bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectively communicating with local policymakers: a randomized trial of policy brief dissemination to address obesity
Authors: Dodson Elizabeth A. , Parks Renee G. , Jacob Rebekah R. , An Ruopeng , Eyler Amy A. , Lee Nathan , Morshed Alexandra B. , Politi Mary C. , Tabak Rachel G. , Yan Yan , Brownson Ross C.
Published: March 2024

Introduction

Evidence-based policies are a powerful tool for impacting health and addressing obesity. Effectively communicating evidence to policymakers is critical to ensure evidence is incorporated into policies. While all public health is local, limited knowledge exists regarding effective approaches for improving local policymakers' uptake of evidence-based policies.

Methods

Local policymakers were randomized to view one of four versions of a policy brief (usual care, narrative, risk-framing, and narrative/risk-framing combination). They then answered a brief survey including questions about their impressions of the brief, their likelihood of using it, and how they determine legislative priorities.

Results

Responses from 331 participants indicated that a majority rated local data (92%), constituent needs/opinions (92%), and cost-effectiveness data (89%) as important or very important in determining what issues they work on. The majority of respondents agreed or strongly agreed that briefs were understandable (87%), believable (77%), and held their attention (74%) with no brief version rated significantly higher than the others. Across the four types of briefs, 42% indicated they were likely to use the brief. Logistic regression models showed that those indicating that local data were important in determining what they work on were over seven times more likely to use the policy brief than those indicating that local data were less important in determining what they work on (aOR = 7.39, 95% CI = 1.86,52.57).

Discussion

Among local policymakers in this study there was no dominant format or type of policy brief; all brief types were rated similarly highly. This highlights the importance of carefully crafting clear, succinct, credible, and understandable policy briefs, using different formats depending on communication objectives. Participants indicated a strong preference for receiving materials incorporating local data. To ensure maximum effect, every effort should be made to include data relevant to a policymaker's local area in policy communications.
Knowledge about type 2 diabetes: its impact for future management
Authors: Ferreira Pedro L. , Morais Carminda , Pimenta Rui , Ribeiro Inês , Amorim Isabel , Alves Sandra Maria , Santiago Luiz
Published: March 2024

Diabetes can cause several long-term complications. Knowledge about this disease can play an important role in reducing diabetes-related complications. In addition, the lack of awareness leads to misconceptions, which joined with inadequate knowledge, are relevant barriers to proper diabetes management. In this study, we aimed to assess the diabetes knowledge of a type 2 diabetes (T2D) population and identify major knowledge gaps, in order to prevent complications and to increase quality of life. In a cross-sectional, observational study in a convenience sample, we identified individuals diagnosed with T2D attending ambulatory visits from five health settings, older than 18 years, with a time diagnosis of at least 1 year, and attending multidisciplinary visits for at least 3 months. To assess the knowledge of T2D individuals, we applied the Portuguese version of the Diabetes Knowledge Test. The sample included a total of 1,200 persons, of whom almost half were female. The age range of the participants varied from 24 to 94 years old, and the mean age was 65.6 ± 11.4 years. Most of the sample had a level of education under secondary and lived with someone. In our sample, 479 (39.9%) were insulin-treated. The percentage of correct answers was 51.8% for non-insulin vs. 58.7% for insulin treated (p < 0.05). There were three items with a percentage of correct answers lower than 15%; the item with the lower value of correct answers was the one related to the identification of signs of ketoacidosis with only 4.4% of correct answers, the errors presented a random pattern; the item related to the identification of which food should not be used to treat low blood glucose with 11.9%, where 56.9% of the sample’s participants considered that one cup of skim milk would be the correct answer (53.1% in non-insulin patients and 62.6% in insulin treated patients; p < 0.001). The item regarding the knowledge of free food presented a 13.3% of correct answers (10.8% non-insulin group vs. 17.1% insulin group; p < 0.01). Two of the three items with lower value of correct answers were related to glycemic control and health status monitoring, the other was related to diet and food.
The psychosocial aid response after the 22/03/2016 attacks in Belgium: a community case study
Authors: Muysewinkel Emilie , Vesentini Lara , Van Deynse Helena , Stene Lise Eilin , Bilsen Johan , Van Overmeire Roel
Published: March 2024

Introduction

After the terrorist attacks, early psychosocial care is provided to people considered at risk of developing mental health issues due to the attacks. Despite the clear importance of such early intervention, there is very few data on how this is registered, who is targeted, and whether target-recipients accept such aid.

Methods

Using registry data from the Centre General Wellbeingwork (CAW), a collection of centers in the regions Brussels and Flanders that provide psychosocial care, we examined the early psychosocial care response after the terrorist attacks of 22/03/2016 in Belgium.

Results

In total, 327 people were listed to be contacted by the CAW, while only 205 were reached out to (62.7%). Most were contacted within a month (84.9%), and were victims of the attacks (69.8%). Overall, the majority was female (55.6%).

Conclusion

Overall, target recipients were witnesses and survivors of the attacks, though a large proportion of people were not reached by the early outreach.
Mother’s Curse effects on lifespan and aging
Authors: Edmands Suzanne
Published: March 2024

The Mother’s Curse hypothesis posits that mothers curse their sons with harmful mitochondria, because maternal mitochondrial inheritance makes selection blind to mitochondrial mutations that harm only males. As a result, mitochondrial function may be evolutionarily optimized for females. This is an attractive explanation for ubiquitous sex differences in lifespan and aging, given the prevalence of maternal mitochondrial inheritance and the established relationship between mitochondria and aging. This review outlines patterns expected under the hypothesis, and traits most likely to be affected, chiefly those that are sexually dimorphic and energy intensive. A survey of the literature shows that evidence for Mother’s Curse is limited to a few taxonomic groups, with the strongest support coming from experimental crosses in Drosophila. Much of the evidence comes from studies of fertility, which is expected to be particularly vulnerable to male-harming mitochondrial mutations, but studies of lifespan and aging also show evidence of Mother’s Curse effects. Despite some very compelling studies supporting the hypothesis, the evidence is quite patchy overall, with contradictory results even found for the same traits in the same taxa. Reasons for this scarcity of evidence are discussed, including nuclear compensation, factors opposing male-specific mutation load, effects of interspecific hybridization, context dependency and demographic effects. Mother’s Curse effects may indeed contribute to sex differences, but the complexity of other contributing factors make Mother’s Curse a poor general predictor of sex-specific lifespan and aging.
Accumulation, tissue distribution, health hazard of microplastics in a commercially important cat fish, Silonia silondia from a tropical large-scale estuary
Authors: Hossain M. Belal , Pingki Farjana Haque , Azad Md. Abdus Samad , Nur As-Ad Ujjaman , Banik Partho , Sarker Pallab Kumer , Paray Bilal Ahamad , Arai Takaomi , Yu Jimmy
Published: March 2024

The current knowledge regarding the presence of microplastics (MPs) in the digestive tracts of fish, particularly the non-edible parts, provides limited assistance in assessing the risk to human health and establishing guideline values for policy-making purposes. Therefore, we conducted the first investigation into MPs within the commercially significant catfish species S. silondia, form a major tropical estuary assessing their accumulation, characteristics, and associated risks in various tissues, particularly the consumable muscle. A sum of 132 MPs were identified, and the mean abundance of MPs were 7.40 ± 4.12 item/DT, 3.20 ± 1.69 item/gill and 2.60 ± 1.65 item/muscle found in digestive tract (DT), gill and muscle of the fish, respectively. The strong relationships of MPs among three different tissues (y = 0.6069x - 22.69, R2 = 0.7589) indicated the pathways and how MPs were influenced by the physiology of organisms. The prevalence of MPs in fish muscle demonstrated their trophic transmission to humans. Moreover, fishes with higher weight had higher MPs in their gill, and DT. The dominant type, color and size of MPs were fibrous (89.67%), violet (41%) and < 0.5 mm sized (94%), respectively. The high percentage of fibers suggests that they might have come from ropes, fishing nets or sewage. FTIR chemical composition analyses of microplastics (MPs) identified three primary polymer types: PET (44.5%), PE (33.3%), and PP (22.2%) in fish. These polymers are commonly associated with packaging materials, household wastes and plastic pipes. Contamination level assessment by CF (CF = 2.76) and PLI (PLI > 1) indicated moderately to highly contaminated fish with MPs ingestion. While the complete understanding of the direct negative effects of microplastics (MPs) on human health remains elusive, their presence in estuarine fish raises concerns for both human and ecosystem health. The findings will be useful for assessing the hazards to human health from exposure to MPs and for creating effective risk management plans to reduce those risks.
Numerical and Experimental Study of Low-Frequency Membrane Damper for Tube Vibration Suppression
Authors: I Boris , Lee Jaesun
Published: March 2024

In modern days, low-frequency vibration is still challenging to suppress due to its high vibrational energy. A typical suppression method is to increase the object’s mass to reduce the amplitude of the vibration, but such a way is unsuitable in many cases. Membrane dampers can potentially eliminate the limitation and offer lightweight and compact damper. The idea is to decrease the stiffness and add additional mass to increase the dissipation of the vibration energy. For that, the membrane and an extra mass made of silicone rubber were used for the damper. Finite element eigenfrequency simulation showed the transformation of each mode to the damper mode, where the tube displacement was zero. Also, it showed the bandgap between modes in the frequency range from 106 Hz to 158 Hz. The experimental verification of clamped from both ends of the tube showed the predicted bandgap and absence of the resonance peak of the bare tube. Overall, the membrane damper showed good efficiency in extremely low frequencies and seems promising for vibration suppression.
Managerial Digitalisation Cost in the Hotel Sector: The Case of Northern Greece
Authors: Chatzipetrou Evrikleia , Varvaropoulos Konstantinos
Published: March 2024

The main purpose of the research is to measure the managerial digitalisation cost of the hotel sector in Northern Greece. Taking into consideration the impact of the pandemic crisis on business management and the lack of rich relevant literature, the study focuses on the cost of managerial digitalisation and its possible relationship with certain hotel demographic characteristics, like star ranking, period of operation, size and accommodation type. The population consists of 2187 hotel units, based on the register of the Hellenic Chamber of Hotels and other local associations such as Chalkidiki Hotels Association. Data were collected through a structured questionnaire, registered in Google forms, and sent by e-mail or alternatively via social media like Facebook. The main finding concerns the low amount of investment related to revenue, as the majority of hotel units spend less than 2.5% of their annual turnover on managerial digitalisation. In addition to this, members of hotel groups, seasonal and summer accommodations invest more in the adoption of digital managerial tools. A positive correlation with the number of employees was also detected. As digitalisation cost in the Greek hospitality sector is a completely unexplored scientific field, this is the first effort to deal with it. Furthermore, as Northern Greece is not as popular a tourist destination as other parts of Greece (i.e., the Aegean islands), the present research is a unique attempt to focus on the hotel sector of a less well-known Greek tourist region.
A Rapid RI-TP Model for Predicting Turbine Wake Interaction Broadband Noise
Authors: Xiang Kangshen , Chen Weijie , Aneeb Siddiqui , Qiao Weiyang
Published: March 2024

Future UHBR (Ultra-High Bypass-Ratio) engines might cause serious ‘turbine noise storms’ but, at present, turbine noise prediction capability is lacking. The large turning angle of the turbine blade is the first major factor deserving special attention. The RANS (Reynold Averaged Navier–Stokes equation)-informed (here called RI) method and LINSUB (the bound vorticity 2D model LINearized SUBsonic flow in cascade), developed to predict fan broadband noise, coupled with a two-flat-plates (here called TP) assumption for the turbine blade, is applied here, and one autonomous rapid RI-TP model for predicting turbine wake interaction broadband noise has been developed. Firstly, taking the single axial turbine test rig NPU-Turb as the object, both the experimental data and the DDES/AA (delayed Detached Eddy Simulation/Acoustic Analogy) hybrid model have been used to validate the RI-TP model. High consistency in the medium and high frequencies among the three designed and off-designed rotation speeds indicates that the RI-TP model has the ability to predict turbine broadband noise rapidly. And compared with the original RANS-informed method, with one thin-flat-plate assumption on the blade, the RI-TP model can enhance the PWL (sound power level) in almost the whole spectral range below 10 KHz, which, in turn, is closer to the experimental data and the DDES/AA prediction results. The PWL trend with a ‘dividing point’ position is also studied. The spectrum would move up or down if the location is away from true value. In addition, the extraction location for turbulence as an input for the RI-TP model is negligible. In the future, multi-stage characteristics and the blade thickness effect should be further considered when predicting turbine noise.
Research on Energy Distribution Strategy of Tandem Hybrid Tractor Based on the Pontryagin Minimum Principle
Authors: Zhou Rundong , Wang Lin , Deng Xiaoting , Su Chao , Fang Song , Lu Zhixiong
Published: March 2024

In order to study the energy distribution of the tandem hybrid tractor and achieve optimal fuel economy under the whole operating condition, an energy distribution strategy based on PMP (Pontryagin minimum principle) is proposed. The performance parameters of the relevant power components are obtained by constructing the test bench of the tandem hybrid tractor. At the same time, the mathematical model of energy distribution is established from the aspects of energy distribution objective function, state variable, and variable constraint. Based on the external characteristic test of the hub motor and the resistance analysis, the transport operation condition of the tractor is selected as the simulation target condition. The ADVISOR2002 and Simulink software are used to jointly simulate the three energy distribution strategies: the thermostat type, the power-following type, and the PMP type. The simulation results show that, compared with the other two, the fuel economy and battery power loss of the PMP-based energy distribution strategy are significantly improved. The fuel consumption per 100 km is decreased by 32.91% and 26.10%, respectively, which verifies the feasibility of the strategy. This study is of great significance for improving the production efficiency and reducing fuel consumption of hybrid tractors.
An Agronomic Efficiency Analysis of Winter Wheat at Different Sowing Strategies and Nitrogen Fertilizer Rates: A Case Study in Northeastern Poland
Authors: Lachutta Krzysztof , Jankowski Krzysztof Józef
Published: March 2024

This study was undertaken to examine the influence of the sowing date, sowing density, and split spring application of nitrogen (N) fertilizer on plant density, tillering, yield components, and grain yields of winter wheat (Triticum aestivum L.) grown in northeastern Poland between 2018 and 2021. The experiment had a split-plot design with three sowing dates (early (3–6 September), delayed by 14 days, and delayed by 28 days), three sowing densities (200, 300, and 400 live grains m−2), and three split spring N rates (40 + 100, 70 + 70, and 100 + 40 kg ha−1 applied in BBCH stages 22–25 and 30–31, respectively). The number of spikes m−2 increased by 11% on average when winter wheat was sown with a delay of 14 days (17–20 September) and 28 days (1–4 October). The number of spikes m−2 was highest when winter wheat was sown at 300 and 400 live grains m−2. The application of 100 + 40 kg N ha−1 (BBCH 22–25 and 30–31, respectively) increased the number of spikes m−2. An increase in sowing density from 200 to 300 to 400 live grains m−2 decreased the number of grains spike−1 by 5% and 7%, respectively. Thousand grain weight (TGW) increased by 1% and 2% when sowing was delayed by 14 (17–20 September) and 28 days (1–4 October), respectively. In northeastern Poland, grain yields peaked when winter wheat was sown between 17 September and 4 October (10.52–10.58 Mg ha−1). In late-sown winter wheat, grain yields increased due to a higher number of spikes m−2 and higher grain weight. The highest sowing density (400 live grains m−2) induced a greater increase in grain yields than the lowest sowing density (200 live grains m−2) (10.25 vs.10.02 Mg ha−1). In winter wheat sown at a density of 400 live grains m−2, the increase in grain yields resulted in a higher number of spikes m−2. Grain yields peaked in response to 100 kg N ha−1 applied in BBCH stages 22–25 and 40 kg N ha−1 applied in BBCH stages 30–31 (this split N rate increased the number of spikes m−2). In turn, the highest straw yield (6.23 Mg ha−1) was obtained when the second split of N fertilizer was applied in BBCH stages 30–31 (40 + 100 kg N ha−1). Straw yields decreased significantly (by 6%) when winter wheat was sown late (early October). Delayed sowing (mid-September and early October) increased the harvest index (HI) of winter wheat by 5–7%. Split spring N application influenced grain and straw yields, but it had no effect on the HI of winter wheat.
Which Households Raise Livestock in Urban and Peri-Urban Areas of Eight Developing Asian Countries?
Authors: Ushimaru Sayaka , Iwata Rintaro , Amrullah Eka Rastiyanto , Utami Arini W. , Ishida Akira
Published: March 2024

In many developing countries, ensuring a stable and affordable supply of safe and nutritious food for urban dwellers, especially impoverished households, has become an urgent policy issue due to growing urban populations. Since urban and peri-urban agriculture (UPA) has emerged as a potential solution, research interest in UPA has increased. However, most studies have been conducted in specific African towns, and analyses in Asian countries are scarce. In addition, further research must be performed on urban and peri-urban livestock farming (UPLF), which may provide animal-based protein to the urban population. Therefore, this study aims to clarify who raises livestock in the urban and peri-urban areas of eight developing Asian countries using raw data from the Demographic and Health Survey (DHS). The aggregation results reveal that at least 10% of households keep livestock, with more than 30% of households in four of the eight Asian countries practicing UPLF. Poultry is the most common type of livestock, and the number of animals per household is usually limited. Logistic regression analysis reveals that poorer families are more likely to raise livestock, suggesting UPLF can enhance food and nutritional security for low-income households.
Improved Collision Avoidance Algorithm of Autonomous Rice Transplanter Based on Virtual Goal Point
Authors: Li Jinyang , Zhang Miao , Li Meiqing , Ge Deqiang
Published: March 2024

To ensure the operation safety and efficiency of an autonomous rice transplanter, a path planning method of obstacle avoidance based on the improved artificial potential field is proposed. Firstly, the obstacles are divided into circular or elliptic obstacles according to the difference between the length and width of an obstacle as well as the angle between the vehicle’s forward direction and the length direction of the obstacle. Secondly, improved repulsive fields for circular and elliptic models are developed. To escape the local minimum and goal inaccessibility of the traditional artificial potential field as well as meet the requirements of agronomy and vehicle kinematics constraints, the adaptive setting and adjusting strategy for virtual goal points is proposed according to relative azimuth between obstacle and vehicle. The path smoothing method based on the B-spline interpolation method is presented. Finally, the intelligent obstacle avoidance algorithm is designed, and the path evaluation rule is given to obtain the low-cost, non-collision, smooth and shortest obstacle avoidance path. To verify the effectiveness of the proposed obstacle avoidance algorithm, simulation and field experiments are conducted. Simulation and experimental results demonstrate that the proposed improved collision avoidance algorithm is highly effective and realizable.
Soqia: A Responsive Web Geographic Information System Solution for Dynamic Spatio-Temporal Monitoring of Soil Water Status in Arboriculture
Authors: Ennatiqi Lahoucine , Bouziani Mourad , Yaagoubi Reda , Kenny Lahcen
Published: March 2024

The optimization of irrigation in arboriculture holds crucial importance for effectively managing water resources in arid regions. This work introduces the development and implementation of an innovative solution named ‘Soqia’, a responsive WEB-GIS web application designed for real-time monitoring of the water status in arboriculture. This solution integrates meteorological data, remote sensing data, and ground sensor-collected data for precise irrigation management at the agricultural plot level. A range of features has been considered in the development of this WEB -GIS solution, ranging from visualizing vegetation indices to accessing current weather data, thereby contributing to more efficient irrigation management. Compared to other existing applications, ‘Soqia’ provides users with the current amount of water to irrigate, as well as an estimated amount for the next 8 days. Additionally, it offers spatio-temporal tracking of vegetation indices provided as maps and graphs. The importance of the Soqia solution at the national level is justified by the scarcity of water resources due to increasingly frequent and intense drought seasons for the past years. Low rainfall is recorded in all national agricultural areas. The implemented prototype is a first step toward the development of future innovative tools aimed at improving water management in regions facing water challenges. This prototype illustrates the potential of Web-GIS-based precision irrigation systems for the rational use of water in agriculture in general and arboriculture in particular.
Infiltration and Leaching Characteristics of Soils with Different Salinity under Fertilizer Irrigation
Authors: Zhu Hongyan , Zheng Bingyan , Zhong Weizheng , Xu Jinbo , Nie Weibo , Sun Yan , Guan Zilong
Published: March 2024

Salt and nutrient transport and transformations during water infiltration directly influence saline soil improvement and the efficient use of water and fertilizer resources. The effects of soil initial salinity (18.3 g/kg, 25.5 g/kg, 42.2 g/kg, 79.94 g/kg, and 165 g/kg, respectively, labeled S1 to S5) on the infiltration and leaching characteristics of water, salt, and nitrogen were analyzed via a one-dimensional vertical fertilizer infiltration experiment. Meanwhile, the estimation models of cumulative infiltration and wetting front, including the effect of soil initial salinity, were established. The results showed that, with the increase in soil initial salinity, the cumulative infiltration within the same time decreased, and the migration time of wet front to 45 cm was longer. The time required for S5 to reach the preset cumulative infiltration was more than six times that of S1, and, for the wet front migration to 45 cm, the time requirement for S5 was about four times that of S1. In the established Kostiakov model and wetting front model, the coefficients all decreased with the increase in soil initial salinity, and the test index R2 values both reached 0.999. In the Kostiakov model, coefficient K had a linear relationship with the natural logarithm of initial soil salt content, while index a had a direct linear relationship with initial soil salt content. The cumulative leachate volume decreased with the increase in soil initial salinity, and the corresponding data of S3 and S5 were reduced by 37% and 57.3%, respectively, compared with S1. The electrical conductivity values of S1, S3, and S5 were 15.4, 209.8, and 205.6 ms/cm, respectively, being affected by the initial content in soil, soil moisture transport rate, and exogenous potassium nitrate (KNO3) addition. The NO3−-N concentrations in the leachates of S1, S3, and S5 at the end of leaching were 55.26, 16.17, and 3.2 mg/L, respectively. Based on the results of this study, for soil with high initial salinity, the conventional irrigation amount (2250 m3/ha) of the general soil in the study area could not meet the requirements of leaching salt. These results can provide a reference for the formulation of irrigation and fertilization strategies for soils with different salinity and contribute to the sustainable development of saline soil agriculture and the ecological environment.
Mechanisms Underlying the Differential Sensitivity to Mesotrione in Sweet Corn
Authors: Lv Guihua , Li Xiangnan , Wang Tingzhen , Wu Zhenxing , Fang Ruiqiu , Chen Jianjian
Published: March 2024

Mesotrione is a widely used post-emergence herbicide for maize. The toxicity of mesotrione to maize (especially sweet corn) has been widely reported, and some sweet corn varieties are highly sensitive to mesotrione, which affects subsequent plant growth periods. However, the molecular mechanisms responsible for the differences in susceptibility to mesotrione are not known. By comparing changes in the transcriptome of mesotrione-tolerant line 301 and mesotrione-sensitive line 276 after mesotrione treatment, we found that the genes coding light-harvesting chlorophyll protein complex were induced in 301, and the genes coding loosening cell walls were overrepresented in 276. The net photosynthetic rate, maximum photochemical efficiency of leaf PSII, photochemical quenching of chlorophyll fluorescence, and the electron transport rate were significantly higher in 301 than in 276 after mesotrione treatment, and these effects became more severe as time passed. In addition, oxidative balance was also affected by mesotrione. Compared with 301, SOD, POD, and CAT activities were significantly reduced with longer exposure time in 276. The results suggested that sweet corn can mitigate herbicide mesotrione toxicity by improving photosynthesis, ROS scavenging, and cell wall synthesis.
Assessing Ecogeographic Rules in Two Sigmodontine Rodents along an Elevational Gradient in Central Chile
Authors: Valladares-Gómez Alejandro , Torres-Pérez Fernando , Palma R. Eduardo
Published: March 2024

Bergmann’s and Allen’s rules are two classic ecogeographic rules concerning the physiological mechanisms employed by endotherm vertebrates for heat conservation in cold environments, which correlate with adaptive morphological changes. Thus, larger body sizes (Bergmann’s rule) and shorter appendages and limbs (Allen’s rule) are expected in mammals inhabiting cold environments (higher latitudes). Both rules may also apply to elevational gradients, due to the decrease in external temperature as elevation increases. In this study, we evaluated whether these patterns were true in two coexisting sigmodontine rodents across an elevational gradient in central Chile. We analyzed whether the size of the skull, body, and appendages of Abrothrix olivacea (n = 70) and Phyllotis darwini (n = 58) correlated with elevation, as predicted by these rules in a range between 154 and 2560 m. Our data revealed weak support for the Bergmann and Allen predictions. Moreover, we observed opposite patterns when expectations of Bergmann’s rules were evaluated, whereas Allen’s rule just fitted for ear size in both rodent species. Our results suggest that morphological changes (cranial, body, and appendage sizes) may play a minor role in the thermoregulation of these two species at high elevations, although behavioral strategies could be more critical. Other ecological and environmental variables could explain the morphological trends observed in our study. These hypotheses should be assessed in future studies to consider the relative contribution of morphology, behavior, and physiological mechanisms to the thermal adaptation of these two rodent species at high elevations.
The Relation between Milk Lactose Concentration and the Rumination, Feeding, and Locomotion Behavior of Early-Lactation Dairy Cows
Authors: Antanaitis Ramūnas , Džermeikaitė Karina , Krištolaitytė Justina , Girdauskaitė Akvilė , Arlauskaitė Samanta , Tolkačiovaitė Kotryna , Baumgartner Walter
Published: March 2024

This study hypothesizes that higher in-line milk lactose concentrations are indicative of enhanced dairy cow behaviors—including increased rumination, feeding, and locomotion activities—reflecting superior overall health and well-being. It posits that fluctuations in milk lactose levels have a substantial impact on the physiological and behavioral responses of dairy cows, thereby affecting their milk yields and compositions. Each cow’s milk lactose, fat, protein, and fat-to-protein ratio were continuously monitored using the BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania). The RumiWatch noseband sensor (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland) was employed to measure the biomarkers of the rumination, feeding, and locomotion behavior. The measurements were recorded over 5 days at the same time (during morning milking). A total of 502 cows were examined. During these 5 days, 2510 measurements were taken. Based on the lactose content in their milk, the cows were divided into two categories: the first group consisted of cows with milk lactose levels below 4.70%, while the second group included cows with milk lactose levels of 4.70% or higher. Our study showed that cows with higher milk lactose concentrations (≥4.70%) produced significantly more milk (16.14% increase) but had a lower milk protein concentration (5.05% decrease) compared to cows with lower lactose levels. These cows also exhibited changes in rumination and feeding behaviors, as recorded by the RWS: there was an increase in the mastication and rumination behaviors, evidenced by a 14.09% rise in other chews and a 13.84% increase in rumination chews, along with a 16.70% boost in bolus activity. However, there was a notable 16.18% reduction in their physical activity, as measured by the change in time spent walking.
A Genetic Tool to Identify Predators Responsible for Livestock Attacks in South America and Recommendations for Human–Wildlife Conflict Mitigation
Authors: Díaz Eduardo A. , Pozo María José , Alarcón Pablo , Pozo Gabriela , Zug Rebecca , Sáenz Carolina , Torres Maria de Lourdes
Published: March 2024

Livestock predation induces global human–wildlife conflict, triggering the retaliatory killing of large carnivores. Although domestic dogs (Canis familiaris) contribute to livestock depredation, blame primarily falls on wild predators. Dogs can also transmit pathogens between wildlife, domestic animals, and humans. Therefore, the presence of free-ranging dogs can have negative consequences for biodiversity conservation, smallholder economy, food supply, and public health, four of the United Nations’ Sustainable Developed Goals (SDGs) for 2030. In Ecuador, where livestock sustains rural households, retaliatory poaching threatens Andean bear (Tremarctos ornatus), jaguar (Panthera onca), and puma (Puma concolor) populations. However, the role of dogs in these incidents remains underexplored. The present study evaluates the possibility of reliable molecular identification of predatory species from DNA traces in bite wounds. Our results revealed the presence of dog saliva on four out of six livestock carcasses presumably attacked by wild predators. These findings highlight the importance of rectifying misinformation about large carnivores in Ecuador and the need to control dog populations. We recommend that local administrations incorporate DNA analysis into livestock predation events to examine how common the problem is, and to use the analysis to develop conflict mitigation strategies which are essential for the conservation of large carnivores.
The Genetic Basis Underpinning Sexually Selected Traits across Different Animal Lineages: Are There Genetic Mechanisms in Common?
Authors: Kang Ji Hyoun
Published: March 2024

Sexual selection involving female choice or female preference (‘inter-sexual’ selection) and/or male–male competition (‘intra-sexual’ selection) is one of the key mechanisms for evolutionary diversification and speciation. In particular, sexual selection is recently suggested to be an important mode to drive the evolution of the “novel” phenotype (i.e., “evolutionary novelty”). Despite extensive studies performed on sexually selected traits or male-specific ornaments (or weapon-like structures) with respect to their evolutionary origin, history and fitness benefits, relatively little is known about the molecular genetic mechanisms underlying their developmental process. However, with advances in genomic technologies (including whole transcriptome analysis using Next Generation Sequencing [NGS] techniques; RNA-Seq), progress has been made to unveil the genetic background underpinning diverse sexually selected traits in different animal taxa. In the present review, empirical data on the genes, genetic mechanisms, or regulatory pathways underlying various sexually selected traits were compiled to explore whether “common” genetic architectures shape the development and evolution of these traits across evolutionarily distant animal lineages. It is shown that the recruitment of the pre-existing genetic network for a new purpose (i.e., gene network “co-option”) is rather widespread in the development and evolution of sexually selected traits, indicating that particular genes or gene sets are repeatedly involved in different sexually selected traits. Information on genes or genetic mechanisms regulating the development of sexually selected traits is an essential piece to complete a whole picture of the origin and evolution of sexually selected traits.
Antioxidant Responses and Phytochemical Accumulation in Raphanus Species Sprouts through Elicitors and Predictive Models under High Temperature Stress
Authors: Toro María-Trinidad , Fustos-Toribio Roberto , Ortiz Jaime , Becerra José , Zapata Nelson , López-Belchí María Dolores
Published: March 2024

Crop production is being impacted by higher temperatures, which can decrease food yield and pose a threat to human nutrition. In the current study, edible and wild radish sprouts were exposed to elevated growth temperatures along with the exogenous application of various elicitors to activate defense mechanisms. Developmental traits, oxidative damage, glucosinolate and anthocyanin content, and antioxidant capacity were evaluated alongside the development of a predictive model. A combination of four elicitors (citric acid, methyl jasmonate—MeJa, chitosan, and K2SO4) and high temperatures were applied. The accumulation of bioactives was significantly enhanced through the application of two elicitors, K2SO4 and methyl jasmonate (MeJa). The combination of high temperature with MeJa prominently activated oxidative mechanisms. Consequently, an artificial neural network was developed to predict the behavior of MeJa and temperature, providing a valuable projection of plant growth responses. This study demonstrates that the use of elicitors and predictive analytics serves as an effective tool to investigate responses and enhance the nutritional value of Raphanus species sprouts under future conditions of increased temperature.
Survey of Deep Learning-Based Methods for FMCW Radar Odometry and Ego-Localization
Authors: Brune Marvin , Meisen Tobias , Pomp André
Published: March 2024

This paper provides an in-depth review of deep learning techniques to address the challenges of odometry and global ego-localization using frequency modulated continuous wave (FMCW) radar sensors. In particular, we focus on the prediction of odometry, which involves the determination of the ego-motion of a system by external sensors, and loop closure detection, which concentrates on the determination of the ego-position typically on an existing map. We initially emphasize the significance of these tasks in the context of radar sensors and underscore the motivations behind them. The subsequent sections delve into the practical implementation of deep learning approaches, strategically designed to effectively address the aforementioned challenges. We primarily focus on spinning and automotive radar configurations within the domain of autonomous driving. Additionally, we introduce publicly available datasets that have been instrumental in addressing these challenges and analyze the importance and struggles of current methods used for radar based odometry and localization. In conclusion, this paper highlights the distinctions between the addressed tasks and other radar perception applications, while also discussing their differences from challenges posed by alternative sensor modalities. The findings contribute to the ongoing discourse on advancing radar sensor capabilities through the application of deep learning methodologies, particularly in the context of enhancing odometry and ego-localization for autonomous driving applications.
Enhancing Diagnostic Accuracy in Orthodontics: Calibration and Validation of a New Tool for Dental Arch Measurements—Pilot Study
Authors: Nikolajević-Stoican Andrada-Nicoleta , Alexa Vlad Tiberiu , Jumanca Daniela , Galuscan Atena , Oancea Roxana , Lalescu Dacian , Szuhanek Camelia
Published: March 2024

(1) Background: In the pursuit of enhancing diagnostic precision and treatment planning in orthodontics, accurate measurements in dental study casts of the different parameters of the dental arch stands as a critical element. Measurements such as dental arch perimetry, arch length or intermolar distance play a key role in achieving optimal results in orthodontics. Therefore, the aim of this study is to develop, calibrate and verify a new tool for determining dental arch measurements and to compare these measurements, carried out with the newly fabricated instrument, to two other conventional measurements used in orthodontics. (2) Methods: The study used 40 dental study casts for measuring the three mentioned arch parameters. The measurements were conducted following three methods: with the new instrument, with the help of a digital caliper and with the conventional method using a graduated ruler and metal wire. The difference between the values obtained by measuring with the new instrument and the other two methods was noted out in order to calculate the margin of error. Descriptive statistics, including mean, minimum, maximum, and standard deviation, were computed for all replicates, while normality was assessed using the Kolmogorov–Smirnov and Shapiro–Wilk tests; mean differences were examined using the Friedman test and the Wilcoxon signed-rank test, with statistical significance set at p-values < 0.05. Results: In the case of the arch perimeter measurement, the difference from the conventional measurement was −0.045 mm ± 0.006 and from the digital measurement was 0.025 ± 0.013. The measurement of the anterior arch length results shows that the difference from the conventional measurement was −0.0002 ± 0.014 and from the digital measurement 0.02 ± 0.0006. For the measurement of the intermolar distance of the upper permanent molars, the difference from the conventional measurement was −0.02 ± 0.01 and from the digital measurement −0.02 ± 0.001. The greatest differences were observed in the measurements of the parameter “Arch perimeter”, obtaining an average value of −0.045 ± 0.006 mm between the measurement with the new instrument and that with the conventional method using graduated rulers, as opposed to a value of 0.025 ± 0.013 for the difference from the digital measurement. Conclusions: the values obtained using the proposed instrument closely align with those obtained through traditional measuring methods like the graduated ruler and metal wire, demonstrating comparable results. Additionally, the measurements closely match those achieved through digital measurement using electronic calipers, showcasing the instrument’s accuracy in comparison to established techniques.
Hourly Long-Term Traffic Volume Prediction with Meteorological Information Using Graph Convolutional Networks
Authors: Park Sangung , Kim Mugeun , Kim Jooyoung
Published: March 2024

Hourly traffic volume prediction is now emerging to mitigate and respond to hourly-level traffic congestion augmented by deep learning techniques. Incorporating meteorological data into the forecasting of hourly traffic volumes substantively improves the precision of long-term traffic forecasts. Nonetheless, integrating weather data into traffic prediction models is challenging due to the complex interplay between traffic flow, time-based patterns, and meteorological conditions. This paper proposes a graph convolutional network to predict long-term traffic volume with meteorological information. This study utilized a four-year traffic volume and meteorological information dataset in Chung-ju si to train and validate the models. The proposed model performed better than the other baseline scenarios with conventional and state-of-the-art deep learning techniques. Furthermore, the counterfactual scenarios analysis revealed the potential negative impacts of meteorological conditions on traffic volume. These findings will enable transportation planners predict hourly traffic volumes for different scenarios, such as harsh weather conditions or holidays. Furthermore, predicting the microscopic traffic simulation for different scenarios of weather conditions or holidays is useful.
A Combined Method for Short-Term Load Forecasting Considering the Characteristics of Components of Seasonal and Trend Decomposition Using Local Regression
Authors: Hu Sile , Wang Yuan , Cai Wenbin , Yu Yuan , Chen Chao , Yang Jiaqiang , Zhao Yucan , Gao Yuan
Published: March 2024

In response to the complexity and high volatility of original load data affecting the accuracy of load forecasting, a combined method for short-term load forecasting considering the characteristics of components of seasonal and trend decomposition using local regression (STL) is proposed. The original load data are decomposed into a trend component, seasonal component, and residual component using STL. Then, considering the characteristics of each component, a long short-term memory (LSTM) neural network, a convolutional neural network (CNN), and Gaussian process regression (GPR) are used to predict the trend component, seasonal component, and residual component, respectively. The final outcome of the load forecasting is obtained by summing the forecasted results of each individual component. A specific case study is conducted to compare the proposed combined method with LSTM, CNN, GPR, STL-LSTM, STL-CNN, and STL-GPR prediction methods. Through comparison, the proposed combined method exhibits lower errors and higher accuracy, demonstrating the effectiveness of this method.
Three-Dimensional Probabilistic Semi-Explicit Cracking Model for Concrete Structures
Authors: Rita Mariane Rodrigues , Rossi Pierre , Fairbairn Eduardo de Moraes Rego , Ribeiro Fernando Luiz Bastos , Tailhan Jean-Louis , Andrade Henrique Conde Carvalho de , Mota Magno Teixeira
Published: March 2024

This paper introduces a three-dimensional (3D) semi-explicit probabilistic numerical model for simulating crack propagation within the framework of the finite element method. The model specifically addresses macrocrack propagation using linear volume elements. The criteria governing the macrocrack propagation is based on the softening behavior observed in concrete under uniaxial tension. This softening behavior corresponds to a dissipated cracking energy that is equal to the mode I critical fracture energy (GIC) used in the Linear Elastic Fracture Mechanics theory (LEFM). The probabilistic nature of this model revolves around the random distribution of two mechanical properties: tensile strength (ft) and fracture energy, which varies based on the volume of finite elements. The scattering of the fracture energy increases as the volume of finite elements decreases in order to consider the strong heterogeneity of the material. This work primarily aims to estimate the relationship between the standard deviation of GIC and the volume of finite elements through the development of the numerical model. For this purpose, an inverse analysis is conducted based on a fracture mechanical test simulation. This test involves macrocrack propagation in a large Double Cantilever Beam (DCB) specimen with a crack length exceeding two meters. The proposed inverse analysis procedure yields highly significant results, indicating that the numerical model effectively evaluates both crack length and crack opening during propagation.
Laccase-Mediated Oxidation of Phenolic Compounds from Wine Lees Extract towards the Synthesis of Polymers with Potential Applications in Food Packaging
Authors: Athanasiou Panagiotis E. , Gkountela Christina I. , Patila Michaela , Fotiadou Renia , Chatzikonstantinou Alexandra V. , Vouyiouka Stamatina N. , Stamatis Haralambos
Published: March 2024

Laccase from Trametes versicolor was applied to produce phenolic polymeric compounds with enhanced properties, using a wine lees extract as the phenolic source. The influence of the incubation time on the progress of the enzymatic oxidation and the yield of the formed polymers was examined. The polymerization process and the properties of the polymeric products were evaluated with a variety of techniques, such as high-pressure liquid chromatography (HPLC) and gel permeation chromatography (GPC), Fourier-transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopies, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). The enzymatic polymerization reaction resulted in an 82% reduction in the free phenolic compounds of the extract. The polymeric product recovery (up to 25.7%) and the molecular weight of the polymer depended on the incubation time of the reaction. The produced phenolic polymers exhibited high antioxidant activity, depending on the enzymatic oxidation reaction time, with the phenolic polymer formed after one hour of enzymatic reaction exhibiting the highest antioxidant activity (133.75 and 164.77 μg TE mg−1 polymer) towards the ABTS and DPPH free radicals, respectively. The higher thermal stability of the polymeric products compared to the wine lees phenolic extract was confirmed with TGA and DSC analyses. Finally, the formed phenolic polymeric products were incorporated into chitosan films, providing them with increased antioxidant activity without affecting the films’ cohesion.