Results 1 to 10 of about 29,247 (265)

Emulación del crecimiento de hongos comestibles y medicinales utilizando un algoritmo evolutivo con un operador genético de tipo cilíndrico

Revista Colombiana de Computación, 2004
En este artículo se describe y analiza un modelo computacional para la emulación del crecimiento del hongo Pleurotus ostreatus en una de sus primeras etapas de crecimiento.
Alejandro Peña P., Jesús Antonio Hernández Riveros   +1 more
doaj  

Data-driven targets for predicting outcomes in patients with HIV infection and tuberculous meningitis in China

BMJ Neurology Open
Objectives For people living with HIV (PLWH) and tuberculous meningitis (TBM), current studies on risk stratification and poor prognosis lack a clear optimal threshold.
Hui Wang, Yan Sun, Zhimin Chen, Weimin Li, Yang Zhou, Qingxia Zhao, Yaokai Chen, Yinzhong Shen, Jianhua Yu, Yuwei Li, Pengfei Zhao, Yahong Chen, Haolan He, Yanfen Liu, Ping Ma, Mingbin Zheng, Min Lei, Hongzhou Lu   +17 more
doaj   +1 more source

Predicting the immunological nonresponse to antiretroviral therapy in people living with HIV: a machine learning-based multicenter large-scale study

Frontiers in Cellular and Infection Microbiology
BackgroundAlthough highly active antiretroviral therapy (HAART) has greatly enhanced the prognosis for people living with HIV (PLWH), some individuals fail to achieve adequate immune reconstitution, known as immunological nonresponse (INR), which is ...
Suling Chen, Suling Chen, Lixia Zhang, Lixia Zhang, Lixia Zhang, Jingchun Mao, Jingchun Mao, Zhe Qian, Yuanhui Jiang, Yuanhui Jiang, Xinrui Gao, Xinrui Gao, Mingzhu Tao, Mingzhu Tao, Guangyu Liang, Guangyu Liang, Jie Peng, Jie Peng, Shaohang Cai, Shaohang Cai   +19 more
doaj   +1 more source

Association between tumor size and prognosis in patients with small bowel adenocarcinoma-a SEER-based study

Heliyon
Background: The association between small-bowel adenocarcinoma (SBA) tumor size and prognosis is unclear, and we used the Surveillance, Epidemiology, and End Results (SEER) database to assess the prognostic value of SBA tumor size. Methods: Patients with
Jialin Zhou, Cong Wang, Tingcong Lv, Zhe Fan   +3 more
doaj   +1 more source

Boyanov-Naydenov problem and Kolmogorov type inequalities for positive (negative) parts of functions

Researches in Mathematics
We prove that Boyanov-Naidenov problem $\|x^{(k)}_{\pm}\|_{q,\, \mu} \to \sup$ on classes of functions $\Omega^r_p(A_0, A_r):=\{x\in L^r_{\infty}: \|x^{(r)}\|_{\infty}\le A_r, L(x)_p\le A_0 \}$, where $k= 0,1,...,r-1$, $q \ge 1$ for $k\ge 1$, $q \ge p ...
V.A. Kofanov
doaj   +1 more source

Numerical simulation of cracked orthotropic materials using extended isogeometric analysis [PDF]

, 2017
Abdel Wahab, Magd, Belaidi, I, Habib, S H, Khatir, S   +3 more
core   +2 more sources

Caffeine intake and late dry age-related macular degeneration: tea’s protective role—insights from NHANES and Mendelian randomization

International Journal of Retina and Vitreous
Background Although caffeine is widely consumed and has demonstrated neuroprotective effects, its role in age-related macular degeneration (AMD) remains unclear, particularly across disease subtypes and dietary sources such as tea and coffee.
Hongli Yang, Boshi Liu, Yunxi Zhang, Zhanhe Zhang, Huang Tan, Xiaorong Li   +5 more
doaj   +1 more source

Dynamic and fluid-structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models. [PDF]

Comput Mech, 2015
Hsu MC, Kamensky D, Xu F, Kiendl J, Wang C, Wu MC, Mineroff J, Reali A, Bazilevs Y, Sacks MS.   +9 more
europepmc   +1 more source

MortalitySmooth: An R Package for Smoothing Poisson Counts with P-Splines

Journal of Statistical Software, 2012
The MortalitySmooth package provides a framework for smoothing count data in both one- and two-dimensional settings. Although general in its purposes, the package is specifically tailored to demographers, actuaries, epidemiologists, and geneticists who ...
Carlo G. Camarda
doaj  

Deep Neural Network With a Smooth Monotonic Output Layer for Dynamic Risk Prediction. [PDF]

Stat Med
Zhou Z, Deng Y, Liu L, Jiang H, Peng Y, Yang X, Zhao Y, Ning H, Allen NB, Wilkins JT, Liu K, Lloyd-Jones DM, Zhao L.   +12 more
europepmc   +1 more source