Photo-electrochemical Hydrogen Sulfide Splitting using SnIV-doped Hematite Photo-anodes

© 2016 The Authors. Published by Elsevier B.V.Spray-pyrolysed SnIV-doped α-Fe2O3 photo-anodes were used for photo-assisted splitting of HS- ions in alkaline aqueous solutions, producing polysulfide (Sn2 -) ions together with hydrogen at the cathode. Subsequent aerial oxidation of polysulfide could be used to produce elemental sulfur. At an applied electrode potential of 1.07 V (RHE) and an irradiance of 5.6 kW m- 2, stable photocurrents of ca. 11 A m- 2 (2 × 10- 3 A W- 1) were recorded over 75 h, polysulfide concentrations increasing linearly with time. Despite being predicted thermodynamically to form iron sulfide(s) in sulfide solutions, such photo-anodes appeared to be stable. In comparison with conventional water splitting under alkaline conditions, the coupled processes of hydrogen sulfide ion oxidation and water reduction had a lower energy requirement

Disrupting 3D printing of medicines with machine learning.

3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice and improve patient care, 3DP must harness modern technologies. Machine learning (ML), an influential branch of artificial intelligence, may be a key partner for 3DP. Together, 3DP and ML can utilise intelligence based on human learning to accelerate drug product development, ensure stringent quality control (QC), and inspire innovative dosage-form design. With ML's capabilities, streamlined 3DP drug delivery could mark the next era of personalised medicine. This review details how ML can be applied to elevate the 3DP of pharmaceuticals and importantly, how it can expedite 3DP's integration into mainstream healthcare

Harnessing Artificial Intelligence for the Next Generation of 3D Printed Medicines

Artificial intelligence (AI) is redefining how we exist in the world. In almost every sector of society, AI is performing tasks with super-human speed and intellect; from the prediction of stock market trends to driverless vehicles, diagnosis of disease, and robotic surgery. Despite this growing success, the pharmaceutical field is yet to truly harness AI. Development and manufacture of medicines remains largely in a ‘one size fits all’ paradigm, in which mass-produced, identical formulations are expected to meet individual patient needs. Recently, 3D printing (3DP) has illuminated a path for on-demand production of fully customisable medicines. Due to its flexibility, pharmaceutical 3DP presents innumerable options during formulation development that generally require expert navigation. Leveraging AI within pharmaceutical 3DP removes the need for human expertise, as optimal process parameters can be accurately predicted by machine learning. AI can also be incorporated into a pharmaceutical 3DP ‘Internet of Things’, moving the personalised production of medicines into an intelligent, streamlined, and autonomous pipeline. Supportive infrastructure, such as The Cloud and blockchain, will also play a vital role. Crucially, these technologies will expedite the use of pharmaceutical 3DP in clinical settings and drive the global movement towards personalised medicine and Industry 4.0

Distribution, pest status and agro-dimatic preferences of lepidopteran stem borers of maize in Kenya

Lepidopterous stem borers are the main field insect pests that attack maize, Zea mays L. in tropical Africa. A survey was carried during the long and short rain cropping seasons of 2002/2003 across six main agro-climatic zones (ACZs) to determine the spatial distribution of important stem borer species in Kenya. A total of 474 visits were made in the seventy-eight localities conveniently chosen to represent each of the six ACZs. 189,600 stems were checked for infestation, of which 27,799 infested stems were destructively cut and dissected for stem borer larvae identification. An average of 1.4 stem borer larvae were recovered per infested plant. 54.5% of the recovered larvae were identified as Chilo partellus (Swinhoe) (Crambidae), 39.7% as Busseola fusca (Fuller) (Noctuidae), 4.5% as Sesamia calamistis Hampson (Noctuidae) and 0.8% as Chilo orichalcociliellus (Strand) (Crambidae). Minor species present included Eldana saccharina Walker (Pyralidae), Sesamia nonagrioides (Lefebvre) (Noctuidae), Sesamia cretica Lederer (Noctuidae), Sesamia sp. (Noctuidae), Sciomesa piscator Fletcher (Noctuidae), Busseola sp near phaia (Noctuidae), Chilo sp, Ematheudes sp 1 (Pyralidae) and Ematheudes sp 2 (Pyralidae). Farms were grouped into respective ACZs for statistical analysis and subsequent comparison of dominant species: Results indicated that B. fusca was the dominant stem borer species in high potential zones (highland tropics, moist transitional zone and moist mid-altitude) while the exotic C. partellus dominated smallholder farms in low potential zones (dry mid-altitude, dry transional and lowland tropical zone). Within each ACZs, there was evidence of variation in species proportions between seasons. These spatio-temporal differences in community structure are discussed in terms of agro-climatic biological adaptations

Spin density wave dislocation in chromium probed by coherent x-ray diffraction

We report on the study of a magnetic dislocation in pure chromium. Coherent x-ray diffraction profiles obtained on the incommensurate Spin Density Wave (SDW) reflection are consistent with the presence of a dislocation of the magnetic order, embedded at a few micrometers from the surface of the sample. Beyond the specific case of magnetic dislocations in chromium, this work may open up a new method for the study of magnetic defects embedded in the bulk.Comment: 8 pages, 7 figure

Optimization of fuel injection parameters of moringa oleifera biodiesel-diesel blend for engine-out-responses improvements

Biodiesel has gained popularity in diesel engines as a result of the rapid decline of fossil fuels and population growth. The processing of biodiesel from non-edible Moringa Oleifera was investigated using a single-step transesterification technique. Both fuels had their key physicochemical properties measured and investigated. In a common-rail diesel engine, the effects of MB50 fuel blend on the symmetric characteristics of engine-out responses were evaluated under five load settings and at 1000 rpm. As compared to standard diesel, MB50 increased brake thermal efficiency (BTE), and nitrogen oxides (NOx) emissions while lowering brake specific fuel consumption (BSFC), and smoke emissions for all engine loads. A further study of injection pressure and start of injection (SOI) timing for MB50 fuel was optimized using response surface methodology (RSM). The RSM optimization resulted in improved combustion dynamics due to symmetry operating parameters, resulting in a simultaneous decrease in NOx and smoke emissions without sacrificing BTE. RSM is an efficient optimization method for achieving optimal fuel injection parameter settings, as can be deduced. As a result, a clearer understanding of the use of MB50 fuel in diesel engines can be given, allowing for the best possible engine efficiency

Connected healthcare: Improving patient care using digital health technologies

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 being increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are currently being investigated for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and scopes for clinical adoption

A novel transcript of oil palm (Elaeis guineensis Jacq.), Eg707, is specifically upregulated in tissues related to totipotency

In this study, we report the molecular characterization of clone Eg707 isolated from cell suspension culture of the oil palm. The deduced polypeptide of clone Eg707 is highly similar to an unknown protein from Arabidopsis thaliana. The presence of an Ald-Xan-dh-C2 superfamily domain in the deduced protein sequence suggested that Eg707 protein might be involved in abscisic acid biosynthesis. Eg707 might be present as a single copy gene in the oil palm genome. This gene is highly expressed in tissue cultured materials compared to vegetative and reproductive tissues, suggesting a role of this gene during oil palm somatic embryogenesis or at the early stages of embryo development. Expression analysis of Eg707 by RNA in situ hybridization showed that Eg707 transcripts were present throughout somatic embryo development starting from proembryo formation at the embryogenic callus stages till the maturing embryo stages. Since proembryo formation within the embryogenic callus is one of the first key factors in oil palm somatic embryo development, it is suggested that Eg707 could be used as a reliable molecular marker for detecting early stage of oil palm somatic embryogenesis

Chemical composition of essential oil of exudates of Dryobalanops aromatica

Purpose: To identify the chemical composition of essential oil from the exudates of Dryobalanops aromatica from Malaysia.Methods: Exudate was collected from D. aromatica and subjected to fractional  distillation to obtain essential oil. Gas chromatography-mass spectrometry  (GC-MS) was used to characterize the composition of the isolated essential oil.Results: The yield of essential oil was 7.58 %, with the highest yield (3.24 %) within the first 2 h of fractional distillation. Thirty compounds which accounted for 97.56 % of essential oil composition were identified. These include sesquiterpenes (46.87 %), monoterpenes (31.05 %), oxygenated monoterpenes (16.76 %) and oxygenated  sesquiterpenes (2.13 %). Borneol accounted for 0.74 % of the essential oil.Conclusion: Essential oil from the exudates of D. aromatica contains terpenoid  compounds and borneol.Keywords: Dryobalanops aromatica, exudate, fractional distillation, essential oil, GS-MS, borneo