Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Increased Nitrogen Availability on C and N Cycles in Tropical Forests: A Meta-Analysis

Atmospheric N deposition is predicted to increase four times over its current status in tropical forests by 2030. Our ability to understand the effects of N enrichment on C and N cycles is being challenged by the large heterogeneity of the tropical forest biome. The specific response will depend on the forest’s nutrient status; however, few studies of N addition appear to incorporate the nutrient status in tropical forests, possibly due to difficulties in explaining how this status is maintained. We used a meta-analysis to explore the consequences of the N enrichment on C and N cycles in tropical montane and lowland forests. We tracked changes in aboveground and belowground plant C and N and in mineral soil in response to N addition. We found an increasing trend of plant biomass in montane forests, but not in lowland forests, as well as a greater increase in NO emission in montane forest compared with lowland forest. The N2O and NO emission increase in both forest; however, the N2O increase in lowland forest was significantly even at first time N addition. The NO emission increase showed be greater at first term compared with long term N addition. Moreover, the increase in total soil N, ammonium, microbial N, and dissolved N concentration under N enrichment indicates a rich N status of lowland forests. The available evidence of N addition experiments shows that the lowland forest is richer in N than montane forests. Finally, the greater increase in N leaching and N gas emission highlights the importance of study the N deposition effect on the global climate change.
Coverage for target localization in wireless sensor networks

Target tracking and localization are important applications in wireless sensor networks. Although the coverage problem for target detection has been intensively studied, few consider the coverage problem from the perspective of target localization. In this paper, we propose two methods to estimate the necessary sensor density which can guarantee a localization error bound over the sensing field. In the first method, we convert the coverage problem for localization to a conventional disk coverage problem, where the sensing area is a disk centered around the sensor. Our results show that the disk coverage model requires 4 times more sensors for tracking compared to detection applications. We then introduce the idea of sector coverage, which can satisfy the same coverage conditions with 2 times less sensors over the disk coverage approach. This shows that conventional disk coverage model is insufficient for tracking applications, since it overestimates the sensor density by two times. Simulation results show that the network density requirements derived through sector coverage are close to the actual need for target tracking applications
A dual-band triple-mode SoC for 802.11a/b/g Embedded WLAN in 90nm CMOS

An 802.11a/b/g-compliant SoC integrates a WLAN system, comprising a dual-band RF transceiver and PHY, MAC and ARM processor units, in 90nm CMOS. Challenges of SoC integration in 90nm CMOS and the mitigation techniques are discussed, along with circuit design techniques to optimize RF performance in 90nm. For 54Mb/s signals, the receiver sensitivity is -75dBm/-72dBm at 2.4GHz/5GHz, where the transmitter achieves an EVM of -35dB/-32dB at 0dBm output power
User Modeling and Personalization in the Microblogging Sphere

Microblogging has become a popular mechanism for people to publish, share, and propagate information on the Web. The massive amount of digital traces that people have left in the microblogging sphere, creates new possibilities and poses challenges for user modeling and personalization. How can microblogging activities be exploited to infer individual users' interests? How can semantically meaningful user profiles be constructed to support different applications? Does the users' microblogging behavior vary between different cultural groups? What is the impact of different user modeling strategies on the characteristics of user profiles and the performance of personalized recommendations? In this thesis, we answer the research questions above and introduce a generic framework that provides a variety of user modeling strategies for inferring individual users' interests from microblogging streams. We propose and evaluate techniques that allow for exploiting external resources to enrich the semantics of short microblogging messages. We explore different approaches for deducing and modeling topics of interests based on enriched microblogging data. Furthermore, we investigate various weighting schemes for constructing user profiles and incorporate temporal constraints into the user modeling process. With flexible design choices, the user modeling framework allows for constructing user profiles which can be consumed in different applications. We apply our user modeling framework to analyze user behavior across cultural groups on microblogging platforms. By exploiting different user characteristics, we unveil key differences in users' microblogging behavior between Chinese and American users. Finally, we analyze and evaluate different user modeling strategies in the context of various personalized recommender systems. The results of our analyses show that the characteristics of user profiles are significantly influenced by different design alternatives. In a set of experiments we reveal that the semantic enrichment of microposts and the consideration of temporal patterns improve the performance of recommender systems. We also prove that the incorporation of public trends and domain specific knowledge into the user modeling process improves the quality of personalized recommendations.
Metabolism of Endosulfan-α by Human Liver Microsomes and Its Utility as a Simultaneous in Vitro Probe for CYP2B6 and CYP3A4

Endosulfan-α is metabolized to a single metabolite, endosulfan sulfate, in pooled human liver microsomes (Km = 9.8 μM, Vmax = 178.5 pmol/mg/min). With the use of recombinant cytochrome P450 (P450) isoforms, we identified CYP2B6 (Km = 16.2 μM, Vmax = 11.4 nmol/nmol P450/min) and CYP3A4 (Km = 14.4 μM, Vmax = 1.3 nmol/nmol P450/min) as the primary enzymes catalyzing the metabolism of endosulfan-α, although CYP2B6 had an 8-fold higher intrinsic clearance rate (CLint = 0.70 μl/min/pmol P450) than CYP3A4 (CLint = 0.09 μl/min/pmol P450). Using 16 individual human liver microsomes (HLMs), a strong correlation was observed with endosulfan sulfate formation and S-mephenytoin N-demethylase activity of CYP2B6 (r2 = 0.79), whereas a moderate correlation with testosterone 6 β-hydroxylase activity of CYP3A4 (r2 = 0.54) was observed. Ticlopidine (5 μM), a potent CYP2B6 inhibitor, and ketoconazole (10 μM), a selective CYP3A4 inhibitor, together inhibited approximately 90% of endosulfan-α metabolism in HLMs. Using six HLM samples, the percentage total normalized rate (% TNR) was calculated to estimate the contribution of each P450 in the total metabolism of endosulfan-α. In five of the six HLMs used, the percentage inhibition with ticlopidine and ketoconazole in the same incubation correlated with the combined % TNRs for CYP2B6 and CYP3A4. This study shows that endosulfan-α is metabolized by HLMs to a single metabolite, endosulfan sulfate, and that it has potential use, in combination with inhibitors, as an in vitro probe for CYP2B6 and 3A4 catalytic activities.
CONVERGENCE ANALYSIS OF A QUADRATURE FINITE ELEMENT GALERKIN SCHEME FOR A BIHARMONIC PROBLEM

A quadrature finite element Galerkin scheme for a Dirichlet boundary value problem for the biharmonic equation is analyzed for a solution existence, uniqueness, and convergence. Conforming finite element space of Bogner-Fox-Schmit rectangles and an integration rule based on the two-point Gaussian quadrature are used to formulate the discrete problem. An H2-norm error estimate is obtained for the solution of the original finite element problem consistent with the solution regularity. A standard quadrature error analysis gives a suboptimal order error estimate. Optimal order error estimates under sufficient regularity assumptions are obtained using an alternative approach based on the equivalence of the quadrature problem with an orthogonal spline collocation problem.
The Long QT Syndrome in Children An International Study of 287 Patients

BackgroundThe Pediatric Electrophysiology Society studied children with the long QT syndrome (LQTS) to describe the features ofLQTS in patients less than 21 years old, define potential “low-risk” and “high-risk” subpopulations, and determine optimal treatment Methods and ResultsPatients less than 21 years old were included if either QTc was more than 0.44; they had unexplained syncope, seizures, or cardiac arrest preceded by emotion or exercise; or family history of LQTS. We found 287 patients from 26 centers in seven countries. Mean±SD age at presentation was 6.8±5.6; 9%o presented with cardiac arrest, 26% with syncope, and 10%, with seizures. Of those with symptoms, 67% had symptoms related to exercise. Family history was positive for long QT interval in 39% and for sudden death in 31%. Hearing loss was present in 4.5%. A normal QTc was present in 6%, and QT, of more than 0.60 was in 13%. Atrioventricular block occurred in 5%, but 13 of 15 patients had second-degree atrioventricular block (2:1), and only two of 287 had complete atrioventricular block. Ventricular arrhythmias were found on 16% of initial routine ECGs: 4% uniform premature ventricular contractions, 5% multiform premature ventricular contractions, 1% monomorphic ventricular tachycardia, and 6% torsade de pointes. Overall, treatment was effective for symptoms in 76% and for ventricular arrhythmias in 60%. There was no difference between propranolol and other β-blockers in effective treatment. Left stellectomy was performed in nine patients, and defibrillators were implanted in four, no sudden death occurred in these 13 patients. In follow-up (duration, 5.0±4 years; age, 10.9±6.3 years), 5% had cardiac arrest, 4% had syncope, and 1% had seizures. The two multivariate predictors of symptoms at follow-up were symptoms at presentation and propranolol failure. Sudden death occurred in 8%; multivariate predictors of sudden death were length of QTc at presentation of more than 0.60 and medication noncompliance. ConclusionThe appearance of 2:1 atrioventricular block, multiform premature ventricular contractions, and torsade de pointes are relatively more common in children with LQTS than other children and should raise the index of suspicion for LQTS. Because 9% of patients presented with cardiac arrest and no preceding symptoms, perhaps prophylactic treatment in asymptomatic children is indicated. Asymptomatic patients with normal QTc and positive family history may be a low-risk group. Patients with QTc of more than 0.60 are at particularly high risk for sudden death, and if treatment is not effective, consideration should be given to cardiac sympathetic denervation, pacemaker implantation, and perhaps implantation of a defibrillator.
Influence of stretch on excitation threshold of single frog ventricular cells

The excitation threshold of enzymatically dissociated single frog ventricular myocytes was measured as a function of cell length or sarcomere length. Field stimulation with 3 ms duration rectangular current pulses was applied via two platinum wire electrodes oriented either parallel or perpendicular to the long axis of the cell. Excitation threshold was measured as the amplitude of applied current, with an error of less than 1%. Single cells were held isometrically by two glass pipettes and wrapped around an optical fibre, which was used to control cell length. Sarcomere length was measured using video microscopy and a phase‐locked loop system. Changes in cell length and sarcomere length were induced by mechanical stretch and release of the whole cell. The excitation threshold decreased with increasing resting length (preload), and increased with decrease of the cell length back to its original length, regardless of the orientation of the electric field. The measured change in excitation threshold with stretch was of the order of 1%/% strain. These results suggest that stretch affects the excitation threshold of cardiac cells by factors other than simple shape changes in the cell, perhaps through the activity of mechanosensitive ionic channels.
Yet Faster Ray-Triangle Intersection (Using SSE4)

Ray-triangle intersection is an important algorithm, not only in the field of realistic rendering (based on ray tracing) but also in physics simulation, collision detection, modeling, etc. Obviously, the speed of this well-defined algorithm's implementations is important because calls to such a routine are numerous in rendering and simulation applications. Contemporary fast intersection algorithms, which use SIMD instructions, focus on the intersection of ray packets against triangles. For intersection between single rays and triangles, operations such as horizontal addition or dot product are required. The SSE4 instruction set adds the dot product instruction which can be used for this purpose. This paper presents a new modification of the fast ray-triangle intersection algorithms commonly used, which-when implemented on SSE4-outperforms the current state-of-the-art algorithms. It also allows both a single ray and ray packet intersection calculation with the same precomputed data. The speed gain measurements are described and discussed in the paper.
The WAAS/L5 Signal for Robust Time Transfer: Adaptive Beamsteering Antennas for Satellite Time Synchronization

Geostationary satellites of the Wide Area Augmentation System (WAAS) offer a novel, robust, and cost-effective means of synchronizing time at widely-separated ground facilities, to levels of ~50ns, without the need for dedicated long-distance wired communication networks. However, reliance on satellite-based signals for time synchronization in high-reliability applications is problematic without explicit hardening against radio frequency interference (RFI). The primary innovations to be discussed in this paper are: (1) adaptive electronicallysteered multi-element antenna arrays and signal processing strategies for RFI mitigation, (2) live signal, synthetic interference, and hardware-in-the-loop testing of jammer cancellation algorithms, and (3) preparations for over-the-air interference tests which will probe the effects of front-end saturation on digital beamsteering performance. We describe a hardware system assembled from readily-available commercial building blocks (data acquisition system, antennas, etc.), and a critical goal of this research is to realize significant GPS anti-jam performance in an open-architecture (or non-defenserelated) platform. Therefore, the central innovations in this research enable adaptive electronic beamsteering with high-dynamic-range signals (14-bit I/Q digitization), employing commercial off-the-shelf (COTS) hardware and computer systems, and targeted for a civilian highreliability, high-volume (many hundreds of deployed systems) GPS timing application.
An Extensible Protocol Architecture for Application-Specific Networking

Plexus is a networking architecture that allows applications to achieve high performance with customized protocols. Application-specific protocols are written in a typesafe language and installed dynamically into the operating system kernel. Because these protocols execute within the kernel, they can access the network interface and other operating system services with low overhead. Protocols implemented with Plexus outperform equivalent protocols implemented on conventional monolithic systems. Plexus runs in the context of the SPIN extensible operating system.
ERK3 Is Required for Metaphase-Anaphase Transition in Mouse Oocyte Meiosis

ERK3 (extracellular signal-regulated kinase 3) is an atypical member of the mitogen-activated protein (MAP) kinase family of serine/threonine kinases. Little is known about its function in mitosis, and even less about its roles in mammalian oocyte meiosis. In the present study, we examined the localization, expression and functions of ERK3 during mouse oocyte meiotic maturation. Immunofluorescent analysis showed that ERK3 localized to the spindles from the pre-MI stage to the MII stage. ERK3 co-localized with α-tubulin on the spindle fibers and asters in oocytes after taxol treatment. Deletion of ERK3 by microinjection of ERK3 morpholino (ERK3 MO) resulted in oocyte arrest at the MI stage with severely impaired spindles and misaligned chromosomes. Most importantly, the spindle assembly checkpoint protein BubR1 could be detected on kinetochores even in oocytes cultured for 10 h. Low temperature treatment experiments indicated that ERK3 deletion disrupted kinetochore-microtubule (K-MT) attachments. Chromosome spreading experiments showed that knock-down of ERK3 prevented the segregation of homologous chromosomes. Our data suggest that ERK3 is crucial for spindle stability and required for the metaphase-anaphase transition in mouse oocyte maturation.
Efficient Distributed Decision Trees for Robust Regression [ Technical Report ]

The availability of massive volumes of data and recent advances in data collection and processing platforms have motivated the development of distributed machine learning algorithms. In numerous real-world applications large datasets are inevitably noisy and contain outliers. These outliers can dramatically degrade the performance of standard machine learning approaches such as regression trees. To this end, we present a novel distributed regression tree approach that utilizes robust regression statistics, statistics that are more robust to outliers, for handling large and noisy data. We propose to integrate robust statistics based error criteria into the regression tree. A data summarization method is developed and used to improve the efficiency of learning regression trees in the distributed setting. We implemented the proposed approach and baselines based on Apache Spark, a popular distributed data processing platform. Extensive experiments on both synthetic and real datasets verify the effectiveness and efficiency of our approach.
Novel therapeutics targeting telomerase and telomeres

Telomerase is a ribonucleoprotein enzyme that binds to the telomeres, increases their length, and extends the lifespan of cells. Telomerase is expressed at low or undetectable levels in normal somatic tissue. However, telomerase is expressed at detectable levels in a wide range of cancer cells, including brain, skin, lung and blood. The selective high level of expression of telomerase in cancer cells makes it an attractive target for cancer therapy. Researchers have investigated cancer therapeutics targeting telomerase and its mechanism of action by multiple approaches, including vaccines, small molecule inhibitors, oligonucleotides and G-quadruplex approaches. Several therapeutics targeting telomerase, such as Imetelstat (GRN163L) and Tertomotide (GV1001), are currently in Phase I, II and III clinic trials to treat a wide range of cancers from pediatric solid tumors to non-small cell lung cancer, leukemia, lymphoma and myeloma.
Endovascular stroke treatment in a small‐volume stroke center

Our purpose was to evaluate the safety and efficacy of endovascular treatment (EVT) of stroke caused by large vessel occlusions (LVO) performed by general interventional radiologists in cooperation with stroke neurologists and neuroradiologists at a center with a limited annual number of procedures. We aimed to compare our results with those previously reported from larger stroke centers.
An Entropy Evaluation Approach for Triaging Field Crashes: A Case Study of Mozilla Firefox

A crash is an unexpected termination of an application during normal execution. Crash reports record stack traces and run-time information once a crash occurs. A group of similar crash reports represents a crash-type. The triaging of crash-types is critical to shorten the development and maintenance process. Crash triaging process decides the priority of crash-types to be fixed. The decision typically depends on many factors, such as the impact of the crash-type, (i.e, its severity), the frequency of occurring, and the effort required to implement a fix for the crash-type. In this paper, we propose the use of entropy region graphs to triage crash-types. An entropy region graph captures the distribution of the occurrences of crash-types among the users of a system. We conduct an empirical study on crash reports and bugs, collected from 10 beta releases of Fire fox 4. We show that our proposed triaging technique enables a better classification of crash-types than the current triaging used by Fire fox teams. Developers and managers could use such a technique to prioritize crash-types during triage, to estimate developer workloads, and to decide which crash-types patches should be included in a next release.
Experimental evaluation of errors in the measurement of respiratory parameters of the newborn performed by a continuous flow neonatal ventilator

Pulmonary ventilators for intensive care provide information on, among many other patient respiratory parameters, patient resistance, compliance and ‘work of breathing’ values calculated from pressure and flow data patterns according to a widely utilized algorithm. The effects induced by the breathing circuit and analogue filtering of the ventilator measuring system are experimentally investigated during controlled ventilation. Three main phenomena are observed: (a) errors in calculation of resistance and compliance due to filtering of pressure and flow waveforms; (b) the presence of pressure oscillations at the beginning of inspiration and expiration phases; and (c) the phase shift between pressure and flow waveforms. The experimental evaluation of the measuring system of a neonatal ventilator is then conducted and: (a) a delay in pressure and flow measurement synchronization equal to 22 ± 2 ms is evaluated; moreover, (b) a difference between the values provided by the ventilator and those measured by the reference experimental setup on respiratory parameters such as the compliance, resistance and work of breathing that lies in the range of 7 – 16% of reading is observed.
Analysis and Effect of Feature Selection with Generic Classifier over Activity Recognition Dataset for Daily Life Activity Recognition

years, the convergence in sensing environments and pervasive computing has opened a scope for human activity recognition research. In this paper, we form populations from smartphone accelerometer and gyroscope sensor training- based data for Human Activity Recognition (HAR). In the same vein, we described in this work an Activity Recognition database, assembled from the recorded activities of 24 subjects doing Activities of Daily Living (ADL). The paper then aggregated this time- series data into features and subsets of features were selected using two filters based, classifier- independent feature selection methods. We used 10-fold cross-validation strategy to validate the experimentation. Evaluation of the variation of generic decision tree classifiers showed that the feature subsets bring forth acceptable performances than classification with the entire feature set resulting in productive computer overhead in the reduced feature subset. Therefore, classifier-independence feature set should be useful for developing and improving HAR systems across and within populations.