Computing in-memory technology is a promising way of solving the “memory wall” problem when processing large-scale data,accelerating data processing, and improving energy efficiency. However, calculations in the analog domain are limited in terms of accuracy and sensitivity to process, voltage, and temperature (PVT) changes. In this study, we proposed a computing in memory multiply-and-accumulate (CIM MAC) circuit which could generate pulses automatically and which endows the time-domain approach with a digital character. The MAC result was reflected by the pulse edge and converted into the final digital output using a dual-edge counter quantization circuit, improving the accuracy of the MAC operation and reducing the difficulty of quantization. The performance of the proposed CIM circuit was evaluated using a 28-nm process. It could achieve 4-bit multiplication without errors with an energy efficiency of 40.34 to 883.37 TOPS/W.

The effective and efficient monitoring of revegetation outcomes is a key component of ecosystem restoration. Monitoring often involves labour intensive manual methods which can be difficult to deploy when sites are inaccessible or involve large areas of revegetation. This study aimed to identify plant species and quantify α-diversity index on a sub-meter scale at Manlailiang Mine Site in Northwestern China using unmanned aerial vehicles (UAVs) as a means to semi-automate large-scale vegetation monitoring. UAVs equipped with multispectral sensors were combined with three industry-standard supervised classification algorithms (support vector machine (SVM), maximum likelihood, and artificial neural network) to classify plant species. Spectral vegetation indices (NDVI, DVI, VDVI, SAVI, MSAVI, EXG - EXR) were used to assess vegetation diversity obtained from on-ground survey plot data (Margalef, Pielou, Simpson, Shannon indices). Our results showed that SVM outperformed other algorithms in species identification accuracy (overall accuracy 84%). Significant relationships were observed between vegetation indices and diversity indices, with DVI performing significantly better than many more commonly used indices such as NDVI. The findings highlight the potential of combining UAV multispectral data, spectral vegetation indices and ground surveys for effective and efficient fine-scale monitoring of vegetation diversity in the ecological restoration of mining areas. This has significant practical benefits for improving adaptive management of restoration through improved monitoring tools.

Quadricuspid aortic valve (QAV) is a rare congenital anomaly with <200 cases reported till date. Most patients are asymptomatic. Symptoms depend on functionality of the valve and associated heart defects, most often presenting as aortic regurgitation followed by aortic stenosis. Management guidelines are ill-defined. We present a case series of 2 patients of QAV with rare associations and variable clinical presentation.

Truncus arteriosus is an exceedingly rare congenital heart disease involving conotruncal septum of developing heart. Clinical presentations vary depending upon associated anomalies. Surgical management is extremely challenging and differs with anatomic subtypes. We present a case of Truncus arteriosus -- Vaan Praagh type A4, quadricuspid truncal valve with moderate truncal stenosis and regurgitation, type B interrupted aortic arch who underwent bilateral pulmonary artery banding.

Semi-arid agroecosystems have a crucial function in supplying food and ecosystem services. However, these ecosystems are under severe threat due to land degradation. To enhance our understanding of environmental trends and their causes and to identify more sustainable land management techniques, it is important to track land degradation in space and time. This study uses land cover, soil organic carbon, and land productivity dynamics maps to evaluate land degradation neutrality (as per Sustainable Development Goal 15, indicator 15.3.1). In this regard, we employed the trends.earth tool in QGIS 3.3, utilising the European Space Agency Climate Change Initiative (ESA CCI) classified LULC maps for 1992, 2000, 2010, and 2020 to assess land degradation. Additionally, we predicted 2050 LULC maps using the MOLUSCE plugin in QGIS, which integrates an artificial neural network (ANN) in cellular automata (CA) modeling (CA-ANN) based on the 2015 LULC map and independent variables such as digital elevation model (DEM) and slope. Our results indicated a significant decrease in bare areas (71%) and an increase in settlements (built-up areas) (163%) between 1992 and 2020. Furthermore, the predicted land cover map shows a significant increase in bare land (238%) and settlements (72%), accompanied by a decrease in water bodies (23%) and forested areas (3.5%). In terms of land degradation, approximately 26.46% of the province exhibited degraded land, accounting for approximately 20,146.35 km 2, while approximately 59.55% (45,337.84 km 2) of the land remained stable. Land cover conversions, particularly from forests to grasslands and settlements, are among the potential drivers of land degradation. Identifying land cover transitions and assessing land degradation is paramount for effective monitoring and planning. By understanding these dynamics, targeted interventions can be developed to mitigate land degradation and promote sustainable land use practices in semi-arid agroecosystems.

The overall efficiency of grain production in China is relatively low, and how to change the current situation of low grain production efficiency has become the key to the high-quality development of grain. The high-standard farmland construction provides a new path for improving Total factor productivity of grain by filling the gaps in grain production. This paper is based on grain sector data from 281 cities in China and uses the Meta-Malmquist index to calculate the Total factor productivity of grain; And the SARAR model was used to analyze the impact of high-standard farmland construction on Total factor productivity of grain. There is room for improvement in Total factor productivity of grain, and the impact of technological efficiency on Total factor productivity of grain is greater than the impact of technological progress, and the Total factor productivity of grain in the eastern region is significantly higher than the central and western regions. The high-standard farmland construction can significantly improve the Total factor productivity of grain. Compared with the advancement of grain technology, the high-standard farmland construction can better improve the efficiency of grain technology.

A high selective and sensitive detection of Cu2+ in the semi-aqueous phase by the naked eye has always been a challenge. In this paper, a simple compound based on diaminomaleonitrile Schiff base probe (L) was synthesized and its structure was confirmed by 1H, 13C NMR, FTIR, and mass analysis. The probe L showed distinct colorimetric upon interaction with Cu2+ in DMSO:H2O (5:5, v/v) media. The probe L exhibited a key absorption peak at 374 nm due to π→π* transitions of the free probe, upon the interaction with Cu2+ it shifted to 462 nm, which is due to the LMCT mechanism. The probe L binds Cu2+ in a 1:1 ratio with an association constant of (Ka) = 5.02×104 M-1 and this is established by using the Job’s and Benasi-Hilderbrand (BH) methods. The detection limit for Cu2+ can reach a concentration of as low as 0.705 μM with high selectivity, even in a solution containing diverse metal ions. Besides, the selective color change of L with Cu2+ was integrated with a smartphone to monitor the change in the RGB tool and test paper kit. The binding mechanism of L with Cu2+ was studied by using ESI mass and DFT analysis.

Abstract— This study aims to investigate the effectiveness of Unified Power Quality Conditioners (UPQC) in reducing the power quality issues and harmonics caused by non-linear loads in the power grid. Here the Photovoltaic (PV) is integrated with Battery Energy Storage System (BESS) to enhance the power quality. During emergencies, the BESS supplies backup power over prolonged voltage interruptions or when the PV system is unable to meet the required power demand. A hybrid PV-BESS system is found to be more reliable than a standalone PV-UPQC system due to its ability to produce continuous clean energy and increase voltage support capacity. The UPQC controller is synchronized using the unit vector generator (UVG) approach in conjunction with the self-tuning filter (STF). The STF-UVG approach ensures normal UPQC operation even in the presence of distorted and imbalanced grid voltage. The proposed methodology is verified through MATLAB-Simulink simulations and various case studies.

Low-carbon development of integrated energy systems is achieved via the sharing of multiple energy interactions by park-level integrated energy systems (PIESs). However, coordinating profit distribution conflict between complex interactive stakeholders under stochastic scenarios is challenging. Accordingly, this study proposes a novel tri-layer framework that aggregates different game mechanisms to investigate the interactions between PIESs and coupled energy markets. First, a linkage trading mechanism is proposed by integrating carbon emissions trading and green certificate trading , which establishes a coupled electricity-carbon-green certificate market. Consequently, a park aggregation operator acts as an intermediary between PIESs and the coupled market, setting purchase and sale prices to guide unit generation in each PIES using the master-slave game theory. Then, the Nash game theory is applied to realize a cooperative bargaining among PIESs for fair revenue distribution. Further, the impact of uncertain environments has been considered using stochastic scenario methods and the conditional value-at-risk theory. Furthermore, to protect the privacy of each participating agent while improving convergence speed, a differential evolutionary method is combined with analysis target cascading to solve the framework. Finally, the proposed scheduling method is verified using a typical case to optimize conflicting PIES interests in multiple scenarios and realize decarbonization transformation.

The power characteristics of offshore wind power will change the regional power flow distribution and affect the regional voltage. In this paper, the direct-drive wind turbine generator controlled by unity power factor is selected as the research object, and the influence of change of wind power on voltage at the grid connection point is analyzed from the simple integration model. Based on the two critical states of the external equivalent power of the grid connection point, an analytical expression of the output of wind power in the corresponding state is obtained, and the relationship among the critical state outputs, the output of wind power and the parameters at the grid connection point is drawn, hence the related influence laws is analyzed. The influence of change of wind power on voltage and regional reactive power and the reactance distribution of transmission lines near the grid connection point is considered to analyze the influence of offshore wind power on the vicinity region of grid connection point. The rationality of the conclusion is verified by study the cases of the integration of offshore wind power into Guangdong power grid, and some suggestions are put forward for the planning of offshore wind power integration.

A significant research effort has been pushed to develop semi-transparent solar cells in last one decade. Organic solar cells (OSCs)’s band gap tunability in near-infrared, and thin film depositions characteristic appeal them attractive as a semi-transparent solar cell. It’s application in wearable energy generation, building-integrated solar cells, agrivoltaics, and the automotive industries, etc. become focus of interest. In OSCs device structure, apart from photoactive layer the top electrode materials play an essential role to maintain the device transparency and the performance. Thus, the choice of the top electrode material is crucial. A few materials such as thin metal film and nanowires, Metal/dielectric/Metal structures, PEDOT: PSS, graphene, and CNT have been reported so far. To date, the highest power conversion efficiency (PCE) reported for OSCs up to 16% with 25.2 % average visible transmittance (AVT %) by using a metal: polymer film as the transparent top electrode (TTE). However, there is an enhancement needed to maintain high transparency with improved device performance. In this review, we discussed atop electrode properties required for transparent or semi-transparent organic solar cells (ST-OSCs). We have also discussed the materials stability, scalability, current challenges, and future perspectives of top electrode materials for ST-OSCs. Also, summarized the top electrode materials reported so far.

This paper proposes a new splitting method for approximating the exponential of skew-symmetric and skew-Hermitian matrix A . Our point of departure is the splitting methods for approximation of the matrix exponential, which we modify and combine with new low-cost analytic formula for some sparse matrix exponential. Our motivation is to create and test a fast exponential approximation method in the context of a balance between speed and quality of approximation. We propose a cross splitting of the matrix A and use it in incomplete form for reducing computational complexity of exponential stage. We have also derived an analytical formula for a cross-type sparse skew-symmetric and skew-Hermitian matrix exponential, similar to the Euler-Rodrigues relation, well known for skew-symmetric matrices in R 3 . We evaluate this approximation problem in the context of computational cost and the speed of the algorithms used in technology. A number of numerical experiments conclude the optimization problem of the Independent Components Analysis type, the results of which confirm the effectiveness of the proposed method in technical applications.

The detection of high voltage permanent magnet motors has always been a big problem due to the interference of high voltage and magnetic field on the diagnosis. Especially the magenetic tile of the motor, the failure of the magenetic tile will directly lead to the operation failure of the motor. We propose Multi-view Unsupervised Consistent Soft-label Feature Selection(MUCSFS). This method constructed consistent pseudo-labels through soft labels of clustering affinity of each view sample and constructed the model by integrating selection constraints into the mapping model. This model is used to filter the fault data set to get the feature subset, and the feature subset is used to cluster. We verify the effectiveness of the method by simulating multi-view data and through the fault clustering experiment of the magnetic tile fault data set of high voltage motor, it is confirmed that our method can effectively cluster the fault categories.

This paper presents a study on the constrained exact boundary controllability of a quasilinear model in fluid mechanics, specifically the Euler equation that describes the motion of inviscid fluids. Our main contribution is the proof of the existence of continuous solutions of the quasilinear model that are Lipschitz continuous with respect to the space variable that take into account lower and upper bounds for the pressure and velocity of the gas flow. These constraints are crucial for the operation of gas pipelines and for ensuring the physical validity of the model. Additionally, we demonstrate the constrained exact boundary controllability of the system under the same pressure and velocity constraints. Our results have potential applications in the control and operation of gas pipelines.

A document by Hasan Dalman. Click on the document to view its contents.

Heart rate variability biofeedback (HRVBF) is a promising anxiety-reducing intervention that activates the autonomic nervous system through paced breathing, using feedback from heart rate variability (HRV). Many studies have reported the anxiety-reducing effects of HRVBF; however, reports on the effectiveness of training have been negative. Furthermore, the effects of training and the underlying brain activity changes remain unclear. This study aimed to examine the anxiety-reducing effects of HRVBF training and related brain activity changes, by randomly assigning participants, employing an active control group, and measuring anxiety-related attentional bias using the emotional Stroop task and EEG. Fifty-five right-handed healthy young students with anxiety were randomly assigned: finally, 21 to the HRVBF group and 19 to the control group. Both groups performed 10 training sessions of 20 minutes per day within three weeks and were assessed using HRV, EEG, attentional bias, and the State-Trait Anxiety Inventory-JYZ (STAI-JYZ), before and after training. Results showed increased HRV in the HRVBF group compared with the control group, but no differences in EEG, attentional bias, and STAI-JYZ. Further analyses revealed that participants with higher pre-training HRV achieved higher heart rhythm coherence in HRVBF training and had reduced attentional bias. This study suggests that individuals with higher HRV are more likely to be proficient in HRVBF training and benefit from its anxiety-reducing effects. The findings contribute to an understanding of participant selection and modification of HRVBF training protocols for non-responders.

Aims: Despite their overall favourable safety profile, the intraocular pressure increases after any routes of triamcinolone acetonide application are not rare. We designed a systematic review and network meta-analysis to compare risk of IOP elevation among TA for different routes of administration used by patients diagnosed with macular edema. Methods: We obtained data from the PubMed, MEDLINE, Embase, and Cochrane Library. We performed random-effects model and consistency model network meta-analyses to summarize the evidence. The Bayesian approach was used for direct and indirect comparisons, and the treatments were ranked by the surface under the cumulative ranking curve. The study was registered with PROSPERO, CRD42022366513 Results: Sixteen studies were included in the network meta-analysis. There was a significant difference in IOP between IVTA and STiTA (MD, 1.67 [95% CrI, 0.25, 3.15]) at the 12th week. At the 24th week, compared with the placebo group, IVTA, SCTA and STiTA had statistically significant effect on IOP (MD, 1.35 [95% CrI, 0.23, 2.30], 2.42 [95% CrI, 4.53, 0.19], and 1.31 [95% CrI, 2.49, 0.02]). The probabilities of rankings and SUCRA showed that IVTA and SCTA were generally considered the higher risk of IOP elevation than the other routes of injection therapy. In addition, RITA was shown to be safer. Conclusion: IVTA and SCTA appeared as the least safe routes of injection therapy for ME, which being more prone to increase the risk of IOP elevation. RITA demonstrated a safer profile. However, more high-quality randomized controlled trials will be necessary to further confirm this.

The nests of ground-nesting birds rely heavily on camouflage for their survival, and predation pressures, often linked to human activity, are a major source of mortality. Numerous ground-nesting bird populations are in decline, so understanding the effects of camouflage on their nesting behaviour is of relevance to their conservation concern. Habitat three-dimensional (3D) geometry together with predator visual abilities, viewing distance, and viewing angle determine whether a nest is either visible, occluded or too far away to detect. While this link is intuitive, few studies have investigated how fine-scale geometry is likely to help defend nests from different predator guilds. We quantified nest visibility based on 3D occlusion, camouflage, and predator visual modelling in northern lapwing, Vanellus Vanellus, on different land management regimes. Lapwings selected local backgrounds that had a higher 3D complexity at a spatial scale greater than their entire clutches compared to nearby control sites. Importantly, our findings show that habitat geometry – rather than predator visual acuity restricts nest visibility to terrestrial predators, and that an open field would actually be perceived as a closed habitat to a terrestrial predator searching for nests on the ground. Taken together with lapwings’ careful nest site selection, our findings highlight the importance of considering habitat geometry for understanding the evolutionary ecology and management of conservation sites for ground-nesting birds.

Micro-magnetic technology has a small size and high spatial resolution, efficiently realizing the targeted stimulation of deep nuclei inside the brain. Studying the precise magnetic stimulation of the hippocampal trisynaptic nerve loop in the brain is essential. Within this work we designed a 1×4-array micro-magnetic stimulation (μMS) device with four submillimeter sized commercial inductance. A 3 cm circular coil was utilized to determine that the 70 kHz/2 mT/1 min stimulation parameters could elevate the LTP within the CA1 region. Then, using a micromanipulator, the μMS device was shifted to the CA1, CA3, and DG areas, after successful induction of LTP using HFS with a 1-s train of pulses delivered at 100 Hz, the fEPSPs was continuously recorded for 15 min. Based on this procedure, two magnetic stimulation schemes were utilized. Scheme a (magnetic stimulation of a single region). The 70 kHz/2 mT/1 min magnetic stimulation was introduced to CA1/CA3 and DG target regions. The experimental results revealed that the LTP enhanced the most in a single CA1 area, followed by the CA3 area, and not significantly within the DG area. Scheme b (magnetic stimulation of the multiple regions). First, the CA1 region was magnetically stimulated and fEPSPs were recorded. Then, further magnetic stimulation of various areas was performed. Experimental results revealed that the increased LTP in the CA1 region was the most effective after magnetic stimulation among the three CA1/CA3/DG regions. Magnetic stimulation of multiple areas performed better than stimulation of a single region.

The information in working memory (WM) is stored in a domain-independent system or domain-specific storage and the storage and processing of cross-modal WM are still under intense debate. This study investigates the mechanism of cross-modal processing and storage of visual and vibrotactile WM using the delayed match-to-sample paradigm, the dual-task paradigm, and the selective interference paradigm. We hypothesized that WM can independently process and store the cross-modal information of vision and haptics, and proposed the domain-specific WM stores. The results suggest that the WM can parallel and sequentially process cross-modal information of vision and haptics and that the storage of visual and tactile WM may be domain-specific. This study provides preliminary evidence for the dissociated relationship between tactile sketchpads and visuospatial sketchpads, thus contributing to the WM storage and processing of information from different modalities and contents, and increasing the cognitive processing bandwidth of WM.

Title: Less asthma control with telemedicine in children during COVID-pandemicAuthors: Casper E.W. Gijsen1,2,3, Edward. Dompeling2,3, Evy H.C. Mulders1, Marieke W.P. van Horck1,2,3

Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution, facilitating evaluation. We imaged fresh ex vivo skin tissues (normal and neoplastic) from Mohs surgery. FF-OCT features were defined and diagnostic accuracy for malignancies was performed by the two experts OCT readers via a blinded analysis. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 BCCs and 17 SCCs). The average reader diagnostic accuracy was 88.1%, a sensitivity of 93.7%, and a specificity of 58.3%. The AI model achieved a diagnostic accuracy of 87.6%±5.9%, sensitivity of 93.2%±2.1%, and specificity of 81.2%±9.2%. A mean intersection-over-union of 60.3%±10.1% was achieved delineating nodular BCC from normal. We envision FF-OCT for rapid evaluation of surgical margins and AI tumor detection leading to widespread technique integration.

The extent to which external light sources illuminate the uterine environment is not completely known. Recent experimental work has indicated that the human fetus will respond to external visual stimuli, and initial modelling work has suggested that the fetus may not develop in a completely dark environment as previously thought. The development of the human visual system begins within the womb, and there is experimental motivation to explore the extent to which light penetrates maternal abdominal tissue. In this study, we develop and adapt a Monte Carlo model that simulates third trimester histological properties of maternal tissue in order to understand the extent to which the womb is illuminated by external point light sources. We next use the results of this mathematical modelling to determine approximate levels of third trimester uterine illumination and suggest improvements for future experimental work.

Lactobacillus paracasei IMC 502 ® is a commercially successful probiotic strain. Until now, there are no reports about the most suitable growth media composition for the highest possible biomass production of this strain. The major outcome of the present study is screening and optimization of growth medium using Design of Experiment (DoE) made up with vegan components to be used in the cultivation of this strain. A screening of carbohydrates and of five different non-animal sourced peptones using De Man, Rogosa and Sharpe (MRS) medium as reference, was performed. After the optimization of the most suitable carbon and nitrogen sources, salts, selective agents and surfactant of the typical MRS medium recipe were examined for their effect on biomass yield using the Plackett-Burman model for DOE screening. Sixty runs using Central Composite Design (CCD) for medium optimization were conducted. A second order polynomial regression model was used for analysis of the experimental data. A model with very high coefficient of determination R 2, and adjusted R 2 value higher than 95% was obtained. Model accuracy was equal to 94.11%. By using a vegan optimized culture medium, a biomass yield increase of 65% compared to standard MRS was evaluated in addition a metabolic fingerprint for primary metabolites with special attention to lactic acid as main component. The possibility to obtain viable lactic acid bacteria at high density from vegetable derived nutrients will be of great interest for specific consumer communities, opening the way to establish/follow this approach with other probiotic microorganisms of impact for human health.