Citation counts and related metrics have pervasive uses and misuses in academia and research appraisal, serving as scholarly influence and recognition measures. Hence, comprehending the citation patterns exhibited by authors is essential for assessing their research impact and contributions within their respective fields. Although the h-index, introduced by Hirsch in 2005, has emerged as a popular bibliometric indicator, it fails to account for the intricate relationships between authors and their citation patterns. This limitation becomes particularly relevant in cases where citations are strategically employed to boost the perceived influence of certain individuals or groups, a phenomenon that we term "orchestration". Orchestrated citations can introduce biases in citation rankings and therefore necessitate the identification of such patterns. Here, we use Scopus data to investigate orchestration of citations across all scientific disciplines. Orchestration could be small-scale, when the author him/herself and/or a small number of other authors use citations strategically to boost citation metrics like h-index; or large-scale, where extensive collaborations among many co-authors lead to high h-index for many/all of them. We propose three orchestration indicators: extremely low values in the ratio of citations over the square of the h-index (indicative of small-scale orchestration); extremely small number of authors who can explain at least 50% of an author's total citations (indicative of either small-scale or large-scale orchestration); and extremely large number of co-authors with more than 50 co-authored papers (indicative of large-scale orchestration). The distributions, potential thresholds based on 1% (and 5%) percentiles, and insights from these indicators are explored and put into perspective across science.
The vast majority of newer interventions had no mortality differences over older ones both overall and specifically in RCTs, while benefits for newer interventions were reported more frequently in observational studies.
Today's high-speed interfaces are limited by the bandwidth of the communication channel, tight power constraints and noise sources that differ from those in standard communication systems. The bandlimited channels make straight circuit solutions inefficient, and the power constraints make standard digital communication approaches infeasible. This thesis presents a system-level link design approach, integrating the noise and channel properties with communication algorithms and circuit-level power and speed constraints. Our model incorporates accurate statistics of the dominant link noise sources. Mapping the timing noise into effective voltage noise reveals the critical impact of high-frequency transmit jitter. The capacity of typical high-speed link backplane channels is shown to be between 50 and 100 Gb/s, which is much higher than 3 Gb/s data rates of currently deployed baseband links. To improve these practical links, we solve the power-constrained optimal linear precoding problem and formulate a bit-error rate (BER) driven optimization, including all link-specific noise sources and hardware constraints. We show that practical data rates are mainly limited by inter-symbol interference due to complexity constraints on the number of equalizer taps. The slicer resolution and sampling jitter limit the higher bandwidth utilization provided by multi-level modulations. Better circuits could improve this utilization to more than 2 bits/dimension. With current circuit precision, links with both PAM2 and PAM4 modulation, and a combination of transmit pre-emphasis and decision-feedback equalization (DFE) achieve 5–12 Gb/s data rates. With only minor modifications, the hardware needed to implement a PAM4 system can be used in a loop-unrolled single-tap DFE receiver. To get the maximum performance from either technique in practice, the link has to adapt itself to the channel. We designed a low-cost adaptive equalizer using data-based update filtering, which minimizes the required sampler front-end hardware and reduces the implementation cost in multi-level signaling schemes. A transceiver chip was fabricated in a 0.13 μm CMOS process to investigate dual-mode PAM2/PAM4 operation and the modifications of the standard adaptive algorithms necessary to operate in high-speed link environments. The experimental data match the statistical link model predictions extremely well, within a couple of mV, even at BERs lower than the required 10−15.
Abstract Several studies have addressed the effect of the Sp1 polymorphism of the collagen Iα 1 (COLIA1) gene on the prevalence of fractures. The results are not in full agreement on whether this polymorphism is associated with fracture risk. To clarify this uncertainty, we performed a meta-analysis including 13 eligible studies with 3641 subjects. The COLIA1 Sp1 polymorphism showed a dose-response relationship with the prevalence of fractures. The risk was 1.25-fold (95% CI, 1.09–1.45) in Ss heterozygotes versus SS homozygotes, 1.68-fold (95% CI, 1.35–2.10) in ss homozygotes versus SS> homozygotes, and 1.35 (95% CI, 1.04–1.75) for ss homozygotes versus Ss heterozygotes by random effects calculations. There was modest heterogeneity for these three effect estimates (p value for heterogeneity, 0.17, 0.16, and 0.08, respectively). The Sp1 polymorphism effects possibly were larger when the analysis was limited to studies considering only vertebral fractures (pooled risk ratios [RR], 1.30, 2.07, and 1.46, respectively). Conversely, the Sp1 polymorphism effects tended to be smaller in studies with mean patient age ≥65 years than in studies with younger patients on average, but the differences were not formally significant. We estimated the total average attributable fraction (AF) of fractures due to the s allele in European/U.S. populations as 9.4%. The meta-analysis suggests an important role for the Sp1 polymorphism in the regulation of fracture risk; however, potential heterogeneity across ethnic groups, age groups, and skeletal sites may be important to clarify in future studies. Very large studies or meta-analyses are required to document subtle genetic differences in fracture risk.
<div>Abstract<p><b>Background:</b> We report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes.</p><p><b>Methods:</b> Comprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols. Additional descriptive data extracted from publicly available sources were also collected. This information was entered in a searchable and publicly accessible database. We summarized the descriptive data across cohorts and reported the characteristics of this resource.</p><p><b>Results:</b> As of December 2015, the CEDCD includes data from 46 cohorts representing more than 6.5 million individuals (29% ethnic/racial minorities). Overall, 78% of the cohorts have collected blood at least once, 57% at multiple time points, and 46% collected tissue samples. Genotyping has been performed by 67% of the cohorts, while 46% have performed whole-genome or exome sequencing in subsets of enrolled individuals. Information on medical conditions other than cancer has been collected in more than 50% of the cohorts. More than 600,000 incident cancer cases and more than 40,000 prevalent cases are reported, with 24 cancer sites represented.</p><p><b>Conclusions:</b> The CEDCD assembles detailed descriptive information on a large number of cancer cohorts in a searchable database.</p><p><b>Impact:</b> Information from the CEDCD may assist the interdisciplinary research community by facilitating identification of well-established population resources and large-scale collaborative and integrative research. <i>Cancer Epidemiol Biomarkers Prev; 25(10); 1392–401. ©2016 AACR</i>.</p></div>
A 10-Gb/s serial link transmitter fabricated in the LSI 0.4-/spl mu/m CMOS process uses multilevel signaling (4-PAM) and a 3-tap pre-emphasis filter to reduce intersymbol interference (ISI) caused by channel low-pass effects. Due to the maximum on-chip frequency set by process limitations, a 5:1 output multiplexer is used to reduce the required clock frequency to 1/5 the symbol rate. With a 3.3-V supply, the chip shows an eye opening of >200 mV after a 10-m coaxial cable in simulations.
A superscalar processor that combines the best qualities of static and dynamic instruction scheduling to increase the performance of nonnumerical applications is described. The architecture performs all instruction scheduling statically to take advantage of the compiler's ability to schedule operations across many basic blocks efficiently. Since the conditional branches in nonnumerical code are highly data dependent, the architecture introduces the concept of boosted instructions, that is, instructions that are committed conditionally upon the result of later branch instructions. Boosting effectively removes the dependences caused by branches and makes the scheduling of side-effect instructions as simple as it is for instructions that are side-effect free. For efficiency, boosting is supported in the hardware by shadow structures that temporarily hold the side effects of boosted instructions until the conditional branches that the boosted instructions depend upon are executed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Abstract Though interest has grown significantly over the past decades in interventions that may slow the aging process, most evidence for these interventions still comes from experiments in non-human animals. These studies may suffer from design, quality and reporting issues. The quality and reporting of preclinical studies have not yet been studied systematically in anti-aging research. Here we analyzed the DrugAge database, assessing reporting study quality, bias and effect sizes across 667 anti-aging preclinical studies. We found significant shortcomings in reporting of crucial design features such as randomization and blinding, as well as large variation in reporting quality and effects across species. Non-mammal findings typically did not translate to mammals. Although anti-aging interventions may have different effects depending on when they are started, most studies began giving the intervention under investigation very early in the organism’s lifespan. Our findings suggest there is substantial room for improvement in preclinical anti-aging research.
