bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of concentrations of chemical species and emission sources PM2.5 before pandemic and during pandemic in Krakow, Poland
Authors: Rys Anna , Samek Lucyna , Stegowski Zdzislaw , Styszko Katarzyna 
Published: October 2022

AbstractObservations of air pollution in Krakow have shown that air quality has been improved during the last decade. In the presented study two factors affecting the physicochemical characteristic of PM2.5 fraction at AGH station in Krakow were observed. One is the ban of using solid fuels for heating purposes and the second is COVID-19 pandemic in Krakow. The PM2.5 fraction was collected during the whole year every 3rd day between 2nd March 2020 and 28th February 2021 at AGH station in Krakow. In total 110 PM2.5 fraction samples were collected. The chemical composition was determined for these samples. The elemental analysis was performed by energy dispersive X-ray fluorescence (EDXRF) technique, ions analysis was performed by ion chromatography (IC) and black carbon by optical method. In order to identify the emission sources the positive matrix factorization (PMF) was used. The results of such study were compared to similar analysis performed for PM2.5 for the period from June 2018 to May 2019 at AGH station in Krakow. The PM2.5 concentration dropped by 25% in 2020/2021 in comparison to 2018/2019 at this station. The concentrations of Si, K, Fe, Zn and Pb were lowering by 43–64% in the year 2020/2021 in comparison to 2018/2019. Cu, Mn, Zn and Pb come from mechanical abrasion of brakes and tires while Ti, Fe, Mn and Si are crustal species. They are the indicators of road dust (non-exhaust traffic source). Moreover, the annual average contribution of traffic/industrial/soil/construction work source was reduced in 2020/2021 in comparison to 2018/2019. As well the annual average contribution of fuels combustion was declining by 22% in 2020/2021 in comparison to 2018/2019. This study shows that the ban and lockdown, during COVID-19 pandemic, had significant impact on the characteristic of air pollution in Krakow.
A data‐driven inertia adequacy‐based approach for sustainable expansion planning in distributed generations‐penetrated power grids
Authors: Golpîra Hêmin , Amini Shiva , Atarodi Azin , Bevrani Hassan 
Published: October 2022

AbstractReduced rotational inertia in power grids due to increasing penetration levels of distributed generations (DGs) may lead to degraded performance of the traditional frequency control scheme. In response to this challenge, inertia adequacy has recently emerged as a new research area in modern power systems. Accordingly, an attempt is made in this paper to tackle inertia adequacy in the generation expansion planning (GEP) problem. This in turn helps to realize sustainable economic development. For this purpose, the inertia adequacy constraint is tied to the frequency stability metrics. In other words, minimum permissible inertia that satisfies frequency dynamic standards is defined as an inertia adequacy constraint in the GEP formulation. Further, an experimentally validated model of a cluster of DGs is employed to realize a penetrated power grid to deal with sustainable planning development. Finally, an iterative‐based algorithm is proposed to expand the system with minimum cost and with the highest permissible penetration level of DGs. The effectiveness of the proposed algorithm is examined in the Garver test system.
Multi‐similarity based hyperrelation network for few‐shot segmentation
Authors: Shi Xiangwen , Cui Zhe , Zhang Shaobing , Cheng Miao , He Lian , Tang Xianghong 
Published: October 2022

AbstractFew‐shot semantic segmentation aims at recognizing the object regions of unseen categories with only a few annotated examples as supervision. The key to few‐shot segmentation is to establish a robust semantic relationship between the support and query images and to prevent overfitting. In this paper, an effective multi‐similarity hyperrelation network (MSHNet) is proposed to tackle the few‐shot semantic segmentation problem. In MSHNet, a new generative prototype similarity (GPS) is proposed, which, together with cosine similarity, establishes a strong semantic relationship between supported images and query images. In addition, a symmetric merging block (SMB) in MSHNet is proposed to efficiently merge multi‐layer, multi‐shot, multi‐similarity features to generate hyperrelation features for semantic segmentation. Experimenting on two benchmark semantic segmentation datasets (Pascal − 5i and COCO − 20i) shows that this method achieves a mean intersection‐over‐union score of 72.3% and 56.0%, respectively, which outperforms the state‐of‐the‐art methods by 1.9% and 6.5%.
Guest editorial: Biomass conversion for energy: Process intensification and economics
Authors: Patience Gregory S. , Villasana Yanet , Boffito Daria C. 
Published: October 2022

AbstractThe symposium Biomass Conversion for Energy: Process Intensification and Economics held at the Canadian Chemical Engineering Conference 2022 corresponds to several United Nations Sustainable Development Goals (SDG): SDG7—produce more affordable and cleaner energy; SDG9—build small‐scale industrial enterprises and domestic technologies; SDG12—improve the management and efficient use of natural resources; SDG13—integrate climate change measures into national strategies. Cooking fuel remains scarce in many regions around the world as three billion people rely on polluting systems while 800 million people have no electricity. The energy density of renewable resources is low, compared to petroleum, which makes transporting bio‐feedstocks to centralized stations prohibitively expensive. Process intensification (PI) and distributed manufacturing are strategies that reduce costs and serve these markets equitably. PI reduces the size of equipment while maintaining productivity by maximizing thermal, electrical, mechanical, and catalytic driving forces. These technologies must be coupled with mass manufacturing (numbering up manufacturing rather than scaling up) to achieve economic parity with centralized power facilities. They apply to converting biomass to electricity, thermo‐processing of lignocellulosics, and producing liquid fuels, butane, and propane from flared and vented natural gas, landfill gas, and biogas, via gas‐to‐liquids technology.
Design and implementation of an adaptive fuzzy sliding mode controller for drug delivery in treatment of vascular cancer tumours and its optimisation using genetic algorithm tool
Authors: Ghasemabad Ehsan Sadeghi , Zamani Iman , Tourajizadeh Hami , Mirhadi Mahdi , Zarandi Zahra Goorkani 
Published: October 2022

AbstractIn this paper, the side effects of drug therapy in the process of cancer treatment are reduced by designing two optimal non‐linear controllers. The related gains of the designed controllers are optimised using genetic algorithm and simultaneously are adapted by employing the Fuzzy scheduling method. The cancer dynamic model is extracted with five differential equations, including normal cells, endothelial cells, cancer cells, and the amount of two chemotherapy and anti‐angiogenic drugs left in the body as the engaged state variables, while double drug injection is considered as the corresponding controlling signals of the mentioned state space. This treatment aims to reduce the tumour cells by providing a timely schedule for drug dosage. In chemotherapy, not only the cancer cells are killed but also other healthy cells will be destroyed, so the rate of drug injection is highly significant. It is shown that the simultaneous application of chemotherapy and anti‐angiogenic therapy is more efficient than single chemotherapy. Two different non‐linear controllers are employed and their performances are compared. Simulation results and comparison studies show that not only adding the anti‐angiogenic reduce the side effects of chemotherapy but also the proposed robust controller of sliding mode provides a faster and stronger treatment in the presence of patient parametric uncertainties in an optimal way. As a result of the proposed closed‐loop drug treatment, the tumour cells rapidly decrease to zero, while the normal cells remain healthy simultaneously. Also, the injection rate of the chemotherapy drug is very low after a short time and converges to zero.
Sex and Gender Multidimensionality in Epidemiologic Research
Authors: Bauer Greta R 
Published: October 2022

Abstract
Along with age and race, sex has historically been a core stratification and control variable in epidemiologic research. While in recent decades research guidelines and institutionalized requirements have incorporated an approach differentiating biological sex from social gender, neither sex nor gender is itself a unidimensional construct. The conflation of dimensions within and between sex and gender presents a validity issue wherein proxy measures are used for dimensions of interest, often without explicit acknowledgement or evaluation. Here, individual-level dimensions of sex and gender are outlined as a guide for epidemiologists, and 2 case studies are presented. The first case study demonstrates how unacknowledged use of a sex/gender proxy for a sexed dimension of interest (uterine status) resulted in decades of cancer research misestimating risks, racial disparities, and age trends. The second illustrates how a multidimensional sex and gender framework may be applied to strengthen research on coronavirus disease 2019 incidence, diagnosis, morbidity, and mortality. Considerations are outlined, including: 1) addressing the match between measures and theory, and explicitly acknowledging and evaluating proxy use; 2) improving measurement across dimensions and social ecological levels; 3) incorporating multidimensionality into research objectives; and 4) interpreting sex, gender, and their effects as biopsychosocial.
Adaptive Federated Learning With Non-IID Data
Authors: Zeng Yan , Mu Yuankai , Yuan Junfeng , Teng Siyuan , Zhang Jilin , Wan Jian , Ren Yongjian , Zhang Yunquan 
Published: October 2022

Abstract
With the widespread use of Internet of things(IoT) devices, it generates an enormous volume of data, and it is a challenge to mine the IoT data value while ensuring security and privacy. Federated learning is a decentralized approach for training data located on edge devices, such as mobile phones and IoT devices, while keeping privacy, efficiency, and security. However, the Non-IID (non-independent and identically distributed) data, always greatly impacts the performance of the global model. In this paper, we propose a FedDynamic algorithm to solve the statistical challenge of federated learning caused by Non-IID. As Non-IID data can lead to significant differences in model parameters between edge devices, we set different weights for different devices during model aggregation to get a high-performance global model. We analyze and exact key indices (local model accuracy, local data quality, and model difference between local models and the global model), which can reflect the quality of the model, and calculate the aggregation weight for edge devices based on the key indices. Furthermore, we dynamically adjust aggregation weight based on accuracy’s variety to solve weight staleness during the training process. Experiments on the MNIST, FMNIST, EMNIST, CINIC-10 and CIFAR-10 datasets show that the FedDynamic algorithm has better accuracy and convergence performance, compared to the FedAvg, FedProx and Scaffold algorithms.
An Efficient Deep Learning Approach To IoT Intrusion Detection
Authors: Cao Jin , Lin Liwei , Ma Ruhui , Guan Haibing , Tian Mengke , Wang Yong 
Published: October 2022

Abstract
With the rapid development of the Internet of Things (IoT), network security challenges are becoming more and more complex, and the scale of intrusion attacks against the network is gradually increasing. Therefore, researchers have proposed Intrusion Detection Systems and constantly designed more effective systems to defend against attacks. One issue to consider is using limited computing power to process complex network data efficiently. In this paper, we take the AWID dataset as an example, propose an efficient data processing method to mitigate the interference caused by redundant data and design a lightweight deep learning-based model to analyze and predict the data category. Finally, we achieve an overall accuracy of 99.77% and an accuracy of 97.95% for attacks on the AWID dataset, with a detection rate of 99.98% for the injection attack. Our model has low computational overhead and a fast response time after training, ensuring the feasibility of applying to edge nodes with weak computational power in the IoT.
Reverse-Payment Settlements Under EU and US Patent Law: Convergence in Remedies
Authors: Signoretta Camilla 
Published: October 2022

Abstract
This paper investigates the existing case law on reverse-payment settlements from a comparative perspective, focusing on the US and EU panoramas. In this respect, we will illustrate the emergence of patent-related proxies in the anticompetitive assessment, which contaminate the antitrust benchmarks in a problematic way, with the effect of hampering patent law and policy. Primarily we will delve into seminal decisions in the EU framework. In this regard we will observe how the Court of Justice of the European Union (CJEU) shifted from a quick-look approach towards a case-by-case antitrust analysis of patent settlements, progressively neglecting, but not eliminating, patent-related presumptions. Then we will look at the fragmented US case law scenario. We will explore the various benchmarks deployed to challenge these agreements, highlighting the differences and similarities with the EU approaches. It will be concluded that a strong IP-law-based perspective about these agreements has arisen in both legal systems. This perspective orientates the anticompetitive assessment through quasi-absolute presumptions, hindering the consistency of competition law remedies and misrecognising the cruciality of patent law and policy. Therefore, we will try to outline that the intermingling of criteria adopted to scrutinise reverse-payment settlements and similar over-exclusionary strategies is pernicious under both antitrust and patent law.
Poppy Seed Consumption May Be Associated with Codeine-Only Urine Drug Test Results
Authors: Reisfield Gary M , Teitelbaum Scott A , Jones Joseph T 
Published: October 2022

AbstractConsumption of poppy seed-containing food products can result in opiate-positive urine drug test results and may pose challenges in distinguishing poppy seed consumption from opiate administration. In this context, guidance has suggested that codeine concentrations exceeding 300 ng/mL coupled with morphine-to-codeine ratios &lt;2 are indicative of codeine consumption and, therefore, exclude poppy seed consumption as a legitimate explanation for the test result. In recent years, we performed independent medical examinations of three individuals who produced codeine-positive/morphine-negative (300 ng/mL) forensic urine drug test results but denied codeine administration, attributing their test results to the consumption of specific poppy seed-containing food products. In the present study, 11 participants consumed one of the 10 unique poppy seed-containing food products, including the three implicated food products. Six of 33 non-baseline urine samples (18%)—representing three food products—were positive for codeine and negative for morphine at 300 ng/mL cut-offs (and therefore featured morphine-to-codeine ratios &lt;2). This study adds to a small literature indicating that consumption of poppy seed-containing food products cannot reliably be distinguished from codeine administration based on previously published urinary opiate concentrations and ratios. An important caveat is that in none of these cases did maximum urinary codeine concentrations exceed 1,300 µg/g creatinine.
On-grid labeling method for freeze-fracture replicas
Authors: Osakada Hiroko , Fujimoto Toyoshi 
Published: October 2022

Abstract
Sodium dodecyl sulfate–treated freeze-fracture replica labeling (SDS-FRL) is an electron microscopic (EM) method that can define the two-dimensional distribution of membrane proteins and lipids in a quantitative manner. Despite its unsurpassed merit, SDS-FRL has been adopted in a limited number of labs, probably because it requires a laborious labeling process as well as equipment and technique for freeze-fracture. Here, we present a method that reduces the manual labor significantly by mounting freeze-fracture replicas on EM grids prior to labeling. This was made possible by the discovery that freeze-fracture replicas invariably adhere to the carbon-coated formvar membrane with their platinum–carbon side, ensuring that the membrane molecules retained in replicas are accessible to labeling solutions. The replicas mounted on EM grids can be stored dry until labeling, checked by light microscopy before labeling and labeled in the same manner as tissue sections. This on-grid method will make SDS-FRL easier to access for many researchers.
Recurrent vaginal vault dehiscence and evisceration following total laparoscopic hysterectomy, successfully repaired with polypropylene mesh and sacrocolpopexy
Authors: Rathigashini R , Wanniarachchi W A D P , De Silva A , Herath R P 
Published: October 2022

Abstract
Recurrent vault dehiscence is a rare and potentially serious complication following hysterectomy. We report a rare case of recurrent vault dehiscence and evisceration following a total laparoscopic hysterectomy (TLH) which was successfully repaired with polypropylene mesh and sacro-colpopexy. A 47-year-old multiparous woman underwent TLH for adenomyosis. During the surgery, vaginal wall was incised with monopolar diathermy and sutured with synthetic absorbable barbed suture in a single layer. She presented 12 weeks later with vault dehiscence and evisceration of omentum. Laparoscopically, eviscerated omental part was removed and the vaginal cuff was repaired vaginally with absorbable synthetic suture. She came with a recurrence in 3 months with vault dehiscence and a vault prolapse without any evisceration. She underwent laparoscopic mesh repair of the vault combined with laparoscopic Sacro-colpopexy with complete recovery. Incidence of vault dehiscence is found to be higher in TLH than abdominal or vaginal hysterectomy. Treatment options for recurrent vault dehiscence involve strengthening the vault with tissues, or with a prosthesis.
Molecular and Developmental Signatures of Genital Size Macro-Evolution in Bugs
Authors: Genevcius Bruno C , Calandriello Denis C , Torres Tatiana T 
Published: October 2022

AbstractOur understanding of the genetic architecture of phenotypic traits has experienced drastic growth over the last years. Nevertheless, the majority of studies associating genotypes and phenotypes have been conducted at the ontogenetic level. Thus, we still have an elusive knowledge of how these genetic-developmental architectures evolve themselves and how their evolution is mirrored in the phenotypic change across evolutionary time. We tackle this gap by reconstructing the evolution of male genital size, one of the most complex traits in insects, together with its underlying genetic architecture. Using the order Hemiptera as a model, spanning over 350 million years of evolution, we estimate the correlation between genitalia and three features: development rate, body size, and rates of DNA substitution in 68 genes associated with genital development. We demonstrate that genital size macro-evolution has been largely dependent on body size and weakly influenced by development rate and phylogenetic history. We further revealed significant correlations between mutation rates and genital size for 19 genes. Interestingly, these genes have diverse functions and participate in distinct signaling pathways, suggesting that genital size is a complex trait whose fast evolution has been enabled by molecular changes associated with diverse morphogenetic processes. Our data further demonstrate that the majority of DNA evolution correlated with the genitalia has been shaped by negative selection or neutral evolution. Thus, in terms of sequence evolution, changes in genital size are predominantly facilitated by relaxation of constraints rather than positive selection, possibly due to the high pleiotropic nature of the morphogenetic genes.
Hull’s Magic Box: Keeping Brain Tumour Biopsies “Alive” in the Lab Brings Research Opportunities for New Therapies and Earlier Diagnosis of Brain Tumour
Authors: Barry Antonia , Samuel Sabrina , Moursi Amr , Deepak Srihari , Achawal Shailendra , Rajaraman Chittoor , Feugere Lauric , Iles Alexander , Green Vicky , Wade Mark , Stead Lucy , Greenman John , Beltran-Alvarez Pedro 
Published: October 2022

Abstract

AIMS
Assess/evaluate apoptosis in GBM samples maintained on a microfluidics system in response to GSK3368715 and other PRMT inhibitors, currently in clinical trials, with the ultimate goal of synergising with personalised patient care and precision medicine. Investigate the effect of treating GBM biopsies on-chip with PRMT inhibitors at the molecular level, including RNA and protein modifications.

METHOD
GBM biopsies are received from Hull Royal Infirmary and maintained on-chip for 8-days. They are perfused with media, at a rate of 3 μl/min, mimicking the in vivo environment and allowing real-time analysis of tumour behaviour. PRMT inhibitors, such as GSK3368715, are added to the media, in conjunction with TMZ, to determine their efficacy ex vivo using a range of techniques, such as: immunohistochemistry, cell viability assays, protein analysis and RNA-sequencing.

RESULTS
We show that PRMT inhibition increases apoptosis five-fold above the control, untreated GBM-on-chip samples. This is compounded by cell viability assays, which have indicated that cell viability in these post-chip tissues is reduced by 30% upon treatment with 1μM GSK3368715. Additionally, western blot analysis has indicated that PRMT inhibition with GSK3368715 appears to switch the methylation status of fused-in-sarcoma (FUS) protein in GBM biopsies.

CONCLUSION
These results indicate that PRMT inhibition may not only be a viable target for GBM therapy, but could also highlight a mechanism for re-sensitising MGMT-negative GBM to TMZ. This data produces an exciting argument for further research into the use of this novel inhibitor for improving prognosis for patients diagnosed with this devastating disease.