Management Unit Research Articles

Delimitation of Differentiated Management Units (DMUs) based on productivity maps, slope maps and vegetation indices

According to several projections, the planet's demographic density will continue to increase in the coming decades, a fact that makes it necessary to increase food production to meet population demand. However, there are factors that can make it difficult to achieve production goals, such as the high cost of inputs. Therefore, aiming to increase productivity and reduce costs through optimizing the use of resources and the area available for production, it is necessary to implement alternatives to traditional production control methods. In this aspect, precision agriculture stands out. For precision agriculture to be applied to crops, it is first necessary to observe the spatial and temporal variability of the area, through georeferenced data on the attributes that involve the production system. The correlation of these attributes can indicate sub-regions within the production areas that can receive homogeneous treatment; these fractions of the area can also be called Differentiated Management Units (DMUs). Therefore, the objective of this study was to evaluate the viability of DMU delimitations using data on productivity, slope and vegetation indices, referring to the 2020 harvest for corn cultivation. To this end, geoprocessing of the data obtained using the QGIS software was carried out, so that 3 DMUs were generated for the area evaluated in the study. Thus, the DMUs were compared with the 2021 corn harvest. The results show that the DMUs, produced with data from the 2020 corn harvest, delimited regions with different productivity data in the 2021 harvest, indicating that the possibility of obtaining better parameters in production if differentiated management were carried out in the field, and such planning can be carried out based on the assessments that DMUs allow to be carried out.

Impact of Supply Chain Agility and Collaboration on Supply Chain Performance: The Moderating Role of Artificial Intelligence

Supply chain resilience is not a novel concept in the supply chain industry; however, its significance importance is increasing, especially in the face of global disruptive events like natural and man-made disasters. Agility and collaboration are critical supply chain resilience elements for enhancing supply chain performance. However, the influence of artificial intelligence (AI) on the impact of agility and collaboration on performance remains unexplored. Therefore, the major objective of this study was to examine the impact of supply chain agility and collaboration on supply chain performance within the healthcare sector in Qatar. In the same vein, it examined the moderating role of AI in these relationships. The study utilized 564 responses from supply chain and clinical unit managers in Qatar and was analysed using the partial least squares (PLS) path modelling technique. The findings of the study indicate a significant positive relationship between supply chain agility, collaboration, and performance. Furthermore, these relationships are found to be positively moderated by AI. This study supports the research paradigm and provides evidence regarding supply chain agility and collaboration and their impact on supply chain performance. More importantly, this study is among the first to provide empirical evidence on the moderating role of AI in enhancing these relationships.

Model predictive control with self-learning capability for automated demand response in buildings

This paper presents an optimal management strategy, called Building Optimizer, based on a Model Predictive Control (MPC) approach with self-learning capabilities for buildings. The proposed MPC is a key enabler of cooperative demand response strategies at community level, ensuring the allocation of an optimal demand profile at each participating member of the community according to an optimal consumption reference defined by a complementary agent at community level. In this way, the proposed solution can contribute to provide demand response services exploiting the unlocked residential flexibility. The MPC calculates the optimal setpoints of the HVAC system’s terminal units, considering the expected usage of the buildings and the outdoor conditions, and exploiting the building’s thermal inertia. The models embedded in the MPC are grey-box models representing a thermal zone of the building. An adaptive MPC is proposed to mitigate the high uncertainty present in building management due to the time-variant characteristics of the building and the uncertain internal heat gains due to occupancy and other disturbances. For that, the reduced models incorporate self-learning capabilities implemented as Moving Horizon Estimators that perform a continuous calibration based on real-time measurements. This solution allows full automation for model calibration and management of the terminal units. This paper presents a case study to assess the thermal comfort assurance and power flexibility provision potential of the proposed solution. First, the Building Optimizer is compared to a regular benchmark consisting of an on–off controller, evaluating the performance of each controller for indoor temperature tracking. For the assessment of the flexibility provision, a baseline MPC with fixed model parameters obtained by an offline calibration is used for comparison to the Building Optimizer with self-learning capabilities. Different flexibility scenarios are simulated, considering different restrictions regarding thermal comfort and various flexibility request signals. Notably, the Building Optimizer outperforms the baseline MPC in all scenarios, particularly guaranteeing thermal comfort. Incorporating self-learning capabilities enhances controller performance by mitigating the effect of uncertainty, allowing the Building Optimizer to shift up to 13.08% of peak periods into valley periods, and tracking a flexibility request scenario of 10% with no discomfort.

Reference genome for the endangered, genetically subdivided, northern tidewater goby, Eucyclogobius newberryi.

The federally endangered sister species, Eucyclogobius newberryi (northern tidewater goby) and E. kristinae (southern tidewater goby) comprise the California endemic genus Eucyclogobius, which historically occurred in all coastal California counties. Isolated lagoons that only intermittently connect to the sea are their primary habitat. Reproduction occurs during lagoon closure, minimizing marine dispersal and generating the most genetically subdivided vertebrate genus on the California coast. We present a new genome assembly for E. newberryi using HiFi long reads and Hi-C chromatin-proximity sequencing. The 980Mb E. newberryi reference genome has an N50 of 34Mb with 22 well-described scaffolds comprising 88% of the genome and a complete BUSCO score of 96.7%. This genome will facilitate studies addressing selection, drift, and metapopulation genetics in subdivided populations, as well as the persistence of the critically endangered E. kristinae, where reintroduction will be an essential element of conservation actions for recovery. It also provides tools critical to the recovery of the genetically distinct management units in the northern tidewater goby, as well as broader ecological and evolutionary studies of gobies, the most speciose family of fishes in the world.

Implementasi Next.Js, Typescript, Dan Tailwind Css Untuk Pengembangan Aplikasi Frontend Sistem Inventory Perusahaan Apar (Studi Kasus: CV Indoka Surya Jaya)

This research succeeded in developing an internal management system using Next.js for the integration of key features such as customer, supplier, category, unit, product, purchase and invoice management. The use of TypeScript increases code security and clarity, and ensures the system is verified through Black Box Testing. Implementing Tailwind CSS in creating company landing pages strengthens online representation with a responsive and modern design. It is hoped that this system can significantly increase operational efficiency and be adaptive to changes in company needs in the future.

A teamwork framework for preventing breaches of academic integrity and improving students’ collaborative skills in the AI era

Generative artificial intelligence (AI) tools have become a major challenge in the education sector in terms of the way that students use and manage them. This study examines the development, implementation, and evaluation of a teamwork framework by using academic integrity standards and formative feedback to minimise the use of generative AI tools in the Business Project Management (BPM) unit and promote students' learning skills through teamwork and self/peer evaluation. This teamwork assessment was designed to transform students into independent learners by improving their cultural awareness, self-confidence, teamwork, communication, leadership, as well as personal and interpersonal skills. The study's objectives are to determine whether a teamwork framework can help to maintain academic integrity and transform BPM students into independent learners and leaders in the era of generative AI, and to determine whether lecturers' formative feedback enhances students' skills in teamwork assessment. This research comprises an empirical study of 408 local and international BPM students from different cultural backgrounds. A mixed-methods approach was used to collect data and achieve a broader perspective of the research topic. BPM students reported their satisfaction with this type of assessment since it helped them acquire skills such as intercultural effectiveness and teamwork. Following the implementation of the teamwork framework, the number of instances of academic misconduct and requests for extensions have decreased dramatically, while the assessment's average marks increased by 10 %. A set of recommendations is offered that will ensure the successful implementation of the proposed framework for teamwork assessment and self/peer evaluation. This study was limited to the Business Project Management unit, but in 2024, the same study will be conducted involving other postgraduate units at Curtin University with a future rollout in other universities to compare how students perceive teamwork assessment.

Use of the value-focused thinking methodology to understand health care waste management under the perspective of occupational and environmental health

The increasing generation of healthcare waste has greatly accelerated the concern about its potential negative environmental and public health effects. In this sense, the application of decision-making methods and techniques at a strategic level has become increasingly indispensable for the management of health units. This article aimed to understand the challenges in healthcare waste management (HCWM), the main mechanisms of action and values. The Value-Focused Thinking methodology was used to evidence important gaps and propose improvements in the context of decision on occupational safety and environmental protection, leading to the creation of alternatives not seen previously and guaranteeing the good ideas would be converted into actions. The structure was developed by semi-structured questionnaires, observation lists and interviews, conducted to expose the values of the main stakeholders (managers, health professionals, and cleaning professionals) of 10 public health units selected in Caruaru (Brazil). As a result, the investigation evidenced four fundamental goals for the decision context: improvement in work and environmental safety; improvement in HCWM practices; improvement in resource management; strengthening of the stakeholder communication network. From the analysis of the attributes associated with the fundamental goals, it was possible to identify actions that should be implemented with a higher priority and, in the short term, aiming at obtaining positive results, especially in the management practices and the safe management of health waste. The study resulted from an investigation that awakened the participants about aspects little questioned in everyday life. Implementing actions to segregate and recycle materials, with data monitoring and sharing, will increase the population's trust and the environment's and professionals' safety. The alternatives derived from the VFT method consider the perspectives of key stakeholders in HCWM, helping decision-makers and policymakers develop more assertive and grounded management strategies.

Drug resistance pattern, prevalence and risk factors for resistance to second line anti-tuberculosis drugs in Balochistan, Pakistan

Background. Pakistan is high burden drug resistant tuberculosis (DR-TB) country. For devising a treatment regimen and optimizing empirical drug therapy, the local epidemiology and drug resistance patterns are needed to be considered. Objectives. To evaluate the drug resistance pattern, prevalence and risk factors for resistance to second line anti-tuberculosis drugs (SLD) among DR-TB patients in Balochistan, Pakistan. Design and setting. This cross-sectional study was carried out at the Fatimah Jinnah Chest and General Hospital in Quetta's programmatic management unit of the DR-TB (PMDT). Methods. This study included all DR-TB patients, regardless of their age, TB location, or medication resistance pattern. The sociodemographic, microbiological, and clinical data of the patients were gathered using a standard data collecting form. SPSS 20 was used to analyze the data. A statistically significant p-value was defined as less than 0.05. Results. A total of 354 patients were included in the final analysis. Among them majority were females (61.7%), belonged to the age group 19-30 years (36.7%), were previously treated for TB (95.8%) at public sector hospital (42.7%) and did not suffer from any other comorbidity(88.7%). The study participants were resistant to a median of three anti-TB drugs (range 1-8). The most common type of DR-TB was multi DR-TB (77.1%), followed by mono DR-TB (18.1%), extensive DR-TB(3.1%) and poly-DR (1.7%). A total of 147 (41.5%) patients were resistant to any second line anti-TB drug (SLD). Among SLD, the resistance was high for fluoroquinolones (38.4%), followed by ethionamide (4.8%) and injectable SLD(4.2%). Upon multivariate binary logistic regression analysis previous treatment of cat-II regimen had statistical significant association with resistance to any SLD (OR=5.273, 95%CI=1.098-25.316). Conclusion. It is concerning to see such a high level of SLD resistance, especially to fluoroquinolones. More stringent regulations are advised to regulate the non-prescription sale and indiscriminate use of fluoroquinolones, as well as testing for drug resistance in cat-I failures instead of placing patients on cat-II therapy.

ARCHITECTURAL AND CIRCUIT MODEL OF NAVIGATION DEVICE FOR ULTRA-LIGHT LAUNCH VEHICLE

The paper considered the architectural and circuitry model of a navigation device for an ultra-lightweight launch vehicle designed to improve the accuracy and reliability of positioning and orientation in flight conditions. The study utilized modern approaches to the integration of global navigation satellite system (GNSS) and inertial navigation system (INS) to achieve high accuracy and stability of the system. The key components of the device including UM980 module, LSM6DSV32X inertial measurement module, STM32 F7 series microcontroller, E220-400T30S radio module, LMR50410XDBVR converter based power supply and RS422 interface were described in detail. The UM980 module, including SAW and LNA filter blocks, demonstrated the ability to efficiently process incoming RF signals. The NebulasIV main function block combined GNSS BB, GNSS RF, interfaces and power management unit (PMU) modules, supporting multiple communication interfaces such as UART, SPI and I²C, as well as RTK and PPS signals. The study analyzed the integration and accuracy aspects of the module in navigation systems. The signal processing scheme of the inertial navigation system module was also presented, including digital filters, free-fall and activity/inactivity detection functions, and interfaces for data communication. User bias functions and filter modes are considered to ensure the accuracy and stability of the navigation device. The work lays the groundwork for further improvements in navigation technology, especially in the context of increasing availability and accuracy for small scale space launches.

Implementation of Strategic Management in Optimizing Merdeka Curriculum

This study aims to describe and analyze the implementation of strategic management in optimizing Merdeka Curriculum at SMA Negeri 3 Unggulan Kayuagung. This study uses qualitative methods. It shows that Implementation of strategic management consists of strategy formulation (environmental analysis, vision, mission, goals, targets and strategies), implementation (operational curriculum, programs, monitoring and communication systems, school resources, organizational structure, school’s principal leadership, and work culture), and strategy evaluation. The obstacles are dynamic policies, limited time, work completion gaps, inconsistency, and evaluation document. The solutions are to optimize growth mindset, digitalization; priority scale-based work plans; collaboration culture; performance work management; evaluation instruments and action plans. Novelty of this study resides in the research setting that implements the Merdeka Curriculum with Mandiri Berbagi category, so this study can contribute to strengthening strategic management in educational units to achieve optimal results in facing changes in the Merdeka Curriculum category options.

Inferring the origin of new D-loop haplotypes of loggerhead sea turtles (Testudinata: Cheloniidae) from the Southwest Atlantic lineage

The populations of the loggerhead turtles, Caretta caretta, present four main D-loop mitochondrial haplogroups that are distributed across the Indo-Pacific, Mediterranean, and Atlantic oceans. The Southwestern Atlantic (SWA) is one of the Regional Management Units (RMUs) of loggerheads, characterized by unique haplotypes, high nest density, and distinct life history traits. Detecting new D-loop haplogroups is important, particularly endemic ones, as they can enhance our understanding of their life history within the RMUs and contribute to the resolution of mixed stock analysis. In this study, we conducted a series of phylogenetic delimitation and network analyses to identify, validate, and infer the origin of four new D-loop haplotypes detected in the loggerhead populations from the SWA. Our findings demonstrate that these new D-loop haplotypes are valid and unique to the SWA lineage, potentially aiding in the delimitation of individuals’ origins and the inference of their lineage.

One century of carbon dynamics in the eastern Canadian boreal forest under various management strategies and climate change projections

Partial cutting has lower canopy removal intensities than clearcutting and has been proposed as an alternative harvesting approach to enhance ecosystem services, including carbon sequestration and storage. However, the ideal partial cutting/clearcutting proportion that should be applied to managed areas of the eastern Canadian boreal forest to enhance long-term carbon sequestration and storage at the landscape scale remains uncertain. Our study projected carbon dynamics over 100 years (2010–2110) under a portfolio of management strategies and future climate scenarios within three boreal forest management units in Quebec, Canada, distributed along an east–west gradient. To model future carbon dynamics, we used LANDIS-II, its Forest Carbon Succession extension, and several extensions that account for natural disturbances in the boreal forest (wind, fire, spruce budworm). We simulated the effects of several management strategies on carbon dynamics, including a business-as-usual strategy (clearcutting applied to more than 95 % of the annually managed area), and compared these projections against a no-harvest natural dynamics scenario. We projected an overall increase in total ecosystem carbon storage, mostly because of increased productivity and broadleaf presence under limited climate change. The drier Western region under climate scenario RCP8.5 was an exception, as stocks decreased after 2090 because of the direct negative effects of extreme climate change on coniferous species’ productivity. Under the natural dynamic scenario, our simulations suggest that the Quebec Forest in the Central and Western regions may act as a carbon sink, despite high fire-related carbon emissions, particularly under RCP4.5 and RCP8.5 Conversely, the eastern region periodically switched from carbon sink to source following SBW outbreaks, thus being a weak sink over the simulation period. Applying partial cutting to over 50 % of the managed forest area effectively mitigated the negative impacts of climate change on carbon balance, reducing differences in stand composition and carbon storage between naturally dynamic forests and those managed for timber. In contrast, clearcutting-based scenarios, including the business-as-usual approach, substantially reduced total ecosystem carbon storage— by approximately double (10 tC ha−1 yr−1) compared to partial cutting scenarios (<5 tC ha−1 yr−1). Clearcutting led to higher heterotrophic respiration due to the proliferation of fast-decomposing broadleaves, resulting in lower carbon accumulation compared to partial cuts. Our findings underscore the importance of balancing canopy removal intensities to increase carbon sequestration and storage while preserving other ecosystem qualities under climate change.

The impact of COVID-19 on Australian plastic and reconstructive surgery trainees: a survey study

Introduction: The COVID-19 pandemic had a significant impact on the training of plastic and reconstructive surgeons and the wellbeing of surgical trainees internationally. The aim of this study was to evaluate the impact of the COVID-19 pandemic on Australian plastic and reconstructive surgery trainees. Method: A web-based self-administered survey was distributed by the Australian Society of Plastic Surgeons to all Australian plastic and reconstructive surgery registrars in October 2021. A questionnaire developed to assess the impact of the COVID-19 pandemic on plastic and reconstructive surgery trainees in the United States of America was adapted for the Australian context. Subgroup analysis evaluated differences in responses between early and late Surgical Education and Training trainees and between Australian states. ​Results: Of 103 Australian plastic and reconstructive surgery trainees invited to participate, 24 responded (23%). Of these, 52 per cent were in their first two years of training. Total working hours were reduced for 61 per cent of respondents, 54 per cent reported less direct operative supervision, and 75 per cent reported missing out on critical operative learning experiences due to elective operating changes. Overall impact on trainee education was reported to be negative by 71 per cent of respondents. Self-assessed overall wellbeing was negatively impacted in 92 per cent of respondents: all reported feeling isolated from colleagues and 67 per cent reported burnout due to changes during the pandemic. Positive innovation in plastic and reconstructive surgery unit management was reported by 29 per cent of respondents. There were no statistically significant differences in responses between early and late Surgical Education and Training trainees. There were some differences identified in senior supervision and frequency of organised teaching between states. Conclusion: Australian plastic and reconstructive surgery trainees in our cohort reported that the COVID-19 pandemic had a negative impact on their clinical training opportunities, formal education and wellbeing. These findings should be considered in planning for future periods of significant disruption to try to mitigate the negative impacts on trainees.

Segment Anything Model Combined with Multi-Scale Segmentation for Extracting Complex Cultivated Land Parcels in High-Resolution Remote Sensing Images

Accurate cultivated land parcel data are an essential analytical unit for further agricultural monitoring, yield estimation, and precision agriculture management. However, the high degree of landscape fragmentation and the irregular shapes of cultivated land parcels, influenced by topography and human activities, limit the effectiveness of parcel extraction. The visual semantic segmentation model based on the Segment Anything Model (SAM) provides opportunities for extracting multi-form cultivated land parcels from high-resolution images; however, the performance of the SAM in extracting cultivated land parcels requires further exploration. To address the difficulty in obtaining parcel extraction that closely matches the true boundaries of complex large-area cultivated land parcels, this study used segmentation patches with cultivated land boundary information obtained from SAM unsupervised segmentation as constraints, which were then incorporated into the subsequent multi-scale segmentation. A combined method of SAM unsupervised segmentation and multi-scale segmentation was proposed, and it was evaluated in different cultivated land scenarios. In plain areas, the precision, recall, and IoU for cultivated land parcel extraction improved by 6.57%, 10.28%, and 9.82%, respectively, compared to basic SAM extraction, confirming the effectiveness of the proposed method. In comparison to basic SAM unsupervised segmentation and point-prompt SAM conditional segmentation, the SAM unsupervised segmentation combined with multi-scale segmentation achieved considerable improvements in extracting complex cultivated land parcels. This study confirms that, under zero-shot and unsupervised conditions, the SAM unsupervised segmentation combined with the multi-scale segmentation method demonstrates strong cross-region and cross-data source transferability and effectiveness for extracting complex cultivated land parcels across large areas.

SLOPE: Safety LOg PEripherals implementation and software drivers for a safe RISC-V microcontroller unit

The focus of this manuscript is related to the main safety issues regarding a mixed criticality system running multiple concurrent tasks. Our concerns are related to the guarantee of Freedom of Interference between concurrent partitions, and to the respect of the Worst Case Execution Time for tasks. Moreover, we are interested in the evaluation of resources budgeting and the study of system behavior in case of occurring random hardware failures. In this paper we present a set of Safety LOg PEripherals (SLOPE): Performance Monitoring Unit (PMU), Execution Tracing Unit (ETU), Error Management Unit (EMU), Time Management Unit (TMU) and Data Log Unit (DLU); then, an implementation of SLOPE on a single core RISC-V architecture is proposed. Such peripherals are able to collect software and hardware information about execution, and eventually trigger recovery actions to mitigate a possible dangerous misbehavior. We show results of the hardware implementation and software testing of the units with a dedicated software library. For the PMU we standardized the software layer according to embedded Performance Application Programming Interface (ePAPI), and compared its functionality with a bare-metal use of the library. To test the ETU we compared the hardware simulation results with software ones, to understand if overflow may occur in internal hardware buffers during tracing. In conclusion, designed devices introduce new instruments for system investigation for RISC-V technologies and can generate an execution profile for safety related tasks.

Impact of head-of-bed elevation angle on the development of pressure ulcers and pneumonia in patients on mechanical ventilation: a systematic review and meta-analysis

BackgroundMechanical ventilation is crucial for patient management in intensive care units, but it comes with complications such as pressure ulcers and ventilator-associated pneumonia (VAP). The impact of head-of-bed elevation angles on these complications remains a critical area for investigation.MethodsThis systematic review and meta-analysis followed PRISMA guidelines and involved searches across PubMed, Embase, Web of Science, and Cochrane Library, conducted on September 19, 2023, with no date or language restrictions. We included randomized controlled trials that compared different head-of-bed elevation angles in adult ICU patients on mechanical ventilation. Data were extracted on study characteristics, quality assessed using the Cochrane risk of bias tool, and statistical analyses performed using chi-square tests for heterogeneity and fixed or random-effects models based on heterogeneity results.ResultsSix studies met inclusion criteria out of an initial 601 articles. These studies showed minimal heterogeneity (I2 = 0.0% for pressure ulcers, p = 0.930; and for VAP, p = 0.797), supporting the use of fixed-effect models. Results indicated that a higher elevation angle (45°) significantly increased the risk of pressure ulcers (OR = 1.95, 95% CI: 1.12–3.37, p < 0.05) and decreased the incidence of VAP compared to a lower angle (30°) (OR = 0.51, 95% CI: 0.31–0.84, p < 0.05).ConclusionsWhile higher head-of-bed elevation can reduce the risk of VAP in mechanically ventilated patients, it may increase the risk of pressure ulcers. Clinical strategies should carefully balance these outcomes to optimize patient care in ICU settings.RegistrationPROSPERO 2024 CRD42024570232.

Profile of Primary Care Managers in A Municipality in Northern Brazil and their Leadership Styles

Objective: Know the profile and leadership style of managers of Basic Health Units (BHU). Theoretical Framework: The 2017 National Primary Care Policy (NPCP) suggested the inclusion of managers in BHU to perform technical-managerial functions, based on the manager's assessment and according to the needs of the territory and coverage of Basic Care (BC). Method: Descriptive, cross-sectional and quantitative research, carried out in the municipality of Barcarena, in the state of Pará. The sample was 22 AB managers, carried out from October 2022 to May 2023. The data obtained from a questionnaire with sociodemographic and of experiences in Primary Health Care (PHC) and another on leadership style, the Multifactorial Leadership Questionnaire (MLQ). Results and Discussion: Most BC managers are female (86.4%), aged 20 to 39 (54.5%), married (59.1%), with higher education (90.9%) in Nursing (59 .1%) and 50.0% have a postgraduate degree at Lato sensu level and have a temporary employment relationship (59.1%). They had previous experience in management (59.1%) and had experience in PHC (72.7%). Regarding leadership styles, transformational leadership was more self-perceived (m=3.33) and was statistically significant (p=0.020), as an attribute, motivational inspiration (m=3.67). Research Implications: This study is one of the few works involving research focused on the leadership profile of BC managers. Originality/Value: This study contributes to the literature by understanding the aspects associated with the leadership style of BC managers, and the relationship between leadership and the guidance suggested by the 2017 NPCP.

Shifting Baselines: Visualizing Climate Change in America’s National Parks

This visual essay highlights four national parks where the impacts of climate change are well-documented and visually compelling (Everglades, Mesa Verde, Joshua Tree, and Mount Rainier). In drawing attention to these visible climate impacts and effectively interpreting the changes in situ, the park service can play a key role in clarifying the issue of climate change for the American public. Park managers and other park professionals have undoubtedly identified locations in their own management units offering similar opportunities to engage visitors in the science of climate change (either through on-site signage or ranger-led programs). The photographs comprising this visual essay, taken over eight weeks of fieldwork from 2017 to 2024, are intended to spark ideas and move the conversation forward.

A Survey on the Management of Patients with Severe Traumatic Brain Injury During Pregnancy: The MAMA Study.

Trauma, including traumatic brain injury (TBI), is the leading cause of nonobstetric maternal mortality during pregnancy. Few data are available regarding the optimal management of pregnant patients with TBI, leading to a lack of dedicated guidelines. We performed an international survey to examine the management of severe TBI in pregnant patients, focusing on monitoring, therapy, and intensive care practices. This survey, endorsed by the World Society of Emergency Surgery, was composed of a questionnaire with 79 items divided into four sections: (1) general information (items 1-7), (2) management of the maternal-fetal unit (items 8-43), (3) management of intracranial hypertension (items 44-76), and (4) specific considerations (items 77-79). One hundred and twenty-two physicians from 110 centers in 35 countries responded. The main findings related to TBI care in pregnant patients included the following: (1) a lack of availability of a specific TBI protocol in pregnancy; (2) an increase in the utilization of magnetic resonance imaging as the primary neuroimaging tool; (3) higher hemoglobin thresholds for transfusion; and (4) a lower utilization of therapeutic hypothermia, neuromuscular blocking agents, and barbiturate coma. We also report large variability in the timing of cesarean section in pregnant patients with TBI (≥ 23weeks of gestation) needing an emergency craniotomy (simultaneously 23% vs. later cesarean section 50.8%). Great variability in the management of pregnant patients with severe TBI was identified worldwide from the results of our survey. These findings, highlighting the lack of robust evidence on this topic, will be helpful to stimulate future investigations and to promote educational efforts on this difficult scenario.

Small watersheds are the best control and management unit for improving soil conservation services in karst areas

Climate factors and changes in landscape patterns are often recognized as the primary drivers of soil conservation services. The influence mechanism of climate factors and landscape patterns on soil conservation service is scale-dependent and spatial heterogeneous. However, it is not clear whether small watershed scale is more conducive to soil erosion control than large scale such as county scale and township scale. For the purpose of creating land use development plans that take local conditions into account, it is crucial to clarify the effects of climate and landscape pattern factors on soil conservation change. Wujiang River basin (WRB), a typical karst basin located in the catchment of the largest first-level tributary on the upper Yangtze River in China, was used as the study area in this research. Soil conservation services provided by water erosion control (SPC) in WRB from 2005 to 2020 were evaluated using the RUSLE model based on the modified rock exposure rate. By using stepwise regression model and multi-scale geographically weighted regression model (MGWR), the spatial heterogeneity of the influence of different driving factors on soil conservation service was comprehensively studied at the scale of district, township and small watershed. The results show that the SPC fluctuates obviously, but the trend is not significant. Climate factor is the dominant factor affecting SPC. With the change of scale from large to small, the adjusted R2 of the regression model gradually increases, especially the factors related to landscape pattern, and more driving factors can be revealed more comprehensively and effectively. Therefore, the small watershed scale is the best control unit to improve the SPC when formulating the regional management landscape plan. The findings of this research also have benchmark significance for other ecological fragile areas, and can provide more comprehensive suggestions for local ecosystem management and landscape planning.