Miracle-dz/UniFAR-FTUs huggingface dataset:
Muscle-gesture robot hand control based on sEMG signals with wavelet transform features and neural network classifier

In this paper, we propose a muscle gesture-computer interface (MGCI) system for a five-fingered robotic hand control employing a commercial wearable MYO gesture armband. Eight channels of surface EMG (sEMG) signals were acquired and segmented. Then four levels of Daubechies 5 Wavelet family were performed to analyze the EMG signal. Totally 72 features were extracted from the EMG raw data for 16 hand motions recognition utilizing artificial Neural Networks. The average of best overall classification rate during off-line training is 87.8%. Consequently, real-time hand gesture recognition was implemented to evaluate the performance of the proposed system and the average recognition accuracy was 89.38%. Finally, it was applied to control a five-fingered robot hand.
ADM-LDA: An aspect detection model based on topic modelling using the structure of review sentences

Probabilistic topic models are statistical methods whose aim is to discover the latent structure in a large collection of documents. The intuition behind topic models is that, by generating documents by latent topics, the word distribution for each topic can be modelled and the prior distribution over the topic learned. In this paper we propose to apply this concept by modelling the topics of sentences for the aspect detection problem in review documents in order to improve sentiment analysis systems. Aspect detection in sentiment analysis helps customers effectively navigate into detailed information about their features of interest. The proposed approach assumes that the aspects of words in a sentence form a Markov chain. The novelty of the model is the extraction of multiword aspects from text data while relaxing the bag-of-words assumption. Experimental results show that the model is indeed able to perform the task significantly better when compared with standard topic models.
Mining Association Rules with Item Constraints

The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice, users are often interested in a subset of association rules. For example, they may only want rules that contain a specific item or rules that contain children of a specific item in a hierarchy. While such constraints can be applied as a post-processing step, integrating them into the mining algorithm can dramatically reduce the execution time. We consider the problem of integrating constraints that are Boolean expressions over the presence or absence of items into the association discovery algorithm. We present three integrated algorithms for mining association rules with item constraints and discuss their tradeoffs.
Seeing protein monolayers with naked eye through plasmonic Fano resonances

We introduce an ultrasensitive label-free detection technique based on asymmetric Fano resonances in plasmonic nanoholes with far reaching implications for point-of-care diagnostics. By exploiting extraordinary light transmission phenomena through high-quality factor (Qsolution ∼ 200) subradiant dark modes, we experimentally demonstrate record high figures of merits (FOMs as high as 162) for intrinsic detection limits surpassing that of the gold standard prism coupled surface-plasmon sensors (Kretschmann configuration). Our experimental record high sensitivities are attributed to the nearly complete suppression of the radiative losses that are made possible by the high structural quality of the fabricated devices as well as the subradiant nature of the resonances. Steep dispersion of the plasmonic Fano resonance profiles in high-quality plasmonic sensors exhibit dramatic light intensity changes to the slightest perturbations within their local environment. As a spectacular demonstration of the extraordinary sensitivity and the quality of the fabricated biosensors, we show direct detection of a single monolayer of biomolecules with naked eye using these Fano resonances and the associated Wood’s anomalies. To fabricate high optical-quality sensors, we introduce a high-throughput lift-off free evaporation fabrication technique with extremely uniform and precisely controlled nanofeatures over large areas, leading to resonance line-widths comparable to that of the ideally uniform structures as confirmed by our time-domain simulations. The demonstrated label-free sensing platform offers unique opportunities for point-of-care diagnostics in resource poor settings by eliminating the need for fluorescent labeling and optical detection instrumentation (camera, spectrometer, etc.) as well as mechanical and light isolation.
Extending Zelterman's Approach for Robust Estimation of Population Size to Zero‐truncated Clustered Data

Estimation of population size with missing zero‐class is an important problem that is encountered in epidemiological assessment studies. Fitting a Poisson model to the observed data by the method of maximum likelihood and estimation of the population size based on this fit is an approach that has been widely used for this purpose. In practice, however, the Poisson assumption is seldom satisfied. Zelterman (1988) has proposed a robust estimator for unclustered data that works well in a wide class of distributions applicable for count data. In the work presented here, we extend this estimator to clustered data. The estimator requires fitting a zero‐truncated homogeneous Poisson model by maximum likelihood and thereby using a Horvitz–Thompson estimator of population size. This was found to work well, when the data follow the hypothesized homogeneous Poisson model. However, when the true distribution deviates from the hypothesized model, the population size was found to be underestimated. In the search of a more robust estimator, we focused on three models that use all clusters with exactly one case, those clusters with exactly two cases and those with exactly three cases to estimate the probability of the zero‐class and thereby use data collected on all the clusters in the Horvitz–Thompson estimator of population size. Loss in efficiency associated with gain in robustness was examined based on a simulation study. As a trade‐off between gain in robustness and loss in efficiency, the model that uses data collected on clusters with at most three cases to estimate the probability of the zero‐class was found to be preferred in general. In applications, we recommend obtaining estimates from all three models and making a choice considering the estimates from the three models, robustness and the loss in efficiency. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Structure and function of the symbiosis partners of the lung lichen (Lobaria pulmonaria L. Hoffm.) analyzed by metaproteomics

Environmental proteomics, also referred to as metaproteomics, is an emerging technology to study the structure and function of microbial communities. Here, we applied semi‐quantitative label‐free proteomics using one‐dimensional gel electrophoresis combined with LC‐MS/MS and normalized spectral counting together with fluorescence in situ hybridization and confocal laser scanning microscopy to characterize the metaproteome of the lung lichen symbiosis Lobaria pulmonaria. In addition to the myco‐ and photobiont, L. pulmonaria harbors proteins from a highly diverse prokaryotic community, which is dominated by Proteobacteria and including also Archaea. While fungal proteins are most dominant (75.4% of all assigned spectra), about the same amount of spectra were assigned to prokaryotic proteins (10%) and to the green algal photobiont (9%). While the latter proteins were found to be mainly associated with energy and carbohydrate metabolism, a major proportion of fungal and bacterial proteins appeared to be involved in PTMs and protein turnover and other diverse functions.
A novel standardized bone model for thermal evaluation of bone osteotomies with various irrigation methods.

OBJECTIVES Based on a novel standardized bovine specimen, the aim of this study was to investigate thermal effects of different irrigation methods during intermittent and graduated drilling. MATERIAL AND METHODS Temperature changes during implant osteotomies (n = 320) of 10 and 16 mm drilling depths with various irrigation methods were investigated on manufactured uniform bone samples providing homogenous cortical and cancellous areas and analogous thermal conductivity comparable to human bone. Automated sequences were performed with surgical twist drills of 2 mm ∅ and conical drills of 3.5, 4.3 and 5 mm ∅. Real-time recording of temperature increase was done using two custom-built multichannel thermoprobes with 14 temperature sensors at a predefined distance of 1 and 2 mm to the final osteotomy. The effects of drilling depth, drilling diameter and irrigation methods on temperature changes were investigated by a linear mixed model. RESULTS Using this uniform bone specimen, the greatest temperature rise was observed without any coolant supply with 29.87°C, followed by external with 28.47°C and then internal with 25.86°C and combined irrigation with 25.68°C. Significant differences (P ≤ 0.0156) between drill depths of 10 vs. 16 mm could be observed with all irrigation methods evaluated. With each of the irrigation methods, significantly higher temperature changes (P < 0.0001) during osteotomies could be observed between twist drills of 2 mm ∅ and conical drills of 3.5, 4.3 and 5 mm ∅. During 10 and 16 mm drilling osteotomies, external irrigation showed significantly higher temperatures (P < 0.05) for all conical drills compared with internal or combined irrigation, respectively. Significantly lower temperatures (P < 0.05) could be detected with internal or combined irrigation for the use of conical drills with various diameters and drilling depths. CONCLUSIONS This fully standardized bone model provides optimized comparability for the evaluation of bone osteotomies and resulting temperature changes. As regards the efficiency of the various irrigation methods, it could be demonstrated that internal and combined irrigation appears to be more beneficial than external irrigation.
Digital enhancement of frequency synthesizers

In this paper, we propose an All-Digital On-Chip Phase Noise Measurement Technique. This Technique can be integrated as part of a built-in self-test (BIST) scheme for phase-locked loop (PLL)-based clock synthesizers. The proposed technique based on an all digital ΣΔ-frequency discriminator. Unlike all previously reported techniques, our proposed technique is implemented using digital-only circuits and can report digital numbers corresponding to the close in phase noise level of the PLL to a digital BIST controller. This makes it easily integrated and scaled down for high-density microprocessor applications with modern sub 100nm technology nodes.
Individual changes in dental fear among children and parents: A longitudinal study

Abstract Objective. The aim was to study longitudinal changes in dental fear among children and one of their parents separately for girls, boys, mothers and fathers over a 3.5-year period. Materials and methods. 11–12-year-old children in Pori, Finland (n = 1691) and one of their parents were invited to participate in this longitudinal study. Dental fear was measured in 2001, 2003 and 2005 when the children were 11–12, 13–14 and 15–16-years-old, respectively. The participants were asked if they were afraid of dental care (1 = ‘not afraid’, 2 = ‘slightly afraid’, 3 = ‘afraid to some degree’, 4 = ‘quite afraid’, 5 = ‘very afraid’ and 6 = ‘I don’t know’). The participants’ gender was also registered. Mean values of the change scores were studied. Prevalence and incidence of dental fear and changes in dichotomized dental fear (responses 4–5 = high dental fear and responses 1–3 = low dental fear) were studied using cross-tabulations and Cochran’s Q test. Results. Overall, the prevalence of dental fear slightly increased and female preponderance in dental fear became more evident during the follow-up. Of the mothers and children with high dental fear at the baseline, 24% and 56%, respectively, reported not to be fearful at the end of the follow-up. Conclusions. Dental fear seems to be more stable in adulthood than in childhood. Thus, it might be better to intervene in dental fear during childhood rather than during adulthood.
Massively multiplayer online role-playing games (MMORPG): Association between its addiction, self-control and mental disorders among young people in Vietnam

Aims: To explore the association between MMORPG addiction and mental health status, and between self-control ability and mental health status among young male MMORPG players in Hanoi, Vietnam. Methods: In this cross-sectional study, 10 computer game rooms were randomly selected out of 77 in five communes in Hanoi. From these game rooms, 350 MMORPG players were purposively recruited as a study group, of whom 344 completed the questionnaire. In the same five communes, 344 non-players were selected as a control group. An online game addiction scale, a self-control scale and the Vietnamese SRQ-20 were used to measure the degree of MMORPG addiction, self-control ability and level of mental disorders. Results: MMORPG players had significantly higher mental disorders scale scores than non-players (p < .001). The strongest positive correlation was detected between MMORPG addiction scale scores and mental disorders scale scores (r = 0.730, p < .001). Self-control scale scores were negatively associated with mental disorders scale scores (r = -0.345, p < .001). The average amount of money spent on games per month, MMORPG addiction scale score and self-control scale score were considered the best predictors of a higher mental disorders scale score. Conclusion: Young, male MMORPG players with higher addiction scores were more likely to have higher mental disorders scale scores, and such mental status was negatively associated with the level of self-control in Hanoi, Vietnam. Closer attention should be paid to prevent mental disorders among MMORPG players.
Surface Functionalization of Fabrics and Threads for Smart Textiles

SURFACE FUNCTIONALIZATION OF FABRICS AND THREADS FOR SMART TEXTILES SEPTEMBER 2018 MORGAN L. BAIMA, B.A., ST. EDWARD’S UNIVERSITY M.A., UNIVERSITY OF WISCONSIN MADISON Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Trisha L. Andrew The future of electronics is moving toward wearable devices and therefore requires a shift away from hard, inflexible materials towards fibers, threads, and fabrics that conform to the shape of the body. Therefore new methods for incorporating textiles as electronic components are needed to replace conventional processing techniques used with smooth, flat substrates like glass, silicon, and many polymers. Toward this end, this work investigates different methods that can be used to tune textile surfaces for electronic functionality, including weaving, solution grafting, and initiated chemical vapor deposition (iCVD). While all of these methods were used to make triboelectrically-active textiles, iCVD combined with simple solution chemistry was also used to synthesize ionically conductive thin films on textiles for solid-state electrolytes. In general these methods elucidate facile pathways towards smart clothing fabrication.
Social Fingerprinting: Detection of Spambot Groups Through DNA-Inspired Behavioral Modeling

Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots. Leveraging such a characterization, we design the Social Fingerprinting technique, which is able to discriminate among spambots and genuine accounts in both a supervised and an unsupervised fashion. We also evaluate the effectiveness of Social Fingerprinting and we compare it with three state-of-the-art detection showing the superiority of our solution. Finally, among the peculiarities of our approach is the possibility to apply off-the-shelf DNA analysis techniques to study online users behaviors and to efficiently rely on a limited number of lightweight account characteristics.
FACTORS INFLUENCING SUSTAINABLE COMPETITIVE ADVANTAGE AMONG CUT FLOWER COMPANIES

Citation: Karuoya, L. N. (2014). Factors influencing sustainable competitive advantage among cut flower companies. ABSTRACT This study sets out to investigate the factors that influence sustainable competitive advantage among cut flower companies in Naivasha District, taking specific cases of two companies which for this purpose we will refer them as company A and B. The study therefore studied how the companies use infrastructure, location, human resource and development and horticultural clusters to achieve competitive advantage.The study adopted a descriptive survey design targeting 105 employees in top level, middle level and low level management working in Company A and Company B. Since the population sample was small, census approach was used. The study collected both primary data and secondary data. Primary data was collected using questionnaires while secondary data was collected from companies' annual reports, manuals and newsletters. A pilot study was carried out to ensure validity of the research instrument. Self-administered questionnaire were used in this study to collect quantitative data. The data was then analyzed using descriptive statistics. The study also used regression method to test the nature of influence of independent variables on a dependent variable. The study findings were presented using tables, figures and graphs whose interpretations were given in prose. This generated quantitative reports through tabulations, percentages, and measure of central tendency. The study found out that infrastructure, location, human resource and horticulture clusters influences sustainable competitive advantage to a large extent. It is recommended that government to encourage flower marketing should develop infrastructure, companies to train their staff well and strive retain employees to achieve competitive advantage. It is also recommended that prior to flower farm set up, location consideration is key also for synergy, firm should agglomerate in clusters to reap the benefits of economies of scale.
On the Factor Revealing LP Approach for Facility Location with Penalties

We consider the uncapacitated facility location problem with (linear) penalty function and show that a modified JMS algorithm, combined with a randomized LP rounding technique due to Byrka-Aardal[1], Li[14] and Li et al.[16] yields 1.488 approximation, improving the factor 1.5148 due to Li et al.[16]. This closes the current gap between the classical facility location problem and this penalized variant. Main ingredient is a straightforward adaptation of the JMS algorithm to the penalty setting plus a consistent use of the upper bounding technique for factor revealing LPs due to Fernandes et al.[7]. In contrast to the bounds in [12], our factor revealing LP is monotone.
Structural Behavior of Confined Concrete Filled Aluminum Tubular (CFT) Columns under Concentric Load

This paper introduces an experimental study on the behavior of confined concrete filled aluminum tubular (CFT) column to improve strength design, ductility and durability of concrete composite structures under concentrically loaded in compression to failure. To achieve this: seven column specimens with same concrete diameter 100mm and without steel reinforcement have been examined through experimental testing, which are used to study the effects of the thickness of the aluminum tube encased concrete ( thickness : 0mm, 2mm, 3mm, 4mm and 5mm with same length of column 450mm), length of column (thickness 5mm and length of column 700mm) and durability (thickness 5mm and length of column 450mm) on the structural behavior of (CFT) columns. It is concluded from this work that the compression force capacity is affected by thicknesses of the aluminum tube with respect to reference specimen. Where the used of aluminum tube thicknesses in column specimens led to increased in load carrying capacity in range (16% for C2 -224% for C5 ). The specimen has a length of 700mm with 5mm thickness the decreased of strength was 0.06% than the specimen with 5mm thickness and length 450mm. For slender column the overall buckling was observed while the local buckling for the short column is the dominant failure shape. Regarding durability, no apparent difference has been found between the structural behavior of the specimen that immersed in aggressive solution and specimen in air. Keywords: circular, column, aluminum, CFT, conﬁnement
Optimal marketing strategies over social networks

We discuss the use of social networks in implementing viral marketing strategies. While influence maximization has been studied in this context (see Chapter 24 of [10]), we study revenue maximization, arguably, a more natural objective. In our model, a buyer's decision to buy an item is influenced by the set of other buyers that own the item and the price at which the item is offered. We focus on algorithmic question of finding revenue maximizing marketing strategies. When the buyers are completely symmetric, we can find the optimal marketing strategy in polynomial time. In the general case, motivated by hardness results, we investigate approximation algorithms for this problem. We identify a family of strategies called influence-and-exploit strategies that are based on the following idea: Initially influence the population by giving the item for free to carefully a chosen set of buyers. Then extract revenue from the remaining buyers using a 'greedy' pricing strategy. We first argue why such strategies are reasonable and then show how to use recently developed set-function maximization techniques to find the right set of buyers to influence.
Suppressive Effects of Tea Catechins on Breast Cancer

Tea leaf (Camellia sinensis) is rich in catechins, which endow tea with various health benefits. There are more than ten catechin compounds in tea, among which epigallocatechingallate (EGCG) is the most abundant. Epidemiological studies on the association between tea consumption and the risk of breast cancer were summarized, and the inhibitory effects of tea catechins on breast cancer, with EGCG as a representative compound, were reviewed in the present paper. The controversial results regarding the role of tea in breast cancer and areas for further study were discussed.