Miracle-dz/UniFAR-FTUs huggingface dataset:
Feeding by the Newly Described Mixotrophic Dinoflagellate Paragymnodinium shiwhaense: Feeding Mechanism, Prey Species, and Effect of Prey Concentration

ABSTRACT. To investigate the feeding by the newly described mixotrophic dinoflagellate Paragymnodinium shiwhaense (GenBank accession number=AM408889), we explored the feeding process and the kinds of prey species that P. shiwhaense is able to feed on using several different types of microscopes, including a transmission electron microscope and high‐resolution video‐microscopy. In addition, we measured the growth and ingestion rates of P. shiwhaense on its optimal algal prey Amphidinium carterae as a function of prey concentration. We also measured these parameters for edible prey at a single concentration at which the growth and ingestion rates of P. shiwhaense on A. carterae were saturated. Paragymnodinium shiwhaense feed on algal prey using a peduncle after anchoring the prey by a tow filament. Among the algal prey offered, P. shiwhaense ingested small algal species that had equivalent spherical diameters (ESDs) ≤11 μm (e.g. the prymnesiophyte Isochrysis galbana, the cryptophytes Teleaulax sp. and Rhodomonas salina, the raphidophyte Heterosigma akashiwo, and the dinoflagellates Heterocapsa rotundata and A. carterae). However, it did not feed on larger algal species that had ESDs ≥12 μm (e.g. the dinoflagellates Prorocentrum minimum, Heterocapsa triquetra, Scrippsiella trochoidea, Alexandrium tamarense, Prorocentrum micans, Gymnodinium catenatum, Akashiwo sanguinea, and Lingulodinium polyedrum) or the small diatom Skeletonema costatum. The specific growth rates for P. shiwhaense feeding upon A. carterae increased rapidly with increasing mean prey concentration before saturating at concentrations of ca. 350 ng C/ml (5,000 cells/ml). The maximum specific growth rate (i.e. mixotrophic growth) of P. shiwhaense on A. carterae was 1.097/d at 20 °C under a 14:10 h light–dark cycle of 20 μE/m2/s, while its growth rate (i.e. phototrophic growth) under the same light conditions without added prey was −0.224/d. The maximum ingestion and clearance rates of P. shiwhaense on A. carterae were 0.38 ng C/grazer/d (5.4 cells/grazer/d) and 0.7 μl/grazer/h, respectively. The calculated grazing coefficients for P. shiwhaense on co‐occurring Amphidinium spp. was up to 0.07/h (i.e. 6.7% of the population of Amphidinium spp. was removed by P. shiwhaense populations in 1 h). The results of the present study suggest that P. shiwhaense can have a considerable grazing impact on algal populations.
Protein Kinase A Phosphorylates Titin’s Cardiac-Specific N2B Domain and Reduces Passive Tension in Rat Cardiac Myocytes

&bgr;-Adrenergic stimulation of cardiac muscle activates protein kinase A (PKA), which is known to phosphorylate proteins on the thin and thick filaments of the sarcomere. Cardiac muscle sarcomeres contain a third filament system composed of titin, and here we demonstrate that titin is also phosphorylated by the &bgr;-adrenergic pathway. Titin phosphorylation was observed after &bgr;-receptor stimulation of intact cardiac myocytes and incubation of skinned cardiac myocytes with PKA. Mechanical experiments with isolated myocytes revealed that PKA significantly reduces passive tension. In vitro phosphorylation of recombinant titin fragments and immunoelectron microscopy suggest that PKA targets a subdomain of the elastic segment of titin, referred to as the N2B spring element. The N2B spring element is expressed only in cardiac titins, in which it plays an important role in determining the level of passive tension. Because titin-based passive tension is a determinant of diastolic function, these results suggest that titin phosphorylation may modulate cardiac function in vivo.
Pestalotioid fungi from Restionaceae in the Cape Floral Kingdom

Eight pestalotioid fungi were isolated from the Restionaceae growing in the Cape Floral Kingdom of South Africa. Sarcostroma restionis, Truncatella megaspora, T. restionacearum and T. spadicea are newly described. New records include Pestalotiopsis matildae, Sarcostroma lomatiae, Truncatella betulae and T. hartigii. To resolve generic affiliations, phylogenetic analyses were performed on ITS (ITS1, 5.8S, ITS2) and part of 28S rDNA. DNA data support the original generic concept of Truncatella, which encompasses Pestalotiopsis species having 3-septate conidia. The genus Sarcostroma is retained as separate from Seimatosporium.
Male Hypogonadism and Osteoporosis: The Effects, Clinical Consequences, and Treatment of Testosterone Deficiency in Bone Health

It is well recognized that bone loss accelerates in hypogonadal states, with female menopause being the classic example of sex hormones affecting the regulation of bone metabolism. Underrepresented is our knowledge of the clinical and metabolic consequences of overt male hypogonadism, as well as the more subtle age-related decline in testosterone on bone quality. While menopause and estrogen deficiency are well-known risk factors for osteoporosis in women, the effects of age-related testosterone decline in men on bone health are less well known. Much of our knowledge comes from observational studies and retrospective analysis on small groups of men with variable causes of primary or secondary hypogonadism and mild to overt testosterone deficiencies. This review aims to present the current knowledge of the consequences of adult male hypogonadism on bone metabolism. The direct and indirect effects of testosterone on bone cells will be explored as well as the important differences in male osteoporosis and assessment as compared to that in females. The clinical consequence of both primary and secondary hypogonadism, as well as testosterone decline in older males, on bone density and fracture risk in men will be summarized. Finally, the therapeutic options and their efficacy in male osteoporosis and hypogonadism will be discussed.
Rectifying projective distortion in 4D light field

The accuracy of calibration will significantly affect the post processing capability of light field imaging. The geometry of the reconstructed scene is related to the parameters of light field closely, involving the accuracy of decoded rays and ambiguities from ray correspondences. Through exploring the ray correspondence, we derive a transformation matrix to describe the projective distortion on reconstructed scene in 4D light field. Based on our derivation, we simplify the light field camera geometry as a 4-parameter model and calibrate its intrinsic parameters, including a linear initialization and a nonlinear refine process. The proposed light field calibration can simply be implemented with a parallel bi-planar board. Experiments on both simulation and real scene data validate the performance of the calibration.
Oblivious lattice codes for Gaussian relay channels

Consider a slowly fading Gaussian relay channel where the source is not aware of channel state information (CSI) and the relay is only partially aware of CSI. As a single cooperation strategy, Decode-and-Forward (DF) or Compress-and-Forward (CF), is not the best for all channel states, the relay should be able to switch between them according to its CSI. However as the source cannot be aware of chosen cooperative strategy, it should use so called oblivious codes that perform equally well under different cooperative strategies. In this paper, we prove that doubly nested lattice codes is an oblivious code which can be used to achieve DF, CF or point-to-point rate in the relay channels. Using the oblivious lattice coding, the relay, according to its CSI, decides to use DF, CF or no cooperation at all. We show that inner bound on outage probability is significantly improved if the oblivious lattice code is used with selective coding strategy at the relay.
A Time-delay Cascading Neural Network Architecture for Modeling Time-dependent predictor in onset Prediction

The occurrence of rain before the real start of a r ainy season often mislead farmers into thinking tha t rainy season has started and suggesting them to start pla nting immediately. In reality, rainy season has not started yet, causing the already-planted rice seed to exper ience dehydration. Therefore, a model that can pred ict the onset of rainy season is required, so that draught disaster can be avoided. This study presents Time D elayCascading Neural Network (TD-CNN) which deals with situations where the response variable is determined by a number of time-dependent inter-rela ted predictors. The proposed model is used to predi ct the onset in Pacitan District Indonesia based on So uthern Oscillation Index (SOI). The Leave One Out (LOO) cross-validation with series data 1982-2012 a re used in order to compare the accuracy of the proposed model with the Back-Propagation Neural Network (BPNN) and Cascading Neural Network (CNN). The experiment shows that the accuracy of the proposed model is 0.74, slightly above than the t wo other models, BPNN and CNN which are 0.71 and 0.72, respectively.
A real-time rescue system: Towards practical implementation of robotic sensor network

A real-time monitor and rescue system must be able to both quickly and reliably detect the event happening in its monitoring region. Furthermore, it is required to fulfill certain rescue mission, e.g., navigate victims to exit through safe path in case of emergency. Current monitor and rescue approaches generally rely on either teleoperated robots, or teams of wireless robots. Typically the robots used in these systems tend to have high cost which make them unpractical in large scale deployment and applications. In this work, we present a realtime monitor and rescue system, TelosW-Bot Net, utilizing integrated networks. The integrated network is an integration of stationary sensor networks and robots: static sensor networks comprised of large numbers of small, simple, and inexpensive wireless sensors, and the robots which can communicate and controlled by sensor nodes. We demonstrate the efficacy of our system in real test bed composed of 46 sensors, which is one of the largest robotic sensor network to our knowledge, providing empirical results.
An Early Nodulin-Like Protein Accumulates in the Sieve Element Plasma Membrane of Arabidopsis1[OA]

Membrane proteins within the sieve element-companion cell complex have essential roles in the physiological functioning of the phloem. The monoclonal antibody line RS6, selected from hybridomas raised against sieve elements isolated from California shield leaf (Streptanthus tortuosus; Brassicaceae) tissue cultures, recognizes an antigen in the Arabidopsis (Arabidopsis thaliana) ecotype Columbia that is associated specifically with the plasma membrane of sieve elements, but not companion cells, and accumulates at the earliest stages of sieve element differentiation. The identity of the RS6 antigen was revealed by reverse transcription-PCR of Arabidopsis leaf RNA using degenerate primers to be an early nodulin (ENOD)-like protein that is encoded by the expressed gene At3g20570. Arabidopsis ENOD-like proteins are encoded by a multigene family composed of several types of structurally related phytocyanins that have a similar overall domain structure of an amino-terminal signal peptide, plastocyanin-like copper-binding domain, proline/serine-rich domain, and carboxy-terminal hydrophobic domain. The amino- and carboxy-terminal domains of the 21.5-kD sieve element-specific ENOD are posttranslationally cleaved from the precursor protein, resulting in a mature peptide of approximately 15 kD that is attached to the sieve element plasma membrane via a carboxy-terminal glycosylphosphatidylinositol membrane anchor. Many of the Arabidopsis ENOD-like proteins accumulate in gametophytic tissues, whereas in both floral and vegetative tissues, the sieve element-specific ENOD is expressed only within the phloem. Members of the ENOD subfamily of the cupredoxin superfamily do not appear to bind copper and have unknown functions. Phenotypic analysis of homozygous T-DNA insertion mutants for the gene At3g20570 shows minimal alteration in vegetative growth but a significant reduction in the overall reproductive potential.
Genes, psychological traits and civic engagement

Civic engagement is a classic example of a collective action problem: while civic participation improves life in the community as a whole, it is individually costly and thus there is an incentive to free ride on the actions of others. Yet, we observe significant inter-individual variation in the degree to which people are in fact civically engaged. Early accounts reconciling the theoretical prediction with empirical reality focused either on variation in individuals’ material resources or their attitudes, but recent work has turned to genetic differences between individuals. We show an underlying genetic contribution to an index of civic engagement (0.41), as well as for the individual acts of engagement of volunteering for community or public service activities (0.33), regularly contributing to charitable causes (0.28) and voting in elections (0.27). There are closer genetic relationships between donating and the other two activities; volunteering and voting are not genetically correlated. Further, we show that most of the correlation between civic engagement and both positive emotionality and verbal IQ can be attributed to genes that affect both traits. These results enrich our understanding of the way in which genetic variation may influence the wide range of collective action problems that individuals face in modern community life.
Sugar sensing by enterocytes combines polarity, membrane bound detectors and sugar metabolism

Sugar consumption and subsequent sugar metabolism are known to regulate the expression of genes involved in intestinal sugar absorption and delivery. Here we investigate the hypothesis that sugar‐sensing detectors in membranes facing the intestinal lumen or the bloodstream can also modulate intestinal sugar absorption. We used wild‐type and GLUT2‐null mice, to show that dietary sugars stimulate the expression of sucrase‐isomaltase (SI) and L‐pyruvate kinase (L‐PK) by GLUT2‐dependent mechanisms, whereas the expression of GLUT5 and SGLT1, did not rely on the presence of GLUT2. By providing sugar metabolites, sugar transporters, including GLUT2, fuelled a sensing pathway. In Caco2/TC7 enterocytes, we could disconnect the sensing triggered by detector from that produced by metabolism, and found that GLUT2 generated a metabolism‐independent pathway to stimulate the expression of SI and L‐PK. In cultured enterocytes, both apical and basolateral fructose could increase the expression of GLUT5, conversely, basolateral sugar administration could stimulate the expression of GLUT2. Finally, we located the sweet‐taste receptors T1R3 and T1R2 in plasma membranes, and we measured their cognate Galpha Gustducin mRNA levels. Furthermore, we showed that a T1R3 inhibitor altered the fructose‐induced expression of SGLT1, GLUT5, and L‐PK. Intestinal gene expression is thus controlled by a combination of at least three sugar‐signaling pathways triggered by sugar metabolites and membrane sugar receptors that, according to membrane location, determine sugar‐sensing polarity. This provides a rationale for how intestine adapts sugar delivery to blood and dietary sugar provision. J. Cell. Physiol. 213:834–843. © 2007 Wiley‐Liss, Inc.
An RNN-based preclassification method for fast continuous Mandarin speech recognition

A novel recurrent neural network-based (RNN-based) front-end preclassification scheme for fast continuous Mandarin speech recognition is proposed. First, an RNN is employed to discriminate each input frame for the three broad classes of initial, final, and silence. A finite state machine (FSM) is then used to classify the input frame into four states including three stable states of initial (I), final (F), and silence (S), and a transient (T) state. The decision is made based on examining whether the RNN discriminates well between classes. We then restrict the search space for the three stable states in the following DP search to speed up the recognition process. The efficiency of the proposed scheme was examined by simulations in which we incorporate it with a hidden Markov model-based (HMM-based) continuous 411 Mandarin based-syllables recognizer. The experimental results showed that it can be used in conjunction with the beam search to greatly reduce the computational complexity of the HMM recognizer while keeping the recognition rate almost undegraded.
Singular value decomposition applied to 4D SAR imaging

This paper discusses the application of the Singular Value Decomposition for analysis and regularization in 4D, space-time SAR imaging. The technique is validated with simulated data. Very preliminary results, obtained by using ERS data are also presented. Multibaseline Interferometry, Tomography, 4D SAR Imaging, Differential-Tomography, Linear Inverse Problems
Predictive Toxicity of Conventional Triazole Pesticides by Simulating Inhibitory Effect on Human Aromatase CYP19 Enzyme

15 common fungicides were evaluated to study their inhibitory effects on the human aromatase enzyme in comparison with the Letrozole LTZ, the most potent inhibitor of aromatase AI used as anti-estrogen for breast cancer treatment using AUTODOCK software for calculation of inhibition energy on CYP19A1 aromatase enzyme. Those compounds with minimal binding energy are safer in terms of toxicity and resistance of other prescription drugs like non-steroid AIs. In the authors' study, they found that four triazole fungicides compounds, Triticonazole, Tebuconazole, Metconazole and Fluquinconazole, exhibited minimal inhibition constant IC.
PVDF-based ferroelectric polymers and dielectric elastomers for sensor and actuator applications: a review

Electroactive polymers (EAPs) are materials that respond to electrical stimulation by exhibiting significantly large strains (to a maximum of a few hundred %) and vice versa. Thanks to their unique behaviors, EAPs have been widely and increasingly applied for sensing and actuating applications. EAPs are a promising material with many attractive properties such as fast electro-mechanical response, high mechanical and chemical stability, flexibility, low modulus, high strain capabilities, and shape adaptability. These features make them attractive for innovative applications such as wearable fabric sensors for IoT products and artificial muscles as bio-friendly actuators. In this article, we have presented a brief overview of electronic EAPs, especially PVDF-based materials, dielectric elastomers such as silicone and acrylic materials for sensors and actuators by focusing on their operation mechanisms and applications.
The Refined Algorithm ReCDRG to Construct DRG Graph for Object-Oriented Class-Level Testing

In order to ensure reliability and quality, software systems must be tested. It is more difficult to test object-oriented software systems than testing procedure-oriented software systems. We have systematically proposed a new methodology, named B&W, for testing object-oriented software at the class level, which was published in ACM Transactions on Software Engineering and Methodology (Vol.7 No.3 pp.250-295). B&W methodology uses Data member Relevance Graph (DRG) to determine observational equivalence of two objects generated by executing two equivalent terms of the given class. (Each term is a syntactically legal operations sequence). If these two objects are not observational equivalent, then an error is revealed. In this paper, we refine the algorithm for constructing the DRG of the given class. This refinement enhances the effectiveness of B&W methodology greatly.
Reordering Query Execution in Tertiary Memory Databases

In the relational model the order of fetching data does not affect query correctness. This flexibility is exploited in query optimization by statically reordering data accesses. However, once a query is optimized, it is executed in a fixed order in most systems, with the result that data requests are made in a fixed order. Only limited forms of runtime reordering can be provided by low-level device managers. More aggressive reordering strategies are essential in scenarios where the latency of access to data objects varies widely and dynamically, as in tertiary devices. This paper presents such a strategy. Our key innovation is to exploit dynamic reordering to match execution order to the optimal data fetch order, in all parts of the plan-tree. To demonstrate the practicality of our approach and the impact of our optimizations, we report on a prototype implementation based on Postgres. Using our system, typical I/O cost for queries on tertiary memory databases is as much as an order of magnitude smaller than with conventional query processing techniques.
Mathematical models of social norms and petty corruption

Corruption is a problem all around the world, but the extent of the problem varies between countries and situations. In this thesis, I focus on how corruption levels can change when they are culturally determined. For this reason, I study the dynamics of the cultural underpinnings: social norms and conventions.The dissertation consists of six papers. In the first paper, I expand a common definition of social norms. The aim of the extension is to capture the fact that the scope of a social norm may be larger than just a single specific situation. I introduce a similarity measure and develop a mathematical model according to which all situations' social norms are interconnected, and affect each other, but those situations that are most similar and most recent have the greatest normative effect on a current situation. Given this model I test the effect of bringing about norm change by temporarily dismantling institutions and then reestablishing them.In the second paper, I show in a mathematical model how it is possible to design fine and reward mechanisms that make it superfluous for individuals to form beliefs about how others will act. Through this mechanism, it should be possible to circumvent the problem that norm change typically will be successful only if it is synchronized across a large part of the population.In the third paper, I and my co-authors, first conducted a survey. The results of which demonstrate that there is a general tendency among people to consider themselves to be less prone to corrupt behavior than the average person. Such an "everyone-is-better-than-average" effect is a well-established phenomenon in social psychology but not previously demonstrated in the corruption domain. We then show in a mathematical model that such systematic biases in estimation of own versus others' corruption make it more difficult to achieve norm change in the direction of less corruption.In the fourth and fifth paper we again consider the "everyone-is-better-than-average" effect and see how in certain value based groups the effect can be reversed. This changes the insight from the third paper slightly.The last paper considers a classic question of how a collective can succeed in collective action when it is risky to be among the first individuals to act. I and my co-author investigate how the collective can benefit from access to a set of signal acts that signal an individual's level of commitment to the collective cause. The problem is modeled as a threshold model where an individual's inclination to conduct a specific act depends on the previous commitment level in the population.