Miracle-dz/UniFAR-FTUs huggingface dataset:
BioTouchPass: Handwritten Passwords for Touchscreen Biometrics

This work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One-Time Passwords (OTP) through the incorporation of biometric information as a second level of user authentication. In our proposed approach, users draw each digit of the password on the touchscreen of the device instead of typing them as usual. A complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and the robustness when increasing the length of the password and the number of enrolment samples. The new e-BioDigit database, which comprises on-line handwritten digits from 0 to 9, has been acquired using the finger as input on a mobile device. This database is used in the experiments reported in this work and it is available together with benchmark results in GitHub.11. https://github.com/BiDAlab/eBioDigitDB. Finally, we discuss specific details for the deployment of our proposed approach on current PIN and OTP systems, achieving results with Equal Error Rates (EERs) ca. 4.0 percent when the attacker knows the password. These results encourage the deployment of our proposed approach in comparison to traditional PIN and OTP systems where the attack would have 100 percent success rate under the same impostor scenario.
A Dual-Layer TOF-DOI Detector Block for Whole-Body PET

We developed a dual-layer high-resolution detector block for whole-body positron-emission tomography systems. The top layer is a 13 × 13 array of lutetium yttrium orthosilicate (LYSO) crystals (2.85 × 2.85 × 10 mm3 ) and the bottom layer a 13 × 13 array of lutetium gadolinium oxyorthosilicate (LGSO) crystals (2.85 2.85 10 mm3 ). The LGSO layer was coupled to four Hamamatsu R11194HA photomultiplier tubes (PMTs) by a photomultiplier quadrant-sharing configuration. This block has both time-of-flight and depth-of-interaction functions. Using a Na-22 point source, the performance of this block was evaluated by coinciding with a reference detector which consisted of a 4 × 4 × 10 mm3 LYSO crystal coupled to a Hamamatsu R9779 PMT. A total of 4.7% of the counts were mixed among the two layers. The LYSO layer had 11.4% energy resolution and 329 ps coincidence time resolution against the reference detector. The LGSO layer had 14.8% energy resolution and 356 ps coincidence time resolution against the reference detector.
A Bottleneck Assigned Binary Ant System for multimodal optimization

A Bottleneck Assigned Binary Ant System (baBAS) is presented and applied to multimodal optimization problems. The strategy is inspired by traffic organization in real ants under crowded conditions found by A. Dussutour et. al. The Strategy can prevent loss of diversity of solutions by introducing a so called “bottleneck” to each path of solutions. Any ant can't pass through the path if the traffic flow on it has reached or exceeded the threshold. Experiment results on some typical multimodal complex functions showed that baBAS had much better capability than Binary Ant System (BAS), Binary Ant System with Elitist Strategy (BASe) and some traditional multimodal methods (Niche GA) in locating and marinating stable global and local optima in multimodal search space.
Electricity Rates, Input Use and Irrrigated Cotton Profitability: A Hedonic Versus Traditional Profit Maximization Approach

The impact of increasing energy cost on the optimal level of nitrogen and irrigation water use is examined for two irrigated cotton production management strategies using LEPA irrigation. The first strategy is a traditional production management strategy where the optimal per acre application rate is the rate that maximizes expected profit based on a fixed expected cotton lint price and known lint yield response to applied nitrogen and irrigation water. Under the second production strategy, cotton producers are assumed to maximize a hedonic profit function that explicitly considers the tradeoff between lint yield and lint quality attributable to alternative nitrogen and irrigation application rates, and the net effect the tradeoff has on per acre profit. The hedonic production approach, which manages for both quality and quantity, was found to be the more profitable producer strategy and used less fertilizer and less irrigation water.
Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification

We consider training probabilistic classifiers in the case that the number of classes is too large to perform exact normalisation over all classes. We show that the source of high variance in standard sampling approximations is due to simply not including the correct class of the datapoint into the approximation. To account for this we explicitly sum over a subset of classes and sample the remaining. We show that this simple approach is competitive with recently introduced non likelihoodbased approximations. 1 Probabilistic Classifier Given an input x, we define a distribution over class labels c ∈ {1, . , C} as pθ(c|x) = uθ(c, x) Zθ(x) , uθ ≥ 0 (1)
Annular ring based metamaterial absorber for S- and C-band applications

An annular ring based metamaterial absorber for S- and C-microwave bands is presented in this paper. The proposed structure is resonating at two frequencies of 3.06 GHz and 7.65 GHz with 99.40 % and 98.83 % absorptivities, respectively. The unit cell of the proposed absorber fits in a small volume of 12 mm × 12 mm × 1.6 mm. The proposed structure is polarization insensitive and performs well up to an incidence angle of 60° for TE and TM polarized wave. To get an insight into the dependence of absorption response on shape parameters, parametric variation of some key parameters is presented. The absorption phenomenon of the proposed absorber is investigated by dielectric and ohmic power loss density plots on the structure.
The Continuing Story of Class IIa Bacteriocins

SUMMARY Many bacteria produce antimicrobial peptides, which are also referred to as peptide bacteriocins. The class IIa bacteriocins, often designated pediocin-like bacteriocins, constitute the most dominant group of antimicrobial peptides produced by lactic acid bacteria. The bacteriocins that belong to this class are structurally related and kill target cells by membrane permeabilization. Despite their structural similarity, class IIa bacteriocins display different target cell specificities. In the search for new antibiotic substances, the class IIa bacteriocins have been identified as promising new candidates and have thus received much attention. They kill some pathogenic bacteria (e.g., Listeria) with high efficiency, and they constitute a good model system for structure-function analyses of antimicrobial peptides in general. This review focuses on class IIa bacteriocins, especially on their structure, function, mode of action, biosynthesis, bacteriocin immunity, and current food applications. The genetics and biosynthesis of class IIa bacteriocins are well understood. The bacteriocins are ribosomally synthesized with an N-terminal leader sequence, which is cleaved off upon secretion. After externalization, the class IIa bacteriocins attach to potential target cells and, through electrostatic and hydrophobic interactions, subsequently permeabilize the cell membrane of sensitive cells. Recent observations suggest that a chiral interaction and possibly the presence of a mannose permease protein on the target cell surface are required for a bacteria to be sensitive to class IIa bacteriocins. There is also substantial evidence that the C-terminal half penetrates into the target cell membrane, and it plays an important role in determining the target cell specificity of these bacteriocins. Immunity proteins protect the bacteriocin producer from the bacteriocin it secretes. The three-dimensional structures of two class IIa immunity proteins have been determined, and it has been shown that the C-terminal halves of these cytosolic four-helix bundle proteins specify which class IIa bacteriocin they protect against.
Life-Threatening Infection Caused by Daptomycin-Resistant Corynebacterium jeikeium in a Neutropenic Patient

ABSTRACT Daptomycin is a novel lipopeptide antibiotic agent approved for the treatment of gram-positive life-threatening infections. Here we report, for the first time, the isolation of a highly daptomycin-resistant strain of Corynebacterium jeikeium causing a life-threatening infection in a neutropenic patient undergoing cord blood transplantation for secondary acute myeloid leukemia.
Insulin/IGF-I binding ratio in skeletal and cardiac muscles of vertebrates: a phylogenetic approach.

Insulin and insulin-like growth factor (IGF-I) receptor binding and tyrosine kinase activity were characterized in cardiac and skeletal muscles of several vertebrates. Specific insulin binding per unit weight of skeletal muscle was clearly higher in pigeon and rat than in ectothermic vertebrates (32 +/- 5 and 25 +/- 2.7%/100 mg initial tissue in pigeon and rat, respectively, vs. 4.4 +/- 0.2%/100 mg in carp samples). Insulin binding clearly predominated over IGF-I binding in skeletal muscle of endotherms (IGF-I binding was 7.7 +/- 0.5%/100 mg in rat). In ectothermic vertebrates the situation was reversed, and IGF-I binding was higher than insulin binding. In cardiac muscle, specific binding of both insulin and especially IGF-I was higher than the values found in skeletal muscle of the same species (IGF-I binding was 60 +/- 4, 103 +/- 2, and 20 +/- 3%/100 mg in carp, turtle, and rat, respectively). The tyrosine kinase activity of insulin and IGF-I receptors of all species studied presented basal phosphotransferase rates (250-1,600 fmol P.micrograms protein-1.30 min-1) and percentage of stimulation (150-520%) with clear differences between species. The present data suggest that insulin and IGF-I binding to skeletal and cardiac muscles change through the vertebrate scale in both quantity and activity.
Prevalence of age-related hearing loss ( ARHL ) in Europe – A Review *

Populations are becoming progressively older thus presenting symptoms of diminished organ function due to degenerative processes. These may be physiological or caused by additional factors damaging the organ. Presbyacusis refers to the physiological age-related changes of the peripheral and central auditory system leading to hearing impairment and difficulty understanding spoken language. In contrast to epidemiological data of other continents, the prevalence of age-related hearing loss (ARHL) in Europe is not well defined, due in part to the use of different classification systems. We performed a systematic literature review with the aim of gaining a picture of the prevalence of ARHL in Europe. The review included only population and epidemiological studies in English since 1970 with samples in European countries with subjects aged 60 years and above. Nineteen studies met our selection criteria and additional five studies reported self-reported hearing impairment. When these data were crudely averaged and interpolated, roughly 30% of men and 20% of women in Europe were found to have a hearing loss of 30 dB HL or more by age 70 years, and 55% of men and 45% of women by age 80 years. Apparent problems in comparing the available data were the heterogeneity of measures and cut-offs for grades of hearing impairment. Our systematic review of epidemiological data revealed more information gaps than information that would allow gaining a meaningful picture of prevalence of ARHL. The need for standardized procedures when collecting and reporting epidemiological data on hearing loss has become evident. Development of hearing loss over time in conjunction with the increase in life expectancy is a major factor determining strategies of detection and correction of ARHL. Thus, we recommend using the WHO classification of hearing loss strictly and including standard audiometric measures in populationbased health surveys. DOI: https://doi.org/10.1007/s00405-011-1597-8 Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-48826 Journal Article Accepted Version Originally published at: Roth, T N; Hanebuth, D; Probst, R (2011). Prevalence of age-related hearing loss in Europe: a review. European Archives of Oto-Rhino-Laryngology, 268(8):1101-1107. DOI: https://doi.org/10.1007/s00405-011-1597-8 Editorial Manager(tm) for European Archives of Oto-Rhino-Laryngology and Head & Neck Manuscript Draft
Preclinical MR fingerprinting (MRF) at 7 T: effective quantitative imaging for rodent disease models

High‐field preclinical MRI scanners are now commonly used to quantitatively assess disease status and the efficacy of novel therapies in a wide variety of rodent models. Unfortunately, conventional MRI methods are highly susceptible to respiratory and cardiac motion artifacts resulting in potentially inaccurate and misleading data. We have developed an initial preclinical 7.0‐T MRI implementation of the highly novel MR fingerprinting (MRF) methodology which has been described previously for clinical imaging applications. The MRF technology combines a priori variation in the MRI acquisition parameters with dictionary‐based matching of acquired signal evolution profiles to simultaneously generate quantitative maps of T1 and T2 relaxation times and proton density. This preclinical MRF acquisition was constructed from a fast imaging with steady‐state free precession (FISP) MRI pulse sequence to acquire 600 MRF images with both evolving T1 and T2 weighting in approximately 30 min. This initial high‐field preclinical MRF investigation demonstrated reproducible and differentiated estimates of in vitro phantoms with different relaxation times. In vivo preclinical MRF results in mouse kidneys and brain tumor models demonstrated an inherent resistance to respiratory motion artifacts as well as sensitivity to known pathology. These results suggest that MRF methodology may offer the opportunity for the quantification of numerous MRI parameters for a wide variety of preclinical imaging applications. Copyright © 2015 John Wiley & Sons, Ltd.
Eight Degrees of Separation

We present a network formation game whose equilibria are undirected networks. Every connected couple contributes to the aggregate payoff by a fixed quantity, and the outcome is split between players according to the Myerson value allocation rule. This setup shows a wide multiplicity of non-empty equilibria, all of them connected. We show that the efficient equilibria of the game are either the empty network, or a network whose diameter does not exceed a threshold of 8 (i.e. there are no two nodes with a distance greater than 8).
Geo-NER: un reconocedor de entidades geográficas para inglés basado en GeoNames y Wikipedia

In this paper we show a tool for detecting and recognizing geographic entities specifically. This tool is based on the use of external resources such as gazetteers, Wikipedia and generic entities recognizers. During its operation, it makes use of geographical reasoning, based on syntactic patterns and geographic features (terms such as river, mountain, lake, etc.). The evaluation was carried on the geographic queries developed for the task GeoCLEF, part of the CLEF conferences, obtaining promising results in the recognition of geographic entities, compared to other generic entity recognizers.
Mining User Attributes Using Large-Scale APP Lists of Smartphones

Prevalence of smartphones is changing people's lifestyle. Mobile applications (abbr. APPs) on a smartphone serve as entries for users to access a wide range of services. What APPs installed on one's smartphone, i.e., APP list, convey lots of information regarding his/her personal attributes, such as gender, occupation, income, and preferences. This paper addresses the discovery of user attributes from an APP list. We develop an attribute-specific representation to describe user characteristics and then model the relationship between an attribute and an APP list. A large-scale real-world data set with APP lists of more than 100 000 smartphones is used for evaluation. Our approach achieves the average equal error rate of 16.4% for 12 predefined user attributes. To our best knowledge, this is the first work to explore mining of user attributes from installed APP lists.
Using genetic algorithms to optimize k-Nearest Neighbors con fi gurations for use with airborne laser scanning data

Article history: Received 11 February 2016 Received in revised form 2 June 2016 Accepted 7 July 2016 Available online xxxx The relatively small sampling intensities used by national forest inventories are often insufficient to produce the desired precision for estimates of population parameters unless the estimation process is augmented with auxiliary information, usually in the form of remotely sensed data. The k-Nearest Neighbors (k-NN) technique is a non-parametric, multivariate approach to prediction that has emerged as particularly popular for use with forest inventory and remotely sensed data and has been shown to contribute substantially to increasing precision. k-NN predictions are calculated as linear combinations of observations for sample units that are nearest in a space of auxiliary variables to the population unit forwhich a prediction is desired. Implementation of a nearest neighbors algorithm requires four choices: (i) a distancemetric, (ii) specific auxiliary variables to be used with the distance metric, (iii) the number of nearest neighbors, and a (iv) scheme for weighting the nearest neighbors. Regardless of the choices for a distance metric and weighting scheme, emerging evidence suggests that optimization of the technique, including selection of an optimal subset of auxiliary variables, greatly enhances prediction. However, optimization can be computationally intensive and time-consuming. A promising approach that is gaining favor is based on genetic algorithms, a technique that uses search heuristics that mimic natural selection to solve optimization problems. The objective of the study was to compare optimized k-NN configurations with respect to inferences for mean volume per unit area using airborne laser scanning variables as auxiliary information. For two study areas, one in Norway and one in Minnesota, USA, the analyses focused on optimizing k-NN configurations that used the weighted Euclidean and canonical correlation distancemetrics and two neighbor weighting schemes. Novel features of the study include introduction of a neighbor weighting scheme that has not previously been used for forestry applications, simultaneous optimization of all four k-NN choices, and basing comparisons on confidence intervals, rather than intermediateproducts suchasprediction accuracies. Two conclusionswere primary: (1) optimized selection of feature variables produced greater precision than using all feature variables, and (2) computational intensity necessary to optimize the weighted Euclidean metric was considerably greater than for the canonical correlation analysis metric. Specific findings were that optimization produced pseudo-R as large as 0.87 for the Norwegian dataset and as large as 0.89 for theMinnesota dataset. For the optimized canonical correlation distance metric, widths of approximate 95% confidence intervals as proportions of the estimated means were as small as 0.13 for the Norwegian dataset and as small as 0.15 for the Minnesota dataset. Published by Elsevier Inc.
Exercise metabolism in human skeletal muscle exposed to prior eccentric exercise

1 The effects of unaccustomed eccentric exercise on exercise metabolism during a subsequent bout of graded concentric exercise were investigated in seven healthy male subjects. Arterial and bilateral femoral venous catheters were inserted 2 days after eccentric exercise of one thigh (eccentric thigh) and blood samples were taken before and during graded two‐legged concentric knee‐extensor exercise. Muscle biopsies were obtained from the eccentric and control vastus lateralis before (rest) and after (post) the concentric exercise bout. 2 Maximal knee‐extensor concentric exercise capacity was decreased by an average of 23 % (P < 0.05) in the eccentric compared with the control thigh. 3 The resting muscle glycogen content was lower in the eccentric thigh than in the control thigh (402 ± 30 mmol (kg dry wt)−1vs. 515 ± 26 mmol (kg dry wt)−1, means ± s.e. m. , P < 0.05), and following the two‐legged concentric exercise this difference substantially increased (190 ± 46 mmol (kg dry wt)−1vs. 379 ± 58 mmol (kg dry wt)−1, P < 0.05) despite identical power and duration of exercise with the two thighs. 4 There was no measurable difference in glucose uptake between the eccentric and control thigh before or during the graded two‐legged concentric exercise. Lactate release was higher from the eccentric thigh at rest and, just before termination of the exercise bout, release of lactate decreased from this thigh (suggesting decreased glycogenolysis), whereas no decrease was found from the contralateral control thigh. Lower glycerol release from the eccentric thigh during the first, lighter part of the exercise (P < 0.05) suggested impaired triacylglycerol breakdown. 5 At rest, sarcolemmal GLUT4 glucose transporter content and glucose transport were similar in the two thighs, and concentric exercise increased sarcolemmal GLUT4 content and glucose transport capacity similarly in the two thighs. 6 It is concluded that in muscle exposed to prior eccentric contractions, exercise at a given power output requires a higher relative workload than in undamaged muscle. This increases utilization of the decreased muscle glycogen stores, contributing to decreased endurance.
A Reprogrammable Low Power Closed-Loop Optogenetic Platform for Freely Moving Animals

In this paper, we present a reprogrammable low power optogenetic based platform for closed-loop processing, which aims on neural abnormal activity invention such as epilepsy. The system is comprised of an embedded control system, and a custom designed ASIC chip for electrical recording and optical stimulation. Compared to current technologies, developed technology is not only show ultra-low power consumptions but also displays strong computational flexibility. A power cycling technique was implemented, which reduces the average power consumption of the system down to 2.93 mA at recording frequency 50Hz (equal to ASIC level). This allows a system lifetime up to 56 hours with a single Lithium-Polymer battery (165mAh). Then a three-stage closed-loop processing scheme is employed to foster a Brain-machine Interface (BMI) tool box, which allows the system meets various biomedical application requirements. By using in-vivo epilepsy neural data, our system demonstrates the capability for realtime intervention of abnormal activities. Hence, the developed technology shows great potential for both rodent behavior control based and implantable electronics applications such as chest units.