bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shipbuilding Innovation: Enabling Technologies and Economic Imperatives
Authors: Stott Paul W. 
Published: April 2018

Commercial shipbuilding in the 21st century is dominated by large suppliers, constructing series' of ships in highly efficient shipyards. The industry would be unrecognizable to shipbuilders from a century ago and this raises the question as to when the modern form developed. Much development has been incremental but there have also been seminal triggers, both technical and economic, that have led to major shifts in the nature of the industry. This paper traces these shifts from the building of SS Great Britain to the current day. The modern industry saw its beginnings in the United States in World War II (wwii), follows a build strategy that was developed in Japan (under U.S. guidance) and a pattern of shipyard design that originated in Europe in the early 1960s. The most significant influences have included developments in iron and steel manufacturing processes, the expansion of the British Empire in the second half of the 19th century, the Liberty Ship program in WWII, Japan's "great reverse" post-WWII, and the "Bretton Woods" conference that initiated the process of globalization in the second half of the 20th century. The greatest steps forward have arisen out of economic imperatives and been assisted by influence from other industry sectors. The most important influences were those from government contractors in the introduction of welding into shipbuilding in WWII and in the influence of the aircraft manufacturing industry in Japanese shipbuilding post-WWII. The greatest barriers to innovation have arisen from conservatism.

1. Introduction
In an article in the New York Times of October 28,1921, Henry Ford coined his famous phrase: "History is bunk." He was paraphrasing an earlier article in the Crawfordsville Review of June 6, 1916, where he had said: "History is more or less bunk" and the three additional words make all the difference in understanding this famous quotation. What Henry Ford did not mean was that we cannot learn the lessons of history. What he did mean was that we cannot reliably predict the future by extrapolating the past and this leads to a very optimistic view of the power of innovation in industry. What innovations might be around the corner that will change everything? Henry Ford is also often quoted in support of this view as saying, relating to the period before his innovations that made the motor car an affordable mode of transport for the masses in the United States: "If I had asked people what they wanted, they would have said faster horses." In reality, Henry Ford is nowhere recorded as actually having said this, but it is a popular misquotation because it illustrates the principle perfectly (Vlaskovits 2011).
Kill two birds with one stone: making multi-transgenic pre-diabetes mouse models through insulin resistance and pancreatic apoptosis pathogenesis
Authors: Kong Siyuan , Ruan Jinxue , Zhang Kaiyi , Hu Bingjun , Cheng Yuzhu , Zhang Yubo , Yang Shulin , Li Kui 
Published: April 2018

BackgroundType 2 diabetes is characterized by insulin resistance accompanied by defective insulin secretion. Transgenic mouse models play an important role in medical research. However, single transgenic mouse models may not mimic the complex phenotypes of most cases of type 2 diabetes.MethodsFocusing on genes related to pancreatic islet damage, peripheral insulin resistance and related environmental inducing factors, we generated single-transgenic (C/EBP homology protein, CHOP) mice (CHOP mice), dual-transgenic (human islet amyloid polypeptide, hIAPP; CHOP) mice (hIAPP-CHOP mice) and triple-transgenic (11β-hydroxysteroid dehydrogenase type 1, 11β-HSD1; hIAPP; CHOP) mice (11β-HSD1-hIAPP- CHOP mice). The latter two types of transgenic (Tg) animals were induced with high-fat high-sucrose diets (HFHSD). We analyzed the diabetes-related symptoms and histology features of the transgenic animals.ResultsComparing symptoms on the spot-checked points, we determined that the triple-transgene mice were more suitable for systematic study. The results of intraperitoneal glucose tolerance tests (IPGTT) of triple-transgene animals began to change 60 days after induction (p < 0.001). After 190 days of induction, the body weights (p < 0.01) and plasma glucose of the animals in Tg were higher than those of the animals in Negative Control (Nc). After sacrificed, large amounts of lipid were found deposited in adipose (p < 0.01) and ectopically deposited in the non-adipose tissues (p < 0.05 or 0.01) of the animals in the Tg HFHSD group. The weights of kidneys and hearts of Tg animals were significantly increased (p < 0.01). Serum C peptide (C-P) was decreased due to Tg effects, and insulin levels were increased due to the effects of the HFHSD in the Tg HFHSD group, indicating that damaged insulin secretion and insulin resistance hyperinsulinemia existed simultaneously in these animals. The serum corticosterone of Tg was slightly higher than those of Nc due to the effects of the 11βHSD-1 transgene and obesity. In Tg HFHSD, hepatic adipose deposition was more severe and the pancreatic islet area was enlarged under compensation, accompanying apoptosis. In the transgenic control diet (Tg ControlD) group, hepatic adipose deposition was also severe, pancreatic islets were damaged, and their areas were decreased (p < 0.05), and apoptosis of pancreatic cells occurred. Taken together, these data show the transgenes led to early-stage pathological changes characteristic of type 2 diabetes in the triple-transgene HFHSD group. The disease of triple-transgenic mice was more severe than that of dual or single-transgenic mice.ConclusionThe use of multi-transgenes involved in insulin resistance and pancreatic apoptosis is a better way to generate polygene-related early-stage diabetes models.
Challenges of transferring models of fish abundance between coral reefs
Authors: Sequeira Ana M.M. , Mellin Camille , Lozano-Montes Hector M. , Meeuwig Jessica J. , Vanderklift Mathew A. , Haywood Michael D.E. , Babcock Russell C. , Caley M. Julian 
Published: April 2018

Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1% <R2 < 50.6% for Acanthuridae) compared to total fish abundance (9% <R2 < 18.6%). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R2 < 6%,p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fish abundance models. However, observations of these local-scale predictors are often not available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.
Inducible nitric oxide synthase (NOS2) knockout mice as a model of trichotillomania
Authors: Casarotto Plinio C. , Biojone Caroline , Montezuma Karina , Cunha Fernando Q. , Joca Samia R.L. , Castren Eero , Guimaraes Francisco S. 
Published: April 2018

Background
Trichotillomania (TTM) is an impulse control disorder characterized by repetitive hair pulling/trimming. Barbering behavior (BB) observed in laboratory animals is proposed as a model of TTM. The neurobiological basis of TTM is unclear, but involves striatal hyperactivity and hypoactivation of the prefrontal cortex.

Methods
In this study, we evaluated the BB in knockout mice for the inducible isoform of nitric oxide synthase (NOS2KO) and the consequences of silencing this enzyme in PC12 cell differentiation.

Results
NOS2KO exhibit exacerbated BB, starting four weeks of age, and increased repetitive movements compared to wild-type mice (WT). The expression of BB was attenuated by repeated treatment with clomipramine, a clinically approved drug to treat TTM in humans, or memantine, an antagonist of NMDA receptors, as well as partial rescue of NOS2 expression in haploinsufficient animals. The silencing of NOS2 expression reduced the MAP2 (microtubule-associated protein 2) levels in activity-induced differentiated PC12 cells.

Discussion
Our data led us to propose that NOS2 is putatively involved in the neuronal maturation of the inhibitory afferent pathways during neurodevelopment, and such inadequate inhibition of motor programs might be associated to the observed phenotype.
Collaborative Approaches to Advance Chemical Safety
Authors: Judson Philip 
Published: April 2018

The sections in this article areIntroductionIncentives for Collaboration and ConstraintsOptions for SharingSharing ResearchSharing KnowledgeSharing DataSharing Software DevelopmentThe Implementation of Collaborative OrganizationsCollaborative ProjectsBritish Industrial Biological Research Association (BIBRA)The Chemical Bioactivity Information Centre (CBIC)The Distributed Structure‐Searchable Toxicity Database Network –DSSToxICHInnovative Medicines Initiative (IMI)CHEM21Electronic Health Record for Clinical Research (EHR4CR)eTOXGETREALiPiEMARCARMIP‐DILIInternational Life Sciences Institute (ILSI) andILSIHealth and Environmental Sciences Institute (HESI)Lhasa LimitedOECD(Q)SARToolboxOpenToxPhUSEThe Pistoia AllianceREACHSubstance Information Exchange Forums (SIEF)SEURAT‐1 (Safety Evaluation Ultimately Replacing Animal Testing)COSMOSDETECTIVEHeMiBioNOTOXSCR&ToxToxBankToxMLThe Traditional Chinese Medicine DatabaseUnited Nations – the European Agreement Concerning the International Carriage of Dangerous Goods by Road (ADR) and the Globally Harmonized System of Classification and Labeling of Chemicals (GHS)USGovernment–Industry CollaborationsVEGAYale University Open Data Access (YODA)Conclusions
Introduction to Green Analytical Chemistry
Authors: Tobiszewski Marek 
Published: April 2018

AbstractGreen analytical chemistry is well known concept that has its own place in analytical chemistry. Its main goal is to minimize the negative environmental impact of chemical laboratories that perform medical, environmental, food, and industrial analyses. There are numerous strategies that are incorporated under the banner of green analytical chemistry. The most important are miniaturization of equipment, especially in the field of sample preparation, avoiding of certain analytical activities, replacement of toxic reagents and even more importantly solvents, or selection appropriate analytical procedure from those characterized by minimized environmental impact. The chapter also presents brief history of achievements that resulted in the state of the art in this.
Green Chemistry Molecular Recognition Processes Applied to Metal Separations in Ore Beneficiation, Element Recycling, Metal Remediation, and Elemental Analysis
Authors: Izatt Reed M. , Izatt Steven R. , Izatt Neil E. , Bruening Ronald L. , Krakowiak Krzysztof E. 
Published: April 2018

AbstractApplication of green chemistry principles to metal separations offers the possibility of markedly reducing generation of waste, process time, operating expenses, and capital expenses associated with these separations. Molecular Recognition Technology (MRT) is a highly metal‐selective green chemistry process that is used in a variety of metal separations with marked success. Commercial applications of MRT in the metals industry cover a wide variety of areas, including processing and beneficiation of mined ore, metal recovery from acid mine drainage streams, metal recycling, toxic metal recovery from environmental streams, recovery of radionuclides from nuclear wastes, and preparation of solutions for metal analyses. Examples are provided for the use ofMRTin each of these fields. Major aims are to demonstrate that green chemistry processes, such asMRT, are simple in design and are capable of clean chemistry separations in a competitive market. Further development and greater use of green chemistry separations in commercial processes can lead to increased global metal sustainability and improvement in worldwide metal stewardship.
The
IFF
Green Chemistry Assessment Tool
Authors: Tampy Geatesh 
Published: April 2018

Abstract

Flavors and fragrances are important because they are known to drive consumer choice and satisfaction, and help improve human health. In conjunction with a dramatic company‐wide acceleration in a commitment to sustainability, International Flavors & Fragrances Inc., now has a very strong focus on green chemistry. As a part of this effort,
IFF
has developed and implemented a unique and customized
IFF
Green Chemistry Assessment Tool tailored to meet the needs of
IFF
's flavor, fragrance, and encapsulated products. Based on the ubiquitous and well‐known Twelve Principles of Green Chemistry, the tool involves the application of
IFF
's own standardized scoring system for each of the 12 principles. All scientific personnel globally have been trained to ensure that the scoring methodology is uniformly applied. Annual refresher training with various example applications and success stories further promotes the use of the tool. An example application to improve a fragrance product is provided as an illustration on how the tool is employed to drive the principles of green chemistry such as novel catalyst versus stoichiometric raw material, significant reduction of waste, more efficient use of resources, use of a renewable resource, greater energy efficiency and improved worker safety, along with the associated economic benefits. The assessment tool thus helps to improve the culture of “green thinking,” while at the same time allowing for a systematic and structured approach toward more sustainable products and processes at
IFF
.
Green Chemistry Metrics
Authors: Constable David J.C. 
Published: April 2018

The sections in this article areIntroduction and General ConsiderationsFeedstocksChemicalsHazard and RiskGeneral Chemistry Considerations and Chemistry MetricsEvolution of Green Chemistry MetricsAndraos: Tree AnalysisProcess MetricsProduct MetricsSustainability and Green ChemistryMaking Decisions
Key Metrics to Inform Chemical Synthesis Route Design
Authors: Andraos John , Hent Andrei 
Published: April 2018

The sections in this article areIntroductionMaterial Efficiency Analysis for Synthesis PlansCase StudyI: BortezomibMillennium Pharmaceuticals' ProcessPharma‐Sintez ProcessMaterial Efficiency – Local and ExpressSynthesis Strategy for Future OptimizationSummaryCase StudyII: AspirinReaction NetworkMaterial EfficiencyEnvironmental and Safety–Hazard ImpactInput EnergyCaseICaseIICaseIIICaseIVCaseVCaseVIConcluding Remarks and Outlook for Improvements
Benchmarking the Sustainability of Biocatalytic Processes
Authors: Woodley John M. 
Published: April 2018

AbstractIn recent years, biocatalytic methods for the synthesis of complex molecules (in the pharmaceutical as well as other industrial sectors) have developed beyond being merely effective single‐enzyme reaction steps into multienzyme cascades with ever greater sophistication and complexity. This has been matched by an increasing variety and range of products synthesized using biocatalysis. Today, industrial examples include not only high‐value pharmaceutical products, but also intermediate‐value products. Driven by these developments, it is increasingly necessary to benchmark new biocatalytic processes, either against acceptable levels of sustainability or where available against alternative catalytic processes. Benchmarking the environmental “green chemistry” profile of such syntheses is particularly important given the claims made for biocatalysis as a “green” process technology in the laboratory. A number of methods have been proposed in the scientific literature to evaluate the sustainability of syntheses and in this chapter it is proposed to use (1) standardization of the methodology and (2) benchmarking processes at similar stages of development to avoid the comparison of unoptimized processes with processes that are fully developed and mature. This is particularly important for biocatalysis, given the significant process improvements reported between laboratory reactions and final implemented process. Benchmarking in this way can not only provide guidance for improvements to be made to the green chemistry profile of a given synthesis but also improve the economic potential of the process. Ultimately, integrating green chemistry metrics together with costing metrics will enable the rapid and rational development of new bioprocesses on a systematic basis.
Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction
Authors: Ziemann Christian , Stille Maik , Cremers Florian , Buzug Thorsten M. , Rades Dirk 
Published: April 2018

AbstractBackgroundMetal artifacts caused by high‐density implants lead to incorrectly reconstructed Hounsfield units in computed tomography images. This can result in a loss of accuracy in dose calculation in radiation therapy. This study investigates the potential of the metal artifact reduction algorithms, Augmented Likelihood Image Reconstruction and linear interpolation, in improving dose calculation in the presence of metal artifacts.Materials and MethodsIn order to simulate a pelvis with a double‐sided total endoprosthesis, a polymethylmethacrylate phantom was equipped with two steel bars. Artifacts were reduced by applying the Augmented Likelihood Image Reconstruction, a linear interpolation, and a manual correction approach. Using the treatment planning system Eclipse™, identical planning target volumes for an idealized prostate as well as structures for bladder and rectum were defined in corrected and noncorrected images. Volumetric modulated arc therapy plans have been created with double arc rotations with and without avoidance sectors that mask out the prosthesis. The irradiation plans were analyzed for variations in the dose distribution and their homogeneity. Dosimetric measurements were performed using isocentric positioned ionization chambers.ResultsIrradiation plans based on images containing artifacts lead to a dose error in the isocenter of up to 8.4%. Corrections with the Augmented Likelihood Image Reconstruction reduce this dose error to 2.7%, corrections with linear interpolation to 3.2%, and manual artifact correction to 4.1%. When applying artifact correction, the dose homogeneity was slightly improved for all investigated methods. Furthermore, the calculated mean doses are higher for rectum and bladder if avoidance sectors are applied.ConclusionStreaking artifacts cause an imprecise dose calculation within irradiation plans. Using a metal artifact correction algorithm, the planning accuracy can be significantly improved. Best results were accomplished using the Augmented Likelihood Image Reconstruction algorithm.
Adaptive predictive control of a differential drive robot tuned with reinforcement learning
Authors: Jardine P. Travis , Kogan Michael , Givigi Sidney N. , Yousefi Shahram 
Published: April 2018

SummaryOne of the most important steps in designing a model predictive control strategy is selecting appropriate parameters for the relative weights of the objective function. Typically, these are selected through trial and error to meet the desired performance. In this paper, a reinforcement learning technique called learning automata is used to select appropriate parameters for the controller of a differential drive robot through a simulation process. Results of the simulation show that the parameters always converge, although to different values. A controller chosen by the learning process is then ported to a real platform. The selected controller is shown to control the robot better than a standard model predictive control.
A Dendritic Nickel Cobalt Sulfide Nanostructure for Alkaline Battery Electrodes
Authors: Li Wenyao , Zhang Bingjie , Lin Runjia , Ho‐Kimura SocMan , He Guanjie , Zhou Xiying , Hu Junqing , Parkin Ivan P. 
Published: April 2018

AbstractA uniform dendritic NiCo2S4@NiCo2S4 hierarchical nanostructure of width ≈100 nm is successfully designed and synthesized. From kinetic analysis of the electrochemical reactions, those electrodes function in rechargeable alkaline batteries (RABs). The dendritic structure exhibited by the electrodes has a high discharge‐specific capacity of 4.43 mAh cm−2 at a high current density of 240 mA cm−2 with a good rate capability of 70.1% after increasing the current densities from 40 to 240 mA cm−2. At low scan rate of 0.5 mV s−1 in cyclic voltammetry test, the semidiffusion controlled electrochemical reaction contributes ≈92% of the total capacity, this value decreases to ≈43% at a high scan rate of 20 mV s−1. These results enable a detailed analysis of the reaction mechanism for RABs and suggest design concepts for new electrode materials.
Emerging Thermal‐Responsive Materials and Integrated Techniques Targeting the Energy‐Efficient Smart Window Application
Authors: Ke Yujie , Zhou Chengzhi , Zhou Yang , Wang Shancheng , Chan Siew Hwa , Long Yi 
Published: April 2018

AbstractArchitectural windows that smartly regulate indoor solar radiation by changing their optical transmittance in response to thermostimuli are developed as a promising solution toward reducing the energy consumption of buildings. Recently, energy‐efficient smart window technology has attracted increasing scientific interest, with the exploration of energy‐efficient novel materials as well as integration with practical techniques to generate various desired multifunctionalities. This review systematically summarizes emerging thermoresponsive materials for smart window applications, including hydrogels, ionic liquids, perovskites, metamaterials, and liquid crystals. These are compared with vanadium dioxide (VO2), a conventional and extensively studied material for thermochromic smart window applications. In addition, recent progress on cutting‐edge integrated techniques for smart windows is covered, including electrothermal techniques, self‐cleaning, wettability, and also integration with solar cells for bifunctional energy conservation and generation. Finally, opportunities and challenges relating to thermochromic smart windows and prospects for future development are discussed.