answer:The police intervened and dispersed the gathering of people who were demonstrating for a particular cause or against a decision.

answer:Here are some other headline options using Ruby programming language: 1. "Mark Zuckerberg's 10 million donation: A game-changer in the fight against climate change?" 2. "Breaking News: Zuckerberg's 10 million donation to climate change research" 3. "Zuckerberg's 10 million donation: A drop in the bucket or a significant step towards a greener future?" 4. "From Facebook to climate change: Zuckerberg's 10 million donation makes headlines" 5. "Zuckerberg joins the fight against climate change with a 10 million donation"

answer:1. Improves flexibility: Yoga involves a series of stretches and poses that help to increase the flexibility of your muscles and joints. This improved flexibility can help to reduce the risk of injury, increase range of motion, and improve overall mobility. 2. Strengthens muscles: Many yoga poses require you to hold your body weight in certain positions, which can help to build strength in your muscles. This improved muscle strength can help to improve posture, increase metabolism, and reduce the risk of chronic conditions such as arthritis. 3. Boosts cardiovascular health: Many yoga practices involve flowing movements and deep breathing, which can help to improve cardiovascular health. Regular practice of yoga can help to reduce blood pressure, lower cholesterol levels, and improve overall heart health.

answer:Here is a possible C++ program that solves the problem: ```c++ #include <iostream> using namespace std; int main() { // Define constants const int RESIDENTIAL_ENERGY = 20; const int COMMERCIAL_ENERGY = 30; const int TOTAL_ENERGY = 100; const int SOLAR_ENERGY = 10; const int WIND_ENERGY = 20; const int HOURS_PER_DAY = 8; // Define variables int solar_hours = 0; int wind_hours = 0; int non_renewable_energy = 0; // Calculate energy demand per hour for each building type double residential_demand = static_cast<double>(RESIDENTIAL_ENERGY) / (HOURS_PER_DAY * 2); // divided by 2 because there are two building types double commercial_demand = static_cast<double>(COMMERCIAL_ENERGY) / (HOURS_PER_DAY * 2); // Calculate energy production per hour for each renewable source double solar_production = static_cast<double>(SOLAR_ENERGY); double wind_production = static_cast<double>(WIND_ENERGY); // Calculate the maximum renewable energy that can be produced per day double max_renewable_energy = (solar_production + wind_production) * HOURS_PER_DAY; // Calculate the minimum non-renewable energy that must be used per day double min_non_renewable_energy = TOTAL_ENERGY - max_renewable_energy; // Check if the renewable sources can meet the energy demand if (max_renewable_energy >= TOTAL_ENERGY) { solar_hours = WIND_ENERGY >= RESIDENTIAL_ENERGY ? HOURS_PER_DAY : 0; wind_hours = HOURS_PER_DAY - solar_hours; } else { // Calculate the optimal distribution of renewable energy sources double solar_potential = solar_production * HOURS_PER_DAY; double wind_potential = wind_production * HOURS_PER_DAY; if (solar_potential >= residential_demand && wind_potential >= commercial_demand) { // Use solar for residential and wind for commercial solar_hours = ceil(residential_demand / solar_production); wind_hours = ceil(commercial_demand / wind_production); } else if (wind_potential >= residential_demand && solar_potential >= commercial_demand) { // Use wind for residential and solar for commercial wind_hours = ceil(residential_demand / wind_production); solar_hours = ceil(commercial_demand / solar_production); } else { // Use non-renewable energy sources non_renewable_energy = min_non_renewable_energy; } } // Print the results cout << "Solar hours: " << solar_hours << endl; cout << "Wind hours: " << wind_hours << endl; cout << "Non-renewable energy: " << non_renewable_energy << endl; return 0; } ``` The program first defines the constants and variables needed for the problem. It then calculates the energy demand per hour for each building type, the energy production per hour for each renewable source, and the maximum renewable energy that can be produced per day. It also calculates the minimum non-renewable energy that must be used per day. The program then checks if the renewable sources can meet the energy demand. If so, it calculates the optimal distribution of renewable energy sources based on the energy demand of each building type and the energy production of each renewable source. If not, it uses non-renewable energy sources to meet the remaining energy demand. Finally, the program prints the results, which include the number of hours that each renewable source should be used and the amount of non-renewable energy that must be used. Note that the program assumes that the renewable sources are available continuously for 8 hours per day, which may not be the case in reality. Therefore, sensor data and analytics should be used to adjust the program accordingly.