Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical clinching with dies for control of metal flow of ultra-high-strength steel and high-strength steel sheets

Ultra-high-strength steel sheets having a tensile strength of more than 1 GPa and a low ductility were joined by mechanical clinching with dies for control of metal flow. The bottom angle of the die was modified to increase interlocking between the sheets under avoidance of the sheet fracture. The effect of the die shape on metal flow in the sheet combination including an ultra-high-strength steel sheet was investigated by the finite element simulation and the experiment. As the tensile strength of the steel sheets increased, the joining range was narrow due to low ductility of the sheets. The static and fatigue strengths of the mechanically clinched joints were compared with those of the welded joints. Although the static loads of the mechanically clinched joints were smaller than those of the resistance spot welded joints in both tension-shearing and cross-tension tests, the fatigue loads of the clinched joints were larger. It was found that the mechanically clinched joint has superior fatigue strength.
THE SPATIAL NATURE OF THOUGHT: UNDERSTANDING INFORMATION SYSTEMS DESIGN THROUGH DIAGRAMS Le caractère spatial de la pensée : comprendre la conception des systèmes d'information grâce aux diagrammes

Design entails the interaction of minds and the tools used to express the design, notably, diagrams. Systems designers use the affordances of the page when they generate structural diagrams of systems. Specifically, they use proximity to augment connectedness (path) information by grouping subsystems. They use horizontal position on the page to express sequence and vertical position to reflect actual spatial position. Finally, they use the permanence of diagrams to generate alternative designs. These conclusions were reached through the analysis of work by student designers, many of whom were practicing information technology professionals. The analysis of designs in topological and Euclidean space required the creation of computational tools that show promise as decision aids for designers, by separating the intertwined qualities of topological and Euclidean space, and by making visible the conceptual similarity of design alternatives.
Dual‐band feedforward linear power amplifier for digital cellular and IMT‐2000 base‐station

This article presents the design of a novel dual‐band signal cancellation circuit and its application to feedforward linear power amplifier. Intermodulation distortion cancellation loop shows 20.45 dB and 25.04 dB suppression for digital cellular band and IMT‐2000 band, respectively, over a correction bandwidth of 100 MHz. From the adjacent channel leakage ratio measurement, 16.5 dB and 18.6 dB improvements are achieved for each band under simultaneous operation. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 922–926, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24198
Semi-blind beamspace-time interference cancellation using subspace channel identification for DS-WCDMA systems

It was shown recently that semi-blind methods can be effective for separation, estimation, and classification of sources in wireless systems. These methods overcome difficulties of training algorithms (reduction of data information throughput) and blind ones (impossibility to classify separated source and multi-modal optimization due to nonlinearities). In this paper, we present a semi-blind spatial-temporal beamforming receiver that uses the recently proposed semi-blind constant modulus algorithm with channel identification (SBCMACI) to perform joint channel equalization, multipath energy combination and spatial interference cancellation for asynchronous direct sequence wide band code division multiple access (DS-WCDMA) systems. The simulation results show a significant performance improvement and reduction of required training symbols when compared against a receiver employing a training-based spatial-temporal recursive least squares (RLS) beamformer.
Extracellular secretion of pectate lyase by the Erwinia chrysanthemi out pathway is dependent upon Sec-mediated export across the inner membrane

The plant pathogenic enterobacterium Erwinia chrysanthemi EC16 secretes several extracellular, plant cell wall-degrading enzymes, including pectate lyase isozyme PelE. Secretion kinetics of 35S-labeled PelE indicated that the precursor of PelE was rapidly processed by the removal of the amino-terminal signal peptide and that the resulting mature PelE remained cell bound for less than 60 s before being secreted to the bacterial medium. PelE-PhoA (alkaline phosphatase) hybrid proteins generated in vivo by TnphoA insertions were mostly localized in the periplasm of E. chrysanthemi, and one hybrid protein was observed to be associated with the outer membrane of E. chrysanthemi in an out gene-dependent manner. A gene fusion resulting in the substitution of the beta-lactamase signal peptide for the first six amino acids of the PelE signal peptide did not prevent processing or secretion of PelE in E. chrysanthemi. When pelE was overexpressed, mature PelE protein accumulated in the periplasm rather than the cytoplasm in cells of E. chrysanthemi and Escherichia coli MC4100 (pCPP2006), which harbors a functional cluster of E. chrysanthemi out genes. Removal of the signal peptide from pre-PelE was SecA dependent in E. coli MM52 even in the presence of the out gene cluster. These data indicate that the extracellular secretion of pectic enzymes by E. chrysanthemi is an extension of the Sec-dependent pathway for general export of proteins across the bacterial inner membrane.
Dual-color-emitting green fluorescent protein from the sea cactus Cavernularia obesa and its use as a pH indicator for fluorescence microscopy

We isolated and characterized a green fluorescent protein (GFP) from the sea cactus Cavernularia obesa. This GFP exists as a dimer and has absorption maxima at 388 and 498 nm. Excitation at 388 nm leads to blue fluorescence (456 nm maximum) at pH 5 and below, and green fluorescence (507 nm maximum) at pH 7 and above, and the GFP is remarkably stable at pH 4. Excitation at 498 nm leads to green fluorescence (507 nm maximum) from pH 5 to pH 9. We introduced five amino acid substitutions so that this GFP formed monomers rather than dimers and then used this monomeric form to visualize intracellular pH change during the phagocytosis of living cells by use of fluorescence microscopy. The intracellular pH change is visualized by use of a simple long-pass emission filter with single-wavelength excitation, which is technically easier to use than dual-emission fluorescent proteins that require dual-wavelength excitation. Copyright © 2013 John Wiley & Sons, Ltd.
Wafer level packaging of MEMS

Wafer level packaging plays many important roles for MEMS (micro electro mechanical systems), including cost, yield and reliability. MEMS structures on silicon chips are encapsulated between bonded wafers or by surface micromachining, and electrical interconnections are made from the cavity. Bonding at the interface, such as glass–Si anodic bonding and metal-to-metal bonding, requires electrical interconnection through the lid vias in many cases. On the other hand, lateral electrical interconnections on the surface of the chip are used for bonding with intermediate melting materials, such as low melting point glass and solder. The cavity formed by surface micromachining is made using sacrificial etching, and the openings needed for the sacrificial etching are plugged using deposition sealing methods. Vacuum packaging methods and the structures for electrical feedthrough for the interconnection are discussed in this review.
Efficient Learning of Action Schemas and Web-Service Descriptions

This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages--traditional STRIPS, and a new language STRIPS+WS that extends STRIPS to allow for the creation of new objects when an action is executed. This modification allows STRIPS+WS to model web services and can be used to describe web-service composition (planning) problems. We show that general STRIPS operators cannot be efficiently learned through raw experience, though restricting the size of action preconditions yields a positive result. We then show that efficient learning is possible without this restriction if an agent has access to a "teacher" that can provide solution traces on demand. We adapt this learning algorithm to efficiently learn web-service descriptions in STRIPS+WS.
Joint Feature Selection and Subspace Learning

Dimensionality reduction is a very important topic in machine learning. It can be generally classified into two categories: feature selection and subspace learning. In the past decades, many methods have been proposed for dimensionality reduction. However, most of these works study feature selection and subspace learning independently. In this paper, we present a framework for joint feature selection and subspace learning. We reformulate the subspace learning problem and use L2,1-norm on the projection matrix to achieve row-sparsity, which leads to selecting relevant features and learning transformation simultaneously. We discuss two situations of the proposed framework, and present their optimization algorithms. Experiments on benchmark face recognition data sets illustrate that the proposed framework outperforms the state of the art methods overwhelmingly.
Double abstraction level heuristic power optimization for digital signal processors using GA's

In this paper the authors explored a new approach towards optimization of dedicated reconfigurable DSP processors using a two pronged approach. At the logic level, metarules are used to abstract global heuristic knowledge or particular design strategies to optimize the parent population size which are dynamically reconfigured by applying genetic algorithms. At the algorithm level, a data based probabilistic heuristic scheduling algorithm incorporating pipelining was proposed, resulting in resource optimization that adapts to programmable infrastructure with better speed, cost and power dissipation compared to GPP especially in image processing and signal processing tasks. This paper proposes an alternative approach to power-minimization based on a dynamic matching between architecture and computation.
Sequential screening: A Bayesian dynamic programming analysis of optimal group-splitting

Sequential screening is the problem of allocating simulation effort to identify those input factors that have an important effect on a simulation's output. In this problem, sophisticated algorithms can be substantially more efficient than simulating one factor at a time. We consider this problem in a Bayesian framework, in which each factor is important independently and with a known probability. We use dynamic programming to compute the Bayes-optimal method for splitting factors among groups within a sequential bifurcation procedure (Bettonvil & Kleijnen 1997). We assume importance can be tested without error. Numerical experiments suggest that existing group-splitting rules are optimal, or close to optimal, when factors have homogeneous importance probability, but that substantial gains are possible when factors have heterogeneous probability of importance.
A Fuzzy Approach to Centrality and Prestige in Online Social Networks

Online Social networks have become popular with the increased use of mobile devices. Online Social network analysis alleviates the quantitative as well as qualitative analysis of online social networks. Online social networks deals with human emotions and communications, the vagueness in the process is more and is a hindrance in computation. We analyze two network measures namely centrality and prestige by developing a fuzzy rule based inference system. We obtained the relation between interaction, centrality and prestige in online social networks. The paper describes in detail, the need for a fuzzy approach in online social network analysis and analyzes the network measures.
University of Massachusetts: MUC-3 Test Results and Analysis

We believe that the score reports we obtained for TST2 provide an accurate assessment of our system's capabilities insofar as they are consistent with the results of our own internal tests conducted near the end of phase 2. The required TST2 score reports indicate that our system achieved the highest combined scores for recall (51%) and precision (62%) as well as the highest recall score of all the MUC-3 systems under the official MATCHED/MISSING scoring profile.
Modeling of the chasing behaviors for developmental program of children with autism spectrum disorders

We are researching and developing dynamic interpersonal distance models and real-time recognition systems for the social development training therapy of children with autism spectrum disorders (ASD). In particular, we modeled the quantitative measurements of chasing behaviors observed during therapy. Chasing behaviors are a highly social activity because children need to predict the movement of a partner (therapist). In order to measure these behaviors, the video coding using observational method by experts is needed but it is very time consuming. We consider that establishing models for real-time automated recognition of chasing behavior supports social skills development programs for children with ASD. This study focuses on chasing behavior and presents experimental results for recognition of chasing behavior during actual therapy. The proposed system reveals that it is possible to extract tracking behaviors which closely agree with therapist observations.
Comparative analysis of commercial and open source mobile device forensic tools

With forensics playing such a crucial role in today's data-driven world, this paper addresses the need to explore the different mobile device forensic tools available. Open Source and Commercial tools are two domains in close contention, with contrasting considerations such as accessibility and security. This paper aims at performing a comparative analysis of the various commercial and open source mobile device forensic tools, with respect to predefined software parameters and by employing a cross-device and test-driven approach. The test scenarios are structured to assess whether the selected tools possess the capabilities of a holistic one, while responding to threats and scenarios pertaining to the digital realm. The Commercial Tools under consideration are MOBILedit! Forensic (including Phone Forensics Express) and Cellebrite's UFED Physical Analyzer, while the Open Source Tools are — The Sleuth Kit (including Autopsy) and SANS SIFT. The result of this paper is a comparison matrix, which could help in identifying the best-fit solution as per the need of the investigation. It could also indicate the degree to which open source tools are comparable to (or better than) their commercial counterparts, and answer questions like — Can open source tools be a suitable replacement for the proprietary tools? Can this in reality, be a feasible shift for the forensic industry?
Prevalence and predictors of habitual snoring in a sample of Saudi middle-aged adults

Objectives: To determine the prevalence of habitual snoring among a sample of middle-aged Saudi adults, and its potential predictors. Methods: A cross-sectional study was conducted from March 2013 until June 2013 in randomly selected Saudi Schools in Jeddah, Kingdom of Saudi Arabia. The enrolled subjects were 2682 school employees (aged 30-60 years, 52.1% females) who were randomly selected and interviewed. The questionnaire used for the interview included: the Wisconsin Sleep Questionnaire to assess for snoring, medical history, and socio-demographic data. Anthropometric measurements and blood pressure readings were recorded using standard methods. Results: Forty percent of the 2682 enrolled subjects were snorers: 23.5% were habitual snorers, 16.6% were moderate snorers, and 59.9%, were non-snorers. A multivariate analysis revealed that independent predictors of snoring were ageing, male gender, daytime sleepiness, hypertension, family history of both snoring and obstructive sleep apnea, water-pipe smoking, and consanguinity. Conclusion: This study shows that snoring is a common condition among the Saudi population. Previously reported risk factors were reemphasized but consanguinity was identified as a new independent predictive risk factor of snoring. Exploring snoring history should be part of the clinical evaluation.
Efficient Informative Sensing using Multiple Robots

The need for efficient monitoring of spatio-temporal dynamics in large environmental applications, such as the water quality monitoring in rivers and lakes, motivates the use of robotic sensors in order to achieve sufficient spatial coverage. Typically, these robots have bounded resources, such as limited battery or limited amounts of time to obtain measurements. Thus, careful coordination of their paths is required in order to maximize the amount of information collected, while respecting the resource constraints. In this paper, we present an efficient approach for near-optimally solving the NP-hard optimization problem of planning such informative paths. In particular, we first develop eSIP (efficient Single-robot Informative Path planning), an approximation algorithm for optimizing the path of a single robot. Hereby, we use a Gaussian Process to model the underlying phenomenon, and use the mutual information between the visited locations and remainder of the space to quantify the amount of information collected. We prove that the mutual information collected using paths obtained by using eSIP is close to the information obtained by an optimal solution. We then provide a general technique, sequential allocation, which can be used to extend any single robot planning algorithm, such as eSIP, for the multi-robot problem. This procedure approximately generalizes any guarantees for the single-robot problem to the multi-robot case. We extensively evaluate the effectiveness of our approach on several experiments performed infield for two important environmental sensing applications, lake and river monitoring, and simulation experiments performed using several real world sensor network data sets.
Probing the Structure, Stability and Hydrogen Adsorption of Lithium Functionalized Isoreticular MOF-5 (Fe, Cu, Co, Ni and Zn) by Density Functional Theory

Li adsorption on isoreticular MOFs with metal Fe, Cu, Co, Ni and Zn was studied using density function theory. Li functionalization shows a considerable structural change associated with a volume change in isoreticular MOF-5 except for the Zn metal center. Hydrogen binding energies on Li functionalized MOFs are seen to be in the range of 0.2 eV, which is the desired value for an ideal reversible storage system. This study has clearly shown that Li doping is possible only in Zn-based MOF-5, which would be better candidate to reversibly store hydrogen.
The environment matters: Comparing individuals and dyads in their adaptive use of decision strategies

Individuals have been shown to adaptively select decision strategies depending on the environment structure. Two experiments extended this research to the group level. Subjects (N = 240) worked either individually or in two-person groups, or dyads, on a multi-attribute paired-comparison task. They were randomly assigned to two different environments that favored one of two prototypical decision strategies—weighted additive or take-the-best (between-subjects design in Experiment 1 and within-subject design in Experiment 2). Performance measures revealed that both individuals and dyads learned to adapt over time. A higher starting and overall performance rate in the environment in which weighted additive performed best led to the conclusion that weighted additive served as a default strategy. When this default strategy had to be replaced, because the environment structure favored take-the-best, the superior adaptive capacity of dyads became observable in the form of a steeper learning rate. Analyses of nominal dyads indicate that real dyads performed at the level of the best individuals. Fine-grained analyses of information-search data are presented. Results thus point to the strong moderating role of the environment structure when comparing individual with group performance and are discussed within the framework of adaptive strategy selection.
Economic Efficiency of Pig Production in Oyo State, Nigeria: A Stochastic Production Frontier Approach

This study investigated the economic efficiency of pig production in Ogbomoso zone, agricultural zone in Oyo State, Nigeria, between June and October 2009 using stochastic production frontier approach. A multistage sampling technique was employed in the selection; Ogbomoso North and South Local Government Areas were purposively selected because of the larger population of pig farmers and structured questionnaires were used to collect data from randomly chosen one hundred and ten (110) pig farmers. Descriptive statistics, cost benefit analysis and stochastic frontier production function were used for analyzing the data. It was revealed from the findings that mean benefit cost ratio for pig production was 2.82, this means that the enterprise is profitable. The result of the CobbDouglass stochastic production frontier function also showed that stocking cost, cost of feed and cost of labour had positive significant effects on the production output, the estimated gamma parameter (γ) was 0.780 and highly significant at 99% (0.01). Sex, age and household size had negative significant effects on economic inefficiency. The sum of elasticity was 1.191, indicating a positive increasing return to scale in the study area which might lead to over utilization of inputs in terms of excess spending on inputs. Although, the pig farmers were found to be operating on the frontier and were generally economically efficient, higher improvement could still be achieved through easy accessibility to institutional credit, pens expansion, improved breeding stocks and provision of technical assistance.