Omega-3 polyunsaturated fatty acids (ω3-PUFAs), including docosahexaenoic acid (DHA), have been shown to exert anticancer effects by inducing apoptotic cell death. However, the mechanism for DHA-induced cell death in lung cancer is not fully understood. Here, we show that DHA induces apoptosis in two human EGFR mutant non-small cell lung cancer (NSCLC) cell lines, and that DHA-induced cell death is accompanied by SIRT6 activation and attenuated Hedgehog (Hh) signaling. Knockdown of SIRT6 using siRNAs inhibited DHA-induced apoptosis, whereas SIRT6 overexpression increased apoptotic cell death. DHA-induced SIRT6 activation was associated with downregulation of Hh signaling, and knockdown of SIRT6 resulted in augmentation of Hh signaling. Pretreatment of NSCLC cells with a Smoothened agonist prevented DHA-induced decreases in the levels of Hh signaling proteins and increases in cleaved PARP levels. Moreover, endogenous production of ω3-PUFAs in PC9 cells via fat-1 expression resulted in elevated SIRT6 levels and reduced levels of Hh signaling molecules, including Gli, following DHA treatment. Overall, these results implicate that ω3-PUFAs induce apoptosis by downregulating Hh signaling via SIRT6 activation in human EGFR mutant NSCLC cells. These findings suggest that ω3-PUFAs potentially represent an effective therapy for the chemoprevention and treatment of NSCLC.

Phosphate (Pi) starvation is a critical factor limiting crop growth, development, and productivity. Rice (Oryza sativa) R2R3-MYB transcription factors function in the transcriptional regulation of plant responses to various abiotic stresses and micronutrient deprivation, but little is known about their roles in Pi starvation signaling and Pi homeostasis. Here we identified the R2R3-MYB transcription factor gene OsMYB58, which shares high sequence similarity with AtMYB58. OsMYB58 expression was induced more strongly by Pi starvation than by other micronutrient deficiencies. Overexpressing OsMYB58 in Arabidopsis thaliana and rice inhibited plant growth and development under Pi-deficiency conditions. In addition, overexpression of OsMYB58 in plants exposed to Pi deficiency strongly affected root development, including seminal root, lateral root, and root hair formation. Overexpressing OsMYB58 strongly decreased the expression of the rice microRNAs, OsmiR399a and OsmiR399j. By contrast, overexpressing OsMYB58 strongly increased the expression of rice PHOSPHATE 2 (OsPHO2), whose expression is repressed by miR399 during Pi starvation signaling. OsMYB58 functions as a transcriptional repressor of the expression of its target genes, as determined by a transcriptional activity assay. These results demonstrate that OsMYB58 negatively regulates OsmiR399-dependent Pi starvation signaling by enhancing OsmiR399s expression.

Extracellular vesicles (EVs) carry diverse cargo of DNA, RNA, proteins, and lipids. They are crucial mediators for regulating various functions through interactions with the host. Recent investigations suggest that EVs or their constituent proteins derived from probiotics could improve the effectiveness of probiotic strains in disease management compared to probiotic strains themselves. This enhanced effec-tiveness arises from their innate antimicrobial properties, which can specifically target pathogenic mol-ecules or cells, in addition to their significant ability to regulate immune responses. Significantly, previous studies have highlighted the inhibitory potential of Lactobacillus crispatus PMC201 against Mycobacterium tuberculosis. In this study, we focused on optimizing isolation conditions for studying extracellular vesicles and proteins from anti-TB potent strains. We provide analysis results based on food-grade media (FGM) optimization and isolation methods. Nanoparticle tracking analysis (NTA) was used to determine se-cretion patterns. Proteomic analysis was performed by liquid chromatography and tandem mass spec-trometry (LC-MS/MS). A total of 64 proteins were identified in the L. crispatus PMC201 strain, particularly enriched in s-layer and splX. Questions remain about their relevance to anti-TB. This anti-tuber strain has potential as a therapeutic agent, given its significant role in intercellular killing. Further studies are needed to investigate its mechanisms of action.

The pond slider (Trachemys scripta) was designated as an invasive alien species in South Korea in 2001. Although the prevention and control of invasive species have received considerable atten-tion worldwide, studies on the current status and effective management of T. scripta in South Korea are lacking. This study aimed to elucidate the status of domestic reuse of T. scripta and provide effective management suggestions. Analysis of the National Institute of Ecology's “Na-tionwide Survey of Non-native Species in Korea” conducted from 2015 to 2022 confirmed the habitats of 1,440 T. scripta individuals at 295 sites. T. scripta is the most frequently observed among invasive turtles identified in the Korean Peninsula. To determine the reuse of T. scripta, 13 tradi-tional markets were surveyed; five markets were confirmed to have T. scripta. Although the exact distribution route is unknown, individuals living or abandoned in the region might be resold in the market. T. scripta is mostly sold for ritual purposes. Moreover, T. scripta accounted for 31% of freshwater turtles abandoned between 2019 and 2022. Their continuous reuse has been confirmed 22 years after their designation as an invasive alien species. Therefore, effective and fundamental management measures for T. scripta are required.

This paper proposes a metaphysical framework for distinguishing between human and machine intelligence. By drawing an analogy from Kant’s incongruent counterparts, it posits two identical deterministic worlds -- one comprising a human agent and the other comprising a machine agent. These agents exhibit different types of information processing mechanisms despite their apparent sameness in a causal sense. By postulating the distinctiveness of human over machine intelligence, this paper resolves what it refers to as “the vantage point problem” – namely, how to legitimize a determinist’s assertion of determinism by placing the determinist within the universe.

Background and Objectives: The ingestion of anhydrous calcium chloride (CaCl2) causes direct injury to the gastrointestinal wall via a thermal burn. Severe CaCl2 intoxication can induce a hypercalcemic crisis, presenting with arrhythmia, acute pancreatitis, and acute kidney injury. This case report details a patient with hematemesis and hypercalcemia following the ingestion of a commercial desiccant. We aimed to report the progression of the case and focused on the elec-trocardiographic manifestations. Case presentation: A 39-year-old female presented at a regional emergency center with blood in her vomit after the ingestion of a commercial desiccant. Bloody emesis was the initial symptom, and various electrolyte imbalances developed during admission. Electrocardiogram (ECG) changes occurred early after hospitalization and disappeared before the electrolyte levels normalized. The patient was maintained in an NPO state throughout her hospital stay. Bloody emesis and abdominal pain resolved rather early, despite her minimal mention of symptoms, possibly due to her suspected negative psychiatric symptoms. Conclusions: The rise in suicidal attempts has led to an increase in unusual intoxication cases. Previous reports on CaCl2 ingestion primarily considered the gastrointestinal injury. In this case, we observed the dynamic and prolonged multiple electrolyte imbalances along with the early-phase ECG changes, all of which responded well to supportive care. This report adds to the understanding of the diverse manifestations and management of CaCl2 intoxication.

Functional connectivity (FC) is a potential candidate that can increase the performance of brain-computer interfaces (BCIs) in the elderly because of its compensatory role in neural circuits. However, it is difficult to decode FC by current machine learning techniques because of a lack of its physiological understanding. To investigate the suitability of FC in BCI for the elderly, we propose the decoding of lower- and higher-order FCs using a convolutional neural network (CNN) in six cognitive-motor tasks. The layer-wise relevance propagation (LRP) method describes how age-related changes in FCs impact BCI applications for the elderly compared to younger adults. Seventeen younger (24.5±2.7 years) and twelve older (72.5±3.2 years) adults were recruited to perform tasks related to hand-force control with or without mental calculation. CNN yielded a six-class classification accuracy of 75.3% in the elderly, exceeding the 70.7% accuracy for the younger adults. In the elderly, the proposed method increases the classification accuracy by 88.3% compared to the filter-bank common spatial pattern (FBCSP). LRP results revealed that both lower- and higher-order FCs were dominantly overactivated in the prefrontal lobe depending on task type. These findings suggest a promising application of multi-order FC with deep learning on BCI systems for the elderly.

In the field of visualization, understanding users’ analytical process is important to determine the effectiveness of a designed visualization application. To understand the users’ analytical process, numerous studies have been performed to capture and analyze user interactions. Although many studies have emphasized the importance of analyzing user interactions to understand users’ analytical reasoning processes, few have successfully linked these interactions to users’ reasoning processes. This paper introduces an approach that bridges this gap by correlating semantic user interactions with analysis decisions through an interactive wire transaction analysis system and a visual state transition matrix. With the designed analysis system, interactive analysis can be performed to evaluate financial fraud in wire transactions. It also allows the mapping of captured user interactions and analytical decisions back onto the visualization, revealing users’ distinct results. The visual state transition matrix further aids to help understanding users’ analytical flows, revealing their decision-making processes. Classification machine learning algorithms are applied to assess the effectiveness of our approach in understanding analysts’ strategies by connecting them to their decisions. From the study, we observed an average of 72% accuracy in clearly classifying the semantic user interactions. For classifying individual decisions, we observed an average of 70% classification accuracy. This emphasizes the importance of capturing semantic user interactions to understand users’ analytical processes. Overall, it is determined that the proposed approach not only enhances the understanding of analytical behaviors but also offers a robust approach for evaluating user interactions in visualization tools.

The use of autonomous Unmanned Aerial Vehicles (UAVs) has been increasing, and the autonomy of these systems and their capabilities in dealing with uncertainties is crucial. Autonomous landing is pivotal for the success of an autonomous mission of UAVs. This paper presents an autonomous landing system for quadrotor UAVs with the ability to perform smooth landing even in undesirable conditions like obstruction by obstacles in and around the designated landing area and inability to identify or the absence of a visual marker establishing the designated landing area. We have integrated algorithms like version 5 of You Only Look Once (YOLOv5), DeepSORT, Euclidean distance transform, and Proportional-Integral-Derivative (PID) controller to strengthen the robustness of the overall system. While the YOLOv5 model is trained to identify the visual marker of the landing area and some common obstacles like people, cars, and trees, the DeepSORT algorithm keeps track of the identified objects. Similarly, using the detection of the identified objects and Euclidean distance transform, an open space without any obstacles to land could be identified if necessary. Finally, the PID controller generates appropriate movement values for the UAV using the visual cues of the target landing area and the obstacles. To warrant the validity of the overall system without risking the safety of the involved people, initial tests are performed, and a software-based simulation is performed before executing the tests in real life. A full-blown hardware system with an autonomous landing system is then built and tested in real life. The designed system is tested in various scenarios to verify the effectiveness of the system.

Over the few decades, cancer-associated mortalities and morbidities were continuously increased worldwide despite sophisticated technological advancements. Pharmaceutical interventions associated with drugs exhibit a high degree of side effects and toxicities in addition to very high costs. Subsequently, to reduce or to vanish the side effects and high costs, researchers are now exploring natural bioactive compounds such as quercetin in its nanoformulations along with biologics as cargo delivery vehicles. Quercetin along with mesenchymal stromal lineage-derived extracellular vesicles (EVs) possesses an anti-cancer potential that can be explored to treat hepatocellular carcinoma (HCC). Exerting enhanced effect, nano quercetin synergistically with EVs triggers the anti-cancer mechanisms by regulating and dysregulating several signalling mechanisms including NF-κB, p53, JAK/STAT, MAPK, Wnt/β-catenin and PI3K/AKT, in addition to PBX3/ERK1/2/CDK2, and miRNAs modulation. In addition, findings regarding the potential checkpoints of anti-cancer signalling pathways were investigated that offer opportunities to develop engineered EVs incorporated with nano quercetin for the development of novel therapeutics to treat HCC in future. In this present mechanistic review, we abridged the regulation of such signalling mechanisms synergetic approach of nano quercetin and EVs. The regulatory role of EVs in the manifestation of innumerable miRNAs has also been tailed with special context to HCC.

Purpose The COVID-19 pandemic, triggered by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in over 160 million infections and 3.5 million fatalities worldwide. Evidence of SARS-CoV-2 presence in the highly vascularized penile tissue and the established correlation between COVID-19 and subsequent erectile dysfunction (ED) has emerged. Robot-assisted radical prostatectomy (RARP) is a popular procedure for prostate cancer because of its reliability and swift recovery rate. However, the ED prevalence post-surgery is believed to be comparable to open surgery, and postoperative ED significantly affects the patient's quality of life. Our study aimed to explore the effect of COVID-19 on ED recovery in patients undergoing bilateral nerve preservation during RARP. Materials and Methods We conducted a retrospective study on 85 patients who underwent bilateral nerve-sparing RARP (nsRARP) at our institution between December 2017 and May 2021. Chart reviews and the International Index of Erectile Function-5 (IIEF-5) questionnaire facilitated the analysis. Our objective was to contrast ED recovery after surgery between SARS-CoV-2–infected and non-infected patients using preoperative IIEF-5 scores and scores at 6, 12, and 24 months post-surgery. We defined successful ED recovery as an IIEF-5 score of 17 or higher and successful sexual intercourse. We also compared ED recovery rates between the two groups, regardless of the timing of COVID-19 diagnosis. IBM's SPSS version 18.0 assisted in the statistical analysis, with Fisher's exact test and chi-square test used for comparing categorical variables. Independent t-tests determined mean differences between baseline and postoperative IIEF-5 scores. A p-value less than 0.05 was considered statistically significant. Results From December 2017 to May 2021, our institution executed 213 RARP cases, with 185 of these involving nerve preservation. Among these patients, 133 had an IIEF-5 score of 17 or higher during preoperative EF assessment. We included 85 patients with consistent IIEF-5 records before surgery and at 6, 12, and 24 months post-surgery in this study. Of these, 44 and 41 patients comprised the COVID-19–positive and COVID-19–negative groups, respectively. The COVID-19–positive group had a higher proportion of diabetes mellitus (DM) patients (24 (54.55%) vs. 7 (17.07%), p<0.001). There was no significant difference in preoperative IIEF-5 scores or scores up to 6 months after surgery between the two groups. However, the IIEF-5 scores of the COVID-19–positive group were statistically lower after 12 and 24 months post-surgery. Additionally, the COVID-19–negative group showed a more considerable score increase between 6 and 12 months post-surgery, and the EF recovery rate was lower in the COVID-19–positive group starting from the 12th month after surgery. Within the COVID-19–positive group, no statistically significant difference in IIEF-5 scores was found between single infection and multiple reinfection groups. Conclusions Principal component analysis revealed the impact of COVID-19 on ED recovery in patients who underwent nsRARP. The most substantial changes in IIEF-5 scores occurred between 6 and 12 months. From 12 months onwards, the COVID-19–positive group had significantly lower scores, and fewer patients had IIEF-5 scores above 17. However, the number of COVID-19 diagnoses did not significantly affect the IIEF-5 scores.

Xerostomia is a subjective symptom of dry mouth resulting from various causes, including side effects of medication, systemic disorders, radiation, and Sjögren’s syndrome. Recently, the number of patients afflicted with xerostomia has increased due to an increase in the elderly population and patients on medication.; (2) Methods: A systematic approach is required to determine the etiology and management of xerostomia. This review summarizes recent literatures on the diagnosis and management of xerostomia.; (3) Results: A patient with xerostomia experiences difficulty in chewing, swallowing, speaking, tasting, and maintaining oral hygiene. Xerostomia and hyposalivation are uncomfortable side-effects in many patients. Assessing the function of the salivary gland is essential for selecting an appropriate treatment, improving symptoms, and preventing oral complications. Also, a more systematic approach is required to differentiate the subjective symptoms of the patient from the objective hyposalivation.; and (4) Conclusions: Although there is no standardized treatment for xerostomia, doctors need to endeavor and adapt the various treatments of xerostomia, to unearth the optimal treatment required for the patient.

Hepatocellular carcinoma (HCC) is currently the third leading cause of malignancy-related mortalities worldwide. Natural killer (NK) cells are involved in the critical role of first line immunological defense against cancer development. Defects in NK cell functions are recognized as important mechanisms for immune evasion of tumor cells. NK cell function appears to be attenuated in HCC, and many previous reports suggested that NK cells play a critical role in controlling HCC, suggesting that boosting the activity of dysfunctional NK cells can enhance tumor cell killing. However, the detailed mechanisms of NK cell dysfunction in tumor microenvironment of HCC remain largely unknown. A better understanding of the mechanisms of NK cell dysfunction in HCC will help in the NK cell-mediated eradication of cancer cells and prolong patient survival. In this review, we describe the various mechanisms underlying NK cell dysfunction in HCC. Further, we summarize current advances in the approaches to enhance endogenous NK cell function and in adoptive NK cell therapies, to cure this difficult-to-treat cancer.

Rotorcrafts operate HUMS for fault diagnosis, but the capabilities of HUMS analysts are important due to the complex mechanical configuration of rotorcraft and the difficulty of analysis. Accordingly, an advanced algorithm is needed to identify faults, and flight data can be used to develop the algorithm. However, flight data contains abnormal or missing data due to problems such as sensor defects, which can be a major problem in algorithm development. Therefore, in this paper, we study a gap filling method using MLP to obtain normal data when there are problems such as abnormal or missing data in rotorcraft flight data. Existing methods typically fill the gap through interpolation or curve fitting using the before and after values of missing data. However, in this study, normal values were estimated using the values of other parameters at the moment of missing or abnormal data occurred. As a result of evaluating the performance of the trained MLP using normal data, it was confirmed that the output of the model well estimates the changing trend of the target. And when abnormal data was applied to the trained model, it was confirmed that point outliers were eliminated and appropriate values were found in the case of missing data.

The research community has shown significant interest in the aqueous synthesis of nanomaterials due to its ability to eliminate the need for complex organic solvents. This synthesis approach aligns with the principles of green chemistry, attracting considerable attention. Aqueous solution technology in fabricating nanostructures has gained recognition for its potential to create ultrasensitive, low-energy, and ultrafast optoelectronic devices. This report focuses on synthesizing lead iodide (PbI2) nanoplates using a water-based solution technique and fabricating a planar photodetector. The photodetectors with a planar type of device structure (ITO/PbI2 NPs/Au) demonstrated a remarkable photosensitivity of 3.9×103 and a photoresponsivity of 0.51 mA/W at a wavelength of 405 nm. Notably, the asymmetrical output properties of ITO/PbI2 NPs/Au detector deliver additional evidence of the effective creation of a Schottky contact. Thus, the photodetector exhibited a photoresponse even at 0 V bias, leading to the realization of self-powered photodetectors. Additionally, the device exhibited a rapid photoresponse of 0.21/0.38 s (−5 V) in the visible range. This study has expanded the horizons for the aqueous-phase synthesis of nanoplate nanostructures, enabling the large-area fabrication of high-performance photodetectors.

An 8-month-old, 3.4 kg, castrated male Toy Poodle was referred for progressive tetraparesis and respiratory disorder without a history of trauma. Diagnostic imaging, including dynamic CT and MRI, revealed concurrent atlanto-occipital dislocation (AOD) and atlantoaxial instability (AAI) with spinal cord compression. This case was unique due to its congenital nature and the absence of trauma. The surgical intervention involved precise removal of the C1 vertebra's ventral articular facet, which was compressing on the spinal cord, attributed to its fixed and malaligned position within the atlantooccipital joint. Following facetectomy, the stabilization of the occipital bone to the C2 vertebra was achieved by screws, wire, and polymethyl methacrylate. Postoperative recovery was monitored with CT and radiographs, showing successful decompression and gradual improvement in gait, despite mild residual ataxia. The dog experienced postoperative complications with screw loosening at 114 days, which was managed successfully by extracting the problematic screws. Postoperatively, the dog showed a near-normal gait and experienced no pain through 21 months of monitoring. This case represents the first report of concurrent congenital AOD and AAI treated with ventral surgical approach, contributing new insights to the understanding and management of such complex cranio-cervical junction disorders in veterinary neurosurgery.

Bullying makes learning difficult for nursing students, and using real-life scenarios during training can improve the understanding of workplace bullying. Thus, to mitigate bullying experienced by nurses, this study developed and evaluated a cognitive rehearsal education program that constituted of training nursing students through role-play simulations. A mixed-method research design was used to evaluate 39 nursing students from two universities. A quasi-experimental research design was applied to assess symptoms, knowledge, and perceptions of bullying, and a focus group interview was conducted with six participants. Quantitative analyses revealed that the program improved participants’ knowledge and perceptions, but not their symptoms. The focus group interview revealed that the program improved participants’ coping skills and desire for education. This program could be effective in raising awareness of workplace bullying and increasing relevant coping skills. It can be further developed as part of an overall strategy to manage workplace bullying and its consequences in hospital settings.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

This study explored the effects of a comprehensive health care program (CHCP) on blood pressure, blood glucose, body composition, and depression in older adults living alone. We used a quasi-experimental, two-group, pre-posttest design. The CHCP consisted of open lectures, health counseling, exercise classes, nutrition counseling, and self-help group meetings at a local senior welfare center. Fifty-eight subjects participated in this study, with thirty subjects in the experimental group and twenty-eight subjects in the control group. Data were analyzed using the descriptive statistics, χ²-test, and t-test. Comparisons of the pretest and posttest systolic blood pressure (t = - 2.530, p < .016) and blood glucose (t = 3.089, p < .004) between the experimental and control groups showed significant differences. In both the experimental (t = 3.949, p < .001) and control groups (t = 3.816, p < .002), depression symptoms showed a significant decrease post-test, compared with pre-test. Our findings infer that older adults require physical and psychosocial healthcare and that more efforts must be made to improve the general health and wellbeing of this population group.

Mesenchymal stem cells (MSCs) showed in vitro mesoderm-lineage differentiation and self-renew capacity. However, no comparative study was reported on the biological characteristics of stem cells derived from skeletal muscle (SM-MSCs), dermal skin (DS-MSCs), and adipose tissues (A-MSCs) from a single donor in camels. The present study aimed to evaluate the influence of MSCs source on stem cell characteristics. We evaluated proliferation capacity and mesoderm-lineage differentiation potential from SM-MSCs, DS-MSCs, and A-MSCs. They showed spindle-like morphology after homogenization. The proliferation ability was no significant difference in all groups. Furthermore, the portion of the cell cycle and expression of pluripotent markers (Oct4, Sox2, and Nanog) were similar in all cell lines at passage 3. The differentiation capacity of A-MSCs into adipocytes was significantly higher than that of SM-MSCs and DS-MSCs. However, the osteoblast differentiation capacity of A-MSCs was significantly lower than that of SM-MSCs and DS-MSCs. Additionally, after osteoblast differentiation, the ALP activity and calcium content was significantly decreased in A-MSCs as compared to SM-MSCs and DS-MSCs. To the best of our knowledge, we primally established MSCs from the single camel and demonstrated their comparative characteristics including expression of pluripotent factors and proliferation, and in vitro differentiation capacity into adipocytes and osteoblasts.

This study reports the preparation of silica and nano-fructosome encapsulated Candida antarctica lipase B particles (CalB@NF@SiO2) and demonstration of their enzymatic hydrolysis and acylation. CalB@NF@SiO2 particles were prepared as a function of TEOS concentration (3-100 mM). Their mean particle size was 185 nm by TEM. Enzymatic hydrolysis was performed to compare catalytic efficiencies of CalB@NF and CalB@NF@SiO2. Catalytic constants (Km, Vmax, and Kcat) of CalB@NF and CalB@NF@SiO2 were calculated with Michaelis-Menten equation and Line-weaver Burk plot. Optimal stability of CalB@NF@SiO2 was found at pH 8 and temperature of 35 ℃. Moreover, CalB@NF@SiO2 particles were reused for seven cycles to evaluate their reusability. In addition, enzymatic synthesis of benzyl benzoate was demonstrated by an acylation reaction with benzoic anhydride. The efficiency of CalB@NF@SiO2 for converting benzoic anhydride to benzyl benzoate by the acylation reaction was 97%, indicating that benzoic anhydride was almost completely converted to benzyl benzoate. Consequently, CalB@NF@SiO2 particles are better than CalB@NF particles for enzymatic synthesis. In addition, they are reusable with high stability at optimal pH and temperature.

We consider Pisot family substitution tilings in $\R^d$ whose dynamical spectrum is pure point. There are two cut-and-project schemes(CPS) which arise naturally: one from the Pisot family property and the other from the pure point spectrum respectively. The first CPS has an internal space $\R^m$ for some integer $m \in \N$ defined from the Pisot family property, and the second CPS has an internal space $H$ which is an abstract space defined from the property of the pure point spectrum. However it is not known how these two CPS's are related. Here we provide a sufficient condition to make a connection between the two CPS's. In the case of Pisot unimodular substitution tiling in $\R$, the two CPS's turn out to be same due to [5, Remark 18.5].

Cardiac hypertrophy is an adaptive response to various pathological insults including hypertension. However, sustained hypertrophy can cause impaired calcium regulation, cardiac dysfunction, and remodeling, accompanied by cardiac fibrosis. Our previous study identified miR-25 as a regulator of SERCA2a, and that inhibition of miR-25 improved cardiac function and reduced fibrosis by restoring SERCA2a expression in a murine heart failure model. However, the precise mechanism underlying the reduction of fibrosis by miR-25 inhibition remains unclear. Therefore, we postulate that miR-25 may have additional targets that contribute to regulating cardiac fibrosis. Using in silico analysis, Krüppel-like factor 4 (KLF4) was identified as an additional target of miR-25. Further experiments confirmed that KLF4 was directly targeted by miR-25 and that its expression was reduced by long-term treatment with Angiotensin II, a major hypertrophic inducer. Subsequently, treatment with a miR-25 inhibitor alleviated the cardiac dysfunction, fibrosis, and inflammation induced by Angiotensin II. These findings indicate that inhibiting miR-25 not only enhances calcium cycling and cardiac function via SERCA2a restoration but also reduces fibrosis by restoring KLF4 expression. Therefore, targeting miR-25 may be a promising therapeutic strategy for treating hypertensive heart diseases.

Cesium lead iodide (CsPbI3) perovskite nanocrystals (NCs) are a promising material for red light-emitting diodes (LEDs) due to their excellent color-purity and high luminous efficiency. However, small-sized CsPbI3 colloidal NCs, such as nanocubes, used in LEDs suffer from confinement effects, negatively impacting their photoluminescence quantum yield (PLQY) and overall efficiency. Here, we introduced YCl3 into the CsPbI3 perovskite, which formed anisotropic, one-dimensional (1D) nanorods. This was achieved by taking advantage of the difference in bond energies between Cl− and I− ions, which caused YCl3 to promote the anisotropic growth of CsPbI3 NCs. The YCl3-based nanorods improved the PLQY and storage stability by passivating the defects reducing the nonradiative recombination rates. When the YCl3-substituted CsPbI3 nanorods are applied to the emissive layer in LEDs, we achieve an external quantum efficiency of ~3.16% which is 1.86-fold higher than the pristine CsPbI3 NCs (1.69%) based LED. Notably, the ratio of horizontal transition dipole moments (TDMs) in the anisotropic YCl3:CsPbI3 nanorods was determined to be 75%, which is higher than the isotropically oriented TDMs in CsPbI3 nanocrystals (67%). This increased TDM ratio led to higher light outcoupling efficiency in nanorods-based LEDs. Overall, the results suggest that YCl3-substituted CsPbI3 nanorods could be promising for achieving high-performance perovskite LEDs.

The accurate diagnosis and effective treatment of mental health disorders such as depression remain challenging owing to the complex underlying causes and varied symptomatology. Traditional information extraction methods struggle to adapt to evolving diagnostic criteria such as the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5) and to contextualize rich patient data effectively. This study proposes a novel approach for enhancing information extraction from mental health data by integrating medical knowledge graphs and large language models (LLMs). Our method leverages the structured organization of knowledge graphs specifically designed for the rich domain of mental health combined with the powerful predictive capabilities and zero-shot learning abilities of LLMs. This research enhances the quality of knowledge graphs through entity linking and demonstrates superiority over traditional information extraction techniques, making a significant contribution to the field of mental health. It enables a more fine-grained analysis of the data and the development of new applications. Our approach redefines the manner in which mental health data are extracted and utilized. By integrating these insights with existing healthcare applications, the groundwork is laid for the development of real-time patient monitoring systems. The performance evaluation of this knowledge graph highlights its effectiveness and reliability, indicating significant advancements in automating medical data processing and depression management.

Background: The Stability Index estimation algorithm was derived and applied to develop and implement a balance ability diagnosis system that can be used at daily life. Methods: The system integrated an approach based on sensory function interaction, called the clinical test of sensory interaction with balance (CTSIB). The piezo-resistive force mat was fabricated, and a Stability Index prediction algorithm was developed and applied using the center of pressure (CoP) variables. The Stability Index prediction algorithm derived a CoP variable for 103 elderly people by Nintendo Wii Balance Board (WBB) to predict the Stability Index of the Balance System (Biodex SD). And, the accuracy was confirmed through the correlation between the real and predicted value. Results: As a result of testing with the test-set, the linear regression model confirmed that the r value ranged between 0.943 to 0.983. To confirm the similarity between the WBB and flexible force mat, each measured CoP value was input and calculated into the developed regression model, and the result of the correlation coefficient validation ​​confirmed an r value of 0.96. Conclusion: The system developed in this study will be applicable to the daily life of the home in the form of a floor mat.

Poly(acrylic acid) (PAAc) hydrogels possess good bioadhesive properties and allow enhanced penetration of drugs. In addition, it is possible to localize the absorption site of the drug in the hydrogel and increase the drug residence time. As opposed to other cross-linking processes radiation-induced polymer cross-linking can be easily and rapidly carried out without the use of cross-linking agents and other chemical additives. In this study, we fabricated metronidazole (MD) containing PAAc hydrogel (MD/PAAc) with different MD contents (0.1, 0.25, 0.5 wt%) using varying radiation doses (25, 50, 75 kGy) by gamma-irradiation. The physical and thermal properties were determined by gel content analysis, swelling ratio measurements, compressive strength measurements, differential scanning calorimetery, and thermogravimetric analysis. The properties of the hydrogel degraded due to the crystalline nature of MD. The properties of the hydrogel degraded due to the crystalline nature of MD. Cumulative release observed after 50 min in the case of 0.5MD/PAAc and 0.1MD/PAAc was 50% and 10%, respectively. Our findings suggest that MD/PAAc could be a suitable drug delivery carrier for use with radiation-based techniques.

Aims TRAIL is a promising anticancer agent that has the potential to sensitize a wide variety of cancer or transformed cells by inducing apoptosis. However, resistance to TRAIL is a growing concern. Current manuscript aimed to employing combination treatment to investigate resveratrol induced TRAIL sensitization in NSCLC. Method A549 and HCC-15 cells were used in experimental design. Cell viability was determined by morphological image, crystal violet staining and MTT assay. Apoptosis was evaluated by LDH assay, Annexin V and DAPI staining. Autophagy and apoptosis indicator protein were examined by western blotting. TEM and puncta assay were carried out to evaluate the autophagy. MTP and ROS activity were evaluated by JC-1 and H₂DCFDA staining. Findings Resveratrol is a polyphenolic compound capable of activation of tumor suppressor p53 and its pro-apoptotic modulator PUMA. Herein, we showed the p53-independent apoptosis by decrease the expression of phosphorylated Akt-mediated suppression of NF-κB that is also substantiated with the downregulation of anti-apoptotic factors Bcl-2 and Bcl-xl in NSCLC, resulting in an attenuation of TRAIL resistance in combined treatment. Furthermore, apoptosis was induced in TRAIL-resistant lung cancer cells with a co-treatment of resveratrol and TRAIL assessed by the loss of MMP, ROS generations which resulting the translocation of cytochrome c from the mitochondria into the cytosol due to mitochondrial dysfunction. Moreover, autophagy flux was not affected by resveratrol-induced TRAIL-mediated apoptosis in NSCLC. Significance Overall, targeting the NF-κB (p65) pathway via resveratrol attenuates TRAIL resistance and induces TRAIL-mediated apoptosis which could be the effective TRAIL-based cancer therapy regimen.

The chemopreventive effects of various mixed cereal grain (MCG) samples on azoxymethane (AOM, 10 mg/kg) and dextran sulfate sodium (DSS, 2% w/v)-induced colorectal cancer (CRC) in C57BL/6J mice were studied. The main MCG preparation consisted of fermented brown rice (FBR), glutinous brown rice, glutinous Sorghum bicolor, glutinous Panicum miliaceum, Coix lacryma-jobi and black soybean at an appropriate mixing ratio. Other MCG preparations contained rice coated with 5% Phellinus linteus and 5% Curcuma longa (MGR-PC), or 10% Phellinus linteus (MCG-P), or 10% Curcuma longa (MCG-C). Consumption of dietary MCG-PC by CRC mice significantly increased colon length, decreased the ratio of colon weight to length, and reduced the number of colon tumors. Similar effects, although to a lower extent, were observed in CRC mice fed with MCG-P, followed by those fed with MCG-C, MCG, FBR or white rice (WR). MCG-PC significantly suppressed colonic neoplasia, and decreased the levels of various cytokines (tumor necrosis factor: Tnf, interleukin 1 beta: Il1b, interleukin 6: Il6, and interferon gamma: Ifng) in serum and colon tissue of the CRC mice. In addition, MCG-PC increased the mRNA expressions of tumor protein p53(Tp53) and cyclin-dependent kinase inhibitor 1A(Cdkn1a), activated pro-apoptotic caspase 3(Casp3), and reduced expression of both mRNA and protein of inducible inducible nitric oxide synthase 2 (Nos2), prostaglandin-endoperoxide synthase 2 (Ptgs2), and cyclin D1(Ccnd1) in colon tissue. These findings suggest that than compared with other cereal grain preparations, MCG-PC had a greater activity against AOM/DSS-induced CRC by reducing intestinal inflammation, and modulating the expression of certain carcinogenesis related factors (Nos2, Ptgs2, Tp53, Cdkn1a, Ccnd1 and Casp3) in colon tissue of CRC mice.

Mitochondria are highly dynamic organelles that continuously change their shape. Their main function is ATP production; however, they are additionally involved in a variety of cellular phenomena, such as apoptosis, cell cycle, proliferation, differentiation, reprogramming, and aging. The change in mitochondrial morphology is closely related to the functionality of mitochondria. Normal mitochondrial dynamics are critical for cellular function, embryonic development, and tissue formation. Thus, defect in proteins involved in mitochondrial dynamics that control mitochondrial fusion and fission can affect cellular differentiation, proliferation, cellular reprogramming, and aging. Here we review the processes and proteins involved in mitochondrial dynamics and its various associated cellular phenomena.

Developing countries, including Small Island Developing States (SIDS) and Least Developed Countries (LDCs), are exceptionally vulnerable to climate change due to their distinct geographical and environmental characteristics. The impacts of climate change extend across their ecosystems, water resources, and vital economic sectors, such as food systems, health, education, and energy. Escalating sea levels and heightened salinity levels imperil freshwater reserves, while warmer ocean temperatures and acidification disrupt water demand, tourism, health services, and fisheries. Furthermore, developing countries bear the brunt of water shortages, flooding, and deteriorating water quality. Alarmingly, nearly two-thirds of the global population experience severe water scarcity for at least one month annually, with the majority residing in developing countries. By 2025, half of the world's population could inhabit areas grappling with water scarcity, predominantly concentrated in developing nations. In this context, innovative adaptation strategies, notably transformative wastewater projects, are imperative for fostering sustainability and resilience in these regions. However, significant barriers impede progress, creating a stark disparity between current financing capabilities and the imperative to fund water security initiatives. Compounding these challenges, developing countries find themselves ensnared in a burgeoning debt crisis, marked by escalating interest rates and inflation, which threatens to impede developmental progress and curtail investments in adaptation and mitigation endeavors. Consequently, there arises a critical necessity to harness innovative financial mechanisms to transform these debts into assets that facilitate climate action. This paper meticulously explores the potential of debt-for-climate swaps as a catalyst for advancing transformative wastewater projects, with a focused lens on their strategic deployment to underpin critical initiatives. Through rigorous examination of case studies and empirical evidence, the paper elucidates how debt-for-climate swaps can effectively bolster sustainable wastewater management systems in developing countries. Furthermore, it delineates best practices for leveraging these mechanisms to fortify environmental sustainability and resilience. Additionally, the paper delineates the roles and responsibilities of key stakeholders, including governments, policymakers, the private sector, communities, and climate financial institutions. By amalgamating theoretical insights with tangible examples, this paper furnishes a comprehensive framework for harnessing debt-for-climate swaps to enhance water security and resilience in developing countries. It endeavors to furnish actionable strategies for policymakers, practitioners, and stakeholders to navigate the complex terrain of climate change and engender sustainable development.

In this study, reinforcement learning (RL) was used in factory simulation to optimize storage devices for use in Industry 4.0 and digital twins. First, we defined an RL environment, modeled it, and validated its ability to simulate a real physical system. Subsequently, we introduced a method to calculate reward signals and apply them to the environment to ensure the alignment of the behavior of the RL agent with the task objective. The stocker simulation model was used to validate the effectiveness of RL. The model is a storage device that simulates logistics in a manufacturing production area. The results revealed that RL is a useful tool for automating and optimizing complex logistics systems and increase the applicability of RL in logistics. We proposed a novel method for creating an agent through learning using the proximal policy optimization algorithm, and the agent was optimized by configuring various learning options. The application of reinforcement learning resulted in an effectiveness of 30% to 100%, and methods can be expanded to other fields.

This paper presents a low-cost C-band frequency-modulated continuous wave (FMCW) radar system for use in indoor through-wall metal detection. Indoor remote-sensing applications, such as through-wall detection and positioning, are essential for the comprehensive realization of the internet of things or super-connected societies. The proposed system comprises a two-stage radio-frequency power amplifier, a voltage-controlled oscillator, circuits for frequency modulation and system synchronization, a mixer, a 3-dB power divider, a low-noise amplifier, and two cylindrical horn antennas (Tx/Rx antennas). The antenna yields gain values in the 6.8 ~ 7.8 range when operating in the 5.83 ~ 5.94 GHz frequency band. The backscattered Tx signal is sampled at 4.5 kHz using the Arduino UNO analog-to-digital converter. Thereafter, the sampled signal is transferred to the MATLAB platform and analyzed using a customized FMCW radar algorithm. The proposed system is built using commercial off-the-shelf components, and it can detect targets within a 56.3 m radius in indoor environments. In this study, the system could successfully detected targets through a 4-cm-thick ply board with a measurement accuracy of less than 10 cm.

VE is a powerful technique for analyzing a design with a focus on functionality, reducing costs, and increasing value. However, in order to proceed with the design of VE, the theoretical basis for the VE target selection process, which must be preceded in the preparation stage, is lacking, and as a result, it is difficult to verify the most effective target selection. Thus, a theoretical basis is needed. In this study, we intend to quantify the WORTH value of the COST TO WORTH technique and present an objective model of the target selection method using the derived Value Index (VI). For this purpose, cost worth (WORTHC) was calculated based on the performance data of 1,008 cases of 15 building types provided by the Domestic Public Procurement Service and the share of 83 detailed processes in 7 fields. Then, a survey was conducted targeting the ordering companies, and the final worth (WORTHF) was calculated by multiplying the derived customer value (WORTHV ) weight for each detailed work type. We calculated the Value Index (VI) by comparing COST and WORTHF for each detailed construction type of the VE project and developed a model to select construction types that exceed the VI standard value derived using the standard error of the population. Both cost experts and non-cost experts can use the developed model to specify the VE target selection criteria in order to easily select the key target, objectively sort the values that serve as the basis for calculating the value index and make it possible to more easily select the VE target selection criteria based on theoretical evidence. Also, the model can be used to obtain effective detailed design VE results.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by swelling in at least one joint. Owing to an overactive immune response, extra-articular manifestations are observed in certain cases, with interstitial lung disease (ILD) being the most common. Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is characterized by chronic inflammation of the interstitial space, which causes fibrosis and the scarring of lung tissue. Controlling inflammation and pulmonary fibrosis in RA-ILD is important because they are associated with high morbidity and mortality. Pirfenidone and nintedanib are specific drugs against idiopathic pulmonary fibrosis and have shown efficacy against RA-ILD in several clinical trials. Immunosuppressants and disease-modifying antirheumatic drugs (DMARDs) with antifibrotic effects have also been used to treat RA-ILD. Immunosuppressants moderate the overexpression of cytokines and immune cells to reduce pulmonary damage and slow the progression of fibrosis. DMARDs with mild antifibrotic effects target specific fibrotic pathways to regulate fibrogenic cellular activity, extracellular matrix homeostasis, and oxidative stress levels. Therefore, specific medications are required to effectively treat RA-ILD. In this review, the commonly used RA-ILD treatments are discussed based on their molecular mechanisms and clinical trial results. In addition, a computational approach is proposed to develop specific drugs for RA-ILD.

Spectral image analysis has the potential to replace traditional approaches for assessing plant responses to different types of stress including herbicide, through non-destructive and high-throughput screening (HTS). Therefore, this study was conducted to develop a rapid bioassay method using a multi-well plate and spectral image analysis for diagnosis of herbicide activity and mode of action. Crabgrass (Digitaria ciliaris) as a model weed was cultivated in multi-well plates and subsequently treated with 6 herbicides with different modes of action when they reached the 1-leaf stage, using only a quarter of the recommended dose. To detect plant response to herbicides, plant spectral images were acquired after herbicide treatment using RGB, infrared (IR) thermal, and chlorophyll fluorescence (CF) sensors and analyzed for diagnosing herbicide efficacy and mode of action. Principal Component Analysis (PCA) using all spectral data successfully distinguished herbicides and clustered depending on their modes of action. The performed experiments have shown that the multi-well plate assay combined with spectral image analysis can be successfully applied for herbicide bioassay. In addition, the use of spectral image sensors, especially in CF image, would facilitate HTS by enabling rapid observation of herbicide response, as early as 3 hours after herbicide treatment.

(1) Background: This study, drawing from the theoretical framework of the Theory of Planned Behavior (TPB), examines the structural relationship among attitudes, subjective norms, perceived behavioral control (PBC), and behavioral intention. The study focuses on investigating how the perceived risk associated with particulate matter moderates the relationships between 'attitudes and behavioral intention,' 'subjective norms and behavioral intention,' and 'PBC and behavioral intention' within the context of individuals engaged in outdoor sports; (2) Methods: The data were collected from outdoor sports gatherings facilitated through a popular South Korean sports meetup application. Confirmatory factor analysis was employed to establish the construct validity of the measurement scale, assess factor loadings, averaged variance extracted (AVE), and construct reliability (CR). We also ensured the reliability of the measurement scale through Cronbach's α analysis. To achieve our research objectives, we utilized structural equation modeling with maximum likelihood estimation to examine the positive relationships under investigation. Additionally, we performed moderation analysis using the statistical software Jamovi.; (3) Results: The findings demonstrate the significant impacts of attitudes, subjective norms, and PBC on behavioral intention and reveal that perceived risk acts as a moderator, influencing the relationship between PBC and behavioral intention.; (4) Conclusions: Therefore, the government will need to exert substantial efforts to mitigate particulate matter levels.

At the LHC, the process of a Higgs boson decaying into bottom or charm quarks produced in association with a pair of top quarks, tt¯H, allows for an empirical exploration of the heavy-flavor quark Yukawa couplings to the Higgs boson. Accordingly, the cross sections for the tt¯ + heavy-flavor production without the appearance of the Higgs boson have been measured at the LHC in various phase spaces using data samples collected in pp collisions at s = 7, 8 and 13 TeV with the ATLAS and CMS experiments. Flavor ratios of cross sections of tt¯ + additional jets processes with different flavors are also measured. In this paper, the measured cross sections and ratios are reviewed and the prospects with more data are presented.

Caries is a prevalent oral disease that primarily affects children and teenagers. Advances in ma-chine learning have caught the attention of scientists working with decision support systems to predict early tooth decay. Current research has developed machine learning algorithm for caries classification and reached high accuracy especially in ML for image data. Unfortunately, most studies on dental caries only focus on classification and prediction tasks, meanwhile dental carries prevention is more important. Therefore, this study aims to design an efficient feature for decision support system machine learning based that can identify various risk factors that cause dental caries and its prevention. The data used in the research work was obtained from the 2018 Korean Children's Oral Health Survey, which totaled nine datasets. The experimental results show that combining the mRMR and GINI Feature Importance methods when training with the GBDT model achieved the optimum performance of 95%, 93%, 99%, and 88% for accuracy, F1 score, precision, and recall, respectively. So, the proposed method has provided effective predictive model for dental caries prediction.

This study examined the effects of group art therapy on depression, burden, and self-efficacy in primary family caregivers of patients with brain injuries. This was a quasi-experimental, nonequivalent control group and a pre- and post-test design. This study was carried out in one national rehabilitation hospital targeting 41 primary family caregivers of patients with brain injuries. Group art therapy intervention was carried out three days per week for 12 times over four consecutive weeks. The experimental group (n = 20) received group art therapy, whereas the control group (n = 21) did not. We used a time difference method to minimize the risk of contaminating the control group by sampling sequentially. The experimental group showed a significantly greater decrease in burden (t = 2.462, p = 0.020) and significantly greater improvement in self-efficacy (t = −6.270, p &lt; 0.001) than the control group. Group art therapy may be an effective nursing intervention for primary family caregivers of patients with brain injuries.

This study compared condylar volume, length, and articular eminence (AE) characteristics in normal individuals and those with unilateral and bilateral juvenile idiopathic osteoarthritis (JOA). The 116 patients were divided into four groups: control (n=16), affected condyle of unilateral JOA (Aff-Uni) (n=36), non-affected condyle of JOA (NonAff-uni) (n=36), and bilateral JOA (Bi-JOA) (n=28). Volume and length differences in the condyle and AE were analyzed using ANOVA and Bonferroni post hoc tests. The results showed that Bi-JOA had significantly different condylar volume, especially in the condylar head (p&lt;0.01), specifically the middle, anterior, and medial parts (p&lt;0.05). Condylar length also differed among the groups, with differences observed between the control group and the other three groups, as well as between the bilateral group and the other three groups (p&lt;0.01). AE total volume differed between the control group and Aff-Uni. In the detailed comparison, Aff-Uni and NonAff-Uni were smaller than the control group in the posterior, lateral, and medial sections (p&lt;0.05). In conclusion, depending on the involvement of unilateral or bilateral JOA, there were differences in condylar volume and AE compared to the normal control group. Therefore, prognosis should be evaluated by distinguishing between patients with unilateral and bilateral JOA.

This study aims to provide an updated overview of the systematic evaluation and management of Post-Traumatic trigeminal neuropathic pain (PTTN) resulting from dental procedures or trauma. PTTN arises following an injury to the trigeminal nerve, which is responsible for sensory and motor functions in the maxillofacial region. The etiology encompasses various dental procedures and craniofacial trauma, leading to a spectrum of symptoms, from tingling to severe pain. Diagnostic challenges stem from the absence of standardized criteria and the overlap with focal neuralgia, necessitating comprehensive evaluation. Misdiagnosis can result in prolonged suffering and unnecessary procedures. Successful management hinges on prompt diagnosis and interdisciplinary collaboration, with early intervention crucial in mitigating chronicity. While nerve recovery post-trauma is challenging, preventive measures through accurate evaluation and treatment are paramount.  Management for PTTN includes non-invasive and surgical interventions. Non-invasive intervention includes systematic and local pharmacological management. This review enhances uniformity in PTTN evaluation and treatment approaches despite standardized study limitations.

The recent increase in global consumption of rice has led to increased demand for sustainable water management in paddy cultivation. In this study, we propose an enhanced paddy simulation module to be introduced to Soil and Water Assessment Tool (SWAT) to evaluate the sustainability of paddy cultivation. The enhancements added to SWAT include: (1) modification of water balance calculation for impounded fields, (2) addition of an irrigation management option for paddy fields that are characterized by flood irrigation with target water depth, and (3) addition of a puddling operation that influences the water quality and infiltration rate of the top soil layer. In a case study, the enhanced model, entitled SWAT-Paddy, was applied to an agricultural watershed in Japan. The results showed that the SWAT-Paddy successfully represented paddy cultivation, water management, and discharge processes. Simulated daily discharge rates with SWAT-Paddy (R² = 0.8) were superior to the SWAT result (R² = 0.002). SWAT-Paddy allows the simulation of paddy management processes realistically, and thus can enhance model accuracy in paddy-dominant agricultural watersheds.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.

This study analyzed eye examination data from the 5th Korea National Health and Nutrition Examination Survey to investigate the relationship between cataract prevalence and sunlight exposure among Koreans. Out of 952 individuals from 192 districts surveyed from January to December, statistical analyses using SPSS version 26, including chi-square tests and logistic regression, were conducted. Results: Results showed that the incidence of cataracts was higher in people exposed to sunlight for more than 5 hours. Regarding gender, the incidence of cataracts was higher in female in the 2-5 hours of sunlight exposure group, and in male in the group exposed to sunlight for more than 5 hours. Age significantly increased cataracts after age 45 in both groups. Additionally, the prevalence was higher among college graduates in the 2 to 5 groups, and among elementary school graduates in the more than 5 hours usage group. In urban areas, the cataract prevalence rate was higher in the 2-5-hour usage group, and in rural areas, the cataract prevalence was higher in the more than 5-hour usage group. In conclusion, prolonged sunlight exposure, particularly over 5 hours, correlated with higher cataract prevalence among Koreans, with various demographic factors influencing incidence rates.

A road network represents road objects in a given geographic area and their interconnections, and is an essential component of intelligent transportation systems (ITS) enabling emerging new applications such as dynamic route guidance, driving assistance systems, and autonomous driving. As the digitization of geospatial information becomes prevalent, a number of road networks with a wide variety of characteristics coexist. In this paper, we present an area partitioning approach to the conflation of two road networks with a large difference in level of details. Our approach first partitions the geographic area by the Network Voronoi Area Diagram (NVAD) of low-detailed road network. Next, a subgraph of high-detailed road network corresponding to a complex intersection is extracted and then aggregated into a supernode so that a high matching precision can be achieved via 1:1 node matching. To improve the matching recall, we also present a few schemes that address the problem of missing corresponding object and representation dissimilarity between these road networks. Numerical results at Yeouido, Korea's autonomous vehicle testing site, show that our area partitioning approach can significantly improve the performance of road network matching.

Radar observation data with high temporal and spatial resolution are used in the data assimilation experiment to improve precipitation forecast of a numerical model. The numerical model considered in this study is Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated radar equivalent reflectivity factor using higher resolution WRF and compared with radar observations in South Korea. To compare the precipitation forecast characteristics of three-dimensional variational (3D-Var) assimilation of radar data, four experiments are performed based on different precipitation types. Comparisons of the 24-h accumulated rainfall with Automatic Weather Station (AWS) data, Contoured Frequency by Altitude Diagram (CFAD), Time Height Cross Sections (THCS), and vertical hydrometeor profiles are used to evaluate and compare the accuracy. The model simulations are performed with and with-out 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The radar data assimilation experiment improved the location of precipitation area and rainfall intensity compared to the control run. Especially, for the two convective cases, simulating mesoscale convective system was greatly improved.

The purpose of this paper is to find the time optimal control to a target set for semilinear stochastic functional differential equations involving time delays or memories under general conditions on a target set and nonlinear terms even though the equations contain unbounded principal operators. Our research approach is construct a fundamental solution for corresponding linear systems and establish variations of constant formula of solutions for given stochastic equations. The existence result of time optimal controls for one point target set governed by the given semilinear stochastic equation is also established.

This study used secondary data from the 2017 Korean Community Health Survey to compare the associations of socio-physical environment, social support networks, and social activities with happiness among older adults with three different family types. As per the results, there was a significant difference in happiness index between the three groups (F = 86.688, p < .001). Older adults living alone (odds ratio (OR) = 0.75, 95% confidence interval (CI) = 0.57–0.99) and those living with family (OR = 0.80, 95% CI = 0.65–0.99) showed greater happiness as the frequency of contact with family increased. Older adults living with only their spouse showed an increase in happiness when their contact with friends was higher (OR = 0.69, 95% CI = 0.56–0.84). It was confirmed that there were differences in factors influencing happiness according to the family type of the older adults in this study. Therefore, the happiness of older adults needs to be adequately ensured, while considering their various circumstances, including family type.

Lately, the Critical Pathway(CP) of Electronic Medical Record(EMR) is used to the guideline for a treatment in the public hospital. We propose a healthcare promotion service using disease pattern with lifestyle risk factors. We classify a medical historical patient data with disease codes with lifestyle risk factors (hypertension, diabetes, smoking, overweight, excessive alcohol intake, and low physical activity) to make the lifestyle risk factors through the classification. We finally make the clusters of disease code with lifestyle risk factors using the medical historical data based on EMR's electronic discharge summary data. As the result of that, we do a healthcare recommending service based on the disease pattern with lifestyle risk. We can build a medical help desk of a public hospital to support people as we check into the public hospital; how to get the procedure of curing, the desired curing clinical method for the healthcare promotion service by each disease code, and how to be better our healthcare. We evaluate the performance of the proposed system by experimenting with the datasets collected at the medical center to measure performance and report some experimental results.

Radiator reliability is crucial in environments characterized by high temperatures and friction, where prompt interventions are often required to prevent system failures. This study introduces a proactive approach to radiator fault diagnosis, leveraging the integration of Gaussian Mixture Model (GMM) and Long-Short Term Memory (LSTM) autoencoders. Vibration signals from radiators were systematically collected through randomized durability vibration bench tests, resulting in four operating states—two normal, one unknown, and one faulty. Time-domain statistical features of these signals were extracted and subjected to Principal Component Analysis (PCA) to facilitate efficient data interpretation. Subsequently, this study discusses the comparative effectiveness of GMM and LSTM in fault detection. GMMs are deployed for initial fault classification, leveraging their clustering capabilities, while LSTM autoencoders excel in capturing time-dependent sequences, facilitating advanced anomaly detection for previously unencountered faults. This alignment offers a potent and adaptable solution for radiator fault diagnosis, particularly in challenging high-temperature or high-friction environments. Consequently, the proposed methodology not only provides a robust framework for early-stage fault diagnosis but also effectively balances diagnostic capabilities during operation. Additionally, this study presents the foundation for advancing reliability life assessment in accelerated life testing, achieved through dynamic threshold adjustments using both the absolute log-likelihood distribution of the GMM and the reconstruction error distribution of the LSTM autoencoder model.

Coastal areas are increasingly being damaged with the expansion of seawater intrusion areas. We suggest a three-step method for reducing seawater intrusion areas by predicting future damage to groundwater being used continuously. First, the area most vulnerable to seawater intrusion damage is selected from among 25 areas on the west coast of the Republic of Korea. Having identified the Taean area as the region in question in the second step, we use RCP 4.5 and 8.5 as future sea level rise scenarios and predict the future usage of groundwater using linear-regression analysis of data for the past 10 years. Consequently, for RCP 8.5 (groundwater-usage scenario 1.0), 68.5% of the total Taean area is projected to be influenced by seawater intrusion. In the third step, the effectiveness of seawater intrusion reduction measures is analyzed considering the projected future situation and the local characteristics of the Taean area. After considering the effects of alternative locations, as well as seawater intrusion related data, alternatives were prioritized using a multi-criteria decision-making method. Consequently, 3, 5, and 4 were prioritized in the listed order, and we judged that by applying seawater intrusion area reduction measures according to this result, we will achieve the biggest effect.

The EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI), EULAR Sjogren’s Syndrome Patient Reported Index (ESSPRI), and other patient-reported outcomes (PROs), such as the visual analog scale (VAS) for symptoms and EULAR sicca score (ESS), are used to assess the disease activity of primary Sjögren’s syndrome (pSS). Recently, Clinical ESSDAI (ClinESSDAI) and Clinical Trials ESSDAI (ClinTrialsESSDAI) were developed for objective clinical disease activity indexes. However, the relationship of ClinESSDAI and ClinTrialsESSDAI with PROs as well as that between ESSPRI and other PROs and the objective parameters of glandular function in pSS have not been established. Herein, we investigated the correlation of ESSPRI and other PROs with the objective parameters of glandular function and the relationship of PROs with ClinESSDAI and ClinTrialsESSDAI in 66 patients with pSS. Correlations were calculated with Spearman’s correlation coefficient. ClinTrialsESSDAI was correlated with ESSPRI, dryness (ESSPRI-Dryness), fatigue, and pain domains of ESSPRI, VAS for oral dryness (oral-VAS), and patient’s global assessment. Although ESSPRI did not correlate with the objective parameters of glandular function, ESSPRI-Dryness, ESS, and oral- and ocular-VAS did. These results suggest that ESSPRI-Dryness, ESS, and VAS for symptoms, but not ESSPRI, reflect the glandular dysfunction and that ClinTrialsESSDAI correlates with PROs for dryness in pSS.

Background: Inflammasomes recognize cytosolic danger signals, including pathogens, and subsequently induce the secretion of pro-inflammatory cytokines, such as interleukin (IL)-1β. Studying inflammasomes in the red fox (Vulpes vulpes) is crucial from a wildlife veterinary and public health perspective, as it can be used to help control and prevent the transmission of zoonotic pathogens. The understanding of how diversity in inflammasomes across species affects pathogen carriage in the red fox is still limited. Methods: We investigated the activation and intracellular mechanisms of three inflammasomes (NLRP3, AIM2, and NLRC4) in fox peripheral blood mononuclear cells (PBMCs), using established triggers and inhibitors derived from humans and mice. Results: Fox PBMCs exhibited normal activation and induction of IL-1β secretion in response to representative inflammasome triggers (ATP and nigericin for NLRP3, dsDNA for AIM2, flagellin for NLRC4). However, in inhibitor studies, MCC950, a selective NLRP3 inhibitor, suppressed IL-1β secretion mediated by the fox AIM2 and NLRC4 inflammasomes. Conclusions: These findings suggest that NLRP3 may have a common role in dsDNA- and flagellin-mediated inflammasome activation in the red fox. In conclusion, this fox inflammasome biology can be applied to the control of zoonotic infections and the treatment of inflammasome-mediated diseases in the red fox.

To expand the application scope and increase the demand for non-crimp fabrics (NCFs) as a lightweight vehicle material, the delamination and thermal strain in NCF composites must be restricted. Accordingly, to simultaneously improve the interfacial bonding and thermal stability of the NCF composites, in this study the epoxy resin, in which SiO2 nanoparticles was modified by a silane coupling agent, were infused to the stacked NCFs and between the layers of NCFs through the vacuum-assisted resin infusion molding (VARIM) process.

Dendritic cells (DCs) are the professional antigen-presenting cells that recognize and present antigens to naïve T cells to induce antigen-specific adaptive immunity. Among the T-cell subsets, T helper type 2 (Th2) cells produce the humoral immune responses required for protection against helminthic disease by activating B cells. DCs induce a Th2 immune response at a certain immune environment. Basophil, eosinophil, mast cells, and type 2 innate lymphoid cells also induce Th2 immunity. However, in the case of DCs, controversy remains regarding which subsets of DCs induce Th2 immunity, which genes in DCs are directly or indirectly involved in inducing Th2 immunity, and the detailed mechanisms underlying induction, regulation, or maintenance of the DC-mediated Th2 immunity against allergic environments and parasite infection. A recent study has shown that a genetic defect in DCs causes an enhanced Th2 immunity leading to a severe atopic dermatitis. We summarize the Th2 immune-inducing DC subsets, the genetic and environmental factors which involved in DC-mediated Th2 immunity, and current therapeutic approaches for Th2-mediated immune disorders. This review is to provide an improved understanding of DC-mediated Th2 immunity and Th1/Th2 immune balancing, leading to control over their adverse consequences.

This study examined ways to prevent failures in the front-end of forklifts by addressing the center of gravity of heavy objects carried by forklifts, predicting the remaining useful lifetime (RUL), and the fault diagnosis based on alarm rules. In the research process, acceleration signals were acquired from the outer beam of the front-end of the forklift. A one-second window was applied to extract the time-domain statistical features, which were then set as variables. An exponentially weighted moving average was used to smooth the noise in the feature data set. The AWGN and LSTM autoencoders were used for data augmentation. Based on them, random forest and lightGBM models were used to develop classification models for the weight center of heavy objects carried by a forklift. In addition, contextual diagnosis performed by applying exponentially weighted moving averages to the classification probabilities of the machine learning models showed that random forest achieved an accuracy of 0.9563 and lightGBM achieved an accuracy of 0.9566. In addition, the acceleration data were collected through experiments to predict forklift failure and RUL because of the repeated forklift use when the center of heavy objects carried by the forklift was skewed to the right. The time-domain statistical features of the acceleration signals were extracted and set as variables by applying a 20-second window. Subsequently, logistic regression and random forest models were used to classify the failure stages of the forklifts. The f1-score (macro) obtained were 0.9790 and 0.9220 for logistic regression and random forest, respectively. In addition, the random forest probabilities for each stage were combined and averaged to generate a degradation curve and derive the failure threshold. The coefficient of the exponential function was calculated using the least squares method on the degradation curve, and the RUL prediction model was developed to predict the failure point. In addition, the SHAP algorithm was used to identify the significant features in classifying the stage. The alarm rule-based fault diagnosis was performed using the threshold of the normal stage distribution of the significant features.

This study is focused on the development of criteria for night and visual line of sight (VLOS) flights, especially in the context of beyond visual line of sight (BVLOS) drone applications. While BVLOS technology is advancing globally, regulatory restrictions and conservative legal regulations often prohibit these flights. The goal is to provide experimental guidelines for operational procedures in night and BVLOS flights. The study aims to establish empirical criteria for physical distances in night and VLOS flights, using a test team composed of a pilot, recorder, and observers. The observers are tasked with assessing the identification and recognition distances, which are crucial for safe drone operations. The criteria established are based on different variables such as aircraft size, altitude, and visual acuity. This research involves extensive flight tests at varying altitudes using different types of drones and observers with differing visual acuities (20/20, 20/13.3, and 20/10). The study also examines the effect of communication equipment limitations on recognition distance and the use of lighting devices to minimize abnormal conditions during nighttime flights. Overall, the study's findings aim to contribute to the safe and efficient planning of BVLOS and night drone flights, especially considering the ever-evolving technology and regulatory landscape in this field.

The ground consists of many layers of soil with different properties. The propagation speed and path of seismic waves are affected by different soil layers. It is necessary to understand that layered soil exhibits different dynamic behaviors and responses under the action of seismic waves. This study utilized weathered soil and silica sand as materials to create multi-layered soil conditions with varying degrees of compaction. By conducting 1 g shaking table test on multi-layered soil, the interaction and influence between different soil layers under different earthquake conditions were observed. The approach of numerical analysis aims to validate the experimental results and provide an in-depth understanding of the dynamic behaviors of multi-layered soil grounds during seismic events. The results of this study show that the amplification effect of seismic waves is related to the number of soil layers and the degree of compaction of the soil layers. This indicates that the multi-layered soil ground and the behavior of the soil layers play an important role in the propagation and impact of seismic waves, and this amplification effect is of great significance in actual seismic disaster risk assessment and design.

Disease detection and prediction have been one of the most frequent uses of machine learning models in the last decade, and Parkinson's disease is no exception. It is common for people in their old age to have one form of disease or another depending on the circumstances in which they find themselves. This study analyzed and evaluated various supervised machine learning models to detect the presence of Parkinson's disease in elderly individuals. An extreme gradient boosting model, along with other models, such as naïve Bayes, random forest, K-nearest neighbor, and support vector machine (SVM), was implemented to determine the best outcome. The extreme gradient boosting (XGBoost) model is a powerful boosting machine learning technique, particularly in terms of speed and accuracy. The results showed that the XGBoost model, which is an optimized version of the other boosting models, is capable of projecting the presence of Parkinson's disease with very high accuracy compared to other algorithms. The implemented classification algorithm extreme gradient boosting method achieved approximately 98 % accuracy, 97.5 % precision, 100.0 % recall, and 98.7% f1-score which are high compared with the results found in the existing literature.

The calculation of the global shear capacity of steel-concrete composite downstand cellular beams with precast hollow-core units is important as it affects the span to depth ratios and the amount of material used, hence affects the embodied CO2 calculation when designers are deciding on the floor grids. This paper presents a reliable tool that can be used by designers to alter and optimise grip options during the preliminary design stages, without the need to run onerous calculations. The global shear capacity prediction formula is developed using five machine learning models. First, a finite element model database is developed. The influence of the opening diameter, web opening spacing, tee-section height, concrete topping thickness, the interaction degree, and the number of shear studs above the web opening are investigated. Reliability analysis is conducted to assess the design method and propose new partial safety factors. The Catboost Regressor algorithm presented better accuracy compared to the other algorithms. An equation to predict the shear capacity of composite cellular beams with hollow-core units is proposed by Gene Expression Programming. In general, the partial safety factor for resistance, according to the reliability analysis, varied between 1.25 and 1.26.

During early embryonic development, fertilized one-cell embryos develop into preimplantation blastocysts and subsequently establish three germ layers through gastrulation during post-implantation development. In recent years, stem cells have emerged as a powerful tool to study embryogenesis and gastrulation without the need for eggs, allowing the generation of embryo-like structures known as synthetic embryos or embryoids. These in vitro models closely resemble early embryos in terms of morphology and gene expression and provide a faithful recapitulation of early pre- and post-implantation embryonic development. Synthetic embryos can be generated through a combinatorial culture of three blastocyst-derived stem cell types, such as embryonic stem cells, trophoblast stem cells, and extraembryonic endoderm cells, or totipotent-like stem cells alone. This review provides an overview of the progress and various approaches in studying in vitro embryogenesis and gastrulation using stem cells. Furthermore, recent findings and breakthroughs in synthetic embryos and gastruloids are outlined. Despite ethical considerations, synthetic embryo models hold promise for understanding mammalian (including human) embryonic development and have potential implications for regenerative medicine and developmental research.

This study uses explainable artificial intelligence to analyze major predictors of poor self-rated health, dementia and their comorbidity, which include various aspects of social support. Data came from the Korean Longitudinal Study of Ageing (2016-2018), with 5527 participants aged 56 or more. The dependent variables were: (1) poor self-rated health (SRH) with 5 categories (very good, good, middle, poor, very poor); (2) dementia (no, yes); and (3) their comorbidity with 4 categories (SRH very good, good or middle, dementia no; SRH very good, good or middle, dementia yes; SRH poor or very poor, dementia no; SRH poor or very poor, dementia yes). The 49 demographic, socioeconomic and health-related predictors were included. The accuracy and area under the receiver operating characteristic curve (AUC) were compared for logistic regression and the random forest. Logistic regression and the random forest registered similar AUCs with the range of 0.80-0.87. Based on random forest variable importance, 18 out of top-20 predictors were identical for SRH, dementia and their comorbidity: previous SRH, life satisfaction - health, age, body mass index, income, chronic diseases, life satisfaction - economic, life satisfaction - overall, grandchildren alive, friendship meeting, brothers/sisters alive, class identity, children alive, social activity - friendship, education, children in weekly contact, religion and drinker. However, some variations were found among the three dependent variables, i.e., previous SRH for comorbidity (1st) and SRH (1st) compared to dementia (11th), grandchildren alive for SRH (6th) and dementia (4th) compared to comorbidity (9th), chronic diseases for comorbidity (6th) compared to SRH (10th) and dementia (10th). In terms of Shapley Additive Explanation (SHAP) values, the probability of dementia is expected to decrease by 5.57% in case a predictor grandchildren alive is included to the model. This study highlights the importance of social support for the prediction of poor self-rated health, dementia and their comorbidity. Specifically, the promotion of family support and friendship activity for elders would be vital for the prevention and management of their self-rated health and dementia.

In this paper, we perform the neural cryptanalysis and comprehensively analyze five block ciphers, Data Encryption Standard (DES), Simplified DES (SDES), Advanced Encryption Standard (AES), Simplified AES (SAES), and SPECK. The vulnerability of the block ciphers is investigated in three different attacks, such as Encryption Emulation (EE), Plaintext Recovery (PR), Key Recovery (KR), and Ciphertext Classification (CC) attacks. For the plaintexts, randomly generated block-sized bit arrays and texts are used. The block ciphers apply different numbers of round functions in the encryption of the block-sized bit arrays, and they are investigated by using the deep learning models trained with different numbers of data in EE, PR, and KR attacks. Moreover, the block ciphers use two different text encryption methods, Word-based Text Encryption (WTE) and Sentence-based Text Encryption (STE), to encrypt the texts in various operation modes, and they are analyzed with deep learning models in EE, PR, and CC attacks. As a result, the block ciphers can be vulnerable to deep learning-based EE and PR attacks using a large amount of train data, and STE can improve the strength of the block ciphers, unlike WTE, which shows almost the same classification accuracy as the plaintexts, especially in CC attack. Additionally, when the keys that are the same as the plaintexts are used in encryption, the block ciphers can be perfectly broken in KR attack. Moreover, especially in KR attack, the RNN-based deep learning model shows higher average Bit Accuracy Probability (BAPavg) than the fully connected-based deep learning model, which is used more often in previous works of neural cryptanalysis. Furthermore, although the transformer-based deep learning model is a state-of-the-art model in Natural Language Processing (NLP), the RNN-based deep learning model is more suitable for CC attack and shows higher classification accuracy.

Residential segregation refers to the phenomenon where people of different socioeconomic backgrounds live in spatially separated areas. It is essential to ensure equitable access to urban amenities for all residents in pursuit of the normative values in urban planning. To achieve this planning goal, the disparity in accessibility to urban amenities needs to be appropriately diagnosed. Private apartments and public rental apartments are representative types of residences where residential segregation is likely to occur in the context of South Korea, since these two types show considerable differences in the education, income, and occupations. The objective of this study is to develop an analysis framework for diagnosing the difference in accessibility to urban amenities between the two residential types, and to empirically demonstrate their utility in the planning process. The empirical analysis conducted on Seoul revealed that not only were there significant local variations in accessibility between the two segregated residential areas, but the overall differences across the entire area were also pronounced. The proposed framework is useful in supporting decision-making processes for locating new public facilities or identifying regional priorities for guiding the placement of private amenities, with the aim of mitigating differences between segregated residential areas.

Although traditional automotive development has mainly focused on functional safety, as the number of automotive hacking cases has increased due to the growing Internet connectivity of automotive control systems, security is also becoming more important. Accordingly, various international organizations are preparing cybersecurity regulations or standards to ensure security in automotive development by emphasizing the concept of security-by-design(i.e. security engineering) which emphasizes trustworthiness from the beginning of development. The problem, however, is that no specific methodology has been suggested. In this paper, we propose a specific security-by-design methodology for automotive development based on Secure System Development Life Cycle (secure SDLC) standards and evidence-based standards. Our methodology could be easily used in the actual field as it is more general and detailed than existing secure SDLC standards and research. Also, since it satisfies all requirements of United Nations Economic Commission for Europe (UNECE) regulation, automobile manufacturers could respond to the upcoming cybersecurity regulation with our methodology.

The Geostationary Ocean Color Imager (GOCI) of the Communication, Ocean, and Meteorological Satellite (COMS) increases the chance of acquiring images with greater clarity at eight times a day and is equipped with spectral bands suitable for monitoring crop yield with a moderate spatial resolution. The objectives of this study were to classify nationwide paddy fields and to project rice (Oryza sativa) yield and production using the grid-based GRAMI-rice model and GOCI satellite products over South Korea from 2011 to 2014. Solar insolation and temperatures were obtained from COMS and the Korea local analysis and prediction system for model inputs, respectively. The paddy fields and transplanting dates were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and land cover products. The crop model was calibrated using observed yield data in 11 counties and was applied to 62 counties in South Korea. The overall accuracies of the detected paddy fields ranged from 89.5 to 90.2%. The simulated rice yields statistically agreed with observed yields, with root-mean-square errors of 0.219 to 0.451 ton ha-1 and Nash–Sutcliffe efficiencies of 0.241 to 0.733 in four years, respectively. According to paired t-tests (α = 0.05), the simulated and observed rice yields were not significantly different. These results demonstrate the possible development of a crop information delivery system that can classify land cover, simulate crop yield, and monitor regional crop production on a national scale.

The present study was conducted to evaluate encapsulated essential oils as an alternative anticoccidial in coccidiosis vaccine challenged broiler chickens. A total of 600 day-old male broiler chicks were provided with no-added corn-soybean meal-based control diet or diets that contained either salinomycin or EO at 60 and 120 mg per kg of diet. On day 21, half of the control groups were orally challenged with a coccidiosis vaccine at 25 times higher than the recommended vaccine dose. During 22 to 28 days (i.e., one-week post coccidiosis vaccine challenge), the challenged chickens had decrease (P < 0.05) in body weight gain and feed intake but increase in feed conversion ratio compared with the non-challenged, naïve control chickens. However, dietary EO significantly counteracted (P < 0.05) coccidiosis vaccine-induced depression in body weight gain and feed intake. Increasing dietary EO linearly decreased (P < 0.05) the concentrations of the volatile fatty acids. Dietary SAL and EO affected gut morphology in chickens at 20 days posthatch. Increasing dietary EO linearly (P = 0.073) increased serum catalase activity. Collectively, our study shows that dietary EO increased coccidiosis vaccine-induced growth depression and altered gut physiology in broiler chickens.

Stereotactic radiosurgery (SRS) is considered the initial treatment for lung cancer patients with small-sized and limited number of brain metastases. The objective of this study was to assess clinical outcomes of SRS treatment using CyberKnife (CK) for recursive partitioning analysis (RPA) class II/III patients with one to three brain metastases from lung cancer and identify which patients in the high RPA class could benefit from SRS. A total of 48 lung cancer patients who received CK-based SRS for their metastatic brain lesions from 2010 to 2017 were retrospectively analyzed. Radiographic response was evaluated during follow-up period. Overall survival (OS) and intracranial progression-free survival (IPFS) were calculated and prognostic variables associated with OS and IPFS were evaluated. Median follow-up time was 6.6 months. Local control rates at 6 months and 1-year following SRS were 98% and 92%, respectively. The median OS of all patients was 8 months. One-year and 2-year OS rates were 40.8% and 20.9%, respectively. In multivariate analysis, uncontrolled primary disease (p = 0.008) and ECOG performance status of 2 or 3 (p = 0.001) were independent prognostic factors for inferior OS. These two factors were also significantly associated with inferior IPFS. In subgroup analysis according to RPA class, primary disease status was the only prognostic factor, showing statistically significant OS differences in both RPA class II and III (controlled vs. uncontrolled: 41.1 vs. 12.3 months in RPA class II, p = 0.031; 26.9 vs. 4.1 months in RPA class III, p = 0.011). Our results indicated that SRS could be an effective treatment option for RPA class II/III patients with brain metastases from lung cancer in the modern treatment era. SRS might be particularly considered for patients with controlled primary disease.

Submucosal invasion is a critical step in gastric cancer (GC) progression, which greatly enhances metastasis risk. Cancer stem cells are responsible for invasion, metastasis, and tumor growth. To identify stem cell-related markers associated with submucosal invasion in GCs, we investigated the expression of candidate cancer stem cell (CSC) markers (CD133, CD44, and ALDH1A) and intestinal stem cell (ISC) markers (EPHB2, OLFM4, and LGR5) in early GCs with submucosal invasion. Remarkably, expression of all ISC markers and CD133 was frequently confined to the basal area of the lamina propria (basal pattern) in mucosal cancer. The proportion of stem cell marker-positive cells substantially increased during submucosal invasion. Given that ISC markers are restricted to the crypt base of the normal intestinal mucosa, these findings suggest that many early GCs may retain hierarchical characteristics. CD44 expression showed a focal pattern, ALDH1A was predominantly expressed diffusely, and there was no expansion of CD44 or ALDH1A expression in the submucosal cancer cells. RSPO2 from muscularis mucosa seem to be partly responsible for the increased expression of ISC markers in GC cells at the basal areas. We also found that ISC markers were correlated with CDX2 expression in GCs, indicating that ISC markers are involved in the intestinal differentiation in GCs. Interestingly, ISC markers (EPHB2 and OLFM4) and CD133 showed a positive impact on clinical outcomes. In particular, the prognostic value of EPHB2 was significant for intestinal-type GCs in a multivariate analysis. In summary, ISC markers and CD133 showed a basal distribution pattern along with enhanced expression in submucosal invading cells in early GCs. EPHB2 was an independent prognostic marker in intestinal-type GCs.

Although numerous citrus varieties have recently been developed to enhance their quality, information on their quality characteristics is limited. We assessed the quality characteristics of Yellowball, a novel citrus variety, by evaluating its appearance, storability, sensory properties, functionality, and metabolite profiles and comparing these characteristics with those of its parent varieties: Haruka and Kiyomi. The metabolite profiles between the citrus varieties differed significantly, resulting in distinct physicochemical and functional qualities. The storability of Yellowball was significantly increased compared with that of its parent varieties owing to its strong antifungal activity and unique peel morphology, including the stoma and albedo layers. While we did not investigate the volatile compounds, overall functional activities, and detailed characteristics of each metabolite, our data provide valuable insights into the relationship between citrus metabolites, peel morphology, physicochemical properties, and storability and demonstrate the potential of Yellowball as a promising variety in the citrus industry.

Perfluorinated compounds (PFCs) are used in the manufacturing process of the semiconductor and display industries, and the need for emission reduction is growing as a greenhouse gas with a very large global warming potential. The decomposition characteristics of etch type and water film (WF) type plasma-wet scrubbers were investigated. The PFCs used in the study were CF4, SF6, NF3, CHF3, C2F6, C3F8, and C4F8, and the destruction removal efficiency (DRE) and by-product gas generation rate according to the changes in the parameters (total flow rate and power) of the plasma-wet scrubber were confirmed. When the total flow rate was 100 L/min and the measured maximum power (11 kW), the reduction efficiency of CF4 in the etch type was 95.60 % and the DRE of other PFCs was 99.99 %. And, in the WF type, the DRE of CF4 was 90.06 %, that of SF6 was 96.44 %, and that of other PFCs was 99.99 %. When the total flow rate was 300 L/min and 11 kW, the DRE of SF6 in the etch type was 99 %, and the DRE of NF3, CHF3, C2F6, C3F8, and C4F8 were 99.80 %, 95.34 %, 85.38 %, 88.49 %, and 98.22 %, respectively. And, in the WF type, the DRE of SF6 was 94.39 %, and the DRE of NF3, CHF3, C2F6, C3F8, and C4F8 were 99.80 %, 95.34 %, 85.38 %, 88.49 %, and 98.22 %, respectively. The by-product gas generation rate was significantly lower in the WF type.

Genus Clematis is one of the largest within Ranunculaceae. Here we report the chloroplast genome of two Clematis species, C. brachyura and C. trichotoma endemic to Korea. The chloroplast genome lengths of C. brachyura and C. trichotoma are 159,532 bp and 159,170 bp, respectively. Gene contents in the complete chloroplast genomes of these two Clematis species are identical to that of most Ranunculaceae and other angiosperms. However, our data results demonstrated that genus Clematis has inversion and rearrangement events concerning gene rps4 gene, rps16 to trnH region, and trnL to ndhC region, and IR regions expansion. Comparison of IR regions among Ranunculaceae species revealed that Clematis species contained six protein coding genes (infA, rps8, rpl14, rpl16, rps3, and rpl22) usually found in the long single copy (LSC) region of other species. Phylogenetic analysis demonstrated that genus Clematis is closely related to genus Ranunculus. Differences in repeat structure, substitution rates, and IR expansion in genera Clematis and Ranunculus, explained their relationship. Clematis species showed slightly higher tandem repeats content than Ranunculus species. The six protein-coding genes showed lower synonymous substitution rates in the IR of Clematis species than in the LSC of Ranunculus species. Overall, the chloroplast genomes and results presented here provide important information on the evolution of Ranunculaceae.

When disposing of waste metal resources in landfills, environmental issues such as soil contamination may arise. Recycling these resources not only recovers valuable metals but also mitigates environmental pollution. Platinum (Pt), a valuable metal used in fuel cells for its high water production activity, will see increased future demand as a fossil fuel alternative. This study analyzes the environmental and resource reduction effects of recycled Pt, considering the growing emphasis on its recycling for stable supply and demand of Pt. The environmental impact and resource consumption of recycled Pt with primary Pt (from natural mines) were compared and analyzed using the Life Cycle Assessment (LCA) technique. Results revealed that resource consumption for primary Pt was 8.25E+01 kg Sb-eq./kg, significantly more than the 5.45E+00 kg Sb-eq./kg for recycled Pt. This represents an environmental reduction effect of approximately 93%. In the case of greenhouse gas emissions, primary Pt emitted 1.35E+04 kg CO2-eq./kg, while recycled Pt emitted 6.94E+02 kg CO2-eq./kg, resulting in an environmental reduction effect of approximately 95%. In conclusion, recycling Pt, compared to primary extraction, offers substantial environmental and resource reduction benefits. This study underscores the significance of recycling and highlights the potential environmental improvements achievable through sustainable practices.

This study examined if people who reside in different regions of South Korea exhibit different WTP for the mitigation of PM2.5 emissions from coal power plants by restricting the operation of such plants during the winter and spring when air pollution becomes severe. A contingent valuation method combined with a double bounded dichotomous choice was used to derive people’s WTP for the mitigation of PM2.5 emissions. Sample group was divided into central, western, eastern, and southern regions. It is known that the eastern region is affected by northwesterly winds in the winter and spring seasons, so air pollutants in the eastern areas fly to the eastern sea. According to the estimation results, respondents who live in eastern regions showed significantly lower WTP than the average WTP. We suggest that the mitigation policy on PM2.5 emissions should consider regional differences in the contributions of coal power plants to PM2.5 emissions.

Air conditioning system of electric vehicles has new change as the internal combustion engine is being replaced with electrified AC motor. With large amount of batteries installed at the bottom of frame, the conventional compressor which is belt-driven can be removed and another AC motor can play the role for air conditioning in electric vehicles. From this change, the system efficiency would be improved since it is possible to control the electrified compressor independently from traction system in contrast with the belt-driven compressor. As a result, by applying the electrified compressor for air conditioning system, the whole system can achieve better efficiency and longer driving distance, which is most important in electric vehicles. In this paper, 3-phase interior permanent magnet synchronous motor (IPMSM) was designed using lumped-parameter model and finite element method.

This paper proposes a novel three-phase voltage source inverter dead-time compensation strategy for accurate compensation in wide current regions of the inverter. In particular, an analysis of the output voltage distortion of the inverter, which appears as parasitic components of the switches, has been conducted for proper voltage compensation in the low current region, and an on-line compensation voltage controller has been proposed. Also, a new trapezoidal compensation voltage implementation method using the current phase is proposed to simplify realizing the trapezoidal shape of the three-phase compensation voltages. Finally, when the proposed dead-time compensation strategy is applied, the maximum phase voltage magnitude in the linear modulation voltage regions is defined to achieve smooth operation even at high modulation index. Simulations and experiments were conducted to verify the performance of the proposed dead-time compensation scheme.

For automobile insurance, it has long been implied that when a policyholder made at least one claim in the prior year, the subsequent premium is likely to increase. When this happens, the policyholder may seek to switch to another insurance company to possibly avoid paying for a higher premium. In such situations, insurers may be faced with the challenges of policyholder retention by keeping premiums low in the face of competition. In this paper, we seek to find empirical evidence of possible association between policyholder switching after a claim and the associated change in premium. In accomplishing this goal, we employ the method of association rule learning, a data mining technique that has its origins in marketing for analyzing and understanding consumer purchase behavior. We apply this unique technique in two stages. In the first stage, we identify policyholder and vehicle characteristics that affect the size of the claim and resulting change in premium regardless of policy switch. In the second stage, together with policyholder and vehicle characteristics, we identify the association among the size of the claim, the level of premium increase and policy switch. This empirical process is often challenging to insurers because they are unable to observe the new premium for those policyholders who switched. However, we used a 9-year claims data for the entire Singapore automobile insurance market that allowed us to track information before and after the switch. Our results provide evidence of a strong association among the size of the claim, the level of premium increase and policy switch. We attribute this to the possible inefficiency of the insurance market because of the lack of sharing and exchange of claims history among the companies.

Acetic acid bacteria (AAB) form a bacterial film on the surface of alcoholic solutions and ferment ethanol to acetic acid while also producing bioactive compounds. To discover functional AAB for industrial use, we isolated and selected strains from farm-produced vinegars using a CaCO3-containing medium. The seven strains belonged to Acetobacter cerevisiae and A. pasteurianus. Physiological properties were determined, including ethanol tolerance at up to 12% (v/v). Acidification at a growth temperature of 40 ℃ was seen for GHA 7, GYA 23, JGB 21-17, and GHA 20 strains, which may be useful in vinegar production where thermotolerant AAB are required. The seven AAB isolates had strong antibacterial activity against Staphylococcus aureus. Antioxidant activity was 2- and 4-fold higher, respectively, for A cerevisiae and A. pasteurianus than for the control, 1% acetic acid. We also observed 91.3% inhibition of angiotensin-converting enzyme activity for the KSO 5 strain, higher than that for the positive control, 0.1% captopril (76.9%). All strains showed complete inhibition of α-glucosidase, except JGB 21-17 and GHA 7 with 98.3% inhibition. Our work suggests usefulness of the strains selected as seed strains for highly efficient production of functional vinegar and illustrates identification of useful functional characteristics on a scientific basis.

The aim of this study is to investigate transient dynamic flow characteristics of the fluid flow through 5-way electric coolant valve (PCCV : Penta-Control Coolant Valve). To achieve this goal, the present paper attempts the three-dimensional dynamic simulation of the fluid flow through the valve using a commercial CFD solver with moving mesh technique to consider flow inertia and dynamic flow in the opening and closing stages of the ball valve rotating motion. Firstly, dynamic flow characteristics and the thermal mixing inside the PCCV ball valve during the opening and closing stage was analyzed. It is found that the discrepancies between dynamic and steady state simulation is remarkable when fluxes with different levels of enthalpy and momentum flow into the PCCV leads to strong flow interference and flow inertia, while the discrepancies are relatively small at low rotation speed and weak flow interference. Then, the effect of dynamic flow characteristics of the valve on dynamic thermal mixing characteristics at two different ball valve rotational speeds and rotational directions were investigated. It was found that the dynamic flow and thermal mixing characteristics inside the PCCV are greatly affected by the rotation speed, rotation direction, and degree of flow interference between fluxes. It is helpful for the design of the better coolant control strategies and the improvement of the FCEV thermal management system.

Background: Brain-derived neurotrophic factor (BDNF) has attracted increasing attention as a therapeutic agent because of its potentially biological activities, including osteogenesis. However, the molecular mechanisms involved in the osteogenic activity of BDNF have not been fully investigated. This study aimed to investigate the action of BDNF on the osteoblast differentiation in bone marrow stromal cells, and its influence on signaling pathways. Methods: Preosteoblast cells (MC3T3-E1), bone marrow-derived stromal cells (ST2), and a direct 2D co-culture system were treated with BDNF. The effect of BDNF on cell proliferation was determined using the CCK-8 assay. Osteoblast differentiation was assessed based on alkaline phosphatase (ALP) activity and staining and the protein expression of multiple osteoblast markers. Calcium accumulation was examined by Alizarin red S staining. Results: BDNF significantly increased ALP activity, calcium deposition, and the expression of osteoblast differentiation-related proteins, such as ALP, osteopontin, etc. in both ST-2 and the MC3T3-E1 and ST-2 co-culture system. Moreover, the effect of BDNF on osteogenic differentiation was diminished by blocking tropomyosin receptor kinase B as well as inhibiting c-Jun N-terminal kinase and p38 MAPK signals. Conclusion: Our study results showed positive effect of BDNF on osteogenesis. It provides essential evidence for clinical applications of BDNF in treating osteoporosis.

The degradation of Proton-exchange membrane fuel cell (PEMFC) gasket materials is crucial in electric vehicles as it can cause hazardous hydrogen fuel leaks, which are usually due to high temperatures, pressures, and hydrogen fuel exposure. Degradation of gasket materials in PEMFC presents a critical concern for electric vehicle safety due to potential hydrogen fuel leaks. This study utilizes finite element analysis (FEA) to assess the suitability of gasket materials for PEMFC applications, focusing on aging and tensile conditions. The dual degradation framework, incorporating contact pressure and von Mises stress, is employed to evaluate Liquid Silicon Rubber (LSR) and Ethylene Propylene Diene Monomer (EPDM) materials. Under aging techniques, the Yeoh model exhibits the least Mean Absolute Percentage Error (MAPE) and computational cost of 0.27 seconds, while the Ogden model records the highest computational cost of 0.89 seconds. In evaluating MAE, Root Mean Square Error (RMSE), and R-squared metrics, LSR and EPDM materials demonstrate respective averages of 0.25%, 0.275%, 0.945%, and 0.815%, 0.685%, 0.77%. Tensile testing (Uniaxial) reveals RMSE and MAE values of 0.30%, 0.40%, and 0.50%, 0.40%, respectively. FEA proves instrumental in identifying suitable gasket materials for PEMFC applications. LSR emerges as the superior choice, demonstrating enhanced FEA modelling performance under aging and tensile conditions. These findings contribute valuable insights to the design and development of improved gasket materials, bolstering the safety and reliability of electric vehicles.

The hematopoietic system plays a crucial role in immune defense response and normal development, and is regulated by various factors from other tissues. The dysregulation of hematopoiesis is associated with melanotic mass formation; however, the molecular mechanisms underlying this process are poorly understood. Here, we observed that the overexpression of miR-274 in the fat body resulted in the formation of melanotic masses. Moreover, abnormal activation of the JNK and JAK/STAT signaling pathways was linked to these consequences. In addition to this defect, miR-274 overexpression in the larval fat body decreased the total tissue mass, leading to a reduction in body weight. miR-274-5p was found to directly suppress the expression of found-in-neurons (fne), which encodes an RNA-binding protein. Similar to the effects of miR-274 overexpression, fne depletion led to melanotic mass formation and growth reduction. Collectively, miR-274 plays a regulatory role in the fne-JNK signaling axis in melanotic mass formation and growth control.

This paper presents a two-stage hierarchical neural network using image classification and object detection algorithms as key building blocks for a system that automatically detects a potential design right infringement. This neural network is trained to return the Top-N original design right records that highly resemble the input image of a counterfeit. Design rights specify the unique aesthetic characteristics of a product. Due to the rapid change of trends, new design rights are continuously generated. This work proposes an Ensemble Neural Network (ENN), an artificial neural network model that aims to deal with a large amount of counterfeit data and design right records that are frequently added and deleted. At first, we performed image classification and objection detection learning per design right using the existing models with a proven track record of high accuracy. The distributed models form the backbone of the ENN and yield intermediate results aggregated at a master neural network. This master neural network is a deep residual network paired with a fully connected network. This ensemble layer is trained to determine the sub-models that return the best result for a given input image of a product. In the final stage, the ENN model multiples the inferred similarity coefficients to the weighted input vectors produced by the individual sub-models to assess the similarity between the test input image and the existing product design rights to see any sign of violation. Given 84 design rights and the sample product images taken meticulously under various conditions, our ENN model achieved average Top-1 and Top-3 accuracies of 98.409% and 99.460%, respectively. Upon introducing new design rights data, a partial update of the inference model was done an order of magnitude faster than the single model. ENN maintained a high level of accuracy as it scaled out to handle more design rights. Therefore, the ENN model is expected to offer practical help to the inspectors in the field, such as the customs at the border that deal with a swarm of products.

Combined sewer overflow (CSO) is a significant environmental concern and public health (e.g., water contamination, eutrophication, and beach closure). The Environmental Protection Agency (EPA) has introduced the National Pollutant Discharge Elimination System (NPDES) permitting program to regulate and address this matter. This program mandates the control of CSOs for more than 700 municipalities obligated to devise Long-term Control Plans (LTCPs) to curb combined sewer overflows and bring them down to safe levels. LTCP involves diverse strategies, including sewer separation, green infrastructure improvements, and conventional gray infrastructure upgrades. This study investigates several municipalities’ solutions for CSO problems in conventional methods and wireless sensor technology as real-time control. The investigation mainly focuses on a comparative analysis of two cities, Richmond, Virginia, and South Bend, Indiana, such as average rainfall, the frequency of overflows, and the capacity of treatment plants. The findings indicate that integrating sensor technology could significantly enhance modeling endeavors, bolster the capacity of existing structures, and substantially enhance preparedness for storm events. The EPA’s Storm Water Management Modeling (SWMM) software is utilized. Through an analysis of SWMM data, the study suggests the potential for leveraging wireless sensor technology to achieve more robust control over CSOs as a part of LTCPs.

A systematic approach for model updating using the modal identification results is proposed. Modal identification provides mode shapes for physical quantities (acceleration strain, etc.) measured in specific directions at the location of the sensors. Besides, model updating involves the use of the mode shapes related to the nodal degrees-of-freedom of the finite element analytic model. Consequently, the mode shapes obtained by modal identification and the mode shapes of the model updating process do not coincide even for the same mode. Therefore, a method constructing transform matrices that distinguish the cases where measurement is done by acceleration, velocity and displacement sensors and the case where measurement is done by strain sensors is proposed to remedy such disagreement between the mode shapes. The so-constructed transform matrices are then applied when the mode shape residual is used as objective function or for mode pairing in the model updating process. The feasibility of the proposed approach is verified by means of a numerical example in which the strain or acceleration of a simple beam is measured and a numerical example in which the strain of a bridge is measured. Using the proposed approach, it is possible to model the structure regardless of the position of the sensors and to select the location of the sensors independently from the model.

In this paper we consider Changhee polynomials of type two, which are motivated from the recent work of Kim and Kim. We investigate some symmetry identities for the Changhee polynomials of type two which are derived from the properties of symmtery for the fermionic p-adic integral on Zp.

Pseudolysimachion nakaianum (Ohwi) T.Yamaz. is an endemic species that is an important species in the forest ecosystems of South Korea. This study aimed to develop an in vitro propagation system for P. nakaianum, to enhance the availability of this rare and endemic plant for commercial horticulture and restoration efforts. We utilized cotyledon explants from in vitro germinated seeds and two types of explants (petiole and leaf) from in vitro seedlings to assess the impact of five different cytokinins on adventitious shoot organogenesis in P. nakaianum. The half-strength Murashige and Skoog (MS) medium, supplemented with 10 µM thidiazuron (TDZ) for both cotyledon and petiole explants, yielded the highest shoot induction rates (61.1 ± 9.6% and 26.7 ± 8.8%, respectively) and the greatest number of shoots (3 ± 0.6 and 4.4 ± 0.5, respectively). Responses from leaf explants were variable, with none showing in vitro regeneration. Successfully acclimatized P. nakaianum plantlets in a greenhouse demonstrated normal growth. This protocol outlines an effective method for the direct in vitro regeneration from cotyledon and petiole explants of P. nakaianum, providing valuable information for the conservation of this species.

A series of polycaprolactones (PCLs) with molecular weights of 950–10,100 g mol−1 and Ð of 1.10–1.87 have been synthesized via one-pot, solvent-free ring-opening polymerization (ROP) of ε-caprolactone (CL) using a heterogeneous double metal cyanide (DMC) catalyst. Various initiators such as polypropylene glycol, ethylene glycol, propylene glycol, glycerol, and sorbitol are employed to tune the number of hydroxyl end groups and properties of the resultant PCLs. Kinetic studies indicate that the DMC-catalyzed ROP of CL proceeds via a coordination mechanism. Branched PCLs copolymers are also synthesized via the DMC-catalyzed copolymerization of CL with glycidol. The α,ω-hydroxyl functionalized PCLs were successfully used as telechelic polymers to produce thermoplastic poly(ester-ester) and poly(ester-urethane) elastomers with well-balanced stress and strain properties.

Surgical techniques are gaining attention for treating physical diseases in aquaculture and aquarium fish. Sturgeon is a suitable species for surgical experiments due to its industrial significance. Maintaining homeostasis is crucial during surgical procedures, and the liver plays a major role in immune regulation. High temperature is suggested to improve physiological activity and wound healing. This study investigated differences in hepatectomy sturgeons' tolerance and histopathological responses of internal organs. Moreover, this study investigated the effects of high temperature on wound healing and hematopoietic recovery in fish undergoing surgical procedures. The liver condition was found to play a pivotal role in the analysis, and cortisol levels were affected by anesthesia. The results showed that high temperature facilitated hematopoietic recovery and wound healing, but excessive induction of physiological activity caused damage. Managing high temperatures and liver condition induced a remarkable improvement in wound healing. However, anesthesia itself can be a significant stressor for fish, and wound healing requires a greater amount of energy. Further research is needed to understand the stress factors caused by surgical procedures and anesthesia and to promote animal welfare in fisheries products.

Religious and spiritual struggles are typically assessed by self-report scales using closed-ended items, yet nascent research suggests that using open-ended items may complement and advance assessment. In the current study, undergraduate participants (N = 976) completed open-ended descriptions of their religious and spiritual struggles, the Religious and Spiritual Struggles Scale (RSS), and a standardized measures of religious belief salience. Qualitative coding showed that the themes emerging from open-ended descriptions generally fell within the broad domains of the RSS though some descriptions reflected more contextualized struggles. Scores derived from the open-ended responses to assess RSS domains achieved evidence of reliability as well as convergent and discriminant validity with the RSS . Correlations revealed a mix of similar and divergent associations between methods of assessing religious and spiritual struggles and religious belief salience. Open-ended descriptions of religious and spiritual struggles may yield reliable and valid information that is related to but distinct from assessments relying on closed-ended items.

This study empirically analyzes the effectiveness of resource optimization utilizing artificial intelligence (AI) within cloud computing environments. It compares systems that have been transitioned from a Monolithic structure to Microservices Architecture (MSA) with those adopting a simple Rehost strategy, to validate the operational efficiency of two systems whose resource efficiency has been enhanced compared to traditional legacy systems. The research is based on systems that determined resource efficiency post-cloud migration using APM tools. It points out the limitations of traditional heuristic operation methods in resource optimization, which lead to issues such as application performance degradation, resource over-allocation, and increased operational costs. This study aims to overcome the conventional resource optimization standards that depended on the average peak usage of CPU and memory infrastructure, by introducing AI-based optimization tools, and applying on-premise standards to cloud and container environments to achieve resource optimization. The paper emphasizes the importance of resource optimization through AI-based automation tools, exploring the possibilities of resolving real-world application performance issues in cloud environments, reducing unnecessary resource usage costs, and cutting down on labor risks and operational expenses. Through this, it presents strategic directions on how AI technology can offer financial and operational advantages in managing cloud resources.

This review explores the field of retreatment strategies for the cases filled with calcium silicate-based root canal sealers. Since the introduction of calcium silicate-based materials in dentistry, calcium silicate-based root canal sealers have become popular among dentists because of their biocom- patibility, bioactivity, and sealing ability. Therefore, effective retreatment strategies are indispensable. This article aims to identify the challenges associated with the removal of calcium silicate-based sealers itself and gutta-percha with the sealers during retreatment, evaluate current techniques and materials, and provide future directions for research in this field. Regarding the strategies of removal of root canal sealers, calcium silicate-based sealers are still relatively new materials for clinicians compared with the traditional sealers such as epoxy- or eugenol-based sealers. First, no clinically established solvents have been reported. Second, calcium silicate-based sealers are currently utilized by clinicians in either cold sealer-based technique or warm vertical condensation technique. Third, the setting process of calcium silicate-based sealers generates byproducts primarily calcium hydroxide and secondarily hydroxyapatite, which could interact with dentine. Lastly, there is a lack of clinical studies evaluating the efficacy of retreatment protocols for teeth filled with calcium silicate-based sealers. Therefore, it is important to investigate chemo-mechanical properties of calcium silicate- based sealers itself and their reactions to solvents and/or mechanical instruments, and identify the interfacial properties of calcium silicate-based sealers in respect to dentine and gutta-percha. In addition, researchers in clinical field need to actively gather and report data on retreatments of teeth filled with calcium silicate-based sealers.

With the increase of intelligent voice phishing and the increasing reliance on open banking systems, there has been a rise in cases where individuals' personal information has been exposed, resulting in significant financial losses for the victims. Non-face-to-face transactions in the financial sector face challenges such as customer identification, ensuring transaction integrity, and preventing transaction rejection. Blockchain-based distributed ledgers have been proposed as a solution, but their adoption is limited due to the difficulty of managing private keys and the burden of gas fees management. This paper proposes a non-face-to-face P2P real-time token payment system that minimizes the risk of key loss by storing private keys in a keystore file and database through a server-based key management module. The proposed system simplifies token creation and management through a server-based token management module and implements an automatic gas charging function for smooth token transactions. Transaction integrity and non-repudiation are ensured through a transaction confirmation module that uses transaction IDs without exposing personal information. Furthermore, advanced security measures such as blocking foreign IP access and DDoS defense are implemented to securely protect user data. The proposed system aims to provide a convenient, secure, and accessible online payment solution to the public by implementing a self-authentication function using a web application that is not limited to smart phones or application platforms.

The irradiation biology of the brown marmorated stink bug (BMSB, Halyomorpha halys Stål) treated at the nymphal stage was investigated to determine its application for sterile insect technique (SIT). Fifth instar males of BMSB were exposed to gamma-radiation 60Co at different doses of 12, 16, 20, 24 and 64 Gy. Irradiated males were mated with non-irradiated virgin females to assess the longevity of both sexes, female fecundity and fertility of their offspring until the egg stage of the F2 generation. The mortality of each of the developmental stages of the F1 and eggs of the F2 generation was observed to determine whether negative effects from exposure to radiation was inherited. The data indicated that irradiation significantly reduced the lifespan of male insects at doses above 20Gy. Irradiated males did not affect the longevity and fecundity of their female partners, nor either sex of their resulting progeny, but it did reduce the hatch rate of the eggs at all doses tested. The sterility rates of F1 eggs were 55.6%, 73.3%, 74.1% and 74.1% at doses of 12Gy, 16Gy, 20Gy and 24Gy respectively. Eggs were completely sterile (100%) at a dose of 64Gy with no egg hatch recorded. A low hatch rate of F2 eggs illustrated that negative effects from radiation was inherited by the subsequent generation. The results support the potential for the use of SIT for BMSB management by irradiating the fifth instar male nymphs at 16-64Gy.

The study aimed to understand the experiences of adolescent smokers who participated in a smoking cessation program based on self-reflection, and to develop the theoretical basis for constructing similar programs. The participants, ten students from middle and high schools located in cities G and S, were interviewed after the program ended. Data were collected from August to November 2019 and analyzed using a phenomenological approach to understand participant experiences in depth. The analysis revealed five major themes: ‘Uniqueness of the Program,’ ‘Perception of Smoking Cessation,’ ‘Positive Reflection on Life,’ ‘Understanding Others,’ and ‘A Search for Hope and Vision in Life.’ The findings revealed that the smoking cessation program facilitated the development of self-identity and vision, which may indirectly strengthen the motivation for adolescent smokers to quit smoking. These findings suggest the need for a life-changing smoking cessation program that enhances self-concept and self-esteem. Moreover, it highlights the importance of follow-up research to ensure effectiveness, and the need to develop programs with creative content.

In this study, a preload monitoring method using impedance signatures obtained from a piezoelectric-based smart interface is presented for bolted girder connections. Firstly, the background theory of the piezoelectric-based smart interface and its implementation into health monitoring of bolted connections are outlined. A simplified electro-mechanical (EM) impedance model of a smart interface-embedded bolted connection system is formulated to interpret mechanistic understanding of EM impedance signatures under the effect of bolt preload. Secondly, finite element modeling of a bolted connection is carried out to show the numerical feasibility of the presented method and to predetermine the sensitive frequency band of impedance signatures. Finally, impedance measurements are conducted on a lab-scaled bolted girder connection to verify the predetermined sensitive frequency range and to assess the bolt preload changes in the test structure.

Preproenkephalin (PPE) is a precursor molecule for multiple endogenous opioid peptides Leu-enkephalin (ENK) and Met-ENK, which are involved in a wide variety of modulatory functions in the nervous system. Despite the functional importance of ENK in the brain, the effect of brain-derived factor(s) on PPE expression is unknown. We report the dual effect of neural epidermal growth factor (EGF)-like-like 2 (NELL2) on PPE gene expression. In cultured NIH3T3 cells, transfection of NELL2 expression vectors induced an inhibition of PPE transcription intracellularly, in parallel with downregulation of protein kinase C signaling pathways and extracellular signal-regulated kinase. Interestingly, these phenomena were reversed when synthetic NELL2 was administered extracellularly. The in vivo disruption of NELL2 synthesis resulted in an increase in PPE mRNA level in the rat brain, suggesting that the inhibitory action of intracellular NELL2 predominates the activation effect of extracellular NELL2 on PPE gene expression in the brain. Biochemical and molecular studies with mutant NELL2 structures further demonstrated the critical role of EGF-like repeat domains in NELL2 for regulation of PPE transcription. These are the first results to reveal the spatio-specific role of NELL2 in the homeostatic regulation of PPE gene expression.

Optimum postharvest storage conditions increase the shelf life and postharvest quality of horticultural crops. The effects of forced-air precooling (FAP) and modified atmosphere packaging (MAP) on shelf life, physicochemical quality, and health-promoting properties of bell pepper (Capsicum annuum L. cv. Nagano) harvested at 90% and 50% coloring stages in May and July respectively, stored at 11℃, 95% relative humidity were assessed. Fruits were treated with FAP + 30 μm polyethylene liner (FOLO), FAP (FOLX), 30 μm polyethylene liner (FXLO), and control (FXLX). The quality attributes, viz. weight loss, firmness, color, SSC, soluble sugars, TPC, TFC, DPPH, and ABTS were evaluated. FOLO maintained sensory quality (weight loss, firmness, and color), physicochemical (soluble solids content and soluble sugars), and health-promoting properties compared to other treatments during storage. The investigated parameters differed significantly (p &lt; 0.05) among treatments except soluble sugars. The 50% coloring fruits had a huge variation between treatments than 90% coloring. The results revealed more TPC and antioxidant capacity in 50% than in 90% coloring fruits. The study highlights the need to consider the ideal fruit coloring stage at harvest under the effect of FAP and MAP treatments in preserving bell pepper's postharvest quality and shelf life.