esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Synthesis of Amidoalkyl Naphthols via Multicomponent Mannich Condensation  
Although many routes to obtain similar structures including phenols and naphthols, e.g., via transition-metal catalysis, have been reported [38, 39, 40, 41], multicomponent Mannich condensation continues to be the primary way to achieve the synthesis of amidoalkyl naphthols.  
Multicomponent reactions are of increasing importance in organic synthesis for the preparation of complex and diverse molecules through the formation of carbon-carbon and carbon-heteroatom bonds. These reactions involve three or more compounds mixed simultaneously in one vessel that react with each other and give the final target product without having to isolate the intermediates. Hence, one-pot multicomponent synthesis is in accordance with the principles of green chemistry, which require the development of new substances and reaction conditions that have the potential to provide benefits to chemical synthesis to meet certain requirements regarding resource and energy efficiency, operational simplicity, and product selectivity, as well as including environmental and health protections through reducing toxic solvent use and amount of waste produced as much as possible [42, 43, 44, 45, 46]. An example of such a reaction is the Mannich condensation of 2-naphth with aldehydes and amide derivatives, in the presence of a catalyst, which is used as a practical synthetic route towards 1-amidoalkyl-2-naphthols [47] (Scheme 3). The same reaction is applicable to the synthesis of 1-carbamatoalkyl-2-naphthols when carbamates are used as reaction partners [48, 49, 50, 51, 52, 53]. However, the reports on the synthesis of 1-carbamatoalkyl-2-naphthols over the last 3 years are limited [54, 55]. The generally accepted reaction mechanism of the acid-promoted three-component Mannich condensation of 2-naphthol with aldehydes and amides proceeds with the initial formation of highly reactive _ortho_-quinone methides. These intermediates react with an amide via nucleophilic conjugate addition to form 1-amidoalkyl-2-naphthol (Scheme 3) [56, 57, 58].  
A number of different catalytic systems that effectively promote this reaction have been reported. These catalytic systems could be generally classified as homogeneous (Bronsted acids, Table 1, and ionic liquids/deep eutectic solvents, Table 2) and heterogeneous (nanomaterials and others, Table 3).
## 2 Materials and Methods
### E-Nose Instrument and Data Measurement  
The e-nose system used was FOX 4000 (Alpha MOS, Toulouse, France), which is equipped with 18 metallic oxide gas sensors in three sensor chambers. VOCs of strawberries in each group were acquired at 0 h (before impact) and 4, 8, and 24 h after impact. Before extracting VOCs, each fruit sample was placed in a 100 mL glass beaker. Parafilm PM996 (Pechiney Plastic Packaging, Menasha, WI, USA) was used to seal the beaker for 1 h to equilibrate the headspace inside. The whole process of generating headspace gas was carried out at 15 \({}^{\circ}\)C to simulate the actual condition in practice. For the acquisition of VOCs, 2 mL of headspace gas was injected into the Fox 4000 system. The gas was then pumped into the sensor array with a constant rate of 150 mL\(\cdot\)min\({}^{-1}\). The entire detection progress of each sample lasted 6 min, including 120 s for the measurement phase and 240 s for the clean phase.
## 3 Optimization of Annual Costs
#### Sensitivity Analysis
It is concluded that the configuration and storage pressure that minimize the costs (under the assumption considered in this work) are four CO\({}_{2}\) compressor stages to a final pressure of 72.5 bar and three H\({}_{2}\) compressor stages to a final pressure of 67.6 bar. In both cases, for the different stages (three, four or five) the final storage pressure is relatively unchanged, but the cost clearly indicates the most feasible configuration. Adding an additional stage increases the TAC by 17.19% using CO\({}_{2}\) as the working gas, and by 11.87% using H\({}_{2}\). These results could also be useful in other applications of temporary energy storage that make use of CO\({}_{2}\), as in the case of calcium looping for concentrated solar power applications [30; 31] or H\({}_{2}\) in the form of gas. Evidently, in this last case, there are several options to storage H\({}_{2}\)[32; 33]; we only consider a temporary gas storage and the results can vary from other sources. In any case, the possibility of H\({}_{2}\) pipe storage up to 100 bar is realistic and there are enough expertise when applied to natural gas [32].
# Carbon Nanotube-Based Composite Filaments for 3D Printing of Structural and Conductive Elements
## 2 Materials and Methods
### FDM Printer and Printing Parameters  
For the sample preparation, we used a commercial, low-end FDM printer, CTC Bizer 2X PRO, using Flashprint control software. The structure and mechanics of the Bizer FDM printer are typical for standard, unmodified direct drive printers. The diameter of the printed nozzle was 800 \(\upmu\)m. Filaments with different amounts of filler were used to print samples for the mechanical and electrical tests. The shape and dimensions of test samples according to ISO standards are shown in Figure 4.  
All test samples were printed at a nozzle temperature of 240 \({}^{\circ}\)C and a platform temperature of 110 \({}^{\circ}\)C. The layer height was set at 200 \(\upmu\)m, printing speed at 30 mm/s, the fill pattern as line at 45\({}^{\circ}\), and a 100% infill. The selected parameters allowed us to obtain high-quality samples without clogging the nozzle (Figure 5).  
Figure 2: Schematic diagram of a single screw extruder used for the composite filaments fabrication.  
Figure 4: Schematic drawing with dimensions of 3D printed samples for mechanical tests according to ISO 527-2 standard.  
Figure 5: 3D printed samples for mechanical and electrical measurements printed from acrylonitrile butadiene styrene/carbon nanotube (ABS/CNT) composites. Quality of the samples is acceptable for further tests.  
Figure 3: Extruded composite filaments filled with 9.09 wt.% of carbon nanotubes, with diameters in the range of 1.7–1.8 mm.
# Coupling Secret Sharing with Decentralized Server-Aided Encryption in Encrypted Deduplication
###### Abstract  
Outsourcing storage to the cloud can save storage costs and is commonly used in businesses. It should fulfill two major goals: storage efficiency and data confidentiality. Encrypted deduplication can achieve both goals via performing deduplication to eliminate the duplicate data within encrypted data. Traditional encrypted deduplication generates the encryption key on the client side, which poses a risk of offline brute-force cracking of the outsourced data. Server-aided encryption schemes have been proposed to strengthen the confidentiality of encrypted deduplication by distributing the encryption process to dedicated servers. Existing schemes rely on expensive cryptographic primitives to provide a decentralized setting on the dedicated servers for scalability. However, this incurs substantial performance slowdown and can not be applied in practical encrypted deduplication storage systems. In this paper, we propose a new decentralized server-aided encrypted deduplication approach for outsourced storage, called ECDedup, which leverages secret sharing to achieve secure and efficient key management. We are the first to use the coding matrix as the encryption key to couple the encryption and encoding processes in encrypted deduplication. We also propose a acceleration scheme to speed up the encryption process of our ECDedup. We prototype ECDedup in cloud environments, and our experimental results based on the real-world backup datasets show that ECDedup can improve the client throughput by up to 51.9% compared to the state-of-the-art encrypted deduplication schemes.  
encrypted deduplication; secret sharing; server-aided encryption; message-locked encryption; distributed data management +
Footnote †: journal: Applied sciences  
Article
# Kolmogorov-Arnold Networks for Reduced-Order Modeling in Unsteady Aerodynamics and Aeroelasticity
## 1 Introduction
In particular, their ability to flexibly represent nonlinear and time-delayed behaviors makes KANs a promising modeling paradigm for unsteady aerodynamics and aeroelastic response prediction, offering new insights into data-driven reduced-order modeling. This paper introduces a reduced-order model for unsteady aerodynamics and aeroelasticity based on Kolmogorov-Arnold Networks. Inspired by the Temporal Kolmogorov-Arnold Network (TKAN) [32], we developed a novel architecture termed the Kolmogorov-Arnold Gated Recurrent Network (KAGRN) for modeling unsteady aerodynamic forces and nonlinear aeroelastic responses. This innovative structure enables the model to effectively capture the inherent time-delay characteristics and nonlinear dynamics of unsteady aerodynamics, thereby allowing for the accurate identification and prediction of unsteady aerodynamic and aeroelastic behaviors. Furthermore, due to its inherently efficient network structure, the model achieves higher predictive accuracy and improved generalization performance compared to conventional architectures. The effectiveness of the proposed reduced-order model is validated through case studies involving the prediction of unsteady aerodynamic coefficients under harmonic motion, as well as the prediction of limit cycle oscillation (LCO) responses, with results exhibiting strong agreement with those obtained from high-fidelity CFD simulations.
## 2 Quasi-Static Finite Cylindrical Cavity Expansion Model
### Basic Model and Equations  
It is assumed that, during the penetration process, the target material undergoes only axisymmetric deformation perpendicular to the penetration direction, with no deformation occurring parallel to it. As shown in Figure 1, the radius of the cylindrical target without expansion is \(r_{\rm 10}\), the target at time \(t\) is \(r_{\rm t}\), the cavity radius is \(r_{\rm c}\), and the elastic-plastic interface radius is \(r_{\rm p}\). As the cavity radius expands to \(r_{\rm c1}\), the elastic-plastic boundary reaches the target lateral boundary. When the cavity radius expands to \(r_{\rm c2}\), the target fractures. Therefore, the process of cavity expansion can be divided into two stages based on the cavity radius. The first stage is the elastic-plastic stage (\(r_{\rm c}<r_{\rm c1}\)), which is composed of the cavity region (\(0<r<r_{\rm c}\)), the plastic region (\(r_{\rm c}<r<r_{\rm p}\)), and the elastic region (\(r_{\rm p}<r<r_{\rm t}\)). The second stage is the plastic stage (\(r_{\rm c1}<r_{\rm c}<r_{\rm c2}\)), which is composed of the cavity region (\(0<r<r_{\rm c}\)) and the plastic region (\(r_{\rm c}<r<r_{\rm t}\)), where \(r\) is the radial coordinate in the Euler coordinate (positive outward).  
Based on the axisymmetric assumption, the momentum conservation equation in Euler coordinates is  
\[\frac{d\sigma_{r}}{dr}+\frac{\sigma_{r}-\sigma_{\theta}}{r}=0, \tag{1}\]  
where \(\sigma_{r}\) and \(\sigma_{\theta}\) are the radial and hoop components, respectively, of Cauchy stress taken to be positive under compression.  
To obtain a relatively precise analytical solution, it is assumed that the target behaves as an elastic, perfectly plastic rate-independent material according to [15; 27]. The target material in the elastic region is assumed to obey [PERSON]'s law. The stress-displacement relations based on the axisymmetric assumption and [PERSON]'s law are as follows:  
\[\sigma_{r}=-\frac{E}{(1+v)(1-2v)}\left[(1-v)\frac{du}{dr}+v\frac{u}{r}\right], \tag{2}\]  
\[\sigma_{\theta}=-\frac{E}{(1+v)(1-2v)}\left[v\frac{du}{dr}+(1-v)\frac{u}{r} \right], \tag{3}\]  
where \(Y_{\mathrm{t}}\) is the flow stress of the target, \(E\) is [PERSON]'s modulus of the target material, \(v\) is [PERSON]'s ratio, and \(u\) is the radial displacement (positive outward).  
And the unified yield criterion of metal materials under axisymmetric conditions [22] is employed to describe the target material in the plastic region and investigate the resistance characteristics of the target under different yield conditions:  
\[\sigma_{r}-\sigma_{\theta}=\frac{2(1+b)}{2+b}Y_{\mathrm{t}}, \tag{4}\]  
where \(Y_{\mathrm{t}}\) is the flow stress of the target and \(b\) (\(0<b<1\)) is the yield criterion coefficient. When b is set to 0, 0.367, and 1, the Tresca yield criterion, Mises yield criterion, and twin shear yield criterion are used, respectively.
## 2 Materials and Methods
### Conceptual Background
In addition, they established the maximisation of the annual cultivation duration as the main criterion to reduce its environmental impact, as long as the solar conditions allow for the growth of the micro-algae. [PERSON] et al. [29] performed a life cycle assessment of two possible configurations of sodium nickel chloride batteries to identify the most relevant environmental impact elements and set the path for future sustainable strategies for these products. [PERSON] and [PERSON] [30] analysed in depth the possible recycling of materials used in dye solar cells. Furthermore, using eco-design principles, they proposed substituting materials used in conventional cells, which cannot be recycled in an economically viable way, with recyclable materials that eliminate toxic gas emissions during the recycling process. A life cycle assessment is a methodology that allows for calculating the environmental impact of any given product or process from cradle to grave [16; 17]. It includes all the phases of the entire existence of a product, from its manufacture to the end-of-life recovery phase, with its negative impacts (resources, emissions, discharges, and unusable waste) and positive impacts (new jobs, reuse of components, new resources). This significant capacity to consider the environmental impact of a product as a whole makes this methodology one of the most widely used in the environmental scientific literature [31; 32; 33; 34; 35; 36; 37]. It is used to analyse the environmental impact all the way from renewable energies [38; 39; 40; 41] to the construction industry [42; 43] or food products [44]. Within the LCA methodology, different life cycle impact assessment (LCIA) methods can be used to calculate the environmental impact of the product or process under study [45]. It is common for a non-expert eye on the topic to have difficulties understanding the results obtained from an LCA and the possible differences depending on the LCIA used. The fact that there are two clearly differentiated categories of LCIA methods, midpoints and endpoints, magnifies this confusion when interpreting LCA results. The midpoint methods (i.e., CML) [46] present the results in a series of categories based on characterisation factors for different emissions, for example, CO\({}_{2}\) for climate change or SO\({}_{2}\) for acidification. On the other hand, endpoint methods (i.e., Eco-indicator 99 or ReCiPe) [47; 48] weigh and group these impact categories to obtain results in several damage categories that are easier to interpret, for example, damage to the ecosystem or human health. Furthermore, these damage categories can be summed to obtain a single environmental impact value that comprises, in a balanced way, all the environmental impacts resulting from the product under study. Logically, these extra steps of weighting and grouping of general impact categories add extra uncertainty to the final LCA results.
# Improving Robotic Bin-Picking Performances through Human-Robot Collaboration
## 2 Open Technological Issues
### Bin-Picking Failures  
Because robotic bin-picking involves picking of overlapping complex objects with an undefined position and subsequent grasping and placing, several types of failures can occur. Bin-picking failures can be classified as follows:  
* Object recognition failures (perception failures): this type of failure occurs when the implemented computer vision algorithm is not able to recognize one or more items inside the bin. This happens frequently with reflective, shiny, or transparent objects or also with changes in lighting conditions. It is strongly correlated to the chosen vision sensor technology and computer vision algorithm, as well as with the resolution of the 3D map acquired;
* Pose estimation failures: this kind of failure happens when an object inside the bin is successfully recognized, but its calculated 3D pose is incorrect, and therefore the subsequent grasp fails. This may be due to vision sensor calibration errors or, more often, to an inaccurate pose estimation algorithm;* Failures because of constraints on robot motion: this type of failure happens when it is not possible to reach the calculated object pose without collisions of the end effector with the bin edges and bin corners or with other objects inside the bin. These failures are strongly correlated to the shape and height of the bin, along with the shape of the end effector. For example, suction grippers are usually more compact and can reach the edges of the bin more easily than parallel grippers. In [22], an eccentrically mounted gripper and chamfered bin edges have been exploited in order to decrease the rate of this type of failure;
* Grasping failures: even though object recognition and pose estimation are successful, grasping can still fail for a number of reasons such as a porous or uneven surface, insufficient friction, grasp interference, entangled objects or multiple grasping of neighboring objects. A very detailed investigation of grasping failures in bin-picking applications with different end effectors can be found in [20].  
Bin-picking task execution failures typically require the assembly/manufacturing line to be paused if the fault is unrecoverable and human intervention to enter the robotic workcell (thus, entering safety fences), clear the fault (for example, pick the entangled objects and either separate or discard them), and restart the line. Failures negatively influence the average cycle time, which often has a large impact on the value of bin-picking.
_Article_  
**Chitosanan Microbeads as Supporter for _Pseudomonas putida_ with Surface Displayed Laccases for Decolorization of Synthetic Dyes**  
**[PERSON] 1,2, [PERSON] 1, [PERSON] 1 and [PERSON] 1,*(c)**  
Received: 3 December 2018; Accepted: 24 December 2018; Published: 3 January 2019  
**Abstract:** Various untreated wastewaters contaminated with industrial dyes pose significant pollution hazards to the natural environment as well as serious risks to public health. The current study reports a new material with a configurative chitosan matrix and engineered _Pseudomonas putida_ cells with surface-displayed lacases that can decolorize five industrial dyes. Through a self-configuring device, five chitosan microbeads (CTS-MBs) with different particle sizes were prepared. _P. putida_ cells were then immobilized onto the CTS-MBs under optimized immobilization conditions, forming a degrading-biosorbent dual-function decolorization complex. Scanning electron microscope and infrared analysis confirmed the successful immobilization of the cells onto the CTS-MB matrix. The optimized CTS-MB1 with surface-grafted aldehyde groups (aCTS-MB1) complex was capable of decolorizing Acid Green 25 and Acid Red 18 over a pH range of 2.5-8.5 and a relatively broad temperature range of 15-85 \({}^{\circ}\)C, with a maximum relative decolorization value of over 94%; the complex was also able to efficiently decolorize Direct Red 243, Reactive Blue 220 and Reactive Blue 198. Moreover, the aCTS-MB1 composite showed favorable activity in continuous and regenerative decolorization reactions. Therefore, the chitosan-immobilized decolorizing material, with both improved mechanical strength and performance, shows potential for further large-scale or continuous processes.  
**Keywords:**chitosan; _Pseudomonas putida_; immobilization; dye decolorization; degradation; biosorption
Because of the unique geometrical shape of LSCs, which are comprised of flat long liners and multiple claddings necessary in the manufacture as well as provision of confinement effects for the explosive charge, an approach to understand the performance of LSCs must be analyzed with a different perspective. For example, in a conventional application of CSCs (conical shaped charges), the top-apex initiation of CSCs followed by the gradual sweeping of detonation propagation from top to bottom of the liner provides for detonation propagation and jet projection both in the same axis, generating a focused penetration in a single-point fashion and facilitating better penetration performance. However, the linearly long-shaped LSCs, accompanied with a typical single end-point initiation, operate with different axes for the detonation propagation and the jetting projection, decreasing the penetration performance. When a detonation propagates along the length of LSCs, the interaction between the liner of LSCs and the detonation front is in a different regime than that of CSCs, creating a simultaneous projection of the entire liner without the typical gradual liner collapse occurred in CSCs.  
An analytical approach of such simultaneous movement of the entire liner is described in Birkhoff theory by applying the \(\alpha=\beta\) assumption, representing an identical apex and collapse angle during the liner collapse in the original equations. The resulting velocity of jetting and slug was calculated as follows [1].  
\[V_{j}=\frac{V_{p}}{sin\alpha}\left(1+cos\alpha\right) \tag{1}\]  
\[V_{\text{s}} \tag{2}\]  
where \(V_{j}\), \(V_{s}\), \(V_{p}\), \(\alpha\) and \(\beta\) are the jet slug, liner velocity, original apex angle, and liner collapse angle respectively. Any explosive system where the \(\alpha=\beta\) condition can be applied should operate according to the same concept.  
Initiated from [PERSON] there have been few publications about the motion of the LSC liner, including an analytical approximation of LSCs utilizing a vector approach [2], and the development of a numerical simulation code DESCA specifically designed for LSCs applications in combination of numerical approaches and a series of analytical approximations [3].  
Analysis of the steady state liner motion of LSCs herein was motivated by the \(\alpha=\beta\) condition because it describes very well the liner motion of LSCs following detonation propagation. In this paper, a steady state equation of motion of LSCs liner will be built and compared to a numerical simulation results to evaluate the applicability.
# Runway Pavement Structural Analysis Using Remote Laser Doppler Vibrometers
## 2 Remote Laser Vibration Measurement System
### Remote Laser Doppler Vibrometer  
In practical applications, RLDV can precisely target a predetermined deflection testing position with the assistance of a high-definition camera. The optical head radiates a measuring laser with a frequency of '\(f\)' towards the testing position. Upon passing through the first polarizer (BS1), the laser is bifurcated into a measuring laser and a reference laser. The reference laser then experiences Bragg diffraction, altering the frequency to '\(f+\Delta f_{1}\)', where '\(\Delta f_{1}\)' is the modulation frequency of the acousto-optic modulator. Following its trajectory through the second polarizer (BS2), the measuring laser undergoes diffuse reflection on the vibrating surface, causing the frequency of the reflected laser to shift to '\(f+\Delta f_{2}\)', where '\(\Delta f_{2}\)' is the Doppler frequency shift instigated by the vibrating surface. Ultimately, the reflected laser interferes with the reference laser post-beam splitter (BS3), and the photodetector transmutes the optical signal into an electrical one [35]. A time-domain vibration velocity curve is derived via demodulation and integrated to obtain the measured surface displacement.  
The RLDV model used in this study is LV-RFS01, with a measuring wavelength of 1550 nm, a measuring distance of up to 100 m, and a speed resolution of 1 um/s. Figure 1 shows the Remote Laser Doppler Vibrometer and its testing principle.