Management Techniques Research Articles

Cystine and urate cystoliths in dogs are frequently visible on radiographs prior to surgical or nonsurgical removal.

To investigate the frequency at which cystine and urate cystoliths (stones) are visible on radiographs prior to surgical or nonsurgical retrieval. Records of client-owned dogs (n = 331) were analyzed between January 2019 and December 2023 for cystoliths submitted for stone analysis after surgical removal or nonsurgical retrieval. Records were analyzed for cystolith type; when cystine or urate stones were identified, records were analyzed for signalment, procedure, presence of mineral opaque cystoliths on pre-procedural radiographs, urine pH and crystalluria, history of previous cystoliths, prior prescription diet attempt, recurrence, and genetic, congenital and acquired comorbidities. Descriptive statistics were generated after data collection. 31 of 331 (9%) were cystine stones, 49 of 331 (15%) were urate, and 1 of 331 (0.3%) was a mix of urate and cystine. When radiographs were taken prior to stone removal, 24 of 28 (85%) of urate, 24 of 26 (92%) of cystine, and 1 of 1 (100%) of urate/cystine were visible on radiographs. Cystine and urate stones are visible on survey radiography at a high frequency in dogs. While cystine and urate stones have been historically designated as radiolucent, they are frequently radiopaque on radiographs. Radiopacity is commonly used as one of the criterion to determine whether a dissolution or prevention diet is an appropriate management technique, particularly when determination of the stone type has yet to be performed. As a result, these findings may prompt clinicians to investigate other patient-specific factors before a specific dietary recommendation is made.

Understanding the implications of climate change for Australia’s water resources: Challenges and future directions

Climate change is altering Australia’s streamflow and water resources due to a complex interplay of shifts in temperature, rainfall, evaporation, vegetation dynamics, soil moisture, and rainfall-runoff partitioning. Meanwhile increases in human activity and urbanisation continue to alter the landscape, further affecting streamflow and flood volumes. Understanding the nature of these recent changes is critical for evaluating future risks and ensuring planning decisions are sustainable. Positively, our knowledge of changes to Australia’s hydrologic regimes has greatly advanced in the last decade. Here we review our current understanding of historical hydrologic changes, focusing first on the drivers of change and then observed changes in streamflow and flooding, before turning our attention to the role that historical observations can play in anticipating future climate change impacts. We conclude with recommendations to help better understand and plan for an unknown future.Increases in extreme rainfalls have increased the risk of large flood events. However, declines in mean rainfall across large parts of the continent, increases in diversions, and increasing evaporate demand have led to an overall drying. Significant advances in our understanding have been made through analysing trends in the observational record and investigating the associated drivers. While these learnings may not reliably inform the potential effects of future change, they can still inform process understanding ultimately helping accurately model and project future impacts. Projecting climate change impacts on water resources in Australia remains challenging, and progress will require improved instrumentation to observe and understand catchment responses together with methods and management techniques that incorporate this additional uncertainty. We argue it is through processed-informed models together with multi-scale observational data that this gap can be breached.

Cloud Replica Management-Based Hybrid Optimization

This research addresses the challenges in cloud-based replica management by proposing a novel strategy employing a Genetically Implied Greywolf with Oppositional Learning (GIGOL) hybrid optimization technique. This approach optimizes multi-objectives such as response time, load balancing, availability, replication cost, and energy consumption, ensuring cost-effectiveness and energy efficiency. The GIGOL model integrates Genetic Algorithm, opposition learning, and Grey Wolf Optimization, aiming to achieve optimal replica placement. The study emphasizes resolving overhead issues through machine learning techniques for efficient cloud-based replica management. Performance evaluation showcases improvements in response time, load balancing, availability, replication cost, and energy consumption, highlighting the effectiveness of the proposed approach within budget constraints and management policies.

S4028 Rendezvous Technique for Successful Management of Complete Esophageal Stenosis

S4028 Rendezvous Technique for Successful Management of Complete Esophageal Stenosis

ANN-based Maximum Power Point Tracking Technique for PV Power Management under Variable Conditions

Due to the increasing energy demand, traditional fossil fuels are gradually decaying day by day as analyzed by many researchers. Fossil fuels are not sufficient to fulfil the requirement of energy demand and it also produces greenhouse gas emissions. In this regard, worldwide research is going on related to renewable energy sources (RESs) like solar photovoltaic (SPV), wind turbines, fuel cells etc. The source of SPV is plentiful and environment friendly which converts solar radiation to non-linear electrical power. This power is not suitable for a stable system. Therefore, the maximum power point tracking (MPPT) controller is required to find the optimum maximum power point (MPP) to the load. The MPPT technology regulates the duty-cycle in favour of the DC-DC converter to continuously obtain maximum power from the SPV arrays. In the past few decades, the learning of MPPT techniques has made substantial progress in the RESs. This research article analyzes the performance of various MPPT techniques in the proposed SPV framework. The main investigation is to assess different MPPT techniques to optimize power from the SPV framework. The artificial neural network (ANN)-MPPT method has been observed to be more effective in output power production and transient response about the MPP than conventional perturb and observe (P&O)-MPPT and fuzzy logic controller (FLC)-MPPT technology.

Novel technique for inguinal lymphatic fistula management using a double U-stitch closure

Novel technique for inguinal lymphatic fistula management using a double U-stitch closure

Impact of dyke and vegetation on fluid force and moment reduction under sub and supercritical flow conditions

Flooding is the most common natural disaster throughout the world and requires efficient management. Therefore, the current investigation aimed to explore the impact of a composite defense system comprising dyke and vegetation on flow dynamics and velocity reduction. Experiments were conducted in an open channel setup with an adjustable bed slope and transparent sidewalls, and the vegetation model was replicated as real trees such as Eucalyptus trees. The study involved calculating several parameters, including flow velocity, reduction of fluid force index (RFI%), reduction in moment index (RMI%), and hydrostatic and hydrodynamic forces. These calculations were done by changing the channel bed slope and keeping the flow rate (discharge) constant while considering both subcritical and supercritical flow conditions. Moreover, regression analysis was performed for the prediction of RFI% and RMI% under various flow conditions. Also, statistical analyses were performed to assess the effectiveness of the defense system in reducing fluid force and moment indices. The result of the current investigation indicates that the highest values of RFI% and RMI% under subcritical flow conditions were 79% and 88%, while under supercritical flow conditions they were 94% and 78%, respectively. Moreover, a velocity reduction of 69% was observed under subcritical flow, while 84% was observed under supercritical flow conditions. Under subcritical flow conditions, RFI% and RMI% enhanced by enhancing Froude number (Fr) because of an increase in velocity reduction and hydraulic jump formation. Similar trends were observed under supercritical flow conditions, with effective mitigation of high-velocity flows by the composite system. The finding of current research helps in providing effective techniques for flood management.

Dorsal Carpal Artery Perforator Flaps: An Anatomical and Clinical Study.

Hand injuries pose challenges due to complexity and aesthetic-functional concerns. Dorsum of hand injuries are difficult to treat due to thin skin cover and increased propensity to exposure of underlying structures. Perforator-based flaps can provide better outcomes with minimal donor site morbidity. This study aims to bridge the gap in anatomical knowledge and explore the potential benefits of dorsal carpal artery perforator flap. A prospective study was done from July 2021 to June 2023, focused on study of dorsal carpal artery perforators on 12 fresh frozen cadaveric hands. Anatomical study involved injection of red latex into arteries at the wrist, followed by dissection and measurements. During the clinical phase, we used the inferences gained from the anatomical study to identify and mark perforator of dorsal carpal arteries. We performed V-Y advancement flap based on the DCPs in 5 patients who had dorsum of hand defects due to trauma. The study was carried out on 6 fresh frozen cadavers (12 hands). Anatomical findings revealed the anatomical location, caliber, and consistent number of dorsal carpal artery perforators supplying the dorsum of the hand arranged in 2 rows. Clinically, we applied this insight to create V-Y flaps in 5 patients with successful outcomes, thus, offering DCP-based flap as an alternative to distant flaps. DCP-based flaps offer an efficient solution for reconstructing proximal hand defects over the dorsum, with minimal complications, enhancing our understanding of hand reconstruction options. The study's comprehensive anatomical insights and clinical outcomes contribute to improving hand defect management and surgical techniques.

An effective farmer-centred mobile intelligence solution using lightweight deep learning for integrated wheat pest management

Integrated Pest Management (IPM) techniques have been widely used in agriculture to manage pest damage in the most economical way and to minimise harm to people, property and the environment. However, current research and products on the market cannot consolidate this process. Most existing solutions either require experts to visually identify pests or cannot automatically assess pest levels and make decisions based on detection results. To make the process from pest identification to pest management decision making more automated and intelligent, we propose an end-to-end integrated pest management solution that uses deep learning for semi-automated pest detection and an expert system for pest management decision making. Specifically, a low computational cost sampling point generation algorithm is proposed to enable mobile devices to generate uniformly distributed sampling points in irregularly shaped fields. We build a pest detection model based on YoloX and use Pytorch Mobile to deploy it on mobile phones, allowing users to detect pests offline. We develop a standardised sampling specification and a mobile application to guide users to take photos that allow pest population density to be calculated. A rule-based expert system is established to derive pest management thresholds from prior agricultural knowledge and make decisions based on pest detection results. We also propose a human-in-the-loop algorithm to continuously track and update the validity of the thresholds in the expert system. The mean average precision of the pest detection model is 58.17% for 97 classes, 75.29% for 2 classes, and 57.33% for 11 classes on three pest datasets, respectively. The usability of the pest management system is assessed by the User Experience Surveys and achieves a System Usability Scale (SUS) score of 76. The usability of the proposed solution is validated by qualitative field experiments.

Clinical outcomes of retrograde intramedullary multiple pinning for proximal humeral fractures using a modified palm tree technique

BackgroundRetrograde intramedullary multiple pinning using a modified palm tree technique for proximal humeral fractures has attracted interest from surgeons because of its minimal invasiveness into the soft tissue around the shoulder joints. We aimed to evaluate the clinical and radiological outcomes of this procedure. MethodsThis retrospective study included 21 patients who underwent surgery using a modified palm tree technique for proximal humeral fractures between March 2010 and March 2022. Patients with two- and three-part proximal humeral fractures that could be reduced by closed manipulation under general anesthesia were included in this study. All patients were clinically evaluated using the Japanese Orthopaedic Association (JOA) and University of California at Los Angeles (UCLA) shoulder scores. Postoperative radiographic findings, including fracture healing and signs of pinning-related complications, were evaluated. ResultsTwenty-one shoulders in 21 patients (9 men and 12 women) with mean age at surgery of 66.3 ± 19.3 years were evaluated. The mean period until bone union was 2.6 ± 0.7 months. The mean JOA and UCLA shoulder scores at the final follow-up were 84.8 ± 12.1 and 27.5 ± 5.4, respectively. Perforation of the humeral head by Kirschner (K) wires was observed in 9 of the 21 (42.9 %) shoulders. The JOA and UCLA shoulder scores at the final follow-up were not significantly different between the groups with and without perforations (p = 0.41 and 0.27, respectively). The oblique or Y-view detected significantly more wires with perforation of the humeral head than did the anteroposterior view (6 vs. 15 wires, p < 0.01). ConclusionsThe modified palm tree technique for proximal humeral fractures demonstrated good postoperative clinical outcomes and early fracture healing. However, modifications in postoperative management and surgical techniques should be considered to reduce the high rate of perforation of the humeral head by K-wires.

Exploring knowledge and uses of Moringa oleifera and understanding its cultivation constraints and proposed solutions: a case from Bangladesh

Multipurpose trees, like the moringa (Moringa oleifera Lam.), have become extremely popular in an attempt to reduce food, nutritional, and economic instability. The significant benefits of moringa’s leaves, pods, seeds, roots, and flowers are used in a wide range of commercial fields, including medicine, cosmetics, food, animal feed, water purification, and more. We applied a questionnaire-based survey to reveal the uses, problems and solutions related to the knowledge, uses and constraints of moringa in the region of Chapainawabganj and Kushtia districts in Bangladesh. Including the easiest propagation process and the lowest cultivation costs, year-round flowering, and production provide moringa with a wide window of opportunity. Besides using regular pruning of moringa branches, respondents make trees bushy to increase fruit and leaf production. Respondents from both regions opined that moringa has a good market value, increases family income, increases opportunity for fallow land utilization, enhances employment opportunities, and is known as a nutritive and multipurpose tree. We were pleased to find that moringa output regularly exceeded previous production records in Bangladesh from 2014–16 to 2020–21. Furthermore, our survey shows that a 5-year-old moringa tree provides a satisfactory yield per season with its high market price and demand. Despite the extensive use of moringa fruits and leaves by respondents, its commercial potential remains largely undeveloped and unknown to them. Constraints like limited scientific knowledge and technological infrastructure are the reasons why the elusive potential of moringa in Bangladesh persists. There is ample opportunity to enhance moringa production via effective management techniques, which will satisfy community demand and create market opportunities both locally and internationally. As a result, smallholder farmers’ livelihoods and food and nutritional security can be improved.

An open-loop and closed loop based passive thermal management techniques applicable to photovoltaic systems

Photovoltaic (PV) technology adoption in recent years has experienced significant growth due to its inherent advantages over alternative technologies. Nevertheless, there is a concern regarding performance deterioration due to high operating temperatures. Various thermal management methods have been studied to address this issue, each having its own advantages and disadvantages. Hence, a comprehensive review aimed at developing effective passive cooling techniques was undertaken and two techniques were finalized for outdoor testing viz. natural circulation loop based cooling (PV-NCL) and evaporative cooling (PV-EVP). Though the former version could drop module temperature by 7.4 °C–13.9 °C (Power output increment in the range of 3.5 %–6.7 %), this improvement was not sustained throughout the day due to factors such as flow resistance within the loop and a lack of convective cooling in the vicinity of the cooler. Subsequent experiments confirmed that loop resistance played a dominant role in this phenomenon. Additionally, concerns about water circulation in PV-NCL were resolved through a comparison with water duct-integrated PV. On the other hand, the innovative gravity-assisted water flow for evaporation method (PV-EVP) yielded more promising results, with a power output enhancement ranging from 3.7 % to 11.5 %. However, considering the in-field operational issues, PV-NCL with a modified design will likely be the best technique.

Phenology forecasting models for detection and management of invasive annual grasses

AbstractNon‐native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well‐timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range‐wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat‐insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within‐season or within‐year decision support.

Effects of irrigation and nutrients managements with plant intensification on rice under saline soil

The area of salt affected agricultural soils has grown on a global scale. The toxicity of salt and the unfavorable characteristics of the soil are two major causes of the low crop productivity on salt-affected soil. Thus, effective and economical management techniques are required for crop production which may sustainable. The experiments were conducted to identify appropriate irrigation and other management practices for higher yield of Boro rice at two locations (Horinkhola, Satkhira and Batiaghata, Khulna) of saline area during two successive years (2021 and 2022). Six treatments were used, consisting of continuous ponding of irrigation water along with recommended fertilizer (farmers practice, as control), and a range of combination of irrigation water and gypsum fertilizer and foliar spray of Urea, TSP, MOP and Zinc Sulphate. The results revealed that at both locations, the treatments showed significant difference and the highest yield (7.35 t/ha at Horinkhola and 6.75 t/ha Batiaghata) were obtained in treatment T5 [Continuous saturation (0-3cm) + 50% recommended fertilizer except MoP + K2SO4 equivalent to 50% K+ OM + no ridge, high density (15 cm x 10 cm) + Change of standing water 20 days interval + Foliar application of Urea-40 g, TSP-44 g, MOP-26 g and Zinc Sulphate 3g (4 times : 25, 35, 45, 60 DAT)]. Overall, this treatment produced 19% higher yield compared to farmer’s practice, along with maximum BCR (1.57) and net profit (52,004 Tk/ha). This technique can be adopted for higher yield in saline area. Bangladesh J. Nuclear Agric, 38(1): 53-64, 2024

Monitoring and Management Techniques for Persistent Organic Pollutants in Groundwater Environment of Subway Stations

Monitoring and Management Techniques for Persistent Organic Pollutants in Groundwater Environment of Subway Stations

Insights from electrical resistivity tomography on the hydrogeological interaction between sand dams and the weathered basement aquifer

Sand dams, composed of recent alluvial aquifers behind concrete dam walls, are a water management technique in drylands. However, their level of hydraulic connectivity with their surrounding weathered basement aquifer is debated. This study aims to constrain this hydrogeological uncertainty in order to better understand their ability to meet water needs and improve dryland water security. The study is the first to use 2D geophysics (Electrical Resistivity Tomography) to provide evidence of seepage from sand dams at three mature and three newly built sites. A generally greater hydraulic connectivity was found between sand dams and their surrounding aquifer than has been assumed in some previous studies, with sites providing at least some local recharge rather than existing as isolated storage structures. This improved understanding is beneficial for both site selection and the performance of sand dams and can help ensure that maximum benefits are derived from the construction of a sand dam depending on its intended purpose.

A thermodynamic approach to evaluating the ecological health and sustainability of integrated production systems in Goharkuh Taftan agro-industrial complex and sensitivity analysis of the results

In recent times, the increasing influx of energy inputs into farming systems has led to a significant enhancement in their overall efficiency. However, this has happened at the expense of endangering the sustainability of these systems and degrading the environment. Therefore, it is crucial to develop a methodology to evaluate the resilience of agricultural systems. This study utilised the Steinborn and Svirezhev methodology to assess five different production systems (wheat, barley, alfalfa, cotton, and Pistachio) within the Goharkuh Taftan agro-industrial complex. The approach measures the excessive production of entropy, which acts as an indicator of the system's departure from sustainability. The study focuses on four components: overproduction of entropy, limit energy load, maximum crop yield for sustainable agriculture, and deviation from sustainable agriculture. The results indicated that the production systems analysed in this study produce surplus entropy, thus rendering them in an unstable condition. Among all the products, alfalfa had the lowest entropy overproduction, while pistachio had the highest. The three agricultural commodities, namely wheat, barley, and cotton, are situated at a point equidistant from the two opposite ends. Alfalfa has shown greater energy use efficiency compared to pistachios. It surpasses the maximum crop yield for sustainable agriculture and has less deviation from sustainable agriculture than other integrated production systems. The differences in the intensity of energy flow and the structural characteristics of the integrated production systems were responsible for the variations in the values of the examined components. Nevertheless, none of these solutions are sustainable in the long term. An analysis of the energy inputs and components of the harvest index revealed the importance of implementing management techniques that decrease the intensity of energy flows into these systems and enhance the harvest index to attain a sustainable state. Integrating supplementary renewable energy sources will bolster the long-term sustainability of production systems.

School Students' Perceptions on School Management and Pedagogical Approaches

This study investigates students' perspectives on teaching-learning pedagogy and school management techniques. The information was collected from 240 students attending schools in urban, suburban, and rural areas, across different grade levels. To get this data, a variety of research techniques were combined. Through surveys, interviews, and focus groups, the study looked at students' attitudes, beliefs, and experiences in the classroom. The results provide a comprehensive understanding of students' viewpoints on a range of school administration topics, such as classroom dynamics, teacher-student interactions, administrative policies, and the use of technology in the classroom. Ann extensive analysis was conducted to obtain a comprehensive understanding of students' inclinations, difficulties, and recommendations concerning instructional strategies, evaluation procedures, and the school's general ethos. The study underlines the value of taking into account students' opinions when making decisions about education and stresses the necessity of creating a welcoming and stimulating learning environment that can accommodate a wide range of learner needs. The implications for educators, policymakers, and school administrators are examined in this paper. It makes recommendations for improving teaching-learning pedagogies and school management techniques to support student engagement, academic achievement, and general well-being.

Comparative identification of suitable vegetable nursery management technique for enhancing SHGs income of Koderma

Comparative identification of suitable vegetable nursery management technique for enhancing SHGs income of Koderma

Long-term AI prediction of ammonium levels in rivers using transformer and ensemble models

This study provides a cutting-edge machine learning approach to forecast ammonium (NH4+) levels in River Lee London. Ammonium concentrations were predicted over several time intervals using a complete dataset that includes temperature, turbidity, chlorophyll, dissolved oxygen, conductivity, and pH. Our technique captures the intricate connections between environmental conditions and ammonium concentrations using developed algorithms, including Temporal Fusion Transformer (TFT), Random Forest (RF) and Extreme Gradient Boosting (XGBoost) levels versus the important factors, considerably improving prediction accuracy. The novel aspect of this study is the utilisation of the TFT model for multi-horizon forecasting, which offers high accuracy and interpretability in hydrological predictions by combining convolutional components with an attention mechanism. The study also demonstrates the effectiveness of the TFT model in capturing short-term fluctuations while retaining accuracy over long time periods, which is a major difficulty in environmental modelling. The models used, have exceptional forecasting skills, predicting 150, 200, 365, 730, and 1095 days based on daily average and 12, 24 and 30 months based on monthly average. This dual-scale model combines flexibility and resilience, making it an effective tool for forecasting both short- and long-term environmental changes. The RF model excelled in long-term forecasts, sustaining high R-squared (R²) (0.97) values and low root mean square error (RMSE) (0.18), and the second best one was the XGBoost with optimiser with R2 of (0.92) and RMSE of (0.25) with forecasting 1095 days. The results also found that whilst the TFT captured the fluctuations in the short-term, it struggled with the longer-term predictions due to data granularity. The XGBoost model did remarkably well in monthly forecasts up to 12 months, maintaining low RSME. The findings also highlight the necessity of proactive water management techniques to reduce the risk of potential ecological effects, including hypoxia and oxygen depletion. The findings support resource managers in addressing prospective ammonium toxicity concerns such as oxygen depletion and ecological stress.