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Dry eye syndrome is one of the most common reasons for eye-related discomfort which, without treatment, in some cases may even lead to corneal damage. Blinking, baseline and reflex lachrymation and drainage compromise the topical application of therapeutics demanding repeated, often hourly applications of common lubricants. In contrast, topically administered chitosan-N-acetylcysteine-based eye drops were reported to sustain on the ocular surface for more than 24 h. The thiolated biopolymer can interact with the corneal mucin layer thereby forming covalent disulphide bridges, which may contribute to extended residence times.

In this study, the tribological characteristics of four different lubricants including hyaluronic acid and chitosan-N-acetylcysteine containing commercially available eye drops were investigated. For this purpose, a representative test setup was developed, which mimics the contact between the cornea and the eyelid wiper. Gels with different elastic properties coated with a mucin layer were used as a substrate to mimic the corneal surface. Tests were conducted with a micro-tribometer, and friction values were recorded. Contact zones were characterized by X-ray photoelectron spectroscopy to investigate wear and thiol bonding on the surface.

Results revealed the lowest average coefficient of friction values for chitosan-N-acetylcysteine-based eye drops and substrate dependence of the test setup.

In this study, the authors introduced an in vitro system to test different types of eye drops so that chemical interaction with the mucin layer can be observed. These interactions change the tribological performance significantly and must be considered to have results relevant to the actual application.

Three Coupled Model Intercomparison Project Phase 5 models involved in the G4 experiment of the Geoengineering Model Inter-comparison Project (GeoMIP) project were used to investigate the impact of stratospheric aerosol injection (SAI) on the mean surface air temperature and precipitation extremes in Africa.

This impact was examined under G4 and Representative Concentration Pathway (RCP) 4.5 scenarios on the total precipitation, the number of rainy days (RR1) and of days with heavy rainfall (R20 mm), the rainfall intensity (SDII), the maximum length of consecutive wet (CWD) and dry (CDD) days and on the maximum rainfall in five consecutive days (Rx5day) across four regions: Western Africa (WAF), Eastern Africa (EAF), Northern Africa and Southern Africa (SAF).

During the 50 years (2020–2069) of SAI, mean continental warming is −0.40°C lower in G4 than under RCP4.5. During the post-injection period (2070–2090), the temperature continues to increase, but at a lower rate (−0.19°C) than in RCP4.5. During SAI, annual rainfall in G4 is significantly greater than in RCP4.5 over the high latitudes (especially over SAF) and lower over the tropics. The termination of SAI leads to a significant increase of rainfall over Sahel and EAF and a decrease over SAF and Guinea Coast (WAF).

Compared to RCP4.5, SAI will contribute to reducing significantly regional warming but with a significant decrease of rainfall in the tropics where rainfed agriculture account for a large part of the economies. After the SAI period, the risk of drought over the extratropical regions (especially in SAF) will be mitigated, while the risk of floods will be exacerbated in the Central Sahel.

To meet the Paris Agreement, African countries will implement mitigation measures to contribute to keep the surface air temperature below 2°C. Geoengineering with SAI is suggested as an option to meet this challenge, but its implication on the African climate system needs a deep investigation in the aim to understand the impacts on temperature and precipitation extremes. To the best of the authors’ knowledge, this study is the first to investigate the potential impact of SAI using the G4 experiment of GeoMIP on temperature and precipitation extremes of the African continent.

The purpose of this study is to assess a novel method for creating tangible three-dimensional (3D) morphologies (scaled models) of neuronal reconstructions and to evaluate its cost-effectiveness, accessibility and applicability through a classroom survey. The study addresses the challenge of accurately representing intricate and diverse dendritic structures of neurons in scaled models for educational purposes.

The method involves converting neuronal reconstructions from the NeuromorphoVis repository into 3D-printable mold files. An operator prints these molds using a consumer-grade desktop 3D printer with water-soluble polyvinyl alcohol filament. The molds are then filled with casting materials like polyurethane or silicone rubber, before the mold is dissolved. We tested our method on various neuron morphologies, assessing the method’s effectiveness, labor, processing times and costs. Additionally, university biology students compared our 3D-printed neuron models with commercially produced counterparts through a survey, evaluating them based on their direct experience with both models.

An operator can produce a neuron morphology’s initial 3D replica in about an hour of labor, excluding a one- to three-day curing period, while subsequent copies require around 30 min each. Our method provides an affordable approach to crafting tangible 3D neuron representations, presenting a viable alternative to direct 3D printing with varied material options ensuring both flexibility and durability. The created models accurately replicate the fidelity and intricacy of original computer aided design (CAD) files, making them ideal for tactile use in neuroscience education.

The development of data processing and cost-effective casting method for this application is novel. Compared to a previous study, this method leverages lower-cost fused filament fabrication 3D printing to create accurate physical 3D representations of neurons. By using readily available materials and a consumer-grade 3D printer, the research addresses the high cost associated with alternative direct 3D printing techniques to produce such intricate and robust models. Furthermore, the paper demonstrates the practicality of these 3D neuron models for educational purposes, making a valuable contribution to the field of neuroscience education.

Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process.

PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles.

PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one.

The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding.

Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data.

The outputs of these sensors were obtained by connecting the sensors to the general-purpose input/output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in a graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software.

The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. This study proposed that the sensors analytic system be applied on an industrial plastic injection mould to measure and display the various parameters of the injection moulds for the purpose of understanding and improving the performance of the injection mould

An electronic system that provides the continuous values of essential parameters of a plastic injection mould in operation.

The different performance tests were conducted on diesel engine compression ignition (CI) mode and CRDi engine.

The CI engine was suitably modified to CRDi engine with Toroidal re-entrant combustion chamber (TRCC) and was run in dual-fuel (DF) mode. Hydrogen (H₂) was supplied at different flow rates during the suction stroke, and 0.22 Kg/h of hydrogen fuel flow rate (HFFR) was found to be optimum. Diesel and biodiesel were used as pilot fuels. The CRDi engine with DF mode was run at various injection pressures, and 900 bar was found to be optimum injection pressure (IP) with 10o before top dead center (bTDC) as fuel injection timing (IT).

These operating engine conditions increased formation of oxides of nitrogen (NOx), which were reduced by exhaust gas recycle (EGR). With EGR of 15%, CRDi engine resulted in 12.6% lower brake thermal efficiency (BTE), 5.5% lower hydrocarbon (HC), 7.7% lower carbon monoxide (CO), 26% lower NOx at 80% load as compared to the unmodified diesel engine (CI mode).

The current research is an effort to study and evaluate the performance of CRDi engine in DF mode with diesel-H₂ and BCPO-H₂ fuel combinations with TRCC.

Pre-eclampsia and eclampsia (PE/E) are rising in Sub-Saharan Africa, including Nigeria. This study aims to evaluate the availability and logistics management of sixteen items from the Nigerian essential medicine list required for managing these conditions.

A cross-sectional study in 50 health-care facilities in Lagos State, Nigeria, at the beginning of the COVID-19 pandemic by interviewing the facility’s main person in charge of health commodities. Data were recorded during the visit and in the previous six months using the adapted Logistics Indicators Assessment Tool (LIAT). In addition, descriptive analysis was conducted based on the World Health Organization availability index.

The availability of 13 (81%) of the commodities were high, and 3 (19%) were relatively high in the facilities, stock out rate during the visitation and previous six months varied with the commodities: urinalysis strip (22%) and (40%), hydralazine (20%) and (20%), labetalol injection (8%) and (20%), labetalol tablet (24%) and (24%) and sphygmomanometer (8%) and (8%). No stock out was recorded for 11 (69%) commodities. All the facilities observed 9 (75%) out of the 12 storage guidelines, and 36 (72%) had a perfect storage condition score.

Current state of PE/E health commodities in the selected facilities is highlighted, and the strengths and weaknesses of the supply chain in these health facilities were identified and discussed.

These commodities’ availability ranged from reasonably high to very high. Regular supportive supervision is germane to strengthening the logistics management system for these commodities to prevent the negative impact on the health and well-being of the people during the COVID-19 pandemic and post-pandemic.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

Japan's decision to release nuclear wastewater into the Pacific Ocean in 2023 has sparked strong opposition at home and abroad. In this study, Graph Model for Conflict Resolution (GMCR) method is adopted to analyze the conflict problem, and reasonable equilibrium solutions are given to solve the conflict event.

In this study, GMCR is adopted to solve the conflict problem. First, identify the key decision-makers (DMs) on the issue of nuclear effluent and the relevant options they might adopt. Second, the options of each DM are arranged and combined to form a set of feasible states. Thirdly, the graph model is constructed according to the change of DM's options, and the relative preference of each DM is determined. Finally, the conflict problem is solved according to the definition of GMCR equilibrium.

Discharging nuclear wastewater into the ocean is not the right choice to solve the problem. Developing more space to store nuclear wastewater is more conducive to the protection of the ocean environment.

It is undesirable for the Japanese government to unilaterally discharge nuclear wastewater into the ocean. Objectively assessing the radioactivity of nuclear wastewater and the cooperation of relevant stakeholders can better solve this conflict.

The problem arising from Japan's releasing plan is complicated because of a lack of information and the existence of multiple stakeholders, while GMCR can help us with a better view of the current circumstance in the conflict.

In the cylinders of a marine diesel engine, self-ignition occurs in a very short time after the fuel injection into the combustion chamber. Therefore, this paper aims to develop a model of diesel fuel spray for the early stage of fuel spray in the marine diesel engine. The main technical aspects such as nozzle diameter of the marine engine injector and backpressure in the combustion chamber were taken into consideration.

In this paper, laboratory experimental studies were carried out to determine parameters of fuel spray in an early stage of injection in the marine diesel engine. The optical measuring Mie scattering technique was used to record the fuel injection process. The working space was a constant volume chamber. The backpressure parameters in the constant volume chamber were the same as during the operation of the marine diesel engine. Based on the experimental studies and important Hiroyasu and Arai models of fuel spray presented in literature was proposed new model of fuel spray parameters for marine diesel injectors.

In this paper, the proposed new model of the two main parameters described fuel spray evolution”: new model of spray tip penetration (STP) and spray cone angle (SCA). New model propagation of fuel STP in time was included the influence of nozzle diameter and backpressure. The proposed model has a lower error, about 15%–34%, than the model of Hiroyasu and Arai. Moreover, a new model of the evolution over time of the SCA is developed.

In the future research of fuel spray process must be taken influence of the fuel temperature. Diesel fuel has a different density and viscosity in dependence of fuel temperature. Therefore are predicted of the expansion about influence of fuel temperature, new model of fuel spray for a marine diesel engine. The main limitations occurring in the research are not possible to carry out the research while real operation marine diesel engine.

An experimental test was carried out for a real fuel injector of a marine diesel engine. Design parameters and fuel injection parameters were selected on the basis of the actual one. In the literature, SCA is defined as a constant parameter for the specific preliminary data. A new model for the early stage of fuel spray of SCA propagation in time has been proposed. The early stage of fuel spray is especially important, because in this time comes in there to fuel self-ignition.