bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemical cannibalistic cues make damselfly larvae hide rather than hunt
Authors: Sysiak Monika , Pietrzak Barbara , Kubiak Matylda , Bednarska Anna , Mikulski Andrzej 
Published: August 2023

AbstractAdopting cannibalism substantially affects individual fitness, and recognizing the presence of other cannibals provides additional benefits such as the opportunity to prepare for hunting or defense. This recognition can be facilitated by perceiving conspecific chemical cues. Their role in cannibalistic interactions is less studied than in interspecific predation and it is unclear whether these cues inform individuals of danger or of food availability. Interpretation of these cues is crucial to balance the costs and benefits of anti-predator and feeding strategies, which can directly influence individual fitness. In this study we aimed to test whether damselfly larvae shift towards bolder and more exploratory (cannibalistic) behavior, or become more careful to avoid potential cannibals (as prey) in response to such cues. We conducted behavioral and respiratory experiments with Ischnura elegans larvae to investigate their response to chemical cues from older and larger conspecific larvae. We found that I. elegans larvae decrease their activity and shift their respiratory-related behavior, indicating activation of anti-predator defense mechanisms in response to conspecific chemical cues. Our findings indicate that individuals exposed to conspecific chemical cues balance catching prey with staying safe.
Methylglyoxal improves zirconium stress tolerance in Raphanus sativus seedling shoots by restricting zirconium uptake, reducing oxidative damage, and upregulating glyoxalase I
Authors: Bless Yoneal , Ndlovu Linda , Gcanga Esihle , Niekerk Lee-Ann , Nkomo Mbukeni , Bakare Olalekan , Mulaudzi Takalani , Klein Ashwil , Gokul Arun , Keyster Marshall 
Published: August 2023

AbstractRaphanus sativus also known as radish is a member of the Brassicaceae family which is mainly cultivated for human and animal consumption. R. sativus growth and development is negatively affected by heavy metal stress. The metal zirconium (Zr) have toxic effects on plants and tolerance to the metal could be regulated by known signaling molecules such as methylglyoxal (MG). Therefore, in this study we investigated whether the application of the signaling molecule MG could improve the Zr tolerance of R. sativus at the seedling stage. We measured the following: seed germination, dry weight, cotyledon abscission (%), cell viability, chlorophyll content, malondialdehyde (MDA) content, conjugated diene (CD) content, hydrogen peroxide (H2O2) content, superoxide (O2•−) content, MG content, hydroxyl radical (·OH) concentration, ascorbate peroxidase (APX) activity, superoxide dismutase (SOD) activity, glyoxalase I (Gly I) activity, Zr content and translocation factor. Under Zr stress, exogenous MG increased the seed germination percentage, shoot dry weight, cotyledon abscission, cell viability and chlorophyll content. Exogenous MG also led to a decrease in MDA, CD, H2O2, O2•−, MG and ·OH, under Zr stress in the shoots. Furthermore, MG application led to an increase in the enzymatic activities of APX, SOD and Gly I as well as in the complete blocking of cotyledon abscission under Zr stress. MG treatment decreased the uptake of Zr in the roots and shoots. Zr treatment decreased the translocation factor of the Zr from roots to shoots and MG treatment decreased the translocation factor of Zr even more significantly compared to the Zr only treatment. Our results indicate that MG treatment can improve R. sativus seedling growth under Zr stress through the activation of antioxidant enzymes and Gly I through reactive oxygen species and MG signaling, inhibiting cotyledon abscission through H2O2 signaling and immobilizing Zr translocation.
Perineural invasion detection in pancreatic ductal adenocarcinoma using artificial intelligence
Authors: Borsekofsky Sarah , Tsuriel Shlomo , Hagege Rami R. , Hershkovitz Dov 
Published: August 2023

AbstractPerineural invasion (PNI) refers to the presence of cancer cells around or within nerves, raising the risk of residual tumor. Linked to worse prognosis in pancreatic ductal adenocarcinoma (PDAC), PNI is also being explored as a therapeutic target. The purpose of this work was to build a PNI detection algorithm to enhance accuracy and efficiency in identifying PNI in PDAC specimens. Training used 260 manually segmented nerve and tumor HD images from 6 scanned PDAC cases; Analytical performance analysis used 168 additional images; clinical analysis used 59 PDAC cases. The algorithm pinpointed key areas of tumor-nerve proximity for pathologist confirmation. Analytical performance reached sensitivity of 88% and 54%, and specificity of 78% and 85% for the detection of nerve and tumor, respectively. Incorporating tumor-nerve distance in clinical evaluation raised PNI detection from 52 to 81% of all cases. Interestingly, pathologist analysis required an average of only 24 s per case. This time-efficient tool accurately identifies PNI in PDAC, even with a small training cohort, by imitating pathologist thought processes.
A person-based approach to emotion socialization in toddlerhood: Individual differences in maternal emotion regulation, mental-health and parental sense of competence
Authors: Arikan Gizem , Kumru Asiye 
Published: August 2023

AbstractMothers adopt various emotion socialization strategies and sometimes exhibit contradictory responses. Thus, it is essential to understand how mothers differentiate in their use of emotion socialization strategies, and whether a set of emotion socialization responses is associated with individual differences in emotion regulation, mental health, and parental sense of competence during toddlerhood. Therefore, we used a person-centred approach to identify mothers’ emotion socialization responses and then compared mothers based on the aforementioned characteristics. The mothers (N = 680) with toddlers (M = 23.56 months) responded to the Coping with Toddlers’ Negative Emotions Scale, the Emotion Regulation Questionnaire, the Brief Symptom Inventory, and the Parental Sense of Competence Scale. The 3-profile-solution revealed: Unspecified (moderate scores in all emotion socialization strategies), supportive (high scores in supportive emotion socialization strategies) and mixture profiles (high in all emotion socialization strategies). The supportive and mixture profiles scored highly in cognitive reappraisal. Unspecified and mixture profiles did not vary in expressive suppression and mental health symptoms, but they scored lower than supportive profile mothers. In the parental sense of competence, the supportive profile scored higher than the mixture profile. The results showed mothers mainly using supportive emotion socialization strategies can demonstrate adequate emotion regulation and benefit from psychological well-being that potentially boosts parenting competence.
Effective DC acceleration of charged particles in a circular ring and its potential application
Authors: Takayama Ken 
Published: August 2023

AbstractA novel scheme is proposed for realizing effective DC acceleration of charged particles in a circular ring. The key is to use an induction acceleration cell with multi-insulating gaps that allow forced short circuit using solid-state switching devices such as SiC-MOSFET or unforced short circuit using diodes. A baseline design of the induction acceleration cell is shown. A coasting beam is accelerated in the circular ring without bunching. As its possible application, a continuous-wave terahertz free-electron laser (FEL) is proposed with numerical parameters, where this effective DC acceleration compensates for energy loss of the electron beam occupying the entire isochronous storage ring due to synchrotron radiation and FEL interaction. As a result, FEL microbunching of a coasting beam can be created, resulting in a high average output power that has not been possible with existing linac-driven FELs or RF storage-ring FELs.
Comparative analysis of salicylic acid levels and gene expression in resistant, tolerant, and susceptible cassava varieties following whitefly-mediated SLCMV infection
Authors: Malichan Srihunsa , Vannatim Nattachai , Chaowongdee Somruthai , Pongpamorn Pornkanok , Paemanee Atchara , Siriwan Wanwisa 
Published: August 2023

AbstractSri Lankan cassava mosaic virus (SLCMV), the primary pathogen responsible for cassava mosaic disease in cassava plantations, is transmitted via infected cutting stems and the whitefly vector, Bemisia tabaci. To obtain better insights into the defense mechanism of cassava against SLCMV, whiteflies were used to induce SLCMV infection for activating the salicylic acid (SA) signaling pathway, which triggers the innate immune system. The study aimed to investigate the specific interactions between viruliferous whiteflies and SA accumulation in resistant (C33), tolerant (Kasetsart 50; KU50), and susceptible (Rayong 11) cassava cultivars by infecting with SLCMV. Leaf samples were collected at various time points, from 1 to 7 days after inoculation (dai). The SA levels were quantified by gas chromatography–mass spectrometry and validated by quantitative reverse transcription polymerase chain reaction. The SA levels increased in KU50 and C33 plants at 2 and 3 dai, respectively, but remained undetected in Rayong11 plants. The expression of PR-9e, PR-7f5, SPS1, SYP121, Hsf8, and HSP90 increased in infected C33 plants at 4 dai, whereas that of KU50 plants decreased immediately at 2 dai, and that of Rayong11 plants increased at 1 dai but gradually decreased thereafter. These findings strongly indicate that SA plays a crucial role in regulating antiviral defense mechanisms, especially in SLCMV-resistant plants. Altogether, the findings provide valuable insights into the mechanisms underlying the activation of SA-mediated anti-SLCMV defense pathways, and the resistance, tolerance, and susceptibility of cassava, which can aid future breeding programs aimed at enhancing SLCMV resistance.
Off-stoichiometry and molybdenum substitution effects on elastic moduli of B1-type titanium carbide
Authors: Ida Shuntaro , Hoshizaki Kotaro , Kaneko Takahiro , Nan Xi , Sekido Nobuaki , Yoshimi Kyosuke 
Published: August 2023

AbstractB1-type MX ceramics are composed of transition metals (M) and C, N, and/or O (X) occupying the M and X sites, respectively, and having M–X nearest neighbor (NN) bonds and M–M and X–X next nearest neighbor (NNN) bonds. Substitution of the elements and the formation of structural vacancies in B1-type ceramics change the numbers and strengths of the bonds, leading to novel properties. The change in elastic modulus of off-stoichiometric TiC in equilibrium with a Ti–Mo solid solution phase was experimentally investigated based on the rule of mixtures from the Voigt model. The experimentally obtained values agreed well with the results of density functional theory calculations. The bulk modulus (K) of TiC increased from 205.6 to 239.2 GPa as the fraction of Ti sites occupied by Mo increased from 0.11 to 0.33, whereas the Young’s modulus (E) and the shear modulus (G) remained nearly constant. On the other hand, all three elastic moduli decreased with increasing vacancy fraction at the C sites. These results suggest that the M–X bond strength should be the dominant factor in these moduli and the effect of M–M bond on K is greater than that of G and E.
Magnetic properties of intercalated quasi-2D Fe3-xGeTe2 van der Waals magnet
Authors: Iturriaga Hector , Martinez Luis M. , Mai Thuc T. , Biacchi Adam J. , Augustin Mathias , Hight Walker Angela R. , Sanad Mohamed Fathi , Sreenivasan Sreeprasad T. , Liu Yu , Santos Elton J. G. , Petrovic Cedomir , Singamaneni Srinivasa R. 
Published: August 2023

AbstractAmong several well-known transition metal-based compounds, cleavable van der Waals (vdW) Fe3-xGeTe2 (FGT) magnet is a strong candidate for use in two-dimensional (2D) magnetic devices due to its strong perpendicular magnetic anisotropy, sizeable Curie temperature (TC ~154 K), and versatile magnetic character that is retained in the low-dimensional limit. While the TC remains far too low for practical applications, there has been a successful push toward improving it via external driving forces such as pressure, irradiation, and doping. Here we present experimental evidence of a room temperature (RT) ferromagnetic phase induced by the electrochemical intercalation of common tetrabutylammonium cations (TBA+) into quasi-2D FGT. We obtained Curie temperatures as high as 350 K with chemical and physical stability of the intercalated compound. The temperature-dependent Raman measurements, in combination with vdW-corrected ab initio calculations, suggest that charge transfer (electron doping) upon intercalation could lead to the observation of RT ferromagnetism. This work demonstrates that molecular intercalation is a viable route in realizing high-temperature vdW magnets in an inexpensive and reliable manner, and has the potential to be extended to bilayer and few-layer vdW magnets.
Deep learning based phenotyping of medical images improves power for gene discovery of complex disease
Authors: Flynn Brianna I. , Javan Emily M. , Lin Eugenia , Trutner Zoe , Koenig Karl , Anighoro Kenoma O. , Kun Eucharist , Gupta Alaukik , Singh Tarjinder , Jayakumar Prakash , Narasimhan Vagheesh M. 
Published: August 2023

AbstractElectronic health records are often incomplete, reducing the power of genetic association studies. For some diseases, such as knee osteoarthritis where the routine course of diagnosis involves an X-ray, image-based phenotyping offers an alternate and unbiased way to ascertain disease cases. We investigated this by training a deep-learning model to ascertain knee osteoarthritis cases from knee DXA scans that achieved clinician-level performance. Using our model, we identified 1931 (178%) more cases than currently diagnosed in the health record. Individuals diagnosed as cases by our model had higher rates of self-reported knee pain, for longer durations and with increased severity compared to control individuals. We trained another deep-learning model to measure the knee joint space width, a quantitative phenotype linked to knee osteoarthritis severity. In performing genetic association analysis, we found that use of a quantitative measure improved the number of genome-wide significant loci we discovered by an order of magnitude compared with our binary model of cases and controls despite the two phenotypes being highly genetically correlated. In addition we discovered associations between our quantitative measure of knee osteoarthritis and increased risk of adult fractures- a leading cause of injury-related death in older individuals-, illustrating the capability of image-based phenotyping to reveal epidemiological associations not captured in the electronic health record. For diseases with radiographic diagnosis, our results demonstrate the potential for using deep learning to phenotype at biobank scale, improving power for both genetic and epidemiological association analysis.
Tin perovskite transistors and complementary circuits based on A-site cation engineering
Authors: Zhu Huihui , Yang Wonryeol , Reo Youjin , Zheng Guanhaojie , Bai Sai , Liu Ao , Noh Yong-Young 
Published: August 2023

Abstract
Tin halide perovskites have the general chemical formula ASnX3, where A is a monovalent cation and X is a monovalent halide anion. These semiconducting materials can be used to fabricate p-type transistors at low cost and temperature and could be potentially integrated with n-type oxide-based transistors to create complementary circuits. However, the materials suffer from low crystallization controllability and high film defect density, resulting in uncompetitive device performance. Here we show that pure-tin perovskite thin-film transistors can be created using triple A cations of caesium–formamidinium–phenethylammonium. The approach leads to high-quality cascaded tin perovskite channel films with low-defect, phase-pure perovskite/dielectric interfaces. The optimized thin-film transistors exhibit hole mobilities of over 70 cm2 V−1 s−1 and on/off current ratios of over 108, which are comparable with commercial low-temperature polysilicon transistors. The transistors are fabricated using solution-processing methods at temperatures no higher than 100 °C. We also integrate the devices with n-type metal oxide transistors to create complementary inverters with voltage gains of 370, and NOR and NAND logic gates with rail-to-rail switching performance.
Glutarate regulates T cell metabolism and anti-tumour immunity
Authors: Minogue Eleanor , Cunha Pedro P. , Wadsworth Brennan J. , Grice Guinevere L. , Sah-Teli Shiv K. , Hughes Rob , Bargiela David , Quaranta Alessandro , Zurita Javier , Antrobus Robin , Velica Pedro , Barbieri Laura , Wheelock Craig E. , Koivunen Peppi , Nathan James A. , Foskolou Iosifina P. , Johnson Randall S. 
Published: August 2023

AbstractT cell function and fate can be influenced by several metabolites: in some cases, acting through enzymatic inhibition of α-ketoglutarate-dependent dioxygenases, in others, through post-translational modification of lysines in important targets. We show here that glutarate, a product of amino acid catabolism, has the capacity to do both, and has potent effects on T cell function and differentiation. We found that glutarate exerts those effects both through α-ketoglutarate-dependent dioxygenase inhibition, and through direct regulation of T cell metabolism via glutarylation of the pyruvate dehydrogenase E2 subunit. Administration of diethyl glutarate, a cell-permeable form of glutarate, alters CD8+ T cell differentiation and increases cytotoxicity against target cells. In vivo administration of the compound is correlated with increased levels of both peripheral and intratumoural cytotoxic CD8+ T cells. These results demonstrate that glutarate is an important regulator of T cell metabolism and differentiation with a potential role in the improvement of T cell immunotherapy.
Identifying important sensory feedback for learning locomotion skills
Authors: Yu Wanming , Yang Chuanyu , McGreavy Christopher , Triantafyllidis Eleftherios , Bellegarda Guillaume , Shafiee Milad , Ijspeert Auke Jan , Li Zhibin 
Published: August 2023

AbstractRobot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state–action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neural networks, human insights and engineering efforts are often required to select appropriate states through qualitative approaches, such as ablation studies, without a quantitative analysis of the state importance. Here we present a systematic saliency analysis that quantitatively evaluates the relative importance of different feedback states for motor skills learned through deep reinforcement learning. Our approach provides a guideline to identify the most essential feedback states for robot motor learning. By using only the important states including joint positions, gravity vector and base linear and angular velocities, we demonstrate that a simulated quadruped robot can learn various robust locomotion skills. We find that locomotion skills learned only with important states can achieve task performance comparable to the performance of those with more states. This work provides quantitative insights into the impacts of state observations on specific types of motor skills, enabling the learning of a wide range of motor skills with minimal sensing dependencies.
The reactivity of dissolved and suspended particulate phosphorus pools decreases with distance downstream in the Yellow River
Authors: Hu Nana , Sheng Yanqing , Li Changyu , Li Zhaoran , Liu Qunqun 
Published: August 2023

AbstractThe Yellow River is a potentially important source of terrestrially derived phosphorus to the phosphorus limited Bohai Sea. However, seasonal variation in concentrations, partitioning and bioavailability of dissolved and particulate phosphorus along the length of the Yellow River are poorly constrained. Here, we measure dissolved and suspended particulate phosphorus at 72 stations from the source to the estuary of the Yellow River during the rainy season in 2020 and dry season in 2021. Mean concentrations of total phosphorus, total dissolved phosphorus and dissolved reactive phosphorus were higher in the rainy season than the dry season. Analysis with sequential fractionation indicated that generally phosphorus associated with calcium carbonate dominated the suspended particulate pool. However, phosphorus content and the relative contribution of iron-bound phosphorus in suspended particles increased during the dry season, suggesting seasonal variations in bioavailability. Reactivity of the phosphorus pools decreased from source to estuary, suggesting low export potential of bioavailable phosphorus to the Bohai Sea.
Equilibrium unconstrained low-temperature CO2 conversion on doped gallium oxides by chemical looping
Authors: Kang Keke , Kakihara Sota , Higo Takuma , Sampei Hiroshi , Saegusa Koki , Sekine Yasushi 
Published: August 2023

It was found that reverse water gas shift (RWGS) can be proceeded at a high conversion rate by using a chemical loop method via the redox of NiGa2Ox.
Bismuth-based two-dimensional nanomaterials for cancer diagnosis and treatment
Authors: Hong Chengyuan , Chen Tianxiang , Wu Manxiang , Lin Jie , Gao Changyong , Ma Xuehua , Liu Zhusheng , Yang Xiaogang , Wu Aiguo 
Published: August 2023

We summarize the recent progress including controllable synthesis, defect engineering, surface modifications, applications, and prospects of Bi-based two-dimensional nanomaterials for cancer diagnosis and treatment.
An improved cascade RCNN detection method for key components and defects of transmission lines
Authors: Dong Chao , Zhang Ke , Xie Zhiyuan , Shi Chaojun 
Published: August 2023

AbstractOverhead transmission line detection based on deep learning of aerial images taken by UAVs has been widely investigated. Despite its success, it is limited by several factors, including inappropriate evaluation criteria and dramatic scaling of components in the images. To mitigate these issues, a relative mean Average Precision evaluation index is proposed to accurately measure the model's detection performance for smaller objects. A data enhancement strategy including multi‐scale transformation is adopted to alleviate the problem of drastic scaling. The existing Cascade RCNN target detection technology is enhanced by incorporating Swin‐v2 and a balanced feature pyramid to improve feature characterization capabilities, while side‐aware boundary localization is utilized to improve the positioning accuracy of the model. Experimental results demonstrate that the proposed method outperforms state‐of‐the‐art methods on CPLID and achieves 7.8%, 11.8%, and 5.5% higher detection accuracy than the baseline for mAP50, relative small and medium mAP, respectively. Additionally, the paper discusses the influence of adopted data enhancement on the robustness of the model.