esa-sceva/satcom-chunk-collection huggingface dataset:
# Digital Planning Technique for Surgical Guides for Prosthetic Implants before Orthodontic Treatment
## 1 Introduction  
In recent years, increasing numbers of adult patients have sought orthodontic treatment and expressed a desire for esthetic and comfortable alternatives to conventional fixed appliances [1]. Using digital models derived from polyvinylsiloxane impressions or oral scanning allows for computer-simulated treatment planning, which includes setting the treatment goal and designing the staging and auxiliary features [2, 3].  
However, many patients present some peculiarities, as they are often affected by periodontal disease and frequent tooth loss [4]. In the 21 st century, the use of digitalization allows clinicians to place dental implants in orthodontic patients treated with aligners at the beginning of their orthodontic treatment, instead of waiting until the end of orthodontictreatment, as it was done before. The transferal of the virtually planned implant into the patient's mouth can be performed using a surgical guide, which can be either constructed on a cast (the conventional manual method) or created virtually by means of computer software [5].  
Here, the authors present a digital workflow for aligner treatment supported by implants, and report two cases in which dental implants were placed at the beginning of orthodontic treatment using surgical guides made according to the computer-simulated orthodontic treatment plans.
# Electrospun Porous PDLLA Fiber Membrane Coated with nHA
###### Abstract  
Porous poly- D, L-lactic acid (PDLLA) electrospinningning fiber membrane was prepared, and nano-hydroxyapatite (nHA) was adsorbed and wrapped into it during the unique shrinking process of the PDLLA fiber membrane to fabricate the PDLLA/nHA composite membrane scaffold for tissue engineering. Compare with the composite fibers prepared by blend electrospinningning, most of nHA particles are observed to distribute on the surface of new type composite fibers, which could significantly improve the water wettability and induce the cellular adherence. FTIR analysis indicated that the PDLLA/nHA composite fibrous membrane was formed by physical adsorption. The combination was probed by scanning electron microscope, thermo-gravimetric, water contact angle and mechanical property analysis. It was proved that the nHA particles' content and distribution, surface wettability, modulus and tensile strength of PDLLA/nHA composite fibrous membrane were influenced by the concentration of nHA dispersion and pores on the PDLLA fiber surface. The 10.6 wt % PDLLA/nHA composite fibrous membrane exhibits a more balanced tensile strength (3.28 MPa) and surface wettability (with a water contact angle of 0\({}^{\circ}\)) of the composite mats. Scanning electron microscope and confocal laser scanning microscopy images of chondrocyte proliferation further showed that the composite scaffold is non-toxic. The adherence and proliferation of chondrocytes on the 10.6 wt % PDLLA/nHA fibrous membrane was significantly improved, compared with PDLLA mat. The 10.6 wt % PDLLA/nHA composite fibrous membrane has potential application value as scaffold material in tissue engineering.  
poly-D-L-lactic acid; hydroxyapatite; composite fibrous membrane; electrospinning; tissue engineering +
Footnote †: journal: Applied Physics Letters
## 2 Characterization and Modeling of the Fault Ride-Through Process in Doubly Fed Wind Turbines
### Structured Model of Electromechanical Transient of Doubly Fed Wind Turbine  
Structured modeling refers to the method of independent packaging and modeling of the main internal functional modules according to the system structure, in which each functional module is designed as an independent and reusable structural block, which can be directly combined with the required structural blocks, thus forming a complete system simulation model efficiently and flexibly. The structure of the doubly fed wind turbine electromechanical transient model is shown in Figure 3, which is divided into the primary circuit and control circuit. Moreover, the primary circuit consists of the generator, converter, filter, and transformer, and the control part mainly includes the following:(1) Mechanical side control and FM inertia control module;  
(2) Outer-loop optimal speed tracking control, constant power control, constant DC voltage control, and inner-loop current control module during regular operation;  
(3) A three-segment control module for the fault ride-through process when voltage disturbances occur in the grid.  
The control system of the doubly fed wind turbine electromechanical transient structured model adopts the adaptive switching strategy based on the voltage state of the grid point, and its operation mechanism can be described as follows: the mechanical side control module firstly calculates the generator rotor torque \(T_{\text{gen}}\) and rotational speed \(\omega_{\text{gen}}\) based on the input wind speed \(V_{\text{wind}}\), and at the same time, the voltage monitoring unit detects the voltage \(U_{\text{t}}\) of the grid point in real-time and generates the binary control signal (0 means normal, 1 means fault) based on whether or not the voltage is out of the rated range. After that, the system switches to the corresponding control module based on the signal and generates active/reactive reference values \(P_{\text{ref}}\), \(Q_{\text{ref}}\), and \(dq\)-axis current commands \(I^{\prime}_{\text{dref}}\) and \(I_{q\text{ref}}\) by integrally processing \(T_{\text{gen}}\), \(\omega_{\text{gen}}\), \(U_{\text{t}}\), and the voltage reference value \(U_{\text{ref}}\). Finally, through the converter's inner-loop current control and coordinate transformation, it outputs the equivalent controlled voltage source commands \(E_{\text{dp}}\) and \(E_{\text{qp}}\), thus realizing the dynamic regulation of the unit's output power and ensuring a fast power response capability during the power grid's transient process. The structured mathematical model of the electromechanical transient of the doubly fed wind turbine in this paper is based on the standardized modeling methodology of the China Electric Power Research Institute (CEPRI), which can be found in the PSD-ST Transient Stabilization Program user manual [46].  
Figure 3: Structured modeling of electromechanical transients in doubly fed wind turbines.
## 2 Project Overview  
### Geological Conditions  
Jinping II Hydropower Station is located at Yalong River, Liangshan Prefecture, Sichuan Province, where the hydroelectric resources are very abundant, as shown in Figure 1a. It is a landmark project to implement the national strategy of \"Western Development\" and \"West to East Power Transmission\" and to promote a new leap forward in Sichuan's economy. The station relies on the water flowing along the 150 km reach of Yalong River to generate electricity by using 310 m natural fall, as shown in Figure 1b. The total installed capacity is 4800 MW, and the annual average power generation can reach 24.23 TWh. In geology, the station is at the hilly area of the eastern Qinghai-Tibet Plateau, affected by the collision between the Eurasian plate and the Indian Ocean plate. In the deep hole drilling of this engineering, the phenomenon of rock cakes is found, which is unique in high geostress environment, and obviously shows an increase with burial depth. The engineering tunnel passes through hard rock strata such as marble, limestone and sandstone, and the strata from west to east is metamorphic medium to fine sandstone, lower Triassic (T\({}_{1}\)) chlorite schist, marble of the Zagunao group, upper Triassic (T\({}_{3}\)) marble, marble of the Baishan group (T\({}_{2b}\)) and marble of the Yantang (T\({}_{2y}\)) group. The bedding is parallel to the direction of the principal tectonic line and the faults all have a steep inclined angle, which can be divided into four structural groups in direction NNE (North-northeast), NNW (North-northwest), NE-NEE (Northeast- Northeastest) and NW-NWW (Northwest-Northwestwest), respectively. The tensile and torsional joints are mainly in the NNE and approximately EW (East-west) direction, as shown in Figure 1c. The burial depths of tunnels are in 1500-2000 m, with a maximum depth reaching 2525 m. The measured maximum geostress is 80 MPa, the uniaxial compressive strength of marble in the engineering area is 60 to 120 MPa. Therefore, the strength-stress ratio of rock mass reaches 0.75 to 1.5, which has met the conditions for strong and even extremely strong rockburst.  
In the construction of seven parallel tunnels of Jinping II Hydropower Station, the first one is the auxiliary tunnel A and B lines, then the drainage tunnel and four diversion tunnels are constructed. Auxiliary tunnels are constructed by drilling-blasting method, with an excavation diameter of 7.2 m and a gate-shaped excavation area of 45 m\({}^{2}\). The diversion tunnels are constructed by the tunnel boring machine (TBM) and the drilling-blasting method. The drilling-blasting part is adopted by the two-bench method, with a horseshoe-shaped section and an excavation diameter of 12.4 m. The excavation area of the upper bench is 110 m\({}^{2}\) and the lower bench is 60 m\({}^{2}\). The drainage tunnel is built between the auxiliary tunnel B and diversion tunnel 4 to discharge the gushing water safely and provide a transportation channel for the diversion tunnels. It is excavated with a full section TBM, with an excavation diameter of 7.2 m and a circular excavation area of 41 m\({}^{2}\).
# A Multilevel Road Alignment Model for Spatial-Query-by-Sketch
## 3 Materials and Methods
### Multilevel Road Classification  
The multilevel road model employed in the approach presented in this paper includes three levels: individual road, composite road, and road scene.  
1. A individual road refers to a road in a given location. For example, R0', R1', R2', and R3' are individual roads in the road network shown in Figure 1a.
2. A composite road contains two individual and intersected roads. For example, the yellow line composed of R0' and R1' is a composite road in the road network shown in Figure 1a.
3. A road scene represents the combination of all the roads in a given location. The green line composed of R0', R1', R2', and R3' in Figure 1a represents a road scene.  
First, the individual roads are extracted from a sketch map. Then, roads in sketch maps are aligned with those in a metric map progressively in three levels. In the first level, individual roads are compared between the sketch maps and the metric map, based on three characteristics: shape distance, number of critical turning points, and circulation direction. Next, according to the matching results of the individual roads and considering the first matching priority, composite roads from the sketch maps and metric map are matched in terms of the topological relationship among their characteristics, order of appearance along one intersection, and relative positions of the intersections. In the third level, road scene matching is performed with respect to (w.r.t.) the road with the second matching priority, characteristics' frequency for a matched road, intersection order along the road, and topological relation between the roads without matching priorities. The details are presented in the following subsections.  
The framework used for sketched road matching is illustrated in Figure 2.
# Physical Layer Authentication in Wireless Networks-Based Machine Learning Approaches
## 5 Analysis
#### 5.2.2 Review of Selected PLA Technique-based Channel Information
However, the authors also assumed that adversaries have the resources to change their antenna characteristics, transmitter RF path timing, and output power, and present reflectors between them and the receiver. For that, they implemented a discriminative model in the receiver, where adversaries were trained by a generative model that created authentic-looking CSI samples to defeat this scenario. For SNR \(\geq\) 10 dB, the discriminator achieved 100% accuracy against the accidental authentication testing dataset; for SNR \(<\) 10 dB, the discriminator incorrectly classified legitimate samples. The proposed method can enhance the security of industrial wireless networks without sacrificing communication resources. RQ3:What Are the Research Gaps in Wireless Network Security Based on Physical Layer Authentication Solutions? Despite extensive research attention, physical layer authentication for wireless security is still struggling for practical deployment due to several challenges. We identified and discussed what we discovered during the systematic review to enhance the PLA research community.
###### Abstract
RFECT [12; 13; 14; 15; 16] uses a probe consisting of an excitation coil and a measuring coil that can be inserted into a ferromagnetic heat pipe tube such as the water-cooled tubes. The magnetic energy generated by the interpolation type excitation coil goes from the excitation coil to the outside of the tube and flows in the axial direction, and then back to the inside from the remote field area at a certain distance. The measuring coil can sense the energy delivered without receiving it from the excitation coil. In order to increase the ratio of the signal to noise, it is necessary to increase the cross-sectional area and the number of turns of the excitation coil and the measurement coil so that the spatial resolution of the probe is low. Therefore, there is a limitation in quantitatively evaluating where the damage is occurring on the water-cooled wall tube, the weld, and the membrane. For further improvement of the sensitivity, a giant magnetoresistance (GMR) and Hall sensors were used to measure the low magnetic leakage signal in the MFLT systems [17; 18]. This method makes it possible to detect a defect on the surface and near the surface of the water-cooled wall tubes. However, it is still difficult to measure the thickness changes of the tube due to the damages. The combination of the ultrasonic and electromagnetic field has been developed in the electromagnetic acoustic transducer (EMAT) system for the inspection of the water-cooled tubes [19; 20]. The magneto-elastic phenomenon and Lorentz force help the EMAT inspect a deeper damage without the need for coupling material. However, the signal is weak and requires advanced signal processing circuits and algorithms. In addition, the EMAT probe has a big size, and thus, it is not efficient to build an array EMAT probe with a high spatial resolution for quantitative evaluation of damage sizes. This study proposed a combination of the magnetic flux leakage testing and ultrasonic testing methods for the efficient detection and quantitative evaluation of the depth and residual thickness distribution of the near-side and far-side corrosion of the water-cooled wall. A Hall sensor array probe with 48 elements arrayed in an interval of 2.5 mm was developed to detect the near-side damages and thus make it possible to evaluate the damage size. A flexible ultrasonic probe (FUP) was developed to detect the far-side damages on the tube, membrane, and welding lines of the water-cooled wall. The FUP was incorporated with a flexible membrane that allows the transmission of the ultrasonic wave from the probe to the water-cool tube surface efficiently. Thus, it is not required to largely supply coupling material during the inspection. In addition, the FUPs could be arrayed according to the water-cool plates for fast inspection. For the verification of the proposed method, artificial taper-type wears and slit-type damages with different sizes were produced on the tube, membrane, and welding lines of the water-cooled wall. Both the detection and size/depth evaluation of the damages will be discussed.
## Materials and Methods
### Reliability and Validity
#### Procedure of Scoring and Analyzing data  
The videos were independently assessed by three raters who underwent a DIS training session by the developer of the DIS (EM). Training consisted of definitions and video explanations on how to discriminate between dystonia and choreoathetosis in DCP. After the training session, the three raters independently scored ten training videos of the existing DIS to assess if they are reliable to score the DIMS videos (see Table A2).  
The videos of each powered mobility task (i.e., T1, T2, T3, T4 and T5) during the two measuring weeks (W1 and W2) were scored by the three raters independently. Kinovea motion analysis software, version 0.8.15 (Kinovea, Bordeaux, France) [19] was used to cut and view the videos. Both the dystonia and choreoathetosis subscale are evaluated for duration and amplitude in five body regions. All body regions are scored during the five powered mobility tasks. Summation of the region scores gives a total score for the DIMS-D subscale and DIMS-CA subscale, each with a range from 0 to 200. The total DIMS score is the sum of the DIMS-D and DIMS-CA subscale (range 0 to 400; see Figure 1). In the current study, missing values were only 4.2% of all collected data. To account for these missing values, the summed region and subscale scores were each separately converted into percentage scores relative to their maximum score. The maximum score was accordingly adjusted (i.e., decreased) for the region or subscale scores which had missing values.  
To assess the interrater reliability of the total scores of the DIMS, the DIMS-D and the DIMS-CA subscale, the scores of three raters were compared. First, all scores of W1 and W2 were converted into percentage scores. Then, the percentage scores of W1 and W2 for each rater were averaged and the obtained final score was used for the interrater reliability analysis.  
To determine test-retest reliability of the DIMS, the total score of the DIMS, DIMS-D, DIMS-CA and region scores were compared between W1 and W2. The final percentage scores used for this comparison were obtained by averaging the scores of all three raters.  
The internal consistency analysis was performed to assess the consistency of measuring the presence and severity of dystonia and choreoathetosis over time during powered mobility.  
For the concurrent validity, neck scores of the DIMS were compared with the neck scores of the DIS for two requested voluntary activities and one rest posture. In the DIS, the first neck requested voluntary activity is neck lateroflexion and the second neck requested voluntary activity is neck rotation. The arms scores (i.e., left proximal, left distal, right proximal and right distal) of the DIMS were compared with overflow movements (scoring the contralateral side of the arm which does the required activity [9]) and rest postures scores of the DIS. The DIS and the W1 data collection of the DIMS were administered during the same week, thereby only data of W1 was used for this analysis.
## 5 Sensor-Based Speech Recognition
### Speech Recognition Module  
The speech recognition module in this study is deeply optimized based on the Paraformer-zh-large architecture, and implements technical innovations in the following three aspects: firstly, a non-autoregressive (NAR) decoding strategy is adopted to improve the serial decoding process of the traditional ASR model into a parallelized one, so as to increase the inference speed by 3.8 times and achieve a real-time factor of 0.18 on the NVIDIA V100 GPU; secondly, the Dynamic Acoustic Compensation (DAC) mechanism is introduced, which dynamically adjusts the band weights of the Mel filter bank by analyzing the spectral characteristics of the noise collected from the acoustic sensors in real time through the LSTM network, and reduces the word error rate (WER) by 12.7% in the 75 dB noise environment. Finally, the Contextual Enhancement Module (CEM) is designed based on attentional gating, and the bidirectional Transformer encoder is utilized to capture cross-sentence semantic associations, effectively solving the long-distance homophonic ambiguity problem such as \"\(\bigtriangleup\)\". At the level of speech signal processing, the system adopts a multi-scale feature fusion preprocessing framework: firstly, it performs Adaptive Endpoint Detection (AED) on the input audio, and realizes accurate excision of mute segments based on the improved energy-entropy ratio algorithm to achieve an accuracy of 98.4% in extracting the effective speech segments; secondly, the system is implementedthrough perceptually weighted spectral subtraction (PSSS), which is a method of extracting the effective speech segments from the input audio. Combined with real-time noise spectral characteristics provided by acoustic sensors, a Time-Varying Spectral Mask (TVSM) is constructed, and the SNR is increased to 18.6 dB in the factory environment test. Then, the quiet segment is accurately excised based on an improved energy-entropy ratio algorithm, so that the effective speech segment extraction accuracy reaches 98.4%. Finally, Dynamic Range Compression (DRC) technology is used to nonlinearly map the speech signal, and adjustable Knee Point design is used to achieve the balance between weak speech component enhancement and strong interference component suppression. The processed speech signal is extracted by a Gammatone filter bank with 128-dimensional time-frequency features, and the effects of device differences are eliminated by Causal Normalization before inputting into the deep neural network.
# An Overview of Biopolymers for Drug Delivery Applications
## 2 Types of Biopolymers Used in Drug Delivery Systems  
Based on their origin, biodegradable polymers are classified into four major categories: (i) from biomass (agro-biopolymers), (ii) from microorganisms, (iii) from biotechnology, and (iv) from petrochemical products.  
Biopolymers obtained from biomass products, which are by far the most studied, consist of various compounds, such as polysaccharides [17], proteins of animal and vegetal origin [18; 19], and lipids [20; 21]. It is possible to create a large variety of biopolymers from natural sources such as agro-wastes, plants, animals, and microorganisms, including algae [22]. Biopolymers have been prepared from different agro-sources (e.g., bananas, rice, maize, corn, etc.), vegetable waste (e.g., from tomatoes, apples, pineapples, etc.), and animal sources (e.g., pigs, cattle, etc.) [23; 24]. The materials obtained from these products present elasticity, softness, and gel-like properties, combining the characteristics of a solid and fluid [25; 26].  
The features of biopolymers based on polysaccharides and proteins--such as their biodegradability, biocompatibility, low immunogenicity, and antibacterial activity--make them more interesting than synthetic ones [27].  
The selection of the biomaterial to be used for drug delivery is a very important step because of the potential toxicity of the products resulting from their degradation. For example, polysaccharides are known to have high biocompatibility and are non-toxic, although they are biodegradable by enzymes (e.g., guar gum is degraded in the human colon by enzymes of colonized bacteria), leading to different degradation byproducts whose biocompatibility needs to be understood assiduously before using them in DDSs [28].