bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of nurse‐led digital health interventions on blood pressure control for people with hypertension: A systematic review and meta‐analysis
Authors: Hwang Misun , Chang Ae Kyung
Published: March 2023

Purpose

Nurse‐led digital health interventions (DHIs) for people with chronic disease are increasing. However, the effect of nurse‐led DHIs on blood pressure control and hypertension self‐management remains unclear. This study aimed to identify the characteristics of nurse‐led DHIs for people with hypertension and compared the effect size of nurse‐led DHIs with that of usual care to establish evidence for the development of effective nursing interventions using technologies.

Design

Systematic review and meta‐analysis.

Methods

This systematic review and meta‐analysis followed the Preferred Reporting Items for Systematic Reviews of Intervention (PRISMA) guidelines and registered the protocol in PROSPERO. Studies published from 2000 to August 5, 2021, were searched using the international databases: PubMed; Embase; Cochrane Central Register of Controlled Trials; Web of Science; CINAHL; Korean databases: RISS, KISS, KMBASE; and NDSL. Risk of bias 2.0 was used for evaluating the quality of studies. The primary outcome was blood pressure control. The secondary outcomes were self‐management, medication adherence, and diet adherence. Publication bias was assessed using the funnel plot and Egger's regression tests.

Findings

The systematic review included 26 studies. A meta‐analysis of 21 studies was conducted to calculate the effect size and identify heterogeneity among the included studies. In our meta‐analysis, we observed that nurse‐led DHIs reduced systolic blood pressure by 6.49 mmHg (95% confidence interval [CI]: −8.52 to −4.46, I2 = 75.4%, p < 0.05) and diastolic blood pressure by 3.30 mmHg (95% CI: −4.58 to −2.01, I2 = 70.3%, p < 0.05) when compared with usual care. Concerning secondary outcomes, the effect size on self‐management, medication adherence, and diet adherence was 0.98 (95% CI: 0.58 to 1.37, I2 = 63.2%, p < 0.05), 1.05 (95% CI: 0.41 to 1.69, I2 = 92.5%, p < 0.05), and 0.80 (95% CI: 0.17 to 1.42, I2 = 80.5%, p < 0.05), respectively.

Conclusion

Nurse‐led DHIs were more effective in reducing blood pressure and enhancing self‐management than usual care among people with hypertension. Therefore, as new technologies are being rapidly developed and applied in healthcare systems, further studies and policy support are needed to utilize the latest digital innovations with nursing interventions.

Clinical relevance

This study could be used to identify that nurse‐led interventions may take advantage of real‐time communication by employing digital technologies for improving blood control and self‐management behaviors such as medication adherence and diet adherence. Using nurse‐led DHIs allows nurses to provide patient‐centered interventions such as reflecting on patients' needs and shared decision‐making without space constraints and limited treatment time.
Normative data for macular and retinal nerve fibre layer thickness in healthy German children and adolescents using optical coherence tomography
Authors: Söhnel Tanja , Meigen Christof , Hiemisch Andreas , Wahl Siegfried , Ziemssen Focke , Truckenbrod Carolin , Hübner Katharina , Kiess Wieland
Published: March 2023

Purpose

To establish normative data for macular thickness, macular volume and peripapillary retinal nerve fibre layer (RNFL) thickness using Spectralis® spectral‐domain optical coherence tomography (SD‐OCT) in healthy German children and adolescents and investigate influencing factors.

Methods

The cross‐sectional study included the right eye of 695 children with at least one complete retinal OCT scan. As part of the LIFE Child study, the children underwent an ophthalmological examination including axial length (AL), spherical equivalent (SE) and OCT measurements. Various questionnaires were answered by the children or their parents to identify media use or outdoor time. Multiple linear regression models were used to investigate the potential influencing factors.

Results

A total of 342 boys and 353 girls with an average age (SD) of 12.91 (3.29) years participated. The mean AL (SD) was 23.20 (0.86) mm. The mean macular thickness (SD) was 320.53 (12.29) μm and the mean RNFL thickness (SD) was 102.88 (8.79) μm. Statistical analysis revealed a significant correlation between average macular thickness and age (p < 0.001, β = 0.77) as well as AL (p < 0.001, β = −4.06). In addition, boys had thicker maculae (p < 0.001, β = 5.36). The RNFL thickness showed no significant correlation with children's age (p > 0.05), but with AL (p = 0.002, β = −2.15), birth weight (p = 0.02, β = 0.003) and a gender‐specific effect of the body mass index standard deviation score for male participants (p = 0.02, β = 1.93).

Conclusion

This study provides normative data and correlations between macular and RNFL thickness in healthy German children. Especially age, gender and AL must be taken into account when evaluating quantitative OCT measurements to classify them as normal.
Restricting the T‐schema to solve the liar
Authors: Warren Jared
Published: March 2023

If we want to retain classical logic and standard syntax in light of the liar, we are forced to restrict the T‐schema. The traditional philosophical justification for this is sentential – liar sentences somehow malfunction. But the standard formal way of implementing this is conditional, our T‐sentences tell us that if “p” does not malfunction, then “p” is true if and only if p. Recently Bacon and others have pointed out that conditional T‐restrictions like this flirt with incoherence. If we want to keep the “malfunction” motivation, our only other option is to non‐conditionally restrict the T‐schema, but Field and others have given powerful philosophical and technical arguments against this kind of approach. Here I argue that if we really take the philosophical motivation for restricting T‐sentences seriously, we can explain why conditional restrictions fail, answer Field's argument, and reason in a coherent way about truth using a non‐conditional restriction strategy. This cracks the door open for a fully classical response to the liar and related paradoxes. In closing, I argue that, when properly understood, this kind of “restriction” is not really a restriction at all. If this is right, then the holy grail of liar studies (classical logic, naïve truth, and standard syntax) may yet be attainable.
Everyday geographies of market transition: Agro‐science, socio‐technical relations, and the contingencies of market making in peri‐urban Lhasa, Tibet
Authors: Qian Junxi , Zhang Han , Liu Yajing
Published: March 2023

State‐promoted and market‐oriented horticultural production has fundamentally reshaped land use and agricultural economy in peri‐urban Lhasa, Tibet Autonomous Region, China. This paper examines two scenarios amidst this transformation. In the first, peri‐urban land has been valorised for vegetable production through the erection of greenhouses and the introduction of agronomic science. However, Tibetans refrain from participating directly, preferring to lease the land to Han migrants, and citing structural inequalities between Han and Tibetans and Tibetan work ethic as explanation. In the second, the municipal government is more proactive in introducing agro‐science and providing technical training to enrol Tibetans. However, the participation of Tibetans is selective and partial, contingent on the same non‐market rationalities that Tibetans invoke to justify non‐participation in the first scenario. This paper explicates the diverging modes of participation for Tibetans by engaging with the Callonian approach on economisation and marketisation, and interrogating how socio‐technical relations established among humans, material infrastructure and agro‐science culminate in variegated calculative and non‐calculative agencies. Focusing in particular on the structural relations and cultural conventions that frustrate the unilinear enactment of a market order, this study contributes to the geographies of marketisation in two ways. First, it works with an analytical framework centred on the ongoing dynamic of framing, overflowing and reframing to argue that the marketisation approach can be expanded to account for the encounters between market agencements and local socio‐cultural contingencies. Geographically, second, it also contributes to the agenda of interrogating diverse market variants and the richness of economic differences in real space‐times.
Weed suppression by cereals: Beyond ‘competitive ability’
Authors: Weiner Jacob
Published: March 2023

Much research on cereal‐weed competition has been directed towards finding cultivars that have high ‘competitive ability’ with weeds. I argue that this objective is insufficient, because weed suppression is usually the result of interactions among genotype, environment and management rather than direct effects of genotype, and this limits the usefulness of competitive ability as a general concept. The clearest example of this is the effect of cereal crop density. Cultivars of wheat and maize that compete best with weeds are often different at high versus low crop density. This is especially relevant because effective weed suppression, a reduction of weed growth to very low levels by competition from the crop, is only possible at high crop density and spatial uniformity. The potential for improving weed suppression by crops under standard regional management practices, which are usually based on weed‐free conditions, is limited, and there is likely to be a significant cost in yield. To make major improvements in weed suppression and thereby reduce greatly our dependence on chemical weed control, researchers should focus more on management strategies that benefit the crop in competition with weeds, and then on traits that improve weed suppression under the relevant management regime, rather than considering differences in management as a form of environmental variation and looking for traits promoting general competitive ability.
Quantum metrology in a lossless Mach–Zehnder interferometer using entangled photon inputs for a sequence of non-adaptive and adaptive measurements
Authors: Sadugol Shreyas , Kaplan Lev
Published: March 2023

Using multi-photon entangled input states, we estimate the phase uncertainty in a noiseless Mach–Zehnder interferometer using photon-counting detection. We assume a flat prior uncertainty and use Bayesian inference to construct a posterior uncertainty. By minimizing the posterior variance to get the optimal input states, we first devise an estimation and measurement strategy that yields the lowest phase uncertainty for a single measurement. N00N and Gaussian states are determined to be optimal in certain regimes. We then generalize to a sequence of repeated measurements, using non-adaptive and fully adaptive measurements. N00N and Gaussian input states are close to optimal in these cases as well, and optimal analytical formulae are developed. Using these formulae as inputs, a general scaling formula is obtained, which shows how many shots it would take on average to reduce phase uncertainty to a target level. Finally, these theoretical results are compared with a Monte Carlo simulation using frequentist inference. In both methods of inference, the local non-adaptive method is shown to be the most effective practical method to reduce phase uncertainty.
Modeling the effect of linguistic predictability on speech intelligibility prediction
Authors: Edraki Amin , Chan Wai-Yip , Fogerty Daniel , Jensen Jesper
Published: March 2023

Many existing speech intelligibility prediction (SIP) algorithms can only account for acoustic factors affecting speech intelligibility and cannot predict intelligibility across corpora with different linguistic predictability. To address this, a linguistic component was added to five existing SIP algorithms by estimating linguistic corpus predictability using a pre-trained language model. The results showed improved SIP performance in terms of correlation and prediction error over a mixture of four datasets, each with a different English open-set corpus.
Biomolecular glass with amino acid and peptide nanoarchitectonics
Authors: Xing Ruirui , Yuan Chengqian , Fan Wei , Ren Xiaokang , Yan Xuehai
Published: March 2023

Glass is ubiquitous in life and widely used in various fields. However, there is an urgent need to develop biodegradable and biorecyclable glasses that have a minimal environmental footprint toward a sustainable society and a circular materials economy. Here, we report a family of eco-friendly glasses of biological origin fabricated using biologically derived amino acids or peptides through the classic heating-quenching procedure. Amino acids and peptides with chemical modification at their ends are found able to form a supercooled liquid before decomposition and eventually glass upon quenching. These developed glasses exhibit excellent glass-forming ability and optical characteristics and are amenable to three-dimensional–printed additive manufacturing and mold casting. Crucially, the glasses show biocompatibility, biodegradability, and biorecyclability beyond the currently used commercial glasses and plastic materials.
Chiral Kondo lattice in doped MoTe
2
/WSe
2
bilayers
Authors: Guerci Daniele , Wang Jie , Zang Jiawei , Cano Jennifer , Pixley J. H. , Millis Andrew
Published: March 2023

We theoretically study the interplay between magnetism and a heavy Fermi liquid in the AB-stacked transition metal dichalcogenide bilayer system, MoTe
2
/WSe
2
, in the regime in which the
Mo
layer supports localized magnetic moments coupled by interlayer electron tunneling to a weakly correlated band of itinerant electrons in the
W
layer. We show that the interlayer electron transfer leads to a chiral Kondo exchange, with consequences including a strong dependence of the Kondo temperature on carrier concentration and anomalous Hall effect due to a topological hybridization gap. The theoretical model exhibits two phases, a small Fermi surface magnet and a large Fermi surface heavy Fermi liquid; at the mean-field level, the transition between them is first order. Our results provide concrete experimental predictions for ongoing experiments on MoTe
2
/WSe
2
bilayer heterostructures and introduces a controlled route to observe a topological selective Mott transition.
Surface premelting and melting of colloidal glasses
Authors: Zhang Qi , Li Wei , Qiao Kaiyao , Han Yilong
Published: March 2023

The nature of liquid-to-glass transition is a major puzzle in science. A similar challenge exists in glass-to-liquid transition, i.e., glass melting, especially for the poorly investigated surface effects. Here, we assemble colloidal glasses by vapor deposition and melt them by tuning particle attractions. The structural and dynamic parameters saturate at different depths, which define a surface liquid layer and an intermediate glassy layer. The power-law growth of both layers and melting front behaviors at different heating rates are similar to crystal premelting and melting, suggesting that premelting and melting can be generalized to amorphous solids. The measured single-particle kinetics reveal various features and confirm theoretical predictions for glass surface layer.
Single-cell dissection of human hematopoietic reconstitution after allogeneic hematopoietic stem cell transplantation
Authors: Huo Yingying , Wu Linjie , Pang Aiming , Li Qing , Hong Fang , Zhu Caiying , Yang Zining , Dai Weiqian , Zheng Yawei , Meng Qianqian , Sun Jiali , Ma Shihui , Hu Linping , Zhu Ping , Dong Fang , Gao Xin , Jiang Erlie , Hao Sha , Cheng Tao
Published: March 2023

Hematopoietic stem cell transplantation is an effective regenerative therapy for many malignant, inherited, or autoimmune diseases. However, our understanding of reconstituted hematopoiesis in transplant patients remains limited. Here, we uncover the reconstitution dynamics of human allogeneic hematopoietic stem and progenitor cells (HSPCs) at single-cell resolution after transplantation. Transplanted HSPCs underwent rapid and measurable changes during the first 30 days after transplantation, characterized by a strong proliferative response on the first day. Transcriptomic analysis of HSPCs enabled us to observe that immunoregulatory neutrophil progenitors expressing high levels of the
S100A
gene family were enriched in granulocyte colony-stimulating factor–mobilized peripheral blood stem cells. Transplant recipients who developed acute graft-versus-host disease (aGVHD) infused fewer S100A
high
immunoregulatory neutrophil progenitors, immunophenotyped as Lin
-
CD34
+
CD66b
+
CD177
+
, than those who did not develop aGVHD. Therefore, our study provides insights into the regenerative process of transplanted HSPCs in human patients and identifies a potential criterion for identifying patients at high risk for developing aGVHD early after transplant.
Development of the Systems Thinking for Health Actions framework: a literature review and a case study
Authors: Thelen Jenna , Sant Fruchtman Carmen , Bilal Muhammad , Gabaake Kebabonye , Iqbal Shahid , Keakabetse Tshiamo , Kwamie Aku , Mokalake Ellen , Mupara Lucia Mungapeyi , Seitio-Kgokgwe Onalenna , Zafar Shamsa , Cobos Muñoz Daniel
Published: March 2023

Background

Systems thinking is an approach that views systems with a holistic lens, focusing on how components of systems are interconnected. Specifically, the application of systems thinking has proven to be beneficial when applied to health systems. Although there is plenty of theory surrounding systems thinking, there is a gap between the theoretical use of systems thinking and its actual application to tackle health challenges. This study aimed to create a framework to expose systems thinking characteristics in the design and implementation of actions to improve health.

Methods

A systematised literature review was conducted and a Taxonomy of Systems Thinking Objectives was adapted to develop the new ‘Systems Thinking for Health Actions’ (STHA) framework. The applicability of the framework was tested using the COVID-19 response in Pakistan as a case study.

Results

The framework identifies six key characteristics of systems thinking: (1) recognising and understanding interconnections and system structure, (2) identifying and understanding feedback, (3) identifying leverage points, (4) understanding dynamic behaviour, (5) using mental models to suggest possible solutions to a problem and (6) creating simulation models to test policies. The STHA framework proved beneficial in identifying systems thinking characteristics in the COVID-19 national health response in Pakistan.

Conclusion

The proposed framework can provide support for those aiming to applying systems thinking while developing and implementing health actions. We also envision this framework as a retrospective tool that can help assess if systems thinking was applied in health actions.
Automatic classification of the phenotype textures of three Thunnus species based on the machine learning SVM algorithm
Authors: Ou Liguo , Liu Bilin , Chen Xinjun , He Qi , Qian Weiguo , Li Wenlong , Zou Leilei , Shi Yixi , Hou Qinglian
Published: March 2023

Tuna resources are an important part of China's pelagic fishery production. However, for China's tuna fishery, tuna species caught at sea are still manually classified, which is a time-consuming and inefficient process; so China's tuna fishery needs to develop toward automation. This study uses gray-level co-occurrence matrix (GLCM) and VGG16 to visualize phenotypic texture through local images of three Thunnus species. At the same time, texture feature index data (TFD), deep feature data (DFD), and their combined feature data (CFD) are obtained from texture images. Support vector machine (SVM) with different kernel functions is used to classify phenotypic texture of tuna automatically. The study shows that visualized texture images of different tuna using GLCM and VGG16 have biological characteristics. In the classification results without cross-validation, the average classification accuracy of TFD in polynomial was 83%, the average classification accuracy of DFD in RBF (Radial basis function) was 93%, and the average classification accuracy of CFD in RBF was 95%. It is concluded that tuna phenotype texture can be efficiently classified by using SVM with different kernel functions.
A Study on the Application of Sentiment-Support Words on Aspect-Based Sentiment Analysis
Authors: Jiang Lei , Zou Ziwei , Liao Jing , Li Yuan
Published: March 2023

Aspect-based sentiment classification is currently an important research direction to identify the sentiment expressed by sentences in different aspects. The primary approach for performing aspect-level sentiment analysis involves extracting both grammatical and semantic information. However, analyzing the grammatical connection between aspect words and other words within a review sentence using morphological features like part of speech can be exceedingly complex. This paper proposes the concept of sentiment-supporting words, dividing sentences into aspectual words, sentiment-supporting words and non-sentiment-supporting words, which simplifies the core task of sentiment analysis. Three rules are designed for determining the “sentiment-support words” of the text in different aspects. Subsequently, the application of sentiment-support words in sentiment analysis models is given, and five classical sentiment analysis models are improved accordingly. According to the experimental outcomes on two publicly available datasets, the “sentiment-support words” and corresponding sentiment support rules proposed in this paper are capable of significantly enhancing aspect-based sentiment analysis.
Fractional local edge dimensions of a graph
Authors: Goshi Nosheen , Zafar Sohail , Rashid Tabasam
Published: March 2023

Metric-based parameters aided the study of the structural properties of graph network space like complexity, central tendency, connectivity, robustness, accessibility, and vulnerability. At the same time, these parameters played a pivotal role in rectifying problems in navigation, integer programming, optimization, pattern recognition and avoidance, combinatoric detection, backtracking in geographical routing, etc. In this paper, we considered the fractional edge dimension, a metric-based parameter in local environment by initiating the study of the fractional local edge dimensions of a graph (FLED). We define the aforesaid concept and give its bounds. We discussed the characterization problem for FLED equal to [Formula: see text], the realization problem, and its relation with the fractional metric dimensions. We also calculated the FLED of the Petersen graph, Coxeter graph, the families of cycle, complete, wheel, grid and complete [Formula: see text]-partite graphs.
A Case Study of Ant Finance’s Innovation Journey — From a Platform Economy Perspective
Authors: Alexandre Herve , Woo Kok Lian
Published: March 2023

During the spring of 2021, the Chinese government profoundly changed its relationship with large digital platforms; the government had decided to strengthen their supervision, fight against monopolies, and promote fair competition. Until then, technology giants such as Alibaba, Tencent, Baidu, and JD.Com dominated a fast-growing market, especially in China, where Fintech represented a very important part of the retail market among middle-class consumers. Various political and economic reasons can be provided for this choice. This paper showcases the economic power of the two-sided markets approach of these platforms today and describes the late but violent reaction of the Chinese government, worried about its economic and monetary sovereignty.
Acquirer’s Operational Performance and Stability of Islamic Banks: Mediation Role of Market Structure
Authors: Ullah Nazim , Nor Fauzias Mat , Abu Seman Junaidah , Ramli Nur Ainna Binti , Rasedee Ahmad Fadly Nurullah Bin
Published: March 2023

Merger and acquisition is known as a market expansions strategy. This paper examines several factors associated with M&A namely bank size, intermediary role, modes of financing, bank-specific variables, and macro-economic variables on the operational performance and stability along with the mediation role of market structure for Islamic banks. This paper employs empirical research methods, namely POLS, panel data techniques and SEM to analyse a set of unbalanced panel samples of 10 Islamic banks during 2004Q1 to 2020Q4 from six countries, namely Qatar, Kuwait, Saudi Arabia, United Arab Emirates, Bahrain, and Pakistan. Stata package 14.2 is used to estimate M&A results (5 years pre and 5 years post). The results indicate that M&A improve Post-M&A performance of Islamic banks while stability does not improve. Interestingly, there is no mediation effects of market structure on the relationship between M&A, operational performance, and stability. Policymakers should take into consideration those factors taking M&A decisions considering the role of market structure.
FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation
Authors: Görür O. Can , Rosman Benjamin , Sivrikaya Fikret , Albayrak Sahin
Published: March 2023

A limitation for collaborative robots (cobots) is their lack of ability to adapt to human partners, who typically exhibit an immense diversity of behaviors. We present an autonomous framework as a cobot’s real-time decision-making mechanism to anticipate a variety of human characteristics and behaviors, including human errors, toward a personalized collaboration. Our framework handles such behaviors in two levels: (1) short-term human behaviors are adapted through our novel Anticipatory Partially Observable Markov Decision Process (A-POMDP) models, covering a human’s changing intent (motivation), availability, and capability; (2) long-term changing human characteristics are adapted by our novel Adaptive Bayesian Policy Selection (ABPS) mechanism that selects a short-term decision model, e.g., an A-POMDP, according to an estimate of a human’s workplace characteristics, such as her expertise and collaboration preferences. To design and evaluate our framework over a diversity of human behaviors, we propose a pipeline where we first train and rigorously test the framework in simulation over novel human models. Then, we deploy and evaluate it on our novel physical experiment setup that induces cognitive load on humans to observe their dynamic behaviors, including their mistakes, and their changing characteristics such as their expertise. We conduct user studies and show that our framework effectively collaborates non-stop for hours and adapts to various changing human behaviors and characteristics in real-time. That increases the efficiency and naturalness of the collaboration with a higher perceived collaboration, positive teammate traits, and human trust. We believe that such an extended human-adaptation is a key to the long-term use of cobots.
Active Colloids as Models, Materials, and Machines
Authors: Bishop Kyle J.M. , Biswal Sibani Lisa , Bharti Bhuvnesh
Published: March 2023

Active colloids use energy input at the particle level to propel persistent motion and direct dynamic assemblies. We consider three types of colloids animated by chemical reactions, time-varying magnetic fields, and electric currents. For each type, we review the basic propulsion mechanisms at the particle level and discuss their consequences for collective behaviors in particle ensembles. These microscopic systems provide useful experimental models of nonequilibrium many-body physics in which dissipative currents break time-reversal symmetry. Freed from the constraints of thermodynamic equilibrium, active colloids assemble to form materials that move, reconfigure, heal, and adapt. Colloidal machines based on engineered particles and their assemblies provide a basis for mobile robots with increasing levels of autonomy. This review provides a conceptual framework for understanding and applying active colloids to create material systems that mimic the functions of living matter. We highlight opportunities for chemical engineers to contribute to this growing field.
Political Inequality in Rich Democracies
Authors: Elsässer Lea , Schäfer Armin
Published: March 2023

In this review, we focus on political inequality in rich democracies. In the two main sections, we look at participation and representation, respectively. The former discusses whether rising income inequality and the weakening of trade unions have led to higher levels of inequality in participation. The latter looks at substantive and descriptive representation and asks how they might be linked. Research highlights that people with fewer individual resources participate much less than those with more resources, and collective organizations lose their ability to counter these trends. In terms of representation, the pattern is very similar. Not only are the opinions of decision-makers more congruent with those of the better off but policy choices also reflect their preferences more clearly. As the social distance between rulers and ruled increases, representative democracy gets more biased in favor of higher-status social groups.
A Slotted Patch Antenna Design and Analysis for Detecting Breast Cancer
Authors: Ahmed Md. Firoz , Kabir M. Hasnat
Published: March 2023

Breast cancer, a common and deadly cancer for woman, is gradually increasing each year. It can be cured at early stages. Magnetic resonance imaging, Mammography, Tomography, Ultrasound, and Biopsy are some of the medical technologies that can be used to identify breast cancer. However, none of them are as simple and effective as a microwave imaging (MI) technique. MI is a non-ionizing, noninvasive, tumor-sensitive, low-cost approach that consumes low power. The performance of MI is primarily determined by the antenna employed in the system. In this paper, we propose a new partial ground plane and slots-based miniature patch antenna designed for breast tumor detection within the FCC’s authorized range (3.1 GHz–10.6 GHz). The dimension of this antenna is 30 × 20 mm2. High frequency structure simulator (HFSS) software is used to design a breast phantom with and without a tumor, and the antenna is separately simulated on both the tumored and tumor-free breast phantoms. The presence of a tumor within the breast is clearly depicted by the changes in return loss, VSWR, current density, electric field, and magnetic field strengths. The findings demonstrate that the proposed antenna is a suitable sensor which can detect a very tiny size tumor (2 mm) due to its compact size and broad bandwidth.
Case Studies in Physiology: Male to female transgender swimmer in college athletics
Authors: Senefeld Jonathon W. , Hunter Sandra K. , Coleman Doriane , Joyner Michael J.
Published: March 2023

This case study, longitudinal analysis of freestyle swimming performances before and after 2 yr of feminizing gender-affirming hormone therapy of an elite transgender woman (male sex, female gender identity), demonstrates superior performance relative to rank-matched female swimmers and a lower performance gap than previously observed between elite male and female swimmers.
Gain of TlBr/BrCl Quantum Dot Semiconductor Optical Amplifier
Authors: Al-Nashy Baqer O. , Al-Mosawi Buraq T. Sh. , Oleiwi Mushtaq Obaid , Al-Khursan Amin H.
Published: March 2023

This work studies the thallium halogenide TlBr/BrCl quantum dot (QD) semiconductor structure and specifies its optical properties. This QD structure is poorly studied. High gain is obtained, with two peaks at

800

and

3000
 
n
m

. Doping is shown to increase the gain by one order. Then, TlBr QD semiconductor optical amplifier (SOA) characteristics are studied. High dB gain is shown mainly at the doped structure, which can be used in various inline applications.
Performance Analysis of Solar Still by Using Octagonal-Pyramid Shape in the Solar Desalination Techniques
Authors: Singh Bipin Kumar , Ramji C. , Ganeshan P. , Mohanavel V. , Balasundaram T. , Kumar V. Vignesh , Balasubramanian B. , Ramshankar P. , Ramesh Adireddy , Thanappan Subash
Published: March 2023

This research work explored and compared the experimental performance of a solar still having novel octagonal-pyramid shape with a single slope solar still. It is found that the novel still provides twice distillation compared with conventional still. The experiments also evaluated the desalination productivity of octagonal-pyramid solar still by varying the depth of saline water inside the basin and angle of inclination of glass cover. It is observed that the optimum condition for high distillation is obtained when depth of water inside the basin is 5 cm with angle of inclination of glass cover which is 30°. Four types of water, i.e., underground borewell water, sea water, leather industry effluent, and plastic industry effluent were also used to see the effect on distillation. Results showed that underground borewell water provides high distillation due to low density. Furthermore, the performance of the octagonal-pyramid solar still is enhanced by adding different latent heat and sensible heat materials in the octagonal-pyramid solar still. Hence, the addition of brick to the octagonal-pyramid still yields the highest productivity compared to incorporation of paraffin wax. Hence, it can be concluded that the octagonal design of the solar still has shown an increased productivity when compared to a single slope solar still (conventional still) under all the conditions.
Variations in Emergency Service Utilization among Cancer Survivors: Results from the Pan-Canadian Experiences of Cancer Patients in Transition Study Survey
Authors: Delisle Megan , Wang Ying , Fitch Margaret I. , Nagaratnam Kalki , Srikanthan Amirrtha
Published: March 2023

Purpose. The objective of this study was to examine variations in emergency service utilization (ESU) among cancer survivors during the first year after completing primary cancer treatment. Methods. In 2016, the Canadian Partnership Against Cancer collected survey responses from cancer survivors across Canada about self-reported ESU after completing primary cancer treatment. We included survey respondents diagnosed with nonmetastatic breast, hematologic, colorectal, melanoma, or prostate cancer. Multivariable, multinomial logistic regression analysis was used to examine factors associated with cancer survivors’ ESU. Results. Of the 5,774 cancer survivors included in our analysis, 22% reported ESU during the first year after completing their primary cancer treatment, 16% reported ESU one to three times, and 6% reported ESU more than three times. Factors significantly associated with frequent ESU included younger age, colorectal and hematologic cancers, more frequent primary care provider and oncology specialist visits, single or retired status, lower income, and self-reported lower quality of life. Conclusion. Our study identified factors associated with more frequent ESU among cancer survivors in the first year after completing primary cancer treatment. These factors highlight differences in cancer survivors’ demographics, their ability to access and need for healthcare services, and the complexity of using ESU as a metric for quality improvement in survivorship care. These variations must be considered in quality improvement initiatives.
Quantum Chemical Characteristics of Additives That Enable the Use of Propylene Carbonate-Based Electrolytes
Authors: Lee Jaeho , Kim Chaewon , Han Young-Kyu
Published: March 2023

Propylene carbonate- (PC-) based electrolytes are gaining attention as electrolytes in next-generation batteries because of their high stability and excellent temperature characteristics at high voltages. Lithium-ion batteries using PC-based electrolytes with 3-methyl-1,4,2-dioxazol-5-one (MDO) showed excellent capacity retention and lifetime characteristics. Here, quantum chemical methods are used to examine the molecular characteristics of MDO, and they suggest the unique molecular properties of this additive. Our calculations reveal that MDO is reduced prior to ethylene carbonate (EC) and PC solvents and undergoes a remarkably fast reduction decomposition process while producing thermodynamically stable reduction reaction products compared to vinylene carbonate (VC) and fluoroethylene carbonate (FEC) additives. This implies that a thermodynamically stable solid-electrolyte interphase (SEI) can form on the anode surface through a very rapid reaction. Upon reduction, the most preferred thermodynamic reaction between MDO and PC forms Li2CO3, a major SEI component. These reaction characteristics are unique and not observed with VC or FEC. The binding energy with Li+ is lower for MDO than for VC, FEC, or the solvents, making MDO the best choice for desolvation. We demonstrate that the molecular characteristics derived from quantum chemical calculations for MDO can also be applied to various previously reported PC-based electrolyte additives.
Phytochemical Screening, Antioxidant Activity, and Acute Toxicity Evaluation of Senna italica Extract Used in Traditional Medicine
Authors: Towanou Rodrigue , Konmy Basile , Yovo Mahudro , Dansou Christian C. , Dougnon Victorien , Loko Frédéric S. , Akpovi Casimir D. , Baba-Moussa Lamine
Published: March 2023

Medicinal plants such as Senna italica are increasingly used for their purgative virtues to treat stomach aches, fever, and jaundice. This study aims to screen the phytochemical compounds and to assess the antioxidant activity in vitro and the acute oral toxicity in vivo of Senna italica leaves. The plant was harvested, dried, pulverized, and preserved. Phytochemical screening was performed using different laboratory protocols. Ethanolic and aqueous extracts were, respectively, obtained by maceration and decoction technics. The assay for free radical scavenging was used to examine the antioxidant activity using DPPH. Acute oral toxicity was performed with aqueous and ethanolic extracts at 5000 mg/kg of body weight on female albinos Wistar rats, weighing 152.44 ± 3.68 g. Subjects were checked for any signs of mortality and macroscopy toxicity during the 14 days of the study. Biochemical and hematological parameters were measured to assess liver and kidney functions, and histological analysis of these organs was conducted. Phytochemical analysis highlighted the presence of total phenols, flavones, tannins, alkaloids, and quinone derivatives. Semiethanolic (78 μg/mL), ethanolic (9.7 μg/mL), and aqueous extract (9.2 μg/mL) showed an interesting antioxidant activity. Biochemical and hematological parameters were normal and not significantly different (

p
>
0.05

). The plant extracts did not produce any toxic effect or mortality at the provided dose. Senna italica extracts induced an increase in the volume of liver and kidney tissues but no necrosis. Thus, lethal dose 50 of Senna italica leaf extract is probably higher than 5000 mg/kg.
Triple Threat: Significant Concomitant Aortic Stenosis, Mitral Stenosis, and Systolic Anterior Motion of the Mitral Valve Causing Left Ventricular Outflow Tract Obstruction in Cardiac Surgical Patients
Authors: Glines Katelyn , Hayanga J. W. Awori , Gibson Christina , El Churafa Mohamad , Wei Lawrence , Hayanga Heather K.
Published: March 2023

Systolic anterior motion (SAM) describes a pathologic condition of the mitral valve in which the anterior leaflet is displaced anteriorly, resulting in a narrowed left ventricular outflow tract (LVOT). The implications of SAM may range in severity from clinically insignificant disease to severe LVOT obstruction resulting in hemodynamic collapse. While SAM is typically observed in patients with hypertrophic cardiomyopathy or following mitral valve repair, it may be seen in any setting in which the anatomy and function of the left ventricle has been altered. Here we discuss two patients who presented for aortic and mitral valve replacements for concomitant aortic and mitral stenosis. These cases were further complicated by the preoperative diagnosis of SAM in addition to the preexisting valvular lesions, further increasing the risk of sudden hemodynamic collapse and cardiac arrest.
Single-Cell RNA Sequencing Unifies Developmental Programs of Esophageal and Gastric Intestinal Metaplasia
Authors: Nowicki-Osuch Karol , Zhuang Lizhe , Cheung Tik Shing , Black Emily L. , Masqué-Soler Neus , Devonshire Ginny , Redmond Aisling M. , Freeman Adam , di Pietro Massimilliano , Pilonis Nastazja , Januszewicz Wladyslaw , O'Donovan Maria , Tavaré Simon , Shields Jacqueline D. , Fitzgerald Rebecca C.
Published: March 2023

Intestinal metaplasia in the esophagus (Barrett's esophagus IM, or BE-IM) and stomach (GIM) are considered precursors for esophageal and gastric adenocarcinoma, respectively. We hypothesize that BE-IM and GIM follow parallel developmental trajectories in response to differing inflammatory insults. Here, we construct a single-cell RNA-sequencing atlas, supported by protein expression studies, of the entire gastrointestinal tract spanning physiologically normal and pathologic states including gastric metaplasia in the esophagus (E-GM), BE-IM, atrophic gastritis, and GIM. We demonstrate that BE-IM and GIM share molecular features, and individual cells simultaneously possess transcriptional properties of gastric and intestinal epithelia, suggesting phenotypic mosaicism. Transcriptionally E-GM resembles atrophic gastritis; genetically, it is clonal and has a lower mutational burden than BE-IM. Finally, we show that GIM and BE-IM acquire a protumorigenic, activated fibroblast microenvironment. These findings suggest that BE-IM and GIM can be considered molecularly similar entities in adjacent organs, opening the path for shared detection and treatment strategies.

Significance:

Our data capture the gradual molecular and phenotypic transition from a gastric to intestinal phenotype (IM) in the esophagus and stomach. Because BE-IM and GIM can predispose to cancer, this new understanding of a common developmental trajectory could pave the way for a more unified approach to detection and treatment.

See related commentary by Stachler, p. 1291.

This article is highlighted in the In This Issue feature, p. 1275
An algorithm for enhancement of audio content classification
Authors: Bang Arti V , Purandare Radhika G. , Ratnaparkhi Archana K.
Published: March 2023

Presently, fast proliferation of information enforces novel challenges on content management. Further, computerized audio classification along-with content description is considered as valuable method to manage audio contents. In general, classification involves two steps. First, is the processing of accessible data in economical ways to deliver explanatory features. Second is how accurate features of undetermined tests is evaluated to choose classifier. In this paper, k-neighbor algorithm with machine learning is proposed for feature extraction as well as content classification/description. This algorithm enhances Quality of Service parameters of classifiers. Here, development of training as well as testing data set is developed to increase the classifier accuracy. A test engine set-up bed using simulation tool MATLAB is designed to estimate the implementation performance of the algorithm. A range of features are studied to evaluate effectiveness in terms of accuracy, zero crossing rate (ZCR) and spectral roll frequency. From the experimentation results, it is observed that the proposed algorithm can achieve accuracy of 95.8% for 2 sec window length as compare with k-neighbor algorithm. A total enhancement of 11% is achieved with cross validation error of 29.6. A superior assortment of training fabric to extract few additional useful features can enhance accuracy further.
Design high voltage gain DC converter based on maximum power point resistance for photovoltaic applications
Authors: Billy Ibraheem Jawad , Hussein Jasim Farhood
Published: March 2023

Due to the nonlinear properties of photovoltaic (PV) modules, the design of the high-gain direct current (DC) converter for maximum power point tracking (MPPT) is complicated. In this paper, the design of a new step-up DC converter for MPPT applications is proposed. The proposed converter is structured of two symmetrical reverse-parallel DC-DC boost converters. This structure is supported by voltage multiplier cells equipped to increase output voltage and decrease voltage stress on semiconductor switches. To simplify the high-gain DC converter design, the PV module's maximum power point is treated as resistance by using the incremental conductance (INC) method. The MPPT boost converter's inductance, input capacitance, and output capacitance are calculated using the derived equations using nine parameters. The results showed that the proposed DC converter simulation meets the necessary requirements. The size of the input capacitor, inductor, and output capacitor have been decreased. When the proposed converter is compared to a traditional converter, there is less voltage stress, low current ripple, and an increase in voltage gain. This has led to an improvement in the overall converter efficiency.
Classification of 27 heart abnormalities using 12-lead ECG signals with combined deep learning techniques
Authors: Rawi Atiaf A. , Elbashir Murtada Khalafallah , Ahmed Awadallah M.
Published: March 2023

An electrocardiogram (ECG) machine with a standard 12-lead configuration is the primary clinical technique for diagnosing abnormalities in heart function. Automated 12-lead ECG machines have the capacity to screen the general population and provide second opinions for physicians. However, expertise and time are required for manual ECG interpretation. Therefore, computer-aided diagnoses are of interest to the medical community. Hence, this study aims to build a deep learning (DL) model with an end-to-end structure that can categorize 12-lead ECG results into 27 different disorders. We use multivariate time-series data to construct a novel end-to-end DL model (based on combined convolutional neural networks (CNNs), long short-term memory, gated recurrent units, and a deep residual network structure) for feature representations and determining spatial relations among deep features. In addition, a dataset of 43,101 classified standard ECG recordings was collected from six different sources to guarantee the model’s ability to generalize and alleviate data divergence. As a result, the residual network-based model obtained promising outcomes and an accuracy of 0.97. According to the experimental data, it outperforms other methods.
An improvement of direct torque controlled PMSM drive using PWM technique and kalman filter
Authors: Nguyen Dung Quang , Vo Hau Huu , Brandstetter Pavel
Published: March 2023

The paper describes pulse-width-modulation (PWM) technique and Kalman filter (KF) process to improve performance of direct torque controlled permanent magnet synchronous motor (DTC-PMSM) drive. Performance of DTC methods are strongly affected by high stator current ripple. For lowering the ripple, high switching frequency space vector PWM and KF are utilized in the paper. Mathematical model of PMSM and calculations of important quantities of DTC applied to PMSM drive are presented in the ﬁrst part. The second part shows computation process of space vector PWM and KF. Performance indices are utilized to evaluate the drive structures. Theorectical assumptions are validated via simulations with Gaussian noised stator current measurement.