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Rhizobacteria play a crucial role in plant health by providing natural antagonism against soil-borne fungi. The use of rhizobacteria has been viewed as an alternative to the use of chemicals that could be useful for the integrated management of plant diseases and also increase yield in an environmentally friendly manner. However, there is limited understanding of the specific mechanisms by which rhizobacteria inhibit these pathogens and the diversity of rhizobacterial species involved. This study aims to isolate, identify, and characterize rhizobacteria with antagonistic activities against soil-borne fungi. Laboratory tests were carried out on isolated rhizobacteria to evaluate their inhibitory activity against Rhizoctonia solani, Pythium aphanidermatum and Macrophomina phaseolina. The selected bacteria were identified using the Vitek 2 compact system and 16S rRNA genes. Experiments were carried out to evaluate the plant growth promotion and biocontrol ability of these selected isolates. Out of 324 rhizobacteria isolates obtained from various plant species, twelve were chosen due to their strong (>50 %) wide-ranging antifungal activity against three significant phytopathogenic fungi species. According to the identification results, they belong to the following species: Aeribacillus pallidus ECC4, Alloiococcus otitis BRE6, Aneurinibacillus thermoaerophilus ECL1, A. thermoaerophilus SDV1, Bacillus halotolerans DMC8, B. megaterium SKE2, B. megaterium TNK1, B. subtilis NAS1, Enterobacter cloacae complex BZD3, Leclercia adecarboxylata DKS3, Paenibacillus polymyxa TRS4, and Staphylococcus lentus BZD2. Eleven isolates produced protease, six isolates produced chitinase, and seven isolates were highly effective in producing hydrogen cyanide. Ten isolates could fix nitrogen, while all isolates could produce potassium, indole-3-acetic acid, siderophore, and ammonia. These findings enhance our understanding of rhizobacterial biodiversity and their potential as biocontrol agents in sustainable agriculture.

Photoacoustic imaging is a good method for biological imaging, for this purpose, materials with strong near infrared (NIR) absorbance are required. In the present study, machine learning models are used to predict the light absorption behavior of polymers. Molecular descriptors are utilized to train a variety of machine learning models. Building blocks are searched from chemical databases, as well as new building blocks are designed using chemical library enumeration method. The Breaking Retrosynthetically Interesting Chemical Substructures (BRICS) method is employed for the creation of 10,000 novel polymers. These polymers are designed based on the input of searched and selected building blocks. To enhance the process, the optimal machine learning model is utilized to predict the UV/visible absorption maxima of the newly designed polymers. Concurrently, chemical similarity analysis is also performed on the selected polymers, and synthetic accessibility of selected polymers is calculated. In summary, the polymers are all easy to synthesize, increasing their potential for practical applications.

As a soft material with biocompatibility and stimulation response, ionic conductive hydrogel‐based wearable strain sensors show great potential across a wide spectrum of engineering disciplines, but their mechanical toughness is limited in practical applications. In this study, freeze‐thawing techniques were utilized to fabricate double‐network hydrogels of poly(vinyl alcohol)/polyacrylamide (PVA/PAM) with both covalent and physical cross‐linking networks. These double‐network hydrogels demonstrate excellent mechanical performance, with an elongation at break of 2253% and tensile strength of 268.2 kPa. Simultaneously, they also display a high sensitivity (Gage factor, GF = 2.32 at 0%–200% strain), achieve a rapid response time of 368 ms without the addition of extra conductive fillers or ions, stable signal transmission even after multiple cycles, and fast response to human motion detection. [ABSTRACT FROM AUTHOR]

The lanthanum doped cobalt ferrite (La+3-CoFe2O4) incorporated in MXene sheets bifunctional electrocatalyst was prepared and then subjected to various analyses to assess their structural, morphological, and functional group characteristics. X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) were employed for this purpose. The electrochemical performance of La-CoFe2O4@MXene was investigated in an alkaline solution to assess the bifunctional (OER/HER) performances. The results revealed that La-CoFe2O4@MXene exhibited significantly lower overpotential and a lesser Tafel slope during OER compared to both CoFe2O4 and La-CoFe2O4 materials. Similarly, during HER, La-CoFe2O4@MXene demonstrated superior performance. The electrochemical impedance (EIS) analysis was also conducted on all samples. These results indicated that the La-CoFe2O4@MXene electrocatalyst displayed reduced charge transfer resistance (2.18 Ω) and a higher exchange current density (2.94 mA cm−2) compared to its counterparts. These results collectively demonstrate the exceptional electrocatalytic behavior of La-CoFe2O4@MXene. This enhanced performance is likely attributable to the synergistic effect of lanthanum doping, which introduces defects into the material, and the presence of MXene sheets, which facilitates faster charge transfer within the electrocatalyst. To the best of our knowledge, this is the first study to explore La-CoFe₂O₄@MXene for water splitting. Our results demonstrate that this material requires significantly lower overpotential for OER and HER in an alkaline medium, showcasing its potential as an efficient and cost-effective catalyst for water splitting. Highlights: MXene-based La+3-doped-CoFe2O4 electrocatalyst has been prepared for bifunctional electrocatalytic activity. The coprecipitation and ultrasonication methods were adopted for the synthesis of bifunctional electrocatalysts, which were responsible for enhanced electrochemical active surface area and superior OER/HER performance. The La-CoFe2O4@MXene exhibited an OER onset potential of 1.47 V versus RHE, while for HER it is 0.26 V versus RHE. The bifunctional material exhibited a 277 mV overpotential to attain 10 mA cm−2 current density during OER and a 285 mV overpotential to reach 100 mA cm−2 current density during HER performance. The excellent bifunctional performance is attributed to the presence of MXene sheets, which facilitates higher conductivity, a greater number of active sites, and superior charge transfer kinetics for the water splitting reactions. [ABSTRACT FROM AUTHOR]

Fusarium vascular wilt disease is one of the most harmful disease that affected broad range of plant species including zucchini (Cucurbita pepo). The objective of the research was to investigate the presence of the phytopathogenic gungus Fusarium oxysporum the causal agent of the disease in zucchini fields. Forty five isolates of F. oxysporum were isolated from four locations in province of Dyala during 2014-2015. Isolate Foq9 was most virulent in the pathogenicity test in vitro. Twenty nine isolates of them amplified their DNA positively with the universal primer of F. oxysporum in the polymerase chain reaction technique (PCR). In vitro significant suppression efficiency were observed of the fungicides Topsin M 70 WP (Tm) and Tecto 500 SC (Tc) and two botanical extract solution extracted from Garlic (Gr) and Ginger (Gn) against the pathogen on the potato sucrose agar (PSA). In greenhouse experiments all of the agents decreased the percentage of disease incidence and severity significantly, while the tetra-inoculum (Tm+Tc+Gr+Gn) was superior which exhibited 0% disease incidence and severity compared to the negative control which was 95%, 79% respectively, also the combined application of the botanical extracts (Gr+Gn) reduced the disease incidence and severity significantly. All of the treatment increased plant growth criteria represented by dry weight of the plant compared to the control.

The reach of Diyala River just before its confluence with Tigris River south of the capital city Baghdad was taken as a case-study. This segment of Diyala River is exposed to multiple points of treated and raw municipal wastewater discharges of Al-Rustimiyah wastewater treatment plants. Its pollution status was assessed with regard to nitrogen compounds levels. The aquatic parameters: DO, TN, TKN NH4-N, NH3-N, NO3-N, NO2-N, pH, and temperature were monitored and measured at nine sites along the river reach for a period of one year to assess seasonal variations. The first and last sites were chosen at the downstream and upstream of the points of pollution flowing into Diyala River, while the second to eighth sites were located at the effluents of the WWTPs of Al-Rustimiyah. It was found that water at sites two, seven, and four, respectively, were the most polluted points among all duo to the presence of the bypasses from the WWTPs at these sites. With regard to NH4-N, NH3-N, and TN concentrations, the river was found to be heavily polluted with untreated wastewater at site two and between low to medium strength at other sites, except for site one. On the other hand, NO3-N and NO2-N concentrations categorized the river water as an effluent rather than a stream according to Iraqi standard classification. Reversed relations were found between the DO concentrations and some of the nitrogen compounds and temperature. A statistical model relating TN concentration to DO, NH3-N, and temperature was derived. It was proved to be accurate.

Nanoparticle incorporation plays an active feature in heat transfer, ultimately enhancing the tribological process under boundary conditions of heat stress. Nanoparticles like zinc oxide (ZnO) and multiwall carbon nanotubes (MWCNT) are well known to significantly affect the cooling and lubrication applications, resulting in improved heat transfer and kinematic viscosity. The present work investigates the tribological performance of ZnO/MWCNTs hybrids as lubricant additive in the paraffinic type of mineral base oil of Group I (SN150) engine oil. The chemical composition of the modified and unmodified oil was examined by an inductively coupled plasma-optical emission spectrometer (ICP-OES), energy dispersive x-ray fluorescence (EDXRF) spectrometer, and Fourier-transform infrared spectroscopy (FTIR). A ring-ondisk tribotester was performed to investigate the tribological behaviour through the linear reciprocating mechanism alloy-steel contacts. The worn steel alloy surfaces morphology and chemical compositions were examined by scanning electron microscope (SEM), energy-dispersive x-ray spectroscopy (EDX), and 3D optical profilometer. Different ZnO/MWCNTs nanomaterial volumetric concentrations were examined in order to determine the most effective performance. According to the tribological results, ZnO/MWCNTs hybrid nanomaterials in the engine oil were found to have significantly higher friction temperature and antiwear capability than the base oil. A volumetric concentration of 3.00 wt% ZnO/MWCNTs nanomaterials to SN150 engine oil imparted excellent wear protection to the steel sample than the pure SN150 base oil. Based on the statistical analysis, the modified oil anti-wear performance was enhanced by reducing the wear loss by 80.5% and friction temperature by 55.8°C compared with the oil base. [ABSTRACT FROM AUTHOR]