Miracle-dz/UniFAR-FTUs huggingface dataset:
A deep learning driven uncertain full‐field homogenization method

This work is directed to uncertainty quantification of homogenized effective properties of composite materials with a complex, three dimensional microstructure. The uncertainties arise in the material parameters of the single constituents as well as in the fiber volume fraction. They are taken into account by multivariate random variables. Uncertainty quantification is carried out by an efficient surrogate model based on pseudospectral polynomial chaos expansion and artificial neural networks, which is trained on a fast Fourier transformation based homogenization method. The numerical example deals with the comparison of the presented method to Monte Carlo‐type simulation for uncertain homogenization of spherical inclusions in a matrix material.
Gazetteer based unsupervised learning approach for location extraction from complaint tweets

In the era of smart city, social media platform like twitter has become the most powerful medium for sharing urban issues. Extracting the locations from the complaint tweets is very much helpful to local government for monitoring and performing spatial analysis of civic issues at city level. We propose a natural language processing and regular expression based system to identify probable locations of complaints in terms of landmarks (hospital, mall, railway station), street level (e.g. road marg), region (e.g. nagar, colony) and suburb. Our system has used n-gram matching, string similarity and spatial proximity measures to confirm and disambiguate the extracted locations using GeoNames and OSM gazetteer data. Proposed system has achieved the F-score of 93% which is very promising. Locations are also displayed on map for better situational awareness across the city.
Investigation of Interpolymer Complexation Between Poly(Vinylcaprolactam) and Poly(Maleic Acid-Alt-Styrene)

ABSTRACT The interactions between two synthetic polymers used in biomedical applications, maleic acid-styrene copolymer (MAc-St) and poly(vinylcaprolactam) (PVCL), were investigated in dilute aqueous solution considering the influence of the pH, the added salt and the ratio between the components in the mixture. Hydrogen-bonding interactions between the COOH groups of MAc-St and the C═O groups of PVCL, together with hydrophobic interactions are involved in the formation of the interpolymer complex. The complex is insoluble below pH = 2.85 in aqueous solution, but the addition of NaCl enlarged the pH domain where the precipitation of the complex occurred. When the ratio between the polymers was varied, two maxima of the optical density were obtained: at a 1:1 ratio between the COOH and caprolactam groups, and also at a lower ratio (1:3). Other investigations, like the measurements of the turbidity in situ during mixing, and fluorescence, viscometric and potentiometric measurements were performed in order to understand these interactions. The phase separation of the thermosensitive poly(vinylcaprolactam) in the presence of MAc-St was also studied. The cloud point and the phase transition profile were found to be influenced by the amount of polyacid, as well as by the pH.
Techno-Economic Assessment of Flexibility Options Versus Grid Expansion in Distribution Grids

In this paper five different flexibility options are analysed from a techno-economic perspective as alternatives to traditional grid expansion for a specific distribution grid in Germany. The options are: two reactive power control strategies with photovoltaic inverters (as a function of the power feed-in, or of the voltage at the connection point), one residential and two large scale battery storage applications (primary control reserve with autonomous reactive power control or self consumption maximisation strategy with autonomous reactive power control). For the pilot grid located in Southern Germany a photovoltaic expansion pathway is determined. The main goal of this work is to quantify the grid expansion actions that can be avoided by applying these five flexibility options for the assumed expansion pathway, focusing on large scale battery storages. It is shown that the five flexibility options increase the hosting capacity for PV systems, compared to a scenario without, by up to 45%. Furthermore, the results of the economic assessment indicate that the analysed flexibility options might be a viable alternative to traditional grid expansion as all of them show a cost reduction potential for the pilot region. These results could encourage DSOs to consider the integration of additional PV and battery storage systems not as a problem which triggers grid expansion, but as part of the solution reducing future grid expansion costs.
Frame Restructuration: The Making of an Alternative Business Incubator amid Detroit’s Crisis

Adaptive responses to crisis rely on effective cognitive frames: understanding what is going on amid unfolding crisis and what should be done to address it. Research has shown that failing to drop a routine cognitive frame exacerbates crises, while nimbly adopting a novel frame enhances resilience. This suggests that actors in crisis have an urgent dual mission: to simultaneously destroy and construct frames. Existing research offers little guidance on how actors can accomplish this in the midst of their struggles to survive threatening and disruptive circumstances. I address this shortcoming by drawing from a 22-month ethnography of a Detroit business incubator, analyzing how it gradually developed a novel diagnostic and prognostic frame of the city’s unfolding crisis. I propose and show that actors amid crisis construct a novel frame—while dismantling an old one—through a process of frame restructuration: the novel frame emerges from and co-evolves with unconventional actions that pragmatically address the exigencies of the crisis. Mutual constitution between pragmatic actions and the emergent frame can be critically propelled by the use of metaphor, which helps actors instantly reframe the context.
Non-Contact Ultrasonic Flow Measurement for Small Pipes Based on AlN Piezoelectric Micromachined Ultrasonic Transducer Arrays

In this paper, we propose a non-contact ultrasonic liquid flowmeter based on AlN piezoelectric micromachined ultrasonic transducer (PMUT) arrays. Two 10 by 10 PMUT arrays with resonant frequency of 980 kHz in air are mounted outside of a pipe to measure liquid flow without contacting the liquid. An acoustic matching layer is designed to mitigate the loss of sound waves caused by sound reflection. Under excitation of continuous wave, the flow of the liquid can be determined via detecting the phase difference between transmitting and received signals. The measurement range of flow is 0.515 L/min ~ 3.40 L/min and the measurement error is less than 3%. Moreover, an interpolation method is proposed to reduce the signal sampling frequency without obviously affecting the measurement accuracy, which shows potential for further system integration. [2021-0033]
Mass Spectral Studies to Investigate Butylbenzene Fragmentation Pathway and Pyrolysis Products.

In this dissertation research, two fundamental studies involving gas chromatography mass spectrometry of n-butylbenzene and pyrolysis products are presented. In the first study, fragmentation pathways of n-butylbenzene in quadrupole ion trap have been investigated. At low energy, product ion corresponding to m/z 92 and m/z 91 are formed via competitive parallel dissociation. Studies have also shown that at higher energy m/z 92 has sufficient internal energy to undergo further fragmentation yielding m/z 91 via consecutive dissociation. Thus in order to discern the fragmentation pathways of n-butylbenzene, the technique of two-dimensional correlation spectroscopy (2DCOS) was applied to the mass spectral data. Application of 2DCOS resulted in two 2D correlation spectra namely synchronous and asynchronous. A third spectra known as coherence spectra was obtained from the ration of asynchronous to synchronous correlation intensities. For the elucidation of n-butylbenzene fragmentation pathways, all the three spectra were utilized in this study. The second study in this dissertation involves investigation of pyrolysis products to aid in fire debris analysis. One of the major concerns in fire debris analysis is that pyrolysis products can mask the patterns of compounds of interest and make the chromatographic results interpretation extremely difficult. One of the approaches for investigating the formation of pyrolysis products is to subject the commonly found building materials to controlled heating in laboratory. In this study, new heating methodologies for controlled heating of substrates involving furnace, paint-cans and flat steel pans have been developed. The substrates used for investigating pyrolysis products were polystyrene, polyvinylchloride, polybutadiene, yellow-pine, nylon carpet and padding. Experiments were also performed to investigate the influence of hydrocarbons on the formation of pyrolysis.
Impedance-Based Stability Analysis Methods for DC Distribution Power System With Multivoltage Levels

The stability analysis methods of single-bus dc distribution power systems (DPSs) have been widely studied; however, the multivoltage-level dc DPSs, which have been used in data center, all-electric ship, and so on, its stability analysis methods are rarely reported. The main focus of this article is to study the stability analysis methods, especially the impedance ratio of multivoltage-level dc DPSs. From the point of view of whole system, the two-port small-signal models of multivoltage-level dc DPSs are established and the equivalent loop gains are obtained and used to judge the system stability. On the other hand, the multivoltage-level dc DPSs can be regarded as conventional single-bus dc DPSs at different interfacing locations, and the impedance-ratio type stability criteria are obtained. And it is proved that the two stability analysis methods, namely the system equivalent loop gain and impedance-ratio type stability criterion at different interfacing locations, have the same stability results, which clarifies the stability status by considering different interfacing locations. Finally, the analysis is verified with simulations and hardware-based experiments of a three-converter three-stage dc DPS.
Thai Word Segmentation Based on Sequence-to-Sequence Model

Thai as a low-resource language has a large word segmentation performance improvement space. In this paper, we investigate a sequence-to-sequence model for Thai word segmentation with two different recurrent neural networks, which could transform one input sequence into another output sequence. Furthermore, we evaluate datasets in four different fields compared then with other multiple word segmentation models, and the F1 value in the encyclopedia dataset reaches 97.15%. The results show that the proposed model has superior performance and is more effective, it is worth mentioning that the expected results can be achieved even with limited data resources.
Aluminum and iron behavior in glasses from destabilized spinels: A record of fluid/meltmineral interaction in mantle xenoliths from Massif Central, France

Abstract Infiltrations of melts (and/or fluids) in mantle rocks are witnessed by the presence of glass-bearing pockets in peridotite xenoliths brought to the surface by alkaline volcanism. Several glass-bearing pockets found around spinels corroded at different degrees were investigated for their chemical compositions, including the Fe3+/∑Fe ratios, in two xenolith samples by electron probe microanalysis. The dissolution/recrystallization of spinels enriches the melt in alumina. We show that the spinel-derived Al3+ ions could have been accommodated to the melt network first as network-modifiers. Then Al3+ ions were network-formers using K+ ions, extracted from the aqueous fluid upon melt dehydration, as stabilizers within the tetrahedral site. The transfer of K+ from the aqueous fluid to the melt network is counterbalanced by an inverse transfer of CaO molecules that form crystalline phases exsolved upon eruption. The evolution of the Al content clearly shows that an increasing fraction of the spinel-derived alumina molecules was exsolved as the melt dehydration proceeded. Spinel corrosion could also be at the origin of melt oxidation through dehydrogenation reactions resulting in the formation of Al3+ and Fe3+ anionic complexes within the melt network. This study shows: (1) how the structure of the percolating melt is modified by the accommodation of chemical elements produced by the dissolution of minerals, and (2) how this process could modify the oxidation state of the melt.
Spatiotemporal Prediction for Energy System of Steel Industry by Generalized Tensor Granularity Based Evolving Type-2 Fuzzy Neural Network

Multiscale prediction analysis for the generation and consumption of by-product gas flows in various devices from the various production regions of the steel industry can be regarded as the prerequisite for energy scheduling and allocation. In this article, a generalized tensor granularity (GTG) based evolving interval type-2 (IT2) fuzzy neural network (GTG-EIT2FNN) is proposed to perform the multiscale prediction for spatio-temporal industrial data streams. A generalized IT2 fuzzy <inline-formula><tex-math notation="LaTeX">$C$</tex-math></inline-formula>-means clustering method is presented to extract the similarity characteristics from GTG that considers the spatial location, the semantics of manufacturing processes, the uncertainty triggered by multiple sensors, time-varying and multiscale property. Moreover, the robustness and adaptability of GTG-EIT2FNN is improved by incorporating an extended <inline-formula><tex-math notation="LaTeX">$Q$</tex-math></inline-formula>-learning to learn the optimal policy in terms of the input structure and network ones. A number of industrial study cases show that GTG-EIT2FNN outperforms state-of-the-art comparative algorithms in achieving the best tradeoff between accuracy and simplicity.
Exploring Interleukin-6 ,CRP in cellphone addiction and depression: a case control study in the precincts of medical college

Cellphone technology has tremendously grown in its market and uses in the last decade. But it's overutilization has led to the development of new problems also. Objectionable cellphone use can be accounted for in the form of technological addiction, which can develop depression, anxiety, and other health problems. Depression is the third leading cause of global disease burden if it continues; by 2030, it will become the leading cause of disease burden. Stress or addiction can lead to the development of psychiatric disorders or vice versa. These stressors lead to the neuroinflammatory response, resulting in an exaggerated response to subsequent pro-inflammatory challenges. This study was done with an objective to explore levels of Interleukin-6 and CRP in smartphone-addicted and depressed individuals. Seventy-five cases and 75 healthy controls were selected for the study. Depression was diagnosed by Hamilton depression scale (HAMD) and cellphone addiction was evaluated by smartphone addition scale-short version (SPAS) and their serum sample was evaluated for IL-6 and CRP according to protocol. Overall Mean score of HAMD in cases was 12.21 and in controls was 4.68. Mean score of SPAS scale in cases and controls was (37.75, 17.43) respectively. Mean IL-6 levels of cases and controls (21.03±35.85, 11.07±13.61 pg/ml) respectively with the significance of (p=0.026). Higher levels of the systemic inflammatory biochemical marker IL-6 in cases are associated with depression. Smartphone addiction scores are in correlation with depression scores but not in association with interleukin-6 or CRP levels. Females of a young age are more prone to depression and smartphone addiction together. Early assessment and diagnosis could be helpful in preventing further more damage to social and mental vicinity of individuals. Inflammatory pathways may provide important new interpolation and anticipation targets for these ailments.
A Weighted Spatially Constrained Finite Mixture Model for Image Segmentation

: Spatially Constrained Mixture Model (SCMM) is an image segmentation model that works over the framework of maximum a-posteriori and Markov Random Field (MAP-MRF). It developed its own maximization step to be used within this framework. This research has proposed an improvement in the SCMM’s maximization step for segmenting simulated brain Magnetic Resonance Images (MRIs). The improved model is named as the Weighted Spatially Constrained Finite Mixture Model (WSCFMM). To compare the performance of SCMM and WSCFMM, simulated T1-Weighted normal MRIs were segmented. A region of interest (ROI) was extracted from segmented images. The similarity level between the extracted ROI and the ground truth (GT) was found by using the Jaccard and Dice similarity measuring method. According to the Jaccard similarity measuring method, WSCFMM showed an overall improvement of 4.72%, whereas the Dice similarity measuring method provided an overall improvement of 2.65% against the SCMM. Besides, WSCFMM significantly stabilized and reduced the execution time by showing an improvement of 83.71%. The study concludes that WSCFMM is a stable model and performs better as compared to the SCMM in noisy and noise-free environments.
Meme Kanserinde Sağkalım Durumunu Etkileyen Faktörlerin İncelenmesi: Eğilim Skoru Analizi

Amac: Egilim skoru (ES), incelenen degiskenlerdeki sistematik hatanin duzeltilmesi ya da ortadan kaldirilabilmesi amaciyla ozellikle gozlemsel calismalarda kullanilan bir yontemdir. Rosenbaum ve Rubin (1983) tarafindan gelistirilen bu yontem, bireyin ortak degiskenlere gore ilgili gruba atanmasinin kosullu olasiligi olarak tanimlanir. Bu calismada, ES ile eslestirme yapilarak meme kanseri nedeniyle olumu etkileyen faktorlerin incelenmesi amaclandi. Yontem: Calismada, 423 meme kanseri hastasina iliskin veri seti kullanildi. Sagkalim durumu uzerine yas, tumor buyuklugu, radyoterapi, hormon terapisi, aksiller lenf nodu tutulumu degiskenlerinin etkisi incelendi. Veri setinde yas degiskeni bakimindan gruplar arasi heterojenlik oldugu icin en yakin komsu yontemi kullanilarak eslestirme yapildi. Bulgular: Eslestirme sonrasi yas degiskeninin etkisi ortadan kaldirildi. 1:1 eslestirme sonrasi tumor buyuklugu (p=0,009) ve aksiller pozitif lenf nodu tutulumu ≥4 (p=0,026) degiskenlerinin sagkalim durumu uzerinde anlamli etkisinin oldugu belirlendi. 2:1 eslestirme sonrasi tumor buyuklugu (p=0,004), radyoterapi (p=0,017) ve aksiller pozitif lenf nodu tutulumu ≥4 (p=0,001) degiskenlerinin sagkalim durumu uzerinde anlamli etkisinin oldugu belirlendi. Sonuc: Heterojen yapidaki verilerin dogrudan analiz edilmesi verideki gercek etkilerin goz ardi edilmesine neden olabilecegi icin mutlaka ES yontemi kullanilarak eslestirme yapilmalidir. Bu yontemin en onemli dezavantaji ise eslestirme nedeniyle veri kaybi olmasidir. Bu nedenle cok sayida birimle calisilmasi verideki bilgi kaybinin onune gececektir.
THE COEFFICIENT OF VARIATION AS A PERFORMANCE METRIC OF MIMO ANTENNA SYSTEMS UNDER ARBITRARY HANDSET ORIENTATIONS

The Coefficient of Variation (CoV) is investigated, studied, and proposed as an alternative and important performance metric to describe the effects of handset orientation on the capacity of Multiple-Input-Multiple-Output (MIMO) systems. We combine 3-D simulated radiation patterns of a base station and handset and their associated scattering parameters in two anisotropic propagation environments. The capacity is evaluated as the handset rotates about the X-Y -Z axes using standard Euler’s angles. The coefficient of variation is numerically derived by rotating the handset over the Euler angles (φ, θ, ψ) in each direction every 15◦ about each axis over a full sphere where each rotation involves the creation of numerous instances of the propagation environment depending on the statistical robustness of the results sought. Three antenna array geometries operating at a frequency of 2.45 GHz are examined using two different propagation channel models (TGnB and TGnF) to verify the validity of the proposed approach. The derived results suggest that the proposed CoV is an effective and practical reasonable metric in selecting the best antenna system design, where “best” here refers to the design with the ability to reach the highest throughput of the designs considered.
Design of experiments‐based high‐throughput strategy for development and optimization of efficient cell disruption protocols

Efficient and reproducible cell lysis is a crucial step during downstream processing of intracellular products. The composition of an optimal lysis buffer should be chosen depending on the organism, its growth status, the applied detection methods, and even the target molecule. Especially for high‐throughput applications, where sample volumes are limited, the adaptation of a lysis buffer to the specific campaign is an urgent need. Here, we present a general design of experiments‐based strategy suitable for eight constituents and demonstrate the strength of this approach by the development of an efficient lysis buffer for Gram‐negative bacteria, which is applicable in a high‐throughput format in a short time. The concentrations of four lysis‐inducing chemical agents EDTA, lysozyme, Triton X‐100, and polymyxin B were optimized for maximal soluble protein concentration and ß‐galactosidase activity in a 96‐well format on a Microlab Star liquid handling platform under design of experiments methodology. The resulting lysis buffer showed the same performance as a commercially available lysis buffer. The developed protocol resulted in an optimized buffer within only three runs. The established procedure can be easily applied to adapt the lysis buffer to other strains and target molecules.
Assessing intrinsic and extrinsic motivational orientations between the public and the private high school teachers toward teaching as profession in Jordan

The aim of this research paper is to assess intrinsic and extrinsic motivational orientations between the public and the private sector for high school teachers toward teaching as a profession. A sample of teachers were chosen from the public and the private school in Jordan (N=204). Four hypotheses were tested using independent-samples T-test, the result shows that private school teachers were more motivated by extrinsic compensation motives and extrinsic outward motives, while public school teachers were more motivated by intrinsic challenge motives and intrinsic enjoyment motives. The authors found out that private school teachers perceived themselves motivated by money and rewards, to be better than their colleagues in doing their job and need to have a recognition for their performance at their work. Public school teachers perceived themselves as enjoying tackling new problems and solving complex and difficult problems and considered their job as very important to them.