Miracle-dz/UniFAR-FTUs huggingface dataset:
Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation.
A Random Graph Theoretic Framework for Analyzing Instantly Decodable Network Codes

In this paper, we consider Instantly Decodable Network Codes (IDNC) in centralized and cooperative wireless networks. Analyzing the performance of these codes in terms of decoding delay under erasure channel assumption is highly complicated in general. We use some results from random graph theory and apply various relaxations to provide a closed form approximation of the average decoding delay. Our experiments show that the gap between analytical approximation and numerical results is small.
Randomized Crossover Trial of Kangaroo Care to Reduce Biobehavioral Pain Responses in Preterm Infants: A Pilot Study

Kangaroo care (KC), skin-to-skin contact between mother and infant, is a promising method for blunting pain responses. This crossover pilot tested KC effects on biobehavioral responses to heel stick in preterm infants (30—32 weeks’ gestational age, 2—9 days old) measured by Premature Infant Pain Profile (PIPP) and salivary and serum cortisol. Mother—infant dyads were randomly assigned to KC heel stick (KCH) first or incubator heel stick (IH) first. Study 1 (80-min study, N = 18) tested the effect of 80 min of KC before and throughout the heel stick procedure versus incubator care. Study 2 (30-min study, N = 10) tested 30 min of KC before and throughout the heel stick versus incubator care. KCH and IH began during a premeasurement phase and continued through four data collection phases: baseline, heel warming, heel stick, and recovery. PIPP responses were measured every 30 s during data collection; salivary cortisol was measured at the end of baseline and recovery; and serum cortisol was measured during heel stick. Study 1 showed no differences between KCH and IH. Study 2 showed lower PIPP scores at four time points during recovery (p < .05 to p < .001), lower salivary cortisol at the end of recovery (p < .05), and lower serum cortisol during heel stick for the KCH condition (p < .05) as well as clinically lower PIPP scores in the KCH condition during heel stick. Thirty minutes of KC before and throughout the heel stick reduced biobehavioral responses to pain in preterm infants.
Design and Analysis of Full-Duplex Massive MIMO Cellular Networks

This paper provides a theoretical framework for the study of full-duplex (FD) massive multiple- input multiple-output (MIMO) cellular networks over Rician self-interference (SI) and Rayleigh intended and other-interference fading channels. To facilitate bi-directional wireless functionality, we incorporate (i) a downlink (DL) linear zero-forcing with self-interference-nulling (ZF-SIN) precoding scheme at the FD base stations (BSs), and (ii) an uplink (UL) self-interference- aware (SIA) fractional power control mechanism at the FD user equipments (UEs). Linear ZF receivers are further utilized for signal detection in the UL. The results indicate that the UL rate bottleneck in the baseline FD single-antenna system can be elevated by several hundred times via exploiting massive MIMO. On the other hand, the findings may be viewed as a reality-check as the largest spectral efficiency gain from the FD massive MIMO cellular network over its half-duplex (HD) counterpart under state-of-the-art system parameters is shown to be in the region of &#8764;40%.
Ship Detection in Spaceborne Optical Image With SVD Networks

Automatic ship detection on spaceborne optical images is a challenging task, which has attracted wide attention due to its extensive potential applications in maritime security and traffic control. Although some optical image ship detection methods have been proposed in recent years, there are still three obstacles in this task: 1) the inference of clouds and strong waves; 2) difficulties in detecting both inshore and offshore ships; and 3) high computational expenses. In this paper, we propose a novel ship detection method called SVD Networks (SVDNet), which is fast, robust, and structurally compact. SVDNet is designed based on the recent popular convolutional neural networks and the singular value decompensation algorithm. It provides a simple but efficient way to adaptively learn features from remote sensing images. We evaluate our method on some spaceborne optical images of GaoFen-1 and Venezuelan Remote Sensing Satellites. The experimental results demonstrate that our method achieves high detection robustness and a desirable time performance in response to all of the above three problems.
Direct detection of early-stage cancers using circulating tumor DNA

Noninvasive liquid biopsy analysis of circulating tumor DNA permits direct detection of early-stage cancers. Finding smaller needles in haystacks The detection and analysis of cell-free DNA in patients’ blood are becoming increasingly accepted in oncology. However, this approach has generally been applied for the monitoring of patients with existing tumors. It has not been useful for early diagnosis of cancer because of insufficient sensitivity to detect really small tumors that only shed minute quantities of DNA into the blood, as well as difficulties with identifying cancer-associated genetic changes without knowing what mutations are present in the primary tumor. A method developed by Phallen et al., called targeted error correction sequencing, addresses both of these limitations and demonstrates the feasibility of detecting circulating cell-free DNA from many early tumors, suggesting its potential use for cancer screening. Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.
Supporting Multi-Dimensional Naming for NDN Applications

Named Data Networking (NDN) adopts onedimensional hierarchical naming and lookup operations based on longest prefix matching. On the other hand, users may express their requests with multi-dimensional attributes in order to meet the intrinsic spatial- temporal nature of the data existing in IoT applications. To bridge the gap between multi- dimensional user requests and one-dimensional hierarchical names in NDN applications, a novel middleware supporting multi-dimensional naming is designed to support efficient Interest expressions through name translation and optimization, as well as keep original NDN operations unchanged. Simulation experiments show that the proposed solution can improve the content retrieval efficiency and outperform the other baseline schemes in terms of the number of Interest packets and content retrieval time.
Traffic Matrix Prediction and Estimation Based on Deep Learning for Data Center Networks

Network traffic analysis is a crucial technique for systematically operating a data center network. Many network management functions rely on exact network traffic information. Although a great number of works to obtain network traffic have been carried out in traditional ISP networks, they cannot be employed effectively in data center networks. Motivated by that, we focus on the problem of network traffic prediction and estimation in data center networks. We involve deep learning techniques in the network traffic prediction and estimation fields, and propose two deep architectures for network traffic prediction and estimation, respectively. We first use a deep architecture to explore the time-varying property of network traffic in a data center network, and then propose a novel network traffic prediction approach based on a deep belief network and a logistic regression model. Meanwhile, to deal with the highly ill-pose property of network traffic estimation, we further propose a network traffic estimation method using the deep belief network trained by link counts. We validate the effectiveness of our methodologies by real traffic data.
Laplacian Regularized Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery

Collaborative graph-based discriminant analysis (CGDA) has been recently proposed for dimensionality reduction and classification of hyperspectral imagery, offering superior performance. In CGDA, a graph is constructed by ℓ2- norm minimization-based representation using available labeled samples. Different from sparse graph-based discriminant analysis (SGDA) where a graph is built by ℓ1- norm minimization, CGDA benefits from within-class sample collaboration and computational efficiency. However, CGDA does not consider data manifold structure reflecting geometric information. To improve CGDA in this regard, a Laplacian regularized CGDA (LapCGDA) framework is proposed, where a Laplacian graph of data manifold is incorporated into the CGDA. By taking advantage of the graph regularizer, the proposed method not only can offer collaborative representation but also can exploit the intrinsic geometric information. Moreover, both CGDA and LapCGDA are extended into kernel versions to further improve the performance. Experimental results on several different multiple-class hyperspectral classification tasks demonstrate the effectiveness of the proposed LapCGDA.
Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system

A handheld and biocompatible mass spectrometry system provides nondestructive molecular diagnosis of cancer tissue samples. Is the pen mightier than the scalpel? Although a surgeon’s goal is to remove cancer in its entirety during excision surgery, achieving negative margins (absence of cancer cells at the outer edge of the excised tumor specimen) can be challenging. To facilitate intraoperative diagnosis, Zhang et al. developed a handheld pen-like device that rapidly identifies the molecular profile of tissues using a small volume water droplet and mass spectrometry analysis. After 3 s of gentle physical contact with a tissue surface, the water droplet is transported to a mass spectrometer, which characterizes diagnostic proteins, lipids, and metabolites. The pen could be used to rapidly distinguish tumor from healthy tissue during surgery in mice, without requiring specific labeling or imaging and without evidence of tissue destruction. Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.
The antimicrobial peptide SAAP-148 combats drug-resistant bacteria and biofilms

Infections refractory to conventional antibiotics may be targeted by the antimicrobial peptide SAAP-148. New way to keep bacteria at bay Antibiotic resistance is a major threat to public health. To develop a new type of weapon in the arms race against bacteria, de Breij et al. generated a panel of synthetic peptides based on the human antimicrobial peptide LL-37. The lead candidate from this panel, SAAP-148, can kill dangerous antibiotic-resistant pathogens in many contexts, including on ex vivo human skin and in biofilms. Long-term exposure to SAAP-148 did not induce bacterial resistance. Topical application of SAAP-148 could one day be used in hospitals to help patients combat bacteria resistant to traditional antibiotics. Development of novel antimicrobial agents is a top priority in the fight against multidrug-resistant (MDR) and persistent bacteria. We developed a panel of synthetic antimicrobial and antibiofilm peptides (SAAPs) with enhanced antimicrobial activities compared to the parent peptide, human antimicrobial peptide LL-37. Our lead peptide SAAP-148 was more efficient in killing bacteria under physiological conditions in vitro than many known preclinical- and clinical-phase antimicrobial peptides. SAAP-148 killed MDR pathogens without inducing resistance, prevented biofilm formation, and eliminated established biofilms and persister cells. A single 4-hour treatment with hypromellose ointment containing SAAP-148 completely eradicated acute and established, biofilm-associated infections with methicillin-resistant Staphylococcus aureus and MDR Acinetobacter baumannii from wounded ex vivo human skin and murine skin in vivo. Together, these data demonstrate that SAAP-148 is a promising drug candidate in the battle against antibiotic-resistant bacteria that pose a great threat to human health.
Psychiatric morbidity among residents in a home for the elderly in spain: Prevalence of disorder and validity of screening

All residents in a home for elderly válidos (able) in Spain were interviewed and 101 completed the study. Non‐medical interviewers adminstered the GHQ‐28 items and either Zung's Self‐Rating Depression Scale (SDS) (N=69) or the Geriatric Depression Rating Scale (GDS) (N=31). The residents were also examined blind by psychiatrists standardized in the use of the Clinical Interview Scale (CIS), who also administered the ‘Mini‐Examen Cognoscitivo’, the Spanish version of the Mini‐Mental State Examination (MMSE), and diagnosed the identified ‘cases’ according to ICD‐9 criteria. Twenty‐one residents (20.8%) were considered to be ‘cases’ on the basis of the CIS; 14 (13.9%) were diagnosed as depressed and only four (4%) were diagnosed as being demented, although the mean age of the sample was 81.9 years (SD=5.6). Most ‘cases’; were of mild intensity and the differences with ‘non‐cases’; seemed quantitative rather than qualitative. The GHQ‐28 correctly identified 81.5% of ‘cases’; with a cutting score of 5/6 (sensitivity 70%, specificity 84.4%) and 77.4% of ‘cases’; with a cutting score of 4/5 (sensitivity 85%, specificity 75.3%), suggesting a discriminative power almost as good as in adult individuals. In the pilot study, the GDS performed better than the SDS as a screening instrument. The addition of the ‘Mini‐Examen’ would have improved the sensitivity of both the GHQ‐28 items and the SDS.
Glycoconjugate vaccines: Principles and mechanisms

Insight into the mechanisms of glycoconjugate vaccines can improve their efficacy and impact in the future. Bacterial conjugate vaccines are used in infants, adolescents, and the elderly, and they are among the safest and most successful vaccines developed during the last 40 years. Conjugation of polysaccharides to proteins provides T cell epitopes that are necessary in the germinal centers for the affinity maturation of polysaccharide-specific B cells. Collective analysis of data from animal experiments and clinical trials, reviewed with current knowledge of immunology, revealed possible mechanistic explanations that may improve our understanding of conjugate vaccines. Key conclusions are that naïve infants respond differently from adolescents and adults and that most of recommended schedules generate only 10 to 35% of the maximal antibody titer that the vaccine can induce, indicating that the full potential of glycoconjugate vaccines has not yet been reached.
A randomized placebo-controlled pilot trial shows that intranasal vasopressin improves social deficits in children with autism

Intranasal delivery of the neuropeptide vasopressin improves social abilities in children with autism spectrum disorder. Modulating vasopressin in ASD The neuropeptide vasopressin has been implicated in the regulation of social behaviors in animals and humans. The VANILLA clinical trial evaluated balovaptan, an oral selective vasopressin V1a receptor antagonist, in 223 men with autism spectrum disorder (ASD). This 12-week phase 2 trial showed no improvement on the primary endpoint (SRS-2 score) but did show improvement on the secondary outcome measure of adaptive behaviors assessed by the Vineland-II scale (Bolognani et al.). In a related clinical study involving a 4-week intranasal administration of vasopressin to children with ASD, improvements were observed on the SRS-2 primary outcome measure (Parker et al.). Both drugs were well tolerated and had an acceptable safety profile, suggesting that modulating the vasopressin pathway may be a useful therapeutic strategy for ASD. The social impairments of autism spectrum disorder (ASD) have a major impact on quality of life, yet there are no medications that effectively treat these core social behavior deficits. Preclinical research suggests that arginine vasopressin (AVP), a neuropeptide involved in promoting mammalian social behaviors, may be a possible treatment for ASD. Using a double-blind, randomized, placebo-controlled, parallel study design, we tested the efficacy and tolerability of a 4-week intranasal AVP daily treatment in 30 children with ASD. AVP-treated participants aged 6 to 9.5 years received the maximum daily target dose of 24 International Units (IU); participants aged 9.6 to 12.9 years received the maximum daily target dose of 32 IU. Intranasal AVP treatment compared to placebo enhanced social abilities as assessed by change from baseline in this phase 2 trial’s primary outcome measure, the Social Responsiveness Scale, 2nd Edition total score (SRS-2 T score; F1,20 = 9.853; P = 0.0052; ηp2 = 33.0%; Cohen’s d = 1.40). AVP treatment also diminished anxiety symptoms and some repetitive behaviors. Most of these findings were more pronounced when we accounted for pretreatment AVP concentrations in blood. AVP was well tolerated with minimal side effects. No AVP-treated participants dropped out of the trial, and there were no differences in the rate of adverse events reported between treatment conditions. Last, no changes from baseline were observed in vital signs, electrocardiogram tracings, height and body weight, or clinical chemistry measurements after 4 weeks of AVP treatment. These preliminary findings suggest that AVP has potential for treating social impairments in children with ASD.
A Cyto-histopathological Analysis of Oral Mucosal Lesions : with Special Reference to Clinical and Flow Cytometrical Findings

In order to evaluate the diagnostic accuracy of exfoliative cytology (EC) in oral mucosal lesions (OML), we studied it and compared with histopathology, clinical findings and flow cytometrical analysis (FCMA). Two hundred and seventy five smear cases were obtained from 40 normal tissue samples (control) and OML ; leukoplakia (187), exophytic epithelial tumor or verrucous carcinoma (EET or VC) (8) and oral squamous cell carcinoma (OSCC) (40). As for FCMA, the DNA and proliferative indices (D.I. and P.I.) of all cases including the misdiagnoses were calculated. In leukoplakia without dysplasia, the accuracy rate of EC diagnosis was 70.0%, while leukoplakia with dysplasia was 26.7% for mild, 47.6% for moderate, and 84.2% for severe cases, respectively. All EET were misdiagnosed by EC, while OSCC had a 100% accuracy rate. The sparsity of atypical cells, which mostly contributed to the discrepancy in EC diagnosis of the under-diagnostic cases. Erythema, ulcers, Candida, nodular outgrowths and increased number of atypical cells that contributed to the over-diagnostic cases. The mean D.I. of leukoplakia without dysplasia was 1.8,while mild, moderate and severe dysplasias were 2.2, 3.5 and 3.9, and EET or VC and OSCC were 4.3 and 4.5, respectively. The P.I. values also showed the same tendency. Overall, 96 cases were cytologically misdiagnosed where 64 cases were under-diagnosed and 32 cases were over-diagnosed. Exact evaluation was made by flow cytometry (FCM) in 77 of 96 misdiagnostic cases (80.2%) of EC. Accurate diagnosis of OML especially oral epithelial dysplasia by clinical and cytological findings is still difficult to achieve. Mild and moderate dysplasias had lower accuracy rate compared to severe and OSCC cases. Main problems for under-diagnosis of dysplasia include limited number of atypical cells and for over-diagnosis include clinical and cytological findings. The FCMA of leukoplakia without dysplasia and mild dysplasia were significantly close, while EET or VC cases were closer to OSCC results. FCM gave significant results for all EET or VC cases. The authors conclude that FCM, though not a replacement for standard cytological examination or biopsy, would help to lessen the subjective evaluation of OML and in establishing strategies and follow-up protocols for patients with dysplasias and EET or VC. Our studies suggest that combination of EC and FCM is very useful in the evaluation of misdiagnostic cases.