scholarly journals Infinitely Many Solutions of Schrödinger-Poisson Equations with Critical and Sublinear Terms

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Xianzhong Yao ◽  
Xia Li ◽  
Fuchen Zhang ◽  
Chunlai Mu
Keyword(s):  
Weight Function ◽  
Negative Energy ◽  
Infinitely Many Solutions ◽  
Poisson Equations ◽  
Genus Theory

In this paper, we study the following Schrödinger-Poisson equations −Δu+u+ϕu=u5+λaxup−1u,x∈ℝ3,−Δϕ=u2,x∈ℝ3, where the parameter λ>0 and p∈0,1. When the parameter λ is small and the weight function ax fulfills some appropriate conditions, we admit the Schrödinger-Poisson equations possess infinitely many negative energy solutions by using a truncation technology and applying the usual Krasnoselskii genus theory. In addition, a byproduct is that the set of solutions is compact.

On the Form of Decision Weight Function

2002 ◽  
Author(s):  
Shyhnan Liou ◽  
Chung-Ping Cheng
Keyword(s):  
Weight Function

Multi Disease-Prediction Framework Using Hybrid Deep Learning: An Optimal Prediction Model (Preprint)

2020 ◽  
Author(s):  
Anusha Ampavathi ◽  
Vijaya Saradhi T
Keyword(s):  
Feature Extraction ◽  
Big Data ◽  
Deep Learning ◽  
Weight Function ◽  
Optimization Algorithm ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Disease Prediction ◽  
Health Care Decisions ◽  
Proposed Model

UNSTRUCTURED Big data and its approaches are generally helpful for healthcare and biomedical sectors for predicting the disease. For trivial symptoms, the difficulty is to meet the doctors at any time in the hospital. Thus, big data provides essential data regarding the diseases on the basis of the patient’s symptoms. For several medical organizations, disease prediction is important for making the best feasible health care decisions. Conversely, the conventional medical care model offers input as structured that requires more accurate and consistent prediction. This paper is planned to develop the multi-disease prediction using the improvised deep learning concept. Here, the different datasets pertain to “Diabetes, Hepatitis, lung cancer, liver tumor, heart disease, Parkinson’s disease, and Alzheimer’s disease”, from the benchmark UCI repository is gathered for conducting the experiment. The proposed model involves three phases (a) Data normalization (b) Weighted normalized feature extraction, and (c) prediction. Initially, the dataset is normalized in order to make the attribute's range at a certain level. Further, weighted feature extraction is performed, in which a weight function is multiplied with each attribute value for making large scale deviation. Here, the weight function is optimized using the combination of two meta-heuristic algorithms termed as Jaya Algorithm-based Multi-Verse Optimization algorithm (JA-MVO). The optimally extracted features are subjected to the hybrid deep learning algorithms like “Deep Belief Network (DBN) and Recurrent Neural Network (RNN)”. As a modification to hybrid deep learning architecture, the weight of both DBN and RNN is optimized using the same hybrid optimization algorithm. Further, the comparative evaluation of the proposed prediction over the existing models certifies its effectiveness through various performance measures.

scholarly journals Effects of peroral alanine administration in lactating ewes with decreased availability of glucose

1997 ◽  
Vol 78 (5) ◽  
pp. 805-813 ◽  
Author(s):  
Kjell Holtenius ◽  
Paul Holtenius
Keyword(s):  
Fatty Acids ◽  
Plasma Level ◽  
Free Fatty Acids ◽  
Skeletal Muscles ◽  
Plasma Insulin ◽  
Glucose Oxidation ◽  
Negative Energy ◽  
Crossover Design ◽  
Metabolic Effects ◽  
Significant Elevation

The metabolic effects of a phlorizin-induced drainage of glucose were studied in six lactating ewes with or without peroral alanine drenches in a study of crossover design. Phlorizin gave rise to a small, but significant, elevation of plasma β-hydroxybutyrate. The plasma level of alanine decreased by about 30 % due to the phlorizin injections and alanine was negatively correlated to β-hydroxybutyrate. The plasma level of free fatty acids increased due to phlorizin. Plasma insulin and glucose concentrations were not significantly affected by phlorizin while glucagon level showed a small but significant increase. Peroral alanine drenches to phlorizin-treated ewes gave rise to a transitory elevation of alanine in plasma. The plasma level of free fatty acids was about 40 % lower in phlorizin-treated ewes receiving alanine and β-hydroxybutyrate tended to be lower (P < 0.08). We suggest that β-hydroxybutyrate, apart from its function as an oxidative fuel, might play an important role by limiting glucose oxidation and protein degradation in skeletal muscles during periods of negative energy balance in ruminants. Furthermore, it is suggested that alanine supplementation decreases lipolysis and ketogenesis in lactating ewes.

scholarly journals Energy Balance Indicators during the Transition Period and Early Lactation of Purebred Holstein and Simmental Cows and Their Crosses

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 309
Author(s):  
Deise Aline Knob ◽  
André Thaler Neto ◽  
Helen Schweizer ◽  
Anna C. Weigand ◽  
Roberto Kappes ◽  
...  
Keyword(s):  
Energy Balance ◽  
Milk Yield ◽  
Milk Composition ◽  
Negative Energy ◽  
The Other ◽  
Negative Energy Balance ◽  
Metabolic Energy ◽  
Genetic Groups ◽  
Significant Difference ◽  
Fat Thickness

Crossbreeding in dairy cattle has been used to improve functional traits, milk composition, and efficiency of Holstein herds. The objective of the study was to compare indicators of the metabolic energy balance, nonesterified fatty acids (NEFA), beta-hydroxybutyrate (BHBA), glucose, body condition score (BCS) back fat thickness (BFT), as well as milk yield and milk composition of Holstein and Simmental cows, and their crosses from the prepartum period until the 100th day of lactation at the Livestock Center of the Ludwig Maximilians University (Munich, Germany). In total, 164 cows formed five genetic groups according to their theoretic proportion of Holstein and Simmental genes as follows: Holstein (100% Holstein; n = 9), R1-Hol (51–99% Holstein; n = 30), first generation (F1) crossbreds (50% Holstein, 50% Simmental; n = 17), R1-Sim (1–49% Holstein; n = 81) and Simmental (100% Simmental; n = 27). The study took place between April 2018 and August 2019. BCS, BFT blood parameters, such as BHBA, glucose, and NEFA were recorded weekly. A mixed model analysis with fixed effects breed, week (relative to calving), the interaction of breed and week, parity, calving year, calving season, milking season, and the repeated measure effect of cow was used. BCS increased with the Simmental proportion. All genetic groups lost BCS and BFT after calving. Simmental cows showed lower NEFA values. BHBA and glucose did not differ among genetic groups, but they differed depending on the week relative to calving. Simmental and R1-Sim cows showed a smaller effect than the other genetic groups regarding changes in body weight, BCS, or back fat thickness after a period of a negative energy balance after calving. There was no significant difference for milk yield among genetic groups, although Simmental cows showed a lower milk yield after the third week after calving. Generally, Simmental and R1-Simmental cows seemed to deal better with a negative energy balance after calving than purebred Holstein and the other crossbred lines. Based on a positive heterosis effect of 10.06% for energy corrected milk (ECM), the F1, however, was the most efficient crossbred line.

scholarly journals Determining Factors of Psychological Performance and Differences among Age Categories in Youth Football Players

2021 ◽  
Vol 13 (14) ◽  
pp. 7713
Author(s):  
Juan De Dios Benítez-Sillero ◽  
Luis Manuel Martínez-Aranda ◽  
Manuel Sanz-Matesanz ◽  
Marta Domínguez-Escribano
Keyword(s):  
Well Being ◽  
Negative Energy ◽  
Attention Control ◽  
Mental Toughness ◽  
Football Players ◽  
Energy Control ◽  
Psychological Performance ◽  
Self Confidence ◽  
Determining Factors ◽  
Motivational Level

Within the determining factors of psychological performance, mental toughness is considered a multidimensional factor, comprising cognitive, affective, and behavioural components together with self-confidence, which is related to success in sports performance as well as psychological health and well-being. The aim of this study was to analyse the relationship between different factors composing mental toughness and age categories in young football players, in order to determine the presence of specific psychological skills in their formative progression. A total of 118 male players (16.91 ± 2.42 years old) completed the Spanish version by Cernuda (1988) of the original Psychological Performance Inventory (PPI) by Loher (1982, 1986). The results indicated significant differences in four variables (negative energy control, attention control, visual and image control, motivational level) on three different age categories, where the U19 category showed the best results for all the variables, decreasing afterwards in the semi-professional category. Significant correlations were established between mental toughness variables and age categories, where the age category variable was significantly correlated in a positive way with attention control, visual and image control, and motivational level. In the same line, the variable self-confidence correlated positively with negative energy control, attention control, motivational level, attention control, and positive energy. The assessment of psychological variables such as mental toughness, taking into account the formative stage, may be helpful for both coaches and players when selecting adequate mental skill training for improving competitive performance and sporting success, as well as for positive and healthy psychological development and well-being.

scholarly journals Performance Characteristics in Runner of an Impulse Water Turbine with Splitter Blade

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 303
Author(s):  
Lingdi Tang ◽  
Shouqi Yuan ◽  
Yue Tang ◽  
Zhijun Gao
Keyword(s):  
Energy Conversion ◽  
Flow Direction ◽  
Mechanical Energy ◽  
Experimental Tests ◽  
High Energy ◽  
Negative Energy ◽  
Water Turbine ◽  
Conversion Performance ◽  
Water Turbines ◽  
Current Energy

The impulse water turbine is a promising energy conversion device that can be used as mechanical power or a micro hydro generator, and its application can effectively ease the current energy crisis. This paper aims to clarify the mechanism of liquid acting on runner blades, the hydraulic performance, and energy conversion characteristics in the runner domain of an impulse water turbine with a splitter blade by using experimental tests and numerical simulations. The runner was divided into seven areas along the flow direction, and the power variation in the runner domain was analyzed to reflect its energy conversion characteristics. The obtained results indicate that the critical area of the runner for doing the work is in the front half of the blades, while the rear area of the blades does relatively little work and even consumes the mechanical energy of the runner to produce negative work. The high energy area is concentrated in the flow passage facing the nozzle. The energy is gradually evenly distributed from the runner inlet to the runner outlet, and the negative energy caused by flow separation with high probability is gradually reduced. The clarification of the energy conversion performance is of great significance to improve the design of impulse water turbines.

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