Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapidly dissolving repaglinide powders produced by the ultra-rapid freezing process

The objective of the study was to produce rapidly dissolving formulations of the poorly water-soluble drug repaglinide using an innovative new technology, ultra-rapid freezing (URF), and to investigate the influence of excipient type on repaglinide stability. Repaglinide compositions containing different types and levels of excipients and different drug potencies (50%–86%) were produced by the URF technology. Repaglinide/excipient solutions were frozen on a cryogenic substrate, collected, and lyophilized to form a dry powder. Surfactants, including sodium dodecyl sulfate, and alkalizing agents such as diethanolamine (DEA) and tromethamine (TRIS) were incorporated into the compositions. Forced degradation of repaglinide was conducted under stressed conditions (eg, elevated temperature, exposure to peroxide) to determine the stability of the drug in such environments. The solubility of repaglinide increased as a function of increasing pH; therefore, incorporation of an alkalizing agent into the URF formulations increased the drug's solubility. Drug instability resulted when the drug was exposed to pH values above 9.0. URF formulations containing alkalizing agents showed no degradation or spontaneous recrystallization in the formulation, indicating that increased stability was afforded by processing. URF processing created nanostructured drug/excipient particles with higher dissolution rates than were achieved for unprocessed drug. Alkalizing agents such as TRIS and DEA, present at levels of 25% to 33% wt/wt in the formulations, did not cause degradation of the drug when processed using URF. URF processing, therefore, yielded fast-dissolving formulations that were physically and chemically stable, resistant to alkali degradation or spontaneous recrystallization in the formulation.
Distribution and health-risk of polycyclic aromatic hydrocarbons in soils at a coking plant.

Nineteen soil samples were collected in and around Songshan coking plant in Guangdong province of China and analyzed for eighteen polycyclic aromatic hydrocarbons (PAHs) by gas chromatography-mass spectrometry (GC-MS). The total concentration of PAHs ranged from 2.36 to 1146.39 mg kg(-1) dry weight, varying significantly among the sampling sites, most individual PAHs were correlated with each other. A cluster analysis was performed to examine the correlation of PAH distribution, five groups were observed with sample types in the coking plant. 2-3 ring PAHs were predominant in group I and II, while 4-5 ring PAHs showed great abundance in group III, IV and V, which contributed to the distance from the emission sources in the coking plant and the behaviors of particle-bound and gaseous PAHs. The ratios of Flu : (Flu + Pyr), BaA : (BaA + Chr), InP : (InP + BgP) and Ant : (Ant + Phen) ratios were 0.51-0.87, 0.16-0.89, 0.47-0.68 and 0.03-0.60, respectively. The total index of all studied soils was > 6, indicating that the source of the PAHs in coking plant soils were from the pyrolysis processes. Health risk assessments were carried out by dermal PAH exposure data to quantify cancer risk. The resultant lifetime exposure levels due to TEQ(BaP) desorbed onto skin for workers ranged from 2.25 × 10(-7) to 7.86 × 10(-5) mg kg(-1) per day, and the estimated cancer risks were between 8.45 × 10(-6) and 2.94 × 10(-3), indicating that the dermal exposures of PAHs to coking workers might be acceptable in most soil sites.
MANAGEMENT AND PLACEMENT OF REPLICAS IN A HIERARCHICAL DATA GRID

In large systems, data management is only possible through the use of replication techniques. In order to improve availability and ensure fast and efficient access, we propose in this paper a dynamic replication algorithm which takes into account also the placement of data in a hierarchical data grid. Experimental results show the effectiveness of our approach in terms of response time and availability of data in the system.
Network cooperation for energy saving in green radio communications

Financial and environmental considerations have motivated a trend in wireless communication network design and operation to minimize the amount of energy consumption. This trend is referred to as green radio communications. In this article, network cooperation is investigated as a means of energy saving. Networks with overlapped coverage can cooperate to reduce their energy consumption by alternately switching on and off their resources according to the traffic load conditions. We present an optimal resource on-off switching framework that adapts to the fluctuations in the traffic load and maximizes the amount of energy saving under service quality constraints in a cooperative networking environment. For the system model under consideration, unlike the existing solutions in the literature, the proposed technique can achieve energy saving while avoiding an increase in transmission power. Numerical results demonstrate the validity of the proposed technique.
Self-Efficacy and Political Skill as Comparative Predictors of Task and Contextual Performance: A Two-Study Constructive Replication

Task and contextual performance are distinct and critical components of job performance. However, empirical studies of antecedents have tended to focus on one or the other type of performance, but not both. Furthermore, sound theoretical rationale has not always been provided for the prediction of different dimensions of job performance. Two studies were conducted to address these issues. In Study 1, as hypothesized, we found self-efficacy to be more strongly related to task than to contextual performance, and political skill to be more strongly related to contextual than to task performance. In addition, and as expected, results indicated self-efficacy to be a better predictor of task performance than political skill, and political skill to be a better predictor of contextual performance than self-efficacy. These results were constructively replicated (Lykken, 1968) in Study 2, thus providing strong support for the validity of the hypothesized and obtained empirical results. Implications of these results and limitations of the research are discussed, as are suggestions for future work.
Chapter 13 Factor Graphs and Message Passing Algorithms

Complex modern day systems are often characterized by the presence of many interacting variables that govern the dynamics of the system. Statistical inference in such systems requires efficient algorithms that offer an ease of implementation while delivering the pre-specified performance guarantees. In developing an algorithm for a sophisticated system, accurate and representative modeling of the underlying system is often the first step. The use of graphical models to explain the working of complex systems has gained a lot of attention in recent years. Stochastic models are often represented by a Bayesian network or a Markov random field. The graphical representation not only provides a better understanding of the system model but also throws up numerous exciting opportunities to develop new and improved algorithms. Factor graphs belong to the class of graphical models that serve to explain the dependencies between several interacting variables. They can be used to model a wide variety of systems and are increasingly applied in statistical learning, signal processing and artificial intelligence.
Short Communication Correlation between positivity for immunoglobulin A antibodies and viraemia of swine hepatitis E virus observed among farm pigs in Japan

and 3 %, respectively. However, anti-HEV IgA was detected significantly more frequently among viraemic pigs than among non-viraemic pigs (55 vs 10 %, P<0? 0001). These results suggest that anti-HEV IgA is more useful than anti-HEV IgM to screen for viraemic pigs.
An Approach to Construct Semantic Networks with Confidence Scores Based on Data Analysis - Case Study in Osaka Wholesale Market

In recent years, several large-scale knowledge bases (KBs) have been constructed, such as YAGO, DBpedia, and Google Knowledge Graph. Although automatic extractio techniques that extract facts and rules from the Web is necessary for constructing such large-scale KBs, incorporation of noisy, unreliable knowledge cannot be unavoidable. Thus, Google Knowledge Vault assigns extracted knowledge with confidence scores based on consistency with the existing KBs. In this paper, we propose a new approach for associating confidence scores with knowledge based on a large amount of raw data for domains, where there is no existing KB. We first construct knowledge in a specific domain as a semantic network, and then design a probabilistic network, that corresponds to the semantic network. To associate the confidence scores with the semantic network, we train the probabilistic network with a large amount of open data, provided by the Osaka central wholesale market in Japan. We also confirm the validity of the confidence scores with the accuracy of reasoning on the probabilistic network. A semantic network associated with confidence scores, that is, a weighted labeled graph is advantageous not only for reducing the noisy, unreliable knowledge with low confidence, but also for making retrieval results ranking on the KB. In the future, probabilistic reasoning on semantic networks may also be possible.
On the Yield of VLSI Processors with On-Chip CPU Cache

Yield enhancement through the acceptance of partially good chips is a well-known technique [1–3]. In this paper we derive a yield model for single-chip VLSI processors with a partially good on-chip cache. Also, we investigate how the yield enhancement of VLSI processors with on-chip CPU cache relates with the number of acceptable faulty cache blocks, the percentage of the cache area with respect to the whole chip area and various manufacturing process parameters as defect densities and the fault clustering parameter.
Perception without awareness of supraliminal stimuli: A critical review and a proposition for an integrated model

This article offers a critical review of marketing research focused on the effects of supraliminal stimuli perceived in the absence of awareness. On the basis of findings emerging from the literature related to memory accessibility, likelihood of inclusion in the consideration set, evaluation and likelihood of consumer choice, we progressively derive 10 research proposals. Finally, we propose an integrated model and outline priority avenues for future research.
Monte Carlo modeling of the light transport in polymer light-emitting devices on plastic substrates

A Monte Carlo method for modeling the light transport phenomena in organic polymer light-emitting devices (PLEDs) has been reported previously (Badano and Kanicki, 2001). The advantage of this simulation method is its ability to model bulk absorption, thin-film coatings, and uneven or irregular surfaces by tracking the photon polarization in realistic device structures. We have applied this method to analyze the PLEDs spectral outputs and out-coupling efficiencies. We have established that the calculated out-coupling efficiencies are approximately the same (/spl eta//sub coup//spl sim/0.2) for the red and green PLEDs. Using a description of uneven surfaces with Fresnel analysis, we showed that the nonsmooth interfaces (as modeled by the algorithm for uneven surfaces) between light-emitting polymer and hole transporting layer increase the probabilities of out-coupling and wave-guiding of the internally generated light. In this paper, we use this method to calculate the angular distribution of the PLED light-emission. We found that the Monte Carlo simulated PLED light-emission angular distribution shows better agreement with the experimental data than previously used models relying on standard refraction theory at one interface.
Principal Professional Development in China: Challenges, Opportunities, and Strategies

This article examines the essential role of school principals in China's “Quality-Oriented Education” national reform movement. Keeping China's cultural and historical context in mind, and taking into consideration the impact of political and societal forces on the nation, we discuss the major challenges faced by Chinese schools, specifically the rising demand for a new generation of school leaders. To address this issue we conduct a critical review of the existing principal evaluation and training systems in China. From this data we then propose a framework of strategic directions for systemic professional development for school leaders.
Exploiting thread-level parallelism in template-based gesture recognition with dynamic time warping

Mobile devices have become ubiquitous, powerful computing devices. While their use scenarios require new input methods, their typical many-core computing architectures allow for new ways to implement these input methods. In this paper the suitability of many-core digital signal processors for online hand gesture recognition is evaluated. To this end, a system consisting of a data glove with three accelerometers and a many-core digital signal processor board is presented. Experiments assess realtime properties in hand gesture recognition on the many-core processing platform.
Do Expectations Meet Reality? A survey of changes in first‐year student opinion

With the projected increase in student numbers, the transition from school to university will cause more problems than at present unless these are acknowledged and solutions properly managed. At the University of Ulster at Coleraine incoming students to the Faculty of Science were surveyed to assess their attitudes to learning and their expectations of life at University. These results were then compared to a repeat survey after students had been studying for one semester. The results confirm that many of the study habits developed in school persist into the first year of university. This is in spite of staff expectations that students will work more independently and the reality of decreased access to staff support.
Novel fault detection criteria based on linear quadratic control performances

This paper proposes a new approach to designing a relatively simple algorithmic fault detection system that is potentially applicable in embedded diagnostic structures. The method blends the LQ control principle with checking and evaluating unavoidable degradation in the sequence of discrete-time LQ control performance index values due to faults in actuators, sensors or system dynamics. Design conditions are derived, and direct computational forms of the algorithms are given. A simulation example subject to different types of failures is used to illustrate the design process and to demonstrate the effectiveness of the method.
Content, Professional Preparation, and Teaching Methods: How Diverse Is Teacher Education across Countries?

A teacher education program offers opportunities to learn (OTL) consistent with its vision of what teachers need to know and be able to do. The “Teacher Education and Development Study: Learning to Teach Mathematics” of the International Association for the Evaluation of Educational Achievement provides, for the first time, the possibility to examine the diversity of OTL across countries. A latent class analysis reveals that it was sufficient to group the 8,000 future teachers from 15 countries into four classes to describe their OTL with respect to the content delivered, their professional preparation and the teaching methods experienced. Such commonality indicates more homogeneity than usually discussed in the comparative literature. This result may be, in turn, an indicator of an inherent logic of mathematics teaching.
Binaural sound generation corresponding to omnidirectional video view using angular region-wise source enhancement

Web applications for watching omnidirectional video through head-mounted displays (HMDs) or smartphones have been widely distributed. The goal of this study was to generate binaural sounds corresponding to the user viewpoint. Assuming that a microphone array is used for sound recording, the enhanced signal for each angular region can be extracted. By convolving head-related transfer functions (HRTFs) and enhanced signals and re-synthesizing them, binaural sounds corresponding to the user viewpoint can be virtually generated. In this paper, we propose a method for achieving angular region-wise source enhancement by generating a multichannel Wiener filter based on the power spectral density (PSD)-estimation-in-beamspace method. To measure user localization when watching omnidirectional video through an HMD, we used a system that enables the generation of binaural sounds corresponding to the user viewpoint in real time. Through subjective tests, we confirmed that sound localization corresponding to the user viewpoint can be obtained when applying about a 40-degree angular region-wise source enhancement.
Detecting Dwelling in Urban Environments Using GPS , WiFi , and Geolocation Measurements

A fundamental part of studying human mobility is to detect dwelling. When we dwell at places such as our homes, the supermarket or the local park, we are not necessarily still or stationary, but move around in a confined area. Most, but not all, of our significant places are indoors, which hampers the detection using GPS. In this work, we discuss three different sensor sources and their idiosyncrasies when used for dwelling detection. In particular, we use geolocation services based on collected WiFi fingerprints and show that they may be used complementary to GPS information. Our study is based on data collected on mobile phones in cities of various sizes in four different European countries.
Extensive silicone lymphadenopathy after breast implant insertion mimicking malignant lymphadenopathy

Silicone implants are widely used in aesthetic and reconstructive breast surgery. Silicone lymphadenopathy is a well-known rare complication of implant insertion. Silicone leakage from a rupture or silicone bleeding can accumulate in lymph nodes. Foreign body reactions in the affected lymph nodes may be misdiagnosed as metastasis or malignant lymphadeno pathy upon initial presentation if silicone lymphadenopathy is not considered in the initial diagnosis. We report a case of siliconoma with extensive involvement of multiple lymph nodes mimicking malignant features to emphasize that clinicians should carefully evaluate each patient's medical history and disease status during differential diagnosis.
FLIES ACROSS THE WATER: GENETIC DIFFERENTIATION AND REPRODUCTIVE ISOLATION IN ALLOPATRIC DESERT DROSOPHILA

Abstract Between sister species of Drosophila, both pre- and postzygotic reproductive isolation commonly appear by the time a Nei's genetic distance of 0.5 is observed. The degree of genetic differentiation present when allopatric populations of the same Drosophila species exhibit incipient reproductive isolation has not been systematically investigated. Here we compare the relationship between genetic differentiation and pre- and postzygotic isolation among allopatric populations of three cactophilic desert Drosophila: D. mettleri, D. nigrospiracula, and D. mojavensis. The range of all three is interrupted by the Gulf of California, while two species, D. mettleri and D. mojavensis, have additional allopatric populations residing on distant Santa Catalina Island, off the coast of southern California. Significant population structure exists within all three species, but only for allopatric populations of D. mojavensis is significant isolation at the prezygotic level observed. The genetic distances for the relevant populations of D. mojavensis were in the range of 0.12, similar to that for D. mettleri whose greatest D = 0.11 was unassociated with any form of isolation. These observations suggest further investigations of Drosophila populations with genetic distances in this range be undertaken to identify any potential patterns in the relationship between degree of genetic differentiation and the appearance of pre- and/or postzygotic isolation. Corresponding Editor: T. Mousseau
Role of Spectral Peaks in Autocoorelation Domain for Robust Speech Recognition

This paper presents a new front-end for robust speech recognition. This new front-end scenario focuses on the spectral features of the filtered speech signals in the autocorrelation domain. The autocorrelation domain is well known for its pole preserving and noise separation properties. In this paper we will use the autocorrelation domain as an appropriate candidate for robust feature extraction. The proposed method introduces a novel representation of speech for the cases where the speech signal is corrupted by additive noises. In this method, the speech features are computed by reducing additive noise effects via an initial filtering stage, followed by the extraction of autocorrelation spectrum peaks. Robust features based on theses peaks are derived by assuming that the corrupting noise is stationary in nature. A task of speaker-independent isolated-word recognition is used to demonstrate the efficiency of these robust features. The cases of white noise and colored noise such as factory, babble and F16 are tested. Experimental results show significant improvement in comparison to the results obtained using traditional front end methods. Further enhancement has been done by applying cepstral mean normalization (CMN) on the above extracted features.
Effect of Three Different Muscle Action Training Protocols on Knee Strength Ratios and Performance

Abstract Ruas, CV, Brown, LE, Lima, CD, Costa, PB, and Pinto, RS. Effect of three different muscle action training protocols on knee strength ratios and performance. J Strength Cond Res 32(8): 2154–2165, 2018—Hamstring to quadriceps (H:Q) ratios are often used to assess strength imbalances. The aims of this study were to compare 3 different muscle action training protocols on H:Q strength balance and functional performance. Forty untrained men (age: 22.87 ± 2.28 years, mass: 70.66 ± 11.049 kg, ht: 174.29 ± 6.90 cm) performed 6 weeks of training on an isokinetic dynamometer. They were randomly assigned to one of 4 groups; concentric quadriceps and concentric hamstring (CON/CON), eccentric quadriceps and eccentric hamstring (ECC/ECC), concentric quadriceps and eccentric hamstring (CON/ECC), or no training. Mixed Factor analyses of variance were used to compare interactions for variables pretest and posttest between groups (p ⩽ 0.05). The ECC/ECC group showed significant increases in H:Q functional ratio (pre = 0.73 ± 0.092, post = 0.87 ± 0.098), ECC peak torque (PT) (pre = 226.44 ± 67.80 N·m, post = 331.74 ± 54.44 N·m), isometric PT (IPT) (pre = 173.69 ± 41.41 N·m, post = 203.091 ± 30.82 N·m), countermovement jump (CMJ) (pre = 52.73 ± 6.95 cm, post = 58.16 ± 6.10 cm), and drop jump (DJ) (pre = 52.91 ± 6.080 cm, post = 58.20 ± 7.72 cm), whereas the CON/CON group increased the rate of torque development (pre = 152.19 ± 65.0074 N·m·s−1, post = 225.26 ± 88.80 N·m·s−1). There were no differences between groups for CON PT, squat jump, conventional ratio or 40 m sprint. Our findings suggest that ECC/ECC training may be the most effective at increasing functional H:Q strength ratios, as well as ECC PT, IPT, CMJ, and DJ performance. Eccentric training increases ECC PT, thereby increasing the functional H:Q ratio. Eccentric training also improves vertical jumping involving ECC actions. CON/CON training may be more effective at increasing explosive muscle strength.