bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevention of Cytomegalovirus Retinitis-Related Retinal Detachment by Prophylactic Argon Laser Demarcation in patients with AIDS in Myanmar
Authors: Hassman Lynn M. , Oo Khin Thida , Larochelle Marissa , Din Zaw Minn , Tun NiNi , Vitale Albert T. , Heiden David 
Published: March 2022

Abstract
Background: Cytomegalovirus retinitis (CMVR) is the primary cause of AIDS-related blindness and remains a substantial cause of blindness in resource-limited settings. Retinal detachment (RD) occurs in approximately 1/3 of patients with CMV retinitis. There is limited capacity to treat retinal detachment in resource-limited settings, and retinal detachment commonly results in permanent profound vision loss. Prophylactic argon laser demarcation was widely used in the pre-HAART era in high income countries, and we here describe our experience with this safe, low-cost intervention to prevent blindness from CMV retinitis-related retinal detachment in a resource-limited setting, in the current era where effective antiretroviral therapy is available. Methods: A non-randomized retrospective observational cohort study was conducted over 4 years in patients on cART (combined antiretroviral therapy) and with inactive AIDS-related CMVR involving at least 25% of the retina, and who were treated with prophylactic argon laser demarcation (LD). The main outcomes were retinal detachment and loss of vision.Results: In a 45 eyes from 38 patients with inactive CMVR on cART for HIV/AIDS who underwent prophylactic laser demarcation, there were no retinal detachments and no loss of vision.Conclusion: In this series of patients at risk for CMVR-related retinal detachment who were treated with prophylactic laser demarcation, retinal detachment was prevented and visual acuity was maintained. Prophylactic argon laser demarcation is a safe, effective, and a realistically affordable intervention to reduce blindness in patients with AIDS-related CMV retinitis.
Multiphasic liquid flow as a universal tool for nanofabrication of diverse polymer morphologies
Authors: Bang Rachel , Roh Sangchul , Williams Austin , Stoyanov Simeon , Velev Orlin 
Published: March 2022

Abstract
Soft matter of synthetic and biological origin find application in a range of consumer products such as rheological modifiers, structural adhesion enhancers, nonwovens, and membranes1. The functionality of materials typically derives from their nano- and microscale structure and overall morphology1-3. Many fabrication techniques are capable of producing morphologies including particles4, fibers4,5, and membranes6,7. Yet, these techniques may be limited in producing a few specific morphologies and in fine-tuning nano- or microscopic features. Many are also resource and energy-intensive, restricting their potential as commercial processes8. Here, we explore interfacial polymer precipitation within sheared multiphasic systems. Through systematic investigation of critical processing parameters, we observe the fabrication of twelve unique polymer morphologies. We verify that the liquid shear-based technique is versatile and works well with chemically diverse polymers, showing potential as a universal tool for fabricating many morphologically distinct polymer structures by simple, scalable processes.
Surgical Treatments for Post-amputation Pain: Study Protocol for an International, Double-blind, Randomised Controlled Trial
Authors: Pettersen Emily , Sassu Paolo , Reinholdt Carina , Dahm Peter , Rolfson Ola , Björkman Anders , Innocenti Marco , Ortiz-Catalan Max 
Published: March 2022

Abstract
Background: Painful conditions such as neuroma pain, stump pain, and phantom limb pain (PLP) can manifest after amputation and are termed generally as post-amputation pain. The mechanisms underlying post-amputation pain are diverse and should be addressed accordingly. Different surgical treatment methods have shown potential for alleviating neuroma pain and at lesser degree stump pain and PLP. Two reconstructive surgical interventions, namely Targeted Muscle Reinnervation (TMR) and Regenerative Peripheral Nerve Interface (RPNI), are gaining popularity in post-amputation pain treatment with promising results. However, these two methods have not been directly compared in a randomised controlled trial (RCT). Here, we present a study protocol for a double-blind RCT to assess the effectiveness of TMR, RPNI, and a non-reconstructive procedure called neuroma transposition as an active control in alleviating neuroma pain, stump pain, and PLP. Methods: Seventy-five upper and lower limb amputees suffering from post-amputation pain, are recruited, and randomly assigned to one of the surgical interventions (TMR, RPNI, or neuroma transposition) in an equal allocation ratio. Complete evaluations are performed during a baseline period prior to the surgical intervention and follow-ups are conducted in short-term (one-, three-, six-, and twelve-months post-surgery) and in long-term (three- and five-years post-surgery). After the twelve-months follow-up, the study is unblinded for the evaluator and the participants. If the participant is unsatisfied with the outcome to treatment at that time, further treatment including one of the other procedures will be discussed in consultation with the clinical investigator.Discussion: A double-blind RCT is necessary for the establishment of evidence-based procedures, hence the motivation for this work. In addition, studies on pain are challenging due to the subjectivity of the experience and the lack of objective evaluation methods. Here, we mitigate this problem by including several different pain evaluation methods known to have clinical relevance. We decided to analyse the results using an adherence to protocol approach (per-protocol, PP), as this is more suitable than intention-to-treat (ITT) in pain studies with long-term follow-ups. This is because patients often experience initial pain relief post-surgery, but over time, gradually returns to pre-surgical levels. This could lead to misinterpretation of the clinical reality. We will instead report the actual values of pain and number of participants in each follow-up. Trial registration: ClincialTrials.gov, NCT05009394.
Prediction Of Postoperative Pulmonary Complications Using Clinical Data And Machine Learning
Authors: Avval Atlas Haddadi , Pourkeshavarz Mozhgan , Sadeghi Hasan Allah , Mostafaei Shayan , Chamani Faraz , Fathollahi Mahmood Sheikh , Sadeghi Sarina , Mirdamadi Mahsa , Maleki Majid , Shiri Isaac , Oveisi Mehrdad 
Published: March 2022

Abstract
In this study, we aimed to predict postoperative pulmonary complications (PPC) with the help of machine learning (ML) in cardiac operations.We prospectively gathered the preoperative and intraoperative data of 918 patients (random split: n=745 and n=173), who were candidates for elective cardiac surgeries. Patients were observed for any pulmonary complications 24, 48, and 72 hours after the surgery. Feature selection, univariate, and multivariate analysis were performed using an ML algorithm. We obtained the p-value and AUC with 95% CI for each feature and then all features together. We also utilized a Bayesian Network (BN) classifier.Among the 16 selected features, 12 features showed a significant effect on PPC prediction in the testing dataset (p<0.05). Peak expiratory flow rate was the most predictive feature (AUC = 0.75) in the testing dataset. Multivariate analysis showed that our features are highly robust in training (p-value<0.001, AUC=0.73) and testing (p-value=0.002, AUC=0.70) datasets. BN classifier showed that type of surgery, opium usage, renal dysfunction, and history of chronic obstructive pulmonary diseases have the highest conditional probability with the occurrence of PPC.In conclusion, a combination of preoperative and postoperative features in patients can be used to predict PPCs in patients undergoing cardiac surgeries.
Calorimetry of a Quantum Phase Slip
Authors: Gümüs Efe , Majidi Danial , Nikolic Danilo , Raif Patrick , Karimi Bayan , Peltonen Joonas , Scheer Elke , Pekola Jukka , Courtois Hervé , Belzig Wolfgang , Winkelmann Clemens 
Published: March 2022

Abstract
In a Josephson junction, which is the central element in superconducting quantum technology, irreversibility arises from abrupt slips of the gauge-invariant quantum phase difference across the contact. A quantum phase slip (QPS) is often visualized as the tunneling of a flux quantum in the transverse direction to the superconducting weak link, which produces dissipation. Here, we detect the instantaneous heat release caused by a QPS in a Josephson junction using time-resolved electron thermometry on a nanocalorimeter, signaled by an abrupt increase of the local electronic temperature in the weak link and subsequent relaxation back to equilibrium. Beyond providing a cornerstone in experimental quantum thermodynamics in form of observation of heat in an elementary quantum process, this result sets the ground for experimentally addressing the ubiquity of dissipation, including that in superconducting quantum sensors and qubits.
A population antibody response against SARS-CoV-2 with differential neutralization activities towards the Delta and Omicron variants
Authors: Xiong Xiaoli , He Ping , Liu Banghui , Gao Xijie , Yan Qihong , Pei Rongjuan , Sun Jing , Chen Qiuluan , Hou Ruitian , Li Zimu , Zhang Yanjun , Zhao Jincun , Sun Hao , Feng Bo , Wang Qian , Yi Haisu , Hu Peiyu , Li Pingchao , Chen Zhilong , Niu Xuefeng , Zhong Xiaolin , Jin Liang , Liu Xiaofeng , Qu Kun , Ciazynska Katarzyna , Carter Andrew , Briggs John , Chen Jizheng , Liu Jinsong , He Jun , Chen Xinwen , Chen Ling 
Published: March 2022

Abstract
Population antibody response is believed to be important in selection of new variant viruses. We identified that SARS-CoV-2 infections elicit a population immune response mediated by a lineage of VH1-69 germline antibodies. The representative antibody R1-32 targets a novel semi-cryptic epitope defining a new class of RBD targeting antibodies. Binding to this non-ACE2 competing epitope leading to spike destruction impairing virus entry. Based on epitope location, neutralization mechanism and analysis of antibody binding to spike variants we propose that recurrent substitutions at 452 and 490 are associated with immune evasion of this population antibody response. These substitutions, including L452R found in the Delta variant, disrupt interaction mediated by the VH1-69 specific hydrophobic HCDR2 to impair antibody-antigen association allowing variants to escape. Lacking 452/490 substitutions, the Omicron variant is sensitive to this class of antibodies. Our results provide new insights into SARS-CoV-2 variant genesis and immune evasion.
Prevention of Customer Churn Due To Issuance of Real-Time Coupons Based on Deep Learning
Authors: Seo Daeho , Choi Soobin , Yoo Yongmin 
Published: March 2022

Abstract
With the development of big data and deep learning technology, big data and deep learning technology have also been applied to the marketing field, which was a part of business administration. Customer churn management is one of the most important areas of marketing. In this paper, we proposed a method to prevent customer churn and increase purchase conversion rate by issuing customized discount coupons to customers with high churn rate based on big data in real time. In this paper, we proposed a method to prevent customer cancellation and increase purchase conversion rate by issuing customized discount coupons to customers with high cancellation rates in real time based on big data. After segmenting customer segments with two-dimensional segment analysis, a real-time churn rate estimation model based on clickstream data was generated for each segment. After that, we issued customized coupons to our customers. Finally, we tested the conversion rate and sales growth. A two-dimensional cluster analysis-based churn rate estimation combined with a recommendation system was found to be significantly more useful than the respective simple models. Using this proposed model, it is possible to increase sales by automatically estimating the customer’s cancellation probability and shopping propensity without the burden of marketing costs in the online shopping mall.
Study on high temperature fracture mechanism of tunnel surrounding rock considering heterogeneity of TC and CTE
Authors: LI Wei , Chen Wenhua 
Published: March 2022

Abstract
The entrance section of the high-speed railway tunnel in southern China has been in a state of high temperature for a long time and is subject to alternating temperature changes. The surrounding rock is heterogeneous characteristics. Under a large temperature difference environment, temperature stress will occur between mineral particles and mineral particles. When the temperature stress is greater than the tensile strength of the surrounding rock, it will cause the rock to crack. In order to analyze the mechanism of the tunnel surrounding rock crack disease:(1)Based on thermoelastic mechanics and Weibull distribution, considering heterogeneous of the coefficient of thermal expansion(CTE) of mineral cells, an improved hightemperature initiation mechanical model of heterogeneous rock is established.(2)Aiming at the heterogeneous of thermal conductivity(TC) of mineral cells, the Agari series-parallel model is introduced to improve the thermal conductivity of the model.(3)By changing the degree of heterogeneous of CTE and TC, considering the joint action of the local temperature gradient of the rock, the macroscopic and mesoscopic laws of the initiation mechanism of rock are studied.(4)Analyze the maximum principal stress and crack initiation temperature regions of sandstone and granite through engineering calculation examples. The results show that with the continuous increase of temperature load, the internal stress of the rock continues to increase. Under the action of temperature load, the peak strength of the rock increases with the increase of the rock homogeneity coefficient. Local
Effect Of Orbital Volume In Unilateral Orbital Fracture On Traumatic Optic Neuropathy
Authors: Senarak Wirapha , Yongvikul Atapol , Ku Jeong-Kui , Kim Jae-Young , Huh Jong-Ki 
Published: March 2022

Abstract
Purpose: This retrospective study aimed to analyze the relationship between the volume of the fractured and the normal orbit in patients with unilateral orbital fractures with and without traumatic optic neuropathy (TON).Subjects: Data of 25 patients with unilateral orbital fractures who underwent computer tomography between January 2016 and December 2020 were investigated. Emergency imaging was performed within 2 h of arrival at the emergency room. The subjects were categorized into two groups: unilateral orbital fractures with and without TON. Methods and Measures: The assessment of TON was performed during a comprehensive ophthalmologic examination by an ophthalmologist. The stereographic orbit was reconstructed and the volume was calculated. Other variables examined included age, sex, and cause of orbital trauma. The variables were compared using paired t-tests. Statistical significance was set at p < 0.05.Results: The orbital volume of the non-fractured orbit was 27.50 ± 2.26 and 27.48 ± 2.64 cm3 in the groups with and without TON, respectively. The average volume of the fractured orbit in the TON group was 27.78 ± 2.56 cm3, and there was no significant volumetric difference between the fractured and non-fractured sides in this group. However, the average volume of the fractured orbit without TON was 28.76 ± 3.18 cm3, larger than that of the non-fractured orbit (p=0.016).Conclusions: Non-expansion of the fractured orbit was a risk factor for indirect TON in patients with unilateral orbital fractures. Volumetric analysis from primary imaging would expedite the diagnosis and treatment of TON, resulting in optimal outcomes.
An Augmented Certificateless Signcryption Model with Rapid Elliptic Curve Cryptosystem for IIoT-Cloud Data Security
Authors: VENKATESAN S. , RAJESHWARI K. RAJA , RAMAKRISHNAN M. 
Published: March 2022

Abstract
Industrial Internet of Things (IIoT) is an advanced version of IoT that actuates the sensors for monitoring and controlling the devices of industrial systems. Cloud is also one of the most popular platform used for enabling the industrial data storage and retrieval operations. But, providing security to this environment is highly demanding and essential for ensuring the privacy and confidentiality of industrial data against the malicious users. Hence, many cryptographic based security models are developed in the conventional works, which intends to securely share and retrieve data in an encrypted form by using the private and public key par. Still, it facing the major problems of high computational cost, complexity, and time consumption for processing the operations. Thus, this paper intends to develop a new IIoT-cloud framework for ensuring the security industrial data by using the certificateless signcryption mechanism. For this purpose, an Augmented Certificateless Signcryption Model (ACSM) incorporated with the Rapid Elliptic Curve Cryptosystem (RECC) is developed in this work, which objects to enhance the security of IIoT-cloud systems with reduced computational cost and time consumption. Also, it helps to avoid the key escrow problem with the ensured security properties of confidentiality, integrity, authentication, and unforgeability. For validating the performance of this mechanism, various evaluation metrics have been utilized, and also the obtained results are compared with the recent state-of-the-art models.
Ponderosa Pine Introduction Methods Following a Stand Replacing Wildfire in the Laramie Mountains of Wyoming
Authors: Winters Stephanie , Diepen Linda T.A. van 
Published: March 2022

Abstract
Background
In July 2012, a lightning strike started the Arapaho Fire in the Laramie Mountains of Wyoming burning approximately 39,700 ha. Ponderosa pine (Pinus ponderosa P. & C. Lawson) mortality due to the high-severity fire was 95% at the University of Wyoming’s Rogers Research Site. Ponderosa pine recruitment post high-severity wildfire is limited in semi-arid and mid-elevation forests in the Rocky Mountain region due to reduction of seed supplies from living trees, warm temperatures, and limited precipitation. Wildfire intensity and frequency is predicted to increase with climate change and ponderosa pine forests are incredibly susceptible to this dramatic shift. The purpose of this research was to determine the best restoration treatments for ponderosa pine regeneration and seedling survival in a Wyoming ponderosa pine forest post high-severity fire.
Results
Our results indicate that the pine introduction treatment ‘planted seedlings’ was the most effective restoration treatment in semi-arid, mid-elevation sites, although overall survival rates of seedlings were very low from initial planting numbers. None of logging methods resulted in improved survival of pine seedling or higher regeneration. The estimated mean percent moss cover was higher in the ‘no logging’ logging method and resulted in a lower mean percent bare ground. Overall, two years after implementation of the restoration treatments did not result in different vegetation communities.
Conclusions
Potential reasons for the lack of restoration effects on vegetation community variables at the Rogers Research Station are likely the large landscape heterogeneity with differing slopes and aspects coupled with the short time frame (2 years) since implementation of the restoration treatments at the site. Further research is needed to determine if restoration treatments will have greater impact on ponderosa pine survival and regeneration in the midterm (6–10) years post implementation. This research is applicable for national, state, and local land managers to implement impactful restoration practices post-wildfire.
Recommendations for Maternal Mortality Review Committees in the United States: A content analysis
Authors: Shahi Anamika , Holzer Jessica , Londhe Shilpa 
Published: March 2022

Abstract
Background: Every year up to 700 mothers die in the United States due to pregnancy complications; at least two-thirds of these deaths are preventable. Despite the presence of state-level Maternal Mortality Review Committees (MMRCs), mortality rates have remained stagnant or increased in many places. Implementing best practices to improve MMRCs may help identify and address the causes of maternal mortality that may be preventable.Methods: We conducted a content analysis of evidence-based recommendations to improve MMRCs. Using a search of PubMed, we restricted our analysis to full-text papers published in English from 2010-2021 that included recommendations. Reviewer 1 (R1) analyzed the initial set of papers and removed any that did not meet the inclusion criteria. R1 coded the recommendations into categories. Reviewer 2 (R2) coded them separately. R1 and R2 then agreed to a common codebook and re-coded all papers for relevant themes.Results: Out of 322 articles identified in PubMed, 16 articles met the inclusion criteria. The articles all acknowledged gaps in current MMRC practice and policies. Recommendations included ensuring representative and diverse committee representation, improving data quality and standardization, and performing in-depth review of cases of maternal death to look for social determinants of health. Several other themes arose regarding funding, support for, and review practices of MMRCs.Conclusion: This is the first study to collect evidence-based recommendations to improve MMRC effectiveness. We offer next steps and best practices to policymakers and MMRCs at a time when reducing maternal mortality rates is a national priority.
Technological shocks and its influence on renewable energy consumption-green growth: Do financial institutions mitigate some environmental burden?
Authors: Chao Tan , Yunbao Xu , Chengbo Dai , Bo Li , Usman Ahmed 
Published: March 2022

Abstract
Technology innovations and financial development are the tools to achieve sustainable development goals (SDGs) in the carbon neutrality process; however, such nexus has lacked evidence, particularly in top-polluting economies countries. The current study examines the effectiveness of technological innovation and financial institutions on renewable energy consumption and green growth in top-polluting economies by using the cross-sectional Autoregressive Distributive Lag (CS-ARDL) method over the period from 1991 to 2019. The findings show that in the long-run, technological progress and financial institutions are major drivers of renewable energy consumption of top-polluting economies. Moreover, the study shows that technological progress, financial institutions, education, and public spending foster green growth in top-polluting economies in long-run. Top-polluting economies need to improve energy technology innovation and financial institutions for achieving green growth and carbon neutrality targets.