Miracle-dz/UniFAR-FTUs huggingface dataset:
Response of heterotrophic bacteria, autotrophic picoplankton and heterotrophic nanoflagellates to re-oligotrophication

We investigated the response of the microbial components of the pelagic food web to re-oligotrophication of large, deep Lake Constance where total phosphorus concentrations during mixing decreased from a maximum of 2.81 mmol L 1 in 1979 via 1.87 mmol L 1 in 1987 to 0.26 mmol L 1 in 2007. Measurements of heterotrophic bacteria, autotrophic picoplankton (APP) and heterotrophic nanoflagellates (HNF) in 2006 and 2007 were compared to values from 1987 to 1997. We hypothesized that the biomass and seasonal variability of all groups will decrease under more oligotrophic conditions due to reduced resource availability, particularly for APP and HNF but less for the competitively stronger bacteria. Average bacterial biomass between spring and autumn was unrelated to phosphorus, whereas the ratio of bacterial biomass to chlorophyll a concentration increased with decreasing trophy due to declining chlorophyll concentrations. In contrast, a unimodal relationship was found between APP and phosphorus with low biomass at low and high phosphorus concentrations and maximum biomass in between. Average HNF biomass decreased strongly by a factor of 10 30 with decreasing trophy, and chlorophyll-specific HNF biomass was unimodally related to phosphorus. The relative seasonal biomass variability did not change for any group during re-oligotrophication. To conclude, HNF responded much more strongly and bacteria less so than chlorophyll concentrations to oligotrophication, whereas APP exhibited a more complex pattern.
Urinary Sucrose and Fructose as Biomarkers for Sugar Consumption

The use of 24-hour urinary sucrose and fructose as potential biomarkers for sugars consumption was investigated in two studies of 21 healthy participants living in a volunteer suite where dietary intake was known and all specimens collected. The dose-response was assessed in 12 males using a randomized crossover design of three diets containing constant levels of 63, 143, and 264 g of sugars for 10 days each. Both sugars and sucrose intake were significantly correlated with the sum of sucrose and fructose concentration in urine (0.888; P < 0.001). To assess effects with volunteers consuming their habitual varying diets, seven males and six females were fed their usual diet (assessed beforehand from four consecutive self-completed 7-day food diaries) for 30 days under controlled conditions in the volunteer suite. The mean (±SD) calculated total sugars intake was 202 ± 69 g/d, 41% from sucrose. Mean (±SD) urinary sucrose and fructose were 36.6 ± 16.6 and 61.8 ± 61.3 mg/d, respectively. The sum of sucrose and fructose in urine was significantly correlated with sugars (0.841; P < 0.001) and sucrose intake (0.773; P = 0.002). In the regression, 200 g of sugars intake predicted ∼100 mg of sucrose and fructose in urine. The correlation between individual means of randomized 16 days of sugars intake and 8 days of sugars excretion data (as used in validation studies) remained as high as that obtained with the means of 30-day measurements and the regression estimates were very similar. Twenty-four–hour urinary sucrose and fructose could be grouped into a new category of biomarkers, predictive biomarkers, that can be used in studies determining the structure of dietary measurement error in free living individuals and to relate sugars intake to disease risk.
Myogenic Differentiation of ES Cells for Therapies in Neuromuscular Diseases: Progress to Date

The neuromuscular disorders are a heterogeneous group of genetic diseases characterized by progressive degeneration and impaired regeneration of skeletal muscle, resulting in weakness. The mobility of patients is very reduced, leading, depending on the disease severity, to wheelchair dependency and reduced life expectancy and quality. Currently there are no proven treatments for these diseases, except for palliative measures to improve a patient’s quality of life. Nevertheless, cell therapy using embryonic or somatic stem cells is considered to offer the best potential for success, and many projects are now being undertaken to evaluate the therapeutic possibilities of this approach. Theoretically, due to their pluripotency, embryonic stem cells can give rise to any type of tissue, and raises the possibility of successfully treating many diseases. However, a simple injection of ES cells into various body locations in model organisms often leads to formation of undesirable teratomas and not to healthy new tissues. Accordingly, ES cells must be partially differentiated and selected prior to injection to increase the likelihood of implantation and growth of tissue exhibiting differentiation of the desired type. Although some modest advances have been achieved, to date the use of ES cells for therapy of neuromuscular disorders still remains a distant goal. In this review we mainly consider the role of embryonic stem cells in neuromuscular therapeutic approaches.
Average recovery performances of non-perfectly informed compressed sensing: With applications to multiclass encryption

The sensitivity of recovery algorithms with respect to a perfect knowledge of the encoding matrix is a general issue in many application scenarios in which compressed sensing is an option to acquire or encode natural signals. Quantifying this sensitivity in order to predict the result of signal recovery is therefore valuable when no a priori information can be exploited, e.g., when the encoding matrix is randomly perturbed without any exploitable structure. We tackle this aspect by means of a simplified model for the signal recovery problem, which enables the derivation of an average performance estimate that depends only on the interaction between the sensing and perturbation matrices. The effectiveness of the resulting heuristic is demonstrated by numerical exploration of signal recovery under three simple perturbation matrix models. Finally, we show how this estimate matches very well the degradation experienced by non-perfectly informed decoders in applications of compressed sensing to protecting the acquired information content in ECG tracks and sensitive images.
Is sociality a crucial prerequisite for the emergence of language

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Theory and Practice of Structure-From-Motion Using Affine Correspondences

Affine Correspondences (ACs) are more informative than Point Correspondences (PCs) that are used as input in mainstream algorithms for Structure-from-Motion (SfM). Since ACs enable to estimate models from fewer correspondences, its use can dramatically reduce the number of combinations during the iterative step of sample-and-test that exists in most SfM pipelines. However, using ACs instead of PCs as input for SfM passes by fully understanding the relations between ACs and multi-view geometry, as well as by establishing practical, effective AC-based algorithms. This article is a step forward into this direction, by providing a clear account about how ACs constrain the two-view geometry, and by proposing new algorithms for plane segmentation and visual odometry that compare favourably with respect to methods relying in PCs.
PGST: Using Personal and Global Factors in the Spatio-Temporal Domain for Mobility Relationship Measurement

As well-developed social networking services collect rich location data of mobile users, it becomes interesting for measuring the mobility relationship strength. The state-of-the-art measure for such relationship is Personal, Global and Temporal factors (PGT) method, which calculates personal and global background in the spatial domain. We argue that meeting events differentiate from each other not only in the spatial domain, but also in the temporal domain. Accordingly, a novel method called PGST for measuring the mobility relationship is proposed. Additional time differences are introduced into the personal and global factors. Thus, background effects of location and time are removed from primitive meeting events. Experiments on real dataset suggest that our method significantly outperforms the state-of-the-art methods.
Transform-invariant dictionary learning for face recognition

Dictionary learning has important applications in face recognition. However, large transformation variations of face images pose a grand challenge to conventional dictionary learning methods. A large portion of misleading dictionary atoms are usually learned to represent transformation factors, which will cause ambiguity in face recognition. To address this problem, this paper proposes a general framework for transform-invariant basis matrix learning. Specifically, we present a transform-invariant dictionary learning method which explicitly incorporates an appearance consistent error term to the original objective function in dictionary learning. The unified objective function is effectively optimized in an alternating iterative way. An ensemble of aligned images and a discriminative transform-invariant dictionary for sparse coding can be obtained by solving the formulated objective function. Experimental results on two public face databases demonstrate our algorithm's superiority compared with two state-of-the-art dictionary learning methods and the recently proposed transform-invariant PCA method.
Supporting the design and fabrication of physical visualizations

Physical visualizations come in increasingly diverse forms, and are used in domains including art and entertainment, business analytics, and scientific research. However, creating physical visualizations requires laborious craftsmanship and demands expertise in both data visualization and digital fabrication. We present three case studies that illustrate limitations of current visualization fabrication workflows. We then present MakerVis, a prototype tool that integrates the entire process of creating physical visualizations, from data filtering to physical fabrication. Design sessions with three end users demonstrate how tools such as MakerVis can dramatically lower the barriers to producing physical visualizations. Observations and interviews from these sessions highlighted future research areas, including customization support, using material properties to represent data variables, and allowing the reuse of physical data objects in new visualizations.
A Survey On Subjective Sentiment Analysis From Twitter Corpus

Twitter is the famous micro blogging site where millions of users share their opinions every day. These opinions are important for the researchers or analyst to research about the services or product which in turn helps to study the market. Sentiment analysis is the task to extract the clear insight from social data. This process helps to determine the emotional tone behind a series of words to gain the overview of the wider public opinion. Intuitively, polarity classification is usually used by the companies for market analysis to fetch public opinion about their products. So businesses are looking forward to understanding the reviewer’s opinion using sentiment analysis. In this paper, we are presenting an approach to implementing a tool that can be used to classify the tweets as positive, negative or neutral.
On Program Security and Obfuscation

This project was set out to survey work in program protection and related elds. I investigate previous work in an attempt to unify a problem statement, along with the necessary and su cient conditions for various forms of software protection. Past research contains a number of informal protection schemes and only a few formal attempts. The fact that I am unable to nd an appropriate formal basis for this type of research has made progress di cult, so I have produced nothing more than this survey and a few speculations. The general problem of program protection is widely held to be impossible. There is no doubt that the problem is di cult, but a formal result, whether positive or negative, is necessary. Given these di culties, I hope only to convince the reader of the inadequacy of the current state of research for attempting to prove a result of this kind, and that program protection is an important, wideopen problem. The problem, as I gather it, crosses cryptography with the fundamentals of programming languages. There exists a wealth of mathematical tools for secure communication, authentication, computation, and much more in the cryptography literature. The past 30 years of research in this eld has produced amazing results{and these techniques have been rapidly integrated into computer systems. Program protection involves a similar set of goals, and many of the same techniques may apply once program protection is properly understood. I will begin with by analyzing the various threats that people wish to protect against (x2). I will then discuss a recent, promising direction towards a solution (x3), summarize relevant topics in cryptography (x4) and relevant topics in program obfuscation (x5), discuss adversarial weaknesses in today's program analysis technology (x6), and summarize related work (x7).
Position estimation and modeling of a flexible industrial robot

Abstract A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman filter and one using the particle filter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramer-Rao lower bound. A significant improvement in position accuracy is achieved using the sensor fusion technique.
Image segmentation by oriented image foresting transform: Handling ties and colored images

Anatomical structures and tissues are often hard to be segmented in medical images due to their poorly defined boundaries, i.e., low contrast in relation to other nearby false boundaries. The specification of the boundary polarity can help to alleviate part of this problem. Although this information is naturally exploited by boundary-based methods like live wire, region-based methods are usually conceived for undirected graphs. This motivated researchers to investigate extensions to better handle oriented transitions. Recently, an Oriented Image Foresting Transform has been proposed. In this work, we further generalize it by different non-smooth connectivity functions that allow a better handling of ties in its energy formulation. We give direct proof for the optimality of the proposed extensions in terms of a global maxima of an energy function, and show the obtained gains in accuracy over a more challenging 3D dataset of MR images of the foot. We also discuss the incorporation of the boundary polarity for the interactive segmentation of colored images.
Stochastic Definite Clause Grammars

This paper introduces Stochastic Definite Clause Grammars, a stochastic variant of the wellknown Definite Clause Grammars. The grammar formalism supports parameter learning from annotated or unannotated corpora and provides a mechanism for parse selection by means of statistical inference. Unlike probabilistic contextfree grammars, it is a context-sensitive grammar formalism and it has the ability to model cross-serial dependencies in natural language. SDCG also provides some syntax extensions which makes it possible to write more compact grammars and makes it straight-forward to add lexicalization schemes to a grammar.
Sporadic long-term variability in radio activity from a brown dwarf

Context. Radio activity has been observed in a large variety of stellar objects, including in the last few years, ultra-cool dwarfs. Aims. To explore the extent of long-term radio activity in ultra-cool dwarfs. Methods. We use data taken over an extended period of 9 hr from the Very Large Array of the source 2MASS J05233822-1403022 in September 2006, plus data taken in 2004. Results. The observation taken in September 2006 failed to detect any radio activity at 8.46 GHz. A closer inspection of earlier data reveals that the source varied from a null detection on 3 May 2004, to ≈95 µJy on 17 May 2004, to 230 µJy on 18 June 2004. The lack of detection in September 2006 suggests at least a factor of ten flux variability at 8.46 GHz. Three short photometric runs did not reveal any optical variability. Conclusions. In addition to the observed pulsing nature of the radio flux from another ultra-cool source, the present observations suggests that ultra-cool dwarfs may not just be pulsing but can also display long-term sporadic variability in their levels of quiescent radio emission. The lack of optical photometric variability suggests an absence of large-scale spots at the time of the latest VLA observations, although small very high latitude spots combined with a low inclination could cause very low amplitude rotational modulation which may not be measurable. We discuss this large variability in the radio emission within the context of both gyrosynchrotron emission and the electron-cyclotron maser, favoring the latter mechanism.
Growth-Differentiation Factor 15 Predicts Worsening of Albuminuria in Patients With Type 2 Diabetes

OBJECTIVE Development of micro- or macroalbuminuria is associated with increased risk of cardiorenal complications, particularly in diabetes. For prevention of transition to micro- or macroalbuminuria, more accurate prediction markers on top of classical risk markers are needed. We studied a promising new marker, growth-differentiation factor (GDF)-15, to predict transition to increasing stage of albuminuria in type 2 diabetes mellitus (T2DM). In addition, we looked at the GDF-15 potential in nondiabetic subjects with hypertension (HT). RESEARCH DESIGN AND METHODS Case and control subjects were selected from the PREVEND cohort, a large (n = 8,592), prospective general population study on the natural course of albuminuria, with >10 years of follow-up and repeated albuminuria measurements. We found 24 T2DM and 50 HT case subjects transitioning from normo- to macroalbuminuria and 9 T2DM and 25 HT case subjects transitioning from micro- to macroalbuminuria (average follow-up 2.8 years). Control subjects with stable albuminuria were pair matched for age, sex, albuminuria status, and diabetes duration. GDF-15 was measured in samples prior to albuminuria transition. RESULTS Prior to transition, GDF-15 was significantly higher in case subjects with T2DM than in control subjects (median [IQR] 1,288 pg/mL [885–1,546] vs. 948 pg/mL [660–1,016], P < 0.001). The odds ratio for transition in albuminuria increased significantly per SD of GDF-15 (2.9 [95% CI 1.1–7.5], P = 0.03). GDF-15 also improved prediction of albuminuria transition, with significant increases in C statistic (from 0.87 to 0.92, P = 0.03) and integrated discrimination improvement (0.148, P = 0.001). In HT, GDF-15 was also independently associated with transition in albuminuria stage (2.0 [1.1–3.5], P = 0.02) and improved prediction significantly. CONCLUSIONS We identified GDF-15 as a clinically valuable marker for predicting transition in albuminuria stage in T2DM beyond conventional risk markers. These findings were confirmed in nondiabetic HT subjects.
Adaptive Interfaces for Value-Driven Agents

As autonomous agents perform increasingly important and complex tasks, they have the potential to greatly expand human capabilities. For this collaboration to be successful, a human must be able to effectively communicate goals and preferences to the agent, so the agent's choices will be consistent with those of the human user. We present our plans for integrating two lines of research towards this end: an architecture for value-based agents, called Icarus, which employs a numeric utility model to resolve choices in skills; and research on adaptive user interfaces that acquire a numerical model of user preferences from experience. Taken together, these capabilities offer a means of tailoring autonomous agent behavior in complex domains.
A Middleware Design for Block Cipher Seamless Connected into Stream Cipher Mode

In order to connect the block cipher into stream cipher mode, the middleware about output of the block cipher was designed according to flexible and scalable principle. The byte wise operation can be paralleled to more large scale such as 32 bit wise or 16 bit wise. Secure of this design was demonstrated by the block cipher algorithm itself and the complexity of mask algorithm. The middleware model and the block cipher algorithm model are seamless connected because of standardized block size and output size. Furthermore, such standardized size can be actively changed with the application environments. The approach of this paper is that a kind of complex mask was used in block cipher algorithm when embedded it into stream operation mode such as Cipher Feedback Mode, Output Feedback Mode and Counter Mode.
Linear current-controlled oscillator for analog to digital conversion

Current-controlled oscillators (CCO) for analog to digital conversion need linear tuning-characteristics. A new CCO design in which the period of oscillation is defined by charging the timing capacitor to a reference voltage by the input current, is described. The sources of non-linearity in the tuning characteristics are identified and modeled. A method of compensating for these errors is presented. Process and temperature effects are minimized by trading speed for robustness in manufacturing. The design has been verified by simulations as well as fabricating a prototype in a typical 0. 18μm process node. Simulation results indicate that 0.2% linearity can be obtained from 0-100 deg C for the frequency range upto 500MHz. The main idea is to improve linearity by design as much as possible before performing calibration.
A Level Set Method for Thin Film Epitaxial Growth 1

Christian Ratsch, ∗,† Li-Tien Cheng, ∗,3 Mark Gyure, † Ronald P. Fedkiw, ‡,2 Christopher Anderson, ∗ and Stanley Osher ∗ ∗Mathematics Department, University of California at Los Angeles, Los Angeles, California 90095-1555; †HRL Laboratories, Malibu, California 90265; and ‡Computer Science Department, Stanford University, Stanford, California 94305 E-mail: suchen@usinter.net, barry@math.ucla. edu, mkang@math.ucla. edu, caflisch@math.ucla. edu, cratsch@math.ucla. edu, lcheng@math.ucla. edu, gyure@hrl.com, fedkiw@cs.stanford. edu, anderson@math.ucla. edu, sjo@math.ucla. edu
Psychopaths: Is a therapeutic community therapeutic?

A therapeutic community for psychopathic and non-psychopathic mentally disordered male offenders is described. The programme was humanistic, heavily peer operated, run by a charismatic leader, somewhat coercive, and employed radical therapeutic techniques. The programme was evaluated by comparing the post-release criminal and violent behaviour of men who participated in the programme with the outcome of matched control subjects who did not participate. Overall, the therapeutic community programme had a marginally positive effect on general recidivism and no effect on violent recidivism. However, whereas treated nonpsychopaths had lower recidivism rates than their untreated counterparts, the opposite was true for psychopaths. Possible explanations as to why a therapeutic community of this type may not be effective for psychopaths are discussed, as are suggestions for what treatments might work to reduce recidivism among psychopaths