bluuebunny/crossref_metadata_2025_split huggingface dataset:
Private and well drinking water are reservoirs for antimicrobial resistant bacteria
Authors: Alawi Marwa , Smyth Cian , Drissner David , Zimmerer Anna , Leupold Denise , Müller Daria , Do Thi Thuy , Velasco-Torrijos Trinidad , Walsh Fiona 
Published: March 2024

AbstractWater quality testing does not recognise antimicrobial resistance (AMR) and is often limited to indicators of faecal contamination Escherichia coli and Enterococcus species. In Europe, data on AMR in drinking water is scarce. In Ireland, as in many countries, household drinking water is supplied via mains or via private wells or water schemes. Using citizen science, we identified Irish private drinking water supplies as reservoirs of antimicrobial resistant bacteria (ARB). Gram-negative (n = 464) and Gram-positive (n = 72) bacteria were isolated. We identified instances of potentially opportunistic ARB such as Enterobacter cloacae, Acinetobacter baumannii and Enterococcus species. We report reservoirs of multidrug resistance in Enterococcus casseliflavus, E. cloacae, E. coli, Stenotrophomonas maltophilia, and Serratia rubidaea. We also identified linezolid-resistant Enterococcus in Irish drinking water. Linezolid is a last-resort antibiotic used to treat vancomycin-resistant Enterococcus sp. Additionally, we identified mobile AMR in three water samples, two of which were carried on IncF group, one on IncQ and five on Col-like plasmids. Our work suggests that private drinking water is a potential sink and source of AMR pathogens. This highlights a value of drinking water surveillance in a One Health framework as the surveillance would provide information regarding the movement and persistence of ARB and ARGs that are able to survive in drinking water and subsequently have the opportunity to be mobilised through humans; linking the environment to the human and potentially threatening human health.
New plastids, old proteins: repeated endosymbiotic acquisitions in kareniacean dinoflagellates
Authors: Novák Vanclová Anna MG , Nef Charlotte , Füssy Zoltán , Vancl Adél , Liu Fuhai , Bowler Chris , Dorrell Richard G 
Published: March 2024

AbstractDinoflagellates are a diverse group of ecologically significant micro-eukaryotes that can serve as a model system for plastid symbiogenesis due to their susceptibility to plastid loss and replacement via serial endosymbiosis. Kareniaceae harbor fucoxanthin-pigmented plastids instead of the ancestral peridinin-pigmented ones and support them with a diverse range of nucleus-encoded plastid-targeted proteins originating from the haptophyte endosymbiont, dinoflagellate host, and/or lateral gene transfers (LGT). Here, we present predicted plastid proteomes from seven distantly related kareniaceans in three genera (Karenia, Karlodinium, and Takayama) and analyze their evolutionary patterns using automated tree building and sorting. We project a relatively limited ( ~ 10%) haptophyte signal pointing towards a shared origin in the family Chrysochromulinaceae. Our data establish significant variations in the functional distributions of these signals, emphasizing the importance of micro-evolutionary processes in shaping the chimeric proteomes. Analysis of plastid genome sequences recontextualizes these results by a striking finding the extant kareniacean plastids are in fact not all of the same origin, as two of the studied species (Karlodinium armiger, Takayama helix) possess plastids from different haptophyte orders than the rest.
Construction personnel dress code detection based on YOLO framework
Authors: Lyu Yunkai , Yang Xiaobing , Guan Ai , Wang Jingwen , Dai Leni 
Published: March 2024

AbstractIt is important for construction personnel to observe the dress code, such as the correct wearing of safety helmets and reflective vests is conducive to protecting the workers' lives and safety of construction. A YOLO network‐based detection algorithm is proposed for the construction personnel dress code (YOLO‐CPDC). Firstly, Multi‐Head Self‐Attention (MHSA) is introduced into the backbone network to build a hybrid backbone, called Convolution MHSA Network (CMNet). The CMNet gives the model a global field of view and enhances the detection capability of the model for small and obscured targets. Secondly, an efficient and lightweight convolution module is designed. It is named Ghost Shuffle Attention‐Conv‐BN‐SiLU (GSA‐CBS) and is used in the neck network. The GSANeck network reduces the model size without affecting the performance. Finally, the SIoU is used in the loss function and Soft NMS is used for post‐processing. Experimental results on the self‐constructed dataset show that YOLO‐CPDC algorithm has higher detection accuracy than current methods. YOLO‐CPDC achieves a mAP50 of 93.6%. Compared with the YOLOv5s, the number of parameters of our model is reduced by 18% and the mAP50 is improved by 1.1%. Overall, this research effectively meets the actual demand of dress code detection in construction scenes.
Miniaturised high‐isolation K‐/Ka‐band diplexer with 3D antarafacial channel integration using vertical quasi‐coaxial matching network
Authors: Zhou Yujin , Wei Haoyu , Zhou Jun , Cheng Chonghu , Cheng Yong 
Published: March 2024

AbstractA miniaturised high‐isolation K‐/Ka‐band diplexer with exceeding adjacent channels using 3D antarafacial channel integration and vertical‐quasi‐coaxial‐based matching network is proposed. For smaller size, lower loss and lower channel interference, the high‐order low‐pass filter for the K‐band channel and the four‐line‐interdigital‐coupled wideband bandpass filter for the Ka‐band channel are respectively designed on two low‐loss glass‐based substrates, and these two substrates are integrated on the two antarafacial surface of the mounting board. The vertical‐quasi‐coaxial (VQC) embedded in the mounting board is not only used as three‐dimensional (3D) interconnection of the two antarafacial channels but also designed as the constituent part of the matching/isolation network, and this can effectively decrease the impedance traction caused by the Ka‐band filter for the K‐band channel of the diplexer. In addition, four transmission zeros of the K‐band filter are designed at the whole passband of the Ka‐band channel to improve the isolation to the K‐band channel for guaranteeing the performance of the diplexer at the Ka‐band channel. Furthermore, working principle, design method and test solution of this proposed K‐/Ka‐band diplexer are well illustrated, and the high‐isolation (>40 dB) in very adjacent wideband channels at K‐band (18–23.5 GHz) and Ka‐band (25.8–31.6 GHz) is achieved within a tiny size of 9 × 4 × 0.87 mm.
Gradient‐based eigenvalue optimization for electromagnetic cavities with built‐in mode matching
Authors: Ziegler Anna , Hahn Robert , Isensee Victoria , Nguyen Anh Duc , Schöps Sebastian 
Published: March 2024

AbstractShape optimization with respect to eigenvalues of a cavity plays an important role in the design of new resonators or in the optimization of existing ones. This paper proposes a gradient‐based optimization scheme, which is enhanced with closed‐form shape derivatives of the system matrices. Based on these, accurate derivatives of eigenvalues, eigenmodes, and the cost function can be computed with respect to the geometry, which significantly reduces the computational effort of the optimizer. The work is demonstrated by applying it to the 9‐cell TESLA cavity, for which the design parameters of the computational model are considered as optimization variables to match the design criteria for devices in realistic use cases. Since eigenvalues may cross during the shape optimization of a cavity, a new algorithm based on an eigenvalue matching procedure is proposed, to ensure the optimization of the desired mode in order to also enable successful matching along large shape variations.
Driving STEM learning effectiveness: dropout prediction and intervention in MOOCs based on one novel behavioral data analysis approach
Authors: Xia Xiaona , Qi Wanxue 
Published: March 2024

AbstractWith the full application of MOOCs online learning, STEM multidisciplinary and knowledge structures have been achieved, but it has also resulted in a massive number of dropouts, seriously affected the learning sustainability of STEM education concepts, and made it difficult to achieve learning effectiveness. Based on the massive STEM learning behavior instances generated by MOOCs, as well as the entire learning periods, this study considers some key explicit and implicit features associated with learning behavior, and achieves the fusion of convolutional neural network and recurrent neural network through data-driven approaches, incorporates long short-term memory mechanism to develop dropout prediction methods and models. Based on the experimental results, we also discuss the relevant problems of dropouts related to STEM learning behavior, explore the key dropout temporal sequences of the learning process, identify related factors that have key impacts on learning behavior, and deduce intervention measures and early warning suggestions. The entire study can provide effective methods and decisions for researching the STEM learning behavior of MOOCs and has strong research feasibility and urgency.
Dictionaries and lexicography in the AI era
Authors: Lew Robert 
Published: March 2024

AbstractThis paper examines the implications of AI and machine translation on traditional lexicography, using three canonical scenarios for dictionary use: text reception, text production, and text translation as test cases. With the advent of high-capacity, AI-driven language models such as OpenAI’s GPT-3 and GPT-4, and the efficacy of machine translation, the utility of conventional dictionaries comes under question. Despite these advancements, the study finds that lexicography remains relevant, especially for less-documented languages where AI falls short, but human lexicographers excel in data-sparse environments. It argues for the importance of lexicography in promoting linguistic diversity and maintaining the integrity of lesser-known languages. Moreover, as AI technologies progress, they present opportunities for lexicographers to expand their methodology and embrace interdisciplinarity. The role of lexicographers is likely to shift towards guiding and refining increasingly automated tools, ensuring ethical linguistic data use, and counteracting AI biases.
Deciphering the conformational preference and ionization dynamics of tetrahydrofuran: Insights from advanced spectroscopic techniques
Authors: Park Sung Man , Kwon Chan Ho 
Published: March 2024

Tetrahydrofuran (THF) has garnered significant attention due to its pivotal role in biological and chemical processes. The diverse array of conformations exhibited by THF profoundly impacts its reactivity and interactions with other molecules. Understanding these conformational preferences is crucial for comprehending its molecular behavior. In this study, we utilize infrared (IR) resonant vacuum ultraviolet photoionization/mass-analyzed threshold ionization (VUV-PI/MATI) mass spectroscopies to capture distinctive vibrational spectra of individual conformers, namely, “twisted” and “bent,” within THF. Our conformer-specific vibrational spectra provide valuable insights into the relative populations of these two conformers. The analysis reveals that the twisted (C2) conformer is more stable than the bent (CS) conformer by 17 ± 15 cm−1. By precisely tuning the VUV photon energy to coincide with vibrational excitation via IR absorption, we selectively ionize specific conformers, yielding two-photon IR + VUV-PI/MATI spectra corresponding to the twisted and bent conformers. This investigation conclusively affirms that both the twisted and bent conformers coexist in the neutral state, while only the twisted conformer exists in the cationic state. These findings not only bridge gaps in existing knowledge but also provide profound insights into the behavior of this pivotal molecule in the realms of biology and medicine.
Optimization of the gamma reaction history diagnostic for double-shell pusher areal density and reaction history measurements on the National Ignition Facility
Authors: Dwyer R. H. , Meaney K. D. , Geppert-Kleinrath H. , Loomis E. N. , Robey H. F. , Mohamed Z. L. , Fry C. , Kim Y. 
Published: March 2024

The double-shell inertial confinement fusion campaign, which consists of an aluminum ablator, a foam cushion, a high-Z pusher (tungsten or molybdenum), and liquid deuterium–tritium (DT) fuel, aims for its first DT filled implosions on the National Ignition Facility (NIF) in 2024. The high-Z, high density pusher does not allow x-rays to escape the double-shell capsule. Therefore, nuclear diagnostics such as the Gamma Reaction History (GRH) diagnostic on the NIF are crucial for understanding high-Z implosion performance. To optimize the GRH measurement of fusion reaction history and the pusher’s areal density, the MCNP6.3-based forward model of the detector was built. When calculating the neutron-induced inelastic gamma ray production, the interaction of neutrons with the compressed fuel was additionally included. By folding the calculated gamma ray spectrum output and the previously calibrated GRH detector responses, the optimum set of GRH energy thresholds for measuring the pusher areal density is determined to be 2.9 and 6.3 MeV for DT double-shell experiments. In addition, the effect of the down-scattering of neutrons on the gamma ray spectrum, the minimum required yield for measurements, and the attenuation of the gamma rays through the pusher are analyzed.
Pulsed voltage cold atmospheric plasma jet and gold nanoparticles enhance cytotoxic anticancer effect
Authors: Schweigert I , Biryukov M , Polyakova A , Krychkova N , Gorbunova E , Epanchintseva A , Pyshnaya I , Zakrevsky Dm , Milakhina E , Koval O 
Published: March 2024

Abstract
Efficient and biologically safe mode of cold atmospheric plasma jet (CAPJ) is crucial for the development of CAPJ-based anticancer therapy. In the experiment and numerical simulations, by changing the pulse duration of a positive-pulsed (PP) voltage, we found the optimal CAPJ modes with a regular streamer propagation and a maximum discharge current at a temperature

T
<

42 ∘C. These CAPJs substantially suppressed the viability of cancer cells. To enhance a cytotoxic effect of CAPJ treatment, gold nanoparticles (NPs) were added to the cells before and after the CAPJ exposure. Combination of CAPJ, generated with the PP voltage, and gold NPs decreased the viability of NCI-H23 epithelial-like lung adenocarcinoma, A549 lung adenocarcinoma, BrCCh4e-134 breast adenocarcinoma and uMel1 uveal melanoma cells. Polyethylene glycol-modified NPs with attached fluorescent labels were used to visualize the uptake of NPs. We demonstrated that NPs efficiently entered the cells when were added to the cells just before CAPJ exposure or up to two hours afterwards. The efficiency of NPs penetration into cells positively correlated with the induced cytotoxic effect: it was maximal when NPs was added to cells right before or immediately after CAPJ exposure. Summarizing, the treatment with optimal CAPJ modes in combination with modified NPs, bearing the cancer-addressed molecules and therapeutics may be the next strategy of strengthening the CAPJ-based antitumor approaches.
Signatures of quantum phases in a dissipative system
Authors: Joshi Rohan , Mondal Saikat , Bandyopadhyay Souvik , Bhattacharjee Sourav , Agarwala Adhip 
Published: March 2024

Abstract
Lindbladian formalism, as tuned to dissipative and open systems, has been all-pervasive to interpret non-equilibrium steady states of quantum many-body systems. We study the fate of free fermionic and superconducting phases in a dissipative one-dimensional Kitaev model—where the bath acts both as a source and a sink of fermionic particles with different coupling rates. As a function of these two couplings, we investigate the steady state, its entanglement content, and its approach from varying initial states. Interestingly, we find that the steady state phase diagram retains decipherable signatures of ground state critical physics. We also show that early-time fidelity is a useful marker to find a subclass of phase transitions in such situations. Moreover, we show that the survival of critical signatures at late-times, strongly depend on the thermal nature of the steady state. This connection hints at a correspondence between quantum observables and classical magnetism in the steady state of such systems. Our work uncovers interesting connections between dissipative quantum many-body systems, thermalization of a classical spin and many-body quantum critical phenomena.
A polynomial model with line-of-sight constraints for Lagrangian particle tracking under interface refraction
Authors: Zeng Xin , Qu Hao , He Chuangxin , Liu Yingzheng , Gan Lian 
Published: March 2024

Abstract
This paper introduces an improvement of the ‘shake-the-box (STB)’ (Schanz, Gesemann, and Schröder, Exp. Fluids 57.5, 2016) technique using the polynomial calibration model and the line-of-sight constraints (LOSC) to overcome the refractive interface issues in Lagrangian particle tracking (LPT) measurement. The method (named LOSC-LPT) draws inspiration from the two-plane polynomial camera calibration in tomographic particle image velocimetry (Worth, Nickels, Thesis, 2010) and the STB-based open-source Lagrangian particle tracking (OpenLPT) framework (Tan, Salibindla, Masuk, and Ni, Exp. Fluids 61.2, 2019). The LOSC-LPT introduces polynomial mapping functions into STB calibration in conditions involving gas–solid–liquid interfaces at container walls exhibiting large refractive index variations, which facilitates the realization of particle stereo matching, three-dimensional (3D) triangulation, iterative particle reconstruction, and further refinement of 3D particle position by shaking the LOS. Performance evaluation based on synthetic noise-free images with a particle image density of 0.05 particle per pixel in the presence of refractive interfaces demonstrates that LOSC-LPT can detect a higher number of particles and exhibits lower position uncertainty in the reconstructed particles, resulting in higher accuracy and robustness than that achieved with OpenLPT. In the application to an elliptical jet flow in an octagonal tank with refractive interfaces, the use of polynomial mapping results in smaller errors (mean calibration error <0.1 px) and thus more long trajectories identified by LOSC-LPT (13 000) compared with OpenLPT (4500) which uses the pinhole Tsai model (mean calibration error >1.0 px). Moreover, 3D flow-field reconstructions demonstrate that the LOSC-LPT framework can recover a more accurate 3D Eulerian flow field and capture more complete coherent structures in the flow, and thus holds great potential for widespread application in 3D experimental fluid measurements.
A digital twin library of mechanical transmission system for the application of small sample fault diagnosis problem
Authors: Meng Xianglong , Hu Tianliang , Li Jinfeng , Zhang Yan , Ma Songhua 
Published: March 2024

Abstract
Timely and accurate fault diagnosis of transmission systems is crucial to ensuring the systems’ reliability, safety, and economic viability. However, intelligent fault diagnosis algorithms require a lot of labeled data for training, which may not be available and accessible, especially for many critical devices. This hinders the application of some excellent diagnosis methods in real industry. Digital twin (DT), as an advanced cyber-physical integration method, can be utilized to generate rich fidelity data with virtual models to overcome the dilemma of insufficient data, especially for the small sample problem. We propose the DT library to model the mechanical transmission system with various faults for the data augmentation of the small sample problem. In the library, common components in mechanical transmission systems are modular and digitalized into several differential equations. They can compose a mechanical transmission system digital twin (TSDT) and be injected with various faults to simulate the transmission signal, and even replace the physical experimental platform. The simulation data is used as a pre-training dataset, which can be imported into the transfer learning method for the fault diagnosis. After several verifications, it can be concluded that the simulation data from TSDT is effective in transfer ability and fault feature learning, which significantly improves fault recognition accuracy in the small sample problem.
Multilayer modeling framework for analyzing thermo-mechanical properties and responses of twisted and coiled polymer actuators
Authors: Gao Zhiwen , Guo Juanjuan , Zhang Yuhao , Zhou Zhiwen , Zhang Cennan , Li Hua , Chen Bin , Wang Jizeng 
Published: March 2024

Abstract
The twisted and coiled polymer actuator (TCPA) has a complex multi-scale structure consisting of crystalline micro-fibrils and an amorphous matrix at the micro-scale, which are organized into a macro-scale fiber. When the polymer fiber undergoes twisting and coiling, its mechanical and thermal properties become variable. In this study, we developed a multi-layer modeling framework capable of accurately predicting the effective mechanical and thermal properties, as well as the thermo-mechanical responses of the TCPA. Our numerical results demonstrate that the effective mechanical and thermal properties of the TCPA are influenced by the radius and twisting angle of the polymer fiber. By analyzing the precise mechanical and thermal properties, the numerical calculated driving responses exhibit good agreement with experimental data. We also examined the influence of initial helical radius, helical pitch and fiber radius on the driving responses of the TCPA. The proposed numerical model can be further utilized to optimize the driving responses of the TCPA by adjusting geometric parameters and the twisting angle of the polymer fiber.
FEA and CFD analysis and optimization of tube in tube heat exchanger for various cases
Authors: Shah Abhijeet , Wasnik Ankit , Patil Ajinkya 
Published: March 2024

Abstract
This research describes the use of advanced simulation techniques to investigate use of different materials for a tube-in-tube heat exchanger. Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations are employed to simulate thermal aspects and optimize the heat exchanger design. The objective is to identify the best-Suitable material combination considering both design and thermal considerations. The findings of this research contribute to the development of more efficient heat exchanger designs.
Leveraging the strain transfer at the interface between self-composite CoFe2O4 embedded in pre-sintered Na0.5Bi0.5TiO3 ceramics matrix for the enhancement of magnetoelectric voltage coefficient
Authors: Dharsini P M Priya , Priya Bhadra , Nandakumar K , Sundarakannan B 
Published: March 2024

Abstract
Magnetoelectric particulate composite (100-x) NBT- xCFO(sc) (x = 5,15,25,35) were prepared from pre-sintered NBT and self-composite CFO(sc) by solid-state reaction route. XRD, SEM, and Raman studies confirm the biphasic composite formation without diffusion at the interfaces. Unsaturated ferroelectric loops and enhanced ferromagnetic properties are evidenced. ME coefficient value is enhanced to 25.1 mV cm−1 Oe in the N65SC35 composite which is the greatest among the reported values in the literature of NBT-CFO composites. The enhancement is due to the effective strain transfer at the interfaces of the composites. This is explained by a simple dimensionless quantity, degree of interface. This quantity is defined using the interface length of ferroelectric-ferromagnetic phases and the weighted average grain size which corroborates the enhancement of the ME coefficient.