Miracle-dz/UniFAR-FTUs huggingface dataset:
Transient climate change and net ecosystem production of the terrestrial biosphere

In this sensitivity study, we have applied the Terrestrial Ecosystem Model ((TEM) version 4.1) to examine the responses of terrestrial ecosystems to transient changes in atmospheric CO2 concentration and climate in the 21st century at the scales of the globe, biomes, latitudinal gradient, and economic regions. Three predictions of transient change in climate and atmospheric CO2 concentration in the 21st century from the Integrated Global System Model developed at Massachusetts Institute of Technology were used. The TEM estimates a global annual net ecosystem production (NEP) of about 0.8 Pg C yr−1 in 1990. Global annual NEP in 2100 increases by about 2.6 Pg C yr−1 for the HHL (higher CO2 emissions and temperature increases), 1.8 Pg C yr−1 for the RRR (reference CO2 emissions and temperature increases), and 0.5 Pg C yr−1 for the LLH (lower CO2 emissions and temperature increases) climate change predictions. The boreal and tropical evergreen forests account for a large portion of the increased global annual NEP. Latitudinal distribution of total annual NEP along 0.5°‐resolution latitudinal bands shifts significantly from the tropics to the northern middle and high latitudes over time. The potential CO2 uptake over the period of 1990–2100 differs substantially among the 12 economic regions of the world. As we used potential mature natural vegetation in the global extrapolation of TEM, these NEP estimates represent the potential CO2 uptake or the upper bound for long‐term carbon sequestration by the terrestrial biosphere. This sensitivity study shows that the temporal dynamics and spatial distribution of carbon, nitrogen, and water fluxes of terrestrial ecosystems are very sensitive to the magnitudes and paths of transient changes in atmospheric CO2 concentration and climate in the 21st century.
Exploratory Multilevel Hot Spot Analysis: Australian Taxation Office Case Study

Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called 'hot spots', are small and sparse, they are usually of special interest to an analyst. In this paper we introduce a visual drill-down Self-Organizing Map (SOM)-based approach to explore such hot spots characteristics in real-life datasets. Iterative clustering algorithms (such as k-means) and SOM are not designed to show these small and sparse clusters in detail. The feasibility of our approach is demonstrated using a large real life dataset from the Australian Taxation Office.
Fault Diagnosis With Convolutional Compactors

This paper presents new nonadaptive fault-diagnosis techniques for scan-based designs. They guarantee accurate and time-efficient identification of failing scan cells based on results of convolutional compaction of test responses. The essence of the method is to use a branch-and-bound algorithm to narrow the set of scan cells down to certain sites that are most likely to capture faulty signals. This search is guided by a number of heuristics and self-learned information used to accelerate the diagnosis process for the subsequent test patterns. A variety of experimental results for benchmark circuits, industrial designs, and real fail logs confirm the feasibility of the proposed approach even in the presence of unknown states. The scheme remains consistent with a single test session scenario and allows high-volume in-production diagnosis.
Induction of Angiogenesis by Matrigel Coating of VEGF-Loaded PEG/PCL-Based Hydrogel Scaffolds for hBMSC Transplantation

hBMSCs are multipotent cells that are useful for tissue regeneration to treat degenerative diseases and others for their differentiation ability into chondrocytes, osteoblasts, adipocytes, hepatocytes and neuronal cells. In this study, biodegradable elastic hydrogels consisting of hydrophilic poly(ethylene glycol) (PEG) and hydrophobic poly(ε-caprolactone) (PCL) scaffolds were evaluated for tissue engineering because of its biocompatibility and the ability to control the release of bioactive peptides. The primary cultured cells from human bone marrow are confirmed as hBMSC by immunohistochemical analysis. Mesenchymal stem cell markers (collagen type I, fibronectin, CD54, integrin1β, and Hu protein) were shown to be positive, while hematopoietic stem cell markers (CD14 and CD45) were shown to be negative. Three different hydrogel scaffolds with different block compositions (PEG:PCL=6:14 and 14:6 by weight) were fabricated using the salt leaching method. The hBMSCs were expanded, seeded on the scaffolds, and cultured up to 8 days under static conditions in Iscove’s Modified Dulbecco’s Media (IMDM). The growth of MSCs cultured on the hydrogel with PEG/PCL= 6/14 was faster than that of the others. In addition, the morphology of MSCs seemed to be normal and no cytotoxicity was found. The coating of the vascular endothelial growth factor (VEGF) containing scaffold with Matrigel slowed down the release of VEGF in vitro and promoted the angiogenesis when transplanted into BALB/c nude mice. These results suggest that hBMSCs can be supported by a biode gradable hydrogel scaffold for effective cell growth, and enhance the angiogenesis by Matrigel coating.
Muscle-actuated power generator using cultured cardiomyocytes and pzt fiber

A novel bio hybrid micro power generator using cardiomyocytes on a polymer wire is proposed. Cultured cardiomyocytes convert chemical energy into kinetic energy efficiently and beat themselves autonomously. PZT fiber was utilized for cell immobilized substrate and electro-mechanical coupling material. In this paper, two preliminary experimental results were shown to prove this principle.
Behavior modulation of autonomous mobile robotics using fuzzy control method

In recent years, intelligent control is playing a more and more important role when dealing with Autonomous Mobile Robot (known as AMR), in unstructured, unknown or partly unknown, and dynamic environments. In dividing the overall task into subtasks, the intelligent controller allows reducing the robot's task complexity. But the fusion of different behaviors with different objectives may cause contradiction in the procedure and alter the stability of system. Therefore the issue of behavior coordination mechanisms is crucial in order to realize the non-collision safety-ensured movement. A method based on Fuzzy Discrete Event System is proposed in this paper. A new approach with four basic behaviors: route following, target going, obstacle avoiding and deadlock disarming, for mobile robot navigation are discussed. Player/Stage simulation results show that the proposed approach is effective in navigating mobile robots in dynamic unknown circumstances.
Vision-Based Nighttime Vehicle Detection Using CenSurE and SVM

In this paper, we propose a method for detecting vehicles from a nighttime driving scene taken by an in-vehicle monocular camera. Since it is difficult to recognize the shape of the vehicles during nighttime, vehicle detection is based on the headlights and the taillights, which are bright areas of pixels called blobs. Many research studies using automatic multilevel thresholding are being conducted, but these methods are prone to get affected by the ambient light because it uses the luminance of the whole image to derive the thresholds. Owing to such reasons, we focused on the Laplacian of Gaussian operator, which derives the response of luminance difference between the blob and its surroundings. Compared with automatic multilevel thresholding, Laplacian of Gaussian operator is more robust to the ambient light. However, the computational cost to derive the response of this operator is large. Therefore, we used a method called Center Surround Extremas to detect the blobs in high speed. Since the detected blobs include nuisance lights, we had to determine whether the blob is a light of a vehicle or not. Thus, we classified them according to the features of the blob using support vector machines. Then, we detected vehicle traffic lane and specified the region where the vehicle may exist. Finally, we classified the blobs based on the movements across the frames. We applied the proposed method to nighttime driving sequences and confirmed the effectiveness of the classification process used in this method and that it could process within frame rate.
Cooperative relay cognitive interference channel

The cooperative relay cognitive interference channel (RCIC) is a four-node network with two source nodes (primary source and cognitive source) and two destination nodes, in which sources try to communicate at certain rates with their corresponding destinations simultaneously through a common medium and each destination can act as a relay to assist the other one. For the partially cooperative RCIC (PC-RCIC), in which only one of the destinations (corresponding to the cognitive source) acts as a relay, we derive an achievable rate region based on using rate splitting and superposition coding at the cognitive source, and using decode-and-forward scheme at the relay. For the degraded PC-RCIC, we characterize the capacity region. We also investigate the Gaussian PC-RCIC in details. In this case, we present the achievability and converse arguments for a class of degraded Gaussian PC-RCIC and determine the capacity region of this class. Obtained results offer the cooperative relaying as an effective strategy for improving the capacity region of the cognitive interference channels (CICs).
The Making of "Estimation of Common Long-Memory Components in Cointegrated Systems"

The eighties were very good years for music as well as econometrics. In time-series econometrics, the ﬁrst half of that decade was dominated by research onunit roots while cointegration was the queen of the second half. Estimation andtesting of a cointegrated system were the key questions to answer.When I started my dissertation at the end of the eighties, under the super-vision of Clive Granger and Robert Engle, you could sense that everyone was ofthe opinion that the testing problem of the cointegration rank had been solvedby Johansen (1988). Johansen applied reduced rank regression techniques to thefollowing error correction model (ECM) (Granger’s old notation is used to keepthe spirit of the eighties)Δ
Hermoupolis: a semantic trajectory generator in the data science era

The domain of trajectory data management and mining undoubtedly contributes with interesting research problems and corresponding effective solutions to what is called data science. An interesting trend that poses new challenges in the field and has emerged especially due to the advance of location-based social networks, is that involved data cannot be considered purely spatiotemporal; trajectories of moving objects also contain additional semantic information that deserves to be further explored. On the other hand, the recently available real trajectory datasets are neither adequate nor appropriate for a wide empirical evaluation of related research proposals. As in other domains, a practical approach to overcome this limitation is developing efficient and functional synthetic trajectory generators. In this line of research, we present Hermoupolis, a pattern- and semantic-aware synthetic trajectory generator, which is able to produce realistic semantic trajectory datasets (along with their synchronized raw spatiotemporal counterparts), conforming to mobility profiles given as input by users.
Learning networks from high dimensional binary data: An application to genomic instability data

Genomic instability, the propensity of aberrations in chromosomes, plays a critical role in the development of many diseases. High throughput genotyping experiments have been performed to study genomic instability in diseases. The output of such experiments can be summarized as high dimensional binary vectors, where each binary variable records aberration status at one marker locus. It is of keen interest to understand how these aberrations interact with each other. In this paper, we propose a novel method, \texttt{LogitNet}, to infer the interactions among aberration events. The method is based on penalized logistic regression with an extension to account for spatial correlation in the genomic instability data. We conduct extensive simulation studies and show that the proposed method performs well in the situations considered. Finally, we illustrate the method using genomic instability data from breast cancer samples.
Face Indexing and Retrieval by Spatial Similarity

In this paper a face indexing scheme based on spatial similarity is proposed. Spatial scattering of anatomically relevant dominant points on faces is preserved in the kd-tree index structure for efficient retrieval. The methodology is invariant to linear transformation and is robust for pose and expression variations. Experimentation on ORL face database has corroborated the retrieval effectiveness and time efficiency of the proposed methodology.
The importance of selecting the appropriate reference genes for quantitative real time PCR as illustrated using colon cancer cells and tissue

Quantitative real-time reverse-transcription polymerase chain reaction (RT-qPCR) remains the most sensitive technique for nucleic acid quantification. Its popularity is reflected in the remarkable number of publications reporting RT-qPCR data. Careful normalisation within RT-qPCR studies is imperative to ensure accurate quantification of mRNA levels. This is commonly achieved through the use of reference genes as an internal control to normalise the mRNA levels between different samples. The selection of appropriate reference genes can be a challenge as transcript levels vary with physiology, pathology and development, making the information within the transcriptome flexible and variable. In this study, we examined the variation in expression of a panel of nine candidate reference genes in HCT116 and HT29 2-dimensional and 3-dimensional cultures, as well as in normal and cancerous colon tissue. Using normfinder we identified the top three most stable genes for all conditions. Further to this we compared the change in expression of a selection of PKC coding genes when the data was normalised to one reference gene and three reference genes. Here we demonstrated that there is a variation in the fold changes obtained dependent on the number of reference genes used. As well as this, we highlight important considerations namely; assay efficiency tests, inhibition tests and RNA assessment which should also be implemented into all RT-qPCR studies. All this data combined demonstrates the need for careful experimental design in RT-qPCR studies to help eliminate false interpretation and reporting of results.
An Active Learning Method for Mining Time-Changing Data Streams

Many applications generate continuous, time-changing data streams. Mining it for an adaptive classifier is of great interest and challenge. Many previous efforts impractically assume the labeled data is available and can be mined at anytime. In this paper, we propose an effective active learning method to mine time-changing data streams efficiently. It designs a way to monitoring the possible changes on the fly without need knowing the labeled data. Upon the suspected changes are indicated, it employs a light-weight uncertainty sampling algorithm to choose the most informative instances to label. With these representative labeled instances, it tests the significance of the suspected changes. If the changes indeed cause significant performance deterioration of the current classifier, it reconstructs the old model. Thus, our method can reliably detect significant changes, quickly adapt to concept-drift, and result effective models. Experimental results from real-world data confirm the advantages of our method.
Inulin-Based Tablet in Capsule Device for Variable Multipulse Delivery of Aceclofenac: Optimization and In Vivo Roentgenography

The aim of the study was to develop single-unit tablet in capsule system of aceclofenac for the treatment of late night pain and morning stiffness associated with rheumatoid arthritis. The system was conceptualized as a three-component design (1) a hard gelatin enteric-coated capsule (for carrying two pulses), (2) first-pulse granules (for rapid release in intestine), and (2) second-pulse matrix tablet (for slow release in colon). An appropriate integration of pH-sensitive (Eudragit S100) and bacteria-responsive (inulin) functions, on the basis of 32 factorial design, led to formulation of TICS 1–9 that were screened for in vitro release. TICS 2 with biphasic drug release of 98.64% from first-pulse granules in simulated intestinal fluid (12 h) and 97.82% from second-pulse matrix tablet in simulated colonic fluid (24 h) was the optimized formulation that exhibited Fickian diffusion of drug (n = 0.363). In vivo fluoroscopy in rats traced the intact tablet to colon in 7.5 h that got eroded at the tenth hour. This demonstrated the colon-specific delivery of the matrix tablet affirming the potential of the system to obviate the need for two-time administration of drug at odd hours. The experimental design was validated by extra design check point, and diffuse reflectance spectroscopy and DSC revealed absence of chemical interaction between the formulation excipients.
Selective placement of quantum dots on nanoscale areas of metal‐free substrates

We demonstrate a novel approach for selectively immobiliz‐ing semiconductor core–shell quantum dots directly on metal‐free substrates with nanoscale resolution. This is accomplished by defining a mask via electron‐beam lithography (EBL) followed by the functionalization of only the exposed areas of the substrate with quantum dots using a heterobi‐functional linker. Non‐specific binding is suppressed by a binding inhibitor. (© 2014 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)
ROCK IMAGE RETRIEVAL AND CLASSIFICATION BASED ON GRANULARITY

In this paper, we consider the use of texture granularity in the classification and retrieval of natural rock images. In rock science, the rock images are nowadays stored into large image databases. In the images, there often occur large grains which differ clearly from rock texture. The purpose of this work is to find grain rock images from the database. We present two approaches to this purpose: classification and retrieval approach. In both approaches, the grains of desired color and size are recognized from the database images using color analysis combined with morphological tools. The experimental results show that using our method, the images with grain can be distinguished from the other rock images.
Reproductive Parameters in the Critically Endangered Blue-Throated Macaw: Limits to the Recovery of a Parrot under Intensive Management

Rediscovered in the wild twenty years ago, the breeding biology of wild Blue-throated Macaws remains largely unexplored, yet is essential to its effective conservation and recovery. Here, we analyse reproductive parameters in an intensively managed wild population of Blue-throated Macaws, providing the first data on the breeding biology of this critically endangered species. During the six-year study period, 2007–2012, the number of active breeding pairs either remained constant or decreased, depending on the site, and no new breeding pairs were discovered despite extensive searching. We documented nesting attempts in natural cavities in dead palms or live hardwoods, and artificial nest boxes. Egg-laying was concentrated during the end of dry season and the beginning of the wet season, August through December. Hatching failure was the greatest cause of egg losses. Half of the breeding attempts of Blue-throated Macaws produced at least one fledging, on average two, after a 85 days nestling period. An average of 4.3 nestlings per year fledged from all known wild nests combined. Each pair lost roughly 65% of its initial reproductive investment at each nesting attempt. In most successful nesting attempts of individualized pairs, a new nesting attempt was not detected the following year. All monitored breeding pairs showed high nest site fidelity, reusing hardwood-tree cavities and nest boxes. Our findings will aid conservation efforts by refining current actions and prompting new approaches towards the conservation and recovery of the Blue-throated Macaw.
Identification of a Putative Protein Profile Associated with Tamoxifen Therapy Resistance in Breast Cancer*S⃞

Tamoxifen resistance is a major cause of death in patients with recurrent breast cancer. Current clinical factors can correctly predict therapy response in only half of the treated patients. Identification of proteins that are associated with tamoxifen resistance is a first step toward better response prediction and tailored treatment of patients. In the present study we intended to identify putative protein biomarkers indicative of tamoxifen therapy resistance in breast cancer using nano-LC coupled with FTICR MS. Comparative proteome analysis was performed on ∼5,500 pooled tumor cells (corresponding to ∼550 ng of protein lysate/analysis) obtained through laser capture microdissection (LCM) from two independently processed data sets (n = 24 and n = 27) containing both tamoxifen therapy-sensitive and therapy-resistant tumors. Peptides and proteins were identified by matching mass and elution time of newly acquired LC-MS features to information in previously generated accurate mass and time tag reference databases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with ≥2 peptides. 1,713 overlapping proteins between the two data sets were used for further analysis. Comparative proteome analysis revealed 100 putatively differentially abundant proteins between tamoxifen-sensitive and tamoxifen-resistant tumors. The presence and relative abundance for 47 differentially abundant proteins were verified by targeted nano-LC-MS/MS in a selection of unpooled, non-microdissected discovery set tumor tissue extracts. ENPP1, EIF3E, and GNB4 were significantly associated with progression-free survival upon tamoxifen treatment for recurrent disease. Differential abundance of our top discriminating protein, extracellular matrix metalloproteinase inducer, was validated by tissue microarray in an independent patient cohort (n = 156). Extracellular matrix metalloproteinase inducer levels were higher in therapy-resistant tumors and significantly associated with an earlier tumor progression following first line tamoxifen treatment (hazard ratio, 1.87; 95% confidence interval, 1.25–2.80; p = 0.002). In summary, comparative proteomics performed on laser capture microdissection-derived breast tumor cells using nano-LC-FTICR MS technology revealed a set of putative biomarkers associated with tamoxifen therapy resistance in recurrent breast cancer.
A time-optimal trajectory planning approach based on calculation cost consideration

A new smooth online near time-optimal trajectory planning approach is proposed to reduce the computation cost compared to traditional dynamics trajectory planning method. The robot path is expressed by a scalar path coordinate s. The joints torque bounds and speed bounds are transformed into the s-s plane, which can generate the limitation curves of pseudo-velocity. The maximum pseudo-velocity curve which meets the limitation of torque and speed is constructed through the feature points and control points in the s-s plane using cubic polynomial fitting method. Control points used for cubic polynomial construction are optimized by the Golden-Section method. The calculation time of this method is shorter than traditional dynamics method. Compared to five-order polynomial trajectory optimization method, the approach proposed in this paper can effectively take advantage of joints maximum speed.