Experimental analyses to investigate the feasibility and effectiveness in using heat pipe-embedded drills

This paper presents an experimental investigation to verify the feasibility and effectiveness of heat pipe cooling in drilling operations. The basic idea is to insert a heat pipe at the center of the drill tool with the evaporator close to the drill tip and the condenser at the end of the drill. Consequently, the heat generated at the tool–chip interface can be removed by convection heat transfer. Experimental studies were involved in three cases, including solid drill without coolant, solid drill with coolant, and heat pipe drill. Drilling tests were conducted on a CNC machining center with full immersion cutting. The cast iron square block was used as the workpiece, and the high-speed steel was chosen for the drill tool material. Flank wear is considered as the criterion for tool failure, and the wear was measured using a Hisomet II Toolmaker’s microscope. The tests were conducted until the drill was rejected when an average flank wear greater than 0.10 mm was recorded. The results demonstrate that using a heat pipe in the drilling process can effectively perform thermal management comparable to the flooding coolant cooling used pervasively in the manufacturing industry, extending the tool life of the drill

Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system

Tomatoes have different water requirements in each growing period. Excessive water use or insufficient water supply will affect the growth and yield of tomato plants. Therefore, precise irrigation control is necessary during cultivation to increase crop productivity. Traditionally, the soil moisture content or leaf water potential has been used as an indicator of plant water status. These methods, however, have limited accuracy and are time-consuming, making it difficult to be put into practice in tomato production. This study developed an online hyperspectral imaging system to measure the leaf water potential of tomato nondestructively. Linear Discriminant Analysis was utilized to automatically and quickly extract the leaf images, with the recognition accuracy of 94.68% was achieved. The mathematical processing of Standard Normal Variate scattering correction was used to remove the spectral variations caused by the defocused leave images. The developed leaf water potential prediction model based on the spectral image information attained using the developed system achieved the standard error of calibration of 0.201, coefficient of determination in calibration set of 0.814 and standard error of cross�validation of 0.230, and one minus the variance ratio of 0.755. The obtained performance indicated the feasibility of apply�ing the developed online hyperspectral imaging system as a real-time non-destructive measurement technique for the leaf water potential of tomato plants

Differentiating impacts of non‐pharmaceutical interventions on non‐coronavirus disease‐2019 respiratory viral infections: Hospital‐based retrospective observational study in Taiwan

Background Physical distancing and facemask use are worldwide recognized as effective non-pharmaceutical interventions (NPIs) against the coronavirus disease-2019 (COVID-19). Since January 2020, Taiwan has introduced both NPIs but their effectiveness on non-COVID-19 respiratory viruses (NCRVs) remain underexplored. Methods This retrospective observational study examined electronic records at a tertiary hospital in northern Taiwan from pre-COVID (January–December 2019) to post-COVID period (January–May 2020). Patients with respiratory syndromes were tested for both enveloped (eg, influenza virus and seasonal coronavirus) and non-enveloped RVs (eg, enterovirus and rhinovirus) using multiplex reverse transcription polymerase chain reaction assays. Monthly positivity rates of NCRVs among adult and pediatric patients were analyzed with comparison between pre- and post-COVID periods. Results A total of 9693 patients underwent 12 127 multiplex RT-PCR tests. The average positivity rate of NCRVs reduced by 11.2% (25.6% to 14.4%) after nationwide PHIs. Despite the COVID-19 pandemic, the most commonly identified enveloped and non-enveloped viruses were influenza virus and enterovirus/rhinovirus, respectively. Observed reduction in NCRV incidence was predominantly contributed by enveloped NCRVs including influenza viruses. We did not observe epidemiological impacts of NPIs on non-enveloped viruses but an increasing trend in enterovirus/rhinovirus test positivity rate among pediatric patients. Our data were validated using Taiwan's national notification database. Conclusions Our frontline investigation suggests that the current NPIs in Taiwan might not effectively control the transmission of non-enveloped respiratory viruses, despite their protective effects against influenza and seasonal coronavirus. Health authorities may consider using hydrogen peroxide or chloride-based disinfectants as additional preventative strategies against non-enveloped respiratory viruses in the post-COVID-19 era

Improving Success Rates of Percutaneous Coronary Intervention for Chronic Total Occlusion at a Rural Hospital in East Taiwan

SummaryBackgroundWe aimed to report the results of percutaneous coronary intervention for chronic total occlusion (CTO) in a remote hospital of southeast Taiwan that does not have on-site coronary artery bypass graft support and has insufficient medical resources.MethodsFrom 2006 to 2009, we identified 96 patients who underwent percutaneous coronary intervention and whose coronary angiogram showed CTO lesions. On-site cardiovascular surgeons were unavailable from 2006 to 2009.ResultsThe success rate (test for trend, p = 0.02) and numbers of guidewires used (test for trend, p = 0.59) significantly increased from 2006 to 2009, and the procedural time reduced significantly (test for trend, p = 0.001). The volume of contrast media injected decreased, although this result was not statistically significant (p = 0.70).ConclusionOur experience in managing CTO lesions substantially improved and the procedural time reduced over 4 years, even when constrained by a relative shortage of medical resources

Role of autophagy-related proteins ATG8f and ATG8h in the maintenance of autophagic activity in Arabidopsis roots under phosphate starvation

Nutrient starvation-induced autophagy is a conserved process in eukaryotes. Plants defective in autophagy show hypersensitivity to carbon and nitrogen limitation. However, the role of autophagy in plant phosphate (Pi) starvation response is relatively less explored. Among the core autophagy-related (ATG) genes, ATG8 encodes a ubiquitin-like protein involved in autophagosome formation and selective cargo recruitment. The Arabidopsis thaliana ATG8 genes, AtATG8f and AtATG8h, are notably induced in roots under low Pi. In this study, we show that such upregulation correlates with their promoter activities and can be suppressed in the phosphate response 1 (phr1) mutant. Yeast one-hybrid analysis failed to attest the binding of the AtPHR1 transcription factor to the promoter regions of AtATG8f and AtATG8h. Dual luciferase reporter assays in Arabidopsis mesophyll protoplasts also indicated that AtPHR1 could not transactivate the expression of both genes. Loss of AtATG8f and AtATG8h leads to decreased root microsomal-enriched ATG8 but increased ATG8 lipidation. Moreover, atg8f/atg8h mutants exhibit reduced autophagic flux estimated by the vacuolar degradation of ATG8 in the Pi-limited root but maintain normal cellular Pi homeostasis with reduced number of lateral roots. While the expression patterns of AtATG8f and AtATG8h overlap in the root stele, AtATG8f is more strongly expressed in the root apex and root hair and remarkably at sites where lateral root primordia develop. We hypothesize that Pi starvation-induction of AtATG8f and AtATG8h may not directly contribute to Pi recycling but rely on a second wave of transcriptional activation triggered by PHR1 that fine-tunes cell type-specific autophagic activity

Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results

In this paper we present the multilingual language model BLOOM-zh that features enhanced support for Traditional Chinese. BLOOM-zh has its origins in the open-source BLOOM models presented by BigScience in 2022. Starting from released models, we extended the pre-training of BLOOM by additional 7.4 billion tokens in Traditional Chinese and English covering a variety of domains such as news articles, books, encyclopedias, educational materials as well as spoken language. In order to show the properties of BLOOM-zh, both existing and newly created benchmark scenarios are used for evaluating the performance. BLOOM-zh outperforms its predecessor on most Traditional Chinese benchmarks while maintaining its English capability. We release all our models to the research community