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Ship detection from infrared images occupies an important role in maritime search and tracking applications. When compared with methods to process daytime RGB photos, processing infrared images has challenges due to the reduced signal-to-clutter ratio (SCR), indistinct outlines, and inadequate spatial resolutions. In addition, the detection of small targets remains challenging owing to their size variations and unclear edges, leading to missed detections and low accuracy. This work suggests the use of infrared-ship YOLO (IS-YOLO), a model to recognize small ships in infrared images. The proposed technique, based on YOLOv7, enhances the ability to detect infrared objects in heterogeneous scenarios. First, we improve the ability of the YOLOv7 backbone to extract features by introducing a new structure for the efficient layer aggregation network (ELAN) with a two convolutions and GhostConv module. Secondly, the max pooling pyramid-ELAN is introduced to integrate multi-scale information. Furthermore, we capture an infrared small ship dataset using the FLIR T620 camera. The experimental results demonstrate that the IS-YOLO model had the best performance in small ship detection from infrared images compared to several state-of-the-art models, as shown by optimal metrics that include average precision (AP@.5, AP@.5:.95, the number of parameters, and the model size): AP@.5, 88.9%; AP@.5:.95, 38.2%; 32.8 M; and 63.1 Mb, respectively. The proposed approach can serve as a valuable reference for the development of small-ship detection methods with infrared images. [ABSTRACT FROM AUTHOR]

Let Y be a prequantization bundle over a closed spherically monotone symplectic manifold Σ . Adapting an idea due to Diogo and Lisi, we study a split version of Rabinowitz Floer homology for Y in the following two settings. First, Σ is a symplectic hyperplane section of a closed symplectic manifold X satisfying a certain monotonicity condition; in this case, X \ Σ is a Liouville filling of Y. Second, the minimal Chern number of Σ is greater than one, which is the case where the Rabinowitz Floer homology of the symplectization R × Y is defined. In both cases, we construct a Gysin-type exact sequence connecting the Rabinowitz Floer homology of X \ Σ or R × Y and the quantum homology of Σ . As applications, we discuss the invertibility of a symplectic hyperplane section class in quantum homology, the isotopy problem for fibered Dehn twists, the orderability problem for prequantization bundles, and the existence of translated points. We also provide computational results based on the exact sequence that we construct. [ABSTRACT FROM AUTHOR]

The construction industry substantially contributes to the economic growth of a country. However, it records a large number of workplace injuries and fatalities annually due to its hesitant adoption of automated safety monitoring systems. To address this critical concern, this study presents a real-time monitoring approach that uses the Internet of Things and ensemble learning. This study leverages wearable sensor technology, such as photoplethysmography and electroencephalography sensors, to continuously track the physiological parameters of construction workers. The sensor data is processed using an ensemble learning approach called the ChronoEnsemble Fatigue Analysis System (CEFAS), comprising deep autoregressive and temporal fusion transformer models, to accurately predict potential physical and mental fatigue. Comprehensive evaluation metrics, including mean square error, mean absolute scaled error, and symmetric mean absolute percentage error, demonstrated the superior prediction accuracy and reliability of the proposed model compared to standalone models. The ensemble learning model exhibited remarkable precision in predicting physical and mental fatigue, as evidenced by the mean square errors of 0.0008 and 0.0033, respectively. The proposed model promptly recognizes potential hazards and irregularities, considerably enhancing worker safety and reducing on-site risks. [ABSTRACT FROM AUTHOR]

In the inherently hazardous construction industry, where injuries are frequent, the unsafe operation of heavy construction machinery significantly contributes to the injury and accident rates. To reduce these risks, this study introduces a novel framework for detecting and classifying these unsafe operations for five types of construction machinery. Utilizing a cascade learning architecture, the approach employs a Super-Resolution Generative Adversarial Network (SRGAN), Real-Time Detection Transformers (RT-DETR), self-DIstillation with NO labels (DINOv2), and Dilated Neighborhood Attention Transformer (DiNAT) models. The study focuses on enhancing the detection and classification of unsafe operations in construction machinery through upscaling low-resolution surveillance footage and creating detailed high-resolution inputs for the RT-DETR model. This enhancement, by leveraging temporal information, significantly improves object detection and classification accuracy. The performance of the cascaded pipeline yielded an average detection and first-level classification precision of 96%, a second-level classification accuracy of 98.83%, and a third-level classification accuracy of 98.25%, among other metrics. The cascaded integration of these models presents a well-rounded solution for near-real-time surveillance in dynamic construction environments, advancing surveillance technologies and significantly contributing to safety management within the industry. [ABSTRACT FROM AUTHOR]

Summary: Teriparatide and denosumab, anti-osteoporosis medications with different mechanisms, have been widely used in the patients with osteoporotic vertebral fracture (OVF) considered as advanced osteoporosis. Teriparatide has been shown to enhance bone formation and fracture healing in OVF, but there are still no sufficient evidences discussing about the role of denosumab in newly developed OVF. In this study, we found the similar radiological deformation and functional outcomes of conservative treatment with teriparatide and denosumab in thoracolumbar (TL) OVF, and teriparatide showed a more frequent incidence of fracture union with paravertebral bone bridge formation compared to denosumab. Introduction: Teriparatide and denosumab have been widely used to treat advanced osteoporosis and prevent subsequent fractures in patients with OVCF. Unlike teriparatide, which is considered to be effective in fracture healing, there is still no clear role and evidence for the effect of denosumab in acute OVCF. This study compared the radiological and functional outcomes of conservative treatment with teriparatide and denosumab in TL-OVF. Methods: This retrospective study enrolled 78 women with mean age of 74.69 ± 7.66 (60–92) years diagnosed as a TL-OVF with no neurological deficits. All patients were treated conservatively with teriparatide (34 of group T, once-daily 20 μg) or denosumab (44 of group D, once-6 months 60 mg) for 6 months. We evaluated the radiological deformation (kyphotic angle, segmental vertebral kyphotic angle, and compression ratio) and the incidence of fracture union with paravertebral bone bridge formation (FUPB) and functional outcomes using the visual analog scale (VAS) and Oswestry Disability Index (ODI) at 0, 3, and 6 months. Results: In the radiological deformation and functional outcomes, there were no significant differences at 0, 3, and 6 months between the two groups (P > 0.05). However, the incidence of FUPB at 6 months was higher in group T (20/34, 58.8%) compared to group D (11/44, 25.0%) (P = 0.004), and teriparatide was the most statistically significant factor for achieving FUPB (OR 4.486, P = 0.012) in multivariable logistic analysis. Conclusions: Teriparatide and denosumab, despite of their different pharmacological mechanisms, showed similar radiological deformation and functional outcomes in the conservative treatment of TL-OVF. However, teriparatide showed a significantly higher incidence of fracture union with paravertebral bone bridge formation. [ABSTRACT FROM AUTHOR]

This paper is concerned with experiments and finite element (FE) simulations using the coupled Eulerian‒Lagrangian (CEL) method for multi-material joining by the flow drill screw (FDS) process. The FDS joining experiments involved various combinations of aluminum alloys (Al6061-T6 2.0t and Al6063-T6 2.0t), and steel (SPRC45E 1.6t) sheets. During the FDS joining, thermocouples and a thermal imaging camera, FLIR, were used to measure the elevated temperature near the joint. Cross-sections of the multi-material joint specimens were prepared to check the joining quality and the deformed shape of the materials. To consider the complexity of the joining process and convergence issue of numerical simulation, the FE modeling approach for the FDS joining was constructed based on the CEL method using the ABAQUS/Explicit, considering the strain rate and thermal softening dependent strain hardening of each material. From the comparison of experimental and FE simulation results, the reliability of the FE modeling was validated, revealing the predictability of the deformed shape was 90% or more, especially in terms of the bushing length. Furthermore, it was confirmed that the proposed modeling approach can accurately describe the temperature history and peak values during rapid joining. [ABSTRACT FROM AUTHOR]

SRAM-based physically unclonable function (PUF) is an attractive security primitive for cryptographic protocol and security architecture because SRAM itself is one of the most widely used embedded memories. In terms of robustness, however, there is a weakness for SRAM PUF owing to a bit error; thus, a method must be explored to reduce this error. In this work, a novel hardware chip to characterize cell-to-cell entropy is demonstrated for robust SRAM based PUF by implementation of a screening test to filter out poor cells. We design a chip with a power controller, circuits for error correction coding, a SRAM array and central processing unit. Then it was fabricated by a foundry service. We also propose a procedure to suppress the bit error by use of a screening test, which is based on SRAM cells possessing their own entropy. Through the screening test, the bit error rate (BER) is reduced to below 10 - 6 , which is much smaller than the BER of 0.05 in previous reports, i.e., the robustness is notably improved. Moreover, this robustness was evaluated in terms of an error correction code (ECC) failure rate and temperature after the screening test. SRAM-based PUF with enhanced robustness can contribute to implementing a security protocol and architecture for chip authentication. [ABSTRACT FROM AUTHOR]

Algorithms for intelligent drone flights based on sensor fusion are usually implemented using conventional digital computing platforms. However, alternative energy-efficient computing platforms are required for robust flight control in a variety of environments to reduce the burden on both the battery and computing power. In this study, we demonstrated an analog–digital hybrid computing platform based on SnS2 memtransistors for low-power sensor fusion in drones. The analog Kalman filter circuit with memtransistors facilitates noise removal to accurately estimate the rotation of the drone by combining sensing data from the gyroscope and accelerometer. We experimentally verified that the power consumption of our hybrid computing-based Kalman filter is only 1/4th of that of the traditional software-based Kalman filter. Analog–digital hybrid computing based on SnS2 memtransistors is demonstrated for lowpower sensor fusion in drones, where a drone with hybrid computing performs sensor fusion with higher energy efficiency than that with only a digital processor. [ABSTRACT FROM AUTHOR]

Background: Laparoscopic pancreaticoduodenectomy (LPD) is technically demanding and there is much controversy about its safety. We evaluated the learning curve for pure LPD based on the clinical outcomes of consecutive patients treated by a single surgeon.Methods: We reviewed the medical records of 119 consecutive patients who underwent LPD by a single surgeon between June 2013 and August 2018. The learning curve was evaluated using the cumulative summation (CUSUM) and risk-adjusted CUSUM (RA-CUSUM) methods. Perioperative outcomes were compared among the learning curve phases.Results: CUSUM analysis of the operation time showed that the operation time improved after the 47th case. RA-CUSUM analysis showed the learning curve for surgical failure, defined as severe complications (Clavien-Dindo grade ≥ 3) or open conversion, comprised three phases (phase 1: cases 1-60; phase 2: cases 61-83; phase 3: cases 84-119). There were no significant differences in operation time among the three phases. Intraoperative blood loss decreased significantly over the three phases (P = 0.032). There were no postoperative deaths. The rates of postoperative complications, pancreatic fistula (grade B/C), and post-pancreatic hemorrhage were significantly lower in phase 3 than in phase 2 (2.8% vs. 21.7%, P = 0.019; 2.8% vs. 17.4%, P = 0.049; 0% vs. 13.0%, P = 0.026), but not between phases 1 and 2. Postoperative hospital stay decreased progressively, and was significantly shorter in phase 3 than in phase 1 (9.1 vs. 16.7 days, P = 0.001).Conclusions: The LPD failure rate decreased after the first 60 cases and stabilized after 84 cases. For safe dissemination of LPD, it is important to shorten the long learning curve and decrease the unfavorable outcomes in the early phase of the learning curve. [ABSTRACT FROM AUTHOR]

The human sensory system has a fascinating stimulus-detection capability attributed to the fact that the feature (pattern) of an input stimulus can be extracted through perceptual learning. Therefore, sensory information can be organized and identified efficiently based on iterative experiences, whereby the sensing ability is improved. Specifically, the distributed network of receptors, neurons, and synapses in the somatosensory system efficiently processes complex tactile information. Herein, we demonstrate an artificial tactile sensor system with a sensory neuron and a perceptual synaptic network composed of a single device: a semivolatile carbon nanotube transistor. The system can differentiate the temporal features of tactile patterns, and its recognition accuracy can be improved by an iterative learning process. Furthermore, the developed circuit model of the system provides quantitative analytical and product-level feasibility. This work is a step toward the design and use of a neuromorphic sensory system with a learning capability for potential applications in robotics and prosthetics. Neuromorphic computing: simultaneously simulating neurons and synapses An array of electronic components that can mimic information processing in the brain has been developed by scientists in South Korea. Digital electronic devices operate using only ones and zeros, but neurons in the brain and the synapses that connect them work on an analog basis. Neuromorphic devices attempt to mimic this analog behavior to achieve low-power information processing. Previous neuromorphic networks have been created using different types of structures to mimic neurons and synapses. Sung-Jin Choi from Kookmin University in Seoul and co-workers have now demonstrated a device that can simulate both synaptic and neuronal functions simultaneously. The researchers used an array of carbon nanotube transistors to create a neuromorphic system that can recognize different tactile patterns and learn in the process. The system has potential applications in robotics and prosthetics. We demonstrate an artificial tactile sensor system with a sensory neuron and a perceptual synaptic network that is composed of a single device type, i.e., a semivolatile carbon nanotube transistor. The system can differentiate the temporal features of tactile patterns, and its recognition accuracy can be improved by an iterative learning process. [ABSTRACT FROM AUTHOR]

Fluid catalytic cracking (FCC) is an important chemical process that is widely used to produce valuable petrochemical products by cracking heavier components. However, many difficulties exist in modeling the FCC process due to its complexity. In this study, a dynamic process model of a FCC process is suggested and its structural observability is analyzed. In the process modeling, yield function for the kinetic model of the riser reactor was applied to explain the product distribution. Hydrodynamics, mass balance and energy balance equations of the riser reactor and the regenerator were used to complete the modeling. The process model was tested in steady-state simulation and dynamic simulation, which gives dynamic responses to the change of process variables. The result was compared with the measured data from operating plaint. In the structural analysis, the system was analyzed using the process model and the process design to identify the structural observability of the system. The reactor and regenerator unit in the system were divided into six nodes based on their functions and modeling relationship equations were built based on nodes and edges of the directed graph of the system. Output-set assignment algorithm was demonstrated on the occurrence matrix to find observable nodes and variables. Optimal locations for minimal addition of measurements could be found by completing the whole output-set assignment algorithm of the system. The result of this study can help predict the state more accurately and improve observability of a complex chemical process with minimal cost. [ABSTRACT FROM AUTHOR]

Background: We have recently performed a blunt dissection technique using LigaSure technology for laparoscopic spleen- and splenic-vessel-preserving distal pancreatectomy to reduce the risk of bleeding during the dissection of the splenic vessels. The aim of this study was to compare the utility of the blunt dissection technique and a conventional dissection technique during laparoscopic spleen- and splenic-vessel-preserving distal pancreatectomy.Methods: Fifty-five patients who underwent laparoscopic spleen- and splenic-vessel-preserving distal pancreatectomy performed by a single surgeon between March 2003 and December 2015 were enrolled in this retrospective single-center study. The patients were divided into the LigaSure group (n = 23) and non-LigaSure group (n = 26). Perioperative clinical outcomes and the postoperative patency of the preserved splenic vessels in the two groups were compared.Results: The patient and tumor characteristics did not differ significantly between the two groups. The incidence of postoperative complications was similar in the two groups. However, the mean operative time (145 vs. 231.1 min, P = 0.001), intraoperative blood loss (95.6 vs. 360 ml, P = 0.001), and postoperative hospital stay (6.4 vs. 9.8 days, P = 0.001) were significantly lower in the LigaSure group than in the non-LigaSure group, respectively. The splenic artery patency rate was similar in both groups, but the splenic vein patency was significantly better in the LigaSure group than in the non-LigaSure group (total occlusion rate: 4.5 vs. 30.8%, respectively, P = 0.017).Conclusion: The results of this study suggest that the blunt dissection technique using a LigaSure reduces the operating time and intraoperative blood loss during laparoscopic spleen- and splenic-vessel-preserving distal pancreatectomy and increases the patency of the preserved splenic vessels. [ABSTRACT FROM AUTHOR]

Background: Many centers consider hepatocellular carcinoma (HCC) located in segments 7 or 8 to be unsuitable for laparoscopic liver resection (LLR). We evaluated the safety of LLR of HCC in segments 7 or 8 following the introduction of new laparoscopic techniques.Methods: This retrospective study included 104 patients who underwent LLR (n = 46) or open liver resection (OLR) (n = 58) for HCC located in segments 7 or 8 between October 2004 and June 2015. The LLR group was subdivided into two subgroups according to whether LLR was performed before (Lap1; n = 29) or after (Lap2; n = 17) the introduction of the Pringle maneuver, intercostal trocars, and semi-lateral patient positioning.Results: Non-anatomical resection was more frequent (63.0 vs. 29.3%; P < 0.001) and tumor size was smaller (2.8 vs. 4.7 cm; P < 0.001) in the LLR group than in the OLR group. Blood transfusion (P = 0.526), operation time (P = 0.267), postoperative complications (P = 0.051), and resection margin (P = 0.705) were similar in both groups. LLR was associated with less blood loss (550 vs. 700 ml, P = 0.030) and shorter hospital stay (8 vs. 10 days; P = 0.001). The 3-year overall (90.2 vs. 81.2%, P = 0.096) and disease-free survival (15.1 vs. 12.1%; P = 0.857) rates were similar in both groups. The Lap2 group has less blood loss (230 vs. 500 ml; P = 0.005) and shorter hospital stay (7 vs. 9 days; P = 0.038) compared with the Lap1 group.Conclusion: LLR can be safely performed for HCC located in segments 7 or 8 with recent improvements in surgical techniques and accumulated experience. [ABSTRACT FROM AUTHOR]

Background: Several classification systems for assessing the surgical difficulty of laparoscopic liver resection (LLR) have been proposed. We evaluated three current classification systems, including traditional Major/Minor Classification, Complexity Classification, and the Difficulty Scoring System for predicting the surgical outcomes after LLR.Methods: We reviewed the clinical data of 301 patients who underwent LLR for hepatocellular carcinoma between March 1, 2004 and June 30, 2015. We compared the intraoperative, pathologic, and postoperative outcomes according to the three classifications. We also compared the prognostic value of the three classifications using receiver operating characteristic (ROC) curves.Results: The Major/Minor Classification, Complexity Classification, and the Difficulty Scoring System efficiently differentiated surgical difficulty in terms of blood loss (P = 0.001, P = 0.009, and P < 0.001, respectively) and operation time (all P < 0.001). Regarding intraoperative outcomes, the Difficulty Scoring System and Complexity Classification successfully differentiated the transfusion rate (P = 0.001 and P < 0.001, respectively). However, only the Complexity Classification adequately predicted severe postoperative complications (P = 0.032), the severity of complications (P < 0.001), and the length of hospital stay (P = 0.005). In ROC curve analysis, the Complexity Classification (area under the curve [AUC] = 0.611) outperformed the Major/Minor Classification (AUC = 0.544) and the Difficulty Scoring System (AUC = 0.530) for predicting severe postoperative complications. None of the classification systems predicted recurrence or patient survival.Conclusion: The Complexity Classification was superior to the other methods for assessing surgical difficulty and predicting complications after LLR for hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Transient electronics represent an emerging class of technology comprising materials that can vanish in a controlled manner in response to stimuli. In contrast to conventional electronic devices that are designed to operate over the longest possible period, transient electronics are defined by operation typically over a short and well-defined period; when no longer needed, transient electronics undergo self-deconstruction and disappear completely. In this work, we demonstrate the fabrication of thermally triggered transient electronic devices based on a paper substrate, specifically, a nitrocellulose paper. Nitrocellulose paper is frequently used in acts of magic because it consists of highly flammable components that are formed by nitrating cellulose by exposure to nitric acid. Therefore, a complete and rapid destruction of electronic devices fabricated on nitrocellulose paper is possible without producing any residue (i.e., ash). The transience rates can be modified by controlling radio frequency signal-induced voltages that are applied to a silver (Ag) resistive heater, which is stamped on the backside of the nitrocellulose paper. The Ag resistive heater was prepared by a simple, low-cost stamping fabrication, which requires no harsh chemicals or complex thermal treatments. For the electronics on the nitrocellulose paper substrate, we employed semiconducting carbon nanotube (CNT) network channels in the transistor for superior electrical and mechanical properties. [ABSTRACT FROM AUTHOR]

In the modern society, the forms of disasters are getting larger and more diverse by abnormal weather phenomena due to rapid social changes. As human and economic damage is increasing by these disasters, interest in disaster observation and prevention is increasing and studies have been carried out in various fields. In order to minimize disaster damage, National Disaster Information Center provides disaster-related information such as disaster situations, risk index, local situation and so on. At present, however, various descriptive studies on action tips in the event of a disaster, disaster alert, disaster communications network have been in progress but there are few studies on prediction or simulation for preventing disasters etc. Therefore, this paper proposes a slope-based intelligent 3D disaster simulation using a physics engine. The proposed method is to infer a variety of disaster situations that may occur in reality through ontology and apply it to 3D simulation. Disaster situation ontology constitutes context information of outside, inside, disasters etc. and generates rule bases using Jena 2.0 inference engine. Inference results are derived in the form of XML and applicable to a variety of devices. The expression of 3D simulation virtual space is divided into interior and exterior. Interior constitutes the index information based on actually measured terrain and then expresses it into 3D compound type terrain data. Exterior expresses six planes into a hexahedron by using Sky Box technique. Simulation operates object collision, movement, surroundings etc. in real time by using a physics engine and represents a disaster situation in 3D virtual space by using particles function. Based on ontology based context awareness, environment context information on slope, including landslides, snow, rain, fogs, fire, explosion, and smoke, is developed into the slope based intelligent 3D disaster simulation. As a result, depending on geomorphic characteristics, disaster management service can realistically and visually be offered to users in 3D virtual reality. In addition, it is possible to experimentally apply disaster situations virtually through 3D virtual reality, and thereby judge their potential risk. [ABSTRACT FROM AUTHOR]

An infrared search and track system is an important research goal for military applications. Although there has been much research into small infrared target detection methods, we cannot apply them in real field situations due to the high false alarm rate caused by clutter. This paper presents a novel target attribute extraction and machine learning-based target discrimination method. In our study, eight target features were extracted and analyzed statistically. Learning-based classifiers, such as SVM and Adaboost, have been incorporated and then compared to conventional classifiers using real infrared images. In addition, the generalization capability has also been inspected for various types of infrared clutter. [ABSTRACT FROM AUTHOR]

A potential solution to reduce global warming is to store greenhouse gases. Greenhouse gas storage has been recently improved using several materials and techniques. However, the actual storage capacity is slow, limited, and costly. Here, we tested the use of an accelerating agent, sodium dodecyl sulfate, and coal to produce methane hydrate for methane storage. Experiments of storing methane gas in coal samples have been carried out under high pressures, 4 or 6 MPa, and low temperature of 273.15 K. Results reveal that sodium dodecyl sulfate improved the rate up to 58.26 cm/min and the capacity up to 179.97 volume at standard temperature and pressure per unit volume of coal. This finding shows that sodium dodecyl sulfate is efficient to accelerate the formation of methane hydrate. We also found that storage capacity increased with pressure. We conclude that our method allows a gas storage capacity higher than any other medium materials reported previously. [ABSTRACT FROM AUTHOR]

In this paper, we present a new shape encoding method for object recognition. We first introduce a neuro-physiologically inspired visual part detector and shape encoder. The optimal form of the visual part detector is a combination of a circular symmetry detector and a corner-like structure detector. A perceptually novel shape descriptor, known as the curvature-orientation descriptor, is then discussed. This descriptor encodes the curvature as well as the dominant orientation. The perceptual shape encoder enhances the performance of feature matching and object recognition taken from standard test images. The results from the repeatability and object recognition tests validate the feasibility of the proposed perceptual feature extraction method. [ABSTRACT FROM AUTHOR]

This paper presents an analog image recognition system with a novel MESFET device fabricated on a fully depleted (FD) CMOS process. An analog image recognition system with a power consumption of 2.4 mW/cell and a settling time of 6.5 μs was designed, fabricated and characterized. A CNN is employed to realize a core cell of the proposed image recognition system. While a CNN benefits from its regular structure, it faces challenges due to its power consumption, speed, and size in their CMOS implementations. SOS MESFETs can deal with the challenges associated with CMOS-based CNNs. Advantages of SOS MESFETs associated with nonlinear signal processing include lower power consumption and higher operating speeds compared to similar geometry MOSFETs carrying the same current. SOS MESFET-based analog image recognition systems were fabricated and the transient response is characterized in both simulation using a TOM3 SPICE model extracted from SOS MESFETs and in experiment using image testing lab equipment. Settling times of 3.5 and 6.5 μs for one-by-four and one-by-eight arrays, respectively, were achieved with line recognition template. The corresponding power consumption for the two arrays was 9.6 and 19.2 mW, respectively. [ABSTRACT FROM AUTHOR]

Injection molding is a flexible production method for manufacturing polymer products, but introduces residual stresses. This study employs the incremental hole-drilling method to measure the residual stresses in injection molded parts. To compare the results, the layer-removal method is utilized for measurement of residual stresses. A commercial software, Moldflow, is used for prediction of residual stresses in molded plastic parts. Results obtained by experiments and Moldflow analysis are compared. The incremental hole-drilling method is applicable to determination of the residual stresses in complex geometries and can be used as an adoptable technique for measurement of the residual stress in polymeric materials. [ABSTRACT FROM AUTHOR]

A solution is given for the elastodynamic problem of a crack perpendicular to the graded interfacial zone in bonded materials under the action of antiplane shear impact. The interfacial zone is modeled as a nonhomogeneous interlayer with the power-law variations of its shear modulus and mass density between the two dissimilar, homogeneous half-planes. Laplace and Fourier integral transforms are employed to reduce the transient problem to the solution of a Cauchy-type singular integral equation in the Laplace transform domain. Via the numerical inversion of the Laplace transforms, the values of the dynamic stress intensity factors are obtained as a function of time. As a result, the influences of material and geometric parameters of the bonded media on the overshoot characteristics of the dynamic stress intensities are discussed. A comparison is also made with the corresponding elastostatic solutions, addressing the inertia effect on the dynamic load transfer to the crack tips for various combinations of the physical properties. [ABSTRACT FROM AUTHOR]

A model is constructed to analyze the stress and to determine the yield surface for cracked layer which is perfectly bonded to the substrate. It is assumed that the layer and substrate are isotropic and crack surface is subjected to a constant pressure. Mixed boundary value problem is formulated by Fourier integral transform method, and governing equations are reduced to a Fredholm integral equation. From the numerical analysis, stress components including Mises stress are evaluated. Finally, using the Mises yield criterion, the yield surface is determined for various layer-substrate combinations. [ABSTRACT FROM AUTHOR]

Fatigue tests are performed to evaluate the fatigue strength of high strength steel containing partial penetration butt weld and full penetration butt weld. The influence of the unwelded ligament (Lack of Penetration) in the partial penetration welds on the fatigue life is analyzed for various LOP sizes. For full penetration welds, the fatigue crack initiated at the weld toe and propagated to the HAZ. For partial penetration welds, however, the fatigue cracks initiated at the LOP section and propagated to the weld metal (or weld toe) for the considered LOP sizes (from 2mm to 4mm) reducing the fatigue strength. Consequently, the increament of the LOP size yield in the fatigue life degradation by some extent. [ABSTRACT FROM AUTHOR]

Background: Gallbladder cancer (GBC) has been contraindicated for laparoscopic surgery since this procedure was introduced [1, 2]. Recently, however, there have been several reports of laparoscopic extended cholecystectomy for GBC, but most cases involved early GBC confined to the GB [3, 4]. This video describes our technique of laparoscopic extended cholecystectomy for T3 GBC.Methods: A 77-year-old female presented with a gallbladder mass, which was incidentally detected during evaluation of back pain. Abdominal computed tomography and endoscopic ultrasonography revealed a 3.5 × 2.5 cm hypoechoic mass in the gallbladder fundus with liver invasion. We performed laparoscopic en bloc resection of the gallbladder and the gallbladder bed, as well as lymphadenectomy.Results: Two 5-mm and three 12-mm trocars were used. After carefully dissecting Calot's triangle, the cystic duct was dissected and ligated. The cystic duct margin was negative on the frozen section biopsy. Cholecystectomy with en bloc wedge resection of the liver was performed first. Ultrasonic shears were used to transect the superficial hepatic parenchyma and a Cavitron Ultrasonic Surgical Aspirator was used to transect the deeper parenchyma. We then performed lymphadenectomy of involved lymph nodes (LNs) around the hepatoduodenal ligament, common hepatic artery, and posterior superior pancreas. After Kocherization of the duodenum, LNs were dissected from the posterior superior portion of the pancreas. LN dissection continued along the right side of the common bile duct and the portal vein. After dissection from the inferior vena cava and the aorta, the dissected LNs were pushed toward the left side under the portal vein. LN dissection continued along the left side of the hepatoduodenal ligament, while exposing the common hepatic artery and proper hepatic artery. Skeletonizing en bloc LN dissection was the final procedure. The operation time was 215 min and the estimated intraoperative blood loss was 200 mL. The postoperative pathology confirmed a small cell neuroendocrine carcinoma with clear resection margins. The pathologic staging was pT3N1. LN metastasis was found in one of 12 retrieved LNs. The patient was discharged on postoperative day 4 without postoperative complications. The patient received combined chemoradiation therapy for 6 months after surgery. There was no evidence of recurrence over the follow-up period of 14 months.Conclusion: Laparoscopic extended cholecystectomy is technically feasible in patients with T3 GBC, and the extent of resection is the same as that of open surgery. [ABSTRACT FROM AUTHOR]

Brain-inspired neuromorphic systems (hardware neural networks) are expected to be an energy-efficient computing architecture for solving cognitive tasks, which critically depend on the development of reliable synaptic weight storage (i.e., synaptic device). Although various nanoelectronic devices have successfully reproduced the learning rules of biological synapses through their internal analog conductance states, the sustainability of such devices is still in doubt due to the variability common to all nanoelectronic devices. Alternatively, a neuromorphic system based on a relatively more reliable digital-type switching device has been recently demonstrated, i.e., a binarized neural network (BNN). The synaptic device is a more mature digital-type switching device, and the training/recognition algorithm developed for the BNN enables the task of facial image classification with a supervised training scheme. Here, we quantitatively investigate the effects of device parameter variations on the classification accuracy; the parameters include the number of weight states (Nstate), the weight update margin (ΔG), and the weight update variation (Gvar). This analysis demonstrates the feasibility of the BNN and introduces a practical neuromorphic system based on mature, conventional digital device technologies. [ABSTRACT FROM AUTHOR]

In the biological neural network, the learning process is achieved through massively parallel synaptic connections between neurons that can be adjusted in an analog manner. Recent developments in emerging synaptic devices and their networks can emulate the functionality of a biological neural network, which will be the fundamental building block for a neuromorphic computing architecture. However, on-chip implementation of a large-scale artificial neural network is still very challenging due to unreliable analog weight modulation in current synaptic device technology. Here, we demonstrate a binarized neural network (BNN) based on a gate-all-around silicon nanosheet synaptic transistor, where reliable digital-type weight modulation can contribute to improve the sustainability of the entire network. BNN is applied to three proof-of-concept examples: (1) handwritten digit classification (MNIST dataset), (2) face image classification (Yale dataset), and (3) experimental 3 × 3 binary pattern classifications using an integrated synaptic transistor network (total 9 × 9 × 2 162 cells) through a supervised online training procedure. The results consolidate the feasibility of binarized neural networks and pave the way toward building a reliable and large-scale artificial neural network by using more advanced conventional digital device technologies. [ABSTRACT FROM AUTHOR]

Alloys are recently receiving considerable attention in the community of rechargeable batteries as possible alternatives to carbonaceous negative electrodes; however, challenges remain for the practical utilization of these materials. Herein, we report the synthesis of germanium-zinc alloy nanofibers through electrospinning and a subsequent calcination step. Evidenced by in situ transmission electron microscopy and electrochemical impedance spectroscopy characterizations, this one-dimensional design possesses unique structures. Both germanium and zinc atoms are homogenously distributed allowing for outstanding electronic conductivity and high available capacity for lithium storage. The as-prepared materials present high rate capability (capacity of ~ 50% at 20 C compared to that at 0.2 C-rate) and cycle retention (73% at 3.0 C-rate) with a retaining capacity of 546 mAh g−1 even after 1000 cycles. When assembled in a full cell, high energy density can be maintained during 400 cycles, which indicates that the current material has the potential to be used in a large-scale energy storage system. Alloy anode materials are receiving renewed interest. Here the authors show the design of Ge-Zn nanofibers for lithium ion batteries. Featured by a homogeneous composition at the atomic level and other favorable structural attributes, the materials allow for impressive electrochemical performance. [ABSTRACT FROM AUTHOR]

The thermochemical reduction of silica to silicon using chemical reductants requires high temperature and has a high activation energy, which depends on the melting temperature of the reductant. The addition of bi-functional molten salts with a low melting temperature may reduce the required energy, and several examples using molten salts have been demonstrated. Here we study the mechanism of reduction of silica in the presence of aluminum metal reductant and aluminum chloride as bi-functional molten salts. An aluminum–aluminum chloride complex plays a key role in the reduction mechanism, reacting with the oxygen of the silica surfaces to lower the heat of reaction and subsequently survives a recycling step in the reaction. This experimentally and theoretically validated reaction mechanism may open a new pathway using bi-functional molten salts. Furthermore, the as-synthesized hollow porous silicon microsphere anodes show structural durability on cycling in both half/full cell tests, attributed to the high volume-accommodating ability. Thermochemical reduction of silica by molten salts is known to yield promising microstructured silica energy materials. Here a combined experimental and computational study suggests a mechanism for low temperature thermochemical reduction of silica by molten aluminum chloride. [ABSTRACT FROM AUTHOR]

The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe2 heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state. The device operates with low voltage spikes of 0.3 V and consumes only 66 fJ per spike. This consequently facilitates the demonstration of accurate and energy efficient colored and color-mixed pattern recognition. The work will be an important step toward neural networks that comprise neural sensing and training functions for more complex pattern recognition. Artificial neural networks can emulate the human vision because of their spike-based operation by employing memristors as synapses. Here, Seo et al. integrate synaptic and optical sensing functions in a single heterostructure, which enables accurate and energy-efficient recognition of colored patterns. [ABSTRACT FROM AUTHOR]

Background: Laparoscopic resection of retroperitoneal mass is challenging because of its location close to major vessels and a limited range of laparoscopic instruments [1-3]. We report a case of a huge retroperitoneal paraganglioma that was successfully excised laparoscopically using maneuver of hanging IVC METHOD: A 67-year-old female had abdominal mass detected during routine check-up. She had no symptoms associated mass. Hematologic, biochemical investigations, and hormone tests reveal normal results. Preoperative CT shows retroperitoneal tumor, measuring 6.1 cm in diameter, which was closely adhered to right adrenal gland and seemed to originate from adrenal gland. Three 12-mm trocars and two 5-mm trocars were used. Laparoscopic views showed that severe adhesion in peritoneal cavity due to previous subtotal gastrectomy for gastric polyp about 30 years ago. After adhesiolysis, the mass was visualized behind inferior vena cava. The mass was carefully dissected and separated from duodenum and inferior vena cava as well as right adrenal gland. Inferior vena cava was retracted with hanging maneuver of IVC with vascular tape. The fibrotic tissues covering the mass were dissected with ligasure™. The feeding vessels supplying mass were identified and clipped, then subsequently sealed and divided. After complete resection of mass, the specimen was inserted into plastic retrieval bag and extracted via extended umbilical port. And then Jackson Pratt drain was placed around inferior vena cava.Result: There was no intraoperative transfusion and complications during laparoscopic retroperitoneal excision for paraganglioma. The operation time was 190 min, and estimated blood loss was 100 ml. The patient was discharged on postoperative 5th day without complications. Final pathologic result was paraganglioma of 7.5 cm sized with PASS score 4 (pheochromocytoma of the adrenal gland scaled score).Conclusion: Laparoscopic surgery for huge retroperitoneal paraganglioma behind IVC was successfully performed with the maneuver of hanging IVC. This procedure could be useful with appropriate laparoscopic technique and proper patient selection. [ABSTRACT FROM AUTHOR]

Contact and non-contact based atomic force microscopy (AFM) approaches have been extensively utilized to explore various nanoscale surface properties. In most AFM-based measurements, a concurrent electrostatic effect between the AFM tip/cantilever and sample surface can occur. This electrostatic effect often hinders accurate measurements. Thus, it is very important to quantify as well as remove the impact of the electrostatic effect on AFM-based measurements. In this study, we examine the impact of the electrostatic effect on the electromechanical (EM) response in piezoresponse force microscopy as a model AFM mode. We quantitatively studied the effects of increasing the external electric field and reducing the spring constant of a cantilever. Further, we explored ways to minimize the electrostatic effect. The results provide broad guidelines for quantitatively analyzing the EM response as well as, eventually, for obtaining the electrostatic-free EM response. The conclusions can be applied to other AFM-based measurements that are subject to a strong electrostatic effect between the AFM tip/cantilever and sample surface, regardless of contact and non-contact modes. [ABSTRACT FROM AUTHOR]