Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying uncertainty for AWARE characterization factors

Although it is not yet current practice in life cycle assessment, it is recommended that impact assessment methods be accompanied by their uncertainty data to better guide the decision maker. This work uses the best available information to assess uncertainty of the AWARE model for water scarcity and corresponding sensitivities of input parameters. An uncertainty estimate for the AWARE characterization factors (CFs) is provided via (1) arrays (5000 values per CF) with statistics, (2) dispersion analysis, and (3) distribution best fit and parameters. Results show that uncertainty, represented by the dispersion of the values, varies significantly around the world and tends to be more important in regions of higher scarcity and low in most regions around the world (area based) in terms of absolute spread. Globally, values of 18.8 and 66.28 are found for the spread, represented by the interpercentile range (95%) and interquartile range (25–75%), respectively. The lognormal distribution shows the best fit for most regions around the world and could be used as a default distribution. Two parameters come out as influential: actual water availability (because of precipitation uncertainty) and the global hydrological model itself (because of the variability of results obtained from different models). When compared with uncertainty associated with spatio‐temporal variability, uncertainties found in this work are generally lower, and hence improving resolution in water scarcity assessments (to monthly and watershed levels) should remain the priority. Finally, required data for software integration of AWARE uncertainty are provided. This article met the requirements for a Gold‐Gold JIE data openness badge described at http://jie.click/badges.
Prediksi Status Pinjaman Bank dengan Deep Learning Neural Network

Penilaian risiko pada penentuan status pinjaman merupakan proses yang penting dalam usaha simpan pinjam. Prediksi dalam mengklasifikasikan apakah nasabah akan melunasi atau tidak akan menentukan pengambilan keputusan dan tindaklanjutnya yang berdampak pada kinerja entitas dalam menjalankan usahanya. Berbagai teknik dalam prediksi status pinjaman dengan machine learning diterapkan dengan hasil yang meningkat dalam akurasi dan performance. Metode Deep Learning Neural Network (DNN) merupakan salah satu metode machine learning yang sekarang ini memiliki peran penting di era big data dimana data yang besar, dengan kemampuan mesin yang mumpuni dan kompleksitas pada suatu fitur mampu ditangani oleh DNN. Penelitian ini memvariasikan beberapa arsitektur dan parameter dalam pembangunan model DNN dengan score yang terbaik. Pengujian terhadap dataset bank loan status dengan metode DNN menghasilkan akurasi 82.27% tidak lebih baik dari metode SVM dengan hasil akurasi 84%. Namun metode DNN masih lebih baik dibandingkan dengan metode lainnya. Karena penggunaan variasi arsitektur dan parameter DNN tidak berpengaruh signifikan dalam menghasilkan score terbaik. Data yang diproses benar-benar diperlukan pemrosesan lebih lanjut sebelum dilakukan pemodelan.
Integrative Analysis of Multimodal Biomedical Data with Machine Learning

With the rapid development in high-throughput technologies and the next generation sequencing (NGS) during the past decades, the bottleneck for advances in computational biology and bioinformatics research has shifted from data collection to data analysis. As one of the central goals in precision health, understanding and interpreting high-dimensional biomedical data is of major interest in computational biology and bioinformatics domains. Since significant effort has been committed to harnessing biomedical data for multiple analyses, this thesis is aiming for developing new machine learning approaches to help discover and interpret the complex mechanisms and interactions behind the high dimensional features in biomedical data. Moreover, this thesis also studies the prediction of post-treatment response given histopathologic images with machine learning.Capturing the important features behind the biomedical data can be achieved in many ways such as network and correlation analyses, dimensionality reduction, image processing, etc. In this thesis, we accomplish the computation through co-expression analysis, survival analysis, and matrix decomposition in supervised and unsupervised learning manners. We use co-expression analysis as upfront feature engineering, implement survival regression in deep learning to predict patient survival and discover associated factors. By integrating Cox proportional hazards regression into non-negative matrix factorization algorithm, the latent clusters of human genes are uncovered. Using machine learning and automatic feature extraction workflow, we extract thirty-six image features from histopathologic images, and use them to predict post-treatment response. In addition, a web portal written by R language is built in order to bring convenience to future biomedical studies and analyses.In conclusion, driven by machine learning algorithms, this thesis focuses on the integrative analysis given multimodal biomedical data, especially the supervised cancer patient survival prognosis, the recognition of latent gene clusters, and the application of predicting post-treatment response from histopathologic images. The proposed computational algorithms present its superiority comparing to other state-of-the-art models, provide new insights toward the biomedical and cancer studies in the future.
Removal of Soluble Proteins during Fermentation Process for Improving Textural Properties of Traditional Thai Rice Noodles, Kanom-jeen

Traditional Thai fermented rice noodles called Kanom-jeen are characterized by a unique flavor and pleasing texture, and widely consumed as a staple food in Thailand and throughout the Indochina region. This study aimed to determine the effect of the fermentation process on rice noodle protein content and composition, and the relationship to Kanom-jeen texture. The protein content of rice flour decreased during the fermentation process. SDS-PAGE showed that the protein bands at 2033 kDa, representing protein body-II (PB-II) disappeared during rice fermentation, while the bands around 13 kDa representing protein body-I (PB-I) remained. Microstructural analysis of noodles demonstrated that unfermented Kanom-jeen was composed of cluster-like structures of PB-II proteins, while fermented Kanom-jeen contained only uniformly spherical protein bodies of PB-I in starch gel. Both results give the product a stronger texture. Therefore, the fermentation process is necessary during Kanom-jeen preparation to obtain the desired specific texture. Discipline: Food Additional key words: enzymatic modification; protein composition, microscopy This work was conducted within the framework of an international collaborative research project entitled “Establishment of food value chain through value-addition of local food resources for sustainable rural development” and supported by the Japan International Research Center for Agricultural Sciences (JIRCAS). *Corresponding Author: e-mail tadashi@affrc.go. jp Received 26 October 2016; accepted 4 April 2017. Introduction Kanom-jeen is a traditional fermented rice noodle, popularly consumed as a staple food in Thailand. Similar rice noodles are also prevalent in other food cultures in the Indochina region, such as Bun (Vietnam), Nom Banvuchock (Cambodia), Khao Bun (Laos) and Mohinga (Myanmar). In Thailand, two types of Kanom-jeen (nonfermented and fermented) are commercially available. Consumers prefer fermented Kanom-jeen, however, due to its unique flavor and textural characteristics (Oupathumpanont et al. 2008, Pisitkul & Rengpipat 2014). The traditional preparation of Kanom-jeen involves
Banking and Economic Growth: Comparison between Islamic and Conventional Banking in Malaysia

This study investigates the contribution of conventional banking and Islamic banking to economic growth in Malaysia. Return on assets, return on equity representing the profitability, total deposit, representing bank development, and several indicators such as total government expenditure, trade openness, and gross fixed capital formation were independent variables. In contrast, the dependent variable was GDP per capita. The study utilised secondary data collected from the Fitch Connect database and Datastream database. This study used a sample of 10 Islamic banking and 10 Conventional banking. The study found that the Islamic banking system variable can influence Malaysia's economic growth. ROA and Ltdep are found significant and have positive effect to economic growth, but ROE has adverse effects. On the other hand, the results show that ROA in Conventional bank does not have a relationship with economic growth. However, other banking indicators such as ROE and total deposit are significant to economic growth. Based on the ROE results, ROE Islamic bank contributes more to economic growth than Conventional bank because the percentage that contributes to the decreases of economic growth for Islamic banks is lesser than Conventional bank. The results also showed that Islamic banking provides an efficient channel for productive resources and monitors the use of the funds by the participation of business ventures, leading to bank profitability and then economic growth. This study also stressed on total deposit indicator as a proxy to bank development. This study found that total deposit for the both banking system is significant to economic growth. However, the contribution of banking development in conventional banking is much better than by Islamic banking. However, the gap of differences is too small, which shows that Islamic deposits can cope with conventional deposits.
Vertical Fibre Interfacing Interleaved Angled MMI for Thermal-Tuning-Free Wavelength Division (de)Multiplexing and Low-Cost Fibre Packaging

We propose and experimentally demonstrate a vertical fibre interfacing interleaved angled MMI (AMMI) for wavelength division (de)multiplexing (WDM) near 1550 nm. This 6-channel WDM device is composed of two 1 × 3 AMMIs and a Mach-Zehnder interferometer (MZI) with an apodized bidirectional grating acting as both vertical optical coupler and 3-dB power splitter. By thoroughly design the bidirectional gratings, a high coupling efficiency of 72.5% and low return loss of −34 dB is obtained by simulation. The AMMI couplers are designed and optimized using the Eigenmode expansion method. For wavelength matching between the MZI and AMMIs, the circuit simulation model of the interleaved AMMI is built by importing the S-parameter matrices of all the optical components extracted from the physical-level simulations. The device was fabricated using the standard CMOS technology and the feature size is compatible with the 193 nm deep-UV lithography. Experimental results obtained without thermal tuning are in good agreement with the simulation results, the device exhibits a small insertion loss (IL) varies between 3.3 and 4.58 dB (including the grating coupling loss), channel spacing of 6 nm, crosstalk (XT) below −20 dB. To investigate the fabrication tolerance, devices on two different chips are measured individually. The results show good consistency in device performance. Also, the fibre misalignment tolerance of the device is experimentally investigated.
Influence of the Madden-Julian Oscillation on multiweek prediction of Australian rainfall extremes using the ACCESS-S1 prediction system

We assessed the ability of the Bureau of Meteorology’s ACCESS-S1 dynamical forecast system to simulate and predict high rainfall extremes for each season over Australia, especially focusing on the role of the Madden-Julian Oscillation (MJO). Using retrospective forecasts for the period 1990–2012, we show that ACCESS-S1 simulated the observed modulation of extreme weekly mean rainfall by each phase of the MJO reasonably well; however the simulated changes in probabilities tended to be weaker than those observed, especially across the far north during the austral summer season. The ability of the model to (i) simulate the observed modulation of extreme rainfall and (ii) predict the MJO to a lead time of four weeks, translated to enhanced forecast skill for predicting the occurrence of extreme weekly mean rainfall across much of Australia at times when the MJO was strong, compared to when the MJO was weak, during the austral spring and summer seasons in weeks 2 and 3. However, skill reduced across the central far north during the summer when the MJO was strong, suggesting the model is not good at depicting the MJO’s convective phases as it protrudes southward over northern Australia. During autumn and winter, there was little indication of changes in forecast skill, depending on the strength of the MJO. The results of this study will be useful for regional applications when the MJO is forecast to be strong during spring and summer, particularly where the swing in probability of extreme rainfall is large for specific phases of the MJO.
Direction finding in sensors model based automatic modulation classification

In this paper, the RSSI testing as well the Angle of Arrival (AoA) have been examined for position prediction also produce the front specified composition of the possibility distribution of the location of a sensor node. "Multiple Signal Classification" (MUSIC) defined as a popular "Eigen" construction approach with large declaration, which broadly utilized for predicting the total of waveforms, as well their corners of arrival. In this research an examination of the ability to development of part of key specifications of the "MUSIC" technique has been presented, which might improve the response of the prediction operation. The outcomes of the simulation of this approach point out that the position of the sensor node may be evaluated in a little time period values as well that the condition of the explanation is competitive beside last techniques.
Office Room Channel Modeling and Object Attenuation at Sub-THz Frequencies

Large bandwidths are needed to meet the high-throughput requirements of future wireless communication systems. These larger bandwidths are available at mmWave and sub-THz frequencies, such as the V-band ranging from 50 to 75 GHz and the D-band ranging from 110 to 170 GHz. In this paper, we present channel measurements in an office environment, covering the full D-band. Line-of-Sight (LOS) path loss (PL) is modeled as a function of frequency and distance. Both a single-frequency floating-intercept and multi-frequency alpha-beta-gamma model provide a good fit to the measured LOS PL data. Attenuation due to blockage of the LOS path by various desk objects, such as computer peripherals and cables, is determined, as well as attenuation due to plant obstructions. Attenuation due to an obstructed LOS path ranges from 3 dB for a single universal serial bus (USB) cable, and up to 25 dB for a laptop power supply, computer mouse, computer monitor, or plant. Because of a higher diffraction angle, the measured attenuation is higher when the distance between the antennas decreases. We measure diffraction around a computer monitor for dual polarization and verify whether communication via the reflected non Line-of-Sight path makes high-throughput wireless communication possible when the LOS path is blocked.
Lymphatic Fluid Mechanics: An In Situ and Computational Analysis of Lymph Flow

Lymphatic Fluid Mechanics: An In Situ and Computational Analysis of Lymph Flow. (August 2011) Elaheh Rahbar, B.S., Michigan State University Chair of Advisory Committee: Dr. James E. Moore Jr. The lymphatic system is an extensive vascular network responsible for the transport of fluid, immune cells, proteins and lipids. It is composed of thin-walled vessels, valves, nodes and ducts, which work together to collect fluid, approximately 4 L/day, from the interstitium transporting it back to the systemic network via the great veins. The failure to transport lymph fluid results in a number of disorders and diseases. Lymphedema, for example, is a pathology characterized by the retention of fluid in limbs creating extreme discomfort, reduced mobility and impaired immunity. In general, there are two types of edema: primary edema, being those cases that are inherited (i.e. genetic predisposition), and secondary edema, which develop post-trauma or injury of the lymphatic vessels. With the onset of breast cancer and radiation therapies, the prevalence of secondary edema is on the rise. Clinical studies show that up to 80% of women who undergo nodal-dissection surgery develop lymphedema in their arms within 3-5 years of the surgery. Unfortunately, there is no cure or remedy for lymphedema stemming from our lack of understanding of the lymphatic system.
Serendipity in the city: User evaluations of urban recommender systems

The contemporary city is increasingly being labeled as a smart city consisting of both physical and virtual spaces. This digital augmentation of urban life sets the scene for urban recommender systems to help citizens dealing with the abundance of digital information and corresponding choice overload, for example, by recommending the best place to have dinner based on your personal profile. There are, however, concerns that this kind of algorithmic filtering could lead to homogenization of urban experiences and a decline of social cohesion among citizens. To overcome this issue, scholars increasingly encourage the introduction of serendipity in all types of recommender systems. Nonetheless, it remains unclear how this can be achieved in practice. In this work, we study user evaluations of serendipity in urban recommender systems through a survey among 1,641 citizens. More specifically, we study which characteristics of recommended items contribute to serendipitous experiences and to what extent this increases user satisfaction and conversion. Our results align with findings in other application domains in the sense that there is a strong relation between the relevance and novelty of recommendations and the corresponding experienced serendipity. Moreover, serendipitous recommendations are found to increase the chance of users following up on these recommendations.
Combining Interference Lithography and Two-Photon Lithography for Fabricating Large-Area Photonic Crystal Structures with Controlled Defects

Interference lithography is a promising method for fabricating large-area, defect-free three-dimensional photonic crystal structures which can be used for facilitating the realization of photonic devices with a fast processing time. Although they can be used in waveguides, resonators, and detectors, their repeated regular array patterns can only be used for limited applications. In this study, we demonstrate a method for fabricating large-area photonic crystal structures with controlled defects by combining interference lithography and two-photon lithography using a light-curable resin. By combining regular array structures and controlled patterns, monotonous but large-area regular structures can be obtained. Furthermore, the patterned structures have considerable potential for use in various applications, such as solar cells, sensors, photodetectors, micro-/nano-electronics, and cell growth.
Polarization dependent second harmonic generations of equilateral triangular Au nanorods at localized surface plasmon resonances

The paper presents second harmonic generations (SHG) from Au nanoprisms at localized surface plasmon resonances. The model system was equilateral triangular nanoprisms that were arranged two-dimensionally in trigonal lattices. At lower excitation power regions, the SHG conversion efficiencies were almost independent of the excitation light polarization angles, while the polarization angles of the SHG waves were twice as much as those of the excitation light polarizations. The polarization dependencies were in a good agreement with the demands required from the C3v point symmetry of the systems. On the other hand, the SHG conversion efficiencies were dependent on the excitation light polarization angles at higher excitation power regions. The anisotropy in the nonlinear optical responses was explained from the viewpoint of the polarization-dependent depletions of the surface electrons on the metal surfaces.
The ageing of Asian migrant populations in Australia: projections and implications for aged care services

ABSTRACT Until the 1970s the Asia-born population of Australia remained small due to the racist White Australia Policy which denied entry to non-Europeans. Following its abolition in the early 1970s, Asian immigration progressively intensified, and in 2016 the Asia-born population of the country reached a total of 2.7 million, though the older population aged 65+ remained relatively small. This paper presents new projections of Australia's older Asia-born populations from 2016 to 2056 created with a new birthplace projection model. The results show substantial growth of the older Asia-born population can be expected over coming decades, along with changing composition by country of birth. The Asia-born proportion of Australia's older population overall is projected to rise from just 6 per cent in 2016 to 19 per cent in 2056. These coming demographic changes present challenges and opportunities - in particular relating to the provision of culturally appropriate residential and community aged care.
The Effect of Accountability, Responsibility, Independence, and Fairness on the Performance of Klungkung LPDs

The progress of a country can be seen from its economic growth level. One of the financial institutions that helps the economic sector at the traditional village level in Bali Province is the Village Credit Institution (LPD). LPD performance describes its goal achievement. This research aims to determine the LPD performance of Klungkung with several variables such as accountability, responsibility, independence, and fairness tested using multiple linear regression analysis. The findings show that accountability does not affect LPD performance while responsibility, independence, and fairness positively affect LPD performance.
Analysis of the heart-torso conductivity parameters recovery inverse problem in cardiac electrophysiology ECG modelling

In this paper, we prove a stability estimate of the conductivity parameters identification problem in cardiac electrophysiology. The propagation of the electrical wave in the heart is described by the monodomain model coupled to an elliptic equation describing the diffusion of the electrical wave in the whole body. Our result concerns both heart and torso conductivity parameters. The main difficulty that we solve in this paper is related to the transmission conditions between the heart and the torso. We first, establish Carleman estimates for the coupled heart-torso system. Then, using these estimates and the Bukhgeim and Klibanov approach, we prove a Lipschitz stability estimate of cardiac and torso conductivity parameters.