Miracle-dz/UniFAR-FTUs huggingface dataset:
Harvesting aware power management for sensor networks

Energy harvesting offers a promising alternative to solve the sustainability limitations arising from battery size constraints in sensor networks. Several considerations in using an environmental energy source are fundamentally different from using batteries. Rather than a limit on the total energy, harvesting transducers impose a limit on the instantaneous power available. Further, environmental energy availability is often highly variable and a deterministic metric such as residual battery capacity is not available to characterize the energy source. The different nodes in a sensor network may also have different energy harvesting opportunities. Since the same end-user performance may be achieved using different workload allocations at multiple nodes, it is important to adapt the workload allocation to the spatio-temporal energy availability profile in order to enable energy-neutral operation of the network. This paper describes power management techniques for such energy harvesting sensor networks. Platform design considerations as well as power scaling techniques at the node-level and network-level are described
Biomedical Named Entity Recognition based on Deep Neutral Network

Many machine learning methods have been applied on the biomedical named entity recognition and achieve good results on GENIA corpus. However most of those methods reply on the feature engineering which is labor-intensive. In this paper ， huge potential feature information represented as word vectors are generated by neutral networks based on unlabeled biomedical text files. We propose a Biomedical Named Entity Recognition (Bio-NER) method based on deep neural network architecture which has multiple layers and each layer abstracts features based upon the features generated by lower layers. Our system achieved F-score 71.01% on GENIA regular test corpus , F-score values for 5-fold cross-validation is 71.01% and this result is closed to the state-of-the-art performance with only POS (Part-of-speech) feature and represents the deep learning can effectively performed on biomedical NER.
Candidate microRNA Biomarkers in Human Gastric Cancer: A Systematic Review and Validation Study

Gastric cancer (GC) remains a major cause of morbidity and mortality worldwide and there is therefore a clear need to search for more sensitive early diagnostic biomarkers. We performed a systematic review of eight published miRNA profiling studies that compared GC tissues with adjacent noncancerous tissues. A miRNA ranking system was used that took the frequency of comparisons, direction of differential expression and total sample size into consideration. We identified five miRNAs that were most consistently reported to be upregulated (miR-21, miR-106b, miR-17, miR-18a and miR-20a) and two miRNAs that were downregulated (miR-378 and miR-638). Six of these were further validated in 32 paired sets of GC and adjacent noncancerous tissue samples using real-time PCR. MiR-21, miR-106b, miR-17, miR-18a and miR-20a were confirmed to be upregulatedin GC tissues, while the expression of miR-378 was decreased. Moreover, we found a significant association between expression levels of miR-21, miR-106b, miR-17, miR-18a and miR-20a and clinicopathological features of GC. These miRNAs may be used for diagnostic and/or prognostic biomarkers for GC and therefore warrant further investigation.
A Novel Method of Automatic Plant Species Identification Using Sparse Representation of Leaf Tooth Features

Automatic species identification has many advantages over traditional species identification. Currently, most plant automatic identification methods focus on the features of leaf shape, venation and texture, which are promising for the identification of some plant species. However, leaf tooth, a feature commonly used in traditional species identification, is ignored. In this paper, a novel automatic species identification method using sparse representation of leaf tooth features is proposed. In this method, image corners are detected first, and the abnormal image corner is removed by the PauTa criteria. Next, the top and bottom leaf tooth edges are discriminated to effectively correspond to the extracted image corners; then, four leaf tooth features (Leaf-num, Leaf-rate, Leaf-sharpness and Leaf-obliqueness) are extracted and concatenated into a feature vector. Finally, a sparse representation-based classifier is used to identify a plant species sample. Tests on a real-world leaf image dataset show that our proposed method is feasible for species identification.
Improving Mycobacterium bovis Bacillus Calmette-Guèrin as a Vaccine Delivery Vector for Viral Antigens by Incorporation of Glycolipid Activators of NKT Cells

Recombinant Mycobacterium bovis bacillus Calmette-Guèrin (rBCG) has been explored as a vector for vaccines against HIV because of its ability to induce long lasting humoral and cell mediated immune responses. To maximize the potential for rBCG vaccines to induce effective immunity against HIV, various strategies are being employed to improve its ability to prime CD8+ T cells, which play an important role in the control of HIV infections. In this study we adopted a previously described approach of incorporating glycolipids that activate CD1d-restricted natural killer T (NKT) cells to enhance priming of CD8+ T cells by rBCG strains expressing an SIV Gag antigen (rBCG-SIV gag). We found that the incorporation of the synthetic NKT activating glycolipid α-galactosylceramide (α-GC) into rBCG-SIV gag significantly enhanced CD8+ T cell responses against an immunodominant Gag epitope, compared to responses primed by unmodified rBCG-SIV gag. The abilities of structural analogues of α-GC to enhance CD8+ T cell responses to rBCG were compared in both wild type and partially humanized mice that express human CD1d molecules in place of mouse CD1d. These studies identified an α-GC analogue known as 7DW8-5, which has previously been used successfully as an adjuvant in non-human primates, as a promising compound for enhancing immunogenicity of antigens delivered by rBCG.vectors. Our findings support the incorporation of synthetic glycolipid activators of NKT cells as a novel approach to enhance the immunogenicity of rBCG-vectored antigens for induction of CD8+ T cell responses. The glycolipid adjuvant 7DW8-5 may be a promising candidate for advancing to non-human primate and human clinical studies for the development of HIV vaccines based on rBCG vectors.
Microtubule depolymerization promotes particle and chromosome movement in vitro

We have developed a system for studying the motions of cellular objects attached to depolymerizing microtubules in vitro. Radial arrays of microtubules were grown from lysed and extracted Tetrahymena cells attached to a glass coverslip that formed the top of a light microscope perfusion chamber. A preparation of chromosomes, which also contained vesicles, was then perfused into the chamber and allowed to bind to the microtubule array. The concentration of tubulin was then reduced by perfusing buffer that lacked both tubulin and nucleotide triphosphates, and the resulting microtubule depolymerization was observed by light microscopy. A fraction of the bound objects detached in the flow and washed away, while others stabilized the microtubules to which they were bound. Some of the particles and chromosomes, however, moved in toward the Tetrahymena ghost as their associated microtubules shortened. The mean speeds for particles and chromosomes were 26 +/- 20 and 15 +/- 12 microns/min, respectively. These motions occurred when nucleotide triphosphate levels were very low, as a result of either dilution or by the action of apyrase. Furthermore, the motions were unaffected by 100 microM sodium orthovanadate, suggesting that these forces are not the result of ATP hydrolysis by a minus end-directed mechanoenzyme. We conclude that microtubule depolymerization provided the free energy for the motions observed. All the objects that we studied in detail moved against a stream of buffer flowing at approximately 100 microns/s, so that the force being developed was at least 10(-7) dynes. This force is large enough to contribute to some forms of motility in living cells.
Improving Uniformity of Cache Access Pattern using Split Data Caches

In this paper we show that partitioning data cache into array and scalar caches can improve cache access pattern without having to remap data, while maintaining the constant access time of a direct-mapped cache and improving the performance of L-1 cache memories. By using 4 central moments (mean, standard-deviation, skewness and kurtosis) we report on the frequency of accesses to cache sets and show that split data caches significantly mitigate the problem of non-uniform accesses to cache sets for several embedded benchmarks (from MiBench) and some SPEC benchmarks.
A computationally efficient algorithm for state-to-state quadrocopter trajectory generation and feasibility verification

An algorithm is proposed allowing for the rapid generation and evaluation of quadrocopter state interception trajectories. These trajectories are from arbitrary initial states to final states defined by the vehicle position, velocity and acceleration with a specified end of time. Sufficient criteria are then derived allowing trajectories to be tested for feasibility with respect to thrust and body rates. It is also shown that the range of a linear combination of the vehicle state can be solved for in closed form, useful e.g. for testing that the position remains within a box. The algorithm is applied by revisiting the problem of finding a trajectory to hit a ball towards a target with a racket attached to a quadrocopter. The trajectory generator is used in a model predictive control like strategy, where thousands of trajectories are generated and evaluated at every controller update step, with the first input of the optimal trajectory being sent to the vehicle. It is shown that the method can generate and evaluate on the order of one million trajectories per second on a standard laptop computer.
Acoustic Features for Pig Wasting Disease Detection

Failure to detect pig wasting disease in a timely and accurate manner can become a limiting factor in achieving efficient reproductive performance. In this paper, we discuss the methodology and results of a study we conducted to analyze for acoustic features for pig wasting disease and to use pattern recognition to examine the differences of the sounds pigs make when affected with pig wasting disease compared to normal sounds. The proposed acoustic feature subset selection algorithm indicated that {F7, RMS, Max Pitch, PSD1, Peak frequency} is the optimal feature subset that can be used to detect pig wasting disease. Finally, the results of the performance evaluation conducted using real sound data from an audio surveillance system showed that the average detection accuracy approached 98.4%, with FPR and FNR reaching on average 0.2% and 1.6%, respectively, when a support vector machine algorithm was used for detection. Moreover, we empirically confirmed that the performance of the optimal acoustic feature subset does not depend on the specific detector used.
High Performance Polymer Thermoelectric Composite Achieved by Carbon-Coated Carbon Nanotubes Network

Poly(3,4-ethylenedioxythiophene)poly(styrenesulfonate)/carbon nanotube (PEDOT:PSS/CNTs) composite films have been demonstrated to offer an excellent thermoelectric performance. In this work, p-type thermoelectric films prepared by a simple dipping coating process based on the carbon-coated carbon nanotubes (C-CNTs) continuous network are investigated. The highest power factor obtained in this work is 504.8 μW/mK2 (at 300 K) due to the relatively high electrical conductivity and Seebeck coefficient. The excellent TE properties of the C-CNTs/PEDOT:PSS composite film are attributed to the interfacial carrier scattering introduced by the unique structure. Composite materials based on a continuous network would open up new opportunities to develop high performance organic thermoelectric materials.
Unity-Rate Codes Maximize the Normalized Throughput of ON–OFF Keying Visible Light Communication

In this letter, we aim for maximizing the throughput of a visible light communication (VLC) system. Explicitly, we conceive a soft-in soft-out decoder providing soft feedback for the classic run length limited (RLL) codes, hence facilitating iterative decoding for exchanging valuable extrinsic information between the RLL and the error correction modules of a VLC system. Furthermore, we propose a unity rate code for our VLC system, which, hence, becomes capable of matching the ON–OFF keying capacity, while maintaining a flicker-free dimming value of 50%.
Correlation Clustering for Crosslingual Link Detection

The crosslingual link detection problem calls for identifying news articles in multiple languages that report on the same news event. This paper presents a novel approach based on constrained clustering. We discuss a general way for constrained clustering using a recent, graph-based clustering framework called correlation clustering. We introduce a correlation clustering implementation that features linear program chunking to allow processing larger datasets. We show how to apply the correlation clustering algorithm to the crosslingual link detection problem and present experimental results that show correlation clustering improves upon the hierarchical clustering approaches commonly used in link detection, and, hierarchical clustering approaches that take constraints into account.
Successful conversion of patients with hypercholesterolemia from a brand name to a generic cholesterol-lowering drug.

OBJECTIVE To evaluate the safety and effectiveness of a simvastatin-to-lovastatin therapeutic conversion program. STUDY DESIGN Observational database study of a therapeutic conversion in members of the Northern and Southern California regions of Kaiser Permanente, using a pretest/posttest design. METHODS All patients actively converted from simvastatin to lovastatin between April 1, 2002, and March 31, 2003, were identified for inclusion in the analysis. The conversion from simvastatin to lovastatin was based on an equipotent dose ratio of 1 mg of simvastatin to 2 mg of lovastatin. Electronic prescription record and laboratory data were collected for converted patients beginning 365 days before changing therapy through June 30, 2003. The primary effectiveness end point was a comparison of the preconversion and postconversion low-density lipoprotein cholesterol (LDL-C) levels. Safety end points included an analysis of preconversion and postconversion alanine aminotransferase (ALT) tests and creatine kinase values. RESULTS A total of 33,318 converted patients met criteria for inclusion in the analysis. The mean LDL-C was lowered from 110.9 to 108.4 mg/dL (P < .001) following the conversion to lovastatin. The percentage of patients with serum ALT levels greater than 3 times the upper limit of normal (ULN) was similar before (0.7%) and after (0.6%) conversion from simvastatin to lovastatin. Creatine kinase elevations greater then 10 times the ULN occurred at similar rates before and after the conversion. CONCLUSIONS Overall, patients had an improvement in their lipid profile without evidence of hepatic or muscle enzyme elevations. Appropriately selected patients can be safely and effectively converted from simvastatin to lovastatin.
Traffic-Aware Base Station Sleeping Control and Power Matching for Energy-Delay Tradeoffs in Green Cellular Networks

In this paper, traffic-aware sleeping control (SC) and power matching (PM) of a single base station (BS) in cellular networks are studied. The objective is to find the sleeping control and power matching configurations that achieve the Pareto optimal tradeoff between total power consumption and average delay. Two types of sleeping control schemes are considered: The BS goes to sleep whenever there is no active user, and wakes up when N users are assembled or after a period of multiple or single vacation time. We first discuss when to incorporate sleeping control into power matching energy efficiently. The explicit relationship between total power consumption and average delay with varying service rate is analyzed theoretically, indicating that sacrificing delay cannot always be traded for energy saving, and we also provide conditions under which the energy-optimal rate exists. Moreover, the optimal pair of sleeping parameter and service rate to achieve the optimal energy-delay tradeoff, and the energy consumption lower bound are also derived. Both the analytical and simulation results show that tolerable sacrifice of delay performance can be traded for substantial amount of energy saving given that careful designs were made according to our analysis.
Profile-based detection of microRNA precursors in animal genomes

MOTIVATION MicroRNAs (miRNA) are essential 21-22 nt regulatory RNAs produced from larger hairpin-like precursors. Local sequence alignment tools such as BLAST are able to identify new members of known miRNA families, but not all of them. We set out to estimate how many new miRNAs could be recovered using a profile-based strategy such as that implemented in the ERPIN program. RESULTS We constructed alignments for 18 miRNA families and performed ERPIN searches on animal genomes. Results were compared to those of a WU-BLAST search at the same E-value cutoff. The two combined approaches produced 265 new miRNA candidates that were not found in miRNA databases. About 17% of hits were ERPIN specific. They showed better structural characteristics than BLAST-specific hits and included interesting candidates such as members of the miR-17 cluster in Tetraodon. Profile-based RNA detection will be an important complement of similarity search programs in the completion of miRNA collections.
Shareholder Protection in the USA and Germany - “Law and Finance” Revisited

Though Company Laws of the United States and Germany have much in common, they are opposite in many important ways. While the Anglo-Saxon Law derives from Common Law, German Law has its origin in the Civil Law. La Porta et al. are not the only ones highlighting that the quality of shareholder protection varies across different jurisdictions depending on which legal system family the jurisdiction belongs. Pistor and Siems went a step further, highlighting that variations in market systems are explainable by more fundamental factors than law, like differences in the underlying ground rules.
MACAON An NLP Tool Suite for Processing Word Lattices

MACAON is a tool suite for standard NLP tasks developed for French. MACAON has been designed to process both human-produced text and highly ambiguous word-lattices produced by NLP tools. MACAON is made of several native modules for common tasks such as a tokenization, a part-of-speech tagging or syntactic parsing, all communicating with each other through XML files. In addition, exchange protocols with external tools are easily definable. MACAON is a fast, modular and open tool, distributed under GNU Public License.
On the Nature and the Stability of the Canadian Phillips Curve

This paper empirically determines why, during the 1990s, inflation in Canada was consistently more stable than predicted by the fixed-coefficients Phillips curve. A time-varying-coefficient model, where all the parameters adjust simultaneously, shows that the behaviour of expectations was probably a major contributing factor. A decrease in the value of the coefficient on the first difference of the output gap also seems to have influenced the observed pattern of inflation. Finally, pass-through of relative price shocks into domestic prices is shown to have been low since 1983.
A Novel High-Speed and High-Accuracy Manipulator of Planar Five-Link Structure: Modeling and Calibration

This paper describes a novel manipulator of planar five-link structure, which is designed to be characterized as high speed and high accuracy. The manipulator's mathematic models are built for purposes of analysis and control. Due to the lack of high-accuracy angular measurement equipment during manufacturing, the exact initial joint positions of the manipulator are unknown. An extended Kalman filter-based calibration algorithm is proposed to estimate those initial angles and a laser interferometer is adopted as the measurement equipment. To satisfy the high-speed requirement, a new Cartesian trajectory which combines the trapezoidal and S-shape trajectories is proposed. The testing results show that the requirements with respect to velocity, acceleration and accuracy are successfully achieved. Finally, an application example is given to demonstrate its potential uses.
Modulation of the Antidepressant-Like Effects of Sustained Administration of Carisbamate and Lamotrigine on Monoaminergic Systems: Electrophysiological Studies in the Rat Brain

Carisbamate and lamotrigine are anticonvulsants that act on neuronal voltage-gated sodium channels. Carisbamate has shown antidepressant-like effects in animal models of depression, and lamotrigine is a mood stabilizer with a therapeutic effect in depressive episodes of patients with bipolar disorder. This study examined the effects of carisbamate and lamotrigine on monoaminergic transmission in rodents, which could contribute to their antidepressant action. In vivo electrophysiological recordings were carried out in rats after 2 and 14 days administration of vehicle, carisbamate (60 mg/kg daily), or lamotrigine (25 mg/kg daily). Overall firing activity of the dorsal raphe nucleus (DRN) serotonin (5-HT), locus coeruleus norepinephrine, and ventral tegmental area dopamine (DA) neurons was decreased with carisbamate. Lamotrigine also decreased 5-HT neuronal firing, and this effect was abolished by lesion of the prefrontal cortex. Despite these decreases in firing activity after their prolonged administration, both anticonvulsants exhibited a significant increase in tonic activation of hippocampus 5-HT1A receptors, as shown by a disinhibition of the firing activity of pyramidal neurons in response to the selective antagonist WAY-100635 (N-{2-[4(2-methoxyphenyl)-1-piperazinyl] ethyl}-N-(2-pyridinyl) cyclohexanecarboxamide trihydrochloride). This finding reveals an increase in the 5-HT level that may be attributed to a desensitization of the terminal 5-HT1B autoreceptors. This study demonstrates that sustained carisbamate and lamotrigine administration decreases 5-HT firing in the DRN but nevertheless enhances 5-HT transmission in the forebrain. This serotonergic effect may be associated with an antiglutamatergic action and may contribute to the antidepressant-like effect of carisbamate in the forced swim test and the antidepressant properties of lamotrigine.
Numerical simulation of behavior of red blood cells and cancer cells in complex geometrical domains

Investigation of the motion of deformable particles immersed in fluid is clinically very relevant because it can help to improve treatment planning, diagnostics of disease, design of efficient terapeutical procedures, analysis of drug transport, etc. Experimental investigation of these phenomena is difficult and expensive and, therefore, numerical simulations can contribute to the acquisition of a lot of new and useful information. In this paper, a numerical model that simulates solid-fluid interaction is presented and used to simulate the motion of red blood cells and spherical particles through a fluid domain. A comparison with experimental results and other results presented in literature is performed. The good accuracy of the model demonstrates that this method has a great potential for simulating phenomena happening within complex geometric domains, such as microfluidic chips for cancer cell separation.