bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing
Authors: Tuite Logan , Braun James , Paniagua Guillermo
Published: November 2023

As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.
Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways
Authors: Broughton Justin , Torres Emanuel , Narayanan Akshith , Joshi Yogendra K.
Published: November 2023

The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.
Convective Heat Transfer and Entropy Generation Analysis in Elliptic Microchannels
Authors: Su Liangbin , Yang Yongyi
Published: November 2023

In this paper, we investigate analytically the first and the second law characteristics of fully developed gaseous slip flow with the H1 boundary condition through elliptical microchannels. The closed-form solution of temperature distribution was obtained with the separation of variables method. Expressions for the Nusselt number, the nondimensional entropy generation rate, and the Bejan number were further deduced. The influences of crucial factors, including viscous dissipation, rarefaction, aspect ratio, and fluid axial heat conduction, have been carefully evaluated. The results indicated that viscous dissipation has a dramatic impact on heat transfer characteristics. But the rarefaction effect was found to significantly reduce the effect of the viscous dissipation on the Nusselt number, and the former may not deteriorate the heat transfer performance when considering the viscous dissipation. The main source of the entropy generation rate is controlled by fluid axial heat conduction when the Peclet number is less than one. The impacts of the viscous dissipation, the rarefaction, and the aspect ratio on entropy generation are magnified when fluid axial conduction dominates the irreversibility. The analytical solutions of the current study will make it possible to compare, evaluate, and optimize alternative elliptical microchannel heat exchanger design options.
Modeling Stiffness and Stress in Serpentine Flexures for Use in a Compliant Bone Plate
Authors: Huxman Connor , Butler Jared
Published: November 2023

Serpentine flexures offer several advantages for use in linear motion mechanisms, including distributed compliance to reduce stress and increase range of motion. In this work, we develop an analytical model for predicting the moment, vertical deflection, and maximum stress experienced in serpentine flexures in response to an input vertical force. Two classes of serpentines are introduced and modeled with linear motion boundary conditions enforced. Finite element analysis demonstrates a mean model error of 0.86% for these metrics across many flexure topologies. Experimental testing is performed to validate the force–deflection response of three steel serpentine compliant mechanisms. The model is able to predict the experimental stiffness data with a mean error at yield of 5.3%, compared to 6.5% with finite element analysis. Large displacement simulations show the model could remain below 10% error for deflections 3–7 times beyond the mechanisms’ deflection at yield. Finally, the model’s utility is demonstrated in the design of a novel single-piece compliant fracture fixation plate that leverages serpentine flexures to deliver controlled axial motion for long bone secondary healing. Model-derived stress-equivalent flexures are compared in their transverse and torsional rigidity. The proposed model and specific findings can be leveraged to design linear motion mechanisms that incorporate serpentine flexures across a wide range of applications.
Identification of Design Strategies and Their Effects on Performance Outcomes in Pair Parameter Design Tasks
Authors: Avşar Alkım Z. , Grogan Paul T.
Published: November 2023

Understanding design processes and behaviors is important for building more effective design outcomes. During design tasks, teams exhibit sequences of actions that form strategies. This article investigates patterns of design actions in a paired parameter design experiment to discover design strategies that influence outcomes. The analysis uses secondary data from a design experiment in which each pair completes a series of simplified cooperative parameter design tasks to minimize completion time. Analysis of 192 task observations uses exploratory factor analysis to identify design strategies and regression analysis to evaluate their impacts on performance outcomes. The article finds that large actions and high action size variability significantly increase completion times, leading to poor performance outcomes. However, results show that frequently changing input controllers within and among designers significantly reduces completion times, leading to higher performance outcomes. Discussion states that larger actions can introduce unexpected errors, while smaller and consistent actions enhance designers’ understanding of the effects of each action, aiding in better planning for subsequent steps. Frequent controller switching reflects effective communication and understanding within design teams, which is crucial for cooperative tasks.
Experimental Investigations on the Effects of Surface Roughness for Compressor Cascades With Different Roughness Magnitude and Location
Authors: Yu Xianjun , Zhao Shouyang , An Guangfeng , Xu Yuhang , Xu Xiaobin
Published: November 2023

Blade surface roughness could significantly affect the aerodynamic performance of compressors. To explore the influence of roughness magnitude and location on blade performance, experiments were conducted in a low-speed linear compressor cascade with controlled diffusion airfoils (CDA). A part-span roughness method was employed in the experiment to maintain the axial velocity–density ratio (AVDR) during the change of blade roughness magnitudes and locations. Five blade surface local roughness schemes, including the leading-edge, the fore- and aft-part of the suction surface, and the pressure surface, which were determined based on geometry sensitivity analysis, were investigated with the variation of the surface roughness magnitude between Ra = 3.1 μm to 18.8 μm. Cascade inlet and outlet flowfields and the blade surface static pressure distributions were measured, which could help to distinguish the change of blade performance characteristics and even blade surface boundary layer development state. A critical roughness effect was found, and significant blade loss increment and available incidence range reduction appear at super-critical roughness states. At the measured maxi-roughness condition, 28.4% loss increase and 41.2% incidence range reduction were reached.
Mechanical Properties of Buried Steel Pipe With Polyurethane Isolation Layer Under Strike-Slip Fault
Authors: Xue Jinghong , Ji Li
Published: November 2023

Long-distance buried pipelines are one of the most common and economical transportation methods for oil and gas, but the fault movement will pose a threat to the safety of pipelines. The main challenge of pipeline under strike-slip faults is to improve the ability of resistance to fault dislocation, and the main aim of the study is how to improve the critical fault displacement of pipelines with the help of polyurethane isolation layer. Three-dimensional finite element models were proposed for mechanical analysis of X80 buried steel pipe with polyurethane isolation layer under strike-slip fault. The influence of factors on the mechanical properties of pipelines were studied, such as thickness of isolation layer, internal pressure, fault displacement, diameter-thickness ratio, and the angle of pipe and fault line. The simulation results indicate that with the increase of the thickness of the isolation layer, the development of the maximum tensile and compressive strain of the pipeline is significantly reduced for the same fault displacement, resulting in a significant increase in the critical fault displacement corresponding to the three failure modes of the pipeline. As the ratio of diameter to thickness and internal pressure decrease, the critical displacements decrease. When designing and planning the pipeline, pipeline is recommended with the seismic isolation layer, large wall thickness, and the crossing-angle at 70 deg∼80 deg. The research provided a reference for judgment of earthquake resistance, failure analysis, and safety design of pipelines with polyurethane isolation layer crossing strike-slip faults.
PhyNRnet: Physics-Informed Newton–Raphson Network for Forward Kinematics Solution of Parallel Manipulators
Authors: He Chongjian , Guo Wei , Zhu Yanxia , Jiang Lizhong
Published: November 2023

Despite significant performance advantages, the intractable forward kinematics have always restricted the application of parallel manipulators to small posture spaces. Traditional analytical methods and Newton–Raphson method usually cannot solve this problem well due to lack of generality or latent divergence. To address this issue, this study employs recent advances in deep learning to propose a novel physics-informed Newton–Raphson network (PhyNRnet) to rapidly and accurately solve this forward kinematics problem for general parallel manipulators. The main strategy of PhyNRnet is to combine the Newton–Raphson method with the neural network, which helps to significantly improve the accuracy and convergence speed of the model. In addition, to facilitate the network optimization, semi-autoregression, hard imposition of initial/boundary conditions (I/BCs), batch normalization, etc. are developed and applied in PhyNRnet. Unlike previous data-driven paradigms, PhyNRnet adopts the physics-informed loss functions to guide the network optimization, which gives the model clear physical meaning and helps improve generalization ability. Finally, the performance of PhyNRnet is verified by three parallel manipulator paradigms with large postures, where the Newton–Raphson method has generally diverged. Besides, the efficiency analysis shows that PhyNRnet consumes only a small amount of time at each time-step, which meets the real-time requirements.
Ring Origami Spring Capable of Eversion Morphing
Authors: Zou Yu , Chen Qianying , Lu Lu , Li Xiying , Li Hongyuan , Shao Li-Hua , Duan Huiling , Lv Pengyu
Published: November 2023

Origami structures have been widely used in soft robots, mechanical metamaterials, architectural engineering, and biomedical engineering in recent years, benefiting from their reconfigurable shape morphing and tunable mechanical properties through folding and unfolding. In this work, we construct a new origami structure named ring origami spring (ROS) by alternately folding two perpendicularly arranged paper ribbons of the same size and connecting two ends of them. ROS can achieve an eversion morphing with four stable states, based on which both underwater locomotion and traversing water–air interface have been implemented. Theoretical models for characterizing the eversion morphing during the transition of stable states and the induced locomotion performance of ROS have been developed, and the theoretical predictions are in good agreement with the experimental results. The current work provides a new strategy for the design of origami robots, which is potentially applied in exploring complex environments.
Assessing dead time effects when attempting isotope ratio quantification by time-of-flight secondary ion mass spectrometry
Authors: Baqué Laura C. , Cabello Federico M. , Viva Federico A. , Corti Horacio R.
Published: November 2023

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is a quasi-non-destructive technique capable of analyzing the outer monolayers of a solid sample and detecting all elements of the periodic table and their isotopes. Its ability to analyze the outer monolayers resides in sputtering the sample surface with a low-dose primary ion gun, which, in turn, imposes the use of a detector capable of counting a single ion at a time. Consequently, the detector saturates when more than one ion arrives at the same time hindering the use of TOF-SIMS for quantification purposes such as isotope ratio estimation. Even though a simple Poisson-based correction is usually implemented in TOF-SIMS acquisition software to compensate the detector saturation effects, this correction is only valid up to a certain extent and can be unnoticed by the inexperienced user. This tutorial describes a methodology based on different practices reported in the literature for dealing with the detector saturation effects and assessing the validity limits of Poisson-based correction when attempting to use TOF-SIMS data for quantification purposes. As a practical example, a dried lithium hydroxide solution was analyzed by TOF-SIMS with the aim of estimating the 6Li/7Li isotope ratio. The approach presented here can be used by new TOF-SIMS users on their own data for understanding the effects of detector saturation, determine the validity limits of Poisson-based correction, and take into account important considerations when treating the data for quantification purposes.
A swap-based sparse array design method in personal sound zone
Authors: Cheng Jiazheng , Gao Hao , Feng Xuelei , Shen Yong
Published: November 2023

Sparse array design (SAD) optimizes the geometrical configuration of the loudspeaker array. It provides possibilities for further improving the performance of personal sound zone (PSZ). In this paper, the SAD problem in PSZ is formulated as a sparse multi-objective optimization problem, which takes multiple performance metrics into consideration during the sparsity promotion procedure. A swap-based group search algorithm is designed and proposed for solving the formulated non-convex and combinatorial problem to near-optimality. An approximate form is also proposed for reducing computational burden when there exist multiple target sound fields in bright zone. Simulation and experimental results suggest that the proposed method is more suitable in PSZ for controlling over trade-offs and achieving the same good or even better performances, and the proposed approximate form is effective.
Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission
Authors: Chen Weipeng , Zhai Linxin , Zhang Suli , Zhao Ziguang , Hu Yuhao , Xiang Yun , Liu Huirong , Xu Zhiping , Jiang Lei , Wen Liping
Published: November 2023

Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.
From single cells to neural circuits
Authors: Skinnider Michael A.
Published: November 2023

Neural circuits are mapped in high throughput with single-cell genomics
Trophic cascades help restore vegetation
Authors: Villar Nacho
Published: November 2023

Herbivores and their predators have a major impact on restoration outcomes
The neural basis of mental navigation in rats
Authors: Coulter Michael E. , Kemere Caleb
Published: November 2023

A brain–machine interface demonstrates volitional control of hippocampal activity
Shore patrol
Authors: Reese April
Published: November 2023

Researchers are ringing the Atlantic with hundreds of sensors in a bid to track how ocean warming is affecting coastal ecosystems
Lawsuits force changes in U.S. pesticide regs
Authors: Stokstad Erik
Published: November 2023

EPA is drawing up new rules for farmers, but some worry the science isn’t ready
ArcA positively regulates the expression of virulence genes and contributes to virulence of porcine Shiga toxin-producing enterotoxigenic
Escherichia coli
Authors: Jiang Fengwei , Yang Yan , Mao Zhao , Cai Wentong , Li Ganwu
Published: November 2023

Enterotoxigenic
Escherichia coli
(ETEC) cause severe diarrhea in humans and animals. These bacteria encode two major classes of virulence factors, adhesins that promote colonization of the small intestine and enterotoxins that induce fluid secretion and thus diarrhea. Oxygen and redox sensors are regulators of virulence expression in multiple bacterial pathogens. In this study, we show that microaerobic conditions enhance the expression of virulence factors in a porcine Shiga toxin-producing ETEC (STEC/ETEC) strain. We then investigated the role of the aerobic respiration control regulator ArcA in the pathogenicity and virulence regulation in STEC/ETEC. In a mouse model, deletion of
arcA
caused less severe pathology, and the
arcA
mutant displayed lower levels of colonization and obvious weight gain of the mice compared to the wild type (WT). In a cell culture model, a lack of
arcA
reduced the adherence of STEC/ETEC to porcine intestinal epithelial cells. Furthermore, ArcA positively regulated the expression of several key virulence factors, including F18 fimbriae (
fed
), heat-labile (
eltA
) and heat-stable (
estB
) toxins, Shiga toxin 2e (
stx2e
), and hemolysin (
hlyC
), under microaerobic conditions and
in vivo
conditions. We then found that ArcA positively regulated the expression of
eltA
,
estB
, and
hlyC
by competing with a global repressor H-NS (histone-like nucleoid structuring). Mechanistically, we show that ArcA protein directly binds to the promoters of target genes, displaces H-NS silencing from the promoter and counteracts H-NS’s repression. Collectively, our data established a key role for ArcA in the pathogenicity and virulence expression of porcine STEC/ETEC.

IMPORTANCE

Enterotoxigenic
Escherichia coli
(ETEC) cause severe diarrhea in humans and animals, leading to death and huge economic loss worldwide. Thus, elucidation of ETEC’s pathogenic mechanisms will provide powerful data for the discovery of drugs serving as prevention or therapeutics against ETEC-caused diarrheal diseases. Here, we report that ArcA plays an essential role in the pathogenicity and virulence regulation in ETEC by positively regulating the expression of several key virulence factors including F18 fimbriae, heat-labile and heat-stable toxins, Shiga toxin 2e, and hemolysin, under microaerobic conditions and
in vivo
. Moreover, we found that positive regulation of several virulence genes by ArcA requires a global repressor H-NS (histone-like nucleoid structuring), implying that ArcA may exert positive effects by antagonizing H-NS. Collectively, our data established a key role for ArcA in the pathogenicity of porcine ETEC and ETEC strains isolated from human infections. Moreover, our work reveals another layer of regulation in relation to oxygen control of virulence factors in ETEC.
Metabolic and chromosomal changes in a
Bacillus subtilis whiA
mutant
Authors: Bohorquez Laura C. , de Sousa Joana , Garcia-Garcia Transito , Dugar Gaurav , Wang Biwen , Jonker Martijs J. , Noirot-Gros Marie-Françoise , Lalk Michael , Hamoen Leendert W.
Published: November 2023

The conserved protein WhiA is present in most Gram-positive bacteria and plays a role in cell division. WhiA contains a DNA-binding motif and is a transcription regulator of the key cell division gene
ftsZ
in actinomycetes. In
Bacillus subtilis
, the absence of WhiA influences both cell division and chromosome segregation; however, the protein does not regulate any gene involved in these processes. In this study, we addressed three alternative mechanisms by which WhiA might exert its activity in
B. subtilis
and examined whether WhiA influences either (i) central carbon metabolism, (ii) fatty acid composition of the cell membrane, or (iii) chromosome organization. Mutations in glycolytic enzymes have been shown to influence both cell division and DNA replication. To measure the effect of WhiA on carbon metabolism, we tested different carbon sources and measured exometabolome fluxes. This revealed that the absence of WhiA does not affect glycolysis but does influence the pool of branched-chain fatty acid precursors. Due to the effect of WhiA on chromosome segregation, we examine chromosome organization in a ∆
whiA
mutant using chromosome conformation capture (Hi-C) analysis. This revealed a local reduction in short-range chromosome interactions. Together, these findings provide new avenues for future research into how this protein works in the non-actinomycete firmicutes.

IMPORTANCE

WhiA is a conserved DNA-binding protein that influences cell division in many Gram-positive bacteria and, in
B. subtilis,
also chromosome segregation. How WhiA works in
Bacillus subtilis
is unknown. Here, we tested three hypothetical mechanisms using metabolomics, fatty acid analysis, and chromosome confirmation capture experiments. This revealed that WhiA does not influence cell division and chromosome segregation by modulating either central carbon metabolism or fatty acid composition. However, the inactivation of WhiA reduces short-range chromosome interactions. These findings provide new avenues to study the molecular mechanism of WhiA in the future.
Familial recurrent molar pregnancy: positive for KHDC3L gene mutation
Authors: Rath Abhipsa , Sethi Pruthwiraj , Jena Saubhagya Kumar , Mitra Subarna
Published: November 2023

Recurrent hydatidiform moles are defined by the occurrence of two or more molar pregnancies in the same patient. These can be sporadic or familial where familial recurrent hydatidiform mole is rare and inherited as an autosomal recessive condition. Here, we present a case of four consecutive complete molar pregnancies with similar history in the sisters, who was diagnosed with fourth complete molar pregnancy. She underwent suction and evacuation followed by weekly serum β-hCG. On genetic analysis, she was found to be homozygous for KHDC3L gene mutation. She was advised for evaluation of her sisters and to consider In vitro fertilization (IVF) with donor ovum or adoption. Prompt suspicion and diagnosis along with counselling of the couple regarding the fertility options available to them are the main aspects of this disease to protect them from repeated physical as well as psychological trauma.
‘Being disabled’ as an exclusion criterion for clinical trials: a scoping review
Authors: Camanni Guido , Ciccone Ornella , Lepri Alessandro , Tinarelli Chiara , Bedetti Chiara , Cicuttin Sandra , Murgia Nicola , Elisei Sandro
Published: November 2023

Background

People with disabilities (PWDs) are often excluded from biomedical research, but comprehensive data regarding their participation in clinical trials are not available. The objective of this study was to assess the rates of exclusion of PWDs from recent medical scientific research.

Methods

The protocol of the study was designed according to PRISMA-ScR (PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for Scoping Reviews) guidelines. All completed interventional clinical trials registered on ClinicalTrials.gov between 2010 and 2020 regarding the 10 leading causes of global disability-adjusted life-years according to the Global Burden of Disease Study were analysed. An exclusion criterion from the study was considered explicit if it could be associated with one of the following seven categories: disability, physical impairment, cognitive impairment, behavioural or psychiatric disorders, language and communication impairment, sensory impairment. Comorbidities not more clearly defined and researcher discretion regarding exclusion of study participants were considered to be ‘implicit exclusion criteria’. We assessed the appropriateness of explicit exclusion criteria in relation to the primary objectives of the trials and labelled them as ‘absolute’, ‘relative’ or ‘questionable’.

Results

The total number of trials analysed was 2710; 170 were paediatric trials (6.3%), 2374 were adult trials (87.6%) and 166 were trials including subjects of all ages (6.1%). Explicit exclusion criteria were found in 958 trials (35.3%). The disability category most frequently excluded was behavioural or psychiatric disorders, present in 588 trials (61.4%). In only 3% and 1% of the trials, the exclusion criteria were considered either ‘absolute’ or ‘questionable’, while in 96% the exclusion criteria were judged as ‘relative’. Implicit exclusion criteria were present in 1205 trials (44.5%).

Conclusions

This study highlights the high rate of exclusion of PWDs from biomedical research and the widespread use of ill-defined exclusion criteria in clinical trials. It underscores the importance of more inclusive study designs so that PWDs can become active participants in research.
Role of the microbiome in pathophysiology of necrotising enterocolitis in preterm neonates
Authors: Stanikova Andrea , Jouza Martin , Bohosova Julia , Slaby Ondrej , Jabandziev Petr
Published: November 2023

Although necrotising enterocolitis (NEC) is a serious, life-threatening disease, improved neonatal care is increasing the number of survivors with NEC among extremely preterm neonates. Therapy is nevertheless mostly symptomatic and the mortality rate remains high, especially among neonates requiring surgery. Therefore, it is important to focus on preventing the disease and modifiable risk factors. NEC’s pathophysiology is multifaceted, with key factors being immaturity of the immune and barrier protective mechanisms of the premature gut and exaggerated proinflammatory reaction to insults like gut hypoxia, enteral nutrition or microbial dysbiosis. The role of the intestinal microbiome in the pathophysiology of NEC has been a subject of research for many years, but to date no specific pathogen or type of dysbiosis has been connected with NEC development. This review assesses current knowledge as to the role of the intestinal microbiota in the pathophysiology of NEC and the possibilities for positively influencing it
Th17-inducing dendritic cell vaccines stimulate effective CD4 T cell-dependent antitumor immunity in ovarian cancer that overcomes resistance to immune checkpoint blockade
Authors: Luo Yan , Shreeder Barath , Jenkins James W , Shi Huashan , Lamichhane Purushottam , Zhou Kexun , Bahr Deborah A , Kurian Sophia , Jones Katherine A , Daum Joshua I , Dutta Navnita , Necela Brian M , Cannon Martin J , Block Matthew S , Knutson Keith L
Published: November 2023

Background

Ovarian cancer (OC), a highly lethal cancer in women, has a 48% 5-year overall survival rate. Prior studies link the presence of IL-17 and Th17 T cells in the tumor microenvironment to improved survival in OC patients. To determine if Th17-inducing vaccines are therapeutically effective in OC, we created a murine model of Th17-inducing dendritic cell (DC) (Th17-DC) vaccination generated by stimulating IL-15 while blocking p38 MAPK in bone marrow-derived DCs, followed by antigen pulsing.

Methods

ID8 tumor cells were injected intraperitoneally into mice. Mice were treated with Th17-DC or conventional DC (cDC) vaccine alone or with immune checkpoint blockade (ICB). Systemic immunity, tumor associated immunity, tumor size and survival were examined using a variety of experimental strategies.

Results

Th17-DC vaccines increased Th17 T cells in the tumor microenvironment, reshaped the myeloid microenvironment, and improved mouse survival compared with cDC vaccines. ICB had limited efficacy in OC, but Th17-inducing DC vaccination sensitized it to anti-PD-1 ICB, resulting in durable progression-free survival by overcoming IL-10-mediated resistance. Th17-DC vaccine efficacy, alone or with ICB, was mediated by CD4 T cells, but not CD8 T cells.

Conclusions

These findings emphasize using biologically relevant immune modifiers, like Th17-DC vaccines, in OC treatment to reshape the tumor microenvironment and enhance clinical responses to ICB therapy.
Comparison of balloon guide catheter versus non-balloon guide catheter for mechanical thrombectomy in patients with distal medium vessel occlusion
Authors: Orscelik Atakan , Kallmes David F , Bilgin Cem , Musmar Basel , Senol Yigit Can , Kobeissi Hassan , Elawady Sameh Samir , Cunningham Conor , Matsukawa Hidetoshi , Zandpazandi Sara , Sowlat Mohammad-Mahdi , Maier Ilko , Al Kasab Sami , Jabbour Pascal , Kim Joon-tae , Wolfe Stacey Q , Rai Ansaar , Starke Robert M , Psychogios Marios-Nikos , Samaniego Edgar A , Arthur Adam S , Yoshimura Shinichi , Cuellar Hugo , Howard Brian M , Alawieh Ali , Romano Daniele G , Tanweer Omar , Mascitelli Justin , Fragata Isabel , Polifka Adam J , Osbun Joshua W , Crosa Roberto Javier , Matouk Charles , Park Min S , Levitt Michael R , Moss Mark , Dumont Travis M , Williamson Richard , Navia Pedro , Kan Peter , De Leacy Reade , Chowdhry Shakeel A , Ezzeldin Mohamad , Spiotta Alejandro M , Brinjikji Waleed
Published: November 2023

Background

Several studies have established the safety and efficacy of balloon guide catheters (BGCs) for large vessel occlusions. However, the utility of BGCs remains largely unexplored for distal medium vessel occlusions (DMVOs). In this study, we aim to compare the outcomes of BGC vs. Non-BGC in patients undergoing mechanical thrombectomy (MT) for DMVO.

Method

This retrospective study from the Stroke Thrombectomy and Aneurysm Registry (STAR) encompassed adult patients with acute anterior cerebral artery, posterior cerebral artery, and middle cerebral artery-M2–3–4 occlusions. Procedure times, safety, recanalization, and neurological outcomes were compared between the two groups, with subgroup analysis based on first-line thrombectomy techniques.

Results

A total of 1508 patients were included, with 231 patients (15.3%) in the BGC group and 1277 patients (84.7%) in the non-BGC group. The BGC group had a lower modified Thrombolysis in Cerebral Infarction (mTICI) score ≥2C (43.2% vs 52.7%, P=0.01), longer time from puncture to intracranial access (15 vs 8 min, P<0.01), and from puncture to final recanalization (97 vs 34 min, P<0.01). In the Solumbra subgroup, the first pass effect (FPE) rate was lower in the BGC group (17.4% vs 30.7%, P=0.03). Regarding clinical outcomes, the BGC group had a lower rate of distal embolization (8.8% vs 14.9%, P=0.03).

Conclusion

Our study found that use of BGC in patients with DMVO was associated with lower mTICI scores, decreased FPE rates, reduced distal embolization, and longer procedure times.
Effect of anti-P ribosomal and anti-NR2 antibodies on depression and cognitive processes in SLE: an integrated clinical and functional MRI study
Authors: Chessa Elisabetta , Piga Matteo , Perra Alessandra , Pintus Elisa , Porcu Michele , Serafini Cristina , Congia Mattia , Angioni Maria Maddalena , Naitza Micaela Rita , Floris Alberto , Mathieu Alessandro , Saba Luca , Carta Mauro Giovanni , Cauli Alberto
Published: November 2023

Objectives

To explore the effects of anti-ribosomal P protein (anti-P) and anti-N-methyl-D-aspartic acid receptor subunit 2 (anti-NR2) autoantibodies on depression and cognitive dysfunction and their relationships with functional brain connectivity in SLE.

Methods

This cross-sectional study included adult patients who fulfilled the American College of Rheumatology/European Alliance of Associations for Rheumatology 2019 SLE criteria. Anti-P and anti-NR2 were quantified using ELISA. A 1-hour battery of neuropsychological testing interpreted by a neuropsychologist explored depressive symptoms (Center for Epidemiologic Studies Depression Scale, CES-D), cognitive domains and quality of life (SF-12). Resting-state functional connectivity (rs-fc) MRI analysis was performed within 1 month, and region-of-interest to region-of-interest (ROI-to-ROI) analyses with the graph theory were performed.

Results

Thirty-three patients with SLE (9% male) were enrolled, mean age (SD) of 43.5 (14) years and median disease duration of 10.4 years (2.9–25.4). Anti-P was positive in 6 (18.2%) and anti-NR2 in 14 (42.4%) patients. Depressive symptoms were found in 14 (42.4%) patients using the CES-D (range 0–51). After correction for age, disease duration, disease activity and white matter lesion load, the CES-D score was independently associated with anti-P serum level (β=0.32; p=0.049) and prednisone daily dose (β=0.38; p=0.023). Nineteen patients (57.6%) showed at least a cognitive test alteration, but no significant association with autoantibodies was found. The rs-fc MRI analysis revealed an independent association between the anti-P serum levels and many altered brain ROI properties but no anti-NR2 and prednisone effects on the cerebral network.

Conclusions

Anti-P was associated with brain network perturbation, which may be responsible for depressive symptoms in patients with SLE.
Worth the dip? Polar bear predation on swimming flightless greater snow geese and estimation of energetic efficiency
Authors: Weiss-Blais Matthieu , Bolduc David , Corbeil-Robitaille Madeleine-Zoé , Dulude-de Broin Frédéric , Grandmont Thierry , LeTourneux Frédéric , Poirier Mathilde , Sarrazin Denis , Legagneux Pierre
Published: November 2023

As sea-ice cover is shrinking, polar bears ( Ursus maritimus, Phipps, 1774) face decreased access to seals, their primary prey, resulting in a greater dependence on terrestrial food sources. Whether polar bears can benefit from these terrestrial food sources, however, depends on their ability to find and capture prey items without expending more energy than is acquired. Here, we report one of the northernmost observations of polar bear predation on adult birds. The bear used a dive-hunting technique, which consisted of submerging itself, approaching underwater, and catching flightless greater snow geese ( Anser caerulescens caerulescens (Linnaeus, 1758)) from beneath the surface of a tundra pond. After evaluating energy expenditures during swimming and energy intakes from consuming geese, we estimated that this rarely documented dive-hunting technique could be energetically profitable for a certain range of pursuit durations. This observation highlights the behavioral plasticity that polar bears can deploy to punctually exploit land-based food sources.
Physical analysis of Rastall PFRF black hole through accretion process
Authors: Rehman H. , Abbas G. , Jawad Abdul , Yang Rong-Jia , Mustafa G.
Published: November 2023

The adiabatic accretion onto the charged black hole surrounded by perfect fluid radiation field (PFRF) in Rastall gravity is addressed in this manuscript. For this purpose, mass accretion rate $$\dot{M}$$

M
˙

, critical horizon radius and some other flow parameters are being determined in the presence of polytropic fluid. Overall the process is being done analytically. The location of critical points, polytropic gas compression ratios and temperature profiles are also being investigated for different versions of polytropic equation of state. We also give the comparison of the location of critical points with case of Schwarzschild black hole in which critical points lies out side the horizon. Through above scenario, it is found that charge Q and Rastall parameter $$N_{r}$$

N
r

have deep effects on the accretion process. It is also mentioned here that under some constraints on parameters, our results reduce to Schwarzschild and charged black holes results.
Digital Economy: Dark Innovations in the Digital Economy
Authors: Denning Peter
Published: November 2023

Innovations are adoptions of new practice in communities. They are adopted because people perceive value from them. However, around the edges of the standard community practice, new practices can emerge that are of negative value. They are called dark innovations. Four examples are examined here: privacy, subscriptions, automation, and class abstraction. There is no easy way to eliminate dark innovations.
Eciton: Very Low-power Recurrent Neural Network Accelerator for Real-time Inference at the Edge
Authors: Chen Jeffrey , Jun Sang-Woo , Hong Sehwan , He Warrick , Moon Jinyeong
Published: November 2023

This article presents Eciton, a very low-power recurrent neural network accelerator for time series data within low-power edge sensor nodes, achieving real-time inference with a power consumption of 17 mW under load. Eciton reduces memory and chip resource requirements via 8-bit quantization and hard sigmoid activation, allowing the accelerator as well as the recurrent neural network model parameters to fit in a low-cost, low-power Lattice iCE40 UP5K FPGA.

We evaluate Eciton on multiple, established time-series classification applications including predictive maintenance of mechanical systems, sound classification, and intrusion detection for IoT nodes. Binary and multi-class classification edge models are explored, demonstrating that Eciton can adapt to a variety of deployable environments and remote use cases. Eciton demonstrates real-time processing at a very low power consumption with minimal loss of accuracy on multiple inference scenarios with differing characteristics, while achieving competitive power efficiency against the state-of-the-art of similar scale. We show that the addition of this accelerator actually reduces the power budget of the sensor node by reducing power-hungry wireless transmission. The resulting power budget of the sensor node is small enough to be powered by a power harvester, potentially allowing it to run indefinitely without a battery or periodic maintenance.
Disentangling Structure and Appearance in ViT Feature Space
Authors: Tumanyan Narek , Bar-Tal Omer , Amir Shir , Bagon Shai , Dekel Tali
Published: November 2023

We present a method for semantically transferring the visual appearance of one natural image to another. Specifically, our goal is to generate an image in which objects in a source structure image are “painted” with the visual appearance of their semantically related objects in a target appearance image. To integrate semantic information into our framework, our key idea is to leverage a pre-trained and fixed Vision Transformer (ViT) model. Specifically, we derive novel disentangled representations of structure and appearance extracted from deep ViT features. We then establish an objective function that splices the desired structure and appearance representations, interweaving them together in the space of ViT features. Based on our objective function, we propose two frameworks of semantic appearance transfer – “Splice”, which works by training a generator on a
single and arbitrary
pair of structure-appearance images, and “SpliceNet”, a
feed-forward
real-time appearance transfer model trained on a
dataset
of images from a
specific domain
. Our frameworks do not involve adversarial training, nor do they require any additional input information such as semantic segmentation or correspondences. We demonstrate high-resolution results on a variety of in-the-wild image pairs, under significant variations in the number of objects, pose, and appearance. Code and supplementary material are available in our project page: splice-vit.github.io.
A Joint Entity-Relation Detection and Generalization Method Based on Syntax and Semantics for Chinese Intangible Cultural Heritage Texts
Authors: Tan Yuyao , Wang Hao , Zhao Zibo , Fan Tao
Published: November 2023

Annotation of a natural language corpus not only facilitates researchers in extracting knowledge from it but also helps achieve deeper mining of the corpus. However, an annotated corpus in the humanities knowledge domain is lacking. In addition, the semantic annotation of humanities texts is difficult, because it requires a high domain background for researchers and even requires the participation of domain experts. Based on this, this study proposes a method for detecting entities and relations in a domain that lacks an annotated corpus, as well as provides a referenceable idea for constructing conceptual models based on textual instances. Based on syntactic and semantic features, this study proposes SPO triple recognition rules from the perspective of giving priority to predicates and generalization rules from the perspective of a triple’s content and the meaning of its predicate. The recognition rules are used to extract text-descriptive SPO triples centered on predicates. After clustering and adjusting triples, the generalization rules proposed in this study are used to obtain coarse-grained entities and relations, and then form a conceptual model. This study recognizes SPO triples with high precision and summarization from descriptive texts, generalizes them, and then forms a domain conceptual model. Our proposed method provides a research idea for entity-relation detection in a domain with a missing annotated corpus, and the formed domain conceptual model provides a reference for building a domain Linked Data Graph. The feasibility of the method is verified through practice on texts related to the four traditional Chinese festivals.
The Hybrid Features and Supervised Learning for Batik Pattern Classification
Authors: Winarno Edy , Septiarini Anindita , Hadikurniawati Wiwien , Hamdani Hamdani
Published: November 2023

Several countries have traditional textiles as a piece of their cultural heritage. Indonesia has a traditional textile called batik. Central Java is one of the regions producing batik known for its variety of distinctive themes. It has unique designs and several motifs that emphasize the beauty of historic sites. Since the diversity of central java batik motifs and the lack of knowledge from the surrounding community, only a select group of people, especially the batik craftsmen themselves, can recognize these motifs. Consequently, the method to identify the batik according to the primary ornament pattern is required. Therefore, this study proposes a computer vision-based method for classifying batik patterns. The proposed method required discriminating appropriate features to produce optimal results. The discriminating features were constructed based on color, shape, and texture. Those features were derived using the method of Color Moments, Area Based Invariant Moments, Gray Level Co-occurrence Matrix (GLCM), and Local Binary Pattern (LBP). This study’s proposed hybrid features were formed based on the most discriminating and appropriate features. These were yielded by the Correlation-based feature selection (CFS) method. The hybrid features were then fed into several classifiers to determine the batik pattern. The pattern consists of ten classes: Asem Arang, Asem Sinom, Asem Warak, Blekok, Blekok Warak, Gambang Semarangan, Kembang Sepatu, Semarangan, Tugu Muda, and Warak Beras Utah. Based on the experimental results, the most optimal predicted class of the batik pattern was generated using the Artificial Neural Network (ANN) classifier. It was indicated by achieving an accuracy value of 99.76% based on the 3,000 images (each class consists of 300 images) with cross-validation using a k-fold value of 10. This study has proved that the hybrid features incorporated with ANN can be selected as a suitable model to classify the batik patterns.
Subjective and Objective Quality Assessment for in-the-Wild Computer Graphics Images
Authors: Zhang Zicheng , Sun Wei , Zhou Yingjie , Jia Jun , Zhang Zhichao , Liu Jing , Min Xiongkuo , Zhai Guangtao
Published: November 2023

Computer graphics images (CGIs) are artificially generated by means of computer programs and are widely perceived under various scenarios, such as games, streaming media, etc. In practice, the quality of CGIs consistently suffers from poor rendering during production, inevitable compression artifacts during the transmission of multimedia applications, and low aesthetic quality resulting from poor composition and design. However, few works have been dedicated to dealing with the challenge of computer graphics image quality assessment (CGIQA). Most image quality assessment (IQA) metrics are developed for natural scene images (NSIs) and validated on databases consisting of NSIs with synthetic distortions, which are not suitable for in-the-wild CGIs. To bridge the gap between evaluating the quality of NSIs and CGIs, we construct a large-scale in-the-wild CGIQA database consisting of 6,000 CGIs (CGIQA-6k) and carry out the subjective experiment in a well-controlled laboratory environment to obtain the accurate perceptual ratings of the CGIs. Then, we propose an effective deep learning–based no-reference (NR) IQA model by utilizing both distortion and aesthetic quality representation. Experimental results show that the proposed method outperforms all other state-of-the-art NR IQA methods on the constructed CGIQA-6k database and other CGIQA-related databases. The database is released athttps://github.com/zzc-1998/CGIQA6K.