Two additional cases of metformin‐associated encephalopathy in patients with end‐stage renal disease undergoing hemodialysis

We report on two additional cases of metformin‐associated encephalopathy in patients with end‐stage renal disease (ESRD) undergoing hemodialysis. Two patients were seen at our hospital with abnormal neurological signs and symptoms. Magnetic resonance imaging (MRI) revealed the same pattern of high signal intensity in both basal ganglia in T2‐weighted images in the two patients. The two patients had started taking metformin 5 and 6 weeks earlier at the same dose of 1000 mg per day. Metformin was immediately stopped, and regular hemodialysis was conducted. Their signs and symptoms resolved completely after these measures. The high signal intensity in both ganglia in T2‐weighted MRI also disappeared. We should suspect metformin‐induced encephalopathy and withdraw the drug when presented with diabetic patients with chronic kidney disease and neurological signs and symptoms of unknown cause.     

Time estimation method for manual assembly using MODAPTS technique in the product design stage

This paper aims to propose an accurate and quick assembly time estimation method using the modular arrangement of predetermined time standards in the product design stage. It describes a classification of 2382 assembly operations that are incurred in manually assembling consumer electronics such as air conditioners, washing machines and refrigerators, and a method of choosing representative motions comprising work elements by examining the frequency distribution of the assembly operation’s motions. It then presents criteria for assigning time values associated with the movement of the representative motions using the design factors employed in design for assembly and the layout factors of an assembly line. A case study then presents the practicality of the method, the statistical results of which indicate that the proposed method would be accurate enough for practical purposes.     

Memory-efficient real-time map building using octree of planes and points

This paper presents an octree-based map building algorithm for mobile home-service robots. The robot is equipped with a time-of-flight camera, which produces point clouds of the environment surfaces. Given the successive input of point clouds, a 3D map is incrementally computed in real time. The map is accurate and memory-efficient because the octree nodes containing points on a plane are merged and represented simply by an index to the plane. The real-time performance is achieved largely due to the parallel processing capability of the many-core Graphics Processing Unit used for plane extraction.     

A Study of Mill Power as a Function of Media Type and Shape

ABSTRACT

The mill power of a laboratory scale tumbling media mill was determined for the different shapes of media which are used industrially for dry grinding of quartz to produce silica flow. The tested media were ceramic balls and cylinders of high density alumina, and natural flint pebbles; tests were performed over ranges of filling levels and rotational speeds, with and without lifters in the mill. The experiments showed that ceramic balls at low levels of ball charge slipped excessively against the mill wall when the mill interior was smooth and without lifters. The use of lifters gave a consistent tumbling action and, under otherwise comparable conditions, mill power was linearly proportional to media density. Equations were developed which enable the comparison of mill conditions which give the same mill power draw for the different shapes and densities. Combined with studies of grinding kinetics, this enables comparison of the grinding efficiencies for different media shapes.     

Investigation of the effect of metal foam characteristics on the PCM melting performance in a latent heat thermal energy storage unit by pore-scale lattice Boltzmann modeling

Latent heat thermal energy storage (LHTES) has many advantages such as high energy density and phase change at a nearly constant temperature compared with sensible thermal energy storage or chemical energy storage techniques. However, one of its major drawbacks is the low thermal conductivity of phase change materials (PCMs) which impedes the heat transfer efficiency. High thermal conductivity metal foams could be added into the LHTES to enhance the heat transfer speed. Under this case, the investigation of the effects of metal foam porosity and pore size on the melting process is essential for improving the heat storage capability of LHTES. In this article, a pore-scale modeling of melting process in a LHTES unit filled with metal foams is carried out by enthalpy-based multiple-relaxation-time lattice Boltzmann method. The quartet structure generation set is used to generate the morphology of metal foams. In addition, a Compute Unified Device Architecture (CUDA) Fortran code is developed in this work for executing highly parallel computation through graphics processing units. The melting process in the PCMs is investigated in terms of porosity, pore size, nonuniform metal foam, hot wall temperature, and initial subcooled temperature to optimize the design of LHTES filled with metal foams.     

Heat transfer and solidification microstructure evolution of continuously cast steel by non-steady physical simulation

The heat transfer and solidification microstructure evolution during continuous casting were experimentally studied in this work. A new approach to physically simulate the steel solidification behavior during continuous casting was developed. Six steel grades with different solidification mode were introduced to elucidate the carbon equivalent dependent mold heat flux, prior austenite grain size and secondary dendrite arm spacing. It is found that the non-steady mold heat fluxes in the experiment against time for all steel grades are comparative to that versus distance in practical continuous casting. Due to the occurrence of L→L+δ→δ+γ→γ transformation with the largest amount of volume contraction in hypo-peritectic steel, it shows the lowest mold heat flux among these six steel grades. It is also demonstrated from the solidification microstructure results that the prior austenite grain size and secondary dendrite arm spacing in the physical simulation are in good agreement with those in continuously cast strand. In addition, the steel with a higher temperature for the onset of δ→γ transformation reveals the larger prior austenite grains resulted from the higher grains growth rate in the post solidification process.     

Structural design of transom pod for outboard motor in polyethylene boat

In a polyethylene boat, a transom pod is subjected to repeated thrust forces generated by an outboard motor. The structural design of the transom pod for the outboard motor must be considered because it is subjected to cyclic bending moments causing thrust forces of the outboard motor. We designed a transom pod reinforced with aluminum alloy plate inside the transom pod in a polyethylene boat and obtained an optimal thickness of the Al alloy plate to ensure the transom pod durability. We then performed a structural analysis for the transom pod reinforced with Al alloy plate and estimated the fatigue life using modified Goodman diagram. The optimal thickness of Al alloy plate was 7 mm.     

Modeling Sialidosis with Neural Precursor Cells Derived from Patient-Derived Induced Pluripotent Stem Cells

Sialidosis, caused by a genetic deficiency of the lysosomal sialidase gene (NEU1), is a systemic disease involving various tissues and organs, including the nervous system. Understanding the neurological dysfunction and pathology associated with sialidosis remains a challenge, partially due to the lack of a human model system. In this study, we have generated two types of induced pluripotent stem cells (iPSCs) with sialidosis-specific NEU1^G227R and NEU1^V275A/R347Q mutations (sialidosis-iPSCs), and further differentiated them into neural precursor cells (iNPCs). Characterization of NEU1^G227R- and NEU1^V275A/R347Q- mutated iNPCs derived from sialidosis-iPSCs (sialidosis-iNPCs) validated that sialidosis-iNPCs faithfully recapitulate key disease-specific phenotypes, including reduced NEU1 activity and impaired lysosomal and autophagic function. In particular, these cells showed defective differentiation into oligodendrocytes and astrocytes, while their neuronal differentiation was not notably affected. Importantly, we found that the phenotypic defects of sialidosis-iNPCs, such as impaired differentiation capacity, could be effectively rescued by the induction of autophagy with rapamycin. Our results demonstrate the first use of a sialidosis-iNPC model with NEU1^G227R- and NEU1^V275A/R347Q- mutation(s) to study the neurological defects of sialidosis, particularly those related to a defective autophagy–lysosome pathway, and may help accelerate the development of new drugs and therapeutics to combat sialidosis and other LSDs.     

Progressive NO2 Sensors with Rapid Alarm and Persistent Memory-Type Responses for Wide-Range Sensing Using Antimony Triselenide Nanoflakes

Antimony triselenide (Sb₂Se₃) nanoflake-based nitrogen dioxide (NO₂) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb₂Se₃ nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO₂ gas concentrations from 0.1 to 100 ppm. These Sb₂Se₃ nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb₂Se₃ nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO₂ gas flow of only 1 ppm. As a result, the Sb₂Se₃ nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations.