Optical Phonon Modes and Electron-optical Phonon Interaction in Core-shell Semiconductor Quantum Wires

Within the framework of the macroscopic dielectric continuum model the longitudinal optical (LO) phonon modes are derived for a cylindrical semiconductor quantum wire made of semiconductor 1 (well material) embedded in another finite semiconductor 2 (barrier material).  The phonon states of modes are given by solving the generalized Born-Huang equation. It is shown that there may exist four types of longitudinal optical phonon modes according to the concrete materials forming the wire. The dispersion equations for phonon frequencies with wave-vector components parallel to the wire are obtained. After having quantized the phonon field we derive the Fröhlich Hamiltonian describing the electron--LO-phonon interaction. The influence of the thickness of the barrier layer as well as the thin metallic shell on the phonon frequencies and their interaction with electrons is studied

Prognostic Values of Serum Lactate-to-Bicarbonate Ratio and Lactate for Predicting 28-Day IN-Hospital Mortality in Children With Dengue Shock Syndrome

This study aimed to assess the clinical utility of blood lactate-to-bicarbonate (L/B) ratio, as a prognostic factor for 28-day in-hospital mortality in children with dengue shock syndrome (DSS), admitted to the pediatric intensive care unit (PICU). This single-center retrospective study was conducted at a tertiary children hospital in southern Vietnam from 2013 to mid-2022. Prognostic models for DSS mortality were developed, using a predefined set of covariates in the first 24 hours of PICU admission. Area under the curves (AUCs), multivariable logistic and Least Absolute Shrinkage and Selection Operator (LASSO) regressions, bootstrapping and calibration slope were performed. A total of 492 children with DSS and complete clinical and biomarker data were included in the analysis, and 26 (5.3%) patients died. The predictive values for DSS mortality, regarding lactate showing AUC 0.876 (95% CI, 0.807-0.944), and that of L/B ratio 0.867 (95% CI, 0.80-0.934) (P values of both biomarkers \u3c .001). The optimal cutoff point of the L/B ratio was 0.25, while that of lactate was 4.2 mmol/L. The multivariable model showed significant clinical predictors of DSS fatality including severe bleeding, cumulative amount of fluid infused and vasoactive-inotropic score (\u3e30) in the first 24 hours of PICU admission. Combined with the identified clinical predictors, the L/B ratio yielded higher prognostic values (odds ratio [OR] = 8.66, 95% confidence interval [CI], 1.96-38.3; P \u3c .01) than the lactate-based model (OR = 1.35, 95% CI, 1.15-1.58; P \u3c .001). Both the L/B and lactate models showed similarly good performances. Considering that the L/B ratio has a better prognostic value than the lactate model, it may be considered a potential prognostic biomarker in clinical use for predicting 28-day mortality in PICU-admitted children with DSS

Preparation of self-assembly silica redox nanoparticles to improve drug encapsulation and suppress the adverse effect of doxorubicin

Background and Purpose: The utilization of doxorubicin (DOX) in clinal trials is also challenging owing to its adverse effects, including low oral bioavailability, generation of reactive oxygen species (ROS), cardiotoxicity, and epithelial barrier damage. Recently, scavenging of ROS reduced the cytotoxicity of DOX, suggesting a new approach for using DOX as an anticancer treatment. Thus, in this study, non-silica and silica redox nanoparticles (denoted as RNPN and siRNP, respectively) with ROS scavenging features have been designed to encapsulate DOX and reduce its cytotoxicity. Experimental Approach: DOX-loaded RNPN (DOX@RNPN) and DOX-loaded siRNP (DOX@siRNP) were prepared by co-dissolving DOX with RNPN and siRNP, respectively. The size and stability of nanoparticles were characterized by the dynamic light scattering system. Additionally, encapsulation efficiency, loading capacity, and release profile of DOX@RNPN and DOX@siRNP were identified by measuring the absorbance of DOX. Finally, the cytotoxicity of DOX@RNPN and DOX@siRNP against normal murine fibroblast cells (L929), human hepatocellular carcinoma cells (HepG2), and human breast cancer cells (MCF-7) were also investigated. Key results: The obtained result showed that RNPN exhibited a pH-sensitive character while silanol moieties improved the stability of siRNP in physiological conditions. DOX@RNPN and DOX@siRNP were formed at several tens of nanometers in diameter with narrow distribution. Moreover, DOX@siRNP stabilized under different pH buffers, especially gastric pH, and improved encapsulation of DOX owing to the addition of silanol groups. DOX@RNPN and DOX@siRNP maintained anticancer activity of DOX against HepG2, and MCF-7 cells, while their cytotoxicity on L929 cells was significantly reduced compared to free DOX treatment. Conclusion: DOX@RNPN and DOX@siRNP could effectively suppress the adverse effect of DOX, suggesting the potential to become promising nanomedicines for cancer treatments

Effect of Camellia flava (Pitard) Sealy flower extract on the degeneration of Islets of Langerhans and insulin resistance in alloxan-induced hyperglycemia model on Swiss albino mice

Diabetes has always been a matter of concern to health experts as well as the community due to the increasing number of patients with diabetes and the severe consequences it may cause. Many attempts have been made to discover new treatment options for diabetes, and herbal medicines are currently considered to have great potential. This study was conducted to evaluate the effect of Camellia flava flower extract on the degeneration of the islets of Langerhans and insulin resistance in an alloxan-induced hyperglycemia model in Swiss albino mice. Hyperglycemic conditions were induced by alloxan (55 mg/kg, i.v.). The animals were then treated with glibenclamide (10 mg/kg, p.o.) and flower extract at doses of 1.09 and 2.19 g/kg, p.o. The results showed that the blood glucose, AUC, HbA1c, and HOMA-IR levels of two groups of mice receiving flower extract were considerably lower than those of the hyperglycemic untreated group (p < 0.05). The body weights of these two groups were also lower than the untreated group on the last day of the experiment, though the differences were not significant (p > 0.05). However, this was not observed when assessing insulin levels as well as relative organ weights. In biochemical tests, creatinine and AST and ALT concentrations were evaluated. There was no significant variation in creatinine and AST concentrations between the five experimental groups, whereas mice treated with glibenclamide and flower extract at both doses showed a remarkable decline in ALT concentration (p < 0.05). The hepatic histomicrographs were consistent with ALT results, while the H&E staining of kidneys showed no difference between groups. Histomicrographs of the pancreas revealed that the treatment groups using glibenclamide and flower extract had larger islets of Langerhans than those of the alloxan-treated group. Based on these results, this study demonstrated that Camellia flava flower extract exerted several beneficial effects, including blood sugar level reduction, weight loss promotion, and organ protection, hence making it a new potential herbal medication for the management of diabetes

Dielectric function and impurity-limited mobility of semiconductor quantum wires: effects of dielectric mismatch and finite confining potential

The dielectric response function of the electron system in a cylindrical semiconductor quantum wire (QWR) embedded in a dielectric material is derived within the random phase approximation in the quantum limit when only the lowest electron subband is considered. The wire is studied in both finite and infinite confining potential models. It is shown that the dielectric mismatch strongly affects the collective excitations of the electron system and the electrostatic interaction between charged particles in the wire. The electron screening is greatly enhanced in thin QWRs with low-$$\kappa$$ dielectric surroundings and weakened for high-$$\kappa$$ dielectric environment. Thus, the impurity-limited electron mobility can be improved in small-radius semiconductor QWRs coated with a material having a dielectric constant smaller than that of the semiconductor, as opposed to a number of previous reports. The calculations also indicate that the model of infinite potential barrier for thin QWRs underestimates the impurity electron mobility compared to the finite barrier model and can be used in the case of QWRs with large radii

Geological and Geochemical Characteristics of the Pac Lang Gold Deposits, Northeastern Vietnam and Their Potential Prospects

The Song Hien Rift basin, located in northeast Vietnam, has been identified as an important region for gold deposits, including the Pac Lang deposit. Several methods like petrographic observations, elemental analyses, and geochemical elements and vertical zoning models of primary halo have been used to describe geological characteristic of this deposit. The investigation focused on examining the geological events that occurred both before and after the formation of the ore. The use of ICP-MS analysis and element concentration contrast enabled an effective assessment of the relative degrees of denudation that occurred at the Pac Lang deposit. The findings of this study were consistent with prior research on ore deposit geology, geochemical primary-halo, and examination of geochemical indicator zoning patterns for gold ore bodies. The study's application of singularity analysis for evaluating the degree of denudation provides important geological information that can aid in data interpretation. The results of the study can also have significant reference value in furthering our understanding of the post-ore deformation of deposits and in the investigation of unknown orebodies in northeast Vietnam. There indicate that, the research's findings suggest that the use of singularity analysis to evaluate the degree of denudation is a valuable tool for exploring potential gold deposits and enhancing our knowledge of gold deposit geology in northeast Vietnam. Overall, this study contributes to the existing body of knowledge on gold deposits in the Song Hien Rift basin and can serve as a useful reference for future research in the area

Stock Return Prediction using Machine Learning-Based Techniques

The paper attempts to forecast the intraday return of HNX index by using 3 machine learning models: Support Vector Machine, Random Forest, and Extra-Trees Classifier. Kernel principal component analysis is used for feature extraction and dimension reduction. The prediction performance is compared to the classic Logistic Regression’s. Our empirical results show that Extra-Trees Classifier has the highest prediction accuracy of about 55% which outperforms Logistic Regression by about 0.6%. Although both Extra-Trees Classifier and Random Forest (RF) are based on the same approach, the former always obtains better prediction performance. Besides, while not providing the optimal results, Support Vector Machine seems not to depend on the number of features and training length

Improving Vietnamese-English Medical Machine Translation

Machine translation for Vietnamese-English in the medical domain is still an under-explored research area. In this paper, we introduce MedEV -- a high-quality Vietnamese-English parallel dataset constructed specifically for the medical domain, comprising approximately 360K sentence pairs. We conduct extensive experiments comparing Google Translate, ChatGPT (gpt-3.5-turbo), state-of-the-art Vietnamese-English neural machine translation models and pre-trained bilingual/multilingual sequence-to-sequence models on our new MedEV dataset. Experimental results show that the best performance is achieved by fine-tuning "vinai-translate" for each translation direction. We publicly release our dataset to promote further research.Comment: To appear in Proceedings of LREC-COLING 202

Future Changes in Hydro-Climatic Extremes across Vietnam: Evidence from a Semi-Distributed Hydrological Model Forced by Downscaled CMIP6 Climate Data

Flood hazards have led to substantial fatalities and economic loss in the last five decades, making it essential to understand flood dynamics in a warming climate. This study reports the first comprehensive assessment of projected flood hazards across Vietnam. We used downscaled climate data from the CMIP6 initiative, involving a total of 20 climate models, and streamflow projection simulated using a semi-distributed hydrological model. The assessment covers seven near-natural catchments, each representing a climate zone of the country. To evaluate climate change impacts on floods, the study simultaneously analyzes changes in three indices: (i) the annual hottest day temperature, to represent temperature extremes; (ii) the maximum daily rainfall amount, to represent rainfall extremes; and (iii) the discharge value exceeding 5% in a year, to assess streamflow extremes. Changes in the selected indices (relative to the reference period from 1985 to 2014) are assessed under four emission scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) and two future time slices (2036–2065 and 2070–2099). Although the robustness (as indicated by multi-model agreement) and significance (identified through the statistical test) of the changes vary substantially, depending on the selected indices and assessed time slices, an overall increase is consistently identified across all of the assessed hydro-climatic extremes (up to 4.8 °C for temperature extremes, 43 mm for rainfall extremes, and 31% for streamflow extremes). The findings suggest a potential increase in flood risk across Vietnam in a warming climate, highlighting the urgent need for improved flood preparedness and investment to reduce economic loss and mortality in an uncertain future