Miracle-dz/UniFAR-FTUs huggingface dataset:
Location privacy via geo-indistinguishability

In this paper we report on our ongoing project aimed at protecting the privacy of the user when dealing with location-based services. The starting point of our approach is the principle of geo-indistinguishability, a formal notion of privacy that protects the user's exact location, while allowing approximate information -- typically needed to obtain a certain desired service -- to be released. We then present two mechanisms for achieving geo-indistinguishability, one generic to sanitize locations in any setting with reasonable utility, the other custom-built for a limited set of locations but providing optimal utility. Finally we extend our mechanisms to the case of location traces, where the user releases his location repeatedly along the day and we provide a method to limit the degradation of the privacy guarantees due to the correlation between the points. All the mechanisms were tested on real datasets and compared both among themselves and with respect to the state of the art in the field.
National differences in gender–science stereotypes predict national sex differences in science and math achievement

About 70% of more than half a million Implicit Association Tests completed by citizens of 34 countries revealed expected implicit stereotypes associating science with males more than with females. We discovered that nation-level implicit stereotypes predicted nation-level sex differences in 8th-grade science and mathematics achievement. Self-reported stereotypes did not provide additional predictive validity of the achievement gap. We suggest that implicit stereotypes and sex differences in science participation and performance are mutually reinforcing, contributing to the persistent gender gap in science engagement.
A Single-Stage Target Tracking Algorithm for Multistatic DVB-T Passive Radar Systems

In this contribution, a particle filter (PF) is proposed for tracking a single target illuminated with a digital-video-broadcasting terrestrial (DVB-T) signal in a multistatic radar system. This algorithm utilizes a single-stage scheme, i.e. it estimates the target position trajectory in a Cartesian coordinate system directly from the signal reflected by this target. The multiple stages adopted in the conventional approaches are unnecessary. The proposed algorithm augmented with successive interference cancellation can be used to track individual targets in a multiple-target scenario. Simulation studies show that this PF exhibits lower complexity and better performance than two conventional algorithms using multiple stages.
Use of neuroanatomical pattern classification to identify subjects in at-risk mental states of psychosis and predict disease transition.

CONTEXT Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance imaging-based diagnostic classification of neuropsychiatric patient populations. OBJECTIVE To determine whether multivariate neuroanatomical pattern classification facilitates identification of individuals in different at-risk mental states (ARMS) of psychosis and enables the prediction of disease transition at the individual level. DESIGN Multivariate neuroanatomical pattern classification was performed on the structural magnetic resonance imaging data of individuals in early or late ARMS vs healthy controls (HCs). The predictive power of the method was then evaluated by categorizing the baseline imaging data of individuals with transition to psychosis vs those without transition vs HCs after 4 years of clinical follow-up. Classification generalizability was estimated by cross-validation and by categorizing an independent cohort of 45 new HCs. SETTING Departments of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany. PARTICIPANTS The first classification analysis included 20 early and 25 late at-risk individuals and 25 matched HCs. The second analysis consisted of 15 individuals with transition, 18 without transition, and 17 matched HCs. MAIN OUTCOME MEASURES Specificity, sensitivity, and accuracy of classification. RESULTS The 3-group, cross-validated classification accuracies of the first analysis were 86% (HCs vs the rest), 91% (early at-risk individuals vs the rest), and 86% (late at-risk individuals vs the rest). The accuracies in the second analysis were 90% (HCs vs the rest), 88% (individuals with transition vs the rest), and 86% (individuals without transition vs the rest). Independent HCs were correctly classified in 96% (first analysis) and 93% (second analysis) of cases. CONCLUSIONS Different ARMSs and their clinical outcomes may be reliably identified on an individual basis by assessing patterns of whole-brain neuroanatomical abnormalities. These patterns may serve as valuable biomarkers for the clinician to guide early detection in the prodromal phase of psychosis.
Receiver design of MIMO systems in a mixture of Gaussian noise and impulsive noise

In this paper, the receiver design of MIMO systems is performed in a mixture of Gaussian noise and impulsive noise modeled as a symmetric alpha stable process. Both spatial multiplexing systems (SM-systems) and diversity based systems are considered. The optimal receiver and several suboptimal receivers are developed and the related problems, such as performance and robustness, are discussed. Simulation shows that the proposed receivers can achieve much better performance than the traditional MIMO receivers in the mixed noise.
Composting from a Sustainable Point of View: Respirometric Indices as Key Parameter

Composting at an industrial scale can be performed using low technology processes, such as windrows, or by implementing more complex technologies such as tunnels or, in general, in-vessel systems. In both cases process control can be done via measurement of oxygen content in the exhaust gases (or as interstitial oxygen in the material) and/or by monitoring the temperature evolution of the material. However, the use of respiration indices (RIs) as a control parameter to obtain reliable information on the actual microbial activity is being increasingly studied. Also RIs are used to determine the biological stability of the final product or the biodegradability of the wastes intended to be composted. In this case, the RI value can be related to the amount of biodegradable organic matter content. As a new application, RIs can also be used to determine the environmental impact of composting plants. Indeed, emission factors of pollutant gases (ammonia, Volatile Organic Compounds, etc.) or consumption of resources (water, energy, electricity) can be referred to the resulting reduction of RI obtained during the entire composting process. In this case, RI might be a promising parameter for the comparison of composting technologies from the point of view of its sustainability or to define the critical phases of the process in terms of environmental impact (for instance, treatment of exhaust composting gases by biofiltration). In fact, studies on composting sustainability should consider not only the composting process but the equipment used for the treatment of its emissions, which has an important effect on the global environmental impact of waste treatment plants. This paper discusses the above mentioned topics, with RIs as the key parameter in the analysis of composting processes. The discussion will be based on the experience of our previous research on composting and gas cleaning.
Evidence that rat liver mitochondrial and cytosolic fumarases are synthesized from one species of mRNA by alternative translational initiation at two in-phase AUG codons.

Rat liver contains two isozymes of fumarase, mitochondrial and cytosolic enzymes. Recently, we suggested that the precursors of both isozymes might be synthesized by one species of mRNA [Suzuki, T. , Sato, M. , Yoshida, T. & Tuboi, S. (1989) J. Biol. Chem. 264, 2581-2586]. To examine this possibility, we have isolated and characterized rat genomic clones for fumarase. The isolated clones covered almost all of the 5' half of the fumarase gene consisting of five exons. The first exon contained the whole 5' non-coding region and the signal peptide of mitochondrial precursor. The second exon encoded 45 amino acid residues of both mature proteins, starting from the N-terminal alanine. By using the boundary region of the first intron and the second exon as an S1-nuclease-analysis probe, we obtained conclusive evidence that rat liver contains no other mRNA specific for the cytosolic isozyme of fumarase. Two transcription-initiation sites were identified by further S1-nuclease-mapping analysis and were shown to be located very close to each other, differing by only four bases in length. Therefore, these sites were considered to be functionally the same. The results obtained by hybrid-selected translation, with a DNA fragment of the 5' non-coding region as a hybridization probe for selecting mRNA, were consistent with the above findings. We found a plausible secondary structure within the 5' non-coding mRNA sequence that may impede initiation and so alter the efficiency of translation. We also discuss the mechanism regulating translational initiation.
Effects of microstructures on mesoscopic morphological transitions in deposition growth models

We study the influence of competing microstructure symmetries on the emergence of different morphologies during the growth by vapour deposition of thin solid films. We perform extensive numerical simulations with a minimal model that includes different microstructures, as well as thermal surface diffusion, to compute the corresponding structure zone model (SZM) and analyse, with statistical physics techniques, the details of transitional morphologies at border zones. We show that the maximum coordination number of the underlying microstructure provides a classification of the statistics of the transitional morphologies at the border between zones I (porous structures) and II (columnar faceted structures) of the SZM.
Representative volume element-based design and analysis tools for composite materials with nanofillers

Representative volume element-based three-dimensional models with various nanofiller geometries and process parameters are presented for the design and analysis of composite materials. Analytical, computer-aided design, and computer-aided engineering tools are integrated to develop user interface tools with automated three-dimensional models for mechanical and electrical analyses. Various process parameters in the manufacture of nanocomposites are quantified using image analysis techniques. A filler-to-filler distance algorithm is incorporated in developing a three-dimensional network of fillers within matrix representative volume element to account for filler–filler interactions and compatibility. The stress–strain behavior of metal matrix nanocomposites, the effective modulus, and the electrical conductivity of polymer nanocomposite fibers are presented as case studies to demonstrate the capabilities of the developed representative volume element-based design and analysis tools. The unique automated design and analysis framework presented in this study integrates various software tools, quantifies the effect of process parameters of experimental composites with nanofillers, and provides quick what-if analysis for manufacturing application-specific composites.
Uniform derandomization from pathetic lower bounds

The notion of probabilistic computation dates back at least to Turing, who also wrestled with the practical problems of how to implement probabilistic algorithms on machines with, at best, very limited access to randomness. A more recent line of research, known as derandomization, studies the extent to which randomness is superfluous. A recurring theme in the literature on derandomization is that probabilistic algorithms can be simulated quickly by deterministic algorithms, if one can obtain impressive (i.e. superpolynomial, or even nearly exponential) circuit size lower bounds for certain problems. In contrast to what is needed for derandomization, existing lower bounds seem rather pathetic. Here, we present two instances where ‘pathetic’ lower bounds of the form n1+ε would suffice to derandomize interesting classes of probabilistic algorithms. We show the following: — If the word problem over S5 requires constant-depth threshold circuits of size n1+ε for some ε>0, then any language accepted by uniform polynomial size probabilistic threshold circuits can be solved in subexponential time (and, more strongly, can be accepted by a uniform family of deterministic constant-depth threshold circuits of subexponential size). — If there are no constant-depth arithmetic circuits of size n1+ε for the problem of multiplying a sequence of n 3×3 matrices, then, for every constant d, black-box identity testing for depth-d arithmetic circuits with bounded individual degree can be performed in subexponential time (and even by a uniform family of deterministic constant-depth AC0 circuits of subexponential size).
An Ontology-Based Approach to Social Media Mining for Crisis Management

We describe an existing multilingual information extraction system that automatically detects event information on disasters, conflicts and health threats in near-real time from a continuous flow of on-line news articles. We illustrate a number of strategies for customizing the system to process social media texts such as Twitter messages, which are currently seen as a crucial source of information for crisis management applications. On one hand, we explore the mapping of our domain model with standard ontologies in the field. On the other hand, we show how the language resources of such a system can be built, starting from an existing domain ontology and a text corpus, by deploying a semisupervised method for ontology lexicalization. As a result, event detection is turned up into an ontology population process, where crowdsourced content is automatically augmented with a shared structured representation, in accordance with the Linked Open Data principles.
Four Transmit Diversity Schemes for Coded OFDM Systems with Four Transmit Antennas

We compare four open-loop transmit diversity schemes in a coded Orthogonal Frequency Division Multiplexing (OFDM) system with four transmit antennas, namely cyclic shift diversity (CSD), Space-Time Block Code (STBC, Alamouti code is used) with CSD, Quasi-Orthogonal STBC (QO-STBC) and Minimum-Decoding-Complexity QOSTBC (MDC-QOSTBC). We show that in a coded system with low code rate, a scheme with spatial transmit diversity of second order can achieve similar performance to that with spatial transmit diversity of fourth order due to the additional diversity provided by the phase shift diversity with channel coding. In addition, we also compare the decoding complexity and other features of the above four mentioned schemes, such as the requirement for the training signals, hybrid automatic retransmission request (HARQ), etc. The discussions in this paper can be readily applied to many modern wireless communication systems, such as mobile systems beyond 3G, IEEE 802.11 wireless LAN, or IEEE 802.16 WiMAX, that employ more than two transmit antennas and OFDM.
Prediction of the Exposure Status of transmembrane beta Barrel residues from protein Sequence

We present BTMX (Beta barrel TransMembrane eXposure), a computational method to predict the exposure status (i.e. exposed to the bilayer or hidden in the protein structure) of transmembrane residues in transmembrane beta barrel proteins (TMBs). BTMX predicts the exposure status of known TM residues with an accuracy of 84.2% over 2,225 residues and provides a confidence score for all predictions. Predictions made are in concert with the fact that hydrophobic residues tend to be more exposed to the bilayer. The biological relevance of the input parameters is also discussed. The highest prediction accuracy is obtained when a sliding window comprising three residues with similar C(α)-C(β) vector orientations is employed. The prediction accuracy of the BTMX method on a separate unseen non-redundant test dataset is 78.1%. By employing out-pointing residues that are exposed to the bilayer, we have identified various physico-chemical properties that show statistically significant differences between the beta strands located at the oligomeric interfaces compared to the non-oligomeric strands. The BTMX web server generates colored, annotated snake-plots as part of the prediction results and is available under the BTMX tab at http://service.bioinformatik. uni-saarland.de/tmx-site/. Exposure status prediction of TMB residues may be useful in 3D structure prediction of TMBs.
Interactions between plasma concentrations of folate and markers of vitamin B12 status with cognitive performance in elderly people not exposed to folic acid fortification: the Hordaland Health Study

A combination of high folate with low vitamin B12 plasma status has been associated with cognitive impairment in a population exposed to mandatory folic acid fortification. The objective of the present study was to examine the interactions between plasma concentrations of folate and vitamin B12 markers in relation to cognitive performance in Norwegian elderly who were unexposed to mandatory or voluntary folic acid fortification. Cognitive performance was assessed by six cognitive tests in 2203 individuals aged 72–74 years. A combined score was calculated using principal component analysis. The associations of folate concentrations, vitamin B12 markers (total vitamin B12, holotranscobalamin (holoTC) and methylmalonic acid (MMA)) and their interactions in relation to cognitive performance were evaluated by quantile regression and least-squares regression, adjusted for sex, education, apo-ɛ4 genotype, history of CVD/hypertension and creatinine. Cross-sectional analyses revealed an interaction (P= 0·009) between plasma concentrations of folate and vitamin B12 in relation to cognitive performance. Plasma vitamin B12 concentrations in the lowest quartile ( < 274 pmol/l) combined with plasma folate concentrations in the highest quartile (>18·5 nmol/l) were associated with a reduced risk of cognitive impairment compared with plasma concentrations in the middle quartiles of both vitamins (OR 0·22, 95 % CI 0·05, 0·92). The interaction between folate and holoTC or MMA in relation to cognitive performance was not significant. In conclusion, this large study population unexposed to mandatory folic acid fortification showed that plasma folate, but not plasma vitamin B12, was associated with cognitive performance. Among the elderly participants with vitamin B12 concentrations in the lower range, the association between plasma folate and cognitive performance was strongest.
Sarcopenia: A Major Challenge in Elderly Patients with End-Stage Renal Disease

Sarcopenia is a condition of multifaceted etiology arising in many elderly people. In patients with chronic kidney, the loss of muscle mass is much more intensive and the first signs of sarcopenia are observed in younger patients than it is expected. It is associated with the whole-body protein-energy deficiency called protein-energy wasting (PEW). It seems to be one of the major factors limiting patient's autonomy as well as decreasing the quality of life. If it cannot be treated with the simple methods requiring some knowledge and devotion, we will fail to save patients who die due to cardiovascular disease and infection, despite proper conduction of renal replacement therapy. Many factors influencing the risk of sarcopenia development have been evaluated in number of studies. Many studies also were conducted to assess the efficacy of different therapeutic strategies (diet, physical activity, hormones). Nevertheless, there is still no consensus on treatment the patients with PEW. Therefore, in the paper we present the reasons and pathophysiology of sarcopenia as an important element of protein energy wasting (PEW) in elderly patients suffering from chronic kidney disease. We also analyze possible options for treatment according to up-to-date knowledge.
Australasian Language Technology Association Workshop 2016

In this talk, I will survey several different kinds of dialogue models in use at the University of Southern California’s Institute for Creative Technologies. These models differ in complexity, robustness, ease of authoring, and thus suitability for different kinds of projects, ranging from research prototypes to systems in use for training applications or as presentation tools accessible to the general public. The models include a text-classification approach in which answers are selected from an authored set and no semantic reasoning is performed, “traditional” form-filling dialogue, a merging of the previous two approaches along with finite state networks for local dialogue structure, and a more advanced information-state model that is closely linked with AI planners and emotion reasoners.
Semantic Consistency: A Local Subspace Based Method for Distant Supervised Relation Extraction

One fundamental problem of distant supervision is the noisy training corpus problem. In this paper, we propose a new distant supervision method, called Semantic Consistency, which can identify reliable instances from noisy instances by inspecting whether an instance is located in a semantically consistent region. Specifically, we propose a semantic consistency model, which first models the local subspace around an instance as a sparse linear combination of training instances, then estimate the semantic consistency by exploiting the characteristics of the local subspace. Experimental results verified the effectiveness of our method.
Characteristics of Kwark Cheese Supplemented with Bifidobacterium longum KACC 91563

The effect of addition of the probiotic Bifidobacterium longum KACC 91563 on the chemical and sensory properties of Kwark cheese produced using CHN-11 as a cheese starter were investigated. The addition of B. longum KACC 91563 to Kwark cheese did not change the composition or pH value of the cheese, compared with control. B. longum KACC 91563 survived at a level of 7.58 Log CFU/g and did not have any negative effect on survival of the cheese starter. A sensory panel commented that the addition of B. longum KACC 91563 made Kwark cheese more desirable to consumers, and that the probiotic supplementation had no effect on perceived taste. Thus, B. longum KACC 91563 can be used for inclusion of probiotic bacteria in cheese.