A Comprehensive Review on Manufacturing and Characterization of Polyetheretherketone Polymers for Dental Implant Applications.

Aging, tooth trauma, and pathological infections cause partial or total tooth loss, leading to the usage of dental implants for restoration treatments. As such, mechanical and tribological properties play an important role in the osseointegration and durability of these implants. Metallic and ceramic implants are shown to have mechanical properties much higher than the natural teeth structure, leading to stress shielding-related failure of an implant. Stress shielding occurs due to the difference in the elastic modulus between the implant material and the surrounding teeth structure, leading to bone loss and implant failure. The implant's properties (i.e., mechanical) should be as close as human teeth components. To achieve this, various materials and coatings are being developed and investigated. This review is a comprehensive survey of materials, manufacturing, coating techniques, and mechanical and tribological characterizations of dental implants, with a particular focus on polyetheretherketone (PEEK) as a potential alternative dental implant material. PEEK has mechanical properties similar to natural teeth, which make it a promising material for dental implants. The findings of this review suggest that PEEK offers superior biocompatibility, osseointegration, and wear resistance for implant applications. With the help of bioactive coatings, bone growth on the implant surface can be promoted. In addition, PEEK dental implants made using three-dimensional (3D) printing technology can significantly reduce the cost of implants, making them more affordable and increasing access to dental care, which can improve oral health significantly. In summary, this review highlights the potential of PEEK as a promising alternative dental implant material, and provides an overview of various techniques, testing, and future directions for PEEK dental implants.

Costs and benefits of allomaternal care to mothers and others in wild Phayre's leaf monkeys.

OBJECTIVES: Allomaternal care (AMC) is suggested to be energetically beneficial to mothers and costly to allomothers. However, among primates, AMC is a heterogeneous phenomenon and its implications are less clear especially in female dispersal species. Here, we investigated infant care in a female dispersal species, Phayre's leaf monkeys (Trachypithecus phayrei crepusculus), to evaluate whether mothers were constrained by infant care and benefitted energetically from AMC, whether AMC was energetically costly for allomothers and how maternal experience was associated with AMC. MATERIALS AND METHODS: Data were collected via instantaneous focal animal sampling between 2004 and 2005 for juvenile and adult females (N = 18) from two groups at the Phu Khieo Wildlife Sanctuary, Thailand (440 h). We used generalized linear mixed models to determine how infant care during the first month after birth affected the time mothers and allomothers spent feeding, socializing, resting, and locomoting and how AMC varied. RESULTS: In the first month, infants spent 26% of their time with an allomother. We found no differences in mothers' overall activity before versus after birth, although mothers fed significantly more and rested less when without their infant. Allomothers fed and rested less when with an infant. AMC varied between 0.0% and 20.5%, with immature females being most active. DISCUSSION: Mothers appear to benefit energetically from AMC such that their overall activity after birth remained unchanged. Costs and benefits for allomothers seem to be variable. Some very active immature females may be benefitting from learning-to-mother. The overall low cost of AMC may facilitate a reciprocal social network among unrelated females.

Evaluation of a low-cost portable NIRS device for monitoring muscle ischemia.

The main objective of this study is to evaluate the low-cost, open-source HEGduino device as a tissue oximetry monitor to advance the research of somatic NIRS monitoring. Specifically, this study analyzes the use of this portable functional NIRS system for detecting the cessation of blood flow due to vascular occlusion in an upper limb. 19 healthy patients aged between 25 and 50 were recruited and monitored using HEGduino device. Participants underwent a vascular occlusion test on one forearm. Raw values collected by HEGduino as well as the processed variables derived from the measurements were registered. Additional variables to characterize the signal noise during the tests were also recorded. The results of the data distribution curves for all the subjects in the study accurately detected the physiological events associated with transient tissue ischemia. The statistical analysis of the recorded data showed that the difference between the baseline values recorded by the red led (RED) and its normalized minimum variable was always different from zero (p < 0.014). Furthermore, the difference between the normalized baseline values recorded by the infrared led (IR) and the corresponding normalized minimum value was also different from zero (p < 0.001). The R-squared coefficient of determination for the noise variables considered in this study on the normalized RED and IR values was 0.08 and 0.105, respectively. The study confirms the potential of HEGduino system to detect an interruption of the blood flow by means of variations in regional tissue oxygen saturation. This study demonstrates the potential of the HEGduino device as a monitoring alternative to advance the study of the applicability of NIRS in muscle tissue oximetry.

Low-Cost Classroom and Laboratory Exercises for Investigating Both Wave and Event-Related Electroencephalogram Potentials.

Electroencephalography (EEG) has given rise to a myriad of new discoveries over the last 90 years. EEG is a noninvasive technique that has revealed insights into the spatial and temporal processing of brain activity over many neuroscience disciplines, including sensory, motor, sleep, and memory formation. Most undergraduate students, however, lack laboratory access to EEG recording equipment or the skills to perform an experiment independently. Here, we provide easy-to-follow instructions to measure both wave and event-related EEG potentials using a portable, low-cost amplifier (Backyard Brains, Ann Arbor, MI) that connects to smartphones and PCs, independent of their operating system. Using open-source software (SpikeRecorder) and analysis tools (Python, Google Colaboratory), we demonstrate tractable and robust laboratory exercises for students to gain insights into the scientific method and discover multidisciplinary neuroscience research. We developed 2 laboratory exercises and ran them on participants within our research lab (N = 17, development group). In our first protocol, we analyzed power differences in the alpha band (8-13 Hz) when participants alternated between eyes open and eyes closed states (n = 137 transitions). We could robustly see an increase of over 50% in 59 (43%) of our sessions, suggesting this would make a reliable introductory experiment. Next, we describe an exercise that uses a SpikerBox to evoke an event-related potential (ERP) during an auditory oddball task. This experiment measures the average EEG potential elicited during an auditory presentation of either a highly predictable ("standard") or low-probability ("oddball") tone. Across all sessions in the development group (n=81), we found that 64% (n=52) showed a significant peak in the standard response window for P300 with an average peak latency of 442ms. Finally, we tested the auditory oddball task in a university classroom setting. In 66% of the sessions (n=30), a clear P300 was shown, and these signals were significantly above chance when compared to a Monte Carlo simulation. These laboratory exercises cover the two methods of analysis (frequency power and ERP), which are routinely used in neurology diagnostics, brain-machine interfaces, and neurofeedback therapy. Arming students with these methods and analysis techniques will enable them to investigate this laboratory exercise's variants or test their own hypotheses.

Subdural drain with Nelaton catheter and latex glove, a low-cost alternative and how to make it.

Background: One of the most commonly encountered surgical pathologies in neurosurgical practice worldwide is subdural hematoma. The use of prefabricated drains following surgical procedures is widely recommended. However, their availability can be inconsistent due to various issues. Methods: An intensive search was conducted regarding the availability and cost of subdural drains. The Medtronic subdural evacuating port system costs between 100 and 150 USD, the Blake drain costs between 35 and 40 USD, and the Jackson-Pratt drain costs between 25 and 35 USD. We present a low-cost alternative and describe how it can be implemented using materials available in almost every hospital. Results: A simple step-by-step guide for crafting handmade subdural drains has been created, aiming to make this affordable alternative accessible to every surgeon who may need one due to the unavailability of prefabricated drains in developing countries. Conclusion: The benefits associated with using a subdural drain during the evacuation of subdural hematomas are well-documented. In cases where prefabricated drains are not available, a handmade alternative can always be utilized. Materials are often readily available in every hospital, and the cost may not exceed 100 MXN (5 USD), making it at least 5 times cheaper than the cheapest prefabricated alternative. This solution is particularly beneficial for developing countries without access to prefabricated drains.

Low-Cost, Scalable Simulations in Obstetric Trauma and Resuscitative Hysterotomy for Emergency Medicine Residents.

Introduction: Simulation-based learning is essential for health care providers to prepare for rare obstetric emergencies, such as severe trauma and maternal cardiac arrest. These situations demand rapid and prompt actions, often testing the skill of emergency physicians. Resuscitative hysterotomy (RH), a critical procedure in maternal cardiac arrest, requires technical expertise, coordination, and anatomical knowledge. The high cost of commercial trainers and complex existing models restricts accessibility. This resource introduces a low-cost anatomically accurate RH task trainer and assesses its effectiveness in improving skills and confidence among trainee emergency physicians. Methods: A 20-minute-long case scenario depicted the resuscitation of a pregnant trauma patient with tension pneumothorax and uterine rupture, culminating in maternal cardiac arrest necessitating RH. Residents performed RH on the task trainer under faculty guidance. Feedback followed the Pendleton model, and an online questionnaire gauged the residents' experiences. Results: Thirty emergency medicine residents participated in the simulation. The questionnaire revealed positive responses, confirming the session's relevance and enhancement of clinical skills and confidence. Discussion: Our results underscore the RH task trainer's critical role in improving residents' skills and confidence during obstetric trauma simulations. Its realism and effectiveness were notably well received. Future refinements aim to augment fidelity while preserving affordability and integrating regular reinforcement sessions. This innovative educational approach equips health care professionals to respond adeptly to rare and challenging obstetric emergencies, ultimately elevating outcomes for mothers and infants during critical situations.

Energy-aware bio-inspired spiking reinforcement learning system architecture for real-time autonomous edge applications.

Mobile, low-cost, and energy-aware operation of Artificial Intelligence (AI) computations in smart circuits and autonomous robots will play an important role in the next industrial leap in intelligent automation and assistive devices. Neuromorphic hardware with spiking neural network (SNN) architecture utilizes insights from biological phenomena to offer encouraging solutions. Previous studies have proposed reinforcement learning (RL) models for SNN responses in the rat hippocampus to an environment where rewards depend on the context. The scale of these models matches the scope and capacity of small embedded systems in the framework of Internet-of-Bodies (IoB), autonomous sensor nodes, and other edge applications. Addressing energy-efficient artificial learning problems in such systems enables smart micro-systems with edge intelligence. A novel bio-inspired RL system architecture is presented in this work, leading to significant energy consumption benefits without foregoing real-time autonomous processing and accuracy requirements of the context-dependent task. The hardware architecture successfully models features analogous to synaptic tagging, changes in the exploration schemes, synapse saturation, and spatially localized task-based activation observed in the brain. The design has been synthesized, simulated, and tested on Intel MAX10 Field-Programmable Gate Array (FPGA). The problem-based bio-inspired approach to SNN edge architectural design results in 25X reduction in average power compared to the state-of-the-art for a test with real-time context learning and 30 trials. Furthermore, 940x lower energy consumption is achieved due to improvement in the execution time.

Simultaneous Regulation of Organic and Inorganic Components in Interphase by Fiber Separator for High-stable Sodium Metal Batteries.

Uncontrollable side reactions at the metal interface have been identified as the root cause of the formation of a fragile solid electrolyte interphase, leading to irreversible sodium loss in sodium metal batteries. Here, we proposed an interface engineering strategy that employed a carboxyl functionalized cellulose separator to provide strong dipole moments and induce the cleavage of P-F bond to construct a SEI rich in NaF. In addition, we employed nuclear magnetic resonance technology confirmed that the separator with strong dipole moments prevented the reduction of organic solvents by attracting electrons, thereby inhibiting the formation of organic oligomers. SEI with high NaF content and few oligomers is smooth and robust, obviously decreasing the interface impedance of the Na anode. The symmetric Na||Na cells, equipped with the functionalized separator, efficiently operated for 1400 hours with a stable 72 mV overpotential at 0.25 mA cm-2, exhibiting low energy barrier and fast ion transport kinetics. The Na||Na3V2(PO4)3 cell also showed stable cycling performance, with the capacity remaining at 94.83% of the initial capacity after 1000 cycles at 1C. The proposed separator could control the formation and composition of SEI, paving the way for the development of long-life sodium metal batteries.

Recycling of Sewage Sludge: Synthesis and Application of Sludge-Based Activated Carbon in the Efficient Removal of Cadmium (II) and Lead (II) from Wastewater.

The limited supply of drinking water has aroused people's curiosity in recent decades. Adsorption is a popular method for removing hazardous substances from wastewater, especially heavy metals, as it is cheap, highly efficient, and easy to use. In this work, a new sludge-based activated carbon adsorbent (thickened samples SBAC1 and un-thickened samples SBAC2) was developed to remove hazardous metals such as cadmium (Cd+2) and lead (Pb+2) from an aqueous solution. The chemical structure and surface morphology of the produced SBAC1 and SBAC2 were investigated using a range of analytical tools such as CHNS, BET, FT-IR, XRD, XRF, SEM, TEM, N2 adsorption/desorption isothermal, and zeta potential. BET surface areas were examined and SBAC2 was found to have a larger BET surface area (498.386 m2/g) than SBAC1 (336.339 m2/g). While the average pore size was 10-100 nm for SBAC1 and 45-50 nm for SBAC2. SBAC1 and SBAC2 eliminated approximately 99.99% of Cd+2 and Pb+2 out the water under all conditions tested. The results of the adsorption of Cd+2 and Pb+2 were in good agreement with the pseudo-second-order equation (R2 = 1.00). Under the experimental conditions, the Cd+2 and Pb+2 adsorption equilibrium data were effectively linked to the Langmuir and Freundlich equations for SBAC1 and SBAC2, respectively. The regeneration showed a high recyclability for the fabricated SBAC1 and SBAC2 during five consecutive reuse cycles. As a result, the produced SBAC1 and SBAC2 are attractive adsorbents for the elimination of heavy metals from various environmental and industrial wastewater samples.

Assessment of Low-Cost and Higher-End Soil Moisture Sensors across Various Moisture Ranges and Soil Textures.

The accuracy and unit cost of sensors are important factors for a continuous soil moisture monitoring system. This study compares the accuracy of four soil moisture sensors differing in unit costs in coarse-, fine-, and medium-textured soils. The sensor outputs were recorded for the VWC, ranging from 0% to 50%. Low-cost capacitive and resistive sensors were evaluated with and without the external 16-bit analog-to-digital converter ADS1115 to improve their performances without adding much cost. Without ADS1115, using only Arduino's built-in analog-to-digital converter, the low-cost sensors had a maximum RMSE of 4.79% (v/v) for resistive sensors and 3.78% for capacitive sensors in medium-textured soil. The addition of ADS1115 showed improved performance of the low-cost sensors, with a maximum RMSE of 2.64% for resistive sensors and 1.87% for capacitive sensors. The higher-end sensors had an RMSE of up to 1.8% for VH400 and up to 0.95% for the 5TM sensor. The RMSE differences between higher-end and low-cost sensors with the use of ADS1115 were not statistically significant.

Gas Detection and Classification Using Multimodal Data Based on Federated Learning.

The identification of gas leakages is a significant factor to be taken into consideration in various industries such as coal mines, chemical industries, etc., as well as in residential applications. In order to reduce damage to the environment as well as human lives, early detection and gas type identification are necessary. The main focus of this paper is multimodal gas data that were obtained simultaneously by using multiple sensors for gas detection and a thermal imaging camera. As the reliability and sensitivity of low-cost sensors are less, they are not suitable for gas detection over long distances. In order to overcome the drawbacks of relying just on sensors to identify gases, a thermal camera capable of detecting temperature changes is also used in the collection of the current multimodal dataset The multimodal dataset comprises 6400 samples, including smoke, perfume, a combination of both, and neutral environments. In this paper, convolutional neural networks (CNNs) are trained on thermal image data, utilizing variants such as bidirectional long-short-term memory (Bi-LSTM), dense LSTM, and a fusion of both datasets to effectively classify comma separated value (CSV) data from gas sensors. The dataset can be used as a valuable source for research scholars and system developers to improvise their artificial intelligence (AI) models used for gas leakage detection. Furthermore, in order to ensure the privacy of the client's data, this paper explores the implementation of federated learning for privacy-protected gas leakage classification, demonstrating comparable accuracy to traditional deep learning approaches.

Laboratory Tests of Metrological Characteristics of a Non-Repetitive Low-Cost Mobile Handheld Laser Scanner.

The popularity of mobile laser scanning systems as a surveying tool is growing among construction contractors, architects, land surveyors, and urban planners. The user-friendliness and rapid capture of precise and complete data on places and objects make them serious competitors for traditional surveying approaches. Considering the low cost and constantly improving availability of Mobile Laser Scanning (MLS), mainly handheld surveying tools, the measurement possibilities seem unlimited. We conducted a comprehensive investigation into the quality and accuracy of a point cloud generated by a recently marketed low-cost mobile surveying system, the MandEye MLS. The purpose of the study is to conduct exhaustive laboratory tests to determine the actual metrological characteristics of the device. The test facility was the surveying laboratory of the University of Agriculture in Kraków. The results of the MLS measurements (dynamic and static) were juxtaposed with a reference base, a geometric system of reference points in the laboratory, and in relation to a reference point cloud from a higher-class laser scanner: Leica ScanStation P40 TLS. The Authors verified the geometry of the point cloud, technical parameters, and data structure, as well as whether it can be used for surveying and mapping objects by assessing the point cloud density, noise and measurement errors, and detectability of objects in the cloud.

Reliability of Real-Time Kinematic (RTK) Positioning for Low-Cost Drones' Navigation across Global Navigation Satellite System (GNSS) Critical Environments.

UAVs are nowadays used for several surveying activities, some of which imply flying close to tall walls, in and out of tunnels, under bridges, and so forth. In these applications, RTK GNSS positioning delivers results with very variable quality. It allows for centimetric-level kinematic navigation in real time in ideal conditions, but limitations in sky visibility or strong multipath effects negatively impact the positioning quality. This paper aims at assessing the RTK positioning limitations for lightweight and low-cost drones carrying cheap GNSS modules when used to fly in some meaningful critical operational conditions. Three demanding scenarios have been set up simulating the trajectories of drones in tasks such as infrastructure (i.e., building or bridges) inspection. Different outage durations, flight dynamics, and obstacle sizes have been considered in this work to have a complete overview of the positioning quality. The performed tests have allowed us to define practical recommendations to safely fly drones in potentially critical environments just by considering common software and standard GNSS parameters.

Surgical Aortic Valve Replacement Using a Porcine Model: A Low-Cost Simulation for Surgical Trainees.

Simulation experiences are valuable to the training of future successful surgeons. These experiences introduce trainees to operational concepts through hands-on engagement within a low-stress environment to promote skill, information retention, and increased competency for future success in real-life scenarios. The study aimed to develop a low-cost, reproducible surgical simulation for teaching aortic valve replacement using porcine models. This study employed a single-center educational workshop design to provide trainees with a comprehensive wet laboratory experience in surgical aortic valve replacement using a porcine model. The simulation involved step-by-step procedures using porcine hearts in a wet lab environment, emphasizing specific surgical techniques such as suturing, knot tying, and valve replacement. Simulated valves were created using insulation foaming and aluminum wiring. The study was conducted at a southeastern medical school's wet lab. Thirty-eight preclinical medical students participated. The simulation was designed to provide a comprehensive overview of the steps involved in aortic valve replacement using porcine models. It emphasized the importance of teamwork, fundamental surgical skills, and effective communication within a surgical setting. The low-cost surgical simulation allowed trainees to learn technical skills that could be tailored to their proficiency level. Simulation for cardiothoracic procedures is limited by monetary spending and the availability of adequate materials to create a beneficial learning experience. This low-cost simulation allows resource-limited institutions to provide their students an additional opportunity to practice fundamental surgical principles such as suturing.

Development of low-cost pressure mapping device to evaluate force distribution for seat cushion modification.

This study aimed to determine the reliability and concurrent validity of a low-cost pressure mapping system (Smart mat) and reference standard pressure mapping (MatScan). Thirty healthy volunteers aged 29.57 ± 4.50 years who could sit still for at least one minute and had a hip width of less than 40 cm (36 ± 2.05 cm) were recruited. The participants sat on the Smart mat system and MatScan for 60 s per trial for 3 trials. The reliability of Smart mat using intraclass correlation coefficients (ICC) showed an excellent ICC of normalised total force (nTF) and normalised ischial width (nIW) in sitting (0.93, 0.98). The validity was assessed using Spearman correlation coefficients, which showed that nTF in sitting had a significantly strong correlation (r = 0.70**) and nIW in sitting had a significantly moderate correlation (r = 0.67**). This study's satisfactory results indicated that a low-cost pressure mapping system could be used for assessing forced distribution and ischial width during sitting.

Robust and low-cost open-source device for detecting infectious microorganisms by loop-mediated isothermal amplification.

Loop-Mediated Isothermal Amplification (LAMP) is a useful technique for detecting infectious microorganisms in human fluids since it performs similarly to conventional PCR, the results are obtained faster and no thermocyclers or complex devices are required. Since only two isothermal blocks (95 °C to lyse cells and 65 °C for DNA amplification) are needed, LAMP is particularly suited for applications in Low- and Middle-Income Countries (LMICs). To validate such assumption, we first designed and tested Arduino-controlled LAMP thermoblocks to process a considerable number of samples simultaneously with a low-energy consumption to enable routine use under worst-case conditions (no main power source and low ambient temperatures). The thermoblocks were tested when battery-powered at temperature down to 5 °C, showing high stability in well temperatures (<0.8 °C). The charge required for both thermoblocks to simultaneously achieve the target temperatures after switching on and to keep their working temperatures were 4.1 A·h and 2.4 A·h/h, respectively. Second, we implemented a low-cost viewer with LEDs and filters to detect the fluorescent LAMP reaction. All the components required for the instrument are for general purpose and readily available by e-commerce. Thus, the LAMP device allows for considerable autonomy by using a typical car battery in rural and itinerant healthcare or field hospitals in LMICs, even under difficult environmental conditions.

Feasibility Study on the Use of NO2 and PM2.5 Sensors for Exposure Assessment and Indoor Source Apportionment at Fixed Locations.

Recent advances in sensor technology for air pollution monitoring open new possibilities in the field of environmental epidemiology. The low spatial resolution of fixed outdoor measurement stations and modelling uncertainties currently limit the understanding of personal exposure. In this context, air quality sensor systems (AQSSs) offer significant potential to enhance personal exposure assessment. A pilot study was conducted to investigate the feasibility of the NO2 sensor model B43F and the particulate matter (PM) sensor model OPC-R1, both from Alphasense (UK), for use in epidemiological studies. Seven patients with chronic obstructive pulmonary disease (COPD) or asthma had built-for-purpose sensor systems placed inside and outside of their homes at fixed locations for one month. Participants documented their indoor activities, presence in the house, window status, and symptom severity and performed a peak expiratory flow test. The potential inhaled doses of PM2.5 and NO2 were calculated using different data sources such as outdoor data from air quality monitoring stations, indoor data from AQSSs, and generic inhalation rates (IR) or activity-specific IR. Moreover, the relation between indoor and outdoor air quality obtained with AQSSs, an indoor source apportionment study, and an evaluation of the suitability of the AQSS data for studying the relationship between air quality and health were investigated. The results highlight the value of the sensor data and the importance of monitoring indoor air quality and activity patterns to avoid exposure misclassification. The use of AQSSs at fixed locations shows promise for larger-scale and/or long-term epidemiological studies.

Synchronising an IMX219 image sensor and AS7265x spectral sensor to make a novel low-cost spectral camera.

A low-cost novel spectral camera able to be used for near infrared spectroscopy was made by using a Jetson Nano to synchronize a Sony IMX219 NOIR autofocus image sensor, an AMS AS7265x 18-channel spectral sensor and Osram SFH 4737 broadband infrared LED's. Synchronizing an image sensor and spectral sensor augments a standard RGB image with light spectrum information; capturing the light distribution information normally lost in RGB image capture. Sutherland et al. [1] used this novel spectral camera to examine the dorsal surface of juvenile lobsters as a possible pre-moult detector. Having the image and spectrum in combination allowed the incomplete and unmineralized post-moult dorsal surface to be characterized with 86.7% accuracy for the first time. A proposed application for the spectral camera is to omit the local SFH 4737 light source and use the camera in daylight, effectively making a low-cost substitute hyperspectral snapshot camera. In this configuration the camera may have application for low-cost drone deployment for small scale agriculture.

Design of innovative and low-cost dopamine-biotin conjugate sensor for the efficient detection of protein and cancer cells.

The rapid, precise identification and quantification of specific biomarkers, toxins, or pathogens is currently a key strategy for achieving more efficient diagnoses. Herein a dopamine-biotin monomer was synthetized and oxidized in the presence of hexamethylenediamine, to obtain adhesive coatings based on polydopamine-biotin (PDA-BT) on different materials to be used in targeted molecular therapy. Insight into the structure of the PDA-BT coating was obtained by solid-state 13C NMR spectroscopy acquired, for the first time, directly onto the coating, deposited on alumina spheres. The receptor binding capacity of the PDA-BT coating toward 4-hydroxyazobenzene-2-carboxylic acid/Avidin complex was verified by means of UV-vis spectroscopy. Different deposition cycles of avidin onto the PDA-BT coating by layer-by-layer assembly showed that the film retains its receptor binding capacity for at least eight consecutive cycles. Finally, the feasibility of PDA-BT coating to recognize cell lines with different grade of overexpression of biotin receptors (BR) was investigated by tumor cell capture experiments by using MCF-7 (BR+) and HL-60 (BR-) cell lines. The results show that the developed system can selectively capture MCF-7 cells indicating that it could represent a first approach for the development of future more sophisticated biosensors easily accessible, low cost and recyclable with the dual and rapid detection of both proteins and cells.

A study of quantifying the influence of kitchen human activity on indoor air quality dynamics.

Indoor air quality (IAQ) is increasingly recognised as one of the critical factors influencing human health, particularly given the amount of time people spend indoors. This study investigated the impact of real-life kitchen human activity (KHA) on IAQ. We used low-cost sensors to measure real-time concentrations of smoke, carbon monoxide (CO), and particulate matter (PM10 and PM2.5) in the kitchen of a household with three adults, analysing KHAs by dividing them into five categories. The fixed effect model was employed to analyse the data, explaining the impact of different KHAs on IAQ. The results showed that compared to other KHAs, using the gas stove had the greatest impact on IAQ, with average increases of 13% in smoke, 24.4% in CO, 9.8% in PM10, and 5.34% in PM2.5. The study also found that without windows and with insufficient ventilation, only using the range hood cannot effectively and obviously reduce PM levels. These findings highlight the need for comprehensive IAQ management strategies and further research. Despite its limitations, this study also validated the potential of low-cost sensors in IAQ monitoring.