Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of the Pan-African Natural Product Library Identifies Ixoratannin A-2 and Boldine as Novel HIV-1 Inhibitors

The continued burden of HIV in resource-limited regions such as parts of sub-Saharan Africa, combined with adverse effects and potential risks of resistance to existing antiretroviral therapies, emphasize the need to identify new HIV inhibitors. Here we performed a virtual screen of molecules from the pan-African Natural Product Library, the largest collection of medicinal plant-derived pure compounds on the African continent. We identified eight molecules with structural similarity to reported interactors of Vpu, an HIV-1 accessory protein with reported ion channel activity. Using in vitro HIV-1 replication assays with a CD4+ T cell line and peripheral blood mononuclear cells, we confirmed antiviral activity and minimal cytotoxicity for two compounds, ixoratannin A-2 and boldine. Notably, ixoratannin A-2 retained inhibitory activity against recombinant HIV-1 strains encoding patient-derived mutations that confer resistance to protease, non-nucleoside reverse transcriptase, or integrase inhibitors. Moreover, ixoratannin A-2 was less effective at inhibiting replication of HIV-1 lacking Vpu, supporting this protein as a possible direct or indirect target. In contrast, boldine was less effective against a protease inhibitor-resistant HIV-1 strain. Both ixoratannin A-2 and boldine also inhibited in vitro replication of hepatitis C virus (HCV). However, BIT-225, a previously-reported Vpu inhibitor, demonstrated antiviral activity but also cytotoxicity in HIV-1 and HCV replication assays. Our work identifies pure compounds derived from African plants with potential novel activities against viruses that disproportionately afflict resource-limited regions of the world.
Field information links permafrost carbon to physical vulnerabilities of thawing

Deep soil profiles containing permafrost (Gelisols) were characterized for organic carbon (C) and total nitrogen (N) stocks to 3 m depths. Using the Community Climate System Model (CCSM4) we calculate cumulative distributions of active layer thickness (ALT) under current and future climates. The difference in cumulative ALT distributions over time was multiplied by C and N contents of soil horizons in Gelisol suborders to calculate newly thawed C and N. Thawing ranged from 147 PgC with 10 PgN by 2050 (representative concentration pathway RCP scenario 4.5) to 436 PgC with 29 PgN by 2100 (RCP 8.5). Organic horizons that thaw are vulnerable to combustion, and all horizon types are vulnerable to shifts in hydrology and decomposition. The rates and extent of such losses are unknown and can be further constrained by linking field and modelling approaches. These changes have the potential for strong additional loading to our atmosphere, water resources, and ecosystems.
Atherogenic Diet‐Induced Modification of the Subtraction Distribution of High Density Lipoproteins in Monkeys

High density lipoproteins (HDL) were isolated from the plasma of adult male African green monkeys fed control or atherogenic diets and were then subfractionated in a density gradient by centrifugation at 50,000 rpm, 20° C for 18 hours in the Beckman VTi50 vertical rotor. Material from the gradient was pooled into six subfractions for further analysis. With increasing density across the gradient, the subfractions had progressively decreasing flotation rates, molecular weights, apo A-l/apo A-ll mass ratios, lipid percentages of mass, and average sizes. Apoprotein content per particle was reasonably constant compared to lipid content. The physical and chemical properties of the HDL subfractions suggested that the gradient separated three subclasses of HDL equivalent to HDL2b, HDL2a, and HDL3 of human beings. When values among animals were compared, the atherogenic diet shifted the relationship between total plasma cholesterol concentration and total HDL concentration from a positive to a negative correlation. The subfractions most affected were those of d<1.10 g/ml (HDL2b), while the 1.10<d<1.13 g/ml (HDL2a) subfractions were affected to a lesser degree; the more responsive the animal to dietary cholesterol, the lower was the mass concentrations of these subfractions. This pattern suggested that diet-induced changes in HDL2 subfraction particle concentrations may be related to the development of atherosclerosis in African green monkeys; parallel changes in particle composition were not identified.
Answering Questions from Multiple Documents – the Role of Multi-Document Summarization

Ongoing research work on Question Answering using multi-document summarization has been described. It has two main sub modules, document retrieval and Multi-document Summarization. We first preprocess the documents and then index them using Nutch with NE field. Stop words are removed and NEs are tagged from each question and all remaining question words are stemmed and then retrieve the most relevant 10 documents. Now, document graph-based query focused multidocument summarizer is used where question words are used as query. A document graph is constructed, where the nodes are sentences of the documents and edge scores reflect the correlation measure between the nodes. The system clusters similar texts from the graph using this edge score. Each cluster gets a weight and has a cluster center. Next, question dependent weights are added to the corresponding cluster score. Top two-ranked sentences of each cluster is identified in order and compressed and then fused to a single sentence. The compressed and fused sentences are included into the output summary with a limit of 500 words, which is presented as answer. The system is tested on data set of INEX QA track from 2011 to 2013 and best readability score was achieved.
A BIAS-REDUCED LOG-PERIODOGRAM REGRESSION ESTIMATOR FOR THE LONG-MEMORY PARAMETER

The widely used log-periodogram regression estimator of the long-memory parameter d proposed by Geweke and Porter-Hudak (1983) (GPH) has been criticized because of its finite-sample bias, see Agiakloglou, Newbold, and Wohar (1993). In this paper, we propose a simple bias-reduced log-periodogram regression estimator, {d hat}r, that eliminates the first- and higher-order biases of the GPH estimator. The bias-reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k = 1,. ,r, for some positive integer r, as additional regressors in the pseudo-regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency, which is consistent with the semiparametric nature of the long-memory model under consideration. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean-squared error (MSE) of {d hat}r, determine the MSE optimal choice of the number of frequencies, m to include in the regression, and establish the asymptotic normality of {d hat}r. These results show that the bias of {d hat}r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. In consequence, the optimal rate of convergence to zero of the MSE of {d hat}dr is faster than that of the GPH estimator. We establish the optimal rate of convergence of a minimax risk criterion for estimators of d when the normalized spectral density is in a class that includes those that are smooth of order s > 1 at zero. We show that the bias-reduced estimator {d hat}r attains this rate when r > (s-2)/2 and m is chosen appropriately. For s > 2, the GPH estimator does not attain this rate. The proof of these results uses results of Giraitis, Robinson, and Samarov (1997). Some Monte Carlo simulation results for stationary Gaussian ARFIMA(1,d,1) models show that the bias-reduced estimators perform well relative to the standard log-periodogram estimator.
Hierarchical Modulation to Support Low-Density Parity-Check Code Design?

We study variable node degree distributions resulting from a linear programming approach for designing a lowdensity parity-check (LDPC) code optimized for an irregular modulation alphabet. We opt for an irregular LDPC code and make use of the irregularities of the channel in the sense of different modulation classes originating especially from different distances in a hierarchical modulation signal set. Our aim is to investigate if differences in equivalent binary channels as given by hierarchical modulation signal sets would in any way support resulting variable node degree distributions.
A clustering genetic algorithm for software modularisation with a multiple hill climbing approach

Software clustering is a useful technique for software comprehension and re-engineering. In this thesis we examine Software Module Clustering by Hill Climbing (HC) and Genetic Algorithms (GA). Our work primarily addresses graph partitioning using HC and GA. The software modules are represented as directed graphs and clustered using novel HC and GA search techniques. We use a fitness criterion to direct the search. The search consists of using multiple preliminary search to gather information about the search landscape, which is then converted to Building Blocks and used for subsequent search. This thesis includes the results of a series of empirical studies to use these novel HC and GA techniques. These results show this technique to be an effective way to improve Software Module Clustering. They also show that our GA reduces the need for user defined solution structure, which requires in depth understanding of the solutions landscape and it can also help improve efficiency. We also present work for automation of useful Building Block recognition and the results of an experiment which shows Building Blocks created in this way also help our GA search, making this an ideal opportunity for further investigation.
The genetic dissection of complex traits in a founder population.

We estimated broad heritabilities (H(2)) and narrow heritabilities (h(2)) and conducted genomewide screens, using a novel association-based mapping approach for 20 quantitative trait loci (QTLs) among the Hutterites, a founder population that practices a communal lifestyle. Heritability estimates ranged from.21 for diastolic blood pressure (DBP) to.99 for whole-blood serotonin levels. Using a multipoint method to detect association under a recessive model we found evidence of major QTLs for six traits: low-density lipoprotein (LDL), triglycerides, lipoprotein (a) (Lp[a]), systolic blood pressure (SBP), serum cortisol, and whole-blood serotonin. Second major QTLs for Lp(a) and for cortisol were identified using a single-point method to detect association under a general two-allele model. The heritabilities for these six traits ranged from.37 for triglycerides to.99 for serotonin, and three traits (LDL, SBP, and serotonin) had significant dominance variances (i.e., H(2) > h(2)). Surprisingly, there was little correlation between measures of heritability and the strength of association on a genomewide screen (P>.50), suggesting that heritability estimates per se do not identify phenotypes that are influenced by genes with major effects. The present study demonstrates the feasibility of genomewide association studies for QTL mapping. However, even in this young founder population that has extensive linkage disequilibrium, map densities <<5 cM may be required to detect all major QTLs.
Pre-Equalization for Pre-Rake MISO DS-UWB Systems

In this paper, we propose two novel pre-equalization schemes for multiple-input single-output (MISO) direct-sequence ultra-wideband (DS-UWB) systems with pre-Rake combining and symbol-by-symbol detection. The first pre-equalization filter (PEF) scheme employs one PEF per transmit antenna, whereas in the second, simplified PEF (S-PEF) scheme all transmit antennas share the same PEF. For both schemes, the optimum finite impulse response (FIR) and infinite impulse response (IIR) PEFs are calculated based on the minimum mean squared error (MMSE) criterion. Our approach is sufficiently general to include also complexity-reduced versions of pre-Rake combining that employ a limited number of Rake fingers. We show that under certain conditions the S-PEF scheme achieves the same performance as the more complex PEF scheme. Moreover, our simulation results show that the proposed PEF schemes achieve significant performance gains over pure pre-Rake combining without equalization, even if only short PEFs are employed.
Cytoskeleton-associated protein 5 and clathrin heavy chain binding regulates spindle assembly in mouse oocytes

Mammalian oocyte meiotic maturation is the precondition of early embryo development. Lots of microtubules (MT)-associated proteins participate in oocyte maturation process. Cytoskeleton-associated protein 5 (CKAP5) is a member of the XMAP215 family that regulates microtubule dynamics during mitosis. However, its role in meiosis has not been fully studied. Here, we investigated the function of CKAP5 in mouse oocyte meiotic maturation and early embryo development. Western blot showed that CKAP5 expression increased from GVBD, maintaining at high level at metaphase, and decreased after late 1-cell stage. Confocal microscopy showed there is no specific accumulation of CKAP5 at interphase (GV, PN or 2-cell stage). However, once cells enter into meiotic or mitotic division, CKAP5 was localized at the whole spindle apparatus. Treatment of oocytes with the tubulin-disturbing reagents nocodazole (induces MTs depolymerization) or taxol (prevents MTs depolymerization) did not affect CKAP5 expression but led to a rearrangement of CKAP5. Further, knock-down of CKAP5 resulted in a failure of first polar body extrusion, serious defects in spindle assembly, and failure of chromosome alignment. Loss of CKAP5 also decreased early embryo development potential. Furthermore, co-immunoprecipitation showed that CKAP5 bound to clathrin heavy chain 1 (CLTC). Taken together, our results demonstrate that CKAP5 is important in oocyte maturation and early embryo development, and CKAP5 might work together with CLTC in mouse oocyte maturation.
Recycled Error Bits: Energy-Efficient Architectural Support for Higher Precision Floating Point

In this work, we provide energy-efficient architectural support for floating point accuracy. Our goal is to provide accuracy that is far greater than that provided by the processor's hardware floating point unit (FPU). Specifically, for each floating point addition performed, we "recycle" that operation's error: the difference between the finite-precision result produced by the hardware and the result that would have been produced by an infinite-precision FPU. We make this error architecturally visible such that it can be used, if desired, by software. Experimental results on physical hardware show that software that exploits architecturally recycled error bits can achieve accuracy comparable to a 2B-bit FPU with performance and energy that are comparable to a B-bit FPU.
Gamma oscillations dynamically couple hippocampal CA3 and CA1 regions during memory task performance

The hippocampal formation is believed to be critical for the encoding, consolidation, and retrieval of episodic memories. Yet, how these processes are supported by the anatomically diverse hippocampal networks is still unknown. To examine this issue, we tested rats in a hippocampus-dependent delayed spatial alternation task on a modified T maze while simultaneously recording local field potentials from dendritic and somatic layers of the dentate gyrus, CA3, and CA1 regions by using high-density, 96-site silicon probes. Both the power and coherence of gamma oscillations exhibited layer-specific changes during task performance. Peak increases in the gamma power and coherence were found in the CA3–CA1 interface on the maze segment approaching the T junction, independent of motor aspects of task performance. These results show that hippocampal networks can be dynamically coupled by gamma oscillations according to specific behavioral demands. Based on these findings, we propose that gamma oscillations may serve as a physiological mechanism by which CA3 output can coordinate CA1 activity to support retrieval of hippocampus-dependent memories.
Toward Improved Communication in Laparoscopic Surgery: Accounting for Multiple Frames of Reference and Mental Rotations

This work is an examination of barriers to communication between the attending and assisting surgeons during laparoscopic surgery, where the same image of the surgical site is viewed from different vantage points with respect to the patient. Part of the problem lies with the multiple frames of reference each surgeon holds, and the mental rotations each must perform to construct a common frame of reference for communication and collaborative work. An experiment was conducted to demonstrate the effects of display-control incongruency on the performance of an aiming task in a simulated laparoscopic environment. Aiming performance was best when the camera was oriented at 0° perspective and worsened as the angle of deviation from 0° increased. Performance was affected to a greater degree by viewing perspectives from the left of the subject than viewing perspectives from the right. Results also suggest that when surgeons are facing each other, as is the case in many laparoscopic surgeries, one surgeon's performance will be worse than the other's. The mismatched display-control perspectives are compounded by ambiguous spatial references in verbal communication. From these findings, a case can be made for the importance of vocabulary that forces a common frame of reference during laparoscopic surgery.
Emotion-focused therapy for complex trauma

ABSTRACT This article describes emotion-focused therapy for complex trauma (EFTT). EFTT is an evidence-based, short-term treatment for childhood abuse and neglect that posits the therapeutic relationship and emotional processing of trauma material as key mechanisms of change. This paper outlines sources of disturbance and long-term effects of complex trauma. It reviews the theoretical framework on which EFTT is based, mechanisms of change and phases of treatment, as well as supporting research. Primary interventions are demonstrated using a case example from a published video of a single session.
Nash-peering: A new techno-economic framework for internet interconnections

The current framework of Internet interconnections, based on transit and settlement-free peering relations, has systemic problems that often cause peering disputes. Repeated high-profile incidents show that this unfortunate state of affairs stands in the way of better Internet performance, sometimes even leading to large-scale Internet outages. We propose a new techno-economic interconnection framework called Nash-Peering, which is based on the principles of Nash Bargaining in game theory and economics. Nash-Peering constitutes a radical departure from current interconnection practices, providing a broader and more economically efficient set of interdomain relations. In particular, the direction of payment is not determined by the direction of traffic or by rigid customer-provider relationships but based on which AS benefits more from the interconnection. We argue that Nash-Peering can address the root cause of various types of peering disputes.
A Two-Phase Approach to Data Allocation in Distributed Databases

In this paper, we propose a two-phase approach to the problem of optimal allocation of data objects (fragments) on a network in a distributed database system. In the rst phase, we perform fragment clustering 1 , in which we form groupings of fragments that tend to be accessed together. In the second phase, we use a \divide and con-quer" search technique to allocate clusters to the computing nodes (sites) in the network. We show, via complexity analysis, that the combined process of clustering and data allocation takes time that is polynomial with respect to the number of objects and sites. We also show, via experimental analysis, that our approach produces solutions that are close to optimal for a wide range of fragmentations, queries and network structures.
Automatic Identification of Stop Words in Chinese Text Classification

Text classification is an active research area in information retrieval and natural language processing. A fundamental tool in text classification is a list of 'stop' words(stop word list) that is used to identify frequent words that are unlikely to assist in classification and hence are deleted during pre-processing. Till now, many stop word lists have been developed for English language. However, there is no standard stop word list which has been constructed for Chinese text classification yet. In this paper, we give a refined definition for stop words in Chinese text classification from a perspective of statistical correlation, then propose an automatic approach to extracting the stop word list in text classification based on the weighted Chi-squared statistic on 2*p contingency table. We evaluate the stop word lists using accuracies obtained from text classification experiments in the real-world Chinese corpus. The results show that the proposed approach is effective. The stop word lists derived by the approach can speed up the calculation and increase the accuracy of classification at the same time.
Automatic rules extraction from medical texts

The majority of existing knowledge is encoded in unstructured texts and is not linked to formalized knowledge, like ontologies and rules. The potential solution to this problem is to acquire this knowledge through natural language processing (NLP) tools and text mining techniques. Prior work has focused on the automatic extraction of ontologies from texts, but the acquired knowledge is generally limited to simple hierarchies of terms. This paper presents a polyvalent framework for acquiring more complex relationships from texts and codes them in the form of rules. Our approach starts with existing domain knowledge represented as OWL ontology and SWRL "Semantic Web Rule Language" rules by applying NLP tools and text matching techniques to deduce different atoms as classes, properties etc. This is to capture the deductive knowledge in the form of new rules. We evaluate our approach thereafter by applying it on medical field more precisely Gynecology specialty, showing that this approach can generate automatically and accurately SWRL rules for the representation of more formal knowledge necessary for reasoning.
A real time visual SLAM for RGB-D cameras based on chamfer distance and occupancy grid

We present a feature based visual SLAM method that uses chamfer distance to estimate the camera motion from RGB-D images. The proposed method does not require any matching which is an expensive operation and always generates false matching that affects the estimated camera motion. Our approach registers the input image iteratively by minimizing the distance between the feature points and the occupancy grid using a distance map. We demonstrate with real experiments the capability of the method to build accurate 3D map of the environment with a hand-held camera. While the system was mainly developed to work with RGB-D camera, occupancy grid representation gives the method the ability to work with various types of sensors, we show the capacity of the system to construct accurate 2D maps using telemeter data. We also discuss the similarities between the proposed approach and the traditional ICP algorithm.