esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion
### Performance Evaluation  
This experiment shows that the complexity of the dataset architecture greatly affects the modeling performance, network selection, and the training process of the latest slum classification. The Places365 VGG16 network is a convolutional neural network (CNN) architecture that has been demonstrated to be highly effective in the classification of images, particularly in the recognition of various environments. However, the complexity of its architecture may not be compatible with simpler datasets, such as the 2020 Bandung City Cumulative Map dataset, which is considered too simple for the capabilities of the VGG16 model. This discrepancy can result in suboptimal classification performance [16]. In addition, the condition of the dataset from the Bandung City Government shows that the distribution of slum areas are uneven, less varied in each area, and does not cover all slum categories (light, medium, and heavy), causing an imbalance when using more complex modeling such as a Visual Geometry Group (VGG). VGG is more appropriate and superior in terms of storing varied data patterns so it can be adapted to improve the ability to recognize slum category variations with a more diverse and balanced dataset [16].
## 3 Results  
The configuration of the SCISCCO for use with human participants is illustrated in Figure 5a where, similar to the set-up in Figure 1, the NIR and SWIR SC light source was followed by a tunable spectrometer, optical chopper, and polarizer. Unlike the previous lab set-up, a beam splitter with a 99:1 ratio was used to split the beam into a sample and reference arm (i.e., much less power delivered to the reference arm beam). The reference arm was sent to one silicon detector, and this was used to divide out the laser fluctuations. The sample arm beam was coupled into a fiber-based probe for the delivery of light to and collection of light from the human participant. The outputs from the two silicon detectors in the sample and reference arms were sent to a lock-in amplifier synchronized to the optical chopper. The output from the lock-in amplifier was sent to a computer for data collection and analysis.  
Figure 5b provides more details on the SC fiber probe for placement on the human participant for the blood pressure tests (Section 3.1) and the breath-holding tests (Section 3.2). As will be described in Section 3.3, this probe was slightly modified for use in the attention test. The fibers used for delivery and pick-up were a 2-mm diameter borosilicate fiber bundle with SMA connectors on both ends. The two fibers were mounted on a solid base. Although the distance between the probes was adjustable, the experiments were conducted with a spacing of 2 cm between the delivery and pick-up fibers. For a \"banana pattern\" optical penetration pattern, this would mean that signals are measured from a -2-cm penetration into the sample or skin (perhaps less with intervening bones). This probe was used on the forearm for the blood pressure test and on the forehead for the breath-holding test.  
Figure 5: (**a**) Block diagram of optical set-up for SCISCCO system for human testing. (Note that the chopper was moved after the spectrometer due to space constraints, but no change in performance was detected from having the chopper before or after the spectrometer). (**b**) SC probe for placement on human participants for blood pressure and breath-holding tests.
## 4 Discussion
### Glucose Metabolism and Respiratory Exchange Ratio  
Supplemented nitrate has been shown to have a moderate but significant effect on glucose and lipid metabolism in rats [11; 25; 68; 69]. We hypothesized that supplemented nitrate would lead to changes in blood glucose concentrations in humans. No significant differences in venous glucose concentration were found in the present study, but there was group\(\times\)time interaction. After 45 min of high-intensity, high-volume intermittent exercise, there was non-significant Glu\({}_{v}\) reduction in the N group (uncorrected \(p=0.089\)). This would be consistent with other studies, which have shown that nitrite-derived reactive species can increase glucose uptake in mice and rats by activating adenosine monophosphate-dependent kinase (AMPK) and subsequent translocation of GLUT4 [70; 71; 72]. However, resting Glu\({}_{v}\) was not reduced in the N group, although the plasma concentrations of NO\({}_{3}\)\({}^{-}\) and NO\({}_{2}\)\({}^{-}\) were significantly higher. Lactate concentrations in venous and arterialized blood were unchanged. Regarding RER, no significant differences were found between the two groups in the present study. RER may be influenced by increased respiration, specifically through an increase in the exhalation of CO\({}_{2}\). However, no differences in VE, BF, and petCO\({}_{2}\) were found between the groups. These results are similar to those observed in other studies [15; 16; 18; 21; 73], although there are studies showing that RER tended to increase [15; 74] or increased significantly [13] after nitrate supplementation. An increased RER would suggest a slight shift towards carbohydrate utilization and/or amino acid combustion during exercise. Due to increased plasma and muscle tissue concentrations, the transport of glucose into the skeletal muscle and organs may be enhanced [11; 75]. Therefore, it could be plausible that dietary nitrate influences glucose metabolism during HIHVT. However, this effect appears to be very small and may be restricted to tissues other than working muscle, and possible changes in Glu\({}_{v}\) and RER are not significant in the present study.
# Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization
## 2 Analysis of Non-Isolated Interleaved DC-DC Converter  
As analyzed in the Introduction, isolated MPCs are usually used for low-power systems due to the limitation of magnetic designs for transformers. Non-isolated MPC topologies are more suitable for high-power powertrain system of vehicles. Thus, in this paper, the topology of MPC in Figure 2 has been selected for optimization. The MPC consists of two Interleaved Bidirectional Converters (IBC) interfacing with a battery port and SC port, respectively. The objective of design optimization is to minimize input current ripple, converter losses, and inductor weight of IBC for each port. Some key parameters are foreseen intuitively to have an impact on optimization objectives. Firstly, if the switching frequency \(f_{sw}\) increases, the size of the inductor core can be reduced; however, switching loss is increased. Secondly, the more number of phases added, the more current flowing in each phase can be reduced, leading to less semiconductor losses and reduction in inductor sizing. However, this adds more weight to the power electronics system. Finally, a bulky inductor can reduce the input current ripple that is important for battery lifespan; however, it introduces more weight and core losses. Therefore, the relationship of optimization objectives and design variables needs to be thoroughly analyzed.
# A Survey on Energy-Aware Security Mechanisms for the Internet of Things
## 3 Security Protections in IoT Environments
### Evolving Threats in the IoT
#### 3.1.3 Unique Vulnerabilities of IoT Devices  
Now let us analyze the unique vulnerabilities of IoT devices from the following three perspectives, namely weak authentication [42], insecure communication protocols [43], and outdated firmware [44].  
* _Weak Authentication_. Weak authentication in IoT devices, like unchangeable default passwords, opens doors for attackers to seize control of entire networks.
* _Insecure Communication Protocols_. Insecure communication protocols, similar to weak authentication, leave users vulnerable to data theft and manipulation attacks by acting as open doors for hackers, especially on public WiFi networks.
* _Outdated Firmware_. Outdated firmware and limited update capabilities in IoT devices create easy openings for hackers, leaving networks vulnerable to known software attacks.  
Authentication technology is the most direct and cutting-edge line of defense in network security, and is an important means of preventing illegal invasion and virus damage. Many IoT devices have weak authentication mechanisms [45], such as default passwords or simple passwords, and users rarely change these passwords, thereby making IoT systems vulnerable to unauthorized accesses. Weak credentials, coupled with limited authentication methods, create opportunities for attackers to compromise devices and gain control of IoT networks.  
As with weak authentication by default, insecure communication protocols allow hackers to intercept traffic or perform network \"snooping\" to easily view sensitive data traveling over the networks. This issue makes systems and devices vulnerable to man-in-the-middle (MITM) attacks [46], and one of the most common methods of MITM attacks is through public WiFi, which often has insecure communication protocols allowing an attacker to gain access to information from any devices connected to the network. The attacker can even lure the user to a fake server that has been set up in advance so as to conduct illegal activities such as fraud against the user.  
IoT devices often have limited computing resources, and may lack appropriate mechanisms for regular firmware updates and security patches. As a result, these devices often run on outdated and vulnerable versions of software. Hackers actively exploit known vulnerabilities in outdated firmware to gain unauthorized access to, or control of, IoT devices. The lack of a streamlined process for providing timely updates and patches to IoT devices poses a significant challenge, as it exposes devices and networks to attacks that could be prevented.
# A Survey on Energy-Aware Security Mechanisms for the Internet of Things
## 3 Security Protections in IoT Environments
### Defense at the Software Level
#### 3.5.1 Secure Coding Practices  
Secure coding practices are a critical part of the software-development process designed to guide developers on how to write more secure code [67]. These practices are designed to reduce the vulnerability of software and systems to security breaches, thereby protecting applications from attacks. Examples include using strong hash functions like Argon2, bcrypt, or PBKDF2 [68] to store user passwords, and employing salt to further enhance security.  
Common security threats and vulnerabilities that can be protected by secure coding practices include memory security and buffer overflows. This method requires developers to use safe functions when coding, avoiding functions such as _strcpy()_ and _sprintf()_ that are known to cause problems [69].  
Regularly reviewing code [70] is the process of checking source code to pinpoint and eliminate vulnerabilities or errors that are likely to compromise security in software. The code-reviewing process ensures that the implemented code meets the security standards and complies with the industry regulations. This practice not only helps to enhance the code quality and performance but also prevents potential attacks by hackers.  
Using secure coding libraries coupled with software frameworks with embedded security is an effective way to improve the quality and security of code during software development (see Figure 7). These libraries provide a collection of rigorously vetted and tested code modules that enable developers to avert insecure code practices. Common secure coding libraries and frameworks that prevent security vulnerabilities include OWASP ESAPI, Spring Security, and Microsoft SDL. Figure 7 lists a set of example secure codinglibraries, frameworks, and patches, which are devised to help software developers to implement security features throughout the development lifecycle [71].
# Can Biochar Improve the Sustainability of Animal Production?
## 2 Summary of Biochar-Production Techniques
### Properties of Biochar
#### 2.3.3 Point of Zero Charge (PZC)  
The efficacy of biochars when applied as adsorbents to some extent depends on their PZC [66]. The PZC is defined as the pH of the solution at which the biochar experiences a net neutral charge [67]. During the adsorption process, if the pH of the solution falls below the PZC of the biochar, the surface acquires a positive charge and facilitates the electrostatic adsorption of anionic species, such as nitrates, nitrites, and chlorides [68]. Conversely, when the pH of the solution increases beyond the PZC of the biochar, the surface turns negative and can actively adsorb cationic species, such as metal ions and ammonium [69].
## 2 Materials and Methods
### POCIS Preparation and Extraction  
Both commercial POCIS (E&H Services, Praha, Czech Republic) and devices assembled in our laboratories were used for passive sampling. The laboratory assembly was performed in accordance with the characteristics of commercial ones (mass of the sorbent phase 200 mg and 45.8 cm\({}^{2}\) as sampler surface area). PES membranes (0.1 \(\upmu\)m pore size) and Oasis HLB sorbent were purchased from Pall Italia (Buccinasco, Italy) and Waters (Vimodrone, Italy), respectively. Before use, PES membranes were washed in a H\({}_{2}\)O/CH\({}_{3}\)OH solution (80:20 _v/v_) for 24 h at room temperature (RT) and 1 h at 40 \({}^{\circ}\)C. Membranes were allowed to dry and subsequently washed with CH\({}_{3}\)OH for 24 h at RT and 1 h at 40 \({}^{\circ}\)C. After drying under a fume hood, 200 mg of HLB phase was weighted and placed between two membranes. Then, the membrane-sorbent-membrane layer was compressed between two stainless-steel support rings and held together with three thumbscrews. The prepared POCIS were stored at \(-\)20 \({}^{\circ}\)C.  
After the exposure, samplers were collected, rinsed with Milli-Q water, wrapped in aluminum foil, transported to the laboratory under cooled conditions (4 \({}^{\circ}\)C) and kept at \(-\)20 \({}^{\circ}\)C until analysis.  
Prior to processing, the samplers were thawed and rinsed with Milli-Q water to remove fouling present on POCIS membranes, although during all the sampling experiments, no significant biofouling was observed. This is probably due to the daily replacement of a part of the water in the shark tank. POCISs were dismantled and the sorbent phase was transferred using Milli-Q water into a 1 cm diameter glass syringe cartridge fitted with a polytetrafluoroethylene (PTFE) frit and glass wool and dried under a gentle nitrogen stream. Elution was performed with 10 mL of dichloromethane: isopropanol: trifluoroacetic acid (80:19.9:0.1 _v/v/v_) in a flask and the extract was reduced back down to a small volume [9]. Then, 20 mL of dichloromethane was added, and the solution was evaporated to dryness and redissolved in 1 mL of methanol for GC-MS analysis. The extracts in methanol were diluted 1:1 using Milli-Q water for LC-MS/MS. Samples were filtered through 0.2 \(\upmu\)m PTFE filters before chromatographic analysis.
## 3 Methodology and Data Sources
### Determination of Pollution Episodes  
PM\({}_{2.5}\) is a typical indicator of SOB-induced haze pollution episodes. In this study, PM\({}_{2.5}\) air pollution episodes (PEs) are defined as a consecutive duration of >10 h with the hourly average PM\({}_{2.5}\) concentration exceeding the Grade II China Ambient Air Quality Standard (GB3095-2012) of 75 \(\upmu\)g m\({}^{-3}\). The hourly average PM\({}_{2.5}\) concentrations of Changchun were obtained from the Jilin Provincial Environmental Monitoring Centre, which collects official data from all state-controlled ambient air quality ground-monitoring stations in urban areas of Changchun. The ground-monitoring data for the hourly meteorological conditions, including mean wind speed (m/s), wind direction (\({}^{\circ}\)), and mean relative humidity (%), were obtained from the Jilin Provincial Meteorological Service. PBLH data were from regional gridded meteorological data archives from GDAS with a resolution of \(1^{\circ}\times 1^{\circ}\), which was obtained from the NOAA site [37]. Hourly PBLH was obtained via interpolation from observed data at 3 h intervals.  
Figure 2: Framework and procedures of the GIS-based integrated method in this study.
###### Abstract  
The efficiency and method of regeneration in in vitro culture conditions depend primarily on the plant growth regulators (PCRs) used. Even growth regulators belonging to one group may have different effects, stimulating the process of direct or indirect organogenesis, thus possibly disturbing the genetic stability among regenerants. The main aim of this study was to identify the genetic stability of _Scutellaria bacialensis_ regenerates obtained by in vitro culture method using start codon targeted (ScoT) markers. _S. bacialensis_ nodal explants were regenerated on MS medium supplemented with kinetin (KIN) at concentrations of 0.25, 0.5, 1.0, and 2.0 mg \(\times\) dm\({}^{-3}\) or benzylaminopurine (BAP)--0.25, 0.5, 1.0, and 2.0 mg \(\times\) dm\({}^{-3}\). The effects of the number of propagated shoots, length, number of nodes, and fresh mass of regenerants were assessed. Moreover, the genetic stability of the regenerants was analyzed using start codon targeted (SCoT) markers. Direct shoot organogenesis was observed on an MS medium containing kinetin, while indirect shoot induction occurred on an MS medium supplemented with BAP. The highest average number of shoots (3.6) was achieved for the MS + KIN medium at a concentration of 0.25 and 5.8 for the MS + BAP 1.0 medium. The average length and average number of nodes were the highest on the MS + BAP 0.25 medium (50.0 and 6.0, respectively), while the lowest values of these features were observed on the MS + KIN 2.0 medium (40.3 and 4.9, respectively). A total of 111 amplified bands were exhibited by ScoT primers. Three of the analyzed primers revealed four unique genotype-specific markers. The average percentage of polymorphism obtained was 36.7%. The analysis of genetic similarity revealed a high level of genetic similarity between the donor plant and regenerants obtained on MS \"0\" (medium without the addition of phytohormones). A slightly lower value of genetic similarity was observed for regenerants obtained by direct organogenesis (MS + KIN medium at all concentrations). Indirect shoot organogenesis observed on the MS + BAP medium (all concentrations) resulted in the highest differentiation, both in relation to the donor plant and MS \"0\" regenerants. The results of our work indicate that, in the case of _S. bacialensis_, the maintenance of genetic stability depends primarily on the presence of the cytokinin type in the medium.  
cluster analysis; direct organogenesis; genetic fidelity; herbal plant; somacional variation; ScoT marker +
Footnote †: journal: Applied Sciences
## 2 Materials and Methods
### Statistical Analysis  
Data were analysed using the Statistical Package for the Social Sciences (SPSS) version 21 (SPSS Inc., Chicago, IL, USA). Means and SDs were calculated using traditional statistical techniques. Normality and homoscedasticity assumptions were tested with the Kolmogorov-Smirnov test. A one-factor ANOVA for intergroup comparisons and a Student's \(t\)-test for intragroup comparisons, since variables presented a parametric distribution, were conducted. The effect size was calculated using [PERSON]'s d formula, which is defined as the difference between two group means divided by the pooled standard deviation. In terms of the variables presented in the charts, this calculation allows us to quantify the magnitude of differences between the pre- and post-race measures for both the control (baseline) and experimental (post-race) conditions. A positive effect size indicates that the mean post-race value is higher than the pre-race value, signifying an increase in the variable (e.g., blood lactate or rate of perceived exertion) as a result of the race. Conversely, a negative effect size indicates a decrease in the post-race mean compared to the pre-race mean, such as the observed decreases in leg strength or stability. In terms of interpreting the magnitude of effect sizes, we followed the conventional benchmarks where an effect size of 0.2 represents a small effect, 0.5 is a medium effect, and 0.8 or greater is a large effect. For example, in the sprint race, the decrease in leg strength had a medium to large effect (d = \(-\)0.56), while the increase in urine glucose showed a large effect (d = 3.00). The significance level was set at \(p\) < 0.05.  
In addition, A post hoc correlation analysis was conducted to assess the relationships between key pre- and post-race physiological variables. [PERSON]'s correlation coefficients were calculated to determine the strength and direction of associations between pre-race and post-race measures, including countermovement jump (CMJ), Abalakov jump (ABK), upper body coordination and grip strength (CCUB), forced vital capacity (FVC), and forced expiratory volume (Fev1). The analysis was performed using a two-tailed significance level of \(p\) < 0.05. This approach allowed us to explore how pre-race performance indicators predicted post-race outcomes, providing deeper insight into the physiological responses of athletes during obstacle course racing.  
Finally, a linear regression analysis was conducted to assess the predictive power of pre-race physiological measures on post-race countermovement jump (CMJ) performance. The independent variables included pre-race CMJ, Abalakov jump (ABK), upper body coordination and grip strength (CCUB), forced vital capacity (FVC), forced expiratory volume (Fev1), and FER25. The dependent variable was post-race CMJ. The dataset was split into training (80%) and testing (20%) sets, and the model's goodness of fit was evaluated using R-squared. The regression coefficients were analyzed to determine the influence of each predictor on post-race performance.