esa-sceva/satcom-chunk-collection huggingface dataset:
# Numerical Analysis of Human Cancer Therapy Using Microwave Ablation
## 3 Results
### Temperature and Thermal Gradient Fields  
Temperature profile is a major characteristic relating to the effective performance of the MWA. Indeed, microwave ablation should be used as a thermal therapy for cancer tumor treatment without damaging surrounding normal tissue. For this reason, thermal study and temperature control are required.  
Figure 9 shows the contours lines of the temperature distribution in the biological tissue at \(t=300\) s for three different values of the input microwave power. It may be noted first that the contour lines of the temperature in the three cases are similar and display an ellipsoidal behavior. The temperature is very high in the vicinity of the antenna slot. Then, it drops noticeably when one moves away from the slot. The maximal temperature value is reached inside the tumor region. The maximum temperature produced by microwave power \(P_{in}=10\) W is estimated to 86 \({}^{\circ}\)C, while the maximum value obtained for \(P_{in}=45\) W is 238 \({}^{\circ}\)C, and for \(P_{in}=75\) W, the maximum temperature is 353 \({}^{\circ}\)C. We note that the temperature increases rapidly when increasing the microwave power. This increase is too high and will destroy healthy cells.  
It is also interesting to delimit the region where \(\Delta T=T-T_{b}\geq 15\)\({}^{\circ}\)C. For \(P_{in}=10\) W, this region is mainly situated inside the tumor. Hence, there is a very small risk of damaging healthy tissue. The central part of the tumor is killed, however, and the external ring is not completely treated. When \(P_{in}\) increases, the area corresponding to \(\Delta T\geq 15\)\({}^{\circ}\)C becomes larger and more extended than the tumor itself, i.e., it covers the tumor and a part of healthy tissue. Thus, the risk of destroying the tissue surrounding the tumor threatens the process. We may conclude that an input power of about 10 W is sufficient to treat a tumor which has a radius of 15 mm. The results may be extended to deduce the optimal input power required for tumors which have other extensions.  
Figure 10 exhibits the temporal evolution of the temperature for different values of the input power and for 4 positions corresponding to \(r=5\) mm, \(r=10\) mm, \(r=15\) mm, and \(r=20\) mm. \(z=20\) mm for all the positions. When the ablation duration is small, the behavior of the curves is mainly governed by the source term. For this reason, a linear increase of the temperature is observed. When the temperature reaches a certain value, the diffusion and the heat conduction due to the blood perfusion become important and lead to a counterbalancing of the source term. Thus, a saturation regime occurs. The maximal values depend on the position and the input power as mentioned above. These curves may help to assess the optimal value of the treatment time.  
Figure 8: Axial profile of specific absorption rate (SAR) at \(t=300\) s and \(r=2.5\) mm for various input powers.
# Extracellular Vesicles and Artificial Intelligence: Unique Weapons against Breast Cancer
### Extracellular Vesicles (EVs)  
EVs are very small lipid bilayer particles of a cellular origin, measuring in the order of nanometers to micrometers; they lack replicative power and express receptors that give them specificity and are produced by all three domains of Bacteria, Archaea, and Eukarya. Based on their size, the specific biomarkers expressed, and biogenesis mechanisms, they are divided into exosomes (40 to 150 nm), microvesicles (40 to 10,000 nm), and apoptotic bodies (100-5000 nm). According to the current classification, exosomes are subdivided into small and large (Exo-S, measuring 40-80 nm, and Exo-L, measuring 80-150 nm) exosomes, microvesicles are subdivided into ARMMs (arrestin domain-containing protein 1 (ARRDC1)-mediated microvesicles measuring 40-100 nm), which are distinguished from classical large microvesicles (-150-1000 nm) and large oncogenes (1-10 \(\upmu\)m), and apoptotic EVs are subdivided into apoptotic bodies (1-5 \(\upmu\)m) and apoptotic vesicles (-100-1000 nm) [14].  
EVs' cargo consists of several cell-derived components such as lipids, proteins, nuclei acids, and viral-derived particles (in case of infection), and their bilayer composition protects EVs' cargo from aspecific cytotoxicity and consequent degradation. Figure 2 shows a typical exosome structure and main cargo component.  
EVs are secreted by all cell types, both in physiological and pathological conditions, and are released by several biological fluids, such as blood, liquor, saliva, urine, milk, and others [15; 16; 17]. In the last decade, their characterization and functional studies have been implemented thanks to the use of highly technological and well-performing tools, reevaluating their importance. EVs have been identified as an alternative cell-to-cell communication strategy due to their cargo release to the receiving cell. Therefore, their contribution to homeostasis processes, tumoral context, and viral infections is well reported in the literature [18]. Thanks to their small size, ability to cross the blood-brain barrier, low toxicity, and nonimmunogenic phenotype, EVs can be engineered and directed to a specific target by the expression of particular surface structures (anchoring proteins and transmembrane), becoming valid candidates for drug delivery for precision medicine approaches.  
Figure 1: Process of the invasiveness and colonization of breast tumor cells in other organs.
## 4 Assessment Indicators
### The Phenomenon of Cavitation  
Several numerical [35] and experimental [36] studies have been carried out on the operating flows of hydraulic turbines under off-design conditions. These studies were carried out as a function of the Thoma number (Thoma's cavitation factor), and demonstrated its influence on the generation of the phenomenon of cavitation. Therefore, the Thoma number is an essential factor to be taken into account for the stable operation of a hydraulic turbine. Thoma's cavitation factor is a dimensionless number that represents the cavitation properties of a fluid and it can be calculated using Equation [37]:  
\[\sigma=\frac{H_{a}-H_{s}-H_{v}}{H} \tag{1}\]  
where \(\sigma\) is the Thoma number (_dimensionless_), \(H_{a}\) is the atmospheric pressure head (m), \(H_{v}\) is the vapor pressure of water corresponding to the water temperature (m), \(H_{s}\) is the suction head of the hydraulic turbine (m), and \(H\) is the head of the hydraulic turbine (m).  
The critical cavitation factor (\(\sigma_{c}\)) was used to evaluate the phenomenon of cavitation. Equation (2) shows an empirical relationship for the determination of the critical cavitation factor for a [PERSON] turbine [38; 39]:  
\[\sigma_{c}=1.1\cdot\left[0.28+\left[\frac{1}{7.5}\cdot\left(N_{s}/380.78 \right)\right]^{3}\right] \tag{2}\]  
where \(\sigma_{c}\) is the critical cavitation factor (_dimensionless_), and \(N_{s}\) is the specific speed of the turbine (rpm). The specific speed can be calculated as [40]:  
\[N_{s}=\frac{N\cdot\sqrt{P_{t}}}{H^{5/4}} \tag{3}\]  
where \(N\) is the speed of the turbine (rpm), \(P_{t}\) is the power output of the turbine (kW), and \(H\) is the head of the hydraulic turbine (m).  
The cavitation factor can also be determined as a function of the specific speed:  
\[\sigma=\frac{\left(0.01\cdot N_{s}-0.54\right)^{2}}{45}+0.035. \tag{4}\]  
Figure 10: Scada system supervision.  
Equation (4) can be used for specific speeds in the range 70 to 800 rpm.  
To assess this indicator, the ratio between \(\sigma\) and \(\sigma_{c}\) was used. If the value of \(\sigma\) is greater than \(\sigma_{c}\) the phenomenon of cavitation will not occur [38]:  
\[\sigma\succ\sigma_{c}. \tag{5}\]  
Therefore, decreasing the specific speed of the turbine decreases the probability of cavitation.
# Micro-Nanobubble Technology in Surface Cleaning and Defouling
## 3 Advanced Applications of NBs in Precision Surface Cleaning
### Food Industry and Pathogen Control
This study showed that CO\({}_{2}\)-MNBs can increase the antimicrobial efficiency of PAA and Cl\({}_{2}\) against pathogens in microbiological growth media, indicating that this strategy may increase the effectiveness of antimicrobials in food safety applications, which should be investigated further. Numerous sectors have seen the sophisticated use of NBs in precise surface cleaning, demonstrating their adaptability and efficiency. NBs are used in membrane cleaning to improve the performance of membranes in water treatment systems by eliminating fouling materials from membrane surfaces. Because NBs can effectively break down impurities without the need for harsh chemicals, they also provide an environmentally acceptable option for surface cleaning and contamination prevention. NBs are used in the textile sector to treat and clean fabric surfaces, enhancing quality and lessening the negative effects on the environment. NBs provide a non-invasive oral care option and have been found to be effective in dental hygiene for the elimination of plaque. NBs optimize recovery rates in flotation and mineral processing by assisting in the separation of precious minerals from ore. Finally, NBs are used in the food industry to manage pathogens, offering a more sustainable and safe way to clean food surfaces and processing machinery.
###### Abstract  
Zooplankton can be detected by using acoustic Doppler current profiler (ADCP) instruments through acquiring the mean volume backscattering strength (MVBS) data. However, the precision of the backscattered signal measured by single ADCP measurement has a limitation in the MVBS variation of zooplankton. The objectives of this study were to analyze the MVBS and vertical velocity from ADCPs at the same time and location for zooplankton's daily vertical migration (DVM) observation. Measurements were conducted in Lembeh Strait, North Sulawesi, Indonesia. Instruments used included a moored ADCP 750 kHz and a mobile ADCP 307.2 kHz. High MVBS value was found at 11.5-16 m depths and was identified as the sound scattering layer (SSL). The DVM patterns in the SSL displayed significant differences over time and had good relationships with the diurnal cycle. Theoretical target strength (TS) from the scattering models based on a distorted-wave Born approximation (DWBA) was estimated for _Oithona_ sp. and _Paracalanus_ sp.; the two dominant species found in the observed area. However, \(\Delta\)MVBS and \(\Delta\)TS proved that the dominant zooplankton species were not the main scatterers. The strong signal in SSL was instead caused by the schools of various zooplankton species.  
ADCP; distorted-wave Born approximation (DWBA); diel vertical migration (DVM); mean volume backscattering strength (MVBS); target strength (TS); zooplankton
# Improving the Robustness of DTW to Global Time Warping Conditions in Audio Synchronization
## 2 Materials and Methods
### Different Transitions and Weights  
One obvious way to deal with global time warping is to simply select a set of allowable transitions to explicitly handle a specified amount of time warping. This is a design decision that must be made whenever DTW is invoked. For example, the transition set \(\{(1,1),(0,1),(1,0)\}\) can theoretically handle an infinite amount of time warp. In practice, however, these transitions often lead to degenerate alignments and unstable or undesirable behavior. A more conservative way to handle global time warping is use transitions like \((2,1)\) and \((3,1)\), which limit the maximum amount of time warping that can be handled. A commonly used set of transitions in the audio synchronization literature is \(\{(1,1),\)\((1,2),\)\((2,1)\}\), which imposes a maximum allowable time warp factor of 2. In a similar manner, the set of transitions \(\{(1,1),\)\((1,2),\)\((2,1),\)\((1,3),\)\((3,1)\}\) imposes a maximum allowable time warp factor of 3, and the set \(\{(1,1),\)\((1,2),\)\((2,1),\)\((1,3),\)\((3,1),\)\((1,4),\)\((4,1)\}\) imposes a maximum allowable time warp factor of 4. These additional transitions come with a significant computational cost, however, since each step of the dynamic programming stage needs to consider every possible transition (cf. Equation (2)). In Sections 3 and 4, we will compare both the alignment accuracy and the runtime of several different settings for transition types and weights.
## 3 Results and Discussion
### Determination of Total Polyphenol Content (TPC)  
The TPC results were given in milligrams of gallic acid equivalent per gram of extract. Figure 1 shows that TPC in the P1E, P2E, and P3E is 29.38 \(\pm\) 1.570, 26.15 \(\pm\) 0.823, and 37.33 \(\pm\) 1.307 mg GAE/g, respectively. The TPC value in the P3E sample is high compared to the P1E and P12 samples, and this difference between the values is significant (_p_ < 0.05). Comparing our values obtained of TPC from three studied samples with the results of previous researches, the obtained values of TPC in the three extracts are higher than those of the fresh petals' hydroethanolic extract and the basal leaves' methanolic extract, at 14.30 mg GAE/g of fresh petals and 25.86 mg GAE/g of extract, respectively [41; 42]. Additionally, our obtained TPC values in whole plant extracts of three samples are higher than those obtained in hydroethanolic extracts of four organs of _P. rhoas_: flower, leaf, stem, and root, at 22.10, 24.24, 10.58, and 10.22 mg GAE/g, respectively [33]. In addition, the TPC in the dried pollen extract of our study plant is approximately similar to our values obtained at 34.8 mg GAE/g [43]. The most abundant metabolites detected in the Papaveraceae family are alkaloids. (+)-rhoedaine was found to be the most abundant alkaloid isolated from the aerial portions of _P. rhoas_. Allocryptope, berberine, protopine, coptisine, coulteropine, (\(-\))-sinactine, (+)-isocorydine, samgunarine, (+)-rhoedaine, and (+)-roemerine were the minor alkaloids [44]. These alkaloids, particularly those of the isoquinoline type, are the most significant in terms of pharmacology [45; 46]. The antioxidant [47; 48; 49] and antimicrobial [50] properties of Papaver alkaloids are well established.
## 1 Introduction
[PERSON] and [PERSON] [27] investigated the HT effects of various fin geometries--square, circular, rectangular, and elliptical--arranged in a circular pattern under a single impingement jet with identical wetted surface areas. Elliptical fins provided the best cooling performance on roughened surfaces as they created weaker recirculation zones and achieved higher velocities around the fins. Both numerical and experimental results showed that elliptical fins significantly reduced local temperatures in the impingement and wall jet regions. Consequently, the area-averaged Nu improved by 47-54% compared to a flat surface. [PERSON] et al. [28] investigated the effects of microfin height and geometry (rectangular and pentagonal) on HT in jet impingement cooling. They found that fin height is a critical parameter in enhancing HT, while the pressure drop remained nearly identical to that of a smooth, flat surface. [PERSON] et al. [29] investigated the combined use of water jets and conical surface modifications for cooling power electronics in automotive applications. Despite only a 1-3% increase in the HT area, they observed a decrease of 3.5-7.5% in the average surface temperature rise. They concluded that conical surface modifications could be effective in achievinguniform surface temperatures, potentially improving device performance and extending operational lifespan. [PERSON] and [PERSON] [30] reported that, in multi-jet impingement cooling, a target surface with hemispherical dimples demonstrated 5-10% greater HT efficiency compared to a smooth surface. In this study, the effective parameters of the heat transfer of the heat sink, which was previously optimized using the Taguchi optimization method, were investigated according to the single variable method. The effects of varying heat sink angles, nozzle diameter, h/d ratio, and velocity under constant heat flux conditions were analyzed for the optimized heat sink. Considering the importance of analyzing the effect of the heat sink angle, nozzle diameter, dimensionless distance, and flow rate variables on the heat transfer performance of jet impingement systems, this study aims to provide scientifically proven answers to the industry. In the field of cooling applications with impinging jets, it is thought that the analyses made using the geometry of longitudinally and laterally arranged fin pairs, which are rarely encountered in studies, will contribute to the literature and industrial applications. When the parameters affecting impingement jet cooling are examined, the analyses performed according to the single variable method will provide new perspectives for the optimization of jet impingement cooling systems and offer potential improvements in thermal performance and efficiency.
# Enhancing IoT Data Dependability through a Blockchain Mirror Model
## 3 The Mirror Model
### The Mirror  
A \"mirror\" is an asset in the Trust domain to be associated to an object in the Representation domain. The association between an object, \(o\), and a \"mirror\", \(a\), is accomplished as a function:  
\[m:R\to T\] \[m(o)\equiv a:T\text{-}o.id=a.id\wedge\]  
where \(P(o,a)\) is a predicate, that is a function whose signature is:  
\[P:T\times R\to B\]  
Figure 1: Mirror Model domains.  
where \(B\) is the Boolean set whose values are True and False.  
It is supposed that any object or asset is uniquely identified by an \"_id_\" that is expressed with the syntax \(o.id\) (_a.id_ in the case of an asset).  
The Trust domain, \(T\), is immutable in that it complies with the following invariant:  
\[\forall\ a:T\text{-}G(a=a)\]  
where \(G\) is the temporal operator \"always\" [18; 19]. This invariant simply states the fact that \(T\) is the domain whose assets never change (assets are always equal to themselves), i.e., they are immutable. (The Trust domain, i.e., the blockchain domain, has many other properties besides the immutability of assets. For instance, in a blockchain an asset may be not modified without the consensus of endorsing parties, but this and other properties are not functional to the present argumentation and their formalization is beyond the scope of this paper.) An identifier is supposed to be unique within the whole domain; something that resembles a Uniform Resource Identifier (URI) or a Digital Object Identifier (DOI).  
The mirror function, \(m()\), given an object, \(o\), in \(R\), selects a corresponding and unique asset in \(T\), where object and asset have the same \"ids\" and a generic predicate \(P()\) is satisfied for both the object and the asset. The function of the predicate in the mirror model is to add flexibility and to avoid objects and corresponding assets that are forced to share the same identical structure and contents. Of course, the trivial identity predicate stating \(o=a\) is admitted and possible but, in general, objects and corresponding mirror assets possess different structure and contents.  
_Example: Let consider an object that represents a real-world thermostat. Its structure could be as follows:_  
_Thermostat::=_  
_id: N;_  
_brand: String;_  
_manual: Bit_ *  
_status: [\"on\", \"off\"]_  
An instance of the thermostat could be:  
_thermo = id 35, brand \"Nest\", manual <0011000... >, status \"on\"]._  
A corresponding valid asset could be:  
_a_thermo = [id 35, hash_manual <1753223>]._  
In this case the structure of the asset could be:  
_ATThermostat::=_  
_id: N;_  
_hash_manual: [01]_.[9]*._  
Given the fact that the basic condition is satisfied, i.e., _thermo.id = a_thermo.id_, the validating predicate could be as follows:  
\[P(o\_a)=hash(o.manual)=a.hash\_manual.\]  
In other words, the asset stores the _hash()_ of the manual. This is the practice in structuring the ledger of a blockchain, particularly when the original object is described using a large amount of information such as a document or an image.
## 4 Design Methodology of Composite-Anchor Uplift Piles  
Previous research has demonstrated the enhanced load-bearing capacity and deformation resistance of composite-anchor piles compared to traditional piles. Additionally, composite-anchor piles exhibit substantial improvements in corrosion resistance, economic performance, and bottom plate waterproofing capabilities. These advantages align with the design objectives of achieving low reinforcement ratios and high bearing capacities. Composite-anchor piles can be directly substituted for traditional piles and are particularly suitable for projects with strict time constraints. This study serves as a valuable demonstration for the future adoption and promotion of composite-anchor piles. To facilitate their application and promotion, it is essential to investigate their design methodologies.  
In the design process for determining the bearing capacity of uplift piles, traditional friction uplift piles only require verification of conditions where the pile's bearing capacity is governed by the soil's frictional resistance on the pile side. However, composite-anchor piles possess a unique composite-anchor cable structure. Through previous experiments and numerical simulations on factors influencing the bearing capacity, it has been established that the calculation of uplift bearing capacity for composite-anchor piles must consider the interface frictional resistance within the composite-anchor cable inside the pile. Consequently, a formula is proposed in this study to calculate the bearing capacity of uplift piles controlled by the interface frictional resistance of the composite-anchor cable inside the pile. Moreover, based on numerical simulation results, parameters such as the number of anchor cables are integrated into the formula design process. Furthermore, previous research findings indicate that composite-anchor piles exhibit superior bearing characteristics compared to conventional piles of the same size. Consequently, the dimension design of the pile shaft can be based on conventional piles, ensuring conservative results that contribute significantly to the safety and deformation control of the structure. Considering these factors, this paper recommends utilizing conventional pile design methods when determining the number and dimensions of composite-anchor piles. The design characteristic value of the bearing capacity of composite-anchor piles can be initially estimated by summing the ultimate lateral frictional resistance of each soil layer. The specific formula design process is outlined as follows.
## 3 System Design and Methods
### Network Architecture Design
#### 3.1.3 Distribution Alignment
At the initial stage, the untrained classification network makes random guesses for unlabeled data, thus the minimization of conditional distributions distance takes little effect. As the iteration proceeds, the accuracy of the classification network will improve for unlabeled samples, thus boosting the minimization of conditional distributions. This is why choosing the soft labeling scheme is better than hard labeling. Furthermore, we can introduce a weight for the soft labels, and the weight increases with the iteration procedure, i.e., \(w_{r}=\frac{r}{R}\), where \(R\) is the total number of iteration stage and \(r\) is the current stage number. Introducing the soft labeling and iteration weight for conditional distribution distance, the MMD over classes can be rewritten as  
\[Q_{c}\left[\tilde{\mathbf{X}}_{s},\tilde{\mathbf{X}}_{t}\right]=\sum_{k=1}^{C} \left\|\frac{1}{n_{s}^{k}}\sum_{i=1}^{n_{s}^{k}}\tilde{\mathbf{x}}_{k,i}^{s}- \frac{\sum_{i=1}^{n_{s}^{k}}\tilde{\mathbf{x}}_{k,i}^{l}+\sum_{i=1}^{n_{u}}w_{r }\hat{y}_{k,i}^{u}\tilde{\mathbf{x}}_{i}^{u}}{n_{t}^{k}+\sum_{i=1}^{n_{s}}w_{r }\hat{y}_{k,i}^{u}}\right\|^{2}. \tag{14}\]