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The direct laser acceleration (DLA) of electrons in a preformed ion channel is examined theoretically using a chirped circularly polarized (CP) laser pulse. The electron acceleration and energy gain from the direct laser beam are enhanced by the effects of linear frequency chirp and the electrostatic space charge field created in the ion channel. The electron trapping and acceleration is strengthened by the frequency chirped CP laser pulse within the created ion cavity. The presence of a preformed ion channel, on the other hand, confines oscillatory electron motion and injects it into the accelerating fields of the laser. This provides a strong betatron resonance between the electrons and electric fields of laser pulse inside the plasma-ion cavity. The chirped CP laser pulse appears to get more energy for electrons than the transformed limited laser pulse when the parameters of the chirped laser pulse and the density in the preformed ion channel are tuned. This study with a chirped CP laser pulses added a new dimension to the DLA mechanisms in a plasma-ion channel.Graphical abstract

The paper presents a small survey on Punjabi morphological analyzer and generator, which does not give any morphological response to lexemes of Malawi dialect of Punjabi. This analyzer works well with the standard variety only. However, it fails to provide an answer when the input is colloquial. The random choice of approximately, (42 words/lexemes, e.g. ਕਾਤੋਂ/ ‘why’, ਉਂਈ/ ‘thus’, ਭੁੰਨਹੋਣਾ/ ‘Unbearable’, ਥੁੰਨੀ/ ‘eating’, ਅੜੀ/ ‘stubborn’, ਭਨਾਲੀ/ ‘breaking’, ਮੰਨਲਾ/ ‘suppose’, ਖਿਜੀ/ ‘annoying’ etc.) is not trained either for the analyzer nor the generator. They are unidentified and unrecognized. In this regard, the schemes of SGMA (similar guidelines for morphological analyzer) or SMGMA (similar but modified guidelines for morphological analyzer) could adopt for booming the performance of Punjabi morphological analyzer and widening its scope in the future.

Objective: The aim of the present work was to propose and implement deep neural network (DNN)-based handheld diagnosis system for more accurate diagnosis and severity assessment of individuals with autism spectrum disorder (ASD). Methods: Initially, the learning of the proposed system for ASD diagnosis was performed by implementing DNN algorithms such as a convolutional neural network (CNN) and long short-term memory (LSTM), and multilayer perceptron (MLP) with DSM-V based acquired dataset. The performance of the DNN algorithms was analyzed based on parameters viz. accuracy, loss, mean squared error (MSE), precision, recall, and area under the curve (AUC) during the training and validation process. Later, the optimum DNN algorithm, among the tested algorithms, was implemented on handheld diagnosis system (HDS) and the performance of HDS was analyzed. The stability of proposed DNN-based HDS was validated with the dataset group of 20 ASD and 20 typically developed (TD) individuals. Results: It was observed during comparative analysis that LSTM resulted better in ASD diagnosis as compared to other artificial intelligence (AI) algorithms such as CNN and MLP since LSTM showed stabilized results achieving maximum accuracy in less consumption of epochs with minimum MSE and loss. Further, the LSTM based proposed HDS for ASD achieved optimum results with 100% accuracy in reference to DSM-V, which was validated statistically using a group of ASD and TD individuals. Conclusion: The use of advanced AI algorithms could play an important role in the diagnosis of ASD in today's era. Since the proposed LSTM based HDS for ASD and determination of its severity provided accurate results with maximum accuracy with reference to DSM-V criteria, the proposed HDS could be the best alternative to the manual diagnosis system for diagnosis of ASD.

Gas Detection Systems (GDSs) are critical safety technologies deployed in semiconductor wafer fabrication facilities to monitor the presence of hazardous gases. A GDS receives input from gas detectors equipped with consumable gas sensors, such as electrochemical (EC) and metal oxide semiconductor (MOS) types, which are used to detect toxic, flammable, or reactive gases. However, over time, sensors degradations, accuracy drift, and cross-sensitivity to interference gases compromise their intended performance. To maintain sensor accuracy and reliability, routine manual calibration is required—an approach that is resource-intensive, time-consuming, and prone to human error, especially in facilities with extensive networks of gas detectors. This systematic review (PROSPERO on 11th October 2025 Registration number: 1166004) explored minimizing or eliminating the dependency on manual calibration. Findings indicate that using properly calibrated gas sensor data can support advanced data analytics and machine learning algorithms to correct accuracy drift and improve gas selectivity. Techniques such as Principal Component Analysis (PCA), Support Vector Machines (SVMs), multivariate regression, and calibration transfer have been effectively applied to differentiate target gases from interferences and compensate for sensor aging and environmental variability. The paper also explores the emerging potential for integrating calibration-free or self-correcting gas sensor systems into existing GDS infrastructures. Despite significant progress, key research challenges persist. These include understanding the dynamics of sensor response drift due to prolonged gas exposure, synchronizing multi-sensor data collection to minimize time-related drift, and aligning ambient sensor signals with gas analytical references. Future research should prioritize the development of application-specific datasets, adaptive environmental compensation models, and hybrid validation frameworks. These advancements will contribute to the realization of intelligent, autonomous, and data-driven gas detection solutions that are robust, scalable, and well-suited to the operational complexities of modern industrial environments.

Asia has a disproportionately large share of the world's hepatocellular carcinoma (HCC), mainly because of the endemic status of chronic hepatitis B and C viruses, which leads to liver cirrhosis and an increased risk of HCC. This etiological factor presents important opportunities for prevention, early detection, diagnosis, and treatment of HCC. This consensus statement reviews the available medical evidence for management of HCC in Asia, and gives treatment recommendations that are adapted to resource availability in this diverse region with disparate health-care delivery systems.

Abstract Background Inferior vena cava (IVC) filters are used to prevent pulmonary embolism (PE) in patients at a high risk for venous thromboembolism with a contraindication to anticoagulation. Inferior vena cava filters are associated with rare but significant long-term complications such as filter fracture and embolization. Case summary We report the case of a 53-year-old female with an IVC filter inserted 8 years back for the management of recurrent bilateral PE resistant to anticoagulation. Imaging revealed an incidental finding of IVC filter limb fracture and migration to the right heart and the hepatic and renal veins. The patient remained asymptomatic with no impairment in cardiac, liver, or renal function. Due to a high operative risk, the broken IVC filter and embolized filter limbs were not retrieved. Discussion There is no consensus on the management of intracardiac embolization of IVC filters. Intravascular fragments may be removed by endovascular or surgical approaches, depending on the anatomical location. Following IVC filter insertion, an appropriate follow-up must be put in place to ensure removal and limit clinical sequelae that are otherwise avoidable. A multidisciplinary approach to the management of IVC filter fracture and embolization is recommended.

AbstractWe examine the electron acceleration by tightly focused radially polarized laser beam in a preformed ion channel. The tight focusing and polarization of laser beam takes the advantage of extremely intense and asymmetric fields. The longitudinal electric field component at the beam center helps in trapping of electrons. For effective acceleration, the preformed ion plasma channel behaves as an applied external magnetic field. The electrostatic space charge field of this preformed ion channel helps in trapping of electrons and confined them to the accelerating phase. The gain in the energy of the electron is due to the fact that the radial component of electric field becomes zero on the propagation axis and only longitudinal component survives which accelerate the electrons in the longitudinal direction to high energy. The electrostatic space charge field assists in confining the motion of electrons from transverse oscillation and injects them to accelerating field which causes a resonance between electric field of laser and electrons. Because of combined role of tightly focused radially polarized laser and ion channel, the electrons can gain energy of the order of GeV.Graphic abstract

Economic sustainability is indispensable for achieving inclusive growth in the Indian banking sector. A sustainable, robust, and healthy banking system keeps a country rolling on its economic wheels. This research study highlights much-talked-about but less-understood aspects of forensic accounting in the Indian banking sector. It examines forensic accounting's impact on the performance of public and private sector banks. The perspectives of bank managers and officers working in the Delhi National Capital Region (NCR) are the primary focal points of this study. Furthermore, the research paper emphasised the importance of shedding light on the benefits. Its Findings suggest that the demand for forensic accountants will also increase with the adoption of forensic accounting practices in India. Since forensic accounting is still optional, most accounting professionals don’t practice forensic accounting. Therefore, there is a need to spread awareness among accounting professionals about adopting Forensic Accounting Practices. This will also add sustainable corporate governance and make forensic accounting a required component of the governance system.

BackgroundMyDispense is a simulation software developed by Monash University that has been utilized by over 200 institutions worldwide to educate pharmacy students. However, little is known about the processes by which it is used to teach dispensing skills to students and how they use it to facilitate critical thinking in an authentic environment. This study aimed to understand and investigate how simulations are used to teach dispensing skills in pharmacy programs globally, and to determine the opinions, attitudes and experiences of pharmacy educators towards MyDispense and other simulation software within their pharmacy program.MethodsPurposive sampling was used to identify pharmacy institutions for the study. A total of 57 educators were contacted, 18 responded to the study invitation, 12 were MyDispense users and 6 were non-users. Two investigators conducted an inductive thematic analysis to generate key themes and subthemes to provide insight into the opinions, attitudes and experiences towards MyDispense and other simulation software used specifically for dispensing within pharmacy programs.Results26 pharmacy educators were interviewed, of which 14 were individual interviews and four were group interviews. Intercoder reliability was investigated and a Kappa coefficient of 0.72 indicated substantial agreement between both coders. Five main themes were identified: “dispensing and counseling”, which encompassed discussions about how dispensing techniques were taught, the time allocated for students to practice their skills and the use of software other than MyDispense; “description of MyDispense use” includes discussions about the setup of the software, how dispensing skills were taught prior to using MyDispense as well as its use in student assessments; “barriers to MyDispense use”, covers discussions about the obstacles users have faced; “facilitators to use MyDispense”, includes discussion about the various motivators to using MyDispense and lastly “future use and suggested improvements” of MyDispense are covered by the interviewees.ConclusionThe initial outcomes of this project evaluated the awareness and utilization of MyDispense and other dispensing simulations by pharmacy programs globally. By addressing the barriers of use, promotion of the sharing of MyDispense cases can assist in creating more authentic assessments, as well as improving staff workload management. The outcomes of this research will also facilitate the development of a framework for MyDispense implementation, thus streamlining and improving the uptake of MyDispense by pharmacy institutions globally.

Pulmonary arterial hypertension (PAH, or PH Group 1), a disease of aberrant pulmonary vascular remodeling, causing progressive right heart failure (RHF) due to elevation of pulmonary vascular resistance (PVR). Patient mortality risk stratification guides choice and intensity of pharmacological intervention and is assessed by haemodynamics (especially PVR) as well as noninvasive tools including WHO functional class (FC), 6‐min walk distance (6MWD), and NT‐proBNP levels. Quality of life (QOL) assessment is acknowledged as a central aspect of patient‐centered care, but our study sought to extend QOL's role as an additional noninvasive risk marker that could further refine risk stratification and hence therapeutic choices within a “treatment to target” paradigm (aiming to achieve low‐risk status). This study found that QOL assessment using the PAH‐SYMPACT© physical activity tool provided enhanced, independent mortality risk information, with one unit rise in this score associated with a 41% increase in likelihood risk (odds ratio 1.41, 95% confidence interval: 1.01–1.98 (p < 0.05)) of falling within intermediate versus low‐group category. We therefore found further support for additional prognostic value being conferred by measurement of QOL as part of routine PAH evaluation, reinforcing its critical role.