Miracle-dz/UniFAR-FTUs huggingface dataset:
Population expansion and genetic structure in Cephalocereus nizandensis (Cactaceae), a microendemic cactus of rocky outcrops of the Tehuantepec basin, Mexico

Background and aims – Cephalocereus nizandensis is a microendemic columnar cactus that grows isolated in xerophytic enclaves associated with rocky outcrops in the Isthmus of Tehuantepec, in the south of Mexico. Its demographic history and genetic structure were assessed to determine the main events that shaped its current restricted distribution. Material and methods – Chloroplast intergenic sequences of 40 individuals and inter simple sequence repeats (ISSRs) of 45 individuals from four isolated populations were used to estimate haplotypic and nucleotide diversity, using expected heterozygosity and the Shannon index. AMOVA, population pairwise FST, and Bayesian clustering analyses were performed to explore the genetic structure. Demographic history was estimated with neutrality tests, mismatch distribution analysis, and Bayesian skyline plots. Phylogenetic relationships and divergence times were determined using a median joining network and a Bayesian molecular clock. Key results – C. nizandensis has a high diversity and moderate genetic differentiation. The lowest elevation locality was found to be the most genetically distinct. The species has undergone a process of population expansion that began 150,000 years ago and has remained without evidence of a population contraction in the transition from the Pleistocene to the Holocene (11,700 years ago). Conclusions – C. nizandensis presents moderate but significant genetic differentiation, which may be due to an early divergence of its populations. Currently observed levels of genetic diversity are the result of historical maintenance of high population sizes and a population expansion approximately in the last 150,000 years, which was sustained independently of the climatic fluctuations of the Early Quaternary, due in part to the stability of the rocky habitat.
Hospital Based Prevalence of SARS-CoV-2 and Clinico-Demographic Profile of COVID-19 Patients: A Study from a Tertiary Care Hospital of North India

Aims: To find out the prevalence, predominant risk factors and various clinico-demographic variables among patients infected with SARS-CoV-2 during the first year of the pandemic. Study Design: Hospital based, cross sectional study. Place and Duration of Study: Postgraduate department of Microbiology, Government Medical College, Srinagar, and associated hospitals, between March 2020 and March 2021. Methodology: Individuals with acute respiratory infection (ILI and SARI), high risk contacts and asymptomatic close contacts of COVID-19 positive patients, hospitalized patients dated for Original Research Article Farhana et al.; JAMMR, 33(14): 126-136, 2021; Article no.JAMMR. 70170 127 surgeries, pregnant women near expected date of deliveries, travellers were screened. A confirmed case of Covid-19 was defined as a positive result on real-time RT-PCR assay of nasopharyngeal and or Oropharyngeal swab specimens. A total of 2,17,665 samples were collected and processed over a period of one year. Results: Out of 2,17,665 samples, 61.3% were males and 38.7% were females, overall mean age was 34.3 years. 24,009 (11%) tested positive for SARS-CoV-2 infection, among them 63.5% were males while 36.5% were females, the mean age observed was 35.3 years. Highest positivity was observed in the age group of 30 – 39 years (22%), followed by 20 -29 years (20.4%), 12 (0.1%). Among positive cases, 19.4% had a history of contact with a lab confirmed case of SARS-CoV-2, 4.3% were HCW’s and 2.6% were pregnant females. 929 (3.9%) patients who tested positive had presented with SARI. Fever was the most common symptom (62%), followed by cough (41%) and fatigue was reported by 37% patients. Comorbidities were present in 23.2% patients, of which Hypertension 10.8% was the most common, followed by COPD 4.9% and Diabetes mellitus 4%. Conclusion: As evident from our study, COVID-19 has a high positivity (11%) in our region, with males twice more likely susceptible than females. High percentages (62%) of people were symptomatic at presentation, while severe disease was seen in only 3.9% patients. Early aggressive testing is essential to decrease the morbidity and mortality rates associated with COVID-19.
INDOOR POSITIONING FOR SMART DEVICES BASED ON SENSOR FUSION WITH PARTICLE FILTER: LOCALIZATION AND MAP UPDATING

With every new generation of smart devices, new sensors are introduced, such as depth camera or UWB sensors. Combined with the rapidly growing number of smart mobile devices, indoor positioning systems (IPS) have seen increasing interest due to numerous indoor location-based services (ILBS) and mobile applications at large. Wi-Fi Received Signal Strength (RSS) based fingerprinting positioning (WF) techniques are popularly used in many IPS as the widespread deployment of IEEE 802.11 WLAN (Wi-Fi) networks, as this technique requires no line-of-sight to the access points (APs), and it is easy to extract Wi-Fi signal from 802.11 networks with smart devices. However, WF techniques have problems with fingerprint variance, i.e., fluctuation of the sensed signal, and efficient map updating due to the frequently changing environment. To address these problems, we propose a novel framework of IPS which uses particle filter to fuse WF and state-of-the-art CNN-based visual localization method to better adapt to changing indoor environment. The suggested system was tested with real-world crowdsourced data collected by multiple devices in an office hallway. The experimental results demonstrate that the system can achieve robust localization at a 0.3~1.5 m mean error (ME) accuracy, and map updating with a 79% correction rate.
Deformation of drops by outer eddies in turbulence

Abstract Drop deformation in fluid flows is investigated as an exchange between the kinetic energy of the fluid and the surface energy of the drop. We show analytically that this energetic exchange is controlled only by the stretching (or compression) of the drop surface by the rate-of-strain tensor. This mechanism is analogous to the stretching of the vorticity field in turbulence. By leveraging the non-local nature of turbulence dynamics, we introduce a new decomposition that isolates the energetic exchange arising from local drop-induced surface effects from the non-local action of turbulent fluctuations. We perform direct numerical simulations of single inertial drops in isotropic turbulence and show that an important contribution to the increments of the surface energy arises from the non-local stretching of the fluid–fluid interface by eddies far from the drop surface (outer eddies). We report that this mechanism is dominant and independent of surface dynamics in a range of Weber numbers in which drop breakup occurs. These findings shed new light on drop deformation and breakup in turbulent flows, and opens the possibility for the improvement and simplification of breakup models.
HUMBO: Bridging Response Generation and Facial Expression Synthesis

Spoken dialogue systems that assist users to solve complex tasks such as movie ticket booking have become an emerging research topic in artificial intelligence and natural language processing areas. With a well-designed dialogue system as an intelligent personal assistant, people can accomplish certain tasks more easily via natural language interactions. Today there are several virtual intelligent assistants in the market; however, most systems only focus on textual or vocal interaction. In this paper, we present HUMBO, a system aiming at generating dialogue responses and simultaneously synthesize corresponding visual expressions on faces for better multimodal interaction. HUMBO can (1) let users determine the appearances of virtual assistants by a single image, and (2) generate coherent emotional utterances and facial expressions on the user-provided image. This is not only a brand new research direction but more importantly, an ultimate step toward more human-like virtual assistants.
Opti-Enc: On the Path to the Optimal Encoder-Decoder for Thermal Image Colorization for Cross Domain Colorized Images

Thermal images can be obtained as either grayscale images or pseudo colored images based on the thermal profile of the object being captured. In this work, we explore what an optimal encoder decoder might look like for creating a thermal-optical fused domain image. We compare the results from several different encoder-decoder structures with different networks to answer this question. This output images obtained from our method provides information of both domains jointly in a colorized image. We call this a cross domain colorized image. We also present a robust registration method for thermal and optical pairs, which can work despite changes in resolution and the make of the thermal imager. Lastly, we present a unique public dataset with registered thermal-visual image pairs containing around 1800 images as a part of this work, collected over a period of 2 years. We compare our results with prior literature, show how our results are different and discuss on some future work that can be explored further in this domain.
A characterization of the Filippov convention

The Filippov convention is widely used in the literature to define vector fields on a discontinuity set of piecewise-continuous vector fields. The aim of this paper is to give a sufficient and necessary condition for an interpolation scheme of piecewise-continuous vector fields to coincide with the Filippov convention. That is, we show that a map from a space of piecewise-continuous vector fields with two components to the space of vector fields coincides with the Filippov convention where the latter can be applied, if it is sufficiently well-behaved as a generalization of continuous vector fields.
A SURVEY OF AN ENHANCED ALGORITHM TO DISCOVER THE FREQUENT ITEMSET FOR ASSOCIATION RULE MINING IN E-COMMERCE

Web mining is the use of information mining strategies to retrieve information from Web content, structure, and usage mining. In a web based business website, e-commerce, e-marketing must assistance buyers in their buy. This requires exact information on the client's preference. This comparison is acquired when the client is visiting an e-shop on the grounds that (s)he leaves an advanced impression that can be utilized to get his/her needs, wants and requests just as to improve web presence. These information can be utilized for information mining to comprehend the e-showcasing and selling measures in a superior manner. This paper presents an examination of Association rule mining calculations (i.e) apriori and FP Growth development dependent on the correlation of the calculation to discover the successive of clients engaged with e-shopping. In the ends, a few thoughts for good e-shopping Practices identified with the purchasing conduct examination of clients are appeared.
High Speed Low Offset Low Kick Back Noise Dynamic Latch Comparator for ADC

: This paper describes the implementation of 10 bit high speed low offset and low kickback noise dynamic latch comparator with preamplifier in 65nm CMOS technology. Dynamic latch comparator which uses a positive feedback mechanism to generate the analog input signal to a full scale digital level. Kick back noise and offset voltage are the parameter which effects its performance, these can be reduced by playing preamplifier before dynamic latch comparator. The simulations of preamplifier based dynamic latch comparator are performed at 6 GHZ maximum clock frequency, with power consumption of 3.24mw at 1.2v supply voltage and offset voltage is reduced to 1.4mv. Monte Carlo simulations are carried out with N no of runs (N=100) where standard deviation and mean values are obtained.
Interplay Between Graph Isomorphism and Earth Mover's Distance in the Query and Communication Worlds

The graph isomorphism distance between two graphs G u and G k is the fraction of entries in the adjacency matrix that has to be changed to make G u isomorphic to G k . We study the problem of estimating, up to a constant additive factor, the graph isomorphism distance between two graphs in the query model. In other words, if G k is a known graph and G u is an unknown graph whose adjacency matrix has to be accessed by querying the entries, what is the query complexity for testing whether the graph isomorphism distance between G u and G k is less than γ 1 or more than γ 2 , where γ 1 and γ 2 are two constants with 0 ≤ γ 1 < γ 2 ≤ 1. It is also called the tolerant property testing of graph isomorphism in the dense graph model. The non-tolerant version (where γ 1 is 0) has been studied by Fischer and Matsliah (SICOMP’08). In this paper, we prove a (interesting) connection between tolerant graph isomorphism testing and tolerant testing of the well studied Earth Mover’s Distance (EMD). We prove that deciding tolerant graph isomorphism is equivalent to deciding tolerant EMD testing between multi-sets in the query setting. Moreover, the reductions between tolerant graph isomorphism and tolerant EMD testing (in query setting) can also be extended directly to work in the two party Alice-Bob communication model (where Alice and Bob have one graph each and they want to solve tolerant graph isomorphism problem by communicating bits), and possibly in other sublinear models as well. Testing tolerant EMD between two probability distributions is equivalent to testing EMD between two multi-sets, where the multiplicity of each element is taken appropriately, and we sample elements from the unknown multi-set with replacement. In this paper, our (main) contribution is to introduce the problem of (tolerant) EMD testing between multi-sets (over Hamming cube) when we get samples from the unknown multi-set without replacement and to show that this variant of tolerant testing of EMD is as hard as tolerant testing of graph isomorphism between two graphs . Thus, while testing of equivalence between distributions is at the heart of the non-tolerant testing of graph isomorphism, we are showing that the estimation of the EMD over a Hamming cube (when we are allowed to sample without replacement) is at the heart of tolerant graph isomorphism. We believe that the introduction of the problem of testing EMD between multi-sets (when we get samples without replacement) opens an entirely new direction in the world of testing properties of distributions.
TRIPHALA: A HERBAL FORMULATION

1 Susan Jose Research Scholar,Dept. of Botany Maharajas College, Ernakulam , India. Abstract Herbal remedies are among the most ancient medicines used in traditional systems of healthcare such as Ayurveda. Triphala, a well-recognized and highly efficacious polyherbal Ayurvedic medicine consisting of fruits of the plant species Emblica officinalis (Amalaki), Terminalia bellerica (Bibhitaki), and Terminalia chebula (Haritaki), is a cornerstone of gastrointestinal and rejuvenative treatment.
Multi-level fuzzy comprehensive evaluation of the influence of reservoir sedimentation based on improved cloud model

The extent of reservoir sedimentation is an important index related to the functional operation of reservoirs. Therefore, it is vital to accurately conduct sedimentary assessment. In this paper, the analytic hierarchy process was used to determine subjective weights, gray correlation analysis and entropy weight method were used to determine objective weights. The combination weights obtained using optimized combination weighting method based on genetic algorithm were more suitable for the comprehensive analysis of the impact of reservoir sedimentation. This was then used to constructed a multi-level fuzzy comprehensive evaluation model based on improved cloud model. A reservoir was selected as the study object, and its sedimentation impact level was evaluated: the numerical characteristics of the stratus cloud of the comment on the impact of the reservoir sedimentation were (0.6372, 0.0664, 0.0795). The results showed that the reservoir sedimentation is considered as severe influence, and the sedimentation has become a major problem that needed to be solved urgently. The results of this paper could provide insight for reservoir research domestically and abroad. Furthermore, it could also enable managers to more accurately grasp the severity of reservoir sedimentation.
Structural Attack (and Repair) of Diffused-Input-Blocked-Output White-Box Cryptography

In some practical enciphering frameworks, operational constraints may require that a secret key be embedded into the cryptographic algorithm. Such implementations are referred to as White-Box Cryptography (WBC). One technique consists of the algorithm’s tabulation specialized for its key, followed by obfuscating the resulting tables. The obfuscation consists of the application of invertible diffusion and confusion layers at the interface between tables so that the analysis of input/output does not provide exploitable information about the concealed key material.Several such protections have been proposed in the past and already cryptanalyzed thanks to a complete WBC scheme analysis. In this article, we study a particular pattern for local protection (which can be leveraged for robust WBC); we formalize it as DIBO (for Diffused-Input-Blocked-Output). This notion has been explored (albeit without having been nicknamed DIBO) in previous works. However, we notice that guidelines to adequately select the invertible diffusion ∅and the blocked bijections B were missing. Therefore, all choices for ∅ and B were assumed as suitable. Actually, we show that most configurations can be attacked, and we even give mathematical proof for the attack. The cryptanalysis tool is the number of zeros in a Walsh-Hadamard spectrum. This “spectral distinguisher” improves on top of the previously known one (Sasdrich, Moradi, Güneysu, at FSE 2016). However, we show that such an attack does not work always (even if it works most of the time). Therefore, on the defense side, we give a straightforward rationale for the WBC implementations to be secure against such spectral attacks: the random diffusion part ∅ shall be selected such that the rank of each restriction to bytes is full. In AES’s case, this seldom happens if ∅ is selected at random as a linear bijection of F322. Thus, specific care shall be taken. Notice that the entropy of the resulting ∅ (suitable for WBC against spectral attacks) is still sufficient to design acceptable WBC schemes.
Uncorrected Proof ) Title : Risk-Taking Behavior Under the Effect of Emotional Stimuli Among Children and Adults Running title : Emotional risk-taking in adults and children

Risk-taking has an important role in human’s life, either positive or negative. Thus, finding a method to control or drive this in a particular way could affect individuals and communities’ health by discouraging negative risks such as reckless driving or encouraging positive risks. Emotion induction is one of the methods that can enhance or reinforce risk-taking according to the perceived emotion. Among the studies which had taken, most of them focus on adolescents’ which is known as the peaked age of risk-taking behavior, while from a developmental learning point of view if there is a way to control or educate people’s behavior childhood could be the best time. Thus, this study along with the introduction of a new risk-taking task, aims to investigate two less studied groups (children and adults) risk-taking behavior, and also their behavioral response after they influence by positive or negative emotional pictures, to test whether these affect their risktaking or not. 21 children and 20 adults participate in this experiment. Their risk-taking behavior is obtained using a new version of game of dice task combined with emotional stimuli. Results show that children have higher tendency to choose riskier options while they affected by positive emotion while adults are more risk-averse after primed by negative emotion. These findings could be helpful for policy makers and tutoring planners to control risk-taking behavior over different ages using priming effect of positive and negative emotions.
Exploring social-ecological trade-offs in fisheries using a coupled food web and human behavior model

Marine fisheries represent a social-ecological system driven by both complex ecological processes and human interactions. Ecosystem-based fisheries management requires an understanding of both the biological and social components, and management failure can occur when either are excluded. Despite the significance of both, most research has focused on characterizing biological uncertainty rather than on better understanding the impacts of human behavior because of the difficulty of incorporating human behavior into simulation models. In this study, we use the fisheries in Narragansett Bay (Rhode Island, USA) as a case study to demonstrate how coupled modeling can be used to represent interactions between the food web and fishers in a social-ecological system. Narragansett Bay holds both a commercial fishery for forage fish, i.e., Atlantic menhaden (Brevoortia tyrannus) and a recreational fishery for their predators, i.e. striped bass (Morone saxatilis) and bluefish (Pomatomus saltatrix). To explore trade-offs between these two fisheries, we created a food web model and then coupled it to a recreational fishers’ behavior model, creating a dynamic socialecological representation of the ecosystem. Fish biomass was projected until 2030 in both the stand-alone food web model and the coupled social-ecological model, with results highlighting how the incorporation of fisher behavior in modeling can lead to changes in the ecosystem. We examined how model outputs varied in response to three attributes: (1) the forage fish commercial harvest scenario, (2) the predatory (piscivorous) fish abundance-catch relationship in the recreational fishery, and (3) the rate at which recreational fishers become discouraged (termed “satisfaction loss”). Higher commercial harvest of forage fish led to lower piscivorous fish biomass but had minimal effects on the number of piscivorous fish caught recreationally or recreational fisher satisfaction. Both the abundancecatch relationship and satisfaction loss rate had notable effects on the fish biomass, the number of fish caught recreationally, and recreational fisher satisfaction. Currently, the lack of spatial and location-specific fisher behavior data limits the predictive use of our model. However, our modeling framework shows that fisher behavior can be successfully incorporated into a coupled social-ecological model through the use of agent-based modeling, and our results highlight that its inclusion can influence ecosystem dynamics. Because fisher decision making and the ecosystem can influence one another, social responses to changing ecosystems should be explicitly integrated into ecosystem modeling to improve ecosystem-based fisheries management efforts.