Market Competition, Institutions, and Contracting Outcomes: Preliminary Model and Experimental Results

Contracts, Competition, Market Power, Enforcement, Institutions, Agribusiness, Industrial Organization, Institutional and Behavioral Economics, Production Economics, C91, D02, D43, D86,

A very high accuracy potential energy surface for H3

An exact quantum Monte Carlo (EQMC) method was used to calculate the potential energy surface (PES) for the ground electronic state of H3 over a grid of about 76000 nuclear geometries. The absolute abinitio statistical or sampling error of the calculation was ±0.01 kcal mol^-1 for energies (V) smaller than 3 eV. This PES was fitted by a three-dimensional cubic spline method and the fitting accuracy was determined from a set of 3684 randomly selected nuclear geometries not used in the fitting. For the range V3 eV the rms fitting error was ±0.010 kcal mol^-1, and the absolute value of the corresponding maximum error was 0.018 kcal mol^-1. This fitted EQMC PES is an order of magnitude more accurate than the best PES previously obtained for this system. Detailed comparisons are made with previous PESs, for the more dynamically important nuclear configurations

Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

Promoting low carbon behaviours through personalised information? Long-term evaluation of a carbon calculator interview

The UK needs to accelerate action to achieve its 80 per cent carbon reduction target by 2050 as it is otherwise in danger of lagging behind. A much discussed question in this context is whether voluntary behaviour change initiatives can make a significant contribution to reaching this target. While providing individuals with general information on climate change or low carbon action is increasingly seen as ineffective, some studies argue that personalised information has greater potential to encourage behaviour change. This mixed methods study examines this claim through a longitudinal field experiment which tested the effectiveness of a carbon calculator interview. It finds that the intervention significantly raised awareness of ways in which participants could reduce their carbon footprint. However, this increased awareness did not translate into measurable behaviour changes in relation to home energy and travel. Qualitative analysis shows that participants refer to infrastructural, social and psychological barriers to change. This indicates that more ambitious government and corporate action is required to speed up carbon reductio

Record Maximum Oscillation Frequency in C-face Epitaxial Graphene Transistors

The maximum oscillation frequency (fmax) quantifies the practical upper bound for useful circuit operation. We report here an fmax of 70 GHz in transistors using epitaxial graphene grown on the C-face of SiC. This is a significant improvement over Si-face epitaxial graphene used in the prior high frequency transistor studies, exemplifying the superior electronics potential of C-face epitaxial graphene. Careful transistor design using a high {\kappa} dielectric T-gate and self-aligned contacts, further contributed to the record-breaking fmax

Protein structure generation via folding diffusion

The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases. Despite recent advances in protein structure prediction, directly generating diverse, novel protein structures from neural networks remains difficult. In this work, we present a new diffusion-based generative model that designs protein backbone structures via a procedure that mirrors the native folding process. We describe protein backbone structure as a series of consecutive angles capturing the relative orientation of the constituent amino acid residues, and generate new structures by denoising from a random, unfolded state towards a stable folded structure. Not only does this mirror how proteins biologically twist into energetically favorable conformations, the inherent shift and rotational invariance of this representation crucially alleviates the need for complex equivariant networks. We train a denoising diffusion probabilistic model with a simple transformer backbone and demonstrate that our resulting model unconditionally generates highly realistic protein structures with complexity and structural patterns akin to those of naturally-occurring proteins. As a useful resource, we release the first open-source codebase and trained models for protein structure diffusion

Top-gated graphene field-effect-transistors formed by decomposition of SiC

Top-gated, few-layer graphene field-effect transistors (FETs) fabricated on thermally-decomposed semi-insulating 4H-SiC substrates are demonstrated. Physical vapor deposited SiO2 is used as the gate dielectric. A two-dimensional hexagonal arrangement of carbon atoms with the correct lattice vectors, observed by high-resolution scanning tunneling microscopy, confirms the formation of multiple graphene layers on top of the SiC substrates. The observation of n-type and p-type transition further verifies Dirac Fermions unique transport properties in graphene layers. The measured electron and hole mobility on these fabricated graphene FETs are as high as 5400 cm2/Vs and 4400 cm2/Vs respectively, which are much larger than the corresponding values from conventional SiC or silicon

Upregulation of CD36, a Fatty Acid Translocase, Promotes Colorectal Cancer Metastasis by Increasing MMP28 and Decreasing E-Cadherin Expression

Altered fatty acid metabolism continues to be an attractive target for therapeutic intervention in cancer. We previously found that colorectal cancer (CRC) cells with a higher metastatic potential express a higher level of fatty acid translocase (CD36). However, the role of CD36 in CRC metastasis has not been studied. Here, we demonstrate that high expression of CD36 promotes invasion of CRC cells. Consistently, CD36 promoted lung metastasis in the tail vein model and GI metastasis in the cecum injection model. RNA-Seq analysis of CRC cells with altered expression of CD36 revealed an association between high expression of CD36 and upregulation of MMP28, a novel member of the metallopeptidase family of proteins. Using shRNA-mediated knockdown and overexpression of CD36, we confirmed that CD36 regulates MMP28 expression in CRC cells. siRNA-mediated knockdown of MMP28 decreases invasion of CRC cells, suggesting that MMP28 regulates the metastatic properties of cells downstream of CD36. Importantly, high expression of MMP28 leads to a significant decrease in active E-cadherin and an increase in the products of E-cadherin cleavage, CTF1 and CTF2. In summary, upregulation of CD36 expression promotes the metastatic properties of CRC via upregulation of MMP28 and an increase in E-cadherin cleavage, suggesting that targeting the CD36–MMP28 axis may be an effective therapeutic strategy for CRC metastasis

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay

<p>Abstract</p> <p>Background</p> <p>Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan^®RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco <it>type</it>DX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application.</p> <p>Results</p> <p>RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan^®reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery.</p> <p>Conclusion</p> <p>We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.</p

Electric Field-Tuned Topological Phase Transition in Ultra-Thin Na3Bi - Towards a Topological Transistor

The electric field induced quantum phase transition from topological to conventional insulator has been proposed as the basis of a topological field effect transistor [1-4]. In this scheme an electric field can switch 'on' the ballistic flow of charge and spin along dissipationless edges of the two-dimensional (2D) quantum spin Hall insulator [5-9], and when 'off' is a conventional insulator with no conductive channels. Such as topological transistor is promising for low-energy logic circuits [4], which would necessitate electric field-switched materials with conventional and topological bandgaps much greater than room temperature, significantly greater than proposed to date [6-8]. Topological Dirac semimetals(TDS) are promising systems in which to look for topological field-effect switching, as they lie at the boundary between conventional and topological phases [3,10-16]. Here we use scanning probe microscopy/spectroscopy (STM/STS) and angle-resolved photoelectron spectroscopy (ARPES) to show that mono- and bilayer films of TDS Na3Bi [3,17] are 2D topological insulators with bulk bandgaps >400 meV in the absence of electric field. Upon application of electric field by doping with potassium or by close approach of the STM tip, the bandgap can be completely closed then re-opened with conventional gap greater than 100 meV. The large bandgaps in both the conventional and quantum spin Hall phases, much greater than the thermal energy kT = 25 meV at room temperature, suggest that ultrathin Na3Bi is suitable for room temperature topological transistor operation