A Comparison of Two Felling Techniques Considering Stump-Height-Related Timber Value Loss

Harvest from plantations can provide both industrial wood and forest residues for bioenergy, including stumps. The literature suggests that the choice of cutting system can affect the division between industrial wood recovery and remaining stump volume. In this study, two felling techniques - motor-manual chainsaw and feller-buncher, were compared based on stump-height-related timber value loss for four ground slope classes: high, medium, low, and flat. The economic value loss of wood material for three products - sawlogs, pulpwood, and fiber-chip wood, was determined based on the estimated volume of stumps left in the woods. The results indicated that the average stump height for the motor-manual chainsaw and fellerbuncher was 17.16 cm and 8.69 cm. The economic value loss of wood material per stump was higher in felling by manual chainsaw as compared to the feller-buncher operation (log: €0.60↑, paper wood: €0.29↑, fiber-chip: €0.15↑). However, volume loss due to high stumps could contribute to wood for bioenergy if stumps are subsequently removed. Additional research is needed to evaluate the benefits and costs of stump removal for bioenergy as part of a total supply chain to provide both industrial wood and wood for bioenergy

Identification of photocurrents in topological insulators

Optical injection and detection of charge currents is an alternative to conventional transport and photoemission measurements, avoiding the necessity of invasive contact that may disturb the system being examined. This is a particular concern for analyzing the surface states of topological insulators. In this work one- and two-color sources of photocurrents are isolated and examined in epitaxial thin films of Bi2Se3. We demonstrate that optical excitation and terahertz detection simultaneously captures one- and two-color photocurrent contributions, which has not been required for other material systems. A method is devised to extract the two components, and in doing so each can be related to surface or bulk excitations through symmetry. The separation of such photocurrents in topological insulators opens a new avenue for studying these materials by all-optical methods

Gliosarcoma: a study of four cases

Gliosarcomas (GS) are highly malignant and rare tumors of the central nervous system with a poor prognosis. We report here on four patients with GS, the median survival for whom was 9.25 months. Prognosis of GS remains poor, and a multidisciplinary approach (surgery, radiation therapy, and chemotherapy) seems to be associated with slightly more prolonged survival times

A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila.

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive

In Vivo Expression of MHC Class I Genes Depends on the Presence of a Downstream Barrier Element

Regulation of MHC class I gene expression is critical to achieve proper immune surveillance. In this work, we identify elements downstream of the MHC class I promoter that are necessary for appropriate in vivo regulation: a novel barrier element that protects the MHC class I gene from silencing and elements within the first two introns that contribute to tissue specific transcription. The barrier element is located in intergenic sequences 3′ to the polyA addition site. It is necessary for stable expression in vivo, but has no effect in transient transfection assays. Accordingly, in both transgenic mice and stably transfected cell lines, truncation of the barrier resulted in transcriptional gene silencing, increased nucleosomal density and decreased histone H3K9/K14 acetylation and H3K4 di-methylation across the gene. Significantly, distinct sequences within the barrier element govern anti-silencing and chromatin modifications. Thus, this novel barrier element functions to maintain transcriptionally permissive chromatin organization and prevent transcriptional silencing of the MHC class I gene, ensuring it is poised to respond to immune signaling

Role of Wnt canonical pathway in hematological malignancies

Wnt canonical signaling pathway plays a diverse role in embryonic development and maintenance of organs and tissues in adults. It has been observed that Wnt/β-catenin signaling pathway is involved in the pathogenesis of many carcinomas. Moreover, Wnt/β-catenin pathway has been revealed to be associated with angiogenesis. Wnt canonical pathway signaling has great potential as a therapeutic target. It has been disclosed that some hematological malignancies, such as chronic lymphocytic leukemia, mantle cell lymphoma, may occur partly due to the constitutive activation of Wnt canonical signaling pathway. This review will summarize the latest development in Wnt canonical signaling pathway and its roles in tumorigenesis and angiogenesis

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio