Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Use of Artificial Neural Networks for the Simulation of Hybrid Solar Collectors

Abstract In the last decade, Artificial Neural Networks (ANNs) have been receiving an increasing attention for simulating engineering systems due to some interesting characteristics such as learning capability, fault tolerance, speed and nonlinearity. This article describes an alternative approach to assess two types of hybrid solar collector/heat pipe systems (plate heat pipe type and tube heat pipe type) using ANNs. Multiple Layer Perceptrons (MLPs) and Radial Basis Networks (RBFs) were considered. The networks were trained using results from mathematical models generated by Monte Carlo simulation. The mathematical models were based on energy balances and resulted in a system of nonlinear equations. The solution of the models was very sensitive to initial estimates, and convergence was not obtained under certain conditions. Between the two neural models, MLPs performed slightly better than RBFs. It can be concluded that similar configurations were adequate for both collector systems. It was found that ANNs simulated both collector efficiency and heat output with high accuracy when “unseen” data were presented to the networks. An important advantage of a trained ANN over the mathematical models is that convergence is not an issue and the result is obtained almost instantaneously. #Contributed by the Organizing Committee for the First International Exergy, Energy and Environment Symposium (IEEES-1). Paper presented at IEEES-1, Izmir, Turkey, 13-17 July 2003. Manuscript received by IJGE on 2003-12-04; final revision received on 2004-02-17. Corresponding guest editors: I. Dincer and A. Hepbasli.
RELAXATION INDUCED BY MICROWAVE RESONANCE THERAPY : EEG CORRELATES

Microwave Resonance Therapy (MRT) as a novel medical treatment represents a synthesis of the ancient Chinese traditional knowledge in medicine (acupuncture) and recent breakthroughs in biophysics. Affecting the appropriate acupuncture points by the generator of high frequency microwaves (52-78 GHz), significant clinical results of the treatment are being achieved. In this paper the EEG correlates of the MRT effects on psychophysical relaxation are evaluated within a group of 28 adults. Upon the MRT application, a few-percentage decrease in the EEG power is observed in most subjects  suggesting some relaxation MRT effect. Such a tendency is particularly significant in the theta frequency band (4-8 Hz), which might be related to the resonance sensitivity of the acupuncture system in this ultralowfrequency (ULF) region.
Circuit to Construct Mapping: A Mathematical Tool for Assisting the Diagnosis and Treatment in Major Depressive Disorder

Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of “constructs” as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning – cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD.
Dealing with Class Imbalance using Thresholding

We propose thresholding as an approach to deal with class imbalance. We define the concept of thresholding as a process of determining a decision boundary in the presence of a tunable parameter. The threshold is the maximum value of this tunable parameter where the conditions of a certain decision are satisfied. We show that thresholding is applicable not only for linear classifiers but also for non-linear classifiers. We show that this is the implicit assumption for many approaches to deal with class imbalance in linear classifiers. We then extend this paradigm beyond linear classification and show how non-linear classification can be dealt with under this umbrella framework of thresholding. The proposed method can be used for outlier detection in many real-life scenarios like in manufacturing. In advanced manufacturing units, where the manufacturing process has matured over time, the number of instances (or parts) of the product that need to be rejected (based on a strict regime of quality tests) becomes relatively rare and are defined as outliers. How to detect these rare parts or outliers beforehand? How to detect combination of conditions leading to these outliers? These are the questions motivating our research. This paper focuses on prediction of outliers and conditions leading to outliers using classification. We address the problem of outlier detection using classification. The classes are good parts (those passing the quality tests) and bad parts (those failing the quality tests and can be considered as outliers). The rarity of outliers transforms this problem into a class-imbalanced classification problem.
Steps toward better debugging tools for LISP

Although contemporary Lisp systems are renown for their excellent debugging facilities, better debugging tools are still urgently needed. A basic flaw with the tools found in most implementations is that they are oriented towards inspection of specific pieces of program or data. and they offer little help in the process of localizing bugs within a large body of code. Among conventional tools, a stepper is the best aid for visualizing the operation of a procedure in such a way that a bug can be found without prior knowledge of its location. But steppers have not been popular, largely because they are often too verbose and difficult to control. In this paper, we present a new stepper for Lisp, Zstep. which integrates a stepper with a real-time full-screen text editor to display programs and data. Zstep presents evaluation of a Lisp expression by visually replacing the expression by its value, conforming to an intuitive model of evaluation as a substitution process. The control structure of Zstep allows a user to “zoom in” on a bug. examining the program first at a very coarse level of detail, then at increasingly finer level until the bug is located. Zstep keeps a history of evaluations, and can be run either forward or backward. Zstep borrows several techniques from the author's example-oriented programming environment. Tinker. including a novel approach to handling error conditions.
A Novel Checkpoint and RPA Inhibitory Pathway Regulated by Rif1

Cells accumulate single-stranded DNA (ssDNA) when telomere capping, DNA replication, or DNA repair is impeded. This accumulation leads to cell cycle arrest through activating the DNA–damage checkpoints involved in cancer protection. Hence, ssDNA accumulation could be an anti-cancer mechanism. However, ssDNA has to accumulate above a certain threshold to activate checkpoints. What determines this checkpoint-activation threshold is an important, yet unanswered question. Here we identify Rif1 (Rap1-Interacting Factor 1) as a threshold-setter. Following telomere uncapping, we show that budding yeast Rif1 has unprecedented effects for a protein, inhibiting the recruitment of checkpoint proteins and RPA (Replication Protein A) to damaged chromosome regions, without significantly affecting the accumulation of ssDNA at those regions. Using chromatin immuno-precipitation, we provide evidence that Rif1 acts as a molecular “band-aid” for ssDNA lesions, associating with DNA damage independently of Rap1. In consequence, small or incipient lesions are protected from RPA and checkpoint proteins. When longer stretches of ssDNA are generated, they extend beyond the junction-proximal Rif1-protected regions. In consequence, the damage is detected and checkpoint signals are fired, resulting in cell cycle arrest. However, increased Rif1 expression raises the checkpoint-activation threshold to the point it simulates a checkpoint knockout and can also terminate a checkpoint arrest, despite persistent telomere deficiency. Our work has important implications for understanding the checkpoint and RPA–dependent DNA–damage responses in eukaryotic cells.
A Layer 2 Wired-Wireless Interworking Model to Achieve Throughput Improvement

Convergence of Internet Protocol based networks is a necessary requirement today. One important aspect of convergence is seamless integration of wired- wireless network. Internetworking of wired-wireless network is important from Quality of Service (QoS) perspective. Providing a wired network support to an overloaded wireless network for load sharing, improves its bandwidth and subsequently its throughput. This results in achieving better QoS. But allowing wireless nodes to freely switch from wireless to wire network has been difficult to achieve due to the reason that the topology of network is affected. This paper attempts to resolve the issue of breach of network topology integrity in an internetworking scenario. A mathematical model to represent the interworking architecture which preserves network topology has been proposed in this paper. Simulation results derived through the implementation of the proposed model show the high reduction of load on the wireless network by providing a wired network support.
FREE AND FOCUSED ATTENTION IN YOUNG AND AGED LISTENERS USING RANDOMIZED DICHOTIC DIGITS TEST

Background and Aim: Aging is associated with reduced cognitive abilities including attention and memory. There is some evidence that shows randomized dichotic digits test (RDDT) has enough d ifficulty to show the ear asymmetry in dichotic listening. This study aimed to compare the effect of free and focused attention on dichotic listening ability of young and elderly listeners . Methods: The cross - sectional comparative study was performed on fi fty right - handed young (18 - 25 years old) and fifty right - handed aged (60 - 80 years old) with equal gender ratio. Recognition performance of right and left ears were compared in free and focused attention conditions . Results: In the free attention condition, mean percent correct of right and left ears of aged group (83.1 and 61.5 respectively) was significantly lower than the scores of the young group (92.8 and 84.3 respectively with p<0.001). In focused attention to right, there was no statistically signific ant difference between mean of performance of the two age groups (p=0.407); however, aged group obtained significantly lower mean score in focused attention to left ear (p<0.05 .( Conclusion: Random presentation of one - , two and three - pair of dichotic digi ts resulted in diminished performance of both ear of aged group in free attention and left ear performance in focused attention conditions. Lower score of aged group in randomized dichotic digits test can be better explained by combinatory (structural and attentional) model of dichotic listening.
Regulators of Trypanosoma brucei Cell Cycle Progression and Differentiation Identified Using a Kinome-Wide RNAi Screen

The African trypanosome, Trypanosoma brucei, maintains an integral link between cell cycle regulation and differentiation during its intricate life cycle. Whilst extensive changes in phosphorylation have been documented between the mammalian bloodstream form and the insect procyclic form, relatively little is known about the parasite's protein kinases (PKs) involved in the control of cellular proliferation and differentiation. To address this, a T. brucei kinome-wide RNAi cell line library was generated, allowing independent inducible knockdown of each of the parasite's 190 predicted protein kinases. Screening of this library using a cell viability assay identified ≥42 PKs that are required for normal bloodstream form proliferation in culture. A secondary screen identified 24 PKs whose RNAi-mediated depletion resulted in a variety of cell cycle defects including in G1/S, kinetoplast replication/segregation, mitosis and cytokinesis, 15 of which are novel cell cycle regulators. A further screen identified for the first time two PKs, named repressor of differentiation kinase (RDK1 and RDK2), depletion of which promoted bloodstream to procyclic form differentiation. RDK1 is a membrane-associated STE11-like PK, whilst RDK2 is a NEK PK that is essential for parasite proliferation. RDK1 acts in conjunction with the PTP1/PIP39 phosphatase cascade to block uncontrolled bloodstream to procyclic form differentiation, whilst RDK2 is a PK whose depletion efficiently induces differentiation in the absence of known triggers. Thus, the RNAi kinome library provides a valuable asset for functional analysis of cell signalling pathways in African trypanosomes as well as drug target identification and validation.
Chronic Stress Increases the Plasmalemmal Distribution of the Norepinephrine Transporter and the Coexpression of Tyrosine Hydroxylase in Norepinephrine Axons in the Prefrontal Cortex

Norepinephrine (NE) potently modulates the cognitive and affective functions of the prefrontal cortex (PFC). Deficits in NE transmission are implicated in psychiatric disorders, and antidepressant drugs that block the NE transporter (NET) effectively treat these conditions. Our initial ultrastructural studies of the rat PFC revealed that most NE axons (85–90%) express NET primarily within the cytoplasm and lack detectable levels of the synthetic enzyme tyrosine hydroxylase (TH). In contrast, the remaining 10–15% of PFC NE axons exhibit predominantly plasmalemmal NET and evident TH immunoreactivity. These unusual characteristics suggest that most PFC NE axons have an unrecognized, latent capacity to enhance the synthesis and recovery of transmitter. In the present study, we used dual-labeling immunocytochemistry and electron microscopy to examine whether chronic cold stress, a paradigm that persistently increases NE activity, would trigger cellular changes consistent with this hypothesis. After chronic stress, neither the number of profiles exhibiting NET labeling nor their size was changed. However, the proportion of plasmalemmal NET nearly doubled from 29% in control animals to 51% in stressed rats. Moreover, the expression of detectable TH in NET-labeled axons increased from only 13% of profiles in control rats to 32% of profiles in stressed animals. Despite the consistency of these findings, the magnitude of the changes varied across individual rats. These data represent the first demonstration of activity-dependent trafficking of NET and expression of TH under physiological conditions and have important implications for understanding the pathophysiology and treatment of stress-related affective disorders.
Essential Principles toward Success: Best Practices of the Bellwether Programs

Leading an institution toward success is not an easy job. Community college leaders, in particular, often face challenges in meeting the diverse demands from their constituencies. Commitment in three essential principles, including being mission driven, practicing adaptability in alignment with that mission, and perpetuating strategic partnerships, has successfully guided institutions in situating themselves in the complex environment of higher education (Hendrickson, Lane, Harris, & Dorman, 2013). The special issue Essential Principles toward Success is an edited collection of case studies on leading programs in the community college sector. By introducing these programs in great detail, we aim to explore how the three essential principles are implemented in practice to solve critical issues in various areas. This edited collection is also unique in sharing best practices of the Bellwether programs. The Bellwether Awards are an integral part of the Community College Futures Assembly, which was established in 1995 and annually recognizes outstanding and innovative programs and practices that are leading community colleges into the future. The Assembly is sponsored by the Institute of Higher Education at the University of Florida and focuses on cutting-edge, trendsetting programs that other colleges might find worthy of replicating. Each year, about 1,000 nominations are received and the nominated colleges are invited to apply and compete for the Bellwether Awards in three categories: Instructional Programs and Services (IPS), Planning, Governance, and Finance (PGF), and Workforce Development (WD). Ten Bellwether finalists and one Bellwether Award winner are competitively selected by a national panel of judges from the cosponsors of each of the award categories. While the nominated programs are categorized into different institutional activities including supporting teaching and learning, improving efficiency and effectiveness, and promoting community and economic development, each program is closely tied to the three essential principles of institutional success. By analyzing the context, resources, and objectives of the program, we hope the readers will find resonance and inspiration in bringing these outstanding and innovative initiatives to their own institutions. Articles selected for this special issue are organized by the three essential principles, and each case study addresses best practice toward community college success.
Opinion mining on Indian newspaper quotations

Opinion Mining is the task of extracting opinions from a sentence on an instance. In this paper, we have collected the quotations from websites of three popular newspaper dailies of India - The Hindu, The Times of India and Deccan Chronicle on an instance. We have proposed a methodology to annotate, label and calculate subjectivity and objectivity of quotations. Using Supervised Learning Classifiers such as Naive Bayes and Support Vector Machine (SVMs) we have classified the subjective quotations and Precison, Recall and F-measure are computed. From the analysis we infer that the Hindu newspaper contains positive news about the issue compared with other newspapers.
Quantifying the Impact of InterBlock Wire Delays on Processor Performance

A chip’s operating temperature is emerging as a major design constraint. Floorplanning is an effective technique that helps spread heat and minimize the occurrence of localized hotspots. The floorplanning process may place two communicating microarchitectural blocks (for example, the issue queue and ALU) far apart in an attempt to surround hot blocks with relatively cooler blocks. As we move to future wire-bound technologies, multiple pipeline stages may be required for the communication of signals between blocks that are placed far apart. This paper provides a detailed characterization of how these wire delays impact performance. Such data can serve as useful inputs to floorplanning algorithms so that performance-critical wire delays can be minimized. Routing and placement tools can also exploit this information by implementing low-power wires for the transmission of non-critical signals. In this work, we show that wire delays between the ALU and L1 data cache are most critical to performance, while most other wire delays degrade performance by less than 5% even if they consume up to four cycles. Our results are incorporated in a floorplanning tool and the generated floorplans perform up to 24% better than a floorplanner that does not take such information into account.
The Adaptive Chemotactic Foraging with Differential Evolution algorithm

This work proposes the application of a novel evolutionary approach called the Adaptive Chemotactic Foraging with Differential Evolution algorithm (ACF_DE) on benchmark problems. This method is based on the well-known Bacterial Foraging Optimization Algorithm (BFOA), applying appropriate Differential Evolution operators and including an adaptation scheme of the chemotaxis step size to concentrate the search in the desired optimal zone. The hybrid system is compared with those of related methods on benchmark problems showing its high performance in overcoming slow and premature convergence.
A Review on the Application of Benzothiadiazole in Plant Diseases Management

A review on the application of Abstract: The use of plant defense activators is a novel method of plant diseases management in recent years. Benzothiadiazole (BTH), is the first synthetic plant defense activator. In general, Benzothiadiazole has no direct effect against the pathogens, but it can activate the systemic acquired resistance (SAR) in plants, against a number of plant diseases. In addition, BTH widely is used to protect the plants against a range of pathogens on wheat, tomato, bean, tobacco, lettuce, banana and pears. In overall, Benzothiadiazole can be used as a safe and reliable product for plant protection and also as an alternative for chemical pesticides, which they have hazardous effects on environment.
Nutritional stimulation of cholecystokinin receptors inhibits inflammation via the vagus nerve

The immune system in vertebrates senses exogenous and endogenous danger signals by way of complex cellular and humoral processes, and responds with an inflammatory reaction to combat putative attacks. A strong protective immunity is imperative to prevent invasion of pathogens; however, equivalent responses to commensal flora and dietary components in the intestine have to be avoided. The autonomic nervous system plays an important role in sensing luminal contents in the gut by way of hard-wired connections and chemical messengers, such as cholecystokinin (CCK). Here, we report that ingestion of dietary fat stimulates CCK receptors, and leads to attenuation of the inflammatory response by way of the efferent vagus nerve and nicotinic receptors. Vagotomy and administration of antagonists for CCK and nicotinic receptors significantly blunted the inhibitory effect of high-fat enteral nutrition on hemorrhagic shock-induced tumor necrosis factor-alpha and interleukin-6 release (P < 0.05). Furthermore, the protective effect of high-fat enteral nutrition on inflammation-induced intestinal permeability was abrogated by vagotomy and administration of antagonists for CCK and nicotinic receptors. These data reveal a novel neuroimmunologic pathway, controlled by nutrition, that may help to explain the intestinal hyporesponsiveness to dietary antigens, and shed new light on the functionality of nutrition.
Network Adaptable Transmission Strategy Applied to H.264

A real-time transmission strategy that adapts network conditions rapidly is brought forward, and it is applied to H.264 encoding standard. Firstly, the strategy forecasts initial network bandwidth using bi-search algorithm, and establishes a dropout rate-smoothing model. In addition, it adopts the AIMD algorithm to adjust the sending bit rates, and then calculates QP based on R-D model. Finally, it encodes the video sequences according to the QP that goes through the operation of smoothness. The result of experiment in model JM shows that, this method reduces the image dithering caused by the change of bit rate, makes better use of network, and improves the video quality.