esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Discussion
Moreover, the amount of lipid peak resonating at 1.3 ppm was used to discriminate the clear cell from non-clear cell RCC histologic subtypes [19]. The spectral signature was also suggested to differentiate the grade of RCC [22]. In a recent study, the renal triglyceride spectrum in type 2 Diabetes Mellitus patients was used to assess glycemic control influences [40]. This infers the possibility of using MR spectroscopy to evaluate glucose-lowering treatments. Additionally, other metabolites such as choline and lactate can be detected by MRS/I techniques that are inaccessible to available imaging techniques. The choline peak detection in malignant renal tissues has been demonstrated in previous MRS studies and approved by histology [20]. The lactate peak was observed in patients with a tumor at an advanced stage, promoting it as a staging biomarker [22]. These peaks were not reported in this work, as the study was performed with healthy volunteers. However, if MRS has already detected choline and lactate signals, there are no reasons to expect that MRSI will not detect these metabolites. The only difference between the MRS and MRSI will be the ability to generate maps for each individual detected peak. In terms of the accuracy of MRS methods, a recent study showed a high correlation between the quantified renal triglyceride content measured by 1H-MRS and the biopsy [9]. In a previous study, we performed a phantom study to evaluate the accuracy of our proposed MRSI and compared its results to a Dixon method, and a higher MRSI quantification accuracy was found [27]. The proposed MRSI method was able to detect the important lipid peaks that were used as biomarkers in previous MRS studies and are detectable in healthy subjects. Since the main goal of this study was to evaluate the feasibility of our proposed accelerated DW-CRT MRSI technique and its reliability for scanning kidneys, we preferred to conduct the study with healthy volunteers. In the future, we hope to use the proposed methods to assess the wide variety of renal abnormalities.
# Behavior of Fiber-Reinforced and Lime-Stabilized Clayey Soil in Triaxial Tests
###### Abstract  
The beneficial role of combining fiber reinforcement with lime stabilization in altering soil behavior has been established in the literature. However, the coupling effect of their combination still remains unclear in terms of its magnitude and microscopic mechanism, especially for natural fibers with special microstructures. The objective of this study was to investigate the coupling effect of wheat straw fiber reinforcement and lime stabilization on the mechanical behavior of Hefei clayey soil. To achieve this, an experimental program including unconsolidated-undrained (UU) triaxial tests and SEM analysis was implemented. Static compaction test samples were prepared on untreated soil, fiber-reinforced soil, lime-stabilized soil, and lime-stabilized/fiber-reinforced soil at optimum moisture content with determining of the maximum dry density of the untreated soil. The lime was added in three different contents of 2%, 4%, and 6%, and 13 mm long wheat straw fiber slices with a cross section one-quarter that of the intact ones were mixed in at 0.2%, 0.4%, and 0.6% by dry weight of soil. Analysis of the derived results indicated that the addition of a small amount of wheat straw fibers into lime-stabilized soil improved the intensity of the strain-softening behavior associated with mere lime stabilization. The observed evidence that the shear strength increase brought by a combination of 0.4% fiber reinforcement and 4% lime stabilization was smaller than the summation of the shear strength increases brought by their presence alone in a sample demonstrated a coupling effect between fiber reinforcement and lime stabilization. This coupling effect was also detected in the comparisons of the secant modulus and failure pattern between the combined treatment and the individual treatments. These manifestations of the coupling effect were explained by a microscopic mechanism wherein the fiber reinforcing effect was made more effective by the ways in which lime chemically stabilized the soil and lime stabilization development was quickened by the water channels passing through the surfaces and honeycomb pores of the wheat straw fibers.  
coupling effect; fiber reinforcement; clayey; triaxial compression; combined treatment Article
# Transmission Performance Analysis of RV Reducers Influenced by Profile Modification and Load
###### Abstract  
RV reducers contain multi-tooth contact characteristics, with high-impact resistance and a small backlash, and are widely used in precision transmissions, such as robot joints. The main parameters affecting the transmission performance include torsional stiffness and transmission errors (TEs). However, a cycloid tooth profile modification has a significant influence on the transmission accuracy and torsional stiffness of an RV reducer. It is important to study the multi-tooth contact characteristics caused by modifying the cycloid profile. The contact force is calculated using a single contact stiffness, inevitably affecting the accuracy of the result. Thus, a new multi-tooth contact model and a TE model of an RV reducer are proposed by dividing the contact area into several differential elements. A comparison of the contact force obtained using the finite element method and the test results of an RV reducer prototype validates the proposed models. On this basis, the influence of load on the different modification methods is studied, including a TE, the mechanical performance, and the transmission efficiency. In addition, the proposed reverse profile is particularly suitable for situations with a large clearance and torque. This study provides a reliable theoretical basis for a multi-tooth contact analysis of a cycloid profile modification.  
RV reducer; contact dynamics; transmission errors; cycloid mechanism +
Footnote †: journal: Applied Physics Letters
# Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method
## 2 Related Work
### CNN and Transformer  
Convolutional Neural Networks (CNNs), such as AlexNet, VGG, ResNet, and DenseNet, have historically excelled in computer vision tasks. Models pre-trained on ImageNet using these architectures have been successfully applied to various computer vision tasks through transfer learning. On the other hand, in recent years, Transformers have gained prominence in natural language processing (NLP) due to their self-attention mechanism. Transformers have gained great attention in the field of computer vision and have gradually been applied to target detection [24], image segmentation [25], and other vision fields. ViT (Vision Transformer) [26], as the first pure Transformer, proved that the reliance on CNN is not necessary in the field of computer vision, and it outperformed classical CNN networks in many tasks. Swin Transformer [27] used a hierarchical construction approach to build a Transformer based on ViT. It introduced the locality idea to substantially re-duce computational complexity, and ViT improved the Transformer's capability as a general-purpose vision backbone network. [PERSON] et al. [28] proposed a Mutual Attention Weight Selection (MAWS) module on the VIT architecture, which can effectively select differentiated image blocks without introducing additional parameters and thus aggregate the important marks of each Transformer layer, to compensate for low- and intermediate-level information. [PERSON] et al. [29] presented the Recurrent AttentionMulti-scale Transformer (Rams-trans), which uses the Transformer's self-attention to learn discriminative regional attention recursively in a multi-scale manner. It is evident that combining Transformer architecture with attention mechanisms is an effective approach for addressing fine-grained tasks. [PERSON] et al. [30] built a ConvNeXt with a pure convolutional backbone network that outperformed Swin Transformer in several tasks by analyzing the superior performance of Transformer architecture and revisiting the design decisions of CNN. In fine-grained classification tasks, the information of prominent regions and the relationships between different regions, along with their importance, are crucial. Therefore, the feature extraction backbone needs to balance the ability to extract local features with the capacity for global long-range modeling. In light of this, in this paper we use the well-tuned ConvNeXt as the feature extraction backbone.
## 3 Experimental Results and Discussion
### Effect of Process Parameters on Surface Roughness  
The side cut appears as a finely grooved surface with regular patterns or drag lines. From the observation of the cutting surface, it is generally possible to distinguish three different zones moving downward in the cutting direction: the upper edge of cut, which is characterized by lower surface roughness; the lower edge of cut, which exhibits higher surface roughness and, in some cases, slug; and the middle of the edge of cut, which is an intermediate roughness surface. The roughness profiles were acquired for each of these zones and analyzed separately. The formation of drag lines is a complex and still less-known mechanism involving at the same time thermodynamic, fluid-dynamic and optical phenomena, small process drifts and disturbance. The waviness or finish of the surface was defined by parameters of amplitude (vertical displacement of the profile) and spacing (the sizes of the irregularities along the surface). Arithmetic mean surface roughness (Ra), surface roughness depth (Rz) and mean width of profile elements (RSm) are the most commonly used when approaching the evaluation of the surface roughness of cut edge.
###### Abstract  
The explosion-suppression effects of NSSs on overpressures, flame propagation and flame tip velocities were explored under the initial pressures of 0.2 MPa, 0.3 MPa and 0.4 MPa. All experiments tested in a constant volume combustion bomb (CVCB). Explosion reaction of premixed propane-air gas in a new designed CVCB filled with nonmetallic spherical spacers (NSSs) was analyzed. The results showed that overpressures decreased under the different initial pressures. With the increase of filling density, the overpressure decreased, the time to reach explosion overpressure decreased, and the decay rate of explosion overpressure increased. It was also found that the explosion-suppression effects of NSSs on pressures. Flame front could be captured by high-speed schlieren photography. Combustion phenomena were captured including flame propagation, corrugated laminar flame, jet flame, corrugated turbulent flame as well as tulip flame under different initial pressures. Flame tip velocities also were captured. The results demonstrate that flame tip velocities decreased with the increase of filling densities. However, compared with unfilled CVCB, flame tip velocities increased after filling NSSs in CVCB under different initial pressures. NSSs suppressed the explosion overpressure in the cylinder, and promoted the flame propagation. In both cases, NSSs played a dual role. The suppression effect of NSSs was affected by both its suppression and promotion effect on the explosion. This work provides a scientific basis for the effective prevention of explosion accidents with propane-air premitxtures and the development of explosion-suppression products.  
Explosion-suppression; nonmetallic spherical spacers; constant volume combustion bomb; overpressure; flame propagation
## 4 Edge Cloud Infrastructure
### Computing  
Like storage, edge cloud computing also brings processing power near to the user and provides faster responses, reducing the limitations of a centralized cloud server. By serving traffic at the network edge, data of the user applications can avoid traveling long distance to a cloud DC. Hence, edge cloud can decrease the transmission latency, and risk of congestion, disruption, and cyber attack. In the research work presented by [PERSON] et al. [31], the authors reported experimental results that show edge cloud can improve response time by about 51%. [PERSON] et al. [24] showed, based on the placement of the edge DC, that latency can be improved by between 6% and 40%.
## 4 Analysis of Test Results for Diversion Function Pipe Segment Models
### Analysis of Earth Pressure Distribution on Both Sides of the Pipe Segment under Different Pressures
#### 4.2.2 Variation in Earth Pressure on Both Sides of the Pipe Segment at Different Depths  
The analysis of the change in earth pressure on both the sides of the pipe segment, as illustrated in Figure 16a-f, reveals that while the earth pressure on the right side of the pipe segment is greater than that on the left, the difference in earth pressure between the two sides is greatest at a depth of 0.3 m, followed by 0.5 m, and it is the lowest at 0.7 m. The earth pressure difference between the two sides of the pipe segment increases with the increase in differential pressure. The greater the depth of the location is, the greater the impact is, resulting in a pipe segment with higher unsymmetrical pressure. This, in turn, increases the possibility of its bending and deformation, which is prone to causing the leakage of the node of the pipe segment and operational and maintenance difficulties. The channelization of the pipe segment is an effective method of reducing the pressure difference between the two sides, thereby protecting the spring system and groundwater ecology. It also weakens the influence of unsymmetrical pressure on the pipe segment and alleviates the difficulties in the operation and maintenance of the pipe segment.  
Figure 15: Variation in earth pressure at each measurement point.
# Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques
## 4 Research Methodology
### Machine Learning Algorithms
The K-Nearest Neighbors (KNN) algorithm is a supervised learning algorithm that can be utilized for both classification and regression tasks. It operates on the principle that data points with similar features are likely to belong to the same class or share similar output values. For a given input, KNN computes the distance between this input and all other instances in the training dataset, which enables KNN to make predictions [64]. KNN is a non-parametric method [65], meaning that it makes no assumptions about the underlying data. Following the computation of the distance between each new data point and every other training data point, the algorithm can classify the new data point in relation to the trained data points [66]. KNN is a simple and adaptable ML algorithm that can solve various predication problems such as multi-class and binary classification problems, like the one being researched in this paper. However, research shows that KNN can be computationally complex to run, and the distance between points can become less meaningful in high-dimensional spaces [67]. An ensemble approach [68] is also used in this research, and for this, the random forest, decision tree, and the K-Nearest Neighbor ML algorithms are all used together in the ensemble approach. A voting classifier was used to combine the results of all the models, and for this research, a soft vote [69] was used for predicting the malware. The soft voting approach is useful, because it can select the average probability of each class [70].
## 2 LNA Design Methodology
### Two-Stage Gain Compensation

Table 1: \(N\)\(F_{min}\) at 28 GHz and \(f_{T}\)/\(f_{MAX}\) of NMOS devices of various widths with CPP of 104 nm (CPP1x) or 208 nm (CPP2x). [gate voltage = 0.45 V, drain voltage = 0.9 V]. Figure 4: Power gain of first, second and overall stages (pre-PEX). The first stage’s power gain was simulated from the RF input to the input of \(C_{3}\), while the second stage power gain was simulated from the input of \(C_{3}\) to the RF output. Figure 3: (**a**) Schematic of the 2-stage LNA and its passive component values (**b**) Load impedance of first stage cascode (\(Z_{\text{load}1}\)) and the simplified small signal model of \(M_{3}\). An alternative way of looking at this would be to simply observe the region where the gain droop occurs (between 20 and 30 GHz) and construct a second stage's load that has its gain peak and provides peak power transfer at the first stage's gain droop region. Since the gain droop region is more narrowband, one L matching network would provide a single gain peak such that it would compensate for the gain droop of the first stage, achieving an overall wide gain bandwidth.
## 4 Discussion
### RQ2: What Thermal Comfort Parameters Were Investigated in the Studies That Analyzed Bus Cabins?
\begin{table}
\begin{tabular}{c c} \hline \hline
**References** & **Comfort Type** \\ \hline [PERSON] et al. [11] & Air quality \\ [PERSON] [48] & Not available \\ [PERSON], [PERSON], and [PERSON] [9] & Not available \\ [PERSON] et al. [13] & Air quality and acoustics \\ [PERSON] et al. [18] & Not available \\ [PERSON] et al. [14] & Air quality \\ [PERSON] and [PERSON] [15] & Not available \\ [PERSON] [49] & Not available \\ [PERSON] and [PERSON] [31] & Not available \\ [PERSON] and [PERSON] [50] & Acoustics, acceleration, and luminous \\ [PERSON] et al. [19] & Not available \\ [PERSON], [PERSON], and [PERSON] [52] & Acoustics and acceleration \\ [PERSON], [PERSON], and [PERSON] [5] & Acoustics and acceleration \\ [PERSON] [10] & Not available \\ [PERSON] et al. [53] & Not available \\ [PERSON], [PERSON], and [PERSON] [46] & Air quality \\ [PERSON] et al. [16] & Not available \\ [PERSON] and [PERSON]. [17] & Air quality \\ [PERSON] et al. [54] & Not available \\ [PERSON] and [PERSON] [47] & Air quality \\ [PERSON] et al. [55] & Not available \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Types of comfort evaluated on thermal comfort studies in bus cabin environments. Table 10 shows that the main international standards of thermal comfort (ISO and ASHRAE) were employed in a few studies, whereas it was not possible to identify the standards used by others. Thus, ASHRAE 55 was present in ten studies [9; 15; 16; 17; 31; 46; 48; 49; 54; 55] and can be considered the most employed in bus cabin environments. [PERSON] et al. [53] were the only authors to employ the ISO 14505-3 standard, one of the four belonging to the ISO 14505 series linked to vehicular thermal comfort. This ISO standard can be utilized in any vehicle type, including buses, and applied to passengers and drivers. As discussed in Section 4.2, three studies questioned bus occupants regarding subjective parameters or sensation, preference, and thermal acceptability votes. [PERSON] and [PERSON] [15] and [PERSON] et al. [53] employed ISO 10551, which provides guidelines for subjective questions to occupants about the mentioned votes. Despite these cited findings, at the end of the analysis of the studies included in this review, it was not possible to find a study that questioned any point of any of the standards linked to thermal comfort that applied to bus cab environments.
# Improving Ship Maneuvering Safety with Augmented Virtuality Navigation Information Displays
## 3 Results
### The Comparison of the Random Variables of Scenario 1. Container Ship  
The values of the arithmetic mean of the distributions of the resultant container ship speed determined at the moment of container ship contact with the fender, during parallel berthing along the ship's port side, are similar for all variants of passage, except for the test series using the ECDIS system (Table 9). The value of the mean distribution of the random variable V1_ECDIS is on average larger by 20% than the other.  
The analysis of the values of the arithmetic means of the distribution of the random variable of maneuvering time in independent groups for the container ship, like previously, showed a slight difference in the values, except the passages using the ECDIS system. The difference between the arithmetic mean of the distribution of the random variable T1_ECDIS obtained during passages using that system and the other was on average 15%. No significant differences were observed in the mean distribution of the random variables of maneuvering times for the other series of simulation tests.  
It should be noted that despite clear differences in the mean distribution of resultant speed and time length of performed maneuvers in independent groups for variants 1_Visual, 1_Pprecise, 1_AV, for the latter two, the mean is slightly larger than for the variant with visual observation. This dependence occurs when we adopt the conditions of good visibility for visual observation. When restricted visibility is introduced, such a relationship may not occur.  
The differences observed (at least one pair) in the values of the mean distribution of the random variables of resultant speed and maneuvering time in independent groups obtained for four variants of Scenario 1 gave the basis for further analysis, in which the means were compared at the confidence level 0.95.
## 1 Introduction
Internal inspection of small-diameter pipes using robots is common, but correction of eventual problems (mostly caused by faults during construction and installation) is often difficult for buried pipes. Man-sized larger pipe diameters enabling access for inspection and correction of problems is, hence, a significant advantage [18]. Indeed, maintenance and other non-heat-transfer related aspects, such as availability of unimpeded soil to bury the pipes, commercial availability of materials, contractors' familiarity with EAHX construction techniques and costs, are paramount to EAHX sizing and introduce practical constraints to optimal heat transfer in EAHXs. Larger-diameter pipes imply larger investment costs (materials and excavation), not only because of the diameter increase but also for the larger pipe length and/or depth required to compensate the reduction in heat transfer; still, EAHX and building construction costs are seldom independent and, in the authors' experience, cost increments related to the use of larger pipe diameters can represent but a small fraction of the total building costs (of course, this relies heavily on the type of soil; indeed, [PERSON] et al. [5] mention a ten-fold or larger increase in excavation cost between sand, clay or gravel and hard rock soils). In this context, as important as costs is the ability to demonstrate the benefits/energy savings of EAHXs, and this depends on experimental evidence. Monitoring results for large-diameter EAHXs (\(>\)0.30 m) used in room cooling are rare. Research on heat transfer in large tunnels, as presented in [PERSON] et al. [19], [PERSON] et al. [20] and [PERSON] et al. [21], uses monitoring data and provides valuable insights into the hygrothermal behaviour of large-diameter EAHXs. However, large tunnel specifications and operating conditions are different from those of EAHXs used for building cooling. Studies using EAHXs as pure passive (no fans) cooling systems [22; 23]or associating EAHXs with solar chimneys [24] also tend to use larger pipe diameters--required to minimize pressure losses--however, most of these studies present numerical rather than monitoring results. This paper addresses this gap in the research literature and uses monitoring data to assess the standalone cooling capacity of a large-diameter EAHX delivering a nominal 8000 m\({}^{3}\)/h flowrate of cooled air to an office building in a region with hot and dry summers. The present paper is structured as follows. Section 2--Materials and Methods--describes the office building served by the EAHX, describes the cooling and ventilation system into which the EAHX is included, introduces the indices used to assess EAHX performance and details the monitoring protocol. Section 3--Results and Discussion--uses monitoring data to characterize the outdoor conditions and challenges posed to standalone EAHX cooling and assesses the large-diameter EAHX cooling performance and design. Section 4 presents the conclusions.