Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustainable land reclamation in coastal area

Many land reclamation projects have been carried out worldwide for many years to create new land from oceans, seas, riverbeds or lakebeds for several purposes. Historically, agriculture was the first drive for land reclamation, followed by urbanization and industrialization. Recent worldwide globalization has enhanced international trading and promoted many land reclamation projects in coastal areas. Land reclamation requires a large amount of relatively high-quality fill soil, which is used to obtain from mountains, rivers and seabeds. For this purpose, many land reclamation projects have been carried out together with other projects, such as dredging projects at rivers and coastal areas and/or the development of mountainous areas. Recently, it has become difficult to obtain such soil at reasonable cost because of restricted environmental protection, which requires the use of lower-quality soil as a reclamation material. Reclaimed land and sea walls are highly susceptible to ground instability, ground settlement and soil liquefaction, which can amplify the amount of damage to buildings and infrastructure there. Various ground improvement techniques have been developed to assure the stability of the sea wall and reduce and accelerate the ground settlement of reclaimed land. As environmental issues have become very critical in recent years, it is necessary to develop sustainable land reclamation techniques to promote the beneficial use of dredged soil and waste, minimize the environmental impact and create a rich natural environment. In this manuscript, the history of land reclamation in the Tokyo Bay area is briefly introduced, and current technologies regarding ground improvement and preservation of environmental conditions are presented to determine the future trends of sustainable land reclamation technologies.
Transcriptomic Analysis of Root Restriction Effects on the Primary Metabolites during Grape Berry Development and Ripening

Root restriction (RR) has been reported to enhance grape berry quality in diverse aspects of grape life. In this study, RR-induced increases in the main primary metabolites in the grape berry and the expression of their related genes were studied at different developmental stages. Mainly the transcriptomic and metabolomic level were analyzed using ‘Summer Black’ grape berry as a material. The main results were as follows: A total of 11 transcripts involved in the primary metabolic pathways were significantly changed by the RR treatment. Metabolites such as sugars, organic acids, amino acids, starch, pectin, and cellulose were qualitatively and quantitatively analyzed along with their metabolic pathways. Sucrose synthase (VIT_07s0005g00750, VIT_11s0016g00470) and sucrose phosphate synthase (VIT_18s0089g00410) were inferred to play critical roles in the accumulation of starch, sucrose, glucose, and fructose, which was induced by the RR treatment. RR treatment also promoted the malic acid and tartaric acid accumulation in the young berry. In addition, the grape berries after the RR treatment tended to have lower pectin and cellulose content.
An integrated control strategy of PMSG-based wind turbine generation system to improve its fault ride-through capability by using an energy storage device

In order to improve the fault ride-though (FRT) capability of PMSG-based wind turbine generation system, an energy storage system composed of ultracapacitor (UC) and bidirectional Buck-Boost converter (BDBBC) paralleled to the DC-link of the dual PWM converter is used in this paper. The integrated control strategy for both grid-side converter (GSC) and BDBBC has been presented, which has two working modes. Under normal grid operation, it works in normal mode where the grid voltage orientation control (VOC) for gird-side converter and power control for BDBBC are applied. During the grid failures, it automatically switches to mode fault, where power control for GSC and voltage control for BDBBC are developed. Simulation results in MATLAB/SIMULINK verified the correctness and feasibility of the integrated control strategy.
MemDroid - LSTM Based Malware Detection Framework for Android Devices

Android smartphones are very popular today due to its versatile features and cost-effectiveness. The popularity of the gadget has attracted malware writers to target the device for spreading malicious software. A large number of malicious software is being introduced daily into the cyber space intended to attack various Android devices and versions. Detection and classification of Android malware is an important problem for researchers due to the severity of threat that the malware poses to the Android users and their information. In this paper, an Android malware detection framework based on Long Short-Term Memory is proposed. We use the relatively recent Android malware database Androzoo for training the LSTM network. The Android system call sequences for malicious software are traced and converted into feature set vector to model the classifier. The experiment is carried out for different sequence lengths to identify the optimum one in order to achieve the highest detection rate. The proposed framework generates an accuracy of 99.23% for detecting Android malware apps. The result obtained is very promising, compared to similar frameworks. Our research work reiterates that Deep Learning based classifiers are more suitable for malware detection than traditional Machine Learning based models.
A New Correlation for Temperature Rise Correction of Heat Flux Gages

Experimental and numerical studies of turbulent heat transfer near a step change in wall temperature have been conducted in connection with an error analysis of small, transient, heat flux gages. The surface temperature of such a gage typically rises above the temperature of the surrounding metal wall, which influences the heat flux to the gage. Data from such gages must be corrected for the effect of this temperature rise. The correction is typically made by superposition using an unheated starting-length correlation, a procedure that has been in practice for many years. In the present work, experimental data from a small, isothermal calorimeter were compared with output from STAN7, a 2-D turbulent boundary layer code, and with predictions based on a textbook correlation. The experiments and the numerical predictions agree within +/−6%, but the correlation underpredicts the required correction by 15–20% over the first half-boundary layer thickness downstream of the step change. As a consequence, data from small gages cannot be properly corrected using the accepted correlation. A new expression is proposed for Stanton number downstream of a step in wall temperature, which can be used as an accurate correction algorithm for use with small gages.
Evaluation and Projection of Diurnal Temperature Range in Maize Cultivation Areas in China Based on CMIP6 Models

The diurnal temperature range (DTR) is an important meteorological component affecting maize yield. The accuracy of climate models simulating DTR directly affects the projection of maize production. We evaluate the ability of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate DTR during 1961–2014 in maize cultivation areas with the observation (CN05.1), and project DTR under different shared socioeconomic pathway (SSP) scenarios. The root mean square error (RMSE), standard deviation (SD), Kling-Gupta efficiency (KGE) and comprehensive rating index (CRI) are used in the evaluation of the optimal model. The results show that CMIP6 models can generally reproduce the spatial distribution. The reproducibility of the annual average DTR in the maize cultivation areas is better than that in China but lower for the maize-growing season. The optimal model (EC-Earth3-Veg-LR) is used in the projection. Under the two SSPs, the DTR decreases compared with the historical period, especially in Northwest and North China. The DTR under SSP245 remains unchanged (annual) or increases slightly (growing season) during 2015–2050, while a significant decreasing trend is observed under SSP585. This highlights the importance of evaluating DTR in maize cultivation areas, which is helpful to further improve the accuracy of maize yield prediction.
Distributed Massive MIMO : Random Access, Extreme Multiplexing and Synchronization

The data traffic in wireless networks has grown tremendously over the past few decades and is ever-increasing. Moreover, there is an enormous demand for speed as well. Future wireless networks need to support three generic heterogeneous services: enhanced mobile broadband(eMBB), ultrareliable low latency communication (URLLC) and massive machine type communication (mMTC). Massive MIMO has shown to be a promising technology to meet the demands and is now an integral part of 5G networks. To get high data rates, ultra densification of the network by deploying more base stations in the same geographical area is considered. This led to an increase in inter-cell interference which limits the capacity of the network. To mitigate the inter-cell interference, distributed MIMO is advocated. Cell-free massive MIMO is a promising technology to improve the capacity of the network. It leverages all the benefits from ultra densification, massive MIMO, and distributed MIMO technologies and operates without cell boundaries. In this thesis, we study random access, extreme multiplexing capabilities, and synchronization aspects of distributed massive MIMO. In Paper A studies the activity detection in grant-free random access for mMTC in cell-free massive MIMO network. An algorithm is proposed for activity detection based on maximum likelihood detection and the results show that the macrodiversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large. RadioWeaves technology is a new wireless infrastructure devised for indoor applications leveraging the benefits of massive MIMO and cell-free massive MIMO. In Paper B, we study the extreme multiplexing capabilities of RadioWeaves which can provide high data rates with very low power. We observe that the RadioWeaves deployment can spatially separate users much better than a conventional co-located deployment, which outweighs the losses caused by grating lobes and thus saves a lot on transmit power. Paper C studies the synchronization aspect of distributed massive MIMO.
Hacking Commensal Bacteria to Consolidate the Adaptive Mucosal Immune Response in the Gut–Lung Axis: Future Possibilities for SARS-CoV-2 Protection

Infectious diseases caused by mucosal pathogens significantly increase mortality and morbidity. Thus, the possibility to target these pathogens at their primary entry points can consolidate protective immunity. Regarding SARS-CoV-2 infection, it has been observed that the upper respiratory mucosa is highly affected and that dysregulation of resident microbiota in the gut–lung axis plays a crucial role in determining symptom severity. Thus, understanding the possibility of eliciting various mucosal and adaptive immune responses allows us to effectively design bacterial mucosal vaccine vectors. Such design requires rationally selecting resident bacterial candidates as potential host carriers, evaluating effective carrier proteins for stimulating an immune response, and combining these two to improve antigenic display and immunogenicity. This review investigated mucosal vaccine vectors from 2015 to present, where a few have started to utilize Salmonella and lactic acid bacteria (LAB) to display SARS-CoV-2 Spike S proteins or fragments. Although current literature is still lacking for its studies beyond in vitro or in vivo efficiency, decades of research into these vectors show promising results. Here, we discuss the mucosal immune systems focusing on the gut–lung axis microbiome and offer new insight into the potential use of alpha streptococci in the upper respiratory tract as a vaccine carrier.
Conceptualizing Problem-Based Learning: An Overview

© 2022 International Journal of Applied and Basic Medical Research | Published by Wolters Kluwer ‐ Medknow In an attempt to restructure the medical undergraduate curricula so as to equip medical graduates with essential competencies expected of an Indian Medical Graduate (IMG) and to keep pace with the changing dynamics of health in India, the National Medical Commission has introduced competency-based medical education in Graduate Medical Education Regulations-2019. [1] Competency in medical graduates can be developed through the acquisition of knowledge integrated with clinical and attitudinal skills necessary to provide high-quality, effective patient care. Competency development is also influenced by the way medical educators facilitate the growth of an integrated knowledge structure in place of rote memorization of facts or procedural practice.
Soil Water Content Directly Affects Bud Burst Rate in Single-Node Cuttings of Perennial Plants

The use of single-node cuttings of shoots as explants to study bud dormancy and its physiology under controlled conditions is a common practice in grapevine (Vitis vinifera L.) or other perennial plant research. In particular, this method has been extensively used to understand the effect of different chemicals on bud dormancy and bud burst. However, the soil water content in those experiments is usually not reported and its relevance is often neglected. Here, we observed that an unevenly distributed soil water content in a tray containing multiple explants results in an uneven pattern of bud burst within the same treatment. Thus, we hypothesised that soil water content can dramatically affect bud burst. To investigate this, we first established that fresh single-node cuttings were able to transport water into the buds. We then tested the rate of bud burst at different water treatments (35%, 55%, 70%, 85%, and 100% of field capacity; FC). We observed a clear dependence of bud burst on water, in which, at very low levels of water, bud burst does not occur; after 35% FC, bud burst rate increases with water content until around 85% FC; and, from 85% FC, bud burst rate becomes independent of water content. These data highlight the critical importance of monitoring soil water content in any bud burst assay in perennials. Finally, we provide a detailed protocol for determining and controlling field capacity and other soil water content indicators.
Selenium nanoparticles inhibited H1N1 influenza virus-induced apoptosis by ROS-mediated signaling pathways

Influenza A (H1N1) viruses are distributed around the world and pose a threat to public health. Vaccination is the main treatment strategy to prevent influenza infection, but antiviral drugs also play an important role in controlling seasonal and pandemic influenza. Currently, as influenza viruses may be developing antiviral resistance, new agents with different modes of action are being investigated. Recently, selenium nanoparticles (SeNPs), which have antiviral effects, have attracted increasing attention in biomedical interventions. The appearance of nanotechnology has attracted great attention in the field of nanomedicine. SeNPs constitute an attractive vector platform for delivering a variety of drugs to action targets. SeNPs are being explored for potential therapeutic efficacy in a variety of oxidative stress and inflammation-mediated diseases, such as cancer, arthritis, diabetes, and kidney disease. SeNPs could inhibit infection of Madin–Darby canine kidney (MDCK) cells with H1N1 and prevent chromatin condensation and DNA fragmentation. ROS play a key role in physiological processes for apoptosis. SeNPs significantly inhibited the production of reactive oxygen species (ROS) in MDCK cells. Mechanistic investigation revealed that SeNPs inhibited the apoptosis induced by H1N1 virus infection in MDCK cells by improving the level of GPx1. Our results suggest that SeNPs are an effective selenium source and a promising H1N1 influenza antiviral candidate.
Identification of Leaf Diseases in Potato Crop Using Deep Convolutional Neural Networks (DCNNs)

Potatoes are used by a billion people globally as its intake per capita is 31.3 kilograms per month worldwide and its crop production surpasses 300 million metric tons. They have great nutritional potential and offer more protein and iron than other vegetables. Various diseases, such as early blight, late blight, and others, will attack potato plants and manifest their symptoms in the leaves. If these outbreaks are discovered early and appropriate treatment is taken, the farmer will not suffer significant economic losses. In this article, the suggested computer vision deep learning approach would significantly help in early identification and detection of different potato disease. Many plant diseases have different visual characteristics that may be utilized to accurately identify and classify them. This study describes a potato disease classification method based on computer vision-deep learning combination. The system trains deep convolutional neural networks such as ResNet-152 and InceptionV3 on the Kaggle potato dataset with an accuracy of 98.34% and 95.24% respectively at learning rate of 0.0005. This system successfully performs the classification of three categories: healthy, early, and late blight for potato leaves.
On the Genesis of the South China Sea Mesoscale Eddies

The climatology of the mesoscale eddies in the upper layer of the South China Sea (SCS) is investigated for an understanding of its genesis using the outputs from a 1/12.5° ocean reanalysis. Employed is a recently developed multiscale energetics formalism on the basis of a multiscale window transform (MWT) and the theory of canonical transfer. Three scale windows, namely, background flow, mesoscale eddy and synoptic eddy, are differentiated, and fields on different scales are reconstructed henceforth. Diagnosis of the mesoscale eddy energy budget reveals that barotropic and baroclinic instabilities, wind work, advection and pressure work are essential ingredients of the eddy energy sources and sinks in the SCS, but their contributions vary from region to region. In the southwestern part of the SCS, the regional mesoscale eddy energy is mainly generated by barotropic instability, while in the northeastern SCS, baroclinic instability and the wind working directly on the eddies are the two dominant eddy generation processes. The eddies southwest of Taiwan are damped by outward energy transport via advection, while the decay of those southeast of Vietnam is due to pressure work. The three-scale framework also reveals that the interaction between the mesoscale eddies and higher-frequency synoptic eddies mainly serves as a sink for the mesoscale eddy energy in the SCS, except for the northeastern SCS, where significant inverse cascade of kinetic energy is found.
Development of Planar Illumination Strategies for Solving Mysteries in the Sub-Cellular Realm

Optical microscopy has vastly expanded the frontiers of structural and functional biology, due to the non-invasive probing of dynamic volumes in vivo. However, traditional widefield microscopy illuminating the entire field of view (FOV) is adversely affected by out-of-focus light scatter. Consequently, standard upright or inverted microscopes are inept in sampling diffraction-limited volumes smaller than the optical system’s point spread function (PSF). Over the last few decades, several planar and structured (sinusoidal) illumination modalities have offered unprecedented access to sub-cellular organelles and 4D (3D + time) image acquisition. Furthermore, these optical sectioning systems remain unaffected by the size of biological samples, providing high signal-to-noise (SNR) ratios for objective lenses (OLs) with long working distances (WDs). This review aims to guide biologists regarding planar illumination strategies, capable of harnessing sub-micron spatial resolution with a millimeter depth of penetration.
Soil-plant-microbiota interactions to enhance plant growth

The nature of the soil is shaped by the presence of roots and the soil microbiota. Bacteria, archaea and fungi profoundly alter plant growth and, in turn, depend on root exudation of carbon-rich and energy-yielding compounds. The microbial communities act as facilitators of plant processes by secreting plant growth regulators, solubilizing minerals, providing N for plant growth, altering plant immune responses and competing with plant pathogens. Characterizing and engineering the processes driven by the multiple microbial taxa that make up a “plant growth-promoting soil” represents an ecologically friendly solution that may lead to unprecedented increases in agronomic efficiency. This review outlines the characteristics of soil-plant-microbiota interactions that would lead to enhanced plant growth and the importance of characterizing the soil microbial communities with metabarcoding and shotgun metagenomics allied to machine learning analytics. Although much is still needed to be understood about soil microbial ecology, it is possible to choose the best soil management practices to take advantage of beneficial microbial activity with our current knowledge.
Asymmetric Damage Mechanism of Floor Roadway based on Stope Floor Zonal Damage Characteristics: A Case Study

By means of field observation, theoretical analysis, numerical simulation etc., the zonal failure characteristics of stope floor and the asymmetric failure mechanism of floor roadway were studied. The study results showed that the floor roadway rib near the residual coal pillar has lower ultrasonic wave velocity than the other rib, with more developed fissures. The deflection is larger in the middle of the roadway roof and the tensile failure is the dominant one, and as a result, the ultrasonic wave velocity in the middle of the roadway roof is lower than that on both sides; under the advance abutment pressure, there was no large-scale failure in stope floor, while in the compaction stability stage, a large range of compressive shear failure was found in the residual pillar floor. The mining-induced unloading causes a large tensile stress at the internal defects of the floor rock in the goaf, which leads to the goaf floor dominated by tensile failure; the numerical simulation results revealed that there is a spherical stress concentrated shell and spherical stress relief body in the goaf floor. The shape and range of tensile plastic zone of the goaf floor correspond to the spherical stress relief body, and the shape and range of shear failure zone of the floor correspond to the spherical stress concentrated shell; One side of the floor roadway is close to the rock mass with compressive shear damage and the other side close to the rock mass with unloading-induced tensile damage, which is the main reason for the asymmetric failure of the roadway. According to the asymmetric failure mechanism of the floor roadway, asymmetric support measures are proposed for the roof and floor respectively.