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The pavement texture wavelength and mean texture depth (MTD) of the pavement macrotexture significantly affect functional performance. However, owing to its higher correlation with the wavelength, the Exposed Aggregate Concrete Pavement (EACP) texture was evaluated based on the MTD and exposed aggregate number (EAN) in the same location. The MTD contributes significantly to road surface friction and tire-pavement noise and is vital for anti-sliding and noise reduction. Conventional methods for MTD measurement require considerable human effort when the sample size is large and sensitive to the operator. Furthermore, it is time-consuming to measure the MTD together with the EAN. Recently, image-based estimation has become a new trend, owing to its economy and convenience. Therefore, this study aimed to estimate the MTD of the EACP pavement surface texture at an image-based level as an alternative measurement approach simultaneously within the EAN location. Initially, the image acquisition was created based on aerial photography. Subsequently, photogrammetry was used to reconstruct a high-resolution point cloud of the pavement texture. Subsequently, the MTD was estimated analytically from image-based point clouds. Experiments were conducted at over 60 locations in three field tests of the EACP in South Korea. The MTD results showed good agreement and a higher correlation between the image-based and sand-patch test (SPT) methods. The image-based method showed results higher than the SPT with a value of 22%. Therefore, the developed method can be used to estimate the MTD using the established regression equation. [ABSTRACT FROM AUTHOR]

Background: Determining the impact of somatic mutations requires understanding the functional relationship of genes acquiring mutations; however, it is largely unknown how mutations in functionally related genes influence each other. Methods: We employed non-synonymous-to-synonymous or dNdS ratios to evaluate the evolutionary dependency (ED) of gene pairs, assuming a mutation in one gene of a gene pair can affect the evolutionary fitness of mutations in its partner genes as mutation context. We employed PanCancer- and tumor type-specific mutational profiles to infer the ED of gene pairs and evaluated their biological relevance with respect to gene dependency and drug sensitivity. Results: We propose that dNdS ratios of gene pairs and their derived cdNS (context-dependent dNdS) scores as measure of ED distinguishing gene pairs either as synergistic (SYN) or antagonistic (ANT). Mutation contexts can induce substantial changes in the evolutionary fitness of mutations in the paired genes, e.g., IDH1 and IDH2 mutation contexts lead to substantial increase and decrease of dNdS ratios of ATRX indels and IDH1 missense mutations corresponding to SYN and ANT relationship with positive and negative cdNS scores, respectively. The impact of gene silencing or knock-outs on cell viability (genetic dependencies) often depends on ED, suggesting that ED can guide the selection of candidates for synthetic lethality such as TCF7L2-KRAS mutations. Using cell line-based drug sensitivity data, the effects of targeted agents on cell lines are often associated with mutations of genes exhibiting ED with the target genes, informing drug sensitizing or resistant mutations for targeted inhibitors, e.g., PRSS1 and CTCF mutations as resistant mutations to EGFR and BRAF inhibitors for lung adenocarcinomas and melanomas, respectively. Conclusions: We propose that the ED of gene pairs evaluated by dNdS ratios can advance our understanding of the functional relationship of genes with potential biological and clinical implications. [ABSTRACT FROM AUTHOR]

We prove that every properly edge-colored n-vertex graph with average degree at least 32 (log 5 n) 2 contains a rainbow cycle, improving upon the (log n) 2 + o (1) bound due to Tomon. We also prove that every properly edge-colored n-vertex graph with at least 10 5 k 3 n 1 + 1 / k edges contains a rainbow 2k-cycle, which improves the previous bound 2 c k 2 n 1 + 1 / k obtained by Janzer. Our method using homomorphism inequalities and a lopsided regularization lemma also provides a simple way to prove the Erdős–Simonovits supersaturation theorem for even cycles, which may be of independent interest. [ABSTRACT FROM AUTHOR]

Tissue barriers in a body, well known as tissue-to-tissue interfaces represented by endothelium of the blood vessels or epithelium of organs, are essential for maintaining physiological homeostasis by regulating molecular and cellular transports. It is crucial for predicting drug response to understand physiology of tissue barriers through which drugs are absorbed, distributed, metabolized and excreted. Since the FDA Modernization Act 2.0, which prompts the inception of alternative technologies for animal models, tissue barrier chips, one of the applications of organ-on-a-chip or microphysiological system (MPS), have only recently been utilized in the context of drug development. Recent advancements in stem cell technology have brightened the prospects for the application of tissue barrier chips in personalized medicine. In past decade, designing and engineering these microfluidic devices, and demonstrating the ability to reconstitute tissue functions were main focus of this field. However, the field is now advancing to the next level of challenges: validating their utility in drug evaluation and creating personalized models using patient-derived cells. In this review, we briefly introduce key design parameters to develop functional tissue barrier chip, explore the remarkable recent progress in the field of tissue barrier chips and discuss future perspectives on realizing personalized medicine through the utilization of tissue barrier chips. [ABSTRACT FROM AUTHOR]

The conversion of CO2 into fuels and value-added chemicals over heterogeneous catalysts may help realize a carbon-neutral or carbon-negative society. Recently, the direct conversion of CO2 to aromatics has been extensively explored. However, the requirement of multifunctional active sites, complexity of tandem cascade reactions, and difficulty in understanding reaction mechanisms present significant challenges to the design of effective heterogeneous catalysts. In this review, catalytic systems used for the direct production of aromatics from CO2 via the methanol-mediated and modified Fischer–Tropsch synthesis pathways are critically discussed. The initial section discusses the role of acid sites in HZSM-5 for the formation of aromatics. This is followed by a thorough review of recent progress on aromatic syntheses in terms of their catalytic performance, Si/Al ratios of zeolites, proximity between metal oxide and zeolite, and reaction conditions. The reaction mechanisms and the stability of existing catalysts are also discussed. Finally, the current challenges and future prospects of the catalytic conversion of CO2 to aromatics are highlighted. [ABSTRACT FROM AUTHOR]

Let f^{(r)}(n;s,k) be the maximum number of edges of an r-uniform hypergraph on n vertices not containing a subgraph with k edges and at most s vertices. In 1973, Brown, Erdős, and Sós conjectured that the limit \begin{equation*} \lim _{n\to \infty } n^{-2} f^{(3)}(n;k+2,k) \end{equation*} exists for all k and confirmed it for k=2. Recently, Glock showed this for k=3. We settle the next open case, k=4, by showing that f^{(3)}(n;6,4)=\left (\frac {7}{36}+o(1)\right)n^2 as n\to \infty. More generally, for all k\in \{3,4\}, r\ge 3 and t\in [2,r-1], we compute the value of the limit \lim _{n\to \infty } n^{-t}f^{(r)}(n;k(r-t)+t,k), which settles a problem of Shangguan and Tamo. [ABSTRACT FROM AUTHOR]

Dysregulation of the hypothalamic–pituitary–adrenal axis and abnormalities in the glucocorticoid receptor (GR) have been linked to major depressive disorder. Given the critical role of GR in stress response regulation, we investigated the impact of GR changes on neural stem cells (NSCs) proliferation and hippocampal neurogenesis. Stress response was induced using dexamethasone (DEX), a GR agonist, which led to reduced proliferation of neural stem cells and neural progenitor cells, as well as decreased expression of GR. Additionally, a reduction of serum concentration within the culture media resulted in suppressed cell proliferation, accompanied by decreased GR expression. The association between GR expression and cell proliferation was further confirmed through GR siRNA knockdown and overexpression experiments. Furthermore, in vivo studies utilizing young male C57BL/6 mice demonstrated that corticosterone (CORT) (35 μg/ml) administered through drinking water for four weeks induced depression-like behavior, as indicated by increased immobility times in forced swimming and tail suspension tests. CORT exposure led to reduced GR and nestin expression levels, along with diminished numbers of BrdU-positive cells in the hippocampi, indicating impaired hippocampal neurogenesis. Taken together, our findings provide the first evidence that stress-induced downregulation of GR negatively affects neurogenesis by inhibiting NSCs proliferation. [ABSTRACT FROM AUTHOR]

Cubic boron arsenide (BAs) is a subject of considerable interest in thermal science due to its exceptionally high thermal conductivity. However, the inherent long mean free path of phonons renders the thermal conductivity of BAs highly susceptible to impurity concentration. In this study, we present a catalyst assisted crystal synthesis approach to achieve high-quality cubic BAs, leveraging Pt as a catalyst in the synthesis process. Our thermal conductivity measurements reveal that over 90% of the samples in a batch exhibit thermal conductivity values exceeding 1000 W·m−1·K−1. The robustness of the synthesis method is further validated through thermal conductivity mapping and Raman spectroscopy. These findings offer valuable insights for enhancing the quality of BAs crystals and hold promise for practical applications. [ABSTRACT FROM AUTHOR]

A celebrated theorem of Pippenger, and Frankl and Rödl states that every almost‐regular, uniform hypergraph H$\mathcal {H}$ with small maximum codegree has an almost‐perfect matching. We extend this result by obtaining a conflict‐free matching, where conflicts are encoded via a collection C$\mathcal {C}$ of subsets C⊆E(H)$C\subseteq E(\mathcal {H})$. We say that a matching M⊆E(H)$\mathcal {M}\subseteq E(\mathcal {H})$ is conflict‐free if M$\mathcal {M}$ does not contain an element of C$\mathcal {C}$ as a subset. Under natural assumptions on C$\mathcal {C}$, we prove that H$\mathcal {H}$ has a conflict‐free, almost‐perfect matching. This has many applications, one of which yields new asymptotic results for so‐called 'high‐girth' Steiner systems. Our main tool is a random greedy algorithm which we call the 'conflict‐free matching process'. [ABSTRACT FROM AUTHOR]

Porous silicon nanoparticles (pSiNPs) are of increased interest for use in drug delivery systems, as catalysts, and as biomedical imaging agents. The most common synthesis of pSiNPs involves electrochemical anodization of a silicon wafer, followed by ultrasonic fracture of the resulting mesoporous film to form well-defined nanoparticles. A major source of loss in this process is the ultrasonic fracture step. This work presents a method of synthesizing gram-scale quantities of pSiNPs with high yield and high reproducibility using an ultrasonic bath equipped with a sample rotation stage and a refrigerator (4 °C) and a higher ultrasound frequency with power delivered in a pulsed modality compared with the static ultrasound "cleaning baths" commonly used for this purpose. The optimal processing conditions are determined by adjusting the pSi film mass, solvent volume, and iteration number of on/off cycles used in sonication. The approach provides pSiNPs with a narrow size distribution (∼170 nm, PDI = 0.149), higher yields (59%), and an approximately 12-fold reduction in the total processing time, allowing the preparation of gram-scale quantities of pSiNPs from single-crystal silicon wafers with high reproducibility in a single 24 h process. The performance of the produced pSiNPs is validated in a drug delivery application in which loading and release of the anthracycline drug doxorubicin are compared with pSiNPs prepared in a conventional cleaning bath ultrasonicator. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a neurodegenerative disorder that results in motor impairment due to dopaminergic neuronal loss. The pathology of PD is closely associated with neuroinflammation, which can be characterized by astrocyte activation. Thus, targeting the inflammatory response in astrocytes might provide a novel therapeutic approach. We conducted a luciferase assay on an in-house chemical library to identify compounds with anti-inflammatory effects capable of reducing MPP+-induced NF-κB activity in astrocytes. Among the compounds identified, EI-16004, a novel 3-benzyl-N-phenyl-1H-pyrazole-5-carboxamides, exhibited a significant anti-inflammatory effect by significantly reducing MPP+-induced astrocyte activation. Biochemical analysis and docking simulation indicated that EI-16004 inhibited the MPP+-induced phosphorylation of p65 by attenuating ERK phosphorylation, and EI-16004 reduced pro-inflammatory cytokine and chemokine levels in astrocytes. In vivo studies on the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD model in male C57BL/6 mice showed that EI-16004 ameliorated motor impairment and protected against dopaminergic neuronal loss, and EI-16004 effectively mitigated the MPTP-induced astrocyte activation in striatum (STR) and substantia nigra (SN). These results indicate EI-16004 is a potential neuroprotective agent for the prevention and treatment of astrocyte-mediated neuroinflammatory conditions in PD. [ABSTRACT FROM AUTHOR]

Given k$$ k $$ graphs G1,...,Gk$$ {G}_1,\dots, {G}_k $$ over a common vertex set of size n$$ n $$, what is the maximum value of ∑i∈[k]e(Gi)$$ {\sum}_{i\in \left[k\right]}e\left({G}_i\right) $$ having no "colorful" copy of H$$ H $$, that is, a copy of H$$ H $$ containing at most one edge from each Gi$$ {G}_i $$? Keevash, Saks, Sudakov, and Verstraëte denoted this number as exk(n,H)$$ {\mathrm{ex}}_k\left(n,H\right) $$ and completely determined exk(n,Kr)$$ {\mathrm{ex}}_k\left(n,{K}_r\right) $$ for large n$$ n $$. In fact, they showed that, depending on the value of k$$ k $$, one of the two natural constructions is always the extremal construction. Moreover, they conjectured that the same holds for every color‐critical graphs, and proved it for 3‐color‐critical graphs. They also asked to classify the graphs H$$ H $$ that have only these two extremal constructions. We prove their conjecture for 4‐color‐critical graphs and for almost all r$$ r $$‐color‐critical graphs when r>4$$ r>4 $$. Moreover, we show that for every non‐color‐critical non‐bipartite graphs, none of the two natural constructions is extremal for certain values of k$$ k $$. [ABSTRACT FROM AUTHOR]

For safe coexistence between robots and humans, it is important for robots to detect the presence of nearby humans as well as any physical contacts made to its body. The design of a modular textile sensor array and an algorithm for multi‐modal sensing of human touches and other contacts with their contact forces proposed. Each sensor module in the array is capable of multi‐modal sensing, and the entire array with multiple modules requires only two wires to read the outputs from all the modules using band‐stop filter circuits. The proposed sensor system shows the structural modularity, achieved by simple fabrication of sequential lamination of conductive and non‐conductive textile materials, realizing electrical connections through conductive snap buttons that connect the modules to the circuit. The functional modularity is also achieved through the compensation algorithm, derived from the analysis of the transfer function in the frequency domain. The algorithm significantly reduces signal interferences between modules. The multi‐modality, the textile‐based design, and the structural and functional modularity of the proposed system enable practical applications to various robotic systems, including robotic skin for a collaborative robot, a wearable sensor, a robot hand sensor, and a human–computer interface, as demonstrated in this study. [ABSTRACT FROM AUTHOR]

Since the invention of transistors and integrated circuits, the development of semiconductor processes has advanced rapidly. Current microchips contain hundreds of millions of transistors. The remarkable development of semiconductors thus far has also led to difficulties in designing tightly packed lithography patterns without unwanted defects called hotspots in the manufacturing process. Therefore, research areas focusing on these problems have received much attention. In particular, predicting hotspots during the design stage is essential for high productivity in the semiconductor industry. In this study, we developed a deep learning-based SEM image generation model to predict hotspots from layout patterns at the design stage. Our model combines a segmentation network and an image-to-image translation network based on a conditional generative adversarial network in parallel. Our proposed model can predict and display potential hotspots in scanning electron microscopy images generated from given layouts. Additionally, the model leverages prior knowledge of the optical diameter to predict patterns that are prone to hotspots. Our model shows improved performance over baseline models when evaluated on real-world industrial data. [ABSTRACT FROM AUTHOR]

Inositol polyphosphates (IPs) are a group of inositol metabolites that act as secondary messengers for external signalling cues. They play various physiological roles such as insulin release, telomere length maintenance, cell metabolism, and aging. Inositol hexakisphosphate kinase 2 (IP6K2) is a key enzyme that produces 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-IP7), which influences the early stages of glucose-induced exocytosis. Therefore, regulation of IP6Ks may serve as a promising strategy for treating diseases such as diabetes and obesity. In this study, we designed, synthesised, and evaluated flavonoid-based compounds as new inhibitors of IP6K2. Structure-activity relationship studies identified compound 20s as the most potent IP6K2 inhibitor with an IC50 value of 0.55 μM, making it 5-fold more potent than quercetin, the reported flavonoid-based IP6K2 inhibitor. Compound 20s showed higher inhibitory potency against IP6K2 than IP6K1 and IP6K3. Compound 20s can be utilised as a hit compound for further structural modifications of IP6K2 inhibitors. [ABSTRACT FROM AUTHOR]

Helly's theorem and its variants show that for a family of convex sets in Euclidean space, local intersection patterns influence global intersection patterns. A classical result of Eckhoff in 1988 provided an optimal fractional Helly theorem for axis-aligned boxes, which are Cartesian products of line segments. Answering a question raised by Bárány and Kalai, and independently Lew, we generalize Eckhoff's result to Cartesian products of convex sets in all dimensions. In particular, we prove that given α ∈ (1 - 1 / t d , 1 ] and a finite family F of Cartesian products of convex sets ∏ i ∈ [ t ] A i in R td with A i ⊂ R d , if at least α -fraction of the (d + 1) -tuples in F are intersecting, then at least (1 - (t d (1 - α)) 1 / (d + 1)) -fraction of sets in F are intersecting. This is a special case of a more general result on intersections of d-Leray complexes. We also provide a construction showing that our result on d-Leray complexes is optimal. Interestingly, the extremal example is representable as a family of Cartesian products of convex sets, implying that the bound α > 1 - 1 / t d and the fraction (1 - (t d (1 - α)) 1 / (d + 1)) above are also best possible. The well-known optimal construction for fractional Helly theorem for convex sets in R d does not have (p , d + 1) -condition for sublinear p, that is, it contains a linear-size subfamily with no intersecting (d + 1) -tuple. Inspired by this, we give constructions showing that, somewhat surprisingly, imposing an additional (p , d + 1) -condition has a negligible effect on improving the quantitative bounds in neither the fractional Helly theorem for convex sets nor Cartesian products of convex sets. Our constructions offer a rich family of distinct extremal configurations for fractional Helly theorem, implying in a sense that the optimal bound is stable. [ABSTRACT FROM AUTHOR]

Herein, we report our findings on 4-carbazole (CBZ)-appended salen-based indium complexes, CBZIn1 and CBZIn2, which feature diimine bridges exhibiting different electron-accepting properties. Notably, CBZIn2 exhibited a significantly higher photoluminescence quantum efficiency (PLQY, ΦPL) in toluene than CBZIn1, with a value over 15 times greater (ΦPL = 57.7% for CBZIn2; ΦPL = 3.7% for CBZIn1). In particular, in the rigid state of THF at 77 K, CBZIn2 exhibited a near-unity PLQY of 98.2%. Even in the PMMA film, CBZIn2 maintained a high level of PLQY (ΦPL = 70.2%). These results can be attributed to the highly efficient radiative decay process based on intramolecular charge-transfer (ICT) transition between the moderately twisted CBZ, characterized by its conformational rigidity and the 1,2-dicyanoethylene-bridged salen, which exhibits a strong electron-accepting ability. Furthermore, these findings are supported by theoretical calculations. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) is a powerful approach that combines reinforcement learning (RL) and deep learning to address complex decision-making problems in high-dimensional environments. Although DRL has been remarkably successful, its low sample efficiency necessitates extensive training times and large amounts of data to learn optimal policies. These limitations are more pronounced in the context of multi-agent reinforcement learning (MARL). To address these limitations, various studies have been conducted to improve DRL. In this study, we propose an approach that combines a masked reconstruction task with QMIX (M-QMIX). By introducing a masked reconstruction task as an auxiliary task, we aim to achieve enhanced sample efficiency—a fundamental limitation of RL in multi-agent systems. Experiments were conducted using the StarCraft II micromanagement benchmark to validate the effectiveness of the proposed method. We used 11 scenarios comprising five easy, three hard, and three very hard scenarios. We particularly focused on using a limited number of time steps for each scenario to demonstrate the improved sample efficiency. Compared to QMIX, the proposed method is superior in eight of the 11 scenarios. These results provide strong evidence that the proposed method is more sample-efficient than QMIX, demonstrating that it effectively addresses the limitations of DRL in multi-agent systems. [ABSTRACT FROM AUTHOR]

Aberrant enhancer activation is a key mechanism driving oncogene expression in many cancers. While much is known about the regulation of larger chromosome domains in eukaryotes, the details of enhancer-promoter interactions remain poorly understood. Recent work suggests co-activators like BRD4 and Mediator have little impact on enhancer-promoter interactions. In leukemias controlled by the MLL-AF4 fusion protein, we use the ultra-high resolution technique Micro-Capture-C (MCC) to show that MLL-AF4 binding promotes broad, high-density regions of enhancer-promoter interactions at a subset of key targets. These enhancers are enriched for transcription elongation factors like PAF1C and FACT, and the loss of these factors abolishes enhancer-promoter contact. This work not only provides an additional model for how MLL-AF4 is able to drive high levels of transcription at key genes in leukemia but also suggests a more general model linking enhancer-promoter crosstalk and transcription elongation. Previous studies have reported MLL-AF4 binding at intragenic and intergenic enhancers, however, the role of MLL-AF4 in enhancer function remains to be investigated. Here, the authors show that MLL-AF4 cooperates with PAF1 and FACT at enhancers to promote high-density interactions with oncogene promoters in leukemia. [ABSTRACT FROM AUTHOR]

In vitro investigation of a glomerular filtration barrier (GFB) remains difficult because of the inability to mimic its specialized structure, although various kidney diseases are characterized by GFB dysfunction. Here, the development of a microfluidic model that replicates the physiology of the GFB has been achieved by tunable glomerular basement membrane (gBM) deposition and 3D co-culture of podocytes with glomerular endothelial cells (gECs). By precisely controlling the thickness of the gBM, our model successfully reproduced the biphasic response of the GFB, where variations in gBM thickness influence barrier properties. Moreover, this microscale proximity of gECs and podocytes facilitated their dynamic crosstalk, which is essential for maintaining the integrity and function of the GFB. We observed that addition of gBM and podocytes enhanced barrier function of gECs by inducing up-regulation of gEC's tight junctions synergistically, and moreover, found an ultrastructure of gECs–gBM–podocytes' foot process contacting each other by confocal and TEM imaging. The dynamic interaction of gECs and podocytes played a significant role in the response to drug-induced injury and the regulation of barrier properties. Nephrotoxic injury simulated in our model helped to elucidate that the over-production of vascular endothelial growth factor A from the injured podocytes mediates GFB impairment. We believe that our GFB model can provide a valuable tool for mechanistic studies such as investigating GFB biology, comprehending disease mechanisms, and evaluating potential therapeutic approaches in a controlled and physiologically relevant environment. [ABSTRACT FROM AUTHOR]

This study investigated the slow pyrolysis behavior of raw rice husk (RRH) and fermented rice husk (FRH) in a fixed-bed reactor at temperatures in the range of 200–600 °C. The effects of pyrolysis temperature on the biochar yield, composition, and physiochemical properties were examined to evaluate the energy potential of biochars produced from RRH and FRH. The FRH-derived biochar produced at 600 °C was found to be more suitable than the RRH-derived biochar because of its higher carbon content (68.9% vs 42.1%), GCV (31.6 vs 24.1 MJ kg−1), and true density (1.94 vs 1.54 g cm −3). The slow pyrolysis in the high-temperature regime facilitated the formation of lignin-rich and aromatically condensed biochar, making it particularly useful for producing carbon-rich materials. Thus, slow pyrolysis can be a technically viable approach for producing high-energy-density solid fuels that can replace medium-ranking coals in co-firing. [ABSTRACT FROM AUTHOR]

Microphysiological system or organ-on-a-chip technologies can replicate the key structure and function of 3D human tissues with higher reproducibility than less controllable 3D cell aggregate models, providing great potential to become advanced drug toxicity and efficacy test platforms alternative to animal models. However, these organ chip models remain to be manufactured and standardized in a highly reproducible manner for reliable drug screening and mechanism of action research. Herein, we present a manufactured form of 'micro-engineered physiological system-tissue barrier chip' called MEPS-TBC for the highly replicable modeling of the human blood–brain barrier (BBB) with a 3D perivascular space. The perivascular region was controlled by tunable aspiration, where human astrocytes reside in 3D, create a network, and communicate with human pericytes facing human vascular endothelial cells, thereby replicating the 3D BBB. The lower channel structure of MEPS-TBC was designed and optimized using a computational simulation to facilitate aspiration while maintaining multicellular construction. Our human BBB model of the 3D perivascular unit and the endothelium perfused by physiological shear stress secured significantly enhanced barrier function exhibiting greater TEER and lower permeability, compared to the only endothelial model, indicating that the cellular interactions between BBB cells significantly contribute to the BBB formation. Importantly, our BBB model showed the cellular barrier function for homeostatic trafficking regulation against inflammatory peripheral immune cells, as well as for molecular transport control across the BBB. We believe our manufactured chip technology will construct reliable and standardized organ-chip models for disease mechanism research and predictive drug screening. [ABSTRACT FROM AUTHOR]

Electrochemical CO production from CO2 electrolysis has been considered the most economically viable approach among various candidate products. AuCu bimetallic alloys are currently receiving attention for their potential to tailor catalytic activity. Here, we synthesized a dilute AuCu alloy nanostructure with an AuCu atomic composition ratio of 3% by using a simple electrochemical treatment method on a 200 nm-thick Au thin film. The dilute AuCu alloy catalyst shows an exceptional CO2 reduction activity in terms of selectivity and overpotential for CO production. In addition, the stability property is more significantly enhanced as compared to pure Au nanostructures. In addition, we describe an in situ tailoring method of catalytic activity for Au nanostructures by repeating an electrochemical treatment process that is performed for forming the Au nanostructure. This approach will be a promising and facile strategy not only for reactive Au catalysts but also to increase the stability activity simultaneously by utilizing Cu impurities existing in an aqueous electrolyte for CO2 reduction. [ABSTRACT FROM AUTHOR]

Brown adipose tissue (BAT) has abundant mitochondria with the unique capability of generating heat via uncoupled respiration. Mitochondrial uncoupling protein 1 (UCP1) is activated in BAT during cold stress and dissipates mitochondrial proton motive force generated by the electron transport chain to generate heat. However, other mitochondrial factors required for brown adipocyte respiration and thermogenesis under cold stress are largely unknown. Here, we show LETM1 domain-containing protein 1 (LETMD1) is a BAT-enriched and cold-induced protein required for cold-stimulated respiration and thermogenesis of BAT. Proximity labeling studies reveal that LETMD1 is a mitochondrial matrix protein. Letmd1 knockout male mice display aberrant BAT mitochondria and fail to carry out adaptive thermogenesis under cold stress. Letmd1 knockout BAT is deficient in oxidative phosphorylation (OXPHOS) complex proteins and has impaired mitochondrial respiration. In addition, BAT-specific Letmd1 deficient mice exhibit phenotypes identical to those observed in Letmd1 knockout mice. Collectively, we demonstrate that the BAT-enriched mitochondrial matrix protein LETMD1 plays a tissue-autonomous role that is essential for BAT mitochondrial function and thermogenesis. Brown adipose tissue (BAT) has abundant mitochondria with the unique capability of generating heat via uncoupled respiration. Here, Park et al. identify LETMD1 as a mitochondrial matrix protein enriched in brown adipose tissue (BAT) and reveal a crucial role for it in maintaining brown adipocyte mitochondrial OXPHOS and thermogenesis upon cold stimulus. [ABSTRACT FROM AUTHOR]

Adult neurogenesis generates new functional neurons from adult neural stem cells in various regions, including the subventricular zone (SVZ) of the lateral ventricles and subgranular zone (SGZ) of hippocampal dentate gyrus (DG). Available evidence shows hippocampal neurogenesis can be negatively or positively regulated by dietary components. In a previous study, we reported that curcumin (diferuloylmethane; a polyphenolic found in curry spice) stimulates the proliferation of embryonic neural stem cells (NSCs) by activating adaptive cellular stress responses. Here, we investigated whether subchronic administration of curcumin (once daily at 0.4, 2, or 10 mg/kg for 14 days) promotes hippocampal neurogenesis and neurocognitive function in young (5-week-old) mice. Oral administration of low-dose curcumin (0.4 mg/kg) increased the proliferation and survival of newly generated cells in hippocampus, but surprisingly, high-dose curcumin (10 mg/kg) did not effectively upregulate the proliferation or survival of newborn cells. Furthermore, hippocampal BDNF levels and phosphorylated CREB activity were elevated in only low-dose curcumin-treated mice. Passive avoidance testing revealed that low-dose curcumin increased cross-over latency times, indicating enhanced memory retention, and an in vitro study showed that low-concentration curcumin increased the proliferative activity of neural progenitor cells (NPCs) by upregulating NF1X levels. Collectively, our findings suggest that low-dose curcumin has neurogenic effects and that it may prevent age and neurodegenerative disease-related cognitive deficits. [ABSTRACT FROM AUTHOR]

Daphnia magna is an important organism in ecotoxicity studies because it is sensitive to toxic substances and easy to culture in laboratory conditions. Its locomotory responses as a biomarker are highlighted in many studies. Over the last several years, multiple high-throughput video tracking systems have been developed to measure the locomotory responses of Daphnia magna. These high-throughput systems, used for high-speed analysis of multiple organisms, are essential for efficiently testing ecotoxicity. However, existing systems are lacking in speed and accuracy. Specifically, speed is affected in the biomarker detection stage. This study aimed to develop a faster and better high-throughput video tracking system using machine learning methods. The video tracking system consisted of a constant temperature module, natural pseudo-light, multi-flow cell, and an imaging camera for recording videos. To measure Daphnia magna movements, we developed a tracking algorithm for automatic background subtraction using k-means clustering, Daphnia classification using machine learning methods (random forest and support vector machine), and tracking each Daphnia magna location using the simple online real-time tracking algorithm. The proposed tracking system with random forest performed the best in terms of identification (ID) precision, ID recall, ID F1 measure, and ID switches, with scores of 79.64%, 80.63%, 78.73%, and 16, respectively. Moreover, it was faster than existing tracking systems such as Lolitrack and Ctrax. We conducted an experiment to observe the impact of toxicants on behavioral responses. Toxicity was measured manually in the laboratory and automatically using the high-throughput video tracking system. The median effective concentration of Potassium dichromate measured in the laboratory and using the device was 1.519 and 1.414, respectively. Both measurements conformed to the guideline provided by the Environmental Protection Agency of the United States; therefore, our method can be used for water quality monitoring. Finally, we observed Daphnia magna behavioral responses in different concentrations after 0, 12, 18, and 24 h and found that there was a difference in movement according to the concentration at all hours. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a hybrid framework that combines a data-driven pose estimation with model-based force calculation in order to predict the ski jumping force from a recorded motion video. A skeletal model consisting of five joints (ear, hip, knee, ankle, and toe) and four rigid segments (head/arm/trunk or HAT, thigh, shank, and foot) connecting each joint is developed. The joint forces are calculated from the dynamic equilibrium equations, which requires the time history of joint coordinates. They are estimated from a recorded motion video using a deep neural network for pose estimation trained with human motion data. Joint coordinates can be obtained by the proposed deep neural network directly from images of jumping motion without using any markers. The validity and usefulness of the proposed method are confirmed in lab experiments. Further, our method is practically applicable to the study in a real competition environment because it is not required to attach any sensor or marker to athletes. Highlights A method to predict the ski jumping force from a recorded motion video is proposed. It combines a data-driven pose estimation with a model-based force calculation. The proposed method does not require any markers and sensors to be attached to athletes. In a laboratory environment, the relative error in the maximum jumping force is less than 7%. The method can be easily applied to a field study in a real competition environment. [ABSTRACT FROM AUTHOR]

A well‐known theorem of Whitney states that a 3‐connected planar graph admits an essentially unique embedding into the 2‐sphere. We prove a 3‐dimensional analogue: a simply‐connected 2‐complex every link graph of which is 3‐connected admits an essentially unique locally flat embedding into the 3‐sphere, if it admits one at all. This can be thought of as a generalisation of the 3‐dimensional Schoenflies theorem. [ABSTRACT FROM AUTHOR]

In this study, we collected various past study results on tools and analytical methods for measuring hand functions of patients with degenerative brain diseases, such as Parkinson's disease and stroke, and selected and proposed appropriate hand function measurement tools, methods, and analysis software based on text network analysis. We searched the literatures using keywords related to degenerative brain disease and stroke patients for participant types, use of devices and sensors for the intervention types, and hand function assessment for measurement types. Among the 2484 literatures collected, 19 were eventually selected based on certain inclusion and exclusion criteria. As a result of text network analysis, the degree-centrality and the betweenness centrality were the highest in the keyword of Parkinson's disease for the participant type, force sensor for the intervention type, and finger tapping for the measurement type. Based on these results, pinch gloves comprising an FSR sensor were manufactured, and software and contents were implemented to measure and analyze various quantitative parameter values during finger tapping. The software can evaluate endurance and agility by measuring the finger-tapping intensity and operation time using the index finger and thumb. The contents can evaluate the stability of hand functions by analyzing the coefficient of variation of the tapping interval, the average contact time, and the accuracy of hand functions by analyzing the reaction rate to the presented visual stimulus. As a result of comparing hand functions through 10 types of analysis parameters with a sample of 12 ordinary subjects (8 men and 4 women) using the manufactured pinch gloves, there was a difference between the two genders in the items evaluating muscle strength and agility, and a significant difference in the analysis parameters evaluating stability and accuracy. The results indicate that using the text network analysis-based hand function measurement tool and the method proposed in this study should help derive the objective research results as well as a quantitative comparison of research results of various researchers. [ABSTRACT FROM AUTHOR]

The Ramsey number R(F,H) is the minimum number N such that any N-vertex graph either contains a copy of F or its complement contains H. Burr in 1981 proved a pleasingly general result that for any graph H, provided n is sufficiently large, a natural lower bound construction gives the correct Ramsey number involving cycles: R(Cn,H)=(n-1)(χ(H)-1)+σ(H), where σ(H) is the minimum possible size of a colour class in a χ(H)-colouring of H. Allen, Brightwell and Skokan conjectured that the same should be true already when n≥|H|χ(H). We improve this 40-year-old result of Burr by giving quantitative bounds of the form n≥C|H|log4χ(H), which is optimal up to the logarithmic factor. In particular, this proves a strengthening of the Allen-Brightwell-Skokan conjecture for all graphs H with large chromatic number. [ABSTRACT FROM AUTHOR]

Changes in water quality were examined during selected rainfall events in a headwater stream severely damaged by a forest fire on 21–23 February 2021. Seven water quality parameters were analyzed: pH, electrical conductivity, biochemical oxygen demand, chemical oxygen demand, total suspended solids (TSS), total nitrogen, and total phosphorous. First-flush effect and event mean concentration analyses were conducted in spring (dry season) and summer (wet season) immediately after the forest fire. In spring, the non-biodegradable organic matter concentrations increased along with pollutants related to ash-enhanced soil water repellency in water affected by first-flush effects. In summer, TSS and nutrient concentrations increased along with pollutants related to fire-induced soil surface disturbances after a series of rainfall events. First-flush analyses indicated that cumulative pollutant loads were greater in the spring than in the summer due to a higher concentration of forest fire ash in the early storm runoff immediately after the forest fire. The event mean concentrations revealed that pollutant loads were associated with both forest fire ash and storm events in the immediate post-fire period. Therefore, this study indicated that water quality along a headwater stream is affected by short-term effects of large and intense forest fires and rainfall seasonality. [ABSTRACT FROM AUTHOR]

Used textiles, such as jeans wastes, exhibit a high potential for generating renewable and sustainable energy. However, limited research has been devoted toward investigating the kinetic and thermodynamic parameters of textile wastes during pyrolysis and applying these wastes as feedstock for fuels such as biogas. Therefore, this study investigated the kinetic and thermodynamic aspects of the thermal decomposition of jeans waste to evaluate its potential for sustainable energy production. Jeans waste was heat treated at 50–850 °C under different heating rates of 10–40 °C min−1. Active pyrolysis for the decomposition of jeans waste occurred at temperatures ranging from 250 to 550 °C. Specific Coats-Redfern-type reaction mechanisms were applied to determine the kinetic and thermodynamic variables in the active temperature zone. The thermodynamic parameters (ΔH and ΔG) and activation energies increased when the heating rate was increased from 10 to 30 °C min−1. When the heating rate was further increased to 40 °C min−1, ΔH, ΔG, and the activation energies decreased. For heating rates of 10, 20, 30, and 40 °C min−1, the pre-exponential factors varied in the ranges of 7.4×103 to 1.4×104, 1.8×104 to 5.1×1010, 2.8×104 to 5.3×1010, and 3.6×104 to 3.1×1010 min−1, respectively. In each reaction mechanism model, the entropy changed negatively for all the heating rates examined in this study. This work and its results could serve as a guide for implementing such pyrolysis processes for textile wastes at a practical scale for bioenergy applications. [ABSTRACT FROM AUTHOR]

In this paper, anomaly detection of wheel flats based on signal processing and deep learning techniques is analyzed. Wheel flats mostly affect running stability and ride comfort. Currently, domestic railway companies visually inspect wheel flats one by one with their eyes after railway vehicles enter the railway depots for maintenance. Therefore, CBM (Condition-Based Maintenance) is required for wheel flats resolution. Anomaly detection for wheel flat signals of railway vehicles using Order analysis and STFT (Short Time Fourier Transform) is studied in this paper. In the case of railway vehicles, it is not easy to obtain actual failure data through running vehicles in a university laboratory due to safety and cost issues. Therefore, vibration-induced acceleration was obtained using a multibody dynamics simulation software, SIMPACK. This method is also proved in the other paper by rig tests. In addition, since the noise signal was not included in the simulated vibration, the noise signal obtained from the Seoul Metro Subway Line 7 vehicle was overlapped with the simulated one. Finally, to improve the performance of both detection rate and real-time of characteristics based on existing LeNet-5 architectures, spectrogram images transformed from time domain data were proceeded with the LeNet deep learning model modified with the pooling method and activation function. As a result, it is validated that the method using the spectrogram with a deep learning approach yields higher accuracy than the time domain data. [ABSTRACT FROM AUTHOR]

We study regular graphs in which the random walks starting from a positive fraction of vertices have small mixing time. We prove that any such graph is virtually an expander and has no small separator. This answers a question of Pak [ SODA: Proceedings of the Thirteenth Annual ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied Mathematics , Philadelphia, PA, 2002, pp. 321–328]. As a corollary, it shows that sparse (constant degree) regular graphs with many well-mixing vertices have a long cycle, improving a result of Pak. Furthermore, such cycle can be found in polynomial time. Secondly, we show that if the random walks from a positive fraction of vertices are well-mixing, then the random walks from almost all vertices are well-mixing (with a slightly worse mixing time). [ABSTRACT FROM AUTHOR]

Sea fog can seriously affect schedules and safety by reducing visibility during marine transportation. Therefore, the forecasting of sea fog is an important issue in preventing accidents. Recently, in order to forecast sea fog, several deep learning methods have been applied to time series data consisting of meteorological and oceanographic observations or image data to predict fog. However, these methods only use a single image without considering meteorological and temporal characteristics. In this study, we propose a multi-modal learning method to improve the forecasting accuracy of sea fog using convolutional neural network (CNN) and gated recurrent unit (GRU) models. CNN and GRU extract useful features from closed-circuit television (CCTV) images and multivariate time series data, respectively. CCTV images and time series data collected at Daesan Port in South Korea from 1 March 2018 to 14 February 2021 by Korea Hydrographic and Oceanographic Agency (KHOA) were used to evaluate the proposed method. We compare the proposed method with deep learning methods that only consider temporal information or spatial information. The results indicate that the proposed method using both temporal and spatial information at the same time shows superior accuracy. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to introduce a new surgical technique for pedicled TRAM flap that removes a part of the rectus abdominis muscle inserting into ribs, and to analyze this technique in comparison with classical pedicled TRAM flap. Methods: A retrospective review of patient charts from May 2006 to February 2016 was performed. The patient group that underwent the removal of the part of the rectus abdominis that inserts into the thorax (partial muscle resection; PMR group) was compared with the group that did not undergo this muscle resection (Classical group). The complications and aesthetic effects of surgery between the two groups were analyzed. Results: There were 34 patients in the classical group and 28 in the PMR group. There were no significant differences in postoperative complications between these two groups. The rates of fat necrosis were 32.1% in the PMR group and 36.1% in the classical group. The postoperative aesthetic outcome of the inframammary fold showed no significant differences in outcome between the classical and PMR groups. However, all items received higher scores in the PMR group. Conclusions: The authors' new surgical method was associated with a positive cosmetic effect of improving inframammary fold aesthetics and could thus represent a new option for pTRAM breast reconstruction. [ABSTRACT FROM AUTHOR]

We prove an asymptotically tight bound on the extremal density guaranteeing subdivisions of bounded-degree bipartite graphs with a mild separability condition. As corollaries, we answer several questions of Reed and Wood on embedding sparse minors. Among others, • average degree is sufficient to force the grid as a topological minor; • average degree forces every -vertex planar graph as a minor, and the constant is optimal, furthermore, surprisingly, the value is the same for -vertex graphs embeddable on any fixed surface; • a universal bound of on average degree forcing every -vertex graph in any nontrivial minor-closed family as a minor, and the constant 2 is best possible by considering graphs with given treewidth. [ABSTRACT FROM AUTHOR]

Neurodegenerative diseases such as Parkinson's disease (PD) are known to be related to oxidative stress and neuroinflammation, and thus, modulating neuroinflammation offers a possible means of treating PD-associated pathologies. Morin (2′,3,4′,5,7-pentahydroxy flavone) is a flavonol with anti-oxidative and anti-inflammatory effects found in wines, herbs, and fruits. The present study was undertaken to determine whether a morin-containing diet has protective effects in an MPTP-induced mouse model of PD. Mice were fed a control or morin diet for 34 days, and then MPTP (30 mg/kg, i.p.) was administered daily for 5 days to induce a PD-like pathology. We found that dietary morin prevented MPTP-induced motor dysfunction and ameliorated dopaminergic neuronal damage in striatum (STR) and substantia nigra (SN) in our mouse model. Furthermore, MPTP-induced neuroinflammation was significantly reduced in mice fed morin. In vitro studies showed that morin effectively suppressed glial activations in primary microglia and astrocytes, and biochemical analysis and a docking simulation indicated that the anti-inflammatory effects of morin were mediated by blocking the extracellular signal-regulated kinase (ERK)-p65 pathway. These findings suggest that morin effectively inhibits glial activations and has potential use as a functional food ingredient with therapeutic potential for the treatment of PD and other neurodegenerative diseases associated with neuroinflammation. [ABSTRACT FROM AUTHOR]

This article studies low-temperature sol–gel processed indium (In)-doped ZnO (IZO) for highly efficient organic photovoltaics (OPVs). Contrary to the prior research trends adopting doped sol–gel processed ZnO with an annealing temperature of over 400 °C for the hydrolysis reaction, IZO with an annealing temperature of 200 °C is studied. Similar to the high-temperature solvent system, it is elucidated that low-temperature sol–gel processed IZO effectively improves the performance of OPVs, increasing the power conversion efficiency from 6.80% to 7.35%. For further analyses, the current–voltage (J–V) characteristics and ideality factors (n) are examined as a function of In doping ratios, which revealed that In doping on ZnO effectively reduces trap-assisted recombination within devices. [ABSTRACT FROM AUTHOR]

Non‐small cell lung carcinoma (NSCLC), which affects the brain, is fatal and resistant to anti‐cancer therapies. Despite innate, distinct characteristics of the brain from other organs, the underlying delicate crosstalk between brain metastatic NSCLC (BM‐NSCLC) cells and brain tumor microenvironment (bTME) associated with tumor evolution remains elusive. Here, a novel 3D microfluidic tri‐culture platform is proposed for recapitulating positive feedback from BM‐NSCLC and astrocytes and brain‐specific endothelial cells, two major players in bTME. Advanced imaging and quantitative functional assessment of the 3D tri‐culture model enable real‐time live imaging of cell viability and separate analyses of genomic/molecular/secretome from each subset. Susceptibility of multiple patient‐derived BM‐NSCLCs to representative targeted agents is altered and secretion of serpin E1, interleukin‐8, and secreted phosphoprotein 1, which are associated with tumor aggressiveness and poor clinical outcome, is increased in tri‐culture. Notably, multiple signaling pathways involved in inflammatory responses, nuclear factor kappa‐light‐chain‐enhancer of activated B cells, and cancer metastasis are activated in BM‐NSCLC through interaction with two bTME cell types. This novel platform offers a tool to elucidate potential molecular targets and for effective anti‐cancer therapy targeting the crosstalk between metastatic cancer cells and adjacent components of bTME. [ABSTRACT FROM AUTHOR]

Non‐small cell lung carcinoma (NSCLC), which affects the brain, is fatal and resistant to anti‐cancer therapies. Despite innate, distinct characteristics of the brain from other organs, the underlying delicate crosstalk between brain metastatic NSCLC (BM‐NSCLC) cells and brain tumor microenvironment (bTME) associated with tumor evolution remains elusive. Here, a novel 3D microfluidic tri‐culture platform is proposed for recapitulating positive feedback from BM‐NSCLC and astrocytes and brain‐specific endothelial cells, two major players in bTME. Advanced imaging and quantitative functional assessment of the 3D tri‐culture model enable real‐time live imaging of cell viability and separate analyses of genomic/molecular/secretome from each subset. Susceptibility of multiple patient‐derived BM‐NSCLCs to representative targeted agents is altered and secretion of serpin E1, interleukin‐8, and secreted phosphoprotein 1, which are associated with tumor aggressiveness and poor clinical outcome, is increased in tri‐culture. Notably, multiple signaling pathways involved in inflammatory responses, nuclear factor kappa‐light‐chain‐enhancer of activated B cells, and cancer metastasis are activated in BM‐NSCLC through interaction with two bTME cell types. This novel platform offers a tool to elucidate potential molecular targets and for effective anti‐cancer therapy targeting the crosstalk between metastatic cancer cells and adjacent components of bTME. [ABSTRACT FROM AUTHOR]