Search

A Machine Learning framework for predicting enrollment is proposed. The framework consists of Amazon Web Services SageMaker together with standard Python tools for data analytics, including Pandas, NumPy, MatPlotLib, and ScikitLearn. The tools are deployed with Jupyter Notebooks running on AWS SageMaker. Based on three years of enrollment history, a model is built to compute--individually or in batch mode--probabilities of enrollments for given applicants. These probabilities can then be used during the admissions period to target undecided students. The audience for this paper is both SEM practitioners and technical practitioners in the area of data analytics. Through reading this paper, enrollment management professionals will be able to understand what goes into the preparation of a Machine Learning model to help with predicting admission rates. Technical experts, on the other hand, will gain a blueprint for what is required from them.

Dengue annually infects millions of people from a regionally and seasonally varying dengue virus population circulating as four distinct serotypes. Effective protection against dengue infection and disease requires tetravalent vaccine formulations to stimulate a balanced protective immune response to all four serotypes. However, this has been a challenge to achieve, and several clinical trials with different leading vaccine candidates have demonstrated unbalanced replication and interference of interindividual serotype components, leading to low efficacy and enhanced disease severity for dengue-naïve populations. Production of serotype-specific neutralizing antibodies is largely viewed as a correlate of protection against severe dengue disease. However, the underlying mechanisms that lead to these protective immune responses are not clearly elucidated. In this work, using a stochastic model of B cell affinity maturation, we tested different live-attenuated vaccine constructs with varied viral replication rates and contrasted the initiation and progress of adaptive immune responses during tetravalent vaccination and after dengue virus challenge. Comparison of our model simulations across different disease-severity levels suggested that individual production of high levels of serotype-specific antibodies together with a lower cross-reactive antibody are better correlates for protection. Furthermore, evolution of these serotype-specific antibodies was dependent on the percent of viral attenuation in the vaccine, and production of initial B cell and T cell populations pre- and post-secondary dengue infection was crucial in providing protective immunity for dengue-naïve populations. Furthermore, contrasting disease severity with respect to different dengue serotypes, our model simulations showed that tetravalent vaccines fare better against DENV-4 serotype when compared to other serotypes.

Hanoi is the second largest city in Vietnam. The effects of climate change, coupled with rapid, unchecked urbanization and population increase are resulting in a severe rise in incidents of heat stress, which has serious ramifications for community health. In this study, a multivariable linear regression, heat index (HI) methods, and climate change scenarios for Vietnam in 2020 are used as input data to calculate the daily maximum heat index (HImax) for Hanoi during 2024-2028. Findings indicate that HImax at danger level has already occurred and will happen again in the future, with seasonal characteristics mainly distributed in June, July, August. For the years 2024-2028, HImax at the danger level increases in two scenarios compared to 2017-2021. Notably, the number of days with HImax at the extreme danger level, which may be the main cause of heat stroke, has 0.4 days/year occurring during 2017-2021. However, it will also appear in the years 2024-2028 in both RCP 4.5 and RCP 8.5 scenarios from June to August, at 0.6 days/year and 2.6 days/year, respectively. Knowing the daily maximum heat index for the future at specific times is crucial information for acting on the risk of heat stress in Hanoi given the current danger posed by climate change. [ABSTRACT FROM AUTHOR]

Even minor fluctuations in the carbon content in forest soil can significantly impact atmospheric carbon concentrations and future global climate patterns. Therefore, investigating the variation characteristics of soil organic carbon (SOC) in tropical forests is essential for comprehending the carbon sequestration potential of forest soil. This study delves into SOC dynamics within the natural forest types of Dongnai Culture and Nature Reserve in southeastern Vietnam. Nine 1000 m² plots were sampled across rich, medium, and poor forests. Soil samples were collected from depths ranging from 0 to 60 cm. The findings revealed increased SOC content from poor to rich forests, with a decrease in depth. The total carbon (C) stocks ranged from 92.20 Mg C ha-1 in poor forests to 124.30 Mg C ha-1 in rich forests within the top 60 cm. Over 81% of soil C was concentrated in the upper 40 cm. Factors such as soil water content and slope gradient emerged as crucial determinants affecting SOC distribution. These results underscore the potential of forest management practices to augment SOC levels, thereby offering valuable insights for estimating carbon stocks in the forest ecosystems of southeastern Vietnam. [ABSTRACT FROM AUTHOR]

The dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequent infections from a different serotype. We developed a stochastic model of the adaptive immune response to dengue infections. We first delineated the mechanisms initiating and sustaining adaptive immune responses during primary infections. We then contrasted these immune responses during secondary infections of either a homotypic or heterotypic serotype to understand the role of pre-existing and reactivated immune pathways on disease severity. Comparison of non-symptomatic and severe cases from heterotypic infections demonstrated that overproduction of specific antibodies during primary infection induces an enhanced population of cross-reactive antibodies during secondary infection, ultimately leading to severe disease manifestations. In addition, the level of disease severity was found to correlate with immune response kinetics, which was dependent on beginning lymphocyte levels. Our results detail the contribution of specific lymphocytes and antibodies to immunity and memory recall that lead to either protective or pathological outcomes, allowing for the understanding and determination of mechanisms of protective immunity.

Meteorological factors, especially temperature and humidity, have a great impact on human physiology. In the context of climate change, the impact of temperature on people's health in Thai Binh city (Vietnam) is becoming more and more serious. Based on meteorological data for the period of 1991-2021 and Vietnam climate change scenario data, the daily maximum heat index (HImax) scenario for the period of 2024-2054 is calculated by the method of correlation evaluation and regression equations. The results show that in the future the trend of HImax is 0.0875°C per year under the RCP 4.5 scenario (Medium Low Greenhouse Gases Concentration Scenario) and 0.0919°C per year under the RCP 8.5 scenario (High Greenhouse Gases Concentration Scenarios). The number of weeks per 5 years having daily HImax at danger level (HIwave) tends to increase 6.14 times for scenario RCP 4.5; 7.0 times for scenario RCP 8.5. Especially, the number of days at risk of heat stroke in the past 31-year period is 5 days, then in the future 31-year period there are 77 days with scenario RCP 4.5 and 116 days with scenario RCP 8.5 and this phenomenon mainly concentrated in the months of June, July, August. [ABSTRACT FROM AUTHOR]

The incidence of chronic graft-versus-host disease (cGVHD) is on the rise and still the major cause of morbidity and mortality among patients after allogeneic hematopoietic stem cell transplantation (HCT). Both donor T and B cells contribute to the pathogenesis of cGVHD. Inducible T-cell co-stimulator (ICOS), a potent co-stimulatory receptor, plays a key role in T-cell activation and differentiation. Yet, how ICOS regulates the development of cGVHD is not well understood. Here, we investigated the role of ICOS in cGVHD pathogenesis using mice with germline or regulatory T cell (Treg)-specific ICOS deficiency. The recipients of ICOS−/− donor grafts had reduced cGVHD compared with wild-type controls. In recipients of ICOS−/− donor grafts, we observed significant reductions in donor T follicular helper (Tfh), Th17, germinal center B-cell, and plasma cell differentiation, coupled with lower antibody production. Interestingly, Tregs, including follicular regulatory T (Tfr) cells, were also impaired in the absence of ICOS. Using ICOS conditional knockout specific for Foxp3+ cells, we found that ICOS was indispensable for optimal survival and homeostasis of induced Tregs during cGVHD. Furthermore, administration of anti-ICOS alleviated cGVHD severity via suppressing T effector cells without affecting Treg generation. Taken together, ICOS promotes T- and B-cell activation and differentiation, which can promote cGVHD development; however, ICOS is critical for the survival and homeostasis of iTregs, which can suppress cGVHD. Hence, ICOS balances the development of cGVHD and could offer a potential target after allo-HCT in the clinic.

Metabolism, including catabolism and anabolism, is a basic cellular process necessary for cell survival. T lymphocytes have a distinct metabolism that can determine both fate and function. T-cell activation depends on glycolysis to obtain materials and energy for proliferation and effector function. Importantly, T cells utilize different metabolic processes under different conditions and diseases. Allogeneic hematopoietic cell transplantation (allo-HCT) is a classic immunotherapy for hematological malignancies; however, the development of graft-versus-host disease (GVHD) is a major factor limiting the success of allo-HCT. T cells in the donor graft drive GVHD by mounting a robust immunological attack against recipient normal tissues. Hence, understanding T-cell metabolism after allo-HCT would provide potential metabolic targets for the control of GVHD and primary tumor relapse. The purpose of the current review is to highlight the key metabolic pathways involved in alloantigen-activated T cells and to discuss how manipulating these pathways can serve as potential new therapeutic strategies to induce immune tolerance after allo-transplantation. We will also summarize the recent progress in regulating T-cell metabolism in bone marrow transplantation by targeting novel metabolic regulators or immune checkpoint molecules.

Herein, bimetal (Mn, Co) codoping on a CuO host is aimed at enhancing oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) activity. Codoping of Mn and Co on CuO to enhance bifunctional action in electrochemical water splitting has not yet been investigated to the best of our knowledge. Literatures are focused on unary Mn-doped CuO or Co-doped CuO nanostructures. Mn, Co codoped CuO through an easy chemical coprecipitation method has been successfully attempted and is more beneficial which is the novelty of the present work. Defect-enriched ample active sites (Mn2+/Mn3+ and Co2+/Co3+) along with Cu2+ in the host CuO achieved high current density (100 mA/cm2) in OER and HER with low overpotential such as 468 mV and 271 mV, respectively. Faster charge transfer and diffusion ability was stimulated by the bimetal codoping CuO. Reasonable Tafel plot values (OER: 199 mV/dec, and HER: 21 mV/dec) with improved water-splitting reaction kinetics were achieved for the Mn, Co codoped CuO nanoflakes. The double-layer capacitance ( C dl ) value of 27.5 mF/cm2 for Mn, Co codoped CuO nanoflakes was achieved. Similarly, the increasing order of an electrochemically active surface area (EASA) was exhibited by the consequent addition of bimetal doping on CuO, denoted as Mn , Co / CuO > Co / CuO > Mn / CuO > CuO. The evidence shows that the codoping strategy could facilitate rapid reaction kinetics to develop overall water splitting. The charge transfer resistances ( R ct ) of 3.6 Ω and 1.2 Ω for the Mn, Co codoped CuO nanostructure corresponding to the OER and HER, respectively, were reported. The long-term stability over 16 h with negligible loss was reported for both the OER and the HER performance. Thus, this work contributes to better insight and analysis of the successful codoping of bimetal elements in earth-abundant electrocatalysts to enhance and make practical the electrocatalytic water-splitting activity. [ABSTRACT FROM AUTHOR]

This paper presents a robust bi-level co-optimization model that promotes the active participation of Internet Data Centers (IDCs) in demand response (DR) programs, thereby enhancing the flexibility of power systems. Our approach involves leveraging virtual power lines to migrate workloads among IDCs, optimizing resource allocations, and benefiting both domains. The model incorporates a Gaussian Process Regression (GPR)-constructed DR price–amount curve, which largely contributes to the simplification of the optimization problem with high accuracy and computational efficiency. It also respects the information barriers between the two domains of power systems and IDCs, and thus safeguards the privacy and flexibility of IDCs. The uncertainty in IDC operations is considered by incorporating the variance in GPR into the demand response curve. By integrating IDCs as DR resources, the framework of this research enhances the flexibility of power systems and the efficiency of cross-domain co-optimization. The model and algorithm are validated using modified IEEE test systems. [ABSTRACT FROM AUTHOR]