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The gastrointestinal (GI) tract, particularly the colon region, holds a highly diverse microbial community that plays an important role in the metabolism, physiology, nutrition, and immune function of the host body. Accumulating evidence has revealed that alteration in these microbial communities is the pivotal step in developing various metabolic diseases, including obesity, inflammatory bowel disease (IBD), and colorectal cancer. However, there is still a lack of clear understanding of the interrelationship between microbiota and diet as well as the effectiveness of chemoprevention strategies, including pre and probiotic agents in modifying the colonic microbiota and preventing digestive diseases. Existing methods for assessing these microbiota-diet interactions are often based on samples collected from the feces or endoscopy techniques which are incapable of providing information on spatial variations of the gut microbiota or are considered invasive procedures. To address this need, here we have developed an electronic-free smart capsule that enables site-specific sampling of the gut microbiome within the proximal colon region of the GI tract. The 3D printed device houses a superabsorbent hydrogel bonded onto a flexible polydimethylsiloxane (PDMS) disk that serves as a milieu to collect the fluid in the gut lumen and its microbiome by rapid swelling and providing the necessary mechanical actuation to close the capsule after the sampling is completed. The targeted colonic sampling is achieved by coating the sampling aperture on the capsule with a double-layer pH-sensitive enteric coating, which delays fluid in the lumen from entering the capsule until it reaches the proximal colon of the GI tract. To identify the appropriate pH-responsive double-layer coating and processing condition, a series of systematic dissolution characterizations in different pH conditions that mimicked the GI tract was conducted. The effective targeted microbial sampling performance and preservation of the smart capsule with the optimized design were validated using both realistic in vitro GI tract models with mixed bacteria cultures and in vivo with pigs as an animal model. The results from 16s rRNA and WideSeq analysis in both in vitro and in vivo studies showed that the bacterial population sampled within the retrieved capsule closely matched the bacterial population within the targeted sampling region (proximal colon). Herein, it is envisioned that such smart sampling capsule technology will provide new avenues for gastroenterological research and clinical applications, including diet-host-microbiome relationships, focused on human GI function and health. STATEMENT OF SIGNIFICANCE: The colonic microbiota plays a major role in the etiology of numerous diseases. Extensive efforts have been conducted to monitor the gut microbiome using sequencing technologies based on samples collected from feces or mucosal biopsies that are typically obtained by colonoscopy. Despite the simplicity of fecal sampling procedures, they are incapable of preserving spatial and temporal information about the bacteria through the gastrointestinal (GI) tract. In contrast, colonoscopy is an invasive and impractical approach to frequently assess the effect of dietary and therapeutic intake on the microbiome and their impact on the health of the patient. Here, we developed a non-invasive capsule that enables targeted sampling from the ascending colon, thereby providing crucial information for disease prediction and monitoring.

Originally developed for use in controlled laboratory settings, potentiometric ion-selective electrode (ISE) sensors have recently been deployed for continuous, in situ measurement of analyte concentration in agricultural (e.g., nitrate), environmental (e.g., ocean acidification), industrial (e.g., wastewater), and health-care sectors (e.g., sweat sensors). However, due to uncontrolled temperature and lack of frequent calibration in these field applications, it has been difficult to achieve accuracy comparable to the laboratory setting. In this paper, we propose a novel temperature self-calibration method where the ISE sensors can serve as their own thermometer and therefore precisely measure the analyte concentration in the field condition by compensating for the temperature variations. We validate the method with controlled experiments using pH and nitrate ISEs, which use the Nernst principle for electrochemical sensing. We show that, using temperature self-calibration, pH and nitrate can be measured within 0.3% and 5% of the true concentration, respectively, under varying concentrations and temperature conditions. Moreover, we perform a field study to continuously monitor the nitrate concentration of an agricultural field over a period of 6 days. Our temperature self-calibration approach determines the nitrate concentration within 4% of the ground truth measured by laboratory-based high-precision nitrate sensors. Our approach is general and would allow battery-free temperature-corrected analyte measurement for all Nernst principle-based sensors being deployed as wearable or implantable sensors.

This investigation compares and contrasts the use of meta-discourse markers in Pashto and English newspaper editorials as persuasive texts. The aforementioned markers are textual components that serve Halliday's (1985) textual and interpersonal objectives while not adding to the propositional substance of the text. Whether metadiscoursal markers were used differently in English and Pashto newspaper editorials was the main research issue. The most prevalent markers from the five subcategories of Text Connectives, Illocution Markers, Hedges, Emphatics, and Attitude Markers were initially found in both English and Pashto newspapers. The frequency of appearance of these markers was then noted in a corpus of 34 editorials (15,000 words each) that were randomly chosen from a variety of English and Pashto newspapers. The significance of the total x2 obs was then demonstrated using a two-way chi square analysis. The null hypothesis of no difference was thus categorically refuted. In order to determine the relative contributions of each subcategory to the overall x 2 value, one-way chi square analysis were employed on the subcategories. Our results showed that only two of the marker subcategories were statistically significant. The many spirits that live in the communities under study are mostly to blame for this discrepancy.

During the γ-radiation sterilization process, the levels of radiation exposure to a medical device must be carefully monitored to achieve the required sterilization without causing deleterious effects on its intended physical and chemical properties. To address this issue, here we have demonstrated the development of an all-printed disposable low-cost sensor that exploits the change in electrical impedance of a semi-interpenetrating polymer network (SIPN) composed of poly(vinyl alcohol) (PVA) and poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) as a functional polymer composite for radiation sterilization monitoring applications. Specifically, the PEDOT:PSS acts as the electrically conductive medium, while the PVA provides the ductility and stability of the printed sensors. During irradiation exposure, chain scission and cross-linking events occur concurrently in the PEDOT:PSS and PVA polymer chains, respectively. The concurrent scissoring of the PEDOT polymer and cross-linking of the PVA polymer network leads to the formation of a stable SIPN with reduced electrical conductivity, which was verified through FTIR, Raman, and TGA analysis. Systematic studies of different ratios of PEDOT:PSS and PVA mixtures were tested to identify the optimal ratio that provided the highest radiation sensitivity and stability performance. The results showed that PEDOT:PSS/PVA composites with 10 wt % PVA produced sensors with relative impedance changes of 30% after 25 kGy and up to 370% after 53 kGy (which are two of the most commonly used radiation exposure levels for sterilization applications). This composition showed high electrical impedance stability with less than ±5% change over 18 days after irradiation exposure. These findings demonstrate the feasibility of utilizing a printing technology for scalable manufacturing of low-cost, flexible radiation sensors for more effective monitoring of radiation sterilization processes.

Many commercially available pH sensors are fabricated with a glass membrane as the sensing component because of several advantages of glass-based electrodes such as versatility, high accuracy, and excellent stability in various conditions. However, because of their bulkiness and poor mechanical properties, conventional glass-based sensors are not ideal for wearable or flexible applications. Here, we report for the first time the fabrication of a flexible glass-based pH sensor suitable for biomedical and environmental applications where flexibility and stability of the sensor are critical for long-term and real-time monitoring. The sensor was fabricated via a simple and facile approach using the cold atmospheric plasma technique in which a pH sensitive silica coating was deposited from a siloxane precursor onto a carbon electrode. In order to increase the sensitivity and stability of the sensor, we employed a postprocessing step which involves annealing of the silica coated electrode at elevated temperatures. This process was optimized to ensure that the crucial properties such as porosity and hydration functionality were balanced to obtain the best and most reliable sensitivity of the sensor. Our sensitivity test results indicated that these sensors exhibit excellent and stable sensitivity with a slope of about 48 mV/pH (

This work illustrates the development of a low-cost wireless sensor tag that could be placed in packaged medical products to accurately monitor the level of radiation exposure during the sterilization process.

Here we report a simple approach to increase the stability performance of all-solid-state electrochemical sensors by improving the interfacial bonding between the ion selective membrane and electrode through cold atmospheric plasma surface treatment.

Few inverse data envelopment analysis (DEA) models have incorporated non-discretionary measures based on radial efficiency values. However, the efficiency may be miscounted in radial approaches when some non-zero slacks appear. Furthermore, there is scant research on inverse DEA to estimate performance measures in the restaurant industry. Accordingly, this research proposes models based on non-radial DEA to analyze the efficiency and output changes of some Iranian restaurants while also presenting non-discretionary measures. Actually, in the company of non-discretionary factors, a non-radial DEA approach and its inverse problem are introduced to assess the performance and estimate the outputs for the modifications of inputs, respectively, while the inefficiency levels are maintained (and when they are preserved or decreased). The inefficiency of each discretionary input and output is specified using the presented non-radial DEA approach, and output targets are determined through inverse non-radial DEA with non-discretionary inputs. The results show containing non-discretionary data leads to more rational determinations through non-radial DEA-founded problems. This research presents analytic insights into the resources of inefficiency and output targets of entities with non-discretionary data, such as restaurants.

Contamination of meat with pathogenic microorganisms can cause severe illnesses and food waste, which has significant negative impacts on both general health and the economy. In many cases, the expiration date is not a good indicator of meat freshness as there is a high risk of contamination during handling throughout the supply chain. Many biomarkers, including color, odor, pH, temperature, and volatile compounds, are used to determine spoilage. Among these, pH presents a simple and effective biomarker directly linked to the overgrowth of bacteria and degradation of the meat tissue. Low-cost methods for wireless pH monitoring are crucial in detecting spoilage on a large commercial scale. Existing technologies are often limited to short-range detection, with the use of batteries and different electronic components that increases both the manufacturing complexity and cost of the final device. To address these shortcomings, we have developed a cost-effective wireless pH sensor, which uses passive resonant frequency (RF) sensing, combined with a pH-responsive polymer that can be placed within packaged meat products and provide a remote assessment of the risk of microbial spoilage throughout the supply chain. The sensor tag consists of a sensing resonator coated with a pH-sensitive material and a passivated reference resonator operating in a differential frequency configuration. Upon exposure to elevated pH levels6.8, the coating on the sensing resonator dissolves, which in turn results in a distinct change in the resonant frequency with respect to the reference resonator. Systematic theoretical and experimental results at different pH levels demonstrated that a 20% shift in resonant frequency demarcates the point for spoilage detection. As a proof of concept, the performance of the sensor in remotely detecting the risk of food spoilage was validated in packaged poultry over 10 days. The sensor fabrication process takes advantage of recent developments in the scalable manufacturing of flexible, low-cost devices, including selective laser etching of metalized plastic films and doctor-blade coating of stimuli-responsive polymer films. Furthermore, the biocompatibility of all the materials used in the sensor was confirmed with human intestinal cells (HCT-8 cells).

The problematic combination of a rising prevalence of skin and soft tissue infections and the growing rate of life-threatening antibiotic resistant infections presents an urgent, unmet need for the healthcare industry. These evolutionary resistances originate from mutations in the bacterial cell walls which prevent effective diffusion of antibiotics. Gram-negative bacteria are of special consideration due to the natural resistance to many common antibiotics due to the unique bilayer structure of the cell wall. The system developed here provides one solution to this problem through a wearable therapy that delivers and utilizes gaseous ozone as an adjunct therapy with topical antibiotics through a novel dressing with drug-eluting nanofibers (NFs). This technology drastically increases the sensitivity of Gram-negative bacteria to common antibiotics by using oxidative ozone to bypass resistances created by the bacterial cell wall. To enable simple and effective application of adjunct therapy, ozone delivery and topical antibiotics have been integrated into a single application patch. The drug delivery NFs are generated via electrospinning in a fast-dissolve PVA mat without inducing decreasing gas permeability of the dressing. A systematic study found ozone generation at 4 mg/h provided optimal ozone levels for high antimicrobial performance with minimal cytotoxicity. This ozone treatment was used with adjunct therapy delivered by the system in vitro. Results showed complete eradication of Gram-negative bacteria with ozone and antibiotics typically used only for Gram-positive bacteria, which showed the strength of ozone as an enabling adjunct treatment option to sensitize bacteria strains to otherwise ineffective antibiotics. Furthermore, the treatment is shown through biocompatibility testing to exhibit no cytotoxic effect on human fibroblast cells.

Typical soil health assessment requires intensive field sampling and laboratory analysis. Although this approach yields accurate results, it can be costly and labor intensive and not suitable for continuous tracking of soil properties. Advances in soil sensor and wireless technologies are poised to replace physical sampling and offline measurement with in-field monitoring. This article reports the development, deployment, and validation of an Internet-of-Things (IoT) system for continuous monitoring of soil health. The end nodes of the proposed system, called soil health monitoring units (SHMUs), are solar powered and can be installed on a field for extended periods of time. Each SHMU transmits soil temperature, moisture, electrical conductivity, carbon dioxide (CO2), and geolocation data wirelessly using long-range wide-area network (LoRaWAN) radio technology. Data are received by a LoRaWAN gateway, which uploads it to a server for long-term storage and analysis. Users can view acquired data through a Web-based dashboard. The following significant experiments were carried out to validate the developed system: 1) a network consisting of eight SHMUs was deployed at an agricultural field site for several weeks and soil health metrics were analyzed using the soil health dashboard; 2) the flexibility of the system was demonstrated by the addition of an extra CO2 sensor allowing an additional variable directly linked to soil health to be recorded; 3) a wireless communication range of 3422 m was estimated at a transmission power of 10 dBm by deploying the developed system on a large field; 4) the average current consumption of a SHMU (including its associated sensors) was estimated to be 13 mA, at this rate, the onboard Li-ion battery is able to sustain a SHMU for several days; and 5) a 7 cm $\times6.5$ cm solar panel was able to fully charge the onboard battery in 14 days while supplying power to the SHMU.

Roll-to-roll printing has significantly shortened the time from design to production of sensors and IoT devices, while being cost-effective for mass production. But due to less manufacturing tolerance controls available, properties such as sensor thickness, composition, roughness, etc., cannot be precisely controlled. Since these properties likely affect the sensor behavior, roll-to-roll printed sensors require validation testing before they can be deployed in the field. In this work, we improve the testing of Nitrate sensors that need to be calibrated in a solution of known Nitrate concentration for around 1–2 days. To accelerate this process, we observe the initial behavior of the sensors for a few hours, and use a physics-informed machine learning method to predict their measurements 24 hours in the future, thus saving valuable time and testing resources. Due to the variability in roll-to-roll printing, this prediction task requires models that are robust to changes in properties of the new test sensors. We show that existing methods fail at this task and describe a physics-informed machine learning method that improves the prediction robustness to different testing conditions (≈ 1.7× lower in real-world data and ≈ 5× lower in synthetic data when compared with the current state-of-the-art physics-informed machine learning method).

Roll-to-Roll (R2R) process is well suited for manufacturing low cost, miniaturized, solid contact Ion-selective electrodes (ISEs) of potentiometric sensors to be used for continuous monitoring of various analytes in environmental, industrial, and health-care applications. It is presumed that the intrinsic thickness variability of the R2R process would limit the accuracy of the ISE-based sensors and would make them inferior to sensors fabricated by higher precision manufacturing processes. Instead, in this paper we propose to use the intrinsic variability of R2R process as a “resource” to achieve high-accuracy sensing even when the sensors are operated in uncontrolled field conditions. This is achieved by applying a fundamentally new physics-guided statistical approach involving: (i) ‘Self calibration’ where we calculate temperature from differential measurement of the ISEs induced by R2R variability to calibrate the sensors in uncontrolled temperature condition, and (ii) ‘Quorum sensing’ where we use a collection of R2R manufactured sensors to estimate the true concentration considering credibility of each sensor calculated by Bayesian Maximum Likelihood Estimation method. With these two new techniques, we demonstrate the use of “low-precision” R2R sensors to measure nitrate concentration of an agricultural field continuously over a period of 15 days within 10% of the ground-truth measured by the traditional high-precision commercial nitrate sensor.

Inefficient soil management is a hindrance to food productivity and a contributing factor to the degradation of soil quality. Despite decades of research confirming the benefits of using sensors in effective soil management and crop yield, they are still not widely used in farms for several reasons including high cost, difficulty in large area deployment, and requirement of labor-intensive wiring. In this paper, we report a low-cost battery-less chipless wireless sensor tag that can be batch-manufactured for large-scale agricultural surveillance. The sensor tag works based on backscattering techniques for the wireless measurements of the volumetric water content (VWC) of the soil. The sensor tag consists of shorted dipole resonators whose resonance frequencies are dependent on the effective permittivity of the VWC of its surrounding soil. The resonant frequency of the sensor tag is measured by an orthogonally polarized reader antenna that observes the peak in the backscattered spectrum. As a proof-of-concept, a sensor tag with two resonators of length 10 cm and 9 cm, is buried at a depth of 10 cm in the soil and is wirelessly read from a free-space distance of 50 cm, to demonstrate its capability to measure the changes in VWC. The resonators of length 10 cm and 9 cm have demonstrated a linear change of −3.92 MHz/VWC and −4.85 MHz/VWC, respectively, within the VWC range 4-27%. By changing the functional passivation layers on the demonstrated sensor tag, this concept can be applied to a wide range of low-cost subsoil sensors for precision agriculture applications.

Copper oxide nanostructures are widely used for various applications due to their unique optical and electrical properties. In this work, we demonstrate an atmospheric laser-induced oxidation technique for the fabrication of highly electrochemically active copper oxide hierarchical micro/nano structures on copper surfaces to achieve highly sensitive non-enzymatic glucose sensing performance. The effect of laser processing power on the composition, crystallinity, microstructure, wettability, and color of the laser-induced oxide on copper (LIO-Cu) surface was systematically studied using scanning electron microscopy (SEM), grazing incidence X-ray diffraction (GI-XRD), Raman spectroscopy, energy dispersive X-ray spectroscopy (EDX), EDX-mapping, water contact angle measurements, and optical microscopy. Results of these investigations showed a remarkable increase in copper oxide composition by increasing the laser processing power. The pore size distribution and surface area of the pristine and LIO-Cu sample estimated by N2 adsorption–desorption data showed a developed mesoporous LIO-Cu structure. The size of the generated nano-oxides, crystallinity, and electroactivity of the LIO-Cu were observed to be adjustable by the laser processing power. The electrocatalytic activity of LIO-Cu surfaces was studied by means of cyclic voltammetry (CV) within a potential window of −0.8 to +0.8 V and chronoamperometry in an applied optimized potential of +0.6 V, in 0.1 M NaOH solution and phosphate buffer solution (PBS), respectively. LIO-Cu surfaces with optimized laser processing powers exhibited a sensitivity of 6950 μA mM−1 cm−2 within a wide linear range from 0.01 to 5 mM, with exceptional specificity and response time (

Topical lidocaine patches are commonly used to relieve pain and suffering in various clinical and household settings. Despite its extensive use, excessive skin absorption during numbing or pain reduction procedures can cause systemic toxicity, which can lead to life-threatening conditions. Rapid and reliable monitoring of escalating levels of lidocaine in the blood could help management/prevention of lidocaine overdose and its associated complications. To address this need, here we have developed a disposable point-of-care (POC) diagnostic platform composed of an integrated graphene-based electrochemical sensor with paper-based microfluidics for rapid detection of lidocaine levels in serum and blood samples. The fabrication process takes advantage of advanced, scalable manufacturing techniques, including printing, laser processing, and nondestructive near infrared (NIR) drying. The sensitivity tests of the platform revealed a sensitivity of ∼0.2 μA μM

The growing pervasiveness of opioid-based drugs such as fentanyl and its analogs represent a foremost hazard to the civilian population and burden on the first responders and clinicians. Thus, to enable a rapid and low-cost surveillance system to detect fentanyl in a non-ideal environment, we demonstrate the use of laser-induced nano-porous carbon structures directly onto commercially available polyimide sheets for rapid and cost-effective manufacturing of electrochemical sensors for fentanyl detection. The porous carbon surface instigated by various laser energy densities was analyzed towards morphological, vibrational, and fentanyl sensing properties. The results showed that laser carbonized electrode (LCE) prepared with 31 J/cm

Despite the great advancement and wide use of titanium (Ti) and Ti-based alloys in different orthopedic implants, device-related infections remain the major complication in modern orthopedic and trauma surgery. Most of these infections are often caused by both poor antibacterial and osteoinductive properties of the implant surface. Here, we have demonstrated a facile two-step laser nanotexturing and immobilization of silver onto the titanium implants to improve both cellular integration and antibacterial properties of Ti surfaces. The required threshold laser processing power for effective nanotexturing and osseointegration was systematically determined by the level of osteoblast cells mineralized on the laser nanotextured Ti (LN-Ti) surfaces using a neodymium-doped yttrium aluminum garnet laser (Nd:YAG, wavelength of 1.06 μm). Laser processing powers above 24 W resulted in the formation of hierarchical nanoporous structures (average pore 190 nm) on the Ti surface with a 2.5-fold increase in osseointegration as compared to the pristine Ti surface. Immobilization of silver nanoparticles onto the LN-Ti surface was conducted by dip coating in an aqueous silver ionic solution and subsequently converted to silver nanoparticles (AgNPs) by using a low power laser-assisted photocatalytic reduction process. Structural and surface morphology analysis via XRD and SEM revealed a uniform distribution of Ag and the formation of an AgTi-alloy interface on the Ti surface. The antibacterial efficacy of the LN-Ti with laser immobilized silver (LN-Ti/LI-Ag) was tested against both Gram-positive (

In this paper, we present a novel laser-induced oxidation procedure for in-situ formation of nickel oxide nanoporous structures directly onto the nickel surface as highly sensitive non-enzymatic gl...