Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the effects of saline water use in agriculture

Use of saline groundwaters is inevitable in rice–wheat, cotton–wheat, and millet–wheat crop rotations in the northern region of India due to limited canal water supplies. The UNSATCHEM model is calibrated and validated with field data on saline water use for the wheat and cotton crop. The calibrated and validated model has been employed to study different aspects of the salinisation process. The effect of irrigation water quality on the salinisation process is understood with the help of simulations in which irrigation waters of different SAR, SO 4 2− and Cl− concentrations are used. A linear relation is observed between the weighted average of irrigation water salinity and the root zone. The salinisation process under different conjunctive use practices is understood through simulations. The practices are compared on the basis of temporal changes in root zone salinity with reference to the sensitivity of the wheat crop to salinity for deciding the preference of one conjunctive use practice over another. The preference order, thus prepared, is verified with the published yield data of wheat from conjunctive use field studies. The effect of soil texture on salinisation is studied through simulations. The saturated water content influences the salinisation process more than the hydraulic conductivity. The long‐term simulations as per water quality guidelines for a six‐year period under wheat–cotton rotation are carried out to assess the sustainability of saline water use for crop production. Copyright © 2006 John Wiley & Sons, Ltd.
The Effects of Separate and Combined Treatment of Male Rats with Type 2 Diabetes with Metformin and Orthosteric and Allosteric Agonists of Luteinizing Hormone Receptor on Steroidogenesis and Spermatogenesis

In men with type 2 diabetes mellitus (T2DM), steroidogenesis and spermatogenesis are impaired. Metformin and the agonists of luteinizing hormone/human chorionic gonadotropin(hCG)-receptor (LH/hCG-R) (hCG, low-molecular-weight allosteric LH/hCG-R-agonists) can be used to restore them. The aim was to study effectiveness of separate and combined administration of metformin, hCG and 5-amino-N-tert-butyl-2-(methylsulfanyl)-4-(3-(nicotinamido)phenyl)thieno[2,3-d]pyrimidine-6-carboxamide (TP3) on steroidogenesis and spermatogenesis in male rats with T2DM. hCG (15 IU/rat/day) and TP3 (15 mg/kg/day) were injected in the last five days of five-week metformin treatment (120 mg/kg/day). Metformin improved testicular steroidogenesis and spermatogenesis and restored LH/hCG-R-expression. Compared to control, in T2DM, hCG stimulated steroidogenesis and StAR-gene expression less effectively and, after five-day administration, reduced LH/hCG-R-expression, while TP3 effects changed weaker. In co-administration of metformin and LH/hCG-R-agonists, on the first day, stimulating effects of LH/hCG-R-agonists on testosterone levels and hCG-stimulated expression of StAR- and CYP17A1-genes were increased, but on the 3–5th day, they disappeared. This was due to reduced LH/hCG-R-gene expression and increased aromatase-catalyzed estradiol production. With co-administration, LH/hCG-R-agonists did not contribute to improving spermatogenesis, induced by metformin. Thus, in T2DM, metformin and LH/hCG-R-agonists restore steroidogenesis and spermatogenesis, with metformin being more effective in restoring spermatogenesis, and their co-administration improves LH/hCG-R-agonist-stimulating testicular steroidogenesis in acute but not chronic administration.
Watch and wait strategies for rectal cancer A systematic review

Watch and wait (WW) strategies have been suggested for patients with clinical complete regression (cCR). The WW approach was first introduced by Habr–Gama in patients with cCR after neoadjuvant treatment. Actually, it is not “no surgery” but “deferral of surgery”; therefore, the WW approach or non-operative management is a representative term currently. The number of publications regarding WW for rectal cancer has increased abruptly. We conducted a systematic review of PubMed for literature published on WW. It is now one of the most interesting issues in rectal cancer treatment. Many studies have reported comparable overall survival with WW and radical resection. However, a high local regrowth rate is a problem, and proper salvage management is the main concern in the WW approach. Adequate patient selection is necessary to achieve favorable oncologic outcomes. However, the appropriate definition and diagnostic method for cCR have not yet been clearly defined. Indeed, advances in local control have not translated into overall survival improvement, and many efforts have been made to improve distant metastasis control and overall survival and improve clinical response to preoperative chemoradiotherapy. In this review, oncologic outcomes, ongoing efforts to improve oncologic outcomes, and limitations for clinical practice were evaluated and described.
Genome-Wide Characterization and Analysis of Expression of the Histone Gene Family in Razor Clam, Sinonovacula constricta

The Chinese razor clam (Sinonovacula constricta), a bivalve species widely distributed in estuaries and mudflats, is often exposed to extreme environmental and microbial stresses. Histones are fundamental components of chromatin and play an important role in innate immunity, as demonstrated by its antimicrobial activities in clams. However, little attention has been paid to histones in bivalves. To fill this gap, we investigated the genomic distribution, structural characteristics, conserved motifs, and phylogenetic relationships of histones in S. constricta. A total of 114 histone genes were detected in the S. constricta genome, which were divided into 25 types in phylogenetic analysis. Among them, partial histones exhibited a tissue-dependent expression pattern, indicating that they may be involved in sustaining the homeostasis of organs/tissues in adult S. constricta. Furthermore, mRNA expression of certain histones changed significantly in S. constricta when infected with Vibrio parahaemolyticus, suggesting that histones play a role in the immune defense of S. constricta. All together, this study on histone genes in S. constricta not only greatly expands our knowledge of histone function in the clam, but also histone evolution in molluscs.
Predictive Analytic Techniques to Identify Hidden Relationships between Training Load, Fatigue and Muscle Strains in Young Soccer Players

This study aimed to analyze different predictive analytic techniques to forecast the risk of muscle strain injuries (MSI) in youth soccer based on training load data. Twenty-two young soccer players (age: 13.5 ± 0.3 years) were recruited, and an injury surveillance system was applied to record all MSI during the season. Anthropometric data, predicted age at peak height velocity, and skeletal age were collected. The session-RPE method was daily employed to quantify internal training/match load, and monotony, strain, and cumulative load over the weeks were calculated. A countermovement jump (CMJ) test was submitted before and after each training/match to quantify players’ neuromuscular fatigue. All these data were used to predict the risk of MSI through different data mining models: Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM). Among them, SVM showed the best predictive ability (area under the curve = 0.84 ± 0.05). Then, Decision tree (DT) algorithm was employed to understand the interactions identified by the SVM model. The rules extracted by DT revealed how the risk of injury could change according to players’ maturity status, neuromuscular fatigue, anthropometric factors, higher workloads, and low recovery status. This approach allowed to identify MSI and the underlying risk factors.
SPICE models for power MOSFETs: an update

Five existing power MOSFET models intended for use with SPICE simulations are reviewed and compared. Methods used for simulating the gate-drain capacitance are evaluated. The internal JFET employed in two of the models is found to be usually unnecessary. A simple two-value capacitance model is recommended. The performance of this model is demonstrated with data obtained from 200 kHz forward converter. <<ETX>>
Tag-n-track system for situation awareness for MOUTs

In order to train war fighters for urban warfare, live exercises are held at various Military Operations on Urban Terrain (MOUT) facilities. Commanders need to have situation awareness (SA) of the entire mock battlefield, and also the individual actions of the various war fighters. The commanders must be able to provide instant feedback and play through different actions and 'what-if' scenarios with the war fighters. The war fighters in their turn should be able to review their actions and rehearse different maneuvers. In this paper, we describe the technologies behind a prototype training system, which tracks war fighters around an urban site using a combination of ultra-wideband (UWB) Radio Frequency Identification (RFID) and smart video based tracking. The system is able to: (1) Tag each individual with an unique ID using an RFID system, (2) Track and locate individuals within the domain of interest, (3) Associate IDs with visual appearance derived from live videos, (4) Visualize movement and actions of individuals within the context of a 3D model, and (5) Store and review activities with (x,y,ID) information associated with each individual. Dynamic acquisition and recording of the precise location of individual troops and units during training greatly aids the analysis of the training sessions allowing improved review, critique and instruction.
Optimization of TSPWM for Common-Mode Voltage Reduction in Vehicular Electric Drive System

Common-mode voltage can be reduced effectively by optimized modulation methods without increasing additional costs. However, the existing methods cannot satisfy the requirements of the vehicular electric-drive application. This paper optimizes the tri-state voltage modulation method to reduce the common-mode voltage for vehicular electric drive system applications. Firstly, the discontinuous switching issue during sector transition is analyzed. Under the limit of two switching times in one period, multiple alignments combination is proposed to address that issue. Secondly, the zero-voltage time intervals in different modulation ranges are explored. This paper proposes an unsymmetric translation method to reconstruct the voltage vector, and then the minimum zero-voltage time interval is controlled to enough value for safe switching. Finally, the proposed methods have been validated through experiments on a vehicular electric drive system. The results show that the common-mode voltage can be reduced effectively in the whole range with the optimized tri-state voltage modulation method.
Negative Binomial Regression of Electric Power Outages in Hurricanes

Hurricanes can cause extensive power outages, resulting in economic loss, business interruption, and secondary effects to other infrastructure systems. Currently, power companies are unable to accurately predict where outages will occur. Therefore, it is difficult for them to deploy repair personnel and materials, and make other emergency response decisions in advance of an event. This paper describes negative binomial regression models for the number of hurricane-related outages likely to occur in each one square kilometer grid cell and in each zip code in a region due to passage of a hurricane. The models are based on a large Geographic Information System database of outages in North and South Carolina from three hurricanes: Floyd (1999), Bonnie (1998), and Fran (1996). The most useful explanatory variables are the number of transformers in the area, the company affected, maximum gust wind speed, and a hurricane effect. Wind speeds were estimated using a calibrated hurricane wind speed model. Pseudo R-squared values and other diagnostic statistics are developed to facilitate model selection with generalized negative binomial models.
Multi-Stage Refinement Feature Matching Using Adaptive ORB Features for Robotic Vision Navigation

Feature matching is a crucial technique to estimate robot pose in the light of natural landmarks for a vision navigation system. It is difficult for the present feature matching approaches to balance the accuracy, robustness and efficiency for a vision-based robot in complex workspaces. A multi-stage KNN-TF-BF-EN-RANSAC (KTBER) refinement matching technique is proposed to combine with the adaptive ORB feature extraction method, in order to develop a novel KTBER_AORB model that can outperform the state-of-the-art feature extraction and matching techniques. Firstly, the adaptive ORB (AORB) features are extracted in the Laplacian Transformation of Gaussian (LTOG) pyramid by using a set of variable-radius templates. The template radius is adjusted in terms of different brightness and contrast conditions. Then, the Eigenvector Norm (EN) and Bidirectional Filtering (BF) techniques are devised to establish a novel KTBER model, which can match AORB feature pairs not only according to the local appearance-based similarity of feature descriptors in the Hamming space, but also by means of the similarity of local image structure and global grayscale information for feature pairs in the Euclidean space. Finally, a large number of feature matching experiments are conducted on five public datasets and our mobile robot dataset, in order to test the algorithm performances for different challenging scenarios, including illumination change, motion blur, image rotation, viewpoint change, and low texture. On the one hand, an intensive experimental analysis of our model with different configurations is made to check the specific effects of different algorithm elements. On the other hand, the KTBER_AORB model is further compared with four state-of-the-art techniques, e.g., SIFT, ORB-SLAM, MP-ORB, and LAAT. The experimental results demonstrate that the KTBER_AORB model outperforms other state-of-the-art feature matching techniques on accuracy and robustness, still preserving a higher efficiency than most counterparts.
Numerical Simulation of Fractional Delay Differential Equations Using the Operational Matrix of Fractional Integration for Fractional-Order Taylor Basis

In this paper, we consider numerical solutions for a general form of fractional delay differential equations (FDDEs) with fractional derivatives defined in the Caputo sense. A fractional integration operational matrix, created using a fractional Taylor basis, is applied to solve these FDDEs. The main characteristic of this approach is, by utilizing the operational matrix of fractional integration, to reduce the given differential equation to a set of algebraic equations with unknown coefficients. This equation system can be solved efficiently using a computer algorithm. A bound on the error for the best approximation and fractional integration are also given. Several examples are given to illustrate the validity and applicability of the technique. The efficiency of the presented method is revealed by comparing results with some existing solutions, the findings of some other approaches from the literature and by plotting absolute error figures.
A Novel Convolutional Neural Network for Classifying Indian Coins by Denomination

Coins recognition systems have humungous applications from vending and slot machines to banking and management firms which directly translate to a high volume of research regarding the development of methods for such classification. In recent years, academic research has shifted towards a computer vision approach for sorting coins due to the advancement in the field of deep learning. However, most of the documented work utilizes what is known as ‘Transfer Learning’ in which we reuse a pre-trained model of a fixed architecture as a starting point for our training. While such an approach saves us a lot of time and effort, the generic nature of the pre-trained model can often become a bottleneck for performance on a specialized problem such as coin classification. This study develops a convolutional neural network (CNN) model from scratch and tests it against a widely-used general-purpose architecture known as Googlenet. We have shown in this study by comparing the performance of our model with that of Googlenet (documented in various previous studies) that a more straightforward and specialized architecture is more optimal than a more complex general architecture for the coin classification problem. The model developed in this study is trained and tested on 720 and 180 images of Indian coins of different denominations, respectively. The final accuracy gained by the model is 91.62% on the training data, while the accuracy is 90.55% on the validation data.
A small-signal equivalent circuit for the collector-up InGaAs/InAlAs/InP heterojunction bipolar transistor

A small-signal equivalent circuit is developed for the InGaAs/InAlAs/InP collector-up heterojunction bipolar transistor (HBT). Device S-parameters are measured in the 0.05- GHz to 40-GHz range at several bias points and used in the modeling. Parameter values are optimized for the equivalent circuit using two methods: (1) the commercial circuit analysis program Touchstone; and (2) the simulated annealing algorithm. The measured and modeled S-parameters show excellent agreement. The current gain and the maximum stable gain/maximum available gain also show very good agreement between measured and modeled values, demonstrating the validity of the model. Consistent results were obtained by two independent methods further supporting the conclusions. >
First Report of Crown Gall of Kiwifruit (Actinidia deliciosa) Caused by Agrobacterium fabacearum in China and the Establishment of Loop-Mediated Isothermal Amplification Technique

Kiwifruit is moderately sweet and sour and quite popular among consumers; it has been widely planted in some areas of the world. In 2019, the crown gall disease of kiwifruit was discovered in the main kiwifruit-producing area of Guizhou Province, China. This disease can weaken and eventually cause the death of the tree. The phylogeny, morphological and biological characteristics of the bacteria were described, and were related to diseases. The pathogenicity of this species follows the Koch hypothesis, confirming that A. fabacearum is the pathogen of crown gall disease of kiwifruit in China. In this study, Loop-mediated isothermal amplification (LAMP) analysis for genome-specific gene sequences was developed for the specific detection of A. fabacearum. The detection limit of the LAMP method is 5 × 10−7 ng/μL, which has high sensitivity. At the same time, the amplified product is stained with SYBR Green I after the reaction is completed, so that the amplification can be detected with the naked eye. LAMP analysis detected the presence of A. fabacearum in the roots and soil samples of the infected kiwifruit plant. The proposed LAMP detection technology in this study offers the advantages of ease of operation, visibility of results, rapidity, accuracy and high sensitivity, making it suitable for the early diagnosis of crown gall disease of kiwifruit.
UNCERTAINTY MODELLING AND LIMIT STATE RELIABILITY OF TUNNEL SUPPORTS UNDER SEISMIC EFFECTS

Underground openings and excavations are increasingly being used for civilian and strategic purposes all over the world. Recent earthquakes and resulting damage have brought into focus and raised the awareness for aseismic design and construction. In addition, underground tunnels, particularly, have distinct seismic behaviour due to their complete enclosure in soil or rock and their significant length. Therefore, seismic response of tunnel support systems warrant closer attention. The geological settings in which they are placed are often difficult to describe due to limited site investigation data and vast spatial variability. Therefore, the parameters which govern the design are many and their variabilities cannot be ignored. A solution to this issue is reliability based analysis and design. These real conditions of variability can only be addressed through a reliability based design. The problem addressed here is one of reliability-based analysis of the support system of an underground tunnel in soil. Issues like the description of the interaction between the tunnel lining and the surrounding medium, the type of limit state that would be appropriate, the nonavailability of a closed form performance function and the advantages of response surface method [RSM] are looked into. Both static and seismic environment with random variability in the material properties are studied here. Support seismic response is studied in terms of thrust, moment and shear forces in the lining. Interactive analysis using finite element method [FEM], combined with RSM and Hasofer-Lind reliability concept to assess the performance of the tunnel support, has proven useful under real field situations.
PCR-Based Analytical Methods for Quantification and Quality Control of Recombinant Adeno-Associated Viral Vector Preparations

Recombinant adeno-associated viral vectors (rAAV) represent a gene therapy tool of ever-increasing importance. Their utilization as a delivery vehicle for gene replacement, silencing and editing, among other purposes, demonstrate considerable versatility. Emerging vector utilization in various experimental, preclinical and clinical applications establishes the necessity of producing and characterizing a wide variety of rAAV preparations. Critically important characteristics concerning quality control are rAAV titer quantification and the detection of impurities. Differences in rAAV constructs necessitate the development of highly standardized quantification assays to make direct comparisons of different preparations in terms of assembly or purification efficiency, as well as experimental or therapeutic dosages. The development of universal methods for impurities quantification is rather complicated, since variable production platforms are utilized for rAAV assembly. However, general agreements also should be achieved to address this issue. The majority of methods for rAAV quantification and quality control are based on PCR techniques. Despite the progress made, increasing evidence concerning high variability in titration assays indicates poor standardization of the methods undertaken to date. This review summarizes successes in the field of rAAV quality control and emphasizes ongoing challenges in PCR applications for rAAV characterization. General considerations regarding possible solutions are also provided.