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The increasing sales of electric vehicles (EVs) in the market poses critical questions for the public on how to deal with millions of retired batteries (RBs). A number of studies have shown that second-life batteries (SLBs) from EVs usually have a considerable remaining capacity and hence still have additional utilization value. This article proposes a novel fuzzy inference system (FIS)-based planning framework for EV charging stations with wind, PV power, battery energy storage system and the utilization of SLBs (EVCS-WPE-SLBs system). In this framework, a narrowed and the most probable candidate node set for EVCS-WPE-SLBs system which makes the trade-off of several off-site factors from different fields that jointly determine the optimal planning results is obtained, including the installation and utilization requirements of SLBs, the transportation network features and power system properties. Numerical case studies are conducted on a coupled IEEE 33-bus distribution system and 25-node transportation system. According to the simulation results, the reasonable utilization of SLBs in the EVCS-WPE-SLBs system can reduce the total system cost while maintaining the normal operation of the system. Besides, a narrowed and most probable candidate node set not only reduces the search space and simplifies the optimization problem, but the results obtained are more practical according to the actual system conditions in real life.

Two-dimensional (2D) perovskite solar cells (PSCs) have attracted rapid growing attention due to their excellent environmental and operational stability. As an important type of 2D perovskite, Dion–Jacobson (DJ) 2D perovskites exhibit better structural integrity and more stable optoelectronic properties than those of Ruddlesden–Popper (RP) ones because of the elimination of weak van der Waals interactions. Random phase distribution, phase impurity, and weak crystallinity, however, can lead to severe nonradiative recombination losses in 2D perovskites and inferior device stability. Herein, formamidinium chloride (FACl) and lead chloride (PbCl2) are selected as additives to fabricate efficient and stable DJ 2D PSCs. The synergistic effect of additives could efficiently induce crystallization and suppress the low-nphase perovskites. The obtained 2D perovskites exhibit extended charge lifetime and enhanced charge transfer. The corresponding PSC device delivers an efficiency of 16.63% with a significantly improved open-circuit voltage (VOC) of 1.18 V and a fill factor (FF) of 81.65% than the control one. This PCE ranks the highest for inverted FA-based 2D DJ PSCs. Moreover, this device has exhibited exceptional long-term stability, which retains more than 95% of the initial efficiencies at about 50% relative humidity for 600 h.

Electrocardiogram (ECG) interpretation is an integral part of the clinical ECG workflow; however, this process is often time‐consuming and labor‐intensive. We aim to develop a rapid, inexpensive means to detect abnormal ECGs using artificial intelligence (AI) from scanned ECG printouts. The study included 1172 12‐lead ECG scans performed in 1172 individuals from a community in Guangzhou, China; 878 (74.9%) were diagnosed with sinus rhythm, and the remaining 294 (25.1%) with abnormal rhythms. A deep learning model consisting of a convolutional neural network based on InceptionV3 and a fully connected layer followed by a GEV activation was trained to classify scanned tracings as either normal or abnormal. In a hold‐out testing set, the model achieved a area under curve (AUC), sensitivity, specificity, PPV, and NPV of 0.932 (95% confidence interval [CI]: 0.890, 0.976), 0.816 (95% CI: 0.657, 0.923), 0.993 (95% CI: 0.959, 1.0), 0.969 (95% CI: 0.838, 0.999), and 0.950 (95% CI: 0.90, 0.980) respectively, when using a probability threshold of 0.5. When compared with a physiological expert, these results show comparable performance with a statistically significant increase in specificity and a non‐significant decrease in sensitivity at the 95% level. We have developed a rapid, inexpensive, accurate means to detect abnormal ECGs using AI. Easy and accurate identification of such “abnormal” ECGs could allow the mass automated review of ECGs in community settings where abnormal ones could be flagged using AI for detailed clinical review by healthcare professionals. We developed a deep learning algorithm that uses scanned ECG printouts to predict normal or abnormal rhythm. In addition, the method can produce saliency maps, showing which areas are relevant in the diagnosis to aid interpretability. The method has applications in low resource settings such as screening, where electrophysiological experts may not be available.

An asymmetric synthesis of silicon-stereogenic monohydrosilanes by rhodium-catalyzed dehydrogenative C–H silylation is developed. The process is suitable for the synthesis of various asymmetrically trisubstituted 1H-benzosiloles and 1H-benzosilolometallocenes in good yields with excellent chemo-, regio-, and stereocontrol. These selected silicon-stereogenic 1H-benzosilole compounds exhibit bright blue fluorescence and CPL (circular polarized luminescence) signals, which could be attractive to practitioners of materials science.

AbstractHead-space solid-phase microextraction (HS-SPME) was adopted to gather volatile organic compounds emitted from the flower of Luculia gratissima(Wallich) Sweet. Gas chromatography combined with mass spectrometry (GC-MS) was employed for the analysis of the characteristics of the volatile component profile. The inflorescence of L. gratissimais a terminal umbel of tubular ended white or pink flowers with 5 spreading petals. A total of 20 compounds were identified, representing 99 % of the entire amount. The major components were γ-muurolene (46.3 %), 3-carene (23.5 %) and trans-isoeugenol (14.4 %), and they were found to make a principal contribution to the volatile compounds of this flower. It is suggested that L. gratissimawould be fully qualified as a delightfully fragrant houseplant.

Successful and minimally invasive extraction of a broken distal end of an intramedullary nail is challenging. This study introduces a simple and reproducible technique for the extraction of broken cannulated intramedullary nails using a novel minimally invasive broken nail extractor. Five amputated adult lower-leg specimens were used to create models of the broken distal end of the cannulated intramedullary nails remaining in the medullary cavity of the distal tibia. Two orthopedic resident physicians with experience in tibial intramedullary nail implantation were selected to blindly extract the broken intramedullary nail using the novel minimally invasive broken nail extractor. The extraction outcome was assessed. The broken nail extractor was applied to 3 patients with broken intramedullary nails remaining in the medullary cavity of the distal tibia. In the lower-leg specimens, the extraction success rate was 100%, the median number of extraction times was 1.9 (range 1–3.5), and the median duration of extraction was 38 s (range 20–52 s). All the broken intramedullary nails in the 3 patients were successfully extracted without complications related to the surgery. The study shows that our technique is simple, reproducible, and has a high extraction success rate, but more case applications are needed to verify its effect.

Secondary phosphine oxides (SPOs) are often difficult coupling partners for transition-metal-catalyzed C–H phosphorylation reactions. Herein, a series of SPO-RhIIIcomplexes relevant to RhIII-catalyzed C–H phosphorylation was isolated and fully characterized. Detailed research on their reactivities in C–H rhodation indicates the crucial role of a suitable base to reduce the deactivation of RhIIIby SPOs. Finally, using silver carbonate as both a base and an oxidant, an efficient RhIII-catalyzed aryl C–H phosphorylation with diarylphosphine oxides was developed.

Bovine tuberculosis (bTB) is caused by Mycobacterium bovis. During the early stage of infection, greater than 15% of M. bovis-infected cattle shed mycobacteria through nasal secretions, which can be detected by nested PCR.