Miracle-dz/UniFAR-FTUs huggingface dataset:
A simple load flow method for radial distribution system

The radial network is the one which passes through the network without any connection to other supply. It is used for isolated loads like rural areas. Different forward-backward sweep algorithms exist for the load flow analysis of radial distribution systems. A new method of load flow analysis for radial distribution system is explained in this paper. This method is worked out by considering voltage independent loads and voltage dependency loads. The voltage profile results of the proposed method are compared with ratio flow method. Adequate simulations are performed by using Matlab.
Dependency Parsing with Lattice Structures for Resource-Poor Languages

In this paper, we present a new dependency parsing method for languages which have very small annotated corpus and for which methods of segmentation and morphological analysis producing a unique (automatically disambiguated) result are very unreliable. Our method works on a morphosyntactic lattice factorizing all possible segmentation and part-of-speech tagging results. The quality of the input to syntactic analysis is hence much better than that of an unreliable unique sequence of lemmatized and tagged words. We propose an adaptation of Eisner's algorithm for finding the k-best dependency trees in a morphosyntactic lattice structure encoding multiple results of morphosyntactic analysis. Moreover, we present how to use Dependency Insertion Grammar in order to adjust the scores and filter out invalid trees, the use of language model to rescore the parse trees and the k-best extension of our parsing model. The highest parsing accuracy reported in this paper is 74.32% which represents a 6.31% improvement compared to the model taking the input from the unreliable morphosyntactic analysis tools.
Antibody-modified liposomes for cancer chemotherapy

Background: Liposomes, phospholipids, nanosized bubbles with a bilayered membrane structure, have drawn a lot of interest as pharmaceutical carriers for drugs and genes. In particular, liposomes are widely used for drug delivery into tumors. Objective: In many cases, to enhance the efficacy of the liposomal drugs, drug-loaded liposomes are targeted to the tumors by means of different specific ligands, such as monoclonal antibodies. Thus, this review analyzes the application of antibody-targeted liposomes loaded with various chemotherapeutic agents and various liposomal products under development at experimental and preclinical level. Methods: The papers published on the subject of cancer-targeted liposomes mainly over the last 10 – 15 years are discussed. Conclusion: Antibody-targeted liposomes loaded with anticancer drugs demonstrate high potential for clinical applications.
Efficacy and safety of denosumab and teriparatide treatment for osteoporosis : a systematic review and meta-analysis

Purpose: It may be promising to combine denosumab with teriparatide for the treatment of osteoporosis. However, the results remain controversial. We conduct a systematic review and meta-analysis to evaluate the efficacy and safety of combination treatment (denosumab and teriparatide) versus teriparatide treatment in patients with osteoporosis. Methods: Medline, SCOPUS, Google Scholar, EMBASE, Springer, and Science Direct are searched electronically. Randomized controlled trials (RCTs) or controlled clinical trials (CCTs) regarding the combination treatment versus teriparatide treatment for osteoporosis are included. Two investigators independently search articles, extracted data, and assess the quality of included studies. The primary outcome is the increase in spine bone mineral density (BMD) and hip BMD. Meta-analysis is performed using the fixed-effect model or random-effect model when appropriate. Results: Four studies are included in this meta-analysis. Overall, compared with teriparatide treatment, combination treatment of denosumab and teriparatide significantly increases hip BMD (mean difference = 3.59%; 95% CI = 2.23% to 4.95%; P<0.00001), femoral neck BMD (mean difference = 3.29%; 95% CI = 2.08% to 4.50%; P<0.00001) and radius BMD (mean difference = 3.35%; 95% CI = 2.59% to 4.11%; P<0.00001), but fails to increase spine BMD (mean difference = 1.65%; 95% CI = -1.27% to 4.56%; P = 0.27). Conclusion: Our meta-analysis suggests that combination treatment of denosumab and teriparatide shows an important ability to increase the BMD in patients with osteoporosis. Combination treatment should be recommended to treat osteoporosis, but with caution due to clinical heterogeneity.
Auditory thalamocortical projections in the cat: Laminar and areal patterns of input

Thalamocortical projections were studied in adult cats using biotinylated dextran amines, wheat germ agglutinin conjugated to horseradish peroxidase, and autoradiography with tritiated leucine and/or proline. The input from 7 architectonically defined nuclei to 14 auditory cortical fields was characterized qualitatively and quantitatively. The principal results were that 1) every thalamic nucleus projected to more than 1 field (range, 4–14 fields; mean, 7 fields); 2) only the projection from the ventral division to some primary fields (primary auditory cortex and posterior auditory cortex) had a periodic, clustered distribution, whereas the input from other divisions to nonprimary areas was continuous; 3) layers III–V received >85% of the total axonal profiles; 4) in most experiments, five or more layers were labeled; 5) the projections to nonprimary auditory areas had many laterally oriented axons; 6) the heaviest input to layer I in all experiments was usually in its upper half, suggesting a sublaminar arrangement; 7) the largest axonal trunks (up to 6 μm in diameter) arose from the medial division and ended in layer Ia, where they ran laterally for long distances; 8) there were three projection patterns: type 1 had its peak in layers III–IV with little input to layer I, and it arose from the ventral division and the dorsal superficial, dorsal, and suprageniculate nuclei of the dorsal division; type 2 had heavy labeling in layer I and less in layers III–IV, arising from the dorsal division nuclei primarily, especially the caudal dorsal and deep dorsal nuclei; and type 3 was a trimodal concentration in layers I, III–IV, and VI that originated chiefly in the medial division and had the lowest density of labeling; and 9) the quantitative profiles with the three methods were very similar. The results suggest that the subdivisions of the auditory thalamus have consistent patterns of laminar distribution to different cortical areas, that an average of five or more layers receive significant input in a specific area, that a given thalamic nucleus can influence areas as far as 20 mm apart, that the first information to arrive at the cortex may reach layer I by virtue of the giant axons, and that several laminar patterns of auditory thalamocortical projection exist. The view that the auditory thalamus (and perhaps other thalamic nuclei) serves mainly a relay function underestimates its many modes for influencing the cortex on a laminar basis. J. Comp. Neurol. 427:302–331, 2000. © 2000 Wiley‐Liss, Inc.
Self-Similarity and Attraction in Stochastic Nonlinear Reaction-Diffusion Systems

Self-similarity solutions play an important role in many fields of science. We explore self-similarity in some stochastic partial differential equations (spdes). Important issues are not only the existence of stochastic self-similarity but also whether a self-similar solution is dynamically attractive, and if it is, to what particular solution does the system evolve. By recasting a class of spdes in a form to which stochastic center manifold theory may be applied, we resolve these issues in this class. For definiteness, a first example of self-similarity in solutions of Burgers equation driven by some stochastic force is studied. Under suitable assumptions a stationary solution is constructed which yields the existence of a stochastically self-similar solution for the stochastic Burgers equation. Further, the asymptotic convergence to the self-similar solution is proved. Second, in more general stochastic reaction-diffusion systems, stochastic center manifold theory provides a framework for constructing s.
Kinematics and metallicities of globular clusters in M104

We have obtained spectra for globular cluster candidates in M104 with LDSS-2 on the William Herschel Telescope, confirming 34 objects as M104 globular clusters. We find a cluster velocity dispersion of � 260 km/sec, and the Projected Mass Estimator gives a mass of 5.0 (3.5,6.7) × 10 11 M⊙ for M104 within a projected radius of � 330 ′′ (14 kpc for D=8.55 Mpc). Our best estimate for the mass-to-light ratio is M/LVT = 16 +5.5 −5.0 within the same radius. Considering all of the possible sources of uncertainty, we find a lower limit of M/LV = 5.3, which is larger than the M/LV found from rotation curve analyses inside 180 ′′ . We thus conclude that the mass-to-light ratio increases with radius, or in other words that M104 possesses a dark matter halo. There is a marginal detection of rotation in the M104 cluster system at the 92.5% confidence level; larger samples will be needed to investigate this possibility. Interestingly, the M104 globular cluster and planetary nebulae (PNe) kinematics are roughly consistent inside � 100 ′′ . Finally, we find a mean cluster metallicity of [Fe/H] = 0.70 ± 0.3, which is more typical of clusters in gE/cD galaxies than it is of clusters in other spirals.
Isolation and phylogenic identification of soil haloalkaliphilic strains in the former Texcoco Lake

A wide diversity of organisms exists in soil. Well-adapted groups can be found in extreme environments. A great economic and metabolic potential for extremozymes produced by organisms living at extreme environments has been reported. Extreme characteristics such as high salt content and high pH level make the soil of the former Texcoco Lake a unique place which has not been exploited. Therefore, in this study, 66 strains from soil of the former Texcoco Lake were isolated and phylogenetically analyzed using universal oligonucleotide primers. Different genera such as Kocuria, Micrococcus, Nesterenkonia, Halomonas, Salinicoccus, Kurthia, Gracilibacillus, and Bacillus were found. However, only 22 from all isolated strains were identified at specie level.
DNA supercoiling factor contributes to dosage compensation in Drosophila

DNA supercoiling factor (SCF) is a protein capable of generating negative supercoils in DNA in conjunction with topoisomerase II. To clarify the biological functions of SCF, we introduced a heritable SCF RNAi into Drosophila. Upon knockdown of SCF, we observed male lethality and male-specific reduction in the expression levels of X-linked genes. SCF functionally interacts with components of the MSL complex, which are required for dosage compensation via hypertranscription of the male X chromosome. Moreover, SCF colocalizes with the MSL complex along the male X chromosome. Upon overexpression of SCF, the male X chromosome had a bloated appearance. This phenotype was dependent on the histone acetyltransferase MOF and was suppressed by simultaneous overexpression of ISWI. These findings demonstrate that SCF plays a role in transcriptional activation via alteration of chromatin structure and provide evidence that SCF contributes to dosage compensation.
HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data

MOTIVATION Cancer cells are often characterized by epigenetic changes, which include aberrant histone modifications. In particular, local or regional epigenetic silencing is a common mechanism in cancer for silencing expression of tumor suppressor genes. Though several tools have been created to enable detection of histone marks in ChIP-seq data from normal samples, it is unclear whether these tools can be efficiently applied to ChIP-seq data generated from cancer samples. Indeed, cancer genomes are often characterized by frequent copy number alterations: gains and losses of large regions of chromosomal material. Copy number alterations may create a substantial statistical bias in the evaluation of histone mark signal enrichment and result in underdetection of the signal in the regions of loss and overdetection of the signal in the regions of gain. RESULTS We present HMCan (Histone modifications in cancer), a tool specially designed to analyze histone modification ChIP-seq data produced from cancer genomes. HMCan corrects for the GC-content and copy number bias and then applies Hidden Markov Models to detect the signal from the corrected data. On simulated data, HMCan outperformed several commonly used tools developed to analyze histone modification data produced from genomes without copy number alterations. HMCan also showed superior results on a ChIP-seq dataset generated for the repressive histone mark H3K27me3 in a bladder cancer cell line. HMCan predictions matched well with experimental data (qPCR validated regions) and included, for example, the previously detected H3K27me3 mark in the promoter of the DLEC1 gene, missed by other tools we tested.
Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments

EXP3 is a popular algorithm for adversarial multiarmed bandits, suggested and analyzed in this setting by Auer et al. [2002b]. Recently there was an increased interest in the performance of this algorithm in the stochastic setting, due to its new applications to stochastic multiarmed bandits with side information [Seldin et al., 2011] and to multiarmed bandits in the mixed stochastic-adversarial setting [Bubeck and Slivkins, 2012]. We present an empirical evaluation and improved analysis of the performance of the EXP3 algorithm in the stochastic setting, as well as a modification of the EXP3 algorithm capable of achieving “logarithmic” regret in stochastic environments.
Evolutionary Ensembles : Combining Learning Agents using Genetic Algorithms

Ensembles of classifiers are often used to achieve accuracy greater than any single classifier. The predictions of these classifiers are typically combined together by uniform or weighted voting. In this paper, we approach the ensembles construction under a multi-agent framework. Each individual agent is capable of learning from data, and the agents can either be homogenous (same learning algorithm) or heterogeneous (different learning algorithm). These learning agents are combined by a meta-agent that utilizes evolutionary algorithm, using the accuracy as fitness score, for discovering the weights for each individual agent. The weights are indicative the best searched combination (or collaboration) of the set of agents. Experimental results show that this approach is a valid model for ensemble building when compared to the best individual agent and a simple plurality vote of the agents.
Comparative De Novo Transcriptome Analysis of Fertilized Ovules in Xanthoceras sorbifolium Uncovered a Pool of Genes Expressed Specifically or Preferentially in the Selfed Ovule That Are Potentially Involved in Late-Acting Self-Incompatibility

Xanthoceras sorbifolium, a tree species endemic to northern China, has high oil content in its seeds and is recognized as an important biodiesel crop. The plant is characterized by late-acting self-incompatibility (LSI). LSI was found to occur in many angiosperm species and plays an important role in reducing inbreeding and its harmful effects, as do gametophytic self-incompatibility (GSI) and sporophytic self-incompatibility (SSI). Molecular mechanisms of conventional GSI and SSI have been well characterized in several families, but no effort has been made to identify the genes involved in the LSI process. The present studies indicated that there were no significant differences in structural and histological features between the self- and cross-pollinated ovules during the early stages of ovule development until 5 days after pollination (DAP). This suggests that 5 DAP is likely to be a turning point for the development of the selfed ovules. Comparative de novo transcriptome analysis of the selfed and crossed ovules at 5 DAP identified 274 genes expressed specifically or preferentially in the selfed ovules. These genes contained a significant proportion of genes predicted to function in the biosynthesis of secondary metabolites, consistent with our histological observations in the fertilized ovules. The genes encoding signal transduction-related components, such as protein kinases and protein phosphatases, are overrepresented in the selfed ovules. X. sorbifolium selfed ovules also specifically or preferentially express many unique transcription factor (TF) genes that could potentially be involved in the novel mechanisms of LSI. We also identified 42 genes significantly up-regulated in the crossed ovules compared to the selfed ovules. The expression of all 16 genes selected from the RNA-seq data was validated using PCR in the selfed and crossed ovules. This study represents the first genome-wide identification of genes expressed in the fertilized ovules of an LSI species. The availability of a pool of specifically or preferentially expressed genes from selfed ovules for X. sorbifolium will be a valuable resource for future genetic analyses of candidate genes involved in the LSI response.
Utilizing the infrastructure to assist autonomous vehicles in a mobility on demand context

In this paper we describe an autonomous vehicle that aims at providing shared transportation services in a mobility on demand context. As the service is limited to a known urban environment, prior knowledge of the environment can be exploited, as well as existing infrastructure sensors such as security cameras. We argue that utilizing infrastructure sensors yields greater safety of operation and allows reduction in the number of sensors required on-board, hereby reducing the cost of the vehicle. We describe the role that infrastructure sensors can play and show the resulting improved performances of the system, supported by simulation and field experiment results.
A Dependency Based Statistical Translation Model

We present a translation model based on dependency trees. The model adopts a tree-to-string approach and extends Phrase-Based translation (PBT) by using the dependency tree of the source sentence for selecting translation options and for reordering them. Decoding is done by translating each node in the tree and combining its translations with those of its head in alternative orders with respect to its siblings. Reordering of the siblings exploits a heuristic based on the syntactic information from the parse tree which is learned from the corpus. The decoder uses the same phrase tables produced by a PBT system for looking up translations of single words or of partial sub-trees. A mathematical model is presented and experimental results are discussed.
On the origin of errors: A fine-grained analysis of MT and PE errors and their relationship

In order to improve the symbiosis between machine translation (MT) system and post-editor, it is not enough to know that the output of one system is better than the output of another system. A fine-grained error analysis is needed to provide information on the type and location of errors occurring in MT and the corresponding errors occurring after post-editing (PE). This article reports on a fine-grained translation quality assessment approach which was applied to machine translated-texts and the post-edited versions of these texts, made by student post-editors. By linking each error to the corresponding source text-passage, it is possible to identify passages that were problematic in MT, but not after PE, or passages that were problematic even after PE. This method provides rich data on the origin and impact of errors, which can be used to improve post-editor training as well as machine translation systems. We present the results of a pilot experiment on the post-editing of newspaper articles and highlight the advantages of our approach.
A HDRI Camera Based on SLM

A high dynamic range image camera (HDRI) is a kind of camera which captures the HDRI image. HDRI means the image with high dynamic range, it can record the gray information of the object with much wider dynamic range. HDR image has great applications in many fields. The existing HDRI camera needs either the special image sensor or can capture the still object only. In this paper, a new kind of camera is proposed. In this camera, a space light modulator (SLM) is used to acquire images with different exposure, then a HDRI is made with these images. This camera can acquire dynamic image and it is cheap and easy to extend.
High-resolution ISAR imaging of maneuvering targets by means of the range instantaneous Doppler technique: modeling and performance analysis

Very high resolution inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is a complicated task. In fact, the conventional range Doppler (RD) ISAR technique does not work properly when target motions generate terms higher than the first order in the phase of the received signal relative to each scatterer. This effect typically happens when at least one of these situations occur: (1) very high resolution images are required; (2) the target maneuvers; and (3) the target undergoes significant angular motions (roll, pitch, and yaw). A novel ISAR technique, named range instantaneous Doppler (RID), has been proposed for the reconstruction of very high resolution images of maneuvering targets. In this paper, we analytically show that the RID technique works properly when high-resolution ISAR images are required of maneuvering and/or rolling, pitching, and yawing targets; we also quantify the performance improvement of the RID technique with respect to the RD technique. The problem is tackled from an analytical point of view. First, we define a new model of the ISAR received signal that is valid for maneuvering targets, then we derive and compare the analytical expression of the point spread function (PSF) for the two techniques. Furthermore, we perform a statistical analysis to evaluate the improvement of the RID technique versus the RD technique in terms of spatial resolution. Finally, we prove the effectiveness of the RID technique by simulating the imaging process for two different targets: (1) a ship that undergoes roll, pitch and yaw motions and (2) a fast maneuvering airplane.
Cost Minimization for Fading Channels With Energy Harvesting and Conventional Energy

In this paper, we investigate resource allocation strategies for a point-to-point wireless communications system with hybrid energy sources consisting of an energy harvester and a conventional energy source. In particular, as an incentive to promote the use of renewable energy, we assume that the renewable energy has a lower cost than the conventional energy. Then, by assuming that the non-causal information of the energy arrivals and the channel power gains are available, we minimize the total energy cost of such a system over N fading slots under a proposed outage constraint together with the energy harvesting constraints. The outage constraint requires a minimum fixed number of slots to be reliably decoded, and thus leads to a mixed-integer programming formulation for the optimization problem. This constraint is useful, for example, if an outer code is used to recover all the data bits. Optimal linear time algorithms are obtained for two extreme cases, i.e., the number of outage slot is 1 or N - 1. For the general case, a lower bound based on the linear programming relaxation, and two suboptimal algorithms are proposed. It is shown that the proposed suboptimal algorithms exhibit only a small gap from the lower bound. We then extend the proposed algorithms to the multi-cycle scenario in which the outage constraint is imposed for each cycle separately. Finally, we investigate the resource allocation strategies when only causal information on the energy arrivals and only channel statistics is available. It is shown that the greedy energy allocation is optimal for this scenario.