Miracle-dz/UniFAR-FTUs huggingface dataset:
Gas Phase Spectroscopy of 4-aminophenethyl Alcohol and Clusters with Carboxylic Acids

Both ultraviolet and infrared laser spectroscopy methods were used to study the structure of 4-aminophenethyl alcohol, 4-AE, and its formic, acetic, and propionic acid clusters. The “floppy” side chain of the 4AE molecule is capable of forming different conformational isomers. The 4AE molecule has both an amine and a hydroxyl functional group which are potential sites for hydrogen bonding with the acids. The acids are all carboxylic acids which were able to form a one-to-one cluster with the 4AE through hydrogen bonding with the 4AE acting as a base. Through quantum chemical calculations using DFT methods and measurements of the S1 excited state using ultraviolet techniques and of the S0 state using IR-UV double resonance techniques determination of the structure of 4AE and its clusters was achieved. Frequency shifts of the origin of the S1 excited state and the –OH stretches of the S0 ground state were used in the structural determination. 4aminophenethyl Alcohol (4-AE)
Security of the sensory data in the cloud

The integration between the clouds and the sensor networks makes it possible to solve the problem of the limited computing power and the limited capacity of the sensor networks, as well as for the storage and processing of the collected data, without unnecessarily increasing the cost of the sensor networks. A significant challenge is the security of the data transmission connection between the sensors and the cloud. An algorithm has been proposed that ensures security in the transmission of data from the sensor network to the cloud via the DLS security protocol. The algorithm is implemented through the ThingSpeak cloud, and the connection between the sensor network and the cloud is implemented through the MQTT protocol, creating the flow that will gather sensor data, using Node-RED and Generate a self-signed certificate with OpenSSL. The algorithm was tested with Wireshark software, which confirmed that the data packets sent from the sensor network to ThingSpeak use the MQTT data transfer protocol and connect to communication port 8883, which is protected/encrypted via TLS / SSL protocol.
Identification of Nitrate Sources in Rivers in a Complex Catchment Using a Dual Isotopic Approach

Excessive nutrient input to surface water, including nitrate, exacerbates water eutrophication. Clarifying the proportions of different nitrate sources in the aquatic environment is critical for improving the polluted water. However, nitrate sources in river basins are very complex and not clearly understood. In this study, nitrogen concentrations and nitrate isotopic compositions were determined to estimate the spatiotemporal variation in nitrate sources in the Yuntaishan River basin, Nanjing, East China, from March 2019 to January 2020. The results showed that the concentrations of total nitrogen (TN), ammonium (NH4+-N), and nitrate (NO3−-N) changed in the ranges of 0.53–18.0 mg/L, 0.01–15.4 mg/L, and 0.06–9.3 mg/L, respectively, wherein NO3−-N was the main nitrogen form. Higher nitrogen concentrations appeared in winter and in the downstream parts of the river. In the entire river basin, the NO3−-N mainly originated from sewage (67%) and soil (26%), with clear spatial variations. NO3−-N in the Yunba sub-watershed was mainly derived from sewage (78%), which was higher than that in other tributaries, i.e., Shengli River (44%) and Yangshan River (49%). This was due to the fact that that Shengli and Yangshan sub-watersheds were covered by urban areas and were equipped with a complete sewage treatment system. In addition, the contributions of sewage to NO3−-N rose from 60% upstream to 86% downstream, suggesting the increasing influence of the point source of sewage. The results showed that 53% of NO3−-N in the basin outlet originated from the point source of sewage near the M4 site. Sewage contributed 75% of NO3−-N in the rainy season and 67% of NO3−-N in the dry season, suggesting the weakly temporal variation. Our results highlight the spatiotemporal variations in sources of NO3−-N. These results will aid in the development of measures needed to control nitrogen pollution in river basins.
ANTENNA USING A MAGNETIC-SLAB LOCATED IN THE PRINCIPAL MAGNETIC-FIELD REGION BENEATH THE PATCH

This paper presents an analysis of microstrip patch antennas with different dielectric/magnetic substrate profiles in an attempt to obtain operating frequency reduction. Initially, different ridge shapes in the substrate were examined. An in-depth investigation of the ridge shape and its dimensions on the antenna performance has been carried out. Subsequently an antenna with a magneticslab loaded in the prime magnetic-field region beneath the patch is proposed. The new magnetic loaded antenna design is aimed to reduce the resonant frequency of a conventional patch and reduce the profile of an earlier design with a substrate ridge. Various magnetic materials have been embedded within the original dielectric substrate of the patch antenna. Measured results validated the hypothesis that this frequency can be reduced by placing magnetic materials at the centre of the patch. The achieved gain is expected to be further enhanced by using forthcoming magnetic materials with improved performance.
Capacity Analysis and Improvement of LDM-Based Multiple-PLP Configurations in ATSC 3.0

This article analyzes the capacities of various layered-division multiplexing (LDM)-based multiple physical layer pipe (M-PLP) configurations in Advanced Television Systems Committee (ATSC) 3.0. Further, this article proposes an extended multi-layer LDM that consists of a core layer and one or more enhanced layer(s) combined with different injection levels. The proposed multi-layer LDM can be combined with time-division multiplexing (TDM) and/or frequency division multiplexing (FDM) to multiplex more than two PLPs. This article provides the structures of a transmitter and receiver for the multi-layer LDM and various M-PLP configurations based on the proposed multi-layer LDM. In addition, by extending to a multi-layer LDM, the low rate low-density parity-check (LDPC) codes are proposed to improve the transmission efficiency of an extremely robust service with lower data rate, such as robust audio, in the core layer of the multi-layer LDM. Simulation results show that the M-PLP configurations based on more than two layers can obtain the improved reception performance compared to the M-PLP configurations based on only two layers supported by the PHY standard in ATSC 3.0. However, since the performance degradation of layered time-division multiplexing (LTDM) with fewer layers is not significant compared to multi-layer LDM, LTDM can be a good solution to efficiently transmit M-PLPs.
Fixing Defect of Photometric Loss for Self-Supervised Monocular Depth Estimation

View-synthesis-based methods have shown very promising results for the task of unsupervised depth estimation in single images. Most existing approaches synthesize a new image and employ it as the supervision signal for depth and pose prediction. There are two problems in these approaches: 1) There are many combinations of pose and depth that can synthesize a certain new image; therefore, reconstructing the depth and pose based on the view-synthesis method from only two images is an inherently ill-posed problem; 2) The model is trained under the photometric consistency assumption that the brightness or gradient is constant when applied to the video sequences. However, this assumption is easily violated in realistic scenes due to light changes, reflective surfaces and occlusions. To overcome the first drawback, we exploit the point cloud consistency constraint to eliminate ambiguity. To overcome the second drawback, we use threshold masks to filter dynamic and occluded points and introduce matching point constraints that implicitly encode the geometry relationship between two matched points to improve the precision of depth prediction. In addition, we employ epipolar constraints to compensate for the instability of the photometric error in textureless regions and varying illumination conditions. The experimental results on the KITTI, Cityscapes and NYUv2 datasets show that the method can improve the accuracy of depth prediction and enhance the robustness of the model in handling textureless regions and illumination changes. The code and data are available at https://github.com/XTUPRLAB/FixUnDepth.
Crowdsourcing as Content Collaboration for STEM Edutainment

In this project, crowdsourcing science, technology, engineering and mathematics (STEM) content was used to promote enjoyable, challenge-based English language gamification to young ESL learners and instructors altogether. The aim is to optimize the participants' engagement in learning STEM disciplines using the target language. However, relevant literature in this area shows inadequate empirical evidence on engagement when these two activities combined are implemented in real-life settings. This research therefore, was conducted to explore the participants' engagement in learning STEM contents, outside their classroom setting, using crowdsourcing and gamification activities. Through needs analysis of 48 participants (school children aged 13 to 14 years) who were assisted by 20 university undergraduates who were involved in the 'Young Scientist Camp' project, it was discovered that the participants had minimal exposure to the use of technology as well as the language in learning STEM disciplines. The participants were assigned to crowd-source for online STEM contents because the target is to maximize the use of English language. The contents were used to form several questions which they then took turns to test their peers from other groups using Kahoot! The qualitative data of the study were gathered via video recorded interaction, observations, and focus group interviews. Tesch's thematic analysis, Kappa coefficient for inter-rater reliability and an observation checklist using Kapp's motivational characteristics of game elements were used to determine crowdsourcing characteristics and elements of engagement from the activities. Interestingly, the pupils showed evidence of engagement when faced by unexpected problems in their groups. They also expressed strong engagement when the autonomy was given to them in deciding the contents and flow of the activities, which was evidence in the process of completing the tasks. This implicates emerging recommendations in engaging young learners via crowdsourcing techniques and gamification to foster interest in learning the language for STEM.
‘One of the worst statistics in British sport’: a sociological perspective on the over-representation of independently (privately) educated athletes in Team GB

ABSTRACT The overrepresentation of independently educated athletes amongst Team GB at the London 2012 Olympics was described as ‘One of the worst statistics in British sport’. Whilst the ensuing debate referred to independent schools en masse, the sector is far from homogenous. Within the UK independent (private) sector, a small subset of schools has educated a significant number of international sportsmen and women. Despite this record of success however, little research exists on young athletes in independent schools. Answering calls to study independent school sport, this paper uses semi-structured interviews with pupils and staff involved in sport in six independent schools in England to explore why some schools consistently produce international athletes. A dual theory framework combining the Eliasian notions of process and figuration, with Bourdieu’s concept of distinction is employed to offer a sociological perspective on the sporting success of the schools studied. The findings reveal striking differences in institutional attractiveness, coaching, the sporting potential of the pupil intake, and facilities between the least and the most successful schools studied, where a number of intra and inter school practices contribute to an increasingly professionalised sporting environment. In concluding, a novel and more variegated perspective on the under researched and often difficult to access field of independent school sport is offered. The proposition being that through reconciliation of the notions of distinction and status rivalry, we are better able to understand the repeated success of some independent schools in supporting the development of talented young athletes.
Codee: A Tensor Embedding Scheme for Binary Code Search

Given a target binary function, the binary code search retrieves top-K similar functions in the repository, and similar functions represent that they are compiled from the same source codes. Searching binary code is particularly challenging due to large variations of compiler tool-chains and options and CPU architectures, as well as thousands of binary codes. Furthermore, there are some pivotal issues in current binary code search schemes, including inaccurate text-based or token-based analysis, slow graph matching, or complex deep learning processes. In this paper, we present an unsupervised tensor embedding scheme, Codee, to carry out code search efficiently and accurately at the binary function level. First, we use an NLP-based neural network to generate the semantic-aware token embedding. Second, we propose an efficient basic block embedding generation algorithm based on the network representation learning model. We learn both the semantic information of instructions and the control flow structural information to generate the basic block embedding. Then we use all basic block embeddings in a function to obtain a variable-length function feature vector. Third, we build a tensor to generate function embeddings based on the tensor singular value decomposition, which compresses the variable-length vectors into short fixed-length vectors to facilitate efficient search afterward. We further propose a dynamic tensor compression algorithm to incrementally update the function embedding database. Finally, we use the local sensitive hash method to find the top-$K$K similar matching functions in the repository. Compared with state-of-the-art cross-optimization-level code search schemes, such as Asm2Vec and DeepBinDiff, our scheme achieves higher average search accuracy, shorter feature vectors, and faster feature generation performance using four datasets, OpenSSL, Coreutils, libgmp and libcurl. Compared with other cross-platform and cross-optimization-level code search schemes, such as Gemini, Safe, the average recall of our method also outperforms others.
Secure IoT via Blockchain

Block chain technology had gained popularity because of its use in crypto-currencies like bitcoin. Today uses of blockchain are growing in number of areas like banking, industries, health centers and even security of IOT. Moreover, the use of IOT is growing exponentially every year with its aim in 5G technologies like e- health, smart homes, distributed intelligence etc. but it faces challenges in security and privacy. The privacy of a user data is at a risk because of its (i.e. IoT) centralized client-server model. This centralized approach of the server poses a serious vulnerability to the data security. This data at the server attracts the attackers to enter into the network and invade through the data and schedule attacks or inject a malware. It indicates that the central architecture of IoT possess a compromised confidentiality, integrity, and security of data which disrupts its use as the widespread adoption of this technology. Therefore, it is essential to evade the hostile centralized server architecture for IoT to enhance its security. It implies a need for decentralized architecture to maintain the data. The data can be kept at the different users without any central control with the help of blocks as suggested by Blockchain. This paper addresses the various security issues in IOT and how block chain helps in solving these issues.
Performance Assessment of GSMaP and GPM IMERG Products during Typhoon Mangkhut

This paper evaluated the latest version 6.0 Global Satellite Mapping of Precipitation (GSMaP) and version 6.0 Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) products during 2018 Typhoon Mangkhut in China. The reference data is the rain gauge datasets from Gauge-Calibrated Climate Prediction Centre (CPC) Morphing Technique (CMORPHGC). The products for comparison include the GSMaP near-real-time, Microwave-IR merged, and gauge-calibrated (GSMaP_NRT, GSMaP_MVK, and GSMaP_Gauge) and the IMERG Early, Final, and Final gauge-calibrated (IMERG_ERUncal, IMERG_FRUncal, and IMERG_FRCal) products. The results show that (1) both GSMaP_Gauge and IMERG_FRCal considerably reduced the bias of their satellite-only products. GSMaP_Gauge outperforms IMERG_FRCal with higher Correlation Coefficient (CC) values of about 0.85, 0.78, and 0.50; lower Fractional Standard Error (FSE) values of about 18.00, 18.85, and 29.30; and Root-Mean-Squared Error (RMSE) values of about 12.12, 33.35, and 32.99 mm in the rainfall centers over mainland China, southern China, and eastern China, respectively. (2) GSMaP products perform better than IMERG products, with higher Probability of Detection (POD) and Critical Success Index (CSI) and lower False Alarm Ratio (FAR) in detecting rainfall occurrence, especially for high rainfall rates. (3) For area-mean rainfall, IMERG performs worse than GSMaP in the rainfall centers over mainland China and southern China but shows better performance in the rainfall center over eastern China. GSMaP_Gauge and IMERG_FRCal perform well in the three regions with a high CC (0.79 vs. 0.94, 0.81 vs. 0.96, and 0.95 vs. 0.97) and a low RMSE (0.04 vs. 0.06, 0.40 vs. 0.59, and 0.19 vs. 0.34 mm). These useful findings will help algorithm developers and data users to better understand the performance of GSMaP and IMERG products during typhoon precipitation events.
HF Pulsating Carrier Voltage Injection Method Based on Improved Position Error Signal Extraction Strategy for PMSM Position Sensorless Control

High-frequency (HF) pulsating carrier voltage injection method is widely used in position sensorless control of permanent magnet synchronous motor. In this method, the position error signal (i.e., amplitude of $q$-axis HF carrier current) is extracted by band-pass filter (BPF) and low-pass filter (LPF). However, with the BPF+LPF-based position error signal extraction strategy, position estimation loop may face the problem of conflict between filtering accuracy and dynamic performance. The conflict is reflected as estimated speed harmonic or position estimation error cannot be balanced at the same time, especially in speed step and load change condition. In this article, an improved position error signal extraction strategy based on amplitude observer (AO) is proposed. First, the AO-based strategy demodulates $q$-axis current directly, which gets rid of the BPF. Second, the AO has the capability of automatic secondary HF harmonic filtering, so the LPF is eliminated as well. Third, the AO extracts the position error signal by closed-loop, which helps to improve the extraction performance under dynamic condition. With the AO-based position error signal extraction strategy, the position estimation loop features both high filtering capability and wide bandwidth. Experimental results demonstrate that compared with BPF+LPF-based strategy, the secondary HF harmonic components of estimated speed are eliminated and the position estimation error is decreased at the same time.
A Method with Pre-trained Word Vectors for Detecting Wordlist-based Malicious Domain Names

In recent years, botnets have used the domain generation algorithm to generate dynamic typified malicious domain names to bypass various detection methods. Given the depth detection model of such domain names, domain names are generally processed by filling and transforming them into a fixed-length one-dimensional vector and then classifying them with poor detection performance. Therefore, this study first divides the domain into a word array and converts it into a word vector using pre-trained word vector models, Embeddings from Language Models. The domain is inputted into the TextCNN model for training classification. From approximately 100,000 data sets, a 94.22% accuracy rate and 6.87% FPR value can be obtained from the training. Compared with previous detection models (i.e., LSTM and CNN), more training and testing are needed, but improvements are made in all indicators.
COLOR DUPLICATION IN LITHIUM DISILICATE RESTORATIONS FABRICATED BY CAD-CAM USING VISUAL AND INSTRUMENTAL SHADE MATCHING SYSTEMS

ABSTRACT Introduction: Color reproduction is one of the most challenging issues encountered by clinicians because of the complexity of visual properties of natural teeth. Objectives: This study aimed to assess color differences among intended and fabricated shades of lithium disilicate restorations fabricated by CAD-CAM after using visual and instrumental shade matching systems. Materials and Method: IPS Emax CAD blocks measuring (12.4mm width x 14.5mm length x 18 mm thickness) were cut under continuous water irrigation using diamond-impregnated slicing wheels mounted on a slow-speed saw microtome (Isomet; Buehler) to yield 16 rectangular specimens measuring (12.4 x 14.5x 1.5 mm). Then they were subjected to the crystallization cycle. Then IPS Emax glaze paste was applied with uniform thickness onto the crystallized specimen surface. Each master disk represented the color of a shade guide tab in the Vita Classic (16 shades). Shade selections for these master disks were carried out following visual and instrumental methods. Accordingly, 16 visual and 16 instrumental experimental disks were fabricated. After analysis, color differences (∆E) between the master and the fabricated ceramic discs were measured using the equation. Results: On comparing Visual Emax CAD and instrumental Emax CAD, the mean(∆E) for visual (2.96± 1.90) was lower than the mean(∆E) for instrumental (22.22± 4.73) with a significant difference between them p < 0.001. Conclusions: Visual shade selection using classical shade guide showed lower delta E than that of instrumental shade matching using Easyshade. Keywords: Color duplication, lithium disilicate, E-max, Visual, Instrumental. Running title: Color duplication using visual and instrumental methods.
Preconditioned Douglas-Rachford type primal-dual method for solving composite monotone inclusion problems with applications

This paper is concerned with the monotone inclusion involving the sum of a finite number of maximally monotone operators and the parallel sum of two maximally monotone operators with bounded linear operators. To solve this monotone inclusion, we first transform it into the formulation of the sum of three maximally monotone operators in a proper product space. Then we derive two efficient iterative algorithms, which combine the partial inverse method with the preconditioned Douglas-Rachford splitting algorithm and the preconditioned proximal point algorithm. Furthermore, we develop an iterative algorithm, which relies on the preconditioned Douglas-Rachford splitting algorithm without using the partial inverse method. We carefully analyze the theoretical convergence of the proposed algorithms. Finally, in order to demonstrate the effectiveness and efficiency of these algorithms, we conduct numerical experiments on a novel image denoising model for salt-and-pepper noise removal. Numerical results show the good performance of the proposed algorithms.