Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerating model predictive control by online constraint removal

We propose a method for the acceleration of the online linear model predictive control (MPC) calculations with partial information on the explicit solution. We highlight two properties of the proposed approach: (i) It does not require to calculate the explicit solution first, and its computational effort grows only polynomially in the number of the constraints of the problem. The proposed approach can therefore be applied to problems that are too large for today's explicit MPC methods. (ii) The method is not based on a specific type or implementation of the optimization algorithm and can therefore easily be combined with a variety of existing MPC implementations. The proposed approach is, to the knowledge of the authors, one of yet a few attempts to use the insight into the structure of the explicit MPC law in online MPC.
Clostridium difficile ribotype does not predict severe infection.

BACKGROUND Studies of Clostridium difficile outbreaks suggested that certain ribotypes (eg, 027 and 078) cause more severe disease than other ribotypes. A growing number of studies challenge the validity of this hypothesis. METHODS We conducted a cross-sectional study of C. difficile infection (CDI) to test whether ribotype predicted clinical severity when adjusted for the influence of other predictors. Toxigenic C. difficile isolates were cultured from stool samples, screened for genes encoding virulence factors by polymerase chain reaction (PCR) and ribotyped using high-throughput, fluorescent PCR ribotyping. We collected data for 15 covariates (microbiologic, epidemiologic, and laboratory variables) and determined their individual and cumulative influence on the association between C. difficile ribotype and severe disease. We then validated this influence using an independent data set. RESULTS A total of 34 severe CDI cases were identified among 310 independent cases of disease (11.0%). Eleven covariates, including C. difficile ribotype, were significant predictors of severe CDI in unadjusted analysis. However, the association between ribotypes 027 and 078 and severe CDI was not significant after adjustment for any of the other covariates. After full adjustment, severe cases were significantly predicted only by patients' white blood cell count and albumin level. This result was supported by analysis of a validation data set containing 433 independent CDI cases (45 severe cases; 10.4%). CONCLUSIONS Ribotype is not a significant predictor of severe CDI when adjusted for the influence of any other variables separately or in combination. White blood cell count and albumin level are the most clinically relevant predictors of severe CDI cases.
A new apparatus to induce lysis of planktonic microbial cells by shock compression, cavitation and spray

Experiments were conducted on an aqueous growth medium containing cultures of Escherichia coli (E. coli) XL1-Blue, to investigate, in a single experiment, the effect of two types of dynamic mechanical loading on cellular integrity. A bespoke shock tube was used to subject separate portions of a planktonic bacterial culture to two different loading sequences: (i) shock compression followed by cavitation, and (ii) shock compression followed by spray. The apparatus allows the generation of an adjustable loading shock wave of magnitude up to 300 MPa in a sterile laboratory environment. Cultures of E. coli were tested with this apparatus and the spread-plate technique was used to measure the survivability after mechanical loading. The loading sequence (ii) gave higher mortality than (i), suggesting that the bacteria are more vulnerable to shear deformation and cavitation than to hydrostatic compression. We present the results of preliminary experiments and suggestions for further experimental work; we discuss the potential applications of this technique to sterilize large volumes of fluid samples.
Phonological and orthographic visual word recognition in the two cerebral hemispheres: Evidence from Hebrew

Studies on the cerebral mechanisms of reading have mostly used Latin-based writing systems and assume that the left, but not the right, cerebral hemisphere is capable of phonological processing. The present study used Hebrew as the test language to examine the effects of phonological and orthographic information in the two hemispheres. In unvoweled Hebrew script, words are read via consonant information alone. We used two naming tasks with an interference paradigm, where phonemically, orthographically, and figurally incorrect vowel information conflicted with the consonant information of words presented in the left, right, or central visual fields. Interference patterns indicated that the left hemisphere automatically transforms graphemes into phonemes (Experiments 1 and 2), whereas the right hemisphere processes vowel diacritics as visual objects (Experiment 1), although it possesses some phonological categories (Experiment 2). The significance of these findings for models of visual word recognition in the cerebral hemispheres is discussed.
The role of atmospheric correction algorithms in the prediction of soil organic carbon from Hyperion data

ABSTRACT In this study, the role of atmospheric correction algorithm in the prediction of soil organic carbon (SOC) from spaceborne hyperspectral sensor (Hyperion) visible near-infrared (vis-NIR, 400–2500 nm) data was analysed in fields located in two different geographical settings, viz. Karnataka in India and Narrabri in Australia. Atmospheric correction algorithms, (1) ATmospheric CORection (ATCOR), (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), (3) 6S, and (4) QUick Atmospheric Correction (QUAC), were employed for retrieving spectral reflectance from radiance image. The results showed that ATCOR corrected spectra coupled with partial least square regression prediction model, produced the best SOC prediction performances, irrespective of the study area. Comparing the results across study areas, Karnataka region gave lower prediction accuracy than Narrabri region. This may be explained due to difference in spatial arrangement of field conditions. A spectral similarity comparison of atmospherically corrected Hyperion spectra of soil samples with field-measured vis-NIR spectra was performed. Among the atmospheric correction algorithms, ATCOR corrected spectra found to capture the pattern in soil reflectance curve near 2200 nm. ATCOR’s finer spectral sampling distance in shortwave infrared wavelength region compared to other models may be the main reason for its better performance. This work would open up a great scope for accurate SOC mapping when future hyperspectral missions are realized.
Multiple-Window Anomaly Detection for Hyperspectral Imagery

Due to advances of hyperspectral imaging sensors many unknown and subtle targets that cannot be resolved by multispectral imagery can now be uncovered by hyperspectral imagery. These targets generally cannot be identified by visual inspection or prior knowledge, but yet provide crucial and vital information for data exploitation. One such type of targets is anomalies which have recently received considerable interest in hyperspectral image analysis. Many anomaly detectors have been developed and most of them are based on the most widely used Reed-Yu's algorithm, called RX detector (RXD). However, a key issue in making RX detector-like anomaly detectors effective is how to effectively utilize the spectral information provided by data samples, e.g., sample covariance matrix used by RXD. Recently, a dual window-based eigen separation transform (DWEST) was developed to address this issue. This paper extends the concept of DWEST to develop a new approach, to be called multiple-window anomaly detection (MWAD) by making use of multiple windows to perform anomaly detection adaptively. As a result, MWAD is able to detect anomalies of various sizes using multiple windows so that local spectral variations can be characterized and extracted by different window sizes. By virtue of this newly developed MWAD, many existing RXD-like anomaly detectors including DWEST can be derived as special cases of MWAD.
Early detection of visual field progression in glaucoma: a comparison of progressor and statpac 2

AIM To compare the performance ofprogressor (pointwise linear regression) and statpac2 (comparison with baseline values) in detecting early deterioration in the visual fields of glaucoma patients. METHODS Visual field series from 19 untreated normal tension glaucoma eyes which were deteriorating on clinical grounds were analysed by progressor and statpac2. Progression criteria forprogressor were (1) inner points: slope < −1 dB/year, p < 0.05 and (2) edge points: slope < −2 dB/year, p < 0.05. Criteria for statpac 2 were p < 0.05 change probability for any point on three consecutive fields. Detection time was defined as the time interval between the initial field and the first field in which at least one progressing point was identified. Detection times produced by the two techniques were compared. RESULTS progressor and statpac2 agreed on progression in all 19 eyes. Mean detection time for progressor was 1.077 (SD 0.985) years and for statpac 2 was 2.161 (1.357) years. progressor detected progression sooner thanstatpac 2 in 18 eyes (p < 0.01, Wilcoxon matched pairs signed rank test). progressordetected progression earlier by a mean of 1.085 (0.936) years. CONCLUSIONS progressor consistently detected progression earlier than statpac2. The progressor software is a useful tool for the early detection of visual field deterioration in glaucoma.
Performance of Global Atmospheric Datasets towards Groundwater Management

Abstract With the aim of refining a reliable tool for groundwater management, the ERA-Interim and ERA5 global atmospheric datasets provided by the European Centre for MediumRange Weather Forecasts (ECMWF) are examined. Attention is focused on the analysis of the behavior of the soil moisture content. The performance of ERA-Interim and ERA5 is evaluated by considering the water table measurements at three sites in the Umbria region as well as the dynamics of water flow towards the groundwater.
Lattice-based threshold cryptography and its applications in distributed cloud computing

Distributed cloud computing provides an opportunity for users, companies, and public organisations to compute with low cost and high efficiency. Meanwhile, information in local computers is now transferred to distributed cloud platforms, where users' information is much easier to obtain and be tampered with by malicious participants. Fortunately, threshold cryptographical schemes can improve robustness against malicious participants in group. However, threshold cryptographical schemes against quantum attack are the main barrier of cloud security in a 'post-quantum' world. This paper focuses on the research of threshold cryptography against quantum attack. We present a more efficient lattice-based secret sharing algorithm LB-SSA, where each sharer can independently generate his public key and secret key without interactivity. We also present two applications of LB-SSA: a multi-authority identity-based encryption MA-IBE scheme from lattices and a threshold decryption scheme from lattices. To the best of our knowledge, our MA-IBE is the first lattice-based IBE scheme under multiple authorities.
Tsunami Hazard Assessment for the Hokuriku Region, Japan: Toward Disaster Mitigation for Future Earthquakes

In Japan, compared with the Pacific coast, the Japan Sea coast has low seismicity and has experienced very few occurrences of historical tsunami damage. These characteristics lead to some difficulties in the promotion of disaster prevention education, because the Japan Sea coast has not often been threatened by earthquakes and tsunamis. In our study, focusing on the Hokuriku region in Japan, we conducted a tsunami simulation and examined the resulting tsunami hazard map. Three potential faults of Mw7.6 earthquake were selected to generate the tsunami. In addition, we calculated these three events with Mw7.8, given the inherent uncertainty in source parameters. Aside from tsunami height, arrival time, inundation height, and inundation area, we calculated the seismic intensity and the liquefaction occurrence rate by simplified methods. Our results indicated that Suzu City in Ishikawa Prefecture, located in the northeastern part of the Noto Peninsula, has a relatively high potential risk of tsunami as well as strong motion and liquefaction. Thus, Suzu City would represent a highly appropriate area in which to promote disaster prevention education in the Hokuriku region.
Function and regulation of Rnd proteins in cortical projection neuron migration

The mammalian cerebral cortex contains a high variety of neuronal subtypes that acquire precise spatial locations and form long or short-range connections to establish functional neuronal circuits. During embryonic development, cortical projection neurons are generated in the areas lining the lateral ventricles and they subsequently undergo radial migration to reach the position of their final maturation within the cortical plate. The control of the neuroblast migratory behavior and the coordination of the migration process with other neurogenic events such as cell cycle exit, differentiation and final maturation are crucial to normal brain development. Among the key regulators of cortical neuron migration, the small GTP binding proteins of the Rho family and the atypical Rnd members play important roles in integrating intracellular signaling pathways into changes in cytoskeletal dynamics and motility behavior. Here we review the role of Rnd proteins during cortical neuronal migration and we discuss both the upstream mechanisms that regulate Rnd protein activity and the downstream molecular pathways that mediate Rnd effects on cell cytoskeleton.
Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing

We consider the problem of estimating a regression function in the common situation where the number of features is small, where interpretability of the model is a high priority, and where simple linear or additive models fail to provide adequate performance. To address this problem, we present Maximum Variance Total Variation denoising (MVTV), an approach that is conceptually related both to CART and to the more recent CRISP algorithm, a state-of-the-art alternative method for interpretable nonlinear regression. MVTV divides the feature space into blocks of constant value and fits the value of all blocks jointly via a convex optimization routine. Our method is fully data-adaptive, in that it incorporates highly robust routines for tuning all hyperparameters automatically. We compare our approach against CART and CRISP via both a complexity-accuracy tradeoff metric and a human study, demonstrating that that MVTV is a more powerful and interpretable method.
On the effectiveness of dynamically allocating resources across program execution phases for media workloads

Processing embedded applications is essentially a trade-off between power and performance. Increasing level of complexity in present day microprocessor at the expense of more power call for different optimization methodologies at architecture level. The study of general characteristics of program execution phases gives insight to dynamically reconfigure or enable/disable additional resources on-demand basis. This leads to significant amount of power saving with negligible or tolerable performance degradation. We characterize execution of such programs into execution phases based on their dynamic IPC profile. We show that program execution of selected phases (based on IPC profile) can be dynamically boosted by activating additional standby functional units which are otherwise powered down for saving energy. Through simulation we show that speedup ranging from 1.1 to 1.25 can be achieved while reducing the energy-delay product (EDP) for most of the media benchmarks evaluated.
A Key-Value Based Application Platform for Enterprise Big Data

Big data poses big challenges to modern enterprises. Traditional data-intensive business applications begin to fall behind the times, because of insufficient capabilities to process large data volumes, ever-changing streaming data and unstructured information. Furthermore, large, complex and all-in-one enterprise applications are no longer popular, whereas lightweight and fragmentary applications become welcome for the sake of the bursts of cloud computing and mobile internet. Below this kind of situation, this paper proposed a big data application platform for enterprises to simply develop and operate personalized data retrieval, data analysis, business intelligence and other data-intensive services. Unlike current related products, it is distinguished for the design of key-value based hybrid data storage and a service-oriented outsourcing architecture. The former is used to resolve the frequently-encountered issue of diversified and massive data storage, and the latter enables an open environment for third-party vendors, which promotes a self-increasing services ecosystem for big data application development. In order to validate the feasibility of our platform, the paper also developed a sentiment analysis application for Kingdee popular products based on the services provided by the platform. The result of our experiment proves that the platform shows enough potential to effectively facilitate data-intensive application development.
Genetic Determination and Linkage Mapping of Plasmodium falciparum Malaria Related Traits in Senegal

Plasmodium falciparum malaria episodes may vary considerably in their severity and clinical manifestations. There is good evidence that host genetic factors contribute to this variability. To date, most genetic studies aiming at the identification of these genes have used a case/control study design for severe malaria, exploring specific candidate genes. Here, we performed a family-based genetic study of falciparum malaria related phenotypes in two independent longitudinal survey cohorts, as a first step towards the identification of genes and mechanisms involved in the outcome of infection. We studied two Senegalese villages, Dielmo and Ndiop that differ in ethnicity, malaria transmission and endemicity. We performed genome-scan linkage analysis of several malaria-related phenotypes both during clinical attacks and asymptomatic infection. We show evidence for a strong genetic contribution to both the number of clinical falciparum malaria attacks and the asymptomatic parasite density. The asymptomatic parasite density showed linkage to chromosome 5q31 (LOD = 2.26, empirical p = 0.0014, Dielmo), confirming previous findings in other studies. Suggestive linkage values were also obtained at three additional chromosome regions: the number of clinical malaria attacks on chromosome 5p15 (LOD = 2.57, empirical p = 0.001, Dielmo) and 13q13 (LOD = 2.37, empirical p = 0.0014 Dielmo), and the maximum parasite density during asymptomatic infection on chromosome 12q21 (LOD = 3.1, empirical p<10−4, Ndiop). While regions of linkage show little overlap with genes known to be involved in severe malaria, the four regions appear to overlap with regions linked to asthma or atopy related traits, suggesting that common immune related pathways may be involved.
Activation of the major immediate early gene of human cytomegalovirus by cis-acting elements in the promoter-regulatory sequence and by virus-specific trans-acting components

Upstream of the major immediate early gene of human cytomegalovirus (Towne) is a strong promoter-regulatory region that promotes the synthesis of 1.95-kilobase mRNA (D. R. Thomsen, R. M. Stenberg, W. F. Goins, and M. F. Stinski, Proc. Natl. Acad. Sci. U.S.A. 81:659-663, 1984; M. F. Stinski, D. R. Thomsen, R. M. Stenberg, and L. C. Goldstein, J. Virol. 46:1-14, 1983). The wild-type promoter-regulatory region as well as deletions within this region were ligated upstream of the thymidine kinase, chloramphenicol acetyltransferase, or ovalbumin genes. These gene chimeras were constructed to investigate the role of the regulatory sequences in enhancing downstream expression. The regulatory region extends to approximately 465 nucleotides upstream of the cap site for the initiation of transcription. The extent and type of regulatory sequences upstream of the promoter influences the level of in vitro transcription as well as the amount of in vivo expression of the downstream gene. The regulatory elements for cis-activation appear to be repeated several times within the regulatory region. A direct correlation was established between the distribution of the 19 (5' CCCCAGTTGACGTCAATGGG 3')- and 18 (5' CACTAACGGGACTTTCCAA 3')-nucleotide repeats and the level of downstream expression. In contrast, the 16 (5' CTTGGCAGTACATCAA 3')-nucleotide repeat is not necessary for the enhancement of downstream expression. In a domain associated with the 19- or 18-nucleotide repeats are elements that can be activated in trans by a human cytomegalovirus-specified component but not a herpes simplex virus-specified component. Therefore, the regulatory sequences of the major immediate early gene of human cytomegalovirus have an important role in interacting with cellular and virus-specific factors of the transcription complex to enhance downstream expression of this critical viral gene.
VALIDATION PROCESS OF THE STVF HARDWARE-IN-THE-LOOP SIMULATION FACILITY

As a partner in the International Space Station (ISS), Canada is responsible for the verification of all tasks involving Dextre, also known as the Special Purpose Dextrous Manipulator (SPDM). Those verifications cannot be performed using only software simulators since the accuracy of current contact dynamic models are yet to be confirmed. Instead, a solution involving hardware-in-the-loop simulation was retained. With this option, the space hardware is simulated while the contact dynamics is emulated using a rigid robot performing the tasks. Using this approach, the Canadian Space Agency developed the SPDM Task and Verification Facility (STVF). The approach suggested to validate STVF is based on first building confidence by comparing experimental results with pure simulation results for cases easy to model. Then, the complexity of the experimentations is increased. Preliminary test results presented in this paper show that STVF is performing well.
Cropland abandonment enhances soil inorganic nitrogen retention and carbon stock in China: A meta‐analysis

Transforming cropland into a semi‐natural ecosystem is an effective approach to increase soil organic carbon (SOC) and nitrogen sequestration. However, we know little about large‐scale response patterns of SOC, soil inorganic nitrogen (SIN), and their interactions over long time of ecosystem restoration. Here, we conducted a meta‐analysis to examine changes in SOC, SIN, and their relationship along 50 year's ecosystem development from cropland transformation in China's ‘Grain for Green’ Programme. Our results showed that SOC and SIN were consistently enhanced by 57% and 35% with transformation, respectively. Similar with SOC, SIN had higher response magnitudes when cropland was restored to forests (47%) than to shrublands (36%) and grasslands (24%). Both SOC and SIN response ratios showed a quadratic relationship with precipitation. Moreover, we found a strong linear relationship (R2 = 0.36) between SOC and SIN response ratio, with the slope indicating a 0.43% increase in SIN per 1% of increasing SOC. This SIN retention capacity (the slope) significantly increased with restoration time but reduced with precipitation, temperature, and initial SOC. Restored forest had a lower SIN retention capacity than had shrubland and grassland. Overall, this study represents the first to regionally uncover SIN retention mechanism with increasing SOC during ecosystem development. It suggests that ecosystem restoration will contribute more to relieving serious environmental problems (i.e., N leaching and N2O emission) by enhancing SIN retention in China's Grain for Green Programme.