Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Screening, Brief Intervention, and Referral to Treatment (SBIRT) Education and Training on Nursing Students’ Attitudes toward Working with Patients who Use Alcohol and Drugs

Background: Screening, Brief Intervention, and Referral to Treatment (SBIRT) can reduce alcohol use and negative health outcomes in patients with risky substance use. However, negative attitudes that some health care professionals have toward patients who use substances are a barrier to implementing SBIRT. Methods: The University of Pittsburgh School of Nursing, in partnership with the Institute for Research, Education, and Training in Addictions (IRETA), developed a curriculum to train baccalaureate student nurses to deliver SBIRT. Results: Following SBIRT education and training, students’ perceived attitudes toward patients who use alcohol became more positive. Less robust changes were found for attitudes related to patients who use drugs. Conclusions: Nurses composing the largest group of healthcare workers are in key positions to screen, intervene, and provide education about substance use.
The error variance of the optimal linear smoother and maximum-variance fractional pole models

The variance of the optimal one-step ahead linear prediction error of a discrete-time stationary stochastic process is given by the well-known Szego-Kolmogorov formula as the geometric mean of the spectral density function. We first derive an analogous expression for the optimal linear smoother which uses the infinite past and the infinite future to determine the present. The least variance turns out to be the harmonic mean of the spectral density function. Building on this, we explore the question of what is the most random power spectrum in the sense of corresponding to the largest variance optimal linear smoother (i.e., least "smoothable"), which is consistent with finitely many covariance moments. It turns out that it can be described by an all-pole model, albeit the poles are fractional
Parity, Age at First Birth, and Risk of Death From Pancreatic Cancer: Evidence From a Cohort in Taiwan

Objectives: This study was undertaken to examine whether there is an association between parity and age at first birth and risk of pancreatic cancer. Methods: The study cohort consisted of all women with a record of a first and singleton childbirth in the Birth Registration System between 1978 and 1987. We tracked each woman from the time of their first childbirth and linked their vital status with mortality database. Cox proportional hazard regression models were used to estimate the relative risks (RRs) of death from pancreatic cancer associated with parity and age at first birth. Results: A trend of increasing risk of pancreatic cancer was seen with increasing age at first birth. The adjusted RR was 0.69 (95% confidence interval, 0.49-0.98) for women who born 2 children and 0.64 (95% confidence interval, 0.44-0.93) for women with 3 or more births, respectively, when compared with women who had given birth to only 1 child. There was a significant decreasing trend in the RR of pancreatic cancer with increasing parity. Conclusions: This study provides evidence that reproductive factors (parity and early age at first birth) may confer a protective effect on the risk of pancreatic cancer.
Question Types for Assessment of Mathematics Education in Dynamic Geometry Environments

Assessment of student learning requires the use of techniques for measuring student achievement. Assessment is more than a collection of techniques, however. It is a systematic process that plays a significant role in effective teaching. It begins with the identification of learning goals, monitors the progress students make toward those goals, and ends with a judgment concerning the extent to which those goals have been attained. In the literature, the integration of technological tools into the assessment process is expressed by the “e-assessment” concept. Assessment using ICT has come to be known as e-assess-ment, which includes the entire assessment process, from designing assignments to storing the results with the help of ICT. The most of the researches related to the e-assessment focused on how to transfer the examinations in paper-pencil environment to the electronic environment. In addition to those studies, in the research about the integration of computer assisted assessment tools to the mathematics instruction, the participant pre-service teachers use these tools in favor of the formative assessment. In a similar study, pre-service teachers prepared lessons and home works using technological tools such as dynamic geometry software and thus it is shown that those tools can be used in the process of assessment. In the literature, there is numerous studies concerning technology supported mathematics instruction. But none of them is related to the assessment dimension of the mathematics teaching. In particular, it is highly recommended to conduct researches about the use of technology in that dimension. The aim of this study is to determine question types that can be used for assessment of computer based mathematics instruction. Case study is considered as the methodology of the research. The reason is that a case study investigates a contemporary phenomenon in depth and within its real-life context when the boundaries between phenomenon and context are not clearly evident. 15 pre-service mathematics teachers have participated to the study of 6 weeks (3 hours per week). Every pre-service teacher worked individually on totally 26 geometry questions of different types. At the same time, they explained their approaches to solve problems by filling out a paper. In addition, a screen capture program is used to grab the video of what is seen on the computer screen. Meanwhile the researchers observed pre-service teachers’ work on computers. The findings of the study are revealed via the analysis of each video, of their comparison with the written explanations and of the researchers’ observations. Based on the findings, the most significant result of the study is that open-ended geometry problems reflect students’ knowledge better than other types of questions. Moreover, all types of questions should be used in order to assess students’ learning performance.
High Fidelity Simulations of Large-Scale Wireless Networks

The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation atmore » Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations. « less
Pipelined execution of stages in Apache Spark

This dissertation investigates the efficiency of a fundamental, low-level building block of modern big-data processing platforms, like Apache Spark. This type of platforms supports complex data analysis tasks by allowing data scientists to express arbitrary data manipulations via a direct graph of, so called, transformation operators that executed in a distributed fashion across a cluster of machines. In many realistic use cases, it is necessary to recur to operators, like Reduce, which have to fed with the results produced by operators executing on different machines. Some state-of-the-art solutions, like the aforementioned Spark platform, take what can be defined a batch strategy, which operates as follows. Operators that induce exchange of data among machines are used to demarcate the beginning of a new stage, which serves to logically group a set of operators that can execute without requiring any input from operators running on different machines. A Spark application is executed in batch mode, in the sense that if the stage i + 1 requires the result of stage i, then stage i needs to finish its computation before stage i + 1 can begin and load the data from stage i. This choice allows for a set of benefits, including higher network usage efficiency, simpler scheduling over operators and fault-tolerance mechanism. However, it can also lead to sub-optimal utilization of cluster’s resources. Another alternative approach consists of pipelining data transmission between stages, so that stage i+1 can start processing the data as it is generated by stage i. With this strategy, the execution of the two stages are overlapped, allowing higher utilization of cluster’s resources. In this thesis, Apache Spark is extended to support the pipeline execution of stages in order to compare the two strategies. An extensive experimental evaluation was conducted using both synthetic and realistic workloads to evaluate the performance difference when switching from batch to pipeline execution.
Epididymal protein 3A is upregulated and promotes cell proliferation in non-small cell lung cancer

Lung cancer is one of the most common cancer types and a major contributor to cancer-associated mortalities worldwide. The aim of the present study was to investigate the function of the epididymal protein 3A (EDDM3A) in non-small cell lung cancer (NSCLC). Data from patients with NSCLC were retrieved from The Cancer Genome Atlas and analyzed, and the differences in EDDM3A expression level between 30 NSCLC tissues and matched adjacent non-tumor tissues (>5 cm) were assessed via tissue microarray analysis. It was revealed that, compared with adjacent non-tumor tissues, EDDM3A expression was significantly increased in NSCLC tissues (P=4.19×10−2). To knock down EDDM3A expression in a human NSCLC cell line, lentivirus-mediated short hairpin RNAs (shRNAs) were used, and the knockdown efficiency was assessed via reverse transcription-quantitative PCR and western blotting. Moreover, cell proliferation was evaluated with an MTT assay and Celigo imaging cytometry. In addition, cell apoptosis was detected by Annexin V staining. It was demonstrated that knockdown of EDDM3A inhibited the proliferation of A549 cells. Furthermore, compared with the control group, the apoptotic rate of the EDDM3A-shRNA group was significantly higher. Collectively, the present results indicate the potential role of EDDM3A in NSCL and suggest that EDDM3A may represent a potent therapeutic target for treating patients with NSCLC.
Fire and deforestation dynamics in Amazonia (1973–2014)

Consistent long‐term estimates of fire emissions are important to understand the changing role of fire in the global carbon cycle and to assess the relative importance of humans and climate in shaping fire regimes. However, there is limited information on fire emissions from before the satellite era. We show that in the Amazon region, including the Arc of Deforestation and Bolivia, visibility observations derived from weather stations could explain 61% of the variability in satellite‐based estimates of bottom‐up fire emissions since 1997 and 42% of the variability in satellite‐based estimates of total column carbon monoxide concentrations since 2001. This enabled us to reconstruct the fire history of this region since 1973 when visibility information became available. Our estimates indicate that until 1987 relatively few fires occurred in this region and that fire emissions increased rapidly over the 1990s. We found that this pattern agreed reasonably well with forest loss data sets, indicating that although natural fires may occur here, deforestation and degradation were the main cause of fires. Compared to fire emissions estimates based on Food and Agricultural Organization's Global Forest and Resources Assessment data, our estimates were substantially lower up to the 1990s, after which they were more in line. These visibility‐based fire emissions data set can help constrain dynamic global vegetation models and atmospheric models with a better representation of the complex fire regime in this region.
The whole-genome assembly of an endangered Salicaceae species: Chosenia arbutifolia (Pall.) A. Skv

Abstract Background As a fast-growing tree species, Chosenia arbutifolia has a unique but controversial taxonomic status in the family Salicaceae. Despite its importance as an industrial material, in ecological protection, and in landscaping, C. arbutifolia is seriously endangered in Northeast China because of artificial destruction and its low reproductive capability. Results To clarify its phylogenetic relationships with other Salicaceae species, we assembled a high-quality chromosome-level genome of C. arbutifolia using PacBio High-Fidelity reads and Hi-C sequencing data, with a total size of 338.93 Mb and contig N50 of 1.68 Mb. Repetitive sequences, which accounted for 42.34% of the assembly length, were identified. In total, 33,229 protein-coding genes and 11,474 small noncoding RNAs were predicted. Phylogenetic analysis suggested that C. arbutifolia and poplars diverged approximately 15.3 million years ago, and a large interchromosomal recombination between C. arbutifolia and other Salicaceae species was discovered. Conclusions Our study provides insights into the genome architecture and systematic evolution of C. arbutifolia, as well as comprehensive information for germplasm protection and future functional genomic studies.
Effects of human activities of southern giant petrels and skuas in the antarctic

In der vorliegenden Dissertation wurde die erste umfassende Bewertung aktueller anthropogener Stressoren in Brutgebieten von drei antarktischen Seevogelarten (King George Island, Sudshetland Inseln) vorgenommen. Der Sudliche Riesensturmvogel Macronectes giganteus gilt als hoch sensible Art im Bezug auf menschliche Aktivitaten (eingestuft als "gefahrdet" in der Rote Liste der IUCN). Dagegen sind die Braune Skua Catharacta antarctica lonnbergi und die Sudpolarskua C. maccormicki teilweise mit antarktischen Stationen assoziiert und werden daher als weniger sensibel angesehen. Unter Benutzung nicht-invasiver Methoden wurden ethologische und physiologische Stressantworten (Herzschlagrate und Glukokortikoide im Kot) von Brutern, Nichtbrutern und Kuken untersucht und dabei Individuen entsprechend ihrer Erfahrung mit Menschen (Gebiete mit hohen, mittleren und niedrigen menschlichen Aktivitaten) verglichen. Diese Ergebnisse und die Analyse anthropogener Effekte auf Reproduktionsparameter fuhrten zu einer Abschatzung des Gefahrdungsgrades der Vogelarten und zu spezifischen Managementvorschlagen in ihren Lebensraumen.
Climate change in the Arctic: using plant functional types in a meta‐analysis of field experiments

Summary 1. The effects of global climate change are predicted to be strongest in the Arctic. This, as well as the suitability of tundra as a simple model ecosystem, has led to many field experiments investigating consequences of simulated environmental change. 2. On the basis of 36 experiments reviewed here, minor light attenuation by clouds, small changes in precipitation, and increases in UV-B radiation and atmospheric CO 2 concentrations will not affect arctic plants in the short term. However, temperature elevation, increases in nutrient availability and major decreases in light availability will cause an immediate plant-growth response and alter nutrient cycling, possibly creating positive feedbacks on plant biomass. The driver of future change in arctic vegetation is likely to be increased nutrient availability, arising for example from temperatureinduced increases in mineralization. 3. Arctic plant species differ widely in their response to environmental manipulations. Classification into plant functional types proved largely unsatisfactory for generalization of responses and predictions of effects. 4. Nevertheless, a few generalizations and consistent differences between PFTs were detected. Responses to fertilization were the strongest, particularly in grasses. Shrubs and grasses were most responsive to elevated temperature. 5. Future studies should focus on interactive effects of environmental factors, investigate long-term responses to manipulations, and incorporate interactions with other trophic levels. With respect to plant functional types, a new approach is advocated, which groups species according to their responses to environmental manipulations.
Socioeconomic and maternal determinants of small‐for‐gestational age births: Patterns of increasing disparity

Objective. To better characterize the relation between socioeconomic disadvantage and small‐for‐gestational age births (SGA). Design. Analysis of data from a mandatory population‐based surveillance system. Setting. Public or private hospitals and at home. Population. All 877,951 singleton births occurring in New South Wales, Australia, between 1994 and 2004. Methods. Multilevel models were developed to determine the factors associated with babies weighing less than the 3rd percentile for gestation and gender. Main outcome measures. Odds of SGA. Results. The risk of SGA increased with increasing socioeconomic disadvantage. Smoking accounted for approximately 40% of the increased risk associated with socioeconomic disadvantage, and delayed antenatal care approximately 5%. While the absolute rate of SGA remained stable over the study period, the odds of SGA in mothers living in the most disadvantaged areas compared to those in the least disadvantaged areas increased from approximately 1.7 to 2.2. This trend persisted after accounting for maternal smoking. The risk of SGA over this period also increased in mothers commencing antenatal care after the first trimester. After accounting for smoking, socioeconomic disadvantage and clinical conditions, mothers under 21 years of age were at reduced risk of SGA, but mothers over 35 were at increased risk. Conclusions. Socioeconomic disadvantage remains one of the dominant determinants of SGA, even in a developed country with universal insurance. This relation appears to be strengthening. Smoking patterns, inadequate antenatal care and clinical conditions partially account for this association and trend, however, most is mediated by other factors.
Kinome-centric pharmacoproteomics identifies signaling pathways underlying cellular responses to targeted cancer drugs

Kinase-dependent signaling networks are frequently dysregulated in cancer, driving disease progression. While kinase inhibition has become an important therapeutic approach many cancers resist drug treatment. Therefore, we need both reliable biomarkers that predict drug responses and new targets to overcome drug resistance. Determining the kinase(s) that control cancer progression in individual cancers can pose a significant challenge. Genomics has identified important, yet limited numbers of kinase driver mutations. Transcriptomics can quantify aberrant gene expression, but it cannot measure the protein phosphorylation that regulates kinase-dependent signaling network activity. Proteomics measures protein expression and phosphorylation and, therefore, quantifies aberrant signaling network activity directly. We developed a kinome-centric pharmacoproteomics platform to study signaling pathways that determine cancer drug response. Using hepatocellular carcinoma (HCC) as our model, we determined kinome activity with kinobead/LC-MS profiling, and screened 299 kinase inhibitors for growth inhibition. Integrating kinome activity with drug responses, we obtained a comprehensive database of predictive biomarkers, and kinase targets that promote drug sensitivity and resistance. Our dataset specified pathway-based biomarkers for the clinical HCC drugs sorafenib, regorafenib and lenvatinib, and we found these biomarkers enriched in human HCC specimens. Strikingly, our database also revealed signaling pathways that promote HCC cell epithelial-mesenchymal transition (EMT) and drug resistance, and that NUAK1 and NUAK2 regulate these pathways. Inhibition of these kinases reversed the EMT and sensitized HCC cells to kinase inhibition. These results demonstrate that our kinome pharmacoproteomics platform discovers both predictive biomarkers for personalized oncology and novel cancer drug targets.
PHOTOREGULATION OF GENE EXPRESSION IN PLANTS *

Light has an extensive regulatory influence on the growth and development of green plants which is quite distinct from its role in driving photosynthesis. In many species light has been shown to control such important processes as seed germination, stem extension, leaf expansion, chloroplast biogenesis and the induction of flowering. It is likely, therefore, that light regulates the expression of large numbers of genes involved in metabolism or development. In support of this contention, Lamb and Lawton (1983) have presented a long list of gene products whose amounts or activities are regulated by light, and de Vries et al. (1982) have detected over 30 translatable mRNAs in pea that change in abundance in response to illumination. Nevertheless, the majority of light-regulated genes, especially those concerned with aspects of development, have not yet been identified. Research to date has concentrated on ‘model’ genes whose transcripts and protein products are relatively abundant, making them most amenable to study. The principal examples are the nuclear genes encoding two chloroplast proteins: the small subunit (rbcSt; often abbreviated to SSU) of ribulose-1,5-bisphosphate carboxylase-oxygenase, an,d the major light-harvesting chlorophyll aib binding protein (cab; often LHCP). Expression of these genes is dramatically stimulated by light in several species (Tobin and Silverthorne, 1985) and is also tissue-specific (Fluhr et al., 1986a; Simpson er al., 1986a). Other genes which have beei! studied in some detail are those encoding the enzyme NADPH-protochlorophyllide oxidoreductase (PCR) and the photoreceptor phytochrome. These genes are negatively regulated by light (Tobin and Silver-