Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Real Options Approach to Analyse Economic Efficiency of Power Plant with CCS Installation under Uncertainty

The main goal of this article is to build a decision model for an investment involving the addition of a CCS (Carbon dioxide Capture and Storage) installation in an existing conventional power plant. The application of CCS systems in coal and gas power plants involves large capital expenditures and an increase in operating costs. The lack of upgrade modernisation and environmentally friendly investments in this type of power plant generates the additional costs of the purchase of emission allowances. An analysis of the impact of the addition of a CCS installation to an existing coal power plant on the costs of electricity generation is presented. Based on the accessible technical and economic data, a concept has been framed and an original decision-making model has been developed for an investment consisting in constructing a CCS installation in an existing power plant. A novelty of the paper is the presented proprietary decision-making model in conditions of uncertainty using the real options approach. Stochastic state variables are included in the model: the price of the CO2 emission allowance, the unit costs of capturing, transporting, storing and stockpiling CO2 and the unit costs of electricity generation. It is assumed that the time curves of the state variables are described by equations of geometric Brownian motions. The values of standard deviations in the equations are measures of uncertainty. The value of the retrofit option is defined as the maximum value from the expected net present value. From the dynamic optimisation equation, resulting from Bellman’s principle of optimality, it results that the retrofit option must satisfy the differential equation. The calculations were made for a specific, commercially applicable case of CCS technology in order to present the model’s capabilities. The analyses’ results and conclusions are presented.
Rich People Poor Countries: The Rise of Emerging-Market Tycoons and Their Mega Firms

Like the robber barons of the 19th century Gilded Age, a new and proliferating crop of billionaires is driving rapid development and industrialization in poor countries. The accelerated industrial growth spurs economic prosperity for some, but it also widens the gap between the super rich and the rest of the population, especially the very poor. In Rich People Poor Countries, Caroline Freund identifies and analyzes nearly 700 emerging-market billionaires whose net worth adds up to more than $2 trillion. Freund finds that these titans of industry are propelling poor countries out of their small-scale production and agricultural past and into a future of multinational industry and service-based mega firms. And more often than not, the new billionaires are using their newfound acumen to navigate the globalized economy, without necessarily relying on political connections, inheritance, or privileged access to resources. This story of emerging-market billionaires and the global businesses they create dramatically illuminates the process of industrialization in the modern world economy.
Exploring the Impact of Solid-State Fermentation on Macronutrient Profile and Digestibility in Chia (Salvia hispanica) and Sesame (Sesamum Indicum) Seeds

Fermentation of plant-based substrates with edible fungi enhances the nutrient profile and digestibility, but it has been scarcely applied to edible seeds, which are rich in healthy lipids. In this study, chia and sesame seeds were solid-state fermented with Pleurotus ostreatus, followed by drying and milling. Fermentation led to increased content of lipid and protein in both seeds’ products, and a change in fatty acid profile in favor of increased polyunsaturated fatty acids. Then, the samples were subjected to in vitro digestion. Lipolysis, determined by nuclear magnetic resonance, was higher in sesame than in chia products, and the fermented counterparts had increased values compared to the controls. In terms of physical properties, fermentation showed reduced particle size and increased matrix degradation and decreased viscosity of the digestion medium, which were related to increased lipolysis. In conclusion, applying solid-state fermentation on chia and sesame seeds could be a recommendable approach.
Matrix topology guides collective cell migration in vivo

Diverse modes of cell migration shape organisms in health and disease and much research has focused on the role of intracellular and extracellular components in different cell migration phenomena. What is less explored, however, is how the arrangement of the underlying extracellular matrix that many cells move upon in vivo influences migration. Combining novel transgenic lines and image analysis pipelines, reveals that during zebrafish optic cup formation cells use cryptopodia-like protrusions to migrate collectively and actively over a topologically changing matrix. These changing topologies correspond to different cell-matrix interactions. Interference with matrix topology results in loss of cryptopodia and inefficient migration. Thus, matrix topology influences the efficiency of directed collective cell migration during eye morphogenesis, a concept likely conserved in other developmental and disease contexts. One-Sentence Summary Dynamic cell-matrix interactions, crucial for successful collective rim cell migration, rely on extracellular matrix topologies during optic cup development in vivo.
Chlorpyrifos should be banned in agriculture and livestock production in Colombia

David Villar ; David J Schaeffer Grupo CIBAC, Facultad de Ciencias Agrarias, Universidad de Antioquia, Medellin, Colombia College of Veterinary Medicine, University of Illinois, Champaign-Urbana, USA To cite this article: Villar D, Schaeffer DJ. Chlorpyrifos should be banned in agriculture and livestock production in Colombia. Rev Colomb Cienc Pecu. Year, volume, number and pages pending. DOI: https://doi.org/10.17533/udea.rccp. v35n2a7
Phenotypic and Functional Plasticity of CXCR6+ Peripheral Blood NK Cells

Human NK cells are comprised of phenotypic subsets, whose potentially unique functions remain largely unexplored. C-X-C-motif-chemokine-receptor-6 (CXCR6) + NK cells have been identified as phenotypically immature tissue-resident NK cells in mice and humans. A small fraction of peripheral blood (PB)-NK cells also expresses CXCR6. However, prior reports about their phenotypic and functional plasticity are conflicting. In this study, we isolated, expanded, and phenotypically and functionally evaluated CXCR6+ and CXCR6– PB-NK cells, and contrasted results to bulk liver and spleen NK cells. We found that CXCR6+ and CXCR6– PB-NK cells preserved their distinct phenotypic profiles throughout 14 days of in vitro expansion (“day 14”), after which phenotypically immature CXCR6+ PB-NK cells became functionally equivalent to CXCR6– PB-NK cells. Despite a consistent reduction in CD16 expression and enhanced expression of the transcription factor Eomesodermin (Eomes), day 14 CXCR6+ PB-NK cells had superior antibody-dependent cellular cytotoxicity (ADCC) compared to CXCR6– PB-NK cells. Further, bulk liver NK cells responded to IL-15, but not IL-2 stimulation, with STAT-5 phosphorylation. In contrast, bulk splenic and PB-NK cells robustly responded to both cytokines. Our findings may allow for the selection of superior NK cell subsets for infusion products increasingly used to treat human diseases.
Hip–Knee Coupling Exoskeleton With Offset Theory for Walking Assistance

To alleviate the influence of aging on the elderly, a hip–knee coupling exoskeleton with offset theory is designed in this article to improve people’s athletic ability. With the novel design, the unique application strategy of the offset principle for hip and knee joints is developed, and a hip–knee coupling mechanism is proposed to solve the discrete power assistance problem for the knee joint. To acquire the success of the design, the mathematical model of the coupling mechanism is established to optimize the load environment of the exoskeleton system, and furthermore, an algorithm adapted to human movement is proposed to determine the monotonicity of the cam profiles. For the selection of the elastic parameters in the coupling mechanism, the sensitivity condition is proposed, and the human–machine interaction model of the KESM is further established. A man–machine coupling model was used to verify the scientificity of the exoskeleton design, and the comparison between the joint powers with or without exoskeleton indicated that the exoskeleton theoretically saved at least 20% of the human body’s energy.
Target Localization by Mobile Handheld UHF RFID Reader

In this paper we design and implement a mobile handheld human operated device used to guide the user towards the desired RFID target, and at the same time provide estimations of the distance and the angle from the user to the target. The main components of the device are a UHF RFID reader operating with one antenna, and an IMU used to measure rotation angles. The user is instructed by the device to perform one of three different actions: SCAN, TURN and MOVE. During these actions phase of arrival and rotation angle data are collected by the RFID reader and the IMU respectively. A particle filter algorithm leverages the collected data to estimate the distance and angle of the target, with respect to the user's current pose. Experimental results show a mean angle estimation error of ~4o, and distance estimation error less than $0.5 m$ when the user approaches the target.
Transformer fault diagnosis based on optimized FCM clustering by hybrid GA and PSO

Optimized FCM clustering by hybrid GA and PSO(GAPSO-FCM) is introduced to diagnose the fault of transformer in order to conquer the shortages of FCM clustering,GA-FCM clustering and PSO-FCM clustering in transformer fault diagnosis. GAPSO-FCM clustering carries out global search,conquering the problem of FCM clustering easily falling into local minimum. According to the best global individual,GAPSO-FCM clustering makes GA algorithm and PSO algorithm organically link together, GA and PSO share a best individual,and the iterative process includes GA operation and PSO operation. It enlarges search area by the randomicity of GA,then searches more carefully according to PSO round the founded individual, conquering the premature problem of optimized FCM clustering based only on single GA or PSO. Simulation and case analysis indicate that GAPSO-FCM clustering for fault diagnosis is of higher accuracy than the other three kinds of clustering.
Hot carrier effects on Brillouin amplification in AIIIBV and AIIBVI semiconductors

A theoretical formulation followed by numerical analysis is carried out to study the hot carrier effects (HCEs) on Brillouin amplification in AIIIBV and AIIBVI semiconductors. The threshold condition for the onset of Brillouin amplification and the parameters characterizing Brillouin amplification of the Brillouin cell are estimated. Numerical analysis is made for three different Brillouin cells at illuminated by a pulsed CO2 laser. HCEs of intense pump beam modifies the momentum transfer collision frequency of carriers and consequently the nonlinearity of the Brillouin medium, which in turn (i) lowers the threshold intensity, (ii) enhances the parameters characterizing Brillouin amplification, (iii) shifts the enhanced Brillouin gain spectrum towards smaller values of magnetic field, and (iv) widens the range of magnetic field at which peak of Brillouin gain spectrum (around resonance) occurs. The incorporation of HCEs in the analysis validate the selection of appropriate Brillouin medium for the fabrication of efficient Brillouin amplifiers.
Network Pharmacology and Molecular Docking Analysis on Pharmacological Mechanisms of Astragalus membranaceus in the Treatment of Gastric Ulcer

Background Astragalus membranaceus (AM, family: Leguminosae) exerts significant therapeutic effect on gastric ulcer (GU); however, there are scarce studies on its molecular mechanism against GU. This study aims to explore the key ingredients, key targets, and potential mechanisms of AM in the treatment of GU by utilizing network pharmacology and molecular docking. Methods Several public databases were used to predict the targets of AM and GU, respectively, and the drug and disease targets were intersected to obtain the common targets. Next, the key ingredients and key targets were identified by constructing ingredient-target network and protein-protein-interaction (PPI) network. Gene Ontology biological processes (GOBP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out on the common targets in order to ascertain the biological processes and signaling pathways involved. Finally, molecular docking was conducted to verify the binding affinity between the key ingredients and key targets. Results A total of 552 predicted targets were obtained from 23 screened active ingredients, of which 203 targets were the common targets with GU. Quercetin, kaempferol, and isorhamnetin were identified as the key ingredients by constructing ingredient-target network, and TP53, AKT1, VEGFA, IL6, TNF, CASP3, and EGFR were selected as the key targets by constructing PPI network. GOBP and KEGG pathway enrichment analysis suggested that the therapeutic effect of AM on GU involved multiple biological processes and signaling pathways related to inflammation, oxidative stress, apoptosis, cell proliferation, and angiogenesis. Molecular docking validation demonstrated that all key ingredients had good binding affinity with the key targets. Conclusion This study revealed the key ingredients, key targets, and potential mechanisms of AM against GU, and these data may provide some crucial references for subsequent research and development of drugs for treating GU.
Genome-Wide Analysis of Alternative Splicing (AS) Mechanism Provides Insights into Salinity Adaptation in the Livers of Three Euryhaline Teleosts, including Scophthalmus maximus, Cynoglossus semilaevis and Oncorhynchus mykiss

Simple Summary Alternative splicing (AS) is a key post-transcriptional regulatory mechanism that acts an important regulator in response to environmental stimuli in organisms. In the present study, 18 RNA-Seq datasets were utilized to investigate the potential roles of AS in response to different salinity environments in the livers of three euryhaline teleosts, including turbot (Scophthalmus maximus), tongue sole (Cynoglossus semilaevis) and steelhead trout (Oncorhynchus mykiss). The results indicated that different salinity environments changed the splicing patterns of numerous RNA splicing regulators, which might affect the splicing decisions of many downstream target genes in response to salinity changes. This study provides preliminary evidence for the important roles of AS events in salinity adaptation in teleosts. Abstract Salinity is an important environmental factor that directly affects the survival of aquatic organisms, including fish. However, the underlying molecular mechanism of salinity adaptation at post-transcriptional regulation levels is still poorly understood in fish. In the present study, 18 RNA-Seq datasets were utilized to investigate the potential roles of alternative splicing (AS) in response to different salinity environments in the livers of three euryhaline teleosts, including turbot (Scophthalmus maximus), tongue sole (Cynoglossus semilaevis) and steelhead trout (Oncorhynchus mykiss). A total of 10,826, 10,741 and 10,112 AS events were identified in the livers of the three species. The characteristics of these AS events were systematically investigated. Furthermore, a total of 940, 590 and 553 differentially alternative splicing (DAS) events were determined and characterized in the livers of turbot, tongue sole and steelhead trout, respectively, between low- and high-salinity environments. Functional enrichment analysis indicated that these DAS genes in the livers of three species were commonly enriched in some GO terms and KEGG pathways associated with RNA processing. The most common DAS genes work as RNA-binding proteins and play crucial roles in the regulation of RNA splicing. The study provides new insights into uncovering the molecular mechanisms of salinity adaptation in teleosts.
Grip Force Control of the Elastic Body based on Contact Surface Eccentricity During the Incipient Slip

In this research, the slip margin between an elastic object and a rigid plate is estimated based on the analysis of Hertz contact model. A method of the grip force control using the slip margin is proposed. When an elastic object is pressed and slid slightly on a rigid plate, a partial slip, called“incipient slip”occurs on the contact surface. The slip margin can be estimated based on tribology from the deformation of the elastic object, the tangential force and the radius on the contact surface. The deformation and the displacement of the elastic object are measured by the camera. In addition, the load force can be measured by the force sensor. In this research, a measuring device consists of a camera and a force sensor is developed. “Eccentricity”is defined to estimate the displacement of the elastic object from the shift of the contact area. The grip force is controlled based on the estimated slip margin without knowing the friction coefficient. The proof of the contact stability is obtained. The validity of the proposed method is confirmed by the experiment.
Improved neural network nonuniformity correction technique for IRFPA

One of the most difficult problems associated with infrared focal plane array(IRFPA) is the nonuniformity between individual detector elements in the sensor arrays,and the nonuniformity correction is the key in the field of infrared formation of image.The principle of the traditional neural network nonuniformity correction(NN-NUC) algorithm was presented.Frame average weight was added to the expected output of each pixel in order to make the NNNUC method more effective to correct the low frequency spatial noise.On the TMS320C62x DSP,the medium wave staring infrared detector was used to test the method in the lab and outside when the image frame was 50 Hz.The residual nonuniformity falled from 5% to less than 2‰ which showed that the improved algorithm had many advantages,such as high precision and practicality.It can satisfy the demands of practical application and employ the application of the infrared formation of image.
Challenges in Identifying Network Attacks Using Netflow Data

Large networks often encounter attacks that can affect the network availability. While multiple techniques exist to detect network attacks, a comprehensive understanding of how an attack occurs considering the various layers and components of the network software stack, can be an important element to help improve network security. By performing correlation analysis on contemporary unlabeled Netflow data, this paper conducts a comprehensive study of network flow events to identify communication patterns that may precede an attack, thereby providing potentially useful attack signatures to network administrators. Our work shows that, surprisingly, the Netflow data is not strongly correlated to network attacks. We observe that while spoof requests trigger reflection attacks, only a small percentage of the network packets are associated with the attack. Furthermore, lead time enhancements are feasible for reflection attacks that show long dwell times. Our study on network event correlations highlights empirical observations that could facilitate better attack handling in large networks.
Designing an App for Immunosuppression Adherence and Communication: A Qualitative Approach

Background: Immunosuppression nonadherence may be the most important factor limiting long-term allograft survival. Objective: Following user-centered design, we explored the essential priorities and preferences of kidney transplant recipients and healthcare providers (HCP) to inform development of a smartphone app to improve immunosuppression adherence and communication. Design: A qualitative descriptive research design was used. Setting: The University of Alberta Hospital adult kidney transplant program in Edmonton, Canada. Participants: Participants were recruited by convenience sampling and included 32 kidney transplant recipients and 11 HCPs. Methods: Seven focus groups (5 with recipients and 2 with HCPs) were conducted to inform app development. Sessions were recorded, and transcripts were coded to elucidate themes. Results: App development to improve adherence was not a priority for HCP. Recipients prioritized choice: that all features be optional. Recipients preferred support while traveling; access to laboratory results; and use by younger or newly transplanted recipients. Both recipients and HCP preferred linkage to pharmacy; and self-management and accountability. For the app to improve communication, HCPs believed the priorities to be addressed included: clarity on scope of app; legal, ethical, and professional obligations; and charting. Both recipients and HCP prioritized HCP workload, and broader medication and health concerns. Healthcare providers preferred tech support; both recipients and HCPs preferred app access for nontransplant HCP. Limitations: Limitations include underrepresentation of physicians, recipients with racial/ethnic diversity, and potential selection bias of transplant recipients who perceived themselves to be adhering to immunosuppression medications. Conclusion: Future research is needed for the app to become a comprehensive, secure platform for broader communication between recipients and HCP, pharmacies, and nontransplant clinicians while streamlining HCP workload.
Evaluating the Performance of Oil and Gas Companies by an Extended Balanced Scorecard and the Hesitant Fuzzy Best-Worst Method

The aim of this research is finding and prioritizing performance indicators based on Balanced Scorecard (BSC) for oil and gas (O&G) companies in an uncertain environment using the Hesitant Fuzzy Best-Worst Method (HFBWM). As the O&G industry has a key role in many countries, its evaluation of performance is crucial. We utilize BSC for this purpose considering the traditional financial, customer-oriented, internal, and learning-oriented and growth perspectives and adding the social responsibility perspective. As it is usually not possible to implement all found performance indicators, we use Multi-Criteria Decision Making (MCDM) methods for prioritizing them. We employ the Best-Worst Method (BWM) which has several advantages compared to other MCDM methods. Due to uncertainties in the considered decision-making environment, we use hesitant fuzzy sets as a suitable method. Our results indicate that among the considered five perspectives of BSC, the customer and internal process perspectives are the most important ones, and the cost of R&D indicator is the most important sub-criterion.