Miracle-dz/UniFAR-FTUs huggingface dataset:
LEARNING to Reduce Recidivism A 50-state analysis of postsecondary correctional education policy

former Graduate Fellows, were instrumental in developing the concept for this report and in assembling much of the background material. who arranged for us to meet with a group of incarcerated men at the Coffeewood Correctional Center for a discussion that opened our eyes to the realities of attending college while in prison. Our work benefi ted from the expertise and assistance of a number of people: We would also like to thank the Ford Foundation for providing generous fi nancial support for this project. FIGURE 1. Race/ethnicity of state and federal prisoners with sentences over one year versus the total U.S. population, 2003. FIGURE 2. Socioeconomic characteristics of state and federal prisoners before arrest versus the total U.S. population, 1997. FIGURE 3. Highest educational attainment of state and federal prisoners versus the total U.S. Executive Summary H igher education for prisoners, often the subject of public controversy, remains a crucial strategy in efforts to reduce recidivism and slow the growth of the nation's incarcerated population. New research conducted by the Institute for Higher Education Policy shows that corrections offi cials are fi nding innovative ways to support postsecondary programs in their prison systems. Despite the loss of Pell Grant eligibility a decade ago, prisoners are participating in higher education in record numbers nationwide. With additional funding and concentrated efforts to reduce the many barriers that still make it diffi cult for prisoners to gain access to higher education, postsecondary correctional education programs offer the potential to provide incarcerated men and women with a second chance at productive citizenship. This report is based upon several primary assumptions that refl ect current research in the fi eld of justice policy. Data collected by the federal government show that prisoners nationwide are far less educated than the general U.S. population and, before incarceration, were signifi cantly more impoverished. Young minority men are particularly overrepresented in American prisons. Overall, the people who make up the incarcerated population are, in fact, those who have had the least opportunity prior to imprisonment. Furthermore, research studies provide strong evidence that postsecondary correctional education can achieve a variety of important purposes. Higher education can improve conditions within correctional facilities, enhance prisoner self-esteem and prospects for employment after release, and function as a cost-effective approach to reducing recidivism. Educating prisoners also allows them access to the many economic and social benefi ts associated with higher education. Postsecondary correctional …
Nonlinear Eigenvalue Problems

Heinrich Voss Hamburg University of Technology 115.1 Basic Properties . 115-2 115.2 Analytic matrix functions . 115-3 115.3 Variational Characterization of Eigenvalues . 115-7 115.4 General Rayleigh Functionals . 115-9 115.5 Methods for dense eigenvalue problems . 115-10 115.6 Iterative projection methods . 115-13 115.7 Methods using invariant pairs . 115-17 115.8 The infinite Arnoldi method . 115-20 References . 115-22
Antecedents and Consequences of Service Quality in Online Banking: an Application of the Servqual Instrument

INTRODUCTION During the past decade, the online service industry has witnessed tremendous growth, much of it spurred by the Internet revolution (Keaveney and Parthasarathy, 2001). Especially, the potential of the Web as a commercial medium is widely recognized and the growth in online service industries such as online banking has increased rapidly. In addition to Internet companies, traditional organizations are investing a huge amount of money and effort in information systems to provide online services through the Web. The underlying assumption of their investment is that, because online services provide their customers with convenience, interactivity, relatively low cost, and a high degree of customization/ personalization, they will enhance customer satisfaction and retention more effectively than offline-based services (Khalifa & Liu, 2001). To justify their investment in online services, many organizations are trying to measure the quality of their online services and investigate the relationships between service quality and customer satisfaction. However, a formal methodology for measuring online service quality is not well developed yet. Traditionally, many studies of service marketing have tried to define service quality and develop instruments to measure it. Since Parasuraman et al.(1988) introduced a service quality instrument, called SERVQUAL, many studies have used SERVQUAL to measure service quality in various domains, ranging from financial services (Lin, 1999), health services (Dean, 1999), travel agent services (Kaynama, 2000), and retailing services (Mehta, 2000), to restaurants (Lee and Hing 1995). However, since SERVQUAL was originally developed to measure service quality delivered through regular offline channels, its use in the Information System (IS) domain could be somewhat problematic (Van Dyke et al., 1999). Recently, a few studies have begun investigating the suitability of SERVQUAL in assessing the quality of online services (Gefen & Devine, 2001). The main objective of this study is to investigate the usefulness and applicability of SERVQUAL in measuring online service quality and its relationships to customer satisfaction and customer retention. By exploring the suitability of SERVQUAL and the outcome of service quality, this study enhances understanding of the causal relationships among service quality, customer satisfaction, and customer retention, in the context of online banking services.
SPECTRUM OCCUPANCY MEASUREMENTS IN NIGERIA: RESULTS AND ANALYSIS

Cognitive radio paradigm has been identified as the solution to spectrum underutilization. It promises to change the face of spectrum management from planning, allocation and subsequently and most importantly utilization. The present command and control approach in allocating spectrum has been found to be ineffective. This inefficiency has lead to a perceived spectrum scarcity. Spectrum occupancy measurements have disputed this fact; through these measurements it has been found that the spectrum is actually underutilized. Thorough understanding of the allocated spectrum will go a long way towards the successful deployment of cognitive radio paradigm. Currently, several spectrum occupancy measurements have been performed all over the world to ascertain the true behaviour of the allocated spectrum. In this paper, a spectrum occupancy measurement performed in Nigeria is presented. This has become necessary because spectrum occupancy measurement performed in a certain location cannot be extended to other locations. From the results obtained, it has been found there is ample spectrum available. Correlation analyses performed also indicate that spectrum occupancy depends on both time and location. This work will go a long way in the deployment of cognitive radio technology in Nigeria.
Health-state valuation using discrete choice models

The aim of this thesis was to investigate specific problems associated with preference-based measures (values) of health states and with the methodology used to derive health-state values. The first chapter covers the changes in phrasing and differences in measurement methods in the EQ-5D instrument after the five-level version was introduced alongside the conventional three-level version. Specifically, a head-to-head comparison of the values elicited from a large sample showed slight differences between the two versions. The study described in the second chapter was motivated by the fact that most instruments do not take into account the interactions of distinct health attributes (reduction in perceived health status may intensify if two different health problems interact). Our study revealed that the inclusion of interactions between various EQ-5D health aspects leads to different values for health states. The third chapter shows that people with experience of disease tend to value health states differently, or assign importance to certain health attributes differently than healthy respondents do. The fourth chapter presents a separate discrete choice study that we conducted to determine the importance of criteria regarding new medical treatments. We found four criteria to be important, based on preferences of the general population and patients: health gains, patient's age, patient's initial health condition, and cause of the disease. In the fifth chapter we present an eye-tracking study, which proved to support a basic assumption in health-state measurement: that respondents pay attention to all elements of the health state description and do not disregard information.
Global Structure Optimization of Quadrilateral Meshes

We introduce a fully automatic algorithm which optimizes the high‐level structure of a given quadrilateral mesh to achieve a coarser quadrangular base complex. Such a topological optimization is highly desirable, since state‐of‐the‐art quadrangulation techniques lead to meshes which have an appropriate singularity distribution and an anisotropic element alignment, but usually they are still far away from the high‐level structure which is typical for carefully designed meshes manually created by specialists and used e.g. in animation or simulation. In this paper we show that the quality of the high‐level structure is negatively affected by helical configurations within the quadrilateral mesh. Consequently we present an algorithm which detects helices and is able to remove most of them by applying a novel grid preserving simplification operator (GP‐operator) which is guaranteed to maintain an all‐quadrilateral mesh. Additionally it preserves the given singularity distribution and in particular does not introduce new singularities. For each helix we construct a directed graph in which cycles through the start vertex encode operations to remove the corresponding helix. Therefore a simple graph search algorithm can be performed iteratively to remove as many helices as possible and thus improve the high‐level structure in a greedy fashion. We demonstrate the usefulness of our automatic structure optimization technique by showing several examples with varying complexity.
Parameterisation of allometric equations for quantifying aboveground biomass of Norway spruce (Picea abies (L.) H. Karst.) in the Czech Republic

Čihák T. , Vejpustková M. (2018): Parameterisation of allometric equations for quantifying aboveground biomass of Norway spruce (Picea abies (L.) H. Karst. ) in the Czech Republic. J. For. Sci., 64: 108–117. The aim of the present study was to develop allometric equations for predicting aboveground biomass of Norway spruce (Picea abies (Linnaeus) H. Karsten) applicable to the typically managed spruce forest on acidic and nutrientmedium sites in the Czech Republic. The models were based on an extensive data set of 139 spruce trees collected in 25 stands on 15 sites. The biomass in dry mass was modelled using linear regression equations with one (diameter at breast height – D), two (D, slenderness ratio – H/D) or three (D, H/D, site index – SI, or tree age – A) predictors. The models were validated using the leave-one-out method. The value of the root mean square error of cross-validation was chosen as the main criterion for the best-model selection. Both the total aboveground biomass and stem biomass were best predicted by three-variable models (D, H/D, SI). For crown and foliage biomass the simple one-variable model (D) is recommended.
Small RNA studies in Drosophila melanogaster, Stylophora pistillata and Symbiodinium sp.

Small non-coding RNAs such as microRNAs (miRNAs), small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs) play a big role in regulating gene expression in cells. In my work, I focus primarily on miRNAs, which represses the expression of the mRNA targets post-transcriptionally. For Drosophila melanogaster, I predicted the tissue-specific expression of several miRNAs based on the expression levels of the predicted mRNA targets in those tissues. The computational predictions are then followed up by quantitative PCR validation of miRNA expression levels in dissected fly tissues. For Stylophora pistillata (a species of coral found in the Red Sea) and Symbiodinium sp. (a photosynthetic, symbiotic algae present in the coral cell), my collaborators and I strived to study the genome, transcriptome and proteome of both organisms. At present, there is another coral genome available — from Acropora digitifera — but the large evolutionary distance between both corals (about 240 million years apart) warrants in-depth study of our coral of interest. On the other hand, our Symbiodinium genome will be the first of its kind for any dinoflagellate. My role in the project was to investigate the small RNAome of both organisms via small RNAseq. As the presence of a thick cell wall in Symbiodinium sp. poses a unique challenge to RNA extraction, and compounded by the dearth of literature regarding RNA extraction from the dinoflagellate, we optimised a procedure that consistently produced high quality RNA for downstream sequencing. From our draft proteome, I showed that the RNA interference (RNAi) machinery is very likely to be present in both organisms. Based on our short RNAseq data, I predicted miRNAs in both organisms. Two of the predicted miRNAs in S. pistillata have been identified in other organisms, while all of the predicted miRNAs in Symbiodinium sp. were novel.
Anaemia in chronic kidney disease pregnancy

Aim To review the incidence and management of anaemia and outcomes in pregnancies in a cohort of Australian women with chronic kidney disease. Methods A retrospective audit of 63 pregnancies in 52 women with chronic kidney disease. Results Sixty-eight percent of chronic kidney disease pregnancies were complicated by haemoglobin less than 100 g/L. Iron stores were measured in only 62% of all pregnancies. Serum ferritin was less than 100 ng/ml in 95% of those tested. Erythropoietin-stimulating agents were used in 24 pregnancies (38%). Intravenous iron was used in only nine non-dialysis pregnancies. Conclusion Greater awareness of the importance of regular measurement of iron stores and appropriate levels for repletion in chronic kidney disease pregnancies amongst health professionals involved in obstetric care may result in earlier detection and treatment of iron deficiency, and potentially improve maternal and fetal outcomes.
Multi-Branch Convolutional Macaron net for Sound Event Detection

Sound Event Detection remains a challenging task due to the lack of strongly labeled data. While the use of weakly labeled and unlabeled data can alleviate this issue, most state-of-the-art (SOTA) utilized the Mean-Teacher approach, which requires training two identical models in a semi-supervised manner. Such methodology can have two critical limitations. Firstly, it can be computationally expensive if a very deep model is designed. Secondly, a model designed might only be optimal for either audio tagging or frame-level prediction but not both. Thus, using the Mean-Teacher approach may only allow a model to perform at its maximum potential for one of the tasks. However, the aforementioned issues can be circumvented by designing two different models where the less complex model provides the frame-level prediction while the more complex model provides the audio tags. To increase the accuracy of the models, we propose the use of Squeeze and Excite, meta-ACON, an improved Transformer encoding layer, a triple instance-level pooling approach (i.e., multi-branch pooling), and an improved cyclic learning scheme. Based on such a framework, the best system can achieve an event-based F1-score of 48.5%. By ensembling the top 5 models, the event-based F1-score increases to 50.4%. The proposed framework can achieve a minimum margin of over 12% against the baseline system while being competitive with the other SOTA.
HAND HYGIENE KNOWLEDGE AND PRACTICE AMONG MEDICAL STUDENTS IN KING ABDULAZIZ UNIVERSITY HOSPITAL.

Salma H. Almadani 1 , Yara A. Kano 1 , Lama A. Rayyis 1 , Weaam S. Magram 1 , Alaa A. Ismail 1 and Dr. Eman K. Aldigs 2 . 1. College of Medicine, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. 2. Assistant Professor, Department of Medical Microbiology, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. Manuscript Info Abstract . Manuscript History
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

Membership Inference Attacks (MIA) aim to infer whether a target data record has been utilized for model training or not. Prior attempts have quantified the privacy risks of language models (LMs) via MIAs, but there is still no consensus on whether existing MIA algorithms can cause remarkable privacy leakage on practical Large Language Models (LLMs). Existing MIAs designed for LMs can be classified into two categories: reference-free and reference-based attacks. They are both based on the hypothesis that training records consistently strike a higher probability of being sampled. Nevertheless, this hypothesis heavily relies on the overfitting of target models, which will be mitigated by multiple regularization methods and the generalization of LLMs. The reference-based attack seems to achieve promising effectiveness in LLMs, which measures a more reliable membership signal by comparing the probability discrepancy between the target model and the reference model. However, the performance of reference-based attack is highly dependent on a reference dataset that closely resembles the training dataset, which is usually inaccessible in the practical scenario. Overall, existing MIAs are unable to effectively unveil privacy leakage over practical fine-tuned LLMs that are overfitting-free and private. We propose a Membership Inference Attack based on Self-calibrated Probabilistic Variation (SPV-MIA). Specifically, since memorization in LLMs is inevitable during the training process and occurs before overfitting, we introduce a more reliable membership signal, probabilistic variation, which is based on memorization rather than overfitting. Furthermore, we introduce a self-prompt approach, which constructs the dataset to fine-tune the reference model by prompting the target LLM itself. In this manner, the adversary can collect a dataset with a similar distribution from public APIs.
Stance-Aware Re-Ranking for Non-factual Comparative Queries

We propose a re-ranking approach to improve the retrieval effectiveness for non-factual comparative queries like ‘Which city is better, London or Paris? ’ based on whether the results express a stance towards the comparison objects (London vs. Paris) or not. Applied to the 26 runs submitted to the Touché 2022 task on comparative argument retrieval, our stance-aware re-ranking significantly improves the retrieval effectiveness for all runs when perfect oracle-style stance labels are available. With our most effective practical stance detector based on GPT-3.5 (F₁ of 0.49 on four stance classes), our re-ranking still improves the effectiveness for all runs but only six improvements are significant. Artificially “deteriorating” the oracle-style labels, we further find that an F₁ of 0.90 for stance detection is necessary to significantly improve the retrieval effectiveness for the best run via stance-aware re-ranking.
The School Social Work Skill Set and Positive Behavior Support: A Good Match

I n many states, implementation of the broad framework of positive behavior support (PBS) or positive behavior intervention support (PBIS) has become a priority for school districts and state departments of education. With the recognition in the literature that school climate affects academics (Bandypadhyay, Cornell, & Konoid, 2009; Dupper & Meyer-Adams, 2002; Stewart, 2008) and school attendance (Bandypadhyay et al., 2009; Nelson, Martella, & Marchand-Martella, 2002), in addition to the encouragement in legislation (Individuals with Disabilities Education Improvement Act of 2004 [P.L. 108-446]) to adopt a response to intervention (Rtl) approach that no longer waits for students to fail before intervening, schools have found that PBIS provides a comprehensive model for implementation of a continuum of interventions that result in better outcomes for students (Fairbanks, Simonsen, & Sugai, 2008; Frey Lingo, & Nelson, 2008; Todd, Campbell, Meyer, & Horner, 2008). Frey et al. (2008) note, that "PBS is not an 'intervention,' and it does not replace what school social workers do in schools. Instead it is a set of problem-solving strategies and processes that can be used to build upon existing strengths" (p. 5). Although both PBIS and Rtl are represented by a three-tiered triangle (a continuum of schoolwide, small-group, and individual services), Rtl represents the broader concept that addresses both academics and behavior (tier 1 universal supports, tier 2 targeted group intervention, tier 3 intensive individual interventions), whereas PBIS provides a model for the continuum of services (primary, secondary, tertiary) that can be provided to address behavior. However, PBIS is not a manualized program, but a framework for the delivery of prevention and intervention services. Efforts to train school personnel in PBIS begin with schoolwide PBIS (SWPBS) (for more information,go to http://www.pbis.org/). Although a recent national survey indicated that school social workers completing the survey spent a limited amount of time involved in schoolwide interventions (Kelly et al., 2010), it is hoped that school social workers are taking advantage of this opportunity to be trained and involved in implementation of SWPBS, which provides the foundation for secondary and tertiary interventions. This column does not address the primary prevention (PBIS) or tier 1 Rtl in the continuum of services, but, rather, the secondary prevention PBIS/tier 2 Rtl and the tertiary prevention PBIS/tier 3 Rtl.
The costs of asthma.

At present, asthma represents a substantial burden on health care resources in all countries so far studied. The costs of asthma are largely due to uncontrolled disease, and are likely to rise as its prevalence and severity increase. Costs could be significantly reduced if disease control is improved. A large proportion of the total cost of illness is derived from treating the consequences of poor asthma control-direct costs, such as emergency room use and hospitalizations. Indirect costs, which include time off work or school and early retirement, are incurred when the disease is not fully controlled and becomes severe enough to have an effect on daily life. In addition, quality of life assessments show that asthma has a significant socioeconomic impact, not only on the patients themselves, but on the whole family. Underuse of prescribed therapy, which includes poor compliance, significantly contributes towards the poor control of asthma. The consequences of poor compliance in asthma include increased morbidity and sometimes mortality, and increased health care expenditure. To improve asthma management, international guidelines have been introduced which recommend an increase in the use of prophylactic therapy. The resulting improvements in the control of asthma will reduce the number of hospitalizations associated with asthma, and may ultimately produce a shift within direct costs, with subsequent reductions in indirect costs. In addition, costs may be reduced by improving therapeutic interventions and through effective patient education programmes. This paper reviews current literature on the costs of asthma to assess how effectively money is spent and, by estimating the proportion of the cost attributable to uncontrolled disease, will identify where financial savings might be made.