Miracle-dz/UniFAR-FTUs huggingface dataset:
Norepinephrine and serotonin imbalance in the locus coeruleus in bipolar disorder.

OBJECTIVES Abnormalities in norepinephrine (NE) and serotonin (5-HT) are implicated in bipolar disorder (BD). We examined 5-HT input and NE neurons in the locus coeruleus (LC, the NE nucleus that innervates the forebrain) in BD by quantifying immunoreactivity (IR) for tyrosine hydroxylase (TH) and tryptophan hydroxylase (TPH), the biosynthetic enzymes for NE and 5-HT, respectively. METHODS Six suicides with BD were compared to matched normal controls and unipolar major depression suicides, using immunocytochemistry with computer-assisted quantification of immunoreactivity. RESULTS Depressed bipolar suicides had 26.7 +/- 1.3% of LC area occupied by the TH immunoreactive (TH-IR) process, while controls had 50.7 +/- 8% (p = 0.002) and unipolar depressed suicides had 50.3 +/- 2.5% (p = 0.003). In bipolars, these processes did not stain as darkly (1.9 +/- 0.5 x background) as controls (2.9 +/- 0.9 x background; p = 0.01) or unipolars (2.9 +/- 0.6 x background; p = 0.002). Bipolar suicides also had less TPH-IR processes in the LC (11.7 +/- 10%) compared with controls (32.8 +/- 8.8%; p = 0.01) or unipolar suicides (30.3 +/- 8%; p = 0.02). The TPH-IR intensity did not differ between groups. CONCLUSIONS We found less TH-IR and TPH-IR in the LC in depressed bipolar suicides, but not unipolar suicides, suggesting that both NE and 5-HT activity is lower in BD. Studies during manic or euthymic states will determine whether these changes are mood state dependent.
Risperidone in Elderly Schizophrenic Patients: An Open-Label Trial.

The authors assessed the safety and efficacy of risperidone in a group of elderly patients with chronic schizophrenia and behavioral disturbances (N = 10). There were no clinically significant changes on physical examination. Also, schizophrenic symptoms and cognitive performance improved during risperidone administration. Patients showed a sufficient improvement in both areas to warrant a larger, double-blind study assessing the effects of risperidone on cognitive and psychiatric symptoms in elderly psychotic patients.
Realtime Recognition of Complex Human Daily Activities Using Human Motion and Location Data

Daily activity recognition is very useful in robot-assisted living systems. In this paper, we proposed a method to recognize complex human daily activities which consist of simultaneous body activities and hand gestures in an indoor environment. A wireless power-aware motion sensor node is developed which consists of a commercial orientation sensor, a wireless communication module, and a power management unit. To recognize complex daily activities, three motion sensor nodes are attached to the right thigh, the waist, and the right hand of a human subject, while an optical motion capture system is used to obtain his/her location information. A three-level dynamic Bayesian network (DBN) is implemented to model the intratemporal and intertemporal constraints among the location, body activity, and hand gesture. The body activity and hand gesture are estimated using a Bayesian filter and a short-time Viterbi algorithm, which reduces the computational complexity and memory usage. We conducted experiments in a mock apartment environment and the obtained results showed the effectiveness and accuracy of our method.
Analysis of Temporal Variation of Soil Salinity during the Growing Season in a Flooded Rice Field of Thessaloniki Plain-Greece

The effects of regional water management practices (WMPs) on the soil salinity of a representative rice field under Mediterranean conditions (Thessaloniki plain, Greece) were investigated. The temporal variation of soil salinity parameters in the soil solution and in the exchangeable phase was monitored at and below the root zone (15–20 and 35–40 cm) during the growing season. The comparative analysis (ANOVA for p = 0.05) of the measurements before and after the growing season showed that: (a) for the soil solution of the 15–20 cm layer, Ca2+, Mg2+, K+, HCO3− and EC were significantly reduced, Na+ remained constant and Cl− increased, while in the 35–40 cm layer no significant differences were detected to all parameters except for Cl− which was increased; (b) for the exchangeable cations Ca2+, Mg2+ and K+ no significant differences were found, while exchangeable Na+ and ESP were significantly increased in both soil layers during the short period of soil drying before harvest. The final values of Na+ and ESP were quite low to indicate soil degradation hazard. Overall the results showed adequate performance of WMPs to preserve a good soil salinity status but with the cost of high water consumption, exceeding 2000 mm.
EdiPulse: Supporting Physical Activity with Chocolate Printed Messages

Designing to support physical activity is a growing field of interest in interaction design. However, existing explorations in this area have mostly focused on using screens to graphically report physical activity data such as heart rate. The use of edible mediums such as 3D printed food for representing such data opens up new possibilities and challenges to push the field forward. Supporting this, we present EdiPulse that 3D prints in chocolates, personalized cheerful messages and emoticons, displaying heart rate data from physical activity session. By varying the thickness of the printed letters and emoticons, the system also supports abstract visualization of the heart rate data, while the printed chocolate incentivizes participation in physical activity. Ultimately, with this work, we aim to inspire and guide design thinking on food printing and edible quantified self representations, which we believe opens up new interaction possibilities to support the physical activity experience.
The Kernel Path in Kernelized LASSO

Kernel methods implicitly map data points from the input space to some feature space where even relatively simple algorithms such as linear methods can deliver very impressive performance. Of crucial importance though is the choice of the kernel function, which determines the mapping between the input space and the feature space. The past few years have seen many efforts in learning either the kernel function or the kernel matrix. In this paper, we study the problem of learning the kernel hyperparameter in the context of the kernelized LASSO regression model. Specifically, we propose a solution path algorithm with respect to the hyperparameter of the kernel function. As the kernel hyperparameter changes its value, the solution path can be traced exactly without having to train the model multiple times. As a result, the optimal solution can be identified efficiently. Some simulation results will be presented to demonstrate the effectiveness of our proposed kernel path algorithm.
The Amygdala and Persistent Pain

A reciprocal relationship exists between persistent pain and negative affective states such as fear, anxiety, and depression. Accumulating evidence points to the amygdala as an important site of such interaction. Whereas a key role of the amygdala in the neuronal mechanisms of emotionality and affective disorders has been well established, the concept of the amygdala as an important contributor to pain and its emotional component is still emerging. This article will review and discuss evidence from anatomical, neuroimaging, behavioral, electrophysiological, pharmacological, and biochemical data that implicate the amygdala in pain modulation and emotional responses to pain. The latero-capsular division of the central nucleus of the amygdala is now defined as the “nociceptive amygdala” and integrates nociceptive information with poly-modal information about the internal and external bodily environment. Dependent on environmental conditions and affective states, the amygdala appears to play a dual facilitatory and inhibitory role in the modulation of pain behavior and nociceptive processing at different levels of the pain neuraxis. Only recently, electrophysiological, pharmacological, and biochemical neuroplastic changes were shown in the nociceptive amygdala in persistent pain. It is conceivable, however, that amygdala plasticity plays an important role in emotional pain behavior and its modulation by affective state.
Generative Benchmark Models for Mesoscale Structures in Multilayer Networks

Multilayer networks allow one to represent diverse and interdependent connectivity patterns --- e.g., time-dependence, multiple subsystems, or both --- that arise in many applications and which are difficult or awkward to incorporate into standard network representations. In the study of multilayer networks, it is important to investigate "mesoscale" (i.e., intermediate-scale) structures, such as dense sets of nodes known as "communities" that are connected sparsely to each other, to discover network features that are not apparent at the microscale or the macroscale. A variety of methods and algorithms are available to identify communities in multilayer networks, but they differ in their definitions and/or assumptions of what constitutes a community, and many scalable algorithms provide approximate solutions with little or no theoretical guarantee on the quality of their approximations. Consequently, it is crucial to develop generative models of networks to use as a common test of community-detection tools. In the present paper, we develop a family of benchmarks for detecting mesoscale structures in multilayer networks by introducing a generative model that can explicitly incorporate dependency structure between layers. Our benchmark provides a standardized set of null models, together with an associated set of principles from which they are derived, for studies of mesoscale structures in multilayer networks. We discuss the parameters and properties of our generative model, and we illustrate its use by comparing a variety of community-detection methods.
Further experiments in phonetic symbolism

Many persons believe that phonetic elements, apart from their function in a particular linguistic context, carry with them certain symbolic connotations. ' The vowels o and u, for instance, are said to be heavier, gloomier, more ponderous than i and e. Although one might extend indefinitely this type of phonetic interpretation, one cannot escape the conviction that normal individuals would tend to disagree considerably in the specific symbolism associated with any vowel or consonant. However true this suspicion of individual difference may be, it does not follow that phonetic sounds in themselves have no consistent symbolic relation outside of their linguistic associations. The two problems are generally confused, and both are branded with the stigma of being unreliably intuitive. The point is stressed because I found, from speaking to a number of the students acting as subjects in this investigation, that their assurance on this matter was at striking variance with their reactions in the experiments. They seemed to feel that the process disclosing the symbolic implications of phonetic elements was in some way a highly variable and arbitrary intuitive association. And this point of view, I am sure, reflects common opinion. But the practical use of this extra-linguistic function of phonetic sounds is familiar enough in literature. The contemporary minor poet, for example, uses great ingenuity in employing this device to gain his effects. This paper is an attempt to study the patterning of phonetic symbolisms on a non-linguistic plane. For this purpose a schedule was devised employing paired nonsense words. The pairs were so arranged that they would be similar in every respect but for the two vowels or consonants that were to be contrasted, e.g. glupa: glopa. The arbitrary meaning "horse"
A perceptual channel for information transfer over kilometer distances: Historical perspective and recent research

For more than 100 years, scientists have attempted to determine the truth or falsity of claims for the existence of a perceptual channel whereby certain individuals are able to perceive and describe remote data not presented to any known sense. This paper presents an outline of the history of scientific inquiry into such so-called paranormal perception and surveys the current state of the art in parapsychological research in the United States and abroad. The nature of this perceptual channel is examined in a series of experiments carried out in the Electronics and Bioengineering Laboratory of Stanford Research Institute. The perceptual modality most extensively investigated is the ability of both experienced subjects and inexperienced volunteers to view, by innate mental processes, remote geographical or technical targets including buildings, roads, and laboratory apparatus. The accumulated data indicate that the phenomenon is not a sensitive function of distance, and Faraday cage shielding does not in any apparent way degrade the quality and accuracy of perception. On the basis of this research, some areas of physics are suggested from which a description or explanation of the phenomenon could be forthcoming.
Coupled Hebbian learning and evolutionary dynamics in a formal model for structural synaptic plasticity

Theoretical models of neuronal function consider different mechanisms through which networks learn, classify and discern inputs. A central focus of these models is to understand how associations are established amongst neurons, in order to predict spiking patterns that are compatible with empirical observations. Although these models have led to major insights and advances, they still do not account for the astonishing velocity with which the brain solves certain problems and what lies behind its creativity, amongst others features. We examine two important components that may crucially aid comprehensive understanding of said neurodynamical processes. First, we argue that once presented with a problem, different putative solutions are generated in parallel by different groups or local neuronal complexes, with the subsequent stabilization and spread of the best solutions. Using mathematical models we show that this mechanism accelerates finding the right solutions. This formalism is analogous to standard replicator-mutator models of evolution where mutation is analogous to the probability of neuron state switching (on/off). The second factor that we incorporate is structural synaptic plasticity, i.e. the making of new and disbanding of old synapses, which we apply as a dynamical reorganization of synaptic connections. We show that Hebbian learning alone does not suffice to reach optimal solutions. However, combining it with parallel evaluation and structural plasticity opens up possibilities for efficient problem solving. In the resulting networks, topologies converge to subsets of fully connected components. Imposing costs on synapses reduces the connectivity, although the number of connected components remains robust. The average lifetime of synapses is longer for connections that are established early, and diminishes with synaptic cost.
Divided We Govern? A Reassessment

The defining characteristic of American politics in the post-World War II era is the dominance of divided partisan control of American political institutions. Congress and the presidency have been controlled, in some combination, by different political parties for twenty-eight of the last forty-six years. And, in the last twenty years, the presidency, the House and the Senate have been controlled by the same party for only four
Macroeconomic Variables and the Demand for Life Insurance in Malaysia

Economic environments have a profound effect on the growth of the insurance industry. History has shown that, although the performance of the insurance industry is closely linked to economic conditions, the life business has been able to survive in different economic environments. In Malaysia, the performance of the insurance industry in 1998 was affected by an economic downturn. The insurance industry as a whole and the nonlife business experienced a negative growth rate but the life business achieved a low, positive growth rate in 1998. Because the macroeconomic environment has an important influence on life business and this area has not been greatly researched in Malaysia, this study is undertaken to examine the demand for life insurance in Malaysia from a macroeconomic perspective. More formally, work is carried out in order to study the interaction between macroeconomic and demographic variables (i.e. financial development, income, inflation, interest rate, price, stock market return, birth rate, death rate, fertility rate and life expectancy) and the demand for life insurance (by sums insured) in order to seek evidence of their relationship in the context of Malaysia. The major findings of this study indicate that the savings deposits rate and price change in insurance are two important macroeconomic variables associated with the demand for life insurance in Malaysia. However, the finding on the savings deposits rate fails to show the expected negative sign. Further research is needed in this respect in order to confirm the relationship between these two variables. A change in the price of insurance has a significant negative relationship with the demand for life insurance. This finding has an important implication on policy formulation for the policy makers of the central bank and the marketing directors of life insurance companies. This finding may be helpful to them in developing pricing strategies to achieve a specific sales target for life business.
Use of “MGE Enhancers” for Labeling and Selection of Embryonic Stem Cell-Derived Medial Ganglionic Eminence (MGE) Progenitors and Neurons

The medial ganglionic eminence (MGE) is an embryonic forebrain structure that generates the majority of cortical interneurons. MGE transplantation into specific regions of the postnatal central nervous system modifies circuit function and improves deficits in mouse models of epilepsy, Parkinson's disease, pain, and phencyclidine-induced cognitive deficits. Herein, we describe approaches to generate MGE-like progenitor cells from mouse embryonic stem (ES) cells. Using a modified embryoid body method, we provided gene expression evidence that mouse ES-derived Lhx6+ cells closely resemble immature interneurons generated from authentic MGE-derived Lhx6+ cells. We hypothesized that enhancers that are active in the mouse MGE would be useful tools in detecting when ES cells differentiate into MGE cells. Here we demonstrate the utility of enhancer elements [422 (DlxI12b), Lhx6, 692, 1056, and 1538] as tools to mark MGE-like cells in ES cell differentiation experiments. We found that enhancers DlxI12b, 692, and 1538 are active in Lhx6-GFP+ cells, while enhancer 1056 is active in Olig2+ cells. These data demonstrate unique techniques to follow and purify MGE-like derivatives from ES cells, including GABAergic cortical interneurons and oligodendrocytes, for use in stem cell-based therapeutic assays and treatments.
Vascular endothelial growth factor and angiopoietin in liver regeneration.

Liver architecture remodeling following partial hepatectomy (PHx) involves the formation of a complex network of liver sinusoids through which the blood flows. The present study examines the involvement of vascular endothelial growth factor (VEGF) and angiopoietin-1 (ang-1) during liver regeneration. Following PHx, VEGF and ang-1 mRNA levels increase, followed by gradual return to baseline levels. RT-PCR analysis of VEGF mRNA reveals three isoforms, VEGF120, VEGF164 and VEGF188. Of the three, VEGF188 is the predominant isoform, VEGF120 being the less abundant. Although VEGF mRNA fluctuates following PHx, the relative expression of each isoform remains the same throughout the recovery process. The level of neuropilin-1, an accessory receptor of VEGF to main receptor corresponds with that of VEGF and ang-1. We have previously demonstrated the capacity of exogenous VEGF165 to stimulate liver cell proliferation following PHx. We now report similar effect using VEGF121, further demonstrating the benefit of manipulating growth factors where such an intervention is required.
Stand-Alone Intelligent Voice Recognition System

In this paper, an expert system for security based on biometric human features that can be obtained without any contact with the registering sensor is presented. These features are extracted from human’s voice, so the system is called Voice Recognition System (VRS). The proposed system consists of a combination of three stages: signal pre-processing, features extraction by using Wavelet Packet Transform (WPT) and features matching by using Artificial Neural Networks (ANNs). The features vectors are formed after two steps: firstly, decomposing the speech signal at level 7 with Daubechies 20-tap (db20), secondly, the energy corresponding to each WPT node is calculated which collected to form a features vector. One hundred twenty eight features vector for each speaker was fed to the Feed Forward Back-propagation Neural Network (FFBPNN). The data used in this paper are drawn from the English Language Speech Database for Speaker Recognition (ELSDSR) database which composes of audio files for training and other files for testing. The performance of the proposed system is evaluated by using the test files. Our results showed that the rate of correct recognition of the proposed system is about 100% for training files and 95.7% for one testing file for each speaker from the ELSDSR database. The proposed method showed efficiency results were better than the well-known Mel Frequency Cepstral Coefficient (MFCC) and the Zak transform.
Colorectal Cancer and the Preventive Effects of Food Components

Although the positive effects of these nutrients have been shown in in vitro studies, it is still difficult to apply the effects of these nutrients in in vivo studies, due to modifications to foods during the process of absorption and delivery within the body. There might be two possible active sites, where foods and their components affect colon epithelium cells, where nutrients are distributed hematogenously after absorption, or retained in the lumen without absorption. Absorbed foods and nutrients might show the effects of anti-inflammation, antioxidant, and anti-proliferative par hematogenously in cancer epithelial cells and stromal cells, while on the other hand, the regulation of enterobacteria might be provided by the component in a poorly-absorbed form. Recent studies have focused on resistant carbohydrates functioning as prebiotics that prevent colorectal cancer (Davis & Milner, 2009).
Evaluating Sentiment Analysis Methods and Identifying Scope of Negation in Newspaper Articles

Automatic detection of linguistic negation in free text is a demanding need for many text processing applications including Sentiment Analysis. Our system uses online news archives from two different resources namely NDTV and The Hindu. While dealing with news articles, we performed three subtasks namely identifying the target; separation of good and bad news content from the good and bad sentiment expressed on the target and analysis of clearly marked opinion that is expressed explicitly, not needing interpretation or the use of world knowledge. In this paper, our main focus was on evaluating and comparing three sentiment analysis methods (two machine learning based and one lexical based) and also identifying the scope of negation in news articles for two political parties namely BJP and UPA by using three existing methodologies. They were Rest of the Sentence (RoS), Fixed Window Length (FWL) and Dependency Analysis (DA). Among the sentiment methods the best F-measure was SVM with the values 0.688 and 0.657 for BJP and UPA respectively. On the other hand, the F measures for RoS, FWL and DA were 0.58, 0.69 and 0.75 respectively. We observed that DA was performing better than the other two. Among 1675 sentences in the corpus, according to annotator I, 1,137 were positive and 538 were negative whereas according to annotator II, 1,130 were positive and 545 were negative. Further we also identified the score of each sentence and calculated the accuracy on the basis of average score of both the annotators.