bluuebunny/crossref_metadata_2025 huggingface dataset:
Improved Machined Accuracy Under a Constant Feed Speed Vector at the End-Milling Point Considering Machining Force and Machining Area in Tool Approach
Authors: Suzuki Takamaru , Hirogaki Toshiki , Aoyama Eiichi
Published: August 2024

A five-axis machining center is known for its synchronous control capability, allowing complicated three-dimensional surfaces, such as propellers and hypoid gears, to be quickly created. We aimed to maintain the feed speed vector at the end-milling point by controlling two linear axes and a rotary axis with a five-axis machining center to improve the machined surface quality. In previous research, we suggested a method to reduce the shape error of machined workpieces (referred to as the shape error herein) considering the approach path of the tool determined via calculation. However, a high machining force at the start of the workpiece cutting was observed. In this research, a theoretical method to estimate the machining force is developed by using an instantaneous cutting force model, which considers the synchronized motion of two linear axes and a rotary axis of the 5MC. Subsequently, the most suitable approach path of the tool is determined considering the prediction of machining force and the machining area in the approach path. Therefore, both a high machining force at the start of the workpiece cutting and shape error reduction can be realized by using the proposed approach path of the tool.
Agile Surface Inspection Framework for Aerospace Components Using Unsupervised Machine Learning
Authors: Nandagopal Arun , Kulkarni Abhishek , Acton Colin , Manohar Krithika , Chen Xu
Published: August 2024

Quality Control is an important step in manufacturing machined parts, especially complex, customized parts for safety critical systems such as airplane engines. Visual Inspection by humans is one of the modalities used for this purpose, but it is limited in many ways. Inspectors need months of training, need to maintain tremendous focus for a long duration, and are required to keep up with the growing pace of manufacturing. It is thus imperative to automate this process. This article proposes a flexible automated path planning framework which can be adapted to any robot, which implements a mesh segmentation algorithm and attempts to generalize the custom solution. The paper describes elements of the solution, and evaluates its efficacy pertaining to geometries of parts with characteristics similar to components found in aerospace. Furthermore, this article explores a potential improvement to the automated inspection process.
Virtual Sensing by Dense Encoder for Process Signals in Resistance Spot Welding
Authors: Kershaw Joseph , Wang Peng , Ghassemi-Armaki Hassan , Carlson Blair E.
Published: August 2024

Resistance Spot Welding (RSW) is one of the largest automated manufacturing processes in industry, consequently making it also one of the most researched. While this ubiquity has led to advancements in the consistency of this process, RSW is innately uncertain due to the high degree of interplaying mechanics that occur during the process. Additionally, to ensure the quality of a completed weld empirically, expensive analysis tools are required to inspect the result. One solution to removing this monetary and temporal cost is in-line process monitoring. During the weld, various signals can be measured and evaluated to predict the weld quality in real-time. The most common signal to measure is the Dynamic Resistance (DR) due to its ease of sensor implementation and richness of information. Other common signals are the electrode force and displacement. These give a more inclusive look into the overall process, especially the mechanical aspects, but these are typically limited to lab settings due to the increased cost of deploying them at scale. One solution to realize the insight of these other process signals on the factory floor is to utilize Machine Learning techniques to create virtual sensors that convert extant sensing data to other domains. This would allow for more robust and interpretable signal processing without incurring additional costs or downtime.
Prediction of Blind via Hole Quality Based on Stacking Ensemble Learning for Laser Drilling Condition of Printed Circuit Boards
Authors: Soma Nowatari , Masao Nakagawa , Toshiki Hirogaki , Eiichi Aoyama
Published: August 2024

In laser drilling, the appropriate laser parameters must be specified to obtain the desired machined hole. Therefore, the effects of process variables on the machined-hole parameters must be investigated and a method for constructing the optimum irradiation condition search must be devised. In this study, we establish a method to predict machined-hole parameters based on artificial intelligence (AI) using the process variables after investigating the parameter distribution of machined holes created via laser drilling. Using this method, the shape of the resulting machined hole can be determined prior to machining. Furthermore, applying the results of this study allows one to determine the irradiation conditions, which consequently enables the identification of process variables that satisfy the required hole parameters and machining quality.

First, the effects of the pulse width and pulse spacing of multiple pulses on machined-hole parameters were investigated. The parameter distribution of the machined-hole diameter was evaluated using the response-surface method by varying the pulse width of a CO2 laser. The result shows that the parameter distribution of the machined-hole diameter varied significantly under different pulse widths. Next, we propose an AI-based method for predicting machined-hole parameters using process variables on a small dataset. The proposed method reduces the prediction error of machined-hole parameters by feeding back the prediction results to the hole-opening process based on laser irradiation via stacking, which is one of the ensemble methods of AI models in the prediction model. By introducing this method, we confirmed that the prediction error was smaller compared with the case when AI was designed to perform prediction using process variables. Furthermore, the stacking was validated using a model comprising ideal data, which is not suitable for actual operation as the measured machined-hole parameters are used as input data during the validation.
Deformed Shape Prediction of Knitted Fabrics at the Stitch Level Based on Deep Learning
Authors: Wakamatsu Hidefumi , Nara Hikaru , Iwata Yoshiharu
Published: August 2024

Due to the global focus on sustainability in recent years, reducing the mass waste of clothing has become one of the important issues. A wearing simulator is thought one solution to such an issue because there is no need to stock large quantities of clothing in stores for trying on. However, conventional wearing simulators cannot accurately reproduce knitted products because prediction of their behavior at the stitch level is very time-consuming. Therefore, in this study, a method is proposed to predict the knitted fabric shape at the stitch level based on deep learning. To use deep learning, it is necessary to prepare large and diverse datasets for training. So, a procedure to efficiently generate such datasets is proposed considering the characteristics of stitches in deformed fabrics at first. Next, a shape predictor of each stitch is constructed with neural networks and learned. Then, the predictor can derive the stitch shape immediately when the boundary conditions of the stitch are given. Finally, by optimizing the boundary conditions of all stitches in a knitted fabric, the deformed shape of the fabric at the stitch level can be predicted.
Designing a Mobile Manipulator and Motion Planning for Autonomous Navigation With A* and Q-Learning Algorithms
Authors: Kaimujjaman Md. , Nishi Tatsushi , Fujiwara Tomofumi , Liu Ziang
Published: August 2024

Mobile manipulators have a crucial role in large manufacturing industries, production houses and retailer shops. Although fixed manipulator arms are very familiar in industries and production houses, a manipulator arm mounted on a movable robot equipped with the feature of autonomous navigation is still unfamiliar in this age. In this research, we propose an autonomous navigation method with A* and Q learning algorithm for a 6-DOF manipulator robot arm that is mounted on a movable 2-wheeled robot and the robot can find its path autonomously in a dynamic environment where knowledge of the environment was not known to the robot previously. The robot scans its surroundings with laser scanners and generates a map of its environment in ROS. The robot’s ability to move from its current location to a desired destination while avoiding obstacles and optimizing its trajectory depends heavily on its motion planning. For motion planning of the manipulator robot graph based and reinforcement learning based algorithms can be integrated. Incorporation of these algorithms helps the manipulator robot to find its path to a known or unknown environment. The result demonstrates the environment map generation using laser scans in RViz and applying A* and Q-Learning algorithms the robot finds its path to move from its initial state to its goal state on a generated map.
Investigation of Localization and Posture Accuracy of AMR During Indoor Mapping Using SLAM With LiDAR and Camera Technology
Authors: Omi Yasuaki , Sasa Hibiki , Matsui Tomoya , Kato Daiki , Nakagawa Masao , Hirogaki Toshiki , Aoyama Eiichi
Published: August 2024

To cope with variable types and quantities of production in factories and a wide variety of orders in distribution centers, the demand for autonomous mobile robots (AMRs), which are not restricted by guide rails, is increasing in place of automated guided vehicles (AGVs). Accurate localization is necessary to realize a highly efficient AMR transport system, and accurate posture control is necessary for cooperative operation with a manipulator on AMR. To realize this, it is important to investigate how AMR changes its localization and posture accuracy while operating, and to correct its position and posture. In this study, we tracked the actual position of an AMR using an overhead camera while the AMR was operating, and examined the accuracy of the AMR’s localization and posture sequentially when the course geometry was changed. It was found that the reflected light was weak in the areas where the incident angle of infrared rays was large, and the areas were lost on the map, which affected the accuracy of localization. A linear relationship was observed between the posture estimation error and angular velocity, and the accuracy could be improved by modifying the posture estimates using this relationship. The accuracy of posture estimation decreased when the AMR turned, which affected the accuracy of localization.
Bearing Remaining Useful Life Prediction Using Personalized Soft Aggregation in Federated Learning
Authors: Chen Xi , Wang Hui , Lu Siliang , Yan Ruqiang
Published: August 2024

Data-driven bearing prognostic methods have achieved significant success, but existing methods often rely on a single data resource, which overlooks the practical scenario in industrial settings where condition monitoring data is usually distributed across multiple locations and generated under diverse operating conditions. To address this issue, this paper proposes a bearing remaining useful life (RUL) prediction method using personalized soft aggregation in federated learning, called PSA-FL. The proposed method involves a central server and multiple clients, where each client possesses monitoring data collected under a specific working condition. Specifically, clients conduct local training of their models and upload them to the central server. The server then uses the personalized soft aggregation algorithm to create an ensemble model for each client, taking advantage of the aggregated degradation features contained in heterogeneous data scenarios. Subsequently, the ensemble model is returned to each client for further rounds of local training. By iteratively repeating the process of local training and personalized soft aggregation, each client obtains its personalized prognostic model. Experiments with bearing data show that the PSA-FL method is effective in RUL prediction tasks. Additionally, the PSA-FL method demonstrates inherent robustness by successfully limiting client drift in real-world settings.
Two new species of the mite family Parholaspididae Evans (Acari: Mesostigmata) from China
Authors: Zhang Shuo , Shen Wei Xing , Wang Yi Zhuo , Jia ChunYan , Wang Hao Ran , Xie Li Xia , Yan Yi
Published: August 2024

Two new species of mites belonging to the family Parholaspididae are described based on female specimens from China, Gamasholaspis transaduncus Zhang, Xie & Yan sp. nov. from Guangdong Province, and Neparholaspis taishanensis Zhang, Xie & Yan sp. nov. from Shandong Province. A key to world species of the genus Gamasholaspis is provided.
Grain boundaries are Brownian ratchets
Authors: Qiu Caihao , Punke Maik , Tian Yuan , Han Ying , Wang Siqi , Su Yishi , Salvalaglio Marco , Pan Xiaoqing , Srolovitz David J. , Han Jian
Published: August 2024

We demonstrate that grain boundaries (GBs) behave as Brownian ratchets, exhibiting direction-dependent mobilities and unidirectional motion under oscillatory driving forces or cyclic thermal annealing. We observed these phenomena for nearly all nonsymmetric GBs but not for symmetric ones. Our observations build on molecular dynamics and phase-field crystal simulations for a wide range of GB types and driving forces in both bicrystal and polycrystalline microstructures. We corroborate these simulation results through in situ experimental observations. We analyze these results with a Markov chain model and explore the implications of GB ratchet behavior for materials processing and microstructure tailoring.
Call of the wild
Why Animals Talk: The New Science of Animal Communication
Arik Kershenbaum
Penguin, 2024. 288 pp.
Authors: Patricelli Gail
Published: August 2024

A zoologist probes the origins of complex communication in the animal world
Deepfakes and students’ deep learning: A harmonious pair in science?
Authors: Erduran Sibel
Published: August 2024

“
Deepfakes
” refers to the use of digital technology, particularly
artificial intelligence, to fabricate media—typically videos but also images and
audio—that appear to be real. For example, a person's face can be superimposed
onto another’s body, creating a realistic image that can be difficult to
distinguish from an image of the real person. Deepfakes have the potential to create
misleading and harmful content, posing
major challenges for
science and society
. What are these challenges? What do they imply for
science education? Are there opportunities as well as challenges about deepfakes that
the scientific community can harness for a positive impact on science and education?
AAAS Pacific Division says farewell after a century
Authors: Korte Andrea
Published: August 2024

102nd annual meeting was the last as AAAS shifts to community engagement focus
In Other Journals
Authors: Jiang Di , Sofowora Iyinoluwa , Stern Peter , Ash Caroline , Ray L. Bryan , Funk Michael A. , Jin Sumin
Published: August 2024

Editors’ selections from the current scientific literature
Varieties of Involution J-Trivial Monoids with Continuum Many Subvarieties
Authors: Gao Meng , Zhang Wenting , Luo Yanfeng
Published: August 2024

In this paper, we give a sufficient condition under which an involution monoid generates a variety with continuum many subvarieties. According to this result, several involution [Formula: see text]-trivial monoids are shown to generate varieties with continuum many subvarieties. These examples include Rees quotients of free involution monoids, Lee monoids with involution, and Straubing monoids with involution.
Sugar-Sweetened Beverages and Adverse Human Health Outcomes: An Umbrella Review of Meta-Analyses of Observational Studies
Authors: Lane Melissa M. , Travica Nikolaj , Gamage Elizabeth , Marshall Skye , Trakman Gina L. , Young Claire , Teasdale Scott B. , Dissanayaka Thusharika , Dawson Samantha L. , Orr Rebecca , Jacka Felice N. , O'Neil Adrienne , Lawrence Mark , Baker Phillip , Rebholz Casey M. , Du Shutong , Marx Wolfgang
Published: August 2024

Our aim was to conduct an umbrella review of evidence from meta-analyses of observational studies investigating the link between sugar-sweetened beverage consumption and human health outcomes. Using predefined evidence classification criteria, we evaluated evidence from 47 meta-analyses encompassing 22,055,269 individuals. Overall, 79% of these analyses indicated direct associations between greater sugar-sweetened beverage consumption and higher risks of adverse health outcomes. Convincing evidence (class I) supported direct associations between sugar-sweetened beverage consumption and risks of depression, cardiovascular disease, nephrolithiasis, type 2 diabetes mellitus, and higher uric acid concentrations. Highly suggestive evidence (class II) supported associations with risks of nonalcoholic fatty liver disease and dental caries. Out of the remaining 40 meta-analyses, 29 were graded as suggestive or weak in the strength of evidence (classes III and IV), and 11 showed no evidence (class V). These findings inform and provide support for population-based and public health strategies aimed at reducing sugary drink consumption for improved health.
Spatiotemporal Characterization of Instability Indices Associated with Thunderstorms in Mexico
Authors: León-Cruz José Francisco , Caetano Ernesto , Dominguez Christian , Cortés-Ramos Jorge , Méndez-Pérez Juan M. , Jaramillo Alejandro
Published: August 2024

Thunderstorms are known to have the potential to cause damage to the population. In Mexico, these weather events can bring threats such as lightning, hail, damaging winds, and even tornadoes. Various parameters and indices have been developed for mid‐latitude regions to improve forecasting and reduce the potential damage from thunderstorms; however, they do not consider the specific conditions of tropical and subtropical environments. This research used a comprehensive set of thunderstorm reports and the proximity‐sounding approach using ERA5 reanalysis data to examine five important instability indices commonly used for thunderstorm forecasting regarding their spatial and temporal characteristics. The results reveal significant variations in the values of the instability indices during thunderstorm events associated with different atmospheric systems in both the high‐activity and low‐activity seasons. The above suggests that no single index can reliably predict thunderstorms throughout Mexico and during all seasons. Analyses provide forecasters with a more comprehensive understanding of the various atmospheric conditions under which thunderstorms develop in the country, which can lead to more accurate forecasting and better disaster risk management for these natural phenomena.
In Vivo Exposure of Deltamethrin Dysregulates the NFAT Signalling Pathway and Induces Lung Damage
Authors: Sharma Prakriti , Sethi R. S.
Published: August 2024

Deltamethrin is an insecticide used to control harmful agricultural insects that otherwise damage crops and to control vector‐borne diseases. Long‐term exposure to deltamethrin results in the inflammation of the lungs. The present study elucidates the molecular mechanism underlying the deltamethrin‐induced lung damage. The lung samples were extracted from the Swiss albino mice following the treatment of low (2.5 mg/kg) and high (5 mg/kg) doses of deltamethrin. The mRNA expression of TCR, IL‐4, and IL‐13 showed upregulation, while the expression of NFAT and FOS was downregulated following a low dose of deltamethrin. Moreover, the expression of TCR was downregulated with the exposure of a high dose of deltamethrin. Furthermore, the immunohistochemistry data confirmed the pattern of protein expression for TCR, FOS, IL‐4, and IL‐13 following a low dose of deltamethrin exposure. However, no change was seen in the TCR, NFAT, FOS, JUN, IL‐4, and IL‐13 immunopositive cells of the high‐dose treatment group. Also, ELISA results showed increased expression of IL‐13 in the BAL fluid of animals exposed to low doses of deltamethrin. Overall, the present study showed that deltamethrin exposure induces lung damage and immune dysregulation via dysregulating the NFAT signalling pathway.
Evaluation of the Microwave Absorption Properties of Solid Dehydrated and Powdered Agricultural Waste at X‐Band Frequencies
Authors: Simon Jorge , Hernandez-Gonzalez Emmanuel , Villanueva-Maldonado Juvenal , Vera-Reveles Gustavo , Alcaraz-Valencia Pablo-Armando , Castillo-Topete Victor H. , Soriano-Equigua Leonel , Maciel-Barboza Fermin Marcelo , Flores-Troncoso Jorge , Gomez-Rodriguez Jose Ricardo , Cardenas-Juarez Marco , Alvarez-Flores Jose
Published: August 2024

In this article, a comparison of the absorption properties of 7 common agricultural waste materials from the state of Colima in Mexico is performed. The study carried out at X‐band frequencies finds that the highest absorption levels were mainly from 8 to 10.5 GHz. The experiment, based on a WR‐90 waveguide with samples inserted in holders in the middle of it, shows that papaya peel and lemon peel had the highest absorption levels in the aforementioned frequency range. This study is relevant because of the vast amount of agricultural waste generated in such state of Mexico, that can be used as absorbers in the microwave regime, and not managed as garbage. In this work, the feasibility of using these eco‐friendly and nontoxic materials as microwave absorbers instead of typical commercial synthetic materials is evaluated.
Data from Evaluating the Impact of Race and Ethnicity on Health-Related Quality of Life Disparities in Patients with Esophageal Cancer: A SEER-MHOS National Database Study
Authors: Wu Trudy C. , Farrell Matthew J. , Karimi-Mostowfi Nicki , Chaballout Basil H. , Akingbemi Wisdom O. , Grogan Tristan R. , Raldow Ann C.
Published: August 2024

AbstractBackground:
It is unclear whether health-related quality of life (HRQOL) disparities exist between racial/ethnic groups in older patients with esophageal cancer, pre- and post-diagnosis.
Methods:
Using the SEER-MHOS (Surveillance, Epidemiology, and End Results and Medicare Health Outcomes Survey) national database, we included patients ages 65-years-old or greater with esophageal cancer diagnosed from 1996 to 2017. HRQOL data within 36 months before and after diagnosis were measured by the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores from the SF-36 and VR-12 instruments. Total combined score (TCS) was reflected by both PCS and MCS.
Results:
We identified 1,312 patients, with evaluable data on 873 patients pre-diagnosis and 439 post-diagnosis. On pre-diagnosis cohort MVA, the MCS was better for White over Hispanic patients (54.1 vs. 48.6, P = 0.012). On post-diagnosis cohort MVA, PCS was better for Hispanic compared with White (39.8 vs. 34.5, P = 0.036) patients, MCS was better for Asian compared with White (48.9 vs. 40.9, P = 0.034) patients, and TCS better for Asian compared with White (92.6 vs. 76.7, P = 0.003) patients.
Conclusions:
In older patients with esophageal cancer, White patients had better mental HRQOL as compared with Hispanic patients pre-diagnosis. However, post-diagnosis, White patients had worse mental and physical HRQOL compared with Asian and Hispanic patients, respectively, suggesting a greater negative impact on self-reported HRQOL in White patients with esophageal cancer.
Impact:
To our knowledge, this study is the first to explore HRQOL differences in patients with esophageal cancer of various racial and ethnic groups and warrants further validation in future studies.
Figure S8 from Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies
Authors: Zhou Huajun , Mao Binchen , Guo Sheng
Published: August 2024

Figure S8
Figure S7 from Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies
Authors: Zhou Huajun , Mao Binchen , Guo Sheng
Published: August 2024

Figure S7
Figure S3 from Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies
Authors: Zhou Huajun , Mao Binchen , Guo Sheng
Published: August 2024

Figure S3
Figure 4 from Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies
Authors: Zhou Huajun , Mao Binchen , Guo Sheng
Published: August 2024

GAM modeling of tumor growth data in mouse models. A, AIC-min model proportion in the 7.5% experimental groups that lack fit by any of the six parametric models. B, Proportion of confidence sets that contain GAM in the 7.5% experimental groups that lack fit by any of the six parametric models. C, Proportion of confidence sets that contain GAM in datasets. D, AIC-min model proportion in all datasets.
Data from Noninvasive Lung Cancer Subtype Classification Using Tumor-Derived Signatures and cfDNA Methylome
Authors: Li Shuo , Li Wenyuan , Liu Bin , Krysan Kostyantyn , Dubinett Steven M.
Published: August 2024

Abstract
Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histologic examination are the standard for determining histologic lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histologic subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy-number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.
Significance:
This study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.
Small loop bowel rupture due to feline gastrointestinal eosinophilicsclerosing fibroplasia
Authors: Souto Daniel Pedro Bonjorno Maia , Ghirelli Carolina de Oliveira
Published: August 2024

A 1-year-old male Persian presented intense prostration and sporadic emesis. Abdominal ultrasound examination revealed an intestinal mass, thick loops, and lymph node enlargement associated with abdominal free gas and fluid. In surgery, a thickened and ruptured duodenum was noted. Histopathological and immunohistochemistry examination revealed feline gastrointestinal eosinophilic sclerosing fibroplasia. This article is relevant because of the poor literature that has been published. Besides, this is the first case of spontaneous rupture of bowel loops due to necrosis secondary to feline gastrointestinal eosinophilic sclerosing fibroplasia without a foreign body in a young cat.
No Compulsion in Religion: Jawdat Saʿīd (d. 2022) and the Jihād of the Prophets
Authors: Pizzi Paola
Published: August 2024

Freedom of belief and of conscience is well attested in the Qurʾan by the many verses that exhort to tolerance towards “others”, among which Q. 2:256: ‘There is no compulsion in religion’. In contemporary Islam, some intellectuals have endeavoured to reaffirm this principle as an essential goal: among them, the Sunni Syrian thinker Jawdat Saʿīd (d. 2022). In his works, Q. 2:256 is at the core of an anthropocentric and social hermeneutics which emphasises the centrality of non-compulsion, considered as the true jihad that Muslims should undertake. His position is in open polemic with a tendency within Islamic societies not to recognise the legitimacy of those opinions – religious or political – that deviate from the “official” discourse on the one hand, and to combat this discourse with violence on the other. This entails a renegotiation of other key doctrinal concepts, the case of nasḫ, “abrogation”, being a key example.
On Andreas Malm’s How to Blow Up a Pipeline
Authors: Martin Brian , Christoyannopoulos Alexandre , Svensson Isak , Gallagher Cunningham Kathleen , Anisin Alexei , Durance Antoine , Cervera-Marzal Manuel
Published: August 2024

Andreas Malm says sabotage is needed to save the world from climate catastrophe. In this Forum, scholars of pacifism and nonviolence caution against such a course of action by pointing to several important factors at play in determining the success or otherwise of activist campaigns, including barriers to participation, organisational dynamics, loyalty shifts, the backfire effect, and the role of framing and public opinion. Ongoing research into pacifism and nonviolence presents a nuanced picture of the current strategic landscape of climate activism, revealing lessons that the climate movement must consider as it reflects on what repertoire of action to embrace to enhance its effectiveness and mitigate the unfolding climate emergency.
A new species of the extinct genus Taphioporus Moseyko & Kirejtshuk (Coleoptera: Chrysomelidae) from Baltic amber
Authors: BUKEJS ANDRIS , MOSEYKO ALEKSEY G. , ALEKSEEV VITALII I.
Published: August 2024

Altogether, 33 fossils of Chrysomelidae in species rank have been described from Baltic amber to date and assigned to nine subfamilies (e.g. Uhmann, 1939; Bukejs & Nadein, 2013, 2015; Bukejs, 2014, 2019; Biondi, 2014; Bukejs & Bezděk, 2014; Bukejs & Chamorro, 2015; Bukejs et al., 2023a; Bukejs & Schmitt, 2016; Legalov, 2016). Eumolpinae are represented by six species within three extinct and one extant genera (Moseyko & Kirejtshuk, 2013; Bukejs & Moseyko, 2015; Nadein et al., 2016; Bukejs et al., 2023b).
The first beetle species described from Oligocene New Zealand amber (Coleoptera: Scirtidae)
Authors: KAULFUSS UWE , SZAWARYN KAROL , LEE DAPHNE , RUTA RAFAŁ
Published: August 2024

Previously reported beetle inclusions from New Zealand amber have preserved insufficient morphological details for an identification beyond family-level. Here, we describe the first beetle species from New Zealand amber, Contacyphon pomahakaensis Ruta sp. nov., based on a newly discovered, well-preserved inclusion from the late Oligocene Pomahaka Formation in southern New Zealand. C. pomahakaensis Ruta sp. nov. is the first fossil record of marsh beetles (Scirtidae) described from New Zealand. The worldwide genus Contacyphon is well diversified with exclusively endemic species in New Zealand, suggesting a long presence and independent evolution in the region, which is confirmed by the new Oligocene amber fossil. A coastal swamp forest environment reconstructed for the formation of Pomahaka amber is in agreement with wet forest habitats of extant marsh beetles. Fourier transform infrared (FTIR) analysis of late Oligocene Pomahaka amber indicates that it originates from an Araucariaceae parent plant of Agathis affinity and has undergone comparatively little maturation.
Systematic position of the genus Liassophyllum (Orthoptera: Hagloidea) with description of new taxa
Authors: GOROCHOV ANDREJ V. , CORAM ROBERT A. , JARZEMBOWSKI EDMUND A. , WEBSTER ANDREW J.
Published: August 2024

The genus Liassophyllum Zeuner, 1935 is redescribed, and its uncertain systematic position is discussed and partially clarified: it may belong to an unknown subfamily of Tuphellidae or to the subfamilies Isfaropterinae or Haglinae within Haglidae. Some probable additional characters of the type species Liassophyllum abbreviatum Zeuner, 1935 from the Lower Jurassic of England are indicated. A new species is described: Liassophyllum patriciae sp. nov. from the Lower Jurassic of England. Liassophyllum caii Gu & Ren, 2012, from the Middle Jurassic of China, is transferred to a new genus: Gurenia gen. nov., which may be referred to the subfamilies Isfaropterinae or Haglinae within Haglidae.
Primary biliary cholangitis has causal effects on systemic rheumatic diseases: a Mendelian randomization study
Authors: Zhang Hai-Ping , Zhou Zhe , Chen Ke , Xiong Li-Fen , Wu Jun , Jin Lei
Published: August 2024

Background

An association has been observed between primary biliary cholangitis (PBC) and systemic rheumatic diseases (SRDs) in observational studies, however the exact causal link remains unclear. We aimed to evaluate the causal effects of PBC on SRDs through Mendelian randomization (MR) analysis.

Methods

The genome-wide association study (GWAS) summary data were obtained from MRC IEU OpenGWAS and FinnGen databases. Independent genetic variants for PBC were selected as instrumental variables. Inverse variance weighted was used as the main approach to evaluate the causal effects of PBC on Sjögren syndrome (SS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), mixed connective tissue disease (MCTD) and polymyositis (PM). Horizontal pleiotropy and heterogeneity were measured by MR‒Egger intercept test and Cochran’s Q value, respectively.

Results

PBC had causal effects on SS (OR = 1.177, P = 8.02e-09), RA (OR = 1.071, P = 9.80e-04), SLE (OR = 1.447, P = 1.04e-09), SSc (OR = 1.399, P = 2.52e-04), MCTD (OR = 1.306, P = 4.92e-14), and PM (OR = 1.416, P = 1.16e-04). Based on the MR‒Egger intercept tests, horizontal pleiotropy was absent (all P values > 0.05). The robustness of our results was further enhanced by the leave-one-out method.

Conclusions

Our research has provided new insights into PBC and SRDs, indicating casual effects on various SRDs.
Perspectives of older adults with chronic illness on person-centered practice at an inpatient hospital department: a descriptive study
Authors: Vareta Diana , Ventura Filipa , Família Carlos , Oliveira Célia
Published: August 2024

Background

The growing aging trend associated with a higher prevalence of chronic illnesses is increasing the demand for the development of person-centered practice in specific care settings. Knowing the person’s perception of the care and the care experience is essential to improving inpatient care toward person-centeredness. This study aims to characterize the perceptions of person-centered practice of hospitalized older adults with chronic illness at a Portuguese inpatient hospital department.

Methods

A quantitative, descriptive, cross-sectional approach was followed. Data were collected using a sociodemographic and health history questionnaire and the Person-Centered Practice Inventory - Care (PCPI-C). The effect of the different variables on each PCPI-C construct was determined using analysis of variance (ANOVA).

Results

The results show that person-centered practice was positively perceived in the five constructs of the person-centered processes domain (M = 3.92; SD = 0.47). The highest-scored construct was working with the person’s beliefs and values (M = 4.12; SD = 0.51), and the lowest was working holistically (M = 3.68; SD = 0.70). No significant effect of the independent variables was found to influence the perceptions of any of the constructs in the person-centered processes domain.

Conclusions

These results might indicate that person-centered processes are perceived uniquely by each person through individualized therapeutic relationships rather than a pattern of care shared by hospitalized older adults.
Evaluation of the New York City COVID-19 case investigation and contact tracing program: a cascade of care analysis
Authors: Conderino Sarah , E. Thorpe Lorna , Shilpi Islam Nadia , A. Berry Carolyn , Bendik Stefanie , Massar Rachel , Hong Chuan , Fair Andrew , Bershteyn Anna
Published: August 2024

Background

New York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country’s largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a “cascade of care” approach.

Methods

This cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the “cascade of care” was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case’s date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact.

Results

A total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and < 1 day to notify contacts.

Conclusions

T2 provided a large volume of NYC residents with timely notification and monitoring. Engagement in the program was lower for contacts than cases, with the largest gap coming from inability to reach individuals during call attempts. To strengthen future test-and-trace efforts, strategies are needed to encourage acceptance of local contact tracer outreach attempts.
B7-1 and PlGF-1 are two possible new biomarkers to identify fracture-associated trauma patients at higher risk of developing complications: a cohort study
Authors: Breinbauer Regina , Mäling Michelle , Ehnert Sabrina , Blumenstock Gunnar , Schwarz Tobias , Jazewitsch Johann , Erne Felix , Reumann Marie K. , Rollmann Mika F. , Braun Benedikt J. , Histing Tina , Nüssler Andreas K.
Published: August 2024

Background

Around 10% of fractures lead to complications. With increasing fracture incidences in recent years, this poses a serious burden on the healthcare system, with increasing costs for treatment. In the present study, we aimed to identify potential ‘new’ blood markers to predict the development of post-surgical complications in trauma patients following a fracture.

Methods

A total of 292 trauma patients with a complete three-month follow-up were included in this cohort study. Blood samples were obtained from 244 of these patients. Two complication groups were distinguished based on the Clavien-Dindo (CD) classification: CD grade I and CD grade III groups were compared to the controls (CD 0). The Mann-Whitney U test was used to compare the complication groups to the control group.

Results

Analysis of the patients’ data revealed that risk factors are dependent on sex. Both, males and females who developed a CD III complication showed elevated blood levels of B7-1 (p = 0.015 and p = 0.018, respectively) and PlGF-1 (p = 0.009 and p = 0.031, respectively), with B7-1 demonstrating greater sensitivity (B7-1: 0.706 (male) and 0.692 (female), PlGF-1: 0.647 (male) and 0.615 (female)). Further analysis of the questionnaires and medical data revealed the importance of additional risk factors. For males (CD 0: 133; CD I: 12; CD III: 18 patients) alcohol consumption was significantly increased for CD I and CD III compared to control with p = 0.009 and p = 0.007, respectively. For females (CD 0: 107; CD I: 10; CD III: 12 patients) a significantly increased average BMI [kg/m2] from 25.5 to 29.7 with CD III was observed, as well as an elevation from one to three comorbidities (p = 0.003).

Conclusions

These two potential new blood markers hold promise for predicting complication development in trauma patients. Nevertheless, further studies are necessary to evaluate the diagnostic utility of B7-1 and PlGF-1 in predicting complications in trauma patients and consider sex differences before their possible use as routine clinical screening tools.
Can minimally invasive transforaminal lumbar interbody fusion achieve a better clinical and radiological outcome than traditional open technique in isthmic spondylolisthesis?
Authors: Ali Elsayed Mohamed Selim , Eladawy Amr Mohamed , ElHewala Tarek
Published: August 2024

Background

Spondylolisthesis is a prevalent condition in the lumbar spine that can cause low back pain, leg pain, neurogenic claudication, and impact health-related quality of life in symptomatic individuals.

Aim

to assess the results of minimally invasive TLIF (MIS-TLIF) versus open-TLIF and the impact of correcting spino-pelvic parameters on the Health-Related Quality of Life (HRQoL) in patients with low-grade isthmic spondylolisthesis. The primary objective was to compare the effectiveness of both methods in correcting spinopelvic parameters. The secondary objectives involved comparing clinical improvement, operating time, blood loss, complications, and postoperative hospital stays between the two procedures.

Patients and methods

Seventy-two patients with low-grade isthmic spondylolisthesis were enrolled in this retrospective cohort-control study, with a minimum follow-up period of 18 months. Disability was assessed using the Oswestry Disability Index (ODI), while back and leg discomfort were rated using the Visual Analogue Scale (VAS) for each patient. The measurements comprised the sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), and Meyerding slip grades. We measured lumbar lordosis (LL), and segmental lordosis.

Results

The seventy-two patients were 60 female and 12 males. There was no statistically significant difference in the duration of operation between the two groups. In the MIS group, there was a notable reduction in blood loss, higher radiation exposure, and a shorter hospital stay (P < 0.001). The back VAS showed more favorable outcomes in the MIS-TLIF, while the leg VAS showed better results in the Open-TLIF in the early outcome. Both procedures significantly reduced leg and back pain VAS scores and ODI, with no notable difference between the two groups at the final follow-up. Post-surgery, the pelvic incidence (PI) and lumbar lordosis (LL) matched properly in all patients, showing a rise in LL and sacral slope along with a decrease in pelvic tilt.

Conclusion

Both open-TLIF and MIS-TLIF are effective methods for correcting spino-pelvic parameters and improving HRQoL in patients with low-grade isthmic spondylolisthesis. The rapid improvement in back pain experienced by these patients favored the use of MIS-TLIF. However, the cost-effectiveness of this approach must be carefully evaluated.
Evaluating the generalizability of graph neural networks for predicting collision cross section
Authors: Engler Hart Chloe , Preto António José , Chanana Shaurya , Healey David , Kind Tobias , Domingo-Fernández Daniel
Published: August 2024

Ion Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the molecular size and shape. However, the effective application of CCS values in structural analysis is still constrained by the limited availability of experimental data, necessitating the development of accurate machine learning (ML) models for in silico predictions. In this study, we evaluated state-of-the-art Graph Neural Networks (GNNs), trained to predict CCS values using the largest publicly available dataset to date. Although our results confirm the high accuracy of these models within chemical spaces similar to their training environments, their performance significantly declines when applied to structurally novel regions. This discrepancy raises concerns about the reliability of in silico CCS predictions and underscores the need for releasing further publicly available CCS datasets. To mitigate this, we introduce Mol2CCS which demonstrates how generalization can be partially improved by extending models to account for additional features such as molecular fingerprints, descriptors, and the molecule types. Lastly, we also show how confidence models can support by enhancing the reliability of the CCS estimates.

Scientific contribution

We have benchmarked state-of-the-art graph neural networks for predicting collision cross section. Our work highlights the accuracy of these models when trained and predicted in similar chemical spaces, but also how their accuracy drops when evaluated in structurally novel regions. Lastly, we conclude by presenting potential approaches to mitigate this issue.