bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pin the loop taut: a one-player topologame
Authors: SIMON Christopher-Lloyd , STUCKY Ben 
Published: June 2024

Abstract

We introduce a 1-player game called pin the loop and analyse its complexity. A loop is a generic immersion of the circle in a surface, considered up to isotopy. A loop is taut when it is minimally intersecting in its homotopy class. A pinning set of a loop is a set of points P in the surface avoiding the loop, such that the loop is taut in the surface punctured at P. The pinning number is the minimal cardinal of its pinning sets, and a pinning set is optimal if it has that cardinal.
We show that the decision problem associated to computing the pinning number of a plane loop is NP-complete. We implement a polynomial algorithm to check if a given point-set is pinning, adapting a method of Birman--Series for computing intersection numbers of curves in surfaces. After improving a theorem of Hass--Scott characterising taut loops in surfaces, we reduce the problem to a boolean formula whose solutions correspond to the pinning sets. Finally, we reduce the vertex-cover problem for graphs to an instance of the pinning problem for plane loops.
Our results imply that given a closed geodesic in a complete Riemannian surface with punctures, it is hard to guess the location of the punctures from the sole isotopy class of the geodesic in the compactified surface.
Evaluation of the Performance of Rubberized Bitumen
Authors: Udo Johnny J. , Edet Anietie 
Published: June 2024

Abstract

This paper presents the results of the evaluation of rubberized bitumen using crumb rubber as the influence material. Conventional bitumen is the material used in asphalt pavement construction. However, due to its challenges such as initial high cost of construction, rutting, cracking and failure in road construction within shorter time frames of about 0–15 years, an alternative material which is the rubberized bitumen has been recommended as a possible replacement. Rubberized bitumen is an innovative concept which involves the incorporation of crumb rubber derived from discarded tyres into bitumen binders, creating a modified binder with unique properties that contribute to improved pavement characteristics. This research was aimed at partially replacing conventional bitumen – a material often used in the construction of asphalt pavement with rubberized bitumen at varied proportions to evaluate its mechanical properties, in order to ascertain whether or not it is suitable for asphalt pavement construction. Eight (8) numbers of rubberized asphalt samples were prepared using The Marshall Mix Design Method. Varied proportions of rubberized bitumen at 0%, 3%, 6% and 9% were used to evaluate the various mechanical properties such as percentage voids, density, Marshall-stability, flow, and the stiffness of the rubberized asphalt. The results illustrate the relationship between the introduction of modified bitumen and the resistance of the asphalt mix to deformation. Initially, at 0% modification, the stiffness of the asphalt mix was measured at 3.52 KN/mm. As the percentage of modified bitumen was increased to 3%, the stiffness of the asphalt mix improved to 4.47 KN/mm, indicating enhanced resistance to deformation. However, with further increases in the percentage of modified bitumen to 6% and 9%, the stiffness decreased to 3.74 KN/mm and 2.76 KN/mm, respectively. Also, a higher value of stiffness typically suggests a greater resistance to deformation and, consequently, better performance of the asphalt mix. Therefore, the results demonstrate that the introduction of modified bitumen at a 3% concentration significantly improved the stiffness and resistance to deformation of the asphalt mix. However, excessive modification beyond this concentration led to a drop, as evidenced by the decrease in stiffness observed at 6% and 9% modification levels. This suggests an optimal range for the percentage of modified bitumen to achieve the desired stiffness and performance characteristics of the asphalt mix.
The Impact of Biocontrol Bacteria on Cotton Resistance and Their Effects on Signaling Pathways Related to Defense Against Verticillium Wilt Infection
Authors: Fan Yongbin , Cao Jianwei , Liu Yuanyuan , Wu Chongdie , Ye Jingyi , Liu Gaijie , Wang Aiying 
Published: June 2024

Abstract

This study prepared a mixed fermentation broth using two strains of Bacillus and investigated its inhibitory effects on the cotton Verticillium wilt pathogen, as well as its impact on the signaling pathways related to defense against Verticillium wilt infection in cotton.Biocontrol bacteria can effectively defend against plant diseases by competitively inhibiting pathogens and inducing plant immunity. Through plate confrontation assays, antimicrobial tests using mixed microbial fermentation broth and its dilutions, and their impacts on cotton seed germination, this study explores the defensive potential of the mixed fermentation broth.During the study, it was discovered that The mixed microbial fermentation broth could produce lipopeptide substances. The cotton's immunity against Verticillium wilt, following treatment with this broth, was assessed using DAB and trypan blue histological staining methods. Furthermore, the study involved monitoring the induced expression of resistance-related genes (PR1, PR5, NPR1), as well as the effects on the activities of defense-related enzymes in cotton (SOD, CAT, PPO, POD).The results indicate that The combination of two biocontrol bacterial strains exhibited a certain inhibitory effect on the cotton Verticillium wilt pathogen. Root drenching with the mixed fermentation broth significantly enhanced the transient burst of reactive oxygen species in cotton's defense signaling pathways, inducing an immune response. This response increased the sensitivity of cotton's hypersensitive response (HR), induced the expression of disease resistance-related genes, and heightened the activity of enzymes involved in reactive oxygen species scavenging, thereby enhancing systemic acquired resistance (SAR) in cotton. This study reveals that the mixed fermentation broth improved cotton's resistance to Verticillium wilt, significantly affecting the defense signaling pathways in response to the pathogen, with varying effects on induced resistance in different resistance genotypes of cotton.
Efficacy of pre-surgical short-term endocrine therapy during the waiting period for surgery in post-menopausal hormone receptor-positive breast cancer
Authors: Maeda Yuka , Sato Ayana , Matsumoto Akiko , Ikeda Tatsuhiko , Jinno Hiromitsu 
Published: June 2024

Abstract

Purpose
To investigate the efficacy of pre-surgical short-term endocrine therapy (preSTE) and assess prognostic factors, including the preoperative endocrine prognostic index (PEPI) score.
Methods
From October 2012 to November 2021, 269 post-menopausal women diagnosed with hormone receptor-positive (HR+), human epidermal growth factor receptor 2 negative breast cancer underwent endocrine therapy with a non-steroidal aromatase inhibitor during the pre-surgical waiting period. The primary endpoint was to assess the changes in tumor size using ultrasonography, and Ki67 expression levels before and after preSTE. The secondary endpoint was the prognosis of patients categorized using the PEPI score.
Results
The median age of patients was 68 years (range, 41–89 years). The median tumor size was 1.65 cm (range, 0.4–7.5 cm). The average pretreatment Ki67 expression level was 10% (range, 0–90%). The median duration of endocrine therapy was 39 days (range, 2–88 days). Tumor diameter and Ki67 expression levels were significantly decreased to 1.43 cm (range, 0.45–5.83 cm) and 3.0% (range, 0–85%) after preSTE, respectively. After the median observation period of 928 days, patients with PEPI scores ≥ 4 showed worse disease-free survival compared with those with lower PEPI scores. In terms of mortality, patients with PEPI score ≥ 4 had worse overall survival than did patients with lower PEPI scores.
Conclusions
Endocrine therapy during the waiting period for surgery might be effective in reducing tumor size, and the Ki67 expression level and PEPI score might be useful in predicting the prognosis of patients with post-menopausal HR + breast cancer.
Enhancing Photovoltaic Performance of Bi-Doped Perovskite Solar Cells with Novel Double Electron Transport Layer: Achieving High Open-Circuit Voltage and Efficiency
Authors: Khan Muhammad Iftihkar , Hussain Saddam , Mustafa Ghulam M. , Amami Mongi , Rodríguez-Rodríguez Margarita , Pellegrini-Cervantes Manuel J. 
Published: June 2024

Abstract

Perovskite solar cells using pristine and 6% Bi-doped MAPbI2Br perovskite layers are deposited using a spin coating route. XRD analysis reveals that the structure of MAPbI2Br is cubic and the grown films are integrating large grains with low micro-strain. UV-visible spectra of the MAPbI2Br perovskite solar cell and the 6% Bi-doped MAPbI2Br perovskite solar cell show a narrower bandgap (Eg) and higher refractive index. The characteristics of the ETL directly affect the photovoltaic performance of Bi-MAPbI2Br perovskite material. The present report aims to propose a new double electron transport layer composed of TiO2 and Al-SnO2 for MAPbI2Br-based PSCs. In the experimental approach, we reached a high open circuit voltage value of 1.07V, while achieving remarkable power conversion efficiencies of 10.39 %. Notably, this is consistent with the highest Voc achieved so far for Bi-MAPbI2Br-based PSCs with an inorganic electron transport layer (Al-SnO2). The results from this study underscore the importance of the conduction band alignment of MAPbI2Br with the conduction band of Al-SnO2 to enhance electron flow and minimize recombination. This alignment leads to increased Voc and total PCE for PSCs.
Flood characteristics and risk analysis in small watersheds on the Loess Plateau under extreme heavy rainfall
Authors: Imran Muhammad , Hou Jingming , Wang Tian , Zhou Qingshi , Li Donglai , Khan Majid Habib , Ullah Irfan , Noor Rana Shahzad , Umair Muhammad , Hussain Shakeel 
Published: June 2024

Abstract

Climate change disrupts the hydrological cycle of river basins, leading to irregularities in rainfall patterns that can cause devastating floods. A two-dimensional hydrodynamic numerical model, GPU Accelerated Surface Water Flow and Transport was employed to simulate the process of flood progression in a small watershed during periods of heavy rainfall. The objective of this study was to examine the flood characteristics of these basins. Hydraulic properties of typical cross-sections were calculated for rainfall recurrence intervals of 50, 100, 500, and 1000 years, and a thorough assessment of flood vulnerability in the watershed was conducted. The results suggest that the rate of increase in the highest flood level is highest at the 500 year return period for all sections, reaching a value of 51.38%. However, during the span of the 1000 year return period, the growth rate undergoes a decrease to 7.61%. The flood peak growth rate exhibits an initial increase followed by a subsequent decrease as the rainfall return period increases. The maximum increase in water level for each cross-section is less than the corresponding rise in flood peak. The magnitude of floods in the watershed remains relatively consistent despite a larger recurrence interval. To maximize the socio-economic benefits, it is recommended to determine the dimensions of new road and railway bridge culverts in this small watershed according to the flood peak that happens once every 500 years. The research findings serve as vital resources for examining the reaction of small watersheds to heavy rainfall and evaluating flood control technologies.
Seismic Response of Rc Building on Sloping Ground Using Sap2000
Authors: Pujari Atul. B , Undre Abhijeet. R , Patil Santosh. K , Kolhe Mayur S. 
Published: June 2024

Abstract

The structures are generally constructed on level ground; however, due to scarcity of level grounds the construction activities have been started on sloping grounds. There are two types of configuration of building on sloping ground, the one is step back and the other is step back setback. In this study, G+ 8 storeys RCC building and the ground slope varying from 150, 300, 450, 600 have been considered for the analysis. A comparison has been made with the building with and without infill wall. The modelling and analysis of the building has been done by using structure analysis tool SAP2000, to study the effect of varying height of the column in bottom storey and the effect of infill wall during the earthquake. The results have been compared with the results of the building with and without infill wall. The seismic analysis was done by linear static analysis and the response spectrum analyses have been carried out as per IS:1893 (part 1): 2002. The results were obtained in the form of top storey displacement, drift, base shear and time period. It is observed that short column is affected more during the earthquake. The analyses showed that for construction of the building on slopy ground the step back setback building configuration is suitable, along with infill and without infill wall.
Developing a machine learning-based flood risk prediction model for the Indus Basin in Pakistan
Authors: Khan Mehran , Khan Afed Ullah , Ullah Basir , Khan Sunaid 
Published: June 2024

ABSTRACT

Pakistan is highly prone to devastating floods, as seen in the June 2010 and September 2022 disasters. The 2010 floods affected 20 million people, causing 1,985 fatalities. In 2022, approximately 33 million individuals were impacted, with multiple districts declared as ‘calamity struck’ by the National Disaster Management Authority (NDMA). Since June 14th, these floods have caused the loss of approximately 1,400 lives. Hence, the urgent necessity to develop an accurate and efficient flood risk prediction system for early warning purposes in Pakistan. This research aims to address this need by developing a predictive model using machine learning (ML) techniques such as k-nearest neighbors (KNN), support vector machine (SVM), Naive Bayes (NB), artificial neural network (ANN), and random forest (RF) for flood risk prediction in the Indus Basin of Pakistan. The performance of each model was evaluated based on accuracy, precision, recall, and F-measure. The findings revealed that SVM outperformed the other models, achieving an accuracy of 82.40%. Consequently, the results of this study can provide valuable insights for organizations to proactively mitigate frequent flood occurrences in Pakistan, aiding preventive actions.
Clinical and Linguistic Profiles and Challenges in Diagnosis of Primary Progressive Aphasia in Medan, Indonesia: A Hospital-based Study
Authors: Fitri Fasihah Irfani , Rambe Aldy Safruddin , Gustianingsih   , Widayati Dwi 
Published: June 2024

Background
Primary Progressive Aphasia (PPA) is a degenerative condition characterized by progressive loss of language function. Studies on PPA patients in Indonesia are still limited, and none has reported clinical and linguistic profiles of PPA patients who speak Bahasa Indonesia.
This study aimed to describe clinical and linguistic profiles and challenges in the diagnosis of PPA patients from referral hospitals in Medan, Indonesia.

Methods
We retrospectively reviewed the clinical records of patients diagnosed with PPA based on the 2011 diagnostic criteria during the 2022-2023 period and described clinical characteristics data and linguistic profiles using descriptive analysis.

Results
We included 6 cases that fulfilled the diagnostic criteria for PPA. There were 3 cases categorized as nfvPPA, 1 case as svPPA, and 2 cases as lvPPA. There was female predominance (83.3%) and the mean age at onset was 59±2.96 years. The first symptom reported in the nfvPPA group was effortful, non-fluent speech; in svPPA, it was impaired naming and single word comprehension, while in lvPPA, it was impairment in word retrieval. Challenges in diagnosis included the availability of a standardized language tool aimed specifically for PPA in Bahasa Indonesia and the expertise needed to make such a diagnosis.

Conclusion
The main clinical features of the PPA reported were similar to previous findings with specific characteristics of Bahasa Indonesia. Determining language profiles of each variant of PPA in Bahasa Indonesia is crucial to establishing a correct diagnosis. Language assessment tool in Bahasa Indonesia is urgently needed to facilitate better assessment and management planning to improve quality of life.
EVALUASI KINERJA DIRECT EXPANSION SOLAR-ASSISTED HEAT PUMP WATER HEATER KAPASITAS 30 LITER DENGAN MENGGUNAKAN REFRIGERAN R134A
Authors: Irawan Teguh , Mainil Rahmat Iman , Aziz Azridjal 
Published: June 2024

Experiments were carried out to determine the performance of a direct expansion solar assisted heat pump water heater (DX-SAHPWH) which mainly consists of an evaporator panel with a surface area of ​​0.23 m2, a rotary compressor with an input power of 122.5 W, an insulated water tank that has been wrapped around a condenser with a diameter of 0.024 m and a length of 15 m and a capillary tube with a diameter of 0.001 m and a length of 1.61 m. Tests were carried out in open spaces, enclosed spaces and air-conditioned rooms exposed to direct sunlight. The results of this test are that the highest coefficient of performance (COP) on the DX-SAHPWH system is obtained at 1,25 and the smallest COP is obtained at 0.60. The higher intensity of solar radiation has a positive effect on the performance of the DX-SAHPWH system, which results in the heat transfer rate at water (Q wm) increases, the time required for heating is faster, and the COP of the DX-SAHPWH system increases.
Handling Missing Data in COVID-19 Incidence Estimation: Secondary Data Analysis
Authors: Pham Hai-Thanh , Do Toan , Baek Jonggyu , Nguyen Cong-Khanh , Pham Quang-Thai , Nguyen Hoa L , Goldberg Robert , Pham Quang Loc , Giang Le Minh 
Published: June 2024

Abstract

Background
The COVID-19 pandemic has revealed significant challenges in disease forecasting and in developing a public health response, emphasizing the need to manage missing data from various sources in making accurate forecasts.

Objective
We aimed to show how handling missing data can affect estimates of the COVID-19 incidence rate (CIR) in different pandemic situations.

Methods
This study used data from the COVID-19/SARS-CoV-2 surveillance system at the National Institute of Hygiene and Epidemiology, Vietnam. We separated the available data set into 3 distinct periods: zero COVID-19, transition, and new normal. We randomly removed 5% to 30% of data that were missing completely at random, with a break of 5% at each time point in the variable daily caseload of COVID-19. We selected 7 analytical methods to assess the effects of handling missing data and calculated statistical and epidemiological indices to measure the effectiveness of each method.

Results
Our study examined missing data imputation performance across 3 study time periods: zero COVID-19 (n=3149), transition (n=1290), and new normal (n=9288). Imputation analyses showed that K-nearest neighbor (KNN) had the lowest mean absolute percentage change (APC) in CIR across the range (5% to 30%) of missing data. For instance, with 15% missing data, KNN resulted in 10.6%, 10.6%, and 9.7% average bias across the zero COVID-19, transition, and new normal periods, compared to 39.9%, 51.9%, and 289.7% with the maximum likelihood method. The autoregressive integrated moving average model showed the greatest mean APC in the mean number of confirmed cases of COVID-19 during each COVID-19 containment cycle (CCC) when we imputed the missing data in the zero COVID-19 period, rising from 226.3% at the 5% missing level to 6955.7% at the 30% missing level. Imputing missing data with median imputation methods had the lowest bias in the average number of confirmed cases in each CCC at all levels of missing data. In detail, in the 20% missing scenario, while median imputation had an average bias of 16.3% for confirmed cases in each CCC, which was lower than the KNN figure, maximum likelihood imputation showed a bias on average of 92.4% for confirmed cases in each CCC, which was the highest figure. During the new normal period in the 25% and 30% missing data scenarios, KNN imputation had average biases for CIR and confirmed cases in each CCC ranging from 21% to 32% for both, while maximum likelihood and moving average imputation showed biases on average above 250% for both CIR and confirmed cases in each CCC.

Conclusions
Our study emphasizes the importance of understanding that the specific imputation method used by investigators should be tailored to the specific epidemiological context and data collection environment to ensure reliable estimates of the CIR.
The Mediating Role of Human Mobility in Temporal-Lagged Relationships Between Risk Perception and COVID-19 Dynamics in Taiwan: Statistical Modeling for Comparing the Pre-Omicron and Omicron Eras
Authors: Chang Min-Chien , Wen Tzai-Hung 
Published: June 2024

Abstract

Background
The COVID-19 pandemic has profoundly impacted all aspects of human life for over 3 years. Understanding the evolution of public risk perception during these periods is crucial. Few studies explore the mechanisms for reducing disease transmission due to risk perception. Thus, we hypothesize that changes in human mobility play a mediating role between risk perception and the progression of the pandemic.

Objective
The study aims to explore how various forms of human mobility, including essential, nonessential, and job-related behaviors, mediate the temporal relationships between risk perception and pandemic dynamics.

Methods
We used distributed-lag linear structural equation models to compare the mediating impact of human mobility across different virus variant periods. These models examined the temporal dynamics and time-lagged effects among risk perception, changes in mobility, and virus transmission in Taiwan, focusing on two distinct periods: (1) April-August 2021 (pre-Omicron era) and (2) February-September 2022 (Omicron era).

Results
In the pre-Omicron era, our findings showed that an increase in public risk perception correlated with significant reductions in COVID-19 cases across various types of mobility within specific time frames. Specifically, we observed a decrease of 5.59 (95% CI −4.35 to −6.83) COVID-19 cases per million individuals after 7 weeks in nonessential mobility, while essential mobility demonstrated a reduction of 10.73 (95% CI −9.6030 to −11.8615) cases after 8 weeks. Additionally, job-related mobility resulted in a decrease of 3.96 (95% CI −3.5039 to −4.4254) cases after 11 weeks. However, during the Omicron era, these effects notably diminished. A reduction of 0.85 (95% CI −1.0046 to −0.6953) cases through nonessential mobility after 10 weeks and a decrease of 0.69 (95% CI −0.7827 to −0.6054) cases through essential mobility after 12 weeks were observed.

Conclusions
This study confirms that changes in mobility serve as a mediating factor between heightened risk perception and pandemic mitigation in both pre-Omicron and Omicron periods. This suggests that elevating risk perception is notably effective in impeding virus progression, especially when vaccines are unavailable or their coverage remains limited. Our findings provide significant value for health authorities in devising policies to address the global threats posed by emerging infectious diseases.