Local Alignment Research Articles

In-depth genomic characterisation of SARS-CoV-2 variants from Egypt exhibited heterogeneous lineages.

Genetic variation of SARS-CoV-2 remains a public health challenge worldwide because of it influences the pathogenicity and transmissibility of the virus. To determine the genomic mutations of SARS-CoV-2 isolated in Egypt. This was an in silico cross-sectional study of 200 SARS-CoV-2 variants of concern, which were retrieved from the National Centre for Biotechnology Information on 11 January 2021 and aligned with the original Wuhan strain (NC_045512). Nucleotide basic local alignment search tool (BLASTN) was used to identify the nucleotide variations. Corresponding proteins were identified using protein basic local alignment search tool (BLASTP). A phylogenetic tree was constructed to study the evolutionary relationships using the neighbour-joining method. The variants of concern belonged to 26 species and there were 4 non-classified variants. All variants of concern showed 99.47-99.98% homology with the original Wuhan strain and demonstrated up to 60 mutations per variant. There were 1101 mutations identified among the variants of concern, with 458 synonymous and 583 nonsynonymous mutations. Specific mutations that were characteristically present in various SARS-CoV-2 lineages were identified, showing the microevolutionary genetic variations. This study showed vast genetic variations of the Egyptian SARS-CoV-2 with characteristic mutations for the A, B and C lineages. The study contributes to a better understanding of the epidemiological and demographic variations of COVID-19 in Egypt based on SARS-CoV-2 genomic evolution and supports further investigation of SARS-CoV-2 contextbased vaccine development and preventive measures.

Using rDNA ITS2 barcoding to identify kratom (Mitragyna speciosa) from the genus Mitragyna and Neolamarckia cadamba.

This study collected 80 samples of suspected kratom plant powder. A polymerase chain reaction sequence analysis was conducted using two sets of DNA barcode primers for plant ribosomal (r)DNA internal transcribed spacers (ITSs), namely, ITS3/ITS4 and ITS-p3/ITS-u4. Among the 80 samples, 40 were analyzed using the ITS3/ITS4 primer pair, and then DNA sequences were subjected to a National Center for Biotechnology Information-Basic Local Alignment Search Tool (NCBI-BLAST) comparison. Results showed that 29 samples had a 100% match (364/364) with Mitragyna speciosa (kratom), and 6 samples had a 99.73% match (363/364) with M. speciosa, whereas 5 samples had disordered and unreadable sequences. The 5 unreadable samples and an additional 40 suspected kratom samples were then analyzed using the ITS-p3/ITS-u4 primer pair, followed by an NCBI-BLAST comparison. Among these, 32 samples had a 100% match (404/404) with M. speciosa, and 11 samples had a 99.75% match (403/404) with M. speciosa. Among the samples with sequences matching M. speciosa, three distinct types were observed (no variance/404, 287M/404, and 287A/404). One sample had a 99.51% match (404/406) with Neolamarckia cadamba, and another sample had a sequencing length of 305bp, with 25 positions showing mixed base pairs, indicating a mixture of different species. Analysis of the mixed base pair pattern suggested a possible mixture of M. speciosa and N. cadamba. Actually, M. speciosa and N. cadamba have very similar external morphologies. This indicates that the ITS-p3/ITS-u4 primer pair is effective in distinguishing mixtures of M. speciosa and N. cadamba and is thus more suitable than ITS3/ITS4 for identifying and analyzing samples of suspected kratom plant powder.

First report of leaf spot disease caused by Cladosporium pseudocladosporioides on Lonicera caerulea L. in Heilongjiang Province, China.

Blue honeysuckle (Lonicera caerulea L.) has contributed to maintaining the forest's ecological balance and remarkable frost-resistant abilities, helping it withstand extremely cold conditions (-46 °C) and a wide pH range (5 to 8) (Sharma and Lee 2021). Between September 2022 and September 2023, leaf spots were observed on approximately 30% of blue honeysuckle plants of the 'Lanjingling' cultivar grown in a 1.13 ha field in Da Hinggan Ling Prefecture (50.32° N, 124.13° E) in Heilongjiang Province, China. The leaves of the affected plants displayed black-colored spots. To identify the causal agents, 10 healthy and symptomatic leaves were randomly collected from ten healthy and infected individual plants, respectively. Small (3 to 4 mm) segments of the symptomatic tissues were immersed in 5% sodium hypochlorite (NaOCl) for 3 min, rinsed three times with sterile distilled water, dried in a paper towel, and plated on 9-cm Petri dishes containing potato dextrose agar (PDA). Ten fungal colonies developed on the PDA plates with an isolation frequency of 100% from 10 symptomatic leaves, and all colonies displayed a morphology consistent with Cladosporium spp. (Bensch et al. 2018). Cladosporium-like fungi were not isolated from healthy leaves. Dark olive-colored mycelia were observed, with straight unbranched conidiophores bearing terminal light brown-colored limoniform conidia (1.80 to 4.50 × 2.10 to 12.60 μm) and surrounded by a thin line of white mycelium (Delisle-Houde et al. 2024). To confirm this identification, PCR amplification of two representative strains LD-299 and LD-300 genomic DNA was performed with ITS1/ITS4 (White et al. 1990) and ACT512F/ACT783R (Carbone and Kohn 1999) primers. Basic local alignment search tool (BLAST) analyses of the National Center for Biotechnology Information database showed that sequences of the ITS (PP600316, PP600317) and ACT (PP624334, PP624335) all revealed 100% (493/493 nt, 493/493 nt; 181/181 nt, 181/181 nt) shared identity with Cladosporium pseudocladosporioides strain ex-type MF473195 and HM148674 (Bensch et al. 2010), respectively. Using a neighbor-joining phylogenetic analysis based on the ITS and ACT sequences, isolates LD-299 and LD-300 clustered in the same clade of C. pseudocladosporioides. Therefore, based on its morphological characteristics and molecular phylogeny, the two isolates were identified as C. pseudocladosporioides (Cosseboom and Hu 2023). A pathogenicity test was performed using nine healthy two-year-old blue honeysuckle Lanjingling plants. Three plants were inoculated with either the LD-299 or the LD-300 conidial suspension (1 × 106 spores/ml) or with clean water as an experimental control (Aydoğdu et al. 2023). All plants were cultured in a greenhouse (28℃, 75% relative humidity, 12 h light and dark cycle), and each experiment was replicated three times. Typical leaf spot symptoms were first observed on the inoculated leaves after 10 days. Morphological and molecular characterization of re-isolated pathogens from the artificially infected leaves indicated that the two isolates were identical, thereby confirming Koch's postulates. Cladosporium pseudocladosporioides previously caused leaf spot disease on artichoke (Cynara scolymus) in Türkiye (Aydoğdu et al. 2023). To the best of our knowledge, this is the first report of C. pseudocladosporioides causing leaf spots on blue honeysuckle in China. Blue honeysuckle production losses due to the leaf spots are critical for growers. Therefore, further focus should be given to investigate the host range and geographic distribution of C. pseudocladosporioides.

Genetic diversity and prevalence of emerging Rickettsiales in Yunnan Province: a large-scale study

BackgroundRickettsia and related diseases have been identified as significant global public health threats. This study involved comprehensive field and systematic investigations of various rickettsial organisms in Yunnan Province.MethodsBetween May 18, 2011 and November 23, 2020, field investigations were conducted across 42 counties in Yunnan Province, China, encompassing small mammals, livestock, and ticks. Preliminary screenings for Rickettsiales involved amplifying the 16S rRNA genes, along with additional genus- or species-specific genes, which were subsequently confirmed through sequencing results. Sequence comparisons were carried out using the Basic Local Alignment Search Tool (BLAST). Phylogenetic relationships were analyzed using the default parameters in the Molecular Evolutionary Genetics Analysis (MEGA) program. The chi-squared test was used to assess the diversities and component ratios of rickettsial agents across various parameters.ResultsA total of 7964 samples were collected from small mammals, livestock, and ticks through Yunnan Province and submitted for screening for rickettsial organisms. Sixteen rickettsial species from the genera Rickettsia, Anaplasma, Ehrlichia, Neoehrlichia, and Wolbachia were detected, with an overall prevalence of 14.72%. Among these, 11 species were identified as pathogens or potential pathogens to humans and livestock. Specifically, 10 rickettsial organisms were widely found in 42.11% (24 out of 57) of small mammal species. High prevalence was observed in Dremomys samples at 5.60%, in samples from regions with latitudes above 4000 m or alpine meadows, and in those obtained from Yuanmou County. Anaplasma phagocytophilum and Candidatus Neoehrlichia mikurensis were broadly infecting multiple genera of animal hosts. In contrast, the small mammal genera Neodon, Dremomys, Ochotona, Anourosorex, and Mus were carrying individually specific rickettsial agents, indicating host tropism. There were 13 rickettsial species detected in 57.14% (8 out of 14) of tick species, with the highest prevalence (37.07%) observed in the genus Rhipicephalus. Eight rickettsial species were identified in 2375 livestock samples. Notably, six new Rickettsiales variants/strains were discovered, and Candidatus Rickettsia longicornii was unambiguously identified.ConclusionsThis large-scale survey provided further insight into the high genetic diversity and overall prevalence of emerging Rickettsiales within endemic hotspots in Yunnan Province. The potential threats posed by these emerging tick-borne Rickettsiales to public health warrant attention, underscoring the need for effective strategies to guide the prevention and control of emerging zoonotic diseases in China.Graphical

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family

PurposeIn this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since viruses within the same family share similar genetic and structural characteristics, the classification process becomes more challenging, necessitating more robust models. With the rapid evolution of viral genomes and the increasing need for timely classification, we aimed to provide a robust and efficient tool that could increase the accuracy of viral identification and classification processes. Contribute to advancing research in viral genomics and assist in surveilling emerging viral strains.MethodsBased on a one-dimensional deep CNN, the proposed tool is capable of training and testing on the Coronaviridae family, including SARS-CoV-2. Our model’s performance was assessed using various metrics, including F1-score and AUROC. Additionally, artificial mutation tests were conducted to evaluate the model’s generalization ability across sequence variations. We also used the BLAST algorithm and conducted comprehensive processing time analyses for comparison.ResultsDeepVirusClassifier demonstrated exceptional performance across several evaluation metrics in the training and testing phases. Indicating its robust learning capacity. Notably, during testing on more than 10,000 viral sequences, the model exhibited a more than 99% sensitivity for sequences with fewer than 2000 mutations. The tool achieves superior accuracy and significantly reduced processing times compared to the Basic Local Alignment Search Tool algorithm. Furthermore, the results appear more reliable than the work discussed in the text, indicating that the tool has great potential to revolutionize viral genomic research.ConclusionDeepVirusClassifier is a powerful tool for accurately classifying viral sequences, specifically focusing on SARS-CoV-2 and other subtypes within the Coronaviridae family. The superiority of our model becomes evident through rigorous evaluation and comparison with existing methods. Introducing artificial mutations into the sequences demonstrates the tool’s ability to identify variations and significantly contributes to viral classification and genomic research. As viral surveillance becomes increasingly critical, our model holds promise in aiding rapid and accurate identification of emerging viral strains.

Unusual Patterns of Lateral Scutes in Two Olive Ridley Turtles and Their Genetic Assignment to the Thai Andaman Sea Populations of Lepidochelys olivacea Eschscholtz, 1829.

Two stranded Lepidochelys-like sea turtles were rescued from the Thai Andaman Sea coastline by veterinarians of the Phuket Marine Biological Center (PMBC), one in May of 2019 and another in July of 2021. They were first identified as olive ridley turtles (Lepidochelys olivacea), as the external appearance of both turtles was closer to that species than the other four species found in the Thai Andaman Sea. In fact, when carefully examined, an unusual pattern of the lateral scutes on each turtle was observed, specifically symmetric 5/5 and asymmetric 5/6, both of which are considered rare for L. olivacea and had never been reported in the Thai Andaman Sea. In contrast, this characteristic was more common for the closely related species, Kemp's ridley (L. kempii), although this species is not distributed in the Indo-Pacific Ocean. Thus, we further investigated their genetic information to confirm species identification using two molecular markers, namely the mtDNA control region and nDNA RAG2. The results from the mtDNA control region sequences using the Basic Local Alignment Search Tool (BLAST) indicated that both individuals exhibited a higher percent identity with L. olivacea (99.81-100.00%) rather than L. kempii (94.29-95.41%) or any other species. A phylogenetic tree confirmed that these two turtles belonged to the L. olivacea clade. Moreover, the results of RAG2 also supported the mtDNA result, as both individuals shared the same RAG2 haplotype with L. olivacea. Thus, we have concluded that the two turtles with unusual lateral scute patterns exhibited genetic consistency with their original species, L. olivacea, which has brought attention to the importance of exploring rare phenotypes in sea turtle populations residing in Thai Seas.

A Hybrid Improved SAC-IA with a KD-ICP Algorithm for Local Point Cloud Alignment Optimization

To overcome incomplete point cloud data obtained from laser scanners scanning complex surfaces, multi-viewpoint cloud data needs to be aligned for use. A hybrid improved SAC-IA with a KD-ICP algorithm is proposed for local point cloud alignment optimization. The scanned point cloud data is preprocessed with statistical filtering, as well as uniform down-sampling. The sampling consistency initial alignment (SAC-IA) algorithm is improved by introducing a dissimilarity vector for point cloud initial alignment. In addition, the iterative closest point (ICP) algorithm is improved by incorporating bidirectional KD-tree to form the KD-ICP algorithm for fine point cloud alignment. Finally, the algorithms are compared in terms of runtime and alignment accuracy. The implementation of the algorithms is based on the Visual Studio 2013 software configurating point cloud library environment for testing experiments and practical experiments. The overall alignment method can be 40%~50% faster in terms of running speed. The improved SAC-IA algorithm provides better transformed poses, combined with the KD-ICP algorithm to select the corresponding nearest neighbor pairs, which improves the accuracy, as well as the applicability of the alignment.

Robust Hashing With Local Tangent Space Alignment for Image Copy Detection

Robust Hashing With Local Tangent Space Alignment for Image Copy Detection

The isolation and identification of lactic acid bacteria from Indonesian traditional fermented food

Abstract Indigenous Indonesian fermented food is considered a source of probiotics because it usually contains lactic acid bacteria (LAB). Some LAB strains meet the requirement to be probiotics with some functional properties for positive health impacts. However, those functional properties of probiotics have not been fully investigated and need to be continued to complete. To investigate more about LAB from traditional Indonesian fermented foods, the isolation and identification of LAB from some traditional Indonesian fermented foods was done. It was isolated LAB from kimchi (Tangerang), mandai (Banjarmasin), menteng fruit (Banjarmasin), petis (Tangerang and Semarang), salty vegetable (Tangerang), fermented cassava (Tangerang), and fermented durian (Lampung). LAB was isolated in MRS medium with 1% CaCO3, then isolates were characterized biochemically by Gram staining and catalase test. Twenty-one isolates were characterized as gram-positive, and catalase-negative. This strain was further identified by 16S rDNA sequence analysis, the sequences were then checked for similarities using the Basic Local Alignment Search Tool. The result showed that 2 strains of Weissella paramesenteroides found was from Kimci, 1 strain of Pediococcus pentosaceus from mandai, 2 strains of Lactobacillus plantarum from menteng fruit, 1 strain of Leuconostoc pseudomesenteroides from petis Tangerang, 1 strain Bacillus sp from petis Semarang, 1 strain Lactobacillus plantarum from salty vegetable, 2 strain Weissella paramesenteroides from fermented cassava, 4 strain Lactobacillus plantarum and 2 strain Lactobacillus sp from tempoyak.

MOLECULAR DETECTION AND ANTIBACTERIAL ACTIVITY OF CITRUS SINENSIS PEEL EXTRACTS AGAINST STAPHYLOCOCCUS AUREUS AND KLEBSIELLA PNEUMONIA ISOLATED FROM WOUNDS

The global rise of resistant bacteria threatens the effectiveness of antibiotics, recommending that herbs' natural chemical constituents could provide alternative antimicrobial and insecticidal properties. The study evaluated Citrus sinensis peel extracts' impact on bacterial species isolated from wound samples collected from six hospitals. Quantitative Phytochemical analysis was conducted on the Citrus sinensis peel extracts, Isolates were tested biochemically and molecularly for detection and confirmation of Staphylococcus aureus and Klebsiella pneumonia. The study assessed the antibacterial activity of Citrus sinensis peel extracts using agar disc diffusion method, revealing significant bioactive compounds such as alkaloids, flavonoids, saponins, steroids, glycosides, and tannins. The extracts effectivity against Staphylococcus aureus and Klebsiella pneumonia comes from its bioactive phytochemical components. The result from the morphological and biochemical tests revealed the presence of Staphylococcus aureus, Klebsiella pneumonia, Staphylococcus epidermis, Pseudomonas aeruginosa, Escherichia coli and Enterobacter spp but only Staphylococcus aureus and Klebsiella pneumonia were confirmed by molecular method with a sequence identity of 99.35% and 97.41% respectively when analyzed using the Basic Local Alignment Search Tool (BLAST) of the NCBI package. The study revealed that Citrus sinensis peel extracts showed antibacterial activity against Staphylococcus aureus and Klebsiella pneumonia at different concentrations and Ciprofloxacin as a control. The ethanolic extract showed high activity, while the aqueous extracts showed significant activity. The study suggests Citrus sinensis peel has potential as an antibacterial agent for wound infection treatment, suggesting the need for its phytochemical composition quantification and purification.

KPPBC TMP Juanda Policy in Achieving Revenue Target as a Impact of De Minimis Value

Background: The implementation of the de minimis value rule, which sets a threshold for import duty exemptions on small shipments, significantly influences national trade dynamics and fiscal policies. Despite global integration and economic transactions escalating, effective customs regulations remain pivotal for controlling import activities and enhancing revenue. Knowledge Gap: Prior research has primarily focused on the implications of the de minimis rule on import volumes and compliance, leaving a gap regarding its impact on revenue targets and administrative practices at the customs office level. Aims: This study aims to explore the strategies employed by KPPBC TMP Juanda in achieving revenue targets influenced by the de minimis value policy. Methods: Utilizing qualitative research methods, including interviews, observation, and documentation, this research engages directly with three customs officials at KPPBC TMP Juanda, analyzing data with NVivo12Plus. Results: The findings indicate that while the de minimis value does not control the surge in import activities, it assists in increasing revenue and meeting fiscal targets. Novelty: This study provides new insights into how customs policies adapted at the local office level can contribute to national fiscal strategies under global trade pressures. Implications: The outcomes underscore the necessity for continuous policy evaluation to balance trade facilitation with fiscal responsibility, suggesting enhancements in customs operations to optimize revenue without stifling economic growth. Highlights: Customs Strategy: De minimis value adjustments reflect local customs alignment with fiscal goals. Revenue Impact: The rule boosts revenue without curbing import volumes. Policy Review: Highlights the need for continual policy optimization to balance trade and revenue. Keywords: Policy, Revenue Target, De Minimis Value

Investigation of Mitochondrial Cytb Gene Region of Both Echinococcus granulosus Eggs from Dogs and Cystic Echinococcosis Isolates Obtained from Sheep and Cattle by Molecular Methods.

We aimed to determine the common Echinococcus granulosus genotypes in Ağrı, Türkiye and to obtain information on the transmission of this parasite. Cystic echinococcosis samples from 100 slaughtered cattle and 100 slaughtered sheep and faecal samples from 200 stray dogs were included in 2021. Collected cyst fluid samples and faces were examined microscopically. DNA was isolated from the germinal membrane of the cysts and from the parasite eggs in the stool samples. The mitochondrial cytb gene region of the parasite was amplified by PCR. Genotypes were determined using the Basic Local Alignment Search Tool (BLAST) after sequence analysis of PCR amplicons. The highest percentage of cysts was found in the lungs of sheep and the liver of cattle. In addition, 75% of sheep cysts and 25.6% of cattle cysts were fertile. Taenia spp./Echinococcus spp. eggs were found in 6% of the faeces of 200 dogs examined microscopically. E. granulosus eggs were detected in 4 out of 50 stool samples analysed by PCR. All samples analysed by sequence analysis were identified as E. granulosus s.s. G1 genotype. Sequence comparison revealed revealed one or more-point mutations in different regions of the five samples. E. granulosus s.s. G1 genotype, known as sheep strain, is common in the Ağrı, Türkiye. The controlled slaughter of livestock, especially sheep, and the avoidance of feeding hydatid cyst organs to dogs, together with public education, were necessary to prevent the spread of the disease.

Multi-level Symmetric Semantic Alignment Network for image–text matching

Image–text matching has attracted much attention as one of the visual-linguistic tasks. Most of the existing methods tend to concentrate on single-level semantic similarity by global embeddings or local alignment, which fail to distinguish the ambiguous image–text instances with highly similar contexts due to insufficient interactions of cross-modal features. To mitigate this problem, in this paper, we propose a novel Multi-level Symmetric Semantic Alignment Network (MSSAN), which fully exploits the multi-level semantic features to capture the complicated correlations between images and text. Specifically, global–global-level alignment is first performed based on visual–textual global representations. Then, considering the local semantic consistency, local–local-level alignment is carried out through inter-modal bidirectional cross-attention module to model fine-grained region–word relations. Moreover, a Multi-granularity Feature Fusion Module (MFFM) is constructed to learn intra-modal distribution of significance and incorporate global concepts into local features to obtain more comprehensive semantic representations, thus achieving global–local-level alignment. Finally, in order to achieve a strong separation of semantically similar samples, we develop a novel generic triplet ranking loss with adaptively updatable margins to train our model. Extensive experimental results on Flickr8K, MSCOCO and Flickr30K datasets demonstrate that our proposed MSSAN is superior to other state-of-the-art methods by a considerable margin.

SC-AOF: A Sliding Camera and Asymmetric Optical-Flow-Based Blending Method for Image Stitching.

Parallax processing and structure preservation have long been important and challenging tasks in image stitching. In this paper, an image stitching method based on sliding camera to eliminate perspective deformation and asymmetric optical flow to solve parallax is proposed. By maintaining the viewpoint of two input images in the mosaic non-overlapping area and creating a virtual camera by interpolation in the overlapping area, the viewpoint is gradually transformed from one to another so as to complete the smooth transition of the two image viewpoints and reduce perspective deformation. Two coarsely aligned warped images are generated with the help of a global projection plane. After that, the optical flow propagation and gradient descent method are used to quickly calculate the bidirectional asymmetric optical flow between the two warped images, and the optical-flow-based method is used to further align the two warped images to reduce parallax. In the image blending, the softmax function and registration error are used to adjust the width of the blending area, further eliminating ghosting and reducing parallax. Finally, by comparing our method with APAP, AANAP, SPHP, SPW, TFT, and REW, it has been proven that our method can not only effectively solve perspective deformation, but also gives more natural transitions between images. At the same time, our method can robustly reduce local misalignment in various scenarios, with higher structural similarity index. A scoring method combining subjective and objective evaluations of perspective deformation, local alignment and runtime is defined and used to rate all methods, where our method ranks first.

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The first molecular research on Iraqi centipede fauna is presented in this article. Between October 2022 and May 2023, during various climatic circumstances, centipedes were collected from several locations in four provinces of Iraq. Three families, represented by four genera, underwent molecular identification, and five species were found. From the order Scolopendromorpha family Scolopendridae, two species were recorded, Scolopendra morsitans Linnaeus, 1758, and S. cingulata Latreille, 1829, Cormocephalus sp.; while from the order Lithobiomorpha, family Lithobiidae, one species was recorded for first time in Iraq; Lithobius crassipes L. Koch, 1862 from the order Geophilomorpha family Himantariidae, one species Bothriogaster Signata Kessler, 1874. DNA was extracted from the specimens, the mtDNA fragment from the Cytochrome C Oxidase Subunit I (COI) gene was amplified by using the PCR technique with appropriate primers, and subsequently, the Basic Local Alignment Search Tool (BLAST) tool, which is accessible at the NCBI, was used. Additionally, a phylogenetic tree was built, and a distant comparison was shown.

GLHDR: HDR video reconstruction driven by global to local alignment strategy

Reconstructing High Dynamic Range (HDR) video from alternating exposure Low Dynamic Range (LDR) sequence is an exceptionally challenging task. It not only demands the reliable reconstruction of missing information caused by occlusion or motion without introducing artifacts but also balances the exposure differences between frames to ensure a visually pleasing reconstructed HDR video. Unfortunately, existing methods are typically complex and struggle with unavoidable artifacts and noise, especially when dealing with low-exposed scenes. To tackle this formidable challenge, we propose a two-stage HDR video reconstruction method that employs a global to local alignment strategy. Firstly, we utilize iterative optical flow estimation and hybrid weighting to achieve global alignment, ensuring well-reconstructed in majority of areas. Secondly, the recursive refinement network further addresses locally misaligned areas, reconstructing HDR frames from bottom to top and recursively refining them to yield faithful reconstruction results. Extensive experimental results demonstrate that our method generates the HDR video with fine details and superior visually, surpassing the state-of-the-art method across diverse scenes.

Phylogenetic analysis of Dengue virus and insect-specific Flavivirus in Aedes aegypti from Gresik, Indonesia 2019

Abstract. Hakim RN, Damayanti M, Fauziyah S, Sucipto TH. 2024. Phylogenetic analysis of Dengue virus and insect-specific Flavivirus in Aedes aegypti from Gresik, Indonesia 2019. Biodiversitas 25: 2340-2347. The spread of several Flaviviruses, such as Dengue virus and insect-specific Flavivirus, is periodically detected in Indonesia, including Surabaya, which is an endemic area. Gresik, as one of Surabaya's satellite cities, has high traffic mobility between regions, increasing the possibility of viral transmission. In this study, we identified Flaviviruses from Aedes aegypti mosquito isolates from Gresik collected in 2019. We also revealed the possibility of virus transmission from Surabaya to Gresik. The mosquito samples were collected using mosquito trap method. The Flavivirus Partial Nonstructural Protein 5 (NS5) -encoding gene region was isolated via the nested reverse transcription-polymerase chain reaction method. Sequence alignment and phylogenetic analysis were carried out to determine the kinship of Gresik strain virus isolates with the GenBank database. The results revealed that six out of 29 isolated samples (Sample from Duduk Sampeyan (47 and 43), Mengare (212 and 31), Kedamean (58), and Manyar (38)) exhibited a 220 bp DNA band, which corresponds to the NS5 gene. Further analysis using basic local alignment search tool - nucleotide and phylogenetic methods revealed that two sample sequences (38 and 212) are closely related to DENV-1 genotype 1, while the other four (31, 43, 47, and 58) are associated with Insect-Spesific Flavivirus (ISF). The similarity in NS5 partial sequence and genotype classifications of the dengue virus suggests the potential transmission of the virus from Surabaya to Gresik. We hypothesize that this phenomenon is closely linked to the population mobility between the two areas.

Enhanced thermoelectric properties of nanostructured Si by excess P-doping

In this study, nanostructures were introduced into bulk Si, and the P content in Si was increased. Arc melting, ball milling, and spark plasma sintering were used to prepare excess P-doped Si samples (Si1−xPx, x = 0.01, 0.03, 0.06, 0.09, and 0.12). In Si0.94P0.06, thermal conductivity decreased to 18 W m−1 K−1 at room temperature, which is about 10% of that of bulk Si. Transmission electron microscopy observation of Si0.94P0.06 revealed a linearly localized alignment, in addition to the nanostructures observed in the previous studies of P-doped Si samples. Linear alignments were composed of Si-P nanoprecipitates and defects linearly localized around dislocations. These sub-microstructures can reduce thermal conductivity; as a result, ZT at 973 K increased to 0.43, which is approximately three times higher than that of single-crystal Si.

KLSANet: Key local semantic alignment Network for few-shot image classification

Few-shot image classification involves recognizing new classes with a limited number of labeled samples. Current local descriptor-based methods, while leveraging consistent low-level features across visible and invisible classes, face challenges including redundant adjacent information, irrelevant partial representation, and limited interpretability. This paper proposes KLSANet, a few-shot image classification approach based on key local semantic alignment network, which aligns key local semantics for accurate classification. Furthermore, we introduce a key local screening module to mitigate the influence of semantically irrelevant image parts on classification. KLSANet demonstrates superior performance on three benchmark datasets (CUB, Stanford Dogs, Stanford Cars), outperforming state-of-the-art methods in 1-shot and 5-shot settings with average improvements of 3.95% and 2.56% respectively. Visualization experiments demonstrate the interpretability of KLSANet predictions. Code is available at: https://github.com/ZitZhengWang/KLSANet.

ТЕСТ-СИСТЕМА ДЛЯ ПРОВЕДЕНИЯ ПЦР В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ ДЛЯ ОБНАРУЖЕНИЯ ДНК ТТV В БИОЛОГИЧЕСКОМ МАТЕРИАЛЕ

Background. The study of biological material for the presence of TTV DNA using the PCR method allows for a timely assessment of the functional state of the human liver and immune system. Objective. To develop components for real-time PCR for TTV DNA detection in biological material. Material and methods. The design and selection of optimal primers and probes (taking into account the size (length) of the amplicon, annealing temperature, nucleotide composition, distribution of nucleotides along the length of the primer, length of primers, the possibility of formation of hairpins and dimers by primers) were performed using the Primer-BLAST/Primer3, FastPCR programs. Since primers, even absolutely unique for certain DNA sequences, could anneal at nonspecific sites, not related to the gene analyzed, we checked the correspondence of the primers to the sequences of the target gene. For this purpose, we used the NCBI Primer BLAST online service and assessed the local pairwise alignment of each primer with all nucleotide sequences of the Refseq databases. Results. As the result of studies carried out on the selection of the optimal primer annealing temperature, primer concentrations, as well as the selection of the optimal nucleotide pair, the main parameters of the designed primers were determined. Conclusions. A kit for the detection and quantification of TTV DNA using the polymerase chain reaction method with hybridization-fluorescent detection in real time was created and became the basis for the development of a commercial test system.