bluuebunny/crossref_metadata_2025 huggingface dataset:
Maximum drag reduction state of viscoelastic turbulent channel flow: marginal inertial turbulence or elasto-inertial turbulence
Authors: Wang Suming , Zhang Wenhua , Wang Xinyi , Li Xiaobin , Zhang Hongna , Li Fengchen
Published: March 2023

The essence of the maximum drag reduction (MDR) state of viscoelastic drag-reducing turbulence (DRT) is still under debate, which mainly holds two different types of views: the marginal state of inertial turbulence (IT) and elasto-inertial turbulence (EIT). To further promote its understanding, this paper conducts a large number of direct numerical simulations of DRT at a modest Reynolds numberRewith$Re = 6000$for the FENE-P model that covers a wide range of flow states and focuses on the problem of how nonlinear extension affects the nature of MDR by varying the maximum extension length$L$of polymers. It demonstrates that the essence of the MDR state can be both IT and EIT, where$L$is somehow an important parameter in determining the dominant dynamics. Moreover, there exists a critical$L_c$under which the minimum flow drag can be achieved in the MDR state even exceeding the suggested MDR limit. Systematic analyses on the statistical properties, energy spectrum, characteristic structures and underly dynamics show that the dominant dynamics of the MDR state gradually shift from IT-related to EIT-related dynamics with an increase of$L$. The above effects can be explained by the effective elasticity introduced by different$L$at a fixed Weissenberg number (Wi) as well as the excitation of pure EIT. It indicates that larger$L$introduces more effective elasticity and is favourable to EIT excitation. Therefore, we argue that the MDR state is still dominated by IT-related dynamics for the case of small$L$, but replaced by EIT-related dynamics at high$L$. The obtained results can harmonize the seemingly controversial viewpoints on the dominant dynamics of the MDR state and also provide some ideas for breaking through the MDR limit, such as searching for a polymer solution with a proper molecular length and concentration.
Immigration, Backlash, and Democracy
Authors: PEVNICK RYAN
Published: March 2023

How do considerations related to backlash affect the desirability of pursuing otherwise justified immigration policies? This paper argues that backlash-related considerations bear on immigration policy decisions in ways that are both more powerful and complicated than typically recognized. The standard possibility, the egalitarian backlash argument, endorses immigration restrictions in order to protect support for egalitarian distributive institutions. The paper shows that this account does not, by itself, provide a convincing rationale for restricting immigration because such diminished support is (a) likely outweighed by the benefits of more permissive immigration policies and (b) caused by the objectionable preferences of citizens. However, the paper develops an alternative account of the relevance of backlash-related considerations, the democratic backlash argument, which holds that increased levels of immigration threaten to contribute to undermining democratic institutions. This argument provides a more powerful rationale for restricting immigration, one that can—under identified conditions—justify immigration restrictions.
Childhood predictors of self-harm, externalised violence and transitioning to dual harm in a cohort of adolescents and young adults
Authors: Steeg Sarah , Farooq Bushra , Taylor Peter , Shafti Matina , Mars Becky , Kapur Nav , Webb Roger T
Published: March 2023

Background

The aetiology of dual harm (co-occurring self-harm and violence towards others) is poorly understood because most studies have investigated self-harm and violence separately. We aimed to examine childhood risk factors for self-harm, violence, and dual harm, including the transition from engaging in single harm to dual harm.

Methods

Data from the Avon Longitudinal Study of Parents and Children, a UK-based birth cohort study, were used to estimate prevalence of self-reported engagement in self-harm, violence, and dual harm at ages 16 and 22 years. Risk ratios were calculated to indicate associations across various self-reported childhood risk factors and risks of single and dual harm, including the transition from single harm at age 16 years to dual harm at age 22.

Results

At age 16 years, 18.1% of the 4176 cohort members had harmed themselves, 21.1% had engaged in violence towards others and 3.7% reported dual harm. At age 22 the equivalent prevalence estimates increased to 24.2, 25.8 and 6.8%, respectively. Depression and other mental health difficulties, drug and alcohol use, witnessing self-harm and being a victim of, or witnessing, violence were associated with higher risks of transitioning from self-harm or violence at age 16 to dual harm by age 22.

Conclusions

Prevalence of dual harm doubled from age 16 to 22 years, highlighting the importance of early identification and intervention during this high-risk period. Several childhood psychosocial risk factors associated specifically with dual harm at age 16 and with the transition to dual harm by age 22 have been identified.
Reliability of the Reflective Essay Marking Scale (REMS): a scale for marking of students’ reflective essays
Authors: Chigwedere Craig , Fitzmaurice Brian , Thwaites Richard
Published: March 2023

Personal practice (PP) is widely practised and a requirement across major psychology and psychotherapy organizations and modalities. However, one of the challenges for training institutions is how to assess the quality of such PP. The Reflective Essay Marking Scale (REMS) was developed to improve standardization of marking reflective essays in cognitive behavioural psychotherapy (CBT) training. A small sample of 16 expert CBT participants recruited by email used the REMS to rate two mock reflective essays in a within-subjects design. The internal consistency of REMS was acceptable (Cronbach’s α=.73) with excellent inter-rater reliability. Across the raters, it sufficiently differentiated quality (t12=4.91; p<.0001). Although these are the results of a preliminary and very small study with a small sample using mock essays, the REMS may be a useful scale, allowing CBT courses to account for students’ reflective work in a standardized way. A larger validation study is required in the future.

Key learning aims

(1)

To improve the thinking about what raters should focus on when rating the reflective essays of trainee therapists.

(2)

To describe the development of the scale and how its reliability was tested.

(3)

To improve the transparency and objectivity in assessing and rating reflective practice.
Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change‐Driven Sea‐Level Rise and Coastal Flooding Hazards in the Chesapeake Bay
Authors: Sherpa Sonam Futi , Shirzaei Manoochcher , Ojha Chandrakanta
Published: March 2023

Future projections of sea‐level rise (SLR) used to assess coastal flooding hazards and exposure throughout the 21st century and devise risk mitigation efforts often lack an accurate estimate of coastal vertical land motion (VLM) rate, driven by anthropogenic or non‐climate factors in addition to climatic factors. The Chesapeake Bay (CB) region of the United States is experiencing one of the fastest rates of relative sea‐level rise on the Atlantic coast of the United States. This study uses a combination of space‐borne Interferometric Synthetic Aperture Radar (InSAR), Global Navigation Satellite System (GNSS), Light Detecting and Ranging (LiDAR) data sets, available National Oceanic and Atmospheric Administration (NOAA) long‐term tide gauge data, and SLR projections from the Intergovernmental Panel on Climate Change (IPCC), AR6 WG1 to quantify the regional rate of relative SLR and future flooding hazards for the years 2030, 2050, and 2100. By the year 2100, the total inundated areas from SLR and subsidence are projected to be 454(316–549)–600(535–690)  for Shared Socioeconomic Pathways (SSPs) 1–1.9 to 5–8.5, respectively, and 342(132–552)–627(526–735)  only from SLR. The effect of storm surges based on Hurricane Isabel can increase the inundated area to 849(832–867)–1,117(1,054–1,205) km2 under different VLM and SLR scenarios. We suggest that accurate estimates of VLM rate, such as those obtained here, are essential to revise IPCC projections and obtain accurate maps of coastal flooding and inundation hazards. The results provided here inform policymakers when assessing hazards associated with global climate changes and local factors in CB, required for developing risk management and disaster resilience plans.
Revisiting HF Ground Wave Propagation Losses Over the Ocean: A Comparison of Long‐Term Observations and Models
Authors: Kirincich Anthony , Emery Brian
Published: March 2023

Understanding variations in the received power levels for land‐based high frequency radar (HFR) systems is critical to advancing radar‐based estimates of winds and waves. We use a long‐term record of one‐way HFR power observations to explore the key factors controlling propagation losses over the ocean. Observed propagation loss was quantified using an 8‐month record of radio frequency power from a shore‐based transmitter, received at two locations: an offshore tower and a nearby island. Observations were compared to environmental factors such as wind speed and air temperature as well as models of path loss incorporating smooth and rough surface impedances and varying atmospheric properties. Significant differences in the observations at the two sites existed. One‐way path loss variations at the tower, a wavelength above mean sea level, were closely related to atmospheric forcing, while variations at the distant island site were dominated by wind‐driven surface gravity wave variability. Seasonal variability in ocean conductivity had no significant effect on over‐ocean path losses. Simplistic analytical models of path loss were found to have more skill than either ground wave propagation models or more complex numerical models of field strength in matching the observations, due in part to under‐observation of the atmosphere but also the differences in rough surface impedance between models of ocean waves.
Streamflow Prediction in Poorly Gauged Watersheds in the United States Through Data‐Driven Sparse Sensing
Authors: Zhang Kun , Luhar Mitul , Brunner Manuela I. , Parolari Anthony J.
Published: March 2023

Many rivers and streams are ungauged or poorly gauged and predicting streamflow in such watersheds is challenging. Although streamflow signals result from processes with different frequencies, they can be “sparse” or have a “lower‐dimensional” representation in a transformed feature space. In such cases, if this appropriate feature space can be identified from streamflow data in gauged watersheds by dimensionality reduction, streamflow in poorly gauged watersheds can be predicted with a few measurements taken. This study utilized this framework, named data‐driven sparse sensing (DSS), to predict daily‐scale streamflow in 543 watersheds across the contiguous United States. A tailored library of features was extracted from streamflow training data in watersheds within the same climatic region, and this feature space was used to reconstruct streamflow in poorly gauged watersheds and identify the optimal timings for measurement. Among different regions, streamflow in snowmelt‐dominated and baseflow‐dominated watersheds (e.g., Rocky Mountains) was more effectively predicted with fewer streamflow measurements taken. The prediction efficiency in some rainfall‐dominated regions, for example, New England and the Pacific coast, increased significantly with an increasing number of measurements. The spatial variability of prediction efficiency can be attributed to the process‐driven mechanisms and the dimensionality of watershed dynamics. Storage‐dominated systems are lower‐dimensional and more predictable than rainfall‐dominated systems. Measurements taken during periods with large streamflow magnitudes and/or variances are more informative and lead to better predictions. This study demonstrates that DSS can be an especially useful technique to integrate ground‐based measurements with remotely sensed data for streamflow prediction, sensor placement, and watershed classification.
Controlled growth of a graphdiyne-Prussian blue analog heterostructure for efficient ammonia production
Authors: Gao Yaqi , Liu Huimin , Zheng Zhiqiang , Luan Xiaoyu , Xue Yurui , Li Yuliang
Published: March 2023

Selective and efficient ammonia (NH3) production using an electrocatalytic nitrate reduction reaction (ECNtRR) under ambient conditions provides a green and promising alternative to the traditional energy-intensive Haber–Bosch process. The challenge is in design and controlled syntheses of efficient electrocatalysts with high selectivities, high NH3 yield rates (YNH3) and long-term stabilities. Here, a freestanding three-dimensional graphdiyne-hollowed FeCoNi Prussian blue analog electrode (h-FeCoNi PBA@GDY) with highly selective and active interfaces was synthesized by in situ growth of a GDY layer on the surface of h-FeCoNi PBA and used for the ECNtRR in alkaline solution at ambient temperatures and pressures. The experimental results demonstrated that the uniquely incomplete charge transfer between metal atoms and GDY effectively enhanced the intrinsic activity and increased the number of active sites of the electrocatalyst and promoted fast redox switching and high-density charge transport at the interface, which resulted in high selectivity, activity and stability for the ECNtRR. The results indicated that the electrocatalyst showed a Faraday efficiency (FE) of 95.1% with a YNH3 of 1015.5 μmol h−1 cm−2 and excellent stability.
Photoactive conjugated polymer-based strategy to effectively inactivate RNA viruses
Authors: Qi Ruilian , Lv Fengting , Zeng Yue , Shen Qi , Huang Yiming , Bai Haotian , Liu Libing , Wang Shu
Published: March 2023

To efficiently combat viral infectious diseases, it is important to develop broadly applicable countermeasures, and efficient antiviral systems can be developed by elaborating the relationship of antiviral efficiency with the interactions between antiviral agents and viruses. In the present study, conjugated polymer (CP)-based photodynamic therapy was used to inhibit RNA virus infections. A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pseudotyped virus composed of an SARS-CoV-2 envelope coated with the S protein and luciferase RNA genome was employed to assess antiviral efficiency. Three cationic CPs with different backbone structures, fluorene-co-phenylene (PFP), thiophene (PMNT), and phenylene vinylene (PPV), exhibit different photoinactivation effects. The highly efficient photoinactivation of PPV and PMNT is derived from the complete photodegradation of spike proteins, nucleocapsid proteins and nucleic acids of SARS-CoV-2 after binding to the viral spike proteins. Although PFP showed the highest efficiency in the photodegradation of spike proteins due to its strong binding affinity, ineffective viral inhibition was observed, which occurred because the viral gene was partially damaged under light irradiation and the process of delivering the viral gene to cells received assistance. This work preliminarily reveals the effect of CP-virus interactions on their photoinactivation activity and should be beneficial for further research on the development of highly efficient antiviral PDT agents.
Nano-encapsulation: overcoming conductivity limitations by growing MOF nanoparticles in meso-porous carbon enables high electrocatalytic performance
Authors: Sathiyan Krishnamoorthy , Dutta Asmita , Marks Vered , Fleker Ohad , Zidki Tomer , Webster Richard D. , Borenstein Arie
Published: March 2023

Among the methods employed for carbon capture, the electroreduction of CO2 offers both a reduction in CO2 levels and the possibility of recycling it into commodity chemicals. However, the most efficient catalysts for this reaction are precious metals. To achieve cost-effective processes, other elements should be used. Transition-metal atoms coordinated with metal-organic frameworks (MOFs) exhibit high performance as electrocatalysts. However, the isolating natures of MOFs limit their utilization as electrocatalysts. In this study, we grew MOF nanoparticles inside hierarchically mesoporous carbon instead of mixing the MOFs with conductive carbon. The incorporated MOF nanoparticles showed improved properties compared with those of MOFs mixed with carbon, indicating strong electronic interactions in the composites. The encapsulated MOF nanoparticles demonstrated high electric conductivity while preserving their original crystallinity. When used as electrodes in CO2 electroreduction, the MOFs exhibited a high electroactive coverage of 155 nmol cm−2. Moreover, in a CO2-saturated electrolyte, the composites exhibited excellent electrochemical performance, including a small onset potential (−0.31 V vs. RHE) and large reduction currents (−18 mA. cm−2 at −1.0 V); these were considerably higher than those usually reported for MOF-based materials except in CO electroreduction. Importantly, the composite produced valuable hydrogenated commodity chemicals, including formic acid.
Achieving structural white inspired by quasiordered microstructures in Morpho theseus
Authors: Zhao Xinkun , Xiong Yuqin , Wang Wanlin , Zhang Wang , Zhang Di
Published: March 2023

As one of the most fascinating phenomena, structural whiteness in natural organisms serves important functions in thermoregulation and mating. However, the architectures that cause visible broadband reflection are often in quasiordered distributions, which hinders systematic research on their color formation mechanisms. Here, through numerical analysis, the architectures in Morpho theseus scales are shown to be distributed in various tubular morphologies between tubular and gyroid structures. Then, the mechanism of structural white is discussed using the numerical model built with the combination of a periodic numerical framework and random elements. Thermodynamic experiments indicate that the white scales can efficiently help reduce the temperature of butterfly wings under a direct light beam. Our work provides a concise method for analyzing quasiordered structures. The methodology developed by this numerical model can facilitate a deep understanding of the performance improvement facilitated by these structural characteristics. Corresponding solutions can guide the design of nano-optical materials to achieve an efficient cooling, camouflage, and photothermal conversion system.
Subcortical serotonin 5HT2c receptor-containing neurons sex-specifically regulate binge-like alcohol consumption, social, and arousal behaviors in mice
Authors: Flanigan M. E. , Hon O. J. , D’Ambrosio S. , Boyt K. M. , Hassanein L. , Castle M. , Haun H. L. , Pina M. M. , Kash T. L.
Published: March 2023

Binge alcohol consumption induces discrete social and arousal disturbances in human populations that promote increased drinking and accelerate the progression of Alcohol Use Disorder. Here, we show in a mouse model that binge alcohol consumption disrupts social recognition in females and potentiates sensorimotor arousal in males. These negative behavioral outcomes were associated with sex-specific adaptations in serotonergic signaling systems within the lateral habenula (LHb) and the bed nucleus of the stria terminalis (BNST), particularly those related to the receptor 5HT2c. While both BNST and LHb neurons expressing this receptor display potentiated activation following binge alcohol consumption, the primary causal mechanism underlying the effects of alcohol on social and arousal behaviors appears to be excessive activation of LHb5HT2c neurons. These findings may have valuable implications for the development of sex-specific treatments for mood and alcohol use disorders targeting the brain’s serotonin system.
Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass
Authors: Daleo Pedro , Alberti Juan , Chaneton Enrique J. , Iribarne Oscar , Tognetti Pedro M. , Bakker Jonathan D. , Borer Elizabeth T. , Bruschetti Martín , MacDougall Andrew S. , Pascual Jesús , Sankaran Mahesh , Seabloom Eric W. , Wang Shaopeng , Bagchi Sumanta , Brudvig Lars A. , Catford Jane A. , Dickman Chris R. , Dickson Timothy L. , Donohue Ian , Eisenhauer Nico , Gruner Daniel S. , Haider Sylvia , Jentsch Anke , Knops Johannes M. H. , Lekberg Ylva , McCulley Rebecca L. , Moore Joslin L. , Mortensen Brent , Ohlert Timothy , Pärtel Meelis , Peri Pablo L. , Power Sally A. , Risch Anita C. , Rocca Camila , Smith Nicholas G. , Stevens Carly , Tamme Riin , Veen G. F. , Wilfahrt Peter A. , Hautier Yann
Published: March 2023

Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.
Theory of sigma bond resonance in flat boron materials
Authors: Qiu Lu , Zhang Xiuyun , Kong Xiao , Mitchell Izaac , Yan Tianying , Kim Sung Youb , Yakobson Boris I. , Ding Feng
Published: March 2023

In chemistry, theory of aromaticity or π bond resonance plays a central role in intuitively understanding the stability and properties of organic molecules. Here we present an analogue theory for σ bond resonance in flat boron materials, which allows us to determine the distribution of two-center two-electron and three-center two-electron bonds without quantum calculations. Based on this theory, three rules are proposed to draw the Kekulé-like bonding configurations for flat boron materials and to explore their properties intuitively. As an application of the theory, a simple explanation of why neutral borophene with ~1/9 hole has the highest stability and the effect of charge doping on borophene’s optimal hole concentration is provided with the assumption of σ and π orbital occupation balance. Like the aromaticity theory for carbon materials, this theory greatly deepens our understanding on boron materials and paves the way for the rational design of various boron-based materials.
Nemacol is a small molecule inhibitor of C. elegans vesicular acetylcholine transporter with anthelmintic potential
Authors: Harrington Sean , Pyche Jacob , Burns Andrew R. , Spalholz Tina , Ryan Kaetlyn T. , Baker Rachel J. , Ching Justin , Rufener Lucien , Lautens Mark , Kulke Daniel , Vernudachi Alexandre , Zamanian Mostafa , Deuther-Conrad Winnie , Brust Peter , Roy Peter J.
Published: March 2023

Nematode parasites of humans and livestock pose a significant burden to human health, economic development, and food security. Anthelmintic drug resistance is widespread among parasites of livestock and many nematode parasites of humans lack effective treatments. Here, we present a nitrophenyl-piperazine scaffold that induces motor defects rapidly in the model nematode Caenorhabditis elegans. We call this scaffold Nemacol and show that it inhibits the vesicular acetylcholine transporter (VAChT), a target recognized by commercial animal and crop health groups as a viable anthelmintic target. We demonstrate that it is possible to create Nemacol analogs that maintain potent in vivo activity whilst lowering their affinity to the mammalian VAChT 10-fold. We also show that Nemacol enhances the ability of the anthelmintic Ivermectin to paralyze C. elegans and the ruminant nematode parasite Haemonchus contortus. Hence, Nemacol represents a promising new anthelmintic scaffold that acts through a validated anthelmintic target.
Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals
Authors: Gu Haogao , Quadeer Ahmed Abdul , Krishnan Pavithra , Ng Daisy Y. M. , Chang Lydia D. J. , Liu Gigi Y. Z. , Cheng Samuel M. S. , Lam Tommy T. Y. , Peiris Malik , McKay Matthew R. , Poon Leo L. M.
Published: March 2023

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.
Generation of third-harmonic spin oscillation from strong spin precession induced by terahertz magnetic near fields
Authors: Zhang Zhenya , Sekiguchi Fumiya , Moriyama Takahiro , Furuya Shunsuke C. , Sato Masahiro , Satoh Takuya , Mukai Yu , Tanaka Koichiro , Yamamoto Takafumi , Kageyama Hiroshi , Kanemitsu Yoshihiko , Hirori Hideki
Published: March 2023

The ability to drive a spin system to state far from the equilibrium is indispensable for investigating spin structures of antiferromagnets and their functional nonlinearities for spintronics. While optical methods have been considered for spin excitation, terahertz (THz) pulses appear to be a more convenient means of direct spin excitation without requiring coupling between spins and orbitals or phonons. However, room-temperature responses are usually limited to small deviations from the equilibrium state because of the relatively weak THz magnetic fields in common approaches. Here, we studied the magnetization dynamics in a HoFeO3 crystal at room temperature. A custom-made spiral-shaped microstructure was used to locally generate a strong multicycle THz magnetic near field perpendicular to the crystal surface; the maximum magnetic field amplitude of about 2 T was achieved. The observed time-resolved change in the Faraday ellipticity clearly showed second- and third-order harmonics of the magnetization oscillation and an asymmetric oscillation behaviour. Not only the ferromagnetic vector M but also the antiferromagnetic vector L plays an important role in the nonlinear dynamics of spin systems far from equilibrium.
Oxidation-resistant all-perovskite tandem solar cells in substrate configuration
Authors: Wang Yurui , Lin Renxing , Wang Xiaoyu , Liu Chenshuaiyu , Ahmed Yameen , Huang Zilong , Zhang Zhibin , Li Hongjiang , Zhang Mei , Gao Yuan , Luo Haowen , Wu Pu , Gao Han , Zheng Xuntian , Li Manya , Liu Zhou , Kong Wenchi , Li Ludong , Liu Kaihui , Saidaminov Makhsud I. , Zhang Lijun , Tan Hairen
Published: March 2023

The commonly-used superstrate configuration (depositing front subcell first and then depositing back subcell) in all-perovskite tandem solar cells is disadvantageous for long-term stability due to oxidizable narrow-bandgap perovskite assembled last and easily exposable to air. Here we reverse the processing order and demonstrate all-perovskite tandems in a substrate configuration (depositing back subcell first and then depositing front subcell) to bury oxidizable narrow-bandgap perovskite deep in the device stack. By using guanidinium tetrafluoroborate additive in wide-bandgap perovskite subcell, we achieve an efficiency of 25.3% for the substrate-configured all-perovskite tandem cells. The unencapsulated devices exhibit no performance degradation after storage in dry air for 1000 hours. The substrate configuration also widens the choice of flexible substrates: we achieve 24.1% and 20.3% efficient flexible all-perovskite tandem solar cells on copper-coated polyethylene naphthalene and copper metal foil, respectively. Substrate configuration offers a promising route to unleash the commercial potential of all-perovskite tandem solar cells.
TRABID overexpression enables synthetic lethality to PARP inhibitor via prolonging 53BP1 retention at double-strand breaks
Authors: Ma Jian , Zhou Yingke , Pan Penglin , Yu Haixin , Wang Zixi , Li Lei Lily , Wang Bing , Yan Yuqian , Pan Yunqian , Ye Qi , Liu Tianjie , Feng Xiaoyu , Xu Shan , Wang Ke , Wang Xinyang , Jian Yanlin , Ma Bohan , Fan Yizeng , Gao Yang , Huang Haojie , Li Lei
Published: March 2023

53BP1 promotes nonhomologous end joining (NHEJ) over homologous recombination (HR) repair by mediating inactivation of DNA end resection. Ubiquitination plays an important role in regulating dissociation of 53BP1 from DNA double-strand breaks (DSBs). However, how this process is regulated remains poorly understood. Here, we demonstrate that TRABID deubiquitinase binds to 53BP1 at endogenous level and regulates 53BP1 retention at DSB sites. TRABID deubiquitinates K29-linked polyubiquitination of 53BP1 mediated by E3 ubiquitin ligase SPOP and prevents 53BP1 dissociation from DSBs, consequently inducing HR defects and chromosomal instability. Prostate cancer cells with TRABID overexpression exhibit a high sensitivity to poly (ADP-ribose) polymerase (PARP) inhibitors. Our work shows that TRABID facilitates NHEJ repair over HR during DNA repair by inducing prolonged 53BP1 retention at DSB sites, suggesting that TRABID overexpression may predict HR deficiency and the potential therapeutic use of PARP inhibitors in prostate cancer.
Single-cell analysis of peripheral blood from high-altitude pulmonary hypertension patients identifies a distinct monocyte phenotype
Authors: Wu Xin-Hua , He Yang-Yang , Chen Zhang-Rong , He Ze-Yuan , Yan Yi , He Yangzhige , Wang Guang-Ming , Dong Yu , Yang Ying , Sun Yi-Min , Ren Yong-Hong , Zhao Qiu-Yan , Yang Xiao-Dan , Wang Li-Ying , Fu Cai-Jun , He Miao , Zhang Si-Jin , Fu Ji-Fen , Liu Hong , Jing Zhi-Cheng
Published: March 2023

Immune and inflammatory responses have an important function in the pathophysiology of pulmonary hypertension (PH). However, little is known about the immune landscape in peripheral circulation in patients with high-altitude pulmonary hypertension (HAPH). We apply single-cell transcriptomics to characterize the monocytes that are significantly enriched in the peripheral blood mononuclear cells (PBMC) of HAPH patients. We discover an increase in C1 (non-classical) and C2 (intermediate) monocytes in PBMCs and a decrease in hypoxia-inducible transcription factor-1α (HIF-1α) in all monocyte subsets associated with HAPH. In addition, we demonstrate that similar immune adaptations may exist in HAPH and PH. Overall, we characterize an immune cell atlas of the peripheral blood in HAPH patients. Our data provide evidence that specific monocyte subsets and HIF-1α downregulation might be implicated in the pathogenesis of HAPH.
MYC reshapes CTCF-mediated chromatin architecture in prostate cancer
Authors: Wei Zhao , Wang Song , Xu Yaning , Wang Wenzheng , Soares Fraser , Ahmed Musaddeque , Su Ping , Wang Tingting , Orouji Elias , Xu Xin , Zeng Yong , Chen Sujun , Liu Xiaoyu , Jia Tianwei , Liu Zhaojian , Du Lutao , Wang Yunshan , Chen Shaoyong , Wang Chuanxin , He Housheng Hansen , Guo Haiyang
Published: March 2023

MYC is a well characterized oncogenic transcription factor in prostate cancer, and CTCF is the main architectural protein of three-dimensional genome organization. However, the functional link between the two master regulators has not been reported. In this study, we find that MYC rewires prostate cancer chromatin architecture by interacting with CTCF protein. Through combining the H3K27ac, AR and CTCF HiChIP profiles with CRISPR deletion of a CTCF site upstream of MYC gene, we show that MYC activation leads to profound changes of CTCF-mediated chromatin looping. Mechanistically, MYC colocalizes with CTCF at a subset of genomic sites, and enhances CTCF occupancy at these loci. Consequently, the CTCF-mediated chromatin looping is potentiated by MYC activation, resulting in the disruption of enhancer-promoter looping at neuroendocrine lineage plasticity genes. Collectively, our findings define the function of MYC as a CTCF co-factor in three-dimensional genome organization.
A machine learning microstructurally predictive framework for the failure of hydrided zirconium alloys
Authors: Hasan Tamir , Capolungo Laurent , Zikry Mohammed
Published: March 2023

Hydride precipitation within zirconium alloys affects ductility and fracture behavior. The complex distribution of hydrides and their interaction with defects, such as dislocations, have a significant role in crack nucleation and failure. Hence, there is substantial variability in the microstructural behavior of hydrided zirconium. A deterministic fracture model coupled to a dislocation-density based crystalline plasticity approach was used to predict failure. Deterministic simulations were used to develop a database of crack initiation for representative microstructural characteristics, such as texture, crystalline structure, hydride orientations and spacing, and hydride geometry. The machine learning (ML) analysis is based on Extreme Value Theory (EVT) and a Bayesian based Gaussian Process Regression (GPR). Fracture probability is significantly influenced by hydride orientation and dislocation-density interactions. Furthermore, surrogate reduced order models (ROM) models were used to predict the likelihood of failure. This approach provides a ML framework to predict failure at different physical scales.
Effects of deep brain stimulation frequency on eye movements and cognitive control
Authors: Zacharia André , Kaski Diego , Bouthour Walid , Dayal Viswas , Bereau Matthieu , Mahlknecht Philipp , Georgiev Dejan , Péron Julie , Foltynie Tom , Zrinzo Ludvic , Jahanshahi Marjan , Rothwell John , Limousin Patricia
Published: March 2023

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for Parkinson’s disease (PD). Varying the frequency DBS has differential effects on axial and distal limb functions, suggesting differing modulation of relevant pathways. The STN is also a critical node in oculomotor and associative networks, but the effect of stimulation frequency on these networks remains unknown. This study aimed to investigate the effects of 80 hz vs. 130 Hz frequency STN-DBS on eye movements and executive control. Twenty-one STN-DBS PD patients receiving 130 Hz vs. 80 Hz stimulation were compared to a healthy control group (n = 16). All participants were tested twice in a double-blind manner. We examined prosaccades (latency and gain) and antisaccades (latency of correct and incorrect antisaccades, error rate and gain of the correct antisaccades). Executive function was tested with the Stroop task. The motor condition was assessed using Unified Parkinson’s Disease Rating Scale part III. The antisaccadic error rate was higher in patients (p = 0.0113), more so in patients on 80 Hz compared to 130 Hz (p = 0.001) stimulation. The differences between patients and controls and between frequencies for all other eye-movements or cognitive measures were not statistically significant. We show that 80 Hz STN-DBS in PD reduces the ability to maintain stable fixation but does not alter inhibition, resulting in a higher antisaccade error rate presumably due to less efficient fixation, without altering the motor state. This provides a wider range of stimulation parameters that can reduce specific DBS-related effects without affecting motor outcomes.
3D bioprinting using a new photo-crosslinking method for muscle tissue restoration
Authors: Lee JaeYoon , Lee Hyeongjin , Jin Eun-Ju , Ryu Dongryeol , Kim Geun Hyung
Published: March 2023

Three-dimensional (3D) bioprinting is a highly effective technique for fabricating cell-loaded constructs in tissue engineering. However, the versatility of fabricating precise and complex cell-loaded hydrogels is limited owing to the poor crosslinking ability of cell-containing hydrogels. Herein, we propose an optic-fiber-assisted bioprinting (OAB) process to efficiently crosslink methacrylated hydrogels. By selecting appropriate processing conditions for the photo-crosslinking technique, we fabricated biofunctional cell-laden structures including methacrylated gelatin (Gelma), collagen, and decellularized extracellular matrix. To apply the method to skeletal muscle regeneration, cell-laden Gelma constructs were processed with a functional nozzle having a topographical cue and an OAB process that could induce a uniaxial alignment of C2C12 and human adipose stem cells (hASCs). Significantly higher degrees of cell alignment and myogenic activities in the cell-laden Gelma structure were observed compared with those in the cell construct that was printed using a conventional crosslinking method. Moreover, an in vivo regenerative potential was observed in volumetric muscle defects in a mouse model. The hASC-laden construct significantly induced greater muscle regeneration than the cell construct without topographical cues. Based on the results, the newly designed bioprinting process can prove to be highly effective in fabricating biofunctional cell-laden constructs for various tissue engineering applications.
Baseline high-resolution maps of organic carbon content in Australian soils
Authors: Wadoux Alexandre M. J-C. , Román Dobarco Mercedes , Malone Brendan , Minasny Budiman , McBratney Alex B. , Searle Ross
Published: March 2023

We introduce a new dataset of high-resolution gridded total soil organic carbon content data produced at 30 m × 30 m and 90 m × 90 m resolutions across Australia. For each product resolution, the dataset consists of six maps of soil organic carbon content along with an estimate of the uncertainty represented by the 90% prediction interval. Soil organic carbon maps were produced up to a depth of 200 cm, for six intervals: 0–5 cm, 5–15 cm, 15–30 cm, 30–60 cm, 60–100 cm and 100–200 cm. The maps were obtained through interpolation of 90,025 depth-harmonized organic carbon measurements using quantile regression forest and a large set of environmental covariates. Validation with 10-fold cross-validation showed that all six maps had relatively small errors and that prediction uncertainty was adequately estimated. The soil carbon maps provide a new baseline from which change in future carbon stocks can be monitored and the influence of climate change, land management, and greenhouse gas offset can be assessed.
A novel form stable phase change material with comb-like cross-linked polyurethane as supporting skeleton
Authors: Yang Yunyun , Xiong Shenghua , Fu Ju , He Yuanhua , Wu Yi , Xu Yi
Published: March 2023

To improve the homogeneity of phase-change materials (PCMs) composites for thermal energy storage, the poly(ethylene glycol monomethyl ether)-based trimethylolpropane (Ymer-N120) with long side ethyoxyl chains is employed to form comb-like polyurethane which functioned as supporting materials for PCMs. And the results of Fourier transform infrared spectroscopy (FTIR), X-ray diffraction, differential scanning calorimetry, accelerated thermal cycling testing, thermogravimetric analysis and field emission scanning electron microscopy (FESEM) suggested a crosslinked polyurethane embedded with micron grade myristic acid (MA) crystals was prepared during the thermal curing process. The obtained comb-like polyurethane (YP) can provide 3D structure supporting materials for melting MA. And the long side ethyoxyl chain of Ymer-N120 promote the melting MA form micron-sized crystals. The results of thermal reliability testing confirmed the advantages of same methylene groups in side chains and suggested the maximal hold capability of YP crosslinks is about 50 wt% of composites. With the 50 wt% addition of MA, YPM50 can supply high latent heat (over 90 J/g of YPM50) with fine thermal stability (due to its initial decomposing temperature reaches 190 °C) without leakage (after 500 times of accelerated thermal cycling testing). All results indicated this structure supplies an effective solution for the leakage of PCMs, which show a promising application in TES.
Experimental and computational investigation on the charge storage performance of a novel Al2O3-reduced graphene oxide hybrid electrode
Authors: Ratha Satyajit , Sahoo Surjit , Mane Pratap , Polai Balaram , Sathpathy Bijoy , Chakraborty Brahmananda , Nayak Saroj Kumar
Published: March 2023

The advancements in electrochemical capacitors have noticed a remarkable enhancement in the performance for smart electronic device applications, which has led to the invention of novel and low-cost electroactive materials. Herein, we synthesized nanostructured Al2O3 and Al2O3-reduced graphene oxide (Al2O3-rGO) hybrid through hydrothermal and post-hydrothermal calcination processes. The synthesized materials were subject to standard characterisation processes to verify their morphological and structural details. The electrochemical performances of nanostructured Al2O3 and Al2O3- rGO hybrid were evaluated through computational and experimental analyses. Due to the superior electrical conductivity of reduced graphene oxide and the synergistic effect of both EDLC and pseudocapacitive behaviour, the Al2O3- rGO hybrid shows much improved electrochemical performance (~ 15-fold) as compared to bare Al2O3. Further, a symmetric supercapacitor device (SSD) was designed using the Al2O3- rGO hybrid electrodes, and detailed electrochemical performance was evaluated. The fabricated Al2O3- rGO hybrid-based SSD showed 98.56% capacity retention when subjected to ~ 10,000 charge–discharge cycles. Both the systems (Al2O3 and its rGO hybrid) have been analysed extensively with the help of Density Functional Theory simulation technique to provide detailed structural and electronic properties. With the introduction of reduced graphene oxide, the available electronic states near the Fermi level are greatly enhanced, imparting a significant increment in the conductivity of the hybrid system. The lower diffusion energy barrier for electrolyte ions and higher quantum capacitance for the hybrid structure compared to pristine Al2O3 justify improvement in charge storage performance for the hybrid structure, supporting our experimental findings.
Dental image enhancement network for early diagnosis of oral dental disease
Authors: Khan Rizwan , Akbar Saeed , Khan Ali , Marwan Muhammad , Qaisar Zahid Hussain , Mehmood Atif , Shahid Farah , Munir Khushboo , Zheng Zhonglong
Published: March 2023

Intelligent robotics and expert system applications in dentistry suffer from identification and detection problems due to the non-uniform brightness and low contrast in the captured images. Moreover, during the diagnostic process, exposure of sensitive facial parts to ionizing radiations (e.g., X-Rays) has several disadvantages and provides a limited angle for the view of vision. Capturing high-quality medical images with advanced digital devices is challenging, and processing these images distorts the contrast and visual quality. It curtails the performance of potential intelligent and expert systems and disincentives the early diagnosis of oral and dental diseases. The traditional enhancement methods are designed for specific conditions, and network-based methods rely on large-scale datasets with limited adaptability towards varying conditions. This paper proposed a novel and adaptive dental image enhancement strategy based on a small dataset and proposed a paired branch Denticle-Edification network (Ded-Net). The input dental images are decomposed into reflection and illumination in a multilayer Denticle network (De-Net). The subsequent enhancement operations are performed to remove the hidden degradation of reflection and illumination. The adaptive illumination consistency is maintained through the Edification network (Ed-Net). The network is regularized following the decomposition congruity of the input data and provides user-specific freedom of adaptability towards desired contrast levels. The experimental results demonstrate that the proposed method improves visibility and contrast and preserves the edges and boundaries of the low-contrast input images. It proves that the proposed method is suitable for intelligent and expert system applications for future dental imaging.
Predicting COVID-19 positivity and hospitalization with multi-scale graph neural networks
Authors: Skianis Konstantinos , Nikolentzos Giannis , Gallix Benoit , Thiebaut Rodolphe , Exarchakis Georgios
Published: March 2023

The pandemic of COVID-19 is undoubtedly one of the biggest challenges for modern healthcare. In order to analyze the spatio-temporal aspects of the spread of COVID-19, technology has helped us to track, identify and store information regarding positivity and hospitalization, across different levels of municipal entities. In this work, we present a method for predicting the number of positive and hospitalized cases via a novel multi-scale graph neural network, integrating information from fine-scale geographical zones of a few thousand inhabitants. By leveraging population mobility data and other features, the model utilizes message passing to model interaction between areas. Our proposed model manages to outperform baselines and deep learning models, presenting low errors in both prediction tasks. We specifically point out the importance of our contribution in predicting hospitalization since hospitals became critical infrastructure during the pandemic. To the best of our knowledge, this is the first work to exploit high-resolution spatio-temporal data in a multi-scale manner, incorporating additional knowledge, such as vaccination rates and population mobility data. We believe that our method may improve future estimations of positivity and hospitalization, which is crucial for healthcare planning.