Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Performance of Isotropic Hyperelastic Constitutive Models for Rubber-Like Materials: A State of the Art Review

Besides the well-known landmark models for the hyperelastic response of rubberlike materials, many new hyperelastic constitutive models have emerged over the last decade. Despite many reviews on constitutive modeling or elastomers, it is still a challenging endeavor for engineers to decide for a constitutive model for the specific rubber compound and application. In this work, we have reviewed 44 hyperelastic constitutive models for elastomers and assessed their strength and weaknesses under uniaxial, pure shear, and (equi)biaxial deformations. To this end, we first present a novel parameter identification methodology based on various multi-objective optimization strategies for the selection of the best constitutive models from a given set of uniaxial tension, pure shear, and (equi)biaxial tension experiments. We utilize a hybrid multi-objective optimization procedure using a genetic algorithm to generate multiple initial points for gradient-based search algorithm, Fmincon utility in matlab. The novelty of the approach is (i) simultaneous fitting with variable weight factors for uniaxial, equibiaxial, and pure shear data, and (ii) the sorting of the models based on objective normalized quality of fit metric. For the models incapable of simultaneously fitting the three distinct deformation data, the validity range is assessed through a threshold value for the quality of fit measure. Accordingly, 44 hyperelastic models are sorted with respect to their simultaneous fitting performance to the experimental dataset of Treloar and Kawabata. Based on the number of material parameters, and their fitting performance to experimental data, a detailed discussion is carried out.
Performance of Clarias gariepinus Juveniles fed fermented Mango Seed Kernel diet at different inclusion level

Bu arastirmanin amaci, meyve isleme ve tuketiminden kaynaklanan tarimsal atiklarin degerlendirilmesidir. Bu atiklar cevresel rahatsizliklara yol acmaktadir ve bu urunlerin su urunleri yemlerine enerji kaynagi olarak katilmasi dusunulmustur. Meyve islemeden kaynaklanan atiklarin kullanimi uc tekerrurlu olarak tanklarda yurutulmustur. Ortalama Agirlik Kazanci (MWG) en yuksek T1 (756.37 ± 13.61g) grubunda tespit edilmis ve diger gruplarla onemli derecede farkli bulunmustur (P 0.05). Deneme yemleri, baliklarin hayatta kalmasi uzerinde hicbir etki gostermedi. Sonuc olarak, yayin baliklar uzerinde herhangi bir etki yapmadan MSKM'nin% 50 seviyesinde ikame edilmesi buyume performansini iyilestirilebilir.
Fault location method of distribution network based on fruit fly optimization algorithm

Fault location is a key procedure during fault diagnosis. However, fault location faces big challenges due to the complexity of distribution network. A fault location method for distribution network is proposed in this paper. Fruit fly optimization algorithm is used in the method for the searching of optimal solution. To analyze the question and construct the simulation model, coding scheme, switch function and fitness function are defined. The algorithm flow based on fruit fly optimization algorithm is designed. Case studies are operated for both traditional distribution network and distribution network containing DGs. The current information distortion is also simulated. The results illustrate that the proposed fault location method based on fruit fly optimization algorithm can correctly locate fault in distribution network, which provide a potential means in fault location.
Facial Expression Recognition based on Image Gradient and Deep Convolutional Neural Network

Facial Expression Recognition (FER) is one of the basic ways of interacting with machines and has been getting more attention in recent years. In this paper, a novel FER system based on a deep convolutional neural network (DCNN) is presented. Motivated by the powerful ability of DCNN to learn features and image classification, the goal of this research is to design a compatible and discriminative input for pre-trained AlexNet-DCNN. The proposed method consists of 4 steps: first, extracting three channels of the image including the original gray-level image, in addition to horizontal and vertical gradients of the image similar to the red, green, and blue color channels of an RGB image as the DCNN input. Second, data augmentation including scale, rotation, width shift, height shift, zoom, horizontal flip, and vertical flip of the images are prepared in addition to the original images for training the DCNN. Then, the AlexNet-DCNN model is applied to learn high-level features corresponding to different emotion classes. Finally, transfer learning is implemented on the proposed model and the presented model is fine-tuned on target datasets. The average recognition accuracy of 92.41% and 93.66% were achieved for JAFEE and CK+ datasets, respectively. Experimental results on two benchmark emotional datasets show promising performance of the proposed model that can improve the performance of current FER systems.
Social Expectations and Abilities to Meet Them as Possible Mechanisms of Youth Personality Development

Rationale: Personality traits change in both mean levels and variance from childhood through mid-adolescence, but the mechanisms underlying these developmental trends remain unknown. We tested the possible roles of social pressure and self-regulation. Methods: The Common-Language California Child Q-Set was used to measure youths’ mean-level personality, social expectations for youths’ behavior from multiple perspectives (parents, teachers, peers) and the self-regulatory requirements for achieving the desired trait levels. Results: There were consistent expectations for youths’ traits, regardless of who described the expectations or whether these pertained to children or adolescents. Mean trait levels were moderately commensurate with social expectations, but age differences in the means did not follow these expectations. Traits with strong expectations showed more pronounced individual differences and increased even more in variance with age. In contrast, traits’ self-regulation requirements did not predict their developmental trends. Implications: Strong social expectations may contribute to the development of individual differences.
PjBL-MOOCs As Future Models for Vocational High Schools

The purpose of this research is to develop a Project Based Learning model assisted by the Massive Open Online Course. The research design uses Research and Development . The results of the feasibility study of PjBL-MOOCs products include: a) design of 93.75%, b) manuals of 95.13%, c) pictures and charts / charts of manuals of 92.31, d) material of 85%, e ) picture quality in material is 77.1%, f) video is 90.4%, g) test instrument is 90.4%, and h) field trial results is 72%. So that PjBL-MOOCs are feasible to improve student learning outcomes.
Investigating a Register on Language Displayed in the Billboard of Food and Beverage in Medan

This research is aimed to investigate a register used in the Billboard of foof and beverage in Medan city, Indonesia. As we know, language used in the billboard of food and beverage in Medan was different from that used by people in daily conversation. There was specific terms to explain the event that happens in the billboard of food and beverage. Many registers used in the billboard of food and beverage could be found especially in English. In this case, this research analyzed the lexical meaning of register used in the billboard of food and beverage. The type of this research was descriptive qualitative research. The object of this research was the register used in the billboard of food and beverage. The data were register words. The data source was the billboard of food and beverage. In collecting the data, the researcher looked for the billboard of food and beverage, data collection, data reduction, data display, verifying conclusion. In analyzed the data, the writer classified the data, analyzed the lexical meaning of register and analyzed how was register realization displayed in the billboard of food and beverage. Based on the analyzed, the researcher found 17 data register words, and then analyzed to the lexical meaning. And the researcher found that the registers on the billboard of food and beverage were realized in different ways according to the context and Based on the field, tenor, and mode.
Embedding Disentanglement in Graph Convolutional Networks for Recommendation

Recent years have witnessed the rapid development of recommender systems. To improve recommendation performance, many efforts have been made to study how to equip the conventional methods with auxiliary information such as item relations. Meanwhile, a growing body of work has focused on applying graph convolutional networks to recommendation tasks. Thus, it is promising to use graph convolution to model multi-order relations among users and items for improving recommendation performance. However, the existing graph convolution-based recommendation methods may suffer from structural design problems: for methods with embedding transformations in graph convolutional layers, the MLP makes the updated embedding dimensions coupled, hurting the embedding expressivity. While for methods based on simplified graph convolution, removing the parameter matrices makes the model attach the same weight to embeddings in different layers, which may be over-simplified and limit the model expressivity. In this paper, we propose a novel graph convolution-based recommendation method, namely Channel-Independent Graph Convolutional Network (CIGCN). To learn disentangled embeddings, CIGCN uses diagonal parameter matrices as filters in graph convolution, keeping the updated embedding dimensions independent. In addition, with layer-aggregation strategies, the parameters in the diagonal matrices act as trainable weights that attach different importance to the embeddings in each layer and each dimension, enhancing the model expressivity. Results of extensive experiments on four real-world datasets show that CIGCN significantly outperforms baseline methods in recommendation accuracy and could learn better representations for users and items.
Optical, electrical, and magnetic properties of Pd3Lu and PdLu

Temperature dependences of the electrical resistivity p(T) and magnetic susceptibility X(T) and the dependence of the complex dielectric constant on the angular frequency of light wave e(ω) (ω is the cyclic frequency of the light wave) were studied for the Pd 3 Lu and PdLu compounds. The compounds are diamagnetic and have metallic conductivity. An analysis of the magnetic susceptibility of Pd 3 Lu showed that the diamagnetic contribution predominates over the paramagnetic conduction electron spin susceptibility. It was concluded that both PdLu and Pd 3 Lu are characterized by a low density of states at the Fermi level because of low contributions from d electrons of the constituents. Parameters of charge carriers-the plasma frequency Φ and the relaxation frequency γ 0 -were determined from the experimental dependences e(ω). The correlation between the optical resistivity (for experimental data extrapolated to zero frequency ω) and static resistivity is found for both PdLu and Pd 3 Lu compounds. The substantial difference in the interband absorption of PdLu and Pd 3 Lu shows that the 4d band of PdLu lies below that of Pd 3 Lu.
Incomplete Implant Insertion Due to the Use of A Non-dynamometric Torque Wrench: A Case Report

A case is reported in which the use of a nondynamometric torque wrench could be the cause of incomplete implant insertion. A woman, 73-year-old, visited the dentist in March 2021 for oral rehabilitation due to the absence of teeth in the left mandibular area. A Galimplant IPX 4.5 x 8 implant (internal hex connection) (Sarria, Spain) was placed in position 36. Bone drilling was performed correctly in width and depth, however, insertion of the implant was difficult due to the hardness of the cortical bone. New drillings were made in the bone with insertion and removal of the implant on three occasions. On the third occasion, the implant was threaded to a depth of 7 mm. At that time, the thread that the implant had carved in the bone had been lost and the implant did not advance until 8 mm in depth, nor could it go back to remove it and continue drilling the bone. We estimate that a dynamometric torque wrench should have been used during implant insertion, to provide adequate torque and not cause the loss of the thread that the implant had carved into the bone. The use of a non-dynamometric torque wrench does not allow a precise insertion torque. If excessive torque is applied, the thread carved by the implant in the bone can be lost and this finally causes an incomplete insertion of the same.
FORMATIVE ASSESSMENT OF CRITICAL READING SKILLS IN HIGHER EDUCATION IN RUSSIA IN THE CONTEXT OF EMERGENCY REMOTE TEACHING

The paper considers the role of formative assessment of critical reading skills within the framework of distance education in conditions of emergency remote teaching English as a foreign language. A model of descriptors for assessment of critical reading skills at 4 levels of language competence and 3 levels of university education has been developed and tested on undergraduate and postgraduate students majoring in Economics, IT and the Humanities in Saint-Petersburg State University of Economics. The model has been tested and conclusions have been made about the effectiveness of formative assessment as a supplementary/helpful tool for the development of critical reading skills in emergency learning conditions of COVID pandemic.
Realization with Fabrication of Double-Gate MOSFET Based Buck Regulator

The traditional buck regulator provides the steady output voltage with high efficiency and low power dissipation. Various parameters of this regulator can be improved by the placement of Double-Gate (DG) MOSFET. The double-gate MOSFET provides twice the drain current flow, which improves the various parameters of buck regulator structure and inevitably increases the device performance and efficiency. In this research work, these parameters have been analyzed with implemented DG MOSFET buck regulator and realized the total losses 42.676 mW and efficiency 74.208%. This research work has designed a DG MOSFET based buck regulator with the specification of input voltage 12 V, output voltage 3.3 V, maximum output current 40 mA, switching frequency 100 kHz, ripple current of 10%, and ripple voltage of 1%. 
Unveiling the End-User Viewport Resolution From Encrypted Video Traces

Video streaming is without doubt the most requested Internet service, and main source of pressure on the Internet infrastructure. At the same time, users are no longer satisfied by the Internet’s best effort service, instead, they expect a seamless service of high quality from the side of the network. As result, Internet Service Providers (ISP) engineer their traffic so as to improve their end-users’ experience and avoid economic losses. Content providers from their side, and to enforce customers privacy, have shifted towards end-to-end encryption (e.g., TLS/SSL). Video streaming relies on the dynamic adaptive streaming over HTTP protocol (DASH) which takes into consideration the underlying network conditions (e.g., delay, loss rate, and throughput) and the viewport capacity (e.g., screen resolution) to improve the experience of the end user in the limit of the available network resources. In this work, we propose an experimental framework able to infer fine-grained video flow information such as chunk sizes from encrypted YouTube video traces. We also present a novel technique to separate video and audio chunks from encrypted traces based on Gaussian Mixture Models (GMM). Then, we leverage our dataset to train models able to predict the class of viewport (either SD or HD) per video session with an average 92% accuracy and 85% F1-score. The prediction of the exact viewport resolution is also possible but shows a lower accuracy than the viewport class.
Supported Gold Nanoparticles as Reusable Catalysts for Oxidation Reactions of Industrial Significance

The efficient single‐pot oxidative functionalisation of alkanes and alcohols under mild conditions was catalysed by Au nanoparticles supported on Al2O3, Fe2O3, ZnO and TiO2. The obtained materials were tested for cyclohexane oxidation under mild conditions (60 °C, atmospheric pressure) using an environmentally friendly oxidant (H2O2). The materials were also tested in the oxidation of benzyl alcohol and methylbenzyl alcohol in the presence of tert‐butylhydroperoxide as the oxidant under microwave irradiation. With regard to cyclohexane oxidation, all materials were highly selective towards the formation of cyclohexanol and cyclohexanone. No traces of byproducts were detected under the optimised conditions. Au on Fe2O3 led to the best results (13.5 % yield). This system showed an interesting almost exclusive formation of cyclohexanol at 4 h reaction time. Catalyst recycling was tested in up to five cycles, and the catalyst maintained almost the original level of activity after three cycles with no significant leaching. With regard to oxidation of benzyl alcohol and methylbenzyl alcohol, all materials were highly selective towards the formation of benzaldehyde or acetophenone, respectively. No traces of byproducts were detected. Addition of Au increased alcohol conversion from 5 (TiO2) to 91 % (Au/TiO2). The recycling of Au/TiO2 was tested in up to 10 cycles, and the catalytic activity remained high in the first four cycles.
Multi-Scale Superhydrophobic Anti-Icing Coating for Wind Turbine Blades

As a surface functional material, super-hydrophobic coating has great application potential in wind turbine blade anti-icing, self-cleaning and drag reduction. In this study, ZnO and SiO2 multi-scale superhydrophobic coatings with mechanical flexibility were prepared by embedding modified ZnO and SiO2 nanoparticles in PDMS. The prepared coating has a higher static water contact angle (CA is 153°) and a lower rolling angle (SA is 3.3°), showing excellent super-hydrophobicity. Because of its excellent superhydrophobic ability and micro-nano structure, the coating has good anti-icing ability. Under the conditions of −10 C and 60% relative humidity, the coating can delay the freezing time by 1511S, which is 10.7 times slower than the normal freezing time. More importantly, due to the mechanical properties provided by SiO2 and the synergistic effect of micro-nano particles, the coating has excellent mechanical durability. After 10 wear tests, the contact angle of the coating is still as high as 141° and the rolling angle is 6.8°. This research provides a theoretical reference for the preparation of a mechanically stable coating with a simple preparation process, as well as a basic research on the anti-icing behavior of the coating.
Tracking young-of-the-year gray seals Halichoerus grypus to estimate fishery encounter risk

The current level of annual incidental bycatch of gray seals Halichoerus grypus in the New England sink gillnet fishery is the highest for all marine mammal species in the USA. One way to evaluate the risk of bycatch is to examine the risk of encounter between an animal and fishing gear based on the animal’s habitat use in relation to fishing activity. Here we used satellite telemetry deployed on 30 gray seal pups in 2019 and 2020 to measure the risk of encounter with large-mesh sink gillnet fishing effort throughout the Gulf of Maine and southern New England. We estimated relative encounter risk within 30 min grid cells in each calendar quarter based on the overlap of seal presence and fishing effort, and then validated the expected risk based on bycatch events reported by independent observers on board fishing vessels. The relative risk of seals encountering gillnet fishing gear was highest off southeastern Massachusetts in spring. Patterns in the estimated encounter risk fit our expectation that relatively high levels of habitat use and fishing effort correspond to increased encounter risk. The approach taken here can be used to identify times and areas of high encounter risk to justify altered fishing practices for purposes of avoidance, or to target observer monitoring intended to characterize and quantify bycatch. Mitigation strategies will need to be continuously monitored and updated to incorporate new information as conflicts with fisheries and gray seals are likely to continue.
FLORA DIVERSITY OF FIELD FOREST PATCHES IN LANDSCAPES WITH VARIED GEOMORPHOLOGICAL UNITS AND LAND USE IN POLAND

A diverse terrain is one of the essential natural features of a balanced landscape and the specific features of its geomorphological units (sandur, moraine) contribute to regional diversity. The present work describes research designed to verify the hypothesis that the diversity of flora in the ecotone zone of woodland in Poland relates to variability both in the terrain and in land use. By using phytoindication it was possible to assess differentiation in the surfaces under study. It was found that land use (agricultural and forest use) was responsible for the occurrence of a positive interrelationship between trophy and synanthropisation values, no matter what kind of geomorphological unit there was. On the basis of the species composition in the areas under research, within the ecotone zone of woodland, it was established that in the area within moraine which had previously been used agriculturally there was a cumulation of species due to habitat diversity in ecological niches resulting from the terrain, the amount of mineral nutrients in the soil and a large amount of, in particular, native and neutral species in the gene pool.
A Novel Wireless Charging Technique for Low-Power Devices Based on Wiegand Transducer

During last decade biomedical devices have become more and more performing, covering an increasing number of usages. In particular, subcutaneous devices represent one of the most invasive yet innovative application; their battery management is one of the most challenging topics because, once implanted, they can be handled only through surgery, so wireless charge is the only way to feed subcutaneous systems with appreciable energy in a controlled manner. But differently from conventional consumer devices, in this scenario the energy delivered necessarily runs into human body and tissues, so the main challenge consists in maximizing the “energy delivered versus energy dissipated in tissues” ratio, in order to guarantee human safety first while also conveying an appreciable amount of energy to the implanted device. After analyzing the state-of-the-art of the principal techniques, this article proposes a novel architecture for low-power wireless charging, based on a Wiegand sensor used as a transducer in order to fulfill all the requirements from both electrical and medical points of view; such architecture is implemented inside an IC prototype in 0.35- $\mu \text{m}$ lithography that acts as an ultralow-power DC–DC buck converter and battery manager.