Characterization of kinetics and performance in a microbial fuel cell supplied with synthetic landfill leachate

Biodegradable municipal solid waste (MSW) is rich in biochemical energy; however, much of this energy is sequestered in conventional landfills. Although bioreactor landfills enhance conversion of MSW to methane, the generated methane is a potent greenhouse gas and cannot be fully captured in landfills. Microbial fuel cells (MFCs) can directly convert the biochemical energy in MSW to electricity, treat leachate, extend landfill longevity, and minimize fugitive methane emissions. However, the electricity production from MFCs cannot yet meet the energy demands of treatment and improvements in the performance of leachate-fed MFCs are needed. Effective approaches for the design and operation of MFCs are currently lacking. Therefore, the goals of this study are to (1) improve our understanding of the effect of substrate concentration and organic loading rate on the performance of MFCs, and (2) estimate the kinetics parameters needed for the modeling of MFC-leachate treatment systems. These goals were achieved by generating synthetic leachate using a laboratory-scale bioreactor landfill filled with shredded paper, food waste, and dry dog food. The leachate was diluted to different substrate (chemical oxygen demand, COD) concentrations until steady-state current production was achieved at a given COD loading rate. Voltage in the MFC was measured continuously and, along with steady-state measurements of COD removal in the MFC, was used to estimate microbial kinetic parameters in the MFC and determine the optimal conditions for current production, the conversion of biochemical substrates to electricity (coulombic efficiency), and COD removal. This study will help inform the future design and operation of bioreactor landfill-MFC treatment systems to achieve more effective leachate treatment as well as more efficient electricity generation

Molecular Biogeochemistry of a Poor Fen

Variations in climate may rapidly change the carbon balance of peatlands and increase greenhouse gas emissions through accelerated decomposition of peat and dissolved organic matter (DOM). In this study, porewater samples were collected monthly from May to October in 2017 to study the effects of plant functional groups (PFGs) on DOM, dissolved inorganic and organic nitrogen through the season in a poor fen with replicate plots dominated by different PFGs in Nestoria, Michigan, USA (46.34˚N 88.16˚W). The composition of the peat porewater showed strong statistical significance with plot type and season.The observed PFG and season impact on the composition of DOM will offer great guidance for the prediction of the DOM decomposition in peatland with respect to climate change

Cross-talk between the Oxytocin and Vasopressin Systems in the Brian: Roles in Social Behavior

Oxytocin (OT) and arginine vasopressin (AVP) are closely related nine amino acid neuropeptides primarily produced in the hypothalamus and released both in the peripheral and central nervous systems. For over 100 years, OT and AVP have been known for their roles in uterine contraction/milk letdown and blood vessel constriction, respectively. Over the past few decades, the roles of OT and AVP in the central nervous system have been extensively investigated in the regulation of a variety of complex social behaviors including sex, parenting, pair bonding, social play, and aggression. High levels of structural similarities exist between OT and AVP and between the OT and AVP1a receptor. Interestingly, there is little data on whether cross-talk between the OT and AVP systems occurs in the central nervous system. Therefore, the goal of this dissertation is to examine cross-activation of OT receptors by AVP and of AVP1a receptors by OT, and the functional significance of this cross-talk in the regulation of social behavior. Three specific aims are addressed using Syrian hamsters as animal models: Aim 1 was to test the hypothesis that central OT enhances social communicative behavior by acting on V1aRs; Aim 2 was to test the hypothesis that central OT and AVP prolong social recognition via activation of the same receptor, OTRs or V1aRs. Aim 3 was to test the hypothesis that AVP in the ventral tegmental area (VTA) enhances social reward via activation of OTRs. Our data showed intraccerebroventricular (ICV) injections of OT or AVP act on V1aRs to induce social communication; ICV injections of OT and AVP act on OTRs to prolong social recognition; OT and AVP in the VTA act on OTRs and not V1aRs to enhance social reward. These results demonstrate the ability of OT and AVP to facilitate three essential aspects of a social interaction: communication, recognition, and reward. Our findings also strongly suggest OT and AVP act on both OTRs and V1aRs to influence social behavior but that OTRs regulate some social behaviors while V1aRs regulate other social behaviors

An Extended Virtual Aperture Imaging Model for Through-the-wall Sensing and Its Environmental Parameters Estimation

Through-the-wall imaging (TWI) radar has been given increasing attention in recent years. However, prior knowledge about environmental parameters, such as wall thickness and dielectric constant, and the standoff distance between an array and a wall, is generally unavailable in real applications. Thus, targets behind the wall suffer from defocusing and displacement under the conventional imag¬ing operations. To solve this problem, in this paper, we first set up an extended imaging model of a virtual aperture obtained by a multiple-input-multiple-output array, which considers the array position to the wall and thus is more applicable for real situations. Then, we present a method to estimate the environmental parameters to calibrate the TWI, without multiple measurements or dominant scatter¬ers behind-the-wall to assist. Simulation and field experi¬ments were performed to illustrate the validity of the pro¬posed imaging model and the environmental parameters estimation method

Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks

This paper addresses the problem of continuous gesture recognition from sequences of depth maps using convolutional neutral networks (ConvNets). The proposed method first segments individual gestures from a depth sequence based on quantity of movement (QOM). For each segmented gesture, an Improved Depth Motion Map (IDMM), which converts the depth sequence into one image, is constructed and fed to a ConvNet for recognition. The IDMM effectively encodes both spatial and temporal information and allows the fine-tuning with existing ConvNet models for classification without introducing millions of parameters to learn. The proposed method is evaluated on the Large-scale Continuous Gesture Recognition of the ChaLearn Looking at People (LAP) challenge 2016. It achieved the performance of 0.2655 (Mean Jaccard Index) and ranked $3^{rd}$ place in this challenge

Large-scale Isolated Gesture Recognition Using Convolutional Neural Networks

This paper proposes three simple, compact yet effective representations of depth sequences, referred to respectively as Dynamic Depth Images (DDI), Dynamic Depth Normal Images (DDNI) and Dynamic Depth Motion Normal Images (DDMNI). These dynamic images are constructed from a sequence of depth maps using bidirectional rank pooling to effectively capture the spatial-temporal information. Such image-based representations enable us to fine-tune the existing ConvNets models trained on image data for classification of depth sequences, without introducing large parameters to learn. Upon the proposed representations, a convolutional Neural networks (ConvNets) based method is developed for gesture recognition and evaluated on the Large-scale Isolated Gesture Recognition at the ChaLearn Looking at People (LAP) challenge 2016. The method achieved 55.57\% classification accuracy and ranked $2^{nd}$ place in this challenge but was very close to the best performance even though we only used depth data.Comment: arXiv admin note: text overlap with arXiv:1608.0633

Experimental investigation on permeability and mechanical deformation of coal containing gas under load

Coalbed effective permeability is widely used as a primary index to evaluate gas-drainage effect in CBM exploitation field. However, it seems to be difficult to obtain by the reason of dynamic change in close relationship with crustal stress, methane pressure, porosity, and adsorption. Due to their dissimilar adsorption properties and tectonic deformation degrees, different types of coal containing gas have various stress-strain and gas seepage curves. The paper presents the experimental investigations of the dynamic relationship between coal permeability and deformation under load. In this work, stress-strain and permeability investigations were performed using anthracite lump with a vitrinite reflectance of about 3.24% at various pressures and temperatures. The permeability (including the initial, minimum, and maximum) decreased with increasing temperature. At a constant confining pressure, the strains in different directions almost all increased with increasing axial stress and decreased with increasing pore methane pressure during the prefracture stage. At a constant pore pressure, the compression strength of the coal specimens increased approximately linearly during the prefracture stage and sharply decreased during the postfracture stage, while the permeability decreased rapidly and then increased slowly during the prefracture and remained stable during the postfracture stage. The permeability of the coal specimens mainly depended on the inner fissures. The permeability was greater during the postfracture than that during the prefracture stage. At the same temperature, the gas seepage curve of each coal specimen could be divided into three sections: decreasing, increasing, and constant sections. The necessary time for the permeability to reach a steady state increased as the confining and pore pressures increased. At high confining pressures (i.e., 6 MPa and 8 MPa), no significant differences between the methane seepage velocities of the specimens were evident, and their seepage curves were similar to prefracture. However, clear differences were observable at the postfracture stage. The seepage abilities of the coal specimens were more sensitive to stress than temperature in the same condition

Weak antilocalization in epitaxial graphene: evidence for chiral electrons

Transport in ultrathin graphite grown on silicon carbide is dominated by the electron-doped epitaxial layer at the interface. Weak anti-localization in 2D samples manifests itself as a broad cusp-like depression in the longitudinal resistance for magnetic fields 10 mT$< B <$ 5 T. An extremely sharp weak-localization resistance peak at B=0 is also observed. These features quantitatively agree with graphene weak-(anti)localization theory implying the chiral electronic character of the samples. Scattering contributions from the trapped charges in the substrate and from trigonal warping due to the graphite layer on top are tentatively identified. The Shubnikov-de Haas oscillations are remarkably small and show an anomalous Berry's phase.Comment: 5 pages, 4 figures. Minor change