The share of American households owning at least one firearm has remained relatively steady since 1972, hovering between ** percent and ** percent. In 2024, about ** percent of U.S. households had at least one gun in their possession. Additional information on firearms in the United States Firearms command a higher degree of cultural significance in the United States than any other country in the world. Since the inclusion of the right to bear arms in the Second Amendment to the Constitution of the United States, firearms have held symbolic power beyond their already obvious material power. Despite many Americans being proud gun-owners, a large movement exists within the country in opposition to the freedom afforded to those in possession of these potentially deadly weapons. Those opposed to current gun regulation have sourced their anger from the large number of deaths due to firearms in the country, as well as the high frequency of gun violence apparent in comparison to other developed countries. Furthermore, the United States has fallen victim to a number of mass shootings in the last two decades, most of which have raised questions over the ease at which a person can obtain a firearm. Although this movement holds a significant position in the public political discourse of the United States, meaningful change regarding the legislation dictating the ownership of firearms has not occurred. Critics have pointed to the influence possessed by the National Rifle Association through their lobbying of public officials. The National Rifle Association also lobbies for the interests of firearm manufacturing in the United States, which has continued to rise since a fall in the early 2000s.

This survey focuses on gun control. Issues addressed include governmental involvement in gun control, the Second Amendment to the Constitution, concealed weapon laws, production of firearms, waiting periods for purchasing weapons, restrictions on purchasing guns, support for the NRA, the Bureau of Alcohol, Tobacco, and Firearms, and personal use and knowledge of guns. Demographic data include marital status, religion, employment status, household composition, age, sex, education, race, income , party affiliation, and political ideology.

Eutrophication of aquatic ecosystems is a serious global issue. Stream nitrate concentrations at the University of Tokyo Chichibu Forest have increased since 2000 after the opening of the new highway in 1998. Nitrogen oxide emissions from automobile exhausts were the most likely source of increased nitrate input in the forest ecosystem. Around the area, the sika deer Cervus nippon Temminck population has greatly increased since around 2000 and intensively browsed the understory vegetation. We hypothesized that the degradation of the understory vegetation caused by the deer overpopulation was one of the causes of increased nitrate output. Monthly observations were carried out from April to October 2013 to investigate the understory vegetation at the heights of 0–30 and 100–150 cm above the ground inside (without deer) and outside (with deer) of a deer exclusion fence. Plant taxa and % coverage of each taxon at each layer were recorded. The in vivo nitrate reductase activity (NRA) (≈ nitrate assimilation rate) was determined for each plant taxa each month. Compared to inside the fence, the understory vegetation outside was poor with smaller % coverage and less diverse community structure, and was occupied by unpalatable plant taxa that were uncommon or absent inside the fence. Contrary to our expectation, the phylogenetic diversity of the community assemblage outside the fence showed greater evenness (less clustering) than inside. The NRA peaked in early in the season or late in the season. In contrast to a previous report, no significant difference in the NRA was found between woody and herbaceous plants. Although the difference was no more than that of vegetation coverage, the estimated community-level NRA inside the fence was 5.6 times higher than that of the outside. The difference was greatest early in the season. These results support our hypothesis.

The fishing, hunting, and trapping market exhibits significant potential, with a market size of $669.15 million in 2025. While the provided CAGR is missing, a reasonable estimate, considering the growth in outdoor recreation and related activities, could be placed between 3% and 5% annually. This translates to substantial market expansion over the forecast period (2025-2033). Key drivers include increasing participation in outdoor activities, particularly among younger demographics seeking nature-based experiences. Furthermore, rising disposable incomes and improved access to gear through online retailers contribute to market growth. However, factors such as environmental regulations, conservation concerns, and the increasing cost of licenses and permits act as restraints on market expansion. The market is segmented by activity type (fishing, hunting, trapping), equipment type (rods, reels, firearms, traps), and consumer demographics (age, location, income). Major players like Legacy Anglers, Keep America Fishing Organization, NASGW, and the NRA play key roles in shaping market trends through advocacy, education, and product development. The long-term outlook for this market remains positive, driven by the enduring appeal of outdoor pursuits and innovative product offerings. The continued growth trajectory of the fishing, hunting, and trapping market is fueled by several factors. Firstly, a growing awareness of the physical and mental health benefits associated with outdoor recreation contributes to increased participation. Secondly, technological advancements in equipment, including more sustainable and eco-friendly options, are attracting a wider range of consumers. Thirdly, the influence of social media and online communities focused on these activities plays a critical role in driving demand. However, managing potential risks, such as habitat degradation and the ethical sourcing of equipment, is essential for the sustainable growth of the market. Regional variations in market penetration will also influence the overall market dynamics, with regions possessing abundant natural resources and established outdoor recreation infrastructure exhibiting greater growth potential. Future market analysis should focus on the impact of climate change, potential changes in regulations, and the integration of technology to better understand the evolving landscape of this dynamic industry.

Models and dataset needed to reproduce the case studies for the manuscript Constraint-based metabolic control analysis for rational strain engineering by S. Tsouka et al.

The code and software requirements to run simulations explained and available at: https://github.com/EPFL-LCSB/NRA and https://gitlab.com/realLCSB/nra

Models:

• Consistently reduced stoichiometric model of E. coli metabolism in the SBML format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): reducedD1Model_FBA.xml
• Thermodynamically curated model of E.coli metabolism in MATLAB's mat format (from Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations by Hameri et al. - https://doi.org/10.1016/j.ymben.2018.10.005): D1_FDP1.mat

Datasets:

• Files containing various data and options used in the generation of control coefficients (dataInfo.mat, metSampDataD1_FDP1.mat)
• Files containing statistics for the previously generated population of 50'000 sets of flux and concentration control coefficients (raw data provided below as Supplementary datasets): CpaggDATA.mat (flux CCs), and CxaggDATA.mat (concentration CCs)
• Files containing the reference and 18 extreme sets of flux and concentration CCs used in the present study: CCforNRA_RXN_GLCptspp.mat (chosen through Principal Component Analysis (PCA) based on the GLCptspp parameter) and CCforNRA_RXN_PYRtex.mat (chosen through PCA based on the PYRtex parameter)
• Supplementary datasets 1-5, 50 files each containing 1000 sets of flux and concentration CCs, named as DataD1_FDP1xx.mat where xx ranges from 1-50. The files are available as:
  • Supplementary dataset 1: http://doi.org/10.5281/zenodo.4500807
  • Supplementary dataset 2: http://doi.org/10.5281/zenodo.4500874
  • Supplementary dataset 3: http://doi.org/10.5281/zenodo.4500971
  • Supplementary dataset 4: http://doi.org/10.5281/zenodo.4501050
  • Supplementary dataset 5: http://doi.org/10.5281/zenodo.4501147

In 2022, around 13.4 million firearms were manufactured in the United States. While this number has generally increased from 1986, there was a significant spike in firearm production in the years following 2019. Firearm business in the U.S. The number of firearms the United States imports greatly exceeds the number of firearms the United States exports. The United States exports the most firearms to Saudi Arabia, as a result of the 2017 United States- Saudi Arabia arms deal, where Saudi Arabia agreed to purchase arms immediately from the U.S. totaling about 110 billion U.S. dollars, and purchasing a further 350 billion U.S. dollars worth of arms over the following ten years. Firearm ownership in the states The United States is the leading country in gun ownership. Wyoming was home to the highest rate of firearm ownership in the country, despite its low population. This can be attributed to Wyoming’s relaxed gun control laws, which allows residents over the age of 21 to possess a gun without a state permit, and they may carry a weapon openly or concealed without a license. Furthermore, even though Mississippi had one of the lowest rates of firearm ownership, it had the highest mortality rate due to firearms. Mississippi also has relaxed gun laws, which allows people to carry a concealed firearm without a license or permit.

Observations of plant species at Crater Lake NP, Lassen Volcanic NP, Lava Beds NM, Oregon Caves NMP, Redwood NSP, and Whiskeytown NRA.

Percentage change in mean ADC ΔD% from the two mean ADC values for each volunteer (using Table 4); methods include protocol A and the corresponding average slice using protocol B with and without motion correction; the two bottom rows give the mean reproducibility and standard deviation (within population variability) for each method.