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Recent studies have revealed that glial sigma-1 receptor (Sig-1R) in the spinal cord may be a critical factor to mediate sensory function. However, the functional role of Sig-1R in astrocyte has not been clearly elucidated. Here, we determined whether Sig-1Rs modulate calcium responses in primary cultured astrocytes and pathological changes in spinal astrocytes, and whether they contribute to pain hypersensitivity in naive mice and neuropathic pain following chronic constriction injury (CCI) of the sciatic nerve in mice. Sig-1R was expressed in glial fibrillary acidic protein (GFAP)-positive cultured astrocytes. Treatment with the Sig-1R agonist, PRE-084 or neurosteroid dehydroepiandrosterone (DHEA) increased intracellular calcium responses in cultured astrocytes, and this increase was blocked by the pretreatment with the Sig-1R antagonist, BD-1047 or neurosteroid progesterone. Intrathecal administration of PRE-084 or DHEA for 10 days induced mechanical and thermal hypersensitivity and increased the number of Sig-1R-immunostained GFAP-positive cells in the superficial dorsal horn (SDH) region of the spinal cord in naive mice, and these changes were inhibited by administration with BD-1047 or progesterone. In CCI mice, intrathecal administration of BD-1047 or progesterone at post-operative day 14 suppressed the developed mechanical allodynia and the number of Sig-1R-immunostained GFAP-positive cells that were increased in the SDH region of the spinal cord following CCI of the sciatic nerve. These results demonstrate that Sig-1Rs play an important role in the modulation of intracellular calcium responses in cultured astrocytes and pathological changes in spinal astrocytes and that administration of BD-1047 or progesterone alleviates the Sig-1R-induced pain hypersensitivity and the peripheral nerve injury-induced mechanical allodynia.

Online continual learning for image classification studies the problem of learning to classify images from an online stream of data and tasks, where tasks may include new classes (class incremental) or data nonstationarity (domain incremental). One of the key challenges of continual learning is to avoid catastrophic forgetting (CF), i.e., forgetting old tasks in the presence of more recent tasks. Over the past few years, many methods and tricks have been introduced to address this problem, but many have not been fairly and systematically compared under a variety of realistic and practical settings. To better understand the relative advantages of various approaches and the settings where they work best, this survey aims to (1) compare state-of-the-art methods such as MIR, iCARL, and GDumb and determine which works best at different experimental settings; (2) determine if the best class incremental methods are also competitive in domain incremental setting; (3) evaluate the performance of 7 simple but effective trick such as "review" trick and nearest class mean (NCM) classifier to assess their relative impact. Regarding (1), we observe iCaRL remains competitive when the memory buffer is small; GDumb outperforms many recently proposed methods in medium-size datasets and MIR performs the best in larger-scale datasets. For (2), we note that GDumb performs quite poorly while MIR -- already competitive for (1) -- is also strongly competitive in this very different but important setting. Overall, this allows us to conclude that MIR is overall a strong and versatile method across a wide variety of settings. For (3), we find that all 7 tricks are beneficial, and when augmented with the "review" trick and NCM classifier, MIR produces performance levels that bring online continual learning much closer to its ultimate goal of matching offline training., Comment: Accepted for publication in the Elsevier's Neurocomputing journal. Codes available at https://github.com/RaptorMai/online-continual-learning

The urban heat island effect has been studied extensively by many researchers around the world with the process of urbanization coming about as one of the major culprits of the increasing urban land surface temperatures. Over the past 20 years, the city of Dallas, Texas, has consistently been one of the fastest growing cities in the United States and has faced rapid urbanization and great amounts of urban sprawl, leading to an increase in built-up surface area. In this study, we utilize Landsat 8 satellite images, Geographic Information System (GIS) technologies, land use/land cover (LULC) data, and a state-of-the-art methodology combining machine learning algorithms (eXtreme Gradient Boosted models, or XGBoost) and a modern game theoretic-based approach (Shapley Additive exPlanation, or SHAP values) to investigate how different land use/land cover classifications impact the land surface temperature and park cooling effects in the city of Dallas. We conclude that green spaces, residential, and commercial/office spaces have the largest impacts on Land Surface Temperatures (LST) as well as the Park’s Cooling Intensity (PCI). Additionally, we have found that the extent and direction of influence of these categories depends heavily on the surrounding area. By using SHAP values we can describe these interactions in greater detail than previous studies. These results will provide an important reference for future urban and park placement planning to minimize the urban heat island effect, especially in sprawling cities.

The deflection of charged particles is an intuitive way to visualize an electromagnetic oscillation of coherent light. Here, we present a real-time ultrafast oscilloscope for time-frozen visualization of a terahertz (THz) optical wave by probing light-driven motion of relativistic electrons. We found the unique condition of subwavelength metal slit waveguide for preserving the distortion-free optical waveform during its propagation. Momentary stamping of the wave, transversely travelling inside a metal slit, on an ultrashort wide electron bunch enables the single-shot recording of an ultrafast optical waveform. As a proof-of-concept experiment, we successfully demonstrated to capture the entire field oscillation of a THz pulse with a sampling rate of 75.7 TS/s. Owing to the use of transversely-wide and longitudinally-short electron bunch and transversely travelling wave, the proposed “single-shot oscilloscope” will open up new avenue for developing the real-time petahertz (PHz) metrology., A travelling wave inside a metal slit can reveal its own waveform by probing deflecting motions of charged particles. Here, a real-time THz oscilloscope was demonstrated by utilizing the relativistic electrons and the subwavelength slit waveguide.

Microalgae have the potential to utilize the nutrients in livestock urine and manure (LUM) for the production of useful biomass, which can be used as a source of bioindustry. This study aims to evaluate the economic benefits of LUM feedstock that have not been clearly discussed before. Two types of photobioreactors were designed with a capacity of 200 m3 d-1. Using the experimental data, the economic feasibility of the suggested processes was evaluated via techno-economic analysis. Itemized cost estimation indicated that the submerged membrane photobioreactor has a lower unit production cost (5.4 $ to 5.1 $ kg−1) than the conventional photobioreactor system (14.6 $ to 13.8 $ kg−1). In addition, LUM-based growth is another good option for reducing the unit production cost of biomass. The revenues from lowering the cost of LUM treatment significantly contribute to enhancing the economic profitability, where the break-even prices were 1.18 $ m−3 (photobioreactor) and 0.98 $ m−3 (submerged membrane photobioreactor). Finally, this study provides several emerging suggestions to reduce microalgal biomass production costs.

Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing for NP structures. An ideal semantic ontology for the classification of NPs should go beyond the simple presence/absence of chemical substructures, but also include the taxonomy of the producing organism, the nature of the biosynthetic pathway, and/or their biological properties. Thus, a holistic and automatic NP classification framework could have considerable value to comprehensively navigate the relatedness of NPs, and especially so when analyzing large numbers of NPs. Here, we introduce NPClassifier, a deep-learning tool for the automated structural classification of NPs from their counted Morgan fingerprints. NPClassifier is expected to accelerate and enhance NP discovery by linking NP structures to their underlying properties.

This study was aimed at assessing the safety of a mixed extract of fenugreek seeds and Lespedeza cuneata (YHM), which effectively relieves male menopausal symptoms. To this end, male and female Sprague-Dawley rats were divided into the following groups and repeatedly administered YHM orally for 90 days: control, low-dose (500 mg/kg/day), intermediate-dose (1,000 mg/kg/day), and high-dose (2,000 mg/kg/day) groups. The animals were monitored for general symptoms; their body weights and electrolyte levels were measured; and urinalysis, blood chemistry and biochemistry tests, and histopathological tests were performed to assess the toxicity of YHM. The no-observed-adverse-effect level of YHM was 2,000 mg/kg/day for all male and female rats. While in the YHM-administered and control groups, most parameters were within the normal range; some rats in the high-dose group showed changes not induced by the test substance but which may be specific to an individual animal or may occur naturally. Thus, on the basis of our findings, we consider that YHM may be a safe, non-toxic substance for alleviating male menopausal symptoms.

Although genetic Creutzfeldt-Jakob disease (CJD) is a rare neurodegenerative disorder, cases of genetic CJD with E200K mutation are being increasingly reported in Korea. However, the clinical features and course of genetic CJD with E200K mutation in Korea remain unclear. We describe the clinical features and course of genetic CJD with E200K mutation in a patient who initially presented with rapid progressive memory impairment and myoclonus.

In this study, we propose an omega-shaped-gate nanowire field effect transistor (ONWFET) with a silicon-on-sapphire (SOS) substrate. In order to investigate improvements in the self-heating characteristic with the use of a SOS substrate, the lattice temperature is examined using a Synopsys Sentaurus 3D Technology computer-aided design (TCAD) simulator with the results compared to those with a silicon-on-insulator (SOI) substrate. To validate the proposed structure with the SOS substrate, the locations of hot spots and heat dissipation paths (heat sinks) depending on the substrate materials are also analyzed. The electrical characteristics, specifically the on-current (Ion), off-current (Ioff), and subthreshold swing (SS), were investigated as well. Hence, it is demonstrated here that incorporating a SOS substrate can improve both the self-heating characteristic and the SS at the same time. Therefore, enhanced logic devices are feasible if using an ONWFET with a SOS substrate. Examples include wearable devices and military and future aerospace applications achieved by the radiation-resistant material Al2O3 that has high thermal conductivity.

Considerable agreement has existed concerning the intertextual relations between the Apostrophe to Zion (Ap Zion) and Third Isaiah. But I propose to reread Ap Zion as a literary and theological response to the most famous lament over Zion, exemplified in the book of Lamentations. The common acrostic feature and leitmotif of Zion shared by Lamentations and Ap Zion clearly reflect the latter’s deliberate attention to the former. In this reconsideration, I argue that the much-acclaimed intertextuality between Ap Zion and Third Isaiah is the consequence of the pre-established Isaianic inner-biblical allusion (Second Isaiah) to Lamentations. To expand on this proposal, the paper will explore the multilayered intertextuality between Lam 2, Isa 49, and Ap Zion through classifying their lexical, thematic, structural, and theological associations.

In this paper, we propose a Deep Packet Filtering Mechanism (DPFM) to analyze and filter malicious data packets moving between network environments. DPFM analyzes the behavior of malicious packets on the network and extracts information about the network as a sequence. After performing the word embedding process on the extracted sequence data using the word2vec technique, it detects malicious packets on the network by learning the LSTM model. In the past, research on filters to prevent malicious packets from entering the network by converting packets into data at the sending and receiving destinations and analyzing their purpose and maliciousness is insufficient. Since DPFM proceeds at the network boundary to analyze and extract malicious packets, primary detection is possible. In this paper, more accurate identification is possible by deep learning of network packets as well as OPcode and system calls, which are static analysis data.

The aim of this study is to propose a new detection method for determining the damage locations in pile foundations based on deep learning using acoustic emission data. First, the damage location is simulated using a back propagation neural network deep learning model with an acoustic emission data set acquired from pile hit experiments. In particular, the damage location is identified using two parameters: the pile location (PL) and the distance from the pile cap (DS). This study investigates the influences of various acoustic emission parameters, numbers of sensors, sensor installation locations, and the time difference on the prediction accuracy of PL and DS. In addition, correlations between the damage location and acoustic emission parameters are investigated. Second, the damage step condition is determined using a classification model with an acoustic emission data set acquired from uniaxial compressive strength experiments. Finally, a new damage detection and evaluation method for pile foundations is proposed. This new method is capable of continuously detecting and evaluating the damage of pile foundations in service.

Plasmonic coupling of metallic nanostructures with two-dimensional molybdenum disulfide (MoS2) atomic layers is an important topic because it provides a pathway to manipulate the optoelectronic properties and to overcome the limited optical cross-section of the materials. Plasmonic enhanced light-matter interaction of a MoS2 layer is known to be mainly governed by optical field enhancement and the Purcell effect, while the discrimination of the contribution from each mechanism to the plasmonic enhancement is challenging. Here, we investigate photoluminescence (PL) enhancement from few-layer MoS2 transferred on Au nanostructure arrays with controlled localized surface plasmon resonance (LSPR) spectral positions that were detuned from the excitation wavelengths. Two distinctive regimes in LSPR mode-dependent PL enhancement were revealed showing a maximum enhancement (∼40-fold) with zero detuning and a modest enhancement (∼10-fold) with the red-shift detuned LSPR from the excitation wavelength, which were attributed to LSPR-induced optical field enhancement and the Purcell effect, respectively. By applying the experimental parameters into the Purcell effect formalism, an effective mode volume of ∼0.016λ03 was estimated. Our work provides an insight into how to utilize few-layer MoS2 as a base material for optoelectronics by harnessing Purcell-enhanced optical responsivity.

Chemical reactions typically have numerous controllable factors that need to be optimized to yield the desired products. Although traditional experimental methods are limited to explore possible combinations of these factors, artificial intelligence (AI) can provide the optimal solution based on chemical reaction data. In this study, we optimize the non-oxidative conversion of methane to C2 compounds using AI, such as machine learning (ML) to predict experimental results and metaheuristics to optimize reaction conditions. A decision tree-based machine learning method can reasonably predict the reaction outcomes (CH4 conversion, C2 yield, and selectivities for C2 and coke) with an error of < 5%. Trained ML models are applied to maximize the C2 yield by optimizing the reaction parameters with metaheuristics. We can simultaneously enhance the C2 yield and suppress the coke formation by improving the multi-objective function for the optimization. We believe that our method will be helpful to optimize the chemical reaction conditions with multiple targets.

In this paper, the design and control of a sphere robot are presented. A small double gimbal control moment gyroscope(DGCMG) designed and analyzed as an indirect actuator for the rotational torque generation. The heading angle of the robot is controlled by a DGCMG and the driving position is controlled by DC motors. The DGCMG has been developed in a scissored-pair configuration which has two gimbals in the opposite direction to maximize the induced torque by double and cancel out the unwanted torque in the plane. Experimental studies of not only position control but also heading control of the sphere robot commanded by a joystick are conducted to demonstrate the functionality of the robot.

The use of porous three-dimensional (3D) bioceramic scaffolds to facilitate the regeneration of bone defects has attracted great attention because their structures closely mimic the natural extracellular matrix. 3D printing is a versatile method for the fabrication of 3D scaffolds. In this study, 3D strontium-substituted hydroxyapatite (Sr-HA) bioceramic scaffolds were prepared by simple precipitation and 3D printing method. The resulting scaffolds exhibited interconnected microporous structures of strands and a single-phase crystal due to HA, meaning that no changes in the phase composition and microstructure of the scaffolds with the Sr content were observed. However, their dissolution rate and biological performance were substantially influenced by changes in the Sr content of the scaffolds. The optimal Sr content in the Sr-HA scaffolds for enhanced proliferation and differentiation of cells were identified by comparing four compositions of the Sr-HA scaffolds. The results of in vitro bioactivity tests demonstrated that the Sr5-HA scaffold with 0.05 of Sr/(Ca + Sr) molar ratio promoted more rapid cell proliferation, osteogenic differentiation, and cellular mineralization compared with the other scaffolds. Therefore, Sr-HA scaffolds have the potential for application in bone regeneration as new bone graft substitutes.

Molecular dynamics (MD) simulations are useful in understanding the interaction between solid materials and molecules. However, performing MD simulations is possible only when interatomic potentials are available and constructing such interatomic potentials usually requires additional computational work. Recently, generating interatomic potentials was shown to be much easier when machine learning (ML) algorithms were used. In addition, ML algorithms require new descriptors for improved performance. Here, we present an ML approach with several categories of atomic descriptors to predict the parameters necessary for MD simulations, such as the potential energies and the atomic forces. We propose several atomic descriptors based on structural information and find that better descriptors can be generated from eXtreme gradient boosting (XGBoost). Moreover, we observe fewer descriptors that perform better in predicting the potential energies and the forces during methane activation processes on a catalytic Pt(111) surface. These results were consistently observed in two different ML algorithms: fully-connected neural network (FNN) and XGBoost. Taking into account the advantages of FNN and XGBoost, we propose an efficient ML model for estimating potential energies. Our findings will be helpful in developing new ML potentials for long-time MD simulations.

Central sleep apnea (CSA) is characterized by respiratory failure of at least 10 seconds without any effort of the chest and abdomen in the absence of upper airway resistance during sleep. In this case, the patient experiences respiratory failure that does not meet the CSA diagnostic criteria and CSA symptoms. Magnetic resonance imaging diffusion-weighted imaging (MRI DWI) scans revealed a lateral medullary infarction. Continuous positive airway pressure (CPAP) was applied as a primary treatment for CSA and respiratory failure. During the titration of CPAP, the apnea-hypopnea index (AHI) and arousal index (AI) were worse than the results before its use (AHI: 42.5/hr→82.8/hr, AI: 21.7/hr→40.8h). As a result, adaptive servo-ventilation (ASV) was chosen as the secondary treatment. Compared to the night-polysomnography results before the ASV treatment, the AHI improved (42.5/hr→8.6/hr). Therefore, ASV is a potential treatment for CSA and respiratory failure in these patients.

Docetaxel, a chemotherapeutic agent used to treat breast cancer, produces a robust painful neuropathy that is aggravated by mechanical and thermal stimuli. This study was undertaken to investigate the analgesic effects of electrical stimulation on docetaxel-induced neuropathic pain in mice and to identify associated changes in ultrasound vocalizations. Peripheral neuropathy was induced with intraperitoneally injected docetaxel (5 mg/kg) on 3 times every 2 days in male ICR mice. Electrical wrist stimulation was administered and pain behavior signs were evaluated by von Frey filaments and thermal stimulation on the hind paw. Ultrasound vocalizations were measured using ultrasound microphones, after electrical stimulation. After mice developed docetaxel-induced neuropathic pain behavior, an electrical stimulation temporarily attenuated mechanical allodynia and thermal hyperalgesia. In formalin and NMDA test, pain-induced mice showed increases in 10-30 kHz ultrasound vocalizations, but not in 30-50 and 50-80 kHz vocalizations. Treatment with docetaxel selectively increased 10-30 kHz ultrasound vocalizations, whereas electrical stimulation caused a meaningful decrease. Moreover, electrical stimulation suppressed the docetaxel-enhanced phosphorylation of the NMDA receptor NR2B subunit in the spinal dorsal horn. These results of the analgesic effect of electrical stimulation in chemotherapy-induced neuropathy could potentially provide a new method to treat and manage peripheral neuropathy in patients with cancer.

Background/purpose: Due to the pneumatization of the maxillary sinus, the sinus floor augmentation is often performed to implant placement in the maxillary posterior region. The aim was to perform radiographic and histomorphometric evaluation after placement of mixed allografts (cortical freeze-dried bone allograft [FDBA] 50%:cancellous FDBA 50%) during sinus floor augmentation. Materials and methods: In 37 patients, anorganic bovine bone (ABB, sites = 16), mineralized cancellous bone allograft (MCBA, sites = 15), and mixed allografts (Mixed AG, sites = 20) were placed during sinus floor elevation via the lateral approach (LSFE), at total 51 sites with residual alveolar bone height (RBH) 0.05). The mean ABH of ABB, MCBA, and mixed AG groups after 6 months was similar (13.72 ± 4.55 mm, 11.83 ± 3.31 mm, and 12.53 ± 2.97 mm, respectively; P > 0.05). In the ABB, MCBA, and mixed AG groups, the proportion of newly formed bone (NB) was similar (36.13 ± 10.01%, 39.26 ± 10.72%, and 31.27 ± 18.31%, respectively; P > 0.05). Conclusion: This result demonstrated that mixed AG led to sufficient bone augmentation and histologically comparable NB formation as compared to ABB and MCBA for sinus floor augmentation.

With the increasing utilization of cloud computing and cyber–physical systems (CPSs), which allow the expression and control of the real world in a virtual environment, researches related to these subjects are being actively conducted in various areas. The convergence of CPS and cloud computing is being researched primarily because of their high availability, high-performance computing, and high-throughput computing. CPS consisting of numerous sensors, actuators, controllers, and control managers requires optimized modeling, simulation, and resource management technologies to integrate physical elements with computing elements for processing, which will provide high-throughput computing and high-reliability services. But the main problem of sensor resource management is that information of sensors cannot be approached in case that a sensor failure occurs at the sensing target area. Thus, various researches have been done to reconstruct the topology, but the self-topology configuration of sensors causes unnecessary events and battery consumption from various sensor nodes. In this paper, adaptive resource management (ARM) is proposed to 1) minimize information loss due to the irregular lifespan of resources, such as sensors and actuators; and 2) quickly respond to any problems. ARM uses the many-core of GPU to speed up fault handling, parallelizes the sensor information to select an alternate node of the fault node, and presents the performance evaluation results of the execution time of CPU and GPU.

Graph neural networks (GNNs) have attracted significant attention from the chemical science community because molecules can be represented as a featured graph. In particular, graph convolutional network (GCN) and its variants have been widely used and have shown a state-of-the-art performance in analyzing molecules, such as molecular label classification, drug discovery, and molecular property prediction. However, in molecular analysis, existing GCNs have two fundamental limitations: (1) information of the molecular scale is distorted and (2) global structures in a molecule are ignored. These limitations can seriously degrade the performance in the machine learning-based molecular analysis because the scale and global structure information of a molecule occasionally have a significant effect on the molecular properties. To overcome the limitations of existing GCNs, we comprehensively analyzed the structure of GCNs and developed a costless solution for the limitations of GCNs. To demonstrate the effectiveness of our solution, extensive experiments were conducted on various benchmark datasets.

Purpose : There has been little research conducted into aggression in persons with epilepsy (PWE). We determine whether sleep disturbances and obesity are associated with aggression in PWE independent of psychological distress. Methods : This was a cross-sectional study. The Aggression Questionnaire (AQ-K), the Insomnia Severity Index (ISI), the Epworth Sleepiness Scale (ESS), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were utilized in the study. A stepwise linear regression analysis was used. Results : A total of 104 participants (49% men) were included. Mean AQ-K score was 51.4 (SD 12.6). PHQ-9 scores ≥10 and GAD-7 scores ≥7 were noted in 26.9% and 24.0% of participants, respectively. In a stepwise linear regression model, AQ-K scores were positively associated with PHQ-9 scores ≥10 (p = 0.002), ISI scores (p = 0.007), body mass index (BMI) (p = 0.001), and composite scores of epilepsy severity (p = 0.013). This model explained 46.6% of the variance in the AQ-K. In the subscale analyses, different variables were identified as independent factors associated with different subscales of the AQ-K. For example, physical aggression was related to a PHQ-9 score ≥10, men, and perampanel usage, whereas hostility was related to a GAD-7 score ≥7, polytherapy, and BMI. Conclusions : Insomnia symptoms and obesity were related to overall aggressive behavior in PWE independent of depressive symptoms. The individual subscales of the AQ were correlated differently with the various factors including male sex, obesity, depressive symptoms, anxiety, insomnia symptoms, epilepsy severity, polytherapy, and the use of perampanel.

We compared the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) with the Patient Health Questionnaire-9 (PHQ-9) according to different antiepileptic drug (AED) loads in people with epilepsy (PWE).Depression and suicidality were assessed with the Mini International Neuropsychiatric Interview (MINI), the NDDI-E, and the PHQ-9. A receiver operating characteristic (ROC) curve analysis was used. Sensitivity and specificity of the NDDI-E and PHQ-9 were compared between an AED load2 and ≥2.Of 213 participants included, 22.5 % were diagnosed with current depression by the MINI, and 9 % had a moderate to severe risk of suicide. Using the cutoff of 9.5 and 13.5 for the PHQ-9 and NDDI-E, respectively, in the total group, the PHQ had a higher sensitivity (91.7 %) but lower specificity (75.8 %) than the NDDI-E (66.7 % and 87.3 %, respectively) (p0.001). In a group with an AED load2, the sensitivity and specificity did not differ between the PHQ-9 and NDDI-E. In a group with an AED load ≥2, however, the PHQ-9 had a higher sensitivity (90.9 %, p0.063) but lower specificity (65.2 %, p0.001) than the NDDI-E (68.2 % and 81.2 %, respectively). For screening of suicide risk, the sensitivity and specificity were not different between the PHQ-9 and NDDI-E in all tested groups. The negative predictive values of both instruments were above 95 % for suicide risk.In patients with a low AED load, the sensitivity and specificity did not differ between the PHQ-9 and NDDI-E. In contrast, in patients with a high AED load, the PHQ-9 had a poor specificity whereas the NDDI-E had a poor sensitivity.

Stroboscopic visualization of nuclear or electron dynamics in atoms, molecules or solids requires ultrafast pump and probe pulses and a close to perfect synchronization between the two. We have developed a 3 MeV ultrafast electron diffraction (UED) probe technology that nominally reduces the electron bunch duration and the arrival time jitter to the subfemtosecond level. This simple configuration uses a radiofrequency photogun and a 90° achromatic bend and is designed to provide effectively jitter-free conditions. Terahertz streaking measurements reveal an electron bunch duration of 25 fs, even for a charge as high as 0.6 pC, and an arrival time jitter of 7.8 fs, the latter limited by only the measurement accuracy. From pump–probe measurements of photoexcited bismuth films, the instrument response function was determined to be 31 fs. This pioneering jitter-free technique paves the way towards UED of attosecond phenomena in atomic, molecular and solid-state dynamics. An ultrafast electron diffraction facility with an overall temporal resolution of 31 fs root mean square is developed. Even for a charge as high as 0.6 pC, the electron bunch duration and timing jitter are 25 fs and less than 10 fs, respectively.

Background Burn injuries are devastating traumas that functionally affect a variety of organ systems. As intensive inflammatory responses induced by burns can lead to multiple organ failures and impaired skin regeneration increases risk of infectious complex, multimodal therapeutic approaches are needed. Objectives To investigate the role of low dose radiation (LDR) treatment for regulation of excessive inflammation and wound healing after burn injury. Methods Mouse burn model was established by generating third-degree burn injury in dorsal skin and local LDR less than 100 mGy was delivered to the mice. After 3 or 12 days after burn injury, systemic inflammation in liver, lung, spleen, and kidney and skin wound healing were assessed. For investigation of molecular mechanisms, HaCaT keratinocytes were administrated with serum from mice with burn injury and alteration of viability and cornification biomarkers are assessed. Results In a mouse burn model, expression of proinflammatory cytokines, interleukin (IL)-1β, IL-6, and tumor necrosis factor-α, were downregulated by LDR in major organs and wound healing capacity was increased by LDR. In skin tissue, we observed the alleviation of reactive oxygen species generation and increased antioxidant gene expression by LDR. In addition, we found that treatment of serum from mice with burn injury and LDR increased proliferation and cornification in HaCaT cells through activation of focal adhesion kinase signaling pathway. Conclusion LDR could reduce proinflammatory signaling pathway and increase skin wound healing after burn injury. Therefore, the present study suggested LDR as a novel treatment for burn injury patients.

Aim: The treatment protocol for supracondylar humeral fracture has mainly been based only on the severity of displacement and percutaneous pinning has been recommend as a first treatment. However, a long oblique fracture line is difficult to fix by the traditional cross pinning. The purpose of this study is to assess the prevalence of high-long oblique supracondylar humeral (HLO) fracture and evaluate the surgical outcome of percutaneous pin fixation.Methods: We reviewed 690 children who had undergone an operation for the displaced supracondylar humeral fracture. HLO fracture was defined as having a fracture line starting from either cortex above the metaphyseal-diaphyseal junction and finishing at the opposite cortex around or below the olecranon fossa. Clinical and radiographic parameter outcomes were assessed.Results: There were 14 patients diagnosed with the HLO fracture (14/690) and all the patients were treated by pin fixation. The median age was 5 years 1 month (range, 2–11 years). The common mode of injury was direct contact injury to the elbow. There were 6 patients with lateral HLO fracture, and 8 patients had medial HLO type. In medial HLO type, medial pinning only was done in 3 patients due to the difficulty in lateral pin insertion. In addition, the lateral pin was not a bicortical fixation through capitellum entry in 2 patients who had it fixed by cross pinning. The final Baumann angle and lateral humero-capitellar angle were 20.5 (5–67.6) degrees and 49.3 (23.3–71.9) degrees, respectively, without statistical significance compared to the normal side. Flynn's cosmetic grade showed satisfactory results in all patients.Conclusion: The prevalence of HLO fractures was 2% in the displaced supracondylar humeral fracture. The mechanism of injury of HLO fractures may be direct contact injury. In medial HLO fractures, medial pinning is important for stability, and sometimes lateral pinning was impossible. Contrarily, lateral HLO fracture could easily be fixed by lateral-only pinning, but the correct lateral pinning is necessary because medial pinning is difficult. The HLO fracture is a difficult pattern to treat by traditional percutaneous pinning and another surgical option should be considered.

Scalding water is the most common cause of burn injury in both elderly and young populations. It is one of the major clinical challenges because of the high mortality and sequelae in low- and middle-income countries. Burns frequently induce intense spontaneous pain and persistent allodynia as well as life-threatening problem. More importantly, excessive pain is often accompanied by depression, which may significantly decrease the quality of life. This article shows how to develop an animal model for the study of burn-induced pain and depression-like behavior. After anesthesia, burn injury was induced by dipping one hind paw of the mouse into hot water (65 °C ± 0.5 °C) for 3 s. The von Frey test and automated gait analysis were performed every 2 days after burn injury. In addition, depression-like behavior was examined using the forced swimming test, and the rota-rod test was performed to differentiate the abnormal motor function after burn injury. The main purpose of this study is to describe the development of an animal model for the study of burn injury-induced pain and depression-like behavior in mice.

PURPOSE We investigated the moderating effect of sleep disturbance on the association between seizure recurrence and emotional instability in patients with epilepsy, independent of psychological distress. METHODS This was a cross-sectional study. Patients completed the short form of the Affective Lability Scale (ALS-18), Insomnia Severity Index (ISI), Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder-7 (GAD-7). A stepwise linear regression analysis and an analysis of covariance with an interaction term were performed. RESULTS A total of 171 subjects (63.2% men) were included. The mean ALS-18 score was 15.6 ± 11.3. An ISI ≥ 15, PHQ-9 ≥ 10, and GAD-7 ≥ 7 were noted in 20.5%, 18.1%, and 23.4% of subjects, respectively. A stepwise linear regression analysis found that recurrent seizures in the last year, an ISI ≥ 15, a GAD-7 ≥ 7, and use of levetiracetam were significant and independent factors that were positively associated with higher ALS-18 scores. The coefficient of determination for the model was 0.331. The interaction between recurrent seizures and an ISI ≥ 15 had a significant effect on the ALS-18 scores (F = 6.812, p = 0.010, partial eta2 = 0.040). An ISI ≥ 15 was associated with ALS-18 scores in patients without seizure recurrence (p

Background and Purpose. Although acute meningitis and encephalitis are known to cause cognitive dysfunction, the prognostic values of neuropsychological and neurophysiological tests in predicting clinical outcomes are seldom studied. We investigated specific neurocognitive dysfunction and event-related potentials (ERPs), which can predict functional outcomes in patients with acute meningitis and encephalitis. Methods. We enrolled consecutive adult patients with acute meningitis and encephalitis and performed neuropsychological tests and ERP studies using a passive auditory oddball paradigm at enrollment. Patient functional outcomes were assessed using the Glasgow Outcome Scale at 6 (GOS6) months after discharge. Results. Twenty-two patients were included in the study. Among 21 patients who performed neuropsychological tests, Korean-Trail Making Test-Elderly's version, Part A time (TMT-A time) correlated with GOS6, which remained significant even after controlling for age. We identified a significant association between TMT-A time and P3a latency. Post-hoc analysis showed that patients with longer TMT-A time (≥23 s) tended to have longer P3a latency than those with shorter TMT-A time. Conclusions. Decreased psychomotor speed predicted poor clinical outcomes. Because TMT-A time can be performed at the bedside in a relatively short time, this might be a useful neuropsychological biomarker to predict or monitor clinical outcomes. Furthermore, passive oddball P3a may be useful in patients with more severe disease who are unable to perform the TMT task.

Aim: Spinal cord injury (SCI)-related flaccid paralysis may result in a debilitating hyperlordosis associated with a progressive hip flexion contracture. The aim of this study was to evaluate the correction of hip flexion contractures and lumbar hyperlordosis in paraplegic patients that had a history of spinal cord injuries.Methods: A retrospective review was performed on 29 hips of 15 consecutive patients who underwent corrective surgeries for severe hip flexion deformity from 2006 to 2018. The mean age at surgery was 10.1 years (2.7 to 15.8), and the mean follow-up was 68 months (7 to 143). Relevant medical, surgical, and postoperative information was collected from the medical records and radiographs.Results: Improvements were seen in the mean hip flexion contracture (p < 0.001) with 100% hip correction at surgery and 92.1% at the latest follow-up. Mean lumbar lordosis decreased (p = 0.029) while the mean Cobb angle increased (p = 0.001) at the latest follow up. Functional score subdomains of the Spinal Cord Independence Measure, Functional Independence Measure, and modified Barthel activities of daily living (ADL) scores remained the same at the final follow-up.Conclusion: For paraplegic SCI patients, we found an association between treating the hip flexion contracture and indirect correction of their lumbar hyperlordosis. We recommend the surgeon carefully examine the hip pathology when managing SCI-related spinal deformities, especially increased lumbar lordosis.

Background Spontaneous intracranial hypotension and post-dural puncture headache are both caused by a loss of cerebrospinal fluid but present with different pathogeneses. We compared these two conditions concerning their clinical characteristics, brain imaging findings, and responses to epidural blood patch treatment. Methods We retrospectively reviewed the records of patients with intracranial hypotension admitted to the Neurology ward of the Pusan National University Hospital between January 1, 2011, and December 31, 2019, and collected information regarding age, sex, disease duration, hospital course, headache intensity, time to the appearance of a headache after sitting, associated phenomena (nausea, vomiting, auditory symptoms, dizziness), number of epidural blood patch treatments, and prognosis. The brain MRI signs of intracranial hypotension were recorded, including three qualitative signs (diffuse pachymeningeal enhancement, venous distention of the lateral sinus, subdural fluid collection), and six quantitative signs (pituitary height, suprasellar cistern, prepontine cistern, mamillopontine distance, the midbrain-pons angle, and the angle between the vein of Galen and the straight sinus). Results A total of 105 patients (61 spontaneous intracranial hypotension patients and 44 post-dural puncture headache patients) who met the inclusion criteria were reviewed. More patients with spontaneous intracranial hypotension required epidural blood patch treatment than those with post-dural puncture headache (70.5% (43/61) vs. 45.5% (20/44); p = 0.01) and the spontaneous intracranial hypotension group included a higher proportion of patients who underwent epidural blood patch treatment more than once (37.7% (23/61) vs. 13.6% (6/44); p = 0.007). Brain MRI showed signs of intracranial hypotension in both groups, although the angle between the vein of Galen and the straight sinus was greater in the post-dural puncture headache group (median [95% Confidence Interval]: 85° [68°-79°] vs. 74° [76°-96°], p = 0.02). Conclusions Patients with spontaneous intracranial hypotension received more epidural blood patch treatments and more often needed multiple epidural blood patch treatments. Although both groups showed similar brain MRI findings, the angle between the vein of Galen and the straight sinus differed significantly between the groups.

In recent years, it has been shown that intense THz pulses are powerful tools to manipulate, deflect or accelerate ultrashort electron bunches. The THz range is of interest, since the corresponding wavelengths are well-matched to a typical electron bunch size of several tens of microns. Here, we propose to use split-ring resonators (SRR) as key-elements to realize various tasks in electron accelerators. Through a judicious choice of shape and geometry these structure exhibit a considerable near-field enhancement, boosting the incident THz field strength by a factor of ten or more.

In actual industrial sites, the ability of the deep learning model to detect defects at a high speed and reducing the time required to train the model is also a very important issue. In this paper, we propose a fast and accurate deep learning model and training method that can be applied to inspect the TFT-LCD(The Film Transistor - Liquid Crystal Display) PAD area image. The deep learning model we propose is a lightweight model based on U-net. By training only about 250,000 parameters, it was possible to confirm excellent performance in defect segmentation. In addition, a study on train data was also conducted so that the model can learn more effectively. We studied a method of training both normal images (images without defects) and abnormal images (images with defects), and it was confirmed that this performance showed better performance than when only data with defects were learned. It was shown that the method of learning both normal and abnormal results in a 50% or more reduction in the incidence of false judgment images than the method of learning only simple abnormal data.

Background: The pathophysiology of migraine has been researched incessantly, and it has been suggested that calcitonin gene-related peptide (CGRP) is associated with migraine attacks. CGRP receptor blockers are attracting attention for migraine prevention and treatment of acute episodes, and CGRP receptor antagonists have been shown to be effective in treating acute migraine headaches. This meta-analysis aimed to assess the effect of available CGRP receptor antagonists, focusing on their therapeutic doses for acute migraine treatment.Methods: We performed a systematic search of MEDLINE (from inception to March 2021) and EMBASE (from inception to March 2021) for English publications using the keywords “migraine” and “Calcitonin gene-related peptide,” limited to human studies.Results: Five studies that focused on examining the effects of CGRP receptor antagonists on acute migraine treatment met the eligibility criteria for this meta-analysis. The pooled analysis demonstrated that the CGRP receptor antagonist improved freedom from pain (OR=2.066, 95% confidence interval [CI] 1.766–2.418, I2=0%), absence of bothersome symptoms (OR=1.606, 95% CI=1.408–1.830, I2=0%), pain relief (OR=1.791, 95% CI=1.598–2.008, I2=0%), and freedom from nausea (OR=1.361, 95% CI=1.196–1.548, I2=0%), significantly more than the placebo. Conclusions: CGRP receptor antagonists are effective for acute migraine treatment and are expected to be used clinically as emerging therapeutic agents.

Although there are many patients with brain tumors worldwide, there are numerous difficulties in overcoming brain tumors. Among brain tumors, glioblastoma, with a 5-year survival rate of 5.1%, is the most malignant. In addition to surgical operations, chemotherapy and radiotherapy are generally performed, but the patients have very limited options. Temozolomide is the most commonly prescribed drug for patients with glioblastoma. However, it is difficult to completely remove the tumor with this drug alone. Therefore, it is necessary to discuss the potential of anticancer drugs, other than temozolomide, against glioblastomas. Since the discovery of cisplatin, platinum-based drugs have become one of the leading chemotherapeutic drugs. Although many studies have reported the efficacy of platinum-based anticancer drugs against various carcinomas, studies on their effectiveness against brain tumors are insufficient. In this review, we elucidated the anticancer effects and advantages of platinum-based drugs used in brain tumors. In addition, the cases and limitations of the clinical application of platinum-based drugs are summarized. As a solution to overcome these obstacles, we emphasized the potential of a novel approach to increase the effectiveness of platinum-based drugs.

Paradoxical reactions during the treatment of tuberculous meningitis indicate the worsening of pre-existing tuberculous lesions or the appearance of new tuberculous lesions in patients who initially showed improvement after anti-tuberculosis treatment.1 High-dose corticosteroid therapy is the most preferred first-line treatment, but there is no definite consensus on the management of paradoxical reactions when corticosteroids have failed. Here, we report successful treatment of a tuberculosis meningitis patient with corticosteroid-refractory paradoxical reaction using anti-tissue necrosis factor α (anti-TNF-α) therapy.