bluuebunny/crossref_metadata_2025 huggingface dataset:
Who owns reefer vessels? Uncovering the ecosystem of transshipment in fisheries
Authors: Bengtsson Frida , Jouffray Jean-Baptiste , Nakayama Shinnosuke , Zhivkoplias Erik , Wabnitz Colette C. C. , Blasiak Robert , Selig Elizabeth R. , Österblom Henrik
Published: October 2024

A central barrier to effective governance and accountability in fisheries is the limited transparency of corporate ownership. Transshipment—the transfer of catches, fuel, parts, or crew between fishing and cargo vessels known as reefers—is often criticized for its opacity and poor governance. Better insight into the beneficial ownership of vessels involved in transshipment and their operational patterns could lead to more effective management. Our study presents a publicly accessible database of reefers’ owners, operators, and flags. We identified 569 individual reefers and found that Russian and Chinese owners control 26 and 20% of the global reefer fleet, respectively. Results also show that 65% of all reefer vessels fly the flags of Russia, Panama, or China. This high level of consolidation suggests considerable leverage for enhancing transparency and governance. Our findings highlight the potential for reforming existing transshipment practices through collaboration among owners, flag states, fishery regulators, and scientists.
Drivers of woody dominance across global drylands
Authors: Biancari Lucio , Aguiar Martín R. , Eldridge David J. , Oñatibia Gastón R. , Le Bagousse-Pinguet Yoann , Saiz Hugo , Gross Nicolas , Austin Amy T. , Ochoa Victoria , Gozalo Beatriz , Asensio Sergio , Guirado Emilio , Valencia Enrique , Berdugo Miguel , Plaza César , Martínez-Valderrama Jaime , Mendoza Betty J. , García-Gómez Miguel , Abedi Mehdi , Ahumada Rodrigo J. , Alcántara Julio M. , Amghar Fateh , Anadón José D. , Aramayo Valeria , Arredondo Tulio , Bader Maaike Y. , Bahalkeh Khadijeh , Salem Farah Ben , Blaum Niels , Boldgiv Bazartseren , Bowker Matthew , Branquinho Cristina , Bu Chongfeng , Byambatsogt Batbold , Calvo Dianela A. , Castillo Monroy Andrea P. , Castro Helena , Castro-Quezada Patricio , Chibani Roukaya , Conceição Abel A. , Currier Courtney M. , Donoso David A. , Dougill Andrew , Ejtehadi Hamid , Espinosa Carlos I. , Fajardo Alex , Farzam Mohammad , Ferrante Daniela , Fraser Lauchlan H. , Gaitán Juan J. , Gherardi Laureano A. , Gusmán-Montalván Elizabeth , Hernández-Hernández Rosa M. , Hölzel Norbert , Huber-Sannwald Elisabeth , Hughes Frederic M. , Jadán Oswaldo , Jeltsch Florian , Jentsch Anke , Ju Mengchen , Kaseke Kudzai F. , Kindermann Liana , Köbel Melanie , le Roux Peter C. , Liancourt Pierre , Linstädter Anja , Liu Jushan , Louw Michelle A. , Maggs-Kölling Gillian , Issa Oumarou Malam , Marais Eugene , Margerie Pierre , Messeder João Vitor S. , Mora Juan P. , Moreno Gerardo , Munson Seth M. , Oliva Gabriel , Pueyo Yolanda , Quiroga R. Emiliano , Reed Sasha C. , Rey Pedro J. , Rodríguez Alexandra , Rodríguez Laura B. , Rolo Víctor , Ruppert Jan C. , Sala Osvaldo , Salah Ayman , Stavi Ilan , Stephens Colton R. A. , Swemmer Anthony M. , Teixido Alberto L. , Thomas Andrew D. , Throop Heather L. , Tielbörger Katja , Travers Samantha K. , van den Brink Liesbeth , Wagner Viktoria , Wamiti Wanyoike , Wang Deli , Wang Lixin , Wolff Peter , Yahdjian Laura , Zaady Eli , Maestre Fernando T.
Published: October 2024

Increases in the abundance of woody species have been reported to affect the provisioning of ecosystem services in drylands worldwide. However, it is virtually unknown how multiple biotic and abiotic drivers, such as climate, grazing, and fire, interact to determine woody dominance across global drylands. We conducted a standardized field survey in 304 plots across 25 countries to assess how climatic features, soil properties, grazing, and fire affect woody dominance in dryland rangelands. Precipitation, temperature, and grazing were key determinants of tree and shrub dominance. The effects of grazing were determined not solely by grazing pressure but also by the dominant livestock species. Interactions between soil, climate, and grazing and differences in responses to these factors between trees and shrubs were key to understanding changes in woody dominance. Our findings suggest that projected changes in climate and grazing pressure may increase woody dominance in drylands, altering their structure and functioning.
Lipopolyplex-formulated mRNA cancer vaccine elicits strong neoantigen-specific T cell responses and antitumor activity
Authors: Fan Ting , Xu Congcong , Wu Jichuan , Cai Yihua , Cao Wanlu , Shen Haifa , Zhang Mingna , Zhu Hanfei , Yang Jingxian , Zhu Zhounan , Ma Xiaopin , Ren Jiale , Huang Lei , Li Qianyun , Tang Yuying , Yu Bo , Chen Chunxiu , Xu Mingcheng , Wang Qiuhe , Xu Zhuya , Chen Fengjia , Liang Shujing , Zhong Zhixian , Jamroze Anmbreen , Tang Dean G. , Li Hangwen , Dong Chunyan
Published: October 2024

mRNA neoantigen cancer vaccine inducing neoantigen-specific T cell responses holds great promise for cancer immunotherapy; however, its clinical translation remains challenging because of suboptimal neoantigen prediction accuracy and low delivery efficiency, which compromise the in vivo therapeutic efficacy. We present a lipopolyplex (LPP)–formulated mRNA cancer vaccine encoding tandem neoantigens as a cancer therapeutic regimen. The LPP-formulated mRNA vaccines elicited robust neoantigen-specific CD8
+
T cell responses in three syngeneic murine tumor models (CT26, MC38, and B16F10) to suppress tumor growth. Prophylactic cancer vaccine treatment completely prevented tumor development, and long-lasting memory T cells protected mice from tumor cell rechallenge. Combining the vaccine with immune checkpoint inhibitor further boosted the antitumor activity. Of note, LPP-based personalized cancer vaccine was administered in two cancer patients and induced meaningful neoantigen-specific T cell and clinical responses. In conclusion, we demonstrated that the LPP-based mRNA vaccine can elicit strong antitumor immune responses, and the results support further clinical evaluation of the therapeutic mRNA cancer vaccine.
Primitive asteroids as a major source of terrestrial volatiles
Authors: Martins Rayssa , Morton Elin M. , Kuthning Sven , Goes Saskia , Williams Helen M. , Rehkämper Mark
Published: October 2024

The origins of Earth’s volatiles are debated. Recent studies showed that meteorites display unique mass-independent isotopic signatures of the volatile element Zn, suggesting that Earth’s Zn originated from materials derived from different regions of the Solar System. However, these studies largely omitted meteorites from the differentiated planetesimals thought to represent the Earth’s building blocks, which underwent melting and substantial volatile loss. Here, we characterize the mass-independent Zn isotope compositions of meteorites from such planetesimals. We incorporate these results in mixing models that aim to reproduce Earth’s abundance and isotope compositions of Zn and other elements. Our results suggest that, while differentiated planetesimals supplied ~70% of Earth’s mass, they provided only ~10% of its Zn. The remaining Zn was supplied by primitive materials that did not experience melting and associated volatile loss. Combined with other findings, our results imply that an unmelted primitive material is likely required to establish the volatile budgets of the terrestrial planets.
Structures of the Foamy virus fusion protein reveal an unexpected link with the F protein of paramyxo- and pneumoviruses
Authors: Fernández Ignacio , Bontems François , Brun Delphine , Coquin Youna , Goverde Casper A. , Correia Bruno E. , Gessain Antoine , Buseyne Florence , Rey Felix A. , Backovic Marija
Published: October 2024

Foamy viruses (FVs) constitute a subfamily of retroviruses. Their envelope (Env) glycoprotein drives the merger of viral and cellular membranes during entry into cells. The only available structures of retroviral Envs are those from human and simian immunodeficiency viruses from the subfamily of orthoretroviruses, which are only distantly related to the FVs. We report the cryo–electron microscopy structures of the FV Env ectodomain in the pre- and post-fusion states, which unexpectedly demonstrate structural similarity with the fusion protein (F) of paramyxo- and pneumoviruses, implying an evolutionary link between the viral fusogens. We describe the structural features that are unique to the FV Env and propose a mechanistic model for its conformational change, highlighting how the interplay of its structural elements could drive membrane fusion and viral entry. The structural knowledge on the FV Env now provides a framework for functional investigations, which can benefit the design of FV Env variants with improved features for use as gene therapy vectors.
A global poleward shift of atmospheric rivers
Authors: Li Zhe , Ding Qinghua
Published: October 2024

Atmospheric rivers (ARs) are key agents in distributing extratropical precipitation and transporting moisture poleward. Climate models forced by historical anthropogenic forcing suggest an increase in AR activity in the extratropics over the past four decades. However, reanalyses indicate a ~6° to 10° poleward shift of ARs during boreal winter in both hemispheres, featuring a rise along 50°N and 50°S and a decrease along 30°N and 30°S. Our analysis demonstrates that low-frequency sea surface temperature variability in the tropical eastern Pacific exhibits a cooling tendency since 2000 that plays a key role in driving this global AR shift, mostly over extratropical oceans, through a tropical-driven eddy-mean flow feedback. This mechanism also operates on interannual timescales, controlled by the El Niño–Southern Oscillation, and is less pronounced over the Southern Ocean due to weaker eddy activity during austral summer. These highlight the sensitivity of ARs to large-scale circulation changes driven by both internal variability and external forcing in current and upcoming decades.
Self-healable and stretchable perovskite-elastomer gas-solid triboelectric nanogenerator for gesture recognition and gripper sensing
Authors: Jiang Feng , Thangavel Gurunathan , Lee Jin Pyo , Gupta Adit , Zhang Yufei , Yu Jian , Yokota Tomoyuki , Yamagishi Kento , Zhang Yihui , Someya Takao , Lee Pooi See
Published: October 2024

Gas-solid triboelectric nanogenerators (GS-TENGs) based on porous elastomers provide a promising avenue for the design of self-powered sensors. However, the intrinsic limitation of low electric output in GS-TENGs could affect the accuracy and sensitivity of sensing systems. Here, we develop a porous composite by integrating an adhesive poly(siloxane-diphenylglyoxime-urethane) (PSDU) elastomer with ferroelectric (3,3-difluorocyclobutylammonium)
2
CuCl
4
[(DF-CBA)
2
CuCl
4
] fillers. PSDU, an intrinsically triboelectric negative material with alternating hard-soft segments and supramolecular bonds, imparts excellent compressibility, adhesion, and self-healing properties to the composite. Simultaneously, the incorporation of (DF-CBA)
2
CuCl
4
as functional fillers leverages the formation of a hydrogen bonding network to enhance charge transfer processes. These fillers facilitate charge accumulation through an electric poling process, resulting in a power output improvement that surpasses 1400 times higher than that of a dense PSDU-based GS-TENG. Tapping onto the versatile properties of porous poly(siloxane-diphenylglyoxime-urethane)-perovskite (PSDU-PK) GS-TENGs, applications such as hand gesture/food recognition and dual-mode sensing system have been demonstrated, suggesting their promising potential in wearable electronics and smart agriculture.
CLIC5 promotes myoblast differentiation and skeletal muscle regeneration via the BGN-mediated canonical Wnt/β-catenin signaling pathway
Authors: Zhang Xin , He Linjuan , Wang Liqi , Wang Yubo , Yan Enfa , Wan Boyang , Zeng Qiuyu , Zhang Pengguang , Zhao Xingbo , Yin Jingdong
Published: October 2024

Myoblast differentiation plays a vital role in skeletal muscle regeneration. However, the protein-coding genes controlling this process remain incompletely understood. Here, we showed that chloride intracellular channel 5 (CLIC5) exerts a critical role in mediating myogenesis and skeletal muscle regeneration. Deletion of CLIC5 in skeletal muscle leads to reduced muscle weight and decreases the number and differentiation potential of satellite cells. In vitro, CLIC5 consistently inhibits myoblast proliferation while promoting myotube formation. CLIC5 promotes myogenic differentiation by activating the canonical Wnt/β-catenin signaling pathway in a biglycan (BGN)–dependent manner. CLIC5 deletion impairs muscle regeneration. Paired box gene 7 (Pax7) expression and the activity of BGN-mediated canonical Wnt/β-catenin signaling are reduced in CLIC5-deficient mice. Conversely, increasing CLIC5 levels in skeletal muscles enhances muscle regeneration capacity. In conclusion, our findings underscore CLIC5 as a pivotal regulator of myogenesis and skeletal muscle regeneration, functioning through interaction with BGN to activate the canonical Wnt/β-catenin signaling pathway.
Contactin-4 suppresses antitumor T cell responses by engaging amyloid precursor protein
Authors: Jeon Bu-Nam , Kim Sujeong , Kim Yunjae , Yu Hyunkyung , Park Changho , Kim Gihyeon , Ha Youngeun , Kim Gyeong-yeon , Kim Hyunuk , Palucka Karolina A. , Lee Charles , Cha Miyoung , Park Hansoo
Published: October 2024

Immune checkpoint inhibitors have substantial advanced tumor treatment, but their limited benefits and strong responses in only a subset of patients remain challenging. In this study, we explored the immunomodulatory function of contactin-4 (CNTN4). CNTN4 was highly expressed in tumor tissues, and expression impaired the antitumor function of T cells. CNTN4 bound to amyloid precursor protein (APP) on T cells, which attenuated conjugation between cancer cells and T cells, and diminished T cell receptor signaling cascades. We developed an anti-CNTN4 antibody (GENA-104A16) and an anti-APP antibody (5A7) that blocked the binding between CNTN4 and APP. Administration of either GENA-104A16 or 5A7 promoted antitumor T cell responses in a syngeneic mouse model and increased tumor-infiltrating lymphocytes in vivo. Furthermore, elevated CNTN4 levels were associated with poor prognosis and negatively correlated with various cytotoxic immune-related markers. These results suggest that CNTN4-APP is an inhibitory checkpoint in T cells and represents a promising therapeutic strategy for cancer immunotherapy.
Late Quaternary slip rate of the strike-slip faults on the eastern margin of the Qaidam Basin on the Tibetan Plateau and its implication on regional strain partitioning
Authors: Bao Guodong , Ren Zhikun , Liu Jinrui , Ha Guanghao , Ji Haomin , Wang Lei
Published: October 2024

The spatial variation in slip rates of large-scale strike-slip faults provides crucial support for the conceptual models of continental collision. However, the reasons for the decrease in slip rate of the East Kunlun Fault at the eastern margin of the Qaidam Basin on the Tibetan Plateau are still unclear. At the eastern margin of the Qaidam Basin, we identified four active strike-slip faults—two NW-SE–orientated dextral (the Xiariha Fault and Yingdeerkang Fault) and two E-W–orientated sinistral (the Reshui-Taosituohe Fault and Taosituohenan Fault)—and determined their slip rates using uncrewed aerial vehicle-based topography and optically stimulated luminescence dating. For the Xiariha Fault, from north to south slip rates are 1.39 +0.51/−0.34 mm/yr, 1.19 +0.15/−0.14 mm/yr, and 0.9 +0.19/−0.16 mm/yr. The Yingdeerkang Fault slips at 0.66 +0.08/−0.07 mm/yr. The Reshui-Taosituohe Fault, from west to east, slips at 0.95 +0.22/−0.19 mm/yr and 1.20 +0.11/−0.09 mm/yr. The Taosituohenan Fault, west to east, slips at 0.62 +0.12/−0.12 mm/yr to 1.01 +0.21/−0.19 mm/yr and 1.21 +0.43/−0.25 mm/yr. We believe that the gradual decrease in slip rate of the East Kunlun Fault at the Tuosuo Lake segment toward the east is influenced by the activity of the four active strike-slip faults with a slip rate of ~1 mm/yr along the eastern margin of the Qaidam Basin and the Elashan Fault. The decrease in fault slip rate is not solely attributed to the diverse structural styles of the fault itself but also to the strain absorption by the development of differently oriented faults around its periphery.
Poor venous outflow is associated with hyperintense acute reperfusion marker on follow-up MRI in patients with acute ischemic stroke with a large vessel occlusion
Authors: Zamarud Aroosa , Yuen Nicole , Wouters Anke , Mlynash Michael , Hugdal Stephen M , Seners Pierre , Kesten Jamie , Yedavalli Vivek , Faizy Tobias D , Albers Gregory W , Lansberg Maarten G , Heit Jeremy J
Published: October 2024

Background

Hyperintense acute reperfusion marker (HARM) refers to delayed enhancement in the subarachnoid or subpial space on post-contrast fluid attenuated inversion recovery (FLAIR) images. HARM is a measure of blood–brain barrier breakdown, which has been correlated with poor outcomes in patients with acute ischemic stroke with large vessel occlusion (AIS-LVO). We hypothesized that unfavorable venous outflow (VO) would be correlated with HARM after thrombectomy treatment of AIS-LVO.

Objective

To determine whether poor VO is associated with HARM on follow-up MRI after stroke in patients with AIS-LVO.

Methods

Patients with AIS-LVO from the prospective CRISP2 and DEFUSE2 studies with a baseline CT angiography (CTA) scan and a follow-up MRI with FLAIR sequence were screened for enrollment. VO was measured on the baseline CTA scan using the cortical venous opacification score (COVES). HARM was determined on FLAIR sequences at the follow-up MRI. The primary outcome was the occurrence of HARM between those with good VO (VO+; COVES 3–6) and bad VO (VO−; COVES 0–2).

Results

121 patients were included; 60.3% (n=73) had VO+ and 39.7% (n=48) had VO−. Patients with VO− had higher presentation National Institutes of Health Stroke Scale scores (18 (IQR 12–20) vs 12 (IQR 8–16) in VO+; P<0.001). Middle cerebral artery M1 segment occlusions were more common in VO− patients (65% vs 43% VO+; P=0.028). VO− patients also had a larger pre-treatment ischemic core (23 (4–44) mL vs 12 (3–22) mL in VO+; P=0.049) and Tmax >6 s volumes (105 (72–142) mL vs 66 (35–95) mL in VO+; P<0.001). VO− patients were more likely to develop HARM after thrombectomy (31% vs 10% in VO+; P=0.003). On multivariable regression analysis, VO− (OR=3.6 (95% CI 1.2 to 10.6); P=0.02) and the presence of any ICH (OR=3.6 (95% CI 1.2 to 10.5); P=0.02) were independently associated with the occurrence of HARM.

Conclusions

In patients with AIS-LVO, VO− correlated with HARM on post-thrombectomy MRI.
Health sciences training for disability inclusion: the need to engage with emotion
Authors: Watermeyer Brian
Published: October 2024

Material aspects of disability inequality, such as access to quality services, housing and employment, are an urgent, worldwide concern. Less recognised though, are psychological layers of prejudice and discrimination, which play a significant role in cementing marginality. Against this backdrop, health practitioners can fill influential roles in shaping the self-identity and citizenship entitlement of people with disabilities. Yet, these professionals are, like the balance of society, socialised in environments where ableism is intrinsic, invisible and unquestioned. Disability prejudice has both an emotional and unconscious basis, and overcoming its effects is argued to require a personal engagement with feelings relating to bodily frailty, universal dependency, mortality and other prickly aspects of the human condition with which it is associated. These aspects are all at play in the clinical encounter between a health professional and a patient with disability, but the layered and consequential nature of such interactions for the flourishing and empowerment of people with disabilities, as well as the disability movement as a whole, is poorly understood. Evidence suggests that mere tuition in social justice has limited effects on behaviour in relation to issues of inequality and exclusion. In this paper I reflect on how socialisation in an ableist world can shape how disability is positioned in the clinical encounter, potentially leading to interactions which embed inequality. Drawing on my own experience as disability studies scholar and disabled person, I then describe a teaching method for facilitating shifts in the personal relationships which health sciences students have to disability, in the context of broader attempts to create clinical spaces and relationships in which empathy and self-compassion are encouraged.
The changing agricultural landscape in Canada’s Mixedwood Plains Ecozone (2011–2022) and the implications for biodiversity
Authors: Fyson Vincent K. , Wilmshurst John F. , Callaghan Carolyn
Published: October 2024

The prairies and savannahs historically found in the Mixedwood Plains Ecozone have been largely converted into farmland, the dominant present-day land cover. Consequently, many species native to these grasslands have shifted to inhabiting suitable agricultural lands. More recently, agricultural intensification has led to the conversion of pastures and hay fields to annual crops, further removing habitat suitable for the persistence of grassland species. We quantified the shift from pasture and forage to annual crops as well as the dynamics among agricultural lands and other land covers in the Mixedwood Plains Ecozone, predicting biodiversity implications by providing a case study on Eastern Meadowlark ( Sturnella magna (Linnaeus, 1758)). The total agricultural land area changed little over the study period, but area of pasture and forage decreased while row crop area increased. The loss of agricultural lands to urbanization was partly offset by the conversion of forests and wetlands; however, the farmland gained was of lesser agricultural quality than the farmland lost. Declines in Eastern Meadowlark abundance correlated significantly with carrying capacity loss, suggesting that habitat availability is a limiting factor for this species. We highlight the importance of land management policies to minimize the impacts of land conversion on biodiversity and agricultural production.
More on Scarf’s Complementarity Problem and its Error Bounds
Authors: Neogy S. K. , Gupta A. , Mondal P.
Published: October 2024

In this paper, we revisit Scarf’s complementarity problem involving a rectangular matrix, known as the vertical block matrix introduced by [Cottle, RW and GB Dantzig (1970). A generalization of the linear complementarity problem. Journal of Combinatorial Theory, 8, 79–90]. We prove that the problem has a unique solution if the underlying matrix is a vertical block [Formula: see text]-matrix. Some results on the error bounds for the vertical block [Formula: see text]- and [Formula: see text]-matrices are derived. This further extends the results on global error bounds obtained by [Mathias, R and JS Pang (1990). Error bounds for the linear complementarity problem with a P-matrix. Linear Algebra and its Applications, 132, 123–136] and [Mangasarian, OL and J Ren (1994). New improved error bounds for the linear complementarity problem. Mathematical Programming, 66, 241–255].
Asian Rainbow Option Pricing Problem Based on Uncertain Fractional Differential Equations
Authors: Han Qian , Zhu Yuanguo
Published: October 2024

Option pricing is a core issue in option trading, which directly affects investors’ trading decisions and risk management. With the growing maturity of uncertainty theory, the research on option pricing problems based upon uncertainty theory has been gradually deepened. However, the volatility of stock price is not only related to the price at the current moment, but also related to all the previous stock price changes. Uncertain fractional differential equations can well portray the memory and history dependence of financial markets. Its nonlocal nature can more accurately describe the long-term memory effect and the phenomenon of spiky fat tails of stock market fluctuations. Thus, this paper mainly explores the pricing of Asian rainbow option in uncertain financial environments, where the underlying asset price is viewed as uncertain fractional processes. First, two models are presented for discussing the price of Asian rainbow option in two-asset cases, respectively. Then the pricing problems of different types of Asian rainbow options under [Formula: see text]-assets case are further discussed. Finally, empirical analysis is conducted on the proposed models with real stock data to verify the validity of the pricing formulas.
Structural regulation of CuOx/CeO2 and its application in α-tert-propylamine synthesis
Authors: Jia WenHao , Wang HaoRui , Duan ZhongYu , Liu Binyuan
Published: October 2024

Four cerium dioxide (CeO2) powders with different particle sizes and shapes were prepared via regulating the amount of alkali and hydrothermal temperature. Then twelve 20 wt.% [Formula: see text]/[Formula: see text] materials were provided by loading the corresponding quantity cupric acetate in the cerium oxide carriers by impregnation method and changing the calcination temperature and atmosphere. These loaded [Formula: see text]/[Formula: see text] catalysts were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscope-energy dispersive spectrometer (SEM-EDS) and X-ray photoelectron spectroscopy (XPS), displaying different valence state of copper on the support surface. The catalytic properties of these new materials were examined by using the coupling reaction of cyclohexanone, morpholine and phenylacetylene as a template reaction. It showed that the small-sized rod-like 20wt.% [Formula: see text]/[Formula: see text]-r-8.4-200 material has the best catalytic effect, and the isolation yield of [Formula: see text]-tert-propargylamine product could reach 75% under the conditions of 10 mg cat, 110[Formula: see text]C, 12 h and no solvent. Notably, the catalyst yield was still above 62% after four cycles of experiments, confirming the practical recoverability of the catalyst. Moreover, some examples of [Formula: see text]-tert-propargylamine derivatives can be obtained in medium isolated yields by replacing morpholine, and/or phenylacetylene. The synthesis mechanisms were discussed. The present results provide a three-component coupling reaction method for synthesizing [Formula: see text]-tert-propargylamine, which has the advantages of simple post-treatment, solvent-free and reusable catalyst.
Improving Instructional Materials with Large Language Models
Authors: Liu Bingbin , He-Yueya Joy
Published: October 2024

In this interview, Joy He-Yueya discusses her work on using GPTs to evaluate the quality of instructional materials, how GPTs compare to human evaluators, and the implications of using these models.
Effective Hard Negative Mining for Contrastive Learning-Based Code Search
Authors: Fan Ye , Li Chuanyi , Ge Jidong , Huang Liguo , Luo Bin
Published: October 2024

Background
. Code search aims to find the most relevant code snippet in a large codebase based on a given natural language query. An accurate code search engine can increase code reuse and improve programming efficiency. The focus of code search is how to represent the semantic similarity of code and query. With the development of code pre-trained models, the pattern of using numeric feature vectors (embeddings) to represent code semantics and using vector distance to represent semantic similarity has replaced traditional string matching methods. The quality of semantic representations is critical to the effectiveness of downstream tasks such as code search. Currently, the state-of-the-art (SOTA) learning method uses the contrastive learning paradigm. The objective of contrastive learning is to maximize the similarity between matching code and query (positive samples) and minimize the similarity between mismatched pairs (negative samples). To increase the reusing of negative samples, prior contrastive learning approaches use a large queue (memory bank) to store embeddings.

Problem
. However, there is still a lot of room for improvement in using negative examples for code search: ① Due to the random selection of negative samples, semantic representations learned by existing models cannot distinguish similar codes well. ② Since semantic vectors in the memory bank are reused from previous inference results and then directly used for loss function calculation without gradient descent, the model cannot effectively learn the negative sample semantic information.
Method
. To solve the above problems, we propose a contrastive learning code search model with hard negative mining called CoCoHaNeRe: ❶ To enable the model to distinguish similar codes, we introduce hard negative examples into contrastive training, which are negative examples in the codebase that are most similar to positive examples. As a result, hard negative examples are most likely to make the model make mistakes. ❷ To improve the learning efficiency of negative samples during training, we add all hard negative examples to the model's gradient descent process.
Result
. To verify the effectiveness of CoCoHaNeRe, we conducted experiments on large code search datasets with six programming languages, as well as similar retrieval tasks code clone detection and code question answering. Experimental results show that our model achieves SOTA performance. In the code search task, the average MRR score of CoCoHaNeRe exceeds CodeBERT, GraphCodeBERT, and UniXcoder by 11.25%, 8.13%, and 7.38%, respectively. It has also made great progress in code clone detection and code question answering. In addition, our method performs well in different programming languages and code pre-training models. Furthermore, qualitative analysis shows that our model effectively distinguishes high-order semantic differences between similar codes.
Seismic Vulnerability Assessment of Reinforced Concrete Educational Buildings Using Machine Learning Algorithm
Authors: Kumar Tapan , Siddique Mohammad Al Amin , Ahsan Raquib
Published: October 2024

The main objective of this paper is to assess the vulnerability of reinforced concrete (RC) educational buildings in Dhaka city to seismic activity by utilizing machine learning (ML) algorithms. There are three main stages in traditional seismic vulnerability assessment: rapid visual assessment (RVA), preliminary engineering assessment (PEA), and detailed engineering assessment (DEA). The conventional three‐step evaluation process for determining the seismic vulnerability of existing buildings is time‐consuming and expensive, especially when dealing with a large building stock or a city. This study focuses on using an ML‐based approach to evaluate seismic vulnerability, specifically in terms of the story shear ratio (SSR), which serves as the risk index. The main concept is the utilization of RVA data to obtain analytical results (SSR). The dataset utilized in this study comprises RVA data for 268 buildings and corresponding PEA data for the same 268 buildings. The RVA data include the construction year, condition, typical floor area, number of stories, total floor area, additions, alterations, redundancy, pounding, and irregularities. The PEA data comprise SSR, which was generated from linear dynamic analysis. These data were collected from the Urban Resilience Project of Rajdhani Unnayan Kartripakkha (RAJUK), which is the development authority of Dhaka. Random forest regression (RFR), support vector regression (SVR), and artificial neural networks (ANNs) are employed to determine the SSR of existing educational RC buildings. A comparative analysis for each model is also made. From the analysis results, it shows that RFR, ANN, and SVR achieved coefficient of determination (R2) of 20%, 25%, and 35%, respectively. Based on the findings from the three separate model analyses, it can be concluded that SVR produced the highest performance among the considered models.
Coupling an Autonomous UAV With a ML Framework for Sustainable Environmental Monitoring and Remote Sensing
Authors: Almalki Faris A. , Salem Shafaa M. , Fawzi Waad M. , Alfeteis Norah S. , Esaifan Shams A. , Alharthi Anoud S. , Alnefaiey Reef Z. , Naith Qamar H.
Published: October 2024

Many countries face problems in monitoring plant problems and monitoring large environments, as until now, there is no accurate means of aerial monitoring through which concerned parties can benefit from watersheds, monitor large agricultural areas, and make wise environmental decisions regarding them. This paper describes a pioneering approach to develop smart agriculture using multimission drones equipped with dual cognitive modules (brains) that are powered by a machine learning (ML) framework. The first brain uses deep reinforcement learning (DRL) principles to enable autonomous flight, allowing drones to navigate complex agricultural terrain with agility and flexibility. The second brain is responsible for precise and crucial agricultural tasks: counting trees, detecting water locations, and observing and analyzing plants using the Faster R‐CNN algorithm. The system is linked with the ground station for control and command, as well as it includes an Internet of Things (IoT) infrastructure equipped with sensors that collect soil parameters, which then get sent via 5G Wi‐Fi. The dual architecture of the drones, combined with the ground‐level IoT system, creates a comprehensive framework that not only enhances agricultural technologies but also aligns with environmental conservation goals, embodying a paradigm shift towards a greener and more sustainable future. Obtained results show reasonable results with an accuracy rate of 98%.
Stability Analysis and Simulation of Diffusive Vaccinated Models
Authors: Al-Shamiri Mohammed M. , Avinash N. , Chellamani P. , Abdallah Manal Z. M. , Antony Xavier G. Britto , Sherine V. Rexma , Abisha M.
Published: October 2024

This paper begins by analyzing the key mathematical properties of diffusive vaccinated models, including existence, uniqueness, positivity, and boundedness. Equilibria are identified, and the basic reproductive number is calculated. The Banach contraction mapping principle is applied to rigorously establish the solution existence and uniqueness. In order to understand the disease’s time transmission, it is important to examine the global stability of the equilibrium points. Disease‐free equilibrium and endemic equilibrium are the two equilibria in this model. Here, we demonstrate that the endemic equilibrium is worldwide asymptotic stable when the basic reproductive number is greater than 1, and the disease‐free equilibrium is globally asymptotic stable whenever the basic reproductive number is less than 1. Moreover, based on the Caputo fractional derivative of order and the implicit Euler’s approximation, we offered an unconditionally stable numerical solution for the resultant system. This work explores the solution of some significant population models of noninteger order using an approach known as the iterative Laplace transform. The proposed methodology is developed by effectively combining Laplace transformation with an iterative procedure. A series form solution that exhibits some convergent behavior towards the precise solution can be attained. It is noted that there is a close contact between the obtained and precise solutions. Moreover, the suggested method can handle a variety of fractional order derivative problems because it involves minimal computations. This information will be helpful in further studies to determine the ideal strategy of action for preventing or stopping the spread disease transmission.
High Li+ Conductivity of Li1.3+xAl0.3−xMgxTi1.7(PO4)3 with Hybrid Solid Electrolytes for Solid‐State Lithium Batteries
Authors: Kim Haena , Shaik Mahammad Rafi , Kim Sukju , Park Yong Min , Jeon Dong Won , Cho Sung Beom , Choi Sungho , Im Won Bin
Published: October 2024

Solid‐state electrolytes (SSEs) are promising future power sources for electronic vehicles (EVs) and devices due to their enhanced safety features, high energy density, and nonflammability. The NASICON structure has emerged as a frontrunner in oxide‐based electrolytes, boasting high Li‐ion conductivity and air stability. Nevertheless, developing high‐performance oxide‐based electrolytes remains challenging due to their inherently hard and brittle nature, presenting obstacles to achieving an optimal interface between the cathode and anode. In this study, to overcome this issue and enhance electrochemical stability and Li‐ion conductivity, a new approach employing a hybrid solid electrolyte amalgamating polymer electrolytes with inorganic Li1.3+xAl0.3−xMgxTi1.7(PO4)3 powder (x = 0, 0.015, 0.030, 0.045, and 0.060) was investigated. Notably, employing nanosized Li1.3Al0.3Ti1.7(PO4)3 (LATP) synthesized via the sol–gel method led to a remarkable increase in ionic conductivity to 7.29 × 10–4 S cm–1, which was attributed to enhanced pellet density. Electrochemical analysis revealed that Li1.345Al0.255Mg0.045Ti1.7(PO4)3 exhibited superior specific capacity, stable high current density performance, and capacity recoverability compared to LATP. This pioneering study highlights the potential of hybrid solid electrolytes incorporating Mg‐doped LATP as a promising material for practical solid‐state lithium batteries.
Two‐Stage Estimation for Ultrahigh Dimensional Sparse Quadratic Discriminant Analysis
Authors: Zhou Shengbin , Huang Yejin , Gao Xiue
Published: October 2024

The conventional Quadratic Discriminant Analysis (QDA) encounters a significant hurdle due to parameter scaling complexities on the order of O(p2), rendering it impractical for the analysis of high or ultrahigh dimensional data. This arises especially when estimating the covariance matrix or its inverse, a necessity in such scenarios. In this research, we present an innovative two‐stage QDA procedure that mitigates this obstacle by reducing the dimensionality from p to a manageable level of o(min{n, p}). This reduction allows for a direct application of QDA even when the dimensionality is growing exponentially in terms of p. We observe that, under certain sparsity assumptions, the Bayes rule can be reformulated in a low‐dimensional form. This observation motivates us to select the most relevant classification features in the first stage using feature screening methods. Subsequently, we concentrate solely on this reduced subspace to formulate classifiers in the second stage. In addition to using QDA directly in the second stage, we introduce sparse QDA, resulting in three methods for constructing classifiers in the second stage. Under appropriate sparsity assumptions, we establish the consistency and misclassification rate of our proposed procedure. Numerical simulations and real data analyses demonstrate the effectiveness of our proposed method in finite‐sample scenarios.
A Comprehensive Survey of Animal Identification: Exploring Data Sources, AI Advances, Classification Obstacles and the Role of Taxonomy
Authors: Zhang Qianqian , Ahmed Khandakar , Sharda Nalin , Wang Hua
Published: October 2024

With the rapid development of entity recognition technology, animal recognition has gradually become essential in modern society, supporting labour‐intensive agriculture and animal husbandry tasks. Severe problems such as maintaining biodiversity can also benefit from animal identification technology. However, certain invasive recognition systems have resulted in permanent harm to animals, while noninvasive identification methods also exhibit certain drawbacks. This paper conducts a systematic literature review (SLR), presenting a comprehensive overview of various animal recognition technologies and their applications. Specifically, it examines methodologies such as deep learning, image processing and acoustic analysis used for different animal characteristics and identification purposes. The contribution of machine learning to animal feature extraction is highlighted, emphasising its significance for animal taxonomy and wild species monitoring. Additionally, this review addresses the challenges and limitations of current technologies, including data scarcity, model accuracy and computational requirements, and suggests opportunities for future research to overcome these obstacles.
Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model
Authors: Bouni Mohamed , Hssina Badr , Douzi Khadija , Douzi Samira
Published: October 2024

Achieving sustainable agricultural advancements necessitates optimizing crop yields while maintaining environmental stewardship. Our research addresses this critical imperative by introducing an innovative predictive model that refines crop recommendation systems through advanced machine learning techniques, specifically random forest and SHapley Additive exPlanations (SHAP). This study aims to overcome the limitations of traditional advisory approaches by incorporating interpretability tools, clarifying the model’s decision‐making process around specific instances. To enhance the model’s local interpretability, we incorporated local interpretable model‐agnostic explanations (LIMEs), providing transparent explanations for each crop recommendation, which fosters user trust, particularly when predictions diverge from established expert opinions. We conducted our empirical investigation using a comprehensive dataset that includes various agricultural parameters, historical crop yields, and environmental conditions to evaluate the model’s performance. Our findings indicate a significant improvement in predictive accuracy over traditional methods. The application of SHAP values offers a groundbreaking analysis of feature importance, enabling a precise quantification of the contributions of factors such as soil quality, climatic variables, and historical crop performance to the predictive outcomes. This research advances the field of precision agriculture by presenting a model that excels not only in accuracy but also in providing actionable insights through enhanced interpretability. By balancing advanced predictive capabilities with user‐centric explanations, our model represents a substantial step forward in developing data‐driven, transparent, and trustworthy agricultural advisories.
Supplementary File 1 from Kidney Function and Risk of Renal Cell Carcinoma
Authors: Alcala Karine , Zahed Hana , Cortez Cardoso Penha Ricardo , Alcala Nicolas , Robbins Hilary A. , Smith-Byrne Karl , Martin Richard M. , Muller David C. , Brennan Paul , Johansson Mattias
Published: October 2024

Supplementary File 1 contains the risk score.
Functional RNAi Screening Identifies G2/M and Kinetochore Components as Modulators of TNFα/NF-κB Prosurvival Signaling in Head and Neck Squamous Cell Carcinoma
Authors: Morgan Ethan L. , Saleh Anthony D. , Cornelius Shaleeka , Carlson Sophie G. , Toni Tiffany , Cheng Hui , Jeon Jun , Viswanathan Ramya , Yang Xinping , Silvin Christopher , Clavijo Paul E. , Sowers Anastasia L. , Mitchell James B. , Ormanoglu Pinar , Lal Nag Madhu , Martin Scott E. , Chen Zhong , Van Waes Carter
Published: October 2024

Immune and radiation resistance of cancer cells to cytotoxicity mediated by TNFα is promoted by the transcription factor NF-κB in several cancers, including head and neck squamous cell carcinoma (HNSCC). Genomic alterations that converge on the TNFα/NF-κB signal axis were found in ∼40% of HNSCCs by The Cancer Genome Atlas. However, identification of therapeutic targets that contribute to aberrant TNFα/NF-κB activation and resistance has been challenging. Here, we conducted a functional RNAi screen to identify regulators of TNFα-induced NF-κB activation and cell viability, using parallel NF-κB β−lactamase reporter and cell viability assays in a HNSCC cell line which harbors expression and genomic alterations typically found in human papillomavirus–negative HNSCC. Besides multiple components of canonical TNFα/NF-κB signaling, we identified components of the WNT, NOTCH, and TGFβ pathways that we previously showed contribute to noncanonical activation of NF-κB. Unexpectedly, we also observed that multiple G2/M cell-cycle kinases [Aurora kinase A, polo-like kinase 1, WEE1, and threonine tyrosine kinase (TTK)], and structural kinetochore/microtubule components (NDC80 and NUF2), modulate TNFα-induced NF-κB activation and cell viability. Several of these targets inhibit TNF-induced nuclear translocation of RELA, consistent with prior reports linking NF-κB activation to G2/M kinases or microtubule assembly. Further investigation of an understudied mitotic kinase, TTK/monopolar spindle 1, shows that its inhibition or depletion attenuates TNFα-induced RELA nuclear translocation, promoting cell death, DNA damage, polyploidy, and mitotic catastrophe, leading to radiosensitization. Together, our RNAi screening identifies a critical linkage between the G2/M cell-cycle checkpoint/kinetochore components and NF-κB activity, as well as targets that can sensitize HNSCC cells to TNFα or radiation.

Significance:

Here, RNAi library screening reveals that multiple G2/M and kinetochore components, including TTK/monopolar spindle 1, modulate TNFα-induced NF-κB activation, cell survival, and genotoxicity, underscoring their potential importance as therapeutic targets in HNSCC.
Unusual Location of a Rare Complication of Celiac Disease
Authors: Lima Capela Tiago , Ferreira Ana Isabel , Cúrdia Gonçalves Tiago , Magalhães Joana , Rosa Bruno , Cotter José
Published: October 2024

Introduction: Celiac disease has been associated with gastrointestinal malignancies, most commonly gastrointestinal lymphoma. Nevertheless, rarer malignancies have also been reported, such as small bowel adenocarcinoma, mainly located in the duodenum or jejunum. Case Presentation: We report a case of a female patient with celiac disease with poor adherence to a gluten-free diet who presented with small bowel obstruction due to a primary ileal adenocarcinoma. The patient remains asymptomatic, adherent to the gluten-free diet, and without clinical, biochemical, or imaging evidence of cancer recurrence. Discussion/Conclusion: This case should raise awareness about the importance of the gluten-free diet and the early diagnosis and appropriate management of rare small bowel malignant complications of celiac disease, namely, adenocarcinoma.
Angiotensin Receptor-Neprilysin Inhibitor for Chronic Kidney Disease: Strategies for Renal Protection
Authors: Hishida Erika , Nagata Daisuke
Published: October 2024

Background: Chronic kidney disease (CKD) and hypertension are significant global health challenges that often coexist and aggravate each other. Renin-angiotensin system inhibitors are important to the management of these conditions; however, their efficacy for advanced CKD remains uncertain. Summary: Angiotensin receptor-neprilysin inhibitors (ARNIs) have superior efficacy for heart failure (HF) management, as evidenced by landmark trials such as the PARADIGM-HF and PARAGON-HF, thus leading to its endorsement by various guidelines. Although direct evidence supporting the renal-protective effects of ARNI is lacking, post hoc analyses have suggested its potential to mitigate the decline of the estimated glomerular filtration rate and renal events, particularly in patients with HF with a relatively preserved ejection fraction. Mechanistically, ARNI augments the glomerular filtration rate by dilating glomerular arterioles, relaxing mesangial cells, and improving renal medullary blood flow, thereby mitigating interstitial fibrosis progression. ARNI also effectively addresses nondipper hypertension, particularly in salt-sensitive individuals, thereby reducing the cardiovascular risk. Key Messages: Uncertainties regarding the efficacy and safety of ARNI for advanced renal failure (estimated glomerular filtration rate <30 mL/min) exist. Excessive hypotension associated with ARNI use may exacerbate the renal function decline, especially in older patients with comorbid HF with a reduced ejection fraction. Hence, vigilant blood pressure monitoring is essential to optimizing the renal benefits of ARNI and minimizing adverse effects. Evidence supporting the renal benefits of ARNI continues to evolve; therefore, ARNI could mitigate renal dysfunction in select patient populations. Further research should be performed to clarify the efficacy of ARNI for advanced renal failure and refine its therapeutic application for patients with concurrent HF and renal dysfunction.