Miracle-dz/UniFAR-FTUs huggingface dataset:
Identity and Ecophysiology of Uncultured Actinobacterial Polyphosphate-Accumulating Organisms in Full-Scale Enhanced Biological Phosphorus Removal Plants

ABSTRACT Microautoradiography combined with fluorescence in situ hybridization (MAR-FISH) was used to screen for potential polyphosphate-accumulating organisms (PAO) in a full-scale enhanced biological phosphorus removal (EBPR) plant. The results showed that, in addition to uncultured Rhodocyclus-related PAO, two morphotypes hybridizing with gene probes for the gram-positive Actinobacteria were also actively involved in uptake of orthophosphate (Pi). Clone library analysis and further investigations by MAR-FISH using two new oligonucleotide probes revealed that both morphotypes, cocci in clusters of tetrads and short rods in clumps, were relatively closely related to the genus Tetrasphaera within the family Intrasporangiaceae of the Actinobacteria (93 to 98% similarity in their 16S rRNA genes). FISH analysis of the community biomass in the treatment plant investigated showed that the short rods (targeted by probe Actino-658) were the most abundant (12% of all Bacteria hybridizing with general bacterial probes), while the cocci in tetrads (targeted by probe Actino-221) made up 7%. Both morphotypes took up Pi aerobically only if, in a previous anaerobic phase, they had taken up organic matter from wastewater or a mixture of amino acids. They could not take up short-chain fatty acids (e.g., acetate), glucose, or ethanol under anaerobic or aerobic conditions. The storage compound produced during the anaerobic period was not polyhydroxyalkanoates, as for Rhodocyclus-related PAO, and its identity is still unknown. Growth and uptake of Pi took place in the presence of oxygen and nitrate but not nitrite, indicating a lack of denitrifying ability. A survey of the occurrence of these actinobacterial PAO in 10 full-scale EBPR plants revealed that both morphotypes were widely present, and in several plants more abundant than the Rhodocyclus-related PAO, thus playing a very important role in the EBPR process.
Retrograde lipid traffic in yeast: identification of two distinct pathways for internalization of fluorescent-labeled phosphatidylcholine from the plasma membrane

Digital, video-enhanced fluorescence microscopy and spectrofluorometry were used to follow the internalization into the yeast Saccharomyces cerevisiae of phosphatidylcholine molecules labeled on one acyl chain with the fluorescent probe 7-nitrobenz-2-oxa-1,3-diazol-4-yl (NBD). Two pathways were found: (1) transport by endocytosis to the vacuole and (2) transport by a non-endocytic pathway to the nuclear envelope and mitochondria. The endocytic pathway was inhibited at low temperature (< 2 degrees C) and by ATP depletion. Mutations in secretory (SEC) genes that are necessary for membrane traffic through the secretory pathway (including SEC1, SEC2, SEC4, SEC6, SEC7, SEC12, SEC14, SEC17, SEC18, and SEC21) almost completely blocked endocytic uptake. In contrast, mutations in the SEC63, SEC65, or SEC11 genes, required for translocation of nascent secretory polypeptides into the ER or signal peptide processing in the ER, only slightly reduced endocytic uptake. Phospholipid endocytosis was also independent of the gene encoding the clathrin heavy chain, CHC1. The correlation of biochemical analysis with fluorescence microscopy indicated that the fluorescent phosphatidylcholine was degraded in the vacuole and that degradation was, at least in part, dependent on the vacuolar proteolytic cascade. The non-endocytic route functioned with a lower cellular energy charge (ATP levels 80% reduced) and was largely independent of the SEC genes. Non-endocytic transport of NBD-phosphatidylcholine to the nuclear envelope and mitochondria was inhibited by pretreatment of cells with the sulfhydryl reagents N-ethylmaleimide and p- chloromercuribenzenesulfonic acid, suggesting the existence of protein- mediated transmembrane transfer (flip-flop) of phosphatidylcholine across the yeast plasma membrane. These data establish a link between lipid movement during secretion and endocytosis in yeast and suggest that phospholipids may also gain access to intracellular organelles through non-endocytic, protein-mediated events.
Viral Ecology and the Maintenance of Novel Host Use

Viruses can occasionally emerge by infecting new host species. However, the early phases of emergence can hinge upon ecological sustainability of the virus population, which is a product of both within‐host population growth and between‐host transmission. Insufficient growth or transmission can force virus extinction before the latter phases of emergence, where genetic adaptations that improve host use may occur. We examined the early phase of emergence by studying the population dynamics of RNA phages in replicated laboratory environments containing native and novel host bacteria. To predict the breadth of transmission rates allowing viral persistence on each species, we developed a simple model based on in vitro data for phage growth rate over a range of initial population densities on both hosts. Validation of these predictions using serial passage experiments revealed a range of transmission rates for which the native host was a source and the novel host was a sink. In this critical range of transmission rates, periodic exposure to the native host was sufficient for the maintenance of the viral population on the novel host. We argue that this effect should facilitate adaptation by the virus to utilize the novel host—often crucial in subsequent phases of emergence.
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators. To address this need, we have developed a pooled sequencing approach1,9 and a novel software package1 for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (http://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.
Soft Decision Decoding of Reed-Solomon Codes Using Sphere Decoding

A new soft decision decoding method for Reed-Solomon (RS) codes is proposed. This method uses sphere decoding in an effort to reduce the decoding complexity. With sphere decoding, instead of considering all of the possible transmitted codewords to determine the most probable one, we only consider the codewords whose distances from the received signal are smaller than a specific search radius. This results in a considerable reduction in the complexity. For an (N,K) RS code, we consider a set of K most reliable and independent positions of a codeword and for each of these positions, an ordered list of most probable transmitted symbols in decreasing order of probability is determined. We start from the hard-decision decoded codeword and we try to find more probable codewords. The search is started by selecting a tentative solution consisting of the K most reliable code symbols whose distance from the corresponding symbols in the received vector is less than the search radius. The acceptable values for each of these K code symbols are determined based of the ordered set of most probable transmitted symbols which means that for each code symbol, we start from the most probable one. We re-encode these K code symbols. If the resulting codeword is within the search radius, we add it to the list of the candidate transmitted codewords. The ordering that was discussed earlier will help finding the candidate codewords quickly. Our method results in considerable improvement of the performance of RS codes compared to hard decision decoding with a moderate increase in complexity.
Decision Model for Cloud Computing under SLA Constraints

With the recent introduction of Spot Instances in the Amazon Elastic Compute Cloud (EC2), users can bid for resources and thus control the balance of reliability versus monetary costs. A critical challenge is to determine bid prices that minimize monetary costs for a user while meeting Service Level Agreement (SLA) constraints (for example, sufficient resource availability to complete a computation within a desired deadline). We propose a probabilistic model for the optimization of monetary costs, performance, and reliability, given user and application requirements and dynamic conditions. Using real instance price traces and workload models, we evaluate our model and demonstrate how users should bid optimally on Spot Instances to reach different objectives with desired levels of confidence.
Amantadine Reduces Mania in Borna Disease Virus-Infected Non-Psychotic Bipolar Patients

This study investigated the clinical use and safety of amanta-dine in acute mania in an on-off-on design. Amantadine was augmented (200 mg / day) to pre-treatment strategies for 6 days, stopped for 6 days, and administered for another 6 days (on-off-on) in 10 manic inpatients. Manic symptoms were reduced in the ﬁ rst study period (on) by 45.8 % [Young Mania Rating Scale (YMRS)]. Eight patients also ﬁ nished the second period (off) which was not paralleled by any further reduction of mania. The third study period (on) was ﬁ nished by seven patients with a further decrease of about 61.5 % . The overall reduction from baseline after 18 days was 79.2 % in this group. Amantadine augmentation reduced severe hypomania and moderate mania in BDV-infected bipolar I or II patients and was very well tolerated, especially no psychotic symptoms were observed.
Dietary glycaemic index and glycaemic load and upper gastrointestinal disorders: results from the SEPAHAN study

BACKGROUND Little is known about the effects of carbohydrate, particularly any association between dietary glycaemic index or glycaemic load and uninvestigated heartburn or uninvestigated chronic dyspepsia in the community. The present study aimed to determine associations between dietary glycaemic index or glycaemic load and uninvestigated heartburn or uninvestigated chronic dyspepsia. METHODS This cross-sectional study was conducted in 2987 adults. Dietary glycaemic index and glycaemic load were estimated using a validated food-frequency questionnaire. Uninvestigated heartburn and uninvestigated chronic dyspepsia were determined using a modified and validated version of the Rome III questionnaire. RESULTS After controlling for various confounders, high glycaemic load was associated with an increased risk of uninvestigated heartburn [odds ration (OR) = 1.75; 95% confidence interval CI = 1.03, 2.97; P = 0.04] and uninvestigated chronic dyspepsia (OR = 2.14; 95% CI: 1.04, 4.37; P = 0.04) in men but not in women. In normal-weight individuals, high glycaemic index was related to an increased risk of uninvestigated heartburn (OR = 1.52; 95% CI: 1.07, 2.15; P = 0.02) and high glycaemic load to an increased risk of uninvestigated chronic dyspepsia (OR=1.78; 95% CI: 1.05, 3.01; P = 0.03). No significant associations were observed in subjects with excess body weight. CONCLUSIONS Our data suggest that there are body mass index- and sex-specific associations between dietary carbohydrate quality with uninvestigated heartburn and uninvestigated chronic dyspepsia.
Numbers of the di ¡ erent types of behavioural comparisons between infected and uninfected hosts used in the analysis

New scienti¢c paradigms often generate an early wave of enthusiasm among researchers and a barrage of studies seeking to validate or refute the newly proposed idea. All else being equal, the strength and direction of the empirical evidence being published should not change over time, allowing one to assess the generality of the paradigm based on the gradual accumulation of evidence. Here, I examine the relationship between the magnitude of published quantitative estimates of parasite-induced changes in host behaviour and year of publication from the time the adaptive host manipulation hypothesis was ¢rst proposed. Two independent data sets were used, both originally gathered for other purposes. First, across 137 comparisons between the behaviour of infected and uninfected hosts, the estimated relative in£uence of parasites correlated negatively with year of publication. This e¡ect was contingent upon the transmission mode of the parasites studied. The negative relationship was very strong among studies of parasites which bene¢t from host manipulation (transmission to the next host occurs by predation on an infected intermediate host), i.e. among studies which were explicit tests of the adaptive manipulation hypothesis. There was no correlation with year of publication among studies on other types of parasites which do not seem to receive bene¢ts from host manipulation. Second, among14 estimates of the relative, parasite-mediated increase in transmission rate (i.e. increases in predation rates by de¢nitive hosts on intermediate hosts), the estimated in£uence of parasites again correlated negatively with year of publication. These results have several possible explanations, but tend to suggest biases with regard to what results are published through time as accepted paradigms changed.
Planning for Autonomous Cars that Leverage Effects on Human Actions

—Traditionally, autonomous cars make predictions about other drivers’ future trajectories, and plan to stay out of their way. This tends to result in defensive and opaque behaviors. Our key insight is that an autonomous car’s actions will actually affect what other cars will do in response, whether the car is aware of it or not. Our thesis is that we can leverage these responses to plan more efﬁcient and communicative behaviors. We model the interaction between an autonomous car and a human driver as a dynamical system, in which the robot’s actions have immediate consequences on the state of the car, but also on human actions. We model these consequences by approximating the human as an optimal planner, with a reward function that we acquire through Inverse Reinforcement Learning. When the robot plans with this reward function in this dynamical system, it comes up with actions that purposefully change human state: it merges in front of a human to get them to slow down or to reach its own goal faster; it blocks two lanes to get them to switch to a third lane; or it backs up slightly at an intersection to get them to proceed ﬁrst. Such behaviors arise from the optimization, without relying on hand-coded signaling strategies and without ever explicitly modeling communication. Our user study results suggest that the robot is indeed capable of eliciting desired changes in human state by planning using this dynamical system.
Factors associated with poor academic achievement among urban primary school children in Malaysia.

INTRODUCTION The aim of this study was to identify factors associated with poor academic achievement during the early school years. METHODS This was a cross-sectional study of urban Primary Two children. Sociodemographic and medical data were obtained from questionnaires and interviews. Achievement was based on marks obtained in the core subjects of the Primary One examination. All students underwent the Raven's Standard Progressive Matrices test as a general measure of cognitive ability, audiometry and visual tests, and standardised measurements of weight and height. RESULTS Out of 1,470 eligible children, 206 (14 percent) had poor academic achievement. Of the 919 children who participated in the study, 111 (12.1 percent) had poor achievement compared with 95 (17.2 percent) of the 551 non-participants. Using logistic regression analysis, the factors that were found to be independently associated with poor academic achievement were lower mean Raven scores (p-value is less than 0.001), lower mean socioeconomic status scores (p-value is less than 0.001), larger sibship size (p-value is 0.031), male gender (odds ratio [OR] 1.7; 95 percent confidence interval [CI] 1.1-2.65) and a history of prematurity (OR 14; 95 percent CI 2-97.8). CONCLUSION Cognitive ability, gender, prematurity and social factors contribute to poor academic achievement during the early school years. The higher proportion of poor achievers among non-participants warrants further attention.
Dynamics of Fiscal Financing in the United States

Dynamic stochastic general equilibrium models that include policy rules for government spending, lump-sum transfers, and distortionary taxation on labor and capital income and on consumption expenditures are fit to U.S. data under a variety of specifications of fiscal policy rules. We obtain several results. First, the best fitting model allows a rich set of fiscal instruments to respond to stabilize debt. Second, responses of aggregate variables to fiscal policy shocks under rich fiscal rules can vary considerably from responses that allow only non-distortionary fiscal instruments to finance debt. Third, based on estimated policy rules, transfers, capital tax rates, and government spending have historically responded strongly to government debt, while labor taxes have responded more weakly. Fourth, all components of the intertemporal condition linking debt to expected discounted surpluses---transfers, spending, tax revenues, and discount factors---display instances where their expected movements are important in establishing equilibrium. Fifth, debt-financed fiscal shocks trigger long lasting dynamics so that short-run multipliers can differ markedly from long-run multipliers, even in their signs.
E-commerce purchase prediction approach by user behavior data

while e-commerce has grown quickly in recent years, more and more people are used to utilize this popular channel to purchase products and services on the Internet. Therefore, it becomes very important for shopping sites to predict precisely which items their customers would buy so as to increase sales or improve customer satisfaction. Traditional algorithms such as Collaborative Filtering, has been very popular in predicting users' preferences in movie, book, or music recommendation areas, but they face the problem that rating data is very sparse or even not available in shopping domain. Compared to the small amount of ratings in e-commerce shopping sites, the quantity of user clicking data is abundant and also contains sufficient information about users' purchase preferences. Therefore, in this paper we propose a prediction method based on probability statistics making use of user clicking behavior data. To evaluate the proposed approach, we use the data set provided by Ali Mobile Recommendation Competition held in 2015 which consisted of the huge amount of the clicking behavior log from 10,000 mobile users in one month. The experimental results show that our proposed method significantly alleviates the problem of data sparseness which traditional algorithms fail to deal with.
Repair of Multiple Descriptions on Distributed Storage

In multiple descriptions on distributed storage, a source is stored in a shared fashion on multiple servers. When a subset of servers are contacted, the source should be estimated with a certain maximum distortion depending on the number of servers. The problem considered in this paper is how to restore the system operation when one of the servers fail and a new server replaces it, that is, repair. The requirement is that the distortions in the restored system should be no more than in the original system. The question is how many extra bits are needed for repair. We find the optimum solution for a two server problem in the Gaussian case, and an achievable rate for general n nodes. One conclusion is that it is necessary to design the multiple description codes with repair in mind.
Mobility aware topology control framework for dynamic multi-robot networks

Multi-robot networks used in surveillance, industrial manufacturing, defense and distributed monitoring require maximal coverage and connectivity while adapting to changes in environmental and channel conditions. Traditional algorithms attempt at solving this issue using deployment schemes and power control. In the case of mobile robot networks, the additional degree of freedom rendered by the mobility of the robots can additionally be used. In this paper we introduce a novel robot topology control mechanism aiming at maximizing coverage, connectivity and reliability using an irregular hexagonal static/mobile multi-robot deployment scheme. Experimental data, along with simulation results demonstrate connectivity enhancement under signal loss.
Title Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio Permalink

[1] Degree of oxidation of organic carbon (Cox) is a fundamental property of the carbon cycle, reflecting the synthesis and decomposition of natural organic matter. Cox is also related to ecosystem oxidative ratio (OR), the molar ratio of O2 to CO2 fluxes associated with net ecosystem exchange (NEE). Here we compare two methods for measuring Cox and OR: (1) %C, %H, %N, and %O elemental analysis, and (2) heat of combustion (DHc) measured by means of bomb calorimetry coupled with %C elemental analysis (hereafter referred to as calorimetry). Compared with %C, %N, %H, and %O elemental analysis, calorimetry generates Cox and OR data more rapidly and cheaply. However, calorimetric measurements yield less accurate Cox and OR data. We additionally report Cox and OR data for a pair of biomass standards and a suite of biomass samples. The OR values we measured in these samples were less variable than OR data reported in the literature (generated by simultaneous measurement of ecosystem O2 and CO2 gas mixing ratios). Our biomass OR values had a mean of 1.03 and range of 0.99–1.06. These estimates are lower than the OR value of 1.10 that is often used to partition uptake of fossil fuel CO2 between the ocean and the terrestrial biosphere.