According to the findings of a survey by IPSOS, when asked what would be the most unpleasant way to die, those in the U.S. are most likely to say cancer, followed by a neurological disorder and a terrorist attack. This data shows the percentage of U.S. respondents who say select causes of death would be the most unpleasant way to die as of 2019.

In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

The graph illustrates the number of deaths per day in the United States from 1950 to 2025. The x-axis represents the years, abbreviated from '50 to '24, while the y-axis indicates the daily number of deaths. Over this 75-year period, the number of deaths per day ranges from a low of 4,054 in 1950 to a high of 9,570 in 2021. Notable figures include 6,855 deaths in 2010 and 8,333 in 2024. The data shows a general upward trend in daily deaths over the decades, with recent years experiencing some fluctuations. This information is presented in a line graph format, effectively highlighting the long-term trends and yearly variations in daily deaths across the United States.

Number of deaths and mortality rates, by age group, sex, and place of residence, 1991 to most recent year.

Translation (by Mike Tu Awng) The way to bury when people die the Kachin people have the most rules and regulations for burial among people on earth. Kachin people have the most rules and regulations. There is no specific research on Kachin history. There are no proper written records. However, there are many rules and regulations for burial in practice. When people die, there are four types of deaths. Four types. If a person dies either because of sickness or old age, we call it 'tsu si' natural death. In this death either a person is a child, an adult man, or young lady, or a respectable man, or an old woman, or an old man, no matter how poor that person is, a coffin must be made, a coffin made of wood. A coffin unlike a wooden box nowadays but it is carved from wood. On the mountain there are plenty of trees. When a person dies, we cut down a tree. Then, split it into half and carve it to make coffin from generation to generation. We use sword as tool. I do not recall when we started using it as far as I remember. We put the corpse nicely in it. We put the corpse in the coffin and some bury it but some other burn it. When we burn it, we burn it together with the coffin. When a person dies this way, we bury him or her well and we have Kabung, 'funeral ritual'. Mostly kabung, 'funeral ritual' is held for two nights. The ritual ceremony is for two days. If it is for chiefs, gentlemen, or the rich, it doesn't matter how we hold Kabung ritual, it's all about celebration. They are like this It is not true that only after becoming Christians that we become human beings. We were more human before. In a village When a person dies even if that person is very poor, we bit gong we can borrow gong. We do not know since when we used gong. Kachin people did not know how to make it. Probably, Chinese made it for us. Gongs come from lower land too, from lower land. However, they did not like gongs from lower land. They like gongs from China. Now, when I do research on history, in about 1200, 1300, 1400 when Ming dynasty ruled in China, the dynasty was very good. They traded together. It was before the war with you, the Japanese. Those days, they traded. There were lots of natural resources, which Chinese people liked in Kachin Land since those times. Natural resources such as bear gallbladder, snake-skin, elephant tusks. Bee hive dried mushroom, deer horn, there were many things Chinese people liked. Then, people from this land sent things to China. And, Chinese people gave things they used such as gongs to Kachins in exchange. So, Kachins got gongs. In a village, even if it is not every house, people had gongs. That's why they hit gong when a person died. Those who had raffles, they shot the raffles. When they heard that a person died, people from the village as well as people from nearby village each one brought a chicken to the house. They just let the chicken roamed. Some were eaten by wild cats, some were eaten by eagles or hawk. Some remained. They had many chickens. Every household had chicken. And, there was no need to build chicken coop. They just attached coops to their houses. People just let them roamed. Some were eaten by eagles or hawk, some were eaten by wild cats, but some remained. They always had chickens. So, each one brought a chicken to the funeral house. Then, they brought a small pack of uncooked rice. And, they brought tsa pa, 'fermented rice' to make Tsapi, 'rice wine' They all gathered at the funeral house. Then, they cooked rice to eat, drank tsapi, 'rice wine', and cooked chicken to eat. To bury the dead, they went to forest to make coffin on the day of death. Moreover, they even gave ration like chicken to those who went to forest to make coffin. When they went, they brought like two or three chickens. Women did not go. There could be like four, five, or ten persons to make coffin. "Take this fermented rice and eat it." Rice was cooked at home. After that, it was all pleasant time. By night time, the corpse was already put in the coffin. The corpse was kept till the next morning, but buried in the afternoon. After the burial, the Kabung ritual started. They hit three gongs. Kabung ritual continued for three days. Then, people went back home. This is how it was done when there was a natural death. When a person died in natural death, Dumsa or shaman will instruct him/her well, saying "Go back to where our ancestors live." "Your mother is there", but sometimes people can die before their parents do. In that case, "Go back to your great grandparents", Dumsa let him/her go well. Whether it is true or not, then, it was done that way. It could happen that a person died without all the relatives around. If a father died, but children were in another village, or if they were on a journey, they buried the corpse. But his spirit and belongs were kept at home. They were all kept in a proper place. It could be similar to you. Kept belongings safely. The corpse was already buried. However, they did not have ceremony. It was a temporary event. They just buried the corpse then covered it like this. And then, the spirit is kept in the house with all his belongings. Just like before, the meal was placed at the right time. They even used the plate which that person used. Well, not really plate like today but wrapped in leave. And the bowl for the curry was bamboo container. Nowadays, we can buy bowls from developed countries like you. Even spatula was made of bamboo, too. Things were put nicely. Kept them well. After the meal time had passed, they did not give the food designated to the dead to neither dogs nor pigs. The food was put away in a safe place, to the forest. They could not just neglect but took care. Then, when the children were all gathered at home. Only then, they held the funeral, they had Kabung ritual as usual. Sometimes, the actual burial ground and his tomb can be at different locations. The person could be buried in a valley. or buried in the forest. However, tomb could be placed beautifully beside the road where people could see. That was for convenience. If possible, the tomb should be where a person was buried. If not, the tomb could be decorated at a popular location. That was like that. Some people burnt the dead. Even if they burnt the dead, they did this for the dead. Thus, this is what we call a natural death. Then, another type is, let's say died of thunder and lightning, or of downing. Killed by a buffalo or people killed one another. Death in these ways are called sawa, 'accidental death'. They could become spirit. They could not go on to the next life. They could just roam around here. Only the physical body disappeared The mind and the spirit did not disappeared. The dead could see those of us who are still alive. However, we cannot see him or her. If that person became nat, spirit, we call him/her 'kumgun' spirit. Not all of them became nats 'spirit' Maybe one out of ten became nat, spirit. These nats, or spirits They could talk through another person. They could talk to us through a medium, 'myi htoi' Nobody can dispute whether it was possible or not. I was conscious of my existence since forty. I was aware that I was a human being at the age of fourty. I remember the time when You, Japanese, and Europe started the war. I remember. Well then, these are our concepts. from the age of forty, I have seen three mediums. I did not see one. I just heard about him. But I saw two. They both lived till the age of 60. In 1960 maybe they lived till 1963 or 64 One was a female but the other one was male. I went to ask them. I told them, "one of my family members is sick, what should I do?" There was a piece of cloth called 'Nat nwat'. The medium took it and placed it at the Spirit house. He put a chair. Then, he put leaves on it. He put traditional swords in front of him. Nat, 'spirit' always carried swords with them, traditional sword. When asked that person shook so intensely like when a person caught a cold malaria. After shaking for a while, he started talking. However, that person started to sing. Even nat, 'spirit' they sang songs. Through that medium, they sang songs. And I will tell you about the person named Nding Hka, who was about fifty years old. In the normal time, he was just a farmer. This part is for general knowledge. I do not talk about lies. Even to tell the truth, i don't have much time left. Anyhow, He was just a farmer. To tell the truth, even when he laughed, he did not make sound. That old man. He was a quiet man, He was poor. Poor, but he was a medium. Once Lahtaw Lords celebrated Manau. He was invited to the Manau. It was in 1952. The Manau was about to begin that morning, then, He started prophesizing. He sat down and prophesized. We listened to him from the crowd. At first, he sang a song. I knew his voice. I have a very good memory. His voice was like that. "i........ ye." It started like this. It was in Jinghpaw language. What is it? I cannot see. Can you say that? Please tell us the story not in Burmese but in Jinghpaw. E, sure, sure. I thought it would be better for him in Burmese that's why I used Burmese. But sure. I was just using it because you specialized in Burmese in Yangon. That's why I used it. Without Burmese is also fine. We have terms for everything. It's just that we don't use it. Like that he could make sound. Nat 'spirit'. Then, it was impossible not to believe it. When he was in a normal situation, he didn't even laugh. He was a quiet person. However, when he was acting as a medium, he made a long sound like the one before. We, Jinghpaw, call that act "ding sat'. He sang songs. A medium 'ding sat.' It was in Jinghpaw. But nobody knows nowadays what it means 'a medium chant'. He started it by chanting like that. Then, he talked. He talked about what was needed. That medium. This is about natural death. We are done with the topic. Now, we will talk about accidental death. Those who died in accidental death, they became medium, became Nat,

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

BackgroundVery few studies have been published on the causes of death of upper tract urothelial carcinoma (UTUC). We sought to explore the mortality patterns of contemporary UTUC survivors.MethodsWe performed a retrospective cohort study involving patients with upper urinary tract carcinoma from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database (2000 and 2015). We used standardized mortality ratios (SMRs) to compare death rates among patients with UTUC in the general population and excess absolute risks (EARs) to quantify the disease-specific death burden.ResultsA total of 10,179 patients with UTUC, including 7,133 who died, were included in our study. In total, 302 (17.17%) patients with the localized disease died of UTUC; however, patients who died from other causes were 4.8 times more likely to die from UTUC (n = 1,457 [82.83%]). Cardiovascular disease was the most common non-cancer cause of death (n = 393 [22.34% of all deaths]); SMR, 1.22; 95% confidence intervals [CI], 1.1–1.35; EAR, 35.96). A total of 4,046 (69.99%) patients with regional stage died within their follow-up, 1,413 (34.92%) of whom died from UTUC and 1,082 (26.74%) of whom died from non-cancer causes. UTUC was the main cause of death (SMR, 242.48; 95% CI, 230–255.47; EAR, 542.47), followed by non-tumor causes (SMR, 1.18; 95% CI, 1.11–1.25; EAR, 63.74). Most patients (94.94%) with distant stage died within 3 years of initial diagnosis. Although UTUC was the leading cause of death (n = 721 [54.29%]), these patients also had a higher risk of death from non-cancer than the general population (SMR, 2.08; 95% CI, 1.67–2.56; EAR, 288.26).ConclusionsNon-UTUC deaths accounted for 82.48% of UTUC survivors among those with localized disease. Patients with regional/distant stages were most likely to die of UTUC; however, there is an increased risk of dying from non-cancer causes that cannot be ignored. These data provide the latest and most comprehensive assessment of the causes of death in patients with UTUC.

What are people dying from?

This question is essential to guide decisions in public health, and find ways to save lives.

Many leading causes of death receive little mainstream attention. If news reports reflected what children died from, they would say that around 1,400 young children die from diarrheal diseases, 1,000 die from malaria, and 1,900 from respiratory infections – every day.

This can change. Over time, death rates from these causes have declined across the world.

A better understanding of the causes of death has led to the development of technologies, preventative measures, and better healthcare, reducing the chances of dying from a wide range of different causes, across all age groups.

In the past, infectious diseases dominated. But death rates from infectious diseases have fallen quickly – faster than other causes. This has led to a shift in the leading causes of death. Now, non-communicable diseases – such as heart diseases and cancers – are the most common causes of death globally.

More progress is possible, and the impact of causes of death can fall further.

On this page, you will find global data and research on leading causes of death and how they can be prevented.

This data can also help understand the burden of disease more broadly, and offer a lens to see the impacts of healthcare and medicine, habits and behaviours, environmental factors, health infrastructure, and more.

By Saloni Dattani, Fiona Spooner, Hannah Ritchie and Max Roser

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

In 2022, the most significant cause of death among men in the United States was heart disease, which contributed to **** percent of deaths. COVID-19 was the third leading cause of death among U.S. men in both 2020 and 2021, and the fourth leading cause in 2022. This statistic shows the distribution of the ** leading causes of death among men in the United States from 2020 to 2022.

BackgroundAs the survival rates of patients with renal cell carcinoma (RCC) continue to increase, noncancer causes of death cannot be ignored. The cause-specific mortality in patients with RCC is not well understood.ObjectiveOur study aimed to explore the mortality patterns of contemporary RCC survivors.MethodsWe performed a retrospective cohort study involving patients with RCC from the Surveillance, Epidemiology, and End Results (SEER) database. We used standardized mortality ratios (SMRs) to compare the death rates in patients with RCC with those in the general population.ResultsA total of 106,118 patients with RCC, including 39,630 who died (27%), were included in our study. Overall, compared with the general US population, noncancer SMRs were increased 1.25-fold (95% confidence intervals [CI], 1.22 to 1.27; observed, 11,235), 1.19-fold (95% CI, 1.14 to 1.24; observed, 2,014), and 2.24-fold (95% CI, 2.11 to 2.38; observed, 1,110) for stage I/II, III, and IV RCC, respectively. The proportion of noncancer causes of death increased with the extension of survival time. A total of 4,273 men with stage I/II disease (23.13%) died of RCC; however, patients who died from other causes were 3.2 times more likely to die from RCC (n = 14,203 [76.87%]). Heart disease was the most common noncancer cause of death (n = 3,718 [20.12%]; SMR, 1.23; 95% CI, 1.19–1.27). In patients with stage III disease, 3,912 (25.98%) died from RCC, and 2,014 (13.37%) died from noncancer causes. Most patients (94.99%) with stage IV RCC died within 5 years of initial diagnosis. Although RCC was the leading cause of death (n = 12,310 [84.65%]), patients with stage IV RCC also had a higher risk of noncancer death than the general population (2.24; 95% CI, 2.11–2.38).ConclusionsNon-RCC death causes account for more than 3/4 of RCC survivors among patients with stage I/II disease. Patients with stage IV are most likely to die of RCC; however, there is an increased risk of dying from septicemia, and suicide cannot be ignored. These data provide the latest and most comprehensive assessment of the causes of death in patients with RCC.

Tree mortality events driven by drought and warmer temperature, often amplified by pests and pathogens, are emerging as one of the predominant climate change impacts on plants. Understanding and predicting widespread tree mortality events in the future is vital as they affect ecosystem goods and services provided by forests and woodlands, including carbon storage needed to help offset warming. Additionally, if extensive enough, tree die-off events can influence not only local climate but also climate and vegetation elsewhere via ecoclimate teleconnections. Consequently, recent efforts have focused on improving predictions of tree mortality. One of the most commercially important genera of trees is Pinus, and the most studied species globally for drought-induced tree mortality is piñon pine, Pinus edulis. Numerous metrics have been developed in association with predicting mortality thresholds or variations in mortality for this species. In this article, we compiled metrics associated with drought and warming related mortality that were developed for P. edulis or for which P. edulis was a key example species used in a calculation or prediction. We grouped these metrics into three categories: (i) those related to simple climate variables, (ii) those related to physiological responses, and (iii) those that require multi-step calculations or modeling using climate, ecohydrological, and/or ecophysiological data; and we identified the spatial-temporal scale of each of these metrics. We also compiled factors shown to modify rates or sensitivities of mortality. The metrics to predict mortality include empirical ones which often have implicit linkages to expected mechanisms, and more mechanistic ones related to physiological drivers. The metrics for P. edulis have similarities with those available for other species of Pinus. Expected future mortality events will provide an opportunity to observationally and experimentally test and compare these metrics related to tree mortality for P. edulis via near-term ecological forecasting. The metrics for P. edulis may also be useful as potential analogs for other genera. Improving predictions of tree mortality for this species and others will be increasingly important as an aid to move toward anticipatory management.

Occupational self-image of German editors and judgement on freedom of the press.

Topics: Most important tasks of the press; judgement on the performance of the press; assessment of the most important problems of German politics and the contribution of the press to problem solution; views about the extent of actual freedom of the press; possibilities to secure freedom of the press; perceived threats to freedom of the press and dependence on advertising business; comparison of possibilities of press and radio to influence public opinion; attitude to self-limitation of the press; press and Federal German Armed Forces; influence of the press on democracy; judgement on selected press agencies; party preference of respondent.

Demography: age (classified); sex; marital status; religious denomination; school education; vocational training; professional position; income; refugee status.

Interviewer rating: social class and willingness of respondent to cooperate; number of contact attempts.

Also encoded were: party orientation of the newspaper; type of newspaper; number of copies and place of publication.

Number and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.

The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

Lithium Ion Battery Slot Die Market Outlook

The global market size for Lithium Ion Battery Slot Die was valued at approximately USD 450 million in 2023 and is projected to reach USD 1.2 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% during the forecast period. This growth can be attributed to the increasing demand for lithium-ion batteries across various industries, advancements in battery technology, and a rise in electric vehicle adoption globally.

One major growth factor for the Lithium Ion Battery Slot Die market is the surging demand for electric vehicles (EVs). As countries worldwide push for greener initiatives and aim to reduce carbon emissions, the adoption of EVs is accelerating. Governments are providing incentives and subsidies to promote the use of electric transportation, which in turn is driving the demand for efficient and high-quality lithium-ion batteries. This directly influences the need for advanced battery manufacturing equipment like slot die coaters, which ensure uniformity and precision in battery electrode production.

Another significant growth driver is the expansion of renewable energy storage systems. With the increasing focus on sustainable energy solutions, the demand for energy storage systems (ESS) is on the rise. Lithium-ion batteries are a critical component of these systems due to their high energy density, long cycle life, and efficiency. The development and deployment of large-scale energy storage projects are expected to boost the market for slot die technology, which is essential for producing high-performance batteries. Investments in renewable energy infrastructure are further propelling market growth.

Technological advancements in battery manufacturing are also contributing to market expansion. Innovations in slot die coating technology, such as multi-layer slot dies, are enhancing the efficiency and quality of lithium-ion battery production. These advancements enable the manufacturing of batteries with improved performance metrics, such as higher energy density and faster charging capabilities. Companies are increasingly investing in research and development to optimize slot die technology, which is anticipated to fuel market growth over the forecast period.

Regionally, Asia Pacific holds the largest market share and is expected to maintain its dominance throughout the forecast period. The region's growth is driven by the presence of key battery manufacturers, increasing adoption of electric vehicles, and significant investments in renewable energy projects. Countries such as China, Japan, and South Korea are at the forefront of battery technology and production, making Asia Pacific a critical market for Lithium Ion Battery Slot Die. Additionally, favorable government policies and initiatives supporting electric mobility and energy storage systems are further boosting the market in this region.

Product Type Analysis

The Lithium Ion Battery Slot Die market is segmented by product type into Single Layer Slot Die and Multi-Layer Slot Die. The Single Layer Slot Die segment is currently the most widely used, primarily due to its simplicity and cost-effectiveness. Single Layer Slot Dies are preferred for applications where uniform coating and precision are essential but multi-layer capabilities are not required. These slot dies are extensively used in the production of consumer electronics and small-scale batteries where single-layer coating suffices.

However, the Multi-Layer Slot Die segment is expected to witness significant growth over the forecast period. Multi-Layer Slot Dies offer the advantage of applying multiple coating layers simultaneously, enhancing the efficiency and quality of the battery production process. This technology is particularly beneficial for high-performance batteries used in electric vehicles and energy storage systems. Multi-layer slot dies enable the manufacture of batteries with higher energy densities and improved performance characteristics, meeting the increasing demands of advanced battery applications.

Technological advancements in multi-layer slot die technology are driving its adoption across the industry. Innovations such as precision control mechanisms and advanced material compatibility are making multi-layer slot dies more efficient and reliable. These advancements are enabling manufacturers to produce high-quality batteries with minimal defects and enhanced performance, contributing to the growing preference for multi-layer slot dies in the market.

The ongoing research a

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.