Miracle-dz/UniFAR-FTUs huggingface dataset:
A policy based conflict resolution mechanism for MLB and MRO in LTE self-optimizing networks

Mobility Load Balancing (MLB) and Mobility Robustness Optimization (MRO) are two major SON (Self-Organizing Network) use cases specified for LTE (Long Term Evolution) by 3GPP (3rd Generation Partnership Project). MRO targets at optimizing the handover (HO) performance of the network by adjusting the HO point. Whereas, MLB reduces the congestion in traffic hotspots by advancing HOs from overloaded hotspot cells to less loaded neighbor cells. However, MLB degrades HO performance of the network because advanced HOs lead to worse SINR (Signal-to-Interference plus Noise Ratio) conditions with the target cells as compared to the original HO point. Hence, MLB can trigger MRO to optimize the HO performance and MRO can in turn trigger MLB to adjust the HO point for advanced HOs. Resultantly, MLB and MRO working in parallel can lead to oscillations. In this paper we present a policy based mechanism, termed as MLB-Static, which exploits users' mobility state to minimize the impact of MLB on HO performance and hence prevents oscillations. The simulation results, for a hexagonal LTE macro cellular deployment, show that MLB-Static has negligible impact on HO performance of the network as compared to conventional MLB while the gain of conventional MLB is preserved by MLB-Static.
Neural-network-based human intention estimation for physical human-robot interaction

To realize physical human-robot interaction, it is essential for the robot to understand the motion intention of its human partner. In this paper, human motion intention is defined as the desired trajectory in human limb model, of which the estimation is obtained based on neural network. The proposed method employs measured interaction force, position and velocity at the interaction point. The estimated human motion intention is integrated to the control design of the robot arm. The validity of the proposed method is verified through simulation.
The role of the family in caring for the elderly nursing home resident. A review

Admission to a nursing home for the elderly is a new and difficult phase of life, which can lead to changes in inter-family relationships. Family visits and interaction are often the only communication with the outside world and changes taking place in a society that the elderly used to be part of. The visits reinforce the feeling that the family continues to love, care, and support them, despite their move to the nursing home. Family involvement in support of elderly nursing-home residents is essential, both in the initial stages of the move and later on. In this paper, we reviewed the literature to determine the contribution of a visit of a son/daughter to the elderly. We also attempted to examine the views of multi-professional staff regarding family visits and whether the attitude of the staff to the residents changed as a result of the visits.
DIKNN: An Itinerary-based KNN Query Processing Algorithm for Mobile Sensor Networks

Current approaches to k nearest neighbor (KNN) search in mobile sensor networks require certain kind of indexing support. This index could be either a centralized spatial index or an in-network data structure that is distributed over the sensor nodes. Creation and maintenance of these index structures, to reflect the network dynamics due to sensor node mobility, may result in long query response time and low battery efficiency, thus limiting their practical use. In this paper, we propose a maintenance-free, itinerary-based approach called density-aware itinerary KNN query processing (DIKNN). The DIKNN divides the search area into multiple cone-shape areas centered at the query point. It then performs a query dissemination and response collection itinerary in each of the cone-shape areas in parallel. The design of the DIKNN scheme also takes into account challenging issues such as the the dynamic adjustment of the search radius (in terms of number of hops) according to spatial irregularity or mobility of sensor nodes. The simulation results show that DIKNN yields substantially better performance and scalability over previous work, both as k increases and as the sensor node mobility increases. It outperforms the second runner with up to 50% saving in energy consumption and up to 40% reduction in query response time, while rendering the same level of query result accuracy.
Prevalence of victimization, and associated risk factors, impacting youth with disabilities in Vietnam: a population-based study

Abstract Little research exists on the victimization of youth with disabilities in Asian countries. Yet, developing Asian countries, such as Vietnam, harbor a significant number of youth with disabilities, while services to address their needs often lag behind. The objectives of this study were to: 1) identify the prevalence of reported injuries due to family violence among youth with disabilities in a nationally representative sample of Vietnamese youth, and 2) analyze the relative contribution of disability status and other factors influencing variations in the prevalence of reported injuries. This study employed the 2003 Vietnam Survey Assessment of Vietnamese Youth (VNSAVY), the first nationally representative, population-based survey of 7584 adolescents and young adults in Vietnam. Data collection included face-to-face interviews and self-administered surveys. Weighted bivariate and multiple logistic regressions were used to investigate the relationship among disability, violence, and selected covariates. Results indicated that approximately 14% of Vietnamese youth reported having a disability. Among these youth, approximately 3% reported victimization, in comparison to 2% of able-bodied youth. The odds of youth with disabilities reporting injuries due to family violence remained 50% higher than those without disabilities, controlling for all other variables. Gender and alcohol abuse among family members were also significant risk factors in family violence. Youth with disabilities in developing Asian countries, such as Vietnam, may be vulnerable to physical violence. Preventative programs and services are thus needed to address the unique vulnerabilities of youth with disabilities in developing contexts by screening for victimization experiences and adapting trauma-informed behavioral health services and supports.
A Novel Network Tomography Approach for Traffic Matrix Estimation Problem in Large-Scale IP Backbone Networks

A traffic matrix is an important input for some network management function such as traffic engineering and network planning. However, traffic matrix usually cannot be obtained directly. That is because the existing network traffic motoring techniques do not extremely well in practice. The common approaches for obtaining a traffic matrix are estimating it via other available information, such as link loads and routing information. The approach using link loads and routing information to infer the traffic matrix is named network tomography approach. Due to the ill-posed nature of the network tomography model, the network tomography techniques still face many challenges for the traffic matrix estimation problem. Motivated by this issue, we propose an optimization model to conquer the ill-posed nature of the network tomography model. In details, we first perturb the network tomography model by a stochastic matrix, which draws on idea from compressive sensing techniques. Then the perturbed model can be solve by a convex optimization model. However, this convex optimization cannot precisely estimate the traffic matrix since the coherence of the perturbed model. Then we proposed an improved optimization model by means of the network tomography model.
Novel, Versatile, and Tightly Regulated Expression System for Escherichia coli Strains

ABSTRACT A novel tightly regulated gene expression system was developed for Escherichia coli by applying the regulatory elements of the Pseudomonas putida F1 cym and cmt operons to control target gene expression at the transcriptional level by using p-isopropylbenzoate (cumate) as an inducer. This novel expression system, referred to as the cumate gene switch, includes a specific expression vector, pNEW, that contains a partial T5 phage promoter combined with the Pseudomonas-based synthetic operator and the cymR repressor protein-encoding gene designed to express constitutively in the host strain. The induction of transcription relies on the addition of the exogenous inducer (cumate), which is nontoxic to the culture, water soluble, and inexpensive. The characteristics and potential of the expression system were determined. Using flow cytometry and fed-batch fermentations, we have shown that, with the newly developed cumate-regulated system, (i) higher recombinant product yields can be obtained than with the pET (isopropyl-β-d-thiogalactopyranoside [IPTG])-induced expression system, (ii) expression is tightly regulated, (iii) addition of cumate quickly results in a fully induced and homogenous protein-expressing population in contrast to the bimodal expression profile of an IPTG-induced population, (iv) expression can be modulated by varying the cumate concentration, and (v) the cumate-induced population remains induced and fully expressing even at 8 h following induction, resulting in high yields of the target protein Furthermore, the cumate gene switch described in this article is applicable to a wide range of E. coli strains.
Fast vision-based minimum distance determination between known and unkown objects

We present a method for quickly determining the minimum distance between multiple known and multiple unkown objects within a camera image. Known objects are objects with known geometry, position, orientation, and configuration. Unkown objects are objects which have to be detected by a vision sensor but with unkown geometry, position, orientation and configuration. The known objects are modeled and expanded in 3D and then projected into a camera image. The camera image is classified into object areas including known and unknown objects and into non-object areas. The distance is conservatively estimated by searching for the largest expansion radius where the projected model does not intersect the object areas classified as unknown in the camera image. The method requires only minimal computation times and can be used for surveillance and safety applications.
Removal of mismatched bases from synthetic genes by enzymatic mismatch cleavage

The success of long polynucleotide de novo synthesis is largely dependent on the quality and purity of the oligonucleotides used. Generally, the primary product of any synthesis reaction is directly cloned, and clones with correct products have to be identified. In this study, a novel strategy has been established for removing undesired sequence variants from primary gene synthesis products. Single base-pair mismatches, insertions and deletions were cleaved with specific endonucleases. Three different enzymes—T7 endonuclease I, T4 endonuclease VII and Escherichia coli endonuclease V—have been tested. As a model, a synthetic polynucleotide encoding the bacterial chloramphenicol-acetyltransferase (cat) was synthesized using different methods for one step polynucleotide synthesis based on ligation of oligonucleotides. The influence of enzymatic mismatch cleavage (EMC) as an error correction step on the frequency of correct products was analyzed by functional cloning of the synthetic cat and comparing the error rate with that of untreated products. Significant reduction of all mutation types was observed. Statistical analysis revealed that the T4 and E.coli endonucleases reduced the occurrence of mutations in cloned synthetic gene products. The EMC treatment was successful especially in the removal of deletions and insertions from the primary ligation products.
Genetics of the human face: Identification of large-effect single gene variants

Significance The human face is extraordinarily variable, and the extreme similarity of the faces of identical twins indicates that most of this variability is genetically determined. We have devised an approach to increase the chance of identifying specific large genetic effects on particular facial features, by choosing features with high heritability and selecting individuals with relatively extreme facial phenotypes for comparison with a control population. This has yielded three specific and replicated genetic variants, two for features of facial profiles, and one for the region around the eyes. Further application of these methods should enable the understanding, eventually at the molecular level, of the nature of this extraordinary genetic variability, which is such an important feature of our everyday human interactions. To discover specific variants with relatively large effects on the human face, we have devised an approach to identifying facial features with high heritability. This is based on using twin data to estimate the additive genetic value of each point on a face, as provided by a 3D camera system. In addition, we have used the ethnic difference between East Asian and European faces as a further source of face genetic variation. We use principal components (PCs) analysis to provide a fine definition of the surface features of human faces around the eyes and of the profile, and chose upper and lower 10% extremes of the most heritable PCs for looking for genetic associations. Using this strategy for the analysis of 3D images of 1,832 unique volunteers from the well-characterized People of the British Isles study and 1,567 unique twin images from the TwinsUK cohort, together with genetic data for 500,000 SNPs, we have identified three specific genetic variants with notable effects on facial profiles and eyes.
DYRK1B as therapeutic target in Hedgehog/GLI-dependent cancer cells with Smoothened inhibitor resistance

A wide range of human malignancies displays aberrant activation of Hedgehog (HH)/GLI signaling, including cancers of the skin, brain, gastrointestinal tract and hematopoietic system. Targeting oncogenic HH/GLI signaling with small molecule inhibitors of the essential pathway effector Smoothened (SMO) has shown remarkable therapeutic effects in patients with advanced and metastatic basal cell carcinoma. However, acquired and de novo resistance to SMO inhibitors poses severe limitations to the use of SMO antagonists and urgently calls for the identification of novel targets and compounds. Here we report on the identification of the Dual-Specificity-Tyrosine-Phosphorylation-Regulated Kinase 1B (DYRK1B) as critical positive regulator of HH/GLI signaling downstream of SMO. Genetic and chemical inhibition of DYRK1B in human and mouse cancer cells resulted in marked repression of HH signaling and GLI1 expression, respectively. Importantly, DYRK1B inhibition profoundly impaired GLI1 expression in both SMO-inhibitor sensitive and resistant settings. We further introduce a novel small molecule DYRK1B inhibitor, DYRKi, with suitable pharmacologic properties to impair SMO-dependent and SMO-independent oncogenic GLI activity. The results support the use of DYRK1B antagonists for the treatment of HH/GLI-associated cancers where SMO inhibitors fail to demonstrate therapeutic efficacy.
Crystal structure of mammalian selenocysteine-dependent iodothyronine deiodinase suggests a peroxiredoxin-like catalytic mechanism

Significance Deiodinases activate and inactivate thyroid hormones through a unique biochemical reaction. Enzymes expand their catalytic capabilities through special heteroatoms in cofactors or in the rare but essential amino acid selenocysteine, and deiodinases use an active-site selenocysteine for the reductive elimination of iodide from the aromatic iodothyronine rings. The mechanism of deiodinases has remained elusive despite many mutational and enzymatic studies. We solved the crystal structure of the deiodinase catalytic domain and find that it resembles a family of peroxiredoxin(s) (Prx). Structure and biochemical data suggest a deiodinase catalytic mechanism with Prx-like elements and enable us to assign unexpected functions to residues previously reported to contribute to deiodinase catalysis. Our findings indicate how deiodinases may have evolved from a common reductase ancestor. Local levels of active thyroid hormone (3,3′,5-triiodothyronine) are controlled by the action of activating and inactivating iodothyronine deiodinase enzymes. Deiodinases are selenocysteine-dependent membrane proteins catalyzing the reductive elimination of iodide from iodothyronines through a poorly understood mechanism. We solved the crystal structure of the catalytic domain of mouse deiodinase 3 (Dio3), which reveals a close structural similarity to atypical 2-Cys peroxiredoxin(s) (Prx). The structure suggests a route for proton transfer to the substrate during deiodination and a Prx-related mechanism for subsequent recycling of the transiently oxidized enzyme. The proposed mechanism is supported by biochemical experiments and is consistent with the effects of mutations of conserved amino acids on Dio3 activity. Thioredoxin and glutaredoxin reduce the oxidized Dio3 at physiological concentrations, and dimerization appears to activate the enzyme by displacing an autoinhibitory loop from the iodothyronine binding site. Deiodinases apparently evolved from the ubiquitous Prx scaffold, and their structure and catalytic mechanism reconcile a plethora of partly conflicting data reported for these enzymes.
From intelligibility to behavior

Auditory prominence is defined as when an acoustic segment is made salient in its context. Prominence is one of the prosodic functions that has been shown to be strongly correlated with facial movements. In this work, we investigate the effects of facial prominence cues, in terms of gestures, when synthesized on animated talking heads. In the first study, a speech intelligibility experiment is con- ducted, speech quality is acoustically degraded and the fun- damental frequency is removed from the signal, then the speech is presented to 12 subjects through a lip synchro- nized talking head carrying head-nods and eyebrows raise gestures, which are synchronized with the auditory promi- nence. The experiment shows that presenting prominence as facial gestures significantly increases speech intelligibil- ity compared to when these gestures are randomly added to speech. We also present a follow-up study examining the perception of the behavior of the talking heads when ges- tures are added over pitch accents. Using eye-gaze track- ing technology and questionnaires on 10 moderately hear- ing impaired subjects, the results of the gaze data show that users look at the face in a similar fashion to when they look at a natural face when gestures are coupled with pitch ac- cents opposed to when the face carries no gestures. From the questionnaires, the results also show that these gestures significantly increase the naturalness and the understanding of the talking head.
A geographical solution to scale and aggregation problems in region-building, partitioning and spatial modelling

The paper describes a geographical solution to the scale and aggregation problems frequently encountered in studies of spatially aggregated data. Instead of trying to model the effects of scale and aggregation, the problem is inverted. An attempt is made to identify a set of zones which optimizes an objective function related in some way to the performance of a model subject to whatever constraints may be relevant. In this way scale and aggregation problems become one of optimal-zone design. A heuristic procedure is described which may solve this problem and it is demonstrated by reference to an empirical study. Finally, there is a brief discussion of some of the possible implications for the study of spatially aggregated data and of the role of the optimal-zone design approach in spatial model building. THE conventional approach to spatial analysis involves the application of a model to a study area which has been partitioned into zones. The definition of these zonal boundaries involves the selection of the scale of the study and the aggregation of data to match the choice of scale. In nearly all cases, there are an incredibly large number of alternative scales and aggregations which could be used. It follows, therefore, that spatial data and the patterns and processes they describe are the product of a particular set of zonal boundaries, and that qualitative or quantita- tive studies of spatial data are not invariant with the choice of these boundaries. Scale is an abstract concept which cannot be easily measured except in relative terms. The best surrogates are probably the size and number of zones used to partition a study area. The scale problem arises because of uncertainty about the number of zones needed for a particular study. The aggregation problem arises because of uncertainty about how the data is to be aggre- gated to form a given number of zones. These problems always occur in the design of zones for the study of spatial data; and the two together represent one of the greatest unsolved problems facing spatial study today. Current zone design procedures are typically haphazard. Zones are mainly based on considerations of convenience and the existence of readily available data, but on occasions may be selected at a certain scale in order to isolate a particular spatial pattern. However, in many cases current knowledge of spatial phenomena is insufficient to define with any precision the scale and the aggregation needed. In other studies zone design is not regarded as being very important, and the relationship between the choice of zones and the results is seldom investigated, even when the data is sufficient for such a study. It is suggested, therefore, that the distribution of zone-dependent results may be widespread throughout the geographical literature, wreaking havoc with at least some of it. The purpose of this paper is to provide a geographical solution to certain aspects of the
Preparation of finasteride capsules-loaded drug nanoparticles: formulation, optimization, in vitro, and pharmacokinetic evaluation

In this study, optimized freeze-dried finasteride nanoparticles (NPs) were prepared from drug nanosuspension formulation that was developed using the bottom–up technique. The effects of four formulation and processing variables that affect the particle size and solubility enhancement of the NPs were explored using the response surface optimization design. The optimized formulation was morphologically characterized using transmission electron microscopy (TEM). Physicochemical interaction among the studied components was investigated. Crystalline change was investigated using X-ray powder diffraction (XRPD). Crystal growth of the freeze-dried NPs was compared to the corresponding aqueous drug nanosuspension. Freeze-dried NPs formulation was subsequently loaded into hard gelatin capsules that were examined for in vitro dissolution and pharmacokinetic behavior. Results revealed that in most of the studied variables, some of the quadratic and interaction effects had a significant effect on the studied responses. TEM image illustrated homogeneity and shape of the prepared NPs. No interaction among components was noticed. XRPD confirmed crystalline state change in the optimized NPs. An enhancement in the dissolution rate of more than 2.5 times from capsules filled with optimum drug NPs, when compared to capsules filled with pure drug, was obtained. Crystal growth, due to Ostwald ripening phenomenon and positive Gibbs free energy, was reduced following lyophilization of the nanosuspension formulation. Pharmacokinetic parameters from drug NPs were superior to that of pure drug and drug microparticles. In conclusion, freeze-dried NPs based on drug nanosuspension formulation is a successful technique in enhancing stability, solubility, and in vitro dissolution of poorly water-soluble drugs with possible impact on the drug bioavailability.