Miracle-dz/UniFAR-FTUs huggingface dataset:
The Requirement for Carotenoids in the Assembly and Function of the Photosynthetic Complexes in Chlamydomonas reinhardtii1[C][W][OA]

We have investigated the importance of carotenoids on the accumulation and function of the photosynthetic apparatus using a mutant of the green alga Chlamydomonas reinhardtii lacking carotenoids. The FN68 mutant is deficient in phytoene synthase, the first enzyme of the carotenoid biosynthesis pathway, and therefore is unable to synthesize any carotenes and xanthophylls. We find that FN68 is unable to accumulate the light-harvesting complexes associated with both photosystems as well as the RC subunits of photosystem II. The accumulation of the cytochrome b6f complex is also strongly reduced to a level approximately 10% that of the wild type. However, the residual fraction of assembled cytochrome b6f complexes exhibits single-turnover electron transfer kinetics comparable to those observed in the wild-type strain. Surprisingly, photosystem I is assembled to significant levels in the absence of carotenoids in FN68 and possesses functional properties that are very similar to those of the wild-type complex.
A taxonomy for financial services selling

The financial services industry accounts for almost half of the country’s nonfarm, commercial profit, making the industry a major driver of the economy. Prior to this study, limited information was available to evaluate financial services sales activities, and a taxonomy of sales activities for individuals in the financial services industry had not previously been conducted. Prior empirically developed sales taxonomies did not include service firms and specifically financial services, while focusing on manufacturing and other product sales. Given that taxonomies are a critical step in scientific inquiry, this is a major limitation in the literature hindering the development of a better understanding of this important industry. Using an established methodology and a seminal sales taxonomy, a financial services sales taxonomy was conducted. Results reflect that financial services sales positions differ from those in other industries. Six sets of sales activities (factors) along with six job positions (clusters) were identified.
Block Relative Gain: Properties and Pairing Rules

Block relative gain (BRG) is a useful method for finding suitable pairings for block decentralized control. In this paper, we present some new algebraic properties of BRG and establish its relation with closed-loop stability, controllability, block diagonal dominance, and interactions. Contrary to published conjecture, we show that strongly interacting systems can have BRG that is nearly the identity matrix. Our results provide simple rules for pairing of variables. We also extend the known method for calculating relative gain array for interacting systems to BRG.
Multitiered Approach Using Quantitative PCR To Track Sources of Fecal Pollution Affecting Santa Monica Bay, California

ABSTRACT The ubiquity of fecal indicator bacteria such as Escherichia coli and Enterococcus spp. in urban environments makes tracking of fecal contamination extremely challenging. A multitiered approach was used to assess sources of fecal pollution in Ballona Creek, an urban watershed that drains to the Santa Monica Bay (SMB) near Los Angeles, Calif. A mass-based design at six main-stem sites and four major tributaries over a 6-h period was used (i) to assess the flux of Enterococcus spp. and E. coli by using culture-based methods (tier 1); (ii) to assess levels of Enterococcus spp. by using quantitative PCR and to detect and/or quantify additional markers of human fecal contamination, including a human-specific Bacteroides sp. marker and enterovirus, using quantitative reverse transcriptase PCR (tier 2); and (iii) to assess the specific types of enterovirus genomes found via sequence analysis (tier 3). Sources of fecal indicator bacteria were ubiquitous, and concentrations were high, throughout Ballona Creek, with no single tributary dominating fecal inputs. The flux of Enterococcus spp. and E. coli averaged 109 to 1010 cells h−1 and was as high at the head of the watershed as at the mouth prior to discharge into the SMB. In addition, a signal for the human-specific Bacteroides marker was consistently detected: 86% of the samples taken over the extent during the study period tested positive. Enteroviruses were quantifiable in 14 of 36 samples (39%), with the highest concentrations at the site furthest upstream (Cochran). These results indicated the power of using multiple approaches to assess and quantify fecal contamination in freshwater conduits to high-use, high-priority recreational swimming areas.
Skin defect detection of pomegranates using color texture features and DWT

Various Skin disorders lower the quality of fruits due to environmental stress such as high temperature and solar radiation some other skin disorders are induced by chemical treatments and pathogens. Skin defect detection is important in the development of automatic grading and sorting system for pomegranate, because manual sorting process is very expensive and time consuming to automate this process skin defect can be identified with the help of color texture feature and discrete wavelet transform. For color texture feature analysis, acquired image is transformed into HSI color space, which is further used for generating SGDM matrix. Total 12 texture features were computed for hue (H), saturation (S) and intensity (I) images from each image samples. Then wavelet transform is used to compute statistical features, Total 3 features were computed for R, G & B components of each image samples. Best features were used as an input to Support Vector Machine (SVM) classifier and tests were performed to identify best classification model. Features showing optimal results were mean (99%), variance (99.80), cluster shade (99.88%), cluster prominence (99.88%), Mean intensity (99.81%).
Leveraging Optimization Methods for Dynamically Assisted Control-Flow Integrity Mechanisms

Dynamic Binary Modification (DBM) tools are useful for cross-platform execution of binaries and are powerful run time environments that allow execution optimizations, instrumentation and profiling. These tools have also been used as enablers for control-flow integrity verification, a process that consists in the observation and analysis of a program's execution path focusing on the detection of anomalies, such as those arising from flow corruption based software attacks. Even though this class of tools helps us in identifying a myriad of attacks, it is typically expensive at run time and introduce significant overhead to the program execution. Considering their inherent high cost, further expanding the capabilities of such tools for detection of program flow anomalies can slow down the analysis to the point that it is unfeasible to run it in real world workflows. In this paper we present a mechanism for including program flow verification in DBMs that uses asynchronous analysis and applies different parallel-programming techniques that leverage current multi-core systems to control the overhead of our analysis. Our mechanism was tested against synthetic program flow corruption use cases and correctly detected all detours. With our new optimizations, we show that our system achieves an slowdown of only 1.46x, while a naively implemented verification system face 4.22x of overhead.
Converting a dependency treebank to a categorial grammar treebank for Italian

The Turin University Treebank (TUT) is a treebank with dependency-based annotations of 2,400 Italian sentences. By converting TUT to binary constituency trees, it is possible to produce a treebank of derivations of Combinatory Categorial Grammar (CCG), with an algorithm that traverses a tree in a top-down manner, employing a stack to record argument structure, using Part of Speech tags to determine the lexical categories. This method reaches a coverage of 77%, resulting in a CCGbank for Italian comprising 1,837 sentences, with an average length of 22,9 tokens. The CCGbank for English has proven to be a useful tool for developing efficient wide-coverage parsers for semantic interpretation, and the Italian CCGbank is expected to be an equally useful linguistic resource for training statistical parsers.
LINKED DATA AND PAGERANK BASED CLASSIFICATION

In this article, we would like to present new approach to classification with Linked Data and PageRank. Our research is focused on classification methods that are enhanced by semantic information. The semantic information can be obtained from ontology or from Linked Data. DBpedia was used as source of Linked Data in our case. Feature selection method is semantically based so features can be recognized by nonprofessional users because they are in a human readable and understandable form. PageRank is used during feature selection and generation phase for expansion of basic features into more general representatives. It means that feature selection and processing is based on a network relations obtained from Linked Data. The features can be used by standard classification algorithms. We will present the promising preliminary results that show the easy applicability of this approach to different datasets.
Real-time Robust Principal Components' Pursuit

In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i. d. sparse outliers is studied and a very elegant solution, principal component pursuit, is proposed. It is motivated as a tool for video surveillance applications with the background image sequence forming the low rank part and the moving objects/persons/abnormalities forming the sparse part. Each image frame is treated as a column vector of the data matrix made up of a low rank matrix and a sparse corruption matrix. Principal component pursuit solves the problem under the assumptions that the singular vectors of the low rank matrix are spread out and the sparsity pattern of the sparse matrix is uniformly random. However, in practice, usually the sparsity pattern and the signal values of the sparse part (moving persons/objects) change in a correlated fashion over time, for e.g., the object moves slowly and/or with roughly constant velocity. This will often result in a low rank sparse matrix. For video surveillance applications, it would be much more useful to have a real-time solution. In this work, we study the online version of the above problem and propose a solution that automatically handles correlated sparse outliers. In fact we also discuss how we can potentially use the correlation to our advantage in future work. The key idea of this work is as follows. Given an initial estimate of the principal directions of the low rank part, we causally keep estimating the sparse part at each time by solving a noisy compressive sensing type problem. The principal directions of the low rank part are updated every-so-often. In between two update times, if new Principal Components' directions appear, the “noise” seen by the Compressive Sensing step may increase. This problem is solved, in part, by utilizing the time correlation model of the low rank part. We call the proposed solution “Real-time Robust Principal Components' Pursuit”. It still requires the singular vectors of the low rank part to be spread out, but it does not require i.i. d. -ness of either the sparse part or the low rank part.
An asynchronous communication scheme for molecular communication

Molecular communications emerge as a promising paradigm for the nano-scale communication in nanotechnology. Though still at an early stage, some research efforts have been made and various molecular communication systems have been proposed. However, existing works mainly focus on the synchronous communication schemes where the synchronous assumption is made for simplifying analyses. In this paper, we propose an asynchronous communication scheme for molecular communications. For the proposed scheme, we make extensive analyses and develop an approximation for channel capacity as a general performance measure which also applies to synchronous systems. Beyond the theoretical analysis, we also examine a specific asynchronous system and compare its performance with synchronous systems to confirm the feasibility of asynchronous molecular communications.
Honeybee nutrition is linked to landscape composition

Declines in insect pollinators in Europe have been linked to changes in land use. Pollinator nutrition is dependent on floral resources (i.e., nectar and pollen), which are linked to landscape composition. Here, we present a stratified analysis of the nutritional composition of beebread in managed honeybee hives with a view to examining potential sources of variation in its nutritional composition. Specifically, we tested the hypothesis that beebread composition correlates with local land use and therefore available floral resources. The results demonstrated that the starch, lipid, and moisture contents of beebread are all highly conserved across hives, whereas levels of protein and nonreducing sugar increased as the year progressed, reducing sugars, however, decreased during the first half of the year and then increased toward the end. Local land use around hives was quantified using data from the Countryside Survey 2007 Land Cover Map. Bee-bread protein content was negatively correlated with increasing levels of arable and horticultural farmland surrounding hives and positively correlated with the cover of natural grasslands and broadleaf woodlands. Reducing sugar content was also positively correlated with the amount of broad-leaved woodland in a 3 Km² radius from the hives. Previous studies on a range of invertebrates, including honeybees, indicate that dietary protein intake may have a major impact on correlates of fitness, including longevity and immune function. The finding that beebread protein content correlates with land use suggests that landscape composition may impact on insect pollinator well-being and provides a link between landscape and the nutritional ecology of socially foraging insects in a way not previously considered.
Planning as needed in BDI systems

BDI systems are robust in dealing with complex and dynamic environments, handling multiple goals arriving dynamically over a time interval and pursuing these goals in parallel where appropriate. BDI agents work with predefined plans or recipes written by the programmer. However in some situations, it can be desirable to do some planning, either as a result of other approaches failing, or in order to look ahead to guide choices at a particular point. We have provided a unified framework that incorporates planning capabilities to suit the intrinsic needs of the BDI architecture. In particular, we leave the choice of when planning should be done, and with what information, to the BDI programmer. Executing the plan is done using regular BDI execution, using advice from the planner. Furthermore, our plan execution model allows the BDI system to maintain control on plan failure, and resume normal BDI execution. Plans are formulated using concepts from both HTN and classical planning disciplines, to provide a more flexible system. We reduce programming overhead required to use planning, by deriving the program to be run by the planner, from the existing BDI program. by converting the required portion of the BDI program into an equivalent planning syntax.
Linear Feature Based Aerial Triangulation

For the past fifteen years line photogrammetry has been an extremely active area of research in the photogrammetry and computer vision communities. It differs from traditional analytical photogrammetry in the nature of the primitives employed in a variety of its fundamental tasks. While in traditional photogrammetry zero-dimensional entities, i.e., points are exclusively used as a driving power in its various orientation and exploitation procedures – in line photogrammetry as the name suggests linear, that is one-dimensional features often corresponding to elongated man-made features in the object space are employed. Of course, that means that no prior correspondence between distinct point in object space and its projection in the image is required and the entire linear feature (with arbitrary geometry) is accommodated in the appropriate mathematical model. However, despite a great effort in that field, only the resection problem, i.e. the solution of the exterior orientation from linear features' correspondences has been thoroughly investigated so far. Two additional fundamental photogrammetric problems space intersection and relative orientation, completing a triple of the most basic photogrammetic procedures needed to support feature-based triangulation have not been adequately addressed in the literature. This paper provides that missing link by presenting a procedure for relative orientation parameters estimation from linear features. We restrict our attention in this paper to planer curves only. We start with the simple idea of optimization procedure using ICP algorithm and proceed to the recovery of the homography matrix induced by the plane of the curve in space.
Development of Terminal and Maternal Economic Selection Indices in Beefmaster Cattle

Two economic selection indices were developed for Beefmaster cattle, one for a terminal objective and one for a maternal objective. For the terminal index it was assumed that bulls will be mated to mature cows with all resulting progeny harvested. For the maternal index it was assumed that bulls will be mated to a combination of heifers and mature cows, with resulting progeny being retained as replacements or sold at weaning. National average prices from 2010 to 2014 were used to establish income and expenses for each system. Economic values were determined by simulating 100,000 animals and approximating the partial derivatives of the profit function by perturbing traits one at a time, by one unit, while holding the other traits constant at their respective means. Relative economic values for the terminal objective traits hot carcass weight (HCW), marbling score (MS), ribeye area (REA), 12 th -rib fat (FAT) and feed intake (FI) were 91.29, 17.01, 8.38, -7.07 and -29.66, respectively. Relative economic values for the maternal objective traits calving difficultly direct (CDd), calving difficulty maternal (CDm), weaning weight direct (WWd), weaning weight maternal (WWm), mature weight (MW) and heifer pregnancy (HP) were -2.11, -1.53, 18.49, 11.28, -33.46 and 1.19, respectively. Selection criteria were chosen from expected progeny differences (EPD) currently reported by Beefmaster Breeders United (BBU). Phenotypic and genetic parameter values among the selection criteria and objective traits were obtained from literature. Index coefficients for EPD of the terminal selection criteria yearling weight
Rethinking the Cooling Out Hypothesis for the 21st Century: The Impact of Financial Aid on Students’ Educational Goals

Background: Most community college students from low-income families have ambitious educational degree goals, but only a small fraction attains them. For many decades, sociologists have primarily attributed this problem to a cooling out process in which college practitioners diminish students’ educational ambitions using academic reorientation processes that encourage the least-promising students to lower their degree goals. The cooling out explanation focuses exclusively on the actions of institutional community college actors rather than other factors affecting student decisions and thus has been used to vilify community colleges as engines of inequality. Objective: This article addresses an alternative hypothesis, considering whether student financial aid, the ubiquitous and multifaceted system that community college actors mainly do not control, influences students’ educational goals. Method and Results: Using data from an experimental study of need-based financial aid in Wisconsin, I find that a private grant program, which triggered a repackaging of students’ financial aid awards, decreased the educational degree aspirations and expectations of 2-year college students, on average. Contributions and Implications: Although counterintuitive, this finding is consistent with the idea that the complex manner in which aid is delivered creates confusion and uncertainty about the actual costs of college. While these lowered degree goals persisted over time, they did not affect degree attainment rates, suggesting students’ expectations may be more malleable and less consequential than prior research suggests. This article demonstrates that the observed cooling out phenomenon is not necessarily the result of a meritocratic sorting system and involves processes previously neglected by sociological theory. A more robust model of college choices is needed.
Anti-ApoE Antibody Given after Plaque Onset Decreases Aβ Accumulation and Improves Brain Function in a Mouse Model of Aβ Amyloidosis

Apolipoprotein E (apoE) is the strongest known genetic risk factor for late onset Alzheimer's disease (AD). It influences amyloid-β (Aβ) clearance and aggregation, which likely contributes in large part to its role in AD pathogenesis. We recently found that HJ6.3, a monoclonal antibody against apoE, significantly reduced Aβ plaque load when given to APPswe/PS1ΔE9 (APP/PS1) mice starting before the onset of plaque deposition. To determine whether the anti-apoE antibody HJ6.3 affects Aβ plaques, neuronal network function, and behavior in APP/PS1 mice after plaque onset, we administered HJ6.3 (10 mg/kg/week) or PBS intraperitoneally to 7-month-old APP/PS1 mice for 21 weeks. HJ6.3 mildly improved spatial learning performance in the water maze, restored resting-state functional connectivity, and modestly reduced brain Aβ plaque load. There was no effect of HJ6.3 on total plasma cholesterol or cerebral amyloid angiopathy. To investigate the underlying mechanisms of anti-apoE immunotherapy, HJ6.3 was applied to the brain cortical surface and amyloid deposition was followed over 2 weeks using in vivo imaging. Acute exposure to HJ6.3 affected the course of amyloid deposition in that it prevented the formation of new amyloid deposits, limited their growth, and was associated with occasional clearance of plaques, a process likely associated with direct binding to amyloid aggregates. Topical application of HJ6.3 for only 14 d also decreased the density of amyloid plaques assessed postmortem. Collectively, these studies suggest that anti-apoE antibodies have therapeutic potential when given before or after the onset of Aβ pathology.
Real-Time Peak Control algorithm using Stochastic Optimization

Battery energy storage systems (BESS) has several uses in electrical system such as peak demand control and energy arbitrage. The benefits of controlling peak can be viewed in both short term and long term. In a long term, it results in a lower electric cost in subsequent years, also it enhances stability and contributes to cost saving in a short term. In this study, we propose a novel Real Time Peak Demand Control, which incorporates a new time series dimensionality reduction technique dubbed TOU base Piecewise Approximation (TPA) for Dynamic Stochastic Optimization. Most peak demand control algorithms employ deterministic approach to controlling peak demand. These methods are not robust and are susceptible to errors. For analysis, we used past load profile obtained from a real site in South Korea. Simulations and the results obtained show that the proposed method achieves a better prediction and as such better peak demand control.