Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation

In order to provide the most effective therapy for cancer, it is important to be able to diagnose whether a patient's cancer will respond to a proposed treatment. Methylation profiling could contain information from which such predictions could be made. Currently, hypothesis testing is used to determine whether possible biomarkers for cancer progression produce statistically significant results. However, this approach requires the identification of individual genes, or sets of genes, as candidate hypotheses, and with the increasing size of modern microarrays, this task is becoming progressively harder. Exhaustive testing of small sets of genes is computationally infeasible, and so hypothesis generation depends either on the use of established biological knowledge or on heuristic methods. As an alternative machine learning, methods can be used to identify groups of genes that are acting together within sets of cancer data and associate their behaviors with cancer progression. These methods have the advantage of being multivariate and unbiased but unfortunately also rapidly become computationally infeasible as the number of gene probes and datasets increases. To address this problem, we have investigated a way of utilizing prior knowledge to segment microarray datasets in such a way that machine learning can be used to identify candidate sets of genes for hypothesis testing. A methylation dataset is divided into subsets, where each subset contains only the probes that relate to a known gene pathway. Each of these pathway subsets is used independently for classification. The classification method is AdaBoost with decision trees as weak classifiers. Since each pathway subset contains a relatively small number of gene probes, it is possible to train and test its classification accuracy quickly and determine whether it has valuable diagnostic information. Finally, genes from successful pathway subsets can be combined to create a classifier of high accuracy.
An Outer Mitochondrial Translocase, Tom22, Is Crucial for Inner Mitochondrial Steroidogenic Regulation in Adrenal and Gonadal Tissues

ABSTRACT After cholesterol is transported into the mitochondria of steroidogenic tissues, the first steroid, pregnenolone, is synthesized in adrenal and gonadal tissues to initiate steroid synthesis by catalyzing the conversion of pregnenolone to progesterone, which is mediated by the inner mitochondrial enzyme 3β-hydroxysteroid dehydrogenase 2 (3βHSD2). We report that the mitochondrial translocase Tom22 is essential for metabolic conversion, as its knockdown by small interfering RNA (siRNA) completely ablated progesterone conversion in both steroidogenic mouse Leydig MA-10 and human adrenal NCI cells. Tom22 forms a 500-kDa complex with mitochondrial proteins associated with 3βHSD2. Although the absence of Tom22 did not inhibit mitochondrial import of cytochrome P450scc (cytochrome P450 side chain cleavage enzyme) and aldosterone synthase, it did inhibit 3βHSD2 expression. Electron microscopy showed that Tom22 is localized at the outer mitochondrial membrane (OMM), while 3βHSD2 is localized at the inner mitochondrial space (IMS), where it interacts through a specific region with Tom22 with its C-terminal amino acids and a small amino acid segment of Tom22 exposed to the IMS. Therefore, Tom22 is a critical regulator of steroidogenesis, and thus, it is essential for mammalian survival.
α-Thalassemia Mutations in Khuzestan Province, Southwest Iran

Although α-thalassemia (α-thal) is the most common hereditary hemoglobin (Hb) disorder in Iran, no comprehensive data are so far available on the prevalence of the disease in the province of Khuzestan in Southwest Iran. This study investigates the spectrum of α-thal mutations in this region. One hundred and twenty-one subjects from Khuzestan Province, Iran, were initially tested for the three most common Iranian α-thal mutations ( − α3.7, − α4.2, and − − MED) by gap-polymerase chain reaction (gap-PCR). Reverse hybridization test strips and DNA sequencing were used to identify additional α-globin mutations. A total of 131 mutated α-globin alleles were identified in these patients. Of the 13 mutations that were detected in Khuzestan Province, Iran, the − α3. 7 single gene deletion was the most frequently identified variant, representing 62.6% of the total; we also observed significant numbers of individuals with compound heterozygous mutations. On the basis of our results, we strongly recommend screening for the most common mutations to improve the molecular diagnosis of anemia in this region.
Improved decision-making for software managers using Bayesian networks

Although there have been many models for predicting quality and resources in software development, they do not provide enough decision-support for software managers. It has been argued that models based on Bayesian Nets (BNs) address this problem. Unlike previous BN models, the new model (called the Productivity Model) presented here takes account of both up-to-date generic empirical data on software productivity and quality and, where relevant, local information and choice of units of measurement. The model provides comprehensive support for 'trade-off' analysis to help decision-making.
An Active Shape Model based approach for Arabic handwritten character recognition

A lot of research has been conducted in order to solve the problem of unconstrained Arabic handwriting recognition. Nonetheless, an effective solution is still a serious challenge. In this paper, we propose an new Active Shape Model (ASM) based approach for recognition of Arabic handwritten text. Character candidate representations are generated using chamfer distance transforms, and optimal parameters for ASMs are calculated. Furthermore, a performance comparison among three different optimization techniques, is presented. For experiments, we used 28046 letter samples from different writers. Two third to build the ASMs and one third for testing. Results were satisfactory, and we showed that our approach is a promising and a step forward in the field.
Relay Selection Strategies for Distributed Space-Time Cooperative Systems Over Wireless Ad-Hoc Networks

We propose several relay selection strategies for distributed space-time cooperative systems, in which the Alamouti scheme is used. Our strategies select the best two nodes among the source and all relays to assist the packet transmissions from the source to the destination. In the amplify-and-forward mode, we develop an efficient algorithm to select the optimal cooperative nodes which can maximize the instantaneous signal-to-noise ratio at the destination. Under the decode-and-forward mode, our relay selection strategies depend on the successful decoding results at the relays. We design our schemes by considering both cases with and without CRC. In addition, we integrate the request- to-send/clear-to-send mechanism into our proposed system and analyze the system throughputs. The simulation results show that our proposed strategies can significantly improve the system throughput and achieve the diversity gain as compared to the conventional existing schemes.
New improvements to range image segmentation by edge detection

This article presents new improvements to range image segmentation based on edge detection techniques. The developed approach better preserves the object's topology and shape even to noisy images. The algorithm also does not depend on rigid threshold values, thus being useful in unsupervised systems. Experiments were performed in a popular range image database and the results were compared to four other traditional range image segmentation algorithms, demonstrating the efficiency of the proposed algorithm.
Disentangling the implementation of local-to-global transformations in a rewrite rule transformation system

Transformation rules are often used to implement compilers for domain-specific languages. In an ideal situation, each transformation rule is a modular unit transforming one input element of the source program into a new element of the output program. However, in practice, transformation rules must be written which take one input element and produce several new elements belonging to various locations in the output program, the so-called local-to-global transformations. The implementation of such transformations is very complex and tightly coupled which imposes severe constraints on maintenance and evolvability. In this paper, we propose a transformation architecture on top of rewrite rules to loosen this coupling. The resulting transformation system combines the simplicity and modularity properties of rewrite rules with a new semi-automatic composition system that enables the implementation of local-to-global transformations without hampering maintenance and future evolutions.
Broad Spectrum Light Harvesting in TiO$_2$ Nanotube Array – Hemicyanine Dye – P3HT Hybrid Solid-State Solar Cells

Control of interfacial electron transfer between electron transporting oxide semiconductors and molecular adsorbates in organic-inorganic hybrid solar cells is a research area of intense interest, with the poor optical harvesting in the red and near-IR (NIR) portion of the solar spectrum a significant limitation to device performance. We fabricate hybrid solar cells, using two new hemicyanine photosensitizers having different π-conjugation lengths that absorb sunlight from visible to NIR range, as well as unsymmetrical squaraine dye. These organic dyes are used not only as a photosensitizer, but also as electronic mediator for n-type TiO2 nanotube arrays, vertically oriented from the fluorine-doped tin oxide coated glass substrate, which are subsequently infiltrated with p-type regio-regular poly(3-hexyl thiophene 2,5 diyl), enabling broad-spectrum response. In general, the organic-dye-inorganic photovoltaic structure appears a promising method for harvesting a broad portion of the solar spectrum energy from a relatively simple photovoltaic device.
Time of Flight Measurements in Real-Time Ultrasound Signatures of Aluminum Spot Welds: An Image Processing Approach

Ultrasonic testing is one of the most popular non-destructive methods to determine the quality in spot welds. The next step of this technology is to be able to determine the quality while the weld is being made, this advance can have a great impact on the quality assurance of joints in materials like aluminum, where the spot welding process is a difficult task. In our approach, a state-of-the-art ultrasound transducer assembly is installed in one of the welding electrodes. Working in pulse-echo mode, the system collects A-scans of the waves passing through the welded plates in the direction perpendicular to the plate’s surface. A-scans are gated to allow stack-up front and back wall reflections to be recorded. Such setup has allowed the acquisition of real-time ultrasonic signatures composed of multiple A-scans for each spot weld. Eventually the signature should be processed to extract information about the weld quality. During the welding process temperature gradually increases within the aluminum plates; as sound speed in metals is inversely proportional to the temperature, the time of flight will increase during welding. The change in time of flight of the ultrasonic wave during the whole welding process is a good indicator of the heating rate in the weld and can be a good judge of weld quality. Unfortunately, electrode deterioration, industrial noises and pulse changes due to frequency dependent attenuation make signal detection a challenging task. To overcome this difficulty the system treats B-scan as an image instead of a set of separate A-scans. With such approach, the weak signal detection (in most of the cases, weak back wall reflection) is performed by applying different image processing techniques which take advantage of statistical properties of neighbouring A-scans (signal similarity). This paper presents an effective and robust means of monitoring the change in time of flight on several signals acquired during the welding process. This is achieved by an image processing technique which exploits the B-Scan representation of the ultrasonic signature of the weld. The proposed method is able to detect the back wall reflection during the complete welding process with sub-pixel resolution and is able to interpolate areas where the signal is not present.
An improved SLM cascade with iterative TR method for PAPR reduction in OFDM system

In this paper, we propose an improved selective mapping (SLM) cascaded with iterative tone reservation (TR) method for peak-to average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) system. In the simple SLM cascaded with iterative TR method, the candidate signal which has the minimum PAPR is selected. However, since the number of iteration L of the largest peak values will be reduced by TR, in the proposed method, the candidate signal which has the minimum (L+1)th peak to average power ratio is selected among other candidates in the SLM process. From the performance comparisons between various PAPR reduction methods, we verified that the PAPR reduction performance of the proposed method achieves the better reduction performance and power efficiency.
Evaluating the Impact of Transactional Characteristics on the Performance of Transactional Memory Applications

Transactional Memory (TM) is reputed by many researchers to be a promising solution to ease parallel programming on multicore processors. This model provides the scalability of fine-grained locking while avoiding common issues of traditional mechanisms, such as deadlocks. During these almost twenty years of research, several TM systems and benchmarks have been proposed. However, TM is not yet widely adopted by the scientific community to develop parallel applications due to unanswered questions in the literature, such as "how to identify if a parallel application can exploit TM to achieve better performance? " or "what are the reasons of poor performances of some TM applications? ". In this work, we contribute to answer those questions through a comparative evaluation of a set of TM applications on four different state- of-the-art TM systems. Moreover, we identify some of the most important TM characteristics that impact directly the performance of TM applications. Our results can be useful to identify opportunities for optimizations.
Automatic acquisition and animation of virtual avatars

The USC Institute for Creative Technologies will demonstrate a pipline for automatic reconstruction and animation of lifelike 3D avatars acquired by rotating the user's body in front of a single Microsoft Kinect sensor. Based on a fusion of state-of-the-art techniques in computer vision, graphics, and animation, this approach can produce a fully rigged character model suitable for real-time virtual environments in less than four minutes.
Phase transitions on Hecke C*-algebras and class-field theory over ℚ

Abstract We associate a canonical Hecke pair of semidirect product groups to the ring inclusion of the algebraic integers 𝒪 in a number field 𝒦, and we construct a C*-dynamical system on the corresponding Hecke C*-algebra, analogous to the one constructed by Bost and Connes for the inclusion of the integers in the rational numbers. We describe the structure of the resulting Hecke C*-algebra as a semigroup crossed product and then, in the case of class number one, analyze the equilibrium (KMS) states of the dynamical system. The extreme KMSβ states at low-temperature exhibit a phase transition with symmetry breaking that strongly suggests a connection with class field theory. Indeed, for purely imaginary fields of class number one, the group of symmetries, which acts freely and transitively on the extreme KMS∞ states, is isomorphic to the Galois group of the maximal abelian extension over the field. However, the Galois action on the restrictions of extreme KMS∞ states to the (arithmetic) Hecke algebra over 𝒦, as given by class-field theory, corresponds to the action of the symmetry group if and only if the number field 𝒦 is ℚ.
An FPGA Based Open Source Network-on-Chip Architecture

Networks on chip (NoC) has long been seen as a potential solution to the problems encountered when implementing large digital hardware designs. In this paper we describe an open source FPGA based NoC architecture with low area overhead, high throughput and low latency compared to other published works. The architecture has been optimized for Xilinx FPGAs and the NoC is capable of operating at a frequency of 260 MHz in a Virtex-4 FPGA. We have also developed a bridge so that generic Wishbone bus compatible IP blocks can be connected to the NoC.
Overexpression of Sigma1 Receptor and Its Positive Associations With Pathologic TNM Classification in Esophageal Squamous Cell Carcinoma

Sigma1 receptor (sigma1R), a significant protein, has been found to be frequently upregulated in human tumor cells and tissues. It has been demonstrated that sigma1R is involved in proliferation and adhesion of cancer cells. However, the significance of sigma1R expression in esophageal squamous cell carcinoma (ESCC) remains unclear. In this article, by a series of methods, the authors examined the expression of sigma1R protein in ESCC cell lines and tissues. Flow cytometry indicated intense staining of sigma1R in ESCC cells. Immunocytochemistry staining demonstrated that sigma1R was mainly distributed in cytoplasm and nucleus in ESCC cell lines. Western blotting was performed to characterize the relative expression of sigma1R in different ESCC cell lines. Moreover, different levels of sigma1R were presented from normal epithelium to carcinoma by immunohistochemistry analysis, which demonstrated that sigma1R was highly expressed in tumors. Association analysis showed significant correlations between total sigma1R protein levels and pathologic TNM (pTNM) classification of tumors (r=0.216, p=0.011). Furthermore, the sigma1R in the nucleus was significantly correlated with pTNM classification and lymph node metastasis (r=0.263, p=0.002, and r=0.269, p=0.002, respectively). These data indicated that sigma1R may serve as a potential predictive factor for pTNM classification and tumor development in ESCC.
Aerobic Activity of Escherichia coliAlcohol Dehydrogenase Is Determined by a Single Amino Acid

ABSTRACT Expression of the alcohol dehydrogenase gene, adhE, inEscherichia coli is anaerobically regulated at both the transcriptional and the translational levels. To study the AdhE protein, the adhE+ structural gene was cloned into expression vectors under the control of the lacZ andtrpc promoters. Wild-type AdhE protein produced under aerobic conditions from these constructs was inactive. Constitutive mutants (adhC) that produced high levels of AdhE under both aerobic and anaerobic conditions were previously isolated. When only the adhE structural gene from one of the adhC mutants was cloned into expression vectors, highly functional AdhE protein was isolated under both aerobic and anaerobic conditions. Sequence analysis revealed that the adhE gene from the adhC mutant contained two mutations resulting in two amino acid substitutions, Ala267Thr and Glu568Lys. Thus,adhC strains contain a promoter mutation and two mutations in the structural gene. The mutant structural gene fromadhC strains was designated adhE*. Fragment exchange experiments revealed that the substitution responsible for aerobic expression in the adhE* clones is Glu568Lys. Genetic selection and site-directed mutagenesis experiments showed that virtually any amino acid substitution for Glu568 produced AdhE that was active under both aerobic and anaerobic conditions. These findings suggest that adhE expression is also regulated posttranslationally and that strict regulation of alcohol dehydrogenase activity in E. coli is physiologically significant.
A Robust Practical Text Summarization

We present an automated method of generating human-readable summaries from text documents such as news, technical reports, government documents, and even court records. Our approach exploits an empirical observation that much of the written text display certain regularities of organization and style, which we call the Discourse Macro Structure (DMS). A summary is therefore created to reflect the con.ponents of a given DMS. In order to produce ~ roherent and readable summary we select continuoa~, well-formed passages from the source document and assemble them into a mini-document within a DMS template. In this paper we describe the SummarizerTool, a Java-implemented prototype, and its applications in various document processing tasks.
A method for direct audio search with applications to indexing and retrieval

A technique for searching audio data to find an exact match for a given piece of cue-audio is described. The method uses a cepstral parameterisation of the audio and a covariance-based distance metric to quickly locate direct repeats. Results on data from ABC news broadcasts show that the method can successfully locate matches several hundred times faster than real-time and requires less than a second of cue-audio. By applying the match recursively to the data, repeated sections of audio, which nearly always correspond to non-news items such as commercials and theme-music, can be identified. Experiments show that the application of the technique can also lead to improved information retrieval using automatically transcribed broadcast data.
Efficient Nonserial Polyadic Dynamic Programming on the Cell Processor

Dynamic programming (DP) is an effective technique for many search and optimization problems. However, the high arithmetic complexity limits its extensive use. Although modern processor architectures with multiple cores and SIMD (single instruction multiple data) instructions provide increasingly high computing power, even the state-of-the-art fully optimized algorithm still largely underutilizes modern multi-core processors. In this paper we propose to improve one family of DP, nonserial polyadic DP (NPDP), targeting a heterogeneous multi-core architecture, the Cell Broadband Engine. We first design a new data layout which efficiently utilizes the on-chip memory system of the Cell processor. Next we devise a CellNPDP algorithm with two tiers. The first tier is a SPE (a co-processor on the Cell processor) procedure which efficiently computes a block of data that can fit into one SPE's local store. The second tier is a parallel procedure which enables all SPEs to efficiently compute all blocks of data. To evaluate CellNPDP, we use both performance modeling and experiments. The performance model reveals that the processor utilization of NPDP can be independent of the problem size. To empirically evaluate CellNPDP, we use two platforms: the IBM QS20 dual-Cell blade and a CPU platform with two latest quad-core CPUs. On both platforms, the processor utilization of CellNPDP is larger than 60%, which demonstrates that our optimizations and CellNPDP can be architecture-independent. Compared to the state-of-the-art fully optimized algorithm on the CPU platform, CellNPDP is 44-fold faster for single-precision and 28-fold faster for double-precision, which is a significant improvement to NPDP.
RAPID PROTOTYPING OF HUMAN INTERFACE TECHNOLOGIES USING SIMULATION

This paper reports the use of simulation to perform rapid prototyping of advanced control and display technologies (direct voice input, 3-dimensional sound and helmet mounted display) for fast-jet aircraft. By integrating the new prototypic systems into a research simulator and making rapid changes to the direct voice input, experienced pilots were able to use the systems in simulated flight, gaining insights into, and providing expert comments on their future application. The rapid-prototyping approach was shown to be useful in establishing how the technologies might be employed in future cockpit systems.