Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Cluster-Level Constructs Measured by Individual Responses: Configuring a Shared Approach

When multiple items are used to measure cluster-level constructs with individual-level responses, multilevel confirmatory factor models are useful. How to model constructs across levels is still an active area of research in which competing methods are available to capture what can be interpreted as a valid representation of cluster-level phenomena. Moreover, the terminology used for the cluster-level constructs in such models varies across researchers. We therefore provide an overview of used terminology and modeling approaches for cluster-level constructs measured through individual responses. We classify the constructs based on whether (a) the target of measurement is at the cluster level or at the individual level and (b) the construct requires a measurement model. Next, we discuss various two-level factor models that have been proposed for multilevel constructs that require a measurement model, and we show that the so-called doubly latent model with cross-level invariance of factor loadings is appropriate for all types of constructs that require a measurement model. We provide two illustrations using empirical data from students and organizational teams on stimulating teaching and on conflict in organizational teams, respectively.
The GIS book : understanding the value and implementation of geographic information systems

Part 1 Defining GIS: an overview of the GIS industry and GIS software defining a GIS using a GIS why implement a GIS? GIS technology trends four leading GIS products in review. Part 2 Selecting and implementing a GIS: implementing a GIS the need for planning a GIS selecting a GIS keys to successful implementation the pitfalls of a GIS using a GIS consultant staffing a GIS financial justification of GIS base map accuracy getting CADD data into a GIS a case study in GIS implementation - Prince William County, Virginia. Appendices: resources for GIS information and training glossary of commonly-used GIS terms.
Dynamic Characteristics Analysis of Metallurgical Waste Heat Radiative Drying of Thin Layers of Sewage Sludge

The utilization of metallurgical waste heat for urban sludge drying and dewatering not only affects the subsequent cost of sludge treatment but also provides a pathway for the rational utilization of metallurgical waste heat. The influence of different experimental conditions on sludge drying characteristics, such as drying temperature and thickness, was analyzed based on metallurgical waste heat. Based on the analysis and evaluation of the drying kinetics parameters of commonly used drying mathematical models, a modified Midilli drying kinetic model is proposed. The kinetic parameters and effective diffusivity of sludge drying were analyzed in three stages of sludge drying: rising rate, constant rate, and falling rate. By utilizing the Arrhenius equation, the relationship between the effective diffusion coefficient and thermodynamic temperature is established, revealing the apparent activation energies for the three stages of urban sludge drying as 29.772 kJ·mol−1, 37.129 kJ·mol−1, and 39.202 kJ·mol−1, respectively. This is closely related to the migration, diffusion, and mass transfer resistance of sludge moisture, indicating that the thickness of sludge accumulation affects the drying time of sludge during the treatment of municipal sludge.
Heterogeneity in Adolescents’ Non-Suicidal Self-Injury Behaviour Trajectories Based on the Group-Based Trajectory Model and a Decision Tree Analysis of Family-Related Determinants

Background Non-suicidal self-injury (NSSI) is a global public health problem. While some studies have noted the importance of behavioural development patterns in NSSI, most NSSI research is based on cross-sectional survey data. Few studies explore the time-series heterogeneity of trajectories of NSSI symptoms and family-related influencing factors of NSSI. Aim The purpose of the study was to identify the heterogeneity in trajectories of adolescents’ NSSI behaviour and their family-related influencing factors. Methods The group-based trajectory model (GBTM) was used to identify the heterogeneity in the NSSI behaviour trajectories of 208 adolescents in China. Next, the decision tree model (DTM) was used to analyse which family related factors influence the trajectory type. Results The GBTM revealed two heterogeneous trajectories of NSSI behaviour: the high–risk and low-risk NSSI behaviour groups. Next, DTM’s average accuracy was 83.2%. A total of seven independent variables were used for the DTM: gender, number of NSSIs in the past month, and family economic, family structure, family conflict, parental psychological control, parental behavior control and family intimacy risks. Family conflict risk was located at the root node and was the most important factor. Conclusion Heterogeneity within the population should be considered in the management of adolescents’ NSSI behaviours. Further, from the perspective of family system theory and cumulative risk, focusing on the adverse effect of multiple risk factors on adolescents’ NSSI addiction is more meaningful rather than the impact of single risk factors. Studies that use time series data should focus on the trend of dynamic changes in NSSI addiction characteristics over time.
O PAPEL DOS PARQUES DE CIÊNCIA E TECNOLOGIA NO CRESCIMENTO DAS VENDAS DAS EMPRESAS PORTUGUESAS

RESUMO O papel dos parques de ciência e tecnologia (PCT) no desenvolvimento econômico, especialmente no crescimento de empresas, tem merecido particular atenção por parte das políticas públicas dos diferentes países. Porém, na literatura não existe consenso sobre se a localização nesses parques tem efeitos positivos no crescimento em vendas das empresas. O objetivo deste artigo é alargar a discussão acerca dos efeitos dos PCT, proporcionando novas evidências empíricas. Para isso, utilizamos uma amostra de 553 firmas portuguesas localizadas nessas infraestruturas e uma amostra de controle de idêntica dimensão. O método de emparelhamento utilizado é o Propensity Score Matching (PSM), e a análise é efetuada com recurso ao método generalizado dos momentos em dados em painel dinâmico. A análise empírica não permite provar qualquer efeito estatisticamente significativo da localização das firmas em PCT sobre o seu crescimento em vendas.
Accelerated ISAR Sparse Imaging Based on Tight Frame and Projection Operator

For the actual inverse synthetic aperture radar (ISAR) system, some received pulses may be invalid or lost in the long coherent processing interval (CPI) due to nonideal conditions, such as target noncooperation or noise interference. Hence, it is usually difficult to obtain well-focused images for such sparse aperture ISAR data. To address this issue, a novel general analysis model with a tight frame for sparse ISAR imaging is proposed in this article, which operates directly on the ISAR image instead of the redundant sparse coefficient. Furthermore, with the help of the projection operator and majorization minimization algorithmic framework, a simple and effective accelerated iterative algorithm with general analysis model (AIA-GAM) is designed to solve the proposed ISAR imaging model, which only performs the simple proximal mapping in each iteration. The experimental results of simulation data and real measured data demonstrate that the proposed method has better imaging performance and faster convergence speed.
The Adaptation of Botrytis cinerea Extracellular Vesicles Proteome to Surrounding Conditions: Revealing New Tools for Its Infection Process

Extracellular vesicles (EVs) are membranous particles released by different organisms. EVs carry several sets of macromolecules implicated in cell communication. EVs have become a relevant topic in the study of pathogenic fungi due to their relationship with fungal–host interactions. One of the essential research areas in this field is the characterization protein profile of EVs since plant fungal pathogens rely heavily on secreted proteins to invade their hosts. However, EVs of Botrytis cinerea are little known, which is one of the most devastating phytopathogenic fungi. The present study has two main objectives: the characterization of B. cinerea EVs proteome changes under two pathogenic conditions and the description of their potential role during the infective process. All the experimental procedure was conducted in B. cinerea growing in a minimal salt medium supplemented with glucose as a constitutive stage and deproteinized tomato cell walls (TCW) as a virulence inductor. The isolation of EVs was performed by differential centrifugation, filtration, ultrafiltration, and sucrose cushion ultracentrifugation. EVs fractions were visualised by TEM using negative staining. Proteomic analysis of EVs cargo was addressed by LC-MS/MS. The methodology used allowed the correct isolation of B. cinerea EVs and the identification of a high number of EV proteins, including potential EV markers. The isolated EVs displayed differences in morphology under both assayed conditions. GO analysis of EV proteins showed enrichment in cell wall metabolism and proteolysis under TCW. KEGG analysis also showed the difference in EVs function under both conditions, highlighting the presence of potential virulence/pathogenic factors implicated in cell wall metabolism, among others. This work describes the first evidence of EVs protein cargo adaptation in B. cinerea, which seems to play an essential role in its infection process, sharing crucial functions with the conventional secretion pathways.
Targeted health promotion with guided nature walks or group exercise: a controlled trial in primary care

Background Contact with nature promotes wellbeing through diverse pathways, providing a potential way of supporting health especially in primary care, where patients commonly suffer from multimorbidity and poor general health. Social prescribing is a non-pharmaceutical approach for improving health as well as social inclusion. This field study explores and compares the effects of a nature-based and an exercise-based social prescribing scheme on mental wellbeing and sleep, in a primary care population. Methods Primary care patients identified to benefit from a general improvement to their health were recruited by nurses, doctors, or social workers to this non-randomized, intention-to-treat, pilot field-study. Participants (n = 79) chose between the group interventions, either taking part in guided walks in nature, including immersion in a forest with high biodiversity, or participating in a versatile sports program. Mental wellbeing was assessed with the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS), with additional questions evaluating self-rated health and sleep. Impact on mental wellbeing was explored in relation to perceived health. The amount and quality of sleep was measured with wrist-worn accelerometers. With a focus on everyday life impacts, the assessments took place before and after the 8-week intervention. All participants lived in Sipoo, Finland, an area with abundant accessible green space. Results Participants (mean age 57 years, 79% female) rated their general and mental health lower than the general population. Participation in the Nature-group resulted in improved mental wellbeing (change in WEMWBS by 3.15, p = 0.008), with a positive change for feeling relaxed, being cheerful, having energy to spare, feeling able to deal well with problems, feeling good about oneself and feeling close to other people. The Sports-group was beneficial for those initially rating their health as good. Sleep duration improved in the Sports-group, while participants in the Nature-group reported better sleep quality. Following the interventions there was improvement in perceived health and ability to function in both groups, while perceived mental health improved only in the Nature-group. Conclusion We attest that even in areas surrounded by greenery, active interventions can further improve health in a primary care population, and that nature-based interventions are beneficial for those in poor health. Clinical trial registration ClinicalTrials.gov, Identifier NCT05893212.
Hybrid Wideband Millimeter Wave Transceiver for Single-User Multi-Relay MIMO Systems

This paper proposes a hybrid wideband millimeter-wave (mm-Wave) beamforming technique for achievable rate maximization in single-user, multi-relay, multi-input multi-output (MIMO) systems. The underlying network architecture is of great practical importance from the perspective of hybrid precoding for enhancing coverage area, transmission range, link quality, and spectral efficiency. In hybrid transceivers, the analog processing component in the radio frequency (RF) section of the system essentially needs to follow an element-wise constant amplitude constraint, which makes the optimization problem non-convex and hence mathematically intractable. Therefore, it is quite a challenging task to obtain the global optimal solution. Moreover, the common analog precoder and combiner are required for different frequency-selective channels in broadband systems, which adds another layer of design complexity. To address this problem, the proposed algorithm transforms the original complicated optimization problem into a relatively simple form. Leveraging this, the complexity of the optimization problem is reduced through decoupled design using the norm preservation property of the unitary transform. Moreover, the analog beamforming design is decomposed into two sub-problems by exploiting statistical independence among the first hop and second hop channels. Each sub-problem is solved to harvest the array gain through RF precoding and combining using an alternative optimization framework. Finally, the frequency-selective baseband processing components are obtained by minimizing interference among transmitted data streams. The spectral efficiency of the proposed scheme is evaluated by changing system parameters under imperfect channel and phase noise (PN). Simulation results demonstrate that the achieved performance is close to full-complexity precoding and outperforms traditional algorithms.
Successful Elective Thoracoscopic Resection of Complicate Extralobar Bronchopulmonary Sequestration after Intrafoetal Vascular Laser Ablation: The Paediatric Surgeon's Point of View

Few reports of laser coagulation for foetal bronchopulmonary sequestration (BPS), a rare congenital malformation characterised by the absence of tracheobronchial connection and the presence of a systemic feeding artery, have been published. Additionally, very few of them focus also on the postnatal management, with results limited and controversial. Postnatal treatment of residual malformation remains debated, hence the need to share our experience of a combined pre- and postnatal approach to complicated extra-lobar BPS. We report the case of a female foetus with the diagnosis of a pulmonary lesion. Due to mediastinal shift, unilateral compressive hydrothorax, ascites, and hydrops, a foetal treatment with ultrasound-guided laser coagulation of the anomalous vessel was performed. At birth, due to the persistence of the malformation, an elective delayed thoracoscopical surgery was performed. Prenatal laser ablation for complicated BPS is a life-saving procedure not always resulting in lesion disappearance. Thoracoscopical surgical exploration in case of persistent lesions at birth offers the possibility of a minimally invasive sequestrectomy feasible and safe.
Accurate seismic inversion techniques in prospecting for small size archaeological features: the case of Akrotiri excavation area on Thera Island, Greece 1

A high resolution seismic inversion technique was used to explore the volcanic basement rock at Akrotiri archaeological site on Thera Island. The survey was carried out in the context of a big scale project, where the old monuments protective roof cover is being replaced by a new environmental and friendly construction which will be supported by 95 pillars embedded in the volcanic basemen rock. The target of the geophysical prospect was the man-made or natural cavities unveiled during the excavations of the foundation shafts, the presence of which might affect the construction response during an earthquake. The cross-shaft seismic tomography technique was adopted for this purpose. A number of synthetic examples and a calibration experiment at a shaft with a known natural cavity clearly indicated that the tomographic inversion is capable of providing highly resolved 2-D models. High S/N ratios ensured field seismic records of high quality. A set of stability tests was run to check the consistency of the method. Travel time residuals verified the validity of the final velocity depth sections while model complexity trends showed a consistency between models after a certain number of iterations. The reconstructed velocity fields were quite consistent with the expected velocities. Impressive low-velocity structures attributed to natural or man-made cavities were reported to the constructing group of engineers and a remedial action plan was undertaken to support and improve the ground behaviour.
Study of object detection in linear terahertz imaging systems

Abstract. A neural network-based system designed for automated detection of concealed items using a postal terahertz scanner is presented, with system optimization provided. A dataset of objects scanned by a THz scanner is introduced. A convolutional neural network is trained on this dataset of terahertz images to classify and detect whether an image contains a prohibited item or not. The system is tested using real-world samples, achieving an accuracy of 95.5% mAP@0.5. The results demonstrate the effectiveness of employing a neural network in postal terahertz scanners and its potential for use in security and surveillance applications.
Reflective-Mode Phase-Variation Submersible Sensor for Liquid Characterization

A one-port reflective-mode microwave submersible sensor based on an open-ended step-impedance microstrip line configuration, operating at a single frequency, useful for the dielectric characterization of liquids and the measurement of liquid composition in binary mixtures, is proposed in this article. The sensor constitutes two parts, namely, the microwave module, including the sensitive region, and a 3-D-printed case (made of polylactic acid—PLA), necessary for sealing, thus preventing from any liquid leakage to the nonsensing regions of the microwave module. To enhance the sensitivity, the open-ended line Section of the microwave module, i.e., the sensing region in contact with the liquid under test (LUT), is a quarter wavelength microstrip line with high impedance. Thus, the phase of the reflection coefficient is the output variable, highly dependent on the input variable—the dielectric constant of the LUT placed directly above the sensing region. In order to validate the sensing structure, a prototype device has been designed and fabricated. The average sensitivity to variations in the concentration of ethanol in solutions of deionized (DI) water is 1.22°/%, and sensor resolution is 2%. The fabricated sensor is resistant to liquid leakage, and therefore, it can be completely submerged for measuring purposes, acting as an effective measuring probe.
Therapeutic Drug Monitoring in Children and Adolescents: Findings on Fluoxetine from the TDM-VIGIL Trial

Fluoxetine is the recommended first-line antidepressant in many therapeutic guidelines for children and adolescents. However, little is known about the relationships between drug dose and serum level as well as the therapeutic serum reference range in this age group. Within a large naturalistic observational prospective multicenter clinical trial (“TDM-VIGIL”), a transdiagnostic sample of children and adolescents (n = 138; mean age, 15; range, 7–18 years; 24.6% males) was treated with fluoxetine (10–40 mg/day). Analyses of both the last timepoint and all timepoints (n = 292 observations), utilizing (multiple) linear regressions, linear mixed-effect models, and cumulative link (mixed) models, were used to test the associations between dose, serum concentration, outcome, and potential predictors. The receiver operating curve and first to third interquartile methods, respectively, were used to examine concentration cutoff and reference values for responders. A strong positive relationship was found between dose and serum concentration of fluoxetine and its metabolite. Higher body weight was associated with lower serum concentrations, and female sex was associated with lower therapeutic response. The preliminary reference ranges for the active moiety (fluoxetine+norfluoxetine) were 208–328 ng/mL (transdiagnostically) and 201.5–306 ng/mL (depression). Most patients showed marked (45.6%) or minimal (43.5%) improvements and reported no adverse effects (64.9%). This study demonstrated a clear linear dose–serum level relationship for fluoxetine in youth, with the identified reference range being within that established for adults.
SEMICONDUCTORS AND DIELECTRICS

This work presents the ab initio study of transition-metal phthalocyanines within a PBE0 hybrid functional. The list of metal impurities includes manganese, iron, cobalt, nickel, copper, and zinc. All calculations of isolated molecules have been performed with the use of the projector augment-wave method. For iron phthalocyanine, we have performed four calculations with different values of the mixing parameter α (the value of the exact exchange) – 0, 1/4, 1/3, and 1/2. For all other molecules, the calculations have been performed for α = 1/4 and 1/3. The electronic structure parameters including the HOMO-LUMO energy gap, Fermi level, magnetization, and imaginary part of the dielectric function are presented and compared with available theoretical and experimental data. Manganese, iron, and cobalt phthalocyanines show a strong dependence of electronic properties on the value of the exact exchange interaction. In other molecules with nickel, copper, and zinc, this dependence is not significant.
Does Protest Influence Political Speech? Evidence from UK Climate Protest, 2017–2019

How does protest affect political speech? Protest is an important form of political claim-making, yet our understanding of its influence on how individual legislators communicate remains limited. Our paper thus extends a theoretical framework on protests as information about voter preferences, and evaluates it using crowd-sourced protest data from the 2017–2019 Fridays for Future protests in the UK. We combine these data with ~2.4m tweets from 553 legislators over this period and text data from ~150k parliamentary speech records. We find that local protests prompted MPs to speak more about the climate, but only online. These results demonstrate that protest can shape the timing and substance of political communication by individual elected representatives. They also highlight an important difference between legislators' offline and online speech, suggesting that more work is needed to understand how political strategies differ across these arenas.
Computer Modeling and Machine Learning in Chemistry and Materials Science: From Properties and Reactions of Small Organic and Inorganic Molecules to the Smart Design of Polymers and Composites

Computer modeling, machine learning, and artificial intelligence are currently considered cutting-edge topics in chemistry and materials science. The application of information technologies in natural sciences can help researchers collect big data and understand patterns that are not obvious to humans. In this perspective, I would like to highlight the recent achievements of our research group and other researchers in relation to computer modeling and machine learning in chemistry and materials science.