Miracle-dz/UniFAR-FTUs huggingface dataset:
Polynomial matrix QR decomposition for the decoding of frequency selective multiple-input multiple-output communication channels

This study proposes a new technique for communicating over multiple-input multiple-output (MIMO) frequency selective channels. This approach operates by calculating the QR decomposition of the polynomial channel matrix at the receiver on the basis of channel state information, which in this work is assumed to be perfectly known. This then enables the frequency selective MIMO system to be transformed into a set of frequency selective single-input single-output systems without altering the statistical properties of the receiver noise, which can then be individually equalised. A like-for-like comparison with the orthogonal frequency division multiplexing scheme, which is typically used to communicate over channels of this form, is provided. The polynomial matrix system is shown to achieve improved performance in terms of average bit error rate results, as a consequence of time-domain symbol decoding.
Target classification of ISAR images based on feature space optimisation of local non-negative matrix factorisation

The problem of target classification using inverse synthetic aperture radar (ISAR) images is studied under conditions of mass data processing, sparse scattering centre distribution, image deterioration and variation with the radar imaging view, all of which make target classification difficult. In this study, the authors propose a novel method based on combination of the feature space and the visual perception theory to achieve an accurate and robust classification of ISAR images. In order to make full use of local spatial structure information for classification, the local non-negative matrix factorisation (LNMF) is employed to construct an initial feature space, which is then optimised to calculate more discriminable feature projection vectors of each target. The approaches including speckle noise and stripes suppression, centroid and scale normalisation, LNMF, feature space optimisation with the maximum intersubject variation and minimum intrasubject variation and feature projection vectors calculation are detailed. Finally, the classification is performed with a k neighbours classifier. ISAR images used are obtained by range–Doppler imaging method with radar echoes of aircraft models generated by RadBase. Simulation results show a significant improvement on recognition accuracy and robustness of the proposed method.
Redundancy in Key Management for WSNs

Security in wireless sensor networks is commonly based on symmetric encryption and requires key-management systems to establish and exchange secret keys. A constraint that is common to many key-management approaches is an upper bound to the total number of nodes in the network. An example is represented by the schemes based on combinatorial design. These schemes use specific rules for the generation of sets of keys that are distributed to the nodes before deploying the network. The aim of these approaches is to improve the resilience of the network. However, the quantity of data that must be stored by each node is proportional to the number of nodes of the network, so the available memory affects the applicability of these schemes. This paper investigates the opportunity of reducing the storage overhead by distributing the same set of keys to more than one node. In addition, the presence of redundant sets of keys affects the resilience and the security of the network. A careful analysis is conducted to evaluate benefits and drawbacks of redundant key distribution approaches. The results show that the use of redundancy decreases the level of resilience, but it scales well on very large networks.
Web Service based Intelligent Search on Legal Documents

Web services such as RESTful APIs provide high flexibility for knowledge base systems in different domains. To apply it to the legal aspect, we can obtain much data of the case law efficiently enabling us to relate one case to another easily and even to compare the details of a plenty of the case laws simultaneously. Having said that, to ensure the performance of the web services and the accuracy of the data sourcing from them is onerous in the consideration of the backend system for the web services and relevant search engine. In this paper, we introduce a web service for the legal knowledge, LegalKB, enhancing a concept search, and implement a method, WMD ranking method, to speed up the data search through the enhanced system queries. On top of this, we propose a method to automate the optimisation of the system parameters to ensure that the system queries run in the most optimal manner - integration of multiple machine learning methods into our web service to facilitate third-party applications to interface with our web service enlarging the knowledge base to a great extent.
Fast parallel simulation of a manycore architecture with a flit-level on-chip network model

The reliance on simulation for the design of a new architecture continues to increase as the complexity of the architecture increases with more cores integrated and a complex communication fabric. A good compromise between the simulation speed and accuracy should be made in order to explore the wide architectural design space at the early design phase. In this work, we present a novel manycore simulator that achieves fast and scalable performance with a trace-driven parallel simulation technique. Since the communication delay affects the simulation accuracy heavily, the proposed simulator supports a high-speed accurate on-chip network model, which can capture link/buffer congestions. Its development is motivated by an industry project to design a new manycore architecture with 96 cores with a NoC architecture. Experimental results show that the proposed simulator could run real parallel benchmark applications with more than 450 Kcycles/sec/core. It marks a Pareto-optimal simulator between speed and accuracy, compared with existent simulators.
Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought

Global climate change is expected to increase drought duration and intensity in certain regions while increasing rainfall in others. The quantitative consequences of increased drought for ecosystems are not easy to predict. Process-based models must be informed by experiments to determine the resilience of plants and ecosystems from different climates. Here, we demonstrate what and how experimentally derived quantitative information can improve the representation of stomatal and non-stomatal photosynthetic responses to drought in large-scale vegetation models. In particular, we review literature on the answers to four key questions: (1) Which photosynthetic processes are affected under short-term drought? (2) How do the stomatal and non-stomatal responses to short-term drought vary among species originating from different hydro-climates? (3) Do plants acclimate to prolonged water stress, and do mesic and xeric species differ in their degree of acclimation? (4) Does inclusion of experimentally based plant functional type specific stomatal and non-stomatal response functions to drought help Land Surface Models to reproduce key features of ecosystem responses to drought? We highlighted the need for evaluating model representations of the fundamental eco-physiological processes under drought. Taking differential drought sensitivity of different vegetation into account is necessary for Land Surface Models to accurately model drought responses, or the drought impacts on vegetation in drier environments may be over-estimated.
Combination of Oncolytic Measles Virus Armed With BNiP3, a Pro-apoptotic Gene and Paclitaxel Induces Breast Cancer Cell Death

Breast cancer is one of the major causes of cancer related mortality in women worldwide. Limitations of conventional anti-cancer therapies such as severe systemic side effects, narrow therapeutic index, non-specificity, and non-availability of drugs for all types of cancers has resulted in the development of various novel and targeted approaches. The use of viruses as oncolytic agents has gained momentum for the development of an efficient therapeutic platform. In this study, we have developed recombinant measles virus armed with BNiP3, a pro-apoptotic gene of human origin, as an oncolytic agent, and have demonstrated its ability to induce apoptosis in breast cancer cells in vitro. Studies have demonstrated the potential of using oncolytic viruses in combination with conventional therapies as an efficient anti-cancer regimen. We also have explored the synergistic potential of this virus in combination with paclitaxel, and a hydrazone derivative, H2 compound as an anti-cancer agent. MCF-7 and MDA-MB-231, human breast cancer cell lines were used for in vitro studies to evaluate toxic effects of armed virus, rMV-BNiP3 both as a standalone therapy and in combination with paclitaxel or H2 compound, a hydrazone derivative. Generation of armed virus was confirmed by detecting the viral transcript and protein expression, while its oncolytic potential by cell viability assays. Induction of apoptosis was demonstrated by fluorescence based caspase 3 activity and flow cytometry based Annexin V/PI staining. In the current study we have demonstrated the successful generation of an oncolytic measles virus armed with BNiP3 (rMV-BNiP3) and the induction of toxic effects in rMV-BNiP3 infected cells with a curious bias toward MDA-MB-231 cells as compared to MCF-7. Infection of breast cancer cells with rMV-BNiP3 caused induction of cell death, but the combination of rMV-BNiP3 with sub-lethal doses of both paclitaxel and H2 lowered the overall viability of cancer cells. As triple negative breast tumors are highly aggressive and resistant subtype of breast cancer with poor prognosis, comparative sensitivity of MDA-MB-231 cells toward this virus may potentially be used to develop a targeted therapy against triple negative breast cancer.
Maximizing Without Borders: Evidence That Maximizing Transcends Decision Domains

Do maximizers maximize across decision domains? An assumption underlying the literature on maximizing is that the tendency to strive to make the best choice spans domains. The current research provides a direct test of this assumption by examining the association between trait maximizing and domain-specific maximizing, consisting of maximizing measures in a wide range of decisions (consumer goods, services and experiences, and life decisions). Study 1 tested this association at two different time points in order to minimize common method bias. Study 2 was a high-powered pre-registered cross-sectional replication. Results of both studies showed that trait maximizing was associated with higher maximizing tendencies across all three decision domains. However, in line with prior research suggesting that people generally maximize less in experiential than in material domains, trait maximizing was associated with maximizing in services and experiences significantly less than with maximizing in consumer goods or in life decisions. These results provide empirical support for a central tenet of maximizing theory and suggest useful directions for future research.
Surface sediment samples from early age of seafloor exploration can provide a late 19th century baseline of the marine environment

Ocean-floor sediment samples collected up to 150 years ago represent an important historical archive to benchmark global changes in the seafloor environment, such as species’ range shifts and invasions and pollution trends. Such benchmarking requires that the historical sediment samples represent the state of the environment at or shortly before the time of collection. However, early oceanographic expeditions sampled the ocean floor using devices like the sounding tube or a dredge, which potentially disturb the sediment surface and recover a mix of Holocene (surface) and deeper, Pleistocene sediments. Here we use climate-sensitive microfossils as a fast biometric method to assess if historical seafloor samples contain a mixture of modern and glacial sediments. Our assessment is based on comparing the composition of planktonic foraminifera (PF) assemblages in historical samples with Holocene and Last Glacial Maximum (LGM) global reference datasets. We show that eight out of the nine historical samples contain PF assemblages more similar to the Holocene than to the LGM PF assemblages, but the comparisons are only significant when there is a high local species’ temporal turnover (from the LGM to the Holocene). When analysing temporal turnover globally, we show that upwelling and temperate regions had greatest species turnover, which are areas where our methodology would be most diagnostic. Our results suggest that sediment samples from historical collections can provide a baseline of the state of marine ecosystems in the late 19th century, and thus be used to assess ocean global change trends.
A Novel Multifunctional Nanowire Platform for Highly Efficient Isolation and Analysis of Circulating Tumor-Specific Markers

Circulating tumor-specific markers are crucial to understand the molecular and cellular processes underlying cancer, and to develop therapeutic strategies for the treatment of the disease in clinical applications. Many approaches to isolate and analyze these markers have been reported. Here, we propose a straightforward method for highly efficient capture and release of exosomes and circulating tumor cells (CTCs) in a single platform with well-ordered three-dimensional (3D) architecture that is constructed using a simple electrochemical method. Conductive polypyrrole nanowires (Ppy NWs) are conjugated with monoclonal antibodies that specifically recognize marker proteins on the surface of exosomes or CTCs. In response to electrical- or glutathione (GSH)-mediated stimulation, the captured exosomes or cells can be finely controlled for retrieval from the NW platform. A surface having nano-topographic structures allows the specific recognition and capture of small-sized exosome-like vesicles (30–100 nm) by promoting topographical interactions, while physically blocking larger vesicles (i.e., microvesicles, 100–1,000 nm). In addition, vertically aligned features greatly improve cell capture efficiency after modification with desired high-binding affinity biomolecules. Notably, exosomes and CTCs can be sequentially isolated from cancer patients' blood samples using a single NW platform via modulating electrochemical and chemical cues, which clearly exhibits great potential for the diagnosis of various cancer types and for downstream analysis due to its facile, effective, and low-cost performance.
Candida albicans Factor H Binding Molecule Hgt1p – A Low Glucose-Induced Transmembrane Protein Is Trafficked to the Cell Wall and Impairs Phagocytosis and Killing by Human Neutrophils

Complement is a tightly controlled arm of the innate immune system, facilitating phagocytosis and killing of invading pathogens. Factor H (FH) is the main fluid-phase inhibitor of the alternative pathway. Many pathogens can hijack FH from the host and protect themselves from complement-dependent killing. Candida albicans is a clinically important opportunistic yeast, expressing different FH binding molecules on its cell surface, which allow complement evasion. One such FH binding molecule is the transmembrane protein “High affinity glucose transporter 1” (Hgt1p), involved in glucose metabolism. This study demonstrated that Hgt1p transcription and expression is induced and highest at the low, but physiological glucose concentration of 0.1%. Thus, this concentration was used throughout the study. We also demonstrated the transport of Hgt1p to the fungal cell wall surface by vesicle trafficking and its release by exosomes containing Hgt1p integrated in the vesicular membrane. We corroborated Hgt1p as FH binding molecule. A polyclonal anti-Hgt1p antibody was created which interfered with the binding of FH, present in normal human serum to the fungal cell wall. A chimeric molecule consisting of FH domains 6 and 7 fused to human IgG1 Fc (FH6.7/Fc) even more comprehensively blocked FH binding, likely because FH6.7/Fc diverted FH away from fungal FH ligands other than Hgt1p. Reduced FH binding to the yeast was associated with a concomitant increase in C3b/iC3b deposition and resulted in significantly increased in vitro phagocytosis and killing by human neutrophils. In conclusion, Hgt1p also exhibits non-canonical functions such as binding FH after its export to the cell wall. Blocking Hgt1p-FH interactions may represent a tool to enhance complement activation on the fungal surface to promote phagocytosis and killing of C. albicans.
Dominant Patterns of Information Flow in the Propagation of the Neuromagnetic Somatosensory Steady-State Response

Methods of functional connectivity are applied ubiquitously in studies involving non-invasive whole-brain signals, but may be not optimal for exploring the propagation of the steady-state responses, which are strong oscillatory patterns of neurodynamics evoked by periodic stimulation. In our study, we explore a functional network underlying the somatosensory steady-state response using methods of effective connectivity. Human magnetoencephalographic (MEG) data were collected in 10 young healthy adults during 23-Hz vibro-tactile stimulation of the right hand index finger. The whole-brain dynamics of MEG source activity was reconstructed with a linearly-constrained minimum variance beamformer. We applied information-theoretic tools to quantify asymmetries in information flows between primary somatosensory area SI and the rest of the brain. Our analysis identified a pattern of coupling, leading from area SI to a source in the secondary somato-sensory area SII, thalamus, and motor cortex all contralateral to stimuli as well as to a source in the cerebellum ipsilateral to the stimuli. Our results support previously reported empirical evidence collected both in in vitro and in vivo, indicating critical areas of activation of the somatosensory system at the level of systems neuroscience.
Functional Molecules in Locally-Adapted Crops: The Case Study of Tomatoes, Onions, and Sweet Cherry Fruits From Tuscany in Italy

The human diet is characterized by highly energetic molecules, but it also requires non-energetic compounds that are equally useful for cell functioning and for preserving the organism's health status. These “functional” molecules are represented by a wide variety of plant secondary metabolites, such as terpenoids, vitamins and polyphenols with antioxidant power. Widespread commercial crop varieties often contain scarce levels of functional molecules, because they have been mostly selected for productivity, rather than for the content of secondary metabolites. Different scenarios (global economic situation, foreseeable environmental changes) are pushing farmers to review the use of high yield crops and to focus on the valorization of locally-adapted plants. This renewed interest is strengthened by the growing need of consumers for functional foods with beneficial effects on human health and by the willingness to promote sustainable low-input agricultural practices exploiting local climate, soil, water, and (micro)biota. Here, we want to discuss a specific case study concerning locally-adapted crops in Tuscany (Italy). Analyses of nutraceutical molecules in locally-grown crop varieties (namely tomatoes, sweet cherries and onions) have shown that they are characterized by substantially higher functional molecule contents than commercial varieties. Our goal is to promote the high-throughput study of locally-adapted varieties to understand, in a medium-term perspective, whether the cultivation of such plants is a valuable support for the diet and an adequate local economic resource. Such plants can provide a boost to the regional economy, by diversifying the local crop-market landscape. Moreover, the exploitation of locally-grown plants results in the manufacture of fully-traceable products (from the raw bioresource to the finished product) with a “0 km” concept that minimizes the C footprint.
A Quantitative Comparison of Clinically Employed Parameters in the Assessment of Acute Cerebral Ischemia Using Dynamic Susceptibility Contrast Magnetic Resonance Imaging

Purpose: Perfusion magnetic resonance imaging (P-MRI) is part of the mismatch concept employed for therapy decisions in acute ischemic stroke. Using dynamic susceptibility contrast (DSC) MRI the time-to-maximum (Tmax) parameter is quite popular, but its inconsistently defined computation, arterial input function (AIF) selection, and the applied deconvolution method may introduce bias into the assessment. Alternatively, parameter free methods, namely, standardized time-to-peak (stdTTP), zf-score, and standardized-zf (stdZ) are also available, offering consistent calculation procedures without the need of an AIF or deconvolution. Methods: Tmax was compared to stdTTP, zf-, and stdZ to evaluate robustness of infarct volume estimation in 66 patients, using data from two different sites and MR systems (i.e., 1.5T vs. 3T; short TR (= 689 ms) vs. medium TR (= 1,390 ms); bolus dose 0.1 or 0.2 ml/kgBW, respectively). Results: Quality factors (QF) for Tmax were 0.54 ± 0.18 (sensitivity), 0.90 ± 0.06 (specificity), and 0.87 ± 0.05 (accuracy). Though not significantly different, best specificity (0.93 ± 0.05) and accuracy (0.90 ± 0.04) were found for stdTTP with a sensitivity of 0.56 ± 0.17. Other tested parameters performed not significantly worse than Tmax and stdTTP, but absolute values of QFs were slightly lower, except for zf showing the highest sensitivity (0.72 ± 0.16). Accordingly, in ROC-analysis testing the parameter performance to predict the final infarct volume, stdTTP and zf showed the best performance. The odds for stdTTP to obtain the best prediction of the final infarct size, was 6.42 times higher compared to all other parameters (odds-ratio test; p = 2.2*10–16). Conclusion: Based on our results, we suggest to reanalyze data from large cohort studies using the parameters presented here, particularly stdTTP and zf-score, to further increase consistency of perfusion assessment in acute ischemic stroke.
Executive Functions in Alzheimer Disease: A Systematic Review

Alzheimer's disease is a severe irreversible syndrome, characterized by a slow and progressive cognitive decline that interferes with the standard instrumental and essential functions of daily life. Promptly identifying the impairment of particular cognitive functions could be a fundamental condition to limit, through preventive or therapeutic interventions, the functional damages found in this degenerative dementia. This study aims to analyse, through a systematic review of the studies, the sensitivity of four experimental paradigms (Wisconsin Card Sorting Test, Stroop Task, Go/No-Go Task, and Flanker Task) considered as golden standard instruments for executive functions assessment in elderly subjects affected by Alzheimer dementia. This review was carried out according to the PRISMA method. Forty-five studies comparing the executive performance of patients with Alzheimer's dementia (diagnosed according to different classification criteria for dementia) and healthy elderly patients both over the age of sixty, were selected. For the research, PubMed, PsycINFO, PsycArticles databases were used. The study highlighted the importance of using standard protocols to evaluate executive dysfunction in Alzheimer's disease. The Stroop task allows discriminating better between healthy and pathological aging.