esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Approach to Fall Detection Based on the Human Torso Motion Model
## 5 Conclusions  
In this paper, we proposed a new and fast fall detection method based on the Kinect sensor. A motion model named the human torso motion model (HTMM) is proposed. A new and significant feature named torso angle was firstly adopted in our approach for fall detection. Comparing with existing posture-based approaches, machine learning-based methods and wearable device-based approaches, our proposed approach has obvious advantages in privacy protection and fall-like activities' differentiation. Our method is time efficient and robust because of the calculation of only the changing rate of torso angle and centroid height. Moreover, the usage of only the Kinect sensor is inexpensive, affordable for common families and capable of being easily applied in the elderly person's home. However, compared to a monocular video camera, the limitation of the utilized Kinect sensor is the relatively narrow field-of-view. The best distance from the monitored person to the Kinect sensor should be within 7 m. Beyond this distance, the depth data become unreliable. Nevertheless, the Kinect-based approaches are still effective, efficient and widely used for fall detection.  
Although the Microsoft Kinect sensor v2.0 was launched in 2013 and is more powerful than its 1.0 version, Microsoft Kinect sensor v1.0 is sufficient for our proposed method because of the calculation of only two joints and the cost reduction. The mechanism of our proposed method is suitable for Kinect sensor 2.0, as well. In our future work, Kinect sensor 2.0, which is more sensitive than Kinect 1.0, will be adopted to collect depth images that contain more information for more possible improvement. Our fall detection model will be continuously improved by further importing other filters and other features to address exceptional situations.  
This research was supported by the National Natural Science Foundation of China under Grants 61762061 and 61662044 and the Natural Science Foundation of Jiangxi Province, China, under Grant 20161 ACB20004. All authors of the paper have made significant contributions to this work. [PERSON] led the project, directed and revised the paper writing. [PERSON] conceived of the idea of the work, wrote the manuscript and analyzed the experiment data. [PERSON] collected the original data of the experiment and participated in programming. The authors declare no conflict of interest.
# The Impact of Sulforapahane on Sex-Specific Conditions and Hormone Balance: A Comprehensive Review
## 5 Male Health
### Sperm Health and Testicular Damage
#### 5.1.1 Toxicities Associated with Diet and Environmental Exposures  
A variety of environmental stresses cause reductions in fertility and have been examined from the perspective of sperm and testicular health. Prime among them are metal (aluminum and cadmium) exposures and pesticides and plasticizers. The effects of SF in counteracting some of these toxicities has been evaluated.  
Aluminum-induced oxidative stress alterations in sperm characterization and testicular histomorphometry of rats were reported after 4 weeks of daily gavage with SF [105]. Testicular histoarchitecture (the macro- and microstructure of the tissue) was normalized by SF treatment compared to control animals, as was semiiferous tubule shrinkage, spermatogenesis disruption, lipid peroxidation, and hormone and antioxidant status.  
SF prevented testicular damage in cadmium-exposed mice via activation of the Nrf2 pathway and thus resulted in less degradation in sperm quality, as well as improvement in a variety of relevant biomarkers, e.g., serum testosterone, antioxidant levels, and expression of genes for glutathione peroxidase (GSH-Px), gamma glutamyl cysteine synthetase (g-GCS), heme oxygenase-1 (HO-1), and NAD(P)H:quinone oxidoreductase-1 (NQO1) [106]. Separately, protective effects against cadmium toxicity were shown in the testes and prostate tissues of rats [107].  
SF reversed ferroptosis and reversed or attenuated oligospermia (reduced sperm count) in mice via Nrf2 activation [108]. Di-2-ethylhexyl phthalate (DEHP; a common plasticizer) induced testicular injury by ferroptosis and those effects were reduced by SF, also via the Nrf2 pathway, in rats [109]. Di-n-butylphthalate (DBP; a common human endocrine disrupter) induced testicular oxidative stress injury, which was reduced via Nrf2 activation in mice [110]. In mouse in testicular Leydig cells, SF-ameliorated oxidative stress was induced by DBP via Nrf2 induction--this was manifest by the enhanced activity of stress related genes, cell proliferation, and testosterone secretion [111].  
SF supplementation significantly ameliorated multiple obesity-related effects on the reproductive systems of male mice that were induced by a high-fat diet. These effects included reduced testes weights, epididymis weights, sperm counts, sperm motility, and testosterone levels and increased leptin and estradiol [43]. In a separate study, subcutaneously injected SF attenuated a range of spermatogenic deficiencies (e.g., sperm viability and mobility) in mice fed a high fat diet [112].
# A Symbolic Encapsulation Point as Tool for 5G Wideband Channel Cross-Layer Modeling
## 3 Methods Applied
### Propagation Deterministic Mechanism
From link budget theory, supposing a small area and isotropic point scatterers of the same radar cross-section, we calculate contributions of each scatterer normalized with respect to direct path \(d_{DP}\) and denoting a transmitter-scatterer path with \(d_{TSc}\) and scatterer-receiver path with \(d_{SCR}\),  
\[c_{i}=\frac{d_{DP}}{d_{TSc}}\frac{1}{d_{SCR}} \tag{6}\]  
and hence, denoting overall receiving signal amplitude with \(a_{i}\), calculate it according to free-space power decay law  
\[\sum_{i}a_{i}^{2}=10^{P_{r}/10} \tag{7}\]  
where \(P_{r}\) is received power attenuated relative to transmission power \(P_{t}\) (link budget calculation). \[P_{r}=P_{t}-10\cdot log\ c_{i}^{2} \tag{8}\]  
Figure 2: Description of small-scale fading analysis: (**a**) small area; (**b**) level-crossing rate (LCR) and average fade duration (AFD) definition. This way, the narrowband channel model was built up, leading to deterministic expression of receiving complex envelope term  
\[x_{RF}(t)=Re\Big{[}x_{CE}(t)e^{j2\pi f_{0}t}\Big{]} \tag{1}\]0  
Hence, observing the small area from Figure 2a, for single (measurement) point \(x[n]\) of summary \(N_{samples}\) samples, introducing scattering amplitude contribution vector \(\mathbf{a}\) and distance path (T-Sc-R) vector \(\mathbf{d}[n]\), the received narrowband signal vector for our deterministic model is constituted  
\[x_{RF}(t)=Re\Big{[}x_{CE}(t)e^{j2\pi f_{0}t}\Big{]} \tag{1}\]1  
where \(n=1,\dots,\)\(N_{SC}\) and \(N_{SC}\) denotes number of scatterers. Now, by vector concatenation, a suitable matrix for the received complex envelope \(r\) of dimensions \(N_{SC}\times N_{samples}\) is composed for the entire small area. In Figure 2b and further, the magnitude is normalized with reference to root mean square (RMS) value.
## 4 Performance Evaluation of Mixed Plc-Fso System  
### Outage Probability Analysis  
The outage probability can be defined as the probability that the end-to-end SNR \(\gamma_{e}\), has a value smaller than a certain specified threshold, \(\gamma_{th}\). It is well-known that when the instantaneous SNR \(\gamma_{e}<\gamma_{th}\), the communication system undergoes the outage state, in which the received SNR \(\gamma_{e}\) can not support the target rate of the system. For the proposed mixed PLC-FSO system with DF relaying, an exact closed-form analytic expression for the outage probability can be represented as [4]  
\[p^{\text{out}}(\gamma_{th})=\Pr[\gamma_{e}<\gamma_{th}]=F_{\gamma_{e}}(\gamma_ {th}). \tag{12}\]
# NeuChain+: A Sharding Permissioned Blockchain System with Ordering-Free Consensus
## 2 Background and Motivation
### OEV Architecture
When executing transactions accessing multiple shards, the execution time of each round increases. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**System** & **Architecture** & **Consensus** & \begin{tabular}{c} **Shard** \\ **Fault** \\ \end{tabular} & \begin{tabular}{c} **Total** \\ **Fault** \\ \end{tabular} & \begin{tabular}{c} **Ledger Model** \\ \end{tabular} & \begin{tabular}{c} **State** \\ **Sharding** \\ \end{tabular} & \begin{tabular}{c} **Cross-Shard** \\ **Transaction** \\ \end{tabular} & \begin{tabular}{c} **Throughput** \\ \end{tabular} & **Latency** \\ \hline Elastico & OEV & PBFT & 33\% & 25\% & UTXO & False & - & 48 kTPS & 800 s \\ OmniLedger & OEV & ByzCoinX & 33\% & 25\% & UTXO & True & 2 PC & \textgreater{}100 kTPS & 1.38 s \\ Rapidchain & OEV & 50\%BFT & 50\% & 33\% & UTXO & True & 2 PC & 7.3 kTPS & 8 s \\ Chainspace & OEV & \begin{tabular}{c} MOD- \\ SmaR \\ \end{tabular} & 33\% & 25\% & Object & True & 2 PC & 350 TPS & 0.1 s \\ Monoxide & OEV & Chu-ko-mu & 33\% & 50\% & Account/balance & True & \begin{tabular}{c} Eventual \\ atomicity \\ \end{tabular} & 11.7 kTPS & 15 s \\ ByShard & OEV & PBFT & 33\% & 33\% & UTXO & True & 2 PC & 20 kTPS & 1 s \\ Meepo & OEV & PoA [40] & 33\% & 25\% & Account/balance & True & \begin{tabular}{c} cross-spec and \\ cross-call \\ \end{tabular} & 124.6 kTPS & 0.52 s \\ BrokerChain & OEV & PBFT & 33\% & 33\% & Account/balance & True & \begin{tabular}{c} Broker \\ Reconnaissance \\ coalition \\ \end{tabular} & 3 kTPS & 14.9 s \\ PROPHET & OEV & PBFT & 33\% & 33\% & Account/balance & True & \
\begin{tabular}{c} Reconnaissance \\ coalition \\ \end{tabular} & 1.2 kTPS & 2.5 s \\ AHL [31] & EOV & AHL & 33\% & 33\% &
\begin{tabular}{c} General \\ workload \\ \end{tabular} & True & 2 PC & 3 kTPS & 18 s \\ \hline NeuChain & EV & PBFT Raft & - & 33\% & Account/balance & - & - & 85.7 kTPS & 0.14 s \\ NeuChain+ & EV & PBFT Raft & 33\% & 33\% & Account/balance & True & Cross-reserve & 247 kTPS & 0.19 s \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comprehensive comparison of blockchain systems. Moreover, if transactions abort during contract execution, the entire block must be rolled back and re-executed, incurring significant overhead. PROPHET [39] proposes a deterministic ordering algorithm for Byzantine fault-tolerant consensus to handle cross-shard transactions, which is close to our work. It deterministically assigns a global order to transactions based on pre-execution results, thereby eliminating transaction conflicts. However, it requires a costly pre-execution phase that still requires multiple rounds of coordination between shards to generate transaction read-write sets. Furthermore, it still maintains an explicit ordering phase.
## 3 5G Technology Enablers for V2X Use Cases
### The Evolution of V2X Communications
#### 3.1.7 3 GPP Releases 19 and 20--Beyond 5G  
The roadmap of 5G-Advanced (or beyond 5G) continues with Release 19 and Release 20 by the 3 GPP. Nevertheless, in line with that, ETSI [77], ITU [67], and the 5 GIA (5G Infrastructure Association) [118] are placing their recommendations as well.  
The actual initial discussions on the concrete content of 3 GPP Release 19 officially began in April 2023, with an anticipated completion of R19 specifications by December 2025 [78]. The actual 3 GPP Work Items that are under discussion by the standardization working groups are listed in [79]. Current items include network sharing aspects, integratedsensing and communication, localized mobile metaverse services, studies of satellite access (phase 3) and UAV (phase 3), energy efficiency, the network of service robots with ambient intelligence, interworking with non-3 GPP networks, multi-path relay, and more.  
Such a detailed work-plan does not yet exist for Release 20--which is in the research phase. Hence, standardization details are non-existent. The same applies to Release 21--the first actual 3 GPP 6G release--which is in its vision and requirements phases for 2023. Still, beyond 5G and 6G is an active research area, as they are expected to solve issues and cover demands already envisioned.
## 4 Simulation Results and Discussion
### Performance Comparison of the KPIs  
Using the results given in Figures 8 and 11 and the KPI values captured in Tables 6-9, we summarize our critical results demonstrated in earlier simulations when using brute-force techniques with/without ICIC optimization for different clustered distributions of GUEs in AG-HetNet.  
From the simulation results given in Figures 9 and 12, we observe reduced power FeICIC in Release-11, which is observed to outperform Release-10 eICIC and without any ICIC, in terms of the overall 5 pSE and coverage probability of the AG-HetNet. Further inspection reveals that the peak values of 5 pSE and coverage probability are observed when fewer MBSs are destroyed. Also, the 5 pSE and coverage probability is higher when more UABSs are deployed.  
performance evaluation of the wireless network. Thus, in the future, critical aspects under consideration include
* Considering the UABS deployment's height variation and mobility in the coordinate system. However, as the deployment height increases, LOS also increases and, in turn, increases the interference at the users located in the cell edge or in the range-expanded regions of small cells. The future system model would be tuned to consider this impact of LOS and interference.
* Considering a multi-tier AG-HetNet with fixed terrestrial cells such as macro-cells and pico-cells and UABSs as aerial small-cells.
* Determining suitable machine learning algorithms for achieving the best performance of the AG-HetNet. However, the complexity of simulating any machine learning algorithm depends on the optimization dimension, the population size, and the cost of the objective function. Therefore, also define a strategy for joint optimization of the wireless network resource scheduling and UABS placement while evaluating the KPIs.
# A 3D Printed Membrane-Based Gas Microflow Regulator for On-Chip Cell Culture  
[PERSON]  
1 Faculty of Microsystems Electronics and Photonics, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland; [EMAIL_ADDRESS] (R.W.); [EMAIL_ADDRESS] (J.D.)1 Faculty of Microsystems Electronics and Photonics, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland; rafal.walczak@pwr.  
is proposed. The device may be applied to deliver gaseous media to polymer microfluidic systems, such as PDMS or glass lab-on-a-chips, as shown in this work. It is suitable to generate bubbles in the liquid medium, which, once nourished, are directed to the cell cultures-on-chip. The regulator controls the specified flow rate of the medium, before it is delivered to the lab-on-a-chip. The microfluidic system does not require improvements in its structure, since the flow adjustment is provided at the level of the regulator.  
In this work, the device was used to deliver gaseous media to the microchannels of the all-glass lab-on-a-chip to achieve a long-term culture of _Euglena gracilis_.  
The working principle of the regulator is based on the well-known phenomenon of gas permeation in thin membranes of silicon elastomers, i.e., PDMS [20; 21]. The authors investigated PDMS in a recently published article [22], concerning a lab-on-a-chip bioreactor for the biochemical energy cascade of microorganisms. The knowledge acquired during the aforementioned study enabled us to propose a novel construction for the regulator, utilizing interesting features of PDMS, i.e., permeability. The permeability value (\(P\)), in most of the applications, can be defined by the Formula (1) [23; 24; 25].  
\[P=\frac{v\times\delta}{A\times t\times(p_{1}-p_{0})} \tag{1}\]  
where:  
\(v\) is the volume of gas penetrating the membrane,  
\(\delta\) is the membrane thickness,  
\(A\) is the surface area of the membrane,  
\(t\) is the time,  
\(p_{1}\) is the input pressure,  
\(p_{0}\) is the output pressure.  
On the basis of the given Equation (1), the flow value may be derived (2), which, basically, depends solely on the pressure difference and parameters of the membrane, including its material type.  
\[\frac{v}{t}=\frac{P\times A\times(p_{1}-p_{0})}{\delta} \tag{2}\]  
In our concept, the gaseous medium under pressure \(p_{1}\) permeates through the membrane and reaches the lab-on-a-chip under pressure \(p_{0}\), being approximately equal to the atmospheric pressure (Figure 1). The flow rate--for the fixed construction of the regulator--changes linearly with the pressure, the membrane surface, and its permeability, and is inversely proportional to the membrane thickness.  
Figure 1: Concept of flow regulation in the 3D printed membrane-based gas microflow regulator. PDMS: polydimethylosiloxane.
# Coastal Wind Measurements Using a Single Scanning LiDAR
## 2 Materials and Methods  
### Experimental Setup  
The measurement campaign was conducted from January to September 2019 at the Hazaki Oceanographic Research Station (HORS) [23]. The HORS is located at the coastline of the Pacific Ocean in Ibaraki prefecture, Japan. This region has a rectilinear coastline running from 150\({}^{\circ}\) to 330\({}^{\circ}\) and is surrounded by flat terrain with mixed vegetation. Figure 1 shows the instruments used in the study and the positions on the HORS pier where they were placed. The pier is 427 m long and at a height of 7 m above sea level (ASL). As 1.5 MW wind turbines with a hub height of 64.5 m and a rotor diameter of 62 m align along the coast, the winds on the pier at a wind direction of approximately 207\({}^{\circ}\) are directly influenced by the wind turbine wake. Detailed wind conditions on the HORS research platform can be found in [PERSON] et al. (2018) [7].  
Table 1 summarizes the list of the measurement devices used in this study. The scanning LiDAR (Windcube 100s, hereafter referred to as the 100s) was deployed on the roof of a 3.5-m-high observational facility located at the landward end of the HORS pier. The dimensions of the scanning LiDAR were approximately 0.8 m \(\times\) 1.0 m \(\times\) 1.2 m and it weighed 235 kg. This LiDAR had a measurement range from 50 to 3000 m, with a horizontal resolution, which can be set between 25 and 100 m. Further specifications of the 100s are available on the manufacturer's website [9]. For validation of the wind speeds and directions obtained from the 100s, the offshore measurements from a sonic anemometer (hereafter referred to as SA) and a vertical profiling LiDAR (Windcube V1, hereafter referred to as V1) installed at the seaside end of the pier were used. The measurements from the V1 were mainly used for the validation of the 10-minute mean wind speeds, while those from the sonic anemometer (SA) were used to assess the accuracy of the turbulence intensity (TI) measurements.  
Figure 1: Experimental setup.
# Transparent Task Delegation in Multi-Agent Systems Using the QuAD-V Framework
## 1 Introduction
In particular, the explanations about the agents' decisions are generated based on the quantitative argumentation with votes framework (QuAD-V) [31]. Such a framework is based on _bipolar argumentation frameworks_ (BAFs) [32], which are more expressive than AAF as they better capture dialectical relationships by considering both attacks and supports between arguments. QuAD-V offers a good balance between simplicity and expressiveness, as it can be modeled as a directed graph with two types of relations, without requiring defeasible logic or complex grammars. Additionally, QuAD-V is particularly suitable for scenarios that require explainability and human participation in decision-making. In our case, the QuAD-V framework is used to address the problem of task delegation, where multiple delegators vote for the best partners based on their behavior. These features make our model transparent, as it provides clear justifications for agent decisions. Its straightforward design ensures high reproducibility and easy replication. Furthermore, the model is adaptable to different contexts by adjusting argument structures, maintaining its explanatory power across various delegation scenarios. These features (transparency, reproducibility, and adaptability) distinguish our model apart from existing delegation approaches. To validate the effectiveness of the model, we simulate a scenario involving the distribution of petroleum products via pipelines. In this scenario, the pipeline network is modeled as a series of delegation chains, where intermediate agents represent temporary storage bases that facilitate the transportation of products from one point to another within the network. In this context, the QuAD-V framework is adopted to generate explanations at two levels: **locally**, by explaining the reasoning behind an individual agent's decision, and **globally**, by justifying why a particular delegation route is optimal given the selected partners. Our results demonstrate that the proposed model not only enhances partner selection by allowing delegators to identify partners with high success rates, low rejection rates, and the ability to make accurate performance estimations, but also provides comprehensible explanations for the agents' decisions, making the decision-making process more interpretable and trustworthy. The remainder of this paper is structured as follows: Section 2 presents the basic concepts adopted in this work. Section 3 presents our proposed model, detailing the integration of the QuAD-V framework. Section 4 describes the experimental setup. Section 5 analyzes the results, highlighting the advantages of our approach. Finally, Section 6 concludes the paper and outlines future research directions.