Miracle-dz/UniFAR-FTUs huggingface dataset:
Solid lipid nanoparticles as new drug delivery system

The main challenge in cancer chemotherapy is toxic side-effects induced by chemotherapeutic drugs. Thus, alternative methods of drug administration like appropriate drug carrier system is needed to overcome this problem. The main objective of new drug delivery systems is to improve the anti-tumor efficacy of drug and reduce their toxic effects on normal tissues. Recently Solid Lipid Nanoparticles (SLN) as colloidal particulate drug delivery system have received much attention from drug development researchers. The use of solid lipid nanoparticle opens up new perspectives for the formulation of poorly soluble drugs. The SLN is a very complex system with some advantages and disadvantages over other colloidal carrier systems. Tamoxifen, an antiestrogen molecule and strong hydrophobic drug is used as a chemotherapy drug against breast cancers. When tamoxifen encapsulated within solid lipid nanoparticles, it is like free TAM display antitumoral activity against human breast cancer cells. The biological availability of drug is not affected when incorporated into SLN. Therefore SLN could be applied as a drug delivery system for cancer treatments. Key words: Drug delivery systems, solid lipid nanoparticles.
Perceptual Evaluation and Enhancement of VoIP Over IEEE 802.11e

With the apparition of the IEEE 802.11e standard, it is already possible to differentiate and to grant several priorities to traffic flows with different needs. However, it does not solve the performance anomaly problem due to the fair channel access of the 802.11. In this article the behavior of a QBSS is analyzed when the main traffic through it is VoIP and FTP taking into account a perceptual evaluation point of view. The influence of the insertion of users at a smaller speed (performance anomaly) is also studied and simulations show that it is possible to improve the results by means of modifications of some of the parameters that come by default with the standard.
A Novel Workflow to Enrich and Isolate Patient-Matched EpCAMhigh and EpCAMlow/negative CTCs Enables the Comparative Characterization of the PIK3CA Status in Metastatic Breast Cancer

Circulating tumor cells (CTCs), potential precursors of most epithelial solid tumors, are mainly enriched by epithelial cell adhesion molecule (EpCAM)-dependent technologies. Hence, these approaches may overlook mesenchymal CTCs, considered highly malignant. Our aim was to establish a workflow to enrich and isolate patient-matched EpCAMhigh and EpCAMlow/negative CTCs within the same blood samples, and to investigate the phosphatidylinositol 3-kinase catalytic subunit alpha (PIK3CA) mutational status within single CTCs. We sequentially processed metastatic breast cancer (MBC) blood samples via CellSearch® (EpCAM-based) and via Parsortix™ (size-based) systems. After enrichment, cells captured in Parsortix™ cassettes were stained in situ for nuclei, cytokeratins, EpCAM and CD45. Afterwards, sorted cells were isolated via CellCelector™ micromanipulator and their genomes were amplified. Lastly, PIK3CA mutational status was analyzed by combining an amplicon-based approach with Sanger sequencing. In 54% of patients′ blood samples both EpCAMhigh and EpCAMlow/negative cells were identified and successfully isolated. High genomic integrity was observed in 8% of amplified genomes of EpCAMlow/negative cells vs. 28% of EpCAMhigh cells suggesting an increased apoptosis in the first CTC-subpopulation. Furthermore, PIK3CA hotspot mutations were detected in both EpCAMhigh and EpCAMlow/negative CTCs. Our workflow is suitable for single CTC analysis, permitting—for the first time—assessment of the heterogeneity of PIK3CA mutational status within patient-matched EpCAMhigh and EpCAMlow/negative CTCs.
Flagellar Protein Dynamics in Chlamydomonas *

Cilia and flagella appear to be stable, terminal, microtubule-containing organelles, but they also elongate and shorten in response to a variety of signals. To understand mechanisms that regulate flagellar dynamics, Chlamydomonas cells with nongrowing flagella were labeled with 35S, and flagella and basal body components were examined for labeled polypeptides. Maximal incorporation of label into the flagella occurred within 3 h. Twenty percent of the flagellar polypeptides were exchanged. These included tubulins, dyneins, and 80 other axonemal and membrane plus matrix polypeptides. The most stable flagellar structure is the PF-ribbon, which comprises part of the wall of each doublet microtubule and is composed of tubulin and three other polypeptides. Most35S was incorporated into the high molecular weight ribbon polypeptide, rib240, and little, if any, 35S is incorporated into PF-ribbon-associated tubulin. Both wild-type (9 + 2) and 9 + 0 flagella, which lack central microtubules, exhibited nearly identical exchange patterns, so labeling is not due to turnover of relatively labile central microtubules. To determine if flagellar length is balanced by protein exchange, 35S incorporation into disassembling flagella was examined, as was exchange in flagella in which microtubule assembly was blocked by colchicine. Incorporation of 35S-labeled polypeptides was found to occur into flagellar axonemes during wavelength-dependent shortening in pf18 and in fla10 cells induced to shorten flagella by incubation at 33 °C. Colchicine blocked tubulin addition but did not affect the exchange of the other exchangeable polypeptides; nor did it induce any change in flagellar length. Basal bodies also incorporated newly synthesized proteins. These data reveal thatChlamydomonas flagella are dynamic structures that incorporate new protein both during steady state and as flagella shorten and that protein exchange does not, alone, explain length regulation.
Applying Event Stream Processing to Network Online Failure Prediction

Predicting failures on networks and systems is critical in order to maintain high uptime rates. Online failure prediction (OFP) techniques use machine learning and predictive analytics to generate failure models that can be applied to computer network data. These techniques can be provisioned on state-of-the-art stream processing systems, such as Spark Streaming, in order to cope with the scalability challenges from the base data. A big challenge with OFP is selecting the right information to process, as well as the appropriate features in order to achieve high accuracy in predicting failures on complex, interconnected systems. In this article we describe an OFP system built over Apache Spark that takes a repository of network management events, trains a Random Forest model, and uses this model to predict the appearance of future events in near real time. We show through our experiments the usefulness of network management events for accurate predictions, and the advantages of the proposed system in terms of predictive quality, cost, and ease of deployment.
Ice COcktails in molecular cloud coresT

Spectra of the 4.67m (2140cm ? 1) solid-CO absorption feature are presented, towards embedded low mass Young Stellar Objects in nearby molecular cloud cores, mostly in Taurus. The likely composition of the CO-bearing ices is analysed by tting the observations with laboratory data and the statistical signiicance of the results is discussed. Excellent ts to the nonpolar component of the CO-ices along the observed lines of sight are produced with irradiated pure CO ices, as previously suggested by Palumbo & Strazzulla (1993). It does not seem to be possible, however, to constrain the composition of the polar component by analysis of the CO band only. The possible origin of the ion irradiation is discussed. The implications of the non-uniqueness of the t on the determination of the abundance ratio between nonpolar and polar CO-ices are noted. Future observations are suggested to discriminate between the diierent possibilities for the polar component. Predictions are made for the abundance of CO 2 and methanol in the mantles.
Mass-producible replication of highly hydrophobic surfaces from plant leaves

Many plant leaves found in nature are known to exhibit a characteristic of superhydrophobicity (‘lotus leaf effect’). The present study proposes a mass-production method of highly hydrophobic surfaces by simply replicating the highly hydrophobic plant leaf surfaces in two steps: the first step of making a nickel mould via electroforming and the second step of replication via a UV-nanoimprint lithography. Making a nickel mould, either a plant leaf or its negative polymer replica is used as a mandrel in electroforming, and final products become positive or negative polymer replicas of a plant leaf, respectively. It is found that the nickel-mould making using the plant leaf as a mandrel is quite successful and the final products in the form of a positive replica are better than those in the form of a negative replica in terms of replication quality and hydrophobicity. Contact angle values of the positive replicas are less than those of the natural leaves’ surfaces by only 2°–5°.
Keystroke Patterns Classification Using the ARTMAP-FD Neural Network

This paper presents the development of a keystroke dynamics-based user authentication system using the ARTMAP-FD neural network. The effectiveness of ARTMAP- FD in classifying keystroke patterns is analyzed and compared against a number of widely used machine learning systems. The results show that ARTMAP-FD performs well against many of its counterparts in keystroke patterns classification. Apart from that, instead of using the conventional typing timing characteristics, the applicability of typing pressure to ascertaining user's identity is investigated. The experimental results show that combining both latency and pressure patterns can improve the equal error rate (ERR) of the system.
Automating and Validating Program Annotations

Program annotations help to catch errors, improve program understanding, and specify invariants. Adding annotations, however, is often a manual, laborious, tedious, and error prone process especially when programs are large. We offer a novel approach for automating a part of this process. Developers first specify an initial set of annotations for a few variables and types. Our LEarning ANnnotations (Lean) system combines these annotations with run-time monitoring, program analysis, and machine-learning approaches to discover and validate annotations on unannotated variables. We evaluate our prototype implementation on open-source software projects and our results suggest that Lean can generalize from a small set of annotated variables to annotate many other variables. Our experiments show that after users annotate approximately 6% of the program variables and types, Lean correctly annotates an additional 69% of variables in the best case, 47% on the average, and 12% in the worst case, taking less than one hour to run on an application with over 20,000 lines of code.
Signal modeling with self-similar α-stable processes: the fractional Levy stable motion model

The purpose of the correspondence is the introduction of fractional Levy stable motion (fLsm) as a model for signals with long-memory and high variability commonly encountered in natural processes. We present a concise description of this model from a signal processing viewpoint and its successful application to real-world infrared signals for the purpose of resolution enhancement via stochastic interpolation.
Behavioural aspects of cerebellar function in adults with Asperger syndrome

Aside from social deficits, Asperger and autistic individuals also exhibit motor control abnormalities such as impaired gait, balance, manual dexterity and grip. One brain area that has consistently been reported on autopsy and imaging studies to be abnormal in such individuals is the cerebellum. As the cerebellum controls sensorimotor coordination and lesions here typically cause hypotonia, dysmetria and dyscoordination, we performed a series of quantitative tests aimed at investigating cerebellar function in Asperger individuals. Tests examining visually guided movement (rapid pointing), speeded complex movement (finger tapping, rapid hand turning), muscle tone (catching dropped weight), prediction, coordination and timing (balance, grip force and interval timing) were conducted on 12 Asperger subjects and 12 age and IQ matched controls. In comparison to control subjects, Asperger subject’s demonstrated: (i) decreased pointing accuracy and rate, (ii) increased postural instability, and (iii) decreased timing accuracy. IQ was found to co-vary with some parameters of each of these tasks and no further impairments were found on the remaining tests. We suggest that these specific deficits reflect impairment in the ability to integrate sensory input with appropriate motor commands and are consistent with cerebellar dysfunction in Asperger syndrome.
Reliability Calculus: A Theoretical Framework to Analyze Communication Reliability

Communication reliability is one of the most important concerns and fundamental issues in network systems, such as cyber-physical systems, where network components, sensors, actuators, controllers are interconnected with each other. These systems are prevalent in many safety-critical areas, including aerospace, automotive, civil infrastructure, energy, healthcare, manufacturing, and transportation, etc. In such systems, a single link failure, or communication delay could lead to catastrophic consequences. Hence, there is an urgent demand on efficient methodologies to model and analyze the delay distribution of control messages or feedback signals, especially when networks grow more complex and more heterogenous. In this paper, a calculus based on frequency domain analysis is developed to address this goal, so we can model and analyze the reliability of communication in large-scale compositional networked systems. Several network structures (e.g. serial, parallel, circular and backup) are defined as building blocks to model a wide variety of connections in networked systems. The advantages of the proposed theoretical framework over the traditional time domain approaches include the capability to capture higher order moments of system characteristics, calability to analyze the reliability of complex systems, efficiency in calculation and practicability in simulation.
Alumina-Mullite Refractories: Prototypal Components Production for Thermal Shock Tests

Alumina-mullite refractory tiles are used as liners in gas turbines for power production, for the thermal insulation of the combustion chambers. The typical microstructure is characterized by a coarse fraction, in order to increase porosity (and hence thermal insulation) and improve thermal shock resistance (by grain bridging mechanism). A mixture of alumina and ceramic wastes was optimized to manufacture prototypal components, by cold isostatic press (CIP). On sintering at 1600°C, a final composition of 40% mullite and 60% alumina was obtained. For the production of refractory tiles with dimensions similar to the commercial ones, an appropriate mould was CAD-CAM designed and produced, using aluminium and silicone. 115 x 95 x 30 mm3 tiles were obtained and utilized for thermal shock tests. Samples were heated up to 1000°C and quenched to 20°C: this cycle was repeated 30 times before inspecting the macroscopic cracks. The results were compared with those obtained with a standard test for advanced technical ceramics based on MOR measurements. Two different pressing conditions were tested (60 and 150 MPa) in order to get data about a possible industrial production by uniaxial pressing.
Are l‐glutamate and ATP cotransmitters of the peripheral chemoreflex in the rat nucleus tractus solitarius?

Peripheral chemoreflex activation in awake rats or in the working heart–brainstem preparation (WHBP) produces sympathoexcitation, bradycardia and an increase in the frequency of phrenic nerve activity. Our focus is the neurotransmission of the sympathoexcitatory component of the chemoreflex within the nucleus of the tractus solitarius (NTS), and recently we verified that the simultaneous antagonism of ionotropic glutamate and purinergic P2 receptors in the NTS blocked the pressor response and increased thoracic sympathetic activity in awake rats and WHBP, respectively, in response to peripheral chemoreflex activation. These previous data suggested the involvement of ATP and L‐glutamate in the NTS in the processing of the sympathoexcitatory component of the chemoreflex by unknown mechanisms. For a better understanding of these mechanisms, here we used a patch‐clamp approach in brainstem slices to evaluate the characteristics of the synaptic transmission of NTS neurons sending projections to the ventral medulla, which include the premotor neurons involved in the generation of the sympathetic outflow. The NTS neurons sending projections to the ventral medulla were identified by previous microinjection of the membrane tracer dye, 1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethylindocarbocyanine perchlorate (DiI), in the ventral medulla and the spontaneous (sEPSCs) and tractus solitarius (TS)‐evoked excitatory postsynaptic current (TS‐eEPSCs) were recorded using patch clamp. With this approach, we made the following observations on NTS neurons projecting to the ventral medulla: (i) the sEPSCs and TS‐eEPSCs of DiI‐labelled NTS neurons were completely abolished by 6,7‐dinitroquinoxaline‐2,3(1H,4H)‐dione (DNQX), an antagonist of ionotropic non‐NMDA glutamatergic receptors, showing that they are mediated by L‐glutamate; (ii) application of ATP increased the frequency of appearance of spontaneous glutamatergic currents, reflecting an increased exocytosis of glutamatergic vesicles; and (iii) ATP decreased the peak of TS‐evoked glutamatergic currents. We conclude that L‐glutamate is the main neurotransmitter of spontaneous and TS‐evoked synaptic activities in the NTS neurons projecting to the ventral medulla and that ATP has a dual modulatory role on this excitatory transmission, facilitating the spontaneous glutamatergic transmission and inhibiting the TS‐evoked glutamatergic transmission. These data also suggest that ATP is not acting as a cotransmitter with L‐glutamate, at least at the level of this subpopulation of NTS neurons studied.
An Investigation on the Role of Spike Latency in an Artificial Olfactory System

Experimental studies have shown that the reactions to external stimuli may appear only few hundreds of milliseconds after the physical interaction of the stimulus with the proper receptor. This behavior suggests that neurons transmit the largest meaningful part of their signal in the first spikes, and than that the spike latency is a good descriptor of the information content in biological neural networks. In this paper this property has been investigated in an artificial sensorial system where a single layer of spiking neurons is trained with the data generated by an artificial olfactory platform based on a large array of chemical sensors. The capability to discriminate between distinct chemicals and mixtures of them was studied with spiking neural networks endowed with and without lateral inhibitions and considering as output feature of the network both the spikes latency and the average firing rate. Results show that the average firing rate of the output spikes sequences shows the best separation among the experienced vapors, however the latency code is able in a shorter time to correctly discriminate all the tested volatile compounds. This behavior is qualitatively similar to those recently found in natural olfaction, and noteworthy it provides practical suggestions to tail the measurement conditions of artificial olfactory systems defining for each specific case a proper measurement time.
Using spiral dynamic algorithm for maximizing power production of wind farm

This paper presents a preliminary study of a model-free approach based on spiral dynamic algorithm (SDA) formaximizing wind farms power production. The SDA based approach is utilized to find the optimal control parameter of each turbine to maximize the total power production of a wind farm. For simplicity, a single row wind farm model with turbulence interaction between turbines is used to validate the proposed approach. Simulation results demonstrate that the SDA based method produces higher total power production compared to the particle swarm optimization (PSO) and game theoretic (GT) based approaches.
Exploration of efficacy of gland morphology and architectural features in prostate cancer gleason grading

Prostate cancer automatic grading has attracted a lot of attention during the last years [1]. Many research efforts have been fixated on the development of computerized recognition and classification systems to automatically grade Gleason patterns. Automatic computerized Gleason grading methods can be classified into two basic classes: image textural-based class and tissue structural-based (nuclear architecture, gland morphology) class. To the best of our knowledge, tissue structural classification based on three-class classification results including Gleason grade 3, 4 and 5 carcinoma were not reported. The goal of this article is to: (1) develop computerized assessment support systems to automatically grade Gleason patterns 3, 4 and 5 by integrating gland morphology and architectural features; (2) improve classification accuracy especially between intermediate Gleason grades 3 and 4. Computer simulations show an average correct classification accuracy of 97.63%, 96.57% and 87.30% when distinguishing Gleason 3 vs. Gleason 4, Gleason 3 vs. Gleason 5, and Gleason 4 vs. Gleason 5 respectively. These results lead the way towards providing an effective and promising software tool in automatic prostate cancer histological Gleason grading.
Impact of Symptoms of Maternal Anxiety and Depression on Quality of Life of Children with Cerebral Palsy.

INTRODUCTION Cerebral palsy (CP) interferes with the quality of life (QOL) of children with CP, and given that parents report having to often guide their children's decision making, it is important to understand the psychosocial factors that have a potential influence on parent-proxy reports. The purpose of this study was to investigate the impact of maternal anxiety and depression symptoms on parent proxy-reported health-related QOL (HRQOL) for children with CP, while controlling other clinical and demographical variables that may have affect HRQOL. METHODS The HRQOL scores of 97 outpatients with CP, aged 7-18 years, were assessed using the Pediatric QOL Inventory, Parent version (PedsQL-P). Each patient's type of CP, gross and fine motor function levels, severity of intellectual disability (ID), and other clinical variables were recorded. The levels of depression symptoms in each mother were assessed using the Beck Depression Inventory (BDI), and the levels of anxiety symptoms were assessed with the Beck Anxiety Inventory (BAI). RESULTS According to regression analyses, male gender, severity of ID, and higher mothers' BAI scores had negative effects on the PedsQL-P physical scores, and severity of ID and higher mothers' BDI scores had negative effects on the PedsQL-P psychosocial scores. Regarding the determinants of total HRQOL, severity of ID, GMFCS score, and higher mothers' BDI scores negatively impacted the PedsQL-P total scores. CONCLUSION Our findings show significant predictor effects of the mothers' anxiety and depressive symptoms, independent from other clinical variables, on the mother-rated HRQOL scores in children with CP.