Miracle-dz/UniFAR-FTUs huggingface dataset:
The method of phase retrieval of complex wavefield from two intensity measurements applicable to hard x-rays

A novel algorithm for a reconstruction of the phase shift profile produced by a transparent object in a coherent wave, from a set of two recorded intensity distributions is presented. Contrary to well known algorithms of in-line holography, the method works under the near-field condition where the size of the first Fresnel zone is much less than the characteristic size of the object's details. Such a condition is typical for an in-line holography experimental setup with the use of coherent high energy x-rays (E > 20 keV) produced by synchrotron radiation sources of the third generation like ESRF. The novel algorithm is fast and insensitive to a partial loss of coherence or weak detector resolution. The method can be applied to x-ray refraction tomography.
Evaluating and Quantifying Viability of 3D-Printed Cells with Mathematical Modeling Across Different Bioprinting Methods

3D-bioprinting has the potential to be a very useful tool in the field of tissue engineering, specifically when it comes to biomanufacturing of tissue engineering medical products. One such example is with tissue engineered muscle repair (TEMR) constructs used to treat volumetric muscle loss (VML). In order to ensure successful integration of 3D-bioprinting in the field of tissue engineering as a biomanufacturing tool, it is necessary to fully understand the printing process and its effects on the printed cells. Currently, it is known that the printing process results in some percentage of cell death largely due to the mechanical stresses induced by the extrusion process. However, full understanding over these stresses and its effects is still needed. In particular, there is a large degree of variability in cell viability between printing parameters and across printing methods. To this end, this project consisted of a quantitative analysis of cell viability using different extrusion-based bioprinting methods and varying nozzle diameters, culminating in mathematical modeling to relate shear stress, nozzle diameter, and cell viability. The project was done in the context of TEMR biofabrication for treating VML. As such, mouse C2C12 cells and human muscle progenitor cells were used along with a hyaluronic acid hydrogel. High cell viability (>98%) for both cell types was achieved using a piston-driven printhead paired with a 0.41mm-diameter nozzle.
Spatial-Temporal Distribution and Trend Analysis of Groundwater Level at Ghazipur District, Uttar Pradesh, India. Current World Environment

The present study has analysed the Spatial-temporal distribution of groundwater level (GWL) in the Ghazipur district has been calculated using statistical and graphical methods for the period 1998, 2008 and 2018. In the present study, the GWL trend was analysed using the non-parametric Modified Mann-Kendall (MMK) test for the 39 locations of the Ghazipur district of UP, India. The trend analysis has been tested at a 5 % significance level. The mean, minimum and maximum GWL during the pre-monsoon season (PRM) ranged from 3.16 m to 12.71 m. However, in the post-monsoon (PTM) season, it ranges from 1.76 m to 9.09 m. The GWL trends have been estimated using the non-parametric tests, MMK during the period 1998 to 2018 at 39 locations in the Ghazipur district of Uttar Pradesh, India. From the analysis, The GWL trend analysis has revealed negative magnitudes for 8 locations that covered 20 % portion of total area and positive magnitudes for 31 locations spread in 80 % area in the PRM season. However, in the PTM season, 9 locations spread in 10 % area showed negative trends and 30 locations covering major area which is 90 % of total area showed positive trends. The changes in the GWL trends in two different seasons (PRM and PTM) can be included in the recharge by rainfall in the PTM season. This study reveals the behaviour of GWL over the study area. This study will help in providing valuable information about the long-term behaviour of groundwater levels for ensuring sustainable groundwater management in the Ghazipur district, Uttar Pradesh.
UvA-DARE (Digital Academic Repository) The subcortical cocktail problem; mixed signals from the subthalamic nucleus and substantia nigra

The subthalamic nucleus and the directly adjacent substantia nigra are small and important structures in the basal ganglia. Functional magnetic resonance imaging studies have shown that the subthalamic nucleus and substantia nigra are selectively involved in response inhibition, conflict processing, and adjusting global and selective response thresholds. However, imaging these nuclei is complex, because they are in such close proximity, they can vary in location, and are very small relative to the resolution of most fMRI sequences. Here, we investigated the consistency in localization of these nuclei in BOLD fMRI studies, comparing reported coordinates with probabilistic atlas maps of young human participants derived from ultra-high resolution 7T MRI scanning. We show that the fMRI signal reported in previous studies is likely not unequivocally arising from the subthalamic nucleus but represents a mixture of subthalamic nucleus, substantia nigra, and surrounding tissue. Using a simulation study, we also tested to what extent spatial smoothing, often used in fMRI preprocessing pipelines, influences the mixture of BOLD signals. We propose concrete steps how to analyze fMRI BOLD data to allow inferences about the functional role of small subcortical nuclei like the subthalamic nucleus and substantia nigra.
The Effectiveness of Local Government Revenue Budgets on the Quality of Human Development: Evidence of Local Governments in South Kalimantan, Indonesia

:-This study aims to investigate the effectiveness of local governments in the use of their revenue budgets to achieve human quality development goals. This effectiveness will be reflected in the role of capital expenditures as mediating the influence of local revenue and income from the central government balancing fund on the human development index (HDI). Using the SEM-PLS method, it was found evidence that local government capital expenditures were successful in mediating the effect of local revenue and special allocation funds on HDI. However, it failed to mediate the effect of the general allocation fund on HDI. It can be concluded that local governments have not been effective in using general allocation funds through capital expenditures in achieving human quality development targets in the regions. These transfer funds are more likely to be used as operational expenditures that do not support human quality development.
A Novel Light Field Camera Calibration Algorithm Applied for Stereo-vision

3D vision plays a fundamental role in many engineering and medical ﬁelds. Stereo-vision is one of the most popular method, which reconstructs depth information from binocular images. Camera calibration is crucial for the reconstruction geometry accuracy. Conventional pinhole camera model represents each pixel as a ray through the optical center and the pixel. In reality, due to the manufacture error, the optical lense and the digital sensors have various distortions, the physical camera rays may not converge to a single point. Conventional calibration method, such as Zhengyou Zhang’s algorithm, uses limited number of parameters to describe the intrinsic distortions, such as eﬀective focal length, slant parameter, principle center and radial and tangential distortions, which are incapable of describing the complicated distortions or more general cameras, such as cell phone cameras and Lytro light ﬁeld cameras. Recently, the light ﬁeld camera becomes popular, which associates each pixel with a ray in the physical world, and there is no optical center for the rays. This model is able to describe all types of complex intrinsic distortions, and represent any types of cameras. Furthermore, a light ﬁeld camera can synthesize virtual pinhole cameras. But, so far there is no calibration algorithm for light ﬁeld camera.This work develops a practical method for light ﬁeld camera calibration, which measures each camera ray individually based on Principle Component Analysis (PCA) and using a simple set up (including a linear rail, a LCD panel and a laser pointer), and stores the representations of all the rays. Comparing to conventional calibration method, the proposed method greatly simpliﬁes the optimization process, and improves the precision. The proposed calibration method is applied for a stereo-vision project to scan geometric objects in the real world. Our experimental results demonstrate that the proposed calibration algorithm can handle complicated geometric or textural features with high precision and outperforms the conventional calibration method.
Machine Learning-Based Selection of Efficient Parameters for the Evaluation of Seismically Induced Slope Displacements

Seismically-induced slope displacements ( D ) are often used as a performance index in the seismic design of slope systems. Although previous studies have developed predictive relationships for estimating D , a comprehensive selection of the most efficient parameters to explain D , considering the linearity and nonlinearity in D has not been thoroughly performed. This study uses modern machine learning based techniques including Stepwise Selection, LASSO, and Random Forest to identify the influential features in the estimation of D in shallow crustal tectonic settings. The detected influential features are the system’s yield coefficient ( k y ), initial fundamental period ( T s ), earthquake moment magnitude ( M w ), peak ground velocity ( PGV ), and the degraded spectral acceleration at 1.3 T s ( S a (1.3 T s )). Moreover, the results indicate that there is no significant gain in accuracy beyond five features. The detected significant parameters provide insight and a basis for developing more efficient prediction models.
Analysing the Eﬀect of Lockdown on Physical Activity, Screen Time, and Emotional Wellbeing Among Young Medical Students of India During the COVID-19 Pandemic

Background: The COVID-19 pandemic aﬀected all population segments, including students switching to online classes and negligible outdoor activities during the lockdown period. However, the data is limited on medical students’ lifestyle changes regarding physical and mental health during the lockdown. Objectives: Thepresentstudyaimedtodeterminetheeﬀectof lockdownonphysicalactivity,screentimeandemotionalwellbeing of young medical students during the COVID-19 pandemic. Methods: An online cross-sectional survey was conducted on 250 medical students of phase-I MBBS during the lockdown period duringOctobertoDecember2020. Thestudentsself-reportedtheirphysicalactivity,screentimeusage,andemotionalhealthstatus usingGoogleForms. PhysicalactivitywasassessedwiththeInternationalPhysicalActivityQuestionnaire,andtheemotionalstatus was determined using the Positive and Negative Aﬀect Schedule (PANAS) Questionnaire. After removing incomplete data, only 174 students’ responses were analyzed using SPSS-20, and P < 0.05 was considered signiﬁcant. Results: The physical inactivity of the medical students was 24.7%, and their average screen usage was six hours/day during the COVID-19pandemic. Physicalactivityintermsof metabolicequivalentscoresexplainsa5% riseinpositiveemotionsanda2% decline in negative emotions. Screen time usage expands negative emotions (9% variance) and reduces positive emotions (7% variance). Conclusions: Students with more physical activity and less screen time usage presented a more positive eﬀect on emotions, and thereartrendwasobservedfortheircounterparts. Thus,physicalinactivityandincreasedscreentimeusagehaveemergedasmajor and independent risk factors for students’ emotional health.
Repurposing Segmentation as a Practical LVI-NULL Mitigation in SGX

Load Value Injection (LVI) uses Meltdown-type data ﬂows in Spectre-like confused-deputy attacks. LVI has been demon-strated in practical attacks on Intel SGX enclaves, and con-sequently, mitigations were deployed that incur tremendous overheads of factor 2 to 19. However, as we discover, on ﬁxed hardware LVI-NULL leakage is still present. Hence, to mitigate LVI-NULL in SGX enclaves on LVI-ﬁxed CPUs, the expensive mitigations would still be necessary. In this paper, we propose a lightweight mitigation focused on LVI-NULL in SGX, LVI-NULLify. We systematically analyze and categorize LVI-NULL variants. Our analysis reveals that previously proposed mitigations targeting LVI-NULL are not effective. Our novel mitigation addresses this problem by repurposing segmentation, a fast legacy hardware mechanism that x86 already uses for every memory operation. LVI-NULLify consists of a modiﬁed SGX-SDK and a compiler extension which put the enclave in control of LVI-NULL-exploitable memory locations. We evaluate LVI-NULLify on the LVI-ﬁxed Comet Lake CPU and observe a performance overhead below 10% for the worst case, which is substantially lower than previous defenses with a prohibitive overhead of 1220% in the worst case. We conclude that LVI-NULLify is a practical solution to protect SGX enclaves against LVI-NULL today.
Image Processing Approach for Detection of Three-Dimensional Tree-Rings from X-Ray Computed Tomography

— Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.
Emerging Co-Opetition Symmetry and Firm Performance: A Study Goods Industry

The purpose of this paper is to examine the co-opetition and firm performance relationship through the mediating role of innovation and moderating role of trust ” . This is broadly acknowledging that symmetry of co-opetition (i.e., simultaneous competition and cooperation) is achieving core advantage when firms engage in such co-opetitive relationship. Further, it is hypothesized that co-opetition has a positive influence and firm performance. The sector selected for this study is sports goods industry where requirements of co-petition are just not a requirement but also a necessity as small businesses with limited assets need heavy resources to perform internationally. Therefore, required attention was given to the effect of co-opetition on firm performance. The sample size were 415 and survey questionnaires distributed to respondents representing sports goods industry using a simple random sampling technique. The only 361 responses were useable for analysis other 54 questionnaires did not receive or not in condition to use them. The finding of this study indicated that co-opetition through innovation has a significant effect on firm performance. Furthermore, this study also verifies that the influence of trust on co-opetition and performance relationship reveals some important nuances that indicate this relationship either strong or weak. The implication of this study investigation offers that the practitioners and managers contain “optimal level” of co opetition with their competitors, which always increases f irm performance. Where as “too little” and “too much” intensity of co -opetition distrust between rivals and ultimately decreases firm performance. “ Finally, this study is one of the initial studies that investigating the role of innovation and trust on co-opetition and performance relationship in sports goods industry ” .
Romantic and Family Movie Database: Towards Understanding Human Emotion and Relationship via Genre-Dependent Movies

Movie gains popularity by successfully immersing viewers into affective contents under an emotion perception and elicitation process. Film genre sets the tone of a movie to shape key emotional context during the storytelling procedure. In romantic and family movies, character relationship is a key contextual attribute guiding the whole storyline, which is expected to evoke a sense of being moved in the audience. In this work, we propose Romantic and Family Movie Database, which consists of 1029 movie clips from 10 romantic and family movies. We provide annotations including character relationship type, character relationship status, perceived emotions, induced emotions, and degree of being moved. Our analysis elaborates the inconsistency between perceived and induced valence with the support of annotations including character relationship status and degree of being moved. We also find that being moved and induced arousal are positively correlated in romantic and family movies. We present comprehensive baseline results in recognizing relationship status and emotions using different models and modalities. The database is publicly available at https://rfmd.ee. nthu.edu. tw/.
ORIGINAL RESEARCH Culture-Associated Q2 DNA Methylation Changes Impact on Cellular Function of Human Intestinal Organoids

SUMMARY This work describes cell culture – induced changes to DNA methylation, gene expression, and cellular function in human intestinal epithelial organoids. Globally, organoids lost DNA methylation with time in culture while DNA methylation also became generally more variable. This work sug-gests a shifted epigenetic pro ﬁ le in organoids cultured long term. enriched in genomic regions associated with colonic cancer and distant to the site of replication, indicating similarities to malignant transformation. CONCLUSIONS: Our study shows distinct culture-associated epigenetic changes in mucosa-derived human IEOs, some of which appear to impact gene transcriptomic and cellular function. These ﬁ ndings highlight the need for future studies in this area and the importance of considering passage number as a potentially confounding factor. (Cell Mol Gastroenterol Hepatol 2022; - : - – - ; https://doi.org/10.1016/j.jcmgh.2022.08.008)
Evaluation of Transfer Learning and Domain Adaptation for Analyzing German-Speaking Job Advertisements

This paper presents text mining approaches on German-speaking job advertisements to enable social science research on the development of the labour market over the last 30 years. In order to build text mining applications providing information about profession and main task of a job, as well as experience and ICT skills needed, we experiment with transfer learning and domain adaptation. Our main contribution consists in building language models which are adapted to the domain of job advertisements, and their assessment on a broad range of machine learning problems. Our findings show the large value of domain adaptation in several respects. First, it boosts the performance of fine-tuned task-specific models consistently over all evaluation experiments. Second, it helps to mitigate rapid data shift over time in our special domain, and enhances the ability to learn from small updates with new, labeled task data. Third, domain-adaptation of language models is efficient: With continued in-domain pre-training we are able to outperform general-domain language models pre-trained on ten times more data. We share our domain-adapted language models and data with the research community.
13C16O2: Global Treatment of Vibrational–Rotational Spectra and First Observation of the 2ν1 + 5ν3 and ν1 + 2ν2 + 5ν3 Absorption Bands

The effective operator approach is applied to the calculation of both line positions and line intensities of the (13)C(16)O(2) molecule. About 11 000 observed line positions of (13)C(16)O(2) selected from the literature have been used to derive 84 parameters of a reduced effective Hamiltonian globally describing all known vibrational-rotational energy levels in the ground electronic state. The standard deviation of the fit is 0.0015 cm(-1). The eigenfunctions of this effective Hamiltonian have then been used in fittings of parameters of an effective dipole-moment operator to more than 600 observed line intensities of the cold and hot bands covering the nu(2) and 3nu(2) regions. The standard deviations of the fits are 3.2 and 12.0% for these regions, respectively. The quality of the fittings and the extrapolation properties of the fitted parameters are discussed. A comparison of calculated line parameters with those provided by the HITRAN database is given. Finally, the first observations of the 2nu(1) + 5nu(3) and nu(1) + 2nu(2) + 5nu(3) absorption bands by means of photoacoustic spectroscopy (PAS) is presented. The deviations of predicted line positions from observed ones is found to be less than 0.1 cm(-1), and most of them lie within the experimental accuracy (0.007 cm(-1)) once the observed line positions are included in the global fit. Copyright 2000 Academic Press.
Building Large-Scale Japanese Pronunciation-Annotated Corpora for Reading Heteronymous Logograms

Although screen readers enable visually impaired people to read written text via speech, the ambiguities in pronunciations of heteronyms cause wrong reading, which has a serious impact on the text understanding. Especially in Japanese, there are many common heteronyms expressed by logograms (Chinese characters or kanji) that have totally different pronunciations (and meanings). In this study, to improve the accuracy of pronunciation prediction, we construct two large-scale Japanese corpora that annotate kanji characters with their pronunciations. Using existing language resources on i) book titles compiled by the National Diet Library and ii) the books in a Japanese digital library called Aozora Bunko and their Braille translations, we develop two large-scale pronunciation-annotated corpora for training pronunciation prediction models. We first extract sentence-level alignments between the Aozora Bunko text and its pronunciation converted from the Braille data. We then perform dictionary-based pattern matching based on morphological dictionaries to find word-level pronunciation alignments. We have ultimately obtained the Book Title corpus with 336M characters (16.4M book titles) and the Aozora Bunko corpus with 52M characters (1.6M sentences). We analyzed pronunciation distributions for 203 common heteronyms, and trained a BERT-based pronunciation prediction model for 93 heteronyms, which achieved an average accuracy of 0.939.