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Abstract Background Antimicrobial resistance is considered one of the greatest threats to human health, according to the World Health Organization (WHO). Gram-negative bacteria, especially carbapenem-resistant Enterobacteriaceae (CRE), have become a significant concern in antimicrobial-resistant bacteria’s global emergence and spread. Among CRE pathogens, carbapenem-resistant Klebsiella pneumoniae (CRKP) has recently been reported as a highly infectious strain associated with high mortality and morbidity in adults and immunocompromised patients. Additionally, CRKP-related infections are challenging to treat, as carbapenems are the last resort of antibiotics. Therefore, developing novel drugs with different mechanisms of action from existing drugs is urgently required to defeat this lethal menace. Under such circumstances, probiotics can be therapeutic candidates for inhibiting pathogens. Thus, our research team has been focusing on probiotics for a long time to develop potential anti-CRKP drug agents. Methods After extensive efforts, we finally found a novel probiotic strain, Lactobacillus sakei PMC104, suitable for treating CRKP infection. It was isolated from kimchi. As part of our expansion into therapeutic development, we evaluated the L. sakei strain effect against CRKP pathogens in both in vitro and in vivo experiments. Moreover, we conducted media optimization at food grade and then established a scale-up process on a pilot scale. Subsequently, a lyophilizate was obtained and used in a mouse model infected with CRKP. Results Data demonstrated that the L. sakei strain has an inhibitory effect against CRKP infection both in in vitro and in vivo experiments and also increases the level of short-chain fatty acids in the feces of mice after receiving L. sakei strain treatment for 10 days. Furthermore, treatment with L. sakei powder remarkably diminished body weight loss, mortality, and illness severity in CRKP-infected mice, showing a preventive effect of our PMC 104 against CRKP infection. Discussion Our results demonstrate the potential therapeutic effect of our candidate probiotic strain against CRKP, suggesting that L. sakei PMC 104 could be considered an antimicrobial candidate for treating CRKP infections. However, extensive studies, including additional toxicity tests and clinical trials, are still essential to develop it as a new anti-CRKP therapeutic agent.

ABSTRACT Multiple drug resistance to Acinetobacter baumannii infection treatment is a great challenge for neuro‐intensivists due to poor drug penetration through the blood–brain barrier (BBB). Fortunately, the intraventricular administration of polymyxin‐B and tigecycline seems to be effective; there are few case reports demonstrating the effectiveness of such treatments. Here, we report the case of a 24‐year‐old male who presented with fever and neck rigidity after intracranial drainage following lung infection caused by MDR Acinetobacter baumannii. Due to the presence of turbid CSF, the administration of the intrathecal (ITH) route polymyxin‐B and tigecycline is not possible. In this situation, the neuro‐intensivist decided to start intraventricular tigecycline and polymyxin‐B administration along with IV tigecycline and polymyxin‐B via the intraventricular route, which was feasible because the patient had an external ventricular drain (EVD) due to obstructive hydrocephalus caused by the neurosurgeon after excision of the tumor.

Sesame (Sesamum indicum L.) is an ancient oilseed crop of the Pedaliaceae family with high oil content and potential health benefits. SHI RELATED SEQUENCE (SRS) proteins are the transcription factors (TFs) specific to plants that contain RING-like zinc finger domain and are associated with the regulation of several physiological and biochemical processes. They also play vital roles in plant growth and development such as root formation, leaf development, floral development, hormone biosynthesis, signal transduction, and biotic and abiotic stress responses. Nevertheless, the SRS gene family was not reported in sesame yet. In this study, identification, molecular characterization, phylogenetic relationship, cis-acting regulatory elements, protein-protein interaction, syntenic relationship, duplication events and expression pattern of SRS genes were analyzed in S. indicum. We identified total six SiSRS genes on seven different linkage groups in the S. indicum genome by comparing with the other species, including the model plant Arabidopsis thaliana. The SiSRS genes showed variation in their structure like 2–5 exons and 1–4 introns. Like other species, SiSRS proteins also contained ‘RING-like zinc finger’ and ‘LRP1’ domains. Then, the SiSRS genes were clustered into subclasses via phylogenetic analysis with proteins of S. indicum, A. thaliana, and some other plant species. The cis-acting regulatory elements analysis revealed that the promoter region of SiSRS4 (SIN_1011561) showed the highest 13 and 16 elements for light- and phytohormone-responses whereas, SiSRS1 (SIN_1015187) showed the highest 15 elements for stress-response. The ABREs, or ABA-responsive elements, were found in a maximum of 8 copies in the SiSRS3 (SIN 1009100). Moreover, the available RNA-seq based expression of SiSRS genes revealed variation in expression patterns between stress-treated and non-treated samples, especially in drought and salinity conditions in. S. indicum. Two SiSRS genes like SiSRS1 (SIN_1015187) and SiSRS5 (SIN_1021065), also exhibited variable expression patterns between control vs PEG-treated sesame root samples and three SiSRS genes, including SiSRS1 (SIN_1015187), SiSRS2 (SIN_1003328) and SiSRS5 (SIN_1021065) were responsive to salinity treatments. The present outcomes will encourage more research into the gene expression and functionality analysis of SiSRS genes in S. indicum and other related species.

Predictive maintenance has gained importance across various industries, including the automotive sector. It is very challenging to detect vehicle failures in advance due to the intricate composition of various components and sensors. The vehicle’s reliability is of utmost importance for ensuring the absence of fatalities or malfunctions to foster economic development. This study introduces an innovative method for developing a predictive framework for vehicle engines with faster and higher decision accuracy. The framework is specifically designed to recognize patterns and abnormalities that may suggest prospective engine problems in real-time and allow proactive maintenance. We assessed the performance of the developed vehicular engine health monitoring systems using a deep learning model based on essential measures like root mean square error, root mean square deviation, mean absolute error, accuracy, confusion matrix, and area under the curve. In this case, the deep learning models are developed by following ensemble techniques using the most prominently used machine learning techniques. Significantly, Stacked Model 1 outperformed other stacked models (Models 2 and 3) and achieved an impressive AUC value of 0.9702 with a low root mean square error (RMSE) of 0.3355, a high accuracy rate of 0.9470, and a precision of 0.9486. It happens due to the effective incorporation of different approaches into Stacked Model 1, which signifies a significant advancement in predicting vehicular engine failures. The model can be used in real-time monitoring systems to continuously monitor the health of vehicular engines and provide early warnings of potential failures, thereby reducing maintenance costs and improving safety.

Xerosis, characterized by dry, rough skin, causes discomfort and aesthetic concerns, necessitating effective treatment. Traditional treatments often show limited efficacy, prompting the need for innovative therapies. This study highlights the efficacy of microbiome therapeutic LP51, derived from a healthy vaginal microbiome, in improving xerosis. A double-blind clinical trial involving 43 subjects with dry inner arm skin compared the effects of a 2.9% LP51 extract formulation to a placebo over 4 weeks. The LP51 group exhibited a significant increase in stratum corneum hydration (10.0 A.U.) compared to the placebo group (4.8 A.U.) and a 21.4% decrease in transepidermal water loss (TEWL), whereas the placebo group showed no significant change. LP51 also demonstrated benefits in enhancing skin hydration, improving the skin barrier, and exhibited anti-atopic, anti-inflammatory, and antioxidant properties. Safety was confirmed through in vitro cytotoxicity tests. These effects are attributed to the microbiome-safe component in LP51 and its role in improving xerosis, reflected by an increase in the xerosis-microbiome index, defined by the Firmicutes/Actinobacteria ratio. These findings position microbiome therapeutic LP51 as a promising novel treatment for xerosis.

Human interaction recognition (HIR) between two people in videos is a critical field in computer vision and pattern recognition, aimed at identifying and understanding human interaction and actions for applications such as healthcare, surveillance, and human–computer interaction. Despite its significance, video-based HIR faces challenges in achieving satisfactory performance due to the complexity of human actions, variations in motion, different viewpoints, and environmental factors. In the study, we proposed a two-stream deep learning-based HIR system to address these challenges and improve the accuracy and reliability of HIR systems. In the process, two streams extract hierarchical features based on the skeleton and RGB information, respectively. In the first stream, we utilised YOLOv8-Pose for human pose extraction, then extracted features with three stacked LSM modules and enhanced them with a dense layer that is considered the final feature of the first stream. In the second stream, we utilised SAM on the input videos, and after filtering the Segment Anything Model (SAM) feature, we employed integrated LSTM and GRU to extract the long-range dependency feature and then enhanced them with a dense layer that was considered the final feature for the second stream module. Here, SAM was utilised for segmented mesh generation, and ImageNet was used for feature extraction from images or meshes, focusing on extracting relevant features from sequential image data. Moreover, we newly created a custom filter function to enhance computational efficiency and eliminate irrelevant keypoints and mesh components from the dataset. We concatenated the two stream features and produced the final feature that fed into the classification module. The extensive experiment with the two benchmark datasets of the proposed model achieved 96.56% and 96.16% accuracy, respectively. The high-performance accuracy of the proposed model proved its superiority.

Glioblastoma, also known as grade IV astrocytoma, is an aggressive and quickly developing brain tumor whose median survival period is believed to be between 12 and 18 months. Patients with glioblastoma are at high risk of developing comorbidities like leukemia, atherosclerosis, autism, sudden cardiac death, and pancreatic neoplasms. Identification of influential biomarker genes is crucial to diagnose and design therapeutic targets for cancer. To do this, we considered The Cancer Genome Atlas (TCGA) dataset to identify the significant genes of glioblastoma. Therefore, we pre-processed the dataset and applied the Kruskal-Wallis test and Bonferroni correction methods to select significant biomarker genes. A total of 26 significant dysregulated genes have been identified from 16261 genes, of which 19 are up-regulated and 7 are down-regulated genes. We performed analysis of functional and ontological pathways, protein-protein interactions (PPI), and protein-drug interactions (PDI) to predict the functions of these influential genes. Comorbidities validation was performed using gold benchmark databases. Furthermore, the Cox proportional hazard model and the product-limit (PL) estimator were used to examine the influence of clinical and genetic variables that play an important role in the survival of glioblastoma patients. This study provides the basis of identifying cancer-influencing genes and understanding the impact of glioblastoma on the progression of comorbidities.

Abstract Mycobacterium tuberculosis (M. tb), the etiological agent of tuberculosis (TB), poses a severe challenge for public health and remains the number one cause of death as a single infectious agent. There are 10 million active cases of TB per year with 1.5 million deaths, and 2–3 billion people are estimated to harbor latent M. tb infection. Moreover, the emergence of multi-drug-resistant (MDR), extremely-drug-resistant (XDR), and the recent totally drug-resistant (TDR) M. tb is becoming a global issue that has fueled the need to find new drugs different from existing regimens. In these circumstances, probiotics can be a potential choice, so we focused on developing them as an anti-tuberculosis drug candidate. Here, we report the anti-tubercular activities of Lacticaseibacillus rhamnosus PMC203 isolated from the vaginal microbiota of healthy women. PMC203 exhibited a promising intracellular killing effect against both drug-sensitive and resistant M. tb infected murine macrophage cell line RAW 264.7 without showing any cytotoxicity. Additionally, it also inhibited the growth of M. tb under broth culture medium. PMC203 did not cause weight change or specific clinical symptoms in a 2-week repeated oral administration toxicity test in a guinea pig model. Here, we also found that PMC203 induces autophagy in a dose dependent manner by increasing the signal of well-known autophagy gene markers, suggesting a possible intracellular killing mechanism.

Cotton-wrapped elastane core yarns have been widely used in producing stretch denim fabrics due to their comfortable stretching and recovery, but they suffer from undesirable fabric growth under prolonged or repeated stress. To reduce that problem, an additional semi-elastic multifilament has been incorporated with the elastane core, called dual-core yarn. Herein, it was intended to produce well-engineered dual-core yarns possessing high elasticity with low bagging. Twenty types of cotton-wrapped elastane/T400 multifilament dual-core yarns with different combinations of elastane and T400 tension draft were produced on industrial scale in a spinning mill. Structural parameters, tensile properties and elastic recovery behavior under cyclic loading of the yarns were thoroughly studied. For an optimum combination of elastane/T400 draft, the dual-core yarn attained excellent tenacity and elongation with significantly low evenness, imperfections and hairiness values. More importantly, the results of the cyclic loading study explicitly revealed a remarkable reduction in plastic deformation and stress decay indicating low growth and high resilience of yarn after deformation. The dual-core yarn containing high strength, high elongation and low growth obtained here can have durable stretch jeans with high body movement comfort and long-lasting shape retention.

Patients with advanced cirrhosis of liver present with clinical manifestations such as intracta- ble ascites, severe hyponatremia, and reduced arterial blood pressure. The purpose of this study was to observe the relationship between serum sodium levels and the severity of complications associated with liver cirrhosis. From April 2019 to September 2020, this cross-sectional study was done at the Department of Gastrenterology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh. Total 96 patients with cirrhosis of liver from both sexes in the study were enrolled by using sequential sampling. Patients were divided into Child-pugh classes, and the severity of complications were evaluated. The serum sodium level was tested in all of the patients. The relationships between it and various stages and complications of cirrhosis were statistically investigated. Serum sodium level was decreased significantly from child pugh class A to B to C (p value

The storage roots and leaves of sweet potato are potential sources of human nutrition. Variations may exist in the growth, yield, and nutritional contents of different genotypes. In this experiment, the growth, storage root yield, yield-contributing traits, leaf chlorophyll (Chlo) index, anthocyanin (Antho) index, flavonoid (Flavo) index, nitrogen-balance index (NBI), proximate compositions, and mineral content of the leaves and storage roots of sweet potato genotypes were investigated to identify nutrient-rich and high-yielding sweet potato. A field experiment was performed using the randomized complete block design, and a laboratory analysis was conducted using the completely randomized design with three replicates. Significant variations were observed in the growth, yield-contributing traits, yield of storage roots, leaf indices, proximate compositions, and mineral content of both organs of sweet potato genotypes. The range of the different components were as follows: storage root yield, 2.04 ± 0.18 t/ha to 48.80 ± 12.06 t/ha; dry matter contents of the storage roots and leaves, 20.26%–35.16%, and 10.24%–16.68%, respectively; leaf Chlo index, 27.25 ± 2.12 to 34.51 ± 0.71; Flavo index, 1.10 ± 0.12 to 1.59 ± 0.05; and Antho index, 0.18 ± 0.02 to 0.21 ± 0.03. Except nitrogen-free extract (NFE) and starch, the proximate compositions and mineral contents were higher in leaves than in storage roots. The mineral content of leaves were 0.80% ± 0.01%–1.29% ± 0.03% calcium (Ca), 0.24% ± 0.01%–0.40% ± 0.01% magnesium (Mg), 5.25% ± 0.02%–6.96% ± 0.04% phosphorus (P) and 1.22% ± 0.01%–1.41% ± 0.01% potassium (K). From the findings of this study, it was indicated that leaves are a good source of protein, fiber, and minerals particularly Ca, Mg, P, and K. Thus, storage roots including sweet potato leaves can be consumed to combat malnutrition, particularly in low income groups in developing countries.

Xanthomonas campestris pv. campestris (Xcc), the pathogen of black rot which is the most destructive disease of Brassica vegetables throughout the world. Here, we reported two novel sequence-characterized amplified region (SCAR) markers (i.e., XccR6-60 and XccR6-67) for the detection of Xcc race 6 via re-alignment of the complete genome sequences of Xcc races/ strains/pathovars. The specificity of SCAR primer sets was verified by mean of PCR amplification using the genomic DNA template of Xcc races/strains/pathovars and two other plant infecting bacterial strains. The PCR result revealed that the XccR6-60 and XccR6-67 primer sets amplified 692-bp and 917-bp DNA fragments, respectively, specifically from race 6, while no visible amplification was detected in other samples. In addition, the SCAR primers were highly sensitive and can detect from a very low concentration of genomic DNA of Xcc race 6. However, the complete genome sequence of Xcc race 6 is not yet publicly available. Therefore, the cloning and sequencing of XccR6-60 and XccR6-67 fragments from race 6 provide more evidence of the specificity of these markers. These results indicated that the newly developed SCAR markers can successfully, effectively and rapidly detect Xcc race 6 from other Xcc races/strains/pathovars as well as other plant pathogenic bacteria. This is the first report for race-specific molecular markers for Xcc race 6.

Tomato (Solanum lycopersicum L.) is a popular nutritious vegetable crop grown in Malaysia and other parts of the world. However, fungal diseases such as anthracnose pose significant threats to tomato production by reducing the fruit quality and food value of tomato, resulting in lower market prices of the crop globally. In the present study, the etiology of tomato anthracnose was investigated in commercial tomato farms in Sabah, Malaysia. A total of 22 fungal isolates were obtained from anthracnosed tomato fruits and identified as Colletotrichum species, using morphological characteristics. The phylogenetic relationships of multiple gene sequence alignments such as internal transcribed spacer (ITS), β-tubulin (tub2), glyceraldehyde 3-phosphate dehydrogenase (gapdh), actin (act), and calmodulin (cal), were adopted to accurately identify the Colletotrichum species as C. truncatum. The results of pathogenicity tests revealed that all C. truncatum isolates caused anthracnose disease symptoms on inoculated tomato fruits. To our knowledge, the present study is the first report of tomato anthracnose caused by C. truncatum in Malaysia. The findings of this study will be helpful in disease monitoring, and the development of strategies for effective control of anthracnose on tomato fruits.

Tuberculosis, an infectious disease, is one of the leading causes of death worldwide. Drug-resistant tuberculosis exacerbates its threat. Despite long-term and costly treatment with second-line drugs, treatment failure rates and mortality remain high. Therefore, new strategies for developing new drugs and improving the efficiency of existing drug treatments are urgently needed. Our research team reported that PPs, a new class of potential anti-tuberculosis drug candidates, can inhibit the growth of drug-resistant Mycobacterium tuberculosis. Here, we report a synergistic effect of PPs with ethionamide (ETH), one of the second-line drugs, as a result of further research on PPs. While investigating gene expression changes based on microarray and 2DE (two-dimensional gel electrophoresis), it was found that PPs induced the greatest overexpression of Rv0560c in M. tuberculosis. Based on this result, a protein microarray using Rv0560c protein was performed, and it was confirmed that Rv0560c had the highest interaction with EthR, a repressor for EthA involved in activating ETH. Accordingly, a synergistic experiment was conducted under the hypothesis of increased susceptibility of ETH to M. tuberculosis by PPs. As a result, in the presence of 0.5× MIC PPs, ETH showed a growth inhibitory effect on drug-sensitive and -resistant M. tuberculosis even at a much lower concentration of about 10-fold than the original MIC of ETH. It is also suggested that the effect was due to the interaction between PPs and Rv2887, the repressor of Rv0560c. This effect was also confirmed in a mouse model of pulmonary tuberculosis, confirming the potential of PPs as a booster to enhance the susceptibility of M. tuberculosis to ETH in treating drug-resistant tuberculosis. However, more in-depth mechanistic studies and extensive animal and clinical trials are needed in the future.

As NGS (next-generation sequencing) technology develops, metagenomics-based microbial ecology, that is, microbiome research, has recently led to the science of fermented food. Based on the above technology, a study was conducted to understand the characteristics of vinegar made from bokbunja, a local crop in Gochang-gun, Korea. Physicochemical characteristics of vinegar, organic acid analysis, microbial community analysis, and electronic tongue analysis were explored while fermenting the vinegar for 70 days under eight fermentation conditions according to the concentration of bokbunja liquid (100% or 50%), type of fermenter (porcelain jar or stainless container), and fermentation environment (natural outdoor conditions or temperature/oxygen controlled). As a result, distinct microbial community patterns were found in the stage of acetic acid fermentation and, accordingly, this fermentation of Gochang vinegar is classified into three categories. Vinegar prepared by the traditional method of outdoor fermentation using jars showed characteristics of “Acetobacter (42.1%)/Lactobacillus (56.9%) fusion fermentation”. Under conditions where oxygen and temperature were controlled indoors using jars, characteristics of “Komagataeibacter (90.2%) fermentation” were found. “Lactobacillus (92.2%) fermentation” characteristics were discovered under natural outdoor conditions using stainless steel containers. These fermentation pattern differences were related to taxonomic phylogenetic diversity, which was also considered involved in determining organic acid production and taste. These results will be helpful as a scientific basis for understanding the fermentation characteristics of Gochang vinegar and developing high-value-added traditional vinegar products.

Minor fruits are rich source of vitamins and minerals which are unexplored. This study was undertaken to evaluate biochemical and nutritional values of selected underutilized minor fruits in Bangladesh. The selected minor fruits were Monkey jack (Artocarpus lakoocha), Velvet apple (Diospyros discolor), River ebony (Diospyros peregrina), Cowa (Garcinia cowa), Governor’s plum (Flacourtia indica), Flacourtia (Flacourtia jangomas) and Red pear (Protium serratum). Ripe fruits were collected from coastal and hilly areas of Bangladesh and nutritional analysis was done following standard protocols during February to November 2018. Results showed that River ebony contained the maximum percent of total soluble solids (TSS) (26.0 %) which was similar with Governor’s plum (24.0 %) and Flacourtia (23.5%) while Cowa contained the minimum TSS (11.0%). On the other hand, Red pear and Monkey jack contained highest amount of ascorbic acid (21.74, 20.86 mg/100 g FW, respectively) and Velvet apple contained lowest (5.73 mg/100g FW). In terms of mineral contents, it was observed that Cowa contained the maximum amount of Na (29.41 mg/100g DW) and Fe (4.56 mg/100g DW) as compared to other minor fruits while River ebony contained highest K (258.35 mg/100g DW) and P (293.38 mg/100g DW). Among the minor fruits, Red pear contained the highest amount of Ca (112.12mg/100g DW), Mg (97.24mg/100g DW), Zn (2.08mg/100g DW) and Cu (1.4mg/100g DW) while Flacourtia contained maximum Mn (14.30mg/100g DW). From the results it can be concluded that selected minor fruits are rich in vitamins and minerals.

Variational quantum circuit (VQC) is a quantum-classical (QC) machine learning approach that accommodates quantum processes on a classical computer. Malaria is a worldwide deadly disease caused by Plasmodium parasites. This research designs an effective VQC-based approach to recognize the existence of malaria from the Red blood cell (RBC) image through the classification of the optimized feature set that has been extracted from a set of RBC images. Minimum redundancy maximum relevance (mRMR), and Principal component analysis (PCA), are used to optimize the feature set. Comparing to existing classical approaches we have found that mRMR with our input encoding and parameterized circuit of VQC shows satisfactory performance by using a lower number of features and a lower number of parameters. After ascertaining the presence of malaria from VQC we have also introduced a rule-based expert system to detect the types of malaria. The proposed mechanism is mainly designed to evaluate the potency of quantum machine learning (QML) in near-term quantum computers and using the ten-fold cross-validation the scheme gained an overall accuracy, precision, recall, and specificity of 99.06%, 99.08%, 99.05%, and 99.07% respectively for malaria disease diagnosis.

Chinese cabbage (Brassica rapa L.) is one of the most important and highly nutritious vegetables in China belonging to the Brassicaceae family. Flowering or bolting is one of the most critical developmental stages in flowering plants. For the spring-sown Chinese cabbage, late-bolting is desirable over early-bolting according to consumer preferences. We determined the inheritance pattern of the late-bolting trait using F1 and F2 generated from a cross between ‘SY2004’ (late-bolting) and ‘CX14-1’ (early-bolting). The genetic analysis revealed that the late-bolting to early-bolting trait was controlled by an incomplete dominant gene that we named BrLb-1. Furthermore, we performed bulked segregant analysis (BSA) via whole genome re-sequencing and the results showed that this gene was harbored on the chromosome A07 at the intersections of 20,070,000 to 25,290,000 bp and 20,330,000 to 25,220,000, an interval distance of 4.89 Mb. In this candidate interval, totals of 2321 and 1526 SNPs with non-synonymous mutations, and 229 and 131 InDels with frameshift mutations, were found between the parents and the bulked pools, respectively. Furthermore, we identified three putative candidate genes for the late-bolting trait, including BraA07g029500, BraA07g029530 and BraA07g030360, which code for the AGAMOUS-like MADS-box protein AGL12, a pentatricopeptide repeat-containing protein and NAC transcription factor 29, respectively; however, further functional analysis is required. These genetic variants could be utilized for the further development of molecular markers for marker-assisted breeding in Chinese cabbage.

Sign language recognition is one of the most challenging applications in machine learning and human-computer interaction. Many researchers have developed classification models for different sign languages such as English, Arabic, Japanese, and Bengali; however, no significant research has been done on the general-shape performance for different datasets. Most research work has achieved satisfactory performance with a small dataset. These models may fail to replicate the same performance for evaluating different and larger datasets. In this context, this paper proposes a novel method for recognizing Bengali sign language (BSL) alphabets to overcome the issue of generalization. The proposed method has been evaluated with three benchmark datasets such as ‘38 BdSL’, ‘KU-BdSL’, and ‘Ishara-Lipi’. Here, three steps are followed to achieve the goal: segmentation, augmentation, and Convolutional neural network (CNN) based classification. Firstly, a concatenated segmentation approach with YCbCr, HSV and watershed algorithm was designed to accurately identify gesture signs. Secondly, seven image augmentation techniques are selected to increase the training data size without changing the semantic meaning. Finally, the CNN-based model called BenSignNet was applied to extract the features and classify purposes. The performance accuracy of the model achieved 94.00%, 99.60%, and 99.60% for the BdSL Alphabet, KU-BdSL, and Ishara-Lipi datasets, respectively. Experimental findings confirmed that our proposed method achieved a higher recognition rate than the conventional ones and accomplished a generalization property in all datasets for the BSL domain.

This study aims to assess the perceived disaster vulnerability, mitigation of humanitarian issues, and the existing knowledge gaps of humanitarian activities in the coastal areas of Bangladesh. Indicators based semi-structured questionnaire was developed to collect data through an extensive literature review followed by several workshops among the authors and relevant stakeholders, and data were analyzed quantitatively. Results indicate that the study area is still highly vulnerable to natural disasters and these vulnerability indices vary significantly (p value

Abstract Background Ornamental cabbage (Brassica oleracea var. acephala) is an attractive landscape plant that remains colorful at low temperatures during winter. Its key feature is its inner leaf coloration, which can include red, pink, lavender, blue, violet and white. Some ornamental cabbages exhibit variation in leaf color pattern linked to leaf developmental stage. However, little is known about the molecular mechanism underlying changes in leaf pigmentation pattern between developmental stages. Results The transcriptomes of six ornamental cabbage leaf samples were obtained using Illumina sequencing technology. A total of 339.75 million high-quality clean reads were assembled into 46,744 transcripts and 46,744 unigenes. Furthermore, 12,771 genes differentially expressed across the different lines and stages were identified by pairwise comparison. We identified 74 and 13 unigenes as differentially expressed genes related to the anthocyanin biosynthetic pathway and chlorophyll metabolism, respectively. Among them, three unigenes (BoC4H2, BoUGT9, and BoGST21) and six unigenes (BoHEMA1, BoCRD1, BoPORC1, BoPORC2, BoCAO, and BoCLH1) were found as candidates for the genes encoding enzymes in the anthocyanin biosynthetic pathway and chlorophyll metabolism, respectively. In addition, two unigenes (BoRAX3 and BoTRB1) as MYB candidates, two unigenes (BoMUTE1, and BHLH168-like) as bHLH candidates were identified for purple pigmentation in ornamental cabbage. Conclusion Our results indicate that the purple inner leaves of purple ornamental cabbage result from a high level of anthocyanin biosynthesis, a high level of chlorophyll degradation and an extremely low level of chlorophyll biosynthesis, whereas the bicolor (purple/green) outer leaves are due to a moderate level of anthocyanin biosynthesis, a high level of chlorophyll degradation and a very low level of chlorophyll biosynthesis. In white ornamental cabbage, the white inner leaves are due to an extremely low level or absence of anthocyanin biosynthesis, a high level of chlorophyll degradation and a very low level of chlorophyll biosynthesis, whereas the bicolor (white/green) leaves are due to a high level of chlorophyll degradation and a low level of chlorophyll biosynthesis and absence of anthocyanin biosynthesis. These results provide insight into the molecular mechanisms underlying inner and bicolor leaf pigmentation in ornamental cabbage and offer a platform for assessing related ornamental species.

Black rot, caused by Xanthomonas campestris pv. campestris (Xcc), produces V-shaped chlorotic lesions on the leaves of cabbage (Brassica oleracea var. capitata L.), causing darkened veins and drastically reducing yield and quality. Of the 11 Xcc races identified, races 1, 4, and 6 are predominant globally. In the present study, we aimed to develop a molecular marker linked to black rot resistance against Xcc races 6 and 7. Crossed between black rot-resistant (‘SCNU-C-3470’) and -susceptible (‘SCNU-C-3328’) lines obtained 186 F2 plants. Resistance to Xcc race 6 segregated in a 3:1 (susceptible:resistant) ratio in the F2 population, which is consistent with a monogenic recessive trait. Nucleotide-binding site (NBS) leucine rich repeat (LRR)-encoding resistance (R) genes play a crucial role in plant defenses to various pathogens. The candidate R gene (Bol031422) located on chromosome C08, previously reported by our research group, was cloned and sequenced in resistant and susceptible cabbage lines. The R gene Bol031422 consisted of a single exon with a 3 bp insertion/deletions (InDels), a 292 bp polymorphism (an insertion in the exon of the resistant line relative to the susceptible line) and several single nucleotide polymorphisms (SNPs). Here, we developed the InDel marker BR6-InDel to assess linkage between variation at Bol031422 and resistance to Xcc races 6 and 7. This marker will help cabbage breeders develop cabbage cultivars resistant to Xcc races 6 and 7.

In plants, anthocyanin production is controlled by MYB and bHLH transcription factors. In peach, among the members of these families, MYB10.1 and bHLH3 have been shown to be the most important genes for production of these pigments during fruit ripening. Anthocyanins are valuable molecules, and the overexpression of regulatory genes in annual fast-growing plants has been explored for their biotechnological production. The overexpression of peach MYB10.1 in tobacco plants induced anthocyanin pigmentation, which was particularly strong in the reproductive parts. Pigment production was the result of an up-regulation of the expression level of key genes of the flavonoid biosynthetic pathway, such as NtCHS, NtCHI, NtF3H, NtDFR, NtANS, and NtUFGT, as well as of the proanthocyanidin biosynthetic pathway such as NtLAR. Nevertheless, phenotypic alterations in transgenic tobacco lines were not only limited to anthocyanin production. Lines showing a strong phenotype (type I) exhibited irregular leaf shape and size and reduced plant height. Moreover, flowers had reduced length of anther’s filament, nondehiscent anthers, reduced pistil length, aborted nectary glands, and impaired capsule development, but the reproductive parts including androecium, gynoecium, and petals were more pigmented that in wild type. Surprisingly, overexpression of peach MYB10.1 led to suppression of NtMYB305, which is required for floral development and, of one of its target genes, NECTARIN1 (NtNCE1), involved in the nectary gland formation. MYB10.1 overexpression up-regulated JA biosynthetic (NtAOS) and signaling (NtJAZd) genes, as well as 1-aminocyclopropane-1-carboxylate oxidase (NtACO) in flowers. The alteration of these hormonal pathways might be among the causes of the observed floral abnormalities with defects in both male and female gametophyte development. In particular, approximately only 30% of pollen grains of type I lines were viable, while during megaspore formation, there was a block during FG1 (St3-II). This block seemed to be associated to an excessive accumulation of callose. It can be concluded that the overexpression of peach MYB10.1 in tobacco not only regulates flavonoid biosynthesis (anthocyanin and proanthocyanidin) in the reproductive parts but also plays a role in other processes such as vegetative and reproductive development.

Tomato, which can be eaten as a vegetable or fruit, is one of the most popular and nutritionally important crops around the world. Although most plants of the cherry tomato cultivar 'Minichal' have a normal phenotype, some plants have a stunted phenotype with reduced plant height, leaf size, and fruit size, as well as altered leaf and fruit shape. To investigate the molecular mechanisms underlying these differences, we generated RNA-seq libraries from pooled leaf samples of 10 normal (N) and 10 stunted (S) plants. Using the Illumina sequencing platform, we obtained a total of 115.45 million high-quality clean reads assembled into 35,216 genes and 35,216 transcripts. A total of 661 genes were differentially expressed between N and S plants. Of these, 420 differentially expressed genes (DEGs) were up-regulated, and 221 DEGs were down-regulated. The RNA-seq data were validated using quantitative reverse-transcription PCR. Enrichment analysis of DEGs using the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the enriched pathways were involved in steroid biosynthesis, homologous recombination, and mismatch repair. Among these, three genes related to steroid biosynthesis, including 3BETAHSD/D2, DIM and DWF5 were down-regulated in S compared to N. Of these, DIM and DWF5 are known to be involved in brassinosteroid biosynthesis. Our results thus provide a useful insight into dwarfism in cherry tomato, and offer a platform for evaluating related species.

Hand gesture-based sign language recognition is a prosperous application of human− computer interaction (HCI), where the deaf community, hard of hearing, and deaf family members communicate with the help of a computer device. To help the deaf community, this paper presents a non-touch sign word recognition system that translates the gesture of a sign word into text. However, the uncontrolled environment, perspective light diversity, and partial occlusion may greatly affect the reliability of hand gesture recognition. From this point of view, a hybrid segmentation technique including YCbCr and SkinMask segmentation is developed to identify the hand and extract the feature using the feature fusion of the convolutional neural network (CNN). YCbCr performs image conversion, binarization, erosion, and eventually filling the hole to obtain the segmented images. SkinMask images are obtained by matching the color of the hand. Finally, a multiclass SVM classifier is used to classify the hand gestures of a sign word. As a result, the sign of twenty common words is evaluated in real time, and the test results confirm that this system can not only obtain better-segmented images but also has a higher recognition rate than the conventional ones.

The most popular way of learning oriental calligraphy has been by practicing the calligraphy under the supervision of a human teacher, but finding a good instructor can be difficult. There are a number of studies in the literature that have evaluated calligraphic characters in holistic ways, but such systems do not support detailed supervision of scripting errors. This study proposes a Kanji calligraphy learning system with computerized supervision and analyzes the learning efficiency of the system, where the supervision includes symmetries between strokes. The proposed system compares a written calligraphic character of a user to the model of a human expert, and indicates error spots with explanations. An experiment with 22 participants proved that this system was more efficient at reducing the number of scripting errors in comparison to the traditional manner of a human expert. The main contribution of this paper was to identify and reveal the efficacy of computerized supervision in comparison to a human supervisor. The proposed system decreased the writing-error-rates of learners from 32.7% to 3.4%, whereas the traditional practice reduced the error rates from 31.0% to 6.8%. This result shows that computerized supervision is more efficient than human supervision for learning calligraphy.

This work outlines the synthesis of MC 25 [Crown -5] which is as an ionophore for selected metal cations. The synthesis of MC 25 proceeds in four steps: the first [...]