Miracle-dz/UniFAR-FTUs huggingface dataset:
Cortical activation by tactile stimulation to face and anterior neck areas: An fMRI study with three analytic methods

The main purpose of this study was to investigate the sensory cortical activation of the anterior neck region and the relationship between the neck and face representation areas. Functional MRI by blood oxygenation level dependent measurements was performed while tactile stimulation was applied to the face or neck area. Nonpainful tactile stimuli were manually delivered by an experimenter at a frequency of ∼1 Hz. Block (epoch) design was adopted with a block duration of 30 s and a whole run duration of 6 min. For each location, two runs were performed. After the image data were preprocessed, both parameteric and nonparametric methods were performed to test the group results. The results showed that (1) unilateral face or neck stimulation could elicit bilateral cortical activation, (2) mainly the face representation and face‐hand junction areas, but not the conventional neck representation area, were activated by face or neck stimulation, and (3) the activation areas were larger when right face or neck was stimulated. In conclusion, the sensory cortical representation area of the anterior neck region was mainly at the junction of hand and face representation area and the activated area was larger when the right face or neck was stimulated. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.
Mahout: Low-overhead datacenter traffic management using end-host-based elephant detection

Datacenters need high-bandwidth interconnection fabrics. Several researchers have proposed highly-redundant topologies with multiple paths between pairs of end hosts for datacenter networks. However, traffic management is necessary to effectively utilize the bisection bandwidth provided by these topologies. This requires timely detection of elephant flows—flows that carry large amount of data—and managing those flows. Previously proposed approaches incur high monitoring overheads, consume significant switch resources, and/or have long detection times. We propose, instead, to detect elephant flows at the end hosts. We do this by observing the end hosts's socket buffers, which provide better, more efficient visibility of flow behavior. We present Mahout, a low-overhead yet effective traffic management system that follows OpenFlow-like central controller approach for network management but augments the design with our novel end host mechanism. Once an elephant flow is detected, an end host signals the network controller using in-band signaling with low overheads. Through analytical evaluation and experiments, we demonstrate the benefits of Mahout over previous solutions.
Assessing the Performance of UAS-Compatible Multispectral and Hyperspectral Sensors for Soil Organic Carbon Prediction

Laboratory spectroscopy has proved its reliability for estimating soil organic carbon (SOC) by exploiting the relationship between electromagnetic radiation and key spectral features of organic carbon located in the VIS-NIR-SWIR (350–2500 nm) region. While this approach provides SOC estimates at specific sampling points, geo-statistical or interpolation techniques are required to infer continuous spatial information. UAS-based proximal or remote sensing has the potential to provide detailed and spatially explicit spectral sampling of the topsoil at the field or even watershed scale. However, the factors affecting the quality of spectral acquisition under outdoor conditions need to be considered. In this study, we investigate the capabilities of two portable hyperspectral sensors (STS-VIS and STS-NIR), and two small-form multispectral cameras with narrow bands in the VIS-NIR region (Parrot Sequoia and Mini-MCA6), to predict SOC content. We collected spectral data under both controlled laboratory and outdoor conditions, with the latter being affected by variable illumination and atmospheric conditions and sensor-sample distance. We also analysed the transferability of the prediction models between different measurement setups by aligning spectra acquired under different conditions (laboratory and outdoor) or by different instruments. Our results indicate that UAS-compatible small-form sensors can be used to reliably estimate SOC. The results show that: (i) the best performance for SOC estimation under outdoor conditions was obtained using the VIS-NIR range, while the addition of the SWIR region decreased the prediction accuracy; (ii) prediction models using only the narrow bands of multispectral cameras gave similar or better performances than those using continuous spectra from the STS hyperspectral sensors; and (iii) when used in outdoor conditions, the micro hyperspectral sensors substantially benefitted from a laboratory model calibration followed by a spectral transfer using an internal soil standard. Based on this analysis, we recommend VIS-NIR portable instruments for estimating spatially distributed SOC data. The integration of these sensors in UAS-mapping devices could represent a cost-effective solution for soil research and precision farming applications when high resolution data are required.
Learning Students' Learning Patterns with Neural Computing

Student modeling is a key ingredient for intelligent interaction with students, and understanding how students learn composite concepts can help us build models of higher quality. An interesting question is how machines can help us infer about students' learning processes of composite concepts from students' external performance. Since Bayesian networks have been used in student modeling in many research projects, we employ them for simulating students' performance in taking tests, and seek methods for learning the original networks based on the simulated students' performance. The problem is not easy because the data we can observe have only indirect and uncertain relationship with the variables for mastery levels, and we would like to know the relationships among these hidden variables. We applied mutual information and artificial neural networks for this learning problem, and we achieved 75% in accuracy even when the item responses have really uncertain relationships with the actual mastery levels.
In Vitro Activation of the Rhesus Macaque Myeloid α-Defensin Precursor proRMAD-4 by Neutrophil Serine Proteinases*

α-Defensins are mammalian antimicrobial peptides expressed mainly by cells of myeloid lineage or small intestinal Paneth cells. The peptides are converted from inactive 8.5-kDa precursors to membrane-disruptive forms by post-translational proteolytic events. Because rhesus myeloid pro-α-defensin-4 (proRMAD-4(20–94)) lacks bactericidal peptide activity in vitro, we tested whether neutrophil azurophil granule serine proteinases, human neutrophil elastase (NE), cathepsin G (CG), and proteinase-3 (P3) have in vitro convertase activity. Only NE cleaved proRMAD-4(20–94) at the native RMAD-4 N terminus to produce fully processed, bactericidal RMAD-4(62–94). The final CG cleavage product was RMAD-4(55–94), and P3 produced both RMAD-4(55–94) and RMAD-4(57–94). Nevertheless, NE, CG, and P3 digests of proRMAD4 and purified RMAD-4(62–94), RMAD-4(55–94), and RMAD-4(57–94) peptides had equivalent in vitro bactericidal activities. Bactericidal peptide activity assays of proRMAD-4(20–94) variants containing complete charge-neutralizing D/E to N/Q or D/E to A substitutions showed that (DE/NQ)-proRMAD-4(20–94) and (DE/A)-proRMAD-4(20–94) were as active as mature RMAD-4(62–94). Therefore, proregion Asp and Glu side chains inhibit the RMAD-4 component of full-length proRMAD-4(20–94), perhaps by a combination of charge-neutralizing and hydrogen-bonding interactions. Although native RMAD-4(62–94) resists NE, CG, and P3 proteolysis completely, RMAD-4(62–94) variants with disulfide pairing disruptions or lacking disulfide bonds were degraded extensively, evidence that the disulfide array protects the α-defensin moiety from degradation by the myeloid converting enzymes. These in vitro analyses support the conclusion that rhesus macaque myeloid pro-α-defensins are converted to active forms by serine proteinases that co-localize in azurophil granules.
Comparison of new topical treatments for herpes labialis: efficacy of penciclovir cream, acyclovir cream, and n-docosanol cream against experimental cutaneous herpes simplex virus type 1 infection.

BACKGROUND There are 3 new topical treatments for herpes labialis that have either been approved by the US Food and Drug Administration (penciclovir cream [Denavir] and n-docosanol cream [Abreva]) or recently undergone extensive clinical evaluation (acyclovir cream). The relative efficacy of these products is unknown. OBJECTIVE To compare the efficacy of penciclovir cream, acyclovir cream, n-docosanol cream, and acyclovir ointment in an experimental animal model of cutaneous herpes simplex virus type 1 (HSV-1) disease. DESIGN The backs of guinea pigs were infected with HSV-1 using a vaccination instrument. Active treatments and corresponding vehicle controls were applied for 3 to 5 days beginning 24 hours after inoculation. MAIN OUTCOME MEASURES After completion of treatment, the animals were killed and the severity of the infection assessed from the number of lesions, the total lesion area, and the lesion virus titer. RESULTS Penciclovir cream effected modest reductions in lesion number (19%), area (38%), and virus titer (88%) compared with its vehicle control, and each of these differences was significantly greater (P<.05) than the reductions effected by acyclovir ointment (0%, 21%, and 75%, respectively). The acyclovir cream effect (reductions of 4%, 28%, and 77%, respectively) was less than that of penciclovir cream, and this difference was confirmed by 2 additional head-to-head experiments. Two experiments with n-docosanol cream failed to show statistically significant differences by any parameter between n-docasonol cream and vehicle control-treated sites or between n-docosanol and untreated infection sites. CONCLUSIONS In this model, the efficacy of penciclovir cream was greater than acyclovir cream, acyclovir cream was greater than or equal to acyclovir ointment, and acyclovir ointment was greater than n-docosanol cream. Since our model was designed to evaluate compounds that function primarily through antiviral activity, the negative findings with n-docosanol in these studies do not exclude that it might work clinically through other mechanisms.
Effect of Atorvastatin on the Concentration, Relative Distribution, and Chemical Composition of Lipoprotein Subfractions in Patients With Dyslipidemias of Type IIA and IIB

The authors investigated the effect of atorvastatin (40 mg qd) on low-density lipoprotein (LDL) particle distribution in patients with dyslipidemias of type IIA (n = 55) and IIB (n = 21). Atorvastatin therapy induced a significant decrease in total and LDL cholesterol in both patient groups. A significant reduction in triglyceride values, which was more profound in type IIB patients, was also observed. In type IIA patients, LDL-3 was the predominant subfraction. Atorvastatin therapy induced a significant reduction in total LDL mass in this group of patients that was mainly due to the reduction in large and intermediate subspecies (LDL-1 to LDL-3), whereas the mass of dense LDL particles (LDL-4 and LDL-5) remained unchanged. As a consequence, the percentage contribution of dense subfractions to the total LDL mass increased significantly after atorvastatin therapy. The dense LDL-4 subfraction was the predominant one in type IIB patients. In this group, atorvastatin therapy resulted in a significant reduction in the total LDL mass, which was due to the reduction in all LDL subfractions. Thus, the percentage mass distribution of LDL particles remained unaffected. These results suggest that the effect of atorvastatin on LDL subfractions is affected by the underlying genetic defect.
A novel approach to partition central and peripheral airway nitric oxide.

BACKGROUND Determining the site of airways inflammation may lead to the targeting of therapy. Nitric oxide (NO) is a biomarker of airway inflammation and can be measured at multiple exhalation flow rates to allow partitioning into bronchial (large/central airway maximal nitric oxide flux [J'awno]) and peripheral (peripheral/small airway/alveolar nitric oxide concentration [Cano]) airway contributions by linear regression. This requires a minimum of three exhalations. We developed a simple and practical method to partition NO. METHODS In 29 healthy subjects (FEV1, 97% ± 3% predicted), 13 patients with asthma (FEV1, 90% ± 4% predicted), 14 patients with COPD (FEV1, 59% ± 3% predicted), and 12 patients with cystic fibrosis (CF) (FEV1, 60% ± 3% predicted), we measured the area under the curve of the NO concentration/exhalation time plot (AUC-NO) at exhalation flow rates of 50, 100, 200, and 300 mL/s. We determined the change of the total AUC-NO production (ΔAUC-NO) among the four different exhalation flow rates and compared these levels to Cano and J'awno indices measured conventionally by linear regression. RESULTS The change in AUC-NO between increasing exhalation flow rates of 50 to 200 mL/s (ΔAUC-NO50-200) was strongly correlated with J'awno in all patient groups as follows: healthy subjects (r = 0.94, P < .001), patients with asthma (r = 0.98, P < .001), patients with COPD (r = 0.93, P < .001), and patients with CF (r = 0.74, P < .05). In all subjects, AUC-NO at an exhalation flow rate of 200 mL/s (AUC-NO200) correlated with Cano (r = 0.69, P < .01). CONCLUSIONS The bronchial production of NO can be determined by measuring ΔAUC-NO50-200, whereas AUC-NO200 measures its peripheral concentration. This approach is simple, quick, and does not require sophisticated equipment or mathematical models.
Mining voter sentiments from Twitter data for the 2016 Uganda Presidential elections

Micro-bogging platforms like Twitter have proved to be fertile ground for political campaigns. In several applications, Twitter data has been mined to understand sentiments of the population, to determine trends and to understand the informal communication amongst people. A key challenge with the Twitter platform is that it produces immense quantities of noisy unstructured user-generated data across multiple social relations. The uniqueness of social media data calls for novel data mining techniques that can effectively handle user-generated content with rich social relations in order to build descriptive and predictive models of social interactions. We analyse Twitter data for the #UgandaDecides hash tag for Uganda Presidential elections 2016, during the period of January to February. We derive inferences from the data and show that in some cases Twitter can be informative on actual events happening on ground. In the analysis we use a word-emotion lexicon to determine the nature of sentiments in the tweets and semantic orientation, to determine the ties conversations within the tweets have with positive and negative contexts, this is based on the pointwise mutual information technique. We find that twitter data analytics using both intensity-based measures and sentiment analysis can be useful to reflect the current offline political sentiment and we make a number of observations related to the task of monitoring public sentiments during an election campaign, including examining a variety of sample sizes, time parameters as well as methods for quantitatively and qualitatively exploring the underlying content.
Role of Human Aldehyde Dehydrogenases in Endobiotic and Xenobiotic Metabolism

The human genome contains at least 17 genes that are members of the aldehyde dehydrogenase (ALDH) superfamily. These genes encode NAD(P)+‐dependent enzymes that oxidize a wide range of aldehydes to their corresponding carboxylic acids. Aldehydes are highly reactive molecules that are intermediates or products involved in a broad spectrum of physiologic, biologic, and pharmacologic processes. Aldehydes are generated during retinoic acid biosynthesis and the metabolism of amino acids, lipids, carbohydrates, and drugs. Mutations in several ALDH genes are the molecular basis of inborn errors of metabolism and contribute to environmentally induced diseases.
Serum ferritin and risk for new‐onset heart failure and cardiovascular events in the community

Heart failure (HF) is a common manifestation of patients with primary and secondary causes of iron overload, whereas in patients with established HF iron deficiency impairs outcome. Whether iron stores, either depleted or in overload, amplify the risk for new‐onset HF among healthy individuals is unknown. The present study aimed to assess whether markers of iron status or the iron‐regulatory hormone hepcidin are associated with new‐onset HF or cardiovascular (CV) events in the general population.
Operational optimization of a stand-alone hybrid renewable energy generation system based on an improved genetic algorithm

In a hybrid renewable energy power generation system, optimization and control is a challenging task because the behaviors of the system are becoming unpredictable and more complex. After the system is built, optimization and control of its operation is important for utilizing the renewable energy efficiently and economically. In the paper, an improved genetic algorithm is developed for achieving the optimization of the hybrid RE system by considering its operation during its life-time. The proposed algorithm is validated by performing a scenario simulation and the results show that the improved genetic algorithm has better convergence speed or accuracy than those of the standard genetic algorithm.
Water Services Sustainability: Institutional Arrangements and Shared Responsibilities

Poor water services in developing countries after national conflict as a result of institutional setups and devastating infrastructures. This study assesses how institutional arrangements have affected the poor water services in Somalia, through thematic analyses. The huge gap in the literature about Somalia highlights the significant need of such research works and the originality of this paper. For this paper, different stakeholders were interviewed from seven zones of the city of Garowe. The results show that public private partnerships (PPP) play a vital role in providing drinking water. The results show that the institutions involved in the water sector in Puntland are not well organized. Roles and responsibilities were unclear, and different governmental institutions criticized each other for deliberately taking over others’ responsibilities, leading to poor and over-priced domestic water quality. Most consumers cannot afford a drinking water supply to their homes, so they are forced to walk long distances and queue for a long time in order to access water. Our analysis shows that it will be difficult for Somalia to achieve Sustainable Development Goal six (SDG 6) (target one) under the current institutional arrangements. Institutional reforms are recommended in the water sector in order to achieve SDG 6 (Target one), and to ensure safe drinking water in Puntland by 2030.
Fast Accurate Detection of Frequency Jumps Using Kalman Filter with Non Linear Improvements

— In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, despite the tradeoff between the noise level and the speed of the detection. In this paper, an improvement is introduced in the Kalman filter, through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in the filter speed with a very low noise level. Additionally, the effect on the response to false alarms is also presented and false alarm rate show improvement.
Optimal Design of Microgrids in Autonomous and Grid-Connected Modes Using Particle Swarm Optimization

The dynamic nature of the distribution network challenges the stability and control effectiveness of the microgrids in both grid-connected and autonomous modes. In this paper, linear and nonlinear models of microgrids operating in different modes are presented. Optimal design of LC filter, controller parameters, and damping resistance is carried out in case of grid-connected mode. On the other hand, controller parameters and power sharing coefficients are optimized in case of autonomous mode. The control problem has been formulated as an optimization problem where particle swarm optimization is employed to search for optimal settings of the optimized parameters in each mode. In addition, nonlinear time-domain-based as well as eigenvalue-based objective functions are proposed to minimize the error in the measured power and to enhance the damping characteristics, respectively. Finally, the nonlinear time-domain simulation has been carried out to assess the effectiveness of the proposed controllers under different disturbances and loading conditions. The results show satisfactory performance with efficient damping characteristics of the microgrid considered in this study. Additionally, the effectiveness of the proposed approach for optimizing different parameters and its robustness have been confirmed through the eigenvalue analysis and nonlinear time-domain simulations.
Cytomegalovirus (CMV) antigenemia assay is more sensitive than shell vial cultures for rapid detection of CMV in polymorphonuclear blood leukocytes

We compared the cytomegalovirus (CMV) antigenemia assay with shell vial cultures of polymorphonuclear leukocyte (PMNL)-enriched blood fractions for rapid diagnosis of CMV viremia. PMNL fractions of 280 blood specimens from 171 patients (170 solid-organ transplant recipients and 1 patient undergoing pretransplant evaluation) were inoculated in shell vial and conventional CMV cultures. A commercially available kit (CMV-vue kit; INCSTAR Corp.) was used for the CMV antigenemia assay, in which PMNL preparations were stained with monoclonal antibodies directed against the CMV protein pp65. Mixed-leukocyte blood fractions from the same blood specimens were inoculated in parallel shell vial and conventional cultures. CMV viremia (defined by the isolation of CMV in conventional cultures) was detected in 32 (13%) of 245 PMNL fractions included in the final analysis. Twenty-eight (87.5%) were also positive in the CMV antigenemia assay, whereas 22 (69%) were positive in shell vial cultures. Ten (4%) additional PMNL fractions positive only in the CMV antigenemia assay were from eight patients with active CMV infections (six patients), who had previous or subsequent episodes of CMV viremia (seven patients), or in whom CMV was isolated in cultures of simultaneously obtained mixed-leukocyte fractions (three patients). Overall, the CMV antigenemia assay was significantly more sensitive than shell vial cultures for detection of CMV in the PMNL fraction of blood leukocytes (P < 0.01, McNemar's test), and we recommend it as the method of choice for rapid diagnosis of CMV viremia.