bluuebunny/crossref_metadata_2025_split huggingface dataset:
Titanium‐Based MOF Materials: From Crystal Engineering to Photocatalysis
Authors: Li Lan , Wang Xu‐Sheng , Liu Tian‐Fu , Ye Jinhua 
Published: December 2020

AbstractTitanium (Ti)‐based metal–organic frameworks (MOFs) have attracted intensive attention due to the low toxicity, high earth's crust abundance, and unique photocatalytic properties of Ti elements. Great efforts have been devoted to the synthesis of novel architectures and their potential applications involving photocatalysis. However, Ti‐MOFs are still very scarce owing to their challenges in controlling the Ti chemistry in the reaction system. Until now, some significant results have been achieved, which may shed new insight into the future investigation of Ti‐MOFs. Herein, some representative researches in Ti‐MOFs are summarized and reviewed from the following four aspects: first, various synthetic strategies for preparing Ti‐MOFs are introduced; second, diverse structures containing multi‐connected ligands are presented in detail; third, the potential photocatalytic applications of Ti‐based MOFs involving H2 production, CO2 reduction, H2O2 production, N2 fixation, remediation of organic and inorganic pollutants, as well as organic transformation reaction and photocatalytic sensors are discussed; finally, perspectives on current challenges and emerging opportunities in this research field are discussed. Through summarizing this specific type of MOF, this review is expected to stimulate researchers’ interest for in‐depth investigation of novel structures synthesis, as well as new applications and concepts in these intriguing fields.
Full‐scale tests on bridge kerbs subjected to horizontal actions
Authors: Meda Alberto , Rinaldi Zila , Spagnuolo Simone , Grecco Raffaella 
Published: December 2020

AbstractThe construction of new kerbs or the replacement of existing ones is usually due to the need of installing safety or anti‐noise barriers. A suitable experimental survey has been studied and developed at the Laboratory of the University of Rome “Tor Vergata" aiming at verifying the vulnerability of the system kerb safety barrier in a bridge deck. The main scope is the analysis, through full‐scale experimental tests, of the system performances under horizontal actions simulating the vehicle derailment. Particular care has been devoted in reproducing actual geometries and materials. Furthermore, the actual elements usually installed in Italian infrastructures (roadways and highways), are adopted, in order to highlight the true damage typologies and failure modes. Both the cases of application of barriers on existing and new cast kerbs are analyzed, and two kerbs geometries, generally found in Italian bridges are cast and tested. The obtained results provide useful information on the safety check to be developed on this kind of structures.
Extracts of Jasminum sambac flowers fermented by Lactobacillus rhamnosus inhibit H2O2‐ and UVB‐induced aging in human dermal fibroblasts
Authors: Ho Chih‐Chu , Ng Shang‐Chuan , Chuang Ho‐Lin , Wen Su‐Ying , Kuo Chia‐Hua , Mahalakshmi B. , Huang Chih‐Yang , Kuo Wei‐Wen 
Published: December 2020

AbstractUltraviolet (UV) irradiation is a crucial factor that leads to skin photoaging and results in increased DNA damage, oxidative stress, and collagen degradation. Jasmine flowers have been utilized as a traditional medicine in Asia to treat various diseases, including dermatitis, diarrhea, and fever. Furthermore, the fermented broth of Lactobacillus rhamnosus has been reported to exert protective effects on the skin. In the present study, jasmine flower extract was fermented with L. rhamnosus. We investigated the antioxidant and collagen‐promoting effects on UVB/H2O2‐induced HS68 dermal fibroblast cell damage. The results indicated that treatment with the fermented flower extracts of Jasminum sambac (F‐FEJS) could enhance the viability of HS68 cells. Furthermore, the UVB/H2O2‐induced excessive production of reactive oxygen species, degradation of collagen, activation of MAPKs, including P38, ERK, and JNK, and premature senescence were remarkably attenuated by F‐FEJS in dermal fibroblast cells. The nuclear accumulation of p‐c‐jun, which is downstream of MAPK, and the inactivation of p‐smad2/3, which is one of the crucial transcription factors that enhance collagen synthesis, were reversed in response to F‐FEJS treatment in UVB/H2O2‐exposed cells. Notably, the expression of antioxidant genes, such as HO‐1, and the nuclear translocation of Nrf2 were further enhanced by F‐FEJS in UVB/H2O2‐treated cells. Interestingly, the F‐FEJS‐induced increase in ARE luciferase activity indicated the activation of Nrf2/ARE signaling. In conclusion, our findings demonstrated that F‐FEJS can effectively ameliorate UVB/H2O2‐induced dermal cell aging and may be considered a promising ingredient in skin aging therapy.
Fetal echocardiographic predictors of biventricular circulation in hypoplastic left heart complex
Authors: Haberer K. , Fruitman D. , Power A. , Hornberger L. K. , Eckersley L. 
Published: December 2020

ABSTRACTObjectivesTo determine which echocardiographic features of hypoplastic left heart complex (HLHC) in the fetal period are predictive of biventricular (BV) circulation and to evaluate the long‐term outcome of patients with HLHC, including rates of mortality, reintervention and development of further cardiac disease.MethodsEchocardiograms of fetuses with HLHC obtained at 18–26 weeks and 27–36 weeks' gestation between 2004 and 2017 were included in the analysis. The primary outcome was successful BV circulation (Group 1). Group 2 included patients with single‐ventricle palliation, death or transplant. Univariate analysis was performed on data obtained at 18–26 and 27–36 weeks and multivariate logistic regression was performed on data obtained at 27–36 weeks only.ResultsOf the 51 included cases, 44 achieved successful BV circulation (Group 1) and seven did not (Group 2). Right‐to‐left/bidirectional foramen ovale (FO) flow and a higher mitral valve (MV) annulus Z‐score were associated with successful BV circulation on both univariate and multivariate analysis. Bidirectional or left‐to‐right FO flow, left ventricular length (LVL) Z‐score of < –2.4 and a MV Z‐score of < –4.5 correctly predicted 80% of Group 2 cases. Late follow‐up was available for 41 patients. There were two late deaths in Group 2. Thirteen patients in Group 1 required reintervention, 12 developed mitral stenosis and five developed isolated subaortic stenosis.ConclusionsBV circulation is common in fetuses with HLHC. Higher MV annulus and LVL Z‐scores and right to left direction of FO flow are important predictors of BV circulation. Long‐term sequelae in those with BV circulation may include mitral and subaortic stenosis. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.
Oxid‐Halbleiter mit ultrabreiter Bandlücke
Authors: Grundmann Marius 
Published: December 2020

ZusammenfassungDie Gepulste Laserdeposition (PLD, pulsed laser deposition) ist eine vergleichsweise einfache physikalische, vakuumbasierte Methode zur Herstellung von Dünnschichten. Hier werden verschiedene Aspekte der Abscheidung von oxidischen Halbleitern beleuchtet, insbesondere für das (Al,Ga,In)2O3‐System mit sehr großer Bandlücke. Die von uns entwickelte Methode der kombinatorischen PLD für einen lateralen Konzentrationsgradienten (CCS‐PLD, continuous composition spread PLD) erlaubt eine einfache Darstellung von Legierungsreihen. In Kombination mit anschließenden ortsaufgelösten Methoden zur strukturellen, elektrischen und optischen Charakterisierung ergibt sich eine effiziente und systematische Untersuchung der physikalischen Eigenschaften der Legierungshalbleiter.
Liveschaltung zum Dünnschichtwachstum
Authors: Krause Bärbel , Abadias Gregory 
Published: December 2020

ZusammenfassungEchtzeitmessungen während der Sputterdeposition ermöglichen einen einzigartigen Zugang zum Wachstum von dünnen Schichten und Nanostrukturen. Eine einfach umsetzbare, hochempfindliche Methode ist die optische Messung der Eigenspannung. Die Interpretation des Signals ist wegen der Vielzahl von potentiellen Ursachen der Eigenspannung eine Herausforderung. Dieses Problem kann mit gleichzeitigen Messungen der Strukturänderungen überwunden werden. Im Folgenden stellen wir einen sehr vielversprechenden Ansatz dafür vor, basierend auf simultanen Röntgen‐ und Spannungsmessungen. Das Potential dieser Methode wird am Beispiel der Metall/Silizium‐Grenzfläche demonstriert. Nach nur 2‐3 Nanometern zeigen beide Metalle eine plötzlich auftretende Zugspannung, danach entwickelt sich die Eigenspannung jedoch sehr unterschiedlich. Unsere Messungen enthüllen, dass die Zugspannung in beiden Fällen auf einen Kristallisationsprozess zurückzuführen ist, sich die Grenzschicht jedoch fundamental unterscheidet.
Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey
Authors: Zhang Jiaxin 
Published: December 2020

AbstractUncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling‐based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time‐consuming if the simulation‐based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. An algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.This article is categorized under:
Statistical and Graphical Methods of Data Analysis > Monte Carlo Methods
Statistical and Graphical Methods of Data Analysis > Sampling
Integral equation technique for water wave interaction by an array of vertical flexible porous wave barriers
Authors: Koley Santanu , Sahoo Trilochan 
Published: December 2020

AbstractScattering of obliquely incident surface gravity waves by an array of partial flexible vertical porous wave barriers of varied configurations is studied in finite water depth and deep water cases. For the mathematical modeling purpose, linearized water wave theory is considered. Firstly, the problem associated with double vertical barriers is handled for a solution. To solve the problem, the associated BVP (boundary value problem) is transformed into a system of Fredholm integral equations of the second kind. By using suitable quadrature formulae, these integral equations are converted to a system of linear algebraic equations. These are solved to compute various important physical quantities associated with wave scattering. The energy identities for both finite water depth and deep water cases are derived. These derived energy identities are used to check the computational accuracy and to quantify the loss of wave energy by the barrier system. Subsequently, the study is extended to deal with wave scattering by multiple non‐identical unequally spaced barriers using wide‐spacing approximation and results for equally spaced identical barriers are obtained as a special case. The methodology is further generalized to deal with Bloch problem to incorporate a periodic array of infinite barriers. Occurrences of Bragg resonance in case of multiple barriers are analyzed. From the results associated with the linearized water wave theory, the second‐order mean wave forces are computed and compared with the first‐order wave forces. The phenomena of cloaking for wave scattering by multiple impervious barriers are discussed for a wide variety of wave and structural parameters. The methodology used in this present study can easily be generalized to solve similar problems that arise in mathematical physics.
Climate Change Resistant Energy Sources for Global Adaptation
Authors: Ife-Adediran Oluwatobi Ololade , Aboyewa Oluyemi Bright 
Published: December 2020

AbstractA holistic response and adaptation to climatic vicissitudes and extreme conditions as well as their associated risks to human and ecological sustainability must adequately cater for energy needs and optimization. An interventional approach should, among other measures, seek to improve the resilience of existing and prospective energy systems to climate change. The structured and policy-driven nature of adaptation measures require a bottom-up proactive approach that envisages the performance and efficiency of these systems, especially in terms of their sensitivity and vulnerability to changing climate conditions. Therefore, this chapter seeks to scrutinize various sources of energy concerning their resistance capabilities to climate change in the face of increasing global energy demands and consumption. Renewable and conventional energy sources are co-examined and compared vis-à-vis the current trends and predictions on climatic factors that are bearing on their principles of production, supply, and distribution. Findings from this article will serve as assessment tools for decision makers and corroborate other ongoing discourse on climate actions towards socioeconomic development and a sustainable environment.
Economic Analysis of Climate-Smart Agriculture Technologies in Maize Production in Smallholder Farming Systems
Authors: Mujeyi Angeline , Mudhara Maxwell 
Published: December 2020

AbstractSmallholder farmers who grow the staple maize crop rely mainly on rain-fed agricultural production, and yields are estimated to have decreased by over 50% largely due to climate change. Climate-smart agriculture (CSA) technologies, as adaptive strategies, are thus increasingly being promoted to overcome problems of declining agricultural productivity and reduced technical efficiency. This study analyzed profitability and profit efficiency in maize (Zea mays) production as a result of CSA technology adoption using cost-benefit analysis and stochastic profit frontier model. The study used data from a cross-sectional household survey of 386 households drawn from 4 districts in Mashonaland East province located in the northeastern part of Zimbabwe. Results from the cost-benefit analysis reveal that maize performs best under CSA technologies. The profit inefficiency model shows that extension contact, number of local traders, and adoption of CSA had significant negative coefficients indicating that as these variables increase, profit efficiency among maize-growing farmers increases. This implies that profit inefficiency in maize production can be reduced significantly with improvement in extension contact, access to farm gate/local markets, and adoption of CSA. The findings call for development practitioners to incorporate market linkages that bring buyers closer to the farmers, support for extension to be able to have frequent contacts with farmers, and promotion of CSA adoption.
Intelligent decision-making support system for manufacturing solution recommendation in a cloud framework
Authors: Simeone Alessandro , Zeng Yunfeng , Caggiano Alessandra 
Published: December 2020

AbstractCloud manufacturing represents a valuable tool to enable wide sharing of manufacturing services and solutions by connecting suppliers and customers in large-scale manufacturing networks through a cloud platform. In this context, with increasing manufacturing network size at global scale, the elevated number of manufacturing solutions offered via cloud platform to connected customers can increase the complexity of decision-making, resulting in poor user experience from a customer perspective. To tackle this issue, in this paper, an intelligent decision-making support tool based on a manufacturing service recommendation system (RS) is designed and developed to provide for tailored manufacturing solution recommendation to customers in a cloud manufacturing system. A machine learning procedure based on neural networks for data regression is employed to process historical data on user manufacturing solution preferences and to carry out the automatic extraction of key features from incoming user instances and compatible manufacturing solutions generated by the cloud platform. In this way, the machine learning procedure is able to perform a customer segmentation and build a recommendation list characterized by a ranking of manufacturing solutions which is tailored to the specific customer profile. With the aim to validate the proposed intelligent decision-making support system, a case study is simulated within the framework of a cloud manufacturing platform delivering dynamic sharing of sheet metal cutting manufacturing solutions. The system capability is discussed in terms of machine learning performance as well as industrial applicability and user selection likelihood.
Somatostatin administration following pancreatoduodenectomy: a case-matched comparison according to surgical technique, body mass index, American Society of Anesthesiologists’ score and Fistula Risk Score
Authors: Furbetta Niccolò , Gianardi Desirée , Guadagni Simone , Di Franco Gregorio , Palmeri Matteo , Bianchini Matteo , Pisani Kevin , Di Candio Giulio , Morelli Luca 
Published: December 2020

Abstract
Purpose
This study evaluated the controversial role of somatostatin after pancreatoduodenectomy (PD), stratifying patients for the main risk factors using the most recent postoperative pancreatic fistula (POPF) classification and including only patients who had undergone PD with the same technique of pancreatojejunostomy.

Methods
Between November 2010 and February 2020, 218 PD procedures were carried out via personal modified pancreatojejunostomy (mPJ-PD). Somatostatin was routinely administered between 2010 and 2016, while from 2017, 97 mPJ-PD procedures without somatostatin (WS) were performed. The WS group was retrospectively compared with a control (C) group obtained with one-to-one case–control matching according to the body mass index, American Society of Anesthesiologists’ score, and Fistula Risk Score (FRS).

Results
A total of 144 patients (72 WS group versus 72 C group) were compared. In the WS group. 6 patients (8.3%) developed clinically relevant POPF, compared with 8 patients (11.1%) in the C group (p = 0.656). In addition, on analyzing the subgroup of high-risk patients according to the FRS, we did not note any significant differences in POPF occurrence. Furthermore, no marked differences in the morbidity or mortality were found. Digestive bleeding and diabetes onset rates were higher in the WS group than in the control group, but not significantly so.

Conclusions
The results of the present study confirm no benefit with the routine administration of somatostatin after PD to prevent POPF, even in high-risk patients. However, a possible role in the prevention of postoperative digestive bleeding and diabetes was observed.
Influence of urbanization on the avian species-area relationship: insights from the breeding birds of Rome
Authors: Di Pietro Stefano , Mantoni Cristina , Fattorini Simone 
Published: December 2020

AbstractThe species-area relationship (SAR) is one of the most investigated patterns in ecology and conservation biology, yet there is no study testing how different levels of urbanization influence its shape. Here we tested the impact of urbanization on avian SARs along a rural-urban gradient using the breeding birds of Rome (Central Italy). We divided the city into 360 cells of 1 km2. Each cell was classified as rural, suburban or urban using the proportion of impervious surface calculated from remote sensing data. For each of these three landscape categories, we constructed a SAR as a species accumulation curve (Gleason function) using bird species distribution data. SAR intercepts (i.e. the number of species per unit area) decreased from rural to urban areas, which indicates that urbanization depressed the number of species, reflecting the loss of specialized species strictly associated with natural habitats. The slope was highest for the rural curve, indicating that natural landscapes have the highest turnover due to their higher habitat heterogeneity. A higher slope for the urban cells, compared to the suburban ones, can be explained by the presence of green spaces embedded in the built-up matrix which host different avian communities. Previous studies that compared whole cities with natural areas failed to find differences in the respective SARs. Our study, which constructed SARs for different levels of urbanization, indicated significant changes in the SARs along the rural-urban gradient. Further analyses in other cities and taxa will be useful to test how general are our findings.
Genomics-directed activation of cryptic natural product pathways deciphers codes for biosynthesis and molecular function
Authors: Tsunematsu Yuta 
Published: December 2020

AbstractNatural products, which can be isolated from living organisms worldwide, have played a pivotal role in drug discovery since ancient times. However, it has become more challenging to identify a structurally novel molecule with promising biological activity for pharmaceutical development, mainly due to the limited methodologies for their acquisition. In this review, we summarize our recent studies that activate the biosynthetic potential of filamentous fungi by genetic engineering to harness the metabolic flow for the efficient production of unprecedented natural products. The recent revolution in genome sequencing technology enables the accumulation of vast amounts of information on biosynthetic genes, the blueprint of the molecular construction. Utilizing the established heterologous expression system, activation of the pathway-specific transcription factor coupled with a knockout strategy, and manipulating the global regulatory gene, the biosynthetic genes were exploited to activate biosynthetic pathways and decipher the encoded enzyme functions. We show that this methodology was beneficial for acquiring fungal treasures for drug discovery. These studies also enabled the investigation of the molecular function of natural products in fungal development.