Miracle-dz/UniFAR-FTUs huggingface dataset:
Review on Computer Aided System Approach for Predictive Diagnosis of Neurological Disease

Neurological conditions in human brain affecting human body’s cognitive function leading to the mental diseases like Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, brain tumor, epilepsy, dementia, headache disorders, neuro infections, stroke and traumatic brain injuries. Alzheimer's disease is an irreversible neurological condition that affects the human body's cognitive functions. A previous diagnosis of Alzheimer's disease will aid in the treatment of the condition. Many mathematical and machine learning models have been used in studies supporting the disease. Magnetic resonance imaging (MRI) is a common method used to diagnose disease clinically. However, because to changes in its MRI samples and their stability in healthy people, it faces certain difficulties in diagnosis. Machine learning algorithms are currently being utilized to assess fundamental brain alterations in magnetic resonance imaging (MRI). Ensemble Learning (EL) also demonstrated its benefits by incorporating many models into the learning system's resilience. By forecasting the sickness, a machine learning system can help solve this problem. This paper presents a review of computer aided system approach for predictive diagnosis of neurological disease.
A Hybrid Machine Learning Technique for Prediction of Heart Diseases

: The heart is significant organ of human body part Heart disease describes a scope of conditions that influence your heart. Machine learning (ML) is the scientific study of algorithms and statistical models that PC systems use to play out a specific task without using unequivocal instructions, depending on patterns and deduction instead. There are various algorithms, which predict the heart disease. Accuracy is a key parameter to judge the algorithm. This paper proposed the hybrid algorithm based on naïve bayes with random forest. Accuracy, classification error, F-measure, Recall and Precision parameters are calculated. 92% accuracy achieved by proposed hybrid algorithm.
Farklı Saklama Sıcaklıklarının Hu Koç Sperm Parametreleri Üzerine Etkisi

: In order to explore the most suitable temperature for the preservation of Hu ram semen at room temperature, the semen samples were placed at 15°C, 20°C, and 25°C respectively. Th e energy metabolism of enzyme activity and triphosphate adenosine (ATP) was detected in the process of preservation. Diff erent parameters such as functional integrity, survival time, reactive oxygen species (ROS) content, superoxide dismutase (SOD) activity, and energy metabolism of adenosine triphosphate (ATP) were detected. Th e results showed that within 2 days of storage, the sperm progressive motility stored at 25°C was the highest. Within 3~5 days of storage, sperm stored at 20°C have the highest progressive motility. Within 6~9 days of storage, the sperm progressive motility stored at 15°C was signifi cantly higher than that of the other groups (P<0.05). Th e eff ective survival time and total survival time of sperm stored at 15°C reached 5.67 d and 18.73 d, respectively, which were signifi cantly higher than those of other groups (P<0.05). On the 1st day of storage, the sperm membrane integrity was signifi cantly higher than that of the other groups (P<0.05). Within 3~5 days of storage, the membrane integrity and acrosome integrity of sperm stored at 15°C and 20°C were signifi cantly higher than the sperm membrane integrity and acrosome integrity stored at 25°C (P<0.05). On the 7 th day of storage, the membrane integrity of sperm stored at 15°C was signifi cantly higher than that of other groups (P<0.05). On the 5 th day of storage, the level of sperm ROS stored at 15°C was signifi cantly lower than that of group 25°C (P<0.05), SOD activity, Catalase enzyme (CAT) activity and ATP content were signifi cantly higher than that of the other groups (P<0.05). Th erefore, compared with 20°C and 25°C, 15ºC was the most suitable temperature for the preservation of Hu ram semen at room temperature.
"Facile Synthesis of Chitosan Nanoparticle with Different Features and Histopathological Ultrastructural Study on The Effect of Its Bio-complex with Bovine Serum Albumin in Mice Liver"

Synthesis with Different Features and Histopathological Ultrastructural Study on The Effect of Its Bio-complex with Bovine Serum Albumin in Mice We have synthesized chitosan nanoparticles (CS-NPs) with different characteristics using ionic gelation method. Results showed that the synthesized CS-NPs with different concentrations of trisodium polyphosphate (TPP) are irregular - spherical shaped with narrow size distribution and high stability. The microporous chitosan was also synthesized with new features characterized with different techniques as SEM, EDX, FTIR and BET. The synthesized microporous chitosan has a surface area and pore volume of 245.571m 2 /g and 0.155cm 3 /g respectively. Its microporous surface is functionalized with carboxyl and amine groups. Histopathological and ultrastructural studies of mice liver were performed using optical and scanning electron microscopy (SEM) by intraperitoneal (IP) injection of male mice to evaluate toxicity of free and BSA-CS-NPs inside the body after three, six and nine days. However, no pathological or illness signs were observed in mice throughout the in vivo experiment with non-significant changes on body and relative weight of liver in compared to the negative control group. In addition, biochemical parameters exhibited a normal functionality of liver after BSA-CS-NPs administration. Accordingly, mild histopathological or ultrastructural alterations were observed in the liver of treated mice in all groups with respect with the negative controls. Activated Kupffer cells and leukocytes were observed due to the synergism of adjuvant effect of CS-NPs and antigenic peptides involved in BSA. Herein, we opened new direction for synthesis of different forms of CS-NPs and providing an obvious insight on histopathological and ultrastructural changes after administration of CS-NPs and its protein bio-complexes.
Tyrosinase Inhibition Ability Provided by Hop Tannins: A Mechanistic Investigation

: The hop is rich in tannins meanwhile used as a conventional additive in beer industry, but 10 other application is limited. This study investigated the tyrosinase inhibition activity of extracted 11 hop tannins and the associated structure-function activity. The tannins were extracted and subjected 12 to a gel permeation chromatography (GPC), a nuclear magnetic resonance (NMR) and an acid-cleav- 13 age coupled HPLC-ESI-MS/MS analysis to obtain the structural information of the tannins. Then tyrosinase inhibition kinetic assays, inductively coupled plasma optical emission spectrometer and 15 antioxidant (ICP-OES), circular dichroism (CD) as well as molecular docking analysis were applied 16 to investigate the inhibition mechanism. Furthermore, the intracellular inhibition ability of hop tan- 17 nins was assessed with B16-F10 cells. The results indicated that, hop tannins were composed of 18 (epi)catechin as extensional units and (epi)gallocatechin as terminal units and can be classified as prodelphenidins. The tyrosinase inhibition assays showed the hop tannin was 6.4 times more effec- tive than hydroquinone, meanwhile it inhibited the tyrosinase through competitive-noncompetitive 21 mixed way. The tannins were found to bind on the surface of tyrosinase via forming hydrogen bonding and consequently changed the secondary structure of tyrosinase. The fluorescence and an- tioxidant assay indicated the tannin had both copper ion chelating and antioxidant ability which may also contribute to the inhibition. The intracellular inhibition analysis showed activity of tyro- 25 sinase were reduced by 66.67% and melanin production were found reduced by 34.50% while 10uM 26 hop tannins were applied. These results indicated that, the hops are not only important in beer 27 industry, the hop tannins can be also applied as whitening agents in cosmetic industry.
2 Applying Positive Psychology to Advance Relationship Science

INTRODUCTION Be it popular culture, age-old wisdom, or rigorous science—most concede that positive relationships are fundamental to what makes life worthwhile. Positive psychology, the scientific pursuit of what makes life worth living, would therefore be a natural home for the systematic study of positive relationships. So how has the field of positive psychology contributed to the science of positive relationships? What is the role of relationships in positive psychology? This chapter sets out to explore these questions. Before we discuss the role of relationships, it is useful to revisit the aims and goals of positive psychology. Positive psychology has been described as the study of the conditions that promote optimal flourishing of people, groups, and institutions (Gable & Haidt, 2005). As such, positive psychology is concerned with evaluating human experience in terms of human assets, rather than liabilities or human shortcomings. At the inception of the positive psychology movement, founding fathers Martin Seligman and Mihaly Csikszentmihalyi aspired to reframe the investigation of human experience away from the model of pathology traditionally found in the psychological sciences, and toward the features of human experience (e.g., hope, creativity, and wisdom) that make life worth living (Seligman & Csikszentmihalyi, 2000). They envisioned positive psychology as a science of well-being and thriving that stood on three pillars: positive states, positive traits, and positive institutions. Positive states were comprised of positive emotions and experiences (e.g., happiness, love). The study of positive traits included empirical examination of character strengths and virtues, such as wisdom,
Innovatics – a new toolbox of skills for innovative production managers

We describe a metaphorical “toolbox” for innovatic s – a new set of skills for managers who specialize in innovation management an d in the study of innovations. We emphasize the importance of quantitative skills, mu ltidisciplinary inspirations and heuristic methods for generatig innovative solutions. Knowled g of organizational behavior is essential to create in the workplace environment co ducive to innovativeness.
UvA-DARE The MediaMill TRECVID 2012 semantic video search engine

In this paper we describe our TRECVID 2012 video retrieval experiments. The MediaMill team participated in four tasks: semantic indexing, multimedia event detection, multimedia event recounting and instance search. The starting point for the MediaMill detection approach is our top-performing bag-of-words system of TRECVID 2008-2011, which uses multiple color SIFT descriptors, averaged and diﬀerence coded into codebooks with spatial pyramids, and kernel-based machine learning. This year our concept detection experiments focus on establishing the inﬂuence of diﬀerence coding, the use of audio features, concept-pair detection using regular concepts, pair detection by spatiotemporal objects, and concept(-pair) detection without annotations. Our event detection and recounting experiments focus on representations using concept detectors. For instance search we study the inﬂuence of spatial veriﬁcation and color invariance. The 2012 edition of the TRECVID benchmark has again been a fruitful participation for the MediaMill team, resulting in the runner-up ranking for concept detection in the semantic indexing task.
Fault Diagnosis of Wind Turbine Double-Fed Induction Generator Based on Multi-Level Fusion and Measurement of Back-to-Back Converter Current Signal

: One of the major faults in Doubly-Fed Induction Generator (DFIG) is the InterTurn Short Circuit (ITSC) fault. This fault leads to an asymmetry between phases and causes problems to the normal state between current lines. Faults diagnosis from non-stationary signals for the Wind Turbine (WT) is difficult. Therefore, the strategy of fault diagnosis must be robust against instability. In this paper, a new intelligent strategy based on multi-level fusion is proposed for diagnosis of DFIG inter-turn stator winding fault. Firstly, to overcome the non-stationary nature of the vibration signals of the WT, empirical mode decomposition (EMD) method is performed in time-frequency domains to extract best fault features from information power sensor and information current sensor. Moreover, a feature evaluation technique is used for the input of the classifier to choose the best subset features. Secondly, Least Squares Wavelet Support Vector Machines (LS-WSVM) classifier is trained to classify fault types based on feature level fusion (FLF) from different sensors. The main parameters of SVM and the kernel function are optimized by Genetic Algorithm (GA). Finally, Dempster-Shafer evidential reasoning (DSER) is used for fusing the GA-LS-WSVM results based on decision level fusion (DLF) of individual classifiers. In order to evaluate the proposed strategy, a DFIG WT test rig is developed. The experimental results show the efficiency of the proposed structure compared to other ITSC fault diagnosis methods. The results show that the classification accuracy of DSER-GA-LS-WSVM is 98.27%.
Anti-inflammatory, Antimicrobial and Cytotoxic Activities of Essential Oil Extracted from Salvia officinalis L.

The aim of the study was to evaluate antimicrobial, antiinflammatory and cytotoxic activities of essential oil extracted from Salvia officinalis using chloroform as the solvent by Soxhlet apparatus. Total phenols and flavonoids were estimated by Folin-Ciocalteu reagent and AlCl 3 reagent methods. The antimicrobial activity was carried out by well diffusion method while the antiinflammatory activity was performed by albumin as well as BSA denaturation inhibition assay method. The cytotoxic activity was carried out on HeLa cell lines by MTT assay method.
Status Signalling with Luxury and Cultural Goods

As the world shifts towards greater consumerism, there is an increasing tendency for individuals to distinguish themselves from the others through the goods that they purchase – which assert the society of their taste and implicit social status. While the pursuit of social status has been well-explored, most studies in this area tend to focus on luxury consumption, limited research investigated the inclusion of cultural goods (books, etiquette classes, etc.) as another signaling tool. The main objective of the paper, therefore, seeks to understand and provide a theoretical grounding for individuals’ choices between the status goods, and its implications for policy formulations and social mobility. The choice to signal status by purchasing either one of the goods is evaluated under two scenarios: when wage-enhancing benefits of cultural goods are not revealed and when they are. Individuals are found to always prefer luxury goods in the first instance, but upon satisfying certain conditions, there is possibility of those endowed with high cultural and social capital to consume cultural goods instead of luxury goods under the second scenario. Given equilibrium choices, the paper proposes policy measures for welfare-maximizing social planner to drive greater consumption of cultural goods, which also has positive impact on intergenerational mobility. While the paper attempts to illustrate the choices made under more realistic settings by relaxing a few assumptions, it mainly serves to lay the groundwork for the incorporation of cultural goods in future analysis of social status signalling.
Research on the Tourism Destination Accessibility: Evidence from China

The research shows, in a broader perspective, that the tourism destination accessibility mainly involves three aspects: transport accessibility, ecological accessibility, and cultural accessibility. But the current literatures are scarce of ecological and cultural accessibility of tourism destination. Technologically, people could go to anywhere on earth, but economically, transport investment is restricted by investment efficiency, and mass tourism means lower transport costs. Ecological accessibility means some destinations could be admitted to while some destinations not under the condition of ecological regulation or natural environment. Cultural accessibility refers to the attitudes to exotic visitors for local residents and local governments.
The Physiology and Application of Lucid Dreaming

: Lucid dreaming provides an opportunity for people to learn more about dreams and sleep, and the study on lucid dreaming is a growing field of research in psychology. The physiology of lucid dreaming contributed to understanding areas like brain connectivity and provided opportunities to reveal mechanisms under cognitive functions such as Metacognition. Lucid dreaming therapy (LTD) might provide an alternative solution to mental disorders such as posttraumatic stress disorders (PTSD). Lucid dreaming also opens more windows in sleep studies where researchers might receive real-time feedback from participants. While there are still debates around lucid dreaming, this is a growing field of research that would contribute to many areas in psychology.
Indonesian plants potentially to be used as the hair growth promoting agent

Traditional hair care using ingredients from plants has been practiced for a long time by local people in many countries, including Indonesia. However, biological-pharmaceutical scientific research has only flourished in the last two decades. This article presents the results of research conducted by students and researchers in Indonesia. There are dozens of types of plants in Indonesia that are known to have the potential to be developed as hair growth-promoting drugs. Even so, there are still many weaknesses in the research process that must be overcome so that the validity of the information on the efficacy of these plants in overcoming the problem of hair loss can be relied on .
Comparing the Effect of Methylphenidate and Anodal tDCS on Inhibitory Control and Working-Memory in Children and Adolescents with Attention Deficit/Hyperactivity Disorder: A Study Protocol for a Randomized, within-Subject Trial

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inappropriate levels of attention, hyperactivity, and impulsivity that interfere with individual functioning. The international guidelines recommend targeting ADHD-related neurochemical brain abnormalities by intervening via drug treatment, such as methylphenidate (MPH), as first choice. Drug treatments are usually associated with a huge amount of cost for families and the healthcare system, suspension for low compliance, poor long-term efficacy, and side effects. Transcranial direct current stimulation (tDCS) has been suggested as a possible noninvasive means to safely manipulate brain activity and, in turn, improve behavior and cognition in developmental ages. Several studies have shown that tDCS has the potential to improve ADHD-related cognitive deficits, but the effect of tDCS compared with MPH has never been evaluated. The aim of the present within-subject, sham-controlled, randomized proof-of-concept study is to demonstrate the positive effect of one-session anodal tDCS analogous to the MPH drug on inhibitory control and working memory in children and adolescents with ADHD. We strongly believe that this study protocol will serve to accelerate research into low-cost, drug-free, feasible interventions for ADHD.
A Study on Intrusion Detection System for IoT Environment Based on Machine Learning

IoT, Internet of Things is now becoming an inevitable part of everyone's life. IoT connects many devices, sensors, applications via wireless or mobile networks to fulfill the required tasks. IoT invests interest in various fields like agriculture, healthcare, smart cities, homes, cars, transportation, etc. Today IoT is being used extensively to lessen the burden of humans. Even though IoT eases human life but also opens to different security challenges. Security must be a priority while across the value chain from the device manufacturers, IoT Service providers, Retailers and consumers. Adopting IoT in a sensitive environment is really a challenging task because of subtle data. This may cause hazards for the nourishment of IoT in the coming days. In light of this, we try to examine the various factors that contribute to the challenges of IoT security. Intrusion Detection System can be used for the security of data as well as devices over the internet. In recent years Machine Learning techniques are applied in the detection of threats in IDS. This research, therefore, focuses on Machine Learning Techniques applied in Internet-of-Things and Intrusion Detection for IoT security. Denial of Service (DoS) is one of the most catastrophic attacks against IoT. In this paper, we investigate the prospects of using machine learning algorithms for securing IoT against DoS attacks.
Planting Density and Geometry Effect on Canopy Development, Forage Yield and Nutritive Value of Sorghum and Annual Legumes Intercropping

Forage sorghum (FS) (Sorghum bicolor L.) is a major forage in crop–livestock production systems. It has low crude protein (CP) and is rich in fiber. Its forage quality can be improved by mixing with legumes rich in CP. Achieving a greater legume contribution to achieve higher CP over monocrops is a challenge for intercropping. Field trials were conducted with lablab (Lablab purpureus L.), pigeon pea (Cajanus cajan L.) and cowpea (Vigna unguiculata), grown with sorghum as mixed 1:1 (sorghum: legumes) and 2:2 (sorghum: legumes) rows. The sorghum plant density was 250,000 and 190,000 plants ha−1. Periodic crop biomass, leaf area index (LAI) and light interception (LI) were measured, together with forage mixture quality at final harvest. The LAI and LI values were greater for lablab and cowpea intercrops in the 1:1 configuration. Legume forage yield contributed up to 10–12% of the total dry matter (DM). A significant improvement in legume biomass was observed for a sorghum population at 190,000 plants ha−1 with paired rows (2:2) of either lablab or cowpea. Sorghum and total forage yields were higher in both 1:1 and 2:2 configurations with 250,000 plants ha−1. The CP concentration of the forage mixture was 62–75 g kg−1 DM. The acid and neutral detergent fibers and the digestibility of the forage mixture were not improved to any great extent. The results suggested that sorghum planted at normal populations with paired rows of lablab or cowpea can improve sorghum–legume intercrop productivity.
Image Sentiment Classiﬁcation Using Latent Correlations Among Visual, Textual

Image sentiment classification has received increasing research attention for several applications including affective image retrieval, opinion mining about social events, product marketing, and healthcare. Most conventional methods focus on the design of visual features, and the use of text associated to the images has not been sufficiently investigated. This paper presents an approach that exploits latent correlations among visual, textual, and sentiment features for image sentiment classification. In the proposed method, we find a latent embedding space in which correlations among the three features are maximized. The projected features in the latent space are used to train a sentiment classifier, which considers the complementary information from different views. Results of experiments conducted on Flickr and Instagram images demonstrate the effectiveness of our approach.