Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Loudspeaker Distortion on Room Acoustic Parameters

The assessment of the range of uncertainty for room acoustic parameters is an ongoing research topic. ISO 3382 demands the calculation of the uncertainty according to the GUM. However, the separation and determination of the main influence factors and their contribution is still not fully solved. Mainly the position of the sound source and the microphones, [1, 2, 3] background noise [4, 5, 6] and the loudspeaker directivity pattern [7] are currently addressed due to strong deviations observed in the past. In this contribution we explain an existing modeling technique of non-linear systems that is used to simulate the effect of loudspeaker distortion in impulse response measurements. Generic impulse responses are used to simulate a room acoustic measurement. We will analyze which room acoustic parameters are potentially affected. The evaluation of the room acoustic parameters leads to a scenario with controllable degree of loudspeaker distortion without the influence of the other uncertainty factors priorly addressed. This simulation approach is validated by measurement results with different amplifications in auditoria using exponential sweep measurements.
A Measurement Strategy to Assess the Optimal Design of an RFID-Based Navigation Aid

Different solutions have been proposed to address orientation in indoor/outdoor environments and among them, radio frequency identification (RFID)-based systems represent a strategic choice for its reduced complexity and cost. Widespread practices to validate the behavior of RFID-based systems use specific metrics related to the addressed application, while a general strategy to assess technical performances of the RFID-based system is lacking. In this paper, a novel measurement approach is proposed to perform optimal choices in developing an RFID-based orientation system and to impartially assess its technical performances. A multivariate measurement strategy is suggested to fully investigate performances of the system as a function of a set of operating quantities (user-tag distance, tag height, and intertag distance). An analysis is also proposed, which aims to assess the system performances in terms of sensitivity and specificity. Moreover, the use of a synthetic index, representing the overall behavior of the system under investigation is addressed. A case of study is presented. The system uses transparent RFID tags positioned in the environment and an embedded system including an RFID reader, as well as a dedicated module to convey audio messages to end-users. Results highlight that the device sensitivity improves in the case of a high intertag distance while the specificity decreases for short intertag distance, which is also confirmed by the synthetic index proposed. Specifically, an optimal tag height of 1 m has been estimated, while best performances are obtained in the case of intertag distance and user-tag distance belonging to ranges [1.50–2.50] m and [0.40–1.60] m, respectively.
Regime switching model: real or spurious long memory?

In this paper, we analyze the possible confusion in terms of long memory behavior of the autocorrelation function of a Markov switching model. Such a model is known to have a short memory behavior. Analyzing the value of sum of the transition probabilities and the number of switches inside such a model, we show their impact to create long memory. The ability of the true Markov switching model to predict is compared with the forecasts obtained from a long memory process adjusted on data derived from the former model. It is shown that, in certain cases, this spurious long memory behavior can be beneﬁt to get better forecasts.
Simple solutions for the summer shallow atmospheric circulation over North Africa

The spring‐to‐summer shallow atmospheric circulation over North Africa is driven by two desert heat lows (DHLs), one over the Sahara (SHL) and one over Arabia (AHL), with cyclones embedded in the convective layer, capped by mid‐tropospheric anticyclones. The aim of this work is to produce a minimal theoretical framework for these dynamical features in terms of Kelvin, mixed and planetary mode solutions to a two‐layer Matsuno–Gill model with a lower Rayleigh frictional layer dynamically coupled to an almost frictionless upper layer. Results show that a DHL drives a Walker‐like cell with rising air over the low and subsiding air to its west, with the lower‐level cyclone to the east of the mid‐tropospheric anticyclone, the latter being bounded to the southwest by an unstable easterly jet. These features, related to frictional differences between the two layers, are enhanced by ambient easterly winds. In spring, the stronger SHL drives a cell with rising air over West Africa and subsiding air over the Atlantic. The weaker AHL drives a cell with rising air over Arabia and subsiding air over East Africa. In summer, the stronger AHL drives a cell with rising air over Arabia and subsiding air over Libya, and the weaker SHL drives a cell with rising air over West Sahara and subsiding air over the Atlantic. The concurrent contributions of easterly winds, monsoonal low‐level convergence, and seasonal airborne dust warming strengthen the SHL, making its winds stronger than those of the AHL. In addition, a third‐order expansion of the Coriolis parameter strengthens the zonal winds and weakens the meridional winds. These contributors strengthen anticyclones over the eastern Mediterranean and to the west of Gibraltar. The ability of the model to represent the main features of the North African atmospheric circulations suggests a potential for better understanding of climate dynamics in connected regions (Mediterranean, Tropical Atlantic).
NBER WORKING PAPER SERIES COMPETITION AND POLITICAL ORGANIZATION: TOGETHER OR ALONE IN LOBBYING FOR TRADE POLICY?

This paper employs a novel data set on lobbying expenditures to measure the degree of within-sector political organization and to explore the determinants of the mode of lobbying and political organization across U.S. industries. The data show that sectors characterized by a higher degree of competition (more substitutable products and a lower concentration of production) tend to lobby more together (through a sector-wide trade association), while sectors with higher concentration and more differentiated products lobby more individually. The paper proposes a theoretical model to interpret the empirical evidence. In an oligopolistic market, firms can benefit from an increase in their product-specific protection measure, if they can raise prices and profits. They find it less profitable to do so in a competitive market where attempts to raise prices are more likely to reduce profits. In competitive markets firms are therefore more likely to lobby together thereby simultaneously raising tariffs on all products in the sector. Matilde Bombardini Department of Economics University of British Columbia 997 1873 East Mall Vancouver, BC V6T 1Z1 Canada matildeb@interchange.ubc. ca Francesco Trebbi Booth School of Business University of Chicago 5807 South Woodlawn Avenue Chicago, IL 60637 and NBER ftrebbi@chicagobooth.edu
Efficient exact motif discovery

Motivation: The motif discovery problem consists of finding over-represented patterns in a collection of biosequences. It is one of the classical sequence analysis problems, but still has not been satisfactorily solved in an exact and efficient manner. This is partly due to the large number of possibilities of defining the motif search space and the notion of over-representation. Even for well-defined formalizations, the problem is frequently solved in an ad hoc manner with heuristics that do not guarantee to find the best motif. Results: We show how to solve the motif discovery problem (almost) exactly on a practically relevant space of IUPAC generalized string patterns, using the p-value with respect to an i.i. d. model or a Markov model as the measure of over-representation. In particular, (i) we use a highly accurate compound Poisson approximation for the null distribution of the number of motif occurrences. We show how to compute the exact clump size distribution using a recently introduced device called probabilistic arithmetic automaton (PAA). (ii) We define two p-value scores for over-representation, the first one based on the total number of motif occurrences, the second one based on the number of sequences in a collection with at least one occurrence. (iii) We describe an algorithm to discover the optimal pattern with respect to either of the scores. The method exploits monotonicity properties of the compound Poisson approximation and is by orders of magnitude faster than exhaustive enumeration of IUPAC strings (11.8 h compared with an extrapolated runtime of 4.8 years). (iv) We justify the use of the proposed scores for motif discovery by showing our method to outperform other motif discovery algorithms (e.g. MEME, Weeder) on benchmark datasets. We also propose new motifs on Mycobacterium tuberculosis. Availability and Implementation: The method has been implemented in Java. It can be obtained from http://ls11-www.cs. tu-dortmund.de/people/marschal/paa_md/ Contact: tobias.marschall@tu-dortmund.de; sven.rahmann@tu-dortmund.de
Using Design-Parameter Sensitivities in Adjoint-Based Design Environments

Over the past several years, considerable progress has been made in aerodynamic design through the use of adjoint-based solution technologies. These design systems allow one to change the surfaces of a configuration so that some objective function, such as lift-todrag ratio or sonic boom strength, is optimized. Unfortunately, these systems change the configuration surfaces on a point-by-point basis, instead of by changing the design parameters that were used to generate the original configuration; this limitation arose from the lack of good sensitivity calculations through the geometric design process. The objective of this paper is to demonstrate the coupling of recently developed configuration sensitivity calculations with the adjoint-based optimization frameworks. In particular, a wing is optimized to minimize the induced drag (for a fixed lift) through both the CART3D and FUN3D design frameworks. Several methods for propagating sensitivity information into the interior of Faces were investigated. The optimized results, both for sensitivities computed by finite differences (which are nearly identical to the predicted displacement field but expensive to compute) and for sensitivities computed analytically (which disagree with the predicted displacements but are inexpensive to compute), are nearly identical.
A Nonhomogeneous Fractional p-Kirchhoff Type Problem Involving Critical Exponent in ℝN

Abstract This paper concerns itself with the nonexistence and multiplicity of solutions for the following fractional Kirchhoff-type problem involving the critical Sobolev exponent: [ a + b ⁢ ( ∬ ℝ 2 ⁢ N | u ⁢ ( x ) - u ⁢ ( y ) | p | x - y | N + p ⁢ s ⁢ 𝑑 x ⁢ 𝑑 y ) θ - 1 ] ⁢ ( - Δ ) p s ⁢ u = | u | p s * - 2 ⁢ u + λ ⁢ f ⁢ ( x ) in ⁢ ℝ N , \Biggl{[}a+b\biggl{(}\iint_{\mathbb{R}^{2N}}\frac{\lvert u(x)-u(y)\rvert^{p}}{% \lvert x-y\rvert^{N+ps}}\,dx\,dy\biggr{)}^{\theta-1}\Biggr{]}(-\Delta)_{p}^{s}% u=\lvert u\rvert^{p_{s}^{*}-2}u+\lambda f(x)\quad\text{in }\mathbb{R}^{N}, where a≥0{a\kern-1.0pt\geq\kern-1.0pt0}, b>0,θ>1{b\kern-1.0pt>\kern-1.0pt0,\theta\kern-1.0pt>\kern-1.0pt1}, (-Δ)ps{(-\Delta)_{p}^{s}} is the fractional p-Laplacian with 0<s<1{0\kern-1.0pt<\kern-1.0pts\kern-1.0pt<\kern-1.0pt1} and 1<p<N/s{1\kern-1.0pt<\kern-1.0ptp\kern-1.0pt<\kern-1.0ptN/s}, ps*=N⁢p/(N-p⁢s){p_{s}^{*}\kern-1.0pt=\kern-1.0ptNp/(N-ps)} is the critical Sobolev exponent, λ≥0{\lambda\geq 0} is a parameter, and f∈Lps*/(ps*-1)⁢(ℝN)∖{0}{f\in L^{p_{s}^{*}/(p_{s}^{*}-1)}(\mathbb{R}^{N})\setminus\{0\}} is a nonnegative function. When λ=0{\lambda=0}, we show that the multiplicity and nonexistence of solutions for the above problem are related with N, θ, s, p, a, and b. When λ>0{\lambda>0}, by using Ekeland’s variational principle and the mountain pass theorem, we show that there exists λ**>0{\lambda^{**}>0} such that the above problem admits at least two nonnegative solutions for all λ∈(0,λ**){\lambda\in(0,\lambda^{**})}. In the latter case, in order to overcome the loss of compactness, we derive a fractional version of the principle of concentration compactness in the setting of the fractional p-Laplacian.
Heritability of Immunity Traits and Resistance of Atlantic Salmon against the Sea Louse Caligus rogercresseyi

Simple Summary Sea lice are a relevant ectoparasite that affect the salmon industry. Not all fish respond in the same way to this parasite—some fish are resistant and have a low sea lice load, and others are susceptible and have a high parasite load. In this work, we studied the heritability of three key proteins associated with the innate immunity and resistance of Atlantic salmon against sea lice. Nkef, Tnfα, and Il-8 were quantified by indirect ELISA in order to determine their heritability in different families of Atlantic salmon. Our results show that the expression of Nkef and Tnfα proteins are highly heritable and are related to resistance to sea lice in Atlantic salmon. Abstract The immune response of Atlantic salmon to sea lice has been extensively studied, but we still do not know the mechanisms by which some fish become resistant and others do not. In this study, we estimated the heritabilities of three key proteins associated with the innate immunity and resistance of Salmo salar against the sea louse Caligus rogercresseyi. In particular, we quantified the abundance of 2 pro-inflammatory cytokines, Tnfα and Il-8, and an antioxidant enzyme, Nkef, in Atlantic salmon skin and gill tissue from 21 families and 268 individuals by indirect ELISA. This covers a wide parasite load range from low or resistant (mean sea lice ± SE = 8.7 ± 0.9) to high or susceptible (mean sea lice ± SE = 43.3 ± 2.0). Our results showed that susceptible fish had higher levels of Nkef and Tnfα than resistant fish in their gills and skin, although gill Il-8 was higher in resistant fish, while no significant differences were found in the skin. Furthermore, moderate to very high heritable genetic variation was estimated for Nkef (h2 skin: 0.96 ± 0.14 and gills: 0.97 ± 0.11) and Tnfα (h2 skin: 0.53 ± 0.17 and gills: 0.32 ± 0.14), but not for Il-8 (h2 skin: 0.22 ± 0.12 ns and gills: 0.09 ± 0.08 ns). This work provides evidence that Nkef and Tnfα protein expressions are highly heritable and related to resistance against sea lice in Atlantic salmon.
Self-Assembly and Mineralization of Peptide-Amphiphile Nanofibers

We have used the pH-induced self-assembly of a peptide-amphiphile to make a nanostructured fibrous scaffold reminiscent of extracellular matrix. The design of this peptide-amphiphile allows the nanofibers to be reversibly cross-linked to enhance or decrease their structural integrity. After cross-linking, the fibers are able to direct mineralization of hydroxyapatite to form a composite material in which the crystallographic c axes of hydroxyapatite are aligned with the long axes of the fibers. This alignment is the same as that observed between collagen fibrils and hydroxyapatite crystals in bone.
In silico evaluation of binding interaction and ADME study of new 1,3-diazetidin-2-one derivatives with high antiproliferative activity

A series of eight novels' 1,3-diazetidin-2-ones have been proposed to assess their potential activities. They are intended to examine antiproliferative effects through inhibition of epidermal growth factor receptor (EGFR) expression. These eight compounds strongly interact with the EGFR protein, responsible for the activity. As part of a present study, these compounds were docked to the crystal structure of the EGFR (Protein Data Bank code: 1 M17) to determine their binding affinity at the active site. Based on computer predictions, two compounds were demonstrated high scores of 80.80 and 85.89. After analyzing ADME properties, these compounds were found to have significant potential for binding. Consequently, the abilities of gefitinib, erlotinib, imatinib, and sorafenib were selected for comparison as controls. Computational methods were performed to predict the critical disposition of eight novels' 1,3-diazetidin-2-one derivatives to the EGFR. Moreover, a docking technique employing the Genetic Optimization for Ligand Docking program was conducted. Compounds 2 and 7 demonstrate a high docking peace-wise scoring function (PLP) fitness of 85.89 and 80.80, respectively. They fulfilled the Lipinski's rule, topological descriptors, and fingerprints of drug-like molecular structure keys. These compounds can be used as lead compounds to develop novel antiproliferative agents. The outcome of applying this study is novel series of 1,3-diazetidin-2-one compounds as new analogs were designed and evaluated for their antiproliferative activity with a higher potency profile and binding affinity within the active sites of EGFR.
Role of Rituximab in the Treatment of Pemphigus Vulgaris: Patient Selection and Acceptability

: Anti-CD20 monoclonal antibody rituximab is an approved adjuvant treatment, in combination with oral corticosteroids, for patients with pemphigus vulgaris, a severe and potentially life-threatening autoimmune blistering skin disorder. Updated approaches to the management of pemphigus vulgaris support rituximab as a first-line adjuvant treatment to induce remission early in the course of disease; however, its feasibility in the clinical setting is often reduced by a series of limitations, including high cost of this biological drug, physician and patient concern for the risk of adverse reactions, and uncertainty regarding the optimum dosing and schedule of administration. The standard approved rituximab dosages, which are derived from lymphoma protocols, have been recognized to exceed the effective dose required for inducing B cell depletion, since the B cell burden in pemphigus vulgaris is much lower than in lymphoproliferative disorders. To overcome these limitations, recent research has investigated alternative regimens of rituximab, using lower doses of the drug. Moreover, differences in patient and disease characteristics that are highlighted in the literature strongly suggest that therapy should be tailored individually on a case-by-case basis: personalized treatment schedules may be necessary to optimize response to treatment and tolerability in different subjects, with the possibility of repeated infusions for severe forms and in case of relapse. Finally, low-dose regimens of rituximab were suggested to be favorable during the COVID-19 pandemic by providing a lesser degree of immune cell depletion while retaining a sufficient response. In conclusion, the current literature suggests that lower-dose regimens of rituximab are not only tolerable and cost-effective but may also be associated with a positive response in pemphigus vulgaris, comparable to that achieved with higher doses especially in early disease. Further evidence from rigorous clinical trials will be required to optimize lower-dose regimens of RTX and establish their position within the treatment scenario of pemphigus vulgaris. thyroid diseases, rheumatoid arthritis, type 1 diabetes mellitus, Sjogren’s syndrome, systemic lupus erythematosus, inflammatory bowel diseases, and alopecia areata. These autoimmune disorders have been additionally observed with higher frequencies in first-degree relatives of patients with pemphigus compared to unrelated controls. 8,13 Future studies are needed to elucidate whether these are sporadic associations or the expression of a predisposition to autoimmunity, which might potentially be relevant to the response to B cell depleting therapies in pemphigus.
Multi-Service Oriented Joint Channel Estimation and Multi-User Detection Scheme for Grant-Free Massive MTC Networks

To satisfy the highly heterogeneous requirements of Internet of Things applications for the sixth-generation (6G) networks, the machine-type communication (MTC) aims to support multiple types of services having diverse traffic demands, which will cause significant challenges in the grant-free based channel estimation (CE) and multi-user detection (MUD) scheme design for massive MTC (mMTC) networks. To address this challenge, we develop a multi-state Markov chain based transmission model to characterize the diverse time-varying traffic demands for MTC users, where the temporal correlation of user activity and the data length diversity are jointly exploited. Based on the developed transmission model, a multi-service oriented joint CE-MUD scheme is proposed to realize the efficient CE, user activity identification and data detection. Specifically, we first construct the joint block sparse structure for the transmitted pilot and data signals to fully explore the structured sparsity of the pilot and data symbols. Then, we convert the joint CE-MUD into a maximum a posteriori probability (MAP) problem such that the block sparsity of the transmitted signals and the diverse traffic demands provided by the established transmission model can be efficiently exploited. Moreover, we further develop an adjustable prior probability aided Bayesian sparsity adaptive matching pursuit (APP-BSAMP) algorithm to efficiently solve the formulated MAP problem. In the proposed algorithm, we first adjust the prior user activation probabilities through the approximate message passing (AMP) based detector to reduce the impact of the misestimation of user transmission status. Then, we jointly reconstruct the transmitted pilot and data signals under the Bayesian pursuit framework, where the active user set is obtained by maximizing the posterior probabilities. Simulation results show that the proposed scheme can achieve a substantial performance gain over existing methods.
Performance investigation of two-stage detection techniques using traffic light detection dataset

Using a camera to monitor an object or a group of objects over time is the process of object detection. It can be used for a variety of things, including security and surveillance, video communication, traffic light detection (TLD), object detection from compressed video in public places. In recent times, object tracking has become a popular topic in computer science particularly, the data science community, thanks to the usage of deep learning (DL) in artificial intelligence (AI). DL which convolutional neural network (CNN) as one of its techniques usually used two-stage detection methods in TLD. Despite all successes recorded in TLD through the use of two-stage detection methods, there is no study that has analyzed these methods in experimental research, studying the strength and witnesses by the researchers. Based on the needs this study analyses the applications of DL techniques in TLD. We implemented object detection for TLD using 5 two-stage detection methods with the traffic light dataset using a Jupyter notebook and the sklearn libraries. We present the achievements of two-stage detection methods in TLD, going by standard performance metrics used, FASTER-CNN was the best in detection accuracy, F1-score, precision and recall with 0.89, 0.93, 0.83 and 0.90 respectively.
Fixed-Time Control of Asymmetric Output-Constrained Nonlinear Systems and Its Application to Boiler–Turbine Unit

This article addresses the fixed-time control problem for high-order nonlinear systems with unknown nonlinear functions and asymmetric output constraint. First, a continuous state-feedback controller is constructed by revamping the adding a power integrator technique (API), which guarantees that the system output does not exceed the pregiven asymmetric output constraint boundary. Second, with the barrier Lyapunov function (BLF) method and the backstepping technique, a fixed-time stability criterion is constructed. It is rigorously proven that the closed-loop systems are fixed-time stable by the Lyapunov theory. The proposed BLF can not only deal with the symmetric output constraint but also cover the traditional logarithm-type BLF as a special case. Finally, a practical application example of the boiler–turbine unit system is offered to certify the availability of the proposed control algorithm.