Miracle-dz/UniFAR-FTUs huggingface dataset:
New records and a notable observation of potentially predator-avoiding amplectic behaviour in Boophis erythrodactylus from Madagascar

ABSTRACT The Red-fingered Bright-eyed Frog Boophis erythrodactylus is an endemic, range-restricted arboreal frog found only in the eastern rainforests of Madagascar. We report new localities for this species, along with locality records for its sister species B. tasymena, including localities where they occur in sympatry, which has never been reported before. We also document evidence for the existence of a colour variant of B. tasymena that is identical to B. erythrodactylus in appearance. We also observed never before documented breeding behaviour in the poorly known B. erythrodactylus, where the male and female in amplexus used a submerged site in a river potentially for oviposition. We also explore why this may be a predator-avoidance strategy considering the presence of aquatic invertebrate predators active near the surface and absence of fully aquatic vertebrate predators, such as fish in headwater stream habitats. Predator-avoidance strategies are a vital component of organismal survival, particularly for amphibians with complex life cycles. Natural history observations are key to revealing such strategies and behaviour, and they form the basis of evolutionary biology and is also fundamental for conservation management.
Single-shot N-step phase measurement profilometry

Abstract. A single-shot N-step phase measurement profilometry (single-shot N-PMP) is proposed. In the traditional N-step PMP, N (N > 2) frames of phase-shifting sinusoidal gratings are needed to be projected onto the measured object. The corresponding N frames of phase-shifting deformed patterns modulated by the object are needed to be captured. And the larger the N is, the higher the measuring accuracy will be. In the proposed method, only one sinusoidal grating is needed to be projected and only one corresponding deformed pattern is captured. The proposed method can efficiently avoid direct filtering in the spectrum of the deformed pattern because of the secondary modulation in computer. The proposed method is an innovative single-shot, three-dimensional (3D) measurement with the highest accuracy among the single-shot 3D measurements so far for inheriting of the traditional optional N-step PMP. And the optional larger N can result in higher accuracy while the single-shot feature can be always guaranteed both the static and real-time 3D measurements. Furthermore, the mathematical model of the proposed method is more concise compared with the traditional PMP for the phase just modulated by the measured object itself can be directly solved without two phase resolutions and two phase unwrappings for both the reference plane and the measured object. The simulations and experimental results show the feasibility and validity of the proposed method.
A Reliable Short‐Term Power Load Forecasting Method Based on VMD‐IWOA‐LSTM Algorithm

To reduce the short‐term load forecasting (STLF) error of off‐line forecasting model, a VMD‐IWOA‐LSTM (VIL) method for STLF is proposed. Firstly, variational mode decomposition (VMD) is used to decompose the historical power load signals. Then, the decomposed signals are reconstructed according to the similarity of Pearson correlation coefficient (PCC), and meteorological data are chosen for each reconstructed component based on the set PCC threshold. The long short‐term memory (LSTM) models are used to predict the corresponding components, and improved whale optimization algorithm (IWOA) is used to optimize the parameters in LSTM. Finally, the forecast results of each component are added together to get the final forecast result. The experimental results of power load data in a certain area show that the proposed method has the advantages of strong anti‐interference performance and high prediction accuracy compared with other methods, and has strong practicability. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
Coconut synthesis report on gaps for priority collecting and conservation : technical report LOA 2014/44

Based on the information available from COGENT, important gaps persist in the affiliated germplasm collections, e.g. for large parts of Polynesia, Melanesia, Micronesia, Australia, Indonesia, Malaysia, India, Myanmar, Madagascar, Kenya and Somalia, among regions where coconut is likely to be native. SSR marker data for 86 coconut populations were analyzed to study the distribution of genetic diversity, using Jost’s J1 index. The Indo-Pacific region presents the highest diversity, with hotspots in Vanuatu, Papua New Guinea, South East Asia, and East Africa. Atlantic shores, where the coconut was introduced in historical times, appear less diverse. However, this picture is incomplete, as many neighboring areas correspond to gaps in collections and genetic studies. The potential impact of climate change on coconut distribution was anticipated for the year 2050, using three climate models (BCC-CSM1-1, CCSM4, and HadGEM2-ES) and three gas emission/radiative forcing scenarios (rcp4.5, rcp6.0, and rcp8.5). All results converge in predicting a very strong increase of areas climatically suitable for the coconut, thus discarding a global negative impact of climate change per se. This seems reassuring in terms of genetic erosion risk, as well as production. However, a few regions, including southeastern India and Bangladesh, would be negatively affected. Due the eastward shift of favorable areas around the Bay of Bengal, Bangladesh could lose about half of his coconut production areas. The 0.2-0.4m sea-level rise expectation for 2000-2050 might be doubled in case the West Antarctic Ice Sheet has already been set into motion. Even so, its impact on coastal coconut populations should be negligible for continents and large islands, where shoreline retreat should be modest, compared to the extension of climatically suitable areas. The situation would be different for distant, small and low-lying islands, as well as delta areas, particularly in the Indo-Pacific region, where rising rates are up to thrice the global rate. Thus, there are severe threats on the Maldives, Laccadive, and Mascarene archipelagos, and on the myriad of far Polynesian, Micronesian, and Melanesian islands, all regions hosting an important diversity of coconut germplasm, not well studied so far. Flooding threats will increase on the shores of eastern India and the Bay of Bengal, increasing the pressure on coconut and people.
Host Identity Protocol

Host Identity Protocol is Internetworking architecture and an associated set of protocols, developed at the IETF since 1999 and reaching their first stable version in 2007. HIP enhances the original Internet architecture by adding a name space used between the IP layer and the transport protocols. This new name space consists of cryptographic identifiers, thereby implementing the so-called identifier / locator split. In the new architecture, the new identifiers are used in naming application level end-points (sockets), replacing the prior identification role of IP addresses in applications, sockets, TCP connections, and UDP-based send and receive system calls. IPv4 and IPv6 addresses are still used, but only as names for topological locations in the network. HIP can be deployed such that no changes are needed in applications or routers. Almost all pre-compiled legacy applications continue to work, without modifications, for communicating with both HIP-enabled and non-HIP-enabled peer hosts. The architectural enhancement implemented by HIP has Profound consequences. A number of the previously hard networking problems become suddenly much easier. Mobility, multihoming, and baseline end-to-end security integrate neatly into the new architecture. The use of cryptographic identifiers allows enhanced accountability, thereby providing a base for easier build up of trust. With privacy enhancements, HIP allows good location anonymity, assuring strong identity only towards relevant trusted parties. Finally, the HIP protocols have been carefully designed to take middle boxes into account, providing for overlay networks and enterprise deployment concerns. This article provides an in-depth look at HIP, discussing its architecture, design, benefits, potential drawbacks, and ongoing work.
Dam Survey Displacement Monitoring Model and Its Establishment

Based on the analysis of the affecting factors of dam displacement, a general formula of multidimensional, multipoint and multidirectional displacement model for dam safety monitoring was put forward. Through FEM calculation together with statistic analysis, the problem, which is difficult to determine the environmental effecting part on the displacement such as water pressure and temperature, was solved. Further more, a complete simulation model system of displacement was built up. The result of application is satisfactory.
Pre-Operative Assessment of Micronutrients, Amino Acids, Phospholipids and Oxidative Stress in Bariatric Surgery Candidates

Obesity has been linked to lower concentrations of fat-soluble micronutrients and higher concentrations of oxidative stress markers as well as an altered metabolism of branched chain amino acids and phospholipids. In the context of morbid obesity, the aim of this study was to investigate whether and to which extent plasma status of micronutrients, amino acids, phospholipids and oxidative stress differs between morbidly obese (n = 23) and non-obese patients (n = 13). In addition to plasma, malondialdehyde, retinol, cholesterol and triglycerides were assessed in visceral and subcutaneous adipose tissue in both groups. Plasma γ-tocopherol was significantly lower (p < 0.011) in the obese group while other fat-soluble micronutrients showed no statistically significant differences between both groups. Branched-chain amino acids (all p < 0.008) and lysine (p < 0.006) were significantly higher in morbidly obese patients compared to the control group. Malondialdehyde concentrations in both visceral (p < 0.016) and subcutaneous (p < 0.002) adipose tissue were significantly higher in the morbidly obese group while plasma markers of oxidative stress showed no significant differences between both groups. Significantly lower plasma concentrations of phosphatidylcholine, phosphatidylethanolamine, lyso-phosphatidylethanolamine (all p < 0.05) and their corresponding ether-linked analogs were observed, which were all reduced in obese participants compared to the control group. Pre-operative assessment of micronutrients in patients undergoing bariatric surgery is recommended for early identification of patients who might be at higher risk to develop a severe micronutrient deficiency post-surgery. Assessment of plasma BCAAs and phospholipids in obese patients might help to differentiate between metabolic healthy patients and those with metabolic disorders.
Robust local slope estimation by deep learning

In the seismic community, the local slope is essential for various applications, including structure prediction, seislet transform, trace interpolation and denoising. The most popular method to calculate slope is the plane‐wave destruction, which assumes that the seismic data can be represented by local plane waves. However, the plane‐wave destruction method fails when the seismic data become very noisy. Taking random noise into consideration, we adopt the deep learning method to calculate the local slope. In the deep learning architecture, the input is noisy data and the target is an accurate slope estimated from the clean data using plane‐wave destruction. The deep learning architecture includes a convolutional layer, deconvolutional layer, normalization layer and activation layer which are suitable to suppress noise and learn the nonlinear relationship between the input and the target. After training, the network is applied to other test examples to calculate local slopes. In addition, we implement the seislet transform and structure prediction applications based on the estimated slope. Both the estimated slope and the related applications indicate that the proposed method can robustly obtain the local slope from noisy seismic data, compared with the plane‐wave destruction method.
Emerging UAV technology for disaster detection, mitigation, response, and preparedness

In recent years, Unmanned Aerial Vehicles (UAVs) have gained significant interest in research groups due to the wide range of applications, such as disaster surveillance and monitoring, rescue operations, military, civil, and so forth. UAVs are most often used to fulfill both user's services and requirements such as wireless communication facilities to end‐users, as a relay node to extend the coverage of the core network, and so forth. UAVs are versatile in design and can cover larger areas, contrary to the Tethered Balloon and Loon Balloon systems. Generally in any natural or human‐made disaster, there is a high potential risk of damage to buildings, transport systems, communication systems, and basic services. During heavy disasters like landslides, forest fires, floods, earthquakes, and so forth, the conventional terrestrial communication system gets destroyed, and people face many problems. In this case, UAVs prove to offer a better solution to provide fast, cost‐effective, easy to deploy, and secure wireless communication to the victims. But there are some issues like interference between UAVs and other base stations, coordination between UAVs, Quality of Service requirements, Size, Weight, and Power limitation, delay, coverage, positioning of UAVs, and so forth. This study article mainly highlighted these issues and try to present the recent developments of the state‐of‐the‐art to overcome these issues. In UAV communications, with an increasing emphasis on how UAVs can be integrated with different technologies, such as the Internet of Things, Wireless Sensor Network, Heterogeneous Network, and Cloud computing. The primary aim of this article is to examine how UAVs can assist survivors in floods, earthquakes, tsunamis, or in any natural or human‐made disaster situations, either in the present or soon. Also, it focused on various applications of UAVs in disaster management (DM). It underlines the significance of UAVs in DM and their advantages. It also focuses on the various issues and challenges faced by the UAV‐based infrastructure and security issues and gives future directions.
BARS Influences Neuronal Development by Regulation of Post-Golgi Trafficking

Neurons are highly polarized cells requiring precise regulation of trafficking and targeting of membrane proteins to generate and maintain different and specialized compartments, such as axons and dendrites. Disruption of the Golgi apparatus (GA) secretory pathway in developing neurons alters axon/dendritic formation. Therefore, detailed knowledge of the mechanisms underlying vesicles exiting from the GA is crucial for understanding neuronal polarity. In this study, we analyzed the role of Brefeldin A-Ribosylated Substrate (CtBP1-S/BARS), a member of the C-terminal-binding protein family, in the regulation of neuronal morphological polarization and the exit of membrane proteins from the Trans Golgi Network. Here, we show that BARS is expressed during neuronal development in vitro and that RNAi suppression of BARS inhibits axonal and dendritic elongation in hippocampal neuronal cultures as well as largely perturbed neuronal migration and multipolar-to-bipolar transition during cortical development in situ. In addition, using plasma membrane (PM) proteins fused to GFP and engineered with reversible aggregation domains, we observed that expression of fission dominant-negative BARS delays the exit of dendritic and axonal membrane protein-containing carriers from the GA. Taken together, these data provide the first set of evidence suggesting a role for BARS in neuronal development by regulating post-Golgi membrane trafficking.
Applying Zero Trust Principles to Secure Industrial Control Networks

The defense in depth principles, normally used by industrial control networks (ICN), may no longer be adequate in an industry 4.0 scenario, which the sensors, actuators and supervisory systems needs to communicate directly to the cloud. The Zero Trust Architecture is raising as de facto standard for securing cloud application and can be used to protect an ICN, but normally it is applicable only by replacing existing applications and network gears. This preliminary work presents an option to apply the Zero Trust principles on ICN, maintaining the existent systems and network.
Holistic and Integrated Framework to Examine Formal Women Business Networks (FWBNs)

Research about women entrepreneurs is not new. In addition to the body of work on women entrepreneurship, networks and businesses, several resources, assistance, and support have been provided through various channels to assist women in their business and entrepreneurial pursuits. Although, research in these areas is popular, there is an aspect that has not gained as much attention – formal women business networks (FWBNs). FWBNs are networks that run like organisations and provide a way for women to network and pursue shared interests while gaining business benefits. These networks provide benefits such as funding, trainings, access to business resource, and are funded by various organisations as well as patronized by several women seeking the benefits they provide. Hence, there is a high expectation on these networks to not only deliver on the very much needed support for women entrepreneurs, but also, to deliver on the ROI to groups, organizations, bodies, and women that give to these networks. Furthermore, recent environmental/external influences like a pandemic have impacted the way entrepreneurs do business and increased the need for support and networks. Thus, it is important that FWBNs that serve to help women businesses be examined more closely and holistically. While literature provides some evidence of the importance of FWBNs, there is limited research about these FWBNs. This could be due to the limited number of frameworks, models or theories that holistically examines all the various possible elements in these networks, as well as the relationships between them. Therefore, a holistic and integrated framework that draws from existing frameworks and provides a lens to measure and explore all possible elements that impact a FWBN, can help provide better insights and understanding in several aspects. This paper is an attempt to provide a holistic and integrated framework that draws from different theories and literature concepts to examine the nature of FWBNs and how they contribute to the success of women entrepreneurs
Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy

Abstract Objective This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model. Methods A retrospective case‐control study was performed. Overall, 367 patients who were diagnosed with sTBI and fulfilled the inclusion criteria were enrolled from the Department of Neurosurgery of the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2020. They were divided into a reoperation group and a non‐reoperation group according to whether they underwent reoperation for hemorrhages. Using univariate binary logistic regression analysis, the possible risk factors were screened. Subsequently, the independent risk factors of reoperation for postoperative hemorrhages were screened using the forward step method of multivariate binary logistic regression analysis, and a corresponding nomogram model was constructed. The receiver operative characteristic (ROC) curve was used to evaluate the reliability of the model. Finally, 30% of the data were randomly selected for internal verification of the model. Results The reoperation rate for hemorrhage after sTBI emergency craniotomy was 14.71% (54/367); multivariate logistic regression analysis showed that multiple hemorrhages (odds ratio [OR] = 4.38, 95% confidence interval [CI]: 1.815–10.587, p = 0.001), day or night surgery (OR = 0.26, 95% CI: 0.119–0.547, p < 0.001), operation duration (OR = 0.74, 95% CI: 0.119–0.547, p < 0.025), and abnormal intraoperative blood pressure fluctuation (OR = 4.15, 95% CI: 2.090–8.245, p < 0.001) were statistically significant. The sensitivity and specificity of the nomogram model were 0.815 and 0.661, respectively, and the area under ROC curve was 0.76 (95% CI: 0.705–0.833). Internal verification showed that the area under the ROC curve was 0.783 (95% CI: 0.683–0.883). Conclusions Taken together, the results of our study reveal that multiple preoperative intracranial hemorrhages, day and night operation, operation duration, and abnormal fluctuation of intraoperative blood pressure were independent risk factors for postoperative bleeding and reoperation for sTBI. Through the analysis of the influencing factors, a prediction model for the risk of bleeding and reoperation after craniocerebral trauma was developed. Compared with other relevant studies, this prediction model has good prediction efficiency and can be used to predict the occurrence of bleeding and reoperation after sTBI in patients.
Risk evaluation of internal short circuit for lithium‐ion battery based on an active protection method

Internal short circuit (ISC) can lead to thermal runaway and even cause fire. But the traditional passive methods cannot prevent the ISC before it occurs. The active protection method is proposed based on the evaluation of the ISC risk. An evaluation model is built based on the electrochemical model and solved with the Monte‐Carlo method. Then, the model is verified with experimental data. The simulation result agrees with the experimental data of accelerated cycle life. Next, the effect of different factors on the probability of ISC risk is studied. It is found that (a) the variation trend of the probability of ISC risk with cycle number is nonlinear. The critical cycle number exists in the long‐time use of the battery. (b) The probability increment of ISC risk becomes apparent when the charge rate reaches a critical value. (c) Battery temperature plays a great role in the critical cycle number. A lower temperature reduces the critical cycle number. (d) Effect of factors on the probability of ISC risk is listed as follows: charge rate > cycle number > battery temperature. With the help of the active protection method, ISC risk can be predicted before ISC occurs.