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Making circularity work:The employee side of organizational change towards the circular economy
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In the flow of fire:The protection of water during armed conflict under public international law
No full textToF-SIMS spectra of gallic acid, ellagic acid, castalin, and quercetin in positive polarity
No full textInitially used for fermentation or storage, oak wood barrels were found to enhance the organoleptic properties of spirits. Over time, wood extractives like ellagitannins and aromatic precursors have been linked to the quality of the spirits. ToF-SIMS being an ionization technique produces intense fragmentation patterns that are not fully understood, and reference spectra are required to analyze wood samples confidently. Here, positive polarity ToF-SIMS reference spectra of important oak wood compounds are involved in spirit maturation, using a Bi-3(+) primary ion species, are presented
Artificial Intelligence and Network Medicine:Path to Precision Medicine
No full textOver the past two decades, network medicine (NM) has evolved to help define disease mechanisms, identify drug targets, and guide increasingly precise therapies. In recent years, the integration of NM with artificial intelligence (AI), particularly deep learning techniques, has evolved with increasing applications. AI techniques help elucidate complex disease mechanisms and define precise therapies. The depth of useful, mechanistic information implicit in molecular interaction networks and prior deep learning successes provide a rational basis for combining NM and AI in the analyses of large multiomic datasets to enhance the speed, predictive precision, and biological insights of the computational process. In this review, we provide a summary of concepts related to the combined use of AI and NM as a path to precision medicine, illustrating the success of this joint approach to biomedical complexity and its ongoing challenges
Exploring the Limitations of Layer Synchronization in Spiking Neural Networks
No full textNeural-network processing in machine learning applications relies on layer synchronization. This is practiced even in artificial Spiking Neural Networks (SNNs), which are touted as consistent with neurobiology, in spite of processing in the brain being in fact asynchronous. A truly asynchronous system however would allow all neurons to evaluate concurrently their threshold and emit spikes upon receiving any presynaptic current. Omitting layer synchronization is potentially beneficial, for latency and energy efficiency, but asynchronous execution of models previously trained with layer synchronization may entail a mismatch in network dynamics and performance. We present and quantify this problem, and show that models trained with layer synchronization either perform poorly in absence of the synchronization, or fail to benefit from any energy and latency reduction, when such a mechanism is in place. We then explore a potential solution direction, based on a generalization of backpropagation-based training that integrates knowledge about an asynchronous execution scheduling strategy, for learning models suitable for asynchronous processing. We experiment with 2 asynchronous neuron execution scheduling strategies in datasets that encode spatial and temporal information, and we show the potential of asynchronous processing to use less spikes (up to 50%), complete inference faster (up to 2x), and achieve competitive or even better accuracy (up to ~10% higher). Our exploration affirms that asynchronous event-based AI processing can be indeed more efficient, but we need to rethink how we train our SNN models to benefit from it. (Source code available at: https://github.com/RoelMK/asynctorch)
Alcohol consumption and upper aerodigestive tract squamous cell carcinoma:evidence from 28 prospective cohorts
No full textBackground This study aimed to investigate the association between alcohol consumption and squamous cell cancers of the upper aerodigestive tract (UADT), using data from 28 cohorts within the Pooling Project of Prospective Studies of Diet and Cancer (DCPP). Methods Individual-level data from 2 365 437 participants were pooled. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox models to quantify the association between alcohol consumption (g/day) and UADT cancer risk, adjusting for potential confounders. Analyses were conducted by sex, smoking status, geographic region, and alcoholic beverages. Results Over a median follow-up of 15.5 years, 6903 UADT cancer cases were identified. Alcohol consumption was positively associated with UADT cancer risk overall. Even at intakes as low as 5-<15 g/day, the HR estimate was 1.12 (95% CI = 1.03 to 1.21) compared with the reference group (0.1-<5 g/day). The HR10 g/day (95% CI) was 1.16 (1.14 to 1.18) for women and 1.12 (1.11 to 1.13) for men (Pheterogeneity <. 0001). HR10 g/day estimates were 1.14 (1.13 to 1.15) in current, 1.10 (1.09 to 1.12) in former, and 1.15 (1.12 to 1.18) in never smokers. Consistent UADT HR10 g/day estimates were observed across all beverage types. HR10 g/day estimates varied across geographic regions, with HR10 g/day (95% CI) equal to 1.15 (1.14 to 1.17) in Europe-Australia, 1.13 (1.11 to 1.15) in Asia, and 1.11 (1.09 to 1.12) in North America (Pheterogeneity <. 0001). Conclusion Alcohol consumption was associated with UADT cancer risk, irrespective of smoking status or beverage type. However, due to differential baseline risks, alcohol is expected to impact the UADT cancer burden more in smokers than never smokers. These findings support public health strategies to reduce alcohol consumption.</p
When less is more:resource constraints and radical innovation in family firms and non-family firms
No full textWhile radical innovation is crucial for long-term organizational success, resource constraints often challenge endeavors toward novel ideas, products, and services. Although there is increasing evidence of the positive impact of resource constraints on radical innovation performance, much still needs to be uncovered regarding the conditions that facilitate this positive impact. Drawing on the recombinative innovation perspective, we explicate the positive impact of knowledge and financial constraints on radical innovation. Moreover, we identify firm type-specifically the distinction between family and non-family firms-as a crucial organizational contingency that sheds more light on the focal relationship. Using data from a broad sample of Belgian firms, we find support for our hypothesis that financial constraints can spur a higher likelihood of introducing radical innovation. Moreover, family firms can better transform knowledge constraints into radical innovation, whereas non-family firms are better at generating radical innovation from financial constraints. By considering the impact of organizational characteristics on firms' ability to innovate from specific constraints radically, we deliver more detailed results on the link between resource constraints and radical innovation
Risk of new HIV diagnosis by intersecting migration, socioeconomic, and mental health vulnerabilities in the Netherlands:a nationwide analysis of the ATHENA cohort and Statistics Netherlands registry data
No full textBackground: To further reduce new HIV diagnoses in the Netherlands, individual and structural barriers hindering prevention must be addressed. We aimed to estimate the disproportional burden of new HIV diagnoses and explore how intersecting socio-demographic, socio-economic, and health-related factors jointly influence the risk of a new HIV diagnosis. Methods: We combined data from the ATHENA cohort, an ongoing nationwide HIV cohort, with registry data from Statistics Netherlands. We selected individuals with a new HIV diagnosis between 1 January 2012 and 31 December 2023 and matched them to individuals from the general population. We assessed determinants of a new HIV diagnosis using a multivariable generalized linear model. We used Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to quantify the joint and individual contribution of intersecting variables. Findings: 6055 men and 1020 women were newly diagnosed with HIV. Having a migration background and a low to middle income or income below the poverty line was associated with a higher risk of a new HIV diagnosis for both men (low to middle: adjusted odd ratio (aOR) = 1.24, 95% confidence interval (CI) = 1.17–1.31; below the poverty line: aOR = 1.75, 95% CI = 1.62–1.89) and women (low to middle: aOR = 2.49, 95% CI = 2.05–3.01; below the poverty line: aOR = 4.71, 95% CI = 3.80–5.83). Use of mental health care (aOR = 1.14, 95% CI = 1.01–1.27) or antidepressants (aOR = 1.66, 95% CI = 1.50–1.84) also increased the risk among men; while receiving social welfare (aOR = 1.39, 95% CI = 1.15–1.67) and use of antipsychotic medication (aOR = 1.66, 95% CI = 1.21–2.28) increased the risk among women. Of all intersections identified in MAIHDA, men with a first-generation migration background, income below the poverty line, and who used antidepressants had the highest predicted probability of an HIV diagnosis (0.036%, 95% confidence interval (CI) = 0.025–0.052). Women with a first-generation background, income below the poverty line, who received social welfare, and who used antipsychotic medication had the highest predicted risk (0.019%, 95% CI = 0.011–0.035). Interpretation: A disproportionally higher burden of a new HIV diagnosis was observed for individuals with a migration background and economic and mental health vulnerabilities. HIV prevention and testing need to be reinforced in these groups. Funding: Dutch Ministry of Health, Welfare and Sport; TKI Health Holland
Validity of accelerometer-based analysis of step time and step time variability during treadmill walking in people with bilateral vestibulopathy
No full textBackground: Gait and balance impairments, including increased gait variability, are prevalent in people with bilateral vestibulopathy (BVP). Wearable accelerometers may provide a clinically feasible method to objectively assess gait variability but have not yet been explored in BVP. Research question: Is accelerometer-based assessment of step time variability during treadmill walking valid in people with BVP? Methods: Adults with BVP and age-sex-matched healthy controls walked at 0.6 m/s, 0.8 m/s, and 1.0 m/s on the treadmill of the Computer Assisted Rehabilitation Environment. We examined differences in step time means and coefficients of variation (CoV) between accelerometery (single lower back sensor; MOX1) and 3D motion capture and force plates (Vicon). Validity was assessed using intraclass correlation coefficients (ICC3,1), Pearson and Spearman correlation coefficients, and Bland-Altman analyses to determine agreement, association and consistency between the methods. Validity was additionally assessed by comparing statistical significant differences and the effect sizes between the groups using each method. Results: Mean step time showed moderate to excellent agreement between methods, while step time CoV showed poor agreement and proportional bias. Accelerometery showed consistent between-group significance and effect size values, particularly at 0.6 m/s, although effect sizes were larger in motion capture data than in accelerometer data. Significance: An accelerometer-based assessment is valid for assessing mean step time in people with BVP. For assessing step time variability, it can distinguish between known groups (particularly at slower speeds) but does not demonstrate criterion validity. Before clinical application, test-retest reliability and sensitivity to change should be assessed in BVP.</p