786 research outputs found
Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends
Machine Learning has garnered significant attention in lithium-ion battery research for its potential to revolutionize various aspects of the field. This paper explores the practical applications, challenges, and emerging trends of employing Machine Learning in lithium-ion battery research. Delves into specific Machine Learning techniques and their relevance, offering insights into their transformative potential. The applications of Machine Learning in lithium-ion-battery design, manufacturing, service, and end-of-life are discussed. The challenges including data availability, data preprocessing and cleaning challenges, limited sample size, computational complexity, model generalization, black-box nature of Machine Learning models, scalability of the algorithms for large datasets, data bias, and interdisciplinary nature and their mitigations are also discussed. Accordingly, by discussing the future trends, it provides valuable insights for researchers in this field. For example, a future trend is to address the challenge of small datasets by techniques such as Transfer Learning and N-shot Learning. This paper not only contributes to our understanding of Machine Learning applications but also empowers professionals in this field to harness its capabilities effectively
Enhanced response of the regular networks to local signals in presence of a fast impurity
We consider an array of inductively coupled Josephson junctions with a fast
impurity (a junction with a smaller value of critical current), and study the
consequences of imposing a small amplitude periodic signal at some point in the
array. We find that when external signal is imposed at the impurity, the
response of the array is boosted and a small amplitude signal can be detected
throughout the array. When the signal is imposed elsewhere, minor effects is
seen on the dynamics of the array. The same results have been also seen in
presence of a single fast spiking neuron in a chain of diffusively coupled
FitzHugh-Nagumo neurons.Comment: 6 pages, 5 figures, arXiv admin note: substantial text overlap with
arXiv:1108.460
Effect of using different levels of pistachio by-products silage on composition and blood parameters of Holstein dairy cows
The goal of this research was to study about the effect of using pistachio hulls silage in cow's nutrition. The initial experiment was about the effect of several feed additives on chemical and fermentative characteristic of pistachio hulls silages. This experiment was designed with 5 treatments and 4 replications in each treatment in a complete randomized design. Additives for preparing pistachio hulls silage were in the sequence of 1.5% citrus pulp (in base of dry matter), 1.5% ground barley, 1.5% beet pulp, 1.5% molasses and one control treatment without any additives. Silages were sampled for chemical analysis and fermentative characteristics. Results of the analysis showed no significant variation between the treatments in respect of ash. In the second experiment, the application of pistachio hulls silage in the nutrition of lactating cows was studied. Eight lactating cows in one Latin square design experiment were used. Treatments included various amounts of pistachio hulls silage replaced with corn silage (in base of dry mater). The results show no significant variation between the treatments in milk, blood, rumen factors and digestibility factors that can show pistachio hulls silage that can be replaced with corn silage up to 15% (%dry matter) in dairy cows ration without any significant variation in cows production.Key words: Dairy cattle's, milk production, pistachio by-product, silage, tannin
Functional scale-free networks in the two-dimensional Abelian sandpile model
Recently, the similarity of the functional network of the brain and the Ising model was investigated by Chialvo [Nat. Phys. 6, 744 (2010)]. This similarity supports the idea that the brain is a self-organized critical system. In this study we derive a functional network of the two-dimensional Bak-Tang-Wiesenfeld sandpile model as a self-organized critical model, and compare its characteristics with those of the functional network of the brain, obtained from functional magnetic resonance imaging.Fil: Zarepour Nasir Abadi, Mahdi. Institute For Advanced Studies In Basic Sciences; Irán. CONICET, Instituto de Física Enrique Gaviola, Córdoba; ArgentinaFil: Niry, M. D.. Institute For Advanced Studies In Basic Sciences; IránFil: Valizadeh, A.. Institute For Advanced Studies In Basic Sciences; Irá
Low secondary electron yield engineered surface for electron cloud mitigation
Secondary electron yield (SEY or δ) limits the performance of a number of devices. Particularly, in high-energy charged particle accelerators, the beam-induced electron multipacting is one of the main sources of electron cloud (e-cloud) build up on the beam path; in radio frequency wave guides, the electron multipacting limits their lifetime and causes power loss; and in detectors, the secondary electrons define the signal background and reduce the sensitivity. The best solution would be a material with a low SEY coating and for many applications δ < 1 would be sufficient. We report on an alternative surface preparation to the ones that are currently advocated. Three commonly used materials in accelerator vacuum chambers (stainless steel, copper, and aluminium) were laser processed to create a highly regular surface topography. It is shown that this treatment reduces the SEY of the copper, aluminium, and stainless steel from δmax of 1.90, 2.55, and 2.25 to 1.12, 1.45, and 1.12, respectively. The δmax further reduced to 0.76-0.78 for all three treated metals after bombardment with 500 eV electrons to a dose between 3.5 × 10-3 and 2.0 × 10-2 C·mm-2
Effect of nanocurcumin and fish oil as natural anti-inflammatory compounds vs. glucocorticoids in a lipopolysaccharide inflammation model on Holstein calves’ health status
Curcumin (CUR) and fish oil (FO) are among the most well-known types of natural anti-inflammatory compounds. The aim of this study was to assess the effect of nanocurcumin and fish oil vs. glucocorticoids on Holstein calves' health status. A lipopolysaccharide (LPS) challenge (0.5 mu g kg(-1) BW) was used to induce an acute phase response. A total of 42 male Holstein calves were randomized into 7 groups: negative control (CON), positive control (LPS, injected once), 250 mg/kg BW per day fish oil + LPS (FO250), 350 mg/kg BW per day fish oil + LPS (FO350), 2 mg/kg BW per day nanocurcumin + LPS (NCUR2), 4 mg/kg BW per day nanocurcumin + LPS (NCUR4), and 0.3 mg/kg BW dexamethasone (injected once) + LPS (DEX). The duration of this experiment was 11 days, with application of the LPS challenge on day 8. Calves were weighed on days 0, 7, 9, 10, and 11 to record the average daily weight gain; diets offered and refused were recorded daily throughout the experiment. Blood collection and clinical scoring were conducted at successive time points until 72 h post LPS challenge. The data obtained also comprised rectal temperature (RT), respiratory rate (RR), heart rate (HR), concentrations of tumor necrosis factor-alpha (TNF-alpha), interleukin 6 (IL-6), serum amyloid A (SAA), and haptoglobin (Hp). This experiment could not uncover significant effects of LPS, FO, NCUR, and DEX on the area under the curve (AUC) of the RT, HR, and RR; in addition, there was no difference between FO and NCUR vs. LPS in sickness behavior, however, DEX group significantly recovered faster than others (P < 0.01). There was no significant difference between groups in dry matter intake (DMI) and average daily gain (ADG) during three days post LPS challenge. The concentrations of TNF-alpha, IL-6, and SAA were lower in the DEX group (P < 0.05). Finally, no effects of FO and NCUR on cytokines and acute phase proteins (APPs) could be observed in this study. In conclusion, supplementation of FO and NCUR was not able to impact the acute phase response (APR) in calves, as levels of inflammatory cytokines and APPs as well as sickness behavior remained unchanged. It seems that the anti-inflammatory effects of FO and CUR on APR, as has been observed for other animal species, do not manifest that clearly in calves
Challenges of the preceptors working with new nurses: A phenomenological research study
© 2016. Introduction: Preceptors play an important role in the transition of new nurses to the practice setting, however, preceptorship experience has been perceived as stressful by preceptors. This study aimed to explore the lived experiences of nurse preceptors working with new nurses. Method: This qualitative study used the hermeneutic phenomenological design to explore the experiences of six nurse preceptors working with new nurses in a tertiary pediatric teaching hospital in Northwest of Iran, who were recruited by purposive sampling. Data were collected using in-depth semi-structured individual interviews between July 2014 and March 2015, and analyzed using the Diekelmann's seven-stage method. Results: Data analysis revealed three themes: 1) preceptorship as a challenging and stressful role; 2) lack of support; and 3) lack of appreciation. Preceptorship as 'a challenging and stressful role' was the constitutive pattern that unified the themes. Conclusion: The preceptorship of new nurses is challenging and stressful. Preceptors endure several roles concurrently, thus, their workload should be balanced appropriately in order not to compromise with one another and evade burnout. The preceptors need to be well supported and their contribution be appropriately recognized. Setting clear objectives and realistic expectations, and having clear policies and guidelines in place should help develop a preceptorship program that is more likely to bring about positive outcomes for both preceptors and new nurses
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