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Applications of Copper (Cu) range from small scale applications such as microelectronics interconnects to very large high-powered applications such as railguns. In all these applications, Cu conductivity and ampacity play vital roles. In some applications such as railguns, where Cu also plays a structural role, not only is high conductivity needed, but high strength, high ductility, and high wear resistance are also critical. Current technologies have achieved their full potential for producing better materials. New approaches and technologies are needed to develop superior properties. This research examines a new fabrication approach that is expected to produce Cu with superior mechanical strength, enhanced wear resistance, and increased electrical conductivity. Materials with refined grain structures were obtained by breaking down the coarse-grained Cu particles via cryogenic ball milling, followed by the consolidation of powders using cold isostatic pressing (CIP) and subsequent Continuous Equal Channel Angular Pressing (C-ECAP). The mixture of fine and ultrafine grains, with sizes between 200 nm to 2.5 µm and an average of 500 nm, was formed after ball milling at cryogenic temperatures. Further processing via C-ECAP produced nanostructured Cu with average grain sizes below 50 nm and excellent homogenous equiaxed grain shapes and random orientations. The hardness and tensile strength of the final Cu were approximately 158% and 95% higher than the traditional coarse-grained Cu bar, respectively. This material also displayed a good electrical conductivity rate of 74% International Annealed Copper Standard (IACS), which is comparable to the current Cu materials used in railgun applications.

The forest volumes are essential as they are directly related to the economic and environmental values of the forests. Satellite-based forest volume estimation was first developed in the 1990s, and the accuracy of the estimation has been improved over time. One of the satellite-based forest volume estimation issues is that it tends to overestimate the large volume class and underestimate the small volume class. Free availability of the major satellite imagery and the development of cloud-based computational platforms facilitate an immense amount of satellite imagery in the estimation. In this paper, we set three objectives: (1) to examine whether the long Landsat time series contributes to the improvement of the estimation accuracy, (2) to explore the effectiveness of forest disturbance record and land cover data as ancillary spatial data on the accuracy of the estimation, and (3) to apply the bias correction method to reduce the bias of the estimation. We computed three Tasseled-cap components from the Landsat data for preparation of short (2014–2016) and long (1984–2016) time series. Each data entity was analyzed with harmonic regressions resulting in the coefficients and the fitted values recorded as pixel values in a multilayer raster database. Data included Forest Inventory and Analysis (FIA) unit field inventory measurements provided by the United States Department of Agriculture Forest Service and the National Land Cover Database and disturbance history data added as ancillary information. The totality of the available data was organized into seven distinct Random Forest (RF) models with different variables compared against each other to identify the ones with the most satisfactory performance. A bias correction method was then applied to all the RF models to examine the effectiveness of the method. Among the seven models, the worst one used the coefficients and fitted values of the short Landsat time series only, and the best one used coefficients and fitted values of both short and long Landsat time series. Using the Out-of-bag (OOB) score, the best model was found to be 34.4% better than the worst one. The model that used only the long time series data had almost the same OOB score as the best model. The results indicate that the use of the long Landsat time series improves model performance. Contrary to the previous research employing forest disturbance data as a feature variable had almost no effect on OOB. The bias correction method reduced the relative size of the bias in the estimates of the best model from 3.79% to −1.47%, the bottom 10% bias by 12.5 points, and the top 10% bias by 9.9 points. Depending on the types of forest, important feature variables were differed, reflecting the relationship between the time series remote sensing data we computed for this research and the forests’ phenological characteristics. The availability of Light Detection And Ranging (LiDAR) data and accessibility of the precise locations of the FIA data are likely to improve the model estimates further.

Background and objectives: Research investigating hydration strategies specialized for women’s soccer players is limited, despite the growth in the sport. The purpose of this study was to determine the effects of fluid balance and electrolyte losses in collegiate women’s soccer players. Materials and Methods: Eighteen NCAA Division I women’s soccer players were recruited (age: 19.2 ± 1.0 yr; weight: 68.5 ± 9.0 kg, and height: 168.4 ± 6.7 cm; mean ± SD), including: 3 forwards (FW), 7 mid-fielders (MD), 5 defenders (DF), and 3 goalkeepers (GK). Players practiced outdoor during spring off-season training camp for a total 14 practices (WBGT: 18.3 ± 3.1 °C). The main outcome measures included body mass change (BMC), sweat rate, urine and sweat electrolyte concentrations, and fluid intake. Results: Results were analyzed for comparison between low (LOW; 16.2 ± 2.6° C, n = 7) and moderate risk environments for hyperthermia (MOD; 20.5 ± 1.5 °C, n = 7) as well as by field position. The majority (54%) of players were in a hypohydrated state prior to practice. Overall, 26.7% of players had a %BMC greater than 0%, 71.4% of players had a %BMC less than −2%, and 1.9% of players had a %BMC greater than −2% (all MD position). Mean %BMC and sweat rate in all environmental conditions were −0.4 ± 0.4 kg (−0.5 ± 0.6% body mass) and 1.03 ± 0.21 mg·cm−2·min−1, respectively. In the MOD environment, players exhibited a greater sweat rate (1.07 ± 0.22 mg·cm−2·min−1) compared to LOW (0.99 ± 0.22 mg·cm−2·min−1; p = 0.02). By position, DF had a greater total fluid intake and a lower %BMC compared to FW, MD, and GK (all p < 0.001). FW had a greater sweat sodium (Na+) (51.4 ± 9.8 mmol·L−1), whereas GK had the lowest sweat sodium (Na+) (30.9 ± 3.9 mmol·L−1). Conclusions: Hydration strategies should target pre-practice to ensure players are adequately hydrated. Environments deemed to be of moderate risk of hyperthermia significantly elevated the sweat rate but did not influence fluid intake and hydration status compared to low-risk environments. Given the differences in fluid balance and sweat responses, recommendations should be issued relative to soccer position.

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens into higher taxonomic categories.

The common bean ( Phaseolus vulgaris L.) is an important nutritional source globally but is sensitive to high temperatures and thus particularly vulnerable to climate change. Derived from a breeding program at CIAT (Colombia), a heat-tolerant breeding line, named heat-tolerant Andean-type 4 (HTA4), was developed by a series of crosses of parents with a small-bean tepary genotype ( Phaseolus acutifolius L.) in their pedigree, which might be the donor of heat stress (HS) tolerance. Importantly, in HTA4, the large, commercially desirable Andean-type beans was restored. To assess underlying tolerance mechanisms, HTA4, together with a heat-sensitive Colombian variety (Calima), was exposed to HS (31 °C/24 °C HS vs. 26 °C/19 °C day/night) under controlled environment conditions. Vegetative growth and photosynthetic performance were not negatively impacted by HS in either genotype, although senescence was delayed in Calima. HS during the reproductive stage caused an increase in pod number in Calima but with few fully developed seeds and many pods aborted and/or abscised. In contrast, HTA4 maintained a similar filled pod number under HS and a higher seed weight per plant. Pollen showed high sterility in Calima, with many non-viable pollen grains (24.9% viability compared to 98.4% in control) with a thicker exine and fewer starch granules under HS. Calima pollen failed to adhere to the stigma and germinate under HS. In HTA4, pollen viability was significantly higher than in Calima (71.1% viability compared to 95.4% under control), and pollen successfully germinated and formed pollen tubes in the style under HS. It is concluded that HTA4 is heat tolerant and maintains a high level of reproductive output due to its ability to produce healthy pollen that is able to adhere to the stigma.

Background: To analyze the fracture resistance of zirconia implants within the anterior region and evaluate whether zirconia-zirconia implants can be a viable alternative to titanium implants., Methods: Four online databases (Cochrane Library, Ovid, PubMed, and Scopus) were searched for the period of January 2011 to July 2021. All studies that analyzed the in vivo clinical outcome of two-piece implants in the anterior region in English language were included., Results: The search strategy identified 242 studies. Of these studies, three studies were included for qualitative synthesis based on the pre-determined eligibility criteria. The results showed that there is significant difference in biological results, fractal behavior and other complications between one-piece and two-piece zirconia implants. Two-piece zirconia implants demonstrated favorable longevity and success rates within anterior maxillary in short-term trials., Conclusions: Although factors involved in fractures have been identified-sandblasting, implant diameter, occlusal load, age and implant coating-there is limited quantitative assessment to gauge the fracture resistance of two-piece zirconia implants. Hence, further research with long-term clinical evidence is required.

Some immune system cells express type A and/or type B γ-aminobutyric acid receptors (GABA A -Rs and/or GABA B -Rs). Treatment with GABA, which activates both GABA A -Rs and GABA B -Rs), and/or a GABA A -R-specific agonist inhibits disease progression in mouse models of type 1 diabetes (T1D), multiple sclerosis, rheumatoid arthritis, and COVID-19. Little is known about the clinical potential of specifically modulating GABA B -Rs. Here, we tested lesogaberan, a peripherally restricted GABA B -R agonist, as an interventive therapy in diabetic NOD mice. Lesogaberan treatment temporarily restored normoglycemia in most newly diabetic NOD mice. Combined treatment with a suboptimal dose of lesogaberan and proinsulin/alum immunization in newly diabetic NOD mice or a low-dose anti-CD3 in severely hyperglycemic NOD mice greatly increased T1D remission rates relative to each monotherapy. Mice receiving combined lesogaberan and anti-CD3 displayed improved glucose tolerance and, unlike mice that received anti-CD3 alone, had some islets with many insulin + cells, suggesting that lesogaberan helped to rapidly inhibit β-cell destruction. Hence, GABA B -R-specific agonists may provide adjunct therapies for T1D. Finally, the analysis of microarray and RNA-Seq databases suggested that the expression of GABA B -Rs and GABA A -Rs, as well as GABA production/secretion-related genes, may be a more common feature of immune cells than currently recognized.

Oral chemotherapy represents a major patient-centric advancement in therapy convenience. However, ownership of safe and correct administration of these agents requires significant patient education. To address this challenge, an in-person pharmacist-led oral chemotherapy education clinic in gastrointestinal oncology patients within an academic medical center was created and assessed. In this pilot program, a medication-specific quiz was administered to patients before and after education performed by a pharmacist to assess patient understanding of their new oral chemotherapy. A five-question satisfaction survey was also administered at the conclusion of the pharmacist clinic visit. Primary outcome was the percentage difference between pre-and post-education quiz scores. Secondary outcomes included patient satisfaction, time to treatment initiation, and number of pharmacist interventions. Frequencies and medians were used to describe categorical and continuous variables, respectively. Of the 18 patients analyzed, 50% were male and median age was 59.5 years. Approximately 28% had colon cancer, and 61% were treated with capecitabine. The median post-education scores improved from a pre-education score of 75% to 100%. Overall, seventeen of the eighteen patients responded with "strongly agree" to all satisfaction survey statements. An in-person oncology pharmacist-led oral chemotherapy education session demonstrated an improvement in patients' understanding of their new oral chemotherapy treatment.