Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic analysis of an interior optimal control problem governed by Stokes equations

This article introduces an interior optimal control problem (OCP) in a two‐dimensional domain with a highly oscillatory boundary governed by the stationary Stokes equations. We consider the periodic controls in the oscillating region of the domain and use the unfolding operators to characterize the optimal controls. We establish the convergences of optimal control, state, and pressure in a suitable space to the ones of the limit system in a fixed domain.
Research on the Influence of After-sale Service on Customer Loyalty -- A Case Study of Budget Hotels

Customer loyalty is very important to the hotel’s survival and development, so the hotel will maintain and improve customer loyalty in all aspects. The same is true in budget hotels. In this paper, budget hotels were selected as the research object, and college students as the research object, through the way of a questionnaire survey to study how after-sale service affects customer loyalty. In the survey, additional services are used to refer to after-sales services. According to the service quality model, additional services were divided into five aspects: responsiveness, caring, compensatory, reliability, and assurance. Through regression analysis, only caring and assurance of additional services had a positive impact on customer loyalty. Therefore, based on the characteristics of college students, it was suggested that budget hotels should be customized in the design and arrangement of additional services. Evaluate the quality of customized services and make service corrections. At the same time, the influence of selected variables on customer loyalty can be verified in other groups.
Phylogenetic Characterisation of the Full Genome of a Bagaza Virus Isolate from Bird Fatalities in South Africa

Bagaza virus (BAGV), a member of the Ntaya serogroup in the Flavivirus genus of the Flaviviridae, was isolated from the brain tissue of a Himalayan monal pheasant that died following neurological signs in Pretoria, South Africa in 2016. Next-generation sequencing was carried out on this isolate resulting in a genome sequence of 10980nt. The full genome sequence of this isolate, designated ZRU96-16, shared 98% nucleotide identity with a BAGV isolate found in Culex univitattus mosquitoes from Namibia and 97% nucleotide identity with a Spanish BAGV sequence isolated from an infected partridge. In total, seven amino acid variations were unique to ZRU96-16 after alignment with other BAGV and Israel turkey meningoencephalomyelitis (ITV) genomes. The 3′UTR sequence of ZRU96-16 was resolved with sufficient detail to be able to annotate the variable and conserved sequence elements within this region. Multiple sequence alignment of the 3′UTR suggested that it could be useful in lineage designation as more similar viruses carried similar mutations across this region, while also retaining certain unique sites. Maximum likelihood phylogenetic analysis revealed two clusters containing both BAGV and ITVs from Europe, the Middle East and Africa. Broadly, temporal clustering separated isolates into two groups, with one cluster representing viruses from the 1960–2000’s and the other from 2010 onwards. This suggests that there is consistent exchange of BAGV and ITV between Europe and Africa. This investigation provides more information on the phylogenetics of an under-represented member of the Flaviviridae and provides an avenue for more extensive research on its pathogenesis and geographic expansion.
Recognition of Everyday Activities through Wearable Sensors and Machine Learning

Over the past several years, the use of wearable devices has increased dramatically, primarily for fitness monitoring, largely due to their greater sensor reliability, increased functionality, smaller size, increased ease of use, and greater affordability.These devices have helped many people of all ages live healthier lives and achieve their personal fitness goals, as they are able to see quantifiable and graphical results of their efforts every step of the way (i.e. in real-time). Yet, while these device systems work well within the fitness domain, they have yet to achieve a convincing level of functionality in the larger domain of healthcare. As an example, according to the Alzheimer’s Association, there are currently approximately 5.5 million Americans with Alzheimer’s Disease and approximately 5.3 million of them are over the age of 65, comprising 10% of this age group in the U.S. The economic toll of this disease is estimated to be around $259 billion. By 2050 the number of Americans with Alzheimer’s disease is predicted to reach around 16 million with an economic toll of over $1 trillion. There are other prevalent and chronic health conditions that are critically important to monitor, such as diabetes, complications from obesity, congestive heart failure, and chronic obstructive pulmonary disease (COPD) among others. The goal of this research is to explore and develop accurate and quantifiable sensing and machine learning techniques for eventual real-time health monitoring by wearable device systems. To that end, a two-tier recognition system is presented that is designed to identify health activities in a naturalistic setting based on accelerometer data of common activities. In Tier I a traditional activity recognition approach is employed to classify short windows of data, while in Tier II these classified windows are grouped to identify instances of a specific activity. Everyday activities that were explored in this research include
Effects of pre-transplant chest physical therapy on spirometric values and respiratory muscle strength in patients waiting for allogeneic hematopoietic stem cell transplantation: a randomized controlled trial

Introduction Many noninfectious pulmonary complications occur immediately within the first few weeks after allogeneic hematopoietic stem cell transplantation (allo-HSCT). This study aimed to evaluate the efficacy of chest physical therapy (CPT) performed during the pre-transplant period in terms of spirometric values and respiratory muscle strength (RMS) in patients waiting for allo-HSCT. Material and methods Fifty patients aged 40 to 55 years who were scheduled for allo-HSCT were randomly allocated into two equal-sized groups, a CPT group and a control group. The CPT group (n = 25) received CPT in addition to routine medical treatment, while the control group (n = 25) received routine medical treatment only. Patients in both groups received standard physical therapy during the inpatient waiting period. Interventions were conducted daily for 3 weeks before allo-HSCT. Pulmonary function (FEV1, FVC, and FEV1/FVC) was measured by spirometry, and RMS was measured by a respiratory pressure meter. A baseline assessment was done 3 weeks before allo-HSCT (T0), then at the end of treatment immediately before allo-HSCT (T1) and the last assessment at 3 weeks after allo-HSCT (T2) for all measured variables. Results In comparing the two groups at T1 and T2, the mean spirometric values and RMS, maximal inspiratory pressure, and maximal expiratory pressure were all improved significantly in the CPT group in comparison with the control group (p < 0.05). Conclusions Adding a 3-week CPT intervention to the pre-transplant rehabilitation program seems to be effective and safe for allo-HSCT recipients, as it improves pre-transplant pulmonary function and respiratory muscle strength and prevents their post-transplant decrease.
Modeling the Effect of Stress Ratio, Loading Frequency and Fiber Orientation on the Fatigue Response of Composite Materials

Fatigue life models are widely used to predict the fatigue behavior at arbitrary cycle counts of composite structures subjected to cyclic or highly dynamic loads. However, their predictive capacity and determination of model parameters are strongly dependent on loading conditions and large experimental efforts. This research aims to develop a new model which uses a single model parameter to predict the variation trend and distribution pattern of fatigue experimental data points subjected to different stress ratios, loading frequencies and fiber orientations. Validation of the model with several sets of experimental data shows that the proposed model is capable of adequately considering the effects of stress ratio, loading frequency and fiber orientation on the fatigue behavior of composite materials and correctly predicting the variation trend of the experimental data points using only one set of model parameters regardless of stress ratios, loading frequencies and fiber orientations.
Can antioxidant responses be induced by habitat fragmentation process?

we we individuals of (Amphibia: within five For individuals we also measured the glutathione-S-transferase (GST) and catalase (CAT) enzyme activity. Results showed a significant increase in individual GST activity for increasing levels of inbreeding, whereas no relationship was found for CAT. We also measured acetylcholinesterase to test the possible confounding effects of in no in enzyme activity found We argue that alterations and trigger the expression of GST for protection against hydrogen peroxide reactive oxygen species. We suggest using GST as a biomarker for environmental stressors with great caution and not to underestimate that the sources of stress deriving from habitat fragmentation could lead to an unbalance in the oxidative status, possibly increasing population susceptibility to infectious diseases and, potentially, spillover events and zoonoses.
Membrane Fixation using Healing Abutment during Guided Bone Regeneration: A Report of Two Cases

Guided bone regeneration, a dental surgical procedure, is used to promote growth of the alveolar hard tissue for bone defect with the help of membranes and other barrier techniques. The membrane fixation technique plays a significant role in the success of the bone graft. Several methods have been proposed for membrane fixation, such as the use of a holding suture and a tag pin. However, there are certain disadvantages as the procedures are cumbersome and often a secondary procedure is required. In this case report, we describe a simple method of membrane fixation using a healing abutments during guided bone regeneration, along with implant placement at the bone level.
Grouping and Occlusion in Perception and Art

In the first part of the lecture several meanings of the term “perceptual grouping” as it applies to contour and texture will be distinguished, especially grouping as segregation and grouping as cohesion. This will be expanded to a discussion of the segregation of surfaces in depth and the occlusion cues on which this is based, which also underlie the perception of “subjective contours”. Special attention will be given to the way pictorial cues interact with binocular stereopsis to influence perceived surface occlusion. Finally, the depiction of occlusion will be discussed as a major feature of art, with support for Kanizsa’s view that this is a perceptual not a conceptual achievement. As such I show that surface segregation can fail perceptually even when the conceptual intention is clear. 1. Grouping 1.1. Major grouping concepts from Gestalt until now • Definition. "Grouping: the fact that observers perceive some elements of the visual field as going together more strongly than others" (Wagemans, Elder, Kubovy, Palmer, Peterson, Singh & von der Heydt, 2012, p. 1180). • Grouping results in “emergent features”. These are properties of the group that are different from the sum of the parts. • Pragnanz. The visual system sees the “best” figure possible given the current conditions. “Best” is usually interpreted as the most regular. (Regularity has been quantified in various ways). The following distinctions are largely absent from traditional and current treatments: • Grouping as SEGMENTATION of elements versus grouping as COHESION. • Grouping as UNIT FORMATION (producing emergent features) versus grouping as AGGREGATION (without emergent features). I'll show that these processes can be operationally distinguished with different roles. 1.2. Laws of grouping (illustrated in Figure 1) Figure 1. (from Rock and Palmer, 1990) illustrates a number of the well-known Wertheimer principles of grouping plus two new ones.
Imaging of Lipid Peroxidation-Associated Chemiluminescence in Plants: Spectral Features, Regulation and Origin of the Signal in Leaves and Roots

Plants, like most living organisms, spontaneously emit photons of visible light. This ultraweak endogenous chemiluminescence is linked to the oxidative metabolism, with lipid peroxidation constituting a major source of photons in plants. We imaged this signal using a very sensitive cooled CCD camera and analysed its spectral characteristics using bandpass interference filters. In vitro oxidation of lipids induced luminescence throughout the visible spectrum (450–850 nm). However, luminescence in the red spectral domain (>640 nm) occurred first, then declined in parallel with the appearance of the emission in the blue-green (<600 nm). This temporal separation suggests that the chemical species emitting in the blue-green are secondary products, possibly deriving from the red light-emitting species. This conversion did not seem to occur in planta because spontaneous chemiluminescence from plant tissues (leaves, roots) occurred only in the red/far-red light domain (>640 nm), peaking at 700–750 nm. The spectrum of plant chemiluminescence was independent of chlorophyll. The in vivo signal was modulated by cellular detoxification mechanisms and by changes in the concentration of singlet oxygen in the tissues, although the singlet oxygen luminescence bands did not appear as major bands in the spectra. Our results indicate that the intensity of endogenous chemiluminescence from plant tissues is determined by the balance between the formation of luminescent species through secondary reactions involving lipid peroxide-derived intermediates, including singlet oxygen, and their elimination by metabolizing processes. The kinetic aspects of plant chemiluminescence must be taken into account when using the signal as an oxidative stress marker.
Earthquake induced Deterministic Damage and Economic Loss Estimation for Kolkata, India

The city of Kolkata, the State Capital of West Bengal is jolted by earthquakes time and again from the tectonic regimes of the Central Himalaya, highly seismogenic Northeast India and the active tectonics of Bengal Basin which is a pericratonic tertiary basin on which the City is located. Earthquake disaster mitigation and management necessitates seismic hazard assessment for the generation of design response spectra at a site of interest with a zone factor for the computation of seismic coefficient to be adapted in building codes. The surface consistent probabilistic seismic hazard model of Kolkata for 475 years of return period have been used for the modeling of damage potential of buildings, human casualty and economic loss employing the widely used SEismic Loss EstimatioN applying a logic tree Approach (SELENA) in a relational analysis protocol considering eleven model building types. The demand spectrum curve of a spectral acceleration through a judicious interaction with the building capacity curve and fragility curve yields the damage state probability of the same in terms of slight, moderate, extensive and complete. Human casualty levels are also computed applying SELENA for three different times of the day viz. Night, Day and Commuting time. The economic loss to the tune of ~231 billion of Indian Rupees due to building damage only have been estimated within 300 socioeconomic clusters in the City. It is expected that this model will go a long way in safe urbanization process with well-defined disaster mitigation and management guidelines for the city of Kolkata.
Fast and effective pedestrian detection based on low-level visual features combination

Abstract. Automatic pedestrian detection is a crucial task for intelligent vehicles as it helps avoid car-to-pedestrian accidents. Recently, several approaches have been proposed to improve detection accuracy, such as the channel-based family, which is based on the aggregation of channel features (e.g., HOG + LUV) to represent the shape of pedestrians. Previous handcrafted-based detectors significantly improved the detection performance by applying different filters to channel features. However, when there are similar-looking background objects, their detection performance suffers due to the lack of texture features. Another drawback of these approaches lies in their high computational cost, limiting their use for real-world applications, especially for resource constrained systems. To mitigate these drawbacks while maintaining a distinguishable detection accuracy, we propose a method that combines a simple but effective texture descriptor based on local binary patterns with HOG + LUV. The concatenated features are used to train a boosted decision trees classifier. To evaluate our approach, we carried out extensive experiments on four well-known datasets, including INRIA, ETH, KITTI, and Caltech. Experimental results show that the proposed method achieves a competitive performance to the channel-based detectors with significantly lower computational cost; it runs at 91.64 and 6.08 times faster than the closest competitors detectors on the INRIA and Caltech datasets, respectively. Furthermore, it outperforms these methods when evaluating under the corrected annotations of the Caltech dataset.
Mindfulness-Based Stress Reduction in Breast Cancer Survivors with Chronic Neuropathic Pain: A Randomized Controlled Trial

Objectives The purpose of this study was to compare the effects of group-delivered mindfulness-based stress reduction as compared to a waitlist control group among breast cancer survivors living with CNP. Methods A randomized controlled trial design was applied, and outcomes collected included pain, emotional function, quality of life, and global impression of change. Results A total of 98 women were randomized and included in analyses. The sample included 49 women in the mindfulness-based stress reduction group, and 49 women in the waitlist control group. The intervention group participants (mean age 51.3 years, standard deviation = 11.4) and waitlist participants (mean age 55.1 years, standard deviation = 9.6) reported an average pain duration of approximately three years. No significant differences were found on the primary outcome of the proportions of women with reduced pain interference scores from the time of randomization to 3 months after the intervention was received. No significant changes were found among secondary outcomes. Conclusion Our randomized clinical trial did not find significant benefits of group-based mindfulness-based stress reduction for the management of CNP. The current study findings should be replicated and are important to consider given ongoing concerns that nonsignificant results of mindfulness-based stress reduction are often unpublished.
A Novel Performance Enhancement Scheme for Doubly-Fed Induction Generator-Based Wind Power Systems under Voltage Sags and Swells

Abstract Wind power is a major contributor in the renewable energy sector but it faces some issues regarding modern grid-code compliance. Popular wind power systems based on Doubly-Fed Induction Generators (DFIG) need additional protection under grid voltage disturbances. They also need to support the grid voltage under such transient occurrences. This paper presents a novel performance enhancement scheme for DFIGs subjected to symmetrical and asymmetrical voltage sags and swells at the Point of Common Coupling (PCC). The scheme comprises a protection system and a reactive power management system working simultaneously under the command of a supervisory control system. The protection system protects the DFIG converter by limiting the overcurrent in the Rotor Side Converter (RSC) of the DFIG and keeping the dc-link capacitor voltage within an acceptable range; whereas, the reactive power management supports the grid voltage by either injecting or absorbing reactive power to reduce the magnitude of voltage sags and swells. It is found that the performance of the DFIG wind generation system improves significantly under the proposed scheme. A grid-connected 9-MW DFIG wind farm is used for simulation in MATLAB/Simscape Power Systems.
A Systematic Review of Horticultural Therapy’s Influence on Chinese Older Adults’ Psychosocial Wellbeing

Aim: This systematic review aims to evaluate changes in Chinese older adults’ psychosocial wellbeing after receiving horticultural therapy, and examine existing evidence regarding horticultural therapy’s effectiveness in a Chinese setting. Method: Intervention studies measuring relevant outcomes amongst older adults and conducted in China were identified from ASSIA, CIHAHL Plus, PsycINFO, EMBASE, MEDLINE, SCOPUS, Web of Science Core Collection and CNKI. Cochrane risk of bias assessment tools were used to appraise study quality. Result: 16 studies were selected, among which four were published in English and 12 in Chinese. Findings suggested that after receiving horticultural therapy, older adults’ psychosocial wellbeing is generally improved, but causal relationships between improvements and horticulture therapy were less clear. Conclusion: Features of horticultural therapy conducted in China is with its cultural and social uniqueness. Existing evidence supports the post-intervention benefits on completion of horticultural therapies, but the limitations in programme design, sample representativeness and methodological robustness limited the quality of the evidence.
Model-Based Design and Optimization of Electrochemical Processes for Sustainable Aviation Fuels

Abstract: Aviation accounts for around 12% of all CO2 emissions from the transport sector, neces-sitating the use of sustainable aviation fuels. Electrofuels, which are gained from renewable sources, are attractive options for sustainable aviation fuels. Model-based electrochemical process design and optimization could very well assist in improved design and operation methods towards better conversion, selectivity, energy conversion, and economics - at a lower cost and time than the exper-imental approach. Moreover, nowadays, process models are also an indispensable technology for realizing Industry 4.0 and digital twin ideas for process intensification and monitoring. Thus, to design better electrofuel manufacturing processes and create digital process representations, this paper makes use of a first-principles model for electroreduction of furfural to furfuryl alcohol and methylfuran as well as hydrogen evolution. In detail, the Volmer reaction forms adsorbed hydrogen, represented by a Frumkin type isotherm. The hydrogen evolution is described by the potential dependent Heyvrosky reaction and the potential independent Tafel reaction. We critically discuss the simulation results using reference data and show its potential application for an AI-assisted process modeling strategy, i.e., predicting an optimal potential profile using the derived first-prin-ciples model and a neural network.
External Debt and Real Exchange Rate Volatility in South Asia

This study empirically examines the mechanism that connects debt accumulation to exchange rate volatility through the lens of important macroeconomic variables in South Asian Countries. One of the most influential explanatory factors behind exchange rate volatility is deemed as the flow of external debt for these countries. Using data from the World Development Indicators for the period 1980–2020, it is shown that external debt increases exchange rate volatility, significantly. The model is identified via panel Granger tests for relevant variables, estimated for a wide range of covariates and tested for all possible sources of endogeneity via subsequent robustness analyses. JEL Classification: C33, F31, H6, O53