bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative study of laparoscopic ventral mesh rectopexy versus perineal stapler resection for external full-thickness rectal prolapse in elderly patients: enhanced outcomes and reduced recurrence rates—a retrospective cohort study
Authors: Habeeb T. A. A. M. , Podda M. , Chiaretti M. , Kechagias A. , Lledó J. B. , Kalmoush Abd-Elfattah , Mustafa Fawzy M. , Nassar Mohammed Shaaban , Labib Mohamed fathy , Teama Sobhy rezk ahmed , Elshafey Mohammed Hassan , Elbelkasi Hamdi , Alsaad Mohamed Ibrahim Abo , Sallam Ahmed M. , Ashour Hassan , Mansour Mohamed Ibrahim , Mostafa Abdelshafy , Elshahidy Tamer Mohamed , Yehia Ahmed m. , Rushdy Tamer , Ramadan Alaaedin , Hamed Abd Elwahab M. , Yassin Mahmoud Abdou , Metwalli Abd-Elrahman M.
Published: April 2024

Background

In elderly patients with external full-thickness rectal prolapse (EFTRP), the exact differences in postoperative recurrence and functional outcomes between laparoscopic ventral mesh rectopexy (LVMR) and perineal stapler resection (PSR) have not yet been investigated.

Methods

We conducted a retrospective multicenter study on 330 elderly patients divided into LVMR group (n = 250) and PSR (n = 80) from April 2012 to April 2019. Patients were evaluated before and after surgery by Wexner incontinence scale, Altomare constipation scale, and patient satisfaction questionnaire. The primary outcomes were incidence and risk factors for EFTRP recurrence. Secondary outcomes were postoperative incontinence, constipation, and patient satisfaction.

Results

LVMR was associated with fewer postoperative complications (p < 0.001), lower prolapse recurrence (p < 0.001), lower Wexner incontinence score (p = 0.03), and lower Altomare’s score (p = 0.047). Furthermore, LVMR demonstrated a significantly higher surgery–recurrence interval (p < 0.001), incontinence improvement (p = 0.019), and patient satisfaction (p < 0.001) than PSR. Three and 13 patients developed new symptoms in LVMR and PSR, respectively. The predictors for prolapse recurrence were LVMR (associated with 93% risk reduction of recurrence, OR 0.067, 95% CI 0.03–0.347, p = 0.001), symptom duration (prolonged duration was associated with an increased risk of recurrence, OR 1.131, 95% CI 1.036–1.236, p = 0.006), and length of prolapse (increased length was associated with a high recurrence risk (OR = 1.407, 95% CI = 1.197–1.655, p < 0.001).

Conclusions

LVMR is safe for EFTRP treatment in elderly patients with low recurrence, and improved postoperative functional outcomes.

Trial registration

Clinical Trial.gov (NCT05915936), retrospectively registered on June 14, 2023.
Socio-Behavioural Barriers to Viral Suppression in the Older Adult Population in Rural South Africa
Authors: Chinogurei Chido , Manne-Goehler J. , Kahn K. , Kabudula C. W. , Cornell M. , Rohr J. K.
Published: April 2024

South Africa has the largest share of people living with HIV in the world and this population is ageing. The social context in which people seek HIV care is often ignored. Apart from clinical interventions, socio-behavioural factors impact successful HIV care outcomes for older adults living with HIV. We use cross-sectional data linked with demographic household surveillance data, consisting of HIV positive adults aged above 40, to identify socio-behavioural predictors of a detectable viral load. Older adults were more likely to have a detectable viral load if they did not disclose their HIV positive status to close family members (aOR 2.56, 95% CI 1.89-3.46), resided in the poorest households (aOR 1.98, 95% CI 1.23-3.18), or were not taking medications other than ART (aOR 1.83, 95% CI 1.02-1.99) likely to have a detectable. Clinical interventions in HIV care must be supported by understanding the socio-behavioural barriers that occur outside the health facility. The importance of community health care workers in bridging this gap may offer more optimum outcomes for older adults ageing with HIV.
Using machine learning to predict artistic styles: an analysis of trends and the research agenda
Authors: Valencia Jackeline , Pineda Geraldine García , Pineda Vanessa García , Valencia-Arias Alejandro , Arcila-Diaz Juan , de la Puente Renata Teodori
Published: April 2024

In the field of art, machine learning models have been used to predict artistic styles in paintings. The foregoing is somewhat advantageous for analysts, as these tools can provide more valuable results and help reduce bias in the results and conclusions provided. Therefore, the objective of this research was to examine research trends in the use of machine learning to predict artistic styles from a bibliometric review based on the PRISMA methodology. From the search equations, 268 documents were found, out of which, following the application of inclusion and exclusion criteria, 128 documents were analyzed. Through quantitative analysis, a growing research interest in the subject is evident, progressing from user perception approaches to the utilization of tools like deep learning for art studies. Among the main results, it is possible to identify that one of the most used techniques in the field has been neural networks for pattern recognition. Also, a large part of the research focuses on the use of design software for image creation and manipulation. Finally, it is found that the number of studies focused on contemporary modern art is still limited, this is due to the fact that a large part of the investigations has focused on historical artistic styles.
Comparative analysis of bevacizumab and LITT for treating radiation necrosis in previously radiated CNS neoplasms: a systematic review and meta-analysis
Authors: Gecici Neslihan Nisa , Gurses Muhammet Enes , Kaye Brandon , Jimenez Natasha L. Frontera , Berke Chandler , Gökalp Elif , Lu Victor M. , Ivan Michael E. , Komotar Ricardo J. , Shah Ashish H.
Published: April 2024

Purpose

Radiation necrosis (RN) is a local inflammatory reaction that arises in response to radiation injury and may cause significant morbidity. This study aims to evaluate and compare the efficacy of bevacizumab and laser interstitial thermal therapy (LITT) in treating RN in patients with previously radiated central nervous system (CNS) neoplasms.

Methods

PubMed, Cochrane, Scopus, and EMBASE databases were screened. Studies of patients with radiation necrosis from primary or secondary brain tumors were included. Indirect meta-analysis with random-effect modeling was performed to compare clinical and radiological outcomes.

Results

Twenty-four studies were included with 210 patients in the bevacizumab group and 337 patients in the LITT group. Bevacizumab demonstrated symptomatic improvement/stability in 87.7% of cases, radiological improvement/stability in 86.2%, and steroid wean-off in 45%. LITT exhibited symptomatic improvement/stability in 71.2%, radiological improvement/stability in 64.7%, and steroid wean-off in 62.4%. Comparative analysis revealed statistically significant differences favoring bevacizumab in symptomatic improvement/stability (p = 0.02), while no significant differences were observed in radiological improvement/stability (p = 0.27) or steroid wean-off (p = 0.90). The rates of adverse reactions were 11.2% for bevacizumab and 14.9% for LITT (p = 0.66), with the majority being grade 2 or lower (72.2% for bevacizumab and 62.5% for LITT).

Conclusion

Both bevacizumab and LITT exhibited favorable clinical and radiological outcomes in managing RN. Bevacizumab was found to be associated with better symptomatic control compared to LITT. Patient-, diagnosis- and lesion-related factors should be considered when choosing the ideal treatment modality for RN to enhance overall patient outcomes.
Bolstering stochastic gradient descent with model building
Authors: Birbil Ş. İlker , Martin Özgür , Onay Gönenç , Öztoprak Figen
Published: April 2024

Stochastic gradient descent method and its variants constitute the core optimization algorithms that achieve good convergence rates for solving machine learning problems. These rates are obtained especially when these algorithms are fine-tuned for the application at hand. Although this tuning process can require large computational costs, recent work has shown that these costs can be reduced by line search methods that iteratively adjust the step length. We propose an alternative approach to stochastic line search by using a new algorithm based on forward step model building. This model building step incorporates second-order information that allows adjusting not only the step length but also the search direction. Noting that deep learning model parameters come in groups (layers of tensors), our method builds its model and calculates a new step for each parameter group. This novel diagonalization approach makes the selected step lengths adaptive. We provide convergence rate analysis, and experimentally show that the proposed algorithm achieves faster convergence and better generalization in well-known test problems. More precisely, SMB requires less tuning, and shows comparable performance to other adaptive methods.
Uncertainty Analysis for Ferromagnetic-Paramagnetic Phase Transition Behavior of Magnetic Materials
Authors: Eger Zekeriya Ender , Acar Pinar
Published: April 2024

This study aims to model the phase transition of ferromagnetic materials using two- (2D) and three-dimensional (3D) Ising models, incorporating long-range magnetic spin-to-spin interactions and the influence of an external magnetic field. The 2D Ising model is investigated mainly for a $$4\times 4$$

4
×
4

domain, while its extension to larger domains is also explored. For the 3D Ising model, the selection of representative volume element is discussed in terms of free energy. An uncertainty quantification formulation is integrated into the Ising model to capture the uncertainties related to the external magnetic field and evaluate their effects on the phase transition from a ferromagnetic to a paramagnetic state. Despite the common use and known effectiveness of the Ising model, there is still no universally accepted exact solution for the 3D domains, making it an ongoing research focus. The research also acknowledges the complexities and limitations arising from experimental methods, despite the insights they provide on the microscopic dynamics of ferromagnetic materials during phase transitions.
Elevation Changes in Restored Marshes at Poplar Island, Chesapeake Bay, MD: II. Modeling the Importance of Marsh Development Time
Authors: Morris James T. , Staver Lorie W.
Published: April 2024

Tidal marshes in the Chesapeake Bay are vulnerable to the accelerating rate of sea-level rise (SLR) and subsidence. Restored and created marshes face the same risks as natural marshes, and their resilience to SLR may depend upon appropriate design and implementation. Here, the Coastal Wetland Equilibrium Model (CWEM) was used to assess the resilience of tidal marshes at the Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island (PI) in mid-Chesapeake Bay, MD, where dredged material from navigation channels is being used to create new tidal marshes planted with Spartina alterniflora in the low marsh and S. patens in the high marsh. The site is microtidal with low inorganic sediment inputs, where the rate of marsh elevation change is dominated by the production of organic matter and, therefore, is proportional to net ecosystem production (NEP). The model demonstrated the importance of marsh development for surface elevation gain. In created marshes, the buildout of belowground biomass adds volume and results in faster growth of marsh elevation, but the gains slow as the marsh matures. Elevation gain is the lessor of the recalcitrant fraction of NEP sequestered in sediment or the rate of increase in accommodation space. Marshes can keep up with and fill accommodation space with sequestered NEP up to a tipping point determined by the rate of SLR. The PI low marsh platform was forecasted to drown in about 43 years after construction at the current rate of SLR. Marsh loss can be mitigated by periodic thin layer placement (TLP) of sediment. CWEM was used to simulate PI marsh responses to different TLP strategies and showed that there is an optimal design that will maximize carbon sequestration and resilience depending on the trajectory of mean sea level.
Operation and Productivity Monitoring from Sound Signal of Legacy Pipe Bending Machine via Convolutional Neural Network (CNN)
Authors: Kim Eunseob , Mun Daeseong , Jun Martin B. G. , Yun Huitaek
Published: April 2024

This study introduces a non-invasive approach to monitor operation and productivity of a legacy pipe bending machine in real-time based on a lightweight convolutional neural network (CNN) model and internal sound as input data. Various sensors were deployed to determine the optimal sensor type and placement, and labels for training and testing the CNN model were generated through the meticulous collection of sound data in conjunction with webcam videos. The CNN model, which was optimized through hyperparameter tuning via grid search and utilized feature extraction using Log-Mel spectrogram, demonstrated notable prediction accuracies in the test. However, when applied in a real-world manufacturing scenario, the model encountered a significant number of errors in predicting productivity. To navigate through this challenge and enhance the predictive accuracy of the system, a buffer algorithm using the inferences of CNN models was proposed. This algorithm employs a queuing method for continuous sound monitoring securing robust predictions, refines the interpretation of the CNN model inferences, and enhances prediction outcomes in actual implementation where accuracy of monitoring productivity information is crucial. The proposed lightweight CNN model alongside the buffer algorithm was successfully deployed on an edge computer, enabling real-time remote monitoring.
A framework for identification of brain tumors from MR images using progressive segmentation
Authors: Narayana M. V. , Rao J. Nageswara , Shrivastava Sanjeev , Ghantasala G. S. Pradeep , Ioannou Iacovos , Vassiliou Vasos
Published: April 2024

Purpose

This study addresses the critical health issue of brain tumors, focusing on enhancing the accuracy of tumor segmentation from Magnetic Resonance Imaging (MRI) images. The primary research question investigates the effectiveness of a novel Hybrid Watershed–Clustering framework and its underlying Progressive Segmentation of the MR Images using the Radius and Intensity Measure (PS-RIM) algorithm. The aim is to improve the detection and segmentation of brain tumors within MR images, surpassing the efficacy of current methodologies.

Methods

The methodology involves a three-stage process. In the preprocessing stage, noise reduction and intensity normalization techniques are applied to clarify the images. The next stage is region-based segmentation, which includes morphological processing, edge detection, and thresholding to delineate tumor areas accurately. The final post-processing stage enhances segmentation accuracy and reduces false positives by integrating clustering machine learning techniques, specifically the K-Means cluster algorithm, to refine tumor identification.

Results

The framework's comprehensive evaluation across various MR images shows a significant improvement in accuracy over existing segmentation methods. The PS-RIM algorithm within the framework effectively captures the diverse presentations of tumor appearances in MR images. The research recorded an impressive accuracy rate of 98.11% in tumor detection, demonstrating enhanced identification and segmentation quality.

Conclusions

The study concludes that the proposed Hybrid Watershed–Clustering framework, powered by the PS-RIM algorithm, markedly improves the detection and differentiation of brain tumors in MR images. It exhibits exceptional accuracy, resilience, and computational efficiency. These findings hold substantial potential for advancing computer vision and image analysis in medical diagnostics, which could improve patient outcomes in managing brain tumors.

Graphical abstract
Pomegranate seed oil extraction by cold pressing, microwave and ultrasound treatments
Authors: Gök Aslı , Uyar Hilal , Demir Özge
Published: April 2024

In this study, pomegranate seed oil was extracted by microwave-assisted extraction, ultrasound-assisted extraction, and cold pressing techniques. Dimethyl succinate was the solvent of microwave and ultrasound-assisted extraction methods. The optimum conditions were determined by using response surface methodology (RSM, Design Expert software version 7.0 and Box-Behnken design). The ultrasound-assisted extraction technique was found to be superior to the microwave-assisted extraction technique in terms of extraction efficiency. The maximum extraction efficiency of microwave-assisted extraction was 22.01% under the optimized conditions (liquid/solid ratio, 5/1; time, 3 min; and microwave power, 300 W). The maximum extraction efficiency obtained by ultrasound-assisted extraction was 26.31% under the optimized conditions (liquid/solid ratio, 10/1; pulse duration/pulse interval ratio, 1; temperature 60 °C; and time, 20 min). The extraction efficiencies were compared at the optimum conditions with hexane, which is the most used solvent for pomegranate seed oil extraction, and the difference was insignificant. The results of this study are very important, especially in the field of green chemistry and chemical engineering.
Cumulative Exposure to Natural Hazards and Mental Health in China: Are Older People More Vulnerable or More Resilient Than Younger and Middle-Aged Adults?
Authors: Zhou Shuai , Kwan Crystal
Published: April 2024

Despite the well-documented impacts of single natural hazards like earthquakes, less is known about the psychological adaptation to multiple natural hazards, particularly in rural areas. This study investigated the associations of multiple natural hazards with depression among Chinese adults. Data were retrieved from the China Family Panel Studies conducted during 2010–2018. With a sample of 11,633 Chinese adults, multilevel logistic regression was employed to examine the relationships between natural hazard exposure and depression in the total sample and different age groups. Overall, experiencing four or more natural hazards was associated with a higher risk of being depressed. Regarding hazard type, the number of hydrometeorological and biological hazards was associated with a higher likelihood of depression, whereas the number of geologic and other hazards was related to a lower risk of depression. Middle-aged adults from villages were more likely to be affected by natural hazard exposure than older and younger adults. The findings of this study show that cumulative exposure to natural hazards can generate lasting effects on depressive symptoms, particularly in middle adulthood. The findings also suggest that older adults from rural areas may have accumulated more resilience to mitigate the adverse well-being effects of hazard events. Policies and interventions should enhance disaster awareness and preparation for aging residents from multi-hazard communities.
A biochar selection method for remediating heavy metal contaminated mine tailings
Authors: Ippolito J. A. , Ducey T. F. , Spokas K. A. , Trippe K. M. , Johnson M. G.
Published: April 2024

Approximately 390,000 abandoned mines across the US pose considerable, pervasive risks to human and environmental health; world-wide the problem is even greater. Lime, organic materials, and other amendments have been used to decrease metal bioavailability (e.g., Cd, Cu, Mn, Ni, Zn) in contaminated mine wastes and to promote plant community establishment for tailings stabilization. Biochar properties (e.g., alkaline pH, metal sorbing capabilities, available nutrients, improved soil water retention) make it a potential amendment for remediating metal contaminated mine tailings. A three-step procedure was developed to identify biochars that were most effective at reducing heavy metal availability, retaining metals, and subsequently selecting biochars for use in a soil amendment laboratory trial to ultimately be utilized in heavy metal contaminated mine land settings: Step (1) a synthetic precipitation leaching procedure extract of mine tailings was produced, representing potentially available metals, and used to identify metal removal properties of 28 different biochars (e.g., made from various feedstocks and pyrolysis or gasification conditions); Step (2) evaluate how well biochars retained previously sorbed metals; and Step (3) laboratory evaluation of the most promising biochars that removed and did not releases metals, applied at 0, 1, 2.5, and 5% (by wt) to mine tailings for reducing metal bioavailability. The reported methodology and results from this study could be used to quickly identify specific biochars and application rates to reduce mine tailings metal availability and aid in future remediation of abandoned mine sites globally.
On the irreducibility of local representations of the Braid group $$B_n$$
Authors: Chreif Mohammad Y. , Dally Malak M.
Published: April 2024

We prove that any homogeneous local representation $$\varphi :B_n \rightarrow GL_n(\mathbb {C})$$

φ
:

B
n

→
G

L
n

(
C
)

of type 1 or 2 of dimension $$n\ge 6$$

n
≥
6

is reducible. Then, we prove that any representation $$\varphi :B_n \rightarrow GL_n(\mathbb {C})$$

φ
:

B
n

→
G

L
n

(
C
)

of type 3 is equivalent to a complex specialization of the standard representation $$\tau _n$$

τ
n

. Also, we study the irreducibility of all local linear representations of the braid group $$B_3$$

B
3

of degree 3. We prove that any local representation of type 1 of $$B_3$$

B
3

is reducible to a Burau type representation and that any local representation of type 2 of $$B_3$$

B
3

is equivalent to a complex specialization of the standard representation. Moreover, we construct a representation of $$B_3$$

B
3

of degree 6 using the tensor product of local representations of type 2. Let $$u_i$$

u
i

, $$i=1,2$$

i
=
1
,
2

, be non-zero complex numbers on the unit circle. We determine a necessary and sufficient condition that guarantees the irreducibility of the obtained representation.
Comprehensive evaluation of early-age hydration and compressive strength development in seawater-mixed binary and ternary cementitious systems
Authors: Rathnarajan Sundar , Cendrowski Krzysztof , Sibera Daniel , Sikora Pawel
Published: April 2024

Seawater-mixed concrete (SWC) is a proposed solution for catering to the needs of developing nations facing extremely severe water stress. Recent research works advocate the feasibility of producing SWC by adding supplementary cementitious materials (SCMs) and alternative reinforcements without reducing the engineering properties of the same. However, limited information is available for optimising the type and amount of SCMs in binary and ternary blended SW-mixed cementitious systems for achieving desirable strength development and early-age hydration. A comprehensive study to understand the evolution of heat of hydration and strength up to 28 days was conducted on 31 binder compositions mixed with both fresh water (FW) and seawater (SW). Fly ash, slag, metakaolin, and limestone are the supplementary cementitious materials used with CEM I as a primary binder at a replacement level between 10 and 70%. Isothermal calorimetry results revealed an increase in total heat of hydration and a reduction in setting time with SW-mixed cement pastes compared to their FW-mixed counterparts. Similarly, a significant increase in strength between 0 and 50% was observed in SW-mixed cement pastes. Suitable binder combinations showing an increase in compressive strength and not a significant reduction in strength compared to the CEM I reference mix were identified using the strength improvement factor approach. Binary and ternary blended cementitious, consisting of fly ash, slag, and metakaolin at different replacement levels, are amongst the chosen binder combinations.
Perfednilm: a practical personalized federated learning-based non-intrusive load monitoring
Authors: Pan Zibin , Wang Haosheng , Li Chi , Wang Haijin , Zhao Junhua
Published: April 2024

Non-Intrusive Load Monitoring (NILM) is a valuable technique for breaking down overall power consumption into the energy usage of individual appliances. Understanding power usage patterns through NILM plays an important role in reducing energy costs and achieving carbon reduction goals. However, privacy concerns often deter consumers from sharing their electricity consumption data. To address these privacy concerns, Federated Learning (FL) has been introduced in NILM, which enables the training of NILM models while keeping power consumers’ data locally. However, FL’s reliance on a single global model leads to poor performance on clients with unique power consumption patterns. In response to this challenge, we present a Personalized Federated Learning NILM algorithm (PerFedNILM), a practical personalized FL approach for NILM. PerFedNILM limits the local update bias across clients and trains personalized models for individual clients to improve load-monitoring performance. In addition, it mitigates the negative impact of client dropout, which is a common issue in practice. Our experiments on using real-world energy data demonstrate that PerFedNILM outperforms previous FL-based NILM methods, especially in client dropout scenarios.
VR digital twin of office space with computer vision-based estimation of room occupancy and power consumption
Authors: Mukhopadhyay Abhishek , Talwar Naveen R. , Viswakarma Himanshu , Rajshekar Reddy G. S. , Srivastava Shakti , Pena-Rios Anasol , Biswas Pradipta
Published: April 2024

In the past years, energy consumption has increased rapidly due to many factors, including the rise in technology adoption. This has many downfalls, from higher costs to CO$$_2$$

2

emissions. Human activities in offices and houses represent a considerable amount of energy usage. A digital twin (DT) of an open-plan common space is created, serving the purpose of remote room occupancy monitoring and automatic detection of energy consumption. A virtual reality (VR) model is developed and integrated to temperature, humidity and imaging sensors. For maintaining privacy, images are processed in local computers to measure occupancy levels and live video feed were never transmitted. The same set of imaging sensors were also used in a bespoke computer vision module for energy consumption estimation. The human avatars were mapped with high correlation (R$$^{2}$$

2

$$= 0.85$$

=
0.85

) with actual positions on floor. Our energy consumption algorithm accuracy obtained true positive rate of $$91.58\%$$

91.58
%

and F1 score of $$81.96\%$$

81.96
%

. Finally, all this information is transmitted and visualized to the 3D digital twin for remote monitoring and simulation.
Acute toxicity of rich triethylene glycol on juvenile African freshwater catfish (Clarias gariepinus) around a natural gas dehydration facility
Authors: Aimikhe Victor Joseph , Lazarus Chibuike Weli , Davies Ibienebo Chris
Published: April 2024

Triethylene glycol (TEG) removes equilibrium water from natural gas but may spill during equipment maintenance and other poor safety practices. Studies on the toxicity of rich TEG in aquatic habitats are scarce. In this study, the toxicity of rich TEG on freshwater juvenile African catfish (Clarias gariepinus) test organism was conducted. The experimental design for the toxicity tests was 3 × 5 × 6 factor in a randomized complete block design, with six levels of treatment, observed at five intervals and in three replicates. The acute toxicity was carried out by exposing them to various lethal concentrations of the Rich TEG in solution. Physicochemical parameters, including temperature, dissolved oxygen, pH, conductivity, and total dissolved solids, were measured and recorded for five test concentrations of 25.92, 12.96, 6.48, 3.24, 1.62, and 0.0 ml/l (control). The concentration responses for the fish mortality at 24, 48, 72, and 96 h were also derived. No mortality was observed between Rich TEG concentrations of 0 ml/l to 25.92 ml/l after 72 h of exposure. However, some mortality was observed between 1.62 ml/l to 25.92 ml/l after 96 h of exposure. The highest concentration of 25.92 ml/l recorded a higher mortality of 6.0 ± 0.4, which is an average of 60%, while the lowest mortality was recorded in the control (0 ml/l), at an average of 0% mortality rate. The results underscore the concentration-dependent effects of rich TEG on the test organism, highlighting the need for targeted attention to higher concentration levels.
Factors Contributing to Pharmacies With Good Disaster Preparedness and the Activities of Their Prefectural Pharmaceutical Association: Pharmacies’ resilience and associations
Authors: Ozeki Kayoko , Ojima Toshiyuki
Published: April 2024

Objective:

Pharmacies have a particularly important responsibility to supply medicine to disaster victims in order to save lives. This study investigated the characteristics of pharmacies that are well prepared for disasters as well as the efforts of the prefectural pharmaceutical association (PPA) to which the pharmacies belong.

Methods:

Questionnaires on matters related to disaster preparedness were mailed to 50 randomly selected pharmacies in each of Japan’s 47 prefectures as well as all 47 PPAs in Japan. Logistic regression analysis was performed to examine the association of pharmacy background and the activities of the PPA to which they belong with pharmacy disaster preparedness as well as the association with pharmacies’ awareness of disaster preparedness.

Results:

Pharmacies in prefectures that conducted disaster preparedness training at least three times a year were better prepared for disasters. In addition, pharmacies with high online utilization and high disaster-preparedness awareness were significantly more prepared for disasters.

Conclusions:

Pharmacies that can promptly provide medicine to disaster victims are considered to be well-prepared for disasters. The results suggest that pharmacy preparedness is also influenced by the disaster preparedness activities of their prefectures.
Immediate Adverse Reaction and SARS-CoV-2 Anti-Spike Receptor Binding Domain IgG of COVID-19 Vaccines Among Health Staffs
Authors: Rasheed Waleed S. , Sarkees Alaa Noori
Published: April 2024

Objective:

To contain the spread of coronavirus disease 2019 (COVID-19), several vaccines have been developed. This study is intended to elucidate the level of anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G (anti-SARS-CoV-2-IgG) antibodies for COVID-19 vaccines (Pfizer BioNTech [BNT162b2], Oxford/AstraZeneca [ChAdOx1], and Sinopharm [BBIBP-CorV]) among health staff from health facilities in Duhok province, and it explored the immediate adverse reactions of COVID-19 vaccines among participants.

Methods:

A longitudinal study was conducted from June 1, 2021, to June 30, 2022, and 300 participants were included through simple random sampling.

Results:

The immune response 1 mo after the second dose was significantly higher than the sustained immune after 5 and 9 mo as results revealed that, in 100% of study samples who had (ChAdOx1) vaccine, their antibody titers exceeded the positivity threshold of 1 AU/m, while 96% for (BNT162b2) and 90% for (BBIBP-CorV) for the first test after 1 mo from the second dose of the COVID-19 vaccine, and these rates were reduced to 94.6% for (ChAdOx1), 97.8% for (BNT162b2), and 81.9% for (BBIBP-CorV) at 5 mo after the second dose, while simultaneously the seropositivity rates were more reduced at 9 mo to 46.5% for (ChAdOx1), 67.5% for (BNT162b2), and 9.20% for (BBIBP-CorV). In terms of adverse reactionsss, fever was reported as the most prevalent after the first dose in 58% for ChAdOx1, 43% for BNT162b2, and 23% for BBIBP-CorV, followed by muscle pain, joint pain, and shoulder pain for both doses.

Conclusions:

The implications of the findings from this study are that higher and potentially longer antibody responses can be obtained if the BNT162b2 is given as compared with the other 2 vaccines. Moreover, the booster doses of the COVID-19 vaccine are highly recommended because more than 50% of the participants either have become anti-spike protein negative or have a deficient level of anti-spike protein against COVD-19 vaccines.
Regulatory Approaches Towards AI-Based Medical Device Cybersecurity: A Transatlantic Perspective
Authors: Biasin Elisabetta , Kamenjašević Erik
Published: April 2024

Cybersecurity of medical devices has become a concrete concern for regulators and policymakers in the European Union and United States. Following the COVID-19 pandemic, there has been an increase in cyber-attacks on critical healthcare infrastructures and their IT systems, which have suffered service disruptions and put patients’ health and safety at risk. The increase in cyberattacks on healthcare infrastructure, including medical devices, exacerbated by the growing digitalisation of healthcare services in the EU and the US, has led legislators and regulatory bodies to pay more attention to cybersecurity. Cybersecurity of AI-based medical devices requires the assessment of three areas subject to evolving regulatory approaches: medical devices, Artificial Intelligence (AI), and cybersecurity. Although they may appear distinguished in regulatory matters, the existence of AI-based medical devices and their possible cyber vulnerabilities makes clear that the three are intertwined and deserve closer attention from a regulatory point of view. Few scholars have devoted attention to AI and cybersecurity together. Even less, in our understanding, few comprehensive and EU/US comparative pieces of literature reflect on this specific issue. This paper aims to fill this gap and address the main implications of different regulatory approaches toward AI medical device cybersecurity in the EU and the US. The research stems from the assumption that regulation of medical devices in the EU has been historically inspired by regulatory trends in the US, although with the different cultural, societal, and legal traditions that made them adapt to the specificities of the territory. The paper observes that the US is a rule-based system reflecting a “command-and-control” approach, while the EU system is a principle-based one. While they share the main characteristic of being risk-regulation-based systems, their differences impact how AI-enhanced cybersecurity is regulated.
Similarities and differences between specification and non-uniform specification
Authors: LIN WANSHAN , TIAN XUETING , YU CHENWEI
Published: April 2024

Pavlov [Adv. Math.295 (2016), 250–270; Nonlinearity32 (2019), 2441–2466] studied the measures of maximal entropy for dynamical systems with weak versions of specification property and found the existence of intrinsic ergodicity would be influenced by the assumptions of the gap functions. Inspired by these, in this article, we study the dynamical systems with non-uniform specification property. We give some basic properties these systems have and give an assumption for the gap functions to ensure the systems have the following five properties: CO-measures are dense in invariant measures; for every non-empty compact connected subset of invariant measures, its saturated set is dense in the total space; ergodic measures are residual in invariant measures; ergodic measures are connected; and entropy-dense. In addition, we will give examples to show the assumption is optimal.
Simulating the rheology of dense suspensions using pairwise formulation of contact, lubrication and Brownian forces
Authors: Li Xuan , Royer John R. , Ness Christopher
Published: April 2024

Dense suspensions of solid particles in viscous liquid are ubiquitous in both industry and nature, and there is a clear need for efficient numerical routines to simulate their rheology and microstructure. Particles of micron size present a particular challenge: at low shear rates, colloidal interactions control their dynamics while at high rates, granular-like contacts dominate. While there are established particle-based simulation schemes for large-scale non-Brownian suspensions using only pairwise lubrication and contact forces, common schemes for colloidal suspensions generally are more computationally costly and thus restricted to relatively small system sizes. Here, we present a minimal particle-based numerical model for dense colloidal suspensions that incorporates Brownian forces in pairwise form alongside contact and lubrication forces. We show that this scheme reproduces key features of dense suspension rheology near the colloidal-to-granular transition, including both shear thinning due to entropic forces at low rates and shear thickening at high rates due to contact formation. This scheme is implemented in LAMMPS, a widely used open source code for parallelised particle-based simulations, with a runtime that scales linearly with the number of particles, making it amenable for large-scale simulations.
Low-order modelling of three-dimensional surface waves in liquid film flow on a rotating disk
Authors: Kim Dong Ju , Kim Daegyoum
Published: April 2024

Using low-dimensional numerical simulations, we investigate the characteristics of complex and three-dimensional surface waves in a liquid film flowing over a rotating disk, focusing on large flow rates from a nozzle. Existing integral boundary layer (IBL) models, which are based on spatially averaged variables along the direction normal to the disk surface, have primarily focused on the formation of axisymmetric waves under relatively small flow rates. In this study, an extended IBL model that accounts for both laminar and turbulent regimes is developed by considering the non-uniformity of the local flow rate in the spreading film flow and incorporating closure models dependent on the local Reynolds number. Our numerical results successfully capture the generation of concentric waves by an impinging circular liquid jet and their transition into three-dimensional solitary waves. These findings are in good agreement with visualization images and time-series data of free-surface fluctuations from a displacement sensor. The backscattering of small-scale three-dimensional turbulence into large-scale horizontal turbulence inside the film plays a critical role in determining the transition of wave modes and the nonlinear dynamics of the waves in the turbulent regime. Furthermore, the behaviour of three-dimensional waves in the downstream region, including frequent wave coalescence in the transition region and the breakup of small-scale solitons, is distinct from that of gravity-driven falling film flows. The amplitude of the three-dimensional waves is inversely related to the generalized Reynolds number defined for rotating films.
Understanding the history of 1930s musical migrants to Britain through minimal computing-led digital humanities
Authors: Whitfield Sarah K.
Published: April 2024

This article explores how historical musicology can use computational methods within a minimal computing framework, recovering the performance histories of three migrant musicians, producing valuable new information about their careers. Líza Fuchsová, Maria Lidka, and Paul Hamburger all left Nazi-occupied Europe during the late 1930s and settled permanently in the UK. Fuchsová (1913-1977) was a Czech pianist who became an advocate for Czech musical culture as well as an important piano soloist; Hamburger (1920-2004) was an accompanist and teacher who left Vienna for London and became a senior figure in BBC radio and Guildhall professor; and Lidka (1914-2013) [Marianne Liedtke], was a violinist, orchestra leader and later Royal College of Music professor. Their careers have been underexplored, but machine-read digitised archives have opened new possibilities for finding and sorting what can seem like an overwhelming amount of performance data. This article uses a minimal computing led approach to demonstrate building a robust and accessible structure to interrogate performance data and establish performance histories. This article will demonstrate the value of this framework and will show how it can be applied to historical musicology work.
Breaking the Mold: Normative Hybridity as the Key to Contemporary “Non-Western” Political Theorizing
Authors: ZILIOTTI ELENA
Published: April 2024

What normative compass can appropriately ground a theory for contemporary “non-Western” societies? This question has become urgent amid the pressure to decolonize political science and academia. The hybridity of numerous contemporary non-Western societies means that political theorists cannot refuse to engage with either Western-originated or premodern Indigenous concepts and ways of thinking that bear on the local public culture. However, these normative strands alone are unsuitable for grounding a contemporary theory. This methodological dilemma can be overcome if theorists adopt normative hybridity as a methodological stance. Normative hybridity suggests that hybridity is not only a feature of the theorist’s context of reference but should also be their modus operandi. Normative hybridity already underpins relevant works in contemporary Confucian political theory. Drawing from these works, I illustrate three methods to apply normative hybridity to theory building. This novel methodological approach uniquely addresses current political theory discussions and influences non-Western policymaking.
Explaining Rural Conservatism: Political Consequences of Technological Change in the Great Plains
Authors: DASGUPTA ADITYA , RAMIREZ ELENA
Published: April 2024

Rural areas are conservative electoral strongholds in the United States and other advanced capitalist economies. But this was not always the case. What explains the rise of rural conservatism? This paper argues that technological change transformed not only agriculture but rural political preferences during the twentieth century. It studies a natural experiment: the post-World War II introduction of new irrigation technologies, which enabled farmers to irrigate otherwise arid land in the Great Plains using groundwater. Difference-in-differences analyses exploiting the shock’s differential impact on counties overlying the Ogallala Aquifer—a pattern validated with remote-sensing data—show that technological change contributed significantly to the region’s long-term conservative electoral transformation. Additional analyses, including comparison of individual policy preferences inside/outside the Ogallala Aquifer boundary, suggest that this was due to the rise of capital-intensive agriculture and the growing power of agribusiness. The findings demonstrate how new technologies made new politics in rural America.
Unequal and Unsupportive: Exposure to Poor People Weakens Support for Redistribution among the Rich
Authors: Christensen Matias Engdal , Dinesen Peter Thisted , Sønderskov Kim Mannemar
Published: April 2024

Do the rich become more or less supportive of redistribution when exposed to poor people in their local surroundings? Most existing observational studies find that exposure to poor individuals is positively associated with support for redistribution among the well-off, but one prominent field experiment found a negative link. We seek to resolve these divergent findings by employing a design closer to the studies that have found a positive link, but with more causal leverage than these; specifically, a three-wave panel survey linked with fine-grained registry data on local income composition in Denmark. In within-individual models, increased exposure to poor individuals is associated with lower support for redistribution among wealthy individuals. By contrast, between-individual models yield a positive relationship, thus indicating that self-selection based on stable individual characteristics likely explains the predominant finding in previous work.
A common multi-host parasite shows genetic structuring at the host species and population levels
Authors: Shaw Clara L. , Bilich Rebecca , Duffy Meghan A.
Published: April 2024

Although individual parasite species commonly infect many populations across physical space as well as multiple host species, the extent to which parasites traverse physical and phylogenetic distances is unclear. Population genetic analyses of parasite populations can reveal how parasites move across space or between host species, including helping assess whether a parasite is more likely to infect a different host species in the same location or the same host species in a different location. Identifying these transmission barriers could be exploited for effective disease control. Here, we analysed population genetic structuring of the parasite Pasteuria ramosa in daphniid host species from different lakes. Outbreaks occurred most often in the common host species Daphnia dentifera and Daphnia retrocurva. The genetic distance between parasite samples tended to be smaller when samples were collected from the same lake, the same host species and closer in time. Within lakes, the parasite showed structure by host species and sampling date; within a host species, the parasite showed structure by lake and sampling date. However, despite this structuring, we found the same parasite genotype infecting closely related host species, and we sometimes found the same genotype in nearby lakes. Thus, P. ramosa experiences challenges infecting different host species and moving between populations, but doing so is possible. In addition, the structuring by sampling date indicates potential adaptation to or coevolution with host populations and supports prior findings that parasite population structure is dynamic during outbreaks.
Monumental Walls, Sovereign Power and Value(s) in Pharaonic Egypt
Authors: Siegel Oren
Published: April 2024

Large walling projects are among the most visible features in the archaeological record. However, enclosure walls remain relatively under-theorized relative to other monumental buildings. In an attempt to move beyond simple explanations that analyse walls solely as defensive features or symbols, I link monumental walls to notions of sovereign power and action-oriented theories of value(s). Using examples from Pharaonic Egypt, I argue that monumental enclosure walls were attempts to define and realize particular social totalities, whether these were a temple complex, a royal tomb or an urban centre. If all efforts at border-making are also an exercise in power, walls have the potential to illuminate some of the goals and values of those ordering their construction. By analysing changes and continuities related to which structures required the protection of a monumental enclosure wall over time, it is possible to shed light on the fluid priorities of the most important political actors in Pharaonic society. Yet the very presence of a wall implies potential dissent and alternative practices—otherwise a wall's construction would not have been necessary.
Transcatheter knocking of a stuck mechanical tricuspid valve
Authors: Herron Christopher , Morales David , Shahanavaz Shabana
Published: April 2024

Immobilisation of mechanical valve leaflets can be a life-threatening complication. In the acute setting, medical therapy can be attempted but is not always successful. We present the first described case of a patient with a mechanical tricuspid valve with recurrent leaflet immobilisation that was able to be mobilised using a transcatheter knocking technique.
A successful surgical management for a thrombosed giant left coronary aneurysm with right ventricular fistula in a young patient
Authors: Lu Yunyi , Wang Jing , Ma Liheng
Published: April 2024

Giant coronary aneurysm with ventricular fistula is rare. Due to the limited data from randomised clinical trials, therapeutic strategies for coronary aneurysms predominantly rely on on case series and anecdotal evidences. Reporting cases that provide practical experience in managing these aneurysms is therefore crucial. In this article, we report a rare case of a successful surgical management for a thrombosed giant left coronary aneurysm with right ventricular fistula, which is larger than any previously reported cases.