Multi-objective Optimization of Turning Performance Characteristics using GA Coupled with AHP based Approach

Heat resistive super alloys (HRSAs) which are commonly known as Inconel alloys are extensively used in aeronautical, food processing and automobile industries. The machinability and parametric optimization of Inconel 825 have not been reported much in the literatures. This study attempts to experimentally investigate and optimize the process parameters during machining Inconel 825 for multiple performance characteristics. Spindle speed (N), feed rate (f) and depth of cut (d) are optimized for different responses namely surface roughness (Ra), cutting force (Fz) and metal removal rate (MRR). Feed is found to have the highest influence on Ra and Fz. A mathematical model based on multiple regression analysis is developed for predicting Ra, Fz and MRR. Taguchi analysis is used for optimizing single objective through mean effect plots. For simultaneously optimizing all the responses a weighted combination of objective function is formulated and optimized using genetic algorithm (GA).The optimum parametric combination being 1200 rpm, 0.113 mm/rev and 0.825 mm for N, f and d respectively. In the present work analytical hierarchy processes (AHP) is employed for evaluating weights for each performance measures based on their relative importance. Also, Pareto optimality approach is used for obtaining optimum solutions that produce components with maximum MRR at desired value of Ra is another new contribution of this research. The developed approach can be economically applied for the production of quality components from Inconel 825 by industries

The Cutting Plane Method is Polynomial for Perfect Matchings

The cutting plane approach to optimal matchings has been discussed by several authors over the past decades (e.g., Padberg and Rao '82, Grotschel and Holland '85, Lovasz and Plummer '86, Trick '87, Fischetti and Lodi '07) and its convergence has been an open question. We give a cutting plane algorithm that converges in polynomial-time using only Edmonds' blossom inequalities; it maintains half-integral intermediate LP solutions supported by a disjoint union of odd cycles and edges. Our main insight is a method to retain only a subset of the previously added cutting planes based on their dual values. This allows us to quickly find violated blossom inequalities and argue convergence by tracking the number of odd cycles in the support of intermediate solutions

The cutting plane method is polynomial for perfect matchings

The cutting plane approach to finding minimum-cost perfect matchings has been discussed by several authors over past decades. Its convergence has been an open question. We develop a cutting plane algorithm that converges in polynomial-time using only Edmonds’ blossom inequalities, and which maintains half-integral intermediate LP solutions supported by a disjoint union of odd cycles and edges. Our main insight is a method to retain only a subset of the previously added cutting planes based on their dual values. This allows us to quickly find violated blossom inequalities and argue convergence by tracking the number of odd cycles in the support of intermediate solution

Decoding neural activity in sulcal and white matter areas of the brain to accurately predict individual finger movement and tactile stimuli of the human hand

Millions of people worldwide suffer motor or sensory impairment due to stroke, spinal cord injury, multiple sclerosis, traumatic brain injury, diabetes, and motor neuron diseases such as ALS (amyotrophic lateral sclerosis). A brain-computer interface (BCI), which links the brain directly to a computer, offers a new way to study the brain and potentially restore impairments in patients living with these debilitating conditions. One of the challenges currently facing BCI technology, however, is to minimize surgical risk while maintaining efficacy. Minimally invasive techniques, such as stereoelectroencephalography (SEEG) have become more widely used in clinical applications in epilepsy patients since they can lead to fewer complications. SEEG depth electrodes also give access to sulcal and white matter areas of the brain but have not been widely studied in brain-computer interfaces. Here we show the first demonstration of decoding sulcal and subcortical activity related to both movement and tactile sensation in the human hand. Furthermore, we have compared decoding performance in SEEG-based depth recordings versus those obtained with electrocorticography electrodes (ECoG) placed on gyri. Initial poor decoding performance and the observation that most neural modulation patterns varied in amplitude trial-to-trial and were transient (significantly shorter than the sustained finger movements studied), led to the development of a feature selection method based on a repeatability metric using temporal correlation. An algorithm based on temporal correlation was developed to isolate features that consistently repeated (required for accurate decoding) and possessed information content related to movement or touch-related stimuli. We subsequently used these features, along with deep learning methods, to automatically classify various motor and sensory events for individual fingers with high accuracy. Repeating features were found in sulcal, gyral, and white matter areas and were predominantly phasic or phasic-tonic across a wide frequency range for both HD (high density) ECoG and SEEG recordings. These findings motivated the use of long short-term memory (LSTM) recurrent neural networks (RNNs) which are well-suited to handling transient input features. Combining temporal correlation-based feature selection with LSTM yielded decoding accuracies of up to 92.04 ± 1.51% for hand movements, up to 91.69 ± 0.49% for individual finger movements, and up to 83.49 ± 0.72% for focal tactile stimuli to individual finger pads while using a relatively small number of SEEG electrodes. These findings may lead to a new class of minimally invasive brain-computer interface systems in the future, increasing its applicability to a wide variety of conditions

Appraising the therapeutical potentials of Alchornea laxiflora (Benth.) Pax & K. Hoffm., an underexplored medicinal herb: A systematic review

Ethnopharmacological relevance:Alchornea laxiflora (Benth.) Pax & K. Hoffm. (Euphorbiaceae) is an important traditional medicinal plant grown in tropical Africa. The stem, leaves, and root have been widely used in the folk medicine systems in Nigeria, Cameroon, South Africa, and Ghana to treat various ailments, including inflammatory, infectious, and central nervous system disorders, such as anxiety and epilepsy.Material and methods: The scientific name of the plant was validated using the “The Plant List,” “Kew Royal Botanic Gardens,” and Tropicos Nomenclatural databases. The literature search on A. laxiflora was performed using electronic search engines and databases such as Google scholar, ScienceDirect, PubMed, AJOL, Scopus, and Mendeley.Results: To the best of our knowledge, no specific and detailed review has been reported on A. laxiflora. Consequently, this review provides an up-to-date systematic presentation on ethnobotany, phytoconstituents, pharmacological activities, and toxicity profiles of A. laxiflora. Phytochemical investigations disclosed the presence of important compounds, such as alkaloids, flavonoids, phenolics, terpenoids, and fatty acids. Furthermore, various pharmacological activities and traditional uses reported for this botanical drug were discussed comprehensively.Conclusion: This systemic review presents the current status and perspectives of A. laxiflora as a potential therapeutic modality that would assist future researchers in exploring this African botanical drug as a source of novel drug candidates for varied diseases

Therapeutic implications of current Janus kinase inhibitors as anti-COVID agents: A review

Severe cases of COVID-19 are characterized by hyperinflammation induced by cytokine storm, ARDS leading to multiorgan failure and death. JAK-STAT signaling has been implicated in immunopathogenesis of COVID-19 infection under different stages such as viral entry, escaping innate immunity, replication, and subsequent inflammatory processes. Prompted by this fact and prior utilization as an immunomodulatory agent for several autoimmune, allergic, and inflammatory conditions, Jakinibs have been recognized as validated small molecules targeting the rapid release of proinflammatory cytokines, primarily IL-6, and GM-CSF. Various clinical trials are under investigation to evaluate Jakinibs as potential candidates for treating COVID-19. Till date, there is only one small molecule Jakinib known as baricitinib has received FDA-approval as a standalone immunomodulatory agent in treating critical COVID-19 patients. Though various meta-analyses have confirmed and validated the safety and efficacy of Jakinibs, further studies are required to understand the elaborated pathogenesis of COVID-19, duration of Jakinib treatment, and assess the combination therapeutic strategies. In this review, we highlighted JAK-STAT signalling in the pathogenesis of COVID-19 and clinically approved Jakinibs. Moreover, this review described substantially the promising use of Jakinibs and discussed their limitations in the context of COVID-19 therapy. Hence, this review article provides a concise, yet significant insight into the therapeutic implications of Jakinibs as potential anti-COVID agents which opens up a new horizon in the treatment of COVID-19, effectively

Case study: persistent recovery of hand movement and tactile sensation in peripheral nerve injury using targeted transcutaneous spinal cord stimulation

Peripheral nerve injury can lead to chronic pain, paralysis, and loss of sensation, severely affecting quality of life. Spinal cord stimulation has been used in the clinic to provide pain relief arising from peripheral nerve injuries, however, its ability to restore function after peripheral nerve injury have not been explored. Neuromodulation of the spinal cord through transcutaneous spinal cord stimulation (tSCS), when paired with activity-based training, has shown promising results towards restoring volitional limb control in people with spinal cord injury. We show, for the first time, the effectiveness of targeted tSCS in restoring strength (407% increase from 1.79 ± 1.24 N to up to 7.3 ± 0.93 N) and significantly increasing hand dexterity in an individual with paralysis due to a peripheral nerve injury (PNI). Furthermore, this is the first study to document a persisting 3-point improvement during clinical assessment of tactile sensation in peripheral injury after receiving 6 weeks of tSCS. Lastly, the motor and sensory gains persisted for several months after stimulation was received, suggesting tSCS may lead to long-lasting benefits, even in PNI. Non-invasive spinal cord stimulation shows tremendous promise as a safe and effective therapeutic approach with broad applications in functional recovery after debilitating injuries