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Bush frogs from Garo and Khasi Hills were collected, and a thorough examination based on morphology and geographic distribution revealed that two of the populations sampled from Garo Hills during this study agree with the holotypes and descriptions of the taxa Ixalus garo and I. kempiae, described more than a century ago. The original description lacked information on several morphological characters, genetic material, and photographs of the species in life. The absence of such information posed challenges in field identification of these species. Our phylogeny shows them to be nested within the Raorchestes clade, and therefore, we allocate these two species to this genus and formally announce their rediscovery. We also redescribe these two species here based on additional adult vouchers and report geographic range extensions from new localities. Based on molecular and morphological analysis, we reassess the status of the recently described Raorchestes cangyuanensis, resulting in its placement under the subjective junior synonymy of R. kempiae. We also describe a morphologically distinct new species from this region. This paper bridges an important gap in the knowledge of the genus Raorchestes in this part of India and highlights the importance of systematic surveys in documenting and understanding amphibian diversity in the region.

Abstract Background A tongue abscess is a rare but serious condition marked by a localized accumulation of pus within the tongue’s tissues. Despite the tongue’s frequent exposure to trauma, bites, and foreign objects, it typically resists infections. However, an acute lingual abscess can be life-threatening due to the risk of airway obstruction from tongue swelling. Common symptoms include increasing pain, fever, swelling, immobility, edema, and redness of the tongue. The case report aimed to highlight the unusual clinical presentation and location of a deep-seated abscess in the anterior third of the tongue, as well as the radiographic approach to diagnosing the lesion. Case presentation A 30-year-old female patient presented with sudden onset tongue pain and swelling persisting for 4–5 days. Clinical examination revealed a solitary diffuse swelling in the anterior two-thirds of the tongue, approximately 3 × 2 cm in size. Diagnostic imaging, including a plain radiograph, ultrasound (USG), and MRI, was conducted. The patient was hospitalized for incision and drainage of the abscess, followed by a 5-day course of intravenous antibiotics. Conclusions A tongue abscess, though rare, is a serious condition indicated by tongue swelling, pain, fever, dysphagia, and dyspnea. Diagnosis involves physical examinations and imaging studies like ultrasound or MRI. Immediate treatment includes maintaining airway patency, draining the abscess, and administering broad-spectrum antibiotics. Prompt recognition and treatment are essential to prevent severe complications such as airway obstruction and sepsis. Regular follow-up ensures complete resolution and prevents recurrence.

Abstract This paper, offers a new method for simulating variable-order fractional differential operators with numerous types of fractional derivatives, such as the Caputo derivative, the Caputo–Fabrizio derivative, the Atangana–Baleanu fractal and fractional derivative, and the Atangana–Baleanu Caputo derivative via power-law kernels. Modeling chaotical systems and nonlinear fractional differential equations can be accomplished with the utilization of variable-order differential operators. The computational structures are based on the fractional calculus and Newton’s polynomial interpolation. These methods are applied to different variable-order fractional derivatives for Wang–Sun, Rucklidge, and Rikitake systems. We illustrate this novel approach’s significance and effectiveness through numerical examples.

Air compressors are critical components in many industries whose catastrophic failure results in huge financial losses and downtime leading to accidents. Hence, real time fault diagnosis of air compressor is essential to predict the health condition of air compressor and plan scheduled maintenance thereby reducing financial losses and accidents. Fault diagnosis using transfer learning aids in real time fault detection. In the present study, five air compressor conditions were considered namely, check valve fault, inlet and outlet reed valve fluttering fault, inlet reed valve fluttering fault, outlet reed valve fluttering fault, and good condition. The raw vibration data was converted to radar plot images that were pre-processed and classified using four pre-trained networks (ResNet-50, GoogLeNet, AlexNet, and VGG-16). The hyperparameters like epochs, batch size, optimizer, train-test split ratio, and learning rate were varied to find out the best network for air compressor fault diagnosis. ResNet-50 among all other pre-trained networks produced the maximum classification accuracy (average of five trials) of 98.72%.

The Gaoligong Mountains are characterized by large variations in elevation and topography, which support high levels of biodiversity and endemism that remain largely understudied. Herein, based on the integration of morphological comparisons and phylogenetic reconstruction, we describe a new species of Rhacophorus from the northern Gaoligong Mountains, Yunnan Province, China. The new species, Rhacophorus dulongensis sp. nov., is morphologically distinguishable from its congeners based on the differences in body size, head length, tibia length, snout and tongue shape, toe webbing formula and coloration, ventral skin texture and coloration, dorsal pattern and coloration, body macroglands, iris coloration, and pattern of markings on flanks. Phylogenetically, it differs from its congeners by uncorrected p-distances of >4.8% for the 16S rRNA gene fragment. Rhacophorus dulongensis sp. nov. is likely to be found in Myanmar, considering its type locality lies close to the China-Myanmar border. The phylogenetic analysis revealed that the “widespread” species, R. rhodopus, is a species complex and a composite of five distinct lineages. The results revealed that R. napoensis is also found in Vietnam, making it a new country record for Vietnam. Interestingly, R. dulongensis sp. nov. likely breeds in bamboo, a hidden behavioral characteristic that makes them easy to overlook. Given the ongoing habitat loss and degradation in the region, further biological exploration is urgently needed in the Gaoligong Mountains as a biodiversity reservoir.

Industrially important metal working fluids are reported to be vulnerable to microbial growth, leading to loss of its working efficiency. The present study is dedicated towards the green synthesis of Zinc Oxide (ZnO) nanoparticles using Eclipta prostrata leaf extract and investigated for antimicrobial activity. Characterization studies using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared spectroscopy (FT-IR) displayed the presence of agglomerated rod shaped ZnO nanoparticles with characteristic peak between 700 and 500 cm−1, respectively. Antimicrobial testing against gram-positive and gram-negative bacteria, as well as fungi, showed the ZnO nanoparticles' effectiveness. Against gram-positive bacteria, inhibition ranged from 0.48 to 1.51 at concentrations of 25 μl to 100 μl. Against gram-negative bacteria, inhibition ranged from 0.82 to 2.02, and against fungi, inhibition ranged from 1.20 to 2.34, all at the highest concentration tested. The results of the study indicate that the ZnO nanoparticles were effective against both fungi and bacteria, more effectively against gram negative bacteria. The results suggest that the green synthesized ZnO nanoparticles from Eclipta prostrata can be exploited to reduce the load of microbial contamination in metal working fluids.

The 4′-(4-chlorobenzoyl)-3,-(2,6-dichlorophenyl)-1′-methylspiro(indole-3,2′-pyrrolidin)-2(1H)-one (SOD1) compound has been synthesized and the single crystals are grown by the slow evaporation method using ethanol. Initially, FT-IR and NMR (1H and 13C NMR) spectroscopic studies were used to confirm the structure of the compound. Single crystal X-ray diffraction data were used to determine the solid state structure of the grown single crystals. The title compound SOD1 crystallizes in the orthorhombic space group Pbca. The crystal packing analysis of the compound shows that distinct hydrogen bonding intermolecular interactions construct the R22(12), R22(8), and R12(8), supramolecular synthons to stabilize the packing modes. The propensity of intermolecular interactions is quantified by the Hirshfeld surface analysis, 2-D fingerprint plots and enrichment ratio analysis. Further, the 3-D packing topology of the molecular fragments is visualized through energy frameworks, which reveal the predominance of dispersion energy over other interaction energies. The optimized structure's geometric parameters were computed using DFT calculations using B3LYP/6–311+G(d,p) basis set and compared with the crystal structure parameters obtained by the X-ray diffraction studies. To explore the anticancer activity of the spiro compound, molecular docking with the 6FS1 protein was performed and the binding score of -7.7 kcal/mol was observed. Further, the binding interaction was explored by the dynamics simulation studies.

Rhacophorus tuberculatus and Rhacophorus verrucopus are two morphologically similar species described in 1871 and 1983 respectively. Their taxonomic distinctiveness has been questioned in the past. In the current study, we encountered frogs that we confer to R. tuberculatus based on morphological similarity to a syntype of this species. We redescribe the species based on a re-examination of a syntype, which is designated as a lectotype here, and additional specimens from Garo hills of Meghalaya. We also present molecular data, natural history notes, and report a range extension of this species. Molecular phylogenetic analysis based on the 16S rRNA fragment revealed minimal genetic divergences (0.20–1.74% uncorrected p-distance) between specimens identified as either R. tuberculatus or R. verrucopus from different locations. On the basis of molecular data and morphological characteristics, we conclude that R. verrucopus is a junior synonym of R. tuberculatus.

BACKGROUND AND OBJECTIVES: Determining food composition and bioactivity is critical to both theoretical and applied research in food science and technology. This is frequently used to determine the nutritional value and overall acceptance of the food by consumers. The current study's goal is to determine the macronutrient, mineral and antioxidant activity of selected wheat and soybean varieties with the potential to be useful in the food industry to develop value-added products that are safe for consumption.METHODS: The proximate and mineral composition, gluten characterization, total phenolic contents, and antioxidant activity of three wheat cultivars and five soybean cultivars that are indigenous to India were studied.FINDINGS: Wheat varieties were found to be rich in carbohydrates (65.8-68.8 percent) and gluten (27.2-28.6 percent), whereas soybean varieties were found to be the richest source of protein (32.8-33.7 percent), fat (17.1-17.6 percent), fiber (21.7-28.8 percent), polyphenols (2.76-3.59 milligram gallic acid equivalent per gram, and antioxidant activity (97-123 microgram ascorbic acid equivalent per gram). These samples were also found to have significant content of essential minerals.CONCLUSION: The tested samples had a high nutritional value and energy content and could be a good source of nutrition for a large population. A comprehensive report on the proximate and mineral composition, total phenolic content and antioxidant activity of the wheat and soybean varieties collected from the Rewa district, India, was reported.

In the present investigation, process parameters were optimized in order to enhance the reduction of calcium oxide (CaO) from sugarcane molasses using acid centrifugation treatment. To predict the effects of process factors on CaO reduction efficiency, a response surface approach with a central composite design was selected. The polynomial quadratic equation was used to predict CaO removal efficiency, and the analysis of variance (ANOVA) test was utilized to assess the relevance of process factors. The appropriateness of the developed model was determined by regression analysis, which yielded a higher R-squared value of 0.99334 ± 0.01. At the optimum process parameters of 100°C temperature, 50°Bx, and 3.50 pH, the CaO clarification efficacy of 66.17 wt.% was achieved. The experimental results indicated that for acidic centrifugation treatment, the experimentally observed CaO reduction of 65.94 wt% is in close agreement with the model equation’s predicted maximum CaO reduction of 66.17 wt% with a t-test value of 0.497726. Under such conditions, 0.982 wt.% CaO sugarcane molasses was obtained, which is low when compared to the world average of 1.5% CaO content of sugarcane molasses. Furthermore, the implementation of an artificial neural network (ANN) provided a better prediction model for CaO reduction, with a substantial R-squared value of 0.99866. However, the genetic algorithm (GA) optimization resulted in an actual CaO reduction of 66.21 wt.% with a t-test value of 0.497726.

BACKGROUND AND OBJECTIVE: Iron, an essential micronutrient, significantly contributes to growth, immune health, and cognitive development in human health. Inadequate dietary iron intake leads to iron deficiency anemia, affecting nearly 1.6 billion people, especially pregnant women and preschool children. Biofortification and fortification of iron in wheat is an acceptable and cost-effective strategy to alleviate iron deficiencies. This study aims to address iron deficiencies through the strategy of fortification and biofortification of wheat varieties. The study places specific emphasis on the proximate composition and iron/mineral content of different wheat varieties. To achieve these objectives, different spectrometric methods were employed to analyze the wheat samples.METHODS: Proximate and mineral quantification were carried out following standard Association of Official Analytical Chemists methods using ultraviolet-visible spectrophotometry, atomic absorption spectrometry, inductive coupled plasma-mass spectroscopy, and prediction was carried out using near-infrared spectra combined with chemometrics.FINDINGS: The samples had moisture content (1.1 - 4.5 percent), protein (18.0 - 22.6 percent), fat (0.3 - 0.6 percent), gluten (6.3 - 10.3 percent), fiber (0.3 - 1.4 percent), alcoholic acidity (0.04 - 0.08 percent), ash (0.9 - 1.7 percent), and carbohydrate (71.1 - 75.2 percent). Iron was determined and compared by spectrophotometric methods. Iron concentration ranged from (0.7 to 6.3 milligrams/100 grams) in ultraviolet-visible analysis, (0.7 to 6.74 milligrams/100 grams) in atomic absorption spectrometry, and (0.81 to 6.8 milligrams/100 grams) in inductive coupled plasma-mass spectroscopy. The obtained results were compared with the standard "Food Composition and Food Safety Standard Authority of India" and predicted using near-infrared spectra combined with chemometrics.CONCLUSION: The work aims to investigate the nutritional content of various wheat varieties, particularly focusing on iron content, which could potentially have implications for improving dietary strategies and addressing nutritional deficiencies. The biofortified varieties (HI-8663 and HI-1605) were found to have high iron content when compared to normal wheat. The acquired results bridge the intricate relationship between plant-based diets, micronutrient deficiencies, providing valuable insights into combating iron deficiencies in public health with the potential achievement of improved nutritional understanding, optimized wheat selection, advanced analytical techniques, education, awareness, and iron deficiency mitigation.

Abstract The propensity of manufacturers to produce goods at affordable cost, with more accuracy, and at a faster rate force them to search for novel solutions, such as deploying robots in place of people in a sector that can accommodate their needs. Welding is one of the most crucial processes in the automotive industry. This process is time-consuming, subject to error, and demands skilled professionals. The robotic application can improve this area of production and quality. Other industries, such as painting and material handling, can also profit from the use of robots. This work describes the fuzzy DC linear servo controller, which functions as a robotic arm actuator. Robots have been widely employed in most productive sectors in recent years, including assembly plates, welding, tasks at higher temperatures, etc. Controlling a robot accurately is a difficult undertaking as a robot is very nonlinear with many joints that are often organized and unstructured. To carry out the effective task, an effective PID control based on fuzzy logic has been employed together with the method of Particle Swarm Optimization (PSO) approach for the estimate of the parameter. This offline technique determines the lowest number of optimal robotic arm control parameters. To verify the controller design with computer simulation, a comparative assessment of controllers is given by means of a fuzzy surveillance controller with PSO which improves the parameter gain to provide a rapid climb, a smaller overflow, no steady condition error signal, and effective torque control of the robot arm.

Background: The inflammatory and immune factors play a key role in the pathogenesis of vitiligo, and there are very few studies that have investigated the levels of major cytokines produced by T helper (Th) 1, Th2, and Th17 cells. This can enable better understanding of the, pathogenesis, and severity of vitiligo. Objectives: To evaluate the serum levels of interleukin (IL)-6, tumor necrosis factor (TNF)-α, IL-1β, interferon (IFN)-γ, and IL-10 in patients with vitiligo and to correlate them with the disease severity and activity and to compare them with normal healthy controls. Materials and Methods: A case–control study was conducted with 100 study participants: 50 cases clinically diagnosed as vitiligo and 50 controls. All patients underwent complete evaluation with detailed demographic parameters, history, and physical examination. The severity of the disease was assessed clinically by Vitiligo Area Scoring Index (VASI) and Vitiligo Disease Activity Score (VIDA). Blood investigations performed were IL-6, TNF-α, IL-1β, IFN-γ, and IL-10. Results: We observed significantly higher levels of serum IFN-γ levels in the patient group when compared with those of the normal controls (P = 0.002) and showed a positive correlation with the activity and severity of the disease with a significant VASI (P = 0.05) and VIDA score (P = < 0.001). The mean serum IL-10 (p < 0.001) in patients with vitiligo was significantly lower than that in the control group. There was no significant difference in the serum level of TNF-α level (P = 0.347), IL-6 (P = 0.365), and IL-1β (P = 0.362) between vitiligo and healthy controls. Conclusion: This study proved that high serum level of IFN-γ may be a risk factor for vitiligo progression and significantly low levels of IL-10, which has an anti-inflammatory role, suggesting that they could be used as a marker for assessing vitiligo activity and may open the way for further therapeutic approaches for vitiligo.

Amikacin is an aminoglycoside antibiotic with a broad-spectrum bacterial coverage that is frequently utilized both as monotherapy and in combination with other antibiotics for severe bacterial infections in the paediatric population. The narrow therapeutic index of the drug and high inter-individual variabilities in drug exposure results in either drug toxicity or subtherapeutic concentrations. Thus, therapeutic drug monitoring and population pharmacokinetics are pivotal to facilitate the optimal dosage regimens in paediatrics and negate the adverse outcomes. The therapeutic goal is to maintain the target peak and trough concentrations within 30-40mg/l and

In this article, we investigate the controllability of damped dynamical system modelled by Hilfer derivative of fractional order [Formula: see text] and [Formula: see text]. The Mittag-Leffler matrix function of two parameters has been used to represent the solution of Hilfer fractional problem of damped dynamical system. With the use of the Schawder fixed point theorem and the contraction mapping theorem, the existence and uniqueness of the linear and non-linear system of Hilfer dynamical control system are determined. More specifically, fractional calculus are used to provide sufficient criteria for the controllability results. Finally, examples are given to show how the key results might be justified.

The present study proposes an ensemble-based deep neural network (DNN) model for autonomous detection of visual faults such as glass breakage, burn marks, snail trail, and discoloration, delamination on various photovoltaic modules (PVM). The proposed technique utilizes an image dataset captured by RGB (Red, Green, Blue) camera mounted on an unmanned aerial vehicle (UAV). In the first step, the images are preprocessed by deriving spatial and frequency domain features, such as discrete wavelet transform (DWT), texture, grey level co-occurrence matrix (GLCM), fast Fourier transform (FFT), and grey level difference method (GLDM). The processed images are inserted as input in the proposed ensemble-based deep neural network (DNN) model in order to detect any visual faults on the photovoltaic modules (PVM). The performance of the proposed model is evaluated through classification accuracy, receiver operating characteristic (ROC) curve, and confusion matrix. The results demonstrate that the proposed ensemble-based deep neural network (DNN) model, along with the random forest classifier, achieved a classification accuracy of 99.68% for detecting visual faults on the PV modules. To verify the performance and robustness of the proposed model, we compare our model’s results to those of various classification approaches described in the literature. The suggested approach is compatible with the commercial unmanned aerial vehicle (UAV) embedded flight management system for fault detection.

IntroductionEmpowering women in a tribal context through entrepreneurship is an approach for enabling and making them economically and socially viable. This paper aims to highlight entrepreneurship in a specific tribal context and provide insight on some instances or cases relating to women's empowerment. Although there are many initiatives from international organizations and governmental institutions to support women entrepreneurs, especially tribal women, they suffer from isolation as a result of their language and lifestyle differ from the rest of society, which made the growth of their business and ability to compete arduous, and thus affected their ability to make various decisions in their lives. This study examines the pathway to a better understanding of increasing access to entrepreneurship for tribal women in Mayurbhanj district, Odisha.MethodsThe sample size was 111 Santhal tribal women entrepreneurs, and all of them were interviewed using an interview schedule and Focus Group Discussions (FGDs). Two analytical tools were used (a linear regression model to find which dependent variables influence entrepreneurs and the Women's Empowerment Index (WEI) to measure the progress in social and economic opportunities). The respondents was interviewed and asked on the various WEI indicators before and after an entrepreneurship intervention.Results and discussionIt was observed through the results that the empowerment of women has changed in a positive direction after establishing their work; according to the indicators of the study, the Women's Empowerment Index has changed from 0.61 to 1.26. It was also found that entrepreneurship has a positive and significant impact on women's decision-making within the family, and therefore, it was suggested through research to increase the intervention from the government and related organizations with more initiatives that contribute to the possibility of increasing women's education and their financial ability to open new enterprises.

Concrete structures exposed to high temperatures often experience thermal damage, which can significantly reduce their structural integrity. Fiber-Reinforced Polymer (FRP) wrapping is a common retrofitting technique used to restore the strength and durability of thermally affected concrete. This study investigates the effectiveness of Basalt Fiber-reinforced Polymer wrapping on different concrete specimens with varying orientations of wrapping. This study mainly focuses on various parameters as fiber orientation and wrapping methodology. A series of 15 columns of dimension 150mm x 150mm with a length of 700mm are cast and subjected to axial compression loading in a pre-heated condition until the initial cracking occurs. These cracked columns are made to strengthen using Basalt Fiber with different patterns of orientation of laminates. The retrofitted columns are subjected to axial compression loading to determine their maximum load-bearing capacities. The test results of this experiment is assessed and compared with conventional RC columns of same grade. The strength of retrofitted columns versus conventional ones are compared and analyzed. The maximum load bearing capacity for a particular pattern of wrapping is determined.

In the present investigation, process parameters were optimized in order to enhance the reduction of calcium oxide (CaO) from sugarcane molasses using acid centrifugation treatment. To predict the effects of process factors on CaO reduction efficiency, a response surface approach with a central composite design was selected. The polynomial quadratic equation was used to predict CaO removal efficiency, and the analysis of variance (ANOVA) test was utilized to assess the relevance of process factors. The appropriateness of the developed model was determined by regression analysis, which yielded a higher R‐squared value of 0.99334 ± 0.01. At the optimum process parameters of 100°C temperature, 50°Bx, and 3.50 pH, the CaO clarification efficacy of 66.17 wt.% was achieved. The experimental results indicated that for acidic centrifugation treatment, the experimentally observed CaO reduction of 65.94 wt% is in close agreement with the model equation's predicted maximum CaO reduction of 66.17 wt% with a t‐test value of 0.497726. Under such conditions, 0.982 wt.% CaO sugarcane molasses was obtained, which is low when compared to the world average of 1.5% CaO content of sugarcane molasses. Furthermore, the implementation of an artificial neural network (ANN) provided a better prediction model for CaO reduction, with a substantial R‐squared value of 0.99866. However, the genetic algorithm (GA) optimization resulted in an actual CaO reduction of 66.21 wt.% with a t‐test value of 0.497726. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has evolved into a powerful tool that has wide-spread application in computer vision such as computer-aided inspection, industrial control systems, and navigation of robots. Monitoring the condition of machineries and mechanical components for the presence of faults with the aid of image-based automated analysis is one major application of computer vision. Diagnosing machinery faults from images can be made feasible with the adoption of deep learning and machine learning techniques. The primary objective of this study is to detect malfunctions in photovoltaic (PV) modules by utilizing a combination of deep learning and machine learning methodologies, with the assistance of RGB images captured via unmanned aerial vehicles. Six test conditions of PV modules such as good panel, snail trail, delamination, glass breakage, discoloration, and burn marks were considered in the study. The overall experimentation was carried out in two phases: (i) deep learning phase and (ii) machine learning phase. In the initial deep learning phase, the final fully connected layer of six pretrained networks, namely, DenseNet-201, VGG19, ResNet-50, GoogLeNet, VGG16, and AlexNet, was utilized to extract PVM image features. During the machine learning phase, feature selection from the extracted features was carried out using the J48 decision tree algorithm. Post selection of features, three families of classifiers such as tree, Bayes, and lazy were applied to determine the best feature extractor-classifier pair. The combination of DenseNet-201 features with k-nearest neighbour (IBK) classifier produced the overall classification accuracy of 100.00% among all other pretrained network features and classifiers considered.

Abstract Background Simultaneous saccharification and fermentation (SSF) of pre-treated lignocellulosics to biofuels and other platform chemicals has long been a promising alternative to separate hydrolysis and fermentation processes. However, the disparity between the optimum conditions (temperature, pH) for fermentation and enzyme hydrolysis leads to execution of the SSF process at sub-optimal conditions, which can affect the rate of hydrolysis and cellulose conversion. The fermentation conditions could be synchronized with hydrolysis optima by carrying out the SSF at a higher temperature, but this would require a thermo-tolerant organism. Economically viable production of platform chemicals from lignocellulosic biomass (LCB) has long been stymied because of the significantly higher cost of hydrolytic enzymes. The major objective of this work is to develop an SSF strategy for D-lactic acid (D-LA) production by a thermo-tolerant organism, in which the enzyme loading could significantly be reduced without compromising on the overall conversion. Results A thermo-tolerant strain of Lactobacillus bulgaricus was developed by adaptive laboratory evolution (ALE) which enabled the SSF to be performed at 45 °C with reduced enzyme usage. Despite the reduction of enzyme loading from 15 Filter Paper Unit/gLCB (FPU/gLCB) to 5 FPU/gLCB, we could still achieve ~ 8% higher cellulose to D-LA conversion in batch SSF, in comparison to the conversion by separate enzymatic hydrolysis and fermentation processes at 45 °C and pH 5.5. Extending the batch SSF to SSF with pulse-feeding of 5% pre-treated biomass and 5 FPU/gLCB, at 12-h intervals (36th–96th h), resulted in a titer of 108 g/L D-LA and 60% conversion of cellulose to D-LA. This is one among the highest reported D-LA titers achieved from LCB. Conclusions We have demonstrated that the SSF strategy, in conjunction with evolutionary engineering, could drastically reduce enzyme requirement and be the way forward for economical production of platform chemicals from lignocellulosics. We have shown that fed-batch SSF processes, designed with multiple pulse-feedings of the pre-treated biomass and enzyme, can be an effective way of enhancing the product concentrations.

A late side effect of radiation for head and neck cancer that has a significant effect on quality of life is esophageal stricture. Many newer techniques of radiation have evolved, but esophageal stricture still remains a complication, especially in a concurrent chemoradiation setting. The treatment options in such conditions can be either invasive or noninvasive. We present a reconstructive option in the form of islanded facial artery myomucosal (iFAMM) flap which carries less donor site morbidity and also provides a mucosal lining. A patient with carcinoma hypopharynx reported with dysphagia following concurrent chemoradiation. The patient was evaluated clinically (video-laryngoscopy, esophago-gastro-duodenoscopy, and video-fluoroscopy) and radiologically and diagnosed as stricture cervical esophagus. The patient had undergone repeated noninvasive techniques of dilatation and failed. Stricture release and patch pharyngoplasty were done with iFAMM flap. Till the last follow-up of 1 year, the patient showed satisfactory deglutition with normal voice. iFAMM is a viable and esthetically appealing option for reconstruction of partial postradiation hypopharynx and cervical esophagus stricture of up to 6 cm in length that are not amenable to dilatation procedures.

In the paper by Naveen et al. [IUCrData (2017), 2, x170234], there was an error in the name of one of the authors.