Miracle-dz/UniFAR-FTUs huggingface dataset:
Silicon and III-V Solar Cells: From Modus Vivendi to Modus Operandi

In the present paper, some novel opportunities for the development of high-efficient Si and III-V-based solar cells are considered: energy-saving environment friendly low-temperature technology of forming p-n junctions in Si (1), elaboration of structurally perfect GaAs/Ge/Si epitaxial substrates (2) and application of protective antireflecting coatings based on cubic zirconia (3). As a result: 1) New technique of forming p-n junctions in silicon has been elaborated. The technique provided easy and comparatively cheap process of production of semiconductor devices such as solar cells. The essence of the technique under the study is comprised in formation p-n junctions in silicon by a change of conductivity in the bulk of the sample occurring as a result of redistribution of the impurities, which already exists in the sample before its processing by ions. It differs from the techniques of diffusion and ion doping where change of conductivity and formation of p-n junction in the sample occur as a result of introduction of atoms of the other dopants from the outside; 2) The conditions for synthesis of GaAs/Ge/Si epitaxial substrates with a thin (200 nm) Ge buffer layer featured with (1 - 2) × 105 cm-2 density of the threading dislocation in the GaAs layer. Ge buffer was obtained by chemical vapor deposition with a hot wire and GaAs layer of 1 μm thick was grown by the metal organic chemical vapor deposition. Root mean square surface roughness of GaAs layers of the less than 1 nm and good photoluminescence properties along with their high uniformity were obtained; 3) The conditions ensuring the synthesis of uniform functional (buffer, insulating and protective) fianite layers on Si and GaAs substrates by means of magnetron and electron-beam sputtering have been determined. Fianite films have been shown to be suitable for the use as an ideal anti-reflecting material with high protective and anticorrosive properties.
Representativeness assessment of the pan-Arctic eddy-covariance site network, and optimized future enhancements

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatio-temporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network’s representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets, and changes therein. This study provides an inventory of Arctic (here >= 60° N) EC sites, which has also been made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/). Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, based on 18 bioclimatic and edaphic variables, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as under-represented. This division between regions is further emphasized for wintertime and methane flux data coverage. Across the Arctic, particularly mountainous regions were poorly represented by the current EC observation network. We tested three different strategies to identify new site locations, or upgrades of existing sites, that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 percent, upgrading as few as 10 existing sites to capture methane fluxes, or remain active during wintertime, can improve their respective network coverage by 28 to 33 percent. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

We used 4 types of datasets: Mouse retina transcriptomes (Macosko et al., 2015; Poličar et al., 2019), Fashion MNIST (Xiao et al., 2017), EMNIST Letters (Cohen et al., 2017), and CIFAR-10 (Krizhevsky et al., 2009). The details on the datasets and the numbers used in training and evaluations are shown in Table 1. The Mouse retina transcriptomes dataset consists of PCA projections of single-cell transcriptome data collected from mouse retina. The Fashion MNIST dataset consists of 10 types of clothing such as shirts, sneakers, and ankle boots. The EMNIST Letters dataset is a set of handwritten alphabet characters of 26 classes. The CIFAR-10 dataset consists of real-world images in 10 classes such as airplanes, automobiles, birds and cats. Except for Mouse retina transcriptomes dataset, the distribution of classes is uniform. The class distribution of the Mouse retina transcriptomes dataset is shown in Table 2. The distribution of each dataset is visualized in Figure 1. For visualization, each dataset was projected into a 2-dimensional embedding space using Parametric UMAP.
Survey on Aspect Based Sentiment Classification Using Machine Learning Framework for Online Reviews

: The tourism and travel sector is improving services using a large amount of data collected from different sources. The easy access to comments, evaluations and experiences of different tourists has made the planning of tourism rich andcomplex. Therefore, a big challenge faced by tourism sector is to use the gathereddata for detecting tourist preferences. Unfortunately, some user's comments are irrelevantand complex for understanding these becomes hard for recommendation. Aspect based sentiment classification methods have shown promise in overcomethe noise. In existing not much work on aspect based sentiment with classification.This paper presents a framework of aspect based sentiment classification recommendationsystem that will not only identify the aspects very efficiently but can perform classification task with high accuracy using machine learning naive Bayesand Decision Tree algorithms. The framework helps tourists and the best place,hotel and restaurant in a city, and performance has been evaluated by conductingexperiments on Yelp and foursquare real-time datasets.
Impact of Knowledge Management Process on Product Innovation in Manufacturing Firms

The current study seeks to investigate the relationship between the dimensions of the knowledge management process and product innovation in manufacturing firms. Specifically, the study examines the autonomous effect of knowledge acquisition, knowledge sharing, and knowledge application on product innovation. 361 copies of questionnaire were sent out, with a 97.2% response rate. Using PLS-SEM, the survey data were checked for common error variance, validity, and reliability. Structural equation modeling was used to test the hypothetical framework. Results demonstrate empirical support for the model. Findings indicate a positive relationship between the knowledge management process (acquisition, sharing, and application) and product innovation in the manufacturing plants sampled. Therefore, each dimension of the knowledge management process plays a crucial role in product development and innovation. These findings serve as a useful guide for managers in designing and mainstreaming the knowledge management process into administrative action for better innovation performance.
A PLISSIT-Model Intervention in People with Type 2 Diabetes with Sexual Problems: Results from a Cluster-Randomized Controlled Trial in Primary Care

Introduction: Sexual problems are prevalent among people with type 2 diabetes, but often remain unaddressed in primary care. We hypothesized that the use of a steppedcare sexual counseling strategy, such as PLISSIT (Permission, Limited Information, Specific Suggestions, Intensive Therapy), would lead to improved (sexual) well-being. Aim: To evaluate the effectiveness of a PLISSIT-model-based intervention on sexual functioning, sexual satisfaction, and quality of life in men and women with type 2 diabetes aged 40-75 years who indicated to be dissatisfied about their sexual functioning. Methods: In a cluster-randomized clinical trial, participants were randomly allocated to the intervention or the control group in 44 general practices using block randomization. Participants in the intervention group were offered discussion of sexual issues with a PLISSIT-trained primary care physician (PCP); the control group received standard care. Main outcome measures: The main outcome measures included subjective reports of sexual function, satisfaction with sexual function, and quality of life. Male sexual functioning was measured with the International Index of Erectile Function. Female sexual function was assessed with the Female Sexual Function Index. Satisfaction with sexual function was measured using a Visual Analogue Scale. Quality of life was measured with the Short Form-12 item survey. Outcomes were measured at baseline and after three and twelve months of follow-up in 44 general practices between January 2015 and February 2017. Longitudinal multilevel linear regression analyses were conducted, adjusted for age and sex. Results: In total, 150 participants with type 2 diabetes (78.7% men, mean age 62.7 (± 8.5) years) were included (87 intervention; 63 control). Female sexual functioning significantly improved at three months follow-up (P=0.036): women in the intervention versus the control group had a 5.87 (SE 2.80) higher score on the Female Sexual Function Index, however after 12 months these differences disappeared. No other statistically significant effects were observed. Nevertheless, PLISSIT-trained PCP’s reported a significant improvement in their competence to discuss sexual issues. Conclusions: Compared to standard care, the PLISSIT-model intervention improved short-term female sexual functioning in women. More intensive, specialized treatment may be necessary to improve male sexual functioning. The PLISSIT-framework may help PCP’s to discuss sexual health in diabetes care. Trial registration: Dutch Trial Registry (NTR4807
Firms' Margins of Adjustment to Wage Growth: The Case of Italian Collective Bargaining

IZA DP No. 14532 JULY 2021 Firms’ Margins of Adjustment to Wage Growth: The Case of Italian Collective Bargaining* This paper studies firms’ adjustment behavior to the growth in labor costs induced by Italian collective bargaining institutions. Our research design compares several firms’ outcomes across collective agreements within the same sector and geographic location, exploiting discontinuities in contractual wages’ growth as a source of variation in labor costs. Results show that on average employment and revenues fall, wages increase, while firms’ productivity, workers’ average quality, the profit margin and capital intensity do not change in response to higher labor costs. These effects are heterogeneous across the firms’ productivity distribution. Employment, revenues, productivity and the profit margin are positively or not related to contractual wage growth among relatively more efficient firms, while they are negatively related to this shock at less productive companies. More efficient firms tend to substitute highwith low-skilled workers, which are instead more likely to be laid off by less efficient employers. These results suggest that more efficient companies adjust to the growth in labor costs through cost-saving strategies and they may benefit from cleansing effects that increase their product market shares. JEL Classification: J00, J23, J24, J31, J38, J58, L13
Weighted convergence in Colombian regions. The role of geography and demography

We analyze per capita GDP convergence among Colombian departments between 2000 and 2016 using the distribution dynamics approach. Compared with previous studies, we provide a more complete view by including some additional information such as the asymptotic half-life of convergence, mobility indices and the continuous version of the ergodic distributions. In addition, we also extend the analysis to evaluate whether patterns could differ if weighted by either the population living in each department or their economic sizes, together with the existence and magnitude of spatial spillovers. The unweighted, unconditional analysis corroborates and supplements previous findings, especially those indicating that convergence patterns differ strongly under either pre-2008 or post-2008 trends. Both the weighted and space-conditioned analyses indicate that convergence could be much faster when these factors are introduced in the analysis. Implications are especially relevant when weighting by population, since results indicate that the number of people escaping from relative poverty would be much higher than the figure predicted by the unweighted analysis.
Research Article: Evaluation of the quality of fish burger produced from Scomberoides commersonnianus surimi during frozen storage

Fish burger was produced from sarm (Scomberoides commersonnianus) surimi and other ingredients. The physicochemical (chemical composition and pH, free fatty acid, peroxide value (PV), shrinking and cooking loss) and sensory attributes of the product were investigated during 90 days of frozen storage. Results showed that shrinkage in size increased significantly in fish burger from 7 to 8.47 percent at the end of frozen storage. Cooking loss increased significantly from 8 to 13.23 percent in fish burger after 90 days of frozen storage (p0.05). The peroxide value (PV) in fish burger was 0.6 at the beginning of the storage but increased significantly to 2.4 meq/kg after 90 days of frozen storage. The level of free fatty acid and weight loss increased significantly in fish burger after frozen storage (p0.05). Fish burger maintained the sensory properties after 90 days of frozen storage (p>0.05). SDS-PAGE confirmed more intensity of the protein bands in raw surimi than in fish burger. SDS-PAGE, indicating stability of the proteins, showed that protein bands in raw surimi were more intense than fish burger. SDS-PAGE indicated no major change in the intensity of protein bands in surimi and fish burgers after 90 days of frozen storage. Overall, the results revealed that fish burger produced from sarm surimi possessed desired sensory properties during frozen storage.
Enhanced Proton Acceleration by Laser-Driven Collisionless Shock in the Near-Critical Density Target Embedding with Solid Nanolayers

Effects of solid nanolayers embedded in a near-critical density plasma on the laser-driven collisionless shock acceleration are investigated by using two-dimensional particle-in-cell simulations. Due to the interaction of nanolayers and the incident laser, an additional number of hot electrons are generated and an inhomogeneous magnetic field is induced. As a result, the collisionless shock is reinforced within the nanolayer gaps compared to the target without the structured nanolayers. When the laser intensity is 9.8 × 1019 W/cm2, the amplitude of the electrostatic field is increased by 30% and the shock velocity is increased from 0.079c to 0.091c, leading to an enhancement of the peak energy and the cutoff energy of accelerated protons, from 6.9MeV to 9.1MeV and 12.2MeV to 20.0MeV, respectively. Furthermore, the effects of the width of the nanolayer gaps are studied, by adjusting the gap width of nanolayers, and optimal nanolayer setups for collisionless shock acceleration can be acquired.
Referee comment on gmd-2021-71

This manuscript explores improvements in the rapidly advancing field of data-driven weather prediction (DDWP). Broadly, DDWP seeks to train empirical weather-prediction models based on deep learning architectures, such as convolutional neural networks, that have proved very successful in fields such as image processing. This work fits within the WeatherBench forecasting challenge, which aims to forecast the global 500hPa geopotential height field, given the same field at an earlier time.
DISCLOSING THE SIDE OF ISLAMIC LEGAL METHODOLOGY OUT OF THE SYAFII FIQH MAZHAB ON THE INTERPRETATION OF MUSLIM SCHOLARS CONSTELLATION AND THE DYNAMICS OF FIQH IN SERDANG SULTANATE (1856-1946)

The Syafii fiqh mazhab became the official mazhab of the Serdang Sultanate. It is not only a religious practice but also a legal methodology as a reference. However, when advocating for contemporary legal cases, the Muslim scholars develop istidlal processes outside the Syafii fiqh mazhab. First, the reason for the benefit, this is a priority. Legal arguments such as istihsan, maslahat al-mursalah, sad al-dzariah and maqashid al-sharia, which in fact are based on mazhab outside of Syafii fiqh, in which the substance teaches about benefit, is actually used in cases of law during the Sultanate of Serdang, such as the law of injections to save many people therefore the law of injection is allowed. Second, the development of the istidlal process. There is a tendency that the pre-muslim scholars' mind today is more open-minded, not dwelling on just one mazhab, with this openness can solve legal problems that arise. Third, the need for law in advocating for problems that arise, requires legal arguments such as istihsan, maslahat al-mursalah, sad al-dzariah and maqashid al-sharia are seen as solutions in the midst of legal dynamics. Fourth, the support and democracy of the Sultanate of Serdang for the istidlal process, has made Islamic law quite developed. The Sultan was not too strict and rigid in using the Syafii mazhab even though it was the official royal mazhab. On the other hand, the Sultan gave room to the istidlal processes of other mazhabs. The process of determining the law is carried out through an istidlal process outside of the Syafii fiqh mazhab. Such as the use of istihsan argument, maslahat al-mursalah, sad al-dzaraiyah and maqashid al-Sharia. This legal methodology as a solution is accepted by all muslim scholars and the output of the law is issued containing benefits felt by the Islamic community of Serdang. In other words, the legal methodology (ushul fiqh) used was not only text-oriented (al-taqlidi) but muslim scholars of the Serdang Sultanate were also able to accommodate ushul fiqh that were oriented towards legal objectives (al-Maqashid)”
L IMITED M EMORY N EURAL -L INEAR B AN -

We study neural-linear bandits for solving problems where both exploration and representation learning play an important role. Neural-linear bandits leverage the representation power of deep neural networks and combine it with efﬁcient exploration mechanisms, designed for linear contextual bandits, on top of the last hidden layer. Since the representation is optimized during learning, information regarding exploration with “old” features is lost. We propose the ﬁrst limited memory neural-linear bandit that is resilient to this catastrophic forgetting phenomenon by solving a semi-deﬁnite program. We then approximate the semi-deﬁnite program using stochastic gradient descent to make the algorithm practical and adjusted for online usage. We perform simulations on a variety of data sets, including regression, classiﬁcation
Self-aligning floating wind turbine has deep water potential

HyStOH Within the framework of the joint HyStOH project, a self-aligning wind turbine has been developed. The concept, consisting of a simple, cost-effective, lightweight installation with low environmental impact, was optimised at the Hamburg University of Technology (TUHH) by extensive numerical simulations and model tank tests. The project is funded by Germany’s Federal Ministry of Economic Affairs and Energy. In the following article, project partners Jens Cruse, Cruse Offshore GmbH; Moustafa Abdel-Maksoud and Alexander Düster, TUHH; Andreas Bockstedte, DNV GL; Gerrit Haake, Jörss – Blunck – Ordemann GmbH; and Sönke Siegfriedsen, aerodyn engineering GmbH, present the concept.
Synthesis of Coccinia grandis (L.) Voigt extract's silver nanoparticles and it’s in vitro antidiabetic activity

The development of ecofriendly methods for synthesis of metallic nanoparticles (NPs) is an important step in the field of Nano biotechnology and Nanoscience. NPs are synthesized by various methods but are hazardous to ecosystem and expensive. Hence, there is need to develop nontoxic, ecofriendly, and less expensive procedures for synthesis of NPs with the ideal morphologies. The present study aimed to synthesize silver nanoparticles (AgNPs) of Coccinia grandis (L.) Voigt hydroalcoholic stem extract and investigate the in vitro antidiabetic activity. AgNPs were synthesized by reducing the silver ions of silver nitrate solution by the hydroalcoholic extract of C. grandis (L.) Voigt stem. Formation of deep brown color qualitatively confirms synthesis of AgNPs which was further confirmed by UV– Visible spectroscopy, Fourier transform infrared spectroscopy, particle size analysis, zeta potential, and HR-TEM. These AgNPs exhibited UV visible absorptions in the range of 400–450 nm; High resolution transmission electron microscopy demonstrated AgNPs particle size at 20 nm. In vitro antidiabetic activity was evaluated for these AgNPs and found potent to reduce blood sugar level. The AgNPs of C. grandis (L.) Voigt stem extract showed remarkable in vitro antidiabetic activity and can be used as vehicle in drug transportation and in the targeted drug delivery system.
Contract Theory-Based Incentive Mechanism for Full Duplex Cooperative NOMA with SWIPT Communication Networks

Cooperative Non-Orthogonal Multiple Access (NOMA) with Simultaneous Wireless Information and Power Transfer (SWIPT) communication can not only effectively improve the spectrum efficiency and energy efficiency of wireless networks but also extend their coverage. An important design issue is to incentivize a full duplex (FD) relaying center user to participate in the cooperative process and achieve a win–win situation for both the base station (BS) and the center user. Some private information of the center users are hidden from the BS in the network. A contract theory-based incentive mechanism under this asymmetric information scenario is applied to incentivize the center user to join the cooperative communication to maximize the BS’s benefit utility and to guarantee the center user’s expected payoff. In this work, we propose a matching theory-based Gale–Shapley algorithm to obtain the optimal strategy with low computation complexity in the multi-user pairing scenario. Simulation results indicate that the network performance of the proposed FD cooperative NOMA and SWIPT communication is much better than the conventional NOMA communication, and the benefit utility of the BS with the stable match strategy is nearly close to the multi-user pairing scenario with complete channel state information (CSI), while the center users get the satisfied expected payoffs.
Eﬀective Pruning Heuristics for the Fixed Route Dial-a-Ride Problem

The ﬁxed route dial-a-ride problem (FRDARP) is a variant of the famous dial-a-ride problem, in which all the requests are chosen between terminals that are located along a ﬁxed route. A reduction to the shortest path problem has been proposed for ﬁnding an FRDARP optimal solution. However, the basic graph construction ends up with a huge graph, which makes the reduction impractical due to its memory consumption. To this end, we propose several pruning heuristics that enable us to considerably reduce the size of the graph through its dynamic construction. Our experiments show that each of the proposed heuristics on its own improves the practical solvability of FRDARP. Moreover, using them together is considerably more eﬃcient than any single heuristic.