Miracle-dz/UniFAR-FTUs huggingface dataset:
DNN-kWTA With Bounded Random Offset Voltage Drifts in Threshold Logic Units

The dual neural network-based <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-winner-take-all (DNN-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>WTA) is an analog neural model that is used to identify the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> largest numbers from <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> inputs. Since threshold logic units (TLUs) are key elements in the model, offset voltage drifts in TLUs may affect the operational correctness of a DNN-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>WTA network. Previous studies assume that drifts in TLUs follow some particular distributions. This brief considers that only the drift range, given by <inline-formula> <tex-math notation="LaTeX">$[-\Delta, \Delta]$ </tex-math></inline-formula>, is available. We consider two drift cases: time-invariant and time-varying. For the time-invariant case, we show that the state of a DNN-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>WTA network converges. The sufficient condition to make a network with the correct operation is given. Furthermore, for uniformly distributed inputs, we prove that the probability that a DNN-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>WTA network operates properly is greater than <inline-formula> <tex-math notation="LaTeX">$(1-2\Delta)^{n}$ </tex-math></inline-formula>. The aforementioned results are generalized for the time-varying case. In addition, for the time-invariant case, we derive a method to compute the exact convergence time for a given data set. For uniformly distributed inputs, we further derive the mean and variance of the convergence time. The convergence time results give us an idea about the operational speed of the DNN-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>WTA model. Finally, simulation experiments have been conducted to validate those theoretical results.
Nitrogen addition regulates allometric growth by changing the distribution patterns of endogenous hormones in different organs of Pinus tabuliformis

Background: The mechanisms by which nitrogen (N) affects the allometric growth of plant organs by influencing the distribution of different hormones in plant organs remain unclear. Therefore, this study aimed to examine the effect of soil N levels on soil properties, the hormonal activities and growth parameters of Pinus tabuliformis Carr. Methods: Seedlings of P. tabuliformis were subjected to 0, 3, 6, 12 g of N m-2 year-1. Growth parameter and hormone activity data (trans-zeatin riboside (ZR), gibberellin (GA1+3), indole acetic acid (IAA), abscisic acid (ABA)) in leaf, stem, total root, coarse root (diameters >2 mm), fine root (1-2 mm) and finest root (0-1 mm) biomass were measured and analysed. Results: The results showed that N addition increased the growth of the leaves; stems; total roots; and coarse, fine, and finest roots of the seedlings, but decreased the ratio of underground to aboveground growth. Additionally, N addition increased the ZR content in stems, while decreasing the ABA content in leaves and whole roots and the GA1+3 content in whole roots, but IAA content was not significantly influenced by N addition. Furthermore, the hormones examined significantly influenced the growth of the leaves, stems, roots, and the coarse, fine, and finest roots. Conclusions: N addition affected the trans-zeatin riboside, gibberellin, indole acetic acid, and abscisic acid content in the various organs examined, which influenced the growth of the seedlings. Our research will provide an important reference for forestland governance and forest systems management under global atmospheric N deposition.
Dyslipidemia Is Positively Associated with Chronic Low Back Pain in Korean Women: Korean National Health and Nutrition Examination Survey 2010–2012

Background: This study aimed to evaluate the association between chronic low back pain (CLBP) and chronic diseases, such as hypertension, diabetes, and dyslipidemia. Methods: This study was a retrospective analysis using data from the Korea National Health and Nutrition Examination Survey (KNHANES) between 2010–2012 and included women who answered a questionnaire in the KNHANES asking whether they had low back pain for ≥3 months. Participants were divided into non-CLBP and CLBP groups. For statistical analysis, the Student’s t-test, chi-square test, Fisher’s exact test, and logistic regression analysis were performed using SPSS. Results: Of 5961 participants, the non-CLBP group comprised 4098 women and the CLBP group comprised 1863. Adjusted logistic regression model revealed that dyslipidemia was positively associated with CLBP (odds ratio, 1.32; 95% confidence interval, 1.140, 1.530; p < 0.001). However, hypertension and diabetes were not associated with CLBP. Conclusions: Our results suggest that proper treatment of dyslipidemia may contribute to lowering the risk of CLBP later in life.
Matita Tutorial

0 Getting Started 94 0.1 Installing Matita . 94 0.2 Preparing a working directory . 95 0.3 Matita interface . 95 0.4 Browsing the library . 96 0.5 Live DVD . 97 0.6 Matita Web . 98
Total phenolic distribution of juice, peel, and seed extracts of four pomegranate cultivars

The total phenolic distribution of juice, peel, and seed extracts of four Turkish pomegranate, Punica granatum L. , cultivars (“Lefan,” “Katirbasi,” “Cekirdeksiz-IV,” and “Asinar”) was investigated. Total phenolic compounds were determined with the Folin–Ciocalteu colorimetric method. The results showed that the levels of total phenolic compounds changed depending on cultivars and fruit parts. In all cultivars, the highest levels of total phenolic content were obtained from the peel extracts. The total phenolic content ranged from 1775.4 to 3547.8 mg gallic acid equivalent (GAE)/L among the cultivars. However, the total phenolic content of pomegranate juice and seed extract ranged from 784.4 to 1551.5 mg GAE/L and 117.0 to 177.4 mg GAE/L, respectively. “Lefan” displayed the highest amount of the total phenolic content among the four popular cultivars tested.
Mobile Payment Fraud: A Practical View on the Technical Architecture and Starting Points for Forensic Analysis of New Attack Scenarios

As payment cards and mobile devices are equipped with Near Field Communication (NFC) technology, electronic payment transactions at physical Point of Sale (POS) environments are changing. Payment transactions do not require the customerto insert their card into a slot of the payment terminal. The customer is able to simply swipe the payment card or mobilephone in front of a dedicated zone of the terminal to initiate a payment transaction. Secure Elements (SEs) in mobile phonesand payment cards with NFC should keep sensitive application data in a save place to protect it from abuse by attackers.Although hardware and the operating system of such a chip has to go through an intensive process of security testing, thecurrent integration of such a chip in mobile phones easily allows attackers to access the information stored. In the followingpaper we present the implementation of two different proof-of-concept attacks. Out of the analysis of the attack scenarios, wepropose various starting points for the forensic analysis in order to detect such fraudulent transactions. The presented conceptshould lead to fewer fraudulent transactions as well as protected evidence in case of fraud.
Feature-based disconnected edge segments linker

Object contour detection plays an important role in image processing. Many edge and object contour detectors have been proposed, such as, Canny edge detector, ACM, and level set methods. However, those detection methods often cannot provide the fully edge and object contour perfectly. In the ACM and level set methods, the initial contour of object has to be specified by a user in advance, and the successful segmentation results highly depend on the given initial object contour. In addition, the ACM and level set methods are significantly sensitive to noise. Giving an initial contour of object is not required for Canny edge detector, but it may bring about "broken edge problem. " To solve the broken edge problem, a feature-based disconnected edge segments (FBDES) linker is provided in this paper. For extracting objects from an image, in this paper Canny edge detector is first used to detect the object contour, and then the FBDES linker is employed to link the disconnected edge segments based on the features of the gray-level difference at vicinity of, the gradient and gradient direction on, and the length of the line segment connecting two disconnected edge segments. The experimental results show that the FBDES linker can give more impressive object segmentation results than the level set method.
COMPARATIVE EVALUATION OF HUMAN AND ACTIVE APPEARANCE MODEL BASED TRACKING PERFORMANCE OF ANATOMICAL LANDMARKS IN LOCOMOTION ANALYSIS 1

The detailed understanding of animal locomotion is an important part of biology, motion science and robotics. To analyze the motion, high-speed x-ray sequences of walking animals are recorded. The biological evaluation is based on anatomical key points in the images, and the goal is to find these landmarks automatically. Unfortunately, low contrast and occlusions in the images drastically complicate this task. As recently shown, Active Appearance Models (AAMs) can be successfully applied to this problem. However, obtaining reliable quantitative results is a tedious task, as the human error is unknown. In this work, we present the results of a large scale study which allows us to quantify both the tracking performance of humans as well as AAMs. Furthermore, we show that the AAM-based approach provides results which are comparable to those of human experts.
Optimisation of the membrane-assisted passive sampler and its comparison with solid phase extraction technique

A novel membrane-assisted passive sampler was further optimised in the laboratory. It was then compared to the solid phase extraction technique in terms of the extraction efficiency, enrichment factor, detection limit and selectivity in wastewater. The passive sampler was exposed to 3 l wastewater samples under laboratory conditions for 3 days. Five hundred millilitres of wastewater was extracted with C 18 cartridges. The extraction efficiency of the passive sampler ranged from 4 to 10% while in solid phase extraction it was 40 to 67% for the 3 chlorophenols. In both cases, extraction efficiency was highest for 2,4-dichlorophenol. The low extraction efficiency in the passive sampler supports the idea that it is not an exhaustive extraction technique and does not disturb the chemical equilibrium of the sample. It therefore measures the bioavailable fraction of the compound and can be used for equilibrium sampling and extraction. The obtained enrichment factors from the passive sampler were 89 and 295 for 2-chlorophenol and 2,4-dichlorophenol, respectively. From solid phase extraction, enrichment factors of 102, 113 and 167 were obtained for 2-chlorophenol, 4-chlorophenol and 2,4-dichlorophenol, respectively. The enrichment factor (~2.5) and sampling rates (~28 µl∙h-1) were both low for 4-chlorophenol in wastewater from passive sampler extraction. The calculated sampling rates were found to be 2 604 µl∙h -1 for 2-chlorophenol, 1 074 µl∙h -1 for 4-chlorophenol and 5 089 µl∙h -1 for 2,4-dichlorophenol in spiked deionised water. In wastewater, the sampling rates were found to be 1 544 µl∙h-1 for 2-chlorophenol, 28 µl∙h-1 for 4-chlorophenol and 5 106 µl∙h-1 for 2,4-dichlorophenol. The passive sampler was found to be superior in its selectivity towards the target compounds compared to solid phase extraction technique with C 18 sorbent. Chromatograms from solid phase extraction of wastewater contained high peaks of unidentified, potentially interfering compounds, especially in the early part of the chromatogram. In contrast, chromatograms from the passive sampler extraction were very clean. The detection limits of the passive sampler were comparable with that of solid phase extraction and were around 1.5 µg∙l-1 except for 4-chlorophenol that was high in wastewater (~100 µg∙l-1).
The effectiveness of a Self-management Programme of Activity Coping and Education - SPACE FOR COPD - in Primary Care

s Wagg, K. , Warrington, V. , Sewell, L. , Bankart, J., Steiner, M. , Morgan, M. , and Singh, S. A self-management programme of activity coping and education (SPACE) for COPD: 6 week results from a randomised controlled trial. European Respiratory Society Congress 2012 Mitchell-Wagg, K. , Warrington, V. , Apps, L. , Sewell, L. , Bankart, J., Steiner, M. , Morgan, M. , Singh, S. (2012) ‘S49 A Self-Management Programme of Activity Coping and Education (SPACE) For COPD: Results from a Randomised Controlled Trial’. Thorax 67, A25-A26 K.E. Mitchell, V. Warrington, L. Sewell, J. Bankart, J.E. A. Williams, M. Steiner, M. Morgan, S.J. Singh. (2013) ‘A Randomised Controlled Trial Of A Self-Management Programme Of Activity Coping And Education SPACE FOR COPD: Impact On Physical Activity At 6 Weeks’. American Thoracic Society Conference
Performance Comparison of GPU-Accelerated Fast Motion Estimation Method

Motion estimation is an important part of ultrasound strain elastography. The sum-table based motion estimation method, which can effectively reduce computation time and redundant calculation, is a fast motion estimation approach. Except for NCC, it can also be extended to other motion estimators. The main work and contribution of this paper is to implement different motion estimators (CC, NCC, SSD, SAD) on GPU platform based on the sum-table method and to compare the performance of these motion estimators with the classical method on GPU. The difference of computational cost of each estimator based on the sum-table method mainly lies in the construction of the sum-table. The computation burden per thread is small, so data addressing is the dominant work per thread. It has been reported that the sum-table method does not have particular advantage over the classical method with a large search range on GPU platform. However, it possesses good performance with a huge tracking kernel window.
Plant functional types and ecological strategies in Patagonian forbs

Abstract. We identified four major functional types of forbs in the Patagonian steppe, taking into account phenological and morphological traits: (1) shallow-rooted mesophytic species (annuals), (2) shallow-rooted non-mesophytic species, (3) deep-rooted evergreen species, and (4) deep-rooted deciduous species. The major attributes differentiating these groups were the date at which seasonal growth ended, rooting depth, sprouting depth, distance between shoots of the same plant, and degree of ‘mesophytism’. We used Cluster and Principal Components Analyses to identify the groups, and the attributes determining them. Late-growth-cycle types had deep roots and/or high ‘xerophytism’. Late-cycle-xerophytic types had a great sprouting depth, and late-cycle-deep-rooted types had a great distance between shoots of the same plant. On the basis of current knowledge of the structure and functioning of the Patagonian steppe, we suggested three explanations to account for these correlations. 1. Late-cycle forbs survive summer water deficit if they have xerophytic characteristics that reduce transpiration water losses, and/or they have deep roots that increase water uptake. 2. Sprouting depth results from the shift of active buds to dormant buds at the end of the cycle. Summer forbs have a great sprouting depth because only buds which are located deep in the soil survive hot and dry summers. 3. Distant shoots of summer forbs allow them simultaneously to use the high protection against desiccating winds provided by shrubs, and the ample water availability of bare soil patches. All the functional types of forbs depend on winter water recharge to begin their cycles, but each one completes its cycle by using a different portion of the water resources available in spring and summer.
A House Burden Score: Measuring the Workload in Therapeutic Residential Care for Young People

ABSTRACT This article is about using data from the Strengths and Difficulties questionnaire to develop a house burden score as a way of measuring the workload of a therapeutic residential care program. The development of the score ensures that residential placement selection is based on empirical data rather than on the often-used criteria of ‘where is there a vacancy? ’ It may also curb comments by inexperienced staff such as ‘our house has the most difficult young people, whereas yours are easy’. The aim of the score is to ensure that a residential program is not overburdened with too many children and young people with complex emotional and behavioral difficulties to the extent that this result is a sub-standard service for all young people.
Standard metabolic rate of spiny lobster (Sagmariasus verreauxi) pueruli determined by intermittent flow-through respirometry

An improved understanding of the metabolic physiology of larval spiny lobsters will aid the development of spiny lobster propagation. The study describes an intermittent flow-through respirometer system for larval crustaceans and discusses its benefits over typical static respirometry methods. The technique is used to determine the standard metabolic rate of the nektonic puerulus stage of the spiny lobster, Sagmariasus verreauxi. Respiration rates of intermoult pueruli (n=5) were determined every 20 min for 16 h. Pueruli metabolism was elevated for 2 h after introduction to the respirometer chamber due to the effects of transfer stress. Thereafter, metabolic rates fluctuated due to spontaneous activity. S. verreauxi pueruli mean standard metabolic rate, determined as the lowest 10% of metabolic recordings, was 0.39 ±0.03 mg h -1 gDW -1 . This is substantially lower than previous recordings of Panulirus cygnus pueruli metabolism using static methodologies. The lower recorded metabolism of S. verreauxi appears due to the use of improved methods which allowed the exclusion of measurements elevated by stress or activity. The results of the current study demonstrate that the standard metabolism of pueruli is substantially reduced to previous recordings of pueruli routine metabolism. Pueruli may have reduced metabolism due to lower maintenance costs associated with lecithotrophy which may be a mechanism of preserving energy during the non-feeding stage. Lower maintenance costs would help pueruli achieve the energetic challenge of swimming from open-ocean to find suitable benthic substrate.
Broad-band study of high-synchrotron-peaked BL Lac object 1ES 1218+304

The origin of the multiwavelength emission from the high-synchrotron-peaked BL Lac 1ES 1218+304 is studied using the data from {\it Swift UVOT/XRT}, {\it NuSTAR} and {\it Fermi-LAT}. A detailed temporal and spectral analysis of the data observed during 2008-2020 in the $\gamma$-ray ($>100$ MeV), X-ray (0.3-70 keV), and optical/UV bands is performed. The $\gamma$-ray spectrum is hard with a photon index of $1.71\pm0.02$ above $100$ MeV. The {\it Swift UVOT/XRT} data show a flux increase in the UV/optical and X-ray bands; the highest $0.3-3$ keV X-ray flux was $(1.13\pm0.02)\times10^{-10}{\rm erg\:cm^{-2}\:s^{-1}}$. In the 0.3-10 keV range the averaged X-ray photon index is $>2.0$ which softens to $2.56 \pm 0.028$ in the 3-50 keV band. However, in some periods, the X-ray photon index became extremely hard ($<1.8$), indicating that the peak of the synchrotron component was above $1$ keV, and so 1ES 1218+304 behaved like an extreme synchrotron BL Lac. The hardest X-ray photon index of 1ES 1218+304 was $1.60 \pm 0.05 $ on MJD 58489. The time-averaged multiwavelength spectral energy distribution is modeled within a one-zone synchrotron self-Compton leptonic model using a broken power-law and power-law with an exponential cutoff electron energy distributions. The data are well explained when the electron energy distribution is $E_{\rm e}^{-2.1}$ extending up to $\gamma_{\rm br/cut}\simeq(1.7-4.3)\times10^{5}$, and the magnetic field is weak ($B\sim1.5\times10^{-2}$ G). By solving the kinetic equation for electron evolution in the emitting region, the obtained electron energy distributions are discussed considering particle injection, cooling, and escape.
A Contract-Based Mobile Charging Scheme for Wireless-Powered Sensors in Industrial Internet of Things Networks

Industrial Internet of Things (IIoT) has provided intelligent industrial operations by leveraging the ubiquity of radio-frequency identification (RFID) and sensor devices. However, a wide range of deployment of IIoT accounts for a considerable amount of energy consumption. Mobile charging is a promising approach to charge low-power IIoT sensors for energy replenishment. In this paper, we consider a mobile charging IIoT network consisting of multiple mobile chargers that can travel through preplanned paths to charge a set of target sensors in the monitoring area. In practice, the limited energy capacity of the mobile chargers constrains their travel time. Thus, the aim of the mobile chargers is to charge more sensors with as less energy as possible. Nonetheless, the mobile chargers might not be aware of the truthful energy demand of the sensors due to information asymmetry. E.g., even if the sensors have sufficient energy to perform their operations, they might report that their current energy level is low with a motivation to receive more energy from the chargers. Information asymmetry leads to other low-power sensors being undercharged and affects the network lifetime. Motivated by this, we develop a contract theory-based mobile charging scheme for the low-power sensors in IIoT network. The optimal contract is derived to maximize the mobile chargers’ utility while meeting the sensors’ interests. Simulation results indicate that our proposed scheme can significantly improve the charging utility than the other mobile charging scheme.
Connective Potential Information for Collectively Interpreting Multi-Layered Neural Networks

paper aims to propose a new type of information-theoretic method to make collective weights, obtained by compressing all connection weights, easily interpretable. The collective weights are to be obtained by averaging all weights by different initial conditions and data subsets, where we need to stabilize the learning processes and the corresponding connection weights. For this purpose, we introduce the connective potential information reduction. The potential information is related to the concept of entropy, but it has a more concrete meaning of how many connection weights are connected with the corresponding neurons. When the potentiality is higher, the number of connection weights between neurons becomes larger. For improved interpretation, we need to reduce the potential information, because it is much easier to understand the inference mechanism with a smaller number of connection weights, though too much reduction may degrade generalization performance. For compromising between interpretation and generalization, we introduce the variance of potentiality, and we try to solve the contradiction of improved interpretation and generalization. We applied the method to the diabetic data set, where we first tried to show that the potential information could be reduced and at the same time the variance of potential information could be changed considerably in intermediate layers. Finally, those compressed weights over different initial conditions and different patterns were averaged to get the final collective weights for interpretation, which turned out to be ones showing easily interpretable, linear, and independent relations between inputs and targets.