Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends of extreme precipitation at the North Appalachian Experimental Watershed in east-central Ohio

The impact of climate change on many disciplines has been examined by researchers in recent decades. One of the indicators of climate change is increasing extreme precipitation. The annual, seasonal, and monthly precipitation trends at the North Appalachian Experimental Watershed (NAEW) were studied to identify statistically significant changes in precipitation trends and to compare the consistency of local precipitation trends with reported trends on a regional scale. Daily average precipitation was calculated using data collected from 1939 to 2011 at 11 rain gauges located at the NAEW near Coshocton, Ohio. Rank correlation was used to test for trends for three time periods (annual, seasonal, and monthly), for three response variables (total amount of precipitation, number of wet days, and the maximum daily precipitation), and for three data sets (the complete set of data and the upper 10th and 5th percentile data sets). Total precipitation showed a significant increasing trend for the fall season and for the months of October and November. Number of wet days showed significantly increasing trends for the months of August, October, and December. Maximum daily precipitation showed significantly increasing trends for the fall season as well as for three individual months of fall (September, October, and November). Considering the upper 10th, the annual averaged precipitation as well as seasonally averaged precipitation of fall and summer showed significantly increasing trends. Considering the upper 5th, the seasonally averaged precipitation of fall and winter showed significantly increasing trends. Annual and extreme trends on the local scale for the time period of 1958 to 2011 showed consistency with the reported trends by Karl et al. (2009) for regional scales for the time period of 1958 to 2007. The first and second response variables showed significant annual increasing trends for the complete set of data as well as for the upper 10th and 5th percentiles from 1958 to 2011. A piecewise linear least-squares estimation showed that starting in ~1963 annual precipitation changes from a decreasing trend to an increasing trend. However, the decreasing trend was not significant, and only the post-1963 data showed a significant increasing trend. The results were similar in Karl's regional approach. Based on the results, one to three months of the fall season (September, October, and November) have an increasing trend in the three precipitation response variables.
Automatic Object Based Plant-level Crop Segmentation in Drone-based Hyperspectral Imagery

In today’s technologically advanced world, precision agriculture plays a pivotal role in enhancing crop yields and minimizing environmental impact by employing data-driven, site-specific farming practices. Agricultural fields can be closely and effectively monitored utilizing drone-mounted hyperspectral sensors with improved spatial, spectral, and temporal resolution. Drone-based spectral imaging has enabled the undertaking of studies aimed at field-level agriculture. Although research on field-level crop monitoring and mapping is well in progress, analyzing crop and soil environment dynamics at finer scales, such as within-field patches or individual plant levels, has yet to be addressed. Object-based image analysis (OBIA) is an approach for detecting objects with greater precision than traditional pixel-based technologies by utilizing both spectral and spatial information. Dimensionality reduction is critical in this context, as it aids in selecting the most discriminating bands for effective segmentation, the primary task of OBIA. In this study, we evaluate various segmentation approaches for discriminating crops in drone-based hyperspectral imagery at the individual plant level, followed by the classification of segmented objects.
FPGA-Based Efficient MLP Neural Network for Digit Recognition

Field Programmable Gate Array (FPGA) based accelerators for Convolutional Neural Networks (CNN) have been developed to address the need for high performance and reconfigurability. The computation throughput of these accelerators may not match the memory bandwidth provided by the FPGA platform, which limits performance. Therefore, a structural improvement in the developed Multiply and Accumulate (MAC) unit within the CNN layers can substantially improve the performance of the network. This work proposes a Multi-Layer Perceptron (MLP) model, developed in Verilog HDL, and synthesized on Xilinx Kria (xck26) FPGA. The model uses the MNIST dataset used for digit recognition as input, implemented using Python on Spyder IDE. The accuracy of the model is obtained for different numbers of epochs and a maximum accuracy model is developed. The weight files from this maximum accuracy model and the bias files are extracted. These weight and bias files are provided as inputs to the MLP model developed in Xilinx Vivado. The model is verified by providing a known input to the Python model and extracting these weights to verify the model in Verilog HDL. The CNN model gives an accuracy of 99.68% for the training dataset and 94.5% for the testing dataset. The utilization of the FPGA resources for the proposed MLP design is 41.32% more efficient than a conventional MAC implementation.
A Salient Feature System for Profanity Detection and Saliency Checking in Text

The paper proposes a system for Profanity Detection and Saliency Checking in Text to address the need for effective content moderation in applications. Profanity detection is used to identify and flag profane words or phrases in text, while saliency checking determines the importance of individual words or phrases in a given context. The system integrates these functionalities and leverages natural language processing and machine learning techniques. It aims to enhance content moderation, sentiment analysis, and text summarization in applications, contributing to a more engaging and respectful digital environment. The paper also highlights the tangible results achieved by the system and its potential use in various applications. By combining profanity detection and saliency checking, the Salient Feature System offers a multifaceted approach to address the challenges posed by textual data in the digital age.
Personalized Clustering of Glucose Time Series in Patients with Type-1 Diabetes Mellitus Using Self Organized Maps During Nocturnal Sleep

The application of clustering techniques to glucose time series data has the potential to enhance early detection and effective management of diabetes and other metabolic disorders. This, in turn, can contribute to improved clinical outcomes and patient-reported outcomes. In this study, we aim to address the issue of personalized clustering of glucose time series data, specifically those recorded during the nocturnal sleep period, via Self Organized Maps. The clustering model was constructed using a dataset comprising 22 patients diagnosed with type 1 diabetes who were closely monitored for a maximum duration of 4 weeks as part of the GlucoseML study. Based on the silhouette coefficient score, two distinct clusters have been identified, indicating the presence of two separate glucose distributions observed during nocturnal sleep. Within Cluster 1, it has been observed that 90% of glucose values fall within the desired euglycemic range of 70-180 mg/dL. Consequently, there is a corresponding increase in the likelihood of hypoglycemia, with a rate of 2.4% occurring below the threshold of 70 mg/dL. Within Cluster 2, patients show a mainly hyperglycemic profile, characterized by 64.4% of values exceeding 180 mg/dL, while no instances of hypoglycemia were observed.
A 23-30 GHz Low-Phase-Noise 5-Bit Voltage-Controlled Oscillator in 90-nm CMOS Process

In this paper, a Ka-band 5-bit voltage-controlled oscillator (VCO) is presented using a 90-nm CMOS process. The proposed VCO is composed of 5-bit switched-capacitor array (SCA) and 1-bit switchable varactor array to achieve a wide tuning range of 27.5% and an excellent tuning figure-of-merit (FoMT) of −193.1 dBc/Hz. The proposed 5-bit VCO also demonstrates a lowest phase noise of -103.5 dBc/Hz at 1-MHz offset frequency, corresponding to a FoMPN of −184.4 dBc/Hz. The measured oscillation frequency is from 22.6 to 29.8 GHz with a differential output power of higher than −3 dBm. The chip size is 0.94 $\times$ 0.81 mm2. The core dc power consumption is merely 3 mW with a supply voltage of 0.6 V. The circuit performances can be compared to the reported silicon-based advanced VCOs.
A Node Confidence Determination Based Moving Target Defense Strategy for SDN

With the rapid development of Internet technology, network assets have become an indispensable part of modern society. Especially in the face of high-value network assets, the attacker is faced with paying a greater cost to study the network structure. Due to the unknown attacker and attack means, the attacker has an advantage in the attack and defense situation. The moving target defense technique can flexibly change the static characteristics of the network attack surface and increase the difficulty for the attacker to detect the network, thus achieving the purpose of enhancing network security. Based on this technique, this paper proposes a defense strategy based on node confidence. It puts forward stricter constraints on the differential selection of address/port hopping paths, dynamically selects the hopping objects according to the node’s confidence, and implements the defense strategy of differential complexity. This further increases the network’s uncertainty and the difficulty for the attacker to detect the network structure. The experimental results show that in the path differentiation comparison, the maximum improvement is about 18% compared to the Dynamic Random Route Hopping strategy. In the CPU load experiment, the CPU load rate is reduced by about 4.625% on average compared to the Double Address Hopping strategy. Moreover, for larger hopping period, the proposed strategy also performs well in terms of CPU load rate. The proposed strategy also exhibits good performance in terms of CPU load ratio for large hopping cycles.
Pushing the Limits of Address Based Authentication: How to Avoid MAC Address Spoofing in Wireless LANs

It is well-known that in wireless local area networks, authenticating nodes by their MAC addresses is not secure since it is very easy for an attacker to learn one of the authorized addresses and change his MAC address accordingly. In this paper, in order to prevent MAC address spoofing attacks, we propose to use dynamically changing MAC addresses and make each address usable for only one session. The scheme we propose does not require any change in 802.11 protocols and incurs only a small performance overhead. One of the nice features of our new scheme is that no third party can link different communication sessions of the same user by monitoring MAC addresses therefore our scheme is preferable also with respect to user privacy. Keywords—Authentication, MAC address spoofing, security, wireless networks.
Djurhälsa hos snabb- och långsamväxande hybrider i ekologisk slaktkycklingproduktion

Efterfragan av ekologiskt slaktkycklingkott okar i varlden pa grund av att konsumenter vardesatter visionen om en battre djurvalfard, men de ekologiska slaktkycklingproducenterna ar fa. Det finns problematik i regelverket kring ekologisk slaktkycklingproduktion som medfor svarigheter i att na en ekonomiskt lonsam och etiskt forsvarbar produktion. EU:s regelverk for ekologisk produktion hanvisar till att anvanda langsamvaxande hybrider men majoriteten av de kommersiellt tillgangliga slaktkycklingarna ar snabbvaxande hybrider. Snabbvaxande hybrider anvands darfor ofta i ekologiska system i Sverige pa grund av att tillgangen pa langsamvaxande hybrider ar lag. Snabbvaxande hybrider ar avlade for en intensiv uppfodning med snabb tillvaxt och god foderomvandlingsformaga avsedd for konventionella produktionsmiljoer. Selektionen for snabb tillvaxt i kontrollerade miljoer har lett till produktionssjukdomar, hogre dodlighet, obalanserade kroppar och passivt beteende. I ett ekologiskt system med langre uppfodningstid blir frekvensen av halsoproblemen annu hogre hos snabbvaxande hybrider och langsamvaxande hybrider anses vara en potentiell losning till problemen. Halsoproblem ar betydligt ovanligare hos langsamvaxande hybrider jamfort med snabbvaxande hybrider. Ur ett etiskt perspektiv bor darfor snabbvaxande hybrider inte hallas i ekologiska system och langsamvaxande hybrider ar battre lampade for dessa system, med lang uppfodningstid och tillgang till utevistelse. Det finns dock indikationer pa halsoproblem aven hos langsamvaxande hybrider och framtida slaktkycklingsavel for ekologiska produktionssystem bor strava mot lag tillvaxttakt, battre benhalsa och motstandskraft mot sjukdomar.
Transcriptome-Wide Identification of Cytochrome P450s in Tea Black Tussock Moth (Dasychira baibarana) and Candidate Genes Involved in Type-II Sex Pheromone Biosynthesis

Simple Summary Sex pheromone plays an important role in mediating mate communication for the tea black tussock moth, Dasychira baibarana, which is a devastating pest in Chinese tea plantations. The sex pheromone of this pest is a ternary blend, including two typical Type-II epoxides and one unsaturated ketone. This study investigated P450 candidates that are associated with the biosynthesis of the sex pheromone components. With a combination of comparative RNAseq, phylogenetic, and tissue expression pattern analysis, one CYP4G with abdomen specifically predominant expression profile was likely to be the P450 decarbonylase, and the pheromone-gland specifically and most abundant CYP341B65 was the most promising epoxidase. This research laid a valuable foundation not only for further functional characterization of P450 decarbonylase and epoxidase in the sex pheromone biosynthetic pathway but also for understanding the physiological functions and functional diversity of the CYP gene superfamily in the D. baibarana. Abstract The tea black tussock moth (Dasychira baibarana), a devastating pest in Chinese tea plantations, uses a ternary Type-II pheromone blend containing (3Z,6Z)-cis-9,10-epoxyhenicosa-3,6-diene (Z3,Z6,epo9-21:H), (3Z,6Z,11E)-cis-9,10-epoxyhenicosa-3,6,11-triene (Z3,Z6,epo9,E11-21:H), and (3Z,6Z)-henicosa-3,6-dien-11-one (Z3,Z6-21:11-one) for mate communication. To elucidate the P450 candidates associated with the biosynthesis of these sex pheromone components, we sequenced the female D. baibarana pheromone gland and the abdomen excluding the pheromone gland. A total of 75 DbP450s were identified. Function annotation suggested six CYPs were orthologous genes that are linked to molting hormone metabolism, and eight antennae specifically and significantly up-regulated CYPs may play roles in odorant processing. Based on a combination of comparative RNAseq, phylogenetic, and tissue expression pattern analysis, one CYP4G with abdomen specifically predominant expression pattern was likely to be the P450 decarbonylase, while the pheromone-gland specifically and most abundant CYP341B65 was the most promising epoxidase candidate for the D. baibarana sex pheromone biosynthesis. Collectively, our research laid a valuable basis not only for further functional elucidation of the candidate P450 decarbonylase and epoxidase for the sex pheromone biosynthesis but also for understanding the physiological functions and functional diversity of the CYP gene superfamily in the D. baibarana.
Skid Trail Stream Crossing Closure Techniques for Protecting Water Quality

The impact of forest roads and skid trails on stream health is being increasingly scrutinized. Forest roads and skid trails have repeatedly been identified as forest operations having the greatest potential to produce sediment by way of non-point source pollution. The stream crossing portion of a skid trail is where sediment delivery is most likely to occur. Forestry Best Management Practices (BMPs) have been developed by most states to reduce both erosion and sedimentation. In general, BMPs have been proven to be effective. Few studies have quantified the impact of various levels of BMPs on sedimentation. In this study, three replications of three skid trail stream crossing BMP treatments were monitored following skidder bridge removal to determine their efficacy in reducing sedimentation: slash, mulch, and mulch plus silt fence. Water samples were collected upstream and downstream of each crossing daily for one year following timber harvesting. Samples were evaluated for total suspended solids. Results indicate that both slash and mulch treatments applied to the stream crossing approach after skidder bridge removal are effective at reducing stream sedimentation after harvest. The mulch plus silt fence treatment allowed the most sediment to enter the stream at the approach, perhaps due to silt fence installation disturbances. We do not recommend using silt fences directly adjacent to a stream bank, if other alternatives exist.
Enhancing Dynamic Performance in K-Rb-21Ne Co-Magnetometers through Atomic Density Optimization

The K-Rb-21Ne co-magnetometer exhibits poorer dynamic performance due to the larger equivalent magnetic field generated by alkali metal atoms. In this study, the impact of the atomic number density of alkali metal atoms and noble gas atoms in the cell on the dynamic performance of the atomic ensemble is investigated quantitatively. Relationships between the slow-decay term in the transient response attenuation of the Spin-Exchange Relaxation-Free (SERF) co-magnetometer to interference magnetic fields and the number densities of noble gas atoms as well as alkali metal atoms are established. Based on the established model, the relationship between the number density of 21Ne atoms and dynamic performance is investigated using cells with five different noble gas pressures. Then, we investigate the impact of the number density of alkali metal atoms using a cell with a pressure of 2.1 atm at different temperatures. The results indicate that, as the number density of alkali metal atoms or noble gas atoms in the cell increases, the dynamic performance of the system improves, which provides a theoretical basis for the design of cell parameters for SERF co-magnetometers.
The Role of the Dysregulated JNK Signaling Pathway in the Pathogenesis of Human Diseases and Its Potential Therapeutic Strategies: A Comprehensive Review

JNK is named after c-Jun N-terminal kinase, as it is responsible for phosphorylating c-Jun. As a member of the mitogen-activated protein kinase (MAPK) family, JNK is also known as stress-activated kinase (SAPK) because it can be activated by extracellular stresses including growth factor, UV irradiation, and virus infection. Functionally, JNK regulates various cell behaviors such as cell differentiation, proliferation, survival, and metabolic reprogramming. Dysregulated JNK signaling contributes to several types of human diseases. Although the role of the JNK pathway in a single disease has been summarized in several previous publications, a comprehensive review of its role in multiple kinds of human diseases is missing. In this review, we begin by introducing the landmark discoveries, structures, tissue expression, and activation mechanisms of the JNK pathway. Next, we come to the focus of this work: a comprehensive summary of the role of the deregulated JNK pathway in multiple kinds of diseases. Beyond that, we also discuss the current strategies for targeting the JNK pathway for therapeutic intervention and summarize the application of JNK inhibitors as well as several challenges now faced. We expect that this review can provide a more comprehensive insight into the critical role of the JNK pathway in the pathogenesis of human diseases and hope that it also provides important clues for ameliorating disease conditions.
Association mapping for seed size and shape traits in soybean cultivars

Seed size and shape traits are closely related to seed yield and appearance quality in soybean (Glycine max L.). Previous studies were mainly derived from bi-parental segregating populations and relatively little is known about the results in soybean cultivars. In this study, 257 soybean cultivars obtained by stratified random sampling from six geographic ecotypes in China were used to carry out association mapping for these traits using information from 135 simple sequence repeat markers and an epistatic association mapping approach implemented using an empirical Bayes algorithm. In this analysis, seed size was measured by seed length (SL), width (SW) and thickness (ST), and seed shape was evaluated by seed length-to-width (SLW), length-to-thickness (SLT) and width-to-thickness (SWT) ratios, in 2008-2010. A total of 59 main-effect quantitative trait loci (QTL) and 31 QTL-by-environment interactions were iden- tified. Among them, 25 QTL were associated simul- taneously with at least two traits; 80 QTL (90 %) could be confirmed by enriched compression mixed linear model analysis; and the size for a large number of detected QTL was minor, except for qSL-5, qSW-7e, qST-5-2 and qSLW-2. According to the estimates for the allelic effects of the detected QTL, elite alleles could be mined: for example, the 307-bp allele of QTL linked to satt453 was the best for seed length. These elite alleles could be used to design parental combi- nations; e.g., the cross of Zhenghezhibanzi and Nannongdahuangdou might improve seed length, and the combination of cultivars Lindou10, De- qingxiangzhudou, Ninghaixiazhidou, Zhenghezhi- banzi, 0803, Shangqiu7605 and 0831 might pyramid 42 elite alleles.
Rosuvastatin as a Supplemental Treatment for the Clinical Symptoms of Nephropathia Epidemica: A Pilot Clinical Study

Nephropathis epidemica (NE), a mild form of hemorrhagic fever with renal syndrome (HFRS), is an acute zoonotic disease endemic in the Republic of Tatarstan. This study aimed to assess the impact of rosuvastatin on the clinical and laboratory results of NE. A total of 61 NE patients and 30 controls were included in this study; 22 NE patients and 7 controls received a daily dose of rosuvastatin (10 mg) for ten consecutive days. Serum samples were collected on days 1, 5, and 10 after admission to the hospital. These samples were analyzed to determine the levels of lipids, cytokines, and kidney toxicity markers. Our findings indicate that rosuvastatin reduced the duration of the second wave of fever and alleviated back pain and headache symptoms. Additionally, low-density lipoprotein cholesterol (LDL-C) serum levels were significantly decreased on days 5 and 10 upon rosuvastatin treatment. Furthermore, rosuvastatin decreased the levels of cytokines in the serum, particularly proinflammatory cytokines IL-1β and IL-8. NE patients had significantly altered levels of the kidney toxicity markers albumin and osteopontin. The data from our study provide evidence supporting the therapeutic potential of rosuvastatin in NE cases.