Gut Microbiota Is a Major Contributor to Adiposity in Pigs

Different breeds of pigs vary greatly in their propensity for adiposity. Gut microbiota is known to play an important role in modulating host physiology including fat metabolism. However, the relative contribution of gut microbiota to lipogenic characteristics of pigs remains elusive. In this study, we transplanted fecal microbiota of adult Jinhua and Landrace pigs, two breeds of pigs with distinct lipogenic phenotypes, to antibiotic-treated mice. Our results indicated that, 4 weeks after fecal transplantation, the mice receiving Jinhua pigs’ “obese” microbiota (JM) exhibited a different intestinal bacterial community structure from those receiving Landrace pigs’ “lean” microbiota (LM). Notably, an elevated ratio of Firmicutes to Bacteroidetes and a significant diminishment of Akkermansia were observed in JM mice relative to LM mice. Importantly, mouse recipients resembled their respective porcine donors in many of the lipogenic characteristics. Similar to Jinhua pig donors, JM mice had elevated lipid and triglyceride levels and the lipoprotein lipase activity in the liver. Enhanced expression of multiple key lipogenic genes and reduced angiopoietin-like 4 (Angptl4) mRNA expression were also observed in JM mice, relative to those in LM mice. These results collectively suggested that gut microbiota of Jinhua pigs is more capable of enhancing lipogenesis than that of Landrace pigs. Transferability of the lipogenic phenotype across species further indicated that gut microbiota plays a major role in contributing to adiposity in pigs. Manipulation of intestinal microbiota will, therefore, have a profound impact on altering host metabolism and adipogenesis, with an important implication in the treatment of human overweight and obesity

Fuel and Emissions Calculator (FEC) Version 2.0

The Fuel and Emissions Calculator (FEC) is an operating-mode-based, life-cycle emissions modeling tool developed by the Georgia Institute of Technology researchers. The primary purpose of the FEC is to assist fleet owners and managers, regulatory agencies, and policy analysts in assessing the energy and emissions impacts of fleet alternatives. The FEC\u2019s modeling approach estimates emissions as a function of engine load, which in turn is a function of vehicle service parameters, allowing modelers to account for local on-road operating mode conditions as model inputs. The functional modules are embedded in an Excel spreadsheet platform for all current model versions. The open platform allows users to see all input data and every calculation, which makes the model transparent and accessible for most users. With Version 2.0 of the model, an online Python version of the model has also been developed. The Python version enhances model performance, and provides functionality for advanced users who may wish to link the FEC with other modeling tools, such as travel demand or simulation models. The first Fuel and Emissions Calculator (Version 1.0), known as \u2018FEC for transit fleets,\u2019 was originally developed by Georgia Tech researchers in 2013-2014 for transit bus, shuttle bus and rail systems (ORNL and Georgia Tech, 2014). This report first summarizes the FEC Version 2.0 model\u2019s main features. The generic methodology that is applied to all transportation modes is introduced in Chapter 2, which includes modules for scenario setting, energy consumption, on road emission rates, life-cycle assessment, and cost-effectiveness. The model specifications for individual transportation modes are introduced in Chapter 3, and case study examples are provided to help users prepare customized analysis for their own fleets. The key considerations for establishing the online FEC are discussed in Chapter 4. Current research achievements and ongoing work to update and improve the FEC are provided in the final Chapter

3% diquafosol sodium eye drops in Chinese patients with dry eye: a phase IV study

IntroductionThe efficacy and safety of 3% diquafosol sodium eye drops in Chinese patients with dry eye in the real-world setting remains unclear.Methods3099 patients with dry eye symptoms were screened according to Asia Dry Eye Society latest recommendation. Among them, 3000 patients were enrolled for a phase IV study. We followed up with multiple clinical characteristics including corneal fluorescein staining, tear break up time, Schirmer’s tests, visual acuity, intraocular pressure, and others. The follow ups were performed at baseline, 2 weeks and 4 weeks after treatment.ResultsBased on the results of corneal fluorescein staining and tear break up time, all age and gender subgroups exhibited obvious alleviation of the symptoms among the patients with dry eye, and the data in elderly group showed the most significant alleviation. All the adverse drug reactions (ADRs, 6.17%) were recorded, among which 6% local ocular ADRs were included. Meanwhile, mild ADRs (91.8%) accounted for the most. Most of the ADRs (89.75%) got a quick and full recovery, with an average time at 15.6 days. 1.37% of patients dropped out of the study due to ADRs.DiscussionThe use of 3% diquafosol sodium eye drop is effective and safe in the treatment of dry eye, with a low incidence of ADRs showing mild symptoms. This trial was registered at Chinese Clinical Trial Registry ID: ChiCTR1900021999 (Registration Date: 19/03/2019)

Distributive justice impact assessment using activity-based modeling with path retention

Sustainable transportation policies seek to change people’s travel behavior by modifying the travel environment. However, the impacts of many such policies are complex and difficult to evaluate. Policy benefits and burdens may take the form of changes in transportation costs, changes in travel time, changes in energy or pollutant burden, etc. In traditional equity assessments, the distribution of costs and benefits across traditional demographic groups, such as low-income household, minority groups, individuals that do not or cannot own personal vehicles, etc. are often considered. Being able to provide an unbiased assessment of how these benefits and burdens are likely to be distributed across demographic groups of interest serves as the starting point for distributive justice (and environmental justice) analysis in transportation planning and policy assessment. The research objectives of this dissertation are to develop a modeling framework within an advanced activity-based travel demand model that can be used to assess the distribution of transportation cost and benefits across communities of interest and implement a data structure and variable tracking system that can be implemented within and across various modeling tools to ensure that data needed for equity assessment transfer between models, and that outputs from combined models can be used to assess equity impacts. The findings are that the ABM with path retention can be used to assess the distributive impact in terms of benefits and costs such as mobility, energy use, and emissions. Demographic groups of any cut can be assessed and compared effectively using the framework (provided that the travel demand model carries the required demographic variables), providing policy makes more valuable information before decision making especially for potential equity assessment. The framework can also be linked to other models such as dispersion models for other distributive equity impacts assessment in the future.Ph.D

Microstructure and Mechanical Properties of Friction Welding Joints with Dissimilar Titanium Alloys

Titanium alloys, which are important in aerospace application, offer different properties via changing alloys. As design complexity and service demands increase, dissimilar welding of the titanium alloys becomes a particular interest. Linear friction welding (LFW) is a relatively novel bond technique and has been successfully applied for joining titanium alloys. In this paper, dissimilar joints with Ti-6Al-4V and Ti-5Al-2Sn-2Zr-4Mo-4Cr alloys were produced by LFW process. Microstructure was studied via optical microscopy and scanning electron microscopy (SEM), while the chemical composition across the welded samples was identified by energy dispersive X-ray spectroscopy. Mechanical tests were performed on welded samples to study the joint mechanical properties and fracture characteristics. SEM was carried out on the fracture surface to reveal their fracture modes. A significant microstructural change with fine re-crystallization grains in the weld zone (WZ) and small recrystallized grains in the thermo-mechanically affected zone on the Ti-6Al-4V side was discovered in the dissimilar joint. A characteristic asymmetrical microhardness profile with a maximum in the WZ was observed. Tensile properties of the dissimilar joint were comparable to the base metals, but the impact toughness exhibited a lower value

Unsupervised Learning of Monocular Depth and Ego-Motion with Optical Flow Features and Multiple Constraints

This paper proposes a novel unsupervised learning framework for depth recovery and camera ego-motion estimation from monocular video. The framework exploits the optical flow (OF) property to jointly train the depth and the ego-motion models. Unlike the existing unsupervised methods, our method extracts the features from the optical flow rather than from the raw RGB images, thereby enhancing unsupervised learning. In addition, we exploit the forward-backward consistency check of the optical flow to generate a mask of the invalid region in the image, and accordingly, eliminate the outlier regions such as occlusion regions and moving objects for the learning. Furthermore, in addition to using view synthesis as a supervised signal, we impose additional loss functions, including optical flow consistency loss and depth consistency loss, as additional supervision signals on the valid image region to further enhance the training of the models. Substantial experiments on multiple benchmark datasets demonstrate that our method outperforms other unsupervised methods