General methods for designing single-mode planar photonic crystal waveguides in hexagonal lattice structures

We systematically investigate and compare general methods of designing single mode photonic crystal waveguides in a two-dimensional hexagonal lattice of air holes in a dielectric material. We apply the rather general methods to dielectric-core hexagonal lattice photonic crystals since they have not been widely explored before. We show that it is possible to obtain single mode guiding in a limited portion of the photonic bandgap of hexagonal lattice structures. We also compare the potentials of different photonic crystal lattices for designing single-mode waveguides and conclude that triangular lattice structures are the best choice

Association of PON1-L55M genetic variation and breast cancer risk: A case-control trial

Background: Paraoxonase 1 (PON1), a multifactorial antioxidant enzyme, has a defensive role against oxidative stress, which is believed to contribute to cancer development. This study aimed to investigate the association of PON1-L55M functional polymorphism with breast cancer risk. Material and methods: In the experimental study, blood samples were collected from 150 healthy women controls and 150 breast cancer subjects. The L55M genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism. Results: Our analysis showed that the genotypes distribution is in Hardy-Weinberg equilibrium for both case and control groups. Our data revealed that there are significant associations between PON1-L55M polymorphism and breast cancer risk in homozygote (OR= 2.13, 95CI= 1.14-4.00, p= 0.018), dominant (OR= 1.72, 95CI= 1.07-2.76, p= 0.024), and allelic (OR= 1.55, 95CI= 1.12-2.15, p= 0.008) models. Conclusions: Our results suggest that the PON1-L55M genetic variation could be a genetic risk factor for breast cancer risk and it could be considered as a molecular biomarker for screening of susceptible women. © 2020 Asian Pacific Organization for Cancer Prevention

Radiographic outcome of surgical treatment of adolescent idiopathic scoliosis in males versus females

Background: Studies on adolescent idiopathic scoliosis have well documented the differences between natural history of male and female patients. There are also differences in responses to nonoperative treatment, but the results of operative treatment in male patients compared with females have not been widely reported. Only few studies had compared the outcomes of operative treatment between male and female patients with different results. Methods: We retrospectively reviewed the outcome of 150 (112 girls and 38 boys) consecutive patients with diagnosis of adolescent idiopathic scoliosis who were managed surgically between May 1996 and September 2005. Next, male radiographic parameters were compared with female ones pre- and postoperatively. Then, a subgroup of 38 matched girls was compared regarding the age, curve type, curve magnitude, and the instrumentation we used. Results: In comparing male patients with unmatched girls, the boys had greater mean age (17.3 ± 2.3 vs. 16.3 ± 2.9; p = 0.049), greater primary curve (71.4 ± 21.3° vs. 62.7 ± 17.5°; p = 0.013), less flexibility (30.1 ± 13.5 vs. 40.3 ± 17.8; p = 0.01), and less correction percentage (51.3 ± 12.9 vs. 58.8 ± 16.5; p = 0/013). The loss of correction was comparable between the two groups. In the matched comparison, the flexibility in boys was less than girls (30.1 ± 13.5 vs. 38.1 ± 17.5; p = 0.027). Also, the boys had a smaller correction percentage compared to the girls, but this finding was not statistically significant. Conclusion: There was similar distribution curve pattern between male and female patients with AIS. Males had more rigid primary curves compared to females but a similar degree of postoperative scoliosis correction. Male AIS patients were older at the time of surgery. These preoperative gender differences, however; did not compromise the radiological outcomes of surgical treatment and the results were comparable between the genders. © 2008 Ameri et al; licensee BioMed Central Ltd

Phase transition in Schwarzschild-de Sitter spacetime

Using a static massive spherically symmetric scalar field coupled to gravity in the Schwarzschild-de Sitter (SdS) background, first we consider some asymptotic solutions near horizon and their local equations of state(E.O.S) on them. We show that near cosmological and event horizons our scalar field behaves as a dust. At the next step near two pure de-Sitter or Schwarzschild horizons we obtain a coupling dependent pressure to energy density ratio. In the case of a minimally couplling this ratio is -1 which springs to the mind thermodynamical behavior of dark energy. If having a negative pressure behavior near these horizons we concluded that the coupling constant must be $\xi<{1/4}$ >. Therefore we derive a new constraint on the value of our coupling $\xi$ . These two different behaviors of unique matter in the distinct regions of spacetime at present era can be interpreted as a phase transition from dark matter to dark energy in the cosmic scales and construct a unified scenario.Comment: 7 pages,no figures,RevTex, Typos corrected and references adde

Some notes about the density of states for a negative pressure matter

The main goal of this paper is deriving Density of states $g(\epsilon)$ (degeneracy function) per volume for an equation of state (EOS) $p=-\rho$ (we called it dark energy(DE)).We have concluded that thermodynamic quantities such as pressure and energy density are simple functions of temperature, fugacity, curvature and mass of Bosons. Our work has been expressed the origin of some claims about the negativity of the entropy for the scalar fields models of DE.Comment: 12 pages,Major revision,Typos fixed,References added,it has now been accepted for publication in International Journal of Modern Physics E. It was accepted on May 31, 201

Tramesan elicits durum wheat defense against the septoria disease complex

The Septoria Leaf Blotch Complex (SLBC), caused by the two ascomycetes Zymoseptoria tritici and Parastagonospora nodorum, can reduce wheat global yearly yield by up to 50%. In the last decade, SLBC incidence has increased in Italy; notably, durum wheat has proven to be more susceptible than common wheat. Field fungicide treatment can efficiently control these pathogens, but it leads to the emergence of resistant strains and adversely affects human and animal health and the environment. Our previous studies indicated that active compounds produced by Trametes versicolor can restrict the growth of mycotoxigenic fungi and the biosynthesis of their secondary metabolites (e.g., mycotoxins). Specifically, we identified Tramesan: a 23 kDa α-heteropolysaccharide secreted by T. versicolor that acts as a pro-antioxidant molecule in animal cells, fungi, and plants. Foliar-spray of Tramesan (3.3 μM) on SLBC-susceptible durum wheat cultivars, before inoculation of causal agents of Stagonospora Nodorum Blotch (SNB) and Septoria Tritici Blotch (STB), significantly decreased disease incidence both in controlled conditions (SNB: –99%, STB: –75%) and field assays (SNB: –25%, STB: –30%). We conducted these tests were conducted under controlled conditions as well as in field. We showed that Tramesan increased the levels of jasmonic acid (JA), a plant defense-related hormone. Tramesan also increased the early expression (24 hours after inoculation-hai) of plant defense genes such as PR4 for SNB infected plants, and RBOH, PR1, and PR9 for STB infected plants. These results suggest that Tramesan protects wheat by eliciting plant defenses, since it has no direct fungicidal activity. In field experiments, the yield of durum wheat plants treated with Tramesan was similar to that of healthy untreated plots. These results encourage the use of Tramesan to protect durum wheat against SLBC

Gauss-Bonnet holographic superconductors with magnetic field

We study the Gauss-Bonnet (GB) holographic superconductors in the presence of an external magnetic field. We describe the phenomena away from the probe limit. We derive the critical magnetic field of the GB holographic superconductors with backreaction. Our analytical approach matches the numerical calculations. We calculate the backreaction corrections up to first order of $O(\kappa^2=8\pi G)$ to the critical temperature $T_C$ and the critical magnetic field $B_C$ for a GB superconductor. We show that the GB coupling $\alpha$ makes the condensation weaker but the backreaction corrections $O(\kappa^2)$ make the critical magnetic field stronger.Comment: 9 pages, 4 figures. Accepted for publication by EP

Resolution of dark matter problem in f(T) gravity

In this paper, we attempt to resolve the dark matter problem in f(T) gravity. Specifically, from our model we successfully obtain the flat rotation curves of galaxies containing dark matter. Further, we obtain the density profile of dark matter in galaxies. Comparison of our analytical results shows that our torsion-based toy model for dark matter is in good agreement with empirical data-based models. It shows that we can address the dark matter as an effect of torsion of the space.Comment: 14 pages, 3 figure

Embryo selection through artificial intelligence versus embryologists: a systematic review

STUDY QUESTION What is the present performance of artificial intelligence (AI) decision support during embryo selection compared to the standard embryo selection by embryologists? SUMMARY ANSWER AI consistently outperformed the clinical teams in all the studies focused on embryo morphology and clinical outcome prediction during embryo selection assessment. WHAT IS KNOWN ALREADY The ART success rate is ∼30%, with a worrying trend of increasing female age correlating with considerably worse results. As such, there have been ongoing efforts to address this low success rate through the development of new technologies. With the advent of AI, there is potential for machine learning to be applied in such a manner that areas limited by human subjectivity, such as embryo selection, can be enhanced through increased objectivity. Given the potential of AI to improve IVF success rates, it remains crucial to review the performance between AI and embryologists during embryo selection. STUDY DESIGN, SIZE, DURATION The search was done across PubMed, EMBASE, Ovid Medline, and IEEE Xplore from 1 June 2005 up to and including 7 January 2022. Included articles were also restricted to those written in English. Search terms utilized across all databases for the study were: (‘Artificial intelligence’ OR ‘Machine Learning’ OR ‘Deep learning’ OR ‘Neural network’) AND (‘IVF’ OR ‘in vitro fertili*’ OR ‘assisted reproductive techn*’ OR ‘embryo’), where the character ‘*’ refers the search engine to include any auto completion of the search term. PARTICIPANTS/MATERIALS, SETTING, METHODS A literature search was conducted for literature relating to AI applications to IVF. Primary outcomes of interest were accuracy, sensitivity, and specificity of the embryo morphology grade assessments and the likelihood of clinical outcomes, such as clinical pregnancy after IVF treatments. Risk of bias was assessed using the Modified Down and Black Checklist. MAIN RESULTS AND THE ROLE OF CHANCE Twenty articles were included in this review. There was no specific embryo assessment day across the studies—Day 1 until Day 5/6 of embryo development was investigated. The types of input for training AI algorithms were images and time-lapse (10/20), clinical information (6/20), and both images and clinical information (4/20). Each AI model demonstrated promise when compared to an embryologist’s visual assessment. On average, the models predicted the likelihood of successful clinical pregnancy with greater accuracy than clinical embryologists, signifying greater reliability when compared to human prediction. The AI models performed at a median accuracy of 75.5% (range 59–94%) on predicting embryo morphology grade. The correct prediction (Ground Truth) was defined through the use of embryo images according to post embryologists’ assessment following local respective guidelines. Using blind test datasets, the embryologists’ accuracy prediction was 65.4% (range 47–75%) with the same ground truth provided by the original local respective assessment. Similarly, AI models had a median accuracy of 77.8% (range 68–90%) in predicting clinical pregnancy through the use of patient clinical treatment information compared to 64% (range 58–76%) when performed by embryologists. When both images/time-lapse and clinical information inputs were combined, the median accuracy by the AI models was higher at 81.5% (range 67–98%), while clinical embryologists had a median accuracy of 51% (range 43–59%). LIMITATIONS, REASONS FOR CAUTION The findings of this review are based on studies that have not been prospectively evaluated in a clinical setting. Additionally, a fair comparison of all the studies were deemed unfeasible owing to the heterogeneity of the studies, development of the AI models, database employed and the study design and quality. WIDER IMPLICATIONS OF THE FINDINGS AI provides considerable promise to the IVF field and embryo selection. However, there needs to be a shift in developers’ perception of the clinical outcome from successful implantation towards ongoing pregnancy or live birth. Additionally, existing models focus on locally generated databases and many lack external validation. STUDY FUNDING/COMPETING INTERESTS This study was funded by Monash Data Future Institute. All authors have no conflicts of interest to declare. REGISTRATION NUMBER CRD4202125633