bluuebunny/crossref_metadata_2025 huggingface dataset:
Holistic healthcare in inflammatory bowel disease: time for patient-centric approaches?
Authors: Sudhakar Padhmanand , Wellens Judith , Verstockt Bram , Ferrante Marc , Sabino João , Vermeire Séverine
Published: September 2022

Inflammatory bowel disease (IBD) is an emerging global disease characterised by chronic inflammation of the gastrointestinal tract. However, IBD is also manifested by several extraintestinal symptoms which, along with the intestinal symptoms, impact on the mental and emotional well-being of patients. Despite therapeutic advancements, only one-third of the diagnosed patients receiving approved medical treatments achieve short-term to medium-term remission. Consequently, patients who do not get successfully treated might resort to using complementary and alternative approaches to manage their symptoms, with or without consulting their treating clinician. Despite their possible potential, such approaches have various risks stemming from unknown adverse reactions and possible interference with medically approved therapies. In this study, we present the results of a well-performed literature review where we included randomised clinical trials which have assessed the efficacy of complementary approaches and dietary therapy on at least one of the following four outcomes: clinical remission, endoscopic remission, modulation of molecular biomarkers or quality of life metrics. By pointing out intraoutcome and interoutcome concordance, we identified possible candidates for clinical adoption and further study in larger randomised clinical trials covering the broad spectrum of IBD heterogeneity. We finally proposed a patient-centric clinical care model and a series of recommendations for stakeholders, with special attention to complementary approaches and dietary strategies, aimed at achieving holistic remission.
Combination of a novel heat shock protein 90-targeted photodynamic therapy with PD-1/PD-L1 blockade induces potent systemic antitumor efficacy and abscopal effect against breast cancers
Authors: Kaneko Kensuke , Acharya Chaitanya R , Nagata Hiroshi , Yang Xiao , Hartman Zachary Conrad , Hobeika Amy , Hughes Philip F , Haystead Timothy A J , Morse Michael A , Lyerly Herbert Kim , Osada Takuya
Published: September 2022

Background

We previously demonstrated potent antitumor activity against human breast cancer xenografts using photodynamic therapy (PDT) targeting a novel tumor-specific photosensitizer (HS201), which binds heat shock protein 90 (HS201-PDT). However, induction of systemic antitumor immunity by HS201-PDT alone or by the combination strategy with immune checkpoint blockade has yet to be determined.

Methods

Using unilateral and bilateral implantation models of syngeneic breast tumors (E0771, MM3MG-HER2, and JC-HER3) in mice, we assessed whether HS201-PDT could induce local and systemic antitumor immunity. In an attempt to achieve a stronger abscopal effect for distant tumors, the combination strategy with anti-PD-L1 antibody was tested. Tumor-infiltrating leukocytes were analyzed by single cell RNA-sequencing and receptor-ligand interactome analysis to characterize in more detailed the mechanisms of action of the treatment and key signaling pathways involved.

Results

HS201-PDT demonstrated greater tumor control and survival in immune competent mice than in immunocompromised mice, suggesting the role of induced antitumor immunity; however, survival was modest and an abscopal effect on distant implanted tumor was weak. A combination of HS201-PDT with anti-PD-L1 antibody demonstrated the greatest antigen-specific immune response, tumor growth suppression, prolonged mouse survival time and abscopal effect. The most significant increase of intratumoral, activated CD8+T cells and decrease of exhausted CD8+T cells occurred following combination treatment compared with HS201-PDT monotherapy. Receptor-ligand interactome analysis showed marked enhancement of several pathways, such as CXCL, GALECTIN, GITRL, PECAM1 and NOTCH, associated with CD8+T cell activation in the combination group. Notably, the expression of the CXCR3 gene signature was the highest in the combination group, possibly explaining the enhanced tumor infiltration by T cells.

Conclusions

The increased antitumor activity and upregulated CXCR3 gene signature induced by the combination of anti-PD-L1 antibody with HS201-PDT warrants the clinical testing of HS201-PDT combined with PD-1/PD-L1 blockade in patients with breast cancer, and the use of the CXCR3 gene signature as a biomarker.
Heterogeneity on long-term disability trajectories in patients with secondary progressive MS: a latent class analysis from Big MS Data network
Authors: Signori Alessio , Lorscheider Johannes , Vukusic Sandra , Trojano Maria , Iaffaldano Pietro , Hillert Jan , Hyde Robert , Pellegrini Fabio , Magyari Melinda , Koch-Henriksen Nils , Sørensen Per Soelberg , Spelman Tim , van der Walt Anneke , Horakova Dana , Havrdova Eva , Girard Marc , Eichau Sara , Grand'Maison Francois , Gerlach Oliver , Terzi Murat , Ozakbas Serkan , Skibina Olga , Van Pesch Vincent , Sa Maria Jose , Prevost Julie , Alroughani Raed , McCombe Pamela A , Gouider Riadh , Mrabet Saloua , Castillo-Trivino Tamara , Zhu Chao , de Gans Koen , Sánchez-Menoyo José Luis , Yamout Bassem , Khoury Samia , Sormani Maria Pia , Kalincik Tomas , Butzkueven Helmut
Published: September 2022

Background

Over the decades, several natural history studies on patients with primary (PPMS) or secondary progressive multiple sclerosis (SPMS) were reported from international registries. In PPMS, a consistent heterogeneity on long-term disability trajectories was demonstrated. The aim of this study was to identify subgroups of patients with SPMS with similar longitudinal trajectories of disability over time.

Methods

All patients with MS collected within Big MS registries who received an SPMS diagnosis from physicians (cohort 1) or satisfied the Lorscheider criteria (cohort 2) were considered. Longitudinal Expanded Disability Status Scale (EDSS) scores were modelled by a latent class growth analysis (LCGA), using a non-linear function of time from the first EDSS visit in the range 3–4.

Results

A total of 3613 patients with SPMS were included in the cohort 1. LCGA detected three different subgroups of patients with a mild (n=1297; 35.9%), a moderate (n=1936; 53.6%) and a severe (n=380; 10.5%) disability trajectory. Median time to EDSS 6 was 12.1, 5.0 and 1.7 years, for the three groups, respectively; the probability to reach EDSS 6 at 8 years was 14.4%, 78.4% and 98.3%, respectively. Similar results were found among 7613 patients satisfying the Lorscheider criteria.

Conclusions

Contrary to previous interpretations, patients with SPMS progress at greatly different rates. Our identification of distinct trajectories can guide better patient selection in future phase 3 SPMS clinical trials. Additionally, distinct trajectories could reflect heterogeneous pathological mechanisms of progression.
Public interest in medical assistance in dying and palliative care
Authors: Cheng Emily YiQin , Mah Kenneth , Al-Awamer Ahmed , Pope Ashley , Swami Nadia , Wong Joanne L , Mathews Jean , Howell Doris , Hannon Breffni , Rodin Gary , Shapiro Gilla K , Li Madeline , Le Lisa W , Zimmermann Camilla
Published: September 2022

Objectives

Medical assistance in dying (MAiD) is legal in an increasing number of countries, but there are concerns that its availability may compromise access to palliative care. We assessed public interest in MAiD, palliative care, both, or neither, and examined characteristics associated with this interest.

Methods

We surveyed a representative sample of the adult Canadian public, accessed through a panel from May to June 2019. Weighted generalised multinomial logistic regression analyses were used to determine characteristics associated with interest in referral to palliative care, MAiD, or both, in the event of diagnosis with a serious illness.

Results

Of 1362 participants who had heard of palliative care, 611 (44.8% weighted (95% CI 42.1% to 47.5%)) would be interested in both MAiD and palliative care, 322 (23.9% (95% CI 21.5% to 26.2%)) palliative care alone, 171 (12.3% (95% CI 10.5% to 14.1%)) MAiD alone and 258 (19.0% (95% CI 16.9% to 21.2%)) neither. In weighted multinomial logistic regression analyses, interest in both MAiD and palliative care (compared with neither) was associated with better knowledge of the definition of palliative care, older age, female gender, higher education and less religiosity; interest in palliative care alone was associated with better knowledge of the definition of palliative care, older age, female gender and being married/common law; interest in MAiD alone was associated with less religiosity (all p<0.05).

Conclusions

There is substantial public interest in potential referral to both MAiD and palliative care. Simultaneous availability of palliative care should be ensured in jurisdictions where MAiD is legal, and education about palliative care should be a public health priority.
Deep white matter hyperintensity is spatially correlated to MRI-visible perivascular spaces in cerebral small vessel disease on 7 Tesla MRI
Authors: Huo Yajing , Wang Yilin , Guo Cen , Liu Qianyun , Shan Lili , Liu Mingyuan , Wu Haibo , Li Guanwu , Lv Huihui , Lu Lingdan , Zhou Yintin , Feng Jianfeng , Han Yan
Published: September 2022

Background

The association between perivascular space (PVS) and white matter hyperintensity (WMH) has been unclear. Normal-appearing white matter (NAWM) around WMH is also found correlated with the development of focal WMH. This study aims to investigate the topological connections among PVS, deep WMH (dWMH) and NAWM around WMH using 7 Tesla (7T) MRI.

Methods

Thirty-two patients with non-confluent WMHs and 16 subjects without WMHs were recruited from our department and clinic. We compared the PVS burden between patients with and without WMHs using a 5-point scale. Then, the dilatation and the number of PVS within a radius of 1 cm around each dWMH were compared with those of a reference site (without WMH) in the contralateral hemisphere. In this study, we define NAWM as an area within the radius of 1 cm around each dWMH. Furthermore, we assessed the spatial relationship between dWMH and PVS.

Results

Higher PVS scores in the centrum semiovale were found in patients with >5 dWMHs (median 3) than subjects without dWMH (median 2, p = 0.014). We found there was a greater dilatation and a higher number of PVS in NAWM around dWMH than at the reference sites (p<0.001, p<0.001). In addition, 79.59% of the dWMHs were spatially connected with PVS.

Conclusion

dWMH, NAWM surrounding WMH and MRI-visible PVS are spatially correlated in the early stage of cerebral small vessel disease. Future study of WMH and NAWM should not overlook MRI-visible PVS.
Demographic and functional responses of kit foxes to changes in prey abundance
Authors: Hodge Ashley E. , Gese Eric M. , Kluever Bryan M.
Published: September 2022

Many carnivores exhibit demographic and functional responses to changes in prey abundance. Demographic responses often include changes in population size, litter size, and recruitment of young into the adult population. Functional feeding responses are commonly reported for many carnivore species. We investigated demographic and functional responses of kit foxes ( Vulpes macrotis Merriam, 1888) to changes in prey abundance during 2010–2013 in western Utah, USA. Between 2010 and 2013, litter size averaged 3.9 (±1.4) pups/litter. Survival rates of kit fox pups were 0.07, 0.01, 0.46, and 0.16, respectively, and there was a correlation between pup survival rates and rodent abundance; leporid (family Leporidae Fischer, 1817) abundance did not influence pup survival. There was a functional response as occurrence of kangaroo rat in the diet closely followed changes in kangaroo rat abundance. The occurrence of rodents in kit fox diet followed declines in rodent abundance (excluding Dipodomys spp. Gray, 1841). Leporid consumption by kit foxes was not correlated to leporid density. Kit fox survival was dependent on rodent abundance and more specifically, kangaroo rats. Understanding which population parameters of kit foxes are influenced by prey is critical for the conservation of this native mesocarnivore.
Prospects for a flavour violating $$Z^\prime $$ explanation of $$\Delta a_{\mu ,e}$$
Authors: Kriewald J. , Orloff J. , Pinsard E. , Teixeira A. M.
Published: September 2022

The apparent tensions emerging from the comparison of experimental data of the anomalous magnetic moments of the muon and electron to the Standard Model predictions ($$\Delta a_{\mu ,e}$$

Δ

a

μ
,
e

) could be interpreted as a potential signal of New Physics. Models encompassing a light vector boson have been known to offer a satisfactory explanation to $$\Delta a_{\mu }$$

Δ

a
μ

, albeit subject to stringent experimental constraints. Here we explore a minimal extension of the Standard Model via a leptophilic vector boson $$Z^\prime $$

Z
′

, under the hypothesis of strictly flavour-violating couplings of the latter to leptons. The most constraining observables to this ad-hoc construction emerge from lepton flavour universality violation (in Z and $$\tau $$
τ
decays) and from rare charged lepton flavour violating transitions. Once these are accommodated, one can saturate the tensions in $$\Delta a_{\mu }$$

Δ

a
μ

, but $$\Delta a_{e}$$

Δ

a
e

is predicted to be Standard Model-like. We infer prospects for several observables, including leptonic Z decays and several charged lepton flavour violating processes. We also discuss potential signatures of the considered $$Z^\prime $$

Z
′

at a future muon collider, emphasising the role of the $$\mu ^+\mu ^- \rightarrow \tau ^+\tau ^- $$

μ
+

μ
-

→

τ
+

τ
-

forward-backward asymmetry as a key probe of the model.
Effect of large light-heavy neutrino mixing and natural type-II seesaw dominance to lepton flavor violation and neutrinoless double beta decay
Authors: Dash Nitali , Patra Sudhanwa , Pritimita Prativa , Yajnik Urjit A.
Published: September 2022

We derive the lower bound on absolute scale of lightest neutrino mass for normal hierarchy and inverted hierarchy pattern of light neutrinos by studying the new physics contributions to charged lepton flavour violations in the framework of a TeV scale left–right symmetric model. In the model the fermion sector comprises of the usual quarks and leptons plus a fermion singlet per generation and the scalar sector consists of isospin doublets, triplets and a bidoublet. The framework allows large light-heavy neutrino mixing where the light neutrino mass formula is governed by natural type-II seesaw mechanism unlike the generic type-II seesaw dominance which assumes suppressed light-heavy neutrino mixing. We demonstrate how sizeable loop-induced contribution to light neutrino mass is kept under control such that light neutrino mass formula is dominantly explained by type-II seesaw mechanism. We examine the heavy neutrino contributions with large light-heavy neutrino mixing to charged lepton flavour violating processes like $$\mu \rightarrow e \gamma $$

μ
→
e
γ

, $$\mu \rightarrow 3 e$$

μ
→
3
e

and $$\mu \rightarrow e$$

μ
→
e

conversion inside a nuclei. We present a complementary study between neutrinoless double beta decay and charged lepton flavour violation taking into account single beta decay bound, double beta decay bound and cosmology bounds on neutrino mass sum.
South and East African fracture zones: a long lifespan since the breakup of Gondwana
Authors: Roche V. , Ringenbach J.-C. , Sapin F. , Leroy S.
Published: September 2022

Gondwana started to split up during the Early Jurassic (
c.
180 Ma) with the separation of Antarctica and Madagascar from Africa, followed by the separation of South America and Africa during the Early Cretaceous. Thanks to recent seismic profiles, the architecture of rifted margins and the transform fault zones, which developed as a result of the relative motion between tectonic plates, have been recently evidenced and studied along the whole eastern and southeastern Africa margins (i.e. in the Western Somali Basin, the Mozambique Basin, the Natal Basin and the Outeniqua Basin). But, the structure and overall kinematic evolution of the three major transform fault zones – such as the Agulhas, the Davie and the Limpopo fracture zones (FZ) – that together control the opening of major oceanic basins (Antarctic Ocean, Weddell Sea and Austral South Atlantic) remain poorly studied. The interpretation of an extensive regional multi-channel seismic dataset coupled with recent studies allows us to propose a detailed regional synthesis of the crustal domains and major structural elements of the rifted margins along the whole eastern and southeastern Africa. We provide new constraints on the structure and evolution of these three transform systems. Although our findings indicate common features in transform style (e.g. a right-lateral transform system, a wide sheared corridor), the deformation and magmatism along these systems appear quite different. In particular, our results show that the Davie and Agulhas transform faults postdate the development of the rift zone-controlling faults, whereas the Limpopo margin seems to be a simple intra-continental transform. Moreover, the Davie and Agulhas FZ recorded spectacular inversions during the transform stage, whereas transtensional deformation is developed along the Limpopo FZ. This different style of deformation may be explained by two main forcing parameters: (i) the far-field forces that may induce a rapid change of regional tectonic stress and (ii) the magmatic additions that modify mainly the crustal rheology. In the post-drift history, several reactivations of transform fault zones are recorded, implying that some transform margins are excellent recorders of large plate kinematic changes. Such reactivations can serve also as drains for magmatic fluids in the vicinity of hotspots emplacement.
Underground energy-related product storage and sequestration: site characterization, risk analysis and monitoring
Authors: Schultz Richard A. , Williams-Stroud Sherilyn , Horváth Birgit , Wickens John , Bernhardt Heike , Cao Wenzhuo , Capuano Paolo , Dewers Thomas A. , Goswick Raven A. , Lei Qinghua , McClure Mark , Prasad Umesh , Schwartz Brandon A. , Yu Haitao , Voegeli Samuel , Zhao Qi
Published: September 2022

This paper presents a high-level overview of site characterization, risk analysis and monitoring priorities for underground energy-related product storage or sequestration facilities. The siting of an underground storage or sequestration facility depends on several important factors beginning with the area of review. Collection of all existing and available records and data from within the rock volume, including potential vulnerabilities such as prior containment issues, proximity to infrastructure and/or population centres, must be evaluated. Baselining of natural processes before storage or sequestration operations begin provides the basis for assessing the effects of storage or sequestration on the surroundings. These initial investigations include geological, geophysical and geochemical analyses of the suitability of the geological host rock and environs for storage or sequestration. A risk analysis identifies and evaluates threats and hazards, the potential impact should they develop into unwanted circumstances or events and the consequences to the facility should any of them occur. This forms the basis for framing effective mitigation measures. A comprehensive monitoring programme that may include downhole well surveillance, observation wells, geochemical sampling and well testing ensures that the facility operates as designed and that unforeseen issues, such as product migration or loss of integrity, can be identified and mitigated. In addition to these technical issues, human factors and public perception of a project are a critical part of the site characterization, construction and operational phases of a project. Despite differences between underground storage and sequestration, the characterization, risk analysis and monitoring approaches that were developed for underground natural gas storage or for carbon dioxide sequestration could be used for underground storage or sequestration of any type of energy-related product. Recommendations from this work include: (1) develop an industry-standard evaluation protocol (workflow) for the evaluation of salt beds, saline aquifers, depleted hydrocarbon reservoirs, underground mines and cased wellbores for potential underground storage or sequestration development beyond those in use today; and (2) develop an industry-wide collaborative process whereby incident and near-miss data related to underground storage or sequestration operations can be reported, documented and shared for use in refining risk analysis modelling.
Towards a dynamic and sustainable management of geological resources
Authors: Compernolle Tine , Eswaran Adithya , Welkenhuysen Kris , Hermans Thomas , Walraevens Kristine , van Camp Marc , Buyle Matthias , Audenaert Amaryllis , Bleys Brent , van Schoubroeck Sophie , Bergmans Anne , Goderniaux Pascal , Baele Jean-Marc , Kaufmann Olivier , Vardon Phil J. , Daniilidis Alex , Orban Philippe , Dassargues Alain , Serge Brouyère , Piessens Kris
Published: September 2022

The subsurface provides multiple resources, the exploitation of which has a lasting impact on future potential provision. Establishing sustainability in terms of fundamental principles, and fitting these principles into a practical framework, is an ongoing endeavour focused mainly on surface activities. The principles of ecological economics lead to six challenges that summarize the current limitations of implementing science-based sustainable management of geological resources in the medium to deep subsurface: integrating value pluralism, defining sustainable scale, evaluating interferences in the subsurface, guaranteeing environmental justice, optimizing environmental and economic efficiency and handling uncertainties. Assessing and managing geological reservoirs is particularly challenging because of slow resource regeneration, complex spatial and temporal interactions, concealment and naturally dictated opportunities. In answer to the challenges, visions are proposed that outline how an indicator framework is needed for guidance, how indicators require reservoir models with extended spatial and temporal scope, how differences in social values in relation to the environment are to be considered and how real option games combined with life cycle assessment can be used for optimizing efficiency. These individual solutions relate to different facets of the same problem, and can be integrated into one overarching solution that takes the form of dynamic multi-criteria decision analysis.
A
Solicitous
Approach to Smart Contract Verification
Authors: Otoni Rodrigo , Marescotti Matteo , Alt Leonardo , Eugster Patrick , Hyvärinen Antti , Sharygina Natasha
Published: September 2022

Smart contracts are tempting targets of attacks, as they often hold and manipulate significant financial assets, are immutable after deployment, and have publicly available source code, with assets estimated in the order of millions of dollars being lost in the past due to vulnerabilities. Formal verification is thus a necessity, but smart contracts challenge the existing highly efficient techniques routinely applied in the symbolic verification of software, due to specificities not present in general programming languages. A common feature of existing works in this area is the attempt to reuse off-the-shelf verification tools designed for general programming languages. This reuse can lead to inefficiency and potentially unsound results, as domain translation is required. In this article, we describe a carefully crafted approach that directly models the central aspects of smart contracts natively, going from the contract to its logical representation without intermediary steps. We use the expressive and highly automatable logic of constrained Horn clauses for modeling and instantiate our approach to the Solidity language. A tool implementing our approach, called
Solicitous
, was developed and integrated into the SMTChecker module of the Solidity compiler solc. We evaluated our approach on an extensive benchmark set containing 22,446 real-world smart contracts deployed on the Ethereum blockchain over a 27-month period. The results show that our approach is able to establish safety of significantly more contracts than comparable, publicly available verification tools, with an order of magnitude increase in the percentage of formally verified contracts.
Theoretical and Empirical Analysis of Parameter Control Mechanisms in the (1 + (λ, λ)) Genetic Algorithm
Authors: Hevia Fajardo Mario Alejandro , Sudholt Dirk
Published: September 2022

The self-adjusting (1 + (λ, λ)) GA is the best known genetic algorithm for problems with a good fitness-distance correlation as in
OneMax
. It uses a parameter control mechanism for the parameter λ that governs the mutation strength and the number of offspring. However, on multimodal problems, the parameter control mechanism tends to increase λ uncontrollably.

We study this problem for the standard
Jump

k

benchmark problem class using runtime analysis. The self-adjusting (1 + (λ, λ)) GA behaves like a (1 + 
n
)  EA whenever the maximum value for λ is reached. This is ineffective for problems where large jumps are required. Capping λ at smaller values is beneficial for such problems. Finally, resetting λ to 1 allows the parameter to cycle through the parameter space. We show that resets are effective for all
Jump

k

problems: the self-adjusting (1 + (λ, λ)) GA performs as well as the (1 + 1) EA with the optimal mutation rate and evolutionary algorithms with heavy-tailed mutation, apart from a small polynomial overhead.

Along the way, we present new general methods for translating existing runtime bounds from the (1 + 1) EA to the self-adjusting (1 + (λ, λ)) GA. We also show that the algorithm presents a bimodal parameter landscape with respect to λ on
Jump

k

. For appropriate
n
and
k
, the landscape features a local optimum in a wide basin of attraction and a global optimum in a narrow basin of attraction. To our knowledge this is the first proof of a bimodal parameter landscape for the runtime of an evolutionary algorithm on a multimodal problem.
Biased Agonism: Lessons from Studies of Opioid Receptor Agonists
Authors: Kelly Eamonn , Conibear Alexandra , Henderson Graeme
Published: September 2022

In ligand bias different agonist drugs are thought to produce distinct signaling outputs when activating the same receptor. If these signaling outputs mediate therapeutic versus adverse drug effects, then agonists that selectively activate the therapeutic signaling pathway would be extremely beneficial. It has long been thought that μ-opioid receptor agonists that selectively activate G protein– over β-arrestin-dependent signaling pathways would produce effective analgesia without the adverse effects such as respiratory depression. However, more recent data indicate that most of the therapeutic and adverse effects of agonist-induced activation of the μ-opioid receptor are actually mediated by the G protein–dependent signaling pathway, and that a number of drugs described as G protein biased in fact may not be biased, but instead may be low-intrinsic-efficacy agonists. In this review we discuss the current state of the field of bias at the μ-opioid receptor and other opioid receptor subtypes.
Benchmarking Solid-State Batteries Containing Sulfide Separators: Effects of Electrode Composition and Stack Pressure
Authors: Self Ethan C. , Tsai Wan-Yu , Westover Andrew S. , Browning Katie L. , Yang Guang , Nanda Jagjit
Published: September 2022

Integrating sulfide separators into solid-state batteries (SSBs) containing high energy cathodes typically requires one or more materials and engineering solutions including: (i) applying interfacial coatings to mitigate electrolyte decomposition, (ii) applying high stack pressures to form robust solid-solid contacts, and (iii) using alloying anodes to avoid Li dendrite formation. Despite the promise of these approaches, a lack of standardized testing protocols makes it difficult to directly compare results among different studies. To address this problem, the present work benchmarks the performance of SSBs containing β-Li3PS4 (LPS) separators and composite cathodes. By systematically varying the anode/cathode composition and stack pressure, this work demonstrates that cathode design is a major bottleneck for solid-state cells cycled at low rates (<100 µA cm-
2). Operando stack pressure measurements show that, while mechanical confinement generally promotes higher active material utilization and cycling stability, this strategy alone does not address interfacial reactivity between LPS and high voltage cathodes. These results also demonstrate that stress evolution during cycling is dominated by volume changes at the Li metal anode. Finally, we show that FeS2 cathodes with moderate operating voltages (<3 V vs Li/Li+) exhibit superior cycling performance compared to high voltage cathodes by facilitating formation of stable cathode/electrolyte interfaces.
A serotonin-deficient rat model of neurogenic hypertension: influence of sex and sympathetic vascular tone
Authors: Spinieli Richard L. , Cornelius-Green Jennifer , Cummings Kevin J.
Published: September 2022

We show that hypertension is evident in female 5-HT-deficient TPH2−/− rats when sex hormones are controlled, an effect most evident upon the transition to REM sleep. In addition, our data strongly suggest that increased sympathetic vascular tone contributes to the hypertension present in this 5-HT-deficient model of neurogenic hypertension.
A Novel Computer Vision Model for Medicinal Plant Identification Using Log-Gabor Filters and Deep Learning Algorithms
Authors: Oppong Stephen Opoku , Twum Frimpong , Hayfron-Acquah James Ben , Missah Yaw Marfo
Published: September 2022

Computer vision is the science that enables computers and machines to see and perceive image content on a semantic level. It combines concepts, techniques, and ideas from various fields such as digital image processing, pattern matching, artificial intelligence, and computer graphics. A computer vision system is designed to model the human visual system on a functional basis as closely as possible. Deep learning and Convolutional Neural Networks (CNNs) in particular which are biologically inspired have significantly contributed to computer vision studies. This research develops a computer vision system that uses CNNs and handcrafted filters from Log-Gabor filters to identify medicinal plants based on their leaf textural features in an ensemble manner. The system was tested on a dataset developed from the Centre of Plant Medicine Research, Ghana (MyDataset) consisting of forty-nine (49) plant species. Using the concept of transfer learning, ten pretrained networks including Alexnet, GoogLeNet, DenseNet201, Inceptionv3, Mobilenetv2, Restnet18, Resnet50, Resnet101, vgg16, and vgg19 were used as feature extractors. The DenseNet201 architecture resulted with the best outcome of 87% accuracy and GoogLeNet with 79% preforming the worse averaged across six supervised learning algorithms. The proposed model (OTAMNet), created by fusing a Log-Gabor layer into the transition layers of the DenseNet201 architecture achieved 98% accuracy when tested on MyDataset. OTAMNet was tested on other benchmark datasets; Flavia, Swedish Leaf, MD2020, and the Folio dataset. The Flavia dataset achieved 99%, Swedish Leaf 100%, MD2020 99%, and the Folio dataset 97%. A false-positive rate of less than 0.1% was achieved in all cases.
IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing
Authors: Wang Lin , Wang Guangying , Chen Jingxu
Published: September 2022

When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree.
Design of Artificial Intelligence-Based English Network Teaching (AI-ENT) System
Authors: Liu Xing , Huang Xiaoyin
Published: September 2022

The English teaching network system uses the Internet to provide distance education. There are several challenges in teaching, including a lack of knowledge and expertise, expectations from students, lack of facilities, and unfavourable opinions about the process of English teaching and learning. In the era of information, education combines the advantages of both online and offline learning, including conventional and networked learning. The production of test pattern paper is an important part of the English teaching network since it helps students study independently. In this study, the artificial intelligence-based English network teaching (AI-ENT) method has been suggested to enhance the student’s performance in distance education. There are strong indicators that the methods of teaching and learning and the teaching tools used by machine learning can be fundamentally altered by AI. With AI technology tools and teacher coaching, students can make significant progress in their English learning experiences. Artificial intelligence expert system thinking is reflected in this design. Teachers and students can improve their English proficiency by gaining access to relevant data from a wide range of sources. The system’s test application reveals that it can assist students in increasing their learning efficiency and making learning information more relevant.
COVID-19 Whole-Genome Resequencing with Redundant Tiling PCR and Subtract-Based Amplicon Normalization Successfully Characterized SARS-CoV-2 Variants in Clinical Specimens
Authors: Sugi Tatsuki , Rahman Mizanur , Rahim Rummana , Hasan Abu , Kawai Naoko , Hayashida Kyoko , Yamagishi Junya
Published: September 2022

With an increasing number of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) sequences gathered worldwide, we recognize that deletion mutants and nucleotide substitutions that may affect whole-genome sequencing are accumulating. Here, we propose an additional strategy for tiling PCR for whole-genome resequencing, which can make the pipeline robust for mutations at the primer annealing site by a redundant amplicon scheme. We further demonstrated that subtracting overrepresented amplicons from the multiplex PCR products reduced the bias of the next-generation sequencing (NGS) library, resulting in decreasing required sequencing reads per sample. We applied this sequencing strategy to clinical specimens collected in Bangladesh. More than 80% out of the 304 samples were successfully sequenced. Less than 5% were ambiguous nucleotides, and several known variants were detected. With the additional strategies presented here, we believe that whole-genome resequencing of SARS-CoV-2 from clinical samples can be optimized.
A Framework and Algorithm for Human-Robot Collaboration Based on Multimodal Reinforcement Learning
Authors: Cai Zeyuan , Feng Zhiquan , Zhou Liran , Ai Changsheng , Shao Haiyan , Yang Xiaohui
Published: September 2022

Despite the emergence of various human-robot collaboration frameworks, most are not sufficiently flexible to adapt to users with different habits. In this article, a Multimodal Reinforcement Learning Human-Robot Collaboration (MRLC) framework is proposed. It integrates reinforcement learning into human-robot collaboration and continuously adapts to the user's habits in the process of collaboration with the user to achieve the effect of human-robot cointegration. With the user's multimodal features as states, the MRLC framework collects the user's speech through natural language processing and employs it to determine the reward of the actions made by the robot. Our experiments demonstrate that the MRLC framework can adapt to the user's habits after repeated learning and better understand the user's intention compared to traditional solutions.
Finite Population Mean Estimation Under Systematic Sampling Scheme in Presence of Maximum and Minimum Values Using Two Auxiliary Variables
Authors: El-Morshedy Mahmoud , Hussain Sardar , Ullah Kalim , Khalil Alamgir , Shabbir Javid , Mansoor Wahidullah
Published: September 2022

The purpose of this paper is to look at how to estimate the finite population mean utilizing information from the auxiliary variable on a systematic sampling technique. By integrating the study variable’s maximum and minimum values, as well as two auxiliary variables, we offer estimators of the ratio, product, and regression types. The mathematical equations of the suggested and existing estimators are derived up to the first order of approximation. Based on real-life data sets, efficiency comparisons are carried out. The suggested ratio, product and regression estimators consistently outperform existing estimators in terms of mean square error, according to theoretical and empirical investigations.
Influence of Pretreatment System on Inorganic Suspended Solids for Influent in Wastewater Treatment Plant
Authors: He Li , Zhang Yong , Song Dan , Ou Zhongwen , Xie Zhigang , Yang Subo , Guan Wei , Dong Cunlan , Zhang Yifu
Published: September 2022

In order to investigate the cause of accumulation of the inorganic suspended solid (ISS) in biochemical tank for wastewater treatment plant (WWTP) in recent years, the influent quality of one WWTP in Chongqing was monitored in one year, and the removal efficiency of ISS during the pretreatment process was studied. Results showed that the low removal efficiency of ISS (<7%) was ascribed to the weak removal efficiency of sand in the grit chamber. The primary sedimentation tank showed a good removal efficiency of ISS up to 69% and also had a good removal efficiency of COD up to 70%. The annual variation rule of MLVSS/MLSS for mixed liquor varied in contrast to the influent quality, ranging from 0.24 to 0.57, much lower than the normal value of 0.7. In order to maintain the normal function of activated sludge, it is necessary to retain the primary sedimentation tank to remove ISS.
Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network
Authors: Lu Yao , Cheng Shuo , Zhu Xiaofei , Yang Geon Seok
Published: September 2022

The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically.
Thanatophoric Dysplasia: A Report of 2 Cases with Antenatal Misdiagnosis
Authors: Audu Lamidi , Gambo Amina , Baduku Tokan Silas , Farouk Bilkisu , Yahaya Anisa , Jacob Kefas
Published: September 2022

Thanatophoric dysplasia (TD) is a rare but uniformly lethal inherited disorder of the skeletal system resulting from defects in the fibroblast growth factor receptor-3 gene on the short arm of chromosome ##4. It is characterised by pronounced shortening of the tubular bones resulting in significant short stature, macrocephaly, a funnel-shaped chest, protuberant abdomen, redundant skin in the limbs, and typical facies among others. The two clinical types of TD are differentiated by typical cranial and tubular bone configurations. Antenatal diagnosis is usually made in the last trimester and corroborated at birth. We present 2 cases of TD seen at Barau Dikko Teaching Hospital (BDTH) between January and August 2021 to highlight the potential difficulty with antenatal diagnosis, its diagnostic features, and associated early postnatal fatality. The antenatal diagnosis was missed in both cases in spite of repeated 2nd and 3rd-trimester sonographic examinations. Both babies presented with remarkable micromelic short stature with the telephone-handle appearance of the femoral bones characteristic of type 1 TD, developed progressive respiratory distress at birth, and died within 36 hours of life despite respiratory support with Bubble CPAP. These cases are discussed along with a review of existing relevant literature.
Diagnostic Value Comparison between Multislice Spiral Computerized Tomography and Magnetic Resonance Imaging under Artificial Intelligence Algorithm in Diagnosing Occult Fractures of the Knee Joint
Authors: Shu Zhenghua , Lei Jun , Ding Chaoqi
Published: September 2022

The aim of this study was to explore the application value of multislice spiral computerized tomography (MSCT) and magnetic resonance imaging (MRI) under intelligent algorithm in the diagnosis of occult fractures of the knee joint (OFKJ). 47 patients with negative X‐ray examination and suspected fracture were included for this research. According to the examination methods, the patients were divided into the MSCT group and MRI group. The diagnostic results of the two methods were compared, and then compared with the traditional algorithm to explore their superiorities. The results demonstrated that the algorithm applied in this study had a clearer segmentation than traditional algorithms, and it run significantly faster than other algorithms. The results of MSCT, MRI, and pathological examination were all different, but which was of no statistical significance, P > 0.05. The specificity, accuracy, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) of MSCT were 83%, 96%, 94%, and 98%, respectively; and its coincidence rate, missed diagnosis rate, and misdiagnosis rate were 98.20%, 1.60%, and 0.20%, respectively. Compared with MRI, the differences were significant statistically, P < 0.05. The segmentation effect of MSCT was closer to the standard segmentation, with the higher efficiency. MSCT under the intelligent algorithm produced the better diagnostic performance and the higher detection rate than MRI in diagnosing OFKJ. It could be used for clinical auxiliary diagnosis and evaluation of OFKJ, deserving an application value.
On a Conjecture about the Saturation Number of Corona Product of Graphs
Authors: Tavakoli Mostafa
Published: September 2022

Let G = (VG, EG) be a simple and connected graph. A set M⊆EG is called a matching if no two edges of M have a common endpoint. A matching M is maximal if it cannot be extended to a larger matching in G. The smallest size of a maximal matching is called the saturation number of G. In this paper, we confirm a conjecture of Alikhani and Soltani about the saturation number of corona product of graphs. We also present the exact value of s(G∘H) where H is a randomly matchable graph.
[Retracted] Expression of SR‐BI and LXRα in Macrophage Origin Foam Cells of Mouse RAW264.7 Up‐regulated by Astragalus Polysaccharide
Authors: Yan Lichen , Guo Jing , Gao Xiaohua
Published: September 2022

Objective. To investigate the influences of Astragalus polysaccharides (APS) on the expressions of SR‐BI(Scavenger receptor‐BI) and LXR α in RAW264.7 macrophage origin foam cells. Methods. Mouse RAW264.7 cells were induced in foam cells and identification of the foamed by oil‐red O staining. The RAW264.7 macrophage origin foam cells were dealt with APS with distinct contents (0, 10, 20, 50, or 100 mg/L). The mRNA and protein expressions of SR‐BI and LXRα were measured by RT‐PCR as well as ELISA, respectively. Results. Macrophages were differentiated into foam cells 48 h after ox‐LDL induction. In contrast to the control part, the mRNA and protein expressions of SR‐BI and LXRα in RAW264.7 macrophage origin foam cells were up‐regulated dosage‐dependently after being treated with different concentrations of APS (P < 0.05). Conclusion. APS could promote intracellular cholesterol efflux by up‐regulating the expressions of SR‐BI and LXR α of RAW264.7 cells.