Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of take-home naloxone in the epidemic of opioid overdose involving illicitly manufactured fentanyl and its analogs

ABSTRACT Introduction: There has been an exponential increase in overdose fatalities as illicitly manufactured fentanyl and its analogs (IMF) are becoming more prevalent in the illicit drug supply. In response, overdose education and naloxone distribution (OEND) programs have been implemented throughout the United States as a harm reduction strategy. However, there are increasing reports that higher naloxone doses or repeat administration might be required for overdose victims involving IMF. Areas covered: In this article, we provide a comprehensive review of the epidemiology, public health impact, and pharmacologic properties of IMF. The pharmacokinetic properties of currently available take-home naloxone (THN) kits, the role of THN as a harm reduction strategy and available data on its clinical use are discussed. Implications of occupational IMF exposure for first responders are also described. Expert opinion: THN administration by a bystander is an effective harm reduction intervention. However, there is growing evidence that higher dose or multiple administrations of naloxone are required to fully reverse IMF related toxicity. Recently, the US Food and Drug Administration approved THN kits with a concentrated naloxone dose that produce high bioavailability. However, limited presence of OEND programs and cost of these new devices impede their accessibility to the general public.
Impedance Control based Assistive Mobility Aid through Online Classification of User’s State

In this paper, we present our effort on the development of an assistive mobility aid for daily elderly care through human-robot interaction. The focus of this work is to provide the user with physical movement support in their daily life such as movement transition, e.g., sit-to-stand and stand-to-sit, and walking using a mobile assistive robot. We propose an approach to providing desirable physical support through an appropriately designed impedance control strategy with online recognition of the user’s current movement states. In the proposed framework, the desired set of impedance parameters are determined based on the online estimation of the probabilities of the user’s state with an LSTM-RNN, and the robot provides suitable mobility aid accordingly. In order to demonstrate the effectiveness of the proposed approach, we first present a performance evaluation of online recognition of user’s movement state and transition. Then, we report experimental results of our proposed assistive mobility aid for sit-to-stand/stand-to-sit and walking movement support with a human support robot.
Trajectory planning method for reduced patient risk in image-guided neurosurgery: concept and preliminary results

We present a new preoperative planning method to quantify and help reduce the risk associated with needle and tool insertion trajectories in image-guided keyhole neurosurgery. The goal is to quantify the risk of a proposed straight trajectory, and/or to find the trajectory with the lowest risk to nearby brain structures based on pre-operative CT/MRI images. The method automatically computes the risk associated with a given trajectory, or finds the trajectory with the lowest risk to nearby brain structures based on preoperative image segmentation and on a risk volume map. The surgeon can revise the suggested trajectory, add a new one using interactive 3D visualization, and obtain a quantitative risk measure. The trajectory risk is evaluated based on the tool placement uncertainty, on the proximity of critical brain structures, and on a predefined table of quantitative geometric risk measures. Our preliminary results on a clinical dataset with eight targets show a significant reduction in trajectory risk and a shortening of the preoperative planning time as compared to the conventional method.
Characterization of a 10 cM region of rice chromosome 5

Rice is a model species for the cereals and a good candidate for genome sequencing due to its relatively small genome (430 Mb), dense physical and genetic maps, and good transgenic systems. As part of an international effort to decode the rice genome, a PAC clone localized at 10 cM of chromosome 5 is completely determined for its sequence using shotgun libraries of its two inserts, 2-kb and 5-kb in length. In total 2,998 sequencing reads were used for the assembly of the final sequence, covering 175,439 bp. This sequence may code for at least 28 putative proteins, as deduced from computational search for homology with other known coding sequences and EST, or predicted using GenScan package. Also present in this sequence are simple repeats, palindrome and retrotransposons. On the basis of these findings, the gene density in the gene-rich region of rice genome is about 6 kb/gene.
Leaf Classification for Plant Recognition with Deep Transfer Learning

Plant recognition systems that developed by computer vision researchers, help botanists in faster recognition and detection of unknown plant species. Until now, multiple studies focused on the process or algorithms that maximize use of botanical datasets for plants prediction modeling, but this method depends on leaf characteristics which can be changed with botanical data and different feature extraction techniques. On the other hand, recently, due to the popularity and successful implementation of deep learning-based methods in various areas such as image classification, object detection, and speech recognition, the researchers directed from traditional feature-based methods to deep learning. In this research, one more efficient method presented that use transfer learning to recognize plant for leaf classification, which first uses a pre-trained deep neural network model for learning useful leaf characteristics directly from the input data representation. Then use a logistic regression classifier for leaf classification. It is seen that transfer learning from a large dataset to limited botanical dataset in plant recognition task is well done. The proposed method is evaluated on two well-known botanical datasets, i.e., Flavia with 32 classes and Leafsnap with 184 classes, and has succeeded in achieving an accuracy of 99.6% and 90.54%, respectively. The results show that despite the large change in the number of classes in these two datasets, the proposed method, have a good performance and show the better result than methods based on the hand-crafted feature and other methods based on the deep learning in terms of memory and precision.
Link prediction using matrix factorization with bagging

Link prediction aims at estimating the likelihood of the existence of links between nodes. In this paper, we treat link prediction as a collaborative filtering problem, and propose an algorithm to solve this problem using matrix factorization approach. For making better predictions, this paper also explores the use of bagging technique as combination approaches for matrix factorization. We subsample the training set and added random noise to make multiple classifiers, and then combine these classifiers to be the final classifier. Results on several data sets show the efficacy of our approach. Compared with several popular proximity metrics, the accuracy of the algorithm can be increased greatly by use of bagging technique, especially measured by precision.
Intelligent Signal Processing and Coordination for the Adaptive Smart Grid: An Overview of Data-Driven Grid Management

In today's era of the Internet of Things (IoT), the amalgamation of information and communication technologies with actuating devices has reached all corners of the modern world. In the context of critical infrastructures, such as the power grid, this cyberphysical transformation has permeated all system levels as evident in devices ranging from crucial operational components (e.g., generators) and advanced sensors [e.g., phasor measurement units (PMUs) and programmable controllers], to consumer-centric devices [smart meters, electric vehicles (EVs), and smart appliances]. These extended cyberphysical functionalities have opened up signal processing opportunities that can be harnessed to empower actuating devices to adaptively and synergistically acquire data, conduct analytics, and respond to system and environmental changes for better power-grid operations. In this article, we demonstrate how a hierarchical signal processing and actuation framework can enable the tractable all-encompassing coordination of thousands of actuating power entities to maintain efficient operations while accounting for physical infrastructure limits.
HiNFS

Persistent memory provides data persistence at main memory with emerging non-volatile main memories (NVMMs). Recent persistent memory file systems aggressively use direct access, which directly copy data between user buffer and the storage layer, to avoid the double-copy overheads through the OS page cache. However, we observe they all suffer from slow writes due to NVMMs’ asymmetric read-write performance and much slower performance than DRAM. In this article, we propose HiNFS, a high-performance file system for non-volatile main memory, to combine both buffering and direct access for fine-grained file system operations. HiNFS uses an NVMM-aware Write Buffer to buffer the lazy-persistent file writes in DRAM, while performing direct access to NVMM for eager-persistent file writes. It directly reads file data from both DRAM and NVMM, by ensuring read consistency with a combination of the DRAM Block Index and Cacheline Bitmap to track the latest data between DRAM and NVMM. HiNFS also employs a Buffer Benefit Model to identify the eager-persistent file writes before issuing I/Os. Evaluations show that HiNFS significantly improves throughput by up to 184% and reduces execution time by up to 64%comparing with state-of-the-art persistent memory file systems PMFS and EXT4-DAX.
Analysis of Finger Vein Feature Extraction and Recognition using DA and KNN Methods

A steady growth in terms of development alongwith the use of consumer electronics has been noticed which is a consequence of and increased rate of globalization that has raised the living standards. This has arisen a need for high security authentication systems in order to safeguard personal information stored on mobile devices. Since the high complexity and security of existing biometric systems is becoming the prime concern in terms of space and time, automated personal identification using finger-vein biometric is emerging to be a prominent topic in both practical as well as examination applications. In this paper, using MATLAB 2016a, we present discriminant analysis and KNN of machine learning method, as it stands for K- nearest neighbor algorithm are used to verify and calculate the accuracy of the features of the finger vein images. Thus, the accuracy obtained from KNN is 55.84% whereas from discriminant analysis the accuracy obtained is 92.21%. Finally discriminant analysis is more accurate than KNN technique.
Oncological Inspired Techniques for Intelligent Software Testing

Biologically inspired computing techniques are highly on demand due to the inter-connection of various specialized fields and their requirement of adaptable methods in solving software engineering problems. Mutation testing has acquired much importance in this scenario. The concept of mutation testing has originated from the bio immune system. This paper is a novel study on mutation testing that proposes a framework OSWM (oncological software mutation) from oncological tests performed in human pancreatic cancer cells. The framework connects the relationship between cancer cell tests and software tests ensuring mutation tests owe its origin from human cells tested. The study argues an intelligent software with an efficient immune system can therefore aim at testing, diagnosing and healing on its own.
Effects of n-3 fatty acids, EPA v. DHA, on depressive symptoms, quality of life, memory and executive function in older adults with mild cognitive impairment: a 6-month randomised controlled trial

Depressive symptoms may increase the risk of progressing from mild cognitive impairment (MCI) to dementia. Consumption of n-3 PUFA may alleviate both cognitive decline and depression. The aim of the present study was to investigate the benefits of supplementing a diet with n-3 PUFA, DHA and EPA, for depressive symptoms, quality of life (QOL) and cognition in elderly people with MCI. We conducted a 6-month double-blind, randomised controlled trial. A total of fifty people aged >65 years with MCI were allocated to receive a supplement rich in EPA (1·67 g EPA+0·16 g DHA/d; n 17), DHA (1·55 g DHA+0·40 g EPA/d; n 18) or the n-6 PUFA linoleic acid (LA; 2·2 g/d; n 15). Treatment allocation was by minimisation based on age, sex and depressive symptoms (Geriatric Depression Scale, GDS). Physiological and cognitive assessments, questionnaires and fatty acid composition of erythrocytes were obtained at baseline and 6 months (completers: n 40; EPA n 13, DHA n 16, LA n 11). Compared with the LA group, GDS scores improved in the EPA (P = 0·04) and DHA (P = 0·01) groups and verbal fluency (Initial Letter Fluency) in the DHA group (P = 0·04). Improved GDS scores were correlated with increased DHA plus EPA (r 0·39, P = 0·02). Improved self-reported physical health was associated with increased DHA. There were no treatment effects on other cognitive or QOL parameters. Increased intakes of DHA and EPA benefited mental health in older people with MCI. Increasing n-3 PUFA intakes may reduce depressive symptoms and the risk of progressing to dementia. This needs to be investigated in larger, depressed samples with MCI.
Analysis of the Measured Coupling between Adjacent Elements of a Dual-Polarized Vivaldi-Antenna System for a VHF GPR

In this article, a structure of Vivaldi antennas for a Ground Penetrating Radar(GPR) in the VHF band is analyzed through different modifications on four antennas using different resonators to obtain the model where coupling is small as possible. A design is obtained with the best performance of isolation between two adjacent elements of the antenna structure in order to ensure that reflected power from the transmitter will not deteriorate components of the receiver at one specific height of the module above arid soil. The GPR with dual polarization will be used for archaeological exploration in the coast of Peru where the ground is mostly sandy.
4G-β-D-galactosylsucrose as a prebiotics may improve underweight in inpatients with schizophrenia

Japanese inpatients with schizophrenia have a higher mortality risk due to underweight compared with the general population. The aim of this study was to investigate the effect of 4G-β-D-galactosylsucrose on body weight in underweight schizophrenia inpatients. The study population consisted of 5 male and 11 female subjects aged 63.0 ± 10.9 years. The subjects had ingested 3.0 g/day 4G-β-D-galactosylsucrose for 6 months. BMI increased significantly, from 20.9 ± 3.7 kg/m2 to 22.3 ± 4.3 kg/m2, and this was accompanied by a significant increase in Bifidobacterium in the fecal microbiota, which increased from 16.1 ± 12.6% to 21.5 ± 13.9%. Although 4G-β-D-galactosylsucrose appears to have no significant effects on nutritional indicators such as serum albumin, it may alleviate underweight in inpatients with schizophrenia. Body weight may be related to fecal microbiota composition.
An Evaluation of Treatment Outcomes in a Cohort of Clients on the DOTS Strategy, 2012–2016

We present, for the first time, an evaluation of treatment outcomes in a cohort at a TB referral centre in the Central Region of Ghana. Of the 213 clients placed on DOTS, 59.2% (126/213) were sputum smear-positive. An overall cure rate of 90.2% (51.6% cured + 37.6% completed) and a death rate of 8.5% (18/213) were estimated. Of the number of clients who died, 5.7% (12/213) were males (χ 2 = 2.891, p = 0.699; LR = 3.004, p = 0.699). Deaths were only recorded among clients who were > 19 years old (χ 2 = 40.319, p = 0.099; LR = 41.244, p = 0.083). Also, 0.9% (2/213) was lost to follow-up, while 1.4% (3/213) had treatment failure. In total, 13.6% (7.0%, 15/213 males, and 6.6%, 14/213 females) of clients who were placed on DOTS were HIV seropositive. Ages of 40–49 years had the highest number, 13/213 (6.1%), infected with HIV, though the difference among the remaining age groups was not statistically significant (χ 2 = 9.621, p = 0.142). Furthermore, 7.0% (15/213) had TB/HIV coinfection. Out of them, 9 were cured and 5 died at home, while 1 had treatment failure. Tuberculosis/HIV infection prevention advocacy and interventions that address sociodemographic determinants of unfavourable treatment outcomes are urgently required to augment national efforts towards control.
Effects of Condensed Tannin-Rich Pine Bark Diet on Experimentally Infected With Haemonchus Contortus in Meat Goats

This study evaluated the effects of dietary supplementation of a novel condensed tannin-rich pine bark (PB) mixture diet on an in vitro gas production, in vivo animal performance, internal parasites, carcass production, and plasma metabolites in meat goats. Fifteen Kiko-cross meat goats (Capra hircus; body weight (BW) = 28.0 ± 1.0 kg) were randomly assigned to two experimental diets (control vs. PB supplementation): 1) control diet (70% grain mixture and 30% wheat straw (WS) and 2) 70% grain mixture with 30% PB. Animals were dewormed on day 10 and animals were artificially inoculated (day 20) with 5,000 infective stage (L3) Haemonchus contortus larvae. Feed intake and performance were monitored for 87 days. Blood samples were taken twice, once at the beginning and once at the end of the experiment. Fecal egg (FEC) was determined approximately every 2 week. At the end of the experimental period, goats were slaughtered, and abomasum parasite load was determined. Abomasal worms were identified and counted. All analyses were conducted using a GLM or MIXED pro - cedure of SAS, but in vitro gas analysis was conducted using non-linear procedure of SAS. Overall, there were no differences (P >0.10) in dry matter intake, body weight, and carcass traits between diets. H.contortus adult worm numbers were lower (P <0.05) for goats that were fed PB diet than for control. On day 84, control goats on control WS diet had greater (P = 0.01) FEC than PB diet group. It was concluded that feeding ground PB as a feed ingredient has the potential to decrease internal parasite infection without detrimental effects.
A Nano-Biased Energy Management Using Reinforced Learning Multi-Agent on Layered Coalition Model: Consumer Sovereignty

Trends in energy management schema have advanced into legislating consumer-centered solutions due to inclination interests for personal owned distributed energy resources at the low-voltage level. Thence, this paper proposes a tailorable energy manager tool that empowers Prosumer(s) in a nanostructured distribution network to take sole precedence when prosuming optimal services to the energy system. It too acts as an aggregator that attests cooperative energy management processes amongst Prosumers to enhance demand-side responses and economics. The suggested nano-biased energy manager engages multi-agent network as the basis coordinator for peer-to-peer advocacy in a decentralized environment. The agents were then programmed with reinforcement and extreme learning machine intelligence on a layered coalition model to compute joint decision-making processes with constraint relaxation relaxed decision constraints and policies. The problem formulations assure engagement of energy management in the liberalized market is sustainable, reliable, and non-discriminated. Computational validations were analyzed using MATLAB and Java agent development framework on four aggregated Nanogrids representing the residential, commercial, and industrial building. Results have shown positive eco-strategic managerial avenues where cooperative assets scheduling and bidding-abled decorum were autonomously acquired. Reduced operating costs were gained from energy trading profit margin due to strategic use/sell of electricity based on real-time tariff and conferred incentive packages but constrained within the mandatory obligation to demand-side management. The subsidiary, the inauguration of meshed communication infrastructure has shown adequate monitoring and commanding resolutions for decentralized Agent(s) to function collaboratively.
Development of Forceps Manipulator Using Pneumatic Soft Actuator for a Bending Joint of Forceps Tip

In this paper, a forceps manipulator using a pneumatic soft actuator for a flexion joint of forceps tip is developed. Many forceps manipulators are driven by wires, however there are problems such as friction between wires and parts and interference between wires. Therefore, this problem is solved by using the soft actuator, which performs bending of two degrees of freedom joint driven by air pressure instead of wires. The soft actuator is made of a silicone rubber and reinforced by two metal springs. It is easy to fabricate the soft actuator by using a metal spring. The outer spring restrains the radial expansion of the soft actuator, and the inner spring is placed in the center of the soft actuator to reinforce the bending stiffness. The actuator has four chambers, and it is possible to bend the soft actuator by inputting air into each chamber. An air gripper is mounted on the tip of the soft actuator. The bending angle of the forceps is estimated by the pressure in the chambers. The total length of the developed forceps is 340 mm, the weight is 23 g, and the maximum bending angle is 53 deg. By using the soft actuator for the bending joint itself, a simple and lightweight forceps manipulator with no driving unit at the rear end is realized.
Empower Me? Yes, Please, But in My Way: Different Patterns of Experiencing Empowerment in Patients with Chronic Conditions

ABSTRACT Empowerment is a widely used word within the realm of health care. This is especially true in the case of patients living with a chronic illness, who may be active participants and learn to manage their disease, irrespective of their desires or preferences. This article focuses on the empowering experience of patients with chronic conditions. We have built on earlier research that explains the factors that mediate communication between health care professionals and patients: patient participation, patient impact, meaning, health care professionals’ information provision, health care professionals’ emotional support, health care professionals’ attentive listening, health care professionals’ trust, and patient collaboration. We propose a new model for detecting types of patients who differ in the way they live their empowering experience. Using survey data from a sample of 181 patients of hemophilia, we found two types of patients: patients with an inner locus of empowerment and patients with an outer locus of empowerment. We conclude by discussing different strategies for fostering the sense of power in each of these types of patients.