Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship of Self-Esteem to Grades, Achievement Scores, and Other Factors Critical to School Success.

According to research completed over students in grades 4 to 12. Kifer (1973) the past two decades, the importance of found a correlation of . 50 between self-es self-esteem related to school achieveteem scores and grades for seventh ment cannot be overemphasized (Bloom, graders. 1977; Ciernes & Bean, 1981; Wiggins, Despite the importance placed on self-es 1978, 1987). Despite the use of different teem by researchers, psychologists, and instruments and study goals, findings counselors, few schools do more than from numerous research studies are employ sporadic "hit or miss" procedures similar; self-esteem seems directly correwith selected students in helping in the lated with school performance to at least affective domain. Although there are cer a moderate degree. Ciernes & Bean tainly caring and concerned teachers and (1981) found that children with high selfother staff in almost any school who in esteem act positively, assume responfluence self-esteem positively, there are sibility, tolerate frustration, feel able to few programs in which self-esteem is a influence their environments, and are primary focus of learning (Purkey & Wat proud of their deeds. Conversely, son, 1984). children with low self-esteem are easily The current study looked at self-esteem led by others, become frustrated quickly related to earned grades, achievement test and easily, often blame others for their shortcomings, and tend to avoid difficult situations. Bloom (1977) found that . _ . , _. , . _ , . James D. Wtggtns and Ehzabeth L. Schatz are achievement and self-esteem were schœ, counselors and Richard w. Wesf is prln_ generally correlated. In another study cipa! , all at Great Bridge Middle School, North, in (Wiggins, 1987), self-esteem scores were Chesapeake, VA. Correspondence should be sent to found to be the only factor significantly James D. Wiggins at 3814 Trant Avenue, Norfolk, correlated with earned grades for 483 VA 23502.
Intercellular Adhesion Molecule 1 Regulates Left Ventricular Leukocyte Infiltration, Cardiac Remodeling, and Function in Pressure Overload–Induced Heart Failure

Background Left ventricular dysfunction and heart failure are strongly associated in humans with increased circulating levels of proinflammatory cytokines, T cells, and soluble intercellular cell adhesion molecule 1 (ICAM1). In mice, infiltration of T cells into the left ventricle contributes to pathological cardiac remodeling, but the mechanisms regulating their recruitment to the heart are unclear. We hypothesized that ICAM1 regulates cardiac inflammation and pathological cardiac remodeling by mediating left ventricular T‐cell recruitment and thus contributing to cardiac dysfunction and heart failure. Methods and Results In a mouse model of pressure overload–induced heart failure, intramyocardial endothelial ICAM1 increased within 48 hours in response to thoracic aortic constriction and remained upregulated as heart failure progressed. ICAM1‐deficient mice had decreased T‐cell and proinflammatory monocyte infiltration in the left ventricle in response to thoracic aortic constriction, despite having numbers of circulating T cells and activated T cells in the heart‐draining lymph nodes that were similar to those of wild‐type mice. ICAM1‐deficient mice did not develop cardiac fibrosis or systolic and diastolic dysfunction in response to thoracic aortic constriction. Exploration of the mechanisms regulating ICAM1 expression revealed that endothelial ICAM1 upregulation and T‐cell infiltration were not mediated by endothelial mineralocorticoid receptor signaling, as demonstrated in thoracic aortic constriction studies in mice with endothelial mineralocorticoid receptor deficiency, but rather were induced by the cardiac cytokines interleukin 1β and 6. Conclusions ICAM1 regulates pathological cardiac remodeling by mediating proinflammatory leukocyte infiltration in the left ventricle and cardiac fibrosis and dysfunction and thus represents a novel target for treatment of heart failure.
Performance Analysis of Superscalar Processors Using A Queueing Model

Performance Analysis of Sup erscalar Pro cessors Using AQueueing Mo delY. Zhu and W.F. WongDepartment of Information Systems and Computer ScienceNational University of Singap oreSingap ore 119260E-mail:fzhuyongx, wongwfg@comp.nus. edu.sgAbstractSup erscalar pro cessors have b ecome thede factostandard of RISC pro cessors to day.Dueto its complexity, estimating the p erformance of any sup erscalar pro cessor design is a diculttask. To this end, several analytical mo dels of such pro cessors have b een prop osed. In thispap er, wepresenta novelMultiple Class and Multiple Resource Queueing Model(MCMR) ofsup erscalar pro cessors. In this mo del, instruction classes and functional units can b e mo delledand studied. With analysis, numerical calculation and discrete event simulations, wewere ableto identify a b ottleneck in sup erscalar pro cessor design.1Intro ductionCurrenttechniques for determining the p erformance of a new sup erscalar pro cessor design areusually based ontrace-drivensimulation. A b enchmark is run on existing hardware to generatea trace. A simulator con gured for the new implementation then \runs" through the trace andgenerates p erformance information. In order to obtain accurate p erformance data, this pro cessmust b e rep eated for many large b enchmarks with extremely long traces. This approach has someshortcomings. The traces are long and exp ensive to store. Simulation of these long traces is alsotime-consuming.Another approach is mo delling. Previous works on this approach includes those of [Austin& Sohi 1992], [Lam & Wilson, 1992] and [Dub ey et al., 1994] which are based on probabilitytheory. These studies are generally exp erimental studies which attempt to obtain p erformance bysimulation. In [No onb erg & Shen, 1994] the use of probabilityvectors were prop osed in obtaining amore theoretical mo del of a sup erscalar pro cessor. However, none of the ab ove use queueing theoryin their mo delling. Our pap er presents a novel queueing mo del of sup erscalar pro cessors. In thistheoretical mo del, a b enchmark and a trace are analysed only once to compute the instructiondistributions. These distributions are essentially an abstraction of the characteristics of the trace.Each pro cessor implementation's sp eci cation is analysed to determine the functional unit resourceset. Once the instruction distributions of a program are determined, its p erformance on an arbitrarymachine, characterised by the functional unit resource set, can b e computed without re-examingthe trace.Section 2 describ es our mo del in detail. Section 3 gives analytical p erformance results of ourmo del. A discrete simulation setup to verify our mo del is describ ed in Section 4. The veri cationof our analytical results by discrete simulation in Section 5. This is followed by a conclusion.1
Chapter 5 : Derivatives and Integration

2 Numerical and Symbolic Integration 2 2.1 Cubature Formulae Notation . 2 2.2 Constructing Cubature Formulae . 3 2.2.1 Interpolatory Cubature Formulae . 3 2.2.2 Ideal Theory . 4 2.2.3 Bounds . 5 2.2.4 The characterization of minimal formulae and the reproducing kernel . 5 2.3 Gauss Formula on an A-patch . 6 2.3. 1 Gauss Points and Weights . 6 2.3. 2 Error Analysis . 6 2.4 T-method . 7 2.5 S-method . 8
1 Environmental Colloids and Particles : Current Knowledge and Future Developments

1 Definitions . 1 2 The Importance of Size . 3 3 Non-size-based measurements of colloids and particles . 9 4 Strategies for advancing our understanding of colloidal systems . 10 5 Future perspectives . 11 References . 12
The construction and analysis of gene co-expression network of differentially expressed genes identifies potential biomarkers in thyroid cancer

Background: The incidence and mortality of thyroid cancer has been increasing steadily in the United States. However, the molecular pathogenesis of thyroid cancer is not fully characterized. Methods: The R package of DESeq2 was applied to detect differentially expressed genes (DEGs) between 57 paired thyroid cancer and noncancerous tissues using RNA sequencing data from The Cancer Genome Atlas database. Weighted gene co-expression network analysis was used to construct co-expression modules and study the relationship between co-expression modules and clinical traits. Gene ontology (GO) enrichment analysis was performed on these genes from interested co-expression modules. Results: A cohort of 750 up-regulated and 296 down-regulated genes were identified in thyroid cancer. The weighted gene co-expression network analysis identified 5 gene co-expression modules. Two modules were significantly associated with patients’ age, cancer stage and multifocality. SERPINA1 and MRO were their hub genes respectively. Conclusions: The bioinformatics study for those co-expression modules and hub genes paves the way for the development of molecular biomarkers in thyroid cancer.
The circle to lariat ratio of the Ll.LtrB group II intron from Lactococcus lactis is greatly influenced by a variety of biological determinants in vivo

Bacterial group II introns mostly behave as versatile retromobile genetic elements going through distinct cycles of gain and loss. These large RNA molecules are also ribozymes splicing autocatalytically from their interrupted pre-mRNA transcripts by two different concurrent pathways, branching and circularization. These two splicing pathways were shown to release in bacterial cells significant amounts of branched intron lariats and perfect end-to-end intron circles respectively. On one hand, released intron lariats can invade new sites in RNA and/or DNA by reverse branching while released intron circles are dead end spliced products since they cannot reverse splice through circularization. The presence of two parallel and competing group II intron splicing pathways in bacteria led us to investigate the conditions that influence the overall circle to lariat ratio in vivo. Here we unveil that removing a prominent processing site within the Ll.LtrB group II intron, raising growth temperature of Lactococcus lactis host cells and increasing the expression level of the intron-interrupted gene all increased the relative amount of released intron circles compared to lariats. Strengthening and weakening the base pairing interaction between the intron and its upstream exon respectively increased and decreased the overall levels of released intron circles in comparison to lariats. Host environment was also found to impact the circle to lariat ratio of the Ll.LtrB and Ll.RlxA group II introns from L. lactis and the Ef.PcfG intron from Enterococcus faecalis. Overall, our data show that multiple factors significantly influence the balance between released intron circles and lariats in bacterial cells.
Spectrum Attention Mechanism for Time Series Classification

Time series classification (TSC) has always been an important and challenging research task. With the wide application of deep learning, more and more researchers use deep learning models to solve TSC problems. Since time series always contains a lot of noise, which has a negative impact on network training, the original data are usually filtered before the training of the network. The existing schemes are to treat the filtering and training as two stages, and the design of the filter requires expert experience, which increases the design difficulty of the algorithm and is not universal. We note that the essence of filtering is to filter out the insignificant frequency components and highlight the important ones, which is similar to the attention mechanism. In this paper, we propose an Spectrum Attention Mechanism (SAM). The network can assign appropriate weights to each frequency component to achieve adaptive filtering. We use $l1$ regularization to further enhance the frequency screening capability of the SAM. We also propose a Segmented-SAM (SSAM) to avoid the loss of time domain information caused by using the spectrum of the whole sequence. In which, a tumbling window is introduced to segment the original data. Then SAM is applied to each segment to generate new features. We propose a heuristic strategy to search for the appropriate number of segments. Experimental results show that SSAM can produce better feature representations to speed up the learning process, and improve the robustness and classification accuracy.
CAPITAL GAINS TAXES UNDER THE TAX REFORM ACT OF 1986: REVENUE ESTIMATES UNDER VARIOUS ASSUMPTIONS

THE the largest Tax Reform capital Act gains of 1986 tax rate enacted inthe largest capital gains tax rate increase in history. For the first time since 1922, the tax treatment of long-term capital gains became the same as the tax treatment of ordinary income. During the intervening 65 years, capital gains were either taxed separately from ordinary income under an "alternative" tax or received a partial exclusion from tax under the regular rate schedule. The end of special treatment for long-term capital gains means that the average tax rate faced by capital gains recipients will more than double from 9 percent under the old tax law to 21 percent under the new tax law. Although it is clear that the new tax rate on capital gains will rise substantially, there is controversy regarding the expected level of capital gains tax revenue. The realization and taxation of accrued capital gains occurs largely at the discretion of the taxpayer. Faced with higher tax rates, taxpayers may elect to realize gains less frequently than they otherwise would have. This reduced rate of realization could cause total capital gains taxes collected to be lower at higher tax rates than at lower tax rates. Substantial econometric research has been done to estimate the responsiveness of capital gains realizations to tax rates. This paper considers the results of five of these studies and the implication of these findings for capital gains tax revenue under the Tax Reform Act of 1986. The new tax law and its resulting effect on taxpayer behavior is simulated for the period 1986-1991. The simulation results produce a range for the expected level of capital gains tax revenue given the scope of academic investigations of taxpayer behavior to date. This range of expected revenue is then contrasted with the official revenue estimates by the Depart-
Why? Why not? When? Visual Explanations of Agent Behaviour in Reinforcement Learning

Reinforcement learning (RL) is used in many domains, including autonomous driving, robotics, stock trading, and video games. Unfortunately, the black box nature of RL agents, combined with legal and ethical considerations, makes it increasingly important that humans (including those are who not experts in RL) understand the reasoning behind the actions taken by an RL agent, particularly in safety-critical domains. To help address this challenge, we introduce PolicyExplainer, a visual analytics interface which lets the user directly query an autonomous agent. PolicyExplainer visualizes the states, policy, and expected future rewards for an agent, and supports asking and answering questions such as: “Why take this action? Why not take this other action? When is this action taken? ” PolicyExplainer is designed based upon a domain analysis with RL researchers, and is evaluated via qualitative and quantitative assessments on a trio of domains: taxi navigation, a stack bot domain, and drug recommendation for HIV patients. We find that PolicyExplainer's visual approach promotes trust and understanding of agent decisions better than a state-of-the-art text-based explanation approach. Interviews with domain practitioners provide further validation for PolicyExplainer as applied to safety-critical domains. Our results help demonstrate how visualization-based approaches can be leveraged to decode the behavior of autonomous RL agents, particularly for RL non-experts.
Fuzzy transfer learning for financial early warning system

XVIII CHAPTER 1: Introduction . 1 1.1 Background . 1 1.2 Research Challenges . 6 1.3 Research Objectives . 9 1.4 Research Contributions . 12 1.5 Research Methodology and Process . 14 1.5. 1 Research Methodology . 15 1.5. 1.1 Awareness of Problem . 15 1.5. 1.2 Suggestion . 15 1.5. 1.3 Development . 16 1.5. 1.4 Evaluation . 16 1.5. 1.5 Conclusion . 16 1.5. 2 Research Process . 17 1.6 Thesis Structure . 17 1.7 Publications Related to This Thesis . 20 CHAPTER 2: Literature Review . 22 2.1 Bank Failure Prediction and Early Warning System . 22 2.2 Feature Selection . 25 2.3 Financial Failure Prediction: Classical Statistical Methods . 28 2.4 Financial Failure Prediction: Intelligent Methods . 31 2.4. 1 Case-based Reasoning . 32 2.4. 2 Decision Tree . 33 2.4. 3 Support Vector Machines . 33 2.4. 4 Fuzzy Rule Based Classifier . 34 2.4. 5 Neural Network . 35 2.4. 6 Ensemble-based and Hybrid Methods. 36 2.4. 7 Fuzzy Neural Network . 39 2.5 Class Imbalance Problem and Solutions . 44 2.5. 1 Data Level Methods . 45 2.5. 2 Algorithm Level Methods . 47 2.5. 3 Cost-sensitive Learning Methods . 48 2.5. 4 Boosting Approaches . 48 2.5. 5 Evaluation Measures . 49 2.6 Transfer Learning . 52 2.6. 1 Definitions and Notations. 55 2.6. 2 Transductive Transfer Learning . 57 2.6. 2.1 Instance Weighting for Covariate Shift Methods . 59 2.6. 2.2 Self-labeling Methods . 60 2.6. 2.3 Feature Representation Methods. 62 2.6. 2.4 Cluster-based Learning Methods . 65 CHAPTER 3: Adaptive Inference-based Fuzzy Neural Network . 67 3.
Improved Tower Cranes Operation Using Integrated 3D BIM Model and GPS Technology

Tower and mobile cranes are the most commonly used equipment on building construction jobsites. They play an essential role in material handling, placement, assembly and erection operations. Statistics reveal that during the last decade, the construction industry has suffered globally from crane related accidents. Hence, detailed study of different aspects of crane-based activity is important in terms of time and safety. There are several studies for enhancing safety conditions of crane operations on jobsites to decrease the number of fatalities and even increase the productivity. Existing approaches and studies have deployed wireless networks and tracking sensors to detect and identify workers, but high initial cost for installation and maintenance of these technologies and inappropriate feedback for disregarding workers privacy hold down their usability. The purpose of this study is to develop a proactive lifting operation management system to prevent potential accidents caused by tower cranes’ components through using GPS in integrated 3D BIM models. In this study, generated workspaces are utilized to demonstrate areas occupied by workers or equipment instead of using individual tags for each entity. As construction workers may leave their work zone for some reasons, 3D video tracking is applied for identifying and tracking if workers leave their pre-defined workspaces. The developed model captures the load position in real time and subsequently compares the load’s bounding box position with defined area in BIM model. In the developed model, tower crane’s load dimensions and starting point of the loading procedure are inserted and subsequently the model updates the load’s position in real time. The updated position in the 3D model is checked proactively with existing spaces to send alerts in case of overlapping. Two case studies are used to demonstrate the concept and to validate the feasibility of the proposed method. In the first case study the added plug-in is used to generate workspaces for material, equipment and labors and in the second one, the real time safety system is validated in two different scenarios. The developed plug-in in Revit environment enhances timely proximity detection for enhanced safety since it detects objects based on pre-defined spaces and retrieves crane’s load location in the model in real time. Identifying resources of interest which being free of tag and developing the real time conflict detection in Revit can be addressed as main findings of this study.
The Practice of System and Network Administration, Second Edition

The first edition of The Practice of System and Network Administration introduced a generation of system and network administrators to a modern IT methodology. Whether you use Linux, Unix, or Windows, this newly revised edition describes the essential practices previously handed down only from mentor to protege. This wonderfully lucid, often funny cornucopia of information introduces beginners to advanced frameworks valuable for their entire career, yet is structured to help even the most advanced experts through difficult projects.The book's four major sections build your knowledge with the foundational elements of system administration. These sections guide you through better techniques for upgrades and change management, catalog best practices for IT services, and explore various management topics. Chapters are divided into The Basics and The Icing. When you get the Basics right it makes every other aspect of the job easier--such as automating the right things first. The Icing sections contain all the powerful things that can be done on top of the basics to wow customers and managers.Inside, you'll find advice on topics such as The key elements your networks and systems need in order to make all other services run better Building and running reliable, scalable services, including web, storage, email, printing, and remote access Creating and enforcing security policies Upgrading multiple hosts at one time without creating havoc Planning for and performing flawless scheduled maintenance windows Managing superior helpdesks and customer care Avoiding the "temporary fix" trap Building data centers that improve server uptime Designing networks for speed and reliability Web scaling and security issues Why building a backup system isn't about backups Monitoring what you have and predicting what you will need How technically oriented workers can maintain their job's technical focus (and avoid an unwanted management role) Technical management issues, including morale, organization building, coaching, and maintaining positive visibility Personal skill techniques, including secrets for getting more done each day, ethical dilemmas, managing your boss, and loving your job System administration salary negotiation It's no wonder the first edition received Usenix SAGE's 2005 Outstanding Achievement Award! This eagerly anticipated second edition updates this time-proven classic: Chapters reordered for easier navigation Thousands of updates and clarifications based on reader feedback Plus three entirely new chapters: Web Services, Data Storage, and Documentation