Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and characterization of ethylcellulose microspheres for sustained-release of pregabalin

Background and purpose: Pregabalin is used in the treatment of epilepsy, chronic pain, and other psychological disorders. Preparation of pregabalin in the sustained-release formulation will enhance patient compliance and reduce the incidence of side effects. The aim of this study was to prepare sustained-release microspheres for pregabalin utilizing ethylcellulose and evaluate the processing factors that influence the fabrication and the performance of the prepared microspheres. Experimental approach: The microspheres were prepared using the water-oil-oil double emulsion solvent evaporation method. Microspheres were characterized for particle size, encapsulation efficiency, and in vitro drug release. The influence of the processing variables on the characteristics of the prepared microspheres was studied. Microspheres solid-state characterization performed using differential scanning calorimetry, Fourier transform infrared spectroscopy and scanning electron microscopy. Findings/Results: The results described in the context of the current work illustrated the suitability of the water-oil-oil system in the preparation of sustained-release microspheres for pregabalin. The optimum formulation was prepared at a drug to polymer ratio of 1:3 w/w, stirring speed of 600 rpm, surfactant concentration of 1.5%, and external phase volume of 150 mL. This formula produced microspheres particle size in the range 600-1000 μm, with 87.6% yield, and 80.14 ± 0.53% encapsulation efficiency. Drug release from the microspheres was found to be diffusion controlled, with a pH-independent behavior. Conclusion and implication The current work presented a successful attempt to fabricate a sustained-release microsphere comprising pregabalin. This will help overcome the frequent dosing problems with conventional pregabalin dosage forms and improve product performance.
Torsion–Vibration–Rotation Interactions in Methanol. I. Millimeter Wave Spectrum

In a study of internal rotation in methanol, the millimeter wave spectra of CH3OH, CD3OH, and CH3OD have been investigated between 90 and 200 Gc/sec. In the analysis of the spectra, torsion–vibration–rotation interactions were treated as adjustable parameters in semiempirical formulas. Kivelson's formula for a‐type ΔK = 0 transitions was tested over a wide range of quantum numbers. It reproduced the CH3OH and CD3OH spectra quite well, but the approximations used in the calculations appear to start breaking down for the larger asymmetry of CH3OD. For assignment of b‐type ΔK = ± 1 transitions, a method was developed based on the wide spectral range of the millimeter wave spectrometer. Sufficient b‐type data were obtained for CH3OH to permit a test of Kirtman's formula for origins of Q branches. Convergence difficulties in the Q‐branch least‐squares fit prompted a re‐examination of the theory, which revealed an interesting linear relation coupling six of the parameters. This relation shows that for any molec.
Inverting peripheral hyperopic defocus into myopic defocus among myopic schoolchildren using addition power of multifocal contact lens

PURPOSE: The purpose was to determine the minimum near-addition power needed using Proclear® multifocal D-Design contact lens (adds: +1.50 D, +2.50 D, +3.00 D, and +3.50 D) to invert the pattern of relative hyperopic defocus in the peripheral retina into relative myopic defocus among the eyes of myopic schoolchildren. METHODS: Twenty-seven right eyes (24 females and 3 males) of 27 myopic schoolchildren aged between 13 and 15 years were included in this study. The measurements of central refraction, peripheral refraction (between 35° temporal and 35° nasal visual field in 5° steps), and lag of accommodation were conducted using the Grand-Seiko WR-5100K open-field autorefractometer initially without correction (WC), followed by with correction using four different addition powers of Proclear® multifocal D-Design contact lens in random sequence. Axial length was measured using a handheld probe ultrasound A-scan (Tomey AL-2000). RESULTS: The relative peripheral refractive error showed high hyperopic defocus of +1.08 ± 1.24 D at 35° nasal and +1.06 ± 1.06 D at 35° temporal visual field WC. All Proclear multifocal contact lenses (MFCLs) decreased the peripheral hyperopic defocus with increasing addition powers (F [2.938, 47.001] = 13.317, P < 0.001). However, only +3.00 D addition and +3.50 D addition (P = 0.001) could invert the peripheral hyperopic defocus into peripheral myopic defocus. Apart from that, the +3.00 D addition lens showed the lowest lag of accommodation (+1.10 ± 0.83 D) among the other MFCL adds (P = 0.002). CONCLUSION: A +3.00 D addition Proclear MFCL is the optimal addition power that can invert the pattern of peripheral hyperopic defocus into myopic defocus.
Long latency reflexes in patients with postural instability and ataxia

Objectives: Distal electrical stimulation of an upper extremity mixed nerve can generate a reflex response from the trapezius muscle. This reflex response may have a central neural pathway and can be affected by postural changes. Materials and Methods: In this study, long latency reflexes (LLRs) from both distal and trapezius muscle were evaluated in patients with Parkinson's disease (PD) with and without postural dysfunction and in patients with cerebellar ataxias. Thirty-three patients with PD, 10 patients with degenerative cerebellar ataxia and 22 healthy volunteers were included in the study. LLRs were recorded from ipsilateral thenar and trapezius muscles. Latencies and amplitudes of LLRs obtained from thenar (thenar LLR) and trapezius (trapezius LLR) muscles were analyzed. Results: In patients with PD, thenar LLRs showed significant shortening in the onset latencies and significant increase in the amplitudes in comparison with healthy controls. Trapezius LLRs did not show any significant difference in latencies or amplitudes; however, these responses showed a significant absence in one or two components in patients with Parkinson's disease with postural dysfunction. Additionally, this reflex was not recorded in patients with cerebellar ataxia. Conclusion: Trapezius LLRs can give some information regarding the physiology of neural circuits responsible for postural arrangement. Cerebellar connections may have a major role in the generation of trapezius LLRs.
Adaptable Switch: A Heterogeneous Switch Architecture for Network-Centric Computing

Network-centric computing offloads and disaggregates computing and data processing from CPU to network in order to support growing throughput, big data volume, and information complexity in data centers. An emerging paradigm is employing SmartNIC for network-centric computing, which introduces user-specific processing at a host's network interface. In this article, we take this initiative further to tackle current proprietary processing and computing issues in the network core: the switches. We propose a new hardware architecture called adaptable switch. Based on testing of its prototype empowering three use cases, we demonstrate that both high throughput and processing flexibility can be achieved simultaneously on an adaptable switch.
Sentimental Analysis of News Headlines for Stock Market

Predicting the stock market is like one of the most common things one does. Predicting exact value is like a futile attempt but one thing is sure we can know the trend or so called the direction in which the price of the stock will move. The stock market is driven by a lot of factors and the majority of them are in the form of news articles. The impact of news on stocks is quite significant. The direction of stock price will be dictated by the sentiments of the market participants. The sentimental analysis is no new topic people have been doing it for quite a long time by implementing several models. In our research paper, we are comparing the results from different models under the same circumstances and concluding which one of the compared models is better based on their accuracy. The methods that we have used for comparison are K-Mean clustering, Naive Bayes, and Support Vector Machine. In our experimental study for sentimental analysis for news headlines, we found that Support Vector Machine and Naive Bayes have better accuracy than K-Means clustering.
Graph Grouping Loss for Metric Learning of Face Image Representations

This paper proposes Graph Grouping (GG) loss for metric learning and its application to face verification. GG loss predisposes image embeddings of the same identity to be close to each other, and those of different identities to be far from each other by constructing and optimizing graphs representing the relation between images. Further, to reduce the computational cost, we propose an efficient way to compute GG loss for cases where embeddings are L2 normalized. In experiments, we demonstrate the effectiveness of the proposed method for face verification on the VoxCeleb dataset. The results show that the proposed GG loss outperforms conventional losses for metric learning.
Cyber-Physical Model for the Internet of Energy Technology Testing

The key foothold for the economic leap is energy sphere. Despite the trend towards the gradual introduction of convergent technologies into production, the traditional raw material model remains the main development sector and at the same time one of the weaknesses of the economy. The global energy market is volatile and strongly influenced by the extraction of natural resources. It needs diversification. An alternative technology, independent of the actions of major players, an "airbag" could make it possible to maneuver quickly the available tools of the material and technical base. That also male possible to maintain the fuel and energy balance. Strategic plans provide for the implementation of initiatives that respond to external challenges for the Russian energy sector. Such as worthy global market competition. These plans also respond to internal challenges like a deep comprehensive modernization of the fuel and energy complex. The cross-sectoral "roadmap" of Russia identifies priority areas for reducing losses in the electric power system (EPS) and increasing the reliability of its operation. Among these priorities the architecture of the Internet of energy or a decentralized EPS appears [2] .
An internet of things based transportation cart for smart construction site

The use of the Internet of Things technology in construction industry supply chain can optimize the construction enterprise's internal process, reduce waste and uncertainty and promote the construction enterprise's profit maximization. This paper involves the development of a sensor-based conveying aid in the form of a smart moving cart for material transport and environment sensing. The cart is equipped with a weight sensor for weight detection and extended with various sensors for environment monitoring and a camera for object recognition using machine learning. The data is geolocalized by means of an Ultra-Wideband based positioning system with Kalman Filtering. The position and sensor data are transmitted using the LoRa radio technology and stored in a cloud server.
Easily Fabricatable Shell Gripper for Packaging Multiple Cucumbers Simultaneously

Soft robot grippers have been investigated for handling different types of objects and have been applied in various applications. However, the fabrication of soft robots usually involves molding and demolding processes and it is time consuming. In this paper, we propose a pneumatic shell gripper which can be easily fabricated without demolding process and its thickness was minimized for the purpose of packaging multiple cucumbers simultaneously. The shell gripper includes multiple gripping units and each unit consists of two flat fingers configured in a parallel pattern. Each finger has a hybrid structure combining a rigid shell and a soft membrane. The membrane can be pneumatically inflated and therefore can be used to grasp objects. Inflation tests on the hybrid finger showed that the new fabrication method can provide similar inflated deformation to the fingers compared with the conventional method. Moreover, the new method yields less individual differences among fingers due to the less manual process. Durability was tested for the new fabrication method and the finger is not ruptured after 100,000 circles. Finally, tests on packaging multiple cucumbers were conducted and results demonstrated the ability and advantages of the shell gripper.
Assessment of a Grism- Based Spectrometer Design for Neurotransmitter Detection

Neurotransmitter sensing is currently a challenge in biomedical research, and optoelectronic sensing may play an important role in this field. In particular, miniature visible-light photo-spectrometers can be very useful for molecular detection. In this respect, this work evaluates a new type of spectrometer geometry based on the grism, or grating-prism, which combines an optical grating and an optical prism. The system was first designed in either transmission or reflection geometry, and then adapted to fit commercially available components so that a prototype could be fabricated in the laboratory. The comparison with a more conventional approach shows that the grism-based spectrometer offers superior resolution as well as a smaller footprint.
Design and Simulation of High Efficient Accuracy Adder Based on SARA

Adders and multipliers are the simple units applied in signal preparation. Hence, its designation and engineering will typically affect the deployment of signal preparing devices. Moreover, the adders and multipliers are independently streamlined to enhance the presentation of the signal preparing gadgets. In the extra part of the sign handling gadgets, adders are trailed by using multipliers, and henceforth the snake multiplier gadgets are shaped. The 16 bit Adder recoding method converts the contributions that are ought to be legitimately introduced to adjust the stall shape is briefly discussed in this paper. A snake multiplierunit is propsoed here to enhance its speed. Furthermore, the number juggling responsibilities will anticipate a widespread element in automated circuit configurations like adders, multipliers, and so forth. Augmentation is a vast essential range-crunching hobby in superior frameworks. For instance, chip and superior signal processors circuits. Usage of multipliers with blower circuit over the standard adders will lessen the number of levels of expansion, with the intention to decrease the inertness of multiplier. Furthermore, the multipliermodule will be probably considered as the fundamental piece of Multiplier-Accumulator unit plan. Blower is primarily based on the multipliers in MAC engineering configuration. In addition, a postponement versatile self-layout strategy is proposed to improve the exactness and reduce the power loss.
A Marked Point Process Model For Visual Perceptual Groups Extraction

Perceptual organization is the process of assigning each part of a scene to a specified association of features to be a part of the same organization. In the twenty century, Gestalt psychologists formalized how image features tend to be grouped by giving a set of organizing principles. In this paper, we propose an approach for the detection of perceptual groups in an image. We are mainly interested in features grouped by the proximity law of Gestalt. We conceive an object-based model within a stochastic framework using a marked point process (MPP). We use a Bayesian learning method to extract perceptual groups in a scene. The proposed model tested on synthetic images proves the efficient detection of perceptual groups in noisy images.
Low-Power Implementation of a High-Throughput Multi-core AES Encryption Architecture

Nowadays, the Internet of Things (IoT) has been a focus of research that improves and optimizes our daily life based on intelligent sensors and smart objects working together. Thanks to Internet Protocol connectivity, devices can be connected to the Internet, thus allowing them to be read, controlled, and managed at any time and at any place. Security and privacy are the key issues for deploying IoT applications, and still face some enormous challenges; especially, for devices that require high throughput and low latency as IoT cameras, IoT gateways, high-quality video conferencing systems… In this paper, we proposed a 10-cores AES hardware architecture to achieve high throughput. These cores shared KeyExpansion Block so this architecture has high efficiency in term of area and power consumption. Fully parallel, outer round pipeline technique is also used to achieve low latency. The design has been modelled in RTL VHDL and then synthesized with a 45nm CMOS technology using Synopsys Design Compiler. On the other hand, clock gating technique is used to save power consumption. We use PrimeTime tool (Synopsys) to estimate the power consumption. Implementation results show that the proposed architecture achieves a throughput of 853.8 Gbps at the maximum operating frequency of 667 MHz and clock gating technique allows more power savings.
A 58 nW ± 35 ppm/°C Oscillator for IoT Battery-less Sensor Applications

We present in this paper a battery-less sensor structure with energy harvesting in which an antenna is used for both collecting the RF signals and as a sensing element. Also, an ultra-low-power oscillator with low sensitivity to temperature variations has been designed to generate a clock signal for the proper operation of the proposed sensor design. This oscillator is intended for ultra-low power and low-frequency applications. It consumes only 58 nW of power from a 1 V supply while occupying 190 μm x 120 μm of silicon area. In addition, it shows temperature sensitivity of ± 35 ppm/°C over temperatures ranging from −40 to 85 °C. The proposed structure has been designed and simulated with a 0.18 μm standard CMOS technology. The proper functionality of the presented design has been validated through post-layout simulation results.
Using Fully Connected and Convolutional Net for GAN-Based Face Swapping

The lifelike results of using face swapping have contributed greatly to the research in computer vision. In this work, we extend the architecture of faceswap-GAN in order to obtain more natural results compared to the original framework. In the original architecture, the self-attention module usually converts the facial features from a source face to the target face with artificial distortion around the facial features. We use a structure of fully connected convolutional layers as a discriminator to approach the problem. The outcome can be smoother and more natural perceptually compared to the results using the original faceswap-GAN.
Analysis of Opamp Non-Idealities in Quadrature Bandpass Sigma-Delta Modulators

The performance of continuous-time ΣΔ modulators dramatically depends on the non-idealities of operational amplifiers (opamps) used within the loop filter. In this paper, the limitations stemming from the opamps regarding the loop filter transfer function (TF) as well as the Noise-Transfer-Function (NTF) are studied. By evoking the impulse-invariant transform a derivation of the non-ideal NTF prior to lengthy simulations is possible, enabling a pre-design study of the NTF's pole and zero placement affected by the opamps non-idealities. Based on the pre-design study precise settings for the opamps can be found without the need for time-consuming simulations on the circuit level. Furthermore, the developed mathematical model can also be utilized for top-level verification.
Comparing Pixel-Based Random Forest and the Object-Based Support Vector Machine Approaches to Map the Quasi-Circular Vegetation Patches Using Individual Seasonal Fused GF-1 Imagery

The seasonal effect on land cover classification has been widely recognized. It is important to use the imagery acquired at key points of vegetation phenological development to obtain a higher classification accuracy for land cover. This study compared the effect of seasons on landscape classification and the quasi-circular vegetation patches (QVPs) detection from four fused Gaofen 1 images acquired in the different seasons by using the pixel-based random forest (RF) and object-based support vector machine (SVM) methods over the Yellow River Delta, China. The results from this study demonstrated that the seasonal effect on classifying landscapes and detecting the QVPs is significant, especially for the pixel-based RF method. The object-based SVM method was more appropriate for classifying landscape from the non-growing season images, while the pixel-based RF approach was more suitable for classifying the growing-season images. The spring data (April imagery; overall accuracy = 99.8%) and the winter data (February imagery; F measure = 65.9%) yielded the best results for landscape classification and QVP detection, respectively, by using the object-based SVM approach. Therefore, in practice, we recommend the use of February to April imagery with the object-based SVM approach to map the QVPs in the future.
A Low-Power Multi-Frequency Chopper-Stabilized Readout with Time-Domain Delta-Sigma Modulator Suitable for Neural Recording

This paper presents a readout for multi-channel neural recording. The proposed architecture is implemented with a system-level frequency-division multiplexing technique and a time-domain delta-sigma modulator. Subthreshold region operation and the time-domain delta-sigma modulator achieves a reduction of the current dissipation. The multiplexing technique in the frequency domain enhances the power efficiency by sharing an instrumentation amplifier and the delta-sigma modulator in each channel. The proposed circuit employs a pulse-width summation technique to achieve frequency-division multiplexing in the time-domain delta-sigma modulator. The multiplexing technique of multiple frequency chopper stabilization can eliminate flicker noise and offsets. The proposed two-channel readout occupies 0.067 mm2 per channel and is designed with 0.18-µm CMOS technology. The spurious-free dynamic range is up to 50 dB in a bandwidth of 625 Hz with a low power consumption of 520 nW per channel.
Novel Design of High Speed 64 bit Optimized MAC Unit

In the present-day, the never-ending demand of the digital processor has been magnifying the ability of the processor to operate the difficulty developed in the integrated chip. To decrease the size of the computer day by day increases the load of the processor. This load may slow down the core processor. This load can be minimized by the co-processor, which is added within the core processor. These are made up of work with particular type functions like DSP, DFT, DCT, etc. So that the MAC unit is the most efficient co-processor. MAC unit consists of a multiplication and accumulation unit. Overall execution speed and performance of entire computing based on the time delay of the multiplication and addition. Multiplication plays an important role to determine all total performance of the MAC unit. Multiplication is a good familiar architecture of shift and adds algorithm which is considered as a chain of replicate addition of partial product. In this display paper work in 64 bit Booth multiplier. Booth multiplication is a high-speed algorithm, and multiplier occupies less area, and consume low power. The proposed multiplier is capable to multiply both negative and positive numbers. In the display, the paper introduces data path and controller to increases the speed and decreases the delay.
A Novel Low Power and Low Cost IoT Wireless Sensor Node for Air Quality Monitoring

This paper presents the design, implementation and testing of a novel low power and low cost air quality monitoring IoT wireless sensor node. The novel device incorporates low cost air quality sensors and features LoRa communication capabilities. Dynamic power management is employed to minimize power consumption to SOA levels. The sensor node draws a current of 3.2 μA in sleep mode, while the average active current demand is 62 mA. The average power consumption per hour is 537 μAh and the proposed device can be operated for up to 14 months using a 6000 mAh battery.