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Poor thermal stability of packaging materials represents a significant obstacle impeding their applications as alternatives to non-biodegradable plastics in the food packaging sector. The thermal stability of biopolymeric films is essential for upholding their structural integrity and preventing degradation at different temperatures during processing, transportation, and storage, thereby safeguarding the quality and safety of packaged food items. A deeper understanding of the interplay between material composition, processing conditions, and thermal behavior will foster the development of stable edible films capable of withstanding elevated temperatures while maintaining their structural integrity and functional attributes. This review provides an overview of various thermal analysis techniques available for analyzing biodegradable edible films (viz. Differential Scanning Calorimetry, Thermogravimetric Analysis, Dynamic Mechanical Analysis, and Thermomechanical Analysis), as well as explores the interrelation between film properties and thermal stability such as film crystallinity, morphological attributes, chemical arrangement, nano-reinforcements and interaction with other ingredients. Furthermore, the thermal behaviour of biopolymers and the recent advancements aimed at engineering desirable thermal behaviour into edible films are extensively discussed. The present study contributes to the current knowledge base and serves as a valuable resource for researchers in the field of food packaging and material science. [ABSTRACT FROM AUTHOR]

This study effectively synthesized monoclinic bismuth oxide nano-photocatalyst (α-Bi2O3) using both template-assisted and template-free methods, employing the hydrothermal process. Xanthan gum, a type of soft biopolymeric material, was used as a sacrificial template to promote the regulated growth of nano-photocatalysts. The structure, morphology, surface features, optical properties, and catalytic activity of both templated and non-templated Bi2O3 were analyzed using XRD, FESEM-EDX, IR, and UV–Vis (DRS) spectral analysis techniques. Additionally, the chemical oxygen (COD) analyzer methodology was used to assess the catalytic activity. The combination of synthetic technique and template has successfully produced Bi2O3 nano-photocatalyst with a consistent and granular shape. Specifically, the template-assisted processes have produced nanostructures of bismuth oxide that are highly crystalline and low band gap (2.76–2.71 eV). The use of template-assisted metal oxide nanostructures has shown potential as very effective photocatalysts for breaking down developing pollutants, such as 2,4-dichlorophenol (2,4-DCP), which is found in paper and pulp mills, when exposed to sunlight. The xanthan gum templated α-Bi2O3 nano-photocatalyst almost completely photodegraded 2,4-DCP within 90 min under sunlight. The remarkable catalytic capability of bismuth oxide (Bi2O3) templated by xanthan gum has been confirmed by their high-rate constants of 0.01–0.05 min−1. As the treatment duration increased to 90 min, the degradation of 2,4-DCP resulted in a maximum elimination rate of 97.5% for COD. As a result, the template-assisted approaches have successfully produced nanostructures with customized features, which makes them very efficient in photocatalysis for quickly breaking down certain emergent organic pollutants present in paper and pulp mill wastewater. These eco-friendly synthetic photocatalysts can be efficiently used for treating wastewater that is contaminated with emerging organic contaminants. [ABSTRACT FROM AUTHOR]

The prediction of rock fragmentation (Fr) is highly beneficial to the optimization of blasting operations in the mining industry. The characteristics of the rock mass, the blast geometry, and the explosive qualities are the primary elements influencing Fr. The methodical explosion of explosives within a rock mass results in the production of smaller rock pieces. This work is a step toward the prediction of the degree of Fr in opencast mining using advanced soft computing (SC) methods like: back propagation neural network (BPNN), k-nearest neighbor (KNN), multilayer perceptron (MLP), radial basis function (RBF), multi-variable regression (MVR), gene expression programming (GEP), Takagi-Sugeno fuzzy model (TSF), least-square-support vector machine (LS-SVM), and support vector machine (SVM). A dataset consisting of 219 blasting events with 10 influencing parameters: hole diameter (HDM), spacing (S), burden (B), maximum charge per delay (MCPD), stemming (ST), compressive strength (CS), powder factor (PF), specific drilling (SPD), number of holes (NH), and bench height (BH), were used in the present study. All models were assessed with the help of following performance parameters: RRSE, RSE, NRMSE, RRMSE, MAD, MAPE, MSE, RMSE, and R2. Based on loss function for Fr, scattered diagram, importance ranking, sensitivity analysis, rank analysis, and violin plot the top models were chosen. From the obtained results, it is seen that SVM produce better result compare to other models when predicting the Fr of rock. Under sensitivity analysis, spider diagrams and Tomado diagrams were plotted to determine the variation of input and output factors. The sensitivity analysis of the developed model shows that HDM has the least impact, whereas the parameters B and PF have the maximum impact on the Fr of rock. [ABSTRACT FROM AUTHOR]

Purpose: Pharmaceutical research continues to focus on developing novel approaches for the effective treatment of ulcerative colitis (UC). To develop a better system than simple nanoparticle-in-microparticle (NP-in-MP), time-dependent NP or MP, and pH-dependent NP or MP, this work sought to construct an enhanced colon-targeting system with a combination of hybrid formulations and dual coating approach consisting of time-dependent nanoparticles loaded in pH-dependent microparticles. Method: The model drug used was mesalamine, and the polymers used were ethyl cellulose (EC) as time dependent polymer and a mixture of Eudragit L100 (EL100) and Eudragit S100 (ES100) as pH dependent polymer. The NP-in-MP were optimized, prepared and characterized to obtain targeted and sustained delivery of drug. The NP were coated with ethyl cellulose to obtain sustained delivery. Then NP were entrapped within eudragit MP using the double emulsion solvent evaporation process. NP-in-MP were evaluated for particle size, entrapment efficiency, surface morphology, in-vitro drug release and in-vivo evaluation. Results: The particle size and entrapment efficiency of the selected formulation was 12.4 ± 3.1 µm and 85.36 ± 2.6%. The in vitro drug release profile verified that the selected formulation released (6.94 ± 1.23%) less than 10% of the drug in an acidic environment, followed by continuous drug release (93.9 ± 3.15%) in a colonic environment. The MPO level confirmed that the maximum recovery (i.e., decrease in MPO level) was observed for NP-in-MP (3.02 ± 0.33, ***P < 0.001) followed by NP (6.2 ± 0.51) compared with disease control. NP-in-MP substantially improved body weight, diarrhea score and rectal bleeding (***P < 0.001) which indicates mucosal healing and the mitigation of inflammation. The NP-in-MP significantly increased colon length (***P < 0.001) and reduced spleen weight (**P < 0.01) in comparison to disease control. NP-in-MP also showed improved histological results compared to those of the other treatment groups. Conclusion: The current findings demonstrate the efficient development of NP-in-MP for enhancing the delivery of NP to the colonic region. The in-vitro data confirms that the NP-in-MP prevented burst release of NP and also targeted them to the colon along with sustained delivery of their payload. The in-vivo data confirms that the NP-in-MP are better in treating colitis than NP. Therefore, it was concluded that a hybrid NP-in-MP can be a potential alternative than other treatment carriers to treat inflammatory bowel disease and colorectal cancer. [ABSTRACT FROM AUTHOR]

We develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction. [ABSTRACT FROM AUTHOR]

As energy demands continue to rise and concerns about the impact on the environment of fossil fuels, renewable energy sources have emerged as viable alternatives. Bio-fuels can replace non-renewable energy sources. Micro and macro-algae, animal fat, leftover cooking oil and vegetable oil can be utilised to make bio-diesel. Micro-algae is readily available and affordable, making it a viable alternative to these sources. A bio-diesel supply chain that supports large-scale production must be developed quickly. A multi-objective framework is used to construct a sustainable micro-algal bio-diesel supply chain. Bio-diesel supply chain economic objective and environmental impact is minimized in the proposed approach. Bio-diesel is advertised as a fossil fuel replacement. Bio-refineries, bio-diesel depositories, multi-harvesting centres and supply sites for micro-algae (Chlorella, chlamydomonas and Scenedesmus) are considered. The suggested multi-objective model is optimized by implementing the G e n e t i c - A l g o r i t h m . The framework and solution technique are validated using numerical illustrations. Findings indicate that bio-diesel production facility starting expenses comprise 59% of overall costs, showing high installation costs in the supply chain. Additionally, their environmental impact accounts for 67% of total environmental installation impact. A sensitivity analysis is performed to determine the feasibility of this study. The suggested paradigm could potentially be beneficial for traders and governing bodies with an interest in bio-fuel industry. Article structure: Paper's remaining sections are organised as: Sect. 1 gives the introduction of the study. A discussion on the existing literature regarding bio-fuel's supply chain is presented in section 2. Sect. 3 presents the assumptions of the investigation along with the mathematical models. In Sect. 4, optimization technique G e n e t i c - A l g o r i t h m approach is described. Sect. 5 provides numerical validation of the approach and analysis of the numerical experiment. A discussion and detailed analysis of the results is discussed in section 6. Sect. 7 describe the implications and applicability of the adopted approach. The work has been concluded in Sect. 8 which also provides some suggestions for future investigation. [ABSTRACT FROM AUTHOR]

Background: Minimally invasive surgical necrosectomy plays an important role in the management of infected pancreatic necrosis, with a goal of removing debris and debriding necrotic tissue. Pulse lavage is designed to simultaneously hydrostatically debride and remove the infected necrotic tissue with suction. It is also able to remove significant amounts of debris without traumatic manipulation of the necrotic tissue which may be adherent to surrounding tissue and can result in injury. Methods and results: The surgical technique of utilising a waterjet pulse lavage device during the minimally invasive necrosectomy is detailed. Sixteen patients being managed via a step-up approach underwent endoscopic necrosectomy via a radiologically placed drain tract. All sixteen patients were successfully managed endoscopically without conversion to open necrosectomy, and survived their admission. There were no complications associated with the use of the waterjet pulse lavage. Conclusion: Waterjet pulse lavage is a useful adjunct in minimally invasive necrosectomy, which reduces the length of the necrosectomy procedure, and facilitates removal of necrotic tissue while minimising the risk of traumatising healthy tissue. [ABSTRACT FROM AUTHOR]

Mood disorders, including depression, remain a significant global health concern, necessitating continuous efforts to develop novel and more effective antidepressant therapies. Although there have been significant advancements in comprehending the biology of Major Depressive Disorder (MDD), a considerable number of people suffering from depression do not exhibit positive responses to the pharmacologic treatments now available. This study specifically examines emerging targets and potential future approaches for pharmaceutical interventions in the treatment of MDD. The discussion revolves around novel therapeutic agents and their effectiveness in treating depression. The focus is on the specific pathophysiological pathways targeted by these agents and the amount of evidence supporting their use. While conventional antidepressants are anticipated to continue being the primary treatment for MDD in the foreseeable future, there is currently extensive research being conducted on numerous new compounds to determine their effectiveness in treating MDD. Many of these compounds have shown encouraging results. This review highlighted the recent advances in the synthesis of antidepressant derivatives and explores their pharmacologic insights for the treatment of mood disorders. [ABSTRACT FROM AUTHOR]

Image caption generation is among the most rapidly growing research areas that combine image processing methodologies with natural language processing (NLP) technique(s). The effectiveness of the combination of image processing and NLP techniques can revolutionaries the areas of content creation, media analysis, and accessibility. The study proposed a novel model to generate automatic image captions by consuming visual and linguistic features. Visual image features are extracted by applying Convolutional Neural Network and linguistic features by Long Short-Term Memory (LSTM) to generate text. Microsoft Common Objects in Context dataset with over 330,000 images having corresponding captions is used to train the proposed model. A comprehensive evaluation of various models, including VGGNet + LSTM, ResNet + LSTM, GoogleNet + LSTM, VGGNet + RNN, AlexNet + RNN, and AlexNet + LSTM, was conducted based on different batch sizes and learning rates. The assessment was performed using metrics such as BLEU-2 Score, METEOR Score, ROUGE-L Score, and CIDEr. The proposed method demonstrated competitive performance, suggesting its potential for further exploration and refinement. These findings underscore the importance of careful parameter tuning and model selection in image captioning tasks. [ABSTRACT FROM AUTHOR]

Background: The clinico-oncological outcomes of precursor epithelial subtypes of adenocarcinoma arising from intraductal papillary mucinous neoplasms (A-IPMN) are limited to small cohort studies. Differences in recurrence patterns and response to adjuvant chemotherapy between A-IPMN subtypes are unknown. Methods: Clincopathological features, recurrence patterns and long-term outcomes of patients undergoing pancreatic resection (2010–2020) for A-IPMN were reported from 18 academic pancreatic centres worldwide. Precursor epithelial subtype groups were compared using uni- and multivariate analysis. Results: In total, 297 patients were included (median age, 70 years; male, 78.9%), including 54 (18.2%) gastric, 111 (37.3%) pancreatobiliary, 80 (26.9%) intestinal and 52 (17.5%) mixed subtypes. Gastric, pancreaticobiliary and mixed subtypes had comparable clinicopathological features, yet the outcomes were significantly less favourable than the intestinal subtype. The median time to recurrence in gastric, pancreatobiliary, intestinal and mixed subtypes were 32, 30, 61 and 33 months. Gastric and pancreatobiliary subtypes had worse overall recurrence (p = 0.048 and p = 0.049, respectively) compared with the intestinal subtype but gastric and pancreatobiliary subtypes had comparable outcomes. Adjuvant chemotherapy was associated with improved survival in the pancreatobiliary subtype (p = 0.049) but not gastric (p = 0.992), intestinal (p = 0.852) or mixed subtypes (p = 0.723). In multivariate survival analysis, adjuvant chemotherapy was associated with a lower likelihood of death in pancreatobiliary subtype, albeit with borderline significance [hazard ratio (HR) 0.56; 95% confidence interval (CI) 0.31–1.01; p = 0.058]. Conclusions: Gastric, pancreatobiliary and mixed subtypes have comparable recurrence and survival outcomes, which are inferior to the more indolent intestinal subtype. Pancreatobiliary subtype may respond to adjuvant chemotherapy and further research is warranted to determine the most appropriate adjuvant chemotherapy regimens for each subtype. [ABSTRACT FROM AUTHOR]

In the present research, an attempt is made to use four machine learning technique techniques such as artificial neural network combined with particle swarm optimization (ANN-PSO), adaptive neuro-fuzzy inference system (ANFIS), multivariate adaptive regression splines (MARS), and M5Tree machine learning (ML) approaches to model the scour depth. A total of 534 live bed scouring (LBS) experimental and field datasets are collected for bridge pier scouring from the previously published literature, and a gamma test has been performed to identify the best input parameter combination. A total of 36 combinations were tested in the gamma test, five distinct input combinations such as pier width to flow depth (b/y), approach flow velocity to sediment incipient velocity (V/Vc), critical Froude number (Frc), pier width to median sediment size (b/d50), geometric standard deviation of bed material (σg) were selected based on the lowest gamma value and Vratio. The developed models have been validated using field datasets of Pearl River, Mississippi, USA, by Mueller and Wagner (2005) and Ganga River, Patna, India, by Kumar and Singh (2022) and compared with six other existing scour depth predictive models. Results indicate that the proposed M5Tree scour depth prediction model (R2 = 0.9196, RMSE = 0.0837) provided better accuracy for all combinations of input variables (b/y, V/Vc, Frc, b/ d50, σg) compared to other ML models. The developed M5Tree model was successfully applied to the field condition for Ganga River, Patna, India and Pearl River, Mississippi, USA, and the mean absolute percentage error (MAPE) value is found to be less than 12% and the coefficient of determination (R2) more than 0.98. [ABSTRACT FROM AUTHOR]

The way the topological structure transforms from a decoupled to a coupled state in multiplex networks has been extensively studied through both analytical and numerical approaches, often utilizing models of artificial networks. These studies typically assume uniform interconnections between layers to simplify the analytical treatment of structural properties in multiplex networks. However, this assumption is not applicable for real networks, where the heterogeneity of link weights is an intrinsic characteristic. Therefore, in this paper, link weights are calculated considering the node's reputation and the impact of the inter-layer link weights are assessed on the overall network's structural characteristics. These characteristics include synchronization time, stability of synchronization, and the second-smallest eigenvalue of the Laplacian matrix (algebraic connectivity). Our findings reveal that the perturbation in link weights (intra-layer) causes a transition in the algebraic connectivity whereas variation in inter-layer link weights has a significant impact on the synchronization stability and synchronization time in the multiplex networks. This analysis is different from the predictions made under the assumption of equal inter-layer link weights. [ABSTRACT FROM AUTHOR]

We explore the cosmic birefringence signal produced by an ultralight axion field with a small CP-violating coupling to bulk SM matter in addition to the usual CP-preserving photon coupling. The change in the vacuum expectation value of the field between recombination and today results in a frequency-independent rotation of the plane of CMB linear polarization across the entire sky. While many previous approaches rely on the axion rolling from a large initial expectation value, the couplings considered in this work robustly generate the birefringence signal regardless of initial conditions, by sourcing the field from the cosmological nucleon density. We place bounds on such monopole-dipole interactions using measurements of the birefringence angle from Planck and WMAP data, which improve upon existing constraints by up to three orders of magnitude. We also discuss UV completions of this model, and possible strategies to avoid fine-tuning the axion mass. [ABSTRACT FROM AUTHOR]

Introduction: The number of reverse shoulder arthroplasties (RSA) performed each year is growing rapidly, especially in elderly patients and with expanded indications including geriatric proximal humerus fractures. As the elderly population grows and the number of RSA's annually continues to rise, there will be a proportionate number of adverse events and mortality. However, the rate of early mortality has consistently shown to be less than 1%, so a large-scale analysis of possible risk factors for post-operative mortality is warranted. Methods: A retrospective multivariate analysis of 59,915 patients from the National Inpatient Sample database between 2016 and 2019 was performed. Patients who underwent RSA were identified based on ICD-10 code. Patients were divided into two groups, early mortality and no mortality. Early mortality was defined as those who died within the same admission. Patient demographics and medical comorbidities were evaluated. Hospital admission status was classified as elective or non-elective. Odds ratios for predictive variables were measured as a ratio of incidence between the early mortality and no mortality groups. Results: The overall incidence of inpatient mortality was 0.07%. The incidence of mortality for elective admissions was 0.04% and for non-elective admissions was 0.34%. On univariate analysis, age greater than 75 years (p < 0.001), octogenarians (p < 0.001), nonagenarians (p < 0.001), and non-elective admission (p < 0.001) were associated with early mortality following RSA. Upon multivariate analysis, age greater than 75 years old had 4 times the odds of early mortality following RSA (OR 4.20; 95%CI (1.67, 10.60); p < 0.001) while non-elective admission had about 5 times the odds (OR 5.38; 95%CI (2.75, 10.53); p < 0.001). Discussion: Age greater than 75 years old has 4-fold higher odds and non-elective admission has 5-fold higher odds of early mortality following RSA. Appropriate pre-operative counseling should be performed with elderly patients and those undergoing non-elective indications for RSA. [ABSTRACT FROM AUTHOR]

The structure and absorption properties of a series of azobenzene derivatives are investigated using the density functional theoretical methods. The study showed that π → π* transitions of azobenzene undergo red shift after mono- and di- substitutions at para positions. Considering the fact that o-fluoro and o-methoxy derivatives of azobenzene have long living cis isomers, the effect of ortho substitution on the excitation energies is examined. An investigation on the azo-protonation revealed prominent red shift for n → π* and π → π* transitions bringing both absorptions in visible region. The effect of substitution on the cis to trans thermal relaxation is also analysed. [ABSTRACT FROM AUTHOR]

The exponential growth of internet-enabled devices and their interconnectedness heightens the vulnerability of technology to cyber threats. The simplicity of communication lures attackers to execute numerous attacks, with Distributed Denial of Service (DDoS) emerging as a major threat due to its challenging detectability. Over recent years, numerous machine learning mitigation methodologies have arisen to combat this issue. In this paper, we present an approach for detecting DDoS attacks, with a primary focus on optimal feature selection and data pre-processing to mitigate the risk of overfitting and enhance accuracy. We employ an embedded method utilizing a decision tree in Recursive Feature Elimination with Cross-Validation (RFECV) to select the most effective features. Subsequently, we apply Gradient Naïve Bayes (GNB), Decision Tree (DT), Random Forest (RF), and Binary Classification using deep neural network deep learning models. These models undergo validation using the CICDDoS2019 dataset. Performance evaluation reveals that the deep learning model surpasses others, achieving an accuracy of 99.72%. [ABSTRACT FROM AUTHOR]

Angina Bullosa Hemorrhagica is characterized with rapid appearance of soft, blood-filled blisters on the mucosa of oral cavity and oropharynx. It is a benign condition, and is not associated with any systemic hematological disorder. No etiological factors have been identified and there are no established guidelines for its management. The current case report describes the sudden appearance of large, bluish, soft lesion on the soft palate which was managed with incision and drainage, and healed completely over the next three weeks. [ABSTRACT FROM AUTHOR]

The selection of drought-tolerant genotypes from the existing gene pool is a preliminary step for breeding for drought tolerance. Research efforts aimed at exploring the ability of crops to withstand drought stress have not yet touched the realm of reproductive drought performance of local genotypes. To examine how local crop accessions demonstrate varying reproductive performance under drought conditions, twenty accessions of maize (Zea mays L.) were evaluated for six quantitative traits in a two-factor factorial completely randomized design with two replications between February to June of 2023. All the traits under study showed significant differences among the genotypes (p < 0.05). Owing to their grain yield, ear weight, and hundred grain weight, accessions NGRC05592, NGRC05582, NGRC05564, NGRC05565, NGRC05571, and NGRC05569 performed better under drought condition than other tested accessions. Accession NGRC05592 showed the highest yield under drought condition, whereas, NGRC05573 and NGRC05576 showed poor performance. GGE Biplot analysis for grain yield revealed that NGRC05571 and NGRC05592 had the highest mean yield, with the accession NGRC05592 standing out as the stable variety under changing soil moisture levels and performing best among all the tested accessions under drought condition. The possibility of accession NGRC05592 being used as a potential genetic resource for drought breeding programs has been observed, but further studies aiming at its stability under field conditions in diverse agro-climatic regions across different years are encouraged to assure its prospect for developing cultivars suited to drought-affected regions. [ABSTRACT FROM AUTHOR]

The level of phosphorus must be carefully monitored for proper and effective utilization of coal and coal ash. The phosphorus content needs to be assessed to optimize combustion efficiency and maintenance costs of power plants, ensure quality, and minimize the environmental impact of coal and coal ash. The detection of low levels of phosphorus in coal and coal ash is a significant challenge due to its complex chemical composition and low concentration levels. Effective monitoring requires accurate and sensitive equipment for the detection of phosphorus in coal and coal ash. X-ray fluorescence (XRF) is a commonly used analytical technique for the determination of phosphorus content in coal and coal ash samples but proves challenging due to their comparatively weak fluorescence intensity. Fourier Transform Infrared spectroscopy (FTIR) emerges as a promising alternative that is simple, rapid, and cost-effective. However, research in this area has been limited. Until now, only a limited number of research studies have outlined the estimation of major elements in coal, predominantly relying on FTIR spectroscopy. In this article, we explore the potential of FTIR spectroscopy combined with machine learning models (piecewise linear regression—PLR, partial least square regression—PLSR, random forest—RF, and support vector regression—SVR) for quantifying the phosphorus content in coal and coal ash. For model development, the methodology employs the mid-infrared absorption peak intensity levels of phosphorus-specific functional groups and anionic groups of phosphate minerals at various working concentration ranges of coal and coal ash. This paper proposes a multi-model estimation (using PLR, PLSR, and RF) approach based on FTIR spectral data to detect and rapidly estimate low levels of phosphorus in coal and its ash (R 2 of 0.836, RMSE of 0.735 ppm, RMSE (%) of 34.801, MBE of − 0.077 ppm, MBE (%) of 5.499, and MAE of 0.528 ppm in coal samples and R 2 of 0.803, RMSE of 0.676 ppm, RMSE (%) of 38.050, MBE of − 0.118 ppm, MBE (%) of 4.501, and MAE of 0.474 ppm in coal ash samples). Our findings suggest that FTIR combined with the multi-model approach combining PLR, PLSR, and RF regression models is a reliable tool for rapid and near-real-time measurement of phosphorus in coal and coal ash and can be suitably modified to model phosphorus content in other natural samples such as soil, shale, etc. [ABSTRACT FROM AUTHOR]

A compact metamaterial-inspired two-port antenna based on negative permeability for isolation enhancement is presented. The antenna size is 65 × 60 × 1.5 µm3 where the distance to the edges of the antenna radiator is only 27 μm (0.173λ), which is less than the conventional distance (λ/2). A modified SRR-based radiator is designed using metamaterial analysis whose negative permeability is responsible for dual operating bands. Metamaterial-inspired meander-line based on negative permeability is used to increase the isolation by 31 dB at 2.1 THz. The maximum value of the isolation of the two-port antenna is 44.3 dB, which shows the low mutual coupling and surface current between the antenna elements. The MTM-inspired MIMO antenna operates at 2.1 THz and 5.3 THz. The required value of ECC and CCL of the two-port antenna is < 0.05 and < 0.4 bits/Sc/Hz, respectively, which shows the diversity performance and antenna can be good choice for THz operating bands. [ABSTRACT FROM AUTHOR]

This paper tackles the critical challenge of detecting and mitigating unintended political bias in offensive meme detection. Political memes are a powerful tool that can be used to influence public opinion and disrupt voters' mindsets. However, current visual-linguistic models for offensive meme detection exhibit unintended bias and struggle to accurately classify non-offensive and offensive memes. This can harm the fairness of the democratic process either by targeting minority groups or promoting harmful political ideologies. With Hindi being the fifth most spoken language globally and having a significant number of native speakers, it is essential to detect and remove Hindi-based offensive memes to foster a fair and equitable democratic process. To address these concerns, we propose three debiasing techniques to mitigate the overrepresentation of majority group perspectives while addressing the suppression of minority opinions in political discourse. To support our approach, we curate a comprehensive dataset called Pol_Off_Meme, designed especially for the Hindi language. Empirical analysis of this dataset demonstrates the efficacy of our proposed debiasing techniques in reducing political bias in internet memes, promoting a fair and equitable democratic environment. Our debiased model, named D R T I M Att Adv , exhibited superior performance compared to the CLIP-based baseline model. It achieved a significant improvement of +9.72% in the F1-score while reducing the False Positive Rate Difference (FPRD) by -16% and the False Negative Rate Difference (FNRD) by -14.01%. Our efforts strive to cultivate a more informed and inclusive political discourse, ensuring that all opinions, irrespective of their majority or minority status, receive adequate attention and representation. [ABSTRACT FROM AUTHOR]

This paper presents the miniaturized and flexible antenna, design on textile material based on the open-ended slot for portable and wearable applications. The jeans substrate is used with an optimized feed position of the miniaturized antenna where the two orthogonal open-ended slots are accomplished on the ground and patch to obtain the dual bandwidth and miniaturization in size. The overall size of the textile antenna is 12 mm × 12 mm with 10 dB bandwidth from 4.9 to 5.05 GHz (Wi-Fi) and 5.7 to 6 GHz (ISM bands) with positive realized gain where the compact size of the antenna covering both important bands for wearable and portable applications. [ABSTRACT FROM AUTHOR]

Next-generation sequencing (NGS) is emerging as a powerful tool for molecular diagnostics but remains limited by cumbersome and inefficient sample preparation. We present an innovative automated NGS library preparation system with a simplified mechanical design that exploits both macro- and microfluidic properties for optimizing heat transfer, reaction kinetics, mass transfer, fluid mechanics, adsorption–desorption rates, and molecular thermodynamics. Our approach introduces a unique two-cannula cylindrical capillary system connected to a programmable syringe pump and a Peltier heating element able to execute all steps with high efficiency. Automatic reagent movement, mixing, and magnetic bead-based washing with capillary-based thermal cycling (capillary-PCR) are completely integrated into a single platform. The manual 3-h library preparation process is reduced to less than 15 min of hands-on time via optimally pre-plated reagent plates, followed by less than 6 h of instrument run time during which no user interaction is required. We applied this method to two library preparation assays with different DNA fragmentation requirements (mechanical vs. enzymatic fragmentation), sufficiently limiting consumable use to one cartridge and one 384 well-plate per run. Our platform successfully prepared eight libraries in parallel, generating sequencing data for both human and Escherichia coli DNA libraries with negligible coverage bias compared to positive controls. All sequencing data from our libraries attained Phred (Q) scores > 30, mapping to reference genomes at 99% confidence. The method achieved final library concentrations and size distributions comparable with the conventional manual approach, demonstrating compatibility with downstream sequencing and subsequent data analysis. Our engineering design offers repeatability and consistency in the quality of sequence-able libraries, asserting the importance of mechanical design considerations that employ and optimize fundamental fluid mechanics and heat transfer properties. Furthermore in this work, we provide unique insights into the mechanisms of sample loss within NGS library preparation assays compared with automated adaptations and pinpoint areas in which the principles of thermodynamics, fluid mechanics, and heat transfer can improve future mechanical design iterations. [ABSTRACT FROM AUTHOR]

The present study investigates unsteady wake dynamics in flow past an oscillating cylinder. A two-dimensional computational analysis is undertaken for flow past a sinusoidally oscillating cylinder. Operating parameters like Reynolds number, forcing frequency, amplitude, and wavelength are systematically varied, and their effect on wake dynamics is investigated. Lift and drag coefficients are plotted with cylinder position to characterize the flow. The flow field is analyzed using Proper Orthogonal Decomposition (POD). POD mode shapes and Power Spectral Density (PSD) plots characterize the flow response to cylinder oscillations. The effect of frequency ratio is examined in achieving synchronized vortex shedding. Previous studies focus on two extremes- the cylinder is either stationary or oscillating with perfect phase-locking. Flow past an oscillating cylinder where Karman and forcing frequencies compete for dominance is rarely reported. This paper considers such a scenario and demonstrates how POD can identify coherent structures, their significance, and associated frequencies. Further, non-symmetric vortex shedding, which is not a common observation, is captured and discussed. Large amplitude and large wavelength regimes are investigated, which remained unexplored in previous research. Coherent structures associated with those regimes are identified. [ABSTRACT FROM AUTHOR]

Objective: Biopharmaceutics Classification System says that simvastatin (SMV) is a Class II drug with low bioavailability (5%). This is because it dissolves slowly and is broken down a lot in the first pass. Simvastatin transdermal patches were produced as part of this study's aim to treat hyperlipidemia. The Box–Behnken design (three-factor, three-level) was selected for optimization of patches. Methodology: The optimization design involved 15 runs with independent factors hydroxypropyl methylcellulose K100, Eudragit L100, and polyethylene glycol 400 percentage, and dependent factors including folding endurance and in-vitro drug release. Results: The results showed that the concentration of hydroxypropyl methylcellulose K-100 positively impacted the patch's folding endurance. The fact that factor C was the only scenario where the p-value was less than 0.05 and the coefficient value was higher in the in vitro drug release model means that it has a greater influence on the release of medicines. The patches were also evaluated for drug content, swelling, moisture uptake, moisture content, etc. The optimized patch shows an in vitro drug release of 55.3% in up to 24 h. In vivo antihyperlipidemic activity was evaluated in albino Wistar rats. In the standard treatment (simvastatin oral) groups, there is a decrease in cholesterol (132.76 ± 0.35) and triglyceride level (139.80 ± 76) whereas in the test formulation group or test group, there is also a decrease in cholesterol (169.65 ± 0.21 mg/dL) and triglyceride level (151.20 ± 31 mg/dL) level. Conclusion: Based on in-vitro and in-vivo results it can be concluded that simvastatin patches can be an alternative to traditional therapy. [ABSTRACT FROM AUTHOR]

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers. Extracting scientific data from published research is a complex task required specialised tools. Here the authors present a scheme based on large language models to automatise the retrieval of information from text in a flexible and accessible manner. [ABSTRACT FROM AUTHOR]

In the present work, the Auto-Regressive Integrated Moving-Average (ARIMA) forecasting method is used to predict the remaining useful life (RUL) of an axial piston pump used in the hydraulic system applied to the sheet metal industry. The leakage volume from the piston pump is considered a significant parameter for the life prediction analysis using the ARIMA model, as the proposed model uses auto-regressive (AR) and moving-average (MA) modelling for forecasting with high prediction accuracy. The life estimation through the ARIMA model is based on the degradation method of remaining useful life prediction. The life prediction results were in an acceptable range with a forecasting root-mean-square error (RMSE) of 0.3. The investigation results concluded that out of the two forecasting models, i.e., ARIMA (1,1,2) and ARIMA (20,1,2), ARIMA (1,1,2) model has the least forecasting error and also shows better adjustment with the historical data. The RUL of the hydraulic pump considered in the present investigation is predicted to be 28 months. Additionally, the model developed can be used to determine the lifetime of the operational pump and plan its maintenance schedule for hydraulic-operated unmanned vehicles used for off-road applications like mining, agriculture, defence, etc. The proposed RUL forecasting technique can help avoid mechanical systems from uncertain breakdowns and will also play a pivotal role in maintenance. [ABSTRACT FROM AUTHOR]

Background: Post-operative hyperamylasemia (POH) following pancreatoduodenectomy (PD) may play a key role in pathogenesis of post-operative pancreatic fistula (POPF). Aim of the current study was to evaluate efficacy of perioperative administration of indomethacin in preventing POH. Methods: Single-center, double-blind, randomized controlled trial (RCT) conducted on consecutive patients undergoing PD. Patients received either 100 mg of indomethacin per-rectally at induction of anesthesia or standard care. Primary endpoint was incidence of POH in the two arms. POH was defined as postoperative day (POD) 1 serum amylase (S. amylase) levels greater than the upper limit of normal. Results: After exclusion 44 patients were randomized. The two arms were comparable for preoperative and intraoperative parameters. POH was noted in 20/44 (45.5%) with significantly lower incidence of POH (60.9% vs. 28.6%, p = 0.032) in intervention arm (IA). Median S. amylase, POD 1, 3, and 5 drain amylase, and incidence of clinically relevant POPF (CR-POPF) were lower in IA but failed to reach statistical significance (30.4% vs. 14.3%, p = 0.18). The severity of delayed gastric emptying (DGE) was significantly lower in the IA (grade B/C DGE 23.8% vs. 47.8%, p = 0.023). Evaluation of risk factors for POH showed IA to confer an independent protective effect and increased risk with soft pancreas. Conclusion: Perioperative per-rectal indomethacin administration is effective in decreasing the incidence of POH following pancreatoduodenectomy. [ABSTRACT FROM AUTHOR]

To close the gap between the rates of computational screening and experimental realization of novel materials1,2, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.An autonomous laboratory, the A-Lab, is presented that combines computations, literature data, machine learning and active learning, which discovered and synthesized 41 novel compounds from a set of 58 targets after 17 days of operation. [ABSTRACT FROM AUTHOR]

This research investigates the cavitation wear phenomena in a direct-acting pressure relief valve (PRV), where the poppet of the PRV is subjected to unseat at over-pressure conditions of the hydraulic system. The poppet unseat results in to sudden fall in system pressure and hence, the expansion and burst of pre-existing tiny air bubbles and thus the cavitation. To reduce the occurrence of cavitation, three different poppet shapes i.e. chamfered conical, blunt, and spherical heads is proposed for replacement over the existing conical head. To investigate the effect of different poppet shapes, the CFD simulation of the simplified 2-D fluid flow geometry is considered and the same is validated through experiments. Further, the validated model is used to investigate the cavitation parameters during the PRV operation at different opening conditions. The results showed that the blunt head PRV poppet offers comparatively lesser cavitation intensity for hydraulic systems subjected to frequent over-pressure conditions. [ABSTRACT FROM AUTHOR]

This study aims to address the scant research on emerging economies, especially the rural population, which are expected to drive the significant growth of mobile payment services. We developed a research model using dual-factor theory as an overarching umbrella by considering the users' perception of both enablers and inhibitors of mobile payments. The enablers and inhibitors of mobile payments were drawn from the extant literature, driving users' satisfaction and leading to continued usage. To test the proposed research model, we collected responses from 412 respondents from rural settings in India. The study finds that the enablers positively affect satisfaction, and the impact of inhibitors was negative. The findings validate the importance and existence of inhibitors along with enablers of mobile payments. The findings would benefit the government, policymakers, marketers, and other stakeholders interested in digitization of the rural economy, empowerment of rural people, and rural market penetration. [ABSTRACT FROM AUTHOR]

One of the critical issues faced by the desalination plants is an accurate analysis of their real-time performance. Soft computing techniques are efficient in overcoming these issues and predicting accurate outcomes. In this paper, models based on the third version of the modified particle swarm optimization algorithm called autonomous groups particles swarm optimization—based artificial neural network (AGPSO3-ANN) have been proposed for accurate prediction of permeate flux of reverse osmosis (RO) desalination plant. It employs remarkable optimization strategy that demonstrates superiority than the conventional PSO-ANN techniques, to update acceleration factors (c1 and c2) and to screen the global best solution. Here, four input parameters: evaporator inlet temperature, feedwater salt concentration, condenser inlet temperature, and feed flow rate have been considered for the modeling, and models' performance evaluated in terms of the regression coefficient (R2) and mean square errors (MSE). The results show an impressive agreement between simulated and experimental datasets indicating that the proposed approach is strongly capable of finding optimal solutions to predict accurate results with minimum errors (R2 = 99.2%, MSE = 0.005) compared to the existing ANN approaches. This demonstrates that the proposed models based on such soft computing tools like AGPSO3-ANN are perfect for analyzing and predicting real-time desalination plant performance that would present an effective way for improved process control and efficiency for plant engineers. [ABSTRACT FROM AUTHOR]

Objective: This study aimed at studying the challenges and outcomes of live-donor liver transplantation (LDLT) for pediatric acute liver failure (PALF). Study design: A total of 315 patients with PALF were treated over a period of 11 years. 42 underwent LT (41 LDLT and one DDLT), constituting 38% (41/110) of all pediatric transplants during this duration. The outcomes of LDLT for PALF were analyzed. Results: All the 41 children who underwent LT met the Kings College criteria (KCC). The etiology was indeterminate in 46.3% (n = 19) children. 75.6% (n = 31) were on mechanical ventilation for grade 3/4 hepatic encephalopathy. There was presence of cerebral edema on a computed tomography scan of the brain in 50% of the children. One-third of our children required hemodynamic support with vasopressors. Systemic inflammatory response syndrome and sepsis were observed in 46.3% and 41.4% of patients, respectively. Post-LDLT 1- and 5-yr patient and graft survival were 75.6% and 70.9%, respectively. The survival in children satisfying KCC but did not undergo LT was 24% (38/161). Vascular and biliary complication rates were 2.4% and 4.8%, respectively. No graft loss occurred because of acute rejection. In multivariate analysis, pre-LT culture positivity and cerebral edema, persistence of brain edema after transplantation, and resultant pulmonary complications were significantly associated with post-LT death. Thirteen (32%) children who underwent plasmapheresis prior to LT had better post-LT neurological recovery, as evidenced by early extubation. Conclusion: LDLT for PALF is lifesaving and provides a unique opportunity to time transplantation. Good long-term survival can be achieved, despite the majority of patients presenting late for transplantation. Early referral and better selection can save more lives through timely transplantation. [ABSTRACT FROM AUTHOR]

In this paper, graphene based SRR loaded on a two-port antenna with high isolation and polarization diversity is used for THz applications. The size of the two-port antenna is compact and two microstrip-fed radiators are placed orthogonally to achieve the polarization diversity. The defective ground and stub are implemented to achieve impedance matching and isolation enhancement. The SRR is loaded on the ground which is based on the quadrupole mode of the electric field and perturbs the surface waves which creates null and weak electric field between antenna elements. The SRR improves the isolation up to 17.23 dB where the distance of edges of the antenna is only 0.15 λ. The SiO2 substrate-based two-port antenna works from 4.9 to 6.3 THz with maximum isolation of 42.3 dB which can be tunable with different chemical potentials applied to SRR. [ABSTRACT FROM AUTHOR]

A novel polarization insensitive, UWB, band stop FSS is discussed with a monopole antenna for gain enhancement application. A compact and simple monopole antenna (16 mm × 28 mm × 1.6 mm dimension) with Wi-Fi /WLAN (4.95–5.35 GHz) notch is designed with loaded CSRR on the radiator. The |S11| of the planar monopole antenna is 3.55 to 10.4 GHz when the FSS loaded on the antenna gain of 10.78 dB. The presented FSS unit cell size is compact and only 0.08 λ × 0.08 λ and covers the UWB achieved on FR-4 substrate. The compact FSS structure is stable for TE/TM polarization at a different angle and provides a high gain and stable radiation pattern. The experimental result shows that a high antenna can be achieved simply and efficiently by placing the FSS layer at an optimized distance below the antenna. The FSS is loaded on a compact monopole antenna to increase and control the gain up to 6 dB. [ABSTRACT FROM AUTHOR]

Despite modern advances in cancer medicine, pancreatic cancer survival remains unchanged at just 12%. For the small proportion of patients diagnosed with 'early' (upfront or borderline resectable) disease, recurrences are common, and many recur soon after surgery. Whilst chemotherapy has been shown to increase survival in this cohort, the morbidity of surgery renders many candidates unsuitable for adjuvant treatment. Due to this, and the success of upfront chemotherapy in the advanced setting, use of neoadjuvant chemotherapy has been introduced in patients with upfront or borderline resectable disease. Randomized controlled trials have been conducted to compare upfront surgery to neoadjuvant chemotherapy in this patient cohort, opinions on the ideal upfront treatment approach are divided. This lack of consensus has highlighted the need for biomarkers to assist in clinical decision making. This review analyses the potential diagnostic, prognostic and predictive biomarkers that may assist in the diagnosis and management of early (upfront and borderline resectable) pancreatic cancer. [ABSTRACT FROM AUTHOR]

Recent advances in peptide delivery and nanotechnology has resulted in emergence of several non-parenteral administration routes that replace subcutaneous injections associated with patient discomfort. Thiolated biopolymers are relatively new materials being explored to enhance mucoadhesivity and permeability in these efforts, yet their pH dependent reactivity remains an obstacle. This work focussed on improving the mucoadhesivity of thiolated chitosans by activating them with mercaptonicotinic acid, in a bid to create a novel thiomerized chitosan that can open cell tight junctions for application in oral delivery. The synthesized mercaptonicotinic acid activated thiolated chistoan (MNA-TG-chitosan), along with thiolated chitosan (TG-chitosan) and unmodified chitosan were then used to create insulin nanoparticles (insNPs) using spray drying encapsulation process. Use of MNA-TG-chitosan in place of chitosan resulted in reduction of particle size of insNPs from 318 to 277 nm with no significant changes in polydispersity index (~ 0.2), encapsulation efficiency (~ 99%), insulin loading content (~ 25%) and morphology. Results from in-vitro cytotoxicity on TR146, CaCo2 and HepG2 cell lines revealed no significant effects on cell viability at 50–1000 μg/mL concentration. insNPs encapsulated with the new material, MNA-TG-chitosan, resulted in a 1.5-fold and 4.4-fold higher cellular uptake by HepG2 liver cells where insulin is metabolized, approximately 40% and 600% greater insulin transport through TR146 buccal cell monolayers, and 40% and 150% greater apparent permeability than insNPs encapsulated with unmodified chitosan and TG-chitosan respectively. The higher permeation achieved on using MNA-TG chitosan was attributed to the greater opening of the cell tight junction evidenced by reduction of transepithelial electrical resistance of TR146 buccal cell monolayers. This study demonstrates MNA-TG-chitosan as a promising material for improved peptide oral delivery. [ABSTRACT FROM AUTHOR]

We investigate the average behavior of the nth normalized Fourier coefficients of the jth (j ≽ 2 be any fixed integer) symmetric power L-function (i.e., L(s,symjf)), attached to a primitive holomorphic cusp form f of weight k for the full modular group S L (2 , ℤ) over certain sequences of positive integers. Precisely, we prove an asymptotic formula with an error term for the sum S j ∗ : = ∑ a 1 2 + a 2 2 + a 3 2 + a 4 2 + a 5 2 + a 6 2 ⩽ x (a 1 , a 2 , a 3 , a 4 , a 5 , a 6) ∈ ℤ 6 λ sym j f 2 (a 1 2 + a 2 2 + a 3 2 + a 4 2 + a 5 2 + a 6 2) , where x is sufficiently large, and L (s , sym j f) : = ∑ n = 1 ∞ λ sym j f (n) n s . When j = 2, the error term which we obtain improves the earlier known result. [ABSTRACT FROM AUTHOR]

Player selection is an important aspect of team-based sports such as cricket. Various situations, like players getting injured, rested, or falling under disciplinary action, etc., are common in cricket, and in those circumstances, the proper substitution of players is very important. We present an innovative knowledge-based intelligent framework for substitute suggestions by employing various clustering techniques like DBSCAN, Spectral clustering. We compared it with the substitution made in the real-time team selection process and obtained a large similarity between that and the recommendations generated using Spectral clustering. We have also compared our proposed results with existing state-of-the-art works in our experimental setup, where they have used the K-means clustering technique. The results highlighted that Spectral clustering is the best choice for substitute recommendations among the mentioned clustering techniques. We also present an intelligent framework for team selection and apply various similarity measures like Euclidean distance, Cosine Similarity, Manhattan distance, and Pearson Correlation Coefficient to find the most accurate combination of players. The recommendations obtained from the Pearson Correlation Coefficient have a maximum accuracy of 77.50% with a high F-measure (0.77) and present different directions for the team line-up formation. [ABSTRACT FROM AUTHOR]

The clustering methodologies for deployed devices in the region of interest consider the similarity of sensed data or target maximization of network lifetime. Thus the clusters formed are either sensing clusters or communication clusters. In the case of motes capable of sensing multi-feature data, the similarity of sensed parameters is generally used to cluster the devices. Event detection methodologies in uni-modal sensor based IoT mainly focus on communication clusters to maximize network lifetime. Yet, the existing approaches for clustered data gathering hardly incorporate user context and preferences for sensing cluster formation and event detection. Additionally, many approaches do not incorporate both sensing and communication clusters in order to detect the event and balance it with energy efficiency. Research work that considers user context in the domain of the internet of things is also limited with a focus on network lifetime, event detection accuracy etc. The present work aims at resolving the existing constraints in 'user context' aware clustering methods and event detection. The user context parameters based on the domain knowledge of the user are used to divide the deployed region into sub-regions forming sensing clusters. The methodology allows the user to change the context and definition of events for each sub-region for accurate, context-aware, and discriminatory event detection. Additionally, the compressive gathering of detected events results in energy efficient data transmission. Simulations were performed for scalability and comparative analysis of the proposed scheme. The results show that the proposed scheme outperforms the existing schemes in terms of detection accuracy and network lifetime. [ABSTRACT FROM AUTHOR]

Main conclusion: This review provides a detailed structural and functional understanding of BBR/BPC TF, their conservation across the plant lineage, and their comparative study with animal GAFs. Plant-specific Barley B Recombinant/Basic PentaCysteine (BBR/BPC) transcription factor (TF) family binds to “GA” repeats similar to animal GAGA Factors (GAFs). These GAGA binding proteins are among the few TFs that regulate the genes at multiple steps by modulating the chromatin structure. The hallmark of the BBR/BPC TF family is the presence of a conserved C-terminal region with five cysteine residues. In this review, we present: first, the structural distinct yet functional similar relation of plant BBR/BPC TF with animal GAFs, second, the conservation of BBR/BPC across the plant lineage, third, their role in planta, fourth, their potential interacting partners and structural insights. We conclude that BBR/BPC TFs have multifaceted roles in plants. Besides the earliest identified function in homeotic gene regulation and developmental processes, presently BBR/BPC TFs were identified in hormone signaling, stress, circadian oscillation, and sex determination processes. Understanding how plants’ development and stress processes are coordinated is central to divulging the growth-immunity trade-off regulation. The BBR/BPC TFs may hold keys to divulge the interactions between development and immunity. Moreover, the conservation of BBR/BPC across plant lineage makes it an evolutionary vital gene family. Consequently, BBR/BPCs are prospective to attract the increasing attention of the scientific communities as they are probably at the crossroads of diverse fundamental processes. [ABSTRACT FROM AUTHOR]

Background: Spinal atypical teratoid rhabdoid tumor (AT/RT) is an extremely rare tumor and represents less than 2% of all AT/RTs. Methods: Available medical literature on spinal AT/RT in English was retrieved from PubMed and comprehensively reviewed. Clinical presentation, diagnosis, management, prognosis, and outcome in patients with spinal AT/RT have been elucidated by citing a case of extradural AT/RT of the cervicodorsal spine. Results: The age at presentation is usually less than 3 years. The most common site is the cervicodorsal spine. The most frequent tumor location is intradural extramedullary. A contrast-enhanced magnetic resonance imaging (MRI) of the entire neuraxis is the imaging modality of choice. The incidence of leptomeningeal dissemination is high (15–30%). Histopathological examination shows an admixture of primitive neuroectodermal, mesenchymal, and epithelial elements along with rhabdoid cells. Loss of SMARCB1/INI1 is considered pathognomonic of AT/RT. Maximal safe resection of tumor is the initial management of choice. Thereafter focal radiotherapy for localized tumor or craniospinal irradiation for leptomeningeal dissemination should be considered. Post-operative intensive polychemotherapy including intrathecal and high-dose chemotherapy (with autologous stem cell rescue) is usually considered to optimize survival. Typically, the time to recurrence and overall survival are less than 6 and 12 months, respectively. However, with judicious multimodality management long-term survivors are increasingly being recognized. The illustrative patient was a 18-month-old girl diagnosed with extradural AT/RT of the cervicodorsal spine (C3-D1), who was managed with maximal safe resection of tumor, multiagent chemotherapy (ICE-ifosfamide, carboplatin, etoposide) and focal RT to the tumor bed—50.4 Gy/28 fractions/5.5 weeks. At the last follow-up visit, 30 months after surgery, she had complete clinicoradiological response. Conclusion: Multimodal treatment comprising maximal safe resection of tumor, multiagent chemotherapy (ICE), and focal RT can lead to successful outcome in patients with localized spinal AT/RT, under the age of 3 years. [ABSTRACT FROM AUTHOR]