Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectral effects of LEDs on chlorophyll fluorescence and pigmentation in Phalaenopsis 'Vivien' and 'Purple Star'.

We examined the effect of light emitting diode (LED) lighting in greenhouse facilities on growth, chlorophyll fluorescence and pigmentation in Phalaenopsis 'Vivien' and 'Purple Star' under purpose-built LED arrays yielding c. 200 µmol m(-2) s(-1) at plant height for 14 h per day and 24/18°C day/night temperature, respectively, from January to April 2013. The light treatments were (1) 40% blue in 60% red (40% B/R), (2) 0% blue in 100% red (0% B/R) and (3) white LEDs with 32% blue in white (32% B/W, control), with background daylight under shade screens. The plants were harvested twice for leaf growth and pigmentation. There was no clear pattern in the spectral effect on growth since the order of leaf size differed between harvests in March and April. Fv /Fm was in the range of 0.52-0.72, but overall slightly higher in the control, which indicated a permanent downregulation of PSII in the colored treatments. The fluorescence quenching showed no acclimation to color in 'Purple Star', while 'Vivien' had lower ETR and higher NPQ in the 40% B/R, resembling low light acclimation. The pigmentation showed corresponding spectral response with increasing concentration of lutein while increasing the fraction of blue light, which increased the light absorption in the green/yellow part of the spectrum. The permanent downregulation of PSII moved a substantial part of the thermal dissipation from the light regulated NPQ to non-regulated energy losses estimated by ΦNPQ and ΦNO and the difference found in the balance between ΦPSII and ΦNPQ in 'Vivien' disappeared when ΦNO was included in the thermal dissipation.
Mutations in trans-acting factors affecting mRNA decapping in Saccharomyces cerevisiae

The decay of several yeast mRNAs occurs by a mechanism in which deadenylation precedes decapping and subsequent 5'-to-3' exonucleolytic decay. In order to identify gene products required for this process of mRNA turnover, we screened a library of temperature-sensitive strains for mutants with altered mRNA degradation. We identified seven mutations in four genes that inhibited mRNA turnover. Two mutations were alleles of the XRN1 5'-to-3' exoribonuclease known to degrade mRNAs following decapping. One mutation defined a new gene, termed DCP1, which in subsequent work was demonstrated to encode a decapping enzyme or a necessary component of a decapping complex. The other mutations defined two additional genes, termed MRT1 and MRT3 (for mRNA turnover). Mutations in the MRT1 and MRT3 genes slow the rate of deadenylation-dependent decapping, show transcript-specific effects on mRNA decay rates, and do not affect the rapid turnover of an mRNA containing an early nonsense codon, which is degraded by a deadenylation-independent decapping mechanism. Importantly, cell extracts from mrt1 and mrt3 strains contain normal levels of the decapping activity required for mRNA decay. These observations suggest that the products of the MRT1 and MRT3 genes function to modulate the rates of decapping that occur following deadenylation.
Priming perceptivo versus priming conceptual y efectos de los niveles de procesamiento sobre la memoria implícita

Perceptual versus conceptual priming and level-of-processing effects on implicit memory . The aim of this work was to find experimental support for the distinction between perceptual and conceptual forms of priming, in order to provide a coherent account of the differential levels of processing effects on implicit memory tests. We hypothesized that the level-of-processing variable would have clear effects in conceptual priming tests and minimal or even null effects in perceptual priming tests. Three experiments were carried out in which the variable was manipulated between subjects. Confirming our suggestion, the results showed a crossover dissociation between a perceptual priming test (word-stem completion) and a conceptual priming test (generation of exemplars from categories). Moreover, our results questioned the perceptual nature of the wordfragment completion test. These results are discussed from two theoretical approaches (the multiple memory systems view and the transfer-appropriate processing account) and lend support to the distinction between perceptual and conceptual priming.
Research on observation of slight debris in space via space-based imaging radar

Propose a plan of slight space debris observation via space-based imaging radar system previously designed. Based on the idea of differential orbit scan, the investigation focuses on the analyses of orbital scanning period, space area segmentation, radar parameters design and echoes record. In order to cope with weak signals detection, pulse accumulated arithmetic is considered. But because of the relative motion between observation platform and space object as well as the perturbations effected by other forces in space, the signal position in different echoes is dithering. Therefore, three kinds of correlated detection methods are proposed to adjust multiple group echoes. Simulations give the correction results of these methods and then through comparison, the maximum correlation and subsection correlation algorithms are chosen to be applied on the detection of different space environment.
Equivalence of distance-based and RKHS-based statistics in hypothesis testing

We provide a unifying framework linking two classes of statistics used in two-sample and independence testing: on the one hand, the energy distances and distance covariances from the statistics literature; on the other, maximum mean discrepancies (MMD), that is, distances between embeddings of distributions to reproducing kernel Hilbert spaces (RKHS), as established in machine learning. In the case where the energy distance is computed with a semimetric of negative type, a positive definite kernel, termed distance kernel, may be defined such that the MMD corresponds exactly to the energy distance. Conversely, for any positive definite kernel, we can interpret the MMD as energy distance with respect to some negative-type semimetric. This equivalence readily extends to distance covariance using kernels on the product space. We determine the class of probability distributions for which the test statistics are consistent against all alternatives. Finally, we investigate the performance of the family of distance kernels in two-sample and independence tests: we show in particular that the energy distance most commonly employed in statistics is just one member of a parametric family of kernels, and that other choices from this family can yield more powerful tests.
Systematic review and meta-analysis of factors that help or hinder treatment decision-making capacity in psychosis

Background The evidence on factors that may influence treatment decisional capacity (‘capacity’) in psychosis has yet to be comprehensively synthesised, which limits the development of effective strategies to improve or support it. Aims To determine the direction, magnitude and reliability of the relationship between capacity in psychosis and a range of clinical, demographic and treatment-related factors, thus providing a thorough synthesis of current knowledge. Method We conducted a systematic review, meta-analytical and narrative synthesis of factors that help or hinder treatment decision-making capacity in psychosis, assessing the direction, magnitude, significance and reliability of reported associations. Results We identified 23 relevant studies (n = 1823). Psychotic symptoms had small, moderate and strong associations with appreciation, understanding and reasoning respectively. Both verbal cognitive functioning and duration of education had small to moderate correlations with understanding and reasoning. Better capacity was also associated with better insight, better metacognitive ability, higher anxiety and lower perceived coercion. No linear relationship with depression was observed. Interventions linked to improved capacity over time were in-patient care, information simplification, shared decision-making and metacognitive training. Conclusions Although much is known about the role of symptoms and other clinical variables, effective and acceptable psychological interventions to support capacity in this group are lacking.
Accurate estimating simultaneous switching noises by using application specific device modeling

In this paper, we study the simultaneous switching noise problem by using an application-specific modeling method. A simple yet accurate MOSFET model is proposed in order to derive closed-form formulas for simultaneous switching noise voltage waveforms. We first derive a simple formula assuming that the inductances are the only parasitics. Through HSPICE simulation, we show that the new formula is more accurate than previous results based on the same assumption. We then study the effect of the parasitic capacitances of ground bonding wires and pads. We show that the maximum simultaneous switching noise should be calculated using four different formulas depending on the value of the parasitic capacitances and the slope of the input signal. The proposed formulas, modeling both parasitic inductances and capacitances, are within 3% of HSPICE simulation results.
Perceptual Continuity and Naturalness of Expressive Strength in Singing Voices Based on Speech Morphing

This paper experimentally shows the importance of perceptual continuity of the expressive strength in vocal timbre for natural change in vocal expression. In order to synthesize various and continuous expressive strengths with vocal timbre, we investigated gradually changing expressions by applying the STRAIGHT speech morphing algorithm to singing voices. Here, a singing voice without expression is used as the base of morphing, and singing voices with three different expressions are used as the target. Through statistical analyses of perceptual evaluations, we confirmed that the proposed morphing algorithm provides perceptual continuity of vocal timbre. Our results showed the following: (i) gradual strengths in absolute evaluations, and (ii) a perceptually linear strength provided by the calculation of corrected intervals of the morph ratio by the inverse (reciprocal) function of an equation that approximates the perceptual strength. Finally, we concluded that applying continuity was highly effective for achieving perceptual naturalness, judging from the results showing that (iii) our gradual transformation method can perform well for perceived naturalness.
Factor Analysis of Vowel Pronunciation in Swedish Dialects

In this study 91 local Swedish dialects were analysed based on vowel pronunciation. Acoustic measurements of vowel quality were made for 18 vowels of 1,014 speakers by means of principal component analysis of vowel spectra. Two principal components were extracted explaining more than ${\textstyle{3 \over 4}}$ of the total variance in the vowel spectra. Plotting vowels in the PC1-PC2 plane showed a solution with strong resemblance to vowels in a formant plane. Per location averages of all speakers were calculated and factor analysis was run with the 91 locations as data cases and the two acoustic component of the 18 words as variables. Nine factors were extracted corresponding to distinct geographic distribution patterns. The factor scores of the analysis revealed co-occurrence of a number of linguistic features.
The effects of endothelial dysfunction and inflammation on slow coronary flow.

OBJECTIVES We evaluated the effects of endothelial dysfunction and inflammation on slow coronary flow (SCF). STUDY DESIGN The study included 26 patients (group 1; 13 females, 13 males; mean age 58.8 years) who had normal coronary arteries but SCF in three coronary vessels and 25 subjects (group 2, 14 females, 11 males; mean age 62.7 years) with normal coronary arteries and normal flow. Coronary flow was quantified according to the TIMI (Thrombolysis In Myocardial Infarction) frame count method for the left anterior descending (LAD), circumflex (Cx), and right coronary (RCA) arteries. Endothelial function was assessed by plasma asymmetric dimethylarginine (ADMA) levels, brachial artery endothelium-dependent flow-mediated dilatation (FMD), and nitroglycerin-mediated dilatation (NMD). Inflammation was assessed by high-sensitivity C-reactive protein (hs-CRP) levels. RESULTS TIMI frame count was significantly higher in group 1 compared to group 2 for each artery (p<0.001). In group 1, the mean FMD was significantly lower (6.6±1.6% vs. 11.2±1.6%, p<0.001) and the mean ADMA level was significantly higher (0.8±0.2 µmol/l vs. 0.5±0.1 µmol/l, p=0.002), whereas NMD and hs-CRP levels did not differ significantly between the two groups (p>0.05). There was a significant correlation between plasma ADMA level and TIMI frame count (RCA: r=0.50, p=0.001; cLAD: r=0.46, p=0.004; Cx: r=0.32, p=0.04) and a significant negative correlation between FMD and TIMI frame count (cLAD: r=-0.68, p=0.0003; Cx: r=-0.54, p=0.0004; RCA: r=-0.46, p=0.004), but hs-CRP level was not correlated with TIMI frame count. In multivariate analysis, only ADMA (p=0.009) and FMD (p=0.02) were significant parameters to predict SCF. CONCLUSION Our results suggest that endothelial dysfunction as determined by increased ADMA level and impaired FMD, rather than inflammation, plays a role in the etiopathogenesis of SCF.
Video see-through in the clinical practice

In this paper, we discuss potentialities and technological limits to overcome for the introduction in the clinical practice of useful functionalities, using video see-through visualizations, created mixing virtual preoperative information, obtained by means of radiological images, with real patient live images, for procedures where the physician have to interact with the patient (palpation, percutaneous biopsy, catheterism, intervention, etc…).
Exploiting social relationship for secure routing in mobile social networks

Mobile social networks (MSNs) are modern paradigms of delay tolerant networks, which exploit human mobility and consequent wireless contacts between mobile devices to share information in a peer-to-peer manner. Since routing in MSNs depends heavily on the cooperation among participating nodes, selfish or malicious behaviors of nodes impact strongly on the routing performance. In this paper, we introduce the social relationship evaluation method (SRM) for detecting the quality of human social relationship and propose the trustworthy behavior evaluation method (TBM) which exploits recommendations from close friends to detect node's selfish or malicious behaviors. Based on SRM, we define the community of each node as the set of nodes having close social relationships with this node either directly or indirectly, and define the local community centrality to identify influential nodes for message forwarding in the community. Then, we propose SSRS, a novel social-based secure routing strategy, which exploits social relationships to enhance routing security and performance. Simulations have been conducted on the real world data set and results demonstrate that SSRS achieves better performances than the existing algorithms.
Factors That Influence Depressive Symptoms in Mothers of Infants

This study explored the association between interpersonal factors and depressive symptoms in first-time mothers over the first two years of parenthood. An interpersonal style characterized by dependency, recollections of rejection in childhood, and current relationship characteristics was assessed in a nonclinical sample of 133 women. The final model explained 52% of the variance in depressive symptoms at 24 months. Controlling for initial symptom levels, interpersonal variables explained 24% of the outcome variance. The findings suggest that two interpersonal attributes, peer rejection in childhood and a dependent interpersonal style, are particularly important to our understanding of depressive symptomatology.
Substrate conditions that influence the assays used for determining the β‐glucosidase activity of cellulolytic microorganisms

Culture filtrates from Trichoderma harzianum E58, T. reesei CL 847 and Penicillium sp. C 462 were assayed for β‐glucosidase activity using a range of substrates and sugar analysis methods. Although sugar analyses by the dinitrosalicylic acid (DNS) and Nelson–Somogyi methods gave a similar profile, when increasing concentrations of salicin were assayed, considerably higher values were obtained with the DNS assay. The salicin concentration used for the assay greatly influenced the final β‐glucosidase values with higher values obtained for T. harzianum E58 and T. reesei CL 847 at substrate concentrations of 1 mg/mL while optimum values for Penicillium sp. C 462 were obtained at substrate concentrations greater than 3 mg/mL. Low concentrations of salicin and p‐nitro‐phenyl‐β‐D‐glucopyranoside (PNPG) gave the same response as cellobiose. Cellobiose should be used at concentrations greater than 3.74 mg/mL to avoid substrate limitation of the β‐glucosidase assay.
A Segmentation Method for Lung Parenchyma Image Sequences Based on Superpixels and a Self-Generating Neural Forest

Background Lung parenchyma segmentation is often performed as an important pre-processing step in the computer-aided diagnosis of lung nodules based on CT image sequences. However, existing lung parenchyma image segmentation methods cannot fully segment all lung parenchyma images and have a slow processing speed, particularly for images in the top and bottom of the lung and the images that contain lung nodules. Method Our proposed method first uses the position of the lung parenchyma image features to obtain lung parenchyma ROI image sequences. A gradient and sequential linear iterative clustering algorithm (GSLIC) for sequence image segmentation is then proposed to segment the ROI image sequences and obtain superpixel samples. The SGNF, which is optimized by a genetic algorithm (GA), is then utilized for superpixel clustering. Finally, the grey and geometric features of the superpixel samples are used to identify and segment all of the lung parenchyma image sequences. Results Our proposed method achieves higher segmentation precision and greater accuracy in less time. It has an average processing time of 42.21 seconds for each dataset and an average volume pixel overlap ratio of 92.22 ± 4.02% for four types of lung parenchyma image sequences.
Estimating Existence Value for Users and Nonusers of New Jersey Beaches

This study reports empirical evidence on existence value for beach nourishment. The focus is an analysis of respondents who intend to use the beach to be nourished and those who do not. Differences are found among the two groups, but not among categories of nonusers. An application of this result is that surveying can be limited to respondents engaged in the recreation activity being analyzed. Existence value for respondents intending to use the beach was found to include a recreation value component. Our results support the argument that the only valid measure of existence value is the willingness-to-pay amounts of nonusers.
On unbiased sampling for unstructured peer-to-peer networks

This paper presents a detailed examination of how the dynamic and heterogeneous nature of real-world peer-to-peer systems can introduce bias into the selection of representative samples of peer properties (e.g., degree, link bandwidth, number of files shared). We propose the Metropolized Random Walk with Backtracking (MRWB) as a viable and promising technique for collecting nearly unbiased samples and conduct an extensive simulation study to demonstrate that our technique works well for a wide variety of commonly-encountered peer-to-peer network conditions. We have implemented the MRWB algorithm for selecting peer addresses uniformly at random into a tool called ion-sampler. Using the Gnutella network, we empirically show that ion-sampler. yields more accurate samples than tools that rely on commonly-used sampling techniques and results in dramatic improvements in efficiency and scalability compared to performing a full crawl.
TAMEX: a Task-Based Query Execution Framework for Mixed Enterprise Workloads on In-Memory Databases

In-memory database management systems (DBMS) have been proposed to run transactional and analytical applications on a single database instance and to reduce the execution time of complex analytical queries to seconds. The two main reasons for this dramatic performance increase are massive intra-query parallelism on many-core CPUs and primary data storage in main memory. The benefits of these in-memory DBMS for enterprises are huge: analytical applications become largely independent of data staging delays, opening the way for real-time analytics. However, this promising approach will only be adopted, if DBMS can execute dynamically arriving transactional queries in a timely manner, even while complex analytical queries are executed. We believe that two system properties are key to achieve this objective: (1) splitting queries into fine granular atomic tasks and (2) efficiently assigning these tasks to a large number of processing units, thereby considering priorities of query classes. In this paper, we propose TAMEX, a framework for the execution of multiple query classes, designed for executing queries of heterogeneous workloads of enterprise applications on in-memory databases. The basic idea is to generate a task graph for each query during query compilation and assign these tasks to processing units by a user-level scheduler based on priorities. We evaluate the concept using a mix of transactional and join-heavy queries and focus on the impact of task sizes on load balancing and responsiveness of the system.
A novel method to assess angle sensor performance for wearable exoskeletal joint kinematics

Full range of motion (ROM) at a joint is necessary for efficient and adaptive movement; as such, it is an essential clinical evaluation measure for assessing an individual's motor function, which can be affected by any number of musculoskeletal injuries and neuropathies. Measurement of joint ROM in the clinic has classically been accomplished statically through the use of a manual goniometer. More recent efforts in the fields of prosthetics and orthotics have demonstrated the potential utility of wearable systems (e.g., exoskeletons, orthoses) designed to control joint motion(s) and instrumented with sensors capable of capturing joint angle data dynamically. This paper presents a novel methodology to assess the performance of a variety of angle sensors in the context of wearable joint angle measurement, particularly for use in articulated ankle-foot orthoses (AFOs). Dynamic and static errors are considered, and a cost-benefit analysis of a variety of off-the-shelf and custom-built sensors is reported to provide comparative data for selecting a sensor to measure joint motion in wearable exoskeletal systems. All of the sensors considered reported angular errors below 5° across all tests, though the optical encoder consistently demonstrated the highest accuracy (<;0.7°) and precision, and both the resistive potentiometers exhibited the highest error in the dynamic tests (1.5° to 4°). The anisotropic magnetoresistive (AMR) sensor demonstrated the highest performance-to-cost ratio.