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The electrochemical behavior and wear characteristics of a Ti30Nb3Ag (at%) alloy processed with powder metallurgy were investigated for bioimplant applications. A linear reciprocating tribometer was used to assess the tribological properties. Advanced scanning electrochemical microscopic testing was used to investigate the passivation properties and subsequent corrosion protection of the processed Ti30Nb3Ag alloy in a simulated body fluid. Cyclic potentiodynamic polarization and electrochemical impedance spectroscopy tests were performed in both potentio-static and potentiodynamic modes. The results showed that the microstructure of the sintered Ti30Nb3Ag alloy has three phases: β-Ti (BCC), α -Ti (HCP), and Ti2Ag phase. In comparison to commercial pure Ti and Ti6Al4V alloy, the Ti30Nb3Ag alloy exhibited an enhancement in wear resistance of 86% and 36%, respectively. The microelectrochemical corrosion results confirmed the Ti30Nb3Ag alloy's superior localized corrosion-resistant performance by forming an effective passive layer on the surface, pointedly, Rct value of Ti30Nb3Ag alloy exhibited 160% improvement compared to that of Ti6Al4V alloy after 24 h of exposure. In comparison to the Ti6Al4V alloy, the Ti30Nb3Ag alloy exhibited enhanced corrosion resistance, increased hardness, and reduced wear rates, indicating a competitive advantage in biomedical applications.

Background: The aim of this study was to identify items that healthcare providers and/or patients consider important to include in a questionnaire for clinical trials and cohort studies in shoulder instability research. This could serve as a basis to develop a core outcome set for shoulder instability research. Methods: Healthcare providers and patients were included in a panel for a modified Delphi consensus study. The study consisted of three rounds, comprising (1) identifying items, (2) rating the importance of the items, and (3) rating the importance again after seeing a summary of the results of round two. Importance was rated on a 9-point Likert scale. Consensus was defined as ≥ 80% of the panel giving a score of 7 or higher. Results: In total, 44 healthcare providers and 30 patients completed all three rounds. Round one identified 54 items. After round three, the panel reached a consensus on 11 items that should be included in a questionnaire, comprising re-dislocation (99%), instable feeling of the shoulder (96%), limitations during sport (93%), patient satisfaction with the shoulder (93%), fear/anxiety for re-dislocation (91%), range of motion (88%), return to old level of functioning (85%), performing daily activities (85%), return to sport (82%), return to work (82%), and trusting the shoulder (81%). Conclusion: Healthcare providers and patients reached a consensus on 11 items that should be included in a questionnaire for shoulder instability research. These items can facilitate design and development of future clinical trials and form the basis for the development of a core outcome set.

Canned food market demand has arisen due to the higher need for instant and ready-to-eat food. Food preservatives are often added to canned and processed foods to prolong their shelf life and help to sustain the quality, taste, color, and food texture. However, excessive usage of such food preservatives can lead to various diseases and health issues including palpitations, allergies, and cancer. Therefore, food preservative detection in food samples is essential for safe consumption and health well-being. This paper proposed a fuzzy logic framework to determine the safety of food products based on the concentration of sulphur dioxide (SD), benzoic acid (BA), and sorbic acid (SA) in five different food categories as referred to the Food Acts 1983 and Food Regulations 1985 in Malaysia. The fuzzy logic framework comprises of Mamdani inference system design with 90 fuzzy rules, 15 and 5 membership functions for both the input and output parameters respectively. 50 random values and 10 lab analysis results based on the industrial samples were used to validate the developed algorithms in ensuring the safety of the food products. The membership functions generated for the three inputs (SD, BA, and SA) during the fuzzification steps are based on the maximum allowable limit from the food acts. The defuzzification of fuzzy logic gave an average output value of 0.1565, 0.1350, 0.1150, 0.1100, and 0.1550 for chicken curry with potatoes, satay sauce, sardine in tomato sauce, anchovies paste, and sardine spread accordingly. Results obtained from the fuzzy logic framework concluded that all the industrial samples are safe to be eaten and comply with the Sixth Schedule, Regulation 20 in both Acts.

Potentiometric sensing of oxyanions such as arsenate over self-assembly engineered and chemically responsive molybdenum dioxide grafted polyaniline (PANI/MoO3) plated ITO glass electrode has been reported. FT-IR, XRD, SEM, EDX, STEM-mapping, Raman spectroscopy, and N2 adsorption-desorption measurements were used to determine the impact of molecular architecture on the structure, morphology, and physical characteristics of PANI/MoO3. The obtained result implies the synthesis of a porous hybrid nanostructured material with enhanced orientated crystallinity, enhanced adsorption capacity, and responsiveness because of an optimized molecular structure and crystallinity alignment. The limit of detection (LOD) for detecting As(V) ions by using PANI/MoO3 composite/ITO electrodes based on the differential pulse voltammetry technique (DPV) was found to be around 0.15 ppb. The interaction between arsenate and molybdate oxyanions led to the development of an induced potential, which helped to clarify the sensing mechanism, charge transfer, and shifting characteristics. For the on-site detection of residual arsenate in diverse environmental samples, the analytical performance of the produced electrode in a genuine sample was also investigated.

This research aims to design and process a low elastic modulus near -β Ti–30Nb–3Ag at% (TNA) alloy with enhanced corrosion and antibacterial characteristics for bioimplant uses. Powder metallurgy was used to process the TNA alloy, which was designed via a combined approach of molybdenum equivalency and the d-electron alloy design method. The alloy powder samples were sintered at 1100, 1200, and 1300 °C. XRD and SEM were utilized to examine the phases and microstructure. The modulus of elasticity and microhardness were evaluated using microindentation. The in vitro corrosion properties were also examined in artificial body fluid medium. The results showed that TNA alloy was predominantly composed of β-Ti, with trace amounts of α-Ti, α’’, and Ti2Ag phases. The density and microhardness were increased by increasing the sintering temperature, and the sample sintered at 1300 °C exhibited a homogeneous microstructure with 89.7% densification. The modulus of elasticity of the designed TNA alloys lowered by (28.5–43) % and (24–38) % compared to Ti6Al4V alloy and CP-Ti, respectively, which potentially contributes to a decrease in the stress-shielding effect. The in vitro corrosion results indicated that the resistance to corrosion of the TNA alloy improved with increasing sintering temperature as evidenced by an increase in charge transfer resistance, noble corrosion potential, and passive current density. Furthermore, the TNA alloy also demonstrated a higher antibacterial capability (82.9%) compared to Ti6Al4V alloy. The designed TNA alloy with low elastic modulus exhibits higher in vitro corrosion resistance and antibacterial properties making it a potential bioimplant material.

Effects of amino acid supplementation to ideal protein (IP) formulated rations were investigated on growth performance, plasma metabolites and organ weights of broilers placed on 100% recycled (reused) litter. Day-old Ross308 male broilers were raised on either clean or reused litter and fed for three weeks on one of five isoenergetic diets, where an IP-based control diet (C) was compared with diets containing threonine (T) or arginine (A) at 25% above requirements, or with 1% supplemented glutamine (G), or with each amino acid added (TAG). Litter and diet treatments did not strongly interact on outcomes. Reused litter placement resulted in greater weight gain, smaller feed conversion ratio and heavier bursal weights (P

Artificial Intelligence (AI) techniques have evolved into practical, fast and effective tools in combination with detecting devices for quality assessment, particularly in adulteration and deficiency detection in the food and agriculture industry. This review discusses recent advances in AI techniques and their integration with a variety of sensing devices to detect food adulteration and agricultural product defects. The results obtained from the sensors require the application of case-specific AI techniques aimed at improving the acquired high-dimensional dataset's understanding, as well as classification and prediction. It is evident that the coupling of AI technique and sensors have shown promising outcome between 81.2 and 100% range of accuracy in adulteration and defect detection for food and agricultural product. The research trends and guidelines are also proposed with the aim to provide references and guidance to both scientific researchers and industrial players in the field of food and agriculture quality assessment. The challenges and prospects regarding AI techniques were also revealed. Furthermore, future potential developments, new sensors and novel algorithms must be pursued and validated. Future AI detection of food adulteration and agricultural product defects can be anticipated, especially with the integration of various sensors and the application of deep learning algorithms. Real-time monitoring and predictive modeling may also receive great attention, which could assist to avoid quality problems before they arise, lower the risk of fraud, and ensure high-valuable products.

This work focuses on the industrial application of silica/thiourea-formaldehyde (SiO2@TF) composite monoliths to recover silver (Ag(I)) and mercury (Hg(II)) ions from contaminated samples. The fabricated SiO2@TF was characterized by various techniques such as Fourier transform infrared spectroscopy, scanning electron microscopy, high-resolution transmission electron microscopy, scanning transmission electron microscopy/energy-dispersive X-ray spectroscopy, N2 adsorption–desorption, Raman spectroscopy, elemental analysis, and zeta potential measurements. The silica-polymer monolithic sorbent displays unique surface dominants including the active surface sites along the micrometric-sized particles, high surface area-to-pore volume ratios, and uniform worm-like pores for suitable accommodation of silver and mercury ions. Thus, leading to creating captured subsets onto monolithic particles and into organized pore caves for proper Ag(I) and Hg(II) ions trapping, with maximal capacities of 1356 and 582 mg/g, respectively. The adsorption behaviors of Ag(I) and Hg(II) ions into SiO2@TF from aqueous solutions were minutely optimized under different experimental conditions of pH, concentration, and time. The key result in our study is the higher capacity exhibited by the designed composite toward the target Ag(I) and Hg(II) ions in environmental and waste disposal samples, as well as its reproducibility over several regeneration cycles. These findings can be useful in the fabrication of low-cost and easy-to-synthesis sorbents and can be tailored to suit various applications.

En el sudeste de la provincia de Buenos Aires se encuentra la principal región productora de papa de la Argentina. La papa que se produce tiene tres destinos: el mercado fresco, la industria y la producción de semilla, la cual se realiza en un área diferenciada. El cultivo de papa se establece a través de la propagación vegetativa y, como consecuencia, los tubérculos infectados se convierten en una vía de transmisión de virus. El objetivo fue determinar la incidencia de Potato virus Y (PVY), Potato leaf roll virus (PLRV), Potato virus X (PVX) y Tomato spotted wilt virus (TSWV) y la ocurrencia de infecciones mixtas entre estos virus en áreas de producción de papa para consumo e industria y papa-semilla del sudeste de Buenos Aires durante las campañas 2013-2014 a la 2018-2019. Otro objetivo fue analizar el progreso de los niveles de infección para estos virus y la tendencia de las categorías de certificación de papa-semilla fiscalizadas por el Instituto Nacional de semillas (INASE) en el área diferenciada en los últimos 35 años. En este estudio se trabajó con datos procedentes de tubérculos de papa de 107 lotes de consumo e industria recolectados según protocolo y 41 lotes de papa-semilla muestreados al azar por técnicos oficiales del INASE para su fiscalización. Los tubérculos fueron brotados y analizados mediante DAS-ELISA para detección de PVY, PLRV, PVX y TSWV. Se estimó la incidencia de cada virus, incidencia relativa entre estos y frecuencias de infecciones simples y mixtas para ambas categorías y para cada campaña. Se analizaron los niveles de infección de PVY, PLRV, PVX y TSWV del área diferenciada de producción de papa-semilla y su relación con las categorías de certificación. PVY resultó el virus con mayor incidencia mientras que PLRV y TSWV fueron los de menor incidencia tanto para la producción de papa destinada a consumo e industria como para papa-semilla. Se observó fluctuación interanual de los valores de incidencia para PVY, PLRV y TSWV en ambas categorías. Se reportó por primera vez infecciones mixtas entre PVY, PLRV y TSWV. Las infecciones mixtas más frecuentes fueron entre TSWV con PVY o PLRV. Se observó una disminución de los niveles de infección para PVY, PLRV, PVX y TSWV y una mejora en la tendencia de las categorías de certificación de papa-semilla para todos los virus en los últimos 35 años. Actualmente, las categorías de papa-semilla son Inicial iii para PVY e Inicial i para PLRV, PVX y TSWV. Desde 2010 no se detecta PVX en papa-semilla. Cabe señalar que la acción integrada de entidades públicas, privadas y productores que adoptaron el protocolo de la Mesa Provincial de papa logró que esta área diferenciada del sudeste de Buenos Aires se destaque por su excelencia sanitaria. No obstante, para la región de producción de papa para consumo e industria se deberían fortalecer las medidas de control de PVY y TSWV.

In this work, we investigate nanostructured Cu2O-gC3N4 composites with diverse Cu2O addition (0.5–3.0 mol %) prepared by ultrasonication-mixture of mesoporous Cu2O and g-C3N4 prepared individually from soft and hard-template sol–gel, respectively. The efficiency of the Cu2O-gC3N4 nanocomposites depends on the Cu2O/gC3N4 ratio because it controls the heterojunctions development between them. The synergistic influence amid Cu2O and g-C3N4 in the nanostructured composites was demonstrated in the production of hydrogen under simulated light achieving a maximum efficiency at 2 mol % of Cu2O (17 and 38 times higher than on bare Cu2O and g-C3N4, respectively). Correlation between photoactivity and physicochemical characteristics of the Cu2O-g-C3N4 nanocomposites shows that the improvement in photoefficiency was related with the variances in the ability to absorb observable light and to separate the charge carriers associated to the different development of Cu2O/gC3N4 heterojunctions in the nanocomposites.

Tylophora indica, a threatened medicinal plant of family Asclepiadaceae, grows profoundly in Asia, Africa, Australia, Oceanic Islands, Ceylon, Malay island, and Borneo. The plant is a twinning herb that is excessively used in folk medicine as a substitute of ipecac, an expectorant. Different parts of the plant are accredited for the anti-asthmatic, antibacterial, anti–psoriasis, antimicrobial, antiulcer, antiallergic, antidiarrhoeal, hypolipidemic, and anxiolytic properties. Antidiabetic, hepatoprotective, antiangiogenic, anti-tumor, antioxidant, anticonvulsant, anti-rheumatic, and diuretic activities are also attributed to the magnificent medicinal plant owing to the occurrence of various active phytochemicals such as alkaloids, saponins, phytosterols, tannins, and primary metabolites. The plant has been exploited by the ethnic people due to the immense medicinal importance, leading to the endangerment of the plant species. The review brings to light the important pharmacological attributes, folk medicinal uses, and biotechnological approaches that must be followed to save the plant from extinction.

New heterometallic complex [NiCu(NO3)2(H2O)2] (1) was prepared via the reaction of aqueous solutions of (oxalic acid, nickel nitrate and copper nitrate). Mixed oxide CuO-NiO was successfully obtained with different morphological structures (2) and (3) through the annealing of 1 at different temperature 300 °C and 600 °C, respectively. The materials were characterized using FT-IR, TGA, XRD and SEM. As showed from XRD data, with increasing the calcination temperature the crystallinity of CuO-NiO in sample 3 was improved and the diffraction peaks exhibited narrower and stronger than CuO-NiO in sample 2. The average size of CuO-NiO crystals obtained was calculated from Debye-Scherrer equation and found to be 16.65 nm. To assemble the working electrode of 2-aminophenol (2-AP) chemical sensor, a thin layer of CuO-NiO NPs was deposited on glassy carbon electrode (GCE) with conducting binder and used to detect 2-AP in aqueous medium successfully. The chemical sensor is exhibited the higher stability, good sensitivity (20.2729 μAmM−1 cm−2) and enhanced electrochemical activity at room conditions. Therefore, the fabricated chemical sensor with active CuO-NiO NPs may be an effective and sensitive sensor for detection of hazardous materials by reliable I–V method for broad scales environmental safety of and healthcare sectors. Keywords: CuO-NiO, Mixed oxides, 2-aminophenol sensor, Electrochemical method, Glassy carbon electrode, Environmental safety.

In this study, two lactobacilli isolates, from dairy food and bovine rumen, were used to investigate the differences in their biochemical characteristics when exposed to low pH and bile salt stress conditions. Production of volatile compounds was analysed by gas liquid chromatography (GLC), alterations in fatty acid profiles of bacterial cells by chromatography-mass spectrophotometry (GC-MS), and changes in protein banding patterns were detected using 1D SDS PAGE. Significant differences were found in the production of acetic acid by stressed and non-stressed cells. Hexanoic acid and octanoic acid production was observed by the cells exposed to bile salt stress only. For both isolates, the saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) levels were significantly different for all treatments, except however an increased level of polyunsaturated fatty acids (PUFA) production under bile salts stress was observed. The comparison of the 1-D protein banding patterns of non-stressed and pH stressed and bile salts stressed cells revealed several protein bands were differentially expressed. Findings of this investigation suggest that lactobacilli isolates possess variation in biochemical characteristics on the basis of origin and in their response to low pH and high bile salt stress conditions.

The paper focused on the implementation of hybrid Interval Type-2 (IT2) Fuzzy with Generic Model Control (GMC) for the nonlinear stochastic waste treatment process in the anaerobic digester. Development of the deterministic methane process model has been extended to a set of stochastic nonlinear differential equations. The stochastic effect is introduced by adding white noise with unit covariance to give an interesting profile like physical plant dynamic. The IT2 Fuzzy based on Takagi-Sugeno-Mendel and GMC by Lee and Sullivan have been developed to control the holdup pH inside reactor. The pH value is being manipulated by the flowrate of Sodium hydroxide at optimal methane gas production condition. The process variables that need to be controlled and included into the controller are pH, error and change of error while the consequence fuzzy set output is from the GMC backpropagation law equations. As a result from several studies; servo and regulatory, the controller show significant improvement on the set point tracking and disturbance rejection over typical Fuzzy, Fuzzy-GMC and conventional Proportional-Integral-Derivative (PID) controllers. It shows the controller is suitable for stochastic process and nonlinear control system application.

The stress-strain state of elastic-plastic material in a neighborhood of the top of arbitrary oriented straight-line crack with determening relations of the flow theory with hardening under plane stress is investigated. Based on the variant of a method of asymptotic expansion taking into account nonholonomicity of the resolving equations and the singularity of fields of stresses and deformations, the problem is reduced to a recurrent sequence of two-point boundary problems, that are solved numerically-analytically. The analysis of stresses and deformations and local characteristics of damage in the area surrounding singular point has been done.

Chemical processes are systems that include complicated network of material, energy and process flow. As time passes, the performance of chemical process gradually degrades due to the deterioration of process equipments and components. The early detection and diagnosis of faults in chemical processes is very important both from the viewpoint of plant safety as well as reduced manufacturing costs. The conventional way used in fault detection and diagnosis is through the use of models of the process, which is not easy to be achieved in many cases. In recent years, an artificial intelligence technique such as neural network has been successfully used for pattern recognition and as such it can be suitable for use in fault diagnosis of processes [1]. The application of neural network methods in process fault detection and diagnosis is demonstrated in this work in two case studies using simulated chemical plant systems. Both systems were successfully diagnosed of the faults introduced in them. The neural networks were able to generalise to successfully diagnosed fault combinations it was not explicitly trained upon. Thus, neural network can be fully applied in industries as it has shown several advantages over the conventional way in fault diagnosis.

The absence of a stable operational state in polymerization reactors that operates in batches is factor that determine the need of a special control system. In this study, advanced control methodology is implemented for controlling the operation of a batch polymerization reactor for polystyrene production utilizingmodel predictive control. By utilizing a model of the polymerization process, the necessary operational conditions were determined for producing the polymer within the desired characteristics. The maincontrol objective is to bring the reactor temperature to its target temperature as rapidly as possible with minimal temperature overshoot. Control performance for the proposed method is encouraging. It has been observed that temperature overshoot can be minimized by the proposed method with the use of both reactor and jacket energy balance for reactor temperature control.

In this paper, the simulink block diagram is used to solve a model consists of a set of ordinary differential and algebraic equations to control the temperature inside a simple stirred tank heater. The flexibility of simulink block diagram gives students a better understanding of the control systems. The simulink also allows solution of mathematical models and easy visualization of the system variables. A polyethylene fluidized bed reactor is considered as an industrial example and the effect of the Proportional, Integral and Derivative control policy is presented for comparison.

Industries are now moving towards PC-based control from PLC (Programmable Logic Control) based control as the PC (personal computer) is easily available and capable of implementing various control strategies to improve productivity. Advances in both hardware and software technology are expediting this move. Absence of a user friendly, cost effective and easy to apply advanced control strategy based software is the motivation for this work. In this paper we reviewed issues of software application in process control systems. We present the development of an advance process control software tool and its application on a pH neutralization plant. Neural network model based DIC (Direct Inverse Control) strategy is implemented to control the process. The application and results shows the viability and robustness of the advanced control software and its superiority over the conventional PID (proportional–integral–derivative) controller.

A Microbial Electrolysis Cells (MECs) is a slightly modified microbial fuel cells (MFCs) where a small amount of electricity is applied to the anode chamber to suppress the production of methane. Oxygen is kept out of the cathode chamber to assist bacterial oxidation of organic matter present in the wastewater to produce hydrogen, a gas which is the becoming the most attractive energy source. While MECs has tremendous potential, the development of this technique is still in its infancy. The goal of this work is to optimize the production of biohydrogen gas by selecting the optimum current and controlling applied voltage in MECs using batch reactor. The mathematical model of the MECs is based on material balances with the integration of bio-electrochemical reactions describing the effect of applied voltage on the performance of MECs batch reactor. The behaviour of the system differs significantly as the value of applied voltage is changed and gives a significant influence on the hydrogen production rate. Finally, this study can be extended in the future to improve the optimization in MEC model and develop advanced control system study.