Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Energy Consumption Scheduling for Connected Microgrids Under Demand Uncertainty

Energy consumption scheduling to achieve low-power generation cost and a low peak-to-average ratio is a critical component in distributed power networks. Implementing such a component requires the knowledge of the whole power demand throughout the network. However, due to the diversity of power demands, this requirement is not always satisfied in practical scenarios. To address this inconsistency, this paper addresses energy consumption scheduling in a distribution network with connected microgrids consisting of a local area with a determined demand and neighboring areas with an uncertain demand. The total cost and peak-to-average ratio minimizations are formulated as a multi objective optimization problem. In addition to a deterministic optimal solution, an adaptive scheduling approach is provided with online stochastic iterations to capture the randomness of the uncertain demand over time. Numerical results demonstrate the effectiveness of the proposed adaptive scheduling schemes in the following results obtained from optimal solutions.
Improved Distributed Turbo Code for Relay Channels

In this paper, two improved distributed turbo coded (DTC) schemes, namely, superposition DTC scheme and punc- tured DTC scheme, are proposed for a two-hop relay system using decode-and-forward protocol. The performance of a communica- tion system using relay mainly depends on the successful decoding of source information at the relay. The proposed techniques increase the decoding success rate at the relay thanks to the unique encoding procedures used at the source to relay link. Here, the input information symbols are first encoded using two rate 1/2 parallel concatenated recursive systematic convolutional (RSC) encoders, and the two parity streams of the two RSC encoders are converted into one stream by superposition and puncturing in the proposed superposition DTC scheme and punctured DTC scheme, respectively. Simulation results show that the error performance of the proposed superposition DTC scheme and the punctured DTC scheme are superior to the conventional DTC scheme by around 1.2 and 0.8 dB respectively.
Three Non-Bayesian Methods of Spam Filtration: CRM114 at TREC 2007

For the TREC 2007 conference, the CRM114 team considered three non­Bayesian methods of spam filtration in the CRM114 framework – an SVM based on the “hyperspace” feature==document paradigm, a bit­entropy matcher, and substring compression based on LZ77. As a calibration yardstick, we used the well­tested and widely used CRM114 OSB markov random field system (basically unchanged since 2003). The results show that the SVM has a spam­filtering accuracy of about a factor of two to three better accuracy than the OSB system, that substring compression is somewhat more accurate than OSB, and that bit entropy is somewhat less accurate for the TREC 2007 test sets.
Appendicostomy stomas and antegrade colonic irrigation after laparoscopic antegrade continence enema.

BACKGROUND Children with spina bifida, high anorectal anomalies, or neuronal intestinal dysplasia who are treated with a laparoscopic antegrade continence enema to achieve a socially acceptable level of fecal continence sometimes have problems with the stoma and its catheterization. The goal of this study was to determine the nature and incidence of these problems, and their relationship to the underlying condition. MATERIALS AND METHODS A retrospective review of the hospital case notes of 74 consecutive patients who had a laparoscopic antegrade continence enema was undertaken. RESULTS The laparoscopic antegrade continence enema procedure is well tolerated but is associated with a variety of usually minor complications including stomal stenosis, leakage, peristomal infection, granulation tissue overgrowth, mucosal prolapse, abdominal discomfort during irrigation, appendiceal false passage, and ineffective irrigation. Surgical revision of the stoma was required in 19% of the cases in this study, usually because of stenosis and skin overgrowth. Ongoing problems achieving colonic emptying were most likely to occur in patients with an anorectal malformation. CONCLUSION Overall, the laparoscopic antegrade continence enema provides an effective method of facilitating emptying of the bowel. However, it has a high incidence of minor troublesome problems, with stenosis and skin overgrowth of the stoma being the most common. Younger children tend to have more complications and difficulty performing effective irrigation. Children with anorectal malformations were more likely to require surgical revision of the stoma, and often needed ongoing manual evacuation and bowel washouts despite the laparoscopic antegrade continence enema.
BB = BlackBerry or Big Brother: Digital media and the Egyptian revolution

This article examines the use of digital media in the 2011 Egyptian revolution (25 January–11 February), termed by many analysts and commentators a “Facebook revolution”, “Twitter revolution”, “digital revolution” or “electronic revolution”. Such appellations highlight the role of the youth who organized and mobilized for the revolution and the essential role played by digital media. Disengaging from the controversial debate over whether Egypt’s revolution was instigated by social media or simply used them for its purposes, the article demonstrates the uncontestable role that social networks, text messages, and satellite news channels played as a tool of control and manipulation, on the one hand, and a mode of resistance, on the other. Delineating some key reasons why the Egyptian revolution came to be associated with digital media, the article shows the government’s reaction to the threat posed by such media through analysis of a key moment on the night of 27 and 28 January 2011, when the Egyptian govern.
Global asymptotic convergence of nonlinear relaxation equations realised through a recurrent perceptron

Conditions for global asymptotic stability (GAS) of a nonlinear relaxation equation realised by a nonlinear autoregressive moving average (NARMA) recurrent perceptron are provided. Convergence is derived through fixed point iteration (FPI) techniques, based upon a contraction mapping feature of a nonlinear activation function of a neuron. Furthermore, nesting is shown to be a spatial interpretation of an FPI, which underpins a pipelined recurrent neural network (PRNN) for nonlinear signal processing.
Series enlazadas de algunos agregados económicos nacionales y regionales, 1955-2007. Versión 2.1

En este trabajo se construyen series “homogeneas” de VAB a precios corrientes y constantes, empleo y poblacion para Espana y sus regiones durante el periodo 1955-2007. Estas series se obtienen enlazando la Contabilidad Regional del INE con las series elaboradas por Julio Alcalde y colaboradores para la Fundacion BBVA. El “punto de corte” en el que se abandona esta ultima fuente en favor de la anterior como referencia para la construccion de la serie enlazada se determina utilizando un procedimiento que permite estimar cual de las dos series disponibles generara un estimador con menor error cuadratico medio cuando se utiliza como variable dependiente en una regresion sobre una variable independiente arbitraria. La discrepancia entre ambas series que aflora en el momento del enlace se reparte entre los niveles iniciales y las tasas de crecimiento de la serie mas antigua utilizando, en la medida de lo posible, estimaciones externas del valor de las variables de interes a comienzos del periodo muestral.
MATLAB for behavioral scientists

Behavioral scientists use computers in virtually all their workfrom data collection to analysis, presentation, and simulation. However, there has been no book written to date specifically for behavioral scientists on how to program with a general-purpose programming language. MATLAB for Behavioral Scientists is a tremendously valuable textbook that walks behavioral scientists through the computer programming process, using terms that are relevant to their concerns and appreciating their special programming needs. Author David A. Rosenbaum, a cognitive psychologist with a Ph.D. in experimental psychology, introduces Matrix Laboratory (MATLAB), a powerful computer programming language with an active community of users engaged in many branches of science and engineering. Among its many attractive features, MATLAB offers high-level commands for performing calculations with large as well as small data sets and for generating publication-quality graphics. Throughout the text, Rosenbaum presents each new principle with one or more illustrations of usable code. In addition, each chapter begins with suggestions regarding which actions to perform, followed by the commands required to do so. The book easily functions as a reference source so that readers can turn to a section of interest and quickly obtain the information desired. An accompanying Web site lists programs and code output, complete with color, motion, and sound. This textbook will grant behavioral scientists the intellectual freedom to perform virtually any computational function in solving problems, and consequently may allow practitioners to think, write, and speak more clearly.
Acute And Sub-Acute Toxicity Evaluation Of Ethanolic ExtractOf Leucas aspera (Lamiaceae) In Experimental Rats

The present study aimed to evaluate the acute (14 days) and sub-acute (28 days) oral toxicity of ethanolic extract of Leucas aspera (EELA) on albino mice and adult Wistar rats. Acute dosage was 2000mg/kg body weight while sub-acute dosage was 100, 200 and 400 mg/kg b.w. per day of the extract. All morphological, biochemical, hematological changes, in addition to mortality and body weight changes were recorded. Histopathological study was done on vital organs. EELA did not show mortality up to 2g/kg b.w. in the acute toxicity studies. The sub-acute toxicity study demonstrated no significant changes in body weight, food, and water intake. Hematological parameters and biochemical analytes inclusive of glucose, urea, creatinine, total cholesterol, total protein and total bilirubin did not show statistically significant differences between the control and treated groups while the activities of aminotransferases was slightly increased in group IV (P < 0.001) animals. No morphological changes were observed in the histopathological analysis of the major vital organs (liver, kidney, heart, spleen, lungs and brain) tested. In conclusion, the results of this study suggest the non-toxic nature of the ethanolic extract of Leucas aspera at normal therapeutic doses.
Viewpoint Good Calories , Bad Calories by Gary Taubes ; New York : AA

brayga@pbrc.edu Summary Good Calories, Bad Calories has much useful information and is well worth reading. Gary Taubes’s tenets related to obesity can be summarized in four statements (i) He believes that you can gain weight and become obese without a positive energy balance; (ii) He also believes that dietary fat is unimportant for the development of obesity; (iii) Carbohydrate, in his view, is what produces obesity and (iv) Insulin secreted by the carbohydrate is the problem in obesity. However, some of the conclusions that the author reaches are not consistent with current concepts about obesity. There are many kinds of obesity, and only some depend on diet composition. Two dietary manipulations produce obesity in susceptible people: eating a high-fat diet and drinking sugaror high-fructose corn syrupsweetened beverages. Insulin is necessary but not sufficient in the diet-dependent obesities. When diet is important, it may be the combination of fat and fructose (the deadly duo) that is most important. Regardless of diet, it is a positive energy balance over months to years that is the sine qua non for obesity. Obese people clearly eat more than do lean ones, and food-intake records are notoriously unreliable, as documented by use of doubly labelled water. Underreporting of food intake is greater in obese than in normal-weight people and is worse for fat than for other macronutrient groups. Accepting the concept that obesity results from a positive energy balance does not tell us why energy balance is positive. This depends on a variety of environmental factors interacting with the genetic susceptibility of certain individuals. Weight loss is related to adherence to the diet, not to its macronutrient composition.
Prevalence of Medical Illness in Patients with Anxiety Disorders

Objective: This investigation examines the prevalence and characteristics of medical illness in 711 patients enrolled in the Harvard/Brown Anxiety Disorders Research Program (HARP), a multi-center, longitudinal study of anxiety disorders. Method: Elligible subjects were those with present or past index anxiety disorders: panic disorder without agoraphobia, panic disorder with agoraphobia, agoraphobia without panic disorder, social phobia, or generalized anxiety disorder. They were assessed by trained raters using structured diagnostic interviews and the Medical History Form II. Results: Patients with panic disorder and co-morbid major depressive disorder had significantly higher rates of reported medical illness than anxiety disorder patients without depression. When the rates of medical illness for all subjects were compared with those from the Rand Health Insurance Experiment, we found the prevalence of several medical problems to be disproportionately increased. Conclusions: Although our results are preliminary, it appears that patients with panic disorder have more reported medical problems than the public at large, in particular, more ulcer disease, angina, and thyroid disease. Somatic complaints in patients with panic disorder, therefore, need to be carefully considered.
Intrahousehold Bargaining Power and Leisure Externalities using the PSID 1968-2011

Using a collective model of labor supply and the methodology of Vermeulen et al. (2006), I estimate intrahousehold bargaining power and leisure externalities from observed labor supply decisions and income in the Panel Study of Income Dynamics. This analysis provides several contributions to the collective model literature. First, I consider a large time period (1968-2011) – a scale rarely approached in this literature. Subsequently, I use this estimation to look at how intrahousehold bargaining power and leisure externalities have changed over time. I find an increasing and concave time profile to male intrahousehold bargaining power, which can be mapped to dramatic changes in the female labor market in the last 40 years. I also find that women’s preference for shared leisure is higher than but converging on men’s, with both preferences exhibiting decreasing and convex profiles over this same time period. Estimates of preferences over a leisure interaction are large in magnitude relative to preferences over private leisure, suggesting that models considering only private leisure are not sufficiently rich to capture the interdependence of labor choices in the household. Heterogeneity across households in intrahousehold bargaining power and preferences over shared leisure is also considered.1 I would like to thank my advisor Pierre-André Chiappori for the countless hours of discussion. I am grateful for his help in making accessible such an important literature on intrahousehold allocations and labor supply. I would also like to thank Lena Edlund for her insights on various drafts, and my thesis class for sitting through presentations of varying quality as my thesis took shape. Finally, many thanks to Frederic Vermeulen for taking the time to discuss his 2006 paper – a work whose methodology forms the backbone of my thesis.
Viewpoint Invariant Action Recognition Using RGB-D Videos

Due to the differences in the appearance of an action from different viewpoints, variations in camera viewpoints often result in major problems for video-based action recognition. This paper exploits the complementary information in RGB and Depth streams of RGB-D videos to address those problems. We capitalize on the spatio-temporal information in the two data streams to extract action features that are largely insensitive to variations in camera viewpoints. We use the RGB data to compute dense trajectories that are translated to viewpoint insensitive deep features under a non-linear knowledge transfer model. Similarly, the Depth stream is used to extract convolutional neural network-based view invariant features on which Fourier Temporal Pyramid is computed to incorporate the temporal information. The heterogeneous features from the two streams are combined and used as a dictionary to predict the label of the test samples. To that end, we propose a sparse-dense collaborative representation classification scheme that strikes a balance between the discriminative abilities of the dense and the sparse representations of the samples over the extracted heterogeneous dictionary. To establish the effectiveness of our approach, we evaluate its performance on three public datasets and benchmark it against 12 existing techniques. Experiments demonstrate that our approach achieves up to 7.7% improvement in the accuracy over its nearest competitor.
Antibody-conjugated Gold Nanoparticles integrated in a fluorescence based Biochip

Gold nanoparticles exhibit remarkable optical properties and could prove useful in sensitive biosensing applications. Upon illumination gold nanoparticles produce localized surface plasmons, which influence nearby fluorophores and an enhancement in their fluorescence intensity can be observed. This property makes gold nanoparticles attractive for enhancing optical signals. In this project gold nanoparticles were functionalized with an antibody and immobilized to the surface of an existing biochip platform based on fluorescence. The aim was to investigate the possibility of obtaining an increased fluorescence signal from the gold nanoparticles. Two different conjugation procedures were investigated, direct physisorption and covalent attachment of the antibodies to the particles. Activity of bound antibodies was confirmed in both cases. The on-chip fluorescence intensity produced by the different conjugates was monitored by use a specialized fluorescence reader designed for point-of-care use. AFM and SEM were used to determine the surface concentration of particles. A correlation between the produced fluorescence intensity and the surface concentration could be seen.
Individual isotoxic radiation dose escalation based on V20 and advanced technologies benefits unresectable stage III non-small cell lung cancer patients treated with concurrent chemoradiotherapy: long term follow-up

Under the assumption that the highest therapeutic ratio could be achieved by increasing the total tumor dose (TTD) to the limits of normal tissues, the phase I trial was conducted in patients with unresectable stage III non-small cell lung cancer treated with concurrent chemoradiotherapy, to determine the feasibility and effects of individual isotoxic radiation dose escalation based on bilateral lung V20 and advanced technologies. Consecutive eligible patients were assigned to cohorts of eight. V20 of each cohort was increased from 27% to 30%, 33%, 35%, 37%, and so on. The criterion for cessation of dose escalation was defined as ≥ 2 patients in each cohort experienced dose limiting toxicity. Isotoxic dose escalation was based on V20, functional imaging was used to improve the accuracy of radiotherapy. To test the power of escalation dose, patients with TTD over 66 Gy were assigned to the higher dose group (HD), while the others to the standard dose one (SD). In result, the recommended value of V20 was 35%. For all patients, follow-up ranged from 1 to 112 months, median overall and progression free survivals were 25.0 and 13.0 months, respectively. The 1-, 3-, 5- and 8-year overall survival (OS) rates were 72.5%, 22.5%, 17.5%, and 10.0%, respectively. Especially, the OS and local recurrence-free survival of patients in HD group were significantly longer than those in SD one (P=0.035, P=0.007, respectively) without increasing severe toxicity. Thus, individual isotoxic dose escalation based on V20 with advanced technologies was feasible and effective.
SPATIAL-SPECTRAL CROSS-CORRELATION FOR CHANGE DETECTION ---A CASE STUDY FOR CITRUS COVERAGE CHANGE DETECTION

Citrus tree change detection is of great importance for citrus production (inventory) analysis and forecasting. The National Agricultural Statistics Service’s recent citrus GIS modernization effort built the GIS infrastructure for the entire State of Florida. To detect changes in citrus acreage, it is necessary to detect not only the land coverage changes between the citrus groves and other land uses, but also the changes in the existing citrus groves, such as tree removal, tree replacement, abandonment or new plantings. There are many change detection techniques applicable if proper imagery is available. However, the data available to our program is collected from different cooperating Florida State Agencies and they originate from different sensors with differences in radiometric, dynamic range, spatial resolution and spectral bands. Spectral signature correlation is one of the spectral based change detection methods, which can overcome radiometric and dynamic range differences. However, it does not solve the mixedpixel effect caused by resolution difference. In this paper, a spatial-spectral cross-correlation method is presented. This method generalized correlation coefficients defined in a spatial domain or a spectral domain into a spatialspectral domain. It has shown that either spatial or spectral correlation coefficients are a special case of spatialspectral cross-correlation coefficients. This method is spatial-spectral signature based; it is invariant to the dynamic range and robust to radiometric difference, the noise and the mixed-pixel effect; yet it is straightforward with minimum preprocessing required. Finally, experimental results will be presented as a comparison between spatialspectral correlation and spectral correlation methods.
Development of a consensus microarray method for identification of some highly pathogenic viruses

Some highly pathogenic viruses, such as Chikungunya virus, Japanese encephalitis virus, Yellow fever virus, Dengue virus, Hanta virus, SARS‐CoV, and H5N1 avian influenza virus can cause severe infectious diseases. However, the consensus method for detecting these viruses has not been well established. A rapid and sensitive microarray approach for detection of these viruses and a panel of specific probes covering nine genera and 16 virus species were designed. 70‐mer oligonucleotides were used at the genus level and 50‐mer oligonucleotides were at the species level, respectively. To decrease the interference of the host genome in hybridization, the consensus genus primers were designed and used to reverse transcribe only virus genome. The synthesis of the second strand was carried out with a random primer sequence (5′‐GTTTCCCAGTAGGTCTCNNNNNNNN‐3′). The amplified products were labeled and processed for microarray analyses. This microarray‐based method used the highly conserved consensus primers to synthesize specifically the virus cDNA and could identify effectively Chikungunya virus, Japanese encephalitis virus, Yellow fever virus, Dengue virus, Tick borne encephalitis virus, and H5N1 avian influenza virus. Using this method, one unknown virus isolated from pig brain in Shanxi Province, China was identified. This method may have an important potential application for the diagnosis of virus infection. J. Med. Virol. 81:1945–1950, 2009. © 2009 Wiley‐Liss, Inc.