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A prerequisite for the development or optimization of heterogeneous catalysts is a comprehensive understanding of the reaction mechanism and kinetics at the level as elementary as possible. In comparison with steady‐state catalytic tests typically used for this purpose, non‐steady‐state (transient) studies provide deeper insights due to higher time resolution. For several decades, temporal analysis of products (TAP) and steady‐state isotopic transient kinetic analysis (SSITKA) have been successfully applied to the analysis of various heterogeneous reactions. In this review, we highlight the contributions made by TAP and SSITKA studies between 2017 and 2023 to the understanding of reaction mechanisms and to the derivation of microkinetics. The versatility of these methods is illustrated by the examples of oxidative coupling of methane, CO/CO2 hydrogenation to hydrocarbons or methanol, metathesis of ethylene with 2‐butenes to propene, acrolein oxidation to acrylic acid, methanol conversion to olefins and non‐oxidative propane dehydrogenation to propene. We also provide our personal views on possible developments in this area. [ABSTRACT FROM AUTHOR]

Ultrabroadband and polarization‐sensitive imaging are essential for pioneering advancements in intelligent technology, offering a pivotal pathway to multidimensional information extraction. However, the dearth of appropriate photosensitive semiconductors in the infrared region and the lack of suitably efficient device architecture for the separation and collection of photocarriers significantly impede the development of ultra‐broadband and polarization‐sensitive photodetectors. To address these challenges, a sandwiched Ta2NiSe5/MoTe2/Graphene heterostructure device is engineered. In this device, efficient and polarization‐sensitive photocarriers are generated in the top Ta2NiSe5 layer, rapidly separated through the middle MoTe2 layer, and effectively collected by the bottom graphene layer. As a result, the developed photodetector exhibits an ultra‐broadband and polarization‐sensitive photoresponse that extends from visible light (520 nm) to short‐wave infrared (2200 nm). At 2200 nm, the device displays a notable responsivity of 5.79 A W−1, a specific detectivity of 1010 Jones, and an anisotropic ratio of 1.44. Furthermore, this device successfully demonstrates high‐resolution ultra‐broadband and polarized light imaging capabilities. This study thus presents an intriguing blueprint for the development of advanced 2D imaging platforms for future‐generation intelligent systems. [ABSTRACT FROM AUTHOR]

Die Metathese von Ethen mit 2‐Butenen zu Propen ist ein etablierter großtechnischer Prozess. Allerdings sind die Grundlagen der In situ‐Umwandlung von geträgerten WOx‐, MoOx‐ oder ReOx‐Spezies in katalytisch aktive Metallcarbene und deren intrinsische Aktivität sowie die Rolle metatheseinaktiver Cokatalysatoren noch ungeklärt, was sich nachteilig auf die Katalysatorentwicklung und Prozessoptimierung auswirkt. Die Studie liefert die erforderlichen Grundlagen basierend auf steady‐state isotopic transient kinetic analysis. Zum ersten Mal wurden die stationäre Konzentration, die Lebensdauer und die intrinsische Reaktivität von Metallcarbenen bestimmt. Die erhaltenen Ergebnisse können direkt für das Design und die Herstellung von Katalysatoren für die Metathese‐Reaktion und Cokatalysatoren verwendet werden, was die Möglichkeit zur Optimierung der Propenproduktivität eröffnet. [ABSTRACT FROM AUTHOR]

The metathesis of ethylene with 2‐butenes to propene is an established large‐scale process. However, the fundamentals behind in situ transformation of supported WOx, MoOx, or ReOx species into catalytically active metal‐carbenes and the intrinsic activity of the latter as well as the role of metathesis‐inactive cocatalysts are still unsolved. This is detrimental for catalyst development and process optimization. In this study, we provide the required essentials derived from steady‐state isotopic transient kinetic analysis. For the first time, the steady‐state concentration, the lifetime, and the intrinsic reactivity of metal carbenes were determined. The obtained results can be directly used for the design and the preparation of metathesis‐active catalysts and cocatalysts, thereby opening up possibilities for optimizing propene productivity. [ABSTRACT FROM AUTHOR]

Systematic reviews are vital instruments for researchers to understand broad trends in a field and synthesize evidence on the effectiveness of interventions in addressing specific issues. The quality of a systematic review depends critically on having comprehensively surveyed all relevant literature on the review topic. In addition to database searching, handsearching is an important supplementary technique that helps increase the likelihood of identifying all relevant studies in a literature search. Traditional handsearching requires reviewers to manually browse through a curated list of field‐specific journals and conference proceedings to find articles relevant to the review topic. This manual process is not only time‐consuming, laborious, costly, and error‐prone due to human fatigue, but it also lacks replicability due to its cumbersome manual nature. To address these issues, this paper presents a free and open‐source Python package and an accompanying web‐app, Paperfetcher, to automate the retrieval of article metadata for handsearching. With Paperfetcher's assistance, researchers can retrieve article metadata from designated journals within a specified time frame in just a few clicks. In addition to handsearching, it also incorporates a beta version of citation searching in both forward and backward directions. Paperfetcher has an easy‐to‐use interface, which allows researchers to download the metadata of retrieved studies as a list of DOIs or as an RIS file to facilitate seamless import into systematic review screening software. To the best of our knowledge, Paperfetcher is the first tool to automate handsearching with high usability and a multi‐disciplinary focus. [ABSTRACT FROM AUTHOR]

With an increasing number of international students enrolled in U.S. higher education, they were reported to have severe mental health issues, especially during the coronavirus disease (COVID‐19) pandemic. It is critical to provide evidence‐based mental health services to help them cope with those issues and promote mental health and the overall well‐being of international students. In this article, we utilized a randomized controlled trial to pilot‐test the effectiveness of a mindfulness‐based well‐being group for international students (MBWIS) in improving participants' overall well‐being and mental health. The results indicated that the MBWIS not only improves international students' trait mindfulness but also increases positive mental health as well as decreases their overall psychological distress and perceived discrimination. Related findings and implications for counselors and university personnel, including how to implement MBWIS in mental health facilities, are discussed within the existing literature. [ABSTRACT FROM AUTHOR]

Purpose: Clinically, single radiotracer positron emission tomography (PET) imaging is a commonly used examination method; however, since each radioactive tracer reflects the information of only one kind of cell, it easily causes false negatives or false positives in disease diagnosis. Therefore, reasonably combining two or more radiotracers is recommended to improve the accuracy of diagnosis and the sensitivity and specificity of the disease when conditions permit. Methods: This paper proposes incorporating 18F‐fluorodeoxyglucose (FDG) as a higher‐quality PET image to guide the reconstruction of other lower‐count 11C‐methionine (MET) PET datasets to compensate for the lower image quality by a popular kernel algorithm. Specifically, the FDG prior is needed to extract kernel features, and these features were used to build a kernel matrix using a k‐nearest‐neighbor (kNN) search for MET image reconstruction. We created a 2‐D brain phantom to validate the proposed method by simulating sinogram data containing Poisson random noise and quantitatively compared the performance of the proposed FDG‐guided kernelized expectation maximization (KEM) method with the performance of Gaussian and non‐local means (NLM) smoothed maximum likelihood expectation maximization (MLEM), MR‐guided KEM, and multi‐guided‐S KEM algorithms. Mismatch experiments between FDG/MR and MET data were also carried out to investigate the outcomes of possible clinical situations. Results: In the simulation study, the proposed method outperformed the other algorithms by at least 3.11% in the signal‐to‐noise ratio (SNR) and 0.68% in the contrast recovery coefficient (CRC), and it reduced the mean absolute error (MAE) by 8.07%. Regarding the tumor in the reconstructed image, the proposed method contained more pathological information. Furthermore, the proposed method was still superior to the MR‐guided KEM method in the mismatch experiments. Conclusions: The proposed FDG‐guided KEM algorithm can effectively utilize and compensate for the tissue metabolism information obtained from dual‐tracer PET to maximize the advantages of PET imaging. [ABSTRACT FROM AUTHOR]

Keywords: 2-Buten; Ethen; Metathese; Propen; SSITKA DE 2-Buten Ethen Metathese Propen SSITKA 1 1 1 09/27/23 20231002 NES 231002 B Heterogeneous Catalysis b . In their Communication (e202308872), Tatiana Otroshchenko, Evgenii V. Kondratenko et al. report performance descriptors for catalysts based on molybdenum, tungsten, or rhenium oxides for ethylene metathesis with 2-butenes to propene. [Extracted from the article]

Frontispiece: Performance Descriptors for Catalysts Based on Molybdenum, Tungsten, or Rhenium Oxides for Metathesis of Ethylene with 2-Butenes to Propene Keywords: 2-Butene; Ethylene; Metathesis; Propene; SSITKA EN 2-Butene Ethylene Metathesis Propene SSITKA 1 1 1 09/27/23 20231002 NES 231002 B Heterogeneous Catalysis b . In their Communication (e202308872), Tatiana Otroshchenko, Evgenii V. Kondratenko et al. report performance descriptors for catalysts based on molybdenum, tungsten, or rhenium oxides for ethylene metathesis with 2-butenes to propene. [Extracted from the article]

Purpose: In recent years, health risks concerning high‐dose x‐ray radiation have become a major concern in dental computed tomography (CT) examinations. Therefore, adopting low‐dose computed tomography (LDCT) technology has become a major focus in the CT imaging field. One of these LDCT technologies is downsampling data acquisition during low‐dose x‐ray imaging processes. However, reducing the radiation dose can adversely affect CT image quality by introducing noise and artifacts in the resultant image that can compromise diagnostic information. In this paper, we propose an artifact correction method for downsampling CT reconstruction based on deep learning. Method: We used clinical dental CT data with low‐dose artifacts reconstructed by conventional filtered back projection (FBP) as inputs to a deep neural network and corresponding high‐quality labeled normal‐dose CT data during training. We trained a generative adversarial network (GAN) with Wasserstein distance (WGAN) and mean squared error (MSE) loss, called m‐WGAN, to remove artifacts and obtain high‐quality CT dental images in a clinical dental CT examination environment. Results: The experimental results confirmed that the proposed algorithm effectively removes low‐dose artifacts from dental CT scans. In addition, we showed that the proposed method is efficient for removing noise from low‐dose CT scan images compared to existing approaches. We compared the performances of the general GAN, convolutional neural networks, and m‐WGAN. Through quantitative and qualitative analysis of the results, we concluded that the proposed m‐WGAN method resulted in better artifact correction performance preserving the texture in dental CT scanning. Conclusions: The image quality evaluation metrics indicated that the proposed method effectively improves image quality when used as a postprocessing technique for dental CT images. To the best of our knowledge, this work is the first deep learning architecture used with a commercial cone‐beam dental CT scanner. The artifact correction performance was rigorously evaluated and demonstrated to be effective. Therefore, we believe that the proposed algorithm represents a new direction in the research area of low‐dose dental CT artifact correction. [ABSTRACT FROM AUTHOR]