Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in Muscle Synergy Symmetry Between Subacute Post-stroke Patients With Bioelectrically-Controlled Exoskeleton Gait Training and Conventional Gait Training

Understanding the reorganization of the central nervous system after stroke is an important endeavor in order to design new therapies in gait training for stroke patients. Current clinical evaluation scores and gait velocity are insufficient to describe the state of the nervous system, and one aspect where this is lacking is in the quantification of gait symmetry. Previous studies have pointed out that spatiotemporal gait asymmetries are commonly observed in stroke patients with hemiparesis. Such asymmetries are known to cause long-term complications like joint pain and deformation. Recent studies also indicate that spatiotemporal measures showed that gait symmetry worsens after discharge from therapy. This study shows that muscle synergy analysis can be used to quantify gait symmetry and compliment clinical measures. Surface EMG was collected from lower limb muscles of subacute post-stroke patients (with an onset of around 14 days) from two groups, one undergoing robotic-assisted therapy (known as HAL group) and the other undergoing conventional therapy (known as Control group). Muscle synergies from the paretic and non-paretic limb were extracted with Non-Negative Matrix Factorization (NNMF) and compared with each other to obtain a gait symmetry index over therapy sessions. Gait events were tracked with motion tracking (for the HAL group) or foot pressure sensors (for the conventional therapy group). Patients from both groups were assessed over a 3-weeks long gait training program. Results indicated that there were no differences in muscle synergy symmetry for both groups of patients. However, the timing of muscle synergies were observed to be symmetrical in the HAL group, but not for the Control group. Intergroup comparisons of symmetry in muscle synergies and their timings were not significantly different. This could be due to a large variability in recovery in the Control group. Finally, stance time ratio was not observed to improve in both groups after their respective therapies. Interestingly, FIM and FMA scores of both groups were observed to improve after their respective therapies. Analysis of muscle coordination could reveal mechanisms of gait symmetry which could otherwise be difficult to observe with clinical scores.
Genetic Basis of Response of Ghanaian Local Chickens to Infection With a Lentogenic Newcastle Disease Virus

Newcastle disease (ND) is a global threat to domestic poultry, especially in rural areas of Africa and Asia, where the loss of entire backyard local chicken flocks often threatens household food security and income. To investigate the genetics of Ghanaian local chicken ecotypes to Newcastle disease virus (NDV), in this study, three popular Ghanaian chicken ecotypes (regional populations) were challenged with a lentogenic NDV strain at 28 days of age. This study was conducted in parallel with a similar study that used three popular Tanzanian local chicken ecotypes and after two companion studies in the United States, using Hy-line Brown commercial laying birds. In addition to growth rate, NDV response traits were measured following infection, including anti-NDV antibody levels [pre-infection and 10 days post-infection (dpi)], and viral load (2 and 6 dpi). Genetic parameters were estimated, and two genome-wide association study analysis methods were used on data from 1,440 Ghanaian chickens that were genotyped on a chicken 600K Single Nucleotide Polymorphism (SNP) chip. Both Ghana and Tanzania NDV challenge studies revealed moderate to high (0.18 – 0.55) estimates of heritability for all traits, except viral clearance where the heritability estimate was not different from zero for the Tanzanian ecotypes. For the Ghana study, 12 quantitative trait loci (QTL) for growth and/or response to NDV from single-SNP analyses and 20 genomic regions that explained more than 1% of genetic variance using the Bayes B method were identified. Seven of these windows were also identified as having at least one significant SNP in the single SNP analyses for growth rate, anti-NDV antibody levels, and viral load at 2 and 6 dpi. An important gene for growth during stress, CHORDC1 associated with post-infection growth rate was identified as a positional candidate gene, as well as other immune related genes, including VAV2, IL12B, DUSP1, and IL17B. The QTL identified in the Ghana study did not overlap with those identified in the Tanzania study. However, both studies revealed QTL with genes vital for growth and immune response during NDV challenge. The Tanzania parallel study revealed an overlapping QTL on chromosome 24 for viral load at 6 dpi with the US NDV study in which birds were challenged with NDV under heat stress. This QTL region includes genes related to immune response, including TIRAP, ETS1, and KIRREL3. The moderate to high estimates of heritability and the identified QTL suggest that host response to NDV of local African chicken ecotypes can be improved through selective breeding to enhance increased NDV resistance and vaccine efficacy.
Hierarchical Bayesian approach for population dynamics modelling of fish complexes without species-specific data

Jiao, Y. , Hayes, C. , and Cortes, E. 2009. Hierarchical Bayesian approach for population dynamics modelling of fish complexes without species-specific data. - ICES Journal of Marine Science, 66: 367-377.Modelling the population dynamics of fish complexes is challenging, and many species have been assessed and managed as a complex that was treated as a single species. Two Bayesian state-space surplus production models with multilevel priors (hierarchical models) were developed to simulate variability in population growth rates of species in a complex, using the hammerhead shark complex (Sphyrna spp.) of the Atlantic and Gulf of Mexico coasts of the US as an example. The complex consists of three species: scalloped (Sphyrna lewini), great (Sphyrna mokarran), and smooth hammerhead (Sphyrna zygaena). Bayesian state-space surplus production models with multilevel priors fitted the hammerhead data better than a model based on single-level priors. The hierarchical Bayesian approach represents an intermediate strategy between traditional models that do not include variability among species, and highly parameterized models that assign an estimate of parameters to each species. By ignoring the variability among species, confidence intervals of the estimates of stock status indicators can be unrealistically narrow, possibly leading to high-risk management strategies being adopted. Use of multilevel priors in a hierarchical Bayesian approach is suggested for future hammerhead shark stock assessments and for modelling fish complexes lacking species-specific data.
Change Detection from Remote Sensing to Guide OpenStreetMap Labeling

The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the latest remote sensing data in combination with state-of-the-art computer vision methods to assist the OSM community in labeling work. This article reports our progress to utilize artificial neural networks (ANN) for change detection of OSM data to update the map. Furthermore, we aim at identifying geospatial regions where mappers need to focus on completing the global OSM dataset. Our approach is technically backed by the big geospatial data platform Physical Analytics Integrated Repository and Services (PAIRS). We employ supervised training of deep ANNs from vertical aerial imagery to segment scenes based on OSM map tiles to evaluate the technique quantitatively and qualitatively.
Machine Learning Generalisation across Different 3D Architectural Heritage

The use of machine learning techniques for point cloud classification has been investigated extensively in the last decade in the geospatial community, while in the cultural heritage field it has only recently started to be explored. The high complexity and heterogeneity of 3D heritage data, the diversity of the possible scenarios, and the different classification purposes that each case study might present, makes it difficult to realise a large training dataset for learning purposes. An important practical issue that has not been explored yet, is the application of a single machine learning model across large and different architectural datasets. This paper tackles this issue presenting a methodology able to successfully generalise to unseen scenarios a random forest model trained on a specific dataset. This is achieved looking for the best features suitable to identify the classes of interest (e.g., wall, windows, roof and columns).
Ethnobotanical survey of medicinal plants used for the management of diabetes mellitus in the Nkonkobe municipality of South Africa.

An ethnobotanical survey was conducted on the medicinal plants frequently used for the management of diabetes mellitus in Nkonkobe Municipality, Eastern Cape of South Africa. Information was obtained through structured questionnaire administered to traditional healers and herbalists in the region. The study revealed 15 species of plants belonging to 13 families namely; Hyacinthaceae, Asphodelaceae, Caryophyllaceae, Aloaceae, Loganiaceae, Portulaceae, Solanaceae, Asteraceae, Hypoxideae, Menispermaceae, Alliaceae, Celastraceae and Lamiaceae. The decoction of the roots leaves and barks of these plants are the most commonly used while the extracts are taken orally for long period of time usually between 6 and 12 months, depending on the severity of the ailments. Strychnos henningsii and Leonotis leonorus of the families Loganiaceae and Lamiaceae respectively, were repeatedly mentioned by the traditional healers as the two mostly used for the management of diabetes mellitus in the study area.
Abundance of Neopelma baccharidis (Homoptera: Psyllidae) Galls on the Dioecious Shrub Baccharis dracunculifolia (Asteraceae )

We assessed whether temporal variation in gall abundance of Neopelma baccharidis Buckhardt on Baccharis dracunculifolia De Candole is determined by climatic conditions, availability of adults for plant colonization, tannin concentration in plant tissue, or attack by natural enemies. We verified the influence of host plant sex on the above-mentioned factors. Gall abundance varied during the study period and was higher on the reproductive phases (10.53 ± 0.87 galls per plant) than on the nonreproductive phases (0.89 ± 0.13 galls per plant) of the host plant. Gall abundance was not influenced by weather conditions. The abundance of adults in the field was not responsible for the pattern on gall frequency. No relationship was found between the frequency of gall dehiscence and abundance of adults. Mortality caused by natural enemies influenced gall survivorship but did not affect gall abundance in the field. Tannin concentration was higher during the reproductive phase (0.117 ± 0.017 mg/g) than the nonreproductive phase (0.042 ± 0.004 mg/g). Nevertheless, no relationship was found between tannin concentration and gall abundance, probably because of the feeding habit of galling insects. We found that the gender of the host plant did not influence gall abundance, tannin concentration, and gall mortality rates. These results suggest that the abundance of galls of N. baccharidis is probably determined by a plant trait that varies between phenological phases, such as other secondary compounds or mechanical defenses not evaluated in this study.
Inhibitors of autoinducer-2 quorum sensing and their effect on bacterial biofilm formation

Title of Document: INHIBITORS OF AUTOINDUCER-2 QUORUM SENSING AND THEIR EFFECT ON BACTERIAL BIOFILM FORMATION Rebecca Melissa Lennen, Master of Science, 2007 Directed by: Dr. William Bentley, Professor Department of Bioengineering Bacteria utilize small signaling molecules, or autoinducers, to regulate their gene expression in tandem by a process termed quorum sensing. The gene encoding the synthase for autoinducer-2 (AI-2), luxS, is conserved in dozens of diverse bacteria. Behaviors controlled by AI-2 include virulence, motility, toxin production, and biofilm formation. The development of therapies that interfere with AI-2 quorum sensing are attractive for targeting biofilms, which exhibit inherent resistance to most antibiotics and biocidal agents. In this study, in vitro synthesized AI-2, LuxS inhibitors, and (5Z)-4bromo-5-(bromomethylene)-3-butyl-2(5H)-furanone were screened for their effect on biofilm formation in Escherichia coli, Bacillus cereus, and Listeria innocua. The LuxS inhibitors were found to have no influence on biofilm formation in any of the screened species, but reduced exponential phase AI-2 production in Listeria innocua. The brominated furanone significantly inhibited growth in B. cereus and L. innocua, and under certain conditions preferentially inhibited biofilm formation independently from
A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics

In this letter, we address the challenge of sensor fusion in Soft Robotics for estimating forces and deformations. In the context of intrinsic sensing, we propose the use of soft capacitive sensing to find a contact’s location, and the use of pneumatic sensing to estimate the force intensity and the deformation. Using a FEM-based numerical approach, we integrate both sensing streams and model two Soft Robotics devices we have conceived. These devices are a Soft Pad and a Soft Finger. We show in an evaluation that external forces on the Soft Pad can be estimated and that the shape of the Soft Finger can be reconstructed.
Granular Description of Data: A Comparative Study Regarding to Different Distance Measures

In data science, how to depict data in the concise and comprehensive way is an important issue. To address the issue, the key is to construct descriptors that are highly interpretable and can be used to reveal the data structure. Information granules, as one important role in the field of granular computing, are entities that can be easily represented and abstracted from data. Therefore, by constructing a series of information granules, the characteristics of data can be captured and described, and the granular description of data is realized. A key part of the granular description of data is to explore the geometric characteristics (locations and shapes) of information granules used to describe data. Since distance measures directly affect the geometric characteristics of the constructed information granules, a comparative study based on three different distance measures is conducted in this paper. From the experimental results based on both synthetic and UCI repository datasets, it can be seen that the information granules constructed in the case where three different distance measures are used show different geometrical shapes, and can describe the data in a concise way. Furthermore, the data structure can be explored more comprehensively by using three distance measures.
A High Performance Adaptive Digital LDO Regulator With Dithering and Dynamic Frequency Scaling for IoT Applications

In this paper, a high performance adaptive digital low-dropout voltage regulator (ADLDO) is proposed for Internet-of-Things (IoT) applications. In the proposed ADLDO, a fully synthesizable adaptive digital controller is designed. It automatically senses load variations and adaptively controls multi-loop architecture to reduce quiescent current, minimize output voltage ripples and achieve fast transient response. The multi-loop architecture with hill climbing reduces the total bi-directional shift registers length which results in the reduced leakage current in the transistor-switch-array (TSA), and improves the recovery time and output DC voltage accuracy. A dithering technique is introduced to eliminate the limit cycle oscillation (LCO) and improve the performance of the regulator. The dynamic frequency scaling (DFS) mechanism is proposed for reducing controller power consumption in steady state. In order to reduce the offset and output voltage error, a dynamic latch comparator is utilized. When the input supply voltage is varied from 0.5 V to 1 V, the measured output voltage ranges from 0.45 V to 0.95 V with 50 mV dropout voltage. The operating frequency is 10 MHz with fast transient response and quiescent current of 350 ns and $3.7~\mu \text{A}$ , respectively. The maximum measured power and current efficiencies are 89.7 % and 99.97 %, respectively, with 1.9 mV output voltage ripples. Measured load and line regulations are 2.2 mV/mA and 9.5 mV/V respectively. The proposed circuit is implemented in 28 nm CMOS process and occupies 0.016 mm2 chip area.
Bryophyte diversity and distribution along an altitudinal gradient on a lava flow in La Réunion

Non‐vascular plant distribution patterns were examined in three microhabitats along an altitudinal gradient on a recent lava flow of the Piton de la Fournaise volcano (La Réunion, Mascarene archipelago). The uniform nature of the lava flow provides an excellent system to study the relationship between altitude and species diversity and distribution, and at the same time avoiding confusing multiple effects of substrate and vegetation heterogeneity. Non‐vascular plants were surveyed with quadrats within an altitudinal range from 250 m to 850 m a.s. l. Fine‐scale variations in bryophyte communities between three ecological microhabitats (the ground and on the rachises of two fern species) were investigated. Three specific questions were addressed: (1) What is the species diversity of bryophyte communities on a 19‐year‐old lava flow? (2) How does altitude influence the diversity and distribution of bryophytes on a lava flow? (3) Does microhabitat variation control bryophyte diversity? In our study, bryophyte diversity increased with altitude. Unexpectedly, species richness was very high; 70 species of bryophytes were recorded including nine new records for the island. Diversity was also controlled by ecological microhabitats. Bryophyte species were structured into six categories according to altitude and microhabitat preferences. Results suggested that the high diversity of these cryptic organisms on this lava flow is fostered in part by their host substrate and their adaptative strategies on new substrates. On a broader scale, it was concluded that lava flows as primary mineral environments are important to conserve, as they support a high diversity of pioneer organisms that constitute the early stages of the development of La Réunion's remnant lowland rainforest.
Evaluation of Topiramate Efficacy on Neuropathic Pain in Patients With Diabetic Polyneuropathy

Polyneuropathy is one of the most common and disabling complications of diabetes. Severe pain is one of the complications of diabetic polyneuropathy . Over the years, many drugs for the treatment of the pain in diabetic neuropathy have been tried. However, no one is completely effective. In a single-blind clinical trial, 200 patients with painful diabetic neuropathy were studied over 12 weeks. In the intervention group, 100 patients were treated with 100 milligrams of Topiramate per day and 100 patients in the control group treated with 90 milligrams of Gabapentin per day. Pain intensity recorded with Visual analogue scale between 0 to 100 millimeter over twelve weeks. Reduction in pain intensity of ≥30 mm was considered as effective response. The purpose of this study was to investigate the effect of Topiramate in the treatment of pain in diabetic polyneuropathy. The mean reduction in pain intensity over twelve weeks in Topiramate groups were 33.83±12.17 and in Gabapentin group were 30.25±15.66. The relative improvement in the Topiramate group was 89.17%, and in the Gabapentin group was 71.25%, respectively. There was a reduction in the mean pain score in both groups, although no statistically significant difference between the two groups was observed. Both of Topiramate and gabapentin were effective on reduction of pain in diabetic polyneuropathy. We can use both of them separately or in combination with each other or other drugs. © 2018 Tehran University of Medical Sciences. All rights reserved. Acta Med Iran 2018;56(12):764-768.
Mixed Hot-Carrier/Bias Temperature Instability Degradation Regimes in Full {VG, VD} Bias Space: Implications and Peculiarities

Characterizing mixed hot-carrier/bias temperature instability (BTI) degradation in full {<inline-formula> <tex-math notation="LaTeX">$\textit {V}_{\text{G}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\textit {V}_{\text{D}}$ </tex-math></inline-formula>} bias space is a challenging task. Therefore, studies usually focus on individual degradation mechanisms, such as BTI and hot-carrier degradation (HCD). However, a simple superposition of these mechanisms at an arbitrary {<inline-formula> <tex-math notation="LaTeX">$\textit {V}_{\text{G}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\textit {V}_{\text{D}}$ </tex-math></inline-formula>} combination often fails to predict the cumulative damage. We experimentally acquired a large data set covering the full bias space of a pMOSFET which allows us to obtain detailed degradation and recovery maps. Our models for describing oxide and interface defects provide physical insights into the underlying mechanisms and a possible interplay between the degradation modes. Additionally, we perform a dedicated experiment to reveal the implications of different stress regimes onto the various types of defects by switching BTI and HCD stress conditions. The results clearly reveal the conceptual limits of the assumption of independent degradation regimes.
Implementation of an Interactive Environment With Multilevel Wireless Links for Distributed Botanical Garden in University Campus

In this contribution, an end to end system to enable user interaction with a distributed botanical university campus garden is designed, implemented and tested. The proposed system employs different wireless links to collect data related to different bio physiological parameters of both the vegetation mass and the surrounding environment. Detailed analysis of these multilevel communication links is performed by using deterministic volumetric wireless channel estimation and considering underground, near ground and over ground radio propagation conditions. An in-house developed technique enables accurate wireless channel characterization for complete campus scenario considering the multiple link types and all its composing elements. Node definition and network topology is thus obtained by wireless channel analysis of over ground, near ground and underground communication for both 868 MHz and 2.4 GHz Wireless Sensor Networks in an inhomogeneous vegetation environment. Connectivity to enable user interaction as well as for telemetry and tele-control purposes within the campus is achieved by combining ZigBee and LoRaWAN transceivers with the corresponding sensor/actuator platforms. Coverage studies have been performed in order to assess communication capabilities in the set of multiple underground/near ground/over ground links, by means of deterministic channel analysis for the complete university campus location. Measurement results in lab environment as well as full system deployment are presented, showing good agreement with deterministic simulations. Moreover, system level tests have been performed over a physical campus cloud, providing adequate quality of experience metrics. The proposed solution is a scalable system that provides real time trees status monitoring by a cloud-based platform, enabling user interaction within a distributed botanical garden environment in the university campus.