Miracle-dz/UniFAR-FTUs huggingface dataset:
Reflections on Juvenile Justice Reform in New York. Keynote address delivered at the Diane Abbey Law Center for Children and Families conference in New York, NY Law School.

ABOUT THE AUTHOR: President, John Jay College of Criminal Justice, the City University of New York; Chair, Governor’s Task Force on Transforming Juvenile Justice, 2008–09. I wish to thank the Diane Abbey Law Center for Children and Families at New York Law School for the invitation to speak at the Juvenile Justice Reform in New York symposium. In particular, I extend my personal thanks to Diane Abbey for her vision in creating this center, which has, in its short life, under the leadership of Professor Carlin Meyer, already become a vibrant forum for discussion of issues facing children and families in New York City. This symposium is a perfect example of how a high-quality academic institution, grounded in the issues affecting New York City and supported by civic leaders such as Diane Abbey, can advance new ideas and promote more thoughtful policies on pressing issues. I also extend thanks to my many friends and colleagues who worked with me on the Governor’s Task Force on Transforming Juvenile Justice. We should be proud of the continuing impact of our Task Force report. It is very gratifying to know that, in a modest way, our work has contributed to a larger movement here in New York, one that is indeed “transforming juvenile justice. ”
Key technologies of digital-current-controlled Bidirectional DC-DC converter in the hybrid electric vehicle

This paper focus on the most important aspects of the bi-directional DC-DC converter in the hybrid electric vehicle(HEV) for the project applications.The different operating modes of converter are introduced under all HEV's work condition.Based on summarization, the demerits including low efficiency at light load and the uncontrolled discontinuous current when charging for the battery are derivated. Through theoretical and mathematical analysis, A new algorithm of average current controlling and digital control method in discontinuous synchronous rectifier mode with a single current sensor resistance have been proposed to realize the multi-mode bi-directional DC-DC converter. At the same time, the 800 W prototype using proposed technology is implemented for 48 V HEV application in order to verify the operational principles and advantages that improve synchronous rectifier inverse-boost converter light load efficiency. Effectiveness and feasibility of the new proposed control method is verified by experiments.So it can be applied to hybrid electric vehicle drive system.
Muramidase Activity of Kidney and Spleen in Swiss Mice Challenged with B.C.G., Zymosan and Bacterial Endotoxins.∗

Summary Elevation of muramidase activity occurs in the spleens and kidneys of normal mice treated with RES stimulators such as BCG infection, zymosan and bacterial endotoxins. This confirms that the increase in muramidase level in kidneys and spleens of tumor-bearing animals is not directly associated with tumor growth but is the result of stimulation of the RES.
e-SURAKSHAK: A Cyber-Physical Healthcare System with Service Oriented Architecture

In this paper we present the design of "e-SURAKSHAK," a novel cyber-physical health care management system of Wireless Embedded Internet Devices (WEIDs) that sense vital health parameters. The system is capable of sensing body temperature, heart rate, oxygen saturation level and also allows noninvasive blood pressure (NIBP) measurement. End to end internet connectivity is provided by using 6LoWPAN based wireless network that uses the 802.15. 4 radio. A service oriented architecture (SOA) [1] is implemented to extract meaningful information and present it in an easy-to-understand form to the end-user instead of raw data made available by sensors. A central electronic database and health care management software are developed. Vital health parameters are measured and stored periodically in the database. Further, support for real-time measurement of health parameters is provided through a web based GUI. The system has been implemented completely and demonstrated with multiple users and multiple WEIDs.
EXPOSURE TO AMBIENT AIR POLLUTION AND FETAL DEATH IN HARRIS COUNTY, TEXAS

This study is the first to use time-to-event analyses to examine stillbirth risk associated with prenatal ozone (O3) exposure. The study was conducted in a racially and ethnically diverse urban area (Harris County, Texas) with historic non-attainment O3 levels. We obtained birth and fetal death records from 2008-2013 and estimated weekly maternal residential O3 concentrations from conception until delivery using inverse distance interpolation from the local monitoring network. We used Cox survival models to examine associations between time-varying O3 exposure and stillbirth. We examined multi-pollutant models (with particulate matter ≤2.5 micrometers in aerodynamic diameter and nitrogen dioxide) and effect measure modification by race/ethnicity and length of gestation. We found a 9% (95% confidence interval (CI): 1%, 18%) increased stillbirth risk associated with a 3.61 parts per billion increase in O3 exposure. The risk was higher among women with pregnancies <37 gestational weeks (hazard ratio (HR) =1.13, 95% CI: 1.04, 1.23) as compared to women with pregnancies of longer gestation (HR=1.05, 95% CI: 0.87, 1.27) and among Hispanic women (HR=1.14, 95% CI: 1.02, 1.27). Our findings indicate that maternal O3 exposure is associated with stillbirth risk, and that Hispanic women and women with shorter pregnancies may be at
A CNSGA-II based method for multi-objective probabilistic transmission network expansion planning

This paper proposes a new method for probabilistic transmission network expansion planning with Controlled Non-dominated Sorting Genetic Algorithm (CNSGA-II) of multi-objective meta-heuristics (MOMH). Recently, power networks increase the degree of uncertainties due to new environment of power network liberations, the emergence of renewable energy, etc. As a result, the importance of improving power supply reliability has been recognized. In this paper, a new method is proposed for probabilistic transmission network expansion planning. The proposed method solves a multi-objective optimization problem that optimizes probabilistic reliability criterion EENS as well as the construction cost to obtain a set of the Pareto solutions in Monte Carlo Simulation (MCS). The effectiveness of the proposed method is successfully demonstrated on the IEEE 24-bus system.
Cloning and expression of beta,beta-carotene 15,15'-dioxygenase.

beta,beta-Carotene 15,15'-dioxygenase cleaves beta-carotene into two molecules of retinal and is therefore the key enzyme in beta-carotene metabolism to vitamin A. In the present study, it was possible to enrich the chicken beta,beta-carotene 15,15'-dioxygenase to such an extent that partial amino acid sequence information could be obtained to design degenerate oligonucleotides. With RT-PCR a cDNA fragment could be obtained and used subsequently in a radioactive screening of a chicken duodenal expression library. We cloned the first eukaryotic beta,beta-carotene 15,15'-dioxygenase which symmetrically cleaves beta-carotene at the 15,15'-double bond.
Genetic Deletion of Catalytic Subunits of AMP-activated Protein Kinase Increases Osteoclasts and Reduces Bone Mass in Young Adult Mice*

Background: AMPK is essential for cellular energy homeostasis and a therapeutic target for metabolic disorders. Results: Genetic deletion of catalytic subunits of AMPK reduces bone mass and AMPK negatively regulates osteoclastogenesis. Conclusion: AMPK is a critical regulator of bone homeostasis. Significance: Mechanistic elucidation of AMPK function in bone homeostasis has implications for bone health in therapeutic intervention of metabolic disorders. AMP-activated protein kinase (AMPK) is a key regulator of cellular and systemic energy homeostasis and a potential therapeutic target for the intervention of cancer and metabolic disorders. However, the role of AMPK in bone homeostasis remains incompletely understood. Here we assessed the skeletal phenotype of mice lacking catalytic subunits of AMPK and found that mice lacking AMPKα1 (Prkaa1−/−) or AMPKα2 (Prkaa2−/−) had reduced bone mass compared with the WT mice, although the reduction was less in Prkaa2−/− mice than in Prkaa1−/− mice. Static and dynamic bone histomorphometric analyses revealed that Prkaa1−/− mice had an elevated rate of bone remodeling because of increases in bone formation and resorption, whereas AMPKα2 KO-induced bone mass reduction was largely attributable to elevated bone resorption. In agreement with our in vivo results, AMPKα deficiency was associated with increased osteoclastogenesis in vitro. Moreover, we found that AMPKα1 inhibited the receptor activator of nuclear factor κB (RANK) signaling, providing an explanation for AMPK-mediated inhibition of osteoclastogenesis. Therefore, our findings further underscore the importance of AMPK in bone homeostasis, in particular osteoclastogenesis, in young adult mammals.
Test Case Selection: A Systematic Literature Review

Time and resource constraints should be taken into account in software testing activities, and thus optimizing the test suite is fundamental in the development process. In this context, the test case selection aims to eliminate redundant or unnecessary test data, which is crucial for the definition of test strategies. This paper presents a systematic review on the test case selection conducted through a selection of 449 articles published in leading journals and conferences in Computer Science. We addressed the state-of-art by collecting and comparing existing evidence on the methods used in the different software domains and the methods used to evaluate the test case selection. Our study identified 32 papers that met the research objectives, which featured 18 different selection methods and were evaluated through 71 case studies. The most commonly reported methods are adaptive random testing, genetic algorithms and greedy algorithm. Most approaches rely on heuristics, such as diversity of test cases and code or model coverage. This paper also discusses the key concepts and approaches, areas of application and evaluation metrics inherent to the methods of test case selection available in the literature.
Incidental Findings in Neuroimaging Research: A Framework for Anticipating the Next Frontier

While strategies for handling unusual and possibly clinically significant anatomical findings on brain scans of research volunteers have been developed and implemented across neuroimaging laboratories worldwide, few concrete steps have been taken to consider the next frontier: Functional anomalies. Drawing on the genetics literature, early work in neuroimaging considered actionability to be a driving force for determining if and when findings should be disclosed to individuals in whom they are detected, as inherent uncertainty raises potential ethical dilemmas of misdiagnosing and mislabelling people as patients. Here we consider the possibility of incidental findings in brain function during the resting state. Our approach does not anchor the resting state as the sine qua non of functional incidental findings, but as a path to thinking about where they may emerge in the future and how our professional communities need to think about thinking about them. We suggest that considering the issues proactively today, within a framework that is maximally flexible and open to modification, is better than responding reactively after the fact and with no framework at all. We argue that there is a duty to consider possible incidental findings despite the ambiguities of data interpretation, while working hard to prevent unnecessary alarm.
Long-term drift compensation algorithms based on the kernel-orthogonal signal correction in electronic nose systems

In order to compensate the drift of the performance of gas sensors in recognition, the kernel-orthogonal signal correction algorithm (K-OSC) is proposed. In the K-OSC, the feature space is mapped into a higher dimension space by using the kernel principal component analysis (KPCA) at first. Then the orthogonal signal correction (OSC) is used to remove undesired components which do not correlate to the label from the feature vector. The feature vector processed by the K-OSC can improve the accuracy of pattern recognition tools, such as support vector machines (SVMs) or deep neural networks. The experimental results of K-OSC demonstrate that the K-OSC has a better performance than other methods considered over a longer interval time between training samples and test samples.
Fast active noise control for robust speech acquisition

: Active noise control (ANC) can be a valuable resort for robust speech acquisition. Furthermore, this technique can have the added benefit of minimising the Lombard effect. In the context of broadband active noise cancellation, the adaptive algorithm most widely used is the well-known Filtered-x Least Mean Squares (FxLMS). In the present work we study an alternative to FxLMS algorithm that tries to overcome its sometimes slow convergence without loss of cancellation capability. The alternative presented here is the ALE + FxLMS system, where an Adaptive Line Enhancer (ALE) is used as decorrelating stage for the FxLMS algorithm. The single-channel case (one reference signal, one actuator and one error sensor) and three different extensions of the system to the multiple channel case are presented and evaluated. The proposed system has proven to be able to achieve faster convergence with reference to the single FxLMS, without decorrelating pre-processing.
Assessment of leptin and resistin levels in patients with chronic obstructive pulmonary disease.

INTRODUCTION Chronic obstructive pulmonary disease (COPD) is the most common chronic lung disease in the world. The increasing severity of inflammatory processes in the respiratory tract leads to exacerbation of COPD. This process may be associated with changes in the synthesis of adipokines, the peptides that participate in immune processes. OBJECTIVES The aim of this study was to identify more sensitive and specific laboratory markers useful in diagnosing inflammatory processes in patients with COPD. PATIENTS AND METHODS The study involved 33 patients with COPD without exacerbation. During the previous year, 1 episode of exacerbation was reported in 15 patients and no exacerbations were reported in the remaining 18 patients. Serum concentrations of adipokines were measured using an enzyme-linked immunosorbent assay (ELISA). RESULTS In patients with COPD, we observed a 2-fold increase in leptin levels compared with healthy controls (18.8 ±10.2 ng/ml vs. 9.06 ±4.33 ng/ml; P = 0.042). Mean resistin levels in these patients were also 2-fold higher than those in controls (8.24 ±4.18 ng/ml vs. 3.58 ±1.51 ng/ml, respectively; P = 0.027). Significant positive correlations between C-reactive protein (CRP) and leptin as well as CRP and resistin levels were observed in patients with COPD (r = 0.75 and r = 0.83, respectively; P <0.05). Moreover, a statistically significant negative correlation between the forced expiratory volume in 1 second (FEV1) and resistin was noted in this group (r = 0.62; P <0.05). There was no correlation between FEV1 and leptin levels either in patients with COPD or in healthy controls. CONCLUSIONS A significant increase in leptin and resistin levels in patients with COPD may suggest that these adipokines are involved in the inflammatory process underlying the disease.
The Roy Adaptation Model: A Theoretical Framework for Nurses Providing Care to Individuals With Anorexia Nervosa

Using a nursing theoretical framework to understand, elucidate, and propose nursing research is fundamental to knowledge development. This article presents the Roy Adaptation Model as a theoretical framework to better understand individuals with anorexia nervosa during acute treatment, and the role of nursing assessments and interventions in the promotion of weight restoration. Nursing assessments and interventions situated within the Roy Adaptation Model take into consideration how weight restoration does not occur in isolation but rather reflects an adaptive process within external and internal environments, and has the potential for more holistic care.
STRM: A sister tweet reinforcement process for modeling hashtag popularity

With social media platform such as Twitter becoming the de facto destination for users' views and opinions, it is of great importance to forecast an information outbreak. In Twitter, tweets are often annotated with hashtags to help its users to quickly extract their contents. The existing approaches for modeling the dynamics of tweet-messages are usually limited to individual or simple aggregates of tweets rather than the underlying hashtags. In this paper, we develop, STRM, a novel point process driven model that considers the effect of cross-tweet impact in hashtag popularity. STRM, by assuming hashtag to be a heterogeneous collection of tweet-chains. Through extensive experimentation, we find that our algorithm — STRM, shows consistent performance boosts with six diverse real datasets against several strong baselines. Moreover surprisingly, it also offers significant accuracy gains in popularity-prediction for individual tweets as compared with the existing paradigms.
Metabolite profiling analysis of Methylobacterium extorquens AM1 by comprehensive two‐dimensional gas chromatography coupled with time‐of‐flight mass spectrometry

Methylobacterium extorquens AM1 is a facultative methylotroph, which is a potential candidate to be used in commercial processes to convert simple one‐carbon compounds to a variety of multicarbon chemicals and products. To better understand C1 metabolism in M. extorquens AM1 at the systems level, metabolite profiling tools were developed and applied in this bacterium. Comprehensive two‐dimensional gas chromatography coupled with time‐of‐flight mass spectrometry (GC × GC‐TOFMS) was used to obtain metabolite profiles of M. extorquens AM1 (primarily organic acids) and to identify the metabolite differences between cells grown on methanol (C1 substrate) and succinate (multicarbon substrate). In this study, a list of compounds that included amino acids and major intermediates of central C1 and multicarbon metabolism were studied as target metabolites. For these, calibration curves were obtained for absolute quantification by spiking different amounts of standard mixtures to cell cultures. Parallel factor analysis (PARAFAC) was used for accurate peak quantification. Unknown chemical differences between cells grown on methanol and succinate were identified by applying Fisher ratio analysis at a selective mass channel (m/z 147). Thirty‐six compounds were discovered to be statistically differentially expressed between C1 and multicarbon metabolism. Among these, 13 were identified by matching to library mass spectra, and the rest were novel compounds that were not included in libraries. These differentially expressed compounds have provided clues to new pathways that are specifically linked to C1 metabolism. Biotechnol. Bioeng. 2008;99: 929–940. © 2007 Wiley Periodicals, Inc.
Modeling of scale‐down effects on the hydrodynamics of expanded bed adsorption columns

Expanded‐bed adsorption (EBA) is a technique for primary recovery of proteins starting from unclarified broths. This process combines centrifugation, concentration, filtration, and initial capturing of the proteins in a single step. An expanded bed (EB) is comparable to a packed bed in terms of separation performance but its hydrodynamics are that of a fluidized bed. Downstream process development involving EBA is normally carried out in small columns to minimize time and costs. Our purpose here is to characterize the hydrodynamics of expanded beds of different diameters, to develop scaling parameters that can be reliably used to predict separation efficiency of larger EBA columns. A hydrodynamic model has been developed which takes into account the radial liquid velocity profile in the column. The scale‐down effect can be characterized in terms of apparent axial dispersion, Daxl,app, and plate number, NEB, adapted for expanded bed. The model is in good agreement with experimental results obtained from 1‐ and 5‐cm column diameters with buffer solutions of different viscosities. The model and the experiments show an increase of apparent axial dispersion with an increase in column diameter. Furthermore, the apparent axial dispersion is affected by an increase in liquid velocity and viscos‐ ity. Supported by visual observations and predictions from the model, it was concluded that operating conditions (liquid viscosity and superficial velocity) resulting in a bed‐void fraction between 0.7 and 0.75 would provide the optimal separation efficiency in terms of NEB. © 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 81: 790–799, 2003.
A 3D sequence-independent representation of the protein data bank.

Here we address the following questions. How many structurally different entries are there in the Protein Data Bank (PDB)? How do the proteins populate the structural universe? To investigate these questions a structurally non-redundant set of representative entries was selected from the PDB. Construction of such a dataset is not trivial: (i) the considerable size of the PDB requires a large number of comparisons (there were more than 3250 structures of protein chains available in May 1994); (ii) the PDB is highly redundant, containing many structurally similar entries, not necessarily with significant sequence homology, and (iii) there is no clear-cut definition of structural similarity. The latter depend on the criteria and methods used. Here, we analyze structural similarity ignoring protein topology. To date, representative sets have been selected either by hand, by sequence comparison techniques which ignore the three-dimensional (3D) structures of the proteins or by using sequence comparisons followed by linear structural comparison (i.e. the topology, or the sequential order of the chains, is enforced in the structural comparison). Here we describe a 3D sequence-independent automated and efficient method to obtain a representative set of protein molecules from the PDB which contains all unique structures and which is structurally non-redundant. The method has two novel features. The first is the use of strictly structural criteria in the selection process without taking into account the sequence information. To this end we employ a fast structural comparison algorithm which requires on average approximately 2 s per pairwise comparison on a workstation. The second novel feature is the iterative application of a heuristic clustering algorithm that greatly reduces the number of comparisons required. We obtain a representative set of 220 chains with resolution better than 3.0 A, or 268 chains including lower resolution entries, NMR entries and models. The resulting set can serve as a basis for extensive structural classification and studies of 3D recurring motifs and of sequence-structure relationships. The clustering algorithm succeeds in classifying into the same structural family chains with no significant sequence homology, e.g. all the globins in one single group, all the trypsin-like serine proteases in another or all the immunoglobulin-like folds into a third. In addition, unexpected structural similarities of interest have been automatically detected between pairs of chains. A cluster analysis of the representative structures demonstrates the way the "structural universe' is populated.