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Citation maturity time varies for different articles. However, the impact of all articles is measured in a fixed window (2-5 years). Clustering their citation trajectories helps understand the knowledge diffusion process and reveals that not all articles gain immediate success after publication. Moreover, clustering trajectories is necessary for paper impact recommendation algorithms. It is a challenging problem because citation time series exhibit significant variability due to non-linear and non-stationary characteristics. Prior works propose a set of arbitrary thresholds and a fixed rule-based approach. All methods are primarily parameter-dependent. Consequently, it leads to inconsistencies while defining similar trajectories and ambiguities regarding their specific number. Most studies only capture extreme trajectories. Thus, a generalized clustering framework is required. This paper proposes a feature-based multiple k-means cluster ensemble framework. Multiple learners are trained for evaluating the credibility of class labels, unlike single clustering algorithms. 195,783 and 41,732 well-cited articles from the Microsoft Academic Graph data are considered for clustering short-term (10-year) and long-term (30-year) trajectories, respectively. It has linear run-time. Four distinct trajectories are obtained – Early Rise-Rapid Decline (ER-RD) (2.2%), Early Rise-Slow Decline (ER-SD) (45%), Delayed Rise-Not yet Declined (DR-ND) (53%), and Delayed Rise-Slow Decline (DR-SD) (0.8%). Individual trajectory differences for two different spans are studied. Most papers exhibit ER-SD and DR-ND patterns. The growth and decay times, cumulative citation distribution, and peak characteristics of individual trajectories' are re-defined empirically. A detailed comparative study reveals our proposed methodology can detect all distinct trajectory classes. • Introduces an innovative unsupervised Multiple K-Means Cluster Ensemble (MKMCE) framework for citation trajectory clustering. • Algorithmically determines the ideal number of clusters, eliminating the need for predefined labels and providing a data-driven approach. • Proposes a feature set that uniformly defines all trajectory patterns, aiding in accurate and consistent feature analysis. • Addresses and analyzes redundant interpretations of similar trajectories identified as different clusters, contributing to clearer nomenclature in the literature. • Offers practical applications, including the automated creation of a taxonomy based on inter-cluster similarity, facilitating a comprehensive understanding of trajectory patterns. [ABSTRACT FROM AUTHOR]

Toxoplasmosis has been recognized as a major public health problem worldwide. The consumption of uncooked or undercooked meat infected with Toxoplasma gondii tissue cysts is one of the main means of transmission of this parasite. Although sheep, goats, and pigs are commonly infected with T. gondii, little information is available on the distribution of T. gondii tissue cysts in naturally infected meat. In this study, we investigated the distribution of viable T. gondii tissue cysts in shoulder muscles of naturally infected lambs and goats. Hearts and shoulders of 46 lambs and 39 goats from a local grocery store were tested for T. gondii infection. Animals were evaluated for the presence of anti–T. gondii antibodies in heart blood and clots by the modified agglutination test. Fourteen of the 85 animals (seven lambs and seven goats) were seropositive. Six to 12 samples weighing 5, 10, and 50 g were obtained from shoulder muscles of each seropositive animal and used for bioassay in mice. The distribution of viable T. gondii differed according to the size of the sample analyzed, but in general larger sample sizes resulted in higher isolation rates (P , 0.05). Results of the study revealed an uneven distribution of T. gondii in muscle samples of lambs and goats and that T. gondii can be transmitted by consumption of very small servings (5 and 10 g) of meat when it is consumed raw or is undercooked. [ABSTRACT FROM AUTHOR]

• Superconducting properties of 2H NbSe 2 upon Sn intercalation is investigated. • Magnetic and transport studies reveal a significant reduction of both T c and B C2 (0). • Suppression of superconductivity due to strengthening of CDW is unlikely. • Strong correlation of Tc vs c -axis lattice parameter is observed. 2H NbSe 2 is known to be an archetype layered transitional metal dichalcogenide superconductor with a superconducting transition temperature of 7.3 K. In this article, we investigate the influence of Sn intercalation on superconducting properties of 2H NbSe 2. Sn being nonmagnetic and having no outer shell d-electrons unlike transition metals, one naively would presume that its effect on superconducting properties will be very marginal. However, our magnetic and transport studies reveal a significant reduction of both superconducting transition temperature and upper critical field [ T c and B C2 (0)] upon Sn intercalation. With a mere 4 mole% Sn intercalation, it is observed that T c and B C2 (0) get suppressed by ∼3.5 K and 3 T, respectively. Werthamer-Helfand-Hohenberg (WHH) analysis of magneto-transport data is performed to estimate B C2 (0). From the low temperature Raman scattering data in the normal phase of intercalated 2H NbSe 2 , it is inferred that the suppression of superconductivity cannot be ascribed to strengthening of charge density wave (CDW) ordering. Rather, the weakening of superconductivity is attributed to the observed increase of c -axis lattice parameter and the possible changes in the Fermi surface upon Sn intercalation. [ABSTRACT FROM AUTHOR]

High quality ultrathin transition-metal dichalcogenide films and their Vander Waals heterostructures are very promising for fabrication of optoelectronic devices for their superior photovoltaic performance, extreme flexibility and long lifetime due to suitable band gap and excellent light absorption capability. Designing the appropriate and suitable band structures of these materials is crucial for its promising applications. Especially, thin molybdenum disulfide (MoS 2 ) film is further attractive as compare to its monolayer counterpart for broad-spectral photo-detectors and photovoltaic application. However, very little understanding regarding the underlying physics behind the photo-response behavior of thin MoS 2 films is known. Here, we demonstrate a large photovoltaic response in thin MoS 2 films which produces an enormous photo-generated carrier and enhance the photocurrent by forming a heterojunction with p-type Si substrate. MoS 2 based photovoltaic devices efficiently produce high short-circuit photocurrent values of 18 mA/cm 2 and reasonably high power-conversion efficiency up to 4.5%. The present work will provide valuable scientific input of layered MoS 2 films for other emerging optoelectronic applications. [ABSTRACT FROM AUTHOR]

A cell line, designated as PHF, has been established from caudal fin of Pangasianodon hypophthalmus . The cell line was developed using explant method and PHF cells have been subcultured for more than 72 passages over a period of 14 months. The cells were able to grow at temperatures between 24 and 32° C, with an optimum temperature of 28° C. The growth rate of PHF cells was directly proportional to FBS concentration, with optimum growth observed at 20% FBS concentration. On the basis of immunophenotyping assay, PHF cells were confirmed to be of epithelial type. Karyotyping of PHF cells revealed diploid number of chromosomes (2n = 60) at 39th and 65th passage, which indicated that the developed cell line is chromosomally stable. The origin of the cell line was confirmed by amplification and sequencing of cytochrome oxidase c subunit I and 16S rRNA genes. The cell line was tested for Mycoplasma contamination and found to be negative. The cells were successfully transfected with GFP reporter gene suggesting that the developed cell line could be utilized for gene expression studies in future. The cell line could be successfully employed for evaluating the cytotoxicity of heavy metals, namely mercuric chloride and sodium arsenite suggesting that PHF cell line can be potential surrogate for whole fish for studying the cytotoxicity of water soluble compounds. The result of virus susceptibility to tilapia lake virus (TiLV) revealed that PHF cells were refractory to TiLV virus. The newly established cell line would be a useful tool for investigating disease outbreaks particularly of viral etiology, transgenic as well as cytotoxicity studies. [ABSTRACT FROM AUTHOR]

Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (808C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol-egg yolk-polymyxin agar and incubating at 308C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between-0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans. [ABSTRACT FROM AUTHOR]

Leafy green vegetables, including lettuce, are recognized as potential vehicles for foodborne pathogens such as Escherichia coli O157:H7. Fresh-cut lettuce is potentially at high risk of causing foodborne illnesses, as it is generally consumed without cooking. Quantitative microbial risk assessments (QMRAs) are gaining more attention as an effective tool to assess and control potential risks associated with foodborne pathogens. This study developed a QMRA model for E. coli O157:H7 in fresh-cut lettuce and evaluated the effects of different potential intervention strategies on the reduction of public health risks. The fresh-cut lettuce production and supply chain was modeled from field production, with both irrigation water and soil as initial contamination sources, to consumption at home. The baseline model (with no interventions) predicted a mean probability of 1 illness per 10 million servings and a mean of 2,160 illness cases per year in the United States. All intervention strategies evaluated (chlorine, ultrasound and organic acid, irradiation, bacteriophage, and consumer washing) significantly reduced the estimated mean number of illness cases when compared with the baseline model prediction (from 11.4- to 17.9-fold reduction). Sensitivity analyses indicated that retail and home storage temperature were the most important factors affecting the predicted number of illness cases. The developed QMRA model provided a framework for estimating risk associated with consumption of E. coli O157:H7–contaminated fresh-cut lettuce and can guide the evaluation and development of intervention strategies aimed at reducing such risk. [ABSTRACT FROM AUTHOR]

A recent study by the Centers for Disease Control and Prevention reported that between 1998 and 2008, leafy greens outbreaks accounted for 22.3% of foodborne outbreaks in the United States. Several studies on the growth of bacteria at different temperatures have been conducted; however, there is a need for the prediction of bacterial growth when leafy greens are transported without temperature control. Food products, when taken out of refrigeration, undergo a temperature change, with the rate of temperature change being proportional to the difference in the temperature of food and its surroundings. The objective of this study was to estimate the growth of Escherichia coli O157:H7, Salmonella enterica, and L. monocytogenes in leafy greens during transportation from retail to home at ambient temperatures ranging from 10 to 40°C for up to 10 h. Experiments were conducted to monitor the temperature increase in fresh spinach taken from refrigeration temperature to ambient temperature. The growth of pathogens was predicted using these changing temperature profiles with the three-phase linear model as a primary model and the square root model as the secondary model. The levels of E. coli O157:H7, S. enterica, and L. monocytogenes increased by 3.12, 2.43, and 3.42 log CFU at 40°C for the 10-h period, respectively, when no lag phase was assumed. If leafy greens are not kept out of refrigeration for more than 3 h, when the air temperature is 40°C or more, pathogen growth should be less than 1 log CFU. These results would assist in developing recommendations for food transportation without refrigeration. [ABSTRACT FROM AUTHOR]