Charm contribution to bulk viscosity

In the range of temperatures reached in future heavy ion collision experiments, hadronic pair annihilations and creations of charm quarks may take place within the lifetime of the plasma. As a result, charm quarks may increase the bulk viscosity affecting the early stages of hydrodynamic expansion. Assuming thermalization, we estimate the charm contribution to bulk viscosity within the same effective kinetic theory framework in which the light parton contribution has been computed previously. The time scale at which this physics becomes relevant is related to the width of the transport peak associated with the trace anomaly correlator, and is found to be 600 MeV.Comment: 7 pages. v2: presentation streamline

Investigation of a parasitic outbreak of Lernaea cyprinacea Linnaeus (Crustacea: Copepoda) in Cyprinid fish from Choghakhor lagoon

The main objectives of this study were to study the parasitic infestation of Lernaea cyprinacea in 4 cyprinids from the Choghakhor Lagoon, Chaharmahal - Bakhtyari Province, west of Iran. A total of 180 cyprinids including Cyprinus carpio (n=101), Carassius auratus (n=47), Capoeta aculeata (n=10) and Alburnus alburnus (n=22) caught, and were studied for Lernaea cyprinacea infestation. Prevalence (C. carpio 61.4, C. auratus 87.2, C. aculeata 70 and A. alburnus 68.2), intensity of infection (C. carpio range 1 to 5, mean 2.1; C. auratus range 1 to 6, mean 1.9; C. aculeata range 1 to 5, mean 2.4; A. alburnus range 1 to 2, mean 1.1), and abundance (C. carpio 1.3, C. auratus 1.6, C. aculeata 1.7 and A. alburnus 0.8) varied with the fish species. A statistically significant difference was found between infestation by L. cyprinacea and fish species (p=0.01), although no statistically significant difference was found between infestation and weight, length and age of the studied fishes (p>0.05). The prevalence was also significantly different (p=0.0) in studying seasons. Population dynamics of L. cyprinacea on fish hosts was studied. The results show that the preferred site of the parasite was body lateral surfaces followed by caudal, dorsal, pectoral and anal fins (P=0.0)

Polymorphism of ompH gene of Pasteurella multocida serotype A strains isolated in Iran

ΔΕΝ ΥΠΑΡΧΕΙ ΠΕΡΙΛΗΨΗOne of the most frequent causes of respiratory infection and death in sheep and goats is Pasteurella multocida. In humans, it has been associated with diseases of the respiratory tracts, arthritis, osteomyelitis and meningitis. Outer membrane protein H (OmpH) has a role in immunogenicity and pathogenicity of P. multocida. The aim of this study was to characterize the genetic diversity of ompH gene of a panel of P. multocida serotype A strains isolated in sheep. Forty P. multocida serotype A strains isolated in previous study were selected and analyzed by restriction fragment length polymorphism (RFLP) of a species-specific PCR assay. RFLP amplified fragment produced five different cleavage patterns. On the basis of combinations resulting from ompH gene digestion, the 40 P. multocida isolates were classified in six RFLP type. It seems that isolates with variants genetic profile represent different pathogenecity. New vaccine formulation should consider multivariants of P. multocida in order to confer a wider protection

Deep Learning Approach to Channel Sensing and Hybrid Precoding for TDD Massive MIMO Systems

This paper proposes a deep learning approach to channel sensing and downlink hybrid analog and digital beamforming for massive multiple-input multiple-output systems with a limited number of radio-frequency chains operating in the time-division duplex mode at millimeter frequency. The conventional downlink precoding design hinges on the two-step process of first estimating the high-dimensional channel based on the uplink pilots received through the channel sensing matrices, then designing the precoding matrices based on the estimated channel. This two-step process is, however, not necessarily optimal, especially when the pilot length is short. This paper shows that by designing the analog sensing and the downlink precoding matrices directly from the received pilots without the intermediate channel estimation step, the overall system performance can be significantly improved. Specifically, we propose a channel sensing and hybrid precoding methodology that divides the pilot phase into an analog and a digital training phase. A deep neural network is utilized in the first phase to design the uplink channel sensing and the downlink analog beamformer. Subsequently, we fix the analog beamformers and design the digital precoder based on the equivalent low-dimensional channel. A key feature of the proposed deep learning architecture is that it decomposes into parallel independent single-user DNNs so that the overall design is generalizable to systems with an arbitrary number of users. Numerical comparisons reveal that the proposed methodology requires significantly less training overhead than the channel recovery based counterparts, and can approach the performance of systems with full channel state information with relatively few pilots.Comment: 6 Pages, 4 figures, to appear in IEEE GLOBECOM 2020 Open Workshop on Machine Learning in Communications (OpenMLC

Ultrasonic Assisted Deep Drilling of Inconel 738LC Superalloy

AbstractSuperalloys have a poor machinability and are often drilled using Electro Discharge Machining (EDM) methods. However EDM is a time-consuming process and has low surface integrity. Ultrasonic Assisted Drilling (UAD) technology is a modern method of drilling such materials. Although this method has very high capabilities, it has not been introduced widely to industry. In this study a special horn is designed and used to apply both rotation and vibration to drill bits. It can transfer power with high efficiency and has the capability to change tools easily. The setup is used to conduct deep drilling tests on Inconel 738LC with depth-to-diameter ratio of 10. The effect of ultrasonic vibration amplitude, spindle speed and number of steps to drill each hole on machining force and surface roughness were investigated. Optimized conditions and results predicted by Taguchi method showed close agreement with the results obtained by experiments

Genetic Engineering Algorithm (GEA): An Efficient Metaheuristic Algorithm for Solving Combinatorial Optimization Problems

Genetic Algorithms (GAs) are known for their efficiency in solving combinatorial optimization problems, thanks to their ability to explore diverse solution spaces, handle various representations, exploit parallelism, preserve good solutions, adapt to changing dynamics, handle combinatorial diversity, and provide heuristic search. However, limitations such as premature convergence, lack of problem-specific knowledge, and randomness of crossover and mutation operators make GAs generally inefficient in finding an optimal solution. To address these limitations, this paper proposes a new metaheuristic algorithm called the Genetic Engineering Algorithm (GEA) that draws inspiration from genetic engineering concepts. GEA redesigns the traditional GA while incorporating new search methods to isolate, purify, insert, and express new genes based on existing ones, leading to the emergence of desired traits and the production of specific chromosomes based on the selected genes. Comparative evaluations against state-of-the-art algorithms on benchmark instances demonstrate the superior performance of GEA, showcasing its potential as an innovative and efficient solution for combinatorial optimization problems.Comment: Accepted in Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2023

Study of effect of arbuscular mycorrhiza (Glomus intraradices) fungus on wheat under nickel stress

ArticleIn many regions of the world soils are contaminated with heavy metals and therefore restricted in their use. For instance, the absorption of nickel (Ni) in the tissue of plants increase the plant’s metabolism and cause physiological disorders or even death. Arbuscular mycorrhizal fungi are known to enhance the tolerance of host plants to abiotic and biotic stress. Thus, we investigated the potential of the arbuscular m ycorrhizal fungi Glomus intraradices to mitigate deleterious effects of Ni in wheat. The experiment was conducted using four levels of Ni (0, 60, 120 and 180 mg per kg of soil) and two levels of mycorrhizal fungi application (with and without Glomus intrar adices ). Nickel stress significantly decreased seed number per spike, thousand - seed weight, seed yield per plant, concentration of chlorophyll a and b. At the same time, we found increased catalase (CAT) enzyme activity and dityrosine (DT) treatments. Mycorrhizal fungi application attenuated Ni effects, i.e. fungal presence increased seed number per spike, thousand - seed weight, chlorophyll a and b. Furthermore mycorrhizal fungi application reduce CAT enzyme activity and DT. In general, our results sugge st that mycorrhizal fungi application reduces harmful effects of Ni stress in wheat

Bilingualism Is Associated with a Delayed Onset of Dementia but Not with a Lower Risk of Developing it: a Systematic Review with Meta-Analyses.

Some studies have linked bilingualism with a later onset of dementia, Alzheimer's disease (AD), and mild cognitive impairment (MCI). Not all studies have observed such relationships, however. Differences in study outcomes may be due to methodological limitations and the presence of confounding factors within studies such as immigration status and level of education. We conducted the first systematic review with meta-analysis combining cross-sectional studies to explore if bilingualism might delay symptom onset and diagnosis of dementia, AD, and MCI. Primary outcomes included the age of symptom onset, the age at diagnosis of MCI or dementia, and the risk of developing MCI or dementia. A secondary outcome included the degree of disease severity at dementia diagnosis. There was no difference in the age of MCI diagnosis between monolinguals and bilinguals [mean difference: 3.2; 95% confidence intervals (CI): -3.4, 9.7]. Bilinguals vs. monolinguals reported experiencing AD symptoms 4.7 years (95% CI: 3.3, 6.1) later. Bilinguals vs. monolinguals were diagnosed with dementia 3.3 years (95% CI: 1.7, 4.9) later. Here, 95% prediction intervals showed a large dispersion of effect sizes (-1.9 to 8.5). We investigated this dispersion with a subgroup meta-analysis comparing studies that had recruited participants with dementia to studies that had recruited participants with AD on the age of dementia and AD diagnosis between mono- and bilinguals. Results showed that bilinguals vs. monolinguals were 1.9 years (95% CI: -0.9, 4.7) and 4.2 (95% CI: 2.0, 6.4) older than monolinguals at the time of dementia and AD diagnosis, respectively. The mean difference between the two subgroups was not significant. There was no significant risk reduction (odds ratio: 0.89; 95% CI: 0.68-1.16) in developing dementia among bilinguals vs. monolinguals. Also, there was no significant difference (Hedges' g = 0.05; 95% CI: -0.13, 0.24) in disease severity at dementia diagnosis between bilinguals and monolinguals, despite bilinguals being significantly older. The majority of studies had adjusted for level of education suggesting that education might not have played a role in the observed delay in dementia among bilinguals vs. monolinguals. Although findings indicated that bilingualism was on average related to a delayed onset of dementia, the magnitude of this relationship varied across different settings. This variation may be due to unexplained heterogeneity and different sources of bias in the included studies. Registration: PROSPERO CRD42015019100