Study on Buffering Performance of Aluminum Foam during Water-entry Process

The structure will suffer a huge overload, when it enters into water. The buffer head cap can effectively reduce the overload, and the buffer material in the cap is the key to its load reduction performance. In order to study the buffering ability of aluminum foam, an effective numerical simulation method is established in this paper. The numerical simulation method can effectively observe the motion of the structure and the energy absorption process of aluminum foam. It is found that the aluminum foam has strong capacity of buffering and reducing load by comparing with the structure without buffer head cap under the same conditions. In the process of energy absorption deformation, it can effectively protect the projectile from buckling deformation.

Hormonal Regulatory Patterns of LaKNOXs and LaBEL1 Transcription Factors Reveal Their Potential Role in Stem Bulblet Formation in LA Hybrid Lily

In lily reproduction, the mechanism of formation of bulbs has been a hot topic. However, studies on stem bulblet formation are limited. Stem bulblets, formed in the leaf axils of under- and above-ground stems, provide lilies with a strong capacity for self-propagation. First, we showed that above-ground stem bulblets can be induced by spraying 100 mg/L 6-BA on the LA hybrid lily ‘Aladdin’, with reduced endogenous IAA and GA4 and a higher relative content of cytokinins. Then, expression patterns of three potential genes (two KNOTTED1-like homeobox (KNOX) and one partial BEL1-like homeobox (BELL)), during stem bulblet formation from our previous study, were determined by RT-qPCR, presenting a down-up trend in KNOXs and a rising tendency in BELL. The partial BELL gene was cloned by RACE from L. ‘Aladdin’ and denoted LaBEL1. Physical interactions of LaKNOX1-LaBEL1 and LaKNOX1-LaKNOX2 were confirmed by yeast two-hybrid and bimolecular fluorescence complementation assays. Furthermore, hormonal regulatory patterns of single LaKNOX1, LaKNOX2, LaBEL1, and their heterodimers, were revealed in transgenic Arabidopsis, suggesting that the massive mRNA accumulations of LaKNOX1, LaKNOX2 and LaBEL1 genes during stem bulblet formation could cause the dramatic relative increase of cytokinins and the decline of GAs and IAA. Taken together, a putative model was proposed that LaKNOX1 interacts with LaKNOX2 and LaBEL1 to regulate multiple phytohormones simultaneously for an appropriate hormonal homeostasis, which suggests their potential role in stem bulblet formation in L. ‘Aladdin’.

Assessing Energy Source Preference of Household and Stand Diversity in the Catchment Area of Bamako, Mali

Wood fuel as a domestic combustible plays a major role for the Malian population (more than 90% of households depend on it for domestic cooking). It is used in rural as well as in urban areas. This paper focuses on assessing the energy source preference of households and stand diversity in Bamako catchment area. We have surveyed 200 households and 70 firewood and charcoal sellers in the District of Bamako. Forest inventory was carried out in Famana and Kassela within the Bamako catchment area where plots have been established (10 plots of 50 x 20 m per site). Plots were separated from each other by 50m. Results showed that the use of charcoal is higher than firewood in the urban households due to its availability and easy handling. 71.50% of households in Bamako use charcoal for cooking meals. Charcoal has become the most preferred source of energy for households in Bamako. The main factors for this trend are related to poverty, cooking habits of households, and urbanization. The two sites (Famana and Faya) are characterized by high diversity. Famana has a Shannon Diversity Index of 2.92 while Faya has 2.55. The study revealed a strong capacity of woody formations to provide species such as Combretum glutinosum, Combretum micranthum, and Lannea velutina which is very convenient for domestic combustion. These species have a rapid regeneration capacity and can grow in many types of ecological environments. Species such as Parkia biglobosa, Vittelaria paradoxa, Ficus gnaphalocarpa, and Khaya senegalensis (protected species) that are highly appreciated by households of Bamako have a great economic value and are constantly under threat. Households demand for these species exceeds the production capacity of forests. Immediate actions are needed to promote modern energy in order to ensure sustainable development.

GicoFace: A Deep Face Recognition Model Based on Global-Information Loss Function

As CNNs have a strong capacity to learn discriminative facial features, CNNs have greatly promoted the development of face recognition, where the loss function plays a key role in this process. Nonetheless, most of the existing loss functions do not simultaneously apply weight normalization, apply feature normalization and follow the two goals of enhancing the discriminative capacity (optimizing intra-class/inter-class variance). In addition, they are updated by only considering the feedback information of each mini-batch, but ignore the information from the entire training set. This paper presents a new loss function called Gico loss. The deep model trained with Gico loss in this paper is then called GicoFace. Gico loss satisfies the four aforementioned key points, and is calculated with the global information extracted from the entire training set. The experiments are carried out on five benchmark datasets including LFW, SLLFW, YTF, MegaFace and FaceScrub. Experimental results confirm the efficacy of the proposed method and show the state-of-the-art performance of the method.

Improvement of One-Shot-Learning by Integrating a Convolutional Neural Network and an Image Descriptor into a Siamese Neural Network

Over the last few years, several techniques have been developed with the aim of implementing one-shot learning, a concept that allows classifying images with only a single image per training category. Conceptually, these methods seek to reproduce certain behavior that humans have. People are able to recognize a person they have only seen once, but they are probably not able to do the same with certain animals, such as a monkey. This is because our brains have been trained for years with images of people but not so much of animals. Among the one-shot learning techniques, some of them have used data generation, such as Generative Adversarial Networks (GAN). Other techniques have been based on the matching of descriptors traditionally used for object detection. Finally, one of the most prominent techniques involves using Siamese neural networks. Siamese networks are usually implemented with two convolutional nets that share their weights. They receive two images as input and can detect whether they belong to the same category or not. In the field of grocery products, there has been a lot of research on the one-shot learning problem but not so much on the use of Siamese networks. In this paper, several classifiers are firstly evaluated to decide on a convolutional model to be used with the Siamese and to improve the baseline results obtained in the dataset used. Then, two existing techniques are integrated within the Siamese model: a convolutional net and a Local Maximal Occurrence (LOMO) descriptor. The latter was initially used for the re-identification of people although it has shown its effectiveness to improve the values of a traditional Siamese with only convolutional sisters. The whole network is trained on categories and responds to different categories, showing its strong capacity to deal with the problem of having only one image per category.

Enhancing the Capacity of Local Health Departments to Address Birth Equity: The Institute for Equity in Birth Outcomes

Introduction Significant and persistent racial and ethnic disparities exist related to infant mortality and other birth outcomes. Few models exist that aim to prepare organizations to implement essential features, such as community engagement or intervening on social determinants of health. Methods Between 2013 and 2015, teams from seven local health departments participated in the Institute for Equity in Birth Outcomes (EI) with the goals of building capacity and implementing changes to address equity in birth outcomes. Four of the teams enrolled in the first cohort (2013–2015), and three enrolled in cohort two (2014–2015). To examine the EI effort and its impact on capacity and implementation of changes, two types of assessments were completed. Capacities of the teams in specific key areas were assessed using “Best Change Process” instruments at the completion of participation in the EI. Teams also documented on an ongoing basis implementation of interventions. The data were analyzed using descriptive statistics and Pearson Correlation tests. Results Best Change Process capacity scores were higher in the first cohort than in the second and were highly correlated with implementation of changes (Pearson’s Correlation = 0.838, p = 0.037). Collectively, the teams implemented about 32 new programs, policies, practices, and systems changes aimed at addressing equity in birth outcomes. Most interventions were based on scientific recommendations and local epidemiologic data. Discussion The results of the study suggest the EI is a promising approach that may result in strong capacity and ability to implement interventions aimed at addressing equity in birth outcomes.

Towards a Concept of Political Robustness

How effective are different political institutions, policy-making processes and policies when it comes to mediating, mitigating and managing vertical and horizontal political tensions caused by disruptive societal challenges and political polarization? The present crisis for liberal democracy places this question high on the research agenda. A concept of political robustness is helpful for identifying the properties of political systems with a strong capacity for coping with political instability and conflict. This article defines political robustness, draws the contours of a conceptual framework for analysis of the political robustness of political systems and applies it illustratively to the political robustness of liberal democracies. We propose that the robustness of a political system depends on how much those who voice political demands—which differs greatly over time and between regimes—are involved in aggregating and integrating political demands into binding decisions.

Primary ectocervical epithelial cells display lower permissivity to Chlamydia trachomatis than HeLa cells and a globally higher pro-inflammatory profile

The tumoral origin and extensive passaging of HeLa cells, a most commonly used cervical epithelial cell line, raise concerns on their suitability to study the cell responses to infection. The present study was designed to isolate primary epithelial cells from human ectocervix explants and characterize their susceptibility to C. trachomatis infection. We achieved a high purity of isolation, assessed by the expression of E-cadherin and cytokeratin 14. The infectious progeny in these primary epithelial cells was lower than in HeLa cells. We showed that the difference in culture medium, and the addition of serum in HeLa cultures, accounted for a large part of these differences. However, all things considered the primary ectocervical epithelial cells remained less permissive than HeLa cells to C. trachomatis serovar L2 or D development. Finally, the basal level of transcription of genes coding for pro-inflammatory cytokines was globally higher in primary epithelial cells than in HeLa cells. Transcription of several pro-inflammatory genes was further induced by infection with C. trachomatis serovar L2 or serovar D. In conclusion, primary epithelial cells have a strong capacity to mount an inflammatory response to Chlamydia infection. Our simplified purification protocol from human explants should facilitate future studies to understand the contribution of this response to limiting the spread of the pathogen to the upper female genital tract.

Health Inequalities in the Time of COVID-19: The Globally Reinforcing Need to Strengthen Health Inequalities Research Capacities

The full impact of coronavirus disease 2019 (COVID-19) is yet to be well established; however, as the pandemic spreads, and early results emerge, unmet needs are being revealed, and pressing questions are being asked about who is most affected, how, where, and in what ways government responses might be exacerbating inequalities. A number of scholars have called for more in-depth critical research on COVID-19 and health inequalities to produce a strong empirical evidence based on these issues. There are also justifiable concerns about the scarcity of health-equity actions oriented analyses of the situation and calls for more empirical evidence on COVID-19 and health inequalities. A preliminary condition to establish this type of information is strong capacity to conduct health inequalities research. Worldwide, however, this type of capacity is limited, which, alongside other challenges, will likely hinder capacities of many countries to develop comprehensive equity-oriented COVID-19 analyses, and adequate responses to present and future crises. The current pandemic reinforces the pending need to invest in and strengthen these research capacities. These capacities must be supported by widespread recognition and concern, cognitive social capital, and greater commitment to coordinated, transparent action, and responsibility. Otherwise, we will remain inadequately prepared to respond and meet our society’s unmet needs.

Assessing City Governance for Low-Carbon Mobility in London

City-level decisions are crucial for delivering a low carbon transition, particularly as urban population dynamics and environments change in response to the COVID-19 pandemic. Ensuring appropriate governance structures, mechanisms and resources to facilitate these decisions is therefore essential. Based on a systematic literature review by van der Heijden (2019), this paper develops a simple framework to assess the state of ten enabling factors for effective urban climate governance, and applies it to low-carbon passenger mobility in London. Drawing on documentary evidence and a series of semi-structured expert interviews, it finds that London’s city authorities have a strong capacity for autonomy, stakeholder participation, local leadership and coordination on climate action and mobility, of which they make extensive use. The national legal and political framework remains broadly supportive following the UK’s departure from the EU, but multi-level co-ordination is thin, and funding issues have intensified conflict over political jurisdiction since the pandemic began. Spatial variation in urban form and infrastructure, coupled with dual-layer city administration, complicate the socio-political landscape and drive for climate action in mobility.