bluuebunny/crossref_metadata_2025 huggingface dataset:
The genome sequence of pellitory-of-the-wall, Parietaria judaica L. (Urticaceae)
Authors: Christenhusz Maarten J. M. ,   Royal Botanic Gardens Kew Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Plant Genome Sizing collective,   Wellcome Sanger Institute Tree of Life Management, Samples and Laboratory team,   Wellcome Sanger Institute Scientific Operations: Sequencing Operations,   Wellcome Sanger Institute Tree of Life Core Informatics team,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: October 2024

We present a genome assembly from an individual Parietaria judaica (pellitory-of-the-wall; Tracheophyta; Magnoliopsida; Rosales; Urticaceae). The genome sequence is 538.7 megabases in span. Most of the assembly is scaffolded into 13 chromosomal pseudomolecules. The three mitochondrial genomes have lengths of 215.28, 107.63 and 112.60 kilobases, while the plastid genome assembly had a length of 152.63 kilobases. Gene annotation of this assembly on Ensembl identified 35,329 protein-coding genes.
role of the ketogenic diet in the treatment of epilepsy
Authors: Kusiak Karolina , Kuśnierz Anna , Głąbień Marta , Aleksandrowicz Daria , Jakubczak Zofia , Miłkowski Paweł , Zimniak Maria Weronika , Kondratowicz Aneta , Wieczorek Olga , Śliwiak Patryk
Published: October 2024

Introduction:
Epilepsy is a prevalent neurological condition that continues to pose therapeutic challenges. Despite the availability of various antiepileptic medications, up to one-third of patients still experience insufficient control of their seizures. One approach to managing epilepsy, particularly in drug-resistant cases, is the ketogenic diet. This diet, along with its variations, has shown effectiveness in reducing seizures across all age groups, with additional improvements in behavior. However, despite numerous studies, the exact mechanisms behind its therapeutic effects and potential risks to the body remain unclear. This review of the current literature outlines the fundamental principles and variations of the ketogenic diet, evaluates its safety and effectiveness in treating epilepsy, and explores the possible mechanisms underlying its success.
Materials and methods:
This article is based on the literature found in the PubMed database with the use of keywords like: "drug resistance epilepsy", "ketogenic diet", "epilepsy treatment".
Conclusion:
The ketogenic diet is an effective treatment for epilepsy, especially drug-resistant forms. It reduces the number of seizures and it also has a positive effect on patients' sleep and cognitive functions. Despite many years of using the diet and observing its effects we still do not fully understand its mechanisms of action.
Sponsor Reputation and Capital Structure Dynamics in Leveraged Buyouts
Authors: Shive Sophie , Forster Margaret
Published: October 2024

We examine whether leveraged buyout (LBO) sponsors’ reputations as borrowers affect the refinancing terms of their portfolio companies. In 510 U.S. LBOs for which we can reconstruct debt financing activity, 67% of financing events occur one quarter before the earliest existing debt maturity. These On Time events generally improve borrowing terms, whereas Early events feature more dividends, leverage, and higher cost. In each case, dividend issuance decreases and cost increases with the proportion of the sponsors’ recent exits that are failures. Effects are absent for matched firms and prior to the LBO and are procyclical; sponsors with recent failures miss opportunities to decrease financing costs in good times.

This paper was accepted by Bo Becker, finance.

Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.00971 .
Increasing Black Employees’ Social Identity Affirmation and Organizational Involvement: Reducing Social Uncertainty Through Organizational and Individual Strategies
Authors: Wang Cynthia , Ku Gillian , Smith Alexis Nicole , Edwards Bryan , Scott Edward , Galinsky Adam D.
Published: October 2024

Despite the psychological benefits of authenticity, Black employees within predominantly White organizations often face the dilemma of whether to downplay versus highlight their social identity. Our research introduces social uncertainty as a unifying lens to understand the reluctance of these employees to express their social identity. Highlighting the central role of social uncertainty also helps identify novel factors at both the organizational level (authenticity climates) and individual level (perspective-taking) that can encourage Black employees to engage in social identity affirmation—authentic expressions of the positive aspects of their social identity. To test our hypotheses, we conducted two survey studies, two experiments, qualitative interviews, as well as coded text responses to our experimental prompts. Across our studies, authenticity climates were associated with greater social identity affirmation by Black employees, and this relationship was strengthened when these employees engaged in perspective-taking. Consistent with our theorizing, social certainty mediated these direct and moderated effects. In addition, social identity affirmation increased Black employees’ organizational involvement. Our experimental studies offer causal evidence for the roles of both authenticity climates and Black employees’ perspective-taking, our qualitative interviews vividly illuminate our hypotheses, and our text response analyses provide insight into how authenticity climates operate. Overall, the current research highlights how organizations can help Black employees feel comfortable emphasizing and expressing their true selves by increasing their social certainty. These findings also have direct implications for organizational leaders, providing them with actionable strategies to create more inclusive environments.

Funding: The research was supported by Northwestern University and Oklahoma State University.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2020.14659 .
How Psychological Barriers Constrain Men’s Interest in Gender-Atypical Jobs and Facilitate Occupational Segregation
Authors: Suh Eileen Y. , Apfelbaum Evan P. , Norton Michael I.
Published: October 2024

Scholarship regarding occupational gender segregation has almost exclusively focused on women’s experiences (e.g., as targets of discrimination in masculine domains), yet understanding factors that perpetuate men’s underrepresentation in traditionally feminine occupations is equally important. We examine a consequential dynamic early in the job search process in which individuals come to learn that an occupation that fits them is perceived as feminine versus masculine. Our research develops and tests the prediction that femininity or masculinity of occupations will exert a stronger impact on men’s (versus women’s) interest in them such that men will be less interested in gender-atypical occupations than women. Across five studies (n = 4,477), we consistently observed robust evidence for this prediction among diverse samples, including high school students (Study 1), unemployed job seekers (Study 2), U.S. adults (Study 3), and undergraduates (Study 4) and using experimental and archival methods. We observed this asymmetry after controlling for alternative accounts related to economic factors (e.g., expected salary), suggesting that they alone cannot fully explain men’s lack of interest in feminine occupations as previously discussed in the literature. Further, we consistently observed that men, compared with women, show heightened sensitivity to gender-based occupational status, and this greater sensitivity explains men’s (versus women’s) reduced interest in gender-atypical occupations. Though past scholarship suggests that increasing pay is key to stoking men’s interest in feminine occupations, our research suggests that targeting men’s underlying psychological concern—sensitivity to gender-based occupational status—may be an underappreciated pathway to reducing gender segregation.

Supplemental Material: The data, materials, preregistration, and ancillary analyses for all studies are available at https://osf.io/h4mgx/?view_only=9a4dbfc9d122417c880354d6b3462072 and at https://doi.org/10.1287/orsc.2023.17550 .
Branch and Price for the Stochastic Traveling Salesman Problem with Generalized Latency
Authors: Lienkamp Benedikt , Hewitt Mike , Schiffer Maximilian
Published: October 2024

We consider an extension of the symmetric traveling salesman problem with generalized latency that explicitly models uncertainty. The stochastic traveling salesman problem with generalized latency (STSP-GL) aims to choose a subset of nodes of an undirected graph and determines a Hamiltonian tour among those nodes, minimizing an objective function that is a weighted combination of route design and passenger routing costs. These nodes are selected to ensure that a predefined percentage of uncertain passenger demand is served with a given probability. We formulate the STSP-GL as a stochastic program and propose a branch-and-price algorithm for solving its deterministic equivalent. We also develop a local search approach with which we improve the performance of the branch-and-price approach. We assess the efficiency of the proposed methods on a set of instances from the literature. We demonstrate that the proposed methods outperform a known benchmark, improving upper bounds by up to 85% and lower bounds by up to 55%. Finally, we show that solutions of the stochastic model are both more cost-effective and robust than those of the deterministic model.

History: This paper has been accepted for the Transportation Science Special Issue on TSL Conference 2023.

Funding: This work was supported by the Bundesministerium für Bildung und Forschung [Grant 03ZU1105FA].

Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0417 .
Concave function inequalities for sum of matrices
Authors: Zhang Feng
Published: October 2024

In this paper, we present some norm inequalities for concave functions, which generalize the main results in [Y. Zhang. Linear Algebra Appl., 574:60-66, 2019].
Three-dimensional metamaterial for reconfigurable multi-band electromagnetically induced transparency based on VO2
Authors: Liang Jing-Jing , Li Bin , Yang Shu-Hui , Meng Rui , Zhang Li , Fu Zi-Hao , Hou Ya-Hui
Published: October 2024

Conventional 2D planar metamaterials struggle to achieve multi-band electromagnetically induced transparency (EIT) effects due to structural constraints. This paper proposes what we believe to be a novel three-dimensional (3D) metamaterial consisting of a vertical split-ring resonator with vanadium dioxide (VO2) islands at the openings. Based on VO2’s reversible phase transition capabilities, the designed metamaterial has excellent reconfigurability for multi-band EIT effects. When the surface temperature is at room temperature, VO2 exhibits an insulating state. The near-field coupling between bright and dark modes leads to a triple-band EIT effect at 1.72, 1.82, and 1.91 THz, characterized by multi-band, low-loss, and narrowband filtering. In contrast, when the temperature exceeds 68°C, VO2 transitions to its metallic state, resulting in a single transmission window with favorable slow light characteristics. Compared to traditional EIT metamaterials, our work realizes multi-band modulation and switchable operating modes, enhancing flexibility and adaptability. The excellent performance indicates its suitability for various applications, including multi-channel sensors, switchable absorptions, enhancing coupling and slow light devices, etc.
Sensitivity fields and parameter estimation from dielectric objects
Authors: Barbastathis George
Published: October 2024

The quantitative phase image formation process is posed as a problem of parameter estimation from intensity measurements. This approach is inclusive of traditional pixel-oriented imaging, where the sought parameters are the pixel values. The resulting optimization process to find the parameters is then seen to depend on the sensitivity field: this is the gradient of the scattered field with respect to the parameters, and it turns out to obey a scattering relationship that is analogous to that of the original scattered field. Examples are given from several regimes of scattering strength.
High-resolution hyperspectral video imaging using a hexagonal camera array
Authors: Sippel Frank , Seiler Jürgen , Kaup André
Published: October 2024

Retrieving the reflectance spectrum from objects is an essential task for many classification and detection problems, since many materials and processes have a unique spectral behavior. In many cases, it is highly desirable to capture hyperspectral images due to the high spectral flexibility. Often, it is even necessary to capture hyperspectral videos or at least to be able to record a hyperspectral image at once, also called snapshot hyperspectral imaging, to avoid spectral smearing. For this task, a high-resolution snapshot hyperspectral camera array using a hexagonal shape is introduced. The hexagonal array for hyperspectral imaging uses off-the-shelf hardware, which enables high flexibility regarding employed cameras, lenses, and filters. Hence, the spectral range can be easily varied by mounting a different set of filters. Moreover, the concept of using off-the-shelf hardware enables low prices in comparison to other approaches with highly specialized hardware. Since classical industrial cameras are used in this hyperspectral camera array, the spatial and temporal resolution is very high, while recording 37 hyperspectral channels in the range from 400 to 760 nm in 10 nm steps. As the cameras are at different spatial positions, a registration process is required for near-field imaging, which maps the peripheral camera views to the center view. It is shown that this combination using a hyperspectral camera array and the corresponding image registration pipeline is superior in comparison to other popular snapshot approaches. For this evaluation, a synthetic hyperspectral database is rendered. On the synthetic data, the novel approach, to our knowledge, outperforms its best competitor by more than 3 dB in reconstruction quality. This synthetic data is also used to show the superiority of the hexagonal shape in comparison to an orthogonal-spaced one. Moreover, a real-world high-resolution hyperspectral video database with 10 scenes is provided for further research in other applications.
Prediction of optical chaos using a multi-stage extreme learning machine with data uncertainty
Authors: Gao Dawei , Ma Chen , Fan Yuanlong , Wang Yangyundou , Shao Xiaopeng
Published: October 2024

In this paper, we study the problem of predicting optical chaos for semiconductor lasers, where data uncertainty can severely degrade the performance of chaos prediction. We hereby propose a multi-stage extreme learning machine (MSELM) based approach for the continuous prediction of optical chaos, which handles data uncertainty effectively. Rather than relying on pilot signals for conventional reservoir learning, the proposed approach enables the use of predicted optical intensity as virtual training samples for the MSELM model learning, which leads to enhanced prediction performance and low overhead. To address the data uncertainty in virtual training, total least square (TLS) is employed for the update of the proposed MSELM’s parameters with simple updating rule and low complexity. Simulation results demonstrate that the proposed MSELM can execute the continuous optical chaos predictions effectively. The chaotic time series can be continuously predicted for a time period in excess of 4 ns with a normalized mean squared error (NMSE) lower than 0.012. It also demands much fewer training samples than state-of-the-art learning-based methods. In addition, the simulation results show that with the help of TLS, the length of prediction is improved significantly as the uncertainty is handled properly. Finally, we verify the prediction ability of the multi-stage ELM under various laser parameters, and make the median boxplot of the predicted results, which shows that the proposed MSELM continues to produce accurate and continuous predictions on time-varying optical chaos.
In-orbit demonstration of acquisition and tracking on OSIRIS4CubeSat
Authors: Rüddenklau René , Rein Fabian , Roubal Christian , Rödiger Benjamin , Schmidt Christopher
Published: October 2024

OSIRIS4CubeSat is the smallest commercially available laser communication terminal within the confines of 0.3-units. It was launched as PIXL-1 inside of a 3-unit CubeSat into space to demonstrate optical direct to earth links. This work primarily focuses on the commissioning phase, particularly emphasizing the performance of the active fine pointing and tracking mechanism. This steering mechanism, with a 1 degree radius field of regard, plays a decisive role in compensating for pointing inaccuracies from the satellite’s attitude determination and control system. The design and validation of open-loop acquisition and closed-loop tracking are presented. The feedback sensor adapts to changing beacon power levels, that occur during a direct to earth link, by an adaptive gain control. Subsequent evaluation of satellite passes, with telemetry recordings obtained from the deployed CubeSat, showcases superior performance that meets the pointing requirements of the link budget. By using the developed control-loop logic, OSIRIS4CubeSat achieves a mean tracking error of 71 µrad, with a 3σ deviation of 140 µrad down to low power levels of 238 pW. These results serve as validation of OSIRIS4CubeSat, demonstrating its capability to enable high-speed data transmission from low Earth orbit to the Earth’s surface at data rates of up to 100 Mbit/s.
Reconfigurable binary diffractive optical neural network based on chalcogenide phase change material Ge2Sb2Se4Te1
Authors: Fu Ziwei , Fu Tingzhao , Wu Hao , Zhu Zhihong , Zhang Jianfa
Published: October 2024

Diffractive optical neural networks (DONNs) possess unique advantages such as light-speed computing, low energy consumption, and parallel processing, which have obtained increasing attention in recent years. However, once conventional DONNs are fabricated, their function remains fixed, which greatly limits the applications of DONNs. Thus, we propose a reconfigurable DONN framework based on a repeatable and non-volatile phase change material Ge2Sb2Se4Te1(GSST). By utilizing phase modulation units made of GSST to form the network's neurons, we can flexibly switch the functions of the DONN. Meanwhile, we apply a binary training algorithm to train the DONN weights to binary values of 0 and π, which is beneficial for simplifying the design and fabrication of DONN while reducing errors during physical implementation. Furthermore, the reconfigurable binary DONN has been trained as a handwritten digit classifier and a fashion product classifier to validate the feasibility of the framework. This work provides an efficient and flexible control mechanism for reconfigurable DONNs, with potential applications in various complex tasks.
Implementation of controlled unitary gates and its application in a remote-controlled quantum gate
Authors: Kim Byungjoo , Hong Seongjin , Kim Yong-Su , Oh Kyunghwan , Lim Hyang-Tag
Published: October 2024

Recently, remote-controlled quantum information processing has been proposed for its applications in secure quantum processing protocols and distributed quantum networks. For remote-controlled quantum gates, the experimental realization of controlled unitary (CU) gates between any quantum gates is an essential task. Here, we propose and experimentally demonstrate a scheme for implementing CU gates between any pair of unitary gates using the polarization and time-bin degrees of freedom of single photons. Then, we experimentally implement remote-controlled single-qubit unitary gates by controlling either the state preparation or measurement of the control qubit with high process fidelities. We believe the proposed remote-controlled quantum gate model can pave the way for secure and efficient quantum information processing.
High-sensitivity multi-gas detection using dual-ridge metasurface emitters with polarization-distinguishable emission spectra
Authors: Song Feng , Wu Xiaohu , Liu Yufang , Yu Kun
Published: October 2024

The metasurface thermal emitter offers an energy-efficient, compact, and sensitive solution as a radiation source for non-contact gas detection, enabling the “molecular fingerprint” technique to be widely applied, from medical diagnostics to environmental monitoring. However, most narrowband emitters are designed for a single target gas, hindering the miniaturization of multi-gas detection systems. In this work, a one-dimensional dual-ridge grating emitter is employed, achieving dual-band and tri-band polarization-distinguishable emission spectra through the excitation of Fabry-Perot (FP) resonances and quasi-bound states in the continuum (qBICs). These emission spectra can be readily matched to multiple non-overlapping absorption peaks of gases such as CH4, CO2, CO, NO, and NH3 within the 3–6 µm range, thereby reducing the impact of mixed gases on measurements. Compared to conventional metal-dielectric-metal structures, the use of a single metal layer results in lower material losses, enabling higher Q-factors and more pronounced directional radiation intensity variations. Furthermore, adjusting the asymmetry to modulate the qBIC-excited absorption peaks does not affect the Q-factor of the FP resonance absorption, thus achieving high-sensitivity multi-band gas detection. This work provides a promising approach for the miniaturization and integration of multi-gas channel detection, facilitating more accurate and sensitive sensing strategies.
Mamyshev oscillation self-starting mode-locked fiber laser based on a self-feedback amplifying sub-cavity
Authors: Liu Zepeng , Jin Liang , Song Yuhong , An Ning , Zhang He , Hu Miao
Published: October 2024

The Mamyshev oscillator (MO) boasts unparalleled modulation depth advantages in establishing mode-locking. However, this also significantly inhibits the self-starting of mode-locking. This Letter addresses the issue by constructing a self-feedback mechanism for regenerative oscillation. By amplifying noise cycles during the initial pumping phase to introduce periodic fluctuations in light intensity, we successfully achieve self-starting mode-locking at 1550 nm in an MO with a single gain arm structure at the pump power threshold of 76 mW. This self-starting mode-locking mechanism based on self-feedback sub-cavity amplification demonstrates excellent stability and repeatability in a single-arm MO structure. It provides what we believe to be a new approach for developing simple, reliable, and high repetition rate mode-locked lasers.
A geometrically scalable method for manufacturing high quality factor mechanical resonators
Authors: Birckigt Pascal , Carter Jonathan J. , Koehlenbeck Sina M. , Leibeling Gilbert , Risse Stefan
Published: October 2024

We present what we believe to be a novel, geometrically scalable manufacturing method for creating compact, low-resonance frequency, and high quality factor fused silica resonators. These resonators are intended to be used in inertial sensors for measuring external disturbances of sensitive physics experiments. The novel method uses direct bonding and chemical–mechanical polishing (CMP) in order to overcome the limitations of current subtractive manufacturing methods, which face prohibitive cost and complexity as material removal increases, inherently restricting the design flexibility of the resonator. We demonstrate a prototype with a test mass of only 3 g that reaches a quality factor of Q = 118 000 ± 400 at a resonance frequency of below 20 Hz. This advancement is particularly significant for future gravitational wave observatories, such as the Einstein Telescope.
Pulse position encoded RZ-OOK transmission for free-space optical communications
Authors: Song H. , Zhong Z. C. , Hong Y. Q.
Published: October 2024

This paper proposes a pulse position encoded return-to-zero on-off keying (PP-RZ-OOK) transmission for free space optical (FSO) communications. At the transmitter end, PP-RZ-OOK signal is modulated by encoding the pulse position of RZ-OOK in the symbol duration. At the receiver end, PP-RZ-OOK signal is demodulated by symbol-by-symbol signal estimation. First, the existence of pulse is distinguished by adaptive threshold decision using the channel state information (CSI). Then, with respect to the symbol with the pulse, the knowledge of pulse position is estimated by slot-by-slot pulse power comparison. Finally, PP-RZ-OOK signal is effectively demodulated by both pulse existence and pulse position estimation. Therefore, the spectral efficiency of RZ-OOK is increased by the proposed pulse position encoding technique. The performance of the proposed PP-RZ-OOK modulation was verified through simulations under different turbulence channels and pulse durations, and it was compared with non-return-to-zero OOK (NRZ-OOK) and RZ-OOK modulations. The simulation results demonstrated that the capability of scintillation effect compensation was significantly enhanced compared with NRZ-OOK due to the pulse power increasing. Besides, the spectral efficiency was improved compared with RZ-OOK due to the additional pulse position encoding.
Bi-chromatic intensity squeezing using four-wave mixing in ⁸⁵Rb vapor
Authors: Niu Ziqi , Wen Jianming , Zhang Chuanwei , Du Shengwang , Novikova Irina
Published: October 2024

We experimentally investigate four-wave mixing (FWM)
in a diamond interaction scheme using ⁸⁵Rb vapor, and
identify the optimal conditions for joint amplification
and relative intensity squeezing of two optical fields:
one near the ⁸⁵Rb D1 optical transition (λ = 794.6 nm)
and the other in the telecom O-band (λ = 1324 nm). We
achieved a reduction of relative intensity noise by up
to 2.6 ± 0.4 dB compared to the shot noise level, signi-
fying the non-classical quantum correlations. The ob-
served level of intensity squeezing is primarily limited
by the available pump laser power, which constrains
the achievable FWM gain. Numerical simulations show
good agreement with the experimental results.
Inscription of Bragg reflectors in polypropylene no-core optical fibers using 248nm laser radiation
Authors: Pissadakis Stavros , Chapalo Ivan , Sarakatsianos Vasilios , Konstantaki Maria , Grantzioti Eleni , Manouras Theodore , Vamvakaki Maria , Tsibidis Giorgos
Published: October 2024

Inscription and characterization of Bragg reflectors in polypropylene (PP) no-core optical fibers using 248-nm KrF excimer laser radiation are presented for the first time. A new photo-sensitization approach is adopted by means of pre-loading the PP no-core fibers using toluene in-diffusion, for increasing Bragg reflector recording yield. The Bragg reflector inscription process was monitored online, for both pristine and toluene loaded PP no-core fibers under identical exposure conditions, revealing that toluene loaded samples leaded to threefold stronger reflectors and average refractive index changes of the order of 1.1x10-3. The Bragg reflectors were characterized for their response to strain (1.62 pm/με), and temperature (-145 pm/℃), while negligible sensitivity to water diffusion was recorded. The photosensitivity mechanism of the toluene in-diffused PP no-core optical fibers using 248-nm KrF excimer laser radiation is also discussed.
DeepPL: A deep-learning-based tool for the prediction of bacteriophage lifecycle
Authors: Zhang Yujie , Mao Mark , Zhang Robert , Liao Yen-Te , Wu Vivian C. H.
Published: October 2024

Bacteriophages (phages) are viruses that infect bacteria and can be classified into two different lifecycles. Virulent phages (or lytic phages) have a lytic cycle that can lyse the bacteria host after their infection. Temperate phages (or lysogenic phages) can integrate their phage genomes into bacterial chromosomes and replicate with bacterial hosts via the lysogenic cycle. Identifying phage lifecycles is a crucial step in developing suitable applications for phages. Compared to the complicated traditional biological experiments, several tools have been designed for predicting phage lifecycle using different algorithms, such as random forest (RF), linear support-vector classifier (SVC), and convolutional neural network (CNN). In this study, we developed a natural language processing (NLP)-based tool—DeepPL—for predicting phage lifecycles via nucleotide sequences. The test results showed that our DeepPL had an accuracy of 94.65% with a sensitivity of 92.24% and a specificity of 95.91%. Moreover, DeepPL had 100% accuracy in lifecycle prediction on the phages we isolated and biologically verified previously in the lab. Additionally, a mock phage community metagenomic dataset was used to test the potential usage of DeepPL in viral metagenomic research. DeepPL displayed a 100% accuracy for individual phage complete genomes and high accuracies ranging from 71.14% to 100% on phage contigs produced by various next-generation sequencing technologies. Overall, our study indicates that DeepPL has a reliable performance on phage lifecycle prediction using the most fundamental nucleotide sequences and can be applied to future phage and metagenomic research.
Assessments of effectiveness of technologies utilizations in VIHSCM among selected health facilities in Tanzania mainland
Authors: Mollel Henry A. , Mushi Lawrencia D. , Nkwera Richard V.
Published: October 2024

Immunization coverage remains a challenge in many developing countries Tanzania being no exception. The current increase in technology adoption in the immunisation supply chain promises the attainment of universal health coverage and Sustainable Development Goals (SDGs) on immunisation. This study evaluates the effectiveness of technology integration in Vaccine and Immunization Health Supply Chain Management (VIHSCM) in Tanzania. This study adopted an exploratory descriptive cross-sectional design. The study collected data using structured questionnaires from health facilities that adopted VIHSCM technologies in Arusha, Mwanza, Morogoro and Mbeya regions, Tanzania. Data were analysed using descriptive statistics and cross-tabulations with the aid of the Statistical Package of Social Sciences 23rd Edition (SPSS). The study included 37 health facilities in Tanzania, mainly district hospitals (59.5%). Respondents were mostly female (70.3%), averaging 45 years old, with 1–5 years of immunization experience. While all facilities had refrigerators, digital reporting tool usage was low, with many relying on paper forms. District hospitals and health centres had higher digital tool adoption rates compared to dispensaries. Despite the underutilization of systems like ILS, TImR, and GoTHOMIS, digital tools were deemed crucial for vaccine supply management. While District Hospitals report high relevance of digital tools, Health Centres and Dispensaries show moderate relevance. Challenges include incomplete technology adoption, inadequate infrastructure, and variable perceptions of technology effectiveness. Digital technologies significantly improve vaccine and immunization supply chain management, particularly in larger facilities. Technologies like the Tanzania Immunization Registry (TImR) and Integrated Logistics Systems (ILS) enhance data accuracy and efficiency. Addressing facility-specific challenges and increasing investment in digital tools are crucial for optimizing vaccine supply chains and achieving immunization targets in Tanzania. Future research should involve larger samples to generalize findings and further explore technology impacts on VIHSCM.
What do Iranians value most when choosing a hospital? Evidence from a discrete choice experiment
Authors: Ranjbar Mohammad , Bazyar Mohammad , Pahlevanshamsi Fatemeh , Angell Blake , Assefa Yibeltal
Published: October 2024

Background

Individual preferences have preceded the use of health care services, and it has been affected by different hospital attributes. This study aimed to elicit the Iranians’ preferences in choosing hospitals using a discrete choice experiment.

Methods

A discrete choice experiment (DCE) was conducted through face to face interviews with 301 participants. The DCE was constructed by six attributes were included based on a literature review, qualitative interviews, Focus Group Discussion (FGD) and consensus development approach: waiting time, quality of care, travel time, hospital type, provider competency, and hospital facilities. individuals’ preferences for hospital attributes were analyzed using a mixed logit model, and interaction terms were used to assess preference heterogeneity among individuals with different sociodemographic characteristics.

Results

Participants had strong and significant preferences for care delivered in hospitals with ‘full’ (β = 0.6052, p<0.001) or ‘moderate’ (β = 0.5882, p<0.001) hospital equipment and with ‘excellent’ provider competency (β = 0.2637, p<0.001). The estimated coefficients for the "waiting time of 120 minutes" (β = −0.1625, p<0.001) and the "travel time of 30 minutes" (β = −0.1157, p<0.001) were negative and significant. The results also show that the personal characteristics such as age, education level, and income significantly affected individual preferences in choosing a hospital.

Conclusion

Considering people’s preferences can be important given the more active role of today’s patients in decision-making about their treatment processes. The results of this study should be taken into consideration by health policymakers and all stakeholders to be aware of differences in preferences of people and maximize their satisfaction. In this case, it is important to continuously involve people and consider their preferences in the design, topology, construction, and equipment of hospitals.
Physical activity, weight management, and mental health during COVID-19 lockdown: A cross-sectional study of healthcare students in China
Authors: Zhang Rong , Yin Yuhuan , Zhang Yiyin , Feng Yuping , Meng Hongyan , Wang Jing , Zhang Min , Zhang Juxia
Published: October 2024

Background

There is growing evidence that the social blockade brought about by the COVID-19 pandemic has dramatically affected college students’ physical activity; however, their weight management behaviors and mental health have not been fully explored, especially among healthcare students. This study aimed to assess physical activity, weight management behaviors, and mental health among healthcare students during the campus lockdown and to analyze the factors influencing physical activity.

Methods

A cross-sectional survey of 1,216 healthcare students from March 24, 2022, to April 11, 2022. To collect information about students’ physical activity, weight management behaviors, and mental health, they were asked to complete the Physical Activity Questionnaire-Short Form (IPAQ-SF), 11 issues related to weight management behavior, and the World Health Organization 5-Item Well-Being Index (WHO-5) questionnaire. Binary logistic regression was performed to determine the factors influencing physical activity.

Results

Almost half of the participants had low levels of physical activity (45%), the mean score for weight management behavior was 39.55±6.26, and 54.6% had low levels of well-being. Healthcare students without exercise habits during the non-epidemic period reported lower levels of physical activity (OR = 1.81; 95%CI = 1.41–2.34, P<0.001). Participants with poor weight management behavior were more likely than other participants to report lower levels of physical activity (OR = 0.92; 95%CI = 0.90–0.94, P < 0.001). Likewise, the odds of being physically inactive were higher among the happier participants (OR = 0.98; 95%CI = 0.96–0.99, P = 0.031).

Conclusions

During the COVID-19 lockdown, most healthcare students in Gansu province lack physical exercise and have a low health level. Significant correlation factors for low physical activity levels were grade level, non-lockout exercise habits, weight management level, and well-being. These findings demonstrate the importance of developing targeted policies and programs encouraging physical activity among medical students.
Evolving fault diagnosis scheme for unbalanced distribution network using fast normalized cross-correlation technique
Authors: Krishna Ponukumati Balamurali , Sinha Pampa , Paul Kaushik , Mbadjoun Wapet Daniel Eutyche , Hussein Hany S. , Hassan Ammar M. , Mahmoud Mohamed Metwally
Published: October 2024

There has been a lack of a satisfactory solution for identifying and locating evolving faults in unbalanced distribution systems. The proposed approach is based on the cross-correlation technique as a key element for fault detection and location. Evolving faults, in this context, refer to two sequential faults that result in a change of fault phase. The captured QRS value reflects the occurrence of the second fault occurrence. In order to identify Evolving Faults, it makes use of the signal that is currently being monitored at any given point in the network. Typical system occurrences, such as a short circuit fault that grew into another short circuit fault, as well as cross-country faults, are simulated, and according to the suggested technique, they are accurately differentiated from one another. Using a real-time simulator, rigorous simulations are performed on the modified IEEE 240 bus distribution system. The results of these simulations reveal that they have the potential to uncover defects that are constantly changing. Regardless of the fault (location\resistance\inception angle), location of the monitored point, or sample frequency that is selected, the suggested approach is unaffected by any of these factors. In addition, the slime mold optimization approach is utilized in order to get the best monitoring points that accurately identify the bus in which the evolving fault has taken place.
Invasion/chemotaxis- and extravasation-chip models for breast cancer bone metastasis
Authors: Firatligil-Yildirir Burcu , Bati-Ayaz Gizem , Nonappa  , Pesen-Okvur Devrim , Yalcin-Ozuysal Ozden
Published: October 2024

Bone is one of the most frequently targeted organs in metastatic cancers including the breast. Breast cancer bone metastasis often results in devastating outcomes as limited treatment options are currently available. Therefore, innovative methods are needed to provide earlier detection and thus better treatment and prognosis. Here, we present a new approach to model bone-like microenvironments to detect invasion and extravasation of breast cancer cells using invasion/chemotaxis (IC-) and extravasation (EX-) chips, respectively. Our results show that the behaviors of MDA-MB-231 breast cancer cells on IC- and EX-chip models correlate with their in vivo metastatic potential. Our culture model constitutes cell lines representing osteoblasts, bone marrow stromal cells, and monocytes embedded in three-dimensional (3D) collagen I-based extracellular matrices of varying composition and stiffness. We show that collagen I offers a better bone-like environment for bone cells and matrix composition and stiffness regulate the invasion of breast cancer cells. Using in situ contactless rheological measurements under cell culture conditions, we show that the presence of cells increased the stiffness values of the matrices up to 1200 Pa when monitored for five days. This suggests that the cellular composition has a significant effect on regulating matrix mechanical properties, which in turn contribute to the invasiveness. The platforms we present here enable the investigation of the underlying molecular mechanisms in breast cancer bone metastasis and provide the groundwork of developing preclinical tools for the prediction of bone metastasis risk.
Cost-effectiveness of prophylactic ramosetron in the prevention of postoperative nausea and vomiting
Authors: Suh David , Kim Dong-Won , Lee Seung-Mi , Jung Yu-Seon , Jung Sun-Young , Kim Chul-Min
Published: October 2024

Objectives

This study was conducted to assess the cost-effectiveness of prophylactic use of ramosetron compared to no antiemetic medications for the prevention of postoperative nausea and vomiting (PONV) from the healthcare payer and societal perspectives in South Korea.

Method

A decision analytic model was constructed to assess the cost-effectiveness of prophylactic ramosetron use versus no antiemetic therapy at 24-hour and 48-hour periods post-surgery over a 5-day duration. The model was populated using costs and utility parameters from published studies as well as from surveys of an expert panel of physicians using structured questionnaires. The cost parameters included the costs of drugs, treatment, patient time, productivity loss, and transportation. Effectiveness was measured using quality adjusted life years (QALYs). The study outcome was the incremental cost-effectiveness ratio (ICER). The parameter uncertainties were addressed using deterministic and probabilistic scenario analyses.

Results

The base-case analysis showed that, on average, patients treated with prophylactic ramosetron had lower costs from both the healthcare payer (US$16.88 vs US$17.33) and societal (US$16.89 vs US$18.72) perspectives and higher QALYs (0.0121 vs 0.0114) over the 5-day study duration compared to patients without any antiemetic medications. Deterministic and probabilistic sensitivity analyses were conducted to examine the robustness of results for the parameters included in the model. The acceptability curve probability showed that treating patients with ramosetron compared to no antiemetic medications was more than 99% cost-effective at a willingness-to pay threshold of US$5,000/QALY from both payer and societal perspectives.

Conclusion

The results demonstrated that prophylactic use of ramosetron compared to no antiemetic therapy is highly cost-effective to prevent PONV for patients undergoing surgery from both healthcare payer and societal perspectives. The cost effectiveness is the result of the decrease in the incidence of PONV and the direct treatment costs of severe PONV with improved patient quality of life.
The influence of care types on the development of orphans——An empirical study from China
Authors: Liang Ping , Li Haimei , Feng Peng
Published: October 2024

Care typess is considered the cornerstone of orphan’s happiness and health. In 2022, China had more than 190,000 orphans in different types of care. The purpose of the study is to examine the relationship between care types and development of orphans in China. We conducted an empirical study using cross-sectional survey data related to orphans from LZ City, Sichuan Province, China, in 2020. The data sample consists of 320 valid samples of orphans and their families, including 166 boys and 154 girls. The study conducted multiple linear regression model to analyze the relationship between care types and other family variables and the development of orphans. The results indicate that compared with other care types, grandparent care has a significant positive impact on the overall development and psychological status of orphans, with this impact being moderated by the social participation of guardians. The higher the social participation of guardians, the greater the positive impact of grandparent care on the development of orphans. Further analysis, grouped by sex and age, revealed that the effects of care types on orphan development are influenced by the gender and age of orphans. Specifically, girls and younger orphans tend to exhibit better development in a grandparent care family. The research results of this study provide an empirical basis for the government to formulate policies, and for the government, society and family to jointly ensure the better development of orphans.
Enhancing DDoS detection in SDIoT through effective feature selection with SMOTE-ENN
Authors: Behera Arati , Sagar Sahoo Kshira , Kumara Mishra Tapas , Nayyar Anand , Bilal Muhammad
Published: October 2024

Internet of things (IoT) facilitates a variety of heterogeneous devices to be enabled with network connectivity via various network architectures to gather and exchange real-time information. On the other hand, the rise of IoT creates Distributed Denial of Services (DDoS) like security threats. The recent advancement of Software Defined-Internet of Things (SDIoT) architecture can provide better security solutions compared to the conventional networking approaches. Moreover, limited computing resources and heterogeneous network protocols are major challenges in the SDIoT ecosystem. Given these circumstances, it is essential to design a low-cost DDoS attack classifier. The current study aims to employ an improved feature selection (FS) technique which determines the most relevant features that can improve the detection rate and reduce the training time. At first, to overcome the data imbalance problem, Edited Nearest Neighbor-based Synthetic Minority Oversampling (SMOTE-ENN) was exploited. The study proposes SFMI, an FS method that combines Sequential Feature Selection (SFE) and Mutual Information (MI) techniques. The top k common features were extracted from the nominated features based on SFE and MI. Further, Principal component analysis (PCA) is employed to address multicollinearity issues in the dataset. Comprehensive experiments have been conducted on two benchmark datasets such as the KDDCup99, CIC IoT-2023 datasets. For classification purposes, Decision Tree, K-Nearest Neighbor, Gaussian Naive Bayes, Random Forest (RF), and Multilayer Perceptron classifiers were employed. The experimental results quantitatively demonstrate that the proposed SMOTE-ENN+SFMI+PCA with RF classifier achieves 99.97% accuracy and 99.39% precision with 10 features.
Evaluating the quality and reliability of YouTube videos on scabies in children: A cross-sectional study
Authors: Ozdemir Kacer Emine , Kacer Ilayda
Published: October 2024

Background

Recently, there has been an increase in scabies cases among young children in low- and middle-income countries. With the rise of online health information, platforms such as YouTube have become popular sources of disease-related content, but the accuracy of this information remains a concern.

Aim

This study evaluates the reliability and quality of YouTube videos concerning scabies in children to address the lack of research in this area.

Materials and methods

A cross-sectional analysis was conducted on April 1, 2024, reviewing the first 200 relevant YouTube videos with the search terms “scabies” and “scabies in children.” Videos were assessed using modified DISCERN (mDISCERN), Global Quality Score (GQS), and Journal of the American Medical Association (JAMA) scoring systems. Statistical analysis included descriptive statistics, Kruskal-Wallis tests, and Spearman correlation analysis.

Results

Out of 200 videos, 107 met the inclusion criteria. The average mDISCERN score was 2.17, GQS was 2.63, and JAMA was 2.05, indicating generally poor quality. Videos by patients had the highest quality scores, while those from academic institutions had the highest JAMA scores. Longer videos with higher view counts were associated with better quality.

Conclusion

This study reveals that the majority of YouTube videos on scabies in children are of low quality. There is a need for healthcare professionals to produce more accurate and reliable content to improve the quality of information available on YouTube. Further research should focus on enhancing the quality of health information on digital platforms.