Integrated assessment of groundwater quality dynamics and Land use/land cover changes in rapidly urbanizing semi-arid region.

Rapid urbanization worldwide, poses numerous environmental challenges between escalating land use land cover (LULC) changes and groundwater quality dynamics. The main objective of this study was to investigate the dynamics of groundwater quality and LULC changes in Sargodha district, Punjab, Pakistan. Groundwater hydrochemistry reveals acceptable pH levels (<8) but total dissolved solids (TDS), electrical conductivity (EC) and HCO3- showed dynamic fluctuations by exceeding WHO limits. Piper diagrams, indicated dominance by magnesium and bicarbonate types, underscoring the influence of natural processes and anthropogenic activities. Major ion relationships in 2010, 2015, and 2021 showed a high correlation (R2 > 0.85) between Na+ and Cl-, suggesting salinization. whereas, the poor correlation (<0.17) between Ca2+ and HCO3- does not support calcite dissolution as the primary process affecting groundwater composition. The examination of nitrate contamination in groundwater across the years 2010, 2015, and 2021 was found to be high in the municipal sewage zone, suggesting a prevailing issue of nitrate contamination attributed to urban activities. The Nitrate Pollution Index (NPI) reveals a concerning trend, with a higher proportion of samples classified under moderate to high pollution categories in 2015 and 2021 compared to 2010. The qualitative assessment of nitrate concentration on spatiotemporal scale showed lower values in 2010 while a consistent rise from 2015 to 2021 in north-east and western parts of district. Likewise, NPI was high in the north-eastern and south-western regions in 2010, then reduced in subsequent years, which may be attributed to effective waste management practices and alterations in agricultural practices. The health risk assessment of 2010 indicated Total Health Hazard Quotient (THQ) within the standard limit, while in 2015 and 2021, elevated health risk was observed. This study emphasizes the need to use multiple approaches to groundwater management for sustainable land use planning and regulations that prioritize groundwater quality conservation.

A Hybrid Approach for Energy Consumption and Improvement in Sensor Network Lifespan in Wireless Sensor Networks.

In this paper, we propose an improved clustering algorithm for wireless sensor networks (WSNs) that aims to increase network lifetime and efficiency. We introduce an enhanced fuzzy spider monkey optimization technique and a hidden Markov model-based clustering algorithm for selecting cluster heads. Our approach considers factors such as network cluster head energy, cluster head density, and cluster head position. We also enhance the energy-efficient routing strategy for connecting cluster heads to the base station. Additionally, we introduce a polling control method to improve network performance while maintaining energy efficiency during steady transmission periods. Simulation results demonstrate a 1.2% improvement in network performance using our proposed model.

Hydrogeochemistry and prediction of arsenic contamination in groundwater of Vehari, Pakistan: comparison of artificial neural network, random forest and logistic regression models.

Arsenic contamination in the groundwater occurs in various parts of the world due to anthropogenic and natural sources, adversely affecting human health and ecosystems. The current study intends to examine the groundwater hydrogeochemistry containing elevated arsenic (As), predict As levels in groundwater, and determine the aptness of groundwater for drinking in the Vehari district, Pakistan. Four hundred groundwater samples from the study region were collected for physiochemical analysis. As levels in groundwater samples ranged from 0.1 to 52 µg/L, with an average of 11.64 µg/L, (43.5%), groundwater samples exceeded the WHO 2022 recommended limit of 10 µg/L for drinking purposes. Ion-exchange processes and the adsorption of ions significantly impacted the concentration of As. The HCO3- and Na+ are the dominant ions in the study area, and the water types of samples were CaHCO3, mixed CaMgCl, and CaCl, demonstrating that rock-water contact significantly impacts hydrochemical behavior. The geochemical modeling indicated negative saturation indices with calcium carbonate and other salt minerals, encompassing aragonite, calcite, dolomite, and halite. The dissolution mechanism suggested that these minerals might have implications for the mobilization of As in groundwater. A combination of human-induced and natural sources of contamination was unveiled through principal component analysis (PCA). Artificial neural networks (ANN), random forest (RF), and logistic regression (LR) were used to predict As in the groundwater. The data have been divided into two parts for statistical analysis: 20% for testing and 80% for training. The most significant input variables for As prediction was determined using Chi-squared analysis. The receiver operating characteristic area under the curve and confusion matrix were used to evaluate the models; the RF, ANN, and LR accuracies were 0.89, 0.85, and 0.76. The permutation feature and mean decrease in impurity determine ten parameters that influence groundwater arsenic in the study region, including F-, Fe2+, K+, Mg2+, Ca2+, Cl-, SO42-, NO3-, HCO3-, and Na+. The present study shows RF is the best model for predicting groundwater As contamination in the research area. The water quality index showed that 161 samples represent poor water, and 121 samples are unsuitable for drinking. Establishing effective strategies and regulatory measures is imperative in Vehari to ensure the sustainability of groundwater resources.

Genome wide and evolutionary analysis of heat shock protein 70 proteins in tomato and their role in response to heat and drought stress.

Heat shock protein 70 (HSP70) proteins play a crucial role in mitigating the detrimental effects of abiotic stresses in plants. In the present study, 21 full length non-redundant SlHSP70 genes were detected and characterized in tomato (Solanum lycopersicum L.). The SlHSP70 genes were classified into four groups based on phylogenetic analysis. Similarities were observed in gene features and motif structures of SlHSP70s belonging to the same group. SlHSP70 genes were unevenly and unequally mapped on 11 chromosomes. Segmental and tandem duplication are the main events that have contributed to the expansion of the SlHSP70 genes. A large number of groups and sub-groups were generated during comparative analysis of HSP70 genes in multiple plant species including tomato. These findings indicated a common ancestor which created diverse sub-groups prior to a mono-dicot split. The selection pressure on specific codons was identified through a maximum-likelihood approach and we found some important coding sites in the coding region of all groups. Diversifying positive selection was indirectly associated with evolutionary changes in SlHSP70 proteins and suggests that gene evolution modulated the tomato domestication event. In addition, expression analysis using RNA-seq revealed that 21 SlHSP70 genes were differentially expressed in response to drought and heat stress. SlHSP70-5 was down-regulated by heat treatment and up-regulated by drought stress. Furthermore, the expression of some of the duplicate genes was partially redundant, while others showed functional diversity. Our results indicate the diverse role of HSP70 gene family in S. lycopersicum under drought and heat stress conditions and open the gate for further investigation of HSP70 gene family functions, especially under drought and heat stress.

Range extension and species confirmation of Rhyneptesicus nasutus (Sind Serotine Bat) (Mammalia:Chiroptera) from Bajaur Agency, FATA, Pakistan.

BACKGROUND: The lack of morphological differentiation among chiropteran species and cryptic speciation impedes species identification. DNA-based approaches help species identification and contribute to the discovery of additional species. Rhyneptesicus nasutus (Sind Serotine Bat) is a rare and poorly studied species in Pakistan. METHODS: This study explores the range extension of Sind Bat within the territorial limits of Pakistan from Sind and Baluchistan to Federally Administered Areas of Pakistan. No molecular record exists for the species in Pakistan. In the present study, we for the first time confirm species identification of Rhyneptesicus nasutus from Pakistan using a genetic marker (cytochrome b) along with morphometric analysis. A neighbor-joining tree based on Kimura-2 parameters was created to infer phylogenetic relationships. We sequenced the cytochrome b gene segment and conducted a phylogenetic analysis with previously published data from other countries. RESULTS: Sequences from Pakistan formed a clade with Iranian Rhyneptesicus nasutus specimens suggesting a common ancestry. Various morphometric parameters (mean values) were measured, including Head and Body length (44.3 mm), Tail length (43.4 mm), Hindfoot length (8.3 mm), Forearm length (35.7 mm), and Ear length 36 mm while 5th Metacarpal Length, 4th Metacarpal Length, and 3rd Metacarpal Lengths were 33.2 mm, 34.7 mm, and 35.3 mm. Approaches based on DNA barcoding reveal a high diversity of bat species in the study area. CONCLUSION: The data will enable researchers to build an improved evolutionary framework of the Serotine Bats from this region and subsequently reconstruct a detailed evolutionary history of the genus. Further research is required to test other molecular markers to support the findings of the current study in Pakistan.

Natural products based crown ethers: synthesis and their anticancer potential.

Natural products based novel crown ethers have been prepared by employing biologically active natural structures including tetrahydroisoquinoline, chrysin and biochanin-A as the side arms. The resulting crown scaffolds were evaluated for their anticancer potential against two cancer cell lines i.e. NCI-H460 (non-small lung carcinoma), MCF-7 (breast adenocarcinoma). The comparative study showed that the addition of crown scaffold put marked effects on antiproliferative profile of parent natural precursors and is significant for lung carcinoma in particular. Biochanin-A derived crown ether showed three (03) folds higher antiproliferative activity (IC50 = 6.08 ± 0.07 µM) against lung carcinoma as compared to standard drug cisplatin (IC50 = 19.00 ± 1.24 µM). Cytotoxic trends for NIH-3T3 cell lines were also examined and found reduced as compared to parent natural structures. Hence, these findings could open a new pathway towards developing effective carcinostatic drugs.HIGHLIGHTSFour natural products based novel crown ethers have been developed.Comparative antiproliferative screening of crown ethers and natural precursors.Addition of crown showed marked effects on anticancer profile of natural products.Crown formation is significant for lung carcinoma potential in particular.Biochanin-A derived crown ether found three folds more active than standard drug.

Low-level laser therapy for the treatment of early stage cutaneous leishmaniasis: A pilot study.

Low-Level Laser Therapy (LLLT) has been investigated for the treatment of various dermatological disorders. Here, we investigate the efficacy of LLLT for the treatment of cutaneous leishmaniasis (CL). This study comprised of 53 patients (total 123 lesions) with a confirmed diagnosis of CL via positive smear of LD-bodies. The CL lesions were classified in Grade I (ie, papule of size ≤1 cm) to Grade V (ie, vesicle formation, ulceration, and superadded infection of size >4 cm). All the patients were divided into group 1 with low grade (ie, Grade I and II) CL lesions and group 2 with high-grade disease (ie, Grade III-V). Red laser light (wavelength = 635 nm) was used for the lesion irradiation, with a light dose of 75 J/cm2 and at a low power of 300 mW. The treatment was divided into four sessions, one session per week. Disease assessment at 10 months follow-up revealed complete response in 91% and partial response in 9% patients of group 1, while no response was observed in patients of group 2. LLLT offers a promising treatment modality for patients presenting with early-stage (ie, Grade I and II) CL lesions.

Stochastic equation of motion approach to fermionic dissipative dynamics. II. Numerical implementation.

This paper provides a detailed account of the numerical implementation of the stochastic equation of motion (SEOM) method for the dissipative dynamics of fermionic open quantum systems. To enable direct stochastic calculations, a minimal auxiliary space (MAS) mapping scheme is adopted, with which the time-dependent Grassmann fields are represented by c-number noises and a set of pseudo-operators. We elaborate on the construction of the system operators and pseudo-operators involved in the MAS-SEOM, along with the analytic expression for the particle current. The MAS-SEOM is applied to study the relaxation and voltage-driven dynamics of quantum impurity systems described by the single-level Anderson impurity model, and the numerical results are benchmarked against those of the highly accurate hierarchical equations of motion method. The advantages and limitations of the present MAS-SEOM approach are discussed extensively.

Stochastic equation of motion approach to fermionic dissipative dynamics. I. Formalism.

In this work, we establish formally exact stochastic equation of motion (SEOM) theory to describe the dissipative dynamics of fermionic open systems. The construction of the SEOM is based on a stochastic decoupling of the dissipative interaction between the system and fermionic environment, and the influence of environmental fluctuations on the reduced system dynamics is characterized by stochastic Grassmann fields. Meanwhile, numerical realization of the time-dependent Grassmann fields has remained a long-standing challenge. To solve this problem, we propose a minimal auxiliary space (MAS) mapping scheme with which the stochastic Grassmann fields are represented by conventional c-number fields along with a set of pseudo-levels. This eventually leads to a numerically feasible MAS-SEOM method. The important properties of the MAS-SEOM are analyzed by making connection to the well-established time-dependent perturbation theory and the hierarchical equations of motion theory. The MAS-SEOM method provides a potentially promising approach for the accurate and efficient simulation of fermionic open systems at ultra-low temperatures.

Treating Genetic Disorders Using State-Of-The-Art Technology.

CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated Protein 9), basically a bacterial immune system is now widely applicable to engineer genomes of a number of cells and organisms because of its simplicity and robustness. In research avenue the system has been optimized to regulate gene expression, modify epigenome and edit target locus. These applications make CRISPR/Cas9, a technology of choice to edit disease causing mutations as well as the epigenome more efficiently than ever before. Meanwhile its application in in vivo and ex vivo cells is encouraging the scientific community for more vigorous gene therapy and in clinical setups for therapeutic genome editing. Here we review the recent advances that CRISPR-Cas9 mediated genome editing has achieved and is reported in previous studies and address the challenges associated with it.

Improving CRISPR-Cas9 On-Target Specificity.

The CRISPR-Cas9 has revolutionized the field of molecular biology, medical genetics and medicine. The technology is robust, facile and simple to achieve genome targeting in cells and organisms. However, to propagate these nucleases for therapeutic application, the on-target specificity is of paramount importance. Although the binding and cleavage of off-target sites by Cas9 is issue of concern, however the specificity of CRISPR technology is greatly improved in current research employing the use of engineer nucleases, improved gRNA selection, novel Cas9 orhtologs and the advancement in methods to detect and screen off-target sites and its effects. Here we summarize the advances in this state-of-the-art technology that will equip the genome editing tools to be applied in clinical research. The researcher should optimize these methods with emphasize to achieve perfection in the specificity.

Advanced biomechanical analytics: Wearable technologies for precision health monitoring in sports performance.

Objective: This study investigated the impact of wearable technologies, particularly advanced biomechanical analytics and machine learning, on sports performance monitoring and intervention strategies within the realm of physiotherapy. The primary aims were to evaluate key performance metrics, individual athlete variations and the efficacy of machine learning-driven adaptive interventions. Methods: The research employed an observational cross-sectional design, focusing on the collection and analysis of real-world biomechanical data from athletes engaged in sports physiotherapy. A representative sample of athletes from Bahawalpur participated, utilizing Dring Stadium as the primary data collection venue. Wearable devices, including inertial sensors (MPU6050, MPU9250), electromyography (EMG) sensors (MyoWare Muscle Sensor), pressure sensors (FlexiForce sensor) and haptic feedback sensors, were strategically chosen for their ability to capture diverse biomechanical parameters. Results: Key performance metrics, such as heart rate (mean: 76.5 bpm, SD: 3.2, min: 72, max: 80), joint angles (mean: 112.3 degrees, SD: 6.8, min: 105, max: 120), muscle activation (mean: 43.2%, SD: 4.5, min: 38, max: 48) and stress and strain features (mean: [112.3 ], SD: [6.5 ]), were analyzed and presented in summary tables. Individual athlete analyses highlighted variations in performance metrics, emphasizing the need for personalized monitoring and intervention strategies. The impact of wearable technologies on athletic performance was quantified through a comparison of metrics recorded with and without sensors. Results consistently demonstrated improvements in monitored parameters, affirming the significance of wearable technologies. Conclusions: The study suggests that wearable technologies, when combined with advanced biomechanical analytics and machine learning, can enhance athletic performance in sports physiotherapy. Real-time monitoring allows for precise intervention adjustments, demonstrating the potential of machine learning-driven adaptive interventions.

Isolation, characterization, and cloning of thermostable pullulanase from Geobacillus stearothermophilus ADM-11.

This study aimed to identify thermo-stable pullulanase-producing bacteria in soil samples of potato fields and food-producing companies. Pullulan agar medium was used to screen 17 bacterial strains, which were incubated at 65 °C. The isolate with the maximum activity (375U/ml) was selected and recognized as Geobacillus stearothermophilus ADM-11 by morphological, biochemical characterization, and 16S rRNA gene sequencing. The pullulanase production required optimum pH of 7 and temperature of 75 °C, respectively. The electrophoresis of purified pullulanase on SDS-polyacrylamide gel revealed 83 kDa of a molecular weight that is active at 70 °C and pH 7.0. It was also stable at 90 °C but its activity was decreased by 10 % at 100 °C. The action of pullulanase was increased and stabilized by Ca+2 among the metal ions. Beta and gamma-cyclodextrins inhibited enzyme activity while ethylenediaminetetraacetate (EDTA) and phenylmethylsulfonyl fluoride (PMSF) have no significant effect on pullulanase activity. A full-length pullulanase gene was amplified from G. stearothermophilus ADM-11 using genomic DNA 2.1 kb of PCR product which was then purified and ligated in the cloning vector pTZ57R using the TA cloning technique. Colony PCR confirmed cloning on the positive clones after the pullulanase gene had been ligated and subjected to restriction digestion. It revealed 74 % similarity with the reported pullulanase gene from Geobacillus sp. 44C. The thermostability of pullulanase and its ability to degrade raw pullulan may therefore have wide-scale applications in starch processing, the detergent business, and new biotechnological applications.

Neuroprotective potential of Mentha piperita extract prevents motor dysfunctions in mouse model of Parkinson's disease through anti-oxidant capacities.

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Neurodegeneration of the substantia nigra (SN) and diminished release of dopamine are prominent causes of this progressive disease. The current study aims to evaluate the protective potential of ethanolic extract of Mentha piperita (EthMP) against rotenone-mediated PD features, dopaminergic neuronal degeneration, oxidative stress and neuronal survival in a mouse model. Swiss albino male mice were assigned to five groups: control (2.5% DMSO vehicle), PD (rotenone 2.5 mg/kg), EthMP and rotenone (200mg/kg and 2.5mg/kg, respectively), EthMP (200 mg/kg), and Sinemet, reference treatment containing levodopa and carbidopa (20 mg/kg and rotenone 2.5mg/kg). Behavioral tests for motor functional deficit analysis were performed. Anti-oxidant capacity was estimated using standard antioxidant markers. Histopathology of the mid-brain for neurodegeneration estimation was performed. HPLC based dopamine level analysis and modulation of gene expression using quantitative real-time polymerase chain reaction was performed for the selected genes. EthMP administration significantly prevented the rotenone-mediated motor dysfunctions compared to PD group as assessed through open field, beam walk, pole climb down, stepping, tail suspension, and stride length tests. EthMP administration modulated the lipid peroxidation (LPO), reduced glutathione (GSH), and superoxide dismutase (SOD) levels, as well as glutathione-s-transferase (GST) and catalase (CAT) activities in mouse brain. EthMP extract prevented neurodegeneration in the SN of mice and partially maintained dopamine levels. The expression of genes related to dopamine, anti-oxidant potential and synapses were modulated in M. piperita (MP) extract treated mice brains. Current data suggest therapeutic capacities of MP extract and neuroprotective capacities, possibly through antioxidant capacities. Therefore, it may have potential clinical applications for PD management.

Molecular identification and genotyping of hepatitis E virus from Southern Punjab, Pakistan.

Hepatitis E is a global health concern. Hepatitis E virus (HEV) infection is endemic in Pakistan. HEV has four genotypes: HEV-1 through HEV-4. The genotypes HEV-1 and HEV-2 are associated with infection in humans, especially in countries with poor sanitation. The genotypes HEV-3 and HEV-4 are zoonotic and human infection takes place by consuming undercooked meat or being in contact with animals. The present study was designed to ascertain the presence of HEV in the Southern Punjab region of Pakistan. First, blood samples (n = 50) were collected from patients suspected of infection with the hepatitis E virus from the Multan District. The serum was separated and the samples were initially screened using an HEV IgM-ELISA. Second, the ELISA-positive samples were subjected to PCR and were genetically characterized. For PCR, the RNA extraction and complementary DNA synthesis were done using commercial kits. The HEV ORF2 (Open Reading Frame-2, capsid protein) was amplified using nested PCR targeting a 348 bp segment. The PCR amplicons were sequenced and an evolutionary tree was constructed using MEGA X software. A protein model was built employing the SWISS Model after protein translation using ExPASy online tool. The positivity rate of anti-HEV antibodies in serum samples was found as 56% (28/50). All Pakistani HEV showed homology with genotype 1 and shared common evolutionary origin and ancestry with HEV isolates of genotype 1 of London (MH504163), France (MN401238), and Japan (LC314158). Sequence analysis of motif regions assessment and protein structure revealed that the sequences had a similarity with the reference sequence. These data suggest that genotype 1 of HEV is circulating in Pakistan. This finding could be used for the diagnosis and control of HEV in the specific geographic region focusing on its prevalent genotype.

Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra.

Time-resolved spectroscopy is an important tool for unraveling the minute details of structural changes in molecules of biological and technological significance. The nonlinear femtosecond signals detected for such systems must be interpreted, but it is a challenging task for which theoretical simulations are often indispensable. Accurate simulations of transient absorption or two-dimensional electronic spectra are, however, computationally very expensive, prohibiting the wider adoption of existing first-principles methods. Here, we report an artificial-intelligence-enhanced protocol to drastically reduce the computational cost of simulating nonlinear time-resolved electronic spectra, which makes such simulations affordable for polyatomic molecules of increasing size. The protocol is based on the doorway-window approach for the on-the-fly surface-hopping simulations. We show its applicability for the prototypical molecule of pyrazine for which it produces spectra with high precision with respect to ab initio reference while cutting the computational cost by at least 95% compared to pure first-principles simulations.

A Novel Approach of Polyvinyl Alcohol/Acrylic Acid Based Hydrogels for Controlled Delivery of Diclofenac Sodium.

AIM AND OBJECTIVE: The aim of this study was to prepare polyvinyl alcohol/acrylic acid (PVA/AA) hydrogels for the controlled release of diclofenac sodium and to develop PVA/AA hydrogels as controlled release carriers to overcome not only the side effects of diclofenac sodium but also sustain its release for an extended period. BACKGROUND: Diclofenac sodium is employed for relieving pain and fever. The half-life of diclofenac sodium is very short (1-2 h). Hence, multiple intakes of diclofenac sodium are required to maintain a constant pharmacological action. Multiple GI adverse effects are produced as a result of diclofenac sodium intake. METHOD: A free radical polymerization technique was used for crosslinking PVA with AA in the presence of APS. EGDMA was used as a cross-linker. FTIR and XRD confirmed the preparation and loading of the drug by prepared hydrogels. An increase in the thermal stability of PVA was shown by TGA and DSC analysis. Surface morphology was investigated by SEM. Similarly, water penetration and drug loading were demonstrated by porosity and drug loading studies. The pH-sensitive nature of PVA/AA hydrogels was investigated at different pH values by swelling and drug release studies. RESULTS: The development and drug loading of PVA/AA hydrogels were confirmed by FTIR and XRD analysis. TGA and DSC indicated high thermal stability of prepared hydrogels as compared to unreacted PVA. SEM indicated a hard and compact network of developed hydrogels. The swelling and drug release studies indicated maximum swelling and drug release at high pH as compared to low pH values, indicating the pH-sensitive nature of prepared hydrogels. Moreover, we demonstrated that drug release was sustained for a prolonged time in a controlled pattern by prepared hydrogels by comparing the drug release of the developed hydrogels with the commercial product Cataflam. CONCLUSION: The results indicated that prepared PVA/AA hydrogels can be used as an alternative approach for the controlled delivery of diclofenac sodium.

Formulation and In Vitro Assessment of Polymeric pH-Responsive Nanogels of Chitosan for Sustained Delivery of Madecassoside.

Madecassoside, a triterpenoid saponin compound mainly isolated from the gotu kola herb (Centella asiatica), shows an extensive range of biological activities, including antiapoptotic, antioxidant, anti-inflammatory, moisturizing, neuroprotective, and wound healing effects. It has been highly used in the management of eczema, skin wounds, and other diseases. Due to poor oral bioavailability, membrane permeability, and intestinal absorption, the clinical application of the madecassoside is limited. Hence, a drug carrier system is needed that not only sustains the release of the madecassoside but also overcomes the drawbacks associated with its administration. Therefore, the authors prepared novel pH-responsive chitosan-based nanogels for the sustained release of madecassoside. Free radical polymerization technique was used for cross-linking of polymer chitosan and monomer methacrylic acid in the presence of cross-linker N',N'-methylene bis(acrylamide). The decrease in polymer crystallinity after polymerization and development of nanogels was demonstrated by XRD and FTIR analysis. The effects of nanogel contents on polymer volume, sol-gel analysis, swelling, drug loading, and release were investigated. Results indicated that high swelling and maximum release of the drug occurred at pH 7.4 compared to pH 1.2 and 4.6, indicating the excellent pH-sensitive nature of the engineered nanogels. High swelling and drug release were perceived with the integration of a high quantity of chitosan, while a decline was observed with the high integration of N',N'-methylene bis(acrylamide) and methacrylic acid contents. The same effects of nanogel contents were shown for drug loading too. Sol fraction was reduced, while gel fraction was enhanced by increasing the chitosan load, N',N'-methylene bis(acrylamide), and methacrylic acid. The Korsmeyer-Peppas model of kinetics was trailed by all nanogel formulations with non-Fickian diffusion. The results demonstrated that prepared nanogels can be employed for sustained release of the madecassoside.

A band gap and photoluminescence properties engineering in BaO semiconductor for ultraviolet (UV) photodetector applications: A comprehensive role of co-doping.

We report on ultra-violet (UV) photodetectors based on BaO nanoparticles by the detailed investigation of band gap and photoluminescence properties. The BaO nanomaterials were fabricated by the modified sol-gel technique. The innovation of co-doping can modulate the photoluminescence or sensing properties by narrowing the band gap related to enhancing the high carrier concentration, higher electronic lifetime, and low carriers recombination. It is investigated that the BaO nanoparticles with co-doping reveals a highly reduced band gap and exceptional photoluminescence properties as compared to the pristine BaO nanoparticles due to hindering carrier,s recombination for Ultra-violet (UV) photodetectors. The optical studies revealed that the addition of co-dopants in BaO host material creates new energy sites, so the band gap declines up to 1.31 eV as compared to that of pristine BaO (1.36 eV). The photoluminescence properties recorded with photoluminescence (PL) spectroscopy were recorded which revealed the decrease in PL intensity due to the hindering of carriers recombination with the addition of co-dopant metal ions. Furthermore, the inclusion of co-dopant metals results in an improvement in electrical conductivity because of a decline in carrier recombination, according to an I-V characteristic study. This factor contributes to enhance the photoluminescence properties of BaO which, in turn, contributes to enhance the sensing capability of the photodetector device. These obtained features modify optoelectronic properties are far superior as compared to that of previously reported literature on BaO nanomaterials, and the synthesized BaO semiconductor material becomes a potential candidate for efficient use in the ultraviolet (UV) photodetectors device applications.

MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows.

Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framework for designing custom workflows. MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows. This open-source package provides plenty of choice to the users who can run simulations with the command-line options, input files, or with scripts using MLatom as a Python package, both on their computers and on the online XACS cloud computing service at XACScloud.com. Computational chemists can calculate energies and thermochemical properties, optimize geometries, run molecular and quantum dynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, and two-photon absorption spectra with ML, quantum mechanical, and combined models. The users can choose from an extensive library of methods containing pretrained ML models and quantum mechanical approximations such as AIQM1 approaching coupled-cluster accuracy. The developers can build their own models using various ML algorithms. The great flexibility of MLatom is largely due to the extensive use of the interfaces to many state-of-the-art software packages and libraries.