Global Bioenergy Availability

In efforts to decarbonize and mitigate climate change impacts, some sectors require unprecedented levels of technological innovation to substantially reduce greenhouse gas emissions. This is especially true for air transportation and maritime shipping, where vehicle electrification is currently infeasible due to limitations in available energy storage technologies. The use of biomass to produce readily substitutable (“drop-in”) and low-carbon liquid fuels presents a lever to reduce emissions along the lifecycle of the fuel. The potential to scale-up production of such fuels depends on establishing a robust supply chain for biogenic feedstocks and on building and operating cost-competitive, high-throughput biorefineries. The ultimate ‘ceiling’ for displacing fossil fuels with bio-based fuels is set by the supply of primary biomass. Existing estimates of biomass potential are heterogenous, ranging from 2 to 1200 EJ/yr for energy crops and 8-215 EJ/yr for biomass sourced as waste or residue. We provide a summary of current understanding and outline the underlying assumptions to evaluate whether these conditions are realistic, sustainable, and comprise a future which is worth pursuing. Motifs within the analysis point towards sizable barriers limiting the development of bioenergy to cover future energy demand, such as the logistics of collection and the implications of large-scale land use. For the case of agricultural residues, where such challenges can be partially mitigated, we conservatively estimate a global potential of 18±15 EJ/yr. for 2050, compared to a median estimate from meta-analysis of 27.5 EJ/yr. We dive into this apparent discrepancy, identifying multiple sources of uncertainty. Overall, our findings show that bio-energy alone is unlikely to cover the needs of decarbonizing tough-to-decarbonize transportation modes such as maritime shipping and aviation in a sustainable way

An implantable piezoelectric ultrasound stimulator (ImPULS) for deep brain activation

Precise neurostimulation can revolutionize therapies for neurological disorders. Electrode-based stimulation devices face challenges in achieving precise and consistent targeting due to the immune response and the limited penetration of electrical fields. Ultrasound can aid in energy propagation, but transcranial ultrasound stimulation in the deep brain has limited spatial resolution caused by bone and tissue scattering. Here, we report an implantable piezoelectric ultrasound stimulator (ImPULS) that generates an ultrasonic focal pressure of 100 kPa to modulate the activity of neurons. ImPULS is a fully-encapsulated, flexible piezoelectric micromachined ultrasound transducer that incorporates a biocompatible piezoceramic, potassium sodium niobate [(K,Na)NbO3]. The absence of electrochemically active elements poses a new strategy for achieving long-term stability. We demonstrated that ImPULS can i) excite neurons in a mouse hippocampal slice ex vivo, ii) activate cells in the hippocampus of an anesthetized mouse to induce expression of activity-dependent gene c-Fos, and iii) stimulate dopaminergic neurons in the substantia nigra pars compacta to elicit time-locked modulation of nigrostriatal dopamine release. This work introduces a non-genetic ultrasound platform for spatially-localized neural stimulation and exploration of basic functions in the deep brain

The Response Regulator OmpR Negatively Controls the Expression of Genes Implicated in Tilimycin and Tilivalline Cytotoxin Production in Klebsiella oxytoca

Klebsiella oxytoca toxigenic strains represent a critical health threat, mainly due to their link to antibiotic-associated hemorrhagic colitis. This serious condition results from the bacteria’s ability to produce tilimycin and tilivalline cytotoxins. Our research highlights the pivotal role of OmpR, a key regulator within the EnvZ/OmpR two-component system, in controlling the virulence factors associated with K. oxytoca. Our findings strongly indicate that OmpR is a repressor of the aroX and npsA genes, the first genes of aroX and NRPS operons, respectively, which are indispensable for producing these enterotoxins. Notably, in the absence of OmpR, we observe a significant increase in cytotoxic effects on Caco-2 cells. These observations identify OmpR as a crucial negative transcription regulator for both operons, effectively managing the release of these cytotoxins. This research deepens our understanding of the mechanisms of toxigenic K. oxytoca and opens promising avenues for targeting OmpR for new therapeutic interventions. By focusing on this innovative approach, we can develop more effective solutions to combat this pressing health challenge, ultimately improving patient outcomes against this pathogen

Visual Acuity Outcomes and Influencing Factors in a Cohort of UK Real-World Diabetic Macular Oedema Patients During the First Two Years of Anti-VEGF Treatment

Background/Objectives: The visual acuity (VA) outcomes after the first and second years of anti-vascular endothelial growth factor (anti-VEGF) treatment in patients with diabetic macular oedema (DMO) were evaluated, and the factors associated with treatment success were investigated. Methods: Using Medisoft electronic medical records (UK), this retrospective cohort study analysed VA outcomes, changes, and determinants in DMO patients at year 1 and year 2 after initial anti-VEGF injection. Descriptive analysis examined baseline demographics and clinical characteristics, while regression models were used to assess associations between these factors and changes in VA. Results: 728 DMO patients (1035 eyes) treated with anti-VEGFs (ranibizumab, aflibercept, or bevacizumab) at the Northern Ireland Mater Macular Clinic from 2008 to 2021 were evaluated. The mean age was 64.5 (SD 12.8) years, and 59.6% were male. In the first year, the median annual injection number and interval were 6.0 (IQR 5.0–8.0) and 6.1 weeks (IQR 5.4–7.8), respectively, and in the second year, they were 3.0 (IQR 2.0–5.0) and 10.0 weeks (IQR 6.5–20.1). In the first two treatment years, 83.4% and 79.8% of eyes had improved/stable VA (ISVA) respectively. The injection number, interval, baseline VA, age, and proliferative diabetic retinopathy (PDR) significantly impacted VA outcomes. Conclusions: Our study confirms the effectiveness of anti-VEGF treatments in improving or maintaining vision for DMO patients, consistent with previous real-world clinical data. An elder age, a better baseline VA, low annual injection numbers (<5), and less frequent injection intervals (≥12 weeks) were negatively associated with ISVA success in the first two years. These findings have implications for managing patient expectations, allocating resources, and understanding DMO clinical management

Microbial methanogenesis fueled by freshwater infiltration and oil biodegradation in the Siljan impact structure, Sweden

Deeply fractured rocks of meteorite impact craters are suggested as prime niches for subsurface microbial colonization. Methane can be a product of such microbial communities and seeps of methane from impact craters on Earth are of strong interest as they act as analogs for Mars. Previous studies report signs of ancient microbial methanogenesis in the Devonian Siljan meteorite impact structure in Sweden, but the proportion of microbial methane, metabolic pathways, and potential modern activity remain elusive. In this study, gas composition, hydrochemistry, oil organic geochemistry, and microbial community analyses are reported in 400 m deep fractures of the Siljan impact structure. The results showed a dominantly microbial origin for methane, which was supported by highly negative δ13CCH4 and positive δ13CCO2 values along with multiply substituted isotopologues (Δ13CH3D) that indicated disequilibrium fractionation due to microbial kinetic isotope effects. The presence of C2 to C5 hydrocarbons suggested a minor thermogenic input in the gas mix. Characterization of the microbial community via 16S rRNA gene amplicon sequencing and real-time PCR indicated a low abundance of several methanogenic archaeal populations, which is common for settings with active methanogenesis. Evidence of oil biodegradation suggested that secondary microbial hydrocarbon utilization was involved in the methanogenesis. Low sulfate and high alkalinity in the groundwaters also suggested a dominantly microbial methane formation driven by infiltration of freshwater that was coupled to sulfate reduction and secondary utilization of early mature thermogenic hydrocarbons

Formal Privacy Proof of Data Encoding: The Possibility and Impossibility of Learnable Encryption

CCS ’24, October 14–18, 2024, Salt Lake City, UT, USAWe initiate a formal study on the concept of learnable obfuscation and aim to answer the following question: is there a type of data encoding that maintains the "learnability" of encoded samples, thereby enabling direct model training on transformed data, while ensuring the privacy of both plaintext and the secret encoding function? This long-standing open problem has prompted many efforts to design such an encryption function, for example, NeuraCrypt and TransNet. Nonetheless, all existing constructions are heuristic without formal privacy guarantees, and many successful reconstruction attacks are known on these constructions assuming an adversary with substantial prior knowledge. We present both generic possibility and impossibility results pertaining to learnable obfuscation. On one hand, we demonstrate that any non-trivial, property-preserving transformation which enables effectively learning over encoded samples cannot offer cryptographic computational security in the worst case. On the other hand, from the lens of information-theoretical security, we devise a series of new tools to produce provable and useful privacy guarantees from a set of heuristic obfuscation methods, including matrix masking, data mixing and permutation, through noise perturbation. Under the framework of PAC Privacy, we show how to quantify the leakage from the learnable obfuscation built upon obfuscation and perturbation methods against adversarial inference. Significantly sharpened utility-privacy tradeoffs are achieved compared to state-of-the-art accounting methods when measuring privacy against data reconstruction and membership inference attacks

Place identity: a generative AI’s perspective

Do cities have a collective identity? The latest advancements in generative artificial intelligence (AI) models have enabled the creation of realistic representations learned from vast amounts of data. In this study, we test the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images. We asked questions on the place identity of 64 global cities to two generative AI models, ChatGPT and DALL·E2. Furthermore, given the ethical concerns surrounding the trustworthiness of generative AI, we examined whether the results were consistent with real urban settings. In particular, we measured similarity between text and image outputs with Wikipedia data and images searched from Google, respectively, and compared across cases to identify how unique the generated outputs were for each city. Our results indicate that generative models have the potential to capture the salient characteristics of cities that make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in simulating the built environment in regard to place-specific meanings. It contributes to urban design and geography literature by fostering research opportunities with generative AI and discussing potential limitations for future studies

Measurement of the double-diferential inclusive jet cross section in proton-proton collisions at √s = 5.02 TeV

The inclusive jet cross section is measured as a function of jet transverse momentum pT and rapidity y. The measurement is performed using proton-proton collision data at s = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb−1. The jets are reconstructed with the anti-kT algorithm using a distance parameter of R = 0.4, within the rapidity interval |y| < 2, and across the kinematic range 0.06 < pT < 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling αS

Photonic Integrated Devices Manufacturing Workforce Preparation Assessment Report: Middle Skilled Technicians

The Conducere-MIT Collaboratory conducted a Manufacturing Workforce Preparation assessment (MWP) for photonic integrated devices, particularly bio-photonic devices. Leveraging data from O*NET and expert interviews, the team identified the need for two manufacturing technician positions, the Photonic Integrated Circuit Technician and the Functionalization Technician. The team identified tasks, skills, and competencies that are critical and needed at entry for manufacturing technicians producing photonic integrated devices. While tasks between these positions are expected to vary somewhat, the skills and competencies needed to be successful are not expected to vary much. Additionally, needed skills and competencies will likely differ for technicians working predominantly with automated equipment and technologists who conduct their work more manually. Much of what technicians need to be able to do will be learned on the job. This report first shares what photonic integrated devices are and summarizes our findings relevant to the market for this emerging technology. The report then details role, task, skill, and competency findings for the technician positions, and provides insight into equipment, education, recruiting, hiring, and training.DoD ManTec

Sequence‐Sensitivity in Functional Synthetic Polymer Properties

Recently, a new class of synthetic methyl methacrylate‐based random heteropolymers (MMA‐based RHPs) has displayed protein‐like properties. Their function appears to be insensitive to the precise sequence. Here, through atomistic molecular dynamics simulation, we show that there are universal protein‐like features of MMA‐based RHPs that are insensitive to the sequence, and mostly depend on the overall composition. In particular, we find that MMA‐based RHPs “fold” into globules with heterogeneous hydration patterns. However, the insensitivity to sequence identity observed in MMA‐based RHPs dramatically changes when we substitute the backbone architecture with acrylate or replace the oxygen atom in the side chain with a nitrogen atom (methacrylamide or acrylamide). In such scenarios, the sequence contributes significantly to the compactness and the hydration of monomers. Using principal component analysis and an intersection‐over‐union based index, we demonstrate that different sequences may not overlap in the property space, meaning that their properties are controlled by the sequence rather than fixed composition. We further investigate the sequence‐insensitive capability of the MMA‐based RHPs as previously reported on bacterial phospholipase OmpLA stabilization through heterodimerization. As experimentally observed, such polymers enhance the stability of OmpLA as reliably as its native bilayer environment. The design of such MMA‐based RHPs provides a sequence‐insensitive alternative to protein‐mimetic biomaterials that is orthogonal to the sequence‐structure‐function paradigm of proteins