Miracle-dz/UniFAR-FTUs huggingface dataset:
A scanning phased array based on a polarization reconfigurable antenna with compact aperture size

A compact antenna with tri‐polarization switching is presented. The antenna is mainly composed of a monopole slot and a shorted loop, and the two radiating elements are connected in series and placed in a metallic box filled with dielectrics. To realize polarization switching, four PIN diodes are introduced into the antenna structure, and they cannot only suppress the excitation of the loop antenna but also vary the direction of the current flowing on the loop. Both simulated and measured results indicate that the proposed antenna can be operated in one linear polarization and dual circular polarization modes within an impedance bandwidth of around 15%; moreover, the aperture size of the antenna is about 0.09 λ02. Based on the polarization reconfigurable antenna, a 1 × 8 phased array with an aperture size of 0.3 λ0 × 2.8 λ0 is then developed. Simulated results show that the phased array operating in each polarization mode can give a gain fluctuation of smaller than 1.5 dB and a side lobe level of less than −10 dB when the beam is scanned from −60° to 60°. Experiments are also carried out, and their results have good agreements with the simulated data.
The Degradation Mechanism of Mg2Si during Exploitation at High Temperature

Oxidized Mg2Si films are annealed in low vacuum at various annealing temperature, and the degradation mechanism of Mg2Si during exploitation at high temperature is investigated. The crystal structure, surface morphology, depth profile, Raman scattering, and electrical properties are measured by X‐ray diffraction (XRD), field emission scanning electron microscopy (FESEM), X‐ray photoelectron spectroscopy (XPS), Raman spectroscopy, and Hall effect system, respectively. XRD results show that MgO exists apparently in Mg2Si films, and as the annealing temperature increases, the content of MgO increases. The surfaces of films present distinct hexagon structures. The results of depth profiles show that the oxygen content decreases gradually from the surface to the subsurface. Raman spectroscopy analysis suggests that as the annealing temperature increases, the intensity of MgO peak enhances gradually. Hall measurement results indicate that the carrier concentration and mobility decrease significantly with the increase in annealing temperature. The films show n‐type at lower annealing temperature, while they present p‐type at higher annealing temperature, which indicates obvious conversions from n‐ to p‐type.
Abiotic and biotic drivers of functional diversity and functional composition of bird and bat assemblages along a tropical elevation gradient

The identification of the mechanisms determining spatial variation in biological diversity along elevational gradients is a central objective in ecology and biogeography. Here, we disentangle the direct and indirect effects of abiotic drivers (climatic conditions, and land use) and biotic drivers (vegetation structure and food resources) on functional diversity and composition of bird and bat assemblages along a tropical elevational gradient.
A Review on Polyherbal Formulations used in the Treatment of Autoimmune Disease like Rheumatoid Arthritis

This article presents about various Polyherbal formulations utilized in arthritis Treatment. Rheumatoid arthritis being a progressive disease causes inflammation in joints and resulting in painful Deformity and immobility especially within the finger, wrist, feet and ankles. It belongs to Non -Organ specific class of Auto immune diseases. Autoimmune disorder is an illness that happens when body tissue is attacked by its own system. Consistent with Ayurvedic principles, PHF is that the one which contains two or more herbs within the formulation which acts synergistically. The herbal plants having ethno-medicinal values are currently being screened for their therapeutic activities. Further the article represents various RA based PHF and thus the Marketed formulation available for it.
Supplementary notes on the minimax and orthogonal least squares line fitting procedures

Abstract The two-variable orthogonal least squares procedure was developed independently by Julius Ludwig Weisbach (1806–1871) and Robert Jackson Adcock (1826–1895). In this article we discuss aspects of two recent articles concerned with the contributions of these individuals. We also identify a prototype of the orthogonal minimax fitting procedure due to August Beyer (1677–1753).
Maternal Proinflammatory Adipokines Throughout Pregnancy and Neonatal Size and Body Composition: A Prospective Study.

Background Increased maternal adiposity and inflammation have impacts on fetal growth. Objectives The purpose of this prospective study was to investigate the associations of 3 proinflammatory adipokines in pregnancy with neonatal anthropometry. Methods In a sample of 321 US pregnant women from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singleton Cohort (NCT00912132), plasma IL-6, fatty acid binding protein-4 (FABP4), and chemerin were measured in plasma samples collected at 10-14, 15-26, 23-31, and 33-39 weeks of gestation. Generalized linear models were used to estimate associations of adipokines with neonatal weight, thigh, and crown-heel length, and skinfolds at birth. Models adjusted for age, race/ethnicity, education, nulliparity, prepregnancy BMI, and weeks of gestation at blood collection. Results At each time point, higher IL-6 was associated with lower neonatal birthweight and thigh length. At 15-26 weeks of gestation, a 1 SD pg/mL increase in IL-6 was associated with -84.46 g lower neonatal birthweight (95% CI: -150.70, -18.22), -0.17 cm shorter thigh length (95% CI: -0.27, -0.07), -0.43 cm shorter crown-heel length (95% CI: -0.75, -0.10), and -0.75 mm smaller sum of skinfolds (95% CI: -1.19, -0.31), with similar associations at 23-31 and 33-39 weeks of gestation. There were no associations of FABP4 and chemerin with neonatal anthropometry. Conclusions Starting as early as 15 weeks of gestation, higher maternal IL-6 concentrations in pregnancy were associated with lower neonatal birthweight, thigh and crown-heel length, and skinfolds. These data provide insight into the relevance of maternal inflammatory markers with neonatal anthropometry.
Energy Efficient Power Allocation for Cell-Free mmWave Massive MIMO With Hybrid Precoder

This letter investigates the downlink of a cell-free millimeter wave (mmWave) massive multiple-input multiple-output (mMIMO) system, where many access points (APs) cooperatively serve a user. Although the intensive deployment of APs can dramatically improve the system capacity, it also increases the network energy consumption substantially. To track the non-concave global energy-efficiency (GEE) optimization problem, we decompose it into hybrid precoder design and power allocation design. A novel dynamic subarray with quantized phase shifters (DS-QPS) hybrid precoder is introduced, where each radio frequency (RF) chain only connects to a disjointed subset of antennas. The optimization problem of the number of RF chains is formulated as an eigenvalue maximization problem considering a realistic power consumption model. For power allocation, a new centralized framework is exploited to solve a sequence of simpler power allocation subproblems while still aiming at the GEE maximization by merging with fractional programming, non-cooperative game theory, and gradient-assisted binary search (GABS) algorithm. Simulations show that the joint design is more energy-efficient than the baselines.
SYSTEMATIC LITERATURE NETWORK ANALYSIS OF THE “INNOVATION POLICY MIX” CONCEPT: EXTENDING LEADERS’ VIEWS ON ORGANIZATIONAL ENVIRONMENT

Introduction/Main Objectives: This study aims to depict the scientific landscape for the innovation policy mix (IPM) from 2012 to 2019 since its re-conceptualization by Flanagan, Uyarra, and Laranja (2011). Background Problems: The seminal work has broadened policy mix thinking with social issues impacting innovation. Since every organization is part of the innovation policy system, this study takes the first step to introduce IPM into management fields by identifying and discussing subsequent works in research trajectories.Novelty: This study shows the remarkable progress toward a mature concept through IPM’s definition, characteristics, and boundaries. As a new string of interdisciplinary social science research, some opportunities and challenges are revealed, allowing future studies to be conducted in more theoretically sounding research traditions.Research Methods: This study applies systematic literature network analysis (SLNA) relying on objective measures from keyword co-occurrences and co-citations networks. It includes 60 articles analyzed using open-source software, i.e., Publish or Perish, Google Scholar database, VOSviewer, and the web-based Local Citation Network.Finding/Results: There are three clusters in the main path of research trajectories, i.e., IPM’s conceptualization, its characteristics for evaluation and measurement, and contextualization. Future research directions are proposed to advance our understanding of the organizational environment and its impact on innovation.Conclusion: IPM studies have opened opportunities to test and extend theories in strategic management and organization studies, especially for leaders who make decisions in the face of dynamic and demanding environments. Moreover, contextualization in developing countries would be a worthwhile exercise by considering the institutional and cultural context.
20 Years of Research on Real Estate Bubbles, Risk and Exuberance: A Bibliometric Analysis

Since the 2008 global financial crisis, the study of real estate risks, bubbles and exuberance has attracted a lot of attention, which is of great significance to the government, enterprises and individuals. This paper carries out a statistical and bibliometric analysis of 739 studies over the past 20 years in this field, and identifies the theoretical basis, research topics and latest research hotspots in this field. Through the construction of a co-citation network and co-word network, we find that the current studies have commonly employed basic economic theories or econometric methods to detect and quantify real estate bubbles. Explosive bubbles and financialization of real estate are frontier hotspots that have gained much popularity. Based on the comparative study, we further discover that American scholars have paid more attention to topics related to the financial crisis, while Chinese scholars have studied topics more related to real estate market policies. Finally, this paper proposes several important research directions in this field for the future.
Phonetic and Prosodic Information Estimation from Texts for Genuine Japanese End-to-End Text-to-Speech

The biggest obstacle to develop end-to-end Japanese text-to-speech (TTS) systems is to estimate phonetic and prosodic information (PPI) from Japanese texts. The following are the reasons: (1) the Kanji characters of the Japanese writing system have multiple corresponding pronunciations, (2) there is no separation mark between words, and (3) an accent nucleus must be assigned at appropriate positions. In this paper, we propose to solve the problems by neural machine translation (NMT) on the basis of encoder–decoder models, and compare NMT models of recurrent neural networks and the Transformer architecture. The proposed model handles texts on token (character) basis, although conventional systems handle them on word basis. To ensure the potential of the proposed approach, NMT models are trained using pairs of sentences and their PPIs that are generated by a conventional Japanese TTS system from 5 million sentences. Evaluation experiments were performed using PPIs that are manually annotated for 5,142 sentences. The experimental results showed that the Transformer architecture has the best performance, with 98.0% accuracy for phonetic information estimation and 95.0% accuracy for PPI estimation. Judging from the results, NMT models are promising toward end-to-end Japanese TTS.
Integrating a dialog system with an intelligent tutoring system for a 3D virtual laboratory

ABSTRACT This paper addresses the challenge of integrating a dialog system with an ITS created for supporting procedural training in a 3D virtual environment. To this end, we first describe the desired features of the dialog to be provided to students in such system. Then, we explain some technical issues of our proposal such as the architecture; the design of the dialog manager; and the construction of the answers to the students’ questions by leveraging an ontology related to the virtual world. Next, we present a pilot study with students to validate our approach. In this pilot study, we utilized a prototype that encompasses a 3D virtual laboratory. In the last seven years, students have used this virtual laboratory to perform a practice guided by an automatic tutor without dialog capacity. So, the evaluated prototype represents an extension of this automatic tutor that aims to give it the dialog capacity in the context of the practice.
Developing sustainable measures to restore fly‐ash contaminated lands: Current challenges and future prospects

Land degradation is one of the major global environmental issues that need serious attention. The land itself is a complex system regulating myriads of processes. Any perturbation in these processes would undoubtedly lead to the stimulation of land degradation. Among these, fly‐ash (FA) dumping is one of the usual practices, which has been adopted to overcome land‐use disruption and other health hazards. However, this practice has become a driving factor for FA‐induced land degradation. Therefore, in purview to tackle this issue, the present article aimed to identify and suggest sustainable practices to restore and manage FA‐contaminated sites. As a preliminarily it deals with the systematic exploration and identification of FA‐based and associated contaminated lands via geospatial technology with a brief focus on assessing its different contaminant profiles in the FA and soil systems. Further, this moreover, the article emphasizes the need to identify identifying the potential local plant species in the FA‐contaminated regions that can meet the local people's demands. Following this we suggest appropriate sustainable approaches to expedite the restoration of FA‐contaminated lands and highlight the critical bottlenecks during ground implementation. Our article aimed to unravel ways to address the aforementioned bottlenecks to develop an efficient restoration enterprise during the UN Decade on Ecosystem Restoration (2021–2030).
Sarcopenia; functional concerns, molecular mechanisms involved, and seafood as a nutritional intervention – review article

Abstract The fundamental basis for the human function is provided by skeletal muscle. Advancing age causes selective fiber atrophy, motor unit loss, and hybrid fiber formation resulting in hampered mass and strength, thus referred to as sarcopenia. Influence on the loss of independence of aged adults, contribute toward inclined healthcare costs conveys the injurious impact. The current understating of age-related skeletal muscle changes are addressed in this review, and further discusses mechanisms regulating protein turnover, although they do not completely define the process yet. Moreover, the reduced capacity of muscle regeneration due to impairment of satellite cell activation and proliferation with neuronal, immunological, hormonal factors were brought into the light of attention. Nevertheless, complete understating of sarcopenia requires disentangling it from disuse and disease. Nutritional intervention is considered a potentially preventable factor contributing to sarcopenia. Seafood is a crucial player in the fight against hunger and malnutrition, where it consists of macro and micronutrients. Hence, the review shed light on seafood as a nutritional intrusion in the treatment and prevention of sarcopenia. Understanding multiple factors will provide therapeutic targets in the prevention, treatment, and overcoming adverse effects of sarcopenia.
An Ensemble of Prediction and Learning Mechanism for Improving Accuracy of Anomaly Detection in Network Intrusion Environments

The connectivity of our surrounding objects to the internet plays a tremendous role in our daily lives. Many network applications have been developed in every domain of life, including business, healthcare, smart homes, and smart cities, to name a few. As these network applications provide a wide range of services for large user groups, the network intruders are prone to developing intrusion skills for attack and malicious compliance. Therefore, safeguarding network applications and things connected to the internet has always been a point of interest for researchers. Many studies propose solutions for intrusion detection systems and intrusion prevention systems. Network communities have produced benchmark datasets available for researchers to improve the accuracy of intrusion detection systems. The scientific community has presented data mining and machine learning-based mechanisms to detect intrusion with high classification accuracy. This paper presents an intrusion detection system based on the ensemble of prediction and learning mechanisms to improve anomaly detection accuracy in a network intrusion environment. The learning mechanism is based on automated machine learning, and the prediction model is based on the Kalman filter. Performance analysis of the proposed intrusion detection system is evaluated using publicly available intrusion datasets UNSW-NB15 and CICIDS2017. The proposed model-based intrusion detection accuracy for the UNSW-NB15 dataset is 98.801 percent, and the CICIDS2017 dataset is 97.02 percent. The performance comparison results show that the proposed ensemble model-based intrusion detection significantly improves the intrusion detection accuracy.
Variations in magmatism and the state of tectonic compensation of the Mariana subduction system

We investigate the variations in the state of isostatic compensation of the Mariana subduction system. We first calculate and analyse the gravity‐derived crustal thickness and non‐isostatic topography of this region. The Mariana back‐arc spreading centre and West Mariana Ridge are both close to Airy isostatic compensation. In contrast, the Mariana Trench axis is associated with a clearly defined zone of negative non‐isostatic topography and free‐air gravity anomaly (FAA), which have been shown to be caused by the flexural bending of the subducting Pacific Plate. The new analyses reveal that the southern Mariana Arc at 12.5°–16.7°N is associated with positive non‐isostatic topography and a local zone of positive FAA, which we interpret to be the result of accretion of young volcanism on a relatively strong lithospheric plate and/or supported by the tectonic stresses induced by the interaction of the subducting Pacific Plate with the upper Mariana micro‐plate.
Degradation Mechanism of Pressure-Assisted Sintered Silver by Thermal Shock Test

This paper investigates the degradation mechanism of pressure-sintered silver (s-Ag) film for silicon carbide (SiC) chip assembly with a 2-millimeter-thick copper substrate by means of thermal shock test (TST). Two different types of silver paste, nano-sized silver paste (NP) and nano-micron-sized paste (NMP), were used to sinter the silver film at 300 °C under a pressure of 60 MPa. The mean porosity (p) of the NP and MNP s-Ag films was 2.4% and 8%, respectively. The pore shape of the NP s-Ag was almost spherical, whereas the NMP s-Ag had an irregular shape resembling a peanut shell. After performing the TST at temperatures ranging from −40 to 150 °C, the scanning acoustic tomography (SAT) results suggested that delamination occurs from the edge of the assembly, and the delamination of the NMP s-Ag assembly was faster than that of the NM s-Ag assembly. The NMP s-Ag assembly showed a random delamination, indicating that the delamination speed varies from place to place. The difference in fracture mechanism is discussed based on cross-sectional scanning electron microscope (SEM) observation results after TST and plastic strain distribution results estimated by finite element analysis (FEA) considering pore configuration.
Node Dynamic Localization and Prediction Algorithm for Internet of Underwater Things

This article investigates the underwater node dynamic localization and prediction problems in a dynamic sensor network. Node localization in the Internet of underwater things is the basis of target tracking and ocean monitoring. At present, most of the node location algorithms assume calm sea and fixed node location. However, the current velocity is uncertain in space and time. The nodes are drifted with the current motion. Therefore, most of the localization algorithms lose efficacy in the actual marine environment. In order to solve the above problems, a node dynamic prediction algorithm is proposed. First, the node mobility model is improved, which is more suitable for the actual marine environment. Second, a frequency-based anchor node prediction algorithm is designed to improve anchor node location accuracy. Third, when the ordinary node receives the signals sent by anchor nodes of different depths, a deep information-based weighted fusion method is designed for the ordinary node localization in order to mine more information in each direction. Finally, location and prediction simulation in sensor networks is carried out. The results show that the proposed node localization and prediction algorithm is more accurate than SMLP and high-precision localization with mobility prediction algorithms and prove the enhanced effect of our method in dynamic marine.
Leveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition

In Uyghur speech, consonant and vowel reduction are often en-countered, especially in spontaneous speech with high speech rate, which will cause a degradation of speech recognition performance. To solve this problem, we propose an effective phone mask training method for Conformer-based Uyghur end-to-end (E2E) speech recognition. The idea is to randomly mask off a certain percentage features of phones during model training, which simulates the above verbal phenomena and facil-itates E2E model to learn more contextual information. According to experiments, the above issues can be greatly allevi-ated. In addition, deep investigations are carried out into different units in masking, which shows the effectiveness of our proposed masking unit. We also further study the masking method and optimize ﬁlling strategy of phone mask. Finally, compared with Conformer-based E2E baseline without mask training, our model demonstrates about 5.51% relative Word Error Rate (WER) reduction on reading speech and 12.92% on spontaneous speech, respectively. The above approach has also been veriﬁed on test-set of open-source data THUYG-20, which shows 20% relative improvements.
Role of NaCl, CO2, and H2S on Electrochemical Behavior of 304 Austenitic Stainless Steel in Simulated Oil Industry Environment

The electrochemical behavior of 304 austenitic stainless steel (304ASS) was studied by different methods such as potentiodynamic polarization, EIS, SEM, and Raman spectroscopy. Potentiodynamic polarization data suggest that 304 ASS could be more susceptible to corrosion due to the presence of H2S. The coexistence of H2S and Cl−-type ionic species in 304 ASS lead to a decrease in the corrosion resistance as compared to the H2S-free condition. It is seen that CO2 helps form a passive layer on the metallic surface, which eventually decreases its corrosion rate. Raman spectroscopy analysis shows that the passive layer developed under different condition consists of FeCO3, FeS2, Fe2O3, Fe(OH)2, etc. SEM images further confirm that elemental S− and Cl− can infiltrate the passive film and cause the passive film to deteriorate.