Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing cardiorespiratory interactions via lagged joint symbolic dynamics during spontaneous and controlled breathing

Introduction: Joint symbolic analysis (JSA) can be utilized to describe interactions between time series while accounting for time scales and nonlinear features. JSA is based on the computation of the rate of occurrence of joint patterns built after symbolization. Lagged JSA (LJSA) is obtained from the more classical JSA by introducing a delay/lead between patterns built over the two series and combined to form the joint scheme, thus monitoring coordinated patterns at different lags. Methods: In the present study, we applied LJSA for the assessment of cardiorespiratory coupling (CRC) from heart period (HP) variability and respiratory activity (R) in 19 healthy subjects (age: 27–35 years; 8 males, 11 females) during spontaneous breathing (SB) and controlled breathing (CB). The R rate of CB was selected to be indistinguishable from that of SB, namely, 15 breaths·minute−1 (CB15), or slower than SB, namely, 10 breaths·minute−1 (CB10), but in both cases, very rapid interactions between heart rate and R were known to be present. The ability of the LJSA approach to follow variations of the coupling strength was tested over a unidirectionally or bidirectionally coupled stochastic process and using surrogate data to test the null hypothesis of uncoupling. Results: We found that: i) the analysis of surrogate data proved that HP and R were significantly coupled in any experimental condition, and coupling was not more likely to occur at a specific time lag; ii) CB10 reduced CRC strength at the fastest time scales while increasing that at intermediate time scales, thus leaving the overall CRC strength unvaried; iii) despite exhibiting similar R rates and respiratory sinus arrhythmia, SB and CB15 induced different cardiorespiratory interactions; iv) no dominant temporal scheme was observed with relevant contributions of HP patterns either leading or lagging R. Discussion: LJSA is a useful methodology to explore HP–R dynamic interactions while accounting for time shifts and scales.
Scaling Microseismic Cloud Shape During Hydraulic Stimulation Using In Situ Stress and Permeability

Forecasting microseismic cloud shape as a proxy of stimulated rock volume may improve the design of an energy extraction system. The microseismic cloud created during hydraulic stimulation of geothermal reservoirs is known empirically to extend in the general direction of the maximum principal stress. However, this empirical relationship is often inconsistent with reported results, and the cloud growth process remains poorly understood. This study investigates microseismic cloud growth using data obtained from a hydraulic stimulation project in Basel, Switzerland, and explores its correlation with measured in situ stress. We applied principal component analysis to a time series of microseismicity for macroscopic characterization of microseismic cloud growth in two‐ and three‐dimensional space. The microseismic cloud, in addition to extending in the general direction of maximum principal stress, expanded in the direction of intermediate principal stress. The orientation of the least microseismic cloud growth was stable and almost identical to the minimum principal stress direction. Further, microseismic cloud shape ratios showed good agreement when compared with in situ stress magnitude ratios. The permeability tensor estimated from microseismicity also provided a good correlation in terms of direction and magnitude with the microseismic cloud growth. We show that in situ stress plays a dominant role by controlling the permeability of each existing fracture in the reservoir fracture system. Consequently, microseismic cloud growth can be scaled by in situ stress as a first‐order approximation if there is sufficient variation in the orientation of existing faults.
Screening of Salvadora persica leaves for antioxidant properties and total phenolic content

The objective of this research was to investigate the antioxidant properties of Salvadora persica leaf extracts using various in vitro assays and compare them with the total phenolic content. Petroleum ether, benzene, chloroform, methanol, and aqueous extracts were assessed for their ability to scavenge free radicals such as DPPH, superoxide, and hydroxyl radicals along with metal chelating capacity and reducing power. Estimation of phenolic content was done using the Folin-ciocalteu reagent and expressed as mg/g Gallic acid equivalent. The results demonstrated that all the solvents exhibited significant concentration-dependent free radical scavenging activity. Among the five extracts, the methanolic extract displayed the highest antioxidant activity and contained 52.64 mg/g Gallic acid equivalents (GAE) of phenolic content. The study identified significant correlation between the total phenolic content and the antioxidant assays suggesting role of phenolic compounds to the antioxidant activity of S. persica extracts. These findings suggest that the methanolic extract of S. persica is rich in phenolic compounds, which may account for its potent antioxidant activity. Consequently, these results emphasize the potential of S. persica as a valuable source of natural antioxidants and provide scientific support for its use in treating various health conditions.
Financial Inclusion and Its Impact on Economic Growth: An Empirical Evidence from South Asian Countries

Financial inclusion contributes to the growth of a country through developing financial infrastructure, which accelerates economic activities and creates employment. The study attempted to explore the contribution of financial inclusion on economic growth in 4 South Asian countries. In my study, I used various panel data models, and several measures of financial inclusion to reveal the relationship between economic growth and financial inclusion. The findings of the study confirmed that financial inclusion had a positive impact on economic growth in those countries although the extent of effect varies across different measures of financial inclusion. Therefore, policy makers in these countries must take necessary steps to accelerate financial inclusion activities to achieve robust economic growth.
Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

A procedure to optimally assimilate Atmospheric Infrared Sounder (AIRS) thermodynamic profiles using WRF-Var is described. The paper focuses on the development of background error covariances and an optimal methodology for ingesting the AIRS profiles into an analysis by assigning separate land and water sounding error characteristics. The version 5.0 AIRS profiles contain information about the quality of each temperature layer, which is used to select the highest quality data at each profile location. Preliminary assessment of the impact of the AIRS profiles will focus on optimized tuning of the WRF-Var and comparison of analysis soundings to radiosondes.
Application of Deep Learning in Multitemporal Remote Sensing Image Classification

The rapid advancement of remote sensing technology has significantly enhanced the temporal resolution of remote sensing data. Multitemporal remote sensing image classification can extract richer spatiotemporal features. However, this also presents the challenge of mining massive data features. In response to this challenge, deep learning methods have become prevalent in machine learning and have been widely applied in remote sensing due to their ability to handle large datasets. The combination of remote sensing classification and deep learning has become a trend and has developed rapidly in recent years. However, there is a lack of summary and discussion on the research status and trends in multitemporal images. This review retrieved and screened 170 papers and proposed a research framework for this field. It includes retrieval statistics from existing research, preparation of multitemporal datasets, sample acquisition, an overview of typical models, and a discussion of application status. Finally, this paper discusses current problems and puts forward prospects for the future from three directions: adaptability between deep learning models and multitemporal classification, prospects for high-resolution image applications, and large-scale monitoring and model generalization. The aim is to help readers quickly understand the research process and application status of this field.
The Implications of the Planning of Beijing’s Imperial City for Sustainable Community Development

China is experiencing the unprecedentedly rapid urbanization hence how to build a sustainable city with Chinese featuresbecomes a common challenge for city planners and researchers in the field of sustainability. Beijing has been the imperialcapital of China for more than eight hundred years and is deeply embedded within ancient Chinese urban planning theoriesand thoughts; for this reason it is chosen as the subject of this study. The history of Beijing as an imperial city from theYuan Dynasty to the Qing Dynasty (1267-1912) is reviewed under the framework PEBOSCA, an assessment framework ofsustainable community development which derives from UN HABITAT Agenda. The state of the seven resources ofsustainability is outlined to demonstrate the sustainability of Beijing’s imperial city planning history. Following this,sustainability was assessed at micro- and macro-levels: first the quadrangle as the basic unit of the city is documented andassessed with the Green Building Assessment Standard of China and the LEED for Homes Ranking system in a qualitativeapproach; then the city as a whole was analyzed to assess the interrelationships between the ancient Chinese urban theory –the Fengshui Theory – and urban ecology to understand its implications for the sustainable city planning.The study shows that although sustainable development is becoming a global issue, the key to the challenges faced is local.Integrated with modern technologies, the quadrangle design and the Fengshui Theory will inspire future sustainablecommunity planning and sustainable development.
Milk Yields and Milk Fat Composition Promoted by Pantothenate and Thiamine via Stimulating Nutrient Digestion and Fatty Acid Synthesis in Dairy Cows

Simple Summary Coated calcium pantothenate or coated thiamine supplementation potentially promotes milk production by stimulating nutrient digestion and fatty acids synthesis of the mammary gland in dairy cows. Owing to the synergistic effect of pantothenate and thiamine on the regulation of energy metabolism, the combined addition of coated calcium pantothenate and coated thiamine will more effectively promote lactation performance than that achieved by coated calcium pantothenate or coated thiamine alone. Further research is needed to determine the influences of coated calcium pantothenate or/and coated thiamine on the development of the mammary gland. Abstract Considering the synergistic effect of pantothenate and thiamine on the regulation of energy metabolism, this study investigated the influences of coated calcium pantothenate (CCP) and coated thiamine (CT) on milk production and composition, nutrients digestion, and expressions of genes involved in fatty acids synthesis in mammary glands. Forty-four multiparous Chinese Holstein cows (2.8 ± 0.19 of parity, 772 ± 12.3 kg of body weight [BW], 65.8 ± 8.6 days in milk [DIM] and 35.3 ± 1.9 kg/d of milk production, mean ± SD) were blocked by parity, BW, DIM, and milk production, and they were allocated into one of four treatments in a 2 × 2 factorial block design. Additional CCP (0 mg/kg [CCP−] or 55 mg/kg dry matter [DM] of calcium pantothenate from CCP [CCP+]) and CT (0 g/kg [CT−] or 5.3 mg/kg DM of thiamine from CT [CT+]) were hand-mixed into the top one-third of total mixed ration. Both CCP and CT additives increased milk production, fat content, true protein, and lactose by promoting nutrient digestibility. The CCP or/and CT supplementation induced the elevation of C11:0, C12:0, C13:0, C14:0, C14:1, C15:0, C15:1, C16:00, C16:1, C24:00, C24:1 fatty acids, saturated fatty acid, and C4-16 fatty acid contents in milk fat; but it decreased C17-22 fatty acid content. Ruminal total VFA content was increased, but pH was decreased by both additives. The ruminal fermentation pattern was altered, and a tendency of acetate formation was implied by the increased acetate-to-propionate ratio after both additives’ supplementation. The expressions of PPARγ, SREBPF1, ACACA, FASN, SCD, and FABP3 mRNAs were enhanced by CCP or CT addition, but the relative expression of LPL mRNA was upregulated by CT addition only. Additionally, blood glucose, triglyceride, insulin-like growth factor-1, and total antioxidant capacity were promoted by both additives. The combination of CCP and CT more effectively increased the ruminal total VFA concentration, the acetate to propionate ratio, and blood glucose level, and decreased ammoniacal nitrogen concentration than that achieved by CCP or CT alone. The results suggested that CCP and CT supplementation stimulated lactation performance by promoting nutrient digestion and fatty acid synthesis in the mammary glands.
Alignment of liquid crystals using Langmuir‒Blodgett films of unsymmetrical bent-core liquid crystals

ABSTRACT The properties of the thin films of liquid crystal (LC) molecules can be governed easily by external fields. The anisotropic structure of the LC molecules has a large impact on the electrical and optical properties of the film. The Langmuir monolayer (LM) of LC molecules at the air–water interface is known to exhibit a variety of surface phases which can be transferred onto a solid substrate using the Langmuir‒Blodgett (LB) technique. Here, we have studied the LM and LB films of asymmetrically substituted bent-core LC molecules. The morphology of LB film of the molecules is found to be a controlling parameter for aligning bulk LC in the nematic phase. It was found that the LB films of the bent-core molecules possessing defects favour the planar orientation of nematic LC, whereas the LB films with fewer defects show homeotropic alignment. The defect in LB films may introduce splay or bend distortions in the nematic near the alignment layer which can govern the planar alignment of the bulk LC. The uniform layer of LB film facilitates the molecules of nematic to anchor vertically due to a strong van der Waals interaction between the aliphatic chains leading to a homeotropic alignment. Graphical Abstract
Superposition States on Different Axes of the Bloch Sphere for Cost-Effective Circuits Realization on IBM Quantum Computers

A proposed method for preparing the superposition states of qubits using different axes of the Bloch sphere. This method utilizes the Y-axis of the Bloch sphere using IBM native (square root of X) gates, instead of utilizing the X-axis of the Bloch sphere using IBM non-native Hadamard gates, for transpiling cost-effective quantum circuits on IBM quantum computers. In this paper, our presented method ensures that the final transpiled quantum circuits always have a lower quantum cost than that of the transpiled quantum circuits using the Hadamard gates.
Bacchus Long‐Term (BLT) data set: Acquisition of the agricultural multimodal BLT data set with automated robot deployment

Achieving a robust long‐term deployment with mobile robots in the agriculture domain is both a demanded and challenging task. The possibility to have autonomous platforms in the field performing repetitive tasks, such as monitoring or harvesting crops, collides with the difficulties posed by the always‐changing appearance of the environment due to seasonality. With this scope in mind, we report an ongoing effort in the long‐term deployment of an autonomous mobile robot in a vineyard, with the main objective of acquiring what we called the Bacchus Long‐Term (BLT) data set. This data set consists of multiple sessions recorded in the same area of a vineyard but at different points in time, covering a total of 7 months to capture the whole canopy growth from March until September. The multimodal data set recorded is acquired with the main focus put on pushing the development and evaluations of different mapping and localization algorithms for long‐term autonomous robots operation in the agricultural domain. Hence, besides the data set, we also present an initial study in long‐term localization using four different sessions belonging to four different months with different plant stages. We identify that state‐of‐the‐art localization methods can only cope partially with the amount of change in the environment, making the proposed data set suitable to establish a benchmark on which the robotics community can test its methods. On our side, we anticipate two solutions pointed at extracting stable temporal features for improving long‐term 4D localization results. The BLT data set is available at https://lncn.ac/lcas-blt.
FAT-based adaptive and velocity feedback control of cooperative manipulators handling a flexible object

The previous regressor-based control method to control two cooperative manipulators in handling a deformable object leads to complex calculations and complicated programming in experimental hardware tests. There is an existing lack of studies about the development of the controller based on a partial differential equation (PDE)-based model and considering the model’s uncertainties. Previous studies have shown fewer experimental validations regarding two cooperative manipulators that handle deformable objects under uncertain model parameters. This study proposes a composite controller comprising a function approximation technique (FAT)-based adaptive control (FATAC) for a slow subsystem and a velocity feedback control (VFC) for a fast subsystem. The proposed FATAC is used for trajectory tracking, and VFC is used to suppress the vibration of the deformable object. Lyapunov stability analysis has been carried out to design controllers that stabilize a non-linear system of two cooperative manipulators handling the flexible object. Simulation and hardware experimental tests have been carried out to validate the performance of proposed controllers. The results verified that the proposed composite controller comprising the FATAC has successfully driven the cooperative manipulators to handle the deformable object so that it follows the desired trajectories. The VFC has successfully suppressed the transverse vibration of the deformable object.
Evaluation of Normalized Difference Vegetation Index by Remote Sensing with Landsat Satellites in the Tayacaja Valley in the Central Andes of Peru

The research sought to evaluate the normalized difference vegetation index (NDVI) of the study area located in the province of Tayacaja, which includes the districts of Acraquia, Ahuaycha, Pampas and Daniel Hernández, which is part of the central Andes of Peru. The data were collected in low water seasons with a longitudinal cut of 30 years with one sample per year, starting in 1993 until 2022; these samples corresponded to the month of August of each year. The images were extracted from maps from Landsat satellite databases, which were filtered for low cloud cover to avoid interference with the images. Maps from 1993 to 2012 were obtained from Landsat 5 satellite, while from 2013 to 2022 data were obtained from Landsat 8 satellite. The normalized difference vegetation index was determined using Quantum GIS based on the red and near infrared maps; being the minimum NDVI value obtained -0.18, which corresponds to the aquatic body of the Upamayu River that crosses from west to east the study area; while the highest NDVI obtained was 0.79 indicating a greater vegetation cover constituted by mainly eucalyptus plants. The mean NDVI of the 30 years is close to 0.21; this is an indicator that the vegetation is scarce and that it is decreasing mainly due to population growth.
Reliability of Self-Screening for Intrinsic Capacity Impairments Using the ICOPE Monitor App

Aim To verify the inter-rater agreement of the Integrated Care for Older People (ICOPE) STEP 1 screening tool using the ICOPE Monitor app, comparing self-assessment to a screening performed by a health professional. Methods We compared the results of the ICOPE Step 1 obtained by self-screening with those obtained by a professional screening using Gwet’s agreement coefficient in two studies. Study 1 tested inter-rater reliability in participants to the INSPIRE-T cohort who agreed to undergo the self-and the professional screening on the same day. Study 2 used data from the INSPIRE-ICOPE care cohort. We included real-life users of the French health system whose first ICOPE Step 1 was a self-assessment followed by a professional Step 1within 130 days (mean=76 days, SD=60). Results Study 1 included 79 participants (45 aged less than 60, 34 aged 60 and over, 60% female, mean (SD) age of 54.5 (18.5) years). Of the 207 participants in Study 2, 49 were less than 60, and 158 were 60 and over (54% female, mean (SD) age 67 (16.1) years). Agreement coefficients in Study 1 ranged from 0.49 (CI95% 0.24; 0.66) in the cognition domain–moderate agreement) to 0.99 (CI95% 0.96;1.00) in the nutrition domain–very good agreement); and in Study 2 from 0.36 (CI95% 0.23;0.49) in the cognition domain to 0.97 (95% 0.95;1.00) in the nutrition domain. The agreement coefficients for the cognition and hearing domains were higher for the participants aged <60 than those aged 60 and over. The time orientation items (cognition) showed high reliability. Conclusion Our study supports using ICOPE Step 1 as a self-assessment screening tool. High reliability was found for intrinsic capacity’s nutrition, psychological, and locomotion domains, regardless of age. We discuss aspects of the self-assessment of cognition, vision, and hearing domains when using the ICOPE monitor app in older adults.
Projecting extreme heat-related mortality in Europe under climate change

The assessment of health impacts of extreme hot weather under climate change is important for adaptation and mitigation actions. This thesis has developed techniques for estimating changes in heat-related mortality in Europe, with a focus on extreme daily mortality counts. The use of these techniques is illustrated through the projections of extreme elderly mortalities for London, UK and Budapest, Hungary from 2010 to 2099, using temperature projections from the perturbed physics ensemble of the regional climate model HadRM3. The present-day relationship between daily number of deaths and temperatures at each location is modelled by Poisson generalized additive models. In order to account for possible discrepancies in climate model simulations, temperature projections from HadRM3 are calibrated by two approaches, bias correction and change factor. These are based on assumptions on the relationships in location, scale and shape between observed andmodelled temperature distributions. In particular, a novel method using the Box-Cox transformation is developed to correct the bias in the upper tails of present-day simulated temperature distributions. Finally, future mortalities are projected by driving the mortality models with calibrated temperature projections. Results of temperature calibration show that the two calibration approaches give substantially different estimates of future extreme temperatures. The estimates of 10-summer temperature return level by the two approaches differ bymore than 4 ◦C over many parts of Europe in the period 2070 to 2099. For London and Budapest, the effect of this calibration uncertainty on extreme temperature projections is comparable to the effect of the uncertainty in climate model parameters which is estimated by the range of perturbed physics ensemble estimates. These two sources of uncertainties, together with the uncertainty in how the mortality-temperature relationship is modelled, contribute to large uncertainties in extreme mortality projections. Assuming constant elderly population in the future, the projected change in the 2-summer return level of number of daily elderly deaths in the period 2070 to 2099 relative to the the present-day ranges from−12% to +75% for London and from −16% to +22% for Budapest. 2