Development of a doorframe-typed swinging seedling pick-up device for automatic field transplantation

A doorframe-typed swing seedling pick-up device for automatic field transplanters was developed and evaluated in a laboratory. The device, consisting of a path manipulator and two grippers, can move the pins slowly to extract seedlings from the tray cells and return quickly to the pick-up point for the next extraction. The path manipulator was constructed with the creative design of type-Ⅱ mechanism combination in series. It consists of an oscillating guide linkage mechanism and a grooved globoidal cam mechanism. The gripper is a pincette-type mechanism using the pick-up pins to penetrate into the root mass for seedling extraction. The dynamic analysis of the designed seedling pick-up device was simulated with ADAMS software. Being the first prototype, various performance tests under local production conditions were conducted to find out the optimal machine operation parameters and transplant production conditions. As the gripper with multiple fine pins was moved by the swing pick-up device, it can effectively complete the transplanting work cycle of extracting, transferring, and discharging a seedling. The laboratory evaluation showed that the pick-up device equipped with two grippers can extract 80 seedlings/min with a 90% success and a 3% failure in discharging seedlings, using 42-day-old tomato plantlets. The quality of extracting seedlings was satisfactory

Mechanical Properties of Steel Fiber-Reinforced Magnesium Phosphate Cement Mortar

A new cement-based mortar with high early strength and toughness was developed by adding micro steel fibers (MSF) in magnesium phosphate cement (MPC) mortar. The compressive and flexural tests were carried out to investigate the effect of curing time, MSF volume fraction, sand-cement mass ratio, and water-cement mass ratio on the strength and flexural toughness of MSF-reinforced MPC mortar (MSFRMM). Also, the flexural toughness and ductility of MSFRMM were evaluated according to ASTM C1609. The results of this study showed that the addition of MSF from 0% to 1.6% by volume significantly improved the compressive strength of MSFRMM. The MSFRMM showed high early strength, especially during the first 3 days. The addition of MSFs changed the flexural failure mode of MPC-based mortar from brittleness to ductility, and the flexural toughness of MSFRMM remarkably increased with the increase of MSF volume fraction from 0% to 1.6%. The toughness and ductility of MSFRMM slightly increased with the increase of the dosage of cement. The toughness and ductility of MSFRMM increased with the decrease of the water-cement mass ratio due to the improved density of the mortar caused by the reduction of water

Effect of supercritical CO2 extraction on pore characteristics of coal and its mechanism

Abundant pore space in coal is not only the place for the accumulation of coalbed methane (CBM), but also the tunnel for gas migration. In this study, five sets of coal samples before and after the second coalification were selected from the eastern margin of Ordos Basin to simulate supercritical CO2 (Sc-CO2) extraction in supercritical extraction equipment. The evolutions of pore structure and porosity were tested by mercury intrusion porosimetry and nuclear magnetic resonance spectroscopy to compare the changes of pore structure and porosity due to the Sc-CO2 extraction, and to explain the related mechanism. The results show that: (1) Pore volume, pore specific surface area, and connectivity characteristics changed significantly due to Sc-CO2 extraction, and the increment of pore volume and pore specific surface area presented a law of increase–decrease–increase with the increase in the coal rank, and the turning point was near the second coalification. (2) The porosity increment change trend due to Sc-CO2 extraction was increase–decrease–increase with increasing coal rank, and the turning point was again near the second coalification, which supports the mercury intrusion porosimetry results. (3) The changes were observed in the porosity characteristics due to Sc-CO2 extraction through pore-increasing and expanding effects. Before the second coalification, the pore-increasing and expanding effects co-existed in the micropores, and after the second coalification, the pore-expanding effect mainly existed in the transitional pores and above. (4) The variation model for the pore structure of coal due to Sc-CO2 extraction was established. The conclusions offer not only important theoretical significance for the CO2-enhanced CBM (CO2-ECBM) mechanism but also important significance for CO2-ECBM engineering

Low geriatric nutritional risk index as a poor prognostic biomarker for immune checkpoint inhibitor treatment in solid cancer

ObjectiveIn this investigation, we focused on the geriatric nutritional risk index (GNRI), a comprehensive metric that takes into account the patient’s ideal weight, actual weight, and serum albumin levels to measure malnutrition. Our primary objective was to examine the predictive value of GNRI-defined malnutrition in determining the response to immunotherapy among cancer patients.MethodsRelevant articles for this study were systematically searched in PubMed, the Cochrane Library, EMBASE, and Google Scholar up to July 2023. Our analysis evaluated overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR) as clinical outcomes.ResultsThis analysis comprised a total of eleven articles encompassing 1,417 patients. The pooled results revealed that cancer patients with low GNRI levels exhibited shorter OS (HR: 2.64, 95% CI: 2.08–3.36, p < 0.001) and PFS (HR: 1.87, 95% CI: 1.46–2.41, p < 0.001), and lower ORR (OR: 0.46, 95% CI: 0.33–0.65, p < 0.001) and DCR (OR: 0.42, 95% CI: 0.29–0.61, p < 0.001). Sensitivity analyses confirmed that the above results were stable. Egger’s and Begg’s tests revealed that there was no publication bias in the above results.ConclusionOur results imply that the GNRI is a useful predictor of immunotherapy response in cancer patients

Overexpression of Polo-like kinase1 (PLK1) in chondrosarcoma and its implications for cancer progression

Polo-like kinase1 (PLK1) is a new therapeutic target for osteosarcoma with good application prospects. Whether PLK1 is highly expressed in chondrosarcoma and whether PLK1 can be a potential therapeutic target for chondrosarcoma are worth exploring. However, PLK1 expression in chondrosarcoma is scarcely investigated. Therefore, we collected 11 cases of chondrosarcoma and 26 cases of osteochondroma with complete clinical pathological data and used immunohistochemical staining to detect the expression of PLK1 in chondrosarcoma and osteochondroma and then studied its significance and relationship with clinical pathological parameters. Our results showed that the positive expression rate of PLK1 in chondrosarcoma tissue (90.91%, 10/11) was significantly higher than the rate of osteochondroma tissues (53.85%, 14/26) (

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