Miracle-dz/UniFAR-FTUs huggingface dataset:
CNS-Antidepressant Activity of Crude Extracts and Different Fractions of Stem Bark of Acacia Nilotica

According to the World Health Report, approximately 450 million people suffer from a mental or behavioral disorder. This amounts of 12.3% of the global burden of disease, and will rise to 15% by 2020. Depression is most prevalent mental disorder and it is recognized to be symptomatically, psychologically and biologically heterogeneous. The crude methanolic extract of Acacia nilotica bark with different soluble partitionates were subjected to investigate for the evaluation of analgesic, hypoglycemic, CNS depressant and antidiarrheal activity on mice and thrombolytic, antihelmentic, antimicrobial, antioxidant along with cytotoxicity different in vivo experiment. The crude methanolic extract of bark of Acacia nilotica were evaluated for antidepressant activity showed insignificant value.
Longitudinal Trajectories and Inter-parental Dynamics of Prairie Vole Biparental Care

For altricial mammalian species, early life social bonds are constructed principally between offspring and their mothers, and the mother-offspring relationship sets the trajectory for offspring bio-behavioral development. In the rare subset of monogamous and biparental species, offspring experience an expanded social network which includes a father. Accordingly, in biparental species fathers also have the potential to influence trajectories of offspring development. Previous semi-natural and laboratory study of one monogamous and biparental species, the prairie vole (Microtus ochrogaster), has given insight into the role that mothers and fathers play in shaping behavioral phenotypes of offspring. Of particular interest is the influence of biparental care in the development of monogamous behavior in offspring. Here, we first briefly review that influence. We then present novel research which describes how parental investment in prairie voles changes across sequential litters of pups, and the extent to which it is coordinated between mothers and fathers. We use approximately 6 years of archival data on prairie vole parenting to investigate trajectories and inter-parent dynamics in prairie vole parenting. We use a series of latent growth models to assess the stability of parental investment across the first 4 l. Our findings suggest that prairie voles display sexually dimorphic patterns of change in parental behavior: mothers’ investment declines linearly whereas fathers’ pattern of change is characterized by initial decline between litters 1 and 2 with subsequent increase from litters 2 to 4. Our findings also support a conclusion that prairie vole paternal care may be better characterized as compensatory—that is, fathers may compensate for decline in maternal investment. Opposing trends in investment between mothers and fathers ultimately imply stability in offspring investment across sequential litters. These findings, combined with previous studies, generate a hypothesis that paternal compensation could play an important role in maintaining the development of monogamous behavioral phenotypes in individual offspring and across cohorts of those offspring. Understanding longitudinal and inter-individual dynamics of complex social behaviors is critical for the informed investigation of both proximate and ultimate mechanisms that may subserve these behaviors.
Multi - Touch in the Air: Device-Free Finger Tracking and Gesture Recognition via COTS RFID

Recently, gesture recognition has gained considerable attention in emerging applications (e.g., AR/VR systems) to provide a better user experience for human-computer interaction. Existing solutions usually recognize the gestures based on wearable sensors or specialized signals (e.g., WiFi, acoustic and visible light), but they are either incurring high energy consumption or susceptible to the ambient environment, which prevents them from efficiently sensing the fine-grained finger movements. In this paper, we present RF-finger, a device-free system based on Commercial-Off-The-Shelf (COTS) RFID, which leverages a tag array on a letter-size paper to sense the fine-grained finger movements performed in front of the paper. Particularly, we focus on two kinds of sensing modes: finger tracking recovers the moving trace of finger writings; multi-touch gesture recognition identifies the multi-touch gestures involving multiple fingers. Specifically, we build a theoretical model to extract the fine-grained reflection feature from the raw RF -signal, which describes the finger influence on the tag array in cm- level resolution. For the finger tracking, we leverage K-Nearest Neighbors (KNN) to pinpoint the finger position relying on the fine-grained reflection features, and obtain a smoothed trace via Kalman filter. Additionally, we construct the reflection image of each multi-touch gesture from the reflection features by regarding the multiple fingers as a whole. Finally, we use a Convolutional Neural Network (CNN) to identify the multi-touch gestures based on the images. Extensive experiments validate that RF -finger can achieve as high as 88% and 92% accuracy for finger tracking and multi-touch gesture recognition, respectively.
Antibacterial activity of daniellia oliveri, lophira alata, and lannea welwitschii against plasmid-carrying enteric pathogens from lagos, nigeria

Aim: Three medicinal plants Daniellia oliveri, Lophira alata and Lannea welwitschii were tested for in vitro antibacterial activity and their plasmid eviction potentials on enteric pathogens. Method: Fresh plant materials collected from herbs seller were sun dried and grounded to fine powder. Water and methanol extracts of these plants were obtained by standard methods. Enteric bacterial agents from clinical samples were used. In-vitro antimicrobial susceptibility testing of the bacterial isolates was carried out using commercial antibiotics and the crude plant extracts by standard procedures. Phytochemical screening of the plant extracts was carried by the standard procedure. Plasmid DNA extraction was performed using the alkaline lyses method. Result: The crude methanol extracts of all the plants were effective on MDR strains of Salmonella enterica serova Typhi, S. Typhimurium, Escherichia. coli, Shigella spp and Klebsiella spp used in this study MIC and MBC values of 0.625 to 10 mcg/ml and 5.0 to 20 mcg/ml respectively were recorded for L. welwitschii,, 10 to 20 mcg/ml and 20 to40 mcg/ml for D. oliveri, and 10 to 20 mcg/ml and 20 to40mcg/ml were recorded for L. alata respectively. The plasmid eviction potentials of the crude plants extracts indicated that only crude extract of L. Welwitschii exerted anti-plasmidic effect on Shigella spp, Klebsiella spp, S. Typhimurium, and S. Typhi , as over 60% of these bacterial strains loss their plasmid DNA. Conclusion: This study revealed that methanol extracts of the three medicinal plants were active against enteric bacterial pathogens. The extracts of L. alata and D. oliveri were not active against MDR pathogens thus; their continuous usage should be discouraged. The methanol crude extract of L. welwitschii exerted antiplasmidic effect on MDR enteric pathogens. This finding suggests possibility of a new approach in drug formulation using anti-plasmidic plant extracts for effective management of plasmid encoded drug resistant enteric bacteria-associated diseases
Design of reduced order disturbance observer of series elastic actuator for robust force control

This paper proposes a new Reduced Order Disturbance OBserver(RODOB) for Series Elastic Actuators (SEAs). The SEAs assess the externally applied force by measuring the spring deformation. To control SEAs, Disturbance OBserver (DOB) has been widely researched to reject nonlinear disturbances and nominalize target plants to nominal models. However, parameter identification of the plant has a complicated process and demands expensive device. To address these identification difficulties, a novel DOB design which is simple and easy to apply is proposed.
Modified aspect/feature based opinion mining for a product ranking system

The extensive and tremendous use of the Internet has led to the trust in word-of-mouth through social networking sites. A product that has best reviews are preferred to the similar kind of product with few favorable reviews. These consumer reviews are rich in knowledge but are unstructured since they are typed by common people using these sites. Aspect/Feature based Opinion Mining is modified in this developed system to help consumers and entrepreneurs in the analysis on these user reviews by determining the strengths and weaknesses of any products. The main motto of the project is ranking the products and its important aspects which would eventually gear up a faster decision-making. The developed system includes four important phases: Pre-processing, Enhanced Aspect Identification and Opinion Word Extraction with modified naïve bayes model, Aspect Polarity Identification, Products and Aspects Ranking in sequence. The developed system will be beneficial for the consumers and business analysts/entrepreneurs who seek customers' online opinions for analyzing purchase decisions and market statistics and strategies.
Self-Adaptive Filtering Algorithm with PCM-Based Memory Storage System

This article proposes a new phase change memory– (PCM) based memory storage architecture with associated self-adaptive data filtering for various embedded devices to support energy efficiency as well as high computing power. In this approach, PCM-based memory storage can be used as working memory and mass storage layers simultaneously, and a self-adaptive data filtering module composed of small DRAM dual buffers was designed to improve unfavorable PCM features, such as asymmetric read/write access latencies and limited endurance and enhance spatial/temporal localities. In particular, the self-adaptive data filtering algorithm enhances data reusability by screening potentially high reusable data and predicting adequate lifetime of those data depending on current victim time decision value. We also propose the possibility that a small amount of DRAM buffer is embedded into mobile processors, keeping this as small as possible for cost effectiveness and energy efficiency. Experimental results show that by exploiting a small amount of DRAM space for dual buffers and using the self-adaptive filtering algorithm to manage them, the proposed system can reduce execution time by a factor of 1.9 compared to the unified conventional model with same the DRAM capacity and can be considered comparable to 1.5× DRAM capacity.
Re: Body weight change is unpredictable after total thyroidectomy

We read with interest the article by Glick et al. assessing predictors for body weight change after total thyroidectomy in 79 patients. They found no predictors and in particular preoperative thyroid status did not predict weight gain after surgery. This observation is in contradiction with a larger study performed by Bel Lassen et al. comparing weight gain after total thyroidectomy for multi-nodular goitre between patients with preoperative euthyroidism (n = 151) and with subclinical hyperthyroidism (n = 74). Body mass index gain was significantly greater in the subclinical hyperthyroid group than in the euthyroid group (1.11 0.17 versus 0.33 0.16 kg/ m; P = 0.003) and in the multivariate analysis, the preoperative serum TSH value was the main predictive factor for the increase in body weight. Methodological factors may explain why TSH or thyroid status did not predict weight change in the study of Glick et al. (1) The low number of patients and the heterogeneity of the preoperative diagnosis: patients with Graves’ disease have probably been treated by antithyroid drugs preoperatively which makes it difficult to interpret thyroid status; patients with a diagnosis of thyroid cancer may have been psychologically affected and may have modified their diet. In our study, we included only patients with benign multi-nodular goitre free of treatment (antithyroid drug or thyroxine). (2) The definition of preoperative hyperthyroidism: TSH <0.3 mU/L is a consensual definition but patients treated with antithyroid drugs means that patients treated with antithyroid drug have been classified as hyperthyroid even with normal TSH value. (3) In the post-operative period, patients have been largely undertreated (mean TSH >5 mU/L). Therefore, we believe that the data presented in the article by Glick et al. do not allow to draw conclusions on possible predictors for weight change after thyroidectomy.
To train or not to train? A survey on training of feature extraction methods for SSVEP-based BCIs

Objective. Despite the vast research aimed at improving the performance of steady-state visually evoked potential (SSVEP)-based brain–computer interfaces (BCIs), several limitations exist that restrict the use of such applications for long-term users in the real-world. One of the main challenges has been to reduce training time while maintaining good BCI performance. In view of this challenge, this survey identifies and compares the different training requirements of feature extraction methods for SSVEP-based BCIs. Approach. This paper reviews the various state-of-the-art SSVEP feature extraction methods that have been developed and are most widely used in the literature. Main results. The main contributions compared to existing reviews are the following: (i) a detailed summary, including a brief mathematical description of each feature extraction algorithm, providing a guide to the basic concepts of the state-of-the-art techniques for SSVEP-based BCIs found in literature; (ii) a categorisation of the training requirements of SSVEP-based methods into three categories, defined as training-free methods, subject-specific and subject-independent training methods; (iii) a comparative review of the training requirements of SSVEP feature extraction methods, providing a reference for future work on SSVEP-based BCIs. Significance. This review highlights the strengths and weaknesses of the three categories of SSVEP training methods. Training-free systems are more practical but their performance is limited due to inter-subject variability resulting from the complex EEG activity. Feature extraction methods that incorporate some training data address this issue and in fact have outperformed training-free methods: subject-specific BCIs are tuned to the individual yielding the best performance at the cost of long, tiring training sessions making these methods unsuitable for everyday use; subject-independent BCIs that make use of training data from various subjects offer a good trade-off between training effort and performance, making these BCIs better suited for practical use.
Study and Sub-System Optimization of Propulsion and Drive Systems for the Large Civil TiltRotor (LCTR2) Rotorcraft

ABSTRACT In a series of study tasks conducted as a part of NASA’s Fundamental Aeronautics Program, Rotary Wing Project, Boeing and Rolls-Royce explored propulsion, drive, and rotor system options for the NASA Large Civil Tilt Rotor (LCTR2) concept vehicle. The original objective of this study was to identify engine and drive system configurations to reduce rotor tip speed during cruise conditions and quantify the associated benefits. Previous NASA studies concluded that reducing rotor speed (from 650 fps hover tip speed) during cruise would reduce vehicle gross weight and fuel burn. Initially, rotor cruise speed ratios of 54% of the hover tip speed were of most interest during operation at cruise air speed of 310 ktas. Interim results were previously reported 1 for cruise tip speed ratios of 100%, 77%, and 54% of the hover tip speed using engine and/or gearbox features to achieve the reduction. Technology levels from commercial off-the-shelf (COTS), through entry-in-service (EIS) dates of 2025 and 2035 were considered to assess the benefits of advanced technology on vehicle gross weight and fuel burn. This technical paper presents the final study results in terms of vehicle sizing and fuel burn as well as Operational and Support (O&S) costs. New vehicle sizing at rotor tip speed reduced to 65% of hover is presented for engine performance with an EIS 2035 fixed geometry variable speed power turbine. LCTR2 is also evaluated for missions range cases of 400, 600, 800, 1000, and 1200 nautical miles and cruise air speeds of 310, 350 and 375 ktas.
Quality-Assured Synchronized Task Assignment in Crowdsourcing

With the rapid development of crowdsourcing platforms that aggregate the intelligence of Internet workers, crowdsourcing has been widely utilized to address problems that require human cognitive abilities. Considering great dynamics of worker arrival and departure, it is of vital importance to design a task assignment scheme to adaptively select the most beneficial tasks for the available workers. In this paper, in order to make the most efficient utilization of the worker labor and balance the accuracy of answers and the overall latency, we a) develop a parameter estimation model that assists in estimating worker expertise, question easiness, and answer confidence; b) propose a quality-assured synchronized task assignment scheme that executes in batches and maximizes the number of potentially completed questions (MCQ) within each batch. We prove that MCQ problem is NP-hard and present two greedy approximation solutions to address the problem. The effectiveness and efficiency of the approximation solutions are further evaluated through extensive experiments on synthetic and real datasets. The experimental results show that the accuracy and the overall latency of the MCQ approaches outperform the existing online task assignment algorithms in the synchronized task assignment scenario.
An early look at the LDBC social network benchmark's business intelligence workload

In this short paper, we provide an early look at the LDBC Social Network Benchmark's Business Intelligence (BI) workload which tests graph data management systems on a graph business analytics workload. Its queries involve complex aggregations and navigations (joins) that touch large data volumes, which is typical in BI workloads, yet they depend heavily on graph functionality such as connectivity tests and path finding. We outline the motivation for this new benchmark, which we derived from many interactions with the graph database industry and its users, and situate it in a scenario of social network analysis. The workload was designed by taking into account technical "chokepoints" identified by database system architects from academia and industry, which we also describe and map to the queries. We present reference implementations in openCypher, PGQL, SPARQL, and SQL, and preliminary results of SNB BI on a number of graph data management systems.
New data on the osteology of some species of Bregmaceros (Teleostei, Gadiformes)

Osteology of four extant species of Bregmacerotidae, Bregmaceros houdei, B. bathymaster, B. japonicus, and B. macclellandi, is described for the first time. The osteological analysis enables the recognition of two groups: (1) B. houdei and B. bathymaster, and (2) B. japonicus and B. macclellandi. Considerable differences in the structure of skull, and pectoral and pelvic girdles among the species indicate the existence of at least two phyletic lines within the genus. Knowledge of the skeleton may be of great importance for the taxonomy of fossil and extant species of Bregmaceros.
Truncated Adenomatous Polyposis Coli Mutation Induces Asef-Activated Golgi Fragmentation

Adenomatous polyposis coli (APC) is a key molecule to maintain cellular homeostasis in colonic epithelium by regulating cell-cell adhesion, cell polarity, and cell migration through activating the APC-stimulated guanine nucleotide-exchange factor (Asef). The APC-activated Asef stimulates the small GTPase, which leads to decreased cell-cell adherence and cell polarity, and enhanced cell migration. ABSTRACT Adenomatous polyposis coli (APC) is a key molecule to maintain cellular homeostasis in colonic epithelium by regulating cell-cell adhesion, cell polarity, and cell migration through activating the APC-stimulated guanine nucleotide-exchange factor (Asef). The APC-activated Asef stimulates the small GTPase, which leads to decreased cell-cell adherence and cell polarity, and enhanced cell migration. In colorectal cancers, while truncated APC constitutively activates Asef and promotes cancer initiation and progression, regulation of Asef by full-length APC is still unclear. Here, we report the autoinhibition mechanism of full-length APC. We found that the armadillo repeats in full-length APC interact with the APC residues 1362 to 1540 (APC-2,3 repeats), and this interaction competes off and inhibits Asef. Deletion of APC-2,3 repeats permits Asef interactions leading to downstream signaling events, including the induction of Golgi fragmentation through the activation of the Asef-ROCK-MLC2. Truncated APC also disrupts protein trafficking and cholesterol homeostasis by inhibition of SREBP2 activity in a Golgi fragmentation-dependent manner. Our study thus uncovers the autoinhibition mechanism of full-length APC and a novel gain of function of truncated APC in regulating Golgi structure, as well as cholesterol homeostasis, which provides a potential target for pharmaceutical intervention against colon cancers.
Phase Margin Oriented Design and Analysis of UDE-Based Controllers Under Actuator Constraints

A loop compensator design for power electronic converters is typically phase margin oriented due to widely varying operation point and actuator delay. The former challenge has been successfully treated recently by uncertainty and disturbance estimator (UDE) based controllers owing to their two-degrees-of-freedom nature, allowing nearly independent tuning of tracking and disturbance rejection performance. On the other hand, actuator-imposed constraints have not been discussed in UDE-related literature by far. It is well known that in order to fully utilize the available control bandwidth, actuator dynamics must be taken into consideration. Consequently, this paper reveals guidelines for UDE-based controllers design considering typical actuator dynamics under phase margin constraint, set a priori. The proposed method is then applied to power control of a multimode bidirectional noninverting buck–boost converter, connecting two dc microgrids. Simulations and experimental results are given to support the revealed findings.
High Step-Up Coupled-Inductor Cascade Boost DC–DC Converter With Lossless Passive Snubber

In this paper, a high step-up coupled-inductor cascade boost dc–dc converter with lossless passive snubber is proposed. Although a conventional cascade boost converter has larger voltage gain compared to a boost converter, it is still not suitable for high step-up voltage conversion. In the proposed converter, a coupled inductor is adopted for the cascaded boost converter to further increase the voltage gain. However, a leakage inductance of the coupled inductor causes a high voltage spike at a main switch. A resistor–capacitor–diode snubber is commonly used to simply solve this problem, but it is also the cause of additional power loss. Therefore, the lossless passive snubber is suggested in this paper in order to prevent efficiency drop by a snubber circuit. In conclusion, the proposed converter has high voltage gain and improved power efficiency. Experimental results from an output 400-V 200-W prototype at a constant switching frequency of 50 kHz are presented to verify the performance of the proposed converter.