bluuebunny/crossref_metadata_2025_split huggingface dataset:
Poetic parodies of Islamic discourses by Abū Nuwās
Authors: van Gelder Geert Jan 
Published: September 2022

Abstract
Abū Nuwās (d. c. 813), one of the greatest and most versatile of Arabic poets,
practised every major genre. His fame and notoriety rest especially on his large corpus of Bacchic verse and love
poetry, most of which is homoerotic. All his poetry is secular: no mystical verse, hymns on God or praise of the
Prophet, but religion is never very far, if not in the foreground then in the background. Much of his verse is
explicitly antinomian, flouting the prescripts of Islam. The present paper deals with his humorous and often obscene
verse parodies of two kinds of Islamic discourse, the waṣiyyah (‘pious instruction’ or ‘testament’),
and Hadith, the corpus of sayings and doings of the prophet Muhammad.
Bilateral comparison of 1 Ω and 10 kΩ standards (ongoing BIPM key comparison BIPM.EM-K13) between the NPLI (India) and the BIPM
Authors: Rolland B , Stock M , Gournay P , Aloysius R P , Kiran U , Hemavathi A , Awana V P S , Biswas J C 
Published: September 2022

Main text
This report gives the result of a bilateral comparison of resistance between the NPLI (India) and the BIPM carried out from August 2021 to April 2022. Two 1 Ω and two 10 kΩ travelling standards belonging to the BIPM were used. The comparison was carried out with an 'A-B-A' pattern of measurements; the standards were measured first at the BIPM for a period of about one month, then for a period of about one month at the NPLI, and finally again at the BIPM. The measurand was the 4 terminal dc resistances at low power. The BIPM was the pilot laboratory, and the comparison forms part of the ongoing BIPM key comparisons BIPM.EM-K13.a (for 1 Ω) and BIPM.EM-K13b (for 10 kΩ).
The results from the NPLI and the BIPM were found to be in good agreement for 1 Ω but not for the 10 kΩ. The difference D is smaller than the relative expanded uncertainty U
c (95% confidence, k = 2) giving D = 0.365 × 10-6, U
c = 0.870 × 10-6 for 1 Ω. The difference D is higher than the relative expanded uncertainty U
c (95% confidence, k = 2) giving D = 0.306 × 10-6, U
c = 0.166 × 10-6 for 10 kΩ.
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Cones with convoluted geometry that always scatter or radiate
Authors: Blåsten Emilia L K , Pohjola Valter 
Published: September 2022

Abstract
We investigate fixed energy scattering from conical potentials having an irregular cross-section. The incident wave can be an arbitrary non-trivial Herglotz wave. We show that a large number of such local conical scatterers scatter all incident waves, meaning that the far-field will always be non-zero. In essence there are no incident waves for which these potentials would seem transparent at any given energy. We show more specifically that there is a large collection of star-shaped cones whose local geometries always produce a scattered wave. In fact, except for a countable set, all cones from a family of deformations between a circular and a star-shaped cone will always scatter any non-trivial incident Herglotz wave. Our methods are based on the use of spherical harmonics and a deformation argument. We also investigate the related problem for sources. In particular if the support of the source is locally a thin cone, with an arbitrary cross-section, then it will produce a non-zero far-field.
Improving the photovoltaic performance of inverted perovskite solar cells via manipulating the molecular packing structure of PCBM
Authors: Chiang Shou-En , Lin Pei-Chen , Wu Jia-Ren , Chang Sheng Hsiung 
Published: September 2022

Abstract
In this study, the molecular packing structure of solution-processed phenyl-C61-butyric acid methyl ester (PCBM) thin film was manipulated by varying the volume ratio of chlorobenzene (CB) to bromobenzene (BrB) from 100:0 to 50:50, which largely influences the device performance of the PCBM/perovskite heterojunction solar cells. Absorbance spectra, photoluminescence spectra, atomic force microscopic images and contact angle images were used to investigate the molecular packing structure effects of the PCBM thin films on the device performance of the inverted perovskite solar cells. Our experimental results show that the formation of PCBM aggregates and the contact quality at the PCBM/perovksite interface significantly influence the open-circuit voltage, short-circuit current density and fill factor of the resultant solar cells simultaneously. It is noted that the PCE of the encapsulated inverted CH3NH3PbI3 (MAPbI3) solar cells exhibited a stable and high power conversion efficiency of 18%.
Validation of a deep learning-based material estimation model for Monte Carlo dose calculation in proton therapy
Authors: Chang Chih-Wei , Zhou Shuang , Gao Yuan , Lin Liyong , Liu Tian , Bradley Jeffrey D , Zhang Tiezhi , Zhou Jun , Yang Xiaofeng 
Published: September 2022

Abstract

Objective. Computed tomography (CT) to material property conversion dominates proton range uncertainty, impacting the quality of proton treatment planning. Physics-based and machine learning-based methods have been investigated to leverage dual-energy CT (DECT) to predict proton ranges. Recent development includes physics-informed deep learning (DL) for material property inference. This paper aims to develop a framework to validate Monte Carlo dose calculation (MCDC) using CT-based material characterization models. Approach. The proposed framework includes two experiments to validate in vivo dose and water equivalent thickness (WET) distributions using anthropomorphic and porcine phantoms. Phantoms were irradiated using anteroposterior proton beams, and the exit doses and residual ranges were measured by MatriXX PT and a multi-layer strip ionization chamber. Two pre-trained conventional and physics-informed residual networks (RN/PRN) were used for mass density inference from DECT. Additional two heuristic material conversion models using single-energy CT (SECT) and DECT were implemented for comparisons. The gamma index was used for dose comparisons with criteria of 3%/3 mm (10% dose threshold). Main results. The phantom study showed that MCDC with PRN achieved mean gamma passing rates of 95.9% and 97.8% for the anthropomorphic and porcine phantoms. The rates were 86.0% and 79.7% for MCDC with the empirical DECT model. WET analyses indicated that the mean WET variations between measurement and simulation were −1.66 mm, −2.48 mm, and −0.06 mm for MCDC using a Hounsfield look-up table with SECT and empirical and PRN models with DECT. Validation experiments indicated that MCDC with PRN achieved consistent dose and WET distributions with measurement. Significance. The proposed framework can be used to identify the optimal CT-based material characterization model for MCDC to improve proton range uncertainty. The framework can systematically verify the accuracy of proton treatment planning, and it can potentially be implemented in the treatment room to be instrumental in online adaptive treatment planning.
Deep learning for automated epileptiform discharge detection from scalp EEG: A systematic review
Authors: Nhu Duong , Janmohamed Mubeen , Antonic-Baker Ana , Perucca Piero , O’Brien Terence J , Gilligan Amanda K , Kwan Patrick , Tan Chang Wei , Kuhlmann Levin 
Published: September 2022

Abstract
Automated interictal epileptiform discharge (IED) detection has been widely studied, with machine learning methods at the forefront in recent years. As computational resources become more accessible, researchers have applied deep learning (DL) to IED detection with promising results. This systematic review aims to provide an overview of the current DL approaches to automated IED detection from scalp electroencephalography (EEG) and establish recommendations for the clinical research community. We conduct a systematic review according to the PRISMA guidelines. We searched for studies published between 2012 and 2022 implementing DL for automating IED detection from scalp EEG in major medical and engineering databases. We highlight trends and formulate recommendations for the research community by analyzing various aspects: data properties, preprocessing methods, DL architectures, evaluation metrics and results, and reproducibility. The search yielded 66 studies, and 23 met our inclusion criteria. There were two main DL networks, convolutional neural networks in 14 studies and long short-term memory networks in three studies. A hybrid approach combining a hidden Markov model with an autoencoder was employed in one study. Graph convolutional network was seen in one study, which considered a montage as a graph. All DL models involved supervised learning. The median number of layers was 9 (IQR: 5–21). The median number of IEDs was 11 631 (IQR: 2663–16 402). Only six studies acquired data from multiple clinical centers. AUC was the most reported metric (median: 0.94; IQR: 0.94–0.96). The application of DL to IED detection is still limited and lacks standardization in data collection, multi-center testing, and reporting of clinically relevant metrics (i.e. F1, AUCPR, and false-positive/minute). However, the performance is promising, suggesting that DL might be a helpful approach. Further testing on multiple datasets from different clinical centers is required to confirm the generalizability of these methods.
Pine caterpillar occurrence modeling using satellite spring phenology and meteorological variables
Authors: Hua Hao , Wu Chaoyang , Jassal Rachhpal S , Huang Jixia , Liu Ronggao , Wang Yue 
Published: September 2022

Abstract
Outbreaks of leaf-feeding Lepidopteran insects substantially weaken the quality of forest trees and strongly affect the ecosystem functions of plant photosynthesis and carbon uptake. The narrow phenological time window of leaf out about ten days, during which Lepidopteran larvae feed on high nutrient newly flushed leaves, may change the insect community and outbreak dynamics by determining the survival rate of larvae. The Chinese pine Caterpillar (Dendrolimus tabulaeformis Tsai et Liu) infestation of the northern Chinese pine (Pinus tabulaeformis) forest in China is a major concern, and accurately modeling the day of insect occurrence (DIO) in the spring remains challenging. With continuous in-situ observed insect activities of 20 plots and satellite and meteorological observations from 1983 to 2014, we found a strong synchronization (r = 0.54, p = 0.001) between the satellite-based vegetation spring phenology, i.e. the green-up day (GUD), and DIO of the pine caterpillar over time. We used partial least squares regression and ridge regression models, and identified that monthly preseason air temperature, wind speed, specific humidity, and downward radiation were key environmental cues that awakened the overwintering pine caterpillars. After removing the collinearity of multiple variables, we showed that the dimensionality reduction-based regression models substantially improved the accuracy of DIO modeling than commonly used models, such as interval and degree-day models. In particular, including GUD significantly enhanced the predictive strength of the models increasing the coefficient of determination (R
2) by 17.1% and consequently a decrease of 16.5% in the root mean square error. We further showed that evapotranspiration changed the environmental moisture content, which indirectly affected the activities of insects. Our results revealed a useful linkage between spring leaf development and insect occurrence, and therefore are of great importance for the large-scale monitoring of pest outbreaks with future remote sensing observations.
Biased random walk on random networks in presence of stochastic resetting: exact results
Authors: Sarkar Mrinal , Gupta Shamik 
Published: September 2022

Abstract
We consider biased random walks on random networks constituted by a random comb comprising a backbone with quenched-disordered random-length branches. The backbone and the branches run in the direction of the bias. For the bare model as also when the model is subject to stochastic resetting, whereby the walkers on the branches reset with a constant rate to the respective backbone sites, we obtain exact stationary-state static and dynamic properties for a given disorder realization of branch lengths sampled following an arbitrary distribution. We derive a criterion to observe in the stationary state a non-zero drift velocity along the backbone. For the bare model, we discuss the occurrence of a drift velocity that is non-monotonic as a function of the bias, becoming zero beyond a threshold bias because of walkers trapped at very long branches. Further, we show that resetting allows the system to escape trapping, resulting in a drift velocity that is finite at any bias.
Energy harvesting of building skins - an innovative renovation for gas-free heating
Authors: Erich S.J.F. , Keizer C. de , Valckenborg R. , Leeuwen S. van , Donkervoort R. , Meulendijks N. , Stuiver A. , Riessen G.J. v. , Weggeman H.J. , Dooremalen M. van , Waterreus E. , Ven H. v.d. 
Published: September 2022

Abstract
Within the framework of the Horizon 2020 project ‘ENVISION’ we have developed a new invisible façade integrated collector panel with a colored solar harvesting coating. This coating system and façade panel is developed with paint company AkzoNobel, prefab element producer Emergo and The Netherlands Organization of Applied Research (TNO). The potential of thermal collectors integrated in the façade is surprisingly high with an annual energy solar gain of 2.5 – 3 GJ/m
2 in a south oriented façade and still a 1 GJ/m
2 in a north facing façade.
Within the framework of the ENVISION-project [1], the performance of these façade collectors were tested at SolarBEAT, the outdoor research facility for innovative solar energy products of TNO. The performance of these panels is measured for different coatings. Laboratory tests have shown that even for the white façade collector up till 35% absorption can be achieved, using a nano-technology modified coating system. This means that we can include the technology seamlessly in all buildings with different colors. It will be a new heat source for heat pumps, next to the commonly accepted sources; air and water (from for example ground loops).
After testing the solution at SolarBEAT, the technologies are demonstrated in demonstrations in Italy and the Netherlands. In Italy, the demonstration focuses at connecting the harvesting panels to a district heating network of the University of Genoa. In the Netherlands, three social houses in Helmond and three social houses in Eindhoven have been renovated using the panels in combination with heat pumps. In Helmond a prefab façade with integrated panels was demonstrated, as well as separate panels on the façade walls. In Eindhoven, besides panels on the façade walls, also an energy shed was developed and shown.
By using the façade collectors with a surface area of 15m
2 as a cold source for a heat pump, sufficient thermal energy is harvested to completely heat a reasonable insulated row dwelling for a whole year, including a strong Dutch winter. In principle, the technology can also be integrated in pre-fab Roof solutions as well as provide cooling next to heating.
Concepts for heat utilization and passive cooling techniques to improve reliability and performance of Building Integrated Photovoltaics (BIPV)
Authors: Ortiz Lizcano Juan Camilo , Calcabrini Andres , Santbergen Rudi , Moya Paul Procel , Zeman Miro , Isabella Olindo 
Published: September 2022

Abstract
When integrated into urban environments, photovoltaic (PV) systems usually present operational temperatures that are significantly higher than those shown by rack-mounted systems. High operating temperatures are associated with reduced reliability of PV modules and significantly impact the electrical performance of solar cells. Utilizing the heat produced on PV modules or reducing operating temperatures can bolster their application within the building sector. We present the three main concepts studied to achieve these goals. First, a PV is a chimney concept that allows the use of the heat generated by the modules. Simulations for a PV chimney installed on a building in the Netherlands showed that although the heat quality produced inside its cavity was low, the potential use of the air mass flow for ventilation applications is promising. Additionally, we present two passive cooling solutions that can reduce the operating temperatures of PV modules: Optical filters and phase change materials. Experimental measurements in Delft showed that these solutions reduce the operating temperature of PV modules between 4 °C to 20 °C, particularly under high irradiance hours.
A second life for school buildings by atelier PRO architects
Authors: Oorschot L M 
Published: September 2022

Abstract
Many educational buildings still do not have proper ventilation systems, are not sustainable in use, and contribute to the spread of Covid-19 viruses. The biggest challenge for the future is to provide attractive, useable, healthy, and sustainable educational buildings in the Netherlands. But is this challenge realistic? Old buildings are usually demolished and replaced by new ones because the government hardly gives any compensation for building renovation or transformation. This leads to the demolition of many school buildings even though the application of new raw materials is not circular and has an impact on our climate and environment. Furthermore, many pre-war buildings are heritage that have a positive impact on neighbourhoods. It is unclear who is responsible for educational buildings, renovation, and financing all the ambitions. The government, the municipality or the school foundation? Problems will soon be exacerbated. At this moment the environmental impact (MilieuPrestatieGebouwen MPG) has no legal base however, this will rapidly change in the age of a circular economy and the upcoming renovation wave. Atelier PRO architects designs many educational buildings and they noticed a change of attitude in conceptualizing educational buildings the last years in the forerunner municipality Amsterdam. Based on these cases and experiences atelier PRO learned their lessons about the ideal renovation towards attractive, healthy and sustainable educational buildings.
A mobile measurement solution for fault detection and diagnosis in buildings
Authors: Rist Tim , Ihlenburg Moritz , Réhault Nicolas 
Published: September 2022

Abstract
Buildings are equipped with increasingly complex Heating, Ventilation and Air Conditioning (HVAC) systems whose energy efficiency can degrade over time because of unnoticed faults. Facility managers (FM) often do not have the time and adapted tools to identify and correct issues. Building Automation Systems generate a multitude of measurement data that can be used to identify operational malfunctions at an early stage by applying fault detection and diagnosis (FDD) methods. However, this data itself can be hardly accessible and contain errors for example due to the degradation of the sensor quality over time. These issues limit the application of analytic methods like FDD in existing buildings. In this paper, we present a prototype implementation of a mobile measurement system based on Internet of Things (IoT) technologies that functions together with an automated FDD system to detect operational faults in HVAC systems independently of the existing measurement infrastructure. Additionally, the solution provides a user interface giving a quick overview on found faults and displaying them in spatial relation with the HVAC system through an integrated BIM visualization. Here, we describe the technical details and the required conditions for the use of our prototype and show the results of an exemplary implementation on an air handling unit.
Energy matching: exploring the value of demand flexibility in educational office buildings
Authors: Vries S B de , Elsayed H , Quaak P , Heller R 
Published: September 2022

Abstract
This research presents a case study exploring the potential for demand side flexibility at a cluster of university buildings. The study investigates the potential of a collection of various electrical devices, excluding heating and cooling systems. With increasing penetration of renewable electricity sources and the phasing out of dispatchable fossil sources, matching grid generation with grid demand will become difficult using traditional grid management methods alone. Additionally, grid congestion is a pressing problem. Demand side management in buildings may contribute to a solution to these problems. Currently demand response is, however, not yet exploited at scale. In part, this is because it is unclear how this flexibility can be translated into successful business models, or whether this is possible under the current market regime. This research gives insight into the potential value of energy demand flexibility in reducing energy costs and increasing the match between electricity demand and purchased renewable electricity. An inventory is made of on-site electrical devices that offer load flexibility and the magnitude and duration of load shifting is estimated for each group of devices. A demand response simulation model is then developed that represents the complete collection of flexible devices. This model, addresses demand response as a ‘distribute candy’ problem and finds the optimal time-of-use for shiftable electricity demand whilst respecting the flexibility constraints of the electrical devices. The value of demand flexibility at the building cluster is then assessed using this simulation model, measured electricity consumption, and data regarding the availability of purchased renewables and day-ahead spot prices. This research concludes that coordinated demand response of large variety of devices at the building cluster level can improve energy matching by 0.6-1.5% and reduce spot market energy cost by 0.4-3.2%.