Search

Sugarcane is an important raw material for sugar and chemical production. However, in recent years, various sugarcane diseases have emerged, severely impacting the national economy. To address the issue of identifying diseases in sugarcane leaf sections, this paper proposes the SE-VIT hybrid network. Unlike traditional methods that directly use models for classification, this paper compares threshold, K-means, and support vector machine (SVM) algorithms for extracting leaf lesions from images. Due to SVM's ability to accurately segment these lesions, it is ultimately selected for the task. The paper introduces the SE attention module into ResNet-18 (CNN), enhancing the learning of inter-channel weights. After the pooling layer, multi-head self-attention (MHSA) is incorporated. Finally, with the inclusion of 2D relative positional encoding, the accuracy is improved by 5.1%, precision by 3.23%, and recall by 5.17%. The SE-VIT hybrid network model achieves an accuracy of 97.26% on the PlantVillage dataset. Additionally, when compared to four existing classical neural network models, SE-VIT demonstrates significantly higher accuracy and precision, reaching 89.57% accuracy. Therefore, the method proposed in this paper can provide technical support for intelligent management of sugarcane plantations and offer insights for addressing plant diseases with limited datasets. [ABSTRACT FROM AUTHOR]

Bacteria-associated late infection of the orthopedic devices would further lead to the failure of the implantation. However, present ordinary antimicrobial strategies usually deal with early infection but fail to combat the late infection of the implants due to the burst release of the antibiotics. Thus, to fabricate long-term antimicrobial (early antibacterial, late antibacterial) orthopedic implants is essential to address this issue. Herein, we developed a sophisticated MAO-I2-PCLx coating system incorporating an underlying iodine layer and an upper layer of polycaprolactone (PCL)-controlled coating, which could effectively eradicate the late bacterial infection throughout the implantation. Firstly, micro-arc oxidation was used to form a microarray tubular structure on the surface of the implants, laying the foundation for iodine loading and PCL bonding. Secondly, electrophoresis was applied to load iodine in the tubular structure as an efficient bactericidal agent. Finally, the surface-bonded PCL coating acts as a controller to regulate the release of iodine. The hybrid coatings displayed great stability and control release capacity. Excellent antibacterial ability was validated at 30 days post-implantation via in vitro experiments and in vivo rat osteomyelitis model. Expectedly, it can become a promising bench-to-bedside strategy for current infection challenges in the orthopedic field. [ABSTRACT FROM AUTHOR]

Summary: Low‐Bit Neural Network (LBNN) is a promising technique to enrich intelligent applications running on sustainable Cyber‐Physical Systems (CPS). Although LBNN has the advantages of low memory usage, fast inference and low power consumption, Low‐bit design requires additional computation units and may cause large accuracy drop. In this paper, we approach to design Field Programmable Gate Array (FPGA)‐based LBNN accelerator to support sustainable CPS. First, we propose a method to quantize the neural networks into 2‐bit weights, 8‐bit activations and 8‐bit biases with few accuracy loss. The mapping function is presented to approximate discrete space of weights gradually and quantize the activations and biases through the improved straight‐through estimator. Second, we design the bitwise FPGA‐based accelerator to speed up the LBNN. Different from traditional accelerating techniques (mainly focused on convolution layer), the dataflows of fully connected layer, pooling layer and convolution layer are considered to accelerate all layers of neural networks. The 2×8 bitwise multiplier implemented by AND/XOR operation is devised to replace 32×32‐bit multiplication unit, which can bring faster inference and lower power consumption. We conduct extensive experiments on benchmarks of MNIST, CIFAR‐10, CIFAR‐100 and ImageNet to evaluate the efficiency of our approach. The LBNN obtained by our quantization method can save 93.75% memory with 2.26% accuracy loss on average compared with original networks. The FPGA‐based accelerator achieves a peak performance of 427.71 GOPS under 100 MHz working frequency, which outperforms previous approaches significantly. [ABSTRACT FROM AUTHOR]

1. Breast cancer is one of the most common malignancies in women worldwide. Metabolomics has been shown to be a promising strategy to elucidate the underlying pathogenesis of cancer and identify new targets for cancer diagnosis and therapy. Valproic acid (VPA), a histone deacetylase inhibitor, is a potential new drug in tumor therapy. This work used metabolomics to examine the effect of VPA on metabolism in breast cancer cells. 2. Based on UPLC-MS/MS, we identified 3137 differential metabolites in human breast cancer MCF-7 cells and 2472 differential metabolites in human breast cancer MDA-MB-231 cells after VPA treatment. 3. We selected 63 differential metabolites from MCF-7 samples and 61 differential metabolites from MDA-MB-231 cells with the more conspicuous changing trend. Furfural was up-regulated after VPA treatment in both cell lines. In both samples, VPA exerted an effect on the beta-alanine metabolism pathway and the taurine and hypotaurine metabolism pathway. 4. This study identified the effect of VPA on metabolites and metabolic pathways in breast cancer cells, and these findings may contribute to the identification of new targets for breast cancer treatment. [ABSTRACT FROM AUTHOR]

Background : The early progression continuum of Alzheimer's disease (AD) has been considered to advance through subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI). Altered functional connectivity (FC) in the default mode network (DMN) is regarded as a hallmark of AD. Furthermore, the DMN can be divided into two subnetworks, the anterior and posterior subnetworks. However, little is known about distinct disruptive patterns in the subsystems of the DMN across the preclinical AD spectrum. This study investigated the connectivity patterns of anterior DMN (aDMN) and posterior DMN (pDMN) across the preclinical AD spectrum. Methods : Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in the DMN subnetworks in 20 healthy controls (HC), eight SCD, 11 naMCI, and 28 aMCI patients. Moreover, a correlation analysis was used to examine associations between the altered connectivity of the DMN subnetworks and the neurocognitive performance. Results : Compared to the HC, SCD patients showed increased FC in the bilateral superior frontal gyrus (SFG), naMCI patients showed increased FC in the left inferior parietal lobule (IPL), and aMCI patients showed increased FC in the bilateral IPL in the aDMN; while SCD patients showed decreased FC in the precuneus, naMCI patients showed increased FC in the left middle temporal gyrus (MTG), and aMCI patients also showed increased FC in the right middle frontal gyrus (MFG) in the pDMN. Notably, the FC between the ventromedial prefrontal cortex (vmPFC) and the left MFG and the IPL in the aDMN was associated with episodic memory in the SCD and aMCI groups. Interestingly, the FC between the posterior cingulated cortex (PCC) and several regions in the pDMN was associated with other cognitive functions in the SCD and naMCI groups. Conclusions : This study demonstrates that the three preclinical stages of AD exhibit distinct FC alternations in the DMN subnetworks. Furthermore, the patient group data showed that the altered FC involves cognitive function. These findings can provide novel insights for tailored clinical intervention across the preclinical AD spectrum. [ABSTRACT FROM AUTHOR]

This paper investigates the bacterial microbiota in tilapia fillets under cold (4 °C), iced (0 °C), and superchilled (–3 °C) storage conditions. At 4 °C, at least seven species/strains of Pseudomonas were detected in the fillets, five of which were dominant either at a certain stage or throughout the entire storage period. Shewanella was less dominant than Pseudomonas at 4 °C, while Serratia became dominant after 6 days storage at 4 °C. The microbiota in fillets stored at 0 and –3 °C were very similar and rarely changed during storage, yet differed greatly from the microbiota at 4 °C. Only two Pseudomonas species/strains grew at 0 and –3 °C, one of which was the most dominant. A Vibrionimonas sp. not found at 4 °C was found to be the second most dominant species at 0 and –3 °C. Shewanella and Psychrobacter were also present at 0 and –3 °C but were the minor genera. The most dominant strains at –3, 0, and 4 °C were separately isolated and subjected to full length 16S rDNA sequencing, which demonstrated that they were identical and were Pseudomonas fluorescens. The changes of the total bacterial count and TVBN value of the fillets inoculated with the isolated P. fluorescens were very similar to those of fillets with natural microbiota. This implies that P. fluorescens is the most important spoiler of tilapia fillets at –3, 0, or 4 °C. Practical Application: This research shows that fewer species of bacteria survive at 0 and –3 °C than those at 4 °C, while among these bacteria, the most important spoiler is P. fluorescens. This may provide some clues to extend the shelf life of tilapia fillets by taking some inhibitory measures targeted at P. fluorescens in the future. [ABSTRACT FROM AUTHOR]

Abstract Background: Hepatitis B virus X-interacting protein (HBXIP) is associated with a variety of tumors. The purpose of this study was to investigate the clinicopathological significance of HBXIP expression in pancreatic ductal adenocarcinoma (PDAC) and to explore its potential as a biomarker for PDAC. Methods: Immunohistochemical (IHC) staining was performed on 126 PDAC tissues, 36 paraneoplastic tissues and 22 normal pancreatic tissues. The relationship between high levels of HBXIP expression and pathological features of PDAC patients was evaluated by chi-squared values. Results:The positive rate of HBXIP protein in PDAC tissues was 85.7% (108/126), which was significantly higher than that of adjacent pancreatic tissue (41.7%, 15/36) and normal pancreas (18.2%, 4/22). In addition, strong positive expression of HBXIP was associated with tumor size, positive lymph node metastasis, clinical stage and 80-month overall survival. Patient's age, gender, degree of differentiation, Ki-67 expression index, and calcification were, however, not associated with high levels of HBXIP expression. Conclusions:We present association between HBXIP expression and the pathological features of patients with PDAC. [ABSTRACT FROM AUTHOR]

The cleanness of steel has always been a big problem for secondary refining. In this work, a new method, which is coupled with slot and porous plugs, is proposed to improve the cleanness in steel. Water experiments and numerical simulations were performed to study this effect. Results revealed that when using slot-porous plugs, the flow field was obviously asymmetrical, and the circulation flow was pushed towards the porous side. Then, the removement of inclusions was increased to about 22.7% percent, comparing with traditional two-slot bottom stirring and reducing the dead zone area near the bottom of the ladle; however, the mixing time delay was 16%, comparing with traditional plugs. Then, in order to explain the reason for these phenomena, we established a mathematical model through large eddy simulation and discrete particle modeling (DPM). Results shows that the asymmetry flow field awoke the recirculation flow downwards after using slot-porous plugs, which would homogenize the flow at the bottom, promoting floating in steel. What is more, the velocity near the free surface was lowered; therefore, it could also stabilize the surface velocity as well, which is also beneficial for removing inclusions as well. [ABSTRACT FROM AUTHOR]

Considering solidification, a large eddy simulation (LES) model of two-phase flow was established to simulate the thermal–magnetic flow coupled fields inside a jumbo bloom. The magnetic field was calculated based on Maxwell's equations, constitutive equations, and Ohm's law. An enthalpy–porosity technique was used to model the solidification of the steel. The movement of the free surface was described by the volume of fluid (VOF) approach. With the effect of electromagnetic stirring (MEMS), the vortices in the bloom tended to be strip-like; large vortices mostly appeared in the injection zone, while small ones were found near the surface of the bloom. It is newly found that even though the submerged entry nozzle (SEN) is asymmetrical about the bloom, a biased flow can also be found under the effect of MEMS. The reason for this phenomenon is because the magnetic force is asymmetrical and transient. A high frequency will reduce the period of biased flow; however, the frequency should not be too high because it could also intensify meniscus fluctuations and thus entrap slag droplets in the mold. The velocity near the solidification front can also be increased with a higher frequency. [ABSTRACT FROM AUTHOR]

With the development of clean steel technology, the control of non-metallic inclusions in steel is of increasing importance. Magnesium–calcium treatment can effectively balance the castability of molten steel and the control on inclusion size, which is an inclusion modification approach with application prospect. In view of this, how three addition methods (i.e., adding Mg before Ca, adding Mg after Ca, and adding Mg together with Ca) influenced the modification effect of inclusions in liquid iron was experimentally studied, and how these inclusions evolved with time was discussed in this paper. The results demonstrated that despite the sharp difference in their inclusion evolution, composite inclusions with a magnesium aluminate spinel (MAS) core and an outer CaO–Al2O3–MgO layer were formed by all the three addition methods, with the average inclusion size of 1–2 μm. Furthermore, thermodynamic calculation was adopted to reveal the transformation relationship between MAS and calcium aluminate in each of the three addition methods, and clarify the formation and disappearance mechanisms of the intermediate product CaS in the process of Mg–Ca treatment. The thermodynamic calculation results agreed well with the experiment data. [ABSTRACT FROM AUTHOR]

Hepatitis B X-interacting protein (HBXIP) is highly expressed in many cancers, but the correlation between the expression of HBXIP and the clinical significance and underlying molecular mechanisms in colorectal cancer (CRC) is still unclear. We selected 186 specimens from CRC patients for analyzing the relationship between the expression of HBXIP and the clinical-pathological features by immunohistochemistry. Migration and invasion experiments were performed to examine the effect of HBXIP on CRC cell metastasis. Besides, we also explored the possible molecular mechanism of HBXIP regulation of CRC cell metastasis by Western blot. Our data indicated that the HBXIP was overexpressed in CRC tissues. High HBXIP expression was correlated with metastasis and shorter survival times in patients with CRC and served as an independent factor for poor prognosis. Moreover, HBXIP promotes CRC metastasis by enhancing the epithelial-mesenchymal transition (EMT) process. Our findings provide the first evidence that HBXIP induces EMT to promote metastasis and predicts the poor prognosis of CRC. Therefore, HBXIP may become a new target for CRC treatment. • We found HBXIP was overexpressed in colorectal cancer (CRC) tissues. • High HBXIP expression was correlated with metastasis. • High HBXIP expression was correlated with shorter survival times in patients with CRC. • HBXIP promotes CRC metastasis by enhancing the epithelial-mesenchymal transition (EMT) process. • Therefore, HBXIP may become a new target for CRC treatment. [ABSTRACT FROM AUTHOR]