bluuebunny/crossref_metadata_2025 huggingface dataset:
Methods for preparing tissue microarray slides using xenografts with different levels of HER2 expression to standardize HER2 detection
Authors: Yorozu Keigo , Kurasawa Mitsue , Iino Yuki , Nakamura Yuka , Hashizume Kaoru , Harada Naoki , Ochiai Atsushi
Published: November 2022

Gene amplification and protein overexpression of human epidermal growth factor receptor type 2 (HER2) are specific targets for HER2‐targeting drugs in breast, gastric, salivary gland, and colorectal cancers. The histopathological determination of HER2 status is crucial for treatment, highlighting the importance of improving HER2 detection accuracy in clinical practice. We prepared tissue microarray (TMA) slides for use as control slides for the standardization of gastric HER2 testing. Four human gastric cancer cell lines with HER2 scores of 3+, 2+, 1+, and 0 were xenografted in NOG mice. The TMA slides were constructed using samples from three different areas in these tumors. Staining properties were determined using six clinical kits for HER2. In TMA, HER2‐positive tumors with HER2 scores of 3+ and 2+ showed good staining with all diagnostic kits, and the tissue images were similar to those of clinical samples. Xenograft tumor slides could potentially be used as external controls to standardize staining conditions for a variety of kits and may improve the accuracy of HER2 detection in clinical practice.
Soil environmental DNA metabarcoding can quantify local plant diversity for biomonitoring across varied environments
Authors: Duley Emma , Iribar Amaia , Bisson Chris , Chave Jérôme , Donald Julian
Published: November 2022

Biomonitoring of plant communities is essential when evaluating outcomes of ecological restoration, but morphology‐based inventories can impede consistency across spatial and temporal scales. The Eden Project botanic garden (Cornwall, UK) offers an opportunity to test whether soil environmental DNA (eDNA) reflects plant species richness, community composition, and diversity. Furthermore, it enables the exploration of whether community complexity, environmental conditions, or sampling scale influence the similarity of soil eDNA‐derived results compared with those derived from classic botanical inventories. Survey plots were established encompassing a mixture of high‐ and low‐complexity plant assemblages, under either hot and humid or cool and dry conditions. Botanical inventories were conducted in quadrats up to 7 m around a soil eDNA sample plot. Soil samples were processed by metabarcoding of trnL p6 loop to determine plant eDNA identity and relative abundance. Differences in diversity and community composition were calculated before determining whether (1) inventory scale; (2) plant assembly complexity; (3) ambient conditions; (4) soil chemistry; (5) bulk root biomass and (6) soil respiration influenced the similarity of soil eDNA and botanical inventory methods. Inventory scale significantly determined the dissimilarity in both diversity and composition, with soil respiration, phosphorus, and C:N ratio also accounting for variation across sites. Our results demonstrate that soil eDNA metabarcoding is an effective approach for quantifying relative diversity in plant communities across broad habitat types and could be integrated into restoration monitoring strategies, but that its application requires an appropriate a priori knowledge of survey sites to best tailor soil eDNA survey implementation.
Structure Learning for Extremal Tree Models
Authors: Engelke Sebastian , Volgushev Stanislav
Published: November 2022

Extremal graphical models are sparse statistical models for multivariate extreme events. The underlying graph encodes conditional independencies and enables a visual interpretation of the complex extremal dependence structure. For the important case of tree models, we develop a data-driven methodology for learning the graphical structure. We show that sample versions of the extremal correlation and a new summary statistic, which we call the extremal variogram, can be used as weights for a minimum spanning tree to consistently recover the true underlying tree. Remarkably, this implies that extremal tree models can be learned in a completely non-parametric fashion by using simple summary statistics and without the need to assume discrete distributions, existence of densities or parametric models for bivariate distributions.
Socioeconomic inequity in coverage and quality of maternal postnatal care in Ethiopia
Authors: Beaumont Emma , Berhanu Della , Allen Elizabeth , Schellenberg Joanna , Avan Bilal Iqbal
Published: November 2022

Objective

High‐quality postnatal care is vital for improving maternal health. This study examined the relationship between household socioeconomic status and both coverage and quality of postnatal care in Ethiopia.

Method

Cross‐sectional household survey data were collected in October–November 2013 from 12 zones in 4 regions of Ethiopia. Women reporting a live birth in the 3–24 months prior to the survey were interviewed about the care they received before, during and after delivery and their demographic characteristics. Using mixed effect logistic and linear regression, the associations between household socioeconomic status and receiving postnatal care, location of postnatal care (health facility vs. non‐health facility), cadre of person providing care and the number of seven key services (including physical checks and advice) provided at a postnatal visit, were estimated.

Results

A total of 16% (358/2189) of women interviewed reported receiving at least one postnatal care visit within 6 weeks of delivery. Receiving a postnatal care visit was strongly associated with socioeconomic status with women from the highest socioeconomic group having twice the odds of receiving postnatal care compared to women in the poorest quintile (OR [95% CI]: 1.98 [1.29, 3.05]). For each increasing socioeconomic status quintile there was a mean increase of 0.24 postnatal care services provided (95% CI: 0.06–0.43, p = 0.009) among women who did not give birth in a facility. There was no evidence that number of postnatal care services was associated with socioeconomic status for women who gave birth in a facility. There was no evidence that socioeconomic status was associated with the provider or location of postnatal care visits.

Conclusion

Postnatal care in Ethiopia shows evidence of socio‐economic inequity in both coverage and quality. This demonstrates the need to focus on quality improvement as well as coverage, particularly among the poorest women who did not deliver in a facility.
Psychosocial Supports Offered to People with Psychotic Disorders by Community Members in Temeke District, Tanzania
Authors: Paul Diyammi Mark
Published: November 2022

This study was about psychosocial support offered to people with psychotic disorders by community members in Temeke district, Tanzania. The findings answered two questions which are: what is the quality of psychological support offered by community members to people suffering from psychotic disorders? To what extent do the people with the psychotic disorder have been socially supported and included in the social network within their communities? Both qualitative and quantitative methods of data collection were used and a descriptive design was adopted. Participants were People with Psychotic Disorders (PPDs) who had received treatment at the psychiatric unit of Temeke district hospital in 2020. A total of 80 PPDs were randomly sampled, of which 57answered study questions by themselves, and 23 were presented by their caregivers. The study noted that both psychological and social supports were rarely given to people with psychotic disorders by community members. It was further revealed that there was a strong and significant association between psychosocial supports and hospitalisation or prognosis of PPDs (p-value < 0.0001). In which one unit increase in psychological supports could significantly reduce hospitalisation of PPDs by 0.365 units (p-value 0.025). Meanwhile, one unit increase in social supports could significantly reduce hospitalisation by 0.22 units (p-value 0.038). Hence, psychosocial supports from community members were significantly important in reducing hospitalisation and improving the prognosis of PPDs. It was recommended that the community should be educated on the causes, treatment, and importance of ‘psychosocial support’ in the comprehensive treatment of psychotic disease.
Exploring College Students’ Perceptions of Esports and Esports Academic Programs
Authors: Hwang Jaeyeon , Kim Jin
Published: November 2022

This study examined how college students’ gender and prior participation in esports affect their perceptions of esports and esports academic programs. After collecting data from college students (N = 162), data were analyzed using 2 × 2 factorial analysis of variance to compare the influence of esports participation, gender, and the interaction effect on perception. Both esports participation, F(1, 150) = 13.78, p < .001, and gender, F(1, 150) = 4.82, p < .05, were significantly associated with esports perception. For the perception of esports academic programs, only esports participation was significant, F(1, 150) = 5.85, p < .05. Men reported positive perceptions, and this phenomenon was amplified in groups with prior esports experience. The authors suggest avenues to embrace esports in higher education, reflecting the findings of this research.
Rapid marine oxygen variability: Driver of the Late Ordovician mass extinction
Authors: Kozik Nevin P. , Young Seth A. , Newby Sean M. , Liu Mu , Chen Daizhao , Hammarlund Emma U. , Bond David P. G. , Them Theodore R. , Owens Jeremy D.
Published: November 2022

The timing and connections between global cooling, marine redox conditions, and biotic turnover are underconstrained for the Late Ordovician. The second most severe mass extinction occurred at the end of the Ordovician period, resulting in ~85% loss of marine species between two extinction pulses. As the only “Big 5” extinction that occurred during icehouse conditions, this interval is an important modern analog to constrain environmental feedbacks. We present a previously unexplored thallium isotope records from two paleobasins that record global marine redox conditions and document two distinct and rapid excursions suggesting vacillating (de)oxygenation. The strong temporal link between these perturbations and extinctions highlights the possibility that dynamic marine oxygen fluctuations, rather than persistent, stable global anoxia, played a major role in driving the extinction. This evidence for rapid oxygen changes leading to mass extinction has important implications for modern deoxygenation and biodiversity declines.
CLEC-1 is a death sensor that limits antigen cross-presentation by dendritic cells and represents a target for cancer immunotherapy
Authors: Drouin Marion , Saenz Javier , Gauttier Vanessa , Evrard Berangere , Teppaz Geraldine , Pengam Sabrina , Mary Caroline , Desselle Ariane , Thepenier Virginie , Wilhelm Emmanuelle , Merieau Emmanuel , Ligeron Camille , Girault Isabelle , Lopez Maria-Dolores , Fourgeux Cynthia , Sinha Debajyoti , Baccelli Irene , Moreau Aurelie , Louvet Cedric , Josien Regis , Poschmann Jeremie , Poirier Nicolas , Chiffoleau Elise
Published: November 2022

Tumors exploit numerous immune checkpoints, including those deployed by myeloid cells to curtail antitumor immunity. Here, we show that the C-type lectin receptor CLEC-1 expressed by myeloid cells senses dead cells killed by programmed necrosis. Moreover, we identified Tripartite Motif Containing 21 (TRIM21) as an endogenous ligand overexpressed in various cancers. We observed that the combination of CLEC-1 blockade with chemotherapy prolonged mouse survival in tumor models. Loss of CLEC-1 reduced the accumulation of immunosuppressive myeloid cells in tumors and invigorated the activation state of dendritic cells (DCs), thereby increasing T cell responses. Mechanistically, we found that the absence of CLEC-1 increased the cross-presentation of dead cell–associated antigens by conventional type-1 DCs. We identified antihuman CLEC-1 antagonist antibodies able to enhance antitumor immunity in CLEC-1 humanized mice. Together, our results demonstrate that CLEC-1 acts as an immune checkpoint in myeloid cells and support CLEC-1 as a novel target for cancer immunotherapy.
Global fjords as transitory reservoirs of labile organic carbon modulated by organo-mineral interactions
Authors: Cui Xingqian , Mucci Alfonso , Bianchi Thomas S. , He Ding , Vaughn Derrick , Williams Elizabeth K. , Wang Chuning , Smeaton Craig , Koziorowska-Makuch Katarzyna , Faust Johan C. , Plante Alain F. , Rosenheim Brad E.
Published: November 2022

The global carbon cycle is strongly modulated by organic carbon (OC) sequestration and decomposition. Whereas OC sequestration is relatively well constrained, there are few quantitative estimates of its susceptibility to decomposition. Fjords are hot spots of sedimentation and OC sequestration in marine sediments. Here, we adopt fjords as model systems to investigate the reactivity of sedimentary OC by assessing the distribution of the activation energy required to break OC bonds. Our results reveal that OC in fjord sediments is more thermally labile than that in global sediments, which is governed by its unique provenance and organo-mineral interactions. We estimate that 61 ± 16% of the sedimentary OC in fjords is degradable. Once this OC is remobilized and remineralized during glacial maxima, the resulting metabolic CO
2
could counterbalance up to 50 ppm of the atmospheric CO
2
decrease during glacial times, making fjords critical actors in dampening glacial-interglacial climate fluctuations through negative carbon cycling loops.
A bioinspired snap-through metastructure for manipulating micro-objects
Authors: Zhang Xuan , Wang Yue , Tian Zhihao , Samri Manar , Moh Karsten , McMeeking Robert M. , Hensel René , Arzt Eduard
Published: November 2022

Micro-objects stick tenaciously to each other—a well-known show-stopper in microtechnology and in handling micro-objects. Inspired by the trigger plant, we explore a mechanical metastructure for overcoming adhesion involving a snap-action mechanism. We analyze the nonlinear mechanical response of curved beam architectures clamped by a tunable spring, incorporating mono- and bistable states. As a result, reversible miniaturized snap-through devices are successfully realized by micron-scale direct printing, and successful pick-and-place handling of a micro-object is demonstrated. The technique is applicable to universal scenarios, including dry and wet environment, or smooth and rough counter surfaces. With an unprecedented switching ratio (between high and low adhesion) exceeding 10
4
, this concept proposes an efficient paradigm for handling and placing superlight objects.
SARS-CoV-2 Omicron BA.1 and BA.2 are attenuated in rhesus macaques as compared to Delta
Authors: van Doremalen Neeltje , Singh Manmeet , Saturday Taylor A. , Yinda Claude Kwe , Perez-Perez Lizzette , Bohler W. Forrest , Weishampel Zachary A. , Lewis Matthew , Schulz Jonathan E. , Williamson Brandi N. , Meade-White Kimberly , Gallogly Shane , Okumura Atsushi , Feldmann Friederike , Lovaglio Jamie , Hanley Patrick W. , Shaia Carl , Feldmann Heinz , de Wit Emmie , Munster Vincent J. , Rosenke Kyle
Published: November 2022

Since the emergence of SARS-CoV-2, five different variants of concern (VOCs) have been identified: Alpha, Beta, Gamma, Delta, and Omicron. Because of confounding factors in the human population, such as preexisting immunity, comparing severity of disease caused by different VOCs is challenging. Here, we investigate disease progression in the rhesus macaque model upon inoculation with the Delta, Omicron BA.1, and Omicron BA.2 VOCs. Disease severity in rhesus macaques inoculated with Omicron BA.1 or BA.2 was lower than those inoculated with Delta and resulted in significantly lower viral loads in nasal swabs, bronchial cytology brush samples, and lung tissue in rhesus macaques. Cytokines and chemokines were up-regulated in nasosorption samples of Delta animals compared to Omicron BA.1 and BA.2 animals. Overall, these data suggest that, in rhesus macaques, Omicron replicates to lower levels than the Delta VOC, resulting in reduced clinical disease.
Gravity-resisting colloidal collectives
Authors: Law Junhui , Chen Hui , Wang Yibin , Yu Jiangfan , Sun Yu
Published: November 2022

Self-assembly of dynamic colloidal structures along the vertical direction has been challenging because of gravity and the complexity in controlling agent-agent interactions. Here, we present a strategy that enables the self-growing of gravity-resisting colloidal collectives. By designing a unique dual-axis oscillating magnetic field, time-varying interparticle interactions are induced to assemble magnetic particles against gravity into vertical collectives, with the structures continuing to grow until reaching dynamic equilibrium. The collectives have swarm behavior and are capable of height reconfiguration and adaptive locomotion, such as moving along a tilted substrate and under nonzero fluidic flow condition, gap and obstacle crossing, and stair climbing.
Little evidence supports gabapentinoid use in bipolar disorder or insomnia
Authors: Saul Helen , Gursul Deniz , Cassidy Samantha , Harrison Paul
Published: November 2022

The study

Hong JSW, Atkinson LZ, Al-Juffali N, et al. Gabapentin and pregabalin in bipolar disorder, anxiety states, and insomnia: systematic review, meta-analysis, and rationale.
Mol Psychiatry
2022;27:1339-49.

To read the full NIHR Alert, go to:
https://evidence.nihr.ac.uk/alert/review-finds-little-evidence-support-gabapentinoid-use-bipolar-disorder-or-insomnia/
Eight-year retrospective study investigating tooth survival after primary non-surgical root canal treatment in a UK military cohort
Authors: Smith Richard Blake , Bryce G E , Ng Y , Gulabivala K , Dermont M A
Published: November 2022

Introduction

Root canal treatment (RCT) plays an important role in preserving the dentition by deferring other invasive treatments. Data on tooth survival and predictive factors for tooth loss after RCT in the military cohort are lacking. This investigation aimed to determine the proportion of teeth surviving in an 8-year period after RCT and identify potential predictive factors for tooth loss in a UK military cohort.

Methodology

A retrospective review of an integrated electronic health record for military patients who had received RCT was performed in a random sample of 205 patients (n=219 root-filled teeth) who had received RCT between 1 January 2011 and 1 January 2012. Tooth survival was defined as tooth presence, regardless of signs or symptoms, and measured from the point of root filling until either the end of the designated study period or time of extraction. Survival was evaluated using Kaplan-Meier estimates and association with tooth loss using the χ2test. Potentially significant predictive factors were investigated using univariate Cox regression.

Results

Tooth survival following RCT was 98% after 24 months; 88% after 48 months; 83% after 72 months; and 78% after 96 months. Four predictive factors were found to affect tooth loss as follows: preoperative pain (HR=3.2; p<0.001), teeth with less than two proximal contacts (HR=3.0; p=0.01), teeth with cores involving more than two surfaces (HR=2.0; p=0.03) and postoperative unscheduled dental attendances (UDA) (HR=2.7; p=0.01).

Conclusions

Within the limitations of this study, the presence of preoperative pain; teeth with less than two proximal contacts or with cores involving more than two tooth surfaces; and occurrence of postoperative UDA were found to significantly increase the hazard of tooth loss.
Analysis on parametric vibration of hydraulic opposing cylinders controlled by a servo valve considering pressure pulsation
Authors: Yuan Xiaoming , Wang Weiqi , Zhu Xuan , Du Bing , Zhang Lijie
Published: November 2022

During the working process of the system of hydraulic opposing cylinders controlled by a servo valve, the fluid equivalent stiffness changes dynamically due to the pressure pulsation of the pump source. Therefore, the transmission system has obvious nonlinear effects, and its dynamic performance is difficult to improve further. Thus, a nonlinear dynamic model of the system of hydraulic opposing cylinders controlled by a servo valve was established. By using the multiscale method, the steady-state approximate solutions of the primary resonance and the combination resonance of the system were derived to reveal their characteristic laws. The results showed that the dominant frequency of the system's primary resonance is the frequency of the external excitation source, and the dominant frequency of the system's combination resonance is the sum of the natural frequency of each order and the fluctuation frequency of the fluid equivalent stiffness. The amplitude of the combination resonance was smaller than that of the primary resonance. The maximum error between the theoretical natural frequency and the experimental modal frequency was 3.77%, which verified the correctness of the system's nonlinear dynamic model. The research can provide a theoretical reference for the dynamics optimization design of the hydraulic transmission system.
Application of mold flow analysis to the study of plastic gear rack injection molding warpage
Authors: Chen Dyi-Cheng , Yang Rih-Sheng , Lu Shang-Wei , Guo Hong-Yao
Published: November 2022

This study employed the Taguchi method, analysis of variance, and response surface methodology for plastic gear rack injection molding parameters followed by a factorial quality validation. This study was expected to reduce the time cost of mold design and injection molding by making different combinations of the molding parameters, designing an experimental method, and performing the data simulation experiment by computer-aided engineering (CAE). With the research tool of polymer (polyacetal) for plastic material, computer-aided design mold design, and CAE mold flow analysis software, a numerical analysis of plastic molding flow was conducted. Taguchi L16 (45) orthogonal array designed 16 experimental combinations including injection molding conditions of filling time, holding pressure, holding time, plastic temperature, and mold temperature. The experimental results of molding analysis of software (Moldex3D) determined the optimum molding essentials of plastic injection: filling time 0.2 s, holding pressure 98 MPa, plastic temperature 195 °C, and mold temperature 65 °C. In this study, the parameters of the response surface method were used for the actual injection verification. The CAE simulation software can greatly improve the mold design and injection molding parameter testing time to enhance the overall working efficiency and cost control.
Toy models for hierarchy studies
Authors: Álvarez-Luna Clara , Cembranos José A. R. , Sanz-Cillero Juan José
Published: November 2022

We provide a simple computation in order to estimate the probability of a given hierarchy between two scales. In particular, we work in a model provided with a gauge symmetry, with two scalar doublets. We start from a scale-invariant classical Lagrangian, but by taking into account the Coleman–Weinberg mechanism, we obtain masses for the gauge bosons and the scalars. This approach typically provides a light (L) and a heavy (H) sector related to the two different vacuum expectation values of the two scalars. We compute the size of the hypervolume of the parameter space of the model associated with an interval of mass ratios between these two sectors. We define the probability as proportional to this size and conclude that probabilities of very large hierarchies are not negligible in the type of models studied in this work.
An Efficient JSH-FCM-Based Thyroid Disease Detection Using Ash-Ann with Stage Classification via a Fuzzy Rule-Based Approach
Authors: Shalini L , Vijayakumar K
Published: November 2022

One of the most misunderstood and undiagnosed diseases is termed Thyroid Disease (TD), which is a subset of endocrinology. It emerges at the edge of the thyroid gland due to the abnormal development of thyroid tissue. Owing to the lack of awareness and early diagnosis, TD is a critical problem in underdeveloped countries. For TD diagnosis, various theoretical works have been introduced; still, in the early diagnosis of TD, accurate prediction of the thyroid data is a significant problem. Thus, by utilizing Altered SigHyper activation-centric Artificial Neural Network (ANN) (ASH-ANN) with various stage classifications, an effectual Jaccard Similarity and He-initialization induced Fuzzy C-Means (FCM) (JSH-FCM) clustering-centric TD detection system is proposed by means of a fuzzy rule-centric methodology. Initially, for accurate detection, the thyroid dataset is gathered and the data is pre-processed. Next, by JSH-FCM clustering, the age-centric clustering is carried out. After that, by utilizing Pearson Correlation-amalgamated Principal Component Analysis ((PC)2A), Feature Extraction (FE) and feature selection is conducted. Moreover, to detect the TD kind, an ASH-ANN classifier is wielded. Finally, for differentiating the stages of TD, the fuzzy rule is employed. The experimental outcomes depict that the proposed system achieved superior performance with an accuracy of 97.32% when weighed against the prevailing system; in addition, the stages of TD are differentiated precisely.
Nonlinear approximation spaces for inverse problems
Authors: Cohen A. , Dolbeault M. , Mula O. , Somacal A.
Published: November 2022

This paper is concerned with the ubiquitous inverse problem of recovering an unknown function u from finitely many measurements, possibly affected by noise. In recent years, inversion methods based on linear approximation spaces were introduced in [1, 2] with certified recovery bounds. It is however known that linear spaces become ineffective for approximating simple and relevant families of functions, such as piecewise smooth functions, that typically occur in hyperbolic PDEs (shocks) or images (edges). For such families, nonlinear spaces [3] are known to significantly improve the approximation performance. The first contribution of this paper is to provide with certified recovery bounds for inversion procedures based on nonlinear approximation spaces. The second contribution is the application of this framework to the recovery of general bidimensional shapes from cell-average data. We also discuss how the application of our results to n-term approximation relates to classical results in compressed sensing.
The influence of non-radiative relaxation on the room-temperature phosphorescence of metalloporphyrin
Authors: Liu Lixin , Han Bo , Cao Yu , Wen Jingji
Published: November 2022

The room-temperature phosphorescence (RTP) of metalloporphyrins, induced by the heavy atom effect (HAE), has been widely concerned in many fields, and the intense emission of RTP is highly desired. The phosphorescent transition rate ([Formula: see text] has been used to quantitatively characterize the HAE’s intrinsic nature. However, the phosphorescent intensity was not determined by [Formula: see text] alone, non-phosphorescent transition ([Formula: see text] induced by surrounding factors was also involved. In this study, the influence of [Formula: see text] on the RTP of palladium octaethylporphyrin (PdOEP), platinum octaethylporphyrin (PtOEP), and platinum tetraphenylporphyrin (PtTPP) was studied. The effect of [Formula: see text] can be quantitatively described by an introduced parameter [Formula: see text], which was defined as [Formula: see text] = [Formula: see text]/([Formula: see text]. The method is proposed for determining the [Formula: see text] of PdOEP, PtOEP, and PtTPP by the UV-visible absorption spectra, luminescence spectra, and phosphorescence dynamic curves. Our research provides a way to understand the effect of knP on the RTP, and may benefit the development and optimization of metalloporphyrins aiming at intense RTP.
k-Product cordial labeling of product of graphs
Authors: Jeya Daisy K. , Santrin Sabibha R. , Jeyanthi P. , Youssef Maged Z.
Published: November 2022

In 2012, Ponraj et al. defined k-product cordial labeling as follows: Let [Formula: see text] be a map from [Formula: see text] to [Formula: see text] where [Formula: see text] is an integer, [Formula: see text]. For each edge [Formula: see text] assign the label [Formula: see text] [Formula: see text]. [Formula: see text] is called a k-product cordial labeling if [Formula: see text], and [Formula: see text], [Formula: see text], where [Formula: see text] and [Formula: see text] denote the number of vertices and edges, respectively, labeled with [Formula: see text] [Formula: see text]. A graph that admits k-product cordial labeling is called k-product cordial graph. Later, we proved that several families of graphs are k-product cordial graphs. In this paper, we show that the product of graphs admit k-product cordial labeling.
Autonomous Leader–Follower Formation of Vehicular Robots Using the Lyapunov Method
Authors: Azid Sheikh Izzal , Raghuwaiya Krishna , Javed Aiman , Kumari Edleen
Published: November 2022

This paper focuses on the control of two self-driven vehicles (leader–follower) in a multi-obstacle environment, while maintaining formation. The acceleration-based control input design governs the overall movement and control of the rovers. This is accomplished through the application of APF functions that support the leader robot to reach the desired target while avoiding obstacles and maintaining formation. The Lyapunov theorem was used for the control design of the leader and follower vehicles. An effective mathematical model was designed and run through the MATLAB software for simulation verification. The simulation results obtained illustrate the behavior of the leader–follower vehicles with respect to the controllers designed. Therefore, this paper looks at the efficiency of the vehicles to converge at a predefined target, from random points in a predefined workspace, while avoiding fixed and moving obstacles. The technique may be applied in transportation and defense sectors where environments are a risk prone to human health or safety.
On automorphisms of strong semilattice of groups
Authors: Shah Aftab Hussain , Mir Dilawar Juneed , Khan Noor Mohammad
Published: November 2022

In this paper, we consider the automorphisms of the strong semilattice of groups and relate them to the isomorphisms and automorphisms of underlying groups. We also provide a construction for non-trivial automorphisms of semilattices.
Digital Stories with the Online Collection of the V&A for Inquiry-Based Learning
Authors: Tsiviltidou Zoi , Vavoula Giasemi
Published: November 2022

This article explores the use of digital storytelling in the classroom to frame inquiry-based learning with digital museum collections. It presents the final in a series of three interventions that were part of doctoral research that tested theDiStoMusInqframework. The intervention involved a class of 15-16-years-old students at an international school in Greece as part of their English Literature curriculum, and included eight lessons, two of which were virtual visits to the online collection of the Victoria and Albert Museum, UK. The students worked in small groups to agree what questions they want to explore and used their own smartphones and laptops to look for answers in the online collection. They then collected material from the collection and/or took inspiration from the collection to create their own material, and used these to produce video stories that presented their answers. The findings suggest that inquiry-driven digital storytelling offers an effective way to leverage digital technologies in the classroom to engage students in purposeful, self-directed explorations of online museum collections. The processes of developing a digital story and inquiring the collections feed into one another, resulting in cultural heritage-inspired, historically informed creative student outputs and the development of student research skills.
Source Matching and Rewriting for MLIR Using String-Based Automata
Authors: Espindola Vinicius , Zago Luciano , Yviquel Hervé , Araujo Guido
Published: November 2022

A typical compiler flow relies on a uni-directional sequence of translation/optimization steps that
lower
the program abstract representation, making it hard to preserve higher-level program information across each transformation step. On the other hand, modern ISA extensions and hardware accelerators can benefit from the compiler’s ability to detect and
raise
program idioms to acceleration instructions or optimized library calls. Although recent works based on Multi-Level IR (MLIR) have been proposed for code raising, they rely on specialized languages, compiler recompilation, or in-depth dialect knowledge. This article presents
Source Matching and Rewriting
(SMR), a user-oriented source-code-based approach for MLIR idiom matching and rewriting that does not require a compiler expert’s intervention. SMR uses a two-phase automaton-based DAG-matching algorithm inspired by early work on tree-pattern matching. First, the idiom
Control-Dependency Graph
(CDG) is matched against the program’s CDG to rule out code fragments that do not have a control-flow structure similar to the desired idiom. Second, candidate code fragments from the previous phase have their
Data-Dependency Graphs
(DDGs) constructed and matched against the idiom DDG. Experimental results show that SMR can effectively match idioms from Fortran (FIR) and C (CIL) programs while raising them as BLAS calls to improve performance. Additional experiments also show performance improvements when using SMR to enable code replacement in areas like approximate computing and hardware acceleration.
A Two-Speed Synchronous Traffic Protocol for Intelligent Intersections: From Single-Vehicle to Platoon Crossing
Authors: Markert Daniel , Masrur Alejandro
Published: November 2022

With progress in cooperative and autonomous driving, there is an increasing interest in intelligent intersections to replace conventional traffic lights and, thereby, improve traffic efficiency. To avoid accidents in such safety-critical systems, a traffic protocol needs to be implemented. In this article, we are concerned with synchronous traffic protocols, i.e., those that synchronize the arrival time of vehicles at the intersection. In particular, such protocols are normally conceived for homogeneous vehicles of approximately the same size/length. However, these do not extend well to heterogeneous vehicles, i.e., they lead to unviable requirements on the road infrastructure. To overcome this limitation, based on the observation that large/overlength vehicles like buses and trams are less frequent than passenger vehicles, we propose an approach that treats them as exceptions (rather than the rule) leading to a much more efficient design. In contrast to approaches from the literature, we implement a two-speed policy—with a high speed for drive-through and a low speed for turn maneuvers—and analyze both single-vehicle as well as fairness-based platoon crossing. To conclude, we perform detailed comparisons illustrating the benefits by the proposed approach.
Perception-Motion Coupling in Active Telepresence: Human Behavior and Teleoperation Interface Design
Authors: Lin Tsung-Chi , Unni Krishnan Achyuthan , Li Zhi
Published: November 2022

Teleoperation enables complex robot platforms to perform tasks beyond the scope of the current state-of-the-art robot autonomy by imparting human intelligence and critical thinking to these operations. For seamless control of robot platforms, it is essential to facilitate optimal situational awareness of the workspace for the operator through active telepresence cameras. However, the control of these active telepresence cameras adds an additional degree of complexity to the task of teleoperation. In this paper we present our results from the user study that investigates: (1) how the teleoperator learns or adapts to performing the tasks via active cameras modeled after camera placements on the TRINA humanoid robot; (2) the perception-action coupling operators implement to control active telepresence cameras, and (3) the camera preferences for performing the tasks. These findings from the human motion analysis and post-study survey will help us determine desired design features for robot teleoperation interfaces and assistive autonomy.
Machine Learning Applications in Internet-of-Drones: Systematic Review, Recent Deployments, and Open Issues
Authors: Heidari Arash , Jafari Navimipour Nima , Unal Mehmet , Zhang Guodao
Published: November 2022

Deep Learning (DL)
and
Machine Learning (ML)
are effectively utilized in various complicated challenges in healthcare, industry, and academia. The
Internet of Drones (IoD)
has lately cropped up due to high adjustability to a broad range of unpredictable circumstances. In addition,
Unmanned Aerial Vehicles (UAVs)
could be utilized efficiently in a multitude of scenarios, including rescue missions and search, farming, mission-critical services, surveillance systems, and so on, owing to technical and realistic benefits such as low movement, the capacity to lengthen wireless coverage zones, and the ability to attain places unreachable to human beings. In many studies, IoD and UAV are utilized interchangeably. Besides, drones enhance the efficiency aspects of various network topologies, including delay, throughput, interconnectivity, and dependability. Nonetheless, the deployment of drone systems raises various challenges relating to the inherent unpredictability of the wireless medium, the high mobility degrees, and the battery life that could result in rapid topological changes. In this paper, the IoD is originally explained in terms of potential applications and comparative operational scenarios. Then, we classify ML in the IoD-UAV world according to its applications, including resource management, surveillance and monitoring, object detection, power control, energy management, mobility management, and security management. This research aims to supply the readers with a better understanding of (1) the fundamentals of IoD/UAV, (2) the most recent developments and breakthroughs in this field, (3) the benefits and drawbacks of existing methods, and (4) areas that need further investigation and consideration. The results suggest that the
Convolutional Neural Networks (CNN)
method is the most often employed ML method in publications. According to research, most papers are on resource and mobility management. Most articles have focused on enhancing only one parameter, with the accuracy parameter receiving the most attention. Also, Python is the most commonly used language in papers, accounting for 90% of the time. Also, in 2021, it has the most papers published.
Identifying Overly Restrictive Matching Patterns in SMT-based Program Verifiers (Extended Version)
Authors: Bugariu Alexandra , Ter-Gabrielyan Arshavir , Müller Peter
Published: November 2022

Universal quantifiers occur frequently in proof obligations produced by program verifiers, for instance, to axiomatize uninterpreted functions and to statically express properties of arrays. SMT-based verifiers typically reason about them via E-matching, an SMT algorithm that requires syntactic matching patterns to guide the quantifier instantiations. Devising good matching patterns is challenging. In particular, overly restrictive patterns may lead to spurious verification errors if the quantifiers needed for proof are not instantiated; they may also conceal unsoundness caused by inconsistent axiomatizations. In this article, we present the first technique that identifies and helps the users and the developers of program verifiers remedy the effects of overly restrictive matching patterns. We designed a novel algorithm to synthesize missing triggering terms required to complete unsatisfiability proofs via E-matching. Tool developers can use this information to refine their matching patterns and prevent similar verification errors, or to fix a detected unsoundness.
Bacteriophages in the Dairy Industry: A Problem Solved?
Authors: Ortiz Charneco Guillermo , de Waal Paul P. , van Rijswijck Irma M.H. , van Peij Noël N.M.E. , van Sinderen Douwe , Mahony Jennifer
Published: November 2022

Bacteriophages (or phages) represent one of the most persistent threats to food fermentations, particularly large-scale commercial dairy fermentations. Phages infecting lactic acid bacteria (LAB) that are used as starter cultures in dairy fermentations are well studied, and in recent years there have been significant advances in defining the driving forces of LAB–phage coevolution. The means by which different starter bacterial species defend themselves against phage predation and the chromosomal or plasmid location of the genes encoding these defense mechanisms have dictated the technological approaches for the development of robust starter cultures. In this review, we highlight recent advances in defining phage–host interactions and how phage resistance occurs in different bacterial species. Furthermore, we discuss how these insights continue to transform the dairy fermentation industry and how they also are anticipated to guide food fermentations involving plant-based alternatives in the future.
Cardiac function, structural, and electrical remodeling by microgravity exposure
Authors: Sy Mary R. , Keefe Joshua A. , Sutton Jeffrey P. , Wehrens Xander H. T.
Published: November 2022

Space medicine is key to the human exploration of outer space and pushes the boundaries of science, technology, and medicine. Because of harsh environmental conditions related to microgravity and other factors and hazards in outer space, astronauts and spaceflight participants face unique health and medical challenges, including those related to the heart. In this review, we summarize the literature regarding the effects of spaceflight on cardiac structure and function. We also provide an in-depth review of the literature regarding the effects of microgravity on cardiac calcium handling. Our review can inform future mechanistic and therapeutic studies and is applicable to other physiological states similar to microgravity such as prolonged horizontal bed rest and immobilization.
Evaluating the Performance of Oil and Gas Companies by an Extended Balanced Scorecard and the Hesitant Fuzzy Best-Worst Method
Authors: Yazdi Amir Karbassi , Mehdiabadi Amir , Hanne Thomas , Sarfaraz Amir Homayoun , Yazdian Fatemeh Tabatabaei
Published: November 2022

The aim of this research is to find and prioritize a multicriteria performance measurement based on the balanced scorecard (BSC) for oil and gas (O & G) companies in an uncertain environment using the hesitant fuzzy best-worst method (HFBWM). The O & G industry has a key role in the economies of many countries. Hence, the evaluation of the performance of the O & G industry plays an important role. We utilize BSC for this purpose, which usually considers the financial, customer-oriented, internal, learning-oriented, and growth perspectives. In our research, the social responsibility perspective will be added. After finding multiple performance measurements, many companies cannot implement all of them because of limited resources. Therefore, multicriteria decision-making (MCDM) methods can be applied for prioritizing and selecting the most important measurement criteria. One of the MCDM methods is the best-worst method (BWM). This approach has several advantages compared to other MCDM methods. Due to uncertainties in decision-making, a suitable method for decision-making in an uncertain environment is necessary. Hesitant fuzzy approaches are applied as one such uncertainty-based method in this research. Our results indicate that among the five perspectives of BSC that we considered, the customer and internal process perspectives are the most important ones, and the cost of the R & D indicator is the most important subcriterion among these.
Spike Protein Subunits of SARS-CoV-2 Alter Mitochondrial Metabolism in Human Pulmonary Microvascular Endothelial Cells: Involvement of Factor Xa
Authors: Zekri-Nechar Khaoula , Zamorano-León José J. , Reche Carmen , Giner Manel , López-de-Andrés Ana , Jiménez-García Rodrigo , López-Farré Antonio J. , Martínez-Martínez Carlos Hugo
Published: November 2022

Background. Mitochondria have been involved in host defense upon viral infections. Factor Xa (FXa), a coagulating factor, may also have influence on mitochondrial functionalities. The aim was to analyze if in human pulmonary microvascular endothelial cells (HPMEC), the SARS-CoV-2 (COVID-19) spike protein subunits, S1 and S2 (S1+S2), could alter mitochondrial metabolism and what is the role of FXA. Methods. HPMEC were incubated with and without recombinants S1+S2 (10 nmol/L each). Results. In control conditions, S1+S2 failed to modify FXa expression. However, in LPS (1 μg/mL)-incubated HPMEC, S1+S2 significantly increased FXa production. LPS tended to reduce mitochondrial membrane potential with respect to control, but in higher and significant degree, it was reduced when S1+S2 were present. LPS did not significantly modify cytochrome c oxidase activity as compared with control. Addition of S1+S2 spike subunits to LPS-incubated HPMEC significantly increased cytochrome c oxidase activity with respect to control. Lactate dehydrogenase activity was also increased by S1+S2 with respect to control and LPS alone. Protein expression level of uncoupled protein-2 (UCP-2) was markedly expressed when S1+S2 were added together to LPS. Rivaroxaban (50 nmol/L), a specific FXa inhibitor, significantly reduced all the above-mentioned alterations induced by S1+S2 including UCP-2 expression. Conclusions. In HPMEC undergoing to preinflammatory condition, COVID-19 S1+S2 spike subunits promoted alterations in mitochondria metabolism suggesting a shift from aerobic towards anaerobic metabolism that was accompanied of high FXa production. Rivaroxaban prevented all the mitochondrial metabolic changes mediated by the present COVID-19 S1 and S2 spike subunits suggesting the involvement of endogenous FXa.
Relationship of Maize Yield to Climatic and Environmental Factors under Deficit Irrigation: A Quantitative Review
Authors: Allakonon M. Gloriose B. , Akponikpè P. B. Irénikatché
Published: November 2022

There is evidence that freshwater resources available for agriculture are decreasing with an unprecedented record. New irrigation strategies are developed and tested on crops that feed the world, such as maize, to improve water productivity. Deficit irrigation is one of these strategies that can improve water productivity without a significant impact on crop production. Here, the authors review the factors that affect the response of maize yield and irrigation water productivity to water stress induced by deficit irrigation using a quantitative approach. Data were collected from peer-reviewed publications worldwide that respond to predefined criteria. The authors defined grain yield variation (GYv) and variation of irrigation water use efficiency (IWUEv) as response variables and used simple and multiple linear regression models for data analysis. Overall, maize response to deficit irrigation is significantly correlated to the water stress level (WD). Mild stress below 20% of optimal irrigation led to 0.5% to 17.45% of yield loss in the vegetative stage (VS) but resulted in 46% yield loss at the reproductive stage (RS). Water stress (20–40%) applied at both vegetative and reproductive stages (VRSs) can reduce yield by 44%. The maximum yield loss was 90% in the RS. The multiple linear regression revealed that 62% of the grain yield variability was explained by both WD and nitrogen rates in the VS, while 54% and 13% of this variability was explained in the RS and VRS, respectively. The authors also found that the WD and the climate explained the best the GYv and the IWUEv under deficit irrigation. These results suggest that regarding the climatic characteristics of site location and the complexity of maize production systems, site-specific levels of deficit irrigation should be recommended to limit yield loss and increase water productivity.