University of California, Berkeley

Modern logic synthesis techniques use multi-level technology-independent representations like And-Inverter-Graphs (AIGs) for digital logic. This involves structural rewriting, resubstitution, and refactoring based on directed-acyclic-graph (DAGs) traversal. Existing DAG-aware logic synthesis algorithms are designed to perform one specific optimization during a single DAG traversal. However, we empirically identify and demonstrate that these algorithms are limited in quality-of-results due to the solely considered optimization operation in the design concept. This work proposes Synthesis Orchestration, which is a fine-grained node-level optimization implying multiple optimizations during the single traversal of the graph. Our experimental results are comprehensively conducted on all 104 designs collected from ISCAS’85/89/99, VTR, and EPFL benchmark suites. The orchestration algorithms consistently outperform existing optimizations, rewriting, resubstitution, refactoring, leading to an average of 4% more node reduction with reasonable runtime cost for the single optimization. Moreover, we evaluate the orchestration algorithm in the sequential optimization, and as a plug-in algorithm in resyn and resyn3 flows in ABC, which demonstrate consistent logic minimization improvements (1%, 4.7% and 11.5% more node reduction on average). Finally, we integrate the orchestration into OpenROAD for end-to-end performance evaluations. Our results demonstrate the advantages of the orchestration optimization techniques, even after technology mapping and post-routing in the design flow.

Resistive random access memory (ReRAM)-based processing-in-memory (PIM) architectures have demonstrated great potential to accelerate Deep Neural Network (DNN) training/ inference. However, the computational accuracy of analog PIM is compromised due to the non-idealities, such as the conductance variation of ReRAM cells. The impact of these non-idealities worsens as the number of concurrently activated wordlines and bitlines increases. To guarantee computational accuracy, only a limited number of wordlines and bitlines of the crossbar array can be turned on concurrently, significantly reducing the achievable parallelism of the architecture. While the constraints on parallelism limit the efficiency of the accelerators, they also provide a new opportunity for finegrained mixed-precision quantization. To enable efficient DNN inference on practical ReRAM-based accelerators, we propose an algorithm-architecture co-design framework called Block-Wise mixed-precision Quantization (BWQ). At the algorithm level, BWQ-A introduces a mixed-precision quantization scheme at the block level, which achieves a high weight and activation compression ratio with negligible accuracy degradation. We also present the hardware architecture design BWQ-H, which leverages the low-bit-width models achieved by BWQ-A to perform high-efficiency DNN inference on ReRAM devices. BWQ-H also adopts a novel precision-aware weight mapping method to increase the ReRAM crossbars throughput. Our evaluation demonstrates the effectiveness of BWQ, which achieves a 6.08× speedup and a 17.47× energy saving on average compared to existing ReRAM-based architectures.

Online junction temperature monitoring of SiC MOSFET based on turn-off Miller plateau voltage (VMP,off) has been explored in this work. As the junction temperature rises, VMP,off experiences a decline while extending its duration, thereby enhancing the precision of sampling VMP,off with a diminutive turn-off resistance (Rg,off). A novel extraction approach for VMP,off is introduced, involving the continuous sampling of gate voltage via a network of resistances and an ADC. VMP,off is ascertained through the discrepancy between two consecutive output points of the ADC. Validation of this monitoring technique is conducted through double pulse tests and a buck converter under varying temperatures. Empirical findings demonstrate a commendable linear relationship between VMP,off and junction temperature. In the quest for a balance among thermal sensitivity accuracy, turn-off delay, and turn-off loss, a recommended value for Rg,off of SCT3040KR stands at approximately 15 Ω. Employing a 15 Ω Rg,off, the temperature sensitivity of VMP,off for SCT3040KR and SCT3105KR hovers around -11.3 mV/°C and -9.1 mV/°C, respectively. With calibrations of aging and threshold voltages in advance, the proposed methodology exhibits promising potential in the realm of SiC MOSFET junction temperature monitoring.

Quantum sensing has a bright future for applications in need of impeccable sensitivities. The study of periodic fields has resulted in various techniques, which deal with the limited coherence time of the quantum sensor in several ways. However, the periodic signal to measure could include forms of randomness as well, such as changes in phase or in frequency. In such cases, long measurement times required to detect the smallest of field amplitudes hamper the effectiveness of conventional techniques. In this paper, we propose and explore a robust sensing technique to combat this problem. For the technique, instead of measuring the signal amplitude directly, we measure another global property of the signal, in this case the standard deviation. This results in a much-improved sensitivity. We analyze the advantages and limitations of this technique, and we demonstrate the working with a measurement using a nitrogen-vacancy center. This work encourages scouting measurements of alternative statistics.

Background Vaccines for diarrhoea could have the ancillary benefit of preventing antibiotic use. We aimed to quantify and compare the expected impact of enteric vaccines on antibiotic use via Monte Carlo simulations. Methods We analysed data from a longitudinal birth cohort, which enrolled children from 2009 to 2012 from Bangladesh, India, Nepal, Pakistan, and Tanzania. We used Monte Carlo simulations to estimate hypothetical vaccine impact in nine vaccination scenarios (including six single vaccines and three combination vaccines) on antibiotic- treated diarrhoea, overall antibiotic courses, and antibiotic exposures to bystander pathogens. For each vaccine scenario, we randomly selected target pathogen-specific diarrhoea episodes to be prevented according to the specified vaccine efficacy and estimated the absolute and relative differences in incidence of antibiotic use outcomes between vaccine and no vaccine scenarios. Findings Among 1119 children, there were 3029 (135·3 courses per 100 child-years) antibiotic-treated diarrhoea episodes. Based on simulated results, a Shigella vaccine would cause the greatest reductions compared with the other single pathogen vaccines in antibiotic courses for all-cause diarrhoea (6·1% relative reduction; –8·2 courses per 100 child-years [95% CI –9·4 to –7·2]), antibiotic courses overall (1·0% relative reduction; –8·2 courses per 100 child-years [–9·4 to –7·2]), and antibiotic exposures to bystander pathogens (1·2% relative reduction; –15·9 courses per 100 child-years [–18·5 to –13·8]). An adenovirus–norovirus–rotavirus vaccine would cause the greatest reductions in antibiotic use (12·2 courses per 100 child-years [–13·7 to –11·0]) compared with the other combination vaccines. However, projected vaccine effects on antibiotic use in 2021 were 45–74% smaller than those estimated in 2009–12 accounting for reductions in diarrhoea incidence in the past decade. Interpretation Vaccines for enteric pathogens could result in up to 8–12 prevented courses of antibiotics per 100 vaccinated children per year. Combination vaccines will probably be necessary to achieve greater than 1% reductions in total antibiotic use among children in similar low-resource settings. Funding Wellcome Trust and Bill & Melinda Gates Foundation.

This chapter reviews the three major theoretical positions that underlie the sociology of intellectuals. It then links these theoretical positions to the type of concrete social intervention that is implied by the theory. Thus, the chapter provides an overview of this edited volume in terms of theories of intellectuals and their practical interventions in the real world. The first position conceptualises intellectuals as a stratum shaped by the particular social and economic settings surrounding them. As a stratum, intellectuals shape the world through public sociology, through which sociologists act on the world in accordance with their political positions. The second position conceptualises intellectuals as a class shaped primarily by economic and technocratic forces. As a class, intellectuals shape the world through sociological interventions, in which sociologists train social actors to create social change. The third position conceptualises intellectuals as a universal group shaped mostly by the internal features of academic life. As a universal group, intellectuals attempt to use their knowledge to solve social problems in a neutral way.

This paper presents the development and application of the equity and climate impacts optimization in community energy (ECOCE) model, a mixed integer linear tool designed to optimize equity-driven investment in community solar projects (CSPs). By providing insight on a variety of impacts of CSP investments, including electricity bill savings, solar production, and greenhouse gas emissions reduction, the model assists policymakers in understanding the possible trade-offs in benefits and impacts of CSP investments. Using a detailed case study of a one-time $100 million investment in CSPs in Washington State, the model evaluates potential scenarios under various funding distributions to determine the optimal allocation of state funds. The study highlights considerations of geographical equity and participation, trade-offs between maximizing greenhouse gas reductions and minimizing energy burden, and the potential to use the model in different regional contexts. The findings suggest that targeted investments can provide significant electricity bill savings ($6.5–8.5 million annually) for low-income communities while contributing to state decarbonization goals (4–42 kTons of avoided emissions annually) in Washington State, though political and practical considerations may influence the feasibility of these optimized allocations. The ECOCE model provides a robust framework for decision-makers aiming to balance a variety of political, equity, and climate change mitigation considerations in the transition to renewable energy.

The electrostatic correlations between ions profoundly influence the structure and forces within electrical double layers. Here, we apply the modified Gaussian renormalized fluctuation theory to investigate the counter-intuitive phenomenon of repulsion between two oppositely charged surfaces and discuss its relationship with overcharging. By accurately accounting for the effect of spatially varying ion–ion correlations, we capture these repulsive forces for divalent, trivalent, as well as tetravalent ions, in quantitative agreement with reported simulation results. We show that the opposite-charge repulsion is long-ranged with an effective length scale of a few nanometers. The strength of opposite-charge repulsion increases monotonically with the multivalent salt concentration, in stark contrast with the non-monotonic salt concentration dependence of other ion correlation-driven phenomena, such as overcharging and like-charge attraction. We also elucidate that the origin of the opposite-charge repulsion is the large number of ions attracted to the double layer as a result of ion–ion correlations, leading to higher osmotic pressure and stronger screening of the electrostatic attraction, which results in an overall repulsive force between two oppositely charged surfaces. Furthermore, we demonstrate that there is no causal relationship between opposite-charge repulsion and the overcharging of the surface. Opposite-charge repulsion is accompanied by overcharging at large separation distances but can also occur in normal double layers without overcharging at intermediate separation distances.

The Born–Oppenheimer framework stipulates that chemistry and physics occur on potential energy surfaces VBO(X) parameterized by a nuclear coordinate X, which are built by diagonalizing a BO Hamiltonian ĤBO(X). However, such a framework cannot recover many measurable chemical and physical features, including vibrational circular dichroism spectra. In this article, we show that a phase-space electronic Hamiltonian ĤPS(X,P), parameterized by both nuclear position X and momentum P, with a similar computational cost as solving ĤBO(X), can recover not just experimental vibrational circular dichroism signals but also a meaningful electronic current density that explains the features of the vibrational circular dichroism rotational strengths. Combined with earlier demonstrations that such Hamiltonians can also recover qualitatively correct electronic momenta with electronic densities that approximately satisfy a continuity equation, the data would suggest that, if one looks closely enough, chemistry in fact occurs on potential energy surfaces parameterized by both X and P, EPS(X, P). While the dynamical implications of such a phase-space electronic Hamiltonian are not yet known, we hypothesize that, by offering classical trajectories that explicitly offer nonzero electronic momentum while also conserving the total angular momentum (unlike Born–Oppenheimer theory), this new phase-space electronic structure Hamiltonian may well explain some fraction of the chiral-induced spin selectivity effect.

Purpose Electrocardiography (ECG) and respiratory‐gated preclinical cardiac CEST‐MRI acquisitions are difficult because of variable saturation recovery with T1, RF interference in the ECG signal, and offset‐to‐offset variation in Z‐magnetization and cardiac phase introduced by changes in cardiac frequency and trigger delays. Methods The proposed method consists of segmented saturation modules with radial FLASH readouts and golden angle progression. The segmented saturation blocks drive the system to steady‐state, and because center k‐space is sampled repeatedly, steady‐state saturation dominates contrast during gridding and reconstruction. Ten complete Z‐spectra were acquired in healthy mice using both ECG and respiratory‐gated and ungated methods. Z‐spectra were also acquired at multiple saturation B1 values to optimize for amide and Cr contrasts. Results There was no significant difference between CEST contrasts (amide, Cr, magnetization transfer) calculated from images acquired using ECG and respiratory‐gated and ungated methods (p = 0.27, 0.11, 0.47). A saturation power of 1.8μT provides optimal contrast amplitudes for both amide and total Cr contrast without significantly complicating CEST contrast quantification because of water direct saturation, magnetization transfer, and RF spillover between amide and Cr pools. Further, variability in CEST contrast measurements was significantly reduced using the ungated radial FLASH acquisition (p = 0.002, 0.006 for amide and Cr, respectively). Conclusion This method enables CEST mapping in the murine myocardium without the need for cardiac or respiratory gating. Quantitative CEST contrasts are consistent with those obtained using gated sequences, and per‐contrast variance is significantly reduced. This approach makes preclinical cardiac CEST‐MRI easily accessible, even for investigators without prior experience in cardiac imaging.

The original publication on the Pliocene Otibanda Formation in Papua New Guinea briefly reported on crocodyliform fossils, including isolated teeth that were tentatively assigned to the notosuchian subclade Sebecosuchia. In this study, we reassess the crocodyliform material from the Otibanda Formation and provide the first detailed descriptions of the same, including the purported sebecosuchian teeth. Direct examination of these teeth confirms their ziphodont condition based on the labiolingual compression of the crowns and the presence of serrated mesial and distal carinae. In addition to the ziphodont teeth, there are also non-serrate conical teeth that are tentatively referred to an undetermined species of Crocodylus as well as fragmentary postcranial elements that we refer to as Crocodylia incertae sedis. Considering the geological age and geographical origin of the isolated ziphodont tooth crowns from Papua New Guinea, they are unlikely to belong to a sebecosuchian crocodyliform. Instead, it is more plausible that they are referable to Mekosuchinae, a highly diverse crocodylian clade inclusive of ziphodont forms that was prevalent on mainland Australia for most of the Cenozoic.

Background Few programs exist to support aging in place for older adults. Age Self Care is a novel program providing older adults with evidence‐based information using group sessions embedded within the structure of a community‐based organization (CBO) to facilitate behavior change and support aging in place. We report on a preliminary study of Age Self Care conducted in collaboration between the University of California, San Francisco (UCSF) Division of Geriatrics, At Home With Growing Older (AHWGO), and San Francisco Village (SF Village). Methods We recruited middle‐income, community‐dwelling adults aged 65+ from university outpatient clinics. Participants attended eight 90‐min, video‐based group sessions and enrolled in SF Village, a non‐profit mutual support organization for older adults. Data collection included direct observations and a participant focus group. We used rapid analysis methods informed by the COM‐B model (Capability, Opportunity, Motivation, Behavior Change) to assess behavior change. Results Fourteen participants completed the 8‐week study (15 enrolled, 1 withdrew). Average attendance was 81% throughout the program. We found that 14 participants made concrete changes to optimize the ability to remain at home during the program. For example, participants engaged in evidence‐based falls risk reduction activities such as decluttering and improving lighting. We identified three facilitators to behavior change. First, Age Self Care promoted self‐management—the day‐to‐day management of health and chronic conditions by individuals—through education and community‐based resources. Second, peer support empowered participants to take charge of their health, home environment, and social networks. Third, the online platform created a community and was a catalyst for social opportunity. We identified one non‐modifiable barrier: pre‐existing financial barriers hindered some behavior change. Conclusions In this preliminary study, Age Self Care facilitated behavior change, including minor home modifications, fall risk reduction, and engagement in social networks, all of which support aging in place.

By combining in situ X‐ray diffraction, Zr K‐edge X‐ray absorption spectroscopy and 1H and 13C nuclear magnetic resonance (NMR) spectroscopy, we show that the properties of the final MOF are influenced by H2O and HCl via affecting the nucleation and crystal growth at the molecular level. The nucleation implies hydrolysis of monomeric zirconium chloride complexes into zirconium‐oxo species, and this process is promoted by H2O and inhibited by HCl, allowing to control crystal size by adjusting H2O/Zr and HCl/Zr ratios. The rate‐determining step of crystal growth is represented by the condensation of monomeric and oligomeric zirconium‐oxo species into clusters, or nodes, with the structure identical to that in secondary building units (SBU) of UiO‐66 framework. The rapid crystallization in the absence of HCl leads to formation of defective secondary building units with missing zirconium atoms, providing a pathway to control the number of defects in UiO‐66 crystals. Remarkably, we have shown that assembling of the metal nodes and linkers into the UiO‐66 structure is not the rate‐limiting step, and the degree of deprotonation of the linker has no direct effect on the crystallization kinetics or crystal size of product.

Objective To examine the relationship between etiologically-based preterm birth sub-groups and early postnatal growth according to gestational age at birth. Methods Prospective, multinational, cohort study involving 15 hospitals that monitored preterm newborns to hospital discharge. Measures/exposures: maternal demographics; etiologically-based preterm birth sub-groups; very, moderate and late preterm categories, and feeding. Primary outcomes: serial anthropometric measures expressed as z -scores of the INTERGROWTH-21 st preterm postnatal growth standards. Results We included 2320 singletons and 1180 twins: very=24.4% ( n = 856, including 178 < 28 weeks’ gestation); moderate=16.9% ( n = 592) and late preterm=58.6% ( n = 2052). The median (interquartile range) postmenstrual age at the last measure was 37 (36–38) weeks. The ‘no main condition’ sub-group percentage increased from early to late preterm; the ‘perinatal sepsis’ sub-group percentage decreased. ‘Perinatal sepsis’, ‘suspected IUGR’ and ‘fetal distress’ very and late preterm infants had lower postnatal growth patterns than the ‘no main condition’ reference sub-group. This pattern persisted in late but not very preterm infants when postnatal growth was corrected for weight z -score at birth. Conclusion The proportional contribution of etiologically-based preterm sub-groups and their postnatal growth trajectories vary by preterm category. Postnatal growth is partially independent of fetal growth in the majority of preterm infants (i.e., those born late preterm). Impact Preterm birth, the leading cause of under-5 mortality, is a highly heterogenous syndrome, with surviving infants at risk of suboptimal growth, morbidity, and impaired neurodevelopment. Both the proportional contribution of etiologically-based sub-groups and their postnatal growth trajectories vary by preterm category (very/moderate/late). The ‘perinatal sepsis’, ‘suspected IUGR’ and ‘fetal distress’ sub-groups amongst very and late preterm infants had lower postnatal growth than the ‘no main condition’ preterm infants. The pattern persisted after adjusting for birth size only in the late preterms. Postnatal growth is partially independent of fetal growth in the majority of preterm infants (i.e., those born late preterm).

Threat perception provokes a range of behaviour, from cooperation to conflict. Correctly interpreting others’ behaviour, and responding optimally, is thought to be aided by ‘stepping into their shoes’ (i.e. mentalising) to understand the threats they have perceived. But IR scholarship on the effects of attempting this exercise has yielded mixed findings. One missing component in this research is a clear understanding of the link between effort and accuracy. I use a US-based survey experiment (study N = 839; pilot N = 297) and a novel analytic approach to study mentalising accuracy in the domain of threat perception. I find that accurately estimating why someone feels threatened by either climate change or illegal immigration is conditional on sharing a belief in the issue’s overall dangerousness. Similar beliefs about dangerousness are not proxies for shared political identities, and accuracy for those with dissimilar beliefs does not exceed chance. Focusing first on the emotional states of those who felt threatened did not significantly improve accuracy. These findings suggest that: (1) effort does not guarantee accuracy in estimating the threats others see; (2) emotion understanding may not be a solution to threat mis-estimation; and (3) misperception can arise from basic task difficulty, even without information constraints or deception.

In mine wastewaters, three microbial sulfur oxidation pathways have the potential to cause different water quality outcomes. These outcomes can differ from abiotic models of sulfate and acidity predictions currently used to monitor potential sulfur risks. However, studies integrating microbiology and geochemistry in active mine tailings impoundments are very limited. Here, we developed a novel diagnostic approach to detect microbially driven sulfur pathways. Within this 28-day study, eight on-site, 500 L mesocosms were filled with water extracted directly from the water cap of an active Ni/Cu mine tailings impoundment. Diverse combinations of tailings, sulfur compounds, and nitrate amendments were added to the mesocosms simulating common operational variations experienced by active tailings impoundments. Mesocosm results linked complete SOx, S4I, and incomplete SOx + rDSR pathway occurrence (metagenomes, inferred from the identity, i.e. 16S rRNA) and activity (mRNA) to physiochemistry and sulfur geochemistry. By integrating the three lines of evidence, the diagnostic approach was able to identify which sulfur pathways were active under varying physiochemical conditions and how geochemical outcomes were affected. A relationship emerged between acid generation and soxCD expression (soxCD expression indicates the complete SOx pathway activity). However, observed proton yields and sulfate concentrations were less than those predicted by complete SOx pathway activity alone. This indicates other sulfur pathways, e.g. the partial S4I pathway (within Thiomonas and Halothiobacillus), and/or activity of the incomplete SOx pathway (within Thiobacillus and Desulfurivibrio) when either not coupled to rDSR, or paired with use of nitrate, influenced overall sulfur outcomes along with the complete SOx pathway.

Disadvantageous inequity aversion (IA), a negative response to receiving less than others, is a key building block of the human sense of fairness. While some theorize that IA is shared by species across the animal kingdom, others argue that it is an exclusively human evolutionary adaptation to the selective pressures of cooperation among non-kin. Essential to this debate is the empirical question of whether non-human animals are averse towards unequal resource distributions. Over the past two decades, researchers have reported that individuals from a wide range of taxa exhibit IA; tasks where participants can reject or accept a given distribution of rewards delivered the bulk of this evidence. Yet these results have been questioned on both conceptual and empirical grounds. In the largest empirical investigation of non-human IA to date, we synthesize the primary data from 23 studies using accept/reject tasks, covering 60 430 observations of 18 species. We find no evidence for IA in non-human animals in these tasks. This finding held across all species in the dataset and pre-registered subsets (all species reported to exhibit IA, primates reported to exhibit IA, chimpanzees and capuchin monkeys). Alternative interpretations of the data and implications for the evolution of fairness are discussed.

Magnetically connected observations of particle distributions and luminosity from the Reimei spacecraft are used to examine energy transport and conversion occurring above a discrete auroral arc. By combining imaging and in situ measurements it is shown how transverse electromagnetic and kinetic energy fluxes measured along the spacecraft trajectory converge across geomagnetic field‐lines into the acceleration region. It is shown how cross‐field energy transport is facilitated by the formation of vortices along the length of the arc. From an integration over the vertical extent of the acceleration region it is shown that the transverse and field‐aligned flow of energy into the arc locally supports the dissipation needed to power the electron acceleration observed. Estimates of gradients in electromagnetic and kinetic energy flows show how field‐aligned electron energization in the acceleration region is supported by the divergence of Poynting flux along and across the background magnetic field.