bluuebunny/crossref_metadata_2025_split huggingface dataset:
A rapid scoping review of self-initiated harm reduction strategies for ecstasy (MDMA) users in recreational settings
Authors: Edwards Deborah , Csontos Judit , Pascoe Michael J , Westwell Andrew , Gillen Elizabeth , Bennett Clare , Hannigan Ben , Carrier Judith , Harden Jane 
Published: June 2023

Abstract

Background:Adverse drug reactions (ADRs) can occur due to ecstasy use, and the number of people dying due to drug-related deaths has increased in the past 10 years. Self-initiated harm reduction strategies could help prevent ADRs or decrease the incidence of life-threatening health consequences due to ecstasy use.Methods:A rapid scoping review was conducted using adapted JBI methodology. The objectives were to describe the strategies employed by ecstasy users to minimise harm, the sources of information they rely on, and to assess the content of user-oriented websites regarding detrimental effects and harm reduction practices. Five databases (CINAHL, EMBASE, Medline, PsycINFO, CENTRAL) were searched for English language records from database inception to August 2022. User-oriented websites were identified via the project’s stakeholder group and Google searches.Results:Twenty reports representing 19 studies (one RCT, nine quantitative descriptive studies and nine qualitative studies) were included. A wide variety of self-initiated harm reduction strategies were reported, including drug checking, dose control (including buying from trusted sources), seeking peer support (e.g., looking out for friends), hydration management and temperature regulation (e.g., monitoring water consumption, taking rest breaks, and avoiding alcohol), avoiding polydrug use, and pre- / post-loading. Information on ecstasy’s effects and/or harm reduction practices is obtained from a variety of sources including friends, nightclubs, drug leaflets, and user-oriented websites. Fourteen websites providing ecstasy-specific harm reduction information were also identified and quality assessed. However, only two webpages provided citations to the evidence used for the content.Conclusions:The provision and quality assessment of ecstasy harm reduction advice from various sources has been collectively analysed for the first time. We hope and anticipate that use of this rapid scoping review will facilitate more comprehensive, evidence-based harm reduction messaging, reducing the likelihood of future ADRs and life-threatening health consequences related to ecstasy use.
Role of Simulation in Italian Emergency Medicine training programs: data from a national survey
Authors: Cascio Michela , INGRASSIA Pier Luigi , ZACCARIA Gianpiero , MORMANDO Giulia 
Published: June 2023

Abstract
Background
Simulation is an educational tool widely used worldwide and simulation-based education is an important training strategy in Emergency Medicine (EM) training programs.
Objective
In the first part of the project SIMinMEU of CosMEU and SIMMED, an electronic survey open to the Italian EM residents’ representatives was created with the aim to assess their awareness about simulation in their programs.
Results
Out of 33 EM residencies, 30 representatives answered the survey. Only 15 schools offer simulation, with a median of 16,27 (range 0–46) annual simulation training, with 53% of representatives indicating that the time dedicated to it met their needs.
15 do skill lab activities (50 %), 14 do High fidelity simulation (46.66%), one does serious games (3,33%) and one does virtual reality (3,33%). In situ simulations aren’t provided.
Crisis resource management (CRM) and soft skills are topics covered in seven (23,3%). In 5 residencies (16,6%) there are certified facilitators. The annual exams aren’t carried out using simulation. Only in five (16,6%) residencies research in simulation is carried out.
Residents’ satisfaction for simulation activities is lower than good in 73% of cases.
Most residents stated lack of simulation standards and poor quality of simulation activities. The main requests are that simulation must be part of the teaching program, increased in number and better structured.
Conclusions
Considering the increasing interest of residents in simulation emerged by this survey, CoSMEU and SIMMED will commit to improving the quality, facilitating the spreading and guaranteeing the standardization of simulation in every EM Italian school.
Vertical textile epifluidics for integrated real-time electrochemical sweat analysis
Authors: Galliani Marina , Azizian Pooya , Makhinia Anatolii , Cabot Joan , Ismailova Esma 
Published: June 2023

Abstract
The non-invasive discovery of novel physiological biomarkers in sweat relies on its precise sampling and analysis. Here, we present a scalable fabrication approach of a wearable microfluidic system within fabric structures for an accurate and ergonomic sweat handling and sensing. Digital 3D printing of a flexible resin precisely defines impermeable microstructures in wicking textiles, only achievable by SLA technique. Regulated fluid collection, storage and transport, avoiding the complexity of traditional valves, is obtained by assembling 3D-printed textile-based modules in an origami-inspired vertical stack offering reduced device footprint, seamless and adhesive-free on-body sensing. The generation of pressure gradient across these microfluidic modules enables vertically distributed, capillary-driven and pre-programmed sweat flow. The tortuous flow characteristics of woven textile conduits based on the numerical fluid-dynamics simulation demonstrate the technological versatility to reproduce this controlled flow in different textile structures. The monolithic integration of textile microfluidics on garments provides unlimited, non-accumulative fluid flow through the extended air-liquid interface for its continuous flow and concomitant evaporation from the fabric surface. In-situ and in real-time sweat analysis with a remotely screen-printed flexible organic electrochemical transistor provides the possibility of various sensor integration and multi-parameter detections. The transistor successfully detects K+ ion concentrations using ion-selective membrane within the sweat physiological ionic range. This mechanically ergonomic, fabric-integrated microfluidic sensing platform, based on rapid additive manufacturing of polyhedral device configurations, offers unique strategies for device design and novel sensing perspectives for advancing wearable point-of-care diagnostics with personalized health monitoring capabilities.
COVID-19 patient experiences in pre-hospital pathways: a processual qualitative approach using the life-events calendar method highlights diagnostic delays and healthcare renunciation.
Authors: LUTAUD Romain , Mirouse Juliette , Borg Manon , Cattaneo Lucie , Constance Jean , Pradier Christian , Cortaredona Sebastien , Irit Touitou , Peretti-Watel Patrick , Million Matthieu , Brouqui Philippe , Carles Michel , Gentile Stephanie 
Published: June 2023

Abstract

Background
During the height of the COVID-19 pandemic in 2020, 11% of patients who were hospitalized in France were immediately admitted to intensive care. We aimed to identify and characterize the different types of primary care pathways of patients hospitalized for COVID-19 using patients’ self-reported experiences.
Method
We conducted a qualitative study using biographic interviews of patients who were hospitalized for COVID-19 between September 2020 and December 2021 in the infectious disease departments in Marseille and Nice. The biographical interviews used a life-events calendar approach to understand the sequences of clinical and care events prior to hospitalization.
Results
31 pathways were described. Short care pathways (i.e., admission to hospital ≤ 3 days after symptom onset) were more likely to be reported by older patients and those with comorbidities. These pathways were characterized by closer GP surveillance and by sudden symptom onset and rapid progression of the disease.
Long care pathways (i.e., >10 days after system onset) were reported more by younger patients with no comorbidities. Multiple tests and medical consultations returning false-negatives had led this population to doubt they had COVID-19. They were more likely to present severe symptoms requiring intensive care.
The study revealed key importance of patients’ loved ones in the process of their hospitalization.
Conclusion
This study highlights that primary care management of COVID-19 patients needing hospitalization in France was particularly slow and detrimental to their health. It also underlines the need to improve the identification and monitoring of patients at risk of complications.
Impacts of Negative Network Opinion on the Purchase Intention of Driverless Cars from the Perspective of Moderating Effects of Mindfulness Intervention
Authors: Li Laibin , Wang Zhong , Zhou Huaqing , Yu Chenxi , Li Xiaoxia 
Published: June 2023

Abstract
The popularization of social media has created a more complex network opinion environment, affecting people's consumption choices for emerging technical products. Compared to positive opinion, negative opinion has a more profound impact, and its impact mechanism has not yet reached consensus in the academia. As a concept of positive psychology and organizational behavior, mindfulness is manifested in the processing of information in the cognitive process, and it is considered to be the key to accept new technologies and experiences. Based on the Information Adoption Model and mindfulness intervention in the cognitive orientation process, this study explores the negative network opinion on driverless cars through empirical research method to analyze consumers' handling of negative information about emerging technical products and their purchase intention in the context of negative information. The research findings indicate that negative opinion does not always bring negative impacts. Under the stimulation of negative opinion, consumers will develop risk perception and activate defense mechanisms. Under the moderating effect of mindfulness, and defense by counter argument and source derogation, consumers will process the information rationally. This study provides a different perspective for exploring the impact mechanism of negative network opinion, expanding the concept of mindfulness model in technology adoption, and extending the boundary of research on mindfulness in cognitive orientation process from the perspectives of information dissemination and psychological intervention.
Enhancement of Hybrid Deep Neural Network Using Activation Function for EEG based Emotion Recognition
Authors: margaret jehosheba , banu masoodhu 
Published: June 2023

Abstract

Deep Neural Network (DNN) is an advancing technology that improves our life by allowing machines to perform complex tasks. Hybrid Deep Neural Network (HDNN) is widely used for emotion recognition using EEG signals due to its increase in performance than DNN. Among several factors that improve the performance of the network, activation is an essential parameter that improves the model accuracy by introducing non-linearity into DNN. Activation function enables non-linear learning and solve the complexity between the input and output data. The selection of activation function depends on the type of data that is used for computation. This paper investigates the model performance of different activation functions like ReLU, ELU and tanh on a hybrid CNN with Bi-LSTM model for emotion recognition. The model was tested on DEAP dataset which is an emotion dataset that uses physiological and EEG signals. The experimental results have shown that the model has improved accuracy when ELU function is used.
Factors Associated with Violent Crimes Among Offenders with Mental Illness in Forensic Assessments
Authors: Lin Chia-Heng , Hsieh Wen-Ching , Lin Li-Ting , Chan Chia-Hsiang 
Published: June 2023

Abstract

Although the media often portrays violent criminal offenders as insane, the crime rate of individuals with severe mental illness is not higher than that of the general population. Social isolation in prisons or general psychiatric hospitals is thus a seemingly futile measures in crime prevention. However, few Asian studies have investigated the risk factors associated with violent criminal offenders with mental illness. The study collected 568 offenses from forensic psychiatric assessment reports completed at a psychiatric center from October 2009 to October 2021, excluding sexual offenses. The offenders were classified as violent offenders or nonviolent offenders. The study analyzed the sociodemographic characteristics, clinical characteristics, and forensic information of the offenders, and assessed their associations with violent crimes. Most offenders (n = 568) were male (74.5%), unemployed (91.4%), and single (92.8%). Compared with offenders without schizophrenia spectrum disorders (n = 287), offenders with schizophrenia spectrum disorders (n = 281) did not have significantly more alcohol use disorder (12.5% vs. 21.3%,p = .007), other substance use disorders (19.2% vs. 16.4%,p = .382), or commit more violent crimes (23.5% vs. 13.8%,p = .209). Men (OR: 2.12; 95% CI: 1.35–3.38) and those diagnosed with alcohol use disorder (OR: 1.62; 95% CI: 1.02–2.57) were more likely to commit violent crimes. Offenders with a diagnosis of intellectual disability (OR: 0.37; 95% CI: 0.19–0.73) were less likely to have commit violent crimes. Alcohol use disorder was the only dynamic factor associated with violent criminal offenders with mental illness.
Genie Aided Channel Learning For Millimeter Wave MIMO System
Authors: chauhan Aisha , Singh Sarvjit 
Published: June 2023

Abstract
Genie aided algorithm can be used for mm wave (Millimeter wave) MIMO systems. It provides the information of AOA's (Angle of Arrival) and AOD's (Angle of Departure) in beam space channel. In this, we proposed a genie-assisted channel learning estimate for uplink transmissions with equal power allocation. In this we study that mmWave MIMO (Multiple Input Multiple Output) channel has unique property and these are not exploited by conventional techniques i.e. LS (Least Square) and MMSE (Minimum Mean Square Error). Hence we created array response vector dictionary of codebook at receiver and transmitter. While we model the mm wave MIMO channel estimation the sparse matrix can be generated with large number of non zero entries. To eliminate this non zero entries we proposed the OMP (Orthogonal matching Pursuit).
Cholinergic Side Effect-Free Anticancer Drugs: Paving the Way for Safer and More Effective Cancer Treatment
Authors: . Ritu , Chandra Prakash , Das Asmita 
Published: June 2023

Abstract

Cancer is a leading cause of mortality worldwide, and various anticancer medications have been developed that target different biological pathways involved in cancer growth and progression. Topoisomerase I (TOP1) is an essential enzyme involved in unwinding supercoiled DNA, and it serves as a key target for several anti-cancer drugs. Irinotecan, a semi-synthetic derivative of camptothecin, is a potent topoisomerase I toxin that is effective at eliminating human tumor cells. However, irinotecan and other topoisomerase I inhibitors are known to cause cholinergic syndrome, which can lead to severe side effects in cancer patients. Further investigation has revealed that the acetylcholinesterase (AChE) enzyme plays a role in the development of cholinergic syndrome in irinotecan-treated patients. It appears that irinotecan or its metabolites directly interact with AChE, leading to an accumulation of acetylcholine and subsequent symptoms of cholinergic syndrome. Phytochemicals present in the plant Phyllanthus emblica, commonly known as amla, have been studied for their therapeutic effects on various diseases. This study focuses on targeting and inhibiting the TOP1 protein using the phytochemicals present in amla as a potential substitute treatment for cancer. In-silico studies were conducted to analyze the binding affinities of sixty three compounds towards the target TOP1 and AChE enzyme and check their drug likeness property using ADME. The six hit compounds with binding affinities similar to or better than their respective standard inhibitors were selected, and their stability was checked using molecular dynamic simulation. These findings suggest that the development of novel anticancer medications that do not inhibit AChE or fresh Topoisomerase inhibitors based on the camptothecin scaffold may help alleviate the side effects of irinotecan.
Autoclave Design for Microgravity Hydrothermal Synthesis
Authors: Frick Jessica J. , Ormsby Rachel , Li Zhou , Ozbakir Yaprak , Liu Chen , Cox Jasmine M. , Carraro Carlo , Maboudian Roya , Senesky Debbie G. 
Published: June 2023

Abstract

Microgravity offers an enticing synthetic knob for materials scientists to explore—however, this environment creates major challenges in hardware development that can turn a simple 3-day experiment into a 3-year long nightmare. This paper provides an overview of engineering an autoclave, compatible with NASA’s Solidification Using a Baffle in Sealed Ampoules (SUBSA) furnace, to enable microgravity hydrothermal synthesis—an acceleration-sensitive technique that processes aqueous samples above the boiling point of water. Hydrothermal synthesis is a universal chemical transformation technique that is used to produce a range of advanced materials with applications in alternative energy, healthcare, and the food industry. In this work, we use the synthesis of graphene hydrogel as a case study to verify our hardware design on Earth before launching to the International Space Station for microgravity testing. The design addresses pertinent challenges which include enabling thermal expansion while preventing air bubble formation in solution and implementing a pressure fail-safe above the maximum operating temperature. Our goal in presenting this autoclave design is to provide a step forward towards commercial-of-the-shelf microgravity hardware.
Expression of Serum Cortisol and Aβ42 in the Prediction of Early Onset Alzheimer's Disease in Patients with Generalised Anxiety Disorders and Stage III/IV Periodontitis
Authors: Kesavaram Jeyvarshini , Cholan Priyanka K , Victor DJ , Tadepalli Anupama , Lakshmi R , Prasanth Shunmuga 
Published: June 2023

Abstract

Objectives: Biochemical inflammatory mediators play a salient role in the pathogenesis as well as inflammatory responses of periodontitis initiated by microbial dysbiosis, linking chronic periodontitis to Alzheimer's disease (AD). The aim of the current study is to assess and correlate the role of serum cortisol and Aβ42 in the prediction of early onset Alzheimer's Disease in patients with and without Generalised Anxiety Disorders and Stage III/IV periodontitis.
Materials and methods : 56 patients were enrolled based on the inclusion criteria into four groups with clinically healthy gingiva and Stage III/IV Periodontitis with and without generalised anxiety disorders. A full mouth periodontal examination was done and DASS-21 scores were recorded. ELISA was done to quantify the levels of serum cortisol and Aβ42.
Results: Cortisol and Aβ42 levels were found to be expressed in the serum of all subjects in the four groups. The levels of assessed biomarkers were the least (Serum Cortisol: 2.57 ± 0.84, Serum Aβ42: 10.57 ± 6.49) in Group I (systemically healthy subjects with clinically healthy gingiva) and highly elevated (Serum Cortisol: 5.36 ± 3.22, Serum Aβ42: 57.64 ± 56.62) in Group IV (Generalised Anxiety Disorder with Generalised Stage III/IV Periodontitis). The clinical parameters of periodontal disease such as PI, mSBI, PPD, CAL, total number of teeth, DASS-21 depicted a significantly positive correlation with Cortisol as well as Aβ42.
Conclusions: The present study suggests that a triad consisting of stress induced serum cortisol, Aβ42 along with clinical periodontal parameters could be useful predictive markers for quantifying the risk of developing Early Onset Alzheimer's Disease (EOAD).
XOR Hash in Blockchain’s Header to Mitigate Storage Constraints
Authors: Karunakaran Vijay , Godfrey W Wilfred 
Published: June 2023

Abstract
The usage of internet and technology inspires the industries to work more on IoT based applications by decentralizing the data storage to ensure data integrity. In such cases, we use blockchain however, with most IoT applications there is always a storage constraint where the IoT devices keep generating the data every few minutes resulting in infinite growth of blockchain that any simple IoT devices would not be able to handle. The idea of deleting old blocks and storing only the recent data by labeling them as expired and unexpired blocks while storing Xor of hashes of deleted set of blocks. Although it resolves some of the issues and attacks, there can be some communication overhead when a node fetches some deleted blocks from other nodes, to validate these blocks, we might need whole set of blocks depending on the set size. Hence arriving at a new idea of adding Xor hash in the block header itself, that resolves the communication overhead along with that full nodes will also be used to always maintain the ledger from the beginning. These ideas will be implemented in an effective way that can be used in real world IoT based applications or any other storage constrained applications
Loading of a porous rock with constant micro-seismic event rate suppresses seismicity and promotes subcritical failure
Authors: Mangriotis Maria-Daphne , Cartwright-Taylor Alexis , Main Ian , Curtis Andrew , Bell Andrew , Butler Ian B. , Fusseis Florian 
Published: June 2023

Abstract

Catastrophic failure is the end result of a progression of damage towards brittle failure on a variety of system scales in the Earth. However, the factors controlling this evolution, and the relationship between deformation and the resulting earthquake hazard, are not well constrained. In particular, induced seismicity is a growing cause of concern in the engineering required for the net-zero carbon transition. Here we address the question of how to optimize operational controls to minimize microseismicity in a laboratory experiment where we can simultaneously image the underlying damage using x-rays and detect acoustic emissions. We show that using continuous servo-control based on acoustic emission event rate not only slows down deformation, but also suppresses events of all sizes, including extreme events. We develop a model that explains this observation, based on the the observed evolution of microstructural damage and the fracture mechanics of subcritical crack growth. The model is independently consistent with the observed stress history and acoustic emission statistics. Our results imply including seismic event rate control may be more effective in managing the risk from induced seismicity than current ‘traffic light’ systems based on extreme events alone.