Miracle-dz/UniFAR-FTUs huggingface dataset:
FK506-Binding Protein 12 Modulates μ-Opioid Receptor Phosphorylation and Protein Kinase Cε–Dependent Signaling by Its Direct Interaction with the Receptor

Protein kinase C (PKC) activation plays an important role in morphine-induced μ-opioid receptor (OPRM1) desensitization and tolerance development. It was recently shown that receptor phosphorylation by G protein–coupled receptor kinase regulates agonist-dependent selective signaling and that inefficient phosphorylation of OPRM1 leads to PKCε activation and subsequent responses. Here, we demonstrate that such receptor phosphorylation and PKCε activation can be modulated by FK506-binding protein 12 (FKBP12). Using a yeast two-hybrid screen, FKBP12 was identified as specifically interacting with OPRM1 at the Pro353 residue. In human embryonic kidney 293 cells expressing OPRM1, the association of FKBP12 with OPRM1 decreased the agonist-induced receptor phosphorylation at Ser375. The morphine-induced PKCε activation and the recruitment of PKCε to the OPRM1 signaling complex were attenuated both by FKBP12 short interfering RNA (siRNA) treatment and in cells expressing OPRM1 with a P353A mutation (OPRM1P353A), which leads to diminished activation of PKC-dependent extracellular signal-regulated kinases. Meanwhile, the overexpression of FKBP12 enabled etorphine to activate PKCε. Further analysis of the receptor complex demonstrated that morphine treatment enhanced the association of FKBP12 and calcineurin with the receptor. The blockade of the FKBP12 association with the receptor by the siRNA-mediated knockdown of endogenous FKBP12 or the mutation of Pro353 to Ala resulted in a reduction in PKCε and calcineurin recruitment to the receptor signaling complex. The receptor-associated calcineurin modulates OPRM1 phosphorylation, as demonstrated by the ability of the calcineurin autoinhibitory peptide to increase the receptor phosphorylation. Thus, the association of FKBP12 with OPRM1 attenuates the phosphorylation of the receptor and triggers the recruitment and activation of PKCε.
AnalogySpace: Reducing the Dimensionality of Common Sense Knowledge

We are interested in the problem of reasoning over very large common sense knowledge bases. When such a knowledge base contains noisy and subjective data, it is important to have a method for making rough conclusions based on similarities and tendencies, rather than absolute truth. We present Analogy Space, which accomplishes this by forming the analogical closure of a semantic network through dimensionality reduction. It self-organizes concepts around dimensions that can be seen as making distinctions such as "good vs. bad" or "easy vs. hard", and generalizes its knowledge by judging where concepts lie along these dimensions. An evaluation demonstrates that users often agree with the predicted knowledge, and that its accuracy is an improvement over previous techniques.
Draft Genome Sequence of the Deep-Subsurface Actinobacterium Tessaracoccus lapidicaptus IPBSL-7T

ABSTRACT The type strain of Tessaracoccus lapidicaptus was isolated from the deep subsurface of the Iberian Pyrite Belt (southwest Spain). Here, we report its draft genome, consisting of 27 contigs with a ~3.1-Mb genome size. The annotation revealed 2,905 coding DNA sequences, 45 tRNA genes, and three rRNA genes.
Multiprocessing with the Exokernel Operating System by Benjie Chen

Exokernel is a minimal operating system kernel that safely m ultiplexes hardware resources, while leaving all system abstractions to applications. An exokernel exhibit s etter performance and offers more functionality because applications can provide optimized system abst r ctions, at the user-level, based on their needs. Current design of the exokernel system, however, does not su pport multiprocessor architectures. This thesis presents a symmetric multiprocessing exokernel and demons trate that unprivileged library implementation of operating system abstractions is viable on a multiproces sor ystem. This thesis focus on three issues. First, it presents synchr o ization strategies used in kernel. Second, this thesis describes three new exokernel interfaces: mess ag passing, kernel support for multithreading, and multiprocessor scheduling. Third, because exokernel appl ications do not trust each other, traditional synchronization primitives used to guard system abstractions, suc h as voluntary memory locks, do not function well. This thesis presents and evaluates a strategy for synchroni zation among untrusted processes. A multiprocessor exokernel and a synchronized library operating syst em result from this thesis. Performance analysis shows that the overheads of synchronization in both the kern el a d the library operating system are small. Thesis Supervisor: M. Frans Kaashoek Title: Associate Professor Multiprocessing with the Exokernel Operating System by Benjie Chen Submitted to the Department of Electrical Engineering and C omputer Science on February, 2000, in partial fulfillment of the requirements for the degree of Bachelor of Science and Master of Engineering in Computer Science and Engineering
Tablet-Based Strength-Balance Training to Motivate and Improve Adherence to Exercise in Independently Living Older People: A Phase II Preclinical Exploratory Trial

Background Reaction time, coordination, and cognition performance typically diminish in older adults, which may lead to gait impairments, falls, and injuries. Regular strength–balance exercises are highly recommended to reduce this problem and to improve health, well-being, and independence in old age. However, many older people face a lack of motivation in addition to other strong barriers to exercise. We developed ActiveLifestyle, an information technology (IT)-based system for active and healthy aging aiming at improving balance and strength. ActiveLifestyle is a training app that runs on a tablet and assists, monitors, and motivates older people to follow personalized training plans autonomously at home. Objective The objectives were to (1) investigate which IT-mediated motivation strategies increase adherence to physical exercise training plans in older people, (2) assess the impact of ActiveLifestyle on physical activity behavior change, and (3) demonstrate the effectiveness of the ActiveLifestyle training to improve gait speed. Methods A total of 44 older adults followed personalized, 12-week strength and balance training plans. All participants performed the exercises autonomously at home. Questionnaires were used to assess the technological familiarity and stage of behavior change, as well as the effectiveness of the motivation instruments adopted by ActiveLifestyle. Adherence to the exercise plan was evaluated using performance data collected by the app and through information given by the participants during the study. Pretests and posttests were performed to evaluate gait speed of the participants before and after the study. Results Participants were 75 years (SD 6), predominantly female (64%), held a trade or professional diploma (54%), and their past profession was in a sitting position (43%). Of the 44 participants who enrolled, 33 (75%) completed the study. The app proved to assist and motivate independently living and healthy older adults to autonomously perform strength–balance exercises (median 6 on a 7-point Likert scale). Social motivation strategies proved more effective than individual strategies to stimulate the participants to comply with the training plan, as well as to change their behavior permanently toward a more physically active lifestyle. The exercises were effective to improve preferred and fast gait speed. Conclusions ActiveLifestyle assisted and motivated independently living and healthy older people to autonomously perform strength–balance exercises over 12 weeks and had low dropout rates. The social motivation strategies were more effective to stimulate the participants to comply with the training plan and remain on the intervention. The adoption of assistive technology devices for physical intervention tends to motivate and retain older people exercising for longer periods of time.
Framework for a New Political Praxis: Respeto, Dignidad y Conocimiento

This article uses story as a process to highlight the work in a South Texas community that focuses on the education of youth and the development of community. The work is guided by a new consciousness of place, community engagement, and identity formation. The work is local, but breaking the isolation of youth, families, and ideas has been part of an emerging theory of change. The document takes us in and out of stories of place in an attempt to transfer the work to other communities. It presents the voices of witnesses to take the concepts used in this Mexican-American community into other spaces. The work is informed by place, theory, and practice.
A new data aggregation scheme via adaptive compression for wireless sensor networks

Data aggregation is necessary for extending the network lifetime of wireless sensor nodes with limited processing and power capabilities, since energy expended in transmitting a single data bit would be at least several orders of magnitude higher when compared to that needed for a 32-bit computation. Therefore, in this article, a novel nonlinear adaptive pulse coded modulation-based compression (NADPCMC) scheme is proposed for data aggregation in a wireless sensor network (WSN). The NADPCMC comprises of two estimators—one at the source or transmitter and the second one at the destination node. The estimator at the source node approximates the data value for each sample. The difference between the data sample and its estimate is quantized and transmitted to the next hop node instead of the actual data sample, thus reducing the amount of data transmission and rending energy savings. A similar estimator at the next hop node or base station reconstructs the original data. It is demonstrated that repeated application of the NADPCMC scheme along the route in a WSN results in data aggregation. Satisfactory performance of the proposed scheme in terms of distortion, compression ratio, and energy efficiency and in the presence of estimation and quantization errors for data aggregation is demonstrated using the Lyapunov approach. Then the performance of the proposed scheme is contrasted with the available compression schemes in an NS-2 environment through several benchmarking datasets. Simulation and hardware results demonstrate that almost 50% energy savings with low distortion levels below 5% and low overhead are observed when compared to no compression. Iteratively applying the proposed compression scheme at the cluster head nodes along the routes over the network yields an additional improvement of 20% in energy savings per aggregation with an overall distortion below 8%.
Real-time multi-bounce many-object ray tracing with distance-normal impostors

This paper presents a fast approximate ray-tracing technique for the GPU. We extend previous distance impostor techniques to handle scenes with multiple reﬂective and refractive objects in real time. There are two key ideas that allow this. First, we turn around the distance impostor approach not to intersect internal rays with enclosing environmental geometry, but external rays with an object. Texture maps representing refractive objects are labelled refractor maps . To remedy problems with cube maps we propose a height-and-normal map representation, which we call a refractor height map , and describe an algorithm to ﬁnd multiple refracted ray bounces within it. The second idea is the separation of static and dynamic objects. Classic distance impostors can be used for the static environment, and only those of moving objects need to be updated in every frame. Light paths passing through moving objects can be found by searching their refractor maps. We demonstrate the proposed techniques in a chess application featuring two full sets of glass pieces, with only one piece moving at a time. Shadows, reﬂections, refractions and caustics are simultaneously rendered in real time.
Doing Educational Research in Rural Settings: Methodological Issues, International Perspectives and Practical Solutions

Doing Educational Research in Rural Settings is a much-needed guide for educational researchers whose research interests are located outside metropolitan areas in places that are generically considered to be rural. Key topics include: • Working with and within the rural • The impact of educational globalisation and the problematisation of cultural difference in social research • Researcher subjectivities • The position of education research in rural contexts • The usefulness of research Reciprocity and converging interest • Ethics and confidentiality. This book is uniquely written with an eye to practicality and applicability, and will be an engaging guide for higher degree and doctoral students seeking to gain a stronger understanding of educational research in rural settings.
Scalable Distributed Processing of Spatial Point Data

The increasing availability of cheap location tracking devices is causing a steadily increasing demand for location based services. Such services usually utilize spatial data structures that need to scale with increasing request load. While static data allows for scaling by simple service replication, dynamic data such as moving users requires administration in a single coherent system to provide consistent and up-to-date processing results. In this paper, we propose a distributed system based on a P2P architecture to store and process spatial data, in particular with window- and k-nearest-neighbors queries. Our system is very simple in that it solely manages a range-partitioned linear data space defined by a Hilbert Curve mapping and neither requires explicit hashing, clustering or the maintenance of a dedicated distributed spatial structure at all. Our main focus is on the inherent quad-tree structure of the 2d Hilbert Curve and how it suffices to efficiently evaluate nearest-neighbor queries in a distributed manner. We verify our approach using real-world data from Open Street Map and demonstrate that the throughput of our system scales asymptotically linear with the network size.
Gender Differences in End-User Debugging, Revisited: What the Miners Found

We have been working to uncover gender differences in the ways males and females problem solve in end-user programming situations, and have discovered differences in males' versus females' use of several debugging features. Still, because this line of investigation is new, knowing exactly what to look for is difficult and important information could escape our notice. We therefore decided to bring data mining techniques to bear on our data, with two aims: primarily, to expand what is known about how males versus females make use of end-user debugging features, and secondarily, to find out whether data mining could bring new understanding to this research, given that we had already studied the data manually using qualitative and quantitative methods. The results suggested several new hypotheses in how males versus females go about end-user debugging tasks, the factors that play into their choices, and how their choices are associated with success
Thyroid Cancer Risk in Areas of Ukraine and Belarus Affected by the Chernobyl Accident

Abstract Jacob, P., Bogdanova, T. I. , Buglova, E. , Chepurniy, M. , Demidchik, Y. , Gavrilin, Y. , Kenigsberg, J., Meckbach, R. , Schotola, C. , Shinkarev, S. , Tronko, M. D. , Ulanovsky, A. , Vavilov, S. and Walsh, L. Thyroid Cancer Risk in Areas of Ukraine and Belarus Affected by the Chernobyl Accident. Radiat. Res. 165, 1–8 (2006). The purpose of the present study was to analyze the thyroid cancer incidence risk after the Chernobyl accident and its degree of dependence on time and age. Data were analyzed for 1034 settlements in Ukraine and Belarus, in which more than 10 measurements of the 131I content in human thyroids had been performed in May/June 1986. Thyroid doses due to the Chernobyl accident were assessed for the birth years 1968– 1985 and related to thyroid cancers that were surgically removed during the period 1990–2001. The central estimate for the linear coefficient of the EAR dose response was 2.66 (95% CI: 2.19; 3.13) cases per 104 PY-Gy; for the quadratic coefficient, it was −0.145 (95% CI: −0.171; −0.119) cases per 104 PY-Gy2. The EAR was found to be higher for females than for males by a factor of 1.4. It decreased with age at exposure and increased with age attained. The central estimate for the linear coefficient of the ERR dose response was 18.9 (95% CI: 11.1; 26.7) Gy−1; for the quadratic coefficient, it was −1.03 (95% CI: −1.46; −0.60) Gy−2. The ERR was found to be smaller for females than for males by a factor of 3.8 and decreased strongly with age at exposure. Both EAR and ERR were higher in the Belarusian settlements than in the Ukrainian settlements. In contrast to ERR, EAR increases with time after exposure. At the end of the observation period, excess risk estimates were found to be close to those observed in a major pooled analysis of seven studies of childhood thyroid cancer after external exposures.
A RSS based statistical localization algorithm in WLAN

With the proliferation of location based services (LBS), various indoor localization techniques have been explored based on received signal strength (RSS). To improve performance, many algorithms and techniques have been proposed in the literature. In this paper, a new RSS based statistical location algorithm is proposed to achieve better localization performance, with a focus on statistical analysis and reasoning in wireless local area network (WLAN). Experimental results demonstrate our proposed algorithm outperforms and more than 20 percent reduction in root mean square error (RMSE) has been achieved, through comparisons with some other existing algorithms. Moreover, it has also been verified that number of training locations can be reduced without too much performance degradation.
Jtop: Managing JUnit Test Cases in Absence of Coverage Information

Test case management may make the testing process more efficient and thus accelerate software delivery. With the popularity of using JUnit for testing Java software, researchers have paid attention to techniques to manage JUnit test cases in regression testing of Java software. Typically, most existing test case management tools are based on the coverage information. However, coverage information may need extra efforts to obtain. In this paper, we present an Eclipse IDE plug-in (named Jtop) for managing JUnit test cases in absence of coverage information. Jtop statically analyzes the program under test and its corresponding JUnit test cases to perform the following management tasks: regression test case selection, test suite reduction and test case prioritization. Furthermore, Jtop also enables the programmer to manually manipulate test cases through a graphical user interface.
Rapid in vivo labeling of identified zebrafish neurons

We report a simple and rapid method to label individual neurons in live zebrafish embryos and to examine their gene expression profiles. Injection of plasmid DNA encoding an α‐tubulin promotor driving GFP expression results in mosaic embryos containing a limited number of GFP‐positive neurons. Labeled neurons express GFP in their soma and axon, providing the opportunity to analyze pathfinding behaviors of identified neurons in vivo. Moreover, the presence of only a small subset of GFP tagged neurons permits the rapid anatomical identification of these neurons based on soma position and axonal trajectory. Analysis of injected embryos reveals that most, if not all, spinal cord cell types and many other neuronal cell types elsewhere in the nervous system can be GFP tagged. Finally, by combining GFP labeling of individual neurons with fluorescent in situ hybridization, we demonstrate the potential of this method to elucidate gene expression patterns at single cell resolution. genesis 2:196–202, 2002. © 2002 Wiley‐Liss, Inc.
Uplink and downlink beamforming in two-way relay networks

In this paper, we consider a two way relay network containing two single antenna transceivers and a MIMO relay. We consider a two stage design process, first by obtaining soft estimate of the transmitted signal through receiver beamformer and then designing transmitter beamformers. We minimize the relay transmit power (dissipated in the relay) subject to two constrains on the transceivers received signal to noise ratios(SNRs).
Private Selective Sweeps Identified from Next-Generation Pool-Sequencing Reveal Convergent Pathways under Selection in Two Inbred Schistosoma mansoni Strains

Background The trematode flatworms of the genus Schistosoma, the causative agents of schistosomiasis, are among the most prevalent parasites in humans, affecting more than 200 million people worldwide. In this study, we focused on two well-characterized strains of S. mansoni, to explore signatures of selection. Both strains are highly inbred and exhibit differences in life history traits, in particular in their compatibility with the intermediate host Biomphalaria glabrata. Methodology/Principal Findings We performed high throughput sequencing of DNA from pools of individuals of each strain using Illumina technology and identified single nucleotide polymorphisms (SNP) and copy number variations (CNV). In total, 708,898 SNPs were identified and roughly 2,000 CNVs. The SNPs revealed low nucleotide diversity (π = 2×10−4) within each strain and a high differentiation level (Fst = 0.73) between them. Based on a recently developed in-silico approach, we further detected 12 and 19 private (i.e. specific non-overlapping) selective sweeps among the 121 and 151 sweeps found in total for each strain. Conclusions/Significance Functional annotation of transcripts lying in the private selective sweeps revealed specific selection for functions related to parasitic interaction (e.g. cell-cell adhesion or redox reactions). Despite high differentiation between strains, we identified evolutionary convergence of genes related to proteolysis, known as a key virulence factor and a potential target of drug and vaccine development. Our data show that pool-sequencing can be used for the detection of selective sweeps in parasite populations and enables one to identify biological functions under selection.
Methylation‐Specific Sequencing of GSTP1 Gene Promoter in Circulating/Extracellular DNA from Blood and Urine of Healthy Donors and Prostate Cancer Patients

Hypermethylated promoters of cancer‐related genes represent convenient targets for early cancer diagnosis and monitoring based on circulating/extracellular DNA (cir/exDNA) from human blood and urine. The frequency of detection of methylated tumor suppressor genes in plasma or urine samples is usually lower than in the samples of tumor tissue because of a low concentration of target DNA and potential polymorphism of cirDNA methylation. Sequencing of the methylated cir/exDNA of tumor suppression genes provides information about methylation of the cirDNA originating from the tumor cells, which is necessary for optimization of cancer diagnosis. In this work, by sequencing chemically converted cir/exDNA, we have studied the cytosine methylation profile of GSTP1 gene promoter (1001–1302, X08058) in the pool of cir/exDNA from the blood and urine of healthy men, prostate cancer (PCa) patients, and patients with benign prostatic hyperplasia (BPH). We demonstrated that the data on cir/exDNA methylation could be obtained from sequencing of the cir/exDNA from blood and urine. The DNA isolated from blood plasma and the eluates of blood cells and urine of each patient were characterized by the same methylation profile of the GSTP1 gene. The profile of GSTP1 gene methylation in the extracellular DNA of PCa patients differs from the profiles characteristic of healthy donors and patients with BPH.