Miracle-dz/UniFAR-FTUs huggingface dataset:
Natriuretic peptides in the diagnosis and management of heart failure

The natriuretic peptides are a family of related hormones that play a crucial role in cardiovascular homeostasis. They have recently emerged as potentially important clinical markers in heart failure. Recent data have suggested an important role for these markers in establishing the diagnosis of heart failure in patients with unexplained dyspnea in both acute care and ambulatory settings. Other clinical uses of the natriuretic peptides, such as screening for asymptomatic ventricular dysfunction, establishing prognosis or guiding titration of drug therapy, are under investigation but have not yet sufficiently been validated for widespread clinical use.
Influence of learning and working climate on the retention of talented employees

Purpose – The aim of this study is to investigate some factors that have an influence on employee retention. Based on the literature and previous research, both employee and organisational factors are taken into account.Design/methodology/approach – Data were collected by means of a questionnaire that was distributed on a voluntary basis in professional organisations and among employees, both electronically and in hard‐copy, during 2008‐2009. The study sample consisted of 972 employees, mainly clerks, from diverse profit and social‐profit organisations.Findings – The results show that when organisations want to retain their employees it is important to pay attention to the learning of employees. Letting people do more and learn more of what they are good at will encourage them to stay with the organisation. Results concerning the selected employee variables show that only age has a significant relationship with retention. Regarding the intention to stay, there exists a positive relationship between age an.
Illuminating the Bias in Pedestrian Detection

Despite major advancements in state-of-the-art object detectors and low-light image enhancements, nighttime pedestrian detection remains a challenge. One commonly used solution to remedy this domain shift problem is re-training object detectors with extra nighttime scenes which is not only computationally expensive but also not generalizable. In this paper, we explore a new solution and aim to systematically analyze and understand the efficiency of a lightening algorithm on pedestrian detection in low-light conditions. In our analysis, we first explore the effect of normalizing image luminance based on the ground truth bounding boxes to adaptively adjust global image luminance and evaluate its effects on detection performance. Second, unlike general low-light image enhancements that rely on global or local image statistics, we design a pedestrian-luminance-aware lightening algorithm to automatically correct nighttime images luminance so that pedestrians can be more robustly detected. Through extensive experiments, our algorithm not only achieves competitive detection results compared to the baseline on two real-world nighttime datasets but also elevates the confidence score of detected pedestrians.
Designing and Analysis of 8 Bit SRAM Cell with Low Subthreshold Leakage Power

The power consumption is major concern in Very Large Scale Integration (VLSI) circuit design and reduce the power dissipation is challenging job for low power designers. International technology roadmap for semiconductors (ITRS) reports that "leakage power dissipation" may come to dominate total power consumption. The sub-threshold leakage power is the main reason to increase the leakage power. So there is some techniques to reduce this leakage power like sleep approach, stack & some new techniques like, sleepy-stack, leakage feedback approach and sleepy keeper techniques which reduces leakage current while saving exact logic state. As the technology increases integration density of transistors increases, power consumption has become a major concern in today's processors and SoC designs. Considerable attention has been paid to the design of low power and high-performance SRAMs as they are critical components in both handheld devices and high performance processors. In this paper we design 8 bit S-RAM by using the leakage current reduction techniques. The proposed circuits were designed in 0. 18µm CMOS/VLSI technology with-in Micro-Wind tool, and measure power consumption for design approaches, and we achieves up to nearly 50% less power consumption than existing basic SRAM.
Optimizing Operation of Photovoltaic System Using Neural Network and Fuzzy Logic

: It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.
Facial Expression Based User Concentration Alert System

Nowadays, due to more social platform usage, the user concentration on major activities has been declined. It can be seen in the education sector as the students are unable to pay attention in online sessions. Therefore, there is a need of an automatic alert system to make a student engaged. This paper focus on implementing face detection, face recognition and face emotion recognition in the education sector. With the concepts of Machine Learning and Neural Networks such as ResNet, AlexNet, VGG-16 as pretrained network helps in recognizing the human face. The emotions of the recognized face are then analysed through the machine learning model i.e. face emotion detector which detects facial emotions like happy, sad, confused, focused, angry, etc. This facial expression system help to send alert to the parents and students for evaluation and for preventing them from getting distracted during sessions.
Comparative Study among Various Machine Learning Algorithms towards the Detection of Alzheimer’s Disease

This article makes an attempt to make a comparative study among various machine learning algorithms in identifying dementia using some biomarkers inside the human brain. In connection to this, percentage volume of cerebro-spinal-fluid and lateral-ventricle are taken into consideration because of their drastic change with the severity of dementia in patients. A number of performance parameters has been computed in order to make a comparative study amongst various algorithms.
Implementing AAC with children with profound and multiple learning disabilities: a study in rationale underpinning intervention

There is a developing research base to support the rationale underpinning augmentative and alternative communication (AAC) for people with learning disabilities. However, there is a paucity of research examining the process involved in implementing AAC support for people who have profound disabilities. This paper seeks to explore the processes involved in planning and implementing AAC systems to support the communication of two six year olds with profound and multiple learning disabilities. Following assessment, a plan of intervention involving specific implementation of objects of reference, gestures and signs was implemented to enhance communication opportunities for both children. Both children improved their communication skills through use of specific AAC supports. Results suggest that important aspects to include when planning intervention are understanding the level of each child’s cognition in relation to their receptive abilities, and a consistent, collaborative approach where strategies are agreed between team members. Specific challenges are discussed.
The Impact of Artemisinin Combination Therapy and Long-Lasting Insecticidal Nets on Forest Malaria Incidence in Tribal Villages of India, 2006–2011

Introduction New tools for malaria control, artemisinin combination therapy (ACT) and long-lasting insecticidal nets (LLINs) were recently introduced across India. We estimated the impact of universal coverage of ACT and ACT plus LLINs in a setting of hyperendemic, forest malaria transmission. Methods We reviewed data collected through active and passive case detection in a vaccine trial cohort of 2,204 tribal people residing in Sundargarh district, Odisha between 2006 and 2011. We compared measures of transmission at the village and individual level in 2006–2009 versus 2010–2011 after ACT (in all villages) and LLINs (in three villages) were implemented. Results During 2006–2009 malaria incidence per village ranged from 156–512 per 1000 persons per year and slide prevalence ranged from 28–53%. Routine indoor residual spray did not prevent seasonal peaks of malaria. Post-intervention impact in 2010–2011 was dramatic with ranges of 14–71 per 1000 persons per year and 6–16% respectively. When adjusted for village, ACT alone decreased the incidence of malaria by 83% (IRR 0.17, 95%CI: 0.10, 0.27) and areas using ACT and LLINs decreased the incidence of malaria by 86% (IRR 0.14, 95%CI: 0.05, 0.38). After intervention, the age of malaria cases, their parasite density, and proportion with fever at the time of screening increased. Conclusions ACT, and LLINs along with ACT, effectively reduced malaria incidence in a closely monitored population living in a forest ecotype. It is unclear whether LLINs were impactful when prompt and quality antimalarial treatment was available. In spite of universal coverage, substantial malaria burden remained.
Visible lives: Identifying the experiences and needs of older lesbian, gay bisexual and transgender people in Ireland.

Approximately two-thirds of the survey participants reported living in towns or cities of more than 5,000 people. Participants from 25 counties out of the 26 counties within the Republic of Ireland were involved in the survey. Nearly seven out of ten survey participants reported owning their own home. Less than 1% of the sample lived in a nursing home/continuing care residence. A¢â,¬Â¢ There were relatively high rates of survey participants who were single (43.1%) and living alone (45.8%). A¢â,¬Â¢ The majority of those under 65 years of age, the typical age of retirement in Ireland, were working, while the majority of those over 65 years of age were retired. A¢â,¬Â¢ There was a large variation in reported household income with almost one-quarter indicating that their household income was under A¢â? sÂ¬19,999 per year and more than one-third reporting it to be over A¢â? sÂ¬50,000 per year. By far the most common source of income for participants was work or selfemployment. A¢â,¬Â¢ Nearly 14% of survey participants were providing care to a variety of people including parents, children, siblings, partners and friends. A¢â,¬Â¢ Only 10 of the survey participants were not out as LGBT to anyone.
Structure of the full-length Shaker potassium channel Kv1.2 by normal-mode-based X-ray crystallographic refinement

Voltage-dependent potassium channels (Kv) are homotetramers composed of four voltage sensors and one pore domain. Because of high-level structural flexibility, the first mammalian Kv structure, Kv1.2 at 2.9 Å, has about 37% molecular mass of the transmembrane portion not resolved. In this study, by applying a novel normal-mode-based X-ray crystallographic refinement method to the original diffraction data and structural model, we established the structure of full-length Kv1.2 in its native form. This structure offers mechanistic insights into voltage sensing. Particularly, it shows a hydrophobic layer of about 10 Å at the midpoint of the membrane bilayer, which is likely the molecular basis for the observed “focused electric field” of Kv1.2 between the internal and external solutions. This work also demonstrated the potential of the refinement method in bringing up large chunks of missing densities, thus beneficial to structural refinement of many difficult systems.
Additive Manufacturing enabling Radio Frequency Identification and Wireless Sensing

Additive manufacturing processes, encompassing both two-dimensional and three-dimensional techniques, present unparalleled levels of flexibility for creating cutting-edge radio frequency identification and sensing systems. The analysis of electromagnetic characteristics in bulk or engineered materials holds a vital significance in the creation of novel devices and the enhancement of existing ones. The potential applications range from integrating tags into objects and wearable sensors to utilizing metasurfaces for improved probing of signals inside the human body and incorporating sensors into robotic hands to achieve precise object grasping.
HVC microlesions do not destabilize the vocal patterns of adult male zebra finches with prior ablation of LMAN

The songs of adult male zebra finches (Taeniopygia guttata) arise by an integration of activity from two neural pathways that emanate from the telencephalic nucleus HVC (proper name). One pathway descends directly from HVC to the vocal premotor nucleus RA (the robust nucleus of the arcopallium) whereas a second pathway descends from HVC into a basal ganglia circuit (the anterior forebrain pathway, AFP) that also terminates in RA. Although HVC neurons that project directly to RA outnumber those that contribute to the AFP, both populations are distributed throughout HVC. Thus, partial ablation (microlesion) of HVC should damage both pathways in a proportional manner. We report here that bilateral HVC microlesions in adult male zebra finches produce an immediate loss of song stereotypy from which birds recover, in some cases within 3 days. The contribution of the AFP to the onset of song destabilization was tested by ablating the output nucleus of this circuit (LMAN, the lateral magnocellular nucleus of the anterior nidopallium) prior to bilateral HVC microlesions. Song stereotypy was largely unaffected. Together, our findings suggest that adult vocal production involves nonproportional integration of two streams of neural activity with opposing effects on song—HVC's direct projection to RA underlies production of stereotyped song whereas the AFP seems to facilitate vocal variation. However, the rapid recovery of song in birds with HVC microlesions alone suggests the presence of dynamic corrective mechanisms that favor vocal stereotypy. © 2006 Wiley Periodicals, Inc. Develop Neurobiol 67: 205–218, 2007.
Respiratory System Function in Patients after Aortic Valve Replacement through Right Anterior Minithoracotomy

Abstract Background The aim of the study was to analyze respiratory system function after minimally invasive aortic valve replacement through right anterior minithoracotomy (RAT-AVR). Methods An observational study of 187 patients electively scheduled for RAT-AVR between January 2010 and December 2013. Pulmonary complications were analyzed and spirometry examinations were performed preoperatively, 1 week, 1 month, and 3 months after surgery. Results Hospital mortality was 1.1%. A double-lumen intratracheal tube was used in 88.2% and single-lumen intratracheal tube was used in 11.8% of patients. Pulmonary complications occurred in 10.8% of the patients. Prolonged (>24 hours) mechanical ventilation time was present in five patients (2.7%). The reasons were stroke (n = 1), perioperative myocardial infarction (n = 2), and pneumothorax (n = 2). Right pleural effusion, which occurred in 7.7% (n = 14) of patients, was the most frequent respiratory system complication. One week after surgery, the spirometry parameters decreased in comparison to the preoperative period, then after 3 months statistically significant improvement occurred; however, the spirometry parameters still had not returned to preoperative values. Multivariable median regression analysis shows that the presence of chronic obstructive pulmonary disease and pulmonary complications were associated with lower values of forced expiratory volume in 1 second after surgery. There was no statistically significant difference regarding spirometry values or incidence of pulmonary complications after surgery between patients in whom single-lung or double-lung ventilation was applied. Conclusion Pulmonary functional status measured with spirometry parameters was diminished after RAT-AVR surgery. Single-lung ventilation did not result in a higher rate of respiratory complications after RAT-AVR surgery.
Biochemistry and structure of phosphoinositide phosphatases

Phosphoinositides are the phosphorylated derivatives of phosphatidylinositol, and play a very significant role in a diverse range of signaling processes in eukaryotic cells. A number of phosphoinositide-metabolizing enzymes, including phosphoinositide-kinases and phosphatases are involved in the synthesis and degradation of these phospholipids. Recently, the function of various phosphatases in the phosphatidylinositol signaling pathway has been of great interest. In the present review we summarize the structural insights and biochemistry of various phosphatases in regulating phosphoinositide metabolism. [BMB Reports 2013; 46(1): 1-8]
An Improved Multiquadric RBF Method for 3D Electromagnetic Problems

The multiquadric radial basis function method (MQ RBF or, simply, MQ) developed recently is a truly meshless method with global basis functions. It was introduced for solving many 1D and 2D PDEs, including linear and nonlinear problems. However, few works are found for electromagnetic PDEs, say nothing of 3D problems. This paper presents an improved MQ method for 3D electromagnetic problems. Numerical results show a considerable improvement in accuracy over the traditional MQ method, although both methods are direct collocation method with exponential convergence
Generalized analysis on diversity-multiplexing trade-off of relay protocols

Under the more practical assumption that transmitters have no knowledge of the channel state information (CSI) but the channel distribution information (CDI), this paper examines the diversity-multiplexing trade-off (DMT) of two classes of cooperative protocols, namely, the amplify-and-forward (AF) and decode-and-forward (DF) protocols, with a three-node half-duplex relay network under slow fading. First, analyzing these protocols reveals that each one has its own optimal DMT with a specific time slot ratio, i.e., the ratio between the durations of the slots assigned to base station transmission and that assigned to relay transmission. We then demonstrate that under ideal coding, the incremental decode-and-forward protocol approaches the DMT upper bound when the two slots are of equal length, which outperforms all the other protocols. Furthermore, it is proved that the selective decode-and-forward protocol achieves its optimal performance with a slot assignment ratio of ( p 5+1)=2. In addition, we also find AF, selective AF and
Paving the Way to Safety: An Automated Traffic Management and Challan Generation System

In India, traffic regulations have become a major concern due to various problems that have arisen. One of the most significant issues is the rising number of accidents and deaths caused by people riding motorcycles and mopeds without helmets. The existing system relies on Closed Circuit Television (CCTV) recordings, where traffic police must manually monitor violations and zoom in to identify the license plate number of the rider. However, this approach is time consuming and requires a lot of manpower, especially since the number of motorcycle riders increasing every day. To address this issue, researchers have developed a new system that can automatically detect violations of not wearing a helmet while riding a motorcycle pr moped. This system utilizes advanced features like Convolutional Neural Networks, Local Binary Patterns (LBP), Region based Convolutional Neural Networks (R-CNN), Histogram Oriented Gradients (HOG) and HAAR to identify and extract the license number plate of the offending vehicle. Given that motorcycle accidents are a leading cause of fatalities on the roads, it is crucial to enforce the use of helmets. The government has made it a punishable offense and law enforcement agencies have been using manual methods to catch violators. However, the proposed approach uses video surveillance to detect violators and record their license plate numbers, thereby making the process more efficient and more effective. The system will generate an E-challan containing the details of the offender, and also create a database with records of all offenders to ensure accurate identification. To identify different types of helmets with minimal computational cost, the system relies solely on pure machine learning techniques.
1 JUST IN TIME APPROACH IN INVENTORY MANAGEMENT

Quality improvement and costs control are vital to organizations for work performance enhancement and fulfilling customers’ requirement. Inventories that are stored in large amount of quantities will result in waste and space usage. One effective solution is using Just in Time (JIT) concept as a method to reduce costs, improve quality and meet the ever-changing customer needs. The adoption of Just in Time (JIT) concepts seems to be the mos t effective way to overcome these circumstances. JIT is managem ent philosophy that emphasizes on eliminating waste nd increase productivity. The main purpose of this res earch is to find out whether the implementation of JIT would reduce the inventories at Electronics component ind ustry especially at the parts producing stamping of FCM. This research is done by case study. Therefore the data collection would be using secondary data which is t he documentation from FCM itself and also via observat ion. The data were analyzed by doing the comparison before and after the implementation of JIT using Microsoft words excel. From the analysis that had been done, th implementation of JIT had increased the inventories management at the stamping parts production. As th e conclusion, the implementation of JIT in the invent ory management at the parts production stamping at Electronics component industry had successfully reduce the inve ntori s level while improving the inventory level.