Боротьба української громадськості за розв’язання мовної проблеми в народних школах (друга половина ХІХ – початок ХХ ст.)

(uk) У статті висвітлено маловідомі сторінки історії боротьби української громадськості за розв’язання мовної проблеми в народних школах у другій половині ХІХ – на початку ХХ ст. Важливу роль у цих змаганнях відіграли педагогічні з’їзди та з’їзди отців-законовчителів.(en) The article covers the little-known pages of the history of the struggle of the Ukrainian Community for the decision of the language problem in national schools in the second half of the 19th century and at the beginning of the 20th century. Pedagogical congresses played an important part in those contests

Dirac-Electrons-Mediated Magnetic Proximity Effect in Topological Insulator / Magnetic Insulator Heterostructures

The possible realization of dissipationless chiral edge current in a topological insulator / magnetic insulator heterostructure is based on the condition that the magnetic proximity exchange coupling at the interface is dominated by the Dirac surface states of the topological insulator. Here we report a polarized neutron reflectometry observation of Dirac electrons mediated magnetic proximity effect in a bulk-insulating topological insulator (Bi$_{0.2}$Sb$_{0.8}$)$_{2}$Te$_{3}$ / magnetic insulator EuS heterostructure. We are able to maximize the proximity induced magnetism by applying an electrical back gate to tune the Fermi level of topological insulator to be close to the charge neutral point. A phenomenological model based on diamagnetic screening is developed to explain the suppressed proximity induced magnetism at high carrier density. Our work paves the way to utilize the magnetic proximity effect at the topological insulator/magnetic insulator hetero-interface for low-power spintronic applications.Comment: 5 pages main text with 4 figures; 2 pages supplemental materials; suggestions and discussions are welcome

Ab initio study of electron mean free paths and thermoelectric properties of lead telluride

Last few years have witnessed significant enhancement of thermoelectric figure of merit of lead telluride (PbTe) via nanostructuring. Despite the experimental progress, current understanding of the electron transport in PbTe is based on either band structure calculation using first principles with constant relaxation time approximation or empirical models, both relying on adjustable parameters obtained by fitting experimental data. Here, we report parameter-free first-principles calculation of electron and phonon transport properties of PbTe, including mode-by-mode electron-phonon scattering analysis, leading to detailed information on electron mean free paths and the contributions of electrons and phonons with different mean free paths to thermoelectric transport properties in PbTe. Such information will help to rationalize the use and optimization of nanostructures to achieve high thermoelectric figure of merit

Auxin response factor 6A regulates photosynthesis, sugar accumulation, and fruit development in tomato.

Auxin response factors (ARFs) are involved in auxin-mediated transcriptional regulation in plants. In this study, we performed functional characterization of SlARF6A in tomato. SlARF6A is located in the nucleus and exhibits transcriptional activator activity. Overexpression of SlARF6A increased chlorophyll contents in the fruits and leaves of tomato plants, whereas downregulation of SlARF6A decreased chlorophyll contents compared with those of wild-type (WT) plants. Analysis of chloroplasts using transmission electron microscopy indicated increased sizes of chloroplasts in SlARF6A-overexpressing plants and decreased numbers of chloroplasts in SlARF6A-downregulated plants. Overexpression of SlARF6A increased the photosynthesis rate and accumulation of starch and soluble sugars, whereas knockdown of SlARF6A resulted in opposite phenotypes in tomato leaves and fruits. RNA-sequence analysis showed that regulation of SlARF6A expression altered the expression of genes involved in chlorophyll metabolism, photosynthesis and sugar metabolism. SlARF6A directly bound to the promoters of SlGLK1, CAB, and RbcS genes and positively regulated the expression of these genes. Overexpression of SlARF6A also inhibited fruit ripening and ethylene production, whereas downregulation of SlARF6A increased fruit ripening and ethylene production. SlARF6A directly bound to the SAMS1 promoter and negatively regulated SAMS1 expression. Taken together, these results expand our understanding of ARFs with regard to photosynthesis, sugar accumulation and fruit development and provide a potential target for genetic engineering to improve fruit nutrition in horticulture crops

Essays on Machine Learning on Financial Economics, and Human Capital Development

The overarching theme of this dissertation revolves around the predictive modeling of economic and financial risks using advanced econometric and machine learning techniques, and human capital development. The three essays presented in this work explore diverse but interconnected aspects of risk assessment: human capital development through education, systemic financial risk forecasting, and loan risk prediction in government intervention programs. Each study contributes to understanding risk dynamics in different domains—education, banking stability, and targeted lending programs—providing valuable insights for policymakers and financial institutions. The first two essays use Machine learning techniques and the third essay use fixed effect OLS methodology.The first paper, "Forecasting Systemic Risk of Banks with Machine Learning," shifts the focus to financial stability. This study applies machine learning techniques to predict systemic risk in the banking sector, particularly through the lens of Value at Risk (VaR) and other risk metrics. By leveraging institutional and macroeconomic variables, the research enhances traditional risk assessment frameworks, demonstrating the predictive power of machine learning in financial stability analysis.The second paper, "Forecasting Loan Risk of Banks with Machine Learning in the Main Street Lending Program," extends the discussion to targeted government interventions in financial markets. This study examines how machine learning can improve loan risk prediction for banks participating in the Main Street Lending Program (MSLP), a key policy response to economic distress. By analyzing borrower characteristics, macroeconomic conditions, and financial indicators, this research provides insights into the effectiveness of such programs in mitigating credit risk and supporting economic recovery.The third paper, "How Birth Order and Gender Affect the Test Score of Children," investigates how demographic factors shape human capital accumulation. Using empirical analysis, the study examines the role of birth order and gender in determining academic performance, shedding light on the long-term implications of family dynamics on educational outcomes. By identifying systematic patterns in test scores, this research contributes to the broader literature on education economics and inter-generational mobility.Together, these essays contribute to the broader understanding of risk forecasting in education and finance. While the first study addresses the early-stage determinants of human capital development, the latter two focus on financial risk assessment and forecasting. The interdisciplinary nature of this dissertation underscores the role of quantitative methods in economic and financial decision-making, offering implications for both policymakers and practitioners

Algal biomass production and nutrient removal from high strength anaerobic digestate

The integration of microalgal biomass production with nutrient removal from the liquid portion of anaerobic digestate holds the potential to close the loop on waste. However, algal growth inhibition in anaerobic digestate has greatly suppressed the development of growing microalgae in anaerobic digestate at scale. Typically, 10-50 fold dilution were used to overcome the inhibition in lab scale studies which tried to grow microalgae in anaerobic digestate, but it is not cost-effective using dilution as the primary approach for inhibition alleviation in large scale algae-digestate treatment systems when considering the expansion of reactor volume, the large amount of freshwater usage, and the increased land occupancy. This dissertation focuses on alleviating algal growth in anaerobic digestate by a non-dilution biological pretreatment process. The algal inhibitory effects from anaerobic effluent were observed shortly after the attempts of growing microalgae in the digestate. The inhibition was severe and ubiquitous for a variety of microalgae in different types of anaerobic digestate based on our own work. The most common hypothesis for inhibition on digestate is the high total ammonia nitrogen (TAN) in the digestates. However, TAN inhibition did not fully explain the observations from algal growth in anaerobic digestate. High ammonium tolerating algae strain such as Chlorella sorokiniana can be robust in a chemical medium with 3500 mg L-1 ammonium. Moreover, the meta-analysis also revealed relationships between cultivation factors (e.g., light intensity, solid-separation, initial TAN, dilution factor, axenic condition etc.) and algal productivity in anaerobic digestate. Interestingly, neither TAN nor dilution were significant factors. In contrast, the use of chemical or biological pretreatment of digestate, solids removal, increased light intensity, and lower pH also resulted in significantly higher algal productivity. This analysis suggests that the development of non-dilution pretreatment approaches is essential for scale-up of algae-digestate treatment systems. Biological wastewater treatment such as activated sludge is a relatively mature technique in most wastewater treatment plants. The use of aerobic bacteria can be effective in removing organic and inorganic pollutants. First objective in this dissertation was to use aerobic bacteria as a pretreatment process for anerobic digestate before the inoculation of microalgae. A consortium of bacteria obtained from an activated sludge wastewater treatment plant was used to pretreat digestate prior to algae growth. No dilution of digestate was used. C. sorokiniana achieved very high biomass productivity of 250-500 mg L-1 day-1 in bacteria-pretreated municipal sludge digestate and food waste digestate whereas little to negative productivity was observed in the digestates without pretreatment. Pretreatment also led to significant increase in nutrient removal rate compared to the non-pretreated ones. The second objective of this research was to understand what cultivation factors contribute to successful pretreatment of digestate prior to algae growth… The performance of aerobic bacteria pretreatment for alleviating algal growth inhibition in undiluted anaerobic digestate was tested with two different strains of algae (C. sorokiniana and A. protothecoides) in two different strengths of anaerobic digestate. Both digestate types were obtained from a sludge digester at a municipal wastewater treatment plant but were collected at two different times: one digestate contained 1372 mg/L NH4-N (high strength) and the other contained 433 mg/L NH4-N (low strength). In high strength municipal sludge digestate, both strains of algae benefited from pretreatment, but in low strength digestate, the growth of C. sorokiniana was suppressed due to nutrient limitations. The performance test also revealed that longer pretreatment period generally had positive effect on alleviating algal growth inhibition from the digestate. Interestingly, the xenic (vs. axenic) condition was not a significant factor in this experimental result which is consistent with the result of multiple regression model from the meta-analysis study. Up until this point, model strains of algae were used in all experiments. However, such strains are unlikely to be practical in real-world systems given concerns about introducing non-native organisms to the environment. Consequently, the third objective of this dissertation was to adapt locally obtained consortia of algae to pretreated digestate and test the adapted community’s growth and nutrient removal performance. Local consortia were collected from local fishponds and the biofloc solids from Auburn University’s aquaponics system. The consortia were initially inoculated in 10% aerobic bacteria pretreated dairy manure anaerobic digestate, and gradually increased to 100% pretreated digestate. A complete restructuring of the algal community was observed in which the initial eukaryotic community was 95% Euglena the final was 70% Coelastrum with complete die-out of Euglena. Although the adapted consortium had 75% of the growth productivity of C. sorokiniana in the pretreated digestate, it did not grow in the non-pretreated digestate. This result reinforced the importance of digestate pretreatment for this native consortium. In summary, aerobic bacteria pretreatment is confirmed to be effective and critical for algal biomass production and nutrient removal in undiluted anaerobic digestate

멀티 태스킹 환경에서 GPU를 사용한 범용적 계산 응용의 효율적인 시스템 자원 활용을 위한 GPU 시스템 최적화

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2020. 8. 염헌영.Recently, General Purpose GPU (GPGPU) applications are playing key roles in many different research fields, such as high-performance computing (HPC) and deep learning (DL). The common feature exists in these applications is that all of them require massive computation power, which follows the high parallelism characteristics of the graphics processing unit (GPU). However, because of the resource usage pattern of each GPGPU application varies, a single application cannot fully exploit the GPU systems resources to achieve the best performance of the GPU since the GPU system is designed to provide system-level fairness to all applications instead of optimizing for a specific type. GPU multitasking can address the issue by co-locating multiple kernels with diverse resource usage patterns to share the GPU resource in parallel. However, the current GPU mul- titasking scheme focuses just on co-launching the kernels rather than making them execute more efficiently. Besides, the current GPU multitasking scheme is not open-sourced, which makes it more difficult to be optimized, since the GPGPU applications and the GPU system are unaware of the feature of each other. In this dissertation, we claim that using the support from framework between the GPU system and the GPGPU applications without modifying the application can yield better performance. We design and implement the frame- work while addressing two issues in GPGPU applications. First, we introduce a GPU memory checkpointing approach between the host memory and the device memory to address the problem that GPU memory cannot be over-subscripted in a multitasking environment. Second, we present a fine-grained GPU kernel management scheme to avoid the GPU resource under-utilization problem in a i multitasking environment. We implement and evaluate our schemes on a real GPU system. The experimental results show that our proposed approaches can solve the problems related to GPGPU applications than the existing approaches while delivering better performance.최근 범용 GPU (GPGPU) 응용 프로그램은 고성능 컴퓨팅 (HPC) 및 딥 러닝 (DL)과 같은 다양한 연구 분야에서 핵심적인 역할을 수행하고 있다. 이러한 응 용 분야의 공통적인 특성은 거대한 계산 성능이 필요한 것이며 그래픽 처리 장치 (GPU)의 높은 병렬 처리 특성과 매우 적합하다. 그러나 GPU 시스템은 특정 유 형의 응용 프로그램에 최저화하는 대신 모든 응용 프로그램에 시스템 수준의 공정 성을 제공하도록 설계되어 있으며 각 GPGPU 응용 프로그램의 자원 사용 패턴이 다양하기 때문에 단일 응용 프로그램이 GPU 시스템의 리소스를 완전히 활용하여 GPU의 최고 성능을 달성 할 수는 없다. 따라서 GPU 멀티 태스킹은 다양한 리소스 사용 패턴을 가진 여러 응용 프로그 램을 함께 배치하여 GPU 리소스를 공유함으로써 GPU 자원 사용률 저하 문제를 해결할 수 있다. 그러나 기존 GPU 멀티 태스킹 기술은 자원 사용률 관점에서 응 용 프로그램의 효율적인 실행보다 공동으로 실행하는 데 중점을 둔다. 또한 현재 GPU 멀티 태스킹 기술은 오픈 소스가 아니므로 응용 프로그램과 GPU 시스템이 서로의 기능을 인식하지 못하기 때문에 최적화하기가 더 어려울 수도 있다. 본 논문에서는 응용 프로그램을 수정 없이 GPU 시스템과 GPGPU 응용 사 이의 프레임워크를 통해 사용하면 보다 높은 응용성능과 자원 사용을 보일 수 있음을 증명하고자 한다. 그러기 위해 GPU 태스크 관리 프레임워크를 개발하여 GPU 멀티 태스킹 환경에서 발생하는 두 가지 문제를 해결하였다. 첫째, 멀티 태 스킹 환경에서 GPU 메모리 초과 할당할 수 없는 문제를 해결하기 위해 호스트 메모리와 디바이스 메모리에 체크포인트 방식을 도입하였다. 둘째, 멀티 태스킹 환 경에서 GPU 자원 사용율 저하 문제를 해결하기 위해 더욱 세분화 된 GPU 커널 관리 시스템을 제시하였다. 본 논문에서는 제안한 방법들의 효과를 증명하기 위해 실제 GPU 시스템에 92 구현하고 그 성능을 평가하였다. 제안한 접근방식이 기존 접근 방식보다 GPGPU 응용 프로그램과 관련된 문제를 해결할 수 있으며 더 높은 성능을 제공할 수 있음을 확인할 수 있었다.Chapter 1 Introduction 1 1.1 Motivation 2 1.2 Contribution . 7 1.3 Outline 8 Chapter 2 Background 10 2.1 GraphicsProcessingUnit(GPU) and CUDA 10 2.2 CheckpointandRestart . 11 2.3 ResourceSharingModel. 11 2.4 CUDAContext 12 2.5 GPUThreadBlockScheduling . 13 2.6 Multi-ProcessServicewithHyper-Q 13 Chapter 3 Checkpoint based solution for GPU memory over- subscription problem 16 3.1 Motivation 16 3.2 RelatedWork. 18 3.3 DesignandImplementation . 20 3.3.1 System Design 21 3.3.2 CUDAAPIwrappingmodule 22 3.3.3 Scheduler . 28 3.4 Evaluation. 31 3.4.1 Evaluationsetup . 31 3.4.2 OverheadofFlexGPU 32 3.4.3 Performance with GPU Benchmark Suits 34 3.4.4 Performance with Real-world Workloads 36 3.4.5 Performance of workloads composed of multiple applications 39 3.5 Summary 42 Chapter 4 A Workload-aware Fine-grained Resource Manage- ment Framework for GPGPUs 43 4.1 Motivation 43 4.2 RelatedWork. 45 4.2.1 GPUresourcesharing 45 4.2.2 GPUscheduling . 46 4.3 DesignandImplementation . 47 4.3.1 SystemArchitecture . 47 4.3.2 CUDAAPIWrappingModule . 49 4.3.3 smCompactorRuntime . 50 4.3.4 ImplementationDetails . 57 4.4 Analysis on the relation between performance and workload usage pattern 60 4.4.1 WorkloadDefinition . 60 4.4.2 Analysisonperformancesaturation 60 4.4.3 Predict the necessary SMs and thread blocks for best performance . 64 4.5 Evaluation. 69 4.5.1 EvaluationMethodology. 70 4.5.2 OverheadofsmCompactor . 71 4.5.3 Performance with Different Thread Block Counts on Dif- ferentNumberofSMs 72 4.5.4 Performance with Concurrent Kernel and Resource Sharing 74 4.6 Summary . 79 Chapter 5 Conclusion. 81 요약. 92Docto