Microbial safety and probiotic potential of packaged yogurt products in Pakistan

Yogurt is a health food with notable market production and demand. Because of this, we conducted a study on prominent commercial brands of yogurts in Pakistan for microbial content and the probiotic potential of the contained lactic acid bacteria (LAB), in the context of their label claims. All contained viable LAB, but the numbers (cfu g⁻¹) varied considerably. Three of the products made explicit probiotic claims, but LAB from these displayed no probiotic attributes per WHO-FAO guidelines. The yogurt starter and nonstarter Lactobacillus strains had no gelatinase or hemolytic activity and exhibited significant antibacterial activity against some human pathogens. One brand with a probiotic claim contained an L. acidophilus strain that showed cholesterol assimilation activity in vitro. Some potential human pathogens that were hemolytic and resistance to β-lactam antibiotics were also detected in the products. The findings demonstrate a need for better quality control and regulation to ensure safety and efficacy of yogurt products.     

Novel strongly coupled tungsten-carbon-nitrogen complex for efficient hydrogen evolution reaction

Alternatives to noble metal based electrocatalysts are vitally necessary to produce hydrogen from water at low overpotentials. Earlier research on tungsten based electrocatalyst has been mainly concentrated towards tungsten carbide (WC) and tungsten nitride (WN) as the potential electrocatalysts for hydrogen evolution reaction (HER), whereas tungsten carbide (W₂C) has been least focused upon. Herein, we report a highly active novel strongly coupled tungsten-carbon-nitrogen complex (W₂C-NC-WN complex) prepared by in situ carbonization method. This W₂C-NC-WN complex exhibits a remarkable electrochemical performance for HER with a small onset potential of 33 mV vs. RHE and requires an overpotential (η) of 145 mV vs. RHE to render ?10 mA cm^?2 current density. The Tafel analysis demonstrates a slope of 96 mV dec^?1 which is much better than WN (109.6 mV dec^?1) and WC (142.4 mV dec^?1). The strong coupling of W₂C and WN within N-doped carbon (NC) framework brings about a significant enhancement in HER kinetics and faster electron transport due to the remarkable reduction in charge transfer resistance. The facile synthetic approach reported here, provides a powerful tool for the structurally controlled modification of the catalyst while simultaneously introducing active species.     

Intrinsic relationship between energy consumption,pressure, and leakage in water distribution systems

The basic implications of changes in delivery pressure on system energy use and cost, on leakage, excess pressure, and environmental impacts are explored. An analytical expression is first developed to characterize the primary relationships between energy use, leakage and pressure for a simple pipe segment. Then, two more realistic case studies, based on varying versions of the Anytown network, are considered. The results indicate that energy use responds more to changes in the delivery pressure in systems with higher leakage rates while reductions in pressures curtail energy use and leakage more dramatically in low resistance systems. Perhaps more surprisingly, systems with more effective water storage and thus uniform pressures tend to have higher leakage rates, greater energy usage, and higher GHG emissions relative to systems relying on direct pumping. The generalization that results from these studies is perhaps predictable but has profound implications: the higher the delivery pressure the greater will likely be the amount of water wasted and energy dissipated.     

Thermodynamic optimization of reverse Brayton cycles of different configurations for cryogenic applications

The thermodynamic optimization of differing Reverse Brayton Refrigeration (RBR) cycle configurations is presented in this study. These cycle configurations include: Conventional 1-stage compression cycle; Conventional 2-stage compression cycle; 1-stage compression Modified cycle with intermediate cooling of the recuperator using an auxiliary cooler; and an Integrated 2-stage expansion RBR cycle. For high pressure ratio applications, multi-stage compressors with intercooling are considered. Analytical solutions for the conventional cycles are developed including thermal and fluid flow irreversibilities of the recuperators and all heat exchangers in addition to the compression and expansion processes. Exergy analysis is performed and the exergy destruction of different components of the RBR cycles for different configurations is presented and the effects of important system parameters on performance are investigated. Thermodynamic optimization of the cycles with intermediate cooling of the recuperator is included. Effects of the 2nd law/exergy efficiency of the auxiliary cooler on the total system efficiencies are presented.     

A wirelessly powered low-power digital temperature sensor

A wirelessly powered temperature sensor is presented in complementary metal-oxide-semiconductor (CMOS) 180-nm process. The wireless power transfer (WPT) is performed using resonant magnetic coupling, and a diode-less AC to DC conversion is achieved through a quadrature-oscillator with native-MOS. The quadrature-signals are subsequently used to control the diode-less rectifier switches. The on-chip temperature sensor exploits the subthreshold region temperature, and the sensed temperature is converted to frequency using a ring-oscillator, which is implemented using differential cross coupled oscillator-based delay cells. The temperature sensor architecture also employs a temperature-insensitive replica circuit to minimize process dependence and enhance power-supply rejection ratio (PSRR) of the sensing process. The application-specific integrated circuit has been designed and fabricated in 180-nm CMOS process and has dimensions of 2 mm × 2 mm. The measurement results demonstrate that the WPT circuit generates a DC voltage of 1V with a power transfer efficiency of 85% for distances 2 to 8 mm with settling time of microseconds to milliseconds. The temperature sensor demonstrates a resolution of < ±0.6C with a sensitivity of 0.52 mV/C and 126.9 Hz/C along with PSRR of −63dB and Integral Non-Linraity (INL) of 5% measured across six different dies. The back-scattering communication demonstrates a −53-dB signal at a distance of 4 mm without affecting the WPT efficiency. The total power consumption of the temperature sensor along with the integrated biases is 120 nW.     

A generic low-noise CMOS readout interface for 64?×?64 imaging array with on-chip ADC

This paper presents a low-noise and high dynamic-range CMOS readout-IC (ROIC) for a 64?×?64 array of opto-electrical sensors. The readout chain comprises a pixel preamplifier array, correlated-double-sampling based switched-capacitor gain blocks, class-AB output buffer for driving off-chip loads and a 12-bit pipeline ADC for on-chip digitization. The pixel preamplifiers array, occupying an area of 30???m?×?30???m per pixel, can either be hybridized to a separate IR or UV sensor or can be used as monolithic visible-light active CMOS pixel-array after exposing (by etching the pad) the embedded photodiode under the bonding pads. The ROIC is designed and fabricated in 0.25???m 1P/5?M CMOS technology with 5?mm?×?5?mm of total dimensions. The integrated readout chain, in integrate-then-read mode, demonstrates a dynamic range of 72?dB for electrically emulated sensor currents from 25?pA to 100?nA. It can support a frame rate of 700?fps, with single fully-differential analog as well as 12-bit digital output, at 10?MHz while consuming 17?mW with on-chip biases.     

Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach

Predicting the dynamics of water-level in lakes plays a vital role in navigation, water resources planning and catchment management. In this paper, the Extreme Learning Machine (ELM) approach was used to predict the daily water-level in the Urmia Lake. Daily water-level data from the Urmia Lake in northwest of Iran were used to train, test and validate the employed models. Results showed that the ELM approach can accurately forecast the water-level in the Urmia Lake. Outcomes from the ELM model were also compared with those of genetic programming (GP) and artificial neural networks (ANNs). It was found that the ELM technique outperforms GP and ANN in predicting water-level in the Urmia Lake. It also can learn the relation between the water-level and its influential variables much faster than the GP and ANN. Overall, the results show that the ELM approach can be used to predict dynamics of water-level in lakes.