Miracle-dz/UniFAR-FTUs huggingface dataset:
Compact Dual‐Band Multi‐Focal Diffractive Lenses

This paper presents the design, fabrication, and characterization of dual‐band multi‐focal diffractive microlenses with sub‐wavelength thickness and the capability to simultaneously focus visible and near‐infrared spectral bands at two different focal positions. This technology utilizes high‐index and low‐loss sputtered hydrogenated amorphous Si, enabling a sub‐wavelength thickness of only 235 nm. Moreover, the proposed flat lens concept is polarization insensitive and can be readily designed to operate across any desired wavelength regime. Imaging under unpolarized broadband illumination with independent focal planes for two targeted spectral bands is experimentally demonstrated, enabling the encoding of the depth information of a sample into different spectral images. In addition, with a small footprint of only 100 µm and a minimum feature size of 400 nm, the proposed dual‐band multi‐focal diffractive microlenses can be readily integrated with vertical detector arrays to simultaneously concentrate and spectrally select electromagnetic radiation. This approach provides novel opportunities for spectroscopic and multispectral imaging systems with advanced detector architectures.
A Survey of 6G Wireless Communications: Emerging Technologies

While fifth-generation (5G) communications are being rolled out around the world, sixth-generation (6G) communications have attracted much attention from both the industry and academia. Compared with 5G, 6G will have a wider frequency band, higher transmission rate, spectrum efficiency, greater connection capacity, shorter delay, wider coverage and stronger anti-interference capability, so as to meet the various network requirements for industries. In this paper, we present a survey of potential essential technologies in 6G. In particular, we will introduce artificial intelligence, intelligent surfaces, terahertz communications technologies in detail, while giving a brief introduction to other potential technologies, including visible light communications, Blockchain-enabled wireless network, advanced duplex and holographic radio.
Organ at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search

OAR segmentation is a critical step in radiotherapy of head and neck (H&N) cancer, where inconsistencies across radiation oncologists and prohibitive labor costs motivate automated approaches. However, leading methods using standard fully convolutional network workflows that are challenged when the number of OARs becomes large, e.g. > 40. For such scenarios, insights can be gained from the stratification approaches seen in manual clinical OAR delineation. This is the goal of our work, where we introduce stratified organ at risk segmentation (SOARS), an approach that stratifies OARs into anchor, mid-level, and small & hard (S&H) categories. SOARS stratifies across two dimensions. The first dimension is that distinct processing pipelines are used for each OAR category. In particular, inspired by clinical practices, anchor OARs are used to guide the mid-level and S&H categories. The second dimension is that distinct network architectures are used to manage the significant contrast, size, and anatomy variations between different OARs. We use differentiable neural architecture search (NAS), allowing the network to choose among 2D, 3D or Pseudo-3D convolutions. Extensive 4-fold cross-validation on 142 H&N cancer patients with 42 manually labeled OARs, the most comprehensive OAR dataset to date, demonstrates that both pipeline- and NAS-stratification significantly improves quantitative performance over the state-of-the-art (from 69.52% to 73.68% in absolute Dice scores). Thus, SOARS provides a powerful and principled means to manage the highly complex segmentation space of OARs.
Headless Horseman: Adversarial Attacks on Transfer Learning Models

Transfer learning facilitates the training of task-specific classifiers using pre-trained models as feature extractors. We present a family of transferable adversarial attacks against such classifiers, generated without access to the classification head; we call these headless attacks. We first demonstrate successful transfer attacks against a victim network using only its feature extractor. This motivates the introduction of a label-blind adversarial attack. This transfer attack method does not require any information about the class-label space of the victim. Our attack lowers the accuracy of a ResNet18 trained on CIFAR10 by over 40%.
Prove Costa's Entropy Power Inequality and High Order Inequality for Differential Entropy with Semidefinite Programming

Costa's entropy power inequality is an important generalization of Shannon's entropy power inequality. Related with Costa's entropy power inequality and a conjecture proposed by McKean in 1966, Cheng-Geng recently conjectured that $D(m,n): (-1)^{m+1}(\partial^m/\partial^m t)H(X_t)\ge0$, where $X_t$ is the $n$-dimensional random variable in Costa's entropy power inequality and $H(X_t)$ the differential entropy of $X_t$. $D(1,n)$ and $D(2,n)$ were proved by Costa as consequences of Costa's entropy power inequality. Cheng-Geng proved $D(3,1)$ and $D(4,1)$. In this paper, we propose a systematical procedure to prove $D(m,n)$ and Costa's entropy power inequality based on semidefinite programming. Using software packages based on this procedure, we prove $D(3,n)$ for $n=2,3,4$ and give a new proof for Costa's entropy power inequality. We also show that with the currently known constraints, $D(5,1)$ and $D(4,2)$ cannot be proved with the procedure.
The Dekel-Zhao profile: a mass-dependent dark-matter density profile with flexible inner slope and analytic potential, velocity dispersion, and lensing properties

We explore a function with two shape parameters for the dark-matter halo density profile subject to baryonic effects, which is a special case of the general Zhao family of models applied to simulated dark-matter haloes by Dekel et al. This profile has variable inner slope and concentration parameter, and analytic expressions for the gravitational potential, velocity dispersion, and lensing properties. Using the Numerical Investigation of a Hundred Astrophysical Objects cosmological simulations, we find that it provides better fits than the Einasto profile and the generalized NFW profile with variable inner slope, in particular towards the halo centres. We show that the profile parameters are correlated with the stellar-to-halo mass ratio Mstar/Mvir. This defines a mass-dependent density profile describing the average dark-matter profiles in all galaxies, which can be directly applied to observed rotation curves of galaxies, gravitational lenses, and semi-analytic models of galaxy formation or satellite–galaxy evolution. The effect of baryons manifests itself by a significant flattening of the inner density slope and a 20 per cent decrease of the concentration parameter for Mstar/Mvir = 10−3.5–10−2, corresponding to $M_{\rm star} \! \sim \! 10^{7-10}\, \mathrm{ M}_\odot$. The accuracy by which this profile fits simulated galaxies is similar to certain multiparameter mass-dependent profiles, but its fewer parameters and analytic nature make it most desirable for many purposes.
Fixed point combinators as fixed points of higher-order fixed point generators

Corrado B\"ohm once observed that if $Y$ is any fixed point combinator (fpc), then $Y(\lambda yx.x(yx))$ is again fpc. He thus discovered the first "fpc generating scheme" -- a generic way to build new fpcs from old. Continuing this idea, define an $\textit{fpc generator}$ to be any sequence of terms $G_1,\dots,G_n$ such that \[ Y \in FPC \Rightarrow Y G_1 \cdots G_n \in FPC \] In this contribution, we take first steps in studying the structure of (weak) fpc generators. We isolate several robust classes of such generators, by examining their elementary properties like injectivity and (weak) constancy. We provide sufficient conditions for existence of fixed points of a given generator $(G_1,\cdots,G_n)$: an fpc $Y$ such that $Y = Y G_1 \cdots G_n$. We conjecture that weak constancy is a necessary condition for existence of such (higher-order) fixed points. This statement generalizes Statman's conjecture on non-existence of "double fpcs": fixed points of the generator $(G) = (\lambda yx.x(yx))$ discovered by B\"ohm. Finally, we define and make a few observations about the monoid of (weak) fpc generators. This enables us to formulate new a conjecture about their structure.
High-speed x-ray imaging with single-pixel detector

We demonstrate experimentally the ability to use a single pixel detector for two-dimensional high-speed and high-resolution x-ray imaging. We image the rotation of a spinning chopper at 100-kHz at spatial resolution of about 15 microns by using the computational ghost imaging approach. The technique we develop can be used for the imaging of high-speed periodic dynamics or periodically stimulated effects with a large field of view and at low dose.
Android Botnet Detection Using Risk Assessment

The increasing popularity of Android mobile phones in recent years has attracted the attention of malware developers. Android applications (apps) pose many risks/threats to the user’s privacy and system integrity. Currently, permission-based models are used in the Android systems to detect the dangerous apps that possess several weaknesses. In this paper, a new risk assessment method is proposed to evaluate the amount of risk associated with every app in terms of privacy risk, financial risk, and smartphones system risk. It focused on the GPS exploitation for Android botnet detection. The assessment was based on static analysis that used features set permission and API calls. The quantitative calculation model was used as a method to differentiate between the benign and botnet apps. Every app was assessed for risk based on five categories such as Very High, High, Medium, Low and Very Low. Two datasets with 2694 Android botnet samples from Drebin and 774 benign apps from Google Play were used to evaluate the effectiveness of this method. The obtained results demonstrate that the proposed method is good in differentiating the Android botnet and benign apps based on the risk level. This will give a promising impression to the users during apps installation.
Printing Direction Optimization Through Slice Number and Support Minimization

One major drawback of 3D printing technologies is the low printing efficiency. In general, it takes 8–12 hours to print a normal 3D model. 3D printing technologies manufacture objects layer by layer where each layer is composed of one or more closed 2D polygons (named as slices in this work). As a result, the number of slices will directly affects the printing time. In addition, most 3D printing technologies need extra supporting structures to support overhang regions during printing, such as Fused Deposition Modeling (FDM), which will largely increase manufacturing time. We observe that both the slicing number and the amount of supporting structures are affected by printing direction. In this work, a novel printing direction optimization algorithm is proposed based on the amount of slices and overhang areas. In the proposed method, Genetic Algorithm is used to obtain optimal printing direction where the fitness function is designed as the weighted slice number and overhang areas. Experimental results show that the proposed algorithm is able to obtain an optimal printing direction to reduce the number of slices and overhang areas.
Two-Layer Game Based Resource Allocation in Cloud Based Integrated Terrestrial-Satellite Networks

This paper investigates the cooperative transmission and resource allocation in cloud based integrated terrestrial-satellite networks, where a resource pool at the cloud acts as the integrated resource management and control center of the entire network. Considering the operator offers two levels of services of different quality of service (QoS) and price, we formulate a two-layer game based resource allocation problem to maximize the utility of the operator, which is composed of the Stackelberg game between the operator and users, the evolutionary game between all users, and the energy minimization problem. By solving the evolutionary game with replicator dynamics, the selections of users are obtained for any pricing strategy. Then, based on the service selections of users, the energy minimization problem is solved to allocate power and computation resources among users while satisfying the QoS constraints. By analyzing the evolution relationship between the utility and the pricing strategy, we eventually find the Stackelberg equilibrium point of the system, and obtain the optimal pricing as well as the resource allocation strategies for the operator. Finally, numerical results are provided to analyze the behavior of users in the game model, and evaluate the performance of the optimal pricing and resource allocation strategies.
Hyperspectral image compressive reconstruction with low-rank tensor constraint

Abstract. Under the condition of a low sampling rate, hyperspectral image (HSI) reconstruction faces important challenges in remote sensing. How to efficiently process HSI data is an urgent problem to be solved. We propose a hyperspectral image compressive sensing reconstruction (HSI-CSR) model based on tensor decomposition and a low-rank constraint. This model can efficiently exploit the underlying structure information in the HSI. Specifically, we study how to exploit reasonably the low-rank constraint of the core tensor and nonlocal self-similarity, respectively, to explore the nonlocal spatial–spectral similarity hidden in an HSI. To solve the proposed HSI-CSR model, we design an efficient algorithm based on the alternating direction method of multipliers knowledge. Finally, extensive simulations show that the proposed model achieves superior reconstruction performance, compared with other state-of-the-art methods.
Performance enhancement of DC/DC converters for solar powered EV

The paper initially presents the essential drive arrangement required for electric vehicle. It requests high power bidirectional stream ability, with wide info voltage range, and yield voltage of vitality stockpiling gadgets, for example, super capacitors or batteries shift with the adjustment in stack. At that point the tenacity and outline of previously mentioned converter is proposed in this paper. The converter which relates a half extension topology, has high power stream ability and least gadget focuses on that can appropriately interface a super capacitor with the drive prepare of a crossover electric vehicle. Besides, by contrasting the fundamental qualities and applications with some ordinary bidirectional DC/DC converter, the proposed converter has low gadget rating and can be controlled by obligation cycle and stage move. Finally, the most essential attributes of this converter is that it utilizes the transformer spillage inductance as the essential vitality exchange component and control parameters, Simulation waveforms in light of MATLAB recreation are given to exhibit the integrity of this novel topology, and this converter is additionally reasonable for high power application, specifically to control the charge-release of super capacitors or batteries that can be utilized as a part of cross breed solar based electric vehicle.
Pulmonary vein remodeling following pulmonary vein isolation in patients with atrial fibrillation-do pulmonary veins represent only an epiphenomenon? A cardiac MRI study.

Background After successful pulmonary vein isolation (PVI) for atrial fibrillation (AF), the left atrium (LA) undergoes reverse remodeling. However, few studies have directly studied pulmonary vein (PV) remodeling and focused on whether pre PVI-PV conditions could predict outcome of the procedure. We hypothesize that: (I) post PVI, in addition to LA remodeling the PVs undergo a parallel degree of remodeling; and (II) that PV characteristics pre PVI can be used to identify patients more likely to sustain normal sinus rhythm (NSR). Methods Patients (n=100) scheduled for PVI had a cardiovascular magnetic resonance (CMR) imaging before and 6±2 months following PVI. PV cross sectional areas (CSA) within 0.5 cm of the ostium and LA volumes were measured. Patients were categorized as responders (R) or non-responders (NR), based on two separate 14-day Holter monitoring. Results PVs CSA were significantly reduced post procedure in both groups, R (233±53 to 192±52 mm2, P<0.001) and NR (241±54 to 207±44 mm2, P<0.001), however, the difference between R and NR post PVI was not significant (192±52 to 207±44 mm2, P=0.19). Reduction in PVs CSAs post procedure moderately correlated with the 3D LA volume reduction (r=0.48, P<0.001). Conclusions PVs mirror the LA in that they significantly change in size following PVI yet they were not found to directly predict maintenance of NSR.
Skyddande immunitet mot Strongylus vulgaris – en framtida möjlighet?

Strongylus vulgaris (stor blodmask) ar den mest patogena parasiten hos hast i Sverige, redan vid lag infektionsdos orsakar parasiten stor skada pa blodkarlen som forsorjer tarmen. Skadorna kan ge upphov till allvarliga fall av kolik och tromboser. Prevalensen av S. vulgaris har stigit fran 3 % i slutet av 90-talet till cirka 26 % vid senaste matningen 2016. En bidragande faktor till den har utvecklingen ar att Sverige for drygt tio ar sedan inforde sa kallad selektiv avmaskning pa grund av en okande resistensutveckling mot anthelmintika hos Cyathostominae (liten blodmask). Ett langsiktigt mal i ett doktorandprojekt vid Immunologiska enheten vid Institutionen for biomedicin och veterinar folkhalsovetenskap ar darfor att utveckla ett vaccin mot S. vulgaris som alternativ till anthelmintika. I projektet studeras ett nytt adjuvans, G3, och dess effekt pa cytokinproduktionen hos equina mononukleara blodceller (eqMBC). I detta examensarbete har G3 utvarderats vidare. EqMBC har odlats i narvaro av G3, liksom i narvaro av G3 tillsammans med ”Toll like receptor” (TLR) agonisterna Pam3SCK4 (Pam) och FliC. Cytokininduktionen analyserades med qPCR (IL-10, IL-8 och IFN-γ) och ELISA (IFNα). En metod att rena och strala L3-larver i syfte att studera larvernas effekt pa cytokininduktionen i kulturer av eqMBC har utvecklats. En forsta cellinduktion i eqMBC med dessa preparerade larver, tillsammans med G3 utfores och cytokininduktion (IFN-γ, IFN-α, TGF-β, IL-10, IL-12 och IL-4) analyserades med qPCR. G3 inducerade generna for IFN-γ och IL-12 samt kunde inhibera uttrycket av generna for IL10 och IL-4. Nar G3 tillsattes i kulturer av eqMBC tillsammans med andra inducerare, var G3’s effekt pa cytokinproduktionen dominant. Vid ett forsta cellinduktionsforsok med G3 och L3larver observerades att L3 larverna inducerar uttryck av genen for IL-4. Narvaro av G3 hindrade det L3-inducerade uttrycket av IL-4 i eqMBC som istallet uttryckte IFN-γ och IL-12. Olikt manga adjuvans pa marknaden tycks G3 starkt driva immunreaktionen mot TH1. Detta gor G3 till ett mycket intressant adjuvans i framtida hastvaccin. Mojligheten att anvanda G3 tillsammans med L3 antigen i ett vaccin mot blodmask behover studeras vidare. Metoden som utvecklats i detta examensarbete att rena fram och strala L3 larver, anses fungera bra och kommer tillampas i de fortsatta studierna med eqMBC.
Smart Grid Security Enhancement by Using Belief Propagation

False data injection attack (FDIA) is a critical cyber-attack that can cause disrupt operations and subsequently blackouts in smart grid networks. Cleverly constructed stealthy false measurement vectors can circumvent the bad data detector unit and mislead the state estimation process. This article proposes a novel belief propagation (BP)-based algorithm to detect both random and stealthy-type FDIAs in smart grids with higher detection rate than the state-of-the-art machine learning classifiers such as Naive Bayes, support vector machines, Random Forest, OneR, and AdaBoost. Another novel feature of the proposed algorithm is to detect FDIAs without using any historical cyber-attack data, which are sketchy due to security constraints and infinitesimal in occurrence numbers. The proposed BP method utilizes local sensor measurement data to calculate local belief and send it as a message signal to the control center. Then, the control center determines final/global belief and compares the result with a predefined threshold value derived from the uncompromised measurement database. The real-time steady-state load data are utilized for dc state estimation. From the obtained results, performance parameters such as detection rate, receiver operating characteristic curve, precision, recall, and F-measure of the proposed BP algorithm are found superior to the aforementioned state-of-the-art machine learning algorithms.
Depression, Substance Abuse, and Suicide Risk: A Rising Problem

Introduction: Suicide is a multifactorial phenomenon that is frequently found in comorbidity with mental disorders, such as depression and substance abuse, which can interact in summation to produce any element of the continuum of suicidal behavior: ideation, planning, attempt, and death by suicide. Objectives: To describe the relationship between depression and other mental disorders with substance abuse and suicidal behavior, and to discuss its implications for mental health services in Mexico. Methods: A narrative review of the literature of articles published national and internationally was carried out to describe the relationship between depression and other mental disorders with substance abuse and suicidal behavior. Results: The review of the literature demonstrates the relationship between depression and substance abuse (mainly alcohol) with suicidal behavior; however, the need for its early diagnosis and timely treatment is indicated, especially in high-risk groups, like adolescents. Conclusions: There is a synergistic relationship between depression and substance use for the presence of greater suicidal behavior, which implies important challenges in mental health care services as early identification and effective management are essential to reduce the impact of the continuum of suicidal behavior.
Evaluation of functional outcome of lumbar spondylolisthesis treated with posterior lumbar interbody fusion with instrumentation

<p class="abstract"><strong>Background:</strong> Spondylolisthesis with or without spondylolysis occurs in 5% to 8% of the adult population. It is commonly believed that spondylolysis does not exist at birth. The incidence is 4.4% to 5% at the age of 6 years, increasing to 6% at the age of 18 years, which is quite similar to that observed in adulthood.To analyze the functional outcome of posterior stabilization by pedicle screws with decompression and interbody fusion by PLIF (Posterior Lumbar Interbody Fusion) technique in adult single level spondylolisthesis. In this study our aim is to analyze the correlation between the degrees of fusion with functional outcomes. </p><p class="abstract"><strong>Methods:</strong> This is a prospective study of 20 patients carried out in the Department of Orthopaedics, Govt. Dharmapuri Medical College Hospital, Dharmapuri from January 2016 to December 2017. All patients were evaluated with anteroposterior, lateral and oblique radiographs of the lumbosacral spine. Dynamic plain radiographs of all our patients showed instability. CT/MRI evaluation of all patients was done. <strong></strong></p><p class="abstract"><strong>Results:</strong> In our study four patients (20%) had a complete reduction of the preoperative slip, fourteen patients (70%) showed a reduction of slip by one grade, while in two patients (10%) there was no change from the preoperative slip percentage. </p><p><strong>Conclusions:</strong> Further, three dimensional multislice thin section CT scans with multiplanar reconstruction are ideal to study the incorporation of the bone graft within the disc space. </p>