scholarly journals Breakfast Canyon Discovered in Honeybee Hive Weight Curves

Insects ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 176 ◽  
Author(s):  
Niels Holst ◽  
William Meikle

Electronic devices to sense, store, and transmit data are undergoing rapid development, offering an ever-expanding toolbox for inventive minds. In apiculture, both researchers and practitioners have welcomed the opportunity to equip beehives with a variety of sensors to monitor hive weight, temperature, forager traffic and more, resulting in huge amounts of accumulated data. The problem remains how to distil biological meaning out of these data. In this paper, we address the analysis of beehive weight monitored at a 15-min resolution over several months. Inspired by an overlooked, classic study on such weight curves we derive algorithms and statistical procedures to allow biological interpretation of the data. Our primary finding was that an early morning dip in the weight curve (‘Breakfast Canyon’) could be extracted from the data to provide information on bee colony performance in terms of foraging effort. We include the data sets used in this study, together with R scripts that will allow other researchers to replicate or refine our method.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kalifa Manjang ◽  
Shailesh Tripathi ◽  
Olli Yli-Harja ◽  
Matthias Dehmer ◽  
Galina Glazko ◽  
...  

AbstractThe identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.


2021 ◽  
Author(s):  
Cong Wang ◽  
Zehao Song ◽  
Pei Shi ◽  
Lin Lv ◽  
Houzhao Wan ◽  
...  

With the rapid development of portable electronic devices, electric vehicles and large-scale grid energy storage devices, it needs to reinforce specific energy and specific power of related electrochemical devices meeting...


Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 158
Author(s):  
Peng Huang ◽  
Dan-Liang Wen ◽  
Yu Qiu ◽  
Ming-Hong Yang ◽  
Cheng Tu ◽  
...  

In recent years, wearable electronic devices have made considerable progress thanks to the rapid development of the Internet of Things. However, even though some of them have preliminarily achieved miniaturization and wearability, the drawbacks of frequent charging and physical rigidity of conventional lithium batteries, which are currently the most commonly used power source of wearable electronic devices, have become technical bottlenecks that need to be broken through urgently. In order to address the above challenges, the technology based on triboelectric effect, i.e., triboelectric nanogenerator (TENG), is proposed to harvest energy from ambient environment and considered as one of the most promising methods to integrate with functional electronic devices to form wearable self-powered microsystems. Benefited from excellent flexibility, high output performance, no materials limitation, and a quantitative relationship between environmental stimulation inputs and corresponding electrical outputs, TENGs present great advantages in wearable energy harvesting, active sensing, and driving actuators. Furthermore, combined with the superiorities of TENGs and fabrics, textile-based TENGs (T-TENGs) possess remarkable breathability and better non-planar surface adaptability, which are more conducive to the integrated wearable electronic devices and attract considerable attention. Herein, for the purpose of advancing the development of wearable electronic devices, this article reviews the recent development in materials for the construction of T-TENGs and methods for the enhancement of electrical output performance. More importantly, this article mainly focuses on the recent representative work, in which T-TENGs-based active sensors, T-TENGs-based self-driven actuators, and T-TENGs-based self-powered microsystems are studied. In addition, this paper summarizes the critical challenges and future opportunities of T-TENG-based wearable integrated microsystems.


2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jun Li ◽  
Qiang Dong ◽  
Yan Fu

As the rapid development of mobile Internet and smart devices, more and more online content providers begin to collect the preferences of their customers through various apps on mobile devices. These preferences could be largely reflected by the ratings on the online items with explicit scores. Both of positive and negative ratings are helpful for recommender systems to provide relevant items to a target user. Based on the empirical analysis of three real-world movie-rating data sets, we observe that users’ rating criterions change over time, and past positive and negative ratings have different influences on users’ future preferences. Given this, we propose a recommendation model on a session-based temporal graph, considering the difference of long- and short-term preferences, and the different temporal effect of positive and negative ratings. The extensive experiment results validate the significant accuracy improvement of our proposed model compared with the state-of-the-art methods.


2021 ◽  
Vol 6 (12) ◽  
pp. 117-132
Author(s):  
Gökçe CEREV ◽  
Ayşegül GÜRSUL

The rapid development of technology has deeply affected labour relationships. With the increasing technological developments, traditional mobbing, which is an important problem in labour relations, has started to leave its place to digital mobbing practices today. The biggest difference of digital mobbing from traditional mobbing is that the electronic devices used, eliminate the time and space factor. In this study, the effects of digital mobbing practices applied to employees in workplaces were examined through the example of private school teachers. The reason for choosing private school teachers is that the education sector is the sector where mobbing is encountered intensely. Teachers working in private schools in Elazig province constituted the population of the study. Semi-structured interview form, one of the qualitative research methods, was used in the study. Interview forms were evaluated with content analysis. As a result of the study, it was determined that digital mobbing practices occur in private schools in a multidimensional way and negatively affect labour relationships.


Nanoscale ◽  
2021 ◽  
Author(s):  
Shaoyang Xiong ◽  
Yue Qin ◽  
Linhong Li ◽  
Guoyong Yang ◽  
Maohua Li ◽  
...  

In order to meet the requirement of thermal performance with the rapid development of high-performance electronic devices, constructing a three-dimensional thermal transport skeleton is an effective method for enhancing thermal...


Author(s):  
Shouren Zhang ◽  
Huili Liu ◽  
Yadan Zhang ◽  
Shuaiwei Wang ◽  
Baocheng Yang

The rapid development of electronic devices require the high power storage battery. However, the reported 3D carbon based materials are semiconductor or metal and used for Li- or Na-ion battery...


2021 ◽  
Vol 21 (12) ◽  
pp. 5960-5964
Author(s):  
Kwon Jai Lee ◽  
Jee Young Oh ◽  
Kyong Nam Kim

With the rapid development of the electronics industry, high-density electronic devices and component mounting have gained popularity. Because of the heat generated from these devices, efficiency of the electronic parts is significantly lowered and life of various electronic devices is considerably shortened. Therefore, it is essential to efficiently dissipate the heat generated from the device to extend product life and ensure high efficiency of electronic components. This study evaluated how residual stress is impacted by the thickness of the deposited copper film, which is widely used as a heat dissipation material, and the number of graphene layers. The results confirmed that the residual stress decreased with increasing thickness. Moreover, the residual stress changed based on the transfer area of graphene, which had an elastic modulus eight times that of copper, indicating that the residual stress of the deposited copper film can be controlled.


Author(s):  
Binghe Liu ◽  
Huacui Wang ◽  
Yangzheng Cao ◽  
Xin Liu ◽  
Ya Mao ◽  
...  

With the rapid development of electric vehicles (EVs) and electronic devices in current mobile society, the safety issues of lithium-ion batteries (LIBs) have attracted worldwide attention. Mechanical, electrochemical, and thermal...


Big Data ◽  
2016 ◽  
pp. 2249-2274
Author(s):  
Chinh Nguyen ◽  
Rosemary Stockdale ◽  
Helana Scheepers ◽  
Jason Sargent

The rapid development of technology and interactive nature of Government 2.0 (Gov 2.0) is generating large data sets for Government, resulting in a struggle to control, manage, and extract the right information. Therefore, research into these large data sets (termed Big Data) has become necessary. Governments are now spending significant finances on storing and processing vast amounts of information because of the huge proliferation and complexity of Big Data and a lack of effective records management. On the other hand, there is a method called Electronic Records Management (ERM), for controlling and governing the important data of an organisation. This paper investigates the challenges identified from reviewing the literature for Gov 2.0, Big Data, and ERM in order to develop a better understanding of the application of ERM to Big Data to extract useable information in the context of Gov 2.0. The paper suggests that a key building block in providing useable information to stakeholders could potentially be ERM with its well established governance policies. A framework is constructed to illustrate how ERM can play a role in the context of Gov 2.0. Future research is necessary to address the specific constraints and expectations placed on governments in terms of data retention and use.


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