Miracle-dz/UniFAR-FTUs huggingface dataset:
Dendritic cell function in the setting of chronic hepatitis cinfection and changes during antiviral treatment

The role of the innate immune system and in particular of dendritic cells, in the establishment of chronic hepatitis C has been studied quite extensively over the last few years but controversy remains as to whether a potential virus-induced defect in DC function leads to sub-optimal initiation of adaptive immune responses and finally to the establishment of chronic infection. In the present thesis we examined monocyte-derived DC (MDDC), generated from patients with chronic hepatitis C (CHC), and healthy subjects in order to gain a better understanding of dendritic cell functions in the setting of hepatitis C infection. We initially observed a defect in CHC patients’ DC capacity to stimulate ‘naive’ CD4+ T-cells into proliferation. Investigating for factors potentially contributing to this defect we demonstrated that HCV genome (both positive strand HCV RNA and the replicative intermediate negative strand HCV RNA) and HCV protein products (HCV core protein) are present in DC without though any obvious correlation to DC functions. We further proccedeed to investigate for potential influence of other, host-related, parameters on DC and tested liver fibrosis, ethanol consumption, HCV viraemia levels and HCV protein products’ concentration in the serum demonstarting significant influences of HCV viraemia / HCV core serum concentration and ethanol consumption on DC functional and phenotypic output. After successful antiviral treatment (with pegylated interferon α and ribavirin) our patients restored their DC functions (allostimulatory capacity, HCV-specific immune-reactivity and IL-12production). Performing ‘cross-over’ experiments we suggest that antiviral treatment exerted its effect by improving mainly DC capacities and not effector CD4+ T-cell reactivity. We also tested plasmacytoid dendritic cell cytokine output after HCV infection and we observed a controversial effect of the virus on the Th1-skewing capacity of this DC subset.
Methods for profling heterogeneous sequencing data

METAGENOMICS which utilises high throughput DNA sequencing is widely applied to study bacteria and viruses and their effects on their host environments. Metagenomics involves collective sequencing of genetic material of the species in an environmental sample, subsequently requiring robust methods to elucidate the characteristics of the species in the sample from the heterogeneous data. A key step in learning the taxonomic diversity of a metagenomic sample is binning. Binning refers to grouping the nucleotide sequences belonging to an individual or closely related species. Identification of appropriate features and machine learning methods is essential in binning a metagenome of many unknown genomes. A significant challenge in binning metagenomic sequences is to bin a sample of closely related species. The thesis addresses this challenge and proposes a new two-tiered workflow called Coverage and composition based binning of Metagenomes (CoMet) for binning assembled sequences (contigs) of a metagenomic sample. It is demonstrated that a combination of features coupled with appropriate unsupervised learning methods can improve the precision in binning while enabling characterization of more species in a metagenome of species with similar genetic variants. Species richness is a key species diversity measure which corresponds to the number of species in an environmental sample. Estimating species richness of a metagenome of viruses (i.e. a virome) based on the reference data is challenging because of the limited amount of sequence data of viruses available in reference databases. A limitation identified with the methods that do not rely on reference sequence data in estimating species richness is the assumption of equal genome length for all the species in the sample. The thesis addresses this limitation by proposing a method to estimate species rich-
Does planning explain why predictability affects reference production?

How does thematic role predictability affect reference production? This study tests a planning facilitation hypothesis – that the predictability effect on reference form can be explained in terms of the time course of utterance planning. In a discourse production task, participants viewed two sequential event pictures, listened to a description of the first picture (depicting a transfer event between two characters), and then provided a description of the second picture (continuing with one thematic role character, either goal or source). We replicated previous findings that goal continuations lead to more reduced forms of reference and shorter latency to begin speaking than source continuations. Additionally, we tracked speakers’ eye movements in two periods of utterance planning, early vs. late. We found that 1) early pre-planning supports the use of reduced forms but is not affected by thematic role; 2) thematic role only affects late planning; and 3) in contrast with our hypothesis, planning does not account for predictability effects on reduced forms. We then speculate that discourse connectedness drives the thematic role predictability effect on reference form choice.
Shooting from the ‘Scrip: Scope of Practice Laws and Access to Immunizations in the Pharmacy Setting

In the past two decades, most states in the United States have added authorization for pharmacists to administer some vaccinations. Expansions of this authority have also come with prescription requirements or other regulatory burdens. The objective of this study was to evaluate the impact of these expansions on influenza immunization rates in adults age 65 and over. A panel data, differences-in-differences regression framework to control for state-level unobserved confounders and shocks at the national level was used on a combination of a dataset of state-level statute and regulatory changes and influenza immunization data from the Behavioral Risk Factor Surveillance System. Giving pharmacists permission to vaccinate had a positive impact on adult influenza immunization rates of 1.4 percentage points for adults age 65 and over. This effect was diminished by the presence of laws requiring pharmacists to obtain patient-specific prescriptions. There was no evidence that allowing pharmacists to administer vaccinations led patients to have fewer annual check-ups with physicians or not have a usual source of health care. Expanding pharmacists’ scope of practice laws to include administering the influenza vaccine had a positive impact on influenza shot uptake. This may have implications for relaxing restrictions on other forms of care that could be provided by pharmacists.
Observational study of adult patients with uncontrolled asthma in pneumology outpatients clinics in Slovenia

Background: Almost 50 % of patients in clinical practice still have poor control of their asthma despite treatment according to the GINA (Global Initiative for Asthma) criteria. The most common causes of uncontrolled asthma are: poor inhaler technique, poor medication adherence, incorrect diagnosis, comorbidities (rhinosinusitis, GERD (Gastroesophageal Reflux Disease), obesity, depression, obstructive sleep apnea) and ongoing exposure to specific triggers (allergens, drugs and smoking). Methods: Observational study was conducted on 323 adult patients with uncontrolled asthma in 14 outpatient pulmonology practices in Slovenia in the period from December 2017 to April 2018. Data about common causes of uncontrolled asthma and exacerbations in the last year were entered in electronic case report forms at the investigator`s site.
INTERDISCIPLINARY CONTEXTUALIZATION (ICon) LESSONS IN TEACHING SENIOR HIGH SCHOOL MATHEMATICS

The study aimed to investigate the effects of Interdisciplinary Contextualization (ICon) lessons in teaching functions and their graphs. The study utilized mixed methods design to describe the features of interdisciplinary contextualization approach and to identify its effect to students’ academic performance. The lessons were implemented to thirty-eight Grade 11 public school students in Albay, Philippines. The features identified are thematic, use of local context, problem-based learning, inquirybased learning and collaborative learning. The features identified came from the teachers interviewed who uses the approach and the researcher’s pertinent document analyses. The problems in the lessons used these features in synthesizing concepts that served as an axis of connection among disciplines. The results obtained from pretest and posttest scores of students revealed that there was a significant difference in favor of the implementation. Consequently, interdisciplinary contextualized lessons helped students to be real-life problem solvers, developed cultural awareness by citing relevant in-context problems and helped connect previously learned concepts from other disciplines. Educators must be aware that Mathematics is part of the students’ personal life, community and cultural heritage. Thus, PEOPLE: International Journal of Social Sciences ISSN 2454-5899 870 interdisciplinary contextualization approach relate the teaching and learning process within specific communities and culture for meaningful learning experiences of the students. This approach that uses integrated lessons in Mathematics make the teaching and learning more accessible, relevant, and meaningful to every students that would further develop 21st century skills.
Empirical likelihood and GMM for spatial models

Abstract We link the empirical likelihood (EL) and GMM for three major spatial models: spatial autoregressive model with spatial autoregressive disturbances (SARAR model), linear regression model with spatial autoregressive errors (SE model) and spatial autoregressive model (SAR model). It is shown that for every GMM estimator (GMME), there is an empirical likelihood (EL) estimator which has the same asymptotic variance as the GMME. Specifically, we show that there exists an EL estimator which is asymptotically efficient as the best GMME proposed by Liu et al. [Liu, X. D. , L. F. Lee, and C. R. Bollinger. 2010. An efficient GMM estimator of spatial autoregressive models. Journal of Econometrics 159 (2):303–19] and the EL confidence regions for the parameters in above models can be constructed without the estimation of asymptotic variances.
A novel conceptual model of intrusion related gold bearing systems and exploration tools

Despite numerous debates conducted in the last two decades, the concept of intrusion related gold systems IRGS remains controversial and sometimes befuddling. The key issue drifts from case to case, i.e., initial to subsequent proposed classifications, presence of gold in reduced fluids-porphyritic environments, non-porphyry gold in orogenic terrains and participation of non-magmatic gold fluids in depositional processes. Trying to avoid atypical or particular aspects of certain deposits, a genuine metallogenetic depiction intends to enhance the intrusion related systems meaning. Gold is either a major constituent or a mere byproduct. A vertical metal zonation develops from surface to depth: Au, Ag  Cu, Pb, Zn  Cu, Au  Cu, Mo (Au), W  Fe, Cu, Au (Co,W)  U, Ce, La. Whether the relationship between different intrusion related occurrences is well known at shallow depth (epithermal, mesothermal, porphyry), so far less knowledge and understanding is assigned to deep seated mineralization (porphyry, Iron OxidesCopper-Gold/IOCG). A specific relationship between those two deep seated ore styles emerges, that is the IOCG, confined to magmatic-hydrothermal type, is situated in the root zone of a deep porphyry system. Complementary information about updated classic exploration tools encompasses specifically geochemical association, geophysical signature, key alteration minerals, Au/Ag ratio and, last but not least, type minerals that contain/include gold in each intrusion related environment. A further valuable tool is given by the estimate of Au grade range specific to each gold bearing mineral sample in shallow or deep seated setting.
Effects of a Realistic O+ Source on Modeling the Ring Current

We use the UNH‐IMEF electric field model to simulate the convection of O+ from the near‐earth plasma sheet into the ring current during the 17 March 2015 storm. Using Van Allen Probes data from the night side apogee, we reconstruct a realistic O+ source. Modeling this storm using the UNH‐IMEF electric field and a dipole magnetic field has previously been found to have good agreement. Using the realistic source along with drift times and charge exchange loss from these results, we model an inbound pass near the peak of the storm where O+ is increasingly dominant over H+. We find that the time‐varying realistic O+ source is necessary to reproduce the observed spectral features and the O+ pressure enhancements at low L‐shells, while our previous results showed that the H+ was able to be modeled sufficiently with a simple, unchanging boundary condition. Further, our results show that adiabatic convective transport of O+ from the near‐earth plasma sheet (L ~ 6) can explain the observed ring current enhancements.
Factors affecting vascular aphasia severity

ABSTRACT Background: Recent studies have emphasized the importance of initial aphasia severity as a determinant of aphasia recovery. However, data on predictors of initial post-stroke aphasia severity itself are far from adequate in the available literature. Aims: The objective of the present study was to enumerate the predictors of initial aphasia severity following stroke. Methods & Procedures: Bengali version of Western Aphasia Battery (BWAB), a validated instrument, was used for language examination. All patients were examined for language deficit during the first week after stroke. Severity was estimated by deducing aphasia quotient (AQ) and considering the severity scale as per BWAB. Lesion assessment was carried out by magnetic resonance imaging (3T) in ischemic stroke (if no contraindications were found) and computed tomography in hemorrhagic stroke. Demographic factors (age, gender, bilingualism, and number of years of formal education), lesion-related factors (type of stroke, lesion volume, cortical versus sub-cortical location, and site of lesion), and initial aphasia type were independent variables, whereas initial aphasia severity (non-severe, AQ = 50 or more; severe, AQ <50) was the dependent variable. Appropriate statistical tests were applied for the analysis of collected data. Among the 515 screened participants with first-ever acute stroke, 208 presented aphasia. Outcomes & Results: On univariate analysis, the factors found to be associated with higher initial severity were monolingualism (p = .014), hemorrhagic stroke (p < .001), larger lesion volume (p < .001), cortico-subcortical mixed stroke lesion (p < .001), and a non-fluent type of aphasia (p < .001). As per binary logistic regression analysis, independent predictors of higher severity were higher volume of lesion (p < .001, OR = 1.651), hemorrhagic stroke (p = .004, OR = 11.987), and non-fluent aphasia (p = .012, OR = 4.796). The overall predictive value of the regression model was 90.4%. Conclusion: The most significant determinants of initial aphasia severity in our sample of stroke patients were lesion-related factors and non-fluent aphasia.
Cloud computing survey on services, enhancements and challenges in the era of machine learning and data science

Cloud computing has sweeping impact on the human productivity. Today it’s used for Computing, Storage, Predictions and Intelligent Decision Making, among others. Intelligent Decision Making using Machine Learning has pushed for the Cloud Services to be even more fast, robust and accurate. Security remains one of the major concerns which affect the cloud computing growth however there exist various research challenges in cloud computing adoption such as lack of well managed service level agreement (SLA), frequent disconnections, resource scarcity, interoperability, privacy, and reliability. Tremendous amount of work still needs to be done to explore the security challenges arising due to widespread usage of cloud deployment using Containers. We also discuss Impact of Cloud Computing and Cloud Standards. Hence in this research paper, a detailed survey of cloud computing, concepts, architectural principles, key services, and implementation, design and deployment challenges of cloud computing are discussed in detail and important future research directions in the era of Machine Learning and Data Science have been identified.
What makes a tweet be retweeted? A Bayesian trigram analysis of tweet propagation during the 2015 Colombian political campaign

This article proposes the use of computationally efficient inverse regression Bayesian method for analysis of tweet propagation of political messages. Our example focuses on the Colombian case, though our method can be used in any election where social media messaging has a direct impact on political outcomes. We find strong evidence that politicians were able to identify the combination of sensitive words to enhance the probability of retweet of the message, which, in turn, had an impact on political outcomes. The contributions of our work entail: (a) an examination of a neglected unit of analysis (trigram) in a language less studied (i.e. Spanish), (b) based on an innovative Bayesian efficient approach and (c) exploiting the predictive power that retweets have on electoral results as an informational diffusion tool in social media. A practical implication of this new methodology is the possibility to adjust political messages as a means to increase voters engagement in political campaigns.
DSFTL: An Efficient FTL for Flash Memory Based Storage Systems

Flash memory is widely used in solid state drives (SSD), smartphones and so on because of their non-volatility, low power consumption, rapid access speed, and resistance to shocks. Due to the hardware features of flash memory that differ from hard disk drives (HDD), a software called FTL (Flash Translation Layer) was presented. The function of FTL is to make flash memory device appear as a block device to its host. However, due to the erase before write features of flash memory, flash blocks need to be constantly availed through the garbage collection (GC) of invalid pages, which incurs high-priced overhead. In the previous hybrid mapping schemes, there are three problems that cause GC overhead. First, operation of partial merge causes more page copies than operation of switch merge. However, many authors just concentrate on reducing operation of full merge. Second, the availability between a data block and a log block makes the space availability of the log block lower, and it also generates a very high-priced operation of full merge. Third, the space availability of the data block is low because the data block, which has many free pages, is merged. Therefore, we propose a new FTL named DSFTL (Dynamic Setting for FTL). In this FTL, we use many SW (sequential write) log blocks to increase operation of switch merge and to decrease operation of partial merge. In addition, DSFTL dynamically handles the data blocks and log blocks to reduce the operations of erase and the high-priced operation of full merge. Additionally, our scheme prevents the data block with many free pages from being merged to increase the space availability of the data block. Our extensive experimental results prove that our proposed approach (DSFTL) reduces the count of erase and increases the operation of switch merge. As a result, DSFTL decreases the garbage collection overhead.
Compositional and antioxidant analysis of peels from different banana varieties (Musa spp.) for their possible use in developing enriched flours

The banana peel represents about 30% of the fruit, it is discarded and could be used for food development, due to its chemical and antioxidant composition. It is rich in fiber, proteins, essential amino acids, polyunsaturated fatty acids, potassium and in phenolic compounds; which could be used in the treatment of certain types of cancer and coronary heart disease. The objective was to bromatologically evaluate banana peels of five different varieties, as well as their antioxidant activity and sensory acceptance for use in food fortification. Bromatological and antioxidant capacity analyzes of five banana varieties (roatán, macho, morado, manzano, and dominico), cereal flour formulation for product generation and sensory evaluation of the food product were performed. The macho banana peel obtained the highest values for protein, fiber and ethereal extract; presented a high antioxidant capacity for ABTS•+ and DPPH• methods. The five varieties of banana peel showed the presence of linoleic and linolenic fatty acids. The macho banana peel, obtained a high presence of essential amino acids. Products with banana peel flour were made with three other flours, where interaction with cornmeal was the best. The sensory evaluation was made with a nacho-type snack, the results showed tendency neither I like nor dislike for attributes of smell, color and flavor. A series of applications for the banana peel were generated to help its production chain and increase food availability.
THE IMPLEMENTATION OF QUADRATIC METHOD USING PV BI-DIRECTIONAL CONVERTER IN CLOSED LOOP CONTROL WITH PI CONTROLLER

In this enormous development of technology, the requirements are new per each day. The needs must be satisfied but fulfilling each requirement will generate new desire or need. The technology is evolving day by day because of this recycling process. The invention of fuel-based vehicles shows some de-merits to evolve and shift over to the electrical vehicles. The proposed paper concentrates its main application to be the electrical vehicles, With an improved form of boost as well as buck converter with high voltage gain and efficiency. This shows close loop operation because of its ability to control a drive or electrical vehicle in the place of load. The bi-directional converter adopts quadratic method in proposed model for highly efficient utilization. This paper focuses on the high efficient utilization of bi-directional converter with quadratic property using proportional integral controller for its switching.
Hydrostatic Pressurization of Dissociated ATDC5 Aggregates as an in Vitro Model of Mechanical Load-induced Chondrocyte Damage

Osteoarthritis is a long-term chronic joint disease and the single most common cause of disability in older adults due to deterioration of articular cartilage. At the cellular level, it is characterized by a decreased expression of cartilage matrix proteins, an increase in cartilage-degrading enzymes and inflammatory markers and cell death. Several mouse or rat in vivo models are routinely used to study osteoarthritis such as the destabilization of the medial meniscus (DMM) model, which alters the joint mechanics. However, there are still very few in vitro tools to study mechanically-induced chondrocyte damage. Here, we used cells from the ATDC5 chondrocyte progenitor cell line and differentiated them into chondrocyte aggregates by seven days of rotation culture; after differentiation, the aggregates were dissociated and the obtained cells were seeded onto Petri dishes to form monolayers; the high chondrocyte marker gene expressions were maintained on the Petri dishes for at least three days; submitting these monolayers to high hydrostatic pressure then led to a rapid down-regulation of chondrocyte marker expression. Such an in vitro cell culture protocol may be useful to study mechanically-induced chondrocyte damage without the need for conventional animal models.