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MLH1 promoter hypermethylation predicts poorer prognosis in mismatch repair deficiency endometrial carcinomas.
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Aphasia testing (auditory comprehension domain) using a new eye tracking system in healthy participants
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Study on the Development of a Rock Identification System Using Artificial Intelligence and Spectral Imaging
Get PDF秋田大学博士（工学）It is imperative that one acknowledges that we now live in a digital age where almost every aspect of our daily lives produces an immense amount of data, with this, one may say the 21st century and those to come are and will be data-driven. With a closer look into the mining industry, trends show a steady but inevitable shift from traditional to modern digital methods. One may attribute this shift to a number of reasons such as the shortage of specialists in various fields within the mining industry, be it exploration, monitoring, maintenance, and processing amongst others. Also, there is a lessening desire to conduct on-sight investigations as health and safety regulations stiffen along with the necessity to distance human life from occupational mishaps. Lastly, traditional methods of delineating rocks and minerals may at times be thought of as subjective, which is an inherent part of procedures conducted by humans. For this reason, this study aims to provide solutions to these problems through the employment of artificially intelligent (AI) algorithms, which are known to be objective in their analysis. Coupled with spectral imaging techniques in the discrimination of rocks and minerals, the study was split into three main chapters, each covering the achievable potential advantages of employing AI-based classifications, hence solving the aforementioned problems.
The first aim was to combine two technologies to classify rocks; hyperspectral imaging, and artificial intelligence in the form of a one-dimensional deep learning convolution neural network (1D DL CNN). In order to classify rocks, visual imagery data generated using a hyperspectral camera was quantified in terms of how each captured image pixel responds across the electromagnetic spectrum, obtaining hyperspectral signatures of that particular rock. The second step involved running the hyperspectral signature data in a 1D CNN, application of this highly capable DL technique allows one to perform classification procedures with minimal error. The output results showed that the 1D CNN was capable of performing rock classifications via hyperspectral signatures as supported by the optimised (across three models) average per class prediction precision of 91.2% for all eight igneous rock lithologies employed in this part of the study.
Having realized the time, computational and data storage costs attained in solving the first aim, the second aim was thus an attempt to develop a method by which rock classification may be performed without these costs. This was achieved by integrating Hyperspectral Imaging, Neighbourhood Component Analysis (NCA) and Machine Learning (ML) as a combined system that can classify rocks. Modestly put, hyperspectral imaging gathers electromagnetic signatures of the rocks in hundreds of spectral bands. However, this data suffers from what is termed the ‘dimensionality curse’, which led to the employment of NCA as a dimensionality reduction technique. NCA, in turn, highlights the most discriminant feature bands, the number of which is dependent on the intended application(s) of the system. The study’s envisioned application was rock classification via specialized multispectral bands. Hence, the study performed a 204-band hyperspectral to 5-band multispectral reduction, the reason being, that current production drones are limited to five multispectral band sensors. Based on these bands, the study applied ML to identify and classify rocks, thereby supporting the study’s hypothesis, reducing computational costs, and attaining an average optimized ML classification accuracy of 91.2%.
The third aim was to investigate the potential use of drones in mining environments as a way in which data pertaining to the state of a site may be remotely collected. This aim proposes a combined system that employs a six bands multispectral image capturing camera mounted on an Unmanned Aerial Vehicle (UAV) drone, Spectral Angle Mapping (SAM), as well as AI. Unlike in the second aim, the 6 multispectral bands are factory pre-set, hence the employment of SAM to aid in pinpointing the spectra of sought after magnetite iron sands. Depth possessing multispectral data was captured at different flight elevations in an attempt to find the best elevation where remote identification via the UAV drone was possible. Data was analysed via SAM to deduce the cosine similarity thresholds at each elevation. Using these thresholds, AI algorithms were trained and tested to find the best performing model at classifying magnetite iron sand. Considering the post-flight logs, the spatial area coverage of 338 m2, a global classification accuracy of 99.7%, as well the per-class precision of 99.4%, the 20 m flight elevation outputs presented the best performance ratios overall.
In conclusion, the study emphasizes that the employment of AI-based spectral imaging methods in various aspects of the mining industry is necessary to ensure the continuation of a robust and future-proof rock and mineral classification practice. Lastly, data-driven classification practices are sustainable, easily optimizable, repeatable, and objective in their outputs, deeming the proposed systems viable for current and future industrial applications
Ground heat exchanger thermal imbalance prevention; feasibility, development, and implementation
Get PDF秋田大学博士（工学）This research presents the outcomes from two main objectives with the first being the creation of a novel design of integrating electrochromic glass window controls with a GSHP system for long-term op-timization and sustainability. For the first objective, a building energy model was developed and simu-lated with the solar heat gain coefficients of 0.41, 0.25, 0.15, and 0.09 to model electrochromic glass windows. The energy model outputs were used for ground heat exchanger model simulations which ana-lyzed 20-year temperature trends and system efficiencies. The results showed that the integrated GSHP system with electrochromic windows was feasible and a conceptual control sequence and design was developed. The annual cooling demand decreased by 32% between the clear glass and fully tinted state. It was recommended to increase the ground heat exchanger capacity to 200 boreholes at 45.7 m in 2040 to prevent overheating from projected climate change. The average system coefficient of performance was 7.6 for the fully tinted window state. The integrated GSHP system reduced CO2 emissions by 30% and the 30-year NPV was US$142,273.65 (-26%) cheaper compared to a conventional boiler and chiller system.
The second objective comprised of the development of a novel software and hardware package that dynamically predicts future ground heat exchanger temperatures to avoid thermal imbalance and future ground source heat pump system failure. An energy meter was installed on the ground heat exchanger of an office building and a software was created on a remote server that collected the measured data. The future ground temperature was dynamically calculated, and the prototype was integrated with the build-ing automation system to prevent future ground source heat pump system failure. The results showed that the building was cooling dominate and if the current mechanical system operation continued, the system would become inefficient in 16 years from high inlet temperatures to the heat pumps. A control sequence was developed for mitigating ground heat exchanger failure on the studied building. It was also determined by adjusting the set-point temperature of the make-up air unit from 12.8C to 4.8C, the amount of heating performed by the ground source heat pump system would increase from 81,122 kWh to 120,453 kWh which maintained the calculated 20-year ground heat exchanger temperature below 32C. The prototype developed in this paper is critical for maintaining an efficient ground source heat pump system and adequate ground heat exchanger temperatures. The outcome of the second objective provides the solution of ensuring a successful adoption of sustainable green technology on a large scale and eliminates ground source heat pump system failure due to thermal imbalance
Upper Cenozoic Calcareous Nannofossil Biostratigraphy and Basin Evolution of the East Java Basin Indonesia
Get PDF秋田大学博士（理学）The East Java Basin is one of Indonesian Cenozoic petroleum basin with fair
production for over a century. The East Java Basin is extensively filled with carbonate
and siliciclastic sedimentary rock since Eocene. Several studies exhibit comprehensive
explanation of the depositional system of the East Java Basin during Cenozoic, most of
the age of the sedimentary rock has not been well-dated and only a few researchers had
conduct precise age dating. Biostratigraphy of several exploration wells in the East Java
Basin also had been studied for both planktic foraminifera and calcareous nannofossil
by. However, the areas studied are limited and some of the results have not indicated
the high resolution. Based on that problem, the calcareous nannofossil biostratigraphy
of LSM-1, JTR-1, BEL-1, TPN-1, KTB-1, and NGB-1 wells located in the onshore East
Java Basin, Indonesia was studied in detail to clarify the age distribution of sedimentary
rocks and the history of basin evolution of the onshore East Java Basin.
Total of 678 cutting samples was selected every 20m interval and processed using
the smear slide preparation method. All smear slides were examined under an Olympus
binocular polarizing microscope and quantitative analysis was employed. Graphic
correlation also applied to derive precise biostratigraphic correlation.
A total of 71 species from 26 genera of calcareous nannofossil were determined
in the seven wells, most of the specimens are found at moderate to good preservation.
Reworked specimens from early Miocene series are sometimes observed in the Pliocene
series. The age assignment based on 27 calcareous nannofossil datum were obtained as
follow: DDR-1 corresponds to NN3-NN15 of the early Miocene to the early Pliocene.
NGB-1 are appointed to NP23 to NN7 of the early Oligocene to the late Miocene. KTB-
1 is assigned to NP25-NN16 of the late Oligocene to the late Pliocene. TPN-1 covers
NN7-NN16 of the middle Miocene to the early Pliocene. BEL-1 is estimated as NN3 to
NN5 of the early to middle Miocene. of JTR-1 is assigned to NP23-NN4 of the early
Oligocene to early Miocene. And the last, LSM-1 is estimated corresponding to NP25-
NN16 of the late Oligocene to early Pliocene.
The result from the biostratigraphic correlation analysis indicates that a total of
four significant unconformities are traceable in the sequence between the Oligocene and
the Pliocene in this area. The Oligo-Miocene Unconformity (OMU) is situated in the
Oligocene/early Miocene boundary. The OMU, which is traceable to all wells, is
characterized by the missing of the interval from NN1 to NN3 zone of the early Miocene.
The Mid-Miocene Unconformity (MMU) is correlated to the early-middle Miocene
which is found only in KTB-1 and NGB-1, since the calcareous nannofossil zone of
NN6 is not present in these wells. The late Miocene Unconformity (LM1), which is
characterized by the missing of the interval NN8 of the early late Miocene is traceable
to KTB-1, DDR-1, and TPN-1. The Mio-Pliocene Unconformity (MPU), which is the
biggest unconformity found in the study area, is situated in the lower Pliocene base. In
this area, the lower Pliocene NN14 sediment is distributed above the MPU. The time
gap of the MPU is the biggest in LSM-1 and BEL-1 located in the north western area.
The interval, NN6 to NN13 of the middle Miocene to the lowest Pliocene is missing in
LSM-1, and NN8-NN13 is also missing in NGB-1.
Based on the bio-lithostratigraphic correlation analysis, the results indicate that
the sediment above the OMU is situated relatively in the centre of the studied area (BEL-
1 and TPN-1). In contrast with sediment of the Miocene above the MMU and LM1
which are concentrated in the central to south-southeast area, the location of Pliocene
sediment above the MPU moves to the north and north-western area. The depositional
pattern also demonstrates that the majority of sandstone and limestone deposition is
linked to the distribution of unconformities, which are located just above them. During
the middle to late Miocene, there is no evidence of sedimentation in the north and
northwest. The thickest sandstones, which are reservoir rocks of this oil field, is
correlated to the early Pliocene Low System Tract and Transgressive System Tract
above the MPU.
The stratigraphic series and unconformities detected in the study area show a good
correlation to the global climatic events and tectonic evolution. The Oligocene Series is
correlated to the late Oligocene warm event. The Miocene Series unconformably overlie
the Oligocene Series and fit to the Mi 1 cooling event. The early Miocene series above
the Oligo-Miocene Unconformity is correlated to the Mid-Miocene climatic optimum
event. The Mid-Miocene Unconformity may be correlated to the cooling events Mi3 or
Mi4 just after the Mid-Miocene Climatic Optimum. The middle-late Miocene sequence
between the Mid-Miocene Unconformities and the Late Miocene Unconformity 1 is
considered a single transgressive-regressive cycle. The Late Miocene Unconformity 1
is correlated to the cooling event of Mi5. The Mio-Pliocene Unconformity is correlated
to the Messinian Salinity Crisis event and RMKS Uplift. The upper-lower Pliocene
series above the unconformity is correlated to the mid-Pliocene Warm Period. These
results indicate that the stratigraphic evolution and formation of the unconformities
detected in the East Java Basin during upper Cenozoic are strongly influenced by
eustacy sea-level changes, and then by tectonics, especially in the late Miocene to the
Quaternary
Severity of Depressive Symptoms is Associated with Venous Thromboembolism in Hospitalized Patients with a Major Depressive Episode
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Risk factors for spinal cord ischemia in frozen elephant trunk–induced upper spinal cord ischemia in patients with combination of degenerative arch aneurysms and peripheral artery diseases: a possible mechanism
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Does the Addition of Abiraterone to Castration Affect the Reduction in Bone Mineral Density?
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Hydrothermal Alteration and Fluid Evolution of the Deep Grasberg Porphyry System, Papua, Indonesia
Get PDF秋田大学博士（理学）The giant Grasberg Cu-Au-(Mo) deposit is one of the world’s largest porphyry Cu
deposit located in Indonesia, which hosts 32 million metric tons of copper and 96 million
ounces of gold. The deposit is contained in two overlapping porphyry systems: Gajah
Tidur Cu-Mo-(Au) and Main Grasberg Cu-Au. The Grasberg Block Cave reserve that lies
beneath the Grasberg open pit has recently been associated with the Gajah Tidur (GT)
porphyry that is older than the shallower Main Grasberg (MG) porphyry system. This
study is intended to confirm and delineate the existence of GT porphyry in the Grasberg
Cu-Au-(Mo) deposit, decipher the hydrothermal fluid evolution, and optimize the wholerock geochemistry as well as chemical variation of GT porphyry white micas to develop exploration vectoring tools for the deep-seated porphyry Cu deposits.
Dating of hydrothermal biotite and muscovite by K-Ar method revealed that the GT
porphyry system is ~300 k.y. older than the shallower MG porphyry system, which
formed at 3.1 ± 0.05 Ma. The age-depth relationships between the GT and MG porphyry
systems suggest there was an accumulation of volcanic rocks in between the two porphyry events, associated with growth of a ~0.5 to 1 km high stratovolcano prior the formation of MG porphyry system. The configuration of alteration patterns and associated mineralization, supported by hydrothermal biotite and muscovite ages, indicates that all white mica assemblages and more than 70% of Cu, Mo, and Au contained in the Grasberg Block Cave reserve are associated with the GT porphyry system.
Sulfur isotope study shows that the evolution of GT hydrothermal fluid is initiated
by the formation of K-feldspar-biotite at a temperature as high as 590 °C. Cooling of this
fluid from ~460° to ~370 °C allowed the formation of white mica-dominated alteration,
which is associated with various amounts of anhydrite, chlorite, chalcopyrite, and pyrite.
Based on the anhydrite and chlorite abundances, this white mica assemblage can be subdivided into muscovite-anhydrite-chlorite and muscovite-chlorite-anhydrite, both of
which contain remnant hydrothermal biotite. The muscovite-quartz ± pyrophyllite
assemblage associated with covellite-pyrite mineralization formed in the outer part of the muscovite-anhydrite-chlorite alteration zone at a lower temperature range (340-280 °C).
Based on mineral chemistry and infrared spectroscopy analysis, the muscoviteanhydrite-
chlorite white micas are characterized by high Na, Fe, Ti, and V concentrations,
and mainly display short-wave infrared Al-OH absorption wavelengths of 2,203-2,208
nm. The muscovite-chlorite-anhydrite white micas have distinctly higher Mg content than the other two GT white mica assemblages but similar Al-OH absorption wavelengths to the muscovite-anhydrite-chlorite white micas. The muscovite-quartz ± pyrophyllite white micas have low Na, Fe, Mg, and Ti, but relatively high Si, Al, and F, and Al-OH absorption wavelengths are largely shorter than 2,202 nm. The amounts of Si and Al contained in the GT white micas allow occupancy of other cations, particularly Fe and Mg in octahedral lattice sites and cause variations in their short-wave infrared Al-OH absorption wavelengths.
Three decades of exploration and geologic studies of the giant Grasberg Cu-Au-(Mo)
deposit provide information that is relevant to porphyry exploration globally. The
existence of GT porphyry below the shallower MG porphyry system reveals that there is
potential for nearby porphyry deposits at depth beneath the already discovered porphyry Cu districts. Taking an example from the deep-seated GT porphyry system, the wholerock geochemical anomaly of F, V, W, and Sn, and the white mica short-wave infrared Al-OH wavelength lie in between ~2,200 and ~2,215 nm can be integrated with other geological and geophysical information to locate the centre of porphyry Cu systems
