Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification statistics of the Montreal Cognitive Assessment (MoCA): Are we interpreting the MoCA correctly?

Abstract Objective The Montreal Cognitive Assessment (MoCA) is a common cognitive screener for detecting mild cognitive impairment (MCI). However, previously suggested cutoff scores of 26/30 and above is often criticized and lacks racial diversity. The purpose of this study is to investigate the potential influence of race on MoCA classification cutoff score accuracy. Method Data were obtained from the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set and yielded 4,758 total participants. Participants were predominately White (82.8%) and female (61.7%) with a mean age of 69.3 years (SD = 10.3) and education level of 16.3 years (SD = 2.6). Based on NACC’s classification, participants were either cognitively normal (n = 3,650) or MCI (n = 1,108). Results Sensitivity and specificity analyses revealed that when using the cutoff score of ≤26/30, the MoCA correctly classified 73.2% of White cognitively normal participants and 83.1% of White MCI participants. In contrast, this criterion correctly classified 40.5% of Black cognitively normal participants and 90.8% of Black MCI participants. Our sample was highly educated; therefore, we did not observe significant differences in scores when accounting for education across race. Classification statistics are presented. Conclusions Black participants were misclassified at a higher rate than White participants when applying the ≤26/30 cutoff score. We suggest cutoff scores of ≤25/30 be applied to White persons and ≤22/30 for Black persons. These findings highlight the need for racially stratified population-based norms given the high misclassification of Black participants without such adjustment.
Material Characterization of 3D-Printed Energy-Absorbent Polymers Inspired by Nature

In nature there is a wealth of mineral-based and protein-based bio-composites spe- cially designed to resist impact and crushing. Some examples are enamel, dentin, horn, hoof and bone among others which are exhibiting unique reinforcing and toughening mechanisms that allow them to withstand large impact- and compressive loads [1]. Such bio-composites feature complex multi-scale and hierarchical struc- tures with several levels and types of reinforcements, density/stiffness gradients and porous phases that act in synergy to efficiently absorb the impact energy [70]. These multiscale architectures/concepts will be utilized to aid the designing of lighter, safer and tailored helmet liners for cyclists, motorcyclists and athletes. This means moving from the conventional EPS foams used nowadays as liner material, to a customized architecture with a liner based on the rider’s skull. But also the head morphology/physiology and impact resistance/absorption requirements mimicking architectures found in nature. The effectiveness of such structures is an example of concepts inspired by nature that can be used to realize more customized/purpose-built and energy absorbing architectures, a process called biomimicry. For centuries, designers and architects have been looking to nature for inspiration for the best source of inspiration with its 3.85 billion years of evolution [42]. Today, the tailored density gradient, nature’s ability to rearrange its structure as well as the self-healing property found in e.g. bones is not achievable using any conventional manufacturing, therefore additive manufacturing is the way forward for solving the tailored density gradient problem. In additive manufacturing or 3D-printing, three-dimensional objects/components are manufactured by deposition of materials in a layer-by-layer fashion. The layer thickness and path are controlled by computer models. Such a manufacturing ap- proach has received rather large global attention the last few years. The reason is that very complex objects can be built which are difficult or impossible to create using conventional, subtractive manufacturing methods. This new way of manufac- turing can produce highly customizable components with minimal material waste. Considering the high complexity of the aforementioned bio-composite structures and the vast capabilities of additive manufacturing, it is foreseen that the combina- tion would enable the realization of complicated 3D-printed architectures capable of withstanding impact and crushing inspired by the long-proven strategies found in living organisms and animals.
Modeling Emergency Managers’ Hurricane Evacuation Decisions

Emergency management and decision support system (EMDSS) tools play an important role in assisting emergency managers with making important decisions about the movement of people to safety when a jurisdiction is threatened by a storm. One of the important components of an EMDSS is an evacuation demand model that predicts whether and when households will evacuate when they are threatened by a storm. A critical input to that model is an emergency manager's decision to issue an evacuation notice. No existing mathematical models predict whether and when an emergency manager will issue an evacuation notice on the basis of a hurricane forecast and other contextual factors. To fill this gap, this research study sought to develop a model that would predict if and when an emergency manager would issue an evacuation notice when a jurisdiction was threatened by a storm. Data from poststorm assessment surveys and newspaper archives were used to retrieve past decisions made by evacuation managers for five storms in 45 coastal counties or parishes. The data were then used to develop a discrete choice model by use of the time-dependent sequential logit paradigm. Five independent predictor variables—storm surge, clearance time, time to landfall, hurricane category, and time of day—were found to be good predictors of the decisions made by emergency managers. This model could be useful to emergency managers to estimate how other emergency managers decide to evacuate an area when they are faced with an evacuation decision. The model could also benefit researchers and practitioners engaged in modeling and understanding hurricane evacuation behavior.
Asthma, chronic obstructive pulmonary disease, and asthma-COPD overlap among US working adults

Abstract Background Asthma-COPD overlap (ACO) is a respiratory condition with more severe respiratory symptoms, poorer quality of life, and increased hospital admissions compared with asthma or COPD alone. Objectives Estimate asthma, chronic obstructive pulmonary disease (COPD), and ACO prevalence among workers by industry and occupation and assess physical and mental health status, healthcare utilization, among workers with ACO. Methods The 2014–2018 National Health Interview Survey (NHIS) data for working adults aged ≥18 years employed (sample n = 99,424) in the 12 months prior to the survey were analyzed. Age-adjusted ACO, COPD and asthma prevalence and prevalence ratios adjusted for age, sex, race and smoking status were estimated. Results During 2014–2018, of the estimated 166 million (annual average) US workers, age-adjusted asthma, COPD, and ACO prevalence was 6.9%, 4.0%, and 1.1%, respectively. ACO prevalence was highest among workers aged ≥65 years (2.0%), females (1.6%), current smokers (1.9%), those living below the federal poverty level (2.3%), and workers in the accommodation and food services (1.6%) industry and personal care and service (2.3%) occupations. Workers with ACO had more frequent (p < 0.05) physician office visits, emergency department visits; and were more likely to be in poorer mental health, obese, have more lost workdays, more bed days, and comorbidities compared to workers with asthma alone and workers with COPD alone. Conclusion: Higher ACO prevalence among worker groups and increased healthcare utilization underscores the need for early identification of asthma and COPD, assessment of potential workplace exposures, and implementation of tailored interventions to reduce ACO among working adults.
A Bayesian Approach to Change Point Estimation in Multivariate SPC

A Bayesian procedure is developed to estimate the time of a change in the process mean vector for a multivariate process, given that an out-of-control signal was raised on a multivariate control chart. In addition, we can infer simultaneously which variable(s) had a change in mean value, when the change occurred, and the value of the changed mean. All three problems (inferring change point time, variables that shifted, and new values for the shifted variables) are addressed in a single statistical model. Markov chain Monte Carlo (MCMC) methods, through the software WinBUGS, are used to estimate parameters of the change point models. To identify the mean shift in a process with more than two variables, we propose a branch-and-bound search algorithm so that MCMC can be carried out with a predictable computing time in each search step. A simulation study shows that the Bayesian approach has similar performance compared to the maximum likelihood estimation (MLE) in terms of identifying the true change point location when a noninformative prior is assumed; however, it can perform better when proper prior knowledge is incorporated into the estimation procedure. The Bayesian approach provides full posterior distributions for the model and change point, which can contain information that is not available in a likelihood analysis.
Ultra Fast Deep Lane Detection with Hybrid Anchor Driven Ordinal Classification

Modern methods mainly regard lane detection as a problem of pixel-wise segmentation, which is struggling to address the problems of efficiency and challenging scenarios like severe occlusions and extreme lighting conditions. Inspired by human perception, the recognition of lanes under severe occlusions and extreme lighting conditions is mainly based on contextual and global information. Motivated by this observation, we propose a novel, simple, yet effective formulation aiming at ultra fast speed and the problem of challenging scenarios. Specifically, we treat the process of lane detection as an anchor-driven ordinal classification problem using global features. First, we represent lanes with sparse coordinates on a series of hybrid (row and column) anchors. With the help of the anchor-driven representation, we then reformulate the lane detection task as an ordinal classification problem to get the coordinates of lanes. Our method could significantly reduce the computational cost with the anchor-driven representation. Using the large receptive field property of the ordinal classification formulation, we could also handle challenging scenarios. Extensive experiments on four lane detection datasets show that our method could achieve state-of-the-art performance in terms of both speed and accuracy. A lightweight version could even achieve 300+ frames per second(FPS). Our code is at https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2.
Bayesian Comorbidity Network and Cost Analysis for Asthma

The evolving disease spectrum poses significant challenges to the asthma management, thus worsening health quality and increased financial burden on patients. However, potential dependency pattern in comorbidity spectrum remains unclear. We built comorbidity networks based on Bayesian networks utilizing 19604 asthma-patient hospitalization data to investigate dependency patterns among asthma comorbidities. We analyze static properties and trajectory behaviors of gender- and age-stratified asthmatic comorbidity networks. Results suggest that chronic obstructive pulmonary disease, respiratory failure, hypertension, atherosclerosis, and gastritis and duodenitis are the hubs of the asthma comorbidity network. They have a strong dependency pattern, while most of the associations among other comorbidities are sparse and weak. The strength of association between comorbidities is higher in female asthmatics than in males. Although the comorbidity network in children with asthma is simple and stable, the onset of common comorbidities as they age will enhance the association between comorbidities and thus increase the risk of developing other comorbidities. Furthermore, the more attributes of comorbidities, the stronger association with each other, and the greater risk of causing high treatment costs. Our study will help to dissect the asthma co-morbidity network and provide a basis for improving asthma management and cost control.
[2+3] Amide Cages by Oxidation of [2+3] Imine Cages – Revisiting Molecular Hosts for Highly Efficient Nitrate Binding

Abstract The pollution of groundwater with nitrate is a serious issue because nitrate can cause several diseases such as methemoglobinemia or cancer. Therefore, selective removal of nitrate by efficient binding to supramolecular hosts is highly desired. Here we describe how to make [2+3] amide cages in very high to quantitative yields by applying an optimized Pinnick oxidation protocol for the conversion of corresponding imine cages. By NMR titration experiments of the eight different [2+3] amide cages with nitrate, chloride and hydrogen sulfate we identified one cage with an unprecedented high selectivity towards nitrate binding vs. chloride (S=705) or hydrogensulfate (S>13500) in CD2Cl2/CD3CN (1 : 3). NMR experiments as well as single‐crystal structure comparison of host‐guest complexes give insight into structure‐property‐relationships.
Elektrotechnik und Informatik SMS-based One-Time Passwords : Attacks and Defense

SMS-based One-Time Passwords (SMS OTP) were introduced to counter phishing and other attacks against Internet services such as online banking. Today, SMS OTPs are commonly used for authentication and authorization for many different applications. Recently, SMS OTPs have come under heavy attack, especially by smartphone trojans. In this paper, we analyze the security architecture of SMS OTP systems and study attacks that pose a threat to Internet-based authentication and authorization services. We determined that the two foundations SMS OTP is built on, cellular networks and mobile handsets, were completely different at the time when SMS OTP was designed and introduced. Throughout this work, we show why SMS OTP systems cannot be considered secure anymore. Based on our findings, we propose mechanisms to secure SMS OTPs against common attacks and specifically against smartphone trojans.
Pain, Analgesic Use, and Patient Satisfaction With Spinal Versus General Anesthesia for Hip Fracture Surgery : A Randomized Clinical Trial.

BACKGROUND The REGAIN (Regional versus General Anesthesia for Promoting Independence after Hip Fracture) trial found similar ambulation and survival at 60 days with spinal versus general anesthesia for hip fracture surgery. Trial outcomes evaluating pain, prescription analgesic use, and patient satisfaction have not yet been reported. OBJECTIVE To compare pain, analgesic use, and satisfaction after hip fracture surgery with spinal versus general anesthesia. DESIGN Preplanned secondary analysis of a pragmatic randomized trial. (ClinicalTrials.gov: NCT02507505). SETTING 46 U.S. and Canadian hospitals. PARTICIPANTS Patients aged 50 years or older undergoing hip fracture surgery. INTERVENTION Spinal or general anesthesia. MEASUREMENTS Pain on postoperative days 1 through 3; 60-, 180-, and 365-day pain and prescription analgesic use; and satisfaction with care. RESULTS A total of 1600 patients were enrolled. The average age was 78 years, and 77% were women. A total of 73.5% (1050 of 1428) of patients reported severe pain during the first 24 hours after surgery. Worst pain over the first 24 hours after surgery was greater with spinal anesthesia (rated from 0 [no pain] to 10 [worst pain imaginable]; mean difference, 0.40 [95% CI, 0.12 to 0.68]). Pain did not differ across groups at other time points. Prescription analgesic use at 60 days occurred in 25% (141 of 563) and 18.8% (108 of 574) of patients assigned to spinal and general anesthesia, respectively (relative risk, 1.33 [CI, 1.06 to 1.65]). Satisfaction was similar across groups. LIMITATION Missing outcome data and multiple outcomes assessed. CONCLUSION Severe pain is common after hip fracture. Spinal anesthesia was associated with more pain in the first 24 hours after surgery and more prescription analgesic use at 60 days compared with general anesthesia. PRIMARY FUNDING SOURCE Patient-Centered Outcomes Research Institute.
Tools and targets: The dual role of plant viruses in CRISPR–Cas genome editing

The recent emergence of tools based on the clustered, regularly interspaced, short palindromic repeats (CRISPR) and CRISPR‐associated (Cas) proteins have revolutionized targeted genome editing, thus holding great promise to both basic plant science and precision crop breeding. Conventional approaches for the delivery of editing components rely on transformation technologies or transient delivery to protoplasts, both of which are time‐consuming, laborious, and can raise legal concerns. Alternatively, plant RNA viruses can be used as transient delivery vectors of CRISPR–Cas reaction components, following the so‐called virus‐induced genome editing (VIGE). During the last years, researchers have been able to engineer viral vectors for the delivery of CRISPR guide RNAs and Cas nucleases. Considering that each viral vector is limited to its molecular biology properties and a specific host range, here we review recent advances for improving the VIGE toolbox with a special focus on strategies to achieve tissue‐culture‐free editing in plants. We also explore the utility of CRISPR–Cas technology to enhance biotic resistance with a special focus on plant virus diseases. This can be achieved by either targeting the viral genome or modifying essential host susceptibility genes that mediate in the infection process. Finally, we discuss the challenges and potential that VIGE holds in future breeding technologies.
Transcatheter Aortic Valve Implantation With and Without Resheathing and Repositioning: A Systematic Review and Meta‐analysis

Background There is a concern that resheathing/repositioning of transcatheter heart valves during transcatheter aortic valve implantation (TAVI) may lead to an increased risk of periprocedural complications. We aimed to evaluate the short‐ and long‐term impact on clinical outcomes of resheathing for repositioning of transcatheter heart valves during TAVI procedures. Methods and Results We conducted a systematic search of Embase, MEDLINE, and Cochrane Central Register of Controlled Trials databases to identify studies comparing outcomes between patients requiring resheathing/repositioning during TAVI and those who did not. Random‐effects meta‐analyses were used to estimate the association of resheathing compared with no resheathing with clinical outcomes after TAVI. Seven studies including 4501 participants (pooled mean age, 80.9±7.4 years; 54% women; and 1374 [30.5%] patients requiring resheathing/repositioning) were included in this study. No significant differences between the 2 groups were identified with regards to safety: 30‐day mortality (n=3125; odds ratio [OR], 0.74 [95% confidence interval [CI], 0.41–1.33]; I 2=0%), stroke (n=4121; OR, 1.09 [95% CI, 0.74–1.62]; I 2=0%), coronary obstruction (n=3000; OR, 2.35 [95% CI, 0.17–33.47]; I 2=75%), major vascular complications (n=3125; OR, 0.92 [95% CI, 0.66–1.33]; I 2=0%), major bleeding (n=3125; OR, 1.13 [95% CI, 0.94–2.01]; I 2=39%), acute kidney injury (n=3495; OR, 1.30 [95% CI, 0.64–2.62]; I 2=44%), and efficacy outcomes: device success (n=1196; OR, 0.77 [95% CI, 0.51–1.14]; I 2=0%), need for a second valve (n=3170; OR, 2.86 [95% CI, 0.96–8.48]; I 2=62%), significant (moderate or higher) paravalvular leak (n=1151; OR, 1.53 [95% CI, 0.83–2.80]; I 2=0%), and permanent pacemaker implantation (n=1908; OR, 1.04 [95% CI, 0.68–1.57]; I 2=58%). One‐year mortality was similar between groups (n=1972; OR, 1.00 [95% CI, 0.68–1.47]; I 2=0%). Conclusions Resheathing of transcatheter heart valves during TAVI is associated with similar periprocedural risk compared with no resheathing in several patient‐important outcomes. These data support the safety of current self‐expanding transcatheter heart valves with resheathing features. Registration URL: https://www.crd. york.ac. uk/prospero/; Unique identifier: CRD42021273715.
Leisure Activities and Depressive Symptoms among Older Men and Women in Mexico: Implications of Physical Health

Objectives This study investigated whether the effects of specific types of group and individual leisure activities on depressive symptoms differ for older men and women in Mexico and whether several indicators of physical health can shape the psychological benefits of these activities. Methods This study used data from two waves (2012 and 2015) of the Mexican Health and Aging Study and employed OLS regressions. Results The association between leisure activities and depressive symptoms among older Mexicans may vary by the type of activity, gender, and physical health. Physical health issues may decrease potential psychological benefits of certain leisure activities. Yet, despite deteriorating physical health, older adults may benefit from involvement in some leisure activities. Discussion This study highlights the diversity of experiences related to later-life mental health and emphasizes the importance of investigating psychological implications of specific types of leisure activities among older men and women with different physical health concerns.
60 GHZ microstrip antenna for remote vital sign monitoring in automobile applications

A microstrip patch antenna (MPA) has been presented for Remote Vital Sign Monitoring (RVSM) at 60GHz frequency band for ambulance and automobile applications. RVSM measurements have been carried out by using Doppler radar principle with the help of two identical MPAs. The measured and simulation results in case of the both fabricated antennas agreed well. Respiration and heart beat rates of a 31 years old man have been successfully measured within the lab environment from 50cm distance. Matlab programming is employed for signal processing purpose. The measured breathing rate (BR) and heart beat rate (HR) showed good agreement with the BR and HR values obtained by both the conventional counting techniques and Fingertip Pulse Oximeter. The RVSM results obtained at 60GHz frequency band are then compared with the results obtained at 10GHz frequency with the similar antennas to evaluate the improvement in the detection sensitivity and it has been found that the 60GHz Doppler radar is 1.8 and 11.5 times more sensitive to the BR and HR signals, respectively.
Gene editing in porcine embryos using a combination of electroporation and transfection methods.

CRISPR/Cas9 technology is growing rapidly and greatly influences the efficiency and effectiveness of genetic modifications in different applications. One aspect of research gaining importance in the development of the CRISPR/Cas9 system is the introduction of CRISPR materials into target organisms. Although we previously demonstrated the efficacy of electroporation- and lipofection-mediated CRISPR/Cas9 gene disruption in porcine zygotes, we still believe that the efficiency of this system could be improved by combining these two methods. The present study was thus conducted to clarify the effects of a combination of electroporation and lipofection for delivering CRISPR/Cas9 components into zona pellucida (ZP)-intact and -free zygotes. The results revealed that electroporation alone significantly increased the biallelic mutation rates in the resulting blastocysts compared to lipofection alone, irrespective of the presence of ZP. None of ZP-intact zygotes treated by lipofectamine alone had any mutations, suggesting that removal of the ZP is necessary for enabling CRISPR/Cas9 based genome editing via lipofection treatment in the zygotes. Additional lipofectamine treatment after electroporation did not improve the rates of total and biallelic mutations in the resulting blastocysts derived from either ZP-intact or -free zygotes.