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A radiological and histological comparison of two unusual adrenal incidentalomas

Loong S, Selvarajan S, Khor LY

Malays J Pathol, 2019 Dec;41(3):327-331.
PMID: 31901917

INTRODUCTION: The increasing use of radiological imaging studies has given rise to 'incidentalomas'.
CASE REPORT: We describe two unusual and diverse incidental adrenal gland lesions, an adenomatoid nodule and a mature ganglioneuroma. Both are deemed 'indeterminate' on radiological assessment. On histology, an adenomatoid nodule is composed of variably-dilated thin-walled cysts lined by bland flattened cells and solid areas of tubules lined by eosinophilic cells with plump nuclei and prominent nucleoli. The lining cells are immunoreactive for calretinin and WT1 while negative for CK5/6, ERG and CD31. Mature ganglioneuroma features fascicles of bland spindle cells with intermixed mature ganglion cells disposed within a background myxoid stroma with no immature neuroblastic component. These spindled Schwann cells are S100 positive.
DISCUSSION: Both adenomatoid nodule and mature ganglioneuroma are rare benign adrenal tumours that need to be differentiated from other, more common adrenal lesions. The management of adrenal incidentalomas is challenging. Surgical excision is indicated if an adrenal incidentaloma is more than 4 cm in size, shows malignant features on imaging or evidence of hormone excess.
Metastatic alveolar rhabdomyosarcoma on the fine-needle aspiration cytology of cervical lymph node in an elderly patient, with FISH confirmation: A case report

Zhao Z, Takano A, Lim AST, Lim TH, Selvarajan S

Malays J Pathol, 2020 Apr;42(1):115-119.
PMID: 32342940

INTRODUCTION: Alveolar rhabdomyosarcoma (RMS) usually occurs in adolescents and young adults, and most frequently arises in the extremities.
CASE REPORT: We present a rare case of metastatic alveolar RMS from a nasal primary to cervical lymph nodes (LNs) in an elderly patient, diagnosed on the fine-needle aspiration (FNA) biopsy. Smears showed malignant round cells featuring focal rhabdoid appearance, with rhabdomyoblastic differentiation further supported by immunocytochemical stains. Diagnosis of alveolar RMS was confirmed by fluorescence in situ hybridization (FISH) identifying FOXO1 gene involvement with dual colour break-apart probes at locus 13q14.
DISCUSSION: The differential diagnosis for a small round blue cell tumour in the elderly generally includes metastatic small cell carcinoma, lymphoma, malignant melanoma, RMS, desmoplastic small round cell tumour and Ewing's sarcoma/primitive neuroectodermal tumour. Subtle morphological analysis and expression pattern of immunostaining for skeletal muscle differentiation led to the diagnosis of RMS. Cytogenetic testing on the FOXO1 gene rearrangement helps definite subtyping of alveolar RMS.
Fulltext Experimental analysis of enhanced finite set model predictive control and direct torque control in SRM drives for torque ripple reduction

M D, Samithas D, Balachandran PK, Selvarajan S

Sci Rep, 2024 Jul 22;14(1):16805.
PMID: 39039123 DOI: 10.1038/s41598-024-65202-1

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC.
Dickson polynomial-based secure group authentication scheme for Internet of Things

Syed SA, Manickam S, Uddin M, Alsufyani H, Shorfuzzaman M, Selvarajan S, et al.

Sci Rep, 2024 Feb 28;14(1):4947.
PMID: 38418484 DOI: 10.1038/s41598-024-55044-2

Internet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli's Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency.
Optimal design of hybrid green energy powered reduced switch converter based shunt active power filter using horse herd algorithm

Srilakshmi K, Kondreddi K, Gowri NV, Vangalapudi R, Devakirubakarn S, Balachandran PK, et al.

Sci Rep, 2024 Sep 03;14(1):20447.
PMID: 39227381 DOI: 10.1038/s41598-024-71100-3

Renewable energy sources are playing a leading role in today's world. However, integrating these sources into the distribution network through power electronic devices can lead to power quality (PQ) challenges. This work addresses PQ issues by utilizing a shunt active power filter in combination with an Energy Storage System (ESS), a Wind Energy Generation System (WEGS), and a Solar Energy System. While most previous research has relied on complex methods like the synchronous reference frame (SRF) and active-reactive power (pq) approaches, this work proposes a simplified approach by using a neural network (NN) for generating reference signals, along with the design of a five-level reduced switch voltage source converter. The gain values of the proportional-integral controller (PIC), as well as the parameters for the shunt filter, boost, and buck-boost converters in the WEGS and ESS, are optimally selected using the horse herd optimization algorithm. Additionally, the weights and biases for the neural network (NN) are also determined using this method. The proposed system aims to achieve three key objectives: (1) stabilizing the voltage across the DC bus capacitor; (2) reducing total harmonic distortion (THD) and improving the power factor; and (3) ensuring superior performance under varying demand and PV irradiation conditions. The system's effectiveness is evaluated through three different testing scenarios, with results compared against those obtained using the genetic algorithm, biogeography-based optimization (BBO), as well as conventional SRF and pq methods with PIC. The results clearly demonstrate that the proposed method achieves THD values of 3.69%, 3.76%, and 4.0%, which are lower than those of the other techniques and well within IEEE standards. The method was developed using MATLAB/Simulink version 2022b.