Miracle-dz/UniFAR-FTUs huggingface dataset:
Online training module for micro suturing incorporating motor imagery and mental practice: a design and development research study

There have been reduced opportunities for surgical skill acquisition due to the COVID‐19 pandemic and the regulated training hours. Despite these challenges, self‐regulated learning allows trainees to learn continuously, and one form of this is through mental practice and motor imagery. The study aimed to design and develop an online basic micro suturing training module for skill acquisition for self‐regulated learning using a low‐fidelity rubber glove model.
Rejoinder to “Reader reaction to ‘Outcome‐adaptive Lasso: Variable selection for causal inference’ by Shortreed and Ertefaie (2017)”

We applaud Balde, Yand, and Lefebvre (BYL) for their useful contribution to the literature on variable selection in causal inference. The generalized outcome adaptive lasso (GOAL) provides an interesting addition to the outcome-adaptive Lasso (OAL) procedure, and the simulations presented within the work demonstrate several curious trends. Through implementing replication experiments, we have come to understand much more about the behavior of the OAL as well as its generalized analog (i.e., GOAL) under certain problematic scenarios. The simulations laid out by BYL demonstrated a clear advantage gained from the addition ofl2 penalization. The increased levels of bias suffered by OAL in these scenarios, and their subsequent remediation through the proposed method, sparked our curiosity. While there is little doubt that high levels of correlation may provide deleterious effects if not handled properly, the presence of such effects at relatively mild correlation levels was surprising. In this rejoinder, we demonstrate that these issues of bias may be explained by the presence of near-positivity violations which are a consequence of the correlation parameter. We give an interpretation that connects the additional ridge penalty to truncation, which provides a heuristic explanation for the observed behavior. Finally, we explore possible methods incorporating OAL or GOAL which are more robust to the positivity issue.
Human Papillomavirus Vaccine Impact and Effectiveness Through 12 Years After Vaccine Introduction in the United States, 2003 to 2018

BACKGROUND Human papillomavirus (HPV) vaccination was introduced in 2006 for females and in 2011 for males. OBJECTIVE To estimate vaccine impact and effectiveness against quadrivalent HPV vaccine (4vHPV)-type prevalent infection among sexually experienced U.S. females and vaccine effectiveness for sexually experienced U.S. males. DESIGN NHANES (National Health and Nutrition Examination Survey) conducted in 2003 to 2006 (prevaccine era) and in 2007 to 2010, 2011 to 2014, and 2015 to 2018 (vaccine eras). SETTING Nationally representative U.S. surveys. PARTICIPANTS Sexually experienced participants aged 14 to 24 years. INTERVENTION U.S. HPV vaccination program. MEASUREMENTS Participant-collected cervicovaginal and penile specimens were tested for HPV DNA. The prevalences of 4vHPV and non-4vHPV types were estimated in each era for females and in 2013 to 2016 for males. Prevalences among the female population overall, vaccinated females, and unvaccinated females were compared in vaccine eras versus the prevaccine era (vaccine impact). Within each vaccine era, prevalence among vaccinated females was compared with that among unvaccinated females (vaccine effectiveness). Vaccine impact and effectiveness were estimated as (1 - prevalence ratio) · 100. RESULTS Among sexually experienced females aged 14 to 24 years, the impact on 4vHPV-type prevalence in 2015 to 2018 was 85% overall, 90% among vaccinated females, and 74% among unvaccinated females. No significant declines were found in non-4vHPV-type prevalence. Vaccine effectiveness ranged from 60% to 84% during vaccine eras for females and was 51% during 2013 to 2016 for males. LIMITATION Self- or parent-reported vaccination history and small numbers in certain subgroups limited precision. CONCLUSION Nationally representative data show increasing impact of the vaccination program and herd protection. Vaccine effectiveness estimates will be increasingly affected by herd effects. PRIMARY FUNDING SOURCE Centers for Disease Control and Prevention.
Tingles down the spinal cord: A spinal functional magnetic resonance imaging investigation of the autonomous sensory meridian response

Autonomous sensory meridian response (ASMR) is a perceptual and emotional phenomenon in which specific sensory stimuli elicit a feeling of calm as well as tingling sensations on the scalp, neck, and shoulders. In the current study, we use fMRI to examine whether the motoric and sensory regions of the spinal cord segments associated with these body parts show increased activity during ASMR experiences. Nine individuals with ASMR completed six spinal functional magnetic resonance imaging runs while passively viewing videos. Three of the videos were shown (through pre-testing) to elicit ASMR tingles and three videos did not (i.e., control videos). The results demonstrated that ASMR-related stimuli elicited activity in dorsal (sensory) regions of spinal cord segments C1, C5, and C6; activity was observed in ventral (motoric) regions of segments C2–C8. Similar activity was not detected in response to control videos.
Half circular modified burr−III distribution, application with different estimation methods

The data related to many medical, environmental and ecological variables are often measured in terms of angles wherein its range is defined in [0,π). This type of data is referred to as axial or half circular data. Modeling based on half circular data has not received its due share of attention in statistical literature. In this paper, we introduce a new half circular distribution based on inverse stereographic projection technique on modified Burr−III distribution, called the half circular modified Burr−III (hcMB−III) distribution. The basic properties of the proposed distribution are derived. It is common observation that while estimating the parameters of a model, one usually adopts maximum likelihood estimation method as the starting point. In this paper, we consider seven frequentist methods of estimation, besides using maximum likelihood method for estimating the parameters of the hcMB−III distribution. Monte Carlo simulations are performed for investigating the performances of the considered methods in terms of their biases and mean square errors using small, medium and large sample sizes. Finally, one data set related to posterior corneal curvature of the eyes of 23 patients, is analyzed to check potentiality of the newly proposed model.
The Novel Amidase PcnH Initiates the Degradation of Phenazine-1-Carboxamide in Sphingomonas histidinilytica DS-9

Phenazines have been widely acknowledged as a natural antibiotic for more than 150 years, but their degradation mechanisms are still not completely elucidated. Compared with the studies on the degradation mechanism of PCA and PYO, little is known regarding PCN degradation by far. ABSTRACT Phenazines are an important class of secondary metabolites and are primarily named for their heterocyclic phenazine cores, including phenazine-1-carboxylic acid (PCA) and its derivatives, such as phenazine-1-carboxamide (PCN) and pyocyanin (PYO). Although several genes involved in the degradation of PCA and PYO have been reported so far, the genetic foundations of PCN degradation remain unknown. In this study, a PCN-degrading bacterial strain, Sphingomonas histidinilytica DS-9, was isolated. The gene pcnH, encoding a novel amidase responsible for the initial step of PCN degradation, was cloned by genome comparison and subsequent experimental validation. PcnH catalyzed the hydrolysis of the amide bond of PCN to produce PCA, which shared low identity (only 26 to 33%) with reported amidases. The Km and kcat values of PcnH for PCN were 33.22 ± 5.70 μM and 18.71 ± 0.52 s−1, respectively. PcnH has an Asp-Lys-Cys motif, which is conserved among amidases of the isochorismate hydrolase-like (IHL) superfamily. The replacement of Asp37, Lys128, and Cys163 with alanine in PcnH led to the complete loss of enzymatic activity. Furthermore, the genes pcaA1A2A3A4 and pcnD were found to encode PCA 1,2-dioxygenase and 1,2-dihydroxyphenazine (2OHPC) dioxygenase, which were responsible for the subsequent degradation steps of PCN. The PCN-degradative genes were highly conserved in some bacteria of the genus Sphingomonas, with slight variations in the sequence identities. IMPORTANCE Phenazines have been widely acknowledged as a natural antibiotic for more than 150 years, but their degradation mechanisms are still not completely elucidated. Compared with the studies on the degradation mechanism of PCA and PYO, little is known regarding PCN degradation by far. Previous studies have speculated that its initial degradation step may be catalyzed by an amidase, but no further studies have been conducted. This study identified a novel amidase, PcnH, that catalyzed the hydrolysis of PCN to PCA. In addition, the PCA 1,2-dioxygenase PcaA1A2A3A4 and 2OHPC dioxygenase PcnD were also found to be involved in the subsequent degradation steps of PCN in S. histidinilytica DS-9. And the genes responsible for PCN catabolism are highly conserved in some strains of Sphingomonas. These results deepen our understanding of the PCN degradation mechanism.
Role of Neighborhood Physical Disorder and Social Cohesion on Racial and Ethnic Disparities in Dementia Risk

Objectives: To analyze how neighborhood physical disorder and social cohesion are associated with racial and ethnic disparities in dementia risk. Methods: Nine years of data (2011–2019) were retrieved from the National Health and Aging Trends Study, a nationally representative U.S. older adult (age 65+) sample. Cox regression analyzed time to dementia diagnosis using composite scores for neighborhood physical disorder and social cohesion. Results: Higher baseline neighborhood physical disorder (Adjusted Hazard Ratio [aHR]=1.11, 95% Confidence Interval [CI]=1.01–1.23) and increased disorder at follow-up (aHR=1.10, 95% CI=1.01–1.19) significantly increased dementia risk. Hispanic older adults with higher physical disorder at baseline (aHR=0.62, 95% CI=0.49–0.79) and follow-up (aHR=0.81, 95% CI=0.67–0.98) had a significantly decreased dementia risk. There were no significant associations for social cohesion. Discussion: Physical but not social neighborhood characteristics are associated with dementia risk. Future research is needed to understand protective mechanisms for dementia among Hispanic older adults in neighborhoods with high physical disorder.
Proarrhythmic risk assessment of drugs by dV m /dt shapes using the convolutional neural network

Comprehensive in vitro Proarrhythmia Assay (CiPA) projects for assessing proarrhythmic drugs suggested a logistic regression model using qNet as the Torsades de Pointes (TdP) risk assessment biomarker, obtained from in silico simulation. However, using a single in silico feature, such as qNet, cannot reflect whole characteristics related to TdP in the entire action potential (AP) shape. Thus, this study proposed a deep convolutional neural network (CNN) model using differential action potential shapes to classify three proarrhythmic risk levels: high, intermediate, and low, considering both characteristics related to TdP not only in the depolarization phase but also the repolarization phase of AP shape. We performed an in silico simulation and got AP shapes with drug effects using half‐maximal inhibitory concentration and Hill coefficients of 28 drugs released by CiPA groups. Then, we trained the deep CNN model with the differential AP shapes of 12 drugs and tested it with those of 16 drugs. Our model had a better performance for classifying the proarrhythmic risk of drugs than the traditional logistic regression model using qNet. The classification accuracy was 98% for high‐risk level drugs, 94% for intermediate‐risk level drugs, and 89% for low‐risk level drugs.
A review of current advancements for wound healing: Biomaterial applications and medical devices

Abstract Wound healing is a complex process that is critical in restoring the skin's barrier function. This process can be interrupted by numerous diseases resulting in chronic wounds that represent a major medical burden. Such wounds fail to follow the stages of healing and are often complicated by a pro‐inflammatory milieu attributed to increased proteinases, hypoxia, and bacterial accumulation. The comprehensive treatment of chronic wounds is still regarded as a significant unmet medical need due to the complex symptoms caused by the metabolic disorder of the wound microenvironment. As a result, several advanced medical devices, such as wound dressings, wearable wound monitors, negative pressure wound therapy devices, and surgical sutures, have been developed to correct the chronic wound environment and achieve skin tissue regeneration. Most medical devices encompass a wide range of products containing natural (e.g., chitosan, keratin, casein, collagen, hyaluronic acid, alginate, and silk fibroin) and synthetic (e.g., polyvinyl alcohol, polyethylene glycol, poly[lactic‐co‐glycolic acid], polycaprolactone, polylactic acid) polymers, as well as bioactive molecules (e.g., chemical drugs, silver, growth factors, stem cells, and plant compounds). This review addresses these medical devices with a focus on biomaterials and applications, aiming to deliver a critical theoretical reference for further research on chronic wound healing.
Associations between prisons and recidivism: A nationwide longitudinal study

Objectives To examine differences in recidivism rates between different prisons using two designs—between-individual and within-individual—to account for confounding factors. Methods We examined recidivism rates among 37,891 individuals released from 44 Swedish prisons in three security levels, and who were followed from 2006 to 2013. We used longitudinal data from nationwide registers, including all convictions from district courts. First, we applied a between-individual design (Cox proportional hazards regression), comparing reconviction rates between individuals released from prisons within the same security level, while adjusting for a range of individual-level covariates. Second, we applied a within-individual design (stratified Cox proportional hazards regression), comparing rates of reconviction within the same individuals, i.e., we compared rates after release from one prison to the rates in the same individual after release from another prison, thus adjusting for all time-invariant confounders within each individual (e.g. genetics and early environment). We also adjusted for a range of time-varying individual-level covariates. Results Results showed differences in the hazard of recidivism between different prisons in between-individual analyses, with hazards ranging from 1.22 (1.05–1.43) to 4.99 (2.44–10.21). Results from within-individual analyses, which further adjusted for all time-invariant confounders, showed minimal differences between prisons, with hazards ranging from 0.95 (0.87–1.05) to 1.05 (0.95–1.16). Only small differences were found when violent and non-violent crimes were analyzed separately. Conclusions The study highlights the importance of research designs that more fully adjust for individual-level confounding factors to avoid over-interpretation of the variability in comparisons across prisons.
Integrated model for food-energy-water (FEW) nexus to study global sustainability: The main generalized global sustainability model (GGSM)

Over the years, several global models have been proposed to forecast global sustainability, provide a framework for sustainable policy-making, or to study sustainability across the FEW nexus. An integrated model is presented here with components like food-web ecosystem dynamics, microeconomics components, including energy producers and industries, and various socio-techno-economic policy dimensions. The model consists of 15 compartments representing a simplified ecological food-web set in a macroeconomic framework along with a rudimentary legal system. The food-web is modeled by Lotka–Volterra type expressions, whereas the economy is represented by a price-setting model wherein firms and human households attempt to maximize their economic well-being. The model development is done using global-scale data for stocks and flows of food, energy, and water, which were used to parameterize this model. Appropriate proportions for some of the ecological compartments like herbivores and carnivores are used to model those compartments. The modeling of the human compartment was carried out using historical data for the global mortality rate. Historical data were used to parameterize the model. Data for key variables like the human population, GDP growth, greenhouse gases like CO2 and NOX emissions were used to validate the model. The model was then used to make long-term forecasts and to study global sustainability over an extended time. The purpose of this study was to create a global model which can provide techno-socio-economic policy solutions for global sustainability. Further, scenario analysis was conducted for cases where the human population or human consumption increases rapidly to observe the impact on the sustainability of the planet over the next century. The results indicated that the planet can support increased population if the per capita consumption levels do not rise. However, increased consumption resulted in exhaustion of natural resources and increased the CO2 emissions by a multiple of 100.
Using partition analysis as a facile method to derive net clearances

Partition analysis has been described previously by W.W. Cleland to derive net rate constants and simplify the derivation of enzyme kinetic equations. Here, we show that partition analysis can be used to derive elimination and transfer (distribution) net clearances for use in pharmacokinetic models. For elimination clearances, the net clearance approach is exemplified with a mammillary two‐compartment model with peripheral elimination, and the established well‐stirred and full hepatic clearance models. The intrinsic hepatic clearance associated with an observed average hepatic clearance can be easily calculated with net clearances. Expressions for net transfer clearances are easily derived, including models with explicit membranes (e.g., monolayer permeability and blood–brain barrier models). Together, these approaches can be used to derive equations for physiologically based and hybrid compartmental/ physiologically based models. This tutorial describes how net clearances can be used to derive relationships for simple models as well as increasingly complex models, such as inclusion of active transport and target mediated processes.
Design of an environmentally aligned flood alleviation scheme: the Burn of Mosset, Moray, Scotland

Forres, Scotland, has a long history of flooding from the Burn of Mosset, and it was forecast that, without investment in flood risk management, flood damages were likely to exceed £43 million over the next 50 years. The decision was taken to implement a flood alleviation scheme (FAS) featuring an earth-fill dam upstream of Forres, capable of storing up to 3.8 million m of water and limiting peak discharges into the urban area to 8.5 m/s. It was recognised that sedimentand debris-related risks to the performance of the structure had to be managed and Burn Management Works were designed using cutting-edge river restoration techniques for channel rehabilitation and habitat creation to enhance the capacity of the flood basin to store sediment and debris. The FAS was opened on 28 August 2009 and the dam impounded flood water for the first time on 4 September 2009, avoiding approximately £9 million of flood damages to the town of Forres. The Burn Management Works have evolved mostly as expected, although some features have not functioned as intended, and lessons have been learnt concerning the need to allow for unexpected developments when using ‘prompted recovery’ in flood risk management and river rehabilitation.
Seven-Band Comb-Shaped Microstrip Antenna for Wireless Systems

This paper presents a very simple comb-shaped single layer microstrip patch antenna with seven operating bands for wireless systems. Eight symmetrical rectangular strips are connected by a single strip to achieve multiple operating bands. The proposed antenna provides maximum number of resonating bands compared to the antennas of its class. Effects of additional strips and the connecting strip on the antenna characteristics are studied. A prototype of the antenna is fabricated for experimental validation. The measured reflection coefficient (S11) and radiation patterns are in good agreement with their simulated counterpart. Measured result shows that the proposed antenna can operate at seven different frequency bands 1.56–1.64 GHz, 1.76–1.94 GHz, 3.62–3.74 GHz, 4.43– 4.48 GHz, 5.02–5.13 GHz, 5.48–5.62 GHz and 5.92–6.02 GHz. These bands cover some of the most useful bands for wireless systems such as GPS (1570.42–1580.42 MHz), DCS-1800 (1710–1880 MHz), PCS-1900 (1850–1990 MHz), WiMAX and WLAN.
Integrated interface electronics for capacitive MEMS inertial sensors

OF DOCTORAL DISSERTATION AALTO UNIVERSITY SCHOOL OF SCIENCE AND TECHNOLOGY P.O. BOX 11000, FI-00076 AALTO http://www.aalto. fi Author Lasse Aaltonen Name of the dissertation Manuscript submitted May 3, 2010 Manuscript revised August 30, 2010 Date of the defence October 29, 2010 Article dissertation (summary + original articles) Monograph Faculty Department Field of research Opponent(s) Supervisor Instructor Abstract