EMaP: Explainable AI with Manifold-based Perturbations

In the last few years, many explanation methods based on the perturbations of input data have been introduced to improve our understanding of decisions made by black-box models. The goal of this work is to introduce a novel perturbation scheme so that more faithful and robust explanations can be obtained. Our study focuses on the impact of perturbing directions on the data topology. We show that perturbing along the orthogonal directions of the input manifold better preserves the data topology, both in the worst-case analysis of the discrete Gromov-Hausdorff distance and in the average-case analysis via persistent homology. From those results, we introduce EMaP algorithm, realizing the orthogonal perturbation scheme. Our experiments show that EMaP not only improves the explainers' performance but also helps them overcome a recently-developed attack against perturbation-based methods.Comment: 29 page

Mechanical Attributes of Fractal Dragons

Fractals are ubiquitous natural emergences that have gained increased attention in engineering applications, thanks to recent technological advancements enabling the fabrication of structures spanning across many spatial scales. We show how the geometries of fractals can be exploited to determine their important mechanical properties, such as the first and second moments, which physically correspond to the center of mass and the moment of inertia, using a family of complex fractals known as the dragons

Direct and indirect effects of risks on service-oriented supply chain: a covid-19 pandemic perspective

Purpose - A solid service-oriented foundation is required to make supply chain management a competitive advantage, especially in this Covid-19 pandemic. A well-established service-oriented supply chain becomes more adaptable to changing client expectations. This study aims at analysing the direct and indirect impact of risks on the service-oriented supply chain from a pandemic perspective. Design/methodology/approach - The Q-sort method is applied with the participation of nine top-level managers to initially review the reliability, validity, and unidimensionality of research concepts. Then a questionnaire containing these measuring variables is developed to obtain the opinions of those who are experienced in logistics and supply chain management. These empirical data are analysed based on Structural Equation Modelling (SEM) to evaluate direct and indirect effects of risks on supply chain performance. Findings - The risk is inherent in service-oriented supply chains, affecting both direct and indirect performance. The proposed risk model explains 33.6 percent of Supplier performance, 46.4 percent of Operational performance, 47.1 percent of Customer satisfaction, and 46.5 percent of Finance variation. We found that service-oriented supply chains effectively monitor demand risk. External risk has the smallest impact on supply chain performance measures, whereas demand risk has the smallest effect. That a service-oriented supply chain is focused on meeting customer demand and managing demand-related risks is reinforced by these findings. Research limitations/implications - In the literature on supply chain risk management, resilience studies and disruption management receive less attention than studies on risk assessment and risk mitigation (Katsaliaki et al., 2021). Future supply chain risk management research should differentiate between risk-as an event and/or risk-as a process since they have different periodic effects on response management and resilience. Originality/value - This is a pioneering study lookingJICA - Japan International Cooperation Agency(undefined)This work was supported by the project of “An Empirical Study on Services Value Chain based on the Experiential and Credibility Values” (Grant-in-Aid for Scientific Research (A) No.25240050), and Japanese Government by Japan International Cooperation Agency (JICA) through AUN/SEED-Net Project: 022674.242.2015/JICA-A

Long-term outcomes of primary cardiac malignant tumors: Difference between African American and Caucasian population

BACKGROUND: The survival outcome for primary cardiac malignant tumors (PMCTs) based on race has yet to be fully elucidated in previously published literature. This study aimed to address the general long-term outcome and survival rate differences in PMCTs among African Americans and Caucasian populations. METHODS: The 18 cancer registries database from the Surveillance, Epidemiology, and End Results (SEER) Program from 1975 to 2016 were utilized. Ninety-four African American (AA) and 647 Caucasian (CAU) patients from the SEER registry were available for survival analysis. The log-rank test was used to compare the difference in mortality between two populations and presented by the Kaplan-Meier curves. A multivariate Cox proportional hazards regression was used to determine the independent predictors of all-cause mortality. RESULTS: The overall 30-day, 1-year, and 5-year survival rates were 74%, 44.3%, and 16.6%, respectively, with a median survival of 10 months. There was no significant difference in survival rate between the two races (p-value = 0.55). The 1-year survival rate improved significantly during the study timeline in the AA population (13.3% during 1975-1998, 40.9% during 1999-2004, 50% during 2005-2010, and 59.7% during 2011-2016, p-value = 0.0064). Age of diagnosis, type of tumor, disease stage, and chemotherapy administration are the main factors that predict survival outcomes of PMCT patients. Interactive nomogram was developed based on significant predictors. CONCLUSIONS: PMCTs have remained one of the most lethal diseases with poor survival outcome. Survival rate improved during the timeline in AA patients, but in general, racial differences in survival outcome were not observed

The impact of cataract surgey on vision-related quality of life for bilateral cataract patients in Ho Chi Minh City, Vietnam: a prospective study

BACKGROUND: To determine the impact of cataract surgery on vision-related quality of life (VRQOL) and examine the association between objective visual measures and change in VRQOL after surgery among bilateral cataract patients in Ho Chi Minh City, Vietnam. METHODS: A cohort of older patients with bilateral cataract was assessed one week before and one to three months after first eye or both eye cataract surgery. Visual measures including visual acuity, contrast sensitivity and stereopsis were obtained. Vision-related quality of life was assessed using the NEI VFQ-25. Descriptive analyses and a generalized linear estimating equation (GEE) analysis were undertaken to measure change in VRQOL after surgery. RESULTS: Four hundred and thirteen patients were assessed before cataract surgery and 247 completed the follow-up assessment one to three months after first or both eye cataract surgery. Overall, VRQOL significantly improved after cataract surgery (p < 0.001) particularly after both eye surgeries. Binocular contrast sensitivity (p < 0.001) and stereopsis (p < 0.001) were also associated with change in VRQOL after cataract surgery. Visual acuity was not associated with VRQOL. CONCLUSIONS: Cataract surgery significantly improved VRQOL among bilateral cataract patients in Vietnam. Contrast sensitivity as well as stereopsis, rather than visual acuity significantly affected VRQOL after cataract surgery

Secular trend, seasonality and effects of a community-based intervention on neonatal mortality: follow-up of a cluster-randomised trial in Quang Ninh province, Vietnam.

BACKGROUND: Little is know about whether the effects of community engagement interventions for child survival in low-income and middle-income settings are sustained. Seasonal variation and secular trend may blur the data. Neonatal mortality was reduced in a cluster-randomised trial in Vietnam where laywomen facilitated groups composed of local stakeholders employing a problem-solving approach for 3 years. In this analysis, we aim at disentangling the secular trend, the seasonal variation and the effect of the intervention on neonatal mortality during and after the trial. METHODS: In Quang Ninh province, 44 communes were allocated to intervention and 46 to control. Births and neonatal deaths were assessed in a baseline survey in 2005, monitored during the trial in 2008-2011 and followed up by a survey in 2014. Time series analyses were performed on monthly neonatal mortality data. RESULTS: There were 30 187 live births and 480 neonatal deaths. The intervention reduced the neonatal mortality from 19.1 to 11.6 per 1000 live births. The reduction was sustained 3 years after the trial. The control areas reached a similar level at the time of follow-up. Time series decomposition analysis revealed a downward trend in the intervention areas during the trial that was not found in the control areas. Neonatal mortality peaked in the hot and wet summers. CONCLUSIONS: A community engagement intervention resulted in a lower neonatal mortality rate that was sustained but not further reduced after the end of the trial. When decomposing time series of neonatal mortality, a clear downward trend was demonstrated in intervention but not in control areas. TRIAL REGISTRATION NUMBER: ISRCTN44599712, Post-results

Quantum Criticality in Heavy Fermion Metals

Quantum criticality describes the collective fluctuations of matter undergoing a second-order phase transition at zero temperature. Heavy fermion metals have in recent years emerged as prototypical systems to study quantum critical points. There have been considerable efforts, both experimental and theoretical, which use these magnetic systems to address problems that are central to the broad understanding of strongly correlated quantum matter. Here, we summarize some of the basic issues, including i) the extent to which the quantum criticality in heavy fermion metals goes beyond the standard theory of order-parameter fluctuations, ii) the nature of the Kondo effect in the quantum critical regime, iii) the non-Fermi liquid phenomena that accompany quantum criticality, and iv) the interplay between quantum criticality and unconventional superconductivity.Comment: (v2) 39 pages, 8 figures; shortened per the editorial mandate; to appear in Nature Physics. (v1) 43 pages, 8 figures; Non-technical review article, intended for general readers; the discussion part contains more specialized topic

Using matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling in order to predict clinical outcomes of patients with heart failure

Background Current risk prediction models in heart failure (HF) including clinical characteristics and biomarkers only have moderate predictive value. The aim of this study was to use matrix assisted laser desorption ionisation mass spectrometry (MALDI-MS) profiling to determine if a combination of peptides identified with MALDI-MS will better predict clinical outcomes of patients with HF. Methods A cohort of 100 patients with HF were recruited in the biomarker discovery phase (50 patients who died or had a HF hospital admission vs. 50 patients who did not have an event). The peptide extraction from plasma samples was performed using reversed phase C18. Then samples were analysed using MALDI-MS. A multiple peptide biomarker model was discovered that was able to predict clinical outcomes for patients with HF. Finally, this model was validated in an independent cohort with 100 patients with HF. Results After normalisation and alignment of all the processed spectra, a total of 11,389 peptides (m/z) were detected using MALDI-MS. A multiple biomarker model was developed from 14 plasma peptides that was able to predict clinical outcomes in HF patients with an area under the receiver operating characteristic curve (AUC) of 1.000 (p = 0.0005). This model was validated in an independent cohort with 100 HF patients that yielded an AUC of 0.817 (p = 0.0005) in the biomarker validation phase. Addition of this model to the BIOSTAT risk prediction model increased the predictive probability for clinical outcomes of HF from an AUC value of 0.643 to an AUC of 0.823 (p = 0.0021). Moreover, using the prediction model of fourteen peptides and the composite model of the multiple biomarker of fourteen peptides with the BIOSTAT risk prediction model achieved a better predictive probability of time-to-event in prediction of clinical events in patients with HF (p = 0.0005). Conclusions The results obtained in this study suggest that a cluster of plasma peptides using MALDI-MS can reliably predict clinical outcomes in HF that may help enable precision medicine in HF

Genetic Rearrangements Can Modify Chromatin Features at Epialleles

Analogous to genetically distinct alleles, epialleles represent heritable states of different gene expression from sequence-identical genes. Alleles and epialleles both contribute to phenotypic heterogeneity. While alleles originate from mutation and recombination, the source of epialleles is less well understood. We analyze active and inactive epialleles that were found at a transgenic insert with a selectable marker gene in Arabidopsis. Both converse expression states are stably transmitted to progeny. The silent epiallele was previously shown to change its state upon loss-of-function of trans-acting regulators and drug treatments. We analyzed the composition of the epialleles, their chromatin features, their nuclear localization, transcripts, and homologous small RNA. After mutagenesis by T-DNA transformation of plants carrying the silent epiallele, we found new active alleles. These switches were associated with different, larger or smaller, and non-overlapping deletions or rearrangements in the 3′ regions of the epiallele. These cis-mutations caused different degrees of gene expression stability depending on the nature of the sequence alteration, the consequences for transcription and transcripts, and the resulting chromatin organization upstream. This illustrates a tight dependence of epigenetic regulation on local structures and indicates that sequence alterations can cause epigenetic changes at some distance in regions not directly affected by the mutation. Similar effects may also be involved in gene expression and chromatin changes in the vicinity of transposon insertions or excisions, recombination events, or DNA repair processes and could contribute to the origin of new epialleles