Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effective Use of the DSmT for Multi-Class Classification

The extension of the Dezert-Smarandache theory (DSmT) for the multi-class framework has a feasible computational complexity for various applications when the number of classes is limited or reduced typically two classes. In contrast, when the number of classes is large, the DSmT generates a high computational complexity. This paper proposes to investigate the effective use of the DSmT for multi-class classification in conjunction with the Support Vector Machines using the One-Against-All (OAA) implementation, which allows offering two advantages: firstly, it allows modeling the partial ignorance by including the complementary classes in the set of focal elements during the combination process and, secondly, it allows reducing drastically the number of focal elements using a supervised model by introducing exclusive constraints when classes are naturally and mutually exclusive. To illustrate the effective use of the DSmT for multi-class classification, two SVM-OAA implementations are combined according three steps: transformation of the SVM classifier outputs into posterior probabilities using a sigmoid technique of Platt, estimation of masses directly through the proposed model and combination of masses through the Proportional Conflict Redistribution (PCR6). To prove the effective use of the proposed framework, a case study is conducted on the handwritten digit recognition. Experimental results show that it is possible to reduce efficiently both the number of focal elements and the classification error rate.
Comparison of Traditional and Activity Theory Based Analysis Methods for Verbal Protocol Data

The think aloud method has been used in this research to generate data that reveals the thoughts of participants of a study while they are performing tasks. The pioneers of this method, Simon and Ericsson, have provided a method to analyze the data so as to obtain meaningful results. However, this analysis method is complicated and time consuming. Most researchers use some form of categorization to perform their analysis. Critical incidents were used to categorize the data gathered in the tests conducted as part of this research. This research proposed the use of tenets of Activity Theory while performing data analysis so that the cultural and environmental aspects that influence task performance are identified and addressed as part of the analysis. A data analysis template was created that directs the analyst to follow activity theory while performing the analysis. Sample data was gathered using the Think Aloud Method. The results obtained after analyzing this data using the proposed Activity Theory Based method were compared with those obtained when the same data was analyzed using a representative traditional method of analysis. The research included positive critical incidents, negative critical incidents and level of severity of negative critical incidents as the dependent measures. No significant differences were found between the two methods based on these dependent measures. Task type had a significant effect on the number of positive and negative critical incidents identified. iii ACKNOWLEDGEMENT I would like to take this opportunity to recognize and thank all the people who were instrumental in this research. I would like to thank my advisor Dr. Tonya Smith-Jackson. This work would not have been possible without her guidance, support and confidence in my abilities. I would like to thank my committee members Dr. Maury Nussbaum and Dr. Brian Kleiner for their help and input towards improving this work. I would like to thank all my friends from Blacksburg and San Diego who helped where they could and lastly I would like to thank my family for their love and support.
Optimal Primal-Dual Methods for a Class of Saddle Point Problems

We present a novel accelerated primal-dual (APD) method for solving a class of deterministic and stochastic saddle point problems (SPPs). The basic idea of this algorithm is to incorporate a multistep acceleration scheme into the primal-dual method without smoothing the objective function. For deterministic SPP, the APD method achieves the same optimal rate of convergence as Nesterov's smoothing technique. Our stochastic APD method exhibits an optimal rate of convergence for stochastic SPP not only in terms of its dependence on the number of the iteration, but also on a variety of problem parameters. To the best of our knowledge, this is the first time that such an optimal algorithm has been developed for stochastic SPP in the literature. Furthermore, for both deterministic and stochastic SPP, the developed APD algorithms can deal with the situation when the feasible region is unbounded, as long as a saddle point exists. In the unbounded case, we incorporate the modified termination criterion introduced b.
Binding of the Chemotaxis Response Regulator CheY to the Isolated, Intact Switch Complex of the Bacterial Flagellar Motor

In bacteria, the chemotactic signal is greatly amplified between the chemotaxis receptors and the flagellar motor. In Escherichia coli, part of this amplification occurs at the flagellar switch. However, it is not known whether the amplification results from cooperativity of CheY binding to the switch or from a post-binding step. To address this question, we purified the intact switch complex (constituting the switch proteins FliG, FliM, and FliN and the scaffolding protein FliF) in quantities sufficient for biochemical work and used it to investigate whether the binding of CheY to the switch complex is cooperative. As a negative control, we used complexes of switchless basal bodies, formed from the proteins FliF and FliG and similarly isolated. Using double-labeling centrifugation assays for binding, we found that CheY binds to the isolated, intact switch complex in a phosphorylation-dependent manner. We observed no significant phosphorylation-dependent binding to the negative control of the switchless basal body. The dissociation constant for the binding between the switch complex and phosphorylated CheY (CheY∼P) was 4.0 ± 1.1 μm, well in line with the published range of CheY∼P concentrations to which the flagellar motor is responsive. Furthermore, the binding was not cooperative (Hill coefficient ≈ 1). This lack of CheY∼P-switch complex binding cooperativity, taken together with earlier in vivo studies suggesting that the dependence of the rotational state of the motor on the fraction of occupied sites at the switch is sigmoidal and very steep (Bren, A., and Eisenbach, M. (2001) J. Mol. Biol. 312, 699–709), indicates that the chemotactic signal is amplified within the switch, subsequent to the CheY∼P binding.
Transient behavior of vertical grounding electrode under impulse current

This paper aims to study the transient behavior of vertical grounding electrode under impulse current and buried in homogeneous soil. We have interested to the variation of the grounding impedance as function of frequency as well as the evolution of the transient potential using Transmission Line Method (TLM) in domain time. Several current magnitudes and soil resistivities and permittivities have been considered. This study has been carried out incorporating or not the soil ionization phenomenon. The obtained results have been confronted to those found by other researcher using Hybrid Electromagnetic Method (HEM). A good accordance has been obtained. As main results, soil ionization generates a decrease of the transient potential. Such decease is accentuated for high current magnitudes and high soil resistivities.
Comparing Agents' Success against People in Security Domains

The interaction of people with autonomous agents has become increasingly prevalent. Some of these settings include security domains, where people can be characterized as uncooperative, hostile, manipulative, and tending to take advantage of the situation for their own needs. This makes it challenging to design proficient agents to interact with people in such environments. Evaluating the success of the agents automatically before evaluating them with people or deploying them could alleviate this challenge and result in better designed agents. In this paper we show how Peer Designed Agents (PDAs) -- computer agents developed by human subjects -- can be used as a method for evaluating autonomous agents in security domains. Such evaluation can reduce the effort and costs involved in evaluating autonomous agents interacting with people to validate their efficacy. Our experiments included more than 70 human subjects and 40 PDAs developed by students. The study provides empirical support that PDAs can be used to compare the proficiency of autonomous agents when matched with people in security domains.
E cient Parallel Data Mining for Association RulesJong

In this paper, we develop an algorithm, called PDM, to conduct parallel data mining for association rules. Consider a transaction as a collection of items, and a large item-set is a set of items such that the number of transactions containing it exceeds a pre-speciied threshold. PDM is so designed that the global set of large itemsets can be identi-ed eeciently and the amount of inter-node data exchange required is minimized. Speciically, with a given database partition, each processing node will collect (count) information on each itemset from its local database eeciently via a hashing method. The information discovered by each node is next shared with other nodes via some communication schemes. Then, PDM employs a technique, called clue-and-poll, to address the uncertainty due to the partial knowledge collected at each node by judiciously selecting a small fraction of the itemsets for the exchange of count information among nodes, thus reducing the communication cost. The global set of large itemsets can hence be determined based on the aggregate count of itemsets. It is experimentally shown that PDM not only attains very good parallelization eeciencies, but also provides robust performance for various input patterns.
Towards a clustering based data diffusion protocol in delay tolerant networks

In Delay Tolerant Networks (DTN), diffusion protocols can benefit from the users' mobility in order to reach some distant nodes. However, existing protocols like flooding present a rather high overhead because of redundant transmissions. The main contribution of this paper is to introduce a new diffusion protocol, called CBD (Clustering Based data Diffusion). Our solution provides to each node the possibility to adapt its diffusion strategy on-the-fly for a more efficient diffusion by evaluating its local density. We show through the use of a real measurements mobility that CBD brings an improvement in forwarding performances, in terms of delivery ratio, delay and the amount of generated messages.
ON THE ACCURACY OF TRANSMEMBRANE HELIX PREDICTION METHODS USING AN UPDATED BENCHMARK

The prediction of transmembrane (TM) helix and topology is an important field of bioinformatics owing to the difficulties in obtaining high-resolution structures of membrane proteins. Many methods have been developed and several evaluations have compared the performance of individual methods using benchmarks from various sources. We present an analysis of a popular evaluation method by Kernytsky and Rost, which is created using data sets from more than six years ago. Our analysis shows that the benchmark contains data that have substantial disagreements in comparison with the current annotations in SwissProt Release 54.1. Furthermore, the benchmark also contains issues such as annotations of low reliability, sequence redundancy, and presence of signal peptides. We perform updating and cleansing of the above issues in the benchmark, and evaluate eleven widely used methods, including SVMtop, a hierarchical classification method based on support vector machines (SVM). The results show that SVMtop is ranked highly among the top-performing methods for helix prediction, correctly predicting the location of helices for more than 80% of the updated benchmark. Given the discrepancies and noises in the original benchmark, it should be used with discretion for assessing the performance of TM helix predictions. The analysis also implies that there is an urgent need for creating a new benchmark for an accurate and objective comparison. The updated benchmark is available for public use at http://bio-cluster.iis. sinica.edu. tw/~bioapp/SVMtop/dataset.htm.
Dual band rectenna with one rectifier

In this paper, we propose a dual band rectenna for wireless energy harvesting. Nowadays, most of the mainstream wireless access points are designed for dual band usage which frequency is located at 2.4GHz and 5GHz. As a result, the proposed design is focused on these two frequency bands. In the proposed dual band rectenna, we utilize only one single feed point to achieve the dual band, where 2.4G band is generated by microstrip antenna and 5G band is generated by the slot antenna. After optimization, the return loss of this dual band rectenna can achieve −33dB at 2.45GHz and −25dB at 5.48GHz. Moreover, the radiation pattern gain can reach 7.7 dBi and 8.8 dBi at 2.45GHz and 5.48GHz, respectively. In addition, we also can get 80% radiation efficiency at 5.48GHz, and even 90% radiation efficiency at 2.45GHz. Besides, we use the dual band matching network to achieve the dual band antenna and impedance matching of rectifier circuit, and also use simulation software to optimize the AC-to-DC transform efficiency of the rectifier circuit. As a result, the measured transform efficiency can reach 56.3% and 37.8% at 2.46GHz and 5.44GHz, respectively. Finally, we use an ultra-low power boost charger, Texas Instruments bq25505, to stabilize the DC voltage at 5V to facilitate charging of the end device. To our knowledge, this is the first rectenna use only one single feed point and one rectifier to achieve the 2.4G and 5G dual band characteristic. Also, it is a simple geometric structure that is easy to be implemented.
Multiple Peptides Homologous to Herpes Simplex Virus Type 1 Glycoprotein B Inhibit Viral Infection

ABSTRACT The 773-residue ectodomain of the herpes simplex virus type 1 (HSV-1) glycoprotein B (gB) has been resistant to the use of mutagenic strategies because the majority of the induced mutations result in defective proteins. As an alternative strategy for the identification of functionally important regions and novel inhibitors of infection, we prepared a library of overlapping peptides homologous to the ectodomain of gB and screened for the ability of the peptides to block infection. Seven of 138 15-mer peptides inhibited infection by more than 50% at a concentration of 100 μM. Three peptides (gB94, gB122, and gB131) with 50% effective concentrations (EC50s) below 20 μM were selected for further studies. The gB131 peptide (residues 681 to 695 in HSV-1 gB [gB-1]) was a specific entry inhibitor (EC50, ∼12 μM). The gB122 peptide (residues 636 to 650 in gB-1) blocked viral entry (EC50, ∼18 μM), protected cells from infection (EC50, ∼72 μM), and inactivated virions in solution (EC50, ∼138 μM). We were unable to discern the step or steps inhibited by the gB94 peptide, which is homologous to residues 496 to 510 in gB-1. Substitution of a tyrosine in the gB122 peptide (Y640 in full-length gB-1) reduced the antiviral activity eightfold, suggesting that this residue is critical for inhibition. This peptide-based strategy could lead to the identification of functionally important regions of gB or other membrane proteins and identify novel inhibitors of HSV-1 entry.
Efficient identification of hot data for flash memory storage systems

Hot data identification for flash memory storage systems not only imposes great impacts on flash memory garbage collection but also strongly affects the performance of flash memory access and its lifetime (due to wear-levelling). This research proposes a highly efficient method for on-line hot data identification with limited space requirements. Different from past work, multiple independent hash functions are adopted to reduce the chance of false identification of hot data and to provide predictable and excellent performance for hot data identification. This research not only offers an efficient implementation for the proposed framework, but also presents an analytic study on the chance of false hot data identification. A series of experiments was conducted to verify the performance of the proposed method, and very encouraging results are presented.
Dynamic structures of phosphodiesterase‐5 active site by combined molecular dynamics simulations and hybrid quantum mechanical/molecular mechanical calculations

Various quantum mechanical/molecular mechanical (QM/MM) geometry optimizations starting from an x‐ray crystal structure and from the snapshot structures of constrained molecular dynamics (MD) simulations have been performed to characterize two dynamically stable active site structures of phosphodiesterase‐5 (PDE5) in solution. The only difference between the two PDE5 structures exists in the catalytic, second bridging ligand (BL2) which is HO− or H2O. It has been shown that, whereas BL2 (i.e. HO−) in the PDE5(BL2 = HO−) structure can really bridge the two positively charged metal ions (Zn2+ and Mg2+), BL2 (i.e. H2O) in the PDE5(BL2 = H2O) structure can only coordinate Mg2+. It has been demonstrated that the results of the QM/MM geometry optimizations are remarkably affected by the solvent water molecules, the dynamics of the protein environment, and the electronic embedding charges of the MM region in the QM part of the QMM/MM calculation. The PDE5(BL2 = H2O) geometries optimized by using the QM/MM method in different ways show strong couplings between these important factors. It is interesting to note that the PDE5(BL2 = HO‐) and PDE5(BL2 = H2O) geometries determined by the QM/MM calculations neglecting these three factors are all consistent with the corresponding geometries determined by the QM/MM calculations that account for all of these three factors. These results suggest the overall effects of these three important factors on the optimized geometries can roughly cancel out. However, the QM/MM calculations that only account for some of these factors could lead to considerably different geometries. These results might be useful also in guiding future QM/MM geometry optimizations on other enzymes. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008
An engineered Escherichia coli tyrosyl–tRNA synthetase for site-specific incorporation of an unnatural amino acid into proteins in eukaryotic translation and its application in a wheat germ cell-free system

Tyrosyl–tRNA synthetase (TyrRS) from Escherichia coli was engineered to preferentially recognize 3-iodo-l-tyrosine rather than l-tyrosine for the site-specific incorporation of 3-iodo-l-tyrosine into proteins in eukaryotic translation systems. The wild-type TyrRS does not recognize 3-iodo-l-tyrosine, because of the bulky iodine substitution. On the basis of the reported crystal structure of Bacillus stearothermophilus TyrRS, three residues, Y37, Q179, and Q195, in the l-tyrosine-binding site were chosen for mutagenesis. Thirty-four single amino acid replacements and 16 of their combinations were screened by in vitro biochemical assays. A combination of the Y37V and Q195C mutations changed the amino acid specificity in such a way that the variant TyrRS activates 3-iodo-l-tyrosine 10-fold more efficiently than l-tyrosine. This engineered enzyme, TyrRS(V37C195), was tested for use in the wheat germ cell-free translation system, which has recently been significantly improved, and is now as productive as conventional recombinant systems. During the translation in the wheat germ system, an E. coli suppressor tRNATyr was not aminoacylated by the wheat germ enzymes, but was aminoacylated by the E. coli TyrRS(V37C195) variant with 3-iodo-l-tyrosine. After the use of the 3-iodotyrosyl–tRNA in translation, the resultant uncharged tRNA could be aminoacylated again in the system. A mass spectrometric analysis of the produced protein revealed that more than 95% of the amino acids incorporated for an amber codon were iodotyrosine, whose concentration was only twice that of l-tyrosine in the translation. Therefore, the variant enzyme, 3-iodo-l-tyrosine, and the suppressor tRNA can serve as an additional set orthogonal to the 20 endogenous sets in eukaryotic in vitro translation systems.
Automatic Segmentation, Classification and Clustering of Broadcast News Audio

Automatic recognition of broadcast feeds from radio and television sources has been gaining importance recently, especially with the success of systems such as the CMU Informedia system [1]. In this work we describe the problems faced in adapting a system built to recognize one utterance at a time to a task that requires recognition of an entire half hour show. We break the problem into three components: segmentation, classification, and clustering. We show that a priori knowledge of acoustic conditions and speakers in the broadcast data is not required for segmentation. The system is able to detect changes in acoustics, recognize previously observed conditions, and use this to pool adaptation data. We also describe a novel application of the Symmetric Kullback-Leibler distance metric that is used as a single solution to both the segmentation and clustering problems. The three components are evaluated through comparisons between the Partitioned and Unpartitioned components of the 1996 ARPA Hub 4 evaluation test set.
Overexpression of PTEN increases sensitivity to SN-38, an active metabolite of the topoisomerase I inhibitor irinotecan, in ovarian cancer cells.

PURPOSE PTEN is a tumor suppressor gene that was identified on chromosome 10q23. In addition to its original function as a tumor suppressor, this gene product was recently reported to enhance the sensitivity of cancer cells to anticancer agents. It is for the purpose of this study to investigate its function and the mechanisms by which PTEN enhances the sensitivity of ovarian cancer to antitumor agents. EXPERIMENTAL DESIGN PTEN cDNA was introduced into the ovarian cancer cell line SHIN-3 and a high-expression cell line (SHIN-3/PTEN) was established. This cell line and a control were further analyzed. RESULTS SHIN-3 cells did not carry any mutations in its genome after sequencing. In vitro examination of sensitivity to anticancer agents showed that the 50% growth-inhibitory concentration value for irinotecan metabolite (SN-38) in SHIN-3/PTEN was 800 nM, a 6.6-fold higher sensitivity compared with that of the control (5300 nM). There were no differences in sensitivity to cisplatin, paclitaxel, or gemcitabine between SHIN-3/PTEN and the controls. The percentage of apoptotic cells in SHIN-3/PTEN was 16.6 +/- 0.7% 24 h after addition of SN-38, a significant increase over controls (8.6 +/- 0.9%; P < 0.01). Lower topoisomerase I activity was observed in SHIN-3/PTEN, compared with controls. CONCLUSIONS These results indicate that high PTEN expression enhances the sensitivity of ovarian cancer cells to irinotecan and the induction of apoptosis and the suppression of topoisomerase I activity in cancer cells are suggested as possible mechanisms attributable to high PTEN expression.
The Smart/Empire TIPSTER IR System

The primary goal of the Cornell/Sabir TIPSTER Phase III project is to develop techniques to improve the end-user efficiency of information retrieval (IR) systems. We have focused our investigations in four related research areas:1. High Precision Information Retrieval. The goal of our research in this area is to increase the accuracy of the set of documents given to the user.