Viable Alternatives Research Articles

CollaPPI: A Collaborative Learning Framework for Predicting Protein-Protein Interactions.

Exploring protein-protein interaction (PPI) is of paramount importance for elucidating the intrinsic mechanism of various biological processes. Nevertheless, experimental determination of PPI can be both time-consuming and expensive, motivating the exploration of data-driven deep learning technologies as a viable, efficient, and accurate alternative. Nonetheless, most current deep learning-based methods regarded a pair of proteins to be predicted for possible interaction as two separate entities when extracting PPI features, thus neglecting the knowledge sharing among the collaborative protein and the target protein. Aiming at the above issue, a collaborative learning framework CollaPPI was proposed in this study, where two kinds of collaboration, i.e., protein-level collaboration and task-level collaboration, were incorporated to achieve not only the knowledge-sharing between a pair of proteins, but also the complementation of such shared knowledge between biological domains closely related to PPI (i.e., protein function, and subcellular location). Evaluation results demonstrated that CollaPPI obtained superior performance compared to state-of-the-art methods on two PPI benchmarks. Besides, evaluation results of CollaPPI on the additional PPI type prediction task further proved its excellent generalization ability.

Preference on Renewal Energy by Operators of Tourist Standard Hotels in Kathmandu, Nepal

Although renewable energy sources are viable alternatives, their uptake by hotel owners is still uneven and frequently constrained. Preference mostly depends on the availability and cost of the renewal energy. This articles aimed to study; firstly, the operator’s preference, renewal energy pattern, renewable energy of tourist standard hotels in Kathmandu, Nepal; secondly, to find the barriers in using renewable energy ; third, to find out the expectation in policy reformation from the government to increase the use of renewal energy in the hotels. Data collected from 30 hotels through a convenience sampling method showed that preference for renewal energy is 80% for Electricity and 2% only for solar energy. Hotel operators agreed that using renewal energy in the hotel will save their time and cost, and expected the concessional rate as well as subsidy from the government on renewal energy with expectaton of policy reforms. All hotel operators mentioned that renewal energy like hydropower electricity was easily available and there were less barriers in use of renewal energy being in Capital City. However, barriers depends on the affordability, availability, geographical location also.Result may differ in different location. Only 2% preference for solar energy is good future research questions.

Green Additives in Chitosan-based Bioplastic Films: Long-term Stability Assessment and Aging Effects.

Although biomass-based alternatives for the manufacturing of bioplastic films are an important aspect of a more sustainable future, their physicochemical properties need to be able to compete with the existing market to establish them as a viable alternative. One important factor that is often neglected is the long-term stability of renewables-based functional materials, as they should neither degrade after a day or week, nor last forever. One material showing high potential in this regard, also due to its intrinsic biodegradability and antibacterial properties, is chitosan, which can form stable, self-standing films. We previously showed that green additives introduce a broad tunability of the chitosan-based material properties. In this work, we investigate the long-term stability and related degradation processes of chitosan-based bioplastics by assessing their physicochemical properties over 400 days. It was found that the film properties change similarly for samples stored in the fridge (4 °C, dark) as at ambient conditions (20 °C, light/dark cycles of the day). Additives with high vapor pressure, such as glycerol, evaporate and degrade, causing both brittleness and discoloration. In contrast, films with the addition of crosslinking additives, such as citric acid, show high stability also over a long time, bearing great preconditions for practical applications. This knowledge serves as a stepping-stone to utilizing chitosan as an alternative material for renewable-resourced bioplastic products.

Acute type a aortic dissection: when not to operate, a review

Acute type A aortic dissection (ATAAD) is a surgical emergency with a nonoperative mortality rate of up to 1% per hour and an operative mortality rate as high as 24%. Therefore, evaluation of comorbidities and patient presentation characteristics prompts a pause for risk stratification before proceeding to the operating room, as emergent surgery may not always be the optimal approach. This comprehensive review explores key considerations in ATAAD management, emphasizing the need for nuanced decision making, by considering medical management and delayed surgery as an alternative management approach for high-risk populations such as the frail or patients who have a history of cardiac surgery. Beyond the immediate threat of aortic rupture, organ malperfusion stands out as the most feared complication of ATAAD, also elevating perioperative risk significantly. In such cases, careful assessment of patient’s hemodynamic status is paramount. For stable patients, a thorough preoperative strategy and multidisciplinary discussions are encouraged. Notably, the advent of endovascular techniques provides viable lower-risk alternatives to the traditional open approach. The consequences of ATAAD surgical intervention extend beyond the immediate procedural concerns, with a substantial impact on the patient’s overall function. Prioritizing patient-centered care becomes imperative in aligning management with individual goals of care. This review seeks to provide insights into these considerations by offering a stepwise approach to patient-centered decision-making in ATAAD management.

Levelized cost of driving for medium and heavy-duty battery electric trucks

The total cost of ownership (TCO) of trucks is known as one of the main decision-making factors by logistics operators for adopting alternative powertrains such as battery electric trucks (BETs). In this study, we develop a very detailed levelized cost of driving (LCOD) model to analyse the TCO of BETs and conventional trucks (CTs) in medium and heavy-duty truck weight classes. The model has methodological advancements such as developing opportunity costs for charging activities, using a detailed operational time calculation, and analysing the optimum driving ranges or battery sizing. By implementing an extensive sensitivity analysis of LCOD for CTs and BETs over 43 variables, it is revealed that the key parameters such as operational driving range, battery pack price, state of charge of battery, driver cost, “mid-shift” charging power, ambient temperature, opportunity charging, and driving speed have major impacts on the cost competitiveness of BETs vs. CTs. In addition, the impact of battery and charging technology improvements as well as designing optimum driving ranges are examined in three different operational trip profiles (urban, short-haul or regional, long-haul). The result shows that: 1) BETs in urban trip profiles with the current and/or short-term battery technology might be economically viable alternatives for CTs without the help of the policy measures, 2) BETs with below 40 t gross vehicle weight and the long-term improvements in battery technology in all the operational trip profiles might be economically viable alternatives for CTs without the help of the policy measures, and 3) the implementation of policy measures affecting the relative costs of CTs and BETs and development of fast-charging facilities would be needed to support the above 40 t BETs in short-haul and long-haul trips for the current and/or short-term as well as mid-term battery technologies.

MICROSURGICAL REIMPLANTATION OUTCOMES FOR COMPLETE AND INCOMPLETE AMPUTATIONS OF DISTAL PHALANGES OF FINGERS.

The intricate endeavor of replanting the distal phalanx of the finger remains a persistent challenge. In the pursuit of addressing this concern, microsurgical replantation procedures have been systematically examined for distal phalanx injuries encircling the distal interphalangeal (DIP) joint, conducted at the Orthopaedic Hospital situated in Ho Chi Minh City. This investigation encompassed a cohort of 31 patients, comprising individuals with 17 instances of complete and 21 instances of incomplete amputations of the distal phalanges. The subjects' ages spanned a range from 3 to 56 years. The study divulged that eight fingers, involving four complete amputations and four incomplete amputations, did not achieve successful outcomes. In contrast, the remaining 30 fingers exhibited survival. A meticulous long-term follow-up of 17 fingers, extending over a period exceeding six months, unveiled commendable achievements encompassing satisfactory sensory recovery, cosmetic enhancement, and the resumption of pre-injury occupational activities by the patients. Vein anastomosis was revealed as a notably challenging aspect of the surgical procedures. In scenarios where conventional vein suturing was rendered unfeasible, the innovative recourse of one-way drainage emerged as a viable alternative. The endeavor to replant the distal phalanx of the finger engenders a substantial level of complexity, particularly in the realm of venous anastomosis. This research underscores the need for focused efforts to address and surmount the intricacies associated with this aspect of surgical intervention.

Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia

Accurately simulating glacier mass balance (GMB) data is crucial for assessing the impacts of climate change on glacier dynamics. Since physical models often face challenges in comprehensively accounting for factors influencing glacial melt and uncertainties in inputs, machine learning (ML) offers a viable alternative due to its robust flexibility and nonlinear fitting capability. However, the effectiveness of ML in modeling GMB data across diverse glacier types within High Mountain Asia has not yet been thoroughly explored. This study addresses this research gap by evaluating ML models used for the simulation of annual glacier-wide GMB data, with a specific focus on comparing maritime glaciers in the Niyang River basin and continental glaciers in the Manas River basin. For this purpose, meteorological predictive factors derived from monthly ERA5-Land datasets, and topographical predictive factors obtained from the Randolph Glacier Inventory, along with target GMB data rooted in geodetic mass balance observations, were employed to drive four selective ML models: the random forest model, the gradient boosting decision tree (GBDT) model, the deep neural network model, and the ordinary least-square linear regression model. The results highlighted that ML models generally exhibit superior performance in the simulation of GMB data for continental glaciers compared to maritime ones. Moreover, among the four ML models, the GBDT model was found to consistently exhibit superior performance with coefficient of determination (R2) values of 0.72 and 0.67 and root mean squared error (RMSE) values of 0.21 m w.e. and 0.30 m w.e. for glaciers within Manas and Niyang river basins, respectively. Furthermore, this study reveals that topographical and climatic factors differentially influence GMB simulations in maritime and continental glaciers, providing key insights into glacier dynamics in response to climate change. In summary, ML, particularly the GBDT model, demonstrates significant potential in GMB simulation. Moreover, the application of ML can enhance the accuracy of GMB modeling, providing a promising approach to assess the impacts of climate change on glacier dynamics.

Algorithm-Based Data Generation (ADG) Engine for Dual-Mode User Behavioral Data Analytics

The increasing significance of data analytics in modern information analysis is underpinned by vast amounts of user data. However, it is only feasible to amass sufficient data for various tasks in specific data-gathering contexts that either have limited security information or are associated with older applications. There are numerous scenarios where a domain is too new, too specialized, too secure, or data are too sparsely available to adequately support data analytics endeavors. In such cases, synthetic data generation becomes necessary to facilitate further analysis. To address this challenge, we have developed an Algorithm-based Data Generation (ADG) Engine that enables data generation without the need for initial data, relying instead on user behavior patterns, including both normal and abnormal behavior. The ADG Engine uses a structured database system to keep track of users across different types of activity. It then uses all of this information to make the generated data as real as possible. Our efforts are particularly focused on data analytics, achieved by generating abnormalities within the data and allowing users to customize the generation of normal and abnormal data ratios. In situations where obtaining additional data through conventional means would be impractical or impossible, especially in the case of specific characteristics like anomaly percentages, algorithmically generated datasets provide a viable alternative. In this paper, we introduce the ADG Engine, which can create coherent datasets for multiple users engaged in different activities and across various platforms, entirely from scratch. The ADG Engine incorporates normal and abnormal ratios within each data platform through the application of core algorithms for time-based and numeric-based anomaly generation. The resulting abnormal percentage is compared against the expected values and ranges from 0.13 to 0.17 abnormal data instances in each column. Along with the normal/abnormal ratio, the results strongly suggest that the ADG Engine has successfully completed its primary task.

Effectiveness of Mediation and Arbitration as Alternative Dispute Resolution Methods in Mexico

Purpose: To aim of the study was to analyze effectiveness of mediation and arbitration as alternative dispute resolution methods
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: Mediation and arbitration offer efficient, cost-effective alternatives to litigation. Mediation involves facilitated negotiation sessions with a neutral mediator, fostering open communication and tailored solutions. Arbitration entails submitting disputes to a neutral arbitrator for a binding decision. Both methods ensure confidentiality, expertise, and enforceability, making them highly effective in resolving disputes outside of court.
 Unique Contribution to Theory, Practice and Policy: Theory of social exchange, justice theory & game theory may be used to anchor future studies on effectiveness of mediation and arbitration as alternative dispute resolution methods. Practitioners in the field of alternative dispute resolution should prioritize enhancing their skills and competencies to effectively facilitate mediation and arbitration processes. Policymakers should prioritize the promotion of mediation and arbitration as viable alternatives to traditional litigation within legal frameworks and regulatory environments.

Problematising Hierarchy and Dualism for Ecological Concern: Johnsen’s Decolonial Methodology in Defence of Non-Hierarchical Worldmaking

The climate crisis presents an urgent problem for World Christianity. Since Lynn White, Jr., argued that ‘Christianity is the most anthropocentric religion the world has seen’ (White 1967), theologians have debated to what extent Christianity is responsible for ecological crisis. In this article, I will focus on two related problems for Christian thought that Majority World theologians have highlighted – hierarchy and dualism – in order to postulate what a non-hierarchical Christian worldview might entail, drawing on the work of Sámi Norwegian Lutheran theologian Tore Johnsen, primarily his recently published book Sámi Nature-Centered Christianity in the European Arctic (2022). This article utilises a multidisciplinary, World Christianity approach to theology that draws upon Johnsen’s work to examine the two themes of hierarchy and dualism, critically questioning these concepts and examining theological implications for the climate crisis. Johnsen’s research amongst the Sámi demonstrates their expression of ‘nature-centred’ Christianity that exhibits a non-hierarchical cosmology. He contrasts this with Western Christian expressions, in particular that of the Church of Norway. Johnsen’s decolonial approach questions aspects of the Western worldview critically and helpfully with reference to the climate crisis. This article therefore problematises two related concepts of hierarchy and dualism, notions which have become embedded within Christian tradition. In questioning these underlying concepts, it draws upon Johnsen’s work to consider whether and to what extent a non-hierarchical expression of Christianity might serve as a viable alternative.

MSK Ultrasound: A Powerful Tool for Evaluating and Diagnosing Pectoralis Major Injuries in Healthcare Practice.

Accurately diagnosing pectoralis major injuries, particularly in athletes, often presents a challenge for healthcare practitioners. Although pectoralis muscle injuries are relatively uncommon, the diagnosis of a tear may be overlooked without careful screening by a thorough physical examination of both the injured and uninjured sides. While magnetic resonance imaging (MRI) has traditionally held the gold standard, musculoskeletal ultrasound (MSKUS) has emerged as a viable alternative. This article delves into the power of MSKUS in evaluating and diagnosing pectoralis major injuries, highlighting its dynamic capabilities, real-time visualization, and cost-effectiveness in comparison to MRI. By equipping healthcare professionals with a thorough understanding of MSKUS's potential, this article aims to empower them to confidently diagnose and manage pectoralis major injuries, ultimately improving patient outcomes and facilitating a faster return to function.

Short-term clinical outcomes of percutaneous biliary tract interventions: analysis of success and complication rates.

Obstructive jaundice is a clinical syndrome that is commonly seen in gastroenterology. Endoscopic retrograde cholangiopancreatography (ERCP) has been recognized as a first-choice therapeutic approach, with percutaneous biliary interventions (PBIs) being a viable alternative. Recent data questions the performance and safety profile of PBIs.

Vertical bearing capacity of spun precast concrete pile in liquefiable soil: a case study

Spun precast prestressed concrete (SPC) pile has been used in many parts of the world as a viable foundation alternative. This study assesses the load-carrying capacity of SPC piles passing through a deep soft subsoil layer and resting on a dense sand layer. The vertical bearing capacity of the SPC pile has been estimated using various analytical methods and static pile load tests for the Jolshiri area of Dhaka. The liquefaction potential of the site has been assessed using local seismic site conditions, field and laboratory test data. The liquefaction analysis suggests that the topsoil layer is liquefiable to a depth of 4.5 m. The capacity obtained from the load test is compared with those obtained from the different methods, ultimate push-in load, and local design guidelines. Finite Element Analysis (FEA) was performed considering the hardening soil (HS) model using PLAXIS 3D to simulate field conditions. The load settlement response obtained from FEA shows a good agreement with the test results. The capacity examinations primarily suggest that the SPC pile can be a viable foundation solution for the subsoil conditions of Jolshiri Abasion area of Dhaka.

Chitosan-based foam composites for hexavalent chromium remediation: Effect of microcellulose and crosslinking agent content

Potentially toxic metal ions, such as hexavalent chromium (Cr6+), present in water concern the population's health due to their persistence, bioaccumulation potential, and high toxicity. Highly porous materials based on polysaccharides are promising technologies for metal removal due to their high surface area, biodegradability, and low toxicity. This study evaluated the effect of concentrations of microcellulose (0.5, 1, and 1.5 %) and glutaraldehyde (1, 2, and 3 %) in the adsorption capacity and mechanical properties of chitosan foams. The developed foams exhibited a three-dimensional structure with interconnected pores. Compared to foams without microcellulose, adding 1.5 % microcellulose increased up to 180 % in maximum stress supported by the foams and up to 135 % in Young's modulus. However, Cr6+ sorption capacity decreased with increasing microcellulose and crosslinking agent content due to the occupation of amino groups. Still, the foams exhibited a highly favorable sorption behavior, and the Sips isotherm model provided the best fit to the experimental data. The maximum sorption capacity reached approximately 1.4 mmol·g−1 at pH 4.0 and 25 °C. The foam structural integrity, enhanced mechanical properties, and efficient sorption capacity make them viable alternatives for environmentally friendly and cost-effective treatment of water contaminated with Cr6+ ions.

Nutritional and functional properties of photosynthetic microorganism proteins: A comparison with soy protein isolate and wheat protein

As a widely acknowledged source of sustainable food protein, there has been limited research on the functional properties of photosynthetic microorganism proteins (PsmPs) applied in food. The nutritional and functional attributes for meat analogue production of Spirulina platensis protein (SpirP), Chlorella pyrenoidosa protein (ChloP), and Schizochytrium sp. protein (SchiP) were investigated and compared with two widely utilized proteins: soy protein isolate (SPI) and wheat protein (WheaP). At a neutral pH, SpirP and SchiP exhibited high emulsifying activities of 69 and 66 m2/g, while ChloP (20 m2/g) was comparable to SPI (15 m2/g) and WheaP (19 m2/g). Their remarkable foaming capacity indicated their potentials to produce meat analogues with fibrous structures. The water absorption capacity of PsmPs (4.4–4.8 g water/g protein) was comparable to WheaP (4.7 g water/g protein), while the oil absorption capacity (3.7–4.4 g oil/g protein) was higher than SPI (2.7 g oil/g protein) and WheaP (3.3 g oil/g protein), implying their potential to produce juicy and tasty meat analogues. Besides, the heat-induced photosynthetic microorganism protein gels had stable structures. In summary, SpirP, ChloP, and SchiP emerge as outstanding protein sources and viable alternatives to SPI for the production of meat analogues.

Comparing the performance of machine learning methods in estimating the shear wave transit time in one of the reservoirs in southwest of Iran.

Shear wave transit time is a crucial parameter in petroleum engineering and geomechanical modeling with significant implications for reservoir performance and rock behavior prediction. Without accurate shear wave velocity information, geomechanical models are unable to fully characterize reservoir rock behavior, impacting operations such as hydraulic fracturing, production planning, and well stimulation. While traditional direct measurement methods are accurate but resource-intensive, indirect methods utilizing seismic and petrophysical data, as well as artificial intelligence algorithms, offer viable alternatives for shear wave velocity estimation. Machine learning algorithms have been proposed to predict shear wave velocity. However, until now, a comprehensive comparison has not been made on the common methods of machine learning that had an acceptable performance in previous researches. This research focuses on the prediction of shear wave transit time using prevalent machine learning techniques, along with a comparative analysis of these methods. To predict this parameter, various input features have been employed: compressional wave transit time, density, porosity, depth, Caliper log, and Gamma-ray log. Among the employed methods, the random forest approach demonstrated the most favorable performance, yielding R-squared and RMSE values of 0.9495 and 9.4567, respectively. Furthermore, the artificial neural network, LSBoost, Bayesian, multivariate regression, and support vector machine techniques achieved R-squared values of 0.878, 0.8583, 0.8471, 0.847 and 0.7975, RMSE values of 22.4068, 27.8158, 28.0138, 28.0240 and 37.5822, respectively. Estimation analysis confirmed the statistical reliability of the Random Forest model. The formulated strategies offer a promising framework applicable to shear wave velocity estimation in carbonate reservoirs.

The Effects of Tillage Systems on the Management of Agronomic Factors in Winter Oilseed Rape Cultivation: A Case Study in North-Eastern Poland

The aim of this study was to analyze agronomic management in the production of winter oilseed rape (WOR) in different tillage systems. The field experiment (Poland, 2016–2019) had a 35–1 fractional factorial design with two replications, where five fixed factors were tested at three levels. The experimental factors were as follows. A—tillage: (A0) strip-till, (A1) low-till, (A2) conventional tillage; B—weed control: (B0) pre-emergent, (B1) foliar, (B2) sequential; C—growth regulation: (C0) none, (C1) in fall, (C2)—in fall and spring; D—rate of spring nitrogen (N) fertilizer: (D0) 160, (D1) 200, (D2) 240 kg ha−1; E—rate of spring sulfur (S) fertilizer: (E0) 0, (E1) 40, (E2) 80 kg ha−1. Seed yields were the highest in the strip-till system (5.95 Mg ha−1). The effectiveness of weed control methods varied across different tillage systems. Foliar herbicides exerted the highest yield-forming effect in the strip-till system, pre-emergent and sequential herbicides were most effective in the low-till system, and pre-emergent herbicides were most effective in the conventional tillage system. Seed yields increased up to the N rate of 200 kg ha−1. The highest N rate of 240 kg ha−1 was justified only when S was applied in spring. Sulfur significantly increased seed yields (by 17%). The results of the study indicate that low-till and strip-till systems can be viable alternatives to the conventional tillage system in WOR production.

Engineering design and economic analysis of offshore seaweed farm

As global demand for sustainable biomass and need to mitigate global warming begin to rise, cultivation of seaweed has gained significant attention in recent years due to its potential for carbon recycling. However, limited availability of suitable coastal areas for large-scale seaweed cultivation has led to exploration of offshore environments as a viable alternative. The nature of many offshore environments often exposes seaweed farming systems to harsh environmental conditions, including strong waves, currents, and wind. These factors can lead to structural failures, kelp losses, and significant financial losses for seaweed farmers. The main objective of this study is to present a robust design and numerical analysis of an economically viable floating offshore kelp farm facility, and evaluate its stability and mooring system performance. A numerical method of preliminary designs of the offshore aquaculture systems were developed using the OrcaFlex software. The models were subjected to a series of dynamic environmental loading scenarios representing extreme events. These simulations aimed to forecast the overall dynamic response of an offshore kelp farm at a depth of 50m and to determine the best possible farm design with structural integrity for a selected offshore environment. Furthermore, to assess the economic feasibility of establishing offshore seaweed farms, a comprehensive capital expenses analysis was conducted. The results revealed that, in terms of the kelp farms with the same number of the kelp cultivating lines, the cost of building kelp farms will be strongly affected by the cost of mooring lines. The present study may help to understand the dynamic response and economic feasibility of offshore kelp farms.

The Virtual Geriatric Assessment Interdisciplinary Team Project: Interprofessional Geriatric Training Against the Backdrop of COVID-19.

Interprofessional geriatric education programs enhance trainees' knowledge of older adults, and the valuable contributions health and social care practitioners make to their well-being when specialists work collaboratively. In response to the 2020 COVID-19 pandemic restrictions, in-person geriatric interprofessional education (IPE) programs were redesigned for virtual delivery. Nineteen virtual programs were held between September 2020 and December 2022. Of the 369 health and social care trainees who participated, 67.2% completed both pre- and post-program surveys. Survey instruments included the Interprofessional Collaborative Competency Attainment Survey (ICASS), which measures perceptions associated with patient-centered, team-based, collaborative care. Significant differences were obtained across ICASS domains, including communication, conflict management/resolution, and team functioning, suggesting that virtual programs may enhance attitudes and perceived abilities for interprofessional collaborative practice. Furthermore, participants' perceived understanding of older adult needs improved, as did their interest in geriatrics. Results illustrate that virtual geriatric interprofessional (IP) programs may be viable alternatives to in-person opportunities.

Ecological factors affecting minerals and nutritional quality of "Dryopteris filix-mas (L.) Schott": an underutilized wild leafy vegetable in rural communities.

Dryopteris filix-mas (hereafter D. filix-mas), a wild leafy vegetable, has gained popularity among high mountain residents in the Hindukush-Himalaya region due to its exceptional nutritional profile, and their commercial cultivation also offers viable income alternatives. Nevertheless, besides phytochemicals with medicinal applications, ecological factors strongly affect their mineral contents and nutritional composition. Despite this, little has been known about how this wild fern, growing in heterogeneous ecological habitats with varying soil physiochemical properties and coexisting species, produces fronds with optimal mineral and nutritional properties. Given its nutritional and commercial significance, we investigated how geospatial, topographic, soil physiochemical characteristics and coexisting plants influence this widely consumed fern's mineral and nutrient content. We collected soil, unripe fern fronds, and associated vegetation from 27 D. filix-mas populations in Swat, NW Pakistan, and were analyzed conjointly with cluster analysis and ordination. We found that the fronds from sandy-loam soils at middle elevation zones exhibited higher nitrogen contents (9.17%), followed by crude fibers (8.62%) and fats (8.09%). In contrast, juvenile fronds from the lower and high elevation zones had lower moisture (1.26%) and ash (1.59%) contents, along with fewer micronutrients such as calcium (0.14-0.16%), magnesium (0.18-0.21%), potassium (0.72-0.81%), and zinc (12% mg/kg). Our findings indicated the fern preference for middle elevation zones with high organic matter and acidic to neutral soil (pH ≥ 6.99) for retaining higher nutritional contents. Key environmental factors emerged from RDA analysis, including elevation (r = -0.42), aspect (r = 0.52), P-3 (r = 0.38), K+ (r = 0.41), EC (r = 0.42), available water (r = -0.42), and field capacity (r = -0.36), significantly impacting fern frond's mineral accumulation and nutrient quality enhancement. Furthermore, coexisting plant species (r = 0.36) alongside D. filix-mas played a pivotal role in improving its mineral and nutritional quality. These findings shed light on the nutritional potential of D. filix-mas, which could help address malnutrition amidst future scarcity induced by changing climates. However, the prevalent environmental factors highlighted must be considered if the goal is to cultivate this fern on marginal lands for commercial exploitation with high mineral and nutrient yields in Hindukush-Himalaya.