Miracle-dz/UniFAR-FTUs huggingface dataset:
Mammal fauna during the Late Pleistocene and Holocene in the far northeast of Europe

The paper summarises materials on the mammal remains in northeastern Europe, dated by radiocarbon. Altogether, 23 local faunas of small mammals and 47 local faunas of large mammals were analysed. Multidimensional statistical analysis shows a strong correlation between changes in small mammal fauna composition and climate changes throughout time. The correlations with the spatial gradients, however, are less pronounced. The faunas are classified into three groups: (1) faunas of Holocene age; (2) Late Pleistocene ‘stadial’ assemblages; and (3) Late Pleistocene ‘interstadial’ assemblages. In some cases, changes in species abundance are better understood in terms of biotic interrelations rather than of climatic effects. The most pronounced change in small mammal fauna composition and structure occurred at the Preboreal/Boreal boundary, and a less conspicuous alteration took place at the LGM/Lateglacial transition. The most noticeable transformation in the large mammal fauna composition is dated to the early Holocene. Less significant changes are observed at the Middle Weichselian/LGM transition and at the LGM/Lateglacial transition. It is safely concluded that variations in the faunas of small and large mammals recorded in NE Europe during the last 35 000 years occurred synchronously and unidirectionally.
Dry sliding tribological behavior of nanocrystalline and conventional polycrystalline copper

Dry sliding tribological behavior of an electro-deposited nanocrystalline Cu (nc Cu) and a conventional coarse-grained Cu (cg Cu) has been investigated using a ball-on-disc tribometer with cemented tungsten carbide ball as the counterface. Experimental results showed that the wear resistance of copper with the nanocrystalline microstructure was enhanced relative to the coarsegrained form. The steady-state friction coefficient of the nc Cu was obviously lower than that of the cg Cu when the load is below 20 N. The wear volume of the nc Cu was always lower than that of the cg Cu for the applied load range from 5 to 40 N. With increase of the load, the difference in wear resistance between the nc and the cg Cu decreased. The enhancement of the wear properties of the nc Cu was associated with the high hardness and the low work-hardening rate of the nanocrystalline structure, and easily being oxidized of wear debris, which was attributed to grain refinement.
Parenting and Psychological Wellbeing of Adolescents-An Intervention Study

Carol Ryff (1988) proposed well being model with six components -Self acceptance, Purpose in life, Personal growth, Positive relation with others, Environmental mastery, Autonomy. Parenting style is a psychological construct representing standard strategies that parents use in their child rearing which influences psychological well being of adolescents. The most consistent predictor of adolescent mental health and well being is the quality of relationship adolescents have with their parents (Resnic et al., 1997). Problems in parenting arise due to lack of skills, so parents can be trained in parenting (life skills training). Life skills training have a significant effect on positive mental health and self esteem of vulnerable adolescents. (Irshad.K.2012). The purpose of the study was to investigate the influence of life skills training given to parents on psychological wellbeing of their adolescent children. Quasi-experimental research design was adopted by the researcher for the study. The students were selected on the basis of simple random technique. The sample consisted of adolescent students in 11 th std (n=60). Psychological wellbeing questionnaire was administered as a screening test. Those adolescents who scored low were selected for the study. They were divided into experimental group (n=30) & control group (n=30). Life skills intervention was given to the parents of experimental group. Life skills questionnaire, psychological wellbeing and parental bonding instrument were the tools used for the study. The data was analyzed with correlation and Independent t-test. Inferences & discussions were made based on the results of the analysis.
Improving Sampling-based Alignment Method for Statistical Machine Translation Tasks

We describe an approach to improve the performance of the sampling-based multilingual alignment method implemented by Anymalign on translation tasks. The idea of the approach is to enforce the alignment of N-grams. We compare the quality of the phrase translation table output by our approach and that of MGIZA++ for statistical machine translation tasks. We improved the performance of Anymalign in the baseline system, but did not beat MGIZA++ as we expected.
The role of adhesion in contact mechanics

Adhesive (e.g. van der Waals) forces were not generally taken into account in contact mechanics until 1971, when Johnson, Kendall and Roberts (JKR) generalized Hertz’ solution for an elastic sphere using an energetic argument which we now recognize to be analogous to that used in linear elastic fracture mechanics. A significant result is that the load–displacement relation exhibits instabilities in which approaching bodies ‘jump in’ to contact, whereas separated bodies ‘jump out’ at a tensile ‘pull-off force’. The JKR approach has since been widely used in other geometries, but at small length scales or for stiffer materials it is found to be less accurate. In conformal contact problems, other instabilities can occur, characterized by the development of regular patterns of regions of large and small traction. All these instabilities result in differences between loading and unloading curves and consequent hysteretic energy losses. Adhesive contact mechanics has become increasingly important in recent years with the focus on soft materials (which generally permit larger areas of the interacting surfaces to come within the range of adhesive forces), nano-devices and the analysis of bio-systems. Applications are found in nature, such as insect attachment forces, in nano-manufacturing, and more generally in industrial systems involving rubber or polymer contacts. In this paper, we review the strengths and limitations of various methods for analysing contact problems involving adhesive tractions, with particular reference to the effect of the inevitable roughness of the contacting surfaces.
Nutritional Value of Four Common Edible Insects in Zambia

Background and Objectives: Insects have played an important part in the history of human nutrition in Africa. The main objective of this research was to assess the nutritional value of four commonly edible insects in Zambia. The insects studied include the caterpillars (Gonimbrasia belina and Gynanisa maja), grasshopper (Ruspolia differens) and winged termites ( Macrotermes falciger). Materials and Methods: The proximate composition and minerals of the insects were determined using standard methods. One way Analysis of Variance (ANOVA) was used in analysing the data. Results: The moisture content of the insects ranged from 4.1% ±0.3 to 9.2%±0.1. The highest amount of crude fat was found in Ruspolia differens with fat content of 49.0 % ±0.1 and the least amount was found in Gonimbrasia belina which had a mean fat content of 10.0 % ± 0.2. The difference in fat content among the insects was statistically significant with P 0.05. However there was a significant difference in protein content between Gonimbrasia belina and the other two insects namely Ruspolia differens and Macrotermes falciger with the P-value <0.05. The insect richer in carbohydrates (32.8 %±0.7) was Macrotermes falciger, while the insect with a least value was Gonimbrasia belina with carbohydrate content of 7.8 % ±0.5. The highest amount of energy of 810.2 kcal/100g was recorded in Macrotermes falciger. The predominant amino acid was glutamic acid (4.35 ± 0.05 - 8.43 ± 0.16g/100g) while the least amino acid was cystein (0.11±0.02 - 0.13±0.05g/100g). Lysine was the most predominant essential amino acid in Gynanisa maja (4.02g/100g), Ruspolia differens (5.74g/100g) and Macrotermes falciger (3.72g/100g), while arginine was the most predominant in Gonimbrasia belina (4.57g/100g). The nutritional content of the insects was generally higher than that found in common meats such as beef and chicken meat and insects were generally cheaper than the common meats. Conclusions: The findings suggest that edible insects have the potential for exploitation to combat nutritional deficiencies that are of public health concern. The insects could form a base for new food products of considerable nutritive value.
Intermittency in electric brain activity in the perception of ambiguous images

Present paper is devoted to the study of intermittency during the perception of bistable Necker cube image being a good example of an ambiguous object, with simultaneous measurement of EEG. Distributions of time interval lengths corresponding to the left-oriented and right-oriented cube perception have been obtain. EEG data have been analyzed using continuous wavelet transform and it was shown that the destruction of alpha rhythm with accompanying generation of high frequency oscillations can serve as a marker of Necker cube recognition process.
Generating High-Quality Landsat Time-Series and Its Applications in Forest Studies

Forest covers about 40 percent of the Earth’s total land surface and is of tremendous ecological and economic value. Spatially explicit knowledge of forest composition and biophysical attributes is very important for monitoring forest development and for informing decisions for sustainable development. Landsat images have been widely used to map forest composition and estimate biophysical attributes but the accuracy is not yet satisfactory. This dissertation seeks to develop new approaches to produce high-quality seasonal Landsat time-series and then classify detailed forest types and model forest aboveground biomass (AGB). First, a new method for removing thick clouds was developed based on a modified neighborhood similar pixel interpolator (NSPI) approach. Second, a new Geostatistical Neighborhood Similar Pixel Interpolator (GNSPI) was developed for gap-filling. After cloud removal and gap filling processes, we can obtain high-quality Landsat time-series data. Third, a hierarchical classification method was proposed to get detailed forest types from dense Landsat time-series to improve forest mapping accuracy. This method integrates a feature selection and an iterative training-sample-adding procedure into a hierarchical classification framework. The proposed method has been tested in Vinton County of southeastern Ohio. The accuracy of these forest types reaches 90%. Last, NDVI time-series derived from six Landsat images across different seasons was used to estimate AGB in southeast Ohio by empirical modeling approaches. Results clearly show that NDVI in the fall season has a stronger correlation to AGB than that in the peak season, and using seasonal NDVI time-series can obtain more accurate AGB estimations and less saturation than using a single NDVI. This study demonstrates the value of multi-seasonal Landsat images for improving forest studies.
Design of Reliable Stochastic Number Generators Using Emerging Devices for Stochastic Computing

Stochastic computing (SC), an unconventional computing paradigm that operates on stochastic bit streams, gains more and more attention recently because of the low area and power consumption of its computing core. SC relies on stochastic number generators (SNGs) to generate input stochastic bit streams. An SNG is composed of a random number source (RNS) and a comparator. However, conventional SNGs, which use linear feedback shift register (LFSR) as the RNS, consume much more area and power than the SC core, offsetting the small area and the low power advantages of the SC core. To mitigate this issue, some emerging devices, such as memristor and spintronic devices, were proposed to build SNGs. However, due to the large process variation in fabricating these devices, these SNGs are unreliable: their output probabilities could have a large error than the desired values. In this paper, we propose a general method to design reliable SNGs that use emerging device-based RNS’s. Experimental results showed that our design is effective in improving the reliability. Keywords—stochastic computing; novel nanoscale devices; stochastic number generator (SNG)
Physiological attributes of banana and plantain cultivars of the Colombian Musaceae Collection

The Colombian Musaceae Collection (CMC) contains 140 banana and plantain cultivars. For this study, twelve cultivars were selected when they were in the initial flowering stage and the physiological attributes of the plants and some components of the bunches were studied. Similar cultivar groups were determined in terms of the evaluated attributes with the use of a multivariate statistical analysis for principal components and grouping analysis. With 89.35% explanation of the total variance by the first five components, the variables fresh weight of the bunches, fresh weight of the fruit, number of fruits, specific leaf area, total dry weight of the plant, dry weight of the corms, and percentage of dry weight of the bunches represented the majority of the differentiation of the cultivars. This study allowed for the evaluation and comparison of the principal promising banana and plantain cultivars for use as basic tools in selection programs of the Musaceae germplasm in terms of agronomic and productive behaviors.
Extended rapidly exploring random tree–based dynamic path planning and replanning for mobile robots

It is necessary for a mobile robot or even a multi-robot team to be able to efficiently plan a path from its starting or current location to a desired goal location. This is a trivial task when the environment is static. However, the operational environment of the robot is rarely static, and it often has many moving obstacles. The robot may encounter one, or many, of these unknown and unpredictable moving obstacles. The robot will need to decide how to proceed when one of these obstacles is obstructing its path. In this article, a new method of dynamic replanning is proposed to allow the robot to efficiently plan a path in such complex environments. Our proposed replanning method is based on an extended rapidly exploring random tree. The robot will modify its current plan when unknown random moving obstacles obstruct the path. We extend the proposed replanning method to multi-robot scenarios in which the ability to share path planning and search tree information is valuable. An efficient method of node sharing is proposed to allow the multi-robot team to quickly develop path plans. Various experimental results in both single and multi-robot scenarios show the effectiveness of the proposed methods.
Genetic Disruption of Ki-67 Results in Decreased Clonogenic Proliferation

Two well-known hallmarks of cancer are the abilities to sustain proliferation and invade surrounding tissue, and pathways involved in these processes have been scrutinized for possible therapeutic targets in recent years. Since its discovery, Ki-67 has been intimately linked to the cell cycle and widely accepted as a marker for the growing fraction of cells in a tumor sample, and more recently its potential as a prognostic and predictive marker for various cancers has been explored. Despite the wide use of Ki-67 in the clinical and pathological setting, little is known about its actual function and role as a potential therapeutic target for cancer. To better characterize Ki-67’s function to optimally exploit this gene/protein for prognostic, predictive, and therapeutic purposes, we created isogenic Ki-67 knockout cells in a “normal” and cancer cell line. Unlike previous efforts to knockdown Ki-67, we were able to generate multiple independent Ki-67 knockout clones in two cell lines that definitively lacked functional full length Ki-67 protein. In colony formation assays in vitro and tumorigenic assays in vivo, the knockout clones displayed a reduced proliferative and clonogenic potential, illustrating how inhibition of Ki-67 could result in a decreased ability of cancer cells to invade and colonize surrounding and distant tissue. A current model of metastasis maintains that cancer stem cells (CSCs) are required to establish tumor formation at distant sites, and in colorectal cancers, those CSCs are often identified by the expression of cell surface markers CD133 and CD44. The knockout clones had a markedly reduced CD133CD44 population of cells compared to the parental cell line, demonstrating that loss of Ki-67 resulted in fewer colonies and tumors by decreasing the “stemness” of the cells. CSCs are known to be resistant to various chemotherapies, but we found that the loss of Ki-67 in the cancer cell line
Comparison of Post-tabular Confidentiality Approaches for Survey Weighted Frequency Tables

One of the most common forms of data release by National Statistical Institutes (NSIs) are frequency tables arising from censuses and surveys and these have been the focus of statistical disclosure limitation (SDL) techniques for decades. With the need to modernize dissemination strategies, NSIs are considering web-based flexible table builders where users can generate their own tables of interest without the need for human intervention. This has caused a shift in the types of disclosure risks of concern under the SDL approaches and a move towards perturbative methods with more formal privacy guarantees for confidentiality protection. We examine three post-tabular confidentiality protection methods to be used in a flexible table builder for generating survey weighted frequency tables: the computer science approach of differential privacy and two SDL approaches of postrandomization and a new technique called drop/add-up-to-q. We demonstrate and compare their application in a simulation study.
90-day Sub-chronic Oral Toxicity Analysis of Antrodia cinnamomea ( “ Niu-chang-chih ” ) Fruiting Body Extract in Rats

Antrodia cinnamomea is considered to improve physical health and traditionally used treat many diseases. In order to ensure that a fruit body extract prepared from A. cinnamomea is safe for long-term consumption, 90-day sub-chronic oral toxicity testing in rats was performed. The test design followed the Organization for Economic Cooperation and Development (OECD) Guideline 408. The dosages tested in this experiment were 1250, 2500 and 5000 mg/kg body weight of the animal for 90 consecutive days and a group administered reverse osmosis water was used as the controls. No rats died during the feeding period in this experiment. The groups administered A. cinnamomea extract showed no significant differences to the controls in terms of body weight increase, food and water consumption, preand post-test ophthalmic examinations, organ to body weight ratios, bloodclotting tests, pathological examination by visual inspection and histopathologic analysis. Urinalysis, hematologic analysis and biochemical analysis demonstrated no treatment-related pathological changes. According to the above experiments and examinations, the no-observed-adverse-effect level (NOAEL) of our A. cinnamomea was determined and the acceptable daily intake (ADI) was estimated.
An Interleaving Scheme for DC-link Current Ripple Reduction in Parallel-Connected Generator Systems

This paper presents an interleaving scheme for parallel-connected power systems to reduce the DC-link current ripple. A paralleled generator system generates current ripple by the Pulse Width Modulation (PWM) of each generator side converter. The current ripple in the DC-link degrades the efficiency of the whole generator system and decreases the lifetime of the DC-link capacitors. To mitigate these issues, the expression of the DC-link current is derived by a double-integral Fourier analysis while considering the modulation schemes. Optimized interleaving angles for the parallel generator system are obtained based on an analysis to minimize the dominant current harmonics component. Finally, the proposed interleaving scheme reduces the RMS value of the DC-link current ripple. Simulation and experimental results verify the effectiveness of the proposed interleaving scheme.
NEURAL NETWORK FOR SOURCE SEPARATION

This paper presents a novel memory-augmented neural network for single-channel source separation. We propose a recall neural network (RCNN) where a couple of external memories are realized for sequence-to-sequence learning based on an encoder and a decoder. These memories are learned in a two-pass sensing procedure where the mixed signal is encoded and then decoded (or recalled) as context vectors by using a bidirectional long short-term memory (LSTM) and a LSTM, respectively. These context vectors are integrated in a gating layer. A set of attention weights are calculated to attend the hidden state of decoder to implement a recurrent neural network for source separation. A gated attention mechanism is carried out to fulfill a specialized memory network. The regression errors due to two passes of sensing procedure and one pass of gated attention are jointly minimized to estimate the weight parameters of different components in different layers. The experiments on multi-speaker speech enhancement show that the proposed RCNN consistently outperforms LSTM and neural Turing machine in different settings.
Effect of Ambiguous Stimuli on the Error Signal 1 Running head : The Effect of Ambiguous Stimuli on the Error Signal in ERP The Effect of Ambiguous Stimuli on the Error Signal in ERP by

The error-related negativity (ERN) is a component of event-related brain potential (ERP) that is expressed when human subjects make errors on certain response tasks. The present study focuses on the impact of perceptual ambiguities on the brain’s error signal, as indicated by the amplitude of the ERN waveform. It is concerned with whether ambiguous stimuli yield a larger or smaller error signal in the ERP than do non-ambiguous stimuli; previous studies have compiled evidence for both scenarios. We hypothesized that error signals associated with nonambiguous stimuli would be greater due to a larger mismatch between correct and actual response representations in the brain. To test this hypothesis, behavioral and EEG data were collected as participants performed a simple choice reaction time task. The results found no significant effect of stimulus ambiguity on ERN amplitude, but revealed a trend in the direction of our hypothesis. Effect of Ambiguous Stimuli on the Error Signal 3 The Effect of Ambiguous Stimuli on the Error Signal in ERP The ability to accurately monitor one’s behavior is essential in order to perform many everyday tasks. Our capacity to learn new skills, avoid adverse scenarios, and behave properly in an array of settings hinges on this ability. While it might seem like a complicated process, the evaluation of behavioral outcomes may begin with a simple brain signal indicating whether a performed action was good or bad. This study serves to investigate the properties of this brain signal elicited upon error commission in a choice reaction time task involving ambiguous and non-ambiguous stimul