bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analyzing the relationship between water pollution and economic activity for a more effective pollution control policy in Bali Province, Indonesia
Authors: Chapagain Saroj Kumar , Mohan Geetha , Rimba Andi Besse , Payus Carolyn , Sudarma I Made , Fukushi Kensuke 
Published: July 2021

Abstract
An adequate water supply is essential for the continued and sustainable growth of the Balinese economy. In addition to mounting water demand, Bali’s water supply has been compromised by high levels of water pollution. Despite being paid great attention, Bali’s earlier efforts to control water pollution yet to prove effective, mainly owing to their reliance on traditional methods and regulations that focus on water pollution being linked to discrete sets of economic activity (e.g., processing industries, livestock farming, and hotels). However, all economic sectors are interconnected through supply chains; thus, water pollution is the combined result of all sectors’ environmental performance. Therefore, determining the structural relationships between water pollution and economic activity serves as an important basis for more effective forms of pollution control for the Balinese economy. In this study, accordingly, we employed an environmentally extended input–output model to establish the links between water pollution and the production processes of the entire economy. Using biochemical oxygen demand (BOD) as a proxy for water quality in our analysis, we estimated that 246,868 tons of BOD were produced from Bali’s economic activity in 2007. Further, we identified the chief BOD-emitting sectors and found that intermediate demand and household demand were the major causes of BOD discharge in the economy. Utilizing supply chain relationships, we also accounted for the indirect role of each sector in total BOD emissions. Moreover, we categorized the sectors into four groups based on their direct and indirect BOD emission characteristics and offered appropriate policy measures for each group. Managing demand (i.e., lowering household consumption and exports) and shifting input suppliers (i.e., from polluters to non-polluters) are effective measures to control pollution for Categories I and II, respectively; clean production and abatement is advised for Category III; and a hybrid approach (i.e., demand management and abatement technology) is recommended for Category IV.
The Topographic Threshold of Gully Erosion and Contributing Factors
Authors: zare maryam , soufi Majid , Nejabat Masoud , Pourghasemi Hamid reza 
Published: July 2021

Abstract
The topographic threshold is based on the power relationship between area and slope and is widely applied in gully-erosion research; however, this relationship requires further testing. Accordingly, the Alamarvdasht Lamerd and Fadagh Larestan regions in Fars Province, Iran, were selected as case studies to explore the topographic threshold for gullies. Thirty active gullies were identified in each study area during field surveys, and data describing land use and land cover, drainage areas, slope, and the physical and chemical properties of the soils were assembled. Multivariate analysis was conducted using SPSS to determine the effects of these factors. Using the power relationship between the catchment area and slope for each gully, the analyses explored critical controls for gully development. The results showed that surface runoff was the most significant effective factor for gullies in the study areas. Sparse ground cover, fine-textured soils, and inappropriate land use all contribute to gully development. The results suggest that the relationship between slope and drainage area in the Fadagh Larestan case study is S = 0.0192 A− 0.159 for gully headcut areas and S = 0.0181 A− 0.258 at gully outlets. The corresponding values of the exponent β at the gully headcuts and outlets at Fadagh were − 0.15, and- 0.25, respectively. The corresponding relationships for gullies in the Alamarvdasht Lamerd area for the gully headcuts and outlets were S = 0.0143 A− 0.061 and S = 0.0073 A− 0. 18, respectively, with β values of -0.06 and − -0.18. This study provides a basis for determining the thresholds for the initiation of gully development. Analyses of the effective factors provide clues to improve the management of bare lands to prevent the initiation of gully erosion.
Sensitivity Enhancement of Silver Based Surface Plasmon Resonance Sensor via Graphene-Dielectric Composite Structure
Authors: Wang Guiqiang , Huang Liang 
Published: July 2021

Abstract
In this paper, a silver based surface plasmon resonance (SPR) sensor with graphene and dielectric layer was presented. The influences of dielectric layer and graphene on sensitivity and other sensing properties were theoretically calculated and then comprehensively discussed. The refractive index sensitivities for composite silver film based SPR sensors with graphene and dielectric layer could be increased by 29% and 288% than that of monolayer silver film based SPR sensor, respectively. Further, the sensitivity could be enhanced by 202% when combining graphene and dielectric layer together. Considering the high adsorptive capacity of graphene for biochemical molecules, the composite silver film with both dielectric layer and graphene would have great potential application in biochemical sensing fields. Further, BSA protein was successfully used to verify the biochemical sensing ability of proposed SPR sensor. The shift of resonance angle is nearly 3.1 folds than that of monolayer silver based SPR sensor.
Inhibiting tumor cell-intrinsic UBA6 by inosine augments tumor immunogenicity
Authors: He Baokun , Zhang Lei , Jiang Li , Yu Liang , Li Qin , Tian Xiangjun , He Jing-Quan , Zeng Ling , Yang Yuqin , Wang Chaoran , Wei Yuhan , Jiang Xiaoyue , Li Jing , Ge Xiaolu , Gu Qisheng , Li Ji-Kun , Wu Di , Sadler Anthony , Yu Di , Xu Dakang , Gao Yue , Yuan Xiangliang 
Published: July 2021

Abstract
Metabolic alteration influences cancer immunity. However, the role and mechanism of metabolic adaption on immune checkpoint blockade (ICB) responses remains ill-defined. Here, to identify metabolites that modulate ICB sensitivity, metabolomic profiling in mouse tumor models and cancer patients treated with ICB was performed. We identified that metabolite inosine was associated with ICB sensitivity in mice and humans, and overcame ICB resistance in several mouse tumor models. Notably, inosine sensitized tumor cells to T cell-mediated cytotoxicity by amplifying tumor-intrinsic immunogenicity. Chemical proteomics further identified that inosine directly bound and inhibited ubiquitin-activating enzyme UBA6. Tumor UBA6 loss augmented tumor immunogenicity and substituted the synergistic effect of inosine in combination with ICB. Clinically, tumor UBA6 expression negatively correlated with ICB response in cancer patients. Thus, we reveal an unappreciated function of inosine on tumor-intrinsic immunogenicity and provide UBA6 as a candidate target for immunotherapy.
Criticality Aware Scheduler Prioritization in Virtual Orthogonal Multichannel Parallelism for 5G Cellular Network
Authors: Ye Dan 
Published: July 2021

Abstract
To fulfill various enhanced requirements of next generation wireless access, 5 G cellular network will drive towards higher energy efficiency, lower latency and higher reliable wireless networks. The key contributions can summarize as follows: (1) proposes frame-based max-weight scheduling (FMWS) with reconfiguration delay in combination of round–robin algorithm can dynamically control throughput and delay. The frame-based dynamic control (FBDC) policy is applicable to 5 G cellular network control systems in data link layer, provides a new framework for developing throughput-optimal network control policies using state-action frequencies. (2) proposes a novel approach in MAC layer--Virtual multichannels Parallelism Carrier Sense Multiple Access (VMCP-CSMA) which can compute a set of TDDM schedules for multiple channels at once rather than computing one schedule at a time and constantly switching or recomputing schedules. (3) proposes a novel criticality aware scheduler prioritization in VMCP-CSMA policy can reorder a set of TDDM schedules based on max-weight scheduling with reconfiguration delay according to different application requirements. It can achieve high throughput and low delay with low complexity compared with other schedulings.
Smart Energy Consumption of IoT With Millimeter-Wave Cognitive Radiofor 5G Cellular Network
Authors: Ye Dan 
Published: July 2021

Abstract
Millimeter-wave technology is rising as a crucial component for 5G radio access and other emerging ancillary wireless networks including Gb/s device-to-device communication and mobile backhaul. This paper envisions that millimeter-wave cognitive radio in 5G network is a proposed smart energy consumption solution of Internet of Things (IoT) devices. Improving resource efficiency and enhancing data rates, resource sharing is a proposed advantage over millimeter wave cognitive radio in 5G IoT network. IoT Fog collaboration is proposed to apply artificial intelligence techniques to offer important energy-saving services allowing integrated systems to perceive, reason, learn, and act intelligently in intelligent gateway control. Smart energy meters are the current energy-saving utility in the flexible deployment of IoT architecture. NarrowBand IoT (NB-IoT) delivers Low Power Wide Area access (LPWA) to a new generation of connected things in the race to 5G IoT network, reducing energy computation and achieving promising network capacity. The renewable energy strategy is a proposed energy-efficiency solution in IoT network, maximizing the power supply while minimizing power consumption. A novel kind of visible light communications (VLC) is proposed to enable mmWave cognitive radio receiver in 5G IoT network. Simulation results show the proposed solution can reap the benefits of higher data rates, more IoT device connectivity, and lower energy consumption.
BIRC5 and PRLR Might Be Novel Immune-Related Prognostic Biomarkers in Adrenocortical Carcinoma (ACC)
Authors: Bai Xiaojie , Yan Xin , Du Guowei , Chen Zhao , Wu Huahui , Tuoheti Kurerban , Liu Tongzu 
Published: July 2021

Abstract
Background: Adrenocortical carcinoma (ACC) is a highly aggressive tumor，which occurs in adrenal cortex. This study aims to identify new immune-related molecular biological markers and therapeutic targets in ACC patients. Results: First, we identified 134 genes by constructing weighted gene co-expression network. Among them, two genes (BIRC5 and PRLR) were eventually regarded as immune-related prognosis biomarkers on the basis of The Immunology Database and Analysis Portal (ImmPort) database. The validation of mRNA level was meaningful (based on Oncomine database and TCGA-ACC). Four methods (overall survival (OS) analysis, disease-free survival (DFS) analysis, stage plot and expression value comparison) were used in GEPIA to verify that PRLR and BIRC5 have significant correlation with the prognosis of ACC. Several other methods including survival analysis, analysis of variance, the spearman correlation analysis, distance correlation analysis and receiver operating characteristic curve were also used for the external validation of them in GEO datasets (GSE10279, GSE19750, GSE76019 and GSE76021). Furthermore, we evaluated the relationship between hub gene expression of and the degree of immune cell infiltration in ACC by ESTIMATE algorithm and ssGSEA. BIRC5 expression was significantly positively related to activated CD4 T cell and type 2 T helper cell. And PRLR expression was positively related to CD56dim NK cell and type 17 T helper cell. Moreover, Gene set enrichment analysis (GSEA) suggested that PRLR has strong correlation with neuroactive ligand receptor interaction and BIRC5 was significantly enriched in cell cycle. In addition, according to Drug Signatures Database (DSigDB), BIRC5 were significantly enriched in “resveratrol_mcf7_down”, “lucanthone_ctd_00006227”, “8-azaguanine_pc3_down”, “thioguanosine _mcf7_down”, “dasatinib_ctd_00004330”, “monobenzone_pc3_down”. Conclusions: In summary, BIRC5 and PRLR were shown to be related to the prognosis of patients with ACC, indicating them as novel immune-related prognostic biomarkers and immunotherapy targets in ACC.
WDR31 is a novel ciliopathy protein displaying functional redundancy with GTPase-activating proteins ELMOD and RP2 in recruiting BBSome to cilium
Authors: Cevik Sebiha , Alabdi Lama , Peng Xiaoyu , Beyer Tina , Zorluer Atiyye , Pir Mustafa , Yenisert Ferhan , Shaheen Ranad , Woerz Franziska , Hoffmann Felix , Altunkaynak Betul , Pir Betul , Boldt Karsten , Karaman Asli , Cakiroglu Miray , Oner Sadik , Cao Ying , Ueffing Marius , Alkuraya Fowzan , Kaplan Oktay 
Published: July 2021

Abstract
The term “ciliopathy” refers to a group of over 35 rare disorders characterized by defective cilia and many overlapping clinical features, such as hydrocephalus, cerebellar vermis hypoplasia, polydactyly, and retinopathy. Even though many genes have been implicated in ciliopathies, the genetic pathogenesis in certain cases remains still undisclosed. Here, we identified a homozygous truncating variant in WDR31 in a patient with a typical ciliopathy phenotype encompassing congenital hydrocephalus, polydactyly, and renal agenesis. WDR31 is an evolutionarily conserved protein that localizes to the cilium and cilia-related compartment. Analysis from zebrafish supports the role of WDR31 in regulating the cilia morphology. The CRISPR/Cas9 knock-in (p.Arg261del) C. elegans model of the patient variant (p.Arg268*) reproduced several cilia-related defects observed in wdr-31 null mutants. Mechanistic analysis from C. elegans revealed that WDR-31 functions redundantly with ELDM-1 (ELMOD protein) and RPI-2 (RP2) to regulate the IFT trafficking through controlling the cilia entry of the BBSome. This work revealed WDR31 as a new ciliopathy protein that regulates IFT and BBSome trafficking.
A Spaced-Repetition Approach to Enhance Medical Student Learning and Engagement in Pharmacology
Authors: Jape Dylan , Zhou Jessie , Bullock Shane 
Published: July 2021

Abstract
Background: Pharmacology is a cornerstone of medical education as it underlies safe prescribing practices. However, medical students have reported unease regarding their perceived proficiency in clinical pharmacology. Despite the significant impetus to improve student outcomes, there is little analysis available of the techniques used by medical students to learn, retain and apply pharmacology knowledge.Methods: A mixed methods, student-focused approach was conducted to design and refine specific resources developed to address gaps in pharmacology education. This methodology comprised an anonymised scoping survey, followed by structured focus group interviews. We developed a relevant and time efficient resource to support long-term revision for academic and clinical success. These resources were released to a cohort of 100 graduate preclinical medical students who were invited at the end of year to evaluate the intervention via a subsequent anonymous survey.Results: The scoping survey received 103 complete responses. Surveys and focus group interviews revealed that only 50% of students engage in ongoing revision. The analysis identified in-semester revision of pharmacology as a significant predictor of strategic and deep learning methods and improved quiz performance (a 5% higher score on average), compared to superficial learning methods. Amongst our cohort, we identified that the evidence-based technique of spaced-repetition was particularly well regarded. Hence, we developed and evaluated a bespoke resource utilising AnkiTM, an open-source, spaced-repetition flashcard program. A total of 1208 flashcards spanning 156 distinct classes of drugs with supplementary summary tables, diagrams and explanatory video and summary guides were created. Designed as a strategic revision tool to reinforce learning, evaluation showed students greatly appreciated the “comprehensive” and “well formatted” AnkiTM resource that supported existing teaching modalities, with a global rating of 3.8 out of 5. Conclusions: Strategic and personalised techniques for pharmacology learning that assist with in-semester revision and long-term retention are highly valued amongst students for examination preparation and preparedness for practice. Collectively, these results define a novel approach to identifying and addressing weaknesses in existing teaching methodologies in a manner that is inclusive of, and acceptable to, medical students.
Observation of the crossover between metallic and insulating regimes of the spin Hall effect
Authors: Moriya Hiroyuki , Musha Akira , Haku Satoshi , Ando Kazuya 
Published: July 2021

Abstract
The physics of the anomalous and spin Hall effects is one of the most intriguing aspects of condensed matter physics. An important finding from a large collection of experimental and theoretical results is the universal scaling of the anomalous or spin Hall conductivity with the electric conductivity. This scaling has been successfully described by the intrinsic Berry curvature and extrinsic scattering mechanisms for metallic systems, revealing the topological nature of these effects. In contrast, the underlying physics in the opposite limit, the disordered insulating regime, is still unclear. In particular, it remains a major challenge to explore the spin Hall effect in the insulating regime. Here, we report the observation of the crossover between the metallic and insulating regimes of the spin Hall effect. The result demonstrates an important correspondence between the spin and anomalous Hall effects, which provides essential information for the fundamental understanding of spin transport.
Pedestrian Evacuation Time Calculation against Tsunami Hazard for Southern Coasts of Bodrum Peninsula
Authors: Çelikbaş Büşra , Tufekci-Enginar Duygu , Dogan Gozde Guney , Kolat Cagil , Santini Marzia , Annunziato Alessandro , Necmioglu Ocal , Yalciner Ahmet Cevdet , Suzen Mehmet Lutfi 
Published: July 2021

Abstract
Historical records with recent events reveal that tsunamis are threatening the western coast of Turkey due to intensely active seismicity of the Eastern Mediterranean Sea. The most recent tsunami events in the region (30 October 2020 Izmir-Samos and 20 July 2017 Bodrum-Kos) restated that the cities located near the Eastern Mediterranean and connected seas should consider tsunami events in their disaster mitigation plans. Bodrum is one of the most critical coastal districts, vulnerable to marine hazards with popular hotels, numerous coastal facilities, long and famous beaches, cultural, historical and touristic places. Tsunami evacuation planning is required for Bodrum district to mitigate the damage caused by destructive tsunami waves inundating on land. In this study, the geospatial distribution of pedestrian evacuation time is calculated based on selected credible worst-case scenarios. A widely used anisotropic least-cost-distance (LCD) model is applied via the Pedestrian Evacuation Analyst Tool (PEAT) to calculate the required time for a pedestrian to evacuate the region under tsunami threat based on the selected scenarios. The model includes landscape properties that affect the walking pace of pedestrians during an evacuation, such as elevation, slope, land cover, and land use types (beach, road, bushes, water bodies, any barriers). The resultant pedestrian evacuation time maps show that the maximum time needed for a pedestrian is 8, 6, 5, 4, 3 minutes for highly populated coastal settlements of Bodrum, which are Central Bodrum, Yahsi, Akyarlar-Karaincir-Aspat Bays, Bitez, and Gumbet Bays, respectively.
FOC-MOP – Fuzzy Optimal Clustering based Multi-Objective Parameter Route Selection for Energy Efficiency
Authors: Sreed Pogula , Venkateswarlu S. 
Published: July 2021

Abstract
Recently, the research area interest towards the development of wireless sensor network (WSN) has increased. However, WSNs have one of significant issues as improving an energy-efficient routing protocol. A WSN has a crucial problem of energy consumption that effects the network lifetime as sensor nodes have a limitation of power. To overcome these limitations, it’s required to improve energy-efficient communication protocols for WSNs. Different types of techniques have considered by various research communities for providing energy-efficient solutions for WSNs. The energy consumption reduces using the clustering as an efficient data collection method and the collected data forward to a cluster-head which belong to the nodes in clustered networks. The information transmits to BS (base station) either in an uncompressed or compressed manner after collecting all data by a cluster-head from all member nodes. Based on other cluster-heads, the data transmit in a multi-hop network. Due to the heavy inter-cluster relay, earlier death happens to the cluster-heads (CHs) that locates very closely to the sink. Therefore, a fuzzy optimal CH selection algorithm has proposed to select the optimal CHs to improve the lifetime. Based on different parameters like cluster load, communication cost, neighbour density, node degree, inter and intra cluster distance, and node energy, the proposed algorithm of CH selection chooses the CHs. To determine an optimal route for transmitting the data from CH to sink, the modified Emperor Penguin Optimization (EPO) uses after selecting the CH. The proposed technique implements and compares with other earlier methods in terms of packet delivery ratio, lifetime, energy consumption, end to end delay and throughput. The proposed approach shows best performance than the other methods based on the simulation results.
Deep learning enables accurate sound redistribution via nonlocal metasurfaces
Authors: Ding Hua , Fang Xinsheng , Jia Bin , Wang Nengyin , CHENG Qian , Li Yong 
Published: July 2021

Abstract
Conventional acoustic metasurfaces are constructed with gradiently "local" phase shift profiles provided by subunits. The local strategy implies the ignorance of the mutual coupling between subunits, which limits the efficiency of targeted sound manipulation, especially in complex environments. By taking into account the "nonlocal" interaction among subunits, nonlocal metasurface offers an opportunity for accurate control of sound propagation, but the requirement of the consideration of gathering coupling among all subunits, not just the nearest-neighbor coupling, greatly increases the complexity of the system and therefore hinders the explorations of functionalities of nonlocal metasurfaces. In this work, empowered by deep learning algorithms, the complex gathering coupling can be learned efficiently from the preset dataset so that the functionalities of nonlocal metasurfaces can be significantly uncovered. As an example, we demonstrate that nonlocal metasurfaces, which can redirect an incident wave into multi-channel reflections with arbitrary energy ratios, can be accurately predicted by deep learning algorithms. Compared to the theory, the relative error of the energy ratios is less than 1\%. Furthermore, experiments witness three-channel reflection with three types of energy ratios of (1, 0, 0), (1/2, 0, 1/2), and (1/3, 1/3, 1/3), proving the validity of the deep learning enabled nonlocal metasurfaces. Our work might blaze a new trail in the design of acoustic functional devices, especially for the cases containing complex wave-matter interactions.