bluuebunny/crossref_metadata_2025 huggingface dataset:
Revisiting Thomson’s model with multiply charged superfluid helium nanodroplets
Authors: García-Alfonso Ernesto , Ancilotto Francesco , Barranco Manuel , Cargnoni Fausto , Halberstadt Nadine , Pi Martí
Published: December 2024

We study superfluid helium droplets multiply charged with Na+ or Ca+ ions. When stable, the charges are found to reside in equilibrium close to the droplet surface, thus representing a physical realization of Thomson’s model. We find the minimum radius of the helium droplet that can host a given number of ions using a model whose physical ingredients are the solvation energy of the cations, calculated within the helium density functional theory approach, and their mutual Coulomb repulsion energy. Our model goes beyond the often used liquid drop model, where charges are smeared out either within the droplet or on its surface, and which neglects the solid-like helium shell around the ions. We find that below a threshold droplet radius R0, the total energy of the system becomes higher than that of the separated system of the pristine helium droplet and the charges embedded in their solvation microcluster (“snowball”). However, the ions are still kept within the droplet by the presence of energy barriers, which hinder Coulomb explosion. A further reduction of the droplet radius below a value Rexpl eventually results in the disappearance of such barrier, leading to Coulomb explosion. Surprisingly, our results are rather insensitive to the ion atomic species. This makes room to discuss them in the context of intrinsic multicharged helium droplets, where the charges are triatomic He3+ ions. Our calculated values for Rexpl display the correct scaling with the number of cations compared to the available experimental results, at variance with other estimates for the critical radii.
Bayesian inverse Navier–Stokes problems: joint flow field reconstruction and parameter learning
Authors: Kontogiannis Alexandros , Elgersma Scott V , Sederman Andrew J , Juniper Matthew P
Published: December 2024

We formulate and solve a Bayesian inverse Navier–Stokes (N–S) problem that assimilates velocimetry data in order to jointly reconstruct a 3D flow field and learn the unknown N–S parameters, including the boundary position. By hardwiring a generalised N–S problem, and regularising its unknown parameters using Gaussian prior distributions, we learn the most likely parameters in a collapsed search space. The most likely flow field reconstruction is then the N–S solution that corresponds to the learned parameters. We develop the method in the variational setting and use a stabilised Nitsche weak form of the N–S problem that permits the control of all N–S parameters. To regularise the inferred geometry, we use a viscous signed distance field as an auxiliary variable, which is given as the solution of a viscous Eikonal boundary value problem. We devise an algorithm that solves this inverse problem, and numerically implement it using an adjoint-consistent stabilised cut-cell finite element method. We then use this method to reconstruct magnetic resonance velocimetry (flow-MRI) data of a 3D steady laminar flow through a physical model of an aortic arch for two different Reynolds numbers and signal-to-noise ratio (SNR) levels (low/high). We find that the method can accurately (i) reconstruct the low SNR data by filtering out the noise/artefacts and recovering flow features that are obscured by noise, and (ii) reproduce the high SNR data without overfitting. Although the framework that we develop applies to 3D steady laminar flows in complex geometries, it readily extends to time-dependent laminar and Reynolds-averaged turbulent flows, as well as non-Newtonian (e.g. viscoelastic) fluids.
Materials and strategies for enhancing the reliability of AgNW-based flexible electronics: a review
Authors: Li Chenyuan , Chen Mingxiang , Xie Bin
Published: December 2024

Silver nanowires (AgNWs), which are one-dimensional metallic nanomaterials, have attracted a great deal of attention owing to their superior electrical conductivity, flexibility and transparency. AgNWs have found extensive applications in the realm of flexible and stretchable electronics, where they act as flexible conducting networks. However, AgNWs face severe reliability challenges, including mechanical fracture, chemical corrosion and thermal failures, when dispersed in a polymer matrix. To tackle this issue, numerous strategies involving surface modification and passivation have been proposed. This review discusses the underlying failure mechanisms of AgNWs, with a particular focus on the effective strategies for enhancing the reliability of AgNWs and their composite materials. Finally, insights into potential strategies for enhancing the reliability of AgNWs and boosting their industrial deployment are also described.
DC series arc fault detection method using LDA-CatBoost for PV system under shaded condition
Authors: Yan Jinjing , Tang Shengxue , Geng Likai , Geng Jiayu
Published: December 2024

Detecting DC series arc faults (SAFs) in photovoltaic (PV) systems is challenging due to shaded conditions. A detection method for SAFs in PV systems focusing on shaded conditions is proposed in this paper. By analyzing voltage–current characteristics under different shaded scenarios and the interaction of arc and PV sources to ignite arc faults, the DC SAFs are classified into three types: strong, weak, and intermittent arcs, and then the DC arc features under various shaded conditions are investigated from the current signals. Then, a linear discriminant analysis (LDA)-CatBoost method is proposed to detect and identify SAFs using the features from extracting both time- and frequency-domain current signals. Experimental results demonstrate that the detection and identification accuracy is 98% under various shaded conditions. It significantly improves SAF detection applicability compared with other methods.
Research on rolling bearing fault diagnosis method based on improved multi-source fusion convolutional neural network
Authors: Shi Huaitao , Sun Huayang , Bai Xiaotian , Song Zelong , Gao Tianhao
Published: December 2024

As sensor technology advances, the variety and number of sensors increase, leading to the capture of more signals. Existing multi-source fusion methods often face issues such as increased model complexity or the failure to fully utilize the potential correlations among multi-sensor data, thereby affecting the accuracy and reliability of fault diagnosis. To address this issue, this paper proposes a multi-source fusion convolutional neural network (MFCNN) that diagnoses bearing faults by integrating features from multi-source signals. Firstly, multiple convolution blocks with gradually increasing one-dimensional kernel sizes are utilized to extract features from the integrated multi-source data. This approach enhances feature extraction efficiency and simplifies the network architecture. Secondly, a feature fusion based on the convolutional block attention module attention mechanism is proposed, which refines feature representation through channel and spatial attention modules. This makes the model more focused on important information, thereby improving recognition accuracy. The diagnostic capabilities of the proposed MFCNN are evaluated utilizing two datasets.
Dual-path fusion network based on transformer and local binary patterns for compressive sensing reconstruction
Authors: Lin Leping , Mao Jiaqi , Ouyang Ning
Published: December 2024

In recent years, deep-learning-based methods have made significant progress in the field of compressed sensing. However, most existing deep-learning-based solutions commonly encounter issues in image reconstruction due to inadequate interaction with image textures during the reconstruction process. In this study, we developed a dual-path fusion network that combined structural and textural information for image reconstruction. Guided by structural priors, we designed a new focus linear cross window transformer network that computes attention through parallel cross-SWs of different sizes, integrating both local and global structural information to enhance feature interaction. Meanwhile, a submodule based on local binary pattern is used to leverage image texture priors for learning texture features, thus providing rich texture information for image reconstruction. The features from these two distinct paths are adaptively fused, and the reconstruction results are optimized using an iterative thresholding algorithm. This method effectively combines the advantages of traditional algorithms and deep neural networks, taking advantage of the structural and textural prior information. Experiments demonstrated that the proposed method significantly improves the quality of image reconstruction and robustness to noise.
Generalized cross-correlation based wavelength extraction for chromatic confocal microscopy
Authors: Zhao Wenhao , Yue Kun , Liang Yongkang , Guo Wenping , Xia Min
Published: December 2024

In this paper, we propose a peak extraction algorithm based on generalized cross-correlation method in chromatic confocal microscopy. In this approach, a high level of localization precision is achieved by utilizing the generalized cross-correlation function between the chromatic confocal signal and the template signal. Compared to the algorithms proposed in recent years, the proposed algorithm is found to have lower localization bias and standard deviation.Both the simulation and the experimental results confirm the significant accuracy advantage of the proposed algorithm.
An improved Patlak-based Ki parametric imaging approach for clinical 18F-FDG total-body PET
Authors: Gu Wenjian , Zhu Zhanshi , Liu Ze , Wang Yihan , Li Yanxiao , Xu Tianyi , Liu Weiping , Wang Kuanquan , Luo Gongning , Zhou Yun
Published: December 2024

Objective. The objective is to generate reliable K
i parametric images from 18F-fluorodeoxyglucose (18F-FDG) total-body positron emission tomography (PET) with clinically acceptable scan durations using Patlak and shallow machine learning algorithms, under conditions of limited computational and data resources. Approach. We proposed a robust and fast algorithm named Patlak-KXD to generate K
i images from dynamic PET images with shortened scan durations. In the training phase, K-means is employed to generate a K
i-balanced training dataset. Subsequently, XGBoost is utilized to learn the mapping relationship between the tissue-to-blood standardized uptake ratio (SUR) time curves and Patlak-based K
i values using this balanced dataset. In the prediction phase, the trained XGBoost can generate K
i images by calculating the K
i values from voxel-based SUR time curves obtained from the dynamic images. We compared the accuracy of K
i images generated by both the Patlak-KXD and the traditional Patlak methods across a range of shortened scan durations, and the differences in K
i images generated by the XGBoost model using static (Patlak-KXS) and dynamic PET inputs. Main results. The K
i images generated by the Patlak-KXD from just a 4 min (56–60 min) dynamic 18F-FDG total-body PET scan are comparable to those generated by the traditional Patlak method using 40 min (20–60 min) dynamic PET images, as demonstrated by a normalized mean square error of 0.13 and a Pearson’s correlation coefficient of 0.94 on average. The K
i images generated by the Patlak-KXD is robust to the scan duration, and the quality of K
i images generated from Patlak-KXD is superior to those from Patlak-KXS as scan duration >10 min. Significance. Reliable K
i images can be rapidly generated using shallow machine learning algorithms from dynamic 18F-FDG total-body PET scans with durations as short as four minutes. This total-body K
i parametric imaging method has potential to be used in clinical nuclear medicine and molecular imaging.
Estimating two-dimensional physical parameters of digital rocks using deep learning
Authors: Alexandra Aldenia , Akmal Fadhillah , Nurcahya Ardian , Yulita Intan Nurma , Dharmawan Irwan Ary
Published: December 2024

This research focused on estimating the physical parameters of porous rocks crucial in hydrocarbon exploration using deep learning algorithms. Laboratory measurements have limitations such as time, cost, and core sample limitations, so digital rock models have emerged as a powerful alternative. Digital rock technology involves creating high-resolution images of rock samples using techniques such as micro-CT scanning for the detailed analysis of rock structures and calculation of physical parameters through image processing and numerical simulations. In this work, the CNN architectures included custom-developed models, and transfer learning was applied using pre-trained models DenseNet201, ResNet152, MobileNetV2, InceptionV3, and Xception to estimate physical parameters such as permeability, absolute porosity, effective porosity, tortuosity, and average grain size. Both CNN A and CNN B were good models for estimating permeability with CNN B being the best model for estimating tortuosity, Xception the best model for estimating absolute porosity and effective porosity, and DenseNet201 the best model for estimating average grain size. These results underscore the potential of deep learning in enhancing the efficiency and accuracy of physical parameter estimation in digital rock analysis.
Gate-tunable high-responsivity photodiode based on 2D ambipolar semiconductor
Authors: Yu 于 Wentao 文韬 , Zhao 赵 Long 龙 , Gao 高 Yanfei 延飞 , Gao 高 Shiping 石平 , Yang 杨 Yuekun 悦昆 , Pan 潘 Chen 晨 , Liang 梁 Shi-Jun 世军 , Cheng 程 Bin 斌
Published: December 2024

Electrically tunable homojunctions based on ambipolar two-dimensional materials have attracted widespread attention in the field of intelligent vision. These devices exhibit inherent switchable positive and negative photovoltaic properties that effectively mimic the behavior of human retinal cells. However, the photovoltaic responsivity of most electrically tunable homojunctions remains significantly low due to the weak light absorption, making it challenging to meet the application requirements for high-sensitivity target detection in the field of intelligent vision. Here, we propose a gate-tunable photodiode based on two-dimensional ambipolar WSe2 with an asymmetric gate electrode, achieving high photovoltaic responsivity. By adjusting the gate voltage and keeping bias voltage zero, we can dynamically realize reconfigurable n−–p and n−–n homojunction states, as well as gate-tunable photovoltaic response characteristics that range from positive to negative. The maximum photovoltaic responsivity of the electrically tunable WSe2 homojunction is approximately 0.4 A/W, which is significantly larger than the previously reported value ∼0.1 A/W in homojunction devices. In addition, the responsivity can be further enhanced to approximately 1.0 A/W when the n−–p photodiode operates in reverse bias mode, enabling high-sensitivity detection of targets. Our work paves the way for developing gate-tunable photodiodes with high photovoltaic responsivity and advancing high-performance intelligent vision technology.
A novel method of cognitive overload assessment based on a fusion feature selection using EEG signals
Authors: Li Zhongrui , Tong Li , Zeng Ying , Gao Yuanlong , Gong Diankun , Yang Kai , Hu Yidong , Yan Bin
Published: December 2024

Objective. Cognitive overload, as an overload state of cognitive workload, negatively impacts individuals’ task performance and mental health. Cognitive overload assessment models based on electroencephalography (EEG) can effectively prevent the occurrence of overload through early warning, thereby enhancing task execution efficiency and safeguarding individuals’ mental health. Although existing EEG-based cognitive load assessment methods have achieved significant research outcomes, evaluating cognitive overload remains an ongoing challenge. Current research aims to develop an effective cognitive overload assessment model and enhance its efficacy through feature selection methods. Approach. In the cognitive overload assessment model, we firstly employ variational mode decomposition to adaptively decompose the signal from each channel into four sub-band signals to capture valuable time–frequency information. Subsequently, frequency domain features are extracted from each sub-band, and an effective feature selection method based on mutual information and neighborhood component analysis was applied for feature selection, which optimizes the distribution of the feature space while considering feature correlations, making the selected features more representative. Finally, traditional machine learning methods are utilized for classification, and the effectiveness of the proposed method is tested using both offline and online classification results. Main results. The average accuracy of offline cognitive overload assessment using the proposed method on local and open datasets is 83.44 ± 1.59% and 78.24 ± 1.43%, respectively. The average classification accuracy of its online cognitive overload assessment is about 79.90 ± 2.53%. This indicates that the proposed method can effectively assess cognitive overload under both offline and online conditions. Furthermore, we found that higher-frequency sub-bands are more advantageous for cognitive overload assessment. Significance. EEG signals can be used for effectively cognitive overload assessment, and the integration of feature selection methods enhances the accuracy of the evaluation, providing reliable methodological support for future cognitive overload monitoring in human–computer interaction systems.
Electrical Explosion-Proof design of Low-Temperature condensation oil and gas recovery machine
Authors: Wang Nana , Lin Ruobo , Bai Zhenwei , Shen Lifeng
Published: December 2024

The condensation oil and gas recovery machine is a highly efficient device specifically designed to recover oil and gas using condensation principles. This equipment is primarily used in flammable and explosive environments; thus, its electrical control system must meet explosion-proof requirements. This paper takes the oil and gas recovery machine as an example to introduce the design process of an explosion-proof electrical control system. The control system is composed of PLC and HMI as the core. The appropriate explosion-proof type is chosen based on the structural and performance characteristics of the recovery machine. The key points and considerations for designing the explosion-proof control box are elaborated on. The experimental results indicate that after undergoing triple-stage refrigeration, the oil and gas recovery machine can reduce the temperature of the oil and gas to −80°C. The electrical control system meets the explosion-proof safety and control function requirements of the oil and gas recovery machine.
Research on the drilling state intelligent sensing and adaptive optimization control of the fast drilling robot
Authors: Liu Xiaohua , Wang Qingfeng , Liu Yang
Published: December 2024

The fast drilling robot is the most intelligent mining drilling equipment at present. The drilling state intelligent sensing and adaptive control technology are developed to solve the problem of the intelligent control of the drilling process. According to the engineering practice, with drilling efficiency as the control target, the characteristics of the working process of the fast drilling robot and the influence of boundary conditions such as sticking probability, slag-discharge smoothness, and anchorage stability on the drilling process are analyzed. Corresponding mathematical formulas are derived, and the mathematical model of the drilling state intelligent sensing and adaptive control is constructed. The adaptive control technology based on the differential evolution algorithm is developed to realize the automatic optimization of control parameters. The ground drilling tests prove that intelligent sensing and adaptive control technology can adjust the control parameters quickly when the drilling rock changes so that the drilling robot can maintain an efficient and stable drilling state.
Intelligent control of extra-high arch dams
Authors: Yang Yunbao , Lv Runqi , Han Shenqiu , Li Yang , Yue Jiali , Wu Jianming
Published: December 2024

At this stage, the intelligent construction system integrating sensing technology, communication transmission, data processing, and intelligent decision-making is becoming increasingly mature. It is fully applied in the construction industry. As a large-volume concrete building with concrete temperature control, the extra-high arch dam faces challenges such as high construction difficulty, management difficulty, and other thorny issues. By introducing an intelligent control system, real-time sensing during the pouring process of the extra-high arch dam allows for autonomous analysis to be conducted in a timely manner. Anticipation of various risks in the construction process and autonomous problem-solving are achieved through intelligent decision-making within the system. Artificial assistance makes up for the shortcomings of the intelligent construction system. Through the system’s own independent learning ability and continuous optimization, the problem of intelligent construction can be solved. It also can solve most of the problems in the dam pouring process, accelerate the project progress, significantly reduce the construction difficulty, improve the quality of dam construction, and improve the overall safety performance of the dam.
Research on automatic welding system for oil and gas pipeline based on laser tracking technology
Authors: Liu Shaozhu , Bi Zhiqiang , Xu Congcong , Feng Shuai , Zhang Yi , Hou Lei
Published: December 2024

With the growing energy demand both domestically and internationally, significant progress has been made in the construction of long-distance oil and gas pipelines and the maintenance of in-service pipelines, which has simultaneously raised higher requirements for automatic welding equipment, process methods, and efficiency. In recent years, automatic welding equipment used for oil and gas pipeline welding has predominantly employed arc-tracking technology, which meets the requirements for fully automatic fill and cap welding in standard groove configurations with stable welding quality. However, in hot-work welding processes for in-service pipeline maintenance and emergency repairs, manual alignment and cutting result in irregular weld seams, leading to poor performance of automatic welding equipment and, consequently, reliance on manual welding, which is inefficient. To address this, a specialized automatic welding machine with a laser vision weld seam tracking system was designed for welding irregular weld seams in long-distance oil and gas pipelines. Research was conducted on its mechanical system, control system, welding system, and tracking process. The specialized machine primarily consists of a power supply box, control box, industrial computer, laser sensing system, and welding carriage. During welding, the laser sensor measures three-dimensional information such as the seam size and center offset in real time along the direction of the welding carriage movement and feeds it back to the controller through the communication system of the machine. The main control system receives the information and adjusts the welding torch’s movement and welding process parameters through internal tracking control algorithms. Welding experiments were conducted on X80 steel V-groove welds of long-distance oil and gas pipelines. The results show that the welding machine can accurately identify the weld seam width, center offset, and height offset, and adjust the welding torch actions and parameters accordingly, achieving fully automated adaptive tracking welding. The precision of single torch oscillation tracking during welding can reach 0.5 mm, and the welding quality is good, meeting the requirements for single-layer single-pass fill welding, and multi-pass welding of irregular pipeline weld seams.
Magnetic Properties and Thermal Negativity of Trinuclear and Tetranuclear Ni Ions Complexes
Authors: Ananikian N , Babujyan H , Burdik Č , Papoyan Vl V , Ananikyan L
Published: December 2024

This study focuses on the quantum magnetic properties and entanglement of trinuclear C84H75N12Ni3O3 · 3(ClO4) · 6.5(C3H7NO) and tetranuclear C24H54Cl2N10Ni4O19. This study compares experimental data with exact theoretical calculations of magnetic susceptibility as a function of temperature, revealing excellent agreement. We observe a correlation between magnetization jumps, magnetic susceptibility peaks, and logarithmic negativity plateaus, in response to changes in external magnetic fields for trinuclear and tetranuclear Ni ion complexes at low temperatures. These observations require further experimental measurements in external magnetic fields at low temperatures.
Multidimensional nanofibrous hydrogels integrated triculture system for advanced myocardial regeneration
Authors: Kim Dongwoo , Kim Yeong Hwan , Lee Gyubok , Lee Eun-Cheol , Bhang Suk Ho , Lee Kangwon
Published: December 2024

Myocardial infarction (MI) remains a leading cause of mortality worldwide, posing a significant challenge to healthcare systems. The limited regenerative capacity of cardiac tissue following MI results in chronic cardiac dysfunction, highlighting the urgent need for innovative therapeutic strategies. In this study, we explored the application of a multidimensional nanofibrous hydrogel for myocardial regeneration. We developed a composite hydrogel system by integrating fibrin, polycaprolactone (PCL), and alginate. In this system, fibrin supported cell proliferation and significantly enhanced angiogenesis when combined with human umbilical vein endothelial cells (HUVECs). PCL contributed to the alignment of encapsulated cells, improving their organization within the scaffold. Adipose-derived stem cells (ADSCs) were encapsulated within the hydrogel for their versatile regenerative potential, while C2C12 cells were incorporated for their ability to form muscle tissue. Additionally, the inclusion of alginate not only enhanced the mechanical properties of the hydrogel to better match the biomechanical demands of cardiac tissue but also played a critical role in reducing the immune response, thereby improving the system’s biocompatibility. This study presents an advanced platform for myocardial regeneration using a nanofibrous hydrogel system designed to meet the dual requirements of mechanical robustness and cellular compatibility essential for cardiac tissue engineering. The triculture system, consisting of ADSCs, C2C12 cells, and HUVECs, harnesses the regenerative capabilities of each cell type, promoting both angiogenesis and tissue regeneration. This comprehensive approach addresses the immediate needs for cellular survival and integration while effectively overcoming long-term mechanical and immunological challenges.
Uncertainty
Authors: Sytch Maxim
Published: December 2024

This chapter explores the first enabling market condition of supplier-induced demand: uncertainty. The modern knowledge-based economy, characterized by increasing abstraction and complexity, breeds a palpable sense of uncertainty. This uncertainty manifests in various forms, such as problem, action, and outcome uncertainty. Consequently, organizations grapple with understanding the situation, determining the optimal course of action, and evaluating potential outcomes. In response, professional service firms have emerged as elite experts adept at navigating this uncertainty. Consequently, companies often delegate complex decision-making to these firms, regarding them as knowledgeable and reputable experts. However, this reliance also exposes organizations to the influence of professional service firms, potentially leading to supplier-induced demand. Moreover, professional service firms may unintentionally exacerbate the uncertainty their clients face, further solidifying their clients’ dependence on external expertise. These dynamics highlight uncertainty as one of the primary enablers of supplier-induced demand.
The Emergence of Supplier-Induced Demand
Authors: Sytch Maxim
Published: December 2024

The fusion of the commercial institutional logic and the resulting internalized professional identity leads to supplier-induced demand through three key biases. The first bias is the bias for action, in which professionals tend to lean toward taking action rather than remaining inactive in situations of uncertainty. The second bias is the familiarity bias, which prompts professionals to promote the expertise, products, and services they are familiar with, even if they may not be an appropriate solution for the client’s problem. The final bias is the agreement bias, wherein professionals and clients agree upon a course of action that neither genuinely supports. Frequent social interactions and embedded relationships between buyers and suppliers, often facilitated by geographical proximity, make proximate professional service providers the most likely sources of supplier-induced demand. Under enabling market conditions and the prevailing commercial institutional logic, geographically proximate relationships become potent channels for social influence toward supplier-induced demand.
Deaf Theater in the United States
Authors: Bradbury Jill Marie
Published: December 2024

Deaf theater in the United States arises out of the community of American Sign Language users. Deaf theater has existed as skits, pantomimes, and signed songs as long as deaf people have formed communities. The development of formal theater is tied to the establishment of schools for the deaf in the 19th century. The spread of deaf education led to the growth of communities centered on social interactions and entertainments in sign language, including theater. The founding of the National Theatre of the Deaf (NTD) in 1967 was a pivotal moment in the United States. NTD exposed hearing audiences to stage sign language, the capabilities of deaf actors, and the artistic possibilities inherent in the merging of deaf and hearing theater. The success of NTD led to many other deaf theater companies being established throughout the United States, creating a “golden age of Deaf theater.” In addition, opportunities to work with hearing theater companies began to open up, sometimes for only one actor, but sometimes for multiple deaf artists. This type of theater has been termed integrated or mainstreamed theater. While deaf, integrated theater, and mainstreamed theater all incorporate deaf actors and sign language, they can be distinguished on the basis of cultural content and themes, ratios of deaf or hearing people involved, and accessibility for deaf audiences. All forms of deaf theater make artistic use of sign language. The unique linguistic, poetic, and musical elements of sign language create several challenges in producing deaf theater, such as translation approaches and choices, alignment of spoken English, sign language lines, and sometimes music; language access within the world of the play; and language access for audiences. William Shakespeare’s plays present unique challenges for translation due to their highly poetic language. Five recent productions in the United States illustrate the artistic and staging aspects of deaf and integrated theater: Grey House (2023), Richard III (2022), Private Jones (2024), ISM II (2023), and Trash (2023).
The Archaeology of Amazonian-Andean Interactions
Authors: Clasby Ryan , Yamamoto Atsushi , Olivera Nuñez Quirino
Published: December 2024

Interaction is viewed within anthropological theory as an important causal mechanism for culture change. It has played an especially prominent role in western South American archaeology due to the dramatic environmental transitions that occur across the continental divide from Pacific coastal deserts to the Andean highlands and the vast expanse of the Amazon rainforest, thereby putting peoples into proximity to a variety of resources from different geographical zones. Indeed, the degree to which Amazonian and Andean populations engaged in interregional interaction prior to European contact has been a fundamental question within South American archaeology since its foundation. While these adjacent geographical zones have traditionally been characterized as separate archaeological culture areas, various types of indirect evidence from comparisons of art styles and iconography to historical linguistics and ethnohistoric accounts have indicated that goods, ideas, and people moved between the Andes and the Amazon as early as the initial peopling of the Americas to the Spanish conquest of the Inca Empire, impacting long-term cultural developments within each region. Unfortunately, archaeological inquiries into this subject were historically impeded by the logistical difficulties of working in tropical forest environments, preconceived notions concerning environmental barriers and limitations that would have minimized interregional movement, and the perishability and abstract nature of the types of evidence that would confer interaction between the Andes and the Amazon. Since the early 2000s, however, major advances have occurred in fields such as remote sensing, petrology, paleobotany, bioarchaeology and genetics, and linguistics. These advances, in combination with increased interest and investigation in the intermediate eastern Andean montane forest (or ceja de selva) and western Amazonian lowlands, have allowed scholars to better reconstruct the cultural histories of tropical forest societies as well as provide new avenues for identifying evidence of Amazonian-Andean interactions. The resulting evidence presents a complex pattern of interaction that varies considerably across time and space as it relates to the type of relationships that occurred and the materials and ideas that were exchanged, one that requires greater focus on the mechanisms behind these processes.
Can I have fries with that? Context-dependent foraging behavior in urban and rural American crows
Authors: Merz Margaret R , Cote Sophie , Weinberg Rachel , Malley Timary , Townsend Andrea K
Published: December 2024

Behavioral flexibility and the ability to respond appropriately to anthropogenic cues that signal potential threats or rewards may promote the success of wild animals in the urban environment. Here, we examine the behavioral responses to anthropogenic cues of free-living American crows (Corvus brachyrhynchos), an opportunistic scavenger and common urban exploiter. Specifically, we tested the hypotheses that crows would more readily approach (1) novel objects and anthropogenic food when in close proximity to trash cans, and (2) paper bags with hidden food rewards when closer to a McDonald’s restaurant, due to their associations of food with these cues. In addition, we examined the preference of crows for bags marked with a McDonald’s logo vs. unmarked bags, hypothesizing that crows closer to McDonald’s would be more likely to approach the labeled bag because of its familiarity. Consistent with our expectations, crows exhibited a lower approach latency to anthropogenic food and novel objects in close proximity to trash cans. Likewise, they were more likely to approach paper bags when in proximity to a McDonald’s restaurant, but they showed no preference for bags with a McDonald’s logo. Overall, we found evidence that the foraging behavior of crows varied in the presence of specific anthropogenic cues and that these responses depended on their probable cue familiarity. Their ability to use anthropogenic cues specific to the local environment, combined with their exploitation of human food resources, likely contributes to the success of the American crow in the city.
‘I had the full support of my family! This family support tops everything else’: Facilitators for Arabs with disabilities in Israel to lead meaningful, independent, and dignified lives by applying self-efficacy theory
Authors: Badran Leena , Amin Hira , Gur Ayelet , Stein Michael Ashley
Published: December 2024

This study aims to explore the significance of facilitators for Arabs with disabilities to lead meaningful, independent, and dignified lives by applying self-efficacy theory and the ecological model in a resource-poor environment. Semi-structured in-depth interviews of fifteen Arabs with physical, visual, and psychiatric disabilities who live in the community were conducted. Thematic analysis revealed two major themes, focusing on facilitators for meaningful, independent, and dignified lives: (1) Self-efficacy, resilience, and strength and (2) Sources of Self-efficacy, most of which were situated at the microsystem level. Studying the available facilitators for Arabs with disabilities living in Israel at the micro level underscores how each facilitator is vitally important for success. The authors recommend (1) localized, family-based, or community training in the availability, acquisition, or creation of services and rights; (2) training for families and local communities to nurture self-efficacy, resilience, and strength; and (3) holistic intervention by social workers is required.
Allograft versus autograft ACL reconstruction in skeletally immature patients: a systematic review
Authors: Migliorini Filippo , Pilone Marco , Schäfer Luise , Bertini Francesca Alzira , Giorgino Riccardo , Maffulli Nicola
Published: December 2024

Introduction

Anterior cruciate ligament (ACL) injuries in children and adolescents with open physes are common.

Areas of agreement

Evidence of ACL reconstruction using allografts in children with open physes is limited.

Areas of controversy

Whether the outcomes of ACL allograft reconstruction in children and adolescents with open physes are superior to autograft ACL reconstruction is unclear, with contrasting evidence.

Source of data

In October 2024, the Web of Science, PubMed, and Embase were accessed with no additional filters. Only clinical investigations evaluating ACL reconstruction in children or adolescents with open physes were eligible. Only studies reporting a minimum length of 24 months of follow-up were included.

Areas timely for developing research

Children who undergo allograft ACL reconstruction demonstrate similar functional outcomes to those who undergo autograft ACL reconstruction. Although allografts allow a faster return to sport, the greater laxity, the reduced activity level, and the higher failure and reoperation rates make their use dubious as a first-choice option for ACL reconstruction in skeletally immature patients.
Combined tofacitinib citrate and 308-nm excimer laser treatment for vitiligo: a pilot study
Authors: Gao Jia , Li Qiuting , Huang Haiying , Yu Siguang , Qiu Yanping , Liang Yanping , Lan Lizhen , Li Lili
Published: December 2024

Background

Vitiligo is a clinically prevalent acquired skin disorder characterized by depigmentation. Currently, the therapeutic options for vitiligo are restricted, and numerous issues exist, such as a prolonged treatment course, unsatisfactory therapeutic efficacy, adverse reactions and a high propensity for recurrence after treatment cessation.

Objectives

To assess the safety and efficacy of combined treatment involving oral tofacitinib citrate (TC) and a 308-nm excimer laser (EL), with the aim of discovering a rapid and effective treatment approach to minimize the side-effects of various drugs.

Methods

In total, 63 patients with progressive vitiligo and a Vitiligo Disease Activity Score of 4 from January 2022 to January 2024 were enrolled and divided into three groups. The three groups were: the TC combined with 308-nm EL and methylprednisolone treatment group (group 1); the TC and 308-nm EL treatment group (group 2); and the methylprednisolone alone treatment group (group 3). The treatment was continued for 24 weeks, and an assessment of therapy outcomes was performed.

Results

When TC was combined with 308-nm EL and methylprednisolone treatment (group 1), the effect was more rapid than in the other two groups. When TC was combined with 308-nm EL (group 2), it had a more favourable treatment effect than that of methylprednisolone alone (group 3), despite having a slower onset of effect. After 24 weeks of treatment, there was no significant difference between group 1 and group 2 in terms of the total response rate or significant response. However, when only methylprednisolone treatment was applied, the effect was relatively slow and ineffective.

Conclusions

This study confirmed a rapid and effective treatment of vitiligo was achieved through a combination of TC and 308-nm EL. No serious adverse reactions were reported, and therefore this could potentially offer an optimal treatment plan for patients with vitiligo.
Testing Hubel and Wiesel’s “ice-cube” model of functional maps at cellular resolution in macaque V1
Authors: Zhang Sheng-Hui , Tang Shi-Ming , Yu Cong
Published: December 2024

Hubel and Wiesel’s ice-cube model proposed that V1 orientation and ocular dominance functional maps intersect orthogonally to optimize wiring efficiency. Here, we revisited this model and additional arrangements at both cellular and pixel levels in awake macaques using two-photon calcium imaging. The recorded response fields of view were similar in size to hypercolumns, each containing up to 2,000 identified neurons and representing full periods of orientation preferences and ocular dominance. We estimated each neuron/pixel's orientation, ocular dominance, and spatial frequency preferences, constructed respective functional maps, computed geometric gradients of feature preferences, and calculated intersection angles among these gradients. At the cellular level, the intersection angles among functional maps were nearly evenly distributed. Nonetheless, pixel-based maps after Gaussian smoothing displayed orientation-ocular dominance and orientation–spatial frequency orthogonality, as well as ocular dominance–spatial frequency parallelism, in alignment with previous results, even though the trends were weak and highly variable. However, these Gaussian smoothing effects were not observed in cellular maps, indicating that the pixel-based trends may not accurately represent the relationships among feature-tuning properties of V1 neurons. We suggest that the widely distributed intersections among cellular maps can ensure that multiple stimulus features are represented within a hypercolumn, and no pair of features is represented with the least economical wiring (e.g. parallel intersections).
Bivalent Boosters and Risk of Postacute Sequelae Following Vaccine-Breakthrough Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Infection: A Cohort Study
Authors: Wee Liang En , Lim Jue Tao , Goel Mayank , Malek Muhammad Ismail Abdul , Chiew Calvin J , Ong Benjamin , Lye David Chien Boon , Tan Kelvin Bryan
Published: December 2024

Background

Vaccination has been shown to attenuate the risk of postacute sequelae following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, no prior population-based studies have evaluated if updated bivalent boosters reduce risk of postacute sequelae following Omicron variant infection, versus ancestral vaccines.

Methods

National databases were utilized to construct a population-based cohort of adult individuals infected during Omicron-predominant transmission. Risk and excess burden (EB) of prespecified multiorgan new-incident diagnoses at 31–365 days post–SARS-CoV-2 infection were compared between individuals who received prior bivalent boosters and those boosted with ancestral messenger RNA (mRNA) vaccines, using competing-risks regression.

Results

A total of 1 080 348 vaccine-breakthrough infections after an ancestral mRNA booster were contrasted against 9824 vaccine-breakthrough infections following a bivalent mRNA booster. There was an estimated 37.8% (hazard ratio [HR], 0.62 [95 confidence interval {CI}, .53–.73]) decrease in risk and lower overall EB per 1000 (−28.73 [95% CI, −40.47 to −16.99]) of any postacute sequelae, as well as a 39.9% (HR, 0.62 [95% CI, .52–.73]) decrease in risk and lower EB (−22.95 [95% CI, −32.71 to −13.19]) of any postacute neurological sequelae, among individuals who received prior bivalent boosters, versus those boosted with ancestral mRNA vaccines. Specifically, there was reduced risk of thrombotic disorders (HR, 0.54 [95% CI, .29–.99]), episodic neurological disorders (HR, 0.55 [95% CI, .43–.72]), movement disorders (HR, 0.57 [95% CI, .47–.70]), and autoimmune vasculitis (HR, 0.54 [95% CI, .29–.99]) 31–365 days postinfection among those who received prior bivalent boosters, versus those boosted with ancestral mRNA vaccines.

Conclusions

Boosting with updated bivalent mRNA vaccines was associated with greater attenuation of risk for postacute sequelae following Omicron variant infection, compared with ancestral mRNA boosters.
Distorted Technology Adoption
Authors: Ayerst Stephen
Published: December 2024

To what extent do firm-level institutional distortions drive cross-country technology differences? I develop a quantitative model of technology adoption in which heterogeneous firms adopt technology depending on their underlying productivity and institutional environment. The institutional environment is represented by size-dependent firm-level wedges on revenues that distort firm decisions. The model is calibrated to match the US firm employment distribution and the average adoption length of new technologies. In less developed countries, measured size-dependent distortions hinder highly productive firms, delaying the adoption of new technologies as these firms are (otherwise) early adopters. Measured differences in size-dependent distortions explain around half of the observed cross-country variation in adoption lags. Additionally, distorted technology adoption over doubles the aggregate productivity loss compared to static misallocation alone.
Paralogous Gene Recruitment in Multiple Families Constitutes Genetic Architecture and Robustness of Pod Dehiscence in Legumes
Authors: Yong Bin , Balarynová Jana , Li Bingbing , Konečná Denisa , Rencoret Jorge , del Río José C , Smýkal Petr , He Chaoying
Published: December 2024

Pod dehiscence facilitates seed dispersal in wild legumes while indehiscence is a key domestication trait in cultivated ones. However, the evolutionary genetic mechanisms underlying its diversity are largely unclear. In this study, we compared transcriptomes of two warm-season (Glycine spp. and Phaseolus spp.) and two cool-season (Pisum spp. and Medicago ruthenica) legumes in analysis of dehiscent and indehiscent pod genotypes. Differentially expressed genes in AP2/ERF-like transcription factors and seven structural gene families, including lactoperoxidase, laccase, and cellulose synthase-interactive proteins, which are involved in secondary cell wall component accumulation, were identified to exert key roles in pod dehiscence variation. In accordance with this, higher lignin and cellulose contents were observed in pod secondary cell wall of dehiscent accessions of soybean and pea; however, the variation patterns of lignin polymers in soybean (accumulation) and pea (proportion) differed between dehiscent and indehiscent pods. Moreover, genome-wide comparative analysis revealed that orthogroups represented <1% of all identified differentially expressed genes could be traced among the four genera of legumes, while recruiting paralogous members may constitute the genetic robustness of legume pod dehiscence. This study compared the genetic mechanism among several legumes in pod dehiscence formation and revealed a compensating role of paralogous redundancy of involved gene families in seed dispersal, which can guide crop breeding.