esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Second Messengers in Cyanobacteria
### Cyclic Adenosine 3',5'-Monophosphate, cAMP
#### 2.3.1 Cyclic AMP Regulates Motility Under Blue, Red, and Far Red Light  
Cyclic AMP was initially recognized for its importance in controlling motility. In the filamentous cyanobacterium _Spirulina platensis_, external cAMP supplementation stimulated gliding motility and algal mat formation [63]. A _Synechocystis_ mutant lacking the AC gene _cyan1_ exhibited lower intracellular levels of cAMP and did not exhibit movement on agar plates under standard white light growth conditions [64]. Further studies showed the blue light significantly and rapidly increased intracellular cAMP levels in _Synechocystis_ compared to red or far red light [65]. Motility was enhanced by blue light in a fluence- and \(\mathrm{Cya1}\)-dependent manner [65], indicating that a blue-light dependent photoreceptor was involved in the regulation of \(\mathrm{Cya1}\) during this process.  
Intracellular levels of cAMP are regulated by light in several cyanobacteria. Similar to _Synechocystis_, blue light serves as a crucial signal for cAMP regulation in _Microcodeus chthonoplastes_ PCC 7420. A protein encoding a blue light-responsive LOV (light, oxygen, voltage) domain with an associated AC domain supported increased synthesis of cAMP _in vitro_ upon exposure to blue light [66]. Whereas, blue light increases cAMP levels in _Synechocystis_ and _M. chthonoplastes_, _Anabaena cylindrica_ exhibits reversible red light-mediated reductions in cAMP levels and far-red light-induced increases in cAMP content [67]. Similarly, in _Anabaena_, red light decreased intracellular levels of cAMP, and far-red light levels increased cellular cAMP content [68]. Together, these findings suggest photoreceptor regulation of cAMP levels. Indeed, a mutant lacking a functional _aphC_ gene, which encodes a phytochrome histidine kinase-like protein, did not exhibit FR-induced accumulation of cAMP [68]. In its photoregulation of intracellular cAMP levels, AphC purportedly phosphorylates and activates the AC CyaC, thereby inducing cAMP synthesis [68].
# A Quad-Band Highly Selective Frequency Selective Surface with Ultra-Wideband Rejection
## 4 Conclusions  
A highly selective quad-band FSS in C/X/Ku bands is proposed in this paper. ECM and full-wave simulation results indicated that the proposed FSS has a transmission response and out-of-band suppression performance. This design achieved a quad-band passband FSS with -20 dB out-of-band suppression in 1-5.5 GHz and 14-40 GHz. Additionally, the measured results are consistent with the simulated ones under an oblique angle for both TE and TM polarizations. The proposed highly selective quad-band FSS could be used for reducing the out-of-band RCS of narrowband antennas.  
Conceptualization, M.W. and Y.L.; methodology, M.W.; software, M.W.; validation, M.W.; formal analysis, M.W.; investigation, B.X.; writing--original draft preparation, M.W.; writing--review and editing, L.Y.; visualization, Y.L. and B.X.; supervision, Z.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded in part by the National Funded Postdoctoral Researchers Program of China, grant number GZC20232050.  
Data are contained within the article.  
The authors declare no conflict of interest.
# Data Fusion in Agriculture: Resolving Ambiguities and Closing Data Gaps
## 2 Literature Review
### Proximal Scale  
The majority of studies dedicated to the proximal scale are concentrated in three main areas: prediction of soil properties, delineation of homogeneous zones, and robotic navigation and control. Applications, such as disease and fruit detection, prediction of water content and water stress, estimation of phonological state and yield prediction, are also present. Ten of the references also explored satellite data, and five studies combined proximal and aerial data. Data sources included cameras (RGB, multispectral, thermal, hyperspectral) spectrometers, conductance and resistivity sensors, GPS, inertial sensors, weather data, among many others. With such a variety of sensors available for field applications, efforts to explore their complementarities have been steadily growing (Table 3), but most problems still lack reliable solutions [73].
## 5 Conclusions  
The influence of induced magnetic field on nanofluid motion and forced convection between two vertical permeable plates is investigated. To solve coupled equations, Runge-Kutta method is utilized. The influence of different dimensionless parameters on induced magnetic field, velocity and temperature distributions are considered. Results illustrate that current density augments with a rise of volume fraction of nanofluid and Hartmann and magnetic Prandtl numbers, while it is reduced with a rise in the suction parameter. As Lorentz force increases, velocity and induced magnetic field are reduced and maximum velocity point shifts to the left side.  
**Acknowledgments: [PERSON] is grateful to [PERSON], Dean Faculty of Science and [PERSON], Chairman Mathematics Department, Taibah University, Madinah Munawwarah, Saudi Arabia for their kind cooperation. [PERSON] is also thankful to PCST to honed him with 7 th top most Productive Scientist Award in category A and Thomson Reuters to rank him among top 1% highly cited researchers on Web of Science in 2015-2016.**  
**Author Contributions: This paper is contributed in all respect by [PERSON], [PERSON] and [PERSON] equally.**  
Figure 8: Influence of nanofluid volume fraction (\(\phi\)) and suction parameter (\(V_{0}\)) on Nusselt number (Nu) when \(Ha=5,\;Pm=1,\;\Pr=6.8\).  
**Conflicts of Interest:** The authors declare no conflict of interest.  
**Nomenclature**  
\(B\): Dimensionless induced horizontal magnetic field  
\(\stackrel{{\rightarrow}}{{\mathcal{D}}}\): Velocity vector  
\(\stackrel{{\rightarrow}}{{b}}\): Vector of magnetic field  
\(k\): Thermal conductivity  
\(c_{p}\): Specific heat  
\(I\): Induced current density  
\(T\): Temperature  
\(Ha\): Hartmann number  
\(V_{0}\): Suction parameter  
\(Pm\): Magnetic Prandtl number  
\(U\): Dimensionless horizontal velocity  
**Greek Symbols**  
\(\eta\): Dimensionless distance  
\(\beta\): Coefficient of thermal expansion  
\(\sigma\): Electrical conductivity  
\(\mu\): Dynamic viscosity of nanofluid  
\(\theta\): Dimensionless temperature  
\(\phi\): Nanofluid volume fraction  
\(\rho\): Density  
**Subscripts**  
\(p\): Solid  
\(f\): Base fluid
## 1 Introduction
### An International Comparison of X-Band SAR Data for Rice Mapping  
The RIICE project--Remote sensing-based Information and Insurance for Crops in Emerging economies--tested SAR-based mapping of rice area across six countries (India, Thailand, Cambodia, Vietnam, Indonesia and the Philippines) between late 2012 and early 2014 (Figure 2). These countries account for 51.5% of the world's rice area and 45.9% of production, and they include both rice net  
Figure 1: Rice crop stages. Image from the International Rice Research Institute (IRRI)-Rice Knowledge Bank.  
exporters (Thailand, Vietnam, India and Cambodia) and rice net importers (Indonesia and the Philippines) [2]. These countries are representative of the wide range of geographies, climates and crop practices in subtropical and tropical Asian rice systems.  
This international collaborative effort used multi-temporal X-band SAR data, semi-automated processing chains, in-season field monitoring and end-of-season validation points to map rice crops across technical demonstrations in six countries (Figure 1). This study uses a greater number of images (127) and number of sites (13) and covers a larger area (4.78 m ha) than any previous assessment of SAR-based remote sensing for rice mapping (Table 1). It is a timely contribution to the literature on the use of SAR for large-scale mapping of rice in Asia for food security applications.  
The following sections describe the sites, data, methods and results. The discussion section includes our observations on the strengths and weaknesses of this approach and the challenges faced in conducting the research. We also suggest some criteria and prerequisites for developing SAR acquisition plans that would ensure that remote sensing supports policies for food security, import/export decisions and price stabilization for the world's most important crop.  
Figure 2: Location of the 13 SAR footprints in Asia in the RIICE (Remote Sensing-based Information and Insurance for Crops in Emerging economies) project. Country names are shown only where there are footprints. Numbers refer to the site ID used in Table 1.
## 3 Numerical Analysis  
### Modeling Methodology  
A finite element model was developed using the commercial package ABAQUS 6.21 software. Arc-shaped washers were placed at the supports and the loading point to mitigate the effect of stress concentration. Concrete and steel plates were modeled using C3D8R [39] (a general-purpose linear brick element, with a reduced integration three-dimensional solid element), while the CFRP rods and GFR spirals were modeled using T3D2 [39] (two-node linear displacement three-dimensional wire element). The material properties listed in Table 1 were adopted in the FE model.  
Tie constraints were adopted on the surface between the washers and the concrete. A full bond between the FRP and concrete was assumed and the embedded constraints were adopted. The mesh density gradually decreased from the mid-span to the ends. Concrete was simulated using a damage plasticity model, with constitutive models and material properties input based on material tests. The FRPs were simulated using a linear elastic model. Before applying external loads, prestressing was applied using the temperature method. For the temperature method, a thermal coefficient of CFRP was defined and prestressing force was applied by imposing a temperature decrease. The bending load was applied after the prestressing step. The finite element model is shown in Figure 10.  
There were three meshing sizes for the concrete: 30 mm between the loading points; 60 mm between the loading point and the support; and 100 mm for the cantilever part. The meshing size of the CFRP was 50 mm.  
Figure 10: Finite element model.  
The analysis ended when either the compressive strain on the concrete exceeded 0.003 or the CFRP stress exceeded 2892 MPa. The corresponding load was taken as the ultimate load of the pile.
## 4 Influence of Dataset Features
### Influence of Sequencing Quality  
Our experiments show that for the three lengths of k-mer CHTKC is more sensitive to sequencing quality than KMC3 (Figure 5(a)). When the dataset has poor sequencing quality, sequencing errors dramatically increase the number of distinct k-mers. The k-mers generated by sequencing errors are low-frequency and random. For CHTKC, these k-mers can exhaust the pre-allocated hash table very soon. Afterward, the algorithm must save the following k-mers to disk, which may cause multiple batches of swaps between memory and disk, resulting in longer running time. Therefore, we can conclude that CHTKC as an NPBKMC algorithm is sensitive to the number of distinct k-mers.  
Compared with the NPBKMC algorithm, KMC3 as a PBKMC algorithm is not so sensitive to the number of distinct k-mers, which gives it a significant advantage over the  
Figure 6: Comparison of KMC3 and CHTKC with various sequencing errors. (**a**) running time; (**b**) cache reference.  
NPBKMC algorithm when dealing with frequency counting tasks of datasets with long k-mers and relatively low sequencing quality. Furthermore, the memory access of KMC3 relates to the number of total k-mers and does not linearly correlate with the number of distinct k-mers (Figure 6b). Nevertheless, the decrease in file size also decreases the time consumption of reading the Gzipped file, and KMC3 can also benefit from the decreasing of Gzipped file size with the improvement of sequencing quality, leading to less time consumption in the partition stage (Supplementary Table S7).
# Vibration Parameters Identification of Rotating Blades Based on Blade Tip-Timing Sensor Waveforms
## 5 Conclusions
When the SNR is constant, with the increase of the number of sensors, the accurately identified initial excitation order gradually becomes smaller, and the relative error of vibration amplitude, relative error of constant offset and relative error of initial phase are all smaller, i.e., there is higher identification accuracy. When the SNR is 90 db, 60 db and 50 db, respectively, single-sensor, double-sensor and three-sensor waveform matching methods can accurately identify all excitation orders. This research result indicates that increasing the number of sensors can improve the identification accuracy of the excitation order and other vibration parameters by the waveform matching method under the condition of low SNR;
4. Compared with the classical blade tip-timing method, the waveform mapping method can not only reduce the number of tip-timing sensors used but also improve the identification accuracy of the blade-synchronous vibration parameters. The vibration frequency identification accuracy of the waveform mapping method is higher than that of the waveform method in reference. Conceptualization, L.Z. ; methodology L.Z. ; software, Q.W. ; validation, L.Z. ; formal analysis, Q.W. ; investigation, X.L. ; data curation, Q.W. ; writing-original draft preparation, L.Z. ; writing-review and editing, L.Z., Q.W. and X.L. ; visualization, X.L. ; supervision, L.Z. ; project administration, L.Z. All authors have read and agreed to the published version of the manuscript. The work is supported by National Natural Science Foundation of China (Grant no. 51505206), Liaoning Province Applied Basic Research Program Project (Grant no. 2023)H2/101300227), Key Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, Northeastern University (Grant no. VCAME202211), Liaoning Provincial Natural Science Foundation Guidance Program Project (Grant no. 2019-ZD-0694), Liaoning Provincial Department of Education Scientific Research General Project (Grant no. L2014246) and Liaoning University of Technology Teacher Research Start Fund Project (Grant no.X201202). Not applicable. Data Availability Statement: The data used to support the findings of this paper are available from the corresponding author upon request. The authors declared no conflict of interest.
# Smart Manufacturing Application in Precision Manufacturing
## 6 Outlook on Future Work
### Connectivity Stage  
As more data are generated from machines, connectivity, maintenance, and diagnostics will become more important to the sustainability of production lines; therefore, proactive maintenance management applications will be required as they can further improve machines' utilization through the better management of unplanned downtime events such as machine failures, which further reduce downtime waste.  
Such generated data are becoming the gold standard for OEMs because they can use them to optimize machine performance and their maintenance services. However, as big data grow, it becomes challenging for SMEs to maintain data storage as well as the IT infrastructure. SMEs can consider moving machine condition monitoring systems to the cloud through the software as a service (SaaS) model to overcome such data and system management challenges to mitigate the risks related to system maintenance, data security,and historical data loss. Furthermore, SaaS solutions in collaboration with OEMs are a good way forward to improve the maintenance services provided by the OEM, because such services reduce the challenges faced by SMEs and provide an additional revenue stream for OEMs by providing additional customer service. For example, the Mazak iConnect and Smart Cloud is an online connectivity and cloud service solution that provides highly secure connectivity and condition monitoring solutions for CNC machines [37]. This removes the burden of managing condition monitoring applications (i.e., Smooth Monitor AX) that are implemented in the connectivity stage, which can be hosted and managed in the cloud by the OEM. It can also include additional services provided by the OEM such as spindle performance diagnostics and machine diagnostics based on AI for predictive maintenance management. This SaaS cloud architecture is currently being piloted with Mazak as a part of the further optimization of the connectivity stage.
## 5 Conclusions/Outlook  
The greatest difficulty in the design of phased array radars (PARs) used as sensors in a rocket tracking system (RTS) is the modeling step. It is a complex optimization problem due to the large number of possible solutions. In order to assist the design of PARs, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) optimization method was developed and tested. This method is used to optimize the electronic control of radiation pattern in phased arrays (PAs) and has a reconfigurable, multi-objective and with differentiated real coding GA, inspired by the physical structure of the array, in order to  
introduces the new genetic operator Maximum-Minimum Crossover (MMC), which has a different approach from conventional ones, because it performs crossover of the fittest individuals with the least fit individuals and, thereby, provides a better optimization in Pas' vast search space problems (around 10\({}^{20}\) possibilities for the situations tested in this paper). This made it possible to increase the final population fitness by more than 20% and reduce processing time.  
To test the method, common applications in radars were used, aiming at positioning the main lobe tilt, reducing the sidelobes level and directing nulls of the radiation pattern in the direction of arrival of interfering signals (e.g., jammers). Test results validated the GA-MMC, since operating conditions were met in more than 90% of the tests total in each proposed application. Hence, it was possible to obtain correct tilt angles and nulls, besides small sidelobes (30.2 dB \(\leq\) RSLL \(\leq\) 34.7 dB, for first application, and 22.2 dB \(\leq\) RSLL \(\leq\) 29.6 dB, for second application) and high values of nulls (55.1 dB \(\leq\) SIR \(\leq\) 77.0 dB). GA-MMC is also generic and reconfigurable for other applications, requiring only the need to inform new input parameters and/or the new objective function. Therefore, one promising outlook is to use GA-MMC in the design of PAs in a radar sensors network, in order to create a rocket tracking system (RTS) composed of phased array radars (PARs), for tracking soon after launch, and parabolic reflectors radars (PRRs), for tracking over long distances.  
The authors acknowledge the support provided by the Brazilian Air Force (FAB, For q A e a Brasileira), the Federal University of Rio Grande do Norte (UFRN, the Universidade Federal do Rio Grande do Norte), the Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES, the Coordena c o de Aperfei opamento de Pessoal de N  v el Superior) and the Brazilian National Counsel of Technological and Scientific Development (CNPq, Conselho Nacional de Desenvolvimento Cient fico e Tecnol  gico).
## 3 Results and Discussion
### Stage 2
#### 3.2.3 Correlations and Empirical Models
From a technological point of view, the introduction of doses of SCO\({}_{2}\) that are too high to the mass of processed AGS may cause a decrease in the pH of the biomass, which implies technological problems related to the activity of methanogenic microorganisms [10; 28]. Although little information has appeared in the world literature so far on the feasibility of low-temperature sludge conditioning with SCO\({}_{2}\), it seems that there is no doubt that it is an environmentally friendly approach, especially since SCO\({}_{2}\) can be recovered by upgrading biogas. The method also avoids secondary pollution, often introduced by chemical breakdown, and the additional energy input required for mechanical processing. It can also be included in the closed CO\({}_{2}\) cycle of biogas production--biogas upgrading--SCO\({}_{2}\) production--sludge disintegration--fermentation--biogas production, which is a significant advantage in terms of environmental protection [26]. This new approach to the production and use of SCO\({}_{2}\) largely counteracts the existing limitations, which are mainly related to the low profitability of the production process. The use of SCO\({}_{2}\) to treat sludge may prove to be an increasingly attractive alternative to other methods, given the current emphasis on the circular economy and the reduction of CO\({}_{2}\) emissions.
## 4 Evaluation of Application Potential of Supercritical Technology in Offshore Heavy Oil Reservoirs
### Development and Application Potential Evaluation Based on Different Evaluation Methods  
Based on the comparison of steam huff and pressure drop of supercritical fluid after different reservoir types and different reservoir fluid parameters, combined with the simple evaluation economic model, the screening criteria of supercritical thermal fluid application after temperature drop and pressure drop under different reservoir types and different engineering models are given (Table 19).  
Through the cumulative oil production evaluation method, cumulative increased oil production evaluation method, and adaptive screening criteria method, the three methods were integrated. A total of 6 oil fields with the most application potential were selected, respectively:  
1. LD 21-2 IV oil group;
2. PL 19-3 11/13 area;
3. KL 10-2;
4. QHD 27-3;
5. KL 16-1 2 well area;
6. LD 21-2 V oil group.  
The total proved reserves are 96 million tons, of which the single sand-body reservoir is the main reservoir, accounting for 84% of the reserves.
# Statistical and Clustering Analysis of Safety Profiles of FDA-Approved Protein Kinase Inhibitors
## 2 Materials and Methods
### Control Group Dataset  
Cortellis, a Clarivate database [21], was queried in June 2023 for drugs approved in the USA, based on the therapeutic area. This database was chosen for regulatory intelligence as it covers information from more than 75 countries and provides easy and customized searches for drugs, targets and therapeutic areas. The therapeutic areas of immunology and oncology were excluded, despite the fact that most protein kinase inhibitors are primarily indicated for conditions in these areas. Immunology and oncology treatments often involve multiple concurrent therapies (such as immune checkpoint inhibitors, chemotherapy, or corticosteroids), which can make it challenging to isolate safety signals specific to PKIs. Therefore, we decided to remove the drugs from these therapeutic areas to minimize noise.  
The query was performed in the following therapeutic areas: cardiovascular, dermatological, endocrine/metabolic, gastrointestinal, genitourinary/sexual dysfunctions, hematological, infectious, inflammatory, musculoskeletal, neurology/psychiatry, ocular, respiratory, toxicity/intoxication, other and unknown. This primary search was further refined. Drugs or combinations of drugs were subsequently excluded on the following criteria:  
1. Had secondary indications in the therapeutic areas of oncology or immunology.
2. Were combinations of drugs.
3. Were vaccines, contrast agents or used as diagnostic methods.
4. Were blood components, anticlotting factors, or organ grafts.
5. Were products used for parenteral nutrition or are vegetable products.  
Further data processing was performed to have a single active substance described only once.  
Figure 1: Study design.  
Eight hundred thirty (830) unique lines were obtained. The number of drugs in the control set was determined through a power analysis using [PERSON]'s method, with an effect size (d) of 0.5 and a desired power of 90%. A total of 145 drugs were randomly selected for analysis.