Loss prevention for hog farmers: Insurance, on-farm biosecurity practices, and vaccination

Using agricultural household survey data and claim records from insurers for the year 2009, this paper analyzes hog producers' choice of means of loss prevention and identifies the relationships among biosecurity practices, vaccination, and hog insurance. By combining one probit and two structural equations, we adopt three-stage estimations on a mixed-process model to obtain the results. The findings indicate that biosecurity practices provide the basic infrastructure for operating pig farms and complement both the usage of quality vaccines and the uptake of hog insurance. In addition, there is a strong relationship of substitution between quality of vaccine and demand for hog insurance. Hog farmers that implement better biosecurity practices are more likely to seek high-quality vaccines or buy into hog insurance schemes but not both. For those households with hog insurance, better biosecurity status, better management practices, and higher-quality vaccine significantly help to reduce loss ratios. However, we also find a moral hazard effect in that higher premium expenditure by the insured households might induce larger loss ratios.Biosecurity, hog insurance, loss prevention, vaccine,

Cryo-EM of full-length α-synuclein reveals fibril polymorphs with a common structural kernel.

α-Synuclein (aSyn) fibrillar polymorphs have distinct in vitro and in vivo seeding activities, contributing differently to synucleinopathies. Despite numerous prior attempts, how polymorphic aSyn fibrils differ in atomic structure remains elusive. Here, we present fibril polymorphs from the full-length recombinant human aSyn and their seeding capacity and cytotoxicity in vitro. By cryo-electron microscopy helical reconstruction, we determine the structures of the two predominant species, a rod and a twister, both at 3.7 Å resolution. Our atomic models reveal that both polymorphs share a kernel structure of a bent β-arch, but differ in their inter-protofilament interfaces. Thus, different packing of the same kernel structure gives rise to distinct fibril polymorphs. Analyses of disease-related familial mutations suggest their potential contribution to the pathogenesis of synucleinopathies by altering population distribution of the fibril polymorphs. Drug design targeting amyloid fibrils in neurodegenerative diseases should consider the formation and distribution of concurrent fibril polymorphs

Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers

Quantum computing has the potential to solve problems that are intractable for classical systems, yet the high error rates in contemporary quantum devices often exceed tolerable limits for useful algorithm execution. Quantum Error Correction (QEC) mitigates this by employing redundancy, distributing quantum information across multiple data qubits and utilizing syndrome qubits to monitor their states for errors. The syndromes are subsequently interpreted by a decoding algorithm to identify and correct errors in the data qubits. This task is complex due to the multiplicity of error sources affecting both data and syndrome qubits as well as syndrome extraction operations. Additionally, identical syndromes can emanate from different error sources, necessitating a decoding algorithm that evaluates syndromes collectively. Although machine learning (ML) decoders such as multi-layer perceptrons (MLPs) and convolutional neural networks (CNNs) have been proposed, they often focus on local syndrome regions and require retraining when adjusting for different code distances. We introduce a transformer-based QEC decoder which employs self-attention to achieve a global receptive field across all input syndromes. It incorporates a mixed loss training approach, combining both local physical error and global parity label losses. Moreover, the transformer architecture's inherent adaptability to variable-length inputs allows for efficient transfer learning, enabling the decoder to adapt to varying code distances without retraining. Evaluation on six code distances and ten different error configurations demonstrates that our model consistently outperforms non-ML decoders, such as Union Find (UF) and Minimum Weight Perfect Matching (MWPM), and other ML decoders, thereby achieving best logical error rates. Moreover, the transfer learning can save over 10x of training cost.Comment: Accepted to ICCAD 2023, FAST ML for Science Workshop; 7 pages, 8 figure

A Turnover in the Galaxy Main Sequence of Star Formation at M∗∼1010M⊙M_{*} \sim 10^{10} M_{\odot} for Redshifts z<1.3z < 1.3

The relationship between galaxy star formation rates (SFR) and stellar masses ($M_\ast$) is re-examined using a mass-selected sample of $\sim$62,000 star-forming galaxies at $z \le 1.3$ in the COSMOS 2-deg$^2$ field. Using new far-infrared photometry from $Herschel$-PACS and SPIRE and $Spitzer$-MIPS 24 $\mu$m, along with derived infrared luminosities from the NRK method based on galaxies' locations in the restframe color-color diagram $(NUV - r)$ vs. $(r - K)$, we are able to more accurately determine total SFRs for our complete sample. At all redshifts, the relationship between median $SFR$ and $M_\ast$ follows a power-law at low stellar masses, and flattens to nearly constant SFR at high stellar masses. We describe a new parameterization that provides the best fit to the main sequence and characterizes the low mass power-law slope, turnover mass, and overall scaling. The turnover in the main sequence occurs at a characteristic mass of about $M_{0} \sim 10^{10} M_{\odot}$ at all redshifts. The low mass power-law slope ranges from 0.9-1.3 and the overall scaling rises in SFR as a function of $(1+z)^{4.12 \pm 0.10}$. A broken power-law fit below and above the turnover mass gives relationships of $SFR \propto M_{*}^{0.88 \pm 0.06}$ below the turnover mass and $SFR \propto M_{*}^{0.27 \pm 0.04}$ above the turnover mass. Galaxies more massive than $M_\ast \gtrsim 10^{10}\ M_{\rm \odot}$ have on average, a much lower specific star formation rate (sSFR) than would be expected by simply extrapolating the traditional linear fit to the main sequence found for less massive galaxies.Comment: 16 pages, 7 figures. Accepted for publication in Ap

Development and Implementation of a High Throughput Screen for the Human Sperm-Specific Isoform of Glyceraldehyde 3-Phosphate Dehydrogenase (GAPDHS)

Glycolytic isozymes that are restricted to the male germline are potential targets for the development of reversible, non-hormonal male contraceptives. GAPDHS, the sperm-specific isoform of glyceraldehyde-3-phosphate dehydrogenase, is an essential enzyme for glycolysis making it an attractive target for rational drug design. Toward this goal, we have optimized and validated a high-throughput spectrophotometric assay for GAPDHS in 384-well format. The assay was stable over time and tolerant to DMSO. Whole plate validation experiments yielded Z’ values >0.8 indicating a robust assay for HTS. Two compounds were identified and confirmed from a test screen of the Prestwick collection. This assay was used to screen a diverse chemical library and identified fourteen small molecules that modulated the activity of recombinant purified GAPDHS with confirmed IC50 values ranging from 1.8 to 42 µM. These compounds may provide useful scaffolds as molecular tools to probe the role of GAPDHS in sperm motility and long term to develop potent and selective GAPDHS inhibitors leading to novel contraceptive agents

Fibromodulin Reduces Scar Formation in Adult Cutaneous Wounds by Eliciting a Fetal-Like Phenotype

Blocking transforming growth factor (TGF)β1 signal transduction has been a central strategy for scar reduction; however, this approach appears to be minimally effective. Here, we show that fibromodulin (FMOD), a 59-kD small leucine-rich proteoglycan critical for normal collagen fibrillogenesis, significantly reduces scar formation while simultaneously increasing scar strength in both adult rodent models and porcine wounds, which simulate human cutaneous scar repair. Mechanistically, FMOD uncouples pro-migration/contraction cellular signals from pro-fibrotic signaling by selectively enhancing SMAD3-mediated signal transduction, while reducing AP-1-mediated TGFβ1 auto-induction and fibrotic extracellular matrix accumulation. Consequently, FMOD accelerates TGFβ1-responsive adult fibroblast migration, myofibroblast conversion, and function. Furthermore, our findings strongly indicate that, by delicately orchestrating TGFβ1 activities rather than indiscriminately blocking TGFβ1, FMOD elicits fetal-like cellular and molecular phenotypes in adult dermal fibroblasts in vitro and adult cutaneous wounds in vivo, which is a unique response of living system undescribed previously. Taken together, this study illuminates the signal modulating activities of FMOD beyond its structural support functions, and highlights the potential for FMOD-based therapies to be used in cutaneous wound repair. © The Author(s) 2017

Interfacial charge transfer in nanoscale polymer transistors

Interfacial charge transfer plays an essential role in establishing the relative alignment of the metal Fermi level and the energy bands of organic semiconductors. While the details remain elusive in many systems, this charge transfer has been inferred in a number of photoemission experiments. We present electronic transport measurements in very short channel ($L < 100$ nm) transistors made from poly(3-hexylthiophene) (P3HT). As channel length is reduced, the evolution of the contact resistance and the zero-gate-voltage conductance are consistent with such charge transfer. Short channel conduction in devices with Pt contacts is greatly enhanced compared to analogous devices with Au contacts, consistent with charge transfer expectations. Alternating current scanning tunneling microscopy (ACSTM) provides further evidence that holes are transferred from Pt into P3HT, while much less charge transfer takes place at the Au/P3HT interface.Comment: 19 preprint pages, 6 figure