Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Location Databases for Tracking Highly Mobile Objects

In current distributed systems, the notion of mobility is emerging in many forms and applications. Increasingly many users are not tied to a fixed access point but instead use wireless communications or dial-up services to access data independent of their physical location. Furthermore, mobile software, a popular example being mobile agents, is frequently used as a new form of building distributed network-centric applications. Tracking mobile objects, i.e. identifying their current location, is central to such settings. In this paper, we exploit the use of hierarchical distributed location databases, where each database site covers a specific geographical region and contains location information about all objects residing in it. For highly mobile objects, a scheme based on forwarding pointers enhanced with auxiliary caching techniques is presented, to reduce the cost of the overall network and database traffic generated by frequent location updates. The scheme is extended to support concurrency and failure recovery. Performance is demonstrated through a number of simulation experiments for a range of call to mobility ratios and for a variety of moving and calling behaviors.
Traffic Congestion and Air Pollution Exposure for Motorists: Comparing Exposure Duration and Intensity

This article investigates the effects of congested freeway traffic conditions on motorists’ exposure to traffic-related air pollution using real-world traffic data and a framework of established emissions and dispersion models. The intent is to isolate and compare the influences of congested traffic characteristics on exposure duration and exposure intensity. Mass inhalation of carbon monoxide (CO) and nitrogen oxides (NOx) is estimated for 45,226 simulated trips through a 14-mile congested freeway corridor. Results show that congestion increases total trip pollutant inhalation primarily through motorist delay (exposure duration), and to a lesser extent through increased concentrations (exposure intensity). The effects of varying wind and background concentration can be sufficient to obscure the influence of congestion on exposure intensity. The variability of exposure intensity due to traffic is mitigated by offsetting impacts among traffic flow, emissions rates, and pollutant dispersion. Exposure intensity increases with higher traffic flow and with lower traffic speed, but the impact of lower traffic speeds (through increased emissions rates and decreased dispersion) is smaller. The importance of exposure “hot spots” at traffic bottlenecks also increases in congestion. These findings suggest that traffic-based motorist exposure mitigation should focus on reducing travel duration on high-volume corridors through reduced vehicle flows (i.e., demand-side congestion mitigation). This analysis does not include non–congestion-based mitigation strategies such as cleaner vehicle engine technology or improvements in vehicle cabins, which can also reduce exposure intensity. On an individual scale, motorists can greatly reduce their own exposure during travel by, among other strategies, adjusting their departure time to less congested, lower volume periods.
Oxidative Stress Triggers STAT3 Tyrosine Phosphorylation and Nuclear Translocation in Human Lymphocytes*

Oxidizing agents are powerful activators of factors responsible for the transcriptional activation of cytokine-encoding genes involved in tissue injury. In this study we show evidence that STAT3 is a transcription factor whose activity is modulated by H2O2 in human lymphocytes, in which endogenous catalase had previously been inhibited. H2O2-induced nuclear translocation of STAT3 to form sequence-specific DNA-bound complexes was evidenced by immunoblotting of nuclear fractions and electrophoretic mobility shift assays, and vanadate was found to strongly synergize with H2O2. Moreover, anti-STAT3 antibodies specifically precipitated a protein of 92 kDa that becomes phosphorylated on tyrosine upon lymphocyte treatment with H2O2. Phenylarsine oxide, a tyrosine phosphatase inhibitor, and genistein, a tyrosine kinase inhibitor, cooperated and cancelled, respectively, the H2O2-promoted STAT3 nuclear translocation. Evidence is also presented, using Fe2+/Cu2+ions, that ⋅OH generated from H2O2through Fenton reactions could be a candidate oxygen reactive species to directly activate STAT3. Present data suggest that H2O2 and vanadate are likely to inhibit the activity of intracellular tyrosine phosphatase(s), leading to enhanced STAT3 tyrosine phosphorylation and hence its translocation to the nucleus. These results demonstrate that the DNA binding activity of STAT3 can be modulated by oxidizing agents and provide a framework to understand the effects of oxidative stress on the JAK-STAT signaling pathway.
Low incidence of delirium in very old patients after surgery for hip fractures.

OBJECTIVE The authors sought to determine the incidence of delirium, its predisposing and precipitating factors, and its implications for rehabilitation outcomes and mortality in elderly patients. METHODS This was a prospective cohort study, conducted in Gedera, Israel, from August 2001 to January 2002, with 137 consecutive patients over age 75, with hip fractures, who were admitted to the orthopedic section of the emergency department. They were evaluated at admission, 1 week after the surgery for hip fracture, and 1 month after surgery. The evaluation included assessments of delirium, cognitive, and functional status, and a wide range of demographic and clinical parameters. RESULTS The cumulative incidence of delirium was 11.4%. No significant difference was found between delirium and non-delirium patients in terms of all demographic, socioeconomic, and perioperative parameters. Mild or moderate cognitive impairment before the fracture and four or more regular medications prescribed to the patient were the only predictive factors for the development of delirium in a multivariate model. Delirium was not a significant predictor of any rehabilitation outcome. CONCLUSION Results documented that the incidence of delirium after hip fracture in elderly patients is much lower than was reported in several previous studies. Premorbid cognitive impairment was the most significant predisposing factor for the development of delirium. Thorough evaluation of earlier cognitive status could improve the probability of the diagnosis of delirium and pinpoint a limited group of patients for a delirium-prevention approach.
A Probabilistic Model for Molecular Systems

We introduce a model for molecular reactions based on probabilistic rewriting rules. We give a probabilistic algorithm for rule applications as a semantics for the model, and we show how a probabilistic transition system can be derived from it. We use the algorithm in the development of an interpreter for the model, which we use to simulate the evolution of molecular systems. In particular, we show the results of the simulation of a real example of enzymatic activity. Moreover, we apply the probabilistic model checker PRISM to the transition system derived by the model of this example, and we show the results of model checking of some illustrative properties.
Disparities in Provider Elicitation of Parents' Developmental Concerns for US Children

OBJECTIVE: To examine factors associated with provider elicitation of parents' developmental concerns among US children. METHODS: The 2007 National Survey of Children's Health was used to examine factors associated with parents' reports of provider elicitation of developmental concerns in the previous 12 months. Independent variables included child characteristics, sociodemographic factors, insurance status, and having a medical home. RESULTS: One-half of US parents reported provider elicitation of developmental concerns. African-American (41%) and Latino (49% in households with English as the primary language and 33% with a non-English primary language) parents were significantly less likely than white parents (55%) to report elicitation of developmental concerns. With multivariate adjustment, African-American (odds ratio [OR]: 0.67 [95% confidence interval [CI]: 0.55–0.81]) and Latino (OR: 0.61 [95% CI: 0.44–0.84]) parents, compared with white parents, had significantly lower adjusted odds of provider elicitation of developmental concerns. Lack of insurance (OR: 0.61 [95% CI: 0.44–0.85]) and having a medical home (OR: 1.42 [95% CI: 1.21–1.67]) were associated with elicitation of developmental concerns. Parents of African-American and Latino children who received family-centered care had almost twice the odds of provider elicitation. For Latino parents in households with a non-English primary language, other medical home components, including having a personal provider (OR: 1.51 [95% CI: 1.08–2.11]) and a usual source of care (OR: 1.76 [95% CI: 1.13–2.74]), were significantly associated with elicitation of developmental concerns. CONCLUSIONS: Racial/ethnic and linguistic disparities exist in provider elicitation of developmental concerns. Addressing lack of insurance, medical homes, and specific medical-home components might reduce disparities.
The uniqueness theorem for entanglement measures

We explore and develop the mathematics of the theory of entanglement measures. After a careful review and analysis of definitions, of preliminary results, and of connections between conditions on entanglement measures, we prove a sharpened version of a uniqueness theorem which gives necessary and sufficient conditions for an entanglement measure to coincide with the reduced von Neumann entropy on pure states. We also prove several versions of a theorem on extreme entanglement measures in the case of mixed states. We analyze properties of the asymptotic regularization of entanglement measures proving, for example, convexity for the entanglement cost and for the regularized relative entropy of entangle ment.
3D building map reconstruction in dense urban areas by integrating airborne laser point cloud with 2D boundary map

Vehicle self-localization techniques, such as GNSS and Velodyne, can benefit greatly by accessing to an accurate 3D building map, especially in urban areas. Though, an accurate automatic 3D building map reconstruction is challenging in dense urban areas, in which buildings are located close to each other. In general, 3D building map can be generated from adding accurate height information of the building roofs to a detailed 2D map. But 2D building maps usually only provide footprint of the buildings which is not enough for 3D shape modeling of complicated buildings in urban areas such as Shinjuku, Tokyo, Japan. On the other hand, with the development of laser scanning technology, airborne laser scanning (ALS) has now become easily accessible for large scale 3D mapping. However, an automatic 3D map reconstruction using only airborne point cloud is not feasible for dense urban areas, because of the difficulty of defining boundary of each building individually. This paper presents an automatic 3D building map reconstruction technique which integrates airborne laser point cloud with 2D boundary map. Results from Shinjuku area is evaluated for the proposed technique.
Decreased G4 (10S) Acetylcholinesterase Content in Motor Nerves to Fast Muscles of Dystrophic 129/ReJ Mice: Lack of a Specific Compartment of Nerve Acetylcholinesterase?

Abstract: Acetylcholinesterase (AChE; EC 3.1.1.7) acivity and the distribution of its molecular forms were studied in the nervous system of normal and dystrophic 129/ReJ mice, including the sciatic‐tibial nerve trunk and motor nerves to slow‐ and fast‐twitch muscles. In normal mice, motor nerves to the slow‐twitch soleus exhibited a low AChE activity together with a low level of G4 (10S form) as compared with nerves of the predominantly fast‐twitch plantaris and extensor digitorum longus. In contrast, in dystrophic mice, the AChE activity as well as the G4 content of nerves to the fast‐twitch muscles were low, displaying an AChE content similar to that of the nerve of the soleus muscle. In the sciatic‐tibial nerve trunk, the AChE activity decreased along the nerve in an exponential mode, at rates that were similar in both conditions. However, in dystrophic mice, the AChE activity was reduced throughout the nerve length by a constant value of approximately 180 nmol/h/mg protein. Further analyses indicated that AChE in this nerve trunk was distributed among two compartments, a decaying and a constant one. The decay involved exclusively the globular forms. The activity of A12 (16S form) remained constant along the nerve and was similar in both normal and dystrophic mice. In addition, according to the equation describing the decay of AChE, the reduction in enzymatic activity observed in the dystrophic mice affected mainly G4 in the constant compartment. Brain, spinal cord, sympathetic ganglia, and serum, which were also examined, showed no remarkable differences between the two conditions in their G4 content. The AChE abnormalities that we found in nervous tissues of 129/ReJ dystrophic mice were confined to the motor system.
Reactive Oxygen Species Mediate Virus-induced STAT Activation

Respiratory syncytial virus (RSV) is the leading cause of epidemic respiratory tract illness in children in the United States and worldwide. RSV infection of airway epithelial cells induces formation of reactive oxygen species (ROS), whose production mediates the expression of cytokines and chemokines involved the immune/inflammatory responses of the lung. In this study, we have investigated the role of ROS in RSV-induced signal transducers and activators of transcription (STAT) activation and interferon regulatory factor (IRF) gene expression in human airway epithelial cells. Our results indicate that RSV replication induces IRF-1 and -7 gene transcription, a response abrogated by antioxidants. RSV infection induces binding of STAT to the IRF-1 γ-interferon-activated sequence (GAS) and IRF-7 interferon-stimulated responsive element (ISRE). STAT1 and STAT3 bind IRF-1 GAS, whereas STAT1, STAT2, IRF-1, and IRF-9 bind IRF-7 ISRE. Antioxidant treatment blocks RSV-induced STAT binding to both the IRF-1 GAS and IRF-7 ISRE by inhibition of inducible STAT1 and STAT3 tyrosine phosphorylation, suggesting that RSV-induced ROS formation is required for STAT activation and IRF gene expression. Although protein tyrosine phosphorylation is necessary for RSV-induced STAT activation, Janus kinase and Src kinase activation do not mediate this effect. Instead, RSV infection inhibits intracellular tyrosine phosphatase activity, which is restored by antioxidant treatment. Pharmacological inhibition of tyrosine phosphatases induces STAT activation. Together, these results suggest that modulation of phosphatases could be an important mechanism of virus-induced STAT activation. Treatment of alveolar epithelial cells with the NAD(P)H oxidase inhibitor diphenylene iodonium abolishes RSV-induced STAT activation, indicating that NAD(P)H oxidase-produced ROS are required for downstream activation of the transcription factors IRF and STAT in virus-infected airway epithelial cells.
Reconstructing influenza incidence by deconvolution of daily mortality time series

We propose a mathematically straightforward method to infer the incidence curve of an epidemic from a recorded daily death curve and time-to-death distribution; the method is based on the Richardson–Lucy deconvolution scheme from optics. We apply the method to reconstruct the incidence curves for the 1918 influenza epidemic in Philadelphia and New York State. The incidence curves are then used to estimate epidemiological quantities, such as daily reproductive numbers and infectivity ratios. We found that during a brief period before the official control measures were implemented in Philadelphia, the drop in the daily number of new infections due to an average infector was much larger than expected from the depletion of susceptibles during that period; this finding was subjected to extensive sensitivity analysis. Combining this with recorded evidence about public behavior, we conclude that public awareness and change in behavior is likely to have had a major role in the slowdown of the epidemic even in a city whose response to the 1918 influenza epidemic is considered to have been among the worst in the U.S.
A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover

Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, grass- and tree-covered areas. SVR and KRR models proved to be stable with regard to the spatial and spectral differences between both images and effectively utilized the higher complexity of the synthetic training mixtures for improving estimates for coarser resolution data. Observed deficiencies mainly relate to known problems arising from spectral similarities or shadowing. The remaining regressors either revealed erratic (NN) or limited (RFR and PLSR) performances when comprehensively mapping urban land cover. Our findings suggest that the combination of kernel-based regression methods, such as SVR and KRR, with synthetically mixed training data is well suited for quantifying urban land cover from imaging spectrometer data at multiple scales.
Winds in the Middle Cloud Deck From the Near‐IR Imaging by the Venus Monitoring Camera Onboard Venus Express

For more than 8 years the Venus Monitoring Camera (VMC) onboard the Venus Express orbiter performed continuous imaging of the Venus cloud layer in UV, visible and near‐IR filters. We applied the correlation approach to sequences of the near‐IR images at 965 nm to track cloud features and determine the wind field in the middle and lower cloud (49–57 km). From the VMC images that spanned from December of 2006 through August of 2013 we derived zonal and meridional components of the wind field. In low‐to‐middle latitudes (5–65°S) the velocity of the retrograde zonal wind was found to be 68–70 m/s. The meridional wind velocity slowly decreases from peak value of +5.8 ± 1.2 m/s at 15°S to 0 at 65–70°S. The mean meridional speed has a positive sign at 5–65°S suggesting equatorward flow. This result, together with the earlier measurements of the poleward flow at the cloud tops, indicates the presence of a closed Hadley cell in the altitude range 55–65 km. Long‐term variations of zonal and meridional velocity components were found during 1,200 Earth days of observation. At 20° ± 5°S the zonal wind speed increases from −67.18 ± 1.81 m/s to −77.30 ± 2.49 m/s. The meridional wind gradually increases from +1.30 ± 1.82 m/s to +8.53 ± 2.14 m/s. Following Bertaux et al. (2016) we attribute this long‐term trend to the influence from the surface topography on the dynamical process in the atmosphere via the upward propagation of gravity waves that became apparent in the VMC observations due to slow drift of the Venus Express orbit over Aphrodite Terra.
Bounded Model Checking for the Universal Fragment of CTL

Bounded Model Checking (BMC) has been recently introduced as an efficient verification method for reactive systems. BMC based on SAT methods consists in searching for a counterexample of a particular length and generating a propositional formula that is satisfiable iff such a counterexample exists. This new technique has been introduced by E. Clarke et al. for model checking of linear time temporal logic (LTL). Our paper shows how the concept of bounded model checking can be extended to ACTL (the universal fragment of CTL). The implementation of the algorithm for Elementary Net Systems is described together with the experimental results.
Storage Management in the NVRAM Era

Emerging nonvolatile memory technologies (NVRAM) offer an alternative to disk that is persistent, provides read latency similar to DRAM, and is byte-addressable. Such NVRAMs could revolutionize online transaction processing (OLTP), which today must employ sophisticated optimizations with substantial software overheads to overcome the long latency and poor random access performance of disk. Nevertheless, many candidate NVRAM technologies exhibit their own limitations, such as greater-than-DRAM latency, particularly for writes. In this paper, we reconsider OLTP durability management to optimize recovery performance and forward-processing throughput for emerging NVRAMs. First, we demonstrate that using NVRAM as a drop-in replacement for disk allows near-instantaneous recovery, but software complexity necessary for disk (i.e., Write Ahead Logging/ARIES) limits transaction throughput. Next, we consider the possibility of removing software-managed DRAM buffering. Finally, we measure the cost of ordering writes to NVRAM, which is vital for correct recovery. We consider three recovery mechanisms: NVRAM Disk-Replacement, In-Place Updates (transactions persist data in-place), and NVRAM Group Commit (transactions commit/persist atomically in batches). Whereas In-Place Updates offers the simplest design, it introduces persist synchronizations at every page update. NVRAM Group Commit minimizes persist synchronization, offering up to a 50% throughput improvement for large synchronous persist latencies.
Modeling electronic health records in ensembles of semantic spaces for adverse drug event detection

Adverse drug events (ADEs) are heavily under-reported in electronic health records (EHRs). Alerting systems that are able to detect potential ADEs on the basis of patient-specific EHR data would help to mitigate this problem. To that end, the use of machine learning has proven to be both efficient and effective; however, challenges remain in representing the heterogeneous EHR data, which moreover tends to be high-dimensional and exceedingly sparse, in a manner conducive to learning high-performing predictive models. Prior work has shown that distributional semantics - that is, natural language processing methods that, traditionally, model the meaning of words in semantic (vector) space on the basis of co-occurrence information - can be exploited to create effective representations of sequential EHR data of various kinds. When modeling data in semantic space, an important design decision concerns the size of the context window around an object of interest, which governs the scope of co-occurrence information that is taken into account and affects the composition of the resulting semantic space. Here, we report on experiments conducted on 27 clinical datasets, demonstrating that performance can be significantly improved by modeling EHR data in ensembles of semantic spaces, consisting of multiple semantic spaces built with different context window sizes. A follow-up investigation is conducted to study the impact on predictive performance as increasingly more semantic spaces are included in the ensemble, demonstrating that accuracy tends to improve with the number of semantic spaces, albeit not monotonically so. Finally, a number of different strategies for combining the semantic spaces are explored, demonstrating the advantage of early (feature) fusion over late (classifier) fusion. Semantic space ensembles allow multiple views of (sparse) data to be captured (densely) and thereby enable improved performance to be obtained on the task of detecting ADEs in EHRs.