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In mathematical analysis, the q-analogue of a function refers to a modified version of the function that is derived from q-series expansions. This paper is focused on the q-analogue of the exponential function and investigates a class of convex functions associated with it. The main objective is to derive precise inequalities that bound the coefficients of these convex functions. In this research, the initial coefficient bounds, Fekete–Szegő problem, second and third Hankel determinant have been determined. These coefficient bounds provide valuable information about the behavior and properties of the functions within the considered class. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive investigation of the Paleocene coal in the Tirah area, District Khyber, Khyber Pakhtunkhwa, Pakistan, utilizing onsite Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) experiments combined with geochemical analyses of obtained coal-rock samples. ERT and GPR profiles, along with geochemical data, were collected and meticulously analyzed to assess the potential and quality of coal seams based on coal ranking, aiming to delineate their spatial distribution and future exploitation prospects. The study reveals a wide range of resistivity values, spanning from 8.93 Ωm to 2472 Ωm. The uppermost layer, comprising silt and clay with water saturation, exhibits resistivity values ranging from 8.93 Ωm to 50 Ωm. The subsequent stratum, characterized by wet sandstone with minor shale and clay, has resistivity values between 50 Ωm and 95.3 Ωm. Significantly, the zone with resistivity values between 95.3 Ωm and 800 Ωm is identified as the probable host of the coal seams. Based on the results, the coal seams are estimated to exist at depths ranging from 14 to 23 m, with resistivity values between 95.3 Ωm and 800 Ωm. GPR results further corroborate these findings, revealing coal-bearing strata at various depths, thus confirming the ERT results. Additionally, proximate and ultimate analysis provided insights into the quality of the coal, with average concentration values of moisture content (6.95%), ash content (22.12%), volatile matter (28.55%), fixed carbon (42.40%), carbon content (55.35%), hydrogen (4.7%), nitrogen (0.95%), sulfur (4.82%), and oxygen (10.06%). Comparative analyses of the obtained results with local coals from the Salt Range in Punjab, Pakistan, and coal from Ogboyaga, Nigeria, confirm that the studied coal ranks as sub-bituminous. This comprehensive assessment offers valuable insights into the potential and quality of Paleocene coal in the studied region and is applicable to other areas with similar geological settings. [ABSTRACT FROM AUTHOR]

Simple Summary: Chordomas are rare tumors of the embryologic spinal cord remnant. They are locally aggressive and typically managed with surgery in combination with radiation therapy. However, there is great variability in practice patterns including different radiation treatment types and approaches, and limited high-level data to drive decision making. The purpose of this manuscript was to summarize the current literature specific to radiotherapy in the management of spine and sacral chordoma and to provide a practical guide on behalf of the Spine Tumor Academy, an international group of spinal oncology experts. Chordomas are rare tumors of the embryologic spinal cord remnant. They are locally aggressive and typically managed with surgery and either adjuvant or neoadjuvant radiation therapy. However, there is great variability in practice patterns including radiation type and fractionation regimen, and limited high-level data to drive decision making. The purpose of this manuscript was to summarize the current literature specific to radiotherapy in the management of spine and sacral chordoma and to provide practice recommendations on behalf of the Spine Tumor Academy. A systematic review of the literature was performed using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach. Medline and Embase databases were utilized. The primary outcome measure was the rate of local control. A detailed review and interpretation of eligible studies is provided in the manuscript tables and text. Recommendations were defined as follows: (1) consensus: approved by >75% of experts; (2) predominant: approved by >50% of experts; (3) controversial: not approved by a majority of experts. Expert consensus supports dose escalation as critical in optimizing local control following radiation therapy for chordoma. In addition, comprehensive target volumes including sites of potential microscopic involvement improve local control compared with focal targets. Level I and high-quality multi-institutional data comparing treatment modalities, sequencing of radiation and surgery, and dose/fractionation schedules are needed to optimize patient outcomes in this locally aggressive malignancy. [ABSTRACT FROM AUTHOR]

The Moroccan government has always advocated reducing energy intensity so as to reach the target of the sustainable development. The current study presents the connection between CO2 emission, energy intensity (EI), natural resource rents (NRRs), energy productivity (EP), and renewable energy (RE) by employing annual time-series data from 1990–2020 for Morocco. Using the ARDL model, the empirical findings illustrate that (i) increasing EI significantly contributes to carbon emissions, (ii) higher consumption of natural resources adversely affects CO2 emissions, and (iii) EP and RE are the key factors to mitigate carbon emissions in both the short term and long term, suggesting that these two factors strengthen the considerable impact of EI and the consumption of natural resources on carbon emissions. Nevertheless, the negative environmental effects are moderately neutralized by adopting significant clean and green energy consumption within the country. The outputs of the robustness test verify the reliability of the regression results. Moreover, a one-way Granger causality running from EI, EP, RE, and NRR to CO2 emissions indicates that any variation in these variables will cause CO2 emissions. The present study offers the latest insights by adding EP and RE into country development and will support government policy makers in decisions related to efficiently abating CO2 emissions. [ABSTRACT FROM AUTHOR]

Advancements in sensor-enabled devices led to the emergence of resource trading models for smart communities, such as the smart marketplace (SMP). Most of the proposed SMP architectures are based on blockchain technology, which has a public ledger to achieve transparency. Consequently, safeguarding the participant's anonymity, untraceability, and transactional data privacy during trading becomes a challenging task. Most of the existing solutions to achieve anonymity are based on multiple account mapping, which is prone to identity-based attacks, and cryptographic techniques are used to achieve transactional data privacy, which often has a high computational overhead. In this work, we propose a lightweight privacy-enabled message exchange mechanism to accomplish our privacy goals in a blockchain-based SMP. Evaluation of the scheme was conducted to measure its resilience toward safeguarding participants' anonymity, untraceability, and transactional data privacy during trading cycles. Statistical game theory-based security analysis and simulation based performance analysis of the proposed scheme showed that it achieved the desired privacy goals with a low computational overhead compared with existing state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

The quality characteristic(s) are assumed to follow the normal distribution in many control chart constructions, although this assumption may not hold in some instances. This study proposes the Bayesian-I and Bayesian-II Shewhart-type control charts for monitoring the Maxwell scale parameter in the phase II study. The posterior and predictive distributions are used to construct the control limits for the proposed Bayesian-I and Bayesian-II Shewhart-type control charts, respectively. Various performance indicators, including average run length, quadratic loss, relative average run length, and performance comparison index, are utilized to evaluate the performance of the proposed control charts. The Bayesian-I and Bayesian-II Shewhart-type control charts are compared to their competitive CUSUMV, EWMAV and V control charts. Sensitivity analysis is also performed to study the effect of hyperparameter values on the performance behavior of the proposed control charts. Finally, real-life data is analyzed for the implementation of the proposed control charts. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) monitoring is an effective tool to quantify the dynamic damage that may cause heavy casualties and huge property losses in rock engineering. Instead of traditional failure evaluation methods, in this paper, the coal failure mechanism is evaluated in a complicated geological environment under uniaxial compression tests by employing machine learning (ML) and automatic speech recognition (ASR). Taking advantage of the ASR technology, the Mel-frequency cepstrum coefficients (MFCC) were extracted as sample features, while ML was used to paradigm the artificial intelligent evaluation of the failure probability of coal (AIEFPC). Additionally, the five-fold cross-validation method was used to assess the AIEFPC predictive effect incorporating cumulative hits number, cumulative ring count, and amplitude as sample features. The influence of category weight on the prediction effect of AIEFPC on a different category of sample sets has been discussed and analyzed. The results show that AIEFPC has the potential to use the MFCC of the 40 ms AE segment at any time to predict the dangerous state of the coal sample with a prediction accuracy of >85%. The probability value of the hazardous samples is computed through AIEFPC that further helped in evaluating the reliability of the prediction results. It is inferred from the obtained results that a larger category weight value of the hazardous samples can improve the prediction accuracy of AIEFPC than the safe sample. This research provides a new way of effectively predicting the coal failure probability before the damage and failure that can be applied to worldwide case-studies. [ABSTRACT FROM AUTHOR]

The dynamic host configuration protocol (DHCP) servers are forms of an Internet of Things (IoT) address management server (IoTAMS) that gives network configuration settings to newly connected hosts. Administrators of a network may save time by setting DHCP servers instead of every network node. However, the absence of a more robust authentication method for DHCP servers makes hosts susceptible to attacks since neither the server nor the users are able to check the other's authenticity during DHCP connections. These concerns result in both internal and external threats to the system that have the potential to impair network services. Among these threats are malicious DHCP servers and DHCP starvation. This paper aims to provide a novel approach for tackling these issues and protect the DHCP protocol. The proposed model uses the Diffie–Hellman key exchange mechanism, the elliptic curve discrete logarithm problem (ECDLP), a one-way hash function, blockchain technology, and a smart contract. In addition, registration and validation processes provide support for the proposed model in combating DHCP risks for both internal and external system threats. Results from this study show that the proposed model has an average of 21.1% more resistance to a growing number of adversaries than the benchmark models, thus revealing that the model is better suited for the security of IoT address management servers in smart homes, thereby enhancing resilience against related threats and the success of IP address management. [ABSTRACT FROM AUTHOR]

Simple Summary: Here, we report the eco-friendly synthesis and antitumor potential of the imidazole hybrids of pyrimidine. The results showed that all the compounds possess excellent inhibition of tumors, promoting enzymes hCA-IX and hCA-II. Furthermore, the selectivity index showed that compounds 7, 10, and 11 are selective inhibitors of hCA-IX, while compound 2 is a selective inhibitor of hCA-IX. More importantly, all the active inhibitors are toxic to the breast cancer cell line and non-cytotoxic for the normal breast cell line. These compounds would be a suitable choice to investigate in the in vivo models to check their efficacy against these particular targets. These newly identified human carbonic anhydrase inhibitors have potential to be considered as therapeutic leads for the treatment of CA-related diseases, especially for breast and lung tumors and glaucoma. Furthermore, lead optimization and preclinical and clinical investigations of these compounds are necessary to develop potential drug entities for the treatment of cancer. Imidazole-based pyrimidine hybrids are considered a remarkable class of compounds in pharmaceutical chemistry. Here, we report the anticancer bioactivities of eleven imidazole-based pyrimidine hybrids (1–11) that specifically target cytosolic carbonic anhydrase (CAs) isoenzymes, including human CA-II and human CA-IX (hCA-II, and hCA-IX). A highly eco-friendly aqueous approach was used for the formation of a carbon–carbon bond by reacting aromatic nitro group substitution of nitroimidazoles with carbon nucleophiles. The in vitro results indicate that this new class of compounds (1–11) includes significant inhibitors of hCA IX with IC50 values in the range of 9.6 ± 0.2–32.2 ± 1.0 µM, while hCA II showed IC50 values in range of 11.6 ± 0.2–31.1 ± 1.3 µM. Compound 2 (IC50 = 12.3 ± 0.1 µM) showed selective inhibition for hCA-II while 7, 8, and 10 (IC50 = 9.6–32.2 µM) were selective for hCA-IX. The mechanism of action was investigated through in vitro kinetics studies that revealed that compounds 7, 3, 11, 10, 4, and 9 for CA-IX and 1, 2, and 11 for CA-II are competitive inhibitors with dissociation constant (Ki) in the range of 7.32–17.02 µM. Furthermore, the in situ cytotoxicity of these compounds was investigated in the human breast cancer cell line MDA-MB-231 and compared with the normal human breast cell line, MCF-10A. Compound 5 showed excellent anticancer/cytotoxic activity in MDA-MB-231 with no toxicity to the normal breast cells. In addition, in silico molecular docking was employed to predict the binding mechanism of active compounds with their targets. This in silico observation aligned with our experimental results. Our findings signify that imidazole-based hybrids could be a useful choice to design anticancer agents for breast and lung tumors, or antiglaucoma compounds, by specific inhibition of carbonic anhydrases. [ABSTRACT FROM AUTHOR]

We present a study concerning the thermospheric O/N2 variations for the period 2002 to 2020, using the measurements of global ultraviolet imager (GUVI) onboard TIMED satellite. In this regard, monthly averaged O/N2 was computed—using the five quietest days of the month—at low- and mid-latitudes. To find the longitudinal dependence of thermospheric variations, the analysis is further extended to different longitudinal sectors, namely Asia, Africa, and America. We found that the latitudinal and longitudinal O/N2 variations follow the solar activity. These variations, during a high solar activity in northern winter, are found to be always much greater than southern winter and northern summer. The latitudinal and longitudinal variations of O/N2 at low- and mid-latitudes in December solstice are observed to be higher than June solstice counterparts in the northern hemisphere. We also computed the amplitudes of annual and semiannual variations using the bandpass filters. The former variations of O/N2 for low-latitudes do not follow the solar activity in the southern hemisphere. Moreover, these variations are stronger for mid-latitudes as compared with low-latitude regions. Similarly, the annual variations in Asian and African sectors of southern hemisphere do not follow the solar cycle (SC) trends. In the northern hemisphere, the variations are stronger during a solar maximum than in the southern counterpart. The observed semiannual variations are in-phase for both hemispheres; moreover, the corresponding amplitude remains almost the same at low- and mid-latitudes, while the semiannual variations for low-latitudes, and corresponding longitudinal regions, are stronger during a high solar activity. These variations, for mid-latitudes, in African, northern Asian, and southern American sectors do not follow the SC activity. [ABSTRACT FROM AUTHOR]

The accurate monitoring and early warning of coal and rock dynamic disasters become challenging in complex geological environments. Mostly, the signal information contains interferences, which misguides the technician, and thus leads to inaccurate monitoring results. To reduce the influence of interference signals, the synchronous response of the acoustic emission (AE) and electromagnetic emission (EME) signals before the failure of coal specimens during uniaxial loading was investigated in this study. Additionally, the coupling relationship between M value, AE energy/AE ringing count per unit time, and the damage of coal is established, and the early warning index of AE and EME (R value) was computed and verified through the field investigations. The results show that a strong synchronization of the acoustoelectric signals occurs only after the specimen enters the strain strengthening area. The analysis of the obtained results showed that the M value of the AE-EME synchronous response signal represents a strong degree of damage occurring in the coal body, however, this is still subject to false alarms. In contrast, the analysis of the R value accurately helped in determining the damage evaluation, thus, it can be regarded as one of the precursors of the imminent failure of coal. With R > 1, the specimen is closed to the failure state, thereby dangerous regions are identified with a dense concentration of R > 1 events. The obtained R value index through on-site AE and EME monitoring corresponds closely with the stress distribution cloud map of the roadway. It is inferred that the anti-interference ability and the reliability of the R value index are stronger than the routine early warning indicators of the single-AE or EME energy. [ABSTRACT FROM AUTHOR]

Yellow rust (YR) globally affects wheat crops. It may turn into an epidemic, resulting in significant yield losses if the environment is suited to YR spread. The provision of resistant wheat cultivars is a sustainable protection strategy against YR. The current study aimed to use a combination of classical analytical tools to identify potential wheat lines through screening under YR stress for utilization in YR-resistance breeding. A total of 14 parents, which included 9 lines and 5 testers, were formed into 45 cross combinations via line × tester mating format. The tested germplasm was grown in a triplicate randomized full-block design, under optimal and yellow rust (YR)-stress conditions. Data were recorded on different morphological, physiochemical, yield and component traits at appropriate crop stages. A pre-combining ability analysis revealed significant inter-genotype variations. A combining ability study identified non-additive gene action in the inheritance of most of the investigated traits. Four potential parents (PR128, AN179, KS17 and WD17) and two crosses (PR128 × WD17 and AN179 × KS17) retained higher combining ability values for yield traits under YR-stress. A cluster analysis based on the overall performance found divergent classes among the screened genotypes. The clustering of different genotypes was shifted under YR-stress, which suggests variable genotypic response. Through factor analysis, we assessed and confirmed genotypes performing consistently under YR-stress. The identified genotypes may be used for disease-resistance breeding in wheat. Based on their positive correlation with grain yield, we suggest the use of peduncle length and tillers per plant as phenotypic markers for wheat selection and breeding. The knowledge base generated through the current study will add to the ongoing research on sustainable wheat breeding program. [ABSTRACT FROM AUTHOR]

Simple Summary: Theileria is the tick-borne disease-causing agent responsible for theileriosis in various animals. Like other tick-borne pathogens, the epidemiology, associated risk factors and genetic diversity of Theileria spp. have mostly remained unexplored in the region. The current study was designed to analyze the epidemiology, associated risk factors, and molecular characterization of Theileria spp. in the selected districts of Khyber Pakhtunkhwa, Pakistan. Among the chosen districts, the highest infection was found in Upper Dir, while the most prevalent species was Theileria annulata clustered with sequences for the same species reported from Pakistan, China, and Italy. The risk factors associated with Theileria infection included age, gender, breeds, feeding system, hygienic measure, farming system, stall system, and seasons. The microscopic examination, in combination with the molecular approach, will enhance the early diagnosis and accurate identification of Theileria spp. and facilitate effective control strategies against these parasites. Theileria annulata is a tick-associated parasite that causes tropical theileriosis in livestock and is responsible for huge economic losses. Studies have been neglected on the effect of Theileria spp. on cattle in Khyber Pakhtunkhwa (KP), Pakistan. The present study was designed to determine the genetic diversity and assess the risk factors associated with Theileria infection in selected districts of KP. Information on the risk factors related to the Theileria infection was collected through a questionnaire. Blood samples were collected from symptomatic cattle from January 2019 to February 2020, identified morphologically through microscopic examination, and processed for molecular characterization using the 18S rRNA gene as a genetic marker. Of the 555 cattle examined (136, 24.5%) and (294, 53%) were found positive for Theileria spp. by microscopic examination and a PCR test, respectively. Based on the PCR test, the highest prevalence of infection was found in district Upper Dir (46/75, 61.3%), followed by Lower Dir (54/90, 60%); Malakand (51/88, 57.9%); Peshawar (40/80, 50%); and Charsadda (52/112, 46.4%), with the lowest in Bajaur (51/110, 46.34%). A BLAST analysis of the 18S rDNA sequences showed 99.5% identity with T. annulata. In a phylogenetic tree, the 18S rDNA sequence of T. annulata clustered with sequences from Pakistan, China, and Italy. A significant association was observed between the prevalence of infection and different host characteristics. The highest infection was found in adult cattle (216/360, 60%); females (218/377, 57.8%); and Holstein Friesian (120/180, 66.6%). Theileria infection was significantly associated with management practices. Higher infection rates were observed in free-grazing cattle (190/412, 42.2%); those kept in unhygienic conditions (246/405, 60.7%); cattle in combined farming systems (165/255, 64.8%); and those in congested stall systems (150/218, 68.8%). Seasonal patterns were found to be significantly associated with infection, and a higher infection rate was observed in summer (215/350, 61.4%) than in winter (79/205, 38.5%). Identified risk factors should be considered in designing practical control approaches to reduce the burden of Theileria infection. Large scale studies are required to explore the diversity of Theileria species in KP, Pakistan. [ABSTRACT FROM AUTHOR]

Drones have been increasingly adopted to address several critical challenges faced by humanity to provide support and convenience. The technological advances in the broader domains of artificial intelligence and the Internet of Things (IoT) as well as the affordability of off-the-shelf devices, have facilitated modern-day drone use. Drones are readily available for deployment in hard to access locations for delivery of critical medical supplies, for surveillance, for weather data collection and for home delivery of purchased goods. Whilst drones are increasingly beneficial to civilians, they have also been used to carry out crimes. We present a survey of artificial intelligence techniques that exist in the literature in the context of processing drone data to reveal criminal activity. Our contribution also comprises the proposal of a novel model to adopt the concepts of machine learning for classification of drone data as part of a digital forensic investigation. Our main conclusions include that properly trained machine-learning models hold promise to enable an accurate assessment of drone data obtained from drones confiscated from a crime scene. Our research work opens the door for academics and industry practitioners to adopt machine learning to enable the use of drone data in forensic investigations. [ABSTRACT FROM AUTHOR]

A complex structural geology generally leads to significant consequences for hydrocarbon reservoir exploration. Despite many existing wells in the Kadanwari field, Middle Indus Basin (MIB), Pakistan, the depositional environment of the early Cretaceous stratigraphic sequence is still poorly understood, and this has implications for regional geology as well as economic significance. To improve our understanding of the depositional environment of complex heterogeneous reservoirs and their associated 3D stratigraphic architecture, the spatial distribution of facies and properties, and the hydrocarbon prospects, a new methodology of three-dimensional structural modeling (3D SM) and joint geophysical characterization (JGC) is introduced in this research using 3D seismic and well logs data. 3D SM reveals that the field in question experienced multiple stages of complex deformation dominated by an NW to SW normal fault system, high relief horsts, and half-graben and graben structures. Moreover, 3D SM and fault system models (FSMs) show that the middle part of the sequence underwent greater deformation compared to the areas surrounding the major faults, with predominant one oriented S30°–45° E and N25°–35° W; with the azimuth at 148°–170° and 318°–345°; and with the minimum (28°), mean (62°), and maximum (90°) dip angles. The applied variance edge attribute better portrays the inconsistencies in the seismic data associated with faulting, validating seismic interpretation. The high amplitude and loss of frequency anomalies of the sweetness and root mean square (RMS) attributes indicate gas-saturated sand. In contrast, the relatively low-amplitude and high-frequency anomalies indicate sandy shale, shale, and pro-delta facies. The petrophysical modeling results show that the E sand interval exhibits high effective porosity (∅eff) and hydrocarbon saturation (Shc) compared to the G sand interval. The average petrophysical properties we identified, such as volume of shale (Vshale), average porosity (∅avg), ∅eff, water saturation (SW), and the Shc of the E sand interval, were 30.5%, 17.4%, 12.2%, 33.2% and, 70.01%, respectively. The findings of this study can help better understand the reservoir's structural and stratigraphic characteristics, the spatial distribution of associated facies, and petrophysical properties for reliable reservoir characterization. [ABSTRACT FROM AUTHOR]

With the innovation of embedded devices, the concept of smart marketplace came into existence. A smart marketplace is a platform on which participants can trade multiple resources, such as water, energy, bandwidth. Trust is an important factor in the trading platform, as the participants would prefer to trade with those peers who have a high trust rating. Most of the existing trust management models for smart marketplace only provide a single aggregated trust score for a participant. However, they lack the mechanism to gauge the level of commitment shown by a participant while trading a particular resource. This work aims to provide a fine-grained trust score for a participant with respect to each resource that it trades. Several parameters, such as resource availability, success rate, and turnaround time are used to gauge the participant's level of commitment, specific to the resource being traded. Moreover, the effectiveness of the proposed model is validated through security analysis against ballot-stuffing and bad-mouthing attacks, along with simulation-based analysis and a comparison in terms of accuracy, false positive, false negative, computational cost and latency. The results indicate that the proposed trust model has 7% better accuracy, 30.13% lower computational cost and 31.74% less latency compared to the existing benchmark model. [ABSTRACT FROM AUTHOR]

This paper presents two new energy balanced routing protocols for Underwater Acoustic Sensor Networks (UASNs); Efficient and Balanced Energy consumption Technique (EBET) and Enhanced EBET (EEBET). The first proposed protocol avoids direct transmission over long distance to save sufficient amount of energy consumed in the routing process. The second protocol overcomes the deficiencies in both Balanced Transmission Mechanism (BTM) and EBET techniques. EBET selects relay node on the basis of optimal distance threshold which leads to network lifetime prolongation. The initial energy of each sensor node is divided into energy levels for balanced energy consumption. Selection of high energy level node within transmission range avoids long distance direct data transmission. The EEBET incorporates depth threshold to minimize the number of hops between source node and sink while eradicating backward data transmissions. The EBET technique balances energy consumption within successive ring sectors, while, EEBET balances energy consumption of the entire network. In EEBET, optimum number of energy levels are also calculated to further enhance the network lifetime. Effectiveness of the proposed schemes is validated through simulations where these are compared with two existing routing protocols in terms of network lifetime, transmission loss, and throughput. The simulations are conducted under different network radii and varied number of nodes. [ABSTRACT FROM AUTHOR]

Most applications of underwater wireless sensor networks (UWSNs) demand reliable data delivery over a longer period in an efficient and timely manner. However, the harsh and unpredictable underwater environment makes routing more challenging as compared to terrestrial WSNs. Most of the existing schemes deploy mobile sensors or a mobile sink (MS) to maximize data gathering. However, the relatively high deployment cost prevents their usage in most applications. Thus, this paper presents an autonomous underwater vehicle (AUV)-aided efficient data-gathering (AEDG) routing protocol for reliable data delivery in UWSNs. To prolong the network lifetime, AEDG employs an AUV for data collection from gateways and uses a shortest path tree (SPT) algorithm while associating sensor nodes with the gateways. The AEDG protocol also limits the number of associated nodes with the gateway nodes to minimize the network energy consumption and to prevent the gateways from overloading. Moreover, gateways are rotated with the passage of time to balance the energy consumption of the network. To prevent data loss, AEDG allows dynamic data collection at the AUV depending on the limited number of member nodes that are associated with each gateway. We also develop a sub-optimal elliptical trajectory of AUV by using a connected dominating set (CDS) tofurther facilitate network throughput maximization. The performance of the AEDG is validated via simulations, which demonstrate the effectiveness of AEDG in comparison to two existing UWSN routing protocols in terms of the selected performance metrics. [ABSTRACT FROM AUTHOR]

Carbonic anhydrase-II (CA-II) is strongly related with gastric, glaucoma, tumors, malignant brain, renal and pancreatic carcinomas and is mainly involved in the regulation of the bicarbonate concentration in the eyes. With an aim to develop novel heterocyclic hybrids as potent enzyme inhibitors, we synthesized a series of twelve novel 3-phenyl-β-alanine 1,3,4-oxadiazole hybrids (4a–l), characterized by 1H- and 13C-NMR with the support of HRESIMS, and evaluated for their inhibitory activity against CA-II. The CA-II inhibition results clearly indicated that the 3-phenyl-β-alanine 1,3,4-oxadiazole derivatives 4a–l exhibited selective inhibition against CA-II. All the compounds (except 4d) exhibited good to moderate CA-II inhibitory activities with IC50 value in range of 12.1 to 53.6 µM. Among all the compounds, 4a (12.1 ± 0.86 µM), 4c (13.8 ± 0.64 µM), 4b (19.1 ± 0.88 µM) and 4h (20.7 ± 1.13 µM) are the most active hybrids against carbonic CA-II. Moreover, molecular docking was performed to understand the putative binding mode of the active compounds. The docking results indicates that these compounds block the biological activity of CA-II by nicely fitting at the entrance of the active site of CA-II. These compounds specifically mediating hydrogen bonding with Thr199, Thr200, Gln92 of CA-II. [ABSTRACT FROM AUTHOR]

In continuation of phytochemical investigations of the methanolic extract of Dictyopteris hoytii, we have obtained twelve compounds (1–12) through column chromatography. Herein, three compounds, namely, dimethyl 2-bromoterepthalate (3), dimethyl 2,6-dibromoterepthalate (4), and (E)-3-(4-(dimethoxymethyl)phenyl) acrylic acid (5) are isolated for the first time as a natural product, while the rest of the compounds (1, 2, 6–12) are known and isolated for the first time from this source. The structures of the isolated compounds were elucidated by advanced spectroscopic 1D and 2D NMR techniques including 1H, 13C, DEPT, HSQC, HMBC, COSY, NEOSY, and HR-MS and comparison with the reported literature. Furthermore, eight compounds (13–20) previously isolated by our group from the same source along with the currently isolated compounds (1–12) were screened against the CA-II enzyme. All compounds, except 6, 8, 14, and 17, were evaluated for in vitro bovine carbonic anhydrase-II (CA-II) inhibitory activity. Eventually, eleven compounds (1, 4, 5, 7, 9, 10, 12, 13, 15, 18, and 19) exhibited significant inhibitory activity against CA-II with IC50 values ranging from 13.4 to 71.6 μM. Additionally, the active molecules were subjected to molecular docking studies to predict the binding behavior of those compounds. It was observed that the compounds exhibit the inhibitory potential by specifically interacting with the ZN ion present in the active site of CA-II. In addition to ZN ion, two residues (His94 and Thr199) play an important role in binding with the compounds that possess a carboxylate group in their structure. [ABSTRACT FROM AUTHOR]

Rockburst is a serious hazard in underground engineering, and accurate prediction of rockburst risk is challenging. To construct an intelligent prediction model of rockburst risk with interpretability and high accuracy, three binary scorecards predicting different risk levels of rockburst were constructed using ChiMerge, evidence weight theory, and the logistic regression algorithm. An intelligent rockburst prediction model based on scorecard methodology (IRPSC) was obtained by integrating the three scorecards. The effects of hazard sample category weights on the missed alarm rate, false alarm rate, and accuracy of the IRPSC were analyzed. Results show that the accuracy, false alarm rate, and missed alarm rate of the IRPSC for rockburst prediction in riverside hydropower stations are 75%, 12.5%, and 12.5%, respectively. Setting higher hazard sample category weights can reduce the missed alarm rate of IRPSC, but it will lead to a higher false alarm rate. The IRPSC can adaptively adjust the threshold and weight value of the indicator and convert the abstract machine learning model into a tabular form, which overcomes the commonly black box problems of machine learning model, as well as is of great significance to the application of machine learning in rockburst risk prediction. [ABSTRACT FROM AUTHOR]

The use of real-time systems is growing at an increasing rate. This raises the power efficiency as the main challenge for system designers. Power asymmetric multicore processors provide a power-efficient platform for building complex real-time systems. The utilization of this efficient platform can be further enhanced by adopting proficient scheduling policies. Unfortunately, the research on real-time scheduling of power asymmetric multicore processors is in its infancy. In this research, we have addressed this problem and added new results. We have proposed a dynamic-priority semi-partitioned algorithm named: Earliest-Deadline First with C=D Task Splitting (EDFwC=D-TS) for scheduling real-time applications on power asymmetric multicore processors. EDFwC=D-TS outclasses its counterparts in terms of system utilization. The simulation results show that EDFwC=D-TS schedules up to 67% more tasks with heavy workloads. Furthermore, it improves the processor utilization up to 11% and on average uses 14% less cores to schedule the given workload. [ABSTRACT FROM AUTHOR]

Delineation of fresh/saline groundwater is essential for sustainable water quality management, especially in the coastal areas all around the globe. Seawater intrusion causes substantial degradation in quality of freshwater resources in the coastal areas. The main reason for saltwater intrusion is the changing environment in terms of sea-level rise, climate change, and over-extraction of freshwater resources to meet the growing demands. In this study, an integrated approach of geophysical and geochemical methods was used to assess saltwater intrusion in the coastal areas of Bela Plain, Pakistan. The inverted electrical resistivity computed from 50 vertical electrical sounding (VES) constrained the subsurface into five layers and two aquifers through 3D imaging, such as silty clay and sandy clay containing saline water, and sand, sandy gravel, and gravel containing freshwater. However, the narrow range of resistivity values shows an overlap of saline/fresh groundwater. Such ambiguity in the resistivity interpretation was removed by Dar-Zarrouk (D-Z) parameters. D-Z parameters, namely transverse unit resistance (Tr), longitudinal unit conductance (Sc), and longitudinal resistivity (ρL) estimated from VES, marked a clear distinction between saline and fresh aquifers with a wide range of values. The geochemical method was performed using 20 water samples for the main cations (K+, Ca2+ Na+, and Mg2+), anions (SO42−, HCO3−, Cl−, and NO3−), and other parameters (TDS, EC, and pH). Fresh/saline aquifers revealed by D-Z parameters are in good agreement with those delineated by physicochemical parameters and local hydrogeological conditions. This study delineates seawater intrusion of about 13–42 km from Sonmiani Bay in the Arabian Sea towards the inlands of Bela Plain. Therefore, it is expected that this investigation will be helpful in future planning for the management and exploitation of freshwater resources in the study area. Our study suggests that D-Z parameters can be used as the most inexpensive alternative to the traditional geotechnical and environmental tests for the demarcation of fresh/saline groundwater with a large coverage in any coastal or contaminated area under a homogeneous or heterogeneous setting. [ABSTRACT FROM AUTHOR]

This review summarizes the latest findings in the literature of Angiopoietin-2 (Ang-2), Tyrosine-protein kinase receptor (Tie-2) complex, and faricimab along with their involvement for the treatment of retinal vascular diseases in various clinical trials. In ischemic diseases, such as diabetic retinopathy, Ang-2 is upregulated, deactivating Tie-2, resulting in vascular leakage, pericyte loss, and inflammation. Recombinant Angiopeotin-1 (Ang-1), Ang-2-blocking molecules, and inhibitors of vascular endothelial protein tyrosine phosphatase (VE-PTP) decrease inflammation-associated vascular leakage, showing therapeutic effects in diabetes, atherosclerosis, and ocular neovascular diseases. In addition, novel studies show that angiopoietin-like proteins may play an important role in cellular metabolism leading to retinal vascular diseases. Current therapeutic focus combines Ang-Tie targeted drugs with other anti-angiogenic or immune therapies. Clinical studies have identified faricimab, a novel bispecific antibody designed for intravitreal use, to simultaneously bind and neutralize Ang-2 and VEGF-A for treatment of diabetic eye disease. By targeting both Ang-2 and vascular endothelial growth factor-A (VEGF-A), faricimab displays an improved and sustained efficacy over longer treatment intervals, delivering superior vision outcomes for patients with diabetic macular edema and reducing the treatment burden for patients with neovascular age-related macular degeneration and diabetic macular edema. Phase 2 results have produced promising outcomes with regard to efficacy and durability. Faricimab is currently being evaluated in global Phase 3 studies. [ABSTRACT FROM AUTHOR]

Lycium shawii Roem. & Schult and resin of Aloe vera (L.) BURM. F. are commonly used in Omani traditional medication against various ailments. Herein, their antiproliferative and antioxidant potential was explored. Bioassay-guided fractionation of the methanol extract of both plants led to the isolation of 14 known compounds, viz., 1–9 from L. shawii and 10–20 from A. vera. Their structures were confirmed by combined spectroscopic techniques including 1D (1H and 13C) and 2D (HMBC, HSQC, COSY) nuclear magnetic resonance (NMR), and electrospray ionization-mass spectrometry (ESI-MS). The cytotoxic potential of isolates was tested against the triple-negative breast cancer cell line (MDA-MB-231). Compound 5 exhibited excellent antiproliferative activity in a range of 31 μM, followed by compounds 1–3, 7, and 12, which depicted IC50 values in the range of 35–60 μM, while 8, 6, and 9 also demonstrated IC50 values >72 μM. Subsequently, in silico target fishing was applied to predict the most potential cellular drug targets of the active compounds, using pharmacophore modeling and inverse molecular docking approach. The extensive in silico analysis suggests that our compounds may target carbonic anhydrase II (CA-II) to exert their anticancer activities. When tested on CA-II, compounds 5 (IC50 = 14.4 µM), 12 (IC50 = 23.3), and 2 (IC50 = 24.4 µM) showed excellent biological activities in vitro. Additionally, the ethyl acetate fraction of both plants showed promising antioxidant activity. Among the isolated compounds, 4 possesses the highest antioxidant (55 μM) activity followed by 14 (241 μM). The results indicated that compound 4 can be a promising candidate for antioxidant drugs, while compound 5 is a potential candidate for anticancer drugs. [ABSTRACT FROM AUTHOR]

Fourteen triterpene acids, viz., three tirucallane-type (1–3), eight ursane-type (4–11), two oleanane-type (12, 13) and one lupane type (21), along with boswellic aldehyde (14), α-amyrine (15), epi-amyrine (16), straight chain acid (17), sesquiterpene (19) and two cembrane-type diterpenes (18, 20) were isolated, first time, from the methanol extract of Boswellia elongata resin. Compound (1) was isolated for first time as a natural product, while the remaining compounds (2‒21) were reported for first time from B. elongata. The structures of all compounds were confirmed by advanced spectroscopic techniques including mass spectrometry and also by comparison with the reported literature. Eight compounds (1–5, 11, 19 and 20) were further screened for in vitro α-glucosidase inhibitory activity. Compounds 3–5 and 11 showed significant activity against α-glucosidase with IC50 values ranging from 9.9–56.8 μM. Compound 4 (IC50 = 9.9 ± 0.48 μM) demonstrated higher inhibition followed by 11 (IC50 = 14.9 ± 1.31 μM), 5 (IC50 = 20.9 ± 0.05 μM) and 3 (IC50 = 56.8 ± 1.30 μM), indicating that carboxylic acid play a key role in α-glucosidase inhibition. Kinetics studies on the active compounds 3–5 and 11 were carried out to investigate their mechanism (mode of inhibition and dissociation constants Ki). All compounds were found to be non-competitive inhibitors with Ki values in the range of 7.05 ± 0.17–51.15 ± 0.25 µM. Moreover, in silico docking was performed to search the allosteric hotspot for ligand binding which is targeted by our active compounds investigates the binding mode of active compounds and it was identified that compounds preferentially bind in the allosteric binding sites of α-glucosidase. The results obtained from docking study suggested that the carboxylic group is responsible for their biologic activities. Furthermore, the α-glucosidase inhibitory potential of the active compounds is reported here for the first time. [ABSTRACT FROM AUTHOR]

In the modern world, the computation of vague data is a challenging job. Different theories are presented to deal with such situations. Amongst them, fuzzy set theory and its extensions produced remarkable results. Samrandache extended the theory to a new horizon with the neutrosophic set (NS), which was further extended to interval neutrosophic set (INS). Neutrosophic cubic set (NCS) is the generalized version of NS and INS. This characteristic makes it an exceptional choice to deal with vague and imprecise data. Aggregation operators are key features of decision-making theory. In recent times several aggregation operators were defined in NCS. The intent of this paper is to generalize these aggregation operators by presenting neutrosophic cubic generalized unified aggregation (NCGUA) and neutrosophic cubic quasi-generalized unified aggregation (NCQGUA) operators. The accuracy and precision are a vital tool to minimize the potential threat in decision making. Generally, in decision making methods, alternatives and criteria are considered to evaluate the better outcome. However, sometimes the decision making environment has more components to express the problem completely. These components are named as the state of nature corresponding to each criterion. This complex frame of work is dealt with by presenting the multi-expert decision-making method (MEDMM). [ABSTRACT FROM AUTHOR]

Herein, a novel method for molecularly imprinted polymers (MIPs) using methacrylic acid functionalized beta-cyclodextrin (MAA-β-CD) monomer is presented, which was designed as a potential water-compatible composite for the controlled release of atropine (ATP). The molecularly imprinted microspheres with pH-sensitive characteristics were fabricated using thermally-initiated precipitation polymerization, employing ATP as a template molecule. The effects of different compounds and concentrations of cross-linking agents were systematically investigated. Uniform microspheres were obtained when the ratio between ATP, MAA-β-CD, and trimethylolpropane trimethacrylate (TRIM) was 1:4:20 (mol/mol/mol) in polymerization system. The ATP loading equilibrium data was best suited to the Freundlich and Langmuir isotherm models. The in vitro drug release study was assessed under simulated oral administration conditions (pH 1.5 and 7.4). The potential usefulness of MIPs as drug delivery devices are much better than non-molecularly imprinted polymers (NIPs). The study shows that the prepared polymers are a pH stimuli-responsive system, which controlled the release of ATP, indicating the potential applications in the field of drug delivery. [ABSTRACT FROM AUTHOR]

Abiotic stress is an important limiting factor in crop growth and yield around the world. Owing to the continued genetic erosion of the upland cotton germplasm due to intense selection and inbreeding, attention has shifted towards wild cotton progenitors which offer unique traits that can be introgressed into the cultivated cotton to improve their genetic performance. The purpose of this study was to characterize the Pkinase gene family in a previously developed genetic map of the F2 population derived from a cross between two cotton species: Gossypium hirsutum (CCRI 12-4) and Gossypium darwinii (5-7). Based on phylogenetic analysis, Pkinase (PF00069) was found to be the dominant domain with 151 genes in three cotton species, categorized into 13 subfamilies. Structure analysis of G. hirsutum genes showed that a greater percentage of genes and their exons were highly conserved within the group. Syntenic analysis of gene blocks revealed 99 duplicated genes among G. hirsutum, Gossypium arboreum and Gossypium raimondii. Most of the genes were duplicated in segmental pattern. Expression pattern analysis showed that the Pkinase gene family possessed species-level variation in induction to salinity and G. darwinii had higher expression levels as compared to G. hirsutum. Based on RNA sequence analysis and preliminary RT-qPCR verification, we hypothesized that the Pkinase gene family, regulated by transcription factors (TFs) and miRNAs, might play key roles in salt stress tolerance. These findings inferred comprehensive information on possible structure and function of Pkinase gene family in cotton under salt stress. [ABSTRACT FROM AUTHOR]

Viable collection is one of the imperative instruments of decision-making hypothesis. Collection operators are not simply the operators that normalize the value; they represent progressively broad values that can underline the entire information. Geometric weighted operators weight the values only, and the ordered weighted geometric operators weight the ordering position only. Both of these operators tend to the value that relates to the biggest weight segment. Hybrid collection operators beat these impediments of weighted total and request total operators. Hybrid collection operators weight the incentive as well as the requesting position. Neutrosophic cubic sets (NCs) are a classification of interim neutrosophic set and neutrosophic set. This distinguishing of neutrosophic cubic set empowers the decision-maker to manage ambiguous and conflicting data even more productively. In this paper, we characterized neutrosophic cubic hybrid geometric accumulation operator (NCHG) and neutrosophic cubic Einstein hybrid geometric collection operator (NCEHG). At that point, we outfitted these operators upon an everyday life issue which empoweredus to organize the key objective to develop the industry. [ABSTRACT FROM AUTHOR]

Neutrosophic cubic sets (NCs) are amore generalized version of neutrosophic sets(Ns) and interval neutrosophic sets (INs). Neutrosophic cubic setsare better placed to express consistent, indeterminate and inconsistent information, which provides a better platform to deal with incomplete, inconsistent and vague data. Aggregation operators play a key role in daily life, and in relation to science and engineering problems. In this paper we defined the algebraic and Einstein sum, multiplication and scalar multiplication, score and accuracy functions. Using these operations we defined geometric aggregation operators and Einstein geometric aggregation operators. First, we defined the algebraic and Einstein operators of addition, multiplication and scalar multiplication. We defined score and accuracy function to compare neutrosophic cubic values. Then we definedthe neutrosophic cubic weighted geometric operator (NCWG), neutrosophic cubic ordered weighted geometric operator (NCOWG), neutrosophic cubic Einstein weighted geometric operator (NCEWG), and neutrosophic cubic Einstein ordered weighted geometric operator (NCEOWG) over neutrosophic cubic sets. A multi-criteria decision making method is developed as an application to these operators. This method is then applied to a daily life problem. [ABSTRACT FROM AUTHOR]

In this research article, we propose a new structure namely inverse left almost semigroup (LA-semigroup) by adding confusion in our proposed image encryption scheme along with discrete and continuous chaotic systems in order to complement the diffusion characteristics. The performance analysis was conducted in terms of the correlation analysis, the pixels uniformity analysis, the sensitivity analysis, the information entropy analysis, and pixels difference based measurements. The results show that the proposed algorithm has better information security properties, which can provide strong security and a high performance. [ABSTRACT FROM AUTHOR]

The influence of Information Communication and Technology (ICT) in power systems necessitates Smart Grid (SG) with monitoring and real-time control of electricity consumption. In SG, huge requests are generated from the smart homes in residential sector. Thus, researchers have proposed cloud based centralized and fog based semi-centralized computing systems for such requests. The cloud, unlike the fog system, has virtually infinite computing resources; however, in the cloud, system delay is the challenge for real-time applications. The prominent features of fog are; awareness of location, low latency, wired and wireless connectivity. In this paper, the impact of longer delay of cloud in SG applications is addressed. We proposed a cloud-fog based system for efficient processing of requests coming from the smart homes, their quick response and ultimately reduced cost. Each smart home is provided with a 5G based Home Energy Management Controller (HEMC). Then, the 5G-HEMC communicates with the High Performance Fog (HPF). The HPFs are capable of processing energy consumers' huge requests. Virtual Machines (VMs) are installed on physical systems (HPFs) to entertain the requests using First Come First Service (FCFS) and Ant Colony Optimization (ACO) algorithms along with Optimized Response Time Policy (ORTP) for the selection of potential HPF for efficient processing of the requests with maximum resource utilization. It is analysed that size and number of virtual resources affect the performance of the computing system. In the proposed system model, micro grids are introduced in the vicinity of energy consumers for uninterrupted and cost optimized power supply. The impact of the number of VMs on the performance of HPFs is analysed with extensive simulations with three scenarios. [ABSTRACT FROM AUTHOR]