First Report of Fruit Rot Caused by Diaporthe amygdali on Papaya in Punjab, Pakistan.

Papaya (Carica papaya L.) is grown widely in tropical and sub-tropical regions (Ahmed et al. 2008). In Pakistan, papaya production and consumption are increasing due to its medicinal, nutritional, pharmacological properties and a rich source of antioxidant, vitamin B, potassium, and magnesium. In November 2021, 26 to 35% incidence of fruit rot was observed in 15 fields of Lahore, a district of Punjab, Pakistan. Affected fruit developed circular, gray-to-brown lesions (8 to 10 mm in diameter) with white mycelia forming on the surface of lesions. In advanced stages of the disease, the lesions enlarged in size and led to the rot of entire fruit. To isolate the causal agent, small tissue segments (1 to 2 cm) were excised from 15 symptomatic fruit, surface disinfected with 1% NaClO for 30 s, rinsed with sterile distilled water three times, air dried in laminar flow hood, aseptically transferred onto petri dishes containing potato dextrose agar (PDA) and incubated at 25℃ for 5 days with a 12-h photoperiod. Eleven isolates were obtained that produced white mycelia on PDA. Flask-shaped, dark-pigmented pycnidia formed on PDA after 18 days of incubation at 25°C, which produced α-conidia measuring 4.1 to 7.2 × 1.5 to 3.0 µm and ß-conidia measuring 16.4 to 25.5 × 1.0 to 1.6 µm (n = 40). α-conidia were hyaline, fusiform, and single-celled, whereas ß-conidia were one-celled, hyaline, and filiform. The morphological characteristics of the fungus were compatible with a Diaporthe species (Gomes et al. 2013). The internal transcribed spacer region (ITS) (OM865414 and OM865415), translation elongation factor 1-alpha (tef1) (OM831226 and OM831229), and histone H3 (HIS) (OM831227 and OM831228) of two representative isolates (UO02 and UO03) were amplified and sequenced using primers ITS1/ITS4 (White et al. 1990), EF1-728F/EF1-986R (Carbone and Kohn 1999), and CYLH3F/H3-1b (Chaisiri et al. 2021), respectively. Blast searches showed 99 to 100% nucleotide identity with reference sequences of several Diaporthe amygdali deposited in NCBI GenBank, including the ex-type strain CBS 126679. A pathogenicity test was also performed on harvested fruit of papaya cv. Bombay using isolates UO02 and UO03. Ten mature and healthy papaya fruit were surface disinfected with 1% NaClO solution for 1 min, rinsed with sterile water and dried. Each fruit was wounded twice with a sterile scalpel (4 to 5 mm incision on the peel) and a 5-mm agar disc with mycelia of each isolate was separately placed in each wound. The wounds were wrapped with Parafilm following inoculation. Sterile PDA plugs were used in separate inoculated controls. All wounds were sealed with parafilm. All fruit were maintained in plastic boxes at 25°C with 80% relative humidity. After 6 days of incubation, rot symptoms similar to those appearing on naturally-infected fruit were observed on inoculated fruits while controls remained asymptomatic. The experiment was repeated twice with similar findings. Diaporthe amygdali was re-isolated (100%) from inoculated fruit and the pathogen identification was confirmed by morphological and molecular analysis, thus fulfilling Koch's postulates. Previously, the pathogen has been reported as a causal agent of canker and shoot blight disease in other countries (Ko and Sun, 2003; Beluzan et al. 2021). To our knowledge, this is the first report of D. amygdali on papaya in Punjab Province of Pakistan. Papaya is an emerging fruit crop in Punjab Province and it is important to further investigate the presence of this pathogen in other papaya orchards of the province since D. amygdali may cause rapid disease outbreaks resulting in severe losses.

Green Synthesis of NiO-SnO2 Nanocomposite and Effect of Calcination Temperature on Its Physicochemical Properties: Impact on the Photocatalytic Degradation of Methyl Orange.

Background: Nickel stannate nanocomposites could be useful for removing organic and toxic water pollutants, such as methyl orange (MO). Aim: The synthesis of a nickel oxide-tin oxide nanocomposite (NiO-SnO2 NC) via a facile and economically viable approach using a leaf extract from Ficus elastica for the photocatalytic degradation of MO. Methods: The phase composition, crystallinity, and purity were examined by X-ray diffraction (XRD). The particles' morphology was studied using scanning electron microscopy (SEM). The elemental analysis and colored mapping were carried out via energy dispersive X-ray (EDX). The functional groups were identified by Fourier transform infrared spectroscopy (FTIR). UV-visible diffuse reflectance spectroscopy (UV-vis DRS) was used to study the optical properties such as the absorption edges and energy band gap, an important feature of semiconductors to determine photocatalytic applications. The photocatalytic activity of the NiO-SnO2 NC was evaluated by monitoring the degradation of MO in aqueous solution under irradiation with full light spectrum. The effects of calcination temperature, pH, initial MO concentration, and catalyst dose were all assessed to understand and optimize the physicochemical and photocatalytic properties of NiO-SnO2 NC. Results: NiO-SnO2 NC was successfully synthesized via a biological route using F. elastica leaf extract. XRD showed rhombohedral NiO and tetragonal SnO2 nanostructures and the amorphous nature of NiO-SnO2 NC. Its degree of crystallinity, crystallite size, and stability increased with increased calcination temperature. SEM depicted significant morphological changes with elevating calcination temperatures, which are attributed to the phase conversion from amorphous to crystalline. The elemental analysis and colored mapping show the formation of highly pure NiO-SnO2 NC. FTIR revealed a decrease in OH, and the ratio of oxygen vacancies at the surface of the NC can be explained by a loss of its hydrophilicity at increased temperatures. All the NC samples displayed significant absorption in the visible region, and a blue shift is seen and the energy band gap decreases when increasing the calcination temperatures due to the dehydration and formation of compacted large particles. NiO-SnO2 NC degrades MO, and the photocatalytic performance decreased with increasing calcination temperature due to an increase in the crystallite size of the NC. The optimal conditions for the efficient NC-mediated photocatalysis of MO are 100 °C, 20 mg catalyst, 50 ppm MO, and pH 6. Conclusions: The auspicious performance of the NiO-SnO2 NCs may open a new avenue for the development of semiconducting p-n heterojunction catalysts as promising structures for removing undesirable organic pollutants from the environment.

Room temperature monitoring of SF6decomposition byproduct SO2F2based on TiO2/NiSO4composite nanofibers.

Sulfuryl fluoride (SO2F2) is one of the ideal decomposition components of sulfur hexafluoride (SF6), which is widely used as an insulating and arc extinguishing medium in gas-insulated switchgear. To detect the decomposition component of SF6at room temperature, the use of SO2F2is still a challenge. In this work, we have successfully fabricated TiO2nanofibers and nickel sulfate (NiSO4NPs) via simple electrospun and hydrothermal methods, followed by calcination process to improve the sensing performance. Metal oxide semiconductor materials (MOSs) are widely used in gas sensing applications due to their superior performance and fast recovery speed. Although the performance of our TiO2/NiSO4composite nanofiber sensor decreases at higher temperatures, it shows an excellent response to target gasses at room temperature. Ni-decoration on the outer surface of the nanofibers could maximize the sensing response of 100 ppm SO2F2by up to 189% at room temperature, showing that the TiO2/NiSO4composite nanofibers are 2.5 times superior to the pure TiO2nanofiber sensors. Thus, the approach for this novel composite nanofiber-based material is promising for the fabrication of superior gas sensors for decomposition of SF6.

Design of highly sensitive and selective ethanol sensor based on α-Fe2O3/Nb2O5 heterostructure.

The introduction of heterostructures is a new approach in gas sensing due to their easy and quick transport of charges. Herein, facile hydrothermal and solid-state techniques are employed to synthesize an α-Fe2O3/Nb2O5 heterostructure. The morphology, microstructure, crystallinity and surface composition of the synthesized heterostructures are investigated by scanning electron microscope, transmission electron microscope, x-ray diffraction, x-ray photoelectron spectroscopy and Brunauer-Emmett-Teller analyses. The successful fabrication of the heterostructures was achieved via the mutual incorporation of α-Fe2O3 nanorods with Nb2O5 interconnected nanoparticles (INPs). A sensor based on the α-Fe2O3(0.09)/Nb2O5 heterostructure with a high surface area exhibited enhanced gas-sensing features, maintaining high selectivity and sensitivity, and a considerable recovery percentage towards ethanol gas. The sensing response of the α-Fe2O3(0.09)/Nb2O5 heterostructure at lower operating temperature (160 °C) is around nine times higher than a pure Nb2O5 (INP) sensor at 180 °C with the flow of 100 ppm ethanol gas. The sensors also show excellent selectivity, good long-term stability and a rapid response/recovery time (8s/2s, respectively) to ethanol. The superior electronic conductivity and upgraded sensitivity performance of gas sensors based on the α-Fe2O3(0.09)/Nb2O5 heterostructure are attributed due to its unique structural features, high specific surface area and the synergic effect of the n-n heterojunction. The promising results demonstrate the potential application of the α-Fe2O3(0.09)/Nb2O5 heterostructure as a good sensing material for the fabrication of ethanol sensors.

Development of broad-spectrum and sustainable resistance in cotton against major insects through the combination of Bt and plant lectin genes.

KEY MESSAGE: Second generation Bt insecticidal toxin in comibination with Allium sativum leaf agglutinin gene has been successfully expressed in cotton to develop sustainable resistance against major chewing and sucking insects. The first evidence of using the Second-generation Bt gene in combination with Allium sativum plant lectin to develop sustainable resistance against chewing and sucking insects has been successfully addressed in the current study. Excessive use of Bt δ-endotoxins in the field is delimiting its insecticidal potential. Second-generation Bt Vip3Aa could be the possible alternative because it does not share midgut receptor sites with any known cry proteins. Insecticidal potential of plant lectins against whitefly remains to be evaluated. In this study, codon-optimized synthetic Bt Vip3Aa gene under CaMV35S promoter and Allium sativum leaf agglutinin gene under phloem-specific promoter were transformed in a local cotton variety. Initial screening of putative transgenic cotton plants was done through amplification, histochemical staining and immunostrip assay. The mRNA expression of Vip3Aa gene was increased to be ninefold in transgenic cotton line L6P3 than non-transgenic control while ASAL expression was found to be fivefold higher in transgenic line L34P2 as compared to non-transgenic control. The maximum Vip3Aa concentration was observed in transgenic line L6P3. Two copy numbers in homozygous form at chromosome number 9 and one copy number in hemizygous form at chromosome number 10 was observed in transgenic line L6P3 through fluorescent in situ hybridization. Significant variation was observed in transgenic cotton lines for morphological characteristics, whereas physiological parameters of plants and fiber characteristics (as assessed by scanning electron microscopic) remained comparable in transgenic and non-transgenic cotton lines. Leaf-detach bioassay showed that all the transgenic lines were significantly resistant to Helicoverpa armigera showing mortality rates between 78% and 100%. Similarly, up to 95% mortality of whiteflies was observed in transgenic cotton lines when compared with non-transgenic control lines.

DeepACTION: A deep learning-based method for predicting novel drug-target interactions.

Drug-target interactions (DTIs) play a key role in drug development and discovery processes. Wet lab prediction of DTIs is time-consuming, expensive, and tedious. Fortunately, computational approaches can identify new interactions (drug-target pairs) and accelerate the process of drug repurposing. However, a vast number of interactions remain undiscovered; therefore, we proposed a deep learning-based method (deepACTION) for predicting potential or unknown DTIs. Here, each drug chemical structure and protein sequence are transformed according to structural and sequence information using different descriptors to represent their features correctly. There have been some challenges, such as the high dimensionality and class imbalance of data during the prediction process. To address these problems, we developed the MMIB technique to balance the majority and minority instances in the dataset and utilized a LASSO model to handle the high dimensionality of the data. In addition, we trained the convolutional neural network algorithm with balanced and reduced features for accurate prediction of DTIs. In this study, the AUC is considered a primary evaluation metric for comparing the performance of the deep ACTION model with that of existing methods by a 5-fold cross-validation test. Our experiential dataset obtained from the DrugBank database and our deepACTION model achieved an AUC of 0.9836 for this dataset. The experimental results ensured that the model can predict significant numbers of new DTIs and provide complete information to motivate scientists to develop drugs.

Development of high-performance sensor based on NiO/SnO2 heterostructures to study sensing properties towards various reducing gases.

In this work, we report the spontaneous formation of NiO nanoparticles-decorated onto smooth SnO2 nanofibers, which is an inexpensive and scalable method for yielding a high composite surface area via a simple two-step synthesis process based on electrospinning and the hydrothermal method. A Nickel Oxide proton-conducting electrolyte is deposited homogeneously over a large surface area in a transparent solution, mixed and decorated onto Tin dioxide nanofibers, as evidenced by cross sectional imaging of the electrospun nanofibers. The composite based on nanoparticle-decorated fibers enlarges the surface area of the exposed electrolyte, which fundamentally improves the overall gas sensing performance. The crystal structure, morphology, and physio-chemical surface state of the NiO/SnO2-based specimen are comprehensively examined using XRD, SEM, TEM, HRTEM, EDX, and photoelectron (XPS) spectroscopy. The composite based on NiO/SnO2 nanoparticle-decorated fibers exhibits an optimistic mesoporous nature with a huge specific area, which is key for superior gas sensors. The result reveals that NiO/SnO2 nanoparticle-decorated fibers with an average size of 180-260 nm in diameter, where the average length of fibers was about 1.5 µm. The composite-based heterojunction of NiO/SnO2 nanoparticle-decorated fibers enhances the adsorption of oxygen molecules, which show fast response, good selectivity and quick recovery speed against ethanol gas at an optimal temperature of about 160 °C. The maximum sensitivity response of the sensor-based composite NiO/SnO2 nanoparticle-decorated fibers was 23.87 in respect of 100 ppm ethanol gas at a low temperature of 160 °C; this is approximately about 7.2 times superior to that of pure SnO2 nanofibers. The superior gas sensing capabilities of a composite based on NiO/SnO2 nanoparticle-decorated fibers may be attributable to the enhanced catalytic effect of the small sized NiO nanoparticles on smooth SnO2 nanofibers, together with the p/n heterojunction effects between NiO and SnO2 heterostructures.

Effect of calcination temperature induced structural modifications on the photocatalytic efficacy of Fe2O3-ZrO2 nanostructures: mechanochemical synthesis.

Water contamination due to organic pollutants is a challenging issue around the globe, and several attempts have been made to deal with this issue. Out of which, the semiconductor-based photocatalytic process had gained much attention and proved to be an efficient, easy, and economical process for the removal of organic dyes from aqueous solutions. For this purpose, the iron oxide-zirconium dioxide nanocomposite (Fe2O3-ZrO2 NC) was prepared via a simple mechanochemical process using a mortar and pestle, followed by a calcination process at 300, 600, and 900 °C. Different physicochemical analyses were carried out in order to investigate the successful synthesis of Fe2O3-ZrO2 NC and the effect of temperature on the crystallinity, surface area, pore size, phase composition, sample morphology, and particle/crystallite size. The Fe2O3-ZrO2 NCs were subjected to a photocatalytic test under solar light irradiation against fluorescein dye in an aqueous medium, and the photocatalytic performance was examined under the influence of calcination temperatures, pH, catalyst dose, and initial concentration. The stability of the Fe2O3-ZrO2 NCs was also checked by recycling them for five reuse cycles.

Oncomeric Profiles of microRNAs as New Therapeutic Targets for Treatment of Ewing's Sarcoma: A Composite Review.

Ewing's sarcoma is a rare type of cancer that forms in bones and soft tissues in the body, affecting mostly children and young adults. Current treatments for ES are limited to chemotherapy and/or radiation, followed by surgery. Recently, microRNAs have shown favourable results as latent diagnostic and prognostic biomarkers in various cancers. Furthermore, microRNAs have shown to be a good therapeutic agent due to their involvement in the dysregulation of various molecular pathways linked to tumour progression, invasion, angiogenesis, and metastasis. In this review, comprehensive data mining was employed to explore various microRNAs that might have therapeutic potential as target molecules in the treatment of ES.

Porous Hierarchical Ni/Mg/Al Layered Double Hydroxide for Adsorption of Methyl Orange from Aqueous Solution.

A basic urea technique was successfully used to synthesize Mg/Al-Layered double hydroxides (Mg/Al LDHs), which were then calcined at 400 °C to form Mg/Al-Layered double oxides (Mg/Al LDOs). To reconstruct LDHs, Mg/Al LDOs were fabricated with different feeding ratios of Ni by the co-precipitation method. After synthesis, the Ni/Mg/Al-layered double hydroxides (NMA-LDHs) with 20% and 30% Ni (S1 and S2) were roasted at 400 °C and transformed into corresponding Ni/Mg/Al-layered double oxides (NMA-LDOs) (S1a and S2b, respectively). The physiochemical properties of synthesized samples were also evaluated by various characterization techniques, such as X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray spectroscopy (EDS), Fourier transform infrared (FTIR), and Brunauer, Emmett, and Teller (BET). The adsorption behavior of methyl orange (MO) onto the synthesized samples was evaluated in batch adsorption mode under varying conditions of contact time, adsorbent quantity, and solution pH. As the dosage amount increased from 0.01-0.04 g, the removal percentage of MO dye also increased from 83% to 90% for S1, 84% to 92% for S1a, 77% to 87% for S2, and 93% to 98% for S2b, respectively. For all of the samples, the adsorption kinetics were well described by the pseudo-second-order kinetic model. The equilibrium adsorption data were well fitted to both Langmuir and Freundlich models for methyl orange (MO). Finally, three adsorption-desorption cycles show that NMA-LDHs and NMA-LDOs have greater adsorption and reusability performance for MO dye, signifying that the design and fabrication strategy can facilitate the application of the natural hydrotalcite material in water remediation.

Qualitative and Quantitative Investigation of Biochar-Cu0 Composite for Nickel Adsorption.

The current investigation deals with the treatment of water pollution that is caused by the leaching of nickel ions from the metallurgical industry and new-energy batteries. Therefore, an eco-friendly treatment of nickel through the use of a composite of cotton stalk biochar with nanozerovalent copper has been presented in this investigation signifying the impact of zerovalent copper in enhancing the adsorption capacity of biochar for nickel adsorption. Thermogravimetric analysis data showed the adsorbent to be significantly stable in the higher thermal range, whereas transmission electron microscopy analysis confirmed the particles to be 27 nm and also showed the cubic geometry of the particles. A much closer scanning electron microscopy analysis shows the morphology of particles to be cubic in shape. Batch adsorption indicated a positive influence of pH increase on adsorption due to the electrostatic attraction between positive nickel ions and post point of zero charge (pHPZC) negative surface of copper biochar composite (pH > 5.5). A high adsorption rate was observed in the first 60 min, whereas adsorption increased with the increase in temperature from 303 to 318 K. Kinetic modeling confirmed the pseudo-first-order to fit best to the data. The apparent activation energy (11.96 kJ mol-1) is indicative of the chemical nature of the process. The adsorption data fitted well to the Langmuir adsorption model. The negative values of apparent ΔG° and the positive values of apparent ΔH° indicate the spontaneity and endothermicity of the process, respectively, whereas the positive values of apparent ΔS° point toward increased randomness during the process. Postadsorption XPS suggests the adsorption of nickel on the surface of biochar composites in the form of Ni(OH)2 and NiO(OH).

In-field deployable and facile nanosensor for the detection of pesticides residues.

Local air and water should be first priority to understand the environment of any area. Different categories of contaminants behave like bottleneck situation in collection and analysis of data about abiotic factors for the understanding and resolving the environmental issues. In digital age the emerging nano technology enroll its role to meet the needs of hour. Due to increase in pesticides residues, the global health threats are on bloom because it inhibits the functionality of acetylcholinesterase (AChE) enzyme. Smart nanotechnology based system can tackle this issue and sense the pesticides residues in environment and vegetables as well. Here Au@ZnWO4 composite is reported, for accurate detection of pesticides residues in biological food and environmental samples. The fabricated unique nanocomposite was characterized by SEM, FTIR, XRD and EDX. The characterized material used for the electrochemical detection of organophosphate pesticide (chlorpyrifos), with 1 pM LoD at a signal to noise ratio of 3. The main concern of study is to help out in disease prevention, food safety and ecosystem protection.

Montmorillonite modified Ni/Mg/Al ternary layered double hydroxide nanoflowers with enhanced adsorption features.

A hydrothermal technique was employed to synthesize Ni/Mg/Al ternary L.D.H.s modified with montmorillonite (NMA-MMT-LDHs). Many characterization methods, including X-ray diffraction (XRD), scanning electron microscopy (S.E.M.), Fourier transform infrared (FTIR), and Brunauer, Emmett, and Teller (B.E.T.), were used to assess the physiochemical properties of the produced analytes. Congo red and methylene blue were utilized as model dyes to treat textile waste with the synthesized analytes. The batch adsorption model was utilized to conduct the adsorption experiments under varying contact time, adsorbent dosage, and solution pH conditions. A pseudo-second-order kinetics and the Langmuir adsorption model control the adsorption process. The maximum monolayer adsorption capacities of C.R. and M.B. were determined to be 344 and 200 mg/g, respectively. As the quantity of dosage increased from the 0.01-0.04 g, the percent removal efficiency (%) increased from 75 to 87 % for S2-LDH, 84-88 % for S2-MMT, 86-93 % for S3-MMT, and 95-97% for S4-MMT for C.R. dye and 82-85 % for S2-LDH, 83-89 % for S2-MMT, 83-91 % for S3-MMT, and 84-92 % for S4-MMT for M.B. dye. The removal percentage of C.R. dye for adsorbents S2-LDH, S2-MMT, S3-MMT, and S4-MMT were 75 %, 84 %, 86 %, and 95 %, respectively and 82 %, 83 %, 83 %, and 85 %, respectively for the M.B. dye removal. The presence of MMT significantly increases the affinity of Ni/Mg/Al-LDHs (NMA-LDHs), and the designed production technique can be used to produce a variety of compositionally distinct adsorbent materials.

An Online Semantic-Enhanced Graphical Model for Evolving Short Text Stream Clustering.

Due to the popularity of social media and online fora, such as Twitter, Reddit, Facebook, and Wechat, short text stream clustering has gained significant attention in recent years. However, most existing short text stream clustering approaches usually work on static data and tend to cause a "term ambiguity" problem due to the sparse word representation. Beyond, they often exploit short text streams in a batch way and are difficult to find evolving topics in term-changing subspaces. In this article, we propose an online semantic-enhanced graphical model for evolving short text stream clustering (OSGM), by exploiting the word-occurrence semantic information and dynamically maintaining evolving active topics in term-changing subspaces in an online way. Compared to the existing approaches, our online model is not only free of determining the optimal batch size but also lends itself to handling large-scale data streams efficiently. It is also able to handle the "term ambiguity" problem without incorporating features from external resources. More importantly, to the best of our knowledge, it is the first work to extract evolving topics in term-changing subspaces automatically in an online way. Extensive experiments demonstrate that the proposed model yields better performance compared to many state-of-the-art algorithms on both synthetic and real-world datasets.

Low-Temperature Detection of Sulfur-Hexafluoride Decomposition Products Using Octahedral Co3O4-Modified NiSnO3 Nanofibers.

Sulfur hexafluoride (SF6) is widely used in electrical equipment because of its excellent insulating properties. The type of internal fault in the power system can be identified by detecting SF6 decomposition products. In this manuscript, we report a novel sensing material based on octahedral Co3O4-modified NiSnO3 nanofibers synthesized via a two-step process based on electrospinning followed by a hydrothermal method for detecting the SF6 decomposition products. From the evaluation of various characterization techniques, it was determined that the Co3O4 octahedra adhered inflexibly to the surface of the NiSnO3 nanofibers, which consist of smaller particles and provide a huge surface area for the adsorption of an enormous amount of gas species. Planar-type chemical gas sensors were devised, and their gas detecting performance against SF6 decomposition products was systematically investigated. A comparison of the sensitivity properties of different amounts of charged Co3O4 octahedra in NiSnO3 nanofibers shows that the S-2-based Co3O4@NiSnO3 composite has a high selectivity for 100 ppm SO2F2 gas with a high sensing response of 22.5 at a relatively low temperature of 50 °C with a moderate response/recovery interval (∼200/∼268 s) and a low detection limit (5 ppm) over other interfering gases, such as SOF2, SO2, and H2S. Interestingly, the sensing properties of the fabricated sensors based on the Co3O4@NiSnO3 composites for the SO2F2 gas were improved in terms of lower operating temperatures, higher gas responses, and mild response/recovery intervals, which could be attributed to the unique microstructure effect, the catalytic influence of Co3O4 octahedra, and the creation of p/n junctions to increase the charge transfer and diffusion rate within the catalytic assembly of the sensor materials. This work highlights the importance of the heterostructure design in the construction of high-performance gas sensors for the real-time detection of SF6 decomposition products.

Learning High-Dimensional Evolving Data Streams With Limited Labels.

In the context of streaming data, learning algorithms often need to confront several unique challenges, such as concept drift, label scarcity, and high dimensionality. Several concept drift-aware data stream learning algorithms have been proposed to tackle these issues over the past decades. However, most existing algorithms utilize a supervised learning framework and require all true class labels to update their models. Unfortunately, in the streaming environment, requiring all labels is unfeasible and not realistic in many real-world applications. Therefore, learning data streams with minimal labels is a more practical scenario. Considering the problem of the curse of dimensionality and label scarcity, in this article, we present a new semisupervised learning technique for streaming data. To cure the curse of dimensionality, we employ a denoising autoencoder to transform the high-dimensional feature space into a reduced, compact, and more informative feature representation. Furthermore, we use a cluster-and-label technique to reduce the dependency on true class labels. We employ a synchronization-based dynamic clustering technique to summarize the streaming data into a set of dynamic microclusters that are further used for classification. In addition, we employ a disagreement-based learning method to cope with concept drift. Extensive experiments performed on many real-world datasets demonstrate the superior performance of the proposed method compared to several state-of-the-art methods.

Enhanced Thermal Stability and Synergistic Effects of Magnesium and Iron Borate Composites against Pathogenic Bacteria.

A simple process based on the dual roles of both magnesium oxide (MgO) and iron oxide (FeO) with boron (B) as precursors and catalysts has been developed for the synthesis of borate composites of magnesium and iron (Mg2B2O5-Fe3BO6) at 1200°C. The as-synthesized composites can be a single material with the improved and collective properties of both iron borates (Fe3BO6) and magnesium borates (Mg2B2O5). At higher temperatures, the synthesized Mg2B2O5-Fe3BO6 composite is found thermally more stable than the single borates of both magnesium and iron. Similarly, the synthesized composites are found to prevent the growth of both gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) pathogenic bacteria on all the tested concentrations. Moreover, the inhibitory effect of the synthesized composite increases with an increase in concentration and is more pronounced against S. aureus as compared to E. coli.

Epidemiological study of dengue fever in District Swabi, Khyber Pakhtunkhwa, Pakistan.

Dengue is a viral disease which is serious health concern from last few decades and the infection transmitted through mosquito bite into human. This study was conducted to carry out prevalence of dengue fever in District Swabi. A total of 196 blood sample were collected from patients with age ranges (0-80 years) having dengue fever on the basis of physical symptoms from Bacha Khan Medical Complex Swabi during August to October 2017. Serological test were performed for detection of IgM, IgG and NS1 (Non structural protein antigen of virus) against dengue. Out of total 196 confirmed dengue cases the most prone gender was male 123(62%) while 73(38%) were female. Among the age groups; 21-30 years group 62 (31.6%) was found the most predominated age group. The higly affected areas in district Swabi were Topi (40.8%) followed by Main Swabi (27%), Maneri (8.2%), Marghuz (6%), Shawa Ada (5.1%), Shah Mansoor (5.1%), Gohati (4.1%), and Chota Lahore (3.6%). Therefore, the health department should take actions by educating the public about basic cleanliness of the environment. The community should be encouraged to participate in the control of such vector based diseases/infections.

Deployment of metal-organic frameworks as robust materials for sustainable catalysis and remediation of pollutants in environmental settings.

From metal-organic chemistry, metal-organic frameworks (MOFs) are of supreme interest for catalysis and environmental settings. Owing to anthropogenic sources and booming industrial practices, the most challenging issue is increased water pollution and environmental insecurity. For instance, several types of synthetic dyes are toxic up to a certain extent, as emerging organic contaminants (EOCs) pose adverse environmental and potential health consequences. A gradual increase in the contamination sources and unpredictable environmental changes in terms of anthropogenic pollution severely affect both water availability and distribution. Therefore, the treatment of dyes containing wastewater matrices for water resource generation is one of the most important tasks, which must be addressed effectively. With structural tunability, MOFs have been appearing as a robust tool for remediating toxic pollutants from wastewater matrices. Moreover, the promising functionality, structural tunability, robust catalytic attributes, compatibility, large surface area, stability in water, and ease in surface functionalization make MOFs one of the considerable materials of interest. This review work spotlights the present-day progress related to MOFs and their catalytic and adsorptive chemistry for a sustainable environment. Following a brief introduction, the characteristic rendering MOFs, as adsorbents, are given with prominent examples. Next, several synthesis routes as a roadmap to engineer MOFs are discussed. From the applied perspective, the adsorptive and catalytic potentialities of MOFs as given by addressing sustainable mitigation of toxic dyes. The last section of the work illustrates key challenging issues and future directions by considering the suiting importance of MOFs.

Analysis of non-Newtonian magnetic Casson blood flow in an inclined stenosed artery using Caputo-Fabrizio fractional derivatives.

BACKGROUND AND OBJECTIVE: Arterial diseases would lead to several serious disorders in the cardiovascular system such as atherosclerosis. These disorders are mainly caused by the presence of fatty deposits, cholesterol and lipoproteins inside blood vessel. This paper deals with the analysis of non-Newtonian magnetic blood flow in an inclined stenosed artery. METHODS: The Casson fluid was used to model the blood that flows under the influences of uniformly distributed magnetic field and oscillating pressure gradient. The governing fractional differential equations were expressed using the Caputo Fabrizio fractional derivative without singular kernel. RESULTS: The analytical solutions of velocities for non-Newtonian model were then calculated by means of Laplace and finite Hankel transforms. These velocities were then presented graphically. The result shows that the velocity increases with respect to Reynolds number and Casson parameter, while decreases when Hartmann number increases. CONCLUSIONS: Casson blood was treated as the non-Newtonian fluid. The MHD blood flow was accelerated by pressure gradient. These findings are beneficial for studying atherosclerosis therapy, the diagnosis and therapeutic treatment of some medical problems.