Miracle-dz/UniFAR-FTUs huggingface dataset:
Pocket backup storage system with cloud integration

A variety of personal backup services now allow users to synchronise their files across multiple devices such as laptops and smartphones. These applications typically operate by synchronising each device with a centralised storage service across the Internet. However, access to the Internet may occasionally not be available, leaving any unsynchronised content in a vulnerable state. To address this, we introduce a cooperative backup storage system that could alternatively make use of storage capacity provided by other devices within close proximity, using ad-hoc or local network connectivity. Such devices can provide a secondary storage tier in case of Internet connectivity issues, and could also be used to forward files to central storage at a later time.
Peripheral chemoreceptors determine the respiratory sensitivity of central chemoreceptors to CO2: role of carotid body CO2

The influence of specific carotid body (CB) normoxic hypocapnia, hypercapnia and normocapnia on the ventilatory sensitivity of central chemoreceptors to systemic hypercapnia was assessed in seven awake dogs with extracorporeal perfusion of the vascularly isolated CB. Chemosensitivity in this preparation was similar to that in the intact animal. Separation of CB circulation from that of the brain was confirmed. When the isolated CB was hypercapnic vs. hypocapnic and when the isolated CB was normocapnic vs. hypocapnic, the group mean central CO2 response slopes of minute ventilation ( V̇I ) (P ≤ 0.01) and mean inspiratory flow rate (VT/TI) (P ≤ 0.05) increased significantly. Tidal volume (VT), breathing frequency (fb)and rate of rise of diaphragm EMG were increased in 6 of 7 dogs but did not achieve statistical significance. We propose that hyperaddition is the dominant form of chemoreceptor interaction under conditions of quiet wakefulness in intact animals and over a wide range of CB PCO2 and PO2 .
Usage and Distribution for Commercial Purposes Requires Written Permission. Intravitreal Daptomycin for Recalcitrant Postoperative Endophthalmitis

Purpose: To report the first case to our knowledge of intravitreal daptomycin used to successfully treat culture-negative vancomycin resistant to exogenous endophthalmitis. Methods: Case report with preoperative, intraoperative, and postoperative findings. Results: A 63-year-old Caucasian male underwent routine pars plana vitrectomy with epiretinal membrane peeling. He developed acute postoperative endophthalmitis, and underwent vitreous tap and injection of intravitreal vancomycin/ceftazidime/dexamethasone. Gram stain showed Gram-positive cocci, but cultures were negative. His infection subsequently proved very recalcitrant and his treatment course involved pars plana vitrectomy with anterior chamber washout and repeat injection of antibiotics, followed by repeat intravitreal vancomycin and ceftazidime. Ultimately, a second vitrectomy with intravitreal daptomycin controlled his intraocular infection. On each occasion, cultures were negative. Conclusion: This case suggests that vanco-mycin resistance should be considered in culture-negative postoperative endophthalmitis, and intravitreal daptomycin should be considered as an important treatment alternative. Although vancomycin resistance is fairly rare in endophthalmitis, acknowledgment of its increasing occurrence rate is critical for optimal management.
Maude as a wide-spectrum framework for formal modeling and analysis of active networks

Modeling and formally analyzing active network systems and protocols is quite challenging, due to their highly dynamic nature and the need for new network models. We propose a wide-spectrum methodology using executable rewriting logic specifications to address this challenge. We also show how, using the Maude rewriting logic language and tools, active network systems, languages, and protocols can be formally specified and analyzed using a wide range of formal methods. Benefits include precise documentation of designs, early discovery of many bugs and omissions, and higher assurance of correct behavior. In this paper we illustrate these methods and their practical usefulness through two case studies: the AER/NCA protocol suite and the PLAN active networks language.
Analysis of semi supervised learning methods towards multi label text classification

The area of multi label text classification is getting more attention of researchers because of its role in the field of information retrieval , text mining , web mining etc. Supervised methods from machine learning are mainly used for its realization. But as it needs labeled data for classification all the time , semi supervised methods are now a day getting popular in the MLTC domain. The goal of Semi supervised learning is to reduce the classification errors using readily available unlabeled data in conjunction with available labeled data. This paper mainly provides survey and analysis of various semi supervised methods used in multi label text classification task ; This overview concludes that consideration of semantic aspects of input document datasets , their representation in conjunction with smoothness and manifold assumptions in semi supervised learning may give more relevant classification results. General Terms Machine learning , Information retrieval , text classification. Keywordssupervised learning, Multi label text classification, Smoothness and manifold assumptions.
Particle Resuspension During the Use of Vacuum Cleaners on Residential Carpet

Vacuuming is generally considered to be an important activity with respect to the cleanliness of indoor environments but may lead to short-term resuspension of particulate matter and elevated particle mass in indoor air. Because resuspended particles often contain toxicants, such as lead and pesticides, or consist of biological agents that can trigger allergic reactions, it is important to understand the role of vacuuming on short-term variations in indoor particulate matter concentrations. The inhalation of particles during vacuuming events may affect adversely those whose occupation requires them to clean a wide range of indoor environments, from homes to schools and offices, as well as those who occupy those environments. In response, a series of 46 experiments was completed to determine time-variant concentrations of both PM 10 and PM 2.5 during various vacuuming activities in 12 separate apartments. Experiments involved the use of two different non-HEPA vacuum cleaners and were completed with a vacuum cleaner activated (switched on) as well as deactivated (switched off). The latter was intended to provide insight on the potential for resuspension of particles by the mechanical agitation of vacuum cleaner movement across carpet. Separate experiments were completed also using “mock” vacuuming simulations, that is, walking on the carpet in a manner consistent with using a vacuum cleaner. Results are presented as incremental particulate matter concentration increases, relative to background (prevacuum) concentrations, and peak-to-background particle concentration ratios. Results indicate significant resuspension of PM 10 mass during vacuum cleaning, with a mean time-averaged PM 10 increase of greater than 17 μ g/m 3 above background. Resuspension of PM 2.5 mass was determined to be small, that is, PM 10 mass was dominated by particles greater than 2.5 μ m. The frequency of vacuuming (between a 10-day standard frequency and several experiments at > 24 days between vacuuming) had little influence on resuspended particle mass. Resuspension by mechanical agitation (rolling of vacuum cleaner across carpet) with the vacuum cleaner switched off was determined to be substantial, with a mean time-averaged (during vacuuming) PM 10 increase of 35 μ g/m 3 relative to background. Peak-to-background PM 10 concentrations exceeded 6 for some experiments and averaged between approximately 3 and 4 for experiments when the vacuum cleaner was switched on.
The Potential of Mushroom Extracts to Improve Chemotherapy Efficacy in Cancer Cells: A Systematic Review

Chemoresistance is a challenge in cancer treatment, limiting the effectiveness of chemotherapy. Mushroom extracts have shown potential as treatments for cancer therapies, offering a possible solution to overcome chemoresistance. This systematic review aimed to explore the role of mushroom extracts in enhancing chemotherapy and reversing chemoresistance in cancer cells. We searched the PubMed, Web of Science and Scopus databases, following the PRISMA guidelines, and registered on PROSPERO. The extracts acted by inhibiting the proliferation of cancer cells, as well as enhancing the effect of chemotherapy. The mechanisms by which they acted included regulating anti-apoptotic proteins, inhibiting the JAK2/STAT3 pathway, inhibiting the ERK1/2 pathway, modulating microRNAs and regulating p-glycoprotein. These results highlight the potential of mushroom extracts to modulate multiple mechanisms in order to improve the efficacy of chemotherapy. This work sheds light on the use of mushroom extracts as an aid to chemotherapy to combat chemoresistance. Although studies are limited, the diversity of mushrooms and their bioactive compounds show promising results for innovative strategies to treat cancer more effectively. It is crucial to carry out further studies to better understand the therapeutic potential of mushroom extracts to improve the efficacy of chemotherapy in cancer cells.
Multiple plasmon excitations in adsorbed two-dimensional systems

Using monolayer graphene as a model system for a purely two-dimensional (2D) electron gas, we show by energy electron loss spectroscopy, highly resolved both in energy and momentum, that there is a significant probability for the excitation of not only one but two dispersing losses. The appearance of both losses is independent of the substrate (we tested graphene on the Si face of 6H-SiC(0001), and on Ir(111) without and with an intercalated Na layer), and the ratio of the slope in the dispersion curves varies between 1.4 (SiC) and 2. While the lower dispersion curve can be attributed to the excitation of the sheet plasmon, in agreement with theoretical model calculations, the upper dispersion branch has not been identified before for plasmonic excitations in a 2D electron gas, and we assign it tentatively to the excitation of a multipole sheet plasmon.
SPARQLing constraints for RDF

The goal of the Semantic Web is to support semantic interoperability between applications exchanging data on the web. The idea heavily relies on data being made available in machine readable format, using semantic markup languages. In this regard, the W3C has standardized RDF as the basic markup language for the Semantic Web. In contrast to relational databases, where data relationships are implicitly given by schema information as well as primary and foreign key constraints, relationships in semantic markup languages are made explicit. When mapping relational data into RDF, it is desirable to maintain the information implied by the origin constraints. As an improvement over existing approaches, our scheme allows for translating conventional databases into RDF without losing general constraints and vital key information. As much as in the relational model, those information are indispensable for data consistency and, as shown by example, can serve as a basis for semantic query optimization. We underline the practicability of our approach by showing that SPARQL, the most popular query language for RDF, can be used as a constraint language, akin to SQL in the relational context. As a theoretical contribution, we also discuss satisfiability for interesting classes of constraints and combinations thereof.
Lens Enhancement of Ubiquitin Conjugation Activity Reduces Intracellular Aggregation of V 76 D Mutant c D-Crystallin

METHODS. Wild type (wt) and V76D mutant cD-crystallin were fused to red fluorescence protein (RFP) and expressed in human lens epithelial cells. The cellular distribution of the expressed proteins was compared by fluorescence microscopy. The solubility of wtand V76D-cD-crystallin was determined by cellular fractionation and Western blotting. Wt-cDRFP and V76D-cD-RFP were also cotransfected along with a ubiquitin ligase (CHIP) or a ubiquitin-conjugating enzyme (Ubc5) into cells. Levels of wtand V76D-cD-crystallin, the percentage of transfected cells with aggregates, and aggregate size were quantified and compared among different groups.
Assessment of The Results of Short Agonist Stop Ovarian Stimulation Protocol in Poor Responder Patients Undergoing ICSI Cycles

Background: Poor ovarian response is defined as the collection of three or fewer oocytes in two prior ovarian stimulation cycles, or collection of three or fewer oocytes in a single stimulation cycle from a woman who is over 40 years of age, or collection of three or fewer oocytes in a single stimulation cycle and an abnormal ovarian reserve test. We aimed to determine if in poor responders’ patients, the SAS stimulation protocol allows for a better number of oocytes, mature oocytes, total embryos at D2 and usable embryos in comparison with the last previous IVF attempt within the same patients. Materials and Methods: We performed a prospective observational study on 56 women aged ≥ 18 and < 43 years who undergo an IVF protocol with the “short agonist stop” (SAS) protocol compared with the same patients’ previous performance in their last IVF attempt. Enrolled patients were treated in two consecutive cycles. The first attempt was achieved with a standard protocol. Patients for whom the standard protocol has failed were treated in the subsequent cycle with the SAS protocol. Results: Regarding the cumulative outcomes, ongoing pregnancy rate was significantly higher in SAS protocol compared to IVF protocol (0% vs. 12.5%, P=0.026 ). Number of cumulative ET, cancellation before oocyte pick, no usable embryo, biochemical pregnancy, and miscarriage rate were insignificantly different between both protocols. Conclusion : The SAS stimulation protocol may offer promising results for poor responders with low prognosis and previous failed IVF.
Universal Morphological Analysis using Structured Nearest Neighbor Prediction

In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly or implicitly encode inductive biases appropriate to the task at hand. We propose instead to treat morphological analysis as a structured prediction problem, where languages with labeled data serve as training examples for unlabeled languages, without the assumption of parallel data. We define a universal morphological feature space in which every language and its morphological analysis reside. We develop a novel structured nearest neighbor prediction method which seeks to find the morphological analysis for each unlabeled language which lies as close as possible in the feature space to a training language. We apply our model to eight inflecting languages, and induce nominal morphology with substantially higher accuracy than a traditional, MDL-based approach. Our analysis indicates that accuracy continues to improve substantially as the number of training languages increases.
Effects of Sleep Deprivation on Action Potential and Transient Outward Potassium Current in Ventricular Myocytes in Rats

Background Sleep deprivation contributes to the development and recurrence of ventricular arrhythmias. However, the electrophysiological changes in ventricular myocytes in sleep deprivation are still unknown. Material/Methods Sleep deprivation was induced by modified multiple platform technique. Fifty rats were assigned to control and sleep deprivation 1, 3, 5, and 7 days groups, and single ventricular myocytes were enzymatically dissociated from rat hearts. Action potential duration (APD) and transient outward current (Ito) were recorded using whole-cell patch clamp technique. Results Compared with the control group, the phases of APD of ventricular myocytes in 3, 5, and 7 days groups were prolonged and APD at 20% and 50% level of repolarization (APD20 and APD50) was significantly elongated (The APD20 values of control, 1, 3, 5, and 7 days groups: 5.66±0.16 ms, 5.77±0.20 ms, 8.28±0.30 ms, 11.56±0.32 ms, 13.24±0.56 ms. The APD50 values: 50.66±2.16 ms, 52.77±3.20 ms, 65.28±5.30 ms, 83.56±7.32 ms, 89.24±5.56 ms. P<0.01, n=18). The current densities of Ito significantly decreased. The current density-voltage (I–V) curve of Ito was vitally suppressed downward. The steady-state inactivation curve and steady-state activation curve of Ito were shifted to left and right, respectively, in sleep deprivation rats. The inactivation recovery time of Ito was markedly retarded and the time of closed-state inactivation was markedly accelerated in 3, 5, and 7 days groups. Conclusions APD of ventricular myocytes in sleep deprivation rats was significantly prolonged, which could be attributed to decreased activation and accelerated inactivation of Ito.
Strict maximum separability of two finite sets: an algorithmic approach

The paper presents a recursive algorithm for the investigation of a strict, linear separation in the Euclidean space. In the case when sets are linearly separable, it allows us to determine the coefficients of the hyperplanes. An example of using this algorithm as well as its drawbacks are shown. Then the algorithm of determining an optimal separation (in the sense of maximizing the distance between the two sets) is presented.
QUALITY BY DESIGN SUPPORTED CONSTRUCTION OF ORAL FAST-DISSOLVING FILMS FOR TELMISARTAN: RECONNOITERING THE QUALITY ATTRIBUTES

Objective: The angiotensin II receptor antagonist telmisartan (TMS) is often used to treat hypertension. The BCS class II antihypertensive drug TMS has a low solubility, poorly absorbed when taken orally. The goal of this study was to formulate an oral fast-dissolving film (OFDF) of TMS. In recent years, the concept of a rapidly dissolving dosage form as an innovative delivery system has gained popularity. By decreasing dosing frequency, maximize therapeutic effectiveness, bioavailability, and stability. It will also prevent the drugs from being metabolized in the first place. This technique allows for faster drug absorption from the gastrointestinal tract (GIT), which might result in a more rapid onset of action. Methods: An experimental design known as Box-Behnken was employed to optimize a OFDF. Mango kernel (100-300 mg), maltodextrin (200-350 mg), and propylene glycol (PG) (15-30%) were chosen as independent variables with the highest preference. Included measurements of T5 tensile strength, disintegration time, folding endurance, elongation, and drug release efficiency as dependent variables. Results: The physical properties of the films were found to be satisfactory, and Fourier transform infrared (FTIR) analysis failed to detect any drug-polymer interaction. F4 was found to have the greatest bioadhesive strength of 49.82 gm and the longest ex-vivo mucoadhesion duration of 189 min. A higher concentration of mango kernel in the formulation resulted in a greater rate of drug release. More than 60% of the drug was discharged within 10 min. Conclusion: The oral mucosa of a rat was used for ex-vivo for irritation studies. Based on the pharmacokinetic plasma parameters, which is made into quick-dissolving films that are taken by mouth, is much better absorbed than aqueous suspensions. Studies of the enhanced formulation's stability showed that F4 may be stored for up to three months without deterioration.
Semantic Description, Publication and Discovery of Workflows in myGrid

The bioinformatics scientific process relies on in silico experiments, which are experiments executed in full in a computational environment. Scientists wish to encode the designs of these experiments as workflows because they provide minimal, declarative descriptions of the designs, overcoming many barriers to the sharing and re-use of these designs between scientists and enable the use of the most appropriate services available at any one time. We anticipate that the number of workflows will increase quickly as more scientists begin to make use of existing workflow construction tools to express their experiment designs. Discovery then becomes an increasingly hard problem, as it becomes more difficult for a scientist to identify the workflows relevant to their particular research goals amongst all those on offer. While many approaches exist for the publishing and discovery of services, there have been few attempts to address where and how authors of experimental designs should advertise the availability of their work or how relevant workflows can be discovered with minimal effort from the user. As the users designing and adapting experiments will not necessarily have a computer science background, we also have to consider how publishing and discovery can be achieved in such a way that they are not required to have detailed technical knowledge of workflow scripting languages. Furthermore, we believe they should be able to make use of others' expert knowledge (the semantics) of the given scientific domain. In this paper, we define the issues related to the semantic description, publishing and discovery of workflows, and demonstrate how the architecture created by the myGrid project aids scientists in this process. We give a walk-through of how users can construct, publish, annotate, discover and enact workflows via the user interfaces of the myGrid architecture; we then describe novel middleware protocols, making use of the Semantic Web technologies RDF and OWL to support workflow publishing and discovery.
High‐Resolution Climate Projections for the Northeastern United States Using Dynamical Downscaling at Convection‐Permitting Scales

To paraphrase former Speaker of the House Tip O'Neill, “All climate change is local”—that is, society reacts most immediately to changes in local weather such as regional heat waves and heavy rainstorms. Such phenomena are not well resolved by the current generation of coupled climate models. Here it is shown that dynamical downscaling of climate reanalyses using a high‐resolution regional model can reproduce both the means and extremes of temperature and precipitation as observed in the well‐measured northeastern United States. Given this result, the downscaling is applied to climate projections for the middle and end of the 21st century under Representative Concentration Pathway (RCP) 8.5 as well as for the historical time period to help assess regional climate impacts in the northeastern United States. The resulting high‐resolution projections are intended to support regional sustainability studies for the northeastern United States and are made publicly available.
Efficient Global Multi Parameter Calibration for Complex System Models Using Machine-Learning Surrogates

In this work, we adress challenges associated with multi parameter calibration of complex system models of high computational expense. We propose to replace the Modelica Model for screening of parameter space by a computational effective Machine-Learning Surrogate, followed by a polishing with a gradient-based optimizer coupled to the Modelica Model. Our results show the superiority of this approach compared to common-used optimization strategies. We can resign on determining initial optimization values while using a small number of Modelica model calls, paving the path towards efficient global optimization. The Machine Learning Surrogate, namely a Physics Enhanced Latent Space Variational Autoencoder (PELS-VAE), is able to capture the impact of most influential parameters on small training sets and delivers sufficiently good starting values to the gradient-based optimizer. In order to make this paper self-contained, we give a sound overview to the necessary theory, namely Global Sensitivity Analysis with Sobol Indices and Variational Autoencoders.