Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and kinematic analysis of biped robot

Most movement tasks are defined in coordinate systems that are different from the actuator space in which motor commands must be issued. Hence, movement planning and learning in task space require appropriate coordinate transformations from task to actuator space before motor commands can be computed. Therefore to move the biped robot to the desired point, the Denavit-Hartenburg (DH) algorithm is being used to provide a matrix method to derive the forward kinematic solution. The forward kinematic analysis is described in this paper.
Pleistocene stone pendant from Western Australia

One of the most unusual objects so far recovered in Australia's Pleistocene archaeology is a perforated stone fragment excavated from the cave deposit of Devil's Lair in 1973 (Dortch and Merrilees 1973). The marl object, thought to be between 12,000 and 19,000 years old, has been described as a possible pendant (Dortch 1979a, 1980). It is one of several unusual objects reported from this site that have been subjected to prolonged discussion and speculation. There are also several 'plaques' with engraved markings thought to be anthropic and some other perforated objects, including three ground bone beads (Dortch 1976, 1979b, 1984; Flood 1995: 109-10). In response to critical review, the identifications of several finds from the site were recently revised (Dortch and Dortch 1996: Table l), and C.E. Dortch, the excavator, has arranged for the marked and some of the perforated objects to be subjected to specialist study (Dortch and Dortch 1996:30).
An Introduction to Test-Driven Code Generation

Agile Software Development promotes the use of techniques such as Test-Driven Development (TDD) and Automation in order to improve software quality and to reduce development time. Code generation represents a way to achieve automation, reducing repetitive and error-prone tasks. Code generation is well accepted, writing a code generator is not necessary that hard, however it is not trivial to decide when and how to embrace code generation. Moreover, it is even harder to embrace at the same time code generation and TDD, wondering for example How to build a generator following a test driven approach? or How to test drive generated code? This paper aims at providing hints to answer those questions. It presents an iterative approach named Test-Driven Code Generation. The main principle is to gain knowledge about the application during the first iterations of its development process and then to identify how to implement code generation. As code generation should not drive you out of TDD, we provide hints to marry both approaches in order to empower your developments. Using a simple 3-tiers web application, this paper is illustrated with Python standard unittest module, CherryPy web application server and Cheetah templating system.
p53 Expression in Pterygium by Immunohistochemical Analysis: A Series Report of 127 Cases and Review of the Literature

Purpose: To assess the p53 protein expression in pterygial tissue and to review all immunohistochemical studies on pterygium from Medline to evaluate the roles of age, gender, race, p53 antibody, cutoff levels of immunohistochemical analysis, parts of pterygium, p53 gene mutation spectrum, and primary or recurrent pterygium on the p53 staining results. Methods: Immunohistochemical staining was performed on 127 pterygial specimens and 18 normal conjunctival samples. All 8 immunohistochemical studies on p53 expression in pterygium from Medline were reviewed. Results: Among the 127 pterygial samples, there were 29 specimens (22.8%) positive for p53 expression. There was no significant difference between the p53-positive and p53-negative groups with respect to age or gender. Conclusion: The positive rate of p53 staining in 8 immunohistochemical studies was 7.9%, 36.8%, 37.5%, 38.1%, 50%, 53.8%, 60%, and 100%, respectively. p53 protein antibody, cutoff level, race, and p53 gene mutational spectra all affect the results on the p53 staining. Different parts of pterygium and gender merit further evaluation in their role on p53 staining result.
Adaptive tone-mapping operator for HDR images based on image statistics

In this paper, we present a novel segmentation method for displaying high dynamic range image based on K-means clustering. The new segmentation method uses statistical features of an image in a logarithmic luminance domain. Each divided region is applied to different global tone mapping operators respectively. The global tone mapping operator is a logarithmic tone mapping with a different user parameters. The parameters for applying to each region are calculated using a centroid which is obtained from K-means clustering. According to results of many HDR image experiments, we demonstrate that our method is faster than other local tone mapping operators and improves an image rendering performance in terms of dark area details and contrast enhancement.
Various Hyperplane Classifiers Using Kernel Feature Spaces

In this paper we introduce a new family of hyperplane classifiers. But, in contrast to Support Vector Machines (SVM) - where a constrained quadratic optimization is used - some of the proposed methods lead to the unconstrained minimization of convex functions while others merely require solving a linear System of equations. So that the efficiency of these methods could be checked, classification tests were conducted on standard databases. In our evaluation, classification results of SVM were of course used as a general point of reference, which we found were outperformed in many cases.
Differentiation of follicular dendritic sarcoma cells into functional myeloid‐dendritic cell‐like elements

Abstract: In a rare case of follicluar dendritic cell sarcoma, malignant cells were isolated and cultured in the presence of granulocyte‐macrophage colony‐stimulating factor (GM‐CSF), interleukin 4 (IL‐4) and tumor necrosis factor alpha (TNF‐α). After 14 d, 15% of neoplastic cells differentiated into myeloid‐dendritic cell‐like elements as demonstrated by immunological and functional characteristics.
Disease tracking service in urban areas

Tracking epidemic disease is a very challenging issue nowadays. The success of such process could help medical administration to stop diseases quicker than usual. In this paper, we suggest a methodology based on wireless sensor networks deployed over volunteers who agree to carry a light wireless sensor network. Sensors over the body will monitor some health parameters (temperature, pressure,.) and will run some light classification algorithms to diagnosis first diseases on the volunteers and later on their neighbors. The classification methodologies used in this study are based on the SVM approach or on the Fuzzy C-Means one. Finally, the wireless sensor network will send aggregated data about the disease to some base stations which collect the results. The main contribution is to execute an on-line disease tracking program and to detect some information about how the disease is propagated.
Multi-view face detection with the multi-resolution MPP classifiers

Detecting multi-view faces is a challenging task, not only because of the face variations in scale, illumination, and expression, but also of the variations caused by multiple views. In this paper, we proposed a multi-layer cascaded architecture, which can focus attention on the promising regions of the image. The whole classifiers are only evaluated on the face like parts of the image, while the most amount of background blocks are excluded by the first few layers of the detector. Instead of using predefined priori knowledge about face view partition, we divide the sample space automatically by the branching competitive learning network at different discriminative resolutions. To maintain the high detection efficiency, we adopt the simplified Support Vector Machines (SVMs), called the mirror pair of points (MPP) classifiers, as the component of our detection system. Experimental results show that our system is competitive with other systems presented recently in the literature.
Economic Growth : A Channel Accounting Exercise

This paper formalizeschannel accounting , a method that systematically decomposes the channels through which the determinants of economic growth operate, and applies it to the data. Under channel accounting, the determinants could affect aggregate productivity growth through physical capital accumulation, through human capital acquisition, and through growth in total factor productivity (TFP). Methodologically, channel accounting combines growth accounting with regression analysis. With this method, it becomes clear that TFP growth, not factor accumulation, is what accounts for conditional convergence. This finding is extremely robust. There is no evidence that rich and poor countries converge through different channels. JEL: O33, O40
Coffee, caffeine, and risk of depression among women.

BACKGROUND Caffeine is the world's most widely used central nervous system stimulant, with approximately 80% consumed in the form of coffee. However, studies that analyze prospectively the relationship between coffee or caffeine consumption and depression risk are scarce. METHODS A total of 50,739 US women (mean age, 63 years) free of depressive symptoms at baseline (in 1996) were prospectively followed up through June 1, 2006. Consumption of caffeine was measured from validated questionnaires completed from May 1, 1980, through April 1, 2004, and computed as cumulative mean consumption with a 2-year latency period applied. Clinical depression was defined as self-reported physician-diagnosed depression and antidepressant use. Relative risks of clinical depression were estimated using Cox proportional hazards regression models. RESULTS During 10 years of follow-up (1996-2006), 2607 incident cases of depression were identified. Compared with women consuming 1 or less cup of caffeinated coffee per week, the multivariate relative risk of depression was 0.85 (95% confidence interval, 0.75-0.95) for those consuming 2 to 3 cups per day and 0.80 (0.64-0.99; P for trend<.001) for those consuming 4 cups per day or more. Multivariate relative risk of depression was 0.80 (95% confidence interval, 0.68-0.95; P for trend=.02) for women in the highest (≥550 mg/d) vs lowest (<100 mg/d) of the 5 caffeine consumption categories. Decaffeinated coffee was not associated with depression risk. CONCLUSIONS In this large longitudinal study, we found that depression risk decreases with increasing caffeinated coffee consumption. Further investigations are needed to confirm this finding and to determine whether usual caffeinated coffee consumption can contribute to depression prevention.
Effects of fluvoxamine and paroxetine on sleep structure in normal subjects: a home-based Nightcap evaluation during drug administration and withdrawal.

BACKGROUND Acute and chronic administration of the selective serotonin reuptake inhibitors (SSRIs) have been widely reported to disrupt sleep in laboratory studies. This study examines the naturalistic, longitudinal effects of paroxetine and fluvoxamine on sleep quality in the home setting. METHOD Fourteen healthy volunteers free of medical and neuropsychiatric symptoms entered a 31-day protocol: 7 days of drug-free baseline (days 1-7), 19 days of drug treatment (steady state during days 18-26), and 5 days of acute withdrawal (days 27-31). On day 8, the subjects were randomly assigned to receive either 100 mg/day of fluvoxamine or 20 mg/day of paroxetine (half receiving each drug) in divided morning and evening oral doses. Investigators remained blinded to drug assignment until all sleep data had been analyzed. Sleep was monitored using the Nightcap ambulatory sleep monitor. Four standard and 3 novel measures were computed and compared using multivariate analysis of variance, analysis of variance, and Bonferroni-corrected comparison of means. RESULTS Sleep disruption was most clearly demonstrated using the novel measures eyelid quiescence index, rhythmicity, and eyelid movements per minute in non-rapid eye movement sleep, but was also apparent as determined by standard measures of sleep efficiency, number of awakenings, and sleep onset latency. Paroxetine disrupted sleep more than fluvoxamine, and paroxetine-induced sleep disruption persisted into the withdrawal phase. Rapid eye movement sleep was suppressed during treatment (especially for fluvoxamine) and rebounded during withdrawal (especially for paroxetine). CONCLUSION We confirm laboratory polysomnographic findings of SSRI-induced sleep quality changes and demonstrate the Nightcap's efficacy as an inexpensive longitudinal monitor for objective sleep changes induced by psychotropic medication.
Smoking behavior among adolescents in rural schools in Malacca, Malaysia - a case-control study

Smoking among rural adolescents in Malaysia is on the rise with a significant difference seen between urban and rural youths. Therefore, this study was carried out to determine a predictive model of smoking among the rural-school adolescents population in Malacca, Malaysia. An unmatched case-control study was conducted in 2010 involving 484 cases and 444 controls of Form Two students in Malacca, Malaysia, using cluster sampling. Smoking was the dependent factor of this study while the independent factors were individual, family, school and environment. Data were obtained through a self-administered questionnaire. The response rate of the study was 100% whereas the smoking prevalence was 20.9%. Binary logistic regression was used to determine the smoking predictive model. Strong predictors of smoking behavior were: influenced by artistes who smoke (Adjusted OR=8.67, 95% CI 5.53-13.58); the male gender (Adjusted OR=6.7, 95% CI 4.14-10.83); Muslim (Adjusted OR=4.46, 95% CI 2.36-8.44); and the belief that smoking is not dangerous when the teacher is seen smoking as well (Adjusted OR=3.95, 95% CI 2.19-7.10). Other predictors were: being offered cigarettes by friends (Adjusted OR=2.81, 95% CI 1.79-4.42); the belief that smoking will relax the mind (Adjusted OR=2.45, 95% CI 1.33-4.51); having friends who smoke (Adjusted OR=2.32, 95% CI 1.29-4.81); forced by friends to smoke (Adjusted OR=2.17, 95% CI 1.15-4.12); have heard of the national No-Smoking Campaign (Adjusted OR=1.89,
A Novel DSA-Driven MAC Protocol for Cognitive Radio Networks

With the deployment of more wireless applications, spectrum scarcity becomes an issue in many countries. Recent reports show that the reason for this spectrum shortage is the underutilization of some spectrum re-sources. Fortunately, the emergence of open spectrum and dynamic spectrum assess (DSA) technology in cognitive radio networks relieves this problem. In this paper, we propose a novel DSA-driven cognitive MAC protocol to achieve highly efficient spectrum usage and QoS provisioning. In the proposed protocol, secondary users are divided into several non-overlapping groups, and all leftover channels are allocated among groups taking the groups’ bandwidth requirements into consideration. Moreover, the allocation of vacant channels can be adjusted dynamically when members join/leave groups or primary users return/leave the current network. Simulations show that the proposed MAC protocol greatly improves the quality of ser-vice for secondary users and maximizes the utilization ratio of spectrum resources.
Base-pair probability profiles of RNA secondary structures

Dynamic programming algorithms are able to predict optimal and suboptimal secondary structures of RNA. These suboptimal or alternative secondary structures are important for the biological function of RNA. The distribution of secondary structures present in solution is governed by the thermodynamic equilibrium between the different structures. An algorithm is presented which approximates the total partition function by a Boltzmann-weighted summation of optimal and suboptimal secondary structures at several temperatures. A clear representation of the equilibrium distribution of secondary structures is derived from a two-dimensional bonding matrix with base-pairing probability as the third dimension. The temperature dependence of the equilibrium distribution gives the denaturation behavior of the nucleic acid, which may be compared to experimental optical denaturation curves after correction for the hypochromicities of the different base-pairs. Similarly, temperature-induced mobility changes detected in temperature-gradient gel electrophoresis of nucleic acids may be interpreted on the basis of the temperature dependence of the equilibrium distribution. Results are illustrated for natural circular and synthetic linear potato spindle tuber viroid RNA respectively, and are compared to experimental data.
Potential Sources of Anxiety for Japanese Learners of English: Preliminary Case Interviews with Five Japanese College Students in the U.S.

This study explores the nature of language anxiety from the perspective of five Japanese learners of English (ESL), especially in reference to their self-reflective accounts of emotional difficulties encountered in the U.S. college settings. Through the use of an in-depth qualitative interview format, this study attempts to identify potential sources of anxiety relevant to their affective needs or concerns as Japanese ESL learners in a cross-cultural learning environment. As the interview findings indicate, characteristics of language anxiety exhibited by the participants seem to be quite influenced by Japanese cultural norms or expectations acquired through numerous socialization processes in Japan. Using Young's (1991) six sources of language anxiety as a theoretical guideline for data collection and analysis, this study also discusses some of the influences or impact of those anxiety-provoking factors on L2 learning, along with some implications for further research on language anxiety and for ESL teaching.
A Real-Time Dynamic Pricing Algorithm for Smart Grid With Unstable Energy Providers and Malicious Users

In this paper, we consider a smart power model, where some subscribers share several energy providers and there are some malicious users in this power grid. The energy providers are managed by a power market scheduling center (PMSC), which broadcasts electricity price to subscribers and energy providers. The energy providers and subscribers update their capacities and energy consumption requirements, respectively, according to the electricity prices received. In order to identify the malicious users and the unstable energy providers, the mechanism of identification and processing (MIP) for the malicious users and unstable energy providers is proposed. By integrating the MIP, we proposed a heuristic algorithm called the dynamic pricing algorithm with malicious users and unstable energy providers (DPAMU) to get the optimal electricity price as well as the optimal power requirement and the load capacity. Finally, the simulation results show that the proposed DPAMU has good convergence performance and can shave and clip the peak load effectively.
Examining Wedding Rituals through a Multidimensional Gender Lens

This paper examines weddings, which are rife with gendered conventions, as a window into processes of gender (re)production. More specifically, it addresses the theoretical question of the relationships among dimensions of gender—individual, interactional, and institutional—via ethnographic data evidencing both consistency and contradiction among levels. While there is evidence that the institutional dimension is reflected in individuals’ assumptions regarding what a wedding should be, and this leads to reproduction of convention in the interactional dimension, I also find ways in which the institutional dimension is inconsistent with individuals’ understandings and their gendered relationships. I identify these inconsistencies as “visibility cues” that make assumptions evident and allow for alternative gender performances. In all, this research answers calls for a more complex understanding of gender as multidimensional and provides an analytic tool for continuing this work, while utilizing a micro-level focus that complements existing studies of the inequality inherent in the American “white wedding. ”
Bring the Noise: Embracing Randomness Is the Key to Scaling Up Machine Learning Algorithms

and storage, major bottlenecks still exist when using big data for statistical inference and predictive modeling. Many classic algorithms used for predictive modeling with big data are constrained by the very math that defines them. These algorithms tend to have complexities that do not scale linearly, so doubling your data often means quadrupling the time it takes to learn models. Many of today’s statistical modelers have been trained using the algorithms and software that have largely been optimized for a ‘‘small data’’ paradigm. New tools and new ways of approaching many machine learning problems are now called for in order to scale up industrialsized applications. Fortunately, new theory, intuition, and tools are emerging to solve these problems. In this article, we introduce the works of Leon Bottou and John Langford (both coincidentally at Microsoft Research), two leading researchers in the field whose research missions have been to scale up machine learning. The work by Bottou, Langford, and their colleagues shows us that by adopting algorithmic strategies that classically would be considered inferior, we can paradoxically both scale up machine learning and end up with better predictive performance. From a predictive modeling perspective, more data certainly is better, but only if you can use it. The strategies presented here offer practitioners promising options to making that happen.
Measuring listening-related fatigue: Behavioural and physiological markers

Murphy, P.R. , O'Connell, R.G. , O'Sullivan, M. , Robertson, I.H. , & Balsters, J.H. (2014). Pupil diameter covaries with BOLD activity in human locus coeruleus. Human brain mapping, 35, 4140-4154. “Bob lives near a beautiful park and loves going for long walks there during Spring. This time he decided to bring binoculars to see if he could spot any pigeons in the trees. Fortunately, he managed to catch a glimpse of one perching in its nest. ”
Performance analysis of relay systems under cascaded Nakagami channels

In this paper, error performance of a cooperative relay system using amplify and forward method is investigated when channels between source, relay and destination have cascaded Nakagami distribution. General pairwise error probability of the system is derived and effective and asymptotic diversity orders are investigated for some special cases. Bit error probability curves are obtained by computer simulations.
Implementation of a high reliable chirp underwater acoustic modem

With the increase of applications on underwater wireless sensor networks (UWSN), reliability of underwater communication (UWC) has become increasingly demanding. In this paper, a new underwater acoustic modem prototype design based M-ary different chirp spread signals (MCSS) is presented. Through sea test, it is verified that under low SNR shallow water environment, the modem can achieve error-free communication at distance of 212m with data rate of 300 bps, and the transmission power consumption is no more than 0.97 W. From these observations, it might be utilized for the wide applications based on underwater acoustic communication.