Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of sleep deprivation and subsequent recovery sleep on cortisol in unmedicated depressed patients.

OBJECTIVE One night of sleep deprivation induces a transient improvement in about 60% of depressed patients. Since depression is associated with abnormalities of the hypothalamic-pituitary-adrenal (HPA) axis, the authors measured cortisol secretion before, during, and after therapeutic sleep deprivation for 1 night. METHOD Fifteen unmedicated depressed inpatients participated in a combined polysomnographic and endocrine study. Blood was sampled at 30-minute intervals during 3 consecutive nights before, during, and after sleep deprivation. Saliva samples were collected at 30-minute intervals during the daytime before and after the sleep deprivation night. RESULTS During the night of sleep deprivation, cortisol levels were significantly higher than at baseline. During the daytime, cortisol levels during the first half of the day were higher than at baseline in the patients who responded to sleep deprivation but not in the nonresponders. During recovery sleep, cortisol secretion returned to baseline values. CONCLUSIONS This study demonstrated a significant stimulatory effect of 1 night of sleep deprivation on the HPA axis in unmedicated depressed patients. The results suggest that the short-term effects of antidepressant treatments on the HPA axis may differ from their long-term effects. A higher cortisol level after sleep deprivation might transiently improve negative feedback to the hypothalamus or interact with other neurotransmitter systems, thus mediating or contributing to the clinical response. The fast return to baseline values coincides with the short clinical effect.
Towards a Selection Model for Software Engineering Tools in Small and Medium Enterprises (SMEs)

Software-developing small and medium enterprises (SMEs) usually make investments with little resources and under severe pressures imposed by competiveness and productivity needs. From the analysis of the characteristics of software-developing SMEs and changes affecting software engineering tools (SETs), we have suggested criteria to support the evaluation and selection of tools that best suit their needs. These criteria have been developed based on ISO/IEC 14102, adopting their guidance on the assessment and selection process. For purposes of their validation, we have applied such criteria to three SETs. We expect that these criteria will provide support to establishing a tool selection model.
An empirical model for the beams of radio pulsars

Motivated by recent results on the location of the radio emission in pulsar magnetospheres, we have developed a model which can account for the large diversity found in the average profile shapes of pulsars. At the centre of our model lies the idea that radio emission at a particular frequency arises from a wide range of altitudes above the surface of the star, and that it is confined to a region close to the last open field lines. We assert that the radial height range over which emission occurs is responsible for the complex average pulse shapes rather than the transverse (longitudinal) range proposed in most current models. By implementing an abrupt change in the height range to discriminate between young, short-period, highly energetic pulsars and their older counterparts, we obtain the observed transition between the simple and complex average pulse profiles observed in each group respectively. Monte Carlo simulations are used to demonstrate the match of our model to real observations.
RNA-directed gene editing specifically eradicates latent and prevents new HIV-1 infection

Significance For more than three decades since the discovery of HIV-1, AIDS remains a major public health problem affecting greater than 35.3 million people worldwide. Current antiretroviral therapy has failed to eradicate HIV-1, partly due to the persistence of viral reservoirs. RNA-guided HIV-1 genome cleavage by the Cas9 technology has shown promising efficacy in disrupting the HIV-1 genome in latently infected cells, suppressing viral gene expression and replication, and immunizing uninfected cells against HIV-1 infection. These properties may provide a viable path toward a permanent cure for AIDS, and provide a means to vaccinate against other pathogenic viruses. Given the ease and rapidity of Cas9/guide RNA development, personalized therapies for individual patients with HIV-1 variants can be developed instantly. AIDS remains incurable due to the permanent integration of HIV-1 into the host genome, imparting risk of viral reactivation even after antiretroviral therapy. New strategies are needed to ablate the viral genome from latently infected cells, because current methods are too inefficient and prone to adverse off-target effects. To eliminate the integrated HIV-1 genome, we used the Cas9/guide RNA (gRNA) system, in single and multiplex configurations. We identified highly specific targets within the HIV-1 LTR U3 region that were efficiently edited by Cas9/gRNA, inactivating viral gene expression and replication in latently infected microglial, promonocytic, and T cells. Cas9/gRNAs caused neither genotoxicity nor off-target editing to the host cells, and completely excised a 9,709-bp fragment of integrated proviral DNA that spanned from its 5′ to 3′ LTRs. Furthermore, the presence of multiplex gRNAs within Cas9-expressing cells prevented HIV-1 infection. Our results suggest that Cas9/gRNA can be engineered to provide a specific, efficacious prophylactic and therapeutic approach against AIDS.
CoHadoop++: A load balanced data co-location in Hadoop Distributed File System

Hadoop [4] is a popular distributed computing framework, widely used for business data analytics. While Hadoop performs parallel operations on large data sets, it does not co-locate related data by default. However, performance of log processing operations such as indexing, grouping joins and sessionization on Hadoop can be significantly improved if related logs are partitioned and processed as a group. In order to facilitate this, these partitions need to be placed on the same set of nodes in the cluster. To enable this, a grouping key can be used to identify the related logs. CoHadoop [1], an extension of Hadoop, uses this key to co-locate all those files which correspond to the same key. However, it selects the data nodes randomly for every new key. While doing so, the load introduced on every data node of the cluster is not considered. This leads to an imbalance in the cluster. In order to address this issue, a load balanced co-location algorithm is incorporated into CoHadoop and it is termed as CoHadoop++. It achieves load balance in the cluster through optimal selection of data nodes based their load. Experimental results on CoHadoop++ show that the data placement happens in a load balanced manner.
STRUCTURE-FROM-MOTION AND MULTIVIEW GEOMETRY FOR PANORAMIC CAMERA MODELS

We consider calibration and structure-from-motion tasks for a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of projection rays. This allows to describe most existing camera types (at least for those operating in the visible domain), including pinhole cameras, sensors with radial or more general distortions, and especially panoramic cameras (central or non-central). Generic algorithms for calibration and structure-from-motion tasks (absolute and relative orientation, 3D point triangulation) are outlined. The foundation for a multi-view geometry of non-central cameras is given, leading to the formulation of multi-view matching tensors, analogous to the essential matrix, trifocal and quadrifocal tensors of perspective cameras. Besides this, we also introduce a natural hierarchy of camera models: the most general model has unconstrained projection rays whereas the most constrained model dealt with here is the central one, where all rays pass through a single point.
High-Resolution Spherical Quantization of Sinusoidal Parameters

Sinusoidal coding is an often employed technique in low bit-rate audio coding. Therefore, methods for efficient quantization of sinusoidal parameters are of great importance. In this paper, we use high-resolution assumptions to derive analytical expressions for the optimal entropy-constrained unrestricted spherical quantizers for the amplitude, phase, and frequency parameters of the sinusoidal model. This is done both for the case of a single sinusoid, and for the more practically relevant case of multiple sinusoids distributed across multiple segments. To account for psychoacoustical effects of the auditory system, a perceptual distortion measure is used. The optimal quantizers minimize a high-resolution approximation of the expected perceptual distortion, while the corresponding quantization indices satisfy an entropy constraint. The quantizers turn out to be flexible and of low complexity, in the sense that they can be determined easily for varying bit rate requirements, without any sort of retraining or iterative procedures. In an objective comparison it is shown that for the squared error distortion measure, the rate-distortion performance of the proposed method is very close to that of the theoretically optimal entropy-constrained vector quantization. Furthermore, for the perceptual distortion measure, the proposed scheme is shown to objectively outperform an existing sinusoidal quantization scheme, where frequency quantization is done independently. Finally, a subjective listening test, in which the proposed scheme is compared to an existing state-of-the-art sinusoidal quantization scheme with fixed quantizers for all input signals, indicates that the proposed scheme leads to an average bit rate reduction of 20%, at the same subjective quality level as the existing scheme
Modulation of DNA damage tolerance in Escherichia coli recG and ruv strains by mutations affecting PriB, the ribosome and RNA polymerase

RecG is a DNA translocase that helps to maintain genomic integrity. Initial studies suggested a role in promoting recombination, a possibility consistent with synergism between recG and ruv null alleles and reinforced when the protein was shown to unwind Holliday junctions. In this article we describe novel suppressors of recG and show that the pathology seen without RecG is suppressed on reducing or eliminating PriB, a component of the PriA system for replisome assembly and replication restart. Suppression is conditional, depending on additional mutations that modify ribosomal subunit S6 or one of three subunits of RNA polymerase. The latter suppress phenotypes associated with deletion of priB, enabling the deletion to suppress recG. They include alleles likely to disrupt interactions with transcription anti‐terminator, NusA. Deleting priB has a different effect in ruv strains. It provokes abortive recombination and compromises DNA repair in a manner consistent with PriB being required to limit exposure of recombinogenic ssDNA. This synergism is reduced by the RNA polymerase mutations identified. Taken together, the results reveal that RecG curbs a potentially negative effect of proteins that direct replication fork assembly at sites removed from the normal origin, a facility needed to resolve conflicts between replication and transcription.
An Elementary Proof of the Existence and Uniqueness Theorem for the Navier-Stokes Equations

Here ν is the viscosity, p is the pressure, and f1, f2 are the components of an external forcing which may be time-dependent. As our setting is periodic, the functions u1, u2, ∇p, f1, and f2 are all periodic in x. For simplicity, we take the period to be one. The first existence and uniqueness theorems for weak solutions of (1) were proven by Leray ([Ler34]) in whole plane R. Later these results were extended by E. Hopf (see [Hop51]). In 1962, Ladyzenskaya proved existence and uniqueness results for strong solutions for general two-dimensional domains [Lad69]. V. Yudovich, C. Foias, R. Teman, P. Constantin, and others developed strong methods which provided deep insights into the dynamics described by (1) (see [Yud89, Tem79, Tem95, CF88]). The purpose of this paper is to present elementary proofs of three theorems. These theorems imply the existence and uniqueness of smooth solutions of (1) and shed some additional light on the dissipative character of the dynamics. We will also discuss what our techniques can give in the three-dimensional setting. In two-dimensions, it is useful to consider the vorticity ω(x1, x2, t) = ∂u1(x1,x2,t) ∂x2 − ∂u2(x1,x2,t) ∂x1 . The equation governing ω has the form ( see [CM93, DG95] )
A Study of the Implementation of Restorative Justice at a Public High School in Southern California

This thesis begins with an introduction and methodology that presents two major research questions: “Can restorative justice exist within a zero-tolerance framework,” and, “What are the challenges that stand in the way of implementing restorative justice ideologies fully at Glenside High School? ” The author provides an autobiographical statement to give context to his positionality within this research. A comprehensive literature review highlights a brief history of restorative justice, a description of the harmful effects of punitive discipline, and results from different communities that have implemented restorative justice. The three major respondents are introduced in order to provide context to their positionality within this research. The author presents his research findings based on qualitative field notes from site visits to a public, Southern California high school in addition to responses from interviews with teachers and a restorative justice expert. The author concludes by arguing for the implementation of restorative justice in a widespread manner in individual schools, in addition to comprehensive teacher training in preprofessional programs for prospective teachers and the need to shift from “teach to the test” ideologies to holistic student development pedagogies. A STUDY OF THE IMPLEMENTATION OF RESTORATIVE JUSTICE AT A PUBLIC HIGH SCHOOL IN SOUTHERN CALIFORNIA 3 Table of
Alteration of S‐adenosylhomocysteine levels affects lignin biosynthesis in switchgrass

Summary Methionine (Met) synthesized from aspartate is a fundamental amino acid needed to produce S‐adenosylmethionine (SAM) that is an important cofactor for the methylation of monolignols. As a competitive inhibitor of SAM‐dependent methylation, the effect of S‐adenosylhomocysteine (SAH) on lignin biosynthesis, however, is still largely unknown in plants. Expression levels of Cystathionine γ‐synthase (PvCGS) and S‐adenosylhomocysteine hydrolase 1 (PvSAHH1) were down‐regulated by RNAi technology, respectively, in switchgrass, a dual‐purpose forage and biofuel crop. The transgenic switchgrass lines were subjected to studying the impact of SAH on lignin biosynthesis. Our results showed that down‐regulation of PvCGS in switchgrass altered the accumulation of aspartate‐derived and aromatic amino acids, reduced the content of SAH, enhanced lignin biosynthesis and stunted plant growth. In contrast, down‐regulation of PvSAHH1 raised SAH levels in switchgrass, impaired the biosynthesis of both guaiacyl and syringyl lignins and therefore significantly increased saccharification efficiency of cell walls. This work indicates that SAH plays a crucial role in monolignol methylation in switchgrass. Genetic regulation of either PvCGS or PvSAHH1 expression in switchgrass can change intracellular SAH contents and SAM to SAH ratios and therefore affect lignin biosynthesis. Thus, our study suggests that genes involved in Met metabolism are of interest as new valuable targets for cell wall bioengineering in future.
Determinants of Residual Risk in Secondary Prevention Patients Treated With High- Versus Low-Dose Statin Therapy: The Treating to New Targets (TNT) Study

Background— Cardiovascular events occur among statin-treated patients, albeit at lower rates. Risk factors for this “residual risk” have not been studied comprehensively. We aimed to identify determinants of this risk above and beyond lipid-related risk factors. Methods and Results— A total of 9251 coronary patients with low-density lipoprotein cholesterol <130 mg/dL randomized to double-blind atorvastatin 10 or 80 mg/d in the Treating to New Targets (TNT) study had complete on-treatment 1-year lipid data. Median follow-up was 4.9 years. The primary end point was major cardiovascular events (n=729): coronary death, nonfatal myocardial infarction, resuscitation after cardiac arrest, or fatal or nonfatal stroke. Multivariable determinants of increased risk were older age (adjusted hazard ratio [aHR], 1.13 per 1 SD [8.8 years]; 95% confidence interval [CI], 1.04–1.23), increased body mass index (aHR, 1.09; 95% CI, 1.02–1.17 per 4.5 kg/m2), male sex (aHR, 1.33; 95% CI, 1.07–1.65), hypertension (aHR, 1.38; 95% CI, 1.17–1.63), diabetes mellitus (aHR, 1.33; 95% CI, 1.11–1.60), baseline apolipoprotein B (aHR, 1.19; 95% CI, 1.11–1.28 per 19 mg/dL), and blood urea nitrogen (aHR, 1.10; 95% CI, 1.03–1.17 per 4.9 mg/dL), in addition to current smoking, prior cardiovascular disease, and calcium channel blocker use. Determinants of decreased risk were high-dose statin (aHR, 0.82; 95% CI, 0.70–0.94), aspirin use (aHR, 0.67; 95% CI, 0.56–0.81), and baseline apolipoprotein A-I (aHR, 0.91; 95% CI, 0.84–0.99 per 25 mg/dL). On-treatment 1-year lipids or apolipoproteins were not additionally associated with risk in multivariable models. Known baseline variables performed moderately well in discriminating future cases from noncases (Harrell c index=0.679). Conclusions— Determinants of residual risk in statin-treated secondary prevention patients included lipid-related and nonlipid factors such as baseline apolipoproteins, increased body mass index, smoking, hypertension, and diabetes mellitus. A multifaceted prevention approach should be underscored to address this risk. Clinical Trial Registration— URL: http://clinicaltrials.gov. Unique identifier: NCT00327691.
Default Mode of Brain Function in Monkeys

Human neuroimaging has revealed a specific network of brain regions—the default-mode network (DMN)—that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment.
Cascade with varying activation probability model for influence maximization in social networks

Activation probability is a key parameter in information diffusion models and has been observed to be varying with history activations in many empirical studies. However, such phenomenon has not been incorporated in the diffusion models applied in Influence Maximization Problem. In this paper, we first conduct empirical analyses on the large scale dataset collected from a popular online social network to demonstrate the variation. Then we propose the Cascade with Varying Activation Probability (CVAP) model and validate its accuracy by extensive simulation experiments. Moreover, we prove the submodularity of CVAP model, which guarantees that greedy algorithm can achieve 1 - 1/e optimality when solving the influence maximization problem.
Occupational Choice, Human Capital, and Financial Constraints

We study the aggregate productivity effects of firm-level financial frictions. Credit constraints affect not only production decisions but also household-level schooling decisions. In turn, entrepreneurial schooling decisions impact firm-level productivities, whose cross-sectional distribution becomes endogenous. In anticipation of future constraints, entrepreneurs under-invest in schooling. Frictions lower aggregate productivity because talent is misallocated across occupations, and capital misallocated across firms. In addition, firm-level productivities are also lower due to distortions induced by the schooling responses. We find that these effects combined account for about 1/5 of the U.S.-India aggregate productivity difference. Requiring the model to match schooling differences significantly amplifies the impact of frictions, and the model accounts for 58% of the aggregate productivity difference.
Weakly Supervised Extraction of Computer Security Events from Twitter

Twitter contains a wealth of timely information, however staying on top of breaking events requires that an information analyst constantly scan many sources, leading to information overload. For example, a user might wish to be made aware whenever an infectious disease outbreak takes place, when a new smartphone is announced or when a distributed Denial of Service (DoS) attack might affect an organization's network connectivity. There are many possible event categories an analyst may wish to track, making it impossible to anticipate all those of interest in advance. We therefore propose a weakly supervised approach, in which extractors for new categories of events are easy to define and train, by specifying a small number of seed examples. We cast seed-based event extraction as a learning problem where only positive and unlabeled data is available. Rather than assuming unlabeled instances are negative, as is common in previous work, we propose a learning objective which regularizes the label distribution towards a user-provided expectation. Our approach greatly outperforms heuristic negatives, used in most previous work, in experiments on real-world data. Significant performance gains are also demonstrated over two novel and competitive baselines: semi-supervised EM and one-class support-vector machines. We investigate three security-related events breaking on Twitter: DoS attacks, data breaches and account hijacking. A demonstration of security events extracted by our system is available at: http://kb1.cse. ohio-state.edu:8123/events/hacked
Power quality evaluation based on wavelet packet decomposition and fuzzy logic

In this paper, a novel power quality (PQ) evaluation approach based on wavelet packet decomposition (WPD) and fuzzy logic is proposed. First, the PQ indices (PQIs) are redefined in the time frequency domain using WPD that prove to be capable of accurately measuring. Then a fuzzy synthetic evaluation model is used to amalgamate the redefined PQIs into one single index, the new index will helps reduce the size of data processed which is required in modern power system applications. The simulation results demonstrated that the proposed approach can effectively evaluate the power quality.