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Optical detection of the freshness of intact in-shell shrimps is a well-known difficult task due to shell occlusion and its signal interference. The spatially offset Raman spectroscopy (SORS) is a workable technical solution for identifying and extracting subsurface shrimp meat information by collecting Raman scattering images at different distances from the offset laser incidence point. However, the SORS technology still suffers from physical information loss, difficulties in determining the optimum offset distance, and human operational errors. Thus, this paper presents a shrimp freshness detection method using spatially offset Raman spectroscopy combined with a targeted attention-based long short-term memory network (attention-based LSTM). The proposed attention-based LSTM model uses the LSTM module to extract physical and chemical composition information of tissue, weight the output of each module by an attention mechanism, and come together as a fully connected (FC) module for feature fusion and storage dates prediction. Modeling predictions by collecting Raman scattering images of 100 shrimps within 7 days. The R2, RMSE, and RPD of the attention-based LSTM model achieved 0.93, 0.48, and 4.06, respectively, which is superior to the conventional machine learning algorithm with manual selection of the optimal spatially offset distance. This method of automatically extracting information from SORS data by Attention-based LSTM eliminates human error and enables fast and non-destructive quality inspection of in-shell shrimp.

Currently, the obstacle avoidance control of patrol robots based on intelligent vision lacks professional controller module assistance. Therefore, this paper proposes a design method of intelligent controller for obstacle avoidance and navigation of electrical inspection mobile robot based on PLC control. The controller designs a laser range finder to determine the required position of electrical patrol inspection. Use PLC as the core controller, and combine sensors, actuators, communication module and PLC selection module in the process of hardware design to achieve autonomous navigation and obstacle avoidance functions of the robot. Then design the software including the PLC compiler system and the virtual machine module. Based on the above steps, design the control module of obstacle avoidance navigation, which realizes the key link of robot autonomous navigation. The test results show that the controller can successfully avoid obstacles, improve the efficiency and quality of inspection, and achieve accurate and fast obstacle avoidance navigation for the electrical inspection mobile robot.

Background Music training for learners has improved greatly in recent years with the inclusion of information technology and optimization methods. The improvements focus on assisted learning, instruction suggestions, and performance assessments. Purpose An adaptive instructive suggestion method (AISM) using deep neural fuzzy control (FC) is introduced in this paper to provide persistent assistance for technology-based music classrooms. This proposed method reduces learning errors by pursuing instructions based on the learner’s level. The instructions are adaptable depending on the error and level independent of different suggestions. The suggestions are replicated for similar issues across various music learning classrooms, retaining the constant fuzzification. Materials and methods The fuzzy control deviates at every new level, and errors are identified over the deviations from the instructions pursued. This control process verifies the input based on instruction deviations to prevent error repetitions. Therefore, the fuzzification relies on error normalization using common adaptive suggestions for different learning sessions. If the fuzzy control fails to match the existing instruction pursued, then new instructions are augmented to reduce errors that serve as the FC constraint. This constraint is pursued by unresolved previous errors to improve learning efficacy. Results Thus, compared to other methods, the system improves adaptability by 13.9%, efficiency analysis by 9.02%, and constraint detection by 10.26%.

Myelodysplastic syndromes (MDS) are characterized by ineffective hematopoiesis and the abnormal differentiation of hematopoietic stem cells. An increasing number of researches have demonstrated that microRNAs play crucial roles in the pathogenesis of myelodysplastic syndromes. Herein, we aimed to identify novel potential microRNAs bound up with the diagnosis and prognosis of MDS. MiRNA microarray analysis was used to screen deregulated microRNAs in the bone marrow of MDS patients. qRT-PCR was employed to confirm the microarray results. All members of miR-320 family (miR-320a, miR-320b, miR-320c, miR-320d, and miR-320e) were significantly increased in MDS patients compared to normal control. Although we found no correlation between miR-320 family and most clinical characteristics, high miR-320c and miR-320d expression seemed to be associated with high numbers of bone marrow (BM) blasts and worse karyotype. High expression of all the members of the miR-320 family seemed to be associated with a high prognostic score based on International Prognostic Scoring System (IPSS). The areas under the miR-320 family member ROC curves were 0.9037 (P < 0.0001), 0.7515 (P = 0.0002), 0.9647 (P < 0.0001), 0.8064 (P < 0.0001) and 0.9019 (P < 0.0001). Regarding Kaplan–Meier analysis, high miR-320c and miR-320d expression were related to shorter overall survival (OS). Moreover, multivariate analysis revealed the independent prognostic value of miR-320d for OS in MDS. The expression of miR-320 family members was up-regulated in MDS, and miR-320 family members could serve as candidate diagnostic biomarkers for MDS. High expression of miR-320d was an independent prognostic factor for OS in MDS.

8p11 myeloproliferative syndrome (EMS) is a rare aggressive hematologic malignancy with a poor prognosis that can rapidly develop into acute leukemia. It is characterized by the translocation of fibroblast growth factor receptor-1 (FGFR1), and there is still a lack of effective and reliable treatment methods at present. This report provides a new therapeutic strategy for EMS patients diagnosed with BCR-FGFR1 fusion. This report describes a case of EMS patient with a positive BCR-FGFR1 fusion gene, whose manifestations are similar to those of chronic myeloid leukemia (CML). After diagnosis by fluorescence in situ hybridization (FISH) and RNA sequencing (RNA-seq), olverembatinib, the third-generation tyrosinase inhibitor (TKI) developed in China, was used for treatment. After monotherapy and follow-up for more than one year, partial molecular response (PR) was achieved. During this period, hematologic remission and cytogenetic remission were achieved. The treatment safety of the entire process was excellent. In summary, olverembatinib provides more treatment options for rare diseases such as 8p11 myeloproliferative syndrome.

Depth degradation caused by the conditions and environment of depth sensor hardware restricts its application potential, and this limitation cannot be avoided simply by improving the design of sensor. To overcome this limitation, we propose a multi-resolution depth image restoration method. Firstly, the sub-images of depth image and color image at different scales are obtained by multi-resolution analysis based on two-dimensional discrete wavelet transform. The multi-resolution joint bilateral filtering is then applied to the approximation low-frequency sub-image of the decomposed image. At the same time, using color-guided filtering method to restore high-frequency sub-images can effectively suppress edge artifacts without adding extra time burden. The high-quality output image is finally reconstructed using two-dimensional inverse discrete wavelet transform. A color guide image with rich edge information is introduced into the depth sub-image restoration to improve the depth image edge detail. Extensive experiments with synthetic and real datasets demonstrate that the proposed algorithm can effectively reduce additive Gaussian noise without losing sharp details in the noisy images and reduce the time consumption of depth image restoration.

Background While single embryo transfer (SET) is widely advocated, double embryo transfer (DET) remains preferable in clinical practice to improve IVF success rate, especially in poor prognosis patients with only poor quality embryos (PQEs) available in addition to one or no good quality embryos (GQEs). Furthermore, previous studies suggest PQE might adversely affect the implantation of a GQE when transferred together. This study aims to evaluate the effect of transferring an additional PQE with a GQE on the outcomes in poor prognosis patients. Methods A total of 5037 frozen-thawed blastocyst transfer (FBT) cycles between January 2012 and May 2019 were included. Propensity score matching was applied to control for potential confounders, and we used generalized estimating equations (GEE) models to identify the association between the effect of an additional PQE and the outcomes. Results Overall, transferring a PQE with GQE (Group GP) achieved significantly higher pregnancy rate (PR), live birth rate (LBR) and multiple pregnancy rate (MPR) than GQE only (group G). The addition of a PQE increased LBR in patients aged 35 and over and in patients who received over 3 cycles of embryo transfer (ET) (48.1% vs 27.2%, OR:2.56, 95% CI: 1.3–5.03 and 46.6% vs 35.4%, OR:1.6, 95% CI: 1.09–2.35), but not in women under 35 and in women who received less than 3 cycles of ET (48.7% vs 43.9%, OR:1.22, 95% CI: 0.93–1.59 and 48.3% vs 41.4%, OR:1.33, 95% CI: 0.96–1.85). Group GP resulted in significantly higher MPR than group G irrespective of age and the number of previous IVF cycles. Conclusions An additional PQE does not negatively affect the implantation potential of the co-transferred GQE. Nevertheless, the addition of a PQE contributes to both live birth and multiple birth in poor prognosis patients. Physicians should still balance the benefits and risks of DET.

Background Advanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the present study was to evaluate the predictive power of conventional morphological evaluation regarding blastocyst formation. Methods Retrospective evaluation of data from 15,613 patients receiving blastocyst culture from January 2013 through December 2020 in our institution were reviewed. Generalized estimating equations (GEE) were used to establish the morphology-based model. To estimate whether including more features regarding patient characteristics and cycle parameters improve the predicting power, we also establish models including 27 more features with either LASSO regression or XGbosst. The predicted number of blastocyst were associated with the observed number of the blastocyst and were used to predict the blastocyst transfer cancellation either in fresh or frozen cycles. Results Based on early cleavage and routine observed morphological parameters (cell number, fragmentation, and symmetry), the GEE model predicted blastocyst formation with an AUC of 0.779(95%CI: 0.77–0.787) and an accuracy of 74.7%(95%CI: 73.9%-75.5%) in the validation set. LASSO regression model and XGboost model based on the combination of cycle characteristics and embryo morphology yielded similar predicting power with AUCs of 0.78(95%CI: 0.771–0.789) and 0.754(95%CI: 0.745–0.763), respectively. For per-cycle blastocyst yield, the predicted number of blastocysts using morphological parameters alone strongly correlated with observed blastocyst number ( r  = 0.897, P  < 0.0001) and predicted blastocyst transfer cancel with an AUC of 0.926((95%CI: 0.911–0.94). Conclusion The data suggested that routine morphology observation remained a feasible tool to support an informed decision regarding the day of transfer. However, models based on the combination of cycle characteristics and embryo morphology do not increase the predicting power significantly.

Objective Bloodstream infection (BSI) is a significant cause of mortality in patients with hematologic malignancies(HMs), particularly amid rising antibiotic resistance. This study aimed to analyze pathogen distribution, drug-resistance patterns and develop a novel predictive model for 30-day mortality in HM patients with BSIs. Methods A retrospective analysis of 231 HM patients with positive blood cultures was conducted. Logistic regression identified risk factors for 30-day mortality. Th1/Th2 cytokines were collected at BSI onset, with LASSO regression and restricted cubic spline analysis used to refine predictors. Seven machine learning(ML) algorithm (XGBoost, Logistic Regression, LightGBM, RandomForest, AdaBoost, GBDT and GNB) were trained using 10-fold cross-validation and model performance was evaluated with the ROC, calibration plots, decision and learning curves and the Shapley Additive Explanations (SHAP) analysis. The predictive model was developed by integrating Th1/Th2 cytokines with clinical features, aiming to enhance the accuracy of 30-day mortality prediction. Results Among the cohort, acute myeloid leukemia (38%) was the most common HM, while gram negative bacteria (64%) were the predominant pathogens causing BSI. Age, polymicrobial BSI, IL-4, IL-6 and AST levels were significant predictors of 30-day mortality. The Logistic Regression model achieved AUCs of 0.802, 0.792, and 0.822 in training, validation, and test cohorts, respectively, with strong calibration and clinical benefit shown in decision curves. SHAP analysis highlighted IL-4 and IL-6 as key predictors. Conclusions This study introduces a novel ML-based model integrating Th1/Th2 cytokines and clinical features to predict 30-day mortality in HM patients with BSIs, demonstrating strong performance and clinical applicability.

PurposeTo compare the neonatal birthweight of singletons derived from ICSI cycles with fresh or frozen–thawed epididymal sperm in patients with obstructive azoospermia.MethodsA total of 436 singletons derived from ICSI cycles with fresh (n = 220) or frozen–thawed (n = 216) epididymal sperm in obstructive azoospermia evaluated from 2012 to 2018 in the retrospective study. Multivariate generalized linear model was used to analyze the association between epididymal sperm cryopreservation and neonatal birthweight.ResultsThe crude birthweight and z-score in neonates derived from frozen–thawed epididymal sperm were significantly lower than those from fresh epididymal sperm (3186.57 g vs 3303.61 g and − 0.18 vs 0.08, respectively), with a mean difference of 117.04 (95% CI 32.36–201.72) g and 0.25 (95% CI 0.06–0.45). Adjusted for confounders including parental age and BMI, maternal ovarian reserve, paternal FSH and T levels, peak E2 during OPU cycles, frozen–thawed embryo transfer, embryo development stage, gestational age, maternal parity and child gender, the multivariate model suggested that singletons conceived from ICSI with fresh epididymal sperm was on average 91.21 g heavier than those conceived from ICSI with frozen–thawed epdidiymal sperm (95% CI 12.72 to 166.7, P = 0.016).ConclusionCryopreservation of epididymal sperm may negatively affect birthweight.