cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2019.1442
title: Multi-objective emergency nurse scheduling with combined hospital policies and individual preference

description: Emergency healthcare services are essentially important since they involve emergency life-threatening health or accident cases. The emergency room (ER) must operate 24 hours every day. During off-hours, all cases are also handled by ER nurses and physicians since the Out-Patient Department (OPD) is closed. The quality of emergency healthcare services depends on both the sufficient number of personnel, work experience, and work schedules. In each planning horizon (e.g., each month), work schedules of ER nurses need to be generated for all shifts. The result work schedules have to satisfy the hospital’s policy and regulations, the regulations set forth by the professional society, and other relevant constraints. Specifically, the factors to be considered include the number of shifts per day, number of shifts per month, number of regular working shifts per nurse, work experience of the nurse, number of ER nurses per shift, preferred working shifts, etc. In Thailand, work schedules of ER nurses are manually generated by Heads of ER nurses without the use of any specialized software program. This proposed research is intended to study and focus on the ER Nurse scheduling problem by developing a multi-objective mathematical model (MO) to generate the work schedules of ER nurses based on the given goals and both soft and hard constraints according to the relevant regulations, policies, and personal requests. An efficient heuristic algorithm will be constructed to generate a near-optimal ER Nurse scheduling solution. A decision support system (DSS) program will be developed to help generate alternative work schedules based on the requirements of the hospital and the preference of the ER nurses. The responsible person (i.e., Head ER Nurse) can then evaluate several work schedules and select the most preferred one. As a result, the resulting work schedules consume a significant amount of valuable time to generate and are usually subject to several revisions. Consequently, the effectiveness and responsiveness of emergency healthcare services can be affected. Using the DSS, it is expected that the implemented work schedules will satisfy most of the constraints and personal requests and will enhance the emergency healthcare services of the hospital.
DOI: 10.14457/tu.the.2019.1443
title: Breast cancer detection by active contour models based on the fusion of a conventional ultrasound image with elasticity and doppler images

description: Active contour models are an effcient method for breast cancer segmentation on an ultrasound (US) image. There are two types of active contour models, which are parametric active contours (snakes) and geometric or geodesic active contours (level sets). This dissertation studies how the fusion of a conventional ultrasound image with elastography and Doppler images was used to improve the performance of active contours for breast cancer segmentation, especially, snake and level set methods. Snakes have been widely used for breast cancer segmentation. However, the methodscould produce inaccurate results if the seeds are initialized improperly (far from the true boundaries and close to the false boundaries). Therefore, we propose a novel initialization method based on the fusion of a conventional US image with elasticity and Doppler images.The combined information extracted from the three types of images provided better initialization and consequently leaded to better segmentation. The proposed fusion method (FM) has been tested against four state-of-the-art initialization methods on 90 ultrasound images from a database collected by the Thammasat University Hospital of Thailand. The groundtruth was hand-drawn by three leading radiologists of the hospital. The reference methods were: center of divergence (CoD), force field segmentation (FFS), Poisson inverse gradient vector flow (PIG), and quasi-automated initialization (QAI). Using a variety of measures,our numerical tests proved the following advantages of the FM. Region-based level sets methods were also extensively applied for breast cancer segmentationon the US images. Regard to the region-based, their segmentation results aremultiple contours. Consequently, the proposed FM method was adapted to enhance their performance for breast cancer detection. The output contours from level sets combined withthe useful features from the FM method were used to develop the breast cancer contour classification model. The support vector machine (SVM) was utilized for binary classifying either correct breast cancer contour or non-breast cancer contour. The binary classifier showedeffective results for breast cancer detection. The proposed model has been tested with three well-known region-based level sets on 60 ultrasound images dataset which was selectedfrom the 90 ultrasound images. The verified level set methods were: distance regularized level set evolution (DRLSE), fuzzy clustering and lattice Boltzmann method (FCLBM), and online region-based active contour model (ORACM). From the experimental results, breast cancer contours were detected correctly using the proposed classifier applied on top of the combination of the FM and the verified level set methods.
DOI: 10.14457/tu.the.2019.1444
title: Novel determination of convective heat transfer coefficient via seebeck effect: an application to thermoelectric anemometer

description: For heat and mass transfer in thermal processes, convective heat transfer is the main mechanism of heat transfer from solid to fluid media in the presence of bulk motion. When fluid passes a solid surface due to an external driving force, this is called "forced convection". In contrast, when fluid moves due to density differences caused by a temperature variation in the fluid, this is called "free convection" or "natural convection". According to Newton’s law of cooling, the rate of heat flow through a fluid is determined by the convective heat transfer coefficient. The convective heat transfer coefficient is usually derived as a constant parameter from empirical correlations for given flow conditions. The convective heat transfer coefficient is a temperature-dependent parameter under variant operating conditions. Also, it strongly depends on the speed of air, which changes with respect to time. The determination of the convective heat transfer coefficient for air under actual convection processes is proposed by using thermoelectric modules. Based on the Seebeck effect and energy balance, voltage signals are mathematically related to the convective heat transfer coefficient in real-time. The effectiveness of the proposed thermoelectric modules in determining the convective heat transfer coefficient in a real-time implementation is presented in this research. The methodology can be generalized by further developing applications for the thermoelectric module.The convective heat transfer coefficient strongly depends on the speed of air. The speed of air or wind speed can be determined when the convective heat transfer coefficient is known. The principle of the Seebeck effect is applied for quantifying the convective heat transfer coefficients of airflow over two thermoelectric modules. The modules are embedded on the vertical wall and the horizontal wall within a small air passage. According to dimensional analysis, the convective heat transfer coefficients depend strongly on wind speed. Wind speeds are systematically determined from the Seebeck voltages of the thermoelectric modules. A prototype of a thermoelectric anemometer is implemented, to measure the wind speeds within a wind tunnel and under open field conditions. The results confirm that there is good agreement between the wind speed measurements from the proposed thermoelectric anemometer and the conventional measurements of wind speed, carried out in a wind tunnel and in open field conditions.
DOI: 10.6084/m9.figshare.14585895
title: Additional data Linked genotype and phenotype data of fine-mapping

description: Linked genotype and phenotype data of fine-mapping
DOI: 10.6084/m9.figshare.14585895.v1
title: Additional data Linked genotype and phenotype data of fine-mapping

description: Linked genotype and phenotype data of fine-mapping
DOI: 10.34808/1rzj-wp41
title: Income obtained according to particular rates only by taxpayers conducting non-agricultural business activity in 2016

description: A special form of income taxation addressed to the SME sector is the Lump sum on registered income, which is a simplified form of income tax payment for natural persons conducting business activity.The choice of this form of taxation is optional. In 2016, the tax in this form could be paid by taxpayers who in 2015 obtained income from non-agricultural economic activity conducted exclusively independently or income from the sale of non-industrial processed plant and animal products from their own cultivation, breeding or breeding, in the amount not exceeding the equivalent of EUR 150,000 (PLN 636,555) or obtained income only from non-agricultural business activities conducted in the form of a company, and the sum of revenues of the company's partners from this activity did not exceed the amount of EUR 150,000 (PLN 636,555).
DOI: 10.34808/mkr1-re22
title: Split-beam echosounder data from Puck Bay autumn 2018 Part II

description: The acoustic data was collected in 2018, in the Bay of Puck, in the seasons: autumn. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected at a designated study area not far from the city of Hel and on the route Hel - Gdynia while the ship was sailing. Additional, data was collected during the sunrise and sunset, while the ship was anchored not far from the city of Hel. To ensure data quality, echosounders were calibrated and passive noise was measured.
DOI: 10.5517/ccdc.csd.cc26sqvl
title: CCDC 2049560: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26sqwm
title: CCDC 2049561: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26sqxn
title: CCDC 2049562: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26sqyp
title: CCDC 2049563: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26v0qt
title: CCDC 2050796: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0rv
title: CCDC 2050797: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0sw
title: CCDC 2050798: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0tx
title: CCDC 2050799: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0vy
title: CCDC 2050800: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0wz
title: CCDC 2050801: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26v0x0
title: CCDC 2050802: Experimental Crystal Structure Determination

description: Related Article: Mark D. Straub, Liane M. Moreau, Yusen Qiao, Erik T. Ouellette, Michael A. Boreen, Trevor D. Lohrey, Nicholas S. Settineri, Stephan Hohloch, Corwin H. Booth, Stefan G. Minasian, John Arnold|2021|Inorg.Chem.|60|6672|doi:10.1021/acs.inorgchem.1c00471
DOI: 10.5517/ccdc.csd.cc26x7cr
title: CCDC 2052924: Experimental Crystal Structure Determination

description: Related Article: Louise M. Cañada, Johanna Kölling, Zhili Wen, Judy I-Chia Wu, Thomas S. Teets|2021|Inorg.Chem.|60|6391|doi:10.1021/acs.inorgchem.1c00103
DOI: 10.5517/ccdc.csd.cc26x7gv
title: CCDC 2052927: Experimental Crystal Structure Determination

description: Related Article: Louise M. Cañada, Johanna Kölling, Zhili Wen, Judy I-Chia Wu, Thomas S. Teets|2021|Inorg.Chem.|60|6391|doi:10.1021/acs.inorgchem.1c00103
DOI: 10.5517/ccdc.csd.cc26x7ky
title: CCDC 2052930: Experimental Crystal Structure Determination

description: Related Article: Louise M. Cañada, Johanna Kölling, Zhili Wen, Judy I-Chia Wu, Thomas S. Teets|2021|Inorg.Chem.|60|6391|doi:10.1021/acs.inorgchem.1c00103
DOI: 10.5517/ccdc.csd.cc26yk0r
title: CCDC 2054184: Experimental Crystal Structure Determination

description: Related Article: Fengying Liang, Kazuo Eda, Takashi Okazoe, Akihiro Wada, Nobuaki Mori, Katsuhiko Konishi, Akihiko Tsuda|2021|J.Org.Chem.|86|6504|doi:10.1021/acs.joc.1c00334
DOI: 10.5517/ccdc.csd.cc26yl4x
title: CCDC 2054219: Experimental Crystal Structure Determination

description: Related Article: Fengying Liang, Kazuo Eda, Takashi Okazoe, Akihiro Wada, Nobuaki Mori, Katsuhiko Konishi, Akihiko Tsuda|2021|J.Org.Chem.|86|6504|doi:10.1021/acs.joc.1c00334
DOI: 10.5517/ccdc.csd.cc26yw57
title: CCDC 2054499: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26yw68
title: CCDC 2054500: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26yw79
title: CCDC 2054501: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26yw8b
title: CCDC 2054502: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26yw9c
title: CCDC 2054503: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26ywbd
title: CCDC 2054504: Experimental Crystal Structure Determination

description: Related Article: Claudia Heindl, Eugenia V. Peresypkina, Gábor Balázs, Eric Mädl, Alexander V. Virovets, Manfred Scheer|2021|Chem.-Eur.J.|27|7542|doi:10.1002/chem.202100203
DOI: 10.5517/ccdc.csd.cc26znc7
title: CCDC 2055249: Experimental Crystal Structure Determination

description: Related Article: Fan Chen, Lei Zhao, Xingdong Wang, Qingqing Yang, Weili Li, Hongkun Tian, Shiyang Shao,Lixiang Wang, Xiabin Jing, Fosong Wang|2021|Sci.China.Chem.|64|547|doi:10.1007/s11426-020-9944-1
DOI: 10.5517/ccdc.csd.cc26znd8
title: CCDC 2055250: Experimental Crystal Structure Determination

description: Related Article: Fan Chen, Lei Zhao, Xingdong Wang, Qingqing Yang, Weili Li, Hongkun Tian, Shiyang Shao,Lixiang Wang, Xiabin Jing, Fosong Wang|2021|Sci.China.Chem.|64|547|doi:10.1007/s11426-020-9944-1
DOI: 10.5517/ccdc.csd.cc26znf9
title: CCDC 2055251: Experimental Crystal Structure Determination

description: Related Article: Fan Chen, Lei Zhao, Xingdong Wang, Qingqing Yang, Weili Li, Hongkun Tian, Shiyang Shao,Lixiang Wang, Xiabin Jing, Fosong Wang|2021|Sci.China.Chem.|64|547|doi:10.1007/s11426-020-9944-1
DOI: 10.5517/ccdc.csd.cc26zsjj
title: CCDC 2055378: Experimental Crystal Structure Determination

description: Related Article: Wen-Ya Lu, Yong You, Ting-Ting Li, Zhen-Hua Wang, Jian-Qiang Zhao, Wei-Cheng Yuan|2021|J.Org.Chem.|86|6711|doi:10.1021/acs.joc.1c00453
DOI: 10.5517/ccdc.csd.cc27156p
title: CCDC 2056701: Experimental Crystal Structure Determination

description: Related Article: Julia Beerhues, Robert R. M. Walter, Hannes Aberhan, Maren Neubrand, Marre Porré, Biprajit Sarkar|2021|Organometallics|40|1077|doi:10.1021/acs.organomet.1c00057
DOI: 10.5517/ccdc.csd.cc27157q
title: CCDC 2056702: Experimental Crystal Structure Determination

description: Related Article: Julia Beerhues, Robert R. M. Walter, Hannes Aberhan, Maren Neubrand, Marre Porré, Biprajit Sarkar|2021|Organometallics|40|1077|doi:10.1021/acs.organomet.1c00057
DOI: 10.5517/ccdc.csd.cc27158r
title: CCDC 2056703: Experimental Crystal Structure Determination

description: Related Article: Julia Beerhues, Robert R. M. Walter, Hannes Aberhan, Maren Neubrand, Marre Porré, Biprajit Sarkar|2021|Organometallics|40|1077|doi:10.1021/acs.organomet.1c00057
DOI: 10.5517/ccdc.csd.cc271b0n
title: CCDC 2056850: Experimental Crystal Structure Determination

description: Related Article: Yuan-Bo Wu, Cheng Xiong, Qing-Yan Liu, Jian-Guo Ma, Feng Luo, Yu-Ling Wang|2021|Inorg.Chem.|60|6472|doi:10.1021/acs.inorgchem.1c00196
DOI: 10.5517/ccdc.csd.cc271b1p
title: CCDC 2056851: Experimental Crystal Structure Determination

description: Related Article: Yuan-Bo Wu, Cheng Xiong, Qing-Yan Liu, Jian-Guo Ma, Feng Luo, Yu-Ling Wang|2021|Inorg.Chem.|60|6472|doi:10.1021/acs.inorgchem.1c00196
DOI: 10.5517/ccdc.csd.cc271svy
title: CCDC 2057310: Experimental Crystal Structure Determination

description: Related Article: Garrit Wicker, Roland Schoch, Jan Paradies|2021|Org.Lett.|23|3626|doi:10.1021/acs.orglett.1c01018
DOI: 10.5517/ccdc.csd.cc271swz
title: CCDC 2057311: Experimental Crystal Structure Determination

description: Related Article: Garrit Wicker, Roland Schoch, Jan Paradies|2021|Org.Lett.|23|3626|doi:10.1021/acs.orglett.1c01018
DOI: 10.5517/ccdc.csd.cc273kwt
title: CCDC 2059016: Experimental Crystal Structure Determination

description: Related Article: Zhizhou Chen, Xiangwen Kong, Shengtong Niu, Shuang Yang, Jinggong Liu, Bolai Chen, Benlong Luo, Changyu Zhou, Chenglin Ding, Xinqiang Fang|2021|Org.Lett.|23|3403|doi:10.1021/acs.orglett.1c00870
DOI: 10.5517/ccdc.csd.cc273kxv
title: CCDC 2059017: Experimental Crystal Structure Determination

description: Related Article: Zhizhou Chen, Xiangwen Kong, Shengtong Niu, Shuang Yang, Jinggong Liu, Bolai Chen, Benlong Luo, Changyu Zhou, Chenglin Ding, Xinqiang Fang|2021|Org.Lett.|23|3403|doi:10.1021/acs.orglett.1c00870
DOI: 10.5517/ccdc.csd.cc277gdc
title: CCDC 2062752: Experimental Crystal Structure Determination

description: Related Article: Ioannis Spanopoulos, Ido Hadar, Weijun Ke, Peijun Guo, Eve M. Mozur, Emily Morgan, Shuxin Wang, Ding Zheng, Suyog Padgaonkar, G. N. Manjunatha Reddy, Emily A. Weiss, Mark C. Hersam, Ram Seshadri, Richard D. Schaller, Mercouri G. Kanatzidis|2021|J.Am.Chem.Soc.|143|7069|doi:10.1021/jacs.1c01727
DOI: 10.21227/p2p9-er60
title: PHDIndic_11: page-level handwritten document image dataset of 11 official Indic scripts

description: Without publicly available dataset, specifically in handwritten document recognition (HDR), we cannot make a fair and/or reliable comparison between the methods. Considering HDR, Indic script’s document recognition is still in its early stage compared to others such as Roman and Arabic. In this paper, we present a page-level handwritten document image dataset (PHDIndic_11), of 11 official Indic scripts: Bangla, Devanagari, Roman, Urdu, Oriya, Gurumukhi, Gujarati, Tamil, Telugu, Malayalam and Kannada. PHDIndic_11 is composed of 1458 document text-pages written by 463 individuals from various parts of India. Further, we report the benchmark results for handwritten script identification (HSI). Beside script identification, the dataset can be effectively used in many other applications of document image analysis such as script sentence recognition/understanding, text-line segmentation, word segmentation/recognition, word spotting, handwritten and machine printed texts separation and writer identification.
DOI: 10.5519/qd.h249497w
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (729 records)
DOI: 10.15468/n6y978
title: A case of gynandromorphy in Ducetia japonica (Thunberg, 1815) (Orthoptera Tettigoniidae: Phaneropterinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Huang, Jiang-Rong, Liu, Yun-Fei, He, Zhu-Qing (2021): A case of gynandromorphy in Ducetia japonica (Thunberg, 1815) (Orthoptera Tettigoniidae: Phaneropterinae). Zootaxa 4970 (1): 182-188, DOI: https://doi.org/10.11646/zootaxa.4970.1.10
DOI: 10.5281/zenodo.4755958
title: PhenCards v.1.0.0 database

description: A db-release of PhenCards to coincide with the release of the paper This is a citable repo with a zip file of everything used to make the Elasticsearch Lucene index database for PhenCards v1.0.0. This includes all data, like HPO, ICD, UMLS (without restricted sources), IRS data, Open990 data. Because of Open990, we cannot make it commercially available, but it is still fully open source for academics. However, we also provide the code for preprocessing of the data for Lucene indexing.
DOI: 10.15151/esrf-es-447102393
title: test scan of styrene-butadiene rubber

description: microtom cut sample of styrene-butadiene rubber will be scanned
DOI: 10.15151/esrf-es-441721775
title: Optimisation for nano-imaging of Alzheimer’s neuritic plaques

description: Alzheimer’s disease is characterized by deposition of amyloid # (A#) plaques and intraneuronal neurofibrillary tangles (NFT) in brain tissues. Accumulation of NFT made of hyperphosphorylated fibrillar forms of the tau (#) protein correlates with decline of the cognitive function. These changes are likely related to dramatic perturbations in the homeostasis of Fe and other metals. Our aim is to assess at &lt;50 nm resolution the changes in elemental composition in the brain tissue at the level of amyloid plaques as a function of # accumulation. For this we require to perform preliminary tests that will be beneficial in the final proposal. The tests will be done to optimise the sample thickness and exposure times to reveal maximum detail.
DOI: 10.26255/heal.5fh6-7qxu
title: Municipality boundaries (Cleisthenes)