Miracle-dz/UniFAR-FTUs huggingface dataset:
Parametric structural analysis of nutritional value of personalized foods using Microsoft Excel

Present-day market relations require enhancing the efficiency of production, sustainable use of resources and development of technological and economical calculations. The use of digital technologies plays a significant role in the development of innovative technologies in food processing industry. At the present time recipe calculation in chocolate manufacturing is done with a book of standardized recipes (1986). According to the method proposed in the present article, a conventional calculation of a chocolate product recipe is carried out with the use of a standardized recipe. It must be pointed out, that the conventional method requires a series of step-by-step calculations, which are very time-consuming, and also it requires the calculation of raw material consumption, caloric and nutritional values of the product. In the case when a new ingredient is introduced into the recipe of the chocolate product, total recalculation is required. The difficulty of the multicomponent recipe problem lies in the fact that at present it involves many ingredients (more than 5). In this case, a recipe calculation that is done without use of present-day digital technologies is extremely time-consuming which leads to the loss of efficiency in production control. The enumerated disadvantages of the conventional method can be solved by using digital technologies that save time of doing technological calculations and eliminate human errors.
Periodic forcing on degenerate Hopf bifurcation

This paper is devoted to the effect of periodic forcing on a system exhibiting a degenerate Hopf bifurcation. Two methods are employed to investigate bifurcations of periodic solution for the periodically forced system. It is obtained by averaging method that the system undergoes fold bifurcation, transcritical bifurcation, and even degenerate Hopf bifurcation of periodic solution. On the other hand, it is also shown by Poincare map that the system will undergo fold bifurcation, transcritical bifurcation, Neimark-Sacker bifurcation and flip bifurcation. Finally, we make a comparison between these two methods.
A Dual-Band Steerable Dual-Beam Metasurface Antenna Based on Common Feeding Network

A novel method of dual-band dual-beam control (DDC) is proposed and applied in metasurface antennas (MSAs). Based on this DDC method, the feeding network employed in MSAs can realize independent forward and/or backward radiation of two bands. Combining the metasurface cells and feeding network, the desired bands and the corresponding beam angles of MSAs can be controlled. The symmetrical two-port feeding network consists of uniformly spaced slots in the ground and a bent microstrip line beneath the slots, so that two identical beams are realized. The radiation direction of the two bands can be implemented independently by adjusting the distance of the slots and length of the bent line simultaneously. To verify the design strategies, two prototypes (MSA A and MSA B) with different performance are designed, respectively. As a result, the proposed MSAs can achieve independent beam angels of two bands with low profile and compact design. The above good features make the proposed MSAs potential candidates in base-station antennas of high-capacity wireless communication system.
A nonlocal low rank model for poisson noise removal

Patch-based methods, which take the advantage of the redundancy and similarity among image patches, have attracted much attention in recent years. However, these methods are mainly limited to Gaussian noise removal. In this paper, the Poisson noise removal problem is considered. Unlike Gaussian noise which has an identical and independent distribution, Poisson noise is signal dependent, which makes the problem more challenging. By incorporating the prior that a group of similar patches should possess a low-rank structure, and applying the maximum a posterior (MAP) estimation, the Poisson noise removal problem is formulated as an optimization one. Then, an alternating minimization algorithm is developed to find the minimizer of the objective function efficiently. Convergence of the minimizing sequence will be established, and the efficiency and effectiveness of the proposed algorithm will be demonstrated by numerical experiments.
A Reset Algorithm Solving Coordination With Antagonistic Reciprocity

This article is dedicated to solving the coordination problem using a reset algorithm that consists of linear impulsive dynamics, over which antagonistic reciprocity among interacting individuals is inevitable. It shows that reciprocal agents are convergent (including consensus and clusters) whenever the scaling parameters of an agent, corresponded to continuous/discrete dynamics, enjoy the same proportion value that matches to all agents. Otherwise, all participating agents share nothing eventually, that is, they achieve stability. This immediately gives rise to that the final aggregated values of agents are entirely determined by the underlying parameters, on condition that the connection property of communication topologies is preserved. Therefore, the proposed setup features a unified perspective on consensus, clusters (including bipartite consensus), and stability that are separately studied in most of the existing literature. The developed method is well supported via numerical examples.
Quantum reading of quantum information

We extend the notion of quantum reading to the case where the information to be retrieved, which is encoded into a set of quantum channels, is of quantum nature. We use two-qubit unitaries describing the system-environment interaction, with the initial environment state determining the system’s input-output channel and hence the encoded information. The performance of the most relevant two-qubit unitaries is determined with two different approaches: (i) one-shot quantum capacity of the channel arising between environment and system’s output; (ii) estimation of parameters characterizing the initial quantum state of the environment. The obtained results are mostly in (qualitative) agreement, with some distinguishing features that include the CNOT unitary.
The Oxidation of Fe(II) in Acidic Sulfate Solutions with Air at Elevated Pressures. Part 1. Kinetics above 1 M H2SO4

The oxidation of ferrous ions in acidic sulfate solutions at elevated air pressures was investigated. The effect of the Fe2+ concentration, initial H2SO4 concentration and partial oxygen pressure on the reaction rate were determined at three different temperatures, that is, T = 90, 70, and 50 °C. The effect on the reaction rate of the components that H2SO4 dissociates into, that is, HSO4–, H3O+, and SO42–, was established as well. A second order of reaction in Fe2+ and a first order of reaction in O2 were determined. No clear order in either H2SO4 or the components H2SO4 dissociates into, could be established. For the experiments with initial concentrations of H2SO4 of 1 M and higher the oxidation rate was not affected, that is, a zero order of reaction in H2SO4 for these concentrations. Therefore, the kinetic rate expression for the oxidation of Fe2+ at concentrations of H2SO4 of 1 M and higher can be calculated with RFe2+ = d[Fe2+]/dt = k[Fe2+]2PO2, where the activation energy EA was determined to be 60.
Extent of urban agriculture and food security: evidence from Ghana and India

PurposeThe study attempted to assess the food security status of urban agriculture households in Ghana and India. Also, the extent of urban agriculture participation and its effect on food security in Ghana and India were examined.Design/methodology/approachA total of 650 urban agriculture farmers were interviewed for this study in Ghana and India. Food security status of urban households was assessed by the use of the Household Food Insecurity Access Scale, whereas the determinants of the extent of urban agriculture and its effect on food security were analysed by the use of the heteroskedastic linear regression and the Seemingly Unrelated Regression models, respectively.FindingsFrom the study on average, households in Ghana were mildly food insecure, but that of India was moderately food insecure. The results further revealed that various demographic, economic, institutional and health and nutrition factors differently influenced urban food security and urban agriculture. Also, the extent of urban agriculture participation positively influenced food security.Originality/valueSeveral studies in Asia (India) and Africa (Ghana) on urban food security have been geographically limited to New Delhi, Mumbai and Greater Accra, with few studies in the Middle Belt of Ghana, and Bihar in India. Besides, there is a limited, rigorous, empirical study on the effect of the extent of UA on food security in Asia (India) and Africa (Ghana) individually and together. Moreover, we extend the frontiers of the methodological approach by applying the Seemingly Unrelated Regression (SUR) model to understand if the factors that affect food-security accessibility based on two food security accessibility tools are correlated.
Open-loop solvability for mean-field stochastic linear quadratic optimal control problems of Markov regime-switching system

This paper investigates the mean-field stochastic linear quadratic optimal control problem of Markov regime switching system (M-MF-SLQ, for short). The representation of the cost functional for the M-MF-SLQ is derived using the technique of operators. It is shown that the convexity of the cost functional is necessary for the finiteness of the M-MF-SLQ problem, whereas uniform convexity of the cost functional is sufficient for the open-loop solvability of the problem. By considering a family of uniformly convex cost functionals, a characterization of the finiteness of the problem is derived and a minimizing sequence, whose convergence is equivalent to the open-loop solvability of the problem, is constructed. We demonstrate with a few examples that our results can be employed for tackling some financial problems such as mean-variance portfolio selection problem.
Does Foreign Direct Investment and Trade Promote Economic Growth? Evidence from Albania

Albania has experienced a rapid transition from a centrally planned economy to a mixed economy since the fall of communism in 1989. Policy changes, trade liberalization, and privatization have come about at a rapid pace, allowing foreign direct investment (FDI) and international trade to become key components of Albania’s economy. Against this backdrop, this study investigates the relationships among FDI, trade, and economic growth in Albania. Annual time-series data were obtained from the World Bank. Then, the following econometric tests were performed on the variables representing FDI inflows, exports, and GDP as proxies for FDI, trade, and economic growth: the unit root test; the unit root test with a structural break; Johansen cointegration analysis; the error correction model; and the Granger causality test. The results revealed a long-term relationship between FDI, trade, and economic growth. The Granger causality tests found unidirectional causality. Economic growth brought about exports and FDI in the short term but not vice versa. In conclusion, policymakers need to design policies that promote technology-based, export-promoting FDI to meet the needs of the economy and develop specialized sectors that are competitive in the global market. Furthermore, the salient takeaway is that the penetration of export markets should be promoted as much as the furtherance of FDI.
Lighting Candles in the Darkness: An Exploration of Commemorative Acts with British Teenagers at the Auschwitz-Birkenau State Museum

Every year around 3000 British school pupils and teachers visit the Auschwitz-Birkenau State Museum as participants on a Lessons from Auschwitz Project organized by the Holocaust Educational Trust. Each visit ends with a memorial ceremony held at the end of the railway tracks at Birkenau. This article analyses interview and survey data from participating students and educators to explore their experiences of these ceremonies. The research findings indicate that the context and content of the ceremony are significant for both groups, with a general consensus that the ceremony is an important and appropriate way to end the day visit to Poland and the museum. The students’ responses also particularly raise issues around their emotional engagement with the ceremony and the impact it had on them in this way. In conclusion, this article suggests how similar reflective spaces might be created in other educational contexts at similar sites of memory.
Biomedical image classification using deep convolutional neural networks – overview

Deep Learning is an advanced area of machine learning which gained much interest in the past decades. It has been widely used in a variety of applications and has proved to be an effective machine learning method for many complicated issues. Especially when it comes to the medical field, the classification of biomedical images is a complex task to identify and classify the images manually by the doctors. So, Deep Learning is a key to enhance the classification of biomedical images using various architectures. The biomedical picture classification aims to identify and classify biomedical characteristics efficiently, which have significant advantages to numerous study and development fields. In this paper, the framework focused on the different architectures that were used to classify the medical images along with their performances.
Oxidative damage and photosynthetic impairment in tropical rice cultivars upon

Iron plays a pivotal role in the redox reactions of photosynthesis and metabolic pro- cesses such as chlorophyll synthesis. Iron availability in waterlogged soils can reach toxic levels and promote oxidative stress. Fe toxicity is the most concerning of stresses for rice in many lowland environments around the world and may cause severe impairments in rice photosynthe- sis. This study aimed to investigate the extension of oxidative stress after excess Fe exposure and its effects on the photosynthesis of rice cultivars with differential sensitivity. Three Brazilian rice cultivars (EPAGRI 107, BRSMG SELETA and BR IRGA 409) were grown in Hoagland nutrient solution (pH 4.0) with two Fe-EDTA doses corresponding to excess Fe (7 mM) and control (0.009 mM) treatments. After just three days of excess Fe exposure, there was a significant increase in iron concentration in the shoots. The BR IRGA 409 cultivar exhibited higher Fe accumulation in its shoots, and the EPAGRI 107 cultivar recorded the lowest values, which were below the criti- cal toxicity level, as a resistance strategy. Impairment in light energy partitioning and oxidative damage became evident before changes in stomatal resistance, chlorophyll content, maximal PSII quantum yield or visual symptoms for the most sensitive cultivar (BR IRGA 409). The photo- synthesis limitations, in addition to the impairment of excess energy dissipation in rice from iron toxicity, are the results of oxidative damage.
Adaptation and Facilitation of Small Group Activities in an Online Introductory Biology Class

In spring 2020, the sudden mid-semester closure of my campus in response to the global COVID-19 pandemic necessitated a rapid transition to emergency online learning. Consequently, I adapted the small group activities and facilitation methods of my face-to-face introductory biology class to a fully online format. During small group activities in the face-to-face classroom, students form teams of two or three and complete paper worksheets that are designed to promote dialogue among teammates, while learning assistants and I circulate around the classroom to provide assistance. Evidence suggests these small group activities are a highly effective form of active learning. Here, I describe how I adapted the content of these paper worksheets for use in my learning management system, how students performed collaborative group work together using videoconferencing software, and how learning assistants and I facilitated this group work in a completely online environment during the spring and summer 2020 semesters. I also discuss the limitations and benefits of online group work. Online group activities present many advantages over use of the same activities in the traditional face-to-face classroom including overcoming the many limitations of the physical classroom space
Design and Control of a Spatial Micromanipulator Inspired by Deployable Structure

This article proposes the design, analysis, and experimental tests of a novel piezoelectrically actuated micromanipulator with spatial structure. Three-stage amplification is employed to amplify input displacement to obtain desired output displacement, and deployable mechanism is adopted to achieve compact structure. The spatial micromanipulator is designed with two fixed fingers and two detachable fingers, which can achieve multioperation modes. Theoretical analysis is utilized to evaluate the characteristics of the micromanipulator. Prototype of the micromanipulator is fabricated and experimental tests are carried out to investigate its performance. The results indicate the motion stroke is 125 μm with respect to 100 V voltage, the amplification ratio is 10.84, and the coupling rate is 4.32%. Close-loop test results show that the settling time is 23.5 ms with 2.8% overshoot, and the resolution can reach 0.1 μm. Finally, the developed micromanipulator is used to operate tiny objects with differentshapes.
Sectorization for Water Distribution Systems with Multiple Sources: A Performance Indices Comparison

Sectorization is an effective technique for reducing the complexities of analyzing and managing of water systems. The resulting sectors, called district metering areas (DMAs), are expected to meet some requirements and performance criteria such as minimum number of intervention, pressure uniformity, similarity of demands, water quality and number of districts. An efficient methodology to achieve all these requirements together and the proper choice of a criteria governing the sectorization is one of the open questions about optimal DMAs design. This question is addressed in this research by highlighting the advantages of three different criteria when applied to real-word water distribution networks (WDNs). To this, here it is presented a two-stage approach for optimal design of DMAs. The first stage, the clustering of the system, is based on a Louvain-type greedy algorithm for the generalized modularity maximization. The second stage, the physical dividing of the system, is stated as a two-objective optimization problem that utilises the SMOSA version of simulated annealing for multiobjective problems. One objective is the number of isolation valves whereas for the second objective three different performance indices (PIs) are analyzed and compared: (a) standard deviation, (b) Gini coefficient and (c) loss of resilience. The methodology is applied to two real case studies where the first two PIs are optimized to address similar demands among DMAs. The results demonstrate that the proposed method is effective for sectorization into independent DMAs with similar demands. Surprisingly, it found that for the real studied systems, loss of resilience achieves better performance for each district in terms of pressure uniformity and demand similarity than the other two specific performance criteria.
Framework for an Integrated Project Management and Change Management Team to Achieve Sustainable Digital Transformation

The latest trend in transforming a business to achieve operational efficiency is through Digital Transformation. To achieve this, both processes and technology within an organization need to strongly align. Successful digital transformation depends not only on technical aspects but also on human assets within the organization. Studies linked to this area of research have concluded that one of the major causes for failure of digital transformation includes human aspects involved within the change and not the technical maturity alone. There is a need to develop a holistic approach to tackle this problem, and this research is aimed at studying the human aspects of digital transformation. This research seeks to answer: To simplify digital transformation within an organization, how can the change management team and project management team be integrated for a seamless transitioning? The researcher will conduct a qualitative study to understand the concept of digital transformation from the perspective of project managers and change managers, their ability to tackle the change process, their understanding of Digitization and need for digitisation from their standpoint. The interview process will be conducted in a semi-structured manner in organizations undergoing digital transformation where leaders working in upper management levels, or executives will be interviewed. Based on the data collected, a thematic analysis will be done, and an integrated framework will be developed to be used as a guideline for project management and change management teams.
OCR-RCNN: An Accurate and Efficient Framework for Elevator Button Recognition

Autonomous elevator operation is considered a promising solution for mobile navigation in office buildings. As a fundamental function, elevator button recognition remains unsolved due to the challenging image conditions and severe data imbalance problem. In this article, we propose an accurate and efficient framework, named OCR-RCNN, for elevator button recognition. The framework is comprised of an region-based convolutional neural network (R-CNN)-based button detector and an attention-RNN-based character recognizer. Leveraging the two components, we further propose an end-to-end architecture and a cascaded architecture to explore the most effective network design for the framework. Moreover, a perspective distortion removal algorithm is also developed to enhance the inference performance of OCR-RCNN. Another key contribution of this work is that we release the first large-scale elevator panel dataset with 2005 images and 21 767 button labels. Extensive experiments are conducted on the released dataset and other two publicly available datasets. The proposed framework achieves an F1 score of 0.94, 1.00, and 1.00 in detection task, and an accuracy of 79.6% 96.5%, and 96.4% in character recognition task. The results demonstrate the advantages of our method, outperforming alternative strategies and other state-of-the-art methods in the literature. The data and code are available on the project webpage https://github.com/zhudelong/ocr-rcnn-v2.
In-Domain Stabilization of Block Diagonal Infinite-Dimensional Systems With Time-Varying Input Delays

This article is concerned with the in-domain stabilization of a class of block diagonal infinite-dimensional systems in the presence of an uncertain and time-varying delay in the distributed control input. Two actuation schemes are considered. The first one assumes a control input that is fully distributed over the domain. The second one assumes that the control input is finite-dimensional, acting over the domain via a bounded operator. In both cases, the control design strategy consists in a predictor feedback law synthesized on a finite-dimensional truncated linear time invariant (LTI) model capturing the unstable dynamics of the original infinite-dimensional system. The predictor feedback law is designed based on the knowledge of the nominal value of the uncertain and time-varying input delay. In the second actuation scheme, the case of distinct input delays in the different scalar control input channels is considered.