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Abstract Neurodegenerative diseases represent one of the utmost imperative well-being health issues and apprehensions due to their escalating incidence of mortality. Natural derivatives are more efficacious in various preclinical models of neurodegenerative illnesses. These natural compounds include phytoconstituents in herbs, vegetables, fruits, nuts, and marine and freshwater flora, with remarkable efficacy in mitigating neurodegeneration and enhancing cognitive abilities in preclinical models. According to the latest research, the therapeutic activity of natural substances can be increased by adding phytoconstituents in nanocarriers such as nanoparticles, nanogels, and nanostructured lipid carriers. They can enhance the stability and specificity of the bioactive compounds to a more considerable extent. Nanotechnology can also provide targeting, enhancing their specificity to the respective site of action. In light of these findings, this article discusses the biological and therapeutic potential of natural products and their bioactive derivatives to exert neuroprotective effects and some clinical studies assessing their translational potential to treat neurodegenerative disorders. Graphical Abstract Common mechanisms, therapeutic targets, and molecular pathogenesis of neurodegeneration. It is focused on the biological and therapeutic potential of natural products and their bioactive derivatives to exert a neuroprotective effect on the pathologies of neurodegenerative diseases.

Abstract The growing global demand for STEM professionals is not being met by the supply of new graduates, a supply that is characterised by a significant lag in the percentage of women pursuing STEM studies. Interestingly enough, the percentage of female applicants entering STEM majors has been increasing yet only a minority of them pursue, or complete, engineering programs. Several studies for the developed world have identified several environmental factors responsible for this phenomenon. The scarcity of engineering professionals is a handicapping factor for development, even for the most advanced countries of the Global South. The objective of this exploratory study is to examine whether the environmental factors identified in the international literature are sufficient to explain the asymmetry in selecting an engineering or a natural sciences career among female undergraduates in an exemplary Global South country, Kazakhstan. To this purpose, a multifaceted survey was conducted among the female students pursuing STEM majors in the premier Kazakhstani university in the academic year 2021–2022. This study utilized a Likert Scale questionnaire, ordinal logistic regression, and factor analysis to explore factors affecting female students. Data reliability was confirmed through Confirmatory Factor Analysis (CFA). The factor and regression analysis of the results obtained demonstrates that there is no discernible difference between the observations in the literature and the situation in Kazakhstan.

This present study aimed to investigate the relationship between childhood maltreatment and its effect on self-esteem among youth. This study was conducted through the survey method, using an online survey via Google Form for the respondents. The total number of respondents received is 156 (n =156) participants from youth aged 18 to 30, with 74 (47.4%) male respondents and 82 (52.6%) female respondents who are willing to participate in the study. Instruments used in this study were the Childhood Trauma Questionnaire (CTQ) and the Rosenberg Self-Esteem Scale (RSES). This research includes the use of descriptive analysis for the demographic information. Meanwhile, the research hypothesis was tested using Pearson’s correlation to obtain the results between the two variables. Results indicated that emotional neglect has the highest number of childhood maltreatment experiences by youth, but emotional abuse has the most severe case. Childhood maltreatment had a strong negative correlation with self-esteem (r(156) = 0.671, p

Nigeria, the largest country on the continent of Africa, has been fighting wars with the proclaimed terrorist group Boko Haram. Currently, Boko Haram has between 1,500 and 2,000 fighters; most documentation about them is either a position paper or a situation review. There is scanty data on the personality and psychological assessment of Boko Haram terrorists using a standardized self-report inventory. Hence, this study aims to describe and explore the profile of the Boko Haram suspects on all the scales of the Minnesota Multiphasic Personality Inventory-2-Restructured Form. Eleven respondents were purposefully recruited because they were the only ones incarcerated at the ‘Kiri-kiri’ Prison facility at the time of this research. Their scores on the inventory were descriptively analyzed. More of these terrorists endorsed significant scores or symptoms of emotional/internalizing dysfunction (EID), somatic complaints (RC1), antisocial behavior (RC4), ideas of persecution (RC6), gastrointestinal complaints (GIC), neurological complaints (NUC), suicidal/death ideation (SUI), anxiety (AXY), shyness (SHY), and disaffiliativeness (DSF), while elevated scores or severe symptoms were reported on stress/worry (STW) and psychoticism (PSYC-r). This research provides personality and psychological assessments of Boko Haram terrorists for the first time using MMPI-2-RF, though it is limited by sample size. Therefore, a larger sample size may be needed for further studies and the ability to make inferences and generalizations.

Recent developments of orthopedic implant applications have discovered a variety of new metallic biomaterials known as β-type titanium alloys. The μ-WEDM (micro-wire electro discharge machining) surface treatment technique, capable of improving the surface properties of orthopedic implants, was studied in a machining Ti-29Nb-13Ta-4.6Zr alloy. This study aimed to evaluate material removal rate (MRR), kerf width, average surface roughness, microhardness and antibacterial response at different machining parameters which are capacitance (1 nF, 10 nF and 100 nF) and gap voltage (80 V, 95 V and 110 V). The Taguchi method was used to optimize the mentioned output parameters, while ANOVA (analysis of variance) described the significance and contribution of capacitance and gap voltage. Grey relation analysis (GRA) was conducted to perform multiple output optimization. For antibacterial response, cultivations of B. subtilis, E. coli, P. aeruginosa and S. aureus bacteria on treated surfaces for 72 h were performed. As the results, optimal values of MRR, kerf width, crater area, average surface roughness and microhardness were equal to 0.0637 mm3/min, 93.0 μm, 21.8 μm2, 0.348 μm and 442 HV, respectively. Meanwhile, μ-WEDM treatment improved antibacterial properties while the highest antibacterial response was achieved at the lowest average surface roughness resulting in least biofilm formation on treated surfaces.

This study investigates the effect of a tantalum addition and lattice structure design on the mechanical and antibacterial properties of Ti-6Al-4V alloys. TPMS lattice structures, such as Diamond, Gyroid, and Primitive, were generated by MSLattice 1.0 software and manufactured using laser powder bed fusion (LPBF). The results indicate that Gyroid and Primitive structures at a 40% density exhibit superior ultimate compressive strength, which closely emulates bone’s biomechanical properties. To be precise, adding 8% tantalum (Ta) significantly increases the material’s elastic modulus and energy absorption, enhancing the material’s suitability for dynamic load-bearing implants. Nevertheless, the Ta treatment reduces bacterial biofilm formation, especially on Gyroid surfaces, suggesting its potential for infection management. Overall, all findings provide critical insights into the development of advanced implant materials, contributing to the fields of additive manufacturing, materials science, and biomedical engineering and paving the way for improved patient outcomes in orthopedic applications.

Bulk metallic glasses (BMGs) are growing in popularity prominently due to their potential in micro-electromechanical systems (MEMSs) and aerospace applications. BMGs have unique mechanical properties, i.e., high strength, hardness, modulus of elasticity, and wear resistance, due to their disordered atomic structure. Due to their unique mechanical properties and amorphous structures, machining of BMGs remains a challenge. This paper aims to carry out a detailed literature review on various aspects of the machining of bulk metallic glasses using both conventional and non-conventional processes, including experimental approaches, modeling, statistical findings, challenges, and guidelines for machining this difficult-to-machine material. Conventional machining processes were found to be challenging for machining bulk metallic glasses due to their high hardness, brittleness, and tendency to convert their amorphous structure into a crystalline structure, especially at the machined surface and sub-surface. Although their high electrical conductivity makes them suitable for machining by non-conventional processes, they impose new challenges such as heat-affected zones and crystallization. Therefore, the successful machining of BMGs requires more in-depth analysis of cutting forces, tool wear, burr formation, surface finish, recast layers or heat-affected zones, crystallization, and mechanical property changes among different varieties of BMGs. This review paper provides guidelines emerging from in-depth analysis of previous studies, as well as offering directions for future research in the machining of BMGs.

Parkinson’s disease is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, including hallucinations. The use of antipsychotic medications is a common strategy to manage hallucinations associated with Parkinson’s disease psychosis (PDP). However, careful consideration is necessary when selecting the most appropriate drug due to the potential risks associated with the available treatment options. Atypical antipsychotics (AAPs), such as Pimavanserin and Clozapine, have effectively controlled PDP symptoms. On the contrary, the support for utilizing quetiapine is not as substantial as other antipsychotics because research studies specifically investigating its application are still emerging and relatively recent. The broad mechanisms of action of AAPs, involving dopamine and serotonin receptors, provide improved outcomes and fewer side effects than typical antipsychotics. Conversely, other antipsychotics, including risperidone, olanzapine, aripiprazole, ziprasidone, and lurasidone, have been found to worsen motor symptoms and are generally not recommended for PDP. While AAPs offer favorable benefits, they are associated with specific adverse effects. Extrapyramidal symptoms, somnolence, hypotension, constipation, and cognitive impairment are commonly observed with AAP use. Clozapine, in particular, carries a risk of agranulocytosis, necessitating close monitoring of blood counts. Pimavanserin, a selective serotonin inverse agonist, avoids receptor-related side effects but has been linked to corrected QT (QTc) interval prolongation, while quetiapine has been reported to be associated with an increased risk of mortality. This review aims to analyze the benefits, risks, and mechanisms of action of antipsychotic medications to assist clinicians in making informed decisions and enhance patient care.

Introduction: The use of assessment tools to measure postnatal mental illness is essential in healthcare settings. However, variations in the types of tools and their reliability in a particular population lead to under-recognition of mental health status in postnatal mothers. The aim of this review is to evaluate the most recent 10 year of research on the validity and reliability of postnatal mental illness assessment tools. Methods: A literature search of studies from online databases PubMed, Scopus, and Science Direct was conducted. Results: A total of 59 studies were selected for this review. Several studies utilised multiple assessment tools, and a total of 96 assessment tools were identified and classified into six domains: postnatal blues, postnatal stress, postnatal anxiety, postnatal depression, postnatal psychosis, and postnatal psychological disorder. In this review, EPDS was the most common tool used to identify postnatal depression and anxiety while DASS 21 was the most common tool used to identify postnatal psychological disorder. There is a wide range in preponderance of evidence for the reliability of each assessment tool and there were inconsistencies in assessing the validity of the assessment tools. Conclusion: This review provides information regarding some of the main assessment tools currently available to measure postnatal mental illnesses. There were no standardised tools that were used in a particular setting. The results may differ in different population because there are differences in not only languages and dialects, but also cultural and racial backgrounds, which greatly influences their perception and interpretation of postnatal mental illness.

The integration of topology optimization into additive manufacturing provides unmatched possibilities for the sustainable manufacturing of lightweight, intricate, custom parts with less material at a lower production time and cost. This study aims to apply and benchmark topology optimization methods, in conjunction with additive manufacturing, to enhance the design of functional components used in aerospace applications, while simultaneously providing an experimental verification and comparative analysis of such optimization techniques. This approach was applied to an industrial bracket used in aerospace applications, which was optimized with the aim of weight reduction without sacrificing its original mechanical stiffness. A density-based technique and a level-set method were used to perform the analysis and optimization, whereas fabrication was performed using fused deposition modeling. Finally, a compression and tensile testing machine was employed for the testing, verification, and comparison of the exhibited mechanical strength for the whole range of printed parts, under the same load conditions. The optimized designs achieved a 20% weight reduction while maintaining the compression displacement of the initial components at the given load. The achieved results demonstrate that topologically optimized components can significantly enhance the design of real-life components, such as those used in the weight-sensitive industrial applications considered in this work.

The use of coat-hanger dies is prevalent in the plastic film and sheet extrusion industry. The product quality and the power of the extrusion machine depend on the uniformities of the fluid velocity at the exit and the pressure drop. Die manufacturers face the challenge of producing coat-hanger dies that can extrude materials uniformly and with a minimal pressure drop. Previous studies have analyzed the die outlet’s flow homogeneity and pressure drop using various numerical simulations. However, the combination of the scheme programming language together with the Adjoint Method of Optimization has yet to be attempted. The adjoint optimization method has been demonstrated to be beneficial in addressing issues related to shape optimization problems and it may also be beneficial in optimizing the design of dies used in polymer melt extrusion. In this study, the proposed innovations involve incorporating both the Scheme programming language and Adjoint solver to examine and optimize the coat hanger’s flow homogeneity and pressure drop. Before optimization, the outlet velocity was almost 10 times higher at the die center than at the edges but after optimization, it became more uniform. The proposed optimized coat-hanger die geometry results in more uniform melt flow as demonstrated by the velocity contour plot and the outlet velocity graph in the die slit area, reducing the deviation value from 0.097 to 0.015. Additionally, the mass flux variance across the die outlet decreased by 71.6% from 0.015069 kg m−2 s−1 to 0.004281 kg m−2 s−1. Therefore, using this method reduces the amount of time wasted on trial and error or other optimization techniques that may be limited by design constraints.

The powder-mixed electro-discharge machining (PM-EDM) technique has shown its advantages in forming surfaces and depositing elements on the machined surface. Moreover, using hydroxyapatite (HA) powder in PM-EDM enhances the biocompatibility of the implant’s surfaces. Ti-6Al-4V alloy has tremendous advantages in biocompatibility over other metallic biomaterials in bone replacement surgeries. However, the increasing demand for orthopedical implants is leading to a more significant number of implant surgeries, increasing the number of patients with failed implants. A significant portion of implant failures are due to bacterial inflammation. Despite that, there is a lack of current research investigating the antibacterial properties of Ti-6Al-4V alloys. This paper focuses on studying the performance of HA PMEDM on Ti-6Al-4V alloy and its effects on antibacterial properties. By changing the capacitance (1 nF, 10 nF and 100 nF), gap voltage (90 V, 100 V and 110 V) and HA powder concentration (0 g/L, 5 g/L and 10 g/L), machining performance metrics such as material removal rate (MRR), overcut, crater size and hardness were examined through the HA PM micro-EDM (PM-μ-EDM) technique. Furthermore, the surface roughness, contact angle, and antibacterial properties of HA PM micro-wire EDM (PM-μ-WEDM)-treated surfaces were evaluated. The antibacterial tests were conducted for Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Bacillus subtilis bacteria. The key results showed a correlation between the discharge energy and powder concentration with the antibacterial properties of the modified surfaces. The modified surfaces exhibited reduced biofilm formation under low discharge energy and a 0 g/L powder concentration, resulting in a 0.273 μm roughness. This pattern persisted with high discharge energy and a 10 g/L powder concentration, where the roughness measured 1.832 μm. Therefore, it is possible to optimize the antibacterial properties of the surface through its roughness.

Alzheimer’s disease (AD) is a severe neurodegenerative disorder of the brain that manifests as dementia, disorientation, difficulty in speech, and progressive cognitive and behavioral impairment. The emerging therapeutic approach to AD management is the inhibition of β-site APP cleaving enzyme-1 (BACE1), known to be one of the two aspartyl proteases that cleave β-amyloid precursor protein (APP). Studies confirmed the association of high BACE1 activity with the proficiency in the formation of β-amyloid-containing neurotic plaques, the characteristics of AD. Only a few FDA-approved BACE1 inhibitors are available in the market, but their adverse off-target effects limit their usage. In this paper, we have used both ligand-based and target-based approaches for drug design. The QSAR study entails creating a multivariate GA-MLR (Genetic Algorithm-Multilinear Regression) model using 552 molecules with acceptable statistical performance (R2 = 0.82, Q2loo = 0.81). According to the QSAR study, the activity has a strong link with various atoms such as aromatic carbons and ring Sulfur, acceptor atoms, sp2-hybridized oxygen, etc. Following that, a database of 26,467 food compounds was primarily used for QSAR-based virtual screening accompanied by the application of the Lipinski rule of five; the elimination of duplicates, salts, and metal derivatives resulted in a truncated dataset of 8,453 molecules. The molecular descriptor was calculated and a well-validated 6-parametric version of the QSAR model was used to predict the bioactivity of the 8,453 food compounds. Following this, the food compounds whose predicted activity (pKi) was observed above 7.0 M were further docked into the BACE1 receptor which gave rise to the Identification of 4-(3,4-Dihydroxyphenyl)-2-hydroxy-1H-phenalen-1-one (PubChem I.D: 4468; Food I.D: FDB017657) as a hit molecule (Binding Affinity = −8.9 kcal/mol, pKi = 7.97 nM, Ki = 10.715 M). Furthermore, molecular dynamics simulation for 150 ns and molecular mechanics generalized born and surface area (MMGBSA) study aided in identifying structural motifs involved in interactions with the BACE1 enzyme. Molecular docking and QSAR yielded complementary and congruent results. The validated analyses can be used to improve a drug/lead candidate’s inhibitory efficacy against the BACE1. Thus, our approach is expected to widen the field of study of repurposing nutraceuticals into neuroprotective as well as anti-cancer and anti-viral therapeutic interventions.

This case study aims to report on the psychological assessment and intervention for a 4-year-old preschooler with selective mutism. A comprehensive assessment that involves parents and teacher interview, classroom observation, Seguin Form Board Test (SFBT), Vineland Adaptive Behaviour Scales Third Edition (Vineland-3), Behaviour Assessment System for Children, Third Edition (BASC-3), Childhood Autism Rating Scale, Second Edition Standard Version Rating Booklet (CARS 2-ST), and School Speech Questionnaire were conducted. The psychological assessment revealed that the child fulfils the criteria for selective mutism. Play-based intervention sessions were then conducted, which involved gradual exposure to the child's teacher and peers and facilitation of verbalization related to child's interests and classroom routines. The child demonstrated improvement in her frequency of verbalizing in the classroom following the intervention, as supported by the improved score in the School Speech Questionnaire (SSQ). This case study illustrates the advantages of a collaborative approach that engages parents, teachers, and peers in the management of selective mutism during early childhood.

Microglial cells serve as molecular sensors of the brain that play a role in physiological and pathological conditions. Under normal physiology, microglia are primarily responsible for regulating central nervous system homeostasis through the phagocytic clearance of redundant protein aggregates, apoptotic cells, damaged neurons, and synapses. Furthermore, microglial cells can promote and mitigate amyloid β phagocytosis and tau phosphorylation. Dysregulation of the microglial programming alters cellular morphology, molecular signaling, and secretory inflammatory molecules that contribute to various neurodegenerative disorders especially Alzheimer’s disease (AD). Furthermore, microglia are considered primary sources of inflammatory molecules and can induce or regulate a broad spectrum of cellular responses. Interestingly, in AD, microglia play a double-edged role in disease progression; for instance, the detrimental microglial effects increase in AD while microglial beneficiary mechanisms are jeopardized. Depending on the disease stages, microglial cells are expressed differently, which may open new avenues for AD therapy. However, the disease-related role of microglial cells and their receptors in the AD brain remain unclear. Therefore, this review represents the role of microglial cells and their involvement in AD pathogenesis.

This research work aims to proceed with the optimization of Fused Deposition Modeling (FDM) printing parameters for acrylonitrile butadiene styrene (ABS) and polyamide (Nylon) to improve fatigue resistance. For that purpose, the methodology of the paper involves two main approaches: experimental study and finite element analysis. The experimental part of the paper used the Taguchi method to find the effects of printing internal geometry, printing speed, and nozzle diameter on the fatigue life of ABS and Nylon plastic materials. ANCOVA multiple linear regression and sensitivity analysis was used to investigate the effects of printing parameters on the fatigue life of materials. The analysis of the results revealed: Nylon performed better than ABS, but had a higher slope; the ‘tri-hexagon’ structure resulted in the highest fatigue life, but the effect was statistically significant only for ABS material; the fatigue life of both materials increased with decreasing the nozzle diameter; the printing speed had no statistically significant influence neither on ABS nor Nylon. The experimental results then were validated by numerical simulations and the difference between the values was within ±14% depending on the experiment. Such differences might occur due to numerical and experimental errors.

Developing biomaterials with appropriate physiochemical and mechanical properties as per the requirements set by biomedical applications remains a challenge. This challenge has pushed research in the direction of biomaterials development and the surface modification of existing materials that could be useful for biomedical applications. Keeping this demand in focus, this paper intends to conduct an in-depth review, which includes, first, the requirements of biomedical surfaces associated with the growth of cells on biomedical alloys, such as the bone formation, adhesion, increased wear resistance and biofilm formation; second, possible biomaterials candidates for such applications; and third, possible surface modification techniques. Both subtractive and additive methods of surface modification are discussed, along with their pros and cons. Hence, this study gives an excellent compendium of scientific works conducted on surface modification techniques and the development of biocompatible surface alloys, along with research trends.

The traditional manufacturing industry has been revolutionized with the introduction of additive manufacturing which is based on layer-by-layer manufacturing. Due to these tool-free techniques, complex shape manufacturing becomes much more convenient in comparison to traditional machining. However, additive manufacturing comes with its inherent process characteristics of high surface roughness, which in turn effect fatigue strength as well as residual stresses. Therefore, in this paper, common post-processing techniques for additive manufactured (AM) parts were examined. The main objective was to analyze the finishing processes in terms of their ability to finish complicated surfaces and their performance were expressed as average surface roughness (Sa and Ra). The techniques were divided according to the materials they applied to and the material removal mechanism. It was found that chemical finishing significantly reduces surface roughness and can be used to finish parts with complicated geometry. Laser finishing, on the other hand, cannot be used to finish intricate internal surfaces. Among the mechanical abrasion methods, abrasive flow finishing shows optimum results in terms of its ability to finish complicated freeform cavities with improved accuracy for both polymer and metal parts. However, it was found that, in general, most mechanical abrasion processes lack the ability to finish complex parts. Moreover, although most of post-processing methods are conducted using single finishing processes, AM parts can be finished with hybrid successive processes to reap the benefits of different post-processing techniques and overcome the limitation of individual process.

Dimensional accuracy and geometric characteristics of the manufactured parts bear significant importance in product assembly. In Rapid Investment Casting, these characteristics can be affected by the printing parameters of the Additive Manufacturing method used in the pattern production process. Stereolithography is one of the important AM techniques mostly exploited in RIC due to its accuracy, smooth surface, and precision. However, the effect of SLA printing parameters on the dimensional accuracy and geometric characteristics have not been studied thoroughly. This study considers an experimental approach to study the effect of SLA printing parameters such as layer thickness, build angle, support structure density, and support touchpoint size on the dimensional accuracy and geometrical characteristics of the Castable Wax printed patterns and the Al cast parts. Taguchi’s Design of Experiment was used to define the number of experimental runs. SolidCast simulation was used to design the orientation of casting feeder to achieve directional solidification. Coordinate Measuring Machine measurements of deviations in the printed and cast parts were analyzed using the “Smaller-the-better” scheme in the two-step optimization method of Taguchi experiments. Build angle and Layer thickness were identified to be the first and the second most impactful parameters, respectively, affecting both the dimensional and geometric accuracy of Castable Wax patterns and Al cast parts, with optimal values of 0 deg and 0.25 μm, respectively. Both printed and cast parts had twice as many deviations in geometry as in dimensions. The sphere roundness and angularity were found to be the most and least accurate geometric characteristics, respectively. The dimensions in the Z direction were more accurate than in the X-Y directions, showing the smallest size deviations for height measurements and large deviations in the length, width, and diameter of the hole.

Despite a large amount of research on depression and abuse, there is still a controversy on how abuse is measured and on childhood trauma’s effect on the physiological function of adults. Here, we attempt to clarify the relationship between different types of abuse and depression while focusing on childhood abuse. This article, unlike prior research, provides an overview that addresses physical, psychological, and sexual abuse and their psychological impact on the victims. Results show that abuse is a vulnerability factor for a variety of mental and physical health problems and that psychological abuse is strongly associated with depression. More research is needed to understand (a) the role of abuse in the development and maintenance of depression and, in particular, longitudinal studies that also account for the large number of risk and protective factors that influence this relationship and (b) how different types of abuse can influence response to treatment among survivors with depression, in order to provide effective trauma-focused approaches to manage depressive symptoms.

Alzheimer’s disease (AD) is an irreversible chronic neurodegenerative disorder that occurs when neurons in the brain degenerate and die. Pain frequently arises in older patients with neurodegenerative diseases including AD. However, the presence of pain in older people is usually overlooked with cognitive dysfunctions. Most of the times dementia patients experience moderate to severe pain but the development of severe cognitive dysfunctions tremendously affects their capability to express the presence of pain. Currently, there are no effective treatments against AD that emphasize the necessity for increasing research to develop novel drugs for treating or preventing the disease process. Furthermore, the prospective therapeutic use of cannabinoids in AD has been studied for the past few years. In this regard, targeting the endocannabinoid system has considered as a probable therapeutic strategy to control several associated pathological pathways, such as mitochondrial dysfunction, excitotoxicity, oxidative stress, and neuroinflammation for the management of AD. In this review, we focus on recent studies about the role of cannabinoids for the treatment of pain and related neuropathological changes in AD.

Neuropathic pain (NP) is the result of irregular processing in the central or peripheral nervous system, which is generally caused by neuronal injury. The management of NP represents a great challenge owing to its heterogeneous profile and the significant undesirable side effects of the frequently prescribed psychoactive agents, including benzodiazepines (BDZ). Currently, several established drugs including antidepressants, anticonvulsants, topical lidocaine, and opioids are used to treat NP, but they exert a wide range of adverse effects. To reduce the burden of adverse effects, we need to investigate alternative therapeutics for the management of NP. Flavonoids are the most common secondary metabolites of plants used in folkloric medicine as tranquilizers, and have been claimed to have a selective affinity to the BDZ binding site. Several studies in animal models have reported that flavonoids can reduce NP. In this paper, we emphasize the potentiality of flavonoids for the management of NP.

Non-conductive structural ceramics are receiving ever-increasing attention due to their outstanding physical and mechanical properties and their critical applications in aerospace and biomedical industries. However, conventional mechanical machining seems infeasible for the machining of these superior ceramics due to their extreme brittleness and higher hardness. Electro discharge machining (EDM), well known for its machining of electrically conductive materials irrespective of materials hardness, has emerged as a potential machining technique due to its noncontact nature when complemented with an assistive electrode technique. This paper investigates the material removal mechanism and effects of machining parameters on machining speed and dimensional and profile accuracies of features machined on zirconia toughened alumina (ZTA) ceramics using assistive electrode EDM. Our experimental results demonstrate that both increasing peak current and pulse on time improves the MRR, however, it also aids in generating thicker layer on machined surface. In addition, pulse interval time is crucial for the machining of nonconductive ceramics, as larger value might cause the complete removal of intrinsic carbon layer which may lead to non/sparking condition. Higher peak current increases circularity whereas short pulse on and pulse off time aid in increasing circularity due to rough machining. In addition, taperness is found to be regulated by the peak current and pulse on time. Overall, thermal cracking and spalling appear to be a dominating material removal mechanism other than melting and evaporation for the EDM of ZTA.

Advanced methods for manufacturing high quality parts should be used to ensure the production of competitive products for the world market. Investment casting (IC) is a process where a wax pattern is used as a sacrificial pattern to manufacture high precision casting of solid metal parts. Rapid casting is in turn, a technique that eases the IC process by combining additive manufacturing (AM) technologies with IC. The use of AM technologies to create patterns for new industrial products is a unique opportunity to develop cost-effective methods for producing investment casting parts in a timely manner. Particularly, stereolithography (SLA) based AM is of interest due to its high dimensional accuracy and the smooth surface quality of the printed parts. From the first appearance of commercially available SLA printers in the market, it took a few decades until desktop SLA printers became available to consumers at a reasonable price. Therefore, the aim of this review paper is to analyze the state-of-the-art and applicability of SLA based 3D printing technology in IC manufacturing, as SLA based AM technologies have been gaining enormous popularity in recent times. Other AM techniques in IC are also reviewed for comparison. Moreover, the SLA process parameters, material properties, and current issues are discussed.

This study reports on the numerical model development for the prediction of the material removal rate and surface roughness generated during electrical discharge machining (EDM). A simplified 2D numerical heat conduction equation along with additional assumptions, such as heat effect from previously generated crater on a subsequent crater and instantaneous evaporation of the workpiece, are considered. For the material removal rate, an axisymmetric rectangular domain was utilized, while for the surface roughness, a rectangular domain where every discharge resides at the end of previous crater was considered. Simulated results obtained by solving the heat equation based on a finite element scheme suggested that results are more realistic by considering instantaneous evaporation of the material from the workpiece and the effect of residual heat generated from each spark. Good agreement between our model and previously published data validated the newly proposed models and demonstrate that instantaneous evaporation, as well as residual heat, provide more realistic predictions of the EDM process.

Conventional machining techniques of ceramics such as milling, drilling, and turning experience high cutting forces as well as extensive tool wear. Nevertheless, non-contact processes such as laser machining and electro-discharge machining (EDM) remain suitable options for machining ceramics materials, which are considered as extremely brittle and hard-to-machine. Considering the importance of ceramic machining, this paper attempts to provide an insight into the state of the art of the EDM process, types of ceramics materials and their applications, as well as the machining techniques involved. This study also presents a concise literature review of experimental and theoretical research studies conducted on the EDM of ceramics. Finally, a section summarizing the major challenges, proposed solutions, and suggestions for future research directions has been included at the end of the paper.