Miracle-dz/UniFAR-FTUs huggingface dataset:
Multipurpose Energetic Materials by Shuffling Nitro Groups on a 3,3'-Bipyrazole Moiety.

A family of 3,3'-bipyrazole-based energetic compounds having C-NO2 /N-NO2 functionalities was synthesized by using various nitrating conditions. These nitro derivatives of bipyrazole are significantly more dense and energetic compared to the corresponding nitropyrazole analogues while maintaining the desired thermal stability and sensitivity. Depending on the number and nature of energetic nitro groups (C-NO2 /N-NO2 ), different classes of energetic materials, such as green primary explosives, high-performance secondary explosives and heat-resistant explosives, were obtained. All the compounds were thoroughly characterized by IR, NMR [1 H, 13 C{1 H}, 15 N], elemental analysis, and differential scanning calorimetry (DSC). Four were also structurally characterized with single-crystal X-ray diffraction studies. Heats of formation and detonation performance were calculated using Gaussian 03 and EXPLO5 v6.01 programs, respectively.
Public Speaking for Engineering Students in a Blended Learning Environment

Effective teaching and learning processes are made possible as information and communication technology (ICTs) tools are used to support the environment. Today, apart from a fully face-to-face or online environment, blended learning promises opportunities for teaching and learning to be done in both environments. This study employed the quasi-experimental, pretest-posttest design to investigate the effects of blended learning in reducing anxiety and improving public speaking skills of ESL learners. Fifty-six students, enrolled in the fifth semester of the Bachelor in Civil Engineering program at a technical university in Malaysia, were involved in the study. The Personal Report of Public Speaking Anxiety (PRPSA) was administered as the pre and post test to measure the students' level of anxiety pertaining to public speaking. The Competent Speaker Speech Evaluation Form (CSSEF) was used as an instrument to measure the students' public speaking performance at pre and post conditions. The findings indicate that blended learning environment does have a positive impact in the development of public speaking skills of these students.
Exploring the Impact of Password Dataset Distribution on Guessing

Leaks from password datasets are a regular occur-rence. An organization may defend a leak with reassurances that just a small subset of passwords were taken. In this paper we show that the leak of a relatively small number of text-based passwords from an organizations' stored dataset can lead to a further large collection of users being compromised. Taking a sample of passwords from a given dataset of passwords we exploit the knowledge we gain of the distribution to guess other samples from the same dataset. We show theoretically and empirically that the distribution of passwords in the sample follows the same distribution as the passwords in the whole dataset. We propose a function that measures the ability of one distribution to estimate another. Leveraging this we show that a sample of passwords leaked from a given dataset, will compromise the remaining passwords in that dataset better than a sample leaked from another source.
The impact on internship of a tailored intern preparation package

Introduction On commencing internship, new medical graduates (new interns) are often required to perform core procedural skills under differing levels of supervision. This variability of knowledge and experience with procedural skills can place patient safety at risk. Consequently, in 2012, we developed a targeted, intensive, 3-day training course for our pre-intern (PrInt) students. The aim of this study was to evaluate the intern preparation package by exploring interns’ self-reported knowledge, confidence, and experience in key procedural skills during the early months of internship. Methods Between 2012 and 2016, 5 cohorts of PrInt students (n=223) participated in our course. In the following years 2013–2017, the same 5 cohorts, at 4–5 months into their internship, were surveyed anonymously and invited to attend focus groups. Descriptive statistics and thematic analysis were used to analyze data. Results Of the 223 interns, 91 (41%) responded. Of the 91, 82 (93%) agreed that the intern preparation package provided during PrInt had been beneficial to their practice as an intern. Awareness of potential risks to patient safety was high, ranging from infection control at 89/89 (100%) to 87/90 (97%) for patient identification. Confidence in performing procedural skills varied from moderate in identifying nasogastric tube placement on X-ray (66/89; 85%), to equal least confidence in managing cardiac-related emergencies (53/90; 59%) and identifying the correct placement of peripherally inserted central catheter lines on X-ray (52/89; 58%). Major qualitative findings The preparation package had refreshed interns’ procedural skills ability and awareness of risks to patient safety. Integration into the clinical team was positive, but requests to perform procedural skills on day 1 was unexpected. Conclusion Interns reported that they had gained substantial benefit from their preparation package, and they performed practical procedures from day 1, further highlighting the need for an intensive preparation course immediately prior to entering internship.
Defining Patient-Centricity: Opportunities, Challenges, and Implications for Clinical Care and Research

The Patient-Centered Outcomes Research Institute (PCORI), created and funded by the Affordable Care Act, is charged with bringing the patient perspective to clinical research design and the outcomes that are studied. However, there is no consensus definition of “patient-centeredness” or “patient-centricity. ” This paper distinguishes between the terms and describes an infrastructure for supporting the concept of patient-centricity. The patient’s role needs to be described in a way that makes it feasible to implement health care delivery and support parameters to conduct clinical research over a sustained period of time. The authors propose the use of a structured Practice-Based Clinical Research Network to perform patient-centered outcomes research consistent with the requirements of the pharmaceutical sector in a safe, ethical, and effective manner and congruent with the principles of Good Clinical Practice (GCP).
Is downstream cardiac testing required in patients with reduced functional capacity and otherwise negative exercise stress test? A single center observational study

Background Exercise stress testing (EST) in patients with poor functional capacity measured by time on treadmill is typically deemed inconclusive and usually leads to further downstream testing. The aim of this study was firstly to evaluate the maximum rate pressure product (MRPP) during initial EST to assessthe need for follow-up testing; and secondly to investigate if MRPP is better than age predicted maximum heart rate (APMHR) for diagnostic outcome based on follow up cardiovascular (CV) events in patients with inconclusive EST due to poor functional capacity. Methods From a total of 2761 tests performed, 236 tests were considered inconclusive due to poor functional capacity which were available for analysis. From receiver operating characteristic (ROC) analysis, a cut-off value for MRPP of 25000 was chosen using CV events as the outcome measure (sensitivity 97%, specificity 45%). Cases were then categorised into those with an MRPP > 25000 and < 25000. Results Regardless of treadmill time, any patient attaining an MRPP > 25000 had no abnormal downstream testing or CV events at 2 years follow-up. On ROC analysis MRPP outperformed APMHR for sensitivity and specificity (area under curve 0.76 vs. 0.59, respectively). Conclusions The results suggest that regardless of functional capacity, individuals whose EST is terminated at maximal fatigue, with no electrocardiogram evidence or symptoms of myocardial ischemia and yields an MRPP > 25000, do not require further downstream testing. Furthermore, this group of patients, while not immune to future CV events, have significantly better outcomes than those not attaining a MRPP > 25000.
Effects of Long-Term Walnut Supplementation on Body Weight in Free-Living Elderly: Results of a Randomized Controlled Trial

Objective: To assess the effects of chronic walnut consumption on body weight and adiposity in elderly individuals. Methods: The Walnuts and Healthy Aging study is a dual-center (Barcelona, Spain and Loma Linda University (LLU)), 2-year randomized parallel trial. This report concerns only the LLU cohort. Healthy elders (mean age 69 year, 67% women) were randomly assigned to walnut (n = 183) or control diets (n = 173). Subjects in the walnut group received packaged walnuts (28–56 g/day), equivalent to ≈15% of daily energy requirements, to incorporate into their habitual diet, while those in the control group abstained from walnuts. Adiposity was measured periodically, and data were adjusted for in-trial changes in self-reported physical activity. Results: After 2 years, body weight significantly decreased (p = 0.031), while body fat significantly increased (p = 0.0001). However, no significant differences were observed between the control and walnut groups regarding body weight (−0.6 kg and −0.4 kg, respectively, p = 0.67) or body fat (+0.9% and +1.3%, respectively, p = 0.53). Lean body mass, waist circumference, and waist-to-hip ratio remained essentially unchanged. Sensitivity analyses were consistent with the findings of primary analysis. Conclusion: Our findings indicate that walnuts can be incorporated into the daily diet of healthy elders without concern for adverse effects on body weight or body composition.
Hybrid Precoding Design for MIMO System With One-Bit ADC Receivers

When wireless transmission is performed over the bandwidth in the order of a gigahertz, high-resolution analog-to-digital converters (ADCs), and the large number of radio frequency chains significantly increase the power consumption. To address this issue, one promising technique is to use low-resolution, even one-bit ADCs. Another promising technique is to apply a hybrid precoding architecture to reduce the number of RF chains. In this paper, we propose to combine those techniques to reduce the hardware costs in multi-input multi-output system. Our objective is to optimize the hybrid precoder with the aim of increasing the achievable rate. To this end, we first derive an expression for the achievable rate in flat fading channels based on the Bussgang theorem, which is able to reformulate the nonlinear quantitative process as a linear function with identical first- and second-order statistics. To solve the non-convex hybrid precoding design problem, we treat the hybrid precoding design as a matrix factorization problem, which can be solved with an efficient alternating minimization algorithm. That is, we solve the digital precoder and the analog precoder in an alternative way in two separate subproblems. To find the optimal precoder in the first subproblem, we first prove the optimal structure of the digital precoding matrix. With it, we transfer the digital precoding design to a power allocation problem, the closed-form solution of which is then optimally found by using Karush–Kuhn–Tucker conditions. In the second subproblem, due to the non-convex modulus-norm constraint, it is challenging to directly solve the analog precoder. To resolve this problem, we propose to optimize the phases in the analog precoding matrix and adopt the subgradient algorithm to find the local optimal solution. Our simulation results show that the proposed hybrid precoding design effectively improves the achievable rates.
Improving Moderation of Online Discussions via Interpretable Neural Models

Growing amount of comments make online discussions difficult to moderate by human moderators only. Antisocial behavior is a common occurrence that often discourages other users from participating in discussion. We propose a neural network based method that partially automates the moderation process. It consists of two steps. First, we detect inappropriate comments for moderators to see. Second, we highlight inappropriate parts within these comments to make the moderation faster. We evaluated our method on data from a major Slovak news discussion platform.
Charging Demonstrator for Ancillary Service Provision in Smart Grids

The target of this paper is to provide a charging infrastructure design for a carpark scenario which enables demand response (DR) management. The presented system not only allows an optimal charging scheduling to maximize the revenue for the carpark operator, but also enables the participation in DR. Numerous advantages to deploy a smart power sharing charging infrastructure in the future carparks have been discussed in the literature. A smart charging scheduling strategy leads to a better usage of grid power and improves the grid stability. Moreover it benefits the users to charge their own electric vehicle (EV) with lower cost and generates additional revenues for carpark operators. The utilization efficiency of the charging station will also be improved in the meantime.
Fundamental Frequency Extraction and Tone Recognition of Chinese Continuous Two-character-words

Chinese is a language composed of syllables with tones. Initials, finals, and tones are the three main attributes of Chinese syllables. In this paper, continuous two-character-words are segmented through syllables, and the effective segmentation of syllables is performed by using the characteristics of short-time energy and short-time zero-crossing rate of initial. It is useful to extracting the pitch frequency with the autocorrelation function and average amplitude difference function method . This paper proposes a speaker-independent two-character-words fuzzy identification method and uses the main characteristics of the pitch curve to form a fuzzy membership function. The tone recognition algorithm uses the decision function to classify the tone pattern. The method has simple, reliable, and good real-time characteristics.
Investigation of Geometry Dependence of Thermal Resistance and Capacitance in RF SOI MOSFETs

According to the thermal theory, the self-heating effect is equivalent to an R–C thermal equivalent circuit. Based on a small-signal equivalent circuit analysis, an analytical method to extract the thermal resistance and capacitance for RF silicon-on-insulator (SOI) MOSFETs is proposed in this paper. The geometry dependence of the thermal resistance and capacitance is investigated by using this method. The method is verified by using RF partial depletion-SOI process. The results show that the thermal resistance decreases and the thermal capacitance increases as the effective channel area increases. A simple equation to estimate the thermal characteristics is proposed to help optimize the device structure and circuit design for application. This method is easy to scale and adjust to devices with different dimensions and fabrication processes.
Comparison of the MODIS and VIIRS on-board SD and SDSM performance

The MODIS reflective solar bands (RSB) are calibrated on-orbit using a solar diffuser (SD) with its on-orbit degradation, or change in the bi-directional reflectance factor (BRF) monitored using a solar diffuser stability monitor (SDSM). By performing alternate observations of direct sunlight via an attenuation screen and of sunlight reflected diffusely off the SD, the SDSM monitors the on-orbit degradation of the SD. The MODIS SDSM has 9 detectors, covering wavelengths from 0.41 to 0.94 μm. Both Terra and Aqua MODIS instruments have successfully operated for more than 16 years on-orbit, with the SD experiencing significant degradation at the shortest wavelength (about 50% for Terra MODIS and about 20% for Aqua MODIS at 0.41 μm). The first VIIRS instrument on the Suomi NPP spacecraft was launched in October, 2011 and the follow-on instrument was launched in November, 2017 on the JPSS-1 spacecraft (now NOAA-20). Both the VIIRS instruments carry a MODIS-like SD and SDSM system with an improved design based on the lessons learned from MODIS. Unlike MODIS, the VIIRS SDSM collects data using 8 detectors covering a similar wavelength range as MODIS. A similar wavelength dependent SD degradation pattern is also observed in both VIIRS instruments. This paper provides a comparison of the on-orbit performance of the four instruments in terms of the on-orbit changes in the SDSM detector responses and on-orbit degradations of their SDs. The NOAA-20 VIIRS instrument is still in its first year of operation and hence the early performance of the Terra and Aqua MODIS and SNPP VIIRS is discussed to provide a perspective comparison.
Distributed Optimal Load Frequency Control with Non-Passive Dynamics

Motivated by an increase of renewable energy sources, we propose a distributed optimal load frequency control scheme achieving frequency regulation and economic dispatch. Based on an energy function of the power network, we derive an incremental passivity property for a well-known nonlinear structure preserving network model, differentiating between generator and load buses. Exploiting this property, we design distributed controllers that adjust the power generation. Notably, we explicitly include the turbine-governor dynamics, where first-order and the widely used second-order dynamics are analyzed in a unifying way. Due to the non-passive nature of the second-order turbine-governor dynamics, incorporating them is challenging, and we develop a suitable dissipation inequality for the interconnected generator and turbine-governor. This allows us to include the generator side more realistically in the stability analysis of optimal load frequency control than was previously possible.
On-orbit performance of the Terra and Aqua MODIS solar diffuser stability monitor

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board the Terra and Aqua space- craft are equipped with several on-board calibrators (OBCs) and continue to operate normally since launch. One such calibrator is the solar diffuser (SD), which allows for the calibration of the 20 reflective solar bands (RSBs) with wavelengths ranging from 0.41 to 2.3 μm. In order to accurately characterize the RSBs on-orbit, the changes associated with the SD bi-directional reflectance factor (BRF) are tracked using a solar diffuser stability monitor (SDSM). The SDSM consists of nine detectors located within a spherical integration source (SIS) and covers wavelengths from 0.41 to 0.94 μm. During each calibration event, the SDSM alternately views sunlight through an attenuation screen and the sunlight reflected from the SD in order to accurately characterize the degradation of the SD at those nine wavelengths. This paper provides a brief overview of the SD/SDSM calibration and operation, with more emphasis on the recent performance of the SD degradation and the SDSM detectors. A methodology to compute the signal-to-noise ratio (SNR) for each of the SDSM detectors is formulated and the noise performance is tracked over the mission lifetime. The importance of the detector noise to the RSB calibration uncertainty and to other instruments, such as the VIIRS SDSM, is also discussed.
Connected Vehicle Channels: On the Consideration of Electromagnetic Scattering From Local Scatterers

Connected vehicles are highly expected to be proactive, cooperative, well-informed, and coordinated. Therefore, high-reliable connected vehicle channels are required. It is widely accepted that the local scatterers appreciably affect wireless propagation channels and connected vehicle channels have no exception. This paper presents a general and highly efficient channel modeling method where electromagnetic (EM) scattering from local scatterers is calculated separately and then combined with ray tracing (RT) results; the method is named as layered-broadband channel model (LBCM) in this study and it is of great value as it could accurately simulate scatterer-included connected vehicle channels. The idea of the LBCM was arisen by the fact that EM scattering from scatterers displays point-scattering-like behaviors. Therefore, the scattering can be parameterized with a sparse point set and then the set could be efficiently implemented in broadband RT channel simulations. In order to validate the capability of proposed LBCM, a traffic sign was first taken as a typical example of local scatterers and its EM scattering was closely studied; then an urban intersection of typical vehicle-to-vehicle scenario was selected, where detailed comparisons were carried out between an LBCM-simulated channel and measured one. The validation processes present an integration of the full-wave simulation, analytical models, and measurement; and their results strongly confirm the feasibility and reliability of the LBCM.
Radiometric stability in 16 years of AIRS hyperspectral infrared data

With global warming at the rate of 10 mK/yr, it is important to carefully characterize instrument related trends, if the AIRS data are used for climate change research. We evaluated the stability of the AIRS Level 1B version 5 calibration for seven atmospheric window channels between 2002 and 2018 under clear ocean clear conditions. We do this by analyzing the trend in the difference between the observed brightness temperatures and those calculated based on the daily Sea Surface Temperature product provided by NOAA. Trends for the 961, 1128 and 1231 cm-1 channels are close to +3 mK/yr, at 790 and 901 cm-1 the trends are 6 mK/yr. For all observation the AIRS window channels read increasingly warmer. The observed trends are day/night consistent and insensitive to changes in the clear filter. The effects of scattering due to scan mirror contamination are evident at 2508 and 2616 cm-1 for extremely cold scenes surrounded by warm scenes, but scattering does not produces the observed warming trends for warm scenes. It is possible that much of the observed warming in the AIRS window channels is due to a shift in the day/night and skin effect corrections, which was not accounted for in our analysis. This would be a new geophysical effect related to the warming of the oceans, which requires more careful evaluation.
Impulsive Noise Removal in Color Digital Images Based on the Concept of Digital Paths

In the paper a fast technique of impulsive noise suppression in color images is described. The proposed method is utilizing the concept of digital paths which link the central pixel of a filtering window with its boundary. Each path is assigned a cost and the minimum one is treated as a measure of the central pixel corruption. If the minimum cost of a link between the window center and its boundary is high, then the central pixel is treated as corrupted. The filter output is a weighted average of a pixel and its robust estimate, in which the minimum cost is used for the creation of a soft switching rule for the filter output. The performed experiments revealed excellent properties of the novel approach, especially in case of highly distorted images. The computational complexity of the proposed technique is low and it can be used in real time applications.
Combinatorial and Structural Results for gamma-Psi-dimensions

This article deals with the generalization performance of margin multi-category classifiers, when minimal learnability hypotheses are made. In that context, the derivation of a guaranteed risk is based on the handling of capacity measures belonging to three main families: Rademacher/Gaussian complexities, metric entropies and scale-sensitive combinatorial dimensions. The scale-sensitive combinatorial dimensions dedicated to the classifiers of this kind are the gamma-Psi-dimensions. We introduce the combinatorial and structural results needed to involve them in the derivation of upper bounds on the metric entropies and the Rademacher complexity. Their incidence on the guaranteed risks is characterized, which establishes that in the theoretical framework of interest, performing the transition from the multi-class case to the binary one with combinatorial dimensions is a promising alternative to proceeding with covering numbers.