Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Link Between the Geographical Origin of European Fermented Foods and the Diversity of Their Bacterial Communities: The Case of Fermented Meats

European fermented meat products are prepared according to a wide variety of different recipes and processing conditions, which can influence their fermentative microbiota. However, due to the diverse processing conditions applied across Europe, it remained unclear to which degree bacterial heterogeneity can be encountered in commercially available fermented meat products and whether this is linked to their geographical origin. Therefore, the bacterial species diversity of 80 fermented meat products available in the Belgian retail, coming from five different countries, was investigated. It was also assessed how this related to the country of origin and the key processing parameters pH and salt concentration. The samples originated from Belgium, France, Germany, Italy, and Spain. In general, Southern European fermented meat products commonly had a higher pH, with their lactic acid bacteria (LAB) communities being represented by Lactobacillus sakei and with mostly Staphylococcus xylosus and Staphylococcus equorum governing over the coagulase-negative staphylococci (CNS) communities. Among these products, the Spanish variants showed a higher prevalence of S. equorum, whereas S. xylosus was the prevailing CNS species in most French and Italian fermented meat products. In contrast, Northern European fermented meat products were generally more acidified and showed a higher prevalence of Pediococcus pentosaceus in their LAB communities, whereas Staphylococcus carnosus represented the CNS communities. Non-parametric statistical tests indicated the impact of the geographical origin on the prevalence of the LAB and CNS species. The latter was likely due to the combination of differences in process technology as well as starter culture use.
Accuracy of Transcranial Doppler Ultrasound Compared with Magnetic Resonance Angiography in the Diagnosis of Intracranial Artery Stenosis

Abstract Background One of the most common causes of acute cerebral infarction (ACI) is intracranial artery stenosis (ICAS). The goal of our study was to evaluate the accuracy of transcranial Doppler (TCD) compared with magnetic resonance angiography (MRA) for diagnosing ICAS in patients with ACI. Materials and Methods Consecutive patients presenting with ACI to the neurology department underwent both MRA and TCD examination within 6 hours of difference. To calculate the agreement between the results of MRA and TCD, kappa coefficient test was used. Sensitivity, specificity, and positive and negative TCD predictive values have been calculated in comparison with MRA. Results A total of 115 patients was included. There were 77 males (66.95%) and 38 females (33.04%). The mean age of patients was 68.32 ± 10.66 years (range 29–80). The agreement between TCD and MRA in detecting stenosis was 0.56 for anterior circulation artery (ACA), and 0.40 for posterior circulation artery. For the detection of ICAS, sensitivity, specificity, positive predictive value, and negative predictive values were 85.9, 90.0, 98.2, and 50.0% for anterior cerebral artery and 73.5, 86.7, 96.2, and 40.0% for posterior cerebral artery, respectively. Conclusions Moderate agreement of anterior circulation stenosis and fair agreement for posterior circulation stenosis was found between TCD and MRA in the evaluation of ICAS. In anterior circulation, the diagnostic accuracy of TCD is higher compared with the posterior circulation.
Pattern of peripheral neuropathy in systemic lupus erythematosus: clinical, electrophysiological, and laboratory properties and their association with disease activity

Aim To study clinical, electrophysiological, and laboratory properties of peripheral neuropathy (PN) in systemic lupus erythematosus (SLE) and their association with disease activity. Patients and methods A total of 30 patients who met the American College of Rheumatology case definition criteria for SLE-PN and 30 age-matched and sex-matched patients with SLE without PN were selected from the Main Alexandria University Hospital Physical Medicine, Rheumatology and Rehabilitation clinic. Demographic data, SLE-related clinical, laboratory data, Systemic Lupus Activity Measure (SLAM) index, and nerve conduction studies were done. This case–control study compared clinical and SLE-related features, laboratory, and SLAM index in patients with SLE with PN versus those without neuropathy. Results The results showed that the most common PN subtype was sensorimotor polyneuropathy which occurred in 18 (60%) patients; the most common PN pathology was axonal degeneration, which occurred 19 (63.3%) patients; and the most common associated nerve entrapment was carpal tunnel syndrome in 10 (33.3%) patients. In comparison between group I (SLE with PN) and group II (SLE without PN), there was no statistically significant difference between the two groups regarding demographic data, disease duration, and lupus clinical features, except malar rash and lupus nephritis, which showed significant increase in patients with SLE with PN compared with patients with SLE without PN (P=0.003 and P<0.001, respectively). There was no statistically significant difference among PN subtype groups regarding sex, age, and immunological markers. Regarding diseases activity, SLAM index showed a significant increase in patients with SLE with PN compared with patients with SLE without PN (P=0.006). Conclusion The pattern of neuropathy in SLE is mainly axonal. Moreover, the most common PN subtype is sensorimotor polyneuropathy. The study suggests significant association of PN in patients with SLE with nephritis, malar rash, and SLAM index.
Chlamydial Infection From Outside to Inside

Chlamydia are obligate intracellular bacteria, characterized by a unique biphasic developmental cycle. Specific interactions with the host cell are crucial for the bacteria’s survival and amplification because of the reduced chlamydial genome. At the start of infection, pathogen-host interactions are set in place in order for Chlamydia to enter the host cell and reach the nutrient-rich peri-Golgi region. Once intracellular localization is established, interactions with organelles and pathways of the host cell enable the necessary hijacking of host-derived nutrients. Detailed information on the aforementioned processes will increase our understanding on the intracellular pathogenesis of chlamydiae and hence might lead to new strategies to battle chlamydial infection. This review summarizes how chlamydiae generate their intracellular niche in the host cell, acquire host-derived nutrients in order to enable their growth and finally exit the host cell in order to infect new cells. Moreover, the evolution in the development of molecular genetic tools, necessary for studying the chlamydial infection biology in more depth, is discussed in great detail.
Wikipedia and Cryptocurrencies: Interplay Between Collective Attention and Market Performance

The production and consumption of information about Bitcoin and other digital-, or 'crypto'-, currencies have grown together with their market capitalisation. However, a systematic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking. Here, we quantify the interplay between the attention towards digital currencies in Wikipedia and their market performance. We consider the entire edit history of currency-related pages, and their view history from July 2015. First, we quantify the evolution of the cryptocurrency presence in Wikipedia by analysing the editorial activity and the network of co-edited pages. We find that a small community of tightly connected editors is responsible for most of the production of information about cryptocurrencies in Wikipedia. Then, we show that a simple trading strategy informed by Wikipedia views performs better, in terms of returns on investment, than classic baseline strategies for most of the covered period. Our results contribute to the recent literature on the interplay between online information and investment markets, and we anticipate it will be of interest for researchers as well as investors.
The Stroop Effect Occurs at Multiple Points Along a Cascade of Control: Evidence From Cognitive Neuroscience Approaches

This article argues that the Stroop effect can be generated at a variety of stages from stimulus input to response selection. As such, there are multiple loci at which the Stroop effect occurs. Evidence for this viewpoint is provided by a review of neuroimaging studies that were specifically designed to isolate levels of interference in the Stroop task and the underlying neural systems that work to control the effects of interference at those levels. In particular, the evidence suggests that lateral prefrontal regions work to bias processing toward the task-relevant dimension of a Stroop stimulus (e.g., its color) and away from the task-irrelevant dimension (e.g., the meaning of the word). Medial prefrontal regions, in contrast, tend to be more involved in response-related and late-stage aspects of control. Importantly, it is argued that this control occurs in a cascade-like manner, such that the degree of control that is exerted at earlier stages influences the degree of control that needs to be exerted at later stages. As such, the degree of behavioral interference that is observed is the culmination of processing in specific brain regions as well as their interaction.
The Dubrava Model—A Novel Approach in Treating Acutely Neurotraumatized Patients in Rural Areas: A Proposal for Management

Abstract Introduction Neurotrauma is one of the leading causes of death and disabilities nowadays and represents one of the largest socioeconomic problems in rich countries, as well as developing ones. A satisfying, medically viable, and cost-effective model of managing acutely neurotraumatized patients, especially ones who come from distant and/or rural areas, has yet to be found. Patient outcome after acute neurotrauma depends on many factors of which the possibility of urgent treatment by an experienced specialist team has a crucial role. Here, we present our own way of managing acutely neurotraumatized patients from distant places which is unique in Croatia, the Dubrava model. Methods We present our 5-year experience cooperating with general hospitals in four neighboring cities (Ĉakovec, Bjelovar, Sisak, and Koprivnica) in managing, operating, and taking care of acutely neurotraumatized patients. Results More than 300 surgeries have been performed in these hospitals through the Dubrava model. Our experience so far provides encouraging results that this system could also be successfully implemented in other institutions. Furthermore, we recorded an increased number of surgeries each year, as well as a good mutual cooperation with the local general hospitals. Discussion This trauma managing model is one of a kind in Croatia. We argue that it is not only better for the patients, providing them with better chances of survival, and disability-free recovery, but is also far superior in many ways to the dominant and currently prevalent way of treating these patients in other parts of Croatia. Conclusion The Dubrava model of treating patients in rural and distant areas is a reliable and proven model with many benefits and as such its implementation should be considered in other institutions as well.
Head and Neck Cancer in Belgium: Quality of Diagnostic Management and Variability Across Belgian Hospitals Between 2009 and 2014

Aims: The study assessed the quality of diagnosis and staging offered to patients with a head and neck squamous cell carcinoma (HNSCC) and the variability across Belgian hospitals. Methods: In total, 9,245 patients diagnosed with HNSCC between 2009 and 2014, were identified in the population-based Belgian Cancer Registry (BCR). The BCR data were coupled with other databases providing information on diagnostic and therapeutic procedures reimbursed by the compulsory health insurance, vital status data, and comorbidities. The use of diagnosis and staging procedures was assessed by four quality indicators (QI) (i.e., use of dedicated head and neck imaging studies, use of PET-CT, TNM reporting and interval between diagnosis and start of treatment), for which a target was defined before the analysis. The association between the binary QIs and observed survival was assessed using Cox proportional hazard models adjusted for potential confounders. Results: Overall, 82.5% of patients received staging by MRI and/or CT of the head and neck region before the start of treatment. In 47.6% of stage III–IV patients eligible for treatment with curative intent, a whole-body FDG-PET(/CT) was performed. The proportion of patients whose cTNM and pTNM stage was reported to the BCR was 80.5 and 78.4%, respectively. The median interval from diagnosis to first treatment with curative intent was 32 days (IQR: 19–46). For none of these QIs the pre-set targets were reached and a substantial variability between centers was observed for all quality indicators. No binary QI was significantly associated with observed survival. Conclusions: The four quality indicators related to diagnosis and staging in HNSCC all showed substantial room for improvement. For none of them the pre-set targets were met at the national level and the variability between centers was substantial. Each Belgian hospital received an individual feedback report in order to stimulate reflection and quality improvement processes.
Spectral Efficiency of Energy Harvesting Random Cognitive Radio Networks in Dual-slope Model

This research article evaluates the performance of an energy harvesting random cognitive radio network employing a dual-slope path-loss model in terms of spectral efficiency. It derives the mathematical expression of spectral efficiency by means of stochastic geometry for secondary receivers present in the network in active mode. The numerical result highlights a rise in the efficiency by 20.7% for an increase of 1 dBm in transmit power at a power splitting ratio of 0.5.
MODELING OF NITRATE REMOVAL FROM AQUEOUS SOLUTION BY Fe-DOPED TiO2 UNDER UV AND SOLAR IRRADIATION USING RESPONSE SURFACE METHODOLOGY

Nitrate is a common groundwater pollutant all over the world. In some regions of Iran, its levels are high enough to cause serious problems to human health and the environment. The objectives of this work were to evaluate the efficiency of Fe-doped TiO2 nanoparticles at removing nitrate from aqueous solutions under UV and solar radiation and to model nitrate removal using response surface methodology techniques. In this study, a response surface methodology based on the Box–Behnken design matrix was used to describe the process of nitrate removal from an aqueous solution with four independent parameters, namely Fe-doped TiO2 (dose 1-2 g l -1 ), nitrate concentration (25-100 mg l -1 ), contact time (10120 min), and pH (4-9). The results indicated that the removal efficiency of nitrate in the presence of ultraviolet and solar radiation was 56.5 % and 21.8%, respectively. The removal efficiency of nitrate increased with time and initial concentration of nitrate. Analysis of variance (ANOVA) indicated that the proposed model was essentially in accordance with the experimental results with the correlation coefficient R 2 = 0.9237 and Adj-R 2 = 0.8347. Response surface methodology (RSM) proved to be a powerful
Computational Psycholinguistics

I want to begin by expressing my deep appreciation to the Nominating and Executive Committees and the Association at large for this tremendous honor. I am especially proud to join my collaborators and friends who previously received the Lifetime Achievement Award: Bill Woods, Martin Kay, Lauri Karttunen, and Joan Bresnan. They have profoundly influenced the contributions for which I think I am being recognized today, as have many other colleagues and students that I have worked with closely over the years. I will follow the tradition set down by most previous LTA recipients by describing how events in my personal history propelled me toward the concepts, theories, and algorithms I have helped to develop and have become known for. This historical perspective is quite different from a paper setting forth some current technical results. Some former recipients, Martin Kay for example, were intrigued by language from a very early age. That was not the case for me. I started as an undergraduate at the University of California Berkeley with a major concentration in physics. I decided at one point that physical reality was a little too messy, and I also discovered that I was not interested in spending long hours in a laboratory. So after a year or two I switched to math. That carried me forward to the middle of my fourth and final year, when I began to contemplate a future as a mathematician. That also seemed a little dry and unappealing. I thought I should look around, even at that late date, and maybe find a specialization that was a little more social and, for me, a little more engaging.
Formalization of Multiway-Join Algorithms

Worst-case optimal multiway-join algorithms are recent seminal achievement of the database community. These algorithms compute the natural join of multiple relational databases and improve in the worst case over traditional query plan optimizations of nested binary joins. In 2014, Ngo, Ré, and Rudra [1] gave a unified presentation of different multi-way join algorithms. We formalized and proved correct their ”Generic Join” algorithm and extended it to support negative joins.
Attribute-Based Credentials in High-Density Platooning

Intelligent transport systems (ITS) rely on V2X communication for allowing coordination and cooperation of traffic participants and increasing traffic efficiency and safety. Communication between traffic participants needs to be secured, especially with respect to authenticity and integrity. Further, a high level of privacy-preservation needs to be ensured. The current European ITS system relies on the use of pseudonym certificates to achieve trust and security while providing a high level of privacy by ensuring unlinkability of messages in the long term. This paper sets out to investigate whether privacy-preserving attribute-based credentials (ABCs) constitute a viable alternative or complement to the current approach. In particular, this paper focuses on the use case of high-density platooning and investigates the applicability of ABCs in that context.
Natural Killer Cells Integrate Signals Received from Tumour Interactions and IL2 to Induce Robust and Prolonged Anti-Tumour and Metabolic Responses

Natural Killer (NK) cells are lymphocytes with an important role in anti-tumour responses. NK cells bridge the innate and adaptive arms of the immune system; they are primed for immediate anti-tumour function but can also have prolonged actions alongside the adaptive T cell response. However, the key signals and cellular processes that are required for extended NK cell responses are not fully known. Herein we show that murine NK cell interaction with tumour cells induces the expression of CD25, the high affinity IL2 receptor, rendering these NK cells highly sensitive to the T cell-derived cytokine IL2. In response to IL2, CD25high NK cells show robust increases in metabolic signalling pathways (mTORC1, cMyc), nutrient transporter expression (CD71, CD98), cellular growth and in NK cell effector functions (IFNγ, granzyme B). Specific ligation of an individual activating NK cell receptor, NK1.1, showed similar increases in CD25 expression and IL2-induced responses. NK cell receptor ligation and IL2 collaborate to induce mTORC1/cMyc signalling leading to high rates of glycolysis and oxidative phosphorylation (OXPHOS) and prolonged NK cell survival. Disrupting mTORC1 and cMyc signalling in CD25high tumour interacting NK cells prevents IL2-induced cell growth and function and compromises NK cell viability. This study reveals that tumour cell interactions and T cell-derived IL2 cooperate to promote robust and prolonged NK cell anti-tumour metabolic responses.
Extraction Process and Antioxidant Activity of Polyphenols from Testa of Quercus mongolica Fischer

In this study,ultrasound assisted extraction was used to extract polyphenols from testa of Quercus mongolica Fischer.Response surface methodology(RSM) combined with Box-Behnken central composite design was applied for modeling and optimizing of three variables that influence the extraction,namely ethanol concentration,extraction time and ratio of liquid to solid.The yields and the contents of polyphenols were selected as responses to optimize the extraction process.The optimum conditions for the extraction of polyphenols were as follows: ethanol concentration 60.56%,ratio of liquid to solid 30.72∶1 mL·g-1,ultrasound time 42.39 min.Under the optimum conditions,the yield and the purity of polyphenols were 0.38% and 18.8%,respectively and EC50 of DPPH free-radical scavenging ability of these polyphenols is 176 μg·mL-1,which is higher than BHA and BHT.
Research on Video Evidence Volume Based on Cloud Storage

—With the development of the Ministry of public security's safety project, video surveillance detectors have been found in every corner of life, it provides an indispensable help to stabilize the public order and detection of criminal cases. In view of the existing problems of storage mode and monitoring video as direct evidence in litigation, this paper first analyzes the problems and challenges in the use of video evidence, and then constructs a video storage system based on cloud storage. Finally, according to the characteristics of monitoring video data involved in the case, the composition of video evidence volume is designed and some suggestions for the extraction and use of video images are proposed. The research of this paper makes the video surveillance storage develop to high capacity, high performance and intelligence. It is more reasonable and legitimate to use as evidence in judicial proceedings.
Ground Segmentation Algorithm Based on 3D Lidar Point Cloud

Aiming at the problem of accurately and efficiently segmenting the ground from the 3D Lidar point cloud, a ground segmentation algorithm based on the features of the scanning line segment is proposed. The algorithm performs denoising and pose correction on the 3D point cloud and divides the scan line according to the Euclidean distance and vertical height difference between adjacent points. Then analyze the characteristics of the adjacent line segments, such as pitch, slope, and height difference, and mark them as the ground segments and obstacle segments according to the classification rules. Finally, the comparison experiments show that this algorithm can accurately segment the ground in real time.
Efficient and Private Scoring of Decision Trees, based on Pre-Computation Technique with Support Vector Machines and Logistic Regression Model

Numerous information driven customized administrations require that private information of clients is scored against a prepared machine learning model. In this paper we propose a novel convention for security protecting order of choice trees, a famous machine learning model in these situations. Our answers is made out of building squares, to be specific a safe correlation convention, a convention for negligently choosing inputs, and a convention for increase. By joining a portion of the building hinders for our choice tree order convention, we additionally enhance beforehand proposed answers for characterization of help vector machines and calculated relapse models. Our conventions are data hypothetically secure and, dissimilar to already proposed arrangements, don't require secluded exponentiations. We demonstrate that our conventions for protection saving arrangement prompt more proficient outcomes from the perspective of computational and correspondence complexities. We introduce exactness and runtime comes about for 7 characterization benchmark datasets from the UCI archive.