the immune system eliminates immunogenic cancer cell clones, allowing the remaining cells to progress and form a tumor, has evolved with growing appreciation of the importance of cancer ecology on tumor progression. As cancer cells grow and modify their environment, they create spatial and nutrient constraints that may affect not only immune cell function but also differentiation, tipping the balance between cytotoxic and regulatory immunity to facilitate tumor growth. Here, we review how immunometabolism may contribute to cancer escape from the immune system, as well as highlight an emerging role of gut microbiota, its effects on the immune system and on response to immunotherapy. We conclude with a discussion of how these pieces can be integrated to devise better combination therapies and highlight the role of computational approaches as a potential tool to aid in combination therapy design. Stem Cells 2019;37:1273–1280
Optimal tuning of fuzzy parameters for structural motion control using multiverse optimizer
Authors: Azizi Mahdi , Ghasemi Seyyed Arash Mousavi , Ejlali Reza Goli , Talatahari Siamak 
Published: July 2019

SummaryIn recent years, there is an increasing interest in optimization of structural control algorithms. Fuzzy logic controller is one of the most common and versatile control algorithms that is generally formulated based on the human knowledge and expert. Human knowledge and experience do not yield optimal control responses for a given structure, and tuning of the fuzzy parameters is necessary. This paper focuses on the optimization of a fuzzy controller applied to a seismically excited nonlinear building. In the majority of cases, this problem is formulated based on the linear behavior of the structure; however, in this paper, objective functions and the evaluation criteria are considered with respect to the nonlinear responses of the structures. Multiverse optimizer is a novel nature‐inspired optimization algorithm that is based on the three concepts of cosmology as white hole, black hole, and wormhole. This algorithm has fast convergence rate and can be utilized in continuous and discrete optimization problems. In this paper, the multiverse optimizer is considered as the optimization algorithm for optimization of the fuzzy controller. The performance of the selected algorithm is compared with eight different optimization algorithms. The results prove that the selected algorithm is able to provide very competitive results.
Metal Nanoparticles Syntheses on Ionic Liquids Functionalized Mesoporous Silica SBA‐15
Authors: Kusumawati Etty N. , Sasaki Takehiko 
Published: July 2019

AbstractSupported metal nanoparticles hold great promise in heterogeneous catalysis as active and reusable catalysts for various organic transformations. Preparation methods of metal nanoparticles with excellent control over size, shape, and morphology on supports has significantly advanced to improve the performances of the resulting catalysts. Here, we aim to discuss the development of supported metal nanoparticles on mesoporous silica SBA‐15 in the presence of immobilized ionic liquids mostly based on examples from the previously reported results. This review highlights the preparation methods for size‐controlled syntheses and the immobilization of metal nanoparticles on solid supports, especially SBA‐15 by various techniques.
Fifth Graders’ Understandings of Giftedness
Authors: Barone Diane , Barone Rebecca 
Published: July 2019

AbstractIn this qualitative study, the authors explored the multimodal responses provided by gifted fifth graders. Students read the novelUngiftedby Gordon Korman and responded through writing, drawing, and talking. They preferred plot summaries for their written response and created a new form, visual summary, in which image was dominant. In their conversations, students discussed giftedness and how teachers marginalized them for instruction. Students shared how giftedness, as measured throughIQtesting, is variable and can be changed by the context of instruction. Using a book that explicitly considers giftedness offered students an opportunity to make meaning of the text and make connections to their own experiences centered on giftedness.
Agent‐based models of inflammation in translational systems biology: A decade later
Authors: Vodovotz Yoram , An Gary 
Published: July 2019

AbstractAgent‐based modeling is a rule‐based, discrete‐event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components (“agents”) of system. Agent‐based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent‐based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent‐based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent‐based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting‐edge technologies such as high‐performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies.This article is categorized under:
Translational, Genomic, and Systems Medicine > Translational Medicine
Models of Systems Properties and Processes > Mechanistic Models
Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models
Models of Systems Properties and Processes > Organismal Models
Optimizing real-world factory flows using aggregated discrete event simulation modelling
Authors: Lidberg Simon , Aslam Tehseen , Pehrsson Leif , Ng Amos H. C. 
Published: July 2019

AbstractReacting quickly to changing market demands and new variants by improving and adapting industrial systems is an important business advantage. Changes to systems are costly; especially when those systems are already in place. Resources invested should be targeted so that the results of the improvements are maximized. One method allowing this is the combination of discrete event simulation, aggregated models, multi-objective optimization, and data-mining shown in this article. A real-world optimization case study of an industrial problem is conducted resulting in lowering the storage levels, reducing lead time, and lowering batch sizes, showing the potential of optimizing on the factory level. Furthermore, a base for decision-support is presented, generating clusters from the optimization results. These clusters are then used as targets for a decision tree algorithm, creating rules for reaching different solutions for a decision-maker to choose from. Thereby allowing decisions to be driven by data, and not by intuition.
Real-time task processing method based on edge computing for spinning CPS
Authors: Yin Shiyong , Bao Jinsong , Li Jie , Zhang Jie 
Published: July 2019

AbstractSpinning production is a typical continuous manufacturing process characterized by high speed and uncertain dynamics. Each manufacturing unit in spinning production produces various real-time tasks, which may affect production efficiency and yarn quality if not processed in time. This paper presents an edge computing-based method that is different from traditional centralized cloud computation because its decentralization characteristics meet the high-speed and high-response requirements of yarn production. Edge computing nodes, real-time tasks, and edge computing resources are defined. A system model is established, and a real-time task processing method is proposed for the edge computing scenario. Experimental results indicate that the proposed real-time task processing method based on edge computing can effectively solve the delay problem of real-time task processing in spinning cyber-physical systems, save bandwidth, and enhance the security of task transmission.