bluuebunny/crossref_metadata_2025 huggingface dataset:
What are the main reasons for the worldwide decline in pollinator populations?
Authors: Brunet Johanne , Fragoso Fabiana P.
Published: May 2024

Pollinator populations are declining worldwide and over 87% of flowering plant species and 87 of the leading global food crops rely on pollinators for seed production. Pollinator decline seriously impacts biodiversity conservation, reduces crop yield, and threatens food security. Understanding the drivers of pollinator decline can guide the development of strategies and action plans to protect and conserve pollinators and the essential ecosystem services they provide. This review introduces the diversity of pollinators, addresses the main drivers of pollinator decline, and presents strategies to reduce their negative impacts. We discuss how managed bees negatively affect wild bee species, and examine the impacts of habitat loss, pesticide use, pests and pathogens, pollution, and climate change on pollinator decline. Connections between humans and pollinator decline are addressed. Climate change emerges as the most prominent threat to pollinators and humans and the most difficult threat to control. The changes in water and temperature associated with climate change can lower the quantity and quality of resources available to pollinators, decrease the survival of larvae or adults, and modify suitable habitats. Climate change is a global issue and a serious threat to food security, and to world stability. Efforts to control the various factors that negatively impact pollinators must continue given the dire consequences.
Bacteria–organelle communication in physiology and disease
Authors: Lee Yi-Tang , Senturk Mumine , Guan Youchen , Wang Meng C.
Published: May 2024

Bacteria, omnipresent in our environment and coexisting within our body, exert dual beneficial and pathogenic influences. These microorganisms engage in intricate interactions with the human body, impacting both human health and disease. Simultaneously, certain organelles within our cells share an evolutionary relationship with bacteria, particularly mitochondria, best known for their energy production role and their dynamic interaction with each other and other organelles. In recent years, communication between bacteria and mitochondria has emerged as a new mechanism for regulating the host’s physiology and pathology. In this review, we delve into the dynamic communications between bacteria and host mitochondria, shedding light on their collaborative regulation of host immune response, metabolism, aging, and longevity. Additionally, we discuss bacterial interactions with other organelles, including chloroplasts, lysosomes, and the endoplasmic reticulum (ER).
First-principles study of the electronic and optical properties of two-dimensional PtS2/GaS van der Waals heterostructure
Authors: Zhu Min-Qi , Wang Xue-Feng
Published: May 2024

Heterostructures based on two-dimensional materials have received increasing attention due to their extraordinary properties and application potential. In this paper, the electronic and optical properties of the PtS2/GaS van der Waals (vdW) heterostructure as well as the effects of biaxial strain and external electric field are systematically investigated based on first-principles calculations. The PtS2/GaS vdW heterostructure has an interlayer distance of 3.01 Å and is a type-Ⅱ semiconductor of band gap 1.54 eV. Large optical absorption coefficients are observed in both the ultraviolet and the visible regions. Furthermore, its band structure can be effectively tuned by applying biaxial strain and external electric field. The transition between the type-Ⅱ and type-I band alignments can be realized. The absorption spectra and their peaks can be then manipulated effectively by applying biaxial strain with good stability under external electric field. The predicted tunable electronic properties and unique optical absorption properties suggests promising potential for the application of the PtS2/GaS vdW heterostructure in future optoelectronic nanodevices.
Muon spin relaxation and emergence of disorder-induced unconventional dynamic magnetic fluctuations in Dy2Zr2O7
Authors: Devi Sheetal , Biswas Pabitra K , Yokoyama K , Adroja D T , Yadav C S
Published: May 2024

The disordered pyrochlore oxide Dy2Zr2O7 shows the signatures of field-induced spin freezing with remnant zero-point spin-ice entropy at 5 kOe magnetic field. We have performed zero-field and longitudinal field Muon spin relaxation (µSR) studies on Dy2Zr2O7. Our zero field studies reveal the absence of both long-range ordering and spin freezing down to 62 mK. The µSR relaxation rate exhibits a temperature-independent plateau below 4 K, indicating a dynamic ground state of fluctuating spins similar to the well-known spin ice system Dy2Ti2O7. The low-temperature spin fluctuations persist in the longitudinal field of 20 kOe as well and show unusual field dependence of the relaxation rate, which is uncommon for a spin-liquid system. Our results, combined with the previous studies do not show any evidence of spin ice or spin glass ground state, rather point to a disorder-induced dynamic magnetic ground state in the Dy2Zr2O7 material.
Evaluation of consumer digital radon measurement devices: a comparative analysis
Authors: Bahadori Alexandra , Hanson Brian
Published: May 2024

Kansas State University (KSU) Engineering Extension conducted an abridged evaluation of eight consumer grade digital radon monitors. Using the KSU secondary radon chamber, these devices were exposed to three different radon concentrations for 7 d in average household temperature and relative humidity conditions. The three different radon concentration ranges used were: 12.8 pCi L−1 to 15.5 pCi L−1 (473.6 Bq m−3–573.5 Bq m−3), 27.7 pCi L−1 to 29.4 pCi L−1 (1024.9–10 857.8 Bq m−3), and ambient room level average radon concentration of 0.6 pCi L−1 (22.2 Bq m−3). The American National Standards Institute/American Academy of Radon Scientists and Technologists Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air (ANSI/AARST MS-PC) (ANSI/AARST MS-PC 2022 Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air (AARST Radon Standards)) minimum performance metrics were used to evaluate the accuracy and precision of each model type for each radon concentration tested. The eight different device models performed within the 0 ± 25% requirement for the individual percent error (IPE) for radon concentrations between 27.7 pCi L−1 and 29.4 pCi L−1 (1024.9–10 857.8 Bq m−3). For radon concentrations between 12.8 pCi L−1 and 15.5 pCi L−1 (444–592 Bq m−3) seven of the eight monitors fell within the IPE requirement and for ambient room radon concentrations six of the eight monitors fell within the IPE requirement for the ANSI/AARST MS-PC minimum performance requirement (ANSI/AARST MS-PC 2022 Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air (AARST Radon Standards)) ranges. All eight device models fell within the ± 15% ANSI/AARST MS-PC minimum performance requirement (ANSI/AARST MS-PC 2022 Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air (AARST Radon Standards)) coefficient of variation (CV) range for radon concentrations between 12.8 pCi L−1 and 15.5 pCi L−1 (444–592 Bq m−3) and for radon concentrations between 27.7 pCi L−1 and 29.4 pCi L−1 (1024.9–10 857.8 Bq m−3). In the future, evaluating the performance of these models over time to observe their long term accuracy and precision is anticipated.
A method for multi-view surface defect detection of Si3N4 ceramic bearing balls integrating features enhanced by the Gabor salient domain
Authors: Li Xinran , Chen Lei , Liu Shuai , Shao Meng , Hu Ronghua , Li Runzhe , Li Yuwei , An Dong
Published: May 2024

Si3N4 ceramic bearing balls exhibit wear, pits, scratches, and delamination defects on the surface during manufacturing processes. Current Si3N4 ceramic ball detection methods mainly focus on a single view input, which leads to insufficient fusion of boundary, color, and shape features, consequently resulting in a low detection accuracy. In this research, propose multi-view surface defect detection of Si3N4 ceramic bearing balls integrating features enhanced by the Gabor salient domain (GSMF). Firstly, color, shape, and boundary information of defects are extracted from different angles, distances, and GSMF enhancement views. Secondly, by designing a salient domain enhancement module, GSMF enhancement boundary features are extracted, addressing the feature loss problem that results in scarce border information during decoding. By improving the co-attention of multi-view to prevent memory loss caused by long-distance transmission, more feature information is preserved. Finally, the accuracy of the detection method is validated through experimental tests.
Small-sample linear profile error uncertainty assessment based on grey system
Authors: Zhang Ke , Chen Suan , Zhang Ruiyu
Published: May 2024

The uncertainty assessment of the profile error of the cam profile, as defined in the national standard method, is difficult to carry out under conditions of small sample size and absence of probability distribution assumptions. This paper proposes a small-sample assessment model for the uncertainty of the profile error based on grey system. Firstly, the coordinate transformation is conducted using Vector Alignment Method to reduce systematic errors, and the non-uniform rational B-splines curve interpolation is utilized to fit the cam profile curve and perform error assessment. Subsequently, based on the error assessment results, Grey Information Measurement Model (GIMM) for the uncertainty of the profile error in small samples is established. This model employs Grey Relational Analysis to eliminate outliers and evaluates the uncertainty of the profile error by solving grey correlation coefficients. Maximum-Minimum Information Measure Method is used to assess the optimal sample size. Finally, numerical experiments and experimental tests were conducted on the uncertainty of camshaft profile error in automobiles. A total of 15 sets of profile data were compared with Guide to the Representation of Uncertainty in Measurement (GUM) and Monte Carlo Method (MCM) under different sample sizes. The results showed that GIMM achieved evaluation with only 8 sets of data samples under small sample and poor information conditions, with an uncertainty of 0.6338 μm, compared to 0.6346 μm for GUM and 0.6391 μm for MCM. The acceptance rate of GIMM reached 95.2%. This model outperforms other methods, providing a simplified and reliable assessment of cam profile error uncertainty.
Accuracy improvement of a multi-ring beam structured inner surface measurement: via novel calibration methodology and light source optimization
Authors: Li Xiang , Deng Chunyu , Wu Yingna , Yang Tingting , Yang Rui , Ni Na , Xie Guangping
Published: May 2024

Parts with a large depth-to-diameter ratio play a critical role in the military, aerospace, and automotive industries. However, accurately measuring their inner surface profile remains challenging owing to the lack of adequate and accurate sensors. We developed a multi-ring structured light system to obtain three-dimensional data of inner contours, such as inner diameters, which are crucial for ensuring component performance and safety. In this study, we proposed three simple yet effective techniques to improve the multi-ring beam structured measurement system. First, we designed a distortion correction method to calibrate the imaging system. Second, a two-step calibration approach was used to calibrate the multi-ring projection. Meanwhile, we benchmarked the effects of different light sources on image speckles. The calibration results demonstrated that the coefficient of determination (R-2) used for line fitting exceeded 0.999. Moreover, the measurement experimental results show that the uncertainty of less than 10 µm and the smallest measurable pipe inner diameter can reach 15 mm, demonstrating that our methods are promising for improving the accuracy of structured light optical sensing systems. This system satisfies the measurement requirements and can be immediately utilized to meet the high demand for inner contour measurements in industrial applications.
Research on infrared spectroscopy detection of furfural content in transformer oil based on acetonitrile extraction
Authors: Tian Yi , Li Zhiwei , Wang Shuai , Zhu Guixin , Shi Haonan , Wang Yanru , Niu Bo , Zhu Yongcan , Huang Xinbo
Published: May 2024

The stable operation of power transformers depends on the oil-paper insulation system, in which the aging degree of insulating paper is the key to evaluate the remaining life of the transformer. Currently, methanol extraction is widely used to detect the furfural content in oil to evaluate the aging state of insulating paper, but it ignores the influence of methanol produced during the operation of the transformer on the extraction results. To address this issue, this paper proposes a new method that can replace methanol extraction for detecting furfural in oil through simulation and experiment. Firstly, through simulation and experiment, it is proved that the strong vibration absorption peaks at 1677 cm−1 for furfural carbonyl and 2240 cm−1 for acetonitrile cyano can be used to establish a new method for extracting furfural content in oil using acetonitrile. A quantitative model between the concentration x of furfural in the furfural-acetonitrile mixed solution and the area y of the infrared absorption peak at 1677 cm−1 is established, with a goodness of fit of 0.9974. Secondly, a comparison between direct detection and acetonitrile extraction methods is conducted. The results show that direct detection is simple to operate, but the minimum detection concentration is 40 mg l−1, which is difficult to meet practical requirements. Acetonitrile extraction can reduce the minimum detection concentration to 0.1 mg l−1. At the same time, the extraction conditions are analyzed to determine the extraction ratio of 30, extraction times of 5, and extraction rate of 60%. Finally, the proposed detection method is applied to thermal aging tests on insulating paper of different types. The experimental results show that the proposed method has good repeatability and improves the detection resolution of furfural content. This paper combines infrared spectroscopy with acetonitrile extraction technology to open up a more efficient and practical new method for detecting furfural content in transformer oil.
Tire defect detection based on low and high-level feature fusion
Authors: Wu Hao , Wang Yunfeng , Zhou Yi , Liu Xiyu , Zhai Xiaodi , Sun Kuizhi , Tian Chengliang , Li Tao , Jia Wenguang , Zhao Haixia , Zhang Yan
Published: May 2024

Recently, object detection based on deep learning has made great progress in the field of defect detection. Due to its complex texture background and varied defect features, existing defect detection methods based on object detection face great challenges in the detection of tire internal defects. In this paper, a tire defect detection model based on low and high-level feature fusion is proposed. First, a multi-head feature extraction module is proposed, which extracts abundant effective information from multiple dimensions. Second, a spatial semantic fusion upsampling module is proposed to alleviate the problem of information loss in the upsampling process. Finally, a novel prediction head is designed to expand the receptive field by compressing the size of the feature map to improve the detection accuracy of large defects. Experimental results show that the mAP of the proposed method achieves 94.03% on the tire internal defect dataset, and the average detection time is 36.74 ms, which can meet the needs of industrial online detection.
Advancements in nanoparticle-based therapies for multidrug-resistant candidiasis infections: a comprehensive review
Authors: Izadi Alireza , Paknia Fatemeh , Roostaee Maryam , Mousavi Seyed Amin Ayatollahi , Barani Mahmood
Published: May 2024

Candida auris, a rapidly emerging multidrug-resistant fungal pathogen, poses a global health threat, with cases reported in over 47 countries. Conventional detection methods struggle, and the increasing resistance of C. auris to antifungal agents has limited treatment options. Nanoparticle-based therapies, utilizing materials like silver, carbon, zinc oxide, titanium dioxide, polymer, and gold, show promise in effectively treating cutaneous candidiasis. This review explores recent advancements in nanoparticle-based therapies, emphasizing their potential to revolutionize antifungal therapy, particularly in combating C. auris infections. The discussion delves into mechanisms of action, combinations of nanomaterials, and their application against multidrug-resistant fungal pathogens, offering exciting prospects for improved clinical outcomes and reduced mortality rates. The aim is to inspire further research, ushering in a new era in the fight against multidrug-resistant fungal infections, paving the way for more effective and targeted therapeutic interventions.
Long time existence of the non-isentropic slightly compressible Navier-Stokes equations with boundary conditions
Authors: Ju Qiangchang , Xu Jianjun
Published: May 2024

We investigate the long time existence of smooth solutions to the initial boundary value problem for the non-isentropic slightly compressible Navier–Stokes equations with slip or non-slip boundary conditions on the velocity. We verify that the compressible Navier–Stokes equations with boundary conditions admit a unique smooth solution on the time interval where the smooth solution of the incompressible Navier–Stokes equations exists, when the Mach number is sufficiently small. Moreover, we obtain the uniform convergence of smooth solutions for the compressible system toward those for the corresponding incompressible system on that time interval.
Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach
Authors: Chang Zhuo , Peng Chen-Hao , Chen Kai-Jung , Xu Guang-Kui
Published: May 2024

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.
Uncertainty estimation and evaluation of deformation image registration based convolutional neural networks
Authors: Rivetti Luciano , Studen Andrej , Sharma Manju , Chan Jason , Jeraj Robert
Published: May 2024

Objective. Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challenges persist in proper uncertainty evaluation and hyperparameter optimization for these methods. This work aims to develop and evaluate a model that can perform fast DIR and predict its uncertainty in seconds. Approach. This study introduces a novel probabilistic multi-resolution image registration model utilizing convolutional neural networks to estimate a multivariate normal distributed dense displacement field (DDF) in a multimodal image registration problem. To assess the quality of the DDF distribution predicted by the model, we propose a new metric based on the Kullback–Leibler divergence. The performance of our approach was evaluated against three other DIR algorithms (VoxelMorph, Monte Carlo dropout, and Monte Carlo B-spline) capable of predicting uncertainty. The evaluation of the models included not only the quality of the deformation but also the reliability of the estimated uncertainty. Our application investigated the registration of a treatment planning computed tomography (CT) to follow-up cone beam CT for daily adaptive radiotherapy. Main results. The hyperparameter tuning of the models showed a trade-off between the estimated uncertainty’s reliability and the deformation’s accuracy. In the optimal trade-off, our model excelled in contour propagation and uncertainty estimation (p <0.05) compared to existing uncertainty estimation models. We obtained an average dice similarity coefficient of 0.89 and a KL-divergence of 0.15. Significance. By addressing challenges in DIR uncertainty estimation and evaluation, our work showed that both the DIR and its uncertainty can be reliably predicted, paving the way for safe deployment in a clinical environment.
DMGM: deformable-mechanism based cervical cancer staging via MRI multi-sequence
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Authors: Cheng Junqiang , Zhao Binnan , Liu Ziyi , Huang Deqing , Qin Na , Yang Aisen , Chen Yuan , Shu Jian
Published: May 2024

Objective. This study aims to leverage a deep learning approach, specifically a deformable convolutional layer, for staging cervical cancer using multi-sequence MRI images. This is in response to the challenges doctors face in simultaneously identifying multiple sequences, a task that computer-aided diagnosis systems can potentially improve due to their vast information storage capabilities. Approach. To address the challenge of limited sample sizes, we introduce a sequence enhancement strategy to diversify samples and mitigate overfitting. We propose a novel deformable ConvLSTM module that integrates a deformable mechanism with ConvLSTM, enabling the model to adapt to data with varying structures. Furthermore, we introduce the deformable multi-sequence guidance model (DMGM) as an auxiliary diagnostic tool for cervical cancer staging. Main results. Through extensive testing, including comparative and ablation studies, we validate the effectiveness of the deformable ConvLSTM module and the DMGM. Our findings highlight the model’s ability to adapt to the deformation mechanism and address the challenges in cervical cancer tumor staging, thereby overcoming the overfitting issue and ensuring the synchronization of asynchronous scan sequences. The research also utilized the multi-modal data from BraTS 2019 as an external test dataset to validate the effectiveness of the proposed methodology presented in this study. Significance. The DMGM represents the first deep learning model to analyze multiple MRI sequences for cervical cancer, demonstrating strong generalization capabilities and effective staging in small dataset scenarios. This has significant implications for both deep learning applications and medical diagnostics. The source code will be made available subsequently.
Virtual cylindrical PET for efficient DOI image reconstruction with sub-millimetre resolution
Authors: Enríquez-Mier-y-Terán Francisco E , Kyme Andre Z , Angelis Georgios , Meikle Steven R
Published: May 2024

Objective. Image reconstruction in high resolution, narrow bore PET scanners with depth of interaction (DOI) capability presents a substantial computational challenge due to the very high sampling in detector and image space. The aim of this study is to evaluate the use of a virtual cylinder in reducing the number of lines of response (LOR) for DOI-based reconstruction in high resolution PET systems while maintaining uniform sub-millimetre spatial resolution. Approach. Virtual geometry was investigated using the awake animal mousePET as a high resolution test case. Using GEANT4 Application for Tomographic Emission (GATE), we simulated the physical scanner and three virtual cylinder implementations with detector size 0.74 mm, 0.47 mm and 0.36 mm (vPET1, vPET2 and vPET3, respectively). The virtual cylinder condenses physical LORs stemming from various crystal pairs and DOI combinations, and which intersect a single virtual detector pair, into a single virtual LOR. Quantitative comparisons of the point spread function (PSF) at various positions within the field of view (FOV) were compared for reconstructions based on the vPET implementations and the physical scanner. We also assessed the impact of the anisotropic PSFs by reconstructing images of a micro Derenzo phantom. Main results. All virtual cylinder implementations achieved LOR data compression of at least 50% for DOI PET reconstruction. PSF anisotropy in radial and tangential profiles was chiefly influenced by DOI resolution and only marginally by virtual detector size. Spatial degradation introduced by virtual cylinders was most prominent in the axial profile. All virtual cylinders achieved sub-millimetre volumetric resolution across the FOV when 6-bin DOI reconstructions (3.3 mm DOI resolution) were performed. Using vPET2 with 6 DOI bins yielded nearly identical reconstructions to the non-virtual case in the transaxial plane, with an LOR compression factor of 86%. Resolution modelling significantly reduced the effects of the asymmetric PSF arising from the non-cylindrical geometry of mousePET. Significance. Narrow bore and high resolution PET scanners require detectors with DOI capability, leading to computationally demanding reconstructions due to the large number of LORs. In this study, we show that DOI PET reconstruction with 50%–86% LOR compression is possible using virtual cylinders while maintaining sub-millimetre spatial resolution throughout the FOV. The methodology and analysis can be extended to other scanners with DOI capability intended for high resolution PET imaging.
Finger photopletysmography detects early acute blood loss in compensated blood donors: a pilot study
Authors: Speroni Gerardo , Antedoro Patricia , Marturet Silvia , Martino Gabriela , Chavez Celia , Hidalgo Cristian , Villacorta María V , Ahrtz Ivo , Casadei Manuel , Fuentes Nora , Kremeier Peter , Böhm Stephan H , Tusman Gerardo
Published: May 2024

Objective. Diagnosis of incipient acute hypovolemia is challenging as vital signs are typically normal and patients remain asymptomatic at early stages. The early identification of this entity would affect patients’ outcome if physicians were able to treat it precociously. Thus, the development of a noninvasive, continuous bedside monitoring tool to detect occult hypovolemia before patients become hemodynamically unstable is clinically relevant. We hypothesize that pulse oximeter’s alternant (AC) and continuous (DC) components of the infrared light are sensitive to acute and small changes in patient’s volemia. We aimed to test this hypothesis in a cohort of healthy blood donors as a model of slight hypovolemia. Approach. We planned to prospectively study blood donor volunteers removing 450 ml of blood in supine position. Noninvasive arterial blood pressure, heart rate, and finger pulse oximetry were recorded. Data was analyzed before donation, after donation and during blood auto-transfusion generated by the passive leg-rising (PLR) maneuver. Main results. Sixty-six volunteers (44% women) accomplished the protocol successfully. No clinical symptoms of hypovolemia, arterial hypotension (systolic pressure < 90 mmHg), brady-tachycardia (heart rate <60 and >100 beats-per-minute) or hypoxemia (SpO2 < 90%) were observed during donation. The AC signal before donation (median 0.21 and interquartile range 0.17 a.u.) increased after donation [0.26(0.19) a.u; p < 0.001]. The DC signal before donation [94.05(3.63) a.u] increased after blood extraction [94.65(3.49) a.u; p < 0.001]. When the legs’ blood was auto-transfused during the PLR, the AC [0.21(0.13) a.u.; p = 0.54] and the DC [94.25(3.94) a.u.; p = 0.19] returned to pre-donation levels. Significance. The AC and DC components of finger pulse oximetry changed during blood donation in asymptomatic volunteers. The continuous monitoring of these signals could be helpful in detecting occult acute hypovolemia. New pulse oximeters should be developed combining the AC/DC signals with a functional hemodynamic monitoring of fluid responsiveness to define which patient needs fluid administration.
The influence of cholesterol and calcium ions on the interaction of cryoprotectors with a biological membrane model
Authors: Svechnikova V Y , Mishukova O V , Mironova A G , Khomutov G B , Marchenkova M A , Yakovenko S A
Published: May 2024

In this work, we studied the effects of three cryoprotectors – ethylene glycol, dimethyl sulfoxide and sucrose – on the compression isotherms of egg yolk Langmuir monolayers both in the presence and in the absence of cholesterol in the monolayer. The influence of calcium ions from the subphase affecting the effectiveness of cryoprotection on π-A isotherms is also examined. In addition, the elastic properties of the obtained monolayers are investigated by calculation and comparison the compression modulus of the monolayer. The scientific novelty of the work is in consideration of a complex biosimilar system (an egg yolk monolayer, cholesterol and their mixtures) on the surface of the aqueous solution of the nutrient mixture and obtaining information about the specific interaction of different cryoprotectors with lipid membranes. We found that when calcium ions and cryoprotectors are simultaneously added to the subphase, they block each other's influence on the lipid monolayer and reduce the effectiveness of cryoprotection. Cholesterol in the yolk in a ratio of 1:50 m m−1 changes the properties of the monolayer, which leads to increased action of cryoprotectors. Also, for the first time, the effect of a significant increase in surface pressure (by ∼20 mN m−1) was detected when cryoprotectors were added to the system under consideration. This effect can serve as an indicator of the effectiveness of membrane dehydration by cryoprotectors and can be used to find the most effective and safe cryoprotector compositions. The obtained data can provide important recommendations for the development of cryoprotective media for cell freezing. Since the study of the mechanisms of calcium interaction (the most important signaling cation) with biological membrane and membrane-like systems is important for understanding the various effects caused by medicinal and biologically active drugs at the cellular level, the study is of interest for various fields of biophysics and biomedicine.
Mechanical property optimization of Sn-1.5Ag-0.5Cu solder alloys with additions of Bi, In, and Te
Authors: Eid N A M , El-Daly A A , Ibrahiem A A
Published: May 2024

The mechanical characteristics of Sn-1.5Ag-0.5Cu (SAC155) alloy modified with In, Bi, and Te microalloying are investigated in relation to three strengthening mechanisms that withstand coarsening: (i) micron-scale Ag3Sn, Cu6Sn5, SnTe, Ag2In and InSn4 IMC precipitated phases, (ii) Bi in solid solution and (iii) Bi precipitated particles formed upon eutectic solidification. Compared to SAC155 alloy with a single strengthening mechanism, the combined effect of three deformation processes operating in SAC(155)-3Bi-2In with high In content and SAC(155)-3Bi-0.2Te (wt%) with low Te content alloys greatly improved the mechanical properties at high temperatures. It was found that, despite a discernible reduction in ductility, the high In content could refine the microstructure, enrich the elastic modulus (E), yield stress (YS), and ultimate tensile strength (UTS) of SAC(155)-3Bi-2In to almost 2.3 times that of SAC155 solder. On the other hand, a low Te content greatly increased SAC(155)-3Bi-0.2Te’s mechanical strength ∼2.3 times, while a large atomic size difference between Te and Sn atoms caused excessive misfit strain, which in turn increased Bi’s solubility in β-Sn grains, and improved ductility by approximately twice that of SAC(155)-3Bi-2In solder.
Thermoelectric effects in ballistic junctions of 2D-Weyl semimetals
Authors: Lotfi Jafar , Abdollahipour Babak
Published: May 2024

Two dimensional Weyl semimetals are a variant of topological materials in two dimensions, which are realized in three atomic layer materials. These materials possess isotropic or anisotropic dispersions around Weyl nodes and present some common physical properties with their 3D counterparts. We study the thermoelectric effects in a ballistic junction of 2D-Weyl semimetal with isotropic or anisotropic dispersions around the Weyl points. We demonstrate that these two types of 2D-Weyl semimetals exhibit different thermoelectric responses at low chemical potentials of the leads. The Weyl semimetal layer’s physical characteristics can significantly affect these junctions’ thermoelectric properties. Moreover, significant Seebeck coefficient and thermoelectric figure of merit of these junctions are only observed at the low chemical potential of the leads. In particular, we unveil that thermoelectric effects in the ballistic junction of 2D-Weyl semimetals are not as efficient as their 3D counterparts.
Michelson interferometer-based tunable multiwavelength thulium-doped fluoride fiber laser in S-band for 5 G networks
Authors: Ahmad Harith , Lohano Leela Wanti , Nizamani Bilal , Samion Muhamad Zharif , Ismail Mohamad Faizal
Published: May 2024

This work reported a multiwavelength thulium-doped fluoride fiber laser (TDFFL) for the S-band region using the Michelson interferometer as an optical filter. Michelson interferometer was utilized as a comb-like filter, whereas dispersion-compensated fiber (DCF) of 10 km length was used to increase the number of lasing lines and reduce mode competition. Approximately 61 lasing lines were achieved with a signal-to-noise ratio (SNR) of 40 dB in the wavelength region from 1501.36 to 1505.52 nm within 10 dB of maximum power. The stability of the multiwavelength fiber laser was also recorded for the time duration of two hours, and it was found that all lasing lines were stable and equally spaced at the free spectral range (FSR) of 0.07 nm. The variation in optical power was less than 0.5 dB; however, the wavelength shift was about 0.01 nm. Tunability of multiwavelength laser has also been observed up to the broader transmission span of 57 nm by incorporating the tunable band pass filter (TBPF). Moreover, FSR was observed to be tunable within the range of 0.02 to 0.14 nm by using the optical delay line (ODL) with a Michelson interferometer. Additionally, the proposed laser can generate frequency signals from 2.65 GHz to 18.54 GHz according to the obtained range of FSR.
On optical soliton solutions of the higher-order Lakshmanan-Porsezian-Daniel model having the cubic-quintic-septic law in the presence of spatio-temporal and chromatic dispersion
Authors: Ozdemir Neslihan , Secer Aydin , Ozisik Muslum , Bayram Mustafa , Yuce Salim
Published: May 2024

The higher-order Lakshmanan-Porsezian-Daniel equation (LPDE) with the cubic-quintic-septic (CQS) law having spatiotemporal and chromatic dispersion terms (STD-CD) is examined to derive new optical soliton solutions. To accomplish this aim, we operated on a simple version of the new extended auxiliary equation method (SAEM26). The optical soliton solutions of the LPDE with CQS as well as STD-CD are constructed in detail. Moreover, 3D-surface, contour, and 2D plots are presented for the bright and periodic singular soliton solutions. Additionally, the effects of diverse model parameters on the bright soliton structure are surveyed, and these effects are displayed with 2D graphics. The findings established in this work can positively contribute to research in nonlinear optics, while the SAEM26 can be effectively applied to similar nonlinear models.
Impact of zinc oxide on dielectric properties of forsterite coated titanium based medical implants
Authors: Pandey Ankur , Sahoo Swagatadeb
Published: May 2024

Zinc oxide-doped forsterite solutions are synthesized through the sol-gel approach by varying the weight percentage of zinc oxide. These solutions are then applied to titanium (Ti) substrates to form zinc oxide-doped forsterite coated Ti substrate samples using the dip-coating method. The structural and surface morphology analyses of the samples are conducted using x-ray Diffraction (XRD) and Scanning Electron Microscope (SEM). Dielectric properties, encompassing dielectric constant, dielectric loss, alternating current conductivity, loss tangent, and relaxation time are explored at room temperature over a frequency range of 200 MHz to 20 GHz utilizing a Vector Network Analyzer (VNA) setup. The impact of zinc oxide on the structure, morphology, and dielectric properties of the samples, particularly in medical implant applications, is extensively discussed. The results indicate that samples with a higher weight percentage of zinc oxide demonstrate superior dielectric characteristics.
Cosmology of Barrow holographic QCD ghost dark energy and a look into the thermodynamics
Authors: Altaibayeva Aziza , Chattopadhyay Surajit , Umurzakhova Zhanar
Published: May 2024

The present study endeavours to study the cosmology of QCD ghost dark energy based on Barrow holographic fluid, a particular example of Nojiri-Odintsov holographic dark energy (2006, General Relativity and Gravitation, 38, 1285–1304); (2017, The European Physical Journal C, 77, 1–8). The Hubble parameter is reconstructed and according the equation of state parameter is reconstructed for the Barrow holographic QCD ghost dark energy. It is observed that the effective equation of state parameter has a transition from quintessence to phantom and for the current universe the equation of state parameter is very close to −1. The deceleration parameter is computed based on the reconstructed Hubble parameter and it is observed that the model can have a transition from decelerated to accelerated universe. The statefinder trajectories are plotted and an interpolation between dust and ΛCDM phases is observed. Finally, the thermodynamics is studied considering apparent horizon as the enveloping horizon of the Universe.
Lie group analysis of bingham plastic flow over a straining surface in the presence of magnetohydrodynamic effects and slip conditions
Authors: Ali Shahbaz
Published: May 2024

This paper investigates the two-dimensional flow of a Bingham plastic over a straining surface subjected to an externally applied magnetic field and surface slips. The study aims to understand the behavior of such flows and their response to external factors, which has applications in various industrial processes involving complex fluid dynamics. Through Lie group analysis, a new set of similarity transformations are derived to reduce the number of variables in the governing partial differential equations, facilitating a more tractable analysis. These transformations enable the conversion of the partial differential equations into a self-similar system of ordinary differential equations. A high-order, three-stage Lobatto IIIa formula along with appropriate boundary conditions is applied to solve this system. The solutions obtained for various physical parameters lead to several key deductions. It is found that under constant physical parameter values, the velocity layer thickness of the plastic flow is lower compared to the thermal layer thickness, indicating the dominance of the plastic flow behavior. Additionally, an increase in the magnetic field results in a reduction in the thickness of the plastic boundary layer, highlighting the significant influence of magnetic fields on the flow characteristics. These findings provide valuable insights into the control and optimization of processes involving Bingham plastic flows, particularly in the presence of magnetic fields and surface slips.
Optimal Fitting and Debiasing for Detectors Read Out Up-the-Ramp
Authors: Brandt Timothy D.
Published: May 2024

This paper derives the optimal fit to a pixel’s count rate in the case of an ideal detector read out nondestructively in the presence of both read and photon noise. The approach is general for any readout scheme, provides closed-form expressions for all quantities, and has a computational cost that is linear in the number of resultants (groups of reads). I also derive the bias of the fit from estimating the covariance matrix and show how to remove it to first order. The ramp-fitting algorithm I describe provides the χ
2 value of the fit of a line to the accumulated counts, which can be interpreted as a goodness-of-fit metric. I provide and describe a pure Python implementation of these algorithms that can process a 10-resultant ramp on a 4096 × 4096 detector in ≈8 s with bias removal on a single core of a 2020 Macbook Air. This Python implementation, together with tests and a tutorial notebook, are available at https://github.com/t-brandt/fitramp. A companion paper describes a jump detection algorithm based on hypothesis testing of ramp fits and demonstrates all algorithms on data from JWST.
Likelihood-based Jump Detection and Cosmic Ray Rejection for Detectors Read Out Up-the-ramp
Authors: Brandt Timothy D.
Published: May 2024

This paper implements likelihood-based jump detection for detectors read out up-the-ramp, using the entire set of reads to compute likelihoods. The approach compares the χ
2 value of a fit with and without a jump for every possible jump location. I show that this approach can be substantially more sensitive than one that only uses the difference between sequential groups of reads, especially for long ramps and for jumps that occur in the middle of a group of reads. It can also be implemented for a computational cost that is linear in the number of resultants. I provide and describe a pure Python implementation that can process a 10-resultant ramp on a 4096 × 4096 detector in ≈20 s, including iterative cosmic ray detection and removal, on a single core of a 2020 Macbook Air. This Python implementation, together with tests and a tutorial notebook, are available at https://github.com/t-brandt/fitramp. I also provide tests and demonstrations of the full ramp fitting and cosmic ray rejection approach on data from the JWST.
Multi-objective global optimization approach predicted quasi-layered ternary TiOS crystals with promising photocatalytic properties
Authors: Xiang 向 Yi-Jie 依婕 , Gao 高 Siyan 思妍 , Wang 王 Chunlei 春雷 , Fang 方 Haiping 海平 , Duan 段 Xiangmei 香梅 , Zheng 郑 Yi-Feng 益峰 , Zhang 张 Yue-Yu 越宇
Published: May 2024

Titanium dioxide (TiO2) has attracted considerable research attentions for its promising applications in solar cells and photocatalytic devices. However, the intrinsic challenge lies in the relatively low energy conversion efficiency of TiO2, primarily attributed to the substantial band gaps (exceeding 3.0 eV) associated with its rutile and anatase phases. Leveraging multi-objective global optimization, we have identified two quasi-layered ternary Ti–O–S crystals, composed of titanium, oxygen, and sulfur. The calculations of formation energy, phonon dispersions, and thermal stability confirm the chemical, dynamical and thermal stability of these newly discovered phases. Employing the state-of-art hybrid density functional approach and many-body perturbation theory (quasiparticle GW approach and Bethe–Salpeter equation), we calculate the optical properties of both the TiOS phases. Significantly, both phases show favorable photocatalytic characteristics, featuring band gaps suitable for visible optical absorption and appropriate band alignments with water for effective charge carrier separation. Therefore, ternary compound TiOS holds the potential for achieving high-efficiency photochemical conversion, showing our multi-objective global optimization provides a new approach for novel environmental and energy materials design with multicomponent compounds.
Application of GIS to monitor the impact of urbanization on surface water quality in Kim Dong district, Hung Yen province, Vietnam
Authors: Nong Duong H. , Ngo An T. , Vo Cong H. , Nguyen Tien X.
Published: May 2024

Rapid urbanization profoundly affects surface water quality in lower-income countries, often extending pressure on resources beyond urban areas. This study assesses the impact of urbanization on surface water quality in Kim Dong district, highlighting its broader implications for the Red River Delta. The demands of urban systems significantly strain natural resources, notably water, impacting both human consumption and environmental sustainability. With a focus on less developed regions where water infrastructure may be limited, ensuring sufficient water supply as these areas grow presents a complex challenge. The economic and population growth in Kim Dong district has heightened water demand in recent years. Despite ample water sources, Kim Dong district is facing surface water pollution, leading to shortages for domestic, agricultural, and industrial use. This study aims to evaluate surface water quality using the Water Quality Index (WQI) and examine urbanization’s impact, employing GIS to map pollution loads across communes. Results of the study reveal significant water quality deterioration, notably in areas with high population density and industrial concentration, causing severe pollutant loads in rivers. Hierarchical Cluster Analysis (HCA) and Discriminant Analysis (DA) was utilized to classify communes into three distinct clusters based on pollutant loads, emphasizing Luong Bang town and adjacent communes as high-load areas. The study demonstrates a strong positive correlation between population density and pollutant loads, indicating the profound impact of urbanization on water quality. Our research calls for strict monitoring of discharge sources, especially from industries and residential areas, emphasizing compliance with environmental regulations. It recommends regular drainage system maintenance, comprehensive environmental assessments for future development plans, and consistent efforts to mitigate urbanization’s adverse effects on surface water in Kim Dong district. These measures aim to sustainably manage water resources and safeguard environmental integrity amidst rapid urbanization.
Assessing the water potential and wastewater load capacity of the La Tinh River, Binh Dinh province by MIKE 11AD and Ecolab model combined with GIS method
Authors: Hai Au Nguyen , Thi Tinh Au Nguyen
Published: May 2024

The study used the NAM model of flow simulation with a time series of 14 years (2008 - 2021), statistical analysis method, and MIKE 11 AD water quality model, and Ecolab combined with GIS method to calculate wastewater reception capacity and load capacity of the basin. The model validation is highly reliable with a model efficiency factor of R2 of 0.777 and BIAS = 5%. The results of the application of the NAM model have determined the daily flow series of 14 years (2008 - 2021) and the average flow characteristics of many years of the La Tinh basin such as Qo flow is about 5.9; 6.0 m3/s, total amount of Wo = 292.1; 188.8 million m3 flow modulus Mo = 19.3 l/s-km2 flow class Yo = 611 mm and flow coefficient α= 0.3 for all sub-basins. The results of the study show that the capacity of receiving wastewater, the capacity of most river sections in the La Tinh basin is still received with five parameters at a relatively high level, the section of the Binh Tri river upstream alone has exceeded its capacity to receive. This is one of the very useful tools in integrated management and effective use management of river basin water resources.