The requirement for external carbonic anhydrase in diatoms is influenced by the supply and demand for dissolved inorganic carbon.

Photosynthesis by marine diatoms contributes significantly to the global carbon cycle. Due to the low concentration of CO2 in seawater, many diatoms use extracellular carbonic anhydrase (eCA) to enhance the supply of CO2 to the cell surface. While much research has investigated how the requirement for eCA is influenced by changes in CO2 availability, little is known about how eCA contributes to CO2 supply following changes in the demand for carbon. We therefore examined how changes in photosynthetic rate influence the requirement for eCA in three centric diatoms. Modeling of cell surface carbonate chemistry indicated that diffusive CO2 supply to the cell surface was greatly reduced in large diatoms at higher photosynthetic rates. Laboratory experiments demonstrated a trend of an increasing requirement for eCA with increasing photosynthetic rate that was most pronounced in the larger species, supporting the findings of the cellular modeling. Microelectrode measurements of cell surface pH and O2 demonstrated that individual cells exhibited an increased contribution of eCA to photosynthesis at higher irradiances. Our data demonstrate that changes in carbon demand strongly influence the requirement for eCA in diatoms. Cell size and photosynthetic rate will therefore be key determinants of the mode of dissolved inorganic carbon uptake.

Embodied Conversational Agents for Chronic Diseases: Scoping Review.

BACKGROUND: Embodied conversational agents (ECAs) are computer-generated animated humanlike characters that interact with users through verbal and nonverbal behavioral cues. They are increasingly used in a range of fields, including health care. OBJECTIVE: This scoping review aims to identify the current practice in the development and evaluation of ECAs for chronic diseases. METHODS: We applied a methodological framework in this review. A total of 6 databases (ie, PubMed, Embase, CINAHL, ACM Digital Library, IEEE Xplore Digital Library, and Web of Science) were searched using a combination of terms related to ECAs and health in October 2023. Two independent reviewers selected the studies and extracted the data. This review followed the PRISMA-ScR (Preferred Reporting Items of Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. RESULTS: The literature search found 6332 papers, of which 36 (0.57%) met the inclusion criteria. Among the 36 studies, 27 (75%) originated from the United States, and 28 (78%) were published from 2020 onward. The reported ECAs covered a wide range of chronic diseases, with a focus on cancers, atrial fibrillation, and type 2 diabetes, primarily to promote screening and self-management. Most ECAs were depicted as middle-aged women based on screenshots and communicated with users through voice and nonverbal behavior. The most frequently reported evaluation outcomes were acceptability and effectiveness. CONCLUSIONS: This scoping review provides valuable insights for technology developers and health care professionals regarding the development and implementation of ECAs. It emphasizes the importance of technological advances in the embodiment, personalized strategy, and communication modality and requires in-depth knowledge of user preferences regarding appearance, animation, and intervention content. Future studies should incorporate measures of cost, efficiency, and productivity to provide a comprehensive evaluation of the benefits of using ECAs in health care.

The ribosomal transcription units of five echinostomes and their taxonomic implications for the suborder Echinostomata (Trematoda: Platyhelminthes).

Five newly obtained nuclear ribosomal transcription unit (rTU) sequences from Echinostomatidae and Echinochasmidae are presented. The inter- and intrafamilial relationships of these and other families in the suborder Echinostomata are also analyzed. The sequences obtained are the complete rTU of Artyfechinostomum malayanum (9,499 bp), the near-complete rTU of Hypoderaeum conoideum (8,076 bp), and the coding regions (from 5'-terminus of 18S to 3'-terminus of 28S rRNA gene) in Echinostoma revolutum (6,856 bp), Echinostoma miyagawai (6,854 bp), and Echinochasmus japonicus (7,150 bp). Except for the longer first internal transcribed spacer (ITS1) in Echinochasmus japonicus, all genes and spacers were almost identical in length. Comprehensive maximum-likelihood phylogenies were constructed using the PhyML software package. The datasets were either the concatenated 28S + 18S rDNA sequences (5.7-5.8 kb) from 60 complete rTUs of 19 families or complete 28S sequences only (about 3.8-3.9 kb) from 70 strains or species of 22 families. The phylogenetic trees confirmed Echinostomatoidea as monophyletic. Furthermore, a detailed phylogeny constructed from alignments of 169 28S D1-D3 rDNA sequences (1.1-1.3 kb) from 98 species of 50 genera of 10 families, including 154 echinostomatoid sequences (85 species/42 genera), clearly indicated known generic relationships within Echinostomatidae and Echinochasmidae and relationships of families within Echinostomata and several other suborders. Within Echinostomatidae, Echinostoma, Artyfechinostomum, and Hypoderaeum appeared as monophyletic, while Echinochasmus (Echinochasmidae) was polyphyletic. The Echinochasmidae are a sister group to the Psilostomidae. The datasets provided here will be useful for taxonomic reappraisal as well as studies of evolutionary and population genetics in the superfamily Echinostomatoidea, the sole superfamily in the suborder Echinostomata.

SARS-CoV-2 Spike Protein Enhances Carboxypeptidase Activity of Angiotensin-Converting Enzyme 2.

In this study, we investigated whether severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein may modify angiotensin-converting enzyme 2 (ACE2) activity in the plasma, heart, kidney, liver, lung, and six brain regions (amygdala, brain stem, cortex, hippocampus, hypothalamus, and striatum) of diabetic and hypertensive rats. We determine ACE2 activity in the plasma and lysates of heart, kidney, liver, lung, and six brain regions. MLN-4760 inhibits ACE2 activity in the plasma and all organs. On the other hand, soluble ACE2 (sACE2) activity increased in the plasma of diabetic rats, and there was no change in the plasma of hypertensive rats. ACE2 activity was augmented in the liver, brain stem, and striatum, while it decreased in the kidney, amygdala, cortex, and hippocampus of diabetic rats. ACE2 activity increased in the kidney, liver, and lung, while it decreased in the heart, amygdala, cortex, and hypothalamus of hypertensive rats. We measured the ACE2 content via enzyme-linked immunosorbent assay and found that ACE2 protein levels increased in the heart, while it decreased in the plasma, kidney, brain stem, cortex, hippocampus, hypothalamus, and striatum of diabetic rats. ACE2 protein levels decreased in the brain stem, cortex, hippocampus, and hypothalamus of hypertensive rats. Our data showed that the spike protein enhanced ACE2 activity in the liver and lungs of diabetic rats, as well as in the heart and three of the brain regions (cortex, hypothalamus, and striatum) of hypertensive rats.

Efficient DNA Coding Algorithm for Polymerase Chain Reaction Amplification Information Retrieval.

Polymerase Chain Reaction (PCR) amplification is widely used for retrieving information from DNA storage. During the PCR amplification process, nonspecific pairing between the 3' end of the primer and the DNA sequence can cause cross-talk in the amplification reaction, leading to the generation of interfering sequences and reduced amplification accuracy. To address this issue, we propose an efficient coding algorithm for PCR amplification information retrieval (ECA-PCRAIR). This algorithm employs variable-length scanning and pruning optimization to construct a codebook that maximizes storage density while satisfying traditional biological constraints. Subsequently, a codeword search tree is constructed based on the primer library to optimize the codebook, and a variable-length interleaver is used for constraint detection and correction, thereby minimizing the likelihood of nonspecific pairing. Experimental results demonstrate that ECA-PCRAIR can reduce the probability of nonspecific pairing between the 3' end of the primer and the DNA sequence to 2-25%, enhancing the robustness of the DNA sequences. Additionally, ECA-PCRAIR achieves a storage density of 2.14-3.67 bits per nucleotide (bits/nt), significantly improving storage capacity.

Clinical Outcomes after Intracorporeal versus Extracorporeal Anastomosis in Patients Undergoing Laparoscopic Right Hemicolectomy for Colon Cancer.

Background and Objectives: Laparoscopic right hemicolectomy (LRHC) is commonly performed for patients with colon cancer, selecting between intracorporeal anastomosis (ICA) or extracorporeal anastomosis (ECA). However, the impact of ICA versus ECA on patient outcomes remains debatable. The varying levels of experience among surgeons may influence the outcomes. Therefore, this study sought to compare the short- and long-term outcomes of LRHC using ICA versus ECA. Materials and Methods: This retrospective study extracted patient data from the medical records database of Changhua Christian Hospital, Taiwan, from 2017 to 2020. Patients with colon cancer who underwent LRHC with either ICA or ECA were included. Primary outcomes were post-surgical outcomes and secondary outcomes were recurrence rate, overall survival (OS), and cancer-specific survival (CSS). Between-group differences were compared using chi-square, t-tests, and Fisher's exact tests and Mann-Whitney U tests. Associations between study variables, OS, and CSS were determined using Cox analyses. Results: Data of 240 patients (61 of ICA and 179 of ECA) with a mean age of 65.0 years and median follow-up of 49.3 months were collected. No recognized difference was found in patient characteristics between these two groups. The ICA group had a significantly shorter operation duration (median (IQR): 120 (110-155) vs. 150 (130-180) min) and less blood loss (median (IQR): 30 (10-30) vs. 30 (30-50) mL) than the ECA group (p < 0.001). No significant differences were found in 30-day readmission (ICA vs. ECA: 1.6% vs. 2.2%, p > 0.999) or recurrence (18.0% vs. 13.4%, p = 0.377) between the two groups. Multivariable analyses revealed no significant differences in OS (adjusted hazard ratio (aHR): 0.65; 95% confidence interval (CI): 0.25-1.44) or CSS (adjusted sub-hazard ratio (aSHR): 0.41, 95% CI: 0.10-1.66) between groups. Conclusions: Both ICA and ECA in LRHC for colon cancer had similar outcomes without statistically significant differences in post-surgical complications, 30-day readmission rates, recurrence rate, and long-term survival outcomes. However, ICA may offer two advantages in terms of a shorter operative duration and reduced blood loss.

Epidemiological, Clinical, and Allergic Profile of Psoriatic Patients. Evaluation of the Spanish Registry of Contact Dermatitis and Cutaneous Allergy (REIDAC). / Perfil epidemiológico, clínico y alérgico en pacientes con psoriasis. Evaluación del Registro Español de Dermatitis de Contacto (REIDAC).

BACKGROUND: Psoriasis is a chronic inflammatory dermatosis whose clinical and topographic distribution requires differential diagnosis, or the possible association with allergic contact dermatitis (ACD), requiring patch testing (PT) as part of the diagnostic procedure. OBJECTIVES: To describe the epidemiological, clinical, and allergic profile of patients with a primary or secondary diagnosis of psoriasis undergoing PT and compare them with patients with a diagnosis of ACD at the end of the diagnostic process. METHODS: Cross-sectional study with data from REIDAC from 2018 through 2023 of selected patients with a diagnosis of psoriasis and/or ACD. RESULTS: A total of 11 502 patients were included, 513 of whom had been diagnosed with primary or secondary psoriasis, 3640 with ACD, and 108 with both diseases. Men were more predominant in the groups of patients with psoriasis, psoriasis+ACD, and lesions were more predominantly seen in the hands with little association with atopic factors vs the ACD group. The rate of positivity in PT to the 2022 Spanish battery of allergens was lower in the group with psoriasis only in 27% of the patients. The most common allergens found in the psoriasis group were also the most common ones found in the overall ACD population. CONCLUSIONS: Overall, 36.2% of psoriatic patients tested positive in PT to the 2022 Spanish battery of allergens, which proved that this association is not uncommon. Overall, psoriatic patients had a higher mean age, were more predominantly men, and showed more hand involvement.

[Translated article] Epidemiological, Clinical, and Allergic Profile of Psoriatic Patients. Evaluation of the Spanish Registry of Contact Dermatitis and Cutaneous Allergy (REIDAC).

BACKGROUND: Psoriasis is a chronic inflammatory dermatosis whose clinical and topographic distribution requires differential diagnosis, or the possible association with allergic contact dermatitis (ACD), requiring patch testing (PT) as part of the diagnostic procedure. OBJECTIVES: To describe the epidemiological, clinical, and allergic profile of patients with a primary or secondary diagnosis of psoriasis undergoing PT and compare them with patients with a diagnosis of ACD at the end of the diagnostic process. METHODS: Cross-sectional study with data from REIDAC from 2018 through 2023 of selected patients with a diagnosis of psoriasis and/or ACD. RESULTS: A total of 11 502 patients were included, 513 of whom had been diagnosed with primary or secondary psoriasis, 3640 with ACD, and 108 with both diseases. Men were more predominant in the groups of patients with psoriasis, psoriasis+ACD, and lesions were more predominantly seen in the hands with little association with atopic factors vs the ACD group. The rate of positivity in PT to the 2022 Spanish battery of allergens was lower in the group with psoriasis only in 27% of the patients. The most common allergens found in the psoriasis group were also the most common ones found in the overall ACD population. CONCLUSIONS: Overall, 36.2% of psoriatic patients tested positive in PT to the 2022 Spanish battery of allergens, which proved that this association is not uncommon. Overall, psoriatic patients had a higher mean age, were more predominantly men, and showed more hand involvement.

Subcellular localization of the enterobacterial common antigen GT-E-like glycosyltransferase, WecG.

Enterobacterales have developed a specialized outer membrane polysaccharide (enterobacterial common antigen [ECA]). ECA biosynthesis begins on the cytoplasmic side of the inner membrane (IM) where glycosyltransferases sequentially add sugar moieties to form a complete repeat unit which is then translocated across the IM by WzxE before being polymerized into short linear chains by WzyE/WzzE. Research into WecG, the enzyme responsible for generating ECA lipid-II, has not progressed beyond Barr et al. (1988) who described WecG as a membrane protein. Here we revise our understanding of WecG and re-characterize it as a peripherally associated membrane protein. Through the use of Western immunoblotting we show that WecG in Shigella flexneri is maintained to the IM via its three C-terminal helices and further identify key residues in helix II which are critical for this interaction which has allowed us to identify WecG as a GT-E glycosyltransferase. We investigate the possibility of protein complexes and ultimately show that ECA lipid-I maintains WecG to the membrane which is crucial for its function. This research is the first since Barr et al. (1988) to investigate the biochemistry of WecG and reveals possible novel drug targets to inhibit WecG and thus ECA function and cell viability.

Effects of Amazonian flying rivers on frog biodiversity and populations in the Atlantic rainforest.

Given the speed at which humans are changing the climate, species with high degrees of endemism may not have time to avoid extinction through adaptation. We investigated through teleconnection analysis the origin of rainfall that determines the phylogenetic diversity of rainforest frogs and the effects of microclimate differences in shaping the morphological traits of isolated populations (which contribute to greater phylogenetic diversity and speciation). We also investigated through teleconnection analysis how deforestation in Amazonia can affect ecosystem services that are fundamental to maintaining the climate of the Atlantic rainforest biodiversity hotspot. Seasonal winds known as flying rivers carry water vapor from Amazonia to the Atlantic Forest, and the breaking of this ecosystem service could lead Atlantic Forest species to population decline and extinction in the short term. Our results suggest that the selection of morphological traits that shape Atlantic Forest frog diversity and their population dynamics are influenced by the Amazonian flying rivers. Our results also suggest that the increases of temperature anomalies in the Atlantic Ocean due to global warming and in the Amazon forest due to deforestation are already breaking this cycle and threaten the biodiversity of the Atlantic Forest hotspot.

Efectos de los ríos voladores de la Amazonía sobre la diversidad y las poblaciones de ranas en la Mata Atlántica Resumen Con la velocidad a la que la humanidad está alterando el clima, puede que las especies con un nivel elevado de endemismo no cuenten con tiempo suficiente para adaptarse y evitar la extinción. Usamos un análisis de teleconexión para investigar el origen de las precipitaciones que determinan la diversidad filogenética de las ranas selváticas y los efectos de las diferencias microclimáticas sobre la determinación de las características morfológicas de las poblaciones aisladas, las cuales contribuyen a una mayor especiación y diversidad filogenética. También utilizamos este análisis para investigar cómo la deforestación en la Amazonía puede afectar los servicios ambientales que son fundamentales para mantener el punto caliente de biodiversidad que es la Mata Atlántica. Los ríos voladores son vientos estacionales que transportan vapor de agua desde la Amazonía hasta la Mata Atlántica; la interrupción de este servicio ambiental podría derivar en la declinación poblacional y la extinción a corto plazo de las especies en este ecosistema. Nuestros resultados sugieren que los ríos voladores de la Amazonía influyen sobre la selección de las características morfológicas que determinan la diversidad de ranas y sus dinámicas poblacionales en la Mata Atlántica. Nuestros resultados también sugieren que el incremento de anomalías térmicas en el Océano Atlántico, causadas por el calentamiento global, y en la Amazonía, causadas por la deforestación, ya están interrumpiendo este ciclo y son una amenaza para la biodiversidad del punto caliente que es la Mata Atlántica.

Embodied Conversational Agents Providing Motivational Interviewing to Improve Health-Related Behaviors: Scoping Review.

BACKGROUND: Embodied conversational agents (ECAs) are advanced human-like interfaces that engage users in natural face-to-face conversations and interactions. These traits position ECAs as innovative tools for delivering interventions for promoting health-related behavior adoption. This includes motivational interviewing (MI), a therapeutic approach that combines brief interventions with motivational techniques to encourage the adoption of healthier behaviors. OBJECTIVE: This study aims to identify the health issues addressed by ECAs delivering MI interventions, explore the key characteristics of these ECAs (eg, appearance, dialogue mechanism, emotional model), analyze the implementation of MI principles and techniques within ECAs, and examine the evaluation methods and primary outcomes of studies that use ECAs providing MI interventions. METHODS: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) methodology. Our systematic search covered the PubMed, Scopus, IEEE Xplore, ACM Digital, and PsycINFO databases for papers published between January 2008 and December 2022. We included papers describing ECAs developed for delivering MI interventions targeting health-related behaviors and excluded articles that did not describe ECAs with human appearances and without the necessary evaluation or MI explanation. In a multistage process, 3 independent reviewers performed screening and data extraction, and the collected data were synthesized using a narrative approach. RESULTS: The initial search identified 404 articles, of which 3.5% (n=14) were included in the review. ECAs primarily focused on reducing alcohol use (n=5, 36%), took on female representations (n=9, 64%), and gave limited consideration to user ethnicity (n=9, 64%). Most of them used rules-driven dialogue mechanisms (n=13, 93%), include emotional behavior to convey empathy (n=8, 57%) but without an automatic recognition of user emotions (n=12, 86%). Regarding MI implementation, of 14 studies, 3 (21%) covered all MI principles, 4 (29%) included all processes, and none covered all techniques. Most studies (8/14, 57%) conducted acceptability, usability, and user experience assessments, whereas a smaller proportion (4/14, 29%) used randomized controlled trials to evaluate behavior changes. Overall, the studies reported positive results regarding acceptability, usability, and user experience and showed promising outcomes in changes in attitudes, beliefs, motivation, and behavior. CONCLUSIONS: This study revealed significant advancements in the use of ECAs for delivering MI interventions aimed at promoting healthier behaviors over the past 15 years. However, this review emphasizes the need for a more in-depth exploration of ECA characteristics. In addition, there is a need for the enhanced integration of MI principles, processes, and techniques into ECAs. Although acceptability and usability have received considerable attention, there is a compelling argument for placing a stronger emphasis on assessing changes in attitudes, beliefs, motivation, and behavior. Consequently, inclusion of more randomized controlled trials is essential for comprehensive intervention evaluations.

Lightweight Network DCR-YOLO for Surface Defect Detection on Printed Circuit Boards.

To resolve the problems associated with the small target presented by printed circuit board surface defects and the low detection accuracy of these defects, the printed circuit board surface-defect detection network DCR-YOLO is designed to meet the premise of real-time detection speed and effectively improve the detection accuracy. Firstly, the backbone feature extraction network DCR-backbone, which consists of two CR residual blocks and one common residual block, is used for small-target defect extraction on printed circuit boards. Secondly, the SDDT-FPN feature fusion module is responsible for the fusion of high-level features to low-level features while enhancing feature fusion for the feature fusion layer, where the small-target prediction head YOLO Head-P3 is located, to further enhance the low-level feature representation. The PCR module enhances the feature fusion mechanism between the backbone feature extraction network and the SDDT-FPN feature fusion module at different scales of feature layers. The C5ECA module is responsible for adaptive adjustment of feature weights and adaptive attention to the requirements of small-target defect information, further enhancing the adaptive feature extraction capability of the feature fusion module. Finally, three YOLO-Heads are responsible for predicting small-target defects for different scales. Experiments show that the DCR-YOLO network model detection map reaches 98.58%; the model size is 7.73 MB, which meets the lightweight requirement; and the detection speed reaches 103.15 fps, which meets the application requirements for real-time detection of small-target defects.

Low-Pass Filters for a Temperature Drift Correction Method for Electromagnetic Induction Systems.

Electromagnetic induction (EMI) systems are used for mapping the soil's electrical conductivity in near-surface applications. EMI measurements are commonly affected by time-varying external environmental factors, with temperature fluctuations being a big contributing factor. This makes it challenging to obtain stable and reliable data from EMI measurements. To mitigate these temperature drift effects, it is customary to perform a temperature drift calibration of the instrument in a temperature-controlled environment. This involves recording the apparent electrical conductivity (ECa) values at specific temperatures to obtain a look-up table that can subsequently be used for static ECa drift correction. However, static drift correction does not account for the delayed thermal variations of the system components, which affects the accuracy of drift correction. Here, a drift correction approach is presented that accounts for delayed thermal variations of EMI system components using two low-pass filters (LPF). Scenarios with uniform and non-uniform temperature distributions in the measurement device are both considered. The approach is developed using a total of 15 measurements with a custom-made EMI device in a wide range of temperature conditions ranging from 10 °C to 50 °C. The EMI device is equipped with eight temperature sensors spread across the device that simultaneously measure the internal ambient temperature during measurements. To parameterize the proposed correction approach, a global optimization algorithm called Shuffled Complex Evolution (SCE-UA) was used for efficient estimation of the calibration parameters. Using the presented drift model to perform corrections for each individual measurement resulted in a root mean square error (RMSE) of <1 mSm-1 for all 15 measurements. This shows that the drift model can properly describe the drift of the measurement device. Performing a drift correction simultaneously for all datasets resulted in a RMSE <1.2 mSm-1, which is considerably lower than the RMSE values of up to 4.5 mSm-1 obtained when using only a single LPF to perform drift corrections. This shows that the presented drift correction method based on two LPFs is more appropriate and effective for mitigating temperature drift effects.

A Multi-Attention Approach for Person Re-Identification Using Deep Learning.

Person re-identification (Re-ID) is a method for identifying the same individual via several non-interfering cameras. Person Re-ID has been felicitously applied to an assortment of computer vision applications. Due to the emergence of deep learning algorithms, person Re-ID techniques, which often involve the attention module, have gained remarkable success. Moreover, people's traits are mostly similar, which makes distinguishing between them complicated. This paper presents a novel approach for person Re-ID, by introducing a multi-part feature network, that combines the position attention module (PAM) and the efficient channel attention (ECA). The goal is to enhance the accuracy and robustness of person Re-ID methods through the use of attention mechanisms. The proposed multi-part feature network employs the PAM to extract robust and discriminative features by utilizing channel, spatial, and temporal context information. The PAM learns the spatial interdependencies of features and extracts a greater variety of contextual information from local elements, hence enhancing their capacity for representation. The ECA captures local cross-channel interaction and reduces the model's complexity, while maintaining accuracy. Inclusive experiments were executed on three publicly available person Re-ID datasets: Market-1501, DukeMTMC, and CUHK-03. The outcomes reveal that the suggested method outperforms existing state-of-the-art methods, and the rank-1 accuracy can achieve 95.93%, 89.77%, and 73.21% in trials on the public datasets Market-1501, DukeMTMC-reID, and CUHK03, respectively, and can reach 96.41%, 94.08%, and 91.21% after re-ranking. The proposed method demonstrates a high generalization capability and improves both quantitative and qualitative performance. Finally, the proposed multi-part feature network, with the combination of PAM and ECA, offers a promising solution for person Re-ID, by combining the benefits of temporal, spatial, and channel information. The results of this study evidence the effectiveness and potential of the suggested method for person Re-ID in computer vision applications.

Red Tide Detection Method Based on Improved U-Net Model-Taking GOCI Data in East China Sea as an Example.

In the coastal areas of China, the eutrophication of seawater leads to the continuous occurrence of red tide, which has caused great damage to Marine fisheries and aquatic resources. Therefore, the detection and prediction of red tide have important research significance. The rapid development of optical remote sensing technology and deep-learning technology provides technical means for realizing large-scale and high-precision red tide detection. However, the difficulty of the accurate detection of red tide edges with complex boundaries limits the further improvement of red tide detection accuracy. In view of the above problems, this paper takes GOCI data in the East China Sea as an example and proposes an improved U-Net red tide detection method. In the improved U-Net method, NDVI was introduced to enhance the characteristic information of the red tide to improve the separability between the red tide and seawater. At the same time, the ECA channel attention mechanism was introduced to give different weights according to the influence of different bands on red tide detection, and the spectral characteristics of different channels were fully mined to further extract red tide characteristics. A shallow feature extraction module based on Atrous Spatial Pyramid Convolution (ASPC) was designed to improve the U-Net model. The red tide feature information in a multi-scale context was fused under multiple sampling rates to enhance the model's ability to extract features at different scales. The problem of limited accuracy improvement in red tide edge detection with complex boundaries is solved via the fusion of deep and shallow features and multi-scale spatial features. Compared with other methods, the method proposed in this paper achieves better results and can detect red tide edges with complex boundaries, and the accuracy, precision, recall, and F1-score are 95.90%, 97.15%, 91.53%, and 0.94, respectively. In addition, the red tide detection experiments in other regions with relatively concentrated distribution also prove that the method has good applicability.

YOLO-GW: Quickly and Accurately Detecting Pedestrians in a Foggy Traffic Environment.

In practice, the object detection algorithm is limited by a complex detection environment, hardware costs, computing power, and chip running memory. The performance of the detector will be greatly reduced during operation. Determining how to realize real-time, fast, and high-precision pedestrian recognition in a foggy traffic environment is a very challenging problem. To solve this problem, the dark channel de-fogging algorithm is added to the basis of the YOLOv7 algorithm, which effectively improves the de-fogging efficiency of the dark channel through the methods of down-sampling and up-sampling. In order to further improve the accuracy of the YOLOv7 object detection algorithm, the ECA module and a detection head are added to the network to improve object classification and regression. Moreover, an 864 × 864 network input size is used for model training to improve the accuracy of the object detection algorithm for pedestrian recognition. Then the combined pruning strategy was used to improve the optimized YOLOv7 detection model, and finally, the optimization algorithm YOLO-GW was obtained. Compared with YOLOv7 object detection, YOLO-GW increased Frames Per Second (FPS) by 63.08%, mean Average Precision (mAP) increased by 9.06%, parameters decreased by 97.66%, and volume decreased by 96.36%. Smaller training parameters and model space make it possible for the YOLO-GW target detection algorithm to be deployed on the chip. Through analysis and comparison of experimental data, it is concluded that YOLO-GW is more suitable for pedestrian detection in a fog environment than YOLOv7.

Multi-Modal Feature Fusion-Based Multi-Branch Classification Network for Pulmonary Nodule Malignancy Suspiciousness Diagnosis.

Detecting and identifying malignant nodules on chest computed tomography (CT) plays an important role in the early diagnosis and timely treatment of lung cancer, which can greatly reduce the number of deaths worldwide. In view of the existing methods in pulmonary nodule diagnosis, the importance of clinical radiological structured data (laboratory examination, radiological data) is ignored for the accuracy judgment of patients' condition. Hence, a multi-modal fusion multi-branch classification network is constructed to detect and classify pulmonary nodules in this work: (1) Radiological data of pulmonary nodules are used to construct structured features of length 9. (2) A multi-branch fusion-based effective attention mechanism network is designed for 3D CT Patch unstructured data, which uses 3D ECA-ResNet to dynamically adjust the extracted features. In addition, feature maps with different receptive fields from multi-layer are fully fused to obtain representative multi-scale unstructured features. (3) Multi-modal feature fusion of structured data and unstructured data is performed to distinguish benign and malignant nodules. Numerous experimental results show that this advanced network can effectively classify the benign and malignant pulmonary nodules for clinical diagnosis, which achieves the highest accuracy (94.89%), sensitivity (94.91%), and F1-score (94.65%) and lowest false positive rate (5.55%).

Comparative Genomics Identifies the Evolutionarily Conserved Gene TPM3 as a Target of eca-miR-1 Involved in the Skeletal Muscle Development of Donkeys.

Species within the genus Equus are valued for their draft ability. Skeletal muscle forms the foundation of the draft ability of Equus species; however, skeletal muscle development-related conserved genes and their target miRNAs are rarely reported for Equus. In this study, a comparative genomics analysis was performed among five species (horse, donkey, zebra, cattle, and goat), and the results showed that a total of 15,262 (47.43%) genes formed the core gene set of the five species. Only nine chromosomes (Chr01, Chr02, Chr03, Chr06, Chr10, Chr18, Chr22, Chr27, Chr29, and Chr30) exhibited a good collinearity relationship among Equus species. The micro-synteny analysis results showed that TPM3 was evolutionarily conserved in chromosome 1 in Equus. Furthermore, donkeys were used as the model species for Equus to investigate the genetic role of TPM3 in muscle development. Interestingly, the results of comparative transcriptomics showed that the TPM3 gene was differentially expressed in donkey skeletal muscle S1 (2 months old) and S2 (24 months old), as verified via RT-PCR. Dual-luciferase test analysis showed that the TPM3 gene was targeted by differentially expressed miRNA (eca-miR-1). Furthermore, a total of 17 TPM3 gene family members were identified in the whole genome of donkey, and a heatmap analysis showed that EaTPM3-5 was a key member of the TPM3 gene family, which is involved in skeletal muscle development. In conclusion, the TPM3 gene was conserved in Equus, and EaTPM3-5 was targeted by eca-miR-1, which is involved in skeletal muscle development in donkeys.

Study of Brewer's Spent Grain Environmentally Friendly Processing Ways.

BACKGROUND: This article is devoted to the study of the effect of electrochemically activated water (catholyte with pH 9.3) on organic compounds of the plant matrix of brewer's spent grain in order to extract various compounds from it. METHODS: Brewer's spent grain was obtained from barley malt at a pilot plant by mashing the malt followed by filtration and washing of the grain in water and storing it at (0 ± 2) °C in craft bags. For the organic compound quantitative determination, instrumental methods of analysis (HPLC) were used, and the results were subjected to mathematical analysis. RESULTS: The study results showed that at atmospheric pressure, the alkaline properties of the catholyte showed better results compared to aqueous extraction with respect to ß-glucan, sugars, nitrogenous and phenolic compounds, and 120 min was the best period for extraction at 50 °C. The excess pressure conditions used (0.5 ÷ 1 atm) revealed an increase in the accumulation of non-starch polysaccharide and nitrogenous compounds, while the level of sugars, furan and phenolic compounds decreased with increasing treatment duration. The waste grain extract ultrasonic treatment used revealed the effectiveness of catholyte in relation to the extraction of ß-glucan and nitrogenous fractions; however, sugars and phenolic compounds did not significantly accumulate. The correlation method made it possible to reveal the regularities in the formation of furan compounds under the conditions of extraction with the catholyte: Syringic acid had the greatest effect on the formation of 5-OH-methylfurfural at atmospheric pressure and 50 °C and vanillic acid under conditions of excess pressure. Regarding furfural and 5-methylfurfural, amino acids had a direct effect at excess pressure. It was shown that the content of all furan compounds depends on amino acids with thiol groups and gallic acid; the formation of 5-hydroxymethylfurfural and 5-methylfurfural is influenced by gallic and vanillic acids; the release of furfural and 5-methylfurfural is determined by amino acids and gallic acid; excess pressure conditions promote the formation of furan compounds under the action of gallic and lilac acids. CONCLUSIONS: This study showed that a catholyte allows for efficient extraction of carbohydrate, nitrogenous and monophenolic compounds under pressure conditions, while flavonoids require a reduction in extraction time under pressure conditions.

Competition and firm recovery post-COVID-19.

This paper examines the impact of the COVID-19 crisis on the reallocation of economic activity across firms and whether this reallocation depends on the competition environment. The paper uses the World Bank's Enterprise Surveys COVID-19 Follow-up Surveys for about 8000 firms, including both small and large firms, in 23 emerging and developing countries in Europe and Central Asia, matched with 2019 Enterprise Surveys data. It finds that during the COVID-19 crisis, smaller firms were hit harder, and economic activity was reallocated toward firms with higher pre-crisis labor productivity. Countries with a strong competition environment experienced more reallocation from less productive to more productive firms than countries with a weak competition environment. The evidence also suggests that reallocation from low- to high-productivity firms during the COVID-19 crisis was stronger compared with pre-crisis times. Finally, the analysis shows that government support measures implemented in response to the crisis may have adverse effects on competition and productivity growth since support went to less productive and larger firms, regardless of their pre-crisis innovation.