Miracle-dz/UniFAR-FTUs huggingface dataset:
Turkey Behavior Identification Using Video Analytics And Object Tracking

In this paper, we propose a method to identify behavior of experimental turkeys by automatically analyzing video recordings. Monitoring turkey health during production is crucial for improved turkey production. Turkey health can be reflected through their common behavior, and changes in the frequency and duration of their behavior can be used to detect sick turkeys early. Video recordings can be manually annotated to assist identifying turkey behaviors, but this is both time consuming and labor intensive. In this paper, we monitor and detect changes in turkey behavior using video analytics. Behaviors of interest include eating, drinking, preening, and pecking. Identifying these behaviors requires accurate estimates of turkeys’ and turkey heads’ locations. Re-identification of each turkey is crucial after significant shape deformation such as wing flapping and fast walking. Therefore, our system integrates a state-of-the-art turkey tracker and a head tracker with a behavior identification module to identify turkey behavior. Results demonstrate that our system is effective and accurate at estimating the spatial location of turkeys and their heads, and identifying all behaviors of interest with high recall.
The Neuroprotective and Anti-Inflammatory Effects of Annona Muricata (Graviola) on Radiation-Induced Rat Sciatic Nerve Injury.

Background: In radiotherapy (RT) exposure area, normal tissues are also affected that may cause serious complications in the patients. This study aimed to evaluate Annona muricata’s radioprotective effects on sciatic nerve injury due to ionizing radiation (IR). Methods and Results: 32 adult female Wistar albino rats separated into 4 equal groups; Control (C), Annona muricata leaf extracts (AME), radiation (RAD), radiation and Annona muricata leaf extracts (AME+RAD). In groups AME and AME+RAD, Annona muricata leaf extracts were administered at a dose of 300 mg/kg for the first day and 50 mg/kg everyday for following one week intraperitoneally. In RAD and AME+RAD, rats were exposed to a single dose of 20 Gray IR to their right legs. All the subjects were sacrified at the end of the first month. Oxidative stress biochemical parameters (SOD, CAT and GPx) from blood samples were analyzed. Right sciatic nerves extracted and histomorphology evaluated. Statistically significant vasculature, degenerative and necrotic changes were observed in RAD, compared to C and AME (p<0,01). Swelling in myelin sheath was predominantly seen in RAD. Alterations in the level of CAT (p<0,01), SOD (p<0,01) and GPx (p<0,05) in AME+RAD group compared to RAD group were found to be statistically significant.Conclusion: Our study unveiled that AM could have a potential of biochemically and histomorphology healing on sciatic nerve injury due to ionizing radiation.
Lossless Video Coding Based On Probability Model Optimization With Improved Adaptive Prediction

We previously proposed a novel lossless coding method that utilizes example search and adaptive prediction within a framework of probability model optimization for monochrome video. In this paper, we improve the adaptive prediction in terms of coding performance and processing time. More precisely, we made modifications to the following three items: (a) reference pel arrangements, (b) motion vector derivation, and (c) optimal selection of predictors. Experimental results show that the proposed method certainly improves the coding performance and the processing time compared to our previous method, and achieves better coding performance than the VVC-based lossless video coding scheme.
Feasibility Study of Low Mass and Low Energy Consumption Drilling Devices for Future Space (Mining Surveying) Missions

The global climate crisis forces the search for new ecological sources of energy and mining methods. Space mining can solve those problems, but, first, wide geological surveying space missions using drilling methods are necessary. Additionally, drilling methods will be important in geological, life searching, geoengineering, and many other studies of extraterrestrial objects. Space is becoming a new area of possible drilling applications. Designing future space drilling missions requires adapting drilling technologies, not only to the conditions of the space environment, but also to the economic and technological realities of the space industry. The possibility of constructing low mass coring devices with energy consumption below 100 W was investigated in this paper. Minimization of energy consumption and mass of a coring is essential for the device to be used in space missions, when lander instruments supplied by low power electric battery are expected to work reliably and the launch cost (depending of mass) at an economically acceptable level. Some similar devices investigated for the future space missions are known from papers listed in the references. To answer whether or not it is possible to build such devices, the authors performed initial drillability tests. The obtained results are presented in this paper.
Predictive Search for Capacitated Multi-Item Lot Sizing Problems

For capacitated multi-item lot sizing problems, we propose a predictive search method that integrates machine learning/advanced analytics, mathematical programming, and heuristic search into a single framework. Advanced analytics can predict the probability that an event will happen and has been applied to pressing industry issues, such as credit scoring, risk management, and default management. Although little research has applied such technique for lot sizing problems, we observe that advanced analytics can uncover optimal patterns of setup variables given properties associated with the problems, such as problem attributes, and solution values yielded by linear programming relaxation, column generation, and Lagrangian relaxation. We, therefore, build advanced analytics models that yield information about how likely a solution pattern is the same as the optimum, which is insightful information used to partition the solution space into incumbent, superincumbent, and nonincumbent regions where an analytics-driven heuristic search procedure is applied to build restricted subproblems. These subproblems are solved by a combined mathematical programming technique to improve solution quality iteratively. We prove that the predictive search method can converge to the global optimal solution point. The discussion is followed by computational tests, where comparisons with other methods indicate that our approach can obtain better results for the benchmark problems than other state-of-the-art methods. Summary of Contribution: In this study, we propose a predictive search method that integrates machine learning/advanced analytics, mathematical programming, and heuristic search into a single framework for capacitated multi-item lot sizing problems. The advanced analytics models are used to yield information about how likely a solution pattern is the same as the optimum, which is insightful information used to divide the solution space into incumbent, superincumbent, and nonincumbent regions where an analytics-driven heuristic search procedure is applied to build restricted subproblems. These subproblems are solved by a combined mathematical programming technique to improve solution quality iteratively. We prove that the predictive search method can converge to the global optimal solution point. Through computational tests based on benchmark problems, we observe that the proposed approach can obtain better results than other state-of-the-art methods.
Effect of tree canopy on herbaceous vegetation and soil characteristics in semi-arid forests of the Aravalli hills

Abstract Herbaceous vegetation is of great ecological importance and responds quickly to environmental changes. The present study was aimed to understand the variation in herbaceous species composition, biomass and soil physico-chemical properties in the naturally formed gap and the understory of semi-arid forests in the Aravalli hills. Four permanent plots consisting of the gap as well as the understory were established. To study herbs phytosociological attributes and biomass, 10 quadrats of 0.5 × 0.5 m size were laid in each plot. For soil physico-chemical properties, 5 soil samples were collected randomly at 0–10 cm depth from each plot. Relationships among biodiversity indices, herbaceous biomass and soil physico-chemical properties were determined using Redundancy Analysis (RDA) and correlation analysis. Across the sites, Poaceae was the dominant family. All species showed a contagious distribution pattern. In the understory, Importance Value Index (IVI) was the recorded highest for Oplismenus burmannii, ranging from 138 to 230.5 while in the gap, it was the highest for Achyranthes aspera (56.15) followed by Eragrostis ciliaris (53.1). Both sites included, herbaceous community biomass in the gap ranging from 700 to 900 g m−2 while in the understory it ranged from 30 to 70 g m−2. Cenchrus ciliaris (597.97 g m−2) and Chrysopogon sp. (391.2 g m−2) contributed a major proportion of herbaceous community biomass in the gap. Oplismenus burmannii (52.2 g m−2), Dipteracanthus prostratus (16.6 g m−2) and Cynodon dactylon (9.6 g m−2) contributed a major proportion of herbaceous community biomass in the understory. The understory soil had significantly (p < 0.05) higher soil moisture (%), electrical conductivity (EC), soil organic carbon (SOC) and soil total nitrogen (TN) compared to the gap. Even though canopy had positive effects on soil physico-chemical properties, it has negatively influenced herbaceous species composition, diversity and biomass, due to significant reduction in solar radiation reaching the ground.
Brand Manager Sensemaking: Cognitive Frames in the Digital Media Environment

Abstract Marketers and advertising agencies must navigate an increasingly complex and ambiguous digital media environment. Advertising agencies have responded by adding new roles and removing barriers to integrating digital media into marketing campaigns. Despite these changes aiming to address clients’ needs, the agency-client relationship has reached an all-time low. The current study seeks to close the knowledge gap by examining how brand managers make sense of the digital media environment. Through phenomenological interviews with 18 North American brand managers at large organizations, this research uncovers three cognitive frames: expertise, efficiency, and consistency. These frames support three capabilities—advertising campaign evaluation, digital expertise, and creative development—that marketing organizations are insourcing from advertising agencies. These insourcing trends have significant ramifications for the advertising agency landscape. This research answers the call to gain deeper insight into the marketing organization, applies sensemaking to the digital media environment, and outlines future research opportunities based on three insourcing trends emerging from brand manager interviews.
Tobacco and Deforestation Revisited. How to Move towards a Global Land-Use Transition?

Articles 17 and 18 of the United Nations (UN) Framework Convention on Tobacco Control address the environmental sustainability of tobacco as a contested agricultural crop. They require regulatory land-use policies to be introduced and designed to enhance a sustainability transition to diversified farming practices and/or alternative livelihoods. Related activities of the UN Study/Working Group on Economically Sustainable Alternatives to Tobacco Growing are reviewed to assess and monitor the crop’s impact on natural resources with a focus on methods to identify tobacco-attributable deforestation (remote sensing, proxy values, secondary statistics, natural valuation, ecological/social surveys). It is posited that since 2007 no advances have been achieved in framing woody biomass destruction/degradation due to land extension and curing (i.e., drying green leaf using wood). Building on support by digital technologies and land surface monitoring systems, a novel post-2020 strategy is proposed to mainstream an extended set of indicators integratively, i.e., addressing biodiversity losses, soil carbon reservoirs and land degradation neutrality of tobacco as an agricultural crop. Thus, the point is emphasized that land stewardship requires political priority setting that makes the framing of land-use sustainability metrics more than a purely technical matter.
A Molecular Hepatocellular Carcinoma Prognostic Score System Precisely Predicts Overall Survival of Hepatocellular Carcinoma Patients

Background and Aims With high rates of recurrence post-treatment, hepatocellular carcinoma (HCC) is one of the most common types of cancer worldwide and the major cause of cancer death. To improve the overall survival of HCC patients, identification of a reliable biomarker and precise early diagnosis of HCC remain major unsolved problems. Methods We initially screened data from the Cancer Genome Atlas liver cancer cohort to identify potential prognosis-related genes. Then, a meta-analysis of five international HCC cohorts was implemented to validate such genes. Subsequently, artificial intelligence models (random forest and neural network) were trained to predict prognosis accurately, and a log-rank test was performed for validation. Finally, the correlation between the molecular hepatocellular carcinoma prognostic score (mHPS) and the stromal and immune scoring in HCC were explored. Results A comprehensive list of 65 prognosis-related genes was obtained, most of which have been not extensively studied thus far. A universal HCC mHPS system depending on the expression pattern of only 23 genes was established. The mHPS system had general applicability to HCC patients (log-rank p<0.05) in a platform-independent manner (RNA sequencing or microarray). The mHPS was also correlated with the stromal and immune scoring in HCC, reflecting the status of the tumor immune microenvironment. Conclusions Overall, the mHPS is an easy and cost-effective prognosis predicting system, which can disclose previously uncovered heterogeneity among patient subpopulations. The mHPS system can further stratify patients who are at the same clinical stage and should be valuable for precise treatment. Moreover, the prognosis-related genes recognized in this study have potential in targeted and immune therapy.
Long‐term trophic state responses of a large tropical coastal lagoon to land use changes and nutrient transport

The watershed of a large tropical coastal lagoon, historically hosting large sugarcane crops, which has been reduced during the last decades. It suggests that land use and land cover changes (LULCC) would lower the trophic state of the coastal lagoon due to less fertilization application and consequently reducing nutrient transfer into the lagoon. In this context, this study assessed the influence of LULCC, represented by the reduction of the sugarcane crops on the trophic state of a large tropical coastal lagoon. This influence was assessed by means of information about the long‐term overall mass‐balance budget, involving the estimation of the N and P loads from the sugarcane crops, other anthropogenic sources and natural processes; measurements of the river N and P fluxes into the lagoon; its seaward outflow and the long‐term lacustrine nutrient retention. The results indicate that sugarcane crop reduction represented a decrease of 686 t of N and 51 t of P being emitted to the lagoon watershed. However, N and P loads from sugarcane crops were partially replaced by other anthropogenic activities, but even with the reduction of the nutrient fluxes, the long‐term supereutrophic responses of the coastal lagoon was maintained. The sediment‐related C/N and isotopic composition of the lagoon was sensitive to LULCC, indicating changes on the organic matter inputs into the lagoon. The trophic state was also influenced by the soil N and P accumulation and the long‐term nutrient retention within the lagoon imposed by its restricted water connection to the sea.
A C-Band High-Efficiency Power Amplifier MMIC With Second-Harmonic Control in 0.25 μm GaN HEMT Technology

This letter presents a <inline-formula> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula>-band high-efficiency fully integrated high-power amplifier (HPA) monolithic microwave integrated circuit (MMIC) in 0.25 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> gallium nitride (GaN) high electron mobility transistor (HEMT) technology. The proposed GaN HPA MMIC consists of two amplifying stages, and its output stage includes eight transistors in parallel. In order to realize the high efficiency, a low-loss harmonic control network (HCN) using a parallel <italic>LC</italic> resonate block is applied to obtain the optimum load impedance to each transistor employed in the output stage of the HPA at both <inline-formula> <tex-math notation="LaTeX">$f_{0}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2f_{0}$ </tex-math></inline-formula>. Thus, the designed GaN HPA can operate in pulse conditions of 100 <inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> pulsewidth and 10% of duty cycle over the frequency from 5.6 to 6.3 GHz. The proposed high-efficiency GaN HPA MMIC provides an average output power of 45.0–45.5 dBm (31.6–35.5 W) with a power-added efficiency (PAE) of 59%–61.8%, and a gain of 26–28.5 dB under a drain voltage of 28 V. The area of the proposed GaN HPA MMIC is 4.2 mm <inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 4 mm including pads.
Tendencies of the Absorptive Capacity and Its Correlation with Innovation and the Incubated Companies’ Performance

This study aims at mapping the scientific production of absorptive capacity (ACAP) and identifying how these studies analyse the correlation of ACAP with company innovation and with organisational performance. For such, a bibliometric study was carried out, and it used criteria that selected the main articles that have been published on absorptive capacity in two research bases—ISI Web of Science and Scopus—within a temporal cut from the past 5 years (2014–2018). With the help of the HistCiteTM and VOSviewer software, it was possible to select the articles that addressed the correlation of absorptive capacity with company innovation and organisational performance in the incubated companies’ context. By analysing these articles’ findings, it can be concluded that the absorptive capacity is an antecedent of innovation in companies and has a positive correlation with organisational performance. The studies’ tendencies show that the factors which help with the external knowledge intake are social networks, bonds with agents and partner proximity. However, the incubated companies need the incubators’ support to help with these factors, since they are novice companies and do not keep in touch with important partners. They also need to know how to explore and transform external knowledge into internal benefits.
Assessing salt marsh loss and degradation by combining long‐term LANDSAT imagery and numerical modelling

The precise evaluation of the conservation status of salt marshes, the understanding of the mechanisms behind loss and degradation and the anticipation of future threats are fundamental to assist management solutions able to reverse the declining trend observed in these environments. Previous methods combining remote sensing and hydrodynamic modelling have been revealed to be effective in assessing degradation in restricted marshes, but unable to characterise dynamics of marshes at the estuarine scale. This study proposes an alternative methodology to identify priority areas for conservation by combining LANDSAT satellite remote sensing and numerical modelling. Using the Ria de Aveiro as case‐study, the main objectives of this work are to: (1) identify vegetation loss and degradation in estuarine marshes; (2) determine the mechanisms behind marsh deterioration; (3) anticipate future threats posed by climate‐induced mean sea level rise and; (4) provide management solutions aiming to protect and recover degraded salt marshes. LANDSAT imagery reveals that the most deteriorated salt marshes are located on the central and upper lagoon regions, and the numerical results support that marsh loss and degradation result from the increased tidal action triggered by the deepening of the lagoon channels. The increase in tidal currents promoted the erosion of marsh shoreline, whereas the changes in the inundation patterns over the intertidal areas triggered interior drowning. Climate‐induced mean sea level rise will likely exacerbate marsh deterioration, increasing the urgency to implement a management plan aiming to protect marshes from erosion and promote sedimentation in submerged marshes, to ensure their sustainability.
A Conservação da Ararinha-azul, Cyanopsitta spixii (Wagler, 1832): Desafios e Conquistas.

A ararinha-azul (Cyanopsitta spixii) é o único representante do seu gênero e hoje é considerada provavelmente extinta na natureza. O manejo ex situ é prioridade na estratégia de conservação desde o início da década de 90, sendo um exemplo de parceria público-privada de sucesso. Em 2017, finalmente, a população cativa alcançou a estabilidade com 152 indivíduos, possibilitando planejar as ações de reintrodução. Além disso, duas unidades de conservação foram criadas para propiciar a recuperação da espécie no ambiente natural, e, em 2020, 52 ararinhas-azuis foram repatriadas para um Centro de Reprodução e Reintrodução no interior do Refúgio de Vida Silvestre da Ararinha Azul. Aproximadamente 20 ararinhas-azuis estão em adaptação para o início da reintrodução e restabelecimento da população na área de distribuição histórica. Estamos perto de devolver a espécie para o seu ambiente natural, de onde nunca deveria ter sido extirpada.
On Block Prediction For Learning-Based Point Cloud Compression

Point clouds are among popular visual representations for immersive media. However, the vast amount of information generated during their acquisition requires effective compression for practical applications. Although relevant activities from standardization bodies have led to state-of-the-art compression using conventional methods, learning-based encoders have recently emerged as promising solutions with comparable performance while offering additional attractive features. Yet, there is still a large unexplored space for research that can lead to further advances. In this paper, we propose a block prediction module for bit-rate reduction of geometry-only point clouds. Our method exploits spatial redundancies at the decoding stage between block partitions in the point cloud, and predicts a query block using Generative Adversarial Networks. Results show performance improvements of the objective metrics at low bit-rates, after integration in a baseline auto-encoder architecture.