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Abstract Battery-based electric vehicles (BEVs) in the United States (U.S.) set a new sales record in 2022, driven by technology, policy, environmental, and economic objectives. However, the rapid deployment of BEVs and charging infrastructure without a careful review of their integration with the electric grid can have negative economic impacts on reliable and resilient electricity supply. Bi-directional power transfer (Bi-Di) vehicle-grid integration technologies and services such as vehicle-to-home or building (V2H/B) and vehicle-to-grid (V2G) can potentially lower local and system peak demand, improve economics for grid operators, and benefit BEV customers. Original equipment manufacturers (OEMs) in the automotive industry are exploring technologies and economics (techno-economics) for Bi-Di services. The study conducted a literature review of eleven case studies in the U.S. and Europe that featured Bi-Di demonstrations from 2005 to 2022 to highlight insights and techno-economic opportunities and challenges for OEMs. The findings should motivate the OEMs to prioritize technology innovation and business models to increase BEV sales and gain continuous revenue from Bi-Di services, which can potentially transition "car makers" to "technology solution" companies.

An online, amendable classifier for detecting malaria parasite country of origin from genomic data is developed using a machine learning approach.

Mutations in the Betaine aldehyde dehydrogenase 2 (OsBadh2) gene resulted in aroma, which is a highly preferred grain quality attribute in rice. However, research on naturally occurring aromatic rice has revealed ambiguity and controversy regarding aroma emission, stress tolerance, and response to salinity. In this study, mutant lines of two non-aromatic varieties, Huaidao#5 (WT_HD) and Jiahua#1 (WT_JH), were generated by targeted mutagenesis of OsBadh2 using CRISPR/Cas9 technology. The mutant lines of both varieties became aromatic; however, WT_HD mutants exhibited an improved tolerance, while those of WT_JH showed a reduced tolerance to salt stress. To gain insight into the molecular mechanism leading to the opposite effects, comparative analyses of the physiological activities and expressions of aroma- and salinity-related genes were investigated. The WT_HD mutants had a lower mean increment rate of malondialdehyde, superoxide dismutase, glutamate, and proline content, with a higher mean increment rate of γ-aminobutyric acid, hydrogen peroxide, and catalase than the WT_JH mutants. Fluctuations were also detected in the salinity-related gene expression. Thus, the response mechanism of OsBadh2 mutants is complicated where the genetic makeup of the rice variety and interactions of several genes are involved, which requires more in-depth research to explore the possibility of producing highly tolerant aromatic rice genotypes.

Invasive foodborne Listeria monocytogenes infection causes gastroenteritis, septicemia, meningitis, and chorioamnionitis, and is associated with high case-fatality rates in the elderly. It is unclear how aging alters gut microbiota, increases risk of listeriosis, and causes dysbiosis post-infection. We used a geriatric murine model of listeriosis as human surrogate of listeriosis for aging individuals to study the effect of aging and L. monocytogenes infection. Aging and listeriosis-induced perturbation of gut microbiota and disease severity were compared between young-adult and old mice. Young-adult and old mice were dosed intragastrically with L. monocytogenes. Fecal pellets were collected pre- and post-infection for microbiome analysis. Infected old mice had higher Listeria colonization in liver, spleen, and feces. Metagenomics analyses of fecal DNA-sequences showed increase in α-diversity as mice aged, and infection reduced its diversity. The relative abundance of major bacterial phylum like, Bacteroidetes and Firmicutes remained stable over aging or infection, while the Verrucomicrobia phylum was significantly reduced only in infected old mice. Old mice showed a marked reduction in Clostridaiceae and Lactobacillaceae bacteria even before infection when compared to uninfected young-adult mice. L. monocytogenes infection increased the abundance of Porphyromonadaceae and Prevotellaceae in young-adult mice, while members of the Ruminococcaceae and Lachnospiraceae family were significantly increased in old mice. The abundance of the genera Blautia and Alistipes were significantly reduced post-infection in young-adult and in old mice as compared to their uninfected counterparts. Butyrate producing, immune-modulating bacterial species, like Pseudoflavonifractor and Faecalibacterium were significantly increased only in old infected mice, correlating with increased intestinal inflammatory mRNA up-regulation from old mice tissue. Histologic analyses of gastric tissues showed extensive lesions in the Listeria-infected old mice, more so in the non-glandular region and fundus than in the pylorus. Commensal species like Lactobacillus, Clostridiales, and Akkermansia were only abundant in infected young-adult mice but their abundance diminished in the infected old mice. Listeriosis in old mice enhances the abundance of butyrate-producing inflammatory members of the Ruminococcaceae/Lachnospiraceae bacteria while reducing/eliminating beneficial commensals in the gut. Results of this study indicate that, aging may affect the composition of gut microbiota and increase the risk of invasive L. monocytogenes infection.

Advanced correlation filters are an effective tool for target detection within a particular class. Most correlation filters are derived from a complex filter equation leading to a closed form filter solution. The response of the correlation filter depends upon the selected values of the optimal trade-off (OT) parameters. In this paper, the OT parameters are optimized using particle swarm optimization with respect to two different cost functions. The optimization has been made generic and is applied to each target separately in order to achieve the best possible result for each scenario. The filters obtained using standard particle swarm optimization (PSO) and hierarchal particle swarm optimization algorithms have been compared for various test images with the filter solutions available in the literature. It has been shown that optimization improves the performance of the filters significantly.

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences.

Lung cancer is one of the major causes of cancer-related deaths due to its aggressive nature and delayed detections at advanced stages. Early detection of lung cancer is very important for the survival of an individual, and is a significant challenging problem. Generally, chest radiographs (X-ray) and computed tomography (CT) scans are used initially for the diagnosis of the malignant nodules; however, the possible existence of benign nodules leads to erroneous decisions. At early stages, the benign and the malignant nodules show very close resemblance to each other. In this paper, a novel deep learning-based model with multiple strategies is proposed for the precise diagnosis of the malignant nodules. Due to the recent achievements of deep convolutional neural networks (CNN) in image analysis, we have used two deep three-dimensional (3D) customized mixed link network (CMixNet) architectures for lung nodule detection and classification, respectively. Nodule detections were performed through faster R-CNN on efficiently-learned features from CMixNet and U-Net like encoder−decoder architecture. Classification of the nodules was performed through a gradient boosting machine (GBM) on the learned features from the designed 3D CMixNet structure. To reduce false positives and misdiagnosis results due to different types of errors, the final decision was performed in connection with physiological symptoms and clinical biomarkers. With the advent of the internet of things (IoT) and electro-medical technology, wireless body area networks (WBANs) provide continuous monitoring of patients, which helps in diagnosis of chronic diseases—especially metastatic cancers. The deep learning model for nodules’ detection and classification, combined with clinical factors, helps in the reduction of misdiagnosis and false positive (FP) results in early-stage lung cancer diagnosis. The proposed system was evaluated on LIDC-IDRI datasets in the form of sensitivity (94%) and specificity (91%), and better results were obatined compared to the existing methods.

In this paper, a double-random phase-encoding technique-based text encryption and hiding method is proposed. First, the secret text is transformed into a 2-dimensional array and the higher bits of the elements in the transformed array are used to store the bit stream of the secret text, while the lower bits are filled with specific values. Then, the transformed array is encoded with double-random phase-encoding technique. Finally, the encoded array is superimposed on an expanded host image to obtain the image embedded with hidden data. The performance of the proposed technique, including the hiding capacity, the recovery accuracy of the secret text, and the quality of the image embedded with hidden data, is tested via analytical modeling and test data stream. Experimental results show that the secret text can be recovered either accurately or almost accurately, while maintaining the quality of the host image embedded with hidden data by properly selecting the method of transforming the secret text into an array and the superimposition coefficient. By using optical information processing techniques, the proposed method has been found to significantly improve the security of text information transmission, while ensuring hiding capacity at a prescribed level.

Cholesterol granuloma is a rare, well-defined lesion of the orbit. In the orbit, diploe of the frontal bone is involved almost exclusively. We report an atypical case of cholesterol granuloma involving superomedial quadrant of orbit. A 42-year-old male presented with progressive, painless, proptosis with infero-temporal displacement of left eye. A large mass was felt beneath the bony orbital margin in the superomedial quadrant of the left orbit. Computerized tomography (CT) scan revealed an extraconal superomedial, heterogeneous enhancing mass which was isodense with brain and pushing the globe inferolaterally and anteriorly. Excision biopsy of the tumor revealed the typical features of a cholesterol granuloma without any epithelial elements. Cholesterol granuloma of the orbit is a rare entity, but it can be diagnosed and differentiated from other lesions of the superior orbit by its characteristic clinical, radiological and histopathological features. An appropriate intervention in time carries a good prognosis with almost no recurrence.