BML Munjal University

Polyvinylidene Fluoride (PVDF) polymer-based nanocomposites are known for their high optoelectronic, dielectric, and electrochemical properties. In the present work, anatase phase Titanium dioxide (A-TiO2) reinforced PVDF nanocomposite films are prepared by the solution casting method to enhance the optical and dielectric properties. The morphology of nanocomposite films is studied by Field Emission Scanning Electron Microscopy (FESEM). The optical properties of prepared nanocomposite films for various compositions of A-TiO2 are estimated using UV-visible spectroscopy. The direct and indirect band gap decreases from 5.93 to 4.45 eV and 4.76 to 3.70 eV respectively for 4 wt% of A-TiO2 nanoparticles. The enhanced absorption in the UV region makes the current material a potential candidate for shielding UV radiations. After filler reinforcement, there is a significant increase in the refractive index and optical conductivity values for nanocomposite films. Thus, nanocomposite films can find many applications to block UV rays, and develop solar cells, and flexible optical devices.

Presently, NEPCMs (nanoencapsulated phase change materials) have received excessive consideration due to their capacity to release heat and absorb heat, taking it as flawless choice for applications in industry and various engineering fields. The present work is associated with the heat transfer performance of water-based NEPCMs nanofluid flow through a wedge surface under free convection condition. The nanoscale PCM capsules are formed by the n-nonadecane as a core and protective shell as a polyurethane. The impact of various operational parameters and geometrical parameter on surface drag force and heat transfer was investigated by using numerical method, i.e., bvp4c. These parameters comprise slip velocity, suction/injection, thermal radiation, magnetic field, viscous dissipation, volume fraction of NEPCMs, and wedge angle. The present code is validated with previous published literature under special case. The study reports that the heat transfer accelerated due to increase in volume fraction of NEPCMs nanoparticles from 2 to 6%. Fluid velocity escalated with increasing the values of suction and injection variables, while higher dissipation results in enhanced heat transfer. The study findings provide a valuable insight for application such as designing aircraft to improve boundary layer stability, optimizing heat extraction in underground thermal reservoir, and cooling of electronic devices.

Orthopedic implants are used to mitigate the problems related to musculoskeletal system. They are essential part in modern healthcare settings, designed to restore functioning and reducing the chronical pain in the patients suffering with any skeletal system disorders. Based on the application and the mechanical as well as biological compatibility of these implants, various suitable biomaterials are used for manufacturing of these implants. The effectiveness and life expectancy of these orthopedic implants are significantly influenced by their surface properties. This review delves into realm of various types of suitable biomaterials used for manufacturing of implant as well as the types of orthopedic implants and trauma fixation devices used in practice. Also, here we have discussed the necessity of coatings for these implants, for reducing bacterial infections, improved osseointegration, and enhanced corrosion resistance. The above approach helps in overcoming the problem of implant failure due to infection, non-union, or corrosion of implant surfaces. We examined different coating materials, including polymers, nanocomposites, and metals. Additionally, we have discussed in depth the advantages and challenges associated with existing coatings and their coating techniques. Overall, the aim of this review to give an overview of how coatings can influence the success of orthopedic implant and reduces the need for revision surgeries, highlighting ongoing challenges that need to be addressed to optimize the implant performance.

Cancer is complex because of the critical imbalance in genetic regulation as characterized by both the overexpression of oncogenes (OGs), mainly through mutations, amplifications, and translocations, and the inactivation of tumor-suppressor genes (TSGs), which entail the preservation of genomic integrity by inducing apoptosis to counter the malignant growth. Reviewing the intricate molecular interplay between OGs and TSGs draws attention to their cell cycle, apoptosis, and cancer metabolism regulation. In the present review, we discuss seminal discoveries, such as Knudson’s two-hit hypothesis, which framed the field’s understanding of cancer genetics, leading to the next breakthroughs with next-generation sequencing and epigenetic profiling, revealing novel insights into OG and TSG dysregulation with opportunities for targeted therapy. The key pathways, such as MAPK/ERK, PI3K/AKT/mTOR, and Wnt/β-catenin, are presented in the context of tumor progression. Importantly, we further highlighted the advances in therapeutic strategies, including inhibitors of KRAS and MYC and restoration of TSG function, despite which mechanisms of resistance and tumor heterogeneity pose daunting challenges. A high-level understanding of interactions between OG-TSGs forms the basis for effective, personalized cancer treatment—something to strive for in better clinical outcomes. This synthesis should integrate foundational biology with translation and, in this case, contribute to the ongoing effort against cancer.

Cancer, characterized by the uncontrolled proliferation of cells, is one of the leading causes of death globally, with approximately one in five people developing the disease in their lifetime. While many driver genes were identified decades ago, and most cancers can be classified based on morphology and progression, there is still a significant gap in knowledge about genetic aberrations and nuclear DNA damage. The study of two critical groups of genes—tumor suppressors, which inhibit proliferation and promote apoptosis, and oncogenes, which regulate proliferation and survival—can help to understand the genomic causes behind tumorigenesis, leading to more personalized approaches to diagnosis and treatment. Aberration of tumor suppressors, which undergo two-hit and loss-of-function mutations, and oncogenes, activated forms of proto-oncogenes that experience one-hit and gain-of-function mutations, are responsible for the dysregulation of key signaling pathways that regulate cell division, such as p53, Rb, Ras/Raf/ERK/MAPK, PI3K/AKT, and Wnt/β-catenin. Modern breakthroughs in genomics research, like next-generation sequencing, have provided efficient strategies for mapping unique genomic changes that contribute to tumor heterogeneity. Novel therapeutic approaches have enabled personalized medicine, helping address genetic variability in tumor suppressors and oncogenes. This comprehensive review examines the molecular mechanisms behind tumor-suppressor genes and oncogenes, the key signaling pathways they regulate, epigenetic modifications, tumor heterogeneity, and the drug resistance mechanisms that drive carcinogenesis. Moreover, the review explores the clinical application of sequencing techniques, multiomics, diagnostic procedures, pharmacogenomics, and personalized treatment and prevention options, discussing future directions for emerging technologies.

Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people’s life. The identification of driver fatigue and the appropriate handling of such information is the primary objective of this study. Ongoing developments in AI (artificial intelligence) as well as ML (machine learning) within ADAS (Advanced Driver Assistance Systems) have made the application of Internet-of-Things (IoT) technology in driver action recognition necessary. These advancements are dramatically changing the driving experience. This study suggests a novel method for machine learning-based automatic driving change-based drowsiness detection. In this instance, the multi-body sensor detects the driver’s EEG signal and gathers information for brain activity analysis. The wavelet time frequency transform model has been used to examine this signal in order to classify patterns of brain activity. A multi-layer convolutional programmed transfer VGG-16 neural network was then used to classify this examined pattern. This classified signal will cause the automatic driving mode to change. In terms of prediction accuracy, sensitivity, specificity, RMSE, ROC, experimental analysis has been performed for a variety of EEG signal datasets. The goal of this work is to reduce the risks that come with driving while drowsy which will improve road safety and reduce incidents that are related to fatigue.

Currently reading: Abstract Save PDF Share Cite Rights & Permissions [Opens in a new window] Abstract The Taliban’s forceful control of Kabul resulted in severe criticism by the world community and has consequently raised a pertinent question about its recognition in international law. Though a few countries publicly denied recognition to the Taliban government, many countries have (re)-started engaging with it by concluding bilateral treaties and (re)-opening embassies without recognition. Besides, countries have put several “conditions”, such as respect for human rights and a promise to form an “inclusive government”, before they will recognize the Taliban government. This note maps out these “conditions”, along with different proposals states have proposed concerning recognizing the Taliban government. It identifies the possible legal consequences of these “proposals” for the institution of recognition of government in international law. The note finally argues that though a recognition decision is largely political, it should nevertheless be regulated by international law to the extent that it would help avoid adverse international legal consequences.

The physical, thermal, mechanical, and morphological characteristics of non‐hybrid and hybrid composites reinforced with vetiver (VF) and rattan fiber (RF) in a PLA matrix were investigated in this work. To achieve this, five types of composites were created: three hybrids and two non‐hybrids, using twin‐screw extrusion and push‐and‐fit injection molding machines. The physical properties, such as density and porosity, were examined. The mechanical properties of the composites, including flexural, tensile, compressive, and impact strengths, were also assessed, along with their thermal properties, which were analyzed through thermal conductivity. In addition, the composite's chemical composition was studied through FTIR and XRD. An increase in density with the addition of RF and VF fibers was noticed. VF50‐RF50 hybrid composite exhibits the highest density with the lowest porosity. Improved crystallinity was obtained in the RF‐PLA composite. RF/PLA composite revealed Young's modulus of 2257.45 MPa and maximum tensile strength of 29.95 MPa, flexural strength of 60.56 MPa. Among the hybrid composites, the VF50‐RF50 composite exhibits very balanced properties with 23.89 MPa tensile strength, 2038.3 MPa Young's modulus, 48.21 MPa of flexural strength, and 0.66 W/mk thermal conductivity, which is the highest among all the fabricated composites. Rattan‐vetiver‐PLA composites can be a better alternative in manufacturing lightweight furniture and partition boards. Highlights A novel hybrid composite was prepared. Improved physical and mechanical properties in rattan/vetiver‐PLA composites. VF50‐RF50 hybrid composite shows the lowest void content of 1.02%. RF/PLA composite shows the highest tensile and compressive strength of 29.95 MPa and 186.52 MPa. Research suggests potential in eco‐friendly furniture, kitchenware, and load‐bearing furniture components.

While Zika virus (ZIKV) infection in pregnant women is known to increase the risk of miscarriage and stillbirth, the mechanism by which ZIKV infection leads to the inability to continue a pregnancy is not clear. In our common marmoset models of ZIKV infection in pregnant individuals, miscarriage was observed in dams infected in the first or second trimester, and preterm delivery was observed in a dam infected in the third trimester. Serum progesterone levels were significantly lower prior to miscarriage or preterm delivery in the infected marmosets. To elucidate the pathology of the placental region just before the onset of ZIKV-induced miscarriage, we newly prepared an infected marmoset in the first trimester of pregnancy and euthanized it when the serum progesterone concentration was markedly reduced. Pathological analysis revealed significant degeneration in cells at the maternal-fetal interface, presumably trophoblasts. Cleaved-caspase was widely observed in the endometrial to placental region, and TNFα at 200 pg/mL was detected in the amniotic fluid, suggesting that apoptosis may progress in the endometrium and placenta, leading to decreased trophoblast function and miscarriage. ZIKV NS1 protein was found sporadically in the cellular degeneration area and widely in the basal layer of the endometrium. Furthermore, the viral protein was frequently detected in the follicles and corpus luteum of the ovary. The developed ZIKV infection model in pregnant marmosets would be useful not only to better understand the mechanism of ZIKV-induced miscarriage but also to analyze the effects of the viral infection on female reproductive tissues. IMPORTANCE Although several viruses, including Zika virus (ZIKV), are known to increase the risk of miscarriage upon viral infection, the mechanism by which miscarriage is induced by viral infection is largely unknown. This is partly due to the difficulty of pathological analysis of maternal tissues in the period following viral infection and prior to miscarriage. In this study, we predicted the occurrence of miscarriage by monitoring serum progesterone levels and performed pathological analysis of peri-placental tissues at a time point assumed to be just before miscarriage. This is the first report of trophoblast degeneration prior to miscarriage, suggesting that the experimental method used here is useful for analyzing the pathogenesis of virus infection-related miscarriage. Further immunostaining revealed that ZIKV NS1 was distributed not only in the uterus but also in the ovaries, with particularly pronounced staining of oocytes. Whether ZIKV infection affects female reproductive function should be clarified in the future.

In a growing demand of accurately predicting the stock market and inefficient complex markets the rising accurate relationship prediction is not adequately addressed by the conventional methods. The dynamic and complex natures of data sources become the issue and we need to propose an effective method for adaptive algorithms to accurately forecasting and make decision efficiently. The system framed with two stages of execution: The first stage has covered time series-based predictions for different stock values involving the LSTM Model; the second stage integrated the experimental scenarios based on trend, value, indicators, and it's supporting impacted data metrics, which experimented on various large-cap stock companies. The dataset is sourced online by yahoo finance API with consecutive days data and dependable, non-dependable influenced indicators, which helped to intend trend-based evaluation performances. The proposed model experimented on distinct stock values and test cases executed based on indicator-based prediction with a 76.92% accurate performance rate using a Random Forest Classifier and 76.92% of Logistic Regression. The value-based prediction test case has achieved a performance rate of 97.5% using SVR Regressor and 97.2% using Linear Regressor. It computed value of root mean square error for the Ten large cap companies for performance evaluation.

Introduction Ventricular assist devices (VADs) are lifesavers for people with advanced heart failure. The design of these devices has undergone drastic changes over time with the latest designs being far more efficient, small, lightweight, and more user-friendly. This study aims to analyze publications using bibliometric analysis and see the progress and identify key themes, trends, and collaboration networks. Method Data relevant to this study were obtained from Scopus and Web of Science databases from 1990 to 2023. Data analysis was done using Biblioshiny which is an R-based software and is part of RStudio and Microsoft Excel to analyze collaboration between countries, authors, keyword analysis, trend topics, and evolution of various themes related to this study. Results A total of 489 published documents were analyzed, and these documents were from 158 different sources and 1,753 authors. The top contributing journals were Artificial Organs and Asaio Journal with 116 and 81 publications, respectively. The top contributing authors in terms of total documents were Nose Y (35) and Throckmorton A (30) and in terms of total citations were Pagani F (2005) and Mehra M (1952). Top countries include the USA, China, and Germany. The trend topics include miniaturization, machine learning, wireless, shear flow, and fiber-optic sensors. Discussion The latest technological advancements in VAD design are making them a more suitable choice for a large number of patients. This bibliometric work will aid in identifying the newest trends and developments in this field and highlight the areas where more research is needed. These data are crucial for driving innovation in this field and for improving the lives of patients who depend on VADs. Future studies can be conducted to explore the use of artificial intelligence and machine learning that can learn from data about patients and then adapt as per the requirements of the patients.

Nanomechanical responses (force-time profiles) of crystal lattices under deformation exhibit random critical jumps, reflecting the underlying structural transition processes. Despite extensive data collection, interpreting dynamic critical responses and their underlying mechanisms remains a significant challenge. This study explores a microscopic theoretical approach to analyse critical force fluctuations in martensitic transitions. Extensive sampling of the critical forces was performed using nonequilibrium molecular dynamics simulations of an atomic model of single-crystalline titanium nickel. We demonstrate that a framework of nonequilibrium statistical mechanics offers a principled explanation of the relationship between strain rate and the critical force distribution as well as its mean. The martensitic transition is represented on a free energy landscape, taking into account the thermally activated evolution of atomic arrangements over a barrier during its time-dependent deformation. The framework enables consistent inference of the relevant fundamental properties (e.g., intrinsic rate, activation free energy) that define the rate process of structural transition. The study demonstrates how the statistical characterisation of nanomechanical response-stimulus patterns can offer microscopic insights into the deformation behaviours of crystalline materials.

The corporate social disclosures made by companies are gaining popularity on a global scale. Companies are either doing it out of disclosure obligations or to reduce information asymmetries and gain investors' confidence. The objective of our study is to examine whether women directors affect the disclosures of social information for a representative sample of Indian listed companies. Our sample includes top listed NSE‐100 non‐banking Indian companies. We measure women participation at the leadership level using the ratio of women at the board level and the Blau index. The social scores include indicators on human rights, community, workforce, and product responsibility and we test the impact of gender diversity on these indicators. Further, three categories of women directors have been created: (a) one woman director, (b) two women directors, and (c) three or more women directors to test their impact on social disclosures. We use the social disclosure scores for measuring the corporate social disclosures of the company. The research is quantitative and has been carried out by using dynamic panel models. The empirical results reveal that gender diversity has a positive impact on social disclosure of firms. Also, the contribution of women directors to social disclosure scores becomes effective only after reaching a critical mass. This study has significant implications for management and practitioners as it helps to determine the significance of women participation at leadership positions in order to improve policies for disseminating information of social nature.