Miracle-dz/UniFAR-FTUs huggingface dataset:
First record of the non-native fish Rhinogobius cliffordpopei (Nichols, 1925) (Gobiiformes: Gobiidae) in Tibet, China

Nichols’ common goby Rhinogobius cliffordpopei (Nichols, 1925) is a small-bodied benthic carnivorous fish, and native to central and southeast China. Due to the interregional commercial exchanges of aquaculture and aquatic trade, it has widely introduced numerous water bodies outside the original range in China, but has not been found in Tibet. During a fish survey in May 2022, we collected 22 individuals of R. cliffordpopei , including five juveniles, from four sites in the Yarlung Zangbo River in Tibet. This finding suggests that R. cliffordpopei has established wild populations in the Yarlung Zangbo. To protect the endemic species, government departments should strictly limit the release to reduce the potential risks of non-native species.
Sources of Farm Risk and Management Strategies among Cowpea (Vigna unguiculata SSP) Producers in North East Nigeria

: The study identified sources of farm risks and management strategies used among cowpea producers in North East, Nigeria. Data were collected using structured questionnaires from 595 cowpea producers. Multi-stage sampling procedure was used to select cowpea producers for the study. In the first stage purposive sampling was used to select three (3) states from the six (6) states in the region and these states include Adamawa, Bauchi and Gombe States. From these selected states two (2) local governments each were selected based on apriory information on cowpea production from the state Agricultural Development Programs (ADPs) and analysed using descriptive statistics, Likert scale and multiple regression model. The result revealed that, pest and diseases emerged as the common source of production risk at 74%. Also, uncertainty from product price 66% was a major source of marketing risk. Furthermore, inadequate credit was an important financial risk at 54% and lack of cooperative 51% were major sources of both financial and institutional risks. The valid management strategies used in mitigating/coping among cowpea producers were livestock production to complement income, sales of produce, engagement in other jobs/activities, access to ADP’s extension agent among others. Therefore, cowpea production is affected by production/environmental risk, marketing risk, financial risk, institutional risk and human/personnel risk and exhibited risk aversion attitude. The study recommends strategy of developing early varieties, disease resistant crops and products that are resistant to pest both in the farm and storage to raise the productivity of cowpea. Also, cowpea producers’ cooperatives should be strengthened with priority given enlightened/educating members, create strong bargaining power for farm products as well as accessing credit facilities. Similarly, inputs such as fertilizers and certified improved high-quality seeds are available and accessible to cowpea producers to increase production and reduce risks.
Stem volume current annual growth rhythm of four Populus tomentosa clones under water-nitrogen coupling and variety selection

Through the experiments of water-nitrogen coupling for Populus tomentosa plantation in Weixian county Hebei province,the influences of water and nitrogen on the stem volume current annual increments of Populus tomentosa clones(BT17,B331,S86,1316) in the second year and fourth year of forestation were investigated and a mathematical model was established.The main results were as follows: the coupling and alternating effects of nitrogen and water to the stem volume current annual increments of four Populus tomentosa clones existed,and the interaction effects of water and nitrogen were positive correlation.The different conditions of water and nitrogen produced the different stem volume current annual increments.The stem volume current annual increments of four Populus tomentosa clones increased gradually with the increases of application amount of nitrogen and soil water content within the limits of experimental scheme.The effects of water,nitrogen and the interactive effects of water and nitrogen on the stem volume current annual increments of four Populus tomentosa clones in the second year of forestation were water nitrogen the interactive effect of water and nitrogen.The effects of water,nitrogen and the interactive effect of water and nitrogen on the stem volume current annual increments of four Populus tomentosa clones in the fourth year of forestation were nitrogen water the interactive effect of water and nitrogen.For stem volume current annual increments of four Populus tomentosa clones(BT17,B331,S86,1316) in the second year of forestation,the optimum application rates of nitrogen were 0.373 1,0.399 2,0.432 7,0.342 5 t·hm-2 respectively,and the optimum soil relative water contents were 74.93%,76.44%,77.74%,76.72% of field capacity respectively.For stem volume current annual increments of four Populus tomentosa clones(BT17,B331,S86,1316) in the fourth year of forestation,the optimum application rates of nitrogen were 0.419 8,0.455 1,0.480 8,0.367 4 t·hm-2 respectively,and the optimum soil relative water contents were 80.71%,83.47%,85.56%,78.42% of field capacity respectively.The growth rates and drought resistance capacity of BT17,B331,S86,1316 existed remarkable differences and the order was S86B331BT171316.
A rainfall design method for spatial flood risk assessment: considering multiple flood sources

Information about the spatial distribution of flood risk is important for integrated urban flood risk management. Focusing on urban areas, spatial flood risk assessment must reflect all risk information derived from multiple flood sources: rivers, drainage, coastal flooding etc. that may affect the area. However, conventional flood risk assessment deals with each flood source independently, which leads to an underestimation of flood risk in the floodplain. Even in floodplains that have no risk from coastal flooding, flooding from river channels and inundation caused by insufficient drainage capacity should be considered simultaneously. For integrated flood risk management, it is necessary to establish a methodology to estimate flood risk distribution across a floodplain. In this paper, a rainfall design method for spatial flood risk assessment, which considers the joint effects of multiple flood sources, is proposed. The concept of critical rainfall duration determined by the concentration time of flooding is introduced to connect response characteristics of different flood sources with rainfall. A copula method is then adopted to capture the correlation of rainfall amount with different critical rainfall durations. Rainfall events are designed taking advantage of the copula structure of correlation and marginal distribution of rainfall amounts within different critical rainfall durations. A case study in the Otsu River Basin, Osaka prefecture, Japan was conducted to demonstrate this methodology.
Advanced Hybrid Model for Multi Paddy diseases detection using Deep Learning

INTRODUCTION: Rapid developments in deep learning (DL) techniques have made it possible to find and recognize objects in pictures. To create a network that is significantly more successful than a single CNN, GAN, RNN, etc., we can mix various neural network models (CNN, GAN, RNN). this combination is known as hybrid model. Hybrid model of deep leaning is give more accurately result for detection and identification of paddy diseases. OBJECTIVES: I have studies outcome of hybrid model 1(DCNN+SVM) and Hybrid model 2 (DCNN + Transfer Learning) to increase accuracy of Rice plant disease detection and classification. The Researched model detects multiple rice plant diseases and it is giving same result in multiple data sets. METHODS: The Proposed System have used Deep Learning Image Processing algorithm and neural Network Like DCNN ,SVM and Transfer Learning . The brand new model is DST where D stands for DCNN, S stands for SVM and T stands for transfer learning. RESULTS: The Researched DST model achieved 95% Training accuracy and 85% validation Accuracy. The Researched model detect multiple rice plant diseases and it is giving same result in multiple data set. CONCLUSION: The proposed model combined 2 existing model and developed hybrid model that a detect various rice plant diseases with better accuracy from available existing model.
Cost-Efficient Method for Detecting and Mitigating DDOS Attacks in SDN Based Networks

Software-defined networks (SDN) provide a centralized administration programming interface for managing the network infrastructure. This new approach replaced traditional networks by establishing a flexible connection between the control and data planes, managing network operations through a centralized controller. As a result, prioritizing the security of the SDN controller becomes imperative in SDN networks. In the recent wave of distributed denial-of-service (DDoS) attacks, attackers have shifted their strategy from directly targeting the SDN controller to concentrating on specific links or area, causing disruptions in connectivity. This attack, known as Link-flooding attack (LFA), represent a novel form of DDoS attack. LFA targets the SDN control channel, which transmits control traffic from the SDN controller to switches, taking advantage of shared links in both control and data traffic paths. This sharing exposes a vulnerability that attackers can exploit to disrupt the control channel, using malicious data traffic to execute LFA. Considering the control channel's responsibility for granting centralized control to the controller over each network switch, it becomes relatively easy for an attacker to compromise all network functions. To handle this problem, in this paper, we develop a novel approach based on SDN designed for security solutions against DDoS and LFA. Our proposed scheme utilizes hop-by-hop network measurement to identify and capture abnormal link performance, enabling effective detection of such attacks. Subsequently, a Machine Learning (ML) model is employed to determine whether the congested links indicate the presence of such attacks. Unlike conventional approaches in the literature that solely rely on automatic ML models, our method begins by measuring congestion in each link. If abnormalities are detected, the ML model is then executed to identify whether it is an attack or not. By adopting this approach, we achieve optimized utilization of controller resources. Our proposed scheme will be implemented as an application at the application layer of the Ryu controller. Through our evaluation, we have demonstrated that this approach can efficiently optimize the process of measuring link performance, optimizing the utilization of SDN controller resources, and detecting DDoS and LFA.
Powering HTC Thermometers and LED Lamps with Microwave Energy

As of 2025, 30.9 billion Internet of Things (IoT) devices will be installed worldwide, up sharply from 13.8 billion units in 2021. Wireless Power Harvesting (WPH) is a next-generation low-power electronics technology we can utilize to power IoT devices. This paper studies how to energize wirelessly smart Internet of Things (IoT) devices with WPH. We can make our lives smarter and more convenient by upgrading IoT devices to use microwave harvesting technology. With future technology, IoT devices will self-energize and charge without wires or batteries. In this paper, we design a rectangular twice-patch antenna and seven-stage voltage multiplier for a microwave energy harvesting device. The project combines wireless power harvesting technology with a smart house. It provides enough energy to power 200 mW clocks and a led lamp with 5 W of power over a five-meter distance. Finally, we conclude that the harvester circuit coupled with the patch antenna can power up the bulb and clock, which will help make IoT devices battery-less.
Virtual Environment Model Generation for CPS Goal Verification using Imitation Learning

Cyber-Physical Systems (CPS) continuously interact with their physical environments through embedded software controllers that observe the environments and determine actions. Field Operational Tests (FOT) are essential to verify to what extent the CPS under analysis can achieve certain CPS goals, such as satisfying the safety and performance requirements, while interacting with the real operational environment. However, performing many FOTs to obtain statistically significant verification results is challenging due to its high cost and risk in practice. Simulation-based verification can be an alternative to address the challenge, but it still requires an accurate virtual environment model that can replace the real environment interacting with the CPS in a closed loop. In this paper, we propose ENVI (ENVironment Imitation), a novel approach to automatically generate an accurate virtual environment model, enabling efficient and accurate simulation-based CPS goal verification in practice.To do this, we first formally define the problem of the virtual environment model generation and solve it by leveraging Imitation Learning (IL), which has been actively studied in machine learning to learn complex behaviors from expert demonstrations. The key idea behind the model generation is to leverage IL for training a model that imitates the interactions between the CPS controller and its real environment as recorded in (possibly very small) FOT logs. We then statistically verify the goal achievement of the CPS by simulating it with the generated model. We empirically evaluate ENVI by applying it to the verification of two popular autonomous driving assistant systems. The results show that ENVI can reduce the cost of CPS goal verification while maintaining its accuracy by generating accurate environment models from only a few FOT logs. The use of IL in virtual environment model generation opens new research directions, further discussed at the end of the paper.
Dip-separated structural filtering using seislet transform and adaptive empirical mode decomposition based dip filter

The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural ﬁltering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic proﬁles that have dip conﬂicts. In order to remove the limitation of seislet thresholding in dealing with conﬂicting-dip data, I propose a dip-separated ﬁltering strategy. In this method, I ﬁrst use an adaptive empirical mode decomposition based dip ﬁlter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the ﬁnal denoised data. Compared with other dip ﬁlters, the empirical mode decomposition based dip ﬁlter is data-adaptive. One only needs to specify the number of dip components to be separated. Both complicated synthetic and ﬁeld data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural ﬁltering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.
Innovative Functional Lactic Acid Bacteria Fermented Oat Beverages with the Addition of Fruit Extracts and Lyophilisates

Nowadays, plant-based fermented products are attracting a lot of consumer interest due to their probiotic and health-promoting properties. The aim of this study was to evaluate the microbiological quality and antioxidant activity of innovative fermented oat beverages with the addition of extracts and freeze-dried local fruit. In the first step, chokeberry and hawthorn were selected based on their antioxidant and antimicrobial properties. The final study material consisted of oat beverages fermented with the use of the Lactiplantibacillus plantarum DKK 003 strain for 20 h with the addition of 1 and 5% of extracts and freeze-dried fruits. It was found that freeze-dried chokeberry and chokeberry extracts showed a higher content of polyphenolic compounds than freeze-dried hawthorn and hawthorn extracts. After the fermentation process of the innovative beverages, the content of polyphenolic compounds remained the same or there was a slight decrease depending on the additive type. Antioxidant activity significantly decreased after 20 h of fermentation in all enriched oat beverages with no significant differences observed compared to control samples. The obtained fermented beverages were characterised by a high lactic acid bacteria count (above 8 log CFU/mL), a low pH (approximately 4.15), and no microbiological contamination. Oat fermented beverages with fruit additives can be good dietary enrichment products.
Three new species of myxomycetes from Siberia.

Information is provided on the find of three new species of myxomycetes of the Perichaena and Gulielmina genera. The description, ecology, known localities, and differences from morphologically similar species are given. A comparative study of the new myxomycete species with similar species was carried out using scanning electron microscopy. Micrographs with relevant details of sporocarps and spores are presented. An analysis of the molecular phylogeny of the new species was carried out and their connections with representatives of bright-spored myxomycetes are shown.
Increased Hepatocyte Growth Factor Secretion by Placenta-Derived Mesenchymal Stem Cells Improves Ovarian Function in an Ovariectomized Rat Model via Vascular Remodeling by Wnt Signaling Activation

The vascular network contributes to the development of follicles. However, the therapeutic mechanism between vascular remodeling and ovarian functions is still unclear. Therefore, we demonstrated whether increased HGF by placenta-derived mesenchymal stem cells (PD-MSCs) improves ovarian function in an ovariectomized rat model via vascular remodeling by Wnt signaling activation. We established a half-ovariectomized rat model in which damaged ovaries were induced by ovariectomy of half of each ovary, and PD-MSCs (5 × 105 cells) were transplanted by intravenous injection. Three weeks after transplantation, rats in all groups were sacrificed. We examined the secretion of HGF by PD-MSCs through culture medium. The vascular structure in injured ovarian tissues was restored to a greater extent in the PD-MSC transplantation (Tx) group than in the nontransplantation (NTx) group (* p < 0.05). The expression of genes related to Wnt signaling (e.g., LRP6, GSK3β, β-catenin) was significantly increased in the Tx group compared to the NTx group (* p < 0.05). However, the expression of genes related to vascular permeability (e.g., Asef, ERG3) was significantly decreased in the Tx group compared to the NTx group (* p < 0.05). Follicular development was improved in the Tx group compared to the NTx group (* p < 0.05). Furthermore, to evaluate vascular function, we cocultivated PD-MSCs after human umbilical vein endothelial cells (HUVECs) with lipopolysaccharide (LPS), and we analyzed the vascular formation assay and dextran assay in HUVECs. Cocultivation of PD-MSCs with injured HUVECs enhanced vascular formation and decreased endothelial cell permeability (* p < 0.05). Also, cocultivation of PD-MSCs with explanted ovarian tissues improved follicular maturation compared to cocultivation of the Wnt inhibitor-treated PD-MSCs with explanted ovarian tissues. Therefore, HGF secreted by PD-MSCs improved ovarian function in rats with ovarian dysfunction by decreasing vascular permeability via Wnt signaling.
Methodology for Selecting an Ideal Thermal Gasification Technique for Municipal Solid Waste Using Multi-Criteria Decision Analysis

Awareness of the consequences of waste mismanagement has resulted in urban planners looking for effective disposal techniques with the added benefit of energy generation. The decision regarding an energy conversion technique to adopt on a community level is based on different technology assessment factors with maximum weightage on environmental effects. Gasification techniques in general and thermal gasification strategies in particular are appropriate methods when environmental impacts are to be minimized. Thermal gasification techniques have evolved with different configurations, syngas generation rates, and other advantages and disadvantages; hence, the selection of the right technique is essential, and establishing guidelines for decision-makers is necessary. The six different gasifiers considered in the present study were updraft gasifiers, downdraft gasifiers, cross-draft gasifiers, bubbling fluidized bed gasifiers, circulating fluidized bed gasifiers, and dual-bed fluidized bed gasifiers. The assessments performed in the present study are based on the attributes of the different techniques using the multi-criteria decision method. Multi-criteria decision analysis is an appropriate method proven to be an ideal procedure in these situations. Attribute values for gasifier performance, environmental effects, economic performance indices, and fuel requirements were determined from collected waste assessment data and published information. Analysis was performed for both recycling and non-recycling scenarios of waste utilization by applying different weight scenarios for the attributes. Results of the study indicate that downdraft gasifiers showed the best performance in terms of environmental effects under the recycling scenario, with 0.1% and 0.0125% by volume of carbon dioxide and methane emissions, and under the non-recycling scenario, with 0.125% and 0.02% by volume of carbon dioxide and methane emissions. Downdraft gasifiers had high overall rankings in performance when evaluated against different entropy weights for both scenarios. The results of the study can be applied to urban communities in different climatic regions as well as for different scales of operation.