bluuebunny/crossref_metadata_2025 huggingface dataset:
Reduction in the activity of VTA/SNc dopaminergic neurons underlies aging-related decline in novelty seeking
Authors: Shan Qiang , Tian Ye , Chen Hang , Lin Xiaoli , Tian Yao
Published: December 2023

Curiosity, or novelty seeking, is a fundamental mechanism motivating animals to explore and exploit environments to improve survival, and is also positively associated with cognitive, intrapersonal and interpersonal well-being in humans. However, curiosity declines as humans age, and the decline even positively predicts the extent of cognitive decline in Alzheimer’s disease patients. Therefore, determining the underlying mechanism, which is currently unknown, is an urgent task for the present aging society that is growing at an unprecedented rate. This study finds that seeking behaviors for both social and inanimate novelties are compromised in aged mice, suggesting that the aging-related decline in curiosity and novelty-seeking is a biological process. This study further identifies an aging-related reduction in the activity (manifesting as a reduction in spontaneous firing) of dopaminergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). Finally, this study establishes that this reduction in activity causally underlies the aging-related decline in novelty-seeking behaviors. This study potentially provides an interventional strategy for maintaining high curiosity in the aged population, i.e., compensating for the reduced activity of VTA/SNc dopaminergic neurons, enabling the aged population to cope more smoothly with the present growing aging society, physically, cognitively and socioeconomically.
Novel WYL domain-containing transcriptional activator acts in response to genotoxic stress in rapidly growing mycobacteria
Authors: Keller Lena Maria Leone , Flattich Kim , Weber-Ban Eilika
Published: December 2023

The WYL domain is a nucleotide-sensing module that controls the activity of transcription factors involved in the regulation of DNA damage response and phage defense mechanisms in bacteria. In this study, we investigated a WYL domain-containing transcription factor in Mycobacterium smegmatis that we termed stress-involved WYL domain-containing regulator (SiwR). We found that SiwR controls adjacent genes that belong to the DinB/YfiT-like putative metalloenzymes superfamily by upregulating their expression in response to various genotoxic stress conditions, including upon exposure to H2O2 or the natural antibiotic zeocin. We show that SiwR binds different forms of single-stranded DNA (ssDNA) with high affinity, primarily through its characteristic WYL domain. In combination with complementation studies of a M. smegmatis siwR deletion strain, our findings support a role of the WYL domains as signal-sensing activity switches of WYL domain-containing transcription factors (WYL TFs). Our study provides evidence that WYL TFs are involved in the adaptation of bacteria to changing environments and encountered stress conditions.
A genome assembly for Orinus kokonorica provides insights into the origin, adaptive evolution and further diversification of two closely related grass genera
Authors: Qu Kunjing , Liu Ai , Yin Mou , Mu Wenjie , Wu Shuang , Hu Hongyin , Chen Jinyuan , Su Xu , Dou Quanwen , Ren Guangpeng
Published: December 2023

Ancient whole-genome duplication (WGD) or polyploidization is prevalent in plants and has played a crucial role in plant adaptation. However, the underlying genomic basis of ecological adaptation and subsequent diversification after WGD are still poorly understood in most plants. Here, we report a chromosome-scale genome assembly for the genus Orinus (Orinus kokonorica as representative) and preform comparative genomics with its closely related genus Cleistogenes (Cleistogenes songorica as representative), both belonging to a newly named subtribe Orininae of the grass subfamily Chloridoideae. The two genera may share one paleo-allotetraploidy event before 10 million years ago, and the two subgenomes of O. kokonorica display neither fractionation bias nor global homoeolog expression dominance. We find substantial genome rearrangements and extensive structural variations (SVs) between the two species. With comparative transcriptomics, we demonstrate that functional innovations of orthologous genes may have played an important role in promoting adaptive evolution and diversification of the two genera after polyploidization. In addition, copy number variations and extensive SVs between orthologs of flower and rhizome related genes may contribute to the morphological differences between the two genera. Our results provide new insights into the adaptive evolution and subsequent diversification of the two genera after polyploidization.
Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry
Authors: Sánchez-Pastor Pilar , Wu Sin-Mei , Hokstad Ketil , Kristjánsson Bjarni , Drouin Vincent , Ducrocq Cécile , Gunnarsson Gunnar , Rinaldi Antonio , Wiemer Stefan , Obermann Anne
Published: December 2023

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.
Tuning interfaces between Cu and oxide via atomic layer deposition method for CO2 hydrogenation to methanol
Authors: Jiang Kun , Zhao Huibo , Chen Yang , Li Baozhen , Zhang Zhang , Cao Fenghai , Wu Lizhi , Tang Yu , Li Tiesen , Tan Li
Published: December 2023

The specific Cu/10c-ZnO/CeO2 catalyst was designed using the atomic layer deposition method and the Cu+–Zn0–Ce4+ structure is the active site for methanol synthesis from CO2 hydrogenation.
3D simulation of conductive nanofilaments in multilayer h-BN memristors via a circuit breaker approach
Authors: Maldonado D. , Cantudo A. , Gómez-Campos F. M. , Yuan Yue , Shen Yaqing , Zheng Wenwen , Lanza M. , Roldán J. B.
Published: December 2023

A 3D simulation of conductive nanofilaments (CNFs) in multilayer hexagonal-BN memristors is performed.
Three-in-one synergistic therapy for tooth whitening and biofilm eradication using Cu-doped Bi2WO6
Authors: Liu Shujuan , Chen Ruoxuan , Wang Yunsong , Zhang Wangyang , Zhang Zijian , Hou Yanfeng , He Liangcan , Tian Feng , Liu Shaoqin
Published: December 2023

Biofilm-associated dental diseases and tooth discoloration have posed a great threat to public oral health in recent years.
Endogenous metal-ion dynamic nuclear polarization for NMR signal enhancement in metal organic frameworks
Authors: Moroz Ilia B. , Feldman Yishay , Carmieli Raanan , Liu Xinyu , Leskes Michal
Published: December 2023

Dynamic nuclear polarization from endogenous metal ions is an efficient route to increase the sensitivity of solid-state NMR for probing host-guest interactions for rational design of metal organic frameworks (MOFs).
Primary activation ofpara-quinone methides by chiral phosphoric acid for enantioselective construction of tetraarylmethanes
Authors: Han Zhengyu , Zhu Biao , Zang Yu , Zhang Chaoshen , Dong Xiu-Qin , Huang Hai , Sun Jianwei
Published: December 2023

Demonstrated here is an asymmetric nucleophilic additionviaprimary activation ofpara-quinone methides (p-QMs) based on a chiral phosphoric acid catalytic system.
Host–guest complexes of perylene bisimide-based metallacage and fullerenes for efficient photoinduced charge separation
Authors: Stasyuk O. A. , Solà M. , Stasyuk A. J.
Published: December 2023

Fast photoinduced charge separation was predicted in non-covalent complexes of Pt6PBI3 metallacage and endohedral metallofullenes.
Efficiency boost in non-doped blue organic light-emitting diodes: Harnessing aggregation-induced emission – a comprehensive review
Authors: Rana Snigdhamayee , Nayak Sandhya Rani , Patel Sabita , Vaidyanathan Sivakumar
Published: December 2023

Revolutionizing OLEDs: AIE-driven efficiency boost in non-doped blue OLEDs showcased in this review. Novel strategies, experimental insights, and promising future prospects unveiled, propelling OLED technology forward.
MBMF: Constructing memory banks of multi‐scale features for anomaly detection
Authors: Sun Yanfeng , Wang Haitao , Hu Yongli , Jiang Huajie , Yin Baocai
Published: December 2023

In industrial manufacturing, how to accurately classify defective products and locate the location of defects has always been a concern. Previous studies mainly measured similarity based on extracting single‐scale features of samples. However, only using the features of a single scale is hard to represent different sizes and types of anomalies. Therefore, the authors propose a set of memory banks of multi‐scale features (MBMF) to enrich feature representation and detect and locate various anomalies. To extract features of different scales, different aggregation functions are designed to produce the feature maps at different granularity. Based on the multi‐scale features of normal samples, the MBMF are constructed. Meanwhile, to better adapt to the feature distribution of the training samples, the authors proposed a new iterative updating method for the memory banks. Testing on the widely used and challenging dataset of MVTec AD, the proposed MBMF achieves competitive image‐level anomaly detection performance (Image‐level Area Under the Receiver Operator Curve (AUROC)) and pixel‐level anomaly segmentation performance (Pixel‐level AUROC). To further evaluate the generalisation of the proposed method, we also implement anomaly detection on the BeanTech AD dataset, a commonly used dataset in the field of anomaly detection, and the Fashion‐MNIST dataset, a widely used dataset in the field of image classification. The experimental results also verify the effectiveness of the proposed method.
Economic evaluation of battery energy storage system on the generation side for frequency and peak regulation considering the benefits of unit loss reduction
Authors: Liu Gengming , Liu Wenxia , Shi Qingxin
Published: December 2023

The indirect benefits of battery energy storage system (BESS) on the generation side participating in auxiliary service are hardly quantified in prior works. Nevertheless, the configuration of BESS could be affected by its indirect benefits. In this paper, the authors purpose a quantitative economic evaluation method of BESS considering the indirect benefits from the reduction in unit loss and the delay in investment. First, the authors complete further the cost model of BESS for frequency and peak regulation based on the whole life cycle theory. Second, the authors quantify the indirect benefits of BESS in thermal power plants based on the theory of rotor fatigue life loss and establish a benefits model that considers the unit loss reduction during frequency regulation and the delay in investment during peak regulation. Finally, the authors propose a set of indexes for economic evaluation of the thermal power plant with BESS. The simulation results show that the total benefits of BESS can be improved effectively by considering the indirect benefits from unit loss reduction and the delay in investment, proving the effectiveness of the proposed approach which can be meaningful for the future investment in BESS on the generation side.
First‐in‐human real‐time AI‐assisted instrument deocclusion during augmented reality robotic surgery
Authors: Hofman Jasper , De Backer Pieter , Manghi Ilaria , Simoens Jente , De Groote Ruben , Van Den Bossche Hannes , D'Hondt Mathieu , Oosterlinck Tim , Lippens Julie , Van Praet Charles , Ferraguti Federica , Debbaut Charlotte , Li Zhijin , Kutter Oliver , Mottrie Alexandre , Decaestecker Karel
Published: December 2023

The integration of Augmented Reality (AR) into daily surgical practice is withheld by the correct registration of pre‐operative data. This includes intelligent 3D model superposition whilst simultaneously handling real and virtual occlusions caused by the AR overlay. Occlusions can negatively impact surgical safety and as such deteriorate rather than improve surgical care. Robotic surgery is particularly suited to tackle these integration challenges in a stepwise approach as the robotic console allows for different inputs to be displayed in parallel to the surgeon. Nevertheless, real‐time de‐occlusion requires extensive computational resources which further complicates clinical integration. This work tackles the problem of instrument occlusion and presents, to the authors’ best knowledge, the first‐in‐human on edge deployment of a real‐time binary segmentation pipeline during three robot‐assisted surgeries: partial nephrectomy, migrated endovascular stent removal, and liver metastasectomy. To this end, a state‐of‐the‐art real‐time segmentation and 3D model pipeline was implemented and presented to the surgeon during live surgery. The pipeline allows real‐time binary segmentation of 37 non‐organic surgical items, which are never occluded during AR. The application features real‐time manual 3D model manipulation for correct soft tissue alignment. The proposed pipeline can contribute towards surgical safety, ergonomics, and acceptance of AR in minimally invasive surgery.
An image inpainting method based on generative adversarial networks inversion and autoencoder
Authors: Wang Yechen , Song Bin , Zhang Zhiyong
Published: December 2023

Image inpainting aims to repair the damaged region according to the known content in the damaged image. Recently, image inpainting methods have poor effects on high‐resolution damaged images, and the research on the inpainting of large‐area damaged images is limited. Therefore, this paper proposes an image inpainting method based on Generative Adversarial Networks (GAN) inversion and autoencoder. This work consists of two phases: first, the authors design an autoencoder‐based GAN, which learns the mapping from noise to low‐dimensional feature maps by training a generator, and then converts the generated feature maps into high‐resolution images. Thus, the difficulty of learning the mapping relationship is reduced. Second, the authors adopt the learning‐based GAN inversion to infer the closest latent code. The trained GAN is then used to reconstruct the complete image. Finally, the authors compare their method with other classical methods on the CelebAMask‐HQ, Flickr‐Faces‐HQ, and ImageNet datasets. According to the quantitative comparison, when the mask range is large, in other words, when the image has a large area of damage, the authors’ method is superior to the comparison methods. According to the qualitative comparison, the structure of the high‐resolution image inpainted by the authors’ method is more reasonable and the texture details are more realistic.
Kongressnachlese
Authors: Wolf Katrin
Published: December 2023

Ganz nach dem Kongressmotto „Perspektivenwechsel in der Allergologie“ blickten beim 18. Deutschen Allergiekongress (DAK) im September 2023 in Bonn die Teilnehmer weit über den Tellerrand und diskutierten wissenschaftliche Forschung und Erfahrungen in der Anwendung.
Hormontherapie fordert Feinstarbeit
Authors: Fessler Beate
Published: December 2023

Der Umgang mit Hormonen will gelernt sein, insbesondere wenn sie in der Pädiatrie eingesetzt werden. Schon eine minimale Veränderung an der Stellschraube kann folgenschwer sein, zu Gunsten oder zu Ungunsten der Patienten. Dies zeigte sich auch bei den intensiven Diskussionen auf der 61. Jahrestagung der Europäischen Gesellschaft für Pädiatrische Endokrinologie (ESPE) im September in Den Haag.
Kein Sex ist auch keine Lösung
Authors: Dathan-Stumpf Anne , Stark Sylvia
Published: December 2023

Die Verhütungsberatung von Jugendlichen stellt für Kinder- und Frauenärzte eine besondere Herausforderung dar. Entscheidend für die Zufriedenheit und letztlich auch zuverlässige Anwendung sind die selbstbestimmte Wahl des Kontrazeptivums nach einer bedürfnisorientierten Beratung, bei der auf die Ängste und Sorgen der Mädchen eingegangen wird. Aufgrund der Vielzahl der heute zur Verfügung stehenden Verhütungsmethoden, sollten die Vor- und Nachteile gründlich diskutiert werden. Zu den Kontrazeptiva der ersten Wahl in der Adoleszenz zählen die kombinierten oralen Kontrazeptiva in Form der Pille oder des Vaginalringes, bei Kontraindikation für eine Östrogengabe die Gestagenpille. Als weitere Optionen gelten intrauterine Kontrazeptiva (hormonhaltig, hormonfrei) und das Verhütungsstäbchen. Außerdem müssen Jugendliche explizit auf die additive Verwendung eines Kondoms in Hinblick auf die Vermeidung sexuell übertragbarer Erkrankungen hingewiesen werden.
A Review of Inline Infrared and Nuclear Magnetic Resonance Applications in Flow Chemistry
Authors: Zhang Yan , Su Wei-Ke
Published: December 2023

As a safe and efficient synthesis technique, flow chemistry has recently gained attention in the pharmaceutical, materials, and environmental protection industries. However, researchers always face challenges in handling samples and selecting sufficiently flexible analytical techniques. Generally, real-time process analysis is crucial for monitoring reactions. The combination of flow chemistry with real-time process analysis can be beneficial for studying reaction kinetics and thermodynamics, monitoring, and control of the chemical synthesis processes, reaction optimization of macro and microreactors, and qualitative and quantitative analyses of compounds. Thus far, studies investigating the combination of flow chemistry with inline monitoring have included ultraviolet–infrared spectroscopy, Raman spectroscopy, gas chromatography, mass spectrometry, liquid chromatography, nuclear magnetic resonance (NMR) spectroscopy, and other automated conventional or unconventional methods. This review sheds light on applying inline infrared and inline NMR spectroscopies in flow chemistry.
Quality by Design Approach for Development and Characterization of Granisetron Hydrochloride-Loaded Orodispersible Films
Authors: Li Ming-Yan , Wang Bing , Zhang Jun-Qi , Yang Liu-Liu , He Jun-Tao , Chen Fang
Published: December 2023

Granisetron hydrochloride can be used to prevent and treat nausea and vomiting induced by chemotherapy. Its prolonged half-life and reduced dose requirement improve patient acceptance. However, patients undergoing chemotherapy often suffer from dysphagia and drug spitting due to emesis. Hence, the development of a patient-centered formulation of granisetron hydrochloride with simple medication and high compliance is crucial. The current study employed a polymer combination of polyvinylpyrrolidone/polyvinyl alcohol (PVP/PVA) as film-forming materials and Lycoat® RS 780 as a disintegrant to formulate orodispersible films (ODFs) loaded with granisetron hydrochloride. Guided by the concept of quality by design, the quality target product profile and critical quality attributes (CQAs) for the ODF were defined. Through the quality risk assessment, essential factors that have a significant impact on CQAs were identified. The formulation was screened using the Box–Behnken statistical design with three factors and three levels. Our data suggested that all ODF formulations exhibited a disintegration time of less than 60 seconds and complete dissolution within 5 minutes. Furthermore, the formulation displayed appropriate mechanical properties, water residue, and pH values. Thus, the granisetron hydrochloride-loaded ODF is regarded as a patient-friendly formulation that enhances compliance and consequently aids in therapeutic effectiveness.
Diet and Exercise in the Management of Polycystic Ovary Syndrome: Practical Considerations for Person-Centered Care
Authors: Colombo Giorgia E. , Pirotta Stephanie , Sabag Angelo
Published: December 2023

Polycystic ovary syndrome (PCOS) is a complex multisystem condition associated with life-long reproductive, metabolic, and psychological symptoms. Individuals with PCOS are at an increased risk of cardiovascular disease and type 2 diabetes, with approximately 70% of all PCOS cases presenting with insulin resistance. Lifestyle interventions have historically been recommended as first-line therapies for the management of PCOS-related cardiometabolic disorders. The term “lifestyle management” incorporates a multifaceted approach to dietary, exercise, and behavioral strategies, aiming to promote a healthy lifestyle. This approach has been commonly employed in practice, in particular through exercise and dietary modulation, due to its effect on cardiometabolic outcomes as well as its tolerability. Furthermore, there is evidence to suggest that combining dietary change with exercise may yield the greatest improvements in clinical outcomes. However, such practices require careful consideration and coordination, as there are instances where certain exercise and/or dietary prescriptions may compromise the effectiveness of the respective interventions. Thus, this review aims to provide practical guidance on diet and exercise planning in the routine care of PCOS. Such recommendations include emphasizing realistic and achievable goals, as well as minimizing barriers to lifestyle changes in order to increase the long-term sustainability of this treatment strategy.
Agri-food crises and news framing of media: an application to the Spanish greenhouse sector
Authors: Pérez-Mesa Juan Carlos , García Barranco Mª Carmen , Serrano Arcos Mª Mar , Sánchez Fernández Raquel
Published: December 2023

The contemporary media narratives frequently exhibit significant contradictions due to the influence of diverse interests. In this context, the framing of information assumes critical importance in shaping consumer opinions, necessitating a comprehensive examination of its management. This article investigates the portrayal of crises in the agri-food sector within the mass media when not anchored in objective and verifiable facts, thereby exerting a consequential impact on the sector’s reputation and public image. Specifically, a detailed analysis is conducted on the greenhouse horticulture sector in southeast Spain, recognized as the primary European supplier. Examination of these news items uncovers a discernible bias in the disseminated information, resulting in an information asymmetry between farmers and consumers. As a remedy for the affected sector, the current study advocates the implementation of a proactive crisis detection and management model grounded in the development and dissemination of verifiable information.
Fighting wildfires: predicting initial attack success across Victoria, Australia
Authors: Plucinski M. P. , Dunstall S. , McCarthy N. F. , Deutsch S. , Tartaglia E. , Huston C. , Stephenson A. G.
Published: December 2023

Background The small portion of fires that escape initial attack (IA) have the greatest impacts on communities and incur most suppression costs. Early identification of fires with potential for escaping IA can prompt fire managers to order additional suppression resources, issue timely public warnings and plan longer-term containment strategies when they have the greatest potential for reducing a fire’s impact. Aims To develop IA models from a state-wide incident dataset containing novel variables that can be used to estimate the probability of IA when a new fire has been reported. Methods A large dataset was compiled from bushfire incident records, geographical data and weather observations across the state of Victoria (n = 35 154) and was used to develop logistic regression models predicting the probability of initial attack success in grassland-, forest- and shrubland-dominated vegetation types. Key results Models including input variables describing weather conditions, travel delay, slope and distance from roads were able to reasonably discriminate fires contained to 5 ha. Conclusions and implications The models can be used to estimate IA success – using information available when the location of a new fire can be estimated – and they can be used to prompt planning for larger fires.
A note on null distance and causality encoding
*
Authors: Galloway Gregory J
Published: December 2023

Under natural conditions, the null distance introduced by Sormani and Vega (2016 Class. Quantum Grav.
33 085001) is a metric space distance function on spacetime, which, in a certain precise sense, can encode the causality of spacetime. The null distance function requires the choice of a time function. The purpose of this note is to observe that the causality assumptions related to such a choice in results used to establish global encoding of causality, due to Sakovich and Sormani (2023 J. Math. Phys.
64 012502) and to Burtscher and García-Heveling (2022 arXiv:2209.15610 [math.DG]), can be weakened.
3D tomographic phase retrieval and unwrapping
Authors: Fannjiang Albert
Published: December 2023

This paper develops uniqueness theory for 3D phase retrieval with finite, discrete measurement data for strong phase objects and weak phase objects, including: (i) Unique determination of (phase) projections from diffraction patterns—General measurement schemes with coded and uncoded apertures are proposed and shown to ensure unique reduction of diffraction patterns to the phase projection for a strong phase object (respectively, the projection for a weak phase object) in each direction separately without the knowledge of relative orientations and locations. (ii) Uniqueness for 3D phase unwrapping—General conditions for unique determination of a 3D strong phase object from its phase projection data are established, including, but not limited to, random tilt schemes densely sampled from a spherical triangle of vertexes in three orthogonal directions and other deterministic tilt schemes. (iii) Uniqueness for projection tomography—Unique determination of an object of n
3 voxels from generic n projections or n + 1 coded diffraction patterns is proved. This approach of reducing 3D phase retrieval to the problem of (phase) projection tomography has the practical implication of enabling classification and alignment, when relative orientations are unknown, to be carried out in terms of (phase) projections, instead of diffraction patterns. The applications with the measurement schemes such as single-axis tilt, conical tilt, dual-axis tilt, random conical tilt and general random tilt are discussed.
Flexible SnO2–MoS2 based memristive device exhibiting stable and enhanced memory phenomenon
Authors: Komal Km , Singh Mukhtiyar , Singh Bharti
Published: December 2023

Flexible non-volatile memory devices have been gaining interest in expanding the digital data storage world. Due to the burgeoning advancement in the healthcare industry, the Internet of Things, and wearable electronics, the demand for ultra-thin, low-power, and flexible memory is increasing. Further, the advancement of synthesis procedures for two-dimensional nanomaterials having better optical, electrical, and mechanical strength with flexibility has fuelled the flexible memory device area, as commonly used flash memory is approaching its physical limit. In this context, the present work reports the flexible resistive switching memory device based on pure molybdenum disulfide (MoS2) and tin oxide (SnO2) based nanocomposite powder synthesized using the simple hydrothermal process. The nanocomposite formation was characterized using x-ray diffraction and Raman spectroscopic techniques. The memory device was fabricated by spin-coating the pure MoS2, pure SnO2, and MoS2–SnO2 nanocomposite film over the ITO-PET flexible substrate. The device was completed by thermally evaporating the thin Al layer through a shadow mask. It was found that MoS2–SnO2 based memory devices exhibited improved switching performance having a higher I
ON/I
OFF ratio, and lower switching voltage in comparison to pure MoS2 and pure SnO2-based devices (I
ON/I
OFF ratio ∼100, V = 0.5 V). Furthermore, to check the stability and cyclic performance of the fabricated device, the retention and endurance test was also performed, and the MoS2–SnO2 device retained the HRS and LRS states up to 2 × 103s and showed stable performance up to 100 switching cycles without much degradation, respectively. It should be mentioned that the presently proposed ReRAM device based on SnO2 and MoS2 with flexible and low-power features had excellent potential for use in the wearable device industry.
Thermal monitoring and deep learning approach for early warning prediction of rock burst in underground structures
Authors: Jaiswal Mrityunjay , Sebastian Resmi , Mulaveesala Ravibabu
Published: December 2023

The occurrence of rockburst has the potential to result in significant economic and human losses in underground mining and excavation operations. The accuracy of traditional methods for early prediction is considerably affected by factors such as site conditions, noise levels, accessibility, and other variables. This study proposes a methodology for identifying the most defected region in a hard rock sample by integrating motion thermogram data obtained from the laboratory monitoring of rock burst phenomena with a cutting-edge deep neural network approach based on a regional convolutional network (i.e. Mask RCNN). The efficacy of the suggested approach was evaluated by determining the F1 score and average precision matrices based on a specific intersection over union value. The findings demonstrate that the proposed approach possesses satisfactory precision with respect to detection, localization, and segmentation, thereby establishing its potential utility as an autonomous predictor of rock bursts.
Compact simply-connected SOI spot size converters for TE and TM polarizations
Authors: Yang Shanglin , Fu Xin , Niu Jiaqi , Yang Lin
Published: December 2023

Spot size converters (SSCs) are pivotal building blocks of silicon on insulator (SOI) on-chip optical systems, which enable efficient coupling of modes between waveguides of different widths. In this paper, we propose two SSCs for TE and TM polarizations based on level-set and adjoint methods, which can convert modes between 0.5 µm and 10 µm wide waveguides. The devices’ lengths are 22.4 µm and 23.7 µm, respectively, with simply-connected structures and the 200 nm minimum feature size. The simulation results demonstrate minimal insertion losses of 0.04 dB and 0.12 dB for the two SSCs, with respective 1 dB bandwidths exceeding 170 nm and 250 nm. Within the wavelength range of 1520–1590 nm, the insertion losses are below 0.42 dB and 0.24 dB. Experimental results, normalized with a referenced 250 µm length adiabatic linear taper, indicates insertion losses of less than

0.26
±
0.35

 dB and

0.43
±
0.18

 dB within the 1520–1590 nm wavelength range for the proposed SSCs, demonstrating a ten-fold reduction in length while maintaining comparable performance to the reference taper. Our devices hold the potential to facilitate the utilization of grating couplers in high-efficiency and high integration applications.
Electrochemical lift-off of GaN films for GaN-on-GaN technology
Authors: Liu Yuzhen , Feng Meixin , Yang Shanshan , Li Chuanjie , Dai Yayu , Zhang Shuming , Liu Jianxun , Jin Jing , Sun Qian , Yang Hui
Published: December 2023

Lifting off the native GaN substrate is an essential step in the fabrication of high-performance devices. In this study, we report a method to separate GaN thin films from GaN substrate through electrochemical (EC) lateral etching. By employing tetramethylammonium hydroxide to treat the dry-etched sidewalls, we addressed the issue of non-uniformity at the EC etching front. Meantime, we investigated the effect of Si doping concentration on the roughness of the lift-off GaN films. It is found that as increasing the doping concentration, the roughness decreases together with a reduced applied bias. Finally, we achieved an epitaxial-level smooth surface with a small roughness of only 0.3 nm.
Sensor self-diagnosis method based on a graph neural network
Authors: Jiang Dongnian , Luo Xiaomin
Published: December 2023

Many types of sensors are used in industrial processes, and their reliability is high. However, the traditional method of regularly detecting and evaluating their health status is time-consuming and laborious, and is not suitable for the development of intelligent sensors. In this work, the relative entropy method is first used to quantitatively evaluate the redundancy relationship between sensors, and a sensor graph network is established based on this relationship. Secondly, an unsupervised multi-sensor self-diagnosis model, called attention-based pruning graph convolutional network, is proposed. In order to capture the strong redundancy among sensors by the attention mechanism, multi-sensor timing prediction is realised using a graph convolutional neural network, and the health status of each sensor can be independently judged by the changes in redundancy among the sensors. Finally, a temperature measurement system in a nickel flash furnace is considered as a case study to verify the feasibility and effectiveness of the proposed method.
Rolling bearing fault diagnosis method based on MTF-MFACNN
Authors: Lei Chunli , Miao Chengxiang , Wan Huiyuan , Zhou Jiyang , Hao Dongfeng , Feng Ruicheng
Published: December 2023

A rolling bearing fault diagnosis method based on the Markov transition field (MTF) and multi-scale feature aggregation convolutional neural network (MFACNN) is proposed to address the problems of excessive parameter number, slow training speed, and insufficient generalization of traditional CNNs. Firstly, the original vibration signal is input into the MTF and converted into two-dimensional images with time correlation. Then, in order to effectively aggregate feature information at different scales and levels, a MFA module is presented to capture rich information from feature maps at different scales and assign different weights to these features for fusion. Secondly, while ensuring the lightweight of the model, utilizing feature information of different resolutions, a lightweight feature fusion module is put forward to fuse multiple feature maps together to improve the performance and efficiency of the model. On this basis, an MFACNN model is constructed. Finally, the two-dimensional images are input into MTF-MFACNN and experimentally validated using two different datasets. The results show that the proposed method has faster calculation speed, higher fault recognition accuracy, and stronger generalization performance compared to other methods.
Weak fault feature extraction of rolling bearing based on multi-system coupled cascaded stochastic resonance system
Authors: Li Jimeng , Peng Junling , Zhang Shi , Zhang Jinfeng , Meng Zong
Published: December 2023

The accurate extraction of weak signal features under strong noise background plays a crucial role in the fault detection of rolling bearings. In order to promote the ability of stochastic resonance (SR) system to detect weak signals and improve the output performance of the system, a multi-system coupled cascaded SR (MCCSR) system is investigated and applied to the fault detection of rolling bearings. Firstly, a MCCSR system is constructed by exploiting the positive synergistic effect between multiple systems, which consists of a triangular-topology coupled system composed of three SR subsystems and a cascaded SR system with topology output as input. This system makes full use of the advantages of coupled system and cascaded system in weak signal detection. In terms of parameter optimization, a stepwise multi-parameter optimization strategy is proposed, which adopts different optimization methods for different parameters, and avoids the inconsistency between error and step factor by improving the least mean square algorithm. Finally, through the comparative analysis of numerical simulation and experimental signals, it is verified that the proposed method can effectively enhance the weak signal features and improve the system output signal-to-noise ratio, which can better serve for rolling bearing fault detection.
Acceleration sensing based on the bifurcation dynamics of parametrically excited mode-localized resonators
Authors: Zhao Jian , Tang Yinghai , Kacem Najib , Sun Rongjian , Dong Zeyuan , Lyu Ming , Liu Pengbo
Published: December 2023

A parametrically excited mode-localized accelerometer is designed using the bifurcation phenomenon to improve the robustness of the fluctuation of the driving voltage and damping while maintaining high sensitivity. A dynamic multi-physics model was established while considering both mechanical and electrostatic nonlinearities. The equation was solved by method of multiple scales and verified by harmonic balanced method coupled with the asymptotic numerical method. Two types of bifurcation exist in amplitude frequency response, namely Saddle-Node bifurcation and Supercritical Hopf bifurcation. By introducing Saddle-Node bifurcation, the response amplitude and measurement range can be improved by 100% and 1000%, respectively, while the sensitivity of the amplitude ratio is about 2 orders of magnitude higher than that based on the frequency ratio. At the Supercritical Hopf bifurcation point, a small acceleration will change the topological structure from Supercritical Hopf to Saddle-Node bifurcation. The variation in the amplitude ratio of the Supercritical Hopf point with acceleration is similar to the sign function, which leads to an extremely high sensitivity of 10000%/g in a dynamic range of ±0.001 g. Moreover, the Supercritical Hopf bifurcation point is not affected by the amplitude of the excitation voltage and damping coefficient, which provides a new method for improving the sensing robustness. Ethical Compliance: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Conflict of Interest declaration: The authors declare that they have NO affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript.
Thermoelectric performance of 1T-ZrS2 bilayer using stacking engineering
Authors: Anisha  , Kumar Ramesh , Srivastava Sunita , Kumar Tankeshwar
Published: December 2023

Stacking engineering have played the very important role in tuning the structural, electronic and thermoelectric properties of 1 T ZrS2 bilayer. All these calculations are performed by using first principles calculations in conjunction with the Boltzmann transport theory. The structural properties of bilayer with all possible stackings i.e., AA1, AA2, AA3, AB1, AB2 and AB3 along with their respective interlayer distance (d) are calculated. Electronic properties of these stacking bilayers have showed the indirect band gap in all the stacking pattern. The dynamical stability of AA1, AA2 and AA3 stackings are more in comparison to other stacking bilayers. The lattice thermal conductivity with values 0.57 W mK−1, 0.47 W mK−1 and 1.45 W/mK for stackings AA1, AA2 and AA3, are obtained, respectively. The obtained values of ZT are 0.86, 0.83 and 0.82 for AA1, AA2 and AA3 stackings, respectively, at room temperature, for n-type doping. The present study has provided the effective approach for selecting the good stacking pattern of 1 T ZrS2 bilayer for various applications with excellent thermoelectric performance.
Research on pipeline inspection gauges localization based on residual denoising autoencoder
Authors: Guo Xiaoting , Song Huadong , Zeng Yanli , Zhang Hongxian , Hu Wenguang , Zhu Haibo
Published: December 2023

To improve pipeline transportation efficiency, long-distance pipelines need to be cleaned regularly. Pipeline inspection gauges (PIGs) are widely used in pigging operations. The traditional PIG localization method generally has a large error and cannot achieve continuous tracking. To solve the problem of PIG real-time tracking and localization, this paper proposes a method of PIG localization for oil pipelines based on a denoising autoencoder(DAE). The attention deconvolution residual block (ADR) is introduced in the decoder part of the DAE, so that this model can learn and use global information to selectively emphasize key features, suppress useless features, and improve the noise removal performance of the model. After denoising, the negative pressure wave(NPW) signal is normalized, the time delay is extracted, and the PIG is located using the NPW localization formula. Experiments show that this method can effectively achieve real-time PIG localization. Compared with the EMD and DAE positioning methods, the relative positioning accuracy is increased by 3.5 times and 8.4 times, respectively.
Effect of out-of-plane dimension on simplified geometric models in stress analysis
Authors: Saeed Hasan Aftab , Awan Yasser Riaz , Waiz Sha , Khan Rehan Ahmed
Published: December 2023

Without exception, every physical object is three-dimensional. However, in many stress analysis situations the analyst is justified in using simplified two-dimensional idealizations of plane stress and plane strain, reducing the complexity of the problem. By obviating the need to mesh in the third dimension, this advantage also extends to numerical studies, helping economize significantly on time and computational power requirements. In plane stress idealization the out-of-plane stresses are zero, whereas in plane strain the out-of-plane strains are zero. These idealizations have variously been linked with the out-of-plane dimension, as well as the end conditions of the object under consideration. However, the exact correlation of the out-of-plane dimension with these idealizations remains ambiguous. Unlike the case of plane stress, there is much disagreement found in literature regarding the necessary conditions for the realization of plane strain, which needs to be addressed. In this article, finite element analysis was employed to study the effect of various out-of-plane dimensions and end constraints. The results show that there is no correlation between the out-of-plane dimension and plane strain, which depends only on the end constraints. However, the out-of-plane dimension does result in the transition from plane stress to generalized plane strain.
Emerging multimodal memristors for biorealistic neuromorphic applications
Authors: Shan Xuanyu , Lin Ya , Wang Zhongqiang , Zhao Xiaoning , Tao Ye , Xu Haiyang , Liu Yichun
Published: December 2023

The integration of sensory information from different modalities, such as touch and vision, is essential for organisms to perform behavioral functions such as decision-making, learning, and memory. Artificial implementation of human multi-sensory perception using electronic supports is of great significance for achieving efficient human–machine interaction. Thanks to their structural and functional similarity with biological synapses, memristors are emerging as promising nanodevices for developing artificial neuromorphic perception. Memristive devices can sense multidimensional signals including light, pressure, and sound. Their in-sensor computing architecture represents an ideal platform for efficient multimodal perception. We review recent progress in multimodal memristive technology and its application to neuromorphic perception of complex stimuli carrying visual, olfactory, auditory, and tactile information. At the device level, the operation model and undergoing mechanism have also been introduced. Finally, we discuss the challenges and prospects associated with this rapidly progressing field of research.
Use of matrix-assisted laser desorption ionization time of flight (MALDI-TOF) to detect antibiotic resistance in bacteria: A scoping review
Authors: Viboud Gloria , Asaro Holly , Huang Michael Bailou
Published: December 2023

Objectives

Matrix-assisted laser desorption ionization time of flight (MALDI-TOF) has revolutionized clinical microbiology laboratories, enabling the identification of microorganisms in minutes. Although this advancement has significantly enhanced patient care by providing early diagnosis, the use of MALDI-TOF for routine detection of antimicrobial resistance (AMR) remains an ongoing area of research. The purpose of this scoping review was to identify and summarize the existing literature on MALDI-TOF–based methodologies for detecting AMR.

Methods

The PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature databases were searched for articles published up to July 2023. Publications were carefully screened, and inclusion was based on their relevance to the topic and detailed explanations of the methodologies employed.

Results

We reviewed 49 articles and identified various MALDI-TOF–based approaches for detecting AMR that we grouped in 2 main categories: (1) bacterial growth detection following a brief incubation with antibiotics and (2) identification of specific mass spectral profiles associated with drug resistance. Recently, the use of machine learning algorithms has been explored to detect characteristic patterns associated with AMR. Thorough evaluation of each study’s procedures was conducted to determine their potential for implementation in clinical laboratories.

Conclusions

MALDI-TOF shows promise as a tool for AMR detection, but its readiness for wider clinical adoption relies on ongoing research, development of algorithms and software for automated interpretation of mass spectra, and validation efforts. Its role in routine clinical practice may evolve as technology and knowledge progress.
KGDiff: towards explainable target-aware molecule generation with knowledge guidance
Authors: Qian Hao , Huang Wenjing , Tu Shikui , Xu Lei
Published: December 2023

Designing 3D molecules with high binding affinity for specific protein targets is crucial in drug design. One challenge is that the atomic interaction between molecules and proteins in 3D space has to be taken into account. However, the existing target-aware methods solely model the joint distribution between the molecules and proteins, disregarding the binding affinities between them, which leads to limited performance. In this paper, we propose an explainable diffusion model to generate molecules that can be bound to a given protein target with high affinity. Our method explicitly incorporates the chemical knowledge of protein–ligand binding affinity into the diffusion model, and uses the knowledge to guide the denoising process towards the direction of high binding affinity. Specifically, an SE(3)-invariant expert network is developed to fit the Vina scoring functions and jointly trained with the denoising network, while the domain knowledge is distilled and conveyed from Vina functions to the expert network. An effective guidance is proposed on both continuous atom coordinates and discrete atom types by taking advantages of the gradient of the expert network. Experiments on the benchmark CrossDocked2020 demonstrate the superiority of our method. Additionally, an atom-level explanation of the generated molecules is provided, and the connections with the domain knowledge are established.