Lost in the woods: Forest vegetation, and not topography, most affects the connectivity of mesh radio networks for public safety.

Real-time data- and location-sharing using mesh networking radios paired with smartphones may improve situational awareness and safety in remote environments lacking communications infrastructure. Despite being increasingly used for wildland fire and public safety applications, there has been little formal evaluation of the network connectivity of these devices. The objectives of this study were to 1) characterize the connectivity of mesh networks in variable forest and topographic conditions; 2) evaluate the abilities of lidar and satellite remote sensing data to predict connectivity; and 3) assess the relative importance of the predictive metrics. A large field experiment was conducted to test the connectivity of a network of one mobile and five stationary goTenna Pro mesh radios on 24 Public Land Survey System sections approximately 260 ha in area in northern Idaho. Dirichlet regression was used to predict connectivity using 1) both lidar- and satellite-derived metrics (LIDSAT); 2) lidar-derived metrics only (LID); and 3) satellite-derived metrics only (SAT). On average the full network was connected only 32.6% of the time (range: 0% to 90.5%) and the mobile goTenna was disconnected from all other devices 18.2% of the time (range: 0% to 44.5%). RMSE for the six connectivity levels ranged from 0.101 to 0.314 for the LIDSAT model, from 0.103 to 0.310 for the LID model, and from 0.121 to 0.313 for the SAT model. Vegetation-related metrics affected connectivity more than topography. Developed models may be used to predict the connectivity of real-time mesh networks over large spatial extents using remote sensing data in order to forecast how well similar networks are expected to perform for wildland firefighting, forestry, and public safety applications. However, safety professionals should be aware of the impacts of vegetation on connectivity.

A novel smartphone-based activity recognition modeling method for tracked equipment in forest operations.

Activity recognition modelling using smartphone Inertial Measurement Units (IMUs) is an underutilized resource defining and assessing work efficiency for a wide range of natural resource management tasks. This study focused on the initial development and validation of a smartphone-based activity recognition system for excavator-based mastication equipment working in Ponderosa pine (Pinus ponderosa) plantations in North Idaho, USA. During mastication treatments, sensor data from smartphone gyroscopes, accelerometers, and sound pressure meters (decibel meters) were collected at three sampling frequencies (10, 20, and 50 hertz (Hz)). These data were then separated into 9 time domain features using 4 sliding window widths (1, 5, 7.5 and 10 seconds) and two levels of window overlap (50% and 90%). Random forest machine learning algorithms were trained and evaluated for 40 combinations of model parameters to determine the best combination of parameters. 5 work elements (masticate, clear, move, travel, and delay) were classified with the performance metrics for individual elements of the best model (50 Hz, 10 second window, 90% window overlap) falling within the following ranges: area under the curve (AUC) (95.0% - 99.9%); sensitivity (74.9% - 95.6%); specificity (90.8% - 99.9%); precision (81.1% - 98.3%); F1-score (81.9% - 96.9%); balanced accuracy (87.4% - 97.7%). Smartphone sensors effectively characterized individual work elements of mechanical fuel treatments. This study is the first example of developing a smartphone-based activity recognition model for ground-based forest equipment. The continued development and dissemination of smartphone-based activity recognition models may assist land managers and operators with ubiquitous, manufacturer-independent systems for continuous and automated time study and production analysis for mechanized forest operations.

Development and validation of smartwatch-based activity recognition models for rigging crew workers on cable logging operations.

Analysis of high-resolution inertial sensor and global navigation satellite system (GNSS) data collected by mobile and wearable devices is a relatively new methodology in forestry and safety research that provides opportunities for modeling work activities in greater detail than traditional time study analysis. The objective of this study was to evaluate whether smartwatch-based activity recognition models could quantify the activities of rigging crew workers setting and disconnecting log chokers on cable logging operations. Four productive cycle elements (travel to log, set choker, travel away, clear) were timed for choker setters and four productive cycle elements (travel to log, unhook, travel away, clear) were timed for chasers working at five logging sites in North Idaho. Each worker wore a smartwatch that recorded accelerometer data at 25 Hz. Random forest machine learning was used to develop predictive models that classified the different cycle elements based on features extracted from the smartwatch acceleration data using 15 sliding window sizes (1 to 15 s) and five window overlap levels (0%, 25%, 50%, 75%, and 90%). Models were compared using multiclass area under the Receiver Operating Characteristic (ROC) curve, or AUC. The best choker setter model was created using a 3-s window with 90% overlap and had sensitivity values ranging from 76.95% to 83.59% and precision values ranging from 41.42% to 97.08%. The best chaser model was created using a 1-s window with 90% overlap and had sensitivity values ranging from 71.95% to 82.75% and precision values ranging from 14.74% to 99.16%. These results have demonstrated the feasibility of quantifying forestry work activities using smartwatch-based activity recognition models, a basic step needed to develop real-time safety notifications associated with high-risk job functions and to advance subsequent, comparative analysis of health and safety metrics across stand, site, and work conditions.

Selecting a Cell Engineering Methodology During Cell Therapy Product Development.

When considering the development pathway for a genetically modified cell therapy product, it is critically important that the product is engineered consistent with its intended human use. For scientists looking to develop and commercialize a new technology, the decision to select a genetic modification method depends on several practical considerations. Whichever path is chosen, the developer must understand the key risks and potential mitigations of the cell engineering approach. The developer should also understand the clinical implications: permanent/memory establishment versus transient expression, and clinical manufacturing considerations when dealing with transplantation of genetically engineered cells. This review covers important topics for mapping out a strategy for developers of new cell-based therapeutics. Biological, technological, manufacturing, and clinical considerations are all presented to map out development lanes for the initiation and risk management of new gene-based cell therapeutic products for human use.

Risk Factors for Failure in Hammertoe Surgery.

BACKGROUND: Hammertoe correction is perhaps the most common elective surgery performed in the foot, yet rates of symptomatic recurrence and revision surgery can be high. In this study, we aimed to identify patient and provider risk factors associated with failure after hammertoe surgery. METHODS: Consecutive patients with a minimum of 6 months' follow-up undergoing hammertoe surgery within a single, urban foot and ankle practice between January 1, 2011, and December 31, 2013, served as the basis of this retrospective cohort study. Cox regression analysis was used to identify important predictor variables obtained through chart and radiographic review. One hundred fifty-two patients (311 toes) with a mean age of 60.8 ± 11.2 years and mean follow-up of 29.5 ± 21.2 months were included. RESULTS: Statistically significant predictors of failure were having a larger preoperative transverse plane deviation of the digit (hazard ratio [HR], 1.03 for each degree; P < .001; 95% CI, 1.02, 1.04), operating on the second toe (vs third or fourth) (HR, 2.23; P = .003; 95% CI, 1.31, 3.81), use of a phalangeal osteotomy to reduce the proximal interphalangeal (PIP) joint (HR, 2.77; P = .005; 95% CI, 1.36, 5.64), and using less common/conventional operative techniques to reduce the PIP joint (HR, 2.62; P = .03; 95% CI, 1.09, 6.26). Concomitant performance of first ray surgery reduced hammertoe recurrence by 50% (HR, 0.51; P = .01; 95% CI, 0.30, 0.87). CONCLUSION: We identified risk factors that may provide guidance for surgeons during preoperative hammertoe surgery consultations. This information may better equip patients with appropriate postoperative expectations when contemplating surgery. LEVEL OF EVIDENCE: Level III, retrospective case series.

Positioning Methods and the Use of Location and Activity Data in Forests.

In this paper, we provide an overview of positioning systems for moving resources in forest and fire management and review the related literature. Emphasis is placed on the accuracy and range of different localization and location-sharing methods, particularly in forested environments and in the absence of conventional cellular or internet connectivity. We then conduct a second review of literature and concepts related to several emerging, broad themes in data science, including the terms location-based services (LBS), geofences, wearable technology, activity recognition, mesh networking, the Internet of Things (IoT), and big data. Our objective in this second review is to inform how these broader concepts, with implications for networking and analytics, may help to advance natural resource management and science in the future. Based on methods, themes, and concepts that arose in our systematic reviews, we then augmented the paper with additional literature from wildlife and fisheries management, as well as concepts from video object detection, relative positioning, and inventory-tracking that are also used as forms of localization. Based on our reviews of positioning technologies and emerging data science themes, we present a hierarchical model for collecting and sharing data in forest and fire management, and more broadly in the field of natural resources. The model reflects tradeoffs in range and bandwidth when recording, processing, and communicating large quantities of data in time and space to support resource management, science, and public safety in remote areas. In the hierarchical approach, wearable devices and other sensors typically transmit data at short distances using Bluetooth, Bluetooth Low Energy (BLE), or ANT wireless, and smartphones and tablets serve as intermediate data collection and processing hubs for information that can be subsequently transmitted using radio networking systems or satellite communication. Data with greater spatial and temporal complexity is typically processed incrementally at lower tiers, then fused and summarized at higher levels of incident command or resource management. Lastly, we outline several priority areas for future research to advance big data analytics in natural resources.

Public Health Social Work as a Unifying Framework for Social Work's Grand Challenges.

Introduced in 2013 by the American Academy of Social Work and Social Welfare, the Grand Challenges for Social Work (GCSW) implicitly embrace a public health perspective. However, the lack of a specific overarching conceptual framework creates a challenge for moving the GCSW from concept to practice. In this article, authors propose that public health social work (PHSW) provides a unifying framework for moving the GCSW from concept to practice. Authors undertook a review of the literature, including a review of published literature and all Web sites and other Web materials focused on the GCSW. Three GCSW were selected to illustrate the utility of PHSW and the social work health impact model (SWHIM): (1) stopping family violence, (2) eradicating social isolation, and (3) achieving opportunity and justice. Using a wide-lens PHSW approach, the illustrations focus on actions that can influence populations through strengthened environments and multilevel interventions. The public health field reflects the rigorous science behind the theoretical models, community-based approaches, and attention to effects of social determinants of health at the population level. Because health and inequalities are the focus of many of the GCSW, incorporating both public and population health, together with the SWHIM, can help provide structure to achieve collective goals.

Trauma-informed care with women diagnosed with postpartum depression: a conceptual framework.

Postpartum depression (PPD) is a mental health disorder that affects approximately 20% of all new mothers. PPD frequently co-occurs with and is exacerbated by trauma, particularly for women from vulnerable populations. Trauma-informed care (TIC) is a best practice that recognizes the importance of, and takes steps to promote recovery from, trauma while preventing retraumatization. Despite its potential utility, there is limited research published on TIC, including how TIC is operationalized across practice settings. Further, despite the prevalence and negative effects of untreated PPD, to date there have been limited articles published on TIC and PPD. The purpose of this article is to provide a TIC framework for service delivery for women diagnosed with PPD including explicit strategies for how TIC should be structured across roles, settings, and systems. Implications for health practice, policy, and future research are provided.

Human Factors Affecting Logging Injury Incidents in Idaho and the Potential for Real-Time Location-Sharing Technology to Improve Safety.

Human factors, including inadequate situational awareness, can contribute to fatal and near-fatal traumatic injuries in logging, which is among the most dangerous occupations in the United States. Real-time location-sharing technology may help improve situational awareness for loggers. We surveyed and interviewed professional logging contractors in Idaho to (1) characterize current perceptions of in-woods hazards and the human factors that lead to injuries; (2) understand their perspectives on using technology-based location-sharing solutions to improve safety in remote work environments; and (3) identify logging hazard scenarios that could be mitigated using location-sharing technology. We found production pressure, fatigue, and inexperience among the most-common factors contributing to logging injuries from the perspective of participants. Potential limitations of location-sharing technology identified included potential for distraction and cost. Contractors identified several situations where the technology may help improve safety, including (1) alerting workers of potential hand-faller injuries due to lack of movement; (2) helping rigging crews to maintain safe distances from yarded trees and logs during cable logging; and (3) providing a means for equipment operators to see approaching ground workers, especially in low-visibility situations.

Community Gun Violence as a Social Determinant of Elementary School Achievement.

The association of indirect exposure to firearm-related violence and standardized test scores among third grade elementary school children were analyzed using geospatial mapping of police department data for all gunshots in Syracuse, NY (n = 2, 127) and state standardized test scores from 2009-2015. Confirmed gunshots were geocoded and mapped across the city and neighborhood school catchment areas. Third grade standardized New York State test scores for English Language Arts (ELA) and math were coded as dichotomous variables of proficient and below proficient scores. State standardized test scores for ELA and math were found to be 50% lower in the elementary schools located within higher concentration gunshot areas, than in elementary schools in lower gunshot areas. Higher levels of gun violence within school catchment areas were significantly associated with higher rates of ELA and math failure (p ≤ .05). These findings suggest that community violence may be an important, though under recognized, social determinant of poor school performance.

Integrating the social determinants of health into two interprofessional courses: Findings from a pilot study.

Five colleges and universities in Upstate New York, United States, created the 'Route-90 Collaborative' to support faculty implementing the Institute of Medicine's (IOM) Framework for Educating Health Professionals to Address the Social Determinants of Health. The two courses described herein used a flipped classroom approach in which students from 14 different nations were responsible for facilitating individual classes. This descriptive study used an educational intervention in two interprofessional courses - reproductive health and global health - based on the IOM Framework into two courses. The evaluation used quantitative and open-ended text response data from students. Course evaluations indicated the students found the courses helped them to learn more about health issues and service delivery in various countries, expand their knowledge base on sociocultural and ecological influences on health care, and broaden their perspectives on various health topics so they will be able to provide higher quality healthcare. Although this is the first effort of our Collaborative to implement the Framework, given the student feedback, we believe implementing the Framework in various courses has the potential to enhance healthcare service delivery and reduce the negative impact of social determinants of health.

Real-time positioning in logging: Effects of forest stand characteristics, topography, and line-of-sight obstructions on GNSS-RF transponder accuracy and radio signal propagation.

Real-time positioning on mobile devices using global navigation satellite system (GNSS) technology paired with radio frequency (RF) transmission (GNSS-RF) may help to improve safety on logging operations by increasing situational awareness. However, GNSS positional accuracy for ground workers in motion may be reduced by multipath error, satellite signal obstruction, or other factors. Radio propagation of GNSS locations may also be impacted due to line-of-sight (LOS) obstruction in remote, forested areas. The objective of this study was to characterize the effects of forest stand characteristics, topography, and other LOS obstructions on the GNSS accuracy and radio signal propagation quality of multiple Raveon Atlas PT GNSS-RF transponders functioning as a network in a range of forest conditions. Because most previous research with GNSS in forestry has focused on stationary units, we chose to analyze units in motion by evaluating the time-to-signal accuracy of geofence crossings in 21 randomly-selected stands on the University of Idaho Experimental Forest. Specifically, we studied the effects of forest stand characteristics, topography, and LOS obstructions on (1) the odds of missed GNSS-RF signals, (2) the root mean squared error (RMSE) of Atlas PTs, and (3) the time-to-signal accuracy of safety geofence crossings in forested environments. Mixed-effects models used to analyze the data showed that stand characteristics, topography, and obstructions in the LOS affected the odds of missed radio signals while stand variables alone affected RMSE. Both stand characteristics and topography affected the accuracy of geofence alerts.

Advancing Social Work Education for Health Impact.

Social work education plays a critical role in preparing social workers to lead efforts that improve health. Because of the dynamic health care landscape, schools of social work must educate students to facilitate health care system improvements, enhance population health, and reduce medical costs. We reviewed the existing contributions of social work education and provided recommendations for improving the education of social workers in 6 key areas: aging, behavioral health, community health, global health, health reform, and health policy. We argue for systemic improvement in the curriculum at every level of education, including substantive increases in content in health, health care, health care ethics, and evaluating practice outcomes in health settings. Schools of social work can further increase the impact of the profession by enhancing the curricular focus on broad content areas such as prevention, health equity, population and community health, and health advocacy.

Filling out the forms: Health literacy among the uninsured.

This study addresses health literacy among patients at a free clinic in Syracuse, NY. Researchers conducted chart reviews of 600 patients and qualitative interviews with 22 patients and 7 providers. Most clinic patients had a high school, or higher, level education and no difficulty with reading comprehension. Nevertheless, a majority had at least some difficulty with comprehending and following through on health information. For many interviewees, the greatest difficulty was completing the required forms for entitlement programs. The findings demonstrate that low health literacy may occur even among well-educated patients and recommend that health literacy be assessed for all patients.

Hazards in Motion: Development of Mobile Geofences for Use in Logging Safety.

Logging is one of the most hazardous occupations in the United States. Real-time positioning that uses global navigation satellite system (GNSS) technology paired with radio frequency transmission (GNSS-RF) has the potential to reduce fatal and non-fatal accidents on logging operations through the use of geofences that define safe work areas. Until recently, most geofences have been static boundaries. The aim of this study was to evaluate factors affecting mobile geofence accuracy in order to determine whether virtual safety zones around moving ground workers or equipment are a viable option for improving situational awareness on active timber sales. We evaluated the effects of walking pace, transmission interval, geofence radius, and intersection angle on geofence alert delay using a replicated field experiment. Simulation was then used to validate field results and calculate the proportion of GNSS error bearings resulting in early alerts. The interaction of geofence radius and intersection angle affected safety geofence alert delay in the field experiment. The most inaccurate alerts were negative, representing early warning. The magnitude of this effect was largest at the greatest intersection angles. Simulation analysis supported these field results and also showed that larger GNSS error corresponded to greater variability in alert delay. Increasing intersection angle resulted in a larger proportion of directional GNSS error that triggered incorrect, early warnings. Because the accuracy of geofence alerts varied greatly depending on GNSS error and angle of approach, geofencing for occupational safety is most appropriate for general situational awareness unless real-time correction methods to improve accuracy or higher quality GNSS-RF transponders are used.

Community health agency administrators' access to public health data for program planning, evaluation, and grant preparation.

The Affordable Care Act mandates that public health data be made available for community agency use. Having access to such data allows community agencies to tailor interventions, evaluations, and funding requests more effectively. This study, jointly undertaken by Syracuse University faculty and students with the New York State Perinatal Association, sought to understand community agencies' access to requests for governmental data, as well as to identify areas for improving data access. Results from this survey of administrators from 43 agencies in New York State found that only one-half of their requests for data were successful. Difficulties in obtaining access to needed data included fiscal and staffing constraints of the state-level agencies that house the data, as well as possible overinterpretation of confidentiality policies. In addition, some of community agency respondents reported that their staff lacked skills in data analysis and would benefit from training in epidemiology and quantitative evaluation.

Characterizing Rigging Crew Proximity to Hazards on Cable Logging Operations Using GNSS-RF: Effect of GNSS Positioning Error on Worker Safety Status.

Logging continues to rank among the most lethal occupations in the United States. Though the hazards associated with fatalities are well-documented and safe distances from hazards is a common theme in safety education, positional relationships between workers and hazards have not been quantified previously. Using GNSS-RF (Global Navigation Satellite System-Radio Frequency) transponders that allow real-time monitoring of personnel, we collected positioning data for rigging crew workers and three common cable logging hazards: a log loader, skyline carriage, and snag. We summarized distances between all ground workers and each hazard on three active operations and estimated the proportion of time crew occupied higher-risk areas, as represented by geofences. We then assessed the extent to which positioning error associated with different stand conditions affected perceived worker safety status by applying error sampled in a separate, controlled field experiment to the operational data. Root mean squared error was estimated at 11.08 m in mature stands and 3.37 m in clearcuts. Simulated error expected for mature stands altered safety status in six of nine treatment combinations, whereas error expected for clearcuts affected only one. Our results show that canopy-associated GNSS error affects real-time geofence safety applications when using single-constellation American Global Positioning System transponders.