bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social Media Guidelines for Young Plastic Surgeons and Plastic Surgery Training Programs
Authors: Hamilton Kristy L. , Kim Roy , Savetsky Ira L. , Avashia Yash J. , Maricevich Renata , Rohrich Rod J. 
Published: August 2021

Summary:
Social media are a powerful tool that creates a unique opportunity for the young plastic surgeon and trainee to share content, brand oneself, educate the public, and develop one’s own professional voice early. The majority of all plastic surgery programs and particularly those that are highly ranked have social media opportunities for their residents, yet clear rules to guide implementation of social media programming in residency have remained unspecified. These guidelines and pitfalls can be used to inform a productive and professional entry into plastic surgery social media use for the resident and young plastic surgeon. Details regarding specific platform use to maximize exposure are provided. The core principles of patient safety and privacy, authentic photography, plastic surgery education and advocacy, and professionalism inform these guidelines. Pitfalls include establishment of an online physician-patient relationship, engaging in debate by means of online reviews, providing medical entertainment, and engaging in non–plastic surgery politics. Use of these guidelines will allow the young plastic surgeon and trainee to succeed by means of social media platforms in an ethical and professional manner.
Bringing Your Idea to the Market: A Primer for Plastic Surgeons
Authors: Manolidis Spiros , Mentz James A. , Davis Matthew J. , Abu-Ghname Amjed , Chu Carrie K. , Buchanan Edward P. , Winocour Sebastian 
Published: August 2021

Summary:
The progress of biotechnology, medical instruments, and applied sciences contributes to a rapidly expanding space for the advancement of the medical field. Surgeons experience first-hand the limitations of current medical devices and thus have unique insight into problems that could be solved with new products. The process of turning an idea into a product capable of success in the marketplace, however, is often unfamiliar to surgeons. The authors seek to illuminate this process and provide an ordered list of tasks that can make bringing ideas to market more achievable for surgeons. The first step in this process is the generation and protection of a new idea. Next, the process of making an idea into a product is outlined. This phase involves team assembly, business planning, and product development. Market research and valuation are key to understanding how a product can be applied in the market, and meticulous research during this phase allows for informed decision-making that will help secure funding down the road. Finally, various options for financing are discussed and compared to help surgeon-entrepreneurs find an option that best fits their project, and steps to maximize leverage are described. The development of new products can be a complicated process for surgeons. Organized into four phases, with ordered instructional steps to advance through each phase, the process of bringing an idea to the market is clarified. Facilitating this process will possibly contribute to the continual improvement of medical and surgical abilities through the introduction of new devices and technologies.
Thumb Carpometacarpal Arthritis Surgery: The Patient Experience
Authors: Hawken Jessica B. , Yousaf Imran S. , Sanghavi Kavya K. , Higgins James P. , Giladi Aviram M. , Means Kenneth R. 
Published: August 2021

Background:
Patients with symptomatic recalcitrant thumb carpometacarpal arthritis often undergo surgery. Although most surgical patients do well, the authors anticipated that a substantial portion of their thumb carpometacarpal surgery patients would have unsatisfactory experiences and express unmet expectations, dissatisfaction, and regret, regardless of surgical procedure performed. The authors hypothesized those experiences would correlate with patient-reported outcomes scores.

Methods:
The authors identified patients who had undergone trapeziectomy alone or with ligament reconstruction 1 to 4 years previously for primary thumb carpometacarpal arthritis. One hundred twelve patients completed Quick Disabilities of the Arm, Shoulder and Hand and visual analogue scale pain, expectations, satisfaction, and regret questionnaires.

Results:
More than 40 percent of patients expected to “return to normal” after surgery for pain, strength, and/or function. Including all patients, 7, 19, and 11 percent had unmet expectations for improvement in pain, strength, and function, respectively. Twelve percent expressed dissatisfaction with their outcome. Although just 4 percent regretted undergoing surgery, 13 percent would likely not recommend the procedure to someone they care about. There were no statistically significant differences for any patient-reported outcomes between trapeziectomy-alone (n = 20) and trapeziectomy with ligament reconstruction (n = 92). Visual analogue scale and Quick Disabilities of the Arm, Shoulder and Hand questionnaire scores were both moderately correlated with expectations being met for pain, strength, and function and for satisfaction with surgical outcome.

Conclusions:
Patients’ thumb carpometacarpal surgical experiences vary considerably. Many express dissatisfaction or a lack of expectations met with the two most common procedures. A thorough understanding and review of expectations preoperatively may be uniquely pertinent for these patients. Further research should determine predictors and potentially modifiable factors for unsatisfactory outcomes.
Cerebral Perfusion Imaging for Intravenous Thrombolysis Treatment
Authors: Slawski, MD Diana E. , Albers, MD Gregory W. 
Published: August 2021

Abstract
Intravenous thrombolysis is the cornerstone of acute ischemic stroke treatment. However, the benefits of recanalization and reperfusion must be balanced against the risk of intracranial hemorrhage. Time from symptom onset was previously the most important selection tool for identifying patients who would benefit from treatment without prohibitive risk for secondary hemorrhage. Enhanced techniques in noncontrast computed tomography followed by computed tomography and magnetic resonance perfusion imaging led to the expansion of treatment eligibility for intravenous thrombolysis. Perfusion imaging allows for more precise evaluation of tissue at-risk to identify patients who would benefit from treatment many hours beyond symptom onset.
A New and Tidier Setting
Authors: Camino Julieta , Kishita Naoko , Trucco Ana P. , Khondoker Mizanur , Mioshi Eneida 
Published: August 2021

Background:
The relationship between the physical environment and the person with dementia’s (PwD) activities of daily living (ADLs) task performance is controversial. Although the general assumption is that this population benefits from their home environment when performing ADLs, very few experimental studies have been conducted to date.

Objectives:
The aim was to investigate the influence of the environment (home vs. Research-lab) and the role of clutter on ADL performance.

Methods:
Sixty-five PwD were evaluated with a performance-based ADL assessment (at home and clutter-free Research-lab). Paired t tests compared ADL performance and level of clutter in both environments. Multiple regression analysis investigated factors associated with better ADL performance.

Results:
Overall, PwD performed better at home even though clutter was significantly lower in the Research-lab. When stratified by dementia stage, PwD in the moderate stage of the disease performed better at home.

Conclusion:
Absence of clutter in the Research-Lab did not appear to play a beneficial role in ADLs. When stratified by dementia stage, only PwD in the moderate stage appeared to benefit from their home environment when performing ADL tasks. Future studies are required to elucidate the wider role of the environment in supporting engagement in daily activities in different dementia stages.
Outcome Measures for Dementia With Lewy Body Clinical Trials
Authors: Patel Bhavana , Irwin David J. , Kaufer Daniel , Boeve Bradley F. , Taylor Angela , Armstrong Melissa J. 
Published: August 2021

Background:
Dementia with Lewy bodies (DLB) is one of the most common degenerative dementias. Clinical trials for individuals with DLB are increasing. We aimed to identify commonly used outcome measures for trials in DLB.

Methods:
A pragmatic literature search of PubMed and clinicaltrials.gov identified interventional studies including populations with DLB. Studies were included if they enrolled participants with DLB and met the National Institutes of Health criteria for a clinical trial. Data were collected using standardized forms. Outcome measures were categorized according to core and supportive features of DLB.

Results:
After de-duplication, 58 trials were identified. The most common cognitive outcome measures were the Mini Mental State Examination (n=24) and Cognitive Drug Research computerized Assessment System (n=5). The Clinician’s Assessment of Fluctuations was the most commonly used measure for fluctuations (n=4). Over half of studies used the Neuropsychiatric Inventory to assess behavioral symptoms (n=31). The Unified Parkinson’s Disease Rating Scale was frequently used for motor assessment (n=23).

Conclusions and Relevance:
Clinical trial outcomes used in DLB are rarely validated in this population and some lack face validity. There is a need to validate existing scales in DLB and develop DLB-specific outcome measures.
Data-driven Discovery of Mathematical and Physical Relations in Oncology Data using Human-understandable Machine Learning
Authors: Kurz Daria , Sánchez Carlos Salort , Axenie Cristian 
Published: August 2021

ABSTRACTFor decades, researchers have used the concepts of rate of change and differential equations to model and forecast neoplastic processes. This expressive mathematical apparatus brought significant insights in oncology by describing the unregulated proliferation and host interactions of cancer cells, as well as their response to treatments. Now, these theories have been given a new life and found new applications. With the advent of routine cancer genome sequencing and the resulting abundance of data, oncology now builds an “arsenal” of new modeling and analysis tools. Models describing the governing physical laws of tumor-host-drug interactions can be now challenged with biological data to make predictions about cancer progression. Our study joins the efforts of the mathematical and computational oncology community by introducing a novel machine learning system for data-driven discovery of mathematical and physical relations in oncology. The system utilizes computational mechanisms such as competition, cooperation, and adaptation in neural networks to simultaneously learn the statistics and the governing relations between multiple clinical data covariates. Targeting an easy adoption in clinical oncology, the solutions of our system reveal human-understandable properties and features hidden in the data. As our experiments demonstrate, our system can describe nonlinear conservation laws in cancer kinetics and growth curves, symmetries in tumor’s phenotypic staging transitions, the pre-operative spatial tumor distribution, and up to the nonlinear intracellular and extracellular pharmacokinetics of neoadjuvant therapies. The primary goal of our work is to enhance or improve the mechanistic understanding of cancer dynamics by exploiting heterogeneous clinical data. We demonstrate through multiple instantiations that our system is extracting an accurate human-understandable representation of the underlying dynamics of physical interactions central to typical oncology problems. Our results and evaluation demonstrate that using simple - yet powerful - computational mechanisms, such a machine learning system can support clinical decision making. To this end, our system is a representative tool of the field of mathematical and computational oncology and offers a bridge between the data, the modeler, the data scientist, and the practising clinician.
The utility of a closed breeding colony of Peromyscus leucopus for dissecting complex traits
Authors: Long Phillip N , Cook Vanessa J , Majumder Arundhati , Barbour Alan G , Long Anthony D 
Published: August 2021

ABSTRACTAlthough Peromyscus leucopus (deermouse) is not considered a genetic model system, its genus is well suited for addressing several questions of biologist interest, including the genetic bases of longevity, behavior, physiology, adaptation, and it’s ability to serve as a disease vector. Here we explore a diversity outbred approach for dissecting complex traits in Peromyscus leucopus, a non-traditional genetic model system. We take advantage of a closed colony of deer-mice founded from 38 individuals between 1982 and 1985 and subsequently maintained for 35+ years (∼40-60 generations). From 405 low-pass (∼1X) short-read sequenced deermice we accurately imputed genotypes at 17,751,882 SNPs. Conditional on observed genotypes for a subset of 297 individuals, simulations were conducted in which a QTL contributes 5% to a complex trait under three different genetic models. The power of either a haplotype- or marker-based statistical test was estimated to be 15-25% to detect the hidden QTL. Although modest, this power estimate is consistent with that of DO/HS mice and rat experiments for an experiment with ∼300 individuals. This limitation in QTL detection is mostly associated with the stringent significance threshold required to hold the genome-wide false positive rate low, as in all cases we observe considerable linkage signal at the location of simulated QTL, suggesting a larger panel would exhibit greater power. For the subset of cases where a QTL was detected, localization ability appeared very desirable at ∼1-2Mb. We finally carried out a GWAS on a demonstration trait, bleeding time. No tests exceeded the threshold for genome-wide significance, but one of four suggestive regions co-localizes with Von Willebrand factor. Our work suggests that complex traits can be dissected in founders-unknown P. leucopus colony mice in much the same manner as founders-known DO/HS mice and rats, with genotypes obtained from low pass sequencing data. Our results further suggest that the DO/HS approach can be powerfully extended to any system in which a founders-unknown closed colony has been maintained for several dozen generations.
Diet-induced modifications to human microbiome reshape colonic homeostasis in irritable bowel syndrome
Authors: Pearl Ayelet , Bootz Hadar , Melzer Ehud , Sharon Efrat , Abuchatzera Shlomi , Amidror Sivan , Aretz Elana , Shoval Irit , Yaron Orly , Malnick Stephen , Yissachar Nissan 
Published: August 2021

AbstractChanges in microbiome composition have been associated with a wide array of human diseases, turning the human microbiota into an attractive target for therapeutic intervention. Yet clinical translation of these findings requires the establishment of causative connections between specific microbial taxa and their functional impact on host tissues. Here, we colonized gut organ cultures with longitudinal microbiota samples collected from newly-diagnosed and therapy-naïve irritable bowel syndrome (IBS) patients under low-FODMAP (fermentable Oligo-, Di-, Mono- saccharides and Polyols) diet. We show that post-diet microbiota regulates intestinal expression of inflammatory and neuro-muscular gene-sets. Specifically, we identify Bifidobacterium adolescentis as a diet-sensitive pathobiont that alters tight junction integrity and disrupts gut barrier functions. Collectively, we present a unique pathway discovery approach for mechanistic dissection and identification of functional diet-host-microbiota modules. Our data support the hypothesis that the gut microbiota mediates the beneficial effects of low-FODMAP diet, and reinforce the potential feasibility of microbiome based-therapies in IBS.
Multiple Channel Electrocardiogram QRS Detection by Temporal Pattern Search
Authors: Hopenfeld Bruce 
Published: August 2021

AbstractA highly constrained temporal pattern search (“TEPS”) based multiple channel heartbeat detector is described. TEPS generates sequences of peaks and statistically scores them according to: 1) peak time coherence across channels; 2) peak prominence; 3) temporal regularity; and 4) number of skipped beats. TEPS was tested on 31 records of three channel capacitive electrode data from the UnoViS automobile database. TEPS showed a sensitivity (SE) of 91.3% and a false discovery rate (FDR) of 3.0% compared to an SE and FDR of 75.3% and 65.0% respectively for a conventional single channel detector (OSEA) applied separately to the three channels. The peak matching window was 30ms. The percentage of 5 second segments with average heart rates within 5 beats/minute of reference was also measured. In 6 of the 31 records, TEPS’ percentage was at least 30% greater than OSEA’s. TEPS was also applied to synthetic data comprising a known signal corrupted with calibrated amounts of noise. At a fixed SE of 85%, increasing the number of channels from one to two resulted in an improvement of approximately 5dB in noise resistance, while increasing the number of channels from two to four resulted in an improvement of approximately 3dB in noise resistance. The quantification of noise resistance as a function of the number of channels could help guide the development of wearable electrocardiogram monitors.
Point set registration for assembly feature pose estimation using simulated annealing nested Gauss-Newton optimization
Authors: Chen Kunyong , Zhao Yong , Wang Jiaxiang , Xing Hongwen , Dong Zhengjian 
Published: August 2021

Purpose
This paper aims to propose a fast and robust 3D point set registration method for pose estimation of assembly features with few distinctive local features in the manufacturing process.

Design/methodology/approach
The distance between the two 3D objects is analytically approximated by the implicit representation of the target model. Specifically, the implicit B-spline surface is adopted as an interface to derive the distance metric. With the distance metric, the point set registration problem is formulated into an unconstrained nonlinear least-squares optimization problem. Simulated annealing nested Gauss-Newton method is designed to solve the non-convex problem. This integration of gradient-based optimization and heuristic searching strategy guarantees both global robustness and sufficient efficiency.

Findings
The proposed method improves the registration efficiency while maintaining high accuracy compared with several commonly used approaches. Convergence can be guaranteed even with critical initial poses or in partial overlapping conditions. The multiple flanges pose estimation experiment validates the effectiveness of the proposed method in real-world applications.

Originality/value
The proposed registration method is much more efficient because no feature estimation or point-wise correspondences update are performed. At each iteration of the Gauss–Newton optimization, the poses are updated in a singularity-free format without taking the derivatives of a bunch of scalar trigonometric functions. The advantage of the simulated annealing searching strategy is combined to improve global robustness. The implementation is relatively straightforward, which can be easily integrated to realize automatic pose estimation to guide the assembly process.
Application of the ANP in the interview phase of air traffic controller candidate selection process
Authors: Özdemir Mustafa , Sagir Mujgan 
Published: August 2021

Purpose
This paper investigates the interview examination applied during the admission process of air traffic controller (ATCO) candidates. This paper aims to select the most appropriate candidates by minimizing any shortcomings of the process.

Design/methodology/approach
ATCOs have a very important role in the air traffic system. They are responsible for ensuring the safe, regular and rapid flow of aircraft traffic. They carry out this challenging task by monitoring the aircraft under their responsibility and by giving instructions to the pilots when necessary. So the selection of ATCO candidates is of critical importance. This process is usually conducted through multistage examinations. It is a critical issue to use correct methods in the selection process to identify the most suitable candidates. Besides, the application of subjective examination in a standard way and standardization of criteria can assist in selecting the right candidates. Within this context, the analytic network process (ANP) and the rating method are used. The weights of the selection criteria are calculated by the ANP, and the candidates are evaluated by the rating method according to the defined criteria.

Findings
39 candidates were ranked using the ANP, and the rankings obtained by the ANP and the current system were compared. The ANP rankings were also compared with the results of a previous study conducted by analytic hierarchy process (AHP). The results indicate that using the ANP yields consistent results with those obtained from the AHP in terms of the rankings.

Research limitations/implications
ATCOs are one of the most important operators in air transport system. They undertake critical tasks where even a small error may cause serious consequences. Therefore, selecting the appropriate candidate is an important first step in training qualified staff. The authors believe that this study will contribute to the training of more qualified ATCOs. On the other hand, the approach about the use of ANP method on the interview examination and the standardization of the criteria can provide insight into improving interview process in different area.

Originality/value
To the best of the authors’ knowledge, this is the first study that presents an ANP-based methodology for the selection process of ATCOs and the interview process.
PSO and GA tuned conventional and fractional order PID controllers for quadrotor control
Authors: Saribas Hasan , Kahvecioglu Sinem 
Published: August 2021

Purpose
This study aims to compare the performance of the conventional and fractional order proportional-integral-derivative (PID and FOPID) controllers tuned with a particle swarm optimization (PSO) and genetic algorithm (GA) for quadrotor control.

Design/methodology/approach
In this study, the gains of the controllers were tuned using PSO and GA, which are included in the heuristic optimization methods. The tuning processes of the controller’s gains were formulated as optimization problems. While generating the objective functions (cost functions), four different decision criteria were considered separately: integrated summation error (ISE), integrated absolute error, integrated time absolute error and integrated time summation error (ITSE).

Findings
According to the simulation results and comparison tables that were created, FOPID controllers tuned with PSO performed better performances than PID controllers. In addition, the ITSE criterion returned better results in control of all axes except for altitude control when compared to the other cost functions. In the control of altitude with the PID controller, the ISE criterion showed better performance.

Originality/value
While a conventional PID controller has three parameters (Kp, Ki, Kd) that need to be tuned, FOPID controllers have two additional parameters (µ). The inclusion of these two extra parameters means more flexibility in the controller design but much more complexity for parameter tuning. This study reveals the potential and effectiveness of PSO and GA in tuning the controller despite the increased number of parameters and complexity.