MEMS (Micro-electromechanical Systems) becomes important increasingly due to the smarter and smaller fuze used in OICW (Objective Individual Combat Weapon). MEMS Safety and Arming (S&A) device is employed in different platforms and regions for small caliber projectile. Therefore, it is necessary to make a parametric study of the MEMS S&A device in different apply environments and explore the main sensitive factors of the MEMS S&A device to provide reference for designs. In this paper, based on the MEMS S&A device designed by our term, theory and finite element models are established, and the centrifugal insurance mechanism of the MEMS S&A device is parametric studied under the different speeds, temperature and thickness of the model by nonlinear dynamic method. By comparing the experimental and predicted results, the established FEM model is verified, and the conclusion is that the temperature and the centrifugal force are the main sensitive factors in the centrifugal insurance mechanism. In summary, we can suggest that the application environment, which the MEMS S&A device is suitable for, is the temperature equal to or slightly greater than normal temperature and the rotating speed higher than35000r/min of small caliber projectile.

Many theoretical models of iron-based superconductors have been proposed but Tc calculations based on the models are usually missing. We have chosen two models of iron-based superconductors in the literature and then compute the Tc values accordingly: Recently two models have been announced which suggest that superconducting electron concentration involved in the pairing mechanism of iron-based superconductors may have been underestimated, and that the antiferromagnetism and the induced xy potential may even have a dramatic amplification effect on electron-phonon coupling. We use bulk FeSe, LiFeAs and NaFeAs data to calculate the Tc based on these models and test if the combined model can predict the superconducting transition temperature (Tc) of the nanostructured FeSe monolayer well. To substantiate the recently announced xy potential in the literature, we create a two-channel model to separately superimpose the dynamics of the electron in the upper and lower tetrahedral plane. The results of our two-channel model support the literature data. While scientists are still searching for a universal DFT functional that can describe the pairing mechanism of all iron-based superconductors, we base on the ARPES data to propose an empirical combination of DFT functional for revising the electron-phonon scattering matrix in the superconducting state, which ensures that all electrons involved in iron-based superconductivity are included in the computation. Our computational model takes into account this amplifying effect of antiferromagnetism and the correction of the electron-phonon scattering matrix together with the abnormal soft out-of-plane lattice vibration of the layered structure, which allows us to calculate theoretical Tc values of LiFeAs, NaFeAs and FeSe as a function of pressure that correspond reasonably well to the experimental values. More importantly, by taking into account the interfacial effect between an FeSe monolayer and its SrTiO3 substrate as an additional gain factor, our calculated Tc value is up to 91 K high, and provides evidence that the strong Tc enhancement recently observed in such monolayers with Tc reaching 100 K may be contributed from the electrons within the ARPES range.

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that alt-hough preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance and an uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limit-ing factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bac-terial proteins are targeted being the biosynthesis of the cell wall and the energetic metabolism two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and how chemical probes for protein profiling enabled the identification of new targets and bi-omarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.

Lake Rawapening, Semarang Regency, Indonesia, has incorporated a holistic plan in its management practices. However, despite successful target achievements, some limitations remain that a review of its management plan is needed. This paper identifies and analyzes existing lake management strategies as a standard specifically in Lake Rawapening by exploring various literature, both legal frameworks and scholarly articles indexed in Google Scholar and published in Water by MDPI about lake management in many countries. There are two major types of lake management, namely pillar-based and object-based. While the former is the foundation of a conceptual paradigm that does not comprehensively consider the roles of finance and technology in the lake management, the latter indicates the objects to manage so as to create standards or benchmarks for the implementation of various programs. Overall, Lake Rawapening management should include more programs on erosion-sedimentation control and monitoring of operational performance using information systems.

Nature-based solutions (NbS) are increasingly recognised for their potential to address both the climate and biodiversity crises. These outcomes are interdependent, and both rely on the capacity of NbS to support and enhance the health of an ecosystem: its biodiversity, the condition of its abiotic and biotic elements, and its capacity to function normally despite environmental change. However, while understanding of ecosystem health outcomes of nature-based interventions for climate change mitigation is growing, the outcomes of those implemented for adaptation remain poorly understood with evidence scattered across multiple disciplines. To address this, we conducted a systematic review of the outcomes of 109 nature-based interventions for climate change adaptation using 33 indicators of ecosystem health across eight broad categories (e.g. diversity, biomass, ecosystem functioning and population dynamics). We showed that 88% of interventions with positive outcomes for climate change adaptation also reported measurable benefits for ecosystem health. We also showed that interventions were associated with a 67% average increase in local species richness. All eight studies that reported benefits in terms of both climate change mitigation and adaptation also supported ecosystem health, leading to a triple win. However, there were also trade-offs, mainly for forest management and creation of novel ecosystems such as monoculture plantations of non-native species. Our review highlights two major limitations of research to date. First, only a limited selection of metrics are used to assess ecosystem health and these rarely include key aspects such as functional diversity and habitat connectivity. Second, taxonomic coverage is poor: 67% of outcomes assessed only plants and 57% did not distinguish between native and non-native species. Future research addressing these issues will allow the design and adaptive management of NbS to support healthy and resilient ecosystems, and thereby enhance their effectiveness for meeting both climate and biodiversity targets.

In this paper, the single event burnout(SEB) and reinforcement structure of 1200V SiC MOSFET (SG-SBD-MOSFET) with split gate and schottky barrier diode(SBD) embedded were studied. The device structure was established using Sentaurus TCAD, and the transient current changes of single event effect(SEE), SEB threshold voltage, as well as the regularity of electricfield peak distribution transfer were studied when heavy ions were incident from different regions of the device. Based on SEE analysis of new structural device, two reinforcement structure designs for SEB resistance were studied, namely the expansion of P+body contact area and the design of multi-layer N-type interval buffer layer. Firstly, two reinforcement schemes for SEB were analyzed separately, and then comprehensive design and analysis were carried out. The results showed that the SEB threshold voltage of heavy ions incident from the N+source region was increased by 16% when using the P+body contact area extension alone; When the device is reinforced with multi-layer N-type interval buffer layer alone, the SEB threshold voltage increases by 29%; The comprehensive use of P+body contact area expansion and multi-layer N-type interval buffer layer reinforcement increased the SEB threshold voltage by 33%. Overall, the breakdown voltage of the reinforced device decreased from 1632.935V to 1403.135V, which can be seen as reducing the remaining redundant voltage to 19%. The device performance was not significantly affected.

In this paper, a 100CMM regenerative thermal oxidizer (RTO) system based on a high heating device for low-emission combustion is implemented at a volatile organic compound (VOCs) gas generation workplace. Existing RTO has a structure that repeats the inflow and discharge of VOCs gas into a cylindrical drum-type rotating disk and has excellent energy efficiency with a heat recovery rate of 95% or more. However, when used for a long time, there is a problem that rotation stops or explodes due to the discharge of pollutants due to dust and thermal expansion due to high temperature of 800℃. To overcome this, a RTO based on a high heating device was developed to reduce low-emission combustion emissions and energy use. Through 177 hours of demonstration time, the oxidation efficiency of VOCs was 98.87%; the waste heat recovery rate was reduced by 95.78%, the fuel consumption was reduced by 21.95%, and the nitrogen oxide concentration was 3.9 ppm

Dermal injections of hyaluronic acid gel for aesthetic skin rejuvenation are increasingly popular nowadays. Although these products are classified as medical devices, the regulations on their administration by licensed practitioners are still weak, whereas their manufacturers increasingly highlight and advertise the cellular effects that underpin the efficacy of these injections. In this re-view, we discuss all current knowledge on the mode of action of dermally injected hyaluronic acid and the potential toxicological implications especially from crosslinked gels in conjunction with the current global regulations. We conclude that dermal injections of hyaluronic acid have several therapeutic implications that warrant further research, and that strict regulations must be applied on their manufacture/quality control and the required qualifications of licensed aesthetic injectors.

In this paper, a 100CMM regenerative thermal oxidizer (RTO) system based on a high heating device for low-emission combustion is implemented at a volatile organic compound (VOCs) gas generation workplace. Existing RTO has a structure that repeats the inflow and discharge of VOCs gas into a cylindrical drum-type rotating disk and has excellent energy efficiency with a heat recovery rate of 95% or more. However, when used for a long time, there is a problem that rotation stops or explodes due to the discharge of pollutants due to dust and thermal expansion due to high temperature of 800℃. To overcome this, a RTO based on a high heating device was developed to reduce low-emission combustion emissions and energy use. Through 177 hours of demonstration time, the oxidation efficiency of VOCs was 97.87%; the waste heat recovery rate was reduced by 95.78%, the fuel consumption was reduced by 21.95%, and the nitrogen oxide concentration was 3.9 ppm

In this work, Al-Mo-B(CN) thin coatings were deposited by magnetron sputtering using composite metal-ceramic Al-Mo-B4C target. A metal-ceramic composite target for magnetron sputtering was fabricated by a robotic complex for detonation spraying of coatings equipped with a multi-chamber detonation accelerator. The powder composition (30Mo-30Al-40B4C) was sprayed onto the copper plate base of the composite target-cathode. The obtained cathode target with Al-Mo-B4C coating (thickness 280-300 μm) was used to deposit the Al-Mo-B(CN) coating (DC mode) on flat specimens of AISI 316 steels and silicon using equipment for magnetron sputtering UNICOAT 200. The Al-Mo-B4C coating has a lamella-type structure with inclusions of boron car-bide particles the elemental composition is evenly distributed in the material. The structure and morphology of coatings were studied using methods of optical, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray analysis (XRD), and X-ray photoelectron spectros-copy (XPS). Mechanical and tribological properties of the Al-Mo-B(CN) thin coatings were determined using methods of nanoindentation, scratch testing, and tribological testing under fluid-free friction regime at room temperature. The Al-Mo-B(CN) coating (thickness ~ 1 μm) exhibited a dense uniform fine-grained structure with no columnar elements and were well-adherent to the substrates after deposition. Al-Mo-B(CN) coating has a amorphous structure. XPS analysis confirmed the formation of the MoB2 and AlN phase with an admixture of oxygen in the form of aluminum oxide, molybdenum oxide and boron oxide. Al-Mo-B(CN) coating possess hardness of 13 GPa, elasticity modulus of 114 GPa, elastic recovery of 45%, and friction coefficient of 0.8 against steel 100 Cr6 ball. The failure mode occurring in the tested coatings was fatigue and abrasive. The adhesion strength of Al-Mo-B(CN) coating amounted to about 11 N, and the failure mode was cohesive associated with plastic deformation and formation of fatigue cracks in the coating material.

Acute myocardial infarction (AMI) is a leading cause of morbidity and mortality worldwide. This study aimed to test the efficacy of a newly-developed symptom self-management program on health outcomes among inpatients post-AMI. A pilot randomised, controlled trial was utilised. A convenience sample of 90 was recruited from a tertiary hospital in Singapore. Adult inpatients with post-AMI were randomly assigned to the three groups: IManage-HSet, IManage-FF or control group. Sample size was computed using power analysis. Data were collected through self-reported questionnaires and physiological instruments. Data analyses included univariate statistics, analysis of variance and repeated measure analysis of variance. Ninety participants were recruited with 30 in each group. Participants in the IManage-HSet and IManage-FF group had significantly greater relaxation (ηp2 = 0.11), lower objective stress (ηp2 =0.14), and greater knowledge (ηp2 = 0.62) than those of the control group. The two intervention groups had lower subjective stress (ηp2 = 0.04), depression (ηp2 = 0.01), and anxiety (ηp2 = 0.03) than the control but such differences did not achieve statistical significance. Furthermore, most participants reported that they were satisfied with the programs and they provided positive comments on the contents, educational materials and relaxation practice. This pilot study supports the potential benefits and feasibility of the IManage-VR and IManage-FF interventions on stress, perceived relaxation, knowledge and patient satisfaction. Contents of the symptom management interventions could be added into current cardiac rehabilitation programs. Future RCTs with multi-centered sites and larger sample size are required to further test the intervention. This study was prospectively registered with the International Standard Randomised Controlled Trial on the 5th August 2014 with registration number ISRCTN61027816.

Silicon-based microchannel technology offers unmatched performances for cooling high energy physics silicon-pixels detectors. Although Si-Si direct bonding, used for the fabrication of cooling plates, meets the stringent requirements of this application, in particular high-pressure resistance (~200 bar), it is reported to be a challenging and expensive process. In this work, we have evaluated two alternative bonding methods towards a more cost-effective fabrication process: Si-Glass-Si anodic bonding (AB) with a thin-film glass and Au-Au thermocompression (TC). The bonding strength of the two methods were evaluated with destructive pressure burst tests (0 - 690 bar) on test structures, each made of a 1×2 cm² silicon die etched with a tank and an inlet channel and sealed with a plain silicon die using AB or TC bonding. The pressure resistance of the structures was measured to be higher for the TC sealed samples (max. 690 bar) than for the AB ones (max. 530 bar) but less reproducible. The failure analysis indicates that the AB structure resistance is limited by the adhesion force of the deposited layers. Nevertheless, both the TC and AB methods provided sufficient bond quality to hold the high pressure required for the high energy physics pixel detectors cooling application.

Generation of unique identifiers extracted from the physical characteristics of the underlying hardware ensures the protection of electronic devices against counterfeiting and provides security to the data they store and process. This work describes the design of an efficient Physical Unclonable Function (PUF) based on the differences in the frequency of Ring Oscillators (ROs) with identical layout due to variations in technological processes involved in the manufacture of the integrated circuit. The logic resources available in the Xilinx Series-7 programmable devices are exploited in the design to make it more compact and achieve an optimal bit-per-area rate. On the other hand, the design parameters can also be adjusted to provide a high bit-per-time rate for a particular target device. The PUF has been encapsulated as a configurable Intellectual Property (IP) module, providing it with an AXI4-Lite interface to ease its incorporation into embedded systems in combination with soft- or hard-core implementations of general-purpose processors. The capability of the proposed RO-PUF to generate implementation-dependent identifiers has been extensively tested, using a series of metrics to evaluate its reliability and robustness for different configuration options. Finally, in order to demonstrate its utility to improve system security, the identifiers provided by RO-PUFs implemented on different devices have been used in a Helper Data Algorithm (HDA) to obfuscate and retrieve a secret key.

Patients often need the use of their arms to assist with functional activities, but after bone disruption, pushing is frequently limited to less than 4.5 kg. No method exists to measure arm weight bearing objectively in clinical settings. This project aimed to design, construct, and test a walker for patients who need to limit arm force to prevent excessive bone stress during post-fracture (iatrogenic or traumatic) ossification. First, a qualitative study was conducted to obtain critiques of a Clinical Force Measuring (CFM) walker prototype from rehabilitation professionals. Key statements and phrases were coded that allowed “themes” to emerge from transcribed interviews, which guided device revisions. Next, a second CFM Walker prototype was designed based on the qualitative data and device criteria/constraints and finally tested. The result was fabrication of a new lightweight, streamlined, and cost-effective prototype walker with a simple visual display and auditory cue with upper limit alarms. Key features included attachments for medical equipment and thin film force-sensing resistors integrated into the walker handles that progressively activated 3 LEDs and a buzzer when arm force exceeded programmed thresholds. The innovative CFM Walker will help patients with restricted arm weight bearing, especially elderly adults, recover safer and faster in the future.

Corresponding to the principles of biological synapses, an essential prerequisite for hardware neural networks using electronics devices is continuous regulation of conductance. We implemented artificial synaptic characteristics in a (GeTe/Sb2Te3)16 iPCM with a superlattice structure under optimized identical pulse trains. Based on atomically controlling the Ge switch in the phase transition that appears in the GeTe/Sb2Te3 superlattice structure, multiple conductance states were implemented by applying the appropriate electrical pulses. Furthermore, we found that the bidirectional switching behavior of a (GeTe/Sb2Te3)16 iPCM can achieve a desired resistance level using the pulse width. Therefore, we also fabricated a Ge2Sb2Te5 PCM and designed a pulse scheme based on the phase transition mechanism to compare to the (GeTe/Sb2Te3)16 iPCM. We designed an identical pulse scheme that implements linear and symmetrical LTP and LTD based on the iPCM mechanism. As a result, the (GeTe/Sb2Te3)16 iPCM showed relatively excellent synaptic characteristics by implementing gradual conductance modulation, a nonlinearity value of 0.32, and LTP/LTD 40 conductance states using identical pulses trains. Our results demonstrate the general applicability of the artificial synaptic device for potential use in neuro-inspired computing and next generation non-volatile memory.

BACKGROUND: The number of waitlisted patients requiring mechanical circulatory support (MCS) as a bridge to heart transplantation is increasing. The data concerning the results of double-bridge strategy are limited. We sought to investigate the post-transplant outcomes across the different bridge strategies. METHODS: We retrospectively reviewed a heart transplantation database from Jan 2009 to Jan 2019. Intra-aortic balloon pump (IABP), extracorporeal membrane oxygenation (ECMO), and ventricular assist devices (VAD) were the MCS that we investigated. The pre- and post-transplant characteristics and variables of patients bridged with the different types of MCS were collected. The post-transplant survival was compared using Kaplan-Meier survival analysis. RESULTS: A total of 251 heart transplants were reviewed; 115 without MCS and 136 with MCS. The patients were divided to five groups: Group 1 (no MCS): n=115; Group 2 (IABP): n=15; Group 3 (ECMO): n=33; Group 4 (ECMO-VAD): double-bridge (n=59); Group 5 (VAD): n=29. Survival analysis demonstrated that the 3-year post-transplant survival rates were significantly different among the groups (Log-rank p < 0.001). There was no difference in survival between group 4(ECMO-VAD) and group 1(no MCS)1 (p = 0.136), or between group 4(ECMO-VAD) and group 5(VAD) (p = 0.994). Group 3(ECMO) had significantly inferior 3-year survival than group 4(ECMO-VAD) and group 5(VAD). CONCLUSION: Double bridge may not lead to worse mid-term results in patients who could receive a transplantation. Initial stabilization with ECMO for critical patients before implantation of VAD might be considered as a strategy for obtaining an optimal post-transplant outcome.

Heavy metal contaminants have serious consequences for the environment and human health. Consequently, effective methods for detecting their presence, particularly in water and food, are urgently required. Accordingly, the present study proposes a sensor for the detection of mercury Hg(II) and lead Pb(II) ions using graphene oxide (GO) as a quenching agent and aptamer solu-tion as a reagent. In the proposed device, the aptamer sequences are labeled by FAM and HEX fluorescent dyes, respectively, and are mixed with 500 ppm GO solution in a microfluidic device. The presence of Hg(II) and Pb(II) ions is then detected by measuring the change in the fluores-cence intensity of the GO/aptamer suspension as the aptamer molecules undergo fluorescence resonance energy transfer (FRET). The experimental results show that the aptamer sensors have a linear range of 10~250 nM (i.e., 2.0~50 ppb) for Hg(II) ions and 10~100 nM (i.e., 2.1~20.7 ppb) for Pb(II) ions. Furthermore, the limit of detection is around 2 ppb for both metals, which is signifi-cantly lower than the maximum limits of 6 ppb and 10 ppb prescribed by the World Health Or-ganization (WHO) for Hg(II) and Pb(II) in drinking water, respectively.

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on the technologies for gait characteristic assessment, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigen-analysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order task execution process based on a Pareto optimal set algorithm that is optimized and evaluated for remotely distributed 3D printing equipment resources. Combined with the multi-objective method of data normalization, an optimization model for C3DP order execution based on the Pareto optimal set algorithm is constructed with these agents' dynamic autonomy and distributed processing. This model can perform functions such as automatic matching and optimization of candidate services, and it is dynamic and reliable in the C3DP order task execution process based on the Pareto optimal set algorithm. Finally, a case study is designed to test the applicability and effectiveness of the C3DP order task execution process based on the analytic hierarchy process and technique for order of preference by similarity to ideal solution (AHP-TOPSIS) optimal set algorithm and the Baldwin effect.

Liquorpheresis (CSF filtration) comprises a therapeutical approach that has been proposed to treat several neurological conditions where antibodies, inflammatory mediators or abnormal peptides are the cause or play an important role in the pathogenesis of the disease. CSF replacement may be an alternative approach not explored so far. Here, we review previous experiences in the use of liquorpheresis in autoimmune and degenerative neurological diseases. Then we describe previous developments and provide some new technical innovations in order to design bidirectional CSF shunting systems. These systems can be complemented either with a deposit of artificial CSF or with a CSF filter, allowing CSF replacement or liquorpheresis respectively. Both options would lead to mechanical dilution of the patient’s CSF.

Due to their increased surface area, extent of swelling and active substance loading capacity and flexibility, nanogels made from natural and synthetic polymers have gained significant interest in the scientific and industrial areas. Especially, customized design and implementation of non-toxic, biocompatible, and biodegradable micro/nano carriers makes their usage very feasible for a range of biomedical applications, including drug delivery, tissue engineering, and bioimaging. The design and application methodologies of nanogels have been outlined in this review. Additionally, the most recent advancements in nanogel biomedical applications have been discussed, with a particular emphasis on applications for the delivery of drugs and biomolecules.

Vision-based tactile sensors (VBTS) have become the de facto method of giving robots the ability to obtain tactile feedback from their environment. Unlike other solutions to tactile sensing, VBTS offers high spatial resolution feedback without compromising on instrumentation costs or incurring additional maintenance expenses. However, conventional cameras used in VBTS have a fixed update rate and output redundant data, leading to computational overhead downstream. In this work, we present a neuromorphic vision-based tactile sensor (N-VBTS) that employs observations from an event-based camera for contact angle prediction. Particularly, we design and develop a novel graph neural network, dubbed TactiGraph, that asynchronously operates on graphs constructed from raw N-VBTS streams exploiting their spatiotemporal correlations to perform predictions. Although conventional VBTS uses an internal illumination source, TactiGraph is reported to perform efficiently in both scenarios, with and without an internal illumination source. Rigorous experimental results revealed that TactiGraph achieved a mean absolute error of 0.62∘ in predicting the contact angle and was faster and more efficient than both conventional VBTS and other N-VBTS, with lower instrumentation costs. Specifically, N-VBTS requires only 5.5% of the compute-time needed by VBTS when both are tested on the same scenario.

For disciplines like biological science, security, and the medical field, link prediction is a popular research area. To demonstrate the link prediction many methods have been proposed. Some of them that have been demonstrated through this review paper are TransE, Complex, DistMult, and DensE models. Each model defines link prediction with different perceptions. We argue that the practical performance potential of these methods, having similar parameter values, using the fine-tuning technique to evaluate their reliability and reproducibility of results. We describe those methods and experiments; provide theoretical proofs and experimental examples, demonstrating how current link prediction methods work in such settings. We use the standard evaluation metrics for testing the model's ability.

Zoos are increasingly putting in place formalized animal welfare assessment programs to allow monitoring of welfare over time, as well as to aid in resource prioritization. These programs tend to rely on assessment tools that incorporate resource-based and observational animal- focused measures since it is rarely feasible to obtain measures of physiology in zoo-housed animals. A range of assessment tools are available which commonly have a basis in the Five Domains framework. A comprehensive review of the literature was conducted to bring together recent studies examining welfare assessment methods in zoo animals. A summary of these methods is provided with advantages and limitations of the approach es presented. We then highlight practical considerations with respect to implementation of these tools into practice, for example scoring schemes, weighting of criteria, and innate animal factors for consideration. It is concluded that would be value in standardizing guidelines for development of welfare assessment tools since zoo accreditation bodies rarely prescribe these. There is also a need to develop taxon or species- specific assessment tools to inform welfare management.

Herein we report the expansion of the chemical space available from the chitin, accessible via the biogenic N-platforms 3A5AF, M4A2C and di-HAF. The biologically active heteroaromatics furo[3,2-d]pyrimidin-4-one and furo[3,2-d]pyrimidin-4-amine can be selectively accessed from 3A5AF and M4A2C, respectively. The chiral pool synthon di-HAF is a viable substrate for the Achmatowicz rearrangement, providing streamlined access to 2-aminosugars possessing a versatile hydroxymethyl group at C5.

The evolution of photovoltaic cells is intrinsically linked to advancements in the materials from which they are fabricated. This review paper provides an in-depth analysis of the latest developments in silicon-based, organic, and perovskite solar cells, which are at the forefront of photovoltaic research. We scrutinize the unique characteristics, advantages, and limitations of each material class, emphasizing their contributions to efficiency, stability, and commercial viability. Silicon-based cells are explored for their enduring relevance and recent innovations in crystalline structures. Organic photovoltaic cells are examined for their flexibility and potential for low-cost production, while perovskites are highlighted for their remarkable efficiency gains and ease of fabrication. The paper also addresses the challenges of material stability, scalability, and environmental impact, offering a balanced perspective on the current state and future potential of these material technologies.

The aim of this study was to investigate the impact of Process Oriented Guided Inquiry Learning (POGIL)-based instruction versus lecture-based instruction on Grade 12 students’ performance in circular motion unit. A quasi-experimental, pretest-posttest design, the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes: Knowing, Applying and Reasoning (KAR). The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys) and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a unit of circular motion in physics using POGIL-based instruction while the control group was taught the unit using lecture-based instruction. The findings of the study showed statistically significant differences between students of the control group and the treatment group in favor of the later regarding their circular motion performance, suggesting the superiority of the POGIL in enhancing student understanding of the circular motion.

This article investigates the prospect of implementing multidisciplinary and multicultural student teamwork (MMT) involving Case-based Learning (CBL) and Problem-based Learning (PBL) as a sustainable teaching practice. Based on a mixed methods approach, which includes direct observation (both physical and virtual), questionnaire distribution and focus-group interviews the study reveals that MMT through CBL and PBL can both facilitate and hinder sustainable learning. Our findings show that while MMT enhances knowledge sharing, it also poses a wide range of challenges, raising questions about its social significance as a sustainable teaching practice. The study suggests the implementation of certain mechanisms, such as ‘Teamwork Training’ and ‘Pedagogical Mentors’, aiming to strengthen the sustainable orientation of MMT through CBL and PBL.

In MBSE there is yet no converged terminology. The term ’system model’ is used in different contexts in literature. In this study we elaborated the definitions and usages of the term ’system model’, to find a common definition. 104 publications have been analyzed in depth for their usage and definition as well as their meta-data e.g., the publication year and publication background to find some common patterns. While the term is gaining more interest in recent years it is used in a broad range of contexts for both analytical and synthetic use cases. Based on this three categories of system models have been defined and integrated into a more precise definition.

This article discusses the use of game design as a method for interdisciplinary project-based teaching in secondary school education to convey informatics and society topics. There is a lot of knowledge about learning games but little background on project-based teaching using game design as a method. We present the results of an analysis of student-created games and an evaluation of a student-authored database on learning contents found in commercial off-the-shelf games. We further contextualise these findings using a group discussion with teachers. Results underline the effectiveness of project-based teaching to raise awareness for informatics and society topics. We further outline informatics and society topics that are particularly interesting to students, genre preferences and potentially engaging game mechanics stemming from our analyses.

The ubiquity of mobile sensors (such as GPS, accelerometer and gyroscope) together with increasing computational power have enabled an easier access to contextual information, which proved its value in next generation of the recommender applications. The importance of contextual information has been recognized by researchers in many disciplines, such as ubiquitous and mobile computing, to filter the query results and provide recommendations based on different user status. A context-aware recommendation system (CoARS) provides a personalized service to each individual user, driven by his or her particular needs and interests at any location and anytime. Therefore, a contextual recommendation system changes in real time as a user’s circumstances changes. CoARS is one of the major applications that has been refined over the years due to the evolving geospatial techniques and big data management practices. In this paper, a CoARS is designed and implemented to combine the context information from smartphones’ sensors and user preferences to improve efficiency and usability of the recommendation. The proposed approach combines user’s context information (such as location, time, and transportation mode), personalized preferences (using individuals past behavior), and item-based recommendations (such as item’s ranking and type) to personally filter the item list. The context-aware methodology is based on preprocessing and filtering of raw data, context extraction and context reasoning. This study examined the application of such a system in recommending a suitable restaurant using both web-based and android platforms. The implemented system uses CoARS techniques to provide beneficial and accurate recommendations to the users. The capabilities of the system is evaluated successfully with recommendation experiment and usability test.

Especially in the last two decades, due to the developments in durable mechanical circulatory support (MCS) technology and applications, left ventricular assist (LVAD) implantation has become used in more fragile end-stage heart failure patients with higher risk. Despite advances in technology and patient care processes, right heart failure remains the leading cause of morbidity and mortality after durable LVAD implantation. It is difficult to make decisions about the type and duration of MCS during preoperative evaluation, and many clinical, hemodynamic, biochemical and echocardiographic criteria must be taken into account when evaluating the right ventricle. Complex quantitative scoring systems, including measurements of different risk factors for postimplant right ventricular failure, and composite variables, including the anatomical and functional status of the right ventricle, have been used to decide between left or biventricular assist device implantation. The successful use of artificial intelligence (AI) and machine learning (ML) in various applications in the medical field has paved the way for the idea of using it to better predict possible conditions such as right heart failure after LVAD implantation. This review aims to evaluate the current situation of risk prediction models using AI and ML technology, which have become popular in recent years, and possible future developments in predicting right heart failure after the application of durable MCS systems.

Background: Patients with infectious complications related to the presence of cardiac implantable electronic devices (CIED) constitute a heterogeneous group, including local pocket infection (PI) and lead related infectious endocarditis (LRIE). The diagnosis of CIED-related infection is often difficult and requires complex imaging and microbiological tests. The aim of the current study was to evaluate the usefulness of new simple hematological parameters in detecting infectious complications in patients with CIED and assessing their extent. Methods: The retrospective analysis of clinical data of 2909 patients (36.37% with CIED-related infections), undergoing transvenous lead extraction (TLE) procedures in three high-volume centres in the years 2006-2020, was conducted. The sensitivity and specificity of new hematological markers were evaluated: the neutrophil to lymphocyte ratio (NLR), neutrophil to platelet ratio (NPR), and lymphocyte to platelet ratio (LPR) in the diagnosis of infectious complications, assessment of the spread of the infectious process and differentiation of additional structures related to the presence of leads. Results: In patients with CIED infections, compared to the non-infectious group, high inflammatory parameters were confirmed, and the highest specificity of the new markers in detecting the infectious process was demonstrated. (79.47% for NPR and 72.82% for NLR). Analysis of laboratory parameters in infectious and non-infectious patients with the presence of additional lead-related masses showed the highest specificity of NPR (82,78%) in predicting the diagnosis of vegetation. Comparison of laboratory parameters in patients with LRIE and PI showed higher NLR % (4.24 vs 2.56; p<0.001, area under curve (AUC) in a receiver operating characteristic (ROC) curve: 0.67 and 0.78 respectively) and higher NPR (0.03 vs 0.02; p<0.001; AUC: 0,51 and 0,55) in patients with LRIE. The highest sensitivity in the detection of coexistence LRIE with PI has been demonstrated for NLR (87.33%). Conclusions: Novel hematological markers may be helpful in the recognition of the inflammatory process in patients with CIED, differentiation of vegetation and vegetation-like masses, and the extent of infection in patients with PI.

The effects of the solvent used for the active layer materials of an OLED based on TADF emitters plays a fundamental role in solution-deposited devices. This work focuses the effects on the performance of different solvents employed to fabricate a very simple two organic layer OLED based on a green TADF emitter, under the concept of host:guest matrix. From the different results of the main figures of merit, it was possible to conclude that the OLED that used toluene as solvent for the active layer reached a maximum EQE of 14%, almost the maximum already obtained for this emitter in more complex device structures. With the analysis of the charge transport processes, it was possible to establish an explanatory model for the obtained results. Through impedance spectroscopy, additional characterization about the nature of charge transport processes was carried out. With these results, it was possible to corelate the relaxation times, with the electrical properties of the active layer, and infer about the interaction between the electrical charges and the defect levels opening new possibilities to further development in the printed OLEDs.

A recently proposed single image parasite quantification (SIMPAQ) platform based on a Lab-On-a-Disc (LOD) device has been earlier successfully tested in field conditions demonstrating the efficiency in soil-transmitted helminths (STH) egg detection and analysis. A related study (Micromachines 2021, 12, 1032) revealed the effects that can limit the performance of a SIMPAQ method due to the action of the Euler and Coriolis forces, and the interaction of the moving eggs with the walls of the LOD chamber. Here we propose a new improved design that allows to overcome those limitations and enhance the yield of the SIMPAQ LOD device which is demonstrated in the experiments with synthetic particle model system and real parasite eggs.

Background: Sensor usage in the classical scientific process has allowed new experimentation in medicine. We report on the design process of a MEMS sensor being used for muscle trauma evaluation in diagnosing acute compartment syndrome (ACS), a medical ailment costing society billions of dollars per year. Objectives: Modeling the disease with scientific process allows a more complete under-standing of the disease. The goal was to formulate a hypothesis that could be tested to aid in making the diagnosis of ACS accurately. Methods: Scientific process was observed throughout the disease modelling process. Background information was improved and clarified, new pre-clinical models were de-signed and verified, a hypothesis built on pressure measurement with MEMS sensors was carried out, and the testing of the model as verified against previous clinical data was accomplished. Results: Scientific process resulted in hypothesis generation around the relationship of intracompartmental pressure measurement and the disease process and therapy. This resulted in new understanding of ACS, accurate modelling, and sensor design resulting in a MEMS device that has an extremely high sensitivity and specificity (over 99%) in treating and diagnosing the disease. Conclusion: MEMS sensor technology defines the new gold standard of implanting a sensor in a muscle compartment that allows accurate diagnosis of ACS with continuous trends in pressure.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P&lt;0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

Although the relations between sleep and academic performance have been extensively examined, how sleep predicts future academic performance (e.g., 2 -3 years) remains to be further investigated. Using wearable smartwatches and a self-report questionnaire, we tracked sleep activities of 45 college students over a period of approximate half a month to see whether their sleep activities predicted their academic performance, which was estimated by grade point average (GPA). Results showed that both nighttime sleep awakening frequency and its consistency in the tracking period were not significantly correlated with the GPA for the courses taken in the semester during sleep tracking (current GPA). However, both nighttime sleep awakening frequency and its consistency inversely predicted the GPA for the rest of the courses taken after that semester (future GPA). Moreover, students with more difficulty staying awake throughout the day obtained lower current and future GPAs, and students with lower inconsistency of sleep quality obtained lower future GPA. Together, these findings highlight the importance of nighttime sleep awakening frequency and consistency in predicting future academic performance and emphasize the necessity of assessing the consistency of sleep measures in future studies.

One third of fatal car accidents and so much tragedies are due to alcohol abuse. These sad numbers could be mitigated if everyone had access to a breathalyzer anytime and anywhere. Having a breathalyzer built into a phone or a wearable could be the way to get around the reluctance to carry a separate device. Towards this goal, we propose an inexpensive breathalyzer that could be integrated in the screen of mobile devices. Our technology is based on the evaporation rate of the fog produced by the breath on the phone screen, which increases as a function of the breath alcohol content. The device simply uses a photodiode placed on the side of the screen to measure the signature of the scattered light intensity from the phone display that is guided through the stress layer of the Gorilla glass screen. A part of the display light is coupled to the stress layer via the evanescent field induced at the edge of the breath microdroplets. We demonstrate that the intensity signature measured at the detector can be linked to the blood alcohol content. We fabricated a prototype in a smartphone case powered by the phone’s battery, controlled by an application software installed in the smartphone and tested it in real-world environments. Limitations and future work toward a fully operational device are discussed.

Peptide nucleic acid (PNA) is a synthetic DNA mimic that outperforms the properties of traditional oligonucleotides (ONs). On account of its outstanding features, such as remarkable binding affinity towards complementary DNA or RNA as well as high thermal and chemical stability, PNA has been proposed as a valuable alternative to the ON probe in gene-sensor design. In this study, a hybrid transducer made-up of graphene oxide (GO) nano-sheets covalently grafted onto a porous silicon (PSi) matrix has been investigated for the early detection of a genetic cardiac disorder, the Brugada syndrome (BS). A functionalization strategy towards the realization of a potential PNA-based device is described. A peptide nucleic acid (PNA), able to detect the SCN5A associated with the BS has been properly synthesized and used as a bioprobe for the realization of a proof-of-concept label-free optical PNA-biosensor. PSi reflectance and GO photoluminescence (PL) signals were simultaneously exploited for the monitoring of the device functionalization and response.

Bone marrow-derived mesenchymal stem cells (BMSCs) have been considered a promising therapeutic approach to cardiovascular disease. This study intends to compare the effect of BMSCs through a standard active cardiac support device (ASD) and intravenous injection on global myocardial injury induced by isoproterenol. BMSCs were cultured in vitro, and the transplanted cells were labeled with a fluorescent dye CM-Dil. Isoproterenol (ISO) was injected into the rats; two weeks later, the labeled cells were transplanted into ISO-induced heart-injury rats through the tail vein or ASD device for five days. The rats were sacrificed on the first day, the third day, and the fifth day after transplantation to observe the distribution of cells in the myocardium by fluorescence microscopy. The hemodynamic indexes of the left ventricle were measured before sacrificing. H&E staining and Masson’s trichrome staining were used to evaluate the cardiac histopathology. In the ASD groups, after three days of transplantation, there were many BMSCs on the epicardial surface, and after five days of transplantation, BMSCs were widely distributed in the ventricular muscle. But in the intravenous injection group, there were no labeled-BMSCs distributed. In the ASD+BMSCs-three days treated group and ASD+BMSCs -five days-treated group, left ventricular systolic pressure (LVSP), the maximum rate of left ventricular pressure rise (+dP/dt), the maximum rate of left ventricular pressure decline (-dP/dt) increased compared with model group and intravenous injection group (P<0.05). By giving BMSCs through ASD device, cells can rapidly and widely distribute in the myocardium and significantly improve heart function.

Uniform illumination is a key requirement in different research fields. However, this requirement is often difficult to achieve when high intensity is required at the same time. Recent advancements in LED lamps allow nowadays for compact and economical solutions. In this work we present a suitable solution for various laboratory purposes requiring stable, uniform and high intensity illumination. The system is composed of four identical high power white LED arrays of 30 mm diameter each, placed on a supporting and cooling structure having a minimum volume of 26 cm x 26 cm x 8 cm. A numerical model has been developed, based on a ray tracing software, in order to simulate the performances. These have then been experimentally validated with measurements of the power density map, carried out with a 1% uncertainty pyranometer. Data show that the built system is very stable over time and provides an illumination uniformity higher than 98%, on a surface of 50 mm radius, which reduces to 95% on a surface of 75 mm radius. The power density can be adjusted in the 390-1360 W m-2 range, not affecting uniformity.

Hospital-based programs democratize mRNA therapeutics by facilitating the processes to translate a novel RNA idea from the bench to the clinic. Because mRNA is essentially biological software, therapeutic RNA constructs can be rapidly developed. The generation of small batches of clinical grade mRNA to support IND applications and first-in-man clinical trials, as well as personalized mRNA therapeutics delivered at the point-of-care, is feasible at a modest scale of cGMP manufacturing. Advances in mRNA manufacturing science and innovations in mRNA biology, are increasing the scope of mRNA clinical applications.

Drug discovery utilizes high-throughput screening (HTS) methods applying target and cell-based assays. This review discusses the challenges and benefits associated with these assays in HTS. Discussed the strategies that can be applied for the development of screening assays through primary and secondary screens for target identification. Further discussion on identify-ing the most efficacious drugs following these approaches in cancer. Even though various drugs have been identified to treat cancer, there is high demand of more relevant phenotypic assays to produce desired diseased phenotype to only highlighting the specific targets instead of off-targets. Hopefully, the new developing strategies could provide innovative drugs to treat cancer patients to reduce mortality rate.

The correlations of seismic noise, recorded during 1997-2022 at 229 stations around the world are investigated. The property of waveforms, known as the Donoho-Johnston threshold, is analyzed, which separates the absolute values of the orthogonal wavelet coefficients into "small" and "large". Network of 50 reference points is considered. For each reference point, a time series with a time step of 1 day is calculated as the median of the values of the DJ index from the 5 nearest stations. For each reference point, the correlations between the values of the DJ index at other reference points are calculated in a sliding time window of 365 days. Average values of the DJ index decrease, which is interpreted as indicators of global seismic hazard increasing. The maximum distances between reference points with strong correlations show an explosive increase after 2011. Bursts in the mean coherences between the length of day (LOD) and the values of the DJ index at the reference points precede the release of seismic energy with a delay of about 530 days. High amplitude of the DJ index response to LOD for the times 2020-2022 was identified, which may forecast a strong earthquake in the second half of 2023.

Noise in requirements has been known to be a defect in software requirements specifications (SRS). Detecting defects at an early stage is crucial in the process of software development. Noise can be in the form of irrelevant requirements that are included within a SRS. A previous study had attempted to detect noise in SRS, in which noise was considered as an outlier. However, the resulting method only demonstrated a moderate reliability due to the overshadowing of unique actor words by unique action words in the topic-word distribution. In this study, we propose a framework to identify irrelevant requirements based on the MultiPhiLDA method. The proposed framework distinguishes the topic-word distribution of actor words and action words as two separate topic-word distributions with two multinomial probability functions. Weights are used to maintain a proportional contribution of actor and action words. We also explore the use of two outlier detection methods, namely Percentile-based Outlier Detection (PBOD) and Angle-based Outlier Detection (ABOD), to distinguish irrelevant requirements from relevant requirements. The experimental results show that the proposed framework was able to exhibit better performance than previous methods. Furthermore, the use of the combination of ABOD as the outlier detection method and topic coherence as the estimation approach to determine the optimal number of topics and iterations in the proposed framework outperformed the other combinations and obtained sensitivity, specificity, F1-score, and G-mean values of 0.59, 0.65, 0.62, and 0.62, respectively.

Animal-based measures are the measure of choice in animal welfare assessment protocols as they can often be applied completely independently to the housing or production system employed. Although there has been a small body of work on potential animal-based measures for farmed crocodilians [1-3], they have not been studied in the context of an animal welfare assessment protocol. Potential animal-based measures, that could be used to reflect the welfare state of farmed crocodilians, were identified and aligned with the Welfare Quality® principles of good housing, good health, good feeding and appropriate behaviour. A consultation process with a panel of experts was used to evaluate and score the potential measures in terms of validity and feasibility. This resulted in a toolbox of measures being identified for further development and integration into animal welfare assessment on the farm. Animal-based measures related to ‘good feeding’ and ‘good health’ received the highest scores for validity and feasibility by the experts. There was less agreement on the animal-based measures that could be used to reflect ‘appropriate behaviour’. Where no animal-based measures were deemed to reliably reflect a welfare criterion nor be useful as a measure on the farm, additional measures of resources or management were suggested as alternatives. Future work in this area should focus on the reliability of the proposed measures and involve further evaluation of their validity and feasibility as they relate to different species of crocodilian and farming system.

The exploitation of lipid membranes in biosensors has provided the ability to reconstitute a considerable part of their functionality to detect trace of food toxicants and environmental pollutants. Nanotechnology enabled sensor miniaturization and extended the range of biological moieties that could be immobilized within a lipid bilayer device. This chapter reviews recent progress in biosensor technologies based on lipid membranes suitable for environmental applications and food quality monitoring. Numerous biosensing applications are presented, putting emphasis on novel systems, new sensing techniques and nanotechnology-based transduction schemes. The range of analytes that can be currently detected include, insecticides, pesticides, herbicides, metals, toxins, antibiotics, microorganisms, hormones, dioxins, etc. Technology limitations and future prospects are discussed, focused on the evaluation/ validation and eventually commercialization of the proposed sensors.

The exploitation of lipid membranes in biosensors has provided the ability to reconstitute a considerable part of their functionality to detect trace of food toxicants and environmental pollutants. Nanotechnology enabled sensor miniaturization and extended the range of biological moieties that could be immobilized within a lipid bilayer device. This chapter reviews recent progress in biosensor technologies based on lipid membranes suitable for environmental applications and food quality monitoring. Numerous biosensing applications are presented, putting emphasis on novel systems, new sensing techniques and nanotechnology-based transduction schemes. The range of analytes that can be currently detected include, insecticides, pesticides, herbicides, metals, toxins, antibiotics, microorganisms, hormones, dioxins, etc. Technology limitations and future prospects are discussed, focused on the evaluation/ validation and eventually commercialization of the proposed sensors.

Given the increase in consumers’ preferences for coffee, it is becoming important to understand their decision-making processes in the coffee chain context. To deepen the understanding of sustainable outcomes in this context, this study investigates the role of dedication- and constraint-based mechanisms in forming consumers’ repurchase and positive word-of-mouth (WOM) intentions, two critical sustainable outcomes. We examined the effects of coffee quality, the quality of the physical environment, and service quality in accelerating the formation of dedication-based factors. Moreover, this study offers an in-depth understanding of the enablers of perceived switching costs. Data collected from 238 university students that frequently visit coffee chains are empirically tested against the proposed theoretical framework by using structural equation modeling. The results confirm that both dedication- and constraint-based factors substantially predict consumers’ sustainable outcomes in the coffee chain context. Brand image and perceived switching costs play an important role in enhancing consumers’ repurchase and positive WOM intentions compared with customer satisfaction. Coffee quality is significantly associated with both customer satisfaction and brand image, whereas the quality of the physical environment and service quality are only significantly associated with brand image. Habit is found to be the key enabler of perceived switching costs, while loyalty programs have no significant impact on perceived switching costs.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

Emerging semiconductor devices often lack accurate analytical models. The same is usually true of any devices working under extreme conditions like cryogenic temperatures. The usual workaround involves the use of approximation models, usually based on lookup tables or neural networks individually fitted to measurement data. In the case of experimental devices or ones working under extreme conditions, the number of units available for measurement is limited. As a result, the number of approximation-model instances is too small to enable a statistical simulation of even middle-sized circuits, which is a necessary step in integrated-circuit design since it provides the realistic picture of the circuit’s behavior in the presence of manufacturing process variations. Approximation models using structure parameters as inputs do exist in the literature, but are only useful if the end user knows the statistical distributions of those parameters, which is not usually the case. We propose a technique based on generative machine learning, namely the variational autoencoder, that uses only a small sample of devices to capture the essential features of their I–V curves under process variations and subsequently generates an arbitrary number of similarly disturbed curves. The model trained on as few as 20 instances per device type is shown to precisely reproduce the distributions of period and power consumption of a ring oscillator.

Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium Nitride-based devices, specifically AlGaN/GaN High Electron Mobility Transistors (HEMTs) in a novel packaging design provided by STMicroelectronics S.r.l. The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of a packaging.

With continued scaling of semiconductor devices , the value of predictive analysis through 1 accurate quantum transport modeling is exponentially increasing. Quantum transmitting Boundary 2 method (QTBM) has been a well-known method of choice to model quantum transport in simple 1-D 3 devices. Here, we present an extension of the QTBM to the 2-D domain and apply it for more realistic 4 devices for accurate performance analysis.

The authors attempt to addresses the importance of timely detection and management of cervical intraepithelial neoplasia (CIN) to prevent cervical cancer. The study focuses on the potential of electrical impedance spectroscopy (EIS) as an adjunct to colposcopy, aiming to enhance the accuracy of identifying high-grade cervical lesions. Colposcopy, a widely used technique, exhibits variable sensitivity in detecting high-grade lesions, which relies on the expertise of the operator. The study's primary objective is to evaluate the effectiveness of combining colposcopy with EIS in detecting high-grade cervical lesions among patients initially diagnosed with low-grade CIN based on cytology. We employ a cross-sectional observational design, recruiting 101 women with abnormal cervical cytology results. The participants undergo colposcopy with acetic acid and subsequent EIS using the ZedScan device. The ZedScan results are categorized into color-coded probability levels, with red indicating the highest likelihood of high-grade squamous intraepithelial lesions (HSIL) occurrence. Results reveal that ZedScan exhibits a sensitivity rate of 89.5% and a specificity rate of 84% for detecting high-grade lesions. Colposcopy, on the other hand, records a sensitivity rate of 85.5% and a specificity rate of 92%. The agreement rate between ZedScan and biopsy is 79.2%, as indicated by a kappa coefficient of 0.71, while the agreement rate between colposcopy and biopsy is 74.3%, with a kappa coefficient of 0.71.

Identifying a vestibular source of pathology in patients complaining of post-traumatic brain injury (TBI) dizziness can be difficult. We describe a possible new method utilizing the reduction of post-TBI symptom (including dizziness) with the use of a noise cancellation device (NCD). This retrospective case series included patients with TBI and dizziness presenting to a binocular vision specialty clinic, who were diagnosed with a vertical heterophoria (VH). If they did not respond adequately to microprism lenses and/or if they experienced hyperacusis, they were evaluated with an NCD. If there was marked reduction of TBI symptoms (including dizziness), the patients were referred to a neuro-otologist for vestibular diagnostic evaluation and treatment. Fourteen patients were identified and found to have abnormalities on vestibular testing consistent with Third Mobile Window Disorder (TMWD). All were treated with a 6-week medical protocol (diuretics, no straining, low sodium/no caffeine diet). Five responded positively, requiring no further treatment. Nine required surgical intervention and responded positively. In conclusion, 14 patients with post-concussive dizziness and VH, a positive response to NCD was associated with abnormal vestibular testing, a diagnosis of TMWD, and symptom reduction/resolution with a medical or surgical approach. The removal of sound resulting in reduction or resolution of vestibular symptoms represents an Inverse Tullio Phenomena.

The COVID-19 pandemic resulted in government restrictions that altered the lifestyle of people worldwide. Studying the impact of these restrictions on exercise behaviors will improve our understanding of environmental factors that influence individuals’ PA. We conducted a retrospective analysis using an index of government pandemic stringency developed by Oxford and a wearable device for runners to compare strictness of lockdowns and exercise habits, using digitally-logged PA data from more than 7,000 runners on a global scale. Additionally, time-of-day of PA globally and levels of PA in 14 countries are compared between the pre-pandemic year of 2019 and the first pandemic year of 2020. We found that during the pandemic the time-of-day that people exercised experienced a major shift, with significantly more activities logged during standard working hours on workdays (p<0.001) and fewer during the same time frame on weekends (p<0.001). Of the countries examined, Italy and Spain had among the most strict lockdowns and suffered the largest decreases in activity counts, whereas France experienced a minimal decrease in activity counts despite enacting a similarly strict lockdown. This study suggests that there are several factors affecting PA, including government policy, workplace policy, and cultural norms.

A new circuit model of the self-powered device for heart rate measurement is presented in this paper. This device consists of piezoelectric energy harvester (PEH), power management circuit (PMC) with energy storage, microcontroller, Photoplethysmography (PPG) sensor, and Wi-Fi module. The PEH is placed under the insole to harvest the pressure energy from human foot-step to generate ac power. In our model, a PEH is represented by sine voltage source, where its parameters were taken from experiments with 20 volunteers. The PMC is simplified by a switch with gain δ placed in series with the main circuit. The model of the main circuit is RC elements in parallel, where C is the capacitance of the storage device, and R is the equivalent parallel resistance of the microcontroller, PPG sensor, and Wi-Fi modules, respectively. The value of R depends on the power and current absorbed by those modules during sleep, deep sleep, sense, and transmit modes which collected from the datasheet. Finally, the proposed circuit model of the self-powered device was built and simulated in SPICE. The simulation results were compared with the laboratory experiment using commercial devices. Based on the results, the proposed model had small gaps compared to the real self-powered devices in terms of average current, voltage, power and efficiency.

Low-cost RGB-D cameras are increasingly used in several research fields including human-machine interaction, safety, robotics, biomedical engineering and even Reverse Engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras proved to be among the best suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e. ~160-10000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations on the RealSense D415. In particular, tests are carried out to assess the device performances in the near range (i.e. 100-1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e. the German VDI/VDE 2634 part 2 normative) with a number of literature-based strategies. Performance analysis is finally compared against latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in Reverse Engineering applications.

Purpose: To compare the efficacy and safety of graft-free short tunnel small flap (STSF) technique with that of scleral patch graft (SPG) in Ahmed glaucoma valve (AGV) implantation. Design: Randomized clinical trial. Participants: Eighty-eyes of eighty patients with medically uncontrolled glaucoma including 41 in STSF and 39 eyes in SPG. Methods: Patients were enrolled and assigned randomly to STSF or SPG. Main Outcome Measures: tube exposure, Intraocular pressure (IOP), number of glaucoma medications, best corrected visual acuity (BCVA), surgical complications, and success rate ( defined as intraocular pressure (IOP) >5 mmHg, ≤21 mmHg, and IOP reduction ≥20% from baseline at two consecutive visits after three months, no reoperation for glaucoma). Results: only one case in SPG developed tube exposure at 1-year follow-up. The cumulative probability of success during the first year of follow-up was 70% in the STSF and 65% in SPG (P = 0.36). IOP decreased significantly from 29.6 ± 8.6 mmHg at baseline to 16.4 ± 3.6 mmHg at the final follow-up in STSF (p = 0.001). The corresponding numbers for SPG were 30.9 ± 11.2 and 15.8 ± 4.7, respectively (p = 0.001). The final IOP was comparable between both groups (p = 0.65). Mean ± standard deviation of the number of glaucoma medications was 1.8 ± 0.9 in STSF and 1.6 ± 0.9 in SPG at final follow-up (P = 0.32). Postoperative complications developed in 8 patients (19%) in STSF and 9 patients (23%) in SPG (P = 0.81). Conclusions: STSF and SPG techniques had comparable complication rate at one-year follow-up. Both techniques were comparable in terms of success rate, postoperative IOP, and glaucoma medications.

Tidal stream energy is a low carbon energy source. Tidal stream turbines operate in a turbulent environment, and the effect of the structure between the turbine and seabed on this environment is not fully understood. An experimental study using 1:72 scale models based on a commercial turbine design was carried out to study the support structure influence on turbulence intensity around turbine blades. The study was conducted using the wave-current tank at LABIMA, University of Florence. A realistic flow environment (ambient turbulent intensity = 11%) was established. Turbulence intensity was measured upstream and downstream of a turbine mounted on two different support structures (one resembling a commercial design, the other the same with an additional vertical element), in order to quantify any variation in turbulence and performance between the support structures. Turbine drive power was used to calculate power generation. Acoustic Doppler Velocimetry was used to record and calculate upstream and downstream turbulence intensity. In otherwise identical conditions, performance variation of only 4% was observed between two support structures. Turbulent intensity at 1, 3 and 5 blade diameters, both upstream and downstream, showed variation up to 21% between the two cases. The additional turbulent structures generated by the additional element of the second support structure appears to cause this effect, and the upstream propagation of turbulent intensity is believed to be permitted by surface waves. This result is significant for the prediction of turbine array performance.

Saudi Arabia is an oil-reliant nation as a large percentage of its GDP comes from oil resources. Oil dependency leaves a county at the mercy of the international crude market, and a decrease in the price of crude can seriously destabilize the economy of such nations. An example is the case of Venezuela whose dependence on oil caused a national disaster (McCarthy, 2017). As such, the nation’s exports, GDP, and government revenue are primarily dependent on oil revenue, and the recent decrease in the oil prices has decreased Venezuela’s national revenue resulting in economic collapse as well as inflation. A shift from a resource based economy to a knowledge based economy will help Saudi Arabia become less reliant on its oil revenues for its economic stability and growth (Nurunnabi, 2017).

This study focuses on enhancing controllable fibrin-based hydrogels for tissue engineering, addressing existing weaknesses. By integrating a novel copolymer, we improve the foundation for cell-based angiogenesis with adaptable structural features. Tissue engineering often faces challenges like waste disposal and nutrient supply beyond the 200 µm diffusion limit. Angiogenesis breaks through this limitation, allowing the construction of larger constructs. Our innovative scaffold combination significantly boosts angiogenesis, resulting in longer branches and more capillary network junctions. The copolymer attached to fibrin fibers enables precise adjustment of hydrogel mechanical-dynamic properties for specific applications. Our material proves effective for angiogenesis, even under suppression factors like suramin. In our study, we prepared fibrin-based hydrogels with and without the copolymer PVP12400-co-GMA10mol%. Using a co-culture system of human umbilical vein endothelial cells (HUVEC) and mesenchymal stem cells (MSC), we analyzed angiogenetic behavior on and within the modified hydrogels. Capillary-like structures were reproducibly formed on different surfaces, demonstrating the general feasibility of three-dimensional endothelial cell networks in fibrin-based hydrogels. This highlights the biomaterial's suitability for in vitro pre-vascularization of biohybrid implants.

In this study, graphite, the most stable form of carbon, was examined for its hexagonal crystalline structure with specific dimensions (ao=2.46 Ǻ; co=6.70 Ǻ). Its framework comprises parallel carbon atom planes forming regular hexagons (side length 1.415 Ǻ) and 120° angles between adjacent atoms. Two structural variations exist: hexagonal symmetry (1-2-1-2-1-2 planes) and rhomboidal symmetry (1-2-3-1-2-3 planes). The research aimed to produce high-density graphite utilizing carbonaceous raw materials. Graphite-based materials often exhibit high porosity, necessitating additional treatments. The study successfully obtained mesophase tar pitch (yield: 45%), a pivotal raw material, and high-density graphite. The resulting graphite underwent characterization for physical properties (apparent and real density, porosity and compression strength), demonstrating conformity with existing literature data.

After the great success of Mobile wallet, the Internet of Things (IoT) leaves the door wide open for consumers to use their connected devices to access their bank accounts and perform routine banking activities from anywhere, anytime and with any device. However, consumers need to feel safe when interacting with IoT-based payment systems, and their personal information should be protected as much as possible. Unlike as usually done in the literature, in this paper, we introduce two lightweight and secure IoT-based payment protocols based on an identity-based signature scheme. We adopt a server-aided verification technique to construct the first scheme. This technique allows to outsource the heavy computation overhead on the sensor node to a cloud server while maintaining the user's privacy. The second scheme is built upon a pairing-free ECC-based security protocol to avoid the heavy computational complexity of bilinear pairing operations. The security reduction results of both schemes are held in the Random Oracle Model (ROM) under the discrete logarithm and computational Diffie-Hellman assumptions. Finally, we experimentally compare the proposed schemes against each other and against the original scheme on the most commonly used IoT devices: a smartphone, a smartwatch and the embedded device Raspberry Pi. Compared with existing schemes, our proposed schemes achieve significant efficiency in the term of communication and computational overheads

The complexity of modern power grids, exacerbated by integrating diverse energy sources, espe-cially inverter-based resources (IBRs), presents a significant challenge to grid operation and plan-ning since linear models fail to capture the intricate IBR dynamics. This study employs the Sparse Identification of Nonlinear Dynamics (SINDy) method to bridge the gap between theoretical un-derstanding and practical implementation in power system analysis. It introduces the novel Volterra-based Nonlinearity Index (VNI) to examine system-level nonlinearity comprehensively. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise elucidates the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to IBRs, revealing system-level nonlinearity compared to module-level nonlinearity in conventional syn-chronous generators. The VNI quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a versatile tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the proposed VIN profile.

Fractional calculus is defined by expanded integer order integration and differentiation. In this paper, multiple mathematical models of a nonlinear dual tank device are precisely formulated by fractional calculus. Using the accurate model, multivariable Fractional-Order Controller is designed for the nonlinear device. The merits of the fractional-order design include: 1) Control of multivariable nonlinearities, 2) Compensation of uncertainties, 3) Elimination of coupling effects. Simulations and experiments are conducted to verify the precision of the fractional order models and the effectiveness of the multivariable fractional-order control design.

Antimicrobial peptides (AMPs) have emerged as a promising solution to tackle bacterial infections and combat antibiotic resistance. However, their clinical application has been hindered by their vulnerability to protease degradation and toxicity towards mammalian cells. To overcome these challenges, our study aims to develop a method to enhance the stability and safety of AMPs, applicable to effective drug-device combination products. KR12 antimicrobial peptide was chosen and in order to further enhance its delivery and efficacy, HIV TAT protein-derived cell-penetrating peptide (CPP) was fused to form CPP-KR12. A new product, CPP-KR12@Si, was developed by forming silica nanoparticles with self-entrapped CPP-KR12 peptide using the biomimetic silica precipitability due to its cationic nature. Peptide delivery from CPP-KR12@Si to bacteria and cells was delivered at a slightly delayed rate with improved stability against trypsin treatment and a reduction in cytotoxicity over CPP-KR12. Finally, the antimicrobial potential of CPP-KR12@Si/bone graft substitute (BGS) combination product was demonstrated, which is coated with CPP-KR12 in the form of nanoparticles on the surface of BGS. Self-entrapped AMP in silica nanoparticles is a safe and effective AMP delivery method that will be useful for developing a drug/device combination product for tissue regeneration.

Device-mediated, non-invasive drug delivery across the blood-brain barrier (BBB) represents a significant advancement in treating neurological diseases. The BBB is a tightly packed layer of endothelial cells that shields the brain from harmful substances in the blood, allowing necessary nutrients to pass through. It is a highly selective barrier, which poses a challenge to delivering therapeutic agents into the brain. Several non-invasive techniques and devices have been proposed or investigated to enhance drug delivery across the BBB. This paper presents the current state of the art and case studies that address the pharmacology, technology, delivery systems, regulatory approval, ethical concerns, and future possibilities.

Computer and Smart Device-assisted Learning (CSDL) has gained increasing attention from educational researchers and practitioners in recent years. However, it remains controversial whether student can benefit from CSDL and what moderator could affect the impact of CSDL. Within the specific context of Korea, where the interest in digital education is steadily increasing, the number of empirical studies exploring the causal effect of CSDL remains relatively scarce. The primary objective of this empirical study was to investigate the impact of CSDL on students' academic achievement in Korea. To achieve this objective, a two-way fixed effect model was employed, utilizing a panel dataset spanning three years derived from the 'Korean Education Longitudinal Study 2013'. The findings revealed a significant positive impact of CSDL on students’ Mathematics achievement. Notably, higher income levels, increased availability of computer resources provided by schools, and the implementation of more individualized education were identified as factors that moderate the effect of CSDL on students' achievement levels in Korean and English subjects. These findings underscore the need for an approach that optimizes the educational benefits of CSDL by considering subject-specific characteristics. Furthermore, this study highlights the importance of allocating educational resources, such as computers and smart devices, and integrating individualized educational activities within the classroom environment.

Background and Objectives: Mucilaginous substances from plant extracts are known to be able to support the lubricating effect of hyaluronic acid (HA) in dry eye disease (DED). In this pilot study, the combined lubricating effect of HA and mallow extract (Malva sylvestris L.) in patients with DED was assessed. Materials and Methods: 20 patients at 5 ophthalmological practices in Italy were treated with eye drops, containing HA and mallow extract on the one hand, and with eye drops containing HA only, on the other hand, in a two-period crossover design. As primary endpoints, the tear film breakup time (TBUT), the reduction of lissamine green staining of the ocular surface (Oxford Scheme, OS), and the safety and efficacy assessment by the ophthalmologists were evaluated. As secondary variables, the patient symptom score, the ocular surface index (OSDI), and the satisfaction, preference and efficacy judgement by the patients were evaluated. All data were analysed descriptively in addition to an exploratory analysis of the target variables. Results: Both products were well tolerated. There were no statistically significant differences, with regard to the TBUT, OS and OSDI, between both treatments. Anyway, the efficacy and safety assessments by the ophthalmologists and the patients showed results in favour of the combined product. Conclusion: The addition of mallow extract to HA containing eye drops enhances the treatment of DED at least with respect to subjective measurements. Further assessments will have to be done to prove and explain this observation in terms of measurable parameters, e.g. markers for inflammatory cytokines.

Glioblastoma (GBM) is one of the most aggressive solid tumors, particularly due to the presence of cancer stem cells (CSCs). Today the characterization of this type of cells with an efficient, fast and low-cost method remains an issue. Hence, we have developed a microfluidic lab-on-a-chip based on dielectrophoresis (DEP) single cell electro-manipulation to measure the two crossover frequencies: f_x01 in low frequency range (below 500 kHz) and f_x02 in Ultra High Frequency range (UHF, above 50 MHz). First, in vitro conditions were investigated. U87-MG cell lines were cultured in different conditions in order to induce an undifferentiated phenotype. Then, ex vivo GBM cells from patients’ primary cell culture, were passed through the developed microfluidic system and characterized in order to reflect clinical conditions. This article demonstrates that the usual exploitation of low frequency range DEP does not allow the discrimination of the undifferentiated from the differentiated phenotypes of GBM cells. However, the presented study highlights the use of UHF-DEP as a relevant discriminant parameter. The proposed microfluidic lab-on-a-chip is able to follow the kinetic of U87-MG phenotype transformation in a CSC enrichment medium and their cancer stem cells phenotype acquirement.

In this paper, we investigate the relationship people have with their smart devices. We use the concept of agency to capture aspects of users’ sense of mastery as they relate to their device. This study gives preliminary evidence of the existence of two independent dimensions of agency for modeling the interaction between humans and smart devices: (i) user agency and (ii) device agency. These constructs emerged from an exploratory factorial analysis conducted on a survey data collected from 587 participants. In addition, we investigate the correlation between user agency and device agency with background variables of the respondents. Finally, we argue that mapping the users’ dynamics with their device into user agency and device agency fosters a better understanding of the needs of the users and helps in designing interfaces tailored for the specific capabilities and expectations of the users.

This work aims to explore the impact of side loads, drill-pipe tool-joint (DP-TJ) speed (RPM), and mud type on the austenitic stainless steel SM2535-110 casing wear characteristics. Actual field drill pipe tool joints, casings, and drilling muds are used in this study. The results of the study show that under both types of lubrication, the wear volume increased with radial load and DP-TJ speed. SM2535-110 casing specimens tested under oil-based mud (OBM) lubrication had higher casing wear volumes than those obtained under water-based mud (WBM) lubrication. This unexpected behavior is mainly due to the increase in the surface hardness of the casing specimens tested under WBM. The results also show that the specific wear factor (K) values of specimens tested under WBM are in general 2 to 4 times higher than those obtained under OBM. While K values under WBM increase with both the side load and RPM, those under OBM show a sharp decrease with RPM. This behavior under OBM is due to this lubricant’s higher viscosity and the change of lubrication regime from thin film to thick film lubrication at higher RPM. Scanning electron microscopy (SEM) and the digital microscopic imaging (DMI) of SM235-110 casing specimens show that an aggressive combination of adhesive, abrasive, and plastic deformation was observed under WBM, while the dominant wear mechanism under OBM is abrasive wear.

Financial markets require a great deal of decision making from the investors and market makers. One metric that can help ease the process of decision making is investment risk which can be measured in two parts; systematic risk and idiosyncratic risk. Clear understanding of the volatilities in each risk component can be a powerful signal in recognizing the right assets to maximize the investment returns. In this paper, we focus on the idiosyncratic volatility values and pre-calculate the idiosyncratic volatility values for 31,198 members of NYSE, Amex and Nasdaq markets for the trades occurring between January 1963 and December 2019. Utilizing a subset of dataset, limited to Nasdaq100 index, we consider the application of machine learning techniques in predicting the idiosyncratic volatility values using the raw trade data to explore a data extension option for the future market trade records that have not yet occurred. We offer a deep learning based regression model and compare it with traditional tree-based methods on a small subset of our per-calculated idiosyncratic volatility dataset. Our analytical results show that the performance of the deep learning techniques is much more robust in comparison to that of the traditional tree-based baselines.

This study compares the effects of lecture-based instruction and process-oriented guided inquiry learning (POGIL)-based instruction on the self-efficacy performance of Grade 12 students. A quasi-experimental, pretest-posttest design was adopted to investigate and assess the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes; Knowing, Applying and Reasoning (KAR). Two government high schools in Alain were selected as research sites, one for the boys and one for the girls. The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys), and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a circular motion unit in physics using POGIL-based instruction, while the control group was taught the unit using lecture-based instruction. The study's findings showed statistically significant differences between students of the control group and the treatment group in favour of the latter regarding their science performance, self-efficacy and science-related attitudes. Moreover, positive correlations were found between participants’ performance at the KAR test, self-efficacy and scientific attitudes towards scientific inquiry after the intervention. In conclusion, it is recommended to shift teaching towards POGIL-based instruction due to its positive impact on students’ performance and self-efficacy. It is also suggested to replicate the study to include government and private schools, elementary and high schools, teachers and advisors.

Background: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, that significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting the physical, and emotional well-being and overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. Objective: To estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database. Population-based retrospective study. Nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database were selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing direct visualisation of the lesions. Main outcomes measures Incidence and prevalence of endometriosis were estimated for the entire 2010-2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: A total of 134,667,646 women aged 15–50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834-0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north-south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north-south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions.

The potential advantages of plant-based interventions in decreasing the incidence and lessening the morbidity and mortality of COVID-19 are yet to be widely acknowledged. Nevertheless, recent publications propose that these interventions could be effective. Our cardiology center conducted an interventional study in which we incorporated plant-based foods and provided supplementation to 3470 elderly COVID-19 patients with multiple comorbidities. We pay close attention to the precise selection of food items, the application of appropriate processing methods, and the provision of nourishing meals to our patients. Our outcome was highly successful as we achieved a zero mortality rate, and none of our patients experienced worsening conditions or required hospitalization. In this review article we present the mechanisms how plant-based and supplement interventions can mitigate COVID-19 disease severity and mortality. And experts have validated our hypotheses very recently. The measures and methods used to address the ongoing SARS-CoV-2 pandemic through plant-based interventions and supplements are effective and may help prevent or manage future pandemics.

Abstract: This study aims to evaluate the effectiveness of plant-based diets and supplement interventions in mitigating the severity and mortality of COVID-19 patients. Observational research suggests that a diet high in plant-based foods may decrease the likelihood and severity of SARS-CoV-2 infection. However, several studies have faced criticism regarding the accuracy of obtaining dietary questionnaires and the insufficient intake of essential vitamins and minerals in such diets. To address these issues, this study employed a prospective interventional design that strictly controlled the quality, quantity, and processing of plant-based foods provided. Furthermore, the study incorporated supplementation, which enhanced the anti-viral, anti-inflammatory, antioxidant, antithrombotic, and immunomodulatory properties of a plant-based diet against the SARS-CoV-2 virus. Of the 3,470 COVID-19 elderly patients, half already followed a plant-based diet, and the other half new patients, both with various comorbidities, were intervened with a plant-based diet and supplementation. The results showed that the participants in the non-plant-based diet group were twice as likely to have experienced moderate disease (with 95% confidence limit: 1.42-3.12) and 2.4 times more likely to have experienced severe disease (with 95% confidence limit: 1.2-5.0) with a significant p-value of less than 0.0005 and 0.016 respectively, compared to those in the PBD group. During the interventions, none of the participants experienced disease progression or hospitalization, and there were no reported deaths by the end of the study. The outcome was highly favorable and aligned with the researchers' expectations, as COVID-19 morbidity and mortality rates in Indonesia were among the highest in Asia. This research may provide significant insights into the prevention and management of COVID-19 and aid in better preparation for future pandemics.

Chitosan is a copolymer of β-glucosamine and N-acetylglucosamine. Recent experiments showed that the degree and pattern of acetylation along the chitosan chain modulate the biological and physicochemical properties; however, the molecular mechanism is unknown. Here we apply the de novo all-atom molecular dynamics (MD) simulations to study chitosan’s self-assembly process at different degrees of acetylation and two different acetylation patterns. The simulations revealed that the 10-mer chitosan chains with 50% acetylation in either block or alternating patterns associate to form ordered nanofibrils comprised of mainly antiparallel chains in agreement with the fiber diffraction data of deacetylated chitosan. Surprisingly, regardless of the acetylation pattern, the same intermolecular hydrogen bonds mediate the fibril sheet formation while water-mediated interactions stabilize the sheet-sheet stacking. Moreover, the acetylated units are involved in forming the strong intermolecular hydrogen bonds (NH–O6 and O6H–O7), which offers an explanation for the experimental observation that increased acetylation lowers chitosan’s solubility. Taken together, the present study provides the atomic-level understanding the role of acetylation plays in modulating chitosan’s physiochemical properties, contributing to the rational design of chitosan-based materials with the ability to tune by its degree and pattern of acetylation. Additionally, we disseminate the improved molecular mechanics parameters that can be applied in MD studies to further understand chitosan-based materials.

The process of Targeted Opinion Word Extraction (TOWE), a critical component of aspect-based sentiment analysis (ABSA), revolves around identifying opinionated words linked to specific aspect-terms within sentences. Existing deep learning approaches, while effective, often overlook the syntactic structure of sentences, a factor that previous studies have identified as beneficial for TOWE. In this study, we introduce the Syntactic-Enhanced Deep Learning Model (SEDLM) that integrates syntactic structures into deep learning frameworks for TOWE. Our approach leverages syntax-driven opinion potential scores and syntactic inter-word connections, enhancing model performance. Additionally, we introduce an innovative regularization strategy aimed at distinguishing word representations in TOWE tasks. Our comprehensive analysis reveals that SEDLM sets new benchmarks in performance across multiple standard datasets.

The implementation of Boolean functions using Nano crossbar- based switching lattices has been suggested as a substitute for conventional CMOS-based approaches in digital circuits . This alternative may satisfy the needs of future electronic designs, con- sidering the expected end of Moore’s law. This study introduces CVM, a Crossbar-based circuit Verification through Modeling tech- nique

Castor oil may be differentiated from other non-edible vegetable oils because of its main composition of hydroxylated fatty acids. Ricinoleic acid comprises 80–90% wt. of fatty acids in castor oil (Ricinus communis). In this study, the thermo-oxidative stability and tribological behavior of bio-based lubricant samples synthesized from castor oil using isoamyl alcohol were evaluated. Initially, the compositional and physicochemical properties of the obtained samples were assessed using 1H NMR, FTIR, and ASTM methods. Oxidative stability of the samples was evaluated using Rancimat method at 110 °C under air flow. The final biolubricant sample (BL2), obtained after esterification, epoxidation, and oxirane rings opening reactions, presented an oxidation stability time (OST) of 14.3 h. The thermal stability was also evaluated by thermogravimetry (TG) from the mass variations under inert and oxidative atmosphere. BL2 showed higher thermal stability compared to the other samples, demonstrating higher decomposition temperatures in both inert (339.04 °C) and oxidative (338.47 °C) atmospheres, for a mass loss of 50%. The tribological properties of the samples were evaluated using a four-ball tribometer configuration. The BL1 and BL2 samples exhibited lower friction coefficients than the mineral oil sample (MOS) by 21.5% and 43.1%, respectively. Regarding wear, the observed wear scar diameter (WSD) was also lower in BL1 and BL2 compared to MOS by 5.2% and 40.4%, respectively. The results of the tribological evaluation suggest that both samples obtained in this study have promising potential for applications in lubricating machines and mechanical systems.

As formally is known, nanozymes are the nanomaterials or nanoscale materials which reveal enzyme-like properties. These nanomaterilas can be utilzied instead of the natural enzymes for simulation of enzymatic reactions in harsh environmental conditions. Among different nanoscale enzyme-like materials, the majority of them reveal peroxidase-like activity, due to the high catalytic efficiency and stability of peroxidase-like nanozymes, they had been widely utilized for sensing and detection via constructing the colorimetric and fluorescence-based analytical and bioanalytical sensors. There are several high impact nanozymatic sensors which reported in the literature. Although the review articles published in this field, however, the current reviews focus on the introducing nanozyme field not description on the best articles published in this filed. Hence, this article aimed to present a brief introduction on the nanozyme-based chemistry with emphasizing on the historical overview of recent nanozymatic sensors. In this regard the best nanozymatic sensors which published over 2016-2023 were briefly described and overviewed.

Waste management is a significant issue that Indonesia must face. The presence of waste will always exist as long as life continues. One of the main challenges in waste management is the proper separation of organic and inorganic waste. As a solution to address this issue, the Ministry of Environment has made efforts to develop Waste Banks. However, it also creates new problems related to manual data collection, lack of monitoring by the community in implementing waste management activities, and a lack of specific reports regarding waste management conducted by officers. We propose the creation of a website using the Agile Development SDLC method. This website involve several steps and incorporate functions for data digitalization and expedited data collection, such as the addition of QR Code functionality, Monthly Reporting Function, and enhanced data security. The method used in this research is Agile Development. The application has been developed with a user-friendly interface and the latest web development technologies to ensure smooth performance. Overall, the web-based application for organic and inorganic waste using Laravel is an important step to promoting sustainable waste management practices.

In this work, the inhibition properties of new bio-based lignine ILs on the corrosion of mild steel in an aqueous solution of 0.01 M NaCl were investigated by Potentiostatic Electrochemical Impedance Spectroscopy (PEIS), Cyclic Potentiodynamic Polarization (CPP). Moreover, the surface was characterized using SEM, EDS, and optical profilometry. The influence of cation and anion on the inhibitor properties and a possible synergistic effect were investigated. The IL choline syringate showed a promising performance, reducing the corrosion current after 24-hour immersion in 0.01 M sodium chloride, from 1.66 µA/cm2 for the control to 0.066 µA/cm2 with 10 mM of the IL present. In addition to the performance as a corrosion inhibitor, both components of this IL also meet or exceed current additional desired properties of such compounds, being readily available, economically efficient, and well tolerated in organisms and the environment.

Paper-based analytical devices have been substantially developed in recent decades. Many fabrication techniques for paper-based analytical devices have been demonstrated and reported. Herein we report a relatively rapid, simple, and inexpensive method for fabricating paper-based analytical devices using parafilm hot pressing. We studied and optimized the effect of the key fabrication parameters, namely pressure, temperature, and pressing time. We discerned the optimal conditions, including pressure of 3.8 MPa (3 tons), temperature of 80oC, and 3 minutes of pressing time, with the smallest hydrophobic barrier size (821 µm) being governed by laminate mask and parafilm dispersal from pressure and heat. Physical and biochemical properties were evaluated to substantiate the paper functionality for analytical devices. Wicking speed in the fabricated paper strips was slightly slower than that of non-processed paper, resulting from reducing paper pore size. A colorimetric immunological assay was performed to demonstrate the protein binding capacity of the paper-based device after exposure to pressure and heat from the fabrication. Moreover, mixing in two-dimensional paper-based device and flowing in a three-dimensional counterpart were thoroughly investigated, demonstrating that the paper device from this fabrication process is potentially applicable as analytical devices for biomolecule detection. Fast, easy, and inexpensive parafilm hot press fabrication presents an opportunity for researchers to develop paper-based analytical devices in resource-limited environments.

Abstract: Calcium-based catalysts are of a high interest for glycerol polymerization due to their high catalytic activity and large availability. However, their poor stability under reaction conditions is an issue. In the present study, we investigated the stability and catalytic activity of Ca-hydroxyapatites (HAps) as one of the most abundant Ca-source in nature. A stochiometric, a Ca-deficient and a Ca-rich HAps have been synthetized and tested as catalysts in the glycerol polymerization reaction. Deficient and stochiometric HAps exhibited a remarkable 100% selectivity to triglycerol at 15 % of glycerol conversion at 245 °C after 8 h of reaction in the presence 0.5 mol.% of catalyst. Moreover, under the same reaction conditions, Ca-rich HAp showed a high selectivity (88 %) to di- and triglycerol at a glycerol conversion of 27 %. Most importantly, these catalysts were unexpectedly stable towards leaching under the reaction conditions based on the ICP-OES results. However, based on the catalytic tests and characterization analysis performed by XRD, XPS, IR, TGA-DSC and ICP-OES, we found that HAps can be deactivated by the presence of the reaction products themselves, i.e., water and polymers.

A project-based module on Sustainable Development Goal number 5, Gender Equality, was im-plemented on 5 different groups of Business English students consisting of a total number of 62 students in higher education. The main purpose of this project was to raise awareness of this goal by means of a flipped method in which students were required to carry out some research on specific areas of the aforementioned goal and work in teams to elaborate oral presentations. Once their findings were shared in class, students were expected to answer a written questionnaire of open-ended questions which were part of a qualitative analysis. Results of this survey showed that not only 90% of the students gained in depth knowledge of this goal, but also 85% had built a positive attitude to take initiative and 80% were optimistic about future gender equality. Finally, 70% of students suggested further social action to curb the problem of gender discrimination. On the whole, the flipped classroom method of learning combined with project-based group work have proven to be an effective way to raise awareness of this goal, create a more positive attitude, in-crease their willingness to take action as well as widening their English lexical resources.

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

Web-Based GIS is a platform that deals with the representation, management and storage of locational information for real-time online retrieval, viewing and manipulations. Web-based GIS incorporate all the functions of information systems: gathering, storing, retrieving, visualizing and dissemination of spatial information on the Internet. In modern-day GIS serve as vital means to not only geo-referenced locational information that are been retrieved but also the development in web-based technologies as well as there involvements in decision making processes. In recent time the increased used of GIS on the Internet have totally transformed and made three distinct changes across our GIS environment. These are: (i) how are GIS data being accessed (ii) what are modes of its transmission and (iii) what available GIS functionalities are within the environment for analysis. This paper examines the applications and technologies associated with web-based GIS architectures with an emphasis on the internet GIS based structure and case studies of GIS Web-based applications in MapInfo, Microsoft Silverlight Technology and the ArcGIS Server using ArcGIS JavaScript API.

A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.

Wearable assistant devices play an important role in daily life for people with disabilities. Those who are hearing impaired may face dangers while walking or driving on the road. The major danger is their inability to hear warning sounds from cars or ambulances. Thus, the goal of this study is to develop a wearable assistant device for the hearing impaired to recognize emergency vehicle sirens on the road using edge computing. An EfficientNet-based fuzzy rank-based ensemble model was proposed to classify seven audio sounds, including human vocalizations and emergency vehicle sirens. This model was embedded in an Arduino Nano 33 BLE Sense development board. The audio files were respectively obtained from the CREMA-D dataset and Large Scale Audio dataset of emergency vehicle sirens on the road, with a total number of 8756 files. The seven audio sounds included neutral vocalization, anger vocalization, fear vocalization, happy vocalization, car horn sound, siren sound, and ambulance siren sound. The audio signal was converted into a spectrogram by the short-time Fourier transform as the feature. When one of the car horns, sirens, or ambulance sirens was detected, the wearable assistant device presented alarms through vibration and messages on the OLED panel. The performances of the EfficientNet-based fuzzy rank-based ensemble model in offline computing achieved an accuracy of 97.1%, precision of 97.79%, sensitivity of 96.8%, and specificity of 97.04%. In edge computing, the results were an accuracy of 95.2%, precision of 93.2%, sensitivity of 95.3%, and specificity of 95.1%. Thus, the proposed wearable assistant device has the potential benefit of helping the hearing impaired avoid traffic accidents.

Graphene-based nanomaterials (GNMs), including graphene, graphene oxide, reduced graphene oxide, and graphene quantum dots, may have direct anticancer activity or be used as nanocarri-ers for antitumor drugs. GNMs usually enter tumor cells by endocytosis and can accumulate in lysosomes. This accumulation prevents drugs bound to GNMs from reaching their targets, sup-pressing their anticancer effects. A number of chemical modifications are made to GNMs to facili-tate the separation of anticancer drugs from GNMs at low lysosomal pH and to enable lysosomal escape of drugs. Lysosomal escape may be associated with oxidative stress, permeabilization of the unstable membrane of cancer cell lysosomes, release of lysosomal enzymes into the cytoplasm, and cell death. GNMs can prevent or stimulate tumor cell death by inducing protective autopha-gy or suppressing autolysosomal degradation, respectively. Furthermore, because GNMs prevent bound fluorescent agents from emitting light, their separation in lysosomes may enable tumor cell identification and therapy monitoring. In this review, we explain how the characteristics of the lysosomal microenvironment and the unique features of tumor cell lysosomes can be exploited for GNM-based cancer therapy.

This study was designed to extend the literature on multicomponent interventions for the children of deaf adults (CODA) population. This study used two evidence-based behavior intervention strategies: pre-session pairing (PSP) and independent group contingency (GC). These strategies have been successfully used to decrease off-task behavior in elementary school children with various abilities and diverse backgrounds. However, the research on multicomponent interventions has yet to examine their effects on the CODA population in inclusive classrooms. This study used a concurrent multiple baseline design across participants with an ABC sequence to examine teacher-implemented PSP with independent GC in reducing the off-task behavior of three CODAs in an inclusive classroom at a public elementary school. The results show that the intervention successfully decreased off-task behavior for all participating CODAs. The results suggest that CODAs can adapt to classroom rules and expectations when PSP and independent GC are systematically applied to them in classrooms.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

Maternal-child care is one of the foundations of primary health care. Nurses’ competency skills they have been taught. Community awareness is an important part of preventive healthcare, and nurses must be aware of the factors that impact the health of the community. This study examines the effectiveness of lecture-based instructions in maternal and child care and its implications to students' social competency skills and community awareness in Nursing Colleges in Nueva Ecija, Philippines. The researcher uses survey questionnaire and employed the descriptive design where fifteen (15) nursing students and five (5) teachers were purposively selected. The findings revealed that the weighted mean for the effectiveness of lecture based instruction in maternal and child care is 3.91 with verbal description of “Effective”, the effects of lecture based instruction in maternal and childcare to students’ social competency skills and community awareness got the weighted mean of 3.87 and interpreted as “very satisfactory” and the effectiveness of actual community-based instruction is very effective with weighted mean of 4.25 and is higher compare to lecture based instruction. The results also revealed that students and teachers were challenged in lecture-based instruction in maternal and chi8ldcare during distance learning. Recommendations for the enhancement of lecture-based instruction in maternal and childcare in social competency skills and community awareness were also made.

Over the last decade, a significant literature has emerged that advocates the potential of different Additive manufacturing (AM) technologies and printable polymeric materials. Nevertheless, large scale printing and complex geometric shapes, with curvatures and non-planar layer deposition, are a challenging process for the traditional gantry-based machine. The 3 degrees of freedom cartesian configuration restricted their capability to planar layered printing and restricted part dimensions. To date, many researchers have used industrial robots to overcomes this limitation. This review gives the reader a good overview of the FDM technique due to its scalability, cost efficiency and a wide range of material printability. A strong emphasis is laid on the PLA and PLA-based composites as promising materials for the FDM process applications. The second part of this paper links the successful use of these materials in the traditional printing process to large scale printing using the robot-based FDM process. This survey presents representative setups for robot-based AM and works that have been used these setups for non-planar material deposition. Finally, we conclude this paper by identifying opportunities for realizing new functional capabilities by exploiting robot-based AM, and we also present the future trends in this area.

Saccharomyces cerevisiae are a phenotypically diverse species that adapt to a wide variety of environments by exploiting standing genetic diversity and selecting for advantageous mutations. Glyphosate and copper-based herbicides/ fungicides affect non-target organisms, these incidental exposures can impact microbial populations. In this study, glyphosate resistance was found in the historical collection of yeast which was collected over the last century, but only in yeast isolated after the introduction of glyphosate. The highest glyphosate-resistant yeasts were isolated from agricultural sites. However, herbicide application at these sites was not recorded. In an effort to assess glyphosate resistance and impact on non-target microorganisms, yeast were harvested from 15 areas with known herbicidal histories, including an organic farm, conventional farm, remediated coal mine, suburban locations, state park, and a national forest. Yeast representing 23 genera were isolated from 237 samples of plant, soil, spontaneous fermentation, nut, flower, fruit, feces, and tree material samples. Saccharomyces, Candida, Metschnikowia, Klyveromyces, Hanseniaspora, and Pichia were other genera commonly found across our sampled environments. Managed areas had less species diversity and at the brewery, only Saccharomyces and Pichia were isolated. A conventional farm growing RoundUp Ready™ corn had the lowest phylogenetic diversity and the highest glyphosate resistance. The mine was sprayed with multiple herbicides including a commercial formulation of glyphosate; however, the yeast did not have elevated glyphosate resistance. In contrast to the conventional farm, the mine was exposed to glyphosate only one year prior to sample isolation. Glyphosate resistance is an example of the anthropogenic selection of nontarget organisms.