bluuebunny/crossref_metadata_2025_split huggingface dataset:
MHD flow of generalized Casson fluid with radiation and porosity under the effects of chemical reaction and arbitrary shear stress
Authors: Sehra Sehra , Sadia Haleema , Haq Sami Ul , Khan Ilyas 
Published: October 2022

Abstract
This recent research article is presented to describe the mass and heat transference in a non-Newtonian Casson fluid, flowing in a medium having porosity. The magnetic-hydrodynamic and exponential heating effects are considered during the fluid flow. The effects of radiation and molecular diffusivity i.e. chemical reaction are investigated with slip boundary condition and exponential heating. The stated problem is patterned by three partial differential equations of classical order with suitable initial and boundary conditions. The component equations of the problem are converted into a non-dimension form by introducing some suitable dimensionless parameters. The partial differential equations PDE’s of classical order are converted into non-integer order by using the non-integer order derivative proposed by Michele Caputo and Mauro Fabrizio. The technique of Laplace transform is used for obtaining the problem’s solutions. Obtained solutions are graphically represented to observe the effects of different parameters on velocity, mass and temperature during fluid flow. The software MathCAD is used for the visualization of the effects.
Constrained large-eddy simulation of laminar-turbulent transition in compressible channel flow
Authors: Chen Sanmu , Wan Minping , Jiang Zhou , Chen Shiyi 
Published: October 2022

Abstract
An improved constrained large-eddy simulations (CLES) for wall-bonded compressible transitional flows is proposed by introducing an intermittency factor. The improved model is tested and validated with a compressible channel flow that is transitioning from laminar to turbulent states. The improved model is
compared against traditional dynamics Smagorinsky model (DSM) and Direct Numerical Simulations (DNS), where the improved model is in better agreement with DNS results than traditional DSM model, in terms of mean velocity profiles, total Reynolds stress and total heat flux. Therefore, the proposed method can be
used to accurately predict the laminar-turbulent transition process of compressible wall-bounded flows.
Challenge of creating an inferior alveolar nerve block device that allows for safe, secure, and successful performance by any operator: Non-clinical studies on models
Authors: Noguchi Tomoyasu , Odaka Kento , Fukuda Ken-ichi 
Published: October 2022

Abstract
Purpose
Inferior alveolar nerve block (IANB) is a useful nerve block in dental practice, but its success rate remains limited. This is largely attributed to operator and anatomical factors. There are some dentists who do not choose IANB owing to complications. Therefore, we conducted a pilot study that aimed to create an IANB device that allows for safe, secure, and successful performance by any operator.
Methods
In this study, three types of IANB devices were created for a skull model as a pilot study for clinical applications. They were designed with the dentition as a fixed point, and mandibular foramen as a target point. The dentition and jawbone were converted into data using an intraoral scanner and computed tomography imaging, respectively. A device was designed from the obtained data and output using a 3D printer. We verified the production time, material usage, and accuracy, and discussed the potential for clinical applications.
Results
The average time required for printing was 201 minutes. The average amount of biocompatible resin and support material used was 36 g and 52.3 g, respectively. The error between the actual needle tip position of the completed device and the needle tip position at the time of design was 0.63 mm on average.
Conclusion
IANB device created in this study requires more time and has higher costs than conventional IANB; however, it has sufficient accuracy for clinical applications, and potential for a safe and secure IANB that can be conducted by any operator can be expected.
DFGR: Diversity and Fairness Awareness of Group Recommendation in an Event-based Social Network
Authors: Liang Yuan 
Published: October 2022

Abstract
An event-based social network (EBSN) is a new type of social network that combines online and offline networks, and one of its important problems is recommending suitable activities to users. However, the current research seldom considers balancing the accuracy, diversity and fairness of group activity recommendations. To solve this problem, we first compute activity similarity based on context and construct an activity similarity matrix and an activity similarity graph, and define a weighted coverage on the maximum similarity graph. Second, we propose a greedy algorithm that achieves an approximate ratio, and propose a new index to evaluate the fairness of a recommendation list S to group g. Finally, we conduct experiments on real datasets, and the experimental results show that the proposed method can better balance the accuracy, diversity and fairness of recommendations than the existing methods.
Reinforcement learning to help intensivists optimize mechanical ventilation settings (EZ-Vent): Derivation and validation using large databases
Authors: Liu Siqi , Xu Zhuoyang , Liu Zhuo , Sun Xingzhi , Xie Guotong , Feng Mengling , See Kay Choong 
Published: October 2022

Abstract
Background
Mechanical ventilation is the cornerstone of critical care medicine. However, choosing the optimal ventilator strategy for a patient remains imprecise. Existing guidelines provide one-size-fits-all recommendations, but do not personalize treatments for different intensive care unit (ICU) patients. In this study, we aimed to design and evaluate an artificial intelligence (AI) solution that could tailor an optimal ventilator strategy for each critically ill patient who requires mechanical ventilation.
Methods
We proposed a reinforcement learning-based AI solution using observational data from multiple ICUs in the US. The primary outcome was hospital mortality. Secondary outcomes were the proportion of optimal oxygen saturation and the proportion of optimal mean arterial blood pressure. We trained our AI agent to learn each patients’ treatment trajectory and thus to recommend low/medium/high levels of three ventilator settings, namely the positive end-expiratory pressure, fraction of inspired oxygen and ideal body weight-adjusted tidal volume. Off-policy evaluation metrics were applied to evaluate the AI policy.
Results
We studied 5105 and 21595 patients’ ICU stays from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC-IV) and eICU Collaborative Research (eICU) databases respectively. Observed hospital mortality rates were 18.2% (eICU) and 31.1% (MIMIC-IV). For the learnt AI policy, we estimated the hospital mortality rate (eICU 14.7\(\pm\)0.7%; MIMIC-IV 29.1\(\pm\)0.9%), proportion of optimal oxygen saturation (eICU 57.8\(\pm\)1.0%; MIMIC-IV 49.0\(\pm\)1.0%), and proportion of optimal mean arterial blood pressure (eICU 34.7 \(\pm\) 1.0%; MIMIC-IV 41.2\(\pm\)1.0%). Based on multiple quantitative and qualitative evaluation metrics, our proposed AI solution has potential to outperform observed clinical practice.
Conclusions
Our proposed approach has potential to be applied as a clinical decision support tool that helps intensivists make better treatment decisions and to improve the survival and prognosis of critically ill patients who require invasive respiratory support.
Visualizing field-effects and chemical passivation in efficient 2D/3D heterojunction perovskite solar cells and modules
Authors: Yang Weichuang , Ding Bin , Yang Zhenhai , Lin Zedong , Sun Jingsong , Meng YuanYuan , Sheng Jiang , Ding Yong , Ye Jichun , Dyson Paul , Nazeeruddin MOHAMMAD KHAJA 
Published: October 2022

Abstract
The full potential of perovskite solar cells (PSCs) is limited by charge-carrier recombination, due to the imperfect passivation methods. Here, interfacial recombination loss of field-effect and chemical passivation mechanisms is quantified. It was found that a favorable alignment of energy levels can provide very good field-effects to reduce minority carriers, and suppresses interfacial recombination losses more effectively than chemical passivation. To obtain high-efficiency PSCs, two-dimensional (2D) perovskites are promising candidates, which offer powerful field-effects and only require modest chemical passivation at the interface. Owing to promoted passivation and charge-carrier extraction, the power conversion efficiency of a 2D/3D heterojunction PSC was boosted to 25.32% (certified 25.04%) for small-size devices and to 21.48% for a large-area module (with a designated area of 29.0 cm2). Ion migration is also suppressed by the 2D/3D heterojunction so that the unencapsulated small-size devices maintain 90% of the initial efficiency after 2000 h of continuous operation at the maximum power point.
A study on the suitability of 3D printed models to analyse sounds of the whistling arrows
Authors: COBAN Recep Efe , AKAN Mertcan 
Published: October 2022

Abstract
Whistling arrows are military equipment that can make a whistling sound through their whistles, which are usually made of horns or bone. Surprisingly, this highly intriguing weapon is one of the least studied subjects in the medieval archery legacy. The reason for this might be that the whistling arrows are very difficult to manufacture and test. On the other hand, using 3D printers has by researchers to test and analyse archaeological artifacts nowadays. Likewise, the affordable prices of 3D printers and the manufacturing speed of the models are also increasing these studies. In this context, our article aims to test the hypothesis of using 3D models produced by 3D printers to overcome the difficulties in producing whistling arrows. Three different whistle types dating to the Turk Khaganate period were selected to use in the tests, and ten 3D whistle models were printed out following these typologies. All whistles were tested in the prepared test setup and their sounds were recorded and analysed.
The secure judgment of graphic similarity against malicious adversaries
Authors: Liu Xin , Xu Yang , Xu Gang , Chen Xiu-Bo 
Published: October 2022

Abstract
With the the advent era of big data, the secure computation calculates data on the premise of protecting data privacy, to realize the availability and invisibility of data. Secure multi-party computation, as one of three major technical tools of privacy computing, can still securely carry out data collaborative computation without a trusted third party. As an important branch of secure multi-party computation, the secure computing geometric problem can solve practical problems in the military, national defense, finance, life, and other fields, which has important research significance. In this paper, the graphic similarity problem is studied. Firstly, this paper proposes the adjacency matrix vector coding method of isomorphic graphics and uses the Paillier variant cryptosystem to securely solve the graphic similarity judgment under the semi-honest model. By using an elliptic curve cryptosystem and zero-knowledge proof to solve the possible malicious attacks under the semi-honest model, a graphic similarity judgment protocol under the malicious model is designed. The protocol can resist malicious attacks, has high computational efficiency, and has wide application value.
Collaborative 360° Virtual Reality training of medical students in clinical examinations
Authors: Davidsen Jacob Gorm , Larsen Dorthe Vinter , Rasmussen Sten , Paulsen Lucas 
Published: October 2022

Abstract
Simulation-based training in computer-generated environments has always played an important role in clinical medical education. Recently, there has been a growing interest in using 360° videos of real-life situations for training in health professions. Several studies report positive results from using 360° Virtual Reality for individuals, however, there are no studies on collaborative 360° Virtual Reality training. In this paper, we study how 360° Virtual Reality can support collaborative training in clinical medical education. 14 medical students from a 5th -semester medical bachelor’s program participated. In three groups, the students watched and annotated a 360° video of an authentic learning situation inside a collaborative immersive virtual reality space. The video shows a problem-based supervised examination of the knee collateral ligaments and the cruciate ligaments performed by students. Afterwards, the students should perform the test in a physical examination. The performance of the students has afterwards been evaluated by a professor with expertise in knee examinations. The results show that 12 out of 14 students gets a score of 2 on one or more test and thereby reaches the required learning objective. One student receives a score of 1 and one student does not perform any of the tests. The students use the tools provided by the software and different communicative strategies when working collaboratively in 360° Virtual Reality, which enables them to perform the tests in the physical examination. These results indicate that our pedagogical design in collaborative immersive 360° Virtual Reality can become a relevant addition to face-to-face clinical medical training.
Exhaled Patient Derived Aerosol Dispersion during Awake Tracheal Intubation with Concurrent High Flow Nasal Therapy
Authors: Eain Marc Mac Giolla , Nolan Kevin , Murphy Brian , McCaul Conan , MacLoughlin Ronan 
Published: October 2022

Abstract
Purpose
Awake Tracheal Intubation (ATI) can be performed in cases where there is potential for difficult airway management. It is considered an aerosol generating procedure and is a source of concern to healthcare workers due to the risk of transmission of airborne viral infections, such as SARS–CoV-2. At present, there is a lack of data on the quantities, size distributions and spread of aerosol particles generated during such procedures.
Methods
This was a volunteer observational study which took place in an operating room of a university teaching hospital. Optical particle sizers were used to provide real time aerosol characterisation during a simulated ATI performed with concurrent high-flow nasal oxygen therapy. The particle sizers were positioned at locations that represented the different locations of clinical staff in an operating room during an ATI.
Results
The greatest concentration of patient derived aerosol particles was within 0.5–1.0 m of the subject and along their midline, 2242 #/cm3. As the distance, both radial and longitudinal, from the subject increased, the concentration decreased towards ambient levels, 36.92 ± 5.12 #/cm3. Patient derived aerosol particles < 5µm in diameter remained entrained in the exhaled aerosol plume and fell to the floor or onto the subject. Patient derived particles > 5µm in diameter broke away from the exhaled plume and spread radially throughout the operating room.
Conclusions
Irrespective of distance and ventilation status, full airborne protective equipment should be worn by all staff when ATI is being performed on patients with suspected viral respiratory infections.
Learning phenotypic patterns in genetic diseases by symptom interaction modeling
Authors: Thevenon Julien , Yauy Kevin , Duforet-Frebourg Nicolas , Testard Quentin , Beaumeunier Sacha , Audoux Jerome , Simard Benoit , Larue DImitri , Blum Michael , Bernard VIrginie , Geneviève David , Bertrand Denis , Philippe Nicolas 
Published: October 2022

Abstract
Observing phenotyping practices from an international cohort of 1,686 cases revealed heterogeneity of phenotype reporting among clinicians. Heterogeneity limited their exploitation for diagnosis as only 43% of symptom-gene associations in the cohort were available in public databases. We developed a symptom interaction model that summarized 16,600 terms into 390 groups of interacting symptoms and detected 3,222,053 novel symptom-gene associations. By learning phenotypic patterns in genetic diseases, symptom interaction modeling handled heterogeneity in phenotyping, to the extent of covering 99.8% of our cohort’s symptom-gene associations. Using these symptom interactions improved the diagnostic performance in gene prioritization by 42% (median rank 80 to 41) compared to the best algorithms. Symptom interaction modeling will provide new discoveries in precision medicine by standardizing clinical descriptions.
Should diverticulitis be considered a qualifying weight related comorbidity for bariatric surgery?
Authors: LaRocque Justin D. , Russell Dylan M. , Nguyen Scott H. , Yheulon Christopher G. 
Published: October 2022

Abstract
Introduction: With rising obesity rates, surgeons are operating on increasingly larger patients. Minimally invasive surgery has helped ease this burden on surgeons. However, we are still quantifying the impact of weight on surgical outcomes. The purpose of this study is to determine the role of obesity in elective laparoscopic colectomy for colonic diverticulitis.
Methods: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) and colectomy targeted procedure databases were queried from 2012-2019, examining patients undergoing elective, minimally invasive partial colectomy with or without primary anastomosis for an indication of diverticulitis. Patients with a BMI under 30 (non-obese) were compared to patients with a BMI between 35-40 (obese). The groups were propensity score matched for pre-operative and intra-operative variables.
Results: 2,217 patients were identified with 1,954 non-obese patients and 263 obese patients. The groups’ average BMIs were 25.3 ± 3 and 37.1 ± 1.5, respectively. There were no significant differences between the two groups after a 2:1 propensity score match. In obese patients, there were higher rates of conversion to open (11.49% vs 7.09%, p =0.038), operative time (178.5 vs 167.0 minutes, p = 0.044), and readmission (7.28% vs 3.64%, p = 0.025). The leak rate was 4.98% for obese patients vs. 2.68% for non-obese patients, though this was not statistically significant (p=0.097).
Conclusion: Obese patients undergoing elective laparoscopic colectomies for diverticulitis suffer from increased rates of conversion to open, operative time, and readmission. Diverticulitis should be strongly considered for inclusion as a qualifying weight related comorbidity for bariatric surgery as significant weight loss prior to diverticulitis surgery improves outcomes.
Efficient Targeted Delivery of Bifunctional Circular Aptamer ASO Chimera to Suppress the SARS-CoV-2 Proliferation and Inflammation
Authors: Yang Gang , Zhang Shengnan , Song William , Bai Xia , Li Ling , Luo Fatao , Cheng Yiran , Wang Diyue , Zhao Jincun , Zhao Yongyun 
Published: October 2022

Abstract
Inhibition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and excessive inflammation is the current task in the prevention and treatment of COVID-19. Here, we designed a dual-function circular aptamerASO chimera (circSApt-NASO) to suppress SARS-CoV-2 replication and inflammation. The chemically unmodified circSApt-NASO exhibited high serum stability by artificial cyclization, significantly enhancing the utility of oligonucleotides. It presents great efficiency in knocking down, demonstrating the superiority of the circular ASO as a novel tool for sequence-specific silencing of gene expression. Furthermore, we propose and demonstrate that the SApt binding to spike protein enables the chimera to be efficiently delivered into the susceptible host cells expressing ACE2 along with the infection of SARS-CoV-2. At high concentrations of SARS-CoV-2, the efficiency of targeted delivery of circSApt-NASO can even be compared to transfection. Among them, the anti-spike aptamer (SApt) that blocks the Spike-TLR4 interaction potently inhibits spike-induced inflammation. The NASO targeting to silence N genes not only display robust anti-N-induced inflammatory activity, but also achieve efficient inhibition of SARS-CoV-2 replication. Therefore, benefiting from the high stability of the cyclization, anti-spike aptamer-dependent and viral infection-mediate targeted delivery, the circSApt-NASO displays robust potential against authentic SARS-CoV-2 and Omicron (B.1.1.529), providing a promising specific anti-inflammatory and anti-proliferative reagent for therapeutic COVID-19 based on the oligonucleotide therapeutics strategy.
FoxO6-mediated TXNIP induces hepatic steatosis through NLRP3 inflammasome activation in vivo and in vitro
Authors: Kim Mi Eun , Lee Jun Sik , Kim Dae Hyun 
Published: October 2022

Abstract
Background
We showed that the activation of the nucleotide-binding oligomerization domain-like receptor pyrin domain-containing-3 (NLRP3) inflammasome by the forkhead box O6 (FoxO6) transcription factor through binding of the thioredoxin-interacting protein (TXNIP) under inflammatory conditions might lead to hepatic steatosis. Although the role of the FoxO6 in mediating lipid accumulation and the chronic inflammatory process underlying the pathophysiology of hepatic steatosis are well explored, the precise mechanisms of the involvement of FoxO6 have not fully been delineated to date.
Methods
NLRP3 inflammasome and lipogenesis were monitored in mice overexpressed with constitutively active (CA)-FoxO6 allele, and FoxO6-null mice. In vitro study, liver cells overexpressing CA-FoxO6 were treated with palmitate, and then alterations in lipid metabolism were measured.
Results
The focus of our investigation was to apply palmitate treatment to elucidate the mechanisms underlying the role of FoxO6 in the activation of the cytokine IL-1β through the NLRP3 inflammasome. Initial experiments revealed that palmitate-induced FoxO6 activity was caused by its dephosphorylation, which induced its transcriptional activity. Further palmitate experiments showed increased expression of IL-1β and the hepatic NLRP3 inflammasome complex, including adapter protein ASC, and pro-caspase-1. Furthermore, TXNIP, a key regulator of cellular redox state in the upstream NLRP3 inflammasome, was induced by FoxO6 in liver and HepG2 cells.
Conclusion
The main contribution of the current study is the identification of FoxO6 as a key signaling element upstream of TXNIP in the regulation of the hepatic NLRP3 inflammasome of the molecular mechanisms involved in hepatic lipogenesis.
Comparing long-term energy pathways in Vietnam: a cost-optimization approach with OSeMOSYS
Authors: Tan Naomi , Harrison John , Howells Mark 
Published: October 2022

Abstract
Vietnam is at a critical juncture in planning for its future energy mix due to its fast-growing economy and recent climate commitments. Focusing on Vietnam’s energy system, this study incorporates a cost-optimization tool to investigate the impact of different policy decisions, resulting in a series of six different energy scenarios. The six scenarios include: (i) Power Development Plan VII (revised); (ii) Power Development Plan VIII (draft); (iii) Renewable Energy Development Strategy; (iv) Renewables-Led Pathway; (v) Net Zero; and (vi) Clean Energy Transition. Based on these cases, main insights are highlighted, with the aim of providing key stakeholders in energy policy strong modelling analysis on potential and practical energy mix alternatives over the next 20–30 years. Thus, modelling suggests that a fossil fuel phase-out and uptake of renewable technologies will allow Vietnam to achieve its climate commitments, whilst providing energy security within the nation. Additionally, adopting sustainable biomass will support the transition to net zero, and energy-efficient technologies will lower costs and emissions. This study also concludes the key findings with recommendations on achieving the optimal pathway for the development of Vietnam’s energy sector.