bluuebunny/crossref_metadata_2025 huggingface dataset:
Coning Control Completion Technology for Water Management
Authors: AlSubaiei Dalal , Al-Mousawi Abdullah , Kumar Priya , Ron Angel , Zakrya Shamseldin , Al-Husaini Mohammad
Published: March 2024

Early in the well's life, the presence of formation water under strong water drive supports oil production. Eventually with time, this will become a problem that is challenging to manage. Maintaining and growing North Kuwait's oil production year after year made it impossible to continue producing well with high water production caused by conning effect. The critical coning rate required for lower Burgan (LB) to eliminate the conning effect and continue producing with low water cut (WC), as determined by Chappelear and Hirasaki correlation, is ± 300 BLPD. In order to prevent coning, an LB well should be produced at a rate lower than 300 BOPD. Producing wells at a rate lower than 300 BLPD is not feasible due to the high requirement of oil rate that north Kuwait targets.

Coning Control Completion (CCC) is a cutting-edge technology used in North Kuwait to solve Lower Burgan formation (LB) coning problems. A reversible Electric Submersible Pump (ESP) is part of this completion system that is positioned below the oil-water contact (OWC). In order to control the progression of the water cone inside the oil zone, the reverse ESP generates a counteractive pressure drop below the OWC.

Redirecting water into the underlying reservoir by drawing it below the desired zone's OWC is a crucial function of the reverse ESP. The quantity of generated water that rises to the surface is reduced by this process keeping the same liquid rate. Water cut (WC) has been decreased as a consequence of the effective use of CCC in North Kuwait, going from 90% to around 40 %.

The successful implementation of CCC in North Kuwait has helped and enhanced the development plan for lower Burgan and will help controlling conning issue world wide
Title Physicochemical Water Control: A Sustainable and Practical Approach to Avoid Deferred Production Related to Chemical Problems and Consumption Management
Authors: Hernandez B. , Salazar J. , Castilla S. , Borjas J. , Jimenez G.
Published: March 2024

Managing oil and gas production requires the integration and analysis of multiple sources, including chemical analysis data, laboratory reports, and specialized analyses. Quick and efficient access to this data will allow engineers to focus on generating analysis and decision-making tasks to improve production and field performance.

This document presents an overview of the project on the implementation of an automated workflow designed to support the analysis physicochemical of production water applied to Colombian fields. The project was developed through cloud apps, as a new platform that supports the visualizer solution, using data analysis and the production domain of physicochemical.

The implementation consists of three stages, the first standardized the information from the field physicochemical, which was stored in Database as a centralized platform. With the results from the first step, the second stage begins to apply different automated calculations to establish the Langelier, Ryznar, Puckorius and Larson Indexes, among others, to determine the stability of the fluids and formations of corrosion, wax, scale, asphaltenes with the objective of identifying and improving self-sufficiency, product consumption and ensuring operational autonomy.

The third stage and completion of the solution workflow is integrated through data analysis where the calculations are visualized based on different knowledge, avoiding delays associated with chemical problems and allowing the flow assurance of the wells that are part of the field. This workflow resulted in considerable time savings as relevant data will be automatically updated and used in analysis, instead of manual processing, improving efficiency in field management practices. Furthermore, it is a new workflow that can be replicated in other solutions.
Delayed Fungal Infection After Anterior Lateral Interbody Fusion Treated With Oblique Lateral Interbody Fusion: A Case Report and Literature Review
Authors: Kim Se Woon , Oh Bu Kwang , Son Dong Wuk , Lee Jun Seok , Lee Su Hun , Kim Young Ha , Sung Soon Ki , Lee Sang Weon , Song Geun Sung
Published: March 2024

This report presents a rare case of a fungal infection following an anterior lateral interbody fusion (ALIF) procedure. A 73-year-old man with rheumatoid arthritis underwent ALIF for lumbar spondylolisthesis and spinal stenosis. After surgery, he experienced severe back pain. Radiological tests showed pseudoarthrosis, osteolysis, and signs of surgical site infection. Revision surgery using oblique lateral interbody fusion (OLIF) and an allo-bone graft was performed. This addressed the complications, removed the previous cage, and provided interbody support. The patient’s pain significantly decreased, and he recovered from an Aspergillus fumigatus infection after voriconazole treatment. Follow-up examinations confirmed the infection’s resolution and the maintenance of spinal stability. It is crucial to identify fungal infections in patients on immunosuppressive drugs. The case validates the efficacy of voriconazole efficacy in treating Aspergillus spondylitis and the safety and effectiveness of OLIF for ALIF revision surgery.
Caregiver Experiences and Needs in Paediatric Rheumatic Disease: A Mixed-Methods Systematic Review Protocol
Authors: Xiang Yuxuan , Ding Ru , Yuan Bixia , Wu Jing , Lu Yongmei , Yang Xiangwei
Published: March 2024

Introduction We will employ a mixed-methods approach to evaluate the real-life experiences and requirements of caregivers for children diagnosed with rheumatic diseases, with the aim of providing insights for both research and clinical interventions. Understanding the genuine experiences and requirements of caregivers and implementing targeted interventions can have a positive impact on the physical and mental well-being of caregivers, ultimately reducing their burden and enhancing their quality of life. While there has been a gradual increase in research in this area in recent years, there remains a gap in the evidence that comprehensively and systematically reflects the actual experiences and needs of caregivers.
Methods and analysis We will conduct a comprehensive search across multiple databases, including MEDLINE (PubMed), Embase (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (CENTRAL), CNKI, WanFang, and VIP, as well as the grey literature, to identify primary studies published in either English or Chinese since 2000. In our systematic review, we will employ a mixed methods assessment tool to evaluate study quality, and we will apply a convergent integration approach to synthesize the data. Studies employing qualitative, quantitative, or mixed methods to elucidate the authentic experiences, emotions, and requirements of caregivers of children diagnosed with rheumatic diseases will be included in this review.
Ethics and dissemination Ethical approval is not needed, as no primary data will be collected. The results will be made available through a peer-reviewed publication.
PROSPERO registration number 42023465302
The feasibility and acceptability of delivering and evaluating a physical activity intervention (ACCEPTANCE) for cervical cancer survivors
Authors: Millet Nessa , McDermott Hilary J , Munir Fehmidah , Edwardson Charlotte L , Plekhanova Tatiana , Moss Esther L
Published: March 2024

Background: Cervical cancer treatment can be associated with long-term physical, psychological and emotional issues leading to compromised quality of life (QOL). Physical activity (PA) may improve QOL in cervical cancer survivors.
Methods: A one arm pre/post- feasibility study with parallel process evaluation was conducted to test the feasibility and acceptability of a 12-week PA intervention (ACCEPTANCE). Feasibility was determined by using pre-established criteria relating to: inclusion criteria, recruitment and retention, compliance with intervention components and compliance with evaluation measures. The 12- week intervention consisted of: 1) an online education session on the benefits of PA and a barrier identification and problem-solving session; 2) a Fitbit monitor; 3) daily and weekly diary entries; 4) brief fortnightly online health coaching sessions; and 5) organising and participating in group walks 6) online social interaction via a messaging group. Measures included accelerometer assessed PA and sleep, quality-of-life and PA behaviour change questionnaires distributed at 4-time points (baseline, week-6, week-12 and week-24). Process evaluation measures were questionnaires on the acceptance of intervention components and semi-structured interviews with participants after completion.
Results: 30 participants were recruited with a retention rate of 77% at week-24. The education session, health coaching and Fitbit PA monitor were deemed to be feasible based on compliance rates whilst the online messaging group, diary and group waking compliance suggested that modifications would be needed. Accelerometer and questionnaires were deemed to be feasible evaluation measures based on compliance rates. Process evaluation results suggest that the Fitbit and health coaching sessions were perceived to be the most beneficial aspects of the programme as they enabled self-monitoring of behaviour and goal setting. Unexpected mechanisms of behaviour change were the integration of a small change approach and formation of habits to facilitate PA, whilst barriers to behaviour change included the online, virtual nature of the programme, poor mental health, and environmental challenges. Physical activity levels were higher after the intervention, whilst QOL was seen to worsen throughout the study.
Conclusions: The ACCEPTANCE study is deemed to be feasible based on criteria established a priori, and only minor modifications would be needed ready for a definitive randomised control trial. The intervention showed potential to increase PA, through hypothesised mechanisms of self-monitoring behaviour and problem solving and unexpected mechanisms such as habit formation.
Trial registration: ISRCTN16349793, Registered 30 September 2020.
Key words: Exercise Oncology, Feasibility trial, Process evaluation, Cervical cancer survivorship
Implementation of a program to strengthen oral hygiene in patient with cleft deformities: a prospective clinical trial
Authors: Boeffard Camille , LOIN Justine , CLOUET Roselyne , GAUDIN Alexis , CORRE Pierre , PRUD'HOMME Tony
Published: March 2024

Background: Cleft lip and/or palate is the most common congenital orofacial deformity, affecting 1/800 births. A thorough review of the literature has shown that children with cleft have poorer oral hygiene and dental health than other children, with higher levels of caries in both temporary and permanent teeth and poorer periodontal health. Cleft patients are treated by a multidisciplinary team that aims to provide comprehensive care from pre- or post-natal diagnosis to early adulthood and the end of growth. We aim to assess, through a single-center, prospective, randomized and controlled clinical trial conducted at the Nantes Cleft Centre, the impact of an enhanced dental program on oral hygiene and dental health in cleft patients.
Methods: Patients aged 3 to 15 years with unilateral or bilateral cleft lip and/or palate will be offered to participate in this study. After acceptance, patients will be randomly assigned to 2 groups: test group or control group. For the control group, there will be no change in the patient's care, and they will continue to see their surgeon on an annual basis.
For the test group, a 30–45-minute consultation will be added to the annual check-up. During this visit, patients and their parents will receive oral and written oral hygiene instructions to improve oral hygiene knowledge and brushing technique. If necessary, dental treatment will be provided at the same appointment or at a later date. In addition, patients will be contacted via telemedicine every 2 months to increase motivation, and an additional dental appointment will be scheduled at 6 months.
Discussion: This is a single-center study which, if conclusive, could lead to a paradigm shift in the dental care pathway for cleft patients.
Trial registration: NCT05867862 subbmited 2023-07-05 https://clinicaltrials.gov/study/NCT05867862?locStr=Nantes,%20France&country=France&state=Pays%20de%20la%20Loire&city=Nantes&distance=50
&cond=CLEFT%20LIP&rank=1- - Trial Sponsor Nantes University Hospital
Mid-Infrared Silicon Nitride Metalens: Achieving High Achromaticity and Wideband Performance Trough Inverse Design Techniques
Authors: Maher Abdullah , Swillam Mohamed A.
Published: March 2024

Inverse design with topology optimization considers a promising methodology for discovering new optimized photonic structure that enables to break the limitations of the forward or the traditional design especially for the meta-structure. This work presents a high efficiency mid infra-red imaging photonics element along mid infra-red wavelengths band starts from 2 µm to 5 µm based on silicon nitride optimized material structures. The first two designs are broadband focusing and reflective meta-lens under very high numerical aperture condition (NA = 0.9). The two designs are modeled by inverse design with topology optimization problem with Kreisselmeier-Steinhauser (k-s) aggregation objective function, while the final design is depended on novel inverse design optimization problem with double aggregation objective function that can target multi focal points along the wavelength band producing high efficiency achromatic broadband multi-focal meta-lens under very high numerical aperture (NA = 0.9).
Utility of artificial intelligence “one-minute free conversational voice” analysis for detecting cognitive decline in individuals
Authors: Kuroda Takeshi , Ono Kenjiro , Murakami Kouzou , Onishi Masaki , Shoji Daiki , Kosuge Shota , Ishida Atsushi , Hieda Sotaro , Yamaguchi Shohei , Takahashi Masato , Nakashima Hisashi , Ito Yoshinori , Murakami Hidetomo
Published: March 2024

Recent developments in artificial intelligence (AI) have provided new technologies that can aid in detecting cognitive decline. This study developed a voice AI model that screens for cognitive decline solely based on a short conversational voice sample. This study involved collecting voice data, AI machine learning (ML), and confirming accuracy using test data. AI extracts multiple voice features from the collected voice data to detect potential signs of cognitive impairment. Data labeling for ML was based on Mini-Mental State Examination scores; scores of 23 or lower were labeled as “cognitively declined (CD),” while scores above 24 were labeled as “cognitively normal (CN).” A fully coupled neural network architecture was employed for deep learning using voice data from 263 patients. Twenty voice samples, comprising “one-minute conversations,” were used for accuracy evaluation. The developed AI model achieved an accuracy of 0.950 in discriminating between CD and CN individuals, with a sensitivity of 0.875, specificity of 1.000, and average area under the curve of 0.990. This voice AI model serves as a promising cognitive screening tool accessible via mobile devices, requiring no specialized environments or equipment.
Plastic sex-trait modulation by differential gene expression according to social environment in male red deer
Authors: Broggini Camilla , Abril Nieves , Membrillo Alberto , Peña Eva de la , Carranza Juan
Published: March 2024

Mates competition encourages individuals to modulate characters involved in mating success. Adult Iberian red deer (Cervus elaphus hispanicus) males show a dark ventral patch (DVP) that plays a central role in mating rivalry, whose size and chemical compounds varied according to the level of male-male competition within the population. In the pigmentation of the DVP appears, after urinary excretion, a molecule called DOPEG originating from the metabolism of norepinephrine, leading us to investigate whether differential expression mechanisms of key genes (DBH and TH) encoding enzymes catalyzing the process can be sensitive to different competitive population situations and responsible for the plastic development of the DVP in red deer. We found that social environment with higher intrasexual competition, where male invest more in sexual traits, was associated with increased levels of DBH and TH transcripts, while Dopamine showed reversed values. We found alternative splicing for the TH gene, although differences between social environments appeared just related to expression levels. Our results support the internal cause of trait modulation based on differential gene expression in relation to the conditions of intrasexual competition in social environment. We propose the quantification of DBH transcripts as a molecular biomarker of male red deer reproductive activity.
Consecutive Cytokeratin Immunochemistry-Supervised Algorithm for Predicting Tumor Areas in Ki67 Breast Cancer Images
Authors: Wu Chien-Hui , Chang Min-Hsiang , Tsai Hsin-Hsiu , Yang Mei-Lin , Peng Yi-Ting
Published: March 2024

Automatic Ki67 index (KI) assessment has become popular in breast cancer research; however, the results are easily influenced by non-tumor cells. This can be addressed by using neural networks to predict tumor areas. Compared to human annotation, cytokeratin immunostaining can more accurately highlight epithelial regions and provide reliable ground truth. We built an immunohistochemistry (IHC)-supervised neural network using the ground truth extracted from consecutive cytokeratin-stained slides, which could predict the tumor area in Ki67 images of breast cancer. The effect of masks on KI quantification was evaluated in 20 patients with breast carcinoma. Set A (three cases) was used to measure the similarity of adjacent whole-slide images (WSIs). A UNet++ (with an EfficientNet-b7 backbone) model was built using Set B (67 cases) for tumor area prediction. The KI in Set C (20 cases) was quantified with and without the application of tumor-area masks, and the KI difference was computed. The mean intersection over union of the epithelial masks extracted from adjacent cytokeratin sections was 0.72 (0.68–0.76). After training and validating in 49 cases, the intersection over union in the test set was 0.44–0.73. At the tile image-level, KI difference was − 42.5–41.7%. Images with the highest difference usually contained numerous lymphocytes or vessels, and the masks prevented disguised cells from being counted. At the WSI-level, the hotspot location changed in 18/20 cases, but hotspot KI changed insignificantly (− 1.0% on average). The global KI changed less (0.9% on average). Thus, consecutive IHC staining provides substantial, precise, and reliable ground truths that trained the algorithm efficiently. This IHC-supervised training workflow can be applied to other targets by replacing IHC antibodies. Furthermore, the virtual tumor areas improved Ki67 counting by excluding the non-tumor areas at the tile image-level, although the effect on the WSI-level was insignificant.
PMNBARL: Enhancing Efficiency of Privacy Management in Digital Networks through Blockchain and Adaptive Reinforcement Learning
Authors: Research Hiralal Solunke , Bhaladhare Pawan , Potgantwar Amol
Published: March 2024

The urgent need for advanced privacy mechanisms in the digital era is underscored by the growing concerns over data breaches and privacy invasions. Traditional privacy management methods often fall short in addressing these challenges, primarily due to their static nature and limited adaptability to evolving cyber threats. This work presents an efficient method to privacy management by integrating blockchain technology with adaptive privacy mechanisms, leveraging the power of machine learning (ML) and deep learning (DL) algorithms. Existing privacy management systems are predominantly rigid, offering limited scope for dynamic adaptation to changing network conditions and user behaviors. Such systems are increasingly inadequate in handling the complexities of modern data environments, often leading to compromised data confidentiality and higher instances of unauthorized data access or policy violations for different use cases. In response, this paper introduces an innovative model that employs smart contracts on the blockchain for privacy policy enforcement operations. These smart contracts ensure secure, transparent, and immutable privacy management, markedly enhancing data confidentiality and reducing policy violations under different attacks. Furthermore, the application of Reinforcement Learning (RL), enables dynamic privacy policy management operations. RL's ability to learn and adjust policies adaptively in response to environmental feedback ensures improved responsiveness and efficiency in privacy settings. A novel aspect of this work is the integration of Anomaly Detection using Deep Neural Networks (DNNs) with blockchain technology for self-adaptive security. DNNs' proficiency in identifying complex patterns in large datasets allows for the early detection of privacy breaches, enhancing the overall security performance levels. Additionally, the implementation of Differential Privacy in Federated Learning addresses the challenge of preserving data privacy during collective model training, thus ensuring robust privacy protection operations. The proposed methods were tested on various real-time simulation datasets, showcasing superior performance over existing methods in terms of energy efficiency, speed, throughput, consistency, and packet delivery ratio sets. This work not only presents a significant advancement in privacy management but also sets a new standard for future research in the field of data privacy and security levels.
Acquisition of clinical reasoning skills by undergraduate nursing students in Malawi; towards development of a middle-range theory : A qualitative study
Authors: Mwale Omero. G. , Mukwato Patricia. K. , makukula Marjorie .k.
Published: March 2024

Introduction: Acquisition of clinical reasoning skills is essential in nursing for patient safety. Lack of clinical reasoning skills in nursing can impose harmful consequences on the patient. However, teaching and learning clinical reasoning skills is not easy due to its complexity. Without a model, clinical reasoning is taught intuitively. Therefore, this study aimed at investigating how undergraduate nursing students acquire clinical reasoning skills, towards development of a middle-range theory.
Methods: This study employed Grounded theory of systematic design underpinned by a social constructivism paradigm. The participants were undergraduate nursing students and nurse educators. Purposive sampling was used to sample the participants. Data were collected in six months using numerous methods of interviews, observations, and document review Twelve individual in-depth interviews and six focus group discussions were conducted. Data collection and initial data analysis occurred concurrently using a coding process, with comparative analysis.
Results: The study revealed that undergraduate nursing students acquired clinical reasoning skills through automation while utilizing the nursing process. Through the themes, a new theory called ‘a middle-range theory for the acquisition of clinical reasoning skills’, was generated in this current study. The associated concepts were environmental setting, type of curriculum, anchors and expected outcomes which included individual and health care system indicators.
Conclusion: Teaching undergraduate nursing students how to reason clinically will develop nurses who can adjust and solve problems in changing patient’s situations. Based on the findings of this study, it is recommended that nursing students be equipped with adequate clinical reasoning skills before they graduate. Therefore, implementing the new model called ‘a middle range theory for the acquisition of clinical reasoning skills’ could foster the development of clinical reasoning skills from the start of the nursing training program.
Intraoperative virtual reality for older patients undergoing total knee arthroplasty: study protocol for a randomized clinical trial
Authors: Espinosa-Leon Juan P. , Mathura Ryan , Chen Guanqing , Joseph Melisa , Sadhwani Trishna , Beydoun Najla , Hernandez Edjay R. , Riley Tyler , Kunze Lisa J. , Goodspeed Valerie , O'Gara Brian P.
Published: March 2024

Background:
In an aging surgical patient population, preventing complications such as oversedation has taken increasing priority in perioperative care. Intraoperative use of Virtual Reality (VR) may decrease sedative requirements. We hypothesize that the use of immersive VR during total knee arthroplasty (TKA) will lead to decreased propofol requirements, improved patient-reported satisfaction, and reduced postoperative opioid requirements compared to active and usual care controls.
Methods:
This is a single center, randomized clinical trial of older (age > 60) patients undergoing TKA. Participants will be randomized into three groups (2:2:1): VR immersion, music, and sham VR plus usual care. All patients will receive a regional block and spinal anesthesia. Patients in the immersive VR and music groups will use Patient Controlled Sedation (PCS) with propofol, while those in the sham VR group will act as the standard of care control group and will receive Monitored Anesthesia Care (MAC) with propofol infusion.
Statistical Analysis:
Analyses will be conducted using IBM SPSS Statistics Version 25, considering a two-sided p-value < 0.05 to be statistically significant. The primary outcome is the intraoperative dose of propofol (mg kg− 1 min− 1). Secondary outcomes include patient satisfaction, post-anesthesia care unit (PACU) length of stay, postoperative pain scores and analgesic requirements, functional outcomes, postoperative delirium, and postoperative neurocognition.
Discussion:
VR used as a non-pharmacological adjunct to regional and spinal anesthesia during TKA may reduce sedative requirements while maintaining patient satisfaction. If true, this approach to minimizing sedation may impact clinical outcomes including perioperative complications and length of stay for older patients, while maintaining a high degree of patient satisfaction.
Trial Registration:
This trial was registered on clinicaltrials.gov on January 29, 2021. The registration number is NCT04748549.
https://clinicaltrials.gov/ct2/show/NCT04748549
Sintilimab plus GemOx is an effective salvage therapy in patients with refractory⁄relapsing nodal peripheral T cell lymphomas
Authors: Xiao Xibin , Hu Mengmeng , Jiang Huawei , Chen Panpan , Lei Huyi
Published: March 2024

Peripheral T-cell lymphomas (PTCLs) are a heterogeneous group of rare malignancies. Once relapse or progression after front-line therapy, treatment options are minimal. We designed a retrospective study to explore the effectiveness and safety of chemoimmunotherapy in relapse or refractory nodal PTCLs. 31 patients with r/r nodal PTCLs were enrolled, including 23 PTCL-NOS, 4 AITL, and 4 ALCL. 21 (67.7%) patients received at least two lines of therapy. 71.0% (95% CI, 53.4%-83.9%) of patients documented objective response of 2–4 cycles of sintilimab plus GemOx therapy, including 9 complete response and 13 partial response. 21 (67.7%) patients received consolidation therapy, including 5 autologous stem-cell transplantation and 12 histone deacetylase inhibitors. After a median 25.6 months follow-up, the median PFS was 22.0 (95% CI,11.8–24.7) months, and the median OS was 26.2 (95% CI, 24.4 –NA) months. 29 (93.5%) patients experienced at least one adverse event, and 26 (83.9% patients only had mild (grade 1–2) AEs.Univariable Cox regression showed the progression risk of AITL is 22.7 (3.9–131.0, p < 0.01) times of PTCL-NOS, while the HR of ALCL was 1.14 (0.33–3.96,p = 0.833). Sintilimab plus GemOx showed encouraging activity and manageable toxicity for patients with r/r PTCL, warranting further investigations.
Incidence of In-Hospital Mortality and Its Determinants among Intensive Care Unit Patients with Acute Respiratory Distress Syndrome in Ethiopian: A multilevel analysis
Authors: Abate Semagn Mekonnen , Kebede Melkamu , Hailu Seyoum , Adamu Yayeh , Mantefardo Bahru , Meno Abinet , Lafebo Lakew
Published: March 2024

Purpose
Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome with substantial morbidity and mortality globally. Body of evidence revealed that the epidemiologic estimates are currently disproportional due to differences in patient populations, risk factors, resources, and practice protocols around the world, and the rate of mortality and its predictors are uncertain in Ethiopia.
Method
A multi-centre longitudinal study was conducted in Ethiopia from January 2018 to June 2023. After receiving ethical clearance from the Institutional Review Board (IRB) of Dilla University College of Health Science and Medicine, 356 ARDS patients’ records were retrieved with a systematic random sampling technique. A multilevel multivariate analysis was used to control the effect of clustering. A P < 0.05 was taken as statistically significant.
Results
This study demonstrated that the cumulative mortality rate of patients with ARDS was 59% (95% CI: 53.5 to 63.9). The multilevel multivariable model analysis showed that GCS < 8 (AOR = 7.4; 95% CI: 2.79, 19.75), severe form of ARDS (AOR 4.7 95% CI 1.64, 13.36), invasive ventilation (AOR 3.2, 95% CI 1.56, 6.42), and respiratory comorbidity (AOR 4.9, 95% CI 1.71, 14.32) were independent predictors of in-hospital mortality among patients with ARDS.
Conclusion
The study revealed that the hospital mortality rate was substantially higher than that of developed nations. The study also highlighted various risk factors that independently predicted in-hospital mortality.The findings of this study call for mitigating strategies to improve ICU care for ARDS patients.
An ultra-sensitive dopamine electrochemical sensor based on PVP/rGO-MWCNT composites
Authors: Jiang Yixuan , Luo Dandan , Liu Saiwen , Zhang Jin , Meng Wei , Chen Chao
Published: March 2024

Dopamine (DA) is a neurotransmitter secreted by the brain that plays a variety of roles in the central nervous system. An imbalance in dopamine can cause a range of disease symptoms and negative effects, such as Parkinson's disease and arrhythmia. Detecting DA accurately and rapidly is therefore crucial for medical diagnosis and disease prevention. In this study, PVP and rGO-MWCNT were encapsulated using a hydrothermal method to form a composite material. The composite was then characterized using scanning electron microscopy (SEM). The three materials were combined, and based on this, a new DA electrochemical sensor was constructed. It is worth noting that the high specific surface area and high conductivity of rGO-MWCNT cooperate with the amphiphilic and stable dispersion of PVP, which further improves the electrochemical performance of the sensor for DA. Under optimal conditions, DA content is detected within a wide range and with a low detection limit which is explained by the electrochemical redox process of the sensor. In addition, the sensor shows satisfactory recovery and accuracy in detecting DA content in real human serum samples using the standard addition method.
Los olvidados: Non-BRCA variants associated with Hereditary breast cancer in Mexican population
Authors: Aguilar Dione , Garza-Rodríguez María Lourdes , Muñiz-Garza Carolina Elizabeth , Villarreal-Garza Cynthia Mayte , Vidal-Gutiérrez Oscar , Pérez-Ibave Diana Cristina , Burciaga-Flores Carlos Horacio
Published: March 2024

Background: Hereditary predisposition to breast and ovarian cancer syndrome (HBOC) is a pathological condition with increased cancer risk, including breast (BC), ovarian cancer (OC), and others. HBOC pathogenesis is caused mainly by germline pathogenic variants (GPV) in BRCA1 and BRCA2 genes. However, other relevant genes are related to this syndrome diagnosis, prognosis, and treatment, including TP53, PALB2, CHEK2, ATM, etc. This study aimed to identify the prevalence of non-BRCA genes in HBOC patients of Northeast Mexico.
Methods: This multicentric study included 1285 patients with HBOC diagnosis from four oncologic centers in northeast Mexico from 2016 to 2023. Genomic and clinical data were analyzed based on multi-gene panel results and electronic records of the medical geneticist consultation. For the data analysis of qualitative and quantitative variants JASP statistical software (version 0.18.1) was used, taking p<0.05 as a significant results.
Results: We found that 32.7% of the patients had at least one GPV in non-BRCA genes. The five most frequent non-BRCA genes were CHEK2, PALB2, MUTYH, CDKN2A, and ATM. Among the group of non-BRCA genes, six are involved in the homologous repair pathway (HR), and three are related to DNA damage repair (DDR) pathways. In the analysis of GPVs in molecular pathways, DDR GPVs had a higher risk of developing BC and having cancer between 41-50 years.
Conclusion: Multi-gene testing implementation improves the detection of often overlooked genes related to HBOC pathogenesis and treatment. Non-BRCA GPVs in Northern Mexico correspond to one-third of the HBOC cases, including HR and DDR pathways genes that would be misdiagnosed if not tested. HR patient carriers are potential targets of iPARP therapies. The optimal approach to cancer treatment for non-BRCA mutation carriers warrants further investigation to develop newer therapies.
Transition from endogenous to exogenous feeding in longfin yellowtail Seriola rivoliana larvae under simultaneous effects of daily temperature fluctuation and enrichment of the rotifer Brachionus rotundiformis
Authors: Pacheco-Carlón Nairoby , Dios Marco A. Hernández-de , Nolasco-Soria Hector , Tovar-Ramírez Dariel , Maldonado-García Minerva , Maldonado-García Deneb
Published: March 2024

The most sensitive period in fish larva culture occurs when larvae must make the transition from endogenous to exogenous feeding, where temperature and nutrition are suggested as the primary factors affecting development and survival. However, little is known about its simultaneous impact during this period. This study aimed to determine the effect of two temperature regimes and rotifer enrichment at the first feeding of longfin yellowtail Seriola rivoliana. Eggs were subjected to a constant 24°C (CTE) and a daily temperature fluctuation (DTF) between 22.8–25.2°C until oil droplet exhaustion, 5.5 days after hatching. Inside the temperature treatments, the impact of three rotifer enrichment products (Ori-green, S.presso, and a Domestic emulsion) for the euryhaline Brachionus rotundiformis was evaluated. Results showed that larval survival was higher and larvae were bigger at DTF compared to CTE at oil droplet exhaustion. At the same stage, larval size from rotifer enrichments resulted bigger at Domestic emulsion compared to Ori-green. The relative expression of trypsin gen in larvae aged 3.7 DAH was higher at Domestic emulsion compared to S.presso emulsion and Ori-green. This study indicates that daily temperature fluctuation and Domestic emulsion can improve larval performance at first feeding. Domestic emulsion is probably a potential rotifer-enricher for longfin yellowtail larvae.
A city under siege: Time-series analysis of shootouts and the association with health and living conditions in Rio de Janeiro, Brazil, 2017-2022
Authors: Cunha Ana Paula , Mota Jurema Corrêa da , Bastos Francisco I
Published: March 2024

Armed violence is characterized by episodes of conflicts with the use of firearms and occasionally knives and other sharp objects. Ecological time series study applying the joinpoint model based on data on shootouts in the city of Rio de Janeiro, Brazil, from 2017 to 2022. We analyzed the possible association between shootouts and living conditions based on linear and polynomial regressions. Decreases were observed in the number of shootouts in the city of Rio de Janeiro from 2017 to 2022, although current levels of violence are still far above those defined by international agencies as desirable or even acceptable. The statistically significant associations between indicators of living and health conditions and episodes of shootouts were nonlinear (SPI: -2747.9 [(-4973.8; -522.0]; SDI: -2987.4 [(-537.1; -437.6)]). A decrease was observed in episodes of armed violence. The relationship with living conditions points to a complex association, not reducible to a possible linear relationship between violence and living conditions. The findings suggest that complex phenomena should be analyzed with state-of-the-art models, whether for diagnosis or to inform truly structural interventions.
How can equity, diversity, and inclusion (EDI) principles be incorporated into research excellence with industry and community partners? Lessons learnt from Canada andAustralia
Authors: Hung Lillian , Wong Karen Lok Yi , Rasekaba Tshepo , Ren Haopu , Blackberry Irene
Published: March 2024

Background
The rapid advancement of gerontechnology, technologies for older adults, needs a collaborative approach, integrating the efforts of researchers, industry and community partners. Multisectoral collaboration fosters a holistic view, merging industry expertise, academic rigour, and the lived experiences of older adults and caregivers. This paper explores the role of Equity, Diversity, and Inclusion (EDI) perspectives in such collaboration.
Methods
We present two case studies from Canada and Australia. Study one involves a Dementia Television project, and study two an innovative rural dementia care project. Data sources included case studies’ focus group transcripts, research meeting notes, or publications between 2021–2023 and 2016–2024, respectively. Utilizing Rofel’s reflective model, we reflected on lessons learned regarding challenges, strategies, and their implications for future research. Our analysis focused on two questions: 1) What were the common challenges we encountered in partnering with industry and community in the research process? And 2) How can EDI be applied to help overcome those challenges?
Results
Thematic analysis identified five common themes of challenges and ten practical strategies. The challenges are (1) implicit bias, (2) underrepresentation, (3) communication gaps, (4) mistrust and (5) power dynamics. Based on the lessons learned, we identified ten practical strategies through EDI principles: (1) diverse representation, (2) establish transparent agreements, (3) inclusive language and cultural sensitivity, (4) apply flexibility to learn and adapt, (5) embed team reflection (6) take time to build trust and relationships, (7) meaningful engagement, (8) equitable recognition (9) foster a respectful environment for shared learning, and (10) cultivate a long-term sustained relationship.
Conclusion
The older population is diverse, and their needs are complex. EDI considerations contribute to fostering research excellence and maximizing the potential to develop aging technologies that truly meet the diverse needs of older adults for societal impact. Multisector collaboration requires clear communication and intentional efforts to build trust. EDI considerations should be embedded at every stage of the research process. This paper outlined common challenges, strategies, and implications as practical tips for future research and practice.
Capturing lay perspectives on policy effectiveness: Employers’ and precariously employed workers’ suggested improvements for the workers’ compensation system and work injury processes
Authors: Billias Nicole , MacEachen Ellen
Published: March 2024

Purpose: Precarious employment rates are rising, which challenges the effectiveness of current workers’ compensation systems. Precariously employed workers encounter problems related to short-term and/or temporary employment, and complicated employment relationships. Few voices are captured in the literature from precariously employed workers and employers of these workers regarding day-today experience of workers’ compensation policies. This article describes employers’ and precariously employed workers’ suggested changes and improvements to a workers’ compensation system and other processes related to work injury and return-to-work.
Methods: Semi-structured interviews were conducted in Ontario, Canada with 36 precariously employed workers and 15 employers of precariously employed workers who were recruited via social media, email lists, cold calling, word-of-mouth, and the “snowball” method. Thematic code summaries were analyzed to identify suggested workers’ compensation system improvements that relate to precarious employment.
Results: Employers’ and precariously employed workers’ suggestions fell into the categories of (1) communication, (2) worker health and healthcare, and (3) worker and employer support.
Conclusions: Identifying precariously employed workers and employers of precariously employed workers’ suggestions enables a better understanding of areas of improvement for workers’ compensation policy and how these policy changes could affect these stakeholders with regards to managing workplace rehabilitation and disability.
MCPF: Fault-Tolerant Scheduling of Scientific Workflow on Cloud Computing
Authors: Ulabedin Zain , Khan Pervez , Uddin Burhan
Published: March 2024

Scientific workflow applications entail extensive amounts of tasks and data-sets necessitating systematic processing. Cloud platform is utilized for executing these applications which provide access to extensive amounts of scalable and on demand resources. Running scientific workflow applications on cloud computing experiences a huge amount of failure, i.e., hardware failures, software failures, network failures, etc., due to the large scale heterogeneity and distributed nature. That affects overall workflow execution time, monitory cost, and resource utilization. Numerous fault-tolerance methods are used to resolve and handle failures in cloud computing environment. In this paper, we used the MCPF (Multiple Critical Partitions with Failure) technique. The proposed technique has two phases. In the first phase, the rank of all tasks is calculated by summing the ranks, i.e., downward and upward rank. And then, in the second phase tasks are scheduled based on their ranking on the VMs, which has a lower failure rate. We evaluated the performance of our proposed technique under different conditions using parameters, i.e., makespan and cost. We have compared the results of MCPF with well-known existing HEFT, and RDEARP algorithms. Simulation results obtained through experiments and their comparison with existing techniques lead us to the conclusion that our proposed technique yields better results than existing algorithms.
Development of a LC-UV method for the rapid screening of arbutin, hydroquinone, dexamethasone, hydrocortisone, and clobetasol propionate in skin-whitening cosmetic products
Authors: Tang Erasmus N , Lenga Stephanie , Siani-Yonga Henri G , Ngono-Mballa Rose , Heudi Olivier
Published: March 2024

A simple liquid chromatography method with UV detection was developed for the rapid screening of arbutin, hydroquinone, dexamethasone, hydrocortisone and clobetasol propionate in four skin-whitening cosmetic products. The chromatographic conditions for their screening in less than 15 min were optimized on a Kinetex® 2.6 µm Polar C18 column (150 x 4.6 mm) with a gradient of mobile phase made of 0.025% TFA in water and acetonitrile ) and UV detection was performed at two wavelengths, 240 nm and 270 nm. Under these conditions, arbutin, hydroquinone, dexamethasone, hydrocortisone and clobetasol propionate eluted with retention time of 2.20, 3.75, 11.95, 12.58 and 12.75 min, respectively. By comparing the retention characteristics and UV spectra and the peak purity of the standard with each compound, arbutin, hydroquinone, hydrocortisone and clobetasol were identified in the milk and whitening cream products tested while dexamethasone was not found. An attempt for their quantification showed that hydroquinone was the major ingredients. The preliminary results of study show that our method is suitable for rapid screening of arbutin, hydroquinone, hydrocortisone and clobetasol propionate in skin-whitening cosmetic and, could be applied after validation to their quantitation.
A Deep Learning model for the identification of Potato leaf diseases using Wrapper Feature Selection and Concatenation
Authors: Naeem Muhammad Ahtsam , Saleem Muhammad Asim , Sharif Muhammad Imran , Akbar Shahzad , Sajid Muhammad Zaheer
Published: March 2024

Potato is a popular crop that is cultivated in many different climates. Potato farming has recently gained incredible traction, increasing relevance in international agricultural production. Potatoes are susceptible to several illnesses that stunt their development. This plant has significant leaf disease. Early blight (EB) and late blight (LB) are the two devastating leaf diseases for potato plants. The early detection of these diseases would be beneficial for enhancing the yield of this crop. The ideal solution is image processing to identify and analyze these disorders. Using image processing and machine learning, we detail a method that requires no outside help to detect late-blight potato leaf in this article. The pro- posed method comprises four different phases: (1) Histogram input images may improve from equalization to boost their overall quality; (2) feature extraction is performed using a Deep CNN model, then these extracted features are concatenated; (3) feature selection is performed using wrapper-based feature selection; (4) classification is performed using an SVM classifier and its variants. By utilizing SVM and a meticulously selected set of 550 characteristics, the suggested technique achieves an unprecedented 99% accuracy.
Evolution state prediction of step-like landslide based on an optimized intelligent model
Authors: Ma T. , WU Lizhou , Zhou J.T. , Zhang H.
Published: March 2024

Prediction of landslide evolution state is important for early warning system of landslides. The displacement curve of reservoir landslides has step-like characteristics. However, the mutation point of displacement curve is difficult to predict. An optimized machine learning model based on Extreme Gradient Boosting (XGBoost) and Bayesian method (Baye-XGB) is proposed to predict mutation points of displacement curve. The accuracy of models was testified by the Baishuihe landslide. Rainfall, reservoir water level and former displacement are taken as input parameters. K-means cluster was used to classify mutation points and regular points. XGBoost is used to predict evolution state, and the Bayesian method is applied to search hyperparameters. The results indicate that Baye-XGB is better than other models such as Support vector machine (SVM) and artificial neural network (ANN). The monthly displacement greater than 50mm is classified as a mutation point, the monthly displacement smaller than 50mm is classified as a regular point. The F1-score and AUC of the Baye-XGB are 0.95 and 0.99, respectively. The AUC score of Baye-XGB is improved by 17.86% compared with XGBoost_NoSmote, which means the SMOTE disposition can greatly improve the accuracy. Therefore, Baye-XGB can provide scientific guidelines for landslide earning waring.