bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cycling Route Mapping via Cartography and GIS Techniques
Authors: Mustapha Nurul Iffah , Rasam Abdul Rauf Abdul , Saraf Noraain Mohamed , Idris Roslina , Wakijan Azizah 
Published: September 2023

Abstract
Cycling has been embraced as a mode of transportation with numerous health and environmental benefits, yet it is underfunded and needs more priority in many central cities in Malaysia. Despite a will from the Shah Alam City Council (MBSA) to enhance sustainable transport, cycling requires being accorded its due position in urban areas. It implies the presence of bottlenecks and barriers in the cycle route map. A cycling or bike map is designed specifically for cyclists addressed in the city using cartography and Geographical Information System (GIS) techniques. Four stages of operations were applied in the study, including a preliminary study, data collection, data processing and data visualization. The first result identified the significant criteria and features of the cycling route map since there are no specific features or concepts in designing the ideal cycling route map of the city. The criteria include the essential elements of cartography, the ideal design of cartography content and principle and relevant features in a standard cycling map. A proposed cycling route map was created with significant features such as route routes, route information, point of interest, land use and sign, and designated cycle route. The map testing revealed that the proposed map was practical since respondents had positive feedback. Having a suitable cycling map will benefit the cyclist to become one of the modes of transportation in the city.
The Exploratory Study of Normalized Indicator of Heat Vulnerability Index (HVI) By Using Functional Relationship
Authors: Latif Siti Zubaidah Abdul , Salleh Siti Aekbal , Salim Pauziyah Mohamad , Saraf Noraain Mohamed , Halim Maisarah Abdul , Idris Ahmad Norhisyam , Mustaha Emad , Pintor Lynlei 
Published: September 2023

Abstract
Extreme urban heat, a major environmental stressor caused by urbanisation, poses a substantial hazard to human health and well-being. The environmental, demographic, and health-related risk factors for heat stress must be identified as the urban population grows. As a result, this study provides insight into city people’ heat susceptibility and its extent at the district level. This examination was carried out using a multivariate index that included evaluations of the exposure, sensitivity, and coping ability components. Using nine indicators for three different characteristics, this study examined data on the spatial distribution from diverse sources such as satellite imaging processing and quantitative analysis output. This study employed a normalised indicator method that used functional relationships to normalise all of the indicators in the unit or a scale-free method. The index’s value of each parameter is then processed using weightage formula. Kuala Lumpur district has been rated as the most vulnerable to heat, followed by Petaling and Hulu Langat, according to the heat vulnerability index produced. The findings demonstrated a regional pattern of heat vulnerability, with significant differences between individual spatial indexes. While exposure and adaptive capacities have a distinct regional pattern, sensitivity has a more complicated spatial pattern. All factors were statistically significant as markers in the development of the heat vulnerability index, according to this study. In a highly dynamic metropolitan region, these criteria can be used for both urban planning and suggesting special strategies to reduce heat dangers.
Spatial Distribution and the Influence of Surface Temperature and Green Area on Sea Turtle Nesting Sites in Peninsular Malaysia
Authors: Fadli S N , Idris N H , Osman M J , Othman N , Ishak M H I 
Published: September 2023

Abstract
Malaysia is home to four of the seven sea turtles in the world, with Malaysian islands being one of the potential areas for sea turtle landing and nesting. However, sea turtles are classified as endangered species because they face extinction mainly due to land use changes, human marine activities, and environmental factors. As a result, they are now among the most important resources for ecotourism. Green turtles are the most prevalent species (endangered), while the hawksbill turtle is one of the world’s most seriously endangered marine turtle species today. Hence, considering the importance of improving turtle habitat in Malaysia, this study investigated the sea turtle’s nesting site preference in Peninsular Malaysia using spatial analysis. The objectives of this study are (1) to map sea turtle nesting sites in Peninsular Malaysia for five years (from 2017-2021) and (2) to identify the influence of surface temperature and landscape characteristics on sea turtle nesting habitats. This study used the binomial regression method to determine the significant environmental factors such as temperature, distance from the green area and the coastal line that could influence the preference for sea turtle habitat. The results show a positive relationship between temperature and that more sea turtles will nest and land in the area with the higher temperature. Also, more sea turtles prefer to land and nest near green areas. These findings confirmed the influence of green areas in turtle nesting sites in Peninsular Malaysia. It could assist the authorities in further understanding the importance of green areas in turtle nesting site preference and developing a mitigation plan to protect sea turtle habitat.
Landslide Susceptibility Mapping in Ampang Jaya: Comparing Probabilistic Method and Weighted Overlay Method
Authors: Samsul Siti Nur Aishah , Idris Roslina , Zulkarnain Siti Hafsah , Ahmad Che Bon , Rasam Abdul Rauf , Idris Mohd Rizal 
Published: September 2023

Abstract
When it came time to produce the map, the entire district of Ampang Jaya was chosen as the area for the research. These two approaches gave very different results in terms of accuracy. The results of the map were categorised using a range of different classification techniques, some of which include Natural Breaks and Equal Interval, respectively. Various landslide susceptibility hazard zoning results were found when the two different classification systems were applied to the data. These zoning areas need to go through an accuracy assessment process in order to be validated. The accuracy of the model was evaluated by comparing the findings about the historical locations of landslide occurrences with the findings regarding the susceptibility hazard locations of potential landslide areas. Because the accuracy of the Probabilistic technique was 66.67% for Equal Interval and 73.33% for Natural Breaks, respectively, this demonstrates that the Probabilistic method produces more dependable results than the Weighted Overlay method produces. Therefore, the accuracy assessment results indicate that the probabilistic method provides more reliable information for accuracy assessment than the Weighted Overlay method. This is due to the fact that the result of the accuracy assessment obtained from Weighted Overlay is significantly lower than that obtained from Probabilistic for each classification technique.
Leveraging Google Earth Engine (GEE) for determining land use and land cover changes around Tasik Chini Malaysia.
Authors: Akhir Nurul Syazna Mat , Salim Pauziyah Mohammad , Yusoff Zaharah Mohd 
Published: September 2023

Abstract
This study explores the capability of Google Earth Engine in determining land use and land cover changes around Tasik Chini Malaysia which is one of the tourism areas severely affected by landscape changes. Two Landsat satellite composite data spanning ten years of difference and Machine Learning Approach algorithm namely Random Forest (RF) and Support Vector machine (SVM) are used to create landuse land cover changes (LULCC) map of the area. GEE is capable of processing time series data as well as performing temporal aggregation. In our case median metrics is used in creating many different alternatives of image composites for creating the LULC map with ease but accurate result. It is an excellent alternative for geospatial and big data analysts for both advance and novice users in processing long term EO dataset especially in dealing with many imageries. The best classification accuracy with the highest Overall Accuracy (OA) is by using Random Forest classifier with 81.58% for the year 2010 and 83.59% for 2020. The Kappa coefficient of both years are 0.75 and 0.78. It is found using this technique, Tasik Chini lost about 6600 hectares of forest area and an increase of bareland and develop area especially around the Tasik Chini lake due to the reported increase of mining activities for the past few years.
Dielectric breakdown and sub-wavelength patterning of monolayer hexagonal boron nitride using femtosecond pulses
Authors: Ahmad Sabeeh Irfan , Dave Arpit , Sarpong Emmanuel , Yao Hsin-Yu , Solomon Joel M , Jiang Jing-Kai , Luo Chih-Wei , Chang Wen-Hao , Her Tsing-Hua 
Published: September 2023

Abstract
Hexagonal boron nitride (hBN) has emerged as a promising two-dimensional (2D) material for many applications in electronics and photonics. Although its linear and nonlinear optical properties have been extensively studied, the interaction of hBN with high-intensity laser pulses, which is important for realizing high-harmonic generation, creating deterministic defects as quantum emitters, and resist-free patterning in this material, has not been investigated. Here we report the first systematic study of dielectric breakdown in chemical vapor deposition (CVD)-grown hBN monolayers induced by single femtosecond laser pulses. We report a breakdown fluence of 0.7 J cm−2, which is at least 7× higher than that of other monolayer 2D materials. A clean removal of hBN without leaving traces behind or causing lateral damage is demonstrated. The ablation features exhibit excellent fidelity with very small edge roughness, which we attribute to its ultrahigh fracture toughness due to its heterogeneous nature with three-fold symmetry. Moreover, even though defects are known to be abundant in CVD-grown hBN, we show experimentally and theoretically that its nonlinear optical breakdown is nearly intrinsic as defects only marginally lower the breakdown threshold. On top of this, we observe that hBN monolayers have a 4–5× lower breakdown threshold than their bulk equivalent. The last two observations can be understood if the carrier generation in monolayers is intrinsically enhanced due to its 2D nature. Finally, we demonstrate laser patterning of array of holes and lines in hBN with sub-wavelength feature sizes. Our work advances the fundamental knowledge of light-hBN interaction in the strong field regime and firmly establishes femtosecond lasers as novel and promising tools for resist-free patterning of hBN monolayers with high fidelity.
Raman study of layered breathing kagome lattice semiconductor Nb3Cl8
Authors: Jeff Dylan A , Gonzalez Favian , Harrison Kamal , Zhao Yuzhou , Fernando Tharindu , Regmi Sabin , Liu Zhaoyu , Gutierrez Humberto R , Neupane Madhab , Yang Jihui , Chu Jiun-Haw , Xu Xiaodong , Cao Ting , Khondaker Saiful I 
Published: September 2023

Abstract
Niobium chloride (Nb3Cl8) is a layered two-dimensional semiconducting material with many exotic properties including a breathing kagome lattice, a topological flat band in its band structure, and a crystal structure that undergoes a structural and magnetic phase transition at temperatures below 90 K. Despite being a remarkable material with fascinating new physics, the understanding of its phonon properties is at its infancy. In this study, we investigate the phonon dynamics of Nb3Cl8 in bulk and few layer flakes using polarized Raman spectroscopy and density-functional theory (DFT) analysis to determine the material’s vibrational modes, as well as their symmetrical representations and atomic displacements. We experimentally resolved 12 phonon modes, five of which are A
1g
modes while the remaining seven are Eg
modes, which is in strong agreement with our DFT calculation. Layer-dependent results suggest that the Raman peak positions are mostly insensitive to changes in layer thickness, while peak intensity and full width at half maximum are affected. Raman measurements as a function of excitation wavelength (473–785 nm) show a significant increase of the peak intensities when using a 473 nm excitation source, suggesting a near resonant condition. Temperature-dependent Raman experiments carried out above and below the transition temperature did not show any change in the symmetries of the phonon modes, suggesting that the structural phase transition is likely from the high temperature P

3
m

ˉ

1 phase to the low-temperature R

3
m

ˉ

phase. Magneto-Raman measurements carried out at 140 and 2 K between −2 and 2 T show that the Raman modes are not magnetically coupled. Overall, our study presented here significantly advances the fundamental understanding of layered Nb3Cl8 material which can be further exploited for future applications.
Rediscovering orbital mechanics with machine learning
Authors: Lemos Pablo , Jeffrey Niall , Cranmer Miles , Ho Shirley , Battaglia Peter 
Published: September 2023

Abstract
We present an approach for using machine learning to automatically discover the governing equations and unknown properties (in this case, masses) of real physical systems from observations. We train a ‘graph neural network’ to simulate the dynamics of our Solar System’s Sun, planets, and large moons from 30 years of trajectory data. We then use symbolic regression to correctly infer an analytical expression for the force law implicitly learned by the neural network, which our results showed is equivalent to Newton’s law of gravitation. The key assumptions our method makes are translational and rotational equivariance, and Newton’s second and third laws of motion. It did not, however, require any assumptions about the masses of planets and moons or physical constants, but nonetheless, they, too, were accurately inferred with our method. Naturally, the classical law of gravitation has been known since Isaac Newton, but our results demonstrate that our method can discover unknown laws and hidden properties from observed data.
Double quantum dots in atomically-precise graphene nanoribbons
Authors: Zhang Jian , Qian Liu , Borin Barin Gabriela , Chen Peipei , Müllen Klaus , Ruffieux Pascal , Fasel Roman , Zhang Jin , Calame Michel , Perrin Mickael L 
Published: September 2023

Abstract
Bottom-up synthesized graphene nanoribbons (GNRs) are precise quantum materials, offering a high degree of tunability of their physical properties. While field-effect transistors and single quantum dot (QD) devices have been reported, the fabrication of double QD devices using GNRs remains challenging due to their nanometer-scale dimensions. In this study, we present a multi-gate double QD device based on atomically precise GNRs that are contacted by a pair of single-walled carbon nanotube electrodes. At low temperatures, the device can be tuned with multiple gates and reveals triangular features characteristic for charge transport through a double QD system. From these features, the QD level spacing, as well as the interdot tunnel coupling and lead-dot tunnel couplings are extracted. Double QD systems serve as essential building blocks for developing different types of qubits based on atomically precise GNRs.
Gut microbiome correlates with plasma lipids in amyotrophic lateral sclerosis
Authors: Guo Kai , Figueroa-Romero Claudia , Noureldein Mohamed H , Murdock Benjamin J , Savelieff Masha G , Hur Junguk , Goutman Stephen A , Feldman Eva L 
Published: September 2023

Abstract
Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease. Disease pathophysiology is incompletely understood but evidence suggests gut dysbiosis occurs in ALS, linked to impaired gastrointestinal integrity, immune system dysregulation and altered metabolism. Gut microbiome and plasma metabolome have been separately investigated in ALS, but little is known about gut microbe-plasma metabolite correlations, which could identify robust disease biomarkers and potentially shed mechanistic insight. Here, gut microbiome changes were longitudinally profiled in ALS and correlated to plasma metabolome. Gut microbial structure at the phylum level differed in ALS versus control participants, with differential abundance of several distinct genera. Unsupervised clustering of microbe and metabolite levels identified modules, which differed significantly in ALS versus control participants. Network analysis found several prominent amplicon sequence variants strongly linked to a group of metabolites, primarily lipids. Similarly, identifying the features that contributed most to case versus control separation pinpointed several bacteria correlated to metabolites, predominantly lipids. Mendelian randomization indicated possible causality from specific lipids related to fatty acid and acylcarnitine metabolism. Overall, the results suggest ALS cases and controls differ in their gut microbiome, which correlates with plasma metabolites, particularly lipids, through specific genera. These findings have the potential to identify robust disease biomarkers and shed mechanistic insight into ALS.
Description of Cryptococcosis Following SARS-CoV-2 Infection: A Disease Survey Through the Mycosis Study Group Education and Research Consortium (MSG-19)
Authors: Walker Jeremey , McCarty Todd , McGwin Gerald , Ordaya Eloy E , Vergidis Paschalis , Ostrosky-Zeichner Luis , Mammadova Mehriban , Spec Andrej , Rauseo Adriana M , Perfect John , Messina Julia , Vilchez Gabriel , McMullen Rachel , Jones Carolynn T , Pappas Peter G ,   for the Mycoses Study Group Education and Research Consortium (MSGERC) Cryptococcal Registry Cohort, Yetmar Zachary , Masayuki Nigo , Steinbrink Julie , Cahuayme-Zuniga Lizbeth , Vootukuri Shobha , Onyeaghala Chizaram , Ta Tuan V , Kale Pratibha , Franklin Alexander , Gandhi Ravi , Ostrander Darin , Miceli Marisa , Warner Nathaniel , Thomas Lora , Obeid Karam , La Hoz Ricardo M , Sochanska Ada , Klausing Benjamin , El-Herte Rima , Tirmizi Amir , Traver Edward C , Thompson George R , Gorsline Chelsea , Sivasubramanian Geetha , Osborn Rebecca , Mounajjed Mark 
Published: September 2023

Abstract

Background
Invasive fungal infections have been described throughout the COVID-19 pandemic. Cryptococcal disease after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported in several isolated case reports and 1 larger case series. We sought to describe cryptococcal infections following SARS-CoV-2 through establishing a database to investigate underlying risk factors, disease manifestations, and outcomes.

Methods
We created a crowdsourced call for cases solicited through the Mycoses Study Group Education and Research Consortium, the Centers for Disease Control and Prevention Emerging Infectious Diseases Network, and infectious diseases Twitter groups. Data were collected in a web-based and secure REDCap survey without personal identifiers.

Results
Sixty-nine cases were identified and submitted by 29 separate institutional sites. Cryptococcosis was diagnosed a median of 22 days (interquartile range, 9–42 days) after SARS-CoV-2 infection. Mortality among those with available follow-up was 72% (26/36) for the immunocompetent group and 48% (15/31) for the immunocompromised group (likelihood ratio, 4.01; P = .045). We observed a correlation between disease manifestation (central nervous system infection, proven/probable disseminated disease, and respiratory) and mortality (P = .002).

Conclusions
The mortality rate of 59% for patients with cryptococcosis following SARS-CoV-2 is higher than that of modern Cryptococcus cohorts. There was an association between immunocompromised status and cryptococcal disease manifestations as well as mortality. Moreover, our series emphasizes the need for clinical and laboratory assessment of opportunistic infections beyond 30 days when concerning symptoms develop.
Urinary markers of the alternative and lectin complement pathway are increased in IgA vasculitis nephritis
Authors: Marro Julien , Chetwynd Andrew J , Hawkes Jennifer , Northey Sarah J , Oni Louise 
Published: September 2023

ABSTRACT

Background
IgA vasculitis (IgAV) is the most common form of childhood vasculitis. Nephritis (IgAVN) occurs in 50% of patients and 1–2% progress to chronic kidney disease stage 5. The pathophysiology of nephritis remains largely unknown, but recent evidence suggests that the complement system may be involved. The aim of this cross-sectional study was to explore whether there is evidence of alternative and/or lectin complement pathway activation in children with IgAVN.

Methods
Children with IgAV were recruited and grouped according to proteinuria: IgAVN or IgAV without nephritis (IgAVwoN). Age and sex-matched healthy controls (HCs) were also recruited. Cross-sectional urine and plasma concentrations of complement factor D (CFD), factor B (CFB), and MBL-associated protease 1 (MASP-1) were performed using commercially available enzyme-linked immunoassays.

Results
A total of 50 children were included (IgAVN, n = 15; IgAVwoN, n = 20, HCs, n = 15). The mean age was 8.5 ± 3.7 years old, male:female ratio was 1:1. Urinary CFD and CFB concentrations were statistically significantly increased in children with IgAVN (3.5 ± 5.4 μg/mmol; 25.9 ± 26.5 μg/mmol, respectively) compared to both IgAVwoN (0.4 ± 0.4 μg/mmol, P = 0.002; 9.2 ± 11.5 μg/mmol, P = 0.004) and HCs (0.3 ± 0.2 μg/mmol, P &lt; 0.001; 5.1 ± 6.0 μg/mmol, P &lt; 0.001). No statistically significant difference was reported for the plasma concentrations of CFD and CFB. Urinary MASP-1 concentrations were statistically significantly increased in IgAVN (116.9 ± 116.7 ng/mmol) compared to HCs (41.4 ± 56.1 ng/mmol, P = 0.006) and plasma MASP-1 concentrations were increased in IgAVwoN (254.2 ± 23.3 ng/mL) compared to HCs (233.4 ± 6.6 ng/mL, P = 0.046).

Conclusion
There is evidence of complement pathway products in the urine of children with IgAVN that warrants further investigation.
Odor cues rather than personality affect tadpole deposition in a neotropical poison frog
Authors: Peignier Mélissa , Ringler Max , Ringler Eva 
Published: September 2023

Abstract
Animals constantly need to evaluate available external and internal information to make appropriate decisions. Identifying, assessing, and acting on relevant cues in contexts such as mate choice, intra-sexual competition, and parental care is particularly important for optimizing individual reproductive success. Several factors can influence decision-making, such as external environmental cues and the animal’s own internal state, yet, we have limited knowledge on how animals integrate available information. Here, we used an entire island population (57 males, 53 females, and 1,109 tadpoles) of the neotropical brilliant-thighed poison frog Allobates femoralis to investigate how 2 factors (olfactory cues and personality traits) influence the ability of males to find and use new resources for tadpole deposition. We experimentally manipulated the location of tadpole deposition sites and their associated olfactory cues, and repeatedly measured exploration and boldness in adult males. We further reconstructed tadpole deposition choices via inferred parent–offspring relationships of adult frogs and tadpoles deposited in our experimental pools using molecular parentage analysis. We found that the discovery and use of new rearing sites were heavily influenced by olfactory cues; however, we did not find an effect of the measured behavioral traits on resource discovery and use. We conclude that in highly dynamic environments such as tropical rainforests, reliable external cues likely take priority over personality traits, helping individuals to discover and make use of reproductive resources.