Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Distributed Compression of Symmetrically Correlated Gaussian Sources

Consider a lossy compression system with <inline-formula> <tex-math notation="LaTeX">$\ell $ </tex-math></inline-formula>-distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under the mean-squared-error distortion constraint. It is assumed that the observed sources can be expressed as the sum of the target signals and the corruptive noises, which are generated independently from two symmetric multivariate Gaussian distributions. Depending on the parameters of such distributions, the rate-distortion limit of this system is characterized either completely or at least for sufficiently low distortions. The results are further extended to the robust distributed compression setting, where the outputs of a subset of encoders may also be used to produce a non-trivial reconstruction of the corresponding target signals. In particular, we obtain in the high-resolution regime a precise characterization of the minimum achievable reconstruction distortion based on the outputs of <inline-formula> <tex-math notation="LaTeX">$k+1$ </tex-math></inline-formula> or more encoders when every <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> out of all <inline-formula> <tex-math notation="LaTeX">$\ell $ </tex-math></inline-formula> encoders are operated collectively in the same mode that is greedy in the sense of minimizing the distortion incurred by the reconstruction of the corresponding <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> target signals with respect to the average rate of these <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> encoders.
Improving wait time from referral to opiate replacement therapy in a drug recovery service

While the reported incidence of heroin use in the UK has reduced, related hospital admissions and associated mortality have continued to increase. Prompt access to treatment (opiate replacement therapy (ORT) and counselling support) have been shown to reduce risk and offer clients the optimal route to recovery. The Specialist Drug and Alcohol Recovery Service (Osprey House) within National Health Service Highland had lengthy delays from referral to commencing ORT (median wait 56 days), which this project aimed to reduce. A rapid process improvement workshop (RPIW) was undertaken to redesign the patient pathway from referral to recovery. The RPIW consisted of three phases: phase I, planning and preparation (12 weeks before the workshop week); phase II, the workshop week; and phase III, the follow-up. Metrics included the lead time from referral to initiating ORT and other process measures at baseline, and then repeated at 30, 60, 90 and 180 days, respectively. Additionally, data were routinely collected on the percentage of clients treated within 3 weeks, as was weekly data on the new process of screening clients within 1 day of referral. Multiple lean tools and techniques, including Plan, Do, Study, Act cycles, were used to test and implement new ways of working. Results at 180 days found the median time from referral to initiating ORT improved from a baseline of 56 to 21 days (63% improvement), room usage improved from 49% to 65% (32% increase) and standard work improved from level 1 to level 3. Increases in the number of clients treated within 3 weeks were demonstrated. Other metrics remained static or reported fluctuations too inconsistent to claim improvement at this point. By applying the Lean principles of removing waste and increasing value, we have redesigned our service, reducing the length of time clients with drug problems wait from referral to commencing ORT.
Rationale and Plan for Vitamin D Food Fortification: A Review and Guidance Paper

Vitamin D deficiency can lead to musculoskeletal diseases such as rickets and osteomalacia, but vitamin D supplementation may also prevent extraskeletal diseases such as respiratory tract infections, asthma exacerbations, pregnancy complications and premature deaths. Vitamin D has a unique metabolism as it is mainly obtained through synthesis in the skin under the influence of sunlight (i.e., ultraviolet-B radiation) whereas intake by nutrition traditionally plays a relatively minor role. Dietary guidelines for vitamin D are based on a consensus that serum 25-hydroxyvitamin D (25[OH]D) concentrations are used to assess vitamin D status, with the recommended target concentrations ranging from ≥25 to ≥50 nmol/L (≥10–≥20 ng/mL), corresponding to a daily vitamin D intake of 10 to 20 μg (400–800 international units). Most populations fail to meet these recommended dietary vitamin D requirements. In Europe, 25(OH)D concentrations <30 nmol/L (12 ng/mL) and <50 nmol/L (20 ng/mL) are present in 13.0 and 40.4% of the general population, respectively. This substantial gap between officially recommended dietary reference intakes for vitamin D and the high prevalence of vitamin D deficiency in the general population requires action from health authorities. Promotion of a healthier lifestyle with more outdoor activities and optimal nutrition are definitely warranted but will not erase vitamin D deficiency and must, in the case of sunlight exposure, be well balanced with regard to potential adverse effects such as skin cancer. Intake of vitamin D supplements is limited by relatively poor adherence (in particular in individuals with low-socioeconomic status) and potential for overdosing. Systematic vitamin D food fortification is, however, an effective approach to improve vitamin D status in the general population, and this has already been introduced by countries such as the US, Canada, India, and Finland. Recent advances in our knowledge on the safety of vitamin D treatment, the dose-response relationship of vitamin D intake and 25(OH)D levels, as well as data on the effectiveness of vitamin D fortification in countries such as Finland provide a solid basis to introduce and modify vitamin D food fortification in order to improve public health with this likewise cost-effective approach.
Changes in gene expression as one of the key mechanisms involved in radiation-induced bystander effect

The radiation-induced bystander effect (RIBE) refers to the manifestation of responses by non-targeted/non-hit cells or tissues situated in proximity to cells and tissues directly exposed to ionizing radiation (IR). The RIBE is elicited by agents and factors released by IR-hit cells. The growing body of data suggests that the underlying mechanisms of the RIBE are multifaceted depending both on the biological (characteristics of directly IR-exposed cells, bystander cells, intercellular milieu) and the physical (dose, rate and type of IR, time after exposure) factors/parameters. Although the exact identity of bystander signal(s) is yet to be identified, the published data indicate changes in gene expression for multiple types of RNA (mRNA, microRNA, mitochondrial RNA, long non-coding RNA, small nucleolar RNA) as being one of the major responses of cells and tissues in the context of the RIBE. Gene expression profiles demonstrate a high degree of variability between distinct bystander cell and tissue types. These alterations could independently, or in a signaling cascade, result in the manifestation of readily observable endpoints, including changes in viability and genomic instability. Here, the relevant publications on the gene candidates and signaling pathways involved in the RIBE are reviewed, and a framework for future studies, both in vitro and in vivo, on the genetic aspect of the RIBE is provided.
Insulating chitosan/casein multilayers on corona charged polylactic acid substrates

The influence of the structure and physico-chemical properties of chitosan/casein multilayer films on their potential use for drug delivery systems was investigated. The multilayer films were prepared using layer-by-layer self-assembly, whereby chitosan and casein were deposited onto poly(lactic acid) substrates pretreated with either a positive or a negative corona. The corona discharge system consisted of a corona electrode, a grounded plate and a grid. The deposition was studied by ATR FT-IR, AFM, and surface energy measurements. ATR FT-IR spectra proved the formation of polyelectrolyte chitosan — casein complexes. The increasing content of chitosan and casein with increasing number of bilayers was further confirmed by XPS analysis. The surface topography was examined by AFM and the average roughness was evaluated. A comparative analysis of the experimental results was performed and the most appropriate substrate corona treatment for the irreversible binding of the chitosan/casein polyelectrolytes was determined.
Herpes Simplex Virus Colitis in a Patient with Newly Diagnosed Crohn's Disease

Herpesvirus colitis is a known cause of morbidity and mortality amongst immunosuppressed individuals. We present a case of HSV colitis following a diagnosis of Crohn's Disease and methylprednisolone therapy. Diagnosis was confirmed by immunohistochemical staining and supported by polymerase chain reaction (PCR) of cutaneous vesicles. The patient recovered following three weeks of acyclovir.
Contextual Memory Trees

We design and study a Contextual Memory Tree (CMT), a learning memory controller that inserts new memories into an experience store of unbounded size. It is designed to efficiently query for memories from that store, supporting logarithmic time insertion and retrieval operations. Hence CMT can be integrated into existing statistical learning algorithms as an augmented memory unit without substantially increasing training and inference computation. Furthermore CMT operates as a reduction to classification, allowing it to benefit from advances in representation or architecture. We demonstrate the efficacy of CMT by augmenting existing multi-class and multi-label classification algorithms with CMT and observe statistical improvement. We also test CMT learning on several image-captioning tasks to demonstrate that it performs computationally better than a simple nearest neighbors memory system while benefitting from reward learning.
Distributed kNN Query Authentication

With the prevalence of location-based services and geo-functioned devices, the trend of spatial data outsourcing is rising. In the data outsourcing scenario, result integrity must be ensured by means of a query authentication scheme. However, most of the existing studies are confined to a centralized environment. In this paper, we investigate the query authentication problem in distributed environments and focus on the k nearest neighbor (kNN) query, which is widely used in spatial data analytics. We design a new distributed spatial authenticated data structure (ADS), distributed MR-tree, to facilitate efficient kNN processing. Furthermore, we propose a basic algorithm to process authenticated kNN queries based on the new ADS. Apart from the results, some verification objects are generated to guarantee the results' integrity. We also design two optimized algorithms to reduce the size of verification objects as well as the verification cost. Our experiments validate the good performance of the proposed techniques in terms of query cost, communication overhead, and verification time.
Urology as rehabilitation medicine: a literature review

As a urologist, we usually encounter with two representative functional behaviors, namely, voiding and sexual function. These are not only important but also complex and synchronized so if these functions are impaired, patients need active functional rehabilitation to recover. These functional impairments should be recognized and corrected early because they could not only cause direct damage to the affected functions but also have harmful consecutive consequences such as kidney damage due to voiding abnormality and self-esteem damage due to decreased sexual function. Numerous rehabilitative methods are currently available, which help minimize the negative effects of these functional impairments. In terms of voiding function, pelvic floor muscle exercise, biofeedback, functional magnetic stimulation, neuromodulation, and clean intermittent self-catheterization are representative rehabilitation modalities. In case of children, extra-attention should be paid because this might affect their entire life. In impairment of sexual function, early intervention to maintain male erection is the main target of rehabilitation to prevent corporal fibrosis and penile deformity and increase recovery chance in patients who underwent radical prostatectomy or major surgery. In this review, we will elucidate various rehabilitation methods in urology to further increase our understanding of the rehabilitative characteristics of urology and widen our view of rehabilitation medicine.
Tip Over Community: Backbone Nodes Detection Based on Community Structure

Key nodes detection is conducive to the information promotion and public opinion monitoring. Traditional works mainly focus on the nodes affecting the breadth of information diffusion. However, there are several works concentrate on the depth of information diffusion. Breadth dictates the number of nodes receiving information in one-hop propagation. Depth implies the length of the retweeting cascade of information and the number of social circles getting information. Depth is as important as breadth, for the nodes which contribute to the depth of information diffusion can promote society propagation (SP). If we have a good control of these nodes, information will ignite the community and minority will tip over the cognitive of the group. The purpose of this paper is to identify the influential nodes which can influence the SP in breadth and depth. With the analysis of SP, we proposed backbone node detection based on community structure (BNDCS) to detect these nodes. In this paper, we defined backbone nodes (BNs) by the location feature and the process of information diffusion. Besides, we presented a cohesion subgroup detection method based on hybrid seed expansion. It can adapt the network with no significant community structure and fit the star topology well. We proposed an information tension factor to measure the influence of bridge nodes. Through the experiment contrasts, the BNDCS is superior to compared methods. It showed that the BNs play a critical role in SP. Therefore, monitoring the BNs can prevent the mass incidents occurring and stop the spread of panic.
Comparison of the clinical outcome of frozen-thawed embryo transfer with and without pretreatment with a gonadotropin-releasing hormone agonist

Objective To describe the clinical outcomes of frozen-thawed embryo transfer (FET) with artificial preparation of the endometrium, using a combination of estrogen (E2) and progesterone (P4) with or without a gonadotropin-releasing hormone agonist (GnRHa), and the modified natural cycle (MNC) with human chorionic gonadotropin (hCG) trigger. Methods In this retrospective study, we evaluated 187 patients during 3 years (February 2012–April 2015). The patients were allocated to the following treatment groups: group A, comprising 113 patients (181 cycles) who received GnRHa+E2+P4; group B, comprising 49 patients (88 cycles) who received E2+P4; and group C, comprising 25 patients (42 cycles) who received hCG+P4. The inclusion criteria were regular menstrual cycles (length 24–35 days) and age 21–45 years. Results The primary outcome of the study — implantation rate (IR) per embryo transferred — was not statistically different among the 3 groups. Similar results were found for the IRs with fetal heartbeat per embryo transferred (68/181 [37.6%] in group A vs. 22/88 [25.0%] in group B vs. 14/42 [33.3%] in group C) and for the live birth rates (LBRs) per embryo transferred (56/181 [30.9%] in group A vs. 18/88 [20.5%] in group B vs. 11/42 [26.2%] in group C). Conclusion Although the pregnancy outcomes were better in the hormone therapy with GnRHa group, hormone therapy FET with GnRHa for pituitary suppression did not result in significantly improved IRs and LBRs when compared with hormone therapy FET without GnRHa or MNC FET.
Expression of a Plastid-Targeted Flavodoxin Decreases Chloroplast Reactive Oxygen Species Accumulation and Delays Senescence in Aging Tobacco Leaves

Leaf senescence is a concerted physiological process involving controlled degradation of cellular structures and reallocation of breakdown products to other plant organs. It is accompanied by increased production of reactive oxygen species (ROS) that are proposed to signal cell death, although both the origin and the precise role of ROS in the execution of this developmental program are still poorly understood. To investigate the contribution of chloroplast-associated ROS to natural leaf senescence, we used tobacco plants expressing a plastid-targeted flavodoxin, an electron shuttle flavoprotein present in prokaryotes and algae. When expressed in plants, flavodoxin specifically prevents ROS formation in chloroplasts during stress situations. Senescence symptoms were significantly mitigated in these transformants, with decreased accumulation of chloroplastic ROS and differential preservation of chlorophylls, carotenoids, protein contents, cell and chloroplast structures, membrane integrity and cell viability. Flavodoxin also improved maintenance of chlorophyll-protein complexes, photosynthetic electron flow, CO2 assimilation, central metabolic routes and levels of bioactive cytokinins and auxins in aging leaves. Delayed induction of senescence-associated genes indicates that the entire genetic program of senescence was affected by flavodoxin. The results suggest that ROS generated in chloroplasts are involved in the regulation of natural leaf senescence.
Identification of DAPK1 Promoter Hypermethylation as a Biomarker for Intra-Epithelial Lesion and Cervical Cancer: A Meta-Analysis of Published Studies, TCGA, and GEO Datasets

Background: Promoter hypermethylation in death-associated protein kinase 1 (DAPK1) gene has been long linked to cervical neoplasia, but the established results remained controversial. Here, we performed a meta-analysis to assess the associations of DAPK1 promoter hypermethylation with low-grade intra-epithelial lesion (HSIL), high-grade intra-epithelial lesion (HSIL), cervical cancer (CC), and clinicopathological features of CC. Methods: Published studies with qualitative methylation data were initially searched from PubMed, Web of Science, EMBASE, and China National Knowledge Infrastructure databases (up to March 2018). Then, quantitative methylation datasets, retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, were pooled to validate the results of published studies. Results: In a meta-analysis of 37 published studies, DAPK1 promoter hypermethylation progressively increased the risk of LSIL by 2.41-fold (P = 0.012), HSIL by 7.62-fold (P < 0.001), and CC by 23.17-fold (P < 0.001). Summary receiver operating characteristic curves suggested a potential diagnostic value of DAPK1 promoter hypermethylation in CC, with a large area-under-the-curve of 0.83, a high specificity of 97%, and a moderate sensitivity of 59%. There were significant impacts of DAPK1 promoter hypermethylation on histological type (odds ratio (OR) = 3.53, P < 0.001) and FIGO stage of CC (OR = 2.15, P = 0.003). Then, a pooled analysis of nine TCGA and GEO datasets, covering 13 CPG sites within DAPK1 promoter, identified eight CC-associated sites, six sites with diagnostic values for CC (pooled specificities: 74–90%; pooled sensitivities: 70–81%), nine loci associated with the histological type of CC, and all 13 loci with down-regulated effects on DAPK1 mRNA expression. Conclusion: The meta-analysis suggests that DAPK1 promoter hypermethylation is significantly associated with the disease severity of cervical neoplasia. DAPK1 methylation detection exhibits a promising ability to discriminate CC from cancer-free controls.
CDKN3 expression is an independent prognostic factor and associated with advanced tumor stage in nasopharyngeal carcinoma

Background: Through data mining from the public transcriptome of NPC, cyclin-dependent kinase inhibitor 3 (CDKN3) was identified as a significantly upregulated gene in NPC. CDKN3 functions as a key factor in cell cycle regulation. This study was aimed to investigate the expression of CDKN3 in NPC tissues and its prognostic significance. Methods: Immunohistochemistry was performed for 124 NPC patients to assess the protein expression of CDKN3. The stainings of CDKN3 were scored by using H-score method. The relationships between CDKN3 expression status and clinicopathological parameters, disease-specific survival (DSS), distant metastasis-free survival (DMeFS), and local recurrence-free survival (LRFS) were statistically analyzed. Results: High expression of CDKN3 was significantly associated with higher primary nodal status (P=0.030) and higher TNM stage (P=0.019). In univariate analysis, high expression of CDKN3 predicted worse DSS (P<0.0001), DMeFS (P<0.0001), and LRFS (P<0.0001). In multivariate analysis, CDKN3 overexpression still acted as an independent prognostic factor for worse DSS (P<0.001; hazard ratio [HR]=11.999, 95% CI: 5.378-26.771), DMeFS (P<0.001; HR=15.069, 95% CI: 5.884-38.592), and LRFS (P<0.001; HR=5.000, 95% CI: 2.312-10.815). Conclusion: High expression of CDKN3 was an independent negative prognostic factor for NPC and was associated with advanced disease status. It might serve as potential therapeutic target and aid in risk stratification for patients with NPC.
Neural Network-Based Uncertainty Quantification: A Survey of Methodologies and Applications

Uncertainty quantification plays a critical role in the process of decision making and optimization in many fields of science and engineering. The field has gained an overwhelming attention among researchers in recent years resulting in an arsenal of different methods. Probabilistic forecasting and in particular prediction intervals (PIs) are one of the techniques most widely used in the literature for uncertainty quantification. Researchers have reported studies of uncertainty quantification in critical applications such as medical diagnostics, bioinformatics, renewable energies, and power grids. The purpose of this survey paper is to comprehensively study neural network-based methods for construction of prediction intervals. It will cover how PIs are constructed, optimized, and applied for decision-making in presence of uncertainties. Also, different criteria for unbiased PI evaluation are investigated. The paper also provides some guidelines for further research in the field of neural network-based uncertainty quantification.
A Cross-Layer Security Monitoring Selection Algorithm Based on Traffic Prediction

Intrusion detection system (IDS) is emerging as a technology to improve the security of vehicular ad hoc network. However, the recent research on performance of IDS indicates that monitoring overhead is still a significant issue and challenge. The fundamental problem is caused by the fact that each node repeatedly detects adjacent nodes during operation. At the same time, monitoring results are sent to other nodes in the form of control packets, resulting in the decline of the network throughput. In this paper, we focus on selecting a bunch of monitoring nodes and propose a cross-layer security monitoring selection algorithm based on traffic prediction (CLSM-TP). Instead of repeatedly detection for each node, we select the monitoring node whose idle degree is relatively high by predicting the node’s traffic based on a cross-layer vehicular ad hoc network. Moreover, the proposed algorithm leverages the mutual information and residual energy to optimize the node selection through social network analysis. The noteworthy contributions are that CLSM-TP can balance the resource consumption among all nodes and prolong the lifetime of vehicular ad hoc network to some extent. Our experimental results show that, the monitoring nodes selected by the algorithm proposed in this paper with higher idle degree preform good enough to monitor the whole vehicular ad hoc network.