Miracle-dz/UniFAR-FTUs huggingface dataset:
Error control variability in pathway-based microarray analysis

Motivation: The decision to commit some or many false positives in practice rests with the investigator. Unfortunately, not all error control procedures perform the same. Our problem is to choose an error control procedure to determine a P-value threshold for identifying differentially expressed pathways in high-throughput gene expression studies. Pathway analysis involves fewer tests than differential gene expression analysis, on the order of a few hundred. We discuss and compare methods for error control for pathway analysis with gene expression data. Results: In consideration of the variability in test results, we find that the widely used Benjamini and Hochberg's (BH) false discovery rate (FDR) analysis is less robust than alternative procedures. BH's error control requires a large number of hypothesis tests, a reasonable assumption for differential gene expression analysis, though not the case with pathway-based analysis. Therefore, we advocate through a series of simulations and applications to real gene expression data that researchers control the number of false positives rather than the FDR. Availability: Our R package, EPath.omg is available at http://sphhp.buffalo.edu/biostat/research/software. Contact: dlgold@buffalo.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Design Tradeoffs for Electrothermal Microgrippers

Microgrippers based on electrothermal actuation were designed and fabricated using the deep reactive ion etching (DRIE) process with 100mum thick silicon on insulator (SOI) wafer. The design requirements are restricted to basic manipulation tasks such as pick and place, and nonprehensile manipulation. This paper explores several electrothermal end-effectors which have been fabricated for serial and parallel microassembly. The end-effectors include three main building blocks: 1) Integrated and symmetrical actuators of V and U shapes. The symmetrical expansions on Chevron and hot arms allow combination of forward translations that amplify angular motion at the tips of a gripper. 2) A joule heating element based on a resistive V-shape electrothermal actuator. In 3D microassembly, the joining of a micropart is essentially performed by providing an integrated microheater device. 3) A force or position feedback sensing block based on self-straining or electrostatic principle. The integrated sensor can be calibrated for both position and force measurements. Serial heterogeneous assembly of meso and micro-scale objects is demonstrated using a 3D microassembly station. Black-box dynamical models for microgrippers are derived using experimentally obtained data, and performance variations due to the way the microgrippers are mounted onto the robot are discussed.
The Effect of Sign Language Structure on Complex Word Reading in Chinese Deaf Adolescents

The present study was carried out to investigate whether sign language structure plays a role in the processing of complex words (i.e., derivational and compound words), in particular, the delay of complex word reading in deaf adolescents. Chinese deaf adolescents were found to respond faster to derivational words than to compound words for one-sign-structure words, but showed comparable performance for two-sign-structure words. For both derivational and compound words, response latencies to one-sign-structure words were shorter than to two-sign-structure words. These results provide strong evidence that the structure of sign language affects written word processing in Chinese. Additionally, differences between derivational and compound words in the one-sign-structure condition indicate that Chinese deaf adolescents acquire print morphological awareness. The results also showed that delayed word reading was found in derivational words with two signs (DW-2), compound words with one sign (CW-1), and compound words with two signs (CW-2), but not in derivational words with one sign (DW-1), with the delay being maximum in DW-2, medium in CW-2, and minimum in CW-1, suggesting that the structure of sign language has an impact on the delayed processing of Chinese written words in deaf adolescents. These results provide insight into the mechanisms about how sign language structure affects written word processing and its delayed processing relative to their hearing peers of the same age.
Molecular Decay of the Tooth Gene Enamelin (ENAM) Mirrors the Loss of Enamel in the Fossil Record of Placental Mammals

Vestigial structures occur at both the anatomical and molecular levels, but studies documenting the co-occurrence of morphological degeneration in the fossil record and molecular decay in the genome are rare. Here, we use morphology, the fossil record, and phylogenetics to predict the occurrence of “molecular fossils” of the enamelin (ENAM) gene in four different orders of placental mammals (Tubulidentata, Pholidota, Cetacea, Xenarthra) with toothless and/or enamelless taxa. Our results support the “molecular fossil” hypothesis and demonstrate the occurrence of frameshift mutations and/or stop codons in all toothless and enamelless taxa. We then use a novel method based on selection intensity estimates for codons (ω) to calculate the timing of iterated enamel loss in the fossil record of aardvarks and pangolins, and further show that the molecular evolutionary history of ENAM predicts the occurrence of enamel in basal representatives of Xenarthra (sloths, anteaters, armadillos) even though frameshift mutations are ubiquitous in ENAM sequences of living xenarthrans. The molecular decay of ENAM parallels the morphological degeneration of enamel in the fossil record of placental mammals and provides manifest evidence for the predictive power of Darwin's theory.
Searching with Feature Similarity in Unstructured Peer-to-Peer Networks

This paper proposes a semantic overlay architecture design in unstructured peer-to-peer network environments. According to semantic distances based on feature similarity of files in a system, this design organizes a semantic peer-to-peer overlay that is capable of delivering query messages to neighboring peers in semantic proximity. In addition, this paper develops a deterministic search approach that can perform content search in a parallel manner over a semantic overlay. Extensive simulations are conducted to examine the proposed deterministic search mechanism in unstructured peer-to-peer networks. Experimental results show that this mechanism can provide satisfactory search services with cost-effective performance in terms of message cost, search latency and hit ratio.
Is the Risk-Return Tradeoff Hypothesis valid: Should an Investor hold Growth Stocks rather than Value Stocks?

This paper will examine if smaller companies outperform large ones in the backwashes of the crisis, i.e. if growth stocks are better off than value stocks when investing. I will investigate how well the three largest companies from Nasdaq OMX’s small cap, mid cap and large cap managed to perform compared to the market index OMXSPI. Using the Capital Asset Pricing Model I will use the beta as a measure of risk to see if higher risk entails higher returns, as the risk-return tradeoff model assumes. Three portfolios consisting of three companies each will be observed and compared. The samples observed will be: i) a portfolio consisting of the three largest companies at Nasdaq OMX small cap list, ii) a portfolio consisting of the three largest companies at Nasdaq OMX mid cap list and iii) a portfolio consisting of the three largest companies at Nasdaq OMX large cap list and an comparing index: OMXSPI. The three portfolios will be divided into two different measure groups: one where the three portfolios are equally weighted and one where the portfolios are weighted by its market capitalization, to investigate if there are any significantly large differences. Each one of the three portfolios will also be compared to an appropriate index. The result supports the assumption of the risk-return tradeoff: the higher the risk, the higher the return. Given that the investor is willing to bear more risk, the return on the investment made will be higher. According to the research made I found that smaller companies do outperform larger ones, since the large cap portfolio had the lowest rate of return for the given time period. But the risk-return tradeoff assumption is not totally true: the small cap portfolio did not manage to outperform the mid cap, hence the best performance made after the crisis was by the mid cap portfolio. I therefore conclude that the risk-return tradeoff is partly true, that a mix of growthand value stocks would generate the highest return and that more data need to be used to give more exact result.
Construction of a Biodiversity Knowledge Repository using a Text Mining-based Framework

In our aim to make the information encapsulated by biodiversity literature more accessible and searchable, we have developed a text mining-based framework for automatically transforming text into a structured knowledge repository. A text mining workflow employing information extraction techniques, i.e., named entity recognition and relation extraction, was implemented in the Argo platform and was subsequently applied on biodiversity literature to extract structured information. The resulting annotations were stored in a repository following the emerging Open Annotation standard, thus promoting interoperability with external applications. Accessible as a SPARQL endpoint, the repository supports knowledge discovery over a huge amount of biodiversity literature by retrieving annotations matching user-specified queries.
Applications of the Microelectromechanical Systems in Nanoscience

The miniaturization and development of complex Micro Electro Mechanical Systems (MEMS) led to a need for an increase in performance of such systems in terms of displacement range, accuracy, velocity etc. There is a huge potential of using them as tools in nanonoscience such as high-density probe memory applications, scanning probe microscopy (e.g. nanolithography, prototyping of nanostructures), bio-physical applications (e.g. cell stimulation and monitoring), chemistry (e.g. trapping molecules in nano-gaps for further analysis). Recent development of such MEMS devices in the Transducers Science and Technology group, as well as experimental testing in different nano-scale related applications are presented. The work focuses on bidirectional and 2DOF (two degrees of freedom) microactuator stages, nano-positioning systems, and development of atomic force microscopy based applications and characterization techniques.
An Improved Haze Removal Algorithm Based on Genetic Fuzzy Clustering

Aiming at the degeneration phenomenon of images taken in mist, according to the features of the degraded images, an improved haze removal algorithm based on genetic fuzzy clustering is presented in this paper after analyzing its defects and shortcomings. Firstly, the improved atmospheric scattering model is established. Secondly, the original image is converted into a standard image through the improved model, and then we present a new multi-scale image edge detection by genetic fuzzy clustering, Based on this observation, we can use the multi-scale image edge detection to estimate the haze thickness directly and recover a high quality haze-free image. The new algorithm uses good global search ability of the genetic algorithm, which will implement the transfer from the scene defogging problem into the optimal estimation problem under global contrast optimal point. Compared with other algorithms for degraded images, the improved haze removal algorithm not only detects image edge precisely, but also has better performance in situations of dense haze. Theoretical analysis and experimental results demonstrate that, the new algorithm improved in this paper are effective for removal of fog-degraded images, and can be applied to the practical situations.
Local Delivery of Mesenchymal Stem Cells with Poly-Lactic-Co-Glycolic Acid Nano-Fiber Scaffold Suppress Arthritis in Rats

Mesenchymal stem cells (MSC) have been used recently for the treatment of autoimmune diseases in murine animal models due to the immunoregulatory capacity. Current utilization of MSC requires cells in certain quantity with multiple courses of administration, leading to limitation in clinical usage. Here we efficiently treated collagen-induced arthritis rats with a single local implantation with reduced number of MSC (2∼20% of previous studies) with nano-fiber poly-lactic-co-glycolic acid (nano-fiber) scaffold. MSC seeded on nano-fiber scaffold suppressed arthritis and bone destruction due to inhibition of systemic inflammatory reaction and immune response by suppressing T cell proliferation and reducing anti- type II collagen antibody production. In vivo tracing of MSC demonstrated that these cells remained within the scaffold without migrating to other organs. Meanwhile, in vitro culture of MSC with nano-fiber scaffold significantly increased TGF-β1 production. These results indicate an efficient utilization of MSC with the scaffold for destructive joints in rheumatoid arthritis by a single and local inoculation. Thus, our data may serve as a new strategy for MSC-based therapy in inflammatory diseases and an alternative delivery method for bone destruction treatment.
A Novel Steganographic Algorithm and Hashing to Improve Authentication using Mobile Phones

- Security has become major issue in all online services. Strong authentication is provided conveniently using mobile phone as security token. While sending security token to user mobile via GSM network, it is vulnerable to several attacks. We can avoid them using Steganography which enforces the security of hashing algorithms. We can share tokens securely with steganography and authentication to prevent participants from the intentional provision of a false stego-image. However, an illegitimate person can easily manipulate the stego-image for successful authentication but cannot recover the secret image. We propose a new authentication method called Σ -hash, which combines an efficient steganographic algorithm and hashing. This paper tells how Σ - Hash can be used for securing OTP(One Time Password) from tampering attacks and other applications.
Improved Statistical Machine Translation Using Monolingual Paraphrases

We propose a novel monolingual sentence paraphrasing method for augmenting the training data for statistical machine translation systems “for free” --by creating it from data that is already available rather than having to create more aligned data. Starting with a syntactic tree, we recursively generate new sentence variants where noun compounds are paraphrased using suitable prepositions, and vice-versa --preposition-containing noun phrases are turned into noun compounds. The evaluation shows an improvement equivalent to 33%--50% of that of doubling the amount of training data.
The Power behind the Table: A Qualitative Analysis of Two School Board Members

School boards are a major influence in local com­ munities throughout America. Their efforts to deter­ mine policy, procedure, and reform in the educational community are often met with confrontation and con­ fl ict . Members of the local school board typically come from a variety of backgrounds and their ability to communicate effectively and resolve conflicts is es­ sential if the board expects to accomplish their goal of creating a quality school environment for their stu­ dents and their community. Effective communication should be an essential component of every school board's agenda. However, previous research exploring the relationship of superintendents and school board members has shown that often, both parties lie at fault when it comes to poor communication (Castillo, 1992) . Even though superintendents and board members are typically in agreement on issues associated with restructuring and reform (Dlugosh and Sybouts , 1995) , quantitative studies have determined that board members tend to have low opinions of the superintendent and he or she in turn , consistently has low opinions of the board (Seaton , 1991 ; Drucker, 1992) . Personality conflicts and specific individual agendas tend to drive many issues that come before school boards and seldom do superintendents or board members use all the informa­ tion available to them in the decision-making process (Casher and Gaylord , 1990) . America's schools re­ quire strong, good decision making unfettered by board members who put their personal and political
A New Approach to Efficient Enumeration by Push-out Amortization

Enumeration algorithms have been one of recent hot topics in theoretical computer science. Different from other problems, enumeration has many interesting aspects, such as the computation time can be shorter than the total output size, by sophisticated ordering of output solutions. One more example is that the recursion of the enumeration algorithm is often structured well, thus we can have good amortized analysis, and interesting algorithms for reducing the amortized complexity. However, there is a lack of deep studies from these points of views; there are only few results on the fundamentals of enumeration, such as a basic design of an algorithm that is applicable to many problems. In this paper, we address new approaches on the complexity analysis, and propose a new way of amortized analysis Push-Out Amortization for enumeration algorithms, where the computation time of an iteration is amortized by using all its descendant iterations. We clarify sufficient conditions on the enumeration algorithm so that the amortized analysis works. By the amortization, we show that many elimination orderings, matchings in a graph, connected vertex induced subgraphs in a graph, and spanning trees can be enumerated in O(1) time for each solution by simple algorithms with simple proofs.
Speech recognition performance over time with the Clarion cochlear prosthesis.

The amount and nature of aural rehabilitation that shouldbe offered to adult, postlingually deaf recipients of cochlear prostheses remains uncertain. With the devices that have been available for the past decade, recovery of clinically useful levels of speech perception usually occurred gradually over several years, if it happened at al1.112 Systematic training has been applied only sporadically, and attempts to demonstrate its usefulness have been unsuccessful.3 In principle, however, a well-fitted cochlearprosthesis should produce temporospatial patterns of auditory nerve activity that immediately produce perceptions of sounds that are recognizable from previous acoustic experience. The Clarion cochlear prosthesis provides both the Multi-Strategy speech processof' and the University of California-San Francisco radial bipolar electrode? a combination that provides unique capabilities to fit the stimulation strategy to the auditory nervous system of each individual patient. Thirty-two of the first 46 patients (70%) fitted with the Clarion obtained moderate to excellent openset speech recognition scores (30% to 100% on Central Institute for the Deaf sentence test) at 12 months. Nineteenof these successful patients (59%) had already achieved at least 80% of their 12-month performance level at the first postoperative test interval (3 months), minimizing their need for aural rehabilitation. STUDY DESIGN
The construction of DEM's using aerial video images sequences

In this paper a method for construction of Digital Elevation Maps (DEM’s) using aerial video image sequences is presented. Using video images sequences implies that many images of relatively low resolution are available. From these image sequences position measurements of point and line features are obtained and measurements of surface orientation. This results in several different types of measurements with different accuracies. A method is presented that can combine these different types of measurements and provides a measure of accuracy for each point in the DEM.
Expressivity of Datalog Variants - Completing the Picture

Computational and model-theoretic properties of logical languages constitute a central ﬁeld of research in logic-based knowledge representation. Datalog is a very popular formalism, a de-facto standard for expressing and querying knowledge. Diverse results exist regarding the expressivity of Datalog and its extension by input negation (semi-positive Datalog) and/or a linear order (order-invariant Datalog). When classifying the expressivity of logical formalisms by their model-theoretic properties, a very natural and prominent such property is preservation under homomorphisms. This paper solves the remaining open questions needed to arrive at a complete picture regarding the inter-relationships between the class of homomorphism-closed queries and the query classes related to the four versions of Datalog. Most notably, we exhibit a query that is both homomorphism-closed and computable in polynomial time but cannot be expressed in order-invariant Datalog.
Classification and detection of metamorphic malware using value set analysis

Metamorphic malware changes the structure of its code from infection to infection. This makes it very hard to classify or to detect. While the byte-sequence of two variants may be completely different, the core functionality of the malware has to stay the same. This includes the use of flags and constants that have to be consistent at specific points. We present a novel approach that allows us to detect metamorphic variants. Based on this detection, it is also possible to classify new samples to a metamorphic family. Our approach identifies variants by tracking the use of consistent values throughout the malware. Our evaluation shows a 100% detection rate with 0 false positives for all metamorphic samples that do not change their behavior.
A Multi-view Non-parametric Clustering Approach to Mobile Subscriber Segmentation

Marketers use segmentation as an important tool to better understand and effectively target customers by adopting marketing strategies catering to the needs and characteristics of each segment. Traditionally, customer segmentation using clustering algorithms is performed using a single attribute set. However, there may be multiple meaningful natural customer groupings possible if independent subsets of attributes were considered while discovering the clusters. Multi-view clustering provides a meaningful way to combine groupings in different feature subsets by assigning customers to multiple segments, representing different perspectives of customer behavior. In this paper we propose a novel method for performing multi-view clustering wherein multiple groupings are generated using a non-parametric clustering algorithm and are then combined and visualized using a cross-tab/sunburst based visualization scheme. We also demonstrate the effectiveness of the proposed approach by applying it to a variety of real-world problems related to mobile subscriber segmentation.
Considering high utilities for time interval sequential pattern mining

The earlier ideas for time interval sequential pattern mining discovering the time interval pattern between two product items help managers promote the sale prediction of the items. For example, if most of the customers purchased product item A, and then they bought item B and C after r to s and t to u days respectively, the time interval between r to s and t to u days can be provided for managers to make marketing decision while predicting the purchasing time interval between A and B, as well as B and C based on the prediction. Nevertheless, the earlier research for the mining does not consider the significance of product items while mining the time-interval sequential patterns. This work implements the previous work and keeps time interval patterns with high utility in which the mining does not just consider the frequent item sets. This is intended to make the sequential pattern mining close to business behaviors. The experimental results show the differences between two mining approaches if considering item utility or item frequency for the purchased items.