Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic of heavy metals in wheat grains collected from the Liangfeng Irrigated Area, Beijing and a discussion of availability and human health risks

Irrigation using wastewater containing elevated levels of heavy metals can result in steadily increasing soil concentrations which, in turn, can contribute to elevated tissue levels in crops. A field experiment was conducted in the Liangfeng Irrigated Area in Beijing to investigate the effects of wastewater irrigation on heavy metal concentrations in wheat grain. In addition, the study explored the relationship between total and extractable concentrations of heavy metals in soil and concentrations in grain. Twenty-one soil samples and corresponding wheat grain samples were collected, and the concentration of As, Cr, Cd, Cu, Hg, Ni, Pb and Zn were measured. The concentrations of Ni, Pb, and Zn in wheat grain were 38.1, 28.6 and 4.8% higher, respectively, than the China National Hygienic Standards for Food. The concentrations of Hg and Cd in some samples were near, although still lower than, the China National Hygienic Standards for Food. Concentrations of Hg, Pb and Cu in wheat grain were significantly higher than concentrations measured during investigations in the same area in the 1970s. These data indicate that the accumulation of some heavy metals has accelerated and there may be human health risks associated with consumption of the grain of wheat grown in the Liangfeng Irrigated Area. Despite the elevated levels of some metals in wheat, there were no significant correlations between either the total or the extractable metal concentrations in soils and metal concentrations in wheat grains. It might indicate that using the extractable heavy metal to evaluate the effect of heavy metal to the crop in soil was not more convictive than total heavy metals.
Coupled Ocean-Cloud-Resolving Simulations of the Air–Sea Interaction over the Equatorial Western Pacific

Abstract A cloud-resolving model coupled to an ocean model with high vertical resolution is used to investigate air–sea interactions in 10-day long simulations. Modeled fields showed good agreement with two different convective regimes during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Research Experiment (TOGA COARE) Intensive Observing Period. The model simulates the formation of precipitation-produced, stable freshwater lenses at the top of the ocean mixed layer, with a variety of horizontal dimensions and lifetimes. The simulated fresh anomalies show realistic features, such as a positive correlation between salinity and temperature, the development of a surface jet in the direction of the wind, and, as a consequence, downwelling (upwelling) on its downwind (upwind) edge. The dataset generated by the coupled model is used to evaluate the contribution from several factors (ocean currents, gustiness, and correlations between wind speed and air temperature, wind speed and water vapor mi.
Asynchronous-Symmetric Channel-Hopping Sequences Over Prime Field for Cognitive Radio Networks

In this letter, two families of asynchronous-symmetric channel-hopping (CH) sequences over prime field are constructed. With straightforward construction algorithms, they provide a flexible balance between adjustable cardinality, full degree-of-rendezvous, and short maximum-time-to-rendezvous (MTTR) for practical cognitive radio networks. These CH sequences have smaller rendezvous-success-rate variance than their counterparts, thus supporting a more stable and uniform rendezvous process. As secondary users cannot transmit in channels occupied by primary (licensed) users, the average MTTR of these CH sequences is analyzed under a random channel-replacement method.
Borderline Personality Disorder Symptoms and Aggression: A Within-Person Process Model

Theoretical and empirical work suggests that aggression in those with borderline personality disorder (BPD) occurs primarily in the context of emotional reactivity, especially anger and shame, in response to perceived rejection. Using intensive repeated measures, we examined a within-person process model in which perceived rejection predicts increases in aggressive urges and behaviors via increases in negative affect (indirect effect) and in which BPD symptoms exacerbate this process (moderated mediation). Participants were 117 emerging adult women (ages 18–24) with recent histories of aggressive behavior who were recruited from a community-based longitudinal study of at-risk youth. Personality disorder symptoms were assessed by semistructured clinical interview, and aggressive urges, threats, and behaviors were measured in daily life during a 3-week ecological momentary assessment protocol. Multilevel path models revealed that within-person increases in perceived rejection predicted increases in negative affect, especially in women with greater BPD symptoms. In turn, increases in negative affect predicted increased likelihood of aggressive urges or behaviors. Further analysis revealed that BPD symptoms predicted greater anger and shame reactivity to perceived rejection, but not to criticism or insult. Additionally, only anger was associated with increases in aggression after controlling for other negative emotions. Whereas BPD symptoms exacerbated the link between perceived rejection and aggression via increases in negative affect (particularly anger), this process was attenuated in women with greater antisocial personality disorder symptoms. These findings suggest that anger reactivity to perceived rejection is one unique pathway, distinct from antisocial personality disorder, by which BPD symptoms increase risk for aggression.
Evaluation of relevance vector machine classifier for a real-time face recognition system

Face recognition has found a variety of applications in consumer electronics, such as laptops, smart phones, home security systems, home automation systems and many more. Machine learning is one of the important concepts, required for designing any pattern recognition system, including the proposed real-time face recognition system. Relevance vector machine is considered as one of the most recent machine learning algorithms reported in literature. In this paper, design and evaluation of Relevance Vector Machine classifier architectures for a real-time face recognition system using Histogram of Oriented Gradient features is proposed. In order to assess the performance of system designed, AT&T database of faces are initially considered, followed by the performance evaluation using real-time face inputs from the system camera. 81.25–97.00% recognition accuracy is obtained on using the proposed system and the proposed work can be easily extended for various other pattern recognition systems too.
Impact of Discharge Disposition on 30‐Day Readmissions Following Elective Spine Surgery

BACKGROUND: Readmissions are a significant economic burden on the health care system and increasingly being utilized as a metric of quality. Patients discharged to home vs an inpatient facility have different characteristics, which might influence the readmissions following spine surgery. OBJECTIVE: To determine the effect of discharge disposition on readmission rates and causes of readmission after spine surgery. METHODS: Patients enrolled in a prospective registry and undergoing elective spine surgery were analyzed. Readmissions (30 d), demographic, clinical variables, and baseline patient‐reported outcomes were recorded. Patients were dichotomized as discharged home vs inpatient facility. RESULTS: Of total 1631 patients, 1444 (89%) patients were discharged home and 187 (11%) discharged to an inpatient facility. Sixty‐five (4%) patients were readmitted at 30 d. There was no significant difference in readmissions between patients discharged to a facility 10 (5%) vs home 55 (4%; P = .210). In a multivariable analysis, adjusting for all the comorbidities, the discharge destination was not associated with readmission within 30 d. The medical complications (80%) were the most common cause of readmission in those discharged to a facility. Patients discharged home had significantly higher readmissions related to surgical wound issues (67%; P = .034). CONCLUSION: Despite the older age and higher comorbidities in patients discharged to an inpatient facility, the proportion of readmissions was comparable to those discharged home. Patients discharged home had a higher proportion of readmissions related to surgical wound complications and those discharged to facility had higher readmissions associated with medical complications. Understanding causes of readmission based on discharge destination may allow targeted intervention to reduce the readmission rates following spine surgery.
Impact of Early Vasopressor Administration on Neurological Outcomes after Prolonged Out-of-Hospital Cardiac Arrest

Abstract Introduction Vasopressors are associated with return of spontaneous circulation (ROSC), but no long-term benefit has been demonstrated in randomized trials. However, these trials did not control for the timing of vasopressor administration which may influence outcomes. Consequently, the objective of this study was to develop a model describing the likelihood of favorable neurological outcome (cerebral performance category [CPC] 1 or 2) as a function of the public safety answering point call receipt (PSAP)-to-pressor-interval (PPI) in prolonged out-of-hospital cardiac arrest. Hypothesis The likelihood of favorable neurological outcome declines with increasing PPI. Methods This investigation was a retrospective study of cardiac arrest using linked data from the Cardiac Arrest Registry to Enhance Survival (CARES) database (Centers for Disease Control and Prevention [Atlanta, Georgia USA]; American Heart Association [Dallas, Texas USA]; and Emory University Department of Emergency Medicine [Atlanta, Georgia USA]) and the North Carolina (USA) Prehospital Medical Information System. Adult patients suffering a bystander-witnessed, non-traumatic cardiac arrest between January 2012 and June 2014 were included. Logistic regression was used to calculate the adjusted odds ratio (OR) of neurological outcome as a function of PPI, while controlling for patient age, gender, and race; endotracheal intubation (ETI); shockable rhythm; layperson cardiopulmonary resuscitation (CPR); and field hypothermia. Results Of the 2,100 patients meeting inclusion criteria, 913 (43.5%) experienced ROSC, 618 (29.4%) survived to hospital admission, 187 (8.9%) survived to hospital discharge, and 155 (7.4%) were discharged with favorable neurological outcomes (CPC 1 or 2). Favorable neurological outcome was less likely with increasing PPI (OR=0.90; P<.01) and increasing age (OR=0.97; P<.01). Compared to patients with non-shockable rhythms, patients with shockable rhythms were more likely to have favorable neurological outcomes (OR=7.61; P<.01) as were patients receiving field hypothermia (OR=2.13; P<.01). Patient gender, non-Caucasian race, layperson CPR, and ETI were not independent predictors of favorable neurological outcome. Conclusion In this evaluation, time to vasopressor administration was significantly associated with favorable neurological outcome. Among adult, witnessed, non-traumatic arrests, the odds of hospital discharge with CPC 1 or 2 declined by 10% for every one-minute delay between PSAP call-receipt and vasopressor administration. These retrospective observations support the notion of a time-dependent function of vasopressor effectiveness on favorable neurological outcome. Large, prospective studies are needed to verify this relationship. HubbleMW, TysonC. Impact of early vasopressor administration on neurological outcomes after prolonged out-of-hospital cardiac arrest. Prehosp Disaster Med. 2017; 32(3):297–304.
Virtual Surgery for the Nasal Airway: A Preliminary Report on Decision Support and Technology Acceptance

Importance Nasal airway obstruction (NAO) is a common problem that affects patient quality of life. Surgical success for NAO correction is variable. Virtual surgery planning via computational fluid dynamics (CFD) has the potential to improve the success rates of NAO surgery. Objective To elicit surgeon feedback of a virtual surgery planning tool for NAO and to determine if this tool affects surgeon decision making. Design, Setting, and Participants For this cross-sectional study, 60-minute face-to-face interviews with board-certified otolaryngologists were conducted at a single academic otolaryngology department from September 16, 2016, through October 7, 2016. Virtual surgery methods were introduced, and surgeons were able to interact with the virtual surgery planning tool interface. Surgeons were provided with a patient case of NAO, and open feedback of the platform was obtained, with emphasis on surgical decision making. Main Outcomes and Measures Likert scale responses and qualitative feedback were collected for the virtual surgery planning tool and its influence on surgeon decision making. Results Our 9 study participants were all male, board-certified otolaryngologists with a mean (range) 15 (4-28) number of years in practice and a mean (range) number of nasal surgeries per month at 2.2 (0.0-6.0). When examined on a scale of 1 (not at all) to 5 (completely), surgeon mean (SD) score was 3.4 (0.5) for how realistic the virtual models were compared with actual surgery. On the same scale, when asked how much the virtual surgery planning tool changed surgeon decision making, mean (SD) score was 2.6 (1.6). On a scale of 1 (strongly disagree) to 7 (strongly agree), surgeon scores for perceived usefulness of the technology and attitude toward using it were 5.1 (1.1) and 5.7 (0.9), respectively. Conclusions and Relevance Our study shows positive surgeon experience with a virtual surgery planning tool for NAO based on CFD simulations. Surgeons felt that future applications and areas of study of the virtual surgery planning tool include its potential role for patient counseling, selecting appropriate surgical candidates, and identifying which anatomical structures should be targeted for surgical correction. Level of Evidence NA.
Client-Focused Security Assessment of mHealth Apps and Recommended Practices to Prevent or Mitigate Transport Security Issues

Background Mobile health (mHealth) apps show a growing importance for patients and health care professionals. Apps in this category are diverse. Some display important information (ie, drug interactions), whereas others help patients to keep track of their health. However, insufficient transport security can lead to confidentiality issues for patients and medical professionals, as well as safety issues regarding data integrity. mHealth apps should therefore deploy intensified vigilance to protect their data and integrity. This paper analyzes the state of security in mHealth apps. Objective The objectives of this study were as follows: (1) identification of relevant transport issues in mHealth apps, (2) development of a platform for test purposes, and (3) recommendation of practices to mitigate them. Methods Security characteristics relevant to the transport security of mHealth apps were assessed, presented, and discussed. These characteristics were used in the development of a prototypical platform facilitating streamlined tests of apps. For the tests, six lists of the 10 most downloaded free apps from three countries and two stores were selected. As some apps were part of these top 10 lists in more than one country, 53 unique apps were tested. Results Out of the 53 apps tested from three European App Stores for Android and iOS, 21/53 (40%) showed critical results. All 21 apps failed to guarantee the integrity of data displayed. A total of 18 apps leaked private data or were observable in a way that compromised confidentiality between apps and their servers; 17 apps used unprotected connections; and two apps failed to validate certificates correctly. None of the apps tested utilized certificate pinning. Many apps employed analytics or ad providers, undermining user privacy. Conclusions The tests show that many mHealth apps do not apply sufficient transport security measures. The most common security issue was the use of any kind of unprotected connection. Some apps used secure connections only for selected tasks, leaving all other traffic vulnerable.
Long‐Term Effect of Surface Roughness and Patients' Factors on Crestal Bone Loss at Dental Implants. A Systematic Review and Meta‐Analysis

Publications from 2011 to 2015 were selected to evaluate effect of implant surface roughness on long-term bone loss as surrogate for peri-implantitis risk. 87 out of 2,566 papers reported the mean bone loss after at least 5 years of function. Estimation of the proportion of implants with bone loss above 1, 2, and 3 mm as well as analysis the effect of implant surface roughness, smoking, and history of periodontitis was performed. By means of the provided statistical information of bone loss (mean and standard deviation) the prevalence of implants with bone loss ranging from 1 to 3 mm was estimated. The bone loss was used as a surrogate parameter for "peri-implantitis" given the fact that "peri-implantitis" prevalence was not reported in most studies or when reported, the diagnostic criteria were unclear or of dubious quality. The outcome of this review suggests that peri-implant bone loss around minimally rough implant systems was statistically significant less in comparison to the moderately rough and rough implant systems. No statistically significant difference was observed between moderately rough and rough implant systems. The studies that compared implants with comparable design and different surface roughness, showed less average peri-implant bone loss around the less rough surfaces in the meta-analysis. However, due to the heterogeneity of the papers and the multifactorial cause for bone loss, the impact of surface roughness alone seems rather limited and of minimal clinical importance. Irrespective of surface topography or implant brand, the average weighted implant survival rate was 97.3% after 5 years or more of loading. If considering 3 mm bone loss after at least 5 years to represent the presence of "peri-implantitis," less than 5% of the implants were affected. The meta-analysis indicated that periodontal history and smoking habits yielded more bone loss.
Regulation of 4E-BP1 activity in the mammalian oocyte

ABSTRACT Fully grown mammalian oocytes utilize transcripts synthetized and stored during earlier development. RNA localization followed by a local translation is a mechanism responsible for the regulation of spatial and temporal gene expression. Here we show that the mouse oocyte contains 3 forms of cap-dependent translational repressor expressed on the mRNA level: 4E-BP1, 4E-BP2 and 4E-BP3. However, only 4E-BP1 is present as a protein in oocytes, it becomes inactivated by phosphorylation after nuclear envelope breakdown and as such it promotes cap-dependent translation after NEBD. Phosphorylation of 4E-BP1 can be seen in the oocytes after resumption of meiosis but it is not detected in the surrounding cumulus cells, indicating that 4E-BP1 promotes translation at a specific cell cycle stage. Our immunofluorescence analyses of 4E-BP1 in oocytes during meiosis I showed an even localization of global 4E-BP1, as well as of its 4E-BP1 (Thr37/46) phosphorylated form. On the other hand, 4E-BP1 phosphorylated on Ser65 is localized at the spindle poles, and 4E-BP1 phosphorylated on Thr70 localizes on the spindle. We further show that the main positive regulators of 4E-BP1 phosphorylation after NEBD are mTOR and CDK1 kinases, but not PLK1 kinase. CDK1 exerts its activity toward 4E-BP1 phosphorylation via phosphorylation and activation of mTOR. Moreover, both CDK1 and phosphorylated mTOR co-localize with 4E-BP1 phosphorylated on Thr70 on the spindle at the onset of meiotic resumption. Expression of the dominant negative 4E-BP1 mutant adversely affects translation and results in spindle abnormality. Taken together, our results show that the phosphorylation of 4E-BP1 promotes translation at the onset of meiosis to support the spindle assembly and suggest an important role of CDK1 and mTOR kinases in this process. We also show that the mTOR regulatory pathway is present in human oocytes and is likely to function in a similar way as in mouse oocytes.
Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI

Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score <4+3), 3) high-grade vs. other tissue components and 4) high-grade vs. benign tissue by selecting the classifier with the highest AUC using 1-10 features from forward feature selection. The CAD model was able to classify malignant vs. benign tissue and detect high-grade cancer with high accuracy. Once fully validated, this work will form the basis for a tool that enhances the radiologist’s ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.
Making Object Learning and Recognition an Active Process

The exploration and learning of new objects is an essential capability of a cognitive robot. In this paper we focus on making use of the robot's manipulation abilities to learn complete object representations suitable for 3D object recognition. Taking control of the object allows the robot to focus on relevant parts of the images, thus bypassing potential pitfalls of purely bottom-up attention and segmentation. The main contribution of the paper consists in integrated visuomotor processes that allow the robot to learn object representations by manipulation without having any prior knowledge about the objects. Our experimental results show that the acquired data is of sufficient quality to train a classifier that can recognize 3D objects independently of the viewpoint.