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In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (DEA) to appraise sustainably resilient SCs is our purpose in this article. To do so, we present a new double-frontier methodology to provide optimistic and pessimistic efficiency measures in network structures. Moreover, ideas of outputs weak disposability, chance-constrained programming, and discrete dominance are incorporated in a unified framework of modelling efficient and inefficient production technologies. The new network DEA model also can address dissimilar types of data, including undesirable and integer-valued and ratio outputs, stochastic intermediate products, and integer-valued inputs in a unified framework. Furthermore, an aggregated Farrell type efficiency measure is developed which allows to provide the complete ranking of units so that each decision-making unit (DMU) has its own rank in both overall and divisional point of view. We show the unique features of our developed model using a real case study in paint industry to evaluate the efficiency and reducing carbon dioxide (CO2) emissions. The results show that how well the proposed models can evaluate the sustainability and resilience of supply chains in the presence of uncertainty and with dissimilar types of data.

Blood supply chains (BSCs) play a strategic and crucial role in healthcare systems especially in unexpected situations such as earthquakes and pandemic outbreaks. Nevertheless, measuring the sustainability and resilience of BSCs is a major challenge for many decision-makers in healthcare systems. To this end, this paper presents an advanced network data envelopment analysis (NDEA) method to evaluate the sustainability and resilience of BSCs. We deal with BSCs, including blood collection centers (BCCs), blood production centers (BPCs), and blood distribution centers (BDCs). A new directional distance function (DDF) is also developed for evaluating both the overall and stage efficiency scores. Our proposed model can deal with different types of data, including integers, undesirable outputs, negative, zero, and positive. The undesirable outputs are the outputs that adversely impact the performance of DMUs. Moreover, the developed method addresses the sustainability and resilience of BSCs. A case study is provided to demonstrate the usefulness of the proposed model.

In this paper, we reported the extraction process of five different flowering plants utilizing different dye extraction methods and solvents (ethanol and water) to choose the best dye removal process. The FTIR spectra revealed the presence of several clear functional groups for all five natural dyes. The analytical studies such as UV spectroscopy, column chromatography, and vacuum evaporation were performed to isolate the dyes from their solutions. The UV-Vis studies on the pigments of flower extracts indicated broad absorption peaks in the visible region including clear bandgaps. Among the studied pigments, Alternanthera ficoidea showed the lowest direct bandgap of 1.69 eV and an Urbach energy value of 6.33 meV. The dye extraction yield rate improvement was extended from 11.7 to 24.7% (water solvent) and 11.3–32.4% (ethanol solvent). Throughout the studies, it was observed that ethanol produced a better extraction for organic dyes than water as a solvent. Aging studies revealed that all the dyes at the room temperature showed better stability with minor changes in the observed optical parameters in oxygen-rich conditions; however, these parameters have shown significant variations at a 60 °C temperature.

BACKGROUND: Early-stage mycosis fungoides (MF) includes involvement of dermatopathic lymph nodes (LNs) or early lymphomatous LNs. There is a lack of unanimity among current guidelines regarding the indications for initial staging imaging in early-stage presentation of MF in the absence of enlarged palpable LNs. OBJECTIVES: To investigate how often imaging is performed in patients with early-stage presentation of MF, to assess the yield of LN imaging, and to determine what disease characteristics promoted imaging. METHODS: A review of clinicopathologically confirmed newly diagnosed patients with cutaneous patch/plaque (T1/T2) MF from PROspective Cutaneous Lymphoma International Prognostic Index (PROCLIPI) data. RESULTS: PROCLIPI enrolled 375 patients with stage T1/T2 MF: 304 with classical MF and 71 with folliculotropic MF. Imaging was performed in 169 patients (45%): 83 with computed tomography, 18 with positron emission tomography-computed tomography and 68 with ultrasound. Only nine of these (5%) had palpable enlarged (≥ 15 mm) LNs, with an over-representation of plaques, irrespectively of the 10% body surface area cutoff that distinguishes T1 from T2. Folliculotropic MF was not more frequently imaged than classical MF. Radiologically enlarged LNs (≥ 15 mm) were detected in 30 patients (18%); only seven had clinical lymphadenopathy. On multivariate analysis, plaque presentation was the sole parameter significantly associated with radiologically enlarged LNs. Imaging of only clinically enlarged LNs upstaged 4% of patients (seven of 169) to at least IIA, whereas nonselective imaging upstaged another 14% (24 of 169). LN biopsy, performed in eight of 30 patients, identified N3 (extensive lymphomatous involvement) in two and N1 (dermatopathic changes) in six. CONCLUSIONS: Physical examination was a poor determinant of LN enlargement or involvement. Presence of plaques was associated with a significant increase in identification of enlarged or involved LNs in patients w