Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Electrochemical Performance of Li4Ti5O12 by Niobium Doping for Pseudocapacitive Applications

Niobium-doped nanocrystalline Li4Ti5O12 (LTO) is synthesized by the solid-state reaction method, and the influence of dopant concentration (x = 2–10 mol%) on microstructural and electrochemical properties is studied. The X-ray diffraction and Raman patterns assessed the cubic spinel structure of Li4Ti5−xNbxO12 phase in all samples. Marginal changes in the lattice parameters, unit cell volume and dislocation density of LTO are observed with Nb substitution. The higher ionic radius of Nb induces a lattice expansion, which may be favorable for more ion intercalation/deintercalation. The SEM and TEM images display uniformly distributed nano-sized cubical particles. The represented (hkl) orientations of the SAED pattern and d-spacing (0.46 nm) between bright fringes confirm the well-crystallized LTO phase. The EDS and elemental mapping results demonstrate that Nb elements are uniformly doped in LTO with a proper stoichiometric ratio. The optimized 8%Nb-doped LTO electrode exhibits pseudocapacitive behavior and delivers a high specific capacitance of 497 F g−1 at a current density of 1 A g−1 with 92.3% of specific capacitance retention even after 5000 cycles.
Development and Validation of a Dynamic Simulation Model for an Integrated Solar Combined Cycle Power Plant

The combined cycle power plants are the most recognized thermal power plants for their high efficiency, fast start-up capability, and relatively low environmental impact. Moreover, their flexible unit dispatch supports the share of renewable energy, which contributes to carbon mitigation. The operational flexibility of Integrated Solar Combined Cycle (ISCC) power plants is a crucial factor for reliable grid stability. To evaluate the limitations and capabilities of ISCC power plants and their control structures, dynamic simulation is a feasible method. In this study, a sophisticated dynamic process model of the ISCC power plant in Kuraymat, Egypt, has been developed using APROS software. The model describes the plant with a high level of detail including the solar field, the heat recovery steam generator, and the control structures. The model was implemented structurally identical to the reference plant and tuned using the operational design data. Actual measurements were used as the basis for the initialization and validation of the dynamic simulation environment. Dynamic analysis of four different days was performed, then the simulation results were presented and compared with actual measurements. The comparison showed that the course of the actual measurements could be predicted with high accuracy. The solar field influences and the system’s overall power curves are reliably simulated. Consequently, the validated model can simulate the dynamic behavior of the ISCC power plant with a high degree of accuracy, and can be considered in future planning decisions.
Quantifying Root Colonization in Arbuscular Mycorrhizas by Image Segmentation and Machine Learning

MotivationArbuscular mycorrhizas are the most widespread plant symbioses and involve the majority of crop plants. The beneficial interaction between plant roots and a group of soil fungi (Glomeromycotina) grants the green host a preferential access to soil mineral nutrients and water, supporting plant health, biomass production and resistance to both abiotic and biotic stresses. The nutritional exchanges at the core of this symbiosis take place inside the living root cells, which are diffusely colonized by specialized fungal structures called arbuscules. For this reason, the vast majority of studies investigating arbuscular mycorrhizas and their applications in agriculture require a precise quantification of the intensity of root colonization. To this aim, several manual methods have been used for decades to estimate the extension of intraradical fungal structures, mostly based on optical microscopy observations and individual assessment of fungal abundance in the root tissues. ResultsHere we propose a novel semi-automated approach to quantify AM colonization based on digital image analysis and compare two methods based on image thresholding and machine learning. Our results indicate in machine learning a very promising tool for accelerating, simplifying and standardizing this critical type of analysis, with a direct potential interest for applicative and basic research.Contactivan. sciascia@unito.it; andrea.genre@unito.it
Artificial Intelligence in Smart Farms: Plant Phenotyping for Species Recognition and Health Condition Identification Using Deep Learning

This paper analyses the contribution of residual network (ResNet) based convolutional neural network (CNN) architecture employed in two tasks related to plant phenotyping. Among the contemporary works for species recognition (SR) and infection detection of plants, the majority of them have performed experiments on balanced datasets and used accuracy as the evaluation parameter. However, this work used an imbalanced dataset having an unequal number of images, applied data augmentation to increase accuracy, organised data as multiple test cases and classes, and, most importantly, employed multiclass classifier evaluation parameters useful for asymmetric class distribution. Additionally, the work addresses typical issues faced such as selecting the size of the dataset, depth of classifiers, training time needed, and analysing the classifier’s performance if various test cases are deployed. In this work, ResNet 20 (V2) architecture has performed significantly well in the tasks of Species Recognition (SR) and Identification of Healthy and Infected Leaves (IHIL) with a Precision of 91.84% and 84.00%, Recall of 91.67% and 83.14% and F1 Score of 91.49% and 83.19%, respectively.
Effect of Fusarium graminearum and F. Poae infection on barley and malt quality

On a examine l'influence de contaminations de Fusarium graminearum et F. poae sur la qualite de l'orge et la qualite brassicole. Le F. graminearum est le principal contaminant de maladie de fusariose d'epis au centre ouest des USA. Le F, posae a une influence moins importante. L'inoculation et la maturation des plantes sous serre dimmuent la contamination par d'autres microorganismes. Les semences temoin et celles inoculees ont ete maltees et la qualite du malt a ete evaluee. On a trouve des concentrations elevees en desoxynivalenol, 15-acetyl-desoxynivalenol et zearalenone sur des grains inocules par F. graminearum. Toutefois le F. poae produisast de faibles quantites de nivalenol. Les parametres de qualite les plus affectes etaient la taille des grains et la capacite de germination qui setrouvaient reduits. Dans l'ensemble, le F. graminearum provoquait une diminution plus significative de la qualite du grain et de la qualite brassicole que F. poae. La reduction de la taille du grain par des pathogenes rend plus difficile l'interpretation de la qualite brassicole Toutefois la contamination du Fusarium augmente le taux d'azote soluble, l'azote amine libre et la couleur du mout. Ce fait est accentue par une reduction de 40 % de grains germes compare au temoin. Le maltage des grains contamines donnait du malt avec une activite proteasique plus faible.
The interplay between e-tailer information sharing and supplier cause marketing

Inspired by the increasing cause marketing (CM) practices of business firms, this paper investigates an e-tailer's incentives to share demand information with its supplier who may implement a CM campaign. Two different selling modes, agency selling and reselling, are examined. Although most previous studies suggest that a retailer should withhold its private demand observations to maintain an information advantage over the supplier, we find that CM may be a driving factor which motivates the e-tailer to share demand information with its supplier under certain conditions. Specifically, when the CM implementation cost is small or large, the e-tailer would like to share demand information under agency selling mode while keeping information private under reselling mode. When the CM implementation cost is intermediate, the consumer's prosociality level is high and information uncertainty is small, the e-tailer misleads (incentives) the supplier to implement CM by withholding (sharing) information under the agency selling (reselling) mode; otherwise, the e-tailer prefers to share (withhold) information under the agency selling (reselling) mode.
On the Estimation of Deep Atlantic Ventilation from Fossil Radiocarbon Records. Part II. (In)consistency with Modern Estimates

Measurements of radiocarbon concentration (Δ14C) in fossil biogenic carbonates have been interpreted as reecting a reduced ventilation of the deep Atlantic during the last ice age. Here we evaluate the (in)consistency of an updated compilation of fossil Δ14C data for the last deglaciation with the abyssal circulation in the modern Atlantic. A 14C transport equation, in which the mean velocity field is a modern field estimate and turbulent flux divergence is treated as a random fluctuation, is fitted to deglacial Δ14C records by using recursive weighted least-squares. This approach allows us to interpret the records in terms of deviations from the modern flow with due regard for uncertainties in the fossil data, the 14C transport equation, and its boundary conditions.We find that the majority of fit residuals could be explained by uncertainties in fossil Δ14C data, for two distinct estimates of the modern flow and of the error variance in the boundary conditions. Thus, most, not all, deglacial data appear consistent with present-day ventilation rates. From 20 to 32% of the residuals exceed in magnitude the published errors in the fossil data by a factor of two. Residuals below 4000 m in the western North Atlantic are all negative, suggesting that deglacial Δ14C values from this region are too low to be explained by modern ventilation. Whilst deep water ventilation appeared different from today at some locations, a larger database and a better understanding of error (co)variances are needed to make reliable paleoceanographic inferences from fossil Δ14C records.
Impact of growth faults on mixed siliciclastic‐carbonate‐evaporite deposits during rift climax and reorganisation—Billefjorden Trough, Svalbard, Norway

Fault‐controlled mixed siliciclastic‐carbonate‐evaporite depositional systems exhibit distinct sensitivity to tectonic and eustatic controls that are expressed in the sedimentary architecture. In the Upper Carboniferous Billefjorden Trough (Svalbard, Norway), up to 2,000 m of a warm and arid climate syn‐rift basin fill comprises such depositional systems, documented in this study with traditional field techniques supported by helicopter‐ and ground‐based LIDAR models. The basin evolved from siliciclastics‐dominated red beds and paralic units that filled a symmetrical basin, to a rift climax half‐graben with alluvial fans entering the basin along relay ramps of the master fault zone (Billefjorden fault zone). Faults located in the hanging wall dip‐slope prevented the progradation of coarser material to the eastern part of the basin. Later, structural reorganisation in the dipslope led to the cessation of easternmost faults with deformation focusing along one major lineament (Løvehovden fault zone) antithetic to the master fault zone. The basin subsidence became more symmetrical, with main central depocentre and shallower platforms near the basin flanks. Footwall anticlines from faults displacement gradients were sensitive to periodical exposure and recorded dissolution breccias and footwall synclines preserved evaporites coupled with shallow marine siliciclastic deposits. Concurrently, thick gypsum/anhydrite deposits in the basin centre reflect glacio‐eustatic lowstands, whereas evenly thick carbonate deposition characterises highstands. While most analysis of syn‐rift basin fill is based on siliciclastics deposits, we here demonstrate the complexity of tectonism versus eustatic sea level changes in a mixed carbonate‐evaporite syn‐rift deposits. Tectonic influence is ascribed to the deposition of alluvial fans that prograded from the master fault towards the basin centre. On the dipslope glacio‐eustatic signals outperformed tectonic influence on deposition. Sea level lowstands promoted deposition of red sabkha mudstones and gypsum/anhydrite, salinas evaporites or dissolution breccias, interbedded with highstand carbonate beds.
Does a Wikipedia-based assignment increase self-efficacy among female students? A qualified maybe

Abstract Wikipedia has become one of the most used reference works, by students, educators, academics, and the general public, and there is a growing body of research exploring when and how students use the online encyclopedia. A smaller body of work examines the role of Wikipedia as a pedagogical tool for teaching information literacy and subject-matter expertise. Yet, despite the ubiquitous nature of the resource on campus, there remains a well-documented gender gap in contributions to the site. We build on previous scholarship to explore how the use of Wikipedia as a pedagogical tool can improve female self-efficacy and bridge the gender gap prevalent in contributions to open access resources. A survey of two undergraduate political science courses suggests an assignment in which students create original content for Wikipedia increases confidence in using the platform and information-seeking behavior among both female and male students, although the advantages continue to be greater for men. Furthermore, while female students are more confident in creating content after the Wikipedia assignment, once accounting for confidence there appears to be no significant difference between male and female contributions to Wikipedia. Because the assignment does lead to slight increases in confidence for women, however, it could be considered a promising first step in increasing female contributions to the site and the confidence of female students in evaluating information, more generally. We also include assignment details and recommendations for implementation.
Fertilization modes and the evolution of sperm characteristics in marine fishes: Paired comparisons of externally and internally fertilizing species

Abstract Fertilization mode may affect sperm characteristics, such as morphology, velocity, and motility. However, there is little information on how fertilization mode affects sperm evolution because several factors (e.g., sperm competition) are intricately intertwined when phylogenetically distant species are compared. Here, we investigated sperm characteristics by comparing seven externally and four internally fertilizing marine fishes from three different groups containing close relatives, considering sperm competition levels. The sperm head was significantly slenderer in internal fertilizers than in external fertilizers, suggesting that a slender head is advantageous for swimming in viscous ovarian fluid or in narrow spaces of the ovary. In addition, sperm motility differed between external and internal fertilizers; sperm of external fertilizers were only motile in seawater, whereas sperm of internal fertilizers were only motile in an isotonic solution. These results suggest that sperm motility was adapted according to fertilization mode. By contrast, total sperm length and sperm velocity were not associated with fertilization mode, perhaps because of the different levels of sperm competition. Relative testis mass (an index of sperm competition level) was positively correlated with sperm velocity and negatively correlated with the ratio of sperm head length to total sperm length. These findings suggest that species with higher levels of sperm competition have faster sperm with longer flagella relative to the head length. These results contradict the previous assumption that the evolution of internal fertilization increases the total sperm length. In addition, copulatory behavior with internal insemination may involve a large genital morphology, but this is not essential in fish, suggesting the existence of various sperm transfer methods. Although the power of our analyses is not strong because of the limited number of species, we propose a new scenario of sperm evolution in which internal fertilization would increase sperm head length, but not total sperm length, and change sperm motility.
Does Independent Director Experience Improve Individual Auditors’ Audit Quality?

This study examines whether individual auditors with experience as independent directors provide better audit performance than those without independent directorship experience. Using the Chinese setting where audit partners’ names are publicly disclosed, we find that audit partners with independent director experience provide higher audit quality for clients that operate in the same industries as the companies where they concurrently hold or have previously held directorships. However, directorship experience at companies in different industries has an insignificant effect on audit quality. These findings suggest that independent director service enables audit partners to gain industry-specific knowledge. This leads to knowledge spillovers on the audits of clients in the same industries. This study contributes to the literature by identifying an alternative channel through which auditors gain industry-specific knowledge which enhances their performance.
Iterative learning control for nonlinear nonaffine networked systems with stochastic noise in communication channels

This article investigates the convergence analysis of networked iterative learning control for nonlinear nonaffine systems firstly by considering stochastic noise introduced by the network channels. The convergence analysis is under a data-driven framework, which does not rely on any mechanism model information. To deal with the nonlinearity, both the state transition technique and the differential mean value principle are used to formulate the iterative dynamics of system states, tracking errors and input signals using a lifted matrix expression, respectively. In terms of the contraction mapping principle, the tracking error is shown to be iteratively convergent under the sense of mathematical expectation. Since the λ -norm is not used in the analysis, the convergence property of the tracking error is not affected by the operation interval and a good transient performance can be ensured in theory. Simulation studies test the theoretical results.
Research on Multi-Echelon Inventory Optimization for Fresh Products in Supply Chains

Fresh products are perishable and fragile, which easily leads to higher inventory costs and requires reasonable planning of inventory management. Therefore, it is very important for fresh product supply chain systems to have multi-echelon inventory control. However, in past studies, few control models of the multi-echelon inventory considered the deterioration rate of perishable products as the variable factor. In this paper, on the basis of considering the perishable characteristics of fresh products, combining the deterioration rate with the inventory control model, a multi-echelon inventory control model for fresh products is designed and optimized, and the optimal solution from the whole supply chain is obtained through the optimal fitness function by genetic algorithm. Finally, Flexsim is used to simulate the two inventory strategies before and after optimization. After simulation comparison and analysis, it is verified that the optimized inventory control strategy has lower costs. The research results can help supply chain managers of fresh products to make inventory management decisions and save costs, which is of practical significance.
A Survey of Deep Learning Techniques for Cybersecurity in Mobile Networks

The widespread use of mobile devices, as well as the increasing popularity of mobile services has raised serious cybersecurity challenges. In the last years, the number of cyberattacks has grown dramatically, as well as their complexity. Traditional cybersecurity systems have failed to detect complex attacks, unknown malware, and they do not guarantee the preservation of user privacy. Consequently, cybersecurity systems have embraced Deep Learning (DL) models as they provide efficient detection of novel attacks and better accuracy. This paper presents a comprehensive survey of recent cybersecurity works that use DL in mobile and wireless networks. It covers all cybersecurity aspects: infrastructure threads and attacks, software attacks and privacy preservation. First, we provide a detailed overview of DL techniques applied, or with potential applications, to cybersecurity. Then, we review cybersecurity works based on DL. For each cybersecurity threat or attack, we discuss the challenges for using DL methods. For each contribution, we review the implementation details and the performance of the solution. In a nutshell, this paper constitutes the first survey that provides a complete review of the DL methods for cybersecurity. Given the analysis performed, we identify the most effective DL methods for the different threats and attacks.
Malicious Behavior Detection Method Using API Sequence in Binary Execution Path

: Today, the amount of malware is growing very rapidly, and the types and behaviors of malware are becoming very diverse. Unlike existing malicious codes, new types or variants of malicious codes are being identified, and it takes a lot of time to analyze all malicious codes. To solve these problems malware analysts analyze and research effective ways to reduce analysis time and cost. In this paper, we propose a method to express characteristics and detect malicious codes by using API Sequence for malicious code detection and classification. It compares and analyzes several existing expression methods and verifies the effectiveness through actual malicious code samples. Using the expression method proposed in the paper, we detected six malicious behaviors: DLL Injection, Downloader, IAT Hooking, Key Logger, Screen Capture and Antidebugging. As a result, more detection was detected than by conventional detection methods, and it can be seen that the more complex the malicious behavior, the higher the detection efficiency. In addition, static analysis was adopted as the main method, but because it searches execution compression, the flow of malicious behavior can be analyzed.
Human Capital Management as a Resource in Achieving Competitive Advantage

The aim is to provide the conceptual framework for the administration of human capital (MHC) and to show how human capital may be employed to secure the competitive advantage of an organization. Human capital is a concept referring to the extra value provided to organizations by humans. It stresses the necessity for strategic human capital investments through commitment, retention, talent management, and learning and development programs. These studies often mostly depend on an examination of the literature available for their data. Study results stress the relevance of human capital and the strategic measures that contribute to success and competitiveness.