Search

Analyzing the statistical behavior of the assets' returns has shown to be an interesting approach to perform asset selection. In this work, we explore a stress-strength reliability approach to perform asset selection based on probabilities of the type $ P(X < Y) $ when both $ X $ and $ Y $ follow a generalized extreme value (GEV) distribution with three parameters. At first, we derive new analytical and closed form relations in terms of the extreme value $ \mathbb{H} $-function, which have been obtained under fewer parameter restrictions compared to similar results in the literature. To show the performance of our results, we include a Monte-Carlo simulation study and we investigate the application of the reliability measure $ P(X < Y) $ in selecting financial assets with returns characterized by the distributions $ X $ and $ Y $. Therefore, rather than the conventional approach of comparing the expected values of $ X $ and $ Y $ based on modern portfolio theory, we delve into the metric $ P(X < Y) $ as an alternative parameter for assessing better returns.

In reliability contexts, probabilities of the type R=P(X

Properly modeling the shadowing effects during wireless transmissions is crucial to perform the network quality assessment. From a mathematical point of view, using composite distributions allows one to combine both fast fading and slow fading stochastic phenomena. Numerous statistical distributions have been used to account for the fast fading effects. On the other hand, even though several studies indicate the adequacy of the Lognormal distributon (LNd) as a shadowing model, they also reveal this distribution renders some analytic tractability issues. Past works include the combination of Rayleigh and Weibull distributions with LNd. Due to the difficulty inherent to obtaining closed form expressions for the probability density functions involved, other authors approximated LNd as a Gamma distribution, creating Nakagami-m/Gamma and Rayleigh/Gamma composite distributions. In order to better mimic the LNd, approximations using the inverse Gamma and the inverse Nakagami-m distributions have also been considered. Although all these alternatives were discussed, it is still an open question how to effectively use the LNd in the compound models and still get closed-form results. We present a novel understanding on how the α-μ distribution can be reduced to a LNd by a limiting procedure, overcoming the analytic intractability inherent to Lognormal fading processes. Interestingly, new closed-form and series representations for the PDF and CDF of the composite distributions are derived. We build computational codes to evaluate all the expression hereby derived as well as model real field trial results by the equations developed. The accuracy of the codes and of the model are remarkable.

Hump-nosed viper (Hypnale hypnale; HNV) is one of the six major snake species in Sri Lanka that cause envenomation. Nephrotoxicity, coagulopathy, and neurotoxicity are wellrecognized features of its envenomation. Type 4 renal tubular acidosis (RTA4) has only once been described previously in this condition, and we report two further cases. Two patients aged 53 and 51 presented following HNV bites with acute kidney injury and microangiopathic hemolytic anemia. Both underwent multiple cycles of hemodialysis until the polyuric phase was reached. Despite polyuria, both patients developed resistant hyperkalemia that needed further hemodialysis. The urinary pH, arterial pH, delta ratio, and transtubular potassium gradient confirmed RTA4. HNV venom has been shown to damage the proximal convoluted tubules in animal studies, but not the distal convoluted tubule, and hence the mechanism of our observation in these two patients is unclear. Unexplained hyperkalemia in recovery phase of HNV bite should raise suspicions of RTA4.

Background: The psoas minor (PMi) is the most unstable muscle of the psoas group of the posterior abdominal muscle. This muscle has a fusiform shape and consists of a short fusiform belly continuing distally as a long tendon inserted on the pecten pubis and the iliopectineal arch. The present study was conducted to obtain more detailed information about the muscle and to expand knowledge about its morphology and morphometry. Materials and methods: The posterior abdominal wall of 30 adult cadavers was dissected. Anatomical variabilities in origin, insertion, length, width, and muscle-to-cone ratio were measured when PMi was found. The data collected was interpreted descriptively. Results: PMi was found in 12 cases - 10 bilateral and 2 unilateral. The origin was constant in all cases and, except for 3 cases, extended into the iliac fascia and the iliopubic eminence. Morphometric analysis revealed that the average length of the proximal muscle belly and distal tendons was 4.52 ± 1.35 cm and 13.05 ± ± 0.90 cm, respectively. The mean width of the muscle belly was 1.71 ± 0.17 cm, and that of the tendon was 0.47 ± 0.10 cm. On average, the muscle belly occupied the proximal 33.71 ± 6.15% of the total musculotendinous unit. Conclusions: Findings confirm the inconsistency of PMi in the study population. Morphological variations became more evident as the tendon approached the insertion level. The muscle's distal attachment to the iliac fascia may partially control the position and mechanical stability of the underlying iliopsoas, and this circumstantial function may be clinically related to iliopsoas inflammation and pathology. However, further studies are recommended to determine the biomechanical validity and clinical applicability of this vestigial muscle in humans. [ABSTRACT FROM AUTHOR]

This work aimed to derive new analytical formulas for the stress–strength reliability of the type P (X < Y) when both X and Y follow Fréchet, reversed Weibull or Weibull distributions. The new expressions were given in terms of extreme value H -functions and have been obtained under fewer parameter restrictions while compared to similar results in the literature of these distributions. The performance of the maximum likelihood estimator was evaluated through Monte-Carlo simulations and the results were compared with a nonparametric estimator. Three real dataset applications were carried out. First, we analyzed the statistical behavior of financial assets' returns, showing how P (X < Y) can be used to build an interesting approach to perform asset selection. Second, minimum monthly flows of water were analyzed. Finally, we compared failure voltage levels of two types of electrical cable insulation. For all the real case applications, confidence intervals for P (X < Y) were obtained by Bootstrap methods. [ABSTRACT FROM AUTHOR]

This paper reports the fabrication and 60Co gamma radiation effects on the silicon heterojunction solar cells (SHJ). The SHJ solar cells were fabricated by using physical vapor deposition technique. An n-type Si wafer was used as a substrate. The intrinsic layer, hole selective layer and transparent conductive oxide were deposited above the substrate. A complete SHJ solar cell was fabricated in dimension of 1 × 1 cm2. The illuminated I–V characteristics of SHJ solar cell with A.M 1.5 are done using the solar simulator. The different electrical characteristics of solar cell such as short circuit current (Isc), open circuit voltage (Voc), fill factor (FF) and conversion efficiency (η) were studied. The fabricated SHJ solar cell displayed a conversion η of 9.09%, a Voc of 0.733 V, an Isc of 19.14 mA, and an FF of 64.74%. The fabricated SHJ solar cells are subjected to doses of 60Co gamma radiation ranging from 100 krad to 100 Mrad. As the gamma dose aincreased, the solar cell output parameters also reduced. FF decreased from 64.74 to 57.16%, and Voc decreased from 0.73 to 0.66 V. The Isc decreased to 7.825 from 19.14 mA. The η decreased from 9.09 to 2.98% for the fabricated silicon SHJ solar cell. [ABSTRACT FROM AUTHOR]

Analyzing the statistical behavior of the assets' returns has shown to be an interesting approach to perform asset selection. In this work, we explore a stress-strength reliability approach to perform asset selection based on probabilities of the type P(X < Y) when both X and Y follow a generalized extreme value (GEV) distribution with three parameters. At first, we derive new analytical and closed form relations in terms of the extreme value H-function, which have been obtained under fewer parameter restrictions compared to similar results in the literature. To show the performance of our results, we include a Monte-Carlo simulation study and we investigate the application of the reliability measure P(X < Y) in selecting financial assets with returns characterized by the distributions X and Y. Therefore, rather than the conventional approach of comparing the expected values of X and Y based on modern portfolio theory, we delve into the metric P(X < Y) as an alternative parameter for assessing better returns. [ABSTRACT FROM AUTHOR]

This paper focuses on the estimation of multicomponent stress–strength models, an important concept in reliability analyses used to determine the probability that a system will function successfully under varying stress conditions. Understanding and accurately estimating these probabilities is essential in fields such as engineering and risk management, where the reliability of components under extreme conditions can have significant consequences. This is the case in applications where one seeks to model extreme hydrological events. Specifically, this study examines cases where the random variables X (representing strength) and Y (representing stress) follow extreme value distributions. New analytical expressions are derived for multicomponent stress–strength reliability (MSSR) when different classes of extreme distributions are considered, using the extreme value H-function. These results are applied to three l-max stable laws and six p-max stable laws, providing a robust theoretical framework for multicomponent stress–strength analyses under extreme conditions. To demonstrate the practical relevance of the proposed models, a real dataset is analyzed, focusing on the monthly water capacity of the Shasta Reservoir in California (USA) during August and December from 1980 to 2015. This application showcases the effectiveness of the derived expressions in modeling real-world data.

Anatomy, one of medicine’s vital subjects, demands extreme visualization to understand the intricate architecture of the human body. Although various other methods of virtual dissections are in place, an increasing number of anatomists, clinicians, and surgeons are advocating for re-enhancing anatomical education through traditional cadaveric dissection. These traditional pedagogies potentially expose anatomy educators to various risks in the dissection laboratory, which endangers their health and well-being. Unfortunately, no one is counting on them or the hazards they face. It’s like saying, “Fall ill at your own peril.” Various studies have revealed the occupational hazards anatomists are exposed to, but the issue remains unheard of or relatively heard. Hence, this narrative review aims to highlight numerous occupational risks that anatomists face worldwide, particularly in underdeveloped or developing nations. Simultaneously, the authors strongly advocate that competent authorities review and evaluate the working conditions of anatomy laboratories and frame policies that ensure the rights and optimal health of anatomy educators. [ABSTRACT FROM AUTHOR]