Lower Limit Research Articles

Search for lepton-flavor-violating τ−→ μ−μ+μ− decays at Belle II

We present the result of a search for the charged-lepton-flavor violating decay τ− → μ−μ+μ− using a 424 fb−1 sample of data recorded by the Belle II experiment at the SuperKEKB e+e− collider. The selection of e+e− → τ+τ− events is based on an inclusive reconstruction of the non-signal tau decay, and on a boosted decision tree to suppress background. We observe one signal candidate, which is compatible with the expectation from background processes. We set a 90% confidence level upper limit of 1.9 × 10−8 on the branching fraction of the τ−→ μ−μ+μ− decay, which is the most stringent bound to date.

Insight of low flammability limit on sustainable aviation fuel blend and prediction by ANN model

Sustainable aviation fuel (SAF) blend has been confirmed to benefit for greenhouse gases reduction, and thus the property of blend fuel should be understanded the detail to support the utilization in aircraft. Low flammability limit (LFL) is a key property of jet fuel which should be sufficiently flammable to burn in combustor of aeroengine and meanwhile should be non-flammable for safety storage in fuel tank of aircraft. LFL of fuel could be influenced by integrating effects including molecule structure, intramolecular chemical bond energy and binding energy of molecule to molecule. Three types of theoretical models, based on different individual view including LFL of every pure hydrocarbon, stoichiometric concentration, and combustion enthalpy, present unsatisfactory simulation results, which can be deduced without integrating all potential influence factors together. The artificial neural network (ANN) approaches have been involved to bridge the relationship of the complex compositions in jet fuels with LFL. For providing adequate and available composition input, the boundary of fuel compositions has been extracted based on constrains of boiling point, flash point and freeze point coupling with statistic petroleum-based jet fuels. By clustering analysis, 43 critical classes of compositions, extracted as surrogate hydrocarbons based on with similar LFL within 1 % deviation, have been deployed as input matrix. ANN-LFL model, trained by only drop-in fuel with feature of Sigmoid function as an activation function, can distinguish drop-in fuel with non-drop-in fuel. ANN LFL model can predict LFL of drop-in fuel with 0.988 accuracy. The predict output value of non-drop-in fuel could present obvious deviation with traditional jet fuel. The optimization methodologies of ANN-LFL model could be improved the understanding of LFL and extend ANN in SAF utilization.

Electrocardiographic and morphological cardiac remodeling in competitive female athletes - a scoping review.

To quantitatively analyse exercise-induced cardiac remodeling (EICR) data in female athletes. This scoping review included from the databases Medline, Embase, and Google Scholar, peer-reviewed original English-language articles on female athlete-populations aged ≥18 years containing data on electrocardiography (ECG), echocardiography or cardiac magnetic resonance (CMR), and excluded athletes with cardiovascular conditions. From the extracted ECG data, we calculated prevalence percentages, and from the imaging data we compared the results with the upper reference limits of the general female population (URL). We included 31 articles comprising 4,896 female athletes, aged mean 22.2±4.6 years. On ECG (n=889), most prevalent findings were increased QRS voltages for LV hypertrophy (LVH, n=97), J-point elevation (JPE, n=108), and T-wave inversion (TWI, n=104). On echocardiography (n=4,644), we found increased mean of means BSA-indexed volumes for the LV 67.3 mL/m2 (95%CI 66.8-67.8; URL=61) and right ventricle (RV) 82.7 mL/m2 (95%CI 79.5-86.0; URL=74), while atrial volumes, septal wall thickness and LV mass were within the upper reference limits of the general population (URL). On CMR (n=309), the mean of means volumes of LA (62.0 mL/m2, 95%CI 58.8-65.2; URL=61), LV (103.4 mL/m2, 95%Ci 101.8-105.0; URL=96), and RV (105.3 mL/m2, 95%CI 103.3-110.6; URL=107.2) were >URL. Female athletes demonstrate distinct features of electrical (increased QRS voltages for LVH, JPE and TWI) and morphological EICR (biventricular dilatation). On CMR, LA was borderline dilated. Extensive studies on female athletes are needed to understand sex specific EICR.

Reliability and validity of the German version of the University of Jyvaskyla Active Aging Scale (UJACAS-G)

BackgroundThe University of Jyvaskyla Active Aging Scale (UJACAS) assesses active aging through willingness, ability, opportunity, and frequency of involvement in activities. Recognizing the lack of a German version, the Finnish original was translated (UJACAS-G). This study aimed: (1) to evaluate the test-retest reliability of UJACAS-G; and (2) to explore correlations with health-related parameters (concurrent validity).MethodsThe study (test-retest design) targeted healthy older adults aged 65+. Reliability of UJACAS-G (total and subscores) was assessed using Bland-Altman analyses and Intraclass Correlation Coefficients (ICCs). Furthermore, correlations (Spearman’s rho) between UJACAS-G scores and physical function (walking speed, handgrip strength, balance, 6-minute walk distance), physical activity (International Physical Activity Questionnaire), life-space mobility (Life-Space Assessment), and health-related quality of life (Short Form-36 Health Survey) were calculated.ResultsBland-Altman analyses (N = 60; mean age 72.3, SD 5.9 years; 50% women) revealed mean differences close to zero and narrow limits of agreement for all scores (total score: mean difference −1.9; limits −31.7 to 27.9). The ability subscore showed clustering at its upper limit. ICC was 0.829 (95% CI 0.730 to 0.894) for the total score and ranged between 0.530 and 0.876 for subscores (all p-values < 0.001). The total score correlated with walking speed (rho = 0.345; p = 0.008), physical activity (rho = 0.279; p = 0.033) and mental health (rho = 0.329; p = 0.010).ConclusionsUJACAS-G is reliable for assessing active aging among German-speaking healthy older adults. A potential ‘ceiling effect’ regarding the ability subscore should be considered when applying UJACAS-G to well-functioning populations. Analyses of concurrent validity indicated only weak correlations with health-related parameters.

A heat-measurement-free strategy for Economic Model Predictive Control of hydronic radiators

Cost-efficient measurement of room-level heat output from hydronic radiators is a major barrier to large-scale implementation of Economic Model Predictive Control (EMPC) in residential space heating for demand-side management. This paper therefore presents a novel EMPC strategy for hydronic radiators that relies on measurements of radiator pipe temperatures as a proxy for the radiator heat output, thus eliminating the need for costly flow-based meters at each radiator in a building. Simulation-based experiments indicate that the proposed proxy-based EMPC matches the performance of its heat-based counterpart. The proxy-based EMPC achieved a 16.6 % cost reduction compared to the heat-based EMPC's 16.8 %, with no comfort violations in both cases. Furthermore, the strategy shows resilience towards uncertainties in the user-estimated radiator exponent and maximum heating capacity. The proposed EMPC scheme also allows system operators to fine-tune the balance between cost savings and return temperatures using the proxy's upper limit. The findings presented in this paper suggest that the proposed proxy-based EMPC scheme provides a practical pathway for broader applications of EMPC in hydronic-based space heating with the prospect of unlocking significant load shifting potential, cost savings for end-users, and enhanced efficiency in individual and collective energy systems.

Signal amplification strategy based on target-controlled release of mediator for ultrasensitive self-powered biosensing of acetamiprid

Self-powered biosensors with high sensitivity have garnered significant interest for their potential applications in the realm of portable sensing. Herein, a self-powered biosensor with a novel signal amplification strategy was developed by integrating target-controlled release of mediator with an enzyme biofuel cell for the ultrasensitive detection of acetamiprid (ACE). Zeolitic imidazolate framework-67 was utilized as both a nanocontainer for capturing the electron mediator 2,2′-azidobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and a precursor for the synthesis of cobalt nanoparticles/nitrogen, sulfur-codoped carbon nanotubes (Co NPs/NS-CNTs), which were employed as the electrode material for constructing both the glucose oxidase-based bioanode and the laccase-based biocathode. The target analyte ACE can specifically bind to its aptamer, leading to the release of ABTS, which cyclically participates in the catalytic reaction of the biocathode, thereby amplifying the electrochemical signal. By leveraging the benefits of ABTS cyclic catalysis and the effective electrocatalysis of bioelectrodes based on Co NPs/NS-CNTs, the self-powered biosensor has a broad detection range of 0.1–1000 fM and a low detection limit of 25 aM toward ACE. The proposed signal amplification approach presents a promising strategy for enhancing sensitivity and enabling portable analysis in applications of food safety, environmental monitoring, and medical diagnostics.

Carbon dots-based dual-mode sensor for highly selective detection of nitrite in food substrates through diazo coupling reaction

As an antioxidant and preservative agent, nitrite (NO2−) plays an essential role in the food industry to maintain freshness or inhibit microbial growth. However, excessive addition of NO2− is detrimental to health, so accurate and portable detection of NO2− is critical for food quality control. Notably, the selectivity of most carbon dots (CDs)-based fluorescence sensors was not enough due to the nonspecific interaction mechanism of hydrogen bond, electrostatic interaction and inner filter effect etc. Herein, a novel fluorescence/UV–vis absorption (FL/UV–vis) dual-mode sensor was developed on basis of mC-CDs, which were prepared by simple solvothermal treatment of m-Phenylenediamine (m-PDA) and cyanidin cation (CC). The fluorescence of these mC-CDs could be selectively responded by NO2− through the specific diazo coupling reaction between NO2− and amino groups on the surface of mC-CDs, thus effectively improving the selectivity of NO2− detection. The CDs-based fluorescence sensor possessed a low detection limit of 0.091 μM and 0.143 μM for FL and UV–vis methods and the excellent linear range of 0.0–60.0 μM. Furthermore, the mC-CDs sensor was employed to detect NO2− in real samples with a recovery rate of 97.11 %–104.15 % for quantitative addition. Moreover, the smartphone-assisted fluorescence sensing platform developed could identify the subtle color changes that could not be distinguished by the naked eye, and had the advantages of fast detection speed and intelligence. More importantly, the portable solid phase sensor based on mC-CDs had been successfully applied to the specific fluorescence identification and concentration monitoring of NO2−. Accordingly, the designed sensor provided a new strategy for the highly selective and convenient sensing of NO2− in food substrates, and paved the way for the wide application of CDs-based nanomaterials in the detection of food safety.

Restricted-Enhanced Electrochemiluminescence biosensor of low excitation potential carbon quantum dots driven by magnetic Metal-Organic frameworks for sensitive immunoassay of neuron specific enolase

Electrochemiluminescence (ECL) of highly efficient and non-toxic carbon quantum dots (CQDs) plays an important role in immunoassays. However, the high absolute value of the excitation potential and poor controllability make precise detection of low levels difficult. In this work, novel CQDs with low excitation potential were reported to be used for the ultra-sensitive immunoassay of neuron-specific enolase (NSE). It is noteworthy that the narrow bandgap CQDs exhibit a trigger potential of −0.5 V and show excellent applicability of ECL signal at an excitation potential of −0.8 V. This property eliminates side reactions and electrode passivation and significantly improves ECL efficiency. Based on this, the magnetic zeolite-imidazole framework (MZIF) nanoreactor with co-reaction acceleration was employed as a carrier for the in-situ encapsulation of CQDs. The constrained-enhanced ECL sensor platform demonstrated the ability to achieve stable and controllable signal output. A sandwich-type biosensor was constructed by introducing copper sulfide (Cu7S4) as a dual-mechanism quencher, with NSE serving as the target analyte. Moreover, the electrochemical detection method based on the differential pulse voltammetry (DPV) properties of Cu7S4, was successfully validated against ECL. The sensors constructed on magnetic electrodes exhibited a bimodal signal output of ECL and DPV, encompassing a wide detection range (0.001 ng/mL − 500 ng/mL) and low detection limit (0.18 pg/mL for ECL and 0.15 pg/mL for DPV). This design offers a novel approach to understanding the efficient emission of carbon dots and provides a solution for the sensitive detection of biomarkers in clinical research.

Collaborative effects of fuel properties and EGR on the efficiency improvement and load boundary extension of a medium-duty engine

EGR dilution combustion has problems such as weakened anti-knock capability at high load, slow combustion speed and poor combustion stability, which results in limitations in the thermal efficiency improvement and load boundary extension of medium-duty highly-downsized engines. It is necessary to combine EGR dilution and other measures to collaboratively control the in-cylinder thermodynamic state and combustion process. The experimental investigations in this study isolate the effect of the ethanol blending ratio in ethanol gasoline on the anti-knock performance, combustion performance and thermal efficiency, and verifies the potential of collaborative optimization of fuel properties and EGR in improving the thermal efficiency and extending the load boundary for a medium-duty highly-downsized engine. The results show that as the load increases, the improvement effect of increasing the blending ratio of ethanol in the anti-knock performance, combustion speed, and the turbine inlet temperature reduction will become more obvious. At high load, using E20 fuel can improve the EGR tolerance, advance the spark timing and CA50, and thus increase the BTE. As the speed decreases, the thermal efficiency improvement effect of E20 fuel gradually increases, and the improved load range extends. The collaborative optimization of E20 fuel and EGR can further extend the high thermal efficiency area of the engine. And the Max. achievable load is 0.11 MPa higher than that of E10, which effectively extends the upper load limit during the stoichiometric combustion.

Spectrophotometric determination of o-phenylphenol in canned drinks using three-phase hollow-fiber liquid phase microextraction

A three-phase hollow-fiber liquid phase microextraction for o-phenylphenol (OPP) determination was developed. 1-octanol was employed as the organic phase, impregnated within the pores of the hollow fiber wall which was immersed in the sample solution, serving as a donor phase. OPP in the sample solution was extracted via octanol in the fiber pores into NaOH, which acted as the acceptor phase in the lumen of the fiber. The extracted OPP was then subjected to spectrophotometric detection at 712 nm using the indophenol blue reaction. The developed method showed a linear calibration curve (0.002–0.040 mg L−1) with high sensitivity (5.75 L mg−1), low limit of detection (0.31 μg L−1), and high recovery (73.6–94.8 %). Intra-day and inter-day precision at 2.1 μg L−1 OPP were 7.4 % (n = 12) and 10.9 % (n = 4) relative standard deviations, respectively. The determined OPP in various canned drinks was found to be between 2.0 and 17.8 μg L−1 using the developed method.

Optimizing photosynthetic light-harvesting under stars: simple and general antenna models

In the next 10–20 years, several observatories will aim to detect the signatures of oxygenic photosynthesis on exoplanets, though targets must be carefully selected. Most known potentially habitable exo-planets orbit cool M-dwarf stars, which have limited emission in the photosynthetically active region of the spectrum (PAR, 400<λ<700\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$400< \\lambda < 700$$\\end{document} nm) used by Earth’s oxygenic photoautotrophs. Still, recent experiments have shown that model cyanobacteria, algae, and non-vascular plants grow comfortably under simulated M-dwarf light, though vascular plants struggle. Here, we hypothesize that this is partly due to the different ways they harvest light, reflecting some general rule that determines how photosynthetic antenna structures may evolve under different stars. We construct a simple thermodynamic model of an oxygenic antenna-reaction centre supercomplex and determine the optimum structure, size and absorption spectrum under light from several star types. For the hotter G (e.g. the Sun) and K-stars, a small modular antenna is optimal and qualitatively resembles the PSII-LHCII supercomplex of higher plants. For the cooler M-dwarfs, a very large antenna with a steep ’energy funnel’ is required, resembling the cyanobacterial phycobilisome. For the coolest M-dwarfs an upper limit is reached, where increasing antenna size further is subject to steep diminishing returns in photosynthetic output. We conclude that G- and K-stars could support a range of niches for oxygenic photo-autotrophs, including high-light adapted canopy vegetation that may generate detectable bio-signatures. M-dwarfs may only be able to support low light-adapted organisms that have to invest considerable resources in maintaining a large antenna. This may negatively impact global coverage and therefore detectability.

Uncertainty in the number of contributor estimation methods applied to a Y-STR profile

Maximum allele count (MAC) and total allele count (TAC) methods are widely used for estimating the number of contributors (NoC) of autosomal short tandem repeat (STR) profile in many forensic laboratories. In this study, we applied NoC estimation methods to mixed Y-STR profiles and evaluated its uncertainty and performance. For the MAC method, as recent Y-STR typing kits involve single- and multi-copy loci, we defined “MAC-single” for use across only single-copy loci and “MAC-multi” for use across only multi-copy loci. We generated a dataset containing 120,000 Y-STR profiles for a one to six-person mixture in silico based on previously reported haplotype frequencies of 27 Y-STR loci in Yfiler Plus for the U.S. population (reported by NIST) and the Henan Han population. The dataset was randomly split into a training set and a test set. The training set was used to construct a TAC distribution (TAC curve), whereas the test set was used to calculate the performance metrics (accuracy, precision, recall, and F1-score). In addition, the effect of the upper limit of NoC considered for estimation on overall accuracy was evaluated. The overall accuracies of MAC-single, MAC-multi, and TAC methods when the upper limit of NoC was set to six-person were 0.7920, 0.4329, and 0.7877 for the U.S. population and 0.8207, 0.4609, and 0.8385 for the Henan Han population. Our results suggest that the MAC-single and TAC methods can estimate the NoC for mixed Y-STR profiles with high levels of accuracy.

Cascading failure model and resilience-based sequential recovery strategy for complex networks

Complex networks, which exhibit high connectivity, self-organization, small-world properties, and heterogeneity, are susceptible to the rapid spread of local failures, often resulting in cascading effects throughout the entire system. The paper introduces a cascading failure model based on biased random walks that incorporate betweenness centrality and the power-law distribution of node degrees. This model is used to investigate cascade failures triggered by extreme fluctuations in load that follow a Poisson distribution. Furthermore, we propose a resilience-based sequential recovery strategy that accounts for varying node recovery time and resource limitations, setting an upper limit on the number of nodes that can be in recovery simultaneously. The network’s robustness improves, and the variation in the power-law exponent during cascading failures and recovery decreases when the betweenness bias parameter is set to 1 instead of -1. The capacity parameter has the most significant and direct effect on improving the network’s robustness. Reducing node recovery time can improve the network’s initial invulnerability; however, its impact on final residual resilience remains limited. The power-law exponent of the initial network significantly affects residual resilience during the recovery process, with higher exponents leading to improved network performance. An appropriate increase in the number of nodes that can be in recovery simultaneously can enhance the overall recovery performance of the network. Extensive comparative simulations reveal substantial advantages of our proposed recovery strategy in enhancing network recovery.

3D printing of high-stiffness and high-strength glass fiber reinforced PEEK composites by selective laser sintering

Glass fiber reinforced poly-ether-ether-ketone (PEEK) composites are emerging as structural materials of multifunctional devices in space applications, due to their outstanding mechanical properties, electrical insulating properties, and resistance to irradiation. Here, a new approach for preparing glass fiber/PEEK powders tailored for selective laser sintering (SLS) process is proposed. The surface of glass fiber is modified with the sulfonated PEEK following the designed procedure. The flowability of glass fiber/PEEK powders is also improved by adding the nano-scale SiO2 flow agent. The glass fiber reinforced PEEK composites are successfully 3D printed using the glass fiber/PEEK powders. Further, the enhancement of interfacial bonding between PEEK and glass fiber is analyzed through quasi-static tension tests and scanning electron microscopy (SEM) for the SLSed glass fiber reinforced PEEK composites. The average ultimate tensile strength reaches approximately 100 MPa using these optimal process parameters, while the average elastic modulus is around 7 GPa. Finally, the upper limit of fiber weight fraction is evaluated with the X-ray computed tomography (XCT) and the high-fidelity discrete element method (DEM) simulation.

Chlorella Vulgaris‐Inspired Versatile Theranostic Nanoparticles for Specific Recognition and Detoxification to Copper (II) In Vitro and In Vivo

AbstractSpecific recognition and detoxification for copper is the key step for the early diagnosis and treatment of various diseases such as neurodegenerative disease and Wilson's disease. Herein, a Chlorella vulgaris‐inspired versatile theranostic nanoparticles is facilely and greenly prepared by assembling quercetin into poly(beta‐cyclodextrin) (PQNPs), which is further employed in the specific recognition and detoxification for Cu2+ in vitro and in vivo. PQNPs can be used in the detection of Cu2+ in aqueous solutions with fast response time (&lt;5 s) and low detection limit (6.499 nM). The detection for Cu2+ in water and serum can be achieved by naked eye instantaneously on a PQNPs‐based paper sensor, and PQNPs can also act as a biological diagnostic agent for the Cu2+ imaging. Remarkably, PQNPs significantly enhance cell viability of the cell models induced by Cu2+ through the synergistic capacities of chelating Cu2+ and antioxidation. The detoxification of PQNPs for copper poisoning model is further ascertained in vivo, and it found that poly‐β‐cyclodextrin is capable of crossing the blood–brain barrier. Taken together, the as‐prepared versatile theranostic nanoparticles possess advantages of simple composition, significant theranostic efficacy, and novel treatment pattern, presenting an intriguing avenue to develop therapeutics for tackling abnormal copper metabolism in the clinic.

Low detection limit of uric acid based on Prussian blue-enhanced photothermal effect with microfiber knot resonator

The human serum uric acid (UA) level is a crucial indicator for diagnosing dementia in middle-aged and elderly individuals, with decreased levels being expressed in patients. Therefore, developing a high-performance sensor for online uric acid detection is of significant research interest. Herein, a microfiber knot resonator (MKR) sensor for quantitative detection of UA levels is reported. Combining polydimethylsiloxane (PDMS) with an adiabatic MKR, the specificity of UA detection in serum is improved using the photothermal effect of Prussian blue-enhanced uricase reaction. During the sensor operation, UA generates the photothermal effect under 650 nm laser irradiation, causing the PDMS film to expand with heat absorption, thereby shifting the resonance spectrum of the PDMS-MKR sensor. Experimental results demonstrate a sensitivity of 0.0559 nm/(μmol/L) within a UA concentration range of 40–120 μmol/L and a detection limit as low as 0.3578 μmol/L. The proposed sensor shows potential applications in clinical point-of-care early diagnosis and prognosis of dementia due to its specificity, fast detection speed, robustness, and high integration.

One‐Pot Carbothermal Reduction Preparation of Cu‐BTC@Cu/C Heterostructure for Enhanced Nonenzymatic Electrochemical Glucose Sensing

AbstractA heterostructure based on MOFs with a small lattice mismatch is ideal for improving glucose‘s electrochemical sensing performance. Herein, a novel one‐pot carbothermal reduction technique to prepare Cu‐BTC@Cu/C heterostructure with intimate interfacial contact and high yield was developed, by in situ integrating Cu‐BTC (Cu3(BTC)2 ⋅ 3H2O) and its derived Cu/C nanocomposites. Structure characterizations demonstrated that Cu‐BTC@Cu/C heterostructure shows a synergistic effect in the combination of these two components, with more electrochemical active sites and lower resistance. Compared with each individual component, Cu‐BTC@Cu/C heterostructure exhibits better glucose electrooxidation performance. Under optimal condition, an extremely sensitive nonenzymatic glucose sensor with a low detection limit of 6.78 μM, sensitivity of 911.03 μA mM−1 cm−2, linear range of 0.001–2.0 mM, and anti‐interference performance is presented. Meanwhile, the newly constructed sensor was effectively employed for detecting glucose in honey sample with perfect recoveries, showing its great potential toward glucose monitoring in real sample. In addition, it has been demonstrated Cu(II) can be induced into Cu(I) by glucose in solution, while Cu(I) could be electrochemically converted to Cu(II), therefore achieving a Cu(I)/Cu(II) redox cycle. It offers a promising strategy for synthesis of advanced electrocatalysts with high efficiency and promising applications in this paper.

Asymmetric Nanobowl Confinement-Engineered "Plasmonic Storms" for Machine Learning-Assisted Ultrasensitive Immunochromatographic Assay of Pathogens.

Efficient field enhancement effects through plasmonic chemistry for ultrasensitive biosensing still face a great challenge. Herein, nanoconfinement engineering accumulation and synergistic effects are used to develop a "plasmonic storms" strategy with a high field enhancement effect, and gold nanoparticles (AuNPs) are used as active sites for a proof of concept because of their distinctive localized surface plasmon resonance and neighborly coupled electromagnetic field. Briefly, a large number of AuNPs are selectively and accurately stacked in the confined nanocavity of the bowl-like nanostructure through an in situ-synthesized strategy, which provides a space for strong coupling of electromagnetic fields between these adjacent AuNPs, forming "plasmonic storms" with an enhanced field that is 3 orders of magnitude higher than that of free AuNPs. The proposed nanoconfinement-engineered "plasmonic storms" are demonstrated by surface-enhanced Raman scattering (SERS) and photothermal experiments and theoretically visualized by finite element simulation. Finally, the proposed "plasmonic storms" are used for enhanced colorimetric/SERS/photothermal immunochromatographic assay to detect Salmonella typhimurium with the help of a machine learning algorithm, achieving a low limit of detection of 142 CFU mL-1, highlighting the potential of nanoconfinement in biosensing.

Construction of Cu2Y2O5/g-C3N4 Novel Composite for the Sensitive and Selective Trace-Level Electrochemical Detection of Sulfamethazine in Food and Water Samples.

The most frequently used sulfonamide is sulfamethazine (SMZ) because it is often found in foods made from livestock, which is hazardous for individuals. Here, we have developed an easy, quick, selective, and sensitive analytical technique to efficiently detect SMZ. Recently, transition metal oxides have attracted many researchers for their excellent performance as a promising sensor for SMZ analysis because of their superior redox activity, electrocatalytic activity, electroactive sites, and electron transfer properties. Further, Cu-based oxides have a resilient electrical conductivity; however, to boost it to an extreme extent, a composite including two-dimensional (2D) graphitic carbon nitride (g-C3N4) nanosheets needs to be constructed and ready as a composite (denoted as g-C3N4/Cu2Y2O5). Moreover, several techniques, including X-ray diffraction analysis, scanning electron microscopy analysis, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy were employed to analyze the composites. The electrochemical measurements have revealed that the constructed g-C3N4/Cu2Y2O5 composites exhibit great electrochemical activity. Nevertheless, the sensor achieved outstanding repeatability and reproducibility alongside a low limit of detection (LOD) of 0.23 µM, a long linear range of 2 to 276 µM, and an electrode sensitivity of 8.86 µA µM-1 cm-2. Finally, the proposed GCE/g-C3N4/Cu2Y2O5 electrode proved highly effective for detection of SMZ in food samples, with acceptable recoveries. The GCE/g-C3N4/Cu2Y2O5 electrode has been successfully applied to SMZ detection in food and water samples.

Techno economic approach of biogas in Konya Türkiye

In determining biogas potential, the current number of materials that can be used in biogas production is as important as the availability and usability of the materials. Potential studies that were conducted without knowing the structures of the systems in which these materials could be evaluated give us only the theoretical upper limit that can be reached. The ‘theoretical’, ‘technical’ and ‘economic’ potential distinctions made to prevent the error from occurring unfortunately only take into account the availability of the materials, and the process sizes and properties are either very limited or not at all. This causes the facilities established by considering existing potential research to fail in implementation or operate at low capacity. In this study, the importance of the international production chain of the apparel industry in Turkey’s economy is examined. The study is based on Konya, which has a total of 1,079,644 cattle animals, 737,395 of which are dairy cattle. In the study, the number of dairy cattle with high waste collectability rates was particularly taken into consideration. Thus, the seasonal number of changes that may occur was tried to be avoided. In this study, the number of animals per farm and the distances between businesses were taken into consideration, and the biogas systems that could be installed were evaluated within this framework. Series of analysis were made under 3 different scenarios. In the first scenario, it was assumed that biogas systems would be installed by waste-generating enterprises. The installation of village-type common biogas systems was examined when possible within the scope of the second scenario. In the third scenario, the installation of district-based biogas systems was considered. Considering the difficulties in collecting the waste of enterprises with less than 50 cattle (due to the lack of regular collection systems), it is assumed that the waste of these enterprises cannot be used in village or central systems. According to the data obtained, Scenario 1 stands out in terms of creating employment and reducing environmental problems. The 3rd Scenario was the most profitable in macroeconomic terms. However, it was emphasized that the 1st and 2nd Scenarios stand out in terms of the sustainability of the systems.