Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study of Methods for Measurement of Energy of Computing

Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using external power meters; (b) Measurements using on-chip power sensors and (c) Energy predictive models. In this work, we present a comprehensive study comparing the accuracy of state-of-the-art on-chip power sensors and energy predictive models against system-level physical measurements using external power meters, which we consider to be the ground truth. We show that the average error of the dynamic energy profiles obtained using on-chip power sensors can be as high as 73% and the maximum reaches 300% for two scientific applications, matrix-matrix multiplication and 2D fast Fourier transform for a wide range of problem sizes. The applications are executed on three modern Intel multicore CPUs, two Nvidia GPUs and an Intel Xeon Phi accelerator. The average error of the energy predictive models employing performance monitoring counters (PMCs) as predictor variables can be as high as 32% and the maximum reaches 100% for a diverse set of seventeen benchmarks executed on two Intel multicore CPUs (one Haswell and the other Skylake). We also demonstrate that using inaccurate energy measurements provided by on-chip sensors for dynamic energy optimization can result in significant energy losses up to 84%. We show that, owing to the nature of the deviations of the energy measurements provided by on-chip sensors from the ground truth, calibration can not improve the accuracy of the on-chip sensors to an extent that can allow them to be used in optimization of applications for dynamic energy. Finally, we present the lessons learned, our recommendations for the use of on-chip sensors and energy predictive models and future directions.
Auto-regressive modeling and diagnostics for qPCR amplification

Current methods used to analyze real-time quantitative polymerase chain reaction (qPCR) data exhibit systematic deviations from the assumed model over the progression of the reaction. Slight variations in the amount of the initial target molecule or in early amplifications are likely responsible for these deviations. Commonly-used 4- and 5-parameter sigmoidal models appear to be particularly susceptible to this issue, often displaying patterns of autocorrelation in the residuals. The presence of this phenomenon, even for technical replicates, suggests that these parametric models may be misspecified. Specifically, they do not account for the sequential dependent nature of qPCR fluorescence measurements. We demonstrate that a Smooth Transition Autoregressive (STAR) model addresses this limitation by explicitly modeling the dependence between cycles and the gradual transition between amplification regimes. In summary, application of a STAR model to qPCR amplification data improves model fit and reduces autocorrelation in the residuals.
Evaluation of Suspected Adverse Drug Reactions of Oral Anti-diabetic Drugs in a Tertiary Care Hospital for Type II Diabetes Mellitus

Background and Objective: The objective of the study was to evaluate and analyse ADRs in type II diabetic patients and to determine the causality, severity and preventability of reactions. Methods: 460 diabetic patients on oral anti-diabetic drugs were evaluated prospectively over a period of six months. All patients were followed up for ADRs which were evaluated for incidence, frequency, severity and causality. Causality was graded according to WHO-UMC scale and Naranjo scale. Severity according to Modified Hartwig and Siegel scale and preventibility based on Modified Schumock and Thornton Scale. Results and Discussion: A total of 58 ADRs were reported from 460 patients during the study period with female predominance over male. All the ADRs that were reported were of type A category. The class of drug responsible for causing more ADRs was found to be biguanides. The most commonly affected organ system was GI System The suspected ADRs were assessed for their causality, it was revealed that 52 were probable and 6 were possible and as per Naranjo scale 53 were probable and 5 possible. The ADRs were assessed for severity using Modified Hartwig and Siegel scale and it was observed that 28 were mild and 30 moderate. Preventibility of reported ADR cases was assessed using the Modified Schumock and Thornton Scale. Using this scale all 58 ADRs were probably preventable. Conclusion: These study results provide insight to the healthcare providers on the importance of monitoring and reporting ADR associated with the drugs.
Hardware Implementation of Edge Detection Algorithm-A Review

Edge is one of the most fundamental and significant feature of image. It helps us to analyze, infer and take decision in various applications. Several edge detection algorithms are available; each one has significance based on subjective application. In this paper edge detection algorithm is proposed to be implemented over Field Programmable Gate Array (FPGA) for real time applications. FPGA has large internal memory, embedded multipliers and it offers parallelism. Hence, provides platform for processing real time algorithm with substantially higher performance than programmable Digital Signal Processor (DSPs) and microprocessor. Hardware implementation yields dedicated system which can serve for many real time image processing applications. For implementation ‘Xilinx System Generator’ (XSG) tool of Matlab may be used that generates net-list and bit-stream file by simplified approach.
BYPASS1-LIKE, A DUF793 Family Protein, Participates in Freezing Tolerance via the CBF Pathway in Arabidopsis

The C-REPEAT BINDING FACTOR signaling pathway is strictly modulated by numerous factors and is essential in the cold response of plants. Here, we show that the DUF793 family gene BYPASS1-LIKE modulates freezing tolerance through the CBFs in Arabidopsis. The expression of B1L was rapidly induced under cold treatment. Comparing to wild type, B1L knockout mutants were more sensitive to freezing treatment, whereas B1L-overexpressing lines were more tolerant. The expression of CBFs and CBF target genes was significantly decreased in b1l mutant. Using yeast two-hybrid screening system, 14-3-3λ was identified as one of proteins interacting with B1L. The interaction was confirmed with bimolecular fluorescence complementation assay and co-immunoprecipitation assay. Biochemical assays revealed that b1l mutation promoted the degradation of CBF3 compared to wild type, whereas 14-3-3κλ mutant and b1l 14-3-3κλ mutant suppressed the degradation of CBF3. Consistently, 14-3-3κλ and b1l 14-3-3κλ mutants showed enhanced freezing tolerance compared to wild type. These results indicate that B1L enhances the freezing tolerance of plants, at least partly through stabilizing CBF. Our findings improve our understanding of the regulation of CBF in response to cold stress.
Maintaining the utility of learned knowledge using model-based adaptive control

The overfit problem in empirical learning and the utility problem in analytical learning both describe a common behavior of machine learning methods: the eventual degradation of performance due to increasing amounts of learned knowledge. Plotting the performance of the changing knowledge during execution of a machine learning method (the performance response) reveals similar curves for several methods. The performance response generally indicates a single peak performance greater than that attained by popular pruning techniques. The similarity in performance responses suggests a parameterized model relating performance to the amount of learned knowledge. Given this model, a model-based adaptive control (MBAC) approach can be used to update the model based on feedback from the performance element and make control decisions regarding the amount of knowledge to be learned or unlearned. In view of the large number of alternative learning methods, a more general utility problem exists in determining not only the correct amount of learned knowledge, but also the correct method for learning this knowledge. Relying too heavily on one particular learning method may result in less than optimal performance achievement. Overcoming this general utility problem requires a new control mechanism for determining the correct learning method and amount of learned knowledge in order to achieve the performance objectives of the task. Maintaining models for several learning methods allows the MBAC approach to decide the appropriate type of learning, in addition to the amount. Experimentation analyzes the ability of the MBAC approach to converge upon the peak of the performance response and avoid generation of low utility knowledge. Results indicate that a quadratic model is sufficient to fit the peak of the performance response and that MBAC using the quadratic model performs well at selecting the best learning method for a given learning task. More formal analysis of the performance response supports the quadratic model for controlling how much knowledge to learn as opposed to which knowledge.
XQuery Processing in the MapReduce Framework

This master’s thesis addresses the mapping of declarative query processing and computation to the programming model of MapReduce. MapReduce is a popular framework for large-scale data analysis on cluster architectures. Its popularity arises from the fact that it provides distribution transparency, which is based on the computation patterns of functional list processing. This work proposes a translation mechanism which maps XQuery expressions to MapReduce programs, allowing the transparent, parallel execution of data-processing queries in a distributed environment. Our approach reuses the compilation logic of an existing XQuery processor and extends it with the MapReduce programming model and distribution awareness. This thesis describes the computational model of MapReduce and introduces the major aspects of data processing in XQuery, including an overview of the compiler organization. The mapping mechanism is described in three major steps: the transformation of the query logical plan into a distribution-aware representation; the compilation of this representation into MapReduce job descriptions; and their execution in the distributed framework. Furthermore, this work analyzes the performance of the approach in terms of execution time and provides a critical analysis with respect to existing approaches.
Accessing Olfactory Habituation in Drosophila melanogaster with a T-maze Paradigm

Habituation is the process whereby perceptual changes alter the value of environmental stimuli, enabling salience filtering. This behavioral response decrement is a form of non-associative learning, where the subject learns about the stimulus and does not involve sensory adaptation, sensory or motor fatigue. The range of behavioral responses in D. melanogaster led to the development of a number of habituation paradigms addressing various sensory modalities. Habituation of osmotactic responses has previously been measured with the Y-maze test and required 30 min of odor exposure. Here, we describe an olfactory habituation assay utilizing the widely used in associative learning paradigms T-maze. Continuous or repetitive odor exposure for 4 min is adequate to attenuate osmotactic responses both to attractive and aversive odors. Importantly, the decreased response conforms to habitation parameters, presenting dishabituation and spontaneous recovery. This assay allows the study of habituation after brief odor exposure, but also discriminates between the two distinct phases of the response, an initial habituation latency period followed by habituation. In addition, the characterization of the neuronal circuits implicated in each phase facilitates further study of the molecular components underlying this process.
Endocytosis as an Additional Mechanism of Glucose Transport to the Hexose Transporter in Trypanosoma brucei

Endocytosis as an Additional Mechanism of Glucose Transport to the Hexose Transporter in Trypanosoma brucei JongSu Choi Department of Chemistry and Biochemistry, BYU Master of Science Trypanosoma brucei is an extracellular kineotoplastid parasite that causes human African trypanosomiasis (HAT), also known as sleeping sickness. As trypanosomes undergo vector to host transition, heavy transcriptional adaptation such as metabolic shift to glycolysis and upregulated endocytosis occurs. Specifically, glycolysis in the infectious stage becomes the sole source of energy production; thus, the glucose transport mechanism in T. brucei provides one of the most promising therapeutic targets for development of new drugs to treat HAT. Despite an established trypanosome hexose transporter (THT) model for glucose transport across the plasma membrane, there remains gaps in the detailed mechanism of glucose transport especially as it relates to glucose transport across the glycosomal membrane. Using 2-NBDG, a fluorescent glucose analog, we measured glucose uptake rates in the presence of small molecule inhibitors and by using RNA interference (RNAi) to knockdown key proteins to investigate the mechanism of glucose transport in trypanosomes. We have confirmed a direct role of THT in glucose transport of BSF trypanosomes; however, in our investigations, we observed an unexpected ATP-dependence on glucose transport in live trypanosomes, which initiated further study where we focused on the role of endocytosis as an ATP-coupled bulk glucose transport mechanism. Experimental approaches that inhibited endocytosis reduced the observed glucose uptake rate confirming a role for endocytosis-coupled glucose transport in BSF trypanosomes. We provide evidence for an endocytosis-coupled glucose transport mechanism in BSF trypanosomes as an additional and important mechanism that functions in parallel with the established THT model.
Afro-Hispanic contact varieties as conventionalized advanced second languages

This article focuses on some linguistic aspects of Afro-Hispanic contact varieties that have traditionally been ascribed to their supposed creole origin. Conversely, the present analysis suggests that such linguistic features can be accounted for as the result of conventionalized advanced SLA strategies (Plag 2008a; Siegel 2008), which do not necessarily imply any previous creole stage. The theoretical framework adopted here is the one provided by the Minimalist Constructionism, which assumes that SLA is driv- en by UG through a path of “possible grammars” (Herschensohn 2000). In particular, the features under analysis are seen as possible L2 instantiations of UG, which crys- tallized under the form of L1 structures in the grammars of the following generations of speakers. In addition, this paper provides a reflection on the nature of these contact dialects and their contribution to the study of syntax and SLA from a microparametric perspective (Kayne 1996).
Polycyclic Aromatic Hydrocarbons and their Adducts with Solvents from Ag(II)SO4-Based Oxidative C-C Coupling

Abstract 9,9′-bianthryl and 9,9′-biphenanthryl were synthesized by direct oxidative C–C coupling of anthracene and phenanthrene, respectively, using divalent silver sulfate Ag(II)SO4 under ambient temperature conditions. Syntheses proceed with rather low yields 6–10%, however, they are competitive to more complex synthetic pathways due to single-pot process and lower waste. The single crystal structures of 9,9′-bianthryl, 9,9′-biphenanthryl and adducts of 9,9′-bianthryl with benzene, toluene and o- and p-xylene were obtained. X-ray structure of the adducts attested that the guest molecules of aromatic hydrocarbons were accommodated in cavities formed by the host 9,9′-bianthryl molecule. The adducts are stabilized mostly by the C–H•••π interactions, as indicated by analysis of crystal structures and Hirschfeld surfaces.
A 32 Channel Receive-only Head Coil And Detunable Transmit Birdcage Coil For 7 Tesla Brain Imaging

G. C. Wiggins, C. J. Wiggins, A. Potthast, V. Alagappan, O. Kraff, A. Reykowski, L. L. Wald Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, Siemens Medical Solutions, Inc, Malvern, PA, United States, Department of Diagnostic and Interventional Radiology, University Hospital Essen, Essen, Germany, Invivo Corporation, Gainesville, FL, United States Introduction The phased array [1] provides a particularly attractive solution for MR imaging at 7 Tesla. Increases in tissue loading at high frequency favor the use of arrays with many small receiver coils, and accelerated parallel reconstruction techniques can decrease scan times and reduce susceptibility distortions. There are however many challenges in their design and use at fields of 7 Tesla and higher, including coil to coil and cable interactions. Since body transmit coils are not routinely available on 7 Tesla scanner systems, it is also necessary to incorporate a detunable transmit coil. While many favor gapped array designs with the aim of improving gfactor in SENSE acceleration, recent analysis suggests that for large numbers of coils (<16) the SNR which can be achieved with accelerated imaging techniques is higher for overlapped coil designs [2]. In this study we extend the 32 channel soccer ball geometry previously described at 3T [3] to 7T with a hybrid birdcage transmit coil and extended measures for reducing cable interactions. This device was designed to work inside a 36cm diameter head gradient coil. This prototype was evaluated in human imaging for SNR and g-factor performance.
Exploring innovative rehabilitation for the knee using eHealth, biofeedback and online communities

Knee pain is regarded as an inevitable outcome in an ageing population and subsequent management, treatment and rehabilitation may exacerbate demand on stretched health services globally. Knee pain can be influenced by a number of factors; gender, body mass, activity profile, arthrokinematics, patient biopsychosociology and predisposing injury or trauma. Treatment options are typically viewed as pharmacological and non-pharmacological. Exercise and physical therapy are key elements within the latter option, alongside surgical procedures. Knee pain sufferers may vindicate their condition through clinical diagnosis and shift of locus of control; compliance to exercise interventions can depend on the scope of this shift. Such values should be acknowledged when monitoring individualised progression in the management of knee pain. Technology may have a role to play in capturing and influencing compliance within the scope of knee rehabilitation. The main aim of this thesis was to explore the use of innovative rehabilitation interventions for the knee that integrated eHealth, biofeedback and online communities. As this constitutes a complex scenario, this thesis has been reported using elements of the Medical Research Council (MRC) framework for the development and evaluation of complex interventions to improve health (Blackwood et al., 2010; Craig et al., 2008); notably the Preclinical (theory) stage, the Phase I (modelling) stage, and Phase II (exploratory trial). The findings further inform the options for rehabilitation around knee pain, encompassing latest generation techniques for addressing progressive joint disease and eHealth initiatives. These also included options for self-management and reporting that could be generalised to knee pain sufferers; an approach informed by the exploration of the reported experiences of individuals engaging with an online health community for knee pain. The eHealth component of the thesis looked to explore the use of simple Web 2.0 solutions and readily available domiciliary equipment for efficacy and accessibility.
Acupuncture for smoking cessation: A systematic review and meta-analysis of 24 randomized controlled trials

INTRODUCTION We evaluate the effectiveness and safety of transdermal acupuncture by needles for smoking cessation. METHODS A literature search for randomized controlled trials (RCTs) was performed in seven electronic databases from inception to February 2017. Meta-analysis was conducted using Revman 5.3. 0 software. We used either a random effects model (REM) or a fixed effects model (FEM) for pooling data according to the result of a heterogeneity test (defined as significant if I2>75%). Trial sequential analysis (TSA) was applied by TSA 0.9. 5.10 Beta software RESULTS Twenty-four trials involving 3984 participants were included. The methodological quality was generally low. With regard to smoking abstinence, meta-analysis showed acupuncture was more effective compared to no intervention/waiting list for short-term (4 weeks) cessation (1 trial, RR=2.37, 95% 1.41, 3.97) and long-term (longer than 6 months) (2 trials, RR=2.66, 95% CI: 1.50, 4.70). Compared to acupuncture/auricular acupressure alone, acupuncture plus auricular acupressure showed more benefit for short-term cessation (3 trials, RR=1.52, 95% CI: 1.03, 2.25). Acupuncture plus auricular acupressure was more effective compared to sham acupuncture plus sham auricular acupressure for short-term cessation (3 trials, RR=2.50, 95% CI: 1.44, 4.33) and long-term (2 trials, RR=3.61, 95% CI: 1.37, 9.48). Acupuncture in combination with counseling, educational smoking cessation program or moxibustion had more benefit compared to acupuncture for short-term cessation (3 trials, RR=0.75, 95% 0.63, 0.91) and long-term (2 trials, RR=0.77, 95% CI: 0.56, 1.05), and TSA illustrated the cumulative Z-curve of this comparison for long-term across the traditional boundary of 5% significance and monitoring boundaries. No serious adverse events occurred CONCLUSIONS Acupuncture combined with counseling, educational smoking cessation program or moxibustion was more effective than acupuncture as monotherapy with regard to long-term smoking cessation. Further, high quality trials are needed to confirm the result.
Observing the Unobservable. Quantum Interference of Complex Macromolecules

In my laboratory I work on a Kapitza–Dirac–Talbot–Lau interferometer for large and complex molecules. In this interferometer we have demonstrated the quantum interference for the largest objects that have shown quantum interference so far—well, at least we claim it’s quantum interference. Those were molecules with a mass of more than 10,000 atomic mass units, which is about the mass of more than 10,000 hydrogen atoms. The interference pattern that we get looks like that shown in the inset of Fig. 1.