Potato Yield Response to Different Rates of Phosphorus Fertilization in Northern Maine - USA

Potato (Solanum tuberosum L.) is a major vegetable crop worldwide, including the United States of America. No other crops could equal potato in its production of food in terms of energy and value per unite area. Because potato is a high-value vegetable, farmers apply phosphorus fertilization at high rates despite high soil phosphorus availability. Phosphorus is the most critical major soil nutrient limiting potato growth after nitrogen and potassium. Six rates of P fertilization (0 – 280 kg P ha−1) were applied at twelve different sites across Northern Maine, United States of America. In the present study, soil pH was significantly correlated with total potato tuber yield (R2 = 0.38). Sites with soil pH values \u3c 6 had total tuber yields, marketable tuber yields, tuber numbers per plant, and total tuber mean weights all higher than these same parameters at sites with soil pH ≥ 6. All sites with soil pH\u3c 6 showed a highly correlated relationship between P uptake and petiole dry weight (R2 = 0.76). The Cate-Nelson analysis for this study allowed distinguishing two P fertility classes: Low and High, that is, 0–14.2 and 14.2 – 43.0 mg P kg-1 soil at the early potato stage and 0 –17.0 and 17.0– 42.0 mg P kg-1 soil at potato harvest time, respectively, for the Modified Morgan (MM) extractant method and 0–307.2 and 307.2–844.0 mg P kg-1 soil at the early potato stage and 0–334.0 and 334.0–845.0 mg P kg-1soil at potato harvest time, respectively, for the Mehlich3 (M3) extractant method. The highest robustness value (R2= 62.0%) was obtained at potato harvest for the Cate-Nelson analysis with the M3 extractant method. The DPS, using the logarithmic model, showed that desorbable P increased from 16 to 29%. Vegetation indices (VIs) and plant pigments were calculated at various time points and correlated with total potato yield and P uptake. Active sensors provided a poor prediction of total potato yields, adjusted R2 ranged ( 0.05 – 0.36 ) for Crop CircleTM and ranged (0.02 – 0.57) for a GreenSeekerTM, and P uptake, adjusted R2 ranged (0.07 – 0.62) for Crop CircleTM ranged (0.01 – 0.44) for a GreenSeekerTM. Passive sensors provided a good prediction of potato yield, with R2adj ranging between 0.44 – 0.63. Their predictive values increased dramatically throughout the season, with the highest R2adj of 0.63 for the relationship between normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), and chlorophyll green (CHLGR) and total potato yield at the first flight date (25 June), with a log-transformed response variable (log- transformed models). This study demonstrated multi-spectral imaging\u27s potential application by using an unmanned aerial vehicle (UAVs) to predict total potato yield at the early vegetative growth stage with high accuracy. This study was conducted to evaluate the influence of phosphorus (P) application rates and inoculation with arbuscular vascular mycorrhizal (VAM) fungi on tuber yield, specific gravity, petioles dry weight, phosphorus concentration, and uptake. None of the treatments affected any of the yield parameters. At the same time, soil test phosphorus (Modified Morgan and Mehlich 3) was significantly correlated with VAM fungi\u27s root colonization. It appears that the soils with high soil phosphorus test and soil pH higher than 6 was not benefited from being inoculated with additional mycorrhiza

Legal Translation Instruction at Discourse Level and the Problem of Equivalence

Legal translation is often claimed to be one of the most difficult types of technical translation. The difficulty may partly be due to the characteristic features of legal discourse which is typically archaic, obscure, complex, and culturally-bound, different linguistic systems, and the type of equivalence the legal translator seeks to achieve; and partly be due to the item-centered approach commonly used in teaching legal translation which emphasizes word-for-word equivalence. The present paper introduces a discourse-oriented approach as an alternative to the currently-used method of teaching legal translation in Iraqi universities. The major argument is that teaching legal translation at discourse level helps the students of translation to recognize the lexical, grammatical, pragmatic, and stylistic dimensions of the legal text which are essential for providing appropriate legal equivalence. Keywords: legal translation, legal equivalence, translation instruction, discourse-oriented approach, characteristics of legal discourse DOI: 10.7176/JEP/11-17-03 Publication date:June 30th 2020

Evaluation of the Level of Histamine 1 and 2 Receptors with Some Biochemical Variables in Patients with Hepatitis C Virus Infection

The current study was carried out at Ibn - Sina Hospital in Nineveh Governorate, where the relationship between histamine receptors1&2, liver enzyme functions, Albumin, and Alkaline phosphate was studied in patients with hepatitis C virus type. Samples were taken from patients diagnosed with hepatitis C, 60 of whom were compared with 30 controls. Take 5ml of blood, separate it with a centrifuge, and test the serum. The sample size was equal for Men and Women, and the age range was 18 to 78 years. ALT (GPT), Albumin, Alkaline phosphates, and histamine-2 receptor levels were statistically significant, while AST (GOT) and histamine-1 receptor levels were not statistically significant

Defamation in English and Arabic: A Pragmatic Contrastive Study

Defamation is one of the verbal offences in which the plaintiff is accused of a certain wrongful act by one of the ways of publicity. If that wrongful act is proved, then the accused will be punished by law or lowered by his/her home people. Defamation is surely accusing another person of a wrongful act . Accusing can be done by any spoken or written ways whether truthful or doubtful. The purpose beyond those ways is to make those accusations about the victim true in the people's mind even if they are temporarily made. The aim of this study is to elucidate if there is a similarity or a difference between English and Arabic in terms of defamation. It has been hypothesized that both languages are different from each other in terms of the topic under investigation. This study arrives at: In terms of defamation, English and Arabic are similar to each other in having speech acts, grammatical referencing, conveyed meaning, malicious meaning, and discourse structure and framing with intentionality. English defamation cases include speech acts more than Arabic defamation ones

Study and Analysis of Power System Stability Based on FACT Controller System

Energy framework soundness is identified with standards rotational movement and the swing condition administering electromechanical unique conduct. In the exceptional instance of two limited machines, the basis of equivalent territory security can be utilized to ascertain the basic clearing point in the force framework, It is important to look after synchronization, in any case the degree of administration for customers won't be accomplished. This term steadiness signifies "looking after synchronization." This paper is an audit of three kinds of consistent state. The main sort of adjustment, consistent state steadiness clarifies the most extreme consistent state quality and force point chart. The transient solidness clarifies the wavering condition and the idleness steady while dynamic soundness manages the transient security time frame. There are a few different ways to improve framework soundness a portion of the techniques are clarified. Versatile AC Transmission Frameworks (FACTS) Flexible AC Transmission System (FACTS) regulators have been utilized frequently to comprehend the different issues of a non-variable force structure. Versatile AC Transmission Frames or FACTS are devices that permit versatile and dynamic control of intensity outlines. Improving casing respectability has been explored with FACTS regulators. This examination focuses to the upsides of utilizing FACTS apparatuses with the explanation behind improving electric force tire activity. There has been discussion of an execution check for different FACTS regulators

Review of Intelligent Control Systems with Robotics

Interactive between human and robot assumes a significant job in improving the productivity of the instrument in mechanical technology. Numerous intricate undertakings are cultivated continuously via self-sufficient versatile robots. Current automated control frameworks have upset the creation business, making them very adaptable and simple to utilize. This paper examines current and up and coming sorts of control frameworks and their execution in mechanical technology, and the job of AI in apply autonomy. It additionally expects to reveal insight into the different issues around the control frameworks and the various approaches to fix them. It additionally proposes the basics of apply autonomy control frameworks and various kinds of mechanical technology control frameworks. Each kind of control framework has its upsides and downsides which are talked about in this paper. Another kind of robot control framework that upgrades and difficulties the pursuit stage is man-made brainpower. A portion of the speculations utilized in man-made reasoning, for example, Artificial Intelligence (AI) such as fuzzy logic, neural network and genetic algorithm, are itemized in this paper. At long last, a portion of the joint efforts between mechanical autonomy, people, and innovation were referenced. Human coordinated effort, for example, Kinect signal acknowledgment utilized in games and versatile upper-arm-based robots utilized in the clinical field for individuals with inabilities. Later on, it is normal that the significance of different sensors will build, accordingly expanding the knowledge and activity of the robot in a modern domai

Study of Hydrocarbon Potentials and Sedimentary Properties of Ispartaçay Formation, Turkey

The idea of the current work was the combination of the organic geochemical analyses, and the study of sedimentology characteristics of the source rock samples collected from the Ispartaçay Formation (Cretaceous period) between the city of Antalya and the city of Isparta, southwestern Turkey. Total Organic Carbon analysis and Rock-Eval pyrolysis were performed on the 24 samples taken from the study area, in order to evaluate quantitatively, and qualitatively organic matter and thermal maturity to determine the potential for hydrocarbon production. As well as studying the petrographic features (component and diagenesis), microfacies analysis, and sedimentary environment of the Ispartaçay Formation. The successions of the Ispartaçay Formation are poor to fair organic matter content and consist of dark grayish limestone, marly limestone, shale, massive cherty limestone, and thin-bedded radiolarian limestone. Total Organic Carbon values indicate that Ispartaçay Formation rocks are fair potential. Besides this, most of the samples from the Ispartaçay Formation contain mature to pot-mature (Type III -Type IV) kerogen. Petrographically, the particle portion of the Ispartaçay sediments is composed mainly of radiolarians, and planktonic foraminifera, In addition to the presence of a proportion of benthic foraminifera, whereas the groundmass is composed of micrite. Generally, the present sediments are subjected to some diagenetic processes like silicification, cementation, and dissolution. The microfacies analysis revealed that the succession of the Ispartaçay Formation is composed of alternations of two major microfacies, namely lime mudstone and lime wackestone microfacies. Depending on the facies and petrographic evidence, Ispartaçay Formation represents sediments deposited in the mid to outer ramp environment

Molecular Biology View on Down syndrome: Review article

Background:   Down Syndrome (DS) is a resulting from a defect of the genotype in patients affected by it. The occurrence of this type of disease is very common. It has been associated with causing many genetic diseases with a significant change  in phenotypic pattern. People with this type of disease suffer from intellectual disability that ranges from mild to moderate, delay in growth and the emergence of some distinctive signs in the face. It  leads to Alzheimer’s in some cases. The treatment cost  is very high and exorbitant,   many laboratories have   sophisticated diagnoses methods, but they are expensive and require high skill. Therefore, this disease still needs to develop many genetic methods to facilitate its diagnosis infection rates reduction among humans.The present review article  empasied an overview of DS-associated phenotypes diagnosis and managment of the disease.   Furthermore,we  have also Reviewed further parental diagnosis methods to facilate  moleculr  methods  CSV,  MLPA, FISH, QF-PCR, PSQ, and NGS and  noninvasive dignosis in detail

Elevating metaverse virtual reality experiences through network-integrated neuro-fuzzy emotion recognition and adaptive content generation algorithms

Interactions between individuals and digital material have completely changed with the advent of the Metaverse. Due to this, there is an immediate need to construct cutting-edge technology that can recognize the emotions of users and continuously provide material that is relevant to their psychological states, improving their overall experience. An inventive method that combines natural language processing adaptive content generation algorithms and neuro-fuzzy-based support vector machines natural language processing (SVM-NLP) is proposed by researchers to meet this demand. With this merging, the Metaverse will be able to offer highly tailored and engaging experiences. Initially, a neuro-fuzzy algorithm was developed to identify people's emotional moods from their physiological reactions and other biometric information. Fuzzy Logic and Support Vector Machine work together to manage the inherent ambiguity and unpredictability, which results in a more exact and accurate categorization of emotions. A key component of the ACGA is NLP technology, which uses real-time emotional data to dynamically modify and personalize characters, stories, and interactive features in the Metaverse. The novelty of the proposed approach lies in the innovative integration of neuro-fuzzy-based SVM-NLP algorithms to accurately recognize and adapt to users' emotional states, enhancing the Metaverse experience across various applications. The proposed method is implemented using Python software. This adaptive approach significantly enhances users' immersion, emotional involvement, and overall satisfaction within the augmented reality environment by tailoring information to their responses. The findings show that the SVM-NLP emotion identification algorithm based on neuro-fuzzy, has a high degree of accuracy in recognizing emotional states, which holds promise for creating a Metaverse that is more emotionally compelling and immersive. Stronger human–computer interactions and a wider range of applications, including virtual therapy, educational resources, entertainment, and social media networking, might be made possible by integrating SVM-NLP. These sophisticated systems are around 92% accurate in interpreting the emotions

Federated learning with hybrid differential privacy for secure and reliable cross-IoT platform knowledge sharing

The federated learning has gained prominent attention as a collaborative machine learning method, allowing multiple users to jointly train a shared model without directly exchanging raw data. This research addresses the fundamental challenge of balancing data privacy and utility in distributed learning by introducing an innovative hybrid methodology fusing differential privacy with federated learning(HDP-FL) Through meticulous experimentation on EMNIST and CIFAR-10 datasets, this hybrid approach yields substantial advancements, showcasing a noteworthy 4.22% and up to 9.39% enhancement in model accuracy for EMNIST and CIFAR-10, respectively, compared to conventional federated learning methods. Our adjustments to parameters highlighted how noise impacts privacy, showcasing the effectiveness of our hybrid DP approach in striking a balance between privacy and accuracy. Assessments across diverse FL techniques and client counts emphasized this trade-off, particularly in non-IID data settings, where our hybrid method effectively countered accuracy declines. Comparative analyses against standard machine learning and state-of-the-art FL approaches consistently showcased the superiority of our proposed model, achieving impressive accuracies of 96.29% for EMNIST and 82.88% for CIFAR-10. These insights offer a strategic approach to securely collaborate and share knowledge among IoT devices without compromising data privacy, ensuring efficient and reliable learning mechanisms across decentralized networks