Smart Cities and FDI

Smart cities have emerged as a worldwide trend, progressing from the implementation of sensors and technologies to enhance infrastructures and service delivery to the development of city-wide policy through the utilization of big data analysis. The goal of a "Smart City" is to improve standard of life by acquiring knowledge from information gathered from people, technologies, and networked sensors. This research argues that smart cities may attract inflows Foreign Direct Investment FDI by influencing the investment choices of global corporate players in the new age by facilitating the flow of data, technology, innovations, and best practices while offering a livable and productive environment. When deciding where to invest, foreign investors will take new criteria into account. These factors include how sociable the environment is, how stable the economic condition is, and how digitally advanced the destination is. These variables will outweigh conventional investment considerations like inexpensive labor, abundant resources, and a large population. For developing nations and rising economies where businesses need capital and knowledge to increase their worldwide sales, foreign direct investment is crucial. To maintain high growth rates the countries should attract international investors, and, most importantly, provide its citizens with a good standard of living, and therefore, should speed up its investments in sustainable smart cities. &nbsp

Impact of Augmented Reality on Purchase Intention of Foreign Products Online

Augmented reality (AR) is a significant technology that holds the promise to transform how consumers interact with products before purchasing. It creates immersive experiences that enable people to engage with digital material in a more intuitive and straightforward manner. When used effectively, AR can be influential in every stage of customer journey including purchase intention stage. Assessing purchase intention of international consumers is critical for organizations because it allows them to plan and make choices about marketing, inventory, and expenses. Purchase intent provides international companies with information on what their global consumers are willing to purchase enabling them to modify their marketing and goods to better fit their customers' demands.  This research examined how augmented reality increase the purchase intention of global customer using the data, which includes data for 810 different overseas visitors of an e-commerce site.  We collected these data from visitors of a global e-commerce shop that integrated augmented reality (AR) into their smartphone app to enable users to imagine how they would appear with various items.  The study performed a Robust Least Squares Method-estimation. Our research's findings provide some early proof that using AR increases the level of purchase intention of foreign products.  The findings also indicate that price, and the number of positive reviews increase the purchase intention of foreign products.  Customers' buying intentions may help firms predict future trends and organize their strategy appropriately. Businesses must also understand the elements that drive purchase intent, such as immersive experience with AR, consumer demographics, nationality, product attributes, pricing, and customer experience. &nbsp

Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma

Rationale: The clinical application of biomarkers reflecting tumor immune microenvironment is hurdled by the invasiveness of obtaining tissues despite its importance in immunotherapy. We developed a deep learning-based biomarker which noninvasively estimates a tumor immune profile with fluorodeoxyglucose positron emission tomography (FDG-PET) in lung adenocarcinoma (LUAD). Methods: A deep learning model to predict cytolytic activity score (CytAct) using semi-automatically segmented tumors on FDG-PET trained by a publicly available dataset paired with tissue RNA sequencing (n = 93). This model was validated in two independent cohorts of LUAD: SNUH (n = 43) and The Cancer Genome Atlas (TCGA) cohort (n = 16). The model was applied to the immune checkpoint blockade (ICB) cohort, which consists of patients with metastatic LUAD who underwent ICB treatment (n = 29). Results: The predicted CytAct showed a positive correlation with CytAct of RNA sequencing in validation cohorts (Spearman rho = 0.32, p = 0.04 in SNUH cohort; spearman rho = 0.47, p = 0.07 in TCGA cohort). In ICB cohort, the higher predicted CytAct of individual lesion was associated with more decrement in tumor size after ICB treatment (Spearman rho = -0.54, p < 0.001). Higher minimum predicted CytAct in each patient associated with significantly prolonged progression free survival and overall survival (Hazard ratio 0.25, p = 0.001 and 0.18, p = 0.004, respectively). In patients with multiple lesions, ICB responders had significantly lower variance of predicted CytActs (p = 0.005). Conclusion: The deep learning model that predicts CytAct using FDG-PET of LUAD was validated in independent cohorts. Our approach may be used to noninvasively assess an immune profile and predict outcomes of LUAD patients treated with ICB.

Dexmedetomidine Use in Patients with 33℃ Targeted Temperature Management: Focus on Bradycardia as an Adverse Effect

Background This study aimed to investigate bradycardia as an adverse effect after administration of dexmedetomidine during 33℃ target temperature management. Methods A retrospective study was conducted on patients who underwent 33℃ target temperature management in the emergency department during a 49-month study period. We collected data including age, sex, weight, diagnosis, bradycardia occurrence, target temperature management duration, sedative drug, and several clinical and laboratory results. We conducted logistic regression for an analysis of factors associated with bradycardia. Results A total of 68 patients were selected. Among them, 39 (57.4%) showed bradycardia, and 56 (82.4%) were treated with dexmedetomidine. The odds ratio for bradycardia in the carbon monoxide poisoning group compared to the cardiac arrest group and in patients with higher body weight were 7.448 (95% confidence interval [CI] 1.834-30.244, p = 0.005) and 1.058 (95% CI 1.002-1.123, p = 0.044), respectively. In the bradycardia with dexmedetomidine group, the infusion rate of dexmedetomidine was 0.41 ± 0.15 μg/kg/h. Decisions of charged doctor’s were 1) slowing infusion rate and 2) stopping infusion or administering atropine for bradycardia. No cases required cardiac pacing or worsened to asystole. Conclusions Despite the frequent occurrence of bradycardia after administration of dexmedetomidine during 33℃ target temperature management, bradycardia was completely recovered after reducing infusion rate or stopping infusion. However, reducing the infusion rate of dexmedetomidine lower than the standard maintenance dose could be necessary to prevent bradycardia from developing in patients with higher body weight or carbon monoxide poisoning during 33℃ targeted temperature management

Controlled Arrivals on the Retrial Queueing–Inventory System with an Essential Interruption and Emergency Vacationing Server

In recent times, we have encountered new situations that have imposed restrictions on our ability to visit public places. These changes have affected various aspects of our lives, including limited access to supermarkets, vegetable shops, and other essential establishments. As a response to these circumstances, we have developed a continuous review retrial queueing–inventory system featuring a single server and controlled customer arrivals. In our system, customers arriving to procure a single item follow a Markovian Arrival Process, while the service time for each customer is modeled by an exponential distribution. Inventories are replenished according to the (s,Q) reordering policy with exponentially distributed lead times. The system controls arrival in the waiting space with setup time. The customers who arrive at a not allowed situation decide to enter an orbit of infinite size with predefined probability. Orbiting customers make retrials to claim a place in the waiting space, and their inter-retrial times are exponentially distributed. The server may experience essential interruption (emergency situation) which arrives according to Poisson process. Then, the server goes for an emergency vacation of a random time which is exponentially distributed. In the steady-state case, the joint probability of the number of customers in orbit and the inventory level has been found, and the Matrix Geometric Method has been used to find the steady-state probability vector. In numerical calculations, the convexity of the system and the impact of F-policy and emergency vacation in the system are discussed

Prospective Evaluation of the Clinical Implications of the Tumor Metabolism and Chemotherapy-Related Changes in Advanced Biliary Tract Cancer

Tumor metabolism measured by F-18-FDG PET has a diagnostic and prognostic role in several cancers. The clinical implication of tumor metabolism in biliary tract cancer (BTC) has not been studied well. Therefore, we evaluated the prognostic value of tumor metabolism and chemotherapy-related changes in advanced BTC patients. Methods: We prospectively enrolled advanced BTC patients before the initiation of palliative chemotherapy. Using F-18-FDG PET, we assessed the baseline SUVmax and monitored the changes in SUVmax during chemotherapy. We analyzed the associations between SUVmax, and clinicopathologic factors and clinical outcomes. Results: Seventy-five patients were enrolled. All patients received gemcitabine/ cisplatin as first-line chemotherapy. Primary tumor site, histologic differentiation, molecular characteristics, laboratory findings, and disease extent were associated with the metabolic characteristics. The high-metabolism group showed worse survival outcome (hazard ratio [HR] = 4.09, P = 0.001 for progression-free survival; HR = 2.61, P = 0.019 for overall survival [OS]) than the low-metabolism group. The lesser reduction of SUVmax was also associated with worse outcome (HR = 3.35, P = 0.002 for progression-free survival; HR = 1.96, P = 0.082 for OS). When both baseline tumor metabolism and its chemotherapy-related changes were considered, patients with a low metabolism and more reduction in metabolism obtained the best OS (20.7 vs. 6.2 mo, P = 0.013). Conclusion: Tumor metabolic activity and the chemotherapy-related changes in the metabolism are associated with prognosis in advanced BTC patients