A single LC tank based active voltage balancing circuit for battery management system

Nowadays, battery operated vehicles and machine power tools are becoming popular due to their simple and compact structure, low operating and maintenance costs, moreover renewable energy utilization facility etc. In order to obtain the necessary operating voltage and current of these devices, many electric cells are combined together in series and parallel combination. A series battery balancing circuit can be used to improve the efficiency of each cell charging and discharging process and consequently increase the lifespan of it. A battery management system (BMS) needs an efficient balancing circuit. This paper presents a high-speed single LC-tank DC to DC converter based electric cell balancing schemes. Since the supercapacitors are equivalent of rechargeable battery; in this research two supercapacitors have been used instead of rechargeable batteries. The voltage balance has been maintained by charging and discharging the supercapacitors through a single LC-tank circuit. As a result, the overall voltage balancing time has been reduced and improved the circuit performance. Experimental result shows that the proposed balancing circuit can reduce the voltage difference between the two supercapacitors from 350 mV to 0 V in 284 seconds, which is less time than the existing system. Satu pengubah resonan sesiri telah direka bagi mengimbangi aras voltan pada kenderaan beroperasikan bateri dan pada mesin jana kuasa yang menjadi semakin popular.Ini kerana strukturnya yang mudah dan kompak, kos operasi dan penyelenggaraan yang rendah, termasuk kemudahan penggunaan tenaga kitar semula dan sebagainya. Bagi mendapatkan voltan dan arus operasi yang sesuai, banyak sel elektrik telah digabungkan bersama dalam gabungan sesiri dan selari. Litar pengimbang bateri sesiri boleh digunakan bagi meningkatkan kecekapan setiap proses pengecasan dan penyahcas sel dan sekaligus meningkatkan jangka hayat sel. Sistem pengurusan bateri (BMS) memerlukan litar pengimbang yang cekap. Kertas ini membentangkan tentang satu pengubah DC-DC tangki-LC berkelajuan tinggi berdasarkan skim pengimbang sel elektrik. Oleh kerana supercapacitors bertindak seperti bateri boleh cas semula; penyelidikan ini telah mengguna pakai dua super-kapasitor dan bukan bateri boleh cas semula. Baki voltan telah dikekalkan dengan mengecas dan menyahcas super-kapasitor menggunakan satu litar tangki-LC. Dengan ini, masa pengimbang keseluruhan voltan dapat dikurangkan dan kecekapan litar dapat ditingkatkan. Hasil eksperimen menunjukkan litar pengimbang yang dicadangkan dapat mengurangkan perbezaan voltan antara dua super-kapasitor dari 350 mV kepada 0 V dalam tempoh 284 saat, kurang daripada masa sistem sedia ada

A series regeneration converter technique for voltage balancing of energy storage devices

A single series resonant converter has been designed to balance the voltage level of a storage battery for electric vehicles. The proposed design has been simulated and verified by using two 100F supercapacitors instate of the conventional rechargeable battery. A voltage monitoring circuit detects the voltage condition of the individual capacitor and sends the voltage status to the control circuit for action. A technique has been developed to control a set of switches to transfer the current between the capacitor to balance the voltage level. The MATLAB simulated result shows the balancing circuit decreases the voltage difference between the two supercapacitors from 200 mV to 0V in 140 seconds, which is less than the existing methods. This fast voltage balancing technique can be used in the battery management system or electric vehicles for long lasting the battery life

DNA Barcoding of Six Commercially Important Groupers (Epinephelidae) from Langsa, Aceh, Indonesia

Groupers are among the fish groups that are difficult to recognize due to their high morphological similarities. Therefore, molecular techniques, particularly DNA barcoding, are extensively utilized to differentiate this fish group. This study aimed to analyze and validate six grouper species belonging to the Epinephelidae family that were harvested from Langsa district waters in Aceh province, Indonesia, based on DNA barcode data. It was conducted from June to December 2021, with the fish specimens collected from fishers at fish landing sites and the fish market in Langsa City, Aceh province. A total of 22 grouper sequences belonging to six species were generated, namely Epinephelus coioides, E. bleekeri, E. malabaricus, E. erythrurus, E. sexfasciatus and Mycteroperca poecilonotus (formerly Epinephelus poecilonotus). Genetic distance within these species ranged from 0.10 to 0.73% (average: 0.40%). Notably, E. malabaricus and E. coioides exhibited the closest genetic kinship (4.07%), while E. sexfasciatus and M. poecilonotus displayed the greatest genetic distance (19.33%). This study provides the first DNA reference for grouper in Langsa district, Indonesia, with significant implications for future sustainable grouper management

Active voltage balancing circuit using single switched-capacitor and series LC resonant energy carrier

Single switched-capacitor and series LC resonant converter-based active voltage balancing circuit are presented in this Letter. This converter is proposed to balance the cell voltage in series-connected electrochemical energy storage devices namely battery or supercapacitor. This balancing circuit directly transfers the energy from higher capacitive energy storage cells to lower energy storage cells in the string. It realises the maximum energy recovery and zero voltage gap between the cells and overcomes the drawback of switching loss, conduction loss, balancing time duration, and the voltage difference between the cells of conventional switched-capacitor as well as single LC converter. The details of the balancing circuit operation, theoretical, and mathematical analysis are presented. The experimental result demonstrated that the balancing circuit result where the voltage difference is 451–0 mV in 124 min for two 12 V, 4.5 Ah lead-acid batteries

Automated measurement of penile curvature using deep learning-based novel quantification method

ObjectiveDevelop a reliable, automated deep learning-based method for accurate measurement of penile curvature (PC) using 2-dimensional images.Materials and methodsA set of nine 3D-printed models was used to generate a batch of 913 images of penile curvature (PC) with varying configurations (curvature range 18° to 86°). The penile region was initially localized and cropped using a YOLOv5 model, after which the shaft area was extracted using a UNet-based segmentation model. The penile shaft was then divided into three distinct predefined regions: the distal zone, curvature zone, and proximal zone. To measure PC, we identified four distinct locations on the shaft that reflected the mid-axes of proximal and distal segments, then trained an HRNet model to predict these landmarks and calculate curvature angle in both the 3D-printed models and masked segmented images derived from these. Finally, the optimized HRNet model was applied to quantify PC in medical images of real human patients and the accuracy of this novel method was determined.ResultsWe obtained a mean absolute error (MAE) of angle measurement <5° for both penile model images and their derivative masks. For real patient images, AI prediction varied between 1.7° (for cases of ∼30° PC) and approximately 6° (for cases of 70° PC) compared with assessment by a clinical expert.DiscussionThis study demonstrates a novel approach to the automated, accurate measurement of PC that could significantly improve patient assessment by surgeons and hypospadiology researchers. This method may overcome current limitations encountered when applying conventional methods of measuring arc-type PC

QCovSML: A reliable COVID-19 detection system using CBC biomarkers by a stacking machine learning model

The reverse transcription-polymerase chain reaction (RT-PCR) test is considered the current gold standard for the detection of coronavirus disease (COVID-19), although it suffers from some shortcomings, namely comparatively longer turnaround time, higher false-negative rates around 20–25%, and higher cost equipment. Therefore, finding an efficient, robust, accurate, and widely available, and accessible alternative to RT-PCR for COVID-19 diagnosis is a matter of utmost importance. This study proposes a complete blood count (CBC) biomarkers-based COVID-19 detection system using a stacking machine learning (SML) model, which could be a fast and less expensive alternative. This study used seven different publicly available datasets, where the largest one consisting of fifteen CBC biomarkers collected from 1624 patients (52% COVID-19 positive) admitted at San Raphael Hospital, Italy from February to May 2020 was used to train and validate the proposed model. White blood cell count, monocytes (%), lymphocyte (%), and age parameters collected from the patients during hospital admission were found to be important biomarkers for COVID-19 disease prediction using five different feature selection techniques. Our stacking model produced the best performance with weighted precision, sensitivity, specificity, overall accuracy, and F1-score of 91.44%, 91.44%, 91.44%, 91.45%, and 91.45%, respectively. The stacking machine learning model improved the performance in comparison to other state-of-the-art machine learning classifiers. Finally, a nomogram-based scoring system (QCovSML) was constructed using this stacking approach to predict the COVID-19 patients. The cut-off value of the QCovSML system for classifying COVID-19 and Non-COVID patients was 4.8. Six datasets from three different countries were used to externally validate the proposed model to evaluate its generalizability and robustness. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.961 for the internal cohort and average AUC of 0.967 for all external validation cohort, respectively. The external validation shows an average weighted precision, sensitivity, F1-score, specificity, and overall accuracy of 92.02%, 95.59%, 93.73%, 90.54%, and 93.34%, respectively

Development, characterization, and in vivo validation of a humanized C6 monoclonal antibody that Inhibits the membrane attack complex

Damage and disease of nerves activates the complement system. We demonstrated that activation of the terminal pathway of the complement system leads to the formation of the membrane attack complex (MAC) and delays regeneration in the peripheral nervous system. Animals deficient in the complement component C6 showed improved recovery after neuronal trauma. Thus, inhibitors of the MAC might be of therapeutic use in neurological disease. Here, we describe the development, structure, mode of action, and properties of a novel therapeutic monoclonal antibody, CP010, against C6 that prevents formation of the MAC in vivo. The monoclonal antibody is humanized and specific for C6 and binds to an epitope in the FIM1-2 domain of human and primate C6 with sub-nanomolar affinity. Using biophysical and structural studies, we show that the anti-C6 antibody prevents the interaction between C6 and C5/C5b by blocking the C6 FIM1-2:C5 C345c axis. Systemic administration of the anti-C6 mAb caused complete depletion of free C6 in circulation in transgenic rats expressing human C6 and thereby inhibited MAC formation. The antibody prevented disease in experimental autoimmune myasthenia gravis and ameliorated relapse in chronic relapsing experimental autoimmune encephalomyelitis in human C6 transgenic rats. CP010 is a promising complement C6 inhibitor that prevents MAC formation. Systemic administration of this C6 monoclonal antibody has therapeutic potential in the treatment of neuronal disease

チタン ト マグネシウム ゴウキン ノ エネルギー セイギョ ニヨル スイチュウ バクハツ アツセツ ニ カンスル ケンキュウ

熊本大