Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional trait and phylogenetic tests of community assembly across spatial scales in an Amazonian forest

Despite a long history of the study of tropical forests, uncertainty about the importance of different ecological processes in shaping tropical tree species distributions persists. Trait- and phylogenetic-based tests of community assembly provide a powerful way to detect community assembly processes but have seldom been applied to the same community. Both methods are well suited to testing how the relative importance of different ecological processes changes with spatial scale. Here we apply both methods to the Yasuni Forest Dynamics Plot, a 25-ha Amazonian forest with >1100 tree species. We found evidence for habitat filtering from both trait and phylogenetic methods from small (25 m2) to intermediate (10 000 m2) spatial scales. Trait-based methods detected even spacing of strategies, a pattern consistent with niche partitioning or enemy-mediated density dependence, at smaller spatial scales (25–400 m2). Simulation modeling of community assembly processes suggests that low statistical power to detect eve.
Declarative and procedural memory functioning in abstinent cocaine abusers.

BACKGROUND We determined the nature and recovery of procedural and declarative memory functioning in a cocaine-abusing cohort in the 45-day period following use. METHODS Thirty-seven cocaine abusers and 27 control subjects were administered the following memory and mood measures: California Verbal Learning Test, recall of the Rey-Osterrieth Complex Figure Test, Pursuit Rotor Task, and Profile of Mood States at 4 visits (within 72 hours of admission and at 10, 21, and 45 days following abstinence). RESULTS Analysis of performance on the Rey-Osterrieth Complex Figure Test revealed that both groups improved in their recall over repeated administrations, though the control group recalled significantly more of the information than cocaine subjects during the 45-day interval. Results for the California Verbal Learning Test indicated improved learning for both subject groups over time, but no group x time interaction. On the Pursuit Rotor Task, cocaine abusers improved their performance at a faster rate than controls at visit 1. At day 45 (visit 4), cocaine abusers again showed improvement on the Pursuit Rotor Task, whereas controls demonstrated a relative plateau in rate of learning. CONCLUSIONS This study documented a lasting detrimental effect on a sensitive nonverbal declarative memory task in cocaine-dependent subjects following abstinence of 45 days. In contrast, abstinence from cocaine during this 45-day period was associated with sustained improvement on a motor learning test in the cocaine abusers relative to controls.
Distinguishing a truncated random permutation from a random function

An oracle chooses a function $f$ from the set of $n$ bits strings to itself, which is either a randomly chosen permutation or a randomly chosen function. When queried by an $n$-bit string $w$, the oracle computes $f(w)$, truncates the $m$ last bits, and returns only the first $n-m$ bits of $f(w)$. How many queries does a querying adversary need to submit in order to distinguish the truncated permutation from a random function? In 1998, Hall et al. showed an algorithm for determining (with high probability) whether or not $f$ is a permutation, using $O(2^{\frac{m+n}{2}})$ queries. They also showed that if $m n/7$, their method gives a weaker bound. In this manuscript, we show how a modification of the method used by Hall et al. can solve the porblem completely. It extends the result to essentially every $m$, showing that $\Omega(2^{\frac{m+n}{2}})$ queries are needed to get a non-negligible distinguishing advantage. We recently became aware that a better bound for the distinguishing advantage, for every $m
A low-power architecture for integrating analog-to-digital converters

This paper reports on a modified architecture for single-slope integrating analog-to-digital converter (ADC) for use in image sensors and biomedical or any other applications where the value of the input analog signal has small and slow variations. In this architecture, instead of digitizing every new analog sample independently, the difference of the new sample with the previous sample is digitized. This idea will therefore considerably reduce the power consumption of the ADC. In order to illustrate the effectiveness of the proposed idea, an 8- bit, 4 kS/s ADC is designed and simulated in a 0. 18µm CMOS technology. The proposed ADC is very power efficient when the input signal is very slow and has a small variation in voltage amplitude. Simulations confirm that the proposed ADC architecture shows more than 80% power saving compared to conventional architecture for an input signal amplitude of 0.2VFS.
Very Long Time Scales and Black Hole Thermal Equilibrium

We estimate the very long time behaviour of correlation functions in the pres- ence of eternal black holes. It was pointed out by Maldacena (2) that their vanishing would lead to a violation of a unitarity-based bound. The value of the bound is obtained from the holographic dual fleld theory. The correlators indeed vanish in a semiclassical bulk approximation. We trace the origin of their vanishing to the continuum energy spectrum in the presence of event horizons. We elaborate on the two very long time scales involved: one associated with the black hole and the other with a thermal gas in the vacuum back- ground. We flnd that assigning a role to the thermal gas background, as suggested in the above work, does restore the compliance with a time-averaged unitarity bound. We also flnd that additional conflgurations are needed to explain the expected time dependence of the Poincare recurrences and their magnitude. It is suggested that, while a semiclassical black hole does reproduce faithfully \coarse grained" properties of the system, additional dynamical features of the horizon may be necessary to resolve a flner grained information- loss problem. In particular, an efiectively formed stretched horizon could yield the desired results.
Chapter 5 Kalman Filtering over Wireless Fading Channels

In this chapter, we consider the estimation of a dynamical sy stem over a wireless fading channel using a Kalman filter. We develop a fr amework for understanding the impact of stochastic communication noise, pac ket drop and the knowledge available on the link qualities on Kalman filtering over fading channels. We consider three cases of “full knowledge”, “no knowledge” an d “partial knowledge”, based on the knowledge available on the communication quali ty. We characterize the dynamics of these scenarios and establish the necessary and sufficient conditions to ensure stability. We then propose new ways of optimi zing the packet drop in order to minimize the average estimation error variance o f the Kalman filter. We consider both adaptive and non-adaptive optimization of th e packet drop. Our results show that considerable performance improvement can b e achieved by using the proposed framework.
Analysis of emergency message dissemination in vehicular networks

Safety-critical applications form the main motivation for intelligent transportation systems. Studying the major concerns in such applications, i.e., delay and reliability, through mathematical analysis is extremely beneficial because it enables us to design optimized schemes. Such analysis is, however, challenging due to the dynamics of such a network. In this paper, we present a mathematical model that bounds the delay of emergency message dissemination in vehicular networks. We make some interesting observations from the presented model. First, the end-to-end reliability has a fairly fast transition over time which we formally prove this observation. The second observation from the analytical model confirms the fact that using the vehicle density on the road is a good metric for setting the right forwarding probability in vehicles. We exploit this conclusion and propose a completely distributed forwarding strategy. Simulation studies indicate that our model does capture the delay characteristics of vehicular networks. It also affirms the effectiveness of our warning dissemination scheme in terms of delay and single-hop reliability. We believe that this is a promising step towards accurate characterization of communication delay and reliability in vehicular networks.
Development and Characterization of Liposomal Doxorubicin Hydrochloride with Palm Oil

The usage of natural products in pharmaceuticals has steadily seen improvements over the last decade, and this study focuses on the utilization of palm oil in formulating liposomal doxorubicin (Dox). The liposomal form of Dox generally minimizes toxicity and enhances target delivery actions. Taking into account the antiproliferative and antioxidant properties of palm oil, the aim of this study is to design and characterize a new liposomal Dox by replacing phosphatidylcholine with 5% and 10% palm oil content. Liposomes were formed using the freeze_thaw method, and Dox was loaded through pH gradient technique and characterized through in vitro and ex vivo terms. Based on TEM images, large lamellar vesicles (LUV) were formed, with sizes of 438 and 453 nm, having polydispersity index of 0.21 ± 0.8 and 0.22 ± 1.3 and zeta potentials of about −31 and −32 mV, respectively. In both formulations, the entrapment efficiency was about 99%, and whole Dox was released through 96 hours in PBS (pH = 7.4) at 37°C. Comparing cytotoxicity and cellular uptake of LUV with CaelyxR on MCF7 and MDA-MBA 231 breast cancer cell lines indicated suitable uptake and lower IC50 of the prepared liposomes.
A Semi-automatic Approach for Labeling Large Amounts of Automated and Non-automated Social Media User Accounts

Automated accounts are used for many purposes in social media, including sending spam, spreading of viruses and conducting psychological operations in political or military conflicts. While several previous attempts have been made to classify bot accounts in the spam domain, there are (to the best of our knowledge) no previous studies on detection of automated accounts in a military information operation context. Traditional machine learning approaches to bot detection rely on manual annotation of training sets from which classifiers can be learnt, which requires a large manual effort. We present a semi automated alternative to manual annotation which significantly reduces the effort and resources needed, and hence speeds up the process of adapting classifiers to new domains. Our application of the method to Twitter data from the Russia-Ukraine conflict and our classification results suggest that good classification performance still can be obtained despite generating training sets semi-automatically rather than using manual annotation.
Two extremely metal-poor emission-line galaxies in the Sloan Digital Sky Survey

We present spectroscopic observations with the 3.6 m ESO telescope of two emission-line galaxies, J2104-0035 and J0113+0052, selected from the Data Release 4 (DR4) of the Sloan Digital Sky Survey (SDSS). From our data we determine the oxygen abundance of these systems to be respectively 12 + log O/H = 7.26 ± 0.03 and 7.17 ± 0.09, making them the two most metal-deficient galaxies found thus far in the SDSS and placing them among the five most metal-deficient emission-line galaxies ever discovered. Their oxygen abundances are close to those of the two most metal-deficient emission-line galaxies known, SBS 0335–052W with 12 + log O/H = 7.12 ± 0.03 and I Zw 18 with 12 + log O/H = 7.17 ± 0.01.
Non-contiguous Processor Allocation Algorithms for Mesh-connected Multicomputers 1

Current processor allocation techniques for highly parallel systems are typically restricted to contiguous allocation strategies for which performance suuers signiicantly due to the inherent problem of fragmentation. As a result, message passing systems have yet to achieve the high utilization levels exhibited by traditional vector supercomputers. We are investigating processor allocation algorithms which lift the restriction on contiguity of processors in order to address the problem of fragmentation. Three non-contiguous processor allocation strategies: Paging allocation, Random allocation and the Multiple Buddy Strategy (MBS) are proposed and studied in this paper. Simulations compare the performance of the non-contiguous strategies with that of several well-known contiguous algorithms. We show that non-contiguous allocation algorithms perform better overall than the contiguous ones, even when message-passing contention is considered. We also present the results of experiments on an Intel Paragon XP/S-15 with 208 nodes that show non-contiguous allocation is feasible with current technologies.
Rank-Index based posteriorgram representation for isolated word recognition

This paper examines recognition performance of approaches using Dynamic Time Warping (DTW) on phonetic and Gaussian posteriorgram templates for isolated spoken word recognition task. The performance is assessed on two parameters: i) recognition accuracy and ii) time taken for execution. It is observed that the approaches using phonetic posteriorgram templates exhibit higher recognition accuracy compared to those using Gaussian posteriorgram templates. However, the execution time in both cases are comparable. Further, the paper proposes a new rank-index based representation of posteriorgram templates based on indices of top components derived from a ranked list of posterior probability values. The rank-index based representation exhibits higher recognition performance compared to the representation based on posterior probability values. However, the time taken in case of former is almost 45 times more than the later on the same isolated word recognition task. The paper also proposes a non-dynamic time warping (non-DTW) based approach for modeling and matching spoken words based on rank-index posteriorgram templates. The proposed approach involves unsupervised segmentation of rank-index posteriorgram templates followed by modeling of the obtained segments. This approach reduces the execution time compared to the approaches using DTW by ~98% on rank-index based representation and ~31% on representation based on posterior probability values, while exhibiting recognition accuracy close to the later in the phonetic posteriorgram case.
Multilingual number image interpreter

India is multilingual country, in India people speak different language, and they also used different ways to write number text. Due to lack of language knowledge, people are not able to read number text from one language to another language. This proposed method solves the problem of reading number text from one language to another language. It is part of Natural Language Processing (NLP). Optical Character is used for separate out number text from image. Perform translation on number text by using rule based approach, so that it will convert number text from one regional language to another regional language. By using speech synthesis, it will give number text in voice form.
Coping with SEUs/SETs in microprocessors by means of low-cost solutions: a comparative study and experimental results

In this paper two lost-cost solutions for providing error detection capabilities to processor-based systems are compared. The effects of SEUs and SETs is studied through simulation-based fault injection which is used to compare the error detection capabilities of a hardware-implemented solution, based on parity code, with that of a software-implemented solution based on source-level code modification. Radiation testing experiments confirmed the obtained results.
Role of progestogen in hormone therapy for postmenopausal women: position statement of The North American Menopause Society.

OBJECTIVE To create an evidence-based position statement regarding the role of progestogen in postmenopausal hormone therapy (estrogen plus a progestogen, or EPT) for the management of menopause-related symptoms. DESIGN NAMS followed the general principles established for evidence-based guidelines to create this document. Clinicians and researchers acknowledged to be experts in the field of postmenopausal hormone therapy were enlisted to review the evidence obtained from the medical literature and develop a position statement for approval by the NAMS Board of Trustees. RESULTS The primary role of progestogen in postmenopausal hormone therapy is endometrial protection. Unopposed estrogen therapy (ET) is associated with a significantly increased risk of endometrial hyperplasia and adenocarcinoma. Adding the appropriate dose and duration of progestogen to ET has been shown to lower that risk to the level found in never-users of ET. The clinical goal of progestogen in EPT is to provide endometrial protection while maintaining estrogen benefits and minimizing progestogen-induced side effects, particularly uterine bleeding. EPT discontinuance correlates with uterine bleeding-women with more days of amenorrhea have higher rates of continuance. All US Food and Drug Administration-approved progestogen formulations will provide endometrial protection if the dose and duration are adequate. Progestogens may diminish the beneficial effects of ET on cardiovascular risk factors. However, no EPT (or ET) regimen should be initiated for the primary or secondary prevention of cardiovascular heart disease. Some progestogens may negatively affect mood. Adding progestogen to ET does not decrease the breast cancer risk, although it does not seem to increase mortality. Progestogen increases mammographic density, which is reversed after discontinuation of use. Progestogen has limited effect on the bone-enhancing action of ET. In general, the side effects of added progestogen are mild, although they may be severe in a small percentage of women. CONCLUSIONS Progestogen should be added to ET for all postmenopausal women with an intact uterus to prevent the elevated risk of estrogen-induced endometrial hyperplasia and adenocarcinoma. There is no consensus on a preferred regimen for all women. By changing the progestogen type, route, or regimen, clinicians can individualize therapy to minimize side effects, especially uterine bleeding, and limit any effects on ET benefits while providing adequate endometrial protection.
Smart Media Pricing (SMP): Non-uniform packet pricing game for wireless multimedia communications

Service Providers (SPs) typically set data price according to flat rate, the time or the usage. However, the importance of multimedia content is different among various packets, and such diversity has largely been ignored in the past. In this paper, we propose a fundamentally new framework named Smart Media Pricing (SMP), to allocate price according to multimedia packet importance in terms of distortion reduction. Specifically, we investigate the profit maximization problem of a network SP (selling video transmission service) and a client device (requesting video sequences). The transmission power and the packet price are allocated non-uniformly among video frames. By deriving game equilibrium, the SP and the client device both can achieve maximum utilities. Simulation results show that the video quality, the energy efficiency, and the social profit are improved significantly compared to traditional uniform data pricing.
Sialophorin, a surface sialoglycoprotein defective in the Wiskott- Aldrich syndrome, is involved in human T lymphocyte proliferation

The mAb L10 was used to determine the distribution and the function of sialophorin, the heavily glycosylated surface molecule that is deficient/defective in lymphocytes of patients with the X-linked immunodeficiency Wiskott-Aldrich syndrome. Dual-parameter FACS analysis indicated that sialophorin is expressed on CD4+ and CD8+ lymphocytes, on a subpopulation of peripheral blood B lymphocytes, on all thymocytes, and on a subpopulation of bone marrow cells. Functional studies demonstrated that L10 mAb stimulates the proliferation of peripheral blood T lymphocytes as measured by stimulation of [3H]thymidine incorporation. The time course and magnitude of increased [3H]thymidine incorporation by T lymphocytes in response to L10 mAb paralleled that induced by anti-CD3 mAb. Effective stimulation was dependent on the presence of monocytes and the Fc portion of L10 mAb. Stimulation of lymphocytes by L10, like stimulation by anti-CD3 mAb, involves increased expression of 4F2, HLA-DR, and IL-2-R. These observations suggest that sialophorin functions in T cell activation.
Forces Generating and Limiting Concentration under Schumpeterian Competition

Stochastic theories of the firm size distribution explain observed size differences among firms as the consequence of random growth rate differences, accumulated over time. Little attention has thus far been paid, however, to economic interpretation of the abstract stochastic processes involved. This paper investigates the implications for size distribution phenomena of a model of industry evolution in which the stochastic elements reflect the uncertainties attending firms' efforts to advance productivity. A simulation experiment establishes that the development of concentration in the model industry is significantly affected by the rate of growth of potential ("latent") productivity, the effectiveness of technological imitation efforts, and the extent to which firms restrain investment in response to perceived market power.
Does naltrexone treatment lead to depression? Findings from a randomized controlled trial in subjects with opioid dependence.

OBJECTIVE Dysphoria and depression have been cited as side effects of the opioid antagonist naltrexone. We aimed to assess whether depressive symptoms are a clinically relevant side effect in a population receiving naltrexone as a treatment for opioid dependence. METHODS We carried out a randomized controlled, open-label trial comparing rapid opiate detoxification under anesthesia and naltrexone treatment with continued methadone maintenance at the Alcohol and Drug Service, Royal Brisbane and Women's Hospital, Brisbane, Australia. The study subjects were patients stabilized on methadone maintenance treatment for heroin dependence who wished to transfer to naltrexone treatment. The Beck Depression Inventory, State-Trait Anxiety Inventory and Opiate Treatment Index subscales for heroin use and social functioning were used at baseline and follow-up assessments at 1, 2, 3 and 6 months. RESULTS Forty-two participants were allocated to receive naltrexone treatment, whereas 38 continued methadone maintenance as the control condition. Participants who received naltrexone did not exhibit worsening of depressive symptoms. In participants attending all follow-up assessments, there was a trend for those receiving naltrexone to exhibit an improvement in depression over time compared with the control group. Participants who were adherent to naltrexone treatment exhibited fewer depressive symptoms than those who were nonadherent. CONCLUSIONS These results suggest that depression need not be considered a common adverse effect of naltrexone treatment or a treatment contraindication and that engaging with or adhering to naltrexone treatment may be associated with fewer depressive symptoms.