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As global pressures mount to diversify supply chain strategies beyond China, the concept of "Altasia" has emerged, encompassing 14 alternative countries. This study offers a comprehensive framework describing the historical context, driving factors, and theoretical underpinnings motivating the global shift away from China. Our research model delineates the strategic pathways employed by multinational corporations to navigate the decoupling process, particularly in identifying alternative manufacturing hubs across the Altasia region. This article critically examines the multifaceted challenges and opportunities inherent in Altasia as a collective entity comprising these 14 alternative countries. Furthermore, it explores the transformative implications of this paradigm shift on the broader global supply chain ecosystem. In conclusion, we highlight the forward-looking significance of these findings, shedding light on avenues for future research endeavors in this evolving landscape. [ABSTRACT FROM AUTHOR]

In this work, we propose active stylus application using selfcapacitive touch with OLED TDDI. Active stylus application using self‐capacitive touch sensor has several benefits in comparison to using mutual‐capacitive touch sensor, such as "Smaller RC Loading in Active Stylus Sensing", "Uplink Signal Partially Driving", and "Downlink Signal Through Palm Removing". With these benefits, active stylus application can get better writing experience and accuracy using self‐capacitive on OLED On‐Cell product. Finally, we propose the word wide first OLED TDDI (Touch and Display Driver Integration) NT38770 passed Wacom LV1 certification with 6.67" OLED module. [ABSTRACT FROM AUTHOR]

The establishment of Japanese encephalitis virus (JEV) infection in brain microvascular endothelial cells (BMECs) is thought to be a critical step to induce viral encephalitis with compromised blood–brain barrier (BBB), and the mechanisms involved in this process are not completely understood. In this study, we found that epidermal growth factor receptor (EGFR) is related to JEV escape from interferon-related host innate immunity based on a STRING analysis of JEV-infected primary human brain microvascular endothelial cells (hBMECs) and mouse brain. At the early phase of the infection processes, JEV induced the phosphorylation of EGFR. In JEV-infected hBMECs, a rapid internalization of EGFR that co-localizes with the endosomal marker EEA1 occurred. Using specific inhibitors to block EGFR, reduced production of viral particles was observed. Similar results were also found in an EGFR-KO hBMEC cell line. Even though the process of viral infection in attachment and entry was not noticeably influenced, the induction of IFNs in EGFR-KO hBMECs was significantly increased, which may account for the decreased viral production. Further investigation demonstrated that EGFR downstream cascade ERK, but not STAT3, was involved in the antiviral effect of IFNs, and a lowered viral yield was observed by utilizing the specific inhibitor of ERK. Taken together, the results revealed that JEV induces EGFR activation, leading to a suppression of interferon signaling and promotion of viral replication, which could provide a potential target for future therapies for the JEV infection. [ABSTRACT FROM AUTHOR]

We investigated the storage lower urinary tract symptoms (LUTS) before and after the first dose of coronavirus disease 2019 (COVID-19) vaccine and the association between pre-vaccinated overactive bladder (OAB) and the worsening of storage LUTS following COVID-19 vaccination. This cross-sectional study in a third-level hospital in Taiwan used the validated pre- and post-vaccinated Overactive Bladder Symptom Score (OABSS). Diagnosis of OAB was made using pre-vaccinated OABSS. The deterioration of storage LUTS was assessed as the increased score of OABSS following vaccination. Of 889 subjects, up to 13.4% experienced worsened storage LUTS after vaccination. OAB was significantly associated with an increased risk of worsening urinary urgency (p = 0.030), frequency (p = 0.027), and seeking medical assistance due to urinary adverse events (p < 0.001) after vaccination. The OAB group faced significantly greater changes in OABSS-urgency (p = 0.003), OABSS-frequency (p = 0.025), and total OABSS (p = 0.014) after vaccination compared to those observed in the non-OAB group. Multivariate regression revealed that pre-vaccinated OAB (p = 0.003) was a risk for the deterioration of storage LUTS. In conclusion, storage LUTS may deteriorate after vaccination. OAB was significantly associated with higher risk and greater changes in worsening storage LUTS. Storage LUTS should be closely monitored after COVID-19 vaccination, especially in those OAB patients. [ABSTRACT FROM AUTHOR]

There is a great need for a diagnostic tool using simple clinical information collected from patients to diagnose uric acid (UA) stones in nephrolithiasis. We built a predictive model making use of machine learning (ML) methodologies entering simple parameters easily obtained at the initial clinical visit. Socio-demographic, health, and clinical data from two cohorts (A and B), both diagnosed with nephrolithiasis, one between 2012 and 2016 and the other between June and December 2020, were collected before nephrolithiasis treatment. A ML-based model for predicting UA stones in nephrolithiasis was developed using eight simple parameters—sex, age, gout, diabetes mellitus, body mass index, estimated glomerular filtration rate, bacteriuria, and urine pH. Data from Cohort A were used for model training and validation (ratio 3:2), while data from Cohort B were used only for validation. One hundred and forty-six (13.3%) out of 1098 patients in Cohort A and 3 (4.23%) out of 71 patients in Cohort B had pure UA stones. For Cohort A, our model achieved a validation AUC (area under ROC curve) of 0.842, with 0.8475 sensitivity and 0.748 specificity. For Cohort B, our model achieved 0.936 AUC, with 1.0 sensitivity, and 0.912 specificity. This ML-based model provides a convenient and reliable method for diagnosing urolithiasis. Using only eight readily available clinical parameters, including information about metabolic disorder and obesity, it distinguished pure uric acid stones from other stones before treatment. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of moving objects in a mobile wireless sensor network, considering the deployment of a limited number of mobile wireless sensor nodes within a predetermined area to provide coverage for moving objects traveling on a predetermined trajectory. Because of the insufficient number and limited sensing range of mobile wireless sensors, the entire object's trajectory cannot be covered by all deployed sensors. To address this problem and provide complete coverage, sensors must move from one point of the trajectory to another. The frequent movement quickly depletes the sensors' batteries. Therefore, solving the moving object coverage problem requires an optimized movement repertoire where (1) the total moving distance is minimized and (2) the remaining energy is also as balanced as possible for mobile sensing. Herein, we used a genetic algorithm (GA) and a discrete particle swarm optimization algorithm (DPSO) to manage the complexity of the problem, compute feasible and quasi-optimal trajectories for mobile sensors, and determine the demand for movement among nodes. Simulations revealed that the GA produced trajectories significantly superior to those produced by the DPSO in terms of total traveled distance and balance of residual energy. [ABSTRACT FROM AUTHOR]