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In the historical process of the new era, China’s socialist cause has flourished and people’s living standards have been continuously improved. However, in this process, corruption still exists, especially in the medical field, which not only damages the vital interests of the masses, but also seriously infringes on social fairness and justice. Therefore, it is particularly important to strengthen medical anti-corruption.

Medical anti-corruption must first strengthen the supervision of medical institutions. Medical institutions are holy places to heal the wounded and rescue the dying, which should be the place full of positive energy. However, in recent years, some medical institutions and their staff have deviated from medical ethics and pursued the maximization of interests, which has led to the tension between doctors and patients. In this regard, we should strengthen the internal and external supervision of medical institutions, improve the system construction, and ensure the normal operation of medical institutions.

Secondly, medical anti-corruption should severely punish corruption. In view of the problem of corruption in the medical field, we must resolutely punish according to law, and all medical institutions and individuals involved in corruption, bribery, power rent-seeking, false reimbursement and other acts must be dealt with seriously and will never be tolerated. At the same time, it is necessary to strengthen the case review, dig out the deep-seated reasons behind corruption, and provide useful reference for the reform in the medical field.

In addition, medical anti-corruption needs to strengthen publicity and education. We should carry out in-depth medical ethics education, so that the majority of medical staff can establish a correct world outlook, outlook on life and values, bearing in mind the purpose of serving the people. At the same time, it is necessary to strengthen the building of a clean and honest party style, raise the awareness of honesty and self-discipline of cadres in party member, and create a clean and healthy medical environment.

Finally, medical anti-corruption should give full play to the role of social supervision. We encourage the public to actively participate in medical anti-corruption and expose corrupt behaviors in the medical field through public opinion supervision and reporting. In addition, it is necessary to establish a medical anti-corruption information sharing platform, strengthen cooperation and communication between departments, and form an anti-corruption pattern in which the whole society participates.

In short, medical anti-corruption is an important task in the new era, which is related to the vital interests of the people and social fairness and justice. Under the new situation, we should take the spirit of the 20th National Congress of the Communist Party of China as the guide, carry out in-depth medical anti-corruption struggle, and strive to create a good medical environment for realizing the goal of common prosperity for all people.

Marco Conidi, an Italian singer who wrote the famous song "Mai sola mai" for Rome in 2006, also participated in the protest. He wrote on Instagram: "The most important thing tomorrow is that everyone brings a white handkerchief. Let’s wave it before the game to protest that our respected coach has been absurdly disqualified from conducting. Everyone supports Mourinho!"

On March 6th, Tesla CEO Elon Musk said on social media: I used to be interested in encrypting digital currency, but now I love artificial intelligence. "

According to media reports, Musk recently contacted artificial intelligence researchers and planned to set up a new research laboratory to develop a substitute for ChatGPT.

In addition, Musk’s remarks also suggest that compared with ChatGPT and Microsoft’s new chat bots, the chat bots he developed may have fewer restrictions on controversial topics.

In the early morning of March 5, Beijing time, the team of Professor Chen Yundai from the Cardiology Center of the General Hospital of the Chinese People’s Liberation Army published a special report on clinical research at the American Heart Association/World Cardiology (ACC/WCC)2023 Conference. Based on the artificial intelligence CT-FFR technology, the clinical research report on the treatment and follow-up of patients with stable coronary heart disease -TARGET trial, the results will be published simultaneously in the top international journals.CirculationJournal (TOP journal in JCR 1 area, impact factor 39.9).

The research was supported by the National Key R&D Program and the Beijing Science and Technology Rising Star Program, and combined with the research teams of cardiology and radiological imaging departments of several top domestic third-class first-class hospitals such as Beijing anzhen hospital affiliated to Capital Medical University, the Second Affiliated Hospital of Zhejiang University Medical College, Qilu Hospital of Shandong University, the First Affiliated Hospital of Xinjiang Medical University, and tongji hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology. The correspondent of this research paper is Professor Chen Yundai, Associate Professor Yang Junjie, Deputy Chief Physician Shan Dongkai and Dr. Wang Xi from the Department of Cardiovascular Medicine of PLA General Hospital are the co-first authors of this paper.

Introduction to research

TARGET study is the first multi-center, randomized and controlled clinical study in the world to evaluate the treatment and management of new stable chest pain patients using the field deployment strategy based on machine learning CT-FFR calculation. The research uses the artificial intelligence CT-FFR computing technology independently developed by China (Keya Medical Technology Co., Ltd.), and a total of 1216 patients from six medical centers in China were selected. The pretest probability of obstructive coronary heart disease in the enrolled patients was medium to high, and coronary CT angiography suggested that there was a critical stenosis of 30%-90%. The researchers randomly divided patients into CT-FFR diagnosis and treatment group (experimental group) or standard diagnosis and treatment group (control group). The main end point of the study was the proportion of patients with non-obstructive coronary artery disease or with obstructive coronary artery disease who did not receive revascularization during the follow-up coronary angiography within 90 days. Secondary end points included major adverse cardiovascular events, quality of life outcomes, improvement of angina symptoms and medical costs.

The results showed that compared with the control group, the proportion of patients with non-obstructive coronary disease or obstructive coronary disease who did not receive revascularization in CT-FFR diagnosis and treatment group decreased significantly (28.3% vs. 46.2%, P<0.001). On the whole, there were more patients receiving revascularization in CT-FFR group than in the control group (49.7% vs. 42.8%, P=0.02), but there was no significant difference in the proportion of MACE during the one-year follow-up (hazard ratio, 0.88; 95%CI, 0.59 to 1.30)。 During the follow-up period, the quality of life and symptoms of the two groups were similar, while the medical cost of CT-FFR treatment group tended to decrease. It is concluded that, compared with the standard diagnosis and treatment strategy represented by cardiac stress examination, the on-site deployment of CT-FFR calculation diagnosis and treatment strategy based on machine learning will significantly reduce the proportion of patients who have found non-obstructive coronary artery disease or do not need intervention within 90 days after coronary angiography. In addition, CT-FFR diagnosis and treatment strategy tends to save medical costs and increase the proportion of revascularization in the selected population. At the same time, CT-FFR strategy is consistent with the traditional path in improving patients’ symptoms or quality of life and the incidence of major clinical adverse vascular events.

Research enlightenment

TARGET research results show that "CT-FFR strategy based on machine learning in the field is feasible, safe and effective".

In the past 10 years, the extensive use of coronary CTA has promoted the diagnosis and treatment process of coronary heart disease in China. According to statistics, in 2017, the total number of coronary CTA angiography examinations in China reached 4.6 million. Therefore, the simple diagnostic function of coronary angiography is weakening, but among the patients who have received coronary angiography in China, most cases have not found obstructive coronary stenosis in the catheter room. Part of the reason for this phenomenon is that functional examination is not widely used or advanced cardiac imaging technology is not available enough. TARGET study further emphasizes that coronary angiography should only be applied to those patients who are most likely to have obstructive coronary stenosis or benefit from revascularization, and CT-FFR strategy will significantly optimize the management of stable coronary heart disease population.

This study adopts the CT-FFR simulation calculation technology-deep pulse fraction independently developed by Keya Medical Technology Co., Ltd., uses deep learning technology to evaluate the physiological function of coronary artery, and uses artificial intelligence technology to evaluate the FFR of coronary angiography image, which is a deep learning technology independently developed and optimized based on the latest development in the field of computer vision. It can quickly and accurately analyze the non-invasive blood flow reserve fraction. In January 2020, this technology was approved as the first NMPA artificial intelligence medical device class III certificate in China, and now it has become the only CT-FFR product in the world that has been triple-certified by NMPA in China, CE in the European Union and FDA in the United States.

Pamela Douglas, MD (Duke Clinical Research Institute, Durham, North Carolina), former president of ACC, led the experiment funded by HeartFlow (PLATFORM and PRECISE research). She pointed out that the most outstanding thing about the TARGET experiment is the novelty of its on-site CT-FFR analysis.

It is indeed possible that the field deployment method is cheaper and can return the results faster. In clinical practice, if CCTA is used as a first-line test, Douglas said, then the question becomes: "If you have borderline lesions, what should you do next?" For her, "this is a little obvious, because CT-FFR is only a software analysis. Although the previous products are very complicated, it is not without risk to make an appointment for a load test and ask the patient to come back later."

It is very important to deploy artificial intelligence computing in the field of TARGET research. "The advantage of using artificial intelligence algorithm is that it provides the possibility of field deployment, avoids the need to transfer sensitive medical data, shortens the calculation time and increases the participation of clinicians." They explained that although FFR can also be calculated by field computational fluid dynamics, this strategy is complex and requires a lot of resources. The convenience of machine learning will contribute to the application of CT-FFR in a wider range of scenarios, adding that "on-site CT-FFR strategy is practical and may be more suitable to meet the clinical practice needs in various clinical environments."

The exit from the Champions League doomed the direction and outcome of Paris Saint-Germain’s surrender in the 2022-23 season, and also sealed the double failure of strategy and management. Even so, Paris Saint-Germain plans to let him continue to lead the team, at least until the end of this season. French media claimed that the report on the crisis meeting between him and President Hellfi was exaggerated, and the club insisted that Galtier would not be fired before the end of the season, but he might not get the support from the top. It remains to be seen whether he can continue to lead Paris next season, but before that, he still has hope of winning Ligue 1.

The new rise of science and technology has also created the heyday of an era. With the growth of the global population, it has promoted the progress and development of industry invisibly based on the need for convenience. The problem of food and clothing for modern people has been basically solved, and the experience brought by science and technology has become people’s spiritual food, bringing more fun and convenience to life.

Looking at the past, no matter from the industrial field or the consumer electronics field, the thinking and manufacturing power of the Internet is relatively backward, and the consumption power is weak, so the application scale of electronic connectors is very different from the present situation. With the opening of the Internet, the new promotion of artificial intelligence and the Internet of Things has greatly changed the life around us.

Intuitive changes that can reflect the development of science and technology are constantly being popularized in life, and the application of smart home makes people sigh! Smart refrigerators, smart TVs, smart washing machines, smart speakers, smart lighting, smart air conditioners, smart door locks, intelligent curtain, etc., with the empowerment of the Internet of Things, have the ability to connect to the network, and have gradually become the new focus of the development of the Internet of Things in 2019.

The application of electronic connectors wins in the Internet of Things and artificial intelligence.

In the field of consumer electronics, whether it is smart home, service robot or smart wear, with the development trend of intelligence, the application of electronic connectors has increased dramatically, showing an unprecedented good trend, which is a new height for the past.

The application of electronic connectors wins in the Internet of Things and artificial intelligence.

According to authoritative statistics, the development of the Internet of Things is growing at an annual rate of 25%. It is estimated that by 2024, the market scale of the Internet of Things is expected to exceed 2.2 trillion yuan. Secondly, the application of the Internet of Things is more extensive, and it penetrates deeply in many industries such as electric power, transportation, industry, medical care, security and so on. In this new field, it will be a new blue ocean for the electronic connector market!

These are some of Xiaobian’s opinions. Readers can also discuss with Xiaobian what they think later.

With the development and application of technology, artificial intelligence has gradually entered people’s lives, and more and more enterprises and organizations have begun to use AI technology in their business. In the future, with the further development of technology, the application prospect of artificial intelligence will be broader and will become an important driving force in the digital age.

At present, artificial intelligence has been widely used in many fields, such as medical care, financial services, transportation, education, entertainment and other fields. For example, in the field of medical care, artificial intelligence can help doctors diagnose and treat diseases quickly and accurately by analyzing and processing a large number of medical data; In the field of financial services, artificial intelligence can provide customers with more personalized financial services by analyzing and processing a large number of financial data; In the field of transportation, artificial intelligence can improve the efficiency and safety of traffic management and reduce the incidence of traffic congestion through vehicle networking technology; In the field of education, artificial intelligence can provide students with more personalized learning services through intelligent teaching systems; In the field of entertainment, artificial intelligence can provide users with entertainment services that are more in line with their needs through the analysis of users’ interests and preferences.

With the continuous development and innovation of artificial intelligence technology, its application prospect will be broader. For example, artificial intelligence will be more and more widely used in smart homes, smart cities, driverless and other fields. Smart home will provide people with a more intelligent, comfortable and safe living environment through the connection and cooperation of intelligent devices; Smart cities will improve the level and efficiency of urban management and services through big data analysis and intelligent management; Unmanned driving will improve traffic safety and reduce traffic congestion through technologies such as automatic driving and intelligent navigation.

Although the application prospect of artificial intelligence is very broad, it also faces some challenges and problems in the application process. For example, issues such as data security, privacy protection, interpretability of algorithms, and the impact of artificial intelligence on the job market require the joint efforts of all parties to promote the further development of technology and applications.

The application prospect of artificial intelligence is very broad and it will play an important role in the future economic and social development. At the same time, we should also note that the application of artificial intelligence technology needs to balance the development of technology and society, taking into account issues such as data security and privacy protection, so that it can be truly used by human beings and promote human development and progress.

Inspired by recent biological discoveries, researchers have developed a new model that shows enhanced memory performance. This is achieved by modifying a classic neural network. Computer models play a key role in studying the process of making and retaining memories and other complex information in the brain. However, building this model is a delicate task.

The intricate interaction between electrical and biochemical signals and the connection network between neurons and other cell types create the basic structure for the formation of memory. Nevertheless, due to the limited understanding of the basic biology of the brain, it has proved to be a difficult task to code the complex biology of the brain into a computer model for further study.

Researchers at Okinawa Institute of Science and Technology (OIST) improved the widely used memory computer model (called Hopfield Network) by incorporating biological insights. This change has inspired a neural network, which not only better reflects the connection between neurons and other cells in the brain, but also has the ability to store more memories.

Thomas Burns, a doctoral student in the group of Professor Zhishu Shenjing, who is the head of OIST’s neurocoding and brain computing department, said that the increased complexity in the network makes it more realistic.

"Why is there so much complexity in biology? Memory may be one reason, "Mr. Burns said.

In the classical Hopfield network (left), each neuron (I, J, K, L) is connected with other neurons in pairs. In the improved network made by Burns and Professor Shenjing, three or more groups of neurons can be connected at the same time. Source: Thomas Burns (OIST)

Hopfield network stores memory as a weighted connection pattern between different neurons in the system. The network is "trained" to encode these patterns, and then researchers can test its memory of these patterns by presenting a series of vague or incomplete patterns to see if the network can recognize them as patterns it already knows. However, in the classical Hopfield network, the neurons in the model are connected with other neurons in the network to form a series of so-called "paired" connections.

Paired connections represent the connection between two neurons at the synapse, which is the connection point between two neurons in the brain. But in reality, neurons have complex branching structures called dendrites, which provide multiple connection points, so the brain relies on more complex synaptic arrangements to complete its cognitive work. In addition, the connections between neurons are regulated by other cell types called astrocytes.

Burns explained: "There are only paired connections between neurons in the brain, which is simply unrealistic. He created an improved Hopfield network, in which not only pairs of neurons, but also three, four or more groups of neurons can be connected, such as astrocytes and dendritic trees in the brain. "

Although the new network allows these so-called "collective" connections, on the whole, it contains the same number of connections as before. The researchers found that a hybrid network with paired connections and collective connections performed best and retained the most memory. They estimate that its effect is more than twice that of the traditional Hopfield network.

It turns out that you actually need to balance the combination of various features to some extent, Burns said. A single synapse is necessary, but you should also need some dendritic trees and some astrocytes.

Hopfield networks are very important for simulating brain processes, but they also have powerful other uses. For example, a very similar network type called Transformers is a language tool based on artificial intelligence, such as ChatGPT, so the improvements identified by Burns and Professor Shenjing may also make such tools more powerful.

Burns and his colleagues plan to continue to study their modified Hopfield networks to make them more powerful. For example, in the brain, the connection strength between neurons is usually different in two directions, so researchers want to know whether this asymmetric feature can also improve the performance of the network. In addition, he also wants to explore ways to make the memories of the network interact, just as they do in the human brain. Our memory is multifaceted and huge. We still have a lot to discover. "

In recent years, with the rapid development of Internet of Things technology, IOT card has become a topic of great concern. As a special SIM card, IOT card can transform various items into IOT devices that can be connected to the Internet, giving them the ability of wireless communication. In this paper, we will discuss the reasons why IOT card is a hot topic, as well as its application and development trend.

First, why has the IOT card become a hot topic?

IOT card has become a hot topic for the following reasons:

The rise of smart home: With the gradual popularization of the concept of smart home, people’s demand for smart home equipment is also growing. IOT card can connect smart home devices with the Internet, thus realizing remote control and data sharing, which greatly facilitates people’s lives.

Application expansion of Internet of Things: Internet of Things technology has been more and more widely used in smart cities, intelligent manufacturing, intelligent transportation and other fields, and the IOT card, as an important part of Internet of Things equipment, has attracted more attention.

Advantages of low cost and power consumption: IOT card adopts low-power wide area network technology (LPWAN), which has the advantages of low cost, low power consumption, low bandwidth and long-distance transmission. This means that IOT cards can be applied to a wider range of fields and further promote the development of the Internet of Things.

Second, the application of IOT card

The application scope of IOT card is very wide, mainly reflected in the following aspects:

Smart home: IOT card can connect all kinds of smart home devices to the Internet, such as smart door locks, smart lighting, smart home appliances and so on. These devices can realize remote control and data sharing through the Internet, which is convenient for people’s lives.

Smart city: IOT card can connect all kinds of devices in the city to the Internet, such as smart bus, smart parking, smart street lamps and so on. These devices can realize intelligent management through the Internet, and improve the service level of the city and the quality of life of residents.

Intelligent medical care: IOT card can connect all kinds of medical equipment to the Internet, such as telemedicine and health monitoring. These devices can be implemented through the Internet.

Realistic on-site monitoring, telemedicine, etc., to improve the efficiency and quality of medical services.

Intelligent transportation: IOT cards can connect transportation equipment to the Internet, such as intelligent vehicles and intelligent traffic lights. These devices can realize intelligent management through the Internet and improve traffic efficiency and safety.

Intelligent manufacturing: IOT card can connect industrial equipment to the Internet, realize intelligent management of industrial equipment, and improve production efficiency and quality.

Third, the development trend of IOT card

The future development trends of IOT cards mainly include the following points:

Large-scale application: With the gradual popularization of Internet of Things technology, IOT cards will be more widely used, which will further promote the development of Internet of Things.

Industry consolidation: The industrial chain of IOT cards will be gradually integrated, and enterprises in different links will cooperate more closely, thus realizing the standardization and scale of IOT card production.

Improvement of low-power technology: the core technology of IOT card is low-power technology, and the future IOT card will pay more attention to the improvement and application of low-power technology.

Improvement of security: With the increasing application of IOT cards, the security of IOT cards will become an important issue. In the future, the IOT card will strengthen the security guarantee and improve the trust and satisfaction of users.

The combination of AI and IOT card: The combination of artificial intelligence and IOT card will bring more innovative applications, thus further promoting the development of IOT technology.

IV. Conclusion

In a word, as a key component of the Internet of Things, IOT card has a wide range of application scenarios and broad development prospects. With the continuous development of technology and the continuous expansion of application scenarios, I believe that IOT cards will be more widely used in smart homes, smart cities, smart medical care, intelligent transportation, intelligent manufacturing and other fields in the future. At the same time, the industry consolidation of IOT card, the improvement of low-power technology, the improvement of security and the combination with artificial intelligence will also become important trends in the future development of IOT card.

[This article was originally issued by the official Qingyi IOT Card, and the source of reprinting needs to be noted]