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Study aim: To identify symptoms of depression, anxiety, and stress in Brazilian university students of both sexes and the association of physical activity parameters during the COVID-19 pandemic.

This study investigated the effectiveness of a coil-shaped optical fiber interferometric sensor, with a diameter of 13 mm, for measuring compression. The sensor’s design utilizes the principles of interferometry to create a pattern that changes with applied pressure. This configuration significantly amplifies the sensor’s sensitivity to compression due to the extended optical path length within the compact form factor. The experimental results demonstrated that even small compressive forces caused detectable alterations in the interference pattern, allowing for precise quantification of pressure changes. The 13 mm diameter proved to be particularly advantageous, providing a balance between sensitivity and practical integration into various systems, from structural health monitoring to biomedical devices. This study also highlights the sensor’s robustness against electromagnetic interference and environmental variations, attributing this to the intrinsic properties of optical fiber. Overall, the findings suggest that coil-shaped optical fiber interferometric sensors are highly effective for accurate and reliable compression sensing, with potential for broad application across multiple industries.

Background/Purpose: This work is focused on the variables that influence the outcomes of mergers and acquisitions, by learning from past mistakes, adopt better strategies and make wiser decisions to enhance the outcomes of their mergers and acquisitions. Using a qualitative approach, this research contributes to existing knowledge on mergers and acquisitions performance by exploring the cultural, managerial and organizational factors dimensions through an integrative approach using multiple perspectives.

The Sungun copper–molybdenum porphyry deposit is located in the north of Varzaghan, northwestern Iran. The Sungun quartz-monzonite is the oldest mineralized intrusive body in the region and was emplaced during the Early Miocene. Eight categories of the late and unmineralized dykes, which include quartz diorite, gabbrodiorite, diorite, dacite, microdiorite and lamprophyre (LAM), intrude the ore deposit. The main mineral phases in the dykes include plagioclase, amphibole and biotite, with minor quartz and apatite and secondary chlorite, epidote, muscovite and sericite. The composition of plagioclase in the quartz diorite dykes (DK1a, DK1b and DK1c) varies from albite-oligoclase to andesine and oligoclase to andesine; in the diorite, it varies from andesine to labradorite; in the LAM, from albite to oligoclase; and in the microdiorite (MDI), it occurs as albite. Amphibole compositions are consistent with classification as hornblende or calcic amphibole. Based on their AlIV value (less than 1.5), amphibole compositions are consistent with an active continental margin affinity. The average percentage of pistacite (Ps) in epidotes formed from alteration of plagioclase and ferromagnesian minerals is 27–23% and 25–30%, respectively. Thermobarometric studies based on amphibole and biotite indicate approximate dyke crystallization temperature of 850–750℃, pressure of 231–336 MPa and high fO2 (>nickel-nickel-oxide buffer). The range of mineral compositions in the postmineralization dyke suite is consistent with a genetic relationship with the subduction of the Neotethys oceanic crust beneath the continental crust of the northwest part of the Central Iranian Structural Zone. Despite the change from calc-alkaline to alkaline magmatism, the dykes are likely related to the late stages of magmatic activity in the subduction system that also generated the porphyry deposit.

This study aims to explore the role of social networks in the internationalisation of startups. For this purpose, the social network LinkedIn is used, and two case studies of Portuguese technological startups are employed. The findings indicate that social networks can contribute to the acceleration of the internationalisation process and decrease their costs. Their relevance is greater in the initial phase of the internationalisation process. However, its relevance is limited in more advanced phases of this process. LinkedIn can be used by startups to obtain several benefits such as brand awareness, identification of new opportunities, customer feedback, among others. The results of this study are essentially useful in a practical dimension for companies that plan to start or improve their internationalisation process sustained on social networks.

In this work ternary bioactive glasses with the molar composition 63 % SiO2, 28 % CaO, and 9 % P2O5 have been prepared via sol-gel processing route leading to xerogel or aerogel glasses, depending on the drying conditions. Two types of drying methods were used: atmospheric pressure drying (evaporative), to produce xerogels, and supercritical fluids drying, to obtain aerogels. Both dried gels were subjected to heat-treatment at three different temperatures: 400, 600 and 800 ºC in order to the removal of synthesis byproducts and structural modifications. The resulting materials were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), scanning electron microscopy (SEM), thermal gravimetric analysis (TGA) and differential thermal analysis (DTA), and by in vitro bioactivity tests in simulated body fluid. The influence of the drying and the sintering temperature of their structure, morphology, and bioactivity of the final products were evaluated. The results show a good bioactivity of xerogel and aerogel bioactive glass powders with the formation of an apatite layer after one day of immersion in SBF solution for aerogel bioactive glass powders and a particle size less than 10 nm. An apatite layer formed after 3 days in the case of xerogel bioactive glass powders and a particle size around 100 nm.

This work presents preliminary results of the ϕ -shaped sensor mounted on support designed by additive manufacturing (AM). This sensor is proposed and experimentally demonstrated to measure the radial variation of cylindrical structures. The sensor presents an easy fabrication. The support was developed to work using the principle of leverage. The sensing head is curled between two points so that the dimension associated with the macro bend is changed when there is a radial variation. The results indicate that the proposed sensor structure can monitor radial variation in applications such as pipelines and trees.

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

The investigation of a D-shaped photonic crystal fiber sensor with a bimetallic layer for operation at the visible and infrared spectra is presented. The bimetallic layer is composed by silver and gold slabs deposited adjacently on the flat face of the fiber. It is shown that this architecture allows the excitation of two sharply distinguished plasmon resonance, which suggest potential applications for multiparameter sensing.

A method based on multiple Fiber Bragg Gratings (FBG) and a structure fabricated using a 3D printer for diameter measurement is proposed and experimentally demonstrated. The sensor is easily developed inserting the FBG on the structure and fixing the FBG in two points. Due to this arrangement, when the diameter is reduced a force is applied on the sensor and this causes a wavelength shift. The study is divided in two steps using one experimental setup. At first, each FBG response is independently evaluated concerning the diameter variation and after that, the FBGs are evaluated together. The results demonstrated that the structure can be used as a way to monitor the diameter variation in some applications.

The only regional evaluation of Lebanese wind-energy potential (National Wind Atlas) dates back to 2011 and was carried out by a United Nations agency. In this work, data from the most recent reanalysis (ERA5) developed at the European Center for Medium Range Weather Forecast (ECMWF), corresponding to the 2010−2017 period, were used to evaluate Lebanese offshore-wind-energy potential. In the present study, wind power density associated to a SIEMENS 154/6 turbine was calculated with a horizontal resolution of 31 km and 1 hour time steps. This work incorporated the impact of air density changes into the calculations due to the seasonal evolution of pressure, temperature, and humidity. Observed average offshore air density ρ 0 was 1.19 kg / m 3 for the 2010−2017 period, but if instead of ρ 0 , hourly ρ values were used, seasonal oscillations of wind power density ( W P D ) represented differences in percentage terms ranging from −4% in summer to +3% in winter. ERA5 provides hourly wind, temperature, pressure, and dew-point temperature values that allowed us to calculate the hourly evolution of air density during this period and could also be used to accurately evaluate wind power density off the Lebanese coast. There was a significant gradient in wind power density along the shore, with the northern coastal area exhibiting the highest potential and reaching winter values of around 400 W / m 2 . Finally, this study suggests that the initial results provided by the National Wind Atlas overestimated the true offshore-wind-energy potential, thus highlighting the suitability of ERA5 as an accurate tool for similar tasks globally.