Miracle-dz/UniFAR-FTUs huggingface dataset:
Controlled Synthesis of CuO from needle to flower-like Particle Morphologies for Highly Sensitive Glucose Detection

CuO particles with morphologies ranging from “needle”, “flat flowers” to “peony-like” flower shape were prepared by varying hydrothermal reaction times. The structure and morphology of the CuO samples were characterized by X-ray diffraction, BET and scanning electron microscopy, and these samples were evaluated as catalysts for glucose oxidation in alkaline solution. Of the three particle morphologies, peony-like CuO produced the highest glucose sensitivity of 1322 μA mM -1 cm -2 , with a broad detection range of 1.0 μM 4.0 mM, and a detection limit of 0.5 μM under an applied potential of +0.5 V vs. Ag/AgCl. The peony-like CuO electrode also had excellent selectivity in the presence of interfering agents which usually co-exist in solution, for example uric acid, ascorbic acid and sodium chloride). Overall, we conclude that complex particle structure (of possible multiple grain boundary content) improves sensitivity for glucose detection and forms a target for developing effective nonenzymatic sensors.
Broadband and High Power Meta-Surface Dielectric Window for W-Band Gyrotron Traveling Wave Tubes

A periodic dielectric meta-surface output window was cold and hot tested to extend the operating bandwidth and suppress the parasitic oscillations for a W-band wideband TE01 mode gyrotron traveling wave tube (gyro-TWT) in this letter. The fabricated beryllium oxide meta-surface dielectric window demonstrates a relative bandwidth of 37.84% with the reflection below −20 dB in the range of 75–110 GHz. The influences of engineering factors and machining errors on the performance are investigated and analyzed. Thermal analysis shows the average power handling capability of the window is over 33 kW within a wide frequency range. Hot test results demonstrate that the meta-surface window is excellent for oscillation suppression and the power handling capability is predicted larger than 20 kW.
Deep learning of deformable registration for breast DCE-MRI images

Conventional image registration approaches optimize an objective function for each pair of images, which can be time-consuming for a large dataset. In this work, we proposed a deep learning method for breast DCE-MRI images that eliminates the need for time consuming iterative methods, and directly generates the registered image with the deformation field. The model is trained by optimizing the similarity measurement between original images and distorted motion images without manual annotation information from doctors. Enhanced image is distorted into the original image through spatial transformation network to obtain the registration result. Our method can speed up medical image analysis, while facilitating novel directions in deep learning-based registration and its applications. The experimental results show that the model is effective and robust for breast images.
Application of Nanoporous Carbon, Extracted from Biomass Combustion Ash, in CO2 Adsorption

Bioenergy with Carbon Capture and Storage has been regarded as one of the most prominent technologies in the battle against climate change as stated in the latest Intergovernmental Panel on Climate Change reports. However, solid residues generated during the combustion of biomass pose a separate set of environmental and economic challenges that must be addressed. In order to utilise the full potential of this waste stream, an effective nanoporous carbonaceous adsorbent for CO2 capture has been directly prepared via a simple and low-cost extraction technique from industrial-grade biomass combustion bottom ash generated at a UK power plant. The adsorbent characterisation data (via Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy as well as Fourier- Transform Infrared Spectroscopy) agrees well with the CO2 adsorption curves obtained through thermogravimetric analysis (TGA). The TGA results have revealed a CO2 adsorption capacity of 0.73 mmol/g at 25°C and 1 atm under a pure CO2 gas stream, thus, proposing a promising and viable route towards in-situ decarbonisation of the biomass combustion sector in the UK via effective waste valorisation.
Electrothermal Parameters of Graphene Nanoplatelets Films

This paper investigates the electrothermal behavior of industrial films made by graphene nanoplatelets (GNP) mixed to polymers, with the final goal of deriving their equivalent electrical resistivity and thermal emissivity. The two parameters are identified by means of suitable models and experimental characterization with ad-hoc test-fixture. The materials analyzed here are thin strips of the order of 1×10 cm, with a thickness of 75 µm, both made by pressed GNPs, mixed to a small quantity of polymeric binders. An analytical model to describe the temperature-dependence of the electrical resistivity is proposed. The impact of the binder percentage (5% or 20%) on the electrical resistivity and thermal emissivity is also studied.
A Low-Profile Vacuum Actuator (LPVAc) With Integrated Inductive Displacement Sensing for a Novel Sit-to-Stand Assist Exosuit

Muscle weakness owing to stroke, spinal cord injuries, or aging can make a person’s life sedentary, temporarily as well as permanently. Such persons need to be motivated to break their sedentary postures and attempt independent motion. A key motivator in this aspect is the ability to easily transition from seated to standing posture. If this sit-to-stand transition (STSt) is easy, it will encourage further mobility. A soft wearable device that can assist the STSt, would fill this need perfectly. Such a device should be able to seamlessly assist during STSt and be unobtrusive during sitting. A major limitation that is currently holding back the development of soft exosuits in STSt-assist is the lack of low-profile soft actuators with high strain rate and force-to-weight ratio. Hence, we propose a novel low-profile vacuum actuator (LPVAc) with an integrated inductive displacement sensor that, can be rapidly fabricated, is lightweight (14g), and can provide high strain (65%) and a high force-to-weight ratio (285 times self-weight). The proposed actuator comprises a low-profile spring encased within a low-density polyethylene film with rapid vacuum actuation and passive quick return. The proposed inductive sensor has a sensitivity of $0.0022~\mu H/mm$ and the hysteresis is below 1.5% with an overall absolute average error percentage of 5.24%. The performance of the proposed integrated sensor in displacement control of the LPVAc is experimentally evaluated. The proposed actuator is integrated into a novel mono-articular STSt-assist exosuit for preliminary testing. Surface electromyography measurements of the gluteus maximus muscles during STSt indicate a mean muscle activity reduction of 45%. This supports the potential use of the proposed actuator in STSt-assist.
Enhanced image encryption algorithm by quantum key distribution

Quantum Key Distribution (QKD) is one type of Quantum Cryptography (QC) which is based on quantum mechanics fundamentals such as Heisenberg’s uncertainty principle and No-cloning theory. The usage of QKD warns the legitimate communicated parties to any attack attempt and this is the most interesting security parameter. Therefore, QKD provides unconditional secure communication method and supports a powerful encryption scheme. The combination between classical communication and QKD creates a new technique called semi quantum key distribution SQKD. Unfortunately, SQKD increases the schemes complexity and requires two steps for ciphering, scramble and encryption. In this paper an enhance image encryption algorithm is proposed based on QKD that eliminates most of the drawbacks of SQKD. The proposed algorithm is simpler than other encryption schemes as it exploits only one encryption step based on the power and the randomness of the generated secret key, which decreases the chance to be cracked. The correctness and efficiency of the proposed algorithm are validated by numerical simulations.
Vibration analysis of composite wing with geometric and material coupling

Composite wing design is complicated but inevitable to enlighten modern airplanes while maintaining the required performance. Using the dynamic transfer method, this paper discusses intensively the dynamic characteristics of a cantilever composite wing with both torsion and bending coupling to represent both material and geometric coupling. The governing differential equations are obtained based upon the principle of Hamilton and are solved analytically using a harmonic oscillation assumption. For this purpose, a MATLAB code is developed and results are validated in comparison with published work. Such a comparison shows a good agreement between both results. Finally, a parametric study is carried out to show the influence of the variation of both geometric coupling and torsion bending coupling rigidity on the free vibration analysis of the composite wing. The study shows the crucial effect of both factors on the dynamic behavior of the composite wing. The current research can be considered as a base for aeroelasticians while designing composite structures.
Multidisciplinary Perspectives in Higher Education Remote Engineering Education Under COVID-19 Pandemic Environment

As a result of the sudden onset of the COVID-19 pandemic, engineering curriculums that were taught in-person for decades were forcibly transitioned into a remote-learning environment in such a short time that instructors and students alike could not adequately consider how to replicate the efficacy and efficiency of in-person learning to the remote learning environment. In this essay, the problem of effective replication is studied from the perspective of emotional experiences that lead to effective learning. Through this review, the authors hope to enlighten instructors and students about simple and effective practices that can be implemented in this harsh environment and to mitigate the effect that COVID-19 will inevitably have on the effectiveness and enrollment of engineering undergraduate curriculums.
Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy

The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni3Pd3Au2(111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations.
Ilomata International Journal of Management (IJJM)

This study aimed at understanding the effects of corporate social responsibility, corporate image, customer attitude, and customer loyalty. The method used for this study was causality and nonprobability sampling and purposive sampling were used as the data collection methods. The data source in this study was primary data collected using questionnaire instruments. The number of samples of the study was 100 respondents. The data analysis model in this study used path diagrams in the form of regression equations. The results of the statistical study showed that: (1) Corporate social responsibility and customer immunity both partially and simultaneously had a positive effect on customer attitude, (2) Corporate social responsibility and corporate image, both partially and simultaneously, had a positive effect on customer loyalty. (3) Corporate social responsibility, customer image, and customer attitude simultaneously had a significant effect on customer loyalty. Partially, only corporate social responsibility and customer image had a significant effect on customer loyalty, while customer attitude had no significant effect. (4) The customer attitude variable was able to mediate the effects of corporate social responsibility and customer image on customer loyalty.
Comparison of Crestal Bone Levels of Prevail Implants with Platform-Switched: Following One Year

Purpose: To evaluate the changes in the bone crest around the implants with abutments with platform-switched in a retrospective clinical investigation derived from a previous study. Materials and Methods: Twenty-six healthy patients mean age of 51,6 ± 11,4 with one or more missing teeth were consecutively treated with Prevail implants, with and without platformswitched, conical, and with complete treatment. A total of 68 implants were placed test group with a prevailing implant with platform-switched (34 implants) and control group with the prevailing implant without platform-switched (34 implants). The final restorations were delivered 4 to 11 months after the insertion of the implant. Digital standardized periapical radiographs using customized film holders were obtained at the time of implant insertion and 12 months after. Marginal levels of peri-implant bone were measured on the mesial and distal surfaces of each implant using digital imaging software. Results: All the osseo integrated implants were clinically stable at the 12-month follow-up. The cumulative survival rate was 100%. The average bone loss was 1,34 ± 1,02 mm on mesial and 1,57 ± 0,99 mm on distal for the control group and 0,56 ± 0.85 mm on mesial and 0,82 ± 0,92 mm on distal for the test group. There are no significant differences related to sex, implant site, and bone density.
WASH Intervention Effects and Implications in Rural Schools and Communities of Georgia

The present article is a combination of research and policy analysis around Water, Sanitation and Hygiene (WASH) interventions implemented by Georgian Medical Group (GMG) in the period of 2015-2021 in rural schools and communities in two regions of Georgia: Adjara and Guria. The mentioned WASH efforts have been funded by the United States Agency for International Development (USAID) and the Coca-Cola Foundation through Global Water Challenge, New World and CARE International in the Caucasus. The shares in funding have been distributed as 85% USAID and 15% the Coca-Cola Foundation. All three components of the effort proved to be quite successful i.e. 4,202 school children in the target regions have substantially improved water supply, toiletry, sanitation and hygienic habits International Journal of Medical Science and Health Research Vol. 5, No. 03; 2021
The effect of salinity on seed germination, early seedling growth and anatomical structure of Beta vulgaris

Beta vulgaris belongs to the family Amaranthaceae and was found to have halophytic ancestors. The objective of this study was to investigate the effect of sodium chloride on seed germination, therefore the early stages of seedling growth of Beta vulgaris grown under different salinity levels (0, 100, 150 and 200 mM of NaCl) were studied. The experiment was laid out in a completely randomized design (CRD) with four replications. It was revealed that as concentration of NaCl increases, the rate and percentage of germination, length and fresh weight of radicle & plumule and seedling vigour index decrease. In conclusion, our results indicated that salt stress decreased Beta vulgaris seed germination and early seedling growth while induced changes in the anatomical characteristics such as increased level of cutin synthesis on epidermal leaves cells and altered the thickness of vascular system, epidermis and parenchyma in leaves, roots and petioles.
Deep Convolutional Neural Network Feature Extraction for Berry Trees Classification

To support biodiversity conservations, plant classification studies, particularly from images, are necessary. This study explores the use of the deep convolutional neural network as a feature extractor to a plant classification problem. An original dataset consisting of images of seedlings of the three most important berry trees belonging to the Philippine indigenous plants was used. The result shows that as the network layers are getting deeper, they are becoming better at extracting discriminative features, such that, irrespective of classifier used their prediction performance keeps on improving. When the different layers were individually visualized, the features extracted were far from random, uninterpretable patterns. Rather, they show relevant properties that are capable of sorting patterns progressively from low to higher level. Hence, for classification problems bounded with the limitation of data, time, and computational hardware, leveraging the representational power of the deep convolutional neural network is very useful.
Portocaval Shunt in Liver Transplantation, Why not?

*Correspondence: Laura Tortolero, Department of Liver Surgery, Ramón y Cajal Hospital, Carretera de Colmenar Viejo, Km 9, 100, Postal Code: 28034, Madrid, Spain, Tel: (+34) 656 518 646; E-mail: laura_tortolero@yahoo.com Received Date: 02 Jun 2020 Accepted Date: 02 Jul 2020 Published Date: 22 Jul 2020 Citation: Tortolero L, Nuño J, Luengo P, Gajate L. Portocaval Shunt in Liver Transplantation, Why not? Clin Surg. 2020; 5: 2871. Copyright © 2020 Laura Tortolero. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Letter to Editor Published: 22 Jul, 2020
Functional state dynamics in cross-country skiers in the summer and autumn preparatory phase

Purpose: To study changes in the functional state of professional Russian cross country skiers in the course of the preparatory phase and their effects on their competition ratings. Material: In this study we examined 10 cross-country skiers. The functional state was assessed through a maximal load bicycle ergometer test, coordination and special performance tests. Concentrations of lactate and cortisol were checked in the blood plasma of participants. Results: The training effects on general physical preparedness and special physical preparation in September in comparison with June were observed as an increased number of pull-ups on a pull-up bar (by 14%) and decreased time of the roller ski test (by 4%). In autumn higher systolic (by 11%) and diastolic (by 10%) arterial blood pressure levels, higher levels of plasma lactate and cortisol (by 48% and 64%, respectively) were detected (p<0.05). At anaerobic threshold the following increased: total performance capacity (by 13%), oxygen consumption (by 14%), watt pulse (by 5%), respiratory minute volume, oxygen utilization coefficient, and oxygen pulse (by 15%) (p<0.05-0.01) at rest before the ergometer test. In September upon completion of the ergometer test we observed an increase of oxygen pulse (by 7%), watt pulse (by 10%), and oxygen utilization coefficient (by 24%) (p<0.05). In autumn at the 5th minute of recovery after the ergometer test the heart rate recovered 11% faster, blood lactate – 29% faster, and the oxygen utilization rate increased by 15% (p<0.05-0.01). In June no statistically significant correlations were found between the studied indicators. In autumn statistically significant correlations appeared between indicators of the cardiorespiratory system, physical performance, and coordination test time. Conclusions: The package program for the summer-autumn training period contributes to the improvement of the functional status of the cross-country skiers and to the development of physical power, endurance, increased strength of the upper limbs, increased speed of movement on roller skis, faster and more complete recovery of physiological and biochemical parameters.
Modeling and Assessing Systematic Risk in Stock Markets in Major Oil Exporting Countries

Results & discussions. The results of the paper support significant evidence of time-varying beta coefficients for all sectors included in the study, in particular the banking sector, and relatively with a lesser degree, the food, and the service sectors in both countries. For the banking sector in Saudi Arabia, the beta coefficients variability during the sample period estimated between (0.18 to 22.1), and also for Kuwait stock market the beta coefficient of the banking sector variability estimated between (0.16 to 22.1). This result invalidates, at least in the context of the sample country’s banking sectors, the standard application of (CAPM) that assumes constant beta coefficients. Also indicated in the paper, time-varying beta estimates are consistent with a modified version of CAPM prediction that is portfolios with wider range of beta variations expected to yield higher return values and those with lower range of beta variations yield lower returns.
Partial Oxidation of High Entropy Alloys. A Route Towards Nanostructured Ferromagnets?

The present work proposes a new approach to the development of nanostructured ferromagnetic composites based on the progressive oxidation of high entropy alloys. Sequential ‘subtraction’ of the metals with lowest oxidation energy destabilizes the remaining solid solution, inducing phase separation at the nanoscale. By exploring immiscibility routes in the multidimensional phase diagram, the strategy can be used to promote intimate contact between mixed oxides and metallic solid solutions with desired magnetic properties. To demonstrate the concept, the relation between oxidation energy, phase separation and magnetic behavior has been investigated across the (CoCrCuFeNi)O x composition space, for 0.1 [[EQUATION]] x [[EQUATION]] 1.3, in materials produced by reactive sputtering. The results point out directions for tuning the composition when aiming for phases with specific magnetic properties arranged in complex microstructures.
Treatment of Oesophageal Cancer with NiTi Stents- An Overall Review

Review Article Esophageal cancer is known to be one of the most commonly affecting disease world wide. People with esophageal cancer develop various symptom. One among those symptoms is esophageal cancer. There are various treatment for esophageal cancer but those treatments were found to have many disadvantages. In recent field of science with various advancements in technology self expanding metal stents (SEMS) and self expanding plastic stents (SEPS) were used. There are various literature stating the uses of other palliative therapy, although it had the same uses it was found to have many disadvantages and are traumatic when compared to SEMS and SEPS. Therefore we conclude that SEMS and SEPS are less traumatic when compared to other palliative treatment.