Miracle-dz/UniFAR-FTUs huggingface dataset:
Antioxidant and Anticholinesterase Potential of Six Thymus Species

The present study aimed to evaluate antioxidant and acetylcholinesterase (AChE) inhibitory activities of the ethanolic extracts of six selected Thymus species growing in Croatia (T. longicaulis, T. praecox subsp. polytrichus, T. pulegioides, T. serpyllum subsp. serpyllum, T. striatus, and T. vulgaris). Antioxidant effectiveness was assessed using six different assays, in comparison with rosmarinic acid, luteolin, and reference antioxidants. All tested Thymus extracts possessed DPPH (IC50 = 3–6 μg/mL) and nitric oxide (IC50 = 70–177 μg/mL) free radical scavenging activities, strong reducing properties (IC50 = 11–15 μg/mL), ferrous ion chelating activity (IC50 = 126–389 μg/mL), ability to inhibit lipid peroxidation (IC50 = 34–80 μg/mL), and high total antioxidant capacities (238–294 mg AAE/g). AChE inhibitory activity was examined using Ellman's colorimetric method and all tested extracts showed anti-AChE activity in a dose dependent manner. The values of 10–28%, 23–39%, and 64–86% were obtained for tested concentrations of 0.25, 0.5, and 1 mg/mL, respectively. Additionally, the contents of total hydroxycinnamic derivatives, flavonoids, and tannins in dried plant samples were determined spectrophotometrically. Our results highlighted Thymus species as a rich source of natural antioxidants and AChE inhibitors that could be useful in preventing and treating Alzheimer's disease and other neurodegenerative disorders.
Trees - Structure and Function Fine root dynamics in Slovenian beech forests in relation to soil temperature and water availability

: The ingrowth and mortality of European beech (Fagus sylvatica L.) fine roots (diameters < 2 mm) were studied in relation to environmental variables describing temperature and water availability at four sites, covering a range in environmental conditions likely to be encountered in Slovenian beech forests. Minirhizotron images were used to determine fine root dynamics in a stand and gap in each of the sites for twelve periods during 2007-2009 growing seasons. The environmental variables included air and soil temperatures, precipitation, forest floor precipitation, evapotranspiration, and soil water contents. For data analysis the daily mean values for each period for all variables were used. Fine root ingrowth and mortality were higher in the managed stand and gap compared to the old-growth stand and gap, but only significantly correlated with each other in the case of the managed stand. Forest floor precipitation and soil temperature were significant in explaining fine root ingrowth whereas maximal evapotranspiration, soil temperature and soil water content were more important for fine root mortality. However, the correlations were weak and inconsistent among the four sites. By including site as predictor as well as environmental variables, R2 values of 0.49 and 0.55 for ingrowth and mortality, respectively, were achieved. Despite
Expression of Molecular Markers in Primary Sites and Metastatic Lymph Nodes of Lung Cancer Patients

Background Recently, there is an increasing interest in developing specific treatments while managing lung cancer cases. We tested the expressions of six molecular markers in the primary tumor and the metastatic lymph nodes of lung cancer patients at a single institution in China. Material/Methods A total of 48 patients with lung cancer who were admitted to the Department of Cardiothoracic Surgery, the First Affiliated Hospital of General Hospital of the Chinese People’s Liberation Army, from September 2010 to February 2011 were retrospectively reviewed. Results One of the six biomarkers’ expressions, excision repair cross-complementation group 1 (ERCC-1), was found to be significantly different in primary tumors and metastatic sites in different cancer subtypes. Conclusions The onset and pathogenesis of small-cell lung carcinoma (SCLC) and non-small-cell lung carcinoma (NSCLC) are not completely understood, and the predictions of prognosis are not very reliable. The use of molecular markers to guide treatment of these cancers is currently in its initial stages.
Novel trends in rehabilitation of proprioception and actuation for assistive technology

In the present work I would like to provide some examples of previous researches conducted in the field of Rehabilitation and Assistive Robotics. These two branches of the classical robotics have in common not only the technology but also the multidisciplinary aspect which ranges from neurosciences and biomechanics to actuation design and haptics. The use of customized high performance haptic displays will be discussed and some example for therapeutic purpose will be illustrated. Starting from the concept of complaint actuation, which nowadays represents the great challenge in assistive technology, a novel solution using carbon fibers and composite material will be described, providing a novel approach to master flexible materials when they are used to improve the dynamics in human machine interaction.
Detection of Action Potentials in the Presence of Noise Using Phase-Space Techniques

— Emerging Bio-engineering fields such as Brain Computer Interfaces, neuroprothesis devices and modeling and simulation of neural networks have led to increased research activity in algorithms for the detection, isolation and classification of Action Potentials (AP) from noisy data trains. Current techniques in the field of ‘unsupervised no-prior knowledge’ biosignal processing include energy operators, wavelet detection and adaptive thresholding. These tend to bias towards larger AP waveforms, AP may be missed due to deviations in spike shape and frequency and correlated noise spectrums can cause false detection. Also, such algorithms tend to suffer from large computational expense. A new signal detection technique based upon the ideas of phase-space diagrams and trajectories is proposed based upon the use of a delayed copy of the AP to highlight discontinuities relative to background noise. This idea has been used to create algorithms that are computationally inexpensive and address the above problems. Distinct AP have been picked out and manually classified from real physiological data recorded from a cockroach. To facilitate testing of the new technique, an Auto Regressive Moving Average (ARMA) noise model has been constructed bases upon background noise of the recordings. Along with the AP classification means this model enables generation of realistic neuronal data sets at arbitrary signal to noise ratio (SNR).
Adaptive censoring for large-scale regressions

Albeit being in the big data era, a significant percentage of data accrued can be overlooked while maintaining reasonable quality of statistical inference at affordable complexity. By capitalizing on data redundancy, interval censoring is leveraged here to cope with the scarcity of resources needed for data exchanging, storing, and processing. By appropriately modifying least-squares regression, first- and second-order algorithms with complementary strengths that operate on censored data are developed for large-scale regressions. Theoretical analysis and simulated tests corroborate their efficacy relative to contemporary competing alternatives.
A security analysis of the OAuth protocol

The OAuth 2.0 authorization protocol standardises delegated authorization on the Web. Popular social networks such as Facebook, Google and Twitter implement their APIs based on the OAuth protocol to enhance user experience of social sign-on and social sharing. The intermediary authorization code can be potentially leaked during the transmission, which then may lead to its abuse. This paper uses an attacker model to study the security vulnerabilities of the OAuth 2.0 protocol. The experimental results show that common attacks such as replay attacks, impersonation attacks and forced-login CSRF attacks are capable of compromising the resources protected by the OAuth 2.0 protocol. The paper presents a systematic analysis of the potential root causes of the disclosed vulnerabilities.
Nucleocapsid: A Mechanism for Persistence Modulate the Immune Response to the The Secreted Hepatitis B Precore Antigen Can

The hepatitis B precore Ag (HBeAg) is a secreted nonparticulate version of the viral nucleocapsid hepatitis B core Ag (HBcAg), and its function is unknown. A proportion of HBeAg-speciﬁc Th cells evade deletion/anergy in HBeAg-transgenic (Tg) mice and mediate anti-HBe “autoantibody” (autoAb) production after in vivo activation with the appropriate Th cell peptide. This model system was used to determine how secretory HBeAg may effect deletion of Th cells in the periphery. For this purpose, HBeAg-Tg mice were bred with Fas and Fas ligand (FasL)-defective lpr / lpr and gld / gld mutant mice. Fas-FasL interactions mediate activation-induced apoptosis in the periphery. In HBeAg-Tg/ 1 mice, high-titrated anti-HBe autoAb was produced that was exclusively composed of the IgG1 isotype (i.e., Th2-like proﬁle). In contrast, HBeAg-Tg/ lpr and HBeAg-Tg/ gld mice produced signiﬁcantly less anti-HBe autoAb, and the IgG isotype patterns were broadened to include IgG2a, IgG2b and IgG3 as well as IgG1 (i.e., mixed Th1/Th2-like proﬁle). These results suggest that HBeAg-speciﬁc Th1 cells are preferentially depleted by Fas-FasL-mediated interactions. The effect of circulating HBeAg on HBcAg-speciﬁc Th1 cells was also examined by transferring HBe/HBcAg-speciﬁc Th cells into dual HBeAg- and HBcAg-expressing Tg recipient mice. The presence of serum HBeAg ablated the expected Th1-mediated anti-HBc Ab response and shifted it toward a Th2 phenotype. These results suggest that in the context of a hepatitis B viral infection, circulating HBeAg has the potential to preferentially deplete inﬂammatory HBeAg- and HBcAg-speciﬁc Th1 cells that are necessary for viral clearance, thereby promoting hepatitis B virus persistence. and anti-HBe IgG Ab was measured in murine sera by an indirect solid-phase ELISA using rHBcAg solid-phase ligands (29). The are representing the reciprocal of of an OD three that of preimmunization IgG isotype-speciﬁc ELISAs were performed using IgG1-, IG2a-, IgG2b-, and IgG3-speciﬁc second Abs (Southern Biotech- nology, AL).
Towards robust estimation of systolic time intervals using head-to-foot and dorso-ventral components of sternal acceleration signals

Continuous measurement of cardiac time intervals throughout normal activities of daily living is of interest for both chronic disease management and preventive wellness monitoring. Systolic time intervals in particular - i.e., pre-ejection period (PEP) and left ventricular ejection time (LVET) - have been shown to be relevant to assessing myocardial health and performance, but are challenging to measure with wearable sensors. In this paper, we present novel methods for estimating PEP and LVET from a single three-axis accelerometer placed at the sternum, based on the measurement of cardiogenic vibrations: seismocardiography (SCG) and ballistocardiography (BCG). Although such signals have been examined in the existing literature, the analysis and interpretation has focused mainly on the dorso-ventral components only in the context of systolic time interval estimation. In this paper, we find that features extracted from the head-to-foot accelerations yield better correlations to PEP measured from impedance cardiogram (ICG) than standard approaches based on dorso-ventral components. Additionally, we examine the effects of postural variations on the correlation between PEP estimated from accelerometer and ICG signals and also on correlation between LVET estimated from both sensors. We determine that such correlations are robust to postural changes. Based on these findings, we anticipate that wearable, accelerometer based vibration measurements from standing subjects can be used for robust systolic time interval estimation in a variety of ubiquitous cardiovascular health and fitness sensing applications.
Effective Data-Race Detection for the Kernel

Data races are an important class of concurrency errors where two threads erroneously access a shared memory location without appropriate synchronization. This paper presents DataCollider, a lightweight and effective technique for dynamically detecting data races in kernel modules. Unlike existing data-race detection techniques, DataCollider is oblivious to the synchronization protocols (such as locking disciplines) the program uses to protect shared memory accesses. This is particularly important for low-level kernel code that uses a myriad of complex architecture/device specific synchronization mechanisms. To reduce the runtime overhead, DataCollider randomly samples a small percentage of memory accesses as candidates for data-race detection. The key novelty of DataCollider is that it uses breakpoint facilities already supported by many hardware architectures to achieve negligible runtime overheads. We have implemented DataCollider for the Windows 7 kernel and have found 25 confirmed erroneous data races of which 12 have already been fixed.
A personalized two-tier cloaking scheme for privacy-aware location-based services

The ubiquity of modern mobile devices with GPS modules and Internet connectivity such as 3G/4G techniques have resulted in rapid development of Location-Based Services (LBSs). However, users enjoy the convenience provided by the untrusted LBS server at the cost of their privacy. To protect user's sensitive information against adversaries with side information, we design a personalized spatial cloaking scheme, termed TTcloak, which provides k-anonymity for user's location privacy, 1-diversity for query privacy and desired size of cloaking region for mobile users in LBSs, simultaneously. TTcloak uses Dummy Query Determining (DQD) algorithm and Dummy Location Determining (DLD) algorithm to find out a set of realistic cells as candidates, and employs a CR-refinement Module (CRM) to guarantee that dummy users are assigned into the cloaking region with desired size. Finally, thorough security analysis and empirical evaluation results verify our proposed TTcloak.
You're driving and texting: detecting drivers using personal smart phones by leveraging inertial sensors

In this work, we address a critical task of detecting the user behavior of driving and texting simultaneously using smartphones. We propose, design, and implement TEXIVE which achieves the goal of distinguishing drivers and passengers, and detecting texting operations during driving utilizing irregularities and rich micro-movements of users. Without relying on any external infrastructures and additional devices, and no need to bring any modification to vehicles, TEXIVE is able to successfully detect dangerous operations with good sensitivity, specificity and accuracy. We conduct experimental study of TEXIVE with the help of a number of volunteers using various vehicles and smartphones. Our results indicate that TEXIVE has a classification accuracy of 87.18%, and precision of 96.67%.
Expression of Phosphocitrate-Targeted Genes in Osteoarthritis Menisci

Phosphocitrate (PC) inhibited calcium crystal-associated osteoarthritis (OA) in Hartley guinea pigs. However, the molecular mechanisms remain elusive. This study sought to determine PC targeted genes and the expression of select PC targeted genes in OA menisci to test hypothesis that PC exerts its disease modifying activity in part by reversing abnormal expressions of genes involved in OA. We found that PC downregulated the expression of numerous genes classified in immune response, inflammatory response, and angiogenesis, including chemokine (C-C motif) ligand 5, Fc fragment of IgG, low affinity IIIb receptor (FCGR3B), and leukocyte immunoglobulin-like receptor, subfamily B member 3 (LILRB3). In contrast, PC upregulated the expression of many genes classified in skeletal development, including collagen type II alpha1, fibroblast growth factor receptor 3 (FGFR3), and SRY- (sex determining region Y-) box 9 (SOX-9). Immunohistochemical examinations revealed higher levels of FCGR3B and LILRB3 and lower level of SOX-9 in OA menisci. These findings indicate that OA is a disease associated with immune system activation and decreased expression of SOX-9 gene in OA menisci. PC exerts its disease modifying activity on OA, at least in part, by targeting immune system activation and the production of extracellular matrix and selecting chondroprotective proteins.
An optimal algorithm for checking regularity: (extended abstract)

We present a deterministic algorithm <i>A</i> that, in <i>O</i>(<i>m</i><sup>2</sup>) time, verifies whether a given <i>m</i> by <i>m</i> bipartite graph <i>G</i> is <i>regular,</i> in the sense of Szemerédi [18]. In the case in which <i>G</i> is <i>not</i> regular enough, our algorithm outputs a <i>witness</i> to this irregularity. Algorithm <i>A</i> may be used as a subroutine in an algorithm that finds an ε-regular partition of a given <i>n</i>-vertex graph Γ in time <i>O</i>(<i>n</i><sup>2</sup>). This time complexity is optimal, up to a constant factor, and improves upon the bound <i>O</i>(<i>M</i>(<i>n</i>)), proved by Alon, Duke, Lefmann, Rödl, and Yuster [1, 2], where <i>M</i>(<i>n</i>) = <i>O</i>(<i>n</i><sup>2.376</sup>) is the time required to square a 0-1 matrix over the integers.Our approach is elementary, except that it makes use of linear-sized expanders to accomplish a suitable form of deterministic sampling.
DDoS Benchmarks and Experimenter's Workbench for the DETER Testbed

While the DETER testbed provides a safe environment and basic tools for security experimentation, researchers face a significant challenge in assembling the testbed pieces and tools into realistic and complete experimental scenarios. In this paper, we describe our work on developing a set of sampled and comprehensive benchmark scenarios, and a workbench for experiments involving denial-of-service (DoS) attacks. The benchmark scenarios are developed by sampling features of attacks, legitimate traffic and topologies from the real Internet. We have also developed a measure of DoS impact on network services to evaluate the severity of an attack and the effectiveness of a proposed defense. The benchmarks are integrated with the testbed via the experimenter's workbench - a collection of traffic generation tools, topology and defense library, experiment control scripts and a graphical user interface. Benchmark scenarios provide inputs to the workbench, bypassing the user's selection of topology and traffic settings, and leaving her only with the task of selecting a defense, its configuration and deployment points. Jointly, the benchmarks and the experimenter's workbench provide an easy, point-and-click environment for DoS experimentation and defense testing.
Inheritance of Hetero-Diploid Pollen S-Haplotype in Self-Compatible Tetraploid Chinese Cherry (Prunus pseudocerasus Lindl)

The breakdown of self-incompatibility, which could result from the accumulation of non-functional S-haplotypes or competitive interaction between two different functional S-haplotypes, has been studied extensively at the molecular level in tetraploid Rosaceae species. In this study, two tetraploid Chinese cherry (Prunus pseudocerasus) cultivars and one diploid sweet cherry (Prunus avium) cultivar were used to investigate the ploidy of pollen grains and inheritance of pollen-S alleles. Genetic analysis of the S-genotypes of two intercross-pollinated progenies showed that the pollen grains derived from Chinese cherry cultivars were hetero-diploid, and that the two S-haplotypes were made up of every combination of two of the four possible S-haplotypes. Moreover, the distributions of single S-haplotypes expressed in self- and intercross-pollinated progenies were in disequilibrium. The number of individuals of the two different S-haplotypes was unequal in two self-pollinated and two intercross-pollinated progenies. Notably, the number of individuals containing two different S-haplotypes (S1- and S5-, S5- and S8-, S1- and S4-haplotype) was larger than that of other individuals in the two self-pollinated progenies, indicating that some of these hetero-diploid pollen grains may have the capability to inactivate stylar S-RNase inside the pollen tube and grow better into the ovaries.
e-Social work in practice: a case study

ABSTRACT This paper presents a theoretical reflection on e-social work by considering a case study: an intervention programme with vulnerable people, included in the services catalogue of a non-governmental organization (NGO), Zaragoza Red Cross Assembly. This programme cares for older people with a home assistance system mediated by information and communication technologies (ICTs). The digital convergence of the Spanish Red Cross and the digitalization of internal processes were accelerated by the use of ICTs as a tool in the aftermath of the 2008 crisis: first, to manage bureaucratic matters; second, to coordinate professionals and third, to interact with users. The text is divided into five sections including an introduction and final remarks. The first section describes the intervention programme and its evolution from a traditional social work vision to an e-social work perspective. The second section describes and analyses the intervention programme and the incorporation of ICTs in this NGO, over more than two decades. The third section describes professional contributions to the implementation and adaptation of social work to new social and technological circumstances and users’ requirements based on these intervention experiences.
Human activity recognition based on compressed sensing

Fast and accurately recognizing human activities is a major challenge in wireless body sensor networks. In this paper, with the help of wearable sensors, the recognition of human activities is well solved from a compressed sensing perspective. Our proposed method first compresses the original sensing data collected using wearable sensors by applying random projections on each sensor node before the data are transmitted to the central node. On the central node, each activity test sample can be approximately represented as a linear combination of all the activity samples in the training set. Then the L1 minimization method is applied to derive the sparse representation of the test sample. Residuals between the activity test sample and its corresponding sparse representation form with only nonzero entries in each activity class are calculated. The activity test sample is finally classified into the activity class with the smallest residual. Our sparse representation based activity recognition method is evaluated on a real-world dataset and its experimental results are also compared with those of Support Vector Machine and Hidden Markov Model. Outcomes of the numerical experiments show that our proposed method achieves the highest recognition rate among the three methods, which verifies the effectiveness of our method and demonstrates that sparse representation classification method based on random projections is promising in recognizing human activities using wearable sensors.