With the evolution of cybersecurity countermeasures, the threat landscape has also evolved, especially in malware from traditional file-based malware to sophisticated and multifarious fileless ...malware. Fileless malware does not use traditional executables to carry-out its activities. So, it does not use the file system, thereby evading signature-based detection system. The fileless malware attack is catastrophic for any enterprise because of its persistence, and power to evade any anti-virus solutions. The malware leverages the power of operating systems, trusted tools to accomplish its malicious intent. To analyze such malware, security professionals use forensic tools to trace the attacker, whereas the attacker might use anti-forensics tools to erase their traces. This survey makes a comprehensive analysis of fileless malware and their detection techniques that are available in the literature. We present a process model to handle fileless malware attacks in the incident response process. In the end, the specific research gaps present in the proposed process model are identified, and associated challenges are highlighted.
‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various ...public and private sector industries generate, store, and analyze big data with an aim to improve the services they provide. In the healthcare industry, various sources for big data include hospital records, medical records of patients, results of medical examinations, and devices that are a part of internet of things. Biomedical research also generates a significant portion of big data relevant to public healthcare. This data requires proper management and analysis in order to derive meaningful information. Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack. There are various challenges associated with each step of handling big data which can only be surpassed by using high-end computing solutions for big data analysis. That is why, to provide relevant solutions for improving public health, healthcare providers are required to be fully equipped with appropriate infrastructure to systematically generate and analyze big data. An efficient management, analysis, and interpretation of big data can change the game by opening new avenues for modern healthcare. That is exactly why various industries, including the healthcare industry, are taking vigorous steps to convert this potential into better services and financial advantages. With a strong integration of biomedical and healthcare data, modern healthcare organizations can possibly revolutionize the medical therapies and personalized medicine.
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CEKLJ, NUK, ODKLJ, UL, UM, UPUK
Rationally designed multiple hydroxyl-group-based chemosensors L1–L4 containing arene-based fluorophores are presented for the selective detection of Al3+ and Ga3+ ions. Changes in the absorption and ...emission spectra of L1–L4 in ethanol were easily observable upon the addition of Al3+ and Ga3+ ions. Competitive binding studies, detection limits, and binding constants illustrate significant sensing abilities of these chemosensors with L4, showing the best results. The interaction of Al3+/Ga3+ ions with chemosensor L4 was investigated by fluorescence lifetime measurements, whereas Job’s plot, high-resolution mass spectrometry, and 1H NMR spectral titrations substantiated the stoichiometry between L4 and Al3+/Ga3+ ions. The solution-generated L-M3+ species further detected pyrophosphate ion (PPi) by exhibiting emission enhancement and a visible color change. The binding of Al3+/Ga3+ ions with chemosensor L4 was further supported by density functional theory studies. Reversibility for the detection of Al3+/Ga3+ ions was achieved by utilizing a suitable proton source. The multiionic response, reversibility, and optical visualization of the present chemosensors make them ideal for practical applications for real samples, which have been illustrated by paper-strip as well as polystyrene film-based detection.
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IJS, KILJ, NUK, PNG, UL, UM
Water splitting via an electrochemical process to generate hydrogen is an economic and green approach to resolve the looming energy and environmental crisis. The rational design of multicomponent ...materials with seamless interfaces having robust stability, facile scalability, and low-cost electrocatalysts is a grand challenge to produce hydrogen by water electrolysis. Herein, we report a superhydrophilic homogeneous bimetallic phosphide of Ni2P–CuP2 on Ni-foam-graphene-carbon nanotubes (CNTs) heterostructure using facile electrochemical metallization followed by phosphorization without any intervention of metal-oxides/hydroxides. This bimetallic phosphide shows ultralow overpotentials of 12 (HER, hydrogen evolution reaction) and 140 mV (OER, oxygen evolution reaction) at current densities of 10 and 20 mA/cm2 in acidic and alkaline mediums, respectively. The excellent stability lasts for at least for 10 days at a high current density of 500 mA/cm2 without much deviation, inferring the practical utilization of the catalyst toward green fuel production. Undoubtedly, the catalyst is capable enough for overall water splitting at a very low cell voltage of 1.45 V @10 mA/cm2 with an impressive stability of at least 40 h, showing a minimum loss of potential. Theoretical study has been performed to understand the reaction kinetics and d-band shifting among metal atoms in the heterostructure (Ni2P–CuP2) that favor the HER and OER activities, respectively. In addition, the catalyst demonstrates an alternate transformation of solar energy to green H2 production using a standard silicon solar cell. This work unveils a smart design and synthesizes a highly stable electrocatalyst against an attractive paradigm of commercial water electrolysis for renewable electrochemical energy conversion.
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IJS, KILJ, NUK, PNG, UL, UM
Easy and bulk-scale syntheses of two-dimensional (2D) covalent organic frameworks (COFs) represent an enduring challenge in material science. Concomitantly, the most critical aspect is to precisely ...control the porosity and crystallinity of these robust structures. Disparate complementary approaches such as solvothermal synthesis have emerged recently and are fueled in part by the usage of different modulators and acids that have enriched the COF library. Yet, the fundamental understanding of the integral processes of 2D COF assembly, including their growth from nucleating sites and the origin of periodicity, is an intriguing chemical question that needs to be answered. To address these cardinal questions, a green and easy-to-perform approach of COF formation has been delineated involving acid-diamine salt precursors. The role of hydrogen bonding d av(Namine–H···Oacid); d av signifies the average Namine–H···Oacid distances, i.e., the average distance from the H atom of the amine to the O atom of the acid present in the acid-diamine salts in improving the COFs’ crystallinity and porosity has further been decoded by thorough crystallographic analyses of the salt molecules. What is particularly noteworthy is that we have established the hydrogen-bonding distances d av(Namine–H···Oacid) in the acid-diamine salts that are pivotal in maintaining the reversibility of the reaction, which mainly facilitates highly crystalline and porous COF formation. Moreover, this reactant-structure to the product-quality relationship has further been utilized for the synthesis of highly crystalline and porous COFs that are unattainable by other synthetic means.
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IJS, KILJ, NUK, PNG, UL, UM
Alzheimer's disease (AD) is a neurodegenerative disease, characterized by progressive loss of memory which is associated with other cognitive deficits. The two protein structures in the brain i.e. ...neurofibrillary tangles and senile plaques are considered to hamper the normal cognitive activity of the brain. There are various therapeutic interpolations under investigation to thwart and treat AD. Secretases inhibitors are important agents that inhibit the development of senile plaques. β-secretase (BACE) inhibitors are in lime light for the drug development of AD. BACE initiates the production of Aβ, so its inhibition provides a valid target for the AD. BACE inhibitors viz. LY2811376, LY2886721, E2609 are in different phases of clinical trials. However, chemical study of MK8931 was discontinued due to lack of chances of finding a positive clinical effect.
The review incorporates exhaustive literature reports on secretase inhibitors, γ-secretase modulators (GSMs) and α-secretase enhancers. The recent studies on the natural products as GSMs have also been included.
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•Summarizes exhaustive literature reports on secretase inhibitors, γ-secretase modulators (GSMs) and α-secretase enhancers.•Highlights recent studies on the natural products as GSMs.•Incorporates the update on β-secretase (BACE) inhibitors in clinical trials.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Covalent organic frameworks (COFs) have attracted considerable interest owing to their structural predesign ability, controllable chemistry, long-range periodicity, and pore interior ...functionalization ability. The most widely adopted solvothermal synthesis of COFs requires the use of toxic organic solvents. In line with the 5
th
principle of green chemistry and the United Nations' 12
th
Sustainable Development Goal, we aim to mitigate the adverse effect of solvents on COF synthesis. Here we have investigated twelve green solvents for the sustainable synthesis of five series of COFs using the solvothermal approach. Crystallinity and porosity were used to assess the quality of the obtained COFs. In addition, the suitability of the solvents in the synthesis of crystalline and porous COFs was investigated and color-coded for the final green assessment. In particular, γ-butyrolactone (for
TpPa
,
TpBD
, and
TpAzo
),
para
-cymene (
TpAnq
), and PolarClean (
TpTab
) were found to be excellent green solvents to produce high-quality COFs. For the first time, we successfully used quantitative structure-property relationships in combination with machine learning approaches to predict both the surface area and crystallinity of COFs using the structure of the solvents and COF building blocks.
Covalent organic frameworks have been prepared in sustainable solvents by a solvothermal method, and their porosity and crystallinity were predicted using QSPR and machine learning approaches.
There is a need for some techniques to solve various problems in today’s computing world. Metaheuristic algorithms are one of the techniques which are capable of providing practical solutions to such ...issues. Due to their efficiency, metaheuristic algorithms are now used in healthcare data to diagnose diseases practically and with better results than traditional methods. In this study, an efficient search has been performed where 173 papers from different research databases such as Scopus, Web of Science, PubMed, PsycINFO, and others have been considered impactful in diagnosing the diseases using metaheuristic techniques. Ten metaheuristic techniques have been studied, which include spider monkey, shuffled frog leaping algorithm, cuckoo search algorithm, ant lion technique of optimization, lion optimization technique, moth flame technique, bat-inspired algorithm, grey wolf algorithm, whale optimization, and dragonfly technique of optimization for selecting and optimizing the features to predict heart disease, Alzheimer's disease, brain disorder, diabetes, chronic disease features, liver disease, covid-19, etc. Besides, the framework has also been shown to provide information on various phases behind the execution of metaheuristic techniques to predict diseases. The study’s primary goal is to present the contribution of the researchers by demonstrating their methodology to predict diseases using the metaheuristic techniques mentioned above. Later, their work has also been compared and evaluated using accuracy, precision, F1 score, error rate, sensitivity, specificity, an area under a curve, etc., to help the researchers to choose the right field and methods for predicting the diseases in the future.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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