esa-sceva/satcom-chunk-collection huggingface dataset:
Compression testing is one of the most fundamental types of mechanical testing, alongside tensile and flexion tests [20; 21]. Compression tests are used to determine a material's behavior under applied crushing loads, and are typically conducted by applying compressive pressure to a test specimen (usually of either a cuboid or cylindrical geometry) using platens or specialized fixtures on a universal testing machine. During the test, various properties of the material can be calculated and plotted as a stress-strain diagram, which is used to determine qualities such as elastic limit, proportional limit, yield point, yield strength, and, for some materials, compressive strength. Dynamic loads (fatigue tests) are an essential component of research and clinical practice in dental implantology, providing crucial information on the strength and durability of implants and dental prostheses, thereby contributing to the improvement of the quality and reliability of implant treatments [3]. These tests are represented through stress-load diagrams, where the number of cycles to failure of the specimen is related to the magnitude of the cyclic stresses. By evaluating the material's fatigue in this way, it is possible to understand the mechanical phenomenon of progressive degradation of a material subjected to variable loads over time (either regularly or randomly), which can lead to its failure. The fatigue limit corresponds to the maximum load level that a material can withstand without fracturing for a theoretically infinite number of load cycles. In laboratories, fatigue tests are conducted at high frequencies, typically between 1 Hz (1 cycle per second) and 10 Hz (10 cycles per second), to accelerate the process. At a frequency of 10 Hz, one year of mastication (365,000 cycles) can be simulated in about 10 h. It has been reported that a minimum of 250,000 cycles in the chewing simulator are enough to simulate 1 year of use in the clinical setting [22; 23]. The aim of the present in vitro comparative study is to validate a novel composite polymer, developed to replace metal-reinforced PMMA interim restorations due to its advantages of easier manufacturing and handling. The null hypothesis is that there are no differences in load and displacement in a compression test, as well as in a dynamic (fatigue) test.
# A Brief Review on the Recent Experimental Advances in Thermal Rectification at the Nanoscale
## 3 Discussion  
In this brief review, we have summarized some recent experimental approaches for realizing thermal rectification at the nanoscale and their underlying physical mechanisms. At the bimaterial nanocontact interface, the localized phonon modes are generally gathered at the edges and suppress the heat flow from the polyamide nanofiber to silicon nanowire. In the asymmetric nanotubes, the thermal conductivity was found to be larger in the heat flow direction from the high mass-loaded end to the low mass-loaded end. Such thermal rectification in the asymmetric one-dimensional system cannot be fully explained by the conventional phonon-edge scattering model while the soliton theory provides a reasonable explanation. In the suspended graphene, thermal rectification was realized by creating nanopores, loading nanoparticles at one side or cutting the membrane into a tapered shape. The asymmetric temperature dependence of thermal conductivity and significant lateral confinement of two-dimensional phonons are found to be the reason. In a tapered VO\({}_{2}\) beam, thermal rectification was observed below the metal-insulator transition temperature. In this system, the asymmetric electron-phonon coupling at the metal-insulator interface is the possible reason for rectification. At cryogenic temperature, significant thermal rectification in the electronic heat current was realized at normal metal-superconductor tunnel junctions. The selective electronic heat flow across the superconducting electrode and enhanced electron-phonon coupling at the normal metal electrode are found to be the reason for thermal rectification. All of these pioneering experiments demonstrate the feasibility of designing efficient thermal diodes at the nanoscale through advanced nanofabrication techniques. A large thermal rectification ratio can be achieved by creating an asymmetric nanocontact interface, mass-loaded nanotube, defect-engineered two-dimensional material, metal-insulator contacting phase or cryogenic superconducting tunnel junctions. Unique and rich physics have been revealed in these nano-thermal rectifiers, but much more remains to be explored. There is no doubt that our rapid growing ability of precise nanofabrication will greatly enlarge the research of logical thermal circuits and become one of the key technologies in thermal sciences.  
[PERSON] and [PERSON] discussed the topic and wrote the manuscript together. [PERSON] directed the research program and provided guidance.  
This research was funded by National Youth 1000 Talents Program in China and National Natural Science Foundation of China grant No. 51636002, 51827807.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Characteristics of Quality Parameters of Wheat Flour and Sugar Beet Pulp Mixtures
#### 3.2.2 Parameters Characterized the Starch Complex of Wheat Flour and Sugar Beet Pulp Mixtures  
Table 3 presents the results describing the starch complex of wheat flour (WF) and its mixtures with sugar beet pulp (SBP) powders. The alpha-amylase activity and starch properties of the tested flours were determined by the falling number (FN) test and selected parameters of the Mixolab(r) curve as follows: starch gelatinization (C3), stability of the hot phase stage (C4), and retrogradation (C5). The control wheat flour (0% SBP) was characterized by common starch properties that were determined by Mixolab(r) as C3, C4, and C5 (Table 3) for the wheat flour produced in Poland [56]. The trials carried out on the wheat flour mixtures were distinguished by low alpha-amylase activity (FN over 300 s). The lowest alpha-amylase activity was evaluated by trials with a 1% addition of SBP (FN\(-\)339 s; C3\(-\)2.039 N\(\cdot\)m; C4\(-\)1.943 N\(\cdot\)m; C5\(-\)2.932 N\(\cdot\)m). The starch gelatinization, C3, indicates the dough's viscosity upon heating and strongly depends on the type and quality of starch. The increase in the SBP additive increased the value of the mentioned parameter. High FN and Mixolab(r) C3 values may indicate the probability of the incorrect appearance of bread, with a round shape and low crumb porosity. With the addition of 10% SBP, the torque in point C4 decreased, which is the effect of the lower level of starch in SBP. In research by [PERSON] et al. [55], the addition of sugar beet fiber caused a reduction of 26% in torque C3 (and a simultaneous lower torque in C4 and C5 by 34%) due to the straight negative and quadratic beneficial results received for the mentioned parameters. Our investigation revealed that starch retrogradation (C5) decreased with the increased of the concentration of sugar beet pulp (SBP) addition to wheat flour, designating a reduced retrogradation during the cooling process with a higher fiber addition [57]. On the other hand, the higher addition of SBP caused a slightly higher dough initial starch gelatinization temperature of D2 and lowered the final gelatinization temperature of D3. SBP has not been a source of alpha-amylase activity. This is why the differences were not significant from the technological point of view. The type of fortification significantly influenced the Mixolab(r) parameters. Starch gelatinization (C3-C2) was the most intensive for the control flour with a 1% addition of SBP, and the stepwise drop was 0.116 for 10% SBP. The opposite effect was found for the gel
# Performance Impact of Nested Congestion Control on Transport-Layer Multipath Tunneling
## 2 The Multi-Access Framework
### Multipath Scheduling  
Our evaluation focuses on the Cheapest Path First (CPF) scheduler, a particular implementation of the more general strict-priority scheduler [6]. CPF prioritizes available paths based on user-defined preferences, such as favoring WiFi interfaces over others. For CPF, a path is considered available if its path congestion window (CWND) has sufficient room to send a packet. Consequently, CPF always schedules packets over the highest priority path if it has available capacity and only schedules packets to the next available path once the CWND of the highest priority path is filled up. This mechanism establishes a clear preference for certain paths, a preference that can also be set by the operator. We concentrated on CPF due to its significance in 5G ATSSS scenarios, where the utilization of cost-effective or free-access links, such as WiFi, is preferred compared to more expensive and volume-restricted cellular access.
## 5 Conclusions  
This study presents a 256-pixel retinal prosthesis system featuring a digital controller capable of dynamic biphasic pulse generation for high-density, low-crosstalk stimulation. The proposed design demonstrates several significant advancements over existing technologies, addressing key challenges in retinal prosthesis development, including current leakage, crosstalk, and power efficiency. Additionally, this study proposes a solution for implementing low-sensitivity electrodes while addressing flicker-free vision through an overlapping current pulse technique. The overlapping technique, with minimal time delay, enables precise control over current loss.  
Moreover, generating 128 distinct pulse shapes and amplitudes allows for adaptive stimulation tailored to individual light intensities and patient-specific retinal thresholds. This feature enhances the versatility of the system and demonstrates its potential to be deployed in a wide range of clinical applications. Additionally, the integration of wireless telemetry for power and data transmission ensures that the device remains compact and suitable for implantation.  
The performance of the system was validated through hardware implementation, simulation, and oscilloscope testing. The fabricated chip, based on a 0.18 \(\upmu\)m CMOS process, demonstrated reliable functionality with a compact active area and minimal external connections. The results of this study indicate that the proposed system has the potential to be a commercially viable device, as evidenced by various tests that meet general safety requirements.  
In the future, we aim to develop a more advanced system by enhancing control over flicker-free vision and crosstalk while increasing the resolution of the system. Future research will implement a chip with a resolution beyond 2000 pixels and integrate refined control algorithms.  
Conceptualization: Y.O., J.H. and J.K.; methodology: Y.O. and J.K.; formal analysis: Y.O. and J.K.; writing--original draft preparation: Y.O., J.H. and J.K.; writing--review and editing: Y.O., J.H. and J.K.; supervision: J.K.; funding acquisition: J.K. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Research Foundation of Korea grants RS-2024-0041926912982076870102 and RS-2024-0044988212982076870102.  
Not applicable.  
The data presented in this study are available in the article.  
The authors express their sincere appreciation to the IC Design Education Center for Chip Fabrication.  
The authors declare no conflicts of interest.
# TEDL: A Text Encryption Method Based on Deep Learning
## 6 Encryption and Decryption
### Training
#### 6.2.1 Sparse Word Vectors and Dense Word Vectors  
Models for word embedding are divided into two categories, namely the sparse word embedding model (e.g.,VSMs [38]) and the dense word embedding model (e.g., Word2 vec [15; 16]). In the sparse word embedding model, the word-context matrix is constructed, and its initial form is a matrix of frequencies. Each element in a frequency matrix is determined by cooccurrence times of a certain word in a certain context. In practice, the process of matrix construction can be time-consuming when the corpus is large. The entire corpus needs to be scanned, in which each word and its corresponding frequency are recorded, and the results are finally placed in a matrix [39], denoted by **F**. The row vector of the \(i\)-th row of the word-context frequency matrix corresponds to the word \(w_{i}\), denoted as \(\textbf{f}_{(i)}\), and the column vector of the \(j\)-th column corresponds to the context \(c_{j}\), denoted as \(\textbf{f}_{(j)}\). The value of \(f_{ij}\) is expressed as the frequency at which the \(i\)-th word co-occurs with the \(j\)-th context. This matrix has \(n_{r}\) rows and \(n_{c}\) columns.  
Based on the initial matrix of frequencies, some adjustments are made to weight the elements in the matrix. Ref. [40] has proposed the Pointwise Mutual Information (PMI), which works well for word-context matrics. Furthermore, the variation of PMI, Positive PMI (PPMI) [41], is also a powerful form for distributional representation of words.  
When PPMI is applied to **F**, the new matrix, denoted by **X**, has the same size as **F**. The value of an element, denoted by \(x_{ij}\), is defined as follows [38]:  
\[p_{ij}=\frac{f_{ij}}{\sum_{i=1}^{n^{\prime}}\sum_{j=1}^{n^{\prime}}f_{ij}} \tag{6}\]  
\[pmi_{ij}=\log\,\left(\frac{p_{ij}}{\left(\sum_{i=1}^{n^{\prime}}p_{ij}\right) \cdot\left(\sum_{i=j}^{n^{\prime}}p_{ij}\right)}\right) \tag{7}\]  
\[x_{ij}=\begin{cases}pmi_{ij},&\text{if }pmi_{ij}>0\\ 0,&\text{otherwise}\end{cases} \tag{8}\]  
In this definition, \(p_{ij}\) is the probability of co-occurrence of the word \(w_{i}\) and the context \(c_{i}\). Apparently, the matrix **X** is very sparse. Furthermore, when \(C_{\beta}\) is added to \(C_{\alpha}\), the size of both matrix **F** and matrix **X** may change. However, most zeroes remain unchanged, causing the risk of crack increasing, especially when selecting a partial component of the wordvector for encryption. For example, if the original vector of word is \(\mathbf{v}=(0\ 0\ 0\ 0.5\ 0.5)\) and the new one is \(\mathbf{v}^{\prime}=(0\ 0\ 0\ 0.25\ 0.75)\), it is extremely dangerous when the first 3 dimensions of the vector are used to replace the word for encryption.  
Such a sparse matrix is hence not available for our encryption method, due to the invariance of some elements. So we need to adopt dense word vectors.
# Exploring Data Augmentation Algorithm to Improve Genomic Prediction of Top-Ranking Cultivars
## 5 Conclusions  
The application of data augmentation, particularly utilizing the mixup method, significantly enhanced prediction accuracies, particularly for top-performing lines, across diverse maize and soybean datasets. However, its effectiveness varied depending on the subset of data under consideration. While it notably improved prediction performance for the top lines within the testing set, there was a discernible decrease in performance for the entire testing set overall. This limitation stemmed from the augmentation technique's primary focus on enhancing prediction accuracy exclusively for the top lines. Notably, employing augmented data exclusively from the top 20% of lines in the training set consistently bolstered the predictive performance for these top lines in the testing set, maintaining the same subset size. This targeted approach effectively aimed at enhancing model generalization and performance within a specific segment of the data. Therefore, while data augmentation proves to be a valuable tool for augmenting predictive capabilities, a comprehensive understanding of its impact on different data subsets and evaluation metrics is essential for its effective implementation in the genomic-assisted plant breeding process. It is crucial to recognize that augmentation may not uniformly enhance prediction performance across all data subsets.  
Conceptualization, O.A.M.-L., A.M.-L. and J.C.; formal analysis, O.A.M.-L., A.M.-L., A.S., G.I.H.P., J.S.-R. and A.E.O.R.; investigation, O.A.M.-L., A.M.-L., J.C., A.S., G.I.H.P., J.S.-R. and A.E.O.R.; resources, K.A.; data curation, O.A.M.-L. and A.M.-L.; writing--original draft preparation, O.A.M.-L., A.M.-L. and J.C.; writing--review and editing, A.A. and R.O. All authors have read and agreed to the published version of the manuscript.  
Open Access fees were received from the Bill & Melinda Gates Foundation. We acknowledge the financial support provided by the Bill & Melinda Gates Foundation (INV-003439 BMGF/FCDO Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods (AGG)) as well as the USAID projects (Amend. No. 9 MTO 069033, USAID-CIMMYT Wheat/AGGMW, Genes 2023, 14, 927 14 of 18 AGG-Maize Supplementary Project, AGG (Stress Tolerant Maize for Africa)) which generated the CIMMYT data analyzed in this study.  
The datasets used and/or analyzed during the current study are available from the first author on reasonable request.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.
# Knowledge Distillation-Based Multilingual Code Retrieval
## 3 Experiments
### Evaluation  
**Mean Reciprocal Rank (MRR)**  
MRR is commonly used in the recommended system as an evaluation metric. It evaluates the performance of the retrieval system by using the ranking of the correct retrieval results in retrieval results. The formula is as follows.  
\[MRR=\frac{1}{|Q|}\sum_{q=1}^{|Q|}\frac{1}{rank_{i}} \tag{13}\]  
**SuccessRate@k**  
SuccessRate@k is a common metric to evaluate whether an approach can retrieve the correct answer in the top k returning results. It is widely used by many studies on the code search task. The metric is calculated as follows:  
\[\small SuccessRate@k=\frac{1}{|Q|}\sum_{q=1}^{|Q|}\delta(Rank_{q}\leqslant k) \tag{14}\]  
where \(Q\) denotes the set of queries, \(Rank_{q}\) denotes the highest rank of the hit snippets in the returned snippet list for the query; \(\delta()\) denotes an indicator function that returns 1 if the Rank of the \(q\)th query (\(Rank_{q}\)) is smaller than k otherwise returns 0. SuccessRate@k is important because a better code search engine should allow developers to find the desired snippet by inspecting fewer results.
## 2 Structure Design and Model Analysis of Straw Guide
### Threshing Device and Straw Guide Structure  
The threshing device is the core component of the harvester, including a feeding inlet, drum assembly, straw guide device, concave plate sieve, cover plate, etc. The straw guide device is installed on the cover plate directly above the threshing drum so that the crops can move smoothly in the threshing chamber. Moreover, the threshing device is connected to the power output through the transmission belt to drive the drum assembly to rotate. When the threshing device works, the straw is fed into the threshing separation chamber under the action of the forced feeding wheel, the straw moves in the threshing separation chamber with the rotation of the threshing roller, and the threshing nail teeth of the high-speed rotation mainly strike the straw. Under the action of friction and impact, the rice grain separates from the rice stem, and the rice stem moves along the roller axis under the action of the straw guide. Under the action of the centrifugal force, the seeds and some impurities, such as short stems and light impurities, fall into the screening device below.  
The straw guide boards on the market mostly use the fixed type, that is, the spiral angle of the straw guide board is at fixed value. The 4 LZ-4.0 harvester prototype in this study adopts a new type of threshing device with an adjustable straw guide structure, as shown in Figures 2 and 3. The straw guide device comprises a rotating shaft, adjusting pull rod, fixed straw guide board (one piece), main adjustable straw guide board (one piece), connecting rod, and follow-up adjustable straw guide board (seven pieces). The adjustable pull rod is connected with the main adjustable straw guide board through the rotating shaft, and the main adjustable straw guide board is connected with the follow-up adjustable straw guide board through the connecting rod. Through the small operating force, the adjusting rod rotates, the rotating shaft drives the main adjustable straw guide board to rotate, and then, it drives the adjustable straw guide board through the connecting rod to rotate synchronously, thus realizing the adjustment of the spiral angle of the straw guide board. Eight adjustable straw guide boards are used to control the flow velocity of crops during the threshing process and improve the smoothness of the threshing transportation. One straw guide board is fixed above the roller of the straw outlet, which can effectively guide the flow of weeds such as long stems.  
Figure 2: Structure diagram of the threshing device.
# An Intrusion Detection System for RPL-Based IoT Networks
## 3 Related Work
### IDSes for IoT and Wireless Sensor Networks
Despite this fact, depending on the purpose of the scenario, it may be worth using to secure an IoT network. Another relevant IDS design for the IoT is the one proposed by [PERSON] et al. [48]. Their system is called INTI and aims to carry out intrusion detection with respect to sinkhole attacks on 6 LoWPAN. More specifically, INTI uses reputation and trust mechanisms in order to detect suspicious behaviour that could lead to sinkhole attacks. In addition, INTI is capable of isolating the attacker by broadcasting a message to the rest of the nodes once the sinkhole attack is detected. Upon receiving this message, benign nodes will change their parents in order to avoid using the malicious node. The experimental results showed that INTI had a false negative rate of about 8%. Moreover, these results showed a better rate of false positives and false negatives when compared with SVELTE. Another work around the topic of IDSs for IoT was performed by [PERSON] et al. [49]. The authors presented a signature-based IDS design and analysed two DoS attacks (Hello flood attack and version number attack) by using ContikiOS and the Cooja simulator. Additionally, in order to exclude the attacker from the network, the authors proposed an IDS module installed in the border router that would create a new rule in the firewall to remove the attacker from the network if the IDS detected that it was acting as a malicious node. [PERSON] et al. concluded their work by showing the high impact caused by the Hello flood attack and the version number attack. A future work is expected to implement the IDS and to test it against DoS attacks in the Cooja simulator to analyse the performance of this IDS design. Recently, [PERSON] et al. [16] proposed an adversarial reinforcement learning (ARL) framework to produce efficient intrusion detection systems for RPL-based IoT environments with evolving data. The authors demonstrated that by detecting a 'concept drift' and using a subsequent adaptation, it was possible to identify changes in the RPL network and improve the detection performance. This was accomplished by considering both black-box and grey-box ML-based adversaries.