Hasil untuk "Costs"

Bonifasius Sumardiyanto, Cecillia Diana Lelyta Marsonia

Slums are one of the threats to Cultural Heritage Areas (KCB) which consist of traditional houses, especially those with living museum status such as KCB Kotagede in Yogyakarta. One of the main causes of slums is the inability of the owner (heir) to provide funds to preserve the building, which requires large costs. Assistance from the government or other parties, which is often incidental, is not a sustainable solution. For this reason, efforts are needed to optimize the potential of KCB so that it can generate sustainable conservation costs. One effort is to adapt traditional houses into homestays that offer cultural experiences for tourists. The study was carried out in 4 (four) residential buildings which were selected using purposive sampling. The study method begins with identifying initial plans of traditional houses and identifying plans for developing adapted designs. Next, using the Form - Function - Meaning structural approach, an analysis was carried out to what extent the architectural meaning of a traditional house was maintained in its adaptation into a homestay. This study reveals that the adaptation of a traditional house into a homestay can be done while maintaining its architectural meaning.

Hasanah Hasanah, Wulandari wulandari, Afriani afriani et al.

Porphyridium cruentum has advantages in pigments and exopolysaccharides, so it has the potential to be developed in the food, pharmaceutical, nutraceutical, and cosmetic industries. Porphyridium cruentum cultivation media uses synthetic and indoors, causing high costs. This study aims to determine the growth performance of Porphyridium cruentum in different mediums and method of cultivation. The research methods used cultivating Porphyridium cruentum for 7 days with four treatments, namely indoors Guillard media (IGM), outdoors Guillard media (OGM), indoors fertilizer media (IFM), and outdoors fertilizer media (OFM. Each treatment had three replications. Growth was identified using an optical density spectrophotometer uv-vis, gravimetrically dried weight of biomass and pH adjustment during 7 days of cultivation. The result shows the best growth performance in IFM, followed by IGM, OFM, and OGM. Fertilizer media is better for the growth of Porphyridium cruentum than Guillard media. pH growth Porphyridium cruentum during cultivation 7-7.5. Indoor cultivation is better than outdoor cultivation. The highest biomass was IFM, which had the best performance in IFM with OD 0.247, pH 7, and biomass 79.6%.

Ion Popa, Sorina-Geanina Stănescu, Anișoara Duică et al.

The food industry faces complex challenges in managing supply chains, significantly affecting operational performance and costs. This paper explores the critical factors influencing the efficiency of food supply chains, such as product perishability, seasonality, climate change, and high logistics costs. The study uses an applied approach based on modelling a cost function that integrates the main components of supply chain expenses — procurement, transportation, warehousing, production and distribution — and how they are affected by industry-specific challenges. The proposed cost function allows for assessing the impact of these variables on total costs and identifying critical areas for optimisation. The results obtained demonstrate that monitoring logistical conditions, adjusting stocks based on seasonal forecasts and optimising transport routes are essential measures to reduce losses and increase the competitiveness of companies in the food industry. The study's applied impact consists of providing a practical cost optimisation tool applicable to manufacturers and distributors. The conclusions emphasise the importance of an integrated approach to risk and cost management in the food industry, providing recommendations for sustainable practices and strategies to increase long-term competitiveness.

Aleksanteri Hamalainen, Aku Karhinen, Jesse Miettinen et al.

Rotating machines are extremely common in many industries, and their maintenance involves substantial costs and labor. Most recent studies aiming to automate fault diagnosis have focused on deep learning, but industry adoption has been slow owing to the lack of well-curated datasets and the complexity of the methods. We propose a new method called Rapid Few-shot Condition Monitoring (Rapid-FSCM), which enables the rapid deployment of deep learning-based condition monitoring models and is readily extensible to future advancements in the field. This will make it simpler for the industry to conduct machine condition monitoring without the cost of an expert. Rapid-FSCM utilizes few-shot learning and the InceptionTime convolutional neural network to enable training on data from a related base domain more readily available than data from the target domain. In addition, the prototypical networks method for few-shot learning is modified to enable the deployment of the model as an anomaly detector, even before any fault samples have been recorded. After faults have occurred and been recorded, the model demonstrates the ability to initiate fault diagnosis without further retraining. Validated with three datasets, two gear datasets from a test bench with complex features, and the CWRU bearing dataset, the model was shown to have high accuracy in target domains containing unseen faults, sensors, operating conditions, and even entirely new components. The developed method can be used to rapidly deploy a condition monitoring model for any rotating machine without the need to first conduct a large data acquisition process.

W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera et al.

The Vehicle Routing Problem (VRP) represents a thoroughly investigated domain within operations research, yielding substantial cost savings in global transportation. The fundamental objective of the VRP is to determine the optimal route plan that minimizes the overall distance traveled. This study employs VRP to address the challenge of distributing fresh agricultural products within retail chains. It introduces an integrated bi-objective VRP model that concurrently optimizes resource allocation, order scheduling, and route planning. The proposed model incorporates two objective functions with the goals of minimizing total distribution costs and ensuring timely product deliveries to retail outlets. Real-world characteristics are integrated to enhance practical applicability. All solution algorithms and the developed VRP model undergo testing using data from one of Sri Lanka's largest retail chains. Numerical experiments showcase the efficiency of the proposed algorithm in solving real-world VRP problems. Moreover, the proposed VRP model achieves a 19% reduction in daily distribution costs, including a 24% saving in fuel costs. This not only provides financial benefits but also contributes to the reduction of the carbon footprint of retail chains. The model ensures on-time deliveries to 95% of retail outlets, which is crucial for maintaining the quality of fresh food. The findings of this study underscore the significant cost savings, enhanced sustainability, and improved quality associated with the efficient distribution of fresh agricultural products within retail chains.

Subhabrata Sengupta, Rupayan Das, Satyajit Chakrabarti

Information retrieval aims to find the most important data for specific queries. The challenge is retrieving relevant data efficiently due to the large search area. Existing solutions lead to unnecessary processing costs. Additionally, identifying the main focus of the query is crucial for targeted retrieval. Current methods struggle to address these issues effectively. To overcome these challenges, we have proposed a goal-question-indicator (GQI) approach for personalized learning inquiry (PLA). This approach allows for efficient retrieval of variable-sized data with reduced processing requirements. We have also presented the open learning analytics platform's (Open-LAP) pointer motor segment, which helps end users specify goals, generates discussion topics, and provides self-characterizing pointers.

Salmaan Keshavjee, Meredith B Brooks, Tom Nicholson et al.

Objectives To estimate the economic impact of failure to find and treat tuberculosis disease and prevent tuberculosis infection from progressing to active disease.Design Estimating the economic cost of not finding and treating a patient suffering from tuberculosis.Setting Estimation methodology is developed in the Indian context, as informed by local costs and reported tuberculosis epidemiology.Participants No individual participants were included.Primary and secondary outcome measures The primary outcome measure is the total cost of patients with drug-susceptible and drug-resistant tuberculosis who are and are not found and treated by tuberculosis programmes, including costs for medications, lost productivity, healthcare services and furthered transmission. We calculate the economic burdens by varying the number of individuals a person sick with tuberculosis infects (10 or 15 people) and the risk of progression to tuberculosis disease if infected (5 or 8%). The secondary outcome measure is the amount saved by finding a patient early or who would not have otherwise been found. All costs are presented in US dollars (exchange rate: 72 Indian rupees/1 US$).Results By finding and treating a patient early before furthered transmission occurs—or stopping progression of tuberculosis infection to tuberculosis disease with preventive therapy—the Indian health system can save US$5502 to US$15 825 and US$5846 to US$25 575, for each individual with drug-susceptible and drug-resistant tuberculosis, respectively, across scenarios.Conclusions These estimates provide crude, lower bounds for the potential costs of not appropriately diagnosing and treating a single patient with active tuberculosis in a timely manner, or preventing a patient with tuberculosis infection from progressing to active disease. The actual financial burden on society is far higher than estimated using this simple, short-term cost-effective analyses. Our results highlight the limitations of tuberculosis costing models to date, and demonstrate the importance of accounting for airborne transmission of tuberculosis.

Adena R. Rissman, Ana Fochesatto, Erin B. Lowe et al.

Perennial grasslands, including prairie and pasture, have declined with tremendous environmental and social costs. This decline reflects unequal policy support for grasslands and managed grazing compared to row crops. To create a resource for community partners and decision-makers, we reviewed and analyzed the policy tools and implementation capacity that supports and constrains grasslands and managed grazing in the U.S. Upper Midwest. Risk reduction subsidies for corn and soybeans far outpace the support for pasture. Some states lost their statewide grazing specialist when the federal Grazing Lands Conservation Initiative lapsed. The United States Department of Agriculture, Natural Resources Conservation Service support for lands with prescribed grazing practices declined after 2005 but remained relatively steady 2010–2020. These results reveal the policy disadvantage for grasslands and managed grazing in comparison with row crop agriculture for milk and meat production. Grassland and grazing policies have an important nexus with water quality, biodiversity, carbon and outdoor recreation policy. Socially just transitions to well-managed, grazed grasslands require equity-oriented interventions that support community needs. We synthesized recommendations for national and state policy that farmers and other grazing professionals assert would support perennial grasslands and grazing, including changes in insurance, conservation programs, supply chains, land access, and fair labor. These policies would provide critical support for grass-based agriculture and prairies that we hope will help build soil, retain nutrients, reduce flooding and enhance biodiversity while providing healthy food, jobs, and communities.

Jessica Pitts, Kunal Singhal, Yashashree Apte et al.

Dual-tasking can cause cognitive–motor interference (CMI) and affect task performance. This study investigated the effects of age, gait speed, and type of cognitive task on CMI during gait. Ten younger and 10 older adults walked on a pressure-sensitive GAITRite walkway which recorded gait speed and step length. Participants walked at a slow, preferred, or fast speed while simultaneously completing four cognitive tasks: visuomotor reaction time (VMRT), serial subtraction (SS), word list generation (WLG), and visual Stroop (VS). Each combination of task and speed was repeated for two trials. Tasks were also performed while standing. Motor and cognitive costs were calculated with the formula: ((single-dual)/single × 100). Higher costs indicate a larger reduction in performance from single to dual-task. Motor costs were higher for WLG and SS than VMRT and VS and higher in older adults (<i>p</i> < 0.05). Cognitive costs were higher for SS than WLG (<i>p</i> = 0.001). At faster speeds, dual-task costs increased for WLG and SS, although decreased for VMRT. CMI was highest for working memory, language, and problem-solving tasks, which was reduced by slow walking. Aging increased CMI, although both ages were affected similarly by task and speed. Dual-task assessments could include challenging CMI conditions to improve the prediction of motor and cognitive status.

Ali Aytac Seymen, Ezgi Gulten, Erol Ozgur et al.

Abstract Coronavirus Disease-19 (COVID-19) is a highly contagious infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The development of rapid antigen tests has contributed to easing the burden on healthcare and lifting restrictions by detecting infected individuals to help prevent further transmission of the virus. We developed a state-of-art rapid antigen testing system, named DIAGNOVIR, based on immune-fluorescence analysis, which can process and give the results in a minute. In our study, we assessed the performance of the DIAGNOVIR and compared the results with those of the qRT-PCR test. Our results demonstrated that the sensitivity and specificity of the DIAGNOVIR were 94% and 99.2%, respectively, with a 100% sensitivity and 96.97% specificity, among asymptomatic patients. In addition, DIAGNOVIR can detect SARS‑CoV‑2 with 100% sensitivity up to 5 days after symptom onset. We observed that the DIAGNOVIR Rapid Antigen Test’s limit of detection (LoD) was not significantly affected by the SARS‑CoV‑2 variants including Wuhan, alpha (B1.1.7), beta (B.1.351), delta (B.1.617.2) and omicron (B.1.1.529) variants, and LoD was calculated as 8 × 102, 6.81 × 101.5, 3.2 × 101.5, 1 × 103, and 1 × 103.5 TCID50/mL, respectively. Our results indicated that DIAGNOVIR can detect all SARS-CoV-2 variants in just seconds with higher sensitivity and specificity lower testing costs and decreased turnover time.

Simone Balmelli, Francesco Moresino

We address the problem of charging plug-in electric vehicles (PEVs) in a decentralized way and under stochastic dynamics affecting the real-time electricity tariff. The model is formulated as a Nash equilibrium seeking problem, where players wish to minimize the costs for charging their own PEVs. For finite PEVs populations, the Nash equilibrium does not correspond to the social optimum, i.e., to a control strategy minimizing the total electricity costs at the aggregate level. We accordingly introduce some taxes/incentives on the price of electricity for charging PEVs and show that it is possible to tune them so that (a) the social optimum is reached as a Nash equilibrium, (b) in correspondence with this equilibrium, players do not pay any net total tax, nor receive any net total incentive.

Janine B. Kastelijn, Yorick L. van de Pavert, Marc G. Besselink et al.

Abstract Background Malignant gastric outlet obstruction (GOO) is a debilitating condition that frequently occurs in patients with malignancies of the distal stomach and (peri)ampullary region. The standard palliative treatment for patients with a reasonable life expectancy and adequate performance status is a laparoscopic surgical gastrojejunostomy (SGJ). Recently, endoscopic ultrasound-guided gastroenterostomy (EUS-GE) emerged as a promising alternative to the surgical approach. The present study aims to compare these treatment modalities in terms of efficacy, safety, and costs. Methods The ENDURO-study is a multicentre, open-label, parallel-group randomized controlled trial. In total, ninety-six patients with gastric outlet obstruction caused by an irresectable or metastasized malignancy will be 1:1 randomized to either SGJ or EUS-GE. The primary endpoint is time to tolerate at least soft solids. The co-primary endpoint is the proportion of patients with persisting or recurring symptoms of gastric outlet obstruction for which a reintervention is required. Secondary endpoints are technical and clinical success, quality of life, gastroenterostomy dysfunction, reinterventions, time to reintervention, adverse events, quality of life, time to start chemotherapy, length of hospital stay, readmissions, weight, survival, and costs. Discussion The ENDURO-study assesses whether EUS-GE, as compared to SGJ, results in a faster resumption of solid oral intake and is non-inferior regarding reinterventions for persistent or recurrent obstructive symptoms in patients with malignant GOO. This trial aims to guide future treatment strategies and to improve quality of life in a palliative setting. Trial registration International Clinical Trials Registry Platform (ICTRP): NL9592. Registered on 07 July 2021.

Yihan Chen, Xingyu Gu, Zhen Liu et al.

Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful application of Transformer architecture in natural language processing (NLP) tasks, a novel Transformer method called LeViT was introduced for automatic asphalt pavement image classification. LeViT consists of convolutional layers, transformer stages where Multi-layer Perception (MLP) and multi-head self-attention blocks alternate using the residual connection, and two classifier heads. To conduct the proposed methods, three different sources of pavement image datasets and pre-trained weights based on ImageNet were attained. The performance of the proposed model was compared with six state-of-the-art (SOTA) deep learning models. All of them were trained based on transfer learning strategy. Compared to the tested SOTA methods, LeViT has less than 1/8 of the parameters of the original Vision Transformer (ViT) and 1/2 of ResNet and InceptionNet. Experimental results show that after training for 100 epochs with a 16 batch-size, the proposed method acquired 91.56% accuracy, 91.72% precision, 91.56% recall, and 91.45% F1-score in the Chinese asphalt pavement dataset and 99.17% accuracy, 99.19% precision, 99.17% recall, and 99.17% F1-score in the German asphalt pavement dataset, which is the best performance among all the tested SOTA models. Moreover, it shows superiority in inference speed (86 ms/step), which is approximately 25% of the original ViT method and 80% of some prevailing CNN-based models, including DenseNet, VGG, and ResNet. Overall, the proposed method can achieve competitive performance with fewer computation costs. In addition, a visualization method combining Grad-CAM and Attention Rollout was proposed to analyze the classification results and explore what has been learned in every MLP and attention block of LeViT, which improved the interpretability of the proposed pavement image classification model.

Naseer T. Alwan, S.E. Shcheklein, Obed M. Ali

Solar water distillation is an effective technology for producing potable water using sustainable energy sources. However, the widespread use of this technology in industrial and domestic applications is hindered by low daily production compared to other methods. In this study, a new modification was introduced by placing a hollow cylinder inside a solar distiller and then integrating the cylindrical solar distiller with a solar heater (modified solar still). An economic analysis and study of the chemical and physical properties of the modified solar still (MSS) were carried out. The MSS produced a 296–300% increase in distillate water yield compared to a commercial solar still (CSS) on 17 July 2019, and reached 400% in other months depending on weather conditions. The costs of producing a liter of distilled water from the conventional and modified solar stills were 0.0282 and 0.0268 $/lit, respectively. Thus, the proposed solar distiller design is economically feasibile, reducing the cost of production compared to a conventional distiller and previous studies. The distillate water produced by the MSS and CSS has given the best results to all TDS, pH, and electrical conductivity tests according to local and international standards.

Umut C. Kucuksezer, Cevdet Ozdemir, Lacin Cevhertas et al.

Allergen-specific immunotherapy (AIT) is the mainstay treatment for the cure of allergic disorders, with depicted efficacy and safety by several trials and meta-analysis. AIT impressively contributes to the management of allergic rhinitis, asthma and venom allergies. Food allergy is a new arena for AIT with promising results, especially via novel administration routes. Cell subsets with regulatory capacities are induced during AIT. IL-10 and transforming growth factor (TGF)-β are the main suppressor cytokines, in addition to surface molecules such as cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) and programmed cell death protein-1 (PD-1) within the micro milieu. Modified T- and B-cell responses and antibody isotypes, increased activity thresholds for eosinophils, basophils and mast cells and consequent limitation of inflammatory cascades altogether induce and maintain a state of sustained allergen-specific unresponsiveness. Established tolerance is reflected into the clinical perspectives as improvement of allergy symptoms together with reduced medication requirements and evolved disease severity. Long treatment durations, costs, reduced patient compliance and risk of severe, even life-threatening adverse reactions during treatment stand as major limiting factors for AIT. By development of purified non-allergenic, highly-immunogenic modified allergen extracts, and combinational usage of them with novel adjuvant molecules via new routes may shorten treatment durations and possibly reduce these drawbacks. AIT is the best model for custom-tailored therapy of allergic disorders. Better characterization of disease endotypes, definition of specific biomarkers for diagnosis and therapy follow-up, as well as precision medicine approaches may further contribute to success of AIT in management of allergic disorders.

Nicoletta Patrizi, Riccardo M. Pulselli, Elena Neri et al.

Overtopping breakwater systems are among the most promising technologies for exploiting wave energy to generate electricity. They consist in water reservoirs, embedded in piers, placed on top of ramps, higher than sea-level. Pushed by wave energy, seawater fills up the reservoirs and produces electricity by flowing back down through low headhydro turbines. Different overtopping breakwater systems have been tested worldwide in recent years. This study focuses on the Overtopping BReakwater for Energy Conversion (OBREC) system that has been implemented and tested in the harbor of Naples (Italy). The Life Cycle Assessment of a single replicable module of OBREC has been performed for analyzing potential environmental impacts, in terms of Greenhouse Gas Emissions, considering construction, installation, maintenance, and the operational phases. The Carbon Footprint (i.e., mass of CO2eq) to build wave energy converters integrated in breakwater systems has been estimated, more specifically the “environmental investment” (i.e., the share of Carbon Footprint due to the integration of wave energy converter) needed to generate renewable electricity has been assessed. The Carbon Intensity of Electricity (i.e., the ratio between the CO2eq emitted and the electricity produced) has been then assessed in order to demonstrate the profitability and the opportunity to foster innovation in the field of blue energy. Considering the impact for implementing an operational OBREC module (Carbon Footprint = 1.08 t CO2eq; Environmental Investment = 0.48 t CO2eq) and the electricity production (12.6 MWh/year per module), environmental benefits (avoided emissions) would compensate environmental costs (i.e., Carbon Footprint; Environmental Investment) those provided within a range of 25 and 13 months respectively.

Florian PHILIPP

Real estate arguably forms the most important asset to most households and the basis for their wealth. Around this context a model has been set up testing the relative affordability of real estate for the median household in Austria and the consequences of lower borrowing costs between 2004 and 2013 by vintage year. In this paper the hypothesis that the significant decline in base interest rates is not sufficient to offset the relative affordability loss caused by declining net household incomes and the simultaneous increase of real estate prices. To test this hypothesis a model has been set up comparing two different Housing Affordability Indices – one including and one excluding financing effects, having been compared via a multi factor model. Based on this calculation the author finds decreased base interest rates to offset relative affordability losses by only approximately 50%, verifying the hypothesis. The paper therefore argues for a potential decoupling of the residential housing market in Austria.

Andrew J Tanentzap, Anthony Lamb, Susan Walker et al.

Agriculture dominates the planet. Yet it has many environmental costs that are unsustainable, especially as global food demand rises. Here, we evaluate ways in which different parts of the world are succeeding in their attempts to resolve conflict between agriculture and wild nature. We envision that coordinated global action in conserving land most sensitive to agricultural activities and policies that internalise the environmental costs of agriculture are needed to deliver a more sustainable future.

Yawn BP, Madison S, Bertram S et al.

Barbara P Yawn,1 Suzanne Madison,1 Susan Bertram,1 Wilson D Pace,2 Anne Fuhlbrigge,3 Elliot Israel,3 Dawn Littlefield,1 Margary Kurland,1 Michael E Wechsler41Olmsted Medical Center, Department of Research, Rochester, MN, 2UCDHSC, Department of Family Medicine, University of Colorado Health Science Centre, Aurora, CO, 3Brigham and Women&amp;#39;s Hospital, Pulmonary and Critical Care Division, Boston, MA, 4National Jewish Medical Center, Division of Pulmonology, Denver, CO, USABackground: Published reports and studies related to patient compensation for clinical trials focus primarily on the ethical issues related to appropriate amounts to reimburse for patient&amp;#39;s time and risk burden. Little has been published regarding the method of payment for patient participation. As clinical trials move into widely dispersed community practices and more complex designs, the method of payment also becomes more complex. Here we review the decision process and payment method selected for a primary care-based randomized clinical trial of asthma management in Black Americans.Methods: The method selected is a credit card system designed specifically for clinical trials that allows both fixed and variable real-time payments. We operationalized the study design by providing each patient with two cards, one for reimbursement for study visits and one for payment of medication costs directly to the pharmacies.Results: Of the 1015 patients enrolled, only two refused use of the ClinCard, requesting cash payments for visits and only rarely a weekend or fill-in pharmacist refused to use the card system for payment directly to the pharmacy. Overall, the system has been well accepted by patients and local study teams. The ClinCard administrative system facilitates the fiscal accounting and medication adherence record-keeping by the central teams. Monthly fees are modest, and all 12 study institutional review boards approved use of the system without concern for patient confidentiality after reviewing all regulatory documents provided by ClinCard.Conclusion: This system works well for studies that recruit patients from widely dispersed practices and for studies that require flexibility in the amount of payments required, eg, the cost of eight different study medications across varying insurance and pharmacy systems.Keywords: clinical trial payment, clinical trials, ClinCard

Yong Wang, Daniel Paushter, Shusen Wang et al.

This study was designed to retrospectively compare the impact of crude Sigma V collagenase (Sigma V, n = 52) with high-purified Serva NB1 collagenase (Serva NB1, n = 42) on human islet isolation outcomes. A three-step filtration was applied to the crude Sigma V to remove endotoxin contamination and impurities; in addition, this process was used as a lot prescreening tool. Isolation outcomes were determined by digestion efficacy, islet yields, purity, viability, glucose-stimulated insulin release, and endotoxin content. The digestion efficacy between Sigma V and Serva NB1 was statistically significant (Sigma V: 64.71% vs. Serva NB1: 69.71%, p = 0.0014). However, the islet yields were similar (Sigma V: 23422.58 vs. Serva NB1: 271097 IEq, p = 0.23) between groups. There was no significant purity difference observed in fractions with purities greater than 75%. Viability (Sigma V: 93.3% vs. Serva NB1: 94.8%, p = 0.061) and stimulation indexes (Sigma V: 3.41 vs. Serva NB1: 2.74, p = 0.187) were also similar between the two groups. The impact of cold ischemia and age on the isolation outcome in the Sigma V group was comparable to the Serva NB1 group. The endotoxin content of the final products in the filtered Sigma V group was significantly less than that in the high-purified Serva NB1 group (0.022 vs. 0.052 EU/ml, p = 0.003). Additionally, in the Sigma V group there was minimal lot to lot variation and no significant loss of enzymatic activity after filtration. These findings indicate that the use of Sigma V or other crude enzyme blends for research pancreata is warranted to reduce isolation costs and increase the amount of islets available for critical islet research. These findings also validate the need for a systematic enzyme analysis to resolve these inconsistencies in overall enzyme quality once and for all.