DC microgrids and low-voltage DC distribution systems have received wide interest because of their higher efficiency and operational flexibility to integrate distributed renewable energy sources. However, the rapid increase of current during fault conditions may prevent the optimal operation of multiple converters which in turn leads to the loss of overall microgrid control. In this paper, the term “controllable fault limiter” is applied in the sense of combining the distributed secondary control within the algorithm of fault mitigation technique. In light of this, a robust fault current preventive scheme based on a controllable fault current limiter (C-FCL) has been proposed. The mitigation technique can limit short-circuit currents and alleviate the impact of faults on voltage regulation and power sharing control in a ring DC microgrid configuration. The functionality of the C-FCL is achieved using coordinated soft switching followed by impedance control. To eliminate the coordination time delay, the C-FCL uses local measurements to provide a quick response to initiate the switching operation of fault-DC breaking. The modeling approach of resistance fault current limiter is presented. The results show that the preventive scheme can improve operational performance and enhance the voltage security of the overall system without affecting power sharing and voltage regulation of multiple converters.

This paper presents metasurface (MS)-based dual-band circularly polarized (CP) antenna. To improve the impedance bandwidth (IBW) and perform linearly polarized (LP) to circularly polarized conversion, a 50 $\Omega$ coplanar waveguide (CPW) microstrip-line-fed termination with an open radial stub is employed. With an overall size of 40 mm $\times 40$ mm $\times 1.658$ mm, the proposed antenna array produced an impedance bandwidth $(\vert \mathrm{S}_{11}\vert \leq-10\text{dB})$ of 7.88-9.03 GHz and 9.36-9.46 GHz with an axial ratio bandwidth of 8.74-8.87 GHz and 9.35-9.44 GHz. Also, it achieves a 90% radiation efficiency and yields broadside left-handed circularly polarized (LHCP) and right-handed circularly polarized (RHCP) radiation with a gain of 4.9 dBi. Additionally, it achieves a peak gain of 8.6 dBi at 8.2 GHz. The proposed antenna is a potential candidate for X-band applications.

This paper describes a metasurface (MS) absorbe-rbased circularly polarized (CP) antenna for 5G mmWave applications. A simple circular notched edge antenna with rectangular slot and 00+00-shaped slot on the ground plane operating at the fundamental mode of the desired frequency band is utilized. Additionally, rectangular patch-based MS is designed to operate at the same fundamental mode as the antenna, and the MS is positioned above the antenna at a specified distance to achieve the desired 3-dB axial ratio bandwidth (ARBW) and a 2.2-dBi gain enhancement while maintaining an appropriate size of 30 x 36 x 0.254 mm(3). The antenna achieved impedance bandwidth (vertical bar S11 vertical bar <= - 10 dB) without MS from 27.18 GHz up to 28.63 GHz and realized a gain of around 4.8 dBi at 28 GHz. The antenna with MS achieved an impedance bandwidth (IBW) from 27.00 GHz up to 29.20 GHz and realized a gain of around 7.0 dB at 28 GHz, and radiation efficiency above of 80%. The proposed antenna is a potential candidate for upcoming 5G applications.

This paper presents a frequency-reconfigurable circularly polarized (CP) meta-antenna for wireless communication systems. It uses low-cost PIN diodes (SMP-1320) for frequency reconfigurability and a 4x4 truncated square patch array for improved impedance bandwidth and CP conversion. With an overall size of 25 mm x 25 mm x 2.03 mm, the antenna has an impedance bandwidth (vertical bar S-11 vertical bar <= 10 dB) of 9.18-11.61 GHz (23.36%) and an axial ratio bandwidth of 10.71-11.47 GHz (6.85%). It achieves ON-state dual-CP performance and a peak gain above 8.4 dBi across all frequency bands, making it a promising candidate for X-band applications.

Underwater Wireless Sensor Networks (UWSNs) are essential for a number of environmental and oceanographic monitoring applications. However, they face different and more complex challenges than terrestrial wireless sensor networks (TWSNs). The main challenges faced by UWSNs are limited include high propagation delays, poor bandwidth, low throughput, and high energy consumption. Replacing sensor batteries in such networks becomes extremely difficult as they are usually deployed in remote areas where limited human interaction is possible. The unbalanced and inefficient usage of energy by various network nodes poses another issue, as it may reduce the applicability and feasibility of the network. Therefore, proposing Energy-Efficient Routing Protocols (E-ER-Ps) is crucial to improve the performance and lifespan of these networks. Due to the challenges mentioned earlier, this research presents an extensive analysis of several different E-ER-Ps intended for UWSNs. We compare contemporary approaches that use machine learning (ML) with conventional protocols, as ML-based approaches have shown significant potential in resolving the intricate challenges faced by UWSNs. This paper aims to present a critical review of different E-ER-Ps from various prospects for UWSNs. To better comprehend the structure and uses of these protocols, we provide an innovative taxonomy for their classification. While ML-based protocols are evaluated for their flexibility, predictive power, and overall efficiency advancements, traditional protocols are evaluated based on their routing tactics and energy-efficiency improvements. A thorough comparative analysis highlights the advantages, disadvantages, and possible uses for different protocols. Furthermore, a critical analysis of ML’s function, incorporating intelligent and adaptive routing approaches, is presented, highlighting the technology’s potential to completely alter UWSN management. To formulate and implement E-ER-Ps for UWSNs, the article concludes by highlighting the present obstacles, including the need for real-time flexibility, resilience to environmental alters, and interaction with pre-existing network infrastructures. The development of ML-based approaches, hybrid approaches that combine conventional and ML-based methodologies, and the design of protocols that can adapt dynamically to the changing circumstances of underwater habitats are highlighted as future research objectives. This research provides the foundation for future advancements in this crucial field by presenting a comprehensive overview of the state-of-the-art UWSN E-ER-Ps.

Soybean ( Glycine max (L.) Merr.) is one of the important oilseed crops that is widely cultivated around the world. It has a high amount of protein content as well as other essential vitamins that are important in our daily lives. For continuous improvement, the development of novel plant species that are resistant to biotic and abiotic stress using effective genetic diversity strategies is important. In the current study, a total of 25 diverse genotypes of soybean using 21 important agro morphological traits were studied. For qualitative traits significant level of variation was found for most of the traits. For quantitative traits, the highest coefficient of variance 32.74% was found for days to flower initiation, followed by days to flower completion 29.62%, while the lowest was found for a number of pods/plants 2.96%. Based on cluster analysis, all the genotypes were separated into two groups at 25% distance and further subdivided at 75% distance, where the genotypes NARC-2 and SWAT-84 were found the most diverse. The cluster three genotypes were found to have early mature genotypes (89 +/- 2.44). Based on a number of pods/plant and yield per plant, the cluster 4 genotypes were found to have a maximum number of pods/plant (98.26 +/- 32.10), and (38.66 +/- 6.85). Among the studied genotypes the highest grain yield (49 g) was produced by genotype C/B 28, whereas the lowest (14.56 g) was observed for C/B 7. Principal component analysis with an eigenvalue of 1.48 accounted for the total variation of 67.73%. The total seed storage proteins analysis resulted in 13 bands, and the molecular weight ranged from 15 to 170 kDa. Two-way cluster analysis was performed and all the populations were divided into two main lineages at 25% distance and further sub divided into six subgroups at distance of a 75%, where the genotypes NARC-2 and SWAT-84 were found the most diverse genotypes. These findings provide a basis for developing elite, locally adapted soybean genotypes as well as implications for understanding the diversity and relationships among these diverse Glycine max genotypes.

Background: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise being a key damaging component introduced due to a variety of environmental and mechanical factors. Objective: The aim of this research work is to addresses the issue of noise reduction and to predict Alzheimer's disease detection efficiently. Methods: First, we present a genetic programming (GP) technique for reducing Rician noise in MRI images to pre-process the dataset. To effectively reduce Rician noise, this GP approach combines a Feature Extraction component, GP Optimal Expression, and an Optimum Removal Estimation component. In the second phase, we design and develop an explainable Deep Learning framework. This framework uses a local data-driven interpretation technique based on SHAP values to investigate the relationship between the neural network's estimated AD diagnosis and the input MRI images. In addition, we handle class distribution by combining an oversampling strategy with a minority approach. Several assessment metrics are used to analyze the performance of our proposed model. Results: The proposed method is tested on a variety of medical samples, and the results are compared to those obtained using other comparable approaches. We also test and compare our model to three cutting-edge models: DenseNet169, VGGNet15, and Inceptionv3. Conclusions: The empirical results show that our proposed model outperforms others, particularly in handling basic structures with limited spectral features, lower computational complexity, and less overfitting. This research worked addressed Rician noise issue in MRI images and predict AD severity prediction using explainable deep learning framework.

Cinchona alkaloid-derived sulfonamides and ester dimers containing chiral hyperbranched polymers have been successfully synthesized and applied as catalysts in asymmetric reactions. Several hyperbranched polymers derived from cinchona alkaloids, incorporating sulfonamides and esters, were synthesized through Mizoroki-Heck coupling polymerization. These polymers were subsequently applied in enantioselective Michael addition reactions. As the prepared polymers are not soluble in frequently used organic solvents, they act as efficient catalysts in the enantioselective reaction of β-ketoesters to nitroolefins, achieving up to 99% enantioselectivity with good yields. The insoluble property allows them to better satisfy "green chemistry" requirements and be used several times without losing the enantioselectivity.

In this paper, we report Zn-doped quasi-two-dimensional (Q-2D) perovskite nanocrystals (NCs).

For the past 25 years, medical imaging has been extensively used for clinical diagnosis. The main difficulties in medicine are accurate disease recognition and improved therapy. Using a single imaging modality to diagnose disease is challenging for clinical personnel. In this paper, a novel structural and spectral feature enhancement method in NSST Domain for multimodal medical image fusion (MMIF) is proposed. Initially, the proposed method uses the Intensity, Hue, Saturation (IHS) method to generate two pairs of images. The input images are then decomposed using the Non-Subsampled Shearlet Transform (NSST) method to obtain low frequency and high frequency sub-bands. Next, a proposed Structural Information (SI) fusion strategy is employed to Low Frequency Sub-bands (LFS's). It will enhance the structural (texture, background) information. Then, Principal Component Analysis (PCA) is employed as a fusion rule to High Frequency Sub-bands (HFS's) to obtain the pixel level information. Finally, the fused final image is obtained by employing inverse NSST and IHS. The proposed algorithm was validated using different modalities containing 120 image pairs. The qualitative and quantitative results demonstrated that the algorithm proposed in this research work outperformed numerous state-of-the-art MMIF approaches.

Free radicals alter DNA, resulting in various chronic disorders, including cancer. Herbal therapy has a significant potential to block cancer progression and other chronic diseases. The Tamarix aphylla plays an essential role in the modulation of free radicals. Calotropis procera (leaves), a tropical medicinal plant, has shown protective effects against cancer progression. We have examined the antioxidant therapy of separate or combined forms of the Tamarix aphylla and Calotropis procera plant extracts. Tamarix aphylla demonstrated scavenging activity at various concentrations, including 100 microgram/ml, 500 microgram/ml, and 1000 microgram/ml (29%, 37% and 62%). The scavenging activity of Calotropis procera at various concentrations (100 microgram/ml, 500 microgram/ml, and 1000 microgram/ml) was 20%, 31% and 40% against the standard of ascorbic acid (65%, 77% and 84%). The mixture of both plant extracts displayed significant antioxidant potential at various concentrations 100 microgram/ml, 500 microgram/ml, and 1000 microgram/ml which were 45%, 64% and 78%. Our study showed that the mixture of both plants has a significant antioxidant potential by comparing individual plant extracts. Further studies are recommended to elucidate the anti-cancer potential of both plant extracts mixture using in vivo approach for tumor models.

The presence of microplastics in aquatic environments has raised concerns about their abundance and potential hazards to aquatic organisms. This review provides insight into the problem that may be of alarm for freshwater fish. Plastic pollution is not confined to marine ecosystems; freshwater also comprises plastic bits, as the most of plastic fragments enter oceans via rivers. Microplastics (MPs) can be consumed by fish and accumulated due to their size and poor biodegradability. Furthermore, it has the potential to enter the food chain and cause health problems. Evidence of MPs s ingestion has been reported in >150 fish species from both freshwater and marine systems. However, microplastic quantification and toxicity in freshwater ecosystems have been underestimated, ignored, and not reported as much as compared to the marine ecosystem. However, their abundance, influence, and toxicity in freshwater biota are not less than in marine ecosystems. The interaction of MPs with freshwater fish, as well as the risk of human consumption, remains a mystery. Nevertheless, our knowledge of the impacts of MPs on freshwater fish is still very limited. This study detailed the status of the toxicity of MPs in freshwater fish. This review will add to our understanding of the ecotoxicology of microplastics on freshwater fish and give subsequent research directions.

Morphometric measurement and roosting ecology of Pteropus medius were aimed to find out in Mansehra district of KP, Pakistan. Total 3149 numbers of bats were found in eight biological spots visited; Baffa Doraha, Darband, Dadar, Jallu, Hazara University, Garhi Habibullah Chattar Plain and Jabori, in total 299 numbers of different species of trees including; Morus alba, Pinus raxburghi, Eucalyptus camaldulensis, Morus nigra, Grevillea robusta, Brousonetia papyrifera, Platanus orientalis, Ailanthus altissima, Hevea brasiliensis and Populus nigra. Morphometric features were measured and found vary according to sex of the bats. The average wing span, wing`s length from tip of wing to neck, from thumb to tip of wing and the body`s length from head and claws were recorded to be 102.98 cm, 49.07cm, 28.7 cm and 22.78 cm respectively in males while 93.67 cm, 44.83cm, 24.78cm and 22.78 cm respectively in female bats. Mean circumference of the body including wings and without wing were measured as 22.78 cm and 17.29 cm in males and that of female were 20.07 cm and 16.9 cm. Average length of thumb 3.64 cm, ear`s length 3.1 cm, snout 5.62cm, eye length were 1.07 cm for both sexes and length between the feet in extended position were16.3 cm. Generally different measurement of males bodies were found to be greater than female such as mean body surface area, mass, volume and pressure were found to be 2691.79 cm2, 855.7gm,1236.4 ml and 295.77 dyne/ c m 3 for male and 2576.46 cm2, 852.71gm,1207 ml and 290.2 dyne/ c m 3 respectively for female. While weight and density for both males and females bats were same with mean of 8.59 newton and 0.701 g/m3. Findings of current reports can add valued information in literature about bats, which can be used for species identification and conservation.

Historical documents such as newspapers, invoices, contract papers are often difficult to read due to degraded text quality. These documents may be damaged or degraded due to a variety of factors such as aging, distortion, stamps, watermarks, ink stains, and so on. Text image enhancement is essential for several document recognition and analysis tasks. In this era of technology, it is important to enhance these degraded text documents for proper use. To address these issues, a new bi-cubic interpolation of Lifting Wavelet Transform (LWT) and Stationary Wavelet Transform (SWT) is proposed to enhance image resolution. Then a generative adversarial network (GAN) is used to extract the spectral and spatial features in historical text images. The proposed method consists of two parts. In the first part, the transformation method is used to de-noise and de-blur the images, and to increase the resolution effects, whereas in the second part, the GAN architecture is used to fuse the original and the resulting image obtained from part one in order to improve the spectral and spatial features of a historical text image. Experiment results show that the proposed model outperforms the current deep learning methods.

One of the possible potential candidates for describing the universe’s rapid expansion is modified gravity. In the framework of the modified theory of gravity f(R, G), this work features the materialization of anisotropic matter such as compact stars. Specifically, to learn more about the physical behavior of compact stars, the radial, and tangential pressures as well as the energy density of six stars namely [Formula: see text], SAXJ1808.4-3658, 4U1820-30, PSR J 1614 2230, VELA X-1, and Cen X-3 are calculated. Herein, the modified theory of gravity f(R, G) is disintegrated into two parts i.e. the [Formula: see text] hyperbolic f(R) model and the three different f(G) models. The study focuses on graphical analysis of compact stars wherein the stability aspects, energy conditions, and anisotropic measurements are mainly addressed. Our calculation revealed that for the positive value of parameter n of the model f(G), all the six stars behave normally.

Hereditary neurological disorders (HNDs) are a clinically and genetically heterogeneous group of disorders. These disorders arise from the impaired function of the central or peripheral nervous system due to aberrant electrical impulses. More than 600 various neurological disorders, exhibiting a wide spectrum of overlapping clinical presentations depending on the organ(s) involved, have been documented. Owing to this clinical heterogeneity, diagnosing these disorders has been a challenge for both clinicians and geneticists and a large number of patients are either misdiagnosed or remain entirely undiagnosed. Contribution of genetics to neurological disorders has been recognized since long; however, the complete picture of the underlying molecular bases are under-explored. The aim of this study was to accurately diagnose 11 unrelated Pakistani families with various HNDs deploying NGS as a first step approach. Using exome sequencing and gene panel sequencing, we successfully identified disease-causing genomic variants these families. We report four novel variants, one each in, ECEL1 , NALCN , TBR1 and PIGP in four of the pedigrees. In the rest of the seven families, we found five previously reported pathogenic variants in POGZ , FA2H , PLA2G6 and CYP27A1 . Of these, three families segregate a homozygous 18 bp in-frame deletion of FA2H , indicating a likely founder mutation segregating in Pakistani population. Genotyping for this mutation can help low-cost population wide screening in the corresponding regions of the country. Our findings not only expand the existing repertoire of mutational spectrum underlying neurological disorders but will also help in genetic testing of individuals with HNDs in other populations.

In this paper, we employed a hyperbolic viable model in the [Formula: see text] gravity to inspect the presence of wormhole geometries combined with the configurations of relativistic matter. In this regard, the static form of spherically symmetric spacetime was taken into account and the validity of energy conditions was verified by considering a particular form of matter and a combination of shape functions. The equilibrium background of wormhole models was analyzed by using the concept of an anisotropic fluid and explored our findings graphically. These nonstandard astrophysical wormhole models were further supported by the gravitational entity resulting from the [Formula: see text] gravity in the form of extra-curvature quantities. Furthermore, in the presence of an anisotropic fluid and [Formula: see text] gravity, it was demonstrated that the wormhole models might actually exist in a couple of zones in the parameter space without the requirement of exotic matter.

Many diseases, including cancer and diabetes mellitus, are caused by reactive oxygen species (ROS). Allium sativum (Garlic) contains vitamins A, B, and C, as well as effective drugs like insulin, alliin, mineral salts, mucilages, allicin, and volatile oils. Garlic has antioxidant properties which showed a therapeutic effect on some cancer types. The overall goal of this study was to conduct pharmacological testing to assess the combined antioxidant abilities of Allium sativum (cloves) methanolic and Tamarix aphylla (leaves) extracts. The extract demonstrated garlic activities in a dose-dependent manner, with scavenging activity of 21, 32, and 39% at different concentrations of 100, 500, and 1000 µg/mL. The antioxidant activity of Tamarix aphylla methanolic extract was 29, 37, and 62% using the DPPH free radical scavenging assay at different concentrations of 100, 500, and 1000 µg/mL. However, combining extracts revealed the greatest scavenging activity at various concentrations of 100, 500, and 1000 µg/mL. By using the DPPH free radical scavenging assay, the combined methanolic extract of Tamarix aphylla and Allium sativum demonstrated substantial antioxidant activity of 45, 65, and 75% at concentrations of 100, 500, and 1000 µg/mL. According to our findings, the combined therapy of Tamarix aphylla and Allium sativum significantly inhibited DPPH free radicals. Tamarix aphylla and Allium sativum combined therapy may play an important role in the inhibition of free radicals that cause cancer.

Food handlers plays a primary role in the transmission of pathogenically important protozoans and helminth parasites. This study was aimed to evaluate the prevalence of intestinal pathogenic protozoans and helminth parasites among food handlers in and around University of Malakand, Lower Dir, Pakistan. Stool samples were collected from 642 food handlers (all of male) in a cross-sectional study from January to November, 2017. Wet Mount Techniques and concentration methods by using salt and formol-ether solutions. Three hundred and eighty four cases (59.8%) were found infected with one more parasites. Most of the individuals were found infected with helminth (47.6%) as compared to intestinal protozoans (0.93%). Seventy two cases (11.2%) of the cases presented mixed infection with both intestinal protozoan and helminth parasites. The order of prevalence for intestinal helminth was Ancylostoma duodenale (n = 258, 40.1%), followed by Taeniasa ginata (n=96, 14.9%) Ascaris lumbricoides (n = 54, 8.40%) and Trichuris trichura (n=30, 4.60%). For intestinal protozoa, Entamoeba histolytica/dispar (n = 36, 5.64%) was the only protozoan detected. Mono-parasitism was higher than poly-parasitism. Family size income and education level were the factors significantly (P<0.05) associated in the parasites prevalence. Current research showed that IPIs are primarily the foodborne pathogens still an important public health problem in Pakistan. Effective control programs on parasitic diseases transfer and their associated factors are recommended.

All-inorganic perovskite quantum dots (QDs) (CsPbX 3 , X = Cl, Br, I) become promising candidate materials for the new generation of light-emitting diodes for their narrow emission spectrum, high photoluminescence quantum yield, and adjustable emission wavelength. However, the perovskite QDs materials still face instability against moisture, high-temperature, and UV-light. Many strategies have been reported to improve the photoluminescence (PL) performance of QDs while increasing their stability. These strategies can be divided into three main categories: doping engineering, surface ligand modification, coating strategies. This paper reviews the recent research progress of surface ligands, inorganic and polymer coating, and metal ions doping of CsPbX 3 QDs. Partial substitution of Pb 2+ with non-toxic or low-toxic metal ions can improve the formation energy of the perovskite lattice and reduce its toxicity. The surface polymer modification can use their ligands to bond with the uncoordinated lead and halogen ions on perovskite QDs surface to reduce surface defects, thereby improving the PL intensity and stability. In addition, the organic or inorganic coating materials on perovskite QDs can effectively avoid their contact with the external environment, thereby improving the stability of the perovskite. The optical properties of the modified QDs, including transient absorption spectra, temperature-dependent PL spectra, time-resolved photoluminescence (TRPL) spectra properties, etc. were discussed to explain the physical mechanism. The potential applications of all-inorganic perovskite QDs as down-conversion fluorescent materials in light-emitting diodes are presented. Finally, we provide some possible methods to further improve the PL performance of the all-inorganic perovskite QDs.