Takefuji Yoshiyasu

This paper examines how testing accuracy plays a key role in detecting someone is positive. Bayesian-theorem exploits how an inaccurate rapid antigen test with a high true-positive rate and a low false-positive rate affects the detection of the probability that someone is positive. The probability is calculated with three determinants in actual dental practices: Infection rate, true positive rate, and false positive rate. The result suggests that in a high infection rate, the false positive rate of rapid antigen tests plays a key role in detecting positive individuals. In 6.5% infection rate, 0.991 true positive rate, and 0.0005 false positive rate, the probability is 0.992 while it with 0.05 false positive rate is reduced to 0.579. The proposed Bayesian analysis can be used for future analysis with imprecise tests in other applications.

Diversity is supposed to create better groups and societies but sometimes fails. It is explained why the power of diversity may not create better groups in the current diversity prediction theory. Diversity may hurt civic life and introduce distrust. This is because the current diversity prediction theory is based on real numbers that ignore individual abilities. Its diversity prediction theory maximizes performance with infinite population size. Contrary to this, collective intelligence or swarm intelligence is not maximized by infinite population size, but by population size. The extended diversity prediction theory using the complex number allows us to express individual abilities or qualities. The diversity of complex numbers always produces better groups and societies. The wisdom of crowds, collective intelligence, swarm intelligence or nature-inspired intelligence is implemented in the current machine learning or artificial intelligence, called Random Forest. The problem of the current diversity prediction theory is detailed in this paper.

Scholar performance evaluation plays a key role in management science and engineering. Scholar evaluation using Google Scholar and ResearchGate can serve as an indispensable scouter for evaluating scholar performance. Both tools to quantitatively evaluate scholars can be used to support evidence-based decision making in administration and human resources. However, both tools must be used together for complementing accurate scholar evaluation. This author shows examples of fatal drawbacks in Google Scholar and ResearchGate, respectively. Scopus and Publons, used as default scholar performance, are affected by publisher-bias selection of journals and conferences. The author recommends scholar performance evaluation using both tools such as Google Scholar and ResearchGate together with Scopus and Publons.

In the early 2000s, Japanese society became aware of the social phenomenon of hikikomori or social withdrawal among Japanese youth. However, the hikikomori phenomenon was not a domestic Japanese social problem, but a global social and health issue or a global silent epidemic. A literature review was conducted on the global silent epidemic issue and identifying hikikomori and effective treatment. This paper will reveal how to identify hikikomori with biomarkers or determinants and treatments for hikikomori. Impact of COVID-19 on hikikomori was briefly investigated.

This paper examines effectiveness of vaccination with symptoms by age groups in the US and Hamamatsu city in Japan. The efficacy of vaccination has been reported in Singapore, but both datasets such as the US CDC dataset and the Hamamatsu dataset contradict the Singapore results. Both local government and government datasets are publicly available for peer review and reader validation.

Active thin film electrochromic or thermochromic coatings have been used in smart windows. However, the current cost of active thin film windows is approximately 10 times that of passive film windows. This paper proposes an inexpensive passive thin metal film for all-season energy savings. The proposed passive thin metal film allows heat to flow preferentially in one direction. Thin metal films attached to glass indoor can absorb solar heat and the solar can radiate the heat to a room and to the glass respectively until thermal equilibrium. Because of the heated metal film against the room, as long as the temperature of the film is higher than that of the room, there is no heat flux from the room to the thin metal film which is called perfect thermal insulation. The 960m2 film was installed in an actual hotel in Japan over 10 years and contributed to reducing the energy cost of air conditioning from 54 million yen to 43 million yen, demonstrating an annual energy savings of 11 million yen (US$0.1 million). This paper briefly describes how the proposed economical passive thin metal film will provide all-season energy savings.

Recently, blockchain technologies seem to have emerged from a period of disillusionment named in the hype cycle, and development has become active again. In this research, substitute and complementary repositories were identified from GitHub records in order to grasp the state of representative blockchain platforms: Bitcoin, Ethereum, Hyperledger, Ripple, and Corda. Within many blockchain platforms, it is common to have complementary relationships. Ethereum and Hyperledger also have a complementary relationship across platforms. The results showed that Ethereum is reactivating Hyperledger, whose development is stabilizing. This research proposes a methodology to find next-step software development from the network based on developers' skills via their movements between repositories.

There are two types of policy outcome analysis tools: snapshot tool and time-series tool. hiscovid is a time-series policy outcome scoring tool of COVID-19 policies by country where the daily cumulative population mortality is used for scoring the outcomes of COVID-19 country policies to visualize and identify when policymakers made mistakes. hiscovid allows policymakers to observe the progress and transition of scores over time to learn lessons from the past decision-making mistakes for correcting the current policies to reduce unnecessary deaths. The lower the score, the better the policy. hiscovid attracted 1480 users worldwide.

Much research has been done on the efficacy of vaccines against the COVID-19 pandemic, but the claims have not yet been realized in the real world. This paper proposes three COVID-19 policy outcome analysis tools such as jpscore for scoring and revealing the best prefecture policy in Japan, scorecovid for scoring and revealing the best country policy in the world, and finally hiscovid for visualizing and identifying when policymakers made mistakes in time-series scores. Poorly scored countries or prefectures can learn good strategies from the best country or prefecture with excellent scores. Three tools are based on a single metric dividing the number of COVID-19 deaths by the population in millions. Three tools suggest us that the sustainable mandatory test-isolation strategy should be adopted in the world for mitigating the pandemic. This paper also addresses what is lacking in Japan for scientific evidence-based research for mitigating the pandemic. Visualization tools and sorted and time-series scores of policy outcomes help policymakers make the right decisions.

Aim: The goal of this paper is to analyze the COVID-19 policies of 10 European countries, including Sweden, Finland, Norway, Italy, France, Germany, Poland, Belgium, the Netherlands, and Hungary, with a time-series policy analysis tool. Subject and methods: The results of the COVID-19 policy analysis are based on a single time-series indicator, or daily population mortality rate: the number of COVID-19 daily cumulative deaths divided by the population in millions. The lower the score, the better the policy. Although many experts believe that the COVID-19 policy outcome analysis is premature, time series analysis is an excellent analysis that can provide information on the progress and transition of policy outcomes. In other words, the proposed time series analysis tool allows policymakers to identify and quantify when mistakes were made during the on-going COVID-19 pandemic. Results: The COVID-19 policy analysis discovered many useful facts. Sweden failed due to the herd immunity approach. Hungary made a fundamental mistake in COVID-19 tactics. Countries such as Sweden, Hungary, Belgium, and Poland showed time-series changes that differed from the others. Conclusion: Public health interventions can play a key role in mitigating the COVID-19 pandemic. The proposed policy analysis tool, hiscovid demonstrated the effectiveness of the time-series score behavior for discovering when policymakers made mistakes.

There are two types of policy analysis tools: snapshot tool and time-series tool. scorecovid is a snapshot tool to score individual COVID-19 policies in the world and sort a list of scores. The population mortality rate is used for evaluating the outcomes of COVID-19 country policies. The lower the score, the less the COVID-19 deaths. The lower the score, the better the policy. The scorecovid tool is intended for poorly scored countries to learn good strategies from countries with excellent scores where scorecovid attracted 15192 users worldwide.

This paper presents a new open-source program called deathdaily for predicting the number of daily COVID-19 deaths in the next 7 days. The predictions can be used by policymakers to determine whether current policies should be strengthened/mitigated or new policies should be challenged to mitigate the COVID-19 pandemic. Although vaccines have been mitigating the pandemic initially, the recent resurgence with new variants has been observed in many vaccinated countries. This paper shows how to use deathdaily to detect symptoms of resurgence. The proposed deathdaily is available in public and can be installed by a Python package manager PyPI. The deathdaily has been downloaded by 15,964 users worldwide, according to https://pepy.tech/project/deathdaily. The fact shows that the applicability, practicality, and usefulness of the proposed program have been duly evaluated.

The current disaster approaches and strategies have failed. Our society is also vulnerable to COVID-19 pandemics and natural disasters. This paper surveys the conventional disaster governance regimes and examines whether a sustainable and resilient society against natural and human-induced disasters can be built. This paper aims to shed light on resilient city and country building from the perspective of disaster prevention. Current disaster strategies must be updated in order to mitigate the cost of disaster events and to make people happy. This paper quantifies the scores of the COVID-19 policies for strengthening disaster prevention technology.

There are two types of policy analysis: socioeconomic analysis and public policy outcome analysis. The socioeconomic analysis is used for understanding the relationship between COVID-19 incident and mortality and building effective governance. There are two types of policy outcome analysis: general policy analysis and time series policy analysis. This paper is a policy outcome analysis of COVID-19, not a policy analysis. This paper examines COVID-19 policy outcome analysis of five countries such as the UAE, Taiwan, New Zealand, Japan and Hungary. Two policy outcome analysis tools are used in this paper such as scorecovid to generate a snapshot list of sorted scores and time-series hiscovid to identify when policymakers made mistakes for correcting mistakes in the near future policy update. Scores in both tools are based on the population mortality rate: dividing the number of COVID-19 deaths by the population in millions. The lower the score, the better the policy. The higher the score, the more deaths that make people unhappy. COVID-19 death is the most unfortunate event in life and is caused by policy. The introduced time-series policy analysis tool, hiscovid discovered ten facts of five countries. Discovered ten facts will be detailed in this paper. Visualization of policy outcomes over time will play an important role in mitigating the COVID-19 pandemic.

COVID-19 policy outcomes are influenced by urban policy and governance. The goal of this paper is to navigate the sustainable solution of the COVID-19 pandemic using evidence-based research for cities. The number of deaths from COVID-19 is one good indicator to evaluate the results of individual policies by country, state and cities. A policy assessment of urban agglomerations is essential to scientific research. Scoring policies with a single determinant is calculated by dividing the number of deaths by the population in millions. The lower the score, the better the policy. The score monotonically increases so that policymakers can suppress it, but they cannot improve or decrease it. Thus, mistakes by policymakers cannot be corrected and are fatal forever. Many countries have used a pharmacological approach alone such as vaccination with boosting, not sustainable, but their scores are poor and their policies are not effective against the pandemic. Sustainable and optimal policies to mitigate the pandemic were discovered by sorting the scores. This paper introduces two new policy scoring tools such as scorev and usscore. Both tools revealing sustainable approaches are designed for policy-poor states or urban agglomerations to learn the good strategies from countries with excellent scores.

COVID-19 is an environmental policy problem. The goal of this paper is to show sustainable policies against the COVID-19 pandemic. Medical professionals tend to stick only to pharmacological approaches such as vaccination and boosting, but that is not sustainable. The scorecovid and hiscovid tools revealed that the sustainable and the best policy against COVID-19 is based on the mandatory test-and-isolation by law. Because COVID-19 variants have the ability to spike mutations and immune escape, pharmacological approaches such as vaccination alone cannot mitigate or end COVID-19. The scorecovid tool is a Python Package Index (PyPI) application for scoring individual policies against COVID-19. In scorecovid, scoring policies is calculated by dividing the number of deaths due to COVID-19 by the population in millions. The hiscovid tool was developed to identify mistakes by policymakers in order to monitor their policies in time-series scores. The lower the score, the better the policy.

<jats:p>Human cooperative behavior includes passive action strategies based on others and active action strategies that prioritize one’s own objective. Therefore, for cooperation with humans, it is necessary to realize a robot that uses these strategies to communicate as a human would. In this research, we aim to realize robots that evaluate the actions of their opponents in comparison with their own action strategies. In our previous work, we obtained a Meta-Strategy with two action strategies through the simulation of learning between agents. However, humans’ Meta-Strategies may have different characteristics depending on the individual in question. In this study, we conducted a collision avoidance experiment in a grid space with agents with active and passive strategies for giving way. In addition, we analyzed whether a subject’s action changes when the agent’s strategy changes. The results showed that some subjects changed their actions in response to changes in the agent’s strategy, as well as subjects who behaved in a certain way regardless of the agent’s strategy and subjects who did not divide their actions. We considered that these types could be expressed in terms of differences in Meta-Strategies, such as active or passive Meta-Strategies for estimating an opponent’s strategy. Assuming a human Meta-Strategy, we discuss the action strategies of agents who can switch between active and passive strategies.</jats:p>

Viral contamination is one of the most urgent and important topics of environmental pollution. COVID-19 is primarily transmitted from person to person, but can also be transmitted from person to animal. Herd immunity must meet the requirements in order to fulfill the goal of mitigating and ending COVID-19. This paper shows five reasons or conditions why herd immunity is not achieved in the present policies without proposed effective strategies in this paper. Unless one of the five reasons for the herd immunity model is met, the promise of herd immunity will not be fulfilled. Many COVID-19 policies worldwide with current vaccines do not meet the requirements. Policymakers have been relying on unreliable R. The number of daily deaths instead of the number of cases is a good indicator of the pandemic which will be mainly used in this paper. Currently, even in vaccinated countries, resurgences are being observed with new variants with spike mutations and immune escape. This paper proposes an effective multipronged approach such as a pharmacological approach and a non-pharmacological approach including digital fencing. Two tools such as scorecovid and deathdaily were used for justifying the claims. Digital fencing as well as pharmacological approaches may be able to overcome the pandemic. Two tools such as scorecovid and deathdaily showed that the proposed multipronged approach will be effective for mitigating the pandemic.

Incident reports show the high risk of losing trust in global supply chain management. Under the covid-19 pandemic, cloud-based global supply chains have been vulnerable to malicious attacks. The goal of this paper is to show the high risk caused by third-party access in the current global supply chains and how to mitigate it. Based on the incident reports, global supply chain leaders are unaware of the risks of third-party access. The current global supply chains must be transformed into robust and resilient systems against malicious attacks. This paper shows methods on how to mitigate the high-security risk. HIGHLIGHTS Incident reports show the high risk of losing trust in global supply chain management against malicious attacks. The high risk caused by third-party access in the current global supply chains will be illustrated. Global supply chain leaders are unaware of the risks of third-party access. The global supply chains must be transformed into robust systems. This paper shows methods on how to mitigate the high-security risk in third-party logistics. The lower the risk, the lower the chance of losing trust. The more a leader is aware of the high risks, the less likely he or she is to lose trust.

This article presents the results of the Arabic countries mitigation using an open-source python package SCORECOVID which calculates the score of the countries based on the death rate. The results presented by the tool reflects the real facts and the ground truth in the different countries and the effectiveness of their policies.

This paper briefly surveyed the promising sustainable and renewable technologies for producing not only fuel but also food and water respectively by capturing air with sustainable energy in order to enhance disaster resilience. Metal–organic frameworks (MOFs) can be used to harvest water from the air, CO2 and water from the air can be used to produce alternative sustainable protein by bacteria, and CO2 from the air can be also converted to fuel by inexpensive chemical catalysts. This paper examines whether surveyed technologies with allow us to build sustainable and resilient societies against disasters for solving real risk problems. The investigated sustainable and renewable technologies can transform our society into a sustainable and renewable society that is truly resilient to natural disasters. No one has yet attempted to combine the three sustainable and renewable technologies to transform our society into one that is sustainable and resilient to natural disasters. The proposed approach will be tested and examined in Kaga City, Japan.

<jats:p>This is the world’s first tutorial article on Python programing on set operations for beginners and practitioners in translational medicine or medicine in general. This tutorial will allow researchers to demonstrate and showcase their tools on PyPI packages around the world. Via the PyPI packaging, a Python application with a single source code can run on Windows, MacOS, and Linux operating systems. In addition to the PyPI packaging, the reproducibility and quality of the source code must be guaranteed. This paper shows how to publish the Python application in Code Ocean after the PyPI packaging. Code Ocean is used in IEEE, Springer, and Elsevier for software reproducibility validation. First, programmers must understand how to scrape a dataset over the Internet. Second, the dataset files must be read in Python. Third, a program must be built to compute the target values using set operations. Fourth, the Python program must be converted to the PyPI package. Finally, the PyPI package is uploaded. Code Ocean plays a key role in publishing validation for software reproducibility. This paper depicts a vaers executable package as an example for calculating the number of deaths due to COVID-19 vaccines. Calculations were based on gender (male and female), age group, and vaccine group (Moderna, Pfizer, and Novartis), respectively.</jats:p>

<jats:p>Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disorder that is characterized by fatigue that persists for more than 6 months, weakness, sleep disturbances, and cognitive dysfunction. There are multiple possible etiologies for ME/CFS, among which mitochondrial dysfunction plays a major role in abnormal energy metabolism. The potential of many substances for the treatment of ME/CFS has been examined; however, satisfactory outcomes have not yet been achieved. The development of new substances for curative, not symptomatic, treatments is desired. Molecular hydrogen (H<jats:sub>2</jats:sub>) ameliorates mitochondrial dysfunction by scavenging hydroxyl radicals, the most potent oxidant among reactive oxygen species. Animal experiments and clinical trials reported that H<jats:sub>2</jats:sub> exerted ameliorative effects on acute and chronic fatigue. Therefore, we conducted a literature review on the mechanism by which H<jats:sub>2</jats:sub> improves acute and chronic fatigue in animals and healthy people and showed that the attenuation of mitochondrial dysfunction by H<jats:sub>2</jats:sub> may be involved in the ameliorative effects. Although further clinical trials are needed to determine the efficacy and mechanism of H<jats:sub>2</jats:sub> gas in ME/CFS, our literature review suggested that H<jats:sub>2</jats:sub> gas may be an effective medical gas for the treatment of ME/CFS.</jats:p>

In humans' cooperative behavior, there are two types of behavioral strategies: passive behavioral strategies based on the others, and active behavioral strategies based on the objective-first. In order to realize a robot that can use different strategies and communicate like a person, we created an agent that can switch between active and passive strategies. However, it is not clear whether people change their own behavioral strategies according to each strategy. In this study, we conducted an experiment in which agents with multiple strategies of actively giving way and passively giving way passed each other in a grid-like space, and analyzed whether people's behavior changed when the agents' strategies changed. The results show that, in addition to subjects who change their own behavior in response to changes in the agent's strategy, there are also subjects who behave in a certain way regardless of the agent's strategy and subjects whose behavior is not clearly divided.

This article will scientifically evaluate individual COVID-19 policies of countries around the world, U.S. states, and Japanese prefectures, respectively. The efficacy of the vaccines has been reported in many of the world&#x2019;s top medical journals, but even after more than a year of vaccination, the claims have yet to be met. Human emotions, behaviors, and individual policies can significantly influence the outcome against the pandemic. The evaluation in this article is based on a single determinant of the policy outcome. Scoring policies is based on dividing the number of deaths due to COVID-19 by the population in millions. The lower the score, the better the policy. Unfortunately, scores monotonically increase, so that policymakers can only suppress them but cannot improve or decrease them. Therefore, mistakes by policymakers cannot be corrected in the future and they are fatal forever. The result using three tools will reveal the best COVID-19 policy in the world. The revealed policy should have been or be adopted in individual countries for mitigating and ending the COVID-19 pandemic. This article also suggests what is needed in our society for reducing the unnecessary deaths due to COVID-19.

Despite the fact that we have reported on the dangers of the explosion of hydrogen gas inhalers, hydrogen gas inhalers with explosive hazards are, as a matter of fact, still being sold today. In this study, we investigated past reports of hydrogen gas inhaler explosion accidents to clarify the causes of these explosion incidents. As a result of this investigation, we found that the central cause was the leakage of hydrogen gas inside the hydrogen gas inhaler. Although it is said that the explosive concentration of hydrogen is between 10% and 75%, and that the gas does not explode above 75% due to the lack of oxygen, we confirmed through a series of ignition experiments that explosions can occur even in hydrogen gas inhalers that produce 100% hydrogen gas. Some manufacturers of such highly concentrated hydrogen gas inhalers claim that the high concentration and purity of hydrogen is safe and that there is no risk of explosion. We believe that manufacturing or selling such products that pose a risk of explosion or detonation is a violation of social justice. This paper presents ideas for selecting safe hydrogen gas inhalers based on a survey of past accident cases.

Intestinal bacteria can be classified into 'beneficial bacteria' and 'harmful bacteria.' However, it is difficult to explain the mechanisms that make 'beneficial bacteria' truly beneficial to human health. This issue can be addressed by focusing on hydrogen-producing bacteria in the intestines. Although it is widely known that molecular hydrogen can react with hydroxyl radicals, generated in the mitochondria, to protect cells from oxidative stress, the beneficial effects of hydrogen are not fully pervasive because it is not generally thought to be metabolized in vivo. In recent years, it has become clear that there is a close relationship between the amount of hydrogen produced by intestinal bacteria and various diseases, and this report discusses this relationship.

Most of the drugs used in modern medical treatments are symptomatic treatments and are far from being a cure for the diseases. The adverse effects are unavoidable in the drugs in modern medical treatments. Molecular hydrogen (H 2) has a remarkable therapeutic effect on various diseases, and many clinical studies have reported that H 2 has no adverse effects. Therefore, H 2 is a novel medical gas that is outside the concept of modern medical treatment. H 2, unlike drugs, works on the root of many diseases by scavenging the two kinds of strong reactive oxygen species, hydroxyl radical (·OH) and peroxynitrite (ONOO-). Since the H 2 alleviates the root of diseases and can treat many diseases at the same time, the medical application of H 2 may be called 'machine gun therapy.' In this review, we demonstrated that the root of many diseases is based on ·OH-induced oxidative stress in the mitochondria, and at the same time, the root of chronic inflammation is also attributed to ·OH.

<jats:p>This paper gives complete guidelines for authors submitting papers for the AIRCC Journals. A sliding puzzle is a combination puzzle where a player slides pieces along specific routes on a board to reach a certain end configuration. In this paper, we propose a novel measurement of the complexity of 100 sliding puzzles with paramodulation, which is an inference method of automated reasoning. It turned out that by counting the number of clauses yielded with paramodulation, we can evaluate the difficulty of each puzzle. In the experiment, we have generated 100 * 8 puzzles that passed the solvability checking by countering inversions. By doing this, we can distinguish the complexity of 8 puzzles with the number generated with paramodulation. For example, board [2,3,6,1,7,8,5,4, hole] is the easiest with score 3008 and board [6,5,8,7,4,3,2,1, hole] is the most difficult with score 48653.Besides, we have succeeded in obverse several layers of complexity (the number of clauses generated) in 100 puzzles. We can conclude that the proposed method can provide a new perspective of paramodulation complexity concerning sliding block puzzles.</jats:p>

This paper examines individual policies against the covid-19. The number of deaths due to COVID-19 can be divided by the population (in million) to score the performance of individual policies. 19 countries were investigated. Although many experts emphasize pharmaceutical methods including vaccines, the most effective policy against the covid-19 is based on a robust digital fence where the physical isolation strategy reveals the remarkable achievement for mitigating the pandemic. To mitigate and end the pandemic, combined policies with vaccination and digital fencing need to be used.

This study proposes SCORECOVID, a new Python Package Index (PyPI) for scoring individual policies against covid-19 and mitigating the pandemic. The new PyPI package consists of two modules. The first module automatically scrapes the latest information on the number of deaths and population by COVID-19 to score individual policies for a given country. The second module calculates the score by dividing the number of deaths by the population in millions. The Federal Communications Commission (FCC) in the US estimates the economic value of a statistical life to be $9.5 million per individual. The higher the number of deaths, the greater the economic loss. To use the best policies to reduce the number of deaths, we should adopt measures and methods from exceptional countries with high scores. The proposed method reveals two groups: a high-scored group and a low-scored group. The number of deaths is an indicator of economic and health policy scores. SCORECOVID is the world's first open-source policy scoring tool for COVID-19. It is designed to help many countries utilize state-of-the-art analytics methods to effectively mitigate the COVID-19 pandemic.

<jats:p>While many antitumor drugs have yielded unsatisfactory therapeutic results, drugs are one of the most prevalent therapeutic measures for the treatment of cancer. The development of cancer largely results from mutations in nuclear DNA, as well as from those in mitochondrial DNA (mtDNA). Molecular hydrogen (H2), an inert molecule, can scavenge hydroxyl radicals (·OH), which are known to be the strongest oxidizing reactive oxygen species (ROS) in the body that causes these DNA mutations. It has been reported that H2 has no side effects, unlike conventional antitumor drugs, and that it is effective against many diseases caused by oxidative stress and chronic inflammation. Recently, there has been an increasing number of papers on the efficacy of H2 against cancer and its effects in mitigating the side effects of cancer treatment. In this review, we demonstrate the efficacy and safety of H2 as a novel antitumor agent and show that its mechanisms may not only involve the direct scavenging of ·OH, but also other indirect biological defense mechanisms via the regulation of gene expression.</jats:p>

In general, preliminary or primary cost estimates are used to select contractors from among bidders in Japan. The primary cost estimate must be accurate, otherwise the contractor selected from the bidding process will lose profit. A general contractor in the world does not have a super-skilled engineer who can achieve the accurate primary cost estimates. The conventional primary estimate has a high error range and low reliability. An automated system converting detailed estimates to primary estimates has been highly demanded in the world. This paper presents a prototype AI converter that can accurately and automatically convert detailed cost estimates into primary estimates. Converting detailed cost estimates to primary estimates lies in a regression problem. This paper proposes a feature-elimination based data augmentation method for regression problems. The empirical experiment shows that the proposed data augmentation method is quite effective with an Extra-Trees ensemble method. The proposed method was empirically examined by using Colorado Department of Transportation (CDOT) dataset for accurately predicting constructions costs with the Extra-Trees algorithm and random forest algorithm respectively. The CDOT dataset is one and only one of the largest datasets available in public for constructions costs quotation/estimation of roads, bridges and buildings.

<jats:p>Mibyou, or pre-symptomatic diseases, refers to state of health in which a disease is slowly developing within the body yet the symptoms are not apparent. Common examples of mibyou in modern medicine include inflammatory diseases that are caused by chronic inflammation. It is known that chronic inflammation is triggered by the uncontrolled release of proinflammatory cytokines by neutrophils and macrophages in the innate immune system. In a recent study, it was shown that molecular hydrogen (H2) has the ability to treat chronic inflammation by eliminating hydroxyl radicals (·OH), a mitochondrial reactive oxygen species (ROS). In doing so, H2 suppresses oxidative stress, which is implicated in several mechanisms at the root of chronic inflammation, including the activation of NLRP3 inflammasomes. This review explains these mechanisms by which H2 can suppress chronic inflammation and studies its applications as a protective agent against different inflammatory diseases in their pre-symptomatic state. While mibyou cannot be detected nor treated by modern medicine, H2 is able to suppress the pathogenesis of pre-symptomatic diseases, and thus exhibits prospects as a novel protective agent.</jats:p>

Although intensity-modulated radiation therapy (IMRT) has been developed as an alternative to conventional radiotherapy, reducing bone marrow damage is limited. Thus, a novel technology is needed to further mitigate IMRT-induced bone marrow damage. Molecular hydrogen (H2) was recently reported as a preventive and therapeutic antioxidant that selectively scavenges hydroxyl radical (·OH) and peroxynitrite (ONOO-). This observational study aimed to examine whether H2gas treatment improves IMRT-induced bone marrow damage in cancer patients. The study was performed at Clinic C4 in Tokyo, Japan between May 2015 and November 2016. During this period, all enrolled patients received IMRT once per day for 1 to 4 weeks. After each time of IMRT, the patients of control group (n = 7, 3 men and 4 women, age range: 26-70 years) received mild hyperbaric oxygen therapy in health care chamber for 30 minutes, and the patients of H2group (n = 16, 8 men and 8 women, age range: 35-82 years) received 5% H2gas in health care chamber for 30 minutes once per day. Radiation-induced bone marrow damage was evaluated by hematological examination of peripheral blood obtained before and after IMRT, and the data were expressed by the ratio after to before treatment. The total number of radiation times and total exposure doses of radiation were similar between the control and H2groups. IMRT with health care chamber therapy significantly reduced white blood cells and platelets, but not red blood cells, hemoglobin and hematocrit. In contrast, H2gas treatment significantly alleviates the reducing effects of white blood cells and platelets (P = 0.0011 and P = 0.0275, respectively). Tumor responses to IMRT were similar between the two groups. The results obtained demonstrated that H2gas inhalation therapy alleviated IMRT-induced bone marrow damage without compromising the anti-tumor effects of IMRT. The present study suggests that this novel approach of H2gas inhalation therapy may be applicable to IMRT-induced bone marrow damage in cancer patients. The study protocol was approved by an Ethics Committee Review of Tokyo Clinic and Research Institute ICVS Incorporated (Tokyo, Japan) on February 1, 2019, and was registered in the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN ID: UMIN000035864) on February 20, 2019.

Although ionizing radiation (radiation) is commonly used for medical diagnosis and cancer treatment, radiation-induced damages cannot be avoided. Such damages can be classified into direct and indirect damages, caused by the direct absorption of radiation energy into DNA and by free radicals, such as hydroxyl radicals (•OH), generated in the process of water radiolysis. More specifically, radiation damage concerns not only direct damages to DNA, but also secondary damages to non-DNA targets, because low-dose radiation damage is mainly caused by these indirect effects. Molecular hydrogen (H2) has the potential to be a radioprotective agent because it can selectively scavenge •OH, a reactive oxygen species with strong oxidizing power. Animal experiments and clinical trials have reported that H2 exhibits a highly safe radioprotective effect. This paper reviews previously reported radioprotective effects of H2 and discusses the mechanisms of H2, not only as an antioxidant, but also in intracellular responses including anti-inflammation, anti-apoptosis, and the regulation of gene expression. In doing so, we demonstrate the prospects of H2 as a novel and clinically applicable radioprotective agent.