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At present, for business lightning positioning systems, the classification of lightning discharge types is mostly based on lightning pulse signal features, and there is still a lot of room for improvement. We propose a lightning discharge classification method based on convolutional encoding features. This method utilizes convolutional neural networks to extract encoding features, and uses random forests to classify the extracted encoding features, achieving high accuracy discrimination for various lightning discharge events. Compared with traditional multi-parameter-based methods, the new method proposed in this paper has the ability to identify multiple lightning discharge events and does not require precise detailed feature engineering to extract individual pulse parameters. The accuracy of this method for identifying lightning discharge types in intra-cloud flash (IC), cloud-to-ground flash (CG), and narrow bipolar events (NBEs) is 97%, which is higher than that of multi-parameter methods. Moreover, our method can complete the classification task of lightning signals at a faster speed. Under the same conditions, the new method only requires 28.2 µs to identify one pulse, while deep learning-based methods require 300 µs. This method has faster recognition speed and higher accuracy in identifying multiple discharge types, which can better meet the needs of real-time business positioning. [ABSTRACT FROM AUTHOR]

The electrochemical reduction of NO2− to NH3 provides a promising approach for both the treatment of harmful NO2− and the sustainable production of NH3. In this study, a low-coordinated Pd metallene (L-Pd) was first explored as an efficient NO2RR electrocatalyst, showing an exceptional FENH3 value of 95.2% and a high NH3 yield rate of 511.5 μmol h−1 cm−2. A combination of experimental and computational studies revealed that the significantly enhanced NO2RR performance of L-Pd originates from the low-coordinated Pd sites for boosting NO2− activation and decreasing the energy barrier of the *NO → *NHO rate-determining step while suppressing the competing hydrogen evolution. [ABSTRACT FROM AUTHOR]

Coriander (Coriandrum sativum L.) is prized for its aroma and medicinal properties and is extensively employed in various cuisines. Light intensity and photoperiod greatly impact its phenological development. The application of light-emitting diodes (LEDs) in facility cultivation systems enables precise control of lighting conditions, leading to enhanced energy efficiency in coriander cultivation. This study investigated three levels of light intensity (133, 200, and 400 μmol·m−2·s−1) and three photoperiods (8L/16D, 16L/8D, and 24L) to comprehensively assess their effects on coriander's morphological development, photosynthetic characteristics, and energy utilization efficiency. The objective was to identify a combination conducive to efficient and energy-saving coriander cultivation in PFALs. Results indicated that high light intensity (400 μmol·m−2·s−1) with continuous lighting (24L) reduces coriander's photosynthetic capacity, while 24-h of continuous lighting can boost yield at the expense of energy efficiency. An 8-h photoperiod significantly decreases the yield compared to 16 h. Low light intensity inhibits plant development, indicating that 133 μmol·m−2·s−1 is suboptimal. For optimal efficiency and yield, a light intensity of 200 μmol·m−2·s−1 and a 16-h photoperiod are recommended in coriander PFAL cultivation. These findings advocate for the adoption of these specific conditions for the indoor cultivation of coriander within PFAL systems. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Cancer survivors are less likely than comparably aged individuals without a cancer history to develop Alzheimer's disease and related dementias (ADRD). METHODS: In the UK Biobank, we investigated associations between cancer history and five structural magnetic resonance imaging (MRI) markers for ADRD risk, using linear mixed‐effects models to assess differences in mean values and quantile regression to examine whether associations varied across the distribution of MRI markers. RESULTS: Cancer history was associated with smaller mean hippocampal volume (b = ‐19 mm3, 95% CI = ‐36, ‐1) and lower mean cortical thickness in the Alzheimer's disease signature region (b = ‐0.004 mm, 95% CI = ‐0.007, ‐0.000). Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. DISCUSSION: Some brain MRI markers associated with ADRD risk were elevated in adults with a history of cancer. The magnitude of the adverse associations varied across quantiles of neuroimaging markers, and the pattern suggests possible harmful associations for individuals already at high ADRD risk. Highlights: We found no evidence of an inverse association between cancer history and ADRD‐related neurodegeneration.Cancer history was associated with smaller mean hippocampal volume and lower mean cortical thickness in the Alzheimer's disease signature region.Quantile regressions indicated individuals most vulnerable to ADRD were more affected by cancer history. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The results of the CLARITY‐AD, GRADUATE I and II, and TRAILBLAZER‐ALZ 2 trials have rekindled discussion on the impact of amyloid‐targeting drugs. We use a Bayesian approach to quantify how rational observers would have updated their prior beliefs based on new trial results. METHODS: We used publicly available data from the CLARITY‐AD, GRADUATE I and II, and TRAILBLAZER‐ALZ 2 trials to estimate the effect of reducing amyloid on the clinical dementia rating scale, sum of boxes (CDR‐SB) score. A range of prior positions were then updated according to Bayes' theorem using these estimates. RESULTS: After updating with new trial data, a wide range of starting positions resulted in credible intervals that did not include no effect of amyloid reduction on CDR‐SB score. DISCUSSION: For a range of starting beliefs and assuming the veracity of the underlying data, rational observers would conclude there is a small benefit of amyloid reductions on cognition. This benefit must be weighed against opportunity cost and side‐effect risk. Highlights: The results of recent trials of amyloid‐targeting drugs have rekindled discussion on the impact of amyloid reductions achieved with amyloid‐targeting drugs on cognition.Prior to the announcement of trial results, beliefs about the effects of altering amyloid levels varied.For a range of starting beliefs, one would conclude there is a small benefit of amyloid reductions due to amyloid‐targeting drugs on cognition.The perceived value of individual drugs must balance the magnitude of this benefit against opportunity cost and risk of side effects. [ABSTRACT FROM AUTHOR]

Electrocatalytic NO2− reduction to NH3 (NO2RR) is an appealing approach for mitigating NO2− pollution and for the synthesis of valuable NH3, and so the exploration for high-performance NO2RR catalysts is pivotal yet remains challenging. Herein, amorphous MoO3 nanosheets (am-MoO3) were designed as a high-performance NO2RR electrocatalyst, delivering a maximum NO2−-to-NH3 faradaic efficiency of 94.8% and NH3 yield rate of 480.4 μmol h−1 cm−2 at −0.6 V vs. RHE. Theoretical computations revealed that the largely enhanced NO2RR activity of am-MoO3 originated from the amorphization-induced O-vacancies, which could enhance the NO2−-to-NH3 reaction energetics and hamper the competitive hydrogen evolution. [ABSTRACT FROM AUTHOR]

BACKGROUND Infertility and pregnancy loss are longstanding problems. Successful fertilization and high-quality embryos are prerequisites for an ongoing pregnancy. Studies have proven that every stage in the human reproductive process is regulated by multiple genes and any problem, at any step, may lead to fertilization failure (FF) or early embryonic arrest (EEA). Doctors can diagnose the pathogenic factors involved in FF and EEA by using genetic methods. With the progress in the development of new genetic technologies, such as single-cell RNA analysis and whole-exome sequencing, a new approach has opened up for us to directly study human germ cells and reproductive development. These findings will help us to identify the unique mechanism(s) that leads to FF and EEA in order to find potential treatments. OBJECTIVE AND RATIONALE The goal of this review is to compile current genetic knowledge related to FF and EEA, clarifying the mechanisms involved and providing clues for clinical diagnosis and treatment. SEARCH METHODS PubMed was used to search for relevant research articles and reviews, primarily focusing on English-language publications from January 1978 to June 2023. The search terms included fertilization failure, early embryonic arrest, genetic, epigenetic, whole-exome sequencing, DNA methylation, chromosome, non-coding RNA, and other related keywords. Additional studies were identified by searching reference lists. This review primarily focuses on research conducted in humans. However, it also incorporates relevant data from animal models when applicable. The results were presented descriptively, and individual study quality was not assessed. OUTCOMES A total of 233 relevant articles were included in the final review, from 3925 records identified initially. The review provides an overview of genetic factors and mechanisms involved in the human reproductive process. The genetic mutations and other genetic mechanisms of FF and EEA were systematically reviewed, for example, globozoospermia, oocyte activation failure, maternal effect gene mutations, zygotic genome activation abnormalities, chromosome abnormalities, and epigenetic abnormalities. Additionally, the review summarizes progress in treatments for different gene defects, offering new insights for clinical diagnosis and treatment. WIDER IMPLICATIONS The information provided in this review will facilitate the development of more accurate molecular screening tools for diagnosing infertility using genetic markers and networks in human reproductive development. The findings will also help guide clinical practice by identifying appropriate interventions based on specific gene mutations. For example, when an individual has obvious gene mutations related to FF, ICSI is recommended instead of IVF. However, in the case of genetic defects such as phospholipase C zeta1 (PLCZ1) , actin-like7A (ACTL7A) , actin-like 9 (ACTL9) , and IQ motif-containing N (IQCN) , ICSI may also fail to fertilize. We can consider artificial oocyte activation technology with ICSI to improve fertilization rate and reduce monetary and time costs. In the future, fertility is expected to be improved or restored by interfering with or supplementing the relevant genes. [ABSTRACT FROM AUTHOR]