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Abstract Out of practicality, ambient air rather than oxygen is preferred as a fuel in electrochemical systems, but CO2 and H2O present in air cause severe irreversible reactions, such as the formation of carbonates and hydroxides, which typically degrades performance. Herein, we report on a Na-air battery enabled by a reversible carbonate reaction (Na2CO3·xH2O, x = 0 or 1) in Nasicon solid electrolyte (Na3Zr2Si2PO12) that delivers a much higher discharge potential of 3.4 V than other metal-air batteries resulting in high energy density and achieves > 86 % energy efficiency at 0.1 mA cm−2 over 100 cycles. This cell design takes advantage of moisture in ambient air to form an in-situ catholyte via the deliquescent property of NaOH. As a result, not only reversible electrochemical reaction of Na2CO3·xH2O is activated but also its kinetics is facilitated. Our results demonstrate the reversible use of free ambient air as a fuel, enabled by the reversible electrochemical reaction of carbonates with a solid electrolyte.

In this paper, a new design of concatenated polar codes is proposed. By concatenating an outer code with polar codes, the distance spectrum can be improved, leading to enhanced decoding performance of vanilla polar codes. In the 5G New Radio standard, both cyclic redundancy check precoding and systematic single-parity-check precoding schemes are adopted and this combination provides stable decoding performance over a wide range of coding parameters. We focus on the design of single-paritycheck precoded polar codes. For the special systematic pre-coding scheme, code construction depends solely on the selection of information and parity bits from the source bits. Since the conventional parity bit selection criteria can draw weaknesses for some coding parameters, we develop new criteria that enhance the protection of weak source bits under the successive cancelation decoding. The simulation results demonstrate that the proposed design consistently outperforms the conventional one across a wide range of coding parameters. The improvement is more pronounced in short-length codes.

Non-linearities and unmodeled dynamics in the control system inevitably degrade the quality and reliability of voltage stabilization performance in DC-DC buck converters. Reinforcement Learning (RL) is an emerging method to mitigate this issue. However, traditional RL typically necessitates significant computational resources and specialized processing units, thus being an economically unreasonable option. This paper proposes a high-performance RL-based method even suitable for a cost-effective Digital Signal Processor (DSP). To address the significant challenge of time delay in a DSP when training the RL agent, this paper adopts a Real-Time Deep Reinforcement Learning (RTDRL) approach that creates an augmented virtual decision process to eliminate the delay effect. The performance is validated through software simulation (PLECS) and an actual system, through which the proposed approach demonstrated superior performance compared to existing benchmarks, including existing approaches and artificial intelligence.

The central perspective of this review is to categorize research in Human Motion Recognition (HMR) over the past decade into two significant categories: vision sensor-based (VS) methods and wearable sensor-based (WS) methods. Within each category, research is further assessed from the viewpoints of sensors, classification algorithms, datasets, gesture types, target body parts, and performance. This approach allows for a comprehensive assessment of the overall research trends and technological advancements in HMR. Both VS methods and WS methods present their own sets of advantages and challenges. VS methods face challenges related to limited workspace, varying lighting conditions, occlusion, and complex image processing. Conversely, WS methods, compared to VS methods, deals with challenges associated with multiple sensor calibration, intrusiveness, and magnetic field mapping due to sensor placement. As such, the choice between these methods depends on the specific application, the required level of accuracy, and user preferences. Gaining insights into the nature of various HMR methods and staying informed about recent research trends is of utmost importance. By the end of this review, readers will gain a comprehensive and systematic understanding of the latest developments in HMR techniques, which will serve as a valuable resource for researchers and practitioners alike.

In the past 30 years, the number of years lived with disability due to osteoarthritis (OA) has doubled, making it an increasing global health burden. To address this issue, interventions that inhibit the progressive pathology driven by age-related low-grade inflammation, the primary mechanism of OA, are being actively pursued. Recent investigations have focused on modulating the age-related low-grade inflammatory pathology of this disease as a therapeutic target. However, no agent has successfully halted the disease’s progression or reversed its irreversible course. Reynoutria japonica Houtt. (RJ), a promising East Asian herbal medicine, has been utilized for several diseases due to its potent anti-inflammatory activity. This study aims to determine RJ’s capacity to inhibit OA symptoms and associated inflammation, exploring its potential for further development. In vivo and in vitro experiments demonstrated RJ’s anti-OA activity and modulation of multifaceted inflammatory targets. RJ significantly inhibited pain, gait deterioration, and cartilage destruction in a monosodium iodoacetate-induced OA rat model, with its analgesic effect further confirmed in an acetic acid-induced writhing model. RJ exhibited consistent anti-inflammatory activity against multiple targets in serum and cartilage of the OA rat model and lipopolysaccharide-induced RAW 264.7 cells. The inhibition of inflammatory cytokines, including interleukin-1β, interleukin-6, matrix metalloproteinase-13, tumor necrosis factor-α, and nitric oxide synthase 2, suggests that RJ’s alleviation of OA manifestations relates to its multifaceted anti-inflammatory activity. These results indicate that RJ merits further investigation as a disease-modifying drug candidate targeting OA’s inflammatory pathology. To further characterize the pharmacological properties of RJ, future studies with expanded designs are warranted.

Osteoarthritis (OA) is an age-related disease characterized by inflammation, pain, articular cartilage damage, synovitis, and irreversible disability. Gynostemma pentaphyllum (Thunb.) Makino (GP), a herbal medicine traditionally used in East Asia for its anti-inflammatory properties, was investigated for its potential to modulate OA pathology and symptoms. This study evaluated GP’s efficacy in inhibiting pain, functional decline, and cartilage destruction in monosodium iodoacetate-induced OA and acetic acid-induced writhing models. Additionally, the effects of GP on OA-related inflammatory targets were assessed via mRNA and protein expression in rat knee cartilage and lipopolysaccharide-induced RAW 264.7 cells. The GP group demonstrated significant pain relief, functional improvement, and cartilage protection. Notably, GP inhibited key inflammatory mediators, including interleukin (IL)-1β, IL-6, matrix metalloproteinases (MMP)-3 and MMP-13, cyclooxygenase-2, and prostaglandin E receptor 2, surpassing the effects of active controls. These findings suggest that GP is a promising candidate for disease-modifying OA drugs and warrants further comprehensive studies.

This study presents a framework for enabling autonomous pick–place operations, addressing the need for efficiency in complex logistics environments using a direct multi-target teaching interface. First, tag and segmentation information were combined to recognize products in a complex warehouse, and a camera was installed on the rack to allow workers to remotely see the work environment, allowing workers to view the work environment in real time through a tablet. Workers can access the camera view showing the rack containing the target product through a swiping action and select the target product through direct teaching action. When the target product is finally selected, an optimal path is created through task planning, and an autonomous pick–place operation is performed based on the generated path. As a result of conducting a usability evaluation using the SUS (System Usability Scale) with six users on the interface that enables these tasks, it was confirmed that high user satisfaction was achieved with an average of 77.5 points. In conclusion, the proposed interface enhances operational efficiency and provides a user-friendly solution for complex warehouse tasks.

Psoriasis is a chronic, immune-mediated inflammatory skin disease with many complications and a poor prognosis that imposes a significant burden on individuals and society. Narrowband ultraviolet B (NB-UVB) represents a cost-effective non-drug therapeutic intervention for psoriasis. East Asian herbal medicine (EAHM) is currently being investigated for its potential as a safe and effective psoriasis treatment. Consequently, it has the potential to be employed as a combination therapy with NB-UVB. The objective was to ascertain the efficacy and safety of the EAHM with NB-UVB combination therapy and to identify important drugs for further research. In this study, randomized controlled trials (RCTs) were retrieved from ten databases in Korea, China, and Japan. All statistical analyses were conducted using R software version 4.3.0. The primary outcomes were the Psoriasis Area and Severity Index (PASI) and the incidence rate of adverse events (AEs), while the secondary outcomes were hematologic markers and the Dermatology Life Quality Index (DLQI), which reflect the immune-mediated inflammatory pathology of psoriasis. The analysis of 40 RCTs, including 3521 participants, demonstrated that EAHM with NB-UVB combination therapy exhibited a statistically significant superiority over NB-UVB monotherapy with respect to primary and secondary outcomes. The Bayesian network meta-analysis revealed that Investigator Presciption 3 and Ziyin Liangxue Decoction exhibited a consistent relative advantage with respect to each PASI-based efficacy metric. The network analysis estimated the potential influence ranking for all individual herbs according to PageRank centrality. The findings of this study suggest that EAHMs co-administered with NB-UVB may provide additional efficacy and safety-related benefits for patients with psoriasis. However, the quality of evidence is still low, and further high-quality trials are needed to reach more definitive conclusions.

Background: We evaluated changes in the smartphone use rate and time among Korean adolescents and their awareness of associated health problems. Methods: This study was a secondary analysis of the Korea Youth Risk Behavior Survey (2020–2023) conducted by the Korean Disease Control and Prevention Agency. The total number of enrolled adolescents aged 12–18 years was 214,526. Results: The weekly smartphone usage rate increased from 96.4% to 97.1% (p = 0.03), with no significant changes observed in weekend usage. The average smartphone use time was 4.7 h on weekdays (p = 0.17) and 6.6 h on weekends (p = 0.37). Middle school adolescents had a higher weekday use rate than high school adolescents, but the average smartphone use time was significantly less. By 2023, the proportion of adolescents with overdependence was 28% (n = 14,672). Additionally, 11.8% (n = 6255) responded that they had experienced health problems due to smartphone use. Conclusions: The longer they used their smartphones for on the weekends, the more likely they considered their health to be worse. In conclusion, our youth population needs to be educated on the proper use of smartphones.

Bone health is a critical aspect of overall well-being, and disorders such as osteoporosis pose significant challenges worldwide. East Asian Herbal Medicine (EAHM), with its rich history and holistic approach, offers promising avenues for enhancing bone regeneration. In this critical review article, we analyze the intricate mechanisms through which EAHM compounds modulate bone health. We explore the interplay between osteogenesis and osteoclastogenesis, dissect signaling pathways crucial for bone remodeling and highlight EAHM anti-inflammatory effects within the bone microenvironment. Additionally, we emphasize the promotion of osteoblast viability and regulation of bone turnover markers by EAHM compounds. Epigenetic modifications emerge as a fascinating frontier where EAHM influences DNA methylation and histone modifications to orchestrate bone regeneration. Furthermore, we highlight EAHM effects on osteocytes, mesenchymal stem cells and immune cells, unraveling the holistic impact in bone tissue. Finally, we discuss future directions, including personalized medicine, combinatorial approaches with modern therapies and the integration of EAHM into evidence-based practice.

Osteoarthritis (OA), characterized by chronic pain and joint degradation, is a progressive joint disease primarily induced by age-related systemic inflammation. Angelica gigas Nakai (AG), a medicinal plant widely used in East Asia, exhibits promising results for such conditions. This study aimed to evaluate the potential of AG as a drug candidate for modulating the multifaceted pathology of OA based on its anti-inflammatory properties. We evaluated the efficacy of AG in pain relief, functional improvement, and cartilage erosion delay using monosodium iodoacetate-induced OA rats and acetic acid-induced writhing mice, along with its anti-inflammatory effects on multiple targets in the serum and cartilage of in vivo models and lipopolysaccharide-stimulated RAW 264.7 cells. In vivo experiments demonstrated significant analgesic and chondroprotective effects of AG, along with functional recovery, in model animals compared with the active controls. AG dose-dependently modulated inflammatory OA pathology-related targets, including interleukin-1β, tumor necrosis factor-α, matrix metalloproteinase-13, and cyclooxygenase-2, both in vitro and in vivo. In conclusion, AG could be a potential drug candidate for modulating the multifaceted pathology of OA. Nevertheless, further comprehensive investigations, involving a broader range of compounds, pathologies, and mechanisms, are warranted to validate these findings.

The most widely used synthetic glucocorticoid, dexamethasone (DEX), causes stunted growth in children when used excessively or for long periods of time; however, there are still plenty of pediatric patients require long-term treatment with DEX. As an alternative, growth hormone is used in combination, but it has side effects, a high cost, and psychological factors, and it is not satisfactory in terms of effectiveness. It is necessary to develop a safe and affordable treatment that can replace it. The Korean Food and Drug Administration approved HT042, a standardized functional food ingredient, with the claim that it can help height growth of children. In this study, it was found that HT042 activated the Indian hedgehog/parathyroid hormone-related protein signaling pathway and enhanced the number of growth hormone receptors and insulin-like growth factor-1 receptors on the growth plate surface, which were reduced by DEX treatment, and restored growth retardation. In metatarsal bone and primary chondrocyte models, it was found that HT042 can promote the length of growth plate and recover DEX-induced growth retardation. It was also found that HT042 promotes cell proliferation using bromodeoxyuridine and terminal deoxynucleotidyl transferase dUTP nick end labeling assays; moreover, we verified increased expression of GHR/IGF-1R and Ihh/PTHrP pathway activity using qRT-PCR, western blotting, and siRNA analyses to verify its direct action on the growth plate. The anti-apoptotic effect of HT042 was identified by regulating the expression of apoptotic factors such as caspase-3, Bcl2, Bclx, and Bax. These results were identified using both ex vivo and in vitro models. Our study verified that co-administration of HT042 could recover the DEX induced growth retardation

PurposeTo investigate changes in vertical strabismus and extorsion in patients with intermittent exotropia and mild unilateral inferior oblique muscle overaction (IOOA) who underwent horizontal muscle surgery without vertical or oblique muscle surgery.MethodsThe medical records of 41 patients were retrospectively analyzed. The patients were followed up for at least 6 months after surgery. Fundus photography was performed before and after surgery, and the sum of the angles of torsion in both eyes was used to measure changes in extorsion using ImageJ software. The enrolled patients were divided into two groups according to the degree of IOOA: patients with grade 1 IOOA were placed in +1 IOOA group and those with grade 2 IOOA in +2 IOOA group. The pre- and postoperative angles of horizontal and vertical strabismus and extorsion were compared between the two groups.ResultsThe +1 IOOA and +2 IOOA groups included 24 and 17 patients, respectively. The angle of preoperative exotropia did not differ significantly: 25.54 ± 5.68 prism diopters (PD) and 25.65 ± 8.11 PD in the +1 IOOA and +2 IOOA groups, respectively. In the +1 IOOA and +2 IOOA groups, hypertropia was 2.67 ± 1.52 PD and 2.82 ± 1.13 PD, respectively, and extorsion angles were 7.14 ± 2.77° and 7.94 ± 2.87°, respectively. As the IOOA degree increased, the extent of hypertropia and extorsion also increased. However, there were no significant differences between the two groups. Postoperative angles of hypertropia and extorsion significantly decreased in both groups (p < 0.001) after surgery. The degree of change in hypertropia and extorsion was not significantly different between the two groups (p = 0.563 and p = 0.354, respectively).ConclusionsHypertropia and extorsion improved significantly after horizontal muscle surgery in patients with mild unilateral IOOA and intermittent exotropia. There was no significant difference in the improvement in hypertropia or extorsion between IOOA grades I and II.

Osteoarthritis (OA) is characterized by irreversible joint destruction, pain, and dysfunction. Piper longum L. [Piperaceae] (PL) is an East Asian herbal medicine with reported anti-inflammatory, analgesic, antioxidant, anti-stress, and anti-osteoporotic effects. This study aimed to evaluate the efficacy of PL in inhibiting pain and progressive joint destruction in OA based on its anti-inflammatory activity, and to explore its potential mechanisms using in vivo and in vitro models of OA. We predicted the potential hub targets and signaling pathways of PL through network analysis and molecular docking. Network analysis results showed that the possible hub targets of PL against OA were F2R, F3, MMP1, MMP2, MMP9, and PTGS2. The molecular docking results predicted strong binding affinities for the core compounds in PL: piperlongumine, piperlonguminine, and piperine. In vitro experiments showed that PL inhibited the expression of LPS-induced pro-inflammatory factors, such as F2R, F3, IL-1β, IL-6, IL-17A, MMP-1, MMP-2, MMP-3, MMP-9, MMP-13, NOS2, PTGS2, PGE2, and TNF-β. These mechanisms and effects were dose-dependent in vivo models. Furthermore, PL inhibited cartilage degradation in an OA-induced rat model. Thus, this study demonstrated that multiple components of PL may inhibit the multilayered pathology of OA by acting on multiple targets and pathways. These findings highlight the potential of PL as a disease-modifying OA drug candidate, which warrants further investigation.

Osteoarthritis (OA) is a degenerative bone disease characterized by inflammation as a primary pathology and currently lacks therapeutic interventions to impede its progression. Erigeron breviscapus (Vant.) Hand.-Mazz. (EB) is an east Asian herbal medicine with a long history of use and a wide range of confirmed efficacy against cardiovascular and central nervous system diseases. The purpose of this study is to evaluate whether EB is worthy of further investigation as a treatment for OA based on anti-inflammatory activity. This study aims to assess the potential of EB as a treatment for OA, focusing on its anti-inflammatory properties. Analgesic effects, functional improvements, and inhibition of cartilage destruction induced by EB were evaluated in acetic acid-induced peripheral pain mice and monosodium iodoacetate-induced OA rat models. Additionally, the anti-inflammatory effect of EB was assessed in serum and cartilage tissue in vivo, as well as in lipopolysaccharide-induced RAW 264.7 cells. EB demonstrated a significant alleviation of pain, functional impairment, and cartilage degradation in OA along with a notable inhibition of pro-inflammatory cytokines, including interleukin-1β, interleukin-6, matrix metalloproteinases 13, and nitric oxide synthase 2, both in vitro and in vivo, in a dose-dependent manner compared to the active control. Accordingly, EB merits further exploration as a potential disease-modifying drug for OA, capable of mitigating the multifaceted pathology of osteoarthritis through its anti-inflammatory properties. Nonetheless, additional validation through a broader experimental design is essential to substantiate the findings of this study.

In recent years, there has been a trend toward expanding the operating frequency range and increasing the output power of Sound Navigation and Ranging (SONAR) systems to enhance their acoustic detection capabilities. However, due to this increase in operational power, the electrical capacity of amplifiers for SONAR system operation also increases, necessitating High-Power Amplifiers. When configured with a single amplifier, as in conventional methods, the volume of amplifiers increases due to volumetric increases in heat dissipation, components, and windings. These issues are detrimental to SONAR amplifier installation, mobility, maintenance, and equipment lifespan due to stress on individual components. Additionally, amplifiers for SONAR systems are comprised of power conversion devices, transformers for LC filters and matching, necessitating consideration of LC filters and matching transformers for enhancing voltage quality and efficiency to improve amplifier performance transmitted to SONAR transducers. However, previous research has focused on single-amplifier design methods, neglecting such considerations. Therefore, this paper proposes a design technique that overcomes the drawbacks of using the conventional design method by configuring multiple H-bridge inverters in a cascade format and utilizes one of the optimization algorithms, Particle Swarm Optimization (PSO), to derive amplifier design techniques that optimize component parameters for enhancing high-capacity amplifier performance. Subsequently, theoretical analysis, simulations, and experimental results comparing the proposed high-power amplifier design method with conventional single-amplifier design methods demonstrate similar error rates in operational frequency bands.

Inertial Measurement Unit (IMU) sensor-based gait phase recognition is widely used in medical and biomechanics fields requiring gait data analysis. However, there are several limitations due to the low reproducibility of IMU sensor attachment and the sensor outputs relative to a fixed reference frame. The prediction algorithm may malfunction when the user changes their walking direction. In this paper, we propose a gait phase recognition method robust to user body movements based on a floating body-fixed frame (FBF) and bi-directional long short-term memory (bi-LSTM). Data from four IMU sensors attached to the shanks and feet on both legs of three subjects, collected via the FBF method, are processed through preprocessing and the sliding window label overlapping method before inputting into the bi-LSTM for training. To improve the model’s recognition accuracy, we selected parameters that influence both training and test accuracy. We conducted a sensitivity analysis using a level average analysis of the Taguchi method to identify the optimal combination of parameters. The model, trained with optimal parameters, was validated on a new subject, achieving a high test accuracy of 86.43%.

Osteoarthritis is the most common type of arthritis, characterized by joint pain and a decline in physiological function. Scutellaria baicalensis Georgi (SB) is potentially effective against osteoarthritis because of its wide range of anti-inflammatory pharmacological activities. This study aimed to identify the mode of action of SB against osteoarthritis using network pharmacology prediction and experimental verification. Networks were constructed to key compounds, hub targets, and pathways essential for SB’s effectiveness against osteoarthritis. Additionally, in vivo and in vitro tests were performed, including investigations on weight bearing in hind limbs, the acetic acid-induced writhing response, lipopolysaccharide-stimulated RAW264.7 cells, and serum cytokine responses. We identified 15 active compounds and 14 hub targets, supporting the anti-osteoarthritis effects of SB. The Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that fluid shear stress, atherosclerosis, phosphatidylinositol 3-kinase-Akt signaling, and cellular senescence pathways were important. SB showed substantial anti-inflammatory, analgesic, and joint tissue-protective effects against osteoarthritis. Our study shows that SB has the potential value to be further investigated as a candidate material for the treatment of osteoarthritis in the future.

Power generation companies, which participate in the electricity trading mechanism, need to determine optimal capacity bidding strategy to maximize their operational profit in Korea. Since the Price-setting Power Generation Schedule determines the profit of power generators, it is important to predict Price-setting Scheduled Energy during the trading day before the bidding phase. We propose a methodology for predicting the Pricing-setting Scheduled Energy from the power exchange without optimizing it. Instead of simulating the planning process, machine learning algorithms are applied and compared in the process of predicting the Pricing-setting Scheduled Energy. The input variables consist of seasonal and price information including calendar, fuel cost, and system marginal price. Three categories of machine learning (ML) algorithms including single, bagging and boosting approaches are implemented and tested to compare their performances. The computational experiments show that ML algorithms with price variable are shown to be better in terms of the considered measures. In addition, boosting approach is more effective than single and bagging approaches.

This study introduces a framework to improve upper extremity motion-based telemanipulation by component-wise rescaling (CWR) of spatial twist. This method allows for separate adjustments of linear and angular scaling parameters, significantly improving precision and dexterity even when the operator’s heading direction changes. By finely controlling both the linear and angular velocities independently, the CWR method enables more accurate telemanipulation in tasks requiring diverse speed and accuracy based on personal preferences or task-specific demands. The study conducted experiments confirming that operators could precisely control the robot gripper with a steady, controlled motion even in confined spaces, irrespective of changes in the subject’s body-heading direction. The performance evaluation of the proposed motion-scaling-based telemanipulation leveraged Optitrack’s motion-capture system, comparing the trajectories of the operator’s hand and the manipulator’s end effector (EEF). This verification process solidified the efficacy of the developed framework in enhancing telemanipulation performance.

As the scale of electricity consumption grows, the peak electricity consumption prediction of campus buildings is essential for effective building energy system management. The selection of an appropriate model is of paramount importance to accurately predict peak electricity consumption of campus buildings due to the substantial variations in electricity consumption trends and characteristics among campus buildings. In this paper, we proposed eight deep recurrent neural networks and compared their performance in predicting peak electricity consumption for each campus building to select the best model. Furthermore, we applied an attention approach capable of capturing long sequence patterns and controlling the importance level of input states. The test cases involve three campus buildings in Incheon City, South Korea: an office building, a nature science building, and a general education building, each with different scales and trends of electricity consumption. The experiment results demonstrate the importance of accurate model selection to enhance building energy efficiency, as no single model’s performance dominates across all buildings. Moreover, we observe that the attention approach effectively improves the prediction performance of peak electricity consumption.

This paper describes the optimal path planning of a redundant finishing mechanism developed for joint space-based additive-finishing integrated manufacturing (AFM). The research motivation results from an inevitable one-sided layout of a finishing stage (FS) with regard to the additive stage (AS) in the AFM. These two stages share a 2-dof bed stage (BS), and the FS can lightly shave off the rough-surfaced 3D print on the bed. Since the FS located at the side of the AS cannot reach all the target points of the 3D print, the bed should be able to rotate the 3D print about the z-axis and translate it in the z-axis. As a result, the AS has 4-dof joints for 2P and 1P1R during the additive process with AS-BS, and FS has 4-dof and 2-dof integrated joints for 2P2R and 1P1R during the finishing process with FS-BS, respectively. For the kinematic modeling of the FS part and the BS, the virtual linkage connecting the bed frame origin and the FS’s joint frame for approaching the BS is considered to realize seamless kinematic redundancy. The minimum Euclidian norm of the joint velocity space is the objective function to find the optimal joint space solution for a given tool path. To confirm the feasibility of the developed joint path planning algorithm in the proposed FS-BS mechanism, layer-by-layer slicing of a given 3D print’s CAD model and tool path generation were performed. Then, the numerical simulations of the optimal joint path planning for some primitive 3D print geometries were conducted. As a result, we confirmed that the maximum and mean pose error in point-by-point only, with the developed optimal joint path planning algorithm, were less than 202 nm and 153 nm, respectively. Since precision and general machining accuracies in tool path generation are in the range of ±10 μm and 20 μm, the pose error in this study fully satisfies the industry requirements.

Abstract Background To evaluate the effectiveness of resected muscle adjustment compared with the recessed muscle adjustment in patients with intermittent exotropia. Methods This retrospective clinical investigation analyzed the data of patients who underwent strabismus surgery with adjustment. Patients who were followed-up for at least one and half year after adjustment were enrolled. They were divided into two groups; patients who underwent adjustment on recessed lateral rectus muscle (LR-Adj group) and adjustment on resected medial rectus muscle (MR-Adj group). Postoperative changes were compared. Surgical success was defined as horizontal deviation

Abstract This paper analyzes the secrecy outage probability of amplify and forward (AF) relaying with triple selection over real valued Nakagami fading channels. This paper derives the new upper bound cumulative distribution function expressions of the proposed system for the received signal to noise ratio in which maximal ratio combining and selection combining receivers are considered. Further, this paper derives the lower bound and asymptotic expressions for the secrecy outage probability. An interesting numerical result is that the secrecy performance of the AF relaying with selection combining is superior to the AF relaying with maximal ratio combining over arbitrary Nakagami fading channels.

Summary: Accurate spatiotemporal control of multicellular self-organization by various signaling pathways is essential for developmental stages. In particular, evolutionarily conserved Wnt signaling serves as a major morphogenetic switch to determine the anteroposterior axis of the embryo. Here, we developed a genetically encoded optochemogenetic Wnt switch, named optochemoWnt, by coupling a blue light-inducible CRY2olig and rapamycin-inducible LRP6c clustering. The rationally designed optochemoWnt successfully modulated Wnt signaling with AND-gated patterns and demonstrated an improved signal-to-noise ratio (SNR). The dual-triggered switch provides a safeguard to prevent signal leakage resulting from ambient light sources under general laboratory conditions. OptochemoWnt expands the molecular toolbox available for the fields of developmental biology and tissue engineering. In addition, the AND-gated strategy of optochemoWnt may be used for other biomedical applications that integrate user defined switch elements with Boolean logic gates.

Osteoarthritis (OA) is a widespread joint disease that affects millions of people worldwide. Conventional treatments for OA, including non-steroidal anti-inflammatory drugs (NSAIDs) and steroids, have a risk of various adverse events, including liver, gastrointestinal, cardiovascular, and kidney disease, which are unsatisfactory in their effectiveness. In this study, Sorbus commixta Hedl. Stem extracts (SCE) were evaluated in animal models as potential inhibitors for the progression of OA. Sorbus commixta Hedl., which was found to have substantial anti-inflammatory and antioxidant activities in earlier investigations, has shown potential as a candidate for OA treatment. To mimic human OA symptoms, male rats were injected using sodium iodoacetate (MIA) in their knee joints. SCE significantly reduced MIA-induced weight-bearing loss in rats after the MIA injection and alleviated cartilage degradation and subchondral bone injury caused by MIA. In addition, SCE administration reduced levels of TNF-α and IL-1β such as pro-inflammatory cytokines in serum, as well as the levels of matrix metalloproteinases (MMPs) such as MMP-1, -3, -8 and -13 in the joint cartilage. SCE significantly inhibited the writhing responses in acetic acid-administered mice and was used to quantify pain. In lipopolysaccharide (LPS)-activated RAW264.7, SCE suppressed NO production and reduced the expression of TNF-α, PGE2, IL-6, IL-1β, MMP1, MMP3, MMP8, and MMP-13. Our study showed that SCE alleviated inflammation and cartilage degradation in arthritis through its anti-inflammatory activities on multiple targets.

This study proposes a telemanipulation framework with two wearable IMU sensors without human skeletal kinematics. First, the states (intensity and direction) of spatial hand-guiding gestures are separately estimated through the proposed state estimator, and the states are also combined with the gesture’s mode (linear, angular, and via) obtained with the bi-directional LSTM-based mode classifier. The spatial pose of the 6-DOF manipulator’s end-effector (EEF) can be controlled by combining the spatial linear and angular motions based on integrating the gesture’s mode and state. To validate the significance of the proposed method, the teleoperation of the EEF to the designated target poses was conducted in the motion-capture space. As a result, it was confirmed that the mode could be classified with 84.5% accuracy in real time, even during the operator’s dynamic movement; the direction could be estimated with an error of less than 1 degree; and the intensity could be successfully estimated with the gesture speed estimator and finely tuned with the scaling factor. Finally, it was confirmed that a subject could place the EEF within the average range of 83 mm and 2.56 degrees in the target pose with only less than ten consecutive hand-guiding gestures and visual inspection in the first trial.

Psoriasis is a chronic inflammatory disease that places a great burden on both individuals and society. The use of East Asian herbal medicine (EAHM) in combination with conventional medications is emerging as an effective strategy to control the complex immune-mediated inflammation of this disease from an integrative medicine (IM) perspective. The safety and efficacy of IM compared to conventional medicine (CM) were evaluated by collecting randomized controlled trial literature from ten multinational research databases. We then searched for important key materials based on integrated drug data mining. Network pharmacology analysis was performed to predict the mechanism of the anti-inflammatory effect. Data from 126 randomized clinical trials involving 11,139 patients were used. Compared with CM, IM using EAHM showed significant improvement in the Psoriasis Area Severity Index (PASI) 60 (RR: 1.4280; 95% CI: 1.3783–1.4794; p < 0.0001), PASI score (MD: −3.3544; 95% CI: −3.7608 to −2.9481; p < 0.0001), inflammatory skin lesion outcome, quality of life, serum inflammatory indicators, and safety index of psoriasis. Through integrated data mining of intervention data, we identified four herbs that were considered to be representative of the overall clinical effects of IM: Rehmannia glutinosa (Gaertn.) DC., Isatis tinctoria subsp. athoa (Boiss.) Papan., Paeonia × suffruticosa Andrews, and Scrophularia ningpoensis Hemsl. They were found to have mechanisms to inhibit pathological keratinocyte proliferation and immune-mediated inflammation, which are major pathologies of psoriasis, through multiple pharmacological actions on 19 gene targets and 8 pathways in network pharmacology analysis. However, the quality of the clinical trial design and pharmaceutical quality control data included in this study is still not optimal; therefore, more high-quality clinical and non-clinical studies are needed to firmly validate the information explored in this study. This study is informative in that it presents a focused hypothesis and methodology for the value and direction of such follow-up studies.

Abstract This paper investigates the impact of a dual‐signal selection (i.e. selection of direct signal and relay signal) and multiple eavesdroppers on secrecy outage probability in cooperative‐relay systems over Nakagami fading channels. This work performs the derivation of the new exact and approximate distributions for the received signal to noise ratio of the dual‐signal selection in analytical forms where maximal‐ratio combining and selection combining are considered in the presence of multiple eavesdroppers. The lower bounds on the secrecy outage probability of the dual‐signal selection are derived for various receiver scenarios over Nakagami fading channels. This paper also quantifies the secrecy diversity order of the proposed scheme and shows that the dual‐signal selection provides a secrecy diversity order gain of λd=mdUMsMu compared to the conventional scheme by the dual‐signal selection. From the numerical results, this work observes that the sharpness of the dual‐signal selection for the secrecy performance curve is improved by the number of user nodes and fading index of the direct signal, while the number of eavesdroppers and fading index of the eavesdropper slightly affect the required signal to noise ratio of the proposed scheme to satisfy the secrecy outage probability.

AbstractThe collaboration productively interacting between multi‐agents has become an emerging issue in real‐world applications. In reinforcement learning, multi‐agent environments present challenges beyond tractable issues in single‐agent settings. This collaborative environment has the following highly complex attributes: sparse rewards for task completion, limited communications between each other, and only partial observations. In particular, adjustments in an agent's action policy result in a nonstationary environment from the other agent's perspective, which causes high variance in the learned policies and prevents the direct use of reinforcement learning approaches. Unexpected social loafing caused by high dispersion makes it difficult for all agents to succeed in collaborative tasks. Therefore, we address a paradox caused by the social loafing to significantly reduce total returns after a certain timestep of multi‐agent reinforcement learning. We further demonstrate that the collaborative paradox in multi‐agent environments can be avoided by our proposed effective early stop method leveraging a metric for social loafing.

Improving the operational efficiency and optimizing the design of sound navigation and ranging (sonar) systems require accurate electrical equivalent models within the operating frequency range. The power conversion system within the sonar system increases power efficiency through impedance-matching circuits. Impedance matching is used to enhance the power transmission efficiency of the sonar system. Therefore, to increase the efficiency of the sonar system, an electrical-matching circuit is employed, and this necessitates an accurate equivalent circuit for the sonar transducer within the operating frequency range. In conventional equivalent circuit derivation methods, errors occur because they utilize the same number of RLC branches as the resonant frequency of the sonar transducer, based on its physical properties. Hence, this paper proposes an algorithm for deriving an equivalent circuit independent of resonance by employing multiple electrical components and particle swarm optimization (PSO). A comparative verification was also performed between the proposed and existing approaches using the Butterworth–van Dyke (BVD) model, which is a method for deriving electrical equivalent circuits.

In this work, preliminary launch opportunities from NARO Space Center to the Sun-Earth Lagrange point are analyzed. Among five different Sun-Earth Lagrange points, L1 and L2 points are selected as suitable candidates for, respectively, solar and astrophysics missions. With high fidelity dynamics models, the L1 and L2 point targeting problem is formulated regarding the location of NARO Space Center and relevant Target Interface Point (TIP) for each different launch date is derived including launch injection energy per unit mass (C3), Right ascension of the injection orbit Apoapsis Vector (RAV) and Declination of the injection orbit Apoapsis Vector (DAV). Potential launch periods to achieve L1 and L2 transfer trajectory are also investigated regarding coasting characteristics from NARO Space Center. The magnitude of the Lagrange Orbit Insertion (LOI) burn, as well as the Orbit Maintenance (OM) maneuver to maintain more than one year of mission orbit around the Lagrange points, is also derived as an example. Even the current work has been made under many assumptions as there are no specific mission goals currently defined yet, so results from the current work could be a good starting point to extend diversities of future Korean deep-space missions.

In this study, we present a classification method for ternary small data using the modified ternary Allen–Cahn (tAC) system. The governing system is the tAC equation with the fidelity term, which keeps the solution as close as possible to the given data. To solve the tAC system with the fidelity term, we apply an operator splitting method. We use an implicit-explicit finite difference method for solving the split equations. To validate the robust and superior performance of the proposed numerical algorithm, we perform the comparison tests with other widely used classifiers such as logistic regression, decision tree, support vector machine, random forest, and artificial neural network for small datasets.

The Astragali Radix–Cinnamomi Ramulus herb-pair (ACP) has been widely used in the treatment of diabetic peripheral neuropathy (DPN) as part of East Asian herbal medicine (EAHM). Eligible randomized controlled trials (RCTs) were identified by searching 10 databases. The outcomes investigated were response rate, sensory nerve conduction velocity (SNCV), and motor nerve conduction velocity (MNCV) in four regions of the body. The compounds in the ACP and their targets of action, disease targets, common targets, and other relevant information were filtered using network pharmacology. Forty-eight RCTs, with 4308 participants, and 16 different interventions were identified. Significant differences were observed in the response rate, MNCV, and SNCV, as all EAHM interventions were superior to conventional medicine or lifestyle modification. The EAHM formula containing the ACP ranked highest in more than half of the assessed outcomes. Furthermore, major compounds, such as quercetin, kaempferol, isorhamnetin, formononetin, and beta-sitosterol, were found to suppress the symptoms of DPN. The results of this study suggest that EAHM may increase therapeutic efficacy in DPN management, and EAHM formulations containing the ACP may be more suitable for improving treatment response rates to NCV and DPN therapy.

Salvia miltiorrhiza (SM) has been used in oriental medicine for its neuroprotective effects against cardiovascular diseases and ischemic stroke. In this study, we investigated the therapeutic mechanism underlying the effects of SM on stroke using a transient middle cerebral artery occlusion (tMCAO) mouse model. Our results showed that SM administration significantly attenuated acute brain injury, including brain infarction and neurological deficits, 3 days after tMCAO. This was confirmed by our magnetic resonance imaging (MRI) study, which revealed a reduction in brain infarction with SM administration, as well as our magnetic resonance spectroscopy (MRS) study, which demonstrated the restoration of brain metabolites, including taurine, total creatine, and glutamate. The neuroprotective effects of SM were associated with the reduction in gliosis and upregulation of inflammatory cytokines, such as interleukin-6 (IL-6) and Tumor necrosis factor-α (TNF-α), along with the upregulation of phosphorylated STAT3 in post-ischemic brains. SM also reduced the levels of 4-Hydroxynonenal (4-HNE) and malondialdehyde (MDA), which are markers of lipid peroxidation, induced by oxidative stress upregulation in the penumbra of the tMCAO mouse brain. SM administration attenuated ischemic neuronal injury by inhibiting ferroptosis. Additionally, post-ischemic brain synaptic loss and neuronal loss were alleviated by SM administration, as demonstrated by Western blot and Nissl staining. Moreover, daily administration of SM for 28 days after tMCAO significantly reduced neurological deficits and improved survival rates in tMCAO mice. SM administration also resulted in improvement in post-stroke cognitive impairment, as measured by the novel object recognition and passive avoidance tests in tMCAO mice. Our findings suggest that SM provides neuroprotection against ischemic stroke and has potential as a therapeutic agent.

This paper proposed a multi-layered 3D NDT (normal distribution transform) scan-matching approach for robust localization even in the highly dynamic environment of warehouse logistics. Our approach partitioned a given 3D point-cloud map and the scan measurements into several layers regarding the degree of environmental changes in the height direction and computed the covariance estimates for each layer using 3D NDT scan-matching. Because the covariance determinant is the estimate’s uncertainty, we can determine which layers are better to use in the localization in the warehouse. If the layer gets close to the warehouse’s floor, the degree of environmental changes, such as the cluttered warehouse layout and position of boxes, would be significantly large, while it has many good features for scan-matching. If the observation at a specific layer is not explained well enough, then the layer for localization can be switched to other layers with lower uncertainties. Thus, the main novelty of this approach is that localization robustness can be improved even in very cluttered and dynamic environments. This study also provides the simulation-based validation using Nvidia’s Omniverse Isaac sim and detailed mathematical descriptions for the proposed method. Moreover, the evaluated results of this study can be a good starting point for further mitigating the effects of occlusion in warehouse navigation of mobile robots.

Tracked mobile robots can overcome the limitations of wheeled and legged robots in environments, such as construction and mining, but there are still significant challenges to be addressed in terms of trajectory tracking. This study proposes a kinematic strategy to improve the trajectory-tracking performance of a PASTRo (Passively Articulated Suspension based Track-typed mobile robot), which comprises four tracks, two rockers, a differential gear, and a main body. Due to the difficulties in explicitly identifying track-terrain contact angles, suspension kinematics is used to identify track-terrain contact angles (TTCA) in arbitrarily rough terrains. Thus, the TTCA-based driving velocity projection method is proposed in this study to improve the maneuverability of PASTRo in arbitrarily rough terrains. The RecurDyn-Simulink co-simulator is used to examine the improvement of PASTRo compared to a tracked mobile robot non-suspension version. The results indicate that PASTRo has a 33.3% lower RMS(Root Mean Square) distance error, 56.3% lower RMS directional error, and 43.2% lower RMS offset error than the four-track skid-steer mobile robot (SSMR), even with planar SSMR kinematics. To improve the maneuverability of PASTRo without any information on the rough terrain, the TTCA is calculated from the suspension kinematics, and the TTCA obtained is used for both TTCA-based driving velocity projection methods. The results show that PASTRo, with the TTCA-based driving velocity projection method, has a 39.2% lower RMS distance error, 57.9% lower RMS directional error, and 51.9% lower RMS offset error than the four-track SSMR.

Purpose: Authors analyzed long-term surgical outcomes of infantile esotropia and the occurrence of associated strabismus, inferior oblique overaction (IOOA), and dissociated vertical deviation (DVD). Clinical factors related to the occurrence of IOOA and DVD in patients with infantile esotropia were also evaluated. Methods: Medical records of patients with infantile esotropia, who underwent surgery between 1995 and 2008, were reviewed retrospectively. Included patients were followed for at least 10 years. The incidence and age at development of IOOA and DVD were analyzed. To evaluate predisposing factors for developing IOOA or DVD, patients were divided into two groups: those with infantile esotropia only (group A) and those who developed IOOA or DVD (group B). Results: A total of 122 patients were enrolled and mean follow-up period was 16.0 years (range: 10–32 years). The mean number of surgeries was 1.7 (range: 1–5), and 64 (52.5%) patients achieved optimal horizontal alignment (esotropia

The ground tracking support is a critical factor for the navigation performance of spacecraft orbiting around the Moon. Because of the tracking limit of antennas, only a small number of facilities can support lunar missions. Therefore, case studies for various ground tracking support conditions are needed for lunar missions on the stage of preliminary mission analysis. This study analyzes the ground supporting condition effect on orbit determination (OD) of Korea Pathfinder Lunar Orbiter (KPLO) in the lunar orbit. For the assumption of ground support conditions, daily tracking frequency, cut-off angle for low elevation, tracking measurement accuracy, and tracking failure situations were considered. Two antennas of deep space network (DSN) and Korea Deep Space Antenna (KDSA) are utilized for various tracking conditions configuration. For the investigation of the daily tracking frequency effect, three cases (full support, DSN 4 pass/day and KDSA 4 pass/day, and DSN 2 pass/day and KDSA 2 pass/day) are prepared. For the elevation cut-off angle effect, two situations, which are 5 deg and 10 deg, are assumed. Three cases (0%, 30%, and 50% of degradation) were considered for the tracking measurement accuracy effect. Three cases such as no missing, 1-day KDSA missing, and 2-day KDSA missing are assumed for tracking failure effect. For OD, a sequential estimation algorithm was used, and for the OD performance evaluation, position uncertainty, position differences between true and estimated orbits, and orbit overlap precision according to various ground supporting conditions were investigated. Orbit prediction accuracy variations due to ground tracking conditions were also demonstrated. This study provides a guideline for selecting ground tracking support levels and preparing a backup plan for the KPLO lunar mission phase.

Abstract The disagreement between the standard model prediction and the experimental measurement of muon anomalous magnetic moment can be alleviated by invoking an additional particle which is either a vector boson (X 1) or a scalar (X 0). This new particle, with the mass m X ≲ 2m μ , can be searched for in the decay J/ψ → μ − μ + X, where X is missing. Our numerical study shows that the search is quite feasible at the BESIII experiment in the parameter space allowed by muon g − 2 measurements.

AIM: To compare the changes in excyclotorsion after inferior oblique (IO) recession in patients with primary and secondary inferior oblique overaction (IOOA). METHODS: We retrospectively analyzed the data obtained from patients with IOOA who underwent graded IO recession. The patients were followed up for at least 3mo after surgery. Fundus photographs were taken pre- and postoperatively, and the sum of the angles of torsion in both eyes was used to analyze changes in excyclotorsion. Patients were divided into two groups: those diagnosed with primary IOOA were enrolled in the 1’IOOA group, and those diagnosed with secondary IOOA caused by superior oblique palsy (SOP) were enrolled in the 2’IOOA group. Excyclotorsion before and after surgery were compared between the two groups. RESULTS: A total of 78 patients were enrolled in this study: 34 eyes in the 1’IOOA group and 44 eyes in the 2’IOOA group. In the 78 patients, torsional angle significantly decreased from 15.31°±7.40° to 12.11°±6.53° after IO recession (P

Abstract We present, how a systematic study of $$B \rightarrow D\ell N$$ B→DℓN ($$D \rightarrow K \ell N$$ D→KℓN ) decays with $$\ell =\mu ,\tau $$ ℓ=μ,τ , at Belle II (BESIII) can provide unambiguous signature of a heavy neutrino N and/or constrain its mixing with active neutrinos $$\nu _\ell $$ νℓ , which is parameterized by $$| U_{\ell N} |^2$$ |UℓN|2 . Our constraint on $$\vert U_{\mu N} \vert ^2$$ |UμN|2 that can be achieved from the full Belle II data is comparable with what can be obtained from the much larger data set of the upgraded LHCb. Additionally, our method offers better constraint on $$\vert U_{\mu N} \vert ^2$$ |UμN|2 for mass of sterile neutrino $$m_N < 2$$ mN

Abstract Background The roots of Pueraria lobata and Scutellaria baicalensis, herbal medicines with a long history of widespread use, have been traditionally prescribed in combination to treat stroke, diabetes, and acute infectious diarrhea in East Asia. Nevertheless, toxicological data on these herbs and their combination are limited. This study investigated the acute and 13-week subchronic toxicity of root extract of P. lobata and S. baicalensis (HT047) for stroke treatment in male and female Sprague-Dawley rats. Methods In the acute toxicity study, HT047 was administered orally at a single dose of 5000 mg/kg. In the subchronic toxicity study, HT047 was administered orally at repeated daily doses of 800, 2000, and 5000 mg/kg/day for 13 weeks, followed by a 4-week recovery period. Results In the acute toxicity study, there were no deaths or toxicologically significant changes in clinical signs, body weight, and necropsy findings. In the subchronic toxicity study, HT047 at all doses caused no death and no treatment-related adverse effects on food consumption; organ weight; ophthalmologic, urinalysis, and hematological parameters; and necropsy findings of both rat sexes. There were some treatment-related alterations in clinical signs, body weight, and serum biochemistry and histopathological parameters; however, these changes were not considered toxicologically significant because they were resolved during the recovery period or resulted from the pharmacological effects of P. lobata and S. baicalensis. Conclusions The oral approximate lethal dose (the lowest dose that causes mortality) of HT047 was greater than 5000 mg/kg in male and female rats. The oral no-observed-adverse-effect level of HT047 was greater than 5000 mg/kg/day in rats of both sexes, and no target organs were identified. The present findings support the safety of an herbal extract of P. lobata and S. baicalensis as a therapeutic agent for stroke and further confirm the safety of the combined use of P. lobata and S. baicalensis in clinical practice.

Deep reinforcement learning (DRL) is a promising approach for developing control policies by learning how to perform tasks. Edge devices are required to control their actions by exploiting DRL to solve tasks autonomously in various applications such as smart manufacturing and autonomous driving. However, the resource limitations of edge devices make it unfeasible for them to train their policies from scratch. It is also impractical for such an edge device to use the policy with a large number of layers and parameters, which is pre-trained by a centralized cloud infrastructure with high computational power. In this paper, we propose a method, on-device DRL with distillation (OD3), to efficiently transfer distilled knowledge of how to behave for on-device DRL in resource-constrained edge computing systems. Our proposed method makes it possible to simultaneously perform knowledge transfer and policy model compression in a single training process on edge devices with considering their limited resource budgets. The novelty of our method is to apply a knowledge distillation approach to DRL based edge device control in integrated edge cloud environments. We analyze the performance of the proposed method by implementing it on a commercial embedded system-on-module equipped with limited hardware resources. The experimental results show that 1) edge policy training with the proposed method achieves near-cloud-performance in terms of average rewards, although the size of the edge policy network is significantly smaller compared to that of the cloud policy network and 2) the training time elapsed for edge policy training with our method is reduced significantly compared to edge policy training from scratch.

Objective: Cancer pain is an important factor in cancer management that affects a patient’s quality of life and survival-related outcomes. The aim of this review was to systematically evaluate the efficacy and safety of oral administration of East Asian herbal medicine (EAHM) for primary cancer pain and to explore core herb patterns based on the collected data.Methods: A comprehensive literature search was conducted in 11 electronic databases, namely, PubMed, Cochrane Library, Cumulative Index to Nursing & Allied Health Literature, EMBASE, Korean Studies Information Service System, Research Information Service System, Oriental Medicine Advanced Searching Integrated System, Korea Citation Index, Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Data, and CiNii for randomized controlled trials from their inception until August 19, 2021. Statistical analysis was performed in R version 4.1.1 and R studio program using the default settings of the meta-package. When heterogeneity in studies was detected, the cause was identified through meta-regression and subgroup analysis. Methodological quality was independently assessed using the revised tool for risk of bias in randomized trials (Rob 2.0).Results: A total of 38 trials with 3,434 cancer pain patients met the selection criteria. Meta-analysis favored EAHM-combined conventional medicine on response rate (risk ratio: 1.06; 95% CI: 1.04 to 1.09, p < 0.0001), continuous pain intensity (standardized mean difference: −1.74; 95% CI: −2.17 to −1.30, p < 0.0001), duration of pain relief (standardized mean difference: 0.96, 95% CI: 0.69 to 1.22, p < 0.0001), performance status (weighted mean difference: 10.71; 95% CI: 4.89 to 16.53, p = 0.0003), and opioid usage (weighted mean difference: −20.66 mg/day; 95% CI: −30.22 to −11.10, p < 0.0001). No significant difference was observed between EAHM and conventional medicine on response rate and other outcomes. Patients treated with EAHM had significantly reduced adverse event (AE) incidence rates. In addition, based on the ingredients of herb data in this meta-analysis, four combinations of herb pairs, which were frequently used together for cancer pain, were derived.Conclusion: EAHM monotherapy can decrease adverse events associated with pain management in cancer patients. Additionally, EAHM-combined conventional medicine therapy may be beneficial for patients with cancer pain in increasing the response rate, relieving pain intensity, improving pain-related performance status, and regulating opioid usage. However, the efficacy and safety of EAHM monotherapy are difficult to conclude due to the lack of methodological quality and quantity of studies. More well-designed, multicenter, double-blind, and placebo-controlled randomized clinical trials are needed in the future. In terms of the core herb combination patterns derived from the present review, four combinations of herb pairs might be promising for cancer pain because they have been often distinctly used for cancer patients in East Asia. Thus, they are considered to be worth a follow-up study to elucidate their actions and effects.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42021265804

The accuracy of the wearable inertia-measurement-unit (IMU)-sensor-based gesture recognition may be significantly affected by undesired changes in the body-fixed frame and the sensor-fixed frame according to the change in the subject and the sensor attachment. In this study, we proposed a novel wearable IMU-sensor-based hand-guiding gesture recognition method robust to significant changes in the subject’s body alignment based on the floating body-fixed frame method and the bi-directional long short-term memory (bi-LSTM). Through comparative experimental studies with the other two methods, it was confirmed that aligning the sensor-fixed frame with the reference frame of the human body and updating the reference frame according to the change in the subject’s body-heading direction helped improve the generalization performance of the gesture recognition model. As a result, the proposed floating body-fixed frame method showed a 91.7% test accuracy, confirming that it was appropriate for gesture recognition under significant changes in the subject’s body alignment during gestures.

Many real-life problems that involve decisions under uncertainty are often sequentially repeated and can be approached iteratively. Knowledge Gradient (KG) formulates the decision-under-uncertainty problem into repeatedly estimating the value of information observed from each possible decisions and then committing to a decision with the highest estimated value. This paper aims to provide a multi-faceted overview of modern research on KG: firstly, on how the KG algorithm is formulated in the beginning with an example implementation of its most frequently used implementation; secondly, on how KG algorithms are related to other problems and iterative algorithms, in particular, Bayesian optimization; thirdly, on the significant trends found in modern theoretical research on KG; lastly, on the diverse examples of applications that use KG in their key decision-making step.

This paper analyzes delta-Vs to maintain an extremely low altitude on the Moon and investigates the possibilities of performing a CubeSat mission. To formulate the station-keeping (SK) problem at an extremely low altitude, current work has utilized real-flight performance proven software, the Systems Tool Kit Astrogator by Analytical Graphics Inc. With a high-fidelity force model, properties of SK maneuver delta-Vs to maintain an extremely low altitude are successfully derived with respect to different sets of reference orbits; of different altitudes as well as deadband limits. The effect of the degree and order selection of lunar gravitational harmonics on the overall SK maneuver strategy is also analyzed. Based on the derived SK maneuver delta-V costs, the possibilities of performing a CubeSat mission are analyzed with the expected mission lifetime by applying the current flight-proven miniaturized propulsion system performances. Moreover, the lunar surface coverage as well as the orbital characteristics of a candidate reference orbit are discussed. As a result, it is concluded that an approximately 15-kg class CubeSat could maintain an orbit (30–50 km reference altitude having ±10 km deadband limits) around the Moon for 1–6 months and provide almost full coverage of the lunar surface.