Numerical Simulation Algorithm Design of Influence on Existing Tunnel by Underpass Construction of New Tunnel

Simulation is a powerful tool that can be used for systematic planning, analysis, and decision-making. Proper designing is preliminary required to construct a new tunnel over an existing tunnel to ensure safety and durability. Once an underpass tunnel completes, the interaction between the tunnel structure and the nearby soil gains a stable state and the stress of the tunnel is balanced. However, the stability of an existing tunnel is affected if the construction in the nearby area is not properly analyzed. This article proposes a numerical simulation model to empirically analyze lining force and surface settlement in order to ensure safety in engineering practice. The existing tunnel structure working condition is simulated under the new tunnel. The artificial honeybee colony algorithm is used to extract the parameter fusion characteristic value of tunnel influence and the model of estimating the bending moment of group piles. The structural mechanics of existing tunnels under new tunnels are analyzed using the triple bend model to improve the bearing capacity of existing tunnels under new tunnels. Based on the above analysis, numerical simulation experiments are designed. The proposed method has high accuracy and strong fitting ability and can effectively reduce the displacement of existing tunnels. Moreover, the method can improve the bearing capacity of tunnels. For tunneling operation, the results of the simulation may be used as a recommendation.

Young honeybees show learned preferences after experiencing adulterated pollen

Pollen selection affects honeybee colony development and productivity. Considering that pollen is consumed by young in-hive bees, and not by foragers, we hypothesized that young bees learn pollen cues and adjust their preferences to the most suitable pollens. To assess whether young bees show preferences based on learning for highly or poorly suitable pollens, we measured consumption preferences for two pure monofloral pollens after the bees had experienced one of them adulterated with a deterrent (amygdalin or quinine) or a phagostimulant (linoleic acid). Preferences were obtained from nurse-aged bees confined in cages and from nurse bees in open colonies. Furthermore, we tested the bees’ orientation in a Y-maze using a neutral odour (Linalool or Nonanal) that had been previously associated with an amygdalin-adulterated pollen. Consumption preferences of bees, both in cages and in colonies, were reduced for pollens that had been adulterated with deterrents and increased for pollens that had been supplemented with linoleic acid. In the Y-maze, individuals consistently avoided the odours that they had previously experienced paired with the deterrent-adulterated pollen. Results show that nurse-aged bees associate pollen-based or pollen-related cues with either a distasteful/malaise experience or a tasty/nutritious event, leading to memories that bias their pollen-mediated response.

Responsiveness to inhibitory signals changes as a function of colony size in honeybees ( Apis mellifera )

Biological collectives, like honeybee colonies, can make intelligent decisions and robustly adapt to changing conditions via intricate systems of excitatory and inhibitory signals. In this study, we explore the role of behavioural plasticity and its relationship to network size by manipulating honeybee colony exposure to an artificial inhibitory signal. As predicted, inhibition was strongest in large colonies and weakest in small colonies. This is ecologically relevant for honeybees, for which reduced inhibitory effects may increase robustness in small colonies that must maintain a minimum level of foraging and food stores. We discuss evidence for size-dependent plasticity in other types of biological networks.

The Lifelog Monitoring System for Honeybees: RFID and Camera Recordings in an Observation Hive

A typical honeybee colony contains more than 15,000 individuals, each with its own task related to supporting the hive and maintaining the colony. In previous studies on honeybees, observing individual animals’ behaviors has been a difficult and time-consuming task to understand the relationship between in-hive communication and environmental changes outside the hive, therefore it is necessary in any attempt to develop applying a remote sensing technology. To allow researchers to pass much of this tracking work on to computers, we have developed the lifelog monitoring system for honeybees, which uses RFID and Raspberry Pi camera recordings. Our preliminary experiments consisted of several tests aimed at identifying the optimal conditions for this system. First, two commercial RFID readers with antennas were compared in terms of their sensitivity to signals from RFID tags placed at various distances. We found that the UP16-1000-J2 reader was much more sensitive and had a longer effective range compared to the UP4-200-J2. The most sensitive region in the RFID antenna on the UP16-1000-J2 reader was 30 mm long and 5 mm wide at its center. Based on this preliminary information, we designed and built a passage from the interior of the observation hive to the outside so that all RFID-tagged bees could be detected individually by the RFID reader as they walked through the passage. Moreover, to detect the direction of either departure or arrival of each bee, we placed two RFID antennas under the passage between the observation hive and the outside, one near each end of the passage. All departure and arrival times of RFID-tagged bees were detected with their ID numbers. Using recorded data from these two RFID readers, we could measure how much time each tagged bee spent outside the hive. In addition to RFID recording on the passage, we also tracked all in-hive movements of numbered RFID-tagged honeybees. In-hive movements were simultaneously, comprehensively and automatically recorded via six Raspberry Pi camera modules arranged on the two sides of the observation hive. The cameras were set to record from 6:30 to 19:30 every day for one month, once or twice each year from 2015 to 2018. The in-hive behaviors of these bees were analyzed according to a simultaneous tracking algorithm that we developed for this purpose. Data from the monitoring system revealed that time spent outside the hive increased markedly after following the waggle dance. In addition to its findings on bee behavior, this study also confirms the effectiveness of our recording system combining RFID and Raspberry Pi cameras for honeybee lifelog monitoring.

The Electronic Bee Spy: Eavesdropping on Honeybee Communication via Electrostatic Field Recordings

As a canary in a coalmine warns of dwindling breathable air, the honeybee can indicate the health of an ecosystem. Honeybees are the most important pollinators of fruit-bearing flowers, and share similar ecological niches with many other pollinators; therefore, the health of a honeybee colony can reflect the conditions of a whole ecosystem. The health of a colony may be mirrored in social signals that bees exchange during their sophisticated body movements such as the waggle dance. To observe these changes, we developed an automatic system that records and quantifies social signals under normal beekeeping conditions. Here, we describe the system and report representative cases of normal social behavior in honeybees. Our approach utilizes the fact that honeybee bodies are electrically charged by friction during flight and inside the colony, and thus they emanate characteristic electrostatic fields when they move their bodies. These signals, together with physical measurements inside and outside the colony (temperature, humidity, weight of the hive, and activity at the hive entrance) will allow quantification of normal and detrimental conditions of the whole colony. The information provided instructs how to setup the recording device, how to install it in a normal bee colony, and how to interpret its data.

Direct Economic Impact Assessment of Winter Honeybee Colony Losses in Three European Countries

Honeybees are of great importance because of their role in pollination as well as for hive products. The population of managed colonies fluctuates over time, and recent monitoring reports show different levels of colony losses in many regions and countries. The cause of this kind of loss is a combination of various factors, such as the parasitic mite Varroa destructor, viruses, pesticides, management practices, climate change, and other stress factors. Having in mind that the economic aspect of honeybee colony losses has not been estimated, a pioneer effort was made for developing a methodology that estimates the economic impact of honeybee colony losses. Winter loss data was based on 2993 answers of the COLOSS standard questionnaire survey of honeybee winter colony losses for 2016/2017. In addition, market and financial data were used for each country. In a comparative analysis, an assessment on the economic impact of colony losses in Austria, Czechia, and Macedonia was made. The estimation considered the value of the colonies and the potential production losses of the lost colonies and of surviving but weak colonies. The direct economic impact of winter honeybee colony losses in 2016/2017 in Austria was estimated to be about 32 Mio €; in Czechia, 21 Mio €; and in Macedonia, 3 Mio €. Economic impact reflects the different value levels in the three countries, national colony populations, and the magnitude of colony losses. This study also suggests that economic losses are much higher than the subsidies, which underlines the economic importance of honeybees for the agricultural sector.

Exposure to Inactivated Deformed Wing Virus Leads to Trans-Generational Costs but Not Immune Priming in Honeybees (Apis mellifera)

Pathogens are identified as one of the major drivers behind the honeybee colony losses, as well as one of the reasons for the reported declines in terrestrial insect abundances in recent decades. To fight infections, animals rely on their immune system. The immune system of many invertebrates can be primed by exposure to a pathogen, so that upon further exposure the animal is better protected. The protective priming effect can even extend to the next generation, but the species capable of priming the immune system of their offspring are still being investigated. Here we studied whether honeybees could prime their offspring against a viral pathogen, by challenging honeybee queens orally with an inactivated deformed wing virus (DWV), one of the most devastating honeybee viruses. The offspring were then infected by viral injection. The effects of immune priming were assayed by measuring viral loads and two typical symptoms of the virus, pupal mortality, and abnormal wing phenotype. We saw a low amount of wing deformities and low pupal mortality. While no clear priming effect against the virus was seen, we found that the maternal immune challenge, when combined with the stress caused by an injection during development, manifested in costs in the offspring, leading to an increased number of deformed wings.