29 research outputs found
An Experimental Study of Within- and Cross-cultural Cooperation: Chinese and American Play in the Prisoner’s Dilemma Game
We study whether cross- and within-culture groups have different cooperation rates in the Prisoner’s Dilemma Game. In an experiment, university students in China and America engage in a single iteration of the game, complete belief elicitation tasks regarding their opponents’ play and take a survey including attitudinal measurements regarding their in- and out-group attitudes. Cooperation rates are higher across the two countries are higher in both cross-culture and in within-culture interactions, although not significantly. We also find that Chinese participants cooperate less than American ones. Further, female Chinese participants are more cooperative than Chinese male ones. In the cross-culture treatment, Chinese participants underestimate the likelihood of cooperative behavior of their American counterparts, while Americans overestimate the same likelihood of their Chinese counterparts. Our results also show that Chinese participants cooperate more conditionally than American ones. Finally, while we find some attitudinal in- and out-biases both they do not generate meaningful impact on cooperative behavior
Dietary 25-hydroxy-cholecalciferol and additional vitamin E improve bone development and antioxidant capacity in high-density stocking broilers.
peer reviewedThis study aimed to investigate the effects of diets supplemented with 25-hydroxycholecalciferol [25-(OH)D3] and additional vitamin E on growth performance, antioxidant capacity, bone development, and carcass characteristics at different stocking densities on commercial broiler farms. A total of 118,800 one-day-old Arbor Acres broilers were assigned to a 2 × 2 factorial treatment consisting of two dietary vitamin levels (5,500 IU vitamin D3 and 60 IU vitamin E: normal diet, using half 25-(OH)D3 as a source of vitamin D3 and an additional 60 IU of vitamin E: 25-(OH)D3+VE diet) and two stocking densities (high density of 20 chickens/m2: HD and 16 chickens/m2: LD). The experiment lasted for 42 d. The results showed that high-density stocking negatively affected the growth performance of broilers during the first four weeks, whereas the vitamin diet treatment significantly improved the feed conversion ratios (FCR) during the last 2 wk. Vitamin diets increased catalase at 14 and 42 d, and the glutathione peroxidase (GSH-px) levels at 42 d in high-density-stocked broilers. The interaction showed that serum vitamin E levels were significantly improved at 28 d of age in high-density-stocked broilers as a result of the vitamin diets. Stocking density and dietary treatments were found to significantly affect bone development, with the vitamin diet significantly increasing metatarsal length and femoral bone strength in broilers from high-density stocking density at 28 d of age. High stocking density increased the proportion of leg muscles and meat yield per square meter. In general, 25-(OH)D3 and additional vitamin E suppressed oxidative stress and ameliorated the negative effects of high-density stocking on bone development in a commercial chicken farm setting. Vitamin diets improved the FCR of broilers, while high-density stocking resulted in better economic outcomes.High-density stocking is often associated with animal welfare risks in broilers, mainly in terms of oxidative stress and bone development. Nevertheless, farming at too low a density remains for the most part economically unviable. Modulation of antioxidant capacity and bone development by nutritional strategies in high-density-farmed broilers has proven an effective tool in developing countries. Therefore, the present study investigated the effects of applying diets with a higher biological potency of vitamin D3 25-hydroxycholecalciferol [25-(OH)D3] and a higher concentration of vitamin E on broiler production performance, antioxidant capacity and meat production performance at different densities of stocking under commercial farming conditions. The results indicated that the vitamin dietary treatments suppressed oxidative stress and ameliorated the negative effects of high-density farming on bone development
Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed
Implicit bias of (stochastic) gradient descent for rank-1 linear neural network
Studying the implicit bias of gradient descent (GD) and stochastic gradient descent (SGD) is critical to unveil the underlying mechanism of deep learning. Unfortunately, even for standard linear networks in regression setting, a comprehensive characterization of the implicit bias is still an open problem. This paper proposes to investigate a new proxy model of standard linear network, rank-1 linear network, where each weight matrix is parameterized as a rank-1 form. For over-parameterized regression problem, we precisely analyze the implicit bias of GD and SGD---by identifying a “potential” function such that GD converges to its minimizer constrained by zero training error (i.e., interpolation solution), and further characterizing the role of the noise introduced by SGD in perturbing the form of this potential. Our results explicitly connect the depth of the network and the initialization with the implicit bias of GD and SGD. Furthermore, we emphasize a new implicit bias of SGD jointly induced by stochasticity and over-parameterization, which can reduce the dependence of the SGD's solution on the initialization. Our findings regarding the implicit bias are different from that of a recently popular model, the diagonal linear network. We highlight that the induced bias of our rank-1 model is more consistent with standard linear network while the diagonal one is not. This suggests that the proposed rank-1 linear network might be a plausible proxy for standard linear net
Implicit bias of adversarial training for deep neural networks
We provide theoretical understandings of the implicit bias imposed by adversarial training for homogeneous deep neural networks without any explicit regularization. In particular, for deep linear networks adversarially trained by gradient descent on a linearly separable dataset, we prove that the direction of the product of weight matrices converges to the direction of the max-margin solution of the original dataset. Furthermore, we generalize this result to the case of adversarial training for non-linear homogeneous deep neural networks without the linear separability of the dataset. We show that, when the neural network is adversarially trained with ℓ2 or ℓ∞ FGSM, FGM and PGD perturbations, the direction of the limit point of normalized parameters of the network along the trajectory of the gradient flow converges to a KKT point of a constrained optimization problem that aims to maximize the margin for adversarial examples. Our results theoretically justify the longstanding conjecture that adversarial training modifies the decision boundary by utilizing adversarial examples to improve robustness, and potentially provides insights for designing new robust training strategies
Discrete State Event-Driven Framework With a Flexible Adaptive Algorithm for Simulation of Power Electronic Systems
An experimental study of intra- and international cooperation: Chinese and American play in the Prisoner's Dilemma Game
We study whether intra- and international groups have different cooperation rates in the Prisoner's Dilemma Game. We report on an experiment in which university students in China and America engage in a single iteration of the game, complete belief elicitation tasks regarding their counterparts' play, and complete a survey including attitudinal measurements regarding their in- and out-group attitudes. We find that Chinese overall cooperation rates are less than American ones. Further, female participants are more cooperative than males. With respect to international cooperation, Chinese participants accurately estimate the likelihood of cooperative behavior of their American counterparts, while Americans overestimate the same likelihood of their Chinese counterparts. Our results further show that Chinese participants cooperate more conditionally than American ones. Finally, we find a more positive attitude towards one's living country is related to less international cooperative behavior, and a more positive attitude towards the other country is related to more international cooperation
Rupture Models of the 2016 Central Italy Earthquake Sequence from Joint Inversion of Strong-Motion and InSAR Datasets: Implications for Fault Behavior
We derived the joint slip models of the three major events in the 2016 Central Italy earthquake sequence by inverting strong-motion and InSAR datasets. b-values and the historic earthquake scarp offset were also investigated after processing the earthquake catalog and near-field digital elevation model data. The three major events gradually released seismic moments of 1.6 × 1018 Nm (Mw 6.1), 1.5 × 1018 Nm (Mw 6.1), and 1.1 × 1019 Nm (Mw 6.7), respectively. All the ruptures exhibit both updip and along-strike directivity, but differ in the along-strike propagation direction. The high b-value found beneath three mainshock hypocenters suggests possible fluid intrusions, explaining the cascading earthquake behavior. The cumulative surface scarp from past earthquakes shows rupturing features that are consistent with the 2016 earthquake sequence, suggesting a characteristic fault behavior. Under the assumption of the Gutenberg–Richter law, the slip budget closure test gives a maximum magnitude of Mw 6.7 and implies the seismic hazard from the largest event has been released in this sequence
Rupture Models of the 2016 Central Italy Earthquake Sequence from Joint Inversion of Strong-Motion and InSAR Datasets: Implications for Fault Behavior
We derived the joint slip models of the three major events in the 2016 Central Italy earthquake sequence by inverting strong-motion and InSAR datasets. b-values and the historic earthquake scarp offset were also investigated after processing the earthquake catalog and near-field digital elevation model data. The three major events gradually released seismic moments of 1.6 × 1018 Nm (Mw 6.1), 1.5 × 1018 Nm (Mw 6.1), and 1.1 × 1019 Nm (Mw 6.7), respectively. All the ruptures exhibit both updip and along-strike directivity, but differ in the along-strike propagation direction. The high b-value found beneath three mainshock hypocenters suggests possible fluid intrusions, explaining the cascading earthquake behavior. The cumulative surface scarp from past earthquakes shows rupturing features that are consistent with the 2016 earthquake sequence, suggesting a characteristic fault behavior. Under the assumption of the Gutenberg–Richter law, the slip budget closure test gives a maximum magnitude of Mw 6.7 and implies the seismic hazard from the largest event has been released in this sequence
RNA sequencing transcriptomics and metabolomics in three poultry breeds
Abstract Chickens are remarkably versatile animals that are used as model organisms for biomedical research. Here, we performed metabolomic and RNA sequencing (RNA-Seq) transcriptomic analyses of the hypothalamus, liver tissue and serum of poultry with different genetic backgrounds, providing detailed information for hypothalamus and liver tissue at the transcriptional level and for liver tissue and serum at the metabolite level. We present two datasets generated from 36 samples from three poultry breeds using high-throughput RNA-Seq and liquid chromatography coupled with mass spectrometry acquisition (LC/MS). The transcriptomic and metabolomic data obtained for poultry of different genetic backgrounds will be a valuable resource for further studies on this model organism