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Fisheries extension programmes frequently fail to secure mandatory or voluntary adoption of bycatch reduction devices and techniques. Approaches for improving the outcomes of extension programmes are often based on ad hoc assessments and do not consider human behaviour or change theories. This paper offers an in-depth analysis of extension activities that led to various adoption outcomes in two prominent bycatch case studies in the United States: turtle excluder devices in shrimp trawl fisheries and dolphin bycatch in the tuna purse seine fishery. Using a grounded theory approach to text analysis of interviews and documents, I examine five periods of voluntary or mandatory adoption efforts. I explain the outcomes through the lens of diffusion of innovation theory. The most effective extension programme involved informative and persuasive efforts, enforced regulations, and commercially practical bycatch reduction devices. Voluntary adoption occurred under exceptional circumstances of public and political pressure and a device that offered substantial benefits to the adopter. The two periods of successful adoption applied the most core principles of diffusion theory. This paper concludes with recommendations for how change agents can apply diffusion theory to future fisheries extension programmes to improve the adoption of bycatch reduction devices. [ABSTRACT FROM AUTHOR]

Tricarbon and pentacarbon monoxides have been detected towards the Taurus Molecular Cloud (TMC-1) with relatively important abundances. Understanding the chemical formation of these molecules requires interpreting their observational spectra by mean of non-local thermodynamical equilibrium modelling. For this purpose, we report rate coefficients of  C3O and  C5O induced by collision with He for temperatures up to 100 K. These data are obtained by calculating inelastic cross sections for the 31 low-lying rotational levels of  C3O and  C5O using the close-coupling approach. The comparison of the new rate coefficients with those of HC3N and HC5N, previously used to interpret the observational spectra of  C3O and  C5O, reveals differences of up to an order of magnitude. The effect of the new collisional rate coefficients in radiative transfer calculations is checked by computing the excitation temperatures for some transitions and simulating the  C3O and  C5O column densities observed towards TMC-1. Our findings suggest that the use of HC n N as template for C n O may lead to local thermodynamic equilibrium conditions for gas densities as low as ∼103  cm−3. Regarding the interpretation of the observational spectra, using radiative transfer modelling based on the actual C n O collisional rate coefficients instead of rotational diagram analysis leads to underestimate the column densities reported in the literature by up to 25 per cent and accordingly the  C3O/ C5O abundance ratio by up to 50 per cent. We expect that the new rate coefficients and the radiative transfer calculations presented in this work will encourage further modellings of the C n O abundance and accordingly constrain the chemistry. [ABSTRACT FROM AUTHOR]

International efforts to avoid dangerous climate change have historically focused on reducing energy-related CO2 emissions from countries with either the largest economies (e.g. the EU and the USA) and/or the largest populations (e.g. China and India). However, in recent years, emissions have surged among a different and much less-examined group of countries, raising concerns that a next generation of high-emitting economies will obviate current mitigation targets. Here, we analyse the trends and drivers of emissions in each of the 59 countries where emissions in 2010–2018 grew faster than the global average (excluding China and India), project their emissions under a range of longer-term energy scenarios and estimate the costs of decarbonization pathways. Total emissions from these 'emerging emitters' reach as much as 7.5 GtCO2/year in the baseline 2.5° scenario—substantially greater than the emissions from these regions in previously published scenarios that would limit warming to 1.5°C or even 2°C. Such unanticipated emissions would in turn require non-emitting energy deployment from all sectors within these emerging emitters, and faster and deeper reductions in emissions from other countries to meet international climate goals. Moreover, the annual costs of keeping emissions at the low level are in many cases 0.2%–4.1% of countries' gross domestic production, pointing to potential trade-offs with poverty-reduction goals and/or the need for economic support and low-carbon technology transfer from historically high-emitting countries. Our results thus highlight the critical importance of ramping up mitigation efforts in countries that to this point have been largely ignored. [ABSTRACT FROM AUTHOR]

Most polygenic risk score (PRS)models have been based on data from populations of European origins (accounting for the majority of the large genomics datasets, e.g. >78% in the UK Biobank and >85% in the GTEx project). Although several large-scale Asian biobanks were initiated (e.g. Japanese, Korean, Han Chinese biobanks), most other Asian countries have little or near-zero genomics data. To implement PRS models for under-represented populations, we explored transfer learning approaches, assuming that information from existing large datasets can compensate for the small sample size that can be feasibly obtained in developing countries, like Vietnam. Here, we benchmark 13 common PRS methods in meta-population strategy (combining individual genotype data from multiple populations) and multi-population strategy (combining summary statistics from multiple populations). Our results highlight the complementarity of different populations and the choice of methods should depend on the target population. Based on these results, we discussed a set of guidelines to help users select the best method for their datasets. We developed a robust and comprehensive software to allow for benchmarking comparisons between methods and proposed a computational framework for improving PRS performance in a dataset with a small sample size. This work is expected to inform the development of genomics applications in under-represented populations. PRSUP framework is available at: https://github.com/BiomedicalMachineLearning/VGP [ABSTRACT FROM AUTHOR]

Background The preparedness of healthcare institutes for the foreseen changes expected to arise through the implementation of E-Health is a significant turning point in determining its success. This should be evaluated through the awareness and readiness of healthcare workers to adopt E-Health technology to reduce health information technology failures. Methods This study investigated the relationship between the perceived attributes of innovation and E-Health adoption decisions of healthcare workers as part of a preimplementation process. Using a cross-sectional quantitative approach, the dimensions of the diffusion of innovation (DOI) theory were used to assess the E-Health readiness of 110 healthcare workers in a Mauritian specialized hospital. Results A strong inclination towards E-Health adoption was observed, where the prime stimulators were perceived as modernization of healthcare management (84.1%, ẋ=4.19), increased work efficiency through reduction of duplication (77.6%, ẋ=4.10) and faster generation of results (71.1%, ẋ=4.07). The findings of this study also validated the use of five DOI dimensions (i.e. relative advantage, compatibility, complexity, trialability and observability) in a predictability model (F(5, 101)=17.067, p<0.001) towards E-Health adoption. A significant association between 'adopter category' and 'willingness to recommend E-Health adoption' (χ2(8)=74.89, p<0.001) endorsed the fact that physicians and nursing managers have central roles within a social ecosystem to facilitate the diffusion of technology and influence the adoption of innovation. Conclusion This is the first study of its kind in Mauritius to successfully characterize each adopter's profile and demonstrate the applicability of the DOI framework to predict the diffusion rate of E-Health platforms, while also highlighting the importance of identifying key opinion leaders who can be primed by innovators regarding the benefits of E-Health platforms, thus ensuring non-disruptive evolutionary innovation in the Mauritian healthcare sector. [ABSTRACT FROM AUTHOR]

The urgent and indispensable need to develop new methods of enhancing heat transfer efficiency to improve energy devices' performance cannot be overlooked in this era of green energy and sustainable technologies. Nanofluids research has proliferated in the past decade, and reports indicate that nanofluids can be used for heat transfer applications in engineering and in general and/or commercial industries. Nanofluid is the dispersion of nanoparticles with high thermal conductivity in common working fluids. Nevertheless, a growing area of research in recent years has involved using two or more nanoparticles in a base fluid, known as hybrid nanofluids. Studies show that hybrid nanofluids exhibited better thermal and rheological characteristics than mono nanofluids. In addition, many researchers have reported on the thermal-fluid behaviors of nanofluids in comparison with hybrid nanofluids on natural convection in cavity flows. This review discusses hybrid nanofluids preparation, stability analysis and characterization, thermal properties and heat transfer characteristics in cavities. Furthermore, hybrid nanofluids demonstrated better heat transfer characteristics than mono nanofluids or conventional fluids even if more research is needed in terms of hybrid nanofluids preparation, stability, characterization and applications. [ABSTRACT FROM AUTHOR]

Sustainable economic growth and identifying factors affecting it are among the important issues which have always received attention from researchers of different countries. Accordingly, one of the factors affecting economic growth, which has received attention from researchers in the developed countries over recent years, is the issue of environmental technologies that enter the economic cycle of other countries after being patented through technology transfer. The current research investigated the role of the environment-related patents and the effects of the patented technological innovations compatible with climate change mitigation on the economic growth and development in the Middle East countries within a specific time period. The required data were gathered from the valid global databases, including Organization for Economic Co-operation and Development and World Bank and have been analyzed using multi-linear regression methods and econometric models with Eviews 10 software. The obtained results with 95% confidence level show that the environmental patents (β = 0.02) and environment management (β = 0.04) and technologies related to the climate change mitigation (β = 0.02) have a significant positive impact on the sustainable economic development and growth rate in the studied countries. Such a study helps innovators and policymakers in policy decisions related to sustainable development programs from the perspective of environmentally friendly technologies by demonstrating the role of patents in three important environmental areas, namely environmental management, water-related adaptation and climate change mitigation, as one of the factors influencing sustainable economic growth. [ABSTRACT FROM AUTHOR]

In this work, the network data envelopment analysis (DEA) model was used to divide the transformation of scientific and technological achievements in colleges and universities into two stages, which makes up for the lack of process measurement in a single DEA model. Also, the relationship between the transformation efficiency of scientific and technological achievements in universities and the development of a low-carbon economy was quantitatively analyzed. The research results show that: (1) the transformation efficiency of scientific and technological achievements of universities in China is increasing year by year and which is significantly higher in the eastern region than that in the central and western regions. (2) The efficiency of the transformation of scientific and technological achievements of the university promotes the reduction of carbon emission intensity and the development of a low-carbon economy, indicating that the improvement of the transformation efficiency of scientific and technological achievements of the university has a good role in promoting the ecological environment protection. However, compared with the developed countries, the quantity and quality of science and technology supply and ecological environment protection in China's universities are still insufficient. In this regard, the development suggestions are put forward from the aspects of government policy guidance, professional talent cooperation and strengthening the docking between universities and industrial low-carbon economic development. The purpose of this paper is to promote the development of a low-carbon economy by improving the efficiency of scientific and technological achievements transformation in universities, to achieve the goal of ecological environment protection. [ABSTRACT FROM AUTHOR]

Amyris is a fermentation product company that leverages synthetic biology and has been bringing novel fermentation products to the market since 2009. Driven by breakthroughs in genome editing, strain construction and testing, analytics, automation, data science, and process development, Amyris has commercialized nine separate fermentation products over the last decade. This has been accomplished by partnering with the teams at 17 different manufacturing sites around the world. This paper begins with the technology that drives Amyris, describes some key lessons learned from early scale-up experiences, and summarizes the technology transfer procedures and systems that have been built to enable moving more products to market faster. Finally, the breadth of the Amyris product portfolio continues to expand; thus the steps being taken to overcome current challenges (e.g. automated strain engineering can now outpace the rest of the product commercialization timeline) are described. [ABSTRACT FROM AUTHOR]

Motivation The generalized linear mixed model (GLMM) is an extension of the generalized linear model (GLM) in which the linear predictor takes random effects into account. Given its power of precisely modeling the mixed effects from multiple sources of random variations, the method has been widely used in biomedical computation, for instance in the genome-wide association studies (GWASs) that aim to detect genetic variance significantly associated with phenotypes such as human diseases. Collaborative GWAS on large cohorts of patients across multiple institutions is often impeded by the privacy concerns of sharing personal genomic and other health data. To address such concerns, we present in this paper a privacy-preserving Expectation–Maximization (EM) algorithm to build GLMM collaboratively when input data are distributed to multiple participating parties and cannot be transferred to a central server. We assume that the data are horizontally partitioned among participating parties: i.e. each party holds a subset of records (including observational values of fixed effect variables and their corresponding outcome), and for all records, the outcome is regulated by the same set of known fixed effects and random effects. Results Our collaborative EM algorithm is mathematically equivalent to the original EM algorithm commonly used in GLMM construction. The algorithm also runs efficiently when tested on simulated and real human genomic data, and thus can be practically used for privacy-preserving GLMM construction. We implemented the algorithm for collaborative GLMM (cGLMM) construction in R. The data communication was implemented using the rsocket package. Availability and implementation The software is released in open source at https://github.com/huthvincent/cGLMM. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The article presents the history of commercial sector engagement, technology transfer and international health policies at the U.S. Agency for International Development (USAID) from 1961 to 1981. The Cooley Fund financed the construction of pharmaceutical manufacturing plants in the developing world to produce drugs to eradicate diseases like malaria. The government controlled bilateral technology transfer during the period of health programming in U.S. foreign aid. USAID budget was cut in the late 1960s and 1970s and the New Directions policy was signed in 1973 to amend the 1961 Foreign Assistance Act to control private and voluntary contracting organizations. Policies like the Reimbursable Development Program were instituted to boost engagement of the private sector in aid operations.

LISA Pathfinder (LPF) was a technology pioneering mission designed to test key technologies required for gravitational wave detection in space. In the low frequency regime (milliHertz and below), where space-based gravitational wave observatories will operate, temperature fluctuations play a crucial role since they can couple into the interferometric measurement and the test masses' free-fall accuracy in many ways. A dedicated temperature measurement subsystem, with noise levels in 10  |$\mu$| K Hz−1/2 down to 1 mHz was part of the diagnostics unit onboard LPF. In this paper we report on the temperature measurements throughout mission operations, characterize the thermal environment, estimate transfer functions between different locations, and report temperature stability (and its time evolution) at frequencies as low as 10  |$\mu$| Hz, where typically values around 1 K Hz−1/2 were measured. [ABSTRACT FROM AUTHOR]

Currently the field of brain-computer interfacing is increasingly focused on developing usable brain-computer interfaces (BCIs) to better ensure technology transfer and acceptance. Many studies have investigated the usability of BCI applications as a whole. Here we aim to investigate one specific component of an electroencephalogram (EEG)-based BCI system: the acquisition component. This study compares on the usability of three different EEG headsets in the context of a P300-based BCI application for communication. Thirteen participants took part in a within-subject experiment. Participants were randomly given a Biosemi, Emotiv EPOC or g.Sahara headset. After every session offline classification accuracy (efficacy) was calculated and usability factors (perceived efficiency and user satisfaction) were measured using questionnaires. The 32-channel Biosemi headset offered the highest accuracy (88.5%) compared with the 8-channel g.Sahara (62.7%) and the 14-channel Emotiv (61.7%). There was no difference in accuracy between the Biosemi and the g.Sahara when comparing the same 8 channels. The Biosemi and g.Sahara were rated as more comfortable than the Emotiv. The Emotiv was rated as best for aesthetics. System setup time was highest for the Biosemi headset when compared with the g.Sahara and the Emotiv. Without information about the effectiveness, participants preferred the Emotiv. We recommend the use of a gelled headset for applications which require high accuracy and efficiency and water-based or dry headsets when aesthetics, easy setup and fun are important. [ABSTRACT FROM AUTHOR]

The purpose of the article is to offer an overview of the latest release of the VEGA suite of programs. This software has been constantly developed and freely released during the last 20 years and has now reached a significant diffusion and technology level as confirmed by the about 22 500 registered users. While being primarily developed for drug design studies, the VEGA package includes cheminformatics and modeling features, which can be fruitfully utilized in various contexts of the computational chemistry. To offer a glimpse of the remarkable potentials of the software, some examples of the implemented features in the cheminformatics field and for structure-based studies are discussed. Finally, the flexible architecture of the VEGA program which can be expanded and customized by plug-in technology or scripting languages will be described focusing attention on the HyperDrive library including highly optimized functions. Availability and implementation The VEGA suite of programs and the source code of the VEGA command-line version are available free of charge for non-profit organizations at http://www.vegazz.net. [ABSTRACT FROM AUTHOR]

Patients with severe aortic valve stenosis are currently treated with 2 different interventional techniques: surgical aortic valve replacement or transcatheter aortic valve implantation (TAVI). Both have strengths and limitations. On the one hand, TAVI represents a valuable option in high- and intermediate-risk patients and is commonly preferred over surgical aortic valve replacement in subjects with porcelain or severely calcified aorta, on the other, the lack of data on valve durability raises concerns on its use in young, low-risk patients. We present herein the case of a low-risk 71-year-old patient with a severely calcified ascending aorta. We successfully combined our minimally invasive surgical approach with the use of a percutaneous cerebral protection system commonly employed during TAVI procedures. We believe that cardiac surgeons could adopt transcatheter technology to improve operative results. [ABSTRACT FROM AUTHOR]