Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Pound-Drever-Hall Techniques for High Resolution Optical Fiber Grating Sensors

The interrogation technology plays a key role in high resolution fiber grating sensors. Due to the high sensitivity and quick response, the Pound-Drever-Hall (PDH) technique is one of the most successful interrogation methods in the high resolution fiber grating sensor systems. However, the traditional PDH technique can only interrogate one sensing element with limited measurement range, and can’t fully exploit the capability of optical fiber sensors. To break through this limitation, lots of efforts have been put to improve the PDH technique. This article reviews the recent improvements on PDH technique towards large measurement range and low probe power interrogation. Sideband interrogation method and high order PDH technique are proposed to expand the measurement range without tuning the laser frequency; In order to enable low probe power interrogation, which is essential in multiplexed sensing, coherent PDH and active PDH techniques are developed. Those improvements will promote the further development of PDH technique and provide powerful tools for high-resolution sensing applications.
Investigations in the aluminium rich part of the ternary phase diagram Al—Fe—Ge

In dieser Arbeit wurde im Fe armen Teil des ternaren Systems Al–Fe–Ge untersucht. Den neuen ternaren Verbindungen, von welchen analoge Strukturen und Zusammensetzungen zu jenen des Systems Al–Fe–Si erwartet wurden, wurde besondere Aufmerksamkeit schenkt. Bisher wurden nur wenige Untersuchungen im ternaren System Al–Fe–Ge in der einschlagigen Literatur erwahnt. Berichte uber isotherme Schnitte sind nur fur Fe-Gehalte uber 50 at. % auf der Al Seite, beziehungsweise uber 72 at. % auf der Ge Seite, der ternaren Phasendiagramme vorhanden. Es sind mehrere Phasen, welche zumeist als metastabil beschrieben werden, in diesem System bekannt. Die zugehorigen Kristallstrukturen, waren jedoch nicht gegeben oder nur aus verfeinerten Rontgen-Pulverdiffraktogrammen gewonnen. Des Weiteren, wird das binare Phasendiagramm Fe–Ge in der Literatur kontrovers diskutiert. Aus diesem Grund, wurden die betreffenden Ausschnitte der beta- und eta-Phase, im Zuge dieser Arbeit erneut untersucht. Unter Inbetrachtnahme der neu untersuchten eta-Phase des binaren Fe–Ge Systems, konnten insgesamt sechs neue Strukturen gefunden werden, welche durch Einkristall-Rontgenstrukturanalyse aufgeklart wurden. Fur eine weitere Phase, wurde ein Strukturvorschlag aus Daten der Rontgen-Pulverdiffraktogrammen erarbeitet; dieser konnte in samtlichen betreffenden Proben die fehlenden Peaks korrekt beschreiben. Die in der Literatur als amorph beschriebenen Strukturen (tau6 uand tau8), konnten auf Grund ihrer Nachbarschaft und dem Fehlen von passenden Einkristallen, nicht eingehend untersucht werden. Nichtsdestotrotz konnte durch Indizierung der scharfen Reflexe einer der beiden (tau6) Strukturen eine orthorhombische Zelle gefunden werden. Weitere Untersuchungen hinsichtlich der Struktur dieser beiden Phasen und der Phase tau 7, welche Anzeichen von Domanenbildung oder Uberstrukturen aufweist, scheinen sinnvoll. Es konnte gezeigt werden, dass strukturelle Beziehungen der neuen ternaren Phasen vornehmlich aus dem binaren Phasendiagramm Fe–Ge herruhren. Wahrend bei Fe-Gehalten unter 35 at. % Fe, die tetragonalen und pseudo-tetragonalen strukturellen Merkmale der FeGe2 Phase dominieren, wurde gezeigt dass bei Fe-Gehalten zwischen 35 und 55 at. % Fe, die pseudo-hexagonalen Merkmale mit den Phasen Fe6Ge5 und FeGe in Verbindung gebracht werden konnen. Im Zuge dieser Arbeit wurden Isotherme Schnitte bei 400 ◦C und 800 ◦C erarbeiten. Eine Stabilisierung des kubischen Polymorph von FeGe, hin zu hoheren Temperaturen, wurde beobachtet. Auf Grund der Komplexitat im Al reichen Teil des Phasendiagramms, sind weitere Untersuchungen notwendig, um die Isopleten sowie eine Liquidusprojektion mit hinreichender Sicherheit beschreiben zu konnen. Eine Untersuchung der magnetischen Eigenschaften aller Phasen, ins besonders mit Hinblick auf die mogliche Supraleitfahigkeit der Phase tau5 scheinen vielversprechend, da in der einschlagigen Literatur auserordentliche magnetische Eigenschaften in Systemen der Art TM–X (X = Al, Ga, Si, Ge) beschrieben werden.
Robust Fixed-Time Stability: Application to Sliding-Mode Control

This article deals with robust fixed-time stability and stabilization. First, new global robust fixed-time stability results are proposed for scalar systems by using constant and variable exponent coefficients. Then, they are applied to global robust fixed-time stabilization of a class of uncertain nonlinear second-order systems by using sliding-mode control. All the results are illustrated in simulation.
Region Pixel Voting Network (RPVNet) for 6D Pose Estimation from Monocular Image

Recent studies have shown that deep learning achieves superior results in the task of estimating 6D-pose of target object from an image. End-to-end techniques use deep networks to predict pose directly from image, avoiding the limitations of handcraft features, but rely on training dataset to deal with occlusion. Two-stage algorithms alleviate this problem by finding keypoints in the image and then solving the Perspective-n-Point (PnP) problem to avoid directly fitting the transformation from image space to 6D-pose space. This paper proposes a novel two-stage method using only local features for pixel voting, called Region Pixel Voting Network (RPVNet). Front-end network detects target object and predicts its direction maps, from which the keypoints are recovered by pixel voting using Random Sample Consensus (RANSAC). The backbone, object detection network and mask prediction network of RPVNet are designed based on Mask R-CNN. Direction map is a vector field with the direction of each point pointing to its source keypoint. It is shown that predicting an object’s keypoints is related to its own pixels and independent of other pixels, which means the influence of occlusion decreases in the object’s region. Based on this phenomenon, in RPVNet, local features instead of the whole features, i.e., the output of the backbone, are used by a well-designed Convolutional Neural Networks (CNN) to compute direction maps. The local features are extracted from the whole features through RoIAlign, based on the region provided by detection network. Experiments on LINEMOD dataset show that RPVNet’s average accuracy (86.1%) is almost equal to state-of-the-art (86.4%) when no occlusion occurs. Meanwhile, results on Occlusion LINEMOD dataset show that RPVNet outperforms state-of-the-art (43.7% vs. 40.8%) and is more accurate for small object in occluded scenes.
What's in an education? Implications of
 CEO
 education for financial inclusion

This article analyses the impact of chief executive officer's (CEO) educational background, that is, business degree (an MBA) on corporate strategies. In essence, the study tests how differences in educational backgrounds, MBACEOs vis-à-vis non-MBACEOs, determine their strategic choices pertaining to financial inclusion. The study evaluates this relationship in the third-sector, faith-based charity organizations (FCOs) context. Using a longitudinal sample of FCOs operating in a developing Muslim-majority country, this paper reports that CEO's educational background, that is, an MBA degree matters for financial inclusion. These findings demonstrate how CEO's educational background shape the strategic posture of third-sector organizations such as the FCOs. Additionally, the interaction effects further suggest that MBACEOs derive their imputes from robust sutural positions within the organization such as role duality, founder and internally hired CEO status. Results reported in this study have import economic and policy implications.
Nuclear Magnetic Resonance (NMR)-Based Quantification on Flavor-Active and Bioactive Compounds and Application for Distinguishment of Chicken Breeds

Abstract The purpose of this study was to use 1H nuclear magnetic resonance (1H NMR) to quantify taste-active and bioactive compounds in chicken breasts and thighs from Korean native chicken (KNC) [newly developed KNCs (KNC-A, -C, and -D) and commercial KNC-H] and white-semi broiler (WSB) used in Samgye. Further, each breed was differentiated using multivariate analyses, including a machine learning algorithm designed to use metabolic information from each type of chicken obtained using 1H-13C heteronuclear single quantum coherence (2D NMR). Breast meat from KNC-D chickens were superior to those of conventional KNC-H and WSB chickens in terms of both taste-active and bioactive compounds. In the multivariate analysis, meat portions (breast and thigh) and chicken breeds (KNCs and WSB) could be clearly distinguished based on the outcomes of the principal component analysis and partial least square-discriminant analysis (R2=0.945; Q2=0.901). Based on this, we determined the receiver operating characteristic (ROC) curve for each of these components. AUC analysis identified 10 features which could be consistently applied to distinguish between all KNCs and WSB chickens in both breast (0.988) and thigh (1.000) meat without error. Here, both 1H NMR and 2D NMR could successfully quantify various target metabolites which could be used to distinguish between different chicken breeds based on their metabolic profile.
Information Literacy Instruction and Online Learning: Making the Case for Incorporating Digital Badges

Abstract Information Literacy Instruction has a long history of being taught by librarians to online learners. Emerging technologies help librarians increase their ability to meet the needs, learning styles and best practices of providing online ILI to their students. Digital badging is an evolving technology which could help librarians develop their online learning practices in areas including sustainability, personalized learning, and collaboration with academic colleagues. This paper examines established best practices identified in the literature regarding online ILI and gives readers a context of how the best practices align with the use of digital badges in ILI.
Degradation Patterns of GH11 xylanases for Efficiently Hydrolyzing xylan in Aspergillus Niger An76

Background: Xylan is the most abundant hemicellulose polysaccharide in nature. Endo-xylanases from GH10 and GH11 families are the most critical xylan degrading enzymes. Filamentous fungi are highly effective xylan degraders and possess numerous xylan degrading isoenzyme-encoding genes, especially Aspergillus niger. Most noteworthy, the amplification of the GH11 xylanase-encoding genes occurs frequently in an organism, but the knowledge of each GH11 xylanases is little known. Results: A. niger An76 encoded a comprehensive set of xylan-degrading enzymes, including five endo-xylanases (one GH10 and four GH11). Quantitative transcriptional analysis showed that three xylanases were up-regulated by xylose substrates, and the order and amount of enzyme secretion differed. Specifically, XynA and XynB were initially secreted successively, followed by XynC. Structural bioinformatics analysis indicated that the different modes of action of the three GH11 xylanases may be due to intricate hydrogen bonding between substrates and functional residues in the active site architectures. Heterologous expression and biochemical characterization of three GH11 xylanases (XynA, XynB and XynD) revealed differences in catalytic performance and product profiles. Furthermore, XynA and XynB displayed obvious synergistic action against beechwood xylan. Conclusions: We investigated subtle differences in the functions of different isoenzymes in the same family using a combination of physiological and biochemical experiments. The transcriptional regulation and catalytic functions of enzymes could be the result of long-term evolutionary adaptation. The finding further expanded our understanding of GH-encoding genes amplification in filamentous fungi, which could guide the design of the optimal enzyme cocktails in industrial applications.
Speech file compression by eliminating unvoiced/silence components

The main objective of this study is to have noise component of a speech signal eliminated and compressing it by storing the locations and durations of silence regions. The separation between voiced, unvoiced, and silence regions are done by using the Short Time Energy (STE) and Zero Crossing Rate (ZCR) methodologies. All operations in this study have been performed by using the User Interface (UI) developed on MATLAB®. These operations include voice recording, playing the recording, eliminating the unwanted regions, playing the modified recording, saving of original and compressed files and loading the recording compressed.
Microstructure and Corrosion Properties of La2Zr2O7/NiCoAlY Thermal Barrier Coatings Deposited on Inconel 718 Superalloy by Laser Cladding

In order to improve the seawater corrosion resistance of Inconel 718 superalloy, a La2Zr2O7/NiCoCrAlY thermal barrier coating corrosion resistant to 3.5 wt. % NaCl aqueous solution was prepared by laser cladding on Inconel 718 superalloy. X-ray diffraction (XRD), Scanning Electron Microscope (SEM), and electrochemical techniques were used to study the microstructure and the corrosion performance of the coating in 3.5 wt. % NaCl solution. The results show that the thermal barrier coating is mainly composed of primary La2Zr2O7 phase and γ + laves/δ phase eutectic structure. The corrosion potential and corrosion current of the coating in 3.5 wt. % NaCl solution are higher and lower than that of the Inconel 718 substrate, respectively, indicating that the corrosion performance of the coating is better than that of the Inconel 718 substrate. The presence of La2Zr2O7 phase in the thermal barrier coating is the main reason for its corrosion resistance to 3.5 wt. % NaCl solution.
Mathematical Modeling as a Catalyst for Equitable Mathematics Instruction: Preparing Teachers and Young Learners with 21st Century Skills

This case study focuses on a team of teachers and students in a Lesson Study, focused on using mathematical modeling (MM) to make significant decisions to design and plan for a sustainable edible garden in their community. We examined (a) how teachers develop students’ capacity to engage in mathematical modeling, while attending to equitable teaching practices; and (b) how teachers’ view of teaching through mathematics modeling changed after unit implementation. We found that teachers were deliberate in employing specific structures, routines, and tools to attend to equitable participation, when eliciting student thinking in the modeling process. We found that teachers’ view of mathematics modeling changed as they recognized how MM allowed for (a) integration of important mathematics concepts while giving students ownership of the mathematics; (b) opportunity to assess both content and 21st century process skills; and (c) positive energy that came from both students and teachers when teaching through the use of mathematical modeling. A promising strategy for preparing our youth for rigorous mathematics and skills to solve ill-structured problems is by integrating mathematical modeling in early elementary grades to develop critical 21st century skills and a productive disposition towards problem posing and problem solving.
The summer precipitation response of latewood tree‐ring chronologies in the southwestern United States

Latewood width tree‐ring chronologies from arid‐site conifers in the southwestern United States are correlated with precipitation during portions of the summer monsoon season. The onset date and length of the monsoon season varies across the region, and these regional differences in summer rainfall climatology may impact the strength and timing of the warm season precipitation response of latewood chronologies. The optimal latewood response to summer precipitation is computed on a daily basis using 67 adjusted latewood chronologies (LWa) from the southwestern United States, adjusted to remove correlation with preceding earlywood growth. Most LWa chronologies are significantly correlated with precipitation summed over a period of approximately 4 weeks (29 days) in early summer. This early summer precipitation signal is present in most ponderosa pine chronologies across the study area. It is also evident in Douglas‐fir chronologies, but only from southern Arizona and New Mexico. The Julian date of summer precipitation onset increases from south to north in the instrumental precipitation data for the southwestern United States. The timing of the early summer season precipitation response in most LWa chronologies also tends to occur later in the summer from southeastern Arizona into northern New Mexico and eastern Colorado. Principal components analysis of the LWa chronologies reproduces two of the three most important spatial modes of early summer precipitation covariability seen in the instrumental data. The first PC of LWa is related to the same atmospheric circulation features associated with PC1 of instrumental early summer precipitation, including cyclonic circulation over the southwestern United States and moisture advection from the eastern Pacific. Correlation analyses between antecedent cool season precipitation and early summer rainfall using instrumental and tree‐ring reconstructed precipitation indicates that the tree‐ring data reproduce the multi‐decadal variability in correlation between seasons seen in the instrumental data.
Art Funds in China: Developments and Limitations

This paper focuses on a type of worldwide art investment vehicle in an unexplored yet significant area: the Chinese art fund. It seeks to understand why art funds exploded in China after the 2008 financial crisis and how they have developed new features in the Chinese context. Further, it discusses the relationship between Chinese art funds and the Chinese art world. While these two groups tend to be what sociologists call “hostile worlds” in the West, my study shows that actors in the Chinese art world tend to take a pragmatic attitude toward capital. Thus, art funds face fewer social limitations in the Chinese art world than their Western counterparts. However, Chinese art funds face limitations in terms of accessibility, credibility, and liquidity. These limitations have been caused mainly by a series of regulations launched since 2013, which has primarily resulted in a decline of art funds in China.
A new statistical approach for the identification of outlier genes in cancer microarray data

The aim of microarrays technology is to discover genes, which are differentially expressed as outliers between two or more groups of patients are an important task in the genomics community. The regular pattern of genes may often breakdown due to the presence of outliers and it is essential to detect those genes whose behavior looks abnormal in experimental and biological conditions. Several statistical techniques - t-statistic, cancer outlier profile analysis (COPA), outlier sums (OS), outlier robust t-statistic (ORT), maximum ordered subset t-statistics (MOST) and least sum of ordered subset square t-statistics (LSOSS) were developed to address the problem of detecting outlier genes in microarray data but these methods are affected by some problems especially if there is an unusual observation in such dataset then the standard assumptions of distribution parameter may be violated and these techniques might not be suitable to detect outliers genes as well. For these consequences, I have developed a new statistical technique that is “Propose t-statistic (PT)”. The performance of the newly proposed method PT statistic compare with the other existing methods applied to the monte carlo simulation data, package data, and real cancer datasets. The result shows that the outlier genes are identified by using the proposed method PT as well and will give the best and identical results than other methods. The performance of the proposed approach significantly improves than the traditional methods and it can extensively contribute to the medical as well as the genomic community. Asian J. Med. Biol. Res. December 2020, 6(4): 795-801
The Development of Yogyakarta Special Batik Design to Meet Customer Desire and Satisfaction Using Quality Function Deployment

Small and Medium Enterprises (SMEs) are industrial sectors that play an essential role in supporting the Indonesian economy. SMEs hold a strategic role in the economic, social, and political fields because of its contribution to gross national product (GNP) and reducing unemployment. The SME sector that has grown rapidly in the last decade is batik. Almost all provinces in Indonesia have batik with their characteristics. Batik has a varied and unique design. High innovation and creativity support this design, making the batik industry more existent and developed. In this case, Yogyakarta is the center of the batik industry, which is growing rapidly, especially in terms of batik design. Consumers have many choices according to their character and taste. However, to better understand the design desired by consumers, it is necessary to conduct research related to the development of batik designs. The purpose of this study was to analyze the development of a special Yogyakarta batik design to fulfill customer desires and satisfaction by using Quality Function Deployment (QFD). The QFD method can be used to identify consumer desires, which will ultimately impact customer satisfaction. According to the manufacturer, based on the relationship between technical responses, the design improvement priorities included color selection, innovative design, and classical design. It deals with many other technical responses, meaning that the improvement of these three means also increases other technical response
Thermoelectric performance of Dy/Y co-doped SrTiO3 ceramic composites with submicron A2Ti2O7 (A = Dy, Y) pyrochlore

Dy/Y co-doped SrTiO3 ceramic composites with submicron A2Ti2O7 (A = Dy, Y) pyrochlore were in situ synthesized by a solid-state method. The microstructure of the A2Ti2O7 phase and its relationship with the thermoelectric properties of Sr0.9−x Dy x Y0.1TiO3 ceramics are studied. As the Dy content increases, the secondary phase content increases and the grain size slightly decreases from 1.03 to 0.77 μm; meanwhile, the grain size of the main phase also decreases. The highest power factor of 1034.5 μWK−2 m−1 at 569 K has been obtained for the x = 0.08 sample due to comparatively lower electrical resistivity. In addition, the introduction of Dy reduces the thermal conductivity dramatically by decreasing the grain size of the main phase, increasing the number of the second phase and enhancing the scattering of mass fluctuation. In the end, the zT> 0.20 is obtained within the range of size of 0.80–1.03 μm and the mass fraction of 4.91%–13.50% for the second phase. The maximum zT value of 0.22 has been obtained for the x = 0.08 sample with the second phase size and the mass fraction of 0.88 μm and 11.6%, respectively. Thus, heavy element doping and the second phase with the right grain size and proportion can result in high thermoelectric properties for SrTiO3 samples.