bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating seedbank stimulants for wild oat and volunteer cereal management on the Canadian Prairies
Authors: Sharpe Shaun M. , Kaye Taylor , Tidemann Breanne D.
Published: June 2023

Wild oat is a widespread threat to annual crop production on the Canadian Prairies. Infestations are difficult to manage due to a persistent seedbank, complex dormancy, a long emergence window, herbicide resistance, and seed shatter corresponding to crop harvest timings. The study objective was to evaluate the efficacy of potassium nitrate (KNO3) and pyroligneous acid for promoting germination and emergence of wild oat and volunteer wheat, barley, and oat. A total of 24 repeated experiments were conducted using freshly produced seeds to ensure adequate endodormancy. Wheat and barley demonstrated no endodormancy following seed formation and rapidly emerged with moisture. All species imbibed but did not germinate in Petri dishes within pyroligneous acid solutions of 5%–100%. Dormancy release was observed within 0.1% and 1% pyroligneous acid solutions. KNO3 did not stimulate germination or emergence for any species and was inhibitory at 125 kg N ha−1. Pyroligneous acid increased wild oat emergence with 50% and 100% solutions applied at 200 L ha−1 in the first study and with 10% solutions in the second study. Emergence inhibition was noted for oat, barley, and wheat with pyroligneous acid applications. This research further confirms that pyroligneous acid may stimulate wild oat emergence and confirms activity on freshly matured seed.
Accessing compton form factors at the electron ion collider in China: an impact study on $${\textbf {Im}} {\mathcal E}$$
Authors: Cao Xu , Zhang Jinlong
Published: June 2023

We estimate the impact of asymmetry measurements of Deeply Virtual Compton Scattering (DVCS) with transversely polarized proton beam taken at a future Electron Ion Collider in China (EicC) on the extraction of Compton Form Factors (CFFs). The CFFs extracted from an analysis based on artificial neural-network approach are reweighted by means of pseudo-data generated in the expected kinematic region of EicC. We find a remarkable improvement in the extraction of CFF $$Im {\mathcal E}$$

I
m
E

, especially at the range of parton momentum fraction $$x \sim $$

x
∼

0.01, thus hinting for a future experimental probe of the parton orbital angular momentum. This work casts a glance at a practical implementation of Bayesian reweighting method on CFFs’ impact study.
Imprints of Casimir wormhole in Einstein Gauss–Bonnet gravity with non-vanishing complexity factor
Authors: Zubair M. , Farooq Mushayydha
Published: June 2023

This article investigates Casimir wormhole solutions in Einstein Gauss–Bonnet (EGB) gravity. We are familiar that Null energy conditions (NEC) need not be satisfied for a stable wormhole due to the existence of exotic matter. As the Casimir effect acts as a negative energy source, it can be treated as a classical applicant for the exotic matter to discuss the stable dynamics of the wormhole. This work explores the Casimir effects with the Generalized Uncertainty Principle (GUP) on wormhole geometry in EGB gravity by confining our results for $$D=5$$

D
=
5

. We have examined two GUP procedures, e.g., Kempf, Mangano, Mann (KMM) and Dentournay, Gabriel, and Spindel (DGS). We have developed shape functions for Casimir wormholes, and GUP corrected Casimir wormholes and studied their existence. In addition, we investigate the behavior of the Gauss–Bonnet (GB) Coupled parameter and minimal uncertainty (MU) parameter on the Equation of state (EOS) parameter. The active gravitational mass and embedding diagrams for all developed shape functions are analysed. Moreover, the violation of the NEC by an exotic matter, the equilibrium forces, and the complexity factor of Casimir wormholes and GUP-corrected Casimir wormholes have also been explored.
Properties of Fredholm, Weyl and Jeribi essential S-spectra in a right quaternionic Hilbert space
Authors: Dharmarha Preeti , Kumari Sarita
Published: June 2023

The paper aims to extend the concept of Fredholm, Weyl and Jeribi essential spectra in the quaternionic setting. Furthermore, some properties and stability of the corresponding spectra of Fredholm and Weyl operators have been investigated in this setting. To achieve the goal, a characterization of the sum of two invariant bounded linear operators has been obtained in order to explore various properties of the Fredholm operator and Weyl operator under some assumptions in quaternionic setting. Also, various sequential properties of the pseudo-resolvent operator, right quaternionic linear operator, Weyl operator, Weyl S-spectrum, Jeribi essential S-spectrum and some properties of [Formula: see text] block operator matrices have been discussed. The spectral mapping theorem of essential S-spectrum, Weyl S-spectrum and Jeribi essential S-spectrum for self-adjoint operators has been established. A characterization of the essential S-spectrum and Weyl S-spectrum of the sum of two bounded linear operators concludes this investigation.
Impact of magnetic field on nanofluid thermophysical treatment within enclosure
Authors: Shafee Ahmad
Published: June 2023

Numerical technique for examining the transport of nanofluid within the porous container has been applied. The tank has one curved hot wall which is located in the center of the outer cylinder. The single-phase approach to deriving properties of nanofluid was applied and Darcy law has been implemented to involve the porous term in the equation. The format of the equation has been converted to stream function format to remove the pressure terms and final equations were solved via CVFEM. The written code was verified according to the previous data of the published work. Outputs showed that loading alumina causes Nu to augment by 26.71% when Ha is zero and it can be increased about 41.22% when Ha = 15. Applying a magnetic field can reduce the Nu around 37.93% when [Formula: see text]. With increase of strength of rotating cell with the rise of Ra, Nu increases by about 38.22%. Changing the shape of alumina can increase the Nu by about 11.73% when [Formula: see text] and [Formula: see text].
Unsteady MHD flow of a fractional second grade fluid in a channel passing through a porous medium subject to a time-dependent motion of the bottom plate
Authors: Ullah Ikram , Ul Haq Sami , Khan Zar Ali
Published: June 2023

The velocity of an unsteady flow of a viscous fluid of the second-grade MHD-type enclosed between two parallel side walls perpendicular to a plate was obtained by applying the integral transformation. The fluid is required to move by the plate, which over time [Formula: see text] subjected the fluid to shear stress. The solutions satisfy the given equation as well as the boundary and initial conditions, and they were separated into two types: steady state and transient state. Furthermore, through [Formula: see text], we are able to recover the results found in the literature for motion across an infinite plate. Graphs depict the effect of the side walls and the time it takes to reach the steady state. The solutions are shown in graphs and discussed physically to examine the impact of different flow parameters. It is found that the fluid velocity decreases with an increasing fractional parameter [Formula: see text] and second-grade parameter [Formula: see text]. Also, it is noticed that the fluid velocity decreases with increasing values of Reynolds number and effective permeability. Numerous industrial products, including honey, paints, varnishes, coffee, chocolate and jelly, use this type of fluid flow concept.
MACS-W: A modified optical clearing agent for imaging 3D cell cultures
Authors: Zhong Xiang , Gao Chao , Li Hui , He Yuening , Fei Peng , Chen Zaozao , Gu Zhongze , Zhu Dan , Yu Tingting
Published: June 2023

Three-dimensional (3D) cell cultures have contributed to a variety of biological research fields by filling the gap between monolayers and animal models. The modern optical sectioning microscopic methods make it possible to probe the complexity of 3D cell cultures but are limited by the inherent opaqueness. While tissue optical clearing methods have emerged as powerful tools for investigating whole-mount tissues in 3D, they often have limitations, such as being too harsh for fragile 3D cell cultures, requiring complex handling protocols, or inducing tissue deformation with shrinkage or expansion. To address this issue, we proposed a modified optical clearing method for 3D cell cultures, called MACS-W, which is simple, highly efficient, and morphology-preserving. In our evaluation of MACS-W, we found that it exhibits excellent clearing capability in just 10[Formula: see text]min, with minimal deformation, and helps drug evaluation on tumor spheroids. In summary, MACS-W is a fast, minimally-deformative and fluorescence compatible clearing method that has the potential to be widely used in the studies of 3D cell cultures.
BIGQA: Declarative Big Data Quality Assessment
Authors: Fadlallah Hadi , Kilany Rima , Dhayne Houssein , El Haddad Rami , Haque Rafiqul , Taher Yehia , Jaber Ali
Published: June 2023

In the big data domain, data quality assessment operations are often complex and must be implementable in a distributed and timely manner. This article tries to generalize the quality assessment operations by providing a new ISO-based declarative data quality assessment framework (BIGQA). BIGQA is a flexible solution that supports data quality assessment in different domains and contexts. It facilitates the planning and execution of big data quality assessment operations for data domain experts and data management specialists at any phase in the data life cycle. This work implements BIGQA to demonstrate its ability to produce customized data quality reports while running efficiently on parallel or distributed computing frameworks. BIGQA generates data quality assessment plans using straightforward operators designed to handle big data and guarantee a high degree of parallelism when executed. Moreover, it allows incremental data quality assessment to avoid reading the whole dataset each time the quality assessment operation is required. The result was validated using radiation wireless sensor data and Stack Overflow users’ data to show that it can be implemented within different contexts. The experiments show a 71% performance improvement over a 1 GB flat file on a single processing machine compared with a non-parallel application and a 75% performance improvement over a 25 GB flat file within a distributed environment compared to a non-distributed application.
Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
Authors: Martin R. John , Oak Rajvardhan , Soni Mukesh , Mahalakshmi V. , Soomar Arsalan Muhammad , Joshi Anjali
Published: June 2023

As mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes multi-source heterogeneous data including ratings, marks, scores, images, and videos, has gained importance. This information is very important for improving the calibre of customized services. The key to the application's success is representational learning of fusing and vectorization on the multi-source heterogeneous UGC. Multi-source text fusion and representation learning have become the key to its application. In this regard, a fusion representation learning for multi-source text and image is proposed. The convolutional fusion technique, in contrast to splicing and fusion, may take into consideration the varied data characteristics in each size. This research proposes a new data feature fusion strategy based on the convolution operation, which was inspired by the convolutional neural network. Using Doc2vec and LDA model, the vectorized representation of multi-source text is given, and the deep convolutional network is used to obtain it. Finally, the proposed algorithm is applied to Amazon's commodity dataset containing UGC content based on the classification accuracy of UGC vectorized representation items and shows the feasibility and impact of the proposed algorithm.
Invariant Node Representation Learning under Distribution Shifts with Multiple Latent Environments
Authors: Li Haoyang , Zhang Ziwei , Wang Xin , Zhu Wenwu
Published: June 2023

Node representation learning methods, such as graph neural networks, show promising results when testing and training graph data come from the same distribution. However, the existing approaches fail to generalize under distribution shifts when the nodes reside in multiple latent environments. How to learn invariant node representations to handle distribution shifts with multiple latent environments remains unexplored. In this article, we propose a novel
I
nvariant
N
ode representation
L
earning (INL) approach capable of generating invariant node representations based on the invariant patterns under distribution shifts with multiple latent environments by leveraging the invariance principle. Specifically, we define invariant and variant patterns as ego-subgraphs of each node and identify the invariant ego-subgraphs through jointly accounting for node features and graph structures. To infer the latent environments of nodes, we propose a contrastive modularity-based graph clustering method based on the variant patterns. We further propose an invariant learning module to learn node representations that can generalize to distribution shifts. We theoretically show that our proposed method can achieve guaranteed performance under distribution shifts. Extensive experiments on both synthetic and real-world node classification benchmarks demonstrate that our method greatly outperforms state-of-the-art baselines under distribution shifts.
Building an Open Representation for Biological Protocols
Authors: Bartley Bryan , Beal Jacob , Rogers Miles , Bryce Daniel , Goldman Robert P. , Keller Benjamin , Lee Peter , Biggers Vanessa , Nowak Joshua , Weston Mark
Published: June 2023

Laboratory protocols are critical to biological research and development, yet difficult to communicate and reproduce across projects, investigators, and organizations. While many attempts have been made to address this challenge, there is currently no available protocol representation that is unambiguous enough for precise interpretation and automation, yet simultaneously “human friendly” and abstract enough to enable reuse and adaptation. The Laboratory Open Protocol language (LabOP) is a free and open protocol representation aiming to address this gap, building on a foundation of UML, Autoprotocol, Aquarium, SBOL RDF, and the Provenance Ontology. LabOP provides a linked-data representation both for protocols and for records of their execution and the resulting data, as well as a framework for exporting from LabOP for execution by either humans or laboratory automation. LabOP is currently implemented in the form of an RDF knowledge representation, specification document, and Python library, and supports execution as manual “paper protocols,” by Autoprotocol or by Opentrons. From this initial implementation, LabOP is being further developed as an open community effort.
DeepPatch: Maintaining Deep Learning Model Programs to Retain Standard Accuracy with Substantial Robustness Improvement
Authors: Wei Zhengyuan , Wang Haipeng , Ashraf Imran , Chan Wing-Kwong
Published: June 2023

Maintaining a deep learning (DL) model by making the model substantially more robust through retraining with plenty of adversarial examples of non-trivial perturbation strength often reduces the model’s standard accuracy. Many existing model repair or maintenance techniques sacrifice standard accuracy to produce a large gain in robustness or vice versa. This article proposes DeepPatch, a novel technique to maintain filter-intensive DL models. To the best of our knowledge, DeepPatch is the first work to address the challenge of standard accuracy retention while substantially improving the robustness of DL models with plenty of adversarial examples of non-trivial and diverse perturbation strengths. Rather than following the conventional wisdom to generalize all the components of a DL model over the union set of clean and adversarial samples, DeepPatch formulates a novel division of labor method to adaptively activate a subset of its inserted processing units to process individual samples. Its produced model can generate the original or replacement feature maps in each forward pass of the patched model, making the patched model carry an intrinsic property of behaving like the model under maintenance on demand. The overall experimental results show that DeepPatch successfully retains the standard accuracy of all pretrained models while improving the robustness accuracy substantially. However, the models produced by the peer techniques suffer from either large standard accuracy loss or small robustness improvement compared with the models under maintenance, rendering them unsuitable in general to replace the latter.
A Systematic Review of Stemmers of Indian and Non-Indian Vernacular Languages
Authors: Dave Nakul R. , Mehta Mayuri A. , Kotecha Ketan
Published: June 2023

The stemming process is crucial and significant in the pre-processing step of natural language processing. The stemmer oversees the stemming process. It facilitates the extraction of morphological variants of a root or base word from the provided word. Over the period, several stemmers for various vernacular languages have been proposed. However, very few research studies have comprehensively investigated these available stemmers. This article makes multifold contributions. First, we discuss the various stemmers of 15 Indian and 17 non-Indian languages describing their key points, benefits, and drawbacks. All the Indian languages for which stemmers have been built are covered in this study. For the non-Indian languages, stemmers of commonly spoken languages have been covered. Second, we present a language-wise comparative analysis of stemmers based on our identified parameters. Third, we discuss the wordnets and dictionaries available for different languages. Fourth, we provide details of the datasets available for various languages. Fifth, we also provide challenges in existing stemmers and future directions for future researchers. The study presented in this article reveals that significant research has been carried out for the stemmers of influential languages such as English, Arabic, and Urdu. On the other hand, languages with d resources, such as Farsi, Polish, Odia, Amharic, and others, have received the least attention for research. Moreover, rigorous analysis reveals that most of the stemmers suffer from over-stemming errors. With a complete catalogue of available stemmers, this study aims at assisting the researchers and professionals working in the areas such as information retrieval, semantic annotation, word meaning disambiguation, and ontology learning.
The Book Review Column
Authors: Tran Nicholas
Published: June 2023

Three new releases in data science, cryptography, and automata await expert opinions, as well as a recent ACM Book series title on approximation of Nash equilibrium. Dear readers, these books are not going to review themselves; please consider sharing your perspectives with the community.
Technical Report Column
Authors: Kelley Dean
Published: June 2023

Welcome to the Technical Reports Column. If your institution publishes technical reports that you'd like to have included here, please contact me at the email address above.
Sensors for Coastal and Ocean Monitoring
Authors: Briciu-Burghina Ciprian , Power Sean , Delgado Adrian , Regan Fiona
Published: June 2023

In situ water monitoring sensors are critical to gain an understanding of ocean biochemistry and ecosystem health. They enable the collection of high-frequency data and capture ecosystem spatial and temporal changes, which in turn facilitate long-term global predictions. They are used as decision support tools in emergency situations and for risk mitigation, pollution source tracking, and regulatory monitoring. Advanced sensing platforms exist to support various monitoring needs together with state-of-the-art power and communication capabilities. To be fit-for-purpose, sensors must withstand the challenging marine environment and provide data at an acceptable cost. Significant technological advancements have catalyzed the development of new and improved sensors for coastal and oceanographic applications. Sensors are becoming smaller, smarter, more cost-effective, and increasingly specialized and diversified. This article, therefore, provides a review of the state-of-the art oceanographic and coastal sensors. Progress in sensor development is discussed in terms of performance and the key strategies used for achieving robustness, marine rating, cost reduction, and antifouling protection.
Nanoparticles for Interrogation of Cell Signaling
Authors: Lee Seonik , Jiao Mengchi , Zhang Zihan , Yu Yan
Published: June 2023

Cell functions rely on signal transduction—the cascades of molecular interactions and biochemical reactions that relay extracellular signals to the cell interior. Dissecting principles governing the signal transduction process is critical for the fundamental understanding of cell physiology and the development of biomedical interventions. The complexity of cell signaling is, however, beyond what is accessible by conventional biochemistry assays. Thanks to their unique physical and chemical properties, nanoparticles (NPs) have been increasingly used for the quantitative measurement and manipulation of cell signaling. Even though research in this area is still in its infancy, it has the potential to yield new, paradigm-shifting knowledge of cell biology and lead to biomedical innovations. To highlight this importance, we summarize in this review studies that pioneered the development and application of NPs for cell signaling, from quantitative measurements of signaling molecules to spatiotemporal manipulation of cell signal transduction.
Multi-Objective Optimization of the Gas Diffusion Layer and Parallel Flow Channel Dimensions for High-Power Proton Exchange Membrane Fuel Cell Operations
Authors: Ghasemi Masoomeh , Choi Jaeyoo , Ghoreishian Seyed Majid , Huh Yun Suk , Ju Hyunchul
Published: June 2023

Currently, energy crisis is believed to be one of the most important issues in developing and developed countries owing to increasing urbanization and industrialization. Proton exchange membrane (PEM) fuel cell is a high-efficiency energy conversion device that can replace fossil fuel energy systems. This study performed a multi-objective optimization to maximize the cell performance and minimize the pressure drop by optimizing four key design parameters (gas diffusion layer thickness, channel depth, channel width, and land width). To this end, the responses of the cell voltage and pressure drop of a PEM fuel cell model under different designs were investigated. First, the interactive effect of the design parameters on the cell voltage and pressure drop was investigated, and the results revealed that a simultaneous decrease in the land width and channel depth can have a beneficial effect on the cell voltage, whereas a simultaneous increase in the channel depth and channel width improves the pressure drop. Second, second-order polynomial equations were derived to predict the cell voltage and pressure drop using the four design parameters. Lastly, the comparison of the obtained optimal design and a reference cell design demonstrated the superior cell performance of the former with a lower pressure drop.
In-Plane Ordering of Li-Intercalated Turbostratic Graphite for the Negative Electrode of High-Power Long-Life Li-Ion Batteries
Authors: Fujimoto Hiroyuki , Shimoda Keiji , Murakami Miwa , Kiuchi Hisao , Takagi Shigeharu , Kano Gentaro , Kawasaki Mitsuo , Ogumi Zempachi , Abe Takeshi
Published: June 2023

Turbostratic carbon graphitized at ca. 2000 °C exhibits low discharge capacity but excellent pulse charge/discharge characteristics and long cycle performance. In this study, to clarify the charge/discharge mechanism, the intercalation process of Li into turbostratic graphite was investigated by operando synchrotron X-ray diffraction and 7Li-NMR spectroscopy. The dataset obtained from both methods was synchronously analyzed by treating it as a function of the LiC
x
composition estimated from the charge/discharge curves. It was found that both the synchrotron X-ray diffraction profile and 7Li-NMR spectrum dynamically changed in conjunction with the composition and the LiC9-type and LiC6-type in-plane structures formed in turbostratic graphite, as in the case of natural graphite when Li ions intercalate. The domain formed by these in-plane structures was a short-range ordered structure that changed depending on the misorientation angle between the two adjacent graphene sheets, and a stage structure with a periodic distance in the c-axis direction did not form, as in the case of natural graphite.
Metastable Phase Formation in Electrodeposited Co-Rich Co-Cu and Co-Ni Alloys
Authors: El-Tahawy M. , Péter L. , Gubicza J. , Molnár G. , Li C. , Vitos L. , Bakonyi I.
Published: June 2023

In a previous work [El-Tahawy et al., J. Magn. Magn. Mater.
560, 169660 (2022)], we reported that from a sulfate type bath, hcp-Co can be electrodeposited at high pH and low current density and investigated the structure and magnetoresistance (MR) characteristics of such hcp-Co electrodeposits. Based on this earlier work, Co-rich Co-Cu and Co-Ni alloy electrodeposits were prepared under the same conditions by adding varying amounts of CuSO4 and NiSO4, respectively, to the CoSO4 bath. According to the results of detailed structural studies by various X-ray diffraction (XRD) geometries, in both the Co-Cu and Co-Ni systems an hcp phase formed exclusively up to about 2 at% of the alloying element. Above this concentration, a significant fcc phase fraction appeared in Co-Cu and a minor fcc fraction in Co-Ni up to about 8 at%. This means that the destabilization effect of Cu on hcp-Co is higher than that of Ni. Although the reduction of the stability of hcp-Co with increasing Cu and Ni content is a well-known phenomenon, a quantitative comparison of this effect in Co-Cu and Co-Ni alloys is missing from the literature. The measured lattice constants are analyzed in comparison with Vegard’s law for the Co-Cu and Co-Ni element pairs deduced from data previously reported for the hcp and fcc phases of all three pure elements. For Co-rich Co-Ni alloys, the concentration dependence of the lattice parameters was found to follow Vegard’s law for both the hcp and fcc phases due to the miscibility of the two components. For the Co-rich Co-Cu alloys, the data indicate a positive deviation from Vegard’s law for both the hcp and fcc phases in agreement with the known similar behavior of fcc Co-Cu alloys for the whole composition range. The positive deviation from Vegard’s law in the Co-Cu system is due to the excess mixing volume required for solid solution alloy formation of these immiscible elements in either phases. The MR data are discussed in the light of the observed phases and of the MR parameters reported in our previous work on the hcp and fcc phases of pure Co.
Role of Photoelectrochemical Oxidation in Enabling High-Efficiency Polishing of Gallium Nitride
Authors: Kayao Kiyoto , Toh Daisetsu , Yamauchi Kazuto , Sano Yasuhisa
Published: June 2023

Photoelectrochemical (PEC) oxidation is currently employed to improve the removal rates of surface polishing methods applied to gallium nitride (GaN) wafers, such as PEC mechanical polishing (PECMP) and PEC catalyst-referred etching (PEC-CARE). The use of PEC along with these methods has successfully achieved removal rates as high as 720 nm h−1 while still ensuring the highly ordered step-and-terrace structures generated by the same methods when PEC-oxidation is not employed. However, the atomic-scale phenomena induced by PEC oxidation to assist the polishing process of GaN surfaces remain unclear. To address such a question, this study investigates the role of PEC oxidation during CARE as an example. The results demonstrate that PEC oxidation selectively occurs at the step edge and advances through the GaN (0001) surface laterally rather than in the depth direction, thus enabling high-speed polishing and resulting in a highly ordered surface, both crystallographically and geometrically.
Cortical facilitation of somatosensory inputs using gravity-related tactile information in humans with vestibular hypofunction
Authors: Fabre Marie , Beullier Laura , Sutter Chloé , Kebritchi Amirreza , Chavet Pascale , Simoneau Martin , Toupet Michel , Blouin Jean , Mouchnino Laurence
Published: June 2023

Somatosensory cortex excitability is greater in participants with bilateral vestibular hypofunction than in age-matched healthy humans. To control balance, healthy humans “locked” the head whereas participants with vestibular hypofunction “locked” their pelvis. For participants with vestibular hypofunction, increasing loading/unloading of the feet enhances the internal representation of body state in the posterior parietal cortex.
Efficient Sensor Location for HVAC Systems Using Lagrangian Coherent Structures
Authors: Ahmed Dildar , Javed Ali , Uz Zaman M. Sami , Mahsud Minhas , Hanifatu Mumuni-Napari
Published: June 2023

Study of thermo‐fluid flow has its significance in energy analysis of a building. Various thermo‐fluid analyses are performed in heating ventilation and air conditioning (HVAC) systems for energy efficient buildings by scientists and engineers to save energy consumption during the life of a building. In order to achieve energy conservation for different HVAC systems, determination of air flow pattern and flow physics are vital parameters. In case of fluid flow postprocessing techniques such as streamlines, vector plots and contours are often employed. These techniques help in understanding the nature of flow and its properties. Each of these postprocessing techniques mentioned are based on Eulerian methods and have certain inherent deficiencies pertaining to the amount of information they can convey about certain aspects of fluid flow. Lagrangian coherent structures (LCS) on the other hand use Lagrangian data for analysis purposes. LCS are generated using finite time Lyapunov exponent fields which in turn depict the rate of expansion or contraction of the trajectories around a certain point. LCS act as the transport barriers across which there is approximately zero mass flux. This property means that LCS can be applied to problems related to separation and reattachment in fluid flow and find virtual boundaries inside flows. In the current study, we focused on the application of LCS for efficient placement of sensors for HVAC systems. We computed LCS using velocity data extracted from the CFD simulations of a 2D room model. Thus, LCS can be used to identify the virtual boundaries in fluid flow. This helps in indication of regions where mixing of particles occurs and also where particles are stagnated. Inlet angles of 0, 15, 22, and 30 degrees are used and analysis shows that manifolds with 30 degree angles provide better ventilation. The outcome of this study can be used to improve the energy efficiency as well as predict the accurate location of HVAC sensor and control units.
Outcomes and Associated Factors of Induction of Labor in East Gojjam Zone, Northwest Ethiopia: A Multicenter Cross-Sectional Study
Authors: Assemie Moges Agazhe , Mihiret Getachew Tilaye , Mekonnen Chernet , Petrucka Pammla , Getaneh Temesgen , Ashebir Wassachew
Published: June 2023

Background. Induction of labor is the initiation of uterine contractions by artificial methods once the fetus has reached viability and prior to spontaneous onset of labor with the aim of achieving vaginal delivery. Although induction of labor is a critical life-saving intervention that potentially reduces adverse pregnancy outcomes, sometimes it has undesirable consequences for the health of the mother and/or the fetus. Hence, this study aimed to evaluate the outcomes and associated factors of labor induction. Methods. An institution-based cross-sectional study was conducted from February 25 to May 25, 2020, among women undergoing induction at East Gojjam zone public hospitals in northwest Ethiopia. A structured interviewer-administered questionnaire was used to collect data from a sample of 411 mothers who were selected using a systematic random sampling technique. Stata/se™ Version 14 statistical software was used to analyze the data. Multivariable binary logistic regression was used to determine the potential factors affecting successful labor induction. Adjusted odds ratios with their 95% CI intervals were used to declare the strength of the association, and a variable with

p

value <0.05 was considered to have statistical significance. Results. The prevalence of successful induction of labor was 70.3% (65.6, 74.7). The favorable Bishop score ((CI 3.90, 1.63–9.29);

p

value = 0.002), the intermediate Bishop score ((CI 3.53, 2.15–5.82);

p

value = 0.001), labor induction using oxytocin with cervical ripening ((CI 2.60, 1.21–5.63);

p

value = 0.015), and urban residence ((CI 0.48, 0.30–0.78);

p

value = 0.003) were associated with successful induction of labor. Conclusion. These findings strongly suggest that cervical conditions are important determinants for the success of labor induction. Therefore, healthcare providers should confirm the favorability of the cervical status (using Bishop score) as a strict prerequisite before actual labor induction, and special consideration should be given to those pregnant women who reside in urban areas.
Micropore Throat Structure and Movable Fluid Characteristics of Chang 63 Tight Sandstone in Baibao Area of Ordos Basin
Authors: Liu Bobiao , Tan Chengqian , Huai Yinchao , Wang Nan , Zhang Han , Feng Zhao
Published: June 2023

Tight sand is an important unconventional reservoir. Aiming at the problem of large unused reserves and the poor development effect of Chang 63 reservoir, this paper researches reunderstanding reservoir and evaluating unused reserves. Employing rock slice and scanning electron microscope (SEM), the experiment of low-field nuclear magnetic resonance (NMR), water-oil relative permeability experiment, reservoir space, movable fluid, and oil-water seepage characteristics was studied. The factors affecting NMR

T

2

cutoff, controlling factors of movable fluids, and controlling factors of displacing efficiency in tight sandstone reservoirs are discussed. The study demonstrates that (1) the mean pore volume and permeability are 4.4% and 0.068 mD, respectively. The reservoir pertains to tight sandstone, mainly intergranular pore and dissolution pore, and the intercalated materials are mainly chlorite and illite. (2) The characteristic of the NMR

T

2

spectrum has bimodal characteristics and can be subdivided into two classes: left peak dominant and right peak dominant. The mean value of mobile fluid saturation was 17.9%. (3) According to the relative permeability curve pattern, it is divided into four categories, and the mean bound water saturation is 29.9%. The average irreducible oil saturation was 40.6%. The mean oil flooding efficiency was 40.2%. (4) The better the pore-throat relationship, the lower the

T

2

cutoff, the stronger ability of the fluid migration ability, and the higher of a percentage of active fluid. The percentage of active fluid in a low-permeability reservoir is affected by the reservoir’s physical property and pore structure.
Robust Approach for Global Stabilization of a Class of Underactuated Mechanical Systems in Presence of Uncertainties
Authors: Shah Ibrahim , Abbasi Waseem , Alhussein Musaed , Khan Imran , Ur Rehman Fazal , Anwar Muhammad Shahid , Aurangzeb Khursheed
Published: June 2023

Underactuated mechanical systems offer complex dynamic behavior and poses control challenges, especially in the presence of uncertainties in the system. To cope with such systems, control mechanisms are required, which needs to be robust. In this research, an algorithm based on sliding mode control (SMC) is presented. The algorithm design offer a methodical way to handle underactuation, while the robustness properties of SMC suppresses the effect of norm bounded uncertainties and external disturbances. To proceed with the design, an underactuated system is converted into cascaded subsystems, a linear one and reduced-order nonlinear subsystem. The proposed SMC design is backed by rigorous mathematical presentation and based on Lyapunov theory, so that the global stabilization of overall system is ensured. Numerical simulations are performed, on the laboratory test bench underactuated systems (Inertial Wheel, Furuta Pendulum, TORA, and an Overhead Crane), to validate the efficacy of the proposed design. In addition, a novel sliding surface is presented for Inertial Wheel and Furuta Pendulum to achieve swingup control and global stabilization subjected to uncertainties.
Heat Transfer Analysis and Structural Optimization for Spiral Channel Regenerative Cooling Thrust Chamber
Authors: Lv Junjie , Du Guanquan , Jin Ping , Li Ruizhi
Published: June 2023

There is currently a lack of efficient heat transfer analysis methodologies for spiral channel regenerative cooling that has been increasingly applied in liquid rocket engines. To figure out the heat transfer characteristics of the spiral channel regenerative cooling thrust chamber, a simple 1D method based on the traditional semi-empirical formula after correcting the flow velocity is proposed. The accuracy of this approach is verified by the 3D numerical simulation. The verified method is further used to analyze the distribution of inner wall temperature in the test case and optimize the channel’s parameters. The research shows that the maximum inner wall temperature cooled by the spiral channel is 8.5% lower than that of the straight channel under the same channel size and boundary condition, indicating that the application of the spiral channel significantly improves the cooling effect. In addition, the 1D model combined with the second-order response surface model is employed to optimize the channel width, channel height, pitch, and inner wall thickness aiming for the best cooling effect. The calculated maximum temperature of the inner wall after the structure optimization is 586.6 K, which is 29.8% lower than the initial structure before optimization.
The Heart Block Hat-Trick: A Case of Alternating First-, Second-, and Third-Degree Heart Blocks
Authors: Huerta Nicholas , Malik Salman , Haas Christopher
Published: June 2023

Idiopathic third-degree atrioventricular (AV) block in a relatively young patient is an uncommon phenomenon. Even more rare is when the third-degree heart block is alternating with the first- and second-degree AV blocks. In this case, we present a 39-year-old man with varying degrees of AV block, alternating the third-degree, second-degree, and first-degree AV blocks. The patient underwent an extensive workup for underlying etiologies, and results were inconclusive. A pacemaker was implanted and set for physiologic pacing via left bundle branch area pacing (LBBAP). This case will discuss potential genetic abnormalities associated with AV block and highlight LBBAP as an emerging technique for physiologic pacing.
Data from Absence of either Ripk3 or Mlkl reduces incidence of hepatocellular carcinoma independent of liver fibrosis
Authors: Mohammed Sabira , Thadathil Nidheesh , Ohene-Marfo Phoebe , Tran Albert L. , Van Der Veldt Michael , Georgescu Constantin , Oh Sangphil , Nicklas Evan H. , Wang Dawei , Haritha Nair Hariprasad , Luo Wenyi , Janknecht Ralf , Miller Benjamin F. , Wren Jonathan D. , Freeman Willard M. , Deepa Sathyaseelan S.
Published: June 2023

Abstract
Nonalcoholic fatty liver disease (NAFLD) is one of the etiologies that contribute to hepatocellular carcinoma (HCC), and chronic inflammation is one of the proposed mediators of HCC. Since necroptosis is a cell death pathway that induces inflammation, we tested whether necroptosis-induced inflammation contributes to the progression of NAFLD to HCC in a mouse model of diet-induced HCC. Male and female wild-type (WT) mice and mouse models where necroptosis is blocked (Ripk3-/- or Mlkl-/- mice) were fed either a control diet or choline-deficient low-fat diet (CD-LFD) or CD-high fat diet (CD-HFD). Blocking necroptosis reduced markers of inflammation [proinflammatory cytokines (TNF, IL-6, and IL-1), F4/80+ve macrophages, CCR2+ve infiltrating monocytes], inflammation associated oncogenic pathways (JNK, PD-L1/PD-1, -catenin), and HCC in male mice. We demonstrate that hepatic necroptosis promotes recruitment and activation of liver macrophages leading to chronic inflammation, which in turn trigger oncogenic pathways leading to the progression of NAFLD to HCC in male mice. Whereas in female mice, blocking necroptosis reduced HCC independent of inflammation. Our data show a sex-specific difference in the development of inflammation, fibrosis and HCC in WT mice. However, blocking necroptosis reduced HCC in both males and females without altering liver fibrosis. Thus, our study suggests that necroptosis is a valid therapeutic target for NAFLD-mediated HCC.
Implications: Necroptosis is a major contributor to hepatic inflammation that drives the progression of NAFLD to HCC and therefore represents a valid target for NAFLD-mediated HCC.
Data from Fibronectin contributes to a BRAF inhibitor-driven invasive phenotype in thyroid cancer through EGR1, which can be blocked by inhibition of ERK1/2.
Authors: Hicks Hannah M. , Pozdeyev Nikita , Sams Sharon B. , Pugazhenthi Umarani , Bales Elise S. , Hofmann Marie-Claude , McKenna Logan R. , Schweppe Rebecca E.
Published: June 2023

Abstract
Mutations in BRAF are common in advanced papillary and anaplastic thyroid cancer (PTC and ATC). However, BRAF-mutant PTC patients currently lack therapies targeting this pathway. Despite the approved combination of BRAF and MEK1/2 inhibition for patients with BRAF-mutant ATC, these patients often progress. Thus, we screened a panel of BRAF-mutant thyroid cancer cell lines to identify new therapeutic strategies. We showed that thyroid cancer cells resistant to BRAF inhibition (BRAFi) exhibit an increase in invasion and a pro-invasive secretome in response to BRAFi. Using Reverse Phase Protein Array (RPPA), we identified a nearly 2-fold increase in expression of the extracellular matrix protein, fibronectin, in response to BRAFi treatment, and a corresponding 1.8 to 3.0-fold increase in fibronectin secretion. Accordingly, the addition of exogenous fibronectin phenocopied the BRAFi-induced increase in invasion while depletion of fibronectin in resistant cells resulted in loss of increased invasion. We further showed that BRAFi-induced invasion can be blocked by inhibition of ERK1/2. In a BRAFi-resistant patient-derived xenograft model, we found that dual inhibition of BRAF and ERK1/2 slowed tumor growth and decreased circulating fibronectin. Using RNA-sequencing, we identified EGR1 as a top downregulated gene in response to combined BRAF/ERK1/2 inhibition, and we further showed that EGR1 is necessary for a BRAFi-induced increase in invasion and for induction of fibronectin in response to BRAFi.
Implications: Together, these data show that increased invasion represents a new mechanism of resistance to BRAF inhibition in thyroid cancer that can be targeted with an ERK1/2 inhibitor.
Data from Associations between physical activity and incidence of cancer among overweight adults in Korea: Results from the Health Examinees-G study
Authors: Choi Jaesung , Park JooYong , Kim Ji-Eun , Lee Miyoung , Kang Daehee , Shin Aesun , Choi Ji-Yeob
Published: June 2023

Abstract
Although the protective effects of physical activity against several cancers are well established, evidence is inconsistent concerning Asian populations. Therefore, we assessed the association between the characteristics of physical activity and overall and type-specific cancer incidence in Koreans and examined the differences in association according to obesity status. Using prospective data from 112,108 participants in the Health Examinees study-G from 2004 to 2013, we evaluated the association between leisure-time physical activity (LTPA) and the incidence of overall and type-specific cancers using the Cox proportional hazards model. Self-reported LTPA participation, duration per week, intensity, type, and diversity were assessed. The incidence of overall and type-specific cancers, including colorectal, gastric, lung, breast, and prostate cancer and 13 obesity-related cancers, was identified using the Korea Central Cancer Registry from 1999 to 2018. Analyses were also stratified according to obesity status. In overweight males, participation in vigorous LTPA (hazard ratio [HR]: 0.84, 95% confidence interval [CI]: 0.72–0.97) and walking (HR: 0.84, 95% CI: 0.72–0.98) were associated with a lower risk of cancer overall. Regarding cancer types, climbing was marginally associated with a lower risk of colorectal cancer in overweight males (HR: 0.61, 95% CI: 0.37–1.00). In normal-weight females, although there was an increased risk in those performing recreational activities, this risk was attenuated when those diagnosed with thyroid cancer were excluded. In the analysis for 13 obesity-related cancers, consistent associations were found. These findings suggest the need for greater public awareness regarding physical activity among overweight individuals within the Asian population.
Data from Mitochondria Transfer from Mesenchymal Stem Cells Confers Chemoresistance to Glioblastoma Stem Cells through Metabolic Rewiring
Authors: Nakhle Jean , Khattar Khattar , Özkan Tülin , Boughlita Adel , Abba Moussa Daouda , Darlix Amélie , Lorcy Frédérique , Rigau Valérie , Bauchet Luc , Gerbal-Chaloin Sabine , Daujat-Chavanieu Martine , Bellvert Floriant , Turchi Laurent , Virolle Thierry , Hugnot Jean-Philippe , Buisine Nicolas , Galloni Mireille , Dardalhon Valérie , Rodriguez Anne-Marie , Vignais Marie-Luce
Published: June 2023

Glioblastomas (GBM) are heterogeneous tumors with high metabolic plasticity. Their poor prognosis is linked to the presence of glioblastoma stem cells (GSC), which support resistance to therapy, notably to temozolomide (TMZ). Mesenchymal stem cells (MSC) recruitment to GBM contributes to GSC chemoresistance, by mechanisms still poorly understood. Here, we provide evidence that MSCs transfer mitochondria to GSCs through tunneling nanotubes, which enhances GSCs resistance to TMZ. More precisely, our metabolomics analyses reveal that MSC mitochondria induce GSCs metabolic reprograming, with a nutrient shift from glucose to glutamine, a rewiring of the tricarboxylic acid cycle from glutaminolysis to reductive carboxylation and increase in orotate turnover as well as in pyrimidine and purine synthesis. Metabolomics analysis of GBM patient tissues at relapse after TMZ treatment documents increased concentrations of AMP, CMP, GMP, and UMP nucleotides and thus corroborate our in vitro analyses. Finally, we provide a mechanism whereby mitochondrial transfer from MSCs to GSCs contributes to GBM resistance to TMZ therapy, by demonstrating that inhibition of orotate production by Brequinar (BRQ) restores TMZ sensitivity in GSCs with acquired mitochondria. Altogether, these results identify a mechanism for GBM resistance to TMZ and reveal a metabolic dependency of chemoresistant GBM following the acquisition of exogenous mitochondria, which opens therapeutic perspectives based on synthetic lethality between TMZ and BRQ.
Significance:
Mitochondria acquired from MSCs enhance the chemoresistance of GBMs. The discovery that they also generate metabolic vulnerability in GSCs paves the way for novel therapeutic approaches.