Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery of critically endangered Nassau grouper (Epinephelus striatus) in the Cayman Islands following targeted conservation actions

Significance Overfishing of tropical grouper- and snapper-spawning aggregations is a globally pervasive problem, but evidence is elusive that recovery can occur following stock collapse. We analyze a uniquely rich research and monitoring dataset from spawning aggregations in the Cayman Islands to reconstruct annual Nassau grouper spawner abundance across almost 2 decades of postcollapse adaptive-fisheries management. Using an integrated population model that leverages both mark–resight and video census techniques, we demonstrate that Nassau grouper have undergone a remarkable recovery during this time frame. Because of the implementation of these deliberate, science-based conservation strategies, Little Cayman is now home to the largest remaining identified Nassau grouper aggregation anywhere in the world. Many large-bodied marine fishes that form spawning aggregations, such as the Nassau grouper (Epinephelus striatus), have suffered regional overfishing due to exploitation during spawning. In response, marine resource managers in many locations have established marine protected areas or seasonal closures to recover these overfished stocks. The challenge in assessing management effectiveness lies largely in the development of accurate estimates to track stock size through time. For the past 15 y, the Cayman Islands government has taken a series of management actions aimed at recovering collapsed stocks of Nassau grouper. Importantly, the government also partnered with academic and nonprofit organizations to establish a research and monitoring program (Grouper Moon) aimed at documenting the impacts of conservation action. Here, we develop an integrated population model of 2 Cayman Nassau grouper stocks based on both diver-collected mark–resight observations and video censuses. Using both data types across multiple years, we fit parameters for a state–space model for population growth. We show that over the last 15 y the Nassau grouper population on Little Cayman has more than tripled in response to conservation efforts. Census data from Cayman Brac, while more sparse, show a similar pattern. These findings demonstrate that spatial and seasonal closures aimed at rebuilding aggregation-based fisheries can foster conservation success.
SOIL STABILIZATION USING INDUSTRIAL WASTE (WHEAT HUSK AND SUGARCANE STRAW ASH)

1M. Tech Scholar, Geotechnical Engineering, Galaxy Global Group of Institutions, Shahabad, Haryana, India. 2Head of Department, Dept. of Civil Engineering, Galaxy Global Group of Institutions, Shahabad, Haryana, India. 3Assistant Professor, Dept. of Civil Engineering, Galaxy Global Group of Institutions, Shahabad, Haryana, India. ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract The safe disposal of both hazardous and nonhazardous waste becomes a problematic for the civil engineers. This is because only few states are able to dump these wastes emanate from industries safely. This paper presents a research on safe disposition of industrial waste such as wheat husk ash (WHA) and sugarcane straw ash(SCSA). So, efforts have been made using WHA and SCSA in this research to revamp the quality of the soil. The main objective of the ground improvement is increasing the shear strength and decreasing the compressibility of the soil. The study was conducted using the expansive soil by taking varying quantities, which are then mingled with the different proportions of stabilized material for Atterberg limit tests and Unconfined compressive strength(UCS) test and soil retained within 7 days curing period for California bearing ratio(CBR) test. These tests are experimented and proved by the standard tests IS 2720 and finally concluded that test results ameliorate the geotechnical properties of the soil.
A REVIEW OF DIGITAL FORENSIC CHALLENGES IN THE INTERNET OF THINGS (IOT)

The Internet of Things (IoT) involves the rapid adoption of smart, adaptive and connected devices and is rapidly being deployed in critical infrastructure areas like heath, utility, homes, transportation and industries. It brings benefits and reliability to consumers, the haste and its large scale connection however poses serious risks to consumers. These risks includes new attack vectors, new vulnerabilities and physical destruction through remote access. The IoT brings implications on cyber security as these devices are connected through the internet. Investigating digital crimes in the IoT domain using digital forensic technology is more challenging. Evidence extraction for forensic investigation is difficult since equipment could lose their data if left to operate for a long time, there is also the problem of jurisdictions. In this paper, we review literature related to forensics in the IoT and analyse the various models that have been proposed. The survey revealed the difficulty in digital evidence extraction in the IoT domain
4G Wireless Network Revolution

—. In 4G mobile technology is the next step in this direction. 4G communication systems is the next generation of wireless networks that will totally replace 3G communication networks. 4G is the fourth generation of broadband cellular network technology, succeeding 3G. A 4G system must provide capabilities defined by ITU in IMT Advanced. It is supposed to provide its customers with better speed and all IP based multimedia services. 4G communication systems is all about an integrated, global network that will be able to provide a comprehensive IP solution where voice, data and streamed multimedia can be given to users on an "Anytime, Anywhere" in the world. At present we have many technologies each capable of performing functions like supporting voice traffic using voice over IP (VoIP), broadband data access in mobile environment etc., but there is a great need of deploying such technologies that can integrate all these systems into a single unified system. 4G communication systems presents a solution of this problem as it is all about seamlessly integrating the terminals, networks and applications. The race to implement 4G is accelerating as well as quite challenging. The aim of this paper is to highlight the benefits, challenges in deployment and scope of 4G technologies. Systems . Fig.1 demonstrates the seamless connectivity of the networks.
SARDO: An Automated Search-and-Rescue Drone-Based Solution for Victims Localization

Natural disasters affect millions of people every year. Finding missing persons in the shortest possible time is of crucial importance to reduce the death toll. This task is especially challenging when victims are sparsely distributed in large and/or difficult-to-reach areas and cellular networks are down. In this paper we present SARDO, a drone-based search and rescue solution that leverages the high penetration rate of mobile phones in the society to localize missing people. SARDO is an autonomous, all-in-one drone-based mobile network solution that does not require infrastructure support or mobile phones modifications. It builds on novel concepts such as pseudo-trilateration combined with machine-learning techniques to efficiently locate mobile phones in a given area. Our results, with a prototype implementation in a field-[1], show that SARDO rapidly determines the location of mobile phones (<inline-formula><tex-math notation="LaTeX">$\sim \! 3$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>∼</mml:mo><mml:mspace width="-0.166667em"/><mml:mn>3</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="albanese-ieq1-3051273.gif"/></alternatives></inline-formula> min/UE) in a given area with an accuracy of few tens of meters and at a low battery consumption cost (<inline-formula><tex-math notation="LaTeX">$\sim \! 5\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>∼</mml:mo><mml:mspace width="-0.166667em"/><mml:mn>5</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="albanese-ieq2-3051273.gif"/></alternatives></inline-formula>). State-of-the-art localization solutions for disaster scenarios rely either on mobile infrastructure support or exploit onboard cameras for human/computer vision, IR, thermal-based localization. To the best of our knowledge, SARDO is the first drone-based cellular search-and-rescue solution able to accurately localize missing victims through mobile phones.
Temperature-Aware Persistent Data Management for LSM-Tree on 3-D NAND Flash Memory

Key-value (KV) store has been widely deployed in both embedded systems and enterprise systems. Most KV stores today use log structured merge tree (LSM-Tree), as LSM-Tree can eliminate random write operations to the secondary storage and maintain acceptable read performance. LSM-Tree is originally designed for the secondary storage device with hard disk drives. As the emerging storage media, three-dimensional (3-D) flash memory has become the mainstream technology to replace hard disk drives. Different from hard disk drives and the conventional planar flash memory, 3-D flash memory is vulnerable to temperature. High temperature will introduce both charge loss and retention degradation. Since LSM-Tree transfers random write operations to the sequential ones, the access to consecutive physical address in flash memory will cause the temperature issue. This will affect the integrity of data stored in 3-D flash memory. This article presents TLSM, a temperature-aware persistent data management scheme for LSM-Tree-based KV store on 3-D NAND flash memory. TLSM offers both application-level LSM-Tree optimization and firmware-level address management to allocate persistent data to 3-D flash. At the application-level, TLSM presents a novel temperature-aware LSM data structure to reduce the amount of data issued from LSM-Tree to 3-D flash memory. At the firmware-level, TLSM reallocates the data to physical blocks with relatively low temperature. This cross-layer optimization can effectively handle the temperature issue to ensure the data integrity of LSM-Tree in 3-D flash memory. We demonstrate the viability of the proposed scheme using a set of standard benchmarks. Our extensive evaluations show that, TLSM can significantly enhance the data integrity and reduce write amplifications compared to representative schemes.
Floristic analysis of semi-arid mountain ecosystems of the Griqualand West centre of plant endemism, Northern Cape, South Africa

Abstract. Van Staden N, Siebert SJ, Cilliers DP, Wilsenach D, Frisby AW. 2020. Floristic analysis of semi-arid mountain ecosystems of the Griqualand West centre of plant endemism, Northern Cape, South Africa. Biodiversitas 21: 1989-2002. The Griqualand West Centre (GWC) is one of 13 centres of plant endemism in South Africa. Despite its unique flora, it remains poorly conserved and studied. A recent study identified an extensive geographical core area for the GWC, but endemic plant species were found to be absent from certain parts within these borders. To address this, we refined the current GWC borders based on an ecological niche model, which predicted that endemic species are restricted to four mountain ranges within GWC. Mountain floras within these refined borders were then floristically compared to assess whether they are hotspots of endemicity. Floristically, the Asteraceae, Fabaceae, Malvaceae, and Poaceae were the dominant plant families. Mountain ecosystems differed from one another at species level, with indicator species explaining the compositional differences. Distribution patterns of indicator species were determined by mean annual precipitation, Ca: Mg ratios, soil pH, cation exchange capacity, iron, and sand content. These environmental factors are possible drivers of niche partitioning, environmental filtering and habitat specialization in each mountain ecosystem. Limestone and banded ironstone habitats were identified as conservation priority areas, since they contained the highest numbers of rare and threatened GWC restricted-range species, of which six were narrow endemics.
Oil

a. Bars indicate recession periods as dated by the National Bureau of Economic Research. b. West Texas intermediate. c. Light sweet crude oil futures. Deliverable grades are determined by sulfur content and API gravity. West Texas intermediate crude oil qualifies for delivery. d. First quarter only. SOURCES: U.S. Department of Commerce, Bureau of the Census and Bureau of Economic Analysis; Energy Information Administration; Nouriel Roubini and Brad Setser, “The Effect of the Recent Oil Price Shock on the U.S. and Global Economy,” Stern School of Business, August 2004; National Bureau of Economic Research; New York Mercantile Exchange; Wall Street Journal; and Bloomberg Financial Information Services.
Perspectives in Life Cycle Impact Assessment: A Structured Approach to Combine Models of the Technosphere, Ecosphere and Valuesphere

Preface. 1. Introduction to Life Cycle Assessment and its Positioning. 2. Shift of Paradigm - Propositions - Objectives. 3. Modelling the Valuesphere by Cultural Theory. 4. Modelling the Ecosphere by the Structured Aggregation Procedure. 5. Dalys - An Index for Human Health Assessment. 6. Damage to Human Health From Environmental Chemicals that Cause Cancer. 7. Damage to Human Health from Respiratory Effects. 8. Perfection of the Framework. 9. Results and Discussion. 10. Conclusions. Appendices. References. Subject Index.
Bayesian mixture cure rate frailty models with an application to gastric cancer data

Mixture cure rate models are commonly used to analyze lifetime data with long-term survivors. On the other hand, frailty models also lead to accurate estimation of coefficients by controlling the heterogeneity in survival data. Gamma frailty models are the most common models of frailty. Usually, the gamma distribution is used in the frailty random variable models. However, for survival data which are suitable for populations with a cure rate, it may be better to use a discrete distribution for the frailty random variable than a continuous distribution. Therefore, we proposed two models in this study. In the first model, continuous gamma as the distribution is used, and in the second model, discrete hyper-Poisson distribution is applied for the frailty random variable. Also, Bayesian inference with Weibull distribution and generalized modified Weibull distribution as the baseline distribution were used in the two proposed models, respectively. In this study, we used data of patients with gastric cancer to show the application of these models in real data analysis. The parameters and regression coefficients were estimated using the Metropolis with Gibbs sampling algorithm, so that this algorithm is one of the crucial techniques in Markov chain Monte Carlo simulation. A simulation study was also used to evaluate the performance of the Bayesian estimates to confirm the proposed models. Based on the results of the Bayesian inference, it was found that the model with generalized modified Weibull and hyper-Poisson distributions is a suitable model in practical study and also this model fits better than the model with Weibull and Gamma distributions.
Longitudinal Study of Total and Pathogenic Vibrio parahaemolyticus (tdh+ and/or trh+) in Two Natural Extraction Areas of Mytilus chilensis in Southern Chile

Vibrio parahaemolyticus is the leading cause of seafood-associated bacterial gastroenteritis worldwide. Although different studies have focused on its pattern of variation over time, knowledge about the environmental factors driving the dynamics of this pathogen, within the Chilean territory, is still lacking. This study determined the prevalence of total and pathogenic V. parahaemolyticus strains (tdh and/or trh genes) in mussels (Mytilus chilensis) collected from two natural growing areas between 2017 and 2018, using selective agar and PCR analysis. V. parahaemolyticus was detected in 45.6% (93/204) of pooled samples from the Valdivia River Estuary. The pathogenic strains carrying the tdh and/or trh gene were detected in 11.8% (24/204): tdh in 9.8% (20/204), trh in 0.5% (1/204), and 1.5% (3/204) presented both genes. In Reloncaví Fjord, V. parahaemolyticus was detected in 14.4% (30/209) of the samples, pathogenic V. parahaemolyticus carrying the trh gene was detected in 0.5% (1/209) of the samples, while the tdh gene was not detected in the samples from this area. The total count of mauve-purple colonies typical of V. parahaemolyticus on CHROMagar was positively associated by multivariate analysis with area, water temperature, and salinity. Similarly, V. parahaemolyticus detection rates by PCR had a positive correlation with the area and water temperature. The chances of detecting total V. parahaemolyticus in the Valdivia River Estuary are significantly higher than in the Reloncaví Fjord, but inversely, during spring-summer months, the interaction factor between the area and temperature indicated that the chances of detecting V. parahaemolyticus are higher in the Reloncaví Fjord. Interestingly, this period coincides with the season when commercial and natural-growing shellfish are harvested. On the other hand, pathogenic V. parahaemolyticus tdh+ was significantly correlated with an increase of water temperature. These environmental parameters could be used to trigger a warning on potential hazard, which would influence human health and economic losses in aquaculture systems.
Revisiting Bayesian autoencoders with MCMC

Autoencoders gained popularity in the deep learning revolution given their ability to compress data and provide dimensionality reduction. Although prominent deep learning methods have been used to enhance autoencoders, the need to provide robust uncertainty quantification remains a challenge. This has been addressed with variational autoencoders so far. Bayesian inference via Markov Chain Monte Carlo (MCMC) sampling methods have faced limitations; however, recent advances in parallel computing and advanced proposal schemes that incorporate gradients have opened routes less travelled. In this paper, we present Bayesian autoencoders powered by MCMC sampling implemented using parallel computing and Langevin-gradient proposal distribution. The proposed Bayesian autoencoder provides similar performance accuracy when compared to related methods from the literature, with the additional feature of robust uncertainty quantification while obtaining a reduced or compressed data representation. This motivates further application of the Bayesian autoencoder framework for other deep learning models.
Effects of Aqueous Extract of Lycopersicum esculentum L. var. “Camone” Tomato on Blood Pressure, Behavior and Brain Susceptibility to Oxidative Stress in Spontaneously Hypertensive Rats

Behavioral disorders affect millions of people worldwide. Hypertension contributes to both the development and progression of brain damage and cognitive dysfunction and could represent the most powerful modifiable risk factor for cerebral vessel dysfunction and consequent behavioral impairment. Tomato contains antioxidants and bioactive molecules that might play an important role in the prevention of cardiovascular and brain diseases. The effects of the combined gel and serum from Lycopersicum esculentum L. var. “Camone” tomatoes and those of purified tomato glycoalkaloids (tomatine) and an antihypertensive drug (captopril) were investigated in male spontaneously hypertensive rats (SHRs) and compared with normotensive Wistar Kyoto (WKY) rats. Body weight, systolic blood pressure, behavioral parameters, as well as brain susceptibility to oxidative stress and brain cytokine contents, were assessed. Treating hypertensive rats with tomato gel/serum or captopril for four weeks caused a significant reduction in blood pressure, decreased locomotor activity and increased grooming behavior; the last two parameters were also significantly affected by tomatine treatment. Brain slices obtained from hypertensive rats treated with tomato gel/serum were more resistant to oxidative stress and contained lower levels of inflammatory cytokines than vehicle-treated ones. In contrast, tomatine treatment had no effect. In conclusion, the tomato-derived gel/serum can be considered a dietary supplement able to drive in vivo blood pressure towards healthier values and also control some central effects such as behavior and brain oxidative stress.
On Margin-Based Cluster Recovery with Oracle Queries

We study an active cluster recovery problem where, given a set of $n$ points and an oracle answering queries like"are these two points in the same cluster? ", the task is to recover exactly all clusters using as few queries as possible. We begin by introducing a simple but general notion of margin between clusters that captures, as special cases, the margins used in previous work, the classic SVM margin, and standard notions of stability for center-based clusterings. Then, under our margin assumptions we design algorithms that, in a variety of settings, recover all clusters exactly using only $O(\log n)$ queries. For the Euclidean case, $\mathbb{R}^m$, we give an algorithm that recovers arbitrary convex clusters, in polynomial time, and with a number of queries that is lower than the best existing algorithm by $\Theta(m^m)$ factors. For general pseudometric spaces, where clusters might not be convex or might not have any notion of shape, we give an algorithm that achieves the $O(\log n)$ query bound, and is provably near-optimal as a function of the packing number of the space. Finally, for clusterings realized by binary concept classes, we give a combinatorial characterization of recoverability with $O(\log n)$ queries, and we show that, for many concept classes in Euclidean spaces, this characterization is equivalent to our margin condition. Our results show a deep connection between cluster margins and active cluster recoverability.