Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Abrogation of Gelatinase Activity Extends the Time Window for tPA Thrombolysis after Embolic Focal Cerebral Ischemia in Mice

Abstract Acute ischemic stroke (AIS) is caused by clotting in the cerebral arteries, leading to brain oxygen deprivation and cerebral infarction. Recombinant human tissue plasminogen activator (tPA) is currently the only Food and Drug Administration-approved drug for ischemic stroke. However, tPA has to be administered within 4.5 h from the disease onset and delayed treatment of tPA can increase the risk of neurovascular impairment, including neuronal cell death, blood-brain barrier (BBB) disruption, and hemorrhagic transformation. A key contributing factor for tPA-induced neurovascular impairment is activation of matrix metalloproteinase-9 (MMP-9). We used a clinically-relevant mouse embolic model of focal-cerebral ischemia by insertion of a single embolus of blood clot to block the right middle cerebral artery. We showed that administration of the potent and highly selective gelatinase inhibitor SB-3CT extends the time window for administration of tPA, attenuating infarct volume, mitigating BBB disruption, and antagonizing the increase in cerebral hemorrhage induced by tPA treatment. We demonstrated that SB-3CT attenuates tPA-induced expression of vascular MMP-9, prevents gelatinase-mediated cleavage of extracellular laminin, rescues endothelial cells, and reduces caveolae-mediated transcytosis of endothelial cells. These results suggest that abrogation of MMP-9 activity mitigates the detrimental effects of tPA treatment, thus the combination treatment holds great promise for extending the therapeutic window for tPA thrombolysis, which opens the opportunity for clinical recourse to a greater number of patients.
Identifying traces of copper in basavakote, Karnataka using hyperspectral remote sensing

The Copper mineral has various uses and it's demand in India is found to be increasing. Copper is essential for human beings, animal and all living organisms. Copper in metal form is also very important. Finding traces of this mineral in India will increase the country's mineral resource and can be used for mining operations. The mineral is generally found in ores like cuprite, azurite, chalcopyrite, bornite and malachite. Copper's property of corrosion resistance and good conductor of heat and electricity makes its purpose most important in the construction field. Using hyperspectral remote sensing techniques, the presence of copper in basavanakote, karnataka is found. The hypespectral remote sensing technique gives high resolution because of its continuous 242 bands. The data is obtained from the USGS — Earth Explorer. This data is being processed using the ENVI software. The presence of copper in the study area is determined by spectral analyst technique. It provides a probability score of 79.43%. The obtained result is then validated using a Spectoradiometer.
Performance Guaranteed Traffic Signal Control with Frame-Based Algorithm

In urban area, fast growth in the number of vehicles has led to a series of traffic problems, including traffic jams,high traffic accident rates, etc. Efficient traffic signal control methods has been shown to be an essential way to significantly mitigate traffic problems. In this poster, different from previous online methods, we propose a frame-based model and an efficient algorithm to solve the drawbacks of online algorithm by scheduling the vehicles that have accumulated at the intersection over a period of time. Preliminary experiments exhibit that the proposed algorithm could greatly improve the throughput of the intersection.
UbiWheel: A simple context-aware universal control concept for smart home appliances that encourages active living

Smart homes contain many useful appliances that can help individuals live independently for longer. A problem with current smart homes prototypes is that each device often has its own remote control or control unit. These control units are often manufactured by different suppliers with totally different and inconsistent user interfaces. This is confusing for most individuals and become a huge barrier for individuals with reduced cognitive function. This paper thus introduces a conceptual sketch of a universal and ubiquitous control wheel, termed UbiWheel that is designed to control most appliances in the home. The user simply moves the controller to the proximity of the device be controlled and adjust parameters by simply twisting the wheel, thereby preventing inactivity as the user need to move around the home. Several cases are explored herein.
Bacterial vaginosis: Prevalence and associated risk factors among non-pregnant women of reproductive age attending a Nigerian tertiary hospital

Aim To determine the prevalence and risk factors associated with bacterial vaginosis (BV) among non-pregnant women of reproductive age group. Methods A cross-sectional study among non-pregnant asymptomatic women aged 19 to 45 years, attending the gynaecological clinic at University of Ilorin Teaching Hospital, Ilorin, Nigeria. Participants were counselled and an informed consent was obtained. This was followed by vaginal swabs for microscopy, culture and sensitivity. Diagnosis of BV was by Nugent's criteria. Data analysis was by Statistical Package for Social Sciences (SPSS) version 20.0. Chi-square and Yates corrected chi-square were calculated, and p value <0.05 was significant. Results Among the 212 participants, prevalence of BV was 40.1%; it was common among women aged 25–34 years (50; 58.8%), the married (77; 90.6%) and those with tertiary education (39; 45.9%). The risk factors for BV were common among women with laboratory evidence of the infection, however statistically significant risk factors were the use of intrauterine device (OR 1.61, 95%CI 0.543–4.759; p0.020) and previous voluntary termination of pregnancy (OR 1.04, 95%CI 0.600–1.808; p0.047). Conclusion There was high prevalence of bacterial vaginosis in the study population. Universal screening and treatment of cases may assist in lowering the associated morbidity.
Hybrid Framework for Consensus in Directed and Asynchronous Network of Non-Holonomic Agents

This letter presents a hybrid systems strategy for consensus (or formation realization) for a fleet of non-holonomic agents. In the proposed model, each agent has a smooth continuous-time dynamics and a piecewise constant impulsive reference. The jumps on the reference trajectory take place at some updating instants that are decided independently by each agent. The jumps computation is based on the relative distance with respect to some time-varying neighbors at the update instants. Between the updates of its reference each robot will track its own constant reference trajectory. Our results provide consensus (formation realization) as far as a minimum dwell-time condition between consecutive updates is satisfied. A numerical example illustrates the theoretical results.
A tabu-search algorithm for scheduling jobs with precedence constraints on parallel machines

A tabu-search algorithm for scheduling jobs with tree-formed precedence constraints on parallel machines is discussed in this paper. The structural characteristic of the problem is studied, which helps the searching procedure focus on “promising” neighboring schedules only, such that computing time can be effectively reduced. Experiment shows the algorithm is capable for solving medium or large-scaled problems within acceptable computing time.
Configuration, programming and implementation of 3 Smart Water network wireless sensor nodes for assessing the water quality

This paper aims to present a Wireless Sensor Network using a Libelium Smart Water kit to allow remote water quality monitoring communication in real time. Equipped with multiple sensors that measure the most relevant water quality parameters, the Smart Water kit can be connected to the internet (using a mobile broadband connection) for real-time water quality control. The water quality parameters measured include pH, oxidation-reduction potential (ORP), electrical conductivity (EC) and temperature. The Smart Water platform includes three ultra-low power sensor nodes designed for use in rugged environments. The sensor nodes communicate through low power radio (802.15.4) sending data to the Meshlium Internet Gateway. This Gateway then sends the data to the Cloud or an external database via 3G or GPRS cellular connections. Sensor data is available in real time, even from sensor nodes situated in remote locations. This specific solution was implemented for three experiments performed in a physical sandbox model or artificial aquifer built in the laboratory.
Short-term urban traffic flow prediction using deep spatio-temporal residual networks

Traffic flow prediction, as the key technology of traffic guidance system (TGS), is of great importance to mitigate traffic congestion and city management. In view of the existing research mainly considering the adjacent area and ignoring the influence of far area on the current section, this paper presents a method, called ST-ResNet, for predicting urban traffic flow the predicts all roads in an area, which takes into account not only the time information but also the effects of nearby and beyond areas. We use two basic traffic parameters, volume and speed, as the input of the model to simultaneously predict the traffic volumes and average speed of the road segment. Experiment on all motorways and ‘A’ roads managed by the Highways Agency, known as the Strategic Road Network (SRN), in England demonstrate its great and precise accuracy of short-term traffic flow prediction.
Enclosure shielding effectiveness calculation using SHADE algorithm

Electromagnetic interference has become a severe problem for electronic and electrical devices, especially for security cameras which are significantly sensitive to electromagnetic field effects. Therefore, there was born an idea to create shielding enclosure which protects these devices against the radiated field. This task was realized by the evolutionary algorithm included in the computational process of optimizing shielding effectiveness.
Transmission expansion planning with wind sources based on constructive metaheuristics

In this work, a new methodology is proposed to solve the transmission expansion planning (TEP) problem, considering the intermittence of renewable energy, in particular wind power sources. The variability of these sources is represented by means of scenarios, obtained with the K-Means classification algorithm, which allows preserving the correlation among generating stations. The identification of the best expansion plan for each defined scenario is initially performed based on the use of a constructive metaheurístic algorithm (CMA-TEP). Then, by means of two heuristic steps, an interactive and a combinatorial one, the solutions obtained for each scenario are converged to a single solution, capable of attending to all considered wind generation scenarios. The performance of the proposed methodology is tested through the IEEE-RTS system, modified to include a significant share of wind energy. A linear DC network model with losses is used to represent the system grid and the “N-1” security criterion is ensured during the search for the best solutions.
Mistype resistant keyboard (NexKey)

Nexkey Project is aimed at developing an android keyboard capable of identifying frequently used words to provide personalized and improved typing experience. It uses a prediction system that makes use of an Android API for implementation. The keyboard has an elastic layout that manipulates the selected key which is predicted to be clicked next and the victim key which is predicted to not be clicked. It gives the selected key more width and reduces width of the victim key. The application always looks for the victim key which could be on either side of the selected key. The proposed project can well provide an alternative to already available keyboards on the app store which provide on-screen suggestions, something which could easily be annoying for the users. Our application facilitates users to type in at high speed without looking at the keyboard. NexKey also reduces the use of backspace key as demonstrated through empirical validation of the project.
Immersive Analytics and Deep Maps – the Next Big Thing for Cultural Heritage & Archaeology

Archaeologists and cultural heritage experts explore complex multifaceted data that is often highly interconnected. We argue for new ways to interact with this data. Such data analysis provides a ‘grand challenge’ for computer science and heritage researchers, it is big Data, multi-dimensional, multi-typed, contains uncertain information, and the questions posed by researchers are often ill-defined (where it is difficult to guarantee an answer). We present two visions (Immersive Analytics, and Deep Mapping) as solutions to allow both expert users and the general public to interact and explore heritage data. We use pre-historic data as a case study, and discuss key technologies that need to develop further, to help accomplish these two visions.
What makes a species central in a cleaning mutualism network

Mutualisms often form networks of interacting species, characterized by the existence of a central core of species that potentially drive the ecology and the evolution of the whole community. Centrality measures allow quantification of how central or peripheral a species is within a network, thus informing about the role of each species in network organization, dynamics, and stability. In the present study we addressed the question whether the structural position of species in the network (i.e. their topological importance) relates to their ecological traits. We studied interactions between cleaner and client reef fishes to identify central and peripheral species within a mutualistic network, and investigated five ecological correlates. We used three measures to estimate the level of centrality of a species for distinct structural patterns, such as the number of interactions and the structural proximity to other species. Through the use of a principal component analysis (PCA) we observed that the centrality measures were highly correlated (92.5%) in the studied network, which indicates that the same species plays a similar role for the different structural patterns. Three cleaner and ten client species had positive values of centrality, which suggests that these species are modulating ecological and evolutionary dynamics within the network. Higher centralities were related to higher abundances and feeding habits for client fishes, but not for cleaners. The high correlation between centrality measures in the present study is likely related to the nested structure of the cleaning network. The cleaner species' set, by having central species that are not necessarily the most abundant ones, bears potentially more vulnerable points for network cohesiveness. Additionally, the present study generalizes previous findings for plant-animal mutualisms, as it shows that the structure of marine mutualisms is also related to a complex interplay between abundance and niche-related features.
Dynamic deadline-constraint scheduler for Hadoop YARN

Hadoop is one of the most popular distributed platforms for big data. Apache YARN is the second generation of MapReduce. YARN has three built-in schedulers: the FIFO, Fair and Capacity Scheduler. Though these schedulers provide users different methods to allocate resources of a Hadoop cluster to execute their MapReduce jobs, they do not guarantee that their jobs will be executed within a specific deadline. In this paper, we propose a deadline constraint scheduler algorithm for Hadoop. This algorithm uses a statistical approach to measure the performance of data nodes and based on this information the proposed algorithm creates several checkpoints to monitor the progress of a job. Based on the progress of jobs at every checkpoint the proposed scheduler will assign them to different job queues. These queues will have different priorities and the proportion of resources used by these queues will depend on their priority. The results of our experiments show that the proposed scheduler ensures that jobs will be completed within a given deadline whereas the native schedulers cannot guarantee this. Moreover, the average job execution time in the proposed scheduler is less when compared to the other schedulers.
A 48-V Wide- $V_{\rm in}$  9–25-MHz Resonant DC–DC Converter

This paper presents a wide-<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ in}}$ </tex-math></inline-formula> step-down parallel-resonant converter (PRC), comprising an integrated 5-bit capacitor array and a 300-nH resonant coil, placed in parallel to a conventional buck converter. Soft-switching resonant converters are beneficial for high-<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ in}}$ </tex-math></inline-formula> multi-MHz converters to reduce dominant switching losses, enabling higher switching frequencies. The output filter inductor is optimized based on an empirical study of available inductors. The study shows that faster switching significantly reduces not only the inductor value but also volume, price, and even the inductor losses. In addition, unlike conventional resonant concepts, soft-switching control as part of the proposed PRC eliminates input voltage-dependent losses over a wide operating range, resulting in 76.3% peak efficiency. At <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ in}}=48$ </tex-math></inline-formula> V, a loss reduction of 35% is achieved compared with the conventional buck converter. Adjusting an integrated capacitor array, and selecting the number of oscillation periods, keeps the switching frequency within a narrow range. This ensures high efficiency across a wide range of <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ in}}$ </tex-math></inline-formula> = 12–48 V, 100–500-mA load, and 5-V output at up to 25-MHz switching frequency. Thanks to the low output current ripple, the output capacitor can be as small as 50 nF.
Real-time flux-torque estimation of three phase induction motor using LabVIEW

Vector control of induction motor is most popular control strategy for industrial applications as it covers the wide speed range from near zero to rated speed. This strategy is very complex and challenging to implement in real time. Therefore, a LabVIEW based development platform has been used for realtime implementation of the strategy. This platform has an advantage of flexible algorithm design and easy monitoring of state variables involved in the design. Here authors have developed the flux estimation technique using real-time data logging and real-time data processing. The relation between magnitude and phase of transformed variables is established. This process involves appropriate calibration of voltage and current sensors and determination of proper scale value of sensor outputs. This scale value is calculated considering the sensitivity of sensors and data acquisition system (DAQ). The main objective of this paper is to enlighten most of the practical difficulties in implementation of a hardware-based design of vector controlled induction motor drive. It encompasses the critical factors during the implementation of an algorithm on a LabVIEW based platform.
Local smoothness enforced cost aggregation on weighted spanning trees

Cost aggregation is one of the key steps in stereo matching process. To improve the accuracy especially in the challenging regions such as boundaries and occluded regions, this paper presents a new cost aggregation approach on minimum spanning trees called robust weighted minimum spanning tree (W-MST). Our method applies not only color features but also gradient information to compute weight in order to improve the matching accuracy in textureless regions. Furthermore, we combine local smoothness with cost aggregation to address the shortage of the “fronto-parallel plane” and obtain accurate disparity boundaries. Besides, the proposed algorithm has low complexity and only requires a linear time implementation. Experimental results on Middlebury datasets demonstrate that the proposed method outperforms than other state-of-the-art methods.
Eliminating Mother-to-Child Transmission of HIV by 2030: 5 Strategies to Ensure Continued Progress

To keep up momentum in preventing mother-to-child transmission we propose: (1) advocating for greater political and financial commitment; (2) targeting high-risk populations such as adolescent girls and young women; (3) implementing novel service delivery models such as community treatment groups; (4) performing regular viral load monitoring during pregnancy and postpartum to ensure suppression before delivery and during breastfeeding; and (5) harnessing technology in monitoring and evaluation and HIV diagnostics. To keep up momentum in preventing mother-to-child transmission we propose: (1) advocating for greater political and financial commitment; (2) targeting high-risk populations such as adolescent girls and young women; (3) implementing novel service delivery models such as community treatment groups; (4) performing regular viral load monitoring during pregnancy and postpartum to ensure suppression before delivery and during breastfeeding; and (5) harnessing technology in monitoring and evaluation and HIV diagnostics.
The Costs and Benefits of Fiscal Rules: Evidence from U.S. States

This paper shows that in American states balanced budget rules are effective in enforcing fiscal discipline but they have no costs in terms of increased output variability. More specifically, we show that tighter fiscal rules are associated with larger average surplus and lower cyclical variability of the budget balance. However, the lower flexibility of the budget balance does not affect state output variability.
A PV panel model considering temperature and irradiance effect on panel resistances

The global energy apetite is exponentially increasing at an alarming pace. The total demand cannot be fulfilled by the existing generating systems and hence dependence on renewable energy sources are predominant. Solar energy is a novel trend and could satisfy global apetite. Due to fluctuating operating condition MPP vary and MPPT algorithm are required. In this paper a novel MPPT methodology is introduced and simulated using MATLAB/SIMULINK.
Media convergence and online representation of president Bachelet's public account: @latercera and @thecliniccl during the presidential speech on 21 May

The purpose of this paper is to take the speech on 21 May as a milestone and analyze the treatment given by The Clinic and La Tercera journals on their Twitter accounts. The study seeks to elucidate which subjects are given greater importance and coverage in the accounts. Moreover, we try to establish which are the politicians, parties and coalitions with greater presence, and what are the approaches and valuations from which they are shown. This study aims to contribute to understand the dynamics of framing information by two media in digital platforms. The media accounts proposed for this analysis are @latercera and @thecliniccl, as they are two written press media that, being both among the 15 most influential accounts in Chile, present dissimilar editorial lines which makes their comparison and tracing even more interesting.
Biogas fueled internal combustion engine Mean Value Model for distributed generation

As an alternative for energy generation, distributed generation has been earning more space among the electric system market. The biogas is one of the sources which is used as a fuel for internal combustion engines, that once connected to a generator, is able to produce clean energy. In front of the necessity of reproducing the behavior of this kind of system, the current paper aims to consolidate a Mean Value Model for an Otto cycle biogas fueled internal combustion engine aiming distributed generation studies. The model was obtained by representing the typical modifications of the biogas conversion on an MVM of an internal combustion engine powered by gasoline.