bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neoliberal Reason, Contemporary Music, and Proximal Critique
Authors: WILSON SAMUEL J. 
Published: August 2024

AbstractTheodor W. Adorno suggested that music is mediated by socially derived forms of reason, a provocation here considered with respect to neoliberalism. Drawing on a Foucauldian understanding of neoliberalism, which in Wendy Brown's summary takes neoliberalism as ‘a specific and normative mode of reason’, I consider what this means for immanent features of music and processes of its composition. This critical attention to music's formal, aesthetic register enables me to go beyond the more well-established (although nonetheless valuable) frameworks for discussing music and neoliberalism, which focus on music's relation to labour conditions and creative industries. A range of music and sonic art is discussed, work by Chino Amobi, Brian Eno, Bryn Harrison, Sarah Hennies, Johannes Kreidler, Wolfgang Rihm, Marina Rosenfeld, and John Zorn. I ultimately argue that some core features of Adorno's conception of critical art and music need reformulating for the neoliberal age.
Environmental enforcement, property rights, and violence: evidence from the Brazilian Amazon
Authors: Oliveira Gustavo Magalhães de , Miranda Bruno Varella 
Published: August 2024

Abstract
Conflicts over resources with poorly defined property rights have fuelled both deforestation and violence in the Brazilian Amazon. However, what happens when the State enhances its ability to monitor and enforce existing environmental laws? We study the case of the list of Municípios Prioritários, a policy that allocates additional resources to verify compliance with environmental laws in municipalities with high deforestation rates. Employing a difference-in-differences approach, our findings suggest that an improvement in the ability of the State to monitor and enforce environmental laws can reduce conflicts over the appropriation of value from resources with poorly defined property rights. Consistent with existing studies, we also find that the policy led to a reduction in deforestation rates in the Brazilian Amazon. Finally, we discuss the limitations of the current approach to curb violence in a region where the activity of mafias has considerably grown since the turn of the twenty-first century.
The Calm and Variable Inner Life of the Atlantic Intertropical Convergence Zone: The Relationship Between the Doldrums and Surface Convergence
Authors: Windmiller J. M. 
Published: August 2024

AbstractThe doldrums are regions of low wind speeds and variable wind directions in the deep tropics that have been known for centuries. Although the doldrums are often associated with the Intertropical Convergence Zone (ITCZ), the exact relationship remains unclear. This study re‐examines the relationship between low‐level convergence and the Atlantic doldrums. By analyzing the frequency distribution of low wind speed events in reanalysis and buoy data, we show that the doldrums are largely confined between the edges of the ITCZ marked by enhanced surface convergence. While the region between the edges is a region of high time‐mean precipitation, low wind speed events occur in the absence of precipitation. Based on these results, we hypothesize that low wind speed events occur in regions of low level divergence rather than convergence.
Large Scale Simulation of 3D Fault Rupture Subjected to Far‐Field Loading With PDS‐FEM: Application to the 2018 Palu Earthquake
Authors: Quaranta Lionel , Maddegedara Lalith , Kato Aitaro , Hori Muneo , Ichimura Tsuyoshi , Fujita Kohei , Nicolin Elia 
Published: August 2024

AbstractSimulating dynamic rupture of fault systems can be computationally demanding, as it requires reproducing complex fault geometry and accurately capturing waves propagating away from the rupture front. It is in particular challenging to predict an initial stress state consistent with fault geometries, heterogeneous distribution of surrounding materials, and far‐field tectonic loading. While standard techniques such as contact analysis and Lagrangian multipliers can be used to model the fault, it can lead to significant computational overhead in FEM. We extended Particle Discretization Scheme‐FEM, which provides numerically efficient crack treatment, without requiring contact analysis, to simulate dynamic fault rupture as a frictional crack propagating along a pre‐existing shear crack surface. Initial stress, which is consistent with initial frictional forces, material distribution and fault geometry, is derived using Coulomb friction and far‐field boundary conditions. The study first demonstrates the ability of the numerical method to reproduce a 2D ideal supershear scenario, and the underlying Burridge‐Andrew rupture mechanism. The methodology is then applied to the large scale simulation of the 2018 Palu earthquake on the Palu‐Koro fault. The simulation successfully reproduces the early and sustained supershear rupture which was observed for the Palu earthquake. Also, it indicates that the presence of an off‐fault damage zone can contribute to the low rupture velocity measured during the earthquake. Unlike sub‐Rayleigh earthquakes, the shockwave propagation was observed to lead to significant amplitudes of the ground motion even far from the fault.
Third-generation anti-CD19 CAR T cells for relapsed/refractory chronic lymphocytic leukemia: a phase 1/2 study
Authors: Derigs Patrick , Schubert Maria-Luisa , Dreger Peter , Schmitt Anita , Yousefian Schayan , Haas Simon , Röthemeier Caroline , Neuber Brigitte , Hückelhoven-Krauss Angela , Brüggemann Monika , Bernhard Helga , Kobbe Guido , Lindemann Albrecht , Rummel Mathias , Michels Birgit , Korell Felix , Ho Anthony D. , Müller-Tidow Carsten , Schmitt Michael 
Published: August 2024

AbstractThird-generation chimeric antigen receptor T cells (CARTs) for relapsed or refractory (r/r) chronic lymphocytic leukemia (CLL) may improve efficacy compared to second-generation CARTs due to their enhanced CAR design. We performed the first phase 1/2 investigator-initiated trial evaluating escalating doses of third-generation CARTs (HD-CAR-1) targeting CD19 in patients with r/r CLL and B-cell lymphoma. CLL eligibility criteria were failure to two therapy lines including at least one pathway inhibitor and/or allogeneic hematopoietic cell transplantation. Nine heavily pretreated patients received HD-CAR-1 at dose levels ranging from 1 × 106 to 200 × 106 CART/m2. In-house HD-CAR-1 manufacturing was successful for all patients. While neurotoxicity was absent, one case of grade 3 cytokine release syndrome was observed. By day 90, six patients (67%) attained a CR, five of these (83%) with undetectable MRD. With a median follow-up of 27 months, 2-year PFS and OS were 30% and 69%, respectively. HD-CAR-1 products of responders contained significantly more CD4 + T cells compared to non-responders. In non-responders, a strong enrichment of effector memory-like CD8 + T cells with high expression of CD39 and/or CD197 was observed. HD-CAR-1 demonstrated encouraging efficacy and exceptionally low treatment-specific toxicity, presenting new treatment options for patients with r/r CLL. Trial registration: #NCT03676504.
Temporally controlled multistep division of DNA droplets for dynamic artificial cells
Authors: Maruyama Tomoya , Gong Jing , Takinoue Masahiro 
Published: August 2024

AbstractSynthetic droplets mimicking bio-soft matter droplets formed via liquid-liquid phase separation (LLPS) in living cells have recently been employed in nanobiotechnology for artificial cells, molecular robotics, molecular computing, etc. Temporally controlling the dynamics of synthetic droplets is essential for developing such bio-inspired systems because living systems maintain their functions based on the temporally controlled dynamics of biomolecular reactions and assemblies. This paper reports the temporal control of DNA-based LLPS droplets (DNA droplets). We demonstrate the timing-controlled division of DNA droplets via time-delayed division triggers regulated by chemical reactions. Controlling the release order of multiple division triggers results in order control of the multistep droplet division, i.e., pathway-controlled division in a reaction landscape. Finally, we apply the timing-controlled division into a molecular computing element to compare microRNA concentrations. We believe that temporal control of DNA droplets will promote the design of dynamic artificial cells/molecular robots and sophisticated biomedical applications.
Controlling photothermoelectric directional photocurrents in graphene with over 400 GHz bandwidth
Authors: Koepfli Stefan M. , Baumann Michael , Gadola Robin , Nashashibi Shadi , Koyaz Yesim , Rieben Daniel , Güngör Arif Can , Doderer Michael , Keller Killian , Fedoryshyn Yuriy , Leuthold Juerg 
Published: August 2024

AbstractPhotodetection in the near- and mid-infrared spectrum requires a suitable absorbing material able to meet the respective targets while ideally being cost-effective. Graphene, with its extraordinary optoelectronic properties, could provide a material basis simultaneously serving both regimes. The zero-band gap offers almost wavelength independent absorption which lead to photodetectors operating in the infrared spectrum. However, to keep noise low, a detection mechanism with fast and zero bias operation would be needed. Here, we show a self-powered graphene photodetector with a > 400 GHz frequency response. The device combines a metamaterial perfect absorber architecture with graphene, where asymmetric resonators induce photothermoelectric directional photocurrents within the graphene channel. A quasi-instantaneous response linked to the photothermoelectric effect is found. Typical drift/diffusion times optimization are not needed for a high-speed response. Our results demonstrate that these photothermoelectric directional photocurrents have the potential to outperform the bandwidth of many other graphene photodetectors and most conventional technologies.
Fecal microbiota transplantation influences microbiota without connection to symptom relief in irritable bowel syndrome patients
Authors: Hartikainen Anna K. , Jalanka Jonna , Lahtinen Perttu , Ponsero Alise J. , Mertsalmi Tuomas , Finnegan Laura , Crispie Fiona , Cotter Paul D. , Arkkila Perttu , Satokari Reetta 
Published: August 2024

AbstractImbalanced microbiota may contribute to the pathophysiology of irritable bowel syndrome (IBS), thus fecal microbiota transplantation (FMT) has been suggested as a potential treatment. Previous studies on the relationship between clinical improvement and microbiota after FMT have been inconclusive. In this study, we used 16S rRNA gene amplicon and shotgun metagenomics data from a randomized, placebo controlled FMT trial on 49 IBS patients to analyze changes after FMT in microbiota composition and its functional potential, and to identify connections between microbiota and patients’ clinical outcome. As a result, we found that the successful modulation of microbiota composition and functional profiles by FMT from a healthy donor was not associated with the resolution of symptoms in IBS patients. Notably, a donor derived strain of Prevotella copri dominated the microbiota in those patients in the FMT group who had a low relative abundance of P. copri pre-FMT. The results highlight the multifactorial nature of IBS and the role of recipient’s microbiota in the colonization of donor’s strains.
Implementing a food first strategy can transform preventive healthcare
Authors: Yu Zhaoshuo , Ke Lijing , Lu Ting , Li Li , Gu Huaiyu , Rao Pingfan 
Published: August 2024

AbstractThe Food-First Strategy advocates seeking a nutritional solution for the prevention and treatment of disease before resorting to supplements or therapeutic agents. Advances in knowledge of nutrition at the cellular level are providing information on how micronutrients are incorporated into cells and how they exert their actions. Micronutrients, in the form of naturally occurring nanoparticles, are more bioavailable and also act as antioxidants to tackle inflammation and promote cellular regeneration and repair. They are the new “superheroes of nutrition” and an understanding of their metabolic impact can explain and support associated health claims.
WorldSeasons: a seasonal classification system interpolating biome classifications within the year for better temporal aggregation in climate science
Authors: Littleboy Chris , Subke Jens-Arne , Bunnefeld Nils , Jones Isabel L. 
Published: August 2024

AbstractWe present a seasonal classification system to improve the temporal framing of comparative scientific analysis. Research often uses yearly aggregates to understand inherently seasonal phenomena like harvests, monsoons, and droughts. This obscures important trends across time and differences through space by including redundant data. Our classification system allows for a more targeted approach. We split global land into four principal climate zones: desert, arctic and high montane, tropical, and temperate. A cluster analysis with zone-specific variables and weighting splits each month of the year into discrete seasons based on the monthly climate. We expect the data will be able to answer global comparative analysis questions like: are global winters less icy than before? Are wildfires more frequent now in the dry season? How severe are monsoon season flooding events? This is a natural extension of the historical concept of biomes, made possible by recent advances in climate data availability and artificial intelligence.
Waste management optimization with NLP modeling and waste-to-energy in a circular economy
Authors: Hernández-Romero Ilse María , Niño-Caballero Javier Camilo , González Lucy T. , Pérez-Rodríguez Michael , Flores-Tlacuahuac Antonio , Montesinos-Castellanos Alejandro 
Published: August 2024

AbstractThis work presents a methodology integrating Non-Linear Programming (NLP) for multi-objective and multi-period optimization, addressing sustainable waste management and energy conversion challenges. It integrates waste-to-energy (WtE) technologies such as Anaerobic Digestion (AD), Incineration (Inc), Gasification (Gsf), and Pyrolysis (Py), and considers thermochemical, technical, economic, and environmental considerations through rigorous non-linear functions. Using Mexico City as a case study, the model develops waste management strategies that balance environmental and economic aims, considering social impacts. A trade-off solution is proposed to address the conflict between objectives. The economical optimal solution generates 1.79M$ with 954 tons of CO2 emissions while the environmental one generates 0.91M$ and reduces emissions by 54%, where 40% is due to gasification technology. Moreover, the environmentally optimal solution, with incineration and gasification generates 9500 MWh/day and 5960 MWh/day, respectively, demonstrates the capacity of the model to support sustainable energy strategies. Finally, this work presents an adaptable framework for sustainable waste management decision-making.
In vitro analysis of a novel dimethylaminododecyl methacrylate modification of dental acrylic soft liner material
Authors: Ammar Mohamed M. , Elkammar Hala A. , Abdelkhalek Abdelfattah A. , Abdelrazek Nada A. , Emam Ahmed A. , Abdelhameed Bassem M. 
Published: August 2024

AbstractSoft denture liners have limitations like short lifespan and increased microbial buildup. Despite promise as a non-leaching antimicrobial polymer in dentistry, the impact of dimethylaminododecyl methacrylate (DMADDM) on soft liner performance remains unexplored. This study aimed to evaluate the effect of integrating different concentrations of DMADDM to cold cure acrylic resin soft liner, on its antimicrobial activity, cytotoxicity, and physical properties. The same properties were compared to a conventional commercially available denture soft liner. The study employed a control group (conventional soft liner) and three test groups containing 3.3%, 6.6%, and 10% (total mass fraction) DMADDM, respectively. Antimicrobial activity against Candida albicans and Streptococcus mutans was assessed through colony counts and biofilm biomass. Cytotoxicity was evaluated using an oral epithelial cell line. Additionally, wettability and hardness were measured to assess physical properties. Incorporation of DMADDM significantly reduced Candida albicans and Streptococcus mutans counts, and biofilm biomass, compared to the control. Additionally, DMADDM improved the soft liner's wettability and mitigated long-term hardness increase. In conclusion, DMADDM holds promise in enhancing soft liner performance. However, careful selection of its optimum concentration is crucial to ensure both safety and efficacy for future clinical use.
Comparative metabolome variation in Brassica juncea different organs from two varieties as analyzed using SPME and GCMS techniques coupled to chemometrics
Authors: Farag Mohamed A. , Goyal Vinod , Baky Mostafa H. 
Published: August 2024

AbstractIndian mustard (Brassica juncea; Brassicaceae) is an edible, oilseeds-yielding crop widely consumed as a food spice owing to its richness in nutrients with several health benefits. The current study aims to dissect the B. juncea metabolome heterogeneity among its different organs including leaf, stem, flower, and seed. Moreover, assessing the metabolome differences between two different varieties RH-725 and RH-761 grown at the same conditions. Gas chromatography-mass spectrometry (GC–MS) post-silylation was used to dissect the composition of nutrient metabolites coupled to multivariate data analysis. Variation in sulphur aglycones was measured using headspace-solid phase-microextraction HS-SPME coupled to GC–MS. A total of 101 nutrient metabolites were identified with the abundance of sugars represented by monosaccharides in all organs, except for seeds which were enriched in disaccharides (sucrose). α-Linolenic acid was detected as a marker fatty acid in leaf from RH-725 at 12.5 µg/mg. Malic acid was detected as a significant variant metabolite between the two varieties as detected in the leaf from the RH-725 variety at ca. 128.2 µg/mg compared to traces in RH-761. 7 Volatile sulphur compounds were detected at comparable levels in RH-725 and RH-761, with 3-butenyl isothiocyanate was the most abundant at 0.8–2 ng/mg.
DFT electronic structure investigation of chromium ion-implanted cupric oxide thin films dedicated for photovoltaic absorber layers
Authors: Ungeheuer Katarzyna , Marszalek Konstanty W. , Tokarz Waldemar , Perzanowski Marcin , Kąkol Zbigniew , Marszalek Marta 
Published: August 2024

AbstractThis study explores the enhancement of cupric oxide (CuO) thin films for photovoltaic applications through chromium doping and subsequent annealing. Thin films of CuO were deposited on silicon and glass substrates using reactive magnetron sputtering. Chromium was introduced via ion implantation, and samples were annealed to restore the crystal structure. The optical and structural properties of the films were characterized using X-ray diffraction, spectrophotometry, and spectroscopic ellipsometry. Results indicated that implantation reduced the absorbance and conductivity of the films, while annealing effectively restored these properties. Sample implanted with 10 keV energy and 1 × 1014 cm−2 dose of Cr ions, after annealing had sheet resistance of 1.1 × 106 Ω/sq compared to 1.7 × 106 Ω/sq for non implanted and annealed CuO. Study of crystalline structure confirmed the importance of annealing as it reduced the stress present in the material after deposition and implantation. Density Functional Theory (DFT) calculations were performed to investigate the electronic structure and optical properties of CuO with varying levels of chromium doping. Calculations revealed an energy gap of 1.8 eV for undoped CuO, with significant changes in optical absorption for doped samples. Energy band gap determined using absorbance measurement and Tauc plot method had value of 1.10 eV for as deposited CuO. Samples after implantation and annealing had energy band gap value increased to about 1.20 eV. The study demonstrates that chromium doping and subsequent annealing can enhance the optical and electronic properties of CuO thin films, making them more efficient for photovoltaic applications.
Exploring the determinants of under-five mortality and morbidity from infectious diseases in Cambodia—a traditional and machine learning approach
Authors: Helldén Daniel , Sok Serey , Nordenstam Alma , Orsini Nicola , Nordenstedt Helena , Alfvén Tobias 
Published: August 2024

AbstractCambodia has made progress in reducing the under-five mortality rate and burden of infectious diseases among children over the last decades. However the determinants of child mortality and morbidity in Cambodia is not well understood, and no recent analysis has been conducted to investigate possible determinants. We applied a multivariable logistical regression model and a conditional random forest to explore possible determinants of under-five mortality and under-five child morbidity from infectious diseases using the most recent Demographic Health Survey in 2021–2022. Our findings show that the majority (58%) of under-five deaths occurred during the neonatal period. Contraceptive use of the mother led to lower odds of under-five mortality (0.51 [95% CI 0.32–0.80], p-value 0.003), while being born fourth or later was associated with increased odds (3.25 [95% CI 1.09–9.66], p-value 0.034). Improved household water source and higher household wealth quintile was associated with lower odds of infectious disease while living in the Great Lake or Coastal region led to increased odds respectively. The odds ratios were consistent with the results from the conditional random forest. The study showcases how closely related child mortality and morbidity due to infectious disease are to broader social development in Cambodia and the importance of accelerating progress in many sectors to end preventable child mortality and morbidity.
A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features
Authors: Carnevali Davide , Zhong Limei , González-Almela Esther , Viana Carlotta , Rotkevich Mikhail , Wang Aiping , Franco-Barranco Daniel , Gonzalez-Marfil Aitor , Neguembor Maria Victoria , Castells-Garcia Alvaro , Arganda-Carreras Ignacio , Cosma Maria Pia 
Published: August 2024

AbstractCellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a substantial challenge. This heterogeneity often reflects variations in the chromatin structure, influenced by factors such as viral infections and cancer, which dramatically reshape the cellular landscape. To address the challenge of identifying distinct cell states, we developed artificial intelligence of the nucleus (AINU), a deep learning method that can identify specific nuclear signatures at the nanoscale resolution. AINU can distinguish different cell states based on the spatial arrangement of core histone H3, RNA polymerase II or DNA from super-resolution microscopy images. With only a small number of images as the training data, AINU correctly identifies human somatic cells, human-induced pluripotent stem cells, very early stage infected cells transduced with DNA herpes simplex virus type 1 and even cancer cells after appropriate retraining. Finally, using AI interpretability methods, we find that the RNA polymerase II localizations in the nucleoli aid in distinguishing human-induced pluripotent stem cells from their somatic cells. Overall, AINU coupled with super-resolution microscopy of nuclear structures provides a robust tool for the precise detection of cellular heterogeneity, with considerable potential for advancing diagnostics and therapies in regenerative medicine, virology and cancer biology.