Miracle-dz/UniFAR-FTUs huggingface dataset:
The focal concerns of sentencing and mandatory sentencing laws: circumvention in the context of mandatory probation and treatment

This study examines courtroom actors' motivations for circumventing Kansas' Senate Bill 123, which created a mandatory probation/treatment sentence for felony drug possession. Building on the focal concerns perspective, the study explores whether the focal concerns traditionally expressed in sentencing decisions – defendant blameworthiness and dangerousness – applied in the context of a mandatory probation/treatment law. Relying on a qualitative approach, involving semi-structured interviews with 60 judges, prosecutors, and public defenders from across Kansas, we find that courtroom actors expressed little outward concern for traditional focal concerns of defendant blameworthiness or dangerousness in circumventing the mandatory probation/treatment law. The more prevalent motivations for circumvention focused on concerns regarding offenders' treatment need/amenability and the efficacy of supervision/treatment regimes. We argue that the orientation of the law – focused on increasing access to treatment and reducing substance abuse – triggered a shift in the focal concerns of sentencing away from concerns over blameworthiness/dangerousness and toward concerns over treatment need/amenability.
The Robustness and Design of Constrained Cross-Directional Control Via Integral Quadratic Constraints

A robust stability test for a class of constrained cross-directional controllers is found. Under special circumstances, the stability test is executed on a mode-by-mode basis and greatly simplified to a frequency-domain criterion. The test is also exploited to develop tuning algorithms. The control system involves a quadratic program embedded within an internal model control antiwindup structure and achieves optimal steady-state performance when the plant is known. Both the nonlinearity in the controller and the plant uncertainty satisfy certain integral quadratic inequalities. This allows us to obtain conditions for robust stability that can be expressed as linear matrix inequalities via the Kalman-Yakubovich-Popov lemma.
Semantic role labeling using lexicalized tree adjoining grammars

The predicate-argument structure (PAS) of a natural language sentence is a useful representation that can be used for a deeper analysis of the underlying meaning of the sentence or directly used in various natural language processing (NLP) applications. The task of semantic role labeling (SRL) is to identify the predicate-argument structures and label the relations between the predicate and each of its arguments. Researchers have been studying SRL as a machine learning problem in the past six years, after large-scale semantically annotated corpora such as FrameNet and PropBank were released to the research community. Lexicalized Tree Adjoining Grammars (LTAGs), a tree rewriting formalism, are often a convenient representation for capturing locality of predicate-argument relations. Our work in this thesis is focused on the development and learning of the state of the art discriminative SRL systems with LTAGs. Our contributions to this field include: We apply to the SRL task a variant of the LTAG formalism called LTAG-spinal and the associated LTAG-spinal Treebank (the formalism and the Treebank were created by Libin Shen). Predicate-argument relations that are either implicit or absent from the original Penn Treebank are made explicit and accessible in the LTAG-spinal Treebank, which we show to be a useful resource for SRL. We propose the use of the LTAGs as an important additional source of features for the SRL task. Our experiments show that, compared with the best-known set of features that are used in state of the art SRL systems, LTAG-based features can improve SRL performance significantly. We treat multiple LTAG derivation trees as latent features for SRL and introduce a novel learning framework – Latent Support Vector Machines (LSVMs) to the SRL task using these latent features. This method significantly outperforms state of the art SRL
Soft-switching Z-source inverters with coupled inductor

This paper presents a new resonant soft-switching quasi-Z-source inverter. On the basis of the quasi-Z-source inverter, the proposed inverter inherits the features of high voltage boost ability, circuit simplicity and high reliability. A resonant network with coupled inductor is employed to achieve the soft-switching scheme. All active devices (switches and diodes) in the inverter are tuned on and off under zero voltage or zero-current switching condition. The principle of the proposed converter and analysis of operation are proposed. Simulation and experimental results are given to illustrate the soft-switching characteristics. The theoretical analysis and simulation agrees well with experimental results.
PET performance and MRI compatibility evaluation of a digital, ToF-capable PET/MRI insert equipped with clinical scintillators

We evaluate the MR compatibility of the Hyperion-IID positron emission tomography (PET) insert, which allows simultaneous operation in a clinical magnetic resonance imaging (MRI) scanner. In contrast to previous investigations, this work aims at the evaluation of a clinical crystal configuration. An imaging-capable demonstrator with an axial field-of-view of 32 mm and a crystal-to-crystal spacing of 217.6 mm was equipped with LYSO scintillators with a pitch of 4 mm which were read out in a one-to-one coupling scheme by sensor tiles composed of digital silicon photomultipliers from Philips Digital Photon Counting (DPC 3200-22). The PET performance degradation (energy resolution and coincidence resolution time (CRT)) was evaluated during simultaneous operation of the MRI scanner. We used clinically motivated imaging sequences as well as synthetic gradient stress test sequences. Without activity of the MRI scanner, we measured for trigger scheme 1 (first photon trigger) an energy resolution of 11.4% and a CRT of 213 ps for a narrow energy (NE) window using five 22Na point-like sources. When applying the synthetic gradient sequences, we found worst-case relative degradations of the energy resolution by 5.1% and of the CRT by 33.9%. After identifying the origin of the degradations and implementing a fix to the read-out hardware, the same evaluation revealed no degradation of the PET performance anymore even when the most demanding gradient stress tests were applied. The PET performance of the insert was initially evaluated using the point sources, a high-activity phantom and hot-rod phantoms in order to assess the spatial resolution. Trigger schemes 2–4 delivered an energy resolution of 11.4% as well and CRTs of 279 ps, 333 ps and 557 ps for the NE window, respectively. An isocenter sensitivity of 0.41% using the NE window and 0.71% with a wide energy window was measured. Using a hot-rod phantom, a spatial resolution in the order of 2 mm was demonstrated and the benefit of time-of-flight PET was shown with a larger rabbit-sized phantom. In conclusion, the Hyperion architecture is an interesting platform for clinically driven hybrid PET/MRI systems.
An Efficient Method for Maintaining Diversity in Evolutionary Multi-objective Optimization

Diversity maintenance of solutions is a crucial part in multi-objective optimization. In this paper, a maintenance method which is based on minimum spanning tree is proposed. The proposed method defines a density estimation metric - minimum spanning tree crowding distance (MSTCD). Moreover, information of degree of solution combined with MSTCD is employed to truncate population. From an extensive comparative study with three other methods on a number of two and three objective test problems, it is observed that the proposed algorithm has good performance in distribution.
The Politics of Age, Temporality and Intergenerationality in Transnational Lesbian, Gay, Bisexual, Transgender and Queer Activist Networks

Age, temporality and intergenerationality have often been neglected in debates on intersectionality within sexuality studies. This article contributes towards these debates by examining how age and generation operate within transnational activism around LGBTQ (lesbian, gay, bisexual, transgender and queer politics) in Poland. Drawing on interviews with activists in Poland, Germany, Belgium, the Netherlands and the UK, this article examines age and generation as significant aspects of activists’ positioning with regard to each other and to archives of political experiences and discursive repertoires. The article argues that age and generation matter on the level of personal inter-subjectivity and are frequently rationalised by recourse to different national and local narratives of LGBTQ movement histories.
Structural Data Recognition With Graph Model Boosting

This paper presents a novel method for structural data recognition using a large number of graph models. In general, prevalent methods for structural data recognition have two shortcomings: 1) only a single model is used to capture structural variation and 2) naive classifiers are used, such as the nearest neighbor method. In this paper, we propose strengthening the recognition performance of these models as well as their ability to capture structural variation. The main contribution of this paper is a novel approach to structural data recognition: graph model boosting. We construct a large number of graph models and train a strong classifier using the models in a boosting framework. Comprehensive structural variation is captured with a large number of graph models. Consequently, we can perform structural data recognition with powerful recognition capability in the face of comprehensive structural variation. The experiments using IAM graph database repository show that the proposed method achieves impressive results and outperforms existing methods.
Optimizing microarray in experimental hypertension.

BACKGROUND Genetic noise between outbred animals can potentially be a major confounder in the use of microarray technology for gene expression profiling. The study of paired organs from the same animal offers an alternative approach (e.g., for studies of the kidney in experimental hypertension). The present study was undertaken to determine the level of genetic noise between outbred adult Sprague-Dawley (SD) rats, and to determine the effects of unilateral nephrectomy on changes in gene expression as a basis for the design of microarray studies in experimental hypertension. METHODS Male SD rats (approximately 130 g) were acclimatized before measurement of tail-cuff systolic blood pressure (SBP) for 6 control days and 4 days of saline treatment. Left kidney nephrectomy was performed, and the tissue snap-frozen in liquid nitrogen for subsequent RNA extraction. Two weeks later, SBP was measured over 4 control and 8 saline treatment days, and the remaining right kidney removed and frozen. Total RNA purification, preparation of cRNA, hybridization, and scanning of the Rat U34A Affymetrix arrays were performed, and data analyzed using MAS5 software Affymetrix Suite (v5), Bioconductor, as well as statistical methods motivated by relevant simulations. RESULTS Gene expression profiles in the left control kidney were extremely consistent across animals. The expression profiles of pairs of kidneys from the same animal were, however, more similar than those of kidneys from different animals. Nephrectomy had little effect on the gene expression profiles in the time frame examined. CONCLUSION Despite the outbred nature of the rats used in this study, they are useful for gene expression profiling comparisons. The use of paired organs from an individual animal ensures even further genetic identity, allowing determination of genes modified by the treatment of interest.
Upper Body Human Detection and Segmentation in Low Contrast Video

In the application of extracting human regions from videos, many existing methods may lose their efficacy when illumination varies or the human remains still. To address this problem, we propose a method in this paper for human region detection and segmentation by constructing a generalized human upper body model. The method mainly consists of two main procedures. First, foreground connected regions are extracted by background subtraction from the current frame and classified through a human upper body model pretrained with a support vector machine to determine whether they are human regions. Second, we assign an energy function to the region contour and apply an energy minimization procedure to evolve the contour when human regions are polluted by background; for example, a change in lighting conditions. After finding the optimal contour, we update the background and repeat the procedures in next frame. This feedback strategy rectifies the mistaken background regions promptly and extracts human regions correctly. Our experimental results demonstrate that the proposed method is robust enough to handle videos of low contrast as well as normal conditions.
Cognitive Behaviour Modification

The increasingly important role assigned to cognitive factors not only challanges the traditional tenets of behavior therapy but also augments and expands the highly specific procedures which have characterized the field in recent years. Self—instructional training, first used with hyperactive children to change maladaptive thinking processes, and stress inoculation training, used successfully with both clinical and highrisk non—clinical population to help them alter conceptualizations, employ coping skills, and successfully confront stressful situations, illustrate the possibilities of a broad-spectrum approach. The theoretical implications of increased interest in cognitive factors direct attention to the nature of the client—therapist interaction, mediation, the content of inner speech and the client's appraisal of outcome as active ingredients of the change process.
FIS based autonomous navigation system

This paper describes a Fuzzy Inference System (FIS) which finds an answer to the navigation problems of an autonomous unmanned vehicle. This autonomous unmanned vehicle is considered to be navigating in an unknown environment comprising of numerous static objects. The system consists of two Mamdani-FIS controllers. The first controller is a Multiple Input Single Output (MISO) system which is used by the autonomous vehicle to avoid collision with an obstacle. The second controller is also a MISO system, which is a path planning fuzzy controller, and it is used to reach the destination. The three inputs to the first controller are left, right and front sensor inputs of the autonomous vehicle in order to detect the obstacles. There are two inputs to the second controller, first one determines the error between the desired orientation and the current orientation of the autonomous vehicle and second is the linear velocity of the autonomous vehicle. This linear velocity is predefined. The output of both the controllers are the angular velocities, which are added after being multiplied by predefined weights to give the final angular velocity of the vehicle. MATLAB software package was used for simulation experiments for three different scenarios namely; a cluttered obstacle environment, a long walled obstacle environment and random obstacle shapes environment in order to scrutinize the feasibility of the proposed FIS technique. The simulation results conveyed that FIS can perform the navigation and path planning tasks safely and efficiently in an environment with randomly distributed static objects. The results when compared with other approaches like neural-networks, ANFIS, Genetic algorithm and other techniques in terms of the computational time and ease of implementation were much more efficient found to be giving an error with acceptable tolerance.
N-terminus of hMLH 1 confers interaction of hMutL a and hMutL b with hMutS a

Mismatch repair is a highly conserved system that ensures replication ®delity by repairing mispairs after DNA synthesis. In humans, the two protein heterodimers hMutSa (hMSH2-hMSH6) and hMutLa (hMLH1-hPMS2) constitute the centre of the repair reaction. After recognising a DNA replication error, hMutSa recruits hMutLa, which then is thought to transduce the repair signal to the excision machinery. We have expressed an ATPase mutant of hMutLa as well as its individual subunits hMLH1 and hPMS2 and fragments of hMLH1, followed by examination of their interaction properties with hMutSa using a novel interaction assay. We show that, although the interaction requires ATP, hMutLa does not need to hydrolyse this nucleotide to join hMutSa on DNA, suggesting that ATP hydrolysis by hMutLa happens downstream of complex formation. The analysis of the individual subunits of hMutLa demonstrated that the hMutSa±hMutLa interaction is predominantly conferred by hMLH1. Further experiments revealed that only the N-terminus of hMLH1 confers this interaction. In contrast, only the C-terminus stabilised and co-immunoprecipitated hPMS2 when both proteins were co-expressed in 293T cells, indicating that dimerisation and stabilisation are mediated by the C-terminal part of hMLH1. We also examined another human homologue of bacterial MutL, hMutLb (hMLH1±hPMS1). We show that hMutLb interacts as ef®ciently with hMutSa as hMutLa, and that it predominantly binds to hMutSa via hMLH1 as well.
Exploring Proteins in Anopheles gambiae Male and Female Antennae through MALDI Mass Spectrometry Profiling

MALDI profiling and imaging mass spectrometry (IMS) are novel techniques for direct analysis of peptides and small proteins in biological tissues. In this work we applied them to the study of Anopheles gambiae antennae, with the aim of analysing expression of soluble proteins involved in olfaction perireceptor events. MALDI spectra obtained by direct profiling on single antennae and by the analysis of extracts, showed similar profiles, although spectra obtained through profiling had a richer ion population and higher signal to noise ratio. Male and female antennae showed distinct protein profiles. MALDI imaging experiments were also performed and differences were observed in the localization of some proteins. Two proteins were identified through high resolution measurement and top-down MS/MS experiments. A 8 kDa protein only present in the male antennae matched with an unannotated sequence of the An. gambiae genome, while the presence of odorant binding protein 9 (OBP-9) was confirmed through experiments of 2-DE, followed by MS and MS/MS analysis of digested spots. This work shows that MALDI MS profiling is a technique suitable for the analysis of proteins of small and medium MW in insect appendices, and allows obtaining data for several specimens which can be investigated for differences between groups. Proteins of interest can be identified through other complementary MS approaches.
Uses of Meta‐Analysis in Criminal Justice Research: A Quantitative Review

Meta‐analysis has been adopted in many scientific fields for synthesizing large bodies of research, for evidence‐based development of practical policies, and for empirical resolution of difficult questions. It provides a rigorous, objective, and quantitative strategy to make effective use of an existing body of research, even when the results seem inconsistent and inconclusive. This paper reviews usage of meta‐analysis in research on criminal justice‐related issues and problems over the past three decades, identifying 176 studies published between 1976 and 2006 using meta‐analysis methods on criminal justice topics. Characteristics of these 176 studies are coded and analyzed to identify trends in the use of meta‐analysis by criminal justice researchers, as well as to summarize distinctive variations in how it has been used. A comparison of criminal justice with meta‐analysis usage in other social and applied science fields suggests some hesitation in adopting the methodology.
Kernel Designs for Efficient Multiresolution Edge Detection and Orientation Estimation

Deals with the design of filter kernels having specified radial and angular frequency responses based on combined optimization and frequency sampling. This is used to generate small-radius, low-pass, and edge-detection kernels for multiresolution pyramids. The performance of the new kernels in estimating orientation is shown to be significantly better than that of other commonly used pyramid kernels. >
Case studies on variation tolerant and low power design using planar asymmetric double gate transistor

In nanometer technologies, low power and process variation control have emerged as the first order design goal after high performance. Short channel effects (SCEs) deteriorate the MOSFET performance and lead to higher leakage power. Process variations cause high variability in power consumption and performance of an IC which affects the overall yield. Double gate devices suppress SCEs and are potential candidates for replacing Bulk technology in nanometer nodes. Threshold voltage control in planar asymmetric double gate transistor (IGFET) using a fourth terminal provides an effective means of combating process variations and low power design. In this paper, we analyze the suitability of IGFET for variation control and low power design. We present extensive comparison between IGFET and Bulk for reducing variability, improving yield and leakage power reduction using threshold voltage modulation. BSIM-IMG models were used for IGFET based simulations. Experimental results show that IGFET is highly suitable for adaptive applications and performs better than Bulk while substantially reducing leakage power.
Space Takes Time: Concentration Dependent Output Codes from Primary Olfactory Networks Rapidly Provide Additional Information at Defined Discrimination Thresholds

As odor concentration increases, primary olfactory network representations expand in spatial distribution, temporal complexity and duration. However, the direct relationship between concentration dependent odor representations and the psychophysical thresholds of detection and discrimination is poorly understood. This relationship is absolutely critical as thresholds signify transition points whereby representations become meaningful to the organism. Here, we matched stimulus protocols for psychophysical assays and intracellular recordings of antennal lobe (AL) projection neurons (PNs) in the moth Manduca sexta to directly compare psychophysical thresholds and the output representations they elicit. We first behaviorally identified odor detection and discrimination thresholds across an odor dilution series for a panel of structurally similar odors. We then characterized spatiotemporal spiking patterns across a population of individually filled and identified AL PNs in response to those odors at concentrations below, at, and above identified thresholds. Using spatial and spatiotemporal based analyses we observed that each stimulus produced unique representations, even at sub-threshold concentrations. Mean response latency did not decrease and the percent glomerular activation did not increase with concentration until undiluted odor. Furthermore, correlations between spatial patterns for odor decreased, but only significantly with undiluted odor. Using time-integrated Euclidean distance (ED) measures, we determined that added spatiotemporal information was present at the discrimination but not detection threshold. This added information was evidenced by an increase in integrated distance between the sub-detection and discrimination threshold concentrations (of the same odor) that was not present in comparison of the sub-detection and detection threshold. After consideration of delays for information to reach the AL we find that it takes ~120–140 ms for the AL to output identity information. Overall, these results demonstrate that as odor concentration increases, added information about odor identity is embedded in the spatiotemporal representation at the discrimination threshold.