*3.1. Reproducible Production Technology for MEAs*

In PEM electrolyzers, the MEA is situated between the gas diffusion layers and consists of two porous, gas-permeable electron- and proton-conducting catalyst layers (anode and cathode) that comprise a gas-tight proton-conducting polymer membrane. Iridium oxide and platinum are common catalyst materials. Nafion, a perfluorinated alkyl sulfonic acid, is predominantly used as a proton-conducting material. Nafion is also used as an electron-isolated proton-conducting material for the membrane itself.

For the production of MEAs in the MW scale, it is important that the manufacturing processes used meet the requirements for scalability and production speed. The transfer or decal method outlined in Figure 2 meets these requirements. The process steps used, such as coating a substrate with a catalyst dispersion using a doctor blade or slot die and the subsequent drying, can be carried out in a laboratory or a roll-to-roll process. This also

applies to the subsequent assembly process where the dried catalyst layers are transferred from substrate to a membrane with a hot pressing process.

**Figure 2.** Process steps for producing an MEA using the decal process.

The production of MEAs for PEM water electrolysis faces the challenge of increasing the electrochemical efficiency of the MEAs and structuring the entailed processes in such a way that they are scalable and can be mass-produced. The electrochemical efficiency of MEAs partially depends on the thickness of the membrane used, as the protons flowing through the membrane during cell operation induce ohmic losses. This requirement can be fulfilled using the aforementioned decal process in which the thinnest possible membranes are used during assembly. However, a compromise must be made between membranes that are as thin as possible but still easy to handle in the production process.

Scalable processes, such as slot die or blade coating, are ideal for the industrial-scale coating of a substrate. A disadvantage of blade coating (a form of self-metered coating) is that the homogeneity of the coating cannot always be precisely controlled [70], whereas slot dies (which allow for a pre-dosed coating) can produce highly homogeneous coatings in combination with homogeneous substrates [71]. The possibility of pre-dosing means that the catalyst loading of the electrodes can be precisely adjusted by means of the dosing rate of the pump and the coating speed, provided that the dispersion composition is known. As the MEAs in the stack are connected in series for PEM electrolysis, it is highly important that the electrodes are identical and that the rolls of electrodes being produced from which the electrodes are subsequently cut are also homogenous. The specifications shown in Table 2 were applied for the catalyst loading of the MEAs being produced for the MW electrolysis system.

**Table 2.** Materials used in the construction of the MEAs.

A Premion (Alfa Aesar) IrO2 catalyst was used as the anode catalyst and a Pt/C 60% high surface area (HAS) Ketjen Black (Fuel Cell Store) catalyst was used as the cathode catalyst. The Nafion NR212 membranes were purchased from Chemours. An additional specification was the use of a recombination catalyst to be inserted into the MEA to break down the hydrogen permeating through the membrane with oxygen and thus minimize the safety risk presented by oxy-hydrogen formation during operation of the stack. As previously published methods of use of such recombination systems [72,73] could not be scaled to the required production size, a new method was developed and used for the production process described in the following sections [74].

Dispersions were produced from the catalyst powders that were applied to a fiberglassreinforced polytetrafluoroethylene (PTFE) roll in the roll-to-roll coating system (Figure 3a) by means of a slot die. During drying, it must be ensured that the combination of solvent evaporation and the formation of layers does not lead to layer defects and the flaking of

dried layers [75,76]. The specific machine settings were determined in preliminary tests. After drying, the coated material was rolled up (see Figure 3b) and the electrodes were cut from the roll with dimensions of 32.5 × 32.5 cm2 (see Figure 3c).

After producing the anodes and cathodes, they were assembled together with the Nafion NR212 membranes using hot presses from P/O/Weber. After pressing, the substrates were then removed from the cooled MEAs, which were then completed (see Figure 4).

**Figure 4.** (**a**): After assembly, the substrate could be removed from the electrode; (**b**): A complete and isolated MEA.

For the purpose of quality assurance, samples were taken from the rolls of electrodes to produce MEAs for laboratory cells and for the electrochemical characterization of the MEAs.

Figure 5 shows a polarization curve plotted from the characterization measurements, an efficiency curve, and a graph demonstrating the proportional volume of hydrogen in the anode gas. The latter clearly shows that safe operation can be achieved with the MEAs produced, even with small current densities. Within the scope of measurement uncertainty, no hydrogen could be detected as a result of the recombination catalyst being used.

#### *3.2. Compact, Efficient, and Robust Cell Components*

The previously considered MEA is a component that plays the main role in producing hydrogen in electrolyzers. It is here that the electrochemical water splitting reactions and the generation of heat occur due to operational and material-related overvoltages. However, as indicated by the setup of the MEAs, additional cell and stack components are required to produce hydrogen in MW electrolyzers on an industrial scale. The entire assembly of the electrolyzer must support the following process functions:

On the left-hand side of Figure 6 can be seen an exploded view of an electrolysis stack from the Ekolyser project (funding reference no. 03ESP106A) being funded by the Federal Ministry for Economic Affairs and Energy (BMWi). The stack is closed off by two massive end plates through which the media are added and removed and through which the power connection is made. The combination of end plates and tie rods also ensures that the inner components are pressed together. A defined contact pressure helps to ensure that the components are sufficiently sealed and that they have electrical or mechanical contact. The contact pressure is adjusted via the tractive forces in the tie rods. A distinction must be made between two areas: the active cell area and the sealing area. Although the optimal contact pressure on the active cell area is 2–3 MPa [44], the required pressure on the sealants is dependent on the sealing concept. The inner components are the repeating units of the electrolysis stack. A repeating unit always consists of one bipolar unit and one MEA. In Figure 6a, three bipolar units are shown. The MEAs (not shown here) are each arranged between the bipolar units. The active cell area is 300 cm2 (10 cm × 15 cm). In Figure 6b, an assembled electrolysis stack comprising 27 cells can be seen. The stack is designed for an electrical power supply of 50 kW with a maximum operating pressure of 50 bar.

**Figure 6.** Electrolysis stack from the Ekolyser project; (**a**): Exploded view with three bipolar units; (**b**): 27-cell stack, 50 kWel, 50 bar.

Developed as part of the Ekolyser project, the bipolar unit with seven individual components is shown in Figure 7. The central aspect of the bipolar unit is the bipolar plate, which separates the anode and cathode sides of the two adjacent electrolysis cells in a gas-tight manner. The bipolar plate is made of stainless steel 1.4404 (316L) and also features flow distributor structures that are produced by hydroforming to distribute the feed water equally across the active cell area and to remove the produced gases—oxygen on the anode side and hydrogen on the cathode side—with surplus water. The bipolar plate is enclosed on both sides by a polyether ether ketone (PEEK) frame. The frames feature distribution and collector structures for the inflow/outflow of media (water and two-phase flow) from pipes installed at the end plates (see Figure 6b) to the respective cell level. Additional covers made of stainless steel are required to provide mechanical support for sealants (not shown) in the distribution and collector structures. The frame cutouts admit fine distribution structures of varying porosity on the anode and cathode sides. The anode side features a layer of sintered Ti powder. A perforated stainless steel plate is used on the cathode side. In addition, a carbon fiber layer can be found on the MEA side, which is not shown in Figure 7.

**Figure 7.** Bipolar unit consisting of several parts from the Ekolyser project.

A significant drawback of this bipolar unit is the fact that all components must be individually laid on top of each other when assembling the stacks. For the 27-cell stack shown above, the individual parts (including O-rings) amount to around 600 for the repeating units alone. The assembly of the stacks is extremely time-intensive and there is also the potential for sources of error, which can lead to malfunctions in stack operation. These

include leaks outside and within the stack, as well as inhomogeneities in contact pressure distribution. The higher the number of individual components, the greater the likelihood of errors occurring during assembly. The dimensional tolerances of the components and the shifting of components during assembly play a key role in ensuring the quality of the entire assembly.

To counter this problem, the development of a "one-component bipolar unit" was initiated as part of the Energy Lab 2.0 and LLEC projects. Another aspect to consider was that only cost-effective, readily available raw materials should be used. The active cell area also had to be significantly increased to approximately 1000 cm2 in order to advance development towards MW electrolysis. The starting components for the newly developed bipolar unit are shown in Figure 8. A distinguishing feature of the bipolar unit is that all of its components are comprised of Ti. According to Lædre et al. [77], Ti is a material that exhibits good corrosion stability under electrolysis conditions. To counteract degradation effects, an additional coating may need to be applied to the contact areas of the MEA. The setup shown in Figure 8 reveals a simple central plate with drill holes and elongated holes for the supply of media. The double-sided simple frames merely contain holes that enable media to pass through. Three-part expanded metal sandwiches are inserted into the frame interiors. The elongated holes in the center plate allow the media to flow in and out of these areas. The expanded metal sandwiches serve as flow distributors. A Ti fleece acting as a fine distribution structure can be found on the anode side of the bipolar unit.

All previously described components are connected to each other in an interlocking manner by means of diffusion welding. This process takes place in a vacuum oven in which the stacked components are heated by thermal radiation up to a temperature close to enabling phase transition (882 ◦C for Ti). When the desired temperature is reached, a defined pressure is applied to the components through a mobile stamp in the oven.

As is shown in Figure 9, the stack assembly can be handled manually and easily by two people. Simple assembly aids in the form of plastic rods enhance the positioning accuracy of the components. The repeating units now comprise the following components: a bipolar unit, flat gasket, carbon fiber sheet, and an MEA. In Figure 9c, a fully assembled short stack can be seen. The performance and long-term behavior of the stack in operation has yet to be determined and will be documented and discussed in a later publication. The nominal power of a stack with 70 cells of this type will be in the range of 400 kW.

**Figure 9.** Manual stack assembly with one-part bipolar plate; (**a**): MEA; (**b**): bipolar unit; (**c**): interlocked stack.

#### *3.3. Design and Setup of the Test Facility*

On the basis of interdisciplinary approaches, Jülich researchers and engineers work on electrolysis technologies at various stages of development. A relatively new technology for industrial-scale application is polymer electrolyte membrane water electrolysis, which features dynamic operation and a high overload capacity. A new test facility, which is unique in this way, was developed in close collaboration with the Canadian company Greenlight, which is schematically illustrated in Figure 10. The test facility allows for the comprehensive characterization of PEM electrolysis stacks with an electrical output of up to 500 kVA with current intensities of up to 4000 ADC/10,000 ADC. The pressures can be flexibly adjusted between 4 bar and 50 bar for the anode and cathode circuits. Characterization can thus be flexibly performed at various pressure levels with balanced pressure or differential pressures.

**Figure 10.** Process overview of the MW electrolysis system.

The main features of the test facility are as follows: power electronics enable the conversion of 400 VAC mains electricity into direct voltage up to 125 VDC. The anode and cathode are each fitted with their own gas/water circuits, which are used for heating and cooling the stack as well as supplying it with water. The gas separators also separate the converted water from the produced gas in the circuits and can regulate the produced gases at pressures of up to 50 bar by means of membrane pressure regulators. Therefore, the gas can be made available for consumers or temporary storage. For stable and disruption-free electrolysis operation, the regulation of pressure to minimize the differential pressure between the two gas circuits is very important. The deionized fresh water required for electrolysis is supplied by an in-house system and introduced to the test stand using a booster pump in accordance with the current operating pressure. In addition to regulating pressure, the temperature is also optimally regulated, which has a significant influence on achieving optimal operation and helps to compensate for highly dynamic load changes and the resulting waste heat as quickly as possible.

Comprehensive recording and processing of the measurement data allows for automated operation under predefined load profiles and ensures the transfer of data to overarching control systems of EnergyLab and LLEC living labs, which are described in the following sections. Data are connected to the control systems of the LLEC, which enables optimal electrolysis operation in terms of energy efficiency and performance in the entire network of systems by means of a specially initiated data exchange in the Jülich virtual local area network (VLAN). The protocol used for the data exchange is based on the message queuing telemetry transport (MQTT) network protocol. The MQTT is very well suited for large networks of systems with high data transfer rates, as is predominantly the case with automation technology. Therefore, it is important that all units in the LLEC are equipped with an MQTT protocol. All required data are collected and evaluated centrally with the LLEC's control systems. To enable optimized operation in the entire network of systems, the desired values must be transferred to the available systems in addition to the evaluated data. This again takes place using the MQTT protocol to ensure optimized control at the highest control level. The electrolyzer itself is then capable of regulating the desired values and can implement the provisions of the LLEC's control system. Safety-based limits for the LLEC's desired values are integrated into the test stand control system and help protect the personnel and systems.

The test facility shown in Figure 11a enables the integration of various PEM electrolysis stacks up to an electrical power input of 400 kW for an active cell area of up to 1200–3000 cm2 if the power electronics reserve is expanded for currents of up to 10,000 ADC.

**Figure 11.** Electrolysis facility with first stack in the pilot plant; (**a**): PEM electrolysis test facility (GREENLIGHT); (**b**): 400 kW PEM stack (IEK-14, FZJ); (**c**): IGBT-based AC/DC converter (AIXCOM).

From a safety perspective, the legal and operational provisions were implemented, adherence to which was confirmed by successful inspections of the Technical Supervisory Association (TÜV), particularly in the areas of explosion protection and pressure equipment. From a technical standpoint, many of the required inspections were performed with the aid of a safety-oriented programmable logic controller (PLC).

The entire electrolysis system is part of a technical center that is equipped with the necessary facilities for the supply of media and energy, as well as the forward transport, conditioning, and removal of all products from the electrolysis process. The technical center also features the technical facilities required for ventilation and the safe removal of media, as well as a control room in which all measurements are recorded and processed.

*3.4. Energy Lab 2.0: Real-Life Laboratory and Simulation Platform for the Energy-Related Testing of Sustainable Conversion and Storage Technologies*

Energy Lab 2.0 [78] is a large-scale research infrastructure of the Helmholtz Association. Its mission is to develop technological solutions for a smart and integrated energy system for a defossilized future. Energy Lab 2.0 allows for technology-oriented research on a demonstration scale in order to successfully integrate renewable energy (RE) into the power grid.

In particular, all relevant components of a future energy system are considered, namely RE generation, storage and grid integration, and power-to-X conversion technologies (X = gas, liquid, heat)—all complemented with a comprehensive system analysis. At Karlsruhe Institute of Technology (KIT), the majority of the components have been set up. Moreover, certain components are located at the German Aerospace Center (DRL) in Stuttgart (Germany) and Forschungszentrum Jülich (Jülich, Germany), respectively (see Figure 12).

**Figure 12.** Energy Lab 2.0 at Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Photo: M. Breig and A. Bramsiepe (KIT).

For the Karlsruhe site, research at the Energy Lab 2.0 can be subdivided into three major areas: (1) the solar power storage park mainly focuses on short-term energy storage via different types of batteries, whereas the plant network (2) targets chemical energy carriers (power-to-molecules), and (3) the Smart Energy System Simulation and Control Center (SEnSSiCC) focuses on power hardware, the power grid, and consumers/prosumers both experimentally and via simulations. In order to investigate and demonstrate the coupling of the different components, plants are interconnected and can be operated within a smart grid design of interest (see Figure 13). Furthermore, power-to-heat is focused on at the DLR (Stuttgart, Germany), whereas major research is conducted on electrolysis at Forschungszentrum Jülich (Jülich, Germany).

3.4.1. The Solar Power Storage Park of the Energy Lab 2.0

A solar power storage park was built at KIT back in 2014. This storage park includes a 1 MWp photovoltaic (PV) system, as well as smaller storage systems. In addition, a 1.5 MWh Li-ion battery and an 800 kWh redox flow storage system were integrated into the park as part of the Energy Lab 2.0 project. Storage systems on a large scale will only be used when their deployment is economically-viable. Economic viability is not only influenced by the investment costs but also by the lifetime and design of the systems, the system control, and system design, including their overall efficiency. The impact and optimization potential of these aspects in terms of the economic viability of the systems are being investigated as part of various projects centered around the Energy Lab 2.0. Efficiency losses in such storage systems can occur, for instance, due to the high cooling and heating requirements. In order to reduce these losses, an innovative cooling concept was developed for the 1.5 MWh Li-ion battery, which was integrated into a concrete structure. The thermal

component activation of the concrete structure and the use of groundwater to control the temperature of the batteries by indirect water cooling ensure minimized system operating costs (through increased efficiency) and a long lifetime for the battery modules as a result of the enhanced temperature control. There also exists the potential to optimize redox flow batteries (RFBs) in terms of efficiency [79]. In addition, research on intelligent operating strategies is being conducted on RFBs and Li-ion batteries. In the majority of cases, the operator of a Li-ion storage system is provided with information on the state of charge. However, the actual state of charge and the battery's usable energy depend on the system's discharge capacity. A model that is capable of self-learning during operation is currently being developed and would be able to provide information on the state of energy of the entire storage system. Furthermore, one of the smaller storage systems is being operated to replicate a Li-ion storage system in a multifamily home and is virtually connected to a part (30 kWp) of the 1 MWp PV system.

**Figure 13.** Interacting components: power generation, transformation, and storage in the Energy Lab 2.0 plant network (power-to-X) coupled with energy systems analysis on the theoretical and experimental levels in the Energy Lab 2.0 Smart Energy System Simulation and Control Center. Solid lines—physically-implemented coupling in the Energy Lab 2.0; dashed lines—data and model exchange; blue lines—electricity; green lines—chemicals; red lines—heat; yellow lines—data and models.

Li-ion batteries are subject to particularly strong degradation if they are in a high state of charge for a long period of time. This can be reduced through an intelligent operating strategy [80,81]. PV and load forecasts are both vital components for arriving at such intelligent operating strategies. Currently research is being conducted to determine which type of PV forecasting methods are best suited for intelligent charging strategies [82].

#### 3.4.2. Power-to-Molecules in Decentralized and Highly Efficient Plants

In the future energy system, "power-to-molecules" technologies will be an important piece of the overall puzzle, not only as an option for chemically-storing electrical energy, but also as a source for CO2-neutral fuels and chemical feedstocks. Within the plant network of the Energy Lab 2.0, there is a focus on the synthesis of hydrocarbons—namely methane and Fischer–Tropsch-based fuels—from CO2 and H2. Although green hydrogen can be obtained through electrolysis, non-fossil CO2 must be captured from the air (direct

air capture—DAC), generated from biomass, or separated from unavoidable industrial point sources that cannot be decarbonized, for example, by electrification. At the Energy Lab 2.0, a PEM electrolysis unit (100 kWAC nominal power, operating pressure of up to 47 bar) and a high-temperature reversible steam electrolysis/fuel cell unit (electrolysis mode: 150 kWAC; fuel cell mode: H2: 25 kWAC, CH4: 20 kWAC) are used to investigate integration into certain process chains. Within the Kopernikus Project "P2X", funded by the German Federal Ministry of Education and Research, a high-temperature co-electrolysis system will be installed. In order to capture CO2 from ambient air, DAC is integrated into the plant network, for example, within the framework of the Power-Fuel project funded by the German Federal Ministry for Economic Affairs and Energy.

Predetermined by the local and temporal availability of both non-fossil CO2 and green electricity in a future defossilized energy system solely based on renewable energy, power-to-molecule process chains must be tolerant to input fluctuations (not only in terms of minutes but also on a day/season scale) and intensified, also allowing for decentralized application. Dynamic operation and process intensification are the major objectives investigated in the synthesis plants at the Energy Lab 2.0, namely the three-phase methanation [83] (output equivalent to 100 kW) and eFuel synthesis plants (1 bpd Fischer–Tropsch products).

While conventional plants for eFuel synthesis, for example, via the Fischer–Tropsch (FT) route, are designed for steady-state operation due to several hurdles such as hot-spot formation; in contrast, process intensification enables the reactor's volume and plant's complexity to be reduced [84]. This is why, in the eFuel synthesis plant (INERATEC GmbH) of the Energy Lab 2.0, a modular microchannel-based reactor is used. Projects utilizing the Energy Lab 2.0 s infrastructure investigate the benefits of process-intensified and modular equipment on the design of the process chain. For example, in the PowerFuel project, the required tank size for buffering the hydrogen produced from renewable sources was investigated. The results show that it is possible to drastically reduce the intermediate tank size due to the ability of the microchannel-based FT reactor and of the eFuel synthesis plant in general to operate under reduced feed within a response time of a few minutes [85].

In a study conducted at KIT, the eFuel synthesis plant of the Energy Lab 2.0 was simulated in AspenDynamics within the framework of the aforementioned PEM electrolyzer plant (160 kWAC overload situation), the 50 m<sup>3</sup> hydrogen tank (which corresponds to up to 2300 Nm<sup>3</sup> H2) and an assumed 320 kWp PV field with experimentally-determined power profile data of the solar power storage park (two weeks in the spring of 2015). The electrolyzer in this scenario was assumed to instantaneously follow the PV profile (with a 10 min temporal resolution). Only the ramp-up was capped in the model, as at least 40% of the nominal load was required to run the system experimentally. It was shown that the control strategy applied for the synthesis plant significantly influences the number of required shutdowns enforced by the unsteady supply of electrical energy and, thus, hydrogen in such a scenario. When running the synthesis plant under steady-state conditions, its operating time can be as low as 35% and 48% when applying constant H2 feed equivalent to 150 kWel or 115 kWel electrolyzer load, respectively. In contrast, when running the synthesis plant dynamically, depending on the hydrogen production rate or a desired tank pressure level (see Figure 14), the operating time can be significantly increased to 70% or even 83%, respectively.

For dynamic synthesis operation, it was also shown via experiments on a relevant lab scale (H2 feed equivalent to 500 Wel electrolyzer load) that the ability of micro-structured reactors to cope with feed fluctuations does not influence the product quality, nor does it induce complete hydrogen consumption in the FT reactor, which could harm the catalyst due to the presence of the remaining CO. This is affected by the possibility of effectively controlling the reactor temperature [86].

**Figure 14.** AspenDynamics results for hydrogen supply from the 50 m<sup>3</sup> hydrogen buffer tank and the pressure in the tank as a function of time with underlying PV data of two weeks in spring 2015. The scenario considers the dynamic operation of the electrolyzer and pressure-dependent control of the synthesis plant. Low pressure limit for running the synthesis plant: 25 bar.

#### 3.4.3. The Smart Energy System Simulation and Control Center

The necessary coupling of various energy sectors in future and the fluctuation in the generation of power from renewable energy sources present an enormous challenge regarding the control and operation of future energy systems. In order to perform control and monitoring tasks under the most realistic conditions possible, the Smart Energy System Simulation and Control Center (SEnSSiCC) [87] was established as part of the Energy Lab 2.0 project. The SEnSSiCC brings together work on information technologies and the corresponding research aspects of the Energy Lab 2.0 (see Figures 13 and 15).

The following sub-labs form the SEnSSiCC: the Smart Energy System Control Laboratory (SESCL), which acts as a representation of the real power grid of the future where the most important energy systems are flexibly interconnected through a busbar matrix, ensuring that experimental configurations can be quickly changed; the Energy Grids Simulation and Analysis Laboratory (EGSAL), where the topography of future energy grids is simulated with the virtual integration of components [88] that are not available at KIT's Campus Nord; the Energy Lab 2.0 s Control, Monitoring and Visualization Center (CMVC), where software tools are being developed for the control room of future energy grids [89]; and the power hardware-in-the-loop (PHiL) laboratory test environment, which enables real hardware components to be integrated into a simulated 1 MVA grid and subjected to stress tests, as in [90]. The SEnSSiCC is complemented by the Living Lab Energy Campus (LLEC, see the next chapter), also a research infrastructure of the Helmholtz Association. Three experimental buildings with identical constructions are connected to the SEnSSiCC in terms of electrical technology and data and thus expand the portfolio of energy technology systems used for experiments.

**Figure 15.** Smart Energy System Simulation and Control Center within the Energy Lab 2.0. Photo: M. Breig (KIT).

The Smart Energy System Control Laboratory focuses on the support of developments and innovations in the field of smart grids under realistic conditions. The SESCL is a laboratory in which state-of-the-art energy technology systems and new control algorithms are developed and tested [91]. This laboratory is galvanically isolated from the public grid, so that the control algorithms can be approved and investigated in limit ranges (frequency, voltage). In addition, it is possible to control operating points approaching the limits of stability. Such experiments would not be possible using the public grid, as the risk of a complete grid failure is too high. In order to conduct experiments on low-voltage networks under realistic conditions, the laboratory provides a number of energy systems, such as electricity generators (e.g., PV systems, wind power units), electrical machines, generators, inverters, storage systems (e.g., Li-ion batteries), and charging stations, that can be very flexibly interconnected by taking into account the physical properties of the connecting lines to form a micro-grid with a variable topology. To model the operating behavior of the cable/overhead lines, the laboratory features real means of transmission and line replicas that physically simulate this behavior using discrete resistor–inductor–capacitor (RLC) components. In terms of the interconnection, flexibility is ensured by a matrix of alternating and direct current busbars and contactors that are controlled by a centralized automation system. Load shedding and the addition of further producers and consumers, or a combination of the two (prosumers) can be achieved very easily.

### *3.5. Living Lab Energy Campus: Integrated Research Platform for Energy-Related Coupling of Pioneering Conversion, Distribution, and Storage Technologies*

The Living Lab Energy Campus (LLEC) project is an integrated research platform (see Figure 16) for the coupling of electrical, thermal, and chemical energy flows through an intelligent sensor and control system. Various production, distribution, and storage systems are integrated into the energy supply of the research campus and are then monitored and optimally controlled according to predefined constraints by an adaptive, cloud-based, and model-predictive IT platform. In addition, digital models have been developed for different energy grids, energy demonstrations, and various building types. The demonstrations include various photovoltaic systems, two large Li-ion batteries, a low-temperature waste heat network, and a hydrogen sector with a high level of sector coupling. A large number of sensors collect data via the fluctuating energy flows at the research site. A special significance is attached to achieving an optimal interaction between humans and technology.

**Figure 16.** Living Lab Energy Campus: living lab and research platform.

A thermal energy center (WVVZ) designed as a modular system supplies the campus with electrical energy and heat. To this end, gas mixtures comprised of natural gas with biogas and hydrogen are used in the installed gas engines. An additional low-temperature network uses waste heat from the JUWELS supercomputer to supply heat to the surrounding buildings by means of heat pumps and simultaneously investigate the electrical and thermal utilization of the network, as well as potential resource savings. Various photovoltaic systems form the basis of the renewable energy supply and are integrated into the energy system in the form of conventional rooftop installations, free-standing modules, and modules fixed to the building façade. The fluctuations in the energy feed that occur are offset by two large Li-ion batteries. At the same time, these batteries serve as an uninterruptible power supply for a selection of sensitive research infrastructures. The LLEC was recently expanded to encompass research issues surrounding vehicle-to-grid (V2G) systems. Various bidirectionally operable charging infrastructures for electric research vehicles are currently being established.

One system- and process-related focus of the LLEC is the long-term and seasonal storage of renewable energy using hydrogen from the MW electrolysis system. As is shown in Figure 1, hydrogen and oxygen from the water electrolysis process each flow through a pressure-resistant pipeline, with only the hydrogen flowing into a pressure tank as additional storage. The hydrogen can also be stored in LOHCs. The loading and unloading of the LOHC takes place in a novel one-reactor system, which for the first time, demonstrates both process steps in a system with a performance of 300 kWp. The level of heat required for hydrogenation is approximately 300 ◦C and is obtained from the waste gas of the gas engines. The heat that is generated during dehydrogenation is supplied to the heat supply system on campus. Significantly higher rates of storage efficiency are achieved through this type of sector coupling. All forms of storage enable the stockpiling of gases over many weeks and months before hydrogen can be used to generate electricity and heat in the WVVZ's gas engines, and hydrogen and oxygen are able to do the same in an alkaline fuel cell.

As they are incorporated in a climate-neutral office complex, all of the energy systems can be monitored in the Data and Energy Services Lab, where researchers are also able to plan and evaluate future energy system experiments together with their colleagues from the technical infrastructure department.


5.11 Partial weight bearing (PWB)

• The handgrips are attached sturdily and not move when pressure is applied.

• User should maintain good posture (hyper flexion of the head, neck and trunk

The following weight bearing status can be used with walkers: non-weight bearing (NWB), touch down weight bearing (TDWB), partial weight bearing (PWB), weight bearing as tolerated (WBT), full weight bearing (FWB).

The user first need to learn how to stand using the walker. The user uses one of the upper limb to hold the walker (for stability and balance) and the other upper limb to assist in standing (pushing on the seat). Clinicians can assist the user into standing position from sitting by assisting the user from the axilla region. Immediately the user is almost standing user change the position of the upper limb that was on the seat to the walker. User stands upright within the walker, adjusting the upper limb and lower limb till the user is balance. User will sit by following the opposite procedure of standing. User first make sure the lower limbs are touching the seat then use one upper limb to hold the seat and user gradually sit on the seat and

The user moves the walker forward to about an arm's length distance, with the weight of the body is on the unaffected/involved lower limb (i.e., weight bearing lower limb) and the affected lower limb is not touching the ground. Then the user put his/her weight on the walker using the upper limbs and moves the affected/ involved (i.e., NWB lower limb) forward towards the walker and finally moves the weight bearing lower limb towards the walker (to the same level as the NWB lower

The user moves the walker forward to an arm's length distance, with weight of the body is on unaffected lower limb and the affected lower limb foot or toes is touching the ground but not bearing weight. Then the user put the weight on the walker using the upper limbs and moves the affected/involved lower limb (i.e., TDWB lower limb) forward towards the walker (the foot or toes touching the ground but not bearing

• There should be no dents, cracks or any irregularities on the walker.

The following instructions should be given to the user before use:

• User should avoid moving too close to the front horizontal bars.

• User should avoid staying too far away from the walker.

remove the other upper limb to adjust the position on the chair.

• Users should not use walker for stair climbing.

5.8 Weight bearing status used with walkers

• No component should be found loosen in the walker.

5.7 Instruction on how to use a walker

should be avoided).

Prosthesis

5.9 Non-weight bearing (NWB)

limb). Then cycle is then repeated.

70

5.10 touch down weight bearing (TDWB)

The user moves the walker forward to an arm's length distance. Then the user put the weight on the walker using the upper limbs and moves the affected/ involved (i.e., PWB) lower limb forward towards the walker, bearing less than 50% of body weight on the PWB lower limb and finally moves the weight bearing lower limb towards the walker (to the same level as the PWB lower limb). The cycle is then repeated.


**1. Introduction**

As a leading gambling destination, in 2017, Macao attracted more than 30 million tourists and created the highest gambling revenue (33 billion US dollars) in the world [1]. The development of Macao's gambling industry is the result of its history, economic development, resource limitations and preferential policy [2]. Although these factors helped Macao to obtain a competitive advantage in gambling tourism, this typical small economy raises a problem—economic dependence on gambling restricts economic diversification. The gambling industry increases labor wages and provides good treatment, which results in its strong absorption of economic resources. However, faster growth of gambling industry leads to higher income inequality [3] which limits other industries' survival and development. Scholars contend that a low level of diversification or concentrated economy can dramatically react to external influences, such as changes in demand for one product [4,5] and a diversified regional economy is less responsive to fluctuations to extra-regional economic growth [6]. Since diversification can reduce a nation's economic volatility and increase its real activity performance, so having a diverse economy has long been thought to play a key role in a sustainable economy [5]. Therefore, both the Macao government [7–10] and scholars [11–14] have recognized the importance of economic diversification, which is the source of long-term economic growth [5,15,16]. Moderate diversification of the economic structure is a way to drive economic sustainability in Macao. Thus, it is critical to establish moderate economic diversification in Macao.

To establish a moderate economic structure, the Macao government is facilitating the development of other industries, such as Meetings, Incentives, Conferences and Exhibitions (MICE), Traditional Chinese Medicines (TCM), Cultural and Creative Industries (CCI) and featured financial services. The Macao government also announced its policy spindle for gambling industry development, "adjustment of the appropriate scale of gambling industry" [7,9]. Recently, some researchers have studied the sources of threats and challenges to Macao's economic development [11,17], the ways Macao's economy is developing and diversifying [11,13,14,17,18] and sustainable tourism development in Macao [12]. They supported the development of moderate economic diversification and agreed that by controlling the scale of the gambling industry, more resources could be unlocked and reallocated to non-gambling industries [19]. However, some academics advocate the advantages of cluster economies or agglomeration economies [20–22], which have the advantages of sharing common resources (i.e., technology and labor), lower unit costs and better innovations for increasing returns to scale and enhancing the growth opportunities of other industries and clusters [20–22]. In a recent study, Aratuo and Etienne [23] studied the relationship between economic growth and tourism-related industries in the US in 1998–2017. They found that tourism-related industries providing local offerings drive the performance of other industries. Although most of the research on agglomeration economies and cluster economies consider the agglomeration of manufacturing industries [24,25], the agglomeration of service industries may occur if they can benefit from the concentration of customers [25]. Therefore, Macao's gambling industry tends to concentrate in certain areas in Macao instead of being scattered across Macao. Considering the needs for supporting service industries such as banks and other financial intermediaries, restaurants, tourism and other business services, the agglomeration of casinos can derive similar benefits to the agglomeration of manufacturing industries, especially regarding the enhancement of the growth opportunities of other industries and clusters [22]. In other words, the agglomeration of casinos may lead to the growth of other industries and clusters. This implies that over-adjustment of the gambling industry may harm the development of moderate economic diversification in Macao. Thus, how to strike a balance between moderate economic diversification and further development of the gambling industry must be determined.

The concept of appropriate scale comes from the economies of scale. Appropriate extension or reduction of the production scale will make the distribution of production factors, like land, capital and labor, more reasonable and will achieve optimal management efficiency under existing conditions [26,27]. To adjust the scale of the gambling industry appropriately, we should know how to calculate this 'appropriate scale.' In general, if the scale of the gambling industry is higher than this 'appropriate scale,' it will limit the development of moderate economic diversification. Then, it causes the sustainable issue of non-gambling industries. On the other hand, if the scale of the gambling industry is lower than this 'appropriate scale,' it will also reduce its support of non-gambling industries to achieve a moderate and diversified economy. It causes the sustainable issue for both gambling and non-gambling industries. Therefore, our study relates the appropriate scale of the gambling industry not only in terms of the economic efficiency of this industry but also the overall economic diversification in Macao. This study helps to address the paradox between economic growth of the gambling industry and sustainable growth of non-gambling industries.

To contribute to a solution for sustainable economic development in Macao, this study aims to determine the appropriate scale of the gambling industry for optimal development of moderate economic diversification in Macao. Firstly, this study applies an entropy index of economic diversification [28] to measure the levels of diversification of Macao's economy from 2008–2016. Then, a Data Envelopment Analysis (DEA) [29–31] is used to measure the efficiency of the gambling industry. A transition probability matrix for three scenarios (rapid, stable and slow transitions) is developed based on expert interviews. To evaluate the appropriate scale, a Markov chain [32] is applied to forecast the future scale of the non-gambling industry and the gambling industry until 2021. The results of this study can be applied to other gambling destinations (such as Cambodia) that may soon face a similar sustainable economic problem of a concentration in the gambling industry and may want to promote industrial diversification. For sustainable economic growth caused by technological innovation and human capital accumulation, it is essential to transform and upgrade the industrial structure. This study also contributes to sustainability through the understanding of the transformation of the industrial structure and its relationship with sustainable economic growth.


**2. Literature review**

Sediment Rating Curve (SRC) is an empirical approach used by practitioners in the engineering studies of sediment and erosion problems. The log linear rating curve method has been used widely and Sivakumar and Wallender (2005) outline the many flaws associated with this technique, including the lack of fit due to missing variables (e.g. Miller, 1951), retransformation bias (e.g. Ferguson, 1986), and non-normality of the error distribution (e.g. Thomas, 1988). According to Sivakumar and Wallender (2005), the technique has been modified including, among others, use of separate curves for different seasons (Miller, 1951), stratifying the data according to the magnitude of flow and applying a separate curve for each stratum (Glysson, 1987), and use of a single multivariate model instead of multiple rating curves (Cohn *et al.*, 1992). Sivakumar and Wallender (2005) argue that there is not a simple (and universal) 'water discharge-suspended sediment concentration-suspended sediment load' relationship. A brief overview of past studies is as follows.

Kisi, et al (2008) review the application of ANN and neuro-fuzzy techniques to time series analysis of sediment loads at various timescales, uncertainty in the data. Variations of these techniques have also been reported by Jain (2001), Tayfur (2002), Cigizoglu (2004), Kisi (2004), Raghuwanshi *et al*. (2006), Cigizoglu & Kisi (2006). Other studies on the application of ANN to suspended sediment include that by Wang et al (2008), who applied ANN to derive the coefficients of regression analysis for their SRC model.

Aytek and Kishi (2008) used the GP approach to model suspended sediment for two stations on the Tongue River in Montana, USA, and indicate that the GP formulation performs quite well compared to sediment rating curves and multi linear regression models.

Chaotic signals have also been identified in time series of suspended sediment loads by Sivakumar and Jayawardena (2002, 2003), Farmer and Sidorowich, 1987). The outcomes revealed the usefulness of these methods towards an effective prediction capability.

Overall, a general understanding of the analysis of suspended sediment load is yet to emerge and one way to gain an insight into the problem is to carry out inter-comparison studies of the performance of a host of models applied to diversity of rivers of different shapes and sizes.


Mitochondrion is a strong candidate to mediate the relationship between exercise and the reduced risk of frailty and mental illness. It is our powerhouse, generating the chemical energy (ATP) necessary for cell survival. On the other hand, it is also responsible for the production of reactive oxidative species (ROS) related to inflammatory processes, aging, and several metabolic and mental diseases (19, 20). According to Radak (21–23), although exercise is associated with acute increases of ROS, chronic alterations related to adaptation to this kind of stimulus contribute to an increased antioxidant enzymes activity. Moreover, exercise promotes mitochondrial biogenesis and makes enzymes more efficient (oxidant and antioxidant), contributing to improved metabolism, function, and cell survival throughout the entire body (24, 25).

Metabolism and protein synthesis maintenance is another important exercise mechanism for promoting health. Inducing the production of trophic factors (such as BDNF, IGF-I, VEGF, GNF) and neurotransmitters (such as dopamine, serotonin, and norepinephrine) contributes to various brain responses, for instance, increased neurogenesis, angiogenesis, synaptogenesis, and inhibition of caspases (3–6, 26–29). Moreover, the increase of neurotropic factors induces presynaptic signals associated with increased release of neurotransmitters in the synaptic cleft and the resulting growth in synaptic transmission and neuroplasticity (30–34). BDNF also contributes to increased long-term potential (LTP) (35–37). During exercise, besides

activating motor circuit areas, associative and limbic areas also benefit from the increased synthesis and release of dopamine. Moreover, the activation of opioid and cannabinoid systems contributes to acute anxiolytic response to exercise (30–34, 38).

# **WHAT SHOULD WE DO? TYPE, FREQUENCY, DURATION, AND INTENSITY OF EXERCISE: IS MORE NECESSARILY BETTER?**

Although many neurobiological mechanisms justify the use of exercise in treating mental illness, it is uncertain how we may prescribe this "polypill." For example, we know that both aerobic and strength training contribute to improve cognitive function, especially the executive function (13– 15, 39), and to reduce depressive symptoms (4, 40, 41). It is also known that this improvement may occur through distinct or redundant neurobiological pathways, such as increased neurotrophins. However, there are currently no evidences indicating if certain exercises, e.g., stretching or swimming, would also be favorable. Moreover, it is known that aerobic exercise at moderate intensity (41, 42) contributes to reducing depression and increasing the rate of remission and response among elderly patients. However, it is unclear if these patients would benefit more from making high-intensity interval workouts. Studies indicate that patients with neurodegenerative diseases such as dementia benefit from aerobic exercises. Recently, our laboratory found that elderly people with Alzheimer's disease have better response to treatment when performing a 30-min walk on the treadmill at a moderate intensity (43). There is only one study submitting patients with AD to a strength training protocol, which found a favorable response in strength and functional capacity. However, the authors did not investigate clinical issues associated with the disease (44). Therefore, it is not possible to indicate this type of exercise for better response to AD treatment.

#### **CONCLUSION**

Although there are many neurobiological evidences indicating exercise programs to reduce symptoms and increase treatment response of several mental disorders, there is still a long way to go in clinical randomized control trials. Authors in this area need to make an effort to find evidences that may help to determine a more adequate prescription of exercise (type, duration, frequency, and intensity) for each diagnosis of mental illness.

#### **REFERENCES**

Available from: http://www.sciencedirect.com/ science/article/pii/S1084952111000887

as an augmentation treatment for Alzheimer's disease: a pilot randomized controlled study.*Arq Neuropsiquiatr* (2014) **72**:190–6. doi:10.1590/0004- 282X20130231

44. Hauer K, Schwenk M, Zieschang T, Essig M, Becker C, Oster P. Physical training improves motor performance in people with dementia: a randomized controlled trial. *J Am Geriatr Soc* (2012) **60**:8–15. doi:10.1111/j.1532-5415.2011.03778.x

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 15 May 2014; accepted: 23 May 2014; published online: 13 June 2014.*

*Citation: Deslandes AC (2014) Exercise and mental health: what did we learn in the last 20 years? Front. Psychiatry 5:66. doi: 10.3389/fpsyt.2014.00066*

*This article was submitted to Affective Disorders and Psychosomatic Research, a section of the journal Frontiers in Psychiatry.*

*Copyright © 2014 Deslandes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

# Trophic mechanisms for exercise-induced stress resilience: potential role of interactions between BDNF and galanin

# **Philip V. Holmes\***

Neuroscience Program, Psychology Department, Biomedical and Health Sciences Institute, The University of Georgia, Athens, GA, USA

#### **Edited by:**

Felipe Schuch, Hospital de Clínicas de Porto Alegre, Brazil

#### **Reviewed by:**

Tariq Munshi, Queen's University, Canada Meera Balasubramaniam, NYU Langone Medical Center, USA

#### **\*Correspondence:**

Philip V. Holmes, Neuroscience Program, Biomedical and Health Sciences Institute, Psychology Department, The University of Georgia, Athens, GA 30602, USA e-mail<EMAIL_ADDRESS>
Current concepts of the neurobiology of stress-related disorders, such as anxiety and depression emphasize disruptions in neural plasticity and neurotrophins.The potent trophic actions of exercise, therefore, represent not only an effective means for prevention and treatment of these disorders, they also afford the opportunity to employ exercise paradigms as a basic research tool to uncover the neurobiological mechanisms underlying these disorders. Novel approaches to studying stress-related disorders focus increasingly on trophic factor signaling in corticolimbic circuits that both mediate and regulate cognitive, behavioral, and physiological responses to deleterious stress. Recent evidence demonstrates that the neural plasticity supported by these trophic mechanisms is vital for establishing and maintaining resilience to stress. Therapeutic interventions that promote these mechanisms, be they pharmacological, behavioral, or environmental, may therefore prevent or reverse stress-related mental illness by enhancing resilience. The present paper will provide an overview of trophic mechanisms responsible for the enhancement of resilience by voluntary exercise with an emphasis on brain-derived neurotrophic factor, galanin, and interactions between these two trophic factors.

**Keywords: galanin, running, BDNF, resilience, psychological, anxiety, depression**

# **TROPHIC MECHANISMS FOR EXERCISE-INDUCED STRESS RESILIENCE: POTENTIAL ROLE OF INTERACTIONS BETWEEN BDNF AND GALANIN**

Clinical studies convincingly establish the efficacy of exercise in the treatment of anxiety and affective disorders (1–3). However, understanding the neurobiological mechanisms responsible for these beneficial effects, a goal that necessitates the application of rodent models, remains a challenge. Since deleterious stress lies at the core of anxiety and depression, understanding the neurobiological impacts of stress, and the mechanisms for adapting to it will significantly enhance the development of more effective prevention and treatment. Recent advances in exercise neuroscience using rodent models have shed new light on the neural mechanisms by which physical activity produces long-term adaptations in brain circuits implicated in anxiety and depressive disorders. This literature reveals that the most significant impact of exercise on stress may not pertain to regulating transient states occurring in the presence of the stressor, but rather on moderating the long-term impact that acute stress may incur on subsequent stress events. The key benefit of exercise may thus involve the promotion of stress resilience.

The present paper will focus on stress resilience as a fundamental phenomenon underlying the beneficial effects of exercise, and it will briefly review the neurotrophic hypothesis of stress resilience. Two trophic mechanisms that may be involved in the stress resilience will be examined; one involving the widely studied brain-derived neurotrophic factor (BDNF) system and another based on the lesser-known trophic actions of the peptide galanin. The purpose of this comparison will be to point out a critical area for future investigation, which should aim to uncover how

different trophic mechanisms may interact to promote optimal neural function.

# **EFFECTS OF EXERCISE IN RODENT MODELS OF DEPRESSION AND ANXIETY AND THEIR IMPLICATIONS FOR STRESS RESILIENCE**

Though exercise represents an effective intervention for stressrelated disorders in humans, evidence for its antidepressant and anxiolytic efficacy in rodent behavioral models is surprisingly inconclusive. In recent, comprehensive reviews of the anxiolytic and antidepressant effects of exercise in rodent models a common theme emerges, in which that exercise produces mixed and conflicting effects in standard rodent tests of anxiety and depression (4–6). Much of the conflicting evidence derives from the species or strain used as subjects, duration, and mode of exercise employed as the independent variable, and the selection of model that serves as the dependent measure of depressive- or anxiety-like behavior. Experiments employing forced modes of exercise, such as treadmill or swimming, introduce the confounding factor of stressor exposure on subsequent measures of stress-related behavior and are thus difficult to interpret. Furthermore, rodent paradigms that putatively model depressive-like behavior are plagued by questions of validity, and the most widely employed "models," such as the forced swim or tail suspension tests, are better characterized as bioassays or screens for pharmacological manipulations with potential antidepressant activity (7). A particularly problematic aspect of these models is that they are too often assumed to represent the chronic, self-perpetuating nature of major depression by assessing a "snapshot" of spontaneous responsiveness to an acute stressor when no predisposing factors have been manipulated. They also assume that antidepressant actions may be observed in a healthy subject. It is with these caveats in mind that one must cautiously interpret the reports that exercise may exert either antidepressant-like, "pro-depressive," or no effects in the forced swim or similar tests (5, 8, 9).

Similar problems of interpretation arise when critically examining exercise effects in anxiety models. When such models are applied as a single measure of spontaneous behavior in the presence of the mild stress associated with standard tests, it is difficult to ascertain whether increased responding reflects behavior reminiscent of anxiety or, rather, adaptive coping to the exigencies of the stressor. Both interpretations have been proposed in previous studies, and exercise has been variously characterized that has anxiogenic, anxiolytic, or without effect (4–6). This range of contradictory results is evident even when focusing on a single model, the elevated plus-maze. After systematically reviewing this literature, we have proposed that understanding the effects of exercise hinge upon examination of the longitudinal impact of stress exposure on subsequent responding (6). We have thus shown that the anxiolytic-like effects of exercise are only consistently observed in standard models of anxiety when rats have been previously exposed to a different type of stressor. Exercise, thus appears to promote resilience to stress.

#### **TROPHIC MECHANISMS IN STRESS RESILIENCE**

Emerging concepts of the neurobiology of stress-related disorders, such as anxiety and depression emphasize disruptions in neural plasticity and trophic mechanisms (10, 11). Current research on the neurobiology of stress, thus, increasingly involves measures of neurogenesis, dendritic arborization, dendritic spine maintenance, synaptogenesis, and other forms of plasticity. This new perspective on the neurobiological basis of anxiety and depressive disorders is superseding traditional explanations that emphasize dysfunction in monoaminergic transmission as the primary etiological mechanism. The focus is thus shifting to the role of disruptions in trophic factor signaling, especially in corticolimbic circuits that mediate and/or regulate cognitive, behavioral, and physiological responses to stress. Recent evidence demonstrates that the neural plasticity supported by these trophic mechanisms is vital for establishing and maintaining stress resilience (12, 13). Stress-induced atrophy of the hippocampus has been linked to decreased resilience in clinical populations and rodent models (11, 14–16). Maintenance of plasticity in the medial prefrontal cortex (mPFC) also plays a crucial role in stress resilience, and disturbances in this plasticity are linked to the pathophysiology of depression and anxiety (17–21). The translational value of this new perspective on trophic mechanisms will be the identification and development of therapeutic interventions that enhance resiliencepromoting plasticity, be they pharmacological, behavioral, or environmental.

# **ROLE OF EXERCISE-INDUCED REGULATION OF HIPPOCAMPAL BDNF IN ANXIETY AND DEPRESSION**

The prominence of trophic mechanisms in determining the pathophysiology of anxiety and depression compels further examination of the profound influence exercise exerts on trophic factor expression. Much work already has demonstrated the capacity for exercise to induce a variety of trophic factors in the brain and periphery, such as BDNF, insulin-like growth factor (IGF-1), vascular endothelial growth factor (VEGF), and the inflammatory protein VGF (11), but most of this previous research has focused on BDNF signaling in the hippocampus (11, 22–24).

Brain-derived neurotrophic factor is a member of the neurotrophin family, a group of structurally related peptide growth factors that signal through TrkB receptors (22). BDNF is directly implicated in various forms of hippocampal plasticity induced by exercise (25, 26), leading many researchers to hypothesize that this action may mediate antidepressant and anxiolytic effects of exercise (11, 15, 23). This hypothesis is supported by numerous findings of relationships between exercise, BDNF, hippocampal plasticity, and antidepressant actions. For example, exercise consistently elevates BDNF expression in the hippocampus (23, 27, 28) and potentiates the antidepressant activity of antidepressant drugs in the forced swim test [(9); though c.f. (8)]. Antidepressant effects of exercise in mice are eliminated by BDNF knockout and inhibition of MAPK signaling, an intracellular mediator of BDNF (29). Exercise also reliably enhances hippocampal neurogenesis (30). This evidence has provided the foundation for the hypothesis that the beneficial effects of exercise are mediated specifically by BDNF-induced neurogenesis in the hippocampus. This hypothesis is an extension, what is generally referred to as the "neurogenesis hypothesis of affective disorders." Some reports from the exercise literature support this hypothesis (11, 25), though systematic reviews of studies linking hippocampal BDNF to antidepressant actions in humans and rodent models found many disassociations between BDNF and depression (31, 32). With respect to neurogenesis specifically, exercise-induced hippocampal neurogenesis is associated with increased spontaneous anxiety-like behavior, an effect that is reversed after irradiation, which effectively eliminates neurogenesis (33, 34). As described above, the discrepancies in the literature may relate to whether the behavioral paradigm measures acute stress reactivity or the longitudinal impact of stress (i.e., resilience). They may also depend on the nature of trophic factor-mediated plasticity in the hippocampus. In addition to its neurogenic effects, exercise induces other forms of plasticity in hippocampal neurons, such as alterations in dendritic spine architecture (23), which must be considered in accounting for antidepressant or anxiolytic effects.

The studies presented above establish links between exercise, BDNF, and antidepressant actions. However, whether BDNFdependent actions of exercise in the hippocampus reflect antidepressant effects *per se* or some underlying process such as stress resilience is not clear. Hippocampal administration of BDNF does not reverse the exaggerated stress response exhibited by rats previously exposed to uncontrollable stress, and a pharmacological manipulation that reduces hippocampal BDNF does not exacerbate the effects of stress on subsequent stress responses (35). These findings suggest that BDNF signaling in the hippocampus does not have a generalized influence on stress resilience.

## **POTENTIAL ROLE OF EXERCISE-INDUCED REGULATION OF LOCUS COERULEUS GALANIN IN STRESS RESILIENCE**

As discussed above, exercise increases the expression of a wide range of trophic factors throughout the brain. A fuller understanding of how trophic mechanisms are involved in the beneficial effects of exercise on stress-related behaviors, therefore, requires expanding the scope beyond BDNF in the hippocampus and examining other trophic systems. Galanin is a neuromodulatory peptide and trophic factor that exerts multiple effects through its interaction with specific G protein-coupled receptor subtypes designated GalR1, GalR2, and GalR3 (36, 37). Both galanin and its receptors are widely distributed in several brain systems, and galanin signaling thus impacts a variety of cognitive, behavioral, and endocrine functions. Some of the highest concentrations of galanin are found in the locus coeruleus (LC), where galanin is colocalized in over 80% of noradrenergic neurons (38). Galanin-containing LC neurons extensively innervate the mPFC, where galanin-immunoreactive terminals and GalR2 receptors are present in relatively high densities (39–41).

Research from my laboratory has repeatedly shown that 3 weeks of voluntary exercise elevates galanin gene expression in the LC in a running distance-dependent fashion (42–44). We have also shown that exercise exerts antidepressant effects in chronic models of depression (45), and chronic antidepressant treatment elevates galanin mRNA in the LC similarly to exercise (46). This evidence raises the obvious question of whether galanin exerts antidepressant and/or anxiolytic effects. Reviews of the extensive literature on the effects of galanin on anxiety- and depression-related behaviors show that galanin's effects on these behaviors, like those of exercise, are mixed and conflicting (47). Most of these previous experiments involved acute, central administration of galanin receptor ligands with subsequent tests of spontaneous behavior in standard models. With regard to galanin/GalR1/GalR2 transgenic mice, the findings are even more conflicting with predominantly negative findings in most standard anxiety and depression models (47).

Despite these confusing results, the behavioral evidence is clearer in experiments that examined galanin's influence on the longitudinal impact of stress. For example Lu et al. (48) reported no effect of GalR2 knockout on spontaneous behaviors such as elevated plus-maze, light/dark transition, forced swim, or tail suspension tests. However, GalR2 knock-out mice exhibited increased susceptibility to the repeated stress employed in a "learned helplessness"-like paradigm compared to wild type mice. Unlike the other tests, "learned helplessness" paradigms examine the impact of uncontrollable stress exposure on subsequent responding to repeated stressors. Loss of GalR2 led to a susceptible phenotype in this paradigm, suggesting that galanin signaling through GalR2 is necessary for resilience. Further supporting a specific role for GalR2 in resilience, transgenic overexpression of GalR2 in several frontocortical areas, including mPFC, was found to decrease immobility in a version of the forced swim test that involved pre-exposure to swim stress on the previous day (49). In contrast, GalR2 overexpression had no effect on elevated plus-maze or novel open field exploration in mice not previously exposed to stress. The behavioral literature thus points to functions for galanin beyond neuromodulatory effects. Galanin and GalR2 in particular, are evidently involved in protecting against the lasting consequences of an acute stress event by diminishing reactivity to subsequent stressors rather than by modulating reactivity to the acute stress event itself. This long-term protection suggests a role for galanin in the plasticity underlying resilience.

Galanin is well positioned as a trophic factor expressed in high concentrations in the LC to modify neural architecture in stress-responsive targets such as the mPFC. As described above, maintenance of dendritic spines in the mPFC may provide a cellular mechanism for resilience. Recent studies of galanin have revealed specific actions on neurite dynamics mediated by activation of GalR2 (50, 51). GalR2-mediated activation of Gq/11 influences multiple downstream targets, which includes inhibition of the RhoA GTPase. Galanin thus promotes neurite formation in neuronal cultures through a pathway involving GalR2-mediated inhibition of RhoA-ROCK signaling through LIMK, with subsequent activation of the actin-binding protein cofilin (51). Stress is associated with excess activation of RhoA, which leads to a reduction in spine densities (52). GalR2-mediated inhibition of RhoA-ROCK signaling thus provides a hypothetical mechanism for galanin-mediated protection against stress-induced spine atrophy. GalR2-signaling may also stabilize neurites via maintenance of microtubule integrity by promoting aggregation of microtubuleassociated protein 2 (MAP2) and β-tubulin (53), a process that may also involve inhibition of RhoA (54). These actions of galanin represent candidate mechanisms for protection against dendritic spine atrophy induced by stress.

# **POTENTIAL INTERACTIONS BETWEEN BDNF AND GALANIN IN OPTIMIZING NEURONAL FUNCTION**

Though BDNF and galanin share common neurotrophic functions, focusing on how the systems interact provides a new approach to understanding neural plasticity. Intracellular signaling of BDNF and galanin converges in many pathways, but their mutual influence on MAP2 may reflect complementary mechanisms to promote spine maintenance during the physiological challenges imposed by stress at the cellular level. TrkB-mediated BDNF signaling promotes the expression of MAP2 and microtubule assembly (54), whereas GalR2-signaling may be more involved in maintaining microtubule assemblies by inhibiting MAP2 phosphorylation, as described above. The two trophic systems may thus mutually maintain microtubule integrity, but through distinct mechanisms. Conversely, BDNF and galanin signaling pathways diverge in the area of coflin activation. Binding of BDNF to TrkB activates a LIMK through a RAC1 pathway, which ultimately leads to the inactivation of cofilin (54). That GalR2 signaling leads to the activation of cofilin through inhibition of LIMK suggests that BDNF and galanin may exert counterregulatory influences in their mutual function to promote spine maintenance.

Counter–regulatory interactions between galanin and BDNF are also evident at the systems level. Left unchecked, exerciseinduced elevations in BDNF may lead to state of neuronal hyperexcitability (22). Exercise induces a long-term enhancement of glutamatergic activity through upregulation of NMDA receptors (30). Additionally, enhanced transmission through AMPA receptors promotes Ca++-mediated BDNF release and signaling through TrkB (11, 54). The resulting BDNF-mediated effects on synaptic plasticity may further enhance excitatory glutamatergic transmission. This positive feedback loop between BDNF and glutamatergic activities accounts for the increased seizure vulnerability and excitotoxicity seen following experimental manipulations that enhance BDNF function, particularly in the hippocampus (55–57). This potential state of hyperexcitability following BDNF upregulation may also account for the finding of increased vulnerability to kainic acid-induced excitotoxicity following direct injection into the hippocampus of anesthetized rats that had undergone several weeks of exercise (58). In contrast to this finding in anesthetized rats, we have shown decreased vulnerability to kainic acid-induced seizures in awake, freely behaving rats (59). The galanin receptor antagonist M40 blocked this exerciseinduced protection against seizures. Taken together, the evidence suggests that under normal physiological conditions, the potential state of hippocampal hyperexcitability induced by elevated BDNF may be regulated by the galanin system. The anticonvulsant and neuroprotective properties of both endogenous and exogenous galanin are well established (50, 60, 61). The dense innervation of the hippocampus by galaninergic projections originating from the LC (62), the presence of galanin receptors in this structure (63), and the increase in galanin with exercise (42–44), all point to this system as a regulatory mechanism controlling the deleterious consequences of exercise-induced upregulation of BDNF.

#### **CONCLUSION**

The trophic influences of exercise, which are mediated by a wide range of neural and humoral factors, are well known. This body of knowledge fits well with new concepts of anxiety and depression as they relate to disturbances in neuroplasticity, and it reveals a compelling neurobiological mechanism that explains the beneficial effects of exercise on stress-related disorders. The literature from rodent models suggests that the primary benefit of exercise may be the promotion of resilience to stress. The translational value of this hypothesis may be realized through the promotion of exercise as a means to mitigate the longitudinal and cumulative impact of the repeated stressors. Exercise may thus afford both preventative and therapeutic benefits. Given the array of neurotrophins influenced by exercise, the next challenge for future research will be to examine how these varied mechanisms coordinate to optimize neuronal health. The interactions between BDNF and galanin represent an informative example of how trophic mechanisms that mutually promote the maintenance and survival of neurons may require reciprocal regulatory influences to achieve their ultimate benefit.

#### **REFERENCES**

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 21 May 2014; accepted: 14 July 2014; published online: 28 July 2014.*

*Citation: Holmes PV (2014) Trophic mechanisms for exercise-induced stress resilience: potential role of interactions between BDNF and galanin. Front. Psychiatry 5:90. doi: 10.3389/fpsyt.2014.00090*

*This article was submitted to Affective Disorders and Psychosomatic Research, a section of the journal Frontiers in Psychiatry.*

*Copyright © 2014 Holmes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*


*Article* **Optimized APF-ACO Algorithm for Ship Collision Avoidance and Path Planning**

**Mingze Li, Bing Li, Zhigang Qi \*, Jiashuai Li and Jiawei Wu**

College of Intelligent Science and Engineering, Harbin Engineering University, Harbin 150001, China<EMAIL_ADDRESS>(M.L<EMAIL_ADDRESS>(B.L<EMAIL_ADDRESS>(J.L<EMAIL_ADDRESS>(J.W.)

**\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** The primary objective of this study is to investigate maritime collision avoidance and trajectory planning in the presence of dynamic and static obstacles during navigation. Adhering to safety regulations is crucial when executing ship collision avoidance tasks. To address this issue, we propose an optimized APF-ACO algorithm for collision avoidance and path planning. First, a ship collision avoidance constraint model is constructed based on COLREGs to enhance the safety and applicability of the algorithm. Then, by introducing factors such as velocity, position, and shape parameters, the traditional APF method is optimized, creating a dynamic APF gradient for collision avoidance decision making in the face of dynamic obstacles. Furthermore, the optimized APF method is integrated with the ant colony optimization algorithm, the latter modified to overcome the inherent local optimality issues in the APF method. Ultimately, validations are conducted in three areas: static avoidance and planning in restricted sea areas, avoidance under conditions of mixed static and dynamic obstacles, and avoidance in situations of multiple ship encounters. These serve to illustrate the feasibility and efficacy of the proposed algorithm in achieving dynamic ship collision avoidance while simultaneously completing path-planning tasks.

**Keywords:** path planning; collision avoidance; the optimal APF; ACO


**1. Introduction**

Fly ash is a waste material that settles in electrostatic precipitators as a residual after the combustion of coal dust in the furnaces of a power plant or thermal power plant. Fly ashes vary in chemical and phase composition. The best-known fly ashes are those with a high silica or calcium content. In this paper, the latter will be presented. Fly ash from the Bełchatów mine is ash with a high calcium oxide content. This material is a by-product of lignite coal combustion. This ash can come from conventional furnaces or be generated by dry flue gas desulfurization (from conventional or fluidized bed furnaces). The concentration of reactive calcium oxide required as a pozzolan and hydraulic component in the whole mixture is more than 10% for lignite fly ash [1–3]. According to EN 197-1 [4], only the fly ash from boiler furnaces can be used. However, EN 206 [5] states that lignite fly ash cannot be used as a Type II active additive.

In Poland, lignite fly ash is a by-product of combustion mainly in the boilers of the Bełchatów Power Plant and Combined Heat and Power Plant, as well as P ˛atnów, Adamowa and Konin (the PAK region). Table 1 shows the chemical composition of the lignite fly ash from the Bełchatów Power Plant and, for comparison, Table 2 shows the coal fly ash from the Skawina Power Plant. Tables 3 and 4 show the phase composition of the fly ash from the Bełchatów Power Plant and, for comparison, the phase composition of fly ash from hard coal. The data presented in Tables 1–4 highlight the great diversity in domestic

**Citation:** B ˛ak, A.; Bazan, P.; Pławecka, K.; Łach, M. Geopolymers Based on Fly Ash from the Bełchatów Power Plant. *Mater. Proc.* **2023**, *13*, 17. https://doi.org/10.3390/ materproc2023013017

Academic Editors: Katarzyna Mróz, Tomasz Tracz, Tomasz Zdeb and Izabela Hager

Published: 14 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

fly ashes. The fly ash from the Bełchatów Power Plant has the characteristic of calcium aluminosilicates and is characterized by a high content of silicon, aluminum and calcium oxide and a small amount of other oxides [6,7].

**Table 1.** Oxide composition of the Belchatów lignite fly ash.

**Table 2.** Oxide composition of the Skawina charcoal fly ash.

\*\*\* **F.A. Skawina**—Fly ash from Skawina.

**Table 3.** Phase composition of the Belchatów lignite fly ash.

**Table 4.** Phase composition of the Skawina charcoal fly ash.

Fly ash from Bełchatów lignite is characterized by a more complex mineral composition compared to fly ash from Skawina coal. As shown in Tables 3 and 4, this observation applies to both the glass phase and minerals. The main minerals in lignite fly ash are quartz, gelenite, anorthite, anhydrite and calcium oxide. Typical cement clinker phases, i.e., C12A7, C3A and C4A3S, have also been identified [ ˆ 6]. These phases determine the hydraulic properties of fly ash. The pozzolanic and hydraulic properties of lignite fly ash are also related to the concentration of the amorphous phase. In the case of lignite fly ash, aluminosilicate glass is identified as the amorphous phase [8]. Fly ash from lignite Bełchatów is

characterized by a relatively high variability in chemical and phase composition. This is also true for other characteristics that affect their functional properties [9].

The purpose of this paper is to study lignite fly ash from the Bełchatów Power Plant and Combined Heat and Power Plant as a replacement for hard coal fly ash from the Skawina Power Plant and Combined Heat and Power Plant. In this paper, the base material was tested and then specimens were made for bending and compression tests, so the mechanical strength of the finished structural material was shown. For the alkaline activation of the raw material, the same activator with different molar concentrations of 10 and 14 M NaOH was used.