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Right ventricular (RV) dysfunction and its linked arrhythmias play a crucial role in determining the prognosis of pulmonary arterial hypertension (PAH). Our paper aimed to explore the potential protective effects of direct pharmacological intervention in the RV muscle using dantrolene (DAN), a stabilizer of the cardiac ryanodine receptor (RyR2), against RV dysfunction and arrhythmia in a rat model of monocrotaline (MCT)-induced PAH. To induce PAH, male 8-week-old Sprague-Dawley rats received MCT injections. The study also assessed the induction of ventricular tachycardia (VT) by catecholamines, examining RyR2-mediated Ca^{2+} release properties in isolated cardiomyocytes. Additionally, a pulmonary artery-banding model was established to evaluate the independent effects of chronic pressure overload on RV morphology and function. In the MCT-induced PAH rat model, findings revealed RV hypertrophy, dilation, and functional decline, resulting in 0% survival rate two months post-MCT induction. Conversely, chronic DAN treatment demonstrated improvements in these RV parameters and an 80% increase in survival. Furthermore, chronic DAN treatment prevented the dissociation of calmodulin from RyR2, inhibiting Ca^{2+} sparks and spontaneous Ca^{2+} transients in MCT-induced hypertrophied RV cardiomyocytes. Epinephrine induced VT in over 50% of rats with MCT-induced PAH, while chronic DAN treatment achieved complete suppression of VT. The paper concludes that stabilizing RyR2 with DAN holds promise as a novel therapeutic approach against the development of RV dysfunction and fatal arrhythmias associated with PAH.

Many mail filtering methods have been proposed, but they have not yet achieved perfect filtering. One of the reasons for this is the influence of modified words created by spammers to slip through the mail filtering, in which words are modified by insert symbols, spaces, HTML tags, etc. For example,“ price$ for be$t drug$! ”，“ priceC I A L I S ”， “ <font>se</font>xu<font>al</font> ”, etc. These are frequently replaced with new strings by changing the combination of symbols ,HTML tags etc. Mail filtering is a technique that captures trends in words in training mails (mails received in the past) and applies these trends to words in test mails (newly received emails). Some of the above modified words appear in both training and test mails, i.e., words that could be used as features of spam mail by using them unprocessed, while others appear only in test mails, i.e., words that have not been learned and require special processing (e.g., removal of symbols, search for similar words, etc.) for their use. However, existing methods do not make these distinctions and treat them in the same way. Therefore, in order to bring the filtering performance of the existing methods closer to perfect filtering, we developed a method in which the above modified words are separated into words that appear in both training and test mails and words that appear only in test mails, and each of these words is used for mail filtering. In this study, we treat the above modified words as ”strange words”. Typical examples of such strange words include, in addition to the above, new words included in ham mails, proper nouns used in close relationships, and abbreviations. The results of this study are as follows (1) In order to compare the filtering performance between strange words and other words, filtering experiments were conducted using existing methods with strange words, nouns, verbs, and adjectives. The results showed that the filtering performance of the strange words was the best. This means that strange words have a significant impact on the filtering performance, and we expect to improve the filtering performance of existing methods by developing a new method to utilize strange words. (2) In order to examine the breakdown of strange words, we counted the number of words that appeared in both training and test mails, and the number of words that appeared only in test mails. The results were compared with those obtained for nouns, verbs and adjectives. We found that there are a significant number of strange words that appear in both training and test mails, but only in one of the groups, i.e., ham or spam mail. Words with this appearance pattern are most useful for mail filtering. On the other hand, we found that there are many strange words that appear only in test mails, i.e., words that cannot be learned. We expect to improve the filtering performance by separating these strange words and developing a new method to use each of them. (3) For the use of strange words, we developed (A) a method for using words that appear in both training and test mails, and (B) a method for using words that appear only in test mails, respectively. (A) To examine the breakdown of strange words that appear in both training and test mails, we divided them into two categories: words that appear only in ham and spam mails, i.e., words with patterns that improve filtering performance, and words that do not, and examined their frequency of occurrence. The results showed that the words with appearance patterns that improve filtering performance tend to appear more frequently than those without such patterns. This means that by using words with a certain number of occurrences in filtering, it is possible to use more words that improve filtering performance. We developed a method to do this and conducted experiments with different threshold values to find the optimal value, and confirmed that setting the threshold around 7 improves filtering performance. (B) We compared the number of strange words that appear only in the test mails between ham and spam mails, and found that the number tends to be higher in spam mail than in ham mail. In order to utilize this difference for filtering, we proposed a method to set a uniform spam probability for strange words that appear only in the test mails, and attempted to find the optimal spam probability. As a result, setting the spam probability to 0.7 improved the filtering accuracy from 98.2% to 98.9%. By using (A) and (B) above together, both words that appear in both training and test mails and words that appear only in test mails can be used for mail filtering to increase accuracy. Mail filtering has been improved and its performance has reached its limit. In order to further improve accuracy, i.e., to approach perfect filtering, a new perspective is needed, and this paper provides one such perspective: the use of strange words. This paper is organized as follows. In Chapter 1, we review the background of mail filtering methods, discuss how spammers use strange words to slip through such filters. The purpose and structure of this paper are then presented. In Chapter 2, we will discuss related research on examples of filtering methods that have been proposed so far are given. In Chapter 3, we describe the mail datasets, word handling, and strange words used in the this paper. This is followed by an explanation of the ROC curve, which is the measure used to evaluate the filtering performance, and explanation of scatter plots and box-and-whisker plots. In Chapter 4, we compare the filtering performance between strange words and other words, and show that strange words have a significant impact on the filtering performance. Furthermore, based on the results of a breakdown of the number of strange words, we discuss the possibility of improving filtering performance by separating words that appear in both training and test mails from those that appear only in the test mails. We will work on this in the next chapters and report the results. In Chapter 5, we develop a method to use (A) above, i.e., strange words that appear in both training and test mails. From the results of counting the number of words used in the subject and body of each email, we show that the number tends to be smaller for words that degrade the filtering performance. Based on these results, we propose a method that sets a threshold for the number of words used in the subject and body of mails, and uses only those words that exceed the threshold for classification. Experiments are conducted to find the optimal value by varying the threshold, and the effect of this method on performance is reported. In Chapter 6, we develop a method to use (B) above, i.e., strange words that appear only in the test mails. We compare the number of types of these words in ham and spam mails, and show that the number tends to be larger in spam mails, and that this feature can be used as a bias for detecting spam mails. In this paper, we deal with experiments using bsfilter and develop a method to set spam probabilities uniformly for strange words that appear only in the test mails. After searching for the optimal spam probability, we report that a spam probability of 0.7 greatly improves the filtering performance. In Chapter 7, we describes the processing flow combining the methods developed in Chapter 5 and Chapter 6. The paper is then summarized, including future prospects.

Steel truss bridges, which are one of the bridge structures applicable to long spans, are widely used as marine bridges connecting mainland and remote island. Since such steel truss bridges are built on the sea, they are exposed to severe corrosive environment due to the influence of airborne salt. In addition, there are many parts where it is not easy to inspect to detect abnormalities, so it is more difficult to eliminate the risk of member damage in such steel truss bridges than in general bridges. On the other hand, once the marine bridges are built, they become an indispensable facility for the life of the island. Therefore, if there are no other traffic routes to access an island, the sustainability of the marine bridge is an important issue that is directly linked to the sustainability of the remote island life. When member damage occurs in a steel truss bridge, it depends on redundancy, which means the margin for the load-bearing capacity and load-bearing function, whether the damage develops into chain damage or remains limited damage. Bridges with redundancy could be restored by repairing even if the member damages occurred, because they did not develop into chain damages. In some cases, vehicles could pass through with traffic restrictions. Although redundancy is an important performance for maintaining life on remote islands that have no alternative traffic routes, there are few studies on evaluation and improvement methods of redundancy for long steel truss bridges used for marine bridges. The purpose of this study is to propose a method for improving the redundancy of long steel truss bridges, and three research subjects are set to achieve this purpose. The first study subject is the investigation of the effect of truss joint modeling on redundancy evaluation, and is the subject to appropriately evaluate the redundancy of steel truss bridges. The second is also the subject related to the redundancy evaluation of steel truss bridges, and is the development of dynamic response calculation method that considers the vibration characteristics of steel truss bridges, which are vibration systems with multiple degrees of freedom. The third study subject is a proposal for methods to improve the redundancy of long steel truss bridges. This paper consists of five chapters. Chapter 1 is an introduction, and describes the background of the research, the setting of the purpose and research subjects, and the previous studies. Chapter 2 describes the study on the modeling of the truss joint. In the analysis of healthy steel truss bridges with no member damage, the sectional forces can be calculated appropriately even with analysis modeling in which frame elements of truss members are rigidly connected at the truss joints, simply. On the other hand, in the redundancy analysis of steel truss bridges with member damages, it is shown that it is necessary to consider the shape of the gusset plates at the truss joints in analysis modeling. Chapter 3 describes the study on the calculation method of dynamic response caused by damage of truss members. There are cases where the dynamic response due to member damage is calculated in the same way as a single-degree-of-freedom vibration system. However, this study develops a dynamic response calculation method considering the vibration characteristics of long steel truss bridges by using the eigenvector of steel truss bridges with member damage. A method is proposed to set the magnitude of the eigenvector using balance equation of the work given to the steel truss bridge by the sectional force unloaded from damaged member and the strain energy stored in the steel truss bridge. In addition, a method is proposed to calculate the dynamic response by setting the range of vibration modes using the sum of effective mass ratio, and selecting the eigenvector that has the greatest effect on the dynamic response for each member. It is shown that the proposed calculation method gives redundancy evaluation closer to time-history-response analysis than the method that calculates the dynamic response in the same way as a single-degree-offreedom vibration system. Chapter 4 describes the study on redundancy improvement for a long steel truss bridge. A combination of the countermeasure against members that trigger chain damage and the countermeasure against members with insufficient load-bearing capacity is planned. Analysis clarifies that the X bracing, which is a reinforcing structure in X shape, is an efficient reinforcement that works against multiple member damage cases as the countermeasure against the trigger member of member chain damage. Also, the load-bearing capacity is verified by a loading test of specimens with reinforced structures. Since the subject bridge has 18 truss panels where X bracing can be installed, the placement patterns were examined by the optimization method. It is clarified that the weight of reinforcing material can be reduced by installing X-braces only at four truss panels in the alternating areas, rather than installing at all 18 truss panels. Chapter 5 describes the summary of this study and future developments.

アミノグリコシド系抗菌薬は有害反応として聴覚障害をきたすことがあり、蝸牛基底回転の外有毛細胞が障害されやすいことが知られている。本研究では、ネオマイシンの有毛細胞障害に対するアスタキサンチンナノ製剤の保護効果を検討した。ネオマイシンを加えたCBA/Nマウスの卵形嚢培養に対し、培養液にアスタキサンチンナノ製剤を投与した群では有毛細胞の減少および酸化ストレスが有意に抑制された。さらに、アスタキサンチンナノ製剤の鼓室内投与を行い音響曝露前後の聴性脳幹反応（ABR）閾値の変化、有毛細胞減少率を評価した。アスタキサンチン投与群では音響曝露後のABR閾値変化、有毛細胞減少率が抑制される傾向が見られた。血液内耳関門の存在により、鼓室内投与に適した薬剤は限られるが、アスタキサンチンナノ製剤の形態は正円窓膜を浸透する可能性があり、内耳障害抑制の効果を有する可能性が示唆された。

The development and implementation of industrial policy are essential in shaping a country’s economic landscape. It promotes industrialization, which, in turn, generates employment opportunities, enhances productivity, and diversifies the economy. the present dissertation studies the subject of industrial policy, with a particular emphasis on resource allocation and computable general equilibrium in Ghana. Chapter 2 delves into the concept of industrial policy and its implementation in Africa in general, and Ghana, in particular. First, we examine Ghana’s past experience with industrial policy implementation and the reasons for its inability to attain the desired outcomes. Subsequently, in response to the call for a return to industrial policy, we argue in favor of a renewed implementation of industrial policy in Ghana. We posit that the likelihood of success is significantly higher with the benefit of better institutions. Chapter 3 examines the subjects of firm-level productivity, productivity distribution, and resource allocation. In the first instance, we decompose labor productivity in Ghana and draw the conclusion that within-sector resource allocation primarily drives productivity growth, with structural change playing a limited role. Next, we analyze the gross allocative effect, finding evidence that resources are migrating toward sectors of lower productivity. Finally, we also examine productivity distribution through the lens of the power law distribution, establishing that firms involved in international trade exhibit higher levels of aggregation. Thus, allocating resources to such firms leads to greater productivity, thereby minimizing resource misallocation. Chapter 4 presents a dynamic recursive computable general equilibrium for Ghana, employing a Social Account Matrix (SAM) with 2015 as the benchmark year, and we conclude this chapter with a brief analysis of SAM. Chapter 5 examines several possible simulation scenarios. We build our simulations around two industrial policy strategies: labor-intensive and capital-intensive, furthermore our simulation is informed by Ghana’s industrial policy plan. We analyze various policies such as efficiency improvement, trade protection, free trade, and taxation policy. We conclude that capital-intensive industrialization would work better under a free trade policy. Moreover, we discovered that the cost of protecting labor-intensive industries is less than the cost of safeguarding capital-intensive industries. We conclude the dissertation with a discussion of the implications of our findings. we aim to provide a comprehensive discussion of the implications of our findings, as well as acknowledge the limitations of our study and propose potential avenues for further research. By doing so, we hope to contribute to the existing body of knowledge in our field and inspire future researchers to expand upon our work.

Since social infrastructure, which was intensively developed during the high economic growth period,will deteriorate all at once in the future, maintenance and management of facilities will be an issue in thefuture. Currently, facility inspection records are based on paperbased forms, and are not premised onautomatic processing by computer. The authors have developed the “Smart Chosa” and realized a databaseof facility inspections and a GIS System. The Smart Chosa was able to record the location of the inspectionphoto on a two dimensional map, but because it was necessary to approach the deformed part when takingthe inspection photo, it was not possible to grasp the position, direction, and size of the entire facility.Therefore, we applied 3D GIS to Smart Chosa for sabo dams, created a 3D model from photographs takenon site, and conducted research to manage inspection results on the 3D model. This study summarizes the results of research on management of inspection photographs on a 3D GISin order to improve the efficiency of management of inspection photographs of sabo facilities. This thesisconsists of 6 chapters, and the main content of each chapter is as follow. [Chapter 1: Introduction] In this chapter, the current status and issues of the maintenance and management of socialinfrastructure in Japan were summarized. Utilization of 3D models for maintenance and management ofcivil engineering facilities, high-precision positioning used for alignment of 3D models, efficientinspection of concrete structures, and existing research trends on iPhone LiDAR applications wereorganized. On that basis, the purpose and points of focus of this research were organized, and the structureand outline of this paper were described. [Chapter 2: Comparison of 3D models and examination of application to sabo facilities maintenance management system] In this chapter, three types of models, a BIM/CIM model, a 3D point cloud model, and a 3D surfacemodel, are compared and examined as 3D models to be applied to the maintenance management system.The problem setting in this chapter is the selection of a 3D model to be used in this system. The constraintis that the Sabo dams including the existing dam can be modeled in 3D. At present, there are few BIM/CIMmodels for sabo dams, so when applying to existing sabo dams, we believe that a 3D surface model thatcan be created by SfM/MVS technology from photographs taken by UAVs will be useful. The 3D modelin the research was a 3D surface model. Knowledge about the 3D model that can be applied to the sabo facility maintenance managementsystem and knowledge for utilizing the 3D model in the 3D GIS were obtained. [Chapter 3: Performance evaluation of RTK receiver used for Sabo facility investigation support system] In this chapter, a survey of high-precision positioning technology necessary for positioning 3D modelsof sabo dams and inspection photos on a 3D GIS, and evaluation of positioning performance in sabo damsand surrounding forests are conducted. The problem setting in this chapter is whether or not locationinformation can be acquired during surveys of Sabo facilities, and accuracy verification. The constraintis that real-time high-precision positioning is required using inexpensive and small devices inenvironments that are unfavorable for satellite positioning (such as sabo dams and forests). It was confirmed that the multi-band receiver whose performance was evaluated has a horizontalvariation of 22 mm (2DRMS) even in a poor environment where about 70% of the sky directly below thesabo dam is covered. It was confirmed that the method can be applied to aligning 3D models ofphotographs. [Chapter 4: Investigation of image synthesis for creation of sabo dams inspection image] In this chapter, as a basic examination of 3D model creation, the image synthesis method is organized.The problem setting in this chapter is normalization and image combination necessary for synthesizinginspection photographs (2D). The constraint is that the inspection photography equipment is a smartphonefor field survey. In the feature point detection method for image synthesis, we compared two types offeature amounts, SIFT feature amount and AKAZE feature amount, and confirmed the accuracy byexperiments. In addition, RANSAC was used as an outlier removal method. By combining these methods,we performed image synthesis using multiple photographs of the concrete surface of the sabo dam. [Chapter 5: 3D model creation by SfM/MVS and application to 3D GIS] The problem setting in this chapter is a superimposed display of a 3D Sabo dam model and inspectionphotographs. The constraint is that the equipment that can be used to create a 3D model of inspectionphotographs is limited to equipment (compact and lightweight) that can be brought by local workers. Inthis chapter, we first present an overview of the "smart chosa" system that expands the scope of applicationfrom 2D to 3D in this research. After that, we investigated SfM/MVS processing to create a 3D surfacemodel. By creating a 3D model of the sabo dam and a 3D model of inspection photos by SfM/MVSprocessing, and importing them into a 3D GIS, we succeeded in superimposing the sabo dam andinspection photos on a 3D map. In addition, we examined a method of creating a 3D surface model using the iPhone LiDARapplication that can perform 3D measurement using the LiDAR function installed from iPhone12Pro. Wecompared the 3D model created with the iPhone LiDAR app and the 3D model created using MetaShape,a software that implements SfM/MVS processing, and confirmed the image resolution and positionalaccuracy for use as inspection photographs. In order to incorporate the created 3D model into 3D GISsoftware, we examined a method for matching the orientation and position, and actually superimposedthe 3D model of the sabo dam and the 3D model of the inspection photograph on the 3D GIS. I haveconfirmed that it is possible. [Chapter 6: Summary] In this chapter, a summary of the results obtained in Chapters 2 to 5 and future issues were discussed. The result of this research is a visualization method that makes it easy for people other than fieldinvestigators to understand the situation of the site by importing 3D surface models acquired by variousmethods into 3D GIS. 3D surface models include SfM models created from photos taken with aUAV/smartphone, SfM models created from photos taken with a handheld RTK rover, and 3D modelscreated with the iPhone LiDAR app. By using this method, it is possible to grasp the deformation position and deformation direction of thesabo dam in 3D space, and by superimposing the photographs of each inspection, it is possible to graspthe change over time.

Japan's declining birthrate and aging population are difficult to resolve in the short term, and the working-age population, which refers to the population aged 15 to 65, continues to decline. On the other hand, mental illness patients are increasing in the working age population. The medical side, which is responsible for treatment, is required to improve efficiency by reforming the way doctors work. Therefore, expectations are placed on psychotherapy performed at home for the purpose of effective treatment of the working-age population. In this study, neurofeedback, which is one of the psychological therapies, was taken up, and applied equipment development and verification were carried out for its implementation at home. In this study, as a preclinical stage, measures were verified based on measurements of general cooperators. Neurofeedback (NFB) is considered to be one of psychotherapy using electroencephalogram signals, and is a psychotherapy that visualizes one's own electroencephalogram and self-controls the visualized electroencephalogram. It is attracting attention because it is a non-drug therapy and provides neuromodulation. NFB is being investigated for many clinical applications. The target diseases are diverse, including chronic pain, ADHD, depression, and mood disorders. However, we believe that there are four tasks to ensure the effectiveness of this therapy. Task 1 is overcoming the difficulty of installing electroencephalogram electrodes. NFB is considered to be a therapy that affects the plasticity of the cranial nerves, and is a therapy that actively promotes the development of neural networks, and is expected to be highly effective if the training frequency is high. It is necessary to be able to perform it at home, and it is required that electroencephalogram electrodes can be easily installed. Therefore, we made a prototype of an electroencephalogram headset with bipolar gel electrodes, and as a result of trial verification with children, we were able to confirm the electroencephalogram signals of 30 people aged 5 to 20 years old. Analysis of the recorded electroencephalogram revealed an age-dependent left-brain tendency in β waves, etc., confirming consistency with previous findings. Task 2 is determining the brain wave derivation part of the NFB training target. For electroencephalography, lead electrodes are usually placed in the scalp, but it is difficult to place the electrodes in the scalp by yourself. There is a need to consider forehead derivation for easy EEG electrode placement at home. There are regional differences in EEG waveforms within the forehead, and it is necessary to select the most appropriate extraction site. For NFB, we explored the optimal site based on the correlation with the top of the head, which is usually the electroencephalogram derivation position. Next, we performed an EEG network analysis at the time of NFB using the EEG derived from the top of the head and the EEG derived from the optimal forehead region, and analyzed the difference in the brain network during NFB due to the difference in the derivation region. For the second task, we explored the optimal site for deriving brain waves from the forehead, and proved that NFB from the brain waves derived from this site works on the same network as NFB from the brain waves derived from the top of the head. Task 3 is a method of selecting an electroencephalogram frequency band to be derived and self-controlled in NFB therapy (training target electroencephalogram frequency band). In previous studies, the EEG frequencies targeted for NFB therapy are diverse and not standardized. Even for the same disease, various electroencephalogram frequency bands are selected and NFB is performed. A personalized frequency band decision is made according to the patient's pathology and condition. In order to make the frequency band determination method more logical, we thought it necessary to determine the electroencephalogram frequency for therapy from the comparison of the basic rhythms of healthy subjects and patients. In this study, we created an electroencephalogram basic rhythm evaluation program and collected electroencephalogram basic rhythm data from randomly selected subjects. The electroencephalogram basic rhythm evaluation program consists of 7 stages. Eyes open stage, Eyes closed stage, 0Back stage, Rest1 stage, 2Back stage, Rest2 stage, Healing Picture stage. Changes in brain waves occur due to external stimuli such as eye opening and eye closing, concentration, and relaxation. An electroencephalogram basic rhythm evaluation program was created considering multiple stimuli that affect electroencephalogram dynamics. The usefulness of this program was confirmed as a preliminary examination of the dominant fluctuation region and network analysis by topographic analysis during the execution of the electroencephalogram basic rhythm evaluation program. EEG basic rhythm brain standard program electroencephalogram measurements were carried out for 89 subjects recruited from the general public, and a database was created. Using the forehead optimally measured parts (left and right) obtained in Task 2 as electroencephalogram derivation parts, a significant difference test was performed for each electroencephalogram frequency band Power value and content rate of each stage of the electroencephalogram basic rhythm evaluation program. The α Power value increased 2.52 times when the eyes were closed, and the θ Power value increased 1.67 times during 2 Back compared to 0 Back. We examined the possibility of clinical application by analyzing the correlation between the score of the questionnaire used in clinical diagnosis and the electroencephalogram component. The questionnaires used were mainly CSI (CENTRAL SENSITIZATION INVENTORY), and POMS2 (Profile of Mood States 2). Task 4 is NFB scoring. Continuation of psychotherapy requires a score as a reward to be visualized. We compared the two scores, the time ratio score and the amplitude ratio score, analyzed the correlation between the questionnaire used in task 3 and the two scores, and examined the optimal score. In results, the frequency band that correlates better with psychological activity during NFB was suggested SMR. Some of the psychological scales included the data probably above the general average level, which might have provided hypotheses at the preclinical stage. 4 tasks were conducted to demonstrate the technical requirements and effectiveness evaluation for the practical application of cognitive psychological training NFB, which is expected to be used with high frequency at home for children to working-age adults. The technological requirements and effectiveness evaluation for the practical application of NFB are presented. This research attempted four tasks and realized the possibility of frequent NFB training at home for patients from children to productive age. As a preclinical stage, it was a study within a range that can be resolved as a stage of policy verification based on the general participant study. In the future, the efficacy of this study will be further evaluated by comparing it with clinical data in the area of mental illness such as depression and developmental disorders, including chronic pain. In the future, the effectiveness of this study will be further evaluated by comparison with clinical data in the area of chronic pain and other mental illnesses such as depression and developmental disorders.

Open source software (OSS) are adopted as embedded systems, server usage, and so on because of quick delivery, cost reduction, and standardization of systems. Therefore, OSS is often used not only for the personal use but also for the commercial use. Many OSS have been developed under the peculiar development style known as the bazaar method. According to this method, many faults are detected and fixed by developers around the world, and the fixed result will be reflected in the next release. Also, many OSS are developed and managed by using the fault big data recorded on the bug tracking systems. Then, many OSS are developed and maintained by several developers with many OSS users. According to the results of the 2022 Open Source Security and Risk Analysis (OSSRA), OSS is an essential part of proprietary software, e.g., the source code containing OSS is 97%, all source code using OSS is 78%. On the other hand, OSS has issues from various perspectives. Therefore, OSS users need to decide on whether they should use OSS with consideration of each issue. In addition, the managers of open source projects need to manage their projects appropriately because OSS has a large impact on software around the world. This thesis focuses on the following three issues among many ones. We examine a method for OSS users and open source project managers to evaluate the stability of open source projects. 1. Selection evaluation and licensing: Methods for OSS users to make selections from the many OSS available situation, 2. Vulnerability support: Predicted fault fix priority for the reported OSS, 3. Maintenance and quality assurance: Prediction of appropriate OSS version upgrade timing, considering the development effort required after OSS upgrade by OSS users. In “1. Selection evaluation and licensing,” we attempt to derive the OSS-oriented EVM by applying the earned value management (EVM) to several open source projects. The EVM is one of the project management methodologies for measuring the project performance and progress. In order to derive the OSS-oriented EVM, we apply the stochastic models based on software reliability growth model (SRGM) considering the uncertainty for the development environment in open source projects. We also improve the method of deriving effort in open source projects. In case of applying the existing method of deriving effort in open source projects, it is not possible to derive some indices in the OSS-oriented EVM. Thus, we resolve this issue. The derived OSSoriented EVM helps OSS users and open source project managers to evaluate the stability of their current projects. It is an important to use the decision-making tool regarding their decisions and projects of OSS. From a different perspective, we also evaluate the stability of the project in terms of the speed of fault fixing by predicting the time transition of fixing the OSS faults reported in the future. 2. In “Vulnerability support”, in terms of open source project managers, we create metrics to detect faults with a high fix priority and predicted a long time for fixing. In addition, we try to improve the detection accuracy of the proposed metrics by learning not only the specific version but also the bug report data of the past version by using the random forest considering the characteristic similarities of bugs fix among different versions. This allows the project managers to identify the faults that should be prioritized for fixing when a large number of faults are reported, and facilitates project operations. In “3. Maintenance and quality assurance”, as an optimum maintenance problem, we predict the appropriate OSS version-up timing considering the maintenance effort required by OSS users after upgrading the OSS. It is dangerous in terms of the vulnerability to continue using the specified version of OSS ignoring the End of Life. Therefore, we should upgrade the version periodically. However, the maintenance cost increase with the version upgrade frequently. Then, we find the optimum maintenance time by minimizing the total expected software maintenance effort in terms of OSS users. In particular, we attempt to reflect the progress of open source projects by using the OSS-oriented EVM in deriving the optimal maintenance time. In conclusion, we found that there is the applicability as the stability evaluation of open source projects from three perspectives. Particularly, the OSS-oriented EVM discussed in “1. Selection evaluation and licensing” can contribute to the visualization of maintenance effort in open source projects. The proposed method will potentially contribute to the development of OSS in the future.

Hyperspectral (HS) imaging can capture the detailed spectral signature of each spatial location of a scene and leads to better understanding of different material characteristics than traditional imaging systems. However, existing HS sensors can only provide low spatial resolution images at a video rate in practice. Thus reconstructing high-resolution HS (HR-HS) image via fusing a low-resolution HS (LR-HS) image and a high-resolution RGB (HR-RGB) image with image processing and machine learning technique, called as hyperspectral image super resolution (HSI SR), has attracted a lot of attention. Existing methods for HSI SR are mainly categorized into two research directions: mathematical model based method and deep learning based method. Mathematical model based methods generally formulate the degradation procedure of the observed LR-HS and HR-RGB images with a mathematical model and employ an optimization strategy for solving. Due to the ill-posed essence of the fusion problem, most works leverage the hand-crafted prior to model the underlying structure of the latent HR-HS image, and pursue a more robust solution of the HR-HS image. Recently, deep learning-based approaches have evolved for HS image reconstruction, and current efforts mainly concentrated on designing more complicated and deeper network architectures to pursue better performance. Although impressive reconstruction results can be achieved compared with the mathematical model based methods, the existing deep learning methods have the following three limitations. 1) They are usually implemented in a fully supervised manner, and require a large-scale external dataset including the degraded observations: the LR-HS/HR-RGB images and their corresponding HR-HS ground-truth image, which are difficult to be collected especially in the HSI SR task. 2) They aim to learn a common model from training triplets, and are undoubtedly insufficient to model abundant image priors for various HR-HS images with rich contents, where the spatial structures and spectral characteristics have considerable difference. 3) They generally assume that the spatial and spectral degradation procedures for capturing the LR-HS and HR-RGB images are fixed and known, and then synthesize the training triplets to learn the reconstruction model, which would produce very poor recovering performance for the observations with different degradation procedures. To overcome the above limitations, our research focuses on proposing the unsupervised learning-based framework for HSI SR to learn the specific prior of an under-studying scene without any external dataset. To deal with the observed images captured under different degradation procedures, we further automatically learn the spatial blurring kernel and the camera spectral response function (CSF) related to the specific observations, and incorporate them with the above unsupervised framework to build a high-generalized blind unsupervised HSI SR paradigm. Moreover, Motivated by the fact that the cross-scale pattern recurrence in the natural images may frequently exist, we synthesize the pseudo training triplets from the degraded versions of the LR-HS and HR-RGB observations and themself, and conduct supervised and unsupervised internal learning to obtain a specific model for the HSI SR, dubbed as generalized internal learning. Overall, the main contributions of this dissertation are three-fold and summarized as follows: 1. A deep unsupervised fusion-learning framework for HSI SR is proposed. Inspired by the insights that the convolution neural networks themself possess large amounts of image low-level statistics (priors) and can more easy to generate the image with regular spatial structure and spectral pattern than noisy data, this study proposes an unsupervised framework to automatically generating the target HS image with the LR-HS and HR-RGB observations only without any external training database. Specifically, we explore two paradigms for the HS image generation: 1) learn the HR-HS target using a randomly sampled noise as the input of the generative network from data generation view; 2) reconstructing the target using the fused context of the LR-HS and HR-RGB observations as the input of the generative network from a self-supervised learning view. Both paradigms can automatically model the specific priors of the under-studying scene by optimizing the parameters of the generative network instead of the raw HR-HS target. Concretely, we employ an encoder-decoder architecture to configure our generative network, and generate the target HR-HS image from the noise or the fused context input. We assume that the spatial and spectral degradation procedures for the under-studying LR-HS and HR-RGB observation are known, and then can produce the approximated version of the observations by degrading the generated HR-HS image, which can intuitively used to obtain the reconstruction errors of the observation as the loss function for network training. Our unsupervised learning framework can not only model the specific prior of the under-studying scene to reconstruct a plausible HR-HS estimation without any external dataset but also be easy to be adapted to the observations captured under various imaging conditions, which can be naively realized by changing the degradation operations in our framework. 2. A novel blind learning method for unsupervised HSI SR is proposed. As described in the above deep unsupervised framework for HSI SR that the spatial and spectral degradation procedures are required to be known. However, different optical designs of the HS imaging devices and the RGB camera would cause various degradation processes such as the spatial blurring kernels for capturing LRHS images and the camera spectral response functions (CSF) in the RGB sensors, and it is difficult to get the detailed knowledge for general users. Moreover, the concrete computation in the degradation procedures would be further distorted under various imaging conditions. Then, in real applications, it is hard to have the known degradation knowledge for each under-studying scene. To handle the above issue, this study exploits a novel parallel blind unsupervised approach by automatically and jointly learning the degradation parameters and the generative network. Specifically, according to the unknown components, we propose three ways to solve different problems: 1) a spatial-blind method to automatically learn the spatial blurring kernel in the capture of the LR-HS observation with the known CSF of the RGB sensor; 2) a spectral-blind method to automatically learn the CSF transformation matrix in the capture of the HR-RGB observation with known burring kernel in the HS imaging device; 3) a complete-blind method to simultaneously learn both spatial blurring kernel and CSF matrix. Based on our previously proposed unsupervised framework, we particularly design the special convolution layers for parallelly realizing the spatial and spectral degradation procedures, where the layer parameters are treated as the weights of the blurring kernel and the CSF matrix for being automatically learned. The spatial degradation procedure is implemented by a depthwise convolution layer, where the kernels for different spectral channel are imposed as the same and the stride parameter is set as the expanding scale factor, while the spectral degradation procedure is achieved with a pointwise convolution layer with the output channel 3 to produce the approximated HR-RGB image. With the learnable implementation of the degradation procedure, we construct an end-toend framework to jointly learn the specific prior of the target HR-HS images and the degradation knowledge, and build a high-generalized HSI SR system. Moreover, the proposed framework can be unified for realizing different versions of blind HSI SR by fixing the parameters of the implemented convolution as the known blurring kernel or the CSF, and is highly adapted to arbitrary observation for HSI SR. 3. A generalized internal learning method for HSI SR is proposed. Motivated by the fact that natural images have strong internal data repetition and the crossscale internal recurrence, we further synthesize labeled training triplets using the LR-HS and HR-RGB observation only, and incorporate them with the un-labeled observation as the training data to conduct both supervised and unsupervised learning for constructing a more robust image-specific CNN model of the under-studying HR-HS data. Specifically, we downsample the observed LR-HS and HR-RGB image to their son versions, and produce the training triplets with the LR-HS/HR-RGB sons and the LR-HS observation, where the relation among them would be same as among the LR-HS/HR-RGB observations and the HR-HS target despite of the difference in resolutions. With the synthesized training samples, it is possible to train a image-specific CNN model to achieve the HR-HS target with the observation as input, dubbed as internal learning. However, the synthesized labeled training samples usually have small amounts especially for a large spatial expanding factor, and the further down-sampling on the LR-HS observation would bring severe spectral mixing of the surrounding pixels causing the deviation of the spectral mixing levels at the training phase and test phase. Therefore, these limitations possibly degrade the super-resolved performance with the naive internal learning. To mitigate the above limitations, we incorporate the naive internal learning with our selfsupervised learning method for unsupervised HSI SR, and present a generalized internal learning method to achieve more robust HR-HS image reconstruction.

Generalized pustular psoriasis (GPP) is a rare form of psoriasis, which is characterized by sudden onset of repeated erythema and pustule formation with generalized inflammation. Recent advances in molecular genetics have led to the identification of several genes associated with GPP, including IL36RN, CARD14, AP1S3, SERPINA3, and MPO. Of these, only limited cases of GPP have been reported to carry mutations in the AP1S3, SERPINA3, or MPO to date. In the present study, we investigated a Japanese patient with GPP and found a bi-allelic missense mutation c.1769G>T (p.Arg590Leu) in the MPO gene. Structural analysis predicted that the mutant MPO protein would abolish its ability to bind with heme protein. In vitro studies using cultured cells revealed that the mutant MPO was stably expressed, but completely lost its myeloperoxidase activity. Immunohistochemistry (IHC) using an anti-MPO antibody showed markedly-reduced expression of MPO protein in the patient’s skin, suggesting that the mutation would lead to an instability of the MPO protein in vivo. Finally, IHC with an anti-citrullinated Histone H3 antibody demonstrated a sparse formation of neutrophil extracellular traps within a Kogoj's spongiform pustule of the patient’s skin. Collectively, we conclude that the c.1769G>T (p.Arg590Leu) in the MPO is a complete loss-of-function mutation associated with GPP in the patient. Our data further underscore critical roles of the MPO gene in the pathogenesis of GPP.