Establishing Data Provenance for Responsible Artificial Intelligence Systems

Data provenance, a record that describes the origins and processing of data, offers new promises in the increasingly important role of artificial intelligence (AI)-based systems in guiding human decision making. To avoid disastrous outcomes that can result from bias-laden AI systems, responsible AI builds on four important characteristics: fairness, accountability, transparency, and explainability. To stimulate further research on data provenance that enables responsible AI, this study outlines existing biases and discusses possible implementations of data provenance to mitigate them. We first review biases stemming from the data’s origins and pre-processing. We then discuss the current state of practice, the challenges it presents, and corresponding recommendations to address them. We present a summary highlighting how our recommendations can help establish data provenance and thereby mitigate biases stemming from the data’s origins and pre-processing to realize responsible AI-based systems. We conclude with a research agenda suggesting further research avenues

Benefits of Blockchain Initiatives for Value-Based Care: Proposed Framework

Background The potential of blockchain technology to achieve strategic goals, such as value-based care, is increasingly being recognized by both researchers and practitioners. However, current research and practices lack comprehensive approaches for evaluating the benefits of blockchain applications. Objective The goal of this study was to develop a framework for holistically assessing the performance of blockchain initiatives in providing value-based care by extending the existing balanced scorecard (BSC) evaluation framework. Methods Based on a review of the literature on value-based health care, blockchain technology, and methods for evaluating initiatives in disruptive technologies, we propose an extended BSC method for holistically evaluating blockchain applications in the provision of value-based health care. The proposed method extends the BSC framework, which has been extensively used to measure both financial and nonfinancial performance of organizations. The usefulness of our proposed framework is further demonstrated via a case study. Results We describe the extended BSC framework, which includes five perspectives (both financial and nonfinancial) from which to assess the appropriateness and performance of blockchain initiatives in the health care domain. Conclusions The proposed framework moves us toward a holistic evaluation of both the financial and nonfinancial benefits of blockchain initiatives in the context of value-based care and its provision

DOA Estimation for Hybrid Massive MIMO Systems using Mixed-ADCs: Performance Loss and Energy Efficiency

Due to the power consumption and high circuit cost in antenna arrays, the practical application of massive multipleinput multiple-output (MIMO) in the sixth generation (6G) and future wireless networks is still challenging. Employing lowresolution analog-to-digital converters (ADCs) and hybrid analog and digital (HAD) structure is two low-cost choice with acceptable performance loss. In this paper, the combination of the mixedADC architecture and HAD structure employed at receiver is proposed for direction of arrival (DOA) estimation, which will be applied to the beamforming tracking and alignment in 6G. By adopting the additive quantization noise model, the exact closedform expression of the Cramer-Rao lower bound (CRLB) for the HAD architecture with mixed-ADCs is derived. Moreover, the closed-form expression of the performance loss factor is derived as a benchmark. In addition, to take power consumption into account, energy efficiency is also investigated in our paper. The numerical results reveal that the HAD structure with mixedADCs can significantly reduce the power consumption and hardware cost. Furthermore, that architecture is able to achieve a better trade-off between the performance loss and the power consumption. Finally, adopting 2-4 bits of resolution may be a good choice in practical massive MIMO systems.Comment: 11 pages, 7 figure

Joint Beamforming and Phase Shift Design for Hybrid IRS and UAV-Aided Directional Modulation Networks

Recently, intelligent reflecting surfaces (IRSs) and unmanned aerial vehicles (UAVs) have been integrated into wireless communication systems to enhance the performance of air–ground transmission. To balance performance, cost, and power consumption well, a hybrid IRS and UAV-assisted directional modulation (DM) network is investigated in this paper in which the hybrid IRS consisted of passive and active reflecting elements. We aimed to maximize the achievable rate by jointly designing the beamforming and phase shift matrix (PSM) of the hybrid IRS subject to the power and unit-modulus constraints of passive IRS phase shifts. To solve the non-convex optimization problem, a high-performance scheme based on successive convex approximation and fractional programming (FP) called the maximal signal-to-noise ratio (SNR)-FP (Max-SNR-FP) is proposed. Given its high complexity, we propose a low-complexity maximal SNR-equal amplitude reflecting (EAR) (Max-SNR-EAR) scheme based on the maximal signal-to-leakage-noise ratio method, and the criteria of phase alignment and EAR. Given that the active and passive IRS phase shift matrices of both schemes are optimized separately, to investigate the effect of jointly optimizing them to improve the achievable rate, a maximal SNR majorization-minimization (MM) (Max-SNR-MM) scheme using the MM criterion to design the IRS PSM is proposed. Simulation results show that the rates harvested by the three proposed methods were slightly lower than those of the active IRS with higher power consumption, which were 35% higher than those of no IRS and random phase IRS, while passive IRS achieved only about a 17% rate gain over the latter. Moreover, compared with the Max-SNR-FP, the proposed Max-SNR-EAR and Max-SNR-MM methods caused obvious complexity degradation at the price of slight performance loss

Array-based DNA methylation profiling of primary lymphomas of the central nervous system

<p>Abstract</p> <p>Background</p> <p>Although primary lymphomas of the central nervous system (PCNSL) and extracerebral diffuse large B-cell lymphoma (DLBCL) cannot be distinguished histologically, it is still a matter of debate whether PCNSL differ from systemic DLBCL with respect to their molecular features and pathogenesis. Analysis of the DNA methylation pattern might provide further data distinguishing these entities at a molecular level.</p> <p>Methods</p> <p>Using an array-based technology we have assessed the DNA methylation status of 1,505 individual CpG loci in five PCNSL and compared the results to DNA methylation profiles of 49 DLBCL and ten hematopoietic controls.</p> <p>Results</p> <p>We identified 194 genes differentially methylated between PCNSL and normal controls. Interestingly, Polycomb target genes and genes with promoters showing a high CpG content were significantly enriched in the group of genes hypermethylated in PCNSL. However, PCNSL and systemic DLBCL did not differ in their methylation pattern.</p> <p>Conclusions</p> <p>Based on the data presented here, PCNSL and DLBCL do not differ in their DNA methylation pattern. Thus, DNA methylation analysis does not support a separation of PCNSL and DLBCL into individual entities. However, PCNSL and DLBCL differ in their DNA methylation pattern from non- malignant controls.</p

Mobile HTS SQUID System for Eddy Current Testing of Aircraft

In Non-Destructive Evaluation (NDE), eddy current techniques are commonly used for the detection of hidden material defects in metallic structures. Conventionally, one works with an excitation coil generating a field at a distinct frequency. The eddy currents are deviated by materials flaws and the resulting distorted field is sensed by a secondary coil. Because of the law of induction, this technique has its limitations in the low frequency range. This leads to a decrease of the Probability of flaw Detection (POD) in larger depths

Development of the Workplace Health Savings Calculator:A practical tool to measure economic impact from reduced absenteeism and staff turnover in workplace health promotion Public Health

Background: Workplace health promotion is focussed on improving the health and wellbeing of workers. Although quantifiable effectiveness and economic evidence is variable, workplace health promotion is recognised by both government and business stakeholders as potentially beneficial for worker health and economic advantage. Despite the current debate on whether conclusive positive outcomes exist, governments are investing, and business engagement is necessary for value to be realised. Practical tools are needed to assist decision makers in developing the business case for workplace health promotion programs. Our primary objective was to develop an evidence-based, simple and easy-to-use resource (calculator) for Australian employers interested in workplace health investment figures. Results: Three phases were undertaken to develop the calculator. First, evidence from a literature review located appropriate effectiveness measures. Second, a review of employer-facilitated programs aimed at improving the health and wellbeing of employees was utilised to identify change estimates surrounding these measures, and third, currently available online evaluation tools and models were investigated. We present a simple web-based calculator for use by employers who wish to estimate potential annual savings associated with implementing a successful workplace health promotion program. The calculator uses effectiveness measures (absenteeism and staff turnover rates) and change estimates sourced from 55 case studies to generate the annual savings an employer may potentially gain. Australian wage statistics were used to calculate replacement costs due to staff turnover. The calculator was named the Workplace Health Savings Calculator and adapted and reproduced on the Healthy Workers web portal by the Australian Commonwealth Government Department of Health and Ageing. Conclusion: The Workplace Health Savings Calculator is a simple online business tool that aims to engage employers and to assist participation, development and implementation of workplace health promotion programs

Pim1 promotes human prostate cancer cell tumorigenicity and c-MYC transcriptional activity

<p>Abstract</p> <p>Background</p> <p>The serine/threonine kinase PIM1 has been implicated as an oncogene in various human cancers including lymphomas, gastric, colorectal and prostate carcinomas. In mouse models, Pim1 is known to cooperate with c-Myc to promote tumorigenicity. However, there has been limited analysis of the tumorigenic potential of Pim1 overexpression in benign and malignant human prostate cancer cells <it>in vivo</it>.</p> <p>Methods</p> <p>We overexpressed Pim1 in three human prostate cell lines representing different disease stages including benign (RWPE1), androgen-dependent cancer (LNCaP) and androgen-independent cancer (DU145). We then analyzed <it>in vitro </it>and <it>in vivo </it>tumorigenicity as well as the effect of Pim1 overexpression on c-MYC transcriptional activity by reporter assays and gene expression profiling using an inducible MYC-ER system. To validate that Pim1 induces tumorigenicity and target gene expression by modulating c-MYC transcriptional activity, we inhibited c-MYC using a small molecule inhibitor (10058-F4) or RNA interference.</p> <p>Results</p> <p>Overexpression of Pim1 alone was not sufficient to convert the benign RWPE1 cell to malignancy although it enhanced their proliferation rates when grown as xenografts <it>in vivo</it>. However, Pim1 expression enhanced the <it>in vitro </it>and <it>in vivo </it>tumorigenic potentials of the human prostate cancer cell lines LNCaP and DU145. Reporter assays revealed increased c-MYC transcriptional activity in Pim1-expressing cells and mRNA expression profiling demonstrated that a large fraction of c-MYC target genes were also regulated by Pim1 expression. The c-MYC inhibitor 10058-F4 suppressed the tumorigenicity of Pim1-expressing prostate cancer cells. Interestingly, 10058-F4 treatment also led to a reduction of Pim1 protein but not mRNA. Knocking-down c-MYC using short hairpin RNA reversed the effects of Pim1 on Pim1/MYC target genes.</p> <p>Conclusion</p> <p>Our results suggest an <it>in vivo </it>role of Pim1 in promoting prostate tumorigenesis although it displayed distinct oncogenic activities depending on the disease stage of the cell line. Pim1 promotes tumorigenicity at least in part by enhancing c-MYC transcriptional activity. We also made the novel discovery that treatment of cells with the c-MYC inhibitor 10058-F4 leads to a reduction in Pim1 protein levels.</p