Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and photocatalytic properties of graphitic carbon nitride nanofibers using porous anodic alumina templates

In the present study, we describe an effective method for the synthesis of Graphitic carbon nitride (GCN) nanostructures using porous anodic alumina (AAO) membrane as template by simple thermal condensation of cyanamide. Synthesized nanostructure was fully analysed by various techniques to detect its crystalline nature, morphology, luminescent properties followed by the evaluation of its photocatalytic activity in the degradation of Methylene blue dye. Structural analysis of synthesized GCNNF was systematically carried out using x-ray powder diffraction (XRD) and scanning electron microscope (SEM), and. The results confirmed the growth of GCN inside the nanochannels of anodic alumina templates. Luminescent properties of GCNNF were studied using photoluminescence (PL) spectroscopy. PL analysis showed the presence of a strong emission peak in the wavelength range of 350–600 nm in blue region. GCNNF displays higher photocatalytic performance in the photodegradation of methylene blue compare to the bulk GCN. Highlights 1. In the present paper, we report the synthesis of graphitic carbon nitride nanofibers (GCNNF) using porous anodic aluminium oxide membranes as templates through thermal condensation of cyanamide at 500 °C. 2. The synthesis of Graphitic carbon nitride nanofibers using porous andic alumina template is the efficient approach for increasing crystallinity and surface area. 3. The high surface area of graphitic carbon nitride nanofibers has a good impact on novel optical and photocatalytic properties of the bulkGCN. 4. AAO templating of GCN is one of the versatile method to produce tailorable GCN nanostructures with higher surface area and less number of structural defects. 5. Towards photocatalytic degradation of dyes, the tuning of physical properties is very essential thing hence we are succeeded in achieving better catalytic performance of GCN nanostructures by making use of AAO templates.
The Dynamics of Subjective Career Success: A Qualitative Inquiry

Current perspectives on career success have yet to show whether and how subjective career success evaluations may change over time and across career phases. By adopting a retrospective life-span approach to careers, our qualitative inquiry into the career experiences of 63 professionals contributes to the temporal understanding of subjective career success by exploring patterns in how subjective career success perceptions and priorities may change over time. The temporal development of subjective career success was explored among early-career, mid-career, and late-career workers by piecing together retrospective evaluations of career success perceptions. Our findings point to common patterns in career success perceptions across the lifespan. Specifically, we found five shift components of career success perceptions during people’s careers: (1) quitting striving for financial success and recognition; (2) an increased focus on personal development across the career; (3) a stronger emphasis on work–life balance across the career; (4) a shift toward being of service to others; and (5) no change in subjective career success components across the career. These patterns reflect ways in which workers engage in motivational self-regulation and the corresponding career goal-setting across the lifespan. The theoretical implications are discussed.
Data Hiding Using PVD and Improving Security Using RSA

Abstract Steganography deals with hiding information, which offers ultimate security in defense, profitable usages, thus sending the imperceptible information, will not be bare or distinguished by others. In this paper, a multidirectional PVD hiding scheme with RSA algorithm is proposed. Secret bits are embedded in three directions of a color image by dividing the non-overlapping blocks into R, G, b channels by selecting the minimum pixels of each block regrouping. In order to ensure the security of an stego-image, the work proposed by scheme is used, and in addition to that RSA algorithm is proposed.
Rethinking the adversary and operational characteristics of deniable storage

Aim: With the widespread adoption of disk encryption technologies, it has become common for adversaries to employ coercive tactics to force users to surrender encryption keys. For some users, this creates a need for hidden volumes that provide plausible deniability, the ability to deny the existence of sensitive information. Previous deniable storage solutions only offer pieces of an implementable solution that do not take into account more advanced adversaries, such as intelligence agencies, and operational concerns. Specifically, they do not address an adversary that is familiar with the design characteristics of any deniable system. Methods: We evaluated existing threat models and deniable storage system designs to produce a new, stronger threat model and identified design characteristics necessary in a plausibly deniable storage system. To better explore the implications of this stronger adversary, we developed Artifice, the first tunable, operationally secure, self repairing, and fully deniable storage system. Results: With Artifice, hidden data blocks are split with an information dispersal algorithm such as Shamir Secret Sharing to produce a set of obfuscated carrier blocks that are indistinguishable from other pseudorandom blocks on the disk. The blocks are then stored in unallocated space of an existing file system. The erasure correcting capabilities of an information dispersal algorithm allow Artifice to self repair damage caused by writes to the public file system. Unlike preceding systems, Artifice addresses problems regarding flash storage devices and multiple snapshot attacks through simple block allocation schemes and operational security measures. To hide the user’s ability to run a deniable system and prevent information leakage, a user accesses Artifice through a separate OS stored on an external Linux live disk. Conclusion: In this paper, we present a stronger adversary model and show that our proposed design addresses the primary weaknesses of existing approaches to deniable storage under this stronger assumed adversary.
Determination of the hygroscopic equilibrium and isosteric heat of aji chili pepper

Determinação do equilíbrio higroscópico e calor isostérico de pimenta Dedo-de-Moça R E S U M O Esta pesquisa focou na determinação do equilíbrio higroscópico e do calor isostérico da pimenta Dedo-de-Moça (Capsicum baccatum) sob diferentes condições controladas de temperatura e umidade relativa do ar. Foi ajustado o modelo que melhor representa o comportamento isotérmico de sorção entre os modelos descritos na literatura, bem como a proposta de um novo modelo e parâmetros que satisfazem com representatividade o fenômeno de higroscopicidade e calor isostérico. As temperaturas utilizadas foram 30, 50 e 70 oC, com níveis de atividade de água variando de 0.11 a 0.84. O calor isostérico integral de sorção da pimenta Dedo-de-Moça, para o teor de água entre 0.07 a 0.54 (b. s.), variou de 3641.66 a 2614.38 kJ kg-1. O modelo que melhor se representa o comportamento do equilíbrio higroscópico e calor isostérico é o novo modelo proposto no presente estudo, com R2 igual a 0.97.
Multilevel analysis of evolution of team process and their relation to performance in semi-professional soccer

The aim of the study was to examine the evolution of players' perception of group variables (leadership, motivational climate, cohesion, and collective efficacy) and to determine whether the intercept and growth trajectory differed as a function of whether expectations have or have not been met in a sample of semi-professional Spanish football players. The results show that the levels of the variables (except for autocratic leadership and coach-created ego climate) decrease over the season. Furthermore, the mean scores of the “fully meets expectations” group were significantly higher in positive leader characteristics, coach-created task climate, cohesion and collective efficacy. Also, rates of decline were significantly greater in the “does not meet expectations” group. The results indicate the importance of establishing reachable expectations by coaches and players because to achieve or to miss the expected goals can affect psychological group dynamics.
A closed-form pricing formula for catastrophe equity options

In this article, we derive a closed-form pricing formula for catastrophe equity put options under a stochastic interest rate framework. A distinguishing feature of the proposed solution is its simplified form in contrast to several recently published formulae that require evaluating several layers of infinite sums of $n$-fold convoluted distribution functions. As an application of the proposed formula, we consider two different frameworks and obtain the closed-form formula for the joint characteristic function of the asset price and the losses, which is the only required ingredient in our pricing formula. The prices obtained by the newly derived formula are compared with those obtained using Monte-Carlo simulations to show the accuracy of our formula.
A Comparative Analysis of Multi-Epoch Double-Differenced Pseudorange Observation and Other Dual-Satellite Lunar Global Navigation Systems

In this study, dual-satellite lunar global navigation systems that consist of a constellation of two navigation satellites providing geo-spatial positioning on the lunar surface were compared. In our previous work, we proposed a new dual-satellite relative-positioning navigation method called multi-epoch double-differenced pseudorange observation (MDPO). While the mathematical model of the MDPO and its behavior under specific conditions were studied, we did not compare its performance with other dual-satellite relative-positioning navigation systems. In this paper, we performed a comparative analysis between the MDPO and other two dual-satellite navigation methods. Based on the difference in their mathematical models, as well as numerical simulation results, we developed useful insights on the system design of dual-satellite lunar global navigation systems.
Biogeochemical Gradients in a Serpentinization‐Influenced Aquifer: Implications for Gas Exchange Between the Subsurface and Atmosphere

Serpentinization involves the hydration and alteration of ultramafic rocks, which produces hydrogen (H2) and methane (CH4) and results in distinctive groundwater chemistries. As reacted fluids mix with recharging surface water, gradients in chemistry and microbiology develop in the subsurface. We present a comprehensive analysis of biogeochemical gradients in the water column of a serpentinite‐hosted well, CSW1.1, at the Coast Range Ophiolite Microbial Observatory (CROMO) in California, USA. Samples for geochemistry, 16S rRNA gene sequencing, and metagenomics were collected at four discrete depths from the top of the well corresponding to 100%, 50%, 15%, and 0% of atmospheric oxygen (O2) levels, and from the well base at 19.5 m depth. Gibbs energy calculations assessed the energy available for a suite of reactions coupled to O2, sulfate (SO42−), and nitrate (NO3−). Metagenomic data from the profile was used to construct metagenome assembled genomes (MAGs) to evaluate the completeness of biochemical pathways and compare the relative abundance of key diagnostic genes. Bioenergetic data point to the favorability of CH4 oxidation reactions despite little genetic evidence for this. Amplicon sequencing results highlight the abundance of key taxa affiliated with the genera Truepera, Serpentinomonas, and Dethiobacter. Although concentrations of NO3− and H2 are low, genes for NO3− reduction and oxidation of H2 and carbon monoxide (CO) were found in high abundance. Conceptual modeling results demonstrate the net depletion of H2 and CO in the groundwater, the consumption of CO2 and O2, and the potential for CH4 emission into the atmosphere at this terrestrial site of serpentinization.
Ultrasound-Assisted Extraction using Response Surface Methodology for Extracting Flavonoids from Padina australis

Seaweed or sea macroalgae are rich in potential compounds which can be used for the treatment of disease. Padina australis is one of the important brown macroalgae classes (Phaeophyes). One of the bioactive compounds of P. australis is a phenolic compound and its derivatives (flavonoid). In this research, P. australis was collected from Bayah Beach, Banten, Indonesia. For the extraction flavonoids from P. australis, ultrasound-assisted extraction (UAE) was employed. In this study, a three-level Box-Behnken design (BBD) and the response surface methodology (RSM) were employed to obtain the optimal combination of extraction conditions. The effects of several independent variables including temperature (30, 50, 70 ℃), extraction time (20, 40, 60 min) and ethanol concentration (30, 50, 70%) were investigated. The result showed that RSM was an accurate and reliable method in predicting the total flavonoid content with R2 value of 0.9935. The optimal UAE conditions for the highest yield of total flavonoid content were 49.70 ℃ in temperature, process time under 44.03 min, and 47.80% ethanol with 0.2162% total flavonoid content. Under the above conditions, the experimental value of total flavonoid content was 0.2144+ 0.0035%. The predicted and experimental values for total flavonoid from brown algae P. australis were not significant differences, it indicating that the developed models are accurate. Therefore, UAE using RSM is effective for the extraction of flavonoid from P. australis.
KF post deposition treatment in co‐evaporated Cu(In,Ga)Se2 thin film solar cells: Beneficial or detrimental effect induced by the absorber characteristics

Recent breakthroughs in Cu(In,Ga)Se2 (CIGS) thin film solar cell energy conversion efficiency are related to the application of a potassium fluoride post‐deposition treatment (KF‐PDT) to the completed absorber. Using X‐ray photoelectron spectroscopy and Raman scattering, we compare CIGS layers prior and after the KF‐PDT in the case of a deterioration and an improvement of the solar cells photovoltaic performance. The purpose is to study and model the modification of the surface in both cases and address some of the required characteristics of the absorber, grown on soda lime glass by 3‐stage process, in order to take advantage of the treatment. We show that, in both cases, KF‐PDT induces the formation of GaF3, which is removed during the subsequent chemical bath deposition of CdS, explaining the Ga depleted absorber surface, already reported in literature. However, the presence or not of an ordered defect compound (ODC), correlated with the third stage duration during the CIGS growth, is shown to be crucial in the modifications of the surface induced by the treatment. When an ODC is present prior the treatment, KF‐PDT leads to the formation of a surface layer of In2Se3 containing K, and the photovoltaic performance of completed solar cells are improved. When no ODC is present prior KF‐PDT, no trace of K is found at the absorber surface after the treatment, copper (Cu) segregates into detrimental CuxSe phases, high amount of elemental Se is formed, and the photovoltaic performance are lowered. The role of the ODC during the KF‐PDT is finally discussed.
Integrative description of a new Tunisian tardigrade species, Macrobiotus azzunae sp. nov. (Eutardigrada, Macrobiotidae, hufelandi group)

In this paper a new tardigrade species, Macrobiotus azzunae sp. nov., from Tunisia, is described. An integrative taxonomic approach was applied by combining morphological, morphometric and molecular data. In particular, light and scanning electron microscopy observations, and four genetic markers, three nuclear (18S rRNA, 28S rRNA and ITS-2) and one mitochondrial (COI) were used. The analysis showed that M. azzunae sp. nov. belongs to the Macrobiotus hufelandi group and is most similar to Macrobiotus sandrae Bertolani & Rebecchi, 1993. It differs from M. sandrae by a more pronounced constriction of the first macroplacoid (hardly visible in M. sandrae) and for the eggshell shape, with thinner wires of the reticulum and meshes around the processes larger than the inter-process meshes in M. azzunae sp. nov., while all meshes are similar in size in M. sandrae. The species is gonochoristic. With this discovery, there are 33 species of tardigrades identified in Tunisia, all non-marine. This result, compared with nearby Sicily, where more research has been conducted, indicates that there is a considerable potential for identification of new species. Further research will be most informative if multiple habitats are explored and if carried out with an integrated approach as done in this present work.
Greek news topics classification using graph neural networks

Recent advancements in deep learning have increased the research interest in the field of Natural Language Processing (NLP). This has led to various state-of-the-art breakthroughs, with the family of graph-based methods being no exception. The aim of this thesis is to contribute in the progression of Graph Neural Networks (GNN) and the field of NLP, by studying the problem of text classification in the Greek language. We start by evaluating the task with well established machine learning and deep learning methods, then we finalize our work by researching graph-based approaches and proposing a novel addition to them. GNN methods use different kinds of neural networks to process spatial information and construct their graphs on document or corpus level. However, regardless their structure, all studies use non-contextual embeddings for their training. Drawing inspiration from contextual language models, in this work we propose a method based on a recent study, which has been modified to utilize quantized contextual embeddings. In order to achieve this, we first employ a pre-trained BERT model which produces the contextual embeddings for our vocabulary. Using every available embedding, though, would lead to a very sparse and inefficient graph. To overcome this issue, we quantize the numerous representations of every word with the use of K-means, by clustering multiple embeddings into a fixed amount of centroids. Finally, we use those centroids as the actual input of the graphs. Multiple experiments on our dataset show that our suggested method outperforms both the baseline experiments and the original method on which we have been based on.
SUSTAINABLE Building Technology and Urban Development

Mobility as a service (MaaS) aims to integrate moving, which has been segmented by the combination of various means of transportation, and payment systems as a service and provide door-to-door services to users. Providing complete door-to-door MaaS services to users requires advances in the level of transportation services to solve the first-last mile problem. Micro mobility, such as public bikes and electric scooters, is drawing attention as a means of transportation that can be used for first-last mile travels. Providing complete door-to-door services to MaaS users requires preemptive responses to the demand for micro mobility as well as the ability to track that demand in real time. This essentially requires the ability to forecast the demand for micro mobility. Unlike existing public transportation, micro mobility does not have a fixed travel route or travel time, which causes large variations in demand within short time frames. Therefore, demand forecasting methods different from those used for existing public transportation are needed. In this study, a hybrid forecasting model was designed to forecast the demand for micro mobility that fluctuates sharply and is irregular, and its accuracy was verified. The hybrid forecasting model was based on a genetic algorithm and deep learning algorithm, and the Seoul public bike service, Ttareungyi, was selected as a representative example of micro mobility. To test the model, the rental and return data for Ttareungyi were predicted at the station with the highest eigenvector centrality. The results show higher forecasting accuracy with the hybrid forecasting model than with single forecasting models. The rental and return data forecast by the hybrid forecasting model could be provided as 'expected rental availability' through a MaaS application, and operators could use the data to efficiently relocate bikes to meet demand.
Growth of Basil (Ocimum basilicum) in Aeroponics, DRF, and Raft Systems with Effluents of African Catfish (Clarias gariepinus) in Decoupled Aquaponics (s.s.)

Basil (Ocimum basilicum) was cultivated in three hydroponic subsystems (i) a modified commercial aeroponics, (ii) a dynamic root floating (DRF) system, and (iii) a floating raft system in a decoupled aquaponic system in Northern Germany, Mecklenburg–Western Pomerania. For plant nutrition, aquaculture process water from intensive rearing of African catfish (Clarias gariepinus) was used without fertilizer. After 39 days, 16 plant growth parameters were compared, with aeroponics performing significantly better in 11 parameters compared with the DRF, and better compared with the raft in 13 parameters. The economically important leaf wet and dry weight was over 40% higher in aeroponics (28.53 ± 8.74 g; 4.26 ± 1.23 g), but similar in the DRF (20.19 ± 6.57 g; 2.83 ± 0.90 g) and raft (20.35 ± 7.14 g; 2.84 ± 1.04 g). The roots in the DRF grew shorter and thicker; however, this resulted in a higher root dry weight in aeroponics (1.08 ± 0.38 g) compared with the DRF (0.82 ± 0.36 g) and raft (0.67 ± 0.27 g). With optimal fertilizer and system improvement, aquaponic aeroponics (s.s.) could become a productive and sustainable large-scale food production system in the future. Due to its simple construction, the raft is ideal for domestic or semi-commercial use and can be used in areas where water is neither scarce nor expensive. The DRF system is particularly suitable for basil cultivation under hot tropical conditions.
Novel Aspects of Constructal Law: Four Distinct and Competing Goals in Flow Channels Design

Constructal law explains the sense of evolution (morphing to get access to flows) of finite size systems, but paradoxes do exist as not all vegetables have a tree form. Also, nature does not improve all animals for displacement. This work aims at creating a model to explain those paradoxes about constructal law. It adopted the system engineering technique of segregation between functions (abstract goals) and solutions (physical entities). Further, this work introduced the assumptions of flow under external threats and imperfect channels (subject to leakages and suboptimal form). Results showed that there are always elements doing four functions in all types of channels: to reduce entropy, to protect channel, to retain integrity and to drive flow. Although the four functions are always present, natural systems typically privilege one function over others, depending on environmental demands. As a solution to improve flows, animal brains also fit in the model of four functions. Human mind seems to have groups of instincts associated with each of the four channel design functions, leading to four behavior phenotypes and four motivations (prominence, inclusiveness, negativity prevention and tradition). Finally, this model (channels need to meet four goals) unified physics and animal psychology and extended applications of Constructal law to the fields of systems engineering methods, management, and psychological science.