Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of wireless multi-media sensor network for precision agriculture

To satisfy the needs of modern precision agriculture, a Precision Agriculture Sensing System (PASS) is designed, which is based on wireless multi-media sensor network. Both hardware and software of PASS are tailored for sensing in wide farmland without human supervision. A dedicated single-chip sensor node platform is designed specially for wireless multi-media sensor network. To guarantee the bulky data transmission, a bitmap index reliable data transmission mechanism is proposed. And a battery-array switching system is design to power the sensor node to elongate the lifetime. The effectiveness and performance of PASS have been evaluated through comprehensive experiments and large-scale real-life deployment.
A SPICE-Oriented Method for Finding DC Operating Points of Nonlinear Circuits Containing Piecewise-Linear Macromodels

Recently, efficient algorithms have been proposed for finding all characteristic curves of one-port piecewise-linear (PWL) resistive circuits. Using these algorithms, a middle scale one-port circuit can be represented by a PWL resistor that is neither voltage nor current controlled. By modeling often used one-port subcircuits by such resistors (macromodels), large scale circuits can be analyzed efficiently. In this paper, an efficient method is proposed for finding DC operating points of nonlinear circuits containing such neither voltage nor current controlled resistors using the SPICE-oriented approach. The proposed method can be easily implemented on SPICE without programming
Coordinating Monetary and Financial Regulatory Policies

How to conduct macro-prudential regulation? How to coordinate monetary policy and macro-prudential policy? To address these questions, I develop a continuous-time New Keynesian economy in which a financial intermediary sector is subject to a leverage constraint. Coordination between monetary and macro-prudential policies helps to reduce the risk of entering into a financial crisis and speeds up exit from the crisis. The downside of coordination is variability in inflation and in the employment gap. JEL Classification: E31, E32, E44, E52, E61, G01
Morphometric Analysis of Nucleus and Nucleolar Organizer Regions (NORs) in Tongue Squamous Cell Carcinoma (SCC)

La lengua es probablemente, el lugar en donde mas frecuentemente surge el carcinoma primario de celulas escamosas (SCC), en el mundo occidental. Este estudio propone realizar la evaluacion morfometrica del nucleo celular, asi como el analisis morfometrico de las regiones de los organizadores nucleolares (NORs). La muestra de biopsia fue removida de pacientes con SCC de lengua, etapificado en T2N0M0, antes de recibir tratamiento. Los pacientes fueron sometidos a una hemiglosectomia y una diseccion supraomohiodea del cuello (SOHND) y presentaron diferente evolucion clinica. De acuerdo a esto, fueron subdividos en tres grupos: Grupo A, grupo control formado por pacientes sin neoplasia de lengua (la muestra fue obtenida del Departamento de Patologia del Hospital Base de la Facultad de Medicina de Sao Jose do Rio Preto - FAMERP-HB, Brasil); Grupo B, T2N0M0 + hemiglosectomia + SOHND, sobrevida de 36 meses; Grupo C, T2N0M0 + hemiglosectomia + SOHND, sobrevida 5 anos. El estudio morfometrico incluyo los analisis del diametro mayor, diametro menor, diametro medio, la relacion entre el diametro mayor/menor, perimetro, area, volumen, relacion volumen/area, idiosincrasia, coeficiente de forma y el indice de contorno nuclear de celulas tumorales en pacientes con SCC de lengua, asi tambien las mismas mediciones de las regiones nucleolares organizadas. El analisis fue aleatorio y doble ciego. Todos los datos morfometricos fueron recopilados y evaluados estadisticamente con el test de Kruskall-Wallis y el Test ANO VA, con un valor alfa de un 5%
Ebola Virus VP 35 Protein Binds Double-Stranded RNA and Inhibits Alpha / Beta Interferon Production Induced by RIGI Signaling

Department of Microbiology, Mount Sinai School of Medicine, New York, New York 10029; Department of Microbiology, University of Texas Southwestern Medical Center, Dallas, Texas; Special Pathogens Branch, Division of Viral and Rickettsial Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, 1600 Clifton Road, MS G-14, Atlanta, Georgia 30329; and Department of Immunology, The Scripps Research Institute, 10550 North Torrey Pines Rd., La Jolla, California 92037
Influence of Chlormethiazole on Cerebral Blood Flow and Oxygen Consumption in the Rat, and its Effect on the Recovery of Cortical Energy Metabolism after Pronounced, Incomplete Ischaemia

The influence of an anaesthetic dose of chlormethiazole (Heminewino) on blood flow (CBF) and oxygen consumption (CMRo2) in the rat brain was investigated. In spontaneously breathing animals a dose of 160 mg.kg‐1 of chlormethiazole, infused i.v. , induced a state close to surgical anaesthesia. In paralyzed animals, the same dose decreased CBF and CMRo2 to about 60% of control, an effect similar to that observed after an anaesthetic dose of phenobarbitone. Neither a protective nor a detrimental effect of chlormethiazole could be demonstrated when the drug was given during reversible and pronounced, incomplete ischaemia, as evaluated from the postischaemic tissue concentrations of labile phosphates (PCr, ATP, ADP, AMP) and of lactate and pyruvate. It is concluded that protection in this situation (as earlier shown with phenobarbitone) must, at least partly, be related to other mechanisms than a depression of metabolism.
Genome wide selection and new methods of maize breeding

Genome wide selection and new methods of maize breeding The objectives of this work were to verify the accuracy of the Genome Wid Selection method (GWS) in the maize breeding for nutritional stress conditions and propose new breeding methods based on GWS. The efficiency of two components of use of nitrogen and phosphorus (absorption and utilization) was estimated in 41 single-cross hybrids assessed in two experiments under low and high availability of N and P . Eighty microsatellite markers were used to genotype the base population. The estimates of genetic parameters were obtained by REML/BLUP and the predictions of genetic genomic values were obtained by random regression (RR), applied to genome wide selection (RR-BLUP/ GWS). GWS showed high values of accuracy for the traits; it was comparable to the methods of Recurrent Intra and Interpopulational Selection. It was concluded that there is a significant increase in selective accuracy and in the genetic gains per unit of time with use of GWS.
Tuning machine learning algorithms for content-based movie recommendation

Machine learning algorithms are often used in content-based recommender systems since a recommendation task can naturally be reduced to a classification problem: A recommender needs to learn a classifier for a given user where learning examples are characteristics of items previously liked/bought/seen by the user. However, multi-valued and continuous attributes require special approaches for classifier implementation as they can significantly influence classifier accuracy. In this paper we propose novel approaches for handling multi- valued and continuous attributes adequate for the naive Bayes classifier and decision trees classifier, and tune it for content-based movie recommendation. We evaluate the performance of the resulting approaches using the MovieLens data set enriched with movie details retrieved from the Internet Movie Database. Our empirical results demonstrate that the naive Bayes classifier is more suitable for content-based movie recommendation than the decision trees algorithm. In addition, the naive Bayes classifier achieves better results with smart discretization of continuous attributes compared to the approach which models continuous attributes with a Gaussian distribution. Finally, we combine our best performing content-based algorithm with the k-means clustering algorithm typically used for collaborative filtering, and evaluate the performance of the resulting hybrid approach for a movie recommendation task. The experimental results clearly show that the hybrid approach significantly increases recommendation accuracy compared to collaborative filtering while reducing the risk of over specification, which is a typical problem of content-based approaches.
Studying addicts over time: methodology and preliminary findings.

This preliminary report of findings pertaining to the “natural history” of narcotic addiction was based on a systematic random sample of males identified as narcotic abusers by the Baltimore City Police Department over a twenty year period (1952–71) and thus differs from other studies of addiction in that it represents a community-wide population of narcotic users. The sample was stratified by year of identification as well as by race and consisted of equal numbers of blacks and whites.Personal interviews with subjects were conducted using a structured questionnaire, and a special staff was used to locate and obtain permission to interview. Of the 349 persons in the sample, 343 were located, with a substantial proportion being out-of-state. Among the 343 located, 57 were dead, two were psychotic, six were not located, and 17 refused to be interviewed. Thus, 267 of the 290 potentially interviewable subjects were actually interviewed, which represents an interview response rate of 92%. The mean age for the e.
Environmental impact assessment of a sewage treatment plant under different operating conditions

Environmental impact assessments of sewage treatment plants should consider not only emissions of greenhouse gases (GHG) from electricity use, but also N2O emissions generated by nitrogen removal processes, and the release of nitrogen nutrients into the water environment. Additionally, ecotoxicity of unionized ammonia is high, however no existing environmental impact assessment methodology addressed it. This study developed a methodology to evaluate the ecotoxicity of NH3 in the context of life cycle assessment. Nitrogen flow was measured in functioning sewage plants, allowing the environmental impact of changes in operating conditions, such as nitrificationinhibited or nitrification-promoted operation, to be compared. Result showed that in consideration of integrated environmental impacts, taking into account nitrogen emissions from discharge water and GHG emissions, nitrification-promoted operation is more preferable than nitrification-inhibited operation.
Optimal referent selection strategies in case-crossover studies: a settled issue.

I n this issue of EPIDEMIOLOGY, Janes et all present a comprehensive review of referent selection strategies in case-crossover analyses of air pollution data. This review is timely, given the increasing popularity of the case-crossover approach, and makes an important contribution to the field. As for other substantive areas of epidemiology, concerns over the validity of estimates of the short-term health effects of air pollution are paramount. Thus, study design decisions and analytic approaches should be engineered to maximize efficiency to the extent possible without introducing inordinate bias. The authors did an excellent job of summarizing insights regarding the importance of careful selection of referent periods to minimize potential biases, including those that arise from time trends in exposure, truncation of the air pollution data at the start and end of the exposure time series, and violations of the assumptions inherent in the conditional logistic likelihood that result in "overlap bias. " The arguments put forth by Janes and colleagues convincingly show that, although other approaches may be valid under certain circumstances, the time-stratified selection strategy is more generally valid than any of the alternatives thus far proposed. Thus, this strategy should be considered the de facto standard approach to the analysis of data arising in studies of the short-term effect of air pollution and weather. The caution against "model shopping" is an extremely important one, but it must be distinguished from the concept of sensitivity analysis. Conducting several analyses and "cherry picking" results (ie, presenting only the subset of results that look the most "interesting" to the investigator) clearly is problematic and is likely to lead to the presentation of spuriously extreme effect estimates. However, assuming one considers only approaches that have been shown to be generally valid, it is reasonable for investigators to conduct sensitivity analyses. For example, when conducting a time-stratified case-crossover analysis, the length of the time strata should be chosen subject to the best judgment of the analyst. In studies of short-term health effects of air pollution, investigators have most commonly chosen strata defined by calendar month. >6 This is clearly a convenient choice that is easy to implement. However, an implicit assumption is that time-dependent confounders, such as season, or respiratory illness outbreaks are relatively constant within a calendar month. It is possible that strata of 2 or 3 weeks duration may better control for such confounding or that longer periods of up to 6 weeks might control confounding as well, but be more efficient.
A MIMO antenna with improved isolation using RFC for LTE mobile application

Multi-input Multi-output (MIMO) antenna with improved isolation using radio frequency choke (RFC) is proposed. By using RFC, the RF signal was suppressed at the desired frequency band, to improve the isolation between the two radiating elements. The isolation between the two radiating elements is improved by approximately 20 dB at the center frequency. The fabricated antenna has a VSWR below 3 and an envelope correlation coefficient below 0.4 in the long term evolution (LTE) band 13 from 746 MHz to 787 MHz.
Effect of dietary fat saturation on LDL oxidation and monocyte adhesion to human endothelial cells in vitro.

Forty-two healthy men and women were subjected to four consecutive dietary periods differing in the fat content of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (n-6) [PUFA(n-6)] and (n-3) [PUFA(n-3)]. Plasma lipids, vitamin E, and in vitro LDL oxidation were examined during each period. Adhesion of human monocytes to cultured human endothelial cells was used as a functional test to identify differences in the biological properties of LDL from each dietary period. Consumption of an SFA-rich diet resulted in higher LDL cholesterol (4.06 +/- 0.85 mmol/L, P < .05) than did consumption of MUFA- (3.59 +/- 0.75 mmol/L), PUFA(n-6)- (3.44 +/- 0.77 mmol/L), or PUFA(n-3)- (3.31 +/- 0.8 mmol/L) rich diets. HDL cholesterol was lower during both PUFA-rich diets (1.24 +/- 0.28 and 1.27 +/- 0.28 mmol/L for n-6 and n-3, respectively) than during the SFA-(1.32 +/- 0.36 mmol/L) and MUFA- (1.32 +/- 0.34 mmol/L) rich diets. LDL resistance to copper-induced oxidation, expressed as lag time, was highest during the MUFA-rich diet (55.1 +/- 7.3 minutes) and lowest during the PUFA(n-3)- (45.3 +/- 7 minutes) and SFA- (45.3 +/- 6.4 minutes) rich diets. LDL induction of monocyte adhesion to endothelial cells was lower during the MUFA-rich diet than the other periods. The highest monocyte adhesion was obtained during the PUFA(n-3) and SFA dietary periods. In conclusion, an MUFA-rich diet benefits plasma lipid levels compared with an SFA-rich diet. Furthermore, this diet results in an increased resistance of LDL to oxidation and a lower rate of monocyte adhesion to endothelial cells than the other dietary fats examined.
Cumulative Intracranial Tumor Volume (CITV) Enhances the Prognostic Value of the Lung-Specific Graded Prognostic Assessment (GPA) Model.

BACKGROUND Management of patients afflicted with brain metastasis requires tailoring of therapeutic strategies based on survival expectations. Therefore, the development of prognostic indices is of critical importance in this patient population. OBJECTIVE To determine whether the cumulative intracranial tumor volume (CITV) of brain metastasis augments the prognostic value of the lung-specific Graded Prognostic Assessment (GPA) index. METHODS Patient data were derived from 365 lung cancer patients with brain metastasis who were consecutively treated with stereotactic radiosurgery at the University of California, San Diego/San Diego Gamma Knife Center. CITV was analyzed to determine the volume cutoff that maximized sensitivity and specificity for 1-year survival. Multivariate Cox proportional hazard modeling was performed, and overall survival was estimated by the Kaplan-Meier method risk stratifying with or without this optimal CITV. The prognostic value of these models (lung-specific GPA ± CITV) was quantitatively compared with the use of net reclassification improvement (>0) and integrated discrimination improvement. RESULTS For the University of California, San Diego/San Diego Gamma Knife Center cohort, the CITV cutoff that had the greatest survival discrimination at 1 year was 4 cm. The addition of CITV to the lung-specific GPA indexes significantly improved the prognostic value of lung-specific GPA, with net reclassification improvement >0 of 0.430 (95% confidence interval, 0.228-0.629) and integrated discrimination improvement of 0.029 (95% confidence interval, 0.004-0.073). These findings were validated in an independent cohort of 1638 lung cancer patients with brain metastasis who were treated with stereotactic radiosurgery at the Katsuta Hospital Mito Gamma House in Japan. CONCLUSION In independent cohorts, the addition of CITV to the lung-specific GPA index significantly improved the prognostic value of this index. ABBREVIATIONS AUC, area under the receiver-operating characteristic curveBM, brain metastasisCITV, cumulative intracranial tumor volumeds-GPA, disease-specific Graded Prognostic AssessmentGPA, Graded Prognostic AssessmentIDI, integrated discrimination improvementKHMGH, Katsuta Hospital Mito Gamma HouseKPS, Karnofsky Performance StatusNRI, net reclassification improvementROC, receiver-operating characteristic curveSRS, stereotactic radiosurgeryUCSD/SDGKC, University of California, San Diego/San Diego Gamma Knife Center.
Appropriate interaction of the microgrid and main network by using unidirectional fault current limiters

Penetration of Distributed Generation (DG) increases continually in electric networks. Adding new DG units in a grid connected microgrid may result in exceeding fault current level above the rating of existing network's equipment and upset coordination of Overcurrent Relays (OCRs). Utilizing Fault Current Limiters (FCLs) between the microgrid (downstream) and main grid (upstream) is a well known approach to overcome the above-mentioned problems. Power Quality (PQ) and coordination between the upstream and downstream OCRs are affected by the conventional bidirectional FCL in case of fault in downstream. In this paper, utilization of Unidirectional Fault Current Limiters (UFCLs) is proposed to achieve an appropriate interaction between the upstream and downstream in a Meshed Distribution System (MDS). Different current limiting scenarios are analyzed to find the best performance of the installed FCLs with regards to the coordination of the OCRs and improvement of microgrid power quality.
ISSE : An

Traditional audio editing tools do not facilitate the task of sep­ arating a single mixture recording (e.g. pop song) into its re­ spective sources (e.g. drums, vocal, etc.). Such ability, how­ ever, would be very useful for a wide variety of audio appli­ cations such as music remixing, audio denoising, and audiobased forensics. To address this issue, we present ISSE–an interactive source separation editor. ISSE is a new opensource, freely available, and cross-platform audio editing tool that enables a user to perform source separation by painting on time-frequency visualizations of sound, resulting in an in­ teractive machine learning system. The system brings to life our previously proposed interaction paradigm and separation algorithm that learns from user-feedback to perform separa­ tion. For evaluation, we conducted user studies and compared results between inexperienced and expert users. For a variety of real-world tasks, we found that inexperienced users can achieve good separation quality with minimal instruction and expert users can achieve state-of-the-art separation quality. Author
Enhanced performance in prediction of protein active sites with THEMATICS and support vector machines

Theoretical microscopic titration curves (THEMATICS) is a computational method for the identification of active sites in proteins through deviations in computed titration behavior of ionizable residues. While the sensitivity to catalytic sites is high, the previously reported sensitivity to catalytic residues was not as high, about 50%. Here THEMATICS is combined with support vector machines (SVM) to improve sensitivity for catalytic residue prediction from protein 3D structure alone. For a test set of 64 proteins taken from the Catalytic Site Atlas (CSA), the average recall rate for annotated catalytic residues is 61%; good precision is maintained selecting only 4% of all residues. The average false positive rate, using the CSA annotations is only 3.2%, far lower than other 3D‐structure‐based methods. THEMATICS–SVM returns higher precision, lower false positive rate, and better overall performance, compared with other 3D‐structure‐based methods. Comparison is also made with the latest machine learning methods that are based on both sequence alignments and 3D structures. For annotated sets of well‐characterized enzymes, THEMATICS–SVM performance compares very favorably with methods that utilize sequence homology. However, since THEMATICS depends only on the 3D structure of the query protein, no decline in performance is expected when applied to novel folds, proteins with few sequence homologues, or even orphan sequences. An extension of the method to predict non‐ionizable catalytic residues is also presented. THEMATICS–SVM predicts a local network of ionizable residues with strong interactions between protonation events; this appears to be a special feature of enzyme active sites.
Benefits of neuroeconomic modeling: New policy interventions and predictors of preference

Neuroeconomics strives to use knowledge from neuroscience to improve models of decisionmaking. Here we introduce a biologically plausible, drift-diffusion model that is able to jointly predict choice behavior and response times across different choice environments. The model has both normative and positive implications for economics. First, we consistently observe that decisionmakers inefficiently allocate their time to choices for which they are close to indifference. We demonstrate that we can improve subjects' welfare using a simple intervention that puts a time limit on their choices. Second, response times can be used to predict indifference points and the strength of preferences.
Twitter Author Profiling Using Word Embeddings and Logistic Regression

The general goal of the author profiling task is to determine various social and demographic aspects of the author based on his pieces of writing. In this work, we propose an approach that combines word embeddings and classical logistic regression for identifying author gender and language variety based on the corresponding tweets. The model was trained on PAN 2017 Twitter Corpus that contains data for English, Spanish, Portuguese and Arabic languages from more than 11 thousand authors. Due to its simplicity, the proposed solution can be treated as a baseline for both gender and language variety identification subtasks.