Orthogonal Technique Research Articles

A New Method of Lung Nodule Detection in CT Scans using 3D U-Net Convolutional Neural Network

Automatic detection of lung nodules in CT scans has attracted significant research interest in computer-aided diagnosis (CAD) system because it can help improve the early and accurate diagnosis, therefore reducing lung cancer mortality. The aim of this paper is to propose a new method of lung nodule detection in CT scans by using 3D U-Net convolutional neural networks (CNNs) which can successfully reflect the 3D characteristics of CT scans. We use 3D U-Net architecture for CNNs in order to accurately and automatically detect the lung nodules in CT scans. We employ the masked Lung Image Database Consortium (LIDC) dataset containing 400000 CT images of over 1000 patients for training the 3D U-Net model. We introduce an integrated loss function in order to detect lung nodules with different sizes and prepare 3D input data by the use of 2D CT images fixing the hyper parameters of CNNs. Our method successfully detects the lung nodules with different sizes ranging from 3mm to 30 mm exhibiting higher sensitivity of 93.2, 94.5 and 94.8% at 1.0, 2.0 and 3.0 FPs per patient, respectively than the state-of-the-art methods. The proposed method of using 3D U-Net CNNs and integrated loss function is effective for early diagnosis of lung nodules in different sizes with improved sensitivity

Neural Dielet 2.0: A 128-Channel 2mm×2mm Battery-Free Neural Dielet Merging Simultaneous Multi-Channel Transmission through Multi-Carrier Orthogonal Backscatter.

Miniaturization of wireless neural-recording systems enables minimally-invasive surgery and alleviates the rejection reactions for implanted brain-computer interface (BCI) applications. Simultaneous massive-channel recording capability is essential to investigate the behaviors and inter-connections in billions of neurons. In recent years, battery-free techniques based on wireless power transfer (WPT) and backscatter communication have reduced the sizes of neural-recording implants by battery eliminating and antenna sharing. However, the existing battery-free chips realize the multi-channel merging in the signal-acquisition circuits, which leads to large chip area, signal attenuation, insufficient channel number or low bandwidth, etc. In this work, we demonstrate a 2mm×2mm battery-free neural dielet, which merges 128 channels in the wireless part. The neural dielet is fabricated with 65nm CMOS process, and measured results show that: 1) The proposed multi-carrier orthogonal backscatter technique achieves a high data rate of 20.16Mb/s and an energy efficiency of 0.8pJ/bit. 2) A self-calibrated direct digital converter (SC-DDC) is proposed to fit the 128 channels in the 2mm×2mm die, and then the all-digital implementation achieves 0.02mm2 area and 9.87μW power per channel.

Flow Cytometric Identification of Human IgE+ B Lineage Subsets.

The use of flow cytometry for immunophenotyping is contingent on the ability to accurately assign biological relevance to the detected signal. This process has historically been challenging when defining IgE expressing B cells or IgE expressing antibody-secreting cells due to widespread expression of receptors for IgE on various leukocyte subsets, including human B cells. Here we describe our implementation of intracellular staining for human IgE following a blocking step to negate the challenge of surface-bound IgE. We also describe our experience with a human B cell culture system that can be used to robustly validate this approach before application to primary human samples. Orthogonal confirmatory techniques remain essential; these are not described in detail, but several possible strategies are suggested.

Higher or Lower? - The Resolution of Analytical Pipelines for the Evaluation of Lipid Nanoparticle Critical Quality Attributes

Dynamic light scattering (DLS) is a routinely used analytical technique to measure the size distribution of a colloidal sample. Nanoparticle tracking analysis (NTA) has more recently emerged as an orthogonal technique to determine particle size and estimated concentration, although widespread use of NTA for lipid nanoparticle (LNP) analysis is not reported. Here, we use DLS and NTA to screen the stability of oligonucleotide drug loaded lipid nanoparticles (oligo-LNPs) at ultra low storage temperatures (-80 °C) in the presence and absence of a cryoprotectant (20 % sucrose, w/v) as a case study to highlight differences in technique resolution. NTA was able to detect additional LNP subpopulations samples for all measured samples, whereas DLS was unable to detect these subpopulations. Our study conveys that the use of orthogonal sizing techniques can support early stage product development, where a more in-depth analysis of formulation and process parameters on LNP stability would support comprehensive understanding of variable defining product stability.

A Green Raman Spectroscopic Assay Method for The Quantification of Tranexamic Acid in Pharmaceutical Formulations

Tranexamic acid (TXA) is a widely used antifibrinolytic agent that is used to prevent and treat excessive bleeding. Current analytical methods for TXA are often time-consuming and require the use of toxic solvents. Raman spectroscopy has the ability to measure TXA because it is a fast and non-destructive analytical method. This research established and validated a green Raman spectroscopic test for TXA measurement. There was no need for harmful solvents because the technique relied on a basic aqueous solution of TXA. Results demonstrated that the technique was linear across the 0.7% to 13.0% concentration range. The method was also shown to be accurate, with results comparable to the orthogonal techniques. The green Raman spectroscopic assay method was applied to the quantification of TXA in pharmaceutical formulations. The results obtained were comparable to those obtained using reference methods. To quantify TXA quickly and accurately, one can use the green Raman spectroscopic test. Since no harmful chemicals are needed for the procedure, it is also eco-friendly. Method has the potential to be used in a variety of settings, including pharmaceutical quality control and research laboratories.

Identification of CD38, CD97, and CD278 on the HIV surface using a novel flow virometry screening assay

While numerous cellular proteins in the HIV envelope are known to alter virus infection, methodology to rapidly phenotype the virion surface in a high throughput, single virion manner is lacking. Thus, many human proteins may exist on the virion surface that remain undescribed. Herein, we developed a novel flow virometry screening assay to discover new proteins on the surface of HIV particles. By screening a CD4+ T cell line and its progeny virions, along with four HIV isolates produced in primary cells, we discovered 59 new candidate proteins in the HIV envelope that were consistently detected across diverse HIV isolates. Among these discoveries, CD38, CD97, and CD278 were consistently present at high levels on virions when using orthogonal techniques to corroborate flow virometry results. This study yields new discoveries about virus biology and demonstrates the utility and feasibility of a novel flow virometry assay to phenotype individual virions.

Applying a risk assessment guided evaluation for verifying comprehensive two-dimensional gas chromatography to analyse complex pharmaceuticals

The reliability of analytical results is critical and indispensable when applied in regulated environments such as the pharmaceutical industry. Therefore, analytical workflows must be validated. However, validation guidelines are often designed for quantitative targeted analysis and rarely apply to qualitative untargeted approaches. In this study, we employ a risk assessment approach to identify critical parameters which might influence the qualitative results derived by online derivatisation — comprehensive two-dimensional gas chromatography coupled to a high-resolution time-of-flight mass spectrometer (GC × GC-HR-ToF–MS) for the analysis of the active pharmaceutical ingredient (API) sodium bituminosulfonate (SBS). To show the complexity and feasibility of such an approach, we focus on investigating three potential risk factors: sample preparation, vapourability, and the thermal stability of sulfonates. Through the individual evaluation of these potential risk factors due to the application of sample preparation approaches and thermal gravimetric analysis (TGA), we demonstrate the high derivatisation efficiency and repeatability of the online derivatisation method and confirm the absence of derivatisation-induced side reactions. In addition, we also show the potential thermal instability of an incompletely derivatised API. To address the limitation of these individual assessments, we applied a holistic evaluation step with negative electrospray ionisation Fourier transform ion cyclotron resonance mass spectrometry (ESI( −) FT-ICR MS) as an orthogonal technique. This confirms that most of the API is detected via the presented GC-based method. Thereby, we demonstrated the practical feasibility of the risk assessment-based approach to ensure the validity of the qualitative data for a complex untargeted method.Graphical

Investigation of OFDM-Based HS-PON Using Front-End LiFiSystem for 5G Networks

Fifth-generation (5G) technology has enabled faster communication speeds, lower latency, a broader range of coverage, and greater capacity. This research aims to introduce a bidirectional high-speed passive optical network (HS-PON) for 5G applications and services including mobile computing, cloud computing, and fiber wireless convergence. Using 16-ary quadrature amplitude modulation orthogonal frequency division multiplexing techniques, the system transmits uplinks and downlinks with a pair of four wavelengths each. Light fidelity (LiFi) services are provided with blue light-emitting-diode-based technology. With a threshold bit error rate (BER) of 10−3, the results demonstrate reliable transportation over a 100 km fiber at −17 dBm received power and in a maximum LiFi range of 20 m. Furthermore, the system offers symmetric 4 × 50 Gbps transmission rates under the impact of fiber–LiFi channel impairments with maximum irradiance and incidence half-angles of 500. Additionally, at threshold BER, the system provides a detection surface range from 1.5 to 4 cm2. Compared to existing networks, the system also provides a high gain and low noise figure. A number of features make this system an attractive option. These include its high speed, high reach, high split ratio, low cost, easy upgradeability, pay-as-you-grow properties, high reliability, and ability to accommodate a large number of users.

Container Closure Integrity of a Glass Prefillable Syringe in Deep Frozen Storage Conditions

Development of novel pharmaceutical drug modalities has created a need for frozen storage and transportation. Accurate and easy assessment of container closure integrity (CCI) in frozen conditions remains a challenge. Thus, container closure systems (CCS) suitable for low temperatures have been primarily restricted to vials despite the growing popularity of prefillable syringes (PFS) for parenteral administration. A new dye ingress test method, suitable for testing at low temperatures, was developed and applied to PFS across a range of deep-frozen temperatures. The method is versatile and can easily be extended to other common CCS formats over a wide range of temperatures including storage on dry ice (-80 °C). This new method was paired with an orthogonal technique, laser-based CO2 headspace gas analysis, to evaluate the CCI of a glass PFS at temperatures from -50 °C to -80 °C. Both test methods showed comparable results and consistent CCI failure below a temperature of -70 °C. The primary mode of failure was the plunger-to-barrel interface, likely attributable to dimensional changes and loss of elasticity. This study demonstrates the temperature dependent CCI behavior of glass PFS and underscores the importance of thorough characterization of package integrity for deep frozen drug products.

A time-course prediction model of global COVID-19 mortality.

The COVID-19 pandemic has caused over 6 million deaths worldwide and is a significant cause of mortality. Mortality dynamics vary significantly by country due to pathogen, host, social and environmental factors, in addition to vaccination and treatments. However, there is limited data on the relative contribution of different explanatory variables, which may explain changes in mortality over time. We, therefore, created a predictive model using orthogonal machine learning techniques to attempt to quantify the contribution of static and dynamic variables over time. A model was created using Partial Least Squares Regression trained on data from 2020 to rank order the significance and effect size of static variables on mortality per country. This model enables the prediction of mortality levels for countries based on demographics alone. Partial Least Squares Regression was then used to quantify how dynamic variables, including weather and non-pharmaceutical interventions, contributed to the overall mortality in 2020. Finally, mortality levels for the first 60 days of 2021 were predicted using rolling-window Elastic Net regression. This model allowed prediction of deaths per day and quantification of the degree of influence of included variables, accounting for timing of occurrence or implementation. We found that the most parsimonious model could be reduced to six variables; three policy-related variables - COVID-19 testing policy, canceled public events policy, workplace closing policy; in addition to three environmental variables - maximum temperature per day, minimum temperature per day, and the dewpoint temperature per day. Country and population-level static and dynamic variables can be used to predict COVID-19 mortality, providing an example of how broad temporal data can inform a preparation and mitigation strategy for both COVID-19 and future pandemics and assist decision-makers by identifying population-level contributors, including interventions, that have the greatest influence in mitigating mortality, and optimizing the health and safety of populations.

In-house CHO HCPs platform: A promising approach for HCPs ELISA monitoring

A key aspect that must be supervised during the development of recombinant therapeutic products is the potential presence of impurities.Residual host cell proteins (HCPs) are a major class of process-related impurities derived from the host organism that even in trace amount have the potential to affect product quality, safety, and efficacy. Therefore, the product purification processes must be optimized to consistently remove as many HCPs as feasible, with the goal of making the product as pure as possible. The workhorse of HCP monitoring and quantitation during bioprocessing manufacturing is sandwich ELISA (enzyme‐linked immunosorbent assay), which employs polyclonal anti-HCP antibodies for both capture and detection. Commercial ELISA kits developed from Chinese Hamster Ovary (CHO) cell lines are widely applied in early drug development stages (preclinical, phase I, and phase II), but are not specifically designed for a given manufacturer's proprietary cell line, and users do not have control over reagent availability and lot-to-lot consistency. For later development stages, the upstream process-specific method is preferred to guarantee an improved sensitivity and coverage. In agreement with the USP General Chapter 〈1132〉, a platform assay can be used in place of the commercial one through all stages of product development, if already available when product development starts.This proof-of-concept study was carried out to demonstrate the feasibility and the advantages of the development of a proprietary CHO HCPs platform ELISA. Different proprietary mock materials have been characterized and compared by orthogonal bidimensional electrophoresis techniques (SDS-PAGE coupled to SS/WB and 2D DIGE) with the scope of selecting the best antigen-antibody couple for setting up the in-house ELISA. A preliminary evaluation of the in-house method performance has been done in comparison with the commercial assay, demonstrating that the platform method is promising for an accurate and precise CHO HCPs quantification during the early phase product and process development.

Mixture detection with Demixtify

The de facto genetic markers of forensics are short tandem repeats (STRs). There are many analytical tools designed to work with STRs, including techniques for analyzing and assessing DNA mixtures. In contrast, the nascent field of forensic genetic genealogy often relies on biallelic single nucleotide polymorphisms (SNPs). Tools designed for the forensic assessment of SNPs are somewhat lacking, especially for DNA mixtures. In this paper we introduce Demixtify, a program that detects DNA mixtures using biallelic SNPs. Demixtify is quite powerful; highly imbalanced mixtures can be detected (≤1:99, considering in silico and in vitro mixtures) when coverage is ample. Demixtify can also detect mixtures in low coverage (∼1×) samples (when the mixture is relatively balanced). Demixtify includes an empirical estimator of sequence error that is specific to the markers assayed, making it especially relevant to the forensic community. Orthogonal techniques are also developed to characterize in vitro mixtures, as well as samples thought to be single source, and the results of these approaches serve to validate the techniques presented.

Numerical investigation on the thermal-hydraulic performance of high Prandtl number fluid in offset strip fin with different offset

To rigorously analyze the thermo-hydraulic performance of offset strip fin operating with high Prandtl number fluid and variable fin offset values, numerical simulation was employed to investigate changes in the Colburn j and the Fanning friction f under varying fin offsets. The results, obtained using a reliable numerical model, indicated that an increase in offset led to a 33.08% and 33.97% rise in j and f, respectively, demonstrating the offset's influence on the thermal-hydraulic performance of offset strip fins. By employing orthogonal design techniques, a set of 49 design points for fin pitch, fin thickness, fin height, interrupted length, fin offset, Reynolds number, and Prandtl number were obtained. Regression analysis was conducted on the simulation results of these 49 design points, ultimately deriving correlations for j and f within the Reynolds number range of 100–1000 and the Prandtl number range of 2–13. A comparison between the predicted and simulated data revealed that j and f fell within the error range of 20% for 91.84% and 93.88% of the data, respectively, confirming the accuracy of the proposed correlations. Furthermore, comparing the correlations from this study with other previously established correlations demonstrated that the proposed correlations were more suitable for predicting the thermal-hydraulic performance of offset strip fins with high Prandtl number fluids. For fluids with Prandtl number range of 30–150, the predicted data of j and f exhibited errors within 15% and 20% of the experimental data, respectively, further validating the applicability of these correlations for predicting the thermo-hydraulic performance of offset strip fins with higher Prandtl number fluids as the working medium.

Extension of the Pt III Analysis

Using a sliding spark and a 6.65 m normal incidence vacuum spectrograph, the third spectrum of platinum was analyzed. The transitions involving high-lying levels were studied. A total of 241 Pt III lines of the transitions from the levels of the 5d76p + 5d66s6p configurations in the region 728–2062 Å were classified, increasing the number of known Pt III lines to more than 1000. Ninety-one energy levels belonging mostly to the 5d66s6p configuration were added to Pt III. The odd Pt III levels were theoretically interpreted by means of multiconfiguration Dirak–Fock calculations and a least-squares fit of the calculated to the observed levels in the framework of the orthogonal parameters technique.

A multi-beam circularly polarised Fabry-Perot resonator antenna array using SIW for X-Band applications

ABSTRACT This paper presents a novel multi-layer beamforming antenna array based on Fabry-Perot resonator that is excited by a high-performance compact 4 × 4 Butler matrix using substrate integrated waveguide (SIW) technology for X-band application. The adapted ring patch antenna is fed through the aperture on a rectangular SIW cavity and forms the radiating element in the antenna array. Enhanced characteristics of the antenna array are realised by inserting an electromagnetic bandgap (EBG) structure between the radiating elements and a superstrate constituted from two complementary frequency selective surfaces (FSS) that forms a Fabry-Perot resonator (FPR). Circular polarisation in the proposed FPR SIW antenna array (FPRSAA) is achieved by using a combination of sequential phase rotation and orthogonal feeding techniques. Measured results of antenna array (Ant. II) show |S11| ≤ −10 dB between 8–12.0 GHz, a circular polarisation (CP) gain variation between 15.64–18.54 dBic, 3 dB axial-ratio between 8.5–11 GHz, and scanning angle covering −47 to 47 degrees.

Contribution of copy number variants to the genetic etiology of dilated cardiomyopathy

Abstract Background/Introduction Dilated cardiomyopathy (DCM) is one of the most common cardiomyopathies, with a prevalence of 1 in 250. Single nucleotide variants (missense, nonsense, or frameshift) in definitive DCM genes are the most frequently identified in positive genetic studies. Despite major advances in genetic diagnostic technologies in recent decades, and more than 100 genes potentially associated with DCM identified to date, the diagnostic yield is still lower than 40%. Copy number variants (CNVs) have been identified as cause of the disease in several studies, especially in genes intolerant to haploinsufficiency. However, the contribution of CNVs to the etiology of DCM has not been evaluated in large cohorts of DCM patients and remains unknown. Purpose To determine the percentage of cases in which CNVs have been identified as the cause of disease in a large cohort of DCM patients evaluated genetically. Methods Retrospective study in which the presence of CNVs was evaluated in a cohort of patients diagnosed with DCM and studied by next-generation-sequencing (NGS). CNVs were detected using a read depth approach and confirmed by an orthogonal molecular technique (Sanger sequencing, MLPA, or dPCR). Results 6,512 DCM patients referred for genetic testing were sequenced in our center by NGS, and the median age at the time of genetic study was 51.1 years (range 0-93). A pathogenic (P) or likely-pathogenic (LP) disease-causing variant was identified in 1,495 of the patients (diagnostic yield of 22.9%). In 67 (1.02%) of the cases, a CNV classified as P/LP was identified. DMD was the gene with the highest number of CNVs identified (n=40), followed by TTN (n=7) and LMNA (n=5). Of the 67 cases, 45 (67%) corresponded to deletions, with a lesser extent to duplications (n=9; 13%), complex alterations (n=7; 11%), and deletion/insertion (n=6; 9%). Only two of the patients harboring disease-causing CNVs had other variants potentially associated with DCM: a likely-pathogenic variant in MYH7 and a homozygous pathogenic variant in the ALMS1 gene. Conclusion In our cohort of DCM patients, 1.02% harbored CNVs considered P/LP, being DMD the most frequently identified gene. These results show that systematic CNVs analysis in NGS studies improves the yield of genetic testing in DCM and highlights the importance of a complete genetic study that includes structural variant detection in the diagnosis of the disease.

Product analog binding identifies the copper active site of particulate methane monooxygenase.

Nature's primary methane-oxidizing enzyme, the membrane-bound particulate methane monooxygenase (pMMO), catalyzes the oxidation of methane to methanol. pMMO activity requires copper, and decades of structural and spectroscopic studies have sought to identify the active site among three candidates: the CuB, CuC, and CuD sites. Challenges associated with the isolation of active pMMO have hindered progress toward locating its catalytic center. However, reconstituting pMMO into native lipid nanodiscs stabilizes its structure and recovers its activity. Here, these active samples were incubated with 2,2,2,-trifluoroethanol (TFE), a product analog that serves as a readily visualized active-site probe. Interactions of TFE with the CuD site were observed by both pulsed ENDOR spectroscopy and cryoEM, implicating CuD and the surrounding hydrophobic pocket as the likely site of methane oxidation. Use of these orthogonal techniques on parallel samples is a powerful approach that can circumvent difficulties in interpreting metalloenzyme cryoEM maps.

Bio-sorptive remediation of crude oil polluted sea water using plantain (Musa parasidiaca) leaves as bio-based sorbent: Parametric optimization by Taguchi technique, equilibrium isotherm and kinetic modelling studies

This study investigated the potential of employing plantain leaves as a natural bio-based sorbent for crude oil spill polluted seawater remediation. Type L9(34) Taguchi orthogonal array technique was used to evaluate the effect of four independent bio-sorption factors at three different levels (crude oil initial concentration (X1 7.8, 11.5 and 15.6 g/L), seawater-crude oil temperature (X2 25, 35 and 45 °C), bio-sorbent dosage (X3 1, 2 and 3 g) and bio-sorbent particle size (X4 1.18, 2.36 and 4.72 mm) on two response indices (bio-sorption efficiency (%) and bio-sorption capacity (g/g)). Taguchi optimization technique, numerical-desirability index function optimization technique and a proposed optimization method were utilized to determine the optimum bio-sorption factors needed for the optimum bio-sorption efficiency and bio-sorption capacity. The results demonstrated that the crude oil bio-sorption efficiency of the plantain leaves was significantly influenced by X1, X3 and X4 and the bio-sorption capacity was mainly influenced by X1 and X3. The optimum bio-sorption efficiency and the optimum bio-sorption capacity were 99.05 % and 12.82 g/g, respectively, obtained at optimum combination of factors and levels of X11 (7.8 g/L), X33 (3 g) and X41 (1.18 mm) for bio-sorption efficiency and X13 (15.6 g/L) X31 (1 g) for bio-sorption capacity. The Freundlich and Dubinin-Rudeshkevich isotherm models best explain the equilibrium bio-sorption data, while the pseudo-second order kinetic model best describes the bio-sorption kinetics. The bio-sorptive remediation mechanism followed dual mechanism of physical and chemical bio-sorption and the mass transfer controlled by film diffusion. The maximum bio-sorption capacity (Kf) was 14.0 gg-1.

Characterization and Reverse Engineering of Pharmaceuticals: Role of Thermoanalytical Techniques

During pharmaceutical or biopharmaceutical drug product development, one of the most important steps to be followed is characterization and reverse engineering of the drug product. Out of so many characterization tools and orthogonal reverse engineering techniques, thermoanalytical methods are the most useful techniques. Different thermoanalytical techniques are used to identify, quantify and understand the interaction between different polymorphic forms of drug substances and excipients. These techniques are also used to monitor the physical form (amorphous or crystalline) of the drug substance in drug product throughout its manufacturing processes and helps in identifying, omitting or modifying the steps or processes responsible for change in physical or polymorphic form of the drug substance in the finished drug product. Thermoanalytical techniques are not only useful for characterization of small molecules but also extensively applied in analysis of biological samples and nano-formulations. In current scenario, pharmaceutical development specifically during generic drug development the most useful step is the reverse engineering. When reverse engineering of drug product is concerned, thermoanalytical techniques are the best tools to be used to prove the similarity of physico-chemical properties or same state of matter or arrangement of matter between test and reference products. However, in earlier days these techniques were not used as frequently as the other techniques like spectroscopy and chromatography. Various reasons for limited use of thermoanalytical techniques were unavailability of software or compatible hardware, manual sampling process and a tedious process of manual calculation which consumes lots of time. Now a day, due to advancement of technology, automation, use of robotics, and better understanding, and the thermal analysis not only become a powerful tool but also increase the throughput. The present review focuses on some of the most commonly used Thermoanalytical techniques e.g. Differential Scanning Calorimeter (DSC), Thermogravimetric Analysis (TGA), Solution Calorimeter (SC), Thermo Mechanical Analysis (TMA) and Isothermal Titration Calorimeter (ITC) for characterization and reverse engineering of different dosage forms like solid oral dosage forms, injectable formulation, inhalation formulation, ophthalmic formulation, and biosimilar formulation products such as peptides and proteins using specific case studies.

Dynamic analysis for V-notch in a piezomagnetic bi-material strip under SH guided wave

In this paper, the problem of a V-notch with complex boundary conditions in a piezomagnetic bi-material strip is studied. Firstly, SH guided wave is considered as an external load acting on piezomagnetic bi-material strip, on the basis of repeated image superposition, the analytical expression of scattering wave is conducted, which satisfies the stress free and magnetic insulation conditions on the upper and lower horizontal boundaries of the strip. Then, the analytical expression of standing wave is established, which satisfies the stress free and magnetic insulation conditions on the boundaries of V-notch by the fractional Bessel function expansion method and Graf addition theorem. Finally, Green’s function method is applied, the bi-material strip is divided into two parts along the vertical interface, a pair of in-plane magnetic field and out-plane forces are applied on the vertical interface, and the first kind of Fredholm integral equations are set up and solved by applying orthogonal function expansion technique and effective truncation. Results clarified the influence on the dynamic stress concentration factor and magnetic field intensity concentration factor under proper conditions. Besides, the analytical solutions are compared with the finite element solutions to verify the accuracy of the conclusions in this article.