Source-free collaborative domain adaptation via multi-perspective feature enrichment for functional MRI analysis.

Resting-state functional MRI (rs-fMRI) is increasingly employed in multi-site research to analyze neurological disorders, but there exists cross-site/domain data heterogeneity caused by site effects such as differences in scanners/protocols. Existing domain adaptation methods that reduce fMRI heterogeneity generally require accessing source domain data, which is challenging due to privacy concerns and/or data storage burdens. To this end, we propose a source-free collaborative domain adaptation (SCDA) framework using only a pretrained source model and unlabeled target data. Specifically, a multi-perspective feature enrichment method (MFE) is developed to dynamically exploit target fMRIs from multiple views. To facilitate efficient source-to-target knowledge transfer without accessing source data, we initialize MFE using parameters of a pretrained source model. We also introduce an unsupervised pretraining strategy using 3,806 unlabeled fMRIs from three large-scale auxiliary databases. Experimental results on three public and one private datasets show the efficacy of our method in cross-scanner and cross-study prediction.

Multipath collaboration-based signal amplification on Z-scheme In2O3/g-C3N4 heterojunction photoelectrode for sensitive photoelectrochemical immunoassay.

The ideal photoelectrode and efficient signaling strategy are pivotal to achieve sensitive photoelectrochemical (PEC) analysis. Here, a multipath collaborative signal amplification-based PEC immunosensor was constructed for the ultrasensitive detection of cytokeratin 19 fragment 21-1. Specifically, the photoelectrode fabricated by Z-scheme In2O3/g-C3N4 heterojunction showed enhanced photocurrent intensity in response to visible light. Meanwhile, the signal probe, horseradish peroxidase functionalized dopamine-melanin nanosphere@Au nanoparticles (HRP-Dpa-melanin NS@AuNPs), were introduced into the system. When the target exists, the signal probe can induce multiple quenching of the photocurrent due to the competition of light absorption, steric hindrance and HRP-mediated biocatalytic precipitation, which effectively inhibit light, electron donor, and electron access to the photoelectrode. The fabricated immunosensor exhibits a wide linear range from 1.0 × 10-3 - 1.0 × 102 ng mL-1 with the detection limit of 0.35 pg mL-1 (S/N = 3) for cytokeratin 19 fragment 21-1 detection. The study enhances sensitivity for PEC detection by utilizing the superior Z-scheme heterojunction photoelectrode, providing a valuable method that combines multiple signal pathways for a synergistic effect in bioanalysis.

Peering into the team role kaleidoscope: the interplay of personal characteristics and verbal interactions in collaborative problem solving.

The objective of this study is to explore the relationship between personality and peer-rated team role behavior on the one hand and team role behavior and verbal behavior on the other hand. To achieve this, different data types were collected in fifteen professional teams of four members (N = 60) from various private and public organizations in Flanders, Belgium. Participants' personalities were assessed using a workplace-contextualized personality questionnaire based on the Big Five, including domains and facets. Typical team role behavior was assessed by the team members using the Team Role Experience and Orientation peer rating system. Verbal interactions of nine of the teams (n = 36) were recorded in an educational lab setting, where participants performed several collaborative problem-solving tasks as part of a training. To process these audio data, a coding scheme for collaborative problem solving and linguistic inquiry and word count were used. We identified robust links and logical correlation patterns between personality traits and typical team role behaviors, complementing prior research that only focused on self-reported team behavior. For instance, a relatively strong correlation was found between Altruism and the Team builder role. Next, the study reveals that role taking within teams is associated with specific verbal interaction patterns. For example, members identified as Organizers were more engaged in responding to others' ideas and monitoring execution.

Predicting collaborative practice between midwives and obstetricians: A regression analysis.

INTRODUCTION: Effective collaborative practice between midwives and obstetricians improves patient safety and obstetrical outcomes, but its implementation remains challenging. Therefore, its determinants need to be better understood. This study examined factors impacting collaborative practice (CP) between these professional groups. METHODS: This study was a cross-sectional survey that took place in Swiss hospital labor wards in 2021. Collaborative practice perceptions of 70 midwives (57.4% response rate) and 44 obstetricians (29.0% response rate) were assessed using the Interprofessional Collaboration Scale, with the score serving as the main outcome. A total of 13 individual, behavioral, and organizational predictors were analyzed by multiple linear regression. RESULTS: Participants rated collaborative practice with a median score of 3.1 (IQR: 2.8-3.4) out of a maximum score of 4.0. Results showed that five predictors significantly influenced collaborative practice: type of profession (ß= -0.180; 95% CI: -0.296 - -0.040, p=0.011), trust/respect (ß=0.343; 95% CI: 0.085-0.040, p=0.000), shared visions/goals (ß=0.218; 95% CI: 0.030-0.204, p=0.009), workplace (ß=0.253; 95% CI: 0.089-0.445, p=0.004) and shared power (ß=0.163; 95% CI: 0.042-0.222, p=0.015). The model explained 66% of the variance (adjusted R2) in collaborative practice in labor wards. CONCLUSIONS: This study has identified key factors influencing CP in Swiss labor wards: workplace characteristics that require tailored CP models, and a power-sharing culture that fosters trust, respectful interactions and shared goals, requiring active exchange between midwives and obstetricians.

Rain Gardens and Rain Gauges: Students Get Hands on With Data While Evaluating Green Infrastructure at Their School.

Two modules were designed for high school science students to investigate the performance of a rain garden installed on school property. The rain garden, a green infrastructure system which allows soil infiltration, was installed to reduce impacts to urban streams and can increase the community's resilience to flooding. By involving students in the analysis of this mitigation strategy, students learned new technical skills, gained varied experiences in collecting and analyzing data, were exposed to new STEM careers, and learned about local issues that impact their community while collaborating with local professionals. In each module, students used their authentic data to address research questions. In the first module, students conducted a land survey and calculated the volumetric capacity of the rain garden. In the second module, students collected rainfall data using rain gauges and analyzed various aspects of rainfall collection. Although these modules were focused on a rain garden already installed on school property, they can be implemented at schools without this mitigation strategy present. The surveying module can easily be applied to measure any land surface feature, and the rain gauge module can be implemented anywhere as it is focused on rainfall collection.

Perceptions and influencing factors of interprofessional collaboration in final-year health science students.

Interprofessional education (IPE) is vital for preparing a competent health workforce. Despite the proven benefits of interprofessional collaborative practice (IPCP), barriers to its implementation persist. Given the importance of health professionals' perspectives for IPCP success, we investigated the perceptions of IPCP among final-year health science students at Khon Kaen University, Thailand, while they transition into practice. A cross-sectional online survey conducted from February to April 2023 included 989 students across six health science disciplines, with a response rate of 57.8%. Using the SPICE-R2 questionnaire on a five-point Likert-type scale, we assessed perceptions related to interprofessional teamwork, roles and responsibilities, and patient outcomes. Results showed significant diversity in IPCP perceptions and experiences with IPE. Nursing students consistently demonstrated the highest IPCP perceptions, while medical and public health students scored the lowest. Positive perceptions about IPCP were notably associated with nursing students and those satisfied with the learning process. Dentistry students and those with IPE experience also exhibited more favorable views on teamwork. This study suggests the need to address disparities in IPCP perceptions among student groups, which is essential for enhancing interprofessional collaboration in future health professionals.

Epidemiology and survival of primary intracranial malignant tumor patients with drop metastasis: a population-based analysis.

BACKGROUND: Drop metastasis significantly impacts the survival of patients with primary intracranial malignant tumors. Using the information of collaborative stage from the SEER database, we aim to analyze the epidemiology and prognosis of primary intracranial malignant tumor patients with drop metastasis. METHODS: We analyzed the distribution of patients and the frequency according to the demography and clinical characteristics of patients with drop metastasis. We also analyzed the survival of these patients with drop metastasis. Multivariate Cox proportional hazards models were used to analyze possible prognostic indicators. RESULTS: A total of 56,839 cases with primary intracranial malignant tumors were ultimately included in this cohort study. A total of 792 cases were confirmed to have drop metastasis. The average rate of drop metastasis was 1.4%. Most of the patients with drop metastases were diagnosed before ten years old. The three most common primary intracranial malignant tumors with drop metastasis were glioblastoma, embryonal/primitive/medulloblastoma, and anaplastic astrocytoma. Embryonal/primitive/medulloblastoma had the highest drop metastasis rate, at 11.6%. Tumors located in the infratentorial space and ventricles had a higher rate of drop metastasis than tumors in other locations. The prognosis for patients with drop metastasis is poor. Routine complete treatment (surgery of the primary tumor plus chemoradiotherapy) can significantly improve overall survival. CONCLUSION: We conducted a population-based analysis of primary intracranial malignant tumor patients with drop metastasis. Our study can help clinicians acquire general information on the epidemiology and survival of primary intracranial malignant tumor patients with drop metastasis.

Results of a randomized controlled superiority trial of the effect of modified collaborative assessment vs. standard assessment on patients' readiness for psychotherapy (CO-ASSM-RCT).

BACKGROUND: Avoidant personality disorder (AvPD) and social phobia (SP) are associated with high personal and societal costs. While psychotherapy can be efficient, many patients drop out during treatment. Little is known about what can be done to increase a patient's readiness for psychotherapy. However, research highlights the fields of collaborative and therapeutic assessment as a possible means to enhance readiness for psychotherapy. METHODS: We conducted a randomized controlled feasibility and superiority trial on patients with SP or AvPD who were to initiate psychotherapeutic treatment in outpatient mental health services. Patients were randomized 1:1 to either assessment as usual or modified collaborative assessment (MCA), provided as a pre-treatment intervention before psychotherapy initiation. MCA included the collaborative administration of a battery of psychological tests designed to assess the patient's psychopathology more systematically. The tests were administered in collaboration with the patient, and detailed oral and written feedback was provided. We investigated the feasibility of the MCA intervention regarding acceptability, patient satisfaction, and adherence. We also investigated MCA's effect on readiness for psychotherapy, as assessed with the University of Rhode Island Change Assessment Scale (URICA), and outcomes relating to symptomatology and dropout rates. RESULTS: All three prespecified feasibility outcomes were met. At the end of treatment, no significant difference was observed in any other outcome, except client satisfaction, which favored MCA (- 7.42 (95% CI - 11.75; - 3.09; p = 0.002)). DISCUSSION: We found that MCA was feasible, and patients were highly satisfied with the intervention. It is relevant to investigate another implementation of MCA. TRIAL REGISTRATION: ClinicalTrials.gov NCT05018312. Registered on August 24, 2021.

Modeling collaborative memory with SAM.

While humans often encode and retrieve memories in groups, the bulk of our knowledge of human memory comes from paradigms with individuals in isolation. The primary phenomenon of interest within the relatively new field of collaborative memory is collaborative inhibition: the tendency for collaborative groups to underperform in free recall tasks compared with noncollaborative groups of the same size. This effect has been found in a variety of materials and group compositions. However, most research in this field is led by verbal conceptual theories without guidance from formal computational models. We present a framework to scale the Search of Associative Memory model (SAM) to collaborative free recall paradigms with multiple models working together. Multiple SAM models recalling together naturally produce collaborative inhibition when the group members use recalls by the group as cues to retrieve from memory, strongly supporting the "retrieval disruption" hypothesis. This work shows that SAM can act as a unified theory to explain both individual and collaborative memory effects and offers a framework for future predictions of scaling to increased group sizes, shared knowledge, and factors facilitating the spread of false memories in groups.

Development and implementation of learning collaboratives for infection prevention and control education in long-term care facilities.

Infections in long-term care facilities pose a critical challenge, with 1 to 3 million serious infections annually and up to 380,000 associated deaths. The vulnerability of aging populations and inadequate infection prevention and control programs underscore the need for intervention. This initiative provided tailored continuing education through 8 virtual learning collaboratives serving 541 infection preventionists. The project also developed 9 infection prevention and control toolkits and a manual to further support long-term care facilities' infection prevention efforts.

Effectiveness of a task-sharing collaborative care model for the detection and management of depression among adults receiving antiretroviral therapy in primary care facilities in South Africa: A pragmatic cluster randomised controlled trial.

BACKGROUND: HIV is characterised by high rates of comorbidity with mental health conditions including depression, as such, the detection and treatment of comorbid depression is critical to achieve viral load suppression. This study evaluated the effectiveness of a collaborative care intervention for depression among adults with comorbid depression symptoms receiving ART in primary health care (PHC) facilities. METHODS: We conducted a pragmatic cluster-randomised trial in 40 clinics in the North West province of South Africa. PHC clinics were stratified by sub-district and randomised in a 1:1 ratio. Participants were ≥ 18 years, receiving ART, and had depression symptoms indicated by Patient Health Questionnaire-9 (PHQ-9) score ≥ 9. Intervention clinics received: i) supplementary mental health training and clinical communication skills for PHC nurses; ii) workshops for PHC doctors on treating depression; and iii) lay counselling services. Using mixed effects regression models, we assessed co-primary outcomes of PHQ-9 response at 6 months (≥50 % reduction in baseline PHQ-9 score) and viral load suppression at 12 months (viral load<1000 copies/mL). RESULTS: The intervention had no effect in PHQ-9 response (49 % vs 57 %, risk difference (RD) = -0.08, 95 % CI = -0.19; 0.03, p = 0.184) or viral load suppression (85 % vs 84 %, RD = 0.02, 95 % CI = -0.01; 0.04, p = 0.125). Nurses referred 4298 clinic patients to counsellors, however, only 66/1008 (7 %) of intervention arm participants were referred to counsellors at any point during the study. LIMITATIONS: The highly pragmatic approach of this trial limited exposure to the counselling component of the intervention and referral to doctors for initiation of antidepressant treatment was extremely low. CONCLUSION: The trial showed no effect of a district-based intervention to strengthen collaborative care for depression. The trial revealed the extent of the treatment gap in the context of scaling up mental health services. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02407691); Pan African Clinical Trials Registry (201504001078347).

Achieving collaborative pollutant and carbon emissions reduction through digital governance: Evidence from Chinese enterprises.

Under China's dual carbon goals, it is imperative for enterprises to effectively reduce carbon emissions while achieving pollutant reduction. This article explores the potential role of government-implemented digital governance in facilitating these objectives. Utilizing a quasi-natural experiment on digital governance, we established an analytical framework to thoroughly examine how digital governance can help Chinese enterprises realize synergistic effects in pollution control and carbon reduction. Our study reveals that digital governance significantly reduces enterprises' emissions of carbon dioxide and pollutants, with emission intensities of the carbon dioxide, air pollutant and water pollutant being decreased by approximately 6.9%, 7.3%, and 7.0%, respectively. These reductions are primarily driven by improvements in energy efficiency, the promotion of green innovation, digital transformation, and enhanced role of media. However, it is important to note that digital governance also negatively impacts overall corporate productivity and widens the digital divide between large and small-to-medium enterprises. The research results have practical significance for promoting the achievement of emission reduction goals and sustainable development for enterprises.

Medical and pharmaceutical activities in occupied territories: legal assessment and Ukraine's experience.

International armed conflicts often involve the occupation of territories of the state under aggression, where some of the population begins to voluntarily cooperate with the enemy. Currently, under the legislation of certain EU countries, such actions may be deemed collaboration or treason. This article examines the scenarios faced by medical or pharmaceutical workers in occupied territories, using the example of Ukraine, which is currently experiencing armed aggression from the Russian Federation. Despite the declared norms of International Humanitarian Law (IHL), medical and pharmaceutical workers find themselves in quite difficult situations. They have taken an oath and have obligations under the Geneva Conventions and Additional Protocols, and thus are required to continue performing their professional duties during the occupation and are de jure granted medical neutrality. However, they also face limited resources, pressure, and, in some cases, their duties may involve illegal actions that could lead to legal responsibility. The study identifies when medical and pharmaceutical activities are lawful during occupation and when they may constitute unlawful behaviour that results in legal accountability. The authors conclude that the current policies of Russia and its occupation authorities deliberately violate IHL norms. Furthermore, they intentionally create conditions where individuals in occupied territories commit actions that will be recognized as crimes. It is based on dialectical, analytic, synthetic, comprehensive methods, and also uses the case-method and the method of content analysis.

Project-Based Learning Adapted as a Physiology Teaching Strategy for the Sophomore Undergraduate Medical Students.

Context: Project-based learning (PBL) is a teaching strategy in which students work as a group to identify a problem and discuss ideas for its solution. It is an educational approach to teaching and learning that involves groups of students working together to solve a problem, complete a task, or even create a product based on a project. It places the student at the center of the teaching-learning process and stimulates their engagement to transform learning into knowledge. Proposal: The aim of the present study was to use an adapted PBL approach as a physiology teaching strategy for sophomore medical students. For this, at the end of the semester, 148 students were organized in groups and were instructed to develop projects on the topics of cardiorespiratory physiology and metabolic physiology. Evaluation was made of the development and presentation of the projects, comparing the grades with those obtained in tests taken individually by the students at the beginning of the semester. The opinions of the students about the strategy were analyzed using a questionnaire answered individually. The results showed that different strategies were developed by the students to present their projects, notably employing question and answer board games, card games, and videos simulating interviews with clinicians. The mean scores for the collaborative group activities were significantly higher than for the tests performed individually by the students. The answers given in the opinion questionnaire indicated that most of the students considered the strategy useful for their learning, since it stimulated research, study, and discussion on the topics studied. Most of the students believed that working as a group was beneficial and that the time allocated for the project development was sufficient. Conclusion: Therefore, use of the adapted project-based learning as a physiology teaching strategy was viewed positively by the students and improved their performance in learning about cardiorespiratory and metabolic physiology. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-024-02092-y.

Personalized movie recommendation in IoT-enhanced systems using graph convolutional network and multi-layer perceptron.

Exploring the optimization of communication strategies for animation films in the context of cross-cultural communication, this research integrates the Internet of Things (IoT) and convolutional networks. The research constructs a collaborative filtering (CF) movie recommendation model based on a graph convolutional neural network (GCN) and investigates its application in cross-cultural communication. The fusion of IoT and convolutional networks in movie communication is also analyzed, and the effectiveness of the proposed GCN-CF model is validated through comparative experiments. The results indicate that, compared to other models, the GCN-CF model achieves the lowest Root Mean Square Error (RMSE) on the MovieLens 100 K and MovieLens 1 M datasets, with values of 0.8762 and 0.8275, respectively. Compared to traditional models, the GCN-CF model exhibits significantly superior performance in terms of RMSE, with reductions ranging from 0.6 to 5.2%, highlighting its heightened detection accuracy and overall performance. Moreover, the performance of the GCN-CF model is enhanced after introducing attention mechanisms and auxiliary information on both datasets, showing an improvement of 0.4% compared to the scenario without these additions. This data demonstrates the effectiveness of attention mechanisms and auxiliary information. Finally, the research presents an animation film communication strategy based on IoT and convolutional networks, offering novel insights for film production and communication, along with positive implications for cultural exchange and the advancement of the global media industry.

Knowing, Being and Becoming a Person-Centred Nurse Leader: Findings from a Transformative Professional Development Programme.

Background/Objectives Leadership is central to the development of effective workplace cultures and as such should be viewed as a practice that is relational, exercised through a process of mutual and reciprocal influence. Person-centred leadership is an approach to leadership that supports a way of being that is authentic, prioritising values lived out in action. However, there is an increasing recognition that leadership development has not been impactful in relation to workplace culture. This paper reports on the ongoing evaluation of an innovative development programme (Queen's Nurse Development Programme), the overall aim of which was to illuminate the participants' experiences of engaging in transformative learning and development and identify the technical and transformative outcomes arising. The programme focused on developing leadership capacity for societal change and maximising the health impact of community nursing leaders. Methods The methodological framework for evaluation was underpinned by a Collaborative Critical Creative Inquiry. Twenty community nurses were selected to undertake the programme during 2020. The collection and analysis of data was consistent with the Collaborative Critical Creative Inquiry and was conducted as a one-day workshop, with participants engaged in a cycle of creative hermeneutic analysis. Results A total of seven themes were identified, including: sense of belonging; personal growth; developing new skills; finding voice; importance of self-care; and creating a safe place. This illuminated how the transformative learning and development processes within this programme were experienced and how these enabled participants to explore how they influence their practice and workplace. It is the journey with self that generates a sense of belonging and enables personal growth and the ability to care for self and others. Conclusions The key learning from this innovative development programme is the importance of focusing on the attributes of practitioners and the key building blocks for knowing, being, and becoming a person-centred practitioner.

Canadian National Pancreas Conference 2023: A Review of Multidisciplinary Engagement in Pancreatic Cancer Care.

Pancreatic cancer is a complex malignancy associated with poor prognosis and high symptom burden. Optimal patient care relies on the integration of various sectors in the healthcare field as well as innovation through research. The Canadian National Pancreas Conference (NPC) was co-organized and hosted by Craig's Cause Pancreatic Cancer Society and The Royal College of Physicians and Surgeons in November 2023 in Montreal, Canada. The conference sought to bridge the gap between Canadian healthcare providers and researchers who share the common goal of improving the prognosis, quality of life, and survival for patients with pancreatic cancer. The accredited event featured discussion topics including diagnosis and screening, value-based and palliative care, pancreatic enzyme replacement therapy, cancer-reducing treatment, and an overview of the current management landscape. The present article reviews the NPC sessions and discusses the presented content with respect to the current literature.

MSAO-EDA: A Modified Snow Ablation Optimizer by Hybridizing with Estimation of Distribution Algorithm.

Metaheuristic algorithms provide reliable and effective methods for solving challenging optimization problems. The snow ablation algorithm (SAO) performs favorably as a physics-based metaheuristic algorithm. Nevertheless, SAO has some shortcomings. SAO is overpowered in its exploitation, has difficulty in balancing the proportion of global and local search, and is prone to encountering local optimum traps when confronted with complex problems. To improve the capability of SAO, this paper proposes a modified snow ablation algorithm hybrid distribution estimation algorithm named MSAO-EDA. In this work, a collaborative search framework is proposed where SAO and EDA can be organically integrated together to fully utilize the exploitation capability of SAO and the exploration capability of EDA. Secondly, an offset EDA approach that combines the optimal solution and the agent itself is used to replace SAO's exploration strategy for the purpose of enhancing SAO's exploration capability. Finally, the convergence of SAO is accelerated by selecting the next generation of agents through a greedy strategy. MSAO-EDA is tested on the CEC 2017 and CEC 2022 test suites and compared with EO, RIME, MRFO, CFOA, and four advanced algorithms, AFDBARO, CSOAOA, EOSMA, and JADE. The experimental results show that MSAO-EDA has excellent efficiency in numerical optimization problems and is a highly competitive SAO variant.

Health Professions Students' Reflections About Principles of Interprofessional Collaboration after Shadowing Interprofessional Palliative Care Rounds.

Future healthcare professionals are educated on collaborative practice methods through interventions that may include shadowing. While shadowing allows students to learn from and about other health professions, it often fails to offer an opportunity for the student to work and collaborate with other health professionals. This study sought to investigate themes regarding interprofessional students' experiences during a palliative care shadowing activity and their understanding of collaborative patient-centered care, social determinants of health, and health disparities. Twenty-eight students representing 13 health professions from the Interprofessional Palliative Care program at Jefferson Center for Interprofessional Practice and Education at Thomas Jefferson University submitted reflection essays at the conclusion of their shadowing experience. Four hundred ninety-eight sentences from 28 essays were analyzed via qualitative directed content analysis. Coding categories were determined a priori using definitions of collaborative practice from the 2023 Interprofessional Education Collaborative (IPEC) competencies and definitions of social determinants of health from Healthy People 2030. Thirty-two percent of sentences described IPEC competencies, 18% described social determinants of health/ health disparities, 4% included student emotional reactions, and 2% included student descriptions of the development of their professional role. These results suggest that shadowing offers an opportunity to identify and learn interprofessional competencies in interprofessional palliative care curricula, as made evident through student reflection assignments.

Collaborative Filtering for the Imputation of Patient Reported Outcomes.

This study addresses the prevalent issue of missing data in patient-reported outcome datasets, particularly focusing on head and neck cancer patient symptom ratings sourced from the MD Anderson Symptom Inventory. Given that many data mining and machine learning algorithms necessitate complete datasets, the accurate imputation of missing data as an initial step becomes crucial. In this study we propose, for the first time, the use of collaborative filtering for imputing missing head and neck cancer patient symptom ratings. Two configurations of collaborative filtering, namely patient-based and symptom-based, leverage known ratings to infer the missing ones. Additionally, this study compares the performance of collaborative filtering with alternative imputation methods such as Multiple Imputation by Chained Equations, Nearest Neighbor Imputation, and Linear interpolation. Performance is compared using Root Mean Squared Error and Mean Absolute Error metrics. Findings demonstrate that collaborative filtering is a viable and comparatively superior approach for imputing missing patient symptom data.