bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural network-based algorithm for door handle recognition using RGBD cameras
Authors: Mochurad Lesia , Hladun Yaroslav
Published: July 2024

The ability to recognize and interact with a variety of doorknob designs is an important component on the path to true robot adaptability, allowing robotic systems to effectively interact with a variety of environments and objects The problem addressed in this paper is to develop and implement a method for recognizing the position of a door handle by a robot using data from an RGBD camera. To achieve this goal, we propose a revolutionary approach designed for autonomous robots that allows them to identify and manipulate door handles in different environments using data obtained from RGBD cameras. This was achieved by creating and annotating a complete dataset consisting of 5000 images of door handles from different angles, with the coordinates of the vertices of the bounding rectangles labeled. The architectural basis of the proposed approach is based on MobileNetV2, combined with a special decoder that optimally increases the resolution to 448 pixels. A new activation function specially designed for this neural network is implemented to ensure increased accuracy and efficiency of raw data processing. The most important achievement of this study is the model's ability to work in real-time, processing up to 16 images per second. This research paves the way for new advancements in the fields of robotics and computer vision, making a substantial contribution to the practical deployment of autonomous robots in a myriad of life's spheres.
Plasma metabolomics identifies differing endotypes of recurrent wheezing in preschool children differentiated by symptoms and social disadvantage
Authors: Fitzpatrick Anne M. , Grunwell Jocelyn R. , Gaur Hina , Kobara Seibi , Kamaleswaran Rishikesan
Published: July 2024

Preschool children with recurrent wheezing are a heterogeneous population with many underlying biological pathways that contribute to clinical presentations. Although the morbidity of recurrent wheezing in preschool children is significant, biological studies in this population remain quite limited. To address this gap, this study performed untargeted plasma metabolomic analyses in 68 preschool children with recurrent wheezing to identify metabolomic endotypes of wheezing. K-means cluster analysis was performed on metabolomic dataset including a total of 1382 named and unnamed metabolites. We identified three metabolomic clusters which differed in symptom severity, exacerbation occurrence, and variables associated with social disadvantage. Metabolites that distinguished the clusters included those involved in fatty acid metabolism, fatty acids (long chain monounsaturated fatty acids, long chain polyunsaturated fatty acids, and long chain saturated fatty acids), lysophospholipids, phosphatidylcholines, and phosphatidylethanolamines. Pathway analyses identified pathways of interest in each cluster, including steroid metabolism, histidine metabolism, sphingomyelins, and sphingosines, among others. This study highlights the biologic complexity of recurrent wheezing in preschool children and offers novel metabolites and pathways that may be amenable to future study and intervention.
Single-cell RNA sequencing reveals special basal cells and fibroblasts in idiopathic pulmonary fibrosis
Authors: Jin Chengji , Chen Yahong , Wang Yujie , Li Jia , Liang Jin , Zheng Shaomao , Zhang Lipeng , Li Qiaoyu , Wang Yongchao , Ling Fayu , Li Yongjie , Zheng Yu , Nie Qiuli , Feng Qiong , Wang Jing , Yang Huiling
Published: July 2024

Idiopathic pulmonary fibrosis (IPF) is the most predominant type of idiopathic interstitial pneumonia and has an increasing incidence, poor prognosis, and unclear pathogenesis. In order to investigate the molecular mechanisms underlying IPF further, we performed single-cell RNA sequencing analysis on three healthy controls and five IPF lung tissue samples. The results revealed a significant shift in epithelial cells (ECs) phenotypes in IPF, which may be attributed to the differentiation of alveolar type 2 cells to basal cells. In addition, several previously unrecognized basal cell subtypes were preliminarily identified, including extracellular matrix basal cells, which were increased in the IPF group. We identified a special population of fibroblasts that highly expressed extracellular matrix-related genes, POSTN, CTHRC1, COL3A1, COL5A2, and COL12A1. We propose that the close interaction between ECs and fibroblasts through ligand–receptor pairs may have a critical function in IPF development. Collectively, these outcomes provide innovative perspectives on the complexity and diversity of basal cells and fibroblasts in IPF and contribute to the understanding of possible mechanisms in pathological lung fibrosis.
Identification of an H-Ras nanocluster disrupting peptide
Authors: Steffen Candy Laura , Manoharan Ganesh babu , Pavic Karolina , Yeste-Vázquez Alejandro , Knuuttila Matias , Arora Neha , Zhou Yong , Härmä Harri , Gaigneaux Anthoula , Grossmann Tom N. , Abankwa Daniel Kwaku
Published: July 2024

Hyperactive Ras signalling is found in most cancers. Ras proteins are only active in membrane nanoclusters, which are therefore potential drug targets. We previously showed that the nanocluster scaffold galectin-1 (Gal1) enhances H-Ras nanoclustering via direct interaction with the Ras binding domain (RBD) of Raf. Here, we establish that the B-Raf preference of Gal1 emerges from the divergence of the Raf RBDs at their proposed Gal1-binding interface. We then identify the L5UR peptide, which disrupts this interaction by binding with low micromolar affinity to the B- and C-Raf-RBDs. Its 23-mer core fragment is sufficient to interfere with H-Ras nanoclustering, modulate Ras-signalling and moderately reduce cell viability. These latter two phenotypic effects may also emerge from the ability of L5UR to broadly engage with several RBD- and RA-domain containing Ras interactors. The L5UR-peptide core fragment is a starting point for the development of more specific reagents against Ras-nanoclustering and -interactors.
Structural constraints limit the regime of optimal flux in autocatalytic reaction networks
Authors: Despons Armand , De Decker Yannick , Lacoste David
Published: July 2024

Autocatalytic chemical networks play a predominant role in a large number of natural systems such as in metabolic pathways and in ecological networks. Despite recent efforts, the precise impact of thermodynamic constraints on these networks remains elusive. In this work, we present a theoretical framework that allows specific bounds on the thermodynamic affinity and on the concentrations of autocatalysts in mass-action autocatalytic networks. These bounds can be obtained solely from the stoichiometry of the underlying chemical reaction network, and are independent from the numerical values of kinetic parameters. This property holds in the specific regime where all the fluxes of the network are tightly coupled and maximal. Our method is applicable to large networks, and can be used to complement constraints-based modeling methods of metabolic networks, which typically do not provide predictions about thermodynamic properties or concentration ranges of metabolites.
Solutions for decarbonising urban bus transport: a life cycle case study in Saudi Arabia
Authors: Zhao Chengcheng , Kobayashi Leiliang Zheng , Alquaity Awad Bin Saud , Monfort Jean-Christophe , Cenker Emre , Miralles Noliner , Sarathy S. Mani
Published: July 2024

With heavy reliance on fossil fuels, countries like Saudi Arabia face challenges in reducing carbon emissions from urban bus transportation. Herein, we address the gaps in evaluating proton-exchange membrane fuel cell buses and develop a globally relevant life-cycle assessment model using Saudi Arabia as a case study. We consider various bus propulsion technologies, including fuel cell buses powered by grey and blue hydrogen, battery electric buses, and diesel engines, and include the shipping phase, air conditioning load, and refuelling infrastructure. The assessment illustrates fuel cell buses using blue hydrogen can reduce emissions by 53.6% compared to diesel buses, despite a 19.5% increase in energy use from carbon capture and storage systems. Battery electric buses are affected by the energy mix and battery manufacturing, so only cut emissions by 16.9%. Sensitivity analysis shows climate benefits depend on energy sources and efficiencies of carbon capture and hydrogen production. By 2030, grey and blue hydrogen-powered fuel cell buses and battery electric buses are projected to reduce carbon emissions by 19.3%, 33.4%, and 51% respectively, compared to their 2022 levels. Fully renewable-powered battery electric buses potentially achieve up to 89.6% reduction. However, fuel cell buses consistently exhibit lower environmental burdens compared to battery electric buses.
Nitric oxide releasing coatings for the prevention of viral and bacterial infections
Authors: Aveyard Jenny , Richards Siobhan , Li Man , Pitt Graeme , Hughes Grant L. , Akpan Asangaedem , Akhtar Riaz , Kazaili Ahmed , D'Sa Raechelle A.
Published: July 2024

Healthcare associated infections are a significant burden worldwide contributing to morbidity and mortality. We report on the development of nitric oxide releasing polymer coatings that have demonstrated excellent antibacterial/antiviral efficacy.
Melatonin-loaded mesoporous zinc- and gallium-doped hydroxyapatite nanoparticles to control infection and bone repair
Authors: Shokri Mahshid , Kharaziha Mahshid , Ahmadi Tafti Hossein , Dalili Faezeh , Mehdinavaz Aghdam Rouhollah , Ghiassi Seyed Reza , Baghaban Eslaminejad Mohamadreza
Published: July 2024

Mesoporous zinc, gallium-doped hydroxyapatite (Zn–Ga:mHA) nanoparticles are synthesized for release of melatonin. The Zn–Ga:mHA shows effective antibacterial properties and stimulates bone regeneration in vivo and in vitro.
Applications of nanotechnology in remodeling the tumour microenvironment for glioblastoma treatment
Authors: Mu Yulei , Zhang Zhen , Zhou Huiqun , Ma Liang , Wang Dong-An
Published: July 2024

The innovative and efficacious application of nanotechnology for remodeling the glioblastoma (GBM) tumor microenvironment (TME) exhibits promising potential as a therapeutic avenue for GBM treatment.
Structurally diverse zinc(ii) complexes containing tripodal tetradentate phenoxido-amines with promising antiproliferative effects
Authors: Massoud Salah S. , Mautner Franz A. , Louka Febee R. , Salem Nahed M. H. , Fischer Roland C. , Torvisco Ana , Vančo Ján , Belza Jan , Dvořák Zdeněk , Trávníček Zdeněk
Published: July 2024

Structurally diverse zinc(ii) complexes with tripodal tetradentate phenolic-amines of variable substituents in the phenol and amine moieties were synthesized and thoroughly characterized.
Structural, photoluminescence and energy transfer investigations of novel Dy3+ → Sm3+ co-doped NaCaPO4 phosphors for white-light-emitting diode applications
Authors: Farooq Mudasir , Rafiq Haqnawaz , Nazir Irfan , Rubab Seemin , Rasool Mir Hashim
Published: July 2024

Configurational coordinate model. Photoluminescence quenching mechanism. Energy transfer mechanism of Dy3+/Sm3+ in NaCaPO4.
Investigation of the spin crossover behaviour of a sublimable Fe(ii)-qsal complex: from the bulk to a submonolayer on graphene/SiO2
Authors: Trapali Adelais , Muppal Mukil , Pandey Satakshi , Boillot Marie-Laure , Repain Vincent , Dappe Yannick J. , Dayen Jean-François , Rivière Eric , Guillot Régis , Arrio Marie-Anne , Otero Edwige , Bellec Amandine , Mallah Talal
Published: July 2024

Spin crossover Fe(ii) molecules deposited on graphene/SiO2 as a submonolayer present a switching behavior within the whole temperature range from 350 to 4 K.
Mesoporous silica-supported platinum nanocatalysts for colorimetric detection of glucose, cholesterol, and C-reactive protein
Authors: Kim Taehyeong , Kim Dokyoon
Published: July 2024

Pt nanoparticles are densely nucleated on mesoporous silica nanoparticle (MSN) surface to produce Pt-MSNs with enhanced peroxidase-like activity. Their utility in colorimetric detection of glucose, cholesterol, and C-reactive protein is validated.
Particulate matter and nanoplastics: synergistic impact on Artemia salina
Authors: Gopikrishnan Mohanraj , Subramanian Kanimozhi , Krn Ashwin , Doss C. George Priya , Srimuruganandam B. , Chandrasekaran Natarajan
Published: July 2024

Investigates the synergistic impacts of particulate matter and nanoplastics on the vitality and longevity of Artemia salina, emphasizing the potential implications for environmental sustainability and ecological balance.
The performance and mechanism of persulfate activated by CuFe-LDHs for ofloxacin degradation in water
Authors: Zhang Xue , Zhang Kang , Li Ting , Wang Yujiao , Xu Yin
Published: July 2024

Cu–Fe bimetallic synergy plays an important role in the generation of SO4·−.
Sustainable synthesis and characterization of nano-triple superphosphate from solid marine wastes
Authors: Alam Md. Kawcher , Hossain Md. Sahadat , Islam Mohammad Saimon , Bahadur Newaz Mohammed , Ahmed Samina
Published: July 2024

Today, it is vitally important to develop an environmentally sound source for the manufacturing of phosphate fertilizers, as the availability of mineral rock phosphate is diminishing day by day.
Metainterfaces with mechanical, thermal, and active programming properties based on programmable orientation-distributed biometric architectonics
Authors: Gao Zhenyang , Wang Hongze , Ren Pengyuan , Zheng Gengchen , Lu Yang , Peng Bokang , Tang Zijue , Wu Yi , Wang Haowei
Published: July 2024

This study presents next-generation biometric “metainterface” enabling programmable mechanical, thermal, and active interfacial effects for intelligent materials and systems with highly engineerable interfacial properties.
Fluid-responsive tunable metasurfaces for high-fidelity optical wireless communication
Authors: Khalid Ramna , Wu Qing Yang Steve , Mahmood Nasir , Deng Jie , Nemati Arash , Sreekanth Kandammathe Valiyaveedu , Cabrera Humberto , Mehmood Muhammad Qasim , Teng Jinghua , Zubair Muhammad
Published: July 2024

Optical wireless communication (OWC), with its blazing data transfer speed and unparalleled security, is a futuristic technology for wireless connectivity.
Electronic metal–support interaction via Ni defect-induced Ru-modified Ni–CeO2 for enhanced hydrogen oxidation activity
Authors: Zhou Shuqing , Liu Yi , Cheng Lianrui , Isimjan Tayirjan Taylor , Tian Jianniao , Yang Xiulin
Published: July 2024

A defect-rich Ru/Ni–CeO2 catalyst was fabricated using a MOF-mediated pyrolysis-reduction strategy. The robust EMSI effect between Ru and Ni–CeO2 with abundant Ni defects provides striking HOR activity and resistance to CO poisoning.
An insoluble p-type organic polymer cathode with a 9,9′-bicarbazole core for highly stable Li/Na/K-based dual-ion full batteries
Authors: Fan Kexin , Ma Huilin , Tang Wu , Li Wenjun , Jia Shan , Hu Jiahui , Liu Xinyu , Zhang Yuanhe , Fan Cong
Published: July 2024

A p-type organic polymer P(BCz4PZ) with a PF6−-storage mechanism is employed as a high-potential cathode for Li/Na/K-based dual-ion full batteries. The resulting batteries with carbon anodes show 193/185/140 W h kg−1 based on total mass.
Alkene insertion enables ring-opening of vinyl epoxides: a theoretical perspective
Authors: Liu Jiabin , Yang Kai , Liu Jiying , Fu Dongmin , Li Shi-Jun , Zhang Wenjing , Lan Yu
Published: July 2024

This mechanistic study on the Cu-catalyzed ring-opening of vinyl epoxides provides valuable insights into the mechanism for vinyl epoxide transformation and the essential roles of the copper catalyst.
Effect of temperature, hydrogen donor, and zeolites on light cycle oil cracking: thermodynamic, experimental, and DFT analyses
Authors: Ramteke Akshata Vijay , Kaushik Marvi , Bhatia Divesh , Pant K. K.
Published: July 2024

Experimental, thermodynamic, and DFT analyses determine optimal conditions for maximizing BTX yields from LCO and provide mechanistic insights.
Sodium decahydrido-closo-1-carbadecaborate as a solid electrolyte: new insight into polymorphism and electrochemical performance
Authors: Kjær Therese S. S. , Grinderslev Jakob B. , Skov Lasse N. , Jensen Torben R.
Published: July 2024

New insights into the polymorphism and electrochemical properties of the solid electrolyte NaCB9H10, investigating the usability of NaCB9H10 as a battery electrolyte at room temperature.
Reconstructed PbCO3 with abundant oxygen vacancies for efficient CO2-to-formate electrocatalysis
Authors: Wang Huan , Zhao Jia Yue , Yang Qian Qian , Wu Jia Chen , Zhang Xin Yu , Yuan Hai Yang , Xu Xiao Lei , He Jing Jing , Niu Qiang , Liu Peng Fei , Yang Hua Gui
Published: July 2024

A PbCO3 electrocatalyst rich in oxygen vacancies was constructed for efficient formate electrosynthesis, with faradaic efficiencies exceeding 90% within current densities from 50 to 400 mA cm−2.
Improving the high-voltage high-rate performance of a P2 layered oxide cathode by a dual-ion doping strategy for sodium-ion batteries
Authors: Xu Huan , Xie Chengde , Chen Huige , Song Tianyi , Lan Yuanqi , Wu Nanzhong , Zhou Xiaolong , Kidkhunthod Pinit , Kang Lei , Han Xiaoqi , Yao Wenjiao , Tang Yongbing
Published: July 2024

Synergy between Ti4+ and F− dual-doping significantly improves the cycling stability of P2-Na0.67Ni0.33Mn0.67O2 at high voltage and enhances its rate performance by suppressing the P2–O2 transition.
Elucidating performance degradation mechanisms in non-fullerene acceptor solar cells
Authors: Sangwan Vinod K. , Martin Zachary , Li Guoping , Qin Fei , Hadke Shreyash , Pankow Robert M. , Jeon Woo Cheol , Zheng Ding , Cho Yongjoon , Young Ryan M. , Kohlstedt Kevin L. , Wasielewski Michael R. , Schatz George C. , Facchetti Antonio , Hersam Mark C. , Marks Tobin J.
Published: July 2024

Degradation of Y6-based organic solar cells involves Y6 vinyl oxidation, with the resulting trap states disrupting cell performance even at very low concentrations.
Recent advances of functional modules for tooth regeneration
Authors: Wang Xuan , Chen Qiuyu , Li Jiayi , Tian Weidong , Liu Zhi , Chen Tian
Published: July 2024

The use of 3D bioprinting, cell sheet technology, electrostatic droplet technology, and electrospinning technology to generate functional tooth modules represents an emerging and promising approach in dental tissue engineering.
Simultaneous photoactivation of a fluoroquinolone antibiotic and nitric oxide with fluorescence reporting
Authors: Martins Tassia J. , Parisi Cristina , Pinto Juliana Guerra , Brambilla Isabelle de Paula Ribeiro , Melilli Barbara , Aleo Danilo , Ferreira-Strixino Juliana , Sortino Salvatore
Published: July 2024

Light excitation of the nitrosated and inactive form of the antibiotic norfloxacin triggers the release of the antibacterial NO and liberates the active drug restoring its typical fluorescence emission, which acts as an optical self-reporter.
Binuclear iridium(iii) complexes for efficient near-infrared light-emitting electrochemical cells with electroluminescence up to 800 nm
Authors: Ballerini Lavinia , Zhang Wei-Min , Groizard Thomaz , Gourlaouen Christophe , Polo Federico , Jouaiti Abdelaziz , Su Hai-Ching , Mauro Matteo
Published: July 2024

A novel family of binuclear iridium(iii) complexes is presented and thoroughly investigated. The compounds display near-infrared (NIR) photoluminescence and their use as NIR emitting materials in light-emitting electrochemical cells is demonstrated.
Recent advances in passive cooling materials for thermal management in flexible electronics
Authors: Li Jiyu , Zhou Yingying , Jiang Cancheng , Lei Dangyuan , Yu Xinge
Published: July 2024

Flexible electronics has been widely recognized as the future of electronics for a broad range of applications, which is also the foundation for wearable devices that can go or even seamlessly integrate with the human skin.
Highly flexible and temperature-tolerant phase change devices for dual-band camouflage
Authors: Huo Liuxiang , Wang Lin , Li Shubing , Xu Xionghu , Zhu Liangqing , Li Yawei , Shang Liyan , Jiang Kai , Chu Junhao , Hu Zhigao
Published: July 2024

Here, we have developed a more temperature-tolerant emitter with a gradient emittance, which can enable adaptation to changing environmental conditions. Such a thermal emitter is mainly constructed by multilayered films composed of nitrogen (N)-doped Ge2Sb2Te5 (N-GST) and an underlying metal film. The proposed device not only possesses special wavelength selectivity in the middle infrared range but can also dynamically adjust average emissivity (from 0.13 to 0.83) through the degree of crystallization. Besides, N doping can elevate the phase transition temperature of GST and enhance its thermal resistance, which renders it particularly well-suited for applications in higher temperature environments than pure GST. This emitter also shows strong adhesion capability and high flexibility against bending, enabling more practical and widespread situations. By using a multi-layer structure, we combined the more temperature-tolerant and dynamically modulating N-GST emitter with an optical thin film, successfully achieving dual camouflage for both infrared and visible light. The element doping technology and multi-layer stacking approach presented in this research will provide valuable insight for the development of dynamic emissive materials in multi-spectral camouflage scenarios.
Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system
Authors: Liu Zheng , Kabirzadeh Pouya , Wu Hao , Fu Wuchen , Qiu Haoyun , Miljkovic Nenad , Li Yumeng , Wang Pingfeng
Published: July 2024

The development of lithium-ion battery technology has ensured that battery thermal management systems are an essential component of the battery pack for next-generation energy storage systems. Using dielectric immersion cooling, researchers have demonstrated the ability to attain high heat transfer rates due to the direct contact between cells and the coolant. However, feedback control has not been widely applied to immersion cooling schemes. Furthermore, current research has not considered battery pack plant design when optimizing feedback control. Uncertainties are inherent in the cooling equipment, resulting in temperature and flow rate fluctuations. Hence, it is crucial to systematically consider these uncertainties during cooling system design to improve the performance and reliability of the battery pack. To fill this gap, we established a reliability-based control co-design optimization framework using machine learning for immersion cooled battery packs. We first developed an experimental setup for 21700 battery immersion cooling, and the experiment data were used to build a high-fidelity multiphysics finite element model. The model can precisely represent the electrical and thermal profile of the battery. We then developed surrogate models based on the finite element simulations in order to reduce computational cost. The reliability-based control co-design optimization was employed to find the best plant and control design for the cooling system, in which an outer optimization loop minimized the cooling system cost while an inner loop ensured battery pack reliability. Finally, an optimal cooling system design was obtained and validated, which showed a 90% saving in cooling system energy consumption.
Generation and repair of thymic epithelial cells
Authors: Anderson Graham , Cosway Emilie J. , James Kieran D. , Ohigashi Izumi , Takahama Yousuke
Published: July 2024

In the vertebrate immune system, thymus stromal microenvironments support the generation of αβT cells from immature thymocytes. Thymic epithelial cells are of particular importance, and the generation of cortical and medullary epithelial lineages from progenitor stages controls the initiation and maintenance of thymus function. Here, we discuss the developmental pathways that regulate thymic epithelial cell diversity during both the embryonic and postnatal periods. We also examine how thymus microenvironments respond to injury, with particular focus on mechanisms that ensure regeneration of thymic epithelial cells for the restoration of thymus function.
The chemical ordering and local pressure dependence for truncated octahedron PdAuRh nanoalloys
Authors: Garip Ali Kemal , Göcen Tuğba , Ünlü Nihan
Published: July 2024

The optimal chemical ordering configurations of 38-atom trimetallic PdnAu(32−n)Rh6 nanoalloys with truncated octahedron (TO) geometry were determined through Monte Carlo Basin-Hopping algorithm employing the Gupta potential, followed by local relaxations. Variations in mixing energy were assessed to compare relative stability, revealing the lowest excess energy at Pd16Au16Rh6 composition at the Gupta level. Furthermore, a comprehensive analysis of local atomic pressure was conducted, exploring the factors influencing these pressures.
Shear-free inhomogeneous energy density in 4D Einstein-Gauss-Bonnet spherical systems
Authors: Yousaf Z , Almutairi Bander , Bhatti M Z , Farhat A , Khan A S
Published: July 2024

We explore the inhomogeneity factors for the initially regular relativistic spheres in 4D-Einstein-Gauss-Bonnet (EGB) theory. The corresponding equations of motion are derived once the generic expressions for the kinematical variables are obtained for spherically symmetric self-gravitating system. By using the non-zero divergence of the stress-energy tensor, the independent components of Bianchi identities are constructed. To enable a thorough explanation of the inhomogeneity of the particular shear free matter distribution, we computed two distinct components of evolution equations employing the Weyl tensor. We then investigate the requisite variables for the irregularity by looking at particular scenarios in both the adiabatic and non-adiabatic domains. These instances demonstrate how, in addition to other factors, the Gauss-Bonnet terms contribute to the regularity requirements of the collapsing fluid.
Dirac fermions collimation in heterostructures based on tilted Dirac cone materials
Authors: Choubabi E B , Lemaalem B , Raggui M , Belouad A , Houça R , Kamal A , Monkade M
Published: July 2024

This paper aims to theoretically analyze the behavior of Dirac fermions in a tilted Dirac cone material, particularly those interacting with a barrier potential. Our results show that the degree of tilt in the y-direction can lead to different collimations of Dirac fermion beams relative to the Fermi and confinement surfaces. We have highlighted a range of results, including the conical geometry by illustrating the active surfaces and their geometric parameters in reciprocal space. To study the transmission probability, we have conducted numerical analyses, considering various system configurations and different external and internal physical parameters to characterize the fermionic transport behavior in a proposed heterostructure. Additionally, we examined the transmission of Dirac fermions in relation to the refractive indices and refraction between the different media constituting the system, discussing the tunneling effect and the Klein paradox in relation to various physical parameters. Our findings lay the groundwork for the development of controllable electronic devices using Dirac fermion collimation, governed by the tilt parameter, enabling precise manipulation and enhanced functionality.
Homogeneous spacetime with shear viscosity
Authors: Cho Inyong , Shaikh Rajibul
Published: July 2024

We study the homogeneous and anisotropic evolution of Bianchi type-I
spacetime driven by perfect fluid with shear viscosity. We obtain exact
solutions by considering the simplest form of the equation of state wherein
the pressure and the shear stress are proportional to the energy density
individually. A special case of our general solutions represent Bianchi
type-VII cosmology. We analyse the singularity structure of the solutions
and its connection with various energy conditions. We find that the
initial singularity can be removed only for the Bianchi type-VII. We also
analyse the late-time behaviour of the solutions and find that, compared
to the usual Friedmann universe, the spacetime expands less rapidly and
the energy density drops faster.
Assessing expert reliability in determining intracranial EEG channel quality and introducing the automated bad channel detection algorithm
Authors: Hattab Tariq , König Seth D , Carlson Danielle C , Hayes Rebecca F , Sha Zhiyi , Park Michael C , Kahn Lora , Patel Sima , McGovern Robert A , Henry Thomas , Khan Fawad , Herman Alexander B , Darrow David P
Published: July 2024

Objective. To evaluate the inter- and intra-rater reliability for the identification of bad channels among neurologists, EEG Technologists, and naïve research personnel, and to compare their performance with the automated bad channel detection (ABCD) algorithm for detecting bad channels. Approach. Six Neurologists, ten EEG Technologists, and six naïve research personnel (22 raters in total) were asked to rate 1440 real intracranial EEG channels as good or bad. Intra- and interrater kappa statistics were calculated for each group. We then compared each group to the ABCD algorithm which uses spectral and temporal domain features to classify channels as good or bad. Main results. Analysis of channel ratings from our participants revealed variable intra-rater reliability within each group, with no significant differences across groups. Inter-rater reliability was moderate among neurologists and EEG Technologists but minimal among naïve participants. Neurologists demonstrated a slightly higher consistency in ratings than EEG Technologists. Both groups occasionally misclassified flat channels as good, and participants generally focused on low-frequency content for their assessments. The ABCD algorithm, in contrast, relied more on high-frequency content. A logistic regression model showed a linear relationship between the algorithm’s ratings and user responses for predominantly good channels, but less so for channels rated as bad. Sensitivity and specificity analyses further highlighted differences in rating patterns among the groups, with neurologists showing higher sensitivity and naïve personnel higher specificity. Significance. Our study reveals the bias in human assessments of intracranial electroencephalography (iEEG) data quality and the tendency of even experienced professionals to overlook certain bad channels, highlighting the need for standardized, unbiased methods. The ABCD algorithm, outperforming human raters, suggests the potential of automated solutions for more reliable iEEG interpretation and seizure characterization, offering a reliable approach free from human biases.
Magnetic nanomaterials mediate precise magnetic therapy
Authors: Liu Sha , Sun Jianfei
Published: July 2024

Magnetic nanoparticle (MNP)-mediated precision magnet therapy plays a crucial role in treating various diseases. This therapeutic strategy compensates for the limitations of low spatial resolution and low focusing of magnetic stimulation, and realizes the goal of wireless teletherapy with precise targeting of focal areas. This paper summarizes the preparation methods of magnetic nanomaterials, the properties of magnetic nanoparticles, the biological effects, and the measurement methods for detecting magnetism; discusses the research progress of precision magnetotherapy in the treatment of psychiatric disorders, neurological injuries, metabolic disorders, and bone-related disorders, and looks forward to the future development trend of precision magnet therapy.
Physics to the frontline
Authors: Banks Michael
Published: July 2024

Holly Tann and Adam McQuire talk to Michael Banks about how their non-profit organization Casus Pax is helping people in Ukraine.
Does upright radiotherapy offer hope or hype?
Authors: Freeman Tami
Published: July 2024

Speakers at this year’s ESTRO 2024 meeting in Glasgow discussed the potential for upright treatment to increase patient access to radiotherapy, as Tami Freeman reports.
Political impact
Authors: Durrani Matin
Published: July 2024

This issue touches on politics – but not in the way you might think.
From death rays to antimatter
Authors: Pancheri Giulia
Published: July 2024

Bruno Touschek was an Austrian-born theoretical physicist who proposed what became the world’s first circular particle collider. But as Giulia Pancheri describes, few colleagues were aware of a dark past, which saw him work on a “death-ray” device for the Nazi military.
Thinking like a scientist
Authors: Amsen Eva
Published: July 2024

Eva Amsen reviews Third Millennium Thinking: Creating Sense in a World of Nonsense by Saul Perlmutter, John Campbell and Robert MacCoun.
Çiğdem İşsever on the importance of thinking about physics early
Authors: Lea Rob
Published: July 2024

Çiğdem İşsever is an elementary particle physicist who works with the Large Hadron Collider detector ATLAS. She tells Rob Lea about her work at CERN and the importance of early and engaging science communication.
Sediment ballast accelerates sinking of Alaska North Slope crude oil measured ex situ with surface water from Cook Inlet
Authors: Ross Jesse , Kinner Nancy , Saupe Susan , Ziervogel Kai
Published: July 2024

Oil spilled into the ocean interacts with suspended matter forming aggregates that transport oil into subsurface layers and towards the bottom. We conducted a series of laboratory experiments to explore aggregation of oil with natural phytoplankton assemblages from Cook Inlet, Alaska at three times during a spring bloom. Oil and phytoplankton formed marine oil snow (MOS) that remained positively buoyant with a small fraction of MOS sinking to the bottom of our experimental bottles. Seawater treatments amended with suspended sediments formed oil-mineral aggregates (OMAs) with an oil capacity similar to MOS (∼20% of aggregate area was covered with oil). OMAs accelerated oil sedimentation in our bottles relative to MOS sedimentation underlining the significance of suspended matter as ballast for sinking oil. Our results reveal potential transport mechanisms of oil in Cook Inlet which apply to other coastal systems with high productivity and sediment loads.
Identification of end-milling chatter based on comprehensive feature fusion
Authors: Matthew Dialoke Ejiofor , Cao Hongrui , Shi Jianghai
Published: July 2024

The main barrier impeding the advancement of high-speed milling is chatter, which has a detrimental effect on the dimensional accuracy and quality of the finished workpiece. A reliable and precise chatter identification method is essential to improving the quality of machining. This paper presents a novel method for chatter identification using a comprehensive feature fusion of the Short-Time Fourier Transform (STFT) and the Fourier Synchrosqueezing Transform (FSST). The Wavelet Packet Transform (WPT) was used to pre-process the collected vibration and force signals. Wavelet packets with rich chatter information were then selected and reconstructed for further analysis. To reduce the effects of the rotating frequency and generate a hybrid spectrum with high resolution, a Gabor time-frequency filter is employed. As chatter indicators, standard deviation, skewness, and root mean square are computed. With a higher Time-Frequency Representation (TFR) resolution and a shorter computation time of 0.46 and 0.97 s across vibration and force signals, the proposed method outperforms conventional STFT and FSST. As a result, it can be used to reliably identify chatter from the onset, which is beneficial for machining monitoring.
Solving deep-learning density functional theory via variational autoencoders
Authors: Costa Emanuele , Scriva Giuseppe , Pilati Sebastiano
Published: July 2024

In recent years, machine learning models, chiefly deep neural networks, have revealed suited to learn accurate energy-density functionals from data. However, problematic instabilities have been shown to occur in the search of ground-state density profiles via energy minimization. Indeed, any small noise can lead astray from realistic profiles, causing the failure of the learned functional and, hence, strong violations of the variational property. In this article, we employ variational autoencoders (VAEs) to build a compressed, flexible, and regular representation of the ground-state density profiles of various quantum models. Performing energy minimization in this compressed space allows us to avoid both numerical instabilities and variational biases due to excessive constraints. Our tests are performed on one-dimensional single-particle models from the literature in the field and, notably, on a three-dimensional disordered potential. In all cases, the ground-state energies are estimated with errors below the chemical accuracy and the density profiles are accurately reproduced without numerical artifacts. Furthermore, we show that it is possible to perform transfer learning, applying pre-trained VAEs to different potentials.
Modular linear differential operators and generalized Rankin-Cohen brackets
Authors: Nagatomo Kiyokazu , Sakai Yuichi , Zagier Don
Published: July 2024

The aim of this paper is to give expressions for modular linear differential operators (MLDOs) of any order. In particular, we show that they can all be described in terms of Rankin-Cohen brackets and a modified Rankin-Cohen bracket found by Kaneko and Koike. We also give more uniform descriptions of MLDOs in terms of canonically defined higher Serre derivatives and an extension of Rankin-Cohen brackets, as well as in terms of quasimodular forms and almost holomorphic modular forms. The last of these descriptions involves the holomorphic projection map. The paper also includes some general results on the theory of quasimodular forms on both cocompact and non-cocompact subgroups of 

S

L
2

(

R

)

SL_2(\mathbb {R})

, as well as a slight sharpening of a theorem of Martin and Royer on Rankin-Cohen brackets of quasimodular forms.
Social Psychological Processes Underlying Collective Action in Repressive Contexts: What We Know and Ways Forward for Future Research
Authors: Ayanian Arin H , Tausch Nicole , Saab Rim
Published: July 2024

Social psychological research recently gained momentum in studying collective action in more repressive and non-democratic contexts. The present chapter provides a detailed account of the social psychological processes underlying engagement in nonviolent collective action at a micro (individual) level when facing risks of repression, and how perceived repression shapes these processes. We draw on our quantitative findings from Egypt, Russia, Ukraine, Hong Kong, and Turkey. We locate our work within the broader interdisciplinary literature. We also propose possible directions research can take to further our understanding of collective action in repressive contexts. Among others, we highlight the need to explore in more detail the nature of repression (e.g., type, severity, duration) and identities (e.g., multiple identities, non-unified movement), compare authoritarian and democratic contexts, and consider different antecedents (e.g., affective loyalties, contextual and cultural factors) and consequences (e.g., well-being). We discuss challenges for future research and implications for protest leaders and organizers.
Social Psychological Dynamics of Repression and Resistance to Repression: Insights From the October 2019 Lebanese Uprising
Authors: Saab Rim , Ayanian Arin H , Adra Aya , Badaan Vivienne
Published: July 2024

Inspired by our lived experience of the October 17 Lebanese uprising in 2019, we propose a framework to advance our understanding of the social psychological dynamics of repression and counter-repression. The framework draws on the growing social psychological literature on antecedents of collective action (e.g., injustice, efficacy, identity, anger, social motive, reward motive), which we term “social psychological capital of collective action.” We argue that to the extent that repression aims to demobilize a social movement by undermining the social psychological capital of collective action, effective counter-repression would consist of (a) identifying the targeted social psychological mechanisms of demobilization, and (b) fighting repression through actions aimed at preserving and reinforcing the threatened social psychological capital of collective action. We illustrate these dynamics with examples from the Lebanese uprising pertaining to perceived injustice, efficacy, personal costs and fear, and identity. We discuss limitations, future research directions, and potential implications for activists.
Digital Interfaces of Repression and Resistance
Authors: Uyheng Joshua , Montiel Cristina Jayme
Published: July 2024

This chapter proposes a discursive view of how digital technologies feature in the social psychologies of repression and resistance in a repressive state. Contemporary authoritarian states increasingly assimilate digital technologies to misinform and repress publics. In counterforce, social resistance harnesses these tools to promote public truth and, cloaked by digital anonymity, protect oppositionists from state harassment. We conceptualize digital space as a political sphere for multi-layered practices of agency in authoritarian societies. Invoking the Philippine experience during the rollout of an anti-terrorism law, we highlight asymmetrical social psychological relations in the political clash, and the necessity for consolidating meso-level and micro-level technological forces against a powerful digitalized state. Finally, we suggest novel, interdisciplinary directions for the study of digital resistance in authoritarian states and beyond.
Expanding the Timeline of Resistance
Authors: Moss Sigrun Marie , Elgizouli Ubai Kamal
Published: July 2024

Scholars have urged psychology to attend more to history, which is also key to understanding the psychology of resistance. Resistance entails struggles grounded in perceived wrongs in the past and present, and vying for a better future. Therefore, we call for expanding the timeline of resistance in research on the psychology of resistance. Using the revolution in Sudan as an example, we unpack how history helps psychology understand dynamics of resistance. We discuss Sudanese perceptions of this resistance as a long-term, anticipated phenomenon rather than a surprising change. Attending to what comes before momentous outbreaks of resistance allows for a better understanding of that resistance. Resistance movements learn from history, and historical narratives of past resistance inform their choices. Importantly, repressive regimes also learn from past resistance and adjust their demobilization accordingly. Both resistance and repression should therefore be analyzed with the before in mind.
The Social World of the Dhobis
Authors: Mitra Channa Subhadra
Published: July 2024

This chapter is about the dhobi community, the polysemic definition of the term biradari, where it covers various levels of identification, from the broadest level of all dhobis across India to the small endogamous community in which they invest their emotions and closest kin and marital relations. The notion of jati is described, along with its appropriateness to be used in the text as against caste. A theoretical discussion on caste as a concept is included. The continuity of the biradari and the relation of biradari to the caste occupation are demonstrated. The chapter also contains a detailed description of gendered life in the dhobi settlements known as katras and describes how the dhobis make efforts to rebuild community life even if they relocate to places other than their original residence within Old Delhi.
Enrolling high-acuity emergency general surgery patients in a prospective longitudinal cohort study
Authors: Baselice Holly , Kellett Whitney , McCarty Adara , Wisler Jon , Santry Heena
Published: July 2024

Over 3 million patients are admitted to hospitals annually with high-acuity conditions mandating emergency abdominal or skin/soft-tissue operations. Patients with these high-acuity emergency general surgery (HA-EGS) diseases experience significant morbidity and mortality, yet the quality-of-life impact on survivors is not well studied. Acuity, transfer patterns, and adverse social determinants of health documented in epidemiologic studies are cited reasons for inability to measure patient-reported outcomes among HA-EGS survivors. We conducted a feasibility study to understand facilitators/barriers to conducting prospective studies of changes in quality of life after surviving HA-EGS. From September 2019 to April 2021, we collected baseline (preadmission) and 30/60 days’ postsurgery data on activities of daily living, depression, self-efficacy, resilience, pain, work limitations, social support, and substance use from patients who enrolled in the study during index hospitalization. One hundred patients consented to participate (71.9% enrollment rate). The retention rate was 65.9% for 30-day follow-up telephone calls and 53.8% for 60-day follow-up calls. Median time needed to complete each time point remained under 25 minutes. Patients with a longer length of stay and nicotine users had higher odds of not completing their 30­day interview, while those with systemic complications had higher odds of not completing their 60­day interview. These results lay the foundation for future patient-reported outcome studies.
GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction
Authors: Zhou Guoqiang , Qin Yuke , Hong Qiansen , Li Haoran , Chen Huaming , Shen Jun
Published: July 2024

Accurate prediction of protein–ligand binding affinity (PLA) is important for drug discovery. Recent advances in applying graph neural networks have shown great potential for PLA prediction. However, existing methods usually neglect the geometric information (i.e. bond angles), leading to difficulties in accurately distinguishing different molecular structures. In addition, these methods also pose limitations in representing the binding process of protein–ligand complexes. To address these issues, we propose a novel geometry-enhanced mid-fusion network, named GEMF, to learn comprehensive molecular geometry and interaction patterns. Specifically, the GEMF consists of a graph embedding layer, a message passing phase, and a multi-scale fusion module. GEMF can effectively represent protein–ligand complexes as graphs, with graph embeddings based on physicochemical and geometric properties. Moreover, our dual-stream message passing framework models both covalent and non-covalent interactions. In particular, the edge-update mechanism, which is based on line graphs, can fuse both distance and angle information in the covalent branch. In addition, the communication branch consisting of multiple heterogeneous interaction modules is developed to learn intricate interaction patterns. Finally, we fuse the multi-scale features from the covalent, non-covalent, and heterogeneous interaction branches. The extensive experimental results on several benchmarks demonstrate the superiority of GEMF compared with other state-of-the-art methods.