Additive Manufacturing: A Comprehensive Review.

Additive manufacturing has revolutionized manufacturing across a spectrum of industries by enabling the production of complex geometries with unparalleled customization and reduced waste. Beginning as a rapid prototyping tool, additive manufacturing has matured into a comprehensive manufacturing solution, embracing a wide range of materials, such as polymers, metals, ceramics, and composites. This paper delves into the workflow of additive manufacturing, encompassing design, modeling, slicing, printing, and post-processing. Various additive manufacturing technologies are explored, including material extrusion, VAT polymerization, material jetting, binder jetting, selective laser sintering, selective laser melting, direct metal laser sintering, electron beam melting, multi-jet fusion, direct energy deposition, carbon fiber reinforced, laminated object manufacturing, and more, discussing their principles, advantages, disadvantages, material compatibilities, applications, and developing trends. Additionally, the future of additive manufacturing is projected, highlighting potential advancements in 3D bioprinting, 3D food printing, large-scale 3D printing, 4D printing, and AI-based additive manufacturing. This comprehensive survey aims to underscore the transformative impact of additive manufacturing on global manufacturing, emphasizing ongoing challenges and the promising horizon of innovations that could further elevate its role in the manufacturing revolution.

Occurrence, distribution, sources, and risk assessment of organophosphate esters in typical coastal aquaculture waters of China.

This study monitored 20 organophosphate esters (OPEs) in water and sediment from three typical mariculture bases (Yunxi Marine Ranching (YX), Hangzhou Bay (HZB), and Zhelin Bay (ZLB)) and Meiliang Bay (MLB) of Taihu Lake in China, focusing on the spatial distribution and sources of OPEs. Moreover, the occurrence and risk of OPEs in fishes from ZLB were evaluated. The ∑OPE concentrations in waters followed the order MLB (591 ng/L) > YX (102 ng/L) > HZB (70.0 ng/L) > ZLB (37.4 ng/L), with tri(1-chloro-2-propyl) phosphate (TCIPP), triethyl phosphate (TEP), and tri(2-chloroethyl) phosphate (TCEP) being the dominant OPEs. Significantly higher ∑OPE concentrations were found in sediment in MLB compared to the other three areas with similar levels. The decreasing concentrations of OPEs from nearshore to offshore areas in HZB and MLB indicated that terrigenous input is the main source of OPEs. The even distribution of OPEs in YX and ZLB combined with PCA analysis suggested ship traffic or aquaculture activities are also potential sources. The ∑OPE concentrations in fishes ranged from 0.551-2.45 ng/g wet weight, with TCIPP, tri-phenyl phosphate (TPHP), and TCEP being the main OPEs. Hydrophobicity was a key factor affecting the sediment-water distribution coefficients and the bioaccumulation factors of OPEs. The human exposure to OPEs through consumption of fishes from ZLB had a low health risk.

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict PET-determined ATN biomarker status using MRI and readily available diagnostic data. Materials and Methods MRI and PET data were retrospectively collected from the Alzheimer's Disease Imaging Initiative. PET scans were paired with MRI scans acquired within 30 days, from August 2005 to September 2020. Pairs were randomly split into subsets as follows: 70% for training, 10% for validation, and 20% for final testing. A bimodal Gaussian mixture model was used to threshold PET scans into positive and negative labels. MRI data were fed into a convolutional neural network to generate imaging features. These features were combined in a logistic regression model with patient demographics, APOE gene status, cognitive scores, hippocampal volumes, and clinical diagnoses to classify each ATN biomarker component as positive or negative. Area under the receiver operating characteristic curve (AUC) analysis was used for model evaluation. Feature importance was derived from model coefficients and gradients. Results There were 2099 amyloid (mean patient age, 75 years ± 10 [SD]; 1110 male), 557 tau (mean patient age, 75 years ± 7; 280 male), and 2768 FDG PET (mean patient age, 75 years ± 7; 1645 male) and MRI pairs. Model AUCs for the test set were as follows: amyloid, 0.79 (95% CI: 0.74, 0.83); tau, 0.73 (95% CI: 0.58, 0.86); and neurodegeneration, 0.86 (95% CI: 0.83, 0.89). Within the networks, high gradients were present in key temporal, parietal, frontal, and occipital cortical regions. Model coefficients for cognitive scores, hippocampal volumes, and APOE status were highest. Conclusion A deep learning algorithm predicted each component of PET-determined ATN status with acceptable to excellent efficacy using MRI and other available diagnostic data. © RSNA, 2023 Supplemental material is available for this article.

SuperMini-seg: An ultra lightweight network for COVID-19 lung infection segmentation from CT images.

The automatic segmentation of lung lesions from COVID-19 computed tomography (CT) images is helpful in establishing a quantitative model to diagnose and treat COVID-19. To this end, this study proposes a lightweight segmentation network called the SuperMini-Seg. We propose a new module called the transformer parallel convolution module (TPCB), which introduces both transformer and convolution operations in one module. SuperMini-seg adopts the structure of a double-branch parallel to downsample the image and designs a gated attention mechanism in the middle of the two parallel branches. At the same time, the attentive hierarchical spatial pyramid (AHSP) module and criss-cross attention module are adopted, and more than 100K parameters are present in the model. At the same time, the model is scalable, and the parameter quantity of SuperMini-seg-V2 reaches more than 70K. Compared with other advanced methods, the segmentation accuracy was almost reached the state-of-art method. The calculation efficiency was high, which is convenient for practical deployment.

Improved weed mapping in corn fields by combining UAV-based spectral, textural, structural, and thermal measurements.

BACKGROUND: Spatial-explicit weed information is critical for controlling weed infestation and reducing corn yield losses. The development of unmanned aerial vehicle (UAV)-based remote sensing presents an unprecedented opportunity for efficient, timely weed mapping. Spectral, textural, and structural measurements have been used for weed mapping, whereas thermal measurements-for example, canopy temperature (CT)-were seldom considered and used. In this study, we quantified the optimal combination of spectral, textural, structural, and CT measurements based on different machine-learning algorithms for weed mapping. RESULTS: CT improved weed-mapping accuracies as complementary information for spectral, textural, and structural features (up to 5% and 0.051 improvements in overall accuracy [OA] and Marco-F1, respectively). The fusion of textural, structural, and thermal features achieved the best performance in weed mapping (OA = 96.4%, Marco-F1 = 0.964), followed by the fusion of structural and thermal features (OA = 93.6%, Marco-F1 = 0.936). The Support Vector Machine-based model achieved the best performance in weed mapping, with 3.5% and 7.1% improvements in OA and 0.036 and 0.071 in Marco-F1 respectively, compared with the best models of Random Forest and Naïve Bayes Classifier. CONCLUSION: Thermal measurement can complement other types of remote-sensing measurements and improve the weed-mapping accuracy within the data-fusion framework. Importantly, integrating textural, structural, and thermal features achieved the best performance for weed mapping. Our study provides a novel method for weed mapping using UAV-based multisource remote sensing measurements, which is critical for ensuring crop production in precision agriculture. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Variations of the Level, Profile, and Distribution of PFAS around POSF Manufacturing Facilities in China: An Overlooked Source of PFCA.

The occurrence of per- and polyfluoroalkyl substances (PFAS) was investigated inside two manufacturing facilities in China. Levels, profiles, and spatial distribution of the detected PFAS were found to be distinctly site-specific and influenced by the area's historic function, production structure of the plant, downpour-induced accidental pollution, and variations in the adsorption and transport of compounds. Very high concentrations of PFAS [mainly C4 and C8 perfluoroalkyl sulfonic acids (PFSAs)] were found in topsoil and groundwater from both plants, with the highest values of 4.89 × 106 µg/kg dw and 1.10 × 104 µg/L, respectively. Elevated concentrations of perfluoroalkyl carboxylic acids (PFCAs) in this study were attributed to their unintentional formation during the electrochemical fluorination process, which might be an overlooked source of PFCA. PFAS generally showed decreasing trends from shallow layers to the bottom of the soil core and demonstrated some downward migrations at different soil depths with time, and C4-C8 PFAS presented a deeper seepage than their long-chain homologues. Total organic carbon appeared to be more important for PFAS sorption to the topsoil than to the soil core. Workers were at potential risk of exposure to perfluorooctanesulfonic acid via soil at production and storage related sites. This study provides a critical reference for the systematic control of PFAS pollution around manufacturing facilities and a proof for an overlooked source of PFCA.

Facile synthesis of mesoporous ZSM-5 aided by sonication and its application for VOCs capture.

Application of ultrasound power to the mother liquor is popular pretreatment for zeolite synthesis which offers a simple way of accelerating crystallization process and finetuning the properties of nanocrystalline zeolites. In this work, sonication-aided synthesis of mesoporous ZSM-5 at low temperature and ambient pressure was systematically studied, in an attempt to reach efficient and benign synthesis of zeolites with hierarchical pore structure, which has wide applications as catalysts and sorbents. The effects of sonication duration, power density, sonication temperature and seeding on the crystallization of ZSM-5 were investigated. The obtained samples were characterized by XRD, SEM, BET and VOCs capture. High quality mesoporous ZSM-5 can be obtained by a facile 5 d synthesis at 363 K, much faster than conventional hydrothermal synthesis. The reduced synthesis time was mainly attributed to the enhanced crystallization kinetics caused by the fragmentation of seeds and nuclei, while sonication radiation had little impact on the nucleation process. Compared with control sample, mesoporous ZSM-5 prepared by sonochemical method had higher surface area and mesoporosity which demonstrated improved adsorption performance for the capture of isopropanol.

Eukaryotic Translation Initiation Factor 5A Independently Predicts Poor Prognosis of Cholangiocarcinoma Patients and Regulates the Ferroptosis and Mitochondrial Apoptosis.

Cholangiocarcinoma (CCA) is a hepatobiliary carcinoma characterized by the differentiation of bile duct cells, and the patients with CCA often have a poor prognosis. Eukaryotic translation initiation factor 5A (eIF5A) is reported to have multiple biological activities. Targeted activation of ferroptosis may be a therapeutic strategy for cancer. Nevertheless, the effects of eIF5A and ferroptosis on CCA are still elucidated. Our study explored the effects of eIF5A in CCA, and the mechanisms also are studied. In this paper, TCGA database analysis suggested that eIF5A was upregulated in CCA, and high expression of eIF5A might predict a poor prognosis. Moreover, FANCD2, SLC7A11, and HSPB1 were significantly overexpressed in CCA. The results indicated that eIF5A was overexpressed in CCA tissues and cells. Further experiments demonstrated that eIF5A silencing decreased CCA cell activity and enhanced ferroptosis and mitochondrial apoptosis. In addition, upregulation of eIF5A showed the opposite effect on CCA cells compared with downregulation of eIF5A. Finally, the silencing of eIF5A could restrain the growth of xenografted tumors and promote ferroptosis. Overall, eIF5A enlarged CCA cell activity and attenuated ferroptosis and mitochondrial apoptosis. The results suggested that assessment of eIF5A might provide help for the diagnosis and treatment of CCA.

Effect of thermal activation and particle size on cementitious activity of bauxite tailings.

To explore the influence of thermal activation and particle size on cementitious activity of bauxite tailings, in this study, the raw bauxite tailings were classified into coarse bauxite tailings (CBT) and fine bauxite tailings (FBT) by a powder separator, and then the effect of activation temperature on cementitious activity of CBT and FBT was investigated. XRD, TG, and FTIR were used to study the phase and structure changes of CBT and FBT during the process of thermal activation. The results show that the main mineral phases of CBT and FBT, diaspore and kaolinite, begin to remove a large amount of hydroxyl groups at 500 ℃ and convert into corundum and metakaolin, respectively. The diaspore and kaolinite have completely removed the hydroxyl groups at 600 °C and 700 °C, respectively. With the increase of activation temperature, the particle size of CBT and FBT are first gradually decreased, when the activation temperature exceeds 700 ℃, as the activation temperature continues to arise, the particle size of CBT and FBT are gradually increased due to the occurrence of sintering. The activity index of bauxite tailings is increased with the increase of fineness, and the optimum activation temperature of CBT and FBT is 700 °C. When the activation temperature is the same, FBT has higher pozzolanic activity than CBT.

Tissue distribution of sodium p-perfluorous nonenoxybenzene sulfonate (OBS) in mice via oral exposure.

Environmental risks caused by emerging per- and polyfluoroalkyl substances (PFASs) have attracted increasing attention. As an important substitute for perfluorooctane sulfonate (PFOS), sodium p-perfluorous nonenoxybenzene sulfonate (OBS) is widely used as a firefighting foam additive and oil recovery agent in China. This study reported the tissue distribution of OBS in KM mice that were administered a dose of OBS at 10 µg/day via daily oral gavage for 7, 14, or 28 days. During exposure, gender-based differences were observed in body weight changes and tissue distribution of OBS. Liver exhibited the highest concentrations (males: 12.57 ± 1.80 µg/g; females: 11.80 ± 5.32 µg/g) and tissue/blood ratios and contributed more than 50% to the whole-body burden of OBS in both male and female mice, showing its ability to enrich PFASs. Furthermore, there were certain differences in the distribution characteristics of the three OBS isomers. Based on its bioaccumulation potential and widespread use, further studies are required on the human exposure risks of OBS.

Using a multidisciplinary team for the staged management and optimally minimally invasive treatment of severe acute pancreatitis.

Severe acute pancreatitis (SAP) is a common critical disease with a high mortality rate that involves a complex, rapid change in condition and multiple organ systems. Therefore, a multidisciplinary team (MDT), including staff from the emergency department, intensive care unit, pancreatic surgery, gastroenterology , and imaging, is necessary for the early diagnosis, evaluation, and treatment of patients with SAP. This involves managing the systemic inflammatory response and maintaining organ function in the early stage and managing systemic infection and treatment of peripancreatic complications in the middle-to-late stages. The MDT should be led by departments corresponding to the clinical characteristics of each stage, and those departments should be responsible for the coordination and implementation of treatment by other relevant departments. In the late stage, pancreatic surgery and gastroenterology are the main departments that should manage peripancreatic complications. In line with the principle of minimally invasive treatment, the timely and reasonable selection of endoscopic or minimally invasive surgical debridement can achieve good therapeutic outcomes. Open surgery is also an effective method for treating an intractable massive hemorrhage in the abdominal cavity or necrotic cavity, intractable abdominal compartment syndrome, visceral perforation, and fistulae.

Establishing NDRE dynamic models of winter wheat under multi-nitrogen rates based on a field spectral sensor.

Field spectral sensors provide real-time, reliable, quantitative monitoring of crop growth. Fitting the continuous growth in the entire growing period from the measurements of limited frequency is helpful to the comparative analysis of interannual growth and fertilizer management in the field. To exploit this capacity, our work presents a model that uses the normalized difference red edge (NDRE) index derived from the field spectral sensor for real-time monitoring of the canopy growth of winter wheat in the whole growing period. We developed this model from experiments in three counties in Hebei province, China, where we obtained the near-infrared and red edge reflectance, grain yield, and canopy parameters for eight growth stages and for various nitrogen (N) rates. Given the correlation between effective accumulated temperature and crop growth, we used the growing degree-days as an adjustment parameter to develop models for dynamic monitoring of the NDRE of the winter wheat canopy during the entire growing period. The results show that high determination coefficients (R2=0.89 to 0.96) are obtained from all models based on relative NDRE and effective accumulative temperature (independent of N fertilization rates). The model based on the rational function is the best of all models tested, with the accuracy for normal and high N fertilization rates being slightly greater than that for low N fertilization rates. Therefore, a relative-NDRE model with the accumulative growing degree-days since sowing could allow monitoring canopy NDRE of winter wheat at any time, which could be helpful for overcoming the shortage of incomparable growth derived from the differences of sensing date, sowing date, and fertilizer, etc.

V-shaped bis-coumarin based fluorescent probe for detecting palladium in natural waters.

A catalytic fluorescent probe based on V-shaped bis-coumarin has been designed and synthesized for detection of palladium (Pd). The detection mechanism of the probe is based on palladium-catalyzed Tsuji‒Trost reaction process and photoinduced electron transfer (PET), which can distinguish and detect palladium (0, +2/+4) in different valence states under different conditions. The fluorescence intensity of the probe enhances after adding the palladium in about 10 min at room temperature. The limit of detection (LOD) of the probe is as low as 40.0 nM (4.2 ng/g), and it has good selectivity and high sensitivity. Apart from that, it has been successfully applied to detection of palladium in environmental waters.

Enhancing Expression of 3-Ketosteroid-9α-Hydroxylase Oxygenase, an Enzyme with Broad Substrate Range and High Hydroxylation Ability, in Mycobacterium sp. LY-1.

3-Ketosteroid-9α-hydroxylase (KSH) consists of two protein systems, KshA and KshB, and is a key enzyme in microbial degradation pathway of natural sterols. 9α-Hydroxy-4-androstene-3,17-dione (9α-OH-AD) is a valuable steroid pharmaceutical intermediate. The expression of a 3-ketosteroid-9α-hydroxylase oxygenase (KshA1) with a broad substrate range and high hydroxylation ability was enhanced in Mycobacterium sp. LY-1 to improve the yield of 9α-OH-AD. Through whole-genome sequence mining and homologous comparison, the putative genes (kshA1 and kshB) in wild strain LY-1 were firstly identified. Then they were heterogeneously co-expressed in Escherichia coli BL21. The transformation results of recombinant BL21-KshA1/B demonstrated KshA1/B had high hydroxylation ability to AD. Moreover, substrate preference analysis suggested that KshA1LY-1 had a broad substrate range. After enhancing expression of kshA1 and kshB in the strain LY-1, the maximum productivity of 9α-OH-AD in recombinant LY-1-KshA1/B reached 0.064 g/L/h in a 5-L stirred fermenter.

Monitoring Maize Lodging Grades via Unmanned Aerial Vehicle Multispectral Image.

Lodging is one of the main factors affecting the quality and yield of crops. Timely and accurate determination of crop lodging grade is of great significance for the quantitative and objective evaluation of yield losses. The purpose of this study was to analyze the monitoring ability of a multispectral image obtained by an unmanned aerial vehicle (UAV) for determination of the maize lodging grade. A multispectral Parrot Sequoia camera is specially designed for agricultural applications and provides new information that is useful in agricultural decision-making. Indeed, a near-infrared image which cannot be seen with the naked eye can be used to make a highly precise diagnosis of the vegetation condition. The images obtained constitute a highly effective tool for analyzing plant health. Maize samples with different lodging grades were obtained by visual interpretation, and the spectral reflectance, texture feature parameters, and vegetation indices of the training samples were extracted. Different feature transformations were performed, texture features and vegetation indices were combined, and various feature images were classified by maximum likelihood classification (MLC) to extract four lodging grades. Classification accuracy was evaluated using a confusion matrix based on the verification samples, and the features suitable for monitoring the maize lodging grade were screened. The results showed that compared with a multispectral image, the principal components, texture features, and combination of texture features and vegetation indices were improved by varying degrees. The overall accuracy of the combination of texture features and vegetation indices is 86.61%, and the Kappa coefficient is 0.8327, which is higher than that of other features. Therefore, the classification result based on the feature combinations of the UAV multispectral image is useful for monitoring of maize lodging grades.

SPAG5 promotes hepatocellular carcinoma progression by downregulating SCARA5 through modifying ß-catenin degradation.

BACKGROUND: The sperm-associated antigen 5 (SPAG5) plays a key role in controlling various cellular phenomena, including cell cycle progression and proliferation. However, the role of SPAG5 in hepatocellular carcinoma (HCC) remains unknown. METHODS: This study investigated the function and clinical significance of SPAG5 protein expression in hepatocellular carcinoma. We analyzed SPAG5 expression in surgical specimens from 136 HCC patients. The correlation between the clinical characteristics and prognosis was also determined. Furthermore, the SPAG5 was overexpressed in HCC cell and silenced with shRNA in HCC cells. Moreover, cell proliferation and apoptosis were measured using Edu assay and flow cytometry and a molecular mechanism of SPAG5 promotes HCC progression was explored. RESULTS: Herein, our study showed that upregulation of SPAG5 was detected frequently in primary HCC tissues, and was associated with significantly worse survival among the HCC patients. Multivariate analyses revealed that high SPAG5 expression was an independent predictive marker for the poor prognosis of HCC. SPAG5 silence effectively abolished the proliferation abilities of SPAG5 in vivo and in vitro, while induced apoptosis in HCC cells. Furthermore, our results indicate that SPAG5 promoted cell progression by decreasing SCARA5 expression, which has been reported to control the progression of HCC, and our data demonstrated that SCARA5 is crucial for SPAG5-mediated HCC cell progression in vitro and in vivo. Moreover, we found that the expression of SPAG5 and SCARA5 are inversely correlated in HCC tissues. In addition, we demonstrated that SPAG5 promoted progression in HCC via downregulating SCARA5 depended on the ß-catenin/TCF4 signaling pathway. Interestingly, the underlying mechanism is which SPAG5 regulates SCARA5 expression by modulating ß-catenin degradation. CONCLUSIONS: Taken together, our data provide a novel evidence for the biological and clinical significance of SPAG5 as a potential biomarker, and we demonstrate that SPAG5-ß-catenin-SCARA5 might be a novel pathway involved in HCC progression.