Future Work Research Articles

Software for Bioprinting.

The bioprinting of heterogeneous organs is a crucial issue. To reach the complexity of such organs, there is a need for highly specialized software that will meet all requirements such as accuracy, complexity, and others. The primary objective of this review is to consider various software tools that are used in bioprinting and to reveal their capabilities. The sub-objective was to consider different approaches for the model creation using these software tools. Related articles on this topic were analyzed. Software tools are classified based on control tools, general computer-aided design (CAD) tools, tools to convert medical data to CAD formats, and a few highly specialized research-project tools. Different geometry representations are considered, and their advantages and disadvantages are considered applicable to heterogeneous volume modeling and bioprinting. The primary factor for the analysis is suitability of the software for heterogeneous volume modeling and bioprinting or multimaterial three-dimensional printing due to the commonality of these technologies. A shortage of specialized suitable software tools is revealed. There is a need to develop a new application area such as computer science for bioprinting which can contribute significantly in future research work.

The future of work of academics in the age of Artificial Intelligence: State-of-the-art and a research roadmap

The Future of Work (FoW) has garnered significant attention among scholars and practitioners, with the advent of Artificial Intelligence (AI) playing an important role in shaping this discourse. Despite the common perception that intelligent machines pose a threat to workers in routine roles, AI technologies are increasingly being utilized for advanced tasks carried out by knowledge workers. Drawing on state-of-the-art research and real-life examples we develop an integrated framework to explore the future of academic work. Our focus is on academics, an essential yet under-researched group of knowledge workers, and we discuss their work in relation to AI across space, time, and task dimensions. Our analysis reveals that the usage of AI technologies can have implications for the research, teaching, and service activities of academics and thereby also for the creation, acquisition, dissemination, and application of knowledge. Based on our framework we develop scenarios and propose a future research roadmap.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Leveraging Tendon Vibration to Enhance Pseudo-Haptic Perceptions in VR.

Pseudo-haptic techniques are used to modify haptic perception by appropriately changing visual feedback to body movements. Based on the knowledge that tendon vibration can affect our somatosensory perception, this article proposes a method for leveraging tendon vibration to enhance pseudo-haptics during free arm motion. Three experiments were performed to examine the impact of tendon vibration on the range and resolution of pseudo-haptics. The first experiment investigated the effect of tendon vibration on the detection threshold of the discrepancy between visual and physical motion. The results indicated that vibrations applied to the inner tendons of the wrist and elbow increased the threshold, suggesting that tendon vibration can augment the applicable visual motion gain by approximately 13% without users detecting the visual/physical discrepancy. Furthermore, the results demonstrate that tendon vibration acts as noise on haptic motion cues. The second experiment assessed the impact of tendon vibration on the resolution of pseudo-haptics by determining the just noticeable difference in pseudo-weight perception. The results suggested that the tendon vibration does not largely compromise the resolution of pseudo-haptics. The third experiment evaluated the equivalence between the weight perception triggered by tendon vibration and that by visual motion gain, that is, the point of subjective equality. The results revealed that vibration amplifies the weight perception and its effect was equivalent to that obtained using a gain of 0.64 without vibration, implying that the tendon vibration also functions as an additional haptic cue. Our results provide design guidelines and future work for enhancing pseudo-haptics with tendon vibration.

Functional analysis of cyclic diguanylate-modulating proteins in Vibrio fischeri.

As bacterial symbionts transition from a motile free-living state to a sessile biofilm state, they must coordinate behavior changes suitable to each lifestyle. Cyclic diguanylate (c-di-GMP) is an intracellular signaling molecule that can regulate this transition, and it is synthesized by diguanylate cyclase (DGC) enzymes and degraded by phosphodiesterase (PDE) enzymes. Generally, c-di-GMP inhibits motility and promotes biofilm formation. While c-di-GMP and the enzymes that contribute to its metabolism have been well-studied in pathogens, considerably less focus has been placed on c-di-GMP regulation in beneficial symbionts. Vibrio fischeri is the sole beneficial symbiont of the Hawaiian bobtail squid (Euprymna scolopes) light organ, and the bacterium requires both motility and biofilm formation to efficiently colonize. C-di-GMP regulates swimming motility and cellulose exopolysaccharide production in V. fischeri. The genome encodes 50 DGCs and PDEs, and while a few of these proteins have been characterized, the majority have not undergone comprehensive characterization. In this study, we use protein overexpression to systematically characterize the functional potential of all 50 V. fischeri proteins. All 28 predicted DGCs and 14 predicted PDEs displayed at least one phenotype consistent with their predicted function, and a majority of each displayed multiple phenotypes. Finally, active site mutant analysis of proteins with the potential for both DGC and PDE activities revealed potential activities for these proteins. This work presents a systems-level functional analysis of a family of signaling proteins in a tractable animal symbiont and will inform future efforts to characterize the roles of individual proteins during lifestyle transitions.

Integrating Artificial Intelligence into Biomedical Science Curricula: Advancing Healthcare Education.

The integration of artificial intelligence (AI) into healthcare practice has improved patient management and care. Many clinical laboratory specialties have already integrated AI in diagnostic specialties such as radiology and pathology, where it can assist in image analysis, diagnosis, and clinical reporting. As AI technologies continue to advance, it is crucial for biomedical science students to receive comprehensive education and training in AI concepts and applications and to understand the ethical consequences for such development. This review focus on the importance of integrating AI into biomedical science curricula and proposes strategies to enhance curricula for different specialties to prepare future healthcare workers. Improving the curriculum can be achieved by introducing specific subjects related to AI such as informatics, data sciences, and digital health. However, there are many challenges to enhancing the curriculum with AI. In this narrative review, we discuss these challenges and suggest mitigation strategies.

Color Transfer for Images: A Survey

High-quality image generation is an important topic in digital visualization. As a sub-topic of the research, color transfer is to produce a high-quality image with ideal color scheme learned from the reference one. In this article, we investigate the mainstream methods of color transfer to provide a survey that introduces the related theories and frameworks. Such methods can be divided into three categories: statistical color transfer, semantic-based color transfer, and color transfer for special target. For these mainstream technical routes, we discuss the related research background, technical details, and representative methods. We also exhibit some new trends of the topic according to recent progress. Based on the comparisons, we discuss the unsolved issues of color transfer and potential solutions in future work.

What supports the emotional well-being of peer workers in an NHS mental health service?

Purpose This study aims to explore the experiences of peers working in a range of roles within a single NHS mental health service. This study also aims to provide evidence of the impact of existing support, organisational structure and culture around peer working and provide recommendations for a Good Practice Guide for Peer Working. Peer roles require lived experience of mental health conditions and/or services. While the impact on them of using their own lived experience is not fully understood, anecdotal evidence suggests that peer workers may experience a greater emotional impact than other mental health workers. Burnout and retention are particular concerns. Design/methodology/approach This was a two-stage study using focus groups and reflexive thematic analysis in Stage 1. The key themes formed the basis of the Stage 2 workshop, which provided recommendations for a Good Practice Guide. The study team consisted of peer researchers with lived experience, supported by a Lived Experience Advisory Panel. Findings There is a perceived lack of support and an increased peer burden for peer workers. Recommendations included relevant ongoing training and development; support and supervision; and organisational cultural change. Originality/value Working within a peer-led co-production framework, this study contributes to the development of the evidence base for peer emotional labour. Based on the findings, a Good Practice Guide for Peer Working is being developed to promote good practice for the development of future peer worker roles.

Explicit and implicit locomotor learning in individuals with chronic hemiparetic stroke.

Motor learning involves both explicit and implicit processes that are fundamental for acquiring and adapting complex motor skills. However, stroke may damage the neural substrates underlying explicit and/or implicit learning, leading to deficits in overall motor performance. While both learning processes are typically used in concert in daily life and rehabilitation, no gait studies have determined how these processes function together after stroke when tested during a task that elicits dissociable contributions from both. Here, we compared explicit and implicit locomotor learning in individuals with chronic stroke to age- and sex-matched neurologically intact controls. We assessed implicit learning using split-belt adaptation (where two treadmill belts move at different speeds). We assessed explicit learning (i.e., strategy-use) using visual feedback during split-belt walking to help individuals explicitly correct for step length errors created by the split-belts. The removal of visual feedback after the first 40 strides of split-belt walking, combined with task instructions, minimized contributions from explicit learning for the remainder of the task. We utilized a multi-rate state-space model to characterize individual explicit and implicit process contributions to overall behavioral change. The computational and behavioral analyses revealed that, compared to controls, individuals with chronic stroke demonstrated deficits in both explicit and implicit contributions to locomotor learning, a result that runs counter to prior work testing each process individually during gait. Since post-stroke locomotor rehabilitation involves interventions that rely on both explicit and implicit motor learning, future work should determine how locomotor rehabilitation interventions can be structured to optimize overall motor learning.

Результаты целевого трудоустройства медицинских работников в городах и сельской местности.

Targeted training of future medical workers and their guaranteed employment is one of the state measures to address the issue of the shortage of specialists. The key mission of targeted training is the balanced regulation by the organization of training and employment. Currently, there are not enough scientific studies on the results and effectiveness of this measure in the health care system, but many researchers emphasize the problems of targeted employment of medical workers. According to the studies of a number of authors, the imperfection of normative legal regulation of issues of targeted training allows graduates not to fulfill the obligations of employment in medical organizations upon graduation [3–9]. The purpose of the study. Conduct an analysis of indicators reflecting the specifics of targeted employment of health workers in organizations located in urban and rural areas in 2022 and 2023. Materials and methods. The study used statistical data for 85 constituent entities of the Russian Federation on the basis of an operative documented request to the health protection authorities of the constituent entities of the Russian Federation, containing information on the number of employed doctors and nursing staff within the framework of targeted training, as well as the planned values of targeted employment in accordance with the concluded contracts. The study period is 2022 and 2023. The total data on targeted employment of medical workers after completion of the specialty program and completion of residency in the context of the names of positions of doctors and nursing staff were analyzed. Analytical and descriptive statistics methods were used in the research process. Results. The share of doctors and nursing staff employed after completion of targeted training from the total number of medical workers in organizations located in rural areas is higher than the share of those recruited to work in urban medical organizations. On average, 1.3% of doctors and 0.21% of nursing staff are annually recruited to urban medical organizations as part of targeted employment out of the total number of the respective key medical personnel as of the end of the reporting year. In rural areas, these figures are 2.6% and 0.30%, respectively. Specialists are predominantly employed in urban medical organizations, while in rural areas – district doctors. The study revealed that in 2023 there were 128.1 target recruitments per 10,000 doctors in urban areas in a given year, and in 2022–124.8, i. e. the intensity of employment by target recruitment in urban areas increased by 2.6% in two years. In rural areas, there were 260.2 target recruitment admissions per 10,000 physicians in 2023 and 262.8 in 2022, that is, the intensity of target recruitment employment of physicians in rural areas decreased by 1% in two years. When analyzing the indicator comparatively, it is noted that in rural areas it is almost twice as high as in urban areas. Conclusions. Targeted employment of medical workers is an effective and efficient measure to attract medical personnel to organizations experiencing a shortage of them. The analysis has shown that the intensity rate of targeted employment per 10,000 physicians in urban areas of the country is lower than in rural areas, which amounted to 128.1 and 260.2, respectively. According to the results of the last two years, 60% of the doctors planned for targeted employment fulfilled their obligations, including 50% in rural areas. The main reason for the current level of employment is the failure to meet the planned indicators of targeted admission to training due to the violation of obligations by students and graduates, which requires the development of a special methodology for assessing the reasonable formation of the plan for targeted recruitment to educational organizations in the context of each medical organization. When comparing the number of vacant positions of doctors and the number of employed graduates within the framework of targeted recruitment, a significant range of the indicator among the subjects of the Russian Federation was revealed, which is presented in the interval from 1 to 29% (9.0±15.95). In this regard, it can be assumed that the number of persons employed under targeted recruitment does not depend on the additional demand for doctors and does not cover the existing deficit.

Electric Motorbike Conversion Training to Reduce Pollution and Create A Friendly Environment For Society

Electric motorbike conversion training at Vocational High Schools (SMK) and motorbike workshops in Kotabumi, North Lampung, is a strategic step to prepare future workers to face the electricity-based transportation revolution. This study aims to evaluate the impact of training on improving the technical skills of vocational school students and motorbike repair shop mechanics, as well as analyzing the contribution of training to the adoption of environmentally friendly technology at the local level. The training method includes theoretical exposure, field practice sessions, and case studies to provide an in-depth understanding of electric motor conversion. Evaluation is carried out through practical exams and collecting feedback from participants and instructors. The research results showed a significant increase in participants' knowledge and skills regarding electric motor conversion. Adoption of this technology in local motorbike workshops is also increasing, creating the potential for reduced environmental impact and generating positive effects on the local automotive industry. The conclusion confirms that this training was successful in empowering vocational school students and motorbike repair mechanics, creating new career opportunities, and stimulating economic growth in the region. However, challenges such as adapting infrastructure and changing mindsets were also identified as areas requiring further attention. Therefore, this research provides valuable insights for further development in supporting technical education, industrial innovation and sustainability at the local level.

PSC as an organisational level determinant of working time lost and expenditure following workplace injuries and illnesses

ObjectivesFinding an association between organisational factors and working time loss following workplace injury and illness (hereafter injury) could rightfully shift the focus in injury management strategies from the individual to the organisation. We investigate whether working time loss and expenditure following compensable injury can be predicted by knowing about organisational characteristics, particularly the Psychosocial Safety Climate (PSC) − the organisation’s climate for worker psychological health. MethodsOur prospective multisource study linked ‘objective’ reports of working conditions assessed in an independent Australian Workplace Barometer (AWB) sample (random population interviews of 1067 workers) to future workers compensation claims data held by a government safety regulator, by aggregating both data sets to the organisational (employer) level. We selected compensation data prior to big policy changes to a short tail scheme. We selected claims with working time loss due to injury or illness ≥1 day yielding 100 organisations and 12,624 claims. ResultsResults support organisational PSC as a leading indicator of future time loss and expenditure, and its effect was mediated through skill discretion, job satisfaction, and rewards. Decision authority, supervisory support, and bullying were also related to time loss but not as strongly as PSC. In very low PSC organisations, days lost were 160 % higher than for those in high PSC organisations (177 vs 68 days). Likewise, expenditure for the injury or illness (e.g., health expenses, wages) was 104 % higher in very low PSC vs high PSC organisations (AUD $67 260 vs $32 939). ConclusionPSC is a modifiable social determinant of injured workers working time loss and expenditure. Practically, it is essential to target PSC for safety improvement — beyond injury prevention PSC is important for return to work and to prevent the shift of the burden of organisational problems to the individual and public health.

Measurement of visual function in infantile nystagmus: a systematic review

Background/aimsRecent work has called into question the ability of visual acuity (VA) to accurately represent changes in visual function in infantile nystagmus (IN). This systematic review investigated factors affecting visual...

Формирование профессионально значимых стереотипов и речевого поведения будущего врача в мультикультурном пространстве вуза

This article examines the process of shaping professional attitudes of future medical specialist within the framework of an open cultural space and the medicalization of culture. Among these attitudes are communicative competence, a tolerant attitude towards patients from diverse cultures, their attitudes towards medicine and health, and their manner of communication with healthcare professionals. The authors emphasize that a medical university serves as a model of an open cultural space, which facilitates the development of necessary attitudes and skills for professional activity. It is demonstrated that within the educational context of a medical university, skills in physician-patient communication must be cultivated. The special role of the university in the development of students’ communicative competence and formation of communicative personality of future medical worker is emphasized. Through intentional curriculum design and experiential learning opportunities, students are empowered to become competent and compassionate medical professionals capable of providing high-quality care to patients from diverse cultural backgrounds. Keywords: professional

Knowledge of Health Students Regarding Nutritional Deficiencies in Patients With Celiac Disease in Jazan Region: A Cross-Sectional Study.

In Saudi Arabia, the prevalence of celiac disease (CeD) was 2.7% greater than the global pooled prevalence of 1.4%. Patients who strictly adhere to a lifetime gluten-free diet (GFD) may develop nutritional deficiencies potentially contributing to obesity, increased cardiovascular risk, and lower bone density. Therefore, this study aims to assess the knowledge of health students in the Jazan region regarding nutritional deficiencies in patients with CeD who are on a GFD and to determine the associated socio-demographic factors. A descriptive cross-sectional study was conducted among health college students of Jazan University, including students from the College of Medicine, Pharmacy, Nursing, Dentistry, Public Health and Health Informatics, and Allied Health Sciences, aged 18 and above, excluding internship students, students who did not complete the survey, and those who refused to participate. The minimum calculated sample size was 368. The questionnaire was adopted from the literature and translated into Arabic.It contained a socio-demographic section and a knowledge section that included 12 questions focusing on the content of macro- and micronutrients in a GFD and the impact of the diet on the health of patients with CeD. The study included 369 participants, with 235 (64%) aged 17-22, 280 (76%) being females, and 341 (92%) being single. The College of Medicine and the College of Applied Medical Sciences had the highest representation, and the College of Dentistry was the lowest. Most participants were in the fourth year (30%) and sixth year (24%). The grade point average (GPA)had a median of 4.3. Approximately 59.1% were aware of nutritional deficiencies among CeD patients. None of the sociodemographic factors were associated with health students' knowledge regarding CeD. Participants from the College of Pharmacy had a lower knowledge of CeD nutrient deficiencies than those from the College of Medicine. (OR: 0.45, 95% CI: 0.22, 0.90). Most students stated that CeD patients should be advised to take multivitamin drugs and vitamin D supplements. Most acknowledged vitamin D, vitamin B12, and folic acid deficiencies in CeD patients. Similarly, most were aware of iron and calcium deficiencies, with a small percentage aware of zinc and copper. Approximately 59.1% had an acceptable level of knowledge, which is considered a low knowledge level among students who will be future physicians and healthcare workers to whom CeD will represent the first-line disease exposed to. Rising knowledge and awareness among those students will guarantee correct diagnosis, treatment, and better outcomes among CeD patients, thus decreasing the disease burden and increasing the quality of those patients.

The perspectives of first-year students on interprofessional education as a vehicle for achieving Sustainable Development Goal 3

Background. The 2030 Agenda for Sustainable Development is a blueprint for world peace and prosperity. The 17 Sustainable Development Goals (SDGs) in the agenda are to be met by the governments of both developed and developing countries. Interprofessional education (IPE) may be regarded as a mechanism for achieving SDG 3. Objectives. To investigate how students perceive an interprofessional first-year curriculum that contributes to the accomplishment of SDG 3. Methods. The study design was focused on consensus-building strategies. The students’ perceptions of the IPE part of the first-year module were measured on a 4-point Likert scale. Results. Students agreed that the content in the interprofessional module is suitable to promote teamwork skills and learning. There was no consensus regarding their understanding of the role of their own profession in an interprofessional team. Participants agreed that IPE helps students learn, encourages teamwork, and is good for both patients and themselves as future healthcare workers. Conclusion. IPE in health professions education has many benefits and can be seen as a vehicle to reach SDG 3, which aims to improve the health and wellbeing of all people at all ages.

Generating Python Type Annotations from Type Inference: How Far Are We?

In recent years, dynamic languages such as Python have become popular due to their flexibility and productivity. The lack of static typing makes programs face the challenges of fixing type errors, early bug detection, and code understanding. To alleviate these issues, PEP 484 introduced optional type annotations for Python in 2014, but unfortunately, a large number of programs are still not annotated by developers. Annotation generation tools can utilize type inference techniques. However, several important aspects of type annotation generation are overlooked by existing works, such as in-depth effectiveness analysis, potential improvement exploration, and practicality evaluation. And it is unclear how far we have been and how far we can go. In this paper, we set out to comprehensively investigate the effectiveness of type inference tools for generating type annotations, applying three categories of state-of-the-art tools on a carefully-cleaned dataset. First, we use a comprehensive set of metrics and categories, finding that existing tools have different effectiveness and cannot achieve both high accuracy and high coverage. Then, we summarize six patterns to present the limitations in type annotation generation. Next, we implement a simple but effective tool to demonstrate that existing tools can be improved in practice. Finally, we conduct a controlled experiment showing that existing tools can reduce the time spent annotating types and determine more precise types, but cannot reduce subjective difficulty. Our findings point out the limitations and improvement directions in type annotation generation, which can inspire future work.

Factors Associated with Costly Hospital Care among Patients with Dementia and Acute Respiratory Failure.

Rationale: Understanding contributors to costly and potentially burdensome care for patients with dementia is of interest to healthcare systems and may facilitate efforts to promote goal-concordant care. Objective: To identify risk factors, in particular whether an early goals-of-care discussion (GOCD) took place, for high-cost hospitalization among patients with dementia and acute respiratory failure. Methods: We conducted an electronic health record-based retrospective cohort study of 298 adults with dementia hospitalized with respiratory failure (receiving ⩾48 h of mechanical ventilation) within an academic healthcare system. We collected demographic and clinical characteristics, including clinical markers of advanced dementia (weight loss, pressure ulcers, hypernatremia, mobility limitations) and intensive care unit (ICU) service (medical, surgical, neurologic). We ascertained whether a GOCD was documented within 48 hours of ICU admission. We used logistic regression to identify patient characteristics associated with high-cost hospitalization measured using the hospital system accounting database and defined as total cost in the top third of the sample (⩾$145,000). We examined a path model that included hospital length of stay as a final mediator between exposure variables and high-cost hospitalization. Results: Patients in the sample had a median age of 71 (IQR, 62-79) years. Approximately half (49%) were admitted to a medical ICU, 29% to a surgical ICU, and 22% to a neurologic ICU. More than half (59%) had a clinical indicator of advanced dementia. A minority (31%) had a GOCD documented within 48 hours of ICU admission; those who did had a 50% lower risk of a high-cost hospitalization (risk ratio, 0.50; 95% confidence interval, 0.2-0.8). Older age, limited English proficiency, and nursing home residence were associated with a lower likelihood of high-cost hospitalization, whereas greater comorbidity burden and admission to a surgical or neurologic ICU compared with a medical ICU were associated with a higher likelihood of high-cost hospitalization. Conclusions: Early GOCDs for patients with dementia and respiratory failure may promote high-value care by ensuring aggressive and costly life support interventions are aligned with patients' goals. Future work should focus on increasing early palliative care delivery for patients with dementia and respiratory failure, in particular in surgical and neurologic ICU settings.

Head Kinematics and Injury Analysis in Elite Bobsleigh Athletes Throughout a World Cup Tour.

The neurocognitive health effects of repetitive head impacts have been examined in many sports. However, characterizations of head impacts for sliding-sport athletes are lacking. To describe head impact kinematics and injury epidemiology in elite athletes during the 2021-2022 Bobsleigh World Cup season. Cross-sectional study. On-track training and competitions during the Bobsleigh World Cup season. Twelve elite bobsleigh athletes (3 pilots [1 female], 9 push athletes [5 females]; age = 30 ± 5 years; female height and weight = 173 ± 8 cm and 75 ± 5 kg, respectively; male height and weight = 183 ± 5 cm and 101 ± 5 kg, respectively). Athletes wore an accelerometer-enabled mouthguard to quantify 6-degrees-of-freedom head impact kinematics. Isometric absolute and relative neck strength, number of head acceleration events (HAEs), workload (J), peak linear velocity (m·s-1), peak angular velocity (rad·s-1), peak linear acceleration (g), and peak angular acceleration (rad·s-2) were derived from mouthguard manufacturer algorithms. Linear mixed-effect models tested the effects of sex (male versus female), setting (training versus competition), and position (pilot versus push athlete) on the kinematic variables. A total of 1900 HAEs were recorded over 48 training and 53 competition days. No differences were found between the number of HAEs per run per athlete by sex (incidence rate ratio [IRR] = 0.82, P = .741), setting (IRR = 0.94, P = .325), or position (IRR = 1.64, P = .463). No sex differences were observed for workload (mean ± SD: males = 3.3 ± 2.2 J, females = 3.1 ± 1.9 J; P = .646), peak linear velocity (males = 1.1 ± 0.3 m·s-1, females = 1.1 ± 0.3 m·s-1; P = .706), peak angular velocity (males = 4.2 ± 2.1 rad·s-1, females = 4.7 ± 2.5 rad·s-1; P = .220), peak linear acceleration (male = 12.4 ± 3.9g, females = 11.9 ± 3.5g; P = .772), or peak angular acceleration (males = 610 ± 353 rad·s-2, females = 680 ± 423 rad·s-2; P = .547). Also, no effects of setting or position on any kinematic variables were seen. Male athletes had greater peak neck strength than female athletes for all neck movements, aside from right-side flexion (P = .085), but no sex differences were noted in relative neck strength. We provide a foundational understanding of the repetitive HAEs that occur in bobsleigh athletes. Future authors should determine the effects of repetitive head impacts on neurocognitive function and mental health.

Towards Faithful Model Explanation in NLP: A Survey

Abstract End-to-end neural Natural Language Processing (NLP) models are notoriously difficult to understand. This has given rise to numerous efforts towards model explainability in recent years. One desideratum of model explanation is faithfulness, that is, an explanation should accurately represent the reasoning process behind the model’s prediction. In this survey, we review over 110 model explanation methods in NLP through the lens of faithfulness. We first discuss the definition and evaluation of faithfulness, as well as its significance for explainability. We then introduce recent advances in faithful explanation, grouping existing approaches into five categories: similarity-based methods, analysis of model-internal structures, backpropagation-based methods, counterfactual intervention, and self-explanatory models. For each category, we synthesize its representative studies, strengths, and weaknesses. Finally, we summarize their common virtues and remaining challenges, and reflect on future work directions towards faithful explainability in NLP.